plotly-4.4.1+dfsg.orig/0000755000175000017500000000000013573746614014271 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/MANIFEST.in0000644000175000017500000000016113525746125016017 0ustar noahfxnoahfxinclude LICENSE.txt include README.md include plotlywidget.json include versioneer.py include plotly/_version.py plotly-4.4.1+dfsg.orig/README.md0000644000175000017500000001434113573746525015554 0ustar noahfxnoahfx# plotly.py
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## Quickstart `pip install plotly==4.4.1` Inside [Jupyter notebook](https://jupyter.org/install) (installable with `pip install "notebook>=5.3" "ipywidgets>=7.2"`): ```python import plotly.graph_objects as go fig = go.Figure() fig.add_trace(go.Scatter(y=[2, 1, 4, 3])) fig.add_trace(go.Bar(y=[1, 4, 3, 2])) fig.update_layout(title = 'Hello Figure') fig.show() ``` See the [Python documentation](https://plot.ly/python/) for more examples. Read about what's new in [plotly.py v4](https://medium.com/plotly/plotly-py-4-0-is-here-offline-only-express-first-displayable-anywhere-fc444e5659ee) ## Overview [plotly.py](https://plot.ly/d3-js-for-python-and-pandas-charts/) is an interactive, open-source, and browser-based graphing library for Python :sparkles: Built on top of [plotly.js](https://github.com/plotly/plotly.js), `plotly.py` is a high-level, declarative charting library. plotly.js ships with over 30 chart types, including scientific charts, 3D graphs, statistical charts, SVG maps, financial charts, and more. `plotly.py` is [MIT Licensed](packages/python/chart-studio/LICENSE.txt). Plotly graphs can be viewed in Jupyter notebooks, standalone HTML files, or hosted online using [Chart Studio Cloud](https://chart-studio.plot.ly/feed/). [Contact us](https://plot.ly/products/consulting-and-oem/) for consulting, dashboard development, application integration, and feature additions.

*** - [Online Documentation](https://plot.ly/python) - [Contributing](contributing.md) - [Changelog](CHANGELOG.md) - [Code of Conduct](CODE_OF_CONDUCT.md) - [Version 4 Migration Guide](https://plot.ly/python/next/v4-migration/) - [New! Announcing Dash 1.0](https://medium.com/plotly/welcoming-dash-1-0-0-f3af4b84bae) - [Community](https://community.plot.ly/c/api/python) *** ## Installation plotly.py may be installed using pip... ``` pip install plotly==4.4.1 ``` or conda. ``` conda install -c plotly plotly=4.4.1 ``` ### Jupyter Notebook Support For use in the Jupyter Notebook, install the `notebook` and `ipywidgets` packages using pip... ``` pip install "notebook>=5.3" "ipywidgets==7.5" ``` or conda. ``` conda install "notebook>=5.3" "ipywidgets=7.5" ``` ### JupyterLab Support (Python 3.5+) For use in JupyterLab, install the `jupyterlab` and `ipywidgets` packages using pip... ``` pip install jupyterlab==1.2 "ipywidgets==7.5" ``` or conda. ``` conda install jupyterlab=1.2 conda install "ipywidgets=7.5" ``` Then run the following commands to install the required JupyterLab extensions (note that this will require [`node`](https://nodejs.org/) to be installed): ``` # Avoid "JavaScript heap out of memory" errors during extension installation # (OS X/Linux) export NODE_OPTIONS=--max-old-space-size=4096 # (Windows) set NODE_OPTIONS=--max-old-space-size=4096 # Jupyter widgets extension jupyter labextension install @jupyter-widgets/jupyterlab-manager@1.1 --no-build # FigureWidget support jupyter labextension install plotlywidget@1.4.0 --no-build # and jupyterlab renderer support jupyter labextension install jupyterlab-plotly@1.4.0 --no-build # Build extensions (must be done to activate extensions since --no-build is used above) jupyter lab build # Unset NODE_OPTIONS environment variable # (OS X/Linux) unset NODE_OPTIONS # (Windows) set NODE_OPTIONS= ``` ### Static Image Export plotly.py supports static image export using the `to_image` and `write_image` functions in the `plotly.io` package. This functionality requires the installation of the plotly [orca](https://github.com/plotly/orca) command line utility and the [`psutil`](https://github.com/giampaolo/psutil) Python package. These dependencies can both be installed using conda: ``` conda install -c plotly plotly-orca psutil ``` Or, `psutil` can be installed using pip... ``` pip install psutil ``` and orca can be installed according to the instructions in the [orca README](https://github.com/plotly/orca). #### Troubleshooting ##### Wrong Executable found If you get an error message stating that the `orca` executable that was found is not valid, this may be because another executable with the same name was found on your system. Please specify the complete path to the Plotly-Orca binary that you downloaded (for instance in the Miniconda folder) with the following command: `plotly.io.orca.config.executable = '/home/your_name/miniconda3/bin/orca'` ### Extended Geo Support Some plotly.py features rely on fairly large geographic shape files. The county choropleth figure factory is one such example. These shape files are distributed as a separate `plotly-geo` package. This package can be installed using pip... ``` pip install plotly-geo==1.0.0 ``` or conda ``` conda install -c plotly plotly-geo=1.0.0 ``` ### Chart Studio support The `chart-studio` package can be used to upload plotly figures to Plotly's Chart Studio Cloud or On-Prem service. This package can be installed using pip... ``` pip install chart-studio==1.0.0 ``` or conda ``` conda install -c plotly chart-studio=1.0.0 ``` ## Migration If you're migrating from plotly.py v3 to v4, please check out the [Version 4 migration guide](https://plot.ly/python/next/v4-migration/) If you're migrating from plotly.py v2 to v3, please check out the [Version 3 migration guide](migration-guide.md) ## Copyright and Licenses Code and documentation copyright 2019 Plotly, Inc. Code released under the [MIT license](packages/python/chart-studio/LICENSE.txt). Docs released under the [Creative Commons license](https://github.com/plotly/documentation/blob/source/LICENSE). plotly-4.4.1+dfsg.orig/_plotly_future_/0000755000175000017500000000000013573746613017503 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/_plotly_future_/v4.py0000644000175000017500000000000013525746125020367 0ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/_plotly_future_/renderer_defaults.py0000644000175000017500000000000013525746125023533 0ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/_plotly_future_/template_defaults.py0000644000175000017500000000000013525746125023540 0ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/_plotly_future_/timezones.py0000644000175000017500000000000013525746125022053 0ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/_plotly_future_/__init__.py0000644000175000017500000000345013525746125021611 0ustar noahfxnoahfximport warnings import functools # Initialize _future_flags with all future flags that are now always in # effect. _future_flags = { "renderer_defaults", "template_defaults", "extract_chart_studio", "remove_deprecations", "v4_subplots", "orca_defaults", "timezones", "trace_uids", } def _assert_plotly_not_imported(): import sys if "plotly" in sys.modules: raise ImportError( """\ The _plotly_future_ module must be imported before the plotly module""" ) warnings.filterwarnings( "default", ".*?is deprecated, please use chart_studio*", DeprecationWarning ) def _chart_studio_warning(submodule): warnings.warn( "The plotly.{submodule} module is deprecated, " "please use chart_studio.{submodule} instead".format(submodule=submodule), DeprecationWarning, stacklevel=2, ) def _chart_studio_error(submodule): raise ImportError( """ The plotly.{submodule} module is deprecated, please install the chart-studio package and use the chart_studio.{submodule} module instead. """.format( submodule=submodule ) ) def _chart_studio_deprecation(fn): fn_name = fn.__name__ fn_module = fn.__module__ plotly_name = ".".join(["plotly"] + fn_module.split(".")[1:] + [fn_name]) chart_studio_name = ".".join( ["chart_studio"] + fn_module.split(".")[1:] + [fn_name] ) msg = """\ {plotly_name} is deprecated, please use {chart_studio_name}\ """.format( plotly_name=plotly_name, chart_studio_name=chart_studio_name ) @functools.wraps(fn) def wrapper(*args, **kwargs): warnings.warn(msg, DeprecationWarning, stacklevel=2) return fn(*args, **kwargs) return wrapper __all__ = ["_future_flags", "_chart_studio_error"] plotly-4.4.1+dfsg.orig/_plotly_future_/orca_defaults.py0000644000175000017500000000000013525746125022651 0ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/_plotly_future_/trace_uids.py0000644000175000017500000000000013525746125022160 0ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/_plotly_future_/v4_subplots.py0000644000175000017500000000000013525746125022322 0ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/_plotly_future_/remove_deprecations.py0000644000175000017500000000000013525746125024073 0ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/_plotly_future_/extract_chart_studio.py0000644000175000017500000000000013525746125024260 0ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/LICENSE.txt0000644000175000017500000000207313525746125016110 0ustar noahfxnoahfxThe MIT License (MIT) Copyright (c) 2016-2018 Plotly, Inc Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. plotly-4.4.1+dfsg.orig/setup.cfg0000644000175000017500000000044713573746614016117 0ustar noahfxnoahfx[metadata] description-file = README.md license_file = LICENSE.txt [bdist_wheel] universal = 1 [versioneer] vcs = git style = pep440 versionfile_source = plotly/_version.py versionfile_build = plotly/_version.py tag_prefix = v parentdir_prefix = plotly- [egg_info] tag_build = tag_date = 0 plotly-4.4.1+dfsg.orig/setup.py0000644000175000017500000003454413547055022016000 0ustar noahfxnoahfxfrom setuptools import setup, Command from setuptools.command.egg_info import egg_info from subprocess import check_call from distutils import log import versioneer import os import sys import platform import json here = os.path.dirname(os.path.abspath(__file__)) project_root = os.path.dirname(os.path.dirname(os.path.dirname(here))) node_root = os.path.join(project_root, "packages", "javascript", "plotlywidget") is_repo = os.path.exists(os.path.join(project_root, ".git")) npm_path = os.pathsep.join( [ os.path.join(node_root, "node_modules", ".bin"), os.environ.get("PATH", os.defpath), ] ) # Load plotly.js version from js/package.json def plotly_js_version(): path = os.path.join( project_root, "packages", "javascript", "plotlywidget", "package.json" ) with open(path, "rt") as f: package_json = json.load(f) version = package_json["dependencies"]["plotly.js"] version = version.replace("^", "") return version def readme(): with open(os.path.join(here, "README.md")) as f: return f.read() def js_prerelease(command, strict=False): """decorator for building minified js/css prior to another command""" class DecoratedCommand(command): def run(self): jsdeps = self.distribution.get_command_obj("jsdeps") if not is_repo and all(os.path.exists(t) for t in jsdeps.targets): # sdist, nothing to do command.run(self) return try: self.distribution.run_command("jsdeps") except Exception as e: missing = [t for t in jsdeps.targets if not os.path.exists(t)] if strict or missing: log.warn("rebuilding js and css failed") if missing: log.error("missing files: %s" % missing) raise e else: log.warn("rebuilding js and css failed (not a problem)") log.warn(str(e)) command.run(self) update_package_data(self.distribution) return DecoratedCommand def update_package_data(distribution): """update package_data to catch changes during setup""" build_py = distribution.get_command_obj("build_py") # distribution.package_data = find_package_data() # re-init build_py options which load package_data build_py.finalize_options() class NPM(Command): description = "install package.json dependencies using npm" user_options = [] node_modules = os.path.join(node_root, "node_modules") targets = [ os.path.join(here, "plotlywidget", "static", "extension.js"), os.path.join(here, "plotlywidget", "static", "index.js"), ] def initialize_options(self): pass def finalize_options(self): pass def get_npm_name(self): npmName = "npm" if platform.system() == "Windows": npmName = "npm.cmd" return npmName def has_npm(self): npmName = self.get_npm_name() try: check_call([npmName, "--version"]) return True except: return False def should_run_npm_install(self): package_json = os.path.join(node_root, "package.json") node_modules_exists = os.path.exists(self.node_modules) return self.has_npm() def run(self): has_npm = self.has_npm() if not has_npm: log.error( "`npm` unavailable. If you're running this command using sudo, make sure `npm` is available to sudo" ) env = os.environ.copy() env["PATH"] = npm_path if self.should_run_npm_install(): log.info( "Installing build dependencies with npm. This may take a while..." ) npmName = self.get_npm_name() check_call( [npmName, "install"], cwd=node_root, stdout=sys.stdout, stderr=sys.stderr, ) os.utime(self.node_modules, None) for t in self.targets: if not os.path.exists(t): msg = "Missing file: %s" % t if not has_npm: msg += "\nnpm is required to build a development version of widgetsnbextension" raise ValueError(msg) # update package data in case this created new files update_package_data(self.distribution) class CodegenCommand(Command): description = "Generate class hierarchy from Plotly JSON schema" user_options = [] def initialize_options(self): pass def finalize_options(self): pass def run(self): if sys.version_info.major != 3 or sys.version_info.minor < 6: raise ImportError("Code generation must be executed with Python >= 3.6") from codegen import perform_codegen perform_codegen() def overwrite_schema(url): import requests req = requests.get(url) assert req.status_code == 200 path = os.path.join(here, "codegen", "resources", "plot-schema.json") with open(path, "wb") as f: f.write(req.content) def overwrite_bundle(url): import requests req = requests.get(url) assert req.status_code == 200 path = os.path.join(here, "plotly", "package_data", "plotly.min.js") with open(path, "wb") as f: f.write(req.content) def overwrite_plotlyjs_version_file(plotlyjs_version): path = os.path.join(here, "plotly", "offline", "_plotlyjs_version.py") with open(path, "w") as f: f.write( """\ # DO NOT EDIT # This file is generated by the updatebundle setup.py command __plotlyjs_version__ = "{plotlyjs_version}" """.format( plotlyjs_version=plotlyjs_version ) ) def overwrite_plotlywidget_version_file(version): path = os.path.join(here, "plotly", "_widget_version.py") with open(path, "w") as f: f.write( """\ # This file is generated by the updateplotlywidgetversion setup.py command # for automated dev builds # # It is edited by hand prior to official releases __frontend_version__ = "{version}" """.format( version=version ) ) def request_json(url): import requests req = requests.get(url) return json.loads(req.content.decode("utf-8")) def get_latest_publish_build_info(branch): url = ( r"https://circleci.com/api/v1.1/project/github/" r"plotly/plotly.js/tree/{branch}?limit=10000\&filter=completed" ).format(branch=branch) branch_jobs = request_json(url) # Get most recent successful publish build for branch builds = [ j for j in branch_jobs if j.get("workflows", {}).get("job_name", None) == "publish" and j.get("status", None) == "success" ] build = builds[0] # Extract build info return {p: build[p] for p in ["vcs_revision", "build_num", "committer_date"]} def get_bundle_schema_urls(build_num): url = ( "https://circleci.com/api/v1.1/project/github/" "plotly/plotly.js/{build_num}/artifacts" ).format(build_num=build_num) artifacts = request_json(url) # Find archive archives = [a for a in artifacts if a.get("path", None) == "plotly.js.tgz"] archive = archives[0] # Find bundle bundles = [a for a in artifacts if a.get("path", None) == "dist/plotly.min.js"] bundle = bundles[0] # Find schema schemas = [a for a in artifacts if a.get("path", None) == "dist/plot-schema.json"] schema = schemas[0] return archive["url"], bundle["url"], schema["url"] class UpdateSchemaCommand(Command): description = "Download latest version of the plot-schema JSON file" user_options = [] def initialize_options(self): pass def finalize_options(self): pass def run(self): url = ( "https://raw.githubusercontent.com/plotly/plotly.js/" "v%s/dist/plot-schema.json" % plotly_js_version() ) overwrite_schema(url) class UpdateBundleCommand(Command): description = "Download latest version of the plot-schema JSON file" user_options = [] def initialize_options(self): pass def finalize_options(self): pass def run(self): url = ( "https://raw.githubusercontent.com/plotly/plotly.js/" "v%s/dist/plotly.min.js" % plotly_js_version() ) overwrite_bundle(url) # Write plotly.js version file plotlyjs_version = plotly_js_version() overwrite_plotlyjs_version_file(plotlyjs_version) class UpdatePlotlyJsCommand(Command): description = "Update project to a new version of plotly.js" user_options = [] def initialize_options(self): pass def finalize_options(self): pass def run(self): self.run_command("updatebundle") self.run_command("updateschema") self.run_command("codegen") class UpdateBundleSchemaDevCommand(Command): description = "Update the plotly.js schema and bundle from master" user_options = [] def initialize_options(self): pass def finalize_options(self): pass def run(self): branch = "master" build_info = get_latest_publish_build_info(branch) archive_url, bundle_url, schema_url = get_bundle_schema_urls( build_info["build_num"] ) # Update bundle in package data overwrite_bundle(bundle_url) # Update schema in package data overwrite_schema(schema_url) # Update plotly.js url in package.json package_json_path = os.path.join(node_root, "package.json") with open(package_json_path, "r") as f: package_json = json.load(f) # Replace version with bundle url package_json["dependencies"]["plotly.js"] = archive_url with open(package_json_path, "w") as f: json.dump(package_json, f, indent=2) # update plotly.js version in _plotlyjs_version rev = build_info["vcs_revision"] date = build_info["committer_date"] version = "_".join([branch, date[:10], rev[:8]]) overwrite_plotlyjs_version_file(version) class UpdatePlotlyJsDevCommand(Command): description = "Update project to a new development version of plotly.js" user_options = [] def initialize_options(self): pass def finalize_options(self): pass def run(self): self.run_command("updatebundleschemadev") self.run_command("jsdeps") self.run_command("codegen") class UpdatePlotlywidgetVersionCommand(Command): description = "Update package.json version of plotlywidget" user_options = [] def initialize_options(self): pass def finalize_options(self): pass def run(self): from plotly._version import git_pieces_from_vcs, render # Update plotly.js url in package.json package_json_path = os.path.join(node_root, "package.json") with open(package_json_path, "r") as f: package_json = json.load(f) # Replace version with bundle url pieces = git_pieces_from_vcs("widget-v", project_root, False) pieces["dirty"] = False widget_ver = render(pieces, "pep440")["version"] package_json["version"] = widget_ver with open(package_json_path, "w") as f: json.dump(package_json, f, indent=2) # write _widget_version overwrite_plotlywidget_version_file(widget_ver) graph_objs_packages = [ d[0].replace("/", ".") for d in os.walk("plotly/graph_objs") if not d[0].endswith("__pycache__") ] validator_packages = [ d[0].replace("/", ".") for d in os.walk("plotly/validators") if not d[0].endswith("__pycache__") ] versioneer_cmds = versioneer.get_cmdclass() setup( name="plotly", version=versioneer.get_version(), use_2to3=False, author="Chris P", author_email="chris@plot.ly", maintainer="Jon Mease", maintainer_email="jon@plot.ly", url="https://plot.ly/python/", project_urls={"Github": "https://github.com/plotly/plotly.py"}, description="An open-source, interactive graphing library for Python", long_description=readme(), long_description_content_type="text/markdown", classifiers=[ "Development Status :: 5 - Production/Stable", "Programming Language :: Python :: 2", "Programming Language :: Python :: 2.7", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.3", "Programming Language :: Python :: 3.4", "Programming Language :: Python :: 3.5", "Programming Language :: Python :: 3.6", "Programming Language :: Python :: 3.7", "Topic :: Scientific/Engineering :: Visualization", ], license="MIT", packages=[ "plotly", "plotlywidget", "plotly.plotly", "plotly.offline", "plotly.io", "plotly.matplotlylib", "plotly.matplotlylib.mplexporter", "plotly.matplotlylib.mplexporter.renderers", "plotly.figure_factory", "plotly.data", "plotly.express", "_plotly_utils", "_plotly_utils.colors", "_plotly_future_", ] + graph_objs_packages + validator_packages, package_data={ "plotly": [ "package_data/*", "package_data/templates/*", "package_data/datasets/*", ], "plotlywidget": ["static/extension.js", "static/index.js"], }, data_files=[ ( "share/jupyter/nbextensions/plotlywidget", ["plotlywidget/static/extension.js", "plotlywidget/static/index.js"], ), ("etc/jupyter/nbconfig/notebook.d", ["plotlywidget.json"]), ], install_requires=["retrying>=1.3.3", "six"], zip_safe=False, cmdclass=dict( build_py=js_prerelease(versioneer_cmds["build_py"]), egg_info=js_prerelease(egg_info), sdist=js_prerelease(versioneer_cmds["sdist"], strict=True), jsdeps=NPM, codegen=CodegenCommand, updateschema=UpdateSchemaCommand, updatebundle=UpdateBundleCommand, updateplotlyjs=js_prerelease(UpdatePlotlyJsCommand), updatebundleschemadev=UpdateBundleSchemaDevCommand, updateplotlyjsdev=UpdatePlotlyJsDevCommand, updateplotlywidgetversion=UpdatePlotlywidgetVersionCommand, version=versioneer_cmds["version"], ), ) plotly-4.4.1+dfsg.orig/versioneer.py0000644000175000017500000020621713525746126017027 0ustar noahfxnoahfx# Version: 0.18 """The Versioneer - like a rocketeer, but for versions. The Versioneer ============== * like a rocketeer, but for versions! * https://github.com/warner/python-versioneer * Brian Warner * License: Public Domain * Compatible With: python2.6, 2.7, 3.2, 3.3, 3.4, 3.5, 3.6, and pypy * [![Latest Version] (https://pypip.in/version/versioneer/badge.svg?style=flat) ](https://pypi.python.org/pypi/versioneer/) * [![Build Status] (https://travis-ci.org/warner/python-versioneer.png?branch=master) ](https://travis-ci.org/warner/python-versioneer) This is a tool for managing a recorded version number in distutils-based python projects. The goal is to remove the tedious and error-prone "update the embedded version string" step from your release process. Making a new release should be as easy as recording a new tag in your version-control system, and maybe making new tarballs. ## Quick Install * `pip install versioneer` to somewhere to your $PATH * add a `[versioneer]` section to your setup.cfg (see below) * run `versioneer install` in your source tree, commit the results ## Version Identifiers Source trees come from a variety of places: * a version-control system checkout (mostly used by developers) * a nightly tarball, produced by build automation * a snapshot tarball, produced by a web-based VCS browser, like github's "tarball from tag" feature * a release tarball, produced by "setup.py sdist", distributed through PyPI Within each source tree, the version identifier (either a string or a number, this tool is format-agnostic) can come from a variety of places: * ask the VCS tool itself, e.g. "git describe" (for checkouts), which knows about recent "tags" and an absolute revision-id * the name of the directory into which the tarball was unpacked * an expanded VCS keyword ($Id$, etc) * a `_version.py` created by some earlier build step For released software, the version identifier is closely related to a VCS tag. Some projects use tag names that include more than just the version string (e.g. "myproject-1.2" instead of just "1.2"), in which case the tool needs to strip the tag prefix to extract the version identifier. For unreleased software (between tags), the version identifier should provide enough information to help developers recreate the same tree, while also giving them an idea of roughly how old the tree is (after version 1.2, before version 1.3). Many VCS systems can report a description that captures this, for example `git describe --tags --dirty --always` reports things like "0.7-1-g574ab98-dirty" to indicate that the checkout is one revision past the 0.7 tag, has a unique revision id of "574ab98", and is "dirty" (it has uncommitted changes. The version identifier is used for multiple purposes: * to allow the module to self-identify its version: `myproject.__version__` * to choose a name and prefix for a 'setup.py sdist' tarball ## Theory of Operation Versioneer works by adding a special `_version.py` file into your source tree, where your `__init__.py` can import it. This `_version.py` knows how to dynamically ask the VCS tool for version information at import time. `_version.py` also contains `$Revision$` markers, and the installation process marks `_version.py` to have this marker rewritten with a tag name during the `git archive` command. As a result, generated tarballs will contain enough information to get the proper version. To allow `setup.py` to compute a version too, a `versioneer.py` is added to the top level of your source tree, next to `setup.py` and the `setup.cfg` that configures it. This overrides several distutils/setuptools commands to compute the version when invoked, and changes `setup.py build` and `setup.py sdist` to replace `_version.py` with a small static file that contains just the generated version data. ## Installation See [INSTALL.md](./INSTALL.md) for detailed installation instructions. ## Version-String Flavors Code which uses Versioneer can learn about its version string at runtime by importing `_version` from your main `__init__.py` file and running the `get_versions()` function. From the "outside" (e.g. in `setup.py`), you can import the top-level `versioneer.py` and run `get_versions()`. Both functions return a dictionary with different flavors of version information: * `['version']`: A condensed version string, rendered using the selected style. This is the most commonly used value for the project's version string. The default "pep440" style yields strings like `0.11`, `0.11+2.g1076c97`, or `0.11+2.g1076c97.dirty`. See the "Styles" section below for alternative styles. * `['full-revisionid']`: detailed revision identifier. For Git, this is the full SHA1 commit id, e.g. "1076c978a8d3cfc70f408fe5974aa6c092c949ac". * `['date']`: Date and time of the latest `HEAD` commit. For Git, it is the commit date in ISO 8601 format. This will be None if the date is not available. * `['dirty']`: a boolean, True if the tree has uncommitted changes. Note that this is only accurate if run in a VCS checkout, otherwise it is likely to be False or None * `['error']`: if the version string could not be computed, this will be set to a string describing the problem, otherwise it will be None. It may be useful to throw an exception in setup.py if this is set, to avoid e.g. creating tarballs with a version string of "unknown". Some variants are more useful than others. Including `full-revisionid` in a bug report should allow developers to reconstruct the exact code being tested (or indicate the presence of local changes that should be shared with the developers). `version` is suitable for display in an "about" box or a CLI `--version` output: it can be easily compared against release notes and lists of bugs fixed in various releases. The installer adds the following text to your `__init__.py` to place a basic version in `YOURPROJECT.__version__`: from ._version import get_versions __version__ = get_versions()['version'] del get_versions ## Styles The setup.cfg `style=` configuration controls how the VCS information is rendered into a version string. The default style, "pep440", produces a PEP440-compliant string, equal to the un-prefixed tag name for actual releases, and containing an additional "local version" section with more detail for in-between builds. For Git, this is TAG[+DISTANCE.gHEX[.dirty]] , using information from `git describe --tags --dirty --always`. For example "0.11+2.g1076c97.dirty" indicates that the tree is like the "1076c97" commit but has uncommitted changes (".dirty"), and that this commit is two revisions ("+2") beyond the "0.11" tag. For released software (exactly equal to a known tag), the identifier will only contain the stripped tag, e.g. "0.11". Other styles are available. See [details.md](details.md) in the Versioneer source tree for descriptions. ## Debugging Versioneer tries to avoid fatal errors: if something goes wrong, it will tend to return a version of "0+unknown". To investigate the problem, run `setup.py version`, which will run the version-lookup code in a verbose mode, and will display the full contents of `get_versions()` (including the `error` string, which may help identify what went wrong). ## Known Limitations Some situations are known to cause problems for Versioneer. This details the most significant ones. More can be found on Github [issues page](https://github.com/warner/python-versioneer/issues). ### Subprojects Versioneer has limited support for source trees in which `setup.py` is not in the root directory (e.g. `setup.py` and `.git/` are *not* siblings). The are two common reasons why `setup.py` might not be in the root: * Source trees which contain multiple subprojects, such as [Buildbot](https://github.com/buildbot/buildbot), which contains both "master" and "slave" subprojects, each with their own `setup.py`, `setup.cfg`, and `tox.ini`. Projects like these produce multiple PyPI distributions (and upload multiple independently-installable tarballs). * Source trees whose main purpose is to contain a C library, but which also provide bindings to Python (and perhaps other langauges) in subdirectories. Versioneer will look for `.git` in parent directories, and most operations should get the right version string. However `pip` and `setuptools` have bugs and implementation details which frequently cause `pip install .` from a subproject directory to fail to find a correct version string (so it usually defaults to `0+unknown`). `pip install --editable .` should work correctly. `setup.py install` might work too. Pip-8.1.1 is known to have this problem, but hopefully it will get fixed in some later version. [Bug #38](https://github.com/warner/python-versioneer/issues/38) is tracking this issue. The discussion in [PR #61](https://github.com/warner/python-versioneer/pull/61) describes the issue from the Versioneer side in more detail. [pip PR#3176](https://github.com/pypa/pip/pull/3176) and [pip PR#3615](https://github.com/pypa/pip/pull/3615) contain work to improve pip to let Versioneer work correctly. Versioneer-0.16 and earlier only looked for a `.git` directory next to the `setup.cfg`, so subprojects were completely unsupported with those releases. ### Editable installs with setuptools <= 18.5 `setup.py develop` and `pip install --editable .` allow you to install a project into a virtualenv once, then continue editing the source code (and test) without re-installing after every change. "Entry-point scripts" (`setup(entry_points={"console_scripts": ..})`) are a convenient way to specify executable scripts that should be installed along with the python package. These both work as expected when using modern setuptools. When using setuptools-18.5 or earlier, however, certain operations will cause `pkg_resources.DistributionNotFound` errors when running the entrypoint script, which must be resolved by re-installing the package. This happens when the install happens with one version, then the egg_info data is regenerated while a different version is checked out. Many setup.py commands cause egg_info to be rebuilt (including `sdist`, `wheel`, and installing into a different virtualenv), so this can be surprising. [Bug #83](https://github.com/warner/python-versioneer/issues/83) describes this one, but upgrading to a newer version of setuptools should probably resolve it. ### Unicode version strings While Versioneer works (and is continually tested) with both Python 2 and Python 3, it is not entirely consistent with bytes-vs-unicode distinctions. Newer releases probably generate unicode version strings on py2. It's not clear that this is wrong, but it may be surprising for applications when then write these strings to a network connection or include them in bytes-oriented APIs like cryptographic checksums. [Bug #71](https://github.com/warner/python-versioneer/issues/71) investigates this question. ## Updating Versioneer To upgrade your project to a new release of Versioneer, do the following: * install the new Versioneer (`pip install -U versioneer` or equivalent) * edit `setup.cfg`, if necessary, to include any new configuration settings indicated by the release notes. See [UPGRADING](./UPGRADING.md) for details. * re-run `versioneer install` in your source tree, to replace `SRC/_version.py` * commit any changed files ## Future Directions This tool is designed to make it easily extended to other version-control systems: all VCS-specific components are in separate directories like src/git/ . The top-level `versioneer.py` script is assembled from these components by running make-versioneer.py . In the future, make-versioneer.py will take a VCS name as an argument, and will construct a version of `versioneer.py` that is specific to the given VCS. It might also take the configuration arguments that are currently provided manually during installation by editing setup.py . Alternatively, it might go the other direction and include code from all supported VCS systems, reducing the number of intermediate scripts. ## License To make Versioneer easier to embed, all its code is dedicated to the public domain. The `_version.py` that it creates is also in the public domain. Specifically, both are released under the Creative Commons "Public Domain Dedication" license (CC0-1.0), as described in https://creativecommons.org/publicdomain/zero/1.0/ . """ from __future__ import print_function try: import configparser except ImportError: import ConfigParser as configparser import errno import json import os import re import subprocess import sys class VersioneerConfig: """Container for Versioneer configuration parameters.""" def get_root(): """Get the project root directory. We require that all commands are run from the project root, i.e. the directory that contains setup.py, setup.cfg, and versioneer.py . """ root = os.path.realpath(os.path.abspath(os.getcwd())) setup_py = os.path.join(root, "setup.py") versioneer_py = os.path.join(root, "versioneer.py") if not (os.path.exists(setup_py) or os.path.exists(versioneer_py)): # allow 'python path/to/setup.py COMMAND' root = os.path.dirname(os.path.realpath(os.path.abspath(sys.argv[0]))) setup_py = os.path.join(root, "setup.py") versioneer_py = os.path.join(root, "versioneer.py") if not (os.path.exists(setup_py) or os.path.exists(versioneer_py)): err = ( "Versioneer was unable to run the project root directory. " "Versioneer requires setup.py to be executed from " "its immediate directory (like 'python setup.py COMMAND'), " "or in a way that lets it use sys.argv[0] to find the root " "(like 'python path/to/setup.py COMMAND')." ) raise VersioneerBadRootError(err) try: # Certain runtime workflows (setup.py install/develop in a setuptools # tree) execute all dependencies in a single python process, so # "versioneer" may be imported multiple times, and python's shared # module-import table will cache the first one. So we can't use # os.path.dirname(__file__), as that will find whichever # versioneer.py was first imported, even in later projects. me = os.path.realpath(os.path.abspath(__file__)) me_dir = os.path.normcase(os.path.splitext(me)[0]) vsr_dir = os.path.normcase(os.path.splitext(versioneer_py)[0]) if me_dir != vsr_dir: print( "Warning: build in %s is using versioneer.py from %s" % (os.path.dirname(me), versioneer_py) ) except NameError: pass return root def get_config_from_root(root): """Read the project setup.cfg file to determine Versioneer config.""" # This might raise EnvironmentError (if setup.cfg is missing), or # configparser.NoSectionError (if it lacks a [versioneer] section), or # configparser.NoOptionError (if it lacks "VCS="). See the docstring at # the top of versioneer.py for instructions on writing your setup.cfg . setup_cfg = os.path.join(root, "setup.cfg") parser = configparser.SafeConfigParser() with open(setup_cfg, "r") as f: parser.readfp(f) VCS = parser.get("versioneer", "VCS") # mandatory def get(parser, name): if parser.has_option("versioneer", name): return parser.get("versioneer", name) return None cfg = VersioneerConfig() cfg.VCS = VCS cfg.style = get(parser, "style") or "" cfg.versionfile_source = get(parser, "versionfile_source") cfg.versionfile_build = get(parser, "versionfile_build") cfg.tag_prefix = get(parser, "tag_prefix") if cfg.tag_prefix in ("''", '""'): cfg.tag_prefix = "" cfg.parentdir_prefix = get(parser, "parentdir_prefix") cfg.verbose = get(parser, "verbose") return cfg class NotThisMethod(Exception): """Exception raised if a method is not valid for the current scenario.""" # these dictionaries contain VCS-specific tools LONG_VERSION_PY = {} HANDLERS = {} def register_vcs_handler(vcs, method): # decorator """Decorator to mark a method as the handler for a particular VCS.""" def decorate(f): """Store f in HANDLERS[vcs][method].""" if vcs not in HANDLERS: HANDLERS[vcs] = {} HANDLERS[vcs][method] = f return f return decorate def run_command(commands, args, cwd=None, verbose=False, hide_stderr=False, env=None): """Call the given command(s).""" assert isinstance(commands, list) p = None for c in commands: try: dispcmd = str([c] + args) # remember shell=False, so use git.cmd on windows, not just git p = subprocess.Popen( [c] + args, cwd=cwd, env=env, stdout=subprocess.PIPE, stderr=(subprocess.PIPE if hide_stderr else None), ) break except EnvironmentError: e = sys.exc_info()[1] if e.errno == errno.ENOENT: continue if verbose: print("unable to run %s" % dispcmd) print(e) return None, None else: if verbose: print("unable to find command, tried %s" % (commands,)) return None, None stdout = p.communicate()[0].strip() if sys.version_info[0] >= 3: stdout = stdout.decode() if p.returncode != 0: if verbose: print("unable to run %s (error)" % dispcmd) print("stdout was %s" % stdout) return None, p.returncode return stdout, p.returncode LONG_VERSION_PY[ "git" ] = ''' # This file helps to compute a version number in source trees obtained from # git-archive tarball (such as those provided by githubs download-from-tag # feature). Distribution tarballs (built by setup.py sdist) and build # directories (produced by setup.py build) will contain a much shorter file # that just contains the computed version number. # This file is released into the public domain. Generated by # versioneer-0.18 (https://github.com/warner/python-versioneer) """Git implementation of _version.py.""" import errno import os import re import subprocess import sys def get_keywords(): """Get the keywords needed to look up the version information.""" # these strings will be replaced by git during git-archive. # setup.py/versioneer.py will grep for the variable names, so they must # each be defined on a line of their own. _version.py will just call # get_keywords(). git_refnames = "%(DOLLAR)sFormat:%%d%(DOLLAR)s" git_full = "%(DOLLAR)sFormat:%%H%(DOLLAR)s" git_date = "%(DOLLAR)sFormat:%%ci%(DOLLAR)s" keywords = {"refnames": git_refnames, "full": git_full, "date": git_date} return keywords class VersioneerConfig: """Container for Versioneer configuration parameters.""" def get_config(): """Create, populate and return the VersioneerConfig() object.""" # these strings are filled in when 'setup.py versioneer' creates # _version.py cfg = VersioneerConfig() cfg.VCS = "git" cfg.style = "%(STYLE)s" cfg.tag_prefix = "%(TAG_PREFIX)s" cfg.parentdir_prefix = "%(PARENTDIR_PREFIX)s" cfg.versionfile_source = "%(VERSIONFILE_SOURCE)s" cfg.verbose = False return cfg class NotThisMethod(Exception): """Exception raised if a method is not valid for the current scenario.""" LONG_VERSION_PY = {} HANDLERS = {} def register_vcs_handler(vcs, method): # decorator """Decorator to mark a method as the handler for a particular VCS.""" def decorate(f): """Store f in HANDLERS[vcs][method].""" if vcs not in HANDLERS: HANDLERS[vcs] = {} HANDLERS[vcs][method] = f return f return decorate def run_command(commands, args, cwd=None, verbose=False, hide_stderr=False, env=None): """Call the given command(s).""" assert isinstance(commands, list) p = None for c in commands: try: dispcmd = str([c] + args) # remember shell=False, so use git.cmd on windows, not just git p = subprocess.Popen([c] + args, cwd=cwd, env=env, stdout=subprocess.PIPE, stderr=(subprocess.PIPE if hide_stderr else None)) break except EnvironmentError: e = sys.exc_info()[1] if e.errno == errno.ENOENT: continue if verbose: print("unable to run %%s" %% dispcmd) print(e) return None, None else: if verbose: print("unable to find command, tried %%s" %% (commands,)) return None, None stdout = p.communicate()[0].strip() if sys.version_info[0] >= 3: stdout = stdout.decode() if p.returncode != 0: if verbose: print("unable to run %%s (error)" %% dispcmd) print("stdout was %%s" %% stdout) return None, p.returncode return stdout, p.returncode def versions_from_parentdir(parentdir_prefix, root, verbose): """Try to determine the version from the parent directory name. Source tarballs conventionally unpack into a directory that includes both the project name and a version string. We will also support searching up two directory levels for an appropriately named parent directory """ rootdirs = [] for i in range(3): dirname = os.path.basename(root) if dirname.startswith(parentdir_prefix): return {"version": dirname[len(parentdir_prefix):], "full-revisionid": None, "dirty": False, "error": None, "date": None} else: rootdirs.append(root) root = os.path.dirname(root) # up a level if verbose: print("Tried directories %%s but none started with prefix %%s" %% (str(rootdirs), parentdir_prefix)) raise NotThisMethod("rootdir doesn't start with parentdir_prefix") @register_vcs_handler("git", "get_keywords") def git_get_keywords(versionfile_abs): """Extract version information from the given file.""" # the code embedded in _version.py can just fetch the value of these # keywords. When used from setup.py, we don't want to import _version.py, # so we do it with a regexp instead. This function is not used from # _version.py. keywords = {} try: f = open(versionfile_abs, "r") for line in f.readlines(): if line.strip().startswith("git_refnames ="): mo = re.search(r'=\s*"(.*)"', line) if mo: keywords["refnames"] = mo.group(1) if line.strip().startswith("git_full ="): mo = re.search(r'=\s*"(.*)"', line) if mo: keywords["full"] = mo.group(1) if line.strip().startswith("git_date ="): mo = re.search(r'=\s*"(.*)"', line) if mo: keywords["date"] = mo.group(1) f.close() except EnvironmentError: pass return keywords @register_vcs_handler("git", "keywords") def git_versions_from_keywords(keywords, tag_prefix, verbose): """Get version information from git keywords.""" if not keywords: raise NotThisMethod("no keywords at all, weird") date = keywords.get("date") if date is not None: # git-2.2.0 added "%%cI", which expands to an ISO-8601 -compliant # datestamp. However we prefer "%%ci" (which expands to an "ISO-8601 # -like" string, which we must then edit to make compliant), because # it's been around since git-1.5.3, and it's too difficult to # discover which version we're using, or to work around using an # older one. date = date.strip().replace(" ", "T", 1).replace(" ", "", 1) refnames = keywords["refnames"].strip() if refnames.startswith("$Format"): if verbose: print("keywords are unexpanded, not using") raise NotThisMethod("unexpanded keywords, not a git-archive tarball") refs = set([r.strip() for r in refnames.strip("()").split(",")]) # starting in git-1.8.3, tags are listed as "tag: foo-1.0" instead of # just "foo-1.0". If we see a "tag: " prefix, prefer those. TAG = "tag: " tags = set([r[len(TAG):] for r in refs if r.startswith(TAG)]) if not tags: # Either we're using git < 1.8.3, or there really are no tags. We use # a heuristic: assume all version tags have a digit. The old git %%d # expansion behaves like git log --decorate=short and strips out the # refs/heads/ and refs/tags/ prefixes that would let us distinguish # between branches and tags. By ignoring refnames without digits, we # filter out many common branch names like "release" and # "stabilization", as well as "HEAD" and "master". tags = set([r for r in refs if re.search(r'\d', r)]) if verbose: print("discarding '%%s', no digits" %% ",".join(refs - tags)) if verbose: print("likely tags: %%s" %% ",".join(sorted(tags))) for ref in sorted(tags): # sorting will prefer e.g. "2.0" over "2.0rc1" if ref.startswith(tag_prefix): r = ref[len(tag_prefix):] if verbose: print("picking %%s" %% r) return {"version": r, "full-revisionid": keywords["full"].strip(), "dirty": False, "error": None, "date": date} # no suitable tags, so version is "0+unknown", but full hex is still there if verbose: print("no suitable tags, using unknown + full revision id") return {"version": "0+unknown", "full-revisionid": keywords["full"].strip(), "dirty": False, "error": "no suitable tags", "date": None} @register_vcs_handler("git", "pieces_from_vcs") def git_pieces_from_vcs(tag_prefix, root, verbose, run_command=run_command): """Get version from 'git describe' in the root of the source tree. This only gets called if the git-archive 'subst' keywords were *not* expanded, and _version.py hasn't already been rewritten with a short version string, meaning we're inside a checked out source tree. """ GITS = ["git"] if sys.platform == "win32": GITS = ["git.cmd", "git.exe"] out, rc = run_command(GITS, ["rev-parse", "--git-dir"], cwd=root, hide_stderr=True) if rc != 0: if verbose: print("Directory %%s not under git control" %% root) raise NotThisMethod("'git rev-parse --git-dir' returned error") # if there is a tag matching tag_prefix, this yields TAG-NUM-gHEX[-dirty] # if there isn't one, this yields HEX[-dirty] (no NUM) describe_out, rc = run_command(GITS, ["describe", "--tags", "--dirty", "--always", "--long", "--match", "%%s*" %% tag_prefix], cwd=root) # --long was added in git-1.5.5 if describe_out is None: raise NotThisMethod("'git describe' failed") describe_out = describe_out.strip() full_out, rc = run_command(GITS, ["rev-parse", "HEAD"], cwd=root) if full_out is None: raise NotThisMethod("'git rev-parse' failed") full_out = full_out.strip() pieces = {} pieces["long"] = full_out pieces["short"] = full_out[:7] # maybe improved later pieces["error"] = None # parse describe_out. It will be like TAG-NUM-gHEX[-dirty] or HEX[-dirty] # TAG might have hyphens. git_describe = describe_out # look for -dirty suffix dirty = git_describe.endswith("-dirty") pieces["dirty"] = dirty if dirty: git_describe = git_describe[:git_describe.rindex("-dirty")] # now we have TAG-NUM-gHEX or HEX if "-" in git_describe: # TAG-NUM-gHEX mo = re.search(r'^(.+)-(\d+)-g([0-9a-f]+)$', git_describe) if not mo: # unparseable. Maybe git-describe is misbehaving? pieces["error"] = ("unable to parse git-describe output: '%%s'" %% describe_out) return pieces # tag full_tag = mo.group(1) if not full_tag.startswith(tag_prefix): if verbose: fmt = "tag '%%s' doesn't start with prefix '%%s'" print(fmt %% (full_tag, tag_prefix)) pieces["error"] = ("tag '%%s' doesn't start with prefix '%%s'" %% (full_tag, tag_prefix)) return pieces pieces["closest-tag"] = full_tag[len(tag_prefix):] # distance: number of commits since tag pieces["distance"] = int(mo.group(2)) # commit: short hex revision ID pieces["short"] = mo.group(3) else: # HEX: no tags pieces["closest-tag"] = None count_out, rc = run_command(GITS, ["rev-list", "HEAD", "--count"], cwd=root) pieces["distance"] = int(count_out) # total number of commits # commit date: see ISO-8601 comment in git_versions_from_keywords() date = run_command(GITS, ["show", "-s", "--format=%%ci", "HEAD"], cwd=root)[0].strip() pieces["date"] = date.strip().replace(" ", "T", 1).replace(" ", "", 1) return pieces def plus_or_dot(pieces): """Return a + if we don't already have one, else return a .""" if "+" in pieces.get("closest-tag", ""): return "." return "+" def render_pep440(pieces): """Build up version string, with post-release "local version identifier". Our goal: TAG[+DISTANCE.gHEX[.dirty]] . Note that if you get a tagged build and then dirty it, you'll get TAG+0.gHEX.dirty Exceptions: 1: no tags. git_describe was just HEX. 0+untagged.DISTANCE.gHEX[.dirty] """ if pieces["closest-tag"]: rendered = pieces["closest-tag"] if pieces["distance"] or pieces["dirty"]: rendered += plus_or_dot(pieces) rendered += "%%d.g%%s" %% (pieces["distance"], pieces["short"]) if pieces["dirty"]: rendered += ".dirty" else: # exception #1 rendered = "0+untagged.%%d.g%%s" %% (pieces["distance"], pieces["short"]) if pieces["dirty"]: rendered += ".dirty" return rendered def render_pep440_pre(pieces): """TAG[.post.devDISTANCE] -- No -dirty. Exceptions: 1: no tags. 0.post.devDISTANCE """ if pieces["closest-tag"]: rendered = pieces["closest-tag"] if pieces["distance"]: rendered += ".post.dev%%d" %% pieces["distance"] else: # exception #1 rendered = "0.post.dev%%d" %% pieces["distance"] return rendered def render_pep440_post(pieces): """TAG[.postDISTANCE[.dev0]+gHEX] . The ".dev0" means dirty. Note that .dev0 sorts backwards (a dirty tree will appear "older" than the corresponding clean one), but you shouldn't be releasing software with -dirty anyways. Exceptions: 1: no tags. 0.postDISTANCE[.dev0] """ if pieces["closest-tag"]: rendered = pieces["closest-tag"] if pieces["distance"] or pieces["dirty"]: rendered += ".post%%d" %% pieces["distance"] if pieces["dirty"]: rendered += ".dev0" rendered += plus_or_dot(pieces) rendered += "g%%s" %% pieces["short"] else: # exception #1 rendered = "0.post%%d" %% pieces["distance"] if pieces["dirty"]: rendered += ".dev0" rendered += "+g%%s" %% pieces["short"] return rendered def render_pep440_old(pieces): """TAG[.postDISTANCE[.dev0]] . The ".dev0" means dirty. Eexceptions: 1: no tags. 0.postDISTANCE[.dev0] """ if pieces["closest-tag"]: rendered = pieces["closest-tag"] if pieces["distance"] or pieces["dirty"]: rendered += ".post%%d" %% pieces["distance"] if pieces["dirty"]: rendered += ".dev0" else: # exception #1 rendered = "0.post%%d" %% pieces["distance"] if pieces["dirty"]: rendered += ".dev0" return rendered def render_git_describe(pieces): """TAG[-DISTANCE-gHEX][-dirty]. Like 'git describe --tags --dirty --always'. Exceptions: 1: no tags. HEX[-dirty] (note: no 'g' prefix) """ if pieces["closest-tag"]: rendered = pieces["closest-tag"] if pieces["distance"]: rendered += "-%%d-g%%s" %% (pieces["distance"], pieces["short"]) else: # exception #1 rendered = pieces["short"] if pieces["dirty"]: rendered += "-dirty" return rendered def render_git_describe_long(pieces): """TAG-DISTANCE-gHEX[-dirty]. Like 'git describe --tags --dirty --always -long'. The distance/hash is unconditional. Exceptions: 1: no tags. HEX[-dirty] (note: no 'g' prefix) """ if pieces["closest-tag"]: rendered = pieces["closest-tag"] rendered += "-%%d-g%%s" %% (pieces["distance"], pieces["short"]) else: # exception #1 rendered = pieces["short"] if pieces["dirty"]: rendered += "-dirty" return rendered def render(pieces, style): """Render the given version pieces into the requested style.""" if pieces["error"]: return {"version": "unknown", "full-revisionid": pieces.get("long"), "dirty": None, "error": pieces["error"], "date": None} if not style or style == "default": style = "pep440" # the default if style == "pep440": rendered = render_pep440(pieces) elif style == "pep440-pre": rendered = render_pep440_pre(pieces) elif style == "pep440-post": rendered = render_pep440_post(pieces) elif style == "pep440-old": rendered = render_pep440_old(pieces) elif style == "git-describe": rendered = render_git_describe(pieces) elif style == "git-describe-long": rendered = render_git_describe_long(pieces) else: raise ValueError("unknown style '%%s'" %% style) return {"version": rendered, "full-revisionid": pieces["long"], "dirty": pieces["dirty"], "error": None, "date": pieces.get("date")} def get_versions(): """Get version information or return default if unable to do so.""" # I am in _version.py, which lives at ROOT/VERSIONFILE_SOURCE. If we have # __file__, we can work backwards from there to the root. Some # py2exe/bbfreeze/non-CPython implementations don't do __file__, in which # case we can only use expanded keywords. cfg = get_config() verbose = cfg.verbose try: return git_versions_from_keywords(get_keywords(), cfg.tag_prefix, verbose) except NotThisMethod: pass try: root = os.path.realpath(__file__) # versionfile_source is the relative path from the top of the source # tree (where the .git directory might live) to this file. Invert # this to find the root from __file__. for i in cfg.versionfile_source.split('/'): root = os.path.dirname(root) except NameError: return {"version": "0+unknown", "full-revisionid": None, "dirty": None, "error": "unable to find root of source tree", "date": None} try: pieces = git_pieces_from_vcs(cfg.tag_prefix, root, verbose) return render(pieces, cfg.style) except NotThisMethod: pass try: if cfg.parentdir_prefix: return versions_from_parentdir(cfg.parentdir_prefix, root, verbose) except NotThisMethod: pass return {"version": "0+unknown", "full-revisionid": None, "dirty": None, "error": "unable to compute version", "date": None} ''' @register_vcs_handler("git", "get_keywords") def git_get_keywords(versionfile_abs): """Extract version information from the given file.""" # the code embedded in _version.py can just fetch the value of these # keywords. When used from setup.py, we don't want to import _version.py, # so we do it with a regexp instead. This function is not used from # _version.py. keywords = {} try: f = open(versionfile_abs, "r") for line in f.readlines(): if line.strip().startswith("git_refnames ="): mo = re.search(r'=\s*"(.*)"', line) if mo: keywords["refnames"] = mo.group(1) if line.strip().startswith("git_full ="): mo = re.search(r'=\s*"(.*)"', line) if mo: keywords["full"] = mo.group(1) if line.strip().startswith("git_date ="): mo = re.search(r'=\s*"(.*)"', line) if mo: keywords["date"] = mo.group(1) f.close() except EnvironmentError: pass return keywords @register_vcs_handler("git", "keywords") def git_versions_from_keywords(keywords, tag_prefix, verbose): """Get version information from git keywords.""" if not keywords: raise NotThisMethod("no keywords at all, weird") date = keywords.get("date") if date is not None: # git-2.2.0 added "%cI", which expands to an ISO-8601 -compliant # datestamp. However we prefer "%ci" (which expands to an "ISO-8601 # -like" string, which we must then edit to make compliant), because # it's been around since git-1.5.3, and it's too difficult to # discover which version we're using, or to work around using an # older one. date = date.strip().replace(" ", "T", 1).replace(" ", "", 1) refnames = keywords["refnames"].strip() if refnames.startswith("$Format"): if verbose: print("keywords are unexpanded, not using") raise NotThisMethod("unexpanded keywords, not a git-archive tarball") refs = set([r.strip() for r in refnames.strip("()").split(",")]) # starting in git-1.8.3, tags are listed as "tag: foo-1.0" instead of # just "foo-1.0". If we see a "tag: " prefix, prefer those. TAG = "tag: " tags = set([r[len(TAG) :] for r in refs if r.startswith(TAG)]) if not tags: # Either we're using git < 1.8.3, or there really are no tags. We use # a heuristic: assume all version tags have a digit. The old git %d # expansion behaves like git log --decorate=short and strips out the # refs/heads/ and refs/tags/ prefixes that would let us distinguish # between branches and tags. By ignoring refnames without digits, we # filter out many common branch names like "release" and # "stabilization", as well as "HEAD" and "master". tags = set([r for r in refs if re.search(r"\d", r)]) if verbose: print("discarding '%s', no digits" % ",".join(refs - tags)) if verbose: print("likely tags: %s" % ",".join(sorted(tags))) for ref in sorted(tags): # sorting will prefer e.g. "2.0" over "2.0rc1" if ref.startswith(tag_prefix): r = ref[len(tag_prefix) :] if verbose: print("picking %s" % r) return { "version": r, "full-revisionid": keywords["full"].strip(), "dirty": False, "error": None, "date": date, } # no suitable tags, so version is "0+unknown", but full hex is still there if verbose: print("no suitable tags, using unknown + full revision id") return { "version": "0+unknown", "full-revisionid": keywords["full"].strip(), "dirty": False, "error": "no suitable tags", "date": None, } @register_vcs_handler("git", "pieces_from_vcs") def git_pieces_from_vcs(tag_prefix, root, verbose, run_command=run_command): """Get version from 'git describe' in the root of the source tree. This only gets called if the git-archive 'subst' keywords were *not* expanded, and _version.py hasn't already been rewritten with a short version string, meaning we're inside a checked out source tree. """ GITS = ["git"] if sys.platform == "win32": GITS = ["git.cmd", "git.exe"] out, rc = run_command(GITS, ["rev-parse", "--git-dir"], cwd=root, hide_stderr=True) if rc != 0: if verbose: print("Directory %s not under git control" % root) raise NotThisMethod("'git rev-parse --git-dir' returned error") # if there is a tag matching tag_prefix, this yields TAG-NUM-gHEX[-dirty] # if there isn't one, this yields HEX[-dirty] (no NUM) describe_out, rc = run_command( GITS, [ "describe", "--tags", "--dirty", "--always", "--long", "--match", "%s*" % tag_prefix, ], cwd=root, ) # --long was added in git-1.5.5 if describe_out is None: raise NotThisMethod("'git describe' failed") describe_out = describe_out.strip() full_out, rc = run_command(GITS, ["rev-parse", "HEAD"], cwd=root) if full_out is None: raise NotThisMethod("'git rev-parse' failed") full_out = full_out.strip() pieces = {} pieces["long"] = full_out pieces["short"] = full_out[:7] # maybe improved later pieces["error"] = None # parse describe_out. It will be like TAG-NUM-gHEX[-dirty] or HEX[-dirty] # TAG might have hyphens. git_describe = describe_out # look for -dirty suffix dirty = git_describe.endswith("-dirty") pieces["dirty"] = dirty if dirty: git_describe = git_describe[: git_describe.rindex("-dirty")] # now we have TAG-NUM-gHEX or HEX if "-" in git_describe: # TAG-NUM-gHEX mo = re.search(r"^(.+)-(\d+)-g([0-9a-f]+)$", git_describe) if not mo: # unparseable. Maybe git-describe is misbehaving? pieces["error"] = "unable to parse git-describe output: '%s'" % describe_out return pieces # tag full_tag = mo.group(1) if not full_tag.startswith(tag_prefix): if verbose: fmt = "tag '%s' doesn't start with prefix '%s'" print(fmt % (full_tag, tag_prefix)) pieces["error"] = "tag '%s' doesn't start with prefix '%s'" % ( full_tag, tag_prefix, ) return pieces pieces["closest-tag"] = full_tag[len(tag_prefix) :] # distance: number of commits since tag pieces["distance"] = int(mo.group(2)) # commit: short hex revision ID pieces["short"] = mo.group(3) else: # HEX: no tags pieces["closest-tag"] = None count_out, rc = run_command(GITS, ["rev-list", "HEAD", "--count"], cwd=root) pieces["distance"] = int(count_out) # total number of commits # commit date: see ISO-8601 comment in git_versions_from_keywords() date = run_command(GITS, ["show", "-s", "--format=%ci", "HEAD"], cwd=root)[ 0 ].strip() pieces["date"] = date.strip().replace(" ", "T", 1).replace(" ", "", 1) return pieces def do_vcs_install(manifest_in, versionfile_source, ipy): """Git-specific installation logic for Versioneer. For Git, this means creating/changing .gitattributes to mark _version.py for export-subst keyword substitution. """ GITS = ["git"] if sys.platform == "win32": GITS = ["git.cmd", "git.exe"] files = [manifest_in, versionfile_source] if ipy: files.append(ipy) try: me = __file__ if me.endswith(".pyc") or me.endswith(".pyo"): me = os.path.splitext(me)[0] + ".py" versioneer_file = os.path.relpath(me) except NameError: versioneer_file = "versioneer.py" files.append(versioneer_file) present = False try: f = open(".gitattributes", "r") for line in f.readlines(): if line.strip().startswith(versionfile_source): if "export-subst" in line.strip().split()[1:]: present = True f.close() except EnvironmentError: pass if not present: f = open(".gitattributes", "a+") f.write("%s export-subst\n" % versionfile_source) f.close() files.append(".gitattributes") run_command(GITS, ["add", "--"] + files) def versions_from_parentdir(parentdir_prefix, root, verbose): """Try to determine the version from the parent directory name. Source tarballs conventionally unpack into a directory that includes both the project name and a version string. We will also support searching up two directory levels for an appropriately named parent directory """ rootdirs = [] for i in range(3): dirname = os.path.basename(root) if dirname.startswith(parentdir_prefix): return { "version": dirname[len(parentdir_prefix) :], "full-revisionid": None, "dirty": False, "error": None, "date": None, } else: rootdirs.append(root) root = os.path.dirname(root) # up a level if verbose: print( "Tried directories %s but none started with prefix %s" % (str(rootdirs), parentdir_prefix) ) raise NotThisMethod("rootdir doesn't start with parentdir_prefix") SHORT_VERSION_PY = """ # This file was generated by 'versioneer.py' (0.18) from # revision-control system data, or from the parent directory name of an # unpacked source archive. Distribution tarballs contain a pre-generated copy # of this file. import json version_json = ''' %s ''' # END VERSION_JSON def get_versions(): return json.loads(version_json) """ def versions_from_file(filename): """Try to determine the version from _version.py if present.""" try: with open(filename) as f: contents = f.read() except EnvironmentError: raise NotThisMethod("unable to read _version.py") mo = re.search( r"version_json = '''\n(.*)''' # END VERSION_JSON", contents, re.M | re.S ) if not mo: mo = re.search( r"version_json = '''\r\n(.*)''' # END VERSION_JSON", contents, re.M | re.S ) if not mo: raise NotThisMethod("no version_json in _version.py") return json.loads(mo.group(1)) def write_to_version_file(filename, versions): """Write the given version number to the given _version.py file.""" os.unlink(filename) contents = json.dumps(versions, sort_keys=True, indent=1, separators=(",", ": ")) with open(filename, "w") as f: f.write(SHORT_VERSION_PY % contents) print("set %s to '%s'" % (filename, versions["version"])) def plus_or_dot(pieces): """Return a + if we don't already have one, else return a .""" if "+" in pieces.get("closest-tag", ""): return "." return "+" def render_pep440(pieces): """Build up version string, with post-release "local version identifier". Our goal: TAG[+DISTANCE.gHEX[.dirty]] . Note that if you get a tagged build and then dirty it, you'll get TAG+0.gHEX.dirty Exceptions: 1: no tags. git_describe was just HEX. 0+untagged.DISTANCE.gHEX[.dirty] """ if pieces["closest-tag"]: rendered = pieces["closest-tag"] if pieces["distance"] or pieces["dirty"]: rendered += plus_or_dot(pieces) rendered += "%d.g%s" % (pieces["distance"], pieces["short"]) if pieces["dirty"]: rendered += ".dirty" else: # exception #1 rendered = "0+untagged.%d.g%s" % (pieces["distance"], pieces["short"]) if pieces["dirty"]: rendered += ".dirty" return rendered def render_pep440_pre(pieces): """TAG[.post.devDISTANCE] -- No -dirty. Exceptions: 1: no tags. 0.post.devDISTANCE """ if pieces["closest-tag"]: rendered = pieces["closest-tag"] if pieces["distance"]: rendered += ".post.dev%d" % pieces["distance"] else: # exception #1 rendered = "0.post.dev%d" % pieces["distance"] return rendered def render_pep440_post(pieces): """TAG[.postDISTANCE[.dev0]+gHEX] . The ".dev0" means dirty. Note that .dev0 sorts backwards (a dirty tree will appear "older" than the corresponding clean one), but you shouldn't be releasing software with -dirty anyways. Exceptions: 1: no tags. 0.postDISTANCE[.dev0] """ if pieces["closest-tag"]: rendered = pieces["closest-tag"] if pieces["distance"] or pieces["dirty"]: rendered += ".post%d" % pieces["distance"] if pieces["dirty"]: rendered += ".dev0" rendered += plus_or_dot(pieces) rendered += "g%s" % pieces["short"] else: # exception #1 rendered = "0.post%d" % pieces["distance"] if pieces["dirty"]: rendered += ".dev0" rendered += "+g%s" % pieces["short"] return rendered def render_pep440_old(pieces): """TAG[.postDISTANCE[.dev0]] . The ".dev0" means dirty. Eexceptions: 1: no tags. 0.postDISTANCE[.dev0] """ if pieces["closest-tag"]: rendered = pieces["closest-tag"] if pieces["distance"] or pieces["dirty"]: rendered += ".post%d" % pieces["distance"] if pieces["dirty"]: rendered += ".dev0" else: # exception #1 rendered = "0.post%d" % pieces["distance"] if pieces["dirty"]: rendered += ".dev0" return rendered def render_git_describe(pieces): """TAG[-DISTANCE-gHEX][-dirty]. Like 'git describe --tags --dirty --always'. Exceptions: 1: no tags. HEX[-dirty] (note: no 'g' prefix) """ if pieces["closest-tag"]: rendered = pieces["closest-tag"] if pieces["distance"]: rendered += "-%d-g%s" % (pieces["distance"], pieces["short"]) else: # exception #1 rendered = pieces["short"] if pieces["dirty"]: rendered += "-dirty" return rendered def render_git_describe_long(pieces): """TAG-DISTANCE-gHEX[-dirty]. Like 'git describe --tags --dirty --always -long'. The distance/hash is unconditional. Exceptions: 1: no tags. HEX[-dirty] (note: no 'g' prefix) """ if pieces["closest-tag"]: rendered = pieces["closest-tag"] rendered += "-%d-g%s" % (pieces["distance"], pieces["short"]) else: # exception #1 rendered = pieces["short"] if pieces["dirty"]: rendered += "-dirty" return rendered def render(pieces, style): """Render the given version pieces into the requested style.""" if pieces["error"]: return { "version": "unknown", "full-revisionid": pieces.get("long"), "dirty": None, "error": pieces["error"], "date": None, } if not style or style == "default": style = "pep440" # the default if style == "pep440": rendered = render_pep440(pieces) elif style == "pep440-pre": rendered = render_pep440_pre(pieces) elif style == "pep440-post": rendered = render_pep440_post(pieces) elif style == "pep440-old": rendered = render_pep440_old(pieces) elif style == "git-describe": rendered = render_git_describe(pieces) elif style == "git-describe-long": rendered = render_git_describe_long(pieces) else: raise ValueError("unknown style '%s'" % style) return { "version": rendered, "full-revisionid": pieces["long"], "dirty": pieces["dirty"], "error": None, "date": pieces.get("date"), } class VersioneerBadRootError(Exception): """The project root directory is unknown or missing key files.""" def get_versions(verbose=False): """Get the project version from whatever source is available. Returns dict with two keys: 'version' and 'full'. """ if "versioneer" in sys.modules: # see the discussion in cmdclass.py:get_cmdclass() del sys.modules["versioneer"] root = get_root() cfg = get_config_from_root(root) assert cfg.VCS is not None, "please set [versioneer]VCS= in setup.cfg" handlers = HANDLERS.get(cfg.VCS) assert handlers, "unrecognized VCS '%s'" % cfg.VCS verbose = verbose or cfg.verbose assert ( cfg.versionfile_source is not None ), "please set versioneer.versionfile_source" assert cfg.tag_prefix is not None, "please set versioneer.tag_prefix" versionfile_abs = os.path.join(root, cfg.versionfile_source) # extract version from first of: _version.py, VCS command (e.g. 'git # describe'), parentdir. This is meant to work for developers using a # source checkout, for users of a tarball created by 'setup.py sdist', # and for users of a tarball/zipball created by 'git archive' or github's # download-from-tag feature or the equivalent in other VCSes. get_keywords_f = handlers.get("get_keywords") from_keywords_f = handlers.get("keywords") if get_keywords_f and from_keywords_f: try: keywords = get_keywords_f(versionfile_abs) ver = from_keywords_f(keywords, cfg.tag_prefix, verbose) if verbose: print("got version from expanded keyword %s" % ver) return ver except NotThisMethod: pass try: ver = versions_from_file(versionfile_abs) if verbose: print("got version from file %s %s" % (versionfile_abs, ver)) return ver except NotThisMethod: pass from_vcs_f = handlers.get("pieces_from_vcs") if from_vcs_f: try: pieces = from_vcs_f(cfg.tag_prefix, root, verbose) ver = render(pieces, cfg.style) if verbose: print("got version from VCS %s" % ver) return ver except NotThisMethod: pass try: if cfg.parentdir_prefix: ver = versions_from_parentdir(cfg.parentdir_prefix, root, verbose) if verbose: print("got version from parentdir %s" % ver) return ver except NotThisMethod: pass if verbose: print("unable to compute version") return { "version": "0+unknown", "full-revisionid": None, "dirty": None, "error": "unable to compute version", "date": None, } def get_version(): """Get the short version string for this project.""" return get_versions()["version"] def get_cmdclass(): """Get the custom setuptools/distutils subclasses used by Versioneer.""" if "versioneer" in sys.modules: del sys.modules["versioneer"] # this fixes the "python setup.py develop" case (also 'install' and # 'easy_install .'), in which subdependencies of the main project are # built (using setup.py bdist_egg) in the same python process. Assume # a main project A and a dependency B, which use different versions # of Versioneer. A's setup.py imports A's Versioneer, leaving it in # sys.modules by the time B's setup.py is executed, causing B to run # with the wrong versioneer. Setuptools wraps the sub-dep builds in a # sandbox that restores sys.modules to it's pre-build state, so the # parent is protected against the child's "import versioneer". By # removing ourselves from sys.modules here, before the child build # happens, we protect the child from the parent's versioneer too. # Also see https://github.com/warner/python-versioneer/issues/52 cmds = {} # we add "version" to both distutils and setuptools from distutils.core import Command class cmd_version(Command): description = "report generated version string" user_options = [] boolean_options = [] def initialize_options(self): pass def finalize_options(self): pass def run(self): vers = get_versions(verbose=True) print("Version: %s" % vers["version"]) print(" full-revisionid: %s" % vers.get("full-revisionid")) print(" dirty: %s" % vers.get("dirty")) print(" date: %s" % vers.get("date")) if vers["error"]: print(" error: %s" % vers["error"]) cmds["version"] = cmd_version # we override "build_py" in both distutils and setuptools # # most invocation pathways end up running build_py: # distutils/build -> build_py # distutils/install -> distutils/build ->.. # setuptools/bdist_wheel -> distutils/install ->.. # setuptools/bdist_egg -> distutils/install_lib -> build_py # setuptools/install -> bdist_egg ->.. # setuptools/develop -> ? # pip install: # copies source tree to a tempdir before running egg_info/etc # if .git isn't copied too, 'git describe' will fail # then does setup.py bdist_wheel, or sometimes setup.py install # setup.py egg_info -> ? # we override different "build_py" commands for both environments if "setuptools" in sys.modules: from setuptools.command.build_py import build_py as _build_py else: from distutils.command.build_py import build_py as _build_py class cmd_build_py(_build_py): def run(self): root = get_root() cfg = get_config_from_root(root) versions = get_versions() _build_py.run(self) # now locate _version.py in the new build/ directory and replace # it with an updated value if cfg.versionfile_build: target_versionfile = os.path.join(self.build_lib, cfg.versionfile_build) print("UPDATING %s" % target_versionfile) write_to_version_file(target_versionfile, versions) cmds["build_py"] = cmd_build_py if "cx_Freeze" in sys.modules: # cx_freeze enabled? from cx_Freeze.dist import build_exe as _build_exe # nczeczulin reports that py2exe won't like the pep440-style string # as FILEVERSION, but it can be used for PRODUCTVERSION, e.g. # setup(console=[{ # "version": versioneer.get_version().split("+", 1)[0], # FILEVERSION # "product_version": versioneer.get_version(), # ... class cmd_build_exe(_build_exe): def run(self): root = get_root() cfg = get_config_from_root(root) versions = get_versions() target_versionfile = cfg.versionfile_source print("UPDATING %s" % target_versionfile) write_to_version_file(target_versionfile, versions) _build_exe.run(self) os.unlink(target_versionfile) with open(cfg.versionfile_source, "w") as f: LONG = LONG_VERSION_PY[cfg.VCS] f.write( LONG % { "DOLLAR": "$", "STYLE": cfg.style, "TAG_PREFIX": cfg.tag_prefix, "PARENTDIR_PREFIX": cfg.parentdir_prefix, "VERSIONFILE_SOURCE": cfg.versionfile_source, } ) cmds["build_exe"] = cmd_build_exe del cmds["build_py"] if "py2exe" in sys.modules: # py2exe enabled? try: from py2exe.distutils_buildexe import py2exe as _py2exe # py3 except ImportError: from py2exe.build_exe import py2exe as _py2exe # py2 class cmd_py2exe(_py2exe): def run(self): root = get_root() cfg = get_config_from_root(root) versions = get_versions() target_versionfile = cfg.versionfile_source print("UPDATING %s" % target_versionfile) write_to_version_file(target_versionfile, versions) _py2exe.run(self) os.unlink(target_versionfile) with open(cfg.versionfile_source, "w") as f: LONG = LONG_VERSION_PY[cfg.VCS] f.write( LONG % { "DOLLAR": "$", "STYLE": cfg.style, "TAG_PREFIX": cfg.tag_prefix, "PARENTDIR_PREFIX": cfg.parentdir_prefix, "VERSIONFILE_SOURCE": cfg.versionfile_source, } ) cmds["py2exe"] = cmd_py2exe # we override different "sdist" commands for both environments if "setuptools" in sys.modules: from setuptools.command.sdist import sdist as _sdist else: from distutils.command.sdist import sdist as _sdist class cmd_sdist(_sdist): def run(self): versions = get_versions() self._versioneer_generated_versions = versions # unless we update this, the command will keep using the old # version self.distribution.metadata.version = versions["version"] return _sdist.run(self) def make_release_tree(self, base_dir, files): root = get_root() cfg = get_config_from_root(root) _sdist.make_release_tree(self, base_dir, files) # now locate _version.py in the new base_dir directory # (remembering that it may be a hardlink) and replace it with an # updated value target_versionfile = os.path.join(base_dir, cfg.versionfile_source) print("UPDATING %s" % target_versionfile) write_to_version_file( target_versionfile, self._versioneer_generated_versions ) cmds["sdist"] = cmd_sdist return cmds CONFIG_ERROR = """ setup.cfg is missing the necessary Versioneer configuration. You need a section like: [versioneer] VCS = git style = pep440 versionfile_source = src/myproject/_version.py versionfile_build = myproject/_version.py tag_prefix = parentdir_prefix = myproject- You will also need to edit your setup.py to use the results: import versioneer setup(version=versioneer.get_version(), cmdclass=versioneer.get_cmdclass(), ...) Please read the docstring in ./versioneer.py for configuration instructions, edit setup.cfg, and re-run the installer or 'python versioneer.py setup'. """ SAMPLE_CONFIG = """ # See the docstring in versioneer.py for instructions. Note that you must # re-run 'versioneer.py setup' after changing this section, and commit the # resulting files. [versioneer] #VCS = git #style = pep440 #versionfile_source = #versionfile_build = #tag_prefix = #parentdir_prefix = """ INIT_PY_SNIPPET = """ from ._version import get_versions __version__ = get_versions()['version'] del get_versions """ def do_setup(): """Main VCS-independent setup function for installing Versioneer.""" root = get_root() try: cfg = get_config_from_root(root) except ( EnvironmentError, configparser.NoSectionError, configparser.NoOptionError, ) as e: if isinstance(e, (EnvironmentError, configparser.NoSectionError)): print("Adding sample versioneer config to setup.cfg", file=sys.stderr) with open(os.path.join(root, "setup.cfg"), "a") as f: f.write(SAMPLE_CONFIG) print(CONFIG_ERROR, file=sys.stderr) return 1 print(" creating %s" % cfg.versionfile_source) with open(cfg.versionfile_source, "w") as f: LONG = LONG_VERSION_PY[cfg.VCS] f.write( LONG % { "DOLLAR": "$", "STYLE": cfg.style, "TAG_PREFIX": cfg.tag_prefix, "PARENTDIR_PREFIX": cfg.parentdir_prefix, "VERSIONFILE_SOURCE": cfg.versionfile_source, } ) ipy = os.path.join(os.path.dirname(cfg.versionfile_source), "__init__.py") if os.path.exists(ipy): try: with open(ipy, "r") as f: old = f.read() except EnvironmentError: old = "" if INIT_PY_SNIPPET not in old: print(" appending to %s" % ipy) with open(ipy, "a") as f: f.write(INIT_PY_SNIPPET) else: print(" %s unmodified" % ipy) else: print(" %s doesn't exist, ok" % ipy) ipy = None # Make sure both the top-level "versioneer.py" and versionfile_source # (PKG/_version.py, used by runtime code) are in MANIFEST.in, so # they'll be copied into source distributions. Pip won't be able to # install the package without this. manifest_in = os.path.join(root, "MANIFEST.in") simple_includes = set() try: with open(manifest_in, "r") as f: for line in f: if line.startswith("include "): for include in line.split()[1:]: simple_includes.add(include) except EnvironmentError: pass # That doesn't cover everything MANIFEST.in can do # (http://docs.python.org/2/distutils/sourcedist.html#commands), so # it might give some false negatives. Appending redundant 'include' # lines is safe, though. if "versioneer.py" not in simple_includes: print(" appending 'versioneer.py' to MANIFEST.in") with open(manifest_in, "a") as f: f.write("include versioneer.py\n") else: print(" 'versioneer.py' already in MANIFEST.in") if cfg.versionfile_source not in simple_includes: print( " appending versionfile_source ('%s') to MANIFEST.in" % cfg.versionfile_source ) with open(manifest_in, "a") as f: f.write("include %s\n" % cfg.versionfile_source) else: print(" versionfile_source already in MANIFEST.in") # Make VCS-specific changes. For git, this means creating/changing # .gitattributes to mark _version.py for export-subst keyword # substitution. do_vcs_install(manifest_in, cfg.versionfile_source, ipy) return 0 def scan_setup_py(): """Validate the contents of setup.py against Versioneer's expectations.""" found = set() setters = False errors = 0 with open("setup.py", "r") as f: for line in f.readlines(): if "import versioneer" in line: found.add("import") if "versioneer.get_cmdclass()" in line: found.add("cmdclass") if "versioneer.get_version()" in line: found.add("get_version") if "versioneer.VCS" in line: setters = True if "versioneer.versionfile_source" in line: setters = True if len(found) != 3: print("") print("Your setup.py appears to be missing some important items") print("(but I might be wrong). Please make sure it has something") print("roughly like the following:") print("") print(" import versioneer") print(" setup( version=versioneer.get_version(),") print(" cmdclass=versioneer.get_cmdclass(), ...)") print("") errors += 1 if setters: print("You should remove lines like 'versioneer.VCS = ' and") print("'versioneer.versionfile_source = ' . This configuration") print("now lives in setup.cfg, and should be removed from setup.py") print("") errors += 1 return errors if __name__ == "__main__": cmd = sys.argv[1] if cmd == "setup": errors = do_setup() errors += scan_setup_py() if errors: sys.exit(1) plotly-4.4.1+dfsg.orig/_plotly_utils/0000755000175000017500000000000013573746613017172 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/_plotly_utils/colors/0000755000175000017500000000000013573746613020473 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/_plotly_utils/colors/plotlyjs.py0000644000175000017500000001341513573717677022741 0ustar noahfxnoahfx# Copied from # https://github.com/plotly/plotly.js/blob/master/src/components/colorscale/scales.js _plotlyjs_scales = { "Greys": [[0, "rgb(0,0,0)"], [1, "rgb(255,255,255)"]], "YlGnBu": [ [0, "rgb(8,29,88)"], [0.125, "rgb(37,52,148)"], [0.25, "rgb(34,94,168)"], [0.375, "rgb(29,145,192)"], [0.5, "rgb(65,182,196)"], [0.625, "rgb(127,205,187)"], [0.75, "rgb(199,233,180)"], [0.875, "rgb(237,248,217)"], [1, "rgb(255,255,217)"], ], "Greens": [ [0, "rgb(0,68,27)"], [0.125, "rgb(0,109,44)"], [0.25, "rgb(35,139,69)"], [0.375, "rgb(65,171,93)"], [0.5, "rgb(116,196,118)"], [0.625, "rgb(161,217,155)"], [0.75, "rgb(199,233,192)"], [0.875, "rgb(229,245,224)"], [1, "rgb(247,252,245)"], ], "YlOrRd": [ [0, "rgb(128,0,38)"], [0.125, "rgb(189,0,38)"], [0.25, "rgb(227,26,28)"], [0.375, "rgb(252,78,42)"], [0.5, "rgb(253,141,60)"], [0.625, "rgb(254,178,76)"], [0.75, "rgb(254,217,118)"], [0.875, "rgb(255,237,160)"], [1, "rgb(255,255,204)"], ], "Bluered": [[0, "rgb(0,0,255)"], [1, "rgb(255,0,0)"]], # modified RdBu based on # http:#www.kennethmoreland.com/color-maps/ "RdBu": [ [0, "rgb(5,10,172)"], [0.35, "rgb(106,137,247)"], [0.5, "rgb(190,190,190)"], [0.6, "rgb(220,170,132)"], [0.7, "rgb(230,145,90)"], [1, "rgb(178,10,28)"], ], # Scale for non-negative numeric values "Reds": [ [0, "rgb(220,220,220)"], [0.2, "rgb(245,195,157)"], [0.4, "rgb(245,160,105)"], [1, "rgb(178,10,28)"], ], # Scale for non-positive numeric values "Blues": [ [0, "rgb(5,10,172)"], [0.35, "rgb(40,60,190)"], [0.5, "rgb(70,100,245)"], [0.6, "rgb(90,120,245)"], [0.7, "rgb(106,137,247)"], [1, "rgb(220,220,220)"], ], "Picnic": [ [0, "rgb(0,0,255)"], [0.1, "rgb(51,153,255)"], [0.2, "rgb(102,204,255)"], [0.3, "rgb(153,204,255)"], [0.4, "rgb(204,204,255)"], [0.5, "rgb(255,255,255)"], [0.6, "rgb(255,204,255)"], [0.7, "rgb(255,153,255)"], [0.8, "rgb(255,102,204)"], [0.9, "rgb(255,102,102)"], [1, "rgb(255,0,0)"], ], "Rainbow": [ [0, "rgb(150,0,90)"], [0.125, "rgb(0,0,200)"], [0.25, "rgb(0,25,255)"], [0.375, "rgb(0,152,255)"], [0.5, "rgb(44,255,150)"], [0.625, "rgb(151,255,0)"], [0.75, "rgb(255,234,0)"], [0.875, "rgb(255,111,0)"], [1, "rgb(255,0,0)"], ], "Portland": [ [0, "rgb(12,51,131)"], [0.25, "rgb(10,136,186)"], [0.5, "rgb(242,211,56)"], [0.75, "rgb(242,143,56)"], [1, "rgb(217,30,30)"], ], "Jet": [ [0, "rgb(0,0,131)"], [0.125, "rgb(0,60,170)"], [0.375, "rgb(5,255,255)"], [0.625, "rgb(255,255,0)"], [0.875, "rgb(250,0,0)"], [1, "rgb(128,0,0)"], ], "Hot": [ [0, "rgb(0,0,0)"], [0.3, "rgb(230,0,0)"], [0.6, "rgb(255,210,0)"], [1, "rgb(255,255,255)"], ], "Blackbody": [ [0, "rgb(0,0,0)"], [0.2, "rgb(230,0,0)"], [0.4, "rgb(230,210,0)"], [0.7, "rgb(255,255,255)"], [1, "rgb(160,200,255)"], ], "Earth": [ [0, "rgb(0,0,130)"], [0.1, "rgb(0,180,180)"], [0.2, "rgb(40,210,40)"], [0.4, "rgb(230,230,50)"], [0.6, "rgb(120,70,20)"], [1, "rgb(255,255,255)"], ], "Electric": [ [0, "rgb(0,0,0)"], [0.15, "rgb(30,0,100)"], [0.4, "rgb(120,0,100)"], [0.6, "rgb(160,90,0)"], [0.8, "rgb(230,200,0)"], [1, "rgb(255,250,220)"], ], "Viridis": [ [0, "#440154"], [0.06274509803921569, "#48186a"], [0.12549019607843137, "#472d7b"], [0.18823529411764706, "#424086"], [0.25098039215686274, "#3b528b"], [0.3137254901960784, "#33638d"], [0.3764705882352941, "#2c728e"], [0.4392156862745098, "#26828e"], [0.5019607843137255, "#21918c"], [0.5647058823529412, "#1fa088"], [0.6274509803921569, "#28ae80"], [0.6901960784313725, "#3fbc73"], [0.7529411764705882, "#5ec962"], [0.8156862745098039, "#84d44b"], [0.8784313725490196, "#addc30"], [0.9411764705882353, "#d8e219"], [1, "#fde725"], ], "Cividis": [ [0.000000, "rgb(0,32,76)"], [0.058824, "rgb(0,42,102)"], [0.117647, "rgb(0,52,110)"], [0.176471, "rgb(39,63,108)"], [0.235294, "rgb(60,74,107)"], [0.294118, "rgb(76,85,107)"], [0.352941, "rgb(91,95,109)"], [0.411765, "rgb(104,106,112)"], [0.470588, "rgb(117,117,117)"], [0.529412, "rgb(131,129,120)"], [0.588235, "rgb(146,140,120)"], [0.647059, "rgb(161,152,118)"], [0.705882, "rgb(176,165,114)"], [0.764706, "rgb(192,177,109)"], [0.823529, "rgb(209,191,102)"], [0.882353, "rgb(225,204,92)"], [0.941176, "rgb(243,219,79)"], [1.000000, "rgb(255,233,69)"], ], } # Create variable named after each scale that contains the sequence of colors only for scale_name, scale_pairs in _plotlyjs_scales.items(): scale_sequence = [c[1] for c in scale_pairs] exec( "{scale_name} = {scale_sequence}".format( scale_name=scale_name, scale_sequence=scale_sequence ) ) # Prefix variable names with _ so that they will not be added to the swatches _contents = dict(globals()) for _k, _cols in _contents.items(): if _k.startswith("_") or _k == "swatches" or _k.endswith("_r"): continue globals()[_k + "_r"] = _cols[::-1] plotly-4.4.1+dfsg.orig/_plotly_utils/colors/cmocean.py0000644000175000017500000001402213573717677022461 0ustar noahfxnoahfx""" Color scales from the cmocean project Learn more at https://matplotlib.org/cmocean/ cmocean is made available under an MIT license: https://github.com/matplotlib/cmocean/blob/master/LICENSE.txt """ from ._swatches import _swatches def swatches(template=None): return _swatches(__name__, globals(), template) swatches.__doc__ = _swatches.__doc__ turbid = [ "rgb(232, 245, 171)", "rgb(220, 219, 137)", "rgb(209, 193, 107)", "rgb(199, 168, 83)", "rgb(186, 143, 66)", "rgb(170, 121, 60)", "rgb(151, 103, 58)", "rgb(129, 87, 56)", "rgb(104, 72, 53)", "rgb(80, 59, 46)", "rgb(57, 45, 37)", "rgb(34, 30, 27)", ] thermal = [ "rgb(3, 35, 51)", "rgb(13, 48, 100)", "rgb(53, 50, 155)", "rgb(93, 62, 153)", "rgb(126, 77, 143)", "rgb(158, 89, 135)", "rgb(193, 100, 121)", "rgb(225, 113, 97)", "rgb(246, 139, 69)", "rgb(251, 173, 60)", "rgb(246, 211, 70)", "rgb(231, 250, 90)", ] haline = [ "rgb(41, 24, 107)", "rgb(42, 35, 160)", "rgb(15, 71, 153)", "rgb(18, 95, 142)", "rgb(38, 116, 137)", "rgb(53, 136, 136)", "rgb(65, 157, 133)", "rgb(81, 178, 124)", "rgb(111, 198, 107)", "rgb(160, 214, 91)", "rgb(212, 225, 112)", "rgb(253, 238, 153)", ] solar = [ "rgb(51, 19, 23)", "rgb(79, 28, 33)", "rgb(108, 36, 36)", "rgb(135, 47, 32)", "rgb(157, 66, 25)", "rgb(174, 88, 20)", "rgb(188, 111, 19)", "rgb(199, 137, 22)", "rgb(209, 164, 32)", "rgb(217, 192, 44)", "rgb(222, 222, 59)", "rgb(224, 253, 74)", ] ice = [ "rgb(3, 5, 18)", "rgb(25, 25, 51)", "rgb(44, 42, 87)", "rgb(58, 60, 125)", "rgb(62, 83, 160)", "rgb(62, 109, 178)", "rgb(72, 134, 187)", "rgb(89, 159, 196)", "rgb(114, 184, 205)", "rgb(149, 207, 216)", "rgb(192, 229, 232)", "rgb(234, 252, 253)", ] gray = [ "rgb(0, 0, 0)", "rgb(16, 16, 16)", "rgb(38, 38, 38)", "rgb(59, 59, 59)", "rgb(81, 80, 80)", "rgb(102, 101, 101)", "rgb(124, 123, 122)", "rgb(146, 146, 145)", "rgb(171, 171, 170)", "rgb(197, 197, 195)", "rgb(224, 224, 223)", "rgb(254, 254, 253)", ] oxy = [ "rgb(63, 5, 5)", "rgb(101, 6, 13)", "rgb(138, 17, 9)", "rgb(96, 95, 95)", "rgb(119, 118, 118)", "rgb(142, 141, 141)", "rgb(166, 166, 165)", "rgb(193, 192, 191)", "rgb(222, 222, 220)", "rgb(239, 248, 90)", "rgb(230, 210, 41)", "rgb(220, 174, 25)", ] deep = [ "rgb(253, 253, 204)", "rgb(206, 236, 179)", "rgb(156, 219, 165)", "rgb(111, 201, 163)", "rgb(86, 177, 163)", "rgb(76, 153, 160)", "rgb(68, 130, 155)", "rgb(62, 108, 150)", "rgb(62, 82, 143)", "rgb(64, 60, 115)", "rgb(54, 43, 77)", "rgb(39, 26, 44)", ] dense = [ "rgb(230, 240, 240)", "rgb(191, 221, 229)", "rgb(156, 201, 226)", "rgb(129, 180, 227)", "rgb(115, 154, 228)", "rgb(117, 127, 221)", "rgb(120, 100, 202)", "rgb(119, 74, 175)", "rgb(113, 50, 141)", "rgb(100, 31, 104)", "rgb(80, 20, 66)", "rgb(54, 14, 36)", ] algae = [ "rgb(214, 249, 207)", "rgb(186, 228, 174)", "rgb(156, 209, 143)", "rgb(124, 191, 115)", "rgb(85, 174, 91)", "rgb(37, 157, 81)", "rgb(7, 138, 78)", "rgb(13, 117, 71)", "rgb(23, 95, 61)", "rgb(25, 75, 49)", "rgb(23, 55, 35)", "rgb(17, 36, 20)", ] matter = [ "rgb(253, 237, 176)", "rgb(250, 205, 145)", "rgb(246, 173, 119)", "rgb(240, 142, 98)", "rgb(231, 109, 84)", "rgb(216, 80, 83)", "rgb(195, 56, 90)", "rgb(168, 40, 96)", "rgb(138, 29, 99)", "rgb(107, 24, 93)", "rgb(76, 21, 80)", "rgb(47, 15, 61)", ] speed = [ "rgb(254, 252, 205)", "rgb(239, 225, 156)", "rgb(221, 201, 106)", "rgb(194, 182, 59)", "rgb(157, 167, 21)", "rgb(116, 153, 5)", "rgb(75, 138, 20)", "rgb(35, 121, 36)", "rgb(11, 100, 44)", "rgb(18, 78, 43)", "rgb(25, 56, 34)", "rgb(23, 35, 18)", ] amp = [ "rgb(241, 236, 236)", "rgb(230, 209, 203)", "rgb(221, 182, 170)", "rgb(213, 156, 137)", "rgb(205, 129, 103)", "rgb(196, 102, 73)", "rgb(186, 74, 47)", "rgb(172, 44, 36)", "rgb(149, 19, 39)", "rgb(120, 14, 40)", "rgb(89, 13, 31)", "rgb(60, 9, 17)", ] tempo = [ "rgb(254, 245, 244)", "rgb(222, 224, 210)", "rgb(189, 206, 181)", "rgb(153, 189, 156)", "rgb(110, 173, 138)", "rgb(65, 157, 129)", "rgb(25, 137, 125)", "rgb(18, 116, 117)", "rgb(25, 94, 106)", "rgb(28, 72, 93)", "rgb(25, 51, 80)", "rgb(20, 29, 67)", ] phase = [ "rgb(167, 119, 12)", "rgb(197, 96, 51)", "rgb(217, 67, 96)", "rgb(221, 38, 163)", "rgb(196, 59, 224)", "rgb(153, 97, 244)", "rgb(95, 127, 228)", "rgb(40, 144, 183)", "rgb(15, 151, 136)", "rgb(39, 153, 79)", "rgb(119, 141, 17)", "rgb(167, 119, 12)", ] balance = [ "rgb(23, 28, 66)", "rgb(41, 58, 143)", "rgb(11, 102, 189)", "rgb(69, 144, 185)", "rgb(142, 181, 194)", "rgb(210, 216, 219)", "rgb(230, 210, 204)", "rgb(213, 157, 137)", "rgb(196, 101, 72)", "rgb(172, 43, 36)", "rgb(120, 14, 40)", "rgb(60, 9, 17)", ] delta = [ "rgb(16, 31, 63)", "rgb(38, 62, 144)", "rgb(30, 110, 161)", "rgb(60, 154, 171)", "rgb(140, 193, 186)", "rgb(217, 229, 218)", "rgb(239, 226, 156)", "rgb(195, 182, 59)", "rgb(115, 152, 5)", "rgb(34, 120, 36)", "rgb(18, 78, 43)", "rgb(23, 35, 18)", ] curl = [ "rgb(20, 29, 67)", "rgb(28, 72, 93)", "rgb(18, 115, 117)", "rgb(63, 156, 129)", "rgb(153, 189, 156)", "rgb(223, 225, 211)", "rgb(241, 218, 206)", "rgb(224, 160, 137)", "rgb(203, 101, 99)", "rgb(164, 54, 96)", "rgb(111, 23, 91)", "rgb(51, 13, 53)", ] # Prefix variable names with _ so that they will not be added to the swatches _contents = dict(globals()) for _k, _cols in _contents.items(): if _k.startswith("_") or _k == "swatches" or _k.endswith("_r"): continue globals()[_k + "_r"] = _cols[::-1] plotly-4.4.1+dfsg.orig/_plotly_utils/colors/diverging.py0000644000175000017500000000217713573717677023042 0ustar noahfxnoahfx""" Diverging color scales are appropriate for continuous data that has a natural midpoint \ other otherwise informative special value, such as 0 altitude, or the boiling point of a liquid. The color scales in this module are \ mostly meant to be passed in as the `color_continuous_scale` argument to various \ functions, and to be used with the `color_continuous_midpoint` argument. """ from .colorbrewer import ( # noqa: F401 BrBG, PRGn, PiYG, PuOr, RdBu, RdGy, RdYlBu, RdYlGn, Spectral, ) from .cmocean import balance, delta, curl # noqa: F401 from .carto import Armyrose, Fall, Geyser, Temps, Tealrose, Tropic, Earth # noqa: F401 from .plotlyjs import Picnic, Portland # noqa: F401 from ._swatches import _swatches def swatches(template=None): return _swatches(__name__, globals(), template) swatches.__doc__ = _swatches.__doc__ # Prefix variable names with _ so that they will not be added to the swatches _contents = dict(globals()) for _k, _cols in _contents.items(): if _k.startswith("_") or _k == "swatches" or _k.endswith("_r"): continue globals()[_k + "_r"] = _cols[::-1] plotly-4.4.1+dfsg.orig/_plotly_utils/colors/colorbrewer.py0000644000175000017500000002114213573717677023402 0ustar noahfxnoahfx""" Color scales and sequences from the colorbrewer 2 project Learn more at http://colorbrewer2.org colorbrewer is made available under an Apache license: http://colorbrewer2.org/export/LICENSE.txt """ from ._swatches import _swatches def swatches(template=None): return _swatches(__name__, globals(), template) swatches.__doc__ = _swatches.__doc__ BrBG = [ "rgb(84,48,5)", "rgb(140,81,10)", "rgb(191,129,45)", "rgb(223,194,125)", "rgb(246,232,195)", "rgb(245,245,245)", "rgb(199,234,229)", "rgb(128,205,193)", "rgb(53,151,143)", "rgb(1,102,94)", "rgb(0,60,48)", ] PRGn = [ "rgb(64,0,75)", "rgb(118,42,131)", "rgb(153,112,171)", "rgb(194,165,207)", "rgb(231,212,232)", "rgb(247,247,247)", "rgb(217,240,211)", "rgb(166,219,160)", "rgb(90,174,97)", "rgb(27,120,55)", "rgb(0,68,27)", ] PiYG = [ "rgb(142,1,82)", "rgb(197,27,125)", "rgb(222,119,174)", "rgb(241,182,218)", "rgb(253,224,239)", "rgb(247,247,247)", "rgb(230,245,208)", "rgb(184,225,134)", "rgb(127,188,65)", "rgb(77,146,33)", "rgb(39,100,25)", ] PuOr = [ "rgb(127,59,8)", "rgb(179,88,6)", "rgb(224,130,20)", "rgb(253,184,99)", "rgb(254,224,182)", "rgb(247,247,247)", "rgb(216,218,235)", "rgb(178,171,210)", "rgb(128,115,172)", "rgb(84,39,136)", "rgb(45,0,75)", ] RdBu = [ "rgb(103,0,31)", "rgb(178,24,43)", "rgb(214,96,77)", "rgb(244,165,130)", "rgb(253,219,199)", "rgb(247,247,247)", "rgb(209,229,240)", "rgb(146,197,222)", "rgb(67,147,195)", "rgb(33,102,172)", "rgb(5,48,97)", ] RdGy = [ "rgb(103,0,31)", "rgb(178,24,43)", "rgb(214,96,77)", "rgb(244,165,130)", "rgb(253,219,199)", "rgb(255,255,255)", "rgb(224,224,224)", "rgb(186,186,186)", "rgb(135,135,135)", "rgb(77,77,77)", "rgb(26,26,26)", ] RdYlBu = [ "rgb(165,0,38)", "rgb(215,48,39)", "rgb(244,109,67)", "rgb(253,174,97)", "rgb(254,224,144)", "rgb(255,255,191)", "rgb(224,243,248)", "rgb(171,217,233)", "rgb(116,173,209)", "rgb(69,117,180)", "rgb(49,54,149)", ] RdYlGn = [ "rgb(165,0,38)", "rgb(215,48,39)", "rgb(244,109,67)", "rgb(253,174,97)", "rgb(254,224,139)", "rgb(255,255,191)", "rgb(217,239,139)", "rgb(166,217,106)", "rgb(102,189,99)", "rgb(26,152,80)", "rgb(0,104,55)", ] Spectral = [ "rgb(158,1,66)", "rgb(213,62,79)", "rgb(244,109,67)", "rgb(253,174,97)", "rgb(254,224,139)", "rgb(255,255,191)", "rgb(230,245,152)", "rgb(171,221,164)", "rgb(102,194,165)", "rgb(50,136,189)", "rgb(94,79,162)", ] Set1 = [ "rgb(228,26,28)", "rgb(55,126,184)", "rgb(77,175,74)", "rgb(152,78,163)", "rgb(255,127,0)", "rgb(255,255,51)", "rgb(166,86,40)", "rgb(247,129,191)", "rgb(153,153,153)", ] Pastel1 = [ "rgb(251,180,174)", "rgb(179,205,227)", "rgb(204,235,197)", "rgb(222,203,228)", "rgb(254,217,166)", "rgb(255,255,204)", "rgb(229,216,189)", "rgb(253,218,236)", "rgb(242,242,242)", ] Dark2 = [ "rgb(27,158,119)", "rgb(217,95,2)", "rgb(117,112,179)", "rgb(231,41,138)", "rgb(102,166,30)", "rgb(230,171,2)", "rgb(166,118,29)", "rgb(102,102,102)", ] Set2 = [ "rgb(102,194,165)", "rgb(252,141,98)", "rgb(141,160,203)", "rgb(231,138,195)", "rgb(166,216,84)", "rgb(255,217,47)", "rgb(229,196,148)", "rgb(179,179,179)", ] Pastel2 = [ "rgb(179,226,205)", "rgb(253,205,172)", "rgb(203,213,232)", "rgb(244,202,228)", "rgb(230,245,201)", "rgb(255,242,174)", "rgb(241,226,204)", "rgb(204,204,204)", ] Set3 = [ "rgb(141,211,199)", "rgb(255,255,179)", "rgb(190,186,218)", "rgb(251,128,114)", "rgb(128,177,211)", "rgb(253,180,98)", "rgb(179,222,105)", "rgb(252,205,229)", "rgb(217,217,217)", "rgb(188,128,189)", "rgb(204,235,197)", "rgb(255,237,111)", ] Accent = [ "rgb(127,201,127)", "rgb(190,174,212)", "rgb(253,192,134)", "rgb(255,255,153)", "rgb(56,108,176)", "rgb(240,2,127)", "rgb(191,91,23)", "rgb(102,102,102)", ] Paired = [ "rgb(166,206,227)", "rgb(31,120,180)", "rgb(178,223,138)", "rgb(51,160,44)", "rgb(251,154,153)", "rgb(227,26,28)", "rgb(253,191,111)", "rgb(255,127,0)", "rgb(202,178,214)", "rgb(106,61,154)", "rgb(255,255,153)", "rgb(177,89,40)", ] Blues = [ "rgb(247,251,255)", "rgb(222,235,247)", "rgb(198,219,239)", "rgb(158,202,225)", "rgb(107,174,214)", "rgb(66,146,198)", "rgb(33,113,181)", "rgb(8,81,156)", "rgb(8,48,107)", ] BuGn = [ "rgb(247,252,253)", "rgb(229,245,249)", "rgb(204,236,230)", "rgb(153,216,201)", "rgb(102,194,164)", "rgb(65,174,118)", "rgb(35,139,69)", "rgb(0,109,44)", "rgb(0,68,27)", ] BuPu = [ "rgb(247,252,253)", "rgb(224,236,244)", "rgb(191,211,230)", "rgb(158,188,218)", "rgb(140,150,198)", "rgb(140,107,177)", "rgb(136,65,157)", "rgb(129,15,124)", "rgb(77,0,75)", ] GnBu = [ "rgb(247,252,240)", "rgb(224,243,219)", "rgb(204,235,197)", "rgb(168,221,181)", "rgb(123,204,196)", "rgb(78,179,211)", "rgb(43,140,190)", "rgb(8,104,172)", "rgb(8,64,129)", ] Greens = [ "rgb(247,252,245)", "rgb(229,245,224)", "rgb(199,233,192)", "rgb(161,217,155)", "rgb(116,196,118)", "rgb(65,171,93)", "rgb(35,139,69)", "rgb(0,109,44)", "rgb(0,68,27)", ] Greys = [ "rgb(255,255,255)", "rgb(240,240,240)", "rgb(217,217,217)", "rgb(189,189,189)", "rgb(150,150,150)", "rgb(115,115,115)", "rgb(82,82,82)", "rgb(37,37,37)", "rgb(0,0,0)", ] OrRd = [ "rgb(255,247,236)", "rgb(254,232,200)", "rgb(253,212,158)", "rgb(253,187,132)", "rgb(252,141,89)", "rgb(239,101,72)", "rgb(215,48,31)", "rgb(179,0,0)", "rgb(127,0,0)", ] Oranges = [ "rgb(255,245,235)", "rgb(254,230,206)", "rgb(253,208,162)", "rgb(253,174,107)", "rgb(253,141,60)", "rgb(241,105,19)", "rgb(217,72,1)", "rgb(166,54,3)", "rgb(127,39,4)", ] PuBu = [ "rgb(255,247,251)", "rgb(236,231,242)", "rgb(208,209,230)", "rgb(166,189,219)", "rgb(116,169,207)", "rgb(54,144,192)", "rgb(5,112,176)", "rgb(4,90,141)", "rgb(2,56,88)", ] PuBuGn = [ "rgb(255,247,251)", "rgb(236,226,240)", "rgb(208,209,230)", "rgb(166,189,219)", "rgb(103,169,207)", "rgb(54,144,192)", "rgb(2,129,138)", "rgb(1,108,89)", "rgb(1,70,54)", ] PuRd = [ "rgb(247,244,249)", "rgb(231,225,239)", "rgb(212,185,218)", "rgb(201,148,199)", "rgb(223,101,176)", "rgb(231,41,138)", "rgb(206,18,86)", "rgb(152,0,67)", "rgb(103,0,31)", ] Purples = [ "rgb(252,251,253)", "rgb(239,237,245)", "rgb(218,218,235)", "rgb(188,189,220)", "rgb(158,154,200)", "rgb(128,125,186)", "rgb(106,81,163)", "rgb(84,39,143)", "rgb(63,0,125)", ] RdPu = [ "rgb(255,247,243)", "rgb(253,224,221)", "rgb(252,197,192)", "rgb(250,159,181)", "rgb(247,104,161)", "rgb(221,52,151)", "rgb(174,1,126)", "rgb(122,1,119)", "rgb(73,0,106)", ] Reds = [ "rgb(255,245,240)", "rgb(254,224,210)", "rgb(252,187,161)", "rgb(252,146,114)", "rgb(251,106,74)", "rgb(239,59,44)", "rgb(203,24,29)", "rgb(165,15,21)", "rgb(103,0,13)", ] YlGn = [ "rgb(255,255,229)", "rgb(247,252,185)", "rgb(217,240,163)", "rgb(173,221,142)", "rgb(120,198,121)", "rgb(65,171,93)", "rgb(35,132,67)", "rgb(0,104,55)", "rgb(0,69,41)", ] YlGnBu = [ "rgb(255,255,217)", "rgb(237,248,177)", "rgb(199,233,180)", "rgb(127,205,187)", "rgb(65,182,196)", "rgb(29,145,192)", "rgb(34,94,168)", "rgb(37,52,148)", "rgb(8,29,88)", ] YlOrBr = [ "rgb(255,255,229)", "rgb(255,247,188)", "rgb(254,227,145)", "rgb(254,196,79)", "rgb(254,153,41)", "rgb(236,112,20)", "rgb(204,76,2)", "rgb(153,52,4)", "rgb(102,37,6)", ] YlOrRd = [ "rgb(255,255,204)", "rgb(255,237,160)", "rgb(254,217,118)", "rgb(254,178,76)", "rgb(253,141,60)", "rgb(252,78,42)", "rgb(227,26,28)", "rgb(189,0,38)", "rgb(128,0,38)", ] # Prefix variable names with _ so that they will not be added to the swatches _contents = dict(globals()) for _k, _cols in _contents.items(): if _k.startswith("_") or _k == "swatches" or _k.endswith("_r"): continue globals()[_k + "_r"] = _cols[::-1] plotly-4.4.1+dfsg.orig/_plotly_utils/colors/qualitative.py0000644000175000017500000000513513573717677023411 0ustar noahfxnoahfx""" Qualitative color sequences are appropriate for data that has no natural ordering, such \ as categories, colors, names, countries etc. The color sequences in this module are \ mostly meant to be passed in as the `color_discrete_sequence` argument to various functions. """ from ._swatches import _swatches def swatches(template=None): return _swatches(__name__, globals(), template) swatches.__doc__ = _swatches.__doc__ Plotly = [ "#636EFA", "#EF553B", "#00CC96", "#AB63FA", "#FFA15A", "#19D3F3", "#FF6692", "#B6E880", "#FF97FF", "#FECB52", ] D3 = [ "#1F77B4", "#FF7F0E", "#2CA02C", "#D62728", "#9467BD", "#8C564B", "#E377C2", "#7F7F7F", "#BCBD22", "#17BECF", ] G10 = [ "#3366CC", "#DC3912", "#FF9900", "#109618", "#990099", "#0099C6", "#DD4477", "#66AA00", "#B82E2E", "#316395", ] T10 = [ "#4C78A8", "#F58518", "#E45756", "#72B7B2", "#54A24B", "#EECA3B", "#B279A2", "#FF9DA6", "#9D755D", "#BAB0AC", ] Alphabet = [ "#AA0DFE", "#3283FE", "#85660D", "#782AB6", "#565656", "#1C8356", "#16FF32", "#F7E1A0", "#E2E2E2", "#1CBE4F", "#C4451C", "#DEA0FD", "#FE00FA", "#325A9B", "#FEAF16", "#F8A19F", "#90AD1C", "#F6222E", "#1CFFCE", "#2ED9FF", "#B10DA1", "#C075A6", "#FC1CBF", "#B00068", "#FBE426", "#FA0087", ] Dark24 = [ "#2E91E5", "#E15F99", "#1CA71C", "#FB0D0D", "#DA16FF", "#222A2A", "#B68100", "#750D86", "#EB663B", "#511CFB", "#00A08B", "#FB00D1", "#FC0080", "#B2828D", "#6C7C32", "#778AAE", "#862A16", "#A777F1", "#620042", "#1616A7", "#DA60CA", "#6C4516", "#0D2A63", "#AF0038", ] Light24 = [ "#FD3216", "#00FE35", "#6A76FC", "#FED4C4", "#FE00CE", "#0DF9FF", "#F6F926", "#FF9616", "#479B55", "#EEA6FB", "#DC587D", "#D626FF", "#6E899C", "#00B5F7", "#B68E00", "#C9FBE5", "#FF0092", "#22FFA7", "#E3EE9E", "#86CE00", "#BC7196", "#7E7DCD", "#FC6955", "#E48F72", ] from .colorbrewer import Set1, Pastel1, Dark2, Set2, Pastel2, Set3 # noqa: F401 from .carto import Antique, Bold, Pastel, Prism, Safe, Vivid # noqa: F401 # Prefix variable names with _ so that they will not be added to the swatches _contents = dict(globals()) for _k, _cols in _contents.items(): if _k.startswith("_") or _k == "swatches" or _k.endswith("_r"): continue globals()[_k + "_r"] = _cols[::-1] plotly-4.4.1+dfsg.orig/_plotly_utils/colors/sequential.py0000644000175000017500000000504513573717677023233 0ustar noahfxnoahfx""" Sequential color scales are appropriate for most continuous data, but in some cases it \ can be helpful to use a `plotly_express.colors.diverging` or \ `plotly_express.colors.cyclical` scale instead. The color scales in this module are \ mostly meant to be passed in as the `color_continuous_scale` argument to various functions. """ from ._swatches import _swatches def swatches(template=None): return _swatches(__name__, globals(), template) swatches.__doc__ = _swatches.__doc__ Plotly3 = [ "#0508b8", "#1910d8", "#3c19f0", "#6b1cfb", "#981cfd", "#bf1cfd", "#dd2bfd", "#f246fe", "#fc67fd", "#fe88fc", "#fea5fd", "#febefe", "#fec3fe", ] Viridis = [ "#440154", "#482878", "#3e4989", "#31688e", "#26828e", "#1f9e89", "#35b779", "#6ece58", "#b5de2b", "#fde725", ] Cividis = [ "#00224e", "#123570", "#3b496c", "#575d6d", "#707173", "#8a8678", "#a59c74", "#c3b369", "#e1cc55", "#fee838", ] Inferno = [ "#000004", "#1b0c41", "#4a0c6b", "#781c6d", "#a52c60", "#cf4446", "#ed6925", "#fb9b06", "#f7d13d", "#fcffa4", ] Magma = [ "#000004", "#180f3d", "#440f76", "#721f81", "#9e2f7f", "#cd4071", "#f1605d", "#fd9668", "#feca8d", "#fcfdbf", ] Plasma = [ "#0d0887", "#46039f", "#7201a8", "#9c179e", "#bd3786", "#d8576b", "#ed7953", "#fb9f3a", "#fdca26", "#f0f921", ] from .plotlyjs import Blackbody, Bluered, Electric, Hot, Jet, Rainbow # noqa: F401 from .colorbrewer import ( # noqa: F401 Blues, BuGn, BuPu, GnBu, Greens, Greys, OrRd, Oranges, PuBu, PuBuGn, PuRd, Purples, RdBu, RdPu, Reds, YlGn, YlGnBu, YlOrBr, YlOrRd, ) from .cmocean import ( # noqa: F401 turbid, thermal, haline, solar, ice, gray, deep, dense, algae, matter, speed, amp, tempo, ) from .carto import ( # noqa: F401 Burg, Burgyl, Redor, Oryel, Peach, Pinkyl, Mint, Blugrn, Darkmint, Emrld, Aggrnyl, Bluyl, Teal, Tealgrn, Purp, Purpor, Sunset, Magenta, Sunsetdark, Agsunset, Brwnyl, ) # Prefix variable names with _ so that they will not be added to the swatches _contents = dict(globals()) for _k, _cols in _contents.items(): if _k.startswith("_") or _k == "swatches" or _k.endswith("_r"): continue globals()[_k + "_r"] = _cols[::-1] plotly-4.4.1+dfsg.orig/_plotly_utils/colors/__init__.py0000644000175000017500000006437113573717677022627 0ustar noahfxnoahfx""" colors ===== Functions that manipulate colors and arrays of colors. ----- There are three basic types of color types: rgb, hex and tuple: rgb - An rgb color is a string of the form 'rgb(a,b,c)' where a, b and c are integers between 0 and 255 inclusive. hex - A hex color is a string of the form '#xxxxxx' where each x is a character that belongs to the set [0,1,2,3,4,5,6,7,8,9,a,b,c,d,e,f]. This is just the set of characters used in the hexadecimal numeric system. tuple - A tuple color is a 3-tuple of the form (a,b,c) where a, b and c are floats between 0 and 1 inclusive. ----- Colormaps and Colorscales: A colormap or a colorscale is a correspondence between values - Pythonic objects such as strings and floats - to colors. There are typically two main types of colormaps that exist: numerical and categorical colormaps. Numerical: ---------- Numerical colormaps are used when the coloring column being used takes a spectrum of values or numbers. A classic example from the Plotly library: ``` rainbow_colorscale = [ [0, 'rgb(150,0,90)'], [0.125, 'rgb(0,0,200)'], [0.25, 'rgb(0,25,255)'], [0.375, 'rgb(0,152,255)'], [0.5, 'rgb(44,255,150)'], [0.625, 'rgb(151,255,0)'], [0.75, 'rgb(255,234,0)'], [0.875, 'rgb(255,111,0)'], [1, 'rgb(255,0,0)'] ] ``` Notice that this colorscale is a list of lists with each inner list containing a number and a color. These left hand numbers in the nested lists go from 0 to 1, and they are like pointers tell you when a number is mapped to a specific color. If you have a column of numbers `col_num` that you want to plot, and you know ``` min(col_num) = 0 max(col_num) = 100 ``` then if you pull out the number `12.5` in the list and want to figure out what color the corresponding chart element (bar, scatter plot, etc) is going to be, you'll figure out that proportionally 12.5 to 100 is the same as 0.125 to 1. So, the point will be mapped to 'rgb(0,0,200)'. All other colors between the pinned values in a colorscale are linearly interpolated. Categorical: ------------ Alternatively, a categorical colormap is used to assign a specific value in a color column to a specific color everytime it appears in the dataset. A column of strings in a panadas.dataframe that is chosen to serve as the color index would naturally use a categorical colormap. However, you can choose to use a categorical colormap with a column of numbers. Be careful! If you have a lot of unique numbers in your color column you will end up with a colormap that is massive and may slow down graphing performance. """ from __future__ import absolute_import import decimal from numbers import Number import six from _plotly_utils import exceptions # Built-in qualitative color sequences and sequential, # diverging and cyclical color scales. # # Initially ported over from plotly_express from . import ( # noqa: F401 qualitative, sequential, diverging, cyclical, cmocean, colorbrewer, carto, plotlyjs, ) DEFAULT_PLOTLY_COLORS = [ "rgb(31, 119, 180)", "rgb(255, 127, 14)", "rgb(44, 160, 44)", "rgb(214, 39, 40)", "rgb(148, 103, 189)", "rgb(140, 86, 75)", "rgb(227, 119, 194)", "rgb(127, 127, 127)", "rgb(188, 189, 34)", "rgb(23, 190, 207)", ] PLOTLY_SCALES = { "Greys": [[0, "rgb(0,0,0)"], [1, "rgb(255,255,255)"]], "YlGnBu": [ [0, "rgb(8,29,88)"], [0.125, "rgb(37,52,148)"], [0.25, "rgb(34,94,168)"], [0.375, "rgb(29,145,192)"], [0.5, "rgb(65,182,196)"], [0.625, "rgb(127,205,187)"], [0.75, "rgb(199,233,180)"], [0.875, "rgb(237,248,217)"], [1, "rgb(255,255,217)"], ], "Greens": [ [0, "rgb(0,68,27)"], [0.125, "rgb(0,109,44)"], [0.25, "rgb(35,139,69)"], [0.375, "rgb(65,171,93)"], [0.5, "rgb(116,196,118)"], [0.625, "rgb(161,217,155)"], [0.75, "rgb(199,233,192)"], [0.875, "rgb(229,245,224)"], [1, "rgb(247,252,245)"], ], "YlOrRd": [ [0, "rgb(128,0,38)"], [0.125, "rgb(189,0,38)"], [0.25, "rgb(227,26,28)"], [0.375, "rgb(252,78,42)"], [0.5, "rgb(253,141,60)"], [0.625, "rgb(254,178,76)"], [0.75, "rgb(254,217,118)"], [0.875, "rgb(255,237,160)"], [1, "rgb(255,255,204)"], ], "Bluered": [[0, "rgb(0,0,255)"], [1, "rgb(255,0,0)"]], # modified RdBu based on # www.sandia.gov/~kmorel/documents/ColorMaps/ColorMapsExpanded.pdf "RdBu": [ [0, "rgb(5,10,172)"], [0.35, "rgb(106,137,247)"], [0.5, "rgb(190,190,190)"], [0.6, "rgb(220,170,132)"], [0.7, "rgb(230,145,90)"], [1, "rgb(178,10,28)"], ], # Scale for non-negative numeric values "Reds": [ [0, "rgb(220,220,220)"], [0.2, "rgb(245,195,157)"], [0.4, "rgb(245,160,105)"], [1, "rgb(178,10,28)"], ], # Scale for non-positive numeric values "Blues": [ [0, "rgb(5,10,172)"], [0.35, "rgb(40,60,190)"], [0.5, "rgb(70,100,245)"], [0.6, "rgb(90,120,245)"], [0.7, "rgb(106,137,247)"], [1, "rgb(220,220,220)"], ], "Picnic": [ [0, "rgb(0,0,255)"], [0.1, "rgb(51,153,255)"], [0.2, "rgb(102,204,255)"], [0.3, "rgb(153,204,255)"], [0.4, "rgb(204,204,255)"], [0.5, "rgb(255,255,255)"], [0.6, "rgb(255,204,255)"], [0.7, "rgb(255,153,255)"], [0.8, "rgb(255,102,204)"], [0.9, "rgb(255,102,102)"], [1, "rgb(255,0,0)"], ], "Rainbow": [ [0, "rgb(150,0,90)"], [0.125, "rgb(0,0,200)"], [0.25, "rgb(0,25,255)"], [0.375, "rgb(0,152,255)"], [0.5, "rgb(44,255,150)"], [0.625, "rgb(151,255,0)"], [0.75, "rgb(255,234,0)"], [0.875, "rgb(255,111,0)"], [1, "rgb(255,0,0)"], ], "Portland": [ [0, "rgb(12,51,131)"], [0.25, "rgb(10,136,186)"], [0.5, "rgb(242,211,56)"], [0.75, "rgb(242,143,56)"], [1, "rgb(217,30,30)"], ], "Jet": [ [0, "rgb(0,0,131)"], [0.125, "rgb(0,60,170)"], [0.375, "rgb(5,255,255)"], [0.625, "rgb(255,255,0)"], [0.875, "rgb(250,0,0)"], [1, "rgb(128,0,0)"], ], "Hot": [ [0, "rgb(0,0,0)"], [0.3, "rgb(230,0,0)"], [0.6, "rgb(255,210,0)"], [1, "rgb(255,255,255)"], ], "Blackbody": [ [0, "rgb(0,0,0)"], [0.2, "rgb(230,0,0)"], [0.4, "rgb(230,210,0)"], [0.7, "rgb(255,255,255)"], [1, "rgb(160,200,255)"], ], "Earth": [ [0, "rgb(0,0,130)"], [0.1, "rgb(0,180,180)"], [0.2, "rgb(40,210,40)"], [0.4, "rgb(230,230,50)"], [0.6, "rgb(120,70,20)"], [1, "rgb(255,255,255)"], ], "Electric": [ [0, "rgb(0,0,0)"], [0.15, "rgb(30,0,100)"], [0.4, "rgb(120,0,100)"], [0.6, "rgb(160,90,0)"], [0.8, "rgb(230,200,0)"], [1, "rgb(255,250,220)"], ], "Viridis": [ [0, "#440154"], [0.06274509803921569, "#48186a"], [0.12549019607843137, "#472d7b"], [0.18823529411764706, "#424086"], [0.25098039215686274, "#3b528b"], [0.3137254901960784, "#33638d"], [0.3764705882352941, "#2c728e"], [0.4392156862745098, "#26828e"], [0.5019607843137255, "#21918c"], [0.5647058823529412, "#1fa088"], [0.6274509803921569, "#28ae80"], [0.6901960784313725, "#3fbc73"], [0.7529411764705882, "#5ec962"], [0.8156862745098039, "#84d44b"], [0.8784313725490196, "#addc30"], [0.9411764705882353, "#d8e219"], [1, "#fde725"], ], "Cividis": [ [0.000000, "rgb(0,32,76)"], [0.058824, "rgb(0,42,102)"], [0.117647, "rgb(0,52,110)"], [0.176471, "rgb(39,63,108)"], [0.235294, "rgb(60,74,107)"], [0.294118, "rgb(76,85,107)"], [0.352941, "rgb(91,95,109)"], [0.411765, "rgb(104,106,112)"], [0.470588, "rgb(117,117,117)"], [0.529412, "rgb(131,129,120)"], [0.588235, "rgb(146,140,120)"], [0.647059, "rgb(161,152,118)"], [0.705882, "rgb(176,165,114)"], [0.764706, "rgb(192,177,109)"], [0.823529, "rgb(209,191,102)"], [0.882353, "rgb(225,204,92)"], [0.941176, "rgb(243,219,79)"], [1.000000, "rgb(255,233,69)"], ], } def color_parser(colors, function): """ Takes color(s) and a function and applies the function on the color(s) In particular, this function identifies whether the given color object is an iterable or not and applies the given color-parsing function to the color or iterable of colors. If given an iterable, it will only be able to work with it if all items in the iterable are of the same type - rgb string, hex string or tuple """ if isinstance(colors, str): return function(colors) if isinstance(colors, tuple) and isinstance(colors[0], Number): return function(colors) if hasattr(colors, "__iter__"): if isinstance(colors, tuple): new_color_tuple = tuple(function(item) for item in colors) return new_color_tuple else: new_color_list = [function(item) for item in colors] return new_color_list def validate_colors(colors, colortype="tuple"): """ Validates color(s) and returns a list of color(s) of a specified type """ from numbers import Number if colors is None: colors = DEFAULT_PLOTLY_COLORS if isinstance(colors, str): if colors in PLOTLY_SCALES: colors_list = colorscale_to_colors(PLOTLY_SCALES[colors]) # TODO: fix _gantt.py/_scatter.py so that they can accept the # actual colorscale and not just a list of the first and last # color in the plotly colorscale. In resolving this issue we # will be removing the immediate line below colors = [colors_list[0]] + [colors_list[-1]] elif "rgb" in colors or "#" in colors: colors = [colors] else: raise exceptions.PlotlyError( "If your colors variable is a string, it must be a " "Plotly scale, an rgb color or a hex color." ) elif isinstance(colors, tuple): if isinstance(colors[0], Number): colors = [colors] else: colors = list(colors) # convert color elements in list to tuple color for j, each_color in enumerate(colors): if "rgb" in each_color: each_color = color_parser(each_color, unlabel_rgb) for value in each_color: if value > 255.0: raise exceptions.PlotlyError( "Whoops! The elements in your rgb colors " "tuples cannot exceed 255.0." ) each_color = color_parser(each_color, unconvert_from_RGB_255) colors[j] = each_color if "#" in each_color: each_color = color_parser(each_color, hex_to_rgb) each_color = color_parser(each_color, unconvert_from_RGB_255) colors[j] = each_color if isinstance(each_color, tuple): for value in each_color: if value > 1.0: raise exceptions.PlotlyError( "Whoops! The elements in your colors tuples " "cannot exceed 1.0." ) colors[j] = each_color if colortype == "rgb" and not isinstance(colors, six.string_types): for j, each_color in enumerate(colors): rgb_color = color_parser(each_color, convert_to_RGB_255) colors[j] = color_parser(rgb_color, label_rgb) return colors def validate_colors_dict(colors, colortype="tuple"): """ Validates dictioanry of color(s) """ # validate each color element in the dictionary for key in colors: if "rgb" in colors[key]: colors[key] = color_parser(colors[key], unlabel_rgb) for value in colors[key]: if value > 255.0: raise exceptions.PlotlyError( "Whoops! The elements in your rgb colors " "tuples cannot exceed 255.0." ) colors[key] = color_parser(colors[key], unconvert_from_RGB_255) if "#" in colors[key]: colors[key] = color_parser(colors[key], hex_to_rgb) colors[key] = color_parser(colors[key], unconvert_from_RGB_255) if isinstance(colors[key], tuple): for value in colors[key]: if value > 1.0: raise exceptions.PlotlyError( "Whoops! The elements in your colors tuples " "cannot exceed 1.0." ) if colortype == "rgb": for key in colors: colors[key] = color_parser(colors[key], convert_to_RGB_255) colors[key] = color_parser(colors[key], label_rgb) return colors def convert_colors_to_same_type( colors, colortype="rgb", scale=None, return_default_colors=False, num_of_defualt_colors=2, ): """ Converts color(s) to the specified color type Takes a single color or an iterable of colors, as well as a list of scale values, and outputs a 2-pair of the list of color(s) converted all to an rgb or tuple color type, aswell as the scale as the second element. If colors is a Plotly Scale name, then 'scale' will be forced to the scale from the respective colorscale and the colors in that colorscale will also be coverted to the selected colortype. If colors is None, then there is an option to return portion of the DEFAULT_PLOTLY_COLORS :param (str|tuple|list) colors: either a plotly scale name, an rgb or hex color, a color tuple or a list/tuple of colors :param (list) scale: see docs for validate_scale_values() :rtype (tuple) (colors_list, scale) if scale is None in the function call, then scale will remain None in the returned tuple """ colors_list = [] if colors is None and return_default_colors is True: colors_list = DEFAULT_PLOTLY_COLORS[0:num_of_defualt_colors] if isinstance(colors, str): if colors in PLOTLY_SCALES: colors_list = colorscale_to_colors(PLOTLY_SCALES[colors]) if scale is None: scale = colorscale_to_scale(PLOTLY_SCALES[colors]) elif "rgb" in colors or "#" in colors: colors_list = [colors] elif isinstance(colors, tuple): if isinstance(colors[0], Number): colors_list = [colors] else: colors_list = list(colors) elif isinstance(colors, list): colors_list = colors # validate scale if scale is not None: validate_scale_values(scale) if len(colors_list) != len(scale): raise exceptions.PlotlyError( "Make sure that the length of your scale matches the length " "of your list of colors which is {}.".format(len(colors_list)) ) # convert all colors to rgb for j, each_color in enumerate(colors_list): if "#" in each_color: each_color = color_parser(each_color, hex_to_rgb) each_color = color_parser(each_color, label_rgb) colors_list[j] = each_color elif isinstance(each_color, tuple): each_color = color_parser(each_color, convert_to_RGB_255) each_color = color_parser(each_color, label_rgb) colors_list[j] = each_color if colortype == "rgb": return (colors_list, scale) elif colortype == "tuple": for j, each_color in enumerate(colors_list): each_color = color_parser(each_color, unlabel_rgb) each_color = color_parser(each_color, unconvert_from_RGB_255) colors_list[j] = each_color return (colors_list, scale) else: raise exceptions.PlotlyError( "You must select either rgb or tuple " "for your colortype variable." ) def convert_dict_colors_to_same_type(colors_dict, colortype="rgb"): """ Converts a colors in a dictioanry of colors to the specified color type :param (dict) colors_dict: a dictioanry whose values are single colors """ for key in colors_dict: if "#" in colors_dict[key]: colors_dict[key] = color_parser(colors_dict[key], hex_to_rgb) colors_dict[key] = color_parser(colors_dict[key], label_rgb) elif isinstance(colors_dict[key], tuple): colors_dict[key] = color_parser(colors_dict[key], convert_to_RGB_255) colors_dict[key] = color_parser(colors_dict[key], label_rgb) if colortype == "rgb": return colors_dict elif colortype == "tuple": for key in colors_dict: colors_dict[key] = color_parser(colors_dict[key], unlabel_rgb) colors_dict[key] = color_parser(colors_dict[key], unconvert_from_RGB_255) return colors_dict else: raise exceptions.PlotlyError( "You must select either rgb or tuple " "for your colortype variable." ) def validate_scale_values(scale): """ Validates scale values from a colorscale :param (list) scale: a strictly increasing list of floats that begins with 0 and ends with 1. Its usage derives from a colorscale which is a list of two-lists (a list with two elements) of the form [value, color] which are used to determine how interpolation weighting works between the colors in the colorscale. Therefore scale is just the extraction of these values from the two-lists in order """ if len(scale) < 2: raise exceptions.PlotlyError( "You must input a list of scale values " "that has at least two values." ) if (scale[0] != 0) or (scale[-1] != 1): raise exceptions.PlotlyError( "The first and last number in your scale must be 0.0 and 1.0 " "respectively." ) if not all(x < y for x, y in zip(scale, scale[1:])): raise exceptions.PlotlyError( "'scale' must be a list that contains a strictly increasing " "sequence of numbers." ) def validate_colorscale(colorscale): """Validate the structure, scale values and colors of colorscale.""" if not isinstance(colorscale, list): # TODO Write tests for these exceptions raise exceptions.PlotlyError("A valid colorscale must be a list.") if not all(isinstance(innerlist, list) for innerlist in colorscale): raise exceptions.PlotlyError("A valid colorscale must be a list of lists.") colorscale_colors = colorscale_to_colors(colorscale) scale_values = colorscale_to_scale(colorscale) validate_scale_values(scale_values) validate_colors(colorscale_colors) def make_colorscale(colors, scale=None): """ Makes a colorscale from a list of colors and a scale Takes a list of colors and scales and constructs a colorscale based on the colors in sequential order. If 'scale' is left empty, a linear- interpolated colorscale will be generated. If 'scale' is a specificed list, it must be the same legnth as colors and must contain all floats For documentation regarding to the form of the output, see https://plot.ly/python/reference/#mesh3d-colorscale :param (list) colors: a list of single colors """ colorscale = [] # validate minimum colors length of 2 if len(colors) < 2: raise exceptions.PlotlyError( "You must input a list of colors that " "has at least two colors." ) if scale is None: scale_incr = 1.0 / (len(colors) - 1) return [[i * scale_incr, color] for i, color in enumerate(colors)] else: if len(colors) != len(scale): raise exceptions.PlotlyError( "The length of colors and scale " "must be the same." ) validate_scale_values(scale) colorscale = [list(tup) for tup in zip(scale, colors)] return colorscale def find_intermediate_color(lowcolor, highcolor, intermed, colortype="tuple"): """ Returns the color at a given distance between two colors This function takes two color tuples, where each element is between 0 and 1, along with a value 0 < intermed < 1 and returns a color that is intermed-percent from lowcolor to highcolor. If colortype is set to 'rgb', the function will automatically convert the rgb type to a tuple, find the intermediate color and return it as an rgb color. """ if colortype == "rgb": # convert to tuple color, eg. (1, 0.45, 0.7) lowcolor = unlabel_rgb(lowcolor) highcolor = unlabel_rgb(highcolor) diff_0 = float(highcolor[0] - lowcolor[0]) diff_1 = float(highcolor[1] - lowcolor[1]) diff_2 = float(highcolor[2] - lowcolor[2]) inter_med_tuple = ( lowcolor[0] + intermed * diff_0, lowcolor[1] + intermed * diff_1, lowcolor[2] + intermed * diff_2, ) if colortype == "rgb": # back to an rgb string, e.g. rgb(30, 20, 10) inter_med_rgb = label_rgb(inter_med_tuple) return inter_med_rgb return inter_med_tuple def unconvert_from_RGB_255(colors): """ Return a tuple where each element gets divided by 255 Takes a (list of) color tuple(s) where each element is between 0 and 255. Returns the same tuples where each tuple element is normalized to a value between 0 and 1 """ return (colors[0] / (255.0), colors[1] / (255.0), colors[2] / (255.0)) def convert_to_RGB_255(colors): """ Multiplies each element of a triplet by 255 Each coordinate of the color tuple is rounded to the nearest float and then is turned into an integer. If a number is of the form x.5, then if x is odd, the number rounds up to (x+1). Otherwise, it rounds down to just x. This is the way rounding works in Python 3 and in current statistical analysis to avoid rounding bias :param (list) rgb_components: grabs the three R, G and B values to be returned as computed in the function """ rgb_components = [] for component in colors: rounded_num = decimal.Decimal(str(component * 255.0)).quantize( decimal.Decimal("1"), rounding=decimal.ROUND_HALF_EVEN ) # convert rounded number to an integer from 'Decimal' form rounded_num = int(rounded_num) rgb_components.append(rounded_num) return (rgb_components[0], rgb_components[1], rgb_components[2]) def n_colors(lowcolor, highcolor, n_colors, colortype="tuple"): """ Splits a low and high color into a list of n_colors colors in it Accepts two color tuples and returns a list of n_colors colors which form the intermediate colors between lowcolor and highcolor from linearly interpolating through RGB space. If colortype is 'rgb' the function will return a list of colors in the same form. """ if colortype == "rgb": # convert to tuple lowcolor = unlabel_rgb(lowcolor) highcolor = unlabel_rgb(highcolor) diff_0 = float(highcolor[0] - lowcolor[0]) incr_0 = diff_0 / (n_colors - 1) diff_1 = float(highcolor[1] - lowcolor[1]) incr_1 = diff_1 / (n_colors - 1) diff_2 = float(highcolor[2] - lowcolor[2]) incr_2 = diff_2 / (n_colors - 1) list_of_colors = [] for index in range(n_colors): new_tuple = ( lowcolor[0] + (index * incr_0), lowcolor[1] + (index * incr_1), lowcolor[2] + (index * incr_2), ) list_of_colors.append(new_tuple) if colortype == "rgb": # back to an rgb string list_of_colors = color_parser(list_of_colors, label_rgb) return list_of_colors def label_rgb(colors): """ Takes tuple (a, b, c) and returns an rgb color 'rgb(a, b, c)' """ return "rgb(%s, %s, %s)" % (colors[0], colors[1], colors[2]) def unlabel_rgb(colors): """ Takes rgb color(s) 'rgb(a, b, c)' and returns tuple(s) (a, b, c) This function takes either an 'rgb(a, b, c)' color or a list of such colors and returns the color tuples in tuple(s) (a, b, c) """ str_vals = "" for index in range(len(colors)): try: float(colors[index]) str_vals = str_vals + colors[index] except ValueError: if colors[index] == "," or colors[index] == ".": str_vals = str_vals + colors[index] str_vals = str_vals + "," numbers = [] str_num = "" for char in str_vals: if char != ",": str_num = str_num + char else: numbers.append(float(str_num)) str_num = "" return (numbers[0], numbers[1], numbers[2]) def hex_to_rgb(value): """ Calculates rgb values from a hex color code. :param (string) value: Hex color string :rtype (tuple) (r_value, g_value, b_value): tuple of rgb values """ value = value.lstrip("#") hex_total_length = len(value) rgb_section_length = hex_total_length // 3 return tuple( int(value[i : i + rgb_section_length], 16) for i in range(0, hex_total_length, rgb_section_length) ) def colorscale_to_colors(colorscale): """ Extracts the colors from colorscale as a list """ color_list = [] for item in colorscale: color_list.append(item[1]) return color_list def colorscale_to_scale(colorscale): """ Extracts the interpolation scale values from colorscale as a list """ scale_list = [] for item in colorscale: scale_list.append(item[0]) return scale_list def convert_colorscale_to_rgb(colorscale): """ Converts the colors in a colorscale to rgb colors A colorscale is an array of arrays, each with a numeric value as the first item and a color as the second. This function specifically is converting a colorscale with tuple colors (each coordinate between 0 and 1) into a colorscale with the colors transformed into rgb colors """ for color in colorscale: color[1] = convert_to_RGB_255(color[1]) for color in colorscale: color[1] = label_rgb(color[1]) return colorscale def named_colorscales(): """ Returns lowercased names of built-in continuous colorscales. """ from _plotly_utils.basevalidators import ColorscaleValidator return [c for c in ColorscaleValidator("", "").named_colorscales] plotly-4.4.1+dfsg.orig/_plotly_utils/colors/_swatches.py0000644000175000017500000000306213573717677023036 0ustar noahfxnoahfxdef _swatches(module_names, module_contents, template=None): """ Parameters ---------- template : str or dict or plotly.graph_objects.layout.Template instance The figure template name or definition. Returns ------- fig : graph_objects.Figure containing the displayed image A `Figure` object. This figure demonstrates the color scales and sequences in this module, as stacked bar charts. """ import plotly.graph_objs as go from plotly.express._core import apply_default_cascade args = dict(template=template) apply_default_cascade(args) sequences = [ (k, v) for k, v in module_contents.items() if not (k.startswith("_") or k == "swatches" or k.endswith("_r")) ] return go.Figure( data=[ go.Bar( orientation="h", y=[name] * len(colors), x=[1] * len(colors), customdata=list(range(len(colors))), marker=dict(color=colors), hovertemplate="%{y}[%{customdata}] = %{marker.color}", ) for name, colors in reversed(sequences) ], layout=dict( title="plotly.colors." + module_names.split(".")[-1], barmode="stack", barnorm="fraction", bargap=0.5, showlegend=False, xaxis=dict(range=[-0.02, 1.02], showticklabels=False, showgrid=False), height=max(600, 40 * len(sequences)), template=args["template"], ), ) plotly-4.4.1+dfsg.orig/_plotly_utils/colors/cyclical.py0000644000175000017500000000441313573717677022642 0ustar noahfxnoahfx""" Cyclical color scales are appropriate for continuous data that has a natural cyclical \ structure, such as temporal data (hour of day, day of week, day of year, seasons) or complex numbers or other phase data. """ from ._swatches import _swatches def swatches(template=None): return _swatches(__name__, globals(), template) swatches.__doc__ = _swatches.__doc__ Twilight = [ "#e2d9e2", "#9ebbc9", "#6785be", "#5e43a5", "#421257", "#471340", "#8e2c50", "#ba6657", "#ceac94", "#e2d9e2", ] IceFire = [ "#000000", "#001f4d", "#003786", "#0e58a8", "#217eb8", "#30a4ca", "#54c8df", "#9be4ef", "#e1e9d1", "#f3d573", "#e7b000", "#da8200", "#c65400", "#ac2301", "#820000", "#4c0000", "#040100", ] Edge = [ "#313131", "#3d019d", "#3810dc", "#2d47f9", "#2593ff", "#2adef6", "#60fdfa", "#aefdff", "#f3f3f1", "#fffda9", "#fafd5b", "#f7da29", "#ff8e25", "#f8432d", "#d90d39", "#97023d", "#313131", ] Phase = [ "rgb(167, 119, 12)", "rgb(197, 96, 51)", "rgb(217, 67, 96)", "rgb(221, 38, 163)", "rgb(196, 59, 224)", "rgb(153, 97, 244)", "rgb(95, 127, 228)", "rgb(40, 144, 183)", "rgb(15, 151, 136)", "rgb(39, 153, 79)", "rgb(119, 141, 17)", "rgb(167, 119, 12)", ] HSV = [ "#ff0000", "#ffa700", "#afff00", "#08ff00", "#00ff9f", "#00b7ff", "#0010ff", "#9700ff", "#ff00bf", "#ff0018", ] mrybm = [ "#f884f7", "#f968c4", "#ea4388", "#cf244b", "#b51a15", "#bd4304", "#cc6904", "#d58f04", "#cfaa27", "#a19f62", "#588a93", "#2269c4", "#3e3ef0", "#6b4ef9", "#956bfa", "#cd7dfe", ] mygbm = [ "#ef55f1", "#fb84ce", "#fbafa1", "#fcd471", "#f0ed35", "#c6e516", "#96d310", "#61c10b", "#31ac28", "#439064", "#3d719a", "#284ec8", "#2e21ea", "#6324f5", "#9139fa", "#c543fa", ] # Prefix variable names with _ so that they will not be added to the swatches _contents = dict(globals()) for _k, _cols in _contents.items(): if _k.startswith("_") or _k == "swatches" or _k.endswith("_r"): continue globals()[_k + "_r"] = _cols[::-1] plotly-4.4.1+dfsg.orig/_plotly_utils/colors/carto.py0000644000175000017500000001717013573717677022173 0ustar noahfxnoahfx""" Color sequences and scales from CARTO's CartoColors Learn more at https://github.com/CartoDB/CartoColor CARTOColors are made available under a Creative Commons Attribution license: https://creativecommons.org/licenses/by/3.0/us/ """ from ._swatches import _swatches def swatches(template=None): return _swatches(__name__, globals(), template) swatches.__doc__ = _swatches.__doc__ Burg = [ "rgb(255, 198, 196)", "rgb(244, 163, 168)", "rgb(227, 129, 145)", "rgb(204, 96, 125)", "rgb(173, 70, 108)", "rgb(139, 48, 88)", "rgb(103, 32, 68)", ] Burgyl = [ "rgb(251, 230, 197)", "rgb(245, 186, 152)", "rgb(238, 138, 130)", "rgb(220, 113, 118)", "rgb(200, 88, 108)", "rgb(156, 63, 93)", "rgb(112, 40, 74)", ] Redor = [ "rgb(246, 210, 169)", "rgb(245, 183, 142)", "rgb(241, 156, 124)", "rgb(234, 129, 113)", "rgb(221, 104, 108)", "rgb(202, 82, 104)", "rgb(177, 63, 100)", ] Oryel = [ "rgb(236, 218, 154)", "rgb(239, 196, 126)", "rgb(243, 173, 106)", "rgb(247, 148, 93)", "rgb(249, 123, 87)", "rgb(246, 99, 86)", "rgb(238, 77, 90)", ] Peach = [ "rgb(253, 224, 197)", "rgb(250, 203, 166)", "rgb(248, 181, 139)", "rgb(245, 158, 114)", "rgb(242, 133, 93)", "rgb(239, 106, 76)", "rgb(235, 74, 64)", ] Pinkyl = [ "rgb(254, 246, 181)", "rgb(255, 221, 154)", "rgb(255, 194, 133)", "rgb(255, 166, 121)", "rgb(250, 138, 118)", "rgb(241, 109, 122)", "rgb(225, 83, 131)", ] Mint = [ "rgb(228, 241, 225)", "rgb(180, 217, 204)", "rgb(137, 192, 182)", "rgb(99, 166, 160)", "rgb(68, 140, 138)", "rgb(40, 114, 116)", "rgb(13, 88, 95)", ] Blugrn = [ "rgb(196, 230, 195)", "rgb(150, 210, 164)", "rgb(109, 188, 144)", "rgb(77, 162, 132)", "rgb(54, 135, 122)", "rgb(38, 107, 110)", "rgb(29, 79, 96)", ] Darkmint = [ "rgb(210, 251, 212)", "rgb(165, 219, 194)", "rgb(123, 188, 176)", "rgb(85, 156, 158)", "rgb(58, 124, 137)", "rgb(35, 93, 114)", "rgb(18, 63, 90)", ] Emrld = [ "rgb(211, 242, 163)", "rgb(151, 225, 150)", "rgb(108, 192, 139)", "rgb(76, 155, 130)", "rgb(33, 122, 121)", "rgb(16, 89, 101)", "rgb(7, 64, 80)", ] Aggrnyl = [ "rgb(36, 86, 104)", "rgb(15, 114, 121)", "rgb(13, 143, 129)", "rgb(57, 171, 126)", "rgb(110, 197, 116)", "rgb(169, 220, 103)", "rgb(237, 239, 93)", ] Bluyl = [ "rgb(247, 254, 174)", "rgb(183, 230, 165)", "rgb(124, 203, 162)", "rgb(70, 174, 160)", "rgb(8, 144, 153)", "rgb(0, 113, 139)", "rgb(4, 82, 117)", ] Teal = [ "rgb(209, 238, 234)", "rgb(168, 219, 217)", "rgb(133, 196, 201)", "rgb(104, 171, 184)", "rgb(79, 144, 166)", "rgb(59, 115, 143)", "rgb(42, 86, 116)", ] Tealgrn = [ "rgb(176, 242, 188)", "rgb(137, 232, 172)", "rgb(103, 219, 165)", "rgb(76, 200, 163)", "rgb(56, 178, 163)", "rgb(44, 152, 160)", "rgb(37, 125, 152)", ] Purp = [ "rgb(243, 224, 247)", "rgb(228, 199, 241)", "rgb(209, 175, 232)", "rgb(185, 152, 221)", "rgb(159, 130, 206)", "rgb(130, 109, 186)", "rgb(99, 88, 159)", ] Purpor = [ "rgb(249, 221, 218)", "rgb(242, 185, 196)", "rgb(229, 151, 185)", "rgb(206, 120, 179)", "rgb(173, 95, 173)", "rgb(131, 75, 160)", "rgb(87, 59, 136)", ] Sunset = [ "rgb(243, 231, 155)", "rgb(250, 196, 132)", "rgb(248, 160, 126)", "rgb(235, 127, 134)", "rgb(206, 102, 147)", "rgb(160, 89, 160)", "rgb(92, 83, 165)", ] Magenta = [ "rgb(243, 203, 211)", "rgb(234, 169, 189)", "rgb(221, 136, 172)", "rgb(202, 105, 157)", "rgb(177, 77, 142)", "rgb(145, 53, 125)", "rgb(108, 33, 103)", ] Sunsetdark = [ "rgb(252, 222, 156)", "rgb(250, 164, 118)", "rgb(240, 116, 110)", "rgb(227, 79, 111)", "rgb(220, 57, 119)", "rgb(185, 37, 122)", "rgb(124, 29, 111)", ] Agsunset = [ "rgb(75, 41, 145)", "rgb(135, 44, 162)", "rgb(192, 54, 157)", "rgb(234, 79, 136)", "rgb(250, 120, 118)", "rgb(246, 169, 122)", "rgb(237, 217, 163)", ] Brwnyl = [ "rgb(237, 229, 207)", "rgb(224, 194, 162)", "rgb(211, 156, 131)", "rgb(193, 118, 111)", "rgb(166, 84, 97)", "rgb(129, 55, 83)", "rgb(84, 31, 63)", ] # Diverging schemes Armyrose = [ "rgb(121, 130, 52)", "rgb(163, 173, 98)", "rgb(208, 211, 162)", "rgb(253, 251, 228)", "rgb(240, 198, 195)", "rgb(223, 145, 163)", "rgb(212, 103, 128)", ] Fall = [ "rgb(61, 89, 65)", "rgb(119, 136, 104)", "rgb(181, 185, 145)", "rgb(246, 237, 189)", "rgb(237, 187, 138)", "rgb(222, 138, 90)", "rgb(202, 86, 44)", ] Geyser = [ "rgb(0, 128, 128)", "rgb(112, 164, 148)", "rgb(180, 200, 168)", "rgb(246, 237, 189)", "rgb(237, 187, 138)", "rgb(222, 138, 90)", "rgb(202, 86, 44)", ] Temps = [ "rgb(0, 147, 146)", "rgb(57, 177, 133)", "rgb(156, 203, 134)", "rgb(233, 226, 156)", "rgb(238, 180, 121)", "rgb(232, 132, 113)", "rgb(207, 89, 126)", ] Tealrose = [ "rgb(0, 147, 146)", "rgb(114, 170, 161)", "rgb(177, 199, 179)", "rgb(241, 234, 200)", "rgb(229, 185, 173)", "rgb(217, 137, 148)", "rgb(208, 88, 126)", ] Tropic = [ "rgb(0, 155, 158)", "rgb(66, 183, 185)", "rgb(167, 211, 212)", "rgb(241, 241, 241)", "rgb(228, 193, 217)", "rgb(214, 145, 193)", "rgb(199, 93, 171)", ] Earth = [ "rgb(161, 105, 40)", "rgb(189, 146, 90)", "rgb(214, 189, 141)", "rgb(237, 234, 194)", "rgb(181, 200, 184)", "rgb(121, 167, 172)", "rgb(40, 135, 161)", ] # Qualitative palettes Antique = [ "rgb(133, 92, 117)", "rgb(217, 175, 107)", "rgb(175, 100, 88)", "rgb(115, 111, 76)", "rgb(82, 106, 131)", "rgb(98, 83, 119)", "rgb(104, 133, 92)", "rgb(156, 156, 94)", "rgb(160, 97, 119)", "rgb(140, 120, 93)", "rgb(124, 124, 124)", ] Bold = [ "rgb(127, 60, 141)", "rgb(17, 165, 121)", "rgb(57, 105, 172)", "rgb(242, 183, 1)", "rgb(231, 63, 116)", "rgb(128, 186, 90)", "rgb(230, 131, 16)", "rgb(0, 134, 149)", "rgb(207, 28, 144)", "rgb(249, 123, 114)", "rgb(165, 170, 153)", ] Pastel = [ "rgb(102, 197, 204)", "rgb(246, 207, 113)", "rgb(248, 156, 116)", "rgb(220, 176, 242)", "rgb(135, 197, 95)", "rgb(158, 185, 243)", "rgb(254, 136, 177)", "rgb(201, 219, 116)", "rgb(139, 224, 164)", "rgb(180, 151, 231)", "rgb(179, 179, 179)", ] Prism = [ "rgb(95, 70, 144)", "rgb(29, 105, 150)", "rgb(56, 166, 165)", "rgb(15, 133, 84)", "rgb(115, 175, 72)", "rgb(237, 173, 8)", "rgb(225, 124, 5)", "rgb(204, 80, 62)", "rgb(148, 52, 110)", "rgb(111, 64, 112)", "rgb(102, 102, 102)", ] Safe = [ "rgb(136, 204, 238)", "rgb(204, 102, 119)", "rgb(221, 204, 119)", "rgb(17, 119, 51)", "rgb(51, 34, 136)", "rgb(170, 68, 153)", "rgb(68, 170, 153)", "rgb(153, 153, 51)", "rgb(136, 34, 85)", "rgb(102, 17, 0)", "rgb(136, 136, 136)", ] Vivid = [ "rgb(229, 134, 6)", "rgb(93, 105, 177)", "rgb(82, 188, 163)", "rgb(153, 201, 69)", "rgb(204, 97, 176)", "rgb(36, 121, 108)", "rgb(218, 165, 27)", "rgb(47, 138, 196)", "rgb(118, 78, 159)", "rgb(237, 100, 90)", "rgb(165, 170, 153)", ] # Prefix variable names with _ so that they will not be added to the swatches _contents = dict(globals()) for _k, _cols in _contents.items(): if _k.startswith("_") or _k == "swatches" or _k.endswith("_r"): continue globals()[_k + "_r"] = _cols[::-1] plotly-4.4.1+dfsg.orig/_plotly_utils/exceptions.py0000644000175000017500000000622613525746125021726 0ustar noahfxnoahfxclass PlotlyError(Exception): pass class PlotlyEmptyDataError(PlotlyError): pass class PlotlyGraphObjectError(PlotlyError): def __init__(self, message="", path=(), notes=()): """ General graph object error for validation failures. :param (str|unicode) message: The error message. :param (iterable) path: A path pointing to the error. :param notes: Add additional notes, but keep default exception message. """ self.message = message self.plain_message = message # for backwards compat self.path = list(path) self.notes = notes super(PlotlyGraphObjectError, self).__init__(message) def __str__(self): """This is called by Python to present the error message.""" format_dict = { "message": self.message, "path": "[" + "][".join(repr(k) for k in self.path) + "]", "notes": "\n".join(self.notes), } return "{message}\n\nPath To Error: {path}\n\n{notes}".format(**format_dict) class PlotlyDictKeyError(PlotlyGraphObjectError): def __init__(self, obj, path, notes=()): """See PlotlyGraphObjectError.__init__ for param docs.""" format_dict = {"attribute": path[-1], "object_name": obj._name} message = "'{attribute}' is not allowed in '{object_name}'".format( **format_dict ) notes = [obj.help(return_help=True)] + list(notes) super(PlotlyDictKeyError, self).__init__( message=message, path=path, notes=notes ) class PlotlyDictValueError(PlotlyGraphObjectError): def __init__(self, obj, path, notes=()): """See PlotlyGraphObjectError.__init__ for param docs.""" format_dict = {"attribute": path[-1], "object_name": obj._name} message = "'{attribute}' has invalid value inside '{object_name}'".format( **format_dict ) notes = [obj.help(path[-1], return_help=True)] + list(notes) super(PlotlyDictValueError, self).__init__( message=message, notes=notes, path=path ) class PlotlyListEntryError(PlotlyGraphObjectError): def __init__(self, obj, path, notes=()): """See PlotlyGraphObjectError.__init__ for param docs.""" format_dict = {"index": path[-1], "object_name": obj._name} message = "Invalid entry found in '{object_name}' at index, '{index}'".format( **format_dict ) notes = [obj.help(return_help=True)] + list(notes) super(PlotlyListEntryError, self).__init__( message=message, path=path, notes=notes ) class PlotlyDataTypeError(PlotlyGraphObjectError): def __init__(self, obj, path, notes=()): """See PlotlyGraphObjectError.__init__ for param docs.""" format_dict = {"index": path[-1], "object_name": obj._name} message = "Invalid entry found in '{object_name}' at index, '{index}'".format( **format_dict ) note = "It's invalid because it doesn't contain a valid 'type' value." notes = [note] + list(notes) super(PlotlyDataTypeError, self).__init__( message=message, path=path, notes=notes ) plotly-4.4.1+dfsg.orig/_plotly_utils/basevalidators.py0000644000175000017500000024704513573717702022560 0ustar noahfxnoahfxfrom __future__ import absolute_import import base64 import numbers import textwrap import uuid from importlib import import_module import copy import io from copy import deepcopy import re import sys from six import string_types from _plotly_utils.optional_imports import get_module # back-port of fullmatch from Py3.4+ def fullmatch(regex, string, flags=0): """Emulate python-3.4 re.fullmatch().""" if "pattern" in dir(regex): regex_string = regex.pattern else: regex_string = regex return re.match("(?:" + regex_string + r")\Z", string, flags=flags) # Utility functions # ----------------- def to_scalar_or_list(v): # Handle the case where 'v' is a non-native scalar-like type, # such as numpy.float32. Without this case, the object might be # considered numpy-convertable and therefore promoted to a # 0-dimensional array, but we instead want it converted to a # Python native scalar type ('float' in the example above). # We explicitly check if is has the 'item' method, which conventionally # converts these types to native scalars. np = get_module("numpy") pd = get_module("pandas") if np and np.isscalar(v) and hasattr(v, "item"): return v.item() if isinstance(v, (list, tuple)): return [to_scalar_or_list(e) for e in v] elif np and isinstance(v, np.ndarray): if v.ndim == 0: return v.item() return [to_scalar_or_list(e) for e in v] elif pd and isinstance(v, (pd.Series, pd.Index)): return [to_scalar_or_list(e) for e in v] elif is_numpy_convertable(v): return to_scalar_or_list(np.array(v)) else: return v def copy_to_readonly_numpy_array(v, kind=None, force_numeric=False): """ Convert an array-like value into a read-only numpy array Parameters ---------- v : array like Array like value (list, tuple, numpy array, pandas series, etc.) kind : str or tuple of str If specified, the numpy dtype kind (or kinds) that the array should have, or be converted to if possible. If not specified then let numpy infer the datatype force_numeric : bool If true, raise an exception if the resulting numpy array does not have a numeric dtype (i.e. dtype.kind not in ['u', 'i', 'f']) Returns ------- np.ndarray Numpy array with the 'WRITEABLE' flag set to False """ np = get_module("numpy") pd = get_module("pandas") assert np is not None # ### Process kind ### if not kind: kind = () elif isinstance(kind, string_types): kind = (kind,) first_kind = kind[0] if kind else None # u: unsigned int, i: signed int, f: float numeric_kinds = {"u", "i", "f"} kind_default_dtypes = {"u": "uint32", "i": "int32", "f": "float64", "O": "object"} # Handle pandas Series and Index objects if pd and isinstance(v, (pd.Series, pd.Index)): if v.dtype.kind in numeric_kinds: # Get the numeric numpy array so we use fast path below v = v.values elif v.dtype.kind == "M": # Convert datetime Series/Index to numpy array of datetimes if isinstance(v, pd.Series): v = v.dt.to_pydatetime() else: # DatetimeIndex v = v.to_pydatetime() if not isinstance(v, np.ndarray): # v has its own logic on how to convert itself into a numpy array if is_numpy_convertable(v): return copy_to_readonly_numpy_array( np.array(v), kind=kind, force_numeric=force_numeric ) else: # v is not homogenous array v_list = [to_scalar_or_list(e) for e in v] # Lookup dtype for requested kind, if any dtype = kind_default_dtypes.get(first_kind, None) # construct new array from list new_v = np.array(v_list, order="C", dtype=dtype) elif v.dtype.kind in numeric_kinds: # v is a homogenous numeric array if kind and v.dtype.kind not in kind: # Kind(s) were specified and this array doesn't match # Convert to the default dtype for the first kind dtype = kind_default_dtypes.get(first_kind, None) new_v = np.ascontiguousarray(v.astype(dtype)) else: # Either no kind was requested or requested kind is satisfied new_v = np.ascontiguousarray(v.copy()) else: # v is a non-numeric homogenous array new_v = v.copy() # Handle force numeric param # -------------------------- if force_numeric and new_v.dtype.kind not in numeric_kinds: raise ValueError( "Input value is not numeric and" "force_numeric parameter set to True" ) if "U" not in kind: # Force non-numeric arrays to have object type # -------------------------------------------- # Here we make sure that non-numeric arrays have the object # datatype. This works around cases like np.array([1, 2, '3']) where # numpy converts the integers to strings and returns array of dtype # ' 'x' for anchor-style # enumeration properties self.regex_replacements = [] # Loop over enumeration values # ---------------------------- # Look for regular expressions for v in self.values: if v and isinstance(v, string_types) and v[0] == "/" and v[-1] == "/": # String is a regex with leading and trailing '/' character regex_str = v[1:-1] self.val_regexs.append(re.compile(regex_str)) self.regex_replacements.append( EnumeratedValidator.build_regex_replacement(regex_str) ) else: self.val_regexs.append(None) self.regex_replacements.append(None) def __deepcopy__(self, memodict={}): """ A custom deepcopy method is needed here because compiled regex objects don't support deepcopy """ cls = self.__class__ return cls(self.plotly_name, self.parent_name, values=self.values) @staticmethod def build_regex_replacement(regex_str): # Example: regex_str == r"^y([2-9]|[1-9][0-9]+)?$" # # When we see a regular expression like the one above, we want to # build regular expression replacement params that will remove a # suffix of 1 from the input string ('y1' -> 'y' in this example) # # Why?: Regular expressions like this one are used in enumeration # properties that refer to subplotids (e.g. layout.annotation.xref) # The regular expressions forbid suffixes of 1, like 'x1'. But we # want to accept 'x1' and coerce it into 'x' # # To be cautious, we only perform this conversion for enumerated # values that match the anchor-style regex match = re.match(r"\^(\w)\(\[2\-9\]\|\[1\-9\]\[0\-9\]\+\)\?\$", regex_str) if match: anchor_char = match.group(1) return "^" + anchor_char + "1$", anchor_char else: return None def perform_replacemenet(self, v): """ Return v with any applicable regex replacements applied """ if isinstance(v, string_types): for repl_args in self.regex_replacements: if repl_args: v = re.sub(repl_args[0], repl_args[1], v) return v def description(self): # Separate regular values from regular expressions enum_vals = [] enum_regexs = [] for v, regex in zip(self.values, self.val_regexs): if regex is not None: enum_regexs.append(regex.pattern) else: enum_vals.append(v) desc = """\ The '{name}' property is an enumeration that may be specified as:""".format( name=self.plotly_name ) if enum_vals: enum_vals_str = "\n".join( textwrap.wrap( repr(enum_vals), initial_indent=" " * 12, subsequent_indent=" " * 12, break_on_hyphens=False, ) ) desc = ( desc + """ - One of the following enumeration values: {enum_vals_str}""".format( enum_vals_str=enum_vals_str ) ) if enum_regexs: enum_regexs_str = "\n".join( textwrap.wrap( repr(enum_regexs), initial_indent=" " * 12, subsequent_indent=" " * 12, break_on_hyphens=False, ) ) desc = ( desc + """ - A string that matches one of the following regular expressions: {enum_regexs_str}""".format( enum_regexs_str=enum_regexs_str ) ) if self.array_ok: desc = ( desc + """ - A tuple, list, or one-dimensional numpy array of the above""" ) return desc def in_values(self, e): """ Return whether a value matches one of the enumeration options """ is_str = isinstance(e, string_types) for v, regex in zip(self.values, self.val_regexs): if is_str and regex: in_values = fullmatch(regex, e) is not None # in_values = regex.fullmatch(e) is not None else: in_values = e == v if in_values: return True return False def validate_coerce(self, v): if v is None: # Pass None through pass elif self.array_ok and is_array(v): v_replaced = [self.perform_replacemenet(v_el) for v_el in v] invalid_els = [e for e in v_replaced if (not self.in_values(e))] if invalid_els: self.raise_invalid_elements(invalid_els[:10]) if is_homogeneous_array(v): v = copy_to_readonly_numpy_array(v) else: v = to_scalar_or_list(v) else: v = self.perform_replacemenet(v) if not self.in_values(v): self.raise_invalid_val(v) return v class BooleanValidator(BaseValidator): """ "boolean": { "description": "A boolean (true/false) value.", "requiredOpts": [], "otherOpts": [ "dflt" ] }, """ def __init__(self, plotly_name, parent_name, **kwargs): super(BooleanValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, **kwargs ) def description(self): return """\ The '{plotly_name}' property must be specified as a bool (either True, or False)""".format( plotly_name=self.plotly_name ) def validate_coerce(self, v): if v is None: # Pass None through pass elif not isinstance(v, bool): self.raise_invalid_val(v) return v class SrcValidator(BaseValidator): def __init__(self, plotly_name, parent_name, **kwargs): super(SrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, **kwargs ) self.chart_studio = get_module("chart_studio") def description(self): return """\ The '{plotly_name}' property must be specified as a string or as a plotly.grid_objs.Column object""".format( plotly_name=self.plotly_name ) def validate_coerce(self, v): if v is None: # Pass None through pass elif isinstance(v, string_types): pass elif self.chart_studio and isinstance(v, self.chart_studio.grid_objs.Column): # Convert to id string v = v.id else: self.raise_invalid_val(v) return v class NumberValidator(BaseValidator): """ "number": { "description": "A number or a numeric value (e.g. a number inside a string). When applicable, values greater (less) than `max` (`min`) are coerced to the `dflt`.", "requiredOpts": [], "otherOpts": [ "dflt", "min", "max", "arrayOk" ] }, """ def __init__( self, plotly_name, parent_name, min=None, max=None, array_ok=False, **kwargs ): super(NumberValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, **kwargs ) # Handle min if min is None and max is not None: # Max was specified, so make min -inf self.min_val = float("-inf") else: self.min_val = min # Handle max if max is None and min is not None: # Min was specified, so make min inf self.max_val = float("inf") else: self.max_val = max if min is not None or max is not None: self.has_min_max = True else: self.has_min_max = False self.array_ok = array_ok def description(self): desc = """\ The '{plotly_name}' property is a number and may be specified as:""".format( plotly_name=self.plotly_name ) if not self.has_min_max: desc = ( desc + """ - An int or float""" ) else: desc = ( desc + """ - An int or float in the interval [{min_val}, {max_val}]""".format( min_val=self.min_val, max_val=self.max_val ) ) if self.array_ok: desc = ( desc + """ - A tuple, list, or one-dimensional numpy array of the above""" ) return desc def validate_coerce(self, v): if v is None: # Pass None through pass elif self.array_ok and is_homogeneous_array(v): np = get_module("numpy") try: v_array = copy_to_readonly_numpy_array(v, force_numeric=True) except (ValueError, TypeError, OverflowError): self.raise_invalid_val(v) # Check min/max if self.has_min_max: v_valid = np.logical_and( self.min_val <= v_array, v_array <= self.max_val ) if not np.all(v_valid): # Grab up to the first 10 invalid values v_invalid = np.logical_not(v_valid) some_invalid_els = np.array(v, dtype="object")[v_invalid][ :10 ].tolist() self.raise_invalid_elements(some_invalid_els) v = v_array # Always numeric numpy array elif self.array_ok and is_simple_array(v): # Check numeric invalid_els = [e for e in v if not isinstance(e, numbers.Number)] if invalid_els: self.raise_invalid_elements(invalid_els[:10]) # Check min/max if self.has_min_max: invalid_els = [e for e in v if not (self.min_val <= e <= self.max_val)] if invalid_els: self.raise_invalid_elements(invalid_els[:10]) v = to_scalar_or_list(v) else: # Check numeric if not isinstance(v, numbers.Number): self.raise_invalid_val(v) # Check min/max if self.has_min_max: if not (self.min_val <= v <= self.max_val): self.raise_invalid_val(v) return v class IntegerValidator(BaseValidator): """ "integer": { "description": "An integer or an integer inside a string. When applicable, values greater (less) than `max` (`min`) are coerced to the `dflt`.", "requiredOpts": [], "otherOpts": [ "dflt", "min", "max", "arrayOk" ] }, """ def __init__( self, plotly_name, parent_name, min=None, max=None, array_ok=False, **kwargs ): super(IntegerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, **kwargs ) # Handle min if min is None and max is not None: # Max was specified, so make min -inf self.min_val = -sys.maxsize - 1 else: self.min_val = min # Handle max if max is None and min is not None: # Min was specified, so make min inf self.max_val = sys.maxsize else: self.max_val = max if min is not None or max is not None: self.has_min_max = True else: self.has_min_max = False self.array_ok = array_ok def description(self): desc = """\ The '{plotly_name}' property is a integer and may be specified as:""".format( plotly_name=self.plotly_name ) if not self.has_min_max: desc = ( desc + """ - An int (or float that will be cast to an int)""" ) else: desc = desc + ( """ - An int (or float that will be cast to an int) in the interval [{min_val}, {max_val}]""".format( min_val=self.min_val, max_val=self.max_val ) ) if self.array_ok: desc = ( desc + """ - A tuple, list, or one-dimensional numpy array of the above""" ) return desc def validate_coerce(self, v): if v is None: # Pass None through pass elif self.array_ok and is_homogeneous_array(v): np = get_module("numpy") v_array = copy_to_readonly_numpy_array( v, kind=("i", "u"), force_numeric=True ) if v_array.dtype.kind not in ["i", "u"]: self.raise_invalid_val(v) # Check min/max if self.has_min_max: v_valid = np.logical_and( self.min_val <= v_array, v_array <= self.max_val ) if not np.all(v_valid): # Grab up to the first 10 invalid values v_invalid = np.logical_not(v_valid) some_invalid_els = np.array(v, dtype="object")[v_invalid][ :10 ].tolist() self.raise_invalid_elements(some_invalid_els) v = v_array elif self.array_ok and is_simple_array(v): # Check integer type invalid_els = [e for e in v if not isinstance(e, int)] if invalid_els: self.raise_invalid_elements(invalid_els[:10]) # Check min/max if self.has_min_max: invalid_els = [e for e in v if not (self.min_val <= e <= self.max_val)] if invalid_els: self.raise_invalid_elements(invalid_els[:10]) v = to_scalar_or_list(v) else: # Check int if not isinstance(v, int): # don't let int() cast strings to ints self.raise_invalid_val(v) # Check min/max if self.has_min_max: if not (self.min_val <= v <= self.max_val): self.raise_invalid_val(v) return v class StringValidator(BaseValidator): """ "string": { "description": "A string value. Numbers are converted to strings except for attributes with `strict` set to true.", "requiredOpts": [], "otherOpts": [ "dflt", "noBlank", "strict", "arrayOk", "values" ] }, """ def __init__( self, plotly_name, parent_name, no_blank=False, strict=False, array_ok=False, values=None, **kwargs ): super(StringValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, **kwargs ) self.no_blank = no_blank self.strict = strict self.array_ok = array_ok self.values = values @staticmethod def to_str_or_unicode_or_none(v): """ Convert a value to a string if it's not None, a string, or a unicode (on Python 2). """ if v is None or isinstance(v, string_types): return v else: return str(v) def description(self): desc = """\ The '{plotly_name}' property is a string and must be specified as:""".format( plotly_name=self.plotly_name ) if self.no_blank: desc = ( desc + """ - A non-empty string""" ) elif self.values: valid_str = "\n".join( textwrap.wrap( repr(self.values), initial_indent=" " * 12, subsequent_indent=" " * 12, break_on_hyphens=False, ) ) desc = ( desc + """ - One of the following strings: {valid_str}""".format( valid_str=valid_str ) ) else: desc = ( desc + """ - A string""" ) if not self.strict: desc = ( desc + """ - A number that will be converted to a string""" ) if self.array_ok: desc = ( desc + """ - A tuple, list, or one-dimensional numpy array of the above""" ) return desc def validate_coerce(self, v): if v is None: # Pass None through pass elif self.array_ok and is_array(v): # If strict, make sure all elements are strings. if self.strict: invalid_els = [e for e in v if not isinstance(e, string_types)] if invalid_els: self.raise_invalid_elements(invalid_els) if is_homogeneous_array(v): np = get_module("numpy") # If not strict, let numpy cast elements to strings v = copy_to_readonly_numpy_array(v, kind="U") # Check no_blank if self.no_blank: invalid_els = v[v == ""][:10].tolist() if invalid_els: self.raise_invalid_elements(invalid_els) # Check values if self.values: invalid_inds = np.logical_not(np.isin(v, self.values)) invalid_els = v[invalid_inds][:10].tolist() if invalid_els: self.raise_invalid_elements(invalid_els) elif is_simple_array(v): if not self.strict: v = [StringValidator.to_str_or_unicode_or_none(e) for e in v] # Check no_blank if self.no_blank: invalid_els = [e for e in v if e == ""] if invalid_els: self.raise_invalid_elements(invalid_els) # Check values if self.values: invalid_els = [e for e in v if v not in self.values] if invalid_els: self.raise_invalid_elements(invalid_els) v = to_scalar_or_list(v) else: if self.strict: if not isinstance(v, string_types): self.raise_invalid_val(v) else: if isinstance(v, string_types): pass elif isinstance(v, (int, float)): # Convert value to a string v = str(v) else: self.raise_invalid_val(v) if self.no_blank and len(v) == 0: self.raise_invalid_val(v) if self.values and v not in self.values: self.raise_invalid_val(v) return v class ColorValidator(BaseValidator): """ "color": { "description": "A string describing color. Supported formats: - hex (e.g. '#d3d3d3') - rgb (e.g. 'rgb(255, 0, 0)') - rgba (e.g. 'rgb(255, 0, 0, 0.5)') - hsl (e.g. 'hsl(0, 100%, 50%)') - hsv (e.g. 'hsv(0, 100%, 100%)') - named colors(full list: http://www.w3.org/TR/css3-color/#svg-color)", "requiredOpts": [], "otherOpts": [ "dflt", "arrayOk" ] }, """ re_hex = re.compile(r"#([A-Fa-f0-9]{6}|[A-Fa-f0-9]{3})") re_rgb_etc = re.compile(r"(rgb|hsl|hsv)a?\([\d.]+%?(,[\d.]+%?){2,3}\)") re_ddk = re.compile(r"var\(\-\-.*\)") named_colors = [ "aliceblue", "antiquewhite", "aqua", "aquamarine", "azure", "beige", "bisque", "black", "blanchedalmond", "blue", "blueviolet", "brown", "burlywood", "cadetblue", "chartreuse", "chocolate", "coral", "cornflowerblue", "cornsilk", "crimson", "cyan", "darkblue", "darkcyan", "darkgoldenrod", "darkgray", "darkgrey", "darkgreen", "darkkhaki", "darkmagenta", "darkolivegreen", "darkorange", "darkorchid", "darkred", "darksalmon", "darkseagreen", "darkslateblue", "darkslategray", "darkslategrey", "darkturquoise", "darkviolet", "deeppink", "deepskyblue", "dimgray", "dimgrey", "dodgerblue", "firebrick", "floralwhite", "forestgreen", "fuchsia", "gainsboro", "ghostwhite", "gold", "goldenrod", "gray", "grey", "green", "greenyellow", "honeydew", "hotpink", "indianred", "indigo", "ivory", "khaki", "lavender", "lavenderblush", "lawngreen", "lemonchiffon", "lightblue", "lightcoral", "lightcyan", "lightgoldenrodyellow", "lightgray", "lightgrey", "lightgreen", "lightpink", "lightsalmon", "lightseagreen", "lightskyblue", "lightslategray", "lightslategrey", "lightsteelblue", "lightyellow", "lime", "limegreen", "linen", "magenta", "maroon", "mediumaquamarine", "mediumblue", "mediumorchid", "mediumpurple", "mediumseagreen", "mediumslateblue", "mediumspringgreen", "mediumturquoise", "mediumvioletred", "midnightblue", "mintcream", "mistyrose", "moccasin", "navajowhite", "navy", "oldlace", "olive", "olivedrab", "orange", "orangered", "orchid", "palegoldenrod", "palegreen", "paleturquoise", "palevioletred", "papayawhip", "peachpuff", "peru", "pink", "plum", "powderblue", "purple", "red", "rosybrown", "royalblue", "rebeccapurple", "saddlebrown", "salmon", "sandybrown", "seagreen", "seashell", "sienna", "silver", "skyblue", "slateblue", "slategray", "slategrey", "snow", "springgreen", "steelblue", "tan", "teal", "thistle", "tomato", "turquoise", "violet", "wheat", "white", "whitesmoke", "yellow", "yellowgreen", ] def __init__( self, plotly_name, parent_name, array_ok=False, colorscale_path=None, **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, **kwargs ) self.array_ok = array_ok # colorscale_path is the path to the colorscale associated with this # color property, or None if no such colorscale exists. Only colors # with an associated colorscale may take on numeric values self.colorscale_path = colorscale_path def numbers_allowed(self): return self.colorscale_path is not None def description(self): named_clrs_str = "\n".join( textwrap.wrap( ", ".join(self.named_colors), width=79 - 16, initial_indent=" " * 12, subsequent_indent=" " * 12, ) ) valid_color_description = """\ The '{plotly_name}' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: {clrs}""".format( plotly_name=self.plotly_name, clrs=named_clrs_str ) if self.colorscale_path: valid_color_description = ( valid_color_description + """ - A number that will be interpreted as a color according to {colorscale_path}""".format( colorscale_path=self.colorscale_path ) ) if self.array_ok: valid_color_description = ( valid_color_description + """ - A list or array of any of the above""" ) return valid_color_description def validate_coerce(self, v, should_raise=True): if v is None: # Pass None through pass elif self.array_ok and is_homogeneous_array(v): v = copy_to_readonly_numpy_array(v) if self.numbers_allowed() and v.dtype.kind in ["u", "i", "f"]: # Numbers are allowed and we have an array of numbers. # All good pass else: validated_v = [self.validate_coerce(e, should_raise=False) for e in v] invalid_els = self.find_invalid_els(v, validated_v) if invalid_els and should_raise: self.raise_invalid_elements(invalid_els) # ### Check that elements have valid colors types ### elif self.numbers_allowed() or invalid_els: v = copy_to_readonly_numpy_array(validated_v, kind="O") else: v = copy_to_readonly_numpy_array(validated_v, kind="U") elif self.array_ok and is_simple_array(v): validated_v = [self.validate_coerce(e, should_raise=False) for e in v] invalid_els = self.find_invalid_els(v, validated_v) if invalid_els and should_raise: self.raise_invalid_elements(invalid_els) else: v = validated_v else: # Validate scalar color validated_v = self.vc_scalar(v) if validated_v is None and should_raise: self.raise_invalid_val(v) v = validated_v return v def find_invalid_els(self, orig, validated, invalid_els=None): """ Helper method to find invalid elements in orig array. Elements are invalid if their corresponding element in the validated array is None. This method handles deeply nested list structures """ if invalid_els is None: invalid_els = [] for orig_el, validated_el in zip(orig, validated): if is_array(orig_el): self.find_invalid_els(orig_el, validated_el, invalid_els) else: if validated_el is None: invalid_els.append(orig_el) return invalid_els def vc_scalar(self, v): """ Helper to validate/coerce a scalar color """ return ColorValidator.perform_validate_coerce( v, allow_number=self.numbers_allowed() ) @staticmethod def perform_validate_coerce(v, allow_number=None): """ Validate, coerce, and return a single color value. If input cannot be coerced to a valid color then return None. Parameters ---------- v : number or str Candidate color value allow_number : bool True if numbers are allowed as colors Returns ------- number or str or None """ if isinstance(v, numbers.Number) and allow_number: # If allow_numbers then any number is ok return v elif not isinstance(v, string_types): # If not allow_numbers then value must be a string return None else: # Remove spaces so regexes don't need to bother with them. v_normalized = v.replace(" ", "").lower() # if ColorValidator.re_hex.fullmatch(v_normalized): if fullmatch(ColorValidator.re_hex, v_normalized): # valid hex color (e.g. #f34ab3) return v elif fullmatch(ColorValidator.re_rgb_etc, v_normalized): # elif ColorValidator.re_rgb_etc.fullmatch(v_normalized): # Valid rgb(a), hsl(a), hsv(a) color # (e.g. rgba(10, 234, 200, 50%) return v elif fullmatch(ColorValidator.re_ddk, v_normalized): # Valid var(--*) DDK theme variable, inspired by CSS syntax # (e.g. var(--accent) ) # DDK will crawl & eval var(-- colors for Graph theming return v elif v_normalized in ColorValidator.named_colors: # Valid named color (e.g. 'coral') return v else: # Not a valid color return None class ColorlistValidator(BaseValidator): """ "colorlist": { "description": "A list of colors. Must be an {array} containing valid colors.", "requiredOpts": [], "otherOpts": [ "dflt" ] } """ def __init__(self, plotly_name, parent_name, **kwargs): super(ColorlistValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, **kwargs ) def description(self): return """\ The '{plotly_name}' property is a colorlist that may be specified as a tuple, list, one-dimensional numpy array, or pandas Series of valid color strings""".format( plotly_name=self.plotly_name ) def validate_coerce(self, v): if v is None: # Pass None through pass elif is_array(v): validated_v = [ ColorValidator.perform_validate_coerce(e, allow_number=False) for e in v ] invalid_els = [ el for el, validated_el in zip(v, validated_v) if validated_el is None ] if invalid_els: self.raise_invalid_elements(invalid_els) v = to_scalar_or_list(v) else: self.raise_invalid_val(v) return v class ColorscaleValidator(BaseValidator): """ "colorscale": { "description": "A Plotly colorscale either picked by a name: (any of Greys, YlGnBu, Greens, YlOrRd, Bluered, RdBu, Reds, Blues, Picnic, Rainbow, Portland, Jet, Hot, Blackbody, Earth, Electric, Viridis) customized as an {array} of 2-element {arrays} where the first element is the normalized color level value (starting at *0* and ending at *1*), and the second item is a valid color string.", "requiredOpts": [], "otherOpts": [ "dflt" ] }, """ def __init__(self, plotly_name, parent_name, **kwargs): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, **kwargs ) # named colorscales initialized on first use self._named_colorscales = None @property def named_colorscales(self): if self._named_colorscales is None: import inspect import itertools from plotly import colors colorscale_members = itertools.chain( inspect.getmembers(colors.sequential), inspect.getmembers(colors.diverging), inspect.getmembers(colors.cyclical), ) self._named_colorscales = { c[0].lower(): c[1] for c in colorscale_members if isinstance(c, tuple) and len(c) == 2 and isinstance(c[0], str) and isinstance(c[1], list) and not c[0].endswith("_r") and not c[0].startswith("_") } return self._named_colorscales def description(self): colorscales_str = "\n".join( textwrap.wrap( repr(sorted(list(self.named_colorscales))), initial_indent=" " * 12, subsequent_indent=" " * 13, break_on_hyphens=False, width=80, ) ) desc = """\ The '{plotly_name}' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: {colorscales_str}. Appending '_r' to a named colorscale reverses it. """.format( plotly_name=self.plotly_name, colorscales_str=colorscales_str ) return desc def validate_coerce(self, v): v_valid = False if v is None: v_valid = True elif isinstance(v, string_types): v_lower = v.lower() if v_lower in self.named_colorscales: # Convert to color list v = self.named_colorscales[v_lower] v_valid = True elif v_lower.endswith("_r") and v_lower[:-2] in self.named_colorscales: v = self.named_colorscales[v_lower[:-2]][::-1] v_valid = True # if v_valid: # Convert to list of lists colorscale d = len(v) - 1 v = [[(1.0 * i) / (1.0 * d), x] for i, x in enumerate(v)] elif is_array(v) and len(v) > 0: # If firset element is a string, treat as colorsequence if isinstance(v[0], string_types): invalid_els = [ e for e in v if ColorValidator.perform_validate_coerce(e) is None ] if len(invalid_els) == 0: v_valid = True # Convert to list of lists colorscale d = len(v) - 1 v = [[(1.0 * i) / (1.0 * d), x] for i, x in enumerate(v)] else: invalid_els = [ e for e in v if ( not is_array(e) or len(e) != 2 or not isinstance(e[0], numbers.Number) or not (0 <= e[0] <= 1) or not isinstance(e[1], string_types) or ColorValidator.perform_validate_coerce(e[1]) is None ) ] if len(invalid_els) == 0: v_valid = True # Convert to list of lists v = [ [e[0], ColorValidator.perform_validate_coerce(e[1])] for e in v ] if not v_valid: self.raise_invalid_val(v) return v def present(self, v): # Return-type must be immutable if v is None: return None elif isinstance(v, string_types): return v else: return tuple([tuple(e) for e in v]) class AngleValidator(BaseValidator): """ "angle": { "description": "A number (in degree) between -180 and 180.", "requiredOpts": [], "otherOpts": [ "dflt" ] }, """ def __init__(self, plotly_name, parent_name, **kwargs): super(AngleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, **kwargs ) def description(self): desc = """\ The '{plotly_name}' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). """.format( plotly_name=self.plotly_name ) return desc def validate_coerce(self, v): if v is None: # Pass None through pass elif not isinstance(v, numbers.Number): self.raise_invalid_val(v) else: # Normalize v onto the interval [-180, 180) v = (v + 180) % 360 - 180 return v class SubplotidValidator(BaseValidator): """ "subplotid": { "description": "An id string of a subplot type (given by dflt), optionally followed by an integer >1. e.g. if dflt='geo', we can have 'geo', 'geo2', 'geo3', ...", "requiredOpts": [ "dflt" ], "otherOpts": [ "regex" ] } """ def __init__(self, plotly_name, parent_name, dflt=None, regex=None, **kwargs): if dflt is None and regex is None: raise ValueError("One or both of regex and deflt must be specified") super(SubplotidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, **kwargs ) if dflt is not None: self.base = dflt else: # e.g. regex == '/^y([2-9]|[1-9][0-9]+)?$/' self.base = re.match(r"/\^(\w+)", regex).group(1) self.regex = self.base + r"(\d*)" def description(self): desc = """\ The '{plotly_name}' property is an identifier of a particular subplot, of type '{base}', that may be specified as the string '{base}' optionally followed by an integer >= 1 (e.g. '{base}', '{base}1', '{base}2', '{base}3', etc.) """.format( plotly_name=self.plotly_name, base=self.base ) return desc def validate_coerce(self, v): if v is None: pass elif not isinstance(v, string_types): self.raise_invalid_val(v) else: # match = re.fullmatch(self.regex, v) match = fullmatch(self.regex, v) if not match: is_valid = False else: digit_str = match.group(1) if len(digit_str) > 0 and int(digit_str) == 0: is_valid = False elif len(digit_str) > 0 and int(digit_str) == 1: # Remove 1 suffix (e.g. x1 -> x) v = self.base is_valid = True else: is_valid = True if not is_valid: self.raise_invalid_val(v) return v class FlaglistValidator(BaseValidator): """ "flaglist": { "description": "A string representing a combination of flags (order does not matter here). Combine any of the available `flags` with *+*. (e.g. ('lines+markers')). Values in `extras` cannot be combined.", "requiredOpts": [ "flags" ], "otherOpts": [ "dflt", "extras", "arrayOk" ] }, """ def __init__( self, plotly_name, parent_name, flags, extras=None, array_ok=False, **kwargs ): super(FlaglistValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, **kwargs ) self.flags = flags self.extras = extras if extras is not None else [] self.array_ok = array_ok self.all_flags = self.flags + self.extras def description(self): desc = ( """\ The '{plotly_name}' property is a flaglist and may be specified as a string containing:""" ).format(plotly_name=self.plotly_name) # Flags desc = ( desc + ( """ - Any combination of {flags} joined with '+' characters (e.g. '{eg_flag}')""" ).format(flags=self.flags, eg_flag="+".join(self.flags[:2])) ) # Extras if self.extras: desc = ( desc + ( """ OR exactly one of {extras} (e.g. '{eg_extra}')""" ).format(extras=self.extras, eg_extra=self.extras[-1]) ) if self.array_ok: desc = ( desc + """ - A list or array of the above""" ) return desc def vc_scalar(self, v): if not isinstance(v, string_types): return None # To be generous we accept flags separated on plus ('+'), # or comma (',') split_vals = [e.strip() for e in re.split("[,+]", v)] # Are all flags valid names? all_flags_valid = all([f in self.all_flags for f in split_vals]) # Are any 'extras' flags present? has_extras = any([f in self.extras for f in split_vals]) # For flaglist to be valid all flags must be valid, and if we have # any extras present, there must be only one flag (the single extras # flag) is_valid = all_flags_valid and (not has_extras or len(split_vals) == 1) if is_valid: return "+".join(split_vals) else: return None def validate_coerce(self, v): if v is None: # Pass None through pass elif self.array_ok and is_array(v): # Coerce individual strings validated_v = [self.vc_scalar(e) for e in v] invalid_els = [ el for el, validated_el in zip(v, validated_v) if validated_el is None ] if invalid_els: self.raise_invalid_elements(invalid_els) if is_homogeneous_array(v): v = copy_to_readonly_numpy_array(validated_v, kind="U") else: v = to_scalar_or_list(v) else: validated_v = self.vc_scalar(v) if validated_v is None: self.raise_invalid_val(v) v = validated_v return v class AnyValidator(BaseValidator): """ "any": { "description": "Any type.", "requiredOpts": [], "otherOpts": [ "dflt", "values", "arrayOk" ] }, """ def __init__(self, plotly_name, parent_name, values=None, array_ok=False, **kwargs): super(AnyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, **kwargs ) self.values = values self.array_ok = array_ok def description(self): desc = """\ The '{plotly_name}' property accepts values of any type """.format( plotly_name=self.plotly_name ) return desc def validate_coerce(self, v): if v is None: # Pass None through pass elif self.array_ok and is_homogeneous_array(v): v = copy_to_readonly_numpy_array(v, kind="O") elif self.array_ok and is_simple_array(v): v = to_scalar_or_list(v) return v class InfoArrayValidator(BaseValidator): """ "info_array": { "description": "An {array} of plot information.", "requiredOpts": [ "items" ], "otherOpts": [ "dflt", "freeLength", "dimensions" ] } """ def __init__( self, plotly_name, parent_name, items, free_length=None, dimensions=None, **kwargs ): super(InfoArrayValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, **kwargs ) self.items = items self.dimensions = dimensions if dimensions else 1 self.free_length = free_length # Instantiate validators for each info array element self.item_validators = [] info_array_items = self.items if isinstance(self.items, list) else [self.items] for i, item in enumerate(info_array_items): element_name = "{name}[{i}]".format(name=plotly_name, i=i) item_validator = InfoArrayValidator.build_validator( item, element_name, parent_name ) self.item_validators.append(item_validator) def description(self): # Cases # 1) self.items is array, self.dimensions is 1 # a) free_length=True # b) free_length=False # 2) self.items is array, self.dimensions is 2 # (requires free_length=True) # 3) self.items is scalar (requires free_length=True) # a) dimensions=1 # b) dimensions=2 # # dimensions can be set to '1-2' to indicate the both are accepted # desc = """\ The '{plotly_name}' property is an info array that may be specified as:\ """.format( plotly_name=self.plotly_name ) if isinstance(self.items, list): # ### Case 1 ### if self.dimensions in (1, "1-2"): upto = " up to" if self.free_length and self.dimensions == 1 else "" desc += """ * a list or tuple of{upto} {N} elements where:\ """.format( upto=upto, N=len(self.item_validators) ) for i, item_validator in enumerate(self.item_validators): el_desc = item_validator.description().strip() desc = ( desc + """ ({i}) {el_desc}""".format( i=i, el_desc=el_desc ) ) # ### Case 2 ### if self.dimensions in ("1-2", 2): assert self.free_length desc += """ * a 2D list where:""" for i, item_validator in enumerate(self.item_validators): # Update name for 2d orig_name = item_validator.plotly_name item_validator.plotly_name = "{name}[i][{i}]".format( name=self.plotly_name, i=i ) el_desc = item_validator.description().strip() desc = ( desc + """ ({i}) {el_desc}""".format( i=i, el_desc=el_desc ) ) item_validator.plotly_name = orig_name else: # ### Case 3 ### assert self.free_length item_validator = self.item_validators[0] orig_name = item_validator.plotly_name if self.dimensions in (1, "1-2"): item_validator.plotly_name = "{name}[i]".format(name=self.plotly_name) el_desc = item_validator.description().strip() desc += """ * a list of elements where: {el_desc} """.format( el_desc=el_desc ) if self.dimensions in ("1-2", 2): item_validator.plotly_name = "{name}[i][j]".format( name=self.plotly_name ) el_desc = item_validator.description().strip() desc += """ * a 2D list where: {el_desc} """.format( el_desc=el_desc ) item_validator.plotly_name = orig_name return desc @staticmethod def build_validator(validator_info, plotly_name, parent_name): datatype = validator_info["valType"] # type: str validator_classname = datatype.title().replace("_", "") + "Validator" validator_class = eval(validator_classname) kwargs = { k: validator_info[k] for k in validator_info if k not in ["valType", "description", "role"] } return validator_class( plotly_name=plotly_name, parent_name=parent_name, **kwargs ) def validate_element_with_indexed_name(self, val, validator, inds): """ Helper to add indexes to a validator's name, call validate_coerce on a value, then restore the original validator name. This makes sure that if a validation error message is raised, the property name the user sees includes the index(es) of the offending element. Parameters ---------- val: A value to be validated validator A validator inds List of one or more non-negative integers that represent the nested index of the value being validated Returns ------- val validated value Raises ------ ValueError if val fails validation """ orig_name = validator.plotly_name new_name = self.plotly_name for i in inds: new_name += "[" + str(i) + "]" validator.plotly_name = new_name try: val = validator.validate_coerce(val) finally: validator.plotly_name = orig_name return val def validate_coerce(self, v): if v is None: # Pass None through return None elif not is_array(v): self.raise_invalid_val(v) # Save off original v value to use in error reporting orig_v = v # Convert everything into nested lists # This way we don't need to worry about nested numpy arrays v = to_scalar_or_list(v) is_v_2d = v and is_array(v[0]) if is_v_2d and self.dimensions in ("1-2", 2): if is_array(self.items): # e.g. 2D list as parcoords.dimensions.constraintrange # check that all items are there for each nested element for i, row in enumerate(v): # Check row length if not is_array(row) or len(row) != len(self.items): self.raise_invalid_val(orig_v[i], [i]) for j, validator in enumerate(self.item_validators): row[j] = self.validate_element_with_indexed_name( v[i][j], validator, [i, j] ) else: # e.g. 2D list as layout.grid.subplots # check that all elements match individual validator validator = self.item_validators[0] for i, row in enumerate(v): if not is_array(row): self.raise_invalid_val(orig_v[i], [i]) for j, el in enumerate(row): row[j] = self.validate_element_with_indexed_name( el, validator, [i, j] ) elif v and self.dimensions == 2: # e.g. 1D list passed as layout.grid.subplots self.raise_invalid_val(orig_v[0], [0]) elif not is_array(self.items): # e.g. 1D list passed as layout.grid.xaxes validator = self.item_validators[0] for i, el in enumerate(v): v[i] = self.validate_element_with_indexed_name(el, validator, [i]) elif not self.free_length and len(v) != len(self.item_validators): # e.g. 3 element list as layout.xaxis.range self.raise_invalid_val(orig_v) elif self.free_length and len(v) > len(self.item_validators): # e.g. 4 element list as layout.updatemenu.button.args self.raise_invalid_val(orig_v) else: # We have a 1D array of the correct length for i, (el, validator) in enumerate(zip(v, self.item_validators)): # Validate coerce elements v[i] = validator.validate_coerce(el) return v def present(self, v): if v is None: return None else: if ( self.dimensions == 2 or self.dimensions == "1-2" and v and is_array(v[0]) ): # 2D case v = copy.deepcopy(v) for row in v: for i, (el, validator) in enumerate(zip(row, self.item_validators)): row[i] = validator.present(el) return tuple(tuple(row) for row in v) else: # 1D case v = copy.copy(v) # Call present on each of the item validators for i, (el, validator) in enumerate(zip(v, self.item_validators)): # Validate coerce elements v[i] = validator.present(el) # Return tuple form of return tuple(v) class LiteralValidator(BaseValidator): """ Validator for readonly literal values """ def __init__(self, plotly_name, parent_name, val, **kwargs): super(LiteralValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, **kwargs ) self.val = val def validate_coerce(self, v): if v != self.val: raise ValueError( """\ The '{plotly_name}' property of {parent_name} is read-only""".format( plotly_name=self.plotly_name, parent_name=self.parent_name ) ) else: return v class DashValidator(EnumeratedValidator): """ Special case validator for handling dash properties that may be specified as lists of dash lengths. These are not currently specified in the schema. "dash": { "valType": "string", "values": [ "solid", "dot", "dash", "longdash", "dashdot", "longdashdot" ], "dflt": "solid", "role": "style", "editType": "style", "description": "Sets the dash style of lines. Set to a dash type string (*solid*, *dot*, *dash*, *longdash*, *dashdot*, or *longdashdot*) or a dash length list in px (eg *5px,10px,2px,2px*)." }, """ def __init__(self, plotly_name, parent_name, values, **kwargs): # Add regex to handle dash length lists dash_list_regex = r"/^\d+(\.\d+)?(px|%)?((,|\s)\s*\d+(\.\d+)?(px|%)?)*$/" values = values + [dash_list_regex] # Call EnumeratedValidator superclass super(DashValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, values=values, **kwargs ) def description(self): # Separate regular values from regular expressions enum_vals = [] enum_regexs = [] for v, regex in zip(self.values, self.val_regexs): if regex is not None: enum_regexs.append(regex.pattern) else: enum_vals.append(v) desc = """\ The '{name}' property is an enumeration that may be specified as:""".format( name=self.plotly_name ) if enum_vals: enum_vals_str = "\n".join( textwrap.wrap( repr(enum_vals), initial_indent=" " * 12, subsequent_indent=" " * 12, break_on_hyphens=False, width=80, ) ) desc = ( desc + """ - One of the following dash styles: {enum_vals_str}""".format( enum_vals_str=enum_vals_str ) ) desc = ( desc + """ - A string containing a dash length list in pixels or percentages (e.g. '5px 10px 2px 2px', '5, 10, 2, 2', '10% 20% 40%', etc.) """ ) return desc class ImageUriValidator(BaseValidator): _PIL = None try: _PIL = import_module("PIL") except ImportError: pass def __init__(self, plotly_name, parent_name, **kwargs): super(ImageUriValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, **kwargs ) def description(self): desc = """\ The '{plotly_name}' property is an image URI that may be specified as: - A remote image URI string (e.g. 'http://www.somewhere.com/image.png') - A data URI image string (e.g. 'data:image/png;base64,iVBORw0KGgoAAAANSU') - A PIL.Image.Image object which will be immediately converted to a data URI image string See http://pillow.readthedocs.io/en/latest/reference/Image.html """.format( plotly_name=self.plotly_name ) return desc def validate_coerce(self, v): if v is None: pass elif isinstance(v, string_types): # Future possibilities: # - Detect filesystem system paths and convert to URI # - Validate either url or data uri pass elif self._PIL and isinstance(v, self._PIL.Image.Image): # Convert PIL image to png data uri string v = self.pil_image_to_uri(v) else: self.raise_invalid_val(v) return v @staticmethod def pil_image_to_uri(v): in_mem_file = io.BytesIO() v.save(in_mem_file, format="PNG") in_mem_file.seek(0) img_bytes = in_mem_file.read() base64_encoded_result_bytes = base64.b64encode(img_bytes) base64_encoded_result_str = base64_encoded_result_bytes.decode("ascii") v = "data:image/png;base64,{base64_encoded_result_str}".format( base64_encoded_result_str=base64_encoded_result_str ) return v class CompoundValidator(BaseValidator): def __init__(self, plotly_name, parent_name, data_class_str, data_docs, **kwargs): super(CompoundValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, **kwargs ) # Save element class string self.data_class_str = data_class_str self._data_class = None self.data_docs = data_docs self.module_str = CompoundValidator.compute_graph_obj_module_str( self.data_class_str, parent_name ) @staticmethod def compute_graph_obj_module_str(data_class_str, parent_name): if parent_name == "frame" and data_class_str in ["Data", "Layout"]: # Special case. There are no graph_objs.frame.Data or # graph_objs.frame.Layout classes. These are remapped to # graph_objs.Data and graph_objs.Layout parent_parts = parent_name.split(".") module_str = ".".join(["plotly.graph_objs"] + parent_parts[1:]) elif parent_name == "layout.template" and data_class_str == "Layout": # Remap template's layout to regular layout module_str = "plotly.graph_objs" elif "layout.template.data" in parent_name: # Remap template's traces to regular traces parent_name = parent_name.replace("layout.template.data.", "") if parent_name: module_str = "plotly.graph_objs." + parent_name else: module_str = "plotly.graph_objs" elif parent_name: module_str = "plotly.graph_objs." + parent_name else: module_str = "plotly.graph_objs" return module_str @property def data_class(self): if self._data_class is None: module = import_module(self.module_str) self._data_class = getattr(module, self.data_class_str) return self._data_class def description(self): desc = ( """\ The '{plotly_name}' property is an instance of {class_str} that may be specified as: - An instance of {module_str}.{class_str} - A dict of string/value properties that will be passed to the {class_str} constructor Supported dict properties: {constructor_params_str}""" ).format( plotly_name=self.plotly_name, class_str=self.data_class_str, module_str=self.module_str, constructor_params_str=self.data_docs, ) return desc def validate_coerce(self, v, skip_invalid=False): if v is None: v = self.data_class() elif isinstance(v, dict): v = self.data_class(v, skip_invalid=skip_invalid) elif isinstance(v, self.data_class): # Copy object v = self.data_class(v) else: if skip_invalid: v = self.data_class() else: self.raise_invalid_val(v) v._plotly_name = self.plotly_name return v class TitleValidator(CompoundValidator): """ This is a special validator to allow compound title properties (e.g. layout.title, layout.xaxis.title, etc.) to be set as strings or numbers. These strings are mapped to the 'text' property of the compound validator. """ def __init__(self, *args, **kwargs): super(TitleValidator, self).__init__(*args, **kwargs) def validate_coerce(self, v, skip_invalid=False): if isinstance(v, string_types + (int, float)): v = {"text": v} return super(TitleValidator, self).validate_coerce(v, skip_invalid=skip_invalid) class CompoundArrayValidator(BaseValidator): def __init__(self, plotly_name, parent_name, data_class_str, data_docs, **kwargs): super(CompoundArrayValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, **kwargs ) # Save element class string self.data_class_str = data_class_str self._data_class = None self.data_docs = data_docs self.module_str = CompoundValidator.compute_graph_obj_module_str( self.data_class_str, parent_name ) def description(self): desc = ( """\ The '{plotly_name}' property is a tuple of instances of {class_str} that may be specified as: - A list or tuple of instances of {module_str}.{class_str} - A list or tuple of dicts of string/value properties that will be passed to the {class_str} constructor Supported dict properties: {constructor_params_str}""" ).format( plotly_name=self.plotly_name, class_str=self.data_class_str, module_str=self.module_str, constructor_params_str=self.data_docs, ) return desc @property def data_class(self): if self._data_class is None: module = import_module(self.module_str) self._data_class = getattr(module, self.data_class_str) return self._data_class def validate_coerce(self, v, skip_invalid=False): if v is None: v = [] elif isinstance(v, (list, tuple)): res = [] invalid_els = [] for v_el in v: if isinstance(v_el, self.data_class): res.append(self.data_class(v_el)) elif isinstance(v_el, dict): res.append(self.data_class(v_el, skip_invalid=skip_invalid)) else: if skip_invalid: res.append(self.data_class()) else: res.append(None) invalid_els.append(v_el) if invalid_els: self.raise_invalid_elements(invalid_els) v = to_scalar_or_list(res) else: if skip_invalid: v = [] else: self.raise_invalid_val(v) return v class BaseDataValidator(BaseValidator): def __init__( self, class_strs_map, plotly_name, parent_name, set_uid=False, **kwargs ): super(BaseDataValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, **kwargs ) self.class_strs_map = class_strs_map self._class_map = None self.set_uid = set_uid def description(self): trace_types = str(list(self.class_strs_map.keys())) trace_types_wrapped = "\n".join( textwrap.wrap( trace_types, initial_indent=" One of: ", subsequent_indent=" " * 21, width=79 - 12, ) ) desc = ( """\ The '{plotly_name}' property is a tuple of trace instances that may be specified as: - A list or tuple of trace instances (e.g. [Scatter(...), Bar(...)]) - A single trace instance (e.g. Scatter(...), Bar(...), etc.) - A list or tuple of dicts of string/value properties where: - The 'type' property specifies the trace type {trace_types} - All remaining properties are passed to the constructor of the specified trace type (e.g. [{{'type': 'scatter', ...}}, {{'type': 'bar, ...}}])""" ).format(plotly_name=self.plotly_name, trace_types=trace_types_wrapped) return desc @property def class_map(self): if self._class_map is None: # Initialize class map self._class_map = {} # Import trace classes trace_module = import_module("plotly.graph_objs") for k, class_str in self.class_strs_map.items(): self._class_map[k] = getattr(trace_module, class_str) return self._class_map def validate_coerce(self, v, skip_invalid=False): # Import Histogram2dcontour, this is the deprecated name of the # Histogram2dContour trace. from plotly.graph_objs import Histogram2dcontour if v is None: v = [] else: if not isinstance(v, (list, tuple)): v = [v] trace_classes = tuple(self.class_map.values()) res = [] invalid_els = [] for v_el in v: if isinstance(v_el, trace_classes): # Clone input traces v_el = v_el.to_plotly_json() if isinstance(v_el, dict): v_copy = deepcopy(v_el) if "type" in v_copy: trace_type = v_copy.pop("type") elif isinstance(v_el, Histogram2dcontour): trace_type = "histogram2dcontour" else: trace_type = "scatter" if trace_type not in self.class_map: if skip_invalid: # Treat as scatter trace trace = self.class_map["scatter"]( skip_invalid=skip_invalid, **v_copy ) res.append(trace) else: res.append(None) invalid_els.append(v_el) else: trace = self.class_map[trace_type]( skip_invalid=skip_invalid, **v_copy ) res.append(trace) else: if skip_invalid: # Add empty scatter trace trace = self.class_map["scatter"]() res.append(trace) else: res.append(None) invalid_els.append(v_el) if invalid_els: self.raise_invalid_elements(invalid_els) v = to_scalar_or_list(res) # Set new UIDs if self.set_uid: for trace in v: trace.uid = str(uuid.uuid4()) return v class BaseTemplateValidator(CompoundValidator): def __init__(self, plotly_name, parent_name, data_class_str, data_docs, **kwargs): super(BaseTemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=data_class_str, data_docs=data_docs, **kwargs ) def description(self): compound_description = super(BaseTemplateValidator, self).description() compound_description += """ - The name of a registered template where current registered templates are stored in the plotly.io.templates configuration object. The names of all registered templates can be retrieved with: >>> import plotly.io as pio >>> list(pio.templates) # doctest: +ELLIPSIS ['ggplot2', 'seaborn', 'simple_white', 'plotly', 'plotly_white', ...] - A string containing multiple registered template names, joined on '+' characters (e.g. 'template1+template2'). In this case the resulting template is computed by merging together the collection of registered templates""" return compound_description def validate_coerce(self, v, skip_invalid=False): import plotly.io as pio try: # Check if v is a template identifier # (could be any hashable object) if v in pio.templates: return copy.deepcopy(pio.templates[v]) # Otherwise, if v is a string, check to see if it consists of # multiple template names joined on '+' characters elif isinstance(v, string_types): template_names = v.split("+") if all([name in pio.templates for name in template_names]): return pio.templates.merge_templates(*template_names) except TypeError: # v is un-hashable pass # Check for empty template if v == {} or isinstance(v, self.data_class) and v.to_plotly_json() == {}: # Replace empty template with {'data': {'scatter': [{}]}} so that we can # tell the difference between an un-initialized template and a template # explicitly set to empty. return self.data_class(data_scatter=[{}]) return super(BaseTemplateValidator, self).validate_coerce( v, skip_invalid=skip_invalid ) plotly-4.4.1+dfsg.orig/_plotly_utils/__init__.py0000644000175000017500000000000013525746125021264 0ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/_plotly_utils/optional_imports.py0000644000175000017500000000165113532445406023140 0ustar noahfxnoahfx""" Stand-alone module to provide information about whether optional deps exist. """ from __future__ import absolute_import from importlib import import_module import logging import sys logger = logging.getLogger(__name__) _not_importable = set() def get_module(name): """ Return module or None. Absolute import is required. :param (str) name: Dot-separated module path. E.g., 'scipy.stats'. :raise: (ImportError) Only when exc_msg is defined. :return: (module|None) If import succeeds, the module will be returned. """ if name in sys.modules: return sys.modules[name] if name not in _not_importable: try: return import_module(name) except ImportError: _not_importable.add(name) except Exception as e: _not_importable.add(name) msg = "Error importing optional module {}".format(name) logger.exception(msg) plotly-4.4.1+dfsg.orig/_plotly_utils/utils.py0000644000175000017500000001671413573745627020721 0ustar noahfxnoahfximport decimal import json as _json import sys import re from _plotly_utils.optional_imports import get_module from _plotly_utils.basevalidators import ImageUriValidator PY36_OR_LATER = sys.version_info.major == 3 and sys.version_info.minor >= 6 class PlotlyJSONEncoder(_json.JSONEncoder): """ Meant to be passed as the `cls` kwarg to json.dumps(obj, cls=..) See PlotlyJSONEncoder.default for more implementation information. Additionally, this encoder overrides nan functionality so that 'Inf', 'NaN' and '-Inf' encode to 'null'. Which is stricter JSON than the Python version. """ def coerce_to_strict(self, const): """ This is used to ultimately *encode* into strict JSON, see `encode` """ # before python 2.7, 'true', 'false', 'null', were include here. if const in ("Infinity", "-Infinity", "NaN"): return None else: return const def encode(self, o): """ Load and then dump the result using parse_constant kwarg Note that setting invalid separators will cause a failure at this step. """ # this will raise errors in a normal-expected way encoded_o = super(PlotlyJSONEncoder, self).encode(o) # now: # 1. `loads` to switch Infinity, -Infinity, NaN to None # 2. `dumps` again so you get 'null' instead of extended JSON try: new_o = _json.loads(encoded_o, parse_constant=self.coerce_to_strict) except ValueError: # invalid separators will fail here. raise a helpful exception raise ValueError( "Encoding into strict JSON failed. Did you set the separators " "valid JSON separators?" ) else: return _json.dumps( new_o, sort_keys=self.sort_keys, indent=self.indent, separators=(self.item_separator, self.key_separator), ) def default(self, obj): """ Accept an object (of unknown type) and try to encode with priority: 1. builtin: user-defined objects 2. sage: sage math cloud 3. pandas: dataframes/series 4. numpy: ndarrays 5. datetime: time/datetime objects Each method throws a NotEncoded exception if it fails. The default method will only get hit if the object is not a type that is naturally encoded by json: Normal objects: dict object list, tuple array str, unicode string int, long, float number True true False false None null Extended objects: float('nan') 'NaN' float('infinity') 'Infinity' float('-infinity') '-Infinity' Therefore, we only anticipate either unknown iterables or values here. """ # TODO: The ordering if these methods is *very* important. Is this OK? encoding_methods = ( self.encode_as_plotly, self.encode_as_sage, self.encode_as_numpy, self.encode_as_pandas, self.encode_as_datetime, self.encode_as_date, self.encode_as_list, # because some values have `tolist` do last. self.encode_as_decimal, self.encode_as_pil, ) for encoding_method in encoding_methods: try: return encoding_method(obj) except NotEncodable: pass return _json.JSONEncoder.default(self, obj) @staticmethod def encode_as_plotly(obj): """Attempt to use a builtin `to_plotly_json` method.""" try: return obj.to_plotly_json() except AttributeError: raise NotEncodable @staticmethod def encode_as_list(obj): """Attempt to use `tolist` method to convert to normal Python list.""" if hasattr(obj, "tolist"): return obj.tolist() else: raise NotEncodable @staticmethod def encode_as_sage(obj): """Attempt to convert sage.all.RR to floats and sage.all.ZZ to ints""" sage_all = get_module("sage.all") if not sage_all: raise NotEncodable if obj in sage_all.RR: return float(obj) elif obj in sage_all.ZZ: return int(obj) else: raise NotEncodable @staticmethod def encode_as_pandas(obj): """Attempt to convert pandas.NaT""" pandas = get_module("pandas") if not pandas: raise NotEncodable if obj is pandas.NaT: return None else: raise NotEncodable @staticmethod def encode_as_numpy(obj): """Attempt to convert numpy.ma.core.masked""" numpy = get_module("numpy") if not numpy: raise NotEncodable if obj is numpy.ma.core.masked: return float("nan") else: raise NotEncodable @staticmethod def encode_as_datetime(obj): """Convert datetime objects to iso-format strings""" try: return obj.isoformat() except AttributeError: raise NotEncodable @staticmethod def encode_as_date(obj): """Attempt to convert to utc-iso time string using date methods.""" try: time_string = obj.isoformat() except AttributeError: raise NotEncodable else: return iso_to_plotly_time_string(time_string) @staticmethod def encode_as_decimal(obj): """Attempt to encode decimal by converting it to float""" if isinstance(obj, decimal.Decimal): return float(obj) else: raise NotEncodable @staticmethod def encode_as_pil(obj): """Attempt to convert PIL.Image.Image to base64 data uri""" image = get_module("PIL.Image") if image is not None and isinstance(obj, image.Image): return ImageUriValidator.pil_image_to_uri(obj) else: raise NotEncodable class NotEncodable(Exception): pass def iso_to_plotly_time_string(iso_string): """Remove timezone info and replace 'T' delimeter with ' ' (ws).""" # make sure we don't send timezone info to plotly if (iso_string.split("-")[:3] is "00:00") or (iso_string.split("+")[0] is "00:00"): raise Exception( "Plotly won't accept timestrings with timezone info.\n" "All timestrings are assumed to be in UTC." ) iso_string = iso_string.replace("-00:00", "").replace("+00:00", "") if iso_string.endswith("T00:00:00"): return iso_string.replace("T00:00:00", "") else: return iso_string.replace("T", " ") def template_doc(**names): def _decorator(func): if sys.version[:3] != "3.2": if func.__doc__ is not None: func.__doc__ = func.__doc__.format(**names) return func return _decorator def _natural_sort_strings(vals, reverse=False): def key(v): v_parts = re.split(r"(\d+)", v) for i in range(len(v_parts)): try: v_parts[i] = int(v_parts[i]) except ValueError: # not an int pass return tuple(v_parts) return sorted(vals, key=key, reverse=reverse) plotly-4.4.1+dfsg.orig/_plotly_utils/files.py0000644000175000017500000000163213525746125020643 0ustar noahfxnoahfximport os PLOTLY_DIR = os.environ.get( "PLOTLY_DIR", os.path.join(os.path.expanduser("~"), ".plotly") ) TEST_FILE = os.path.join(PLOTLY_DIR, ".permission_test") def _permissions(): try: if not os.path.exists(PLOTLY_DIR): try: os.mkdir(PLOTLY_DIR) except Exception: # in case of race if not os.path.isdir(PLOTLY_DIR): raise with open(TEST_FILE, "w") as f: f.write("testing\n") try: os.remove(TEST_FILE) except Exception: pass return True except Exception: # Do not trap KeyboardInterrupt. return False _file_permissions = None def ensure_writable_plotly_dir(): # Cache permissions status global _file_permissions if _file_permissions is None: _file_permissions = _permissions() return _file_permissions plotly-4.4.1+dfsg.orig/PKG-INFO0000644000175000017500000002124613573746614015373 0ustar noahfxnoahfxMetadata-Version: 2.1 Name: plotly Version: 4.4.1 Summary: An open-source, interactive graphing library for Python Home-page: https://plot.ly/python/ Author: Chris P Author-email: chris@plot.ly Maintainer: Jon Mease Maintainer-email: jon@plot.ly License: MIT Project-URL: Github, https://github.com/plotly/plotly.py Description: # plotly.py
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## Quickstart `pip install plotly==4.4.1` Inside [Jupyter notebook](https://jupyter.org/install) (installable with `pip install "notebook>=5.3" "ipywidgets>=7.2"`): ```python import plotly.graph_objects as go fig = go.Figure() fig.add_trace(go.Scatter(y=[2, 1, 4, 3])) fig.add_trace(go.Bar(y=[1, 4, 3, 2])) fig.update_layout(title = 'Hello Figure') fig.show() ``` See the [Python documentation](https://plot.ly/python/) for more examples. Read about what's new in [plotly.py v4](https://medium.com/plotly/plotly-py-4-0-is-here-offline-only-express-first-displayable-anywhere-fc444e5659ee) ## Overview [plotly.py](https://plot.ly/d3-js-for-python-and-pandas-charts/) is an interactive, open-source, and browser-based graphing library for Python :sparkles: Built on top of [plotly.js](https://github.com/plotly/plotly.js), `plotly.py` is a high-level, declarative charting library. plotly.js ships with over 30 chart types, including scientific charts, 3D graphs, statistical charts, SVG maps, financial charts, and more. `plotly.py` is [MIT Licensed](packages/python/chart-studio/LICENSE.txt). Plotly graphs can be viewed in Jupyter notebooks, standalone HTML files, or hosted online using [Chart Studio Cloud](https://chart-studio.plot.ly/feed/). [Contact us](https://plot.ly/products/consulting-and-oem/) for consulting, dashboard development, application integration, and feature additions.

*** - [Online Documentation](https://plot.ly/python) - [Contributing](contributing.md) - [Changelog](CHANGELOG.md) - [Code of Conduct](CODE_OF_CONDUCT.md) - [Version 4 Migration Guide](https://plot.ly/python/next/v4-migration/) - [New! Announcing Dash 1.0](https://medium.com/plotly/welcoming-dash-1-0-0-f3af4b84bae) - [Community](https://community.plot.ly/c/api/python) *** ## Installation plotly.py may be installed using pip... ``` pip install plotly==4.4.1 ``` or conda. ``` conda install -c plotly plotly=4.4.1 ``` ### Jupyter Notebook Support For use in the Jupyter Notebook, install the `notebook` and `ipywidgets` packages using pip... ``` pip install "notebook>=5.3" "ipywidgets==7.5" ``` or conda. ``` conda install "notebook>=5.3" "ipywidgets=7.5" ``` ### JupyterLab Support (Python 3.5+) For use in JupyterLab, install the `jupyterlab` and `ipywidgets` packages using pip... ``` pip install jupyterlab==1.2 "ipywidgets==7.5" ``` or conda. ``` conda install jupyterlab=1.2 conda install "ipywidgets=7.5" ``` Then run the following commands to install the required JupyterLab extensions (note that this will require [`node`](https://nodejs.org/) to be installed): ``` # Avoid "JavaScript heap out of memory" errors during extension installation # (OS X/Linux) export NODE_OPTIONS=--max-old-space-size=4096 # (Windows) set NODE_OPTIONS=--max-old-space-size=4096 # Jupyter widgets extension jupyter labextension install @jupyter-widgets/jupyterlab-manager@1.1 --no-build # FigureWidget support jupyter labextension install plotlywidget@1.4.0 --no-build # and jupyterlab renderer support jupyter labextension install jupyterlab-plotly@1.4.0 --no-build # Build extensions (must be done to activate extensions since --no-build is used above) jupyter lab build # Unset NODE_OPTIONS environment variable # (OS X/Linux) unset NODE_OPTIONS # (Windows) set NODE_OPTIONS= ``` ### Static Image Export plotly.py supports static image export using the `to_image` and `write_image` functions in the `plotly.io` package. This functionality requires the installation of the plotly [orca](https://github.com/plotly/orca) command line utility and the [`psutil`](https://github.com/giampaolo/psutil) Python package. These dependencies can both be installed using conda: ``` conda install -c plotly plotly-orca psutil ``` Or, `psutil` can be installed using pip... ``` pip install psutil ``` and orca can be installed according to the instructions in the [orca README](https://github.com/plotly/orca). #### Troubleshooting ##### Wrong Executable found If you get an error message stating that the `orca` executable that was found is not valid, this may be because another executable with the same name was found on your system. Please specify the complete path to the Plotly-Orca binary that you downloaded (for instance in the Miniconda folder) with the following command: `plotly.io.orca.config.executable = '/home/your_name/miniconda3/bin/orca'` ### Extended Geo Support Some plotly.py features rely on fairly large geographic shape files. The county choropleth figure factory is one such example. These shape files are distributed as a separate `plotly-geo` package. This package can be installed using pip... ``` pip install plotly-geo==1.0.0 ``` or conda ``` conda install -c plotly plotly-geo=1.0.0 ``` ### Chart Studio support The `chart-studio` package can be used to upload plotly figures to Plotly's Chart Studio Cloud or On-Prem service. This package can be installed using pip... ``` pip install chart-studio==1.0.0 ``` or conda ``` conda install -c plotly chart-studio=1.0.0 ``` ## Migration If you're migrating from plotly.py v3 to v4, please check out the [Version 4 migration guide](https://plot.ly/python/next/v4-migration/) If you're migrating from plotly.py v2 to v3, please check out the [Version 3 migration guide](migration-guide.md) ## Copyright and Licenses Code and documentation copyright 2019 Plotly, Inc. Code released under the [MIT license](packages/python/chart-studio/LICENSE.txt). Docs released under the [Creative Commons license](https://github.com/plotly/documentation/blob/source/LICENSE). Platform: UNKNOWN Classifier: Development Status :: 5 - Production/Stable Classifier: Programming Language :: Python :: 2 Classifier: Programming Language :: Python :: 2.7 Classifier: Programming Language :: Python :: 3 Classifier: Programming Language :: Python :: 3.3 Classifier: Programming Language :: Python :: 3.4 Classifier: Programming Language :: Python :: 3.5 Classifier: Programming Language :: Python :: 3.6 Classifier: Programming Language :: Python :: 3.7 Classifier: Topic :: Scientific/Engineering :: Visualization Description-Content-Type: text/markdown plotly-4.4.1+dfsg.orig/plotly.egg-info/0000755000175000017500000000000013573746613017305 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly.egg-info/PKG-INFO0000644000175000017500000002124613573746613020407 0ustar noahfxnoahfxMetadata-Version: 2.1 Name: plotly Version: 4.4.1 Summary: An open-source, interactive graphing library for Python Home-page: https://plot.ly/python/ Author: Chris P Author-email: chris@plot.ly Maintainer: Jon Mease Maintainer-email: jon@plot.ly License: MIT Project-URL: Github, https://github.com/plotly/plotly.py Description: # plotly.py
Latest Release
PyPI Downloads
License
## Quickstart `pip install plotly==4.4.1` Inside [Jupyter notebook](https://jupyter.org/install) (installable with `pip install "notebook>=5.3" "ipywidgets>=7.2"`): ```python import plotly.graph_objects as go fig = go.Figure() fig.add_trace(go.Scatter(y=[2, 1, 4, 3])) fig.add_trace(go.Bar(y=[1, 4, 3, 2])) fig.update_layout(title = 'Hello Figure') fig.show() ``` See the [Python documentation](https://plot.ly/python/) for more examples. Read about what's new in [plotly.py v4](https://medium.com/plotly/plotly-py-4-0-is-here-offline-only-express-first-displayable-anywhere-fc444e5659ee) ## Overview [plotly.py](https://plot.ly/d3-js-for-python-and-pandas-charts/) is an interactive, open-source, and browser-based graphing library for Python :sparkles: Built on top of [plotly.js](https://github.com/plotly/plotly.js), `plotly.py` is a high-level, declarative charting library. plotly.js ships with over 30 chart types, including scientific charts, 3D graphs, statistical charts, SVG maps, financial charts, and more. `plotly.py` is [MIT Licensed](packages/python/chart-studio/LICENSE.txt). Plotly graphs can be viewed in Jupyter notebooks, standalone HTML files, or hosted online using [Chart Studio Cloud](https://chart-studio.plot.ly/feed/). [Contact us](https://plot.ly/products/consulting-and-oem/) for consulting, dashboard development, application integration, and feature additions.

*** - [Online Documentation](https://plot.ly/python) - [Contributing](contributing.md) - [Changelog](CHANGELOG.md) - [Code of Conduct](CODE_OF_CONDUCT.md) - [Version 4 Migration Guide](https://plot.ly/python/next/v4-migration/) - [New! Announcing Dash 1.0](https://medium.com/plotly/welcoming-dash-1-0-0-f3af4b84bae) - [Community](https://community.plot.ly/c/api/python) *** ## Installation plotly.py may be installed using pip... ``` pip install plotly==4.4.1 ``` or conda. ``` conda install -c plotly plotly=4.4.1 ``` ### Jupyter Notebook Support For use in the Jupyter Notebook, install the `notebook` and `ipywidgets` packages using pip... ``` pip install "notebook>=5.3" "ipywidgets==7.5" ``` or conda. ``` conda install "notebook>=5.3" "ipywidgets=7.5" ``` ### JupyterLab Support (Python 3.5+) For use in JupyterLab, install the `jupyterlab` and `ipywidgets` packages using pip... ``` pip install jupyterlab==1.2 "ipywidgets==7.5" ``` or conda. ``` conda install jupyterlab=1.2 conda install "ipywidgets=7.5" ``` Then run the following commands to install the required JupyterLab extensions (note that this will require [`node`](https://nodejs.org/) to be installed): ``` # Avoid "JavaScript heap out of memory" errors during extension installation # (OS X/Linux) export NODE_OPTIONS=--max-old-space-size=4096 # (Windows) set NODE_OPTIONS=--max-old-space-size=4096 # Jupyter widgets extension jupyter labextension install @jupyter-widgets/jupyterlab-manager@1.1 --no-build # FigureWidget support jupyter labextension install plotlywidget@1.4.0 --no-build # and jupyterlab renderer support jupyter labextension install jupyterlab-plotly@1.4.0 --no-build # Build extensions (must be done to activate extensions since --no-build is used above) jupyter lab build # Unset NODE_OPTIONS environment variable # (OS X/Linux) unset NODE_OPTIONS # (Windows) set NODE_OPTIONS= ``` ### Static Image Export plotly.py supports static image export using the `to_image` and `write_image` functions in the `plotly.io` package. This functionality requires the installation of the plotly [orca](https://github.com/plotly/orca) command line utility and the [`psutil`](https://github.com/giampaolo/psutil) Python package. These dependencies can both be installed using conda: ``` conda install -c plotly plotly-orca psutil ``` Or, `psutil` can be installed using pip... ``` pip install psutil ``` and orca can be installed according to the instructions in the [orca README](https://github.com/plotly/orca). #### Troubleshooting ##### Wrong Executable found If you get an error message stating that the `orca` executable that was found is not valid, this may be because another executable with the same name was found on your system. Please specify the complete path to the Plotly-Orca binary that you downloaded (for instance in the Miniconda folder) with the following command: `plotly.io.orca.config.executable = '/home/your_name/miniconda3/bin/orca'` ### Extended Geo Support Some plotly.py features rely on fairly large geographic shape files. The county choropleth figure factory is one such example. These shape files are distributed as a separate `plotly-geo` package. This package can be installed using pip... ``` pip install plotly-geo==1.0.0 ``` or conda ``` conda install -c plotly plotly-geo=1.0.0 ``` ### Chart Studio support The `chart-studio` package can be used to upload plotly figures to Plotly's Chart Studio Cloud or On-Prem service. This package can be installed using pip... ``` pip install chart-studio==1.0.0 ``` or conda ``` conda install -c plotly chart-studio=1.0.0 ``` ## Migration If you're migrating from plotly.py v3 to v4, please check out the [Version 4 migration guide](https://plot.ly/python/next/v4-migration/) If you're migrating from plotly.py v2 to v3, please check out the [Version 3 migration guide](migration-guide.md) ## Copyright and Licenses Code and documentation copyright 2019 Plotly, Inc. Code released under the [MIT license](packages/python/chart-studio/LICENSE.txt). Docs released under the [Creative Commons license](https://github.com/plotly/documentation/blob/source/LICENSE). Platform: UNKNOWN Classifier: Development Status :: 5 - Production/Stable Classifier: Programming Language :: Python :: 2 Classifier: Programming Language :: Python :: 2.7 Classifier: Programming Language :: Python :: 3 Classifier: Programming Language :: Python :: 3.3 Classifier: Programming Language :: Python :: 3.4 Classifier: Programming Language :: Python :: 3.5 Classifier: Programming Language :: Python :: 3.6 Classifier: Programming Language :: Python :: 3.7 Classifier: Topic :: Scientific/Engineering :: Visualization Description-Content-Type: text/markdown plotly-4.4.1+dfsg.orig/plotly.egg-info/requires.txt0000644000175000017500000000002413573746613021701 0ustar noahfxnoahfxretrying>=1.3.3 six plotly-4.4.1+dfsg.orig/plotly.egg-info/dependency_links.txt0000644000175000017500000000000113573746613023353 0ustar noahfxnoahfx plotly-4.4.1+dfsg.orig/plotly.egg-info/top_level.txt0000644000175000017500000000006213573746613022035 0ustar noahfxnoahfx_plotly_future_ _plotly_utils plotly plotlywidget plotly-4.4.1+dfsg.orig/plotly.egg-info/SOURCES.txt0000644000175000017500000017443213573746613021204 0ustar noahfxnoahfxLICENSE.txt MANIFEST.in README.md plotlywidget.json setup.cfg setup.py versioneer.py _plotly_future_/__init__.py _plotly_future_/extract_chart_studio.py _plotly_future_/orca_defaults.py _plotly_future_/remove_deprecations.py _plotly_future_/renderer_defaults.py _plotly_future_/template_defaults.py _plotly_future_/timezones.py _plotly_future_/trace_uids.py _plotly_future_/v4.py _plotly_future_/v4_subplots.py _plotly_utils/__init__.py _plotly_utils/basevalidators.py _plotly_utils/exceptions.py _plotly_utils/files.py _plotly_utils/optional_imports.py _plotly_utils/utils.py _plotly_utils/colors/__init__.py _plotly_utils/colors/_swatches.py _plotly_utils/colors/carto.py _plotly_utils/colors/cmocean.py _plotly_utils/colors/colorbrewer.py _plotly_utils/colors/cyclical.py _plotly_utils/colors/diverging.py _plotly_utils/colors/plotlyjs.py _plotly_utils/colors/qualitative.py _plotly_utils/colors/sequential.py plotly/__init__.py plotly/_docstring_gen.py plotly/_version.py plotly/_widget_version.py plotly/animation.py plotly/basedatatypes.py plotly/basewidget.py plotly/callbacks.py plotly/colors.py plotly/config.py plotly/conftest.py plotly/dashboard_objs.py plotly/exceptions.py plotly/files.py plotly/graph_objects.py plotly/grid_objs.py plotly/optional_imports.py plotly/presentation_objs.py plotly/serializers.py plotly/session.py plotly/subplots.py plotly/tools.py plotly/utils.py plotly/version.py plotly/widgets.py plotly.egg-info/PKG-INFO plotly.egg-info/SOURCES.txt plotly.egg-info/dependency_links.txt plotly.egg-info/not-zip-safe plotly.egg-info/requires.txt plotly.egg-info/top_level.txt plotly/data/__init__.py plotly/express/__init__.py plotly/express/_chart_types.py plotly/express/_core.py plotly/express/_doc.py plotly/express/_imshow.py plotly/express/colors.py plotly/express/data.py plotly/figure_factory/_2d_density.py plotly/figure_factory/__init__.py plotly/figure_factory/_annotated_heatmap.py plotly/figure_factory/_bullet.py plotly/figure_factory/_candlestick.py plotly/figure_factory/_county_choropleth.py plotly/figure_factory/_dendrogram.py plotly/figure_factory/_distplot.py plotly/figure_factory/_facet_grid.py plotly/figure_factory/_gantt.py plotly/figure_factory/_ohlc.py plotly/figure_factory/_quiver.py plotly/figure_factory/_scatterplot.py plotly/figure_factory/_streamline.py plotly/figure_factory/_table.py plotly/figure_factory/_ternary_contour.py plotly/figure_factory/_trisurf.py plotly/figure_factory/_violin.py plotly/figure_factory/utils.py plotly/graph_objs/__init__.py plotly/graph_objs/_deprecations.py plotly/graph_objs/_figure.py plotly/graph_objs/_figurewidget.py plotly/graph_objs/graph_objs.py plotly/graph_objs/area/__init__.py plotly/graph_objs/area/hoverlabel/__init__.py plotly/graph_objs/bar/__init__.py plotly/graph_objs/bar/hoverlabel/__init__.py plotly/graph_objs/bar/marker/__init__.py plotly/graph_objs/bar/marker/colorbar/__init__.py plotly/graph_objs/bar/marker/colorbar/title/__init__.py plotly/graph_objs/bar/selected/__init__.py plotly/graph_objs/bar/unselected/__init__.py plotly/graph_objs/barpolar/__init__.py plotly/graph_objs/barpolar/hoverlabel/__init__.py plotly/graph_objs/barpolar/marker/__init__.py plotly/graph_objs/barpolar/marker/colorbar/__init__.py plotly/graph_objs/barpolar/marker/colorbar/title/__init__.py plotly/graph_objs/barpolar/selected/__init__.py plotly/graph_objs/barpolar/unselected/__init__.py plotly/graph_objs/box/__init__.py plotly/graph_objs/box/hoverlabel/__init__.py plotly/graph_objs/box/marker/__init__.py plotly/graph_objs/box/selected/__init__.py plotly/graph_objs/box/unselected/__init__.py plotly/graph_objs/candlestick/__init__.py plotly/graph_objs/candlestick/decreasing/__init__.py plotly/graph_objs/candlestick/hoverlabel/__init__.py plotly/graph_objs/candlestick/increasing/__init__.py plotly/graph_objs/carpet/__init__.py plotly/graph_objs/carpet/aaxis/__init__.py plotly/graph_objs/carpet/aaxis/title/__init__.py plotly/graph_objs/carpet/baxis/__init__.py plotly/graph_objs/carpet/baxis/title/__init__.py plotly/graph_objs/choropleth/__init__.py plotly/graph_objs/choropleth/colorbar/__init__.py plotly/graph_objs/choropleth/colorbar/title/__init__.py plotly/graph_objs/choropleth/hoverlabel/__init__.py plotly/graph_objs/choropleth/marker/__init__.py plotly/graph_objs/choropleth/selected/__init__.py plotly/graph_objs/choropleth/unselected/__init__.py plotly/graph_objs/choroplethmapbox/__init__.py plotly/graph_objs/choroplethmapbox/colorbar/__init__.py plotly/graph_objs/choroplethmapbox/colorbar/title/__init__.py plotly/graph_objs/choroplethmapbox/hoverlabel/__init__.py plotly/graph_objs/choroplethmapbox/marker/__init__.py plotly/graph_objs/choroplethmapbox/selected/__init__.py plotly/graph_objs/choroplethmapbox/unselected/__init__.py plotly/graph_objs/cone/__init__.py plotly/graph_objs/cone/colorbar/__init__.py plotly/graph_objs/cone/colorbar/title/__init__.py plotly/graph_objs/cone/hoverlabel/__init__.py plotly/graph_objs/contour/__init__.py plotly/graph_objs/contour/colorbar/__init__.py plotly/graph_objs/contour/colorbar/title/__init__.py plotly/graph_objs/contour/contours/__init__.py plotly/graph_objs/contour/hoverlabel/__init__.py plotly/graph_objs/contourcarpet/__init__.py plotly/graph_objs/contourcarpet/colorbar/__init__.py plotly/graph_objs/contourcarpet/colorbar/title/__init__.py plotly/graph_objs/contourcarpet/contours/__init__.py plotly/graph_objs/densitymapbox/__init__.py plotly/graph_objs/densitymapbox/colorbar/__init__.py plotly/graph_objs/densitymapbox/colorbar/title/__init__.py plotly/graph_objs/densitymapbox/hoverlabel/__init__.py plotly/graph_objs/funnel/__init__.py plotly/graph_objs/funnel/connector/__init__.py plotly/graph_objs/funnel/hoverlabel/__init__.py plotly/graph_objs/funnel/marker/__init__.py plotly/graph_objs/funnel/marker/colorbar/__init__.py plotly/graph_objs/funnel/marker/colorbar/title/__init__.py plotly/graph_objs/funnelarea/__init__.py plotly/graph_objs/funnelarea/hoverlabel/__init__.py plotly/graph_objs/funnelarea/marker/__init__.py plotly/graph_objs/funnelarea/title/__init__.py plotly/graph_objs/heatmap/__init__.py plotly/graph_objs/heatmap/colorbar/__init__.py plotly/graph_objs/heatmap/colorbar/title/__init__.py plotly/graph_objs/heatmap/hoverlabel/__init__.py plotly/graph_objs/heatmapgl/__init__.py plotly/graph_objs/heatmapgl/colorbar/__init__.py plotly/graph_objs/heatmapgl/colorbar/title/__init__.py plotly/graph_objs/heatmapgl/hoverlabel/__init__.py plotly/graph_objs/histogram/__init__.py plotly/graph_objs/histogram/hoverlabel/__init__.py plotly/graph_objs/histogram/marker/__init__.py plotly/graph_objs/histogram/marker/colorbar/__init__.py plotly/graph_objs/histogram/marker/colorbar/title/__init__.py plotly/graph_objs/histogram/selected/__init__.py plotly/graph_objs/histogram/unselected/__init__.py plotly/graph_objs/histogram2d/__init__.py plotly/graph_objs/histogram2d/colorbar/__init__.py plotly/graph_objs/histogram2d/colorbar/title/__init__.py plotly/graph_objs/histogram2d/hoverlabel/__init__.py plotly/graph_objs/histogram2dcontour/__init__.py plotly/graph_objs/histogram2dcontour/colorbar/__init__.py plotly/graph_objs/histogram2dcontour/colorbar/title/__init__.py plotly/graph_objs/histogram2dcontour/contours/__init__.py plotly/graph_objs/histogram2dcontour/hoverlabel/__init__.py plotly/graph_objs/image/__init__.py plotly/graph_objs/image/hoverlabel/__init__.py plotly/graph_objs/indicator/__init__.py plotly/graph_objs/indicator/delta/__init__.py plotly/graph_objs/indicator/gauge/__init__.py plotly/graph_objs/indicator/gauge/axis/__init__.py plotly/graph_objs/indicator/gauge/bar/__init__.py plotly/graph_objs/indicator/gauge/step/__init__.py plotly/graph_objs/indicator/gauge/threshold/__init__.py plotly/graph_objs/indicator/number/__init__.py plotly/graph_objs/indicator/title/__init__.py plotly/graph_objs/isosurface/__init__.py plotly/graph_objs/isosurface/caps/__init__.py plotly/graph_objs/isosurface/colorbar/__init__.py plotly/graph_objs/isosurface/colorbar/title/__init__.py plotly/graph_objs/isosurface/hoverlabel/__init__.py plotly/graph_objs/isosurface/slices/__init__.py plotly/graph_objs/layout/__init__.py plotly/graph_objs/layout/annotation/__init__.py plotly/graph_objs/layout/annotation/hoverlabel/__init__.py plotly/graph_objs/layout/coloraxis/__init__.py plotly/graph_objs/layout/coloraxis/colorbar/__init__.py plotly/graph_objs/layout/coloraxis/colorbar/title/__init__.py plotly/graph_objs/layout/geo/__init__.py plotly/graph_objs/layout/geo/projection/__init__.py plotly/graph_objs/layout/grid/__init__.py plotly/graph_objs/layout/hoverlabel/__init__.py 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plotly/validators/waterfall/increasing/__init__.py plotly/validators/waterfall/increasing/marker/__init__.py plotly/validators/waterfall/increasing/marker/line/__init__.py plotly/validators/waterfall/insidetextfont/__init__.py plotly/validators/waterfall/outsidetextfont/__init__.py plotly/validators/waterfall/stream/__init__.py plotly/validators/waterfall/textfont/__init__.py plotly/validators/waterfall/totals/__init__.py plotly/validators/waterfall/totals/marker/__init__.py plotly/validators/waterfall/totals/marker/line/__init__.py plotlywidget/__init__.py plotlywidget/static/extension.js plotlywidget/static/index.jsplotly-4.4.1+dfsg.orig/plotly.egg-info/not-zip-safe0000644000175000017500000000000113551707663021531 0ustar noahfxnoahfx plotly-4.4.1+dfsg.orig/plotlywidget.json0000644000175000017500000000010213525746125017676 0ustar noahfxnoahfx{ "load_extensions": { "plotlywidget/extension": true } } plotly-4.4.1+dfsg.orig/plotly/0000755000175000017500000000000013573746614015614 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/conftest.py0000644000175000017500000000116213573717677020022 0ustar noahfxnoahfximport pytest import os def pytest_ignore_collect(path): # Ignored files, most of them are raising a chart studio error ignored_paths = [ "exploding_module.py", "chunked_requests.py", "v2.py", "v1.py", "presentation_objs.py", "widgets.py", "dashboard_objs.py", "grid_objs.py", "config.py", "presentation_objs.py", "session.py", ] if ( os.path.basename(str(path)) in ignored_paths or "plotly/plotly/plotly/__init__.py" in str(path) or "plotly/api/utils.py" in str(path) ): return True plotly-4.4.1+dfsg.orig/plotly/_widget_version.py0000644000175000017500000000027213573724327021353 0ustar noahfxnoahfx# This file is generated by the updateplotlywidgetversion setup.py command # for automated dev builds # # It is edited by hand prior to official releases __frontend_version__ = "^1.4.0" plotly-4.4.1+dfsg.orig/plotly/exceptions.py0000644000175000017500000000011613525746125020337 0ustar noahfxnoahfxfrom __future__ import absolute_import from _plotly_utils.exceptions import * plotly-4.4.1+dfsg.orig/plotly/offline/0000755000175000017500000000000013573746613017235 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/offline/__init__.py0000644000175000017500000000040113525746125021334 0ustar noahfxnoahfx""" offline ====== This module provides offline functionality. """ from .offline import ( download_plotlyjs, get_plotlyjs_version, get_plotlyjs, enable_mpl_offline, init_notebook_mode, iplot, iplot_mpl, plot, plot_mpl, ) plotly-4.4.1+dfsg.orig/plotly/offline/offline.py0000644000175000017500000007560713573717677021260 0ustar noahfxnoahfx""" Plotly Offline A module to use Plotly's graphing library with Python without connecting to a public or private plotly enterprise server. """ from __future__ import absolute_import import os import warnings import pkgutil import plotly import plotly.tools from plotly.optional_imports import get_module from plotly import tools from ._plotlyjs_version import __plotlyjs_version__ __IMAGE_FORMATS = ["jpeg", "png", "webp", "svg"] def download_plotlyjs(download_url): warnings.warn( """ `download_plotlyjs` is deprecated and will be removed in the next release. plotly.js is shipped with this module, it is no longer necessary to download this bundle separately. """, DeprecationWarning, ) pass def get_plotlyjs_version(): """ Returns the version of plotly.js that is bundled with plotly.py. Returns ------- str Plotly.js version string """ return __plotlyjs_version__ def get_plotlyjs(): """ Return the contents of the minified plotly.js library as a string. This may be useful when building standalone HTML reports. Returns ------- str Contents of the minified plotly.js library as a string Examples -------- Here is an example of creating a standalone HTML report that contains two plotly figures, each in their own div. The include_plotlyjs argument is set to False when creating the divs so that we don't include multiple copies of the plotly.js library in the output. Instead, a single copy of plotly.js is included in a script tag in the html head element. >>> import plotly.graph_objs as go >>> from plotly.offline import plot, get_plotlyjs >>> fig1 = go.Figure(data=[{'type': 'bar', 'y': [1, 3, 2]}], ... layout={'height': 400}) >>> fig2 = go.Figure(data=[{'type': 'scatter', 'y': [1, 3, 2]}], ... layout={'height': 400}) >>> div1 = plot(fig1, output_type='div', include_plotlyjs=False) >>> div2 = plot(fig2, output_type='div', include_plotlyjs=False) >>> html = ''' ... ... ... ... ... ... {div1} ... {div2} ... ... ... '''.format(plotlyjs=get_plotlyjs(), div1=div1, div2=div2) >>> with open('multi_plot.html', 'w') as f: ... f.write(html) # doctest: +SKIP """ path = os.path.join("package_data", "plotly.min.js") plotlyjs = pkgutil.get_data("plotly", path).decode("utf-8") return plotlyjs def _build_resize_script(plotdivid, plotly_root="Plotly"): resize_script = ( '" ).format(plotly_root=plotly_root, id=plotdivid) return resize_script def _build_mathjax_script(url): return ''.format(url=url) def _get_jconfig(config=None): configkeys = ( "staticPlot", "plotlyServerURL", "editable", "edits", "autosizable", "responsive", "queueLength", "fillFrame", "frameMargins", "scrollZoom", "doubleClick", "showTips", "showAxisDragHandles", "showAxisRangeEntryBoxes", "showLink", "sendData", "showSendToCloud", "linkText", "showSources", "displayModeBar", "modeBarButtonsToRemove", "modeBarButtonsToAdd", "modeBarButtons", "toImageButtonOptions", "displaylogo", "watermark", "plotGlPixelRatio", "setBackground", "topojsonURL", "mapboxAccessToken", "logging", "globalTransforms", "locale", "locales", ) if config and isinstance(config, dict): # Warn user on unrecognized config options. We make this a warning # rather than an error since we don't have code generation logic in # place yet to guarantee that the config options in plotly.py are up # to date bad_config = [k for k in config if k not in configkeys] if bad_config: warnings.warn( """ Unrecognized config options supplied: {bad_config}""".format( bad_config=bad_config ) ) clean_config = config else: clean_config = {} plotly_platform_url = plotly.tools.get_config_plotly_server_url() if not clean_config.get("plotlyServerURL", None): clean_config["plotlyServerURL"] = plotly_platform_url if ( plotly_platform_url != "https://plot.ly" and clean_config.get("linkText", None) == "Export to plot.ly" ): link_domain = plotly_platform_url.replace("https://", "").replace("http://", "") link_text = clean_config["linkText"].replace("plot.ly", link_domain) clean_config["linkText"] = link_text return clean_config # Build script to set global PlotlyConfig object. This must execute before # plotly.js is loaded. _window_plotly_config = """\ """ _mathjax_config = """\ """ def get_image_download_script(caller): """ This function will return a script that will download an image of a Plotly plot. Keyword Arguments: caller ('plot', 'iplot') -- specifies which function made the call for the download script. If `iplot`, then an extra condition is added into the download script to ensure that download prompts aren't initiated on page reloads. """ if caller == "iplot": check_start = "if(document.readyState == 'complete') {{" check_end = "}}" elif caller == "plot": check_start = "" check_end = "" else: raise ValueError("caller should only be one of `iplot` or `plot`") return ( "function downloadimage(format, height, width," " filename) {{" "var p = document.getElementById('{{plot_id}}');" "Plotly.downloadImage(p, {{format: format, height: height, " "width: width, filename: filename}});}};" + check_start + "downloadimage('{format}', {height}, {width}, " "'{filename}');" + check_end ) def build_save_image_post_script( image, image_filename, image_height, image_width, caller ): if image: if image not in __IMAGE_FORMATS: raise ValueError( "The image parameter must be one of the " "following: {}".format(__IMAGE_FORMATS) ) script = get_image_download_script(caller) post_script = script.format( format=image, width=image_width, height=image_height, filename=image_filename, ) else: post_script = None return post_script def init_notebook_mode(connected=False): """ Initialize plotly.js in the browser if it hasn't been loaded into the DOM yet. This is an idempotent method and can and should be called from any offline methods that require plotly.js to be loaded into the notebook dom. Keyword arguments: connected (default=False) -- If True, the plotly.js library will be loaded from an online CDN. If False, the plotly.js library will be loaded locally from the plotly python package Use `connected=True` if you want your notebooks to have smaller file sizes. In the case where `connected=False`, the entirety of the plotly.js library will be loaded into the notebook, which will result in a file-size increase of a couple megabytes. Additionally, because the library will be downloaded from the web, you and your viewers must be connected to the internet to be able to view charts within this notebook. Use `connected=False` if you want you and your collaborators to be able to create and view these charts regardless of the availability of an internet connection. This is the default option since it is the most predictable. Note that under this setting the library will be included inline inside your notebook, resulting in much larger notebook sizes compared to the case where `connected=True`. """ import plotly.io as pio ipython = get_module("IPython") if not ipython: raise ImportError("`iplot` can only run inside an IPython Notebook.") if connected: pio.renderers.default = "plotly_mimetype+notebook_connected" else: pio.renderers.default = "plotly_mimetype+notebook" # Trigger immediate activation of notebook. This way the plotly.js # library reference is available to the notebook immediately pio.renderers._activate_pending_renderers() def iplot( figure_or_data, show_link=False, link_text="Export to plot.ly", validate=True, image=None, filename="plot_image", image_width=800, image_height=600, config=None, auto_play=True, animation_opts=None, ): """ Draw plotly graphs inside an IPython or Jupyter notebook figure_or_data -- a plotly.graph_objs.Figure or plotly.graph_objs.Data or dict or list that describes a Plotly graph. See https://plot.ly/python/ for examples of graph descriptions. Keyword arguments: show_link (default=False) -- display a link in the bottom-right corner of of the chart that will export the chart to Plotly Cloud or Plotly Enterprise link_text (default='Export to plot.ly') -- the text of export link validate (default=True) -- validate that all of the keys in the figure are valid? omit if your version of plotly.js has become outdated with your version of graph_reference.json or if you need to include extra, unnecessary keys in your figure. image (default=None |'png' |'jpeg' |'svg' |'webp') -- This parameter sets the format of the image to be downloaded, if we choose to download an image. This parameter has a default value of None indicating that no image should be downloaded. Please note: for higher resolution images and more export options, consider using plotly.io.write_image. See https://plot.ly/python/static-image-export/ for more details. filename (default='plot') -- Sets the name of the file your image will be saved to. The extension should not be included. image_height (default=600) -- Specifies the height of the image in `px`. image_width (default=800) -- Specifies the width of the image in `px`. config (default=None) -- Plot view options dictionary. Keyword arguments `show_link` and `link_text` set the associated options in this dictionary if it doesn't contain them already. auto_play (default=True) -- Whether to automatically start the animation sequence on page load, if the figure contains frames. Has no effect if the figure does not contain frames. animation_opts (default=None) -- Dict of custom animation parameters that are used for the automatically started animation on page load. This dict is passed to the function Plotly.animate in Plotly.js. See https://github.com/plotly/plotly.js/blob/master/src/plots/animation_attributes.js for available options. Has no effect if the figure does not contain frames, or auto_play is False. Example: ``` from plotly.offline import init_notebook_mode, iplot init_notebook_mode() iplot([{'x': [1, 2, 3], 'y': [5, 2, 7]}]) # We can also download an image of the plot by setting the image to the format you want. e.g. `image='png'` iplot([{'x': [1, 2, 3], 'y': [5, 2, 7]}], image='png') ``` animation_opts Example: ``` from plotly.offline import iplot figure = {'data': [{'x': [0, 1], 'y': [0, 1]}], 'layout': {'xaxis': {'range': [0, 5], 'autorange': False}, 'yaxis': {'range': [0, 5], 'autorange': False}, 'title': 'Start Title'}, 'frames': [{'data': [{'x': [1, 2], 'y': [1, 2]}]}, {'data': [{'x': [1, 4], 'y': [1, 4]}]}, {'data': [{'x': [3, 4], 'y': [3, 4]}], 'layout': {'title': 'End Title'}}]} iplot(figure, animation_opts={'frame': {'duration': 1}}) ``` """ import plotly.io as pio ipython = get_module("IPython") if not ipython: raise ImportError("`iplot` can only run inside an IPython Notebook.") config = dict(config) if config else {} config.setdefault("showLink", show_link) config.setdefault("linkText", link_text) # Get figure figure = tools.return_figure_from_figure_or_data(figure_or_data, validate) # Handle image request post_script = build_save_image_post_script( image, filename, image_height, image_width, "iplot" ) # Show figure pio.show( figure, validate=validate, config=config, auto_play=auto_play, post_script=post_script, animation_opts=animation_opts, ) def plot( figure_or_data, show_link=False, link_text="Export to plot.ly", validate=True, output_type="file", include_plotlyjs=True, filename="temp-plot.html", auto_open=True, image=None, image_filename="plot_image", image_width=800, image_height=600, config=None, include_mathjax=False, auto_play=True, animation_opts=None, ): """ Create a plotly graph locally as an HTML document or string. Example: ``` from plotly.offline import plot import plotly.graph_objs as go plot([go.Scatter(x=[1, 2, 3], y=[3, 2, 6])], filename='my-graph.html') # We can also download an image of the plot by setting the image parameter # to the image format we want plot([go.Scatter(x=[1, 2, 3], y=[3, 2, 6])], filename='my-graph.html', image='jpeg') ``` More examples below. figure_or_data -- a plotly.graph_objs.Figure or plotly.graph_objs.Data or dict or list that describes a Plotly graph. See https://plot.ly/python/ for examples of graph descriptions. Keyword arguments: show_link (default=False) -- display a link in the bottom-right corner of of the chart that will export the chart to Plotly Cloud or Plotly Enterprise link_text (default='Export to plot.ly') -- the text of export link validate (default=True) -- validate that all of the keys in the figure are valid? omit if your version of plotly.js has become outdated with your version of graph_reference.json or if you need to include extra, unnecessary keys in your figure. output_type ('file' | 'div' - default 'file') -- if 'file', then the graph is saved as a standalone HTML file and `plot` returns None. If 'div', then `plot` returns a string that just contains the HTML
that contains the graph and the script to generate the graph. Use 'file' if you want to save and view a single graph at a time in a standalone HTML file. Use 'div' if you are embedding these graphs in an HTML file with other graphs or HTML markup, like a HTML report or an website. include_plotlyjs (True | False | 'cdn' | 'directory' | path - default=True) Specifies how the plotly.js library is included in the output html file or div string. If True, a script tag containing the plotly.js source code (~3MB) is included in the output. HTML files generated with this option are fully self-contained and can be used offline. If 'cdn', a script tag that references the plotly.js CDN is included in the output. HTML files generated with this option are about 3MB smaller than those generated with include_plotlyjs=True, but they require an active internet connection in order to load the plotly.js library. If 'directory', a script tag is included that references an external plotly.min.js bundle that is assumed to reside in the same directory as the HTML file. If output_type='file' then the plotly.min.js bundle is copied into the directory of the resulting HTML file. If a file named plotly.min.js already exists in the output directory then this file is left unmodified and no copy is performed. HTML files generated with this option can be used offline, but they require a copy of the plotly.min.js bundle in the same directory. This option is useful when many figures will be saved as HTML files in the same directory because the plotly.js source code will be included only once per output directory, rather than once per output file. If a string that ends in '.js', a script tag is included that references the specified path. This approach can be used to point the resulting HTML file to an alternative CDN. If False, no script tag referencing plotly.js is included. This is useful when output_type='div' and the resulting div string will be placed inside an HTML document that already loads plotly.js. This option is not advised when output_type='file' as it will result in a non-functional html file. filename (default='temp-plot.html') -- The local filename to save the outputted chart to. If the filename already exists, it will be overwritten. This argument only applies if `output_type` is 'file'. auto_open (default=True) -- If True, open the saved file in a web browser after saving. This argument only applies if `output_type` is 'file'. image (default=None |'png' |'jpeg' |'svg' |'webp') -- This parameter sets the format of the image to be downloaded, if we choose to download an image. This parameter has a default value of None indicating that no image should be downloaded. Please note: for higher resolution images and more export options, consider making requests to our image servers. Type: `help(py.image)` for more details. image_filename (default='plot_image') -- Sets the name of the file your image will be saved to. The extension should not be included. image_height (default=600) -- Specifies the height of the image in `px`. image_width (default=800) -- Specifies the width of the image in `px`. config (default=None) -- Plot view options dictionary. Keyword arguments `show_link` and `link_text` set the associated options in this dictionary if it doesn't contain them already. include_mathjax (False | 'cdn' | path - default=False) -- Specifies how the MathJax.js library is included in the output html file or div string. MathJax is required in order to display labels with LaTeX typesetting. If False, no script tag referencing MathJax.js will be included in the output. HTML files generated with this option will not be able to display LaTeX typesetting. If 'cdn', a script tag that references a MathJax CDN location will be included in the output. HTML files generated with this option will be able to display LaTeX typesetting as long as they have internet access. If a string that ends in '.js', a script tag is included that references the specified path. This approach can be used to point the resulting HTML file to an alternative CDN. auto_play (default=True) -- Whether to automatically start the animation sequence on page load if the figure contains frames. Has no effect if the figure does not contain frames. animation_opts (default=None) -- Dict of custom animation parameters that are used for the automatically started animation on page load. This dict is passed to the function Plotly.animate in Plotly.js. See https://github.com/plotly/plotly.js/blob/master/src/plots/animation_attributes.js for available options. Has no effect if the figure does not contain frames, or auto_play is False. Example: ``` from plotly.offline import plot figure = {'data': [{'x': [0, 1], 'y': [0, 1]}], 'layout': {'xaxis': {'range': [0, 5], 'autorange': False}, 'yaxis': {'range': [0, 5], 'autorange': False}, 'title': 'Start Title'}, 'frames': [{'data': [{'x': [1, 2], 'y': [1, 2]}]}, {'data': [{'x': [1, 4], 'y': [1, 4]}]}, {'data': [{'x': [3, 4], 'y': [3, 4]}], 'layout': {'title': 'End Title'}}]} plot(figure, animation_opts={'frame': {'duration': 1}}) ``` """ import plotly.io as pio # Output type if output_type not in ["div", "file"]: raise ValueError( "`output_type` argument must be 'div' or 'file'. " "You supplied `" + output_type + "``" ) if not filename.endswith(".html") and output_type == "file": warnings.warn( "Your filename `" + filename + "` didn't end with .html. " "Adding .html to the end of your file." ) filename += ".html" # Config config = dict(config) if config else {} config.setdefault("showLink", show_link) config.setdefault("linkText", link_text) figure = tools.return_figure_from_figure_or_data(figure_or_data, validate) width = figure.get("layout", {}).get("width", "100%") height = figure.get("layout", {}).get("height", "100%") if width == "100%" or height == "100%": config.setdefault("responsive", True) # Handle image request post_script = build_save_image_post_script( image, image_filename, image_height, image_width, "plot" ) if output_type == "file": pio.write_html( figure, filename, config=config, auto_play=auto_play, include_plotlyjs=include_plotlyjs, include_mathjax=include_mathjax, post_script=post_script, full_html=True, validate=validate, animation_opts=animation_opts, auto_open=auto_open, ) return filename else: return pio.to_html( figure, config=config, auto_play=auto_play, include_plotlyjs=include_plotlyjs, include_mathjax=include_mathjax, post_script=post_script, full_html=False, validate=validate, animation_opts=animation_opts, ) def plot_mpl( mpl_fig, resize=False, strip_style=False, verbose=False, show_link=False, link_text="Export to plot.ly", validate=True, output_type="file", include_plotlyjs=True, filename="temp-plot.html", auto_open=True, image=None, image_filename="plot_image", image_height=600, image_width=800, ): """ Convert a matplotlib figure to a Plotly graph stored locally as HTML. For more information on converting matplotlib visualizations to plotly graphs, call help(plotly.tools.mpl_to_plotly) For more information on creating plotly charts locally as an HTML document or string, call help(plotly.offline.plot) mpl_fig -- a matplotlib figure object to convert to a plotly graph Keyword arguments: resize (default=False) -- allow plotly to choose the figure size. strip_style (default=False) -- allow plotly to choose style options. verbose (default=False) -- print message. show_link (default=False) -- display a link in the bottom-right corner of of the chart that will export the chart to Plotly Cloud or Plotly Enterprise link_text (default='Export to plot.ly') -- the text of export link validate (default=True) -- validate that all of the keys in the figure are valid? omit if your version of plotly.js has become outdated with your version of graph_reference.json or if you need to include extra, unnecessary keys in your figure. output_type ('file' | 'div' - default 'file') -- if 'file', then the graph is saved as a standalone HTML file and `plot` returns None. If 'div', then `plot` returns a string that just contains the HTML
that contains the graph and the script to generate the graph. Use 'file' if you want to save and view a single graph at a time in a standalone HTML file. Use 'div' if you are embedding these graphs in an HTML file with other graphs or HTML markup, like a HTML report or an website. include_plotlyjs (default=True) -- If True, include the plotly.js source code in the output file or string. Set as False if your HTML file already contains a copy of the plotly.js library. filename (default='temp-plot.html') -- The local filename to save the outputted chart to. If the filename already exists, it will be overwritten. This argument only applies if `output_type` is 'file'. auto_open (default=True) -- If True, open the saved file in a web browser after saving. This argument only applies if `output_type` is 'file'. image (default=None |'png' |'jpeg' |'svg' |'webp') -- This parameter sets the format of the image to be downloaded, if we choose to download an image. This parameter has a default value of None indicating that no image should be downloaded. image_filename (default='plot_image') -- Sets the name of the file your image will be saved to. The extension should not be included. image_height (default=600) -- Specifies the height of the image in `px`. image_width (default=800) -- Specifies the width of the image in `px`. Example: ``` from plotly.offline import init_notebook_mode, plot_mpl import matplotlib.pyplot as plt init_notebook_mode() fig = plt.figure() x = [10, 15, 20, 25, 30] y = [100, 250, 200, 150, 300] plt.plot(x, y, "o") plot_mpl(fig) # If you want to to download an image of the figure as well plot_mpl(fig, image='png') ``` """ plotly_plot = plotly.tools.mpl_to_plotly(mpl_fig, resize, strip_style, verbose) return plot( plotly_plot, show_link, link_text, validate, output_type, include_plotlyjs, filename, auto_open, image=image, image_filename=image_filename, image_height=image_height, image_width=image_width, ) def iplot_mpl( mpl_fig, resize=False, strip_style=False, verbose=False, show_link=False, link_text="Export to plot.ly", validate=True, image=None, image_filename="plot_image", image_height=600, image_width=800, ): """ Convert a matplotlib figure to a plotly graph and plot inside an IPython notebook without connecting to an external server. To save the chart to Plotly Cloud or Plotly Enterprise, use `plotly.plotly.plot_mpl`. For more information on converting matplotlib visualizations to plotly graphs call `help(plotly.tools.mpl_to_plotly)` For more information on plotting plotly charts offline in an Ipython notebook call `help(plotly.offline.iplot)` mpl_fig -- a matplotlib.figure to convert to a plotly graph Keyword arguments: resize (default=False) -- allow plotly to choose the figure size. strip_style (default=False) -- allow plotly to choose style options. verbose (default=False) -- print message. show_link (default=False) -- display a link in the bottom-right corner of of the chart that will export the chart to Plotly Cloud or Plotly Enterprise link_text (default='Export to plot.ly') -- the text of export link validate (default=True) -- validate that all of the keys in the figure are valid? omit if your version of plotly.js has become outdated with your version of graph_reference.json or if you need to include extra, unnecessary keys in your figure. image (default=None |'png' |'jpeg' |'svg' |'webp') -- This parameter sets the format of the image to be downloaded, if we choose to download an image. This parameter has a default value of None indicating that no image should be downloaded. image_filename (default='plot_image') -- Sets the name of the file your image will be saved to. The extension should not be included. image_height (default=600) -- Specifies the height of the image in `px`. image_width (default=800) -- Specifies the width of the image in `px`. Example: ``` from plotly.offline import init_notebook_mode, iplot_mpl import matplotlib.pyplot as plt fig = plt.figure() x = [10, 15, 20, 25, 30] y = [100, 250, 200, 150, 300] plt.plot(x, y, "o") init_notebook_mode() iplot_mpl(fig) # and if you want to download an image of the figure as well iplot_mpl(fig, image='jpeg') ``` """ plotly_plot = plotly.tools.mpl_to_plotly(mpl_fig, resize, strip_style, verbose) return iplot( plotly_plot, show_link, link_text, validate, image=image, filename=image_filename, image_height=image_height, image_width=image_width, ) def enable_mpl_offline( resize=False, strip_style=False, verbose=False, show_link=False, link_text="Export to plot.ly", validate=True, ): """ Convert mpl plots to locally hosted HTML documents. This function should be used with the inline matplotlib backend that ships with IPython that can be enabled with `%pylab inline` or `%matplotlib inline`. This works by adding an HTML formatter for Figure objects; the existing SVG/PNG formatters will remain enabled. (idea taken from `mpld3._display.enable_notebook`) Example: ``` from plotly.offline import enable_mpl_offline import matplotlib.pyplot as plt enable_mpl_offline() fig = plt.figure() x = [10, 15, 20, 25, 30] y = [100, 250, 200, 150, 300] plt.plot(x, y, "o") fig ``` """ init_notebook_mode() ipython = get_module("IPython") matplotlib = get_module("matplotlib") ip = ipython.core.getipython.get_ipython() formatter = ip.display_formatter.formatters["text/html"] formatter.for_type( matplotlib.figure.Figure, lambda fig: iplot_mpl( fig, resize, strip_style, verbose, show_link, link_text, validate ), ) plotly-4.4.1+dfsg.orig/plotly/offline/_plotlyjs_version.py0000644000175000017500000000015413573717677023403 0ustar noahfxnoahfx# DO NOT EDIT # This file is generated by the updatebundle setup.py command __plotlyjs_version__ = "1.51.2" plotly-4.4.1+dfsg.orig/plotly/figure_factory/0000755000175000017500000000000013573746613020623 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/figure_factory/_annotated_heatmap.py0000644000175000017500000002372313573717677025027 0ustar noahfxnoahfxfrom __future__ import absolute_import, division from plotly import exceptions, optional_imports import plotly.colors as clrs from plotly.figure_factory import utils from plotly.graph_objs import graph_objs from plotly.validators.heatmap import ColorscaleValidator # Optional imports, may be None for users that only use our core functionality. np = optional_imports.get_module("numpy") def validate_annotated_heatmap(z, x, y, annotation_text): """ Annotated-heatmap-specific validations Check that if a text matrix is supplied, it has the same dimensions as the z matrix. See FigureFactory.create_annotated_heatmap() for params :raises: (PlotlyError) If z and text matrices do not have the same dimensions. """ if annotation_text is not None and isinstance(annotation_text, list): utils.validate_equal_length(z, annotation_text) for lst in range(len(z)): if len(z[lst]) != len(annotation_text[lst]): raise exceptions.PlotlyError( "z and text should have the " "same dimensions" ) if x: if len(x) != len(z[0]): raise exceptions.PlotlyError( "oops, the x list that you " "provided does not match the " "width of your z matrix " ) if y: if len(y) != len(z): raise exceptions.PlotlyError( "oops, the y list that you " "provided does not match the " "length of your z matrix " ) def create_annotated_heatmap( z, x=None, y=None, annotation_text=None, colorscale="Plasma", font_colors=None, showscale=False, reversescale=False, **kwargs ): """ Function that creates annotated heatmaps This function adds annotations to each cell of the heatmap. :param (list[list]|ndarray) z: z matrix to create heatmap. :param (list) x: x axis labels. :param (list) y: y axis labels. :param (list[list]|ndarray) annotation_text: Text strings for annotations. Should have the same dimensions as the z matrix. If no text is added, the values of the z matrix are annotated. Default = z matrix values. :param (list|str) colorscale: heatmap colorscale. :param (list) font_colors: List of two color strings: [min_text_color, max_text_color] where min_text_color is applied to annotations for heatmap values < (max_value - min_value)/2. If font_colors is not defined, the colors are defined logically as black or white depending on the heatmap's colorscale. :param (bool) showscale: Display colorscale. Default = False :param (bool) reversescale: Reverse colorscale. Default = False :param kwargs: kwargs passed through plotly.graph_objs.Heatmap. These kwargs describe other attributes about the annotated Heatmap trace such as the colorscale. For more information on valid kwargs call help(plotly.graph_objs.Heatmap) Example 1: Simple annotated heatmap with default configuration >>> import plotly.figure_factory as ff >>> z = [[0.300000, 0.00000, 0.65, 0.300000], ... [1, 0.100005, 0.45, 0.4300], ... [0.300000, 0.00000, 0.65, 0.300000], ... [1, 0.100005, 0.45, 0.00000]] >>> fig = ff.create_annotated_heatmap(z) >>> fig.show() """ # Avoiding mutables in the call signature font_colors = font_colors if font_colors is not None else [] validate_annotated_heatmap(z, x, y, annotation_text) # validate colorscale colorscale_validator = ColorscaleValidator() colorscale = colorscale_validator.validate_coerce(colorscale) annotations = _AnnotatedHeatmap( z, x, y, annotation_text, colorscale, font_colors, reversescale, **kwargs ).make_annotations() if x or y: trace = dict( type="heatmap", z=z, x=x, y=y, colorscale=colorscale, showscale=showscale, reversescale=reversescale, **kwargs ) layout = dict( annotations=annotations, xaxis=dict(ticks="", dtick=1, side="top", gridcolor="rgb(0, 0, 0)"), yaxis=dict(ticks="", dtick=1, ticksuffix=" "), ) else: trace = dict( type="heatmap", z=z, colorscale=colorscale, showscale=showscale, reversescale=reversescale, **kwargs ) layout = dict( annotations=annotations, xaxis=dict( ticks="", side="top", gridcolor="rgb(0, 0, 0)", showticklabels=False ), yaxis=dict(ticks="", ticksuffix=" ", showticklabels=False), ) data = [trace] return graph_objs.Figure(data=data, layout=layout) def to_rgb_color_list(color_str, default): if "rgb" in color_str: return [int(v) for v in color_str.strip("rgb()").split(",")] elif "#" in color_str: return clrs.hex_to_rgb(color_str) else: return default def should_use_black_text(background_color): return ( background_color[0] * 0.299 + background_color[1] * 0.587 + background_color[2] * 0.114 ) > 186 class _AnnotatedHeatmap(object): """ Refer to TraceFactory.create_annotated_heatmap() for docstring """ def __init__( self, z, x, y, annotation_text, colorscale, font_colors, reversescale, **kwargs ): self.z = z if x: self.x = x else: self.x = range(len(z[0])) if y: self.y = y else: self.y = range(len(z)) if annotation_text is not None: self.annotation_text = annotation_text else: self.annotation_text = self.z self.colorscale = colorscale self.reversescale = reversescale self.font_colors = font_colors def get_text_color(self): """ Get font color for annotations. The annotated heatmap can feature two text colors: min_text_color and max_text_color. The min_text_color is applied to annotations for heatmap values < (max_value - min_value)/2. The user can define these two colors. Otherwise the colors are defined logically as black or white depending on the heatmap's colorscale. :rtype (string, string) min_text_color, max_text_color: text color for annotations for heatmap values < (max_value - min_value)/2 and text color for annotations for heatmap values >= (max_value - min_value)/2 """ # Plotly colorscales ranging from a lighter shade to a darker shade colorscales = [ "Greys", "Greens", "Blues", "YIGnBu", "YIOrRd", "RdBu", "Picnic", "Jet", "Hot", "Blackbody", "Earth", "Electric", "Viridis", "Cividis", ] # Plotly colorscales ranging from a darker shade to a lighter shade colorscales_reverse = ["Reds"] white = "#FFFFFF" black = "#000000" if self.font_colors: min_text_color = self.font_colors[0] max_text_color = self.font_colors[-1] elif self.colorscale in colorscales and self.reversescale: min_text_color = black max_text_color = white elif self.colorscale in colorscales: min_text_color = white max_text_color = black elif self.colorscale in colorscales_reverse and self.reversescale: min_text_color = white max_text_color = black elif self.colorscale in colorscales_reverse: min_text_color = black max_text_color = white elif isinstance(self.colorscale, list): min_col = to_rgb_color_list(self.colorscale[0][1], [255, 255, 255]) max_col = to_rgb_color_list(self.colorscale[-1][1], [255, 255, 255]) # swap min/max colors if reverse scale if self.reversescale: min_col, max_col = max_col, min_col if should_use_black_text(min_col): min_text_color = black else: min_text_color = white if should_use_black_text(max_col): max_text_color = black else: max_text_color = white else: min_text_color = black max_text_color = black return min_text_color, max_text_color def get_z_mid(self): """ Get the mid value of z matrix :rtype (float) z_avg: average val from z matrix """ if np and isinstance(self.z, np.ndarray): z_min = np.amin(self.z) z_max = np.amax(self.z) else: z_min = min([v for row in self.z for v in row]) z_max = max([v for row in self.z for v in row]) z_mid = (z_max + z_min) / 2 return z_mid def make_annotations(self): """ Get annotations for each cell of the heatmap with graph_objs.Annotation :rtype (list[dict]) annotations: list of annotations for each cell of the heatmap """ min_text_color, max_text_color = _AnnotatedHeatmap.get_text_color(self) z_mid = _AnnotatedHeatmap.get_z_mid(self) annotations = [] for n, row in enumerate(self.z): for m, val in enumerate(row): font_color = min_text_color if val < z_mid else max_text_color annotations.append( graph_objs.layout.Annotation( text=str(self.annotation_text[n][m]), x=self.x[m], y=self.y[n], xref="x1", yref="y1", font=dict(color=font_color), showarrow=False, ) ) return annotations plotly-4.4.1+dfsg.orig/plotly/figure_factory/_candlestick.py0000644000175000017500000002353613573717677023641 0ustar noahfxnoahfxfrom __future__ import absolute_import from plotly.figure_factory import utils from plotly.figure_factory._ohlc import ( _DEFAULT_INCREASING_COLOR, _DEFAULT_DECREASING_COLOR, validate_ohlc, ) from plotly.graph_objs import graph_objs def make_increasing_candle(open, high, low, close, dates, **kwargs): """ Makes boxplot trace for increasing candlesticks _make_increasing_candle() and _make_decreasing_candle separate the increasing traces from the decreasing traces so kwargs (such as color) can be passed separately to increasing or decreasing traces when direction is set to 'increasing' or 'decreasing' in FigureFactory.create_candlestick() :param (list) open: opening values :param (list) high: high values :param (list) low: low values :param (list) close: closing values :param (list) dates: list of datetime objects. Default: None :param kwargs: kwargs to be passed to increasing trace via plotly.graph_objs.Scatter. :rtype (list) candle_incr_data: list of the box trace for increasing candlesticks. """ increase_x, increase_y = _Candlestick( open, high, low, close, dates, **kwargs ).get_candle_increase() if "line" in kwargs: kwargs.setdefault("fillcolor", kwargs["line"]["color"]) else: kwargs.setdefault("fillcolor", _DEFAULT_INCREASING_COLOR) if "name" in kwargs: kwargs.setdefault("showlegend", True) else: kwargs.setdefault("showlegend", False) kwargs.setdefault("name", "Increasing") kwargs.setdefault("line", dict(color=_DEFAULT_INCREASING_COLOR)) candle_incr_data = dict( type="box", x=increase_x, y=increase_y, whiskerwidth=0, boxpoints=False, **kwargs ) return [candle_incr_data] def make_decreasing_candle(open, high, low, close, dates, **kwargs): """ Makes boxplot trace for decreasing candlesticks :param (list) open: opening values :param (list) high: high values :param (list) low: low values :param (list) close: closing values :param (list) dates: list of datetime objects. Default: None :param kwargs: kwargs to be passed to decreasing trace via plotly.graph_objs.Scatter. :rtype (list) candle_decr_data: list of the box trace for decreasing candlesticks. """ decrease_x, decrease_y = _Candlestick( open, high, low, close, dates, **kwargs ).get_candle_decrease() if "line" in kwargs: kwargs.setdefault("fillcolor", kwargs["line"]["color"]) else: kwargs.setdefault("fillcolor", _DEFAULT_DECREASING_COLOR) kwargs.setdefault("showlegend", False) kwargs.setdefault("line", dict(color=_DEFAULT_DECREASING_COLOR)) kwargs.setdefault("name", "Decreasing") candle_decr_data = dict( type="box", x=decrease_x, y=decrease_y, whiskerwidth=0, boxpoints=False, **kwargs ) return [candle_decr_data] def create_candlestick(open, high, low, close, dates=None, direction="both", **kwargs): """ **deprecated**, use instead the plotly.graph_objects trace :class:`plotly.graph_objects.Candlestick` :param (list) open: opening values :param (list) high: high values :param (list) low: low values :param (list) close: closing values :param (list) dates: list of datetime objects. Default: None :param (string) direction: direction can be 'increasing', 'decreasing', or 'both'. When the direction is 'increasing', the returned figure consists of all candlesticks where the close value is greater than the corresponding open value, and when the direction is 'decreasing', the returned figure consists of all candlesticks where the close value is less than or equal to the corresponding open value. When the direction is 'both', both increasing and decreasing candlesticks are returned. Default: 'both' :param kwargs: kwargs passed through plotly.graph_objs.Scatter. These kwargs describe other attributes about the ohlc Scatter trace such as the color or the legend name. For more information on valid kwargs call help(plotly.graph_objs.Scatter) :rtype (dict): returns a representation of candlestick chart figure. Example 1: Simple candlestick chart from a Pandas DataFrame >>> from plotly.figure_factory import create_candlestick >>> from datetime import datetime >>> import pandas as pd >>> df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/finance-charts-apple.csv') >>> fig = create_candlestick(df['AAPL.Open'], df['AAPL.High'], df['AAPL.Low'], df['AAPL.Close'], ... dates=df.index) >>> fig.show() Example 2: Customize the candlestick colors >>> from plotly.figure_factory import create_candlestick >>> from plotly.graph_objs import Line, Marker >>> from datetime import datetime >>> import pandas as pd >>> df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/finance-charts-apple.csv') >>> # Make increasing candlesticks and customize their color and name >>> fig_increasing = create_candlestick(df['AAPL.Open'], df['AAPL.High'], df['AAPL.Low'], df['AAPL.Close'], ... dates=df.index, ... direction='increasing', name='AAPL', ... marker=Marker(color='rgb(150, 200, 250)'), ... line=Line(color='rgb(150, 200, 250)')) >>> # Make decreasing candlesticks and customize their color and name >>> fig_decreasing = create_candlestick(df['AAPL.Open'], df['AAPL.High'], df['AAPL.Low'], df['AAPL.Close'], ... dates=df.index, ... direction='decreasing', ... marker=Marker(color='rgb(128, 128, 128)'), ... line=Line(color='rgb(128, 128, 128)')) >>> # Initialize the figure >>> fig = fig_increasing >>> # Add decreasing data with .extend() >>> fig.add_trace(fig_decreasing['data']) # doctest: +SKIP >>> fig.show() Example 3: Candlestick chart with datetime objects >>> from plotly.figure_factory import create_candlestick >>> from datetime import datetime >>> # Add data >>> open_data = [33.0, 33.3, 33.5, 33.0, 34.1] >>> high_data = [33.1, 33.3, 33.6, 33.2, 34.8] >>> low_data = [32.7, 32.7, 32.8, 32.6, 32.8] >>> close_data = [33.0, 32.9, 33.3, 33.1, 33.1] >>> dates = [datetime(year=2013, month=10, day=10), ... datetime(year=2013, month=11, day=10), ... datetime(year=2013, month=12, day=10), ... datetime(year=2014, month=1, day=10), ... datetime(year=2014, month=2, day=10)] >>> # Create ohlc >>> fig = create_candlestick(open_data, high_data, ... low_data, close_data, dates=dates) >>> fig.show() """ if dates is not None: utils.validate_equal_length(open, high, low, close, dates) else: utils.validate_equal_length(open, high, low, close) validate_ohlc(open, high, low, close, direction, **kwargs) if direction is "increasing": candle_incr_data = make_increasing_candle( open, high, low, close, dates, **kwargs ) data = candle_incr_data elif direction is "decreasing": candle_decr_data = make_decreasing_candle( open, high, low, close, dates, **kwargs ) data = candle_decr_data else: candle_incr_data = make_increasing_candle( open, high, low, close, dates, **kwargs ) candle_decr_data = make_decreasing_candle( open, high, low, close, dates, **kwargs ) data = candle_incr_data + candle_decr_data layout = graph_objs.Layout() return graph_objs.Figure(data=data, layout=layout) class _Candlestick(object): """ Refer to FigureFactory.create_candlestick() for docstring. """ def __init__(self, open, high, low, close, dates, **kwargs): self.open = open self.high = high self.low = low self.close = close if dates is not None: self.x = dates else: self.x = [x for x in range(len(self.open))] self.get_candle_increase() def get_candle_increase(self): """ Separate increasing data from decreasing data. The data is increasing when close value > open value and decreasing when the close value <= open value. """ increase_y = [] increase_x = [] for index in range(len(self.open)): if self.close[index] > self.open[index]: increase_y.append(self.low[index]) increase_y.append(self.open[index]) increase_y.append(self.close[index]) increase_y.append(self.close[index]) increase_y.append(self.close[index]) increase_y.append(self.high[index]) increase_x.append(self.x[index]) increase_x = [[x, x, x, x, x, x] for x in increase_x] increase_x = utils.flatten(increase_x) return increase_x, increase_y def get_candle_decrease(self): """ Separate increasing data from decreasing data. The data is increasing when close value > open value and decreasing when the close value <= open value. """ decrease_y = [] decrease_x = [] for index in range(len(self.open)): if self.close[index] <= self.open[index]: decrease_y.append(self.low[index]) decrease_y.append(self.open[index]) decrease_y.append(self.close[index]) decrease_y.append(self.close[index]) decrease_y.append(self.close[index]) decrease_y.append(self.high[index]) decrease_x.append(self.x[index]) decrease_x = [[x, x, x, x, x, x] for x in decrease_x] decrease_x = utils.flatten(decrease_x) return decrease_x, decrease_y plotly-4.4.1+dfsg.orig/plotly/figure_factory/_table.py0000644000175000017500000002237113573717677022440 0ustar noahfxnoahfxfrom __future__ import absolute_import from plotly import exceptions, optional_imports from plotly.graph_objs import graph_objs pd = optional_imports.get_module("pandas") def validate_table(table_text, font_colors): """ Table-specific validations Check that font_colors is supplied correctly (1, 3, or len(text) colors). :raises: (PlotlyError) If font_colors is supplied incorretly. See FigureFactory.create_table() for params """ font_colors_len_options = [1, 3, len(table_text)] if len(font_colors) not in font_colors_len_options: raise exceptions.PlotlyError( "Oops, font_colors should be a list " "of length 1, 3 or len(text)" ) def create_table( table_text, colorscale=None, font_colors=None, index=False, index_title="", annotation_offset=0.45, height_constant=30, hoverinfo="none", **kwargs ): """ Function that creates data tables. See also the plotly.graph_objects trace :class:`plotly.graph_objects.Table` :param (pandas.Dataframe | list[list]) text: data for table. :param (str|list[list]) colorscale: Colorscale for table where the color at value 0 is the header color, .5 is the first table color and 1 is the second table color. (Set .5 and 1 to avoid the striped table effect). Default=[[0, '#66b2ff'], [.5, '#d9d9d9'], [1, '#ffffff']] :param (list) font_colors: Color for fonts in table. Can be a single color, three colors, or a color for each row in the table. Default=['#000000'] (black text for the entire table) :param (int) height_constant: Constant multiplied by # of rows to create table height. Default=30. :param (bool) index: Create (header-colored) index column index from Pandas dataframe or list[0] for each list in text. Default=False. :param (string) index_title: Title for index column. Default=''. :param kwargs: kwargs passed through plotly.graph_objs.Heatmap. These kwargs describe other attributes about the annotated Heatmap trace such as the colorscale. For more information on valid kwargs call help(plotly.graph_objs.Heatmap) Example 1: Simple Plotly Table >>> from plotly.figure_factory import create_table >>> text = [['Country', 'Year', 'Population'], ... ['US', 2000, 282200000], ... ['Canada', 2000, 27790000], ... ['US', 2010, 309000000], ... ['Canada', 2010, 34000000]] >>> table = create_table(text) >>> table.show() Example 2: Table with Custom Coloring >>> from plotly.figure_factory import create_table >>> text = [['Country', 'Year', 'Population'], ... ['US', 2000, 282200000], ... ['Canada', 2000, 27790000], ... ['US', 2010, 309000000], ... ['Canada', 2010, 34000000]] >>> table = create_table(text, ... colorscale=[[0, '#000000'], ... [.5, '#80beff'], ... [1, '#cce5ff']], ... font_colors=['#ffffff', '#000000', ... '#000000']) >>> table.show() Example 3: Simple Plotly Table with Pandas >>> from plotly.figure_factory import create_table >>> import pandas as pd >>> df = pd.read_csv('http://www.stat.ubc.ca/~jenny/notOcto/STAT545A/examples/gapminder/data/gapminderDataFiveYear.txt', sep='\t') >>> df_p = df[0:25] >>> table_simple = create_table(df_p) >>> table_simple.show() """ # Avoiding mutables in the call signature colorscale = ( colorscale if colorscale is not None else [[0, "#00083e"], [0.5, "#ededee"], [1, "#ffffff"]] ) font_colors = ( font_colors if font_colors is not None else ["#ffffff", "#000000", "#000000"] ) validate_table(table_text, font_colors) table_matrix = _Table( table_text, colorscale, font_colors, index, index_title, annotation_offset, **kwargs ).get_table_matrix() annotations = _Table( table_text, colorscale, font_colors, index, index_title, annotation_offset, **kwargs ).make_table_annotations() trace = dict( type="heatmap", z=table_matrix, opacity=0.75, colorscale=colorscale, showscale=False, hoverinfo=hoverinfo, **kwargs ) data = [trace] layout = dict( annotations=annotations, height=len(table_matrix) * height_constant + 50, margin=dict(t=0, b=0, r=0, l=0), yaxis=dict( autorange="reversed", zeroline=False, gridwidth=2, ticks="", dtick=1, tick0=0.5, showticklabels=False, ), xaxis=dict( zeroline=False, gridwidth=2, ticks="", dtick=1, tick0=-0.5, showticklabels=False, ), ) return graph_objs.Figure(data=data, layout=layout) class _Table(object): """ Refer to TraceFactory.create_table() for docstring """ def __init__( self, table_text, colorscale, font_colors, index, index_title, annotation_offset, **kwargs ): if pd and isinstance(table_text, pd.DataFrame): headers = table_text.columns.tolist() table_text_index = table_text.index.tolist() table_text = table_text.values.tolist() table_text.insert(0, headers) if index: table_text_index.insert(0, index_title) for i in range(len(table_text)): table_text[i].insert(0, table_text_index[i]) self.table_text = table_text self.colorscale = colorscale self.font_colors = font_colors self.index = index self.annotation_offset = annotation_offset self.x = range(len(table_text[0])) self.y = range(len(table_text)) def get_table_matrix(self): """ Create z matrix to make heatmap with striped table coloring :rtype (list[list]) table_matrix: z matrix to make heatmap with striped table coloring. """ header = [0] * len(self.table_text[0]) odd_row = [0.5] * len(self.table_text[0]) even_row = [1] * len(self.table_text[0]) table_matrix = [None] * len(self.table_text) table_matrix[0] = header for i in range(1, len(self.table_text), 2): table_matrix[i] = odd_row for i in range(2, len(self.table_text), 2): table_matrix[i] = even_row if self.index: for array in table_matrix: array[0] = 0 return table_matrix def get_table_font_color(self): """ Fill font-color array. Table text color can vary by row so this extends a single color or creates an array to set a header color and two alternating colors to create the striped table pattern. :rtype (list[list]) all_font_colors: list of font colors for each row in table. """ if len(self.font_colors) == 1: all_font_colors = self.font_colors * len(self.table_text) elif len(self.font_colors) == 3: all_font_colors = list(range(len(self.table_text))) all_font_colors[0] = self.font_colors[0] for i in range(1, len(self.table_text), 2): all_font_colors[i] = self.font_colors[1] for i in range(2, len(self.table_text), 2): all_font_colors[i] = self.font_colors[2] elif len(self.font_colors) == len(self.table_text): all_font_colors = self.font_colors else: all_font_colors = ["#000000"] * len(self.table_text) return all_font_colors def make_table_annotations(self): """ Generate annotations to fill in table text :rtype (list) annotations: list of annotations for each cell of the table. """ table_matrix = _Table.get_table_matrix(self) all_font_colors = _Table.get_table_font_color(self) annotations = [] for n, row in enumerate(self.table_text): for m, val in enumerate(row): # Bold text in header and index format_text = ( "" + str(val) + "" if n == 0 or self.index and m < 1 else str(val) ) # Match font color of index to font color of header font_color = ( self.font_colors[0] if self.index and m == 0 else all_font_colors[n] ) annotations.append( graph_objs.layout.Annotation( text=format_text, x=self.x[m] - self.annotation_offset, y=self.y[n], xref="x1", yref="y1", align="left", xanchor="left", font=dict(color=font_color), showarrow=False, ) ) return annotations plotly-4.4.1+dfsg.orig/plotly/figure_factory/_distplot.py0000644000175000017500000003324713573717677023217 0ustar noahfxnoahfxfrom __future__ import absolute_import from plotly import exceptions, optional_imports from plotly.figure_factory import utils from plotly.graph_objs import graph_objs # Optional imports, may be None for users that only use our core functionality. np = optional_imports.get_module("numpy") pd = optional_imports.get_module("pandas") scipy = optional_imports.get_module("scipy") scipy_stats = optional_imports.get_module("scipy.stats") DEFAULT_HISTNORM = "probability density" ALTERNATIVE_HISTNORM = "probability" def validate_distplot(hist_data, curve_type): """ Distplot-specific validations :raises: (PlotlyError) If hist_data is not a list of lists :raises: (PlotlyError) If curve_type is not valid (i.e. not 'kde' or 'normal'). """ hist_data_types = (list,) if np: hist_data_types += (np.ndarray,) if pd: hist_data_types += (pd.core.series.Series,) if not isinstance(hist_data[0], hist_data_types): raise exceptions.PlotlyError( "Oops, this function was written " "to handle multiple datasets, if " "you want to plot just one, make " "sure your hist_data variable is " "still a list of lists, i.e. x = " "[1, 2, 3] -> x = [[1, 2, 3]]" ) curve_opts = ("kde", "normal") if curve_type not in curve_opts: raise exceptions.PlotlyError( "curve_type must be defined as " "'kde' or 'normal'" ) if not scipy: raise ImportError("FigureFactory.create_distplot requires scipy") def create_distplot( hist_data, group_labels, bin_size=1.0, curve_type="kde", colors=None, rug_text=None, histnorm=DEFAULT_HISTNORM, show_hist=True, show_curve=True, show_rug=True, ): """ Function that creates a distplot similar to seaborn.distplot; **this function is deprecated**, use instead :mod:`plotly.express` functions, for example >>> import plotly.express as px >>> tips = px.data.tips() >>> fig = px.histogram(tips, x="total_bill", y="tip", color="sex", marginal="rug", ... hover_data=tips.columns) >>> fig.show() The distplot can be composed of all or any combination of the following 3 components: (1) histogram, (2) curve: (a) kernel density estimation or (b) normal curve, and (3) rug plot. Additionally, multiple distplots (from multiple datasets) can be created in the same plot. :param (list[list]) hist_data: Use list of lists to plot multiple data sets on the same plot. :param (list[str]) group_labels: Names for each data set. :param (list[float]|float) bin_size: Size of histogram bins. Default = 1. :param (str) curve_type: 'kde' or 'normal'. Default = 'kde' :param (str) histnorm: 'probability density' or 'probability' Default = 'probability density' :param (bool) show_hist: Add histogram to distplot? Default = True :param (bool) show_curve: Add curve to distplot? Default = True :param (bool) show_rug: Add rug to distplot? Default = True :param (list[str]) colors: Colors for traces. :param (list[list]) rug_text: Hovertext values for rug_plot, :return (dict): Representation of a distplot figure. Example 1: Simple distplot of 1 data set >>> from plotly.figure_factory import create_distplot >>> hist_data = [[1.1, 1.1, 2.5, 3.0, 3.5, ... 3.5, 4.1, 4.4, 4.5, 4.5, ... 5.0, 5.0, 5.2, 5.5, 5.5, ... 5.5, 5.5, 5.5, 6.1, 7.0]] >>> group_labels = ['distplot example'] >>> fig = create_distplot(hist_data, group_labels) >>> fig.show() Example 2: Two data sets and added rug text >>> from plotly.figure_factory import create_distplot >>> # Add histogram data >>> hist1_x = [0.8, 1.2, 0.2, 0.6, 1.6, ... -0.9, -0.07, 1.95, 0.9, -0.2, ... -0.5, 0.3, 0.4, -0.37, 0.6] >>> hist2_x = [0.8, 1.5, 1.5, 0.6, 0.59, ... 1.0, 0.8, 1.7, 0.5, 0.8, ... -0.3, 1.2, 0.56, 0.3, 2.2] >>> # Group data together >>> hist_data = [hist1_x, hist2_x] >>> group_labels = ['2012', '2013'] >>> # Add text >>> rug_text_1 = ['a1', 'b1', 'c1', 'd1', 'e1', ... 'f1', 'g1', 'h1', 'i1', 'j1', ... 'k1', 'l1', 'm1', 'n1', 'o1'] >>> rug_text_2 = ['a2', 'b2', 'c2', 'd2', 'e2', ... 'f2', 'g2', 'h2', 'i2', 'j2', ... 'k2', 'l2', 'm2', 'n2', 'o2'] >>> # Group text together >>> rug_text_all = [rug_text_1, rug_text_2] >>> # Create distplot >>> fig = create_distplot( ... hist_data, group_labels, rug_text=rug_text_all, bin_size=.2) >>> # Add title >>> fig.update_layout(title='Dist Plot') # doctest: +SKIP >>> fig.show() Example 3: Plot with normal curve and hide rug plot >>> from plotly.figure_factory import create_distplot >>> import numpy as np >>> x1 = np.random.randn(190) >>> x2 = np.random.randn(200)+1 >>> x3 = np.random.randn(200)-1 >>> x4 = np.random.randn(210)+2 >>> hist_data = [x1, x2, x3, x4] >>> group_labels = ['2012', '2013', '2014', '2015'] >>> fig = create_distplot( ... hist_data, group_labels, curve_type='normal', ... show_rug=False, bin_size=.4) Example 4: Distplot with Pandas >>> from plotly.figure_factory import create_distplot >>> import numpy as np >>> import pandas as pd >>> df = pd.DataFrame({'2012': np.random.randn(200), ... '2013': np.random.randn(200)+1}) >>> fig = create_distplot([df[c] for c in df.columns], df.columns) >>> fig.show() """ if colors is None: colors = [] if rug_text is None: rug_text = [] validate_distplot(hist_data, curve_type) utils.validate_equal_length(hist_data, group_labels) if isinstance(bin_size, (float, int)): bin_size = [bin_size] * len(hist_data) hist = _Distplot( hist_data, histnorm, group_labels, bin_size, curve_type, colors, rug_text, show_hist, show_curve, ).make_hist() if curve_type == "normal": curve = _Distplot( hist_data, histnorm, group_labels, bin_size, curve_type, colors, rug_text, show_hist, show_curve, ).make_normal() else: curve = _Distplot( hist_data, histnorm, group_labels, bin_size, curve_type, colors, rug_text, show_hist, show_curve, ).make_kde() rug = _Distplot( hist_data, histnorm, group_labels, bin_size, curve_type, colors, rug_text, show_hist, show_curve, ).make_rug() data = [] if show_hist: data.append(hist) if show_curve: data.append(curve) if show_rug: data.append(rug) layout = graph_objs.Layout( barmode="overlay", hovermode="closest", legend=dict(traceorder="reversed"), xaxis1=dict(domain=[0.0, 1.0], anchor="y2", zeroline=False), yaxis1=dict(domain=[0.35, 1], anchor="free", position=0.0), yaxis2=dict(domain=[0, 0.25], anchor="x1", dtick=1, showticklabels=False), ) else: layout = graph_objs.Layout( barmode="overlay", hovermode="closest", legend=dict(traceorder="reversed"), xaxis1=dict(domain=[0.0, 1.0], anchor="y2", zeroline=False), yaxis1=dict(domain=[0.0, 1], anchor="free", position=0.0), ) data = sum(data, []) return graph_objs.Figure(data=data, layout=layout) class _Distplot(object): """ Refer to TraceFactory.create_distplot() for docstring """ def __init__( self, hist_data, histnorm, group_labels, bin_size, curve_type, colors, rug_text, show_hist, show_curve, ): self.hist_data = hist_data self.histnorm = histnorm self.group_labels = group_labels self.bin_size = bin_size self.show_hist = show_hist self.show_curve = show_curve self.trace_number = len(hist_data) if rug_text: self.rug_text = rug_text else: self.rug_text = [None] * self.trace_number self.start = [] self.end = [] if colors: self.colors = colors else: self.colors = [ "rgb(31, 119, 180)", "rgb(255, 127, 14)", "rgb(44, 160, 44)", "rgb(214, 39, 40)", "rgb(148, 103, 189)", "rgb(140, 86, 75)", "rgb(227, 119, 194)", "rgb(127, 127, 127)", "rgb(188, 189, 34)", "rgb(23, 190, 207)", ] self.curve_x = [None] * self.trace_number self.curve_y = [None] * self.trace_number for trace in self.hist_data: self.start.append(min(trace) * 1.0) self.end.append(max(trace) * 1.0) def make_hist(self): """ Makes the histogram(s) for FigureFactory.create_distplot(). :rtype (list) hist: list of histogram representations """ hist = [None] * self.trace_number for index in range(self.trace_number): hist[index] = dict( type="histogram", x=self.hist_data[index], xaxis="x1", yaxis="y1", histnorm=self.histnorm, name=self.group_labels[index], legendgroup=self.group_labels[index], marker=dict(color=self.colors[index % len(self.colors)]), autobinx=False, xbins=dict( start=self.start[index], end=self.end[index], size=self.bin_size[index], ), opacity=0.7, ) return hist def make_kde(self): """ Makes the kernel density estimation(s) for create_distplot(). This is called when curve_type = 'kde' in create_distplot(). :rtype (list) curve: list of kde representations """ curve = [None] * self.trace_number for index in range(self.trace_number): self.curve_x[index] = [ self.start[index] + x * (self.end[index] - self.start[index]) / 500 for x in range(500) ] self.curve_y[index] = scipy_stats.gaussian_kde(self.hist_data[index])( self.curve_x[index] ) if self.histnorm == ALTERNATIVE_HISTNORM: self.curve_y[index] *= self.bin_size[index] for index in range(self.trace_number): curve[index] = dict( type="scatter", x=self.curve_x[index], y=self.curve_y[index], xaxis="x1", yaxis="y1", mode="lines", name=self.group_labels[index], legendgroup=self.group_labels[index], showlegend=False if self.show_hist else True, marker=dict(color=self.colors[index % len(self.colors)]), ) return curve def make_normal(self): """ Makes the normal curve(s) for create_distplot(). This is called when curve_type = 'normal' in create_distplot(). :rtype (list) curve: list of normal curve representations """ curve = [None] * self.trace_number mean = [None] * self.trace_number sd = [None] * self.trace_number for index in range(self.trace_number): mean[index], sd[index] = scipy_stats.norm.fit(self.hist_data[index]) self.curve_x[index] = [ self.start[index] + x * (self.end[index] - self.start[index]) / 500 for x in range(500) ] self.curve_y[index] = scipy_stats.norm.pdf( self.curve_x[index], loc=mean[index], scale=sd[index] ) if self.histnorm == ALTERNATIVE_HISTNORM: self.curve_y[index] *= self.bin_size[index] for index in range(self.trace_number): curve[index] = dict( type="scatter", x=self.curve_x[index], y=self.curve_y[index], xaxis="x1", yaxis="y1", mode="lines", name=self.group_labels[index], legendgroup=self.group_labels[index], showlegend=False if self.show_hist else True, marker=dict(color=self.colors[index % len(self.colors)]), ) return curve def make_rug(self): """ Makes the rug plot(s) for create_distplot(). :rtype (list) rug: list of rug plot representations """ rug = [None] * self.trace_number for index in range(self.trace_number): rug[index] = dict( type="scatter", x=self.hist_data[index], y=([self.group_labels[index]] * len(self.hist_data[index])), xaxis="x1", yaxis="y2", mode="markers", name=self.group_labels[index], legendgroup=self.group_labels[index], showlegend=(False if self.show_hist or self.show_curve else True), text=self.rug_text[index], marker=dict( color=self.colors[index % len(self.colors)], symbol="line-ns-open" ), ) return rug plotly-4.4.1+dfsg.orig/plotly/figure_factory/_streamline.py0000644000175000017500000003443713573717677023522 0ustar noahfxnoahfxfrom __future__ import absolute_import import math from plotly import exceptions, optional_imports from plotly.figure_factory import utils from plotly.graph_objs import graph_objs np = optional_imports.get_module("numpy") def validate_streamline(x, y): """ Streamline-specific validations Specifically, this checks that x and y are both evenly spaced, and that the package numpy is available. See FigureFactory.create_streamline() for params :raises: (ImportError) If numpy is not available. :raises: (PlotlyError) If x is not evenly spaced. :raises: (PlotlyError) If y is not evenly spaced. """ if np is False: raise ImportError("FigureFactory.create_streamline requires numpy") for index in range(len(x) - 1): if ((x[index + 1] - x[index]) - (x[1] - x[0])) > 0.0001: raise exceptions.PlotlyError( "x must be a 1 dimensional, " "evenly spaced array" ) for index in range(len(y) - 1): if ((y[index + 1] - y[index]) - (y[1] - y[0])) > 0.0001: raise exceptions.PlotlyError( "y must be a 1 dimensional, " "evenly spaced array" ) def create_streamline( x, y, u, v, density=1, angle=math.pi / 9, arrow_scale=0.09, **kwargs ): """ Returns data for a streamline plot. :param (list|ndarray) x: 1 dimensional, evenly spaced list or array :param (list|ndarray) y: 1 dimensional, evenly spaced list or array :param (ndarray) u: 2 dimensional array :param (ndarray) v: 2 dimensional array :param (float|int) density: controls the density of streamlines in plot. This is multiplied by 30 to scale similiarly to other available streamline functions such as matplotlib. Default = 1 :param (angle in radians) angle: angle of arrowhead. Default = pi/9 :param (float in [0,1]) arrow_scale: value to scale length of arrowhead Default = .09 :param kwargs: kwargs passed through plotly.graph_objs.Scatter for more information on valid kwargs call help(plotly.graph_objs.Scatter) :rtype (dict): returns a representation of streamline figure. Example 1: Plot simple streamline and increase arrow size >>> from plotly.figure_factory import create_streamline >>> import plotly.graph_objects as go >>> import numpy as np >>> import math >>> # Add data >>> x = np.linspace(-3, 3, 100) >>> y = np.linspace(-3, 3, 100) >>> Y, X = np.meshgrid(x, y) >>> u = -1 - X**2 + Y >>> v = 1 + X - Y**2 >>> u = u.T # Transpose >>> v = v.T # Transpose >>> # Create streamline >>> fig = create_streamline(x, y, u, v, arrow_scale=.1) >>> fig.show() Example 2: from nbviewer.ipython.org/github/barbagroup/AeroPython >>> from plotly.figure_factory import create_streamline >>> import numpy as np >>> import math >>> # Add data >>> N = 50 >>> x_start, x_end = -2.0, 2.0 >>> y_start, y_end = -1.0, 1.0 >>> x = np.linspace(x_start, x_end, N) >>> y = np.linspace(y_start, y_end, N) >>> X, Y = np.meshgrid(x, y) >>> ss = 5.0 >>> x_s, y_s = -1.0, 0.0 >>> # Compute the velocity field on the mesh grid >>> u_s = ss/(2*np.pi) * (X-x_s)/((X-x_s)**2 + (Y-y_s)**2) >>> v_s = ss/(2*np.pi) * (Y-y_s)/((X-x_s)**2 + (Y-y_s)**2) >>> # Create streamline >>> fig = create_streamline(x, y, u_s, v_s, density=2, name='streamline') >>> # Add source point >>> point = go.Scatter(x=[x_s], y=[y_s], mode='markers', ... marker_size=14, name='source point') >>> fig.add_trace(point) # doctest: +SKIP >>> fig.show() """ utils.validate_equal_length(x, y) utils.validate_equal_length(u, v) validate_streamline(x, y) utils.validate_positive_scalars(density=density, arrow_scale=arrow_scale) streamline_x, streamline_y = _Streamline( x, y, u, v, density, angle, arrow_scale ).sum_streamlines() arrow_x, arrow_y = _Streamline( x, y, u, v, density, angle, arrow_scale ).get_streamline_arrows() streamline = graph_objs.Scatter( x=streamline_x + arrow_x, y=streamline_y + arrow_y, mode="lines", **kwargs ) data = [streamline] layout = graph_objs.Layout(hovermode="closest") return graph_objs.Figure(data=data, layout=layout) class _Streamline(object): """ Refer to FigureFactory.create_streamline() for docstring """ def __init__(self, x, y, u, v, density, angle, arrow_scale, **kwargs): self.x = np.array(x) self.y = np.array(y) self.u = np.array(u) self.v = np.array(v) self.angle = angle self.arrow_scale = arrow_scale self.density = int(30 * density) # Scale similarly to other functions self.delta_x = self.x[1] - self.x[0] self.delta_y = self.y[1] - self.y[0] self.val_x = self.x self.val_y = self.y # Set up spacing self.blank = np.zeros((self.density, self.density)) self.spacing_x = len(self.x) / float(self.density - 1) self.spacing_y = len(self.y) / float(self.density - 1) self.trajectories = [] # Rescale speed onto axes-coordinates self.u = self.u / (self.x[-1] - self.x[0]) self.v = self.v / (self.y[-1] - self.y[0]) self.speed = np.sqrt(self.u ** 2 + self.v ** 2) # Rescale u and v for integrations. self.u *= len(self.x) self.v *= len(self.y) self.st_x = [] self.st_y = [] self.get_streamlines() streamline_x, streamline_y = self.sum_streamlines() arrows_x, arrows_y = self.get_streamline_arrows() def blank_pos(self, xi, yi): """ Set up positions for trajectories to be used with rk4 function. """ return (int((xi / self.spacing_x) + 0.5), int((yi / self.spacing_y) + 0.5)) def value_at(self, a, xi, yi): """ Set up for RK4 function, based on Bokeh's streamline code """ if isinstance(xi, np.ndarray): self.x = xi.astype(np.int) self.y = yi.astype(np.int) else: self.val_x = np.int(xi) self.val_y = np.int(yi) a00 = a[self.val_y, self.val_x] a01 = a[self.val_y, self.val_x + 1] a10 = a[self.val_y + 1, self.val_x] a11 = a[self.val_y + 1, self.val_x + 1] xt = xi - self.val_x yt = yi - self.val_y a0 = a00 * (1 - xt) + a01 * xt a1 = a10 * (1 - xt) + a11 * xt return a0 * (1 - yt) + a1 * yt def rk4_integrate(self, x0, y0): """ RK4 forward and back trajectories from the initial conditions. Adapted from Bokeh's streamline -uses Runge-Kutta method to fill x and y trajectories then checks length of traj (s in units of axes) """ def f(xi, yi): dt_ds = 1.0 / self.value_at(self.speed, xi, yi) ui = self.value_at(self.u, xi, yi) vi = self.value_at(self.v, xi, yi) return ui * dt_ds, vi * dt_ds def g(xi, yi): dt_ds = 1.0 / self.value_at(self.speed, xi, yi) ui = self.value_at(self.u, xi, yi) vi = self.value_at(self.v, xi, yi) return -ui * dt_ds, -vi * dt_ds check = lambda xi, yi: (0 <= xi < len(self.x) - 1 and 0 <= yi < len(self.y) - 1) xb_changes = [] yb_changes = [] def rk4(x0, y0, f): ds = 0.01 stotal = 0 xi = x0 yi = y0 xb, yb = self.blank_pos(xi, yi) xf_traj = [] yf_traj = [] while check(xi, yi): xf_traj.append(xi) yf_traj.append(yi) try: k1x, k1y = f(xi, yi) k2x, k2y = f(xi + 0.5 * ds * k1x, yi + 0.5 * ds * k1y) k3x, k3y = f(xi + 0.5 * ds * k2x, yi + 0.5 * ds * k2y) k4x, k4y = f(xi + ds * k3x, yi + ds * k3y) except IndexError: break xi += ds * (k1x + 2 * k2x + 2 * k3x + k4x) / 6.0 yi += ds * (k1y + 2 * k2y + 2 * k3y + k4y) / 6.0 if not check(xi, yi): break stotal += ds new_xb, new_yb = self.blank_pos(xi, yi) if new_xb != xb or new_yb != yb: if self.blank[new_yb, new_xb] == 0: self.blank[new_yb, new_xb] = 1 xb_changes.append(new_xb) yb_changes.append(new_yb) xb = new_xb yb = new_yb else: break if stotal > 2: break return stotal, xf_traj, yf_traj sf, xf_traj, yf_traj = rk4(x0, y0, f) sb, xb_traj, yb_traj = rk4(x0, y0, g) stotal = sf + sb x_traj = xb_traj[::-1] + xf_traj[1:] y_traj = yb_traj[::-1] + yf_traj[1:] if len(x_traj) < 1: return None if stotal > 0.2: initxb, inityb = self.blank_pos(x0, y0) self.blank[inityb, initxb] = 1 return x_traj, y_traj else: for xb, yb in zip(xb_changes, yb_changes): self.blank[yb, xb] = 0 return None def traj(self, xb, yb): """ Integrate trajectories :param (int) xb: results of passing xi through self.blank_pos :param (int) xy: results of passing yi through self.blank_pos Calculate each trajectory based on rk4 integrate method. """ if xb < 0 or xb >= self.density or yb < 0 or yb >= self.density: return if self.blank[yb, xb] == 0: t = self.rk4_integrate(xb * self.spacing_x, yb * self.spacing_y) if t is not None: self.trajectories.append(t) def get_streamlines(self): """ Get streamlines by building trajectory set. """ for indent in range(self.density // 2): for xi in range(self.density - 2 * indent): self.traj(xi + indent, indent) self.traj(xi + indent, self.density - 1 - indent) self.traj(indent, xi + indent) self.traj(self.density - 1 - indent, xi + indent) self.st_x = [ np.array(t[0]) * self.delta_x + self.x[0] for t in self.trajectories ] self.st_y = [ np.array(t[1]) * self.delta_y + self.y[0] for t in self.trajectories ] for index in range(len(self.st_x)): self.st_x[index] = self.st_x[index].tolist() self.st_x[index].append(np.nan) for index in range(len(self.st_y)): self.st_y[index] = self.st_y[index].tolist() self.st_y[index].append(np.nan) def get_streamline_arrows(self): """ Makes an arrow for each streamline. Gets angle of streamline at 1/3 mark and creates arrow coordinates based off of user defined angle and arrow_scale. :param (array) st_x: x-values for all streamlines :param (array) st_y: y-values for all streamlines :param (angle in radians) angle: angle of arrowhead. Default = pi/9 :param (float in [0,1]) arrow_scale: value to scale length of arrowhead Default = .09 :rtype (list, list) arrows_x: x-values to create arrowhead and arrows_y: y-values to create arrowhead """ arrow_end_x = np.empty((len(self.st_x))) arrow_end_y = np.empty((len(self.st_y))) arrow_start_x = np.empty((len(self.st_x))) arrow_start_y = np.empty((len(self.st_y))) for index in range(len(self.st_x)): arrow_end_x[index] = self.st_x[index][int(len(self.st_x[index]) / 3)] arrow_start_x[index] = self.st_x[index][ (int(len(self.st_x[index]) / 3)) - 1 ] arrow_end_y[index] = self.st_y[index][int(len(self.st_y[index]) / 3)] arrow_start_y[index] = self.st_y[index][ (int(len(self.st_y[index]) / 3)) - 1 ] dif_x = arrow_end_x - arrow_start_x dif_y = arrow_end_y - arrow_start_y orig_err = np.geterr() np.seterr(divide="ignore", invalid="ignore") streamline_ang = np.arctan(dif_y / dif_x) np.seterr(**orig_err) ang1 = streamline_ang + (self.angle) ang2 = streamline_ang - (self.angle) seg1_x = np.cos(ang1) * self.arrow_scale seg1_y = np.sin(ang1) * self.arrow_scale seg2_x = np.cos(ang2) * self.arrow_scale seg2_y = np.sin(ang2) * self.arrow_scale point1_x = np.empty((len(dif_x))) point1_y = np.empty((len(dif_y))) point2_x = np.empty((len(dif_x))) point2_y = np.empty((len(dif_y))) for index in range(len(dif_x)): if dif_x[index] >= 0: point1_x[index] = arrow_end_x[index] - seg1_x[index] point1_y[index] = arrow_end_y[index] - seg1_y[index] point2_x[index] = arrow_end_x[index] - seg2_x[index] point2_y[index] = arrow_end_y[index] - seg2_y[index] else: point1_x[index] = arrow_end_x[index] + seg1_x[index] point1_y[index] = arrow_end_y[index] + seg1_y[index] point2_x[index] = arrow_end_x[index] + seg2_x[index] point2_y[index] = arrow_end_y[index] + seg2_y[index] space = np.empty((len(point1_x))) space[:] = np.nan # Combine arrays into matrix arrows_x = np.matrix([point1_x, arrow_end_x, point2_x, space]) arrows_x = np.array(arrows_x) arrows_x = arrows_x.flatten("F") arrows_x = arrows_x.tolist() # Combine arrays into matrix arrows_y = np.matrix([point1_y, arrow_end_y, point2_y, space]) arrows_y = np.array(arrows_y) arrows_y = arrows_y.flatten("F") arrows_y = arrows_y.tolist() return arrows_x, arrows_y def sum_streamlines(self): """ Makes all streamlines readable as a single trace. :rtype (list, list): streamline_x: all x values for each streamline combined into single list and streamline_y: all y values for each streamline combined into single list """ streamline_x = sum(self.st_x, []) streamline_y = sum(self.st_y, []) return streamline_x, streamline_y plotly-4.4.1+dfsg.orig/plotly/figure_factory/_bullet.py0000644000175000017500000003154213573717677022640 0ustar noahfxnoahfxfrom __future__ import absolute_import import collections import math from plotly import exceptions, optional_imports import plotly.colors as clrs from plotly.figure_factory import utils import plotly import plotly.graph_objs as go pd = optional_imports.get_module("pandas") def _bullet( df, markers, measures, ranges, subtitles, titles, orientation, range_colors, measure_colors, horizontal_spacing, vertical_spacing, scatter_options, layout_options, ): num_of_lanes = len(df) num_of_rows = num_of_lanes if orientation == "h" else 1 num_of_cols = 1 if orientation == "h" else num_of_lanes if not horizontal_spacing: horizontal_spacing = 1.0 / num_of_lanes if not vertical_spacing: vertical_spacing = 1.0 / num_of_lanes fig = plotly.subplots.make_subplots( num_of_rows, num_of_cols, print_grid=False, horizontal_spacing=horizontal_spacing, vertical_spacing=vertical_spacing, ) # layout fig["layout"].update( dict(shapes=[]), title="Bullet Chart", height=600, width=1000, showlegend=False, barmode="stack", annotations=[], margin=dict(l=120 if orientation == "h" else 80), ) # update layout fig["layout"].update(layout_options) if orientation == "h": width_axis = "yaxis" length_axis = "xaxis" else: width_axis = "xaxis" length_axis = "yaxis" for key in fig["layout"]: if "xaxis" in key or "yaxis" in key: fig["layout"][key]["showgrid"] = False fig["layout"][key]["zeroline"] = False if length_axis in key: fig["layout"][key]["tickwidth"] = 1 if width_axis in key: fig["layout"][key]["showticklabels"] = False fig["layout"][key]["range"] = [0, 1] # narrow domain if 1 bar if num_of_lanes <= 1: fig["layout"][width_axis + "1"]["domain"] = [0.4, 0.6] if not range_colors: range_colors = ["rgb(200, 200, 200)", "rgb(245, 245, 245)"] if not measure_colors: measure_colors = ["rgb(31, 119, 180)", "rgb(176, 196, 221)"] for row in range(num_of_lanes): # ranges bars for idx in range(len(df.iloc[row]["ranges"])): inter_colors = clrs.n_colors( range_colors[0], range_colors[1], len(df.iloc[row]["ranges"]), "rgb" ) x = ( [sorted(df.iloc[row]["ranges"])[-1 - idx]] if orientation == "h" else [0] ) y = ( [0] if orientation == "h" else [sorted(df.iloc[row]["ranges"])[-1 - idx]] ) bar = go.Bar( x=x, y=y, marker=dict(color=inter_colors[-1 - idx]), name="ranges", hoverinfo="x" if orientation == "h" else "y", orientation=orientation, width=2, base=0, xaxis="x{}".format(row + 1), yaxis="y{}".format(row + 1), ) fig.add_trace(bar) # measures bars for idx in range(len(df.iloc[row]["measures"])): inter_colors = clrs.n_colors( measure_colors[0], measure_colors[1], len(df.iloc[row]["measures"]), "rgb", ) x = ( [sorted(df.iloc[row]["measures"])[-1 - idx]] if orientation == "h" else [0.5] ) y = ( [0.5] if orientation == "h" else [sorted(df.iloc[row]["measures"])[-1 - idx]] ) bar = go.Bar( x=x, y=y, marker=dict(color=inter_colors[-1 - idx]), name="measures", hoverinfo="x" if orientation == "h" else "y", orientation=orientation, width=0.4, base=0, xaxis="x{}".format(row + 1), yaxis="y{}".format(row + 1), ) fig.add_trace(bar) # markers x = df.iloc[row]["markers"] if orientation == "h" else [0.5] y = [0.5] if orientation == "h" else df.iloc[row]["markers"] markers = go.Scatter( x=x, y=y, name="markers", hoverinfo="x" if orientation == "h" else "y", xaxis="x{}".format(row + 1), yaxis="y{}".format(row + 1), **scatter_options ) fig.add_trace(markers) # titles and subtitles title = df.iloc[row]["titles"] if "subtitles" in df: subtitle = "
{}".format(df.iloc[row]["subtitles"]) else: subtitle = "" label = "{}".format(title) + subtitle annot = utils.annotation_dict_for_label( label, (num_of_lanes - row if orientation == "h" else row + 1), num_of_lanes, vertical_spacing if orientation == "h" else horizontal_spacing, "row" if orientation == "h" else "col", True if orientation == "h" else False, False, ) fig["layout"]["annotations"] += (annot,) return fig def create_bullet( data, markers=None, measures=None, ranges=None, subtitles=None, titles=None, orientation="h", range_colors=("rgb(200, 200, 200)", "rgb(245, 245, 245)"), measure_colors=("rgb(31, 119, 180)", "rgb(176, 196, 221)"), horizontal_spacing=None, vertical_spacing=None, scatter_options={}, **layout_options ): """ **deprecated**, use instead the plotly.graph_objects trace :class:`plotly.graph_objects.Indicator`. :param (pd.DataFrame | list | tuple) data: either a list/tuple of dictionaries or a pandas DataFrame. :param (str) markers: the column name or dictionary key for the markers in each subplot. :param (str) measures: the column name or dictionary key for the measure bars in each subplot. This bar usually represents the quantitative measure of performance, usually a list of two values [a, b] and are the blue bars in the foreground of each subplot by default. :param (str) ranges: the column name or dictionary key for the qualitative ranges of performance, usually a 3-item list [bad, okay, good]. They correspond to the grey bars in the background of each chart. :param (str) subtitles: the column name or dictionary key for the subtitle of each subplot chart. The subplots are displayed right underneath each title. :param (str) titles: the column name or dictionary key for the main label of each subplot chart. :param (bool) orientation: if 'h', the bars are placed horizontally as rows. If 'v' the bars are placed vertically in the chart. :param (list) range_colors: a tuple of two colors between which all the rectangles for the range are drawn. These rectangles are meant to be qualitative indicators against which the marker and measure bars are compared. Default=('rgb(200, 200, 200)', 'rgb(245, 245, 245)') :param (list) measure_colors: a tuple of two colors which is used to color the thin quantitative bars in the bullet chart. Default=('rgb(31, 119, 180)', 'rgb(176, 196, 221)') :param (float) horizontal_spacing: see the 'horizontal_spacing' param in plotly.tools.make_subplots. Ranges between 0 and 1. :param (float) vertical_spacing: see the 'vertical_spacing' param in plotly.tools.make_subplots. Ranges between 0 and 1. :param (dict) scatter_options: describes attributes for the scatter trace in each subplot such as name and marker size. Call help(plotly.graph_objs.Scatter) for more information on valid params. :param layout_options: describes attributes for the layout of the figure such as title, height and width. Call help(plotly.graph_objs.Layout) for more information on valid params. Example 1: Use a Dictionary >>> import plotly.figure_factory as ff >>> data = [ ... {"label": "revenue", "sublabel": "us$, in thousands", ... "range": [150, 225, 300], "performance": [220,270], "point": [250]}, ... {"label": "Profit", "sublabel": "%", "range": [20, 25, 30], ... "performance": [21, 23], "point": [26]}, ... {"label": "Order Size", "sublabel":"US$, average","range": [350, 500, 600], ... "performance": [100,320],"point": [550]}, ... {"label": "New Customers", "sublabel": "count", "range": [1400, 2000, 2500], ... "performance": [1000, 1650],"point": [2100]}, ... {"label": "Satisfaction", "sublabel": "out of 5","range": [3.5, 4.25, 5], ... "performance": [3.2, 4.7], "point": [4.4]} ... ] >>> fig = ff.create_bullet( ... data, titles='label', subtitles='sublabel', markers='point', ... measures='performance', ranges='range', orientation='h', ... title='my simple bullet chart' ... ) >>> fig.show() Example 2: Use a DataFrame with Custom Colors >>> import plotly.figure_factory as ff >>> import pandas as pd >>> data = pd.read_json('https://cdn.rawgit.com/plotly/datasets/master/BulletData.json') >>> fig = ff.create_bullet( ... data, titles='title', markers='markers', measures='measures', ... orientation='v', measure_colors=['rgb(14, 52, 75)', 'rgb(31, 141, 127)'], ... scatter_options={'marker': {'symbol': 'circle'}}, width=700) >>> fig.show() """ # validate df if not pd: raise ImportError("'pandas' must be installed for this figure factory.") if utils.is_sequence(data): if not all(isinstance(item, dict) for item in data): raise exceptions.PlotlyError( "Every entry of the data argument list, tuple, etc must " "be a dictionary." ) elif not isinstance(data, pd.DataFrame): raise exceptions.PlotlyError( "You must input a pandas DataFrame, or a list of dictionaries." ) # make DataFrame from data with correct column headers col_names = ["titles", "subtitle", "markers", "measures", "ranges"] if utils.is_sequence(data): df = pd.DataFrame( [ [d[titles] for d in data] if titles else [""] * len(data), [d[subtitles] for d in data] if subtitles else [""] * len(data), [d[markers] for d in data] if markers else [[]] * len(data), [d[measures] for d in data] if measures else [[]] * len(data), [d[ranges] for d in data] if ranges else [[]] * len(data), ], index=col_names, ) elif isinstance(data, pd.DataFrame): df = pd.DataFrame( [ data[titles].tolist() if titles else [""] * len(data), data[subtitles].tolist() if subtitles else [""] * len(data), data[markers].tolist() if markers else [[]] * len(data), data[measures].tolist() if measures else [[]] * len(data), data[ranges].tolist() if ranges else [[]] * len(data), ], index=col_names, ) df = pd.DataFrame.transpose(df) # make sure ranges, measures, 'markers' are not NAN or NONE for needed_key in ["ranges", "measures", "markers"]: for idx, r in enumerate(df[needed_key]): try: r_is_nan = math.isnan(r) if r_is_nan or r is None: df[needed_key][idx] = [] except TypeError: pass # validate custom colors for colors_list in [range_colors, measure_colors]: if colors_list: if len(colors_list) != 2: raise exceptions.PlotlyError( "Both 'range_colors' or 'measure_colors' must be a list " "of two valid colors." ) clrs.validate_colors(colors_list) colors_list = clrs.convert_colors_to_same_type(colors_list, "rgb")[0] # default scatter options default_scatter = { "marker": {"size": 12, "symbol": "diamond-tall", "color": "rgb(0, 0, 0)"} } if scatter_options == {}: scatter_options.update(default_scatter) else: # add default options to scatter_options if they are not present for k in default_scatter["marker"]: if k not in scatter_options["marker"]: scatter_options["marker"][k] = default_scatter["marker"][k] fig = _bullet( df, markers, measures, ranges, subtitles, titles, orientation, range_colors, measure_colors, horizontal_spacing, vertical_spacing, scatter_options, layout_options, ) return fig plotly-4.4.1+dfsg.orig/plotly/figure_factory/_2d_density.py0000644000175000017500000001134413573717677023413 0ustar noahfxnoahfxfrom __future__ import absolute_import from numbers import Number import plotly.exceptions import plotly.colors as clrs from plotly.graph_objs import graph_objs def make_linear_colorscale(colors): """ Makes a list of colors into a colorscale-acceptable form For documentation regarding to the form of the output, see https://plot.ly/python/reference/#mesh3d-colorscale """ scale = 1.0 / (len(colors) - 1) return [[i * scale, color] for i, color in enumerate(colors)] def create_2d_density( x, y, colorscale="Earth", ncontours=20, hist_color=(0, 0, 0.5), point_color=(0, 0, 0.5), point_size=2, title="2D Density Plot", height=600, width=600, ): """ **deprecated**, use instead :func:`plotly.express.density_heatmap`. :param (list|array) x: x-axis data for plot generation :param (list|array) y: y-axis data for plot generation :param (str|tuple|list) colorscale: either a plotly scale name, an rgb or hex color, a color tuple or a list or tuple of colors. An rgb color is of the form 'rgb(x, y, z)' where x, y, z belong to the interval [0, 255] and a color tuple is a tuple of the form (a, b, c) where a, b and c belong to [0, 1]. If colormap is a list, it must contain the valid color types aforementioned as its members. :param (int) ncontours: the number of 2D contours to draw on the plot :param (str) hist_color: the color of the plotted histograms :param (str) point_color: the color of the scatter points :param (str) point_size: the color of the scatter points :param (str) title: set the title for the plot :param (float) height: the height of the chart :param (float) width: the width of the chart Examples -------- Example 1: Simple 2D Density Plot >>> from plotly.figure_factory import create_2d_density >>> import numpy as np >>> # Make data points >>> t = np.linspace(-1,1.2,2000) >>> x = (t**3)+(0.3*np.random.randn(2000)) >>> y = (t**6)+(0.3*np.random.randn(2000)) >>> # Create a figure >>> fig = create_2d_density(x, y) >>> # Plot the data >>> fig.show() Example 2: Using Parameters >>> from plotly.figure_factory import create_2d_density >>> import numpy as np >>> # Make data points >>> t = np.linspace(-1,1.2,2000) >>> x = (t**3)+(0.3*np.random.randn(2000)) >>> y = (t**6)+(0.3*np.random.randn(2000)) >>> # Create custom colorscale >>> colorscale = ['#7A4579', '#D56073', 'rgb(236,158,105)', ... (1, 1, 0.2), (0.98,0.98,0.98)] >>> # Create a figure >>> fig = create_2d_density(x, y, colorscale=colorscale, ... hist_color='rgb(255, 237, 222)', point_size=3) >>> # Plot the data >>> fig.show() """ # validate x and y are filled with numbers only for array in [x, y]: if not all(isinstance(element, Number) for element in array): raise plotly.exceptions.PlotlyError( "All elements of your 'x' and 'y' lists must be numbers." ) # validate x and y are the same length if len(x) != len(y): raise plotly.exceptions.PlotlyError( "Both lists 'x' and 'y' must be the same length." ) colorscale = clrs.validate_colors(colorscale, "rgb") colorscale = make_linear_colorscale(colorscale) # validate hist_color and point_color hist_color = clrs.validate_colors(hist_color, "rgb") point_color = clrs.validate_colors(point_color, "rgb") trace1 = graph_objs.Scatter( x=x, y=y, mode="markers", name="points", marker=dict(color=point_color[0], size=point_size, opacity=0.4), ) trace2 = graph_objs.Histogram2dContour( x=x, y=y, name="density", ncontours=ncontours, colorscale=colorscale, reversescale=True, showscale=False, ) trace3 = graph_objs.Histogram( x=x, name="x density", marker=dict(color=hist_color[0]), yaxis="y2" ) trace4 = graph_objs.Histogram( y=y, name="y density", marker=dict(color=hist_color[0]), xaxis="x2" ) data = [trace1, trace2, trace3, trace4] layout = graph_objs.Layout( showlegend=False, autosize=False, title=title, height=height, width=width, xaxis=dict(domain=[0, 0.85], showgrid=False, zeroline=False), yaxis=dict(domain=[0, 0.85], showgrid=False, zeroline=False), margin=dict(t=50), hovermode="closest", bargap=0, xaxis2=dict(domain=[0.85, 1], showgrid=False, zeroline=False), yaxis2=dict(domain=[0.85, 1], showgrid=False, zeroline=False), ) fig = graph_objs.Figure(data=data, layout=layout) return fig plotly-4.4.1+dfsg.orig/plotly/figure_factory/_ternary_contour.py0000644000175000017500000005423613573717677024613 0ustar noahfxnoahfxfrom __future__ import absolute_import import plotly.colors as clrs from plotly.graph_objs import graph_objs as go from plotly import exceptions, optional_imports from plotly import optional_imports from plotly.graph_objs import graph_objs as go np = optional_imports.get_module("numpy") scipy_interp = optional_imports.get_module("scipy.interpolate") from skimage import measure # -------------------------- Layout ------------------------------ def _ternary_layout( title="Ternary contour plot", width=550, height=525, pole_labels=["a", "b", "c"] ): """ Layout of ternary contour plot, to be passed to ``go.FigureWidget`` object. Parameters ========== title : str or None Title of ternary plot width : int Figure width. height : int Figure height. pole_labels : str, default ['a', 'b', 'c'] Names of the three poles of the triangle. """ return dict( title=title, width=width, height=height, ternary=dict( sum=1, aaxis=dict( title=dict(text=pole_labels[0]), min=0.01, linewidth=2, ticks="outside" ), baxis=dict( title=dict(text=pole_labels[1]), min=0.01, linewidth=2, ticks="outside" ), caxis=dict( title=dict(text=pole_labels[2]), min=0.01, linewidth=2, ticks="outside" ), ), showlegend=False, ) # ------------- Transformations of coordinates ------------------- def _replace_zero_coords(ternary_data, delta=0.0005): """ Replaces zero ternary coordinates with delta and normalize the new triplets (a, b, c). Parameters ---------- ternary_data : ndarray of shape (N, 3) delta : float Small float to regularize logarithm. Notes ----- Implements a method by J. A. Martin-Fernandez, C. Barcelo-Vidal, V. Pawlowsky-Glahn, Dealing with zeros and missing values in compositional data sets using nonparametric imputation, Mathematical Geology 35 (2003), pp 253-278. """ zero_mask = ternary_data == 0 is_any_coord_zero = np.any(zero_mask, axis=0) unity_complement = 1 - delta * is_any_coord_zero if np.any(unity_complement) < 0: raise ValueError( "The provided value of delta led to negative" "ternary coords.Set a smaller delta" ) ternary_data = np.where(zero_mask, delta, unity_complement * ternary_data) return ternary_data def _ilr_transform(barycentric): """ Perform Isometric Log-Ratio on barycentric (compositional) data. Parameters ---------- barycentric: ndarray of shape (3, N) Barycentric coordinates. References ---------- "An algebraic method to compute isometric logratio transformation and back transformation of compositional data", Jarauta-Bragulat, E., Buenestado, P.; Hervada-Sala, C., in Proc. of the Annual Conf. of the Intl Assoc for Math Geology, 2003, pp 31-30. """ barycentric = np.asarray(barycentric) x_0 = np.log(barycentric[0] / barycentric[1]) / np.sqrt(2) x_1 = ( 1.0 / np.sqrt(6) * np.log(barycentric[0] * barycentric[1] / barycentric[2] ** 2) ) ilr_tdata = np.stack((x_0, x_1)) return ilr_tdata def _ilr_inverse(x): """ Perform inverse Isometric Log-Ratio (ILR) transform to retrieve barycentric (compositional) data. Parameters ---------- x : array of shape (2, N) Coordinates in ILR space. References ---------- "An algebraic method to compute isometric logratio transformation and back transformation of compositional data", Jarauta-Bragulat, E., Buenestado, P.; Hervada-Sala, C., in Proc. of the Annual Conf. of the Intl Assoc for Math Geology, 2003, pp 31-30. """ x = np.array(x) matrix = np.array([[0.5, 1, 1.0], [-0.5, 1, 1.0], [0.0, 0.0, 1.0]]) s = np.sqrt(2) / 2 t = np.sqrt(3 / 2) Sk = np.einsum("ik, kj -> ij", np.array([[s, t], [-s, t]]), x) Z = -np.log(1 + np.exp(Sk).sum(axis=0)) log_barycentric = np.einsum( "ik, kj -> ij", matrix, np.stack((2 * s * x[0], t * x[1], Z)) ) iilr_tdata = np.exp(log_barycentric) return iilr_tdata def _transform_barycentric_cartesian(): """ Returns the transformation matrix from barycentric to Cartesian coordinates and conversely. """ # reference triangle tri_verts = np.array([[0.5, np.sqrt(3) / 2], [0, 0], [1, 0]]) M = np.array([tri_verts[:, 0], tri_verts[:, 1], np.ones(3)]) return M, np.linalg.inv(M) def _prepare_barycentric_coord(b_coords): """ Check ternary coordinates and return the right barycentric coordinates. """ if not isinstance(b_coords, (list, np.ndarray)): raise ValueError( "Data should be either an array of shape (n,m)," "or a list of n m-lists, m=2 or 3" ) b_coords = np.asarray(b_coords) if b_coords.shape[0] not in (2, 3): raise ValueError( "A point should have 2 (a, b) or 3 (a, b, c)" "barycentric coordinates" ) if ( (len(b_coords) == 3) and not np.allclose(b_coords.sum(axis=0), 1, rtol=0.01) and not np.allclose(b_coords.sum(axis=0), 100, rtol=0.01) ): msg = "The sum of coordinates should be 1 or 100 for all data points" raise ValueError(msg) if len(b_coords) == 2: A, B = b_coords C = 1 - (A + B) else: A, B, C = b_coords / b_coords.sum(axis=0) if np.any(np.stack((A, B, C)) < 0): raise ValueError("Barycentric coordinates should be positive.") return np.stack((A, B, C)) def _compute_grid(coordinates, values, interp_mode="ilr"): """ Transform data points with Cartesian or ILR mapping, then Compute interpolation on a regular grid. Parameters ========== coordinates : array-like Barycentric coordinates of data points. values : 1-d array-like Data points, field to be represented as contours. interp_mode : 'ilr' (default) or 'cartesian' Defines how data are interpolated to compute contours. """ if interp_mode == "cartesian": M, invM = _transform_barycentric_cartesian() coord_points = np.einsum("ik, kj -> ij", M, coordinates) elif interp_mode == "ilr": coordinates = _replace_zero_coords(coordinates) coord_points = _ilr_transform(coordinates) else: raise ValueError("interp_mode should be cartesian or ilr") xx, yy = coord_points[:2] x_min, x_max = xx.min(), xx.max() y_min, y_max = yy.min(), yy.max() n_interp = max(200, int(np.sqrt(len(values)))) gr_x = np.linspace(x_min, x_max, n_interp) gr_y = np.linspace(y_min, y_max, n_interp) grid_x, grid_y = np.meshgrid(gr_x, gr_y) # We use cubic interpolation, except outside of the convex hull # of data points where we use nearest neighbor values. grid_z = scipy_interp.griddata( coord_points[:2].T, values, (grid_x, grid_y), method="cubic" ) grid_z_other = scipy_interp.griddata( coord_points[:2].T, values, (grid_x, grid_y), method="nearest" ) # mask_nan = np.isnan(grid_z) # grid_z[mask_nan] = grid_z_other[mask_nan] return grid_z, gr_x, gr_y # ----------------------- Contour traces ---------------------- def _polygon_area(x, y): return 0.5 * np.abs(np.dot(x, np.roll(y, 1)) - np.dot(y, np.roll(x, 1))) def _colors(ncontours, colormap=None): """ Return a list of ``ncontours`` colors from the ``colormap`` colorscale. """ if colormap in clrs.PLOTLY_SCALES.keys(): cmap = clrs.PLOTLY_SCALES[colormap] else: raise exceptions.PlotlyError( "Colorscale must be a valid Plotly Colorscale." "The available colorscale names are {}".format(clrs.PLOTLY_SCALES.keys()) ) values = np.linspace(0, 1, ncontours) vals_cmap = np.array([pair[0] for pair in cmap]) cols = np.array([pair[1] for pair in cmap]) inds = np.searchsorted(vals_cmap, values) if "#" in cols[0]: # for Viridis cols = [clrs.label_rgb(clrs.hex_to_rgb(col)) for col in cols] colors = [cols[0]] for ind, val in zip(inds[1:], values[1:]): val1, val2 = vals_cmap[ind - 1], vals_cmap[ind] interm = (val - val1) / (val2 - val1) col = clrs.find_intermediate_color( cols[ind - 1], cols[ind], interm, colortype="rgb" ) colors.append(col) return colors def _is_invalid_contour(x, y): """ Utility function for _contour_trace Contours with an area of the order as 1 pixel are considered spurious. """ too_small = np.all(np.abs(x - x[0]) < 2) and np.all(np.abs(y - y[0]) < 2) return too_small def _extract_contours(im, values, colors): """ Utility function for _contour_trace. In ``im`` only one part of the domain has valid values (corresponding to a subdomain where barycentric coordinates are well defined). When computing contours, we need to assign values outside of this domain. We can choose a value either smaller than all the values inside the valid domain, or larger. This value must be chose with caution so that no spurious contours are added. For example, if the boundary of the valid domain has large values and the outer value is set to a small one, all intermediate contours will be added at the boundary. Therefore, we compute the two sets of contours (with an outer value smaller of larger than all values in the valid domain), and choose the value resulting in a smaller total number of contours. There might be a faster way to do this, but it works... """ mask_nan = np.isnan(im) im_min, im_max = ( im[np.logical_not(mask_nan)].min(), im[np.logical_not(mask_nan)].max(), ) zz_min = np.copy(im) zz_min[mask_nan] = 2 * im_min zz_max = np.copy(im) zz_max[mask_nan] = 2 * im_max all_contours1, all_values1, all_areas1, all_colors1 = [], [], [], [] all_contours2, all_values2, all_areas2, all_colors2 = [], [], [], [] for i, val in enumerate(values): contour_level1 = measure.find_contours(zz_min, val) contour_level2 = measure.find_contours(zz_max, val) all_contours1.extend(contour_level1) all_contours2.extend(contour_level2) all_values1.extend([val] * len(contour_level1)) all_values2.extend([val] * len(contour_level2)) all_areas1.extend( [_polygon_area(contour.T[1], contour.T[0]) for contour in contour_level1] ) all_areas2.extend( [_polygon_area(contour.T[1], contour.T[0]) for contour in contour_level2] ) all_colors1.extend([colors[i]] * len(contour_level1)) all_colors2.extend([colors[i]] * len(contour_level2)) if len(all_contours1) <= len(all_contours2): return all_contours1, all_values1, all_areas1, all_colors1 else: return all_contours2, all_values2, all_areas2, all_colors2 def _add_outer_contour( all_contours, all_values, all_areas, all_colors, values, val_outer, v_min, v_max, colors, color_min, color_max, ): """ Utility function for _contour_trace Adds the background color to fill gaps outside of computed contours. To compute the background color, the color of the contour with largest area (``val_outer``) is used. As background color, we choose the next color value in the direction of the extrema of the colormap. Then we add information for the outer contour for the different lists provided as arguments. A discrete colormap with all used colors is also returned (to be used by colorscale trace). """ # The exact value of outer contour is not used when defining the trace outer_contour = 20 * np.array([[0, 0, 1], [0, 1, 0.5]]).T all_contours = [outer_contour] + all_contours delta_values = np.diff(values)[0] values = np.concatenate( ([values[0] - delta_values], values, [values[-1] + delta_values]) ) colors = np.concatenate(([color_min], colors, [color_max])) index = np.nonzero(values == val_outer)[0][0] if index < len(values) / 2: index -= 1 else: index += 1 all_colors = [colors[index]] + all_colors all_values = [values[index]] + all_values all_areas = [0] + all_areas used_colors = [color for color in colors if color in all_colors] # Define discrete colorscale color_number = len(used_colors) scale = np.linspace(0, 1, color_number + 1) discrete_cm = [] for i, color in enumerate(used_colors): discrete_cm.append([scale[i], used_colors[i]]) discrete_cm.append([scale[i + 1], used_colors[i]]) discrete_cm.append([scale[color_number], used_colors[color_number - 1]]) return all_contours, all_values, all_areas, all_colors, discrete_cm def _contour_trace( x, y, z, ncontours=None, colorscale="Electric", linecolor="rgb(150,150,150)", interp_mode="llr", coloring=None, v_min=0, v_max=1, ): """ Contour trace in Cartesian coordinates. Parameters ========== x, y : array-like Cartesian coordinates z : array-like Field to be represented as contours. ncontours : int or None Number of contours to display (determined automatically if None). colorscale : None or str (Plotly colormap) colorscale of the contours. linecolor : rgb color Color used for lines. If ``colorscale`` is not None, line colors are determined from ``colorscale`` instead. interp_mode : 'ilr' (default) or 'cartesian' Defines how data are interpolated to compute contours. If 'irl', ILR (Isometric Log-Ratio) of compositional data is performed. If 'cartesian', contours are determined in Cartesian space. coloring : None or 'lines' How to display contour. Filled contours if None, lines if ``lines``. vmin, vmax : float Bounds of interval of values used for the colorspace Notes ===== """ # Prepare colors # We do not take extrema, for example for one single contour # the color will be the middle point of the colormap colors = _colors(ncontours + 2, colorscale) # Values used for contours, extrema are not used # For example for a binary array [0, 1], the value of # the contour for ncontours=1 is 0.5. values = np.linspace(v_min, v_max, ncontours + 2) color_min, color_max = colors[0], colors[-1] colors = colors[1:-1] values = values[1:-1] # Color of line contours if linecolor is None: linecolor = "rgb(150, 150, 150)" else: colors = [linecolor] * ncontours # Retrieve all contours all_contours, all_values, all_areas, all_colors = _extract_contours( z, values, colors ) # Now sort contours by decreasing area order = np.argsort(all_areas)[::-1] # Add outer contour all_contours, all_values, all_areas, all_colors, discrete_cm = _add_outer_contour( all_contours, all_values, all_areas, all_colors, values, all_values[order[0]], v_min, v_max, colors, color_min, color_max, ) order = np.concatenate(([0], order + 1)) # Compute traces, in the order of decreasing area traces = [] M, invM = _transform_barycentric_cartesian() dx = (x.max() - x.min()) / x.size dy = (y.max() - y.min()) / y.size for index in order: y_contour, x_contour = all_contours[index].T val = all_values[index] if interp_mode == "cartesian": bar_coords = np.dot( invM, np.stack((dx * x_contour, dy * y_contour, np.ones(x_contour.shape))), ) elif interp_mode == "ilr": bar_coords = _ilr_inverse( np.stack((dx * x_contour + x.min(), dy * y_contour + y.min())) ) if index == 0: # outer triangle a = np.array([1, 0, 0]) b = np.array([0, 1, 0]) c = np.array([0, 0, 1]) else: a, b, c = bar_coords if _is_invalid_contour(x_contour, y_contour): continue _col = all_colors[index] if coloring == "lines" else linecolor trace = dict( type="scatterternary", a=a, b=b, c=c, mode="lines", line=dict(color=_col, shape="spline", width=1), fill="toself", fillcolor=all_colors[index], showlegend=True, hoverinfo="skip", name="%.3f" % val, ) if coloring == "lines": trace["fill"] = None traces.append(trace) return traces, discrete_cm # -------------------- Figure Factory for ternary contour ------------- def create_ternary_contour( coordinates, values, pole_labels=["a", "b", "c"], width=500, height=500, ncontours=None, showscale=False, coloring=None, colorscale="Bluered", linecolor=None, title=None, interp_mode="ilr", showmarkers=False, ): """ Ternary contour plot. Parameters ---------- coordinates : list or ndarray Barycentric coordinates of shape (2, N) or (3, N) where N is the number of data points. The sum of the 3 coordinates is expected to be 1 for all data points. values : array-like Data points of field to be represented as contours. pole_labels : str, default ['a', 'b', 'c'] Names of the three poles of the triangle. width : int Figure width. height : int Figure height. ncontours : int or None Number of contours to display (determined automatically if None). showscale : bool, default False If True, a colorbar showing the color scale is displayed. coloring : None or 'lines' How to display contour. Filled contours if None, lines if ``lines``. colorscale : None or str (Plotly colormap) colorscale of the contours. linecolor : None or rgb color Color used for lines. ``colorscale`` has to be set to None, otherwise line colors are determined from ``colorscale``. title : str or None Title of ternary plot interp_mode : 'ilr' (default) or 'cartesian' Defines how data are interpolated to compute contours. If 'irl', ILR (Isometric Log-Ratio) of compositional data is performed. If 'cartesian', contours are determined in Cartesian space. showmarkers : bool, default False If True, markers corresponding to input compositional points are superimposed on contours, using the same colorscale. Examples ======== Example 1: ternary contour plot with filled contours >>> import plotly.figure_factory as ff >>> import numpy as np >>> # Define coordinates >>> a, b = np.mgrid[0:1:20j, 0:1:20j] >>> mask = a + b <= 1 >>> a = a[mask].ravel() >>> b = b[mask].ravel() >>> c = 1 - a - b >>> # Values to be displayed as contours >>> z = a * b * c >>> fig = ff.create_ternary_contour(np.stack((a, b, c)), z) >>> fig.show() It is also possible to give only two barycentric coordinates for each point, since the sum of the three coordinates is one: >>> fig = ff.create_ternary_contour(np.stack((a, b)), z) Example 2: ternary contour plot with line contours >>> fig = ff.create_ternary_contour(np.stack((a, b, c)), z, coloring='lines') Example 3: customize number of contours >>> fig = ff.create_ternary_contour(np.stack((a, b, c)), z, ncontours=8) Example 4: superimpose contour plot and original data as markers >>> fig = ff.create_ternary_contour(np.stack((a, b, c)), z, coloring='lines', ... showmarkers=True) Example 5: customize title and pole labels >>> fig = ff.create_ternary_contour(np.stack((a, b, c)), z, ... title='Ternary plot', ... pole_labels=['clay', 'quartz', 'fledspar']) """ if scipy_interp is None: raise ImportError( """\ The create_ternary_contour figure factory requires the scipy package""" ) sk_measure = optional_imports.get_module("skimage") if sk_measure is None: raise ImportError( """\ The create_ternary_contour figure factory requires the scikit-image package""" ) if colorscale is None: showscale = False if ncontours is None: ncontours = 5 coordinates = _prepare_barycentric_coord(coordinates) v_min, v_max = values.min(), values.max() grid_z, gr_x, gr_y = _compute_grid(coordinates, values, interp_mode=interp_mode) layout = _ternary_layout( pole_labels=pole_labels, width=width, height=height, title=title ) contour_trace, discrete_cm = _contour_trace( gr_x, gr_y, grid_z, ncontours=ncontours, colorscale=colorscale, linecolor=linecolor, interp_mode=interp_mode, coloring=coloring, v_min=v_min, v_max=v_max, ) fig = go.Figure(data=contour_trace, layout=layout) opacity = 1 if showmarkers else 0 a, b, c = coordinates hovertemplate = ( pole_labels[0] + ": %{a:.3f}
" + pole_labels[1] + ": %{b:.3f}
" + pole_labels[2] + ": %{c:.3f}
" "z: %{marker.color:.3f}" ) fig.add_scatterternary( a=a, b=b, c=c, mode="markers", marker={ "color": values, "colorscale": colorscale, "line": {"color": "rgb(120, 120, 120)", "width": int(coloring != "lines")}, }, opacity=opacity, hovertemplate=hovertemplate, ) if showscale: if not showmarkers: colorscale = discrete_cm colorbar = dict( { "type": "scatterternary", "a": [None], "b": [None], "c": [None], "marker": { "cmin": values.min(), "cmax": values.max(), "colorscale": colorscale, "showscale": True, }, "mode": "markers", } ) fig.add_trace(colorbar) return fig plotly-4.4.1+dfsg.orig/plotly/figure_factory/__init__.py0000644000175000017500000000416613552431043022724 0ustar noahfxnoahfxfrom __future__ import absolute_import from plotly import optional_imports # Require that numpy exists for figure_factory np = optional_imports.get_module("numpy") if np is None: raise ImportError( """\ The figure factory module requires the numpy package""" ) from plotly.figure_factory._2d_density import create_2d_density from plotly.figure_factory._annotated_heatmap import create_annotated_heatmap from plotly.figure_factory._bullet import create_bullet from plotly.figure_factory._candlestick import create_candlestick from plotly.figure_factory._dendrogram import create_dendrogram from plotly.figure_factory._distplot import create_distplot from plotly.figure_factory._facet_grid import create_facet_grid from plotly.figure_factory._gantt import create_gantt from plotly.figure_factory._ohlc import create_ohlc from plotly.figure_factory._quiver import create_quiver from plotly.figure_factory._scatterplot import create_scatterplotmatrix from plotly.figure_factory._streamline import create_streamline from plotly.figure_factory._table import create_table from plotly.figure_factory._trisurf import create_trisurf from plotly.figure_factory._violin import create_violin if optional_imports.get_module("pandas") is not None: from plotly.figure_factory._county_choropleth import create_choropleth else: def create_choropleth(*args, **kwargs): raise ImportError("Please install pandas to use `create_choropleth`") if optional_imports.get_module("skimage") is not None: from plotly.figure_factory._ternary_contour import create_ternary_contour else: def create_ternary_contour(*args, **kwargs): raise ImportError("Please install scikit-image to use `create_ternary_contour`") __all__ = [ "create_2d_density", "create_annotated_heatmap", "create_bullet", "create_candlestick", "create_choropleth", "create_dendrogram", "create_distplot", "create_facet_grid", "create_gantt", "create_ohlc", "create_quiver", "create_scatterplotmatrix", "create_streamline", "create_table", "create_ternary_contour", "create_trisurf", "create_violin", ] plotly-4.4.1+dfsg.orig/plotly/figure_factory/_quiver.py0000644000175000017500000002200513573717677022656 0ustar noahfxnoahfxfrom __future__ import absolute_import import math from plotly import exceptions from plotly.graph_objs import graph_objs from plotly.figure_factory import utils def create_quiver( x, y, u, v, scale=0.1, arrow_scale=0.3, angle=math.pi / 9, scaleratio=None, **kwargs ): """ Returns data for a quiver plot. :param (list|ndarray) x: x coordinates of the arrow locations :param (list|ndarray) y: y coordinates of the arrow locations :param (list|ndarray) u: x components of the arrow vectors :param (list|ndarray) v: y components of the arrow vectors :param (float in [0,1]) scale: scales size of the arrows(ideally to avoid overlap). Default = .1 :param (float in [0,1]) arrow_scale: value multiplied to length of barb to get length of arrowhead. Default = .3 :param (angle in radians) angle: angle of arrowhead. Default = pi/9 :param (positive float) scaleratio: the ratio between the scale of the y-axis and the scale of the x-axis (scale_y / scale_x). Default = None, the scale ratio is not fixed. :param kwargs: kwargs passed through plotly.graph_objs.Scatter for more information on valid kwargs call help(plotly.graph_objs.Scatter) :rtype (dict): returns a representation of quiver figure. Example 1: Trivial Quiver >>> from plotly.figure_factory import create_quiver >>> import math >>> # 1 Arrow from (0,0) to (1,1) >>> fig = create_quiver(x=[0], y=[0], u=[1], v=[1], scale=1) >>> fig.show() Example 2: Quiver plot using meshgrid >>> from plotly.figure_factory import create_quiver >>> import numpy as np >>> import math >>> # Add data >>> x,y = np.meshgrid(np.arange(0, 2, .2), np.arange(0, 2, .2)) >>> u = np.cos(x)*y >>> v = np.sin(x)*y >>> #Create quiver >>> fig = create_quiver(x, y, u, v) >>> fig.show() Example 3: Styling the quiver plot >>> from plotly.figure_factory import create_quiver >>> import numpy as np >>> import math >>> # Add data >>> x, y = np.meshgrid(np.arange(-np.pi, math.pi, .5), ... np.arange(-math.pi, math.pi, .5)) >>> u = np.cos(x)*y >>> v = np.sin(x)*y >>> # Create quiver >>> fig = create_quiver(x, y, u, v, scale=.2, arrow_scale=.3, angle=math.pi/6, ... name='Wind Velocity', line=dict(width=1)) >>> # Add title to layout >>> fig.update_layout(title='Quiver Plot') # doctest: +SKIP >>> fig.show() Example 4: Forcing a fix scale ratio to maintain the arrow length >>> from plotly.figure_factory import create_quiver >>> import numpy as np >>> # Add data >>> x,y = np.meshgrid(np.arange(0.5, 3.5, .5), np.arange(0.5, 4.5, .5)) >>> u = x >>> v = y >>> angle = np.arctan(v / u) >>> norm = 0.25 >>> u = norm * np.cos(angle) >>> v = norm * np.sin(angle) >>> # Create quiver with a fix scale ratio >>> fig = create_quiver(x, y, u, v, scale = 1, scaleratio = 0.5) >>> fig.show() """ utils.validate_equal_length(x, y, u, v) utils.validate_positive_scalars(arrow_scale=arrow_scale, scale=scale) if scaleratio is None: quiver_obj = _Quiver(x, y, u, v, scale, arrow_scale, angle) else: quiver_obj = _Quiver(x, y, u, v, scale, arrow_scale, angle, scaleratio) barb_x, barb_y = quiver_obj.get_barbs() arrow_x, arrow_y = quiver_obj.get_quiver_arrows() quiver_plot = graph_objs.Scatter( x=barb_x + arrow_x, y=barb_y + arrow_y, mode="lines", **kwargs ) data = [quiver_plot] if scaleratio is None: layout = graph_objs.Layout(hovermode="closest") else: layout = graph_objs.Layout( hovermode="closest", yaxis=dict(scaleratio=scaleratio, scaleanchor="x") ) return graph_objs.Figure(data=data, layout=layout) class _Quiver(object): """ Refer to FigureFactory.create_quiver() for docstring """ def __init__(self, x, y, u, v, scale, arrow_scale, angle, scaleratio=1, **kwargs): try: x = utils.flatten(x) except exceptions.PlotlyError: pass try: y = utils.flatten(y) except exceptions.PlotlyError: pass try: u = utils.flatten(u) except exceptions.PlotlyError: pass try: v = utils.flatten(v) except exceptions.PlotlyError: pass self.x = x self.y = y self.u = u self.v = v self.scale = scale self.scaleratio = scaleratio self.arrow_scale = arrow_scale self.angle = angle self.end_x = [] self.end_y = [] self.scale_uv() barb_x, barb_y = self.get_barbs() arrow_x, arrow_y = self.get_quiver_arrows() def scale_uv(self): """ Scales u and v to avoid overlap of the arrows. u and v are added to x and y to get the endpoints of the arrows so a smaller scale value will result in less overlap of arrows. """ self.u = [i * self.scale * self.scaleratio for i in self.u] self.v = [i * self.scale for i in self.v] def get_barbs(self): """ Creates x and y startpoint and endpoint pairs After finding the endpoint of each barb this zips startpoint and endpoint pairs to create 2 lists: x_values for barbs and y values for barbs :rtype: (list, list) barb_x, barb_y: list of startpoint and endpoint x_value pairs separated by a None to create the barb of the arrow, and list of startpoint and endpoint y_value pairs separated by a None to create the barb of the arrow. """ self.end_x = [i + j for i, j in zip(self.x, self.u)] self.end_y = [i + j for i, j in zip(self.y, self.v)] empty = [None] * len(self.x) barb_x = utils.flatten(zip(self.x, self.end_x, empty)) barb_y = utils.flatten(zip(self.y, self.end_y, empty)) return barb_x, barb_y def get_quiver_arrows(self): """ Creates lists of x and y values to plot the arrows Gets length of each barb then calculates the length of each side of the arrow. Gets angle of barb and applies angle to each side of the arrowhead. Next uses arrow_scale to scale the length of arrowhead and creates x and y values for arrowhead point1 and point2. Finally x and y values for point1, endpoint and point2s for each arrowhead are separated by a None and zipped to create lists of x and y values for the arrows. :rtype: (list, list) arrow_x, arrow_y: list of point1, endpoint, point2 x_values separated by a None to create the arrowhead and list of point1, endpoint, point2 y_values separated by a None to create the barb of the arrow. """ dif_x = [i - j for i, j in zip(self.end_x, self.x)] dif_y = [i - j for i, j in zip(self.end_y, self.y)] # Get barb lengths(default arrow length = 30% barb length) barb_len = [None] * len(self.x) for index in range(len(barb_len)): barb_len[index] = math.hypot(dif_x[index] / self.scaleratio, dif_y[index]) # Make arrow lengths arrow_len = [None] * len(self.x) arrow_len = [i * self.arrow_scale for i in barb_len] # Get barb angles barb_ang = [None] * len(self.x) for index in range(len(barb_ang)): barb_ang[index] = math.atan2(dif_y[index], dif_x[index] / self.scaleratio) # Set angles to create arrow ang1 = [i + self.angle for i in barb_ang] ang2 = [i - self.angle for i in barb_ang] cos_ang1 = [None] * len(ang1) for index in range(len(ang1)): cos_ang1[index] = math.cos(ang1[index]) seg1_x = [i * j for i, j in zip(arrow_len, cos_ang1)] sin_ang1 = [None] * len(ang1) for index in range(len(ang1)): sin_ang1[index] = math.sin(ang1[index]) seg1_y = [i * j for i, j in zip(arrow_len, sin_ang1)] cos_ang2 = [None] * len(ang2) for index in range(len(ang2)): cos_ang2[index] = math.cos(ang2[index]) seg2_x = [i * j for i, j in zip(arrow_len, cos_ang2)] sin_ang2 = [None] * len(ang2) for index in range(len(ang2)): sin_ang2[index] = math.sin(ang2[index]) seg2_y = [i * j for i, j in zip(arrow_len, sin_ang2)] # Set coordinates to create arrow for index in range(len(self.end_x)): point1_x = [i - j * self.scaleratio for i, j in zip(self.end_x, seg1_x)] point1_y = [i - j for i, j in zip(self.end_y, seg1_y)] point2_x = [i - j * self.scaleratio for i, j in zip(self.end_x, seg2_x)] point2_y = [i - j for i, j in zip(self.end_y, seg2_y)] # Combine lists to create arrow empty = [None] * len(self.end_x) arrow_x = utils.flatten(zip(point1_x, self.end_x, point2_x, empty)) arrow_y = utils.flatten(zip(point1_y, self.end_y, point2_y, empty)) return arrow_x, arrow_y plotly-4.4.1+dfsg.orig/plotly/figure_factory/_scatterplot.py0000644000175000017500000012744213573717677023722 0ustar noahfxnoahfxfrom __future__ import absolute_import import six from plotly import exceptions, optional_imports import plotly.colors as clrs from plotly.figure_factory import utils from plotly.graph_objs import graph_objs from plotly.subplots import make_subplots pd = optional_imports.get_module("pandas") DIAG_CHOICES = ["scatter", "histogram", "box"] VALID_COLORMAP_TYPES = ["cat", "seq"] def endpts_to_intervals(endpts): """ Returns a list of intervals for categorical colormaps Accepts a list or tuple of sequentially increasing numbers and returns a list representation of the mathematical intervals with these numbers as endpoints. For example, [1, 6] returns [[-inf, 1], [1, 6], [6, inf]] :raises: (PlotlyError) If input is not a list or tuple :raises: (PlotlyError) If the input contains a string :raises: (PlotlyError) If any number does not increase after the previous one in the sequence """ length = len(endpts) # Check if endpts is a list or tuple if not (isinstance(endpts, (tuple)) or isinstance(endpts, (list))): raise exceptions.PlotlyError( "The intervals_endpts argument must " "be a list or tuple of a sequence " "of increasing numbers." ) # Check if endpts contains only numbers for item in endpts: if isinstance(item, str): raise exceptions.PlotlyError( "The intervals_endpts argument " "must be a list or tuple of a " "sequence of increasing " "numbers." ) # Check if numbers in endpts are increasing for k in range(length - 1): if endpts[k] >= endpts[k + 1]: raise exceptions.PlotlyError( "The intervals_endpts argument " "must be a list or tuple of a " "sequence of increasing " "numbers." ) else: intervals = [] # add -inf to intervals intervals.append([float("-inf"), endpts[0]]) for k in range(length - 1): interval = [] interval.append(endpts[k]) interval.append(endpts[k + 1]) intervals.append(interval) # add +inf to intervals intervals.append([endpts[length - 1], float("inf")]) return intervals def hide_tick_labels_from_box_subplots(fig): """ Hides tick labels for box plots in scatterplotmatrix subplots. """ boxplot_xaxes = [] for trace in fig["data"]: if trace["type"] == "box": # stores the xaxes which correspond to boxplot subplots # since we use xaxis1, xaxis2, etc, in plotly.py boxplot_xaxes.append("xaxis{}".format(trace["xaxis"][1:])) for xaxis in boxplot_xaxes: fig["layout"][xaxis]["showticklabels"] = False def validate_scatterplotmatrix(df, index, diag, colormap_type, **kwargs): """ Validates basic inputs for FigureFactory.create_scatterplotmatrix() :raises: (PlotlyError) If pandas is not imported :raises: (PlotlyError) If pandas dataframe is not inputted :raises: (PlotlyError) If pandas dataframe has <= 1 columns :raises: (PlotlyError) If diagonal plot choice (diag) is not one of the viable options :raises: (PlotlyError) If colormap_type is not a valid choice :raises: (PlotlyError) If kwargs contains 'size', 'color' or 'colorscale' """ if not pd: raise ImportError( "FigureFactory.scatterplotmatrix requires " "a pandas DataFrame." ) # Check if pandas dataframe if not isinstance(df, pd.core.frame.DataFrame): raise exceptions.PlotlyError( "Dataframe not inputed. Please " "use a pandas dataframe to pro" "duce a scatterplot matrix." ) # Check if dataframe is 1 column or less if len(df.columns) <= 1: raise exceptions.PlotlyError( "Dataframe has only one column. To " "use the scatterplot matrix, use at " "least 2 columns." ) # Check that diag parameter is a valid selection if diag not in DIAG_CHOICES: raise exceptions.PlotlyError( "Make sure diag is set to " "one of {}".format(DIAG_CHOICES) ) # Check that colormap_types is a valid selection if colormap_type not in VALID_COLORMAP_TYPES: raise exceptions.PlotlyError( "Must choose a valid colormap type. " "Either 'cat' or 'seq' for a cate" "gorical and sequential colormap " "respectively." ) # Check for not 'size' or 'color' in 'marker' of **kwargs if "marker" in kwargs: FORBIDDEN_PARAMS = ["size", "color", "colorscale"] if any(param in kwargs["marker"] for param in FORBIDDEN_PARAMS): raise exceptions.PlotlyError( "Your kwargs dictionary cannot " "include the 'size', 'color' or " "'colorscale' key words inside " "the marker dict since 'size' is " "already an argument of the " "scatterplot matrix function and " "both 'color' and 'colorscale " "are set internally." ) def scatterplot(dataframe, headers, diag, size, height, width, title, **kwargs): """ Refer to FigureFactory.create_scatterplotmatrix() for docstring Returns fig for scatterplotmatrix without index """ dim = len(dataframe) fig = make_subplots(rows=dim, cols=dim, print_grid=False) trace_list = [] # Insert traces into trace_list for listy in dataframe: for listx in dataframe: if (listx == listy) and (diag == "histogram"): trace = graph_objs.Histogram(x=listx, showlegend=False) elif (listx == listy) and (diag == "box"): trace = graph_objs.Box(y=listx, name=None, showlegend=False) else: if "marker" in kwargs: kwargs["marker"]["size"] = size trace = graph_objs.Scatter( x=listx, y=listy, mode="markers", showlegend=False, **kwargs ) trace_list.append(trace) else: trace = graph_objs.Scatter( x=listx, y=listy, mode="markers", marker=dict(size=size), showlegend=False, **kwargs ) trace_list.append(trace) trace_index = 0 indices = range(1, dim + 1) for y_index in indices: for x_index in indices: fig.append_trace(trace_list[trace_index], y_index, x_index) trace_index += 1 # Insert headers into the figure for j in range(dim): xaxis_key = "xaxis{}".format((dim * dim) - dim + 1 + j) fig["layout"][xaxis_key].update(title=headers[j]) for j in range(dim): yaxis_key = "yaxis{}".format(1 + (dim * j)) fig["layout"][yaxis_key].update(title=headers[j]) fig["layout"].update(height=height, width=width, title=title, showlegend=True) hide_tick_labels_from_box_subplots(fig) return fig def scatterplot_dict( dataframe, headers, diag, size, height, width, title, index, index_vals, endpts, colormap, colormap_type, **kwargs ): """ Refer to FigureFactory.create_scatterplotmatrix() for docstring Returns fig for scatterplotmatrix with both index and colormap picked. Used if colormap is a dictionary with index values as keys pointing to colors. Forces colormap_type to behave categorically because it would not make sense colors are assigned to each index value and thus implies that a categorical approach should be taken """ theme = colormap dim = len(dataframe) fig = make_subplots(rows=dim, cols=dim, print_grid=False) trace_list = [] legend_param = 0 # Work over all permutations of list pairs for listy in dataframe: for listx in dataframe: # create a dictionary for index_vals unique_index_vals = {} for name in index_vals: if name not in unique_index_vals: unique_index_vals[name] = [] # Fill all the rest of the names into the dictionary for name in sorted(unique_index_vals.keys()): new_listx = [] new_listy = [] for j in range(len(index_vals)): if index_vals[j] == name: new_listx.append(listx[j]) new_listy.append(listy[j]) # Generate trace with VISIBLE icon if legend_param == 1: if (listx == listy) and (diag == "histogram"): trace = graph_objs.Histogram( x=new_listx, marker=dict(color=theme[name]), showlegend=True ) elif (listx == listy) and (diag == "box"): trace = graph_objs.Box( y=new_listx, name=None, marker=dict(color=theme[name]), showlegend=True, ) else: if "marker" in kwargs: kwargs["marker"]["size"] = size kwargs["marker"]["color"] = theme[name] trace = graph_objs.Scatter( x=new_listx, y=new_listy, mode="markers", name=name, showlegend=True, **kwargs ) else: trace = graph_objs.Scatter( x=new_listx, y=new_listy, mode="markers", name=name, marker=dict(size=size, color=theme[name]), showlegend=True, **kwargs ) # Generate trace with INVISIBLE icon else: if (listx == listy) and (diag == "histogram"): trace = graph_objs.Histogram( x=new_listx, marker=dict(color=theme[name]), showlegend=False, ) elif (listx == listy) and (diag == "box"): trace = graph_objs.Box( y=new_listx, name=None, marker=dict(color=theme[name]), showlegend=False, ) else: if "marker" in kwargs: kwargs["marker"]["size"] = size kwargs["marker"]["color"] = theme[name] trace = graph_objs.Scatter( x=new_listx, y=new_listy, mode="markers", name=name, showlegend=False, **kwargs ) else: trace = graph_objs.Scatter( x=new_listx, y=new_listy, mode="markers", name=name, marker=dict(size=size, color=theme[name]), showlegend=False, **kwargs ) # Push the trace into dictionary unique_index_vals[name] = trace trace_list.append(unique_index_vals) legend_param += 1 trace_index = 0 indices = range(1, dim + 1) for y_index in indices: for x_index in indices: for name in sorted(trace_list[trace_index].keys()): fig.append_trace(trace_list[trace_index][name], y_index, x_index) trace_index += 1 # Insert headers into the figure for j in range(dim): xaxis_key = "xaxis{}".format((dim * dim) - dim + 1 + j) fig["layout"][xaxis_key].update(title=headers[j]) for j in range(dim): yaxis_key = "yaxis{}".format(1 + (dim * j)) fig["layout"][yaxis_key].update(title=headers[j]) hide_tick_labels_from_box_subplots(fig) if diag == "histogram": fig["layout"].update( height=height, width=width, title=title, showlegend=True, barmode="stack" ) return fig else: fig["layout"].update(height=height, width=width, title=title, showlegend=True) return fig def scatterplot_theme( dataframe, headers, diag, size, height, width, title, index, index_vals, endpts, colormap, colormap_type, **kwargs ): """ Refer to FigureFactory.create_scatterplotmatrix() for docstring Returns fig for scatterplotmatrix with both index and colormap picked """ # Check if index is made of string values if isinstance(index_vals[0], str): unique_index_vals = [] for name in index_vals: if name not in unique_index_vals: unique_index_vals.append(name) n_colors_len = len(unique_index_vals) # Convert colormap to list of n RGB tuples if colormap_type == "seq": foo = clrs.color_parser(colormap, clrs.unlabel_rgb) foo = clrs.n_colors(foo[0], foo[1], n_colors_len) theme = clrs.color_parser(foo, clrs.label_rgb) if colormap_type == "cat": # leave list of colors the same way theme = colormap dim = len(dataframe) fig = make_subplots(rows=dim, cols=dim, print_grid=False) trace_list = [] legend_param = 0 # Work over all permutations of list pairs for listy in dataframe: for listx in dataframe: # create a dictionary for index_vals unique_index_vals = {} for name in index_vals: if name not in unique_index_vals: unique_index_vals[name] = [] c_indx = 0 # color index # Fill all the rest of the names into the dictionary for name in sorted(unique_index_vals.keys()): new_listx = [] new_listy = [] for j in range(len(index_vals)): if index_vals[j] == name: new_listx.append(listx[j]) new_listy.append(listy[j]) # Generate trace with VISIBLE icon if legend_param == 1: if (listx == listy) and (diag == "histogram"): trace = graph_objs.Histogram( x=new_listx, marker=dict(color=theme[c_indx]), showlegend=True, ) elif (listx == listy) and (diag == "box"): trace = graph_objs.Box( y=new_listx, name=None, marker=dict(color=theme[c_indx]), showlegend=True, ) else: if "marker" in kwargs: kwargs["marker"]["size"] = size kwargs["marker"]["color"] = theme[c_indx] trace = graph_objs.Scatter( x=new_listx, y=new_listy, mode="markers", name=name, showlegend=True, **kwargs ) else: trace = graph_objs.Scatter( x=new_listx, y=new_listy, mode="markers", name=name, marker=dict(size=size, color=theme[c_indx]), showlegend=True, **kwargs ) # Generate trace with INVISIBLE icon else: if (listx == listy) and (diag == "histogram"): trace = graph_objs.Histogram( x=new_listx, marker=dict(color=theme[c_indx]), showlegend=False, ) elif (listx == listy) and (diag == "box"): trace = graph_objs.Box( y=new_listx, name=None, marker=dict(color=theme[c_indx]), showlegend=False, ) else: if "marker" in kwargs: kwargs["marker"]["size"] = size kwargs["marker"]["color"] = theme[c_indx] trace = graph_objs.Scatter( x=new_listx, y=new_listy, mode="markers", name=name, showlegend=False, **kwargs ) else: trace = graph_objs.Scatter( x=new_listx, y=new_listy, mode="markers", name=name, marker=dict(size=size, color=theme[c_indx]), showlegend=False, **kwargs ) # Push the trace into dictionary unique_index_vals[name] = trace if c_indx >= (len(theme) - 1): c_indx = -1 c_indx += 1 trace_list.append(unique_index_vals) legend_param += 1 trace_index = 0 indices = range(1, dim + 1) for y_index in indices: for x_index in indices: for name in sorted(trace_list[trace_index].keys()): fig.append_trace(trace_list[trace_index][name], y_index, x_index) trace_index += 1 # Insert headers into the figure for j in range(dim): xaxis_key = "xaxis{}".format((dim * dim) - dim + 1 + j) fig["layout"][xaxis_key].update(title=headers[j]) for j in range(dim): yaxis_key = "yaxis{}".format(1 + (dim * j)) fig["layout"][yaxis_key].update(title=headers[j]) hide_tick_labels_from_box_subplots(fig) if diag == "histogram": fig["layout"].update( height=height, width=width, title=title, showlegend=True, barmode="stack", ) return fig elif diag == "box": fig["layout"].update( height=height, width=width, title=title, showlegend=True ) return fig else: fig["layout"].update( height=height, width=width, title=title, showlegend=True ) return fig else: if endpts: intervals = utils.endpts_to_intervals(endpts) # Convert colormap to list of n RGB tuples if colormap_type == "seq": foo = clrs.color_parser(colormap, clrs.unlabel_rgb) foo = clrs.n_colors(foo[0], foo[1], len(intervals)) theme = clrs.color_parser(foo, clrs.label_rgb) if colormap_type == "cat": # leave list of colors the same way theme = colormap dim = len(dataframe) fig = make_subplots(rows=dim, cols=dim, print_grid=False) trace_list = [] legend_param = 0 # Work over all permutations of list pairs for listy in dataframe: for listx in dataframe: interval_labels = {} for interval in intervals: interval_labels[str(interval)] = [] c_indx = 0 # color index # Fill all the rest of the names into the dictionary for interval in intervals: new_listx = [] new_listy = [] for j in range(len(index_vals)): if interval[0] < index_vals[j] <= interval[1]: new_listx.append(listx[j]) new_listy.append(listy[j]) # Generate trace with VISIBLE icon if legend_param == 1: if (listx == listy) and (diag == "histogram"): trace = graph_objs.Histogram( x=new_listx, marker=dict(color=theme[c_indx]), showlegend=True, ) elif (listx == listy) and (diag == "box"): trace = graph_objs.Box( y=new_listx, name=None, marker=dict(color=theme[c_indx]), showlegend=True, ) else: if "marker" in kwargs: kwargs["marker"]["size"] = size (kwargs["marker"]["color"]) = theme[c_indx] trace = graph_objs.Scatter( x=new_listx, y=new_listy, mode="markers", name=str(interval), showlegend=True, **kwargs ) else: trace = graph_objs.Scatter( x=new_listx, y=new_listy, mode="markers", name=str(interval), marker=dict(size=size, color=theme[c_indx]), showlegend=True, **kwargs ) # Generate trace with INVISIBLE icon else: if (listx == listy) and (diag == "histogram"): trace = graph_objs.Histogram( x=new_listx, marker=dict(color=theme[c_indx]), showlegend=False, ) elif (listx == listy) and (diag == "box"): trace = graph_objs.Box( y=new_listx, name=None, marker=dict(color=theme[c_indx]), showlegend=False, ) else: if "marker" in kwargs: kwargs["marker"]["size"] = size (kwargs["marker"]["color"]) = theme[c_indx] trace = graph_objs.Scatter( x=new_listx, y=new_listy, mode="markers", name=str(interval), showlegend=False, **kwargs ) else: trace = graph_objs.Scatter( x=new_listx, y=new_listy, mode="markers", name=str(interval), marker=dict(size=size, color=theme[c_indx]), showlegend=False, **kwargs ) # Push the trace into dictionary interval_labels[str(interval)] = trace if c_indx >= (len(theme) - 1): c_indx = -1 c_indx += 1 trace_list.append(interval_labels) legend_param += 1 trace_index = 0 indices = range(1, dim + 1) for y_index in indices: for x_index in indices: for interval in intervals: fig.append_trace( trace_list[trace_index][str(interval)], y_index, x_index ) trace_index += 1 # Insert headers into the figure for j in range(dim): xaxis_key = "xaxis{}".format((dim * dim) - dim + 1 + j) fig["layout"][xaxis_key].update(title=headers[j]) for j in range(dim): yaxis_key = "yaxis{}".format(1 + (dim * j)) fig["layout"][yaxis_key].update(title=headers[j]) hide_tick_labels_from_box_subplots(fig) if diag == "histogram": fig["layout"].update( height=height, width=width, title=title, showlegend=True, barmode="stack", ) return fig elif diag == "box": fig["layout"].update( height=height, width=width, title=title, showlegend=True ) return fig else: fig["layout"].update( height=height, width=width, title=title, showlegend=True ) return fig else: theme = colormap # add a copy of rgb color to theme if it contains one color if len(theme) <= 1: theme.append(theme[0]) color = [] for incr in range(len(theme)): color.append([1.0 / (len(theme) - 1) * incr, theme[incr]]) dim = len(dataframe) fig = make_subplots(rows=dim, cols=dim, print_grid=False) trace_list = [] legend_param = 0 # Run through all permutations of list pairs for listy in dataframe: for listx in dataframe: # Generate trace with VISIBLE icon if legend_param == 1: if (listx == listy) and (diag == "histogram"): trace = graph_objs.Histogram( x=listx, marker=dict(color=theme[0]), showlegend=False ) elif (listx == listy) and (diag == "box"): trace = graph_objs.Box( y=listx, marker=dict(color=theme[0]), showlegend=False ) else: if "marker" in kwargs: kwargs["marker"]["size"] = size kwargs["marker"]["color"] = index_vals kwargs["marker"]["colorscale"] = color kwargs["marker"]["showscale"] = True trace = graph_objs.Scatter( x=listx, y=listy, mode="markers", showlegend=False, **kwargs ) else: trace = graph_objs.Scatter( x=listx, y=listy, mode="markers", marker=dict( size=size, color=index_vals, colorscale=color, showscale=True, ), showlegend=False, **kwargs ) # Generate trace with INVISIBLE icon else: if (listx == listy) and (diag == "histogram"): trace = graph_objs.Histogram( x=listx, marker=dict(color=theme[0]), showlegend=False ) elif (listx == listy) and (diag == "box"): trace = graph_objs.Box( y=listx, marker=dict(color=theme[0]), showlegend=False ) else: if "marker" in kwargs: kwargs["marker"]["size"] = size kwargs["marker"]["color"] = index_vals kwargs["marker"]["colorscale"] = color kwargs["marker"]["showscale"] = False trace = graph_objs.Scatter( x=listx, y=listy, mode="markers", showlegend=False, **kwargs ) else: trace = graph_objs.Scatter( x=listx, y=listy, mode="markers", marker=dict( size=size, color=index_vals, colorscale=color, showscale=False, ), showlegend=False, **kwargs ) # Push the trace into list trace_list.append(trace) legend_param += 1 trace_index = 0 indices = range(1, dim + 1) for y_index in indices: for x_index in indices: fig.append_trace(trace_list[trace_index], y_index, x_index) trace_index += 1 # Insert headers into the figure for j in range(dim): xaxis_key = "xaxis{}".format((dim * dim) - dim + 1 + j) fig["layout"][xaxis_key].update(title=headers[j]) for j in range(dim): yaxis_key = "yaxis{}".format(1 + (dim * j)) fig["layout"][yaxis_key].update(title=headers[j]) hide_tick_labels_from_box_subplots(fig) if diag == "histogram": fig["layout"].update( height=height, width=width, title=title, showlegend=True, barmode="stack", ) return fig elif diag == "box": fig["layout"].update( height=height, width=width, title=title, showlegend=True ) return fig else: fig["layout"].update( height=height, width=width, title=title, showlegend=True ) return fig def create_scatterplotmatrix( df, index=None, endpts=None, diag="scatter", height=500, width=500, size=6, title="Scatterplot Matrix", colormap=None, colormap_type="cat", dataframe=None, headers=None, index_vals=None, **kwargs ): """ Returns data for a scatterplot matrix; **deprecated**, use instead the plotly.graph_objects trace :class:`plotly.graph_objects.Splom`. :param (array) df: array of the data with column headers :param (str) index: name of the index column in data array :param (list|tuple) endpts: takes an increasing sequece of numbers that defines intervals on the real line. They are used to group the entries in an index of numbers into their corresponding interval and therefore can be treated as categorical data :param (str) diag: sets the chart type for the main diagonal plots. The options are 'scatter', 'histogram' and 'box'. :param (int|float) height: sets the height of the chart :param (int|float) width: sets the width of the chart :param (float) size: sets the marker size (in px) :param (str) title: the title label of the scatterplot matrix :param (str|tuple|list|dict) colormap: either a plotly scale name, an rgb or hex color, a color tuple, a list of colors or a dictionary. An rgb color is of the form 'rgb(x, y, z)' where x, y and z belong to the interval [0, 255] and a color tuple is a tuple of the form (a, b, c) where a, b and c belong to [0, 1]. If colormap is a list, it must contain valid color types as its members. If colormap is a dictionary, all the string entries in the index column must be a key in colormap. In this case, the colormap_type is forced to 'cat' or categorical :param (str) colormap_type: determines how colormap is interpreted. Valid choices are 'seq' (sequential) and 'cat' (categorical). If 'seq' is selected, only the first two colors in colormap will be considered (when colormap is a list) and the index values will be linearly interpolated between those two colors. This option is forced if all index values are numeric. If 'cat' is selected, a color from colormap will be assigned to each category from index, including the intervals if endpts is being used :param (dict) **kwargs: a dictionary of scatterplot arguments The only forbidden parameters are 'size', 'color' and 'colorscale' in 'marker' Example 1: Vanilla Scatterplot Matrix >>> from plotly.graph_objs import graph_objs >>> from plotly.figure_factory import create_scatterplotmatrix >>> import numpy as np >>> import pandas as pd >>> # Create dataframe >>> df = pd.DataFrame(np.random.randn(10, 2), ... columns=['Column 1', 'Column 2']) >>> # Create scatterplot matrix >>> fig = create_scatterplotmatrix(df) >>> fig.show() Example 2: Indexing a Column >>> from plotly.graph_objs import graph_objs >>> from plotly.figure_factory import create_scatterplotmatrix >>> import numpy as np >>> import pandas as pd >>> # Create dataframe with index >>> df = pd.DataFrame(np.random.randn(10, 2), ... columns=['A', 'B']) >>> # Add another column of strings to the dataframe >>> df['Fruit'] = pd.Series(['apple', 'apple', 'grape', 'apple', 'apple', ... 'grape', 'pear', 'pear', 'apple', 'pear']) >>> # Create scatterplot matrix >>> fig = create_scatterplotmatrix(df, index='Fruit', size=10) >>> fig.show() Example 3: Styling the Diagonal Subplots >>> from plotly.graph_objs import graph_objs >>> from plotly.figure_factory import create_scatterplotmatrix >>> import numpy as np >>> import pandas as pd >>> # Create dataframe with index >>> df = pd.DataFrame(np.random.randn(10, 4), ... columns=['A', 'B', 'C', 'D']) >>> # Add another column of strings to the dataframe >>> df['Fruit'] = pd.Series(['apple', 'apple', 'grape', 'apple', 'apple', ... 'grape', 'pear', 'pear', 'apple', 'pear']) >>> # Create scatterplot matrix >>> fig = create_scatterplotmatrix(df, diag='box', index='Fruit', height=1000, ... width=1000) >>> fig.show() Example 4: Use a Theme to Style the Subplots >>> from plotly.graph_objs import graph_objs >>> from plotly.figure_factory import create_scatterplotmatrix >>> import numpy as np >>> import pandas as pd >>> # Create dataframe with random data >>> df = pd.DataFrame(np.random.randn(100, 3), ... columns=['A', 'B', 'C']) >>> # Create scatterplot matrix using a built-in >>> # Plotly palette scale and indexing column 'A' >>> fig = create_scatterplotmatrix(df, diag='histogram', index='A', ... colormap='Blues', height=800, width=800) >>> fig.show() Example 5: Example 4 with Interval Factoring >>> from plotly.graph_objs import graph_objs >>> from plotly.figure_factory import create_scatterplotmatrix >>> import numpy as np >>> import pandas as pd >>> # Create dataframe with random data >>> df = pd.DataFrame(np.random.randn(100, 3), ... columns=['A', 'B', 'C']) >>> # Create scatterplot matrix using a list of 2 rgb tuples >>> # and endpoints at -1, 0 and 1 >>> fig = create_scatterplotmatrix(df, diag='histogram', index='A', ... colormap=['rgb(140, 255, 50)', ... 'rgb(170, 60, 115)', '#6c4774', ... (0.5, 0.1, 0.8)], ... endpts=[-1, 0, 1], height=800, width=800) >>> fig.show() Example 6: Using the colormap as a Dictionary >>> from plotly.graph_objs import graph_objs >>> from plotly.figure_factory import create_scatterplotmatrix >>> import numpy as np >>> import pandas as pd >>> import random >>> # Create dataframe with random data >>> df = pd.DataFrame(np.random.randn(100, 3), ... columns=['Column A', ... 'Column B', ... 'Column C']) >>> # Add new color column to dataframe >>> new_column = [] >>> strange_colors = ['turquoise', 'limegreen', 'goldenrod'] >>> for j in range(100): ... new_column.append(random.choice(strange_colors)) >>> df['Colors'] = pd.Series(new_column, index=df.index) >>> # Create scatterplot matrix using a dictionary of hex color values >>> # which correspond to actual color names in 'Colors' column >>> fig = create_scatterplotmatrix( ... df, diag='box', index='Colors', ... colormap= dict( ... turquoise = '#00F5FF', ... limegreen = '#32CD32', ... goldenrod = '#DAA520' ... ), ... colormap_type='cat', ... height=800, width=800 ... ) >>> fig.show() """ # TODO: protected until #282 if dataframe is None: dataframe = [] if headers is None: headers = [] if index_vals is None: index_vals = [] validate_scatterplotmatrix(df, index, diag, colormap_type, **kwargs) # Validate colormap if isinstance(colormap, dict): colormap = clrs.validate_colors_dict(colormap, "rgb") elif ( isinstance(colormap, six.string_types) and "rgb" not in colormap and "#" not in colormap ): if colormap not in clrs.PLOTLY_SCALES.keys(): raise exceptions.PlotlyError( "If 'colormap' is a string, it must be the name " "of a Plotly Colorscale. The available colorscale " "names are {}".format(clrs.PLOTLY_SCALES.keys()) ) else: # TODO change below to allow the correct Plotly colorscale colormap = clrs.colorscale_to_colors(clrs.PLOTLY_SCALES[colormap]) # keep only first and last item - fix later colormap = [colormap[0]] + [colormap[-1]] colormap = clrs.validate_colors(colormap, "rgb") else: colormap = clrs.validate_colors(colormap, "rgb") if not index: for name in df: headers.append(name) for name in headers: dataframe.append(df[name].values.tolist()) # Check for same data-type in df columns utils.validate_dataframe(dataframe) figure = scatterplot( dataframe, headers, diag, size, height, width, title, **kwargs ) return figure else: # Validate index selection if index not in df: raise exceptions.PlotlyError( "Make sure you set the index " "input variable to one of the " "column names of your " "dataframe." ) index_vals = df[index].values.tolist() for name in df: if name != index: headers.append(name) for name in headers: dataframe.append(df[name].values.tolist()) # check for same data-type in each df column utils.validate_dataframe(dataframe) utils.validate_index(index_vals) # check if all colormap keys are in the index # if colormap is a dictionary if isinstance(colormap, dict): for key in colormap: if not all(index in colormap for index in index_vals): raise exceptions.PlotlyError( "If colormap is a " "dictionary, all the " "names in the index " "must be keys." ) figure = scatterplot_dict( dataframe, headers, diag, size, height, width, title, index, index_vals, endpts, colormap, colormap_type, **kwargs ) return figure else: figure = scatterplot_theme( dataframe, headers, diag, size, height, width, title, index, index_vals, endpts, colormap, colormap_type, **kwargs ) return figure plotly-4.4.1+dfsg.orig/plotly/figure_factory/utils.py0000644000175000017500000002057213525746125022336 0ustar noahfxnoahfxfrom __future__ import absolute_import import collections import decimal import six from plotly import exceptions from plotly.colors import ( DEFAULT_PLOTLY_COLORS, PLOTLY_SCALES, color_parser, colorscale_to_colors, colorscale_to_scale, convert_to_RGB_255, find_intermediate_color, hex_to_rgb, label_rgb, n_colors, unconvert_from_RGB_255, unlabel_rgb, validate_colors, validate_colors_dict, validate_colorscale, validate_scale_values, ) def is_sequence(obj): return isinstance(obj, collections.Sequence) and not isinstance(obj, str) def validate_index(index_vals): """ Validates if a list contains all numbers or all strings :raises: (PlotlyError) If there are any two items in the list whose types differ """ from numbers import Number if isinstance(index_vals[0], Number): if not all(isinstance(item, Number) for item in index_vals): raise exceptions.PlotlyError( "Error in indexing column. " "Make sure all entries of each " "column are all numbers or " "all strings." ) elif isinstance(index_vals[0], str): if not all(isinstance(item, str) for item in index_vals): raise exceptions.PlotlyError( "Error in indexing column. " "Make sure all entries of each " "column are all numbers or " "all strings." ) def validate_dataframe(array): """ Validates all strings or numbers in each dataframe column :raises: (PlotlyError) If there are any two items in any list whose types differ """ from numbers import Number for vector in array: if isinstance(vector[0], Number): if not all(isinstance(item, Number) for item in vector): raise exceptions.PlotlyError( "Error in dataframe. " "Make sure all entries of " "each column are either " "numbers or strings." ) elif isinstance(vector[0], str): if not all(isinstance(item, str) for item in vector): raise exceptions.PlotlyError( "Error in dataframe. " "Make sure all entries of " "each column are either " "numbers or strings." ) def validate_equal_length(*args): """ Validates that data lists or ndarrays are the same length. :raises: (PlotlyError) If any data lists are not the same length. """ length = len(args[0]) if any(len(lst) != length for lst in args): raise exceptions.PlotlyError( "Oops! Your data lists or ndarrays " "should be the same length." ) def validate_positive_scalars(**kwargs): """ Validates that all values given in key/val pairs are positive. Accepts kwargs to improve Exception messages. :raises: (PlotlyError) If any value is < 0 or raises. """ for key, val in kwargs.items(): try: if val <= 0: raise ValueError("{} must be > 0, got {}".format(key, val)) except TypeError: raise exceptions.PlotlyError("{} must be a number, got {}".format(key, val)) def flatten(array): """ Uses list comprehension to flatten array :param (array): An iterable to flatten :raises (PlotlyError): If iterable is not nested. :rtype (list): The flattened list. """ try: return [item for sublist in array for item in sublist] except TypeError: raise exceptions.PlotlyError( "Your data array could not be " "flattened! Make sure your data is " "entered as lists or ndarrays!" ) def endpts_to_intervals(endpts): """ Returns a list of intervals for categorical colormaps Accepts a list or tuple of sequentially increasing numbers and returns a list representation of the mathematical intervals with these numbers as endpoints. For example, [1, 6] returns [[-inf, 1], [1, 6], [6, inf]] :raises: (PlotlyError) If input is not a list or tuple :raises: (PlotlyError) If the input contains a string :raises: (PlotlyError) If any number does not increase after the previous one in the sequence """ length = len(endpts) # Check if endpts is a list or tuple if not (isinstance(endpts, (tuple)) or isinstance(endpts, (list))): raise exceptions.PlotlyError( "The intervals_endpts argument must " "be a list or tuple of a sequence " "of increasing numbers." ) # Check if endpts contains only numbers for item in endpts: if isinstance(item, str): raise exceptions.PlotlyError( "The intervals_endpts argument " "must be a list or tuple of a " "sequence of increasing " "numbers." ) # Check if numbers in endpts are increasing for k in range(length - 1): if endpts[k] >= endpts[k + 1]: raise exceptions.PlotlyError( "The intervals_endpts argument " "must be a list or tuple of a " "sequence of increasing " "numbers." ) else: intervals = [] # add -inf to intervals intervals.append([float("-inf"), endpts[0]]) for k in range(length - 1): interval = [] interval.append(endpts[k]) interval.append(endpts[k + 1]) intervals.append(interval) # add +inf to intervals intervals.append([endpts[length - 1], float("inf")]) return intervals def annotation_dict_for_label( text, lane, num_of_lanes, subplot_spacing, row_col="col", flipped=True, right_side=True, text_color="#0f0f0f", ): """ Returns annotation dict for label of n labels of a 1xn or nx1 subplot. :param (str) text: the text for a label. :param (int) lane: the label number for text. From 1 to n inclusive. :param (int) num_of_lanes: the number 'n' of rows or columns in subplot. :param (float) subplot_spacing: the value for the horizontal_spacing and vertical_spacing params in your plotly.tools.make_subplots() call. :param (str) row_col: choose whether labels are placed along rows or columns. :param (bool) flipped: flips text by 90 degrees. Text is printed horizontally if set to True and row_col='row', or if False and row_col='col'. :param (bool) right_side: only applicable if row_col is set to 'row'. :param (str) text_color: color of the text. """ l = (1 - (num_of_lanes - 1) * subplot_spacing) / (num_of_lanes) if not flipped: xanchor = "center" yanchor = "middle" if row_col == "col": x = (lane - 1) * (l + subplot_spacing) + 0.5 * l y = 1.03 textangle = 0 elif row_col == "row": y = (lane - 1) * (l + subplot_spacing) + 0.5 * l x = 1.03 textangle = 90 else: if row_col == "col": xanchor = "center" yanchor = "bottom" x = (lane - 1) * (l + subplot_spacing) + 0.5 * l y = 1.0 textangle = 270 elif row_col == "row": yanchor = "middle" y = (lane - 1) * (l + subplot_spacing) + 0.5 * l if right_side: x = 1.0 xanchor = "left" else: x = -0.01 xanchor = "right" textangle = 0 annotation_dict = dict( textangle=textangle, xanchor=xanchor, yanchor=yanchor, x=x, y=y, showarrow=False, xref="paper", yref="paper", text=text, font=dict(size=13, color=text_color), ) return annotation_dict def list_of_options(iterable, conj="and", period=True): """ Returns an English listing of objects seperated by commas ',' For example, ['foo', 'bar', 'baz'] becomes 'foo, bar and baz' if the conjunction 'and' is selected. """ if len(iterable) < 2: raise exceptions.PlotlyError( "Your list or tuple must contain at least 2 items." ) template = (len(iterable) - 2) * "{}, " + "{} " + conj + " {}" + period * "." return template.format(*iterable) plotly-4.4.1+dfsg.orig/plotly/figure_factory/_county_choropleth.py0000644000175000017500000010171713573717677025123 0ustar noahfxnoahfximport io import numpy as np import os import pandas as pd import warnings from math import log, floor from numbers import Number from plotly import optional_imports import plotly.colors as clrs from plotly.figure_factory import utils from plotly.exceptions import PlotlyError import plotly.graph_objs as go pd.options.mode.chained_assignment = None shapely = optional_imports.get_module("shapely") shapefile = optional_imports.get_module("shapefile") gp = optional_imports.get_module("geopandas") _plotly_geo = optional_imports.get_module("_plotly_geo") def _create_us_counties_df(st_to_state_name_dict, state_to_st_dict): # URLS abs_dir_path = os.path.realpath(_plotly_geo.__file__) abs_plotly_geo_path = os.path.dirname(abs_dir_path) abs_package_data_dir_path = os.path.join(abs_plotly_geo_path, "package_data") shape_pre2010 = "gz_2010_us_050_00_500k.shp" shape_pre2010 = os.path.join(abs_package_data_dir_path, shape_pre2010) df_shape_pre2010 = gp.read_file(shape_pre2010) df_shape_pre2010["FIPS"] = df_shape_pre2010["STATE"] + df_shape_pre2010["COUNTY"] df_shape_pre2010["FIPS"] = pd.to_numeric(df_shape_pre2010["FIPS"]) states_path = "cb_2016_us_state_500k.shp" states_path = os.path.join(abs_package_data_dir_path, states_path) df_state = gp.read_file(states_path) df_state = df_state[["STATEFP", "NAME", "geometry"]] df_state = df_state.rename(columns={"NAME": "STATE_NAME"}) filenames = [ "cb_2016_us_county_500k.dbf", "cb_2016_us_county_500k.shp", "cb_2016_us_county_500k.shx", ] for j in range(len(filenames)): filenames[j] = os.path.join(abs_package_data_dir_path, filenames[j]) dbf = io.open(filenames[0], "rb") shp = io.open(filenames[1], "rb") shx = io.open(filenames[2], "rb") r = shapefile.Reader(shp=shp, shx=shx, dbf=dbf) attributes, geometry = [], [] field_names = [field[0] for field in r.fields[1:]] for row in r.shapeRecords(): geometry.append(shapely.geometry.shape(row.shape.__geo_interface__)) attributes.append(dict(zip(field_names, row.record))) gdf = gp.GeoDataFrame(data=attributes, geometry=geometry) gdf["FIPS"] = gdf["STATEFP"] + gdf["COUNTYFP"] gdf["FIPS"] = pd.to_numeric(gdf["FIPS"]) # add missing counties f = 46113 singlerow = pd.DataFrame( [ [ st_to_state_name_dict["SD"], "SD", df_shape_pre2010[df_shape_pre2010["FIPS"] == f]["geometry"].iloc[0], df_shape_pre2010[df_shape_pre2010["FIPS"] == f]["FIPS"].iloc[0], "46", "Shannon", ] ], columns=["State", "ST", "geometry", "FIPS", "STATEFP", "NAME"], index=[max(gdf.index) + 1], ) gdf = gdf.append(singlerow, sort=True) f = 51515 singlerow = pd.DataFrame( [ [ st_to_state_name_dict["VA"], "VA", df_shape_pre2010[df_shape_pre2010["FIPS"] == f]["geometry"].iloc[0], df_shape_pre2010[df_shape_pre2010["FIPS"] == f]["FIPS"].iloc[0], "51", "Bedford City", ] ], columns=["State", "ST", "geometry", "FIPS", "STATEFP", "NAME"], index=[max(gdf.index) + 1], ) gdf = gdf.append(singlerow, sort=True) f = 2270 singlerow = pd.DataFrame( [ [ st_to_state_name_dict["AK"], "AK", df_shape_pre2010[df_shape_pre2010["FIPS"] == f]["geometry"].iloc[0], df_shape_pre2010[df_shape_pre2010["FIPS"] == f]["FIPS"].iloc[0], "02", "Wade Hampton", ] ], columns=["State", "ST", "geometry", "FIPS", "STATEFP", "NAME"], index=[max(gdf.index) + 1], ) gdf = gdf.append(singlerow, sort=True) row_2198 = gdf[gdf["FIPS"] == 2198] row_2198.index = [max(gdf.index) + 1] row_2198.loc[row_2198.index[0], "FIPS"] = 2201 row_2198.loc[row_2198.index[0], "STATEFP"] = "02" gdf = gdf.append(row_2198, sort=True) row_2105 = gdf[gdf["FIPS"] == 2105] row_2105.index = [max(gdf.index) + 1] row_2105.loc[row_2105.index[0], "FIPS"] = 2232 row_2105.loc[row_2105.index[0], "STATEFP"] = "02" gdf = gdf.append(row_2105, sort=True) gdf = gdf.rename(columns={"NAME": "COUNTY_NAME"}) gdf_reduced = gdf[["FIPS", "STATEFP", "COUNTY_NAME", "geometry"]] gdf_statefp = gdf_reduced.merge(df_state[["STATEFP", "STATE_NAME"]], on="STATEFP") ST = [] for n in gdf_statefp["STATE_NAME"]: ST.append(state_to_st_dict[n]) gdf_statefp["ST"] = ST return gdf_statefp, df_state st_to_state_name_dict = { "AK": "Alaska", "AL": "Alabama", "AR": "Arkansas", "AZ": "Arizona", "CA": "California", "CO": "Colorado", "CT": "Connecticut", "DC": "District of Columbia", "DE": "Delaware", "FL": "Florida", "GA": "Georgia", "HI": "Hawaii", "IA": "Iowa", "ID": "Idaho", "IL": "Illinois", "IN": "Indiana", "KS": "Kansas", "KY": "Kentucky", "LA": "Louisiana", "MA": "Massachusetts", "MD": "Maryland", "ME": "Maine", "MI": "Michigan", "MN": "Minnesota", "MO": "Missouri", "MS": "Mississippi", "MT": "Montana", "NC": "North Carolina", "ND": "North Dakota", "NE": "Nebraska", "NH": "New Hampshire", "NJ": "New Jersey", "NM": "New Mexico", "NV": "Nevada", "NY": "New York", "OH": "Ohio", "OK": "Oklahoma", "OR": "Oregon", "PA": "Pennsylvania", "RI": "Rhode Island", "SC": "South Carolina", "SD": "South Dakota", "TN": "Tennessee", "TX": "Texas", "UT": "Utah", "VA": "Virginia", "VT": "Vermont", "WA": "Washington", "WI": "Wisconsin", "WV": "West Virginia", "WY": "Wyoming", } state_to_st_dict = { "Alabama": "AL", "Alaska": "AK", "American Samoa": "AS", "Arizona": "AZ", "Arkansas": "AR", "California": "CA", "Colorado": "CO", "Commonwealth of the Northern Mariana Islands": "MP", "Connecticut": "CT", "Delaware": "DE", "District of Columbia": "DC", "Florida": "FL", "Georgia": "GA", "Guam": "GU", "Hawaii": "HI", "Idaho": "ID", "Illinois": "IL", "Indiana": "IN", "Iowa": "IA", "Kansas": "KS", "Kentucky": "KY", "Louisiana": "LA", "Maine": "ME", "Maryland": "MD", "Massachusetts": "MA", "Michigan": "MI", "Minnesota": "MN", "Mississippi": "MS", "Missouri": "MO", "Montana": "MT", "Nebraska": "NE", "Nevada": "NV", "New Hampshire": "NH", "New Jersey": "NJ", "New Mexico": "NM", "New York": "NY", "North Carolina": "NC", "North Dakota": "ND", "Ohio": "OH", "Oklahoma": "OK", "Oregon": "OR", "Pennsylvania": "PA", "Puerto Rico": "", "Rhode Island": "RI", "South Carolina": "SC", "South Dakota": "SD", "Tennessee": "TN", "Texas": "TX", "United States Virgin Islands": "VI", "Utah": "UT", "Vermont": "VT", "Virginia": "VA", "Washington": "WA", "West Virginia": "WV", "Wisconsin": "WI", "Wyoming": "WY", } USA_XRANGE = [-125.0, -65.0] USA_YRANGE = [25.0, 49.0] def _human_format(number): units = ["", "K", "M", "G", "T", "P"] k = 1000.0 magnitude = int(floor(log(number, k))) return "%.2f%s" % (number / k ** magnitude, units[magnitude]) def _intervals_as_labels(array_of_intervals, round_legend_values, exponent_format): """ Transform an number interval to a clean string for legend Example: [-inf, 30] to '< 30' """ infs = [float("-inf"), float("inf")] string_intervals = [] for interval in array_of_intervals: # round to 2nd decimal place if round_legend_values: rnd_interval = [ (int(interval[i]) if interval[i] not in infs else interval[i]) for i in range(2) ] else: rnd_interval = [round(interval[0], 2), round(interval[1], 2)] num0 = rnd_interval[0] num1 = rnd_interval[1] if exponent_format: if num0 not in infs: num0 = _human_format(num0) if num1 not in infs: num1 = _human_format(num1) else: if num0 not in infs: num0 = "{:,}".format(num0) if num1 not in infs: num1 = "{:,}".format(num1) if num0 == float("-inf"): as_str = "< {}".format(num1) elif num1 == float("inf"): as_str = "> {}".format(num0) else: as_str = "{} - {}".format(num0, num1) string_intervals.append(as_str) return string_intervals def _calculations( df, fips, values, index, f, simplify_county, level, x_centroids, y_centroids, centroid_text, x_traces, y_traces, fips_polygon_map, ): # 0-pad FIPS code to ensure exactly 5 digits padded_f = str(f).zfill(5) if fips_polygon_map[f].type == "Polygon": x = fips_polygon_map[f].simplify(simplify_county).exterior.xy[0].tolist() y = fips_polygon_map[f].simplify(simplify_county).exterior.xy[1].tolist() x_c, y_c = fips_polygon_map[f].centroid.xy county_name_str = str(df[df["FIPS"] == f]["COUNTY_NAME"].iloc[0]) state_name_str = str(df[df["FIPS"] == f]["STATE_NAME"].iloc[0]) t_c = ( "County: " + county_name_str + "
" + "State: " + state_name_str + "
" + "FIPS: " + padded_f + "
Value: " + str(values[index]) ) x_centroids.append(x_c[0]) y_centroids.append(y_c[0]) centroid_text.append(t_c) x_traces[level] = x_traces[level] + x + [np.nan] y_traces[level] = y_traces[level] + y + [np.nan] elif fips_polygon_map[f].type == "MultiPolygon": x = [ poly.simplify(simplify_county).exterior.xy[0].tolist() for poly in fips_polygon_map[f] ] y = [ poly.simplify(simplify_county).exterior.xy[1].tolist() for poly in fips_polygon_map[f] ] x_c = [poly.centroid.xy[0].tolist() for poly in fips_polygon_map[f]] y_c = [poly.centroid.xy[1].tolist() for poly in fips_polygon_map[f]] county_name_str = str(df[df["FIPS"] == f]["COUNTY_NAME"].iloc[0]) state_name_str = str(df[df["FIPS"] == f]["STATE_NAME"].iloc[0]) text = ( "County: " + county_name_str + "
" + "State: " + state_name_str + "
" + "FIPS: " + padded_f + "
Value: " + str(values[index]) ) t_c = [text for poly in fips_polygon_map[f]] x_centroids = x_c + x_centroids y_centroids = y_c + y_centroids centroid_text = t_c + centroid_text for x_y_idx in range(len(x)): x_traces[level] = x_traces[level] + x[x_y_idx] + [np.nan] y_traces[level] = y_traces[level] + y[x_y_idx] + [np.nan] return x_traces, y_traces, x_centroids, y_centroids, centroid_text def create_choropleth( fips, values, scope=["usa"], binning_endpoints=None, colorscale=None, order=None, simplify_county=0.02, simplify_state=0.02, asp=None, show_hover=True, show_state_data=True, state_outline=None, county_outline=None, centroid_marker=None, round_legend_values=False, exponent_format=False, legend_title="", **layout_options ): """ Returns figure for county choropleth. Uses data from package_data. :param (list) fips: list of FIPS values which correspond to the con catination of state and county ids. An example is '01001'. :param (list) values: list of numbers/strings which correspond to the fips list. These are the values that will determine how the counties are colored. :param (list) scope: list of states and/or states abbreviations. Fits all states in the camera tightly. Selecting ['usa'] is the equivalent of appending all 50 states into your scope list. Selecting only 'usa' does not include 'Alaska', 'Puerto Rico', 'American Samoa', 'Commonwealth of the Northern Mariana Islands', 'Guam', 'United States Virgin Islands'. These must be added manually to the list. Default = ['usa'] :param (list) binning_endpoints: ascending numbers which implicitly define real number intervals which are used as bins. The colorscale used must have the same number of colors as the number of bins and this will result in a categorical colormap. :param (list) colorscale: a list of colors with length equal to the number of categories of colors. The length must match either all unique numbers in the 'values' list or if endpoints is being used, the number of categories created by the endpoints.\n For example, if binning_endpoints = [4, 6, 8], then there are 4 bins: [-inf, 4), [4, 6), [6, 8), [8, inf) :param (list) order: a list of the unique categories (numbers/bins) in any desired order. This is helpful if you want to order string values to a chosen colorscale. :param (float) simplify_county: determines the simplification factor for the counties. The larger the number, the fewer vertices and edges each polygon has. See http://toblerity.org/shapely/manual.html#object.simplify for more information. Default = 0.02 :param (float) simplify_state: simplifies the state outline polygon. See http://toblerity.org/shapely/manual.html#object.simplify for more information. Default = 0.02 :param (float) asp: the width-to-height aspect ratio for the camera. Default = 2.5 :param (bool) show_hover: show county hover and centroid info :param (bool) show_state_data: reveals state boundary lines :param (dict) state_outline: dict of attributes of the state outline including width and color. See https://plot.ly/python/reference/#scatter-marker-line for all valid params :param (dict) county_outline: dict of attributes of the county outline including width and color. See https://plot.ly/python/reference/#scatter-marker-line for all valid params :param (dict) centroid_marker: dict of attributes of the centroid marker. The centroid markers are invisible by default and appear visible on selection. See https://plot.ly/python/reference/#scatter-marker for all valid params :param (bool) round_legend_values: automatically round the numbers that appear in the legend to the nearest integer. Default = False :param (bool) exponent_format: if set to True, puts numbers in the K, M, B number format. For example 4000.0 becomes 4.0K Default = False :param (str) legend_title: title that appears above the legend :param **layout_options: a **kwargs argument for all layout parameters Example 1: Florida:: import plotly.plotly as py import plotly.figure_factory as ff import numpy as np import pandas as pd df_sample = pd.read_csv( 'https://raw.githubusercontent.com/plotly/datasets/master/minoritymajority.csv' ) df_sample_r = df_sample[df_sample['STNAME'] == 'Florida'] values = df_sample_r['TOT_POP'].tolist() fips = df_sample_r['FIPS'].tolist() binning_endpoints = list(np.mgrid[min(values):max(values):4j]) colorscale = ["#030512","#1d1d3b","#323268","#3d4b94","#3e6ab0", "#4989bc","#60a7c7","#85c5d3","#b7e0e4","#eafcfd"] fig = ff.create_choropleth( fips=fips, values=values, scope=['Florida'], show_state_data=True, colorscale=colorscale, binning_endpoints=binning_endpoints, round_legend_values=True, plot_bgcolor='rgb(229,229,229)', paper_bgcolor='rgb(229,229,229)', legend_title='Florida Population', county_outline={'color': 'rgb(255,255,255)', 'width': 0.5}, exponent_format=True, ) Example 2: New England ``` import plotly.plotly as py import plotly.figure_factory as ff import pandas as pd NE_states = ['Connecticut', 'Maine', 'Massachusetts', 'New Hampshire', 'Rhode Island'] df_sample = pd.read_csv( 'https://raw.githubusercontent.com/plotly/datasets/master/minoritymajority.csv' ) df_sample_r = df_sample[df_sample['STNAME'].isin(NE_states)] colorscale = ['rgb(68.0, 1.0, 84.0)', 'rgb(66.0, 64.0, 134.0)', 'rgb(38.0, 130.0, 142.0)', 'rgb(63.0, 188.0, 115.0)', 'rgb(216.0, 226.0, 25.0)'] values = df_sample_r['TOT_POP'].tolist() fips = df_sample_r['FIPS'].tolist() fig = ff.create_choropleth( fips=fips, values=values, scope=NE_states, show_state_data=True ) py.iplot(fig, filename='choropleth_new_england') ``` Example 3: California and Surrounding States ``` import plotly.plotly as py import plotly.figure_factory as ff import pandas as pd df_sample = pd.read_csv( 'https://raw.githubusercontent.com/plotly/datasets/master/minoritymajority.csv' ) df_sample_r = df_sample[df_sample['STNAME'] == 'California'] values = df_sample_r['TOT_POP'].tolist() fips = df_sample_r['FIPS'].tolist() colorscale = [ 'rgb(193, 193, 193)', 'rgb(239,239,239)', 'rgb(195, 196, 222)', 'rgb(144,148,194)', 'rgb(101,104,168)', 'rgb(65, 53, 132)' ] fig = ff.create_choropleth( fips=fips, values=values, colorscale=colorscale, scope=['CA', 'AZ', 'Nevada', 'Oregon', ' Idaho'], binning_endpoints=[14348, 63983, 134827, 426762, 2081313], county_outline={'color': 'rgb(255,255,255)', 'width': 0.5}, legend_title='California Counties', title='California and Nearby States' ) py.iplot(fig, filename='choropleth_california_and_surr_states_outlines') ``` Example 4: USA ``` import plotly.plotly as py import plotly.figure_factory as ff import numpy as np import pandas as pd df_sample = pd.read_csv( 'https://raw.githubusercontent.com/plotly/datasets/master/laucnty16.csv' ) df_sample['State FIPS Code'] = df_sample['State FIPS Code'].apply( lambda x: str(x).zfill(2) ) df_sample['County FIPS Code'] = df_sample['County FIPS Code'].apply( lambda x: str(x).zfill(3) ) df_sample['FIPS'] = ( df_sample['State FIPS Code'] + df_sample['County FIPS Code'] ) binning_endpoints = list(np.linspace(1, 12, len(colorscale) - 1)) colorscale = ["#f7fbff", "#ebf3fb", "#deebf7", "#d2e3f3", "#c6dbef", "#b3d2e9", "#9ecae1", "#85bcdb", "#6baed6", "#57a0ce", "#4292c6", "#3082be", "#2171b5", "#1361a9", "#08519c", "#0b4083","#08306b"] fips = df_sample['FIPS'] values = df_sample['Unemployment Rate (%)'] fig = ff.create_choropleth( fips=fips, values=values, scope=['usa'], binning_endpoints=binning_endpoints, colorscale=colorscale, show_hover=True, centroid_marker={'opacity': 0}, asp=2.9, title='USA by Unemployment %', legend_title='Unemployment %' ) py.iplot(fig, filename='choropleth_full_usa') ``` """ # ensure optional modules imported if not _plotly_geo: raise ValueError( """ The create_choropleth figure factory requires the plotly-geo package. Install using pip with: $ pip install plotly-geo Or, install using conda with $ conda install -c plotly plotly-geo """ ) if not gp or not shapefile or not shapely: raise ImportError( "geopandas, pyshp and shapely must be installed for this figure " "factory.\n\nRun the following commands to install the correct " "versions of the following modules:\n\n" "```\n" "$ pip install geopandas==0.3.0\n" "$ pip install pyshp==1.2.10\n" "$ pip install shapely==1.6.3\n" "```\n" "If you are using Windows, follow this post to properly " "install geopandas and dependencies:" "http://geoffboeing.com/2014/09/using-geopandas-windows/\n\n" "If you are using Anaconda, do not use PIP to install the " "packages above. Instead use conda to install them:\n\n" "```\n" "$ conda install plotly\n" "$ conda install geopandas\n" "```" ) df, df_state = _create_us_counties_df(st_to_state_name_dict, state_to_st_dict) fips_polygon_map = dict(zip(df["FIPS"].tolist(), df["geometry"].tolist())) if not state_outline: state_outline = {"color": "rgb(240, 240, 240)", "width": 1} if not county_outline: county_outline = {"color": "rgb(0, 0, 0)", "width": 0} if not centroid_marker: centroid_marker = {"size": 3, "color": "white", "opacity": 1} # ensure centroid markers appear on selection if "opacity" not in centroid_marker: centroid_marker.update({"opacity": 1}) if len(fips) != len(values): raise PlotlyError("fips and values must be the same length") # make fips, values into lists if isinstance(fips, pd.core.series.Series): fips = fips.tolist() if isinstance(values, pd.core.series.Series): values = values.tolist() # make fips numeric fips = map(lambda x: int(x), fips) if binning_endpoints: intervals = utils.endpts_to_intervals(binning_endpoints) LEVELS = _intervals_as_labels(intervals, round_legend_values, exponent_format) else: if not order: LEVELS = sorted(list(set(values))) else: # check if order is permutation # of unique color col values same_sets = sorted(list(set(values))) == set(order) no_duplicates = not any(order.count(x) > 1 for x in order) if same_sets and no_duplicates: LEVELS = order else: raise PlotlyError( "if you are using a custom order of unique values from " "your color column, you must: have all the unique values " "in your order and have no duplicate items" ) if not colorscale: colorscale = [] viridis_colors = clrs.colorscale_to_colors(clrs.PLOTLY_SCALES["Viridis"]) viridis_colors = clrs.color_parser(viridis_colors, clrs.hex_to_rgb) viridis_colors = clrs.color_parser(viridis_colors, clrs.label_rgb) viri_len = len(viridis_colors) + 1 viri_intervals = utils.endpts_to_intervals(list(np.linspace(0, 1, viri_len)))[ 1:-1 ] for L in np.linspace(0, 1, len(LEVELS)): for idx, inter in enumerate(viri_intervals): if L == 0: break elif inter[0] < L <= inter[1]: break intermed = (L - viri_intervals[idx][0]) / ( viri_intervals[idx][1] - viri_intervals[idx][0] ) float_color = clrs.find_intermediate_color( viridis_colors[idx], viridis_colors[idx], intermed, colortype="rgb" ) # make R,G,B into int values float_color = clrs.unlabel_rgb(float_color) float_color = clrs.unconvert_from_RGB_255(float_color) int_rgb = clrs.convert_to_RGB_255(float_color) int_rgb = clrs.label_rgb(int_rgb) colorscale.append(int_rgb) if len(colorscale) < len(LEVELS): raise PlotlyError( "You have {} LEVELS. Your number of colors in 'colorscale' must " "be at least the number of LEVELS: {}. If you are " "using 'binning_endpoints' then 'colorscale' must have at " "least len(binning_endpoints) + 2 colors".format( len(LEVELS), min(LEVELS, LEVELS[:20]) ) ) color_lookup = dict(zip(LEVELS, colorscale)) x_traces = dict(zip(LEVELS, [[] for i in range(len(LEVELS))])) y_traces = dict(zip(LEVELS, [[] for i in range(len(LEVELS))])) # scope if isinstance(scope, str): raise PlotlyError("'scope' must be a list/tuple/sequence") scope_names = [] extra_states = [ "Alaska", "Commonwealth of the Northern Mariana Islands", "Puerto Rico", "Guam", "United States Virgin Islands", "American Samoa", ] for state in scope: if state.lower() == "usa": scope_names = df["STATE_NAME"].unique() scope_names = list(scope_names) for ex_st in extra_states: try: scope_names.remove(ex_st) except ValueError: pass else: if state in st_to_state_name_dict.keys(): state = st_to_state_name_dict[state] scope_names.append(state) df_state = df_state[df_state["STATE_NAME"].isin(scope_names)] plot_data = [] x_centroids = [] y_centroids = [] centroid_text = [] fips_not_in_shapefile = [] if not binning_endpoints: for index, f in enumerate(fips): level = values[index] try: fips_polygon_map[f].type ( x_traces, y_traces, x_centroids, y_centroids, centroid_text, ) = _calculations( df, fips, values, index, f, simplify_county, level, x_centroids, y_centroids, centroid_text, x_traces, y_traces, fips_polygon_map, ) except KeyError: fips_not_in_shapefile.append(f) else: for index, f in enumerate(fips): for j, inter in enumerate(intervals): if inter[0] < values[index] <= inter[1]: break level = LEVELS[j] try: fips_polygon_map[f].type ( x_traces, y_traces, x_centroids, y_centroids, centroid_text, ) = _calculations( df, fips, values, index, f, simplify_county, level, x_centroids, y_centroids, centroid_text, x_traces, y_traces, fips_polygon_map, ) except KeyError: fips_not_in_shapefile.append(f) if len(fips_not_in_shapefile) > 0: msg = ( "Unrecognized FIPS Values\n\nWhoops! It looks like you are " "trying to pass at least one FIPS value that is not in " "our shapefile of FIPS and data for the counties. Your " "choropleth will still show up but these counties cannot " "be shown.\nUnrecognized FIPS are: {}".format(fips_not_in_shapefile) ) warnings.warn(msg) x_states = [] y_states = [] for index, row in df_state.iterrows(): if df_state["geometry"][index].type == "Polygon": x = row.geometry.simplify(simplify_state).exterior.xy[0].tolist() y = row.geometry.simplify(simplify_state).exterior.xy[1].tolist() x_states = x_states + x y_states = y_states + y elif df_state["geometry"][index].type == "MultiPolygon": x = [ poly.simplify(simplify_state).exterior.xy[0].tolist() for poly in df_state["geometry"][index] ] y = [ poly.simplify(simplify_state).exterior.xy[1].tolist() for poly in df_state["geometry"][index] ] for segment in range(len(x)): x_states = x_states + x[segment] y_states = y_states + y[segment] x_states.append(np.nan) y_states.append(np.nan) x_states.append(np.nan) y_states.append(np.nan) for lev in LEVELS: county_data = dict( type="scatter", mode="lines", x=x_traces[lev], y=y_traces[lev], line=county_outline, fill="toself", fillcolor=color_lookup[lev], name=lev, hoverinfo="none", ) plot_data.append(county_data) if show_hover: hover_points = dict( type="scatter", showlegend=False, legendgroup="centroids", x=x_centroids, y=y_centroids, text=centroid_text, name="US Counties", mode="markers", marker={"color": "white", "opacity": 0}, hoverinfo="text", ) centroids_on_select = dict( selected=dict(marker=centroid_marker), unselected=dict(marker=dict(opacity=0)), ) hover_points.update(centroids_on_select) plot_data.append(hover_points) if show_state_data: state_data = dict( type="scatter", legendgroup="States", line=state_outline, x=x_states, y=y_states, hoverinfo="text", showlegend=False, mode="lines", ) plot_data.append(state_data) DEFAULT_LAYOUT = dict( hovermode="closest", xaxis=dict( autorange=False, range=USA_XRANGE, showgrid=False, zeroline=False, fixedrange=True, showticklabels=False, ), yaxis=dict( autorange=False, range=USA_YRANGE, showgrid=False, zeroline=False, fixedrange=True, showticklabels=False, ), margin=dict(t=40, b=20, r=20, l=20), width=900, height=450, dragmode="select", legend=dict(traceorder="reversed", xanchor="right", yanchor="top", x=1, y=1), annotations=[], ) fig = dict(data=plot_data, layout=DEFAULT_LAYOUT) fig["layout"].update(layout_options) fig["layout"]["annotations"].append( dict( x=1, y=1.05, xref="paper", yref="paper", xanchor="right", showarrow=False, text="" + legend_title + "", ) ) if len(scope) == 1 and scope[0].lower() == "usa": xaxis_range_low = -125.0 xaxis_range_high = -55.0 yaxis_range_low = 25.0 yaxis_range_high = 49.0 else: xaxis_range_low = float("inf") xaxis_range_high = float("-inf") yaxis_range_low = float("inf") yaxis_range_high = float("-inf") for trace in fig["data"]: if all(isinstance(n, Number) for n in trace["x"]): calc_x_min = min(trace["x"] or [float("inf")]) calc_x_max = max(trace["x"] or [float("-inf")]) if calc_x_min < xaxis_range_low: xaxis_range_low = calc_x_min if calc_x_max > xaxis_range_high: xaxis_range_high = calc_x_max if all(isinstance(n, Number) for n in trace["y"]): calc_y_min = min(trace["y"] or [float("inf")]) calc_y_max = max(trace["y"] or [float("-inf")]) if calc_y_min < yaxis_range_low: yaxis_range_low = calc_y_min if calc_y_max > yaxis_range_high: yaxis_range_high = calc_y_max # camera zoom fig["layout"]["xaxis"]["range"] = [xaxis_range_low, xaxis_range_high] fig["layout"]["yaxis"]["range"] = [yaxis_range_low, yaxis_range_high] # aspect ratio if asp is None: usa_x_range = USA_XRANGE[1] - USA_XRANGE[0] usa_y_range = USA_YRANGE[1] - USA_YRANGE[0] asp = usa_x_range / usa_y_range # based on your figure width = float( fig["layout"]["xaxis"]["range"][1] - fig["layout"]["xaxis"]["range"][0] ) height = float( fig["layout"]["yaxis"]["range"][1] - fig["layout"]["yaxis"]["range"][0] ) center = ( sum(fig["layout"]["xaxis"]["range"]) / 2.0, sum(fig["layout"]["yaxis"]["range"]) / 2.0, ) if height / width > (1 / asp): new_width = asp * height fig["layout"]["xaxis"]["range"][0] = center[0] - new_width * 0.5 fig["layout"]["xaxis"]["range"][1] = center[0] + new_width * 0.5 else: new_height = (1 / asp) * width fig["layout"]["yaxis"]["range"][0] = center[1] - new_height * 0.5 fig["layout"]["yaxis"]["range"][1] = center[1] + new_height * 0.5 return go.Figure(fig) plotly-4.4.1+dfsg.orig/plotly/figure_factory/_gantt.py0000644000175000017500000010366113573717677022470 0ustar noahfxnoahfxfrom __future__ import absolute_import from numbers import Number import copy from plotly import exceptions, optional_imports import plotly.colors as clrs from plotly.figure_factory import utils import plotly.graph_objects as go pd = optional_imports.get_module("pandas") REQUIRED_GANTT_KEYS = ["Task", "Start", "Finish"] def _get_corner_points(x0, y0, x1, y1): """ Returns the corner points of a scatter rectangle :param x0: x-start :param y0: y-lower :param x1: x-end :param y1: y-upper :return: ([x], [y]), tuple of lists containing the x and y values """ return ([x0, x1, x1, x0], [y0, y0, y1, y1]) def validate_gantt(df): """ Validates the inputted dataframe or list """ if pd and isinstance(df, pd.core.frame.DataFrame): # validate that df has all the required keys for key in REQUIRED_GANTT_KEYS: if key not in df: raise exceptions.PlotlyError( "The columns in your dataframe must include the " "following keys: {0}".format(", ".join(REQUIRED_GANTT_KEYS)) ) num_of_rows = len(df.index) chart = [] for index in range(num_of_rows): task_dict = {} for key in df: task_dict[key] = df.ix[index][key] chart.append(task_dict) return chart # validate if df is a list if not isinstance(df, list): raise exceptions.PlotlyError( "You must input either a dataframe " "or a list of dictionaries." ) # validate if df is empty if len(df) <= 0: raise exceptions.PlotlyError( "Your list is empty. It must contain " "at least one dictionary." ) if not isinstance(df[0], dict): raise exceptions.PlotlyError("Your list must only " "include dictionaries.") return df def gantt( chart, colors, title, bar_width, showgrid_x, showgrid_y, height, width, tasks=None, task_names=None, data=None, group_tasks=False, show_hover_fill=True, show_colorbar=True, ): """ Refer to create_gantt() for docstring """ if tasks is None: tasks = [] if task_names is None: task_names = [] if data is None: data = [] for index in range(len(chart)): task = dict( x0=chart[index]["Start"], x1=chart[index]["Finish"], name=chart[index]["Task"], ) if "Description" in chart[index]: task["description"] = chart[index]["Description"] tasks.append(task) # create a scatter trace for every task group scatter_data_dict = dict() marker_data_dict = dict() if show_hover_fill: hoverinfo = "name" else: hoverinfo = "skip" scatter_data_template = { "x": [], "y": [], "mode": "none", "fill": "toself", "hoverinfo": hoverinfo, } marker_data_template = { "x": [], "y": [], "mode": "markers", "text": [], "marker": dict(color="", size=1, opacity=0), "name": "", "showlegend": False, } # create the list of task names for index in range(len(tasks)): tn = tasks[index]["name"] # Is added to task_names if group_tasks is set to False, # or if the option is used (True) it only adds them if the # name is not already in the list if not group_tasks or tn not in task_names: task_names.append(tn) # Guarantees that for grouped tasks the tasks that are inserted first # are shown at the top if group_tasks: task_names.reverse() color_index = 0 for index in range(len(tasks)): tn = tasks[index]["name"] del tasks[index]["name"] # If group_tasks is True, all tasks with the same name belong # to the same row. groupID = index if group_tasks: groupID = task_names.index(tn) tasks[index]["y0"] = groupID - bar_width tasks[index]["y1"] = groupID + bar_width # check if colors need to be looped if color_index >= len(colors): color_index = 0 tasks[index]["fillcolor"] = colors[color_index] color_id = tasks[index]["fillcolor"] if color_id not in scatter_data_dict: scatter_data_dict[color_id] = copy.deepcopy(scatter_data_template) scatter_data_dict[color_id]["fillcolor"] = color_id scatter_data_dict[color_id]["name"] = str(tn) scatter_data_dict[color_id]["legendgroup"] = color_id # if there are already values append the gap if len(scatter_data_dict[color_id]["x"]) > 0: # a gap on the scatterplot separates the rectangles from each other scatter_data_dict[color_id]["x"].append( scatter_data_dict[color_id]["x"][-1] ) scatter_data_dict[color_id]["y"].append(None) xs, ys = _get_corner_points( tasks[index]["x0"], tasks[index]["y0"], tasks[index]["x1"], tasks[index]["y1"], ) scatter_data_dict[color_id]["x"] += xs scatter_data_dict[color_id]["y"] += ys # append dummy markers for showing start and end of interval if color_id not in marker_data_dict: marker_data_dict[color_id] = copy.deepcopy(marker_data_template) marker_data_dict[color_id]["marker"]["color"] = color_id marker_data_dict[color_id]["legendgroup"] = color_id marker_data_dict[color_id]["x"].append(tasks[index]["x0"]) marker_data_dict[color_id]["x"].append(tasks[index]["x1"]) marker_data_dict[color_id]["y"].append(groupID) marker_data_dict[color_id]["y"].append(groupID) if "description" in tasks[index]: marker_data_dict[color_id]["text"].append(tasks[index]["description"]) marker_data_dict[color_id]["text"].append(tasks[index]["description"]) del tasks[index]["description"] else: marker_data_dict[color_id]["text"].append(None) marker_data_dict[color_id]["text"].append(None) color_index += 1 showlegend = show_colorbar layout = dict( title=title, showlegend=showlegend, height=height, width=width, shapes=[], hovermode="closest", yaxis=dict( showgrid=showgrid_y, ticktext=task_names, tickvals=list(range(len(task_names))), range=[-1, len(task_names) + 1], autorange=False, zeroline=False, ), xaxis=dict( showgrid=showgrid_x, zeroline=False, rangeselector=dict( buttons=list( [ dict(count=7, label="1w", step="day", stepmode="backward"), dict(count=1, label="1m", step="month", stepmode="backward"), dict(count=6, label="6m", step="month", stepmode="backward"), dict(count=1, label="YTD", step="year", stepmode="todate"), dict(count=1, label="1y", step="year", stepmode="backward"), dict(step="all"), ] ) ), type="date", ), ) data = [scatter_data_dict[k] for k in sorted(scatter_data_dict)] data += [marker_data_dict[k] for k in sorted(marker_data_dict)] # fig = dict( # data=data, layout=layout # ) fig = go.Figure(data=data, layout=layout) return fig def gantt_colorscale( chart, colors, title, index_col, show_colorbar, bar_width, showgrid_x, showgrid_y, height, width, tasks=None, task_names=None, data=None, group_tasks=False, show_hover_fill=True, ): """ Refer to FigureFactory.create_gantt() for docstring """ if tasks is None: tasks = [] if task_names is None: task_names = [] if data is None: data = [] showlegend = False for index in range(len(chart)): task = dict( x0=chart[index]["Start"], x1=chart[index]["Finish"], name=chart[index]["Task"], ) if "Description" in chart[index]: task["description"] = chart[index]["Description"] tasks.append(task) # create a scatter trace for every task group scatter_data_dict = dict() # create scatter traces for the start- and endpoints marker_data_dict = dict() if show_hover_fill: hoverinfo = "name" else: hoverinfo = "skip" scatter_data_template = { "x": [], "y": [], "mode": "none", "fill": "toself", "showlegend": False, "hoverinfo": hoverinfo, "legendgroup": "", } marker_data_template = { "x": [], "y": [], "mode": "markers", "text": [], "marker": dict(color="", size=1, opacity=0), "name": "", "showlegend": False, "legendgroup": "", } index_vals = [] for row in range(len(tasks)): if chart[row][index_col] not in index_vals: index_vals.append(chart[row][index_col]) index_vals.sort() # compute the color for task based on indexing column if isinstance(chart[0][index_col], Number): # check that colors has at least 2 colors if len(colors) < 2: raise exceptions.PlotlyError( "You must use at least 2 colors in 'colors' if you " "are using a colorscale. However only the first two " "colors given will be used for the lower and upper " "bounds on the colormap." ) # create the list of task names for index in range(len(tasks)): tn = tasks[index]["name"] # Is added to task_names if group_tasks is set to False, # or if the option is used (True) it only adds them if the # name is not already in the list if not group_tasks or tn not in task_names: task_names.append(tn) # Guarantees that for grouped tasks the tasks that are inserted # first are shown at the top if group_tasks: task_names.reverse() for index in range(len(tasks)): tn = tasks[index]["name"] del tasks[index]["name"] # If group_tasks is True, all tasks with the same name belong # to the same row. groupID = index if group_tasks: groupID = task_names.index(tn) tasks[index]["y0"] = groupID - bar_width tasks[index]["y1"] = groupID + bar_width # unlabel color colors = clrs.color_parser(colors, clrs.unlabel_rgb) lowcolor = colors[0] highcolor = colors[1] intermed = (chart[index][index_col]) / 100.0 intermed_color = clrs.find_intermediate_color(lowcolor, highcolor, intermed) intermed_color = clrs.color_parser(intermed_color, clrs.label_rgb) tasks[index]["fillcolor"] = intermed_color color_id = tasks[index]["fillcolor"] if color_id not in scatter_data_dict: scatter_data_dict[color_id] = copy.deepcopy(scatter_data_template) scatter_data_dict[color_id]["fillcolor"] = color_id scatter_data_dict[color_id]["name"] = str(chart[index][index_col]) scatter_data_dict[color_id]["legendgroup"] = color_id # relabel colors with 'rgb' colors = clrs.color_parser(colors, clrs.label_rgb) # if there are already values append the gap if len(scatter_data_dict[color_id]["x"]) > 0: # a gap on the scatterplot separates the rectangles from each other scatter_data_dict[color_id]["x"].append( scatter_data_dict[color_id]["x"][-1] ) scatter_data_dict[color_id]["y"].append(None) xs, ys = _get_corner_points( tasks[index]["x0"], tasks[index]["y0"], tasks[index]["x1"], tasks[index]["y1"], ) scatter_data_dict[color_id]["x"] += xs scatter_data_dict[color_id]["y"] += ys # append dummy markers for showing start and end of interval if color_id not in marker_data_dict: marker_data_dict[color_id] = copy.deepcopy(marker_data_template) marker_data_dict[color_id]["marker"]["color"] = color_id marker_data_dict[color_id]["legendgroup"] = color_id marker_data_dict[color_id]["x"].append(tasks[index]["x0"]) marker_data_dict[color_id]["x"].append(tasks[index]["x1"]) marker_data_dict[color_id]["y"].append(groupID) marker_data_dict[color_id]["y"].append(groupID) if "description" in tasks[index]: marker_data_dict[color_id]["text"].append(tasks[index]["description"]) marker_data_dict[color_id]["text"].append(tasks[index]["description"]) del tasks[index]["description"] else: marker_data_dict[color_id]["text"].append(None) marker_data_dict[color_id]["text"].append(None) # add colorbar to one of the traces randomly just for display if show_colorbar is True: k = list(marker_data_dict.keys())[0] marker_data_dict[k]["marker"].update( dict( colorscale=[[0, colors[0]], [1, colors[1]]], showscale=True, cmax=100, cmin=0, ) ) if isinstance(chart[0][index_col], str): index_vals = [] for row in range(len(tasks)): if chart[row][index_col] not in index_vals: index_vals.append(chart[row][index_col]) index_vals.sort() if len(colors) < len(index_vals): raise exceptions.PlotlyError( "Error. The number of colors in 'colors' must be no less " "than the number of unique index values in your group " "column." ) # make a dictionary assignment to each index value index_vals_dict = {} # define color index c_index = 0 for key in index_vals: if c_index > len(colors) - 1: c_index = 0 index_vals_dict[key] = colors[c_index] c_index += 1 # create the list of task names for index in range(len(tasks)): tn = tasks[index]["name"] # Is added to task_names if group_tasks is set to False, # or if the option is used (True) it only adds them if the # name is not already in the list if not group_tasks or tn not in task_names: task_names.append(tn) # Guarantees that for grouped tasks the tasks that are inserted # first are shown at the top if group_tasks: task_names.reverse() for index in range(len(tasks)): tn = tasks[index]["name"] del tasks[index]["name"] # If group_tasks is True, all tasks with the same name belong # to the same row. groupID = index if group_tasks: groupID = task_names.index(tn) tasks[index]["y0"] = groupID - bar_width tasks[index]["y1"] = groupID + bar_width tasks[index]["fillcolor"] = index_vals_dict[chart[index][index_col]] color_id = tasks[index]["fillcolor"] if color_id not in scatter_data_dict: scatter_data_dict[color_id] = copy.deepcopy(scatter_data_template) scatter_data_dict[color_id]["fillcolor"] = color_id scatter_data_dict[color_id]["legendgroup"] = color_id scatter_data_dict[color_id]["name"] = str(chart[index][index_col]) # relabel colors with 'rgb' colors = clrs.color_parser(colors, clrs.label_rgb) # if there are already values append the gap if len(scatter_data_dict[color_id]["x"]) > 0: # a gap on the scatterplot separates the rectangles from each other scatter_data_dict[color_id]["x"].append( scatter_data_dict[color_id]["x"][-1] ) scatter_data_dict[color_id]["y"].append(None) xs, ys = _get_corner_points( tasks[index]["x0"], tasks[index]["y0"], tasks[index]["x1"], tasks[index]["y1"], ) scatter_data_dict[color_id]["x"] += xs scatter_data_dict[color_id]["y"] += ys # append dummy markers for showing start and end of interval if color_id not in marker_data_dict: marker_data_dict[color_id] = copy.deepcopy(marker_data_template) marker_data_dict[color_id]["marker"]["color"] = color_id marker_data_dict[color_id]["legendgroup"] = color_id marker_data_dict[color_id]["x"].append(tasks[index]["x0"]) marker_data_dict[color_id]["x"].append(tasks[index]["x1"]) marker_data_dict[color_id]["y"].append(groupID) marker_data_dict[color_id]["y"].append(groupID) if "description" in tasks[index]: marker_data_dict[color_id]["text"].append(tasks[index]["description"]) marker_data_dict[color_id]["text"].append(tasks[index]["description"]) del tasks[index]["description"] else: marker_data_dict[color_id]["text"].append(None) marker_data_dict[color_id]["text"].append(None) if show_colorbar is True: showlegend = True for k in scatter_data_dict: scatter_data_dict[k]["showlegend"] = showlegend # add colorbar to one of the traces randomly just for display # if show_colorbar is True: # k = list(marker_data_dict.keys())[0] # marker_data_dict[k]["marker"].update( # dict( # colorscale=[[0, colors[0]], [1, colors[1]]], # showscale=True, # cmax=100, # cmin=0, # ) # ) layout = dict( title=title, showlegend=showlegend, height=height, width=width, shapes=[], hovermode="closest", yaxis=dict( showgrid=showgrid_y, ticktext=task_names, tickvals=list(range(len(task_names))), range=[-1, len(task_names) + 1], autorange=False, zeroline=False, ), xaxis=dict( showgrid=showgrid_x, zeroline=False, rangeselector=dict( buttons=list( [ dict(count=7, label="1w", step="day", stepmode="backward"), dict(count=1, label="1m", step="month", stepmode="backward"), dict(count=6, label="6m", step="month", stepmode="backward"), dict(count=1, label="YTD", step="year", stepmode="todate"), dict(count=1, label="1y", step="year", stepmode="backward"), dict(step="all"), ] ) ), type="date", ), ) data = [scatter_data_dict[k] for k in sorted(scatter_data_dict)] data += [marker_data_dict[k] for k in sorted(marker_data_dict)] # fig = dict( # data=data, layout=layout # ) fig = go.Figure(data=data, layout=layout) return fig def gantt_dict( chart, colors, title, index_col, show_colorbar, bar_width, showgrid_x, showgrid_y, height, width, tasks=None, task_names=None, data=None, group_tasks=False, show_hover_fill=True, ): """ Refer to FigureFactory.create_gantt() for docstring """ if tasks is None: tasks = [] if task_names is None: task_names = [] if data is None: data = [] showlegend = False for index in range(len(chart)): task = dict( x0=chart[index]["Start"], x1=chart[index]["Finish"], name=chart[index]["Task"], ) if "Description" in chart[index]: task["description"] = chart[index]["Description"] tasks.append(task) # create a scatter trace for every task group scatter_data_dict = dict() # create scatter traces for the start- and endpoints marker_data_dict = dict() if show_hover_fill: hoverinfo = "name" else: hoverinfo = "skip" scatter_data_template = { "x": [], "y": [], "mode": "none", "fill": "toself", "hoverinfo": hoverinfo, "legendgroup": "", } marker_data_template = { "x": [], "y": [], "mode": "markers", "text": [], "marker": dict(color="", size=1, opacity=0), "name": "", "showlegend": False, } index_vals = [] for row in range(len(tasks)): if chart[row][index_col] not in index_vals: index_vals.append(chart[row][index_col]) index_vals.sort() # verify each value in index column appears in colors dictionary for key in index_vals: if key not in colors: raise exceptions.PlotlyError( "If you are using colors as a dictionary, all of its " "keys must be all the values in the index column." ) # create the list of task names for index in range(len(tasks)): tn = tasks[index]["name"] # Is added to task_names if group_tasks is set to False, # or if the option is used (True) it only adds them if the # name is not already in the list if not group_tasks or tn not in task_names: task_names.append(tn) # Guarantees that for grouped tasks the tasks that are inserted first # are shown at the top if group_tasks: task_names.reverse() for index in range(len(tasks)): tn = tasks[index]["name"] del tasks[index]["name"] # If group_tasks is True, all tasks with the same name belong # to the same row. groupID = index if group_tasks: groupID = task_names.index(tn) tasks[index]["y0"] = groupID - bar_width tasks[index]["y1"] = groupID + bar_width tasks[index]["fillcolor"] = colors[chart[index][index_col]] color_id = tasks[index]["fillcolor"] if color_id not in scatter_data_dict: scatter_data_dict[color_id] = copy.deepcopy(scatter_data_template) scatter_data_dict[color_id]["legendgroup"] = color_id scatter_data_dict[color_id]["fillcolor"] = color_id # if there are already values append the gap if len(scatter_data_dict[color_id]["x"]) > 0: # a gap on the scatterplot separates the rectangles from each other scatter_data_dict[color_id]["x"].append( scatter_data_dict[color_id]["x"][-1] ) scatter_data_dict[color_id]["y"].append(None) xs, ys = _get_corner_points( tasks[index]["x0"], tasks[index]["y0"], tasks[index]["x1"], tasks[index]["y1"], ) scatter_data_dict[color_id]["x"] += xs scatter_data_dict[color_id]["y"] += ys # append dummy markers for showing start and end of interval if color_id not in marker_data_dict: marker_data_dict[color_id] = copy.deepcopy(marker_data_template) marker_data_dict[color_id]["marker"]["color"] = color_id marker_data_dict[color_id]["legendgroup"] = color_id marker_data_dict[color_id]["x"].append(tasks[index]["x0"]) marker_data_dict[color_id]["x"].append(tasks[index]["x1"]) marker_data_dict[color_id]["y"].append(groupID) marker_data_dict[color_id]["y"].append(groupID) if "description" in tasks[index]: marker_data_dict[color_id]["text"].append(tasks[index]["description"]) marker_data_dict[color_id]["text"].append(tasks[index]["description"]) del tasks[index]["description"] else: marker_data_dict[color_id]["text"].append(None) marker_data_dict[color_id]["text"].append(None) if show_colorbar is True: showlegend = True for index_value in index_vals: scatter_data_dict[colors[index_value]]["name"] = str(index_value) layout = dict( title=title, showlegend=showlegend, height=height, width=width, shapes=[], hovermode="closest", yaxis=dict( showgrid=showgrid_y, ticktext=task_names, tickvals=list(range(len(task_names))), range=[-1, len(task_names) + 1], autorange=False, zeroline=False, ), xaxis=dict( showgrid=showgrid_x, zeroline=False, rangeselector=dict( buttons=list( [ dict(count=7, label="1w", step="day", stepmode="backward"), dict(count=1, label="1m", step="month", stepmode="backward"), dict(count=6, label="6m", step="month", stepmode="backward"), dict(count=1, label="YTD", step="year", stepmode="todate"), dict(count=1, label="1y", step="year", stepmode="backward"), dict(step="all"), ] ) ), type="date", ), ) data = [scatter_data_dict[k] for k in sorted(scatter_data_dict)] data += [marker_data_dict[k] for k in sorted(marker_data_dict)] # fig = dict( # data=data, layout=layout # ) fig = go.Figure(data=data, layout=layout) return fig def create_gantt( df, colors=None, index_col=None, show_colorbar=False, reverse_colors=False, title="Gantt Chart", bar_width=0.2, showgrid_x=False, showgrid_y=False, height=600, width=None, tasks=None, task_names=None, data=None, group_tasks=False, show_hover_fill=True, ): """ Returns figure for a gantt chart :param (array|list) df: input data for gantt chart. Must be either a a dataframe or a list. If dataframe, the columns must include 'Task', 'Start' and 'Finish'. Other columns can be included and used for indexing. If a list, its elements must be dictionaries with the same required column headers: 'Task', 'Start' and 'Finish'. :param (str|list|dict|tuple) colors: either a plotly scale name, an rgb or hex color, a color tuple or a list of colors. An rgb color is of the form 'rgb(x, y, z)' where x, y, z belong to the interval [0, 255] and a color tuple is a tuple of the form (a, b, c) where a, b and c belong to [0, 1]. If colors is a list, it must contain the valid color types aforementioned as its members. If a dictionary, all values of the indexing column must be keys in colors. :param (str|float) index_col: the column header (if df is a data frame) that will function as the indexing column. If df is a list, index_col must be one of the keys in all the items of df. :param (bool) show_colorbar: determines if colorbar will be visible. Only applies if values in the index column are numeric. :param (bool) show_hover_fill: enables/disables the hovertext for the filled area of the chart. :param (bool) reverse_colors: reverses the order of selected colors :param (str) title: the title of the chart :param (float) bar_width: the width of the horizontal bars in the plot :param (bool) showgrid_x: show/hide the x-axis grid :param (bool) showgrid_y: show/hide the y-axis grid :param (float) height: the height of the chart :param (float) width: the width of the chart Example 1: Simple Gantt Chart >>> from plotly.figure_factory import create_gantt >>> # Make data for chart >>> df = [dict(Task="Job A", Start='2009-01-01', Finish='2009-02-30'), ... dict(Task="Job B", Start='2009-03-05', Finish='2009-04-15'), ... dict(Task="Job C", Start='2009-02-20', Finish='2009-05-30')] >>> # Create a figure >>> fig = create_gantt(df) >>> fig.show() Example 2: Index by Column with Numerical Entries >>> from plotly.figure_factory import create_gantt >>> # Make data for chart >>> df = [dict(Task="Job A", Start='2009-01-01', ... Finish='2009-02-30', Complete=10), ... dict(Task="Job B", Start='2009-03-05', ... Finish='2009-04-15', Complete=60), ... dict(Task="Job C", Start='2009-02-20', ... Finish='2009-05-30', Complete=95)] >>> # Create a figure with Plotly colorscale >>> fig = create_gantt(df, colors='Blues', index_col='Complete', ... show_colorbar=True, bar_width=0.5, ... showgrid_x=True, showgrid_y=True) >>> fig.show() Example 3: Index by Column with String Entries >>> from plotly.figure_factory import create_gantt >>> # Make data for chart >>> df = [dict(Task="Job A", Start='2009-01-01', ... Finish='2009-02-30', Resource='Apple'), ... dict(Task="Job B", Start='2009-03-05', ... Finish='2009-04-15', Resource='Grape'), ... dict(Task="Job C", Start='2009-02-20', ... Finish='2009-05-30', Resource='Banana')] >>> # Create a figure with Plotly colorscale >>> fig = create_gantt(df, colors=['rgb(200, 50, 25)', (1, 0, 1), '#6c4774'], ... index_col='Resource', reverse_colors=True, ... show_colorbar=True) >>> fig.show() Example 4: Use a dictionary for colors >>> from plotly.figure_factory import create_gantt >>> # Make data for chart >>> df = [dict(Task="Job A", Start='2009-01-01', ... Finish='2009-02-30', Resource='Apple'), ... dict(Task="Job B", Start='2009-03-05', ... Finish='2009-04-15', Resource='Grape'), ... dict(Task="Job C", Start='2009-02-20', ... Finish='2009-05-30', Resource='Banana')] >>> # Make a dictionary of colors >>> colors = {'Apple': 'rgb(255, 0, 0)', ... 'Grape': 'rgb(170, 14, 200)', ... 'Banana': (1, 1, 0.2)} >>> # Create a figure with Plotly colorscale >>> fig = create_gantt(df, colors=colors, index_col='Resource', ... show_colorbar=True) >>> fig.show() Example 5: Use a pandas dataframe >>> from plotly.figure_factory import create_gantt >>> import pandas as pd >>> # Make data as a dataframe >>> df = pd.DataFrame([['Run', '2010-01-01', '2011-02-02', 10], ... ['Fast', '2011-01-01', '2012-06-05', 55], ... ['Eat', '2012-01-05', '2013-07-05', 94]], ... columns=['Task', 'Start', 'Finish', 'Complete']) >>> # Create a figure with Plotly colorscale >>> fig = create_gantt(df, colors='Blues', index_col='Complete', ... show_colorbar=True, bar_width=0.5, ... showgrid_x=True, showgrid_y=True) >>> fig.show() """ # validate gantt input data chart = validate_gantt(df) if index_col: if index_col not in chart[0]: raise exceptions.PlotlyError( "In order to use an indexing column and assign colors to " "the values of the index, you must choose an actual " "column name in the dataframe or key if a list of " "dictionaries is being used." ) # validate gantt index column index_list = [] for dictionary in chart: index_list.append(dictionary[index_col]) utils.validate_index(index_list) # Validate colors if isinstance(colors, dict): colors = clrs.validate_colors_dict(colors, "rgb") else: colors = clrs.validate_colors(colors, "rgb") if reverse_colors is True: colors.reverse() if not index_col: if isinstance(colors, dict): raise exceptions.PlotlyError( "Error. You have set colors to a dictionary but have not " "picked an index. An index is required if you are " "assigning colors to particular values in a dictioanry." ) fig = gantt( chart, colors, title, bar_width, showgrid_x, showgrid_y, height, width, tasks=None, task_names=None, data=None, group_tasks=group_tasks, show_hover_fill=show_hover_fill, show_colorbar=show_colorbar, ) return fig else: if not isinstance(colors, dict): fig = gantt_colorscale( chart, colors, title, index_col, show_colorbar, bar_width, showgrid_x, showgrid_y, height, width, tasks=None, task_names=None, data=None, group_tasks=group_tasks, show_hover_fill=show_hover_fill, ) return fig else: fig = gantt_dict( chart, colors, title, index_col, show_colorbar, bar_width, showgrid_x, showgrid_y, height, width, tasks=None, task_names=None, data=None, group_tasks=group_tasks, show_hover_fill=show_hover_fill, ) return fig plotly-4.4.1+dfsg.orig/plotly/figure_factory/_ohlc.py0000644000175000017500000002476513573717677022307 0ustar noahfxnoahfxfrom __future__ import absolute_import from plotly import exceptions from plotly.graph_objs import graph_objs from plotly.figure_factory import utils # Default colours for finance charts _DEFAULT_INCREASING_COLOR = "#3D9970" # http://clrs.cc _DEFAULT_DECREASING_COLOR = "#FF4136" def validate_ohlc(open, high, low, close, direction, **kwargs): """ ohlc and candlestick specific validations Specifically, this checks that the high value is the greatest value and the low value is the lowest value in each unit. See FigureFactory.create_ohlc() or FigureFactory.create_candlestick() for params :raises: (PlotlyError) If the high value is not the greatest value in each unit. :raises: (PlotlyError) If the low value is not the lowest value in each unit. :raises: (PlotlyError) If direction is not 'increasing' or 'decreasing' """ for lst in [open, low, close]: for index in range(len(high)): if high[index] < lst[index]: raise exceptions.PlotlyError( "Oops! Looks like some of " "your high values are less " "the corresponding open, " "low, or close values. " "Double check that your data " "is entered in O-H-L-C order" ) for lst in [open, high, close]: for index in range(len(low)): if low[index] > lst[index]: raise exceptions.PlotlyError( "Oops! Looks like some of " "your low values are greater " "than the corresponding high" ", open, or close values. " "Double check that your data " "is entered in O-H-L-C order" ) direction_opts = ("increasing", "decreasing", "both") if direction not in direction_opts: raise exceptions.PlotlyError( "direction must be defined as " "'increasing', 'decreasing', or " "'both'" ) def make_increasing_ohlc(open, high, low, close, dates, **kwargs): """ Makes increasing ohlc sticks _make_increasing_ohlc() and _make_decreasing_ohlc separate the increasing trace from the decreasing trace so kwargs (such as color) can be passed separately to increasing or decreasing traces when direction is set to 'increasing' or 'decreasing' in FigureFactory.create_candlestick() :param (list) open: opening values :param (list) high: high values :param (list) low: low values :param (list) close: closing values :param (list) dates: list of datetime objects. Default: None :param kwargs: kwargs to be passed to increasing trace via plotly.graph_objs.Scatter. :rtype (trace) ohlc_incr_data: Scatter trace of all increasing ohlc sticks. """ (flat_increase_x, flat_increase_y, text_increase) = _OHLC( open, high, low, close, dates ).get_increase() if "name" in kwargs: showlegend = True else: kwargs.setdefault("name", "Increasing") showlegend = False kwargs.setdefault("line", dict(color=_DEFAULT_INCREASING_COLOR, width=1)) kwargs.setdefault("text", text_increase) ohlc_incr = dict( type="scatter", x=flat_increase_x, y=flat_increase_y, mode="lines", showlegend=showlegend, **kwargs ) return ohlc_incr def make_decreasing_ohlc(open, high, low, close, dates, **kwargs): """ Makes decreasing ohlc sticks :param (list) open: opening values :param (list) high: high values :param (list) low: low values :param (list) close: closing values :param (list) dates: list of datetime objects. Default: None :param kwargs: kwargs to be passed to increasing trace via plotly.graph_objs.Scatter. :rtype (trace) ohlc_decr_data: Scatter trace of all decreasing ohlc sticks. """ (flat_decrease_x, flat_decrease_y, text_decrease) = _OHLC( open, high, low, close, dates ).get_decrease() kwargs.setdefault("line", dict(color=_DEFAULT_DECREASING_COLOR, width=1)) kwargs.setdefault("text", text_decrease) kwargs.setdefault("showlegend", False) kwargs.setdefault("name", "Decreasing") ohlc_decr = dict( type="scatter", x=flat_decrease_x, y=flat_decrease_y, mode="lines", **kwargs ) return ohlc_decr def create_ohlc(open, high, low, close, dates=None, direction="both", **kwargs): """ **deprecated**, use instead the plotly.graph_objects trace :class:`plotly.graph_objects.Ohlc` :param (list) open: opening values :param (list) high: high values :param (list) low: low values :param (list) close: closing :param (list) dates: list of datetime objects. Default: None :param (string) direction: direction can be 'increasing', 'decreasing', or 'both'. When the direction is 'increasing', the returned figure consists of all units where the close value is greater than the corresponding open value, and when the direction is 'decreasing', the returned figure consists of all units where the close value is less than or equal to the corresponding open value. When the direction is 'both', both increasing and decreasing units are returned. Default: 'both' :param kwargs: kwargs passed through plotly.graph_objs.Scatter. These kwargs describe other attributes about the ohlc Scatter trace such as the color or the legend name. For more information on valid kwargs call help(plotly.graph_objs.Scatter) :rtype (dict): returns a representation of an ohlc chart figure. Example 1: Simple OHLC chart from a Pandas DataFrame >>> from plotly.figure_factory import create_ohlc >>> from datetime import datetime >>> import pandas as pd >>> df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/finance-charts-apple.csv') >>> fig = create_ohlc(df['AAPL.Open'], df['AAPL.High'], df['AAPL.Low'], df['AAPL.Close'], dates=df.index) >>> fig.show() """ if dates is not None: utils.validate_equal_length(open, high, low, close, dates) else: utils.validate_equal_length(open, high, low, close) validate_ohlc(open, high, low, close, direction, **kwargs) if direction is "increasing": ohlc_incr = make_increasing_ohlc(open, high, low, close, dates, **kwargs) data = [ohlc_incr] elif direction is "decreasing": ohlc_decr = make_decreasing_ohlc(open, high, low, close, dates, **kwargs) data = [ohlc_decr] else: ohlc_incr = make_increasing_ohlc(open, high, low, close, dates, **kwargs) ohlc_decr = make_decreasing_ohlc(open, high, low, close, dates, **kwargs) data = [ohlc_incr, ohlc_decr] layout = graph_objs.Layout(xaxis=dict(zeroline=False), hovermode="closest") return graph_objs.Figure(data=data, layout=layout) class _OHLC(object): """ Refer to FigureFactory.create_ohlc_increase() for docstring. """ def __init__(self, open, high, low, close, dates, **kwargs): self.open = open self.high = high self.low = low self.close = close self.empty = [None] * len(open) self.dates = dates self.all_x = [] self.all_y = [] self.increase_x = [] self.increase_y = [] self.decrease_x = [] self.decrease_y = [] self.get_all_xy() self.separate_increase_decrease() def get_all_xy(self): """ Zip data to create OHLC shape OHLC shape: low to high vertical bar with horizontal branches for open and close values. If dates were added, the smallest date difference is calculated and multiplied by .2 to get the length of the open and close branches. If no date data was provided, the x-axis is a list of integers and the length of the open and close branches is .2. """ self.all_y = list( zip( self.open, self.open, self.high, self.low, self.close, self.close, self.empty, ) ) if self.dates is not None: date_dif = [] for i in range(len(self.dates) - 1): date_dif.append(self.dates[i + 1] - self.dates[i]) date_dif_min = (min(date_dif)) / 5 self.all_x = [ [x - date_dif_min, x, x, x, x, x + date_dif_min, None] for x in self.dates ] else: self.all_x = [ [x - 0.2, x, x, x, x, x + 0.2, None] for x in range(len(self.open)) ] def separate_increase_decrease(self): """ Separate data into two groups: increase and decrease (1) Increase, where close > open and (2) Decrease, where close <= open """ for index in range(len(self.open)): if self.close[index] is None: pass elif self.close[index] > self.open[index]: self.increase_x.append(self.all_x[index]) self.increase_y.append(self.all_y[index]) else: self.decrease_x.append(self.all_x[index]) self.decrease_y.append(self.all_y[index]) def get_increase(self): """ Flatten increase data and get increase text :rtype (list, list, list): flat_increase_x: x-values for the increasing trace, flat_increase_y: y=values for the increasing trace and text_increase: hovertext for the increasing trace """ flat_increase_x = utils.flatten(self.increase_x) flat_increase_y = utils.flatten(self.increase_y) text_increase = ("Open", "Open", "High", "Low", "Close", "Close", "") * ( len(self.increase_x) ) return flat_increase_x, flat_increase_y, text_increase def get_decrease(self): """ Flatten decrease data and get decrease text :rtype (list, list, list): flat_decrease_x: x-values for the decreasing trace, flat_decrease_y: y=values for the decreasing trace and text_decrease: hovertext for the decreasing trace """ flat_decrease_x = utils.flatten(self.decrease_x) flat_decrease_y = utils.flatten(self.decrease_y) text_decrease = ("Open", "Open", "High", "Low", "Close", "Close", "") * ( len(self.decrease_x) ) return flat_decrease_x, flat_decrease_y, text_decrease plotly-4.4.1+dfsg.orig/plotly/figure_factory/_dendrogram.py0000644000175000017500000002720613573717677023475 0ustar noahfxnoahfx# -*- coding: utf-8 -*- from __future__ import absolute_import from collections import OrderedDict from plotly import exceptions, optional_imports from plotly.graph_objs import graph_objs # Optional imports, may be None for users that only use our core functionality. np = optional_imports.get_module("numpy") scp = optional_imports.get_module("scipy") sch = optional_imports.get_module("scipy.cluster.hierarchy") scs = optional_imports.get_module("scipy.spatial") def create_dendrogram( X, orientation="bottom", labels=None, colorscale=None, distfun=None, linkagefun=lambda x: sch.linkage(x, "complete"), hovertext=None, color_threshold=None, ): """ Function that returns a dendrogram Plotly figure object. See also https://dash.plot.ly/dash-bio/clustergram. :param (ndarray) X: Matrix of observations as array of arrays :param (str) orientation: 'top', 'right', 'bottom', or 'left' :param (list) labels: List of axis category labels(observation labels) :param (list) colorscale: Optional colorscale for dendrogram tree :param (function) distfun: Function to compute the pairwise distance from the observations :param (function) linkagefun: Function to compute the linkage matrix from the pairwise distances :param (list[list]) hovertext: List of hovertext for constituent traces of dendrogram clusters :param (double) color_threshold: Value at which the separation of clusters will be made Example 1: Simple bottom oriented dendrogram >>> from plotly.figure_factory import create_dendrogram >>> import numpy as np >>> X = np.random.rand(10,10) >>> fig = create_dendrogram(X) >>> fig.show() Example 2: Dendrogram to put on the left of the heatmap >>> from plotly.figure_factory import create_dendrogram >>> import numpy as np >>> X = np.random.rand(5,5) >>> names = ['Jack', 'Oxana', 'John', 'Chelsea', 'Mark'] >>> dendro = create_dendrogram(X, orientation='right', labels=names) >>> dendro.update_layout({'width':700, 'height':500}) # doctest: +SKIP >>> dendro.show() Example 3: Dendrogram with Pandas >>> from plotly.figure_factory import create_dendrogram >>> import numpy as np >>> import pandas as pd >>> Index= ['A','B','C','D','E','F','G','H','I','J'] >>> df = pd.DataFrame(abs(np.random.randn(10, 10)), index=Index) >>> fig = create_dendrogram(df, labels=Index) >>> fig.show() """ if not scp or not scs or not sch: raise ImportError( "FigureFactory.create_dendrogram requires scipy, \ scipy.spatial and scipy.hierarchy" ) s = X.shape if len(s) != 2: exceptions.PlotlyError("X should be 2-dimensional array.") if distfun is None: distfun = scs.distance.pdist dendrogram = _Dendrogram( X, orientation, labels, colorscale, distfun=distfun, linkagefun=linkagefun, hovertext=hovertext, color_threshold=color_threshold, ) return graph_objs.Figure(data=dendrogram.data, layout=dendrogram.layout) class _Dendrogram(object): """Refer to FigureFactory.create_dendrogram() for docstring.""" def __init__( self, X, orientation="bottom", labels=None, colorscale=None, width=np.inf, height=np.inf, xaxis="xaxis", yaxis="yaxis", distfun=None, linkagefun=lambda x: sch.linkage(x, "complete"), hovertext=None, color_threshold=None, ): self.orientation = orientation self.labels = labels self.xaxis = xaxis self.yaxis = yaxis self.data = [] self.leaves = [] self.sign = {self.xaxis: 1, self.yaxis: 1} self.layout = {self.xaxis: {}, self.yaxis: {}} if self.orientation in ["left", "bottom"]: self.sign[self.xaxis] = 1 else: self.sign[self.xaxis] = -1 if self.orientation in ["right", "bottom"]: self.sign[self.yaxis] = 1 else: self.sign[self.yaxis] = -1 if distfun is None: distfun = scs.distance.pdist (dd_traces, xvals, yvals, ordered_labels, leaves) = self.get_dendrogram_traces( X, colorscale, distfun, linkagefun, hovertext, color_threshold ) self.labels = ordered_labels self.leaves = leaves yvals_flat = yvals.flatten() xvals_flat = xvals.flatten() self.zero_vals = [] for i in range(len(yvals_flat)): if yvals_flat[i] == 0.0 and xvals_flat[i] not in self.zero_vals: self.zero_vals.append(xvals_flat[i]) if len(self.zero_vals) > len(yvals) + 1: # If the length of zero_vals is larger than the length of yvals, # it means that there are wrong vals because of the identicial samples. # Three and more identicial samples will make the yvals of spliting center into 0 and it will \ # accidentally take it as leaves. l_border = int(min(self.zero_vals)) r_border = int(max(self.zero_vals)) correct_leaves_pos = range( l_border, r_border + 1, int((r_border - l_border) / len(yvals)) ) # Regenerating the leaves pos from the self.zero_vals with equally intervals. self.zero_vals = [v for v in correct_leaves_pos] self.zero_vals.sort() self.layout = self.set_figure_layout(width, height) self.data = dd_traces def get_color_dict(self, colorscale): """ Returns colorscale used for dendrogram tree clusters. :param (list) colorscale: Colors to use for the plot in rgb format. :rtype (dict): A dict of default colors mapped to the user colorscale. """ # These are the color codes returned for dendrograms # We're replacing them with nicer colors d = { "r": "red", "g": "green", "b": "blue", "c": "cyan", "m": "magenta", "y": "yellow", "k": "black", "w": "white", } default_colors = OrderedDict(sorted(d.items(), key=lambda t: t[0])) if colorscale is None: colorscale = [ "rgb(0,116,217)", # blue "rgb(35,205,205)", # cyan "rgb(61,153,112)", # green "rgb(40,35,35)", # black "rgb(133,20,75)", # magenta "rgb(255,65,54)", # red "rgb(255,255,255)", # white "rgb(255,220,0)", ] # yellow for i in range(len(default_colors.keys())): k = list(default_colors.keys())[i] # PY3 won't index keys if i < len(colorscale): default_colors[k] = colorscale[i] return default_colors def set_axis_layout(self, axis_key): """ Sets and returns default axis object for dendrogram figure. :param (str) axis_key: E.g., 'xaxis', 'xaxis1', 'yaxis', yaxis1', etc. :rtype (dict): An axis_key dictionary with set parameters. """ axis_defaults = { "type": "linear", "ticks": "outside", "mirror": "allticks", "rangemode": "tozero", "showticklabels": True, "zeroline": False, "showgrid": False, "showline": True, } if len(self.labels) != 0: axis_key_labels = self.xaxis if self.orientation in ["left", "right"]: axis_key_labels = self.yaxis if axis_key_labels not in self.layout: self.layout[axis_key_labels] = {} self.layout[axis_key_labels]["tickvals"] = [ zv * self.sign[axis_key] for zv in self.zero_vals ] self.layout[axis_key_labels]["ticktext"] = self.labels self.layout[axis_key_labels]["tickmode"] = "array" self.layout[axis_key].update(axis_defaults) return self.layout[axis_key] def set_figure_layout(self, width, height): """ Sets and returns default layout object for dendrogram figure. """ self.layout.update( { "showlegend": False, "autosize": False, "hovermode": "closest", "width": width, "height": height, } ) self.set_axis_layout(self.xaxis) self.set_axis_layout(self.yaxis) return self.layout def get_dendrogram_traces( self, X, colorscale, distfun, linkagefun, hovertext, color_threshold ): """ Calculates all the elements needed for plotting a dendrogram. :param (ndarray) X: Matrix of observations as array of arrays :param (list) colorscale: Color scale for dendrogram tree clusters :param (function) distfun: Function to compute the pairwise distance from the observations :param (function) linkagefun: Function to compute the linkage matrix from the pairwise distances :param (list) hovertext: List of hovertext for constituent traces of dendrogram :rtype (tuple): Contains all the traces in the following order: (a) trace_list: List of Plotly trace objects for dendrogram tree (b) icoord: All X points of the dendrogram tree as array of arrays with length 4 (c) dcoord: All Y points of the dendrogram tree as array of arrays with length 4 (d) ordered_labels: leaf labels in the order they are going to appear on the plot (e) P['leaves']: left-to-right traversal of the leaves """ d = distfun(X) Z = linkagefun(d) P = sch.dendrogram( Z, orientation=self.orientation, labels=self.labels, no_plot=True, color_threshold=color_threshold, ) icoord = scp.array(P["icoord"]) dcoord = scp.array(P["dcoord"]) ordered_labels = scp.array(P["ivl"]) color_list = scp.array(P["color_list"]) colors = self.get_color_dict(colorscale) trace_list = [] for i in range(len(icoord)): # xs and ys are arrays of 4 points that make up the '∩' shapes # of the dendrogram tree if self.orientation in ["top", "bottom"]: xs = icoord[i] else: xs = dcoord[i] if self.orientation in ["top", "bottom"]: ys = dcoord[i] else: ys = icoord[i] color_key = color_list[i] hovertext_label = None if hovertext: hovertext_label = hovertext[i] trace = dict( type="scatter", x=np.multiply(self.sign[self.xaxis], xs), y=np.multiply(self.sign[self.yaxis], ys), mode="lines", marker=dict(color=colors[color_key]), text=hovertext_label, hoverinfo="text", ) try: x_index = int(self.xaxis[-1]) except ValueError: x_index = "" try: y_index = int(self.yaxis[-1]) except ValueError: y_index = "" trace["xaxis"] = "x" + x_index trace["yaxis"] = "y" + y_index trace_list.append(trace) return trace_list, icoord, dcoord, ordered_labels, P["leaves"] plotly-4.4.1+dfsg.orig/plotly/figure_factory/_facet_grid.py0000644000175000017500000011501013573717677023431 0ustar noahfxnoahfxfrom __future__ import absolute_import from plotly import exceptions, optional_imports import plotly.colors as clrs from plotly.figure_factory import utils from plotly.subplots import make_subplots import math from numbers import Number pd = optional_imports.get_module("pandas") TICK_COLOR = "#969696" AXIS_TITLE_COLOR = "#0f0f0f" AXIS_TITLE_SIZE = 12 GRID_COLOR = "#ffffff" LEGEND_COLOR = "#efefef" PLOT_BGCOLOR = "#ededed" ANNOT_RECT_COLOR = "#d0d0d0" LEGEND_BORDER_WIDTH = 1 LEGEND_ANNOT_X = 1.05 LEGEND_ANNOT_Y = 0.5 MAX_TICKS_PER_AXIS = 5 THRES_FOR_FLIPPED_FACET_TITLES = 10 GRID_WIDTH = 1 VALID_TRACE_TYPES = ["scatter", "scattergl", "histogram", "bar", "box"] CUSTOM_LABEL_ERROR = ( "If you are using a dictionary for custom labels for the facet row/col, " "make sure each key in that column of the dataframe is in your facet " "labels. The keys you need are {}" ) def _is_flipped(num): if num >= THRES_FOR_FLIPPED_FACET_TITLES: flipped = True else: flipped = False return flipped def _return_label(original_label, facet_labels, facet_var): if isinstance(facet_labels, dict): label = facet_labels[original_label] elif isinstance(facet_labels, str): label = "{}: {}".format(facet_var, original_label) else: label = original_label return label def _legend_annotation(color_name): legend_title = dict( textangle=0, xanchor="left", yanchor="middle", x=LEGEND_ANNOT_X, y=1.03, showarrow=False, xref="paper", yref="paper", text="factor({})".format(color_name), font=dict(size=13, color="#000000"), ) return legend_title def _annotation_dict( text, lane, num_of_lanes, SUBPLOT_SPACING, row_col="col", flipped=True ): l = (1 - (num_of_lanes - 1) * SUBPLOT_SPACING) / (num_of_lanes) if not flipped: xanchor = "center" yanchor = "middle" if row_col == "col": x = (lane - 1) * (l + SUBPLOT_SPACING) + 0.5 * l y = 1.03 textangle = 0 elif row_col == "row": y = (lane - 1) * (l + SUBPLOT_SPACING) + 0.5 * l x = 1.03 textangle = 90 else: if row_col == "col": xanchor = "center" yanchor = "bottom" x = (lane - 1) * (l + SUBPLOT_SPACING) + 0.5 * l y = 1.0 textangle = 270 elif row_col == "row": xanchor = "left" yanchor = "middle" y = (lane - 1) * (l + SUBPLOT_SPACING) + 0.5 * l x = 1.0 textangle = 0 annotation_dict = dict( textangle=textangle, xanchor=xanchor, yanchor=yanchor, x=x, y=y, showarrow=False, xref="paper", yref="paper", text=str(text), font=dict(size=13, color=AXIS_TITLE_COLOR), ) return annotation_dict def _axis_title_annotation(text, x_or_y_axis): if x_or_y_axis == "x": x_pos = 0.5 y_pos = -0.1 textangle = 0 elif x_or_y_axis == "y": x_pos = -0.1 y_pos = 0.5 textangle = 270 if not text: text = "" annot = { "font": {"color": "#000000", "size": AXIS_TITLE_SIZE}, "showarrow": False, "text": text, "textangle": textangle, "x": x_pos, "xanchor": "center", "xref": "paper", "y": y_pos, "yanchor": "middle", "yref": "paper", } return annot def _add_shapes_to_fig(fig, annot_rect_color, flipped_rows=False, flipped_cols=False): shapes_list = [] for key in fig["layout"].to_plotly_json().keys(): if "axis" in key and fig["layout"][key]["domain"] != [0.0, 1.0]: shape = { "fillcolor": annot_rect_color, "layer": "below", "line": {"color": annot_rect_color, "width": 1}, "type": "rect", "xref": "paper", "yref": "paper", } if "xaxis" in key: shape["x0"] = fig["layout"][key]["domain"][0] shape["x1"] = fig["layout"][key]["domain"][1] shape["y0"] = 1.005 shape["y1"] = 1.05 if flipped_cols: shape["y1"] += 0.5 shapes_list.append(shape) elif "yaxis" in key: shape["x0"] = 1.005 shape["x1"] = 1.05 shape["y0"] = fig["layout"][key]["domain"][0] shape["y1"] = fig["layout"][key]["domain"][1] if flipped_rows: shape["x1"] += 1 shapes_list.append(shape) fig["layout"]["shapes"] = shapes_list def _make_trace_for_scatter(trace, trace_type, color, **kwargs_marker): if trace_type in ["scatter", "scattergl"]: trace["mode"] = "markers" trace["marker"] = dict(color=color, **kwargs_marker) return trace def _facet_grid_color_categorical( df, x, y, facet_row, facet_col, color_name, colormap, num_of_rows, num_of_cols, facet_row_labels, facet_col_labels, trace_type, flipped_rows, flipped_cols, show_boxes, SUBPLOT_SPACING, marker_color, kwargs_trace, kwargs_marker, ): fig = make_subplots( rows=num_of_rows, cols=num_of_cols, shared_xaxes=True, shared_yaxes=True, horizontal_spacing=SUBPLOT_SPACING, vertical_spacing=SUBPLOT_SPACING, print_grid=False, ) annotations = [] if not facet_row and not facet_col: color_groups = list(df.groupby(color_name)) for group in color_groups: trace = dict( type=trace_type, name=group[0], marker=dict(color=colormap[group[0]]), **kwargs_trace ) if x: trace["x"] = group[1][x] if y: trace["y"] = group[1][y] trace = _make_trace_for_scatter( trace, trace_type, colormap[group[0]], **kwargs_marker ) fig.append_trace(trace, 1, 1) elif (facet_row and not facet_col) or (not facet_row and facet_col): groups_by_facet = list(df.groupby(facet_row if facet_row else facet_col)) for j, group in enumerate(groups_by_facet): for color_val in df[color_name].unique(): data_by_color = group[1][group[1][color_name] == color_val] trace = dict( type=trace_type, name=color_val, marker=dict(color=colormap[color_val]), **kwargs_trace ) if x: trace["x"] = data_by_color[x] if y: trace["y"] = data_by_color[y] trace = _make_trace_for_scatter( trace, trace_type, colormap[color_val], **kwargs_marker ) fig.append_trace( trace, j + 1 if facet_row else 1, 1 if facet_row else j + 1 ) label = _return_label( group[0], facet_row_labels if facet_row else facet_col_labels, facet_row if facet_row else facet_col, ) annotations.append( _annotation_dict( label, num_of_rows - j if facet_row else j + 1, num_of_rows if facet_row else num_of_cols, SUBPLOT_SPACING, "row" if facet_row else "col", flipped_rows, ) ) elif facet_row and facet_col: groups_by_facets = list(df.groupby([facet_row, facet_col])) tuple_to_facet_group = {item[0]: item[1] for item in groups_by_facets} row_values = df[facet_row].unique() col_values = df[facet_col].unique() color_vals = df[color_name].unique() for row_count, x_val in enumerate(row_values): for col_count, y_val in enumerate(col_values): try: group = tuple_to_facet_group[(x_val, y_val)] except KeyError: group = pd.DataFrame( [[None, None, None]], columns=[x, y, color_name] ) for color_val in color_vals: if group.values.tolist() != [[None, None, None]]: group_filtered = group[group[color_name] == color_val] trace = dict( type=trace_type, name=color_val, marker=dict(color=colormap[color_val]), **kwargs_trace ) new_x = group_filtered[x] new_y = group_filtered[y] else: trace = dict( type=trace_type, name=color_val, marker=dict(color=colormap[color_val]), showlegend=False, **kwargs_trace ) new_x = group[x] new_y = group[y] if x: trace["x"] = new_x if y: trace["y"] = new_y trace = _make_trace_for_scatter( trace, trace_type, colormap[color_val], **kwargs_marker ) fig.append_trace(trace, row_count + 1, col_count + 1) if row_count == 0: label = _return_label( col_values[col_count], facet_col_labels, facet_col ) annotations.append( _annotation_dict( label, col_count + 1, num_of_cols, SUBPLOT_SPACING, row_col="col", flipped=flipped_cols, ) ) label = _return_label(row_values[row_count], facet_row_labels, facet_row) annotations.append( _annotation_dict( label, num_of_rows - row_count, num_of_rows, SUBPLOT_SPACING, row_col="row", flipped=flipped_rows, ) ) return fig, annotations def _facet_grid_color_numerical( df, x, y, facet_row, facet_col, color_name, colormap, num_of_rows, num_of_cols, facet_row_labels, facet_col_labels, trace_type, flipped_rows, flipped_cols, show_boxes, SUBPLOT_SPACING, marker_color, kwargs_trace, kwargs_marker, ): fig = make_subplots( rows=num_of_rows, cols=num_of_cols, shared_xaxes=True, shared_yaxes=True, horizontal_spacing=SUBPLOT_SPACING, vertical_spacing=SUBPLOT_SPACING, print_grid=False, ) annotations = [] if not facet_row and not facet_col: trace = dict( type=trace_type, marker=dict(color=df[color_name], colorscale=colormap, showscale=True), **kwargs_trace ) if x: trace["x"] = df[x] if y: trace["y"] = df[y] trace = _make_trace_for_scatter( trace, trace_type, df[color_name], **kwargs_marker ) fig.append_trace(trace, 1, 1) if (facet_row and not facet_col) or (not facet_row and facet_col): groups_by_facet = list(df.groupby(facet_row if facet_row else facet_col)) for j, group in enumerate(groups_by_facet): trace = dict( type=trace_type, marker=dict( color=df[color_name], colorscale=colormap, showscale=True, colorbar=dict(x=1.15), ), **kwargs_trace ) if x: trace["x"] = group[1][x] if y: trace["y"] = group[1][y] trace = _make_trace_for_scatter( trace, trace_type, df[color_name], **kwargs_marker ) fig.append_trace( trace, j + 1 if facet_row else 1, 1 if facet_row else j + 1 ) labels = facet_row_labels if facet_row else facet_col_labels label = _return_label( group[0], labels, facet_row if facet_row else facet_col ) annotations.append( _annotation_dict( label, num_of_rows - j if facet_row else j + 1, num_of_rows if facet_row else num_of_cols, SUBPLOT_SPACING, "row" if facet_row else "col", flipped=flipped_rows, ) ) elif facet_row and facet_col: groups_by_facets = list(df.groupby([facet_row, facet_col])) tuple_to_facet_group = {item[0]: item[1] for item in groups_by_facets} row_values = df[facet_row].unique() col_values = df[facet_col].unique() for row_count, x_val in enumerate(row_values): for col_count, y_val in enumerate(col_values): try: group = tuple_to_facet_group[(x_val, y_val)] except KeyError: group = pd.DataFrame( [[None, None, None]], columns=[x, y, color_name] ) if group.values.tolist() != [[None, None, None]]: trace = dict( type=trace_type, marker=dict( color=df[color_name], colorscale=colormap, showscale=(row_count == 0), colorbar=dict(x=1.15), ), **kwargs_trace ) else: trace = dict(type=trace_type, showlegend=False, **kwargs_trace) if x: trace["x"] = group[x] if y: trace["y"] = group[y] trace = _make_trace_for_scatter( trace, trace_type, df[color_name], **kwargs_marker ) fig.append_trace(trace, row_count + 1, col_count + 1) if row_count == 0: label = _return_label( col_values[col_count], facet_col_labels, facet_col ) annotations.append( _annotation_dict( label, col_count + 1, num_of_cols, SUBPLOT_SPACING, row_col="col", flipped=flipped_cols, ) ) label = _return_label(row_values[row_count], facet_row_labels, facet_row) annotations.append( _annotation_dict( row_values[row_count], num_of_rows - row_count, num_of_rows, SUBPLOT_SPACING, row_col="row", flipped=flipped_rows, ) ) return fig, annotations def _facet_grid( df, x, y, facet_row, facet_col, num_of_rows, num_of_cols, facet_row_labels, facet_col_labels, trace_type, flipped_rows, flipped_cols, show_boxes, SUBPLOT_SPACING, marker_color, kwargs_trace, kwargs_marker, ): fig = make_subplots( rows=num_of_rows, cols=num_of_cols, shared_xaxes=True, shared_yaxes=True, horizontal_spacing=SUBPLOT_SPACING, vertical_spacing=SUBPLOT_SPACING, print_grid=False, ) annotations = [] if not facet_row and not facet_col: trace = dict( type=trace_type, marker=dict(color=marker_color, line=kwargs_marker["line"]), **kwargs_trace ) if x: trace["x"] = df[x] if y: trace["y"] = df[y] trace = _make_trace_for_scatter( trace, trace_type, marker_color, **kwargs_marker ) fig.append_trace(trace, 1, 1) elif (facet_row and not facet_col) or (not facet_row and facet_col): groups_by_facet = list(df.groupby(facet_row if facet_row else facet_col)) for j, group in enumerate(groups_by_facet): trace = dict( type=trace_type, marker=dict(color=marker_color, line=kwargs_marker["line"]), **kwargs_trace ) if x: trace["x"] = group[1][x] if y: trace["y"] = group[1][y] trace = _make_trace_for_scatter( trace, trace_type, marker_color, **kwargs_marker ) fig.append_trace( trace, j + 1 if facet_row else 1, 1 if facet_row else j + 1 ) label = _return_label( group[0], facet_row_labels if facet_row else facet_col_labels, facet_row if facet_row else facet_col, ) annotations.append( _annotation_dict( label, num_of_rows - j if facet_row else j + 1, num_of_rows if facet_row else num_of_cols, SUBPLOT_SPACING, "row" if facet_row else "col", flipped_rows, ) ) elif facet_row and facet_col: groups_by_facets = list(df.groupby([facet_row, facet_col])) tuple_to_facet_group = {item[0]: item[1] for item in groups_by_facets} row_values = df[facet_row].unique() col_values = df[facet_col].unique() for row_count, x_val in enumerate(row_values): for col_count, y_val in enumerate(col_values): try: group = tuple_to_facet_group[(x_val, y_val)] except KeyError: group = pd.DataFrame([[None, None]], columns=[x, y]) trace = dict( type=trace_type, marker=dict(color=marker_color, line=kwargs_marker["line"]), **kwargs_trace ) if x: trace["x"] = group[x] if y: trace["y"] = group[y] trace = _make_trace_for_scatter( trace, trace_type, marker_color, **kwargs_marker ) fig.append_trace(trace, row_count + 1, col_count + 1) if row_count == 0: label = _return_label( col_values[col_count], facet_col_labels, facet_col ) annotations.append( _annotation_dict( label, col_count + 1, num_of_cols, SUBPLOT_SPACING, row_col="col", flipped=flipped_cols, ) ) label = _return_label(row_values[row_count], facet_row_labels, facet_row) annotations.append( _annotation_dict( label, num_of_rows - row_count, num_of_rows, SUBPLOT_SPACING, row_col="row", flipped=flipped_rows, ) ) return fig, annotations def create_facet_grid( df, x=None, y=None, facet_row=None, facet_col=None, color_name=None, colormap=None, color_is_cat=False, facet_row_labels=None, facet_col_labels=None, height=None, width=None, trace_type="scatter", scales="fixed", dtick_x=None, dtick_y=None, show_boxes=True, ggplot2=False, binsize=1, **kwargs ): """ Returns figure for facet grid; **this function is deprecated**, since plotly.express functions should be used instead, for example >>> import plotly.express as px >>> tips = px.data.tips() >>> fig = px.scatter(tips, ... x='total_bill', ... y='tip', ... facet_row='sex', ... facet_col='smoker', ... color='size') :param (pd.DataFrame) df: the dataframe of columns for the facet grid. :param (str) x: the name of the dataframe column for the x axis data. :param (str) y: the name of the dataframe column for the y axis data. :param (str) facet_row: the name of the dataframe column that is used to facet the grid into row panels. :param (str) facet_col: the name of the dataframe column that is used to facet the grid into column panels. :param (str) color_name: the name of your dataframe column that will function as the colormap variable. :param (str|list|dict) colormap: the param that determines how the color_name column colors the data. If the dataframe contains numeric data, then a dictionary of colors will group the data categorically while a Plotly Colorscale name or a custom colorscale will treat it numerically. To learn more about colors and types of colormap, run `help(plotly.colors)`. :param (bool) color_is_cat: determines whether a numerical column for the colormap will be treated as categorical (True) or sequential (False). Default = False. :param (str|dict) facet_row_labels: set to either 'name' or a dictionary of all the unique values in the faceting row mapped to some text to show up in the label annotations. If None, labeling works like usual. :param (str|dict) facet_col_labels: set to either 'name' or a dictionary of all the values in the faceting row mapped to some text to show up in the label annotations. If None, labeling works like usual. :param (int) height: the height of the facet grid figure. :param (int) width: the width of the facet grid figure. :param (str) trace_type: decides the type of plot to appear in the facet grid. The options are 'scatter', 'scattergl', 'histogram', 'bar', and 'box'. Default = 'scatter'. :param (str) scales: determines if axes have fixed ranges or not. Valid settings are 'fixed' (all axes fixed), 'free_x' (x axis free only), 'free_y' (y axis free only) or 'free' (both axes free). :param (float) dtick_x: determines the distance between each tick on the x-axis. Default is None which means dtick_x is set automatically. :param (float) dtick_y: determines the distance between each tick on the y-axis. Default is None which means dtick_y is set automatically. :param (bool) show_boxes: draws grey boxes behind the facet titles. :param (bool) ggplot2: draws the facet grid in the style of `ggplot2`. See http://ggplot2.tidyverse.org/reference/facet_grid.html for reference. Default = False :param (int) binsize: groups all data into bins of a given length. :param (dict) kwargs: a dictionary of scatterplot arguments. Examples 1: One Way Faceting >>> import plotly.figure_factory as ff >>> import pandas as pd >>> mpg = pd.read_table('https://raw.githubusercontent.com/plotly/datasets/master/mpg_2017.txt') >>> fig = ff.create_facet_grid( ... mpg, ... x='displ', ... y='cty', ... facet_col='cyl', ... ) >>> fig.show() Example 2: Two Way Faceting >>> import plotly.figure_factory as ff >>> import pandas as pd >>> mpg = pd.read_table('https://raw.githubusercontent.com/plotly/datasets/master/mpg_2017.txt') >>> fig = ff.create_facet_grid( ... mpg, ... x='displ', ... y='cty', ... facet_row='drv', ... facet_col='cyl', ... ) >>> fig.show() Example 3: Categorical Coloring >>> import plotly.figure_factory as ff >>> import pandas as pd >>> mtcars = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/mtcars.csv') >>> mtcars.cyl = mtcars.cyl.astype(str) >>> fig = ff.create_facet_grid( ... mtcars, ... x='mpg', ... y='wt', ... facet_col='cyl', ... color_name='cyl', ... color_is_cat=True, ... ) >>> fig.show() """ if not pd: raise ImportError("'pandas' must be installed for this figure_factory.") if not isinstance(df, pd.DataFrame): raise exceptions.PlotlyError("You must input a pandas DataFrame.") # make sure all columns are of homogenous datatype utils.validate_dataframe(df) if trace_type in ["scatter", "scattergl"]: if not x or not y: raise exceptions.PlotlyError( "You need to input 'x' and 'y' if you are you are using a " "trace_type of 'scatter' or 'scattergl'." ) for key in [x, y, facet_row, facet_col, color_name]: if key is not None: try: df[key] except KeyError: raise exceptions.PlotlyError( "x, y, facet_row, facet_col and color_name must be keys " "in your dataframe." ) # autoscale histogram bars if trace_type not in ["scatter", "scattergl"]: scales = "free" # validate scales if scales not in ["fixed", "free_x", "free_y", "free"]: raise exceptions.PlotlyError( "'scales' must be set to 'fixed', 'free_x', 'free_y' and 'free'." ) if trace_type not in VALID_TRACE_TYPES: raise exceptions.PlotlyError( "'trace_type' must be in {}".format(VALID_TRACE_TYPES) ) if trace_type == "histogram": SUBPLOT_SPACING = 0.06 else: SUBPLOT_SPACING = 0.015 # seperate kwargs for marker and else if "marker" in kwargs: kwargs_marker = kwargs["marker"] else: kwargs_marker = {} marker_color = kwargs_marker.pop("color", None) kwargs.pop("marker", None) kwargs_trace = kwargs if "size" not in kwargs_marker: if ggplot2: kwargs_marker["size"] = 5 else: kwargs_marker["size"] = 8 if "opacity" not in kwargs_marker: if not ggplot2: kwargs_trace["opacity"] = 0.6 if "line" not in kwargs_marker: if not ggplot2: kwargs_marker["line"] = {"color": "darkgrey", "width": 1} else: kwargs_marker["line"] = {} # default marker size if not ggplot2: if not marker_color: marker_color = "rgb(31, 119, 180)" else: marker_color = "rgb(0, 0, 0)" num_of_rows = 1 num_of_cols = 1 flipped_rows = False flipped_cols = False if facet_row: num_of_rows = len(df[facet_row].unique()) flipped_rows = _is_flipped(num_of_rows) if isinstance(facet_row_labels, dict): for key in df[facet_row].unique(): if key not in facet_row_labels.keys(): unique_keys = df[facet_row].unique().tolist() raise exceptions.PlotlyError(CUSTOM_LABEL_ERROR.format(unique_keys)) if facet_col: num_of_cols = len(df[facet_col].unique()) flipped_cols = _is_flipped(num_of_cols) if isinstance(facet_col_labels, dict): for key in df[facet_col].unique(): if key not in facet_col_labels.keys(): unique_keys = df[facet_col].unique().tolist() raise exceptions.PlotlyError(CUSTOM_LABEL_ERROR.format(unique_keys)) show_legend = False if color_name: if isinstance(df[color_name].iloc[0], str) or color_is_cat: show_legend = True if isinstance(colormap, dict): clrs.validate_colors_dict(colormap, "rgb") for val in df[color_name].unique(): if val not in colormap.keys(): raise exceptions.PlotlyError( "If using 'colormap' as a dictionary, make sure " "all the values of the colormap column are in " "the keys of your dictionary." ) else: # use default plotly colors for dictionary default_colors = clrs.DEFAULT_PLOTLY_COLORS colormap = {} j = 0 for val in df[color_name].unique(): if j >= len(default_colors): j = 0 colormap[val] = default_colors[j] j += 1 fig, annotations = _facet_grid_color_categorical( df, x, y, facet_row, facet_col, color_name, colormap, num_of_rows, num_of_cols, facet_row_labels, facet_col_labels, trace_type, flipped_rows, flipped_cols, show_boxes, SUBPLOT_SPACING, marker_color, kwargs_trace, kwargs_marker, ) elif isinstance(df[color_name].iloc[0], Number): if isinstance(colormap, dict): show_legend = True clrs.validate_colors_dict(colormap, "rgb") for val in df[color_name].unique(): if val not in colormap.keys(): raise exceptions.PlotlyError( "If using 'colormap' as a dictionary, make sure " "all the values of the colormap column are in " "the keys of your dictionary." ) fig, annotations = _facet_grid_color_categorical( df, x, y, facet_row, facet_col, color_name, colormap, num_of_rows, num_of_cols, facet_row_labels, facet_col_labels, trace_type, flipped_rows, flipped_cols, show_boxes, SUBPLOT_SPACING, marker_color, kwargs_trace, kwargs_marker, ) elif isinstance(colormap, list): colorscale_list = colormap clrs.validate_colorscale(colorscale_list) fig, annotations = _facet_grid_color_numerical( df, x, y, facet_row, facet_col, color_name, colorscale_list, num_of_rows, num_of_cols, facet_row_labels, facet_col_labels, trace_type, flipped_rows, flipped_cols, show_boxes, SUBPLOT_SPACING, marker_color, kwargs_trace, kwargs_marker, ) elif isinstance(colormap, str): if colormap in clrs.PLOTLY_SCALES.keys(): colorscale_list = clrs.PLOTLY_SCALES[colormap] else: raise exceptions.PlotlyError( "If 'colormap' is a string, it must be the name " "of a Plotly Colorscale. The available colorscale " "names are {}".format(clrs.PLOTLY_SCALES.keys()) ) fig, annotations = _facet_grid_color_numerical( df, x, y, facet_row, facet_col, color_name, colorscale_list, num_of_rows, num_of_cols, facet_row_labels, facet_col_labels, trace_type, flipped_rows, flipped_cols, show_boxes, SUBPLOT_SPACING, marker_color, kwargs_trace, kwargs_marker, ) else: colorscale_list = clrs.PLOTLY_SCALES["Reds"] fig, annotations = _facet_grid_color_numerical( df, x, y, facet_row, facet_col, color_name, colorscale_list, num_of_rows, num_of_cols, facet_row_labels, facet_col_labels, trace_type, flipped_rows, flipped_cols, show_boxes, SUBPLOT_SPACING, marker_color, kwargs_trace, kwargs_marker, ) else: fig, annotations = _facet_grid( df, x, y, facet_row, facet_col, num_of_rows, num_of_cols, facet_row_labels, facet_col_labels, trace_type, flipped_rows, flipped_cols, show_boxes, SUBPLOT_SPACING, marker_color, kwargs_trace, kwargs_marker, ) if not height: height = max(600, 100 * num_of_rows) if not width: width = max(600, 100 * num_of_cols) fig["layout"].update( height=height, width=width, title="", paper_bgcolor="rgb(251, 251, 251)" ) if ggplot2: fig["layout"].update( plot_bgcolor=PLOT_BGCOLOR, paper_bgcolor="rgb(255, 255, 255)", hovermode="closest", ) # axis titles x_title_annot = _axis_title_annotation(x, "x") y_title_annot = _axis_title_annotation(y, "y") # annotations annotations.append(x_title_annot) annotations.append(y_title_annot) # legend fig["layout"]["showlegend"] = show_legend fig["layout"]["legend"]["bgcolor"] = LEGEND_COLOR fig["layout"]["legend"]["borderwidth"] = LEGEND_BORDER_WIDTH fig["layout"]["legend"]["x"] = 1.05 fig["layout"]["legend"]["y"] = 1 fig["layout"]["legend"]["yanchor"] = "top" if show_legend: fig["layout"]["showlegend"] = show_legend if ggplot2: if color_name: legend_annot = _legend_annotation(color_name) annotations.append(legend_annot) fig["layout"]["margin"]["r"] = 150 # assign annotations to figure fig["layout"]["annotations"] = annotations # add shaded boxes behind axis titles if show_boxes and ggplot2: _add_shapes_to_fig(fig, ANNOT_RECT_COLOR, flipped_rows, flipped_cols) # all xaxis and yaxis labels axis_labels = {"x": [], "y": []} for key in fig["layout"]: if "xaxis" in key: axis_labels["x"].append(key) elif "yaxis" in key: axis_labels["y"].append(key) string_number_in_data = False for var in [v for v in [x, y] if v]: if isinstance(df[var].tolist()[0], str): for item in df[var]: try: int(item) string_number_in_data = True except ValueError: pass if string_number_in_data: for x_y in axis_labels.keys(): for axis_name in axis_labels[x_y]: fig["layout"][axis_name]["type"] = "category" if scales == "fixed": fixed_axes = ["x", "y"] elif scales == "free_x": fixed_axes = ["y"] elif scales == "free_y": fixed_axes = ["x"] elif scales == "free": fixed_axes = [] # fixed ranges for x_y in fixed_axes: min_ranges = [] max_ranges = [] for trace in fig["data"]: if trace[x_y] is not None and len(trace[x_y]) > 0: min_ranges.append(min(trace[x_y])) max_ranges.append(max(trace[x_y])) while None in min_ranges: min_ranges.remove(None) while None in max_ranges: max_ranges.remove(None) min_range = min(min_ranges) max_range = max(max_ranges) range_are_numbers = isinstance(min_range, Number) and isinstance( max_range, Number ) if range_are_numbers: min_range = math.floor(min_range) max_range = math.ceil(max_range) # extend widen frame by 5% on each side min_range -= 0.05 * (max_range - min_range) max_range += 0.05 * (max_range - min_range) if x_y == "x": if dtick_x: dtick = dtick_x else: dtick = math.floor((max_range - min_range) / MAX_TICKS_PER_AXIS) elif x_y == "y": if dtick_y: dtick = dtick_y else: dtick = math.floor((max_range - min_range) / MAX_TICKS_PER_AXIS) else: dtick = 1 for axis_title in axis_labels[x_y]: fig["layout"][axis_title]["dtick"] = dtick fig["layout"][axis_title]["ticklen"] = 0 fig["layout"][axis_title]["zeroline"] = False if ggplot2: fig["layout"][axis_title]["tickwidth"] = 1 fig["layout"][axis_title]["ticklen"] = 4 fig["layout"][axis_title]["gridwidth"] = GRID_WIDTH fig["layout"][axis_title]["gridcolor"] = GRID_COLOR fig["layout"][axis_title]["gridwidth"] = 2 fig["layout"][axis_title]["tickfont"] = { "color": TICK_COLOR, "size": 10, } # insert ranges into fig if x_y in fixed_axes: for key in fig["layout"]: if "{}axis".format(x_y) in key and range_are_numbers: fig["layout"][key]["range"] = [min_range, max_range] return fig plotly-4.4.1+dfsg.orig/plotly/figure_factory/_violin.py0000644000175000017500000005012113573717677022643 0ustar noahfxnoahfxfrom __future__ import absolute_import from numbers import Number from plotly import exceptions, optional_imports import plotly.colors as clrs from plotly.graph_objs import graph_objs from plotly.subplots import make_subplots pd = optional_imports.get_module("pandas") np = optional_imports.get_module("numpy") scipy_stats = optional_imports.get_module("scipy.stats") def calc_stats(data): """ Calculate statistics for use in violin plot. """ x = np.asarray(data, np.float) vals_min = np.min(x) vals_max = np.max(x) q2 = np.percentile(x, 50, interpolation="linear") q1 = np.percentile(x, 25, interpolation="lower") q3 = np.percentile(x, 75, interpolation="higher") iqr = q3 - q1 whisker_dist = 1.5 * iqr # in order to prevent drawing whiskers outside the interval # of data one defines the whisker positions as: d1 = np.min(x[x >= (q1 - whisker_dist)]) d2 = np.max(x[x <= (q3 + whisker_dist)]) return { "min": vals_min, "max": vals_max, "q1": q1, "q2": q2, "q3": q3, "d1": d1, "d2": d2, } def make_half_violin(x, y, fillcolor="#1f77b4", linecolor="rgb(0, 0, 0)"): """ Produces a sideways probability distribution fig violin plot. """ text = [ "(pdf(y), y)=(" + "{:0.2f}".format(x[i]) + ", " + "{:0.2f}".format(y[i]) + ")" for i in range(len(x)) ] return graph_objs.Scatter( x=x, y=y, mode="lines", name="", text=text, fill="tonextx", fillcolor=fillcolor, line=graph_objs.scatter.Line(width=0.5, color=linecolor, shape="spline"), hoverinfo="text", opacity=0.5, ) def make_violin_rugplot(vals, pdf_max, distance, color="#1f77b4"): """ Returns a rugplot fig for a violin plot. """ return graph_objs.Scatter( y=vals, x=[-pdf_max - distance] * len(vals), marker=graph_objs.scatter.Marker(color=color, symbol="line-ew-open"), mode="markers", name="", showlegend=False, hoverinfo="y", ) def make_non_outlier_interval(d1, d2): """ Returns the scatterplot fig of most of a violin plot. """ return graph_objs.Scatter( x=[0, 0], y=[d1, d2], name="", mode="lines", line=graph_objs.scatter.Line(width=1.5, color="rgb(0,0,0)"), ) def make_quartiles(q1, q3): """ Makes the upper and lower quartiles for a violin plot. """ return graph_objs.Scatter( x=[0, 0], y=[q1, q3], text=[ "lower-quartile: " + "{:0.2f}".format(q1), "upper-quartile: " + "{:0.2f}".format(q3), ], mode="lines", line=graph_objs.scatter.Line(width=4, color="rgb(0,0,0)"), hoverinfo="text", ) def make_median(q2): """ Formats the 'median' hovertext for a violin plot. """ return graph_objs.Scatter( x=[0], y=[q2], text=["median: " + "{:0.2f}".format(q2)], mode="markers", marker=dict(symbol="square", color="rgb(255,255,255)"), hoverinfo="text", ) def make_XAxis(xaxis_title, xaxis_range): """ Makes the x-axis for a violin plot. """ xaxis = graph_objs.layout.XAxis( title=xaxis_title, range=xaxis_range, showgrid=False, zeroline=False, showline=False, mirror=False, ticks="", showticklabels=False, ) return xaxis def make_YAxis(yaxis_title): """ Makes the y-axis for a violin plot. """ yaxis = graph_objs.layout.YAxis( title=yaxis_title, showticklabels=True, autorange=True, ticklen=4, showline=True, zeroline=False, showgrid=False, mirror=False, ) return yaxis def violinplot(vals, fillcolor="#1f77b4", rugplot=True): """ Refer to FigureFactory.create_violin() for docstring. """ vals = np.asarray(vals, np.float) # summary statistics vals_min = calc_stats(vals)["min"] vals_max = calc_stats(vals)["max"] q1 = calc_stats(vals)["q1"] q2 = calc_stats(vals)["q2"] q3 = calc_stats(vals)["q3"] d1 = calc_stats(vals)["d1"] d2 = calc_stats(vals)["d2"] # kernel density estimation of pdf pdf = scipy_stats.gaussian_kde(vals) # grid over the data interval xx = np.linspace(vals_min, vals_max, 100) # evaluate the pdf at the grid xx yy = pdf(xx) max_pdf = np.max(yy) # distance from the violin plot to rugplot distance = (2.0 * max_pdf) / 10 if rugplot else 0 # range for x values in the plot plot_xrange = [-max_pdf - distance - 0.1, max_pdf + 0.1] plot_data = [ make_half_violin(-yy, xx, fillcolor=fillcolor), make_half_violin(yy, xx, fillcolor=fillcolor), make_non_outlier_interval(d1, d2), make_quartiles(q1, q3), make_median(q2), ] if rugplot: plot_data.append( make_violin_rugplot(vals, max_pdf, distance=distance, color=fillcolor) ) return plot_data, plot_xrange def violin_no_colorscale( data, data_header, group_header, colors, use_colorscale, group_stats, rugplot, sort, height, width, title, ): """ Refer to FigureFactory.create_violin() for docstring. Returns fig for violin plot without colorscale. """ # collect all group names group_name = [] for name in data[group_header]: if name not in group_name: group_name.append(name) if sort: group_name.sort() gb = data.groupby([group_header]) L = len(group_name) fig = make_subplots( rows=1, cols=L, shared_yaxes=True, horizontal_spacing=0.025, print_grid=False ) color_index = 0 for k, gr in enumerate(group_name): vals = np.asarray(gb.get_group(gr)[data_header], np.float) if color_index >= len(colors): color_index = 0 plot_data, plot_xrange = violinplot( vals, fillcolor=colors[color_index], rugplot=rugplot ) layout = graph_objs.Layout() for item in plot_data: fig.append_trace(item, 1, k + 1) color_index += 1 # add violin plot labels fig["layout"].update( {"xaxis{}".format(k + 1): make_XAxis(group_name[k], plot_xrange)} ) # set the sharey axis style fig["layout"].update({"yaxis{}".format(1): make_YAxis("")}) fig["layout"].update( title=title, showlegend=False, hovermode="closest", autosize=False, height=height, width=width, ) return fig def violin_colorscale( data, data_header, group_header, colors, use_colorscale, group_stats, rugplot, sort, height, width, title, ): """ Refer to FigureFactory.create_violin() for docstring. Returns fig for violin plot with colorscale. """ # collect all group names group_name = [] for name in data[group_header]: if name not in group_name: group_name.append(name) if sort: group_name.sort() # make sure all group names are keys in group_stats for group in group_name: if group not in group_stats: raise exceptions.PlotlyError( "All values/groups in the index " "column must be represented " "as a key in group_stats." ) gb = data.groupby([group_header]) L = len(group_name) fig = make_subplots( rows=1, cols=L, shared_yaxes=True, horizontal_spacing=0.025, print_grid=False ) # prepare low and high color for colorscale lowcolor = clrs.color_parser(colors[0], clrs.unlabel_rgb) highcolor = clrs.color_parser(colors[1], clrs.unlabel_rgb) # find min and max values in group_stats group_stats_values = [] for key in group_stats: group_stats_values.append(group_stats[key]) max_value = max(group_stats_values) min_value = min(group_stats_values) for k, gr in enumerate(group_name): vals = np.asarray(gb.get_group(gr)[data_header], np.float) # find intermediate color from colorscale intermed = (group_stats[gr] - min_value) / (max_value - min_value) intermed_color = clrs.find_intermediate_color(lowcolor, highcolor, intermed) plot_data, plot_xrange = violinplot( vals, fillcolor="rgb{}".format(intermed_color), rugplot=rugplot ) layout = graph_objs.Layout() for item in plot_data: fig.append_trace(item, 1, k + 1) fig["layout"].update( {"xaxis{}".format(k + 1): make_XAxis(group_name[k], plot_xrange)} ) # add colorbar to plot trace_dummy = graph_objs.Scatter( x=[0], y=[0], mode="markers", marker=dict( size=2, cmin=min_value, cmax=max_value, colorscale=[[0, colors[0]], [1, colors[1]]], showscale=True, ), showlegend=False, ) fig.append_trace(trace_dummy, 1, L) # set the sharey axis style fig["layout"].update({"yaxis{}".format(1): make_YAxis("")}) fig["layout"].update( title=title, showlegend=False, hovermode="closest", autosize=False, height=height, width=width, ) return fig def violin_dict( data, data_header, group_header, colors, use_colorscale, group_stats, rugplot, sort, height, width, title, ): """ Refer to FigureFactory.create_violin() for docstring. Returns fig for violin plot without colorscale. """ # collect all group names group_name = [] for name in data[group_header]: if name not in group_name: group_name.append(name) if sort: group_name.sort() # check if all group names appear in colors dict for group in group_name: if group not in colors: raise exceptions.PlotlyError( "If colors is a dictionary, all " "the group names must appear as " "keys in colors." ) gb = data.groupby([group_header]) L = len(group_name) fig = make_subplots( rows=1, cols=L, shared_yaxes=True, horizontal_spacing=0.025, print_grid=False ) for k, gr in enumerate(group_name): vals = np.asarray(gb.get_group(gr)[data_header], np.float) plot_data, plot_xrange = violinplot(vals, fillcolor=colors[gr], rugplot=rugplot) layout = graph_objs.Layout() for item in plot_data: fig.append_trace(item, 1, k + 1) # add violin plot labels fig["layout"].update( {"xaxis{}".format(k + 1): make_XAxis(group_name[k], plot_xrange)} ) # set the sharey axis style fig["layout"].update({"yaxis{}".format(1): make_YAxis("")}) fig["layout"].update( title=title, showlegend=False, hovermode="closest", autosize=False, height=height, width=width, ) return fig def create_violin( data, data_header=None, group_header=None, colors=None, use_colorscale=False, group_stats=None, rugplot=True, sort=False, height=450, width=600, title="Violin and Rug Plot", ): """ **deprecated**, use instead the plotly.graph_objects trace :class:`plotly.graph_objects.Violin`. :param (list|array) data: accepts either a list of numerical values, a list of dictionaries all with identical keys and at least one column of numeric values, or a pandas dataframe with at least one column of numbers. :param (str) data_header: the header of the data column to be used from an inputted pandas dataframe. Not applicable if 'data' is a list of numeric values. :param (str) group_header: applicable if grouping data by a variable. 'group_header' must be set to the name of the grouping variable. :param (str|tuple|list|dict) colors: either a plotly scale name, an rgb or hex color, a color tuple, a list of colors or a dictionary. An rgb color is of the form 'rgb(x, y, z)' where x, y and z belong to the interval [0, 255] and a color tuple is a tuple of the form (a, b, c) where a, b and c belong to [0, 1]. If colors is a list, it must contain valid color types as its members. :param (bool) use_colorscale: only applicable if grouping by another variable. Will implement a colorscale based on the first 2 colors of param colors. This means colors must be a list with at least 2 colors in it (Plotly colorscales are accepted since they map to a list of two rgb colors). Default = False :param (dict) group_stats: a dictioanry where each key is a unique value from the group_header column in data. Each value must be a number and will be used to color the violin plots if a colorscale is being used. :param (bool) rugplot: determines if a rugplot is draw on violin plot. Default = True :param (bool) sort: determines if violins are sorted alphabetically (True) or by input order (False). Default = False :param (float) height: the height of the violin plot. :param (float) width: the width of the violin plot. :param (str) title: the title of the violin plot. Example 1: Single Violin Plot >>> from plotly.figure_factory import create_violin >>> import plotly.graph_objs as graph_objects >>> import numpy as np >>> from scipy import stats >>> # create list of random values >>> data_list = np.random.randn(100) >>> # create violin fig >>> fig = create_violin(data_list, colors='#604d9e') >>> # plot >>> fig.show() Example 2: Multiple Violin Plots with Qualitative Coloring >>> from plotly.figure_factory import create_violin >>> import plotly.graph_objs as graph_objects >>> import numpy as np >>> import pandas as pd >>> from scipy import stats >>> # create dataframe >>> np.random.seed(619517) >>> Nr=250 >>> y = np.random.randn(Nr) >>> gr = np.random.choice(list("ABCDE"), Nr) >>> norm_params=[(0, 1.2), (0.7, 1), (-0.5, 1.4), (0.3, 1), (0.8, 0.9)] >>> for i, letter in enumerate("ABCDE"): ... y[gr == letter] *=norm_params[i][1]+ norm_params[i][0] >>> df = pd.DataFrame(dict(Score=y, Group=gr)) >>> # create violin fig >>> fig = create_violin(df, data_header='Score', group_header='Group', ... sort=True, height=600, width=1000) >>> # plot >>> fig.show() Example 3: Violin Plots with Colorscale >>> from plotly.figure_factory import create_violin >>> import plotly.graph_objs as graph_objects >>> import numpy as np >>> import pandas as pd >>> from scipy import stats >>> # create dataframe >>> np.random.seed(619517) >>> Nr=250 >>> y = np.random.randn(Nr) >>> gr = np.random.choice(list("ABCDE"), Nr) >>> norm_params=[(0, 1.2), (0.7, 1), (-0.5, 1.4), (0.3, 1), (0.8, 0.9)] >>> for i, letter in enumerate("ABCDE"): ... y[gr == letter] *=norm_params[i][1]+ norm_params[i][0] >>> df = pd.DataFrame(dict(Score=y, Group=gr)) >>> # define header params >>> data_header = 'Score' >>> group_header = 'Group' >>> # make groupby object with pandas >>> group_stats = {} >>> groupby_data = df.groupby([group_header]) >>> for group in "ABCDE": ... data_from_group = groupby_data.get_group(group)[data_header] ... # take a stat of the grouped data ... stat = np.median(data_from_group) ... # add to dictionary ... group_stats[group] = stat >>> # create violin fig >>> fig = create_violin(df, data_header='Score', group_header='Group', ... height=600, width=1000, use_colorscale=True, ... group_stats=group_stats) >>> # plot >>> fig.show() """ # Validate colors if isinstance(colors, dict): valid_colors = clrs.validate_colors_dict(colors, "rgb") else: valid_colors = clrs.validate_colors(colors, "rgb") # validate data and choose plot type if group_header is None: if isinstance(data, list): if len(data) <= 0: raise exceptions.PlotlyError( "If data is a list, it must be " "nonempty and contain either " "numbers or dictionaries." ) if not all(isinstance(element, Number) for element in data): raise exceptions.PlotlyError( "If data is a list, it must " "contain only numbers." ) if pd and isinstance(data, pd.core.frame.DataFrame): if data_header is None: raise exceptions.PlotlyError( "data_header must be the " "column name with the " "desired numeric data for " "the violin plot." ) data = data[data_header].values.tolist() # call the plotting functions plot_data, plot_xrange = violinplot( data, fillcolor=valid_colors[0], rugplot=rugplot ) layout = graph_objs.Layout( title=title, autosize=False, font=graph_objs.layout.Font(size=11), height=height, showlegend=False, width=width, xaxis=make_XAxis("", plot_xrange), yaxis=make_YAxis(""), hovermode="closest", ) layout["yaxis"].update(dict(showline=False, showticklabels=False, ticks="")) fig = graph_objs.Figure(data=plot_data, layout=layout) return fig else: if not isinstance(data, pd.core.frame.DataFrame): raise exceptions.PlotlyError( "Error. You must use a pandas " "DataFrame if you are using a " "group header." ) if data_header is None: raise exceptions.PlotlyError( "data_header must be the column " "name with the desired numeric " "data for the violin plot." ) if use_colorscale is False: if isinstance(valid_colors, dict): # validate colors dict choice below fig = violin_dict( data, data_header, group_header, valid_colors, use_colorscale, group_stats, rugplot, sort, height, width, title, ) return fig else: fig = violin_no_colorscale( data, data_header, group_header, valid_colors, use_colorscale, group_stats, rugplot, sort, height, width, title, ) return fig else: if isinstance(valid_colors, dict): raise exceptions.PlotlyError( "The colors param cannot be " "a dictionary if you are " "using a colorscale." ) if len(valid_colors) < 2: raise exceptions.PlotlyError( "colors must be a list with " "at least 2 colors. A " "Plotly scale is allowed." ) if not isinstance(group_stats, dict): raise exceptions.PlotlyError( "Your group_stats param " "must be a dictionary." ) fig = violin_colorscale( data, data_header, group_header, valid_colors, use_colorscale, group_stats, rugplot, sort, height, width, title, ) return fig plotly-4.4.1+dfsg.orig/plotly/figure_factory/_trisurf.py0000644000175000017500000004104113573717677023042 0ustar noahfxnoahfxfrom __future__ import absolute_import from plotly import exceptions, optional_imports import plotly.colors as clrs from plotly.graph_objs import graph_objs np = optional_imports.get_module("numpy") def map_face2color(face, colormap, scale, vmin, vmax): """ Normalize facecolor values by vmin/vmax and return rgb-color strings This function takes a tuple color along with a colormap and a minimum (vmin) and maximum (vmax) range of possible mean distances for the given parametrized surface. It returns an rgb color based on the mean distance between vmin and vmax """ if vmin >= vmax: raise exceptions.PlotlyError( "Incorrect relation between vmin " "and vmax. The vmin value cannot be " "bigger than or equal to the value " "of vmax." ) if len(colormap) == 1: # color each triangle face with the same color in colormap face_color = colormap[0] face_color = clrs.convert_to_RGB_255(face_color) face_color = clrs.label_rgb(face_color) return face_color if face == vmax: # pick last color in colormap face_color = colormap[-1] face_color = clrs.convert_to_RGB_255(face_color) face_color = clrs.label_rgb(face_color) return face_color else: if scale is None: # find the normalized distance t of a triangle face between # vmin and vmax where the distance is between 0 and 1 t = (face - vmin) / float((vmax - vmin)) low_color_index = int(t / (1.0 / (len(colormap) - 1))) face_color = clrs.find_intermediate_color( colormap[low_color_index], colormap[low_color_index + 1], t * (len(colormap) - 1) - low_color_index, ) face_color = clrs.convert_to_RGB_255(face_color) face_color = clrs.label_rgb(face_color) else: # find the face color for a non-linearly interpolated scale t = (face - vmin) / float((vmax - vmin)) low_color_index = 0 for k in range(len(scale) - 1): if scale[k] <= t < scale[k + 1]: break low_color_index += 1 low_scale_val = scale[low_color_index] high_scale_val = scale[low_color_index + 1] face_color = clrs.find_intermediate_color( colormap[low_color_index], colormap[low_color_index + 1], (t - low_scale_val) / (high_scale_val - low_scale_val), ) face_color = clrs.convert_to_RGB_255(face_color) face_color = clrs.label_rgb(face_color) return face_color def trisurf( x, y, z, simplices, show_colorbar, edges_color, scale, colormap=None, color_func=None, plot_edges=False, x_edge=None, y_edge=None, z_edge=None, facecolor=None, ): """ Refer to FigureFactory.create_trisurf() for docstring """ # numpy import check if not np: raise ImportError("FigureFactory._trisurf() requires " "numpy imported.") points3D = np.vstack((x, y, z)).T simplices = np.atleast_2d(simplices) # vertices of the surface triangles tri_vertices = points3D[simplices] # Define colors for the triangle faces if color_func is None: # mean values of z-coordinates of triangle vertices mean_dists = tri_vertices[:, :, 2].mean(-1) elif isinstance(color_func, (list, np.ndarray)): # Pre-computed list / array of values to map onto color if len(color_func) != len(simplices): raise ValueError( "If color_func is a list/array, it must " "be the same length as simplices." ) # convert all colors in color_func to rgb for index in range(len(color_func)): if isinstance(color_func[index], str): if "#" in color_func[index]: foo = clrs.hex_to_rgb(color_func[index]) color_func[index] = clrs.label_rgb(foo) if isinstance(color_func[index], tuple): foo = clrs.convert_to_RGB_255(color_func[index]) color_func[index] = clrs.label_rgb(foo) mean_dists = np.asarray(color_func) else: # apply user inputted function to calculate # custom coloring for triangle vertices mean_dists = [] for triangle in tri_vertices: dists = [] for vertex in triangle: dist = color_func(vertex[0], vertex[1], vertex[2]) dists.append(dist) mean_dists.append(np.mean(dists)) mean_dists = np.asarray(mean_dists) # Check if facecolors are already strings and can be skipped if isinstance(mean_dists[0], str): facecolor = mean_dists else: min_mean_dists = np.min(mean_dists) max_mean_dists = np.max(mean_dists) if facecolor is None: facecolor = [] for index in range(len(mean_dists)): color = map_face2color( mean_dists[index], colormap, scale, min_mean_dists, max_mean_dists ) facecolor.append(color) # Make sure facecolor is a list so output is consistent across Pythons facecolor = np.asarray(facecolor) ii, jj, kk = simplices.T triangles = graph_objs.Mesh3d( x=x, y=y, z=z, facecolor=facecolor, i=ii, j=jj, k=kk, name="" ) mean_dists_are_numbers = not isinstance(mean_dists[0], str) if mean_dists_are_numbers and show_colorbar is True: # make a colorscale from the colors colorscale = clrs.make_colorscale(colormap, scale) colorscale = clrs.convert_colorscale_to_rgb(colorscale) colorbar = graph_objs.Scatter3d( x=x[:1], y=y[:1], z=z[:1], mode="markers", marker=dict( size=0.1, color=[min_mean_dists, max_mean_dists], colorscale=colorscale, showscale=True, ), hoverinfo="none", showlegend=False, ) # the triangle sides are not plotted if plot_edges is False: if mean_dists_are_numbers and show_colorbar is True: return [triangles, colorbar] else: return [triangles] # define the lists x_edge, y_edge and z_edge, of x, y, resp z # coordinates of edge end points for each triangle # None separates data corresponding to two consecutive triangles is_none = [ii is None for ii in [x_edge, y_edge, z_edge]] if any(is_none): if not all(is_none): raise ValueError( "If any (x_edge, y_edge, z_edge) is None, " "all must be None" ) else: x_edge = [] y_edge = [] z_edge = [] # Pull indices we care about, then add a None column to separate tris ixs_triangles = [0, 1, 2, 0] pull_edges = tri_vertices[:, ixs_triangles, :] x_edge_pull = np.hstack( [pull_edges[:, :, 0], np.tile(None, [pull_edges.shape[0], 1])] ) y_edge_pull = np.hstack( [pull_edges[:, :, 1], np.tile(None, [pull_edges.shape[0], 1])] ) z_edge_pull = np.hstack( [pull_edges[:, :, 2], np.tile(None, [pull_edges.shape[0], 1])] ) # Now unravel the edges into a 1-d vector for plotting x_edge = np.hstack([x_edge, x_edge_pull.reshape([1, -1])[0]]) y_edge = np.hstack([y_edge, y_edge_pull.reshape([1, -1])[0]]) z_edge = np.hstack([z_edge, z_edge_pull.reshape([1, -1])[0]]) if not (len(x_edge) == len(y_edge) == len(z_edge)): raise exceptions.PlotlyError( "The lengths of x_edge, y_edge and " "z_edge are not the same." ) # define the lines for plotting lines = graph_objs.Scatter3d( x=x_edge, y=y_edge, z=z_edge, mode="lines", line=graph_objs.scatter3d.Line(color=edges_color, width=1.5), showlegend=False, ) if mean_dists_are_numbers and show_colorbar is True: return [triangles, lines, colorbar] else: return [triangles, lines] def create_trisurf( x, y, z, simplices, colormap=None, show_colorbar=True, scale=None, color_func=None, title="Trisurf Plot", plot_edges=True, showbackground=True, backgroundcolor="rgb(230, 230, 230)", gridcolor="rgb(255, 255, 255)", zerolinecolor="rgb(255, 255, 255)", edges_color="rgb(50, 50, 50)", height=800, width=800, aspectratio=None, ): """ Returns figure for a triangulated surface plot :param (array) x: data values of x in a 1D array :param (array) y: data values of y in a 1D array :param (array) z: data values of z in a 1D array :param (array) simplices: an array of shape (ntri, 3) where ntri is the number of triangles in the triangularization. Each row of the array contains the indicies of the verticies of each triangle :param (str|tuple|list) colormap: either a plotly scale name, an rgb or hex color, a color tuple or a list of colors. An rgb color is of the form 'rgb(x, y, z)' where x, y, z belong to the interval [0, 255] and a color tuple is a tuple of the form (a, b, c) where a, b and c belong to [0, 1]. If colormap is a list, it must contain the valid color types aforementioned as its members :param (bool) show_colorbar: determines if colorbar is visible :param (list|array) scale: sets the scale values to be used if a non- linearly interpolated colormap is desired. If left as None, a linear interpolation between the colors will be excecuted :param (function|list) color_func: The parameter that determines the coloring of the surface. Takes either a function with 3 arguments x, y, z or a list/array of color values the same length as simplices. If None, coloring will only depend on the z axis :param (str) title: title of the plot :param (bool) plot_edges: determines if the triangles on the trisurf are visible :param (bool) showbackground: makes background in plot visible :param (str) backgroundcolor: color of background. Takes a string of the form 'rgb(x,y,z)' x,y,z are between 0 and 255 inclusive :param (str) gridcolor: color of the gridlines besides the axes. Takes a string of the form 'rgb(x,y,z)' x,y,z are between 0 and 255 inclusive :param (str) zerolinecolor: color of the axes. Takes a string of the form 'rgb(x,y,z)' x,y,z are between 0 and 255 inclusive :param (str) edges_color: color of the edges, if plot_edges is True :param (int|float) height: the height of the plot (in pixels) :param (int|float) width: the width of the plot (in pixels) :param (dict) aspectratio: a dictionary of the aspect ratio values for the x, y and z axes. 'x', 'y' and 'z' take (int|float) values Example 1: Sphere >>> # Necessary Imports for Trisurf >>> import numpy as np >>> from scipy.spatial import Delaunay >>> from plotly.figure_factory import create_trisurf >>> from plotly.graph_objs import graph_objs >>> # Make data for plot >>> u = np.linspace(0, 2*np.pi, 20) >>> v = np.linspace(0, np.pi, 20) >>> u,v = np.meshgrid(u,v) >>> u = u.flatten() >>> v = v.flatten() >>> x = np.sin(v)*np.cos(u) >>> y = np.sin(v)*np.sin(u) >>> z = np.cos(v) >>> points2D = np.vstack([u,v]).T >>> tri = Delaunay(points2D) >>> simplices = tri.simplices >>> # Create a figure >>> fig1 = create_trisurf(x=x, y=y, z=z, colormap="Rainbow", ... simplices=simplices) Example 2: Torus >>> # Necessary Imports for Trisurf >>> import numpy as np >>> from scipy.spatial import Delaunay >>> from plotly.figure_factory import create_trisurf >>> from plotly.graph_objs import graph_objs >>> # Make data for plot >>> u = np.linspace(0, 2*np.pi, 20) >>> v = np.linspace(0, 2*np.pi, 20) >>> u,v = np.meshgrid(u,v) >>> u = u.flatten() >>> v = v.flatten() >>> x = (3 + (np.cos(v)))*np.cos(u) >>> y = (3 + (np.cos(v)))*np.sin(u) >>> z = np.sin(v) >>> points2D = np.vstack([u,v]).T >>> tri = Delaunay(points2D) >>> simplices = tri.simplices >>> # Create a figure >>> fig1 = create_trisurf(x=x, y=y, z=z, colormap="Viridis", ... simplices=simplices) Example 3: Mobius Band >>> # Necessary Imports for Trisurf >>> import numpy as np >>> from scipy.spatial import Delaunay >>> from plotly.figure_factory import create_trisurf >>> from plotly.graph_objs import graph_objs >>> # Make data for plot >>> u = np.linspace(0, 2*np.pi, 24) >>> v = np.linspace(-1, 1, 8) >>> u,v = np.meshgrid(u,v) >>> u = u.flatten() >>> v = v.flatten() >>> tp = 1 + 0.5*v*np.cos(u/2.) >>> x = tp*np.cos(u) >>> y = tp*np.sin(u) >>> z = 0.5*v*np.sin(u/2.) >>> points2D = np.vstack([u,v]).T >>> tri = Delaunay(points2D) >>> simplices = tri.simplices >>> # Create a figure >>> fig1 = create_trisurf(x=x, y=y, z=z, colormap=[(0.2, 0.4, 0.6), (1, 1, 1)], ... simplices=simplices) Example 4: Using a Custom Colormap Function with Light Cone >>> # Necessary Imports for Trisurf >>> import numpy as np >>> from scipy.spatial import Delaunay >>> from plotly.figure_factory import create_trisurf >>> from plotly.graph_objs import graph_objs >>> # Make data for plot >>> u=np.linspace(-np.pi, np.pi, 30) >>> v=np.linspace(-np.pi, np.pi, 30) >>> u,v=np.meshgrid(u,v) >>> u=u.flatten() >>> v=v.flatten() >>> x = u >>> y = u*np.cos(v) >>> z = u*np.sin(v) >>> points2D = np.vstack([u,v]).T >>> tri = Delaunay(points2D) >>> simplices = tri.simplices >>> # Define distance function >>> def dist_origin(x, y, z): ... return np.sqrt((1.0 * x)**2 + (1.0 * y)**2 + (1.0 * z)**2) >>> # Create a figure >>> fig1 = create_trisurf(x=x, y=y, z=z, ... colormap=['#FFFFFF', '#E4FFFE', ... '#A4F6F9', '#FF99FE', ... '#BA52ED'], ... scale=[0, 0.6, 0.71, 0.89, 1], ... simplices=simplices, ... color_func=dist_origin) Example 5: Enter color_func as a list of colors >>> # Necessary Imports for Trisurf >>> import numpy as np >>> from scipy.spatial import Delaunay >>> import random >>> from plotly.figure_factory import create_trisurf >>> from plotly.graph_objs import graph_objs >>> # Make data for plot >>> u=np.linspace(-np.pi, np.pi, 30) >>> v=np.linspace(-np.pi, np.pi, 30) >>> u,v=np.meshgrid(u,v) >>> u=u.flatten() >>> v=v.flatten() >>> x = u >>> y = u*np.cos(v) >>> z = u*np.sin(v) >>> points2D = np.vstack([u,v]).T >>> tri = Delaunay(points2D) >>> simplices = tri.simplices >>> colors = [] >>> color_choices = ['rgb(0, 0, 0)', '#6c4774', '#d6c7dd'] >>> for index in range(len(simplices)): ... colors.append(random.choice(color_choices)) >>> fig = create_trisurf( ... x, y, z, simplices, ... color_func=colors, ... show_colorbar=True, ... edges_color='rgb(2, 85, 180)', ... title=' Modern Art' ... ) """ if aspectratio is None: aspectratio = {"x": 1, "y": 1, "z": 1} # Validate colormap clrs.validate_colors(colormap) colormap, scale = clrs.convert_colors_to_same_type( colormap, colortype="tuple", return_default_colors=True, scale=scale ) data1 = trisurf( x, y, z, simplices, show_colorbar=show_colorbar, color_func=color_func, colormap=colormap, scale=scale, edges_color=edges_color, plot_edges=plot_edges, ) axis = dict( showbackground=showbackground, backgroundcolor=backgroundcolor, gridcolor=gridcolor, zerolinecolor=zerolinecolor, ) layout = graph_objs.Layout( title=title, width=width, height=height, scene=graph_objs.layout.Scene( xaxis=graph_objs.layout.scene.XAxis(**axis), yaxis=graph_objs.layout.scene.YAxis(**axis), zaxis=graph_objs.layout.scene.ZAxis(**axis), aspectratio=dict( x=aspectratio["x"], y=aspectratio["y"], z=aspectratio["z"] ), ), ) return graph_objs.Figure(data=data1, layout=layout) plotly-4.4.1+dfsg.orig/plotly/session.py0000644000175000017500000000016713525746125017647 0ustar noahfxnoahfxfrom __future__ import absolute_import from _plotly_future_ import _chart_studio_error _chart_studio_error("session") plotly-4.4.1+dfsg.orig/plotly/_version.py0000644000175000017500000000076113573746614020016 0ustar noahfxnoahfx # This file was generated by 'versioneer.py' (0.18) from # revision-control system data, or from the parent directory name of an # unpacked source archive. Distribution tarballs contain a pre-generated copy # of this file. import json version_json = ''' { "date": "2019-12-10T11:52:12-0500", "dirty": false, "error": null, "full-revisionid": "6fb105286d0bf81ed045dafd18ad16cdfcc13dd8", "version": "4.4.1" } ''' # END VERSION_JSON def get_versions(): return json.loads(version_json) plotly-4.4.1+dfsg.orig/plotly/validators/0000755000175000017500000000000013573746614017764 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/isosurface/0000755000175000017500000000000013573746614022127 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/isosurface/contour/0000755000175000017500000000000013573746614023620 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/isosurface/contour/__init__.py0000644000175000017500000000261213573721540025721 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="isosurface.contour", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 16), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="show", parent_name="isosurface.contour", **kwargs): super(ShowValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="isosurface.contour", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/isosurface/hoverlabel/0000755000175000017500000000000013573746614024252 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/isosurface/hoverlabel/__init__.py0000644000175000017500000001352213573721540026355 0ustar noahfxnoahfximport _plotly_utils.basevalidators class NamelengthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="namelengthsrc", parent_name="isosurface.hoverlabel", **kwargs ): super(NamelengthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NamelengthValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="namelength", parent_name="isosurface.hoverlabel", **kwargs ): super(NamelengthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", -1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="isosurface.hoverlabel", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class BordercolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bordercolorsrc", parent_name="isosurface.hoverlabel", **kwargs ): super(BordercolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="isosurface.hoverlabel", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bgcolorsrc", parent_name="isosurface.hoverlabel", **kwargs ): super(BgcolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="isosurface.hoverlabel", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AlignsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="alignsrc", parent_name="isosurface.hoverlabel", **kwargs ): super(AlignsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="align", parent_name="isosurface.hoverlabel", **kwargs ): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "right", "auto"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/isosurface/hoverlabel/font/0000755000175000017500000000000013573746614025220 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/isosurface/hoverlabel/font/__init__.py0000644000175000017500000000611713573721540027325 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="isosurface.hoverlabel.font", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="isosurface.hoverlabel.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="isosurface.hoverlabel.font", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="isosurface.hoverlabel.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="isosurface.hoverlabel.font", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="isosurface.hoverlabel.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/isosurface/colorbar/0000755000175000017500000000000013573746614023732 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/isosurface/colorbar/tickformatstop/0000755000175000017500000000000013573746614027003 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/isosurface/colorbar/tickformatstop/__init__.py0000644000175000017500000000535013573721540031106 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="value", parent_name="isosurface.colorbar.tickformatstop", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="isosurface.colorbar.tickformatstop", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="isosurface.colorbar.tickformatstop", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EnabledValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="enabled", parent_name="isosurface.colorbar.tickformatstop", **kwargs ): super(EnabledValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DtickrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="dtickrange", parent_name="isosurface.colorbar.tickformatstop", **kwargs ): super(DtickrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "calc"}, {"valType": "any", "editType": "calc"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/isosurface/colorbar/title/0000755000175000017500000000000013573746614025053 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/isosurface/colorbar/title/__init__.py0000644000175000017500000000471413573721540027161 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="text", parent_name="isosurface.colorbar.title", **kwargs ): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SideValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="side", parent_name="isosurface.colorbar.title", **kwargs ): super(SideValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["right", "top", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="isosurface.colorbar.title", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/isosurface/colorbar/title/font/0000755000175000017500000000000013573746614026021 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/isosurface/colorbar/title/font/__init__.py0000644000175000017500000000310613573721540030121 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="isosurface.colorbar.title.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="isosurface.colorbar.title.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="isosurface.colorbar.title.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/isosurface/colorbar/__init__.py0000644000175000017500000006011713573721541026040 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="ypad", parent_name="isosurface.colorbar", **kwargs): super(YpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class YanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="yanchor", parent_name="isosurface.colorbar", **kwargs ): super(YanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["top", "middle", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="y", parent_name="isosurface.colorbar", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="xpad", parent_name="isosurface.colorbar", **kwargs): super(XpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="xanchor", parent_name="isosurface.colorbar", **kwargs ): super(XanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "center", "right"]), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="x", parent_name="isosurface.colorbar", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TitleValidator(_plotly_utils.basevalidators.TitleValidator): def __init__( self, plotly_name="title", parent_name="isosurface.colorbar", **kwargs ): super(TitleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Title"), data_docs=kwargs.pop( "data_docs", """ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """, ), **kwargs ) import _plotly_utils.basevalidators class TickwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="tickwidth", parent_name="isosurface.colorbar", **kwargs ): super(TickwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickvalssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="tickvalssrc", parent_name="isosurface.colorbar", **kwargs ): super(TickvalssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickvalsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="tickvals", parent_name="isosurface.colorbar", **kwargs ): super(TickvalsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="ticktextsrc", parent_name="isosurface.colorbar", **kwargs ): super(TicktextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicktextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="ticktext", parent_name="isosurface.colorbar", **kwargs ): super(TicktextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="ticksuffix", parent_name="isosurface.colorbar", **kwargs ): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TicksValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="ticks", parent_name="isosurface.colorbar", **kwargs ): super(TicksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["outside", "inside", ""]), **kwargs ) import _plotly_utils.basevalidators class TickprefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickprefix", parent_name="isosurface.colorbar", **kwargs ): super(TickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="tickmode", parent_name="isosurface.colorbar", **kwargs ): super(TickmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "linear", "array"]), **kwargs ) import _plotly_utils.basevalidators class TicklenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ticklen", parent_name="isosurface.colorbar", **kwargs ): super(TicklenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickformatstopValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickformatstopdefaults", parent_name="isosurface.colorbar", **kwargs ): super(TickformatstopValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatstopsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="tickformatstops", parent_name="isosurface.colorbar", **kwargs ): super(TickformatstopsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickformat", parent_name="isosurface.colorbar", **kwargs ): super(TickformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickfont", parent_name="isosurface.colorbar", **kwargs ): super(TickfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class TickcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="tickcolor", parent_name="isosurface.colorbar", **kwargs ): super(TickcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__( self, plotly_name="tickangle", parent_name="isosurface.colorbar", **kwargs ): super(TickangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="tick0", parent_name="isosurface.colorbar", **kwargs ): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ThicknessmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="thicknessmode", parent_name="isosurface.colorbar", **kwargs ): super(ThicknessmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="thickness", parent_name="isosurface.colorbar", **kwargs ): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowticksuffixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showticksuffix", parent_name="isosurface.colorbar", **kwargs ): super(ShowticksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowtickprefixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showtickprefix", parent_name="isosurface.colorbar", **kwargs ): super(ShowtickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowticklabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showticklabels", parent_name="isosurface.colorbar", **kwargs ): super(ShowticklabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowexponentValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showexponent", parent_name="isosurface.colorbar", **kwargs ): super(ShowexponentValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class SeparatethousandsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="separatethousands", parent_name="isosurface.colorbar", **kwargs ): super(SeparatethousandsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="outlinewidth", parent_name="isosurface.colorbar", **kwargs ): super(OutlinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="outlinecolor", parent_name="isosurface.colorbar", **kwargs ): super(OutlinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NticksValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="nticks", parent_name="isosurface.colorbar", **kwargs ): super(NticksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LenmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="lenmode", parent_name="isosurface.colorbar", **kwargs ): super(LenmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class LenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="len", parent_name="isosurface.colorbar", **kwargs): super(LenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ExponentformatValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="exponentformat", parent_name="isosurface.colorbar", **kwargs ): super(ExponentformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "e", "E", "power", "SI", "B"]), **kwargs ) import _plotly_utils.basevalidators class DtickValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="dtick", parent_name="isosurface.colorbar", **kwargs ): super(DtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BorderwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="borderwidth", parent_name="isosurface.colorbar", **kwargs ): super(BorderwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="isosurface.colorbar", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="isosurface.colorbar", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/isosurface/colorbar/tickfont/0000755000175000017500000000000013573746614025553 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/isosurface/colorbar/tickfont/__init__.py0000644000175000017500000000302013573721540027646 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="isosurface.colorbar.tickfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="isosurface.colorbar.tickfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="isosurface.colorbar.tickfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/isosurface/caps/0000755000175000017500000000000013573746614023055 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/isosurface/caps/x/0000755000175000017500000000000013573746614023324 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/isosurface/caps/x/__init__.py0000644000175000017500000000170413573721540025426 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ShowValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="show", parent_name="isosurface.caps.x", **kwargs): super(ShowValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FillValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="fill", parent_name="isosurface.caps.x", **kwargs): super(FillValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/isosurface/caps/z/0000755000175000017500000000000013573746614023326 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/isosurface/caps/z/__init__.py0000644000175000017500000000170413573721540025430 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ShowValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="show", parent_name="isosurface.caps.z", **kwargs): super(ShowValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FillValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="fill", parent_name="isosurface.caps.z", **kwargs): super(FillValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/isosurface/caps/y/0000755000175000017500000000000013573746614023325 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/isosurface/caps/y/__init__.py0000644000175000017500000000170413573721540025427 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ShowValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="show", parent_name="isosurface.caps.y", **kwargs): super(ShowValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FillValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="fill", parent_name="isosurface.caps.y", **kwargs): super(FillValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/isosurface/caps/__init__.py0000644000175000017500000000672213573721540025164 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ZValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="z", parent_name="isosurface.caps", **kwargs): super(ZValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Z"), data_docs=kwargs.pop( "data_docs", """ fill Sets the fill ratio of the `caps`. The default fill value of the `caps` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. show Sets the fill ratio of the `slices`. The default fill value of the z `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. """, ), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="y", parent_name="isosurface.caps", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Y"), data_docs=kwargs.pop( "data_docs", """ fill Sets the fill ratio of the `caps`. The default fill value of the `caps` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. show Sets the fill ratio of the `slices`. The default fill value of the y `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. """, ), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="x", parent_name="isosurface.caps", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "X"), data_docs=kwargs.pop( "data_docs", """ fill Sets the fill ratio of the `caps`. The default fill value of the `caps` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. show Sets the fill ratio of the `slices`. The default fill value of the x `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/isosurface/lightposition/0000755000175000017500000000000013573746614025023 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/isosurface/lightposition/__init__.py0000644000175000017500000000313613573721540027126 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ZValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="z", parent_name="isosurface.lightposition", **kwargs ): super(ZValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 100000), min=kwargs.pop("min", -100000), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="y", parent_name="isosurface.lightposition", **kwargs ): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 100000), min=kwargs.pop("min", -100000), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="x", parent_name="isosurface.lightposition", **kwargs ): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 100000), min=kwargs.pop("min", -100000), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/isosurface/slices/0000755000175000017500000000000013573746614023411 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/isosurface/slices/x/0000755000175000017500000000000013573746614023660 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/isosurface/slices/x/__init__.py0000644000175000017500000000360713573721540025766 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ShowValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="show", parent_name="isosurface.slices.x", **kwargs): super(ShowValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LocationssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="locationssrc", parent_name="isosurface.slices.x", **kwargs ): super(LocationssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LocationsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="locations", parent_name="isosurface.slices.x", **kwargs ): super(LocationsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class FillValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="fill", parent_name="isosurface.slices.x", **kwargs): super(FillValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/isosurface/slices/z/0000755000175000017500000000000013573746614023662 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/isosurface/slices/z/__init__.py0000644000175000017500000000360713573721540025770 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ShowValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="show", parent_name="isosurface.slices.z", **kwargs): super(ShowValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LocationssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="locationssrc", parent_name="isosurface.slices.z", **kwargs ): super(LocationssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LocationsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="locations", parent_name="isosurface.slices.z", **kwargs ): super(LocationsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class FillValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="fill", parent_name="isosurface.slices.z", **kwargs): super(FillValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/isosurface/slices/y/0000755000175000017500000000000013573746614023661 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/isosurface/slices/y/__init__.py0000644000175000017500000000360713573721540025767 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ShowValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="show", parent_name="isosurface.slices.y", **kwargs): super(ShowValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LocationssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="locationssrc", parent_name="isosurface.slices.y", **kwargs ): super(LocationssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LocationsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="locations", parent_name="isosurface.slices.y", **kwargs ): super(LocationsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class FillValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="fill", parent_name="isosurface.slices.y", **kwargs): super(FillValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/isosurface/slices/__init__.py0000644000175000017500000000753313573721540025521 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ZValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="z", parent_name="isosurface.slices", **kwargs): super(ZValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Z"), data_docs=kwargs.pop( "data_docs", """ fill Sets the fill ratio of the `slices`. The default fill value of the `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. locations Specifies the location(s) of slices on the axis. When not specified slices would be created for all points of the axis z except start and end. locationssrc Sets the source reference on plot.ly for locations . show Determines whether or not slice planes about the z dimension are drawn. """, ), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="y", parent_name="isosurface.slices", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Y"), data_docs=kwargs.pop( "data_docs", """ fill Sets the fill ratio of the `slices`. The default fill value of the `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. locations Specifies the location(s) of slices on the axis. When not specified slices would be created for all points of the axis y except start and end. locationssrc Sets the source reference on plot.ly for locations . show Determines whether or not slice planes about the y dimension are drawn. """, ), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="x", parent_name="isosurface.slices", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "X"), data_docs=kwargs.pop( "data_docs", """ fill Sets the fill ratio of the `slices`. The default fill value of the `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. locations Specifies the location(s) of slices on the axis. When not specified slices would be created for all points of the axis x except start and end. locationssrc Sets the source reference on plot.ly for locations . show Determines whether or not slice planes about the x dimension are drawn. """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/isosurface/surface/0000755000175000017500000000000013573746614023557 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/isosurface/surface/__init__.py0000644000175000017500000000400713573721540025660 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ShowValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="show", parent_name="isosurface.surface", **kwargs): super(ShowValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class PatternValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__( self, plotly_name="pattern", parent_name="isosurface.surface", **kwargs ): super(PatternValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), extras=kwargs.pop("extras", ["all", "odd", "even"]), flags=kwargs.pop("flags", ["A", "B", "C", "D", "E"]), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FillValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="fill", parent_name="isosurface.surface", **kwargs): super(FillValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class CountValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="count", parent_name="isosurface.surface", **kwargs): super(CountValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/isosurface/stream/0000755000175000017500000000000013573746614023422 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/isosurface/stream/__init__.py0000644000175000017500000000211013573721540025514 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TokenValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="token", parent_name="isosurface.stream", **kwargs): super(TokenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "info"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class MaxpointsValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="maxpoints", parent_name="isosurface.stream", **kwargs ): super(MaxpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 10000), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/isosurface/__init__.py0000644000175000017500000011770513573721541024243 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ZsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="zsrc", parent_name="isosurface", **kwargs): super(ZsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="z", parent_name="isosurface", **kwargs): super(ZValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class YsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="ysrc", parent_name="isosurface", **kwargs): super(YsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="y", parent_name="isosurface", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class XsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="xsrc", parent_name="isosurface", **kwargs): super(XsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="x", parent_name="isosurface", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="visible", parent_name="isosurface", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "legendonly"]), **kwargs ) import _plotly_utils.basevalidators class ValuesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="valuesrc", parent_name="isosurface", **kwargs): super(ValuesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="value", parent_name="isosurface", **kwargs): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="isosurface", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UidValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="uid", parent_name="isosurface", **kwargs): super(UidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="textsrc", parent_name="isosurface", **kwargs): super(TextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="text", parent_name="isosurface", **kwargs): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SurfaceValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="surface", parent_name="isosurface", **kwargs): super(SurfaceValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Surface"), data_docs=kwargs.pop( "data_docs", """ count Sets the number of iso-surfaces between minimum and maximum iso-values. By default this value is 2 meaning that only minimum and maximum surfaces would be drawn. fill Sets the fill ratio of the iso-surface. The default fill value of the surface is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. pattern Sets the surface pattern of the iso-surface 3-D sections. The default pattern of the surface is `all` meaning that the rest of surface elements would be shaded. The check options (either 1 or 2) could be used to draw half of the squares on the surface. Using various combinations of capital `A`, `B`, `C`, `D` and `E` may also be used to reduce the number of triangles on the iso-surfaces and creating other patterns of interest. show Hides/displays surfaces between minimum and maximum iso-values. """, ), **kwargs ) import _plotly_utils.basevalidators class StreamValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="stream", parent_name="isosurface", **kwargs): super(StreamValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Stream"), data_docs=kwargs.pop( "data_docs", """ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """, ), **kwargs ) import _plotly_utils.basevalidators class SpaceframeValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="spaceframe", parent_name="isosurface", **kwargs): super(SpaceframeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Spaceframe"), data_docs=kwargs.pop( "data_docs", """ fill Sets the fill ratio of the `spaceframe` elements. The default fill value is 0.15 meaning that only 15% of the area of every faces of tetras would be shaded. Applying a greater `fill` ratio would allow the creation of stronger elements or could be sued to have entirely closed areas (in case of using 1). show Displays/hides tetrahedron shapes between minimum and maximum iso-values. Often useful when either caps or surfaces are disabled or filled with values less than 1. """, ), **kwargs ) import _plotly_utils.basevalidators class SlicesValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="slices", parent_name="isosurface", **kwargs): super(SlicesValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Slices"), data_docs=kwargs.pop( "data_docs", """ x plotly.graph_objects.isosurface.slices.X instance or dict with compatible properties y plotly.graph_objects.isosurface.slices.Y instance or dict with compatible properties z plotly.graph_objects.isosurface.slices.Z instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class ShowscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showscale", parent_name="isosurface", **kwargs): super(ShowscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SceneValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="scene", parent_name="isosurface", **kwargs): super(SceneValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "scene"), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ReversescaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="reversescale", parent_name="isosurface", **kwargs): super(ReversescaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="isosurface", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="isosurface", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="metasrc", parent_name="isosurface", **kwargs): super(MetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetaValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="meta", parent_name="isosurface", **kwargs): super(MetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LightpositionValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="lightposition", parent_name="isosurface", **kwargs): super(LightpositionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Lightposition"), data_docs=kwargs.pop( "data_docs", """ x Numeric vector, representing the X coordinate for each vertex. y Numeric vector, representing the Y coordinate for each vertex. z Numeric vector, representing the Z coordinate for each vertex. """, ), **kwargs ) import _plotly_utils.basevalidators class LightingValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="lighting", parent_name="isosurface", **kwargs): super(LightingValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Lighting"), data_docs=kwargs.pop( "data_docs", """ ambient Ambient light increases overall color visibility but can wash out the image. diffuse Represents the extent that incident rays are reflected in a range of angles. facenormalsepsilon Epsilon for face normals calculation avoids math issues arising from degenerate geometry. fresnel Represents the reflectance as a dependency of the viewing angle; e.g. paper is reflective when viewing it from the edge of the paper (almost 90 degrees), causing shine. roughness Alters specular reflection; the rougher the surface, the wider and less contrasty the shine. specular Represents the level that incident rays are reflected in a single direction, causing shine. vertexnormalsepsilon Epsilon for vertex normals calculation avoids math issues arising from degenerate geometry. """, ), **kwargs ) import _plotly_utils.basevalidators class IsominValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="isomin", parent_name="isosurface", **kwargs): super(IsominValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IsomaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="isomax", parent_name="isosurface", **kwargs): super(IsomaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="idssrc", parent_name="isosurface", **kwargs): super(IdssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ids", parent_name="isosurface", **kwargs): super(IdsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class HovertextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hovertextsrc", parent_name="isosurface", **kwargs): super(HovertextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertext", parent_name="isosurface", **kwargs): super(HovertextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="hovertemplatesrc", parent_name="isosurface", **kwargs ): super(HovertemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertemplate", parent_name="isosurface", **kwargs): super(HovertemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverlabelValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="hoverlabel", parent_name="isosurface", **kwargs): super(HoverlabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Hoverlabel"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """, ), **kwargs ) import _plotly_utils.basevalidators class HoverinfosrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hoverinfosrc", parent_name="isosurface", **kwargs): super(HoverinfosrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverinfoValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="hoverinfo", parent_name="isosurface", **kwargs): super(HoverinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), extras=kwargs.pop("extras", ["all", "none", "skip"]), flags=kwargs.pop("flags", ["x", "y", "z", "text", "name"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FlatshadingValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="flatshading", parent_name="isosurface", **kwargs): super(FlatshadingValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class CustomdatasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="customdatasrc", parent_name="isosurface", **kwargs): super(CustomdatasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdataValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="customdata", parent_name="isosurface", **kwargs): super(CustomdataValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class ContourValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="contour", parent_name="isosurface", **kwargs): super(ContourValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Contour"), data_docs=kwargs.pop( "data_docs", """ color Sets the color of the contour lines. show Sets whether or not dynamic contours are shown on hover width Sets the width of the contour lines. """, ), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__(self, plotly_name="colorscale", parent_name="isosurface", **kwargs): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"autocolorscale": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorBarValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="colorbar", parent_name="isosurface", **kwargs): super(ColorBarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "ColorBar"), data_docs=kwargs.pop( "data_docs", """ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.isosurface.colo rbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.isosurface.colorbar.tickformatstopdefaults), sets the default property values to use for elements of isosurface.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.isosurface.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use isosurface.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use isosurface.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """, ), **kwargs ) import _plotly_utils.basevalidators class ColoraxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="coloraxis", parent_name="isosurface", **kwargs): super(ColoraxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", None), edit_type=kwargs.pop("edit_type", "calc"), regex=kwargs.pop("regex", "/^coloraxis([2-9]|[1-9][0-9]+)?$/"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmin", parent_name="isosurface", **kwargs): super(CminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmidValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmid", parent_name="isosurface", **kwargs): super(CmidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmax", parent_name="isosurface", **kwargs): super(CmaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CautoValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="cauto", parent_name="isosurface", **kwargs): super(CautoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CapsValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="caps", parent_name="isosurface", **kwargs): super(CapsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Caps"), data_docs=kwargs.pop( "data_docs", """ x plotly.graph_objects.isosurface.caps.X instance or dict with compatible properties y plotly.graph_objects.isosurface.caps.Y instance or dict with compatible properties z plotly.graph_objects.isosurface.caps.Z instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class AutocolorscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="autocolorscale", parent_name="isosurface", **kwargs ): super(AutocolorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/isosurface/lighting/0000755000175000017500000000000013573746614023734 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/isosurface/lighting/__init__.py0000644000175000017500000000755513573721540026050 0ustar noahfxnoahfximport _plotly_utils.basevalidators class VertexnormalsepsilonValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="vertexnormalsepsilon", parent_name="isosurface.lighting", **kwargs ): super(VertexnormalsepsilonValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SpecularValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="specular", parent_name="isosurface.lighting", **kwargs ): super(SpecularValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 2), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class RoughnessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="roughness", parent_name="isosurface.lighting", **kwargs ): super(RoughnessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FresnelValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="fresnel", parent_name="isosurface.lighting", **kwargs ): super(FresnelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 5), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FacenormalsepsilonValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="facenormalsepsilon", parent_name="isosurface.lighting", **kwargs ): super(FacenormalsepsilonValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class DiffuseValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="diffuse", parent_name="isosurface.lighting", **kwargs ): super(DiffuseValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AmbientValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ambient", parent_name="isosurface.lighting", **kwargs ): super(AmbientValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/isosurface/spaceframe/0000755000175000017500000000000013573746614024235 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/isosurface/spaceframe/__init__.py0000644000175000017500000000175013573721540026340 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ShowValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="show", parent_name="isosurface.spaceframe", **kwargs ): super(ShowValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FillValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="fill", parent_name="isosurface.spaceframe", **kwargs ): super(FillValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/mesh3d/0000755000175000017500000000000013573746614021147 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/mesh3d/contour/0000755000175000017500000000000013573746614022640 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/mesh3d/contour/__init__.py0000644000175000017500000000257613573721541024753 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="mesh3d.contour", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 16), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="show", parent_name="mesh3d.contour", **kwargs): super(ShowValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="mesh3d.contour", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/mesh3d/hoverlabel/0000755000175000017500000000000013573746614023272 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/mesh3d/hoverlabel/__init__.py0000644000175000017500000001337213573721541025401 0ustar noahfxnoahfximport _plotly_utils.basevalidators class NamelengthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="namelengthsrc", parent_name="mesh3d.hoverlabel", **kwargs ): super(NamelengthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NamelengthValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="namelength", parent_name="mesh3d.hoverlabel", **kwargs ): super(NamelengthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", -1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="font", parent_name="mesh3d.hoverlabel", **kwargs): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class BordercolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bordercolorsrc", parent_name="mesh3d.hoverlabel", **kwargs ): super(BordercolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="mesh3d.hoverlabel", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bgcolorsrc", parent_name="mesh3d.hoverlabel", **kwargs ): super(BgcolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="mesh3d.hoverlabel", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AlignsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="alignsrc", parent_name="mesh3d.hoverlabel", **kwargs ): super(AlignsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="align", parent_name="mesh3d.hoverlabel", **kwargs): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "right", "auto"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/mesh3d/hoverlabel/font/0000755000175000017500000000000013573746614024240 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/mesh3d/hoverlabel/font/__init__.py0000644000175000017500000000603713573721541026347 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="mesh3d.hoverlabel.font", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="mesh3d.hoverlabel.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="mesh3d.hoverlabel.font", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="mesh3d.hoverlabel.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="mesh3d.hoverlabel.font", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="mesh3d.hoverlabel.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/mesh3d/colorbar/0000755000175000017500000000000013573746614022752 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/mesh3d/colorbar/tickformatstop/0000755000175000017500000000000013573746614026023 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/mesh3d/colorbar/tickformatstop/__init__.py0000644000175000017500000000533713573721541030134 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="value", parent_name="mesh3d.colorbar.tickformatstop", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="mesh3d.colorbar.tickformatstop", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="mesh3d.colorbar.tickformatstop", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EnabledValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="enabled", parent_name="mesh3d.colorbar.tickformatstop", **kwargs ): super(EnabledValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DtickrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="dtickrange", parent_name="mesh3d.colorbar.tickformatstop", **kwargs ): super(DtickrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "colorbars"}, {"valType": "any", "editType": "colorbars"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/mesh3d/colorbar/title/0000755000175000017500000000000013573746614024073 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/mesh3d/colorbar/title/__init__.py0000644000175000017500000000471213573721541026200 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="text", parent_name="mesh3d.colorbar.title", **kwargs ): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SideValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="side", parent_name="mesh3d.colorbar.title", **kwargs ): super(SideValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["right", "top", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="mesh3d.colorbar.title", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/mesh3d/colorbar/title/font/0000755000175000017500000000000013573746614025041 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/mesh3d/colorbar/title/font/__init__.py0000644000175000017500000000303113573721541027137 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="mesh3d.colorbar.title.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="mesh3d.colorbar.title.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="mesh3d.colorbar.title.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/mesh3d/colorbar/__init__.py0000644000175000017500000005757613573721542025100 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="ypad", parent_name="mesh3d.colorbar", **kwargs): super(YpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class YanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="yanchor", parent_name="mesh3d.colorbar", **kwargs): super(YanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["top", "middle", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="y", parent_name="mesh3d.colorbar", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="xpad", parent_name="mesh3d.colorbar", **kwargs): super(XpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="xanchor", parent_name="mesh3d.colorbar", **kwargs): super(XanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "center", "right"]), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="x", parent_name="mesh3d.colorbar", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TitleValidator(_plotly_utils.basevalidators.TitleValidator): def __init__(self, plotly_name="title", parent_name="mesh3d.colorbar", **kwargs): super(TitleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Title"), data_docs=kwargs.pop( "data_docs", """ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """, ), **kwargs ) import _plotly_utils.basevalidators class TickwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="tickwidth", parent_name="mesh3d.colorbar", **kwargs ): super(TickwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickvalssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="tickvalssrc", parent_name="mesh3d.colorbar", **kwargs ): super(TickvalssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickvalsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="tickvals", parent_name="mesh3d.colorbar", **kwargs): super(TickvalsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="ticktextsrc", parent_name="mesh3d.colorbar", **kwargs ): super(TicktextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicktextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ticktext", parent_name="mesh3d.colorbar", **kwargs): super(TicktextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="ticksuffix", parent_name="mesh3d.colorbar", **kwargs ): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TicksValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="ticks", parent_name="mesh3d.colorbar", **kwargs): super(TicksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["outside", "inside", ""]), **kwargs ) import _plotly_utils.basevalidators class TickprefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickprefix", parent_name="mesh3d.colorbar", **kwargs ): super(TickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="tickmode", parent_name="mesh3d.colorbar", **kwargs): super(TickmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "linear", "array"]), **kwargs ) import _plotly_utils.basevalidators class TicklenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="ticklen", parent_name="mesh3d.colorbar", **kwargs): super(TicklenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickformatstopValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickformatstopdefaults", parent_name="mesh3d.colorbar", **kwargs ): super(TickformatstopValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatstopsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="tickformatstops", parent_name="mesh3d.colorbar", **kwargs ): super(TickformatstopsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickformat", parent_name="mesh3d.colorbar", **kwargs ): super(TickformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="tickfont", parent_name="mesh3d.colorbar", **kwargs): super(TickfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class TickcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="tickcolor", parent_name="mesh3d.colorbar", **kwargs ): super(TickcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__( self, plotly_name="tickangle", parent_name="mesh3d.colorbar", **kwargs ): super(TickangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="tick0", parent_name="mesh3d.colorbar", **kwargs): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ThicknessmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="thicknessmode", parent_name="mesh3d.colorbar", **kwargs ): super(ThicknessmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="thickness", parent_name="mesh3d.colorbar", **kwargs ): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowticksuffixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showticksuffix", parent_name="mesh3d.colorbar", **kwargs ): super(ShowticksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowtickprefixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showtickprefix", parent_name="mesh3d.colorbar", **kwargs ): super(ShowtickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowticklabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showticklabels", parent_name="mesh3d.colorbar", **kwargs ): super(ShowticklabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowexponentValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showexponent", parent_name="mesh3d.colorbar", **kwargs ): super(ShowexponentValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class SeparatethousandsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="separatethousands", parent_name="mesh3d.colorbar", **kwargs ): super(SeparatethousandsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="outlinewidth", parent_name="mesh3d.colorbar", **kwargs ): super(OutlinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="outlinecolor", parent_name="mesh3d.colorbar", **kwargs ): super(OutlinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NticksValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="nticks", parent_name="mesh3d.colorbar", **kwargs): super(NticksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LenmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="lenmode", parent_name="mesh3d.colorbar", **kwargs): super(LenmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class LenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="len", parent_name="mesh3d.colorbar", **kwargs): super(LenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ExponentformatValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="exponentformat", parent_name="mesh3d.colorbar", **kwargs ): super(ExponentformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "e", "E", "power", "SI", "B"]), **kwargs ) import _plotly_utils.basevalidators class DtickValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="dtick", parent_name="mesh3d.colorbar", **kwargs): super(DtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BorderwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="borderwidth", parent_name="mesh3d.colorbar", **kwargs ): super(BorderwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="mesh3d.colorbar", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="bgcolor", parent_name="mesh3d.colorbar", **kwargs): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/mesh3d/colorbar/tickfont/0000755000175000017500000000000013573746614024573 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/mesh3d/colorbar/tickfont/__init__.py0000644000175000017500000000302313573721541026672 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="mesh3d.colorbar.tickfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="mesh3d.colorbar.tickfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="mesh3d.colorbar.tickfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/mesh3d/lightposition/0000755000175000017500000000000013573746614024043 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/mesh3d/lightposition/__init__.py0000644000175000017500000000305013573721541026142 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ZValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="z", parent_name="mesh3d.lightposition", **kwargs): super(ZValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 100000), min=kwargs.pop("min", -100000), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="y", parent_name="mesh3d.lightposition", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 100000), min=kwargs.pop("min", -100000), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="x", parent_name="mesh3d.lightposition", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 100000), min=kwargs.pop("min", -100000), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/mesh3d/stream/0000755000175000017500000000000013573746614022442 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/mesh3d/stream/__init__.py0000644000175000017500000000206213573721541024543 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TokenValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="token", parent_name="mesh3d.stream", **kwargs): super(TokenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "info"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class MaxpointsValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="maxpoints", parent_name="mesh3d.stream", **kwargs): super(MaxpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 10000), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/mesh3d/__init__.py0000644000175000017500000012573413573721542023265 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ZsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="zsrc", parent_name="mesh3d", **kwargs): super(ZsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZcalendarValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="zcalendar", parent_name="mesh3d", **kwargs): super(ZcalendarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "gregorian", "chinese", "coptic", "discworld", "ethiopian", "hebrew", "islamic", "julian", "mayan", "nanakshahi", "nepali", "persian", "jalali", "taiwan", "thai", "ummalqura", ], ), **kwargs ) import _plotly_utils.basevalidators class ZValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="z", parent_name="mesh3d", **kwargs): super(ZValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class YsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="ysrc", parent_name="mesh3d", **kwargs): super(YsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YcalendarValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="ycalendar", parent_name="mesh3d", **kwargs): super(YcalendarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "gregorian", "chinese", "coptic", "discworld", "ethiopian", "hebrew", "islamic", "julian", "mayan", "nanakshahi", "nepali", "persian", "jalali", "taiwan", "thai", "ummalqura", ], ), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="y", parent_name="mesh3d", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class XsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="xsrc", parent_name="mesh3d", **kwargs): super(XsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XcalendarValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="xcalendar", parent_name="mesh3d", **kwargs): super(XcalendarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "gregorian", "chinese", "coptic", "discworld", "ethiopian", "hebrew", "islamic", "julian", "mayan", "nanakshahi", "nepali", "persian", "jalali", "taiwan", "thai", "ummalqura", ], ), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="x", parent_name="mesh3d", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="visible", parent_name="mesh3d", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "legendonly"]), **kwargs ) import _plotly_utils.basevalidators class VertexcolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="vertexcolorsrc", parent_name="mesh3d", **kwargs): super(VertexcolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class VertexcolorValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="vertexcolor", parent_name="mesh3d", **kwargs): super(VertexcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="mesh3d", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UidValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="uid", parent_name="mesh3d", **kwargs): super(UidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="textsrc", parent_name="mesh3d", **kwargs): super(TextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="text", parent_name="mesh3d", **kwargs): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class StreamValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="stream", parent_name="mesh3d", **kwargs): super(StreamValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Stream"), data_docs=kwargs.pop( "data_docs", """ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """, ), **kwargs ) import _plotly_utils.basevalidators class ShowscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showscale", parent_name="mesh3d", **kwargs): super(ShowscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SceneValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="scene", parent_name="mesh3d", **kwargs): super(SceneValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "scene"), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ReversescaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="reversescale", parent_name="mesh3d", **kwargs): super(ReversescaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="mesh3d", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="mesh3d", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="metasrc", parent_name="mesh3d", **kwargs): super(MetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetaValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="meta", parent_name="mesh3d", **kwargs): super(MetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LightpositionValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="lightposition", parent_name="mesh3d", **kwargs): super(LightpositionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Lightposition"), data_docs=kwargs.pop( "data_docs", """ x Numeric vector, representing the X coordinate for each vertex. y Numeric vector, representing the Y coordinate for each vertex. z Numeric vector, representing the Z coordinate for each vertex. """, ), **kwargs ) import _plotly_utils.basevalidators class LightingValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="lighting", parent_name="mesh3d", **kwargs): super(LightingValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Lighting"), data_docs=kwargs.pop( "data_docs", """ ambient Ambient light increases overall color visibility but can wash out the image. diffuse Represents the extent that incident rays are reflected in a range of angles. facenormalsepsilon Epsilon for face normals calculation avoids math issues arising from degenerate geometry. fresnel Represents the reflectance as a dependency of the viewing angle; e.g. paper is reflective when viewing it from the edge of the paper (almost 90 degrees), causing shine. roughness Alters specular reflection; the rougher the surface, the wider and less contrasty the shine. specular Represents the level that incident rays are reflected in a single direction, causing shine. vertexnormalsepsilon Epsilon for vertex normals calculation avoids math issues arising from degenerate geometry. """, ), **kwargs ) import _plotly_utils.basevalidators class KsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="ksrc", parent_name="mesh3d", **kwargs): super(KsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class KValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="k", parent_name="mesh3d", **kwargs): super(KValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class JsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="jsrc", parent_name="mesh3d", **kwargs): super(JsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class JValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="j", parent_name="mesh3d", **kwargs): super(JValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class IsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="isrc", parent_name="mesh3d", **kwargs): super(IsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IntensitysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="intensitysrc", parent_name="mesh3d", **kwargs): super(IntensitysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IntensityValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="intensity", parent_name="mesh3d", **kwargs): super(IntensityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class IdssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="idssrc", parent_name="mesh3d", **kwargs): super(IdssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ids", parent_name="mesh3d", **kwargs): super(IdsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class IValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="i", parent_name="mesh3d", **kwargs): super(IValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class HovertextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hovertextsrc", parent_name="mesh3d", **kwargs): super(HovertextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertext", parent_name="mesh3d", **kwargs): super(HovertextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hovertemplatesrc", parent_name="mesh3d", **kwargs): super(HovertemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertemplate", parent_name="mesh3d", **kwargs): super(HovertemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverlabelValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="hoverlabel", parent_name="mesh3d", **kwargs): super(HoverlabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Hoverlabel"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """, ), **kwargs ) import _plotly_utils.basevalidators class HoverinfosrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hoverinfosrc", parent_name="mesh3d", **kwargs): super(HoverinfosrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverinfoValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="hoverinfo", parent_name="mesh3d", **kwargs): super(HoverinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), extras=kwargs.pop("extras", ["all", "none", "skip"]), flags=kwargs.pop("flags", ["x", "y", "z", "text", "name"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FlatshadingValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="flatshading", parent_name="mesh3d", **kwargs): super(FlatshadingValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FacecolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="facecolorsrc", parent_name="mesh3d", **kwargs): super(FacecolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FacecolorValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="facecolor", parent_name="mesh3d", **kwargs): super(FacecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class DelaunayaxisValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="delaunayaxis", parent_name="mesh3d", **kwargs): super(DelaunayaxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["x", "y", "z"]), **kwargs ) import _plotly_utils.basevalidators class CustomdatasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="customdatasrc", parent_name="mesh3d", **kwargs): super(CustomdatasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdataValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="customdata", parent_name="mesh3d", **kwargs): super(CustomdataValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class ContourValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="contour", parent_name="mesh3d", **kwargs): super(ContourValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Contour"), data_docs=kwargs.pop( "data_docs", """ color Sets the color of the contour lines. show Sets whether or not dynamic contours are shown on hover width Sets the width of the contour lines. """, ), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__(self, plotly_name="colorscale", parent_name="mesh3d", **kwargs): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"autocolorscale": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorBarValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="colorbar", parent_name="mesh3d", **kwargs): super(ColorBarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "ColorBar"), data_docs=kwargs.pop( "data_docs", """ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.mesh3d.colorbar .Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.mesh3d.colorbar.tickformatstopdefaults), sets the default property values to use for elements of mesh3d.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.mesh3d.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use mesh3d.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use mesh3d.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """, ), **kwargs ) import _plotly_utils.basevalidators class ColoraxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="coloraxis", parent_name="mesh3d", **kwargs): super(ColoraxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", None), edit_type=kwargs.pop("edit_type", "calc"), regex=kwargs.pop("regex", "/^coloraxis([2-9]|[1-9][0-9]+)?$/"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="mesh3d", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), colorscale_path=kwargs.pop("colorscale_path", "mesh3d.colorscale"), **kwargs ) import _plotly_utils.basevalidators class CminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmin", parent_name="mesh3d", **kwargs): super(CminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmidValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmid", parent_name="mesh3d", **kwargs): super(CmidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmax", parent_name="mesh3d", **kwargs): super(CmaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CautoValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="cauto", parent_name="mesh3d", **kwargs): super(CautoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AutocolorscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="autocolorscale", parent_name="mesh3d", **kwargs): super(AutocolorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AlphahullValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="alphahull", parent_name="mesh3d", **kwargs): super(AlphahullValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/mesh3d/lighting/0000755000175000017500000000000013573746614022754 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/mesh3d/lighting/__init__.py0000644000175000017500000000740113573721541025057 0ustar noahfxnoahfximport _plotly_utils.basevalidators class VertexnormalsepsilonValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="vertexnormalsepsilon", parent_name="mesh3d.lighting", **kwargs ): super(VertexnormalsepsilonValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SpecularValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="specular", parent_name="mesh3d.lighting", **kwargs): super(SpecularValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 2), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class RoughnessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="roughness", parent_name="mesh3d.lighting", **kwargs ): super(RoughnessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FresnelValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="fresnel", parent_name="mesh3d.lighting", **kwargs): super(FresnelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 5), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FacenormalsepsilonValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="facenormalsepsilon", parent_name="mesh3d.lighting", **kwargs ): super(FacenormalsepsilonValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class DiffuseValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="diffuse", parent_name="mesh3d.lighting", **kwargs): super(DiffuseValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AmbientValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="ambient", parent_name="mesh3d.lighting", **kwargs): super(AmbientValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/0000755000175000017500000000000013573746614021301 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/margin/0000755000175000017500000000000013573746614022556 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/margin/__init__.py0000644000175000017500000000537013573721540024663 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="t", parent_name="layout.margin", **kwargs): super(TValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class RValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="r", parent_name="layout.margin", **kwargs): super(RValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class PadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="pad", parent_name="layout.margin", **kwargs): super(PadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="l", parent_name="layout.margin", **kwargs): super(LValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="b", parent_name="layout.margin", **kwargs): super(BValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AutoexpandValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="autoexpand", parent_name="layout.margin", **kwargs): super(AutoexpandValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/template/0000755000175000017500000000000013573746614023114 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/template/__init__.py0000644000175000017500000001701413573721540025217 0ustar noahfxnoahfximport _plotly_utils.basevalidators class LayoutValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="layout", parent_name="layout.template", **kwargs): super(LayoutValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Layout"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class DataValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="data", parent_name="layout.template", **kwargs): super(DataValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Data"), data_docs=kwargs.pop( "data_docs", """ area A tuple of plotly.graph_objects.Area instances or dicts with compatible properties barpolar A tuple of plotly.graph_objects.Barpolar instances or dicts with compatible properties bar A tuple of plotly.graph_objects.Bar instances or dicts with compatible properties box A tuple of plotly.graph_objects.Box instances or dicts with compatible properties candlestick A tuple of plotly.graph_objects.Candlestick instances or dicts with compatible properties carpet A tuple of plotly.graph_objects.Carpet instances or dicts with compatible properties choroplethmapbox A tuple of plotly.graph_objects.Choroplethmapbox instances or dicts with compatible properties choropleth A tuple of plotly.graph_objects.Choropleth instances or dicts with compatible properties cone A tuple of plotly.graph_objects.Cone instances or dicts with compatible properties contourcarpet A tuple of plotly.graph_objects.Contourcarpet instances or dicts with compatible properties contour A tuple of plotly.graph_objects.Contour instances or dicts with compatible properties densitymapbox A tuple of plotly.graph_objects.Densitymapbox instances or dicts with compatible properties funnelarea A tuple of plotly.graph_objects.Funnelarea instances or dicts with compatible properties funnel A tuple of plotly.graph_objects.Funnel instances or dicts with compatible properties heatmapgl A tuple of plotly.graph_objects.Heatmapgl instances or dicts with compatible properties heatmap A tuple of plotly.graph_objects.Heatmap instances or dicts with compatible properties histogram2dcontour A tuple of plotly.graph_objects.Histogram2dContour instances or dicts with compatible properties histogram2d A tuple of plotly.graph_objects.Histogram2d instances or dicts with compatible properties histogram A tuple of plotly.graph_objects.Histogram instances or dicts with compatible properties image A tuple of plotly.graph_objects.Image instances or dicts with compatible properties indicator A tuple of plotly.graph_objects.Indicator instances or dicts with compatible properties isosurface A tuple of plotly.graph_objects.Isosurface instances or dicts with compatible properties mesh3d A tuple of plotly.graph_objects.Mesh3d instances or dicts with compatible properties ohlc A tuple of plotly.graph_objects.Ohlc instances or dicts with compatible properties parcats A tuple of plotly.graph_objects.Parcats instances or dicts with compatible properties parcoords A tuple of plotly.graph_objects.Parcoords instances or dicts with compatible properties pie A tuple of plotly.graph_objects.Pie instances or dicts with compatible properties pointcloud A tuple of plotly.graph_objects.Pointcloud instances or dicts with compatible properties sankey A tuple of plotly.graph_objects.Sankey instances or dicts with compatible properties scatter3d A tuple of plotly.graph_objects.Scatter3d instances or dicts with compatible properties scattercarpet A tuple of plotly.graph_objects.Scattercarpet instances or dicts with compatible properties scattergeo A tuple of plotly.graph_objects.Scattergeo instances or dicts with compatible properties scattergl A tuple of plotly.graph_objects.Scattergl instances or dicts with compatible properties scattermapbox A tuple of plotly.graph_objects.Scattermapbox instances or dicts with compatible properties scatterpolargl A tuple of plotly.graph_objects.Scatterpolargl instances or dicts with compatible properties scatterpolar A tuple of plotly.graph_objects.Scatterpolar instances or dicts with compatible properties scatter A tuple of plotly.graph_objects.Scatter instances or dicts with compatible properties scatterternary A tuple of plotly.graph_objects.Scatterternary instances or dicts with compatible properties splom A tuple of plotly.graph_objects.Splom instances or dicts with compatible properties streamtube A tuple of plotly.graph_objects.Streamtube instances or dicts with compatible properties sunburst A tuple of plotly.graph_objects.Sunburst instances or dicts with compatible properties surface A tuple of plotly.graph_objects.Surface instances or dicts with compatible properties table A tuple of plotly.graph_objects.Table instances or dicts with compatible properties treemap A tuple of plotly.graph_objects.Treemap instances or dicts with compatible properties violin A tuple of plotly.graph_objects.Violin instances or dicts with compatible properties volume A tuple of plotly.graph_objects.Volume instances or dicts with compatible properties waterfall A tuple of plotly.graph_objects.Waterfall instances or dicts with compatible properties """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/template/data/0000755000175000017500000000000013573746614024025 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/template/data/__init__.py0000644000175000017500000006303613573721541026136 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WaterfallsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="waterfall", parent_name="layout.template.data", **kwargs ): super(WaterfallsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Waterfall"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class VolumesValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="volume", parent_name="layout.template.data", **kwargs ): super(VolumesValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Volume"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class ViolinsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="violin", parent_name="layout.template.data", **kwargs ): super(ViolinsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Violin"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class TreemapsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="treemap", parent_name="layout.template.data", **kwargs ): super(TreemapsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Treemap"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class TablesValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="table", parent_name="layout.template.data", **kwargs ): super(TablesValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Table"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class SurfacesValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="surface", parent_name="layout.template.data", **kwargs ): super(SurfacesValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Surface"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class SunburstsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="sunburst", parent_name="layout.template.data", **kwargs ): super(SunburstsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Sunburst"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class StreamtubesValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="streamtube", parent_name="layout.template.data", **kwargs ): super(StreamtubesValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Streamtube"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class SplomsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="splom", parent_name="layout.template.data", **kwargs ): super(SplomsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Splom"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class ScatterternarysValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="scatterternary", parent_name="layout.template.data", **kwargs ): super(ScatterternarysValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Scatterternary"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class ScattersValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="scatter", parent_name="layout.template.data", **kwargs ): super(ScattersValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Scatter"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class ScatterpolarsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="scatterpolar", parent_name="layout.template.data", **kwargs ): super(ScatterpolarsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Scatterpolar"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class ScatterpolarglsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="scatterpolargl", parent_name="layout.template.data", **kwargs ): super(ScatterpolarglsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Scatterpolargl"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class ScattermapboxsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="scattermapbox", parent_name="layout.template.data", **kwargs ): super(ScattermapboxsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Scattermapbox"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class ScatterglsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="scattergl", parent_name="layout.template.data", **kwargs ): super(ScatterglsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Scattergl"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class ScattergeosValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="scattergeo", parent_name="layout.template.data", **kwargs ): super(ScattergeosValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Scattergeo"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class ScattercarpetsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="scattercarpet", parent_name="layout.template.data", **kwargs ): super(ScattercarpetsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Scattercarpet"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class Scatter3dsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="scatter3d", parent_name="layout.template.data", **kwargs ): super(Scatter3dsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Scatter3d"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class SankeysValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="sankey", parent_name="layout.template.data", **kwargs ): super(SankeysValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Sankey"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class PointcloudsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="pointcloud", parent_name="layout.template.data", **kwargs ): super(PointcloudsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Pointcloud"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class PiesValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__(self, plotly_name="pie", parent_name="layout.template.data", **kwargs): super(PiesValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Pie"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class ParcoordssValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="parcoords", parent_name="layout.template.data", **kwargs ): super(ParcoordssValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Parcoords"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class ParcatssValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="parcats", parent_name="layout.template.data", **kwargs ): super(ParcatssValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Parcats"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class OhlcsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="ohlc", parent_name="layout.template.data", **kwargs ): super(OhlcsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Ohlc"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class Mesh3dsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="mesh3d", parent_name="layout.template.data", **kwargs ): super(Mesh3dsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Mesh3d"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class IsosurfacesValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="isosurface", parent_name="layout.template.data", **kwargs ): super(IsosurfacesValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Isosurface"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class IndicatorsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="indicator", parent_name="layout.template.data", **kwargs ): super(IndicatorsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Indicator"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class ImagesValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="image", parent_name="layout.template.data", **kwargs ): super(ImagesValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Image"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class HistogramsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="histogram", parent_name="layout.template.data", **kwargs ): super(HistogramsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Histogram"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class Histogram2dsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="histogram2d", parent_name="layout.template.data", **kwargs ): super(Histogram2dsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Histogram2d"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class Histogram2dContoursValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="histogram2dcontour", parent_name="layout.template.data", **kwargs ): super(Histogram2dContoursValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Histogram2dContour"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class HeatmapsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="heatmap", parent_name="layout.template.data", **kwargs ): super(HeatmapsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Heatmap"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class HeatmapglsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="heatmapgl", parent_name="layout.template.data", **kwargs ): super(HeatmapglsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Heatmapgl"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class FunnelsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="funnel", parent_name="layout.template.data", **kwargs ): super(FunnelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Funnel"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class FunnelareasValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="funnelarea", parent_name="layout.template.data", **kwargs ): super(FunnelareasValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Funnelarea"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class DensitymapboxsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="densitymapbox", parent_name="layout.template.data", **kwargs ): super(DensitymapboxsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Densitymapbox"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class ContoursValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="contour", parent_name="layout.template.data", **kwargs ): super(ContoursValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Contour"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class ContourcarpetsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="contourcarpet", parent_name="layout.template.data", **kwargs ): super(ContourcarpetsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Contourcarpet"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class ConesValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="cone", parent_name="layout.template.data", **kwargs ): super(ConesValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Cone"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class ChoroplethsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="choropleth", parent_name="layout.template.data", **kwargs ): super(ChoroplethsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Choropleth"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class ChoroplethmapboxsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="choroplethmapbox", parent_name="layout.template.data", **kwargs ): super(ChoroplethmapboxsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Choroplethmapbox"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class CarpetsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="carpet", parent_name="layout.template.data", **kwargs ): super(CarpetsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Carpet"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class CandlesticksValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="candlestick", parent_name="layout.template.data", **kwargs ): super(CandlesticksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Candlestick"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class BoxsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__(self, plotly_name="box", parent_name="layout.template.data", **kwargs): super(BoxsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Box"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class BarsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__(self, plotly_name="bar", parent_name="layout.template.data", **kwargs): super(BarsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Bar"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class BarpolarsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="barpolar", parent_name="layout.template.data", **kwargs ): super(BarpolarsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Barpolar"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class AreasValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="area", parent_name="layout.template.data", **kwargs ): super(AreasValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Area"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/polar/0000755000175000017500000000000013573746614022416 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/polar/angularaxis/0000755000175000017500000000000013573746614024734 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/polar/angularaxis/tickformatstop/0000755000175000017500000000000013573746614030005 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/polar/angularaxis/tickformatstop/__init__.py0000644000175000017500000000540113573721540032105 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="value", parent_name="layout.polar.angularaxis.tickformatstop", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="layout.polar.angularaxis.tickformatstop", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="layout.polar.angularaxis.tickformatstop", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EnabledValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="enabled", parent_name="layout.polar.angularaxis.tickformatstop", **kwargs ): super(EnabledValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DtickrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="dtickrange", parent_name="layout.polar.angularaxis.tickformatstop", **kwargs ): super(DtickrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "plot"}, {"valType": "any", "editType": "plot"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/polar/angularaxis/__init__.py0000644000175000017500000006345213573721541027047 0ustar noahfxnoahfximport _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="visible", parent_name="layout.polar.angularaxis", **kwargs ): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="uirevision", parent_name="layout.polar.angularaxis", **kwargs ): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TypeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="type", parent_name="layout.polar.angularaxis", **kwargs ): super(TypeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["-", "linear", "category"]), **kwargs ) import _plotly_utils.basevalidators class TickwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="tickwidth", parent_name="layout.polar.angularaxis", **kwargs ): super(TickwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickvalssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="tickvalssrc", parent_name="layout.polar.angularaxis", **kwargs ): super(TickvalssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickvalsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="tickvals", parent_name="layout.polar.angularaxis", **kwargs ): super(TickvalsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="ticktextsrc", parent_name="layout.polar.angularaxis", **kwargs ): super(TicktextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicktextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="ticktext", parent_name="layout.polar.angularaxis", **kwargs ): super(TicktextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="ticksuffix", parent_name="layout.polar.angularaxis", **kwargs ): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TicksValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="ticks", parent_name="layout.polar.angularaxis", **kwargs ): super(TicksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["outside", "inside", ""]), **kwargs ) import _plotly_utils.basevalidators class TickprefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickprefix", parent_name="layout.polar.angularaxis", **kwargs ): super(TickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="tickmode", parent_name="layout.polar.angularaxis", **kwargs ): super(TickmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "linear", "array"]), **kwargs ) import _plotly_utils.basevalidators class TicklenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ticklen", parent_name="layout.polar.angularaxis", **kwargs ): super(TicklenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickformatstopValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickformatstopdefaults", parent_name="layout.polar.angularaxis", **kwargs ): super(TickformatstopValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatstopsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="tickformatstops", parent_name="layout.polar.angularaxis", **kwargs ): super(TickformatstopsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickformat", parent_name="layout.polar.angularaxis", **kwargs ): super(TickformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickfont", parent_name="layout.polar.angularaxis", **kwargs ): super(TickfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class TickcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="tickcolor", parent_name="layout.polar.angularaxis", **kwargs ): super(TickcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__( self, plotly_name="tickangle", parent_name="layout.polar.angularaxis", **kwargs ): super(TickangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="tick0", parent_name="layout.polar.angularaxis", **kwargs ): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ThetaunitValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="thetaunit", parent_name="layout.polar.angularaxis", **kwargs ): super(ThetaunitValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["radians", "degrees"]), **kwargs ) import _plotly_utils.basevalidators class ShowticksuffixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showticksuffix", parent_name="layout.polar.angularaxis", **kwargs ): super(ShowticksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowtickprefixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showtickprefix", parent_name="layout.polar.angularaxis", **kwargs ): super(ShowtickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowticklabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showticklabels", parent_name="layout.polar.angularaxis", **kwargs ): super(ShowticklabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowlineValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showline", parent_name="layout.polar.angularaxis", **kwargs ): super(ShowlineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowgridValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showgrid", parent_name="layout.polar.angularaxis", **kwargs ): super(ShowgridValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowexponentValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showexponent", parent_name="layout.polar.angularaxis", **kwargs ): super(ShowexponentValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class SeparatethousandsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="separatethousands", parent_name="layout.polar.angularaxis", **kwargs ): super(SeparatethousandsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class RotationValidator(_plotly_utils.basevalidators.AngleValidator): def __init__( self, plotly_name="rotation", parent_name="layout.polar.angularaxis", **kwargs ): super(RotationValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class PeriodValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="period", parent_name="layout.polar.angularaxis", **kwargs ): super(PeriodValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NticksValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="nticks", parent_name="layout.polar.angularaxis", **kwargs ): super(NticksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="linewidth", parent_name="layout.polar.angularaxis", **kwargs ): super(LinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="linecolor", parent_name="layout.polar.angularaxis", **kwargs ): super(LinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LayerValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="layer", parent_name="layout.polar.angularaxis", **kwargs ): super(LayerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["above traces", "below traces"]), **kwargs ) import _plotly_utils.basevalidators class HoverformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="hoverformat", parent_name="layout.polar.angularaxis", **kwargs ): super(HoverformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class GridwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="gridwidth", parent_name="layout.polar.angularaxis", **kwargs ): super(GridwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class GridcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="gridcolor", parent_name="layout.polar.angularaxis", **kwargs ): super(GridcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ExponentformatValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="exponentformat", parent_name="layout.polar.angularaxis", **kwargs ): super(ExponentformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "e", "E", "power", "SI", "B"]), **kwargs ) import _plotly_utils.basevalidators class DtickValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="dtick", parent_name="layout.polar.angularaxis", **kwargs ): super(DtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class DirectionValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="direction", parent_name="layout.polar.angularaxis", **kwargs ): super(DirectionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["counterclockwise", "clockwise"]), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="layout.polar.angularaxis", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class CategoryorderValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="categoryorder", parent_name="layout.polar.angularaxis", **kwargs ): super(CategoryorderValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "trace", "category ascending", "category descending", "array", "total ascending", "total descending", "min ascending", "min descending", "max ascending", "max descending", "sum ascending", "sum descending", "mean ascending", "mean descending", "median ascending", "median descending", ], ), **kwargs ) import _plotly_utils.basevalidators class CategoryarraysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="categoryarraysrc", parent_name="layout.polar.angularaxis", **kwargs ): super(CategoryarraysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CategoryarrayValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="categoryarray", parent_name="layout.polar.angularaxis", **kwargs ): super(CategoryarrayValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/polar/angularaxis/tickfont/0000755000175000017500000000000013573746614026555 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/polar/angularaxis/tickfont/__init__.py0000644000175000017500000000314713573721540030662 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="layout.polar.angularaxis.tickfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="layout.polar.angularaxis.tickfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="layout.polar.angularaxis.tickfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/polar/radialaxis/0000755000175000017500000000000013573746614024537 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/polar/radialaxis/tickformatstop/0000755000175000017500000000000013573746614027610 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/polar/radialaxis/tickformatstop/__init__.py0000644000175000017500000000537413573721540031721 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="value", parent_name="layout.polar.radialaxis.tickformatstop", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="layout.polar.radialaxis.tickformatstop", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="layout.polar.radialaxis.tickformatstop", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EnabledValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="enabled", parent_name="layout.polar.radialaxis.tickformatstop", **kwargs ): super(EnabledValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DtickrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="dtickrange", parent_name="layout.polar.radialaxis.tickformatstop", **kwargs ): super(DtickrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "plot"}, {"valType": "any", "editType": "plot"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/polar/radialaxis/title/0000755000175000017500000000000013573746614025660 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/polar/radialaxis/title/__init__.py0000644000175000017500000000367013573721540027766 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="text", parent_name="layout.polar.radialaxis.title", **kwargs ): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="layout.polar.radialaxis.title", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/polar/radialaxis/title/font/0000755000175000017500000000000013573746614026626 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/polar/radialaxis/title/font/__init__.py0000644000175000017500000000315513573721540030732 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="layout.polar.radialaxis.title.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="layout.polar.radialaxis.title.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="layout.polar.radialaxis.title.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/polar/radialaxis/__init__.py0000644000175000017500000007160713573721541026653 0ustar noahfxnoahfximport _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="visible", parent_name="layout.polar.radialaxis", **kwargs ): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="uirevision", parent_name="layout.polar.radialaxis", **kwargs ): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TypeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="type", parent_name="layout.polar.radialaxis", **kwargs ): super(TypeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["-", "linear", "log", "date", "category"]), **kwargs ) import _plotly_utils.basevalidators class TitleValidator(_plotly_utils.basevalidators.TitleValidator): def __init__( self, plotly_name="title", parent_name="layout.polar.radialaxis", **kwargs ): super(TitleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Title"), data_docs=kwargs.pop( "data_docs", """ font Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. text Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """, ), **kwargs ) import _plotly_utils.basevalidators class TickwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="tickwidth", parent_name="layout.polar.radialaxis", **kwargs ): super(TickwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickvalssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="tickvalssrc", parent_name="layout.polar.radialaxis", **kwargs ): super(TickvalssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickvalsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="tickvals", parent_name="layout.polar.radialaxis", **kwargs ): super(TickvalsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="ticktextsrc", parent_name="layout.polar.radialaxis", **kwargs ): super(TicktextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicktextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="ticktext", parent_name="layout.polar.radialaxis", **kwargs ): super(TicktextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="ticksuffix", parent_name="layout.polar.radialaxis", **kwargs ): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TicksValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="ticks", parent_name="layout.polar.radialaxis", **kwargs ): super(TicksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["outside", "inside", ""]), **kwargs ) import _plotly_utils.basevalidators class TickprefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickprefix", parent_name="layout.polar.radialaxis", **kwargs ): super(TickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="tickmode", parent_name="layout.polar.radialaxis", **kwargs ): super(TickmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "linear", "array"]), **kwargs ) import _plotly_utils.basevalidators class TicklenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ticklen", parent_name="layout.polar.radialaxis", **kwargs ): super(TicklenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickformatstopValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickformatstopdefaults", parent_name="layout.polar.radialaxis", **kwargs ): super(TickformatstopValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatstopsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="tickformatstops", parent_name="layout.polar.radialaxis", **kwargs ): super(TickformatstopsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickformat", parent_name="layout.polar.radialaxis", **kwargs ): super(TickformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickfont", parent_name="layout.polar.radialaxis", **kwargs ): super(TickfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class TickcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="tickcolor", parent_name="layout.polar.radialaxis", **kwargs ): super(TickcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__( self, plotly_name="tickangle", parent_name="layout.polar.radialaxis", **kwargs ): super(TickangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="tick0", parent_name="layout.polar.radialaxis", **kwargs ): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SideValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="side", parent_name="layout.polar.radialaxis", **kwargs ): super(SideValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["clockwise", "counterclockwise"]), **kwargs ) import _plotly_utils.basevalidators class ShowticksuffixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showticksuffix", parent_name="layout.polar.radialaxis", **kwargs ): super(ShowticksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowtickprefixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showtickprefix", parent_name="layout.polar.radialaxis", **kwargs ): super(ShowtickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowticklabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showticklabels", parent_name="layout.polar.radialaxis", **kwargs ): super(ShowticklabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowlineValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showline", parent_name="layout.polar.radialaxis", **kwargs ): super(ShowlineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowgridValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showgrid", parent_name="layout.polar.radialaxis", **kwargs ): super(ShowgridValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowexponentValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showexponent", parent_name="layout.polar.radialaxis", **kwargs ): super(ShowexponentValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class SeparatethousandsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="separatethousands", parent_name="layout.polar.radialaxis", **kwargs ): super(SeparatethousandsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class RangemodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="rangemode", parent_name="layout.polar.radialaxis", **kwargs ): super(RangemodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["tozero", "nonnegative", "normal"]), **kwargs ) import _plotly_utils.basevalidators class RangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="range", parent_name="layout.polar.radialaxis", **kwargs ): super(RangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, anim=kwargs.pop("anim", True), edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"autorange": False}), items=kwargs.pop( "items", [ { "valType": "any", "editType": "plot", "impliedEdits": {"^autorange": False}, }, { "valType": "any", "editType": "plot", "impliedEdits": {"^autorange": False}, }, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NticksValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="nticks", parent_name="layout.polar.radialaxis", **kwargs ): super(NticksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="linewidth", parent_name="layout.polar.radialaxis", **kwargs ): super(LinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="linecolor", parent_name="layout.polar.radialaxis", **kwargs ): super(LinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LayerValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="layer", parent_name="layout.polar.radialaxis", **kwargs ): super(LayerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["above traces", "below traces"]), **kwargs ) import _plotly_utils.basevalidators class HoverformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="hoverformat", parent_name="layout.polar.radialaxis", **kwargs ): super(HoverformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class GridwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="gridwidth", parent_name="layout.polar.radialaxis", **kwargs ): super(GridwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class GridcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="gridcolor", parent_name="layout.polar.radialaxis", **kwargs ): super(GridcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ExponentformatValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="exponentformat", parent_name="layout.polar.radialaxis", **kwargs ): super(ExponentformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "e", "E", "power", "SI", "B"]), **kwargs ) import _plotly_utils.basevalidators class DtickValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="dtick", parent_name="layout.polar.radialaxis", **kwargs ): super(DtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="layout.polar.radialaxis", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class CategoryorderValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="categoryorder", parent_name="layout.polar.radialaxis", **kwargs ): super(CategoryorderValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "trace", "category ascending", "category descending", "array", "total ascending", "total descending", "min ascending", "min descending", "max ascending", "max descending", "sum ascending", "sum descending", "mean ascending", "mean descending", "median ascending", "median descending", ], ), **kwargs ) import _plotly_utils.basevalidators class CategoryarraysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="categoryarraysrc", parent_name="layout.polar.radialaxis", **kwargs ): super(CategoryarraysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CategoryarrayValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="categoryarray", parent_name="layout.polar.radialaxis", **kwargs ): super(CategoryarrayValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class CalendarValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="calendar", parent_name="layout.polar.radialaxis", **kwargs ): super(CalendarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "gregorian", "chinese", "coptic", "discworld", "ethiopian", "hebrew", "islamic", "julian", "mayan", "nanakshahi", "nepali", "persian", "jalali", "taiwan", "thai", "ummalqura", ], ), **kwargs ) import _plotly_utils.basevalidators class AutorangeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="autorange", parent_name="layout.polar.radialaxis", **kwargs ): super(AutorangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "reversed"]), **kwargs ) import _plotly_utils.basevalidators class AngleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__( self, plotly_name="angle", parent_name="layout.polar.radialaxis", **kwargs ): super(AngleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/polar/radialaxis/tickfont/0000755000175000017500000000000013573746614026360 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/polar/radialaxis/tickfont/__init__.py0000644000175000017500000000314413573721540030462 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="layout.polar.radialaxis.tickfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="layout.polar.radialaxis.tickfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="layout.polar.radialaxis.tickfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/polar/__init__.py0000644000175000017500000007722013573721540024526 0ustar noahfxnoahfximport _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="layout.polar", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SectorValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="sector", parent_name="layout.polar", **kwargs): super(SectorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), items=kwargs.pop( "items", [ {"valType": "number", "editType": "plot"}, {"valType": "number", "editType": "plot"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class RadialAxisValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="radialaxis", parent_name="layout.polar", **kwargs): super(RadialAxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "RadialAxis"), data_docs=kwargs.pop( "data_docs", """ angle Sets the angle (in degrees) from which the radial axis is drawn. Note that by default, radial axis line on the theta=0 line corresponds to a line pointing right (like what mathematicians prefer). Defaults to the first `polar.sector` angle. autorange Determines whether or not the range of this axis is computed in relation to the input data. See `rangemode` for more info. If `range` is provided, then `autorange` is set to False. calendar Sets the calendar system to use for `range` and `tick0` if this is a date axis. This does not set the calendar for interpreting data on this axis, that's specified in the trace or via the global `layout.calendar` categoryarray Sets the order in which categories on this axis appear. Only has an effect if `categoryorder` is set to "array". Used with `categoryorder`. categoryarraysrc Sets the source reference on plot.ly for categoryarray . categoryorder Specifies the ordering logic for the case of categorical variables. By default, plotly uses "trace", which specifies the order that is present in the data supplied. Set `categoryorder` to *category ascending* or *category descending* if order should be determined by the alphanumerical order of the category names. Set `categoryorder` to "array" to derive the ordering from the attribute `categoryarray`. If a category is not found in the `categoryarray` array, the sorting behavior for that attribute will be identical to the "trace" mode. The unspecified categories will follow the categories in `categoryarray`. Set `categoryorder` to *total ascending* or *total descending* if order should be determined by the numerical order of the values. Similarly, the order can be determined by the min, max, sum, mean or median of all the values. color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. gridcolor Sets the color of the grid lines. gridwidth Sets the width (in px) of the grid lines. hoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" layer Sets the layer on which this axis is displayed. If *above traces*, this axis is displayed above all the subplot's traces If *below traces*, this axis is displayed below all the subplot's traces, but above the grid lines. Useful when used together with scatter-like traces with `cliponaxis` set to False to show markers and/or text nodes above this axis. linecolor Sets the axis line color. linewidth Sets the width (in px) of the axis line. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". range Sets the range of this axis. If the axis `type` is "log", then you must take the log of your desired range (e.g. to set the range from 1 to 100, set the range from 0 to 2). If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. rangemode If *tozero*`, the range extends to 0, regardless of the input data If "nonnegative", the range is non-negative, regardless of the input data. If "normal", the range is computed in relation to the extrema of the input data (same behavior as for cartesian axes). separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showgrid Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. showline Determines whether or not a line bounding this axis is drawn. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. side Determines on which side of radial axis line the tick and tick labels appear. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the tick font. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.layout.polar.ra dialaxis.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.lay out.polar.radialaxis.tickformatstopdefaults), sets the default property values to use for elements of layout.polar.radialaxis.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.layout.polar.radialaxis.Ti tle instance or dict with compatible properties titlefont Deprecated: Please use layout.polar.radialaxis.title.font instead. Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. type Sets the axis type. By default, plotly attempts to determined the axis type by looking into the data of the traces that referenced the axis in question. uirevision Controls persistence of user-driven changes in axis `range`, `autorange`, `angle`, and `title` if in `editable: true` configuration. Defaults to `polar.uirevision`. visible A single toggle to hide the axis while preserving interaction like dragging. Default is true when a cheater plot is present on the axis, otherwise false """, ), **kwargs ) import _plotly_utils.basevalidators class HoleValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="hole", parent_name="layout.polar", **kwargs): super(HoleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class GridshapeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="gridshape", parent_name="layout.polar", **kwargs): super(GridshapeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["circular", "linear"]), **kwargs ) import _plotly_utils.basevalidators class DomainValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="domain", parent_name="layout.polar", **kwargs): super(DomainValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Domain"), data_docs=kwargs.pop( "data_docs", """ column If there is a layout grid, use the domain for this column in the grid for this polar subplot . row If there is a layout grid, use the domain for this row in the grid for this polar subplot . x Sets the horizontal domain of this polar subplot (in plot fraction). y Sets the vertical domain of this polar subplot (in plot fraction). """, ), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="bgcolor", parent_name="layout.polar", **kwargs): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BarmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="barmode", parent_name="layout.polar", **kwargs): super(BarmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["stack", "overlay"]), **kwargs ) import _plotly_utils.basevalidators class BargapValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="bargap", parent_name="layout.polar", **kwargs): super(BargapValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AngularAxisValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="angularaxis", parent_name="layout.polar", **kwargs): super(AngularAxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "AngularAxis"), data_docs=kwargs.pop( "data_docs", """ categoryarray Sets the order in which categories on this axis appear. Only has an effect if `categoryorder` is set to "array". Used with `categoryorder`. categoryarraysrc Sets the source reference on plot.ly for categoryarray . categoryorder Specifies the ordering logic for the case of categorical variables. By default, plotly uses "trace", which specifies the order that is present in the data supplied. Set `categoryorder` to *category ascending* or *category descending* if order should be determined by the alphanumerical order of the category names. Set `categoryorder` to "array" to derive the ordering from the attribute `categoryarray`. If a category is not found in the `categoryarray` array, the sorting behavior for that attribute will be identical to the "trace" mode. The unspecified categories will follow the categories in `categoryarray`. Set `categoryorder` to *total ascending* or *total descending* if order should be determined by the numerical order of the values. Similarly, the order can be determined by the min, max, sum, mean or median of all the values. color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. direction Sets the direction corresponding to positive angles. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. gridcolor Sets the color of the grid lines. gridwidth Sets the width (in px) of the grid lines. hoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" layer Sets the layer on which this axis is displayed. If *above traces*, this axis is displayed above all the subplot's traces If *below traces*, this axis is displayed below all the subplot's traces, but above the grid lines. Useful when used together with scatter-like traces with `cliponaxis` set to False to show markers and/or text nodes above this axis. linecolor Sets the axis line color. linewidth Sets the width (in px) of the axis line. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". period Set the angular period. Has an effect only when `angularaxis.type` is "category". rotation Sets that start position (in degrees) of the angular axis By default, polar subplots with `direction` set to "counterclockwise" get a `rotation` of 0 which corresponds to due East (like what mathematicians prefer). In turn, polar with `direction` set to "clockwise" get a rotation of 90 which corresponds to due North (like on a compass), separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showgrid Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. showline Determines whether or not a line bounding this axis is drawn. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thetaunit Sets the format unit of the formatted "theta" values. Has an effect only when `angularaxis.type` is "linear". tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the tick font. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.layout.polar.an gularaxis.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.lay out.polar.angularaxis.tickformatstopdefaults), sets the default property values to use for elements of layout.polar.angularaxis.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). type Sets the angular axis type. If "linear", set `thetaunit` to determine the unit in which axis value are shown. If *category, use `period` to set the number of integer coordinates around polar axis. uirevision Controls persistence of user-driven changes in axis `rotation`. Defaults to `polar.uirevision`. visible A single toggle to hide the axis while preserving interaction like dragging. Default is true when a cheater plot is present on the axis, otherwise false """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/polar/domain/0000755000175000017500000000000013573746614023665 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/polar/domain/__init__.py0000644000175000017500000000455313573721540025774 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="y", parent_name="layout.polar.domain", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), items=kwargs.pop( "items", [ {"valType": "number", "min": 0, "max": 1, "editType": "plot"}, {"valType": "number", "min": 0, "max": 1, "editType": "plot"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="x", parent_name="layout.polar.domain", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), items=kwargs.pop( "items", [ {"valType": "number", "min": 0, "max": 1, "editType": "plot"}, {"valType": "number", "min": 0, "max": 1, "editType": "plot"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class RowValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="row", parent_name="layout.polar.domain", **kwargs): super(RowValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColumnValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="column", parent_name="layout.polar.domain", **kwargs ): super(ColumnValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/0000755000175000017500000000000013573746614022376 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/annotation/0000755000175000017500000000000013573746614024550 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/annotation/hoverlabel/0000755000175000017500000000000013573746614026673 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/annotation/hoverlabel/__init__.py0000644000175000017500000000500313573721540030771 0ustar noahfxnoahfximport _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="layout.scene.annotation.hoverlabel", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="layout.scene.annotation.hoverlabel", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="layout.scene.annotation.hoverlabel", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/annotation/hoverlabel/font/0000755000175000017500000000000013573746614027641 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/annotation/hoverlabel/font/__init__.py0000644000175000017500000000317113573721540031743 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="layout.scene.annotation.hoverlabel.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="layout.scene.annotation.hoverlabel.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="layout.scene.annotation.hoverlabel.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/annotation/__init__.py0000644000175000017500000004766613573721541026674 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ZValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="z", parent_name="layout.scene.annotation", **kwargs ): super(ZValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YshiftValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="yshift", parent_name="layout.scene.annotation", **kwargs ): super(YshiftValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class YanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="yanchor", parent_name="layout.scene.annotation", **kwargs ): super(YanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "top", "middle", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="y", parent_name="layout.scene.annotation", **kwargs ): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XshiftValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="xshift", parent_name="layout.scene.annotation", **kwargs ): super(XshiftValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="xanchor", parent_name="layout.scene.annotation", **kwargs ): super(XanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "left", "center", "right"]), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="x", parent_name="layout.scene.annotation", **kwargs ): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="width", parent_name="layout.scene.annotation", **kwargs ): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="visible", parent_name="layout.scene.annotation", **kwargs ): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ValignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="valign", parent_name="layout.scene.annotation", **kwargs ): super(ValignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["top", "middle", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class TextangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__( self, plotly_name="textangle", parent_name="layout.scene.annotation", **kwargs ): super(TextangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="text", parent_name="layout.scene.annotation", **kwargs ): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="layout.scene.annotation", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class StartstandoffValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="startstandoff", parent_name="layout.scene.annotation", **kwargs ): super(StartstandoffValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class StartarrowsizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="startarrowsize", parent_name="layout.scene.annotation", **kwargs ): super(StartarrowsizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0.3), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class StartarrowheadValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="startarrowhead", parent_name="layout.scene.annotation", **kwargs ): super(StartarrowheadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 8), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class StandoffValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="standoff", parent_name="layout.scene.annotation", **kwargs ): super(StandoffValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowarrowValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showarrow", parent_name="layout.scene.annotation", **kwargs ): super(ShowarrowValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="opacity", parent_name="layout.scene.annotation", **kwargs ): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="layout.scene.annotation", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class HovertextValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="hovertext", parent_name="layout.scene.annotation", **kwargs ): super(HovertextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverlabelValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="hoverlabel", parent_name="layout.scene.annotation", **kwargs ): super(HoverlabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Hoverlabel"), data_docs=kwargs.pop( "data_docs", """ bgcolor Sets the background color of the hover label. By default uses the annotation's `bgcolor` made opaque, or white if it was transparent. bordercolor Sets the border color of the hover label. By default uses either dark grey or white, for maximum contrast with `hoverlabel.bgcolor`. font Sets the hover label text font. By default uses the global hover font and size, with color from `hoverlabel.bordercolor`. """, ), **kwargs ) import _plotly_utils.basevalidators class HeightValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="height", parent_name="layout.scene.annotation", **kwargs ): super(HeightValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="layout.scene.annotation", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class CaptureeventsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="captureevents", parent_name="layout.scene.annotation", **kwargs ): super(CaptureeventsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BorderwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="borderwidth", parent_name="layout.scene.annotation", **kwargs ): super(BorderwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BorderpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="borderpad", parent_name="layout.scene.annotation", **kwargs ): super(BorderpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="layout.scene.annotation", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="layout.scene.annotation", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AyValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ay", parent_name="layout.scene.annotation", **kwargs ): super(AyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ax", parent_name="layout.scene.annotation", **kwargs ): super(AxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ArrowwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="arrowwidth", parent_name="layout.scene.annotation", **kwargs ): super(ArrowwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0.1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ArrowsizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="arrowsize", parent_name="layout.scene.annotation", **kwargs ): super(ArrowsizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0.3), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ArrowsideValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__( self, plotly_name="arrowside", parent_name="layout.scene.annotation", **kwargs ): super(ArrowsideValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), extras=kwargs.pop("extras", ["none"]), flags=kwargs.pop("flags", ["end", "start"]), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ArrowheadValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="arrowhead", parent_name="layout.scene.annotation", **kwargs ): super(ArrowheadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 8), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ArrowcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="arrowcolor", parent_name="layout.scene.annotation", **kwargs ): super(ArrowcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="align", parent_name="layout.scene.annotation", **kwargs ): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "center", "right"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/annotation/font/0000755000175000017500000000000013573746614025516 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/annotation/font/__init__.py0000644000175000017500000000302013573721540027611 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="layout.scene.annotation.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="layout.scene.annotation.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="layout.scene.annotation.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/yaxis/0000755000175000017500000000000013573746614023533 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/yaxis/tickformatstop/0000755000175000017500000000000013573746614026604 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/yaxis/tickformatstop/__init__.py0000644000175000017500000000534313573721540030711 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="value", parent_name="layout.scene.yaxis.tickformatstop", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="layout.scene.yaxis.tickformatstop", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="layout.scene.yaxis.tickformatstop", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EnabledValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="enabled", parent_name="layout.scene.yaxis.tickformatstop", **kwargs ): super(EnabledValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DtickrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="dtickrange", parent_name="layout.scene.yaxis.tickformatstop", **kwargs ): super(DtickrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "plot"}, {"valType": "any", "editType": "plot"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/yaxis/title/0000755000175000017500000000000013573746614024654 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/yaxis/title/__init__.py0000644000175000017500000000365613573721540026766 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="text", parent_name="layout.scene.yaxis.title", **kwargs ): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="layout.scene.yaxis.title", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/yaxis/title/font/0000755000175000017500000000000013573746614025622 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/yaxis/title/font/__init__.py0000644000175000017500000000305313573721540027723 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="layout.scene.yaxis.title.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="layout.scene.yaxis.title.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="layout.scene.yaxis.title.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/yaxis/__init__.py0000644000175000017500000007727413573721541025655 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ZerolinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="zerolinewidth", parent_name="layout.scene.yaxis", **kwargs ): super(ZerolinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ZerolinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="zerolinecolor", parent_name="layout.scene.yaxis", **kwargs ): super(ZerolinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ZerolineValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="zeroline", parent_name="layout.scene.yaxis", **kwargs ): super(ZerolineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="visible", parent_name="layout.scene.yaxis", **kwargs ): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TypeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="type", parent_name="layout.scene.yaxis", **kwargs): super(TypeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["-", "linear", "log", "date", "category"]), **kwargs ) import _plotly_utils.basevalidators class TitleValidator(_plotly_utils.basevalidators.TitleValidator): def __init__(self, plotly_name="title", parent_name="layout.scene.yaxis", **kwargs): super(TitleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Title"), data_docs=kwargs.pop( "data_docs", """ font Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. text Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """, ), **kwargs ) import _plotly_utils.basevalidators class TickwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="tickwidth", parent_name="layout.scene.yaxis", **kwargs ): super(TickwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickvalssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="tickvalssrc", parent_name="layout.scene.yaxis", **kwargs ): super(TickvalssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickvalsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="tickvals", parent_name="layout.scene.yaxis", **kwargs ): super(TickvalsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="ticktextsrc", parent_name="layout.scene.yaxis", **kwargs ): super(TicktextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicktextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="ticktext", parent_name="layout.scene.yaxis", **kwargs ): super(TicktextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="ticksuffix", parent_name="layout.scene.yaxis", **kwargs ): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TicksValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="ticks", parent_name="layout.scene.yaxis", **kwargs): super(TicksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["outside", "inside", ""]), **kwargs ) import _plotly_utils.basevalidators class TickprefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickprefix", parent_name="layout.scene.yaxis", **kwargs ): super(TickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="tickmode", parent_name="layout.scene.yaxis", **kwargs ): super(TickmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "linear", "array"]), **kwargs ) import _plotly_utils.basevalidators class TicklenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ticklen", parent_name="layout.scene.yaxis", **kwargs ): super(TicklenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickformatstopValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickformatstopdefaults", parent_name="layout.scene.yaxis", **kwargs ): super(TickformatstopValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatstopsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="tickformatstops", parent_name="layout.scene.yaxis", **kwargs ): super(TickformatstopsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickformat", parent_name="layout.scene.yaxis", **kwargs ): super(TickformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickfont", parent_name="layout.scene.yaxis", **kwargs ): super(TickfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class TickcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="tickcolor", parent_name="layout.scene.yaxis", **kwargs ): super(TickcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__( self, plotly_name="tickangle", parent_name="layout.scene.yaxis", **kwargs ): super(TickangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="tick0", parent_name="layout.scene.yaxis", **kwargs): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SpikethicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="spikethickness", parent_name="layout.scene.yaxis", **kwargs ): super(SpikethicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SpikesidesValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="spikesides", parent_name="layout.scene.yaxis", **kwargs ): super(SpikesidesValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SpikecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="spikecolor", parent_name="layout.scene.yaxis", **kwargs ): super(SpikecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowticksuffixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showticksuffix", parent_name="layout.scene.yaxis", **kwargs ): super(ShowticksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowtickprefixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showtickprefix", parent_name="layout.scene.yaxis", **kwargs ): super(ShowtickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowticklabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showticklabels", parent_name="layout.scene.yaxis", **kwargs ): super(ShowticklabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowspikesValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showspikes", parent_name="layout.scene.yaxis", **kwargs ): super(ShowspikesValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ShowlineValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showline", parent_name="layout.scene.yaxis", **kwargs ): super(ShowlineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowgridValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showgrid", parent_name="layout.scene.yaxis", **kwargs ): super(ShowgridValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowexponentValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showexponent", parent_name="layout.scene.yaxis", **kwargs ): super(ShowexponentValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowbackgroundValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showbackground", parent_name="layout.scene.yaxis", **kwargs ): super(ShowbackgroundValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ShowaxeslabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showaxeslabels", parent_name="layout.scene.yaxis", **kwargs ): super(ShowaxeslabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SeparatethousandsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="separatethousands", parent_name="layout.scene.yaxis", **kwargs ): super(SeparatethousandsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class RangemodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="rangemode", parent_name="layout.scene.yaxis", **kwargs ): super(RangemodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["normal", "tozero", "nonnegative"]), **kwargs ) import _plotly_utils.basevalidators class RangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="range", parent_name="layout.scene.yaxis", **kwargs): super(RangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, anim=kwargs.pop("anim", False), edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"autorange": False}), items=kwargs.pop( "items", [ { "valType": "any", "editType": "plot", "impliedEdits": {"^autorange": False}, }, { "valType": "any", "editType": "plot", "impliedEdits": {"^autorange": False}, }, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NticksValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="nticks", parent_name="layout.scene.yaxis", **kwargs ): super(NticksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class MirrorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="mirror", parent_name="layout.scene.yaxis", **kwargs ): super(MirrorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", [True, "ticks", False, "all", "allticks"]), **kwargs ) import _plotly_utils.basevalidators class LinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="linewidth", parent_name="layout.scene.yaxis", **kwargs ): super(LinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="linecolor", parent_name="layout.scene.yaxis", **kwargs ): super(LinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class HoverformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="hoverformat", parent_name="layout.scene.yaxis", **kwargs ): super(HoverformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class GridwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="gridwidth", parent_name="layout.scene.yaxis", **kwargs ): super(GridwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class GridcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="gridcolor", parent_name="layout.scene.yaxis", **kwargs ): super(GridcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ExponentformatValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="exponentformat", parent_name="layout.scene.yaxis", **kwargs ): super(ExponentformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "e", "E", "power", "SI", "B"]), **kwargs ) import _plotly_utils.basevalidators class DtickValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="dtick", parent_name="layout.scene.yaxis", **kwargs): super(DtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="layout.scene.yaxis", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class CategoryorderValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="categoryorder", parent_name="layout.scene.yaxis", **kwargs ): super(CategoryorderValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "trace", "category ascending", "category descending", "array", "total ascending", "total descending", "min ascending", "min descending", "max ascending", "max descending", "sum ascending", "sum descending", "mean ascending", "mean descending", "median ascending", "median descending", ], ), **kwargs ) import _plotly_utils.basevalidators class CategoryarraysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="categoryarraysrc", parent_name="layout.scene.yaxis", **kwargs ): super(CategoryarraysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CategoryarrayValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="categoryarray", parent_name="layout.scene.yaxis", **kwargs ): super(CategoryarrayValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class CalendarValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="calendar", parent_name="layout.scene.yaxis", **kwargs ): super(CalendarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "gregorian", "chinese", "coptic", "discworld", "ethiopian", "hebrew", "islamic", "julian", "mayan", "nanakshahi", "nepali", "persian", "jalali", "taiwan", "thai", "ummalqura", ], ), **kwargs ) import _plotly_utils.basevalidators class BackgroundcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="backgroundcolor", parent_name="layout.scene.yaxis", **kwargs ): super(BackgroundcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AutorangeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="autorange", parent_name="layout.scene.yaxis", **kwargs ): super(AutorangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "reversed"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/yaxis/tickfont/0000755000175000017500000000000013573746614025354 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/yaxis/tickfont/__init__.py0000644000175000017500000000301513573721540027453 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="layout.scene.yaxis.tickfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="layout.scene.yaxis.tickfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="layout.scene.yaxis.tickfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/camera/0000755000175000017500000000000013573746614023626 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/camera/projection/0000755000175000017500000000000013573746614026002 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/camera/projection/__init__.py0000644000175000017500000000104313573721540030100 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TypeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="type", parent_name="layout.scene.camera.projection", **kwargs ): super(TypeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["perspective", "orthographic"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/camera/__init__.py0000644000175000017500000000460313573721540025731 0ustar noahfxnoahfximport _plotly_utils.basevalidators class UpValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="up", parent_name="layout.scene.camera", **kwargs): super(UpValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Up"), data_docs=kwargs.pop( "data_docs", """ x y z """, ), **kwargs ) import _plotly_utils.basevalidators class ProjectionValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="projection", parent_name="layout.scene.camera", **kwargs ): super(ProjectionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Projection"), data_docs=kwargs.pop( "data_docs", """ type Sets the projection type. The projection type could be either "perspective" or "orthographic". The default is "perspective". """, ), **kwargs ) import _plotly_utils.basevalidators class EyeValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="eye", parent_name="layout.scene.camera", **kwargs): super(EyeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Eye"), data_docs=kwargs.pop( "data_docs", """ x y z """, ), **kwargs ) import _plotly_utils.basevalidators class CenterValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="center", parent_name="layout.scene.camera", **kwargs ): super(CenterValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Center"), data_docs=kwargs.pop( "data_docs", """ x y z """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/camera/up/0000755000175000017500000000000013573746614024252 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/camera/up/__init__.py0000644000175000017500000000245413573721540026357 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ZValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="z", parent_name="layout.scene.camera.up", **kwargs): super(ZValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "camera"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="y", parent_name="layout.scene.camera.up", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "camera"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="x", parent_name="layout.scene.camera.up", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "camera"), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/camera/eye/0000755000175000017500000000000013573746614024410 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/camera/eye/__init__.py0000644000175000017500000000253113573721540026511 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ZValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="z", parent_name="layout.scene.camera.eye", **kwargs ): super(ZValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "camera"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="y", parent_name="layout.scene.camera.eye", **kwargs ): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "camera"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="x", parent_name="layout.scene.camera.eye", **kwargs ): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "camera"), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/camera/center/0000755000175000017500000000000013573746614025106 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/camera/center/__init__.py0000644000175000017500000000254213573721540027211 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ZValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="z", parent_name="layout.scene.camera.center", **kwargs ): super(ZValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "camera"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="y", parent_name="layout.scene.camera.center", **kwargs ): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "camera"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="x", parent_name="layout.scene.camera.center", **kwargs ): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "camera"), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/__init__.py0000644000175000017500000016572213573721540024513 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ZAxisValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="zaxis", parent_name="layout.scene", **kwargs): super(ZAxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "ZAxis"), data_docs=kwargs.pop( "data_docs", """ autorange Determines whether or not the range of this axis is computed in relation to the input data. See `rangemode` for more info. If `range` is provided, then `autorange` is set to False. backgroundcolor Sets the background color of this axis' wall. calendar Sets the calendar system to use for `range` and `tick0` if this is a date axis. This does not set the calendar for interpreting data on this axis, that's specified in the trace or via the global `layout.calendar` categoryarray Sets the order in which categories on this axis appear. Only has an effect if `categoryorder` is set to "array". Used with `categoryorder`. categoryarraysrc Sets the source reference on plot.ly for categoryarray . categoryorder Specifies the ordering logic for the case of categorical variables. By default, plotly uses "trace", which specifies the order that is present in the data supplied. Set `categoryorder` to *category ascending* or *category descending* if order should be determined by the alphanumerical order of the category names. Set `categoryorder` to "array" to derive the ordering from the attribute `categoryarray`. If a category is not found in the `categoryarray` array, the sorting behavior for that attribute will be identical to the "trace" mode. The unspecified categories will follow the categories in `categoryarray`. Set `categoryorder` to *total ascending* or *total descending* if order should be determined by the numerical order of the values. Similarly, the order can be determined by the min, max, sum, mean or median of all the values. color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. gridcolor Sets the color of the grid lines. gridwidth Sets the width (in px) of the grid lines. hoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" linecolor Sets the axis line color. linewidth Sets the width (in px) of the axis line. mirror Determines if the axis lines or/and ticks are mirrored to the opposite side of the plotting area. If True, the axis lines are mirrored. If "ticks", the axis lines and ticks are mirrored. If False, mirroring is disable. If "all", axis lines are mirrored on all shared-axes subplots. If "allticks", axis lines and ticks are mirrored on all shared-axes subplots. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". range Sets the range of this axis. If the axis `type` is "log", then you must take the log of your desired range (e.g. to set the range from 1 to 100, set the range from 0 to 2). If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. rangemode If "normal", the range is computed in relation to the extrema of the input data. If *tozero*`, the range extends to 0, regardless of the input data If "nonnegative", the range is non- negative, regardless of the input data. Applies only to linear axes. separatethousands If "true", even 4-digit integers are separated showaxeslabels Sets whether or not this axis is labeled showbackground Sets whether or not this axis' wall has a background color. showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showgrid Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. showline Determines whether or not a line bounding this axis is drawn. showspikes Sets whether or not spikes starting from data points to this axis' wall are shown on hover. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. spikecolor Sets the color of the spikes. spikesides Sets whether or not spikes extending from the projection data points to this axis' wall boundaries are shown on hover. spikethickness Sets the thickness (in px) of the spikes. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the tick font. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.layout.scene.za xis.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.lay out.scene.zaxis.tickformatstopdefaults), sets the default property values to use for elements of layout.scene.zaxis.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.layout.scene.zaxis.Title instance or dict with compatible properties titlefont Deprecated: Please use layout.scene.zaxis.title.font instead. Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. type Sets the axis type. By default, plotly attempts to determined the axis type by looking into the data of the traces that referenced the axis in question. visible A single toggle to hide the axis while preserving interaction like dragging. Default is true when a cheater plot is present on the axis, otherwise false zeroline Determines whether or not a line is drawn at along the 0 value of this axis. If True, the zero line is drawn on top of the grid lines. zerolinecolor Sets the line color of the zero line. zerolinewidth Sets the width (in px) of the zero line. """, ), **kwargs ) import _plotly_utils.basevalidators class YAxisValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="yaxis", parent_name="layout.scene", **kwargs): super(YAxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "YAxis"), data_docs=kwargs.pop( "data_docs", """ autorange Determines whether or not the range of this axis is computed in relation to the input data. See `rangemode` for more info. If `range` is provided, then `autorange` is set to False. backgroundcolor Sets the background color of this axis' wall. calendar Sets the calendar system to use for `range` and `tick0` if this is a date axis. This does not set the calendar for interpreting data on this axis, that's specified in the trace or via the global `layout.calendar` categoryarray Sets the order in which categories on this axis appear. Only has an effect if `categoryorder` is set to "array". Used with `categoryorder`. categoryarraysrc Sets the source reference on plot.ly for categoryarray . categoryorder Specifies the ordering logic for the case of categorical variables. By default, plotly uses "trace", which specifies the order that is present in the data supplied. Set `categoryorder` to *category ascending* or *category descending* if order should be determined by the alphanumerical order of the category names. Set `categoryorder` to "array" to derive the ordering from the attribute `categoryarray`. If a category is not found in the `categoryarray` array, the sorting behavior for that attribute will be identical to the "trace" mode. The unspecified categories will follow the categories in `categoryarray`. Set `categoryorder` to *total ascending* or *total descending* if order should be determined by the numerical order of the values. Similarly, the order can be determined by the min, max, sum, mean or median of all the values. color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. gridcolor Sets the color of the grid lines. gridwidth Sets the width (in px) of the grid lines. hoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" linecolor Sets the axis line color. linewidth Sets the width (in px) of the axis line. mirror Determines if the axis lines or/and ticks are mirrored to the opposite side of the plotting area. If True, the axis lines are mirrored. If "ticks", the axis lines and ticks are mirrored. If False, mirroring is disable. If "all", axis lines are mirrored on all shared-axes subplots. If "allticks", axis lines and ticks are mirrored on all shared-axes subplots. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". range Sets the range of this axis. If the axis `type` is "log", then you must take the log of your desired range (e.g. to set the range from 1 to 100, set the range from 0 to 2). If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. rangemode If "normal", the range is computed in relation to the extrema of the input data. If *tozero*`, the range extends to 0, regardless of the input data If "nonnegative", the range is non- negative, regardless of the input data. Applies only to linear axes. separatethousands If "true", even 4-digit integers are separated showaxeslabels Sets whether or not this axis is labeled showbackground Sets whether or not this axis' wall has a background color. showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showgrid Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. showline Determines whether or not a line bounding this axis is drawn. showspikes Sets whether or not spikes starting from data points to this axis' wall are shown on hover. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. spikecolor Sets the color of the spikes. spikesides Sets whether or not spikes extending from the projection data points to this axis' wall boundaries are shown on hover. spikethickness Sets the thickness (in px) of the spikes. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the tick font. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.layout.scene.ya xis.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.lay out.scene.yaxis.tickformatstopdefaults), sets the default property values to use for elements of layout.scene.yaxis.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.layout.scene.yaxis.Title instance or dict with compatible properties titlefont Deprecated: Please use layout.scene.yaxis.title.font instead. Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. type Sets the axis type. By default, plotly attempts to determined the axis type by looking into the data of the traces that referenced the axis in question. visible A single toggle to hide the axis while preserving interaction like dragging. Default is true when a cheater plot is present on the axis, otherwise false zeroline Determines whether or not a line is drawn at along the 0 value of this axis. If True, the zero line is drawn on top of the grid lines. zerolinecolor Sets the line color of the zero line. zerolinewidth Sets the width (in px) of the zero line. """, ), **kwargs ) import _plotly_utils.basevalidators class XAxisValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="xaxis", parent_name="layout.scene", **kwargs): super(XAxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "XAxis"), data_docs=kwargs.pop( "data_docs", """ autorange Determines whether or not the range of this axis is computed in relation to the input data. See `rangemode` for more info. If `range` is provided, then `autorange` is set to False. backgroundcolor Sets the background color of this axis' wall. calendar Sets the calendar system to use for `range` and `tick0` if this is a date axis. This does not set the calendar for interpreting data on this axis, that's specified in the trace or via the global `layout.calendar` categoryarray Sets the order in which categories on this axis appear. Only has an effect if `categoryorder` is set to "array". Used with `categoryorder`. categoryarraysrc Sets the source reference on plot.ly for categoryarray . categoryorder Specifies the ordering logic for the case of categorical variables. By default, plotly uses "trace", which specifies the order that is present in the data supplied. Set `categoryorder` to *category ascending* or *category descending* if order should be determined by the alphanumerical order of the category names. Set `categoryorder` to "array" to derive the ordering from the attribute `categoryarray`. If a category is not found in the `categoryarray` array, the sorting behavior for that attribute will be identical to the "trace" mode. The unspecified categories will follow the categories in `categoryarray`. Set `categoryorder` to *total ascending* or *total descending* if order should be determined by the numerical order of the values. Similarly, the order can be determined by the min, max, sum, mean or median of all the values. color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. gridcolor Sets the color of the grid lines. gridwidth Sets the width (in px) of the grid lines. hoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" linecolor Sets the axis line color. linewidth Sets the width (in px) of the axis line. mirror Determines if the axis lines or/and ticks are mirrored to the opposite side of the plotting area. If True, the axis lines are mirrored. If "ticks", the axis lines and ticks are mirrored. If False, mirroring is disable. If "all", axis lines are mirrored on all shared-axes subplots. If "allticks", axis lines and ticks are mirrored on all shared-axes subplots. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". range Sets the range of this axis. If the axis `type` is "log", then you must take the log of your desired range (e.g. to set the range from 1 to 100, set the range from 0 to 2). If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. rangemode If "normal", the range is computed in relation to the extrema of the input data. If *tozero*`, the range extends to 0, regardless of the input data If "nonnegative", the range is non- negative, regardless of the input data. Applies only to linear axes. separatethousands If "true", even 4-digit integers are separated showaxeslabels Sets whether or not this axis is labeled showbackground Sets whether or not this axis' wall has a background color. showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showgrid Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. showline Determines whether or not a line bounding this axis is drawn. showspikes Sets whether or not spikes starting from data points to this axis' wall are shown on hover. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. spikecolor Sets the color of the spikes. spikesides Sets whether or not spikes extending from the projection data points to this axis' wall boundaries are shown on hover. spikethickness Sets the thickness (in px) of the spikes. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the tick font. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.layout.scene.xa xis.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.lay out.scene.xaxis.tickformatstopdefaults), sets the default property values to use for elements of layout.scene.xaxis.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.layout.scene.xaxis.Title instance or dict with compatible properties titlefont Deprecated: Please use layout.scene.xaxis.title.font instead. Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. type Sets the axis type. By default, plotly attempts to determined the axis type by looking into the data of the traces that referenced the axis in question. visible A single toggle to hide the axis while preserving interaction like dragging. Default is true when a cheater plot is present on the axis, otherwise false zeroline Determines whether or not a line is drawn at along the 0 value of this axis. If True, the zero line is drawn on top of the grid lines. zerolinecolor Sets the line color of the zero line. zerolinewidth Sets the width (in px) of the zero line. """, ), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="layout.scene", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovermodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="hovermode", parent_name="layout.scene", **kwargs): super(HovermodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "modebar"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["closest", False]), **kwargs ) import _plotly_utils.basevalidators class DragmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="dragmode", parent_name="layout.scene", **kwargs): super(DragmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["orbit", "turntable", "zoom", "pan", False]), **kwargs ) import _plotly_utils.basevalidators class DomainValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="domain", parent_name="layout.scene", **kwargs): super(DomainValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Domain"), data_docs=kwargs.pop( "data_docs", """ column If there is a layout grid, use the domain for this column in the grid for this scene subplot . row If there is a layout grid, use the domain for this row in the grid for this scene subplot . x Sets the horizontal domain of this scene subplot (in plot fraction). y Sets the vertical domain of this scene subplot (in plot fraction). """, ), **kwargs ) import _plotly_utils.basevalidators class CameraValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="camera", parent_name="layout.scene", **kwargs): super(CameraValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Camera"), data_docs=kwargs.pop( "data_docs", """ center Sets the (x,y,z) components of the 'center' camera vector This vector determines the translation (x,y,z) space about the center of this scene. By default, there is no such translation. eye Sets the (x,y,z) components of the 'eye' camera vector. This vector determines the view point about the origin of this scene. projection plotly.graph_objects.layout.scene.camera.Projec tion instance or dict with compatible properties up Sets the (x,y,z) components of the 'up' camera vector. This vector determines the up direction of this scene with respect to the page. The default is *{x: 0, y: 0, z: 1}* which means that the z axis points up. """, ), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="bgcolor", parent_name="layout.scene", **kwargs): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AspectratioValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="aspectratio", parent_name="layout.scene", **kwargs): super(AspectratioValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Aspectratio"), data_docs=kwargs.pop( "data_docs", """ x y z """, ), **kwargs ) import _plotly_utils.basevalidators class AspectmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="aspectmode", parent_name="layout.scene", **kwargs): super(AspectmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "cube", "data", "manual"]), **kwargs ) import _plotly_utils.basevalidators class AnnotationValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="annotationdefaults", parent_name="layout.scene", **kwargs ): super(AnnotationValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Annotation"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class AnnotationsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__(self, plotly_name="annotations", parent_name="layout.scene", **kwargs): super(AnnotationsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Annotation"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the `text` within the box. Has an effect only if `text` spans more two or more lines (i.e. `text` contains one or more
HTML tags) or if an explicit width is set to override the text width. arrowcolor Sets the color of the annotation arrow. arrowhead Sets the end annotation arrow head style. arrowside Sets the annotation arrow head position. arrowsize Sets the size of the end annotation arrow head, relative to `arrowwidth`. A value of 1 (default) gives a head about 3x as wide as the line. arrowwidth Sets the width (in px) of annotation arrow line. ax Sets the x component of the arrow tail about the arrow head (in pixels). ay Sets the y component of the arrow tail about the arrow head (in pixels). bgcolor Sets the background color of the annotation. bordercolor Sets the color of the border enclosing the annotation `text`. borderpad Sets the padding (in px) between the `text` and the enclosing border. borderwidth Sets the width (in px) of the border enclosing the annotation `text`. captureevents Determines whether the annotation text box captures mouse move and click events, or allows those events to pass through to data points in the plot that may be behind the annotation. By default `captureevents` is False unless `hovertext` is provided. If you use the event `plotly_clickannotation` without `hovertext` you must explicitly enable `captureevents`. font Sets the annotation text font. height Sets an explicit height for the text box. null (default) lets the text set the box height. Taller text will be clipped. hoverlabel plotly.graph_objects.layout.scene.annotation.Ho verlabel instance or dict with compatible properties hovertext Sets text to appear when hovering over this annotation. If omitted or blank, no hover label will appear. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. opacity Sets the opacity of the annotation (text + arrow). showarrow Determines whether or not the annotation is drawn with an arrow. If True, `text` is placed near the arrow's tail. If False, `text` lines up with the `x` and `y` provided. standoff Sets a distance, in pixels, to move the end arrowhead away from the position it is pointing at, for example to point at the edge of a marker independent of zoom. Note that this shortens the arrow from the `ax` / `ay` vector, in contrast to `xshift` / `yshift` which moves everything by this amount. startarrowhead Sets the start annotation arrow head style. startarrowsize Sets the size of the start annotation arrow head, relative to `arrowwidth`. A value of 1 (default) gives a head about 3x as wide as the line. startstandoff Sets a distance, in pixels, to move the start arrowhead away from the position it is pointing at, for example to point at the edge of a marker independent of zoom. Note that this shortens the arrow from the `ax` / `ay` vector, in contrast to `xshift` / `yshift` which moves everything by this amount. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. text Sets the text associated with this annotation. Plotly uses a subset of HTML tags to do things like newline (
), bold (), italics (), hyperlinks (). Tags , , are also supported. textangle Sets the angle at which the `text` is drawn with respect to the horizontal. valign Sets the vertical alignment of the `text` within the box. Has an effect only if an explicit height is set to override the text height. visible Determines whether or not this annotation is visible. width Sets an explicit width for the text box. null (default) lets the text set the box width. Wider text will be clipped. There is no automatic wrapping; use
to start a new line. x Sets the annotation's x position. xanchor Sets the text box's horizontal position anchor This anchor binds the `x` position to the "left", "center" or "right" of the annotation. For example, if `x` is set to 1, `xref` to "paper" and `xanchor` to "right" then the right-most portion of the annotation lines up with the right-most edge of the plotting area. If "auto", the anchor is equivalent to "center" for data-referenced annotations or if there is an arrow, whereas for paper-referenced with no arrow, the anchor picked corresponds to the closest side. xshift Shifts the position of the whole annotation and arrow to the right (positive) or left (negative) by this many pixels. y Sets the annotation's y position. yanchor Sets the text box's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the annotation. For example, if `y` is set to 1, `yref` to "paper" and `yanchor` to "top" then the top- most portion of the annotation lines up with the top-most edge of the plotting area. If "auto", the anchor is equivalent to "middle" for data-referenced annotations or if there is an arrow, whereas for paper-referenced with no arrow, the anchor picked corresponds to the closest side. yshift Shifts the position of the whole annotation and arrow up (positive) or down (negative) by this many pixels. z Sets the annotation's z position. """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/xaxis/0000755000175000017500000000000013573746614023532 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/xaxis/tickformatstop/0000755000175000017500000000000013573746614026603 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/xaxis/tickformatstop/__init__.py0000644000175000017500000000534313573721540030710 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="value", parent_name="layout.scene.xaxis.tickformatstop", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="layout.scene.xaxis.tickformatstop", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="layout.scene.xaxis.tickformatstop", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EnabledValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="enabled", parent_name="layout.scene.xaxis.tickformatstop", **kwargs ): super(EnabledValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DtickrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="dtickrange", parent_name="layout.scene.xaxis.tickformatstop", **kwargs ): super(DtickrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "plot"}, {"valType": "any", "editType": "plot"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/xaxis/title/0000755000175000017500000000000013573746614024653 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/xaxis/title/__init__.py0000644000175000017500000000365613573721540026765 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="text", parent_name="layout.scene.xaxis.title", **kwargs ): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="layout.scene.xaxis.title", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/xaxis/title/font/0000755000175000017500000000000013573746614025621 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/xaxis/title/font/__init__.py0000644000175000017500000000305313573721540027722 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="layout.scene.xaxis.title.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="layout.scene.xaxis.title.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="layout.scene.xaxis.title.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/xaxis/__init__.py0000644000175000017500000007727413573721542025655 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ZerolinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="zerolinewidth", parent_name="layout.scene.xaxis", **kwargs ): super(ZerolinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ZerolinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="zerolinecolor", parent_name="layout.scene.xaxis", **kwargs ): super(ZerolinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ZerolineValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="zeroline", parent_name="layout.scene.xaxis", **kwargs ): super(ZerolineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="visible", parent_name="layout.scene.xaxis", **kwargs ): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TypeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="type", parent_name="layout.scene.xaxis", **kwargs): super(TypeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["-", "linear", "log", "date", "category"]), **kwargs ) import _plotly_utils.basevalidators class TitleValidator(_plotly_utils.basevalidators.TitleValidator): def __init__(self, plotly_name="title", parent_name="layout.scene.xaxis", **kwargs): super(TitleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Title"), data_docs=kwargs.pop( "data_docs", """ font Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. text Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """, ), **kwargs ) import _plotly_utils.basevalidators class TickwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="tickwidth", parent_name="layout.scene.xaxis", **kwargs ): super(TickwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickvalssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="tickvalssrc", parent_name="layout.scene.xaxis", **kwargs ): super(TickvalssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickvalsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="tickvals", parent_name="layout.scene.xaxis", **kwargs ): super(TickvalsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="ticktextsrc", parent_name="layout.scene.xaxis", **kwargs ): super(TicktextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicktextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="ticktext", parent_name="layout.scene.xaxis", **kwargs ): super(TicktextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="ticksuffix", parent_name="layout.scene.xaxis", **kwargs ): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TicksValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="ticks", parent_name="layout.scene.xaxis", **kwargs): super(TicksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["outside", "inside", ""]), **kwargs ) import _plotly_utils.basevalidators class TickprefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickprefix", parent_name="layout.scene.xaxis", **kwargs ): super(TickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="tickmode", parent_name="layout.scene.xaxis", **kwargs ): super(TickmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "linear", "array"]), **kwargs ) import _plotly_utils.basevalidators class TicklenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ticklen", parent_name="layout.scene.xaxis", **kwargs ): super(TicklenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickformatstopValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickformatstopdefaults", parent_name="layout.scene.xaxis", **kwargs ): super(TickformatstopValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatstopsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="tickformatstops", parent_name="layout.scene.xaxis", **kwargs ): super(TickformatstopsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickformat", parent_name="layout.scene.xaxis", **kwargs ): super(TickformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickfont", parent_name="layout.scene.xaxis", **kwargs ): super(TickfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class TickcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="tickcolor", parent_name="layout.scene.xaxis", **kwargs ): super(TickcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__( self, plotly_name="tickangle", parent_name="layout.scene.xaxis", **kwargs ): super(TickangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="tick0", parent_name="layout.scene.xaxis", **kwargs): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SpikethicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="spikethickness", parent_name="layout.scene.xaxis", **kwargs ): super(SpikethicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SpikesidesValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="spikesides", parent_name="layout.scene.xaxis", **kwargs ): super(SpikesidesValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SpikecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="spikecolor", parent_name="layout.scene.xaxis", **kwargs ): super(SpikecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowticksuffixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showticksuffix", parent_name="layout.scene.xaxis", **kwargs ): super(ShowticksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowtickprefixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showtickprefix", parent_name="layout.scene.xaxis", **kwargs ): super(ShowtickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowticklabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showticklabels", parent_name="layout.scene.xaxis", **kwargs ): super(ShowticklabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowspikesValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showspikes", parent_name="layout.scene.xaxis", **kwargs ): super(ShowspikesValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ShowlineValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showline", parent_name="layout.scene.xaxis", **kwargs ): super(ShowlineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowgridValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showgrid", parent_name="layout.scene.xaxis", **kwargs ): super(ShowgridValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowexponentValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showexponent", parent_name="layout.scene.xaxis", **kwargs ): super(ShowexponentValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowbackgroundValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showbackground", parent_name="layout.scene.xaxis", **kwargs ): super(ShowbackgroundValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ShowaxeslabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showaxeslabels", parent_name="layout.scene.xaxis", **kwargs ): super(ShowaxeslabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SeparatethousandsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="separatethousands", parent_name="layout.scene.xaxis", **kwargs ): super(SeparatethousandsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class RangemodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="rangemode", parent_name="layout.scene.xaxis", **kwargs ): super(RangemodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["normal", "tozero", "nonnegative"]), **kwargs ) import _plotly_utils.basevalidators class RangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="range", parent_name="layout.scene.xaxis", **kwargs): super(RangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, anim=kwargs.pop("anim", False), edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"autorange": False}), items=kwargs.pop( "items", [ { "valType": "any", "editType": "plot", "impliedEdits": {"^autorange": False}, }, { "valType": "any", "editType": "plot", "impliedEdits": {"^autorange": False}, }, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NticksValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="nticks", parent_name="layout.scene.xaxis", **kwargs ): super(NticksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class MirrorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="mirror", parent_name="layout.scene.xaxis", **kwargs ): super(MirrorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", [True, "ticks", False, "all", "allticks"]), **kwargs ) import _plotly_utils.basevalidators class LinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="linewidth", parent_name="layout.scene.xaxis", **kwargs ): super(LinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="linecolor", parent_name="layout.scene.xaxis", **kwargs ): super(LinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class HoverformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="hoverformat", parent_name="layout.scene.xaxis", **kwargs ): super(HoverformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class GridwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="gridwidth", parent_name="layout.scene.xaxis", **kwargs ): super(GridwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class GridcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="gridcolor", parent_name="layout.scene.xaxis", **kwargs ): super(GridcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ExponentformatValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="exponentformat", parent_name="layout.scene.xaxis", **kwargs ): super(ExponentformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "e", "E", "power", "SI", "B"]), **kwargs ) import _plotly_utils.basevalidators class DtickValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="dtick", parent_name="layout.scene.xaxis", **kwargs): super(DtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="layout.scene.xaxis", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class CategoryorderValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="categoryorder", parent_name="layout.scene.xaxis", **kwargs ): super(CategoryorderValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "trace", "category ascending", "category descending", "array", "total ascending", "total descending", "min ascending", "min descending", "max ascending", "max descending", "sum ascending", "sum descending", "mean ascending", "mean descending", "median ascending", "median descending", ], ), **kwargs ) import _plotly_utils.basevalidators class CategoryarraysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="categoryarraysrc", parent_name="layout.scene.xaxis", **kwargs ): super(CategoryarraysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CategoryarrayValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="categoryarray", parent_name="layout.scene.xaxis", **kwargs ): super(CategoryarrayValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class CalendarValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="calendar", parent_name="layout.scene.xaxis", **kwargs ): super(CalendarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "gregorian", "chinese", "coptic", "discworld", "ethiopian", "hebrew", "islamic", "julian", "mayan", "nanakshahi", "nepali", "persian", "jalali", "taiwan", "thai", "ummalqura", ], ), **kwargs ) import _plotly_utils.basevalidators class BackgroundcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="backgroundcolor", parent_name="layout.scene.xaxis", **kwargs ): super(BackgroundcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AutorangeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="autorange", parent_name="layout.scene.xaxis", **kwargs ): super(AutorangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "reversed"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/xaxis/tickfont/0000755000175000017500000000000013573746614025353 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/xaxis/tickfont/__init__.py0000644000175000017500000000301513573721540027452 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="layout.scene.xaxis.tickfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="layout.scene.xaxis.tickfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="layout.scene.xaxis.tickfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/zaxis/0000755000175000017500000000000013573746614023534 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/zaxis/tickformatstop/0000755000175000017500000000000013573746614026605 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/zaxis/tickformatstop/__init__.py0000644000175000017500000000534313573721540030712 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="value", parent_name="layout.scene.zaxis.tickformatstop", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="layout.scene.zaxis.tickformatstop", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="layout.scene.zaxis.tickformatstop", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EnabledValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="enabled", parent_name="layout.scene.zaxis.tickformatstop", **kwargs ): super(EnabledValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DtickrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="dtickrange", parent_name="layout.scene.zaxis.tickformatstop", **kwargs ): super(DtickrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "plot"}, {"valType": "any", "editType": "plot"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/zaxis/title/0000755000175000017500000000000013573746614024655 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/zaxis/title/__init__.py0000644000175000017500000000365613573721540026767 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="text", parent_name="layout.scene.zaxis.title", **kwargs ): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="layout.scene.zaxis.title", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/zaxis/title/font/0000755000175000017500000000000013573746614025623 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/zaxis/title/font/__init__.py0000644000175000017500000000305313573721540027724 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="layout.scene.zaxis.title.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="layout.scene.zaxis.title.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="layout.scene.zaxis.title.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/zaxis/__init__.py0000644000175000017500000007727413573721542025657 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ZerolinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="zerolinewidth", parent_name="layout.scene.zaxis", **kwargs ): super(ZerolinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ZerolinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="zerolinecolor", parent_name="layout.scene.zaxis", **kwargs ): super(ZerolinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ZerolineValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="zeroline", parent_name="layout.scene.zaxis", **kwargs ): super(ZerolineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="visible", parent_name="layout.scene.zaxis", **kwargs ): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TypeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="type", parent_name="layout.scene.zaxis", **kwargs): super(TypeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["-", "linear", "log", "date", "category"]), **kwargs ) import _plotly_utils.basevalidators class TitleValidator(_plotly_utils.basevalidators.TitleValidator): def __init__(self, plotly_name="title", parent_name="layout.scene.zaxis", **kwargs): super(TitleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Title"), data_docs=kwargs.pop( "data_docs", """ font Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. text Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """, ), **kwargs ) import _plotly_utils.basevalidators class TickwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="tickwidth", parent_name="layout.scene.zaxis", **kwargs ): super(TickwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickvalssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="tickvalssrc", parent_name="layout.scene.zaxis", **kwargs ): super(TickvalssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickvalsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="tickvals", parent_name="layout.scene.zaxis", **kwargs ): super(TickvalsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="ticktextsrc", parent_name="layout.scene.zaxis", **kwargs ): super(TicktextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicktextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="ticktext", parent_name="layout.scene.zaxis", **kwargs ): super(TicktextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="ticksuffix", parent_name="layout.scene.zaxis", **kwargs ): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TicksValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="ticks", parent_name="layout.scene.zaxis", **kwargs): super(TicksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["outside", "inside", ""]), **kwargs ) import _plotly_utils.basevalidators class TickprefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickprefix", parent_name="layout.scene.zaxis", **kwargs ): super(TickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="tickmode", parent_name="layout.scene.zaxis", **kwargs ): super(TickmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "linear", "array"]), **kwargs ) import _plotly_utils.basevalidators class TicklenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ticklen", parent_name="layout.scene.zaxis", **kwargs ): super(TicklenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickformatstopValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickformatstopdefaults", parent_name="layout.scene.zaxis", **kwargs ): super(TickformatstopValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatstopsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="tickformatstops", parent_name="layout.scene.zaxis", **kwargs ): super(TickformatstopsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickformat", parent_name="layout.scene.zaxis", **kwargs ): super(TickformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickfont", parent_name="layout.scene.zaxis", **kwargs ): super(TickfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class TickcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="tickcolor", parent_name="layout.scene.zaxis", **kwargs ): super(TickcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__( self, plotly_name="tickangle", parent_name="layout.scene.zaxis", **kwargs ): super(TickangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="tick0", parent_name="layout.scene.zaxis", **kwargs): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SpikethicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="spikethickness", parent_name="layout.scene.zaxis", **kwargs ): super(SpikethicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SpikesidesValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="spikesides", parent_name="layout.scene.zaxis", **kwargs ): super(SpikesidesValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SpikecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="spikecolor", parent_name="layout.scene.zaxis", **kwargs ): super(SpikecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowticksuffixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showticksuffix", parent_name="layout.scene.zaxis", **kwargs ): super(ShowticksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowtickprefixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showtickprefix", parent_name="layout.scene.zaxis", **kwargs ): super(ShowtickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowticklabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showticklabels", parent_name="layout.scene.zaxis", **kwargs ): super(ShowticklabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowspikesValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showspikes", parent_name="layout.scene.zaxis", **kwargs ): super(ShowspikesValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ShowlineValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showline", parent_name="layout.scene.zaxis", **kwargs ): super(ShowlineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowgridValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showgrid", parent_name="layout.scene.zaxis", **kwargs ): super(ShowgridValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowexponentValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showexponent", parent_name="layout.scene.zaxis", **kwargs ): super(ShowexponentValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowbackgroundValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showbackground", parent_name="layout.scene.zaxis", **kwargs ): super(ShowbackgroundValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ShowaxeslabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showaxeslabels", parent_name="layout.scene.zaxis", **kwargs ): super(ShowaxeslabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SeparatethousandsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="separatethousands", parent_name="layout.scene.zaxis", **kwargs ): super(SeparatethousandsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class RangemodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="rangemode", parent_name="layout.scene.zaxis", **kwargs ): super(RangemodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["normal", "tozero", "nonnegative"]), **kwargs ) import _plotly_utils.basevalidators class RangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="range", parent_name="layout.scene.zaxis", **kwargs): super(RangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, anim=kwargs.pop("anim", False), edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"autorange": False}), items=kwargs.pop( "items", [ { "valType": "any", "editType": "plot", "impliedEdits": {"^autorange": False}, }, { "valType": "any", "editType": "plot", "impliedEdits": {"^autorange": False}, }, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NticksValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="nticks", parent_name="layout.scene.zaxis", **kwargs ): super(NticksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class MirrorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="mirror", parent_name="layout.scene.zaxis", **kwargs ): super(MirrorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", [True, "ticks", False, "all", "allticks"]), **kwargs ) import _plotly_utils.basevalidators class LinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="linewidth", parent_name="layout.scene.zaxis", **kwargs ): super(LinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="linecolor", parent_name="layout.scene.zaxis", **kwargs ): super(LinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class HoverformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="hoverformat", parent_name="layout.scene.zaxis", **kwargs ): super(HoverformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class GridwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="gridwidth", parent_name="layout.scene.zaxis", **kwargs ): super(GridwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class GridcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="gridcolor", parent_name="layout.scene.zaxis", **kwargs ): super(GridcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ExponentformatValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="exponentformat", parent_name="layout.scene.zaxis", **kwargs ): super(ExponentformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "e", "E", "power", "SI", "B"]), **kwargs ) import _plotly_utils.basevalidators class DtickValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="dtick", parent_name="layout.scene.zaxis", **kwargs): super(DtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="layout.scene.zaxis", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class CategoryorderValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="categoryorder", parent_name="layout.scene.zaxis", **kwargs ): super(CategoryorderValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "trace", "category ascending", "category descending", "array", "total ascending", "total descending", "min ascending", "min descending", "max ascending", "max descending", "sum ascending", "sum descending", "mean ascending", "mean descending", "median ascending", "median descending", ], ), **kwargs ) import _plotly_utils.basevalidators class CategoryarraysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="categoryarraysrc", parent_name="layout.scene.zaxis", **kwargs ): super(CategoryarraysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CategoryarrayValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="categoryarray", parent_name="layout.scene.zaxis", **kwargs ): super(CategoryarrayValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class CalendarValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="calendar", parent_name="layout.scene.zaxis", **kwargs ): super(CalendarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "gregorian", "chinese", "coptic", "discworld", "ethiopian", "hebrew", "islamic", "julian", "mayan", "nanakshahi", "nepali", "persian", "jalali", "taiwan", "thai", "ummalqura", ], ), **kwargs ) import _plotly_utils.basevalidators class BackgroundcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="backgroundcolor", parent_name="layout.scene.zaxis", **kwargs ): super(BackgroundcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AutorangeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="autorange", parent_name="layout.scene.zaxis", **kwargs ): super(AutorangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "reversed"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/zaxis/tickfont/0000755000175000017500000000000013573746614025355 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/zaxis/tickfont/__init__.py0000644000175000017500000000301513573721540027454 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="layout.scene.zaxis.tickfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="layout.scene.zaxis.tickfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="layout.scene.zaxis.tickfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/domain/0000755000175000017500000000000013573746614023645 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/domain/__init__.py0000644000175000017500000000455313573721540025754 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="y", parent_name="layout.scene.domain", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), items=kwargs.pop( "items", [ {"valType": "number", "min": 0, "max": 1, "editType": "plot"}, {"valType": "number", "min": 0, "max": 1, "editType": "plot"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="x", parent_name="layout.scene.domain", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), items=kwargs.pop( "items", [ {"valType": "number", "min": 0, "max": 1, "editType": "plot"}, {"valType": "number", "min": 0, "max": 1, "editType": "plot"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class RowValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="row", parent_name="layout.scene.domain", **kwargs): super(RowValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColumnValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="column", parent_name="layout.scene.domain", **kwargs ): super(ColumnValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/aspectratio/0000755000175000017500000000000013573746614024714 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/scene/aspectratio/__init__.py0000644000175000017500000000327613573721540027024 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ZValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="z", parent_name="layout.scene.aspectratio", **kwargs ): super(ZValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"^aspectmode": "manual"}), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="y", parent_name="layout.scene.aspectratio", **kwargs ): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"^aspectmode": "manual"}), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="x", parent_name="layout.scene.aspectratio", **kwargs ): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"^aspectmode": "manual"}), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/angularaxis/0000755000175000017500000000000013573746614023617 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/angularaxis/__init__.py0000644000175000017500000001240713573721540025723 0ustar noahfxnoahfximport _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="visible", parent_name="layout.angularaxis", **kwargs ): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="ticksuffix", parent_name="layout.angularaxis", **kwargs ): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickorientationValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="tickorientation", parent_name="layout.angularaxis", **kwargs ): super(TickorientationValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["horizontal", "vertical"]), **kwargs ) import _plotly_utils.basevalidators class TicklenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ticklen", parent_name="layout.angularaxis", **kwargs ): super(TicklenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="tickcolor", parent_name="layout.angularaxis", **kwargs ): super(TickcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowticklabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showticklabels", parent_name="layout.angularaxis", **kwargs ): super(ShowticklabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowlineValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showline", parent_name="layout.angularaxis", **kwargs ): super(ShowlineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class RangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="range", parent_name="layout.angularaxis", **kwargs): super(RangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), items=kwargs.pop( "items", [ {"valType": "number", "dflt": 0, "editType": "plot"}, {"valType": "number", "dflt": 360, "editType": "plot"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class EndpaddingValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="endpadding", parent_name="layout.angularaxis", **kwargs ): super(EndpaddingValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class DomainValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="domain", parent_name="layout.angularaxis", **kwargs ): super(DomainValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), items=kwargs.pop( "items", [ {"valType": "number", "min": 0, "max": 1, "editType": "plot"}, {"valType": "number", "min": 0, "max": 1, "editType": "plot"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/radialaxis/0000755000175000017500000000000013573746614023422 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/radialaxis/__init__.py0000644000175000017500000001326713573721540025533 0ustar noahfxnoahfximport _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="visible", parent_name="layout.radialaxis", **kwargs ): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="ticksuffix", parent_name="layout.radialaxis", **kwargs ): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickorientationValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="tickorientation", parent_name="layout.radialaxis", **kwargs ): super(TickorientationValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["horizontal", "vertical"]), **kwargs ) import _plotly_utils.basevalidators class TicklenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ticklen", parent_name="layout.radialaxis", **kwargs ): super(TicklenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="tickcolor", parent_name="layout.radialaxis", **kwargs ): super(TickcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowticklabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showticklabels", parent_name="layout.radialaxis", **kwargs ): super(ShowticklabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowlineValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showline", parent_name="layout.radialaxis", **kwargs ): super(ShowlineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class RangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="range", parent_name="layout.radialaxis", **kwargs): super(RangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), items=kwargs.pop( "items", [ {"valType": "number", "editType": "plot"}, {"valType": "number", "editType": "plot"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class OrientationValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="orientation", parent_name="layout.radialaxis", **kwargs ): super(OrientationValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EndpaddingValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="endpadding", parent_name="layout.radialaxis", **kwargs ): super(EndpaddingValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class DomainValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="domain", parent_name="layout.radialaxis", **kwargs): super(DomainValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), items=kwargs.pop( "items", [ {"valType": "number", "min": 0, "max": 1, "editType": "plot"}, {"valType": "number", "min": 0, "max": 1, "editType": "plot"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/transition/0000755000175000017500000000000013573746614023473 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/transition/__init__.py0000644000175000017500000000534013573721541025576 0ustar noahfxnoahfximport _plotly_utils.basevalidators class OrderingValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="ordering", parent_name="layout.transition", **kwargs ): super(OrderingValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["layout first", "traces first"]), **kwargs ) import _plotly_utils.basevalidators class EasingValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="easing", parent_name="layout.transition", **kwargs): super(EasingValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "linear", "quad", "cubic", "sin", "exp", "circle", "elastic", "back", "bounce", "linear-in", "quad-in", "cubic-in", "sin-in", "exp-in", "circle-in", "elastic-in", "back-in", "bounce-in", "linear-out", "quad-out", "cubic-out", "sin-out", "exp-out", "circle-out", "elastic-out", "back-out", "bounce-out", "linear-in-out", "quad-in-out", "cubic-in-out", "sin-in-out", "exp-in-out", "circle-in-out", "elastic-in-out", "back-in-out", "bounce-in-out", ], ), **kwargs ) import _plotly_utils.basevalidators class DurationValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="duration", parent_name="layout.transition", **kwargs ): super(DurationValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/annotation/0000755000175000017500000000000013573746614023453 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/annotation/hoverlabel/0000755000175000017500000000000013573746614025576 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/annotation/hoverlabel/__init__.py0000644000175000017500000000474313573721540027706 0ustar noahfxnoahfximport _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="layout.annotation.hoverlabel", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="layout.annotation.hoverlabel", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="layout.annotation.hoverlabel", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/annotation/hoverlabel/font/0000755000175000017500000000000013573746614026544 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/annotation/hoverlabel/font/__init__.py0000644000175000017500000000316613573721540030652 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="layout.annotation.hoverlabel.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="layout.annotation.hoverlabel.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="layout.annotation.hoverlabel.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/annotation/__init__.py0000644000175000017500000005535613573721541025572 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YshiftValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="yshift", parent_name="layout.annotation", **kwargs): super(YshiftValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+arraydraw"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class YrefValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="yref", parent_name="layout.annotation", **kwargs): super(YrefValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["paper", "/^y([2-9]|[1-9][0-9]+)?$/"]), **kwargs ) import _plotly_utils.basevalidators class YclickValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="yclick", parent_name="layout.annotation", **kwargs): super(YclickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="yanchor", parent_name="layout.annotation", **kwargs ): super(YanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+arraydraw"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "top", "middle", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="y", parent_name="layout.annotation", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+arraydraw"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XshiftValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="xshift", parent_name="layout.annotation", **kwargs): super(XshiftValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+arraydraw"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XrefValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="xref", parent_name="layout.annotation", **kwargs): super(XrefValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["paper", "/^x([2-9]|[1-9][0-9]+)?$/"]), **kwargs ) import _plotly_utils.basevalidators class XclickValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="xclick", parent_name="layout.annotation", **kwargs): super(XclickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="xanchor", parent_name="layout.annotation", **kwargs ): super(XanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+arraydraw"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "left", "center", "right"]), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="x", parent_name="layout.annotation", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+arraydraw"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="layout.annotation", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+arraydraw"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="visible", parent_name="layout.annotation", **kwargs ): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+arraydraw"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ValignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="valign", parent_name="layout.annotation", **kwargs): super(ValignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["top", "middle", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class TextangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__( self, plotly_name="textangle", parent_name="layout.annotation", **kwargs ): super(TextangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+arraydraw"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="text", parent_name="layout.annotation", **kwargs): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+arraydraw"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="layout.annotation", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class StartstandoffValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="startstandoff", parent_name="layout.annotation", **kwargs ): super(StartstandoffValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+arraydraw"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class StartarrowsizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="startarrowsize", parent_name="layout.annotation", **kwargs ): super(StartarrowsizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+arraydraw"), min=kwargs.pop("min", 0.3), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class StartarrowheadValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="startarrowhead", parent_name="layout.annotation", **kwargs ): super(StartarrowheadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), max=kwargs.pop("max", 8), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class StandoffValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="standoff", parent_name="layout.annotation", **kwargs ): super(StandoffValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+arraydraw"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowarrowValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showarrow", parent_name="layout.annotation", **kwargs ): super(ShowarrowValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+arraydraw"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="opacity", parent_name="layout.annotation", **kwargs ): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="layout.annotation", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class HovertextValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="hovertext", parent_name="layout.annotation", **kwargs ): super(HovertextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverlabelValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="hoverlabel", parent_name="layout.annotation", **kwargs ): super(HoverlabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Hoverlabel"), data_docs=kwargs.pop( "data_docs", """ bgcolor Sets the background color of the hover label. By default uses the annotation's `bgcolor` made opaque, or white if it was transparent. bordercolor Sets the border color of the hover label. By default uses either dark grey or white, for maximum contrast with `hoverlabel.bgcolor`. font Sets the hover label text font. By default uses the global hover font and size, with color from `hoverlabel.bordercolor`. """, ), **kwargs ) import _plotly_utils.basevalidators class HeightValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="height", parent_name="layout.annotation", **kwargs): super(HeightValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+arraydraw"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="font", parent_name="layout.annotation", **kwargs): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class ClicktoshowValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="clicktoshow", parent_name="layout.annotation", **kwargs ): super(ClicktoshowValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", [False, "onoff", "onout"]), **kwargs ) import _plotly_utils.basevalidators class CaptureeventsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="captureevents", parent_name="layout.annotation", **kwargs ): super(CaptureeventsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BorderwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="borderwidth", parent_name="layout.annotation", **kwargs ): super(BorderwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+arraydraw"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BorderpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="borderpad", parent_name="layout.annotation", **kwargs ): super(BorderpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+arraydraw"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="layout.annotation", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="layout.annotation", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AyrefValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="ayref", parent_name="layout.annotation", **kwargs): super(AyrefValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["pixel", "/^y([2-9]|[1-9][0-9]+)?$/"]), **kwargs ) import _plotly_utils.basevalidators class AyValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="ay", parent_name="layout.annotation", **kwargs): super(AyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+arraydraw"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AxrefValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="axref", parent_name="layout.annotation", **kwargs): super(AxrefValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["pixel", "/^x([2-9]|[1-9][0-9]+)?$/"]), **kwargs ) import _plotly_utils.basevalidators class AxValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="ax", parent_name="layout.annotation", **kwargs): super(AxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+arraydraw"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ArrowwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="arrowwidth", parent_name="layout.annotation", **kwargs ): super(ArrowwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+arraydraw"), min=kwargs.pop("min", 0.1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ArrowsizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="arrowsize", parent_name="layout.annotation", **kwargs ): super(ArrowsizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+arraydraw"), min=kwargs.pop("min", 0.3), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ArrowsideValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__( self, plotly_name="arrowside", parent_name="layout.annotation", **kwargs ): super(ArrowsideValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), extras=kwargs.pop("extras", ["none"]), flags=kwargs.pop("flags", ["end", "start"]), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ArrowheadValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="arrowhead", parent_name="layout.annotation", **kwargs ): super(ArrowheadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), max=kwargs.pop("max", 8), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ArrowcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="arrowcolor", parent_name="layout.annotation", **kwargs ): super(ArrowcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="align", parent_name="layout.annotation", **kwargs): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "center", "right"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/annotation/font/0000755000175000017500000000000013573746614024421 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/annotation/font/__init__.py0000644000175000017500000000302713573721540026523 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="layout.annotation.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+arraydraw"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="layout.annotation.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+arraydraw"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="layout.annotation.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/title/0000755000175000017500000000000013573746614022422 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/title/pad/0000755000175000017500000000000013573746614023166 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/title/pad/__init__.py0000644000175000017500000000334613573721541025275 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="t", parent_name="layout.title.pad", **kwargs): super(TValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "layoutstyle"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class RValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="r", parent_name="layout.title.pad", **kwargs): super(RValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "layoutstyle"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="l", parent_name="layout.title.pad", **kwargs): super(LValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "layoutstyle"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="b", parent_name="layout.title.pad", **kwargs): super(BValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "layoutstyle"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/title/__init__.py0000644000175000017500000001356013573721541024530 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YrefValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="yref", parent_name="layout.title", **kwargs): super(YrefValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "layoutstyle"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["container", "paper"]), **kwargs ) import _plotly_utils.basevalidators class YanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="yanchor", parent_name="layout.title", **kwargs): super(YanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "layoutstyle"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "top", "middle", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="y", parent_name="layout.title", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "layoutstyle"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XrefValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="xref", parent_name="layout.title", **kwargs): super(XrefValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "layoutstyle"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["container", "paper"]), **kwargs ) import _plotly_utils.basevalidators class XanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="xanchor", parent_name="layout.title", **kwargs): super(XanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "layoutstyle"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "left", "center", "right"]), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="x", parent_name="layout.title", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "layoutstyle"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="text", parent_name="layout.title", **kwargs): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "layoutstyle"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class PadValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="pad", parent_name="layout.title", **kwargs): super(PadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Pad"), data_docs=kwargs.pop( "data_docs", """ b The amount of padding (in px) along the bottom of the component. l The amount of padding (in px) on the left side of the component. r The amount of padding (in px) on the right side of the component. t The amount of padding (in px) along the top of the component. """, ), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="font", parent_name="layout.title", **kwargs): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/title/font/0000755000175000017500000000000013573746614023370 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/title/font/__init__.py0000644000175000017500000000273213573721541025475 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="size", parent_name="layout.title.font", **kwargs): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "layoutstyle"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="family", parent_name="layout.title.font", **kwargs): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "layoutstyle"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="layout.title.font", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "layoutstyle"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/ternary/0000755000175000017500000000000013573746614022765 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/ternary/__init__.py0000644000175000017500000010373613573721541025100 0ustar noahfxnoahfximport _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="uirevision", parent_name="layout.ternary", **kwargs ): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SumValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="sum", parent_name="layout.ternary", **kwargs): super(SumValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DomainValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="domain", parent_name="layout.ternary", **kwargs): super(DomainValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Domain"), data_docs=kwargs.pop( "data_docs", """ column If there is a layout grid, use the domain for this column in the grid for this ternary subplot . row If there is a layout grid, use the domain for this row in the grid for this ternary subplot . x Sets the horizontal domain of this ternary subplot (in plot fraction). y Sets the vertical domain of this ternary subplot (in plot fraction). """, ), **kwargs ) import _plotly_utils.basevalidators class CaxisValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="caxis", parent_name="layout.ternary", **kwargs): super(CaxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Caxis"), data_docs=kwargs.pop( "data_docs", """ color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. gridcolor Sets the color of the grid lines. gridwidth Sets the width (in px) of the grid lines. hoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" layer Sets the layer on which this axis is displayed. If *above traces*, this axis is displayed above all the subplot's traces If *below traces*, this axis is displayed below all the subplot's traces, but above the grid lines. Useful when used together with scatter-like traces with `cliponaxis` set to False to show markers and/or text nodes above this axis. linecolor Sets the axis line color. linewidth Sets the width (in px) of the axis line. min The minimum value visible on this axis. The maximum is determined by the sum minus the minimum values of the other two axes. The full view corresponds to all the minima set to zero. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showgrid Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. showline Determines whether or not a line bounding this axis is drawn. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the tick font. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.layout.ternary. caxis.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.lay out.ternary.caxis.tickformatstopdefaults), sets the default property values to use for elements of layout.ternary.caxis.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.layout.ternary.caxis.Title instance or dict with compatible properties titlefont Deprecated: Please use layout.ternary.caxis.title.font instead. Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. uirevision Controls persistence of user-driven changes in axis `min`, and `title` if in `editable: true` configuration. Defaults to `ternary.uirevision`. """, ), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="bgcolor", parent_name="layout.ternary", **kwargs): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BaxisValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="baxis", parent_name="layout.ternary", **kwargs): super(BaxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Baxis"), data_docs=kwargs.pop( "data_docs", """ color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. gridcolor Sets the color of the grid lines. gridwidth Sets the width (in px) of the grid lines. hoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" layer Sets the layer on which this axis is displayed. If *above traces*, this axis is displayed above all the subplot's traces If *below traces*, this axis is displayed below all the subplot's traces, but above the grid lines. Useful when used together with scatter-like traces with `cliponaxis` set to False to show markers and/or text nodes above this axis. linecolor Sets the axis line color. linewidth Sets the width (in px) of the axis line. min The minimum value visible on this axis. The maximum is determined by the sum minus the minimum values of the other two axes. The full view corresponds to all the minima set to zero. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showgrid Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. showline Determines whether or not a line bounding this axis is drawn. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the tick font. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.layout.ternary. baxis.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.lay out.ternary.baxis.tickformatstopdefaults), sets the default property values to use for elements of layout.ternary.baxis.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.layout.ternary.baxis.Title instance or dict with compatible properties titlefont Deprecated: Please use layout.ternary.baxis.title.font instead. Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. uirevision Controls persistence of user-driven changes in axis `min`, and `title` if in `editable: true` configuration. Defaults to `ternary.uirevision`. """, ), **kwargs ) import _plotly_utils.basevalidators class AaxisValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="aaxis", parent_name="layout.ternary", **kwargs): super(AaxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Aaxis"), data_docs=kwargs.pop( "data_docs", """ color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. gridcolor Sets the color of the grid lines. gridwidth Sets the width (in px) of the grid lines. hoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" layer Sets the layer on which this axis is displayed. If *above traces*, this axis is displayed above all the subplot's traces If *below traces*, this axis is displayed below all the subplot's traces, but above the grid lines. Useful when used together with scatter-like traces with `cliponaxis` set to False to show markers and/or text nodes above this axis. linecolor Sets the axis line color. linewidth Sets the width (in px) of the axis line. min The minimum value visible on this axis. The maximum is determined by the sum minus the minimum values of the other two axes. The full view corresponds to all the minima set to zero. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showgrid Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. showline Determines whether or not a line bounding this axis is drawn. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the tick font. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.layout.ternary. aaxis.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.lay out.ternary.aaxis.tickformatstopdefaults), sets the default property values to use for elements of layout.ternary.aaxis.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.layout.ternary.aaxis.Title instance or dict with compatible properties titlefont Deprecated: Please use layout.ternary.aaxis.title.font instead. Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. uirevision Controls persistence of user-driven changes in axis `min`, and `title` if in `editable: true` configuration. Defaults to `ternary.uirevision`. """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/ternary/aaxis/0000755000175000017500000000000013573746614024072 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/ternary/aaxis/tickformatstop/0000755000175000017500000000000013573746614027143 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/ternary/aaxis/tickformatstop/__init__.py0000644000175000017500000000535513573721540031253 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="value", parent_name="layout.ternary.aaxis.tickformatstop", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="layout.ternary.aaxis.tickformatstop", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="layout.ternary.aaxis.tickformatstop", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EnabledValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="enabled", parent_name="layout.ternary.aaxis.tickformatstop", **kwargs ): super(EnabledValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DtickrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="dtickrange", parent_name="layout.ternary.aaxis.tickformatstop", **kwargs ): super(DtickrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "plot"}, {"valType": "any", "editType": "plot"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/ternary/aaxis/title/0000755000175000017500000000000013573746614025213 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/ternary/aaxis/title/__init__.py0000644000175000017500000000366213573721540027322 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="text", parent_name="layout.ternary.aaxis.title", **kwargs ): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="layout.ternary.aaxis.title", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/ternary/aaxis/title/font/0000755000175000017500000000000013573746614026161 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/ternary/aaxis/title/font/__init__.py0000644000175000017500000000314113573721540030260 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="layout.ternary.aaxis.title.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="layout.ternary.aaxis.title.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="layout.ternary.aaxis.title.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/ternary/aaxis/__init__.py0000644000175000017500000005324213573721541026201 0ustar noahfxnoahfximport _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="uirevision", parent_name="layout.ternary.aaxis", **kwargs ): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TitleValidator(_plotly_utils.basevalidators.TitleValidator): def __init__( self, plotly_name="title", parent_name="layout.ternary.aaxis", **kwargs ): super(TitleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Title"), data_docs=kwargs.pop( "data_docs", """ font Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. text Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """, ), **kwargs ) import _plotly_utils.basevalidators class TickwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="tickwidth", parent_name="layout.ternary.aaxis", **kwargs ): super(TickwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickvalssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="tickvalssrc", parent_name="layout.ternary.aaxis", **kwargs ): super(TickvalssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickvalsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="tickvals", parent_name="layout.ternary.aaxis", **kwargs ): super(TickvalsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="ticktextsrc", parent_name="layout.ternary.aaxis", **kwargs ): super(TicktextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicktextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="ticktext", parent_name="layout.ternary.aaxis", **kwargs ): super(TicktextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="ticksuffix", parent_name="layout.ternary.aaxis", **kwargs ): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TicksValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="ticks", parent_name="layout.ternary.aaxis", **kwargs ): super(TicksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["outside", "inside", ""]), **kwargs ) import _plotly_utils.basevalidators class TickprefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickprefix", parent_name="layout.ternary.aaxis", **kwargs ): super(TickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="tickmode", parent_name="layout.ternary.aaxis", **kwargs ): super(TickmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "linear", "array"]), **kwargs ) import _plotly_utils.basevalidators class TicklenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ticklen", parent_name="layout.ternary.aaxis", **kwargs ): super(TicklenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickformatstopValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickformatstopdefaults", parent_name="layout.ternary.aaxis", **kwargs ): super(TickformatstopValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatstopsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="tickformatstops", parent_name="layout.ternary.aaxis", **kwargs ): super(TickformatstopsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickformat", parent_name="layout.ternary.aaxis", **kwargs ): super(TickformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickfont", parent_name="layout.ternary.aaxis", **kwargs ): super(TickfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class TickcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="tickcolor", parent_name="layout.ternary.aaxis", **kwargs ): super(TickcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__( self, plotly_name="tickangle", parent_name="layout.ternary.aaxis", **kwargs ): super(TickangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="tick0", parent_name="layout.ternary.aaxis", **kwargs ): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowticksuffixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showticksuffix", parent_name="layout.ternary.aaxis", **kwargs ): super(ShowticksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowtickprefixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showtickprefix", parent_name="layout.ternary.aaxis", **kwargs ): super(ShowtickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowticklabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showticklabels", parent_name="layout.ternary.aaxis", **kwargs ): super(ShowticklabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowlineValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showline", parent_name="layout.ternary.aaxis", **kwargs ): super(ShowlineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowgridValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showgrid", parent_name="layout.ternary.aaxis", **kwargs ): super(ShowgridValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowexponentValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showexponent", parent_name="layout.ternary.aaxis", **kwargs ): super(ShowexponentValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class SeparatethousandsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="separatethousands", parent_name="layout.ternary.aaxis", **kwargs ): super(SeparatethousandsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NticksValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="nticks", parent_name="layout.ternary.aaxis", **kwargs ): super(NticksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class MinValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="min", parent_name="layout.ternary.aaxis", **kwargs): super(MinValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="linewidth", parent_name="layout.ternary.aaxis", **kwargs ): super(LinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="linecolor", parent_name="layout.ternary.aaxis", **kwargs ): super(LinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LayerValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="layer", parent_name="layout.ternary.aaxis", **kwargs ): super(LayerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["above traces", "below traces"]), **kwargs ) import _plotly_utils.basevalidators class HoverformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="hoverformat", parent_name="layout.ternary.aaxis", **kwargs ): super(HoverformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class GridwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="gridwidth", parent_name="layout.ternary.aaxis", **kwargs ): super(GridwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class GridcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="gridcolor", parent_name="layout.ternary.aaxis", **kwargs ): super(GridcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ExponentformatValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="exponentformat", parent_name="layout.ternary.aaxis", **kwargs ): super(ExponentformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "e", "E", "power", "SI", "B"]), **kwargs ) import _plotly_utils.basevalidators class DtickValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="dtick", parent_name="layout.ternary.aaxis", **kwargs ): super(DtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="layout.ternary.aaxis", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/ternary/aaxis/tickfont/0000755000175000017500000000000013573746614025713 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/ternary/aaxis/tickfont/__init__.py0000644000175000017500000000305313573721541030015 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="layout.ternary.aaxis.tickfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="layout.ternary.aaxis.tickfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="layout.ternary.aaxis.tickfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/ternary/domain/0000755000175000017500000000000013573746614024234 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/ternary/domain/__init__.py0000644000175000017500000000460113573721541026336 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="y", parent_name="layout.ternary.domain", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), items=kwargs.pop( "items", [ {"valType": "number", "min": 0, "max": 1, "editType": "plot"}, {"valType": "number", "min": 0, "max": 1, "editType": "plot"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="x", parent_name="layout.ternary.domain", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), items=kwargs.pop( "items", [ {"valType": "number", "min": 0, "max": 1, "editType": "plot"}, {"valType": "number", "min": 0, "max": 1, "editType": "plot"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class RowValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="row", parent_name="layout.ternary.domain", **kwargs ): super(RowValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColumnValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="column", parent_name="layout.ternary.domain", **kwargs ): super(ColumnValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/ternary/caxis/0000755000175000017500000000000013573746614024074 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/ternary/caxis/tickformatstop/0000755000175000017500000000000013573746614027145 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/ternary/caxis/tickformatstop/__init__.py0000644000175000017500000000535513573721541031256 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="value", parent_name="layout.ternary.caxis.tickformatstop", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="layout.ternary.caxis.tickformatstop", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="layout.ternary.caxis.tickformatstop", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EnabledValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="enabled", parent_name="layout.ternary.caxis.tickformatstop", **kwargs ): super(EnabledValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DtickrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="dtickrange", parent_name="layout.ternary.caxis.tickformatstop", **kwargs ): super(DtickrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "plot"}, {"valType": "any", "editType": "plot"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/ternary/caxis/title/0000755000175000017500000000000013573746614025215 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/ternary/caxis/title/__init__.py0000644000175000017500000000366213573721540027324 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="text", parent_name="layout.ternary.caxis.title", **kwargs ): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="layout.ternary.caxis.title", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/ternary/caxis/title/font/0000755000175000017500000000000013573746614026163 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/ternary/caxis/title/font/__init__.py0000644000175000017500000000314113573721540030262 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="layout.ternary.caxis.title.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="layout.ternary.caxis.title.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="layout.ternary.caxis.title.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/ternary/caxis/__init__.py0000644000175000017500000005324213573721541026203 0ustar noahfxnoahfximport _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="uirevision", parent_name="layout.ternary.caxis", **kwargs ): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TitleValidator(_plotly_utils.basevalidators.TitleValidator): def __init__( self, plotly_name="title", parent_name="layout.ternary.caxis", **kwargs ): super(TitleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Title"), data_docs=kwargs.pop( "data_docs", """ font Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. text Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """, ), **kwargs ) import _plotly_utils.basevalidators class TickwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="tickwidth", parent_name="layout.ternary.caxis", **kwargs ): super(TickwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickvalssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="tickvalssrc", parent_name="layout.ternary.caxis", **kwargs ): super(TickvalssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickvalsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="tickvals", parent_name="layout.ternary.caxis", **kwargs ): super(TickvalsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="ticktextsrc", parent_name="layout.ternary.caxis", **kwargs ): super(TicktextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicktextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="ticktext", parent_name="layout.ternary.caxis", **kwargs ): super(TicktextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="ticksuffix", parent_name="layout.ternary.caxis", **kwargs ): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TicksValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="ticks", parent_name="layout.ternary.caxis", **kwargs ): super(TicksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["outside", "inside", ""]), **kwargs ) import _plotly_utils.basevalidators class TickprefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickprefix", parent_name="layout.ternary.caxis", **kwargs ): super(TickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="tickmode", parent_name="layout.ternary.caxis", **kwargs ): super(TickmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "linear", "array"]), **kwargs ) import _plotly_utils.basevalidators class TicklenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ticklen", parent_name="layout.ternary.caxis", **kwargs ): super(TicklenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickformatstopValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickformatstopdefaults", parent_name="layout.ternary.caxis", **kwargs ): super(TickformatstopValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatstopsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="tickformatstops", parent_name="layout.ternary.caxis", **kwargs ): super(TickformatstopsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickformat", parent_name="layout.ternary.caxis", **kwargs ): super(TickformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickfont", parent_name="layout.ternary.caxis", **kwargs ): super(TickfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class TickcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="tickcolor", parent_name="layout.ternary.caxis", **kwargs ): super(TickcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__( self, plotly_name="tickangle", parent_name="layout.ternary.caxis", **kwargs ): super(TickangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="tick0", parent_name="layout.ternary.caxis", **kwargs ): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowticksuffixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showticksuffix", parent_name="layout.ternary.caxis", **kwargs ): super(ShowticksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowtickprefixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showtickprefix", parent_name="layout.ternary.caxis", **kwargs ): super(ShowtickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowticklabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showticklabels", parent_name="layout.ternary.caxis", **kwargs ): super(ShowticklabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowlineValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showline", parent_name="layout.ternary.caxis", **kwargs ): super(ShowlineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowgridValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showgrid", parent_name="layout.ternary.caxis", **kwargs ): super(ShowgridValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowexponentValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showexponent", parent_name="layout.ternary.caxis", **kwargs ): super(ShowexponentValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class SeparatethousandsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="separatethousands", parent_name="layout.ternary.caxis", **kwargs ): super(SeparatethousandsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NticksValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="nticks", parent_name="layout.ternary.caxis", **kwargs ): super(NticksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class MinValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="min", parent_name="layout.ternary.caxis", **kwargs): super(MinValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="linewidth", parent_name="layout.ternary.caxis", **kwargs ): super(LinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="linecolor", parent_name="layout.ternary.caxis", **kwargs ): super(LinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LayerValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="layer", parent_name="layout.ternary.caxis", **kwargs ): super(LayerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["above traces", "below traces"]), **kwargs ) import _plotly_utils.basevalidators class HoverformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="hoverformat", parent_name="layout.ternary.caxis", **kwargs ): super(HoverformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class GridwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="gridwidth", parent_name="layout.ternary.caxis", **kwargs ): super(GridwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class GridcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="gridcolor", parent_name="layout.ternary.caxis", **kwargs ): super(GridcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ExponentformatValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="exponentformat", parent_name="layout.ternary.caxis", **kwargs ): super(ExponentformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "e", "E", "power", "SI", "B"]), **kwargs ) import _plotly_utils.basevalidators class DtickValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="dtick", parent_name="layout.ternary.caxis", **kwargs ): super(DtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="layout.ternary.caxis", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/ternary/caxis/tickfont/0000755000175000017500000000000013573746614025715 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/ternary/caxis/tickfont/__init__.py0000644000175000017500000000305313573721540030016 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="layout.ternary.caxis.tickfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="layout.ternary.caxis.tickfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="layout.ternary.caxis.tickfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/ternary/baxis/0000755000175000017500000000000013573746614024073 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/ternary/baxis/tickformatstop/0000755000175000017500000000000013573746614027144 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/ternary/baxis/tickformatstop/__init__.py0000644000175000017500000000535513573721540031254 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="value", parent_name="layout.ternary.baxis.tickformatstop", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="layout.ternary.baxis.tickformatstop", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="layout.ternary.baxis.tickformatstop", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EnabledValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="enabled", parent_name="layout.ternary.baxis.tickformatstop", **kwargs ): super(EnabledValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DtickrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="dtickrange", parent_name="layout.ternary.baxis.tickformatstop", **kwargs ): super(DtickrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "plot"}, {"valType": "any", "editType": "plot"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/ternary/baxis/title/0000755000175000017500000000000013573746614025214 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/ternary/baxis/title/__init__.py0000644000175000017500000000366213573721540027323 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="text", parent_name="layout.ternary.baxis.title", **kwargs ): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="layout.ternary.baxis.title", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/ternary/baxis/title/font/0000755000175000017500000000000013573746614026162 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/ternary/baxis/title/font/__init__.py0000644000175000017500000000314113573721540030261 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="layout.ternary.baxis.title.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="layout.ternary.baxis.title.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="layout.ternary.baxis.title.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/ternary/baxis/__init__.py0000644000175000017500000005324213573721542026203 0ustar noahfxnoahfximport _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="uirevision", parent_name="layout.ternary.baxis", **kwargs ): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TitleValidator(_plotly_utils.basevalidators.TitleValidator): def __init__( self, plotly_name="title", parent_name="layout.ternary.baxis", **kwargs ): super(TitleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Title"), data_docs=kwargs.pop( "data_docs", """ font Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. text Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """, ), **kwargs ) import _plotly_utils.basevalidators class TickwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="tickwidth", parent_name="layout.ternary.baxis", **kwargs ): super(TickwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickvalssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="tickvalssrc", parent_name="layout.ternary.baxis", **kwargs ): super(TickvalssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickvalsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="tickvals", parent_name="layout.ternary.baxis", **kwargs ): super(TickvalsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="ticktextsrc", parent_name="layout.ternary.baxis", **kwargs ): super(TicktextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicktextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="ticktext", parent_name="layout.ternary.baxis", **kwargs ): super(TicktextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="ticksuffix", parent_name="layout.ternary.baxis", **kwargs ): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TicksValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="ticks", parent_name="layout.ternary.baxis", **kwargs ): super(TicksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["outside", "inside", ""]), **kwargs ) import _plotly_utils.basevalidators class TickprefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickprefix", parent_name="layout.ternary.baxis", **kwargs ): super(TickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="tickmode", parent_name="layout.ternary.baxis", **kwargs ): super(TickmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "linear", "array"]), **kwargs ) import _plotly_utils.basevalidators class TicklenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ticklen", parent_name="layout.ternary.baxis", **kwargs ): super(TicklenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickformatstopValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickformatstopdefaults", parent_name="layout.ternary.baxis", **kwargs ): super(TickformatstopValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatstopsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="tickformatstops", parent_name="layout.ternary.baxis", **kwargs ): super(TickformatstopsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickformat", parent_name="layout.ternary.baxis", **kwargs ): super(TickformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickfont", parent_name="layout.ternary.baxis", **kwargs ): super(TickfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class TickcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="tickcolor", parent_name="layout.ternary.baxis", **kwargs ): super(TickcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__( self, plotly_name="tickangle", parent_name="layout.ternary.baxis", **kwargs ): super(TickangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="tick0", parent_name="layout.ternary.baxis", **kwargs ): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowticksuffixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showticksuffix", parent_name="layout.ternary.baxis", **kwargs ): super(ShowticksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowtickprefixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showtickprefix", parent_name="layout.ternary.baxis", **kwargs ): super(ShowtickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowticklabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showticklabels", parent_name="layout.ternary.baxis", **kwargs ): super(ShowticklabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowlineValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showline", parent_name="layout.ternary.baxis", **kwargs ): super(ShowlineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowgridValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showgrid", parent_name="layout.ternary.baxis", **kwargs ): super(ShowgridValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowexponentValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showexponent", parent_name="layout.ternary.baxis", **kwargs ): super(ShowexponentValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class SeparatethousandsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="separatethousands", parent_name="layout.ternary.baxis", **kwargs ): super(SeparatethousandsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NticksValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="nticks", parent_name="layout.ternary.baxis", **kwargs ): super(NticksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class MinValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="min", parent_name="layout.ternary.baxis", **kwargs): super(MinValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="linewidth", parent_name="layout.ternary.baxis", **kwargs ): super(LinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="linecolor", parent_name="layout.ternary.baxis", **kwargs ): super(LinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LayerValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="layer", parent_name="layout.ternary.baxis", **kwargs ): super(LayerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["above traces", "below traces"]), **kwargs ) import _plotly_utils.basevalidators class HoverformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="hoverformat", parent_name="layout.ternary.baxis", **kwargs ): super(HoverformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class GridwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="gridwidth", parent_name="layout.ternary.baxis", **kwargs ): super(GridwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class GridcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="gridcolor", parent_name="layout.ternary.baxis", **kwargs ): super(GridcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ExponentformatValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="exponentformat", parent_name="layout.ternary.baxis", **kwargs ): super(ExponentformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "e", "E", "power", "SI", "B"]), **kwargs ) import _plotly_utils.basevalidators class DtickValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="dtick", parent_name="layout.ternary.baxis", **kwargs ): super(DtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="layout.ternary.baxis", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/ternary/baxis/tickfont/0000755000175000017500000000000013573746614025714 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/ternary/baxis/tickfont/__init__.py0000644000175000017500000000305313573721540030015 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="layout.ternary.baxis.tickfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="layout.ternary.baxis.tickfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="layout.ternary.baxis.tickfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/hoverlabel/0000755000175000017500000000000013573746614023424 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/hoverlabel/__init__.py0000644000175000017500000000660713573721540025535 0ustar noahfxnoahfximport _plotly_utils.basevalidators class NamelengthValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="namelength", parent_name="layout.hoverlabel", **kwargs ): super(NamelengthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", -1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="font", parent_name="layout.hoverlabel", **kwargs): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="layout.hoverlabel", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="layout.hoverlabel", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="align", parent_name="layout.hoverlabel", **kwargs): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "right", "auto"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/hoverlabel/font/0000755000175000017500000000000013573746614024372 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/hoverlabel/font/__init__.py0000644000175000017500000000277613573721540026506 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="layout.hoverlabel.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="layout.hoverlabel.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="layout.hoverlabel.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/grid/0000755000175000017500000000000013573746614022226 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/grid/__init__.py0000644000175000017500000001642613573721540024337 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YsideValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="yside", parent_name="layout.grid", **kwargs): super(YsideValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["left", "left plot", "right plot", "right"]), **kwargs ) import _plotly_utils.basevalidators class YgapValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="ygap", parent_name="layout.grid", **kwargs): super(YgapValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YaxesValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="yaxes", parent_name="layout.grid", **kwargs): super(YaxesValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), free_length=kwargs.pop("free_length", True), items=kwargs.pop( "items", { "valType": "enumerated", "values": ["/^y([2-9]|[1-9][0-9]+)?$/", ""], "editType": "plot", }, ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XsideValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="xside", parent_name="layout.grid", **kwargs): super(XsideValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["bottom", "bottom plot", "top plot", "top"]), **kwargs ) import _plotly_utils.basevalidators class XgapValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="xgap", parent_name="layout.grid", **kwargs): super(XgapValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XaxesValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="xaxes", parent_name="layout.grid", **kwargs): super(XaxesValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), free_length=kwargs.pop("free_length", True), items=kwargs.pop( "items", { "valType": "enumerated", "values": ["/^x([2-9]|[1-9][0-9]+)?$/", ""], "editType": "plot", }, ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SubplotsValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="subplots", parent_name="layout.grid", **kwargs): super(SubplotsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dimensions=kwargs.pop("dimensions", 2), edit_type=kwargs.pop("edit_type", "plot"), free_length=kwargs.pop("free_length", True), items=kwargs.pop( "items", { "valType": "enumerated", "values": ["/^x([2-9]|[1-9][0-9]+)?y([2-9]|[1-9][0-9]+)?$/", ""], "editType": "plot", }, ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class RowsValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="rows", parent_name="layout.grid", **kwargs): super(RowsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class RoworderValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="roworder", parent_name="layout.grid", **kwargs): super(RoworderValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["top to bottom", "bottom to top"]), **kwargs ) import _plotly_utils.basevalidators class PatternValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="pattern", parent_name="layout.grid", **kwargs): super(PatternValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["independent", "coupled"]), **kwargs ) import _plotly_utils.basevalidators class DomainValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="domain", parent_name="layout.grid", **kwargs): super(DomainValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Domain"), data_docs=kwargs.pop( "data_docs", """ x Sets the horizontal domain of this grid subplot (in plot fraction). The first and last cells end exactly at the domain edges, with no grout around the edges. y Sets the vertical domain of this grid subplot (in plot fraction). The first and last cells end exactly at the domain edges, with no grout around the edges. """, ), **kwargs ) import _plotly_utils.basevalidators class ColumnsValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="columns", parent_name="layout.grid", **kwargs): super(ColumnsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/grid/domain/0000755000175000017500000000000013573746614023475 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/grid/domain/__init__.py0000644000175000017500000000261613573721540025602 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="y", parent_name="layout.grid.domain", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), items=kwargs.pop( "items", [ {"valType": "number", "min": 0, "max": 1, "editType": "plot"}, {"valType": "number", "min": 0, "max": 1, "editType": "plot"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="x", parent_name="layout.grid.domain", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), items=kwargs.pop( "items", [ {"valType": "number", "min": 0, "max": 1, "editType": "plot"}, {"valType": "number", "min": 0, "max": 1, "editType": "plot"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/colorscale/0000755000175000017500000000000013573746614023427 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/colorscale/__init__.py0000644000175000017500000000265513573721540025537 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SequentialminusValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__( self, plotly_name="sequentialminus", parent_name="layout.colorscale", **kwargs ): super(SequentialminusValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SequentialValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__( self, plotly_name="sequential", parent_name="layout.colorscale", **kwargs ): super(SequentialValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class DivergingValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__( self, plotly_name="diverging", parent_name="layout.colorscale", **kwargs ): super(DivergingValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/mapbox/0000755000175000017500000000000013573746614022567 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/mapbox/layer/0000755000175000017500000000000013573746614023703 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/mapbox/layer/circle/0000755000175000017500000000000013573746614025144 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/mapbox/layer/circle/__init__.py0000644000175000017500000000073013573721540027244 0ustar noahfxnoahfximport _plotly_utils.basevalidators class RadiusValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="radius", parent_name="layout.mapbox.layer.circle", **kwargs ): super(RadiusValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/mapbox/layer/fill/0000755000175000017500000000000013573746614024631 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/mapbox/layer/fill/__init__.py0000644000175000017500000000077713573721540026744 0ustar noahfxnoahfximport _plotly_utils.basevalidators class OutlinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="outlinecolor", parent_name="layout.mapbox.layer.fill", **kwargs ): super(OutlinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/mapbox/layer/__init__.py0000644000175000017500000002601213573721540026004 0ustar noahfxnoahfximport _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="visible", parent_name="layout.mapbox.layer", **kwargs ): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TypeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="type", parent_name="layout.mapbox.layer", **kwargs): super(TypeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["circle", "line", "fill", "symbol", "raster"]), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="layout.mapbox.layer", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SymbolValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="symbol", parent_name="layout.mapbox.layer", **kwargs ): super(SymbolValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Symbol"), data_docs=kwargs.pop( "data_docs", """ icon Sets the symbol icon image (mapbox.layer.layout.icon-image). Full list: https://www.mapbox.com/maki-icons/ iconsize Sets the symbol icon size (mapbox.layer.layout.icon-size). Has an effect only when `type` is set to "symbol". placement Sets the symbol and/or text placement (mapbox.layer.layout.symbol-placement). If `placement` is "point", the label is placed where the geometry is located If `placement` is "line", the label is placed along the line of the geometry If `placement` is "line-center", the label is placed on the center of the geometry text Sets the symbol text (mapbox.layer.layout.text- field). textfont Sets the icon text font (color=mapbox.layer.paint.text-color, size=mapbox.layer.layout.text-size). Has an effect only when `type` is set to "symbol". textposition Sets the positions of the `text` elements with respects to the (x,y) coordinates. """, ), **kwargs ) import _plotly_utils.basevalidators class SourcetypeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="sourcetype", parent_name="layout.mapbox.layer", **kwargs ): super(SourcetypeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["geojson", "vector", "raster", "image"]), **kwargs ) import _plotly_utils.basevalidators class SourcelayerValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="sourcelayer", parent_name="layout.mapbox.layer", **kwargs ): super(SourcelayerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SourceattributionValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="sourceattribution", parent_name="layout.mapbox.layer", **kwargs ): super(SourceattributionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SourceValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="source", parent_name="layout.mapbox.layer", **kwargs ): super(SourceValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="opacity", parent_name="layout.mapbox.layer", **kwargs ): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="layout.mapbox.layer", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class MinzoomValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="minzoom", parent_name="layout.mapbox.layer", **kwargs ): super(MinzoomValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), max=kwargs.pop("max", 24), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MaxzoomValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="maxzoom", parent_name="layout.mapbox.layer", **kwargs ): super(MaxzoomValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), max=kwargs.pop("max", 24), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="line", parent_name="layout.mapbox.layer", **kwargs): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ dash Sets the length of dashes and gaps (mapbox.layer.paint.line-dasharray). Has an effect only when `type` is set to "line". dashsrc Sets the source reference on plot.ly for dash . width Sets the line width (mapbox.layer.paint.line- width). Has an effect only when `type` is set to "line". """, ), **kwargs ) import _plotly_utils.basevalidators class FillValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="fill", parent_name="layout.mapbox.layer", **kwargs): super(FillValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Fill"), data_docs=kwargs.pop( "data_docs", """ outlinecolor Sets the fill outline color (mapbox.layer.paint.fill-outline-color). Has an effect only when `type` is set to "fill". """, ), **kwargs ) import _plotly_utils.basevalidators class CoordinatesValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="coordinates", parent_name="layout.mapbox.layer", **kwargs ): super(CoordinatesValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="layout.mapbox.layer", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class CircleValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="circle", parent_name="layout.mapbox.layer", **kwargs ): super(CircleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Circle"), data_docs=kwargs.pop( "data_docs", """ radius Sets the circle radius (mapbox.layer.paint.circle-radius). Has an effect only when `type` is set to "circle". """, ), **kwargs ) import _plotly_utils.basevalidators class BelowValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="below", parent_name="layout.mapbox.layer", **kwargs ): super(BelowValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/mapbox/layer/symbol/0000755000175000017500000000000013573746614025210 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/mapbox/layer/symbol/textfont/0000755000175000017500000000000013573746614027063 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/mapbox/layer/symbol/textfont/__init__.py0000644000175000017500000000315513573721540031167 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="layout.mapbox.layer.symbol.textfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="layout.mapbox.layer.symbol.textfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="layout.mapbox.layer.symbol.textfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/mapbox/layer/symbol/__init__.py0000644000175000017500000001064313573721540027314 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextpositionValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="textposition", parent_name="layout.mapbox.layer.symbol", **kwargs ): super(TextpositionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", False), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", [ "top left", "top center", "top right", "middle left", "middle center", "middle right", "bottom left", "bottom center", "bottom right", ], ), **kwargs ) import _plotly_utils.basevalidators class TextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="textfont", parent_name="layout.mapbox.layer.symbol", **kwargs ): super(TextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Textfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="text", parent_name="layout.mapbox.layer.symbol", **kwargs ): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class PlacementValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="placement", parent_name="layout.mapbox.layer.symbol", **kwargs ): super(PlacementValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["point", "line", "line-center"]), **kwargs ) import _plotly_utils.basevalidators class IconsizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="iconsize", parent_name="layout.mapbox.layer.symbol", **kwargs ): super(IconsizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class IconValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="icon", parent_name="layout.mapbox.layer.symbol", **kwargs ): super(IconValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/mapbox/layer/line/0000755000175000017500000000000013573746614024632 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/mapbox/layer/line/__init__.py0000644000175000017500000000257613573721540026744 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="width", parent_name="layout.mapbox.layer.line", **kwargs ): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class DashsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="dashsrc", parent_name="layout.mapbox.layer.line", **kwargs ): super(DashsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DashValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="dash", parent_name="layout.mapbox.layer.line", **kwargs ): super(DashValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "data"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/mapbox/__init__.py0000644000175000017500000002676313573721540024705 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ZoomValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="zoom", parent_name="layout.mapbox", **kwargs): super(ZoomValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="layout.mapbox", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class StyleValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="style", parent_name="layout.mapbox", **kwargs): super(StyleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", [ "basic", "streets", "outdoors", "light", "dark", "satellite", "satellite-streets", "open-street-map", "white-bg", "carto-positron", "carto-darkmatter", "stamen-terrain", "stamen-toner", "stamen-watercolor", ], ), **kwargs ) import _plotly_utils.basevalidators class PitchValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="pitch", parent_name="layout.mapbox", **kwargs): super(PitchValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LayerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="layerdefaults", parent_name="layout.mapbox", **kwargs ): super(LayerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Layer"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class LayersValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__(self, plotly_name="layers", parent_name="layout.mapbox", **kwargs): super(LayersValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Layer"), data_docs=kwargs.pop( "data_docs", """ below Determines if the layer will be inserted before the layer with the specified ID. If omitted or set to '', the layer will be inserted above every existing layer. circle plotly.graph_objects.layout.mapbox.layer.Circle instance or dict with compatible properties color Sets the primary layer color. If `type` is "circle", color corresponds to the circle color (mapbox.layer.paint.circle-color) If `type` is "line", color corresponds to the line color (mapbox.layer.paint.line-color) If `type` is "fill", color corresponds to the fill color (mapbox.layer.paint.fill-color) If `type` is "symbol", color corresponds to the icon color (mapbox.layer.paint.icon-color) coordinates Sets the coordinates array contains [longitude, latitude] pairs for the image corners listed in clockwise order: top left, top right, bottom right, bottom left. Only has an effect for "image" `sourcetype`. fill plotly.graph_objects.layout.mapbox.layer.Fill instance or dict with compatible properties line plotly.graph_objects.layout.mapbox.layer.Line instance or dict with compatible properties maxzoom Sets the maximum zoom level (mapbox.layer.maxzoom). At zoom levels equal to or greater than the maxzoom, the layer will be hidden. minzoom Sets the minimum zoom level (mapbox.layer.minzoom). At zoom levels less than the minzoom, the layer will be hidden. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. opacity Sets the opacity of the layer. If `type` is "circle", opacity corresponds to the circle opacity (mapbox.layer.paint.circle-opacity) If `type` is "line", opacity corresponds to the line opacity (mapbox.layer.paint.line-opacity) If `type` is "fill", opacity corresponds to the fill opacity (mapbox.layer.paint.fill-opacity) If `type` is "symbol", opacity corresponds to the icon/text opacity (mapbox.layer.paint.text- opacity) source Sets the source data for this layer (mapbox.layer.source). When `sourcetype` is set to "geojson", `source` can be a URL to a GeoJSON or a GeoJSON object. When `sourcetype` is set to "vector" or "raster", `source` can be a URL or an array of tile URLs. When `sourcetype` is set to "image", `source` can be a URL to an image. sourceattribution Sets the attribution for this source. sourcelayer Specifies the layer to use from a vector tile source (mapbox.layer.source-layer). Required for "vector" source type that supports multiple layers. sourcetype Sets the source type for this layer, that is the type of the layer data. symbol plotly.graph_objects.layout.mapbox.layer.Symbol instance or dict with compatible properties templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. type Sets the layer type, that is the how the layer data set in `source` will be rendered With `sourcetype` set to "geojson", the following values are allowed: "circle", "line", "fill" and "symbol". but note that "line" and "fill" are not compatible with Point GeoJSON geometries. With `sourcetype` set to "vector", the following values are allowed: "circle", "line", "fill" and "symbol". With `sourcetype` set to "raster" or `*image*`, only the "raster" value is allowed. visible Determines whether this layer is displayed """, ), **kwargs ) import _plotly_utils.basevalidators class DomainValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="domain", parent_name="layout.mapbox", **kwargs): super(DomainValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Domain"), data_docs=kwargs.pop( "data_docs", """ column If there is a layout grid, use the domain for this column in the grid for this mapbox subplot . row If there is a layout grid, use the domain for this row in the grid for this mapbox subplot . x Sets the horizontal domain of this mapbox subplot (in plot fraction). y Sets the vertical domain of this mapbox subplot (in plot fraction). """, ), **kwargs ) import _plotly_utils.basevalidators class CenterValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="center", parent_name="layout.mapbox", **kwargs): super(CenterValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Center"), data_docs=kwargs.pop( "data_docs", """ lat Sets the latitude of the center of the map (in degrees North). lon Sets the longitude of the center of the map (in degrees East). """, ), **kwargs ) import _plotly_utils.basevalidators class BearingValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="bearing", parent_name="layout.mapbox", **kwargs): super(BearingValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AccesstokenValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="accesstoken", parent_name="layout.mapbox", **kwargs ): super(AccesstokenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "info"), strict=kwargs.pop("strict", True), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/mapbox/domain/0000755000175000017500000000000013573746614024036 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/mapbox/domain/__init__.py0000644000175000017500000000455713573721540026151 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="y", parent_name="layout.mapbox.domain", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), items=kwargs.pop( "items", [ {"valType": "number", "min": 0, "max": 1, "editType": "plot"}, {"valType": "number", "min": 0, "max": 1, "editType": "plot"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="x", parent_name="layout.mapbox.domain", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), items=kwargs.pop( "items", [ {"valType": "number", "min": 0, "max": 1, "editType": "plot"}, {"valType": "number", "min": 0, "max": 1, "editType": "plot"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class RowValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="row", parent_name="layout.mapbox.domain", **kwargs): super(RowValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColumnValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="column", parent_name="layout.mapbox.domain", **kwargs ): super(ColumnValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/mapbox/center/0000755000175000017500000000000013573746614024047 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/mapbox/center/__init__.py0000644000175000017500000000156613573721540026157 0ustar noahfxnoahfximport _plotly_utils.basevalidators class LonValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="lon", parent_name="layout.mapbox.center", **kwargs): super(LonValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LatValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="lat", parent_name="layout.mapbox.center", **kwargs): super(LatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/modebar/0000755000175000017500000000000013573746614022712 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/modebar/__init__.py0000644000175000017500000000451713573721540025021 0ustar noahfxnoahfximport _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="uirevision", parent_name="layout.modebar", **kwargs ): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class OrientationValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="orientation", parent_name="layout.modebar", **kwargs ): super(OrientationValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "modebar"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["v", "h"]), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="layout.modebar", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "modebar"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="bgcolor", parent_name="layout.modebar", **kwargs): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "modebar"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ActivecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="activecolor", parent_name="layout.modebar", **kwargs ): super(ActivecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "modebar"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/coloraxis/0000755000175000017500000000000013573746614023304 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/coloraxis/colorbar/0000755000175000017500000000000013573746614025107 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/coloraxis/colorbar/tickformatstop/0000755000175000017500000000000013573746614030160 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/coloraxis/colorbar/tickformatstop/__init__.py0000644000175000017500000000545113573721540032265 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="value", parent_name="layout.coloraxis.colorbar.tickformatstop", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="layout.coloraxis.colorbar.tickformatstop", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="layout.coloraxis.colorbar.tickformatstop", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EnabledValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="enabled", parent_name="layout.coloraxis.colorbar.tickformatstop", **kwargs ): super(EnabledValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DtickrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="dtickrange", parent_name="layout.coloraxis.colorbar.tickformatstop", **kwargs ): super(DtickrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "colorbars"}, {"valType": "any", "editType": "colorbars"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/coloraxis/colorbar/title/0000755000175000017500000000000013573746614026230 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/coloraxis/colorbar/title/__init__.py0000644000175000017500000000506013573721540030331 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="text", parent_name="layout.coloraxis.colorbar.title", **kwargs ): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SideValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="side", parent_name="layout.coloraxis.colorbar.title", **kwargs ): super(SideValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["right", "top", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="layout.coloraxis.colorbar.title", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/coloraxis/colorbar/title/font/0000755000175000017500000000000013573746614027176 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/coloraxis/colorbar/title/font/__init__.py0000644000175000017500000000317713573721540031306 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="layout.coloraxis.colorbar.title.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="layout.coloraxis.colorbar.title.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="layout.coloraxis.colorbar.title.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/coloraxis/colorbar/__init__.py0000644000175000017500000006167213573721541027224 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ypad", parent_name="layout.coloraxis.colorbar", **kwargs ): super(YpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class YanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="yanchor", parent_name="layout.coloraxis.colorbar", **kwargs ): super(YanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["top", "middle", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="y", parent_name="layout.coloraxis.colorbar", **kwargs ): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="xpad", parent_name="layout.coloraxis.colorbar", **kwargs ): super(XpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="xanchor", parent_name="layout.coloraxis.colorbar", **kwargs ): super(XanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "center", "right"]), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="x", parent_name="layout.coloraxis.colorbar", **kwargs ): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TitleValidator(_plotly_utils.basevalidators.TitleValidator): def __init__( self, plotly_name="title", parent_name="layout.coloraxis.colorbar", **kwargs ): super(TitleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Title"), data_docs=kwargs.pop( "data_docs", """ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """, ), **kwargs ) import _plotly_utils.basevalidators class TickwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="tickwidth", parent_name="layout.coloraxis.colorbar", **kwargs ): super(TickwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickvalssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="tickvalssrc", parent_name="layout.coloraxis.colorbar", **kwargs ): super(TickvalssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickvalsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="tickvals", parent_name="layout.coloraxis.colorbar", **kwargs ): super(TickvalsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="ticktextsrc", parent_name="layout.coloraxis.colorbar", **kwargs ): super(TicktextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicktextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="ticktext", parent_name="layout.coloraxis.colorbar", **kwargs ): super(TicktextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="ticksuffix", parent_name="layout.coloraxis.colorbar", **kwargs ): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TicksValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="ticks", parent_name="layout.coloraxis.colorbar", **kwargs ): super(TicksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["outside", "inside", ""]), **kwargs ) import _plotly_utils.basevalidators class TickprefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickprefix", parent_name="layout.coloraxis.colorbar", **kwargs ): super(TickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="tickmode", parent_name="layout.coloraxis.colorbar", **kwargs ): super(TickmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "linear", "array"]), **kwargs ) import _plotly_utils.basevalidators class TicklenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ticklen", parent_name="layout.coloraxis.colorbar", **kwargs ): super(TicklenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickformatstopValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickformatstopdefaults", parent_name="layout.coloraxis.colorbar", **kwargs ): super(TickformatstopValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatstopsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="tickformatstops", parent_name="layout.coloraxis.colorbar", **kwargs ): super(TickformatstopsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickformat", parent_name="layout.coloraxis.colorbar", **kwargs ): super(TickformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickfont", parent_name="layout.coloraxis.colorbar", **kwargs ): super(TickfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class TickcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="tickcolor", parent_name="layout.coloraxis.colorbar", **kwargs ): super(TickcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__( self, plotly_name="tickangle", parent_name="layout.coloraxis.colorbar", **kwargs ): super(TickangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="tick0", parent_name="layout.coloraxis.colorbar", **kwargs ): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ThicknessmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="thicknessmode", parent_name="layout.coloraxis.colorbar", **kwargs ): super(ThicknessmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="thickness", parent_name="layout.coloraxis.colorbar", **kwargs ): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowticksuffixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showticksuffix", parent_name="layout.coloraxis.colorbar", **kwargs ): super(ShowticksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowtickprefixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showtickprefix", parent_name="layout.coloraxis.colorbar", **kwargs ): super(ShowtickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowticklabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showticklabels", parent_name="layout.coloraxis.colorbar", **kwargs ): super(ShowticklabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowexponentValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showexponent", parent_name="layout.coloraxis.colorbar", **kwargs ): super(ShowexponentValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class SeparatethousandsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="separatethousands", parent_name="layout.coloraxis.colorbar", **kwargs ): super(SeparatethousandsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="outlinewidth", parent_name="layout.coloraxis.colorbar", **kwargs ): super(OutlinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="outlinecolor", parent_name="layout.coloraxis.colorbar", **kwargs ): super(OutlinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NticksValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="nticks", parent_name="layout.coloraxis.colorbar", **kwargs ): super(NticksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LenmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="lenmode", parent_name="layout.coloraxis.colorbar", **kwargs ): super(LenmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class LenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="len", parent_name="layout.coloraxis.colorbar", **kwargs ): super(LenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ExponentformatValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="exponentformat", parent_name="layout.coloraxis.colorbar", **kwargs ): super(ExponentformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "e", "E", "power", "SI", "B"]), **kwargs ) import _plotly_utils.basevalidators class DtickValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="dtick", parent_name="layout.coloraxis.colorbar", **kwargs ): super(DtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BorderwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="borderwidth", parent_name="layout.coloraxis.colorbar", **kwargs ): super(BorderwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="layout.coloraxis.colorbar", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="layout.coloraxis.colorbar", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/coloraxis/colorbar/tickfont/0000755000175000017500000000000013573746614026730 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/coloraxis/colorbar/tickfont/__init__.py0000644000175000017500000000317113573721540031032 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="layout.coloraxis.colorbar.tickfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="layout.coloraxis.colorbar.tickfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="layout.coloraxis.colorbar.tickfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/coloraxis/__init__.py0000644000175000017500000003512113573721540025406 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ShowscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showscale", parent_name="layout.coloraxis", **kwargs ): super(ShowscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ReversescaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="reversescale", parent_name="layout.coloraxis", **kwargs ): super(ReversescaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__( self, plotly_name="colorscale", parent_name="layout.coloraxis", **kwargs ): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"autocolorscale": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorBarValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="colorbar", parent_name="layout.coloraxis", **kwargs ): super(ColorBarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "ColorBar"), data_docs=kwargs.pop( "data_docs", """ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.layout.coloraxi s.colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.lay out.coloraxis.colorbar.tickformatstopdefaults), sets the default property values to use for elements of layout.coloraxis.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.layout.coloraxis.colorbar. Title instance or dict with compatible properties titlefont Deprecated: Please use layout.coloraxis.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use layout.coloraxis.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """, ), **kwargs ) import _plotly_utils.basevalidators class CminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmin", parent_name="layout.coloraxis", **kwargs): super(CminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmidValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmid", parent_name="layout.coloraxis", **kwargs): super(CmidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmax", parent_name="layout.coloraxis", **kwargs): super(CmaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CautoValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="cauto", parent_name="layout.coloraxis", **kwargs): super(CautoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AutocolorscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="autocolorscale", parent_name="layout.coloraxis", **kwargs ): super(AutocolorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/yaxis/0000755000175000017500000000000013573746614022436 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/yaxis/tickformatstop/0000755000175000017500000000000013573746614025507 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/yaxis/tickformatstop/__init__.py0000644000175000017500000000520213573721541027607 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="value", parent_name="layout.yaxis.tickformatstop", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="layout.yaxis.tickformatstop", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="layout.yaxis.tickformatstop", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EnabledValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="enabled", parent_name="layout.yaxis.tickformatstop", **kwargs ): super(EnabledValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DtickrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="dtickrange", parent_name="layout.yaxis.tickformatstop", **kwargs ): super(DtickrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "ticks"}, {"valType": "any", "editType": "ticks"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/yaxis/title/0000755000175000017500000000000013573746614023557 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/yaxis/title/__init__.py0000644000175000017500000000460513573721541025665 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="text", parent_name="layout.yaxis.title", **kwargs): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class StandoffValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="standoff", parent_name="layout.yaxis.title", **kwargs ): super(StandoffValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="font", parent_name="layout.yaxis.title", **kwargs): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/yaxis/title/font/0000755000175000017500000000000013573746614024525 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/yaxis/title/font/__init__.py0000644000175000017500000000300413573721541026623 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="layout.yaxis.title.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="layout.yaxis.title.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="layout.yaxis.title.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/yaxis/__init__.py0000644000175000017500000012161513573721542024546 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ZerolinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="zerolinewidth", parent_name="layout.yaxis", **kwargs ): super(ZerolinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ZerolinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="zerolinecolor", parent_name="layout.yaxis", **kwargs ): super(ZerolinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ZerolineValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="zeroline", parent_name="layout.yaxis", **kwargs): super(ZerolineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="visible", parent_name="layout.yaxis", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="layout.yaxis", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TypeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="type", parent_name="layout.yaxis", **kwargs): super(TypeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", ["-", "linear", "log", "date", "category", "multicategory"] ), **kwargs ) import _plotly_utils.basevalidators class TitleValidator(_plotly_utils.basevalidators.TitleValidator): def __init__(self, plotly_name="title", parent_name="layout.yaxis", **kwargs): super(TitleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Title"), data_docs=kwargs.pop( "data_docs", """ font Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. standoff Sets the standoff distance (in px) between the axis labels and the title text The default value is a function of the axis tick labels, the title `font.size` and the axis `linewidth`. Note that the axis title position is always constrained within the margins, so the actual standoff distance is always less than the set or default value. By setting `standoff` and turning on `automargin`, plotly.js will push the margins to fit the axis title at given standoff distance. text Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """, ), **kwargs ) import _plotly_utils.basevalidators class TickwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="tickwidth", parent_name="layout.yaxis", **kwargs): super(TickwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickvalssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="tickvalssrc", parent_name="layout.yaxis", **kwargs): super(TickvalssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickvalsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="tickvals", parent_name="layout.yaxis", **kwargs): super(TickvalsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="ticktextsrc", parent_name="layout.yaxis", **kwargs): super(TicktextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicktextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ticktext", parent_name="layout.yaxis", **kwargs): super(TicktextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="ticksuffix", parent_name="layout.yaxis", **kwargs): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TicksonValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="tickson", parent_name="layout.yaxis", **kwargs): super(TicksonValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["labels", "boundaries"]), **kwargs ) import _plotly_utils.basevalidators class TicksValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="ticks", parent_name="layout.yaxis", **kwargs): super(TicksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["outside", "inside", ""]), **kwargs ) import _plotly_utils.basevalidators class TickprefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="tickprefix", parent_name="layout.yaxis", **kwargs): super(TickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="tickmode", parent_name="layout.yaxis", **kwargs): super(TickmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "linear", "array"]), **kwargs ) import _plotly_utils.basevalidators class TicklenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="ticklen", parent_name="layout.yaxis", **kwargs): super(TicklenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickformatstopValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickformatstopdefaults", parent_name="layout.yaxis", **kwargs ): super(TickformatstopValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatstopsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="tickformatstops", parent_name="layout.yaxis", **kwargs ): super(TickformatstopsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="tickformat", parent_name="layout.yaxis", **kwargs): super(TickformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="tickfont", parent_name="layout.yaxis", **kwargs): super(TickfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class TickcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="tickcolor", parent_name="layout.yaxis", **kwargs): super(TickcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__(self, plotly_name="tickangle", parent_name="layout.yaxis", **kwargs): super(TickangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="tick0", parent_name="layout.yaxis", **kwargs): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SpikethicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="spikethickness", parent_name="layout.yaxis", **kwargs ): super(SpikethicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SpikesnapValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="spikesnap", parent_name="layout.yaxis", **kwargs): super(SpikesnapValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["data", "cursor"]), **kwargs ) import _plotly_utils.basevalidators class SpikemodeValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="spikemode", parent_name="layout.yaxis", **kwargs): super(SpikemodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), flags=kwargs.pop("flags", ["toaxis", "across", "marker"]), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SpikedashValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="spikedash", parent_name="layout.yaxis", **kwargs): super(SpikedashValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", ["solid", "dot", "dash", "longdash", "dashdot", "longdashdot"] ), **kwargs ) import _plotly_utils.basevalidators class SpikecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="spikecolor", parent_name="layout.yaxis", **kwargs): super(SpikecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SideValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="side", parent_name="layout.yaxis", **kwargs): super(SideValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["top", "bottom", "left", "right"]), **kwargs ) import _plotly_utils.basevalidators class ShowticksuffixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showticksuffix", parent_name="layout.yaxis", **kwargs ): super(ShowticksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowtickprefixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showtickprefix", parent_name="layout.yaxis", **kwargs ): super(ShowtickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowticklabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showticklabels", parent_name="layout.yaxis", **kwargs ): super(ShowticklabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowspikesValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showspikes", parent_name="layout.yaxis", **kwargs): super(ShowspikesValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "modebar"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowlineValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showline", parent_name="layout.yaxis", **kwargs): super(ShowlineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks+layoutstyle"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowgridValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showgrid", parent_name="layout.yaxis", **kwargs): super(ShowgridValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowexponentValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showexponent", parent_name="layout.yaxis", **kwargs ): super(ShowexponentValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowdividersValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showdividers", parent_name="layout.yaxis", **kwargs ): super(ShowdividersValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SeparatethousandsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="separatethousands", parent_name="layout.yaxis", **kwargs ): super(SeparatethousandsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ScaleratioValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="scaleratio", parent_name="layout.yaxis", **kwargs): super(ScaleratioValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ScaleanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="scaleanchor", parent_name="layout.yaxis", **kwargs): super(ScaleanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", ["/^x([2-9]|[1-9][0-9]+)?$/", "/^y([2-9]|[1-9][0-9]+)?$/"] ), **kwargs ) import _plotly_utils.basevalidators class RangemodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="rangemode", parent_name="layout.yaxis", **kwargs): super(RangemodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["normal", "tozero", "nonnegative"]), **kwargs ) import _plotly_utils.basevalidators class RangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="range", parent_name="layout.yaxis", **kwargs): super(RangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, anim=kwargs.pop("anim", True), edit_type=kwargs.pop("edit_type", "axrange"), implied_edits=kwargs.pop("implied_edits", {"autorange": False}), items=kwargs.pop( "items", [ { "valType": "any", "editType": "axrange", "impliedEdits": {"^autorange": False}, "anim": True, }, { "valType": "any", "editType": "axrange", "impliedEdits": {"^autorange": False}, "anim": True, }, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class PositionValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="position", parent_name="layout.yaxis", **kwargs): super(PositionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OverlayingValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="overlaying", parent_name="layout.yaxis", **kwargs): super(OverlayingValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", ["free", "/^x([2-9]|[1-9][0-9]+)?$/", "/^y([2-9]|[1-9][0-9]+)?$/"], ), **kwargs ) import _plotly_utils.basevalidators class NticksValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="nticks", parent_name="layout.yaxis", **kwargs): super(NticksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class MirrorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="mirror", parent_name="layout.yaxis", **kwargs): super(MirrorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks+layoutstyle"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", [True, "ticks", False, "all", "allticks"]), **kwargs ) import _plotly_utils.basevalidators class MatchesValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="matches", parent_name="layout.yaxis", **kwargs): super(MatchesValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", ["/^x([2-9]|[1-9][0-9]+)?$/", "/^y([2-9]|[1-9][0-9]+)?$/"] ), **kwargs ) import _plotly_utils.basevalidators class LinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="linewidth", parent_name="layout.yaxis", **kwargs): super(LinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks+layoutstyle"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="linecolor", parent_name="layout.yaxis", **kwargs): super(LinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "layoutstyle"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LayerValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="layer", parent_name="layout.yaxis", **kwargs): super(LayerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["above traces", "below traces"]), **kwargs ) import _plotly_utils.basevalidators class HoverformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hoverformat", parent_name="layout.yaxis", **kwargs): super(HoverformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class GridwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="gridwidth", parent_name="layout.yaxis", **kwargs): super(GridwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class GridcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="gridcolor", parent_name="layout.yaxis", **kwargs): super(GridcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FixedrangeValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="fixedrange", parent_name="layout.yaxis", **kwargs): super(FixedrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ExponentformatValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="exponentformat", parent_name="layout.yaxis", **kwargs ): super(ExponentformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "e", "E", "power", "SI", "B"]), **kwargs ) import _plotly_utils.basevalidators class DtickValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="dtick", parent_name="layout.yaxis", **kwargs): super(DtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class DomainValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="domain", parent_name="layout.yaxis", **kwargs): super(DomainValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), items=kwargs.pop( "items", [ {"valType": "number", "min": 0, "max": 1, "editType": "plot"}, {"valType": "number", "min": 0, "max": 1, "editType": "plot"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DividerwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="dividerwidth", parent_name="layout.yaxis", **kwargs ): super(DividerwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class DividercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="dividercolor", parent_name="layout.yaxis", **kwargs ): super(DividercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ConstraintowardValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="constraintoward", parent_name="layout.yaxis", **kwargs ): super(ConstraintowardValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", ["left", "center", "right", "top", "middle", "bottom"] ), **kwargs ) import _plotly_utils.basevalidators class ConstrainValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="constrain", parent_name="layout.yaxis", **kwargs): super(ConstrainValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["range", "domain"]), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="layout.yaxis", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class CategoryorderValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="categoryorder", parent_name="layout.yaxis", **kwargs ): super(CategoryorderValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "trace", "category ascending", "category descending", "array", "total ascending", "total descending", "min ascending", "min descending", "max ascending", "max descending", "sum ascending", "sum descending", "mean ascending", "mean descending", "median ascending", "median descending", ], ), **kwargs ) import _plotly_utils.basevalidators class CategoryarraysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="categoryarraysrc", parent_name="layout.yaxis", **kwargs ): super(CategoryarraysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CategoryarrayValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="categoryarray", parent_name="layout.yaxis", **kwargs ): super(CategoryarrayValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class CalendarValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="calendar", parent_name="layout.yaxis", **kwargs): super(CalendarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "gregorian", "chinese", "coptic", "discworld", "ethiopian", "hebrew", "islamic", "julian", "mayan", "nanakshahi", "nepali", "persian", "jalali", "taiwan", "thai", "ummalqura", ], ), **kwargs ) import _plotly_utils.basevalidators class AutorangeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="autorange", parent_name="layout.yaxis", **kwargs): super(AutorangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "axrange"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "reversed"]), **kwargs ) import _plotly_utils.basevalidators class AutomarginValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="automargin", parent_name="layout.yaxis", **kwargs): super(AutomarginValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AnchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="anchor", parent_name="layout.yaxis", **kwargs): super(AnchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", ["free", "/^x([2-9]|[1-9][0-9]+)?$/", "/^y([2-9]|[1-9][0-9]+)?$/"], ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/yaxis/tickfont/0000755000175000017500000000000013573746614024257 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/yaxis/tickfont/__init__.py0000644000175000017500000000277613573721541026374 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="layout.yaxis.tickfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="layout.yaxis.tickfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="layout.yaxis.tickfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/geo/0000755000175000017500000000000013573746614022053 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/geo/lataxis/0000755000175000017500000000000013573746614023520 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/geo/lataxis/__init__.py0000644000175000017500000000573513573721540025632 0ustar noahfxnoahfximport _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="tick0", parent_name="layout.geo.lataxis", **kwargs): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ShowgridValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showgrid", parent_name="layout.geo.lataxis", **kwargs ): super(ShowgridValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class RangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="range", parent_name="layout.geo.lataxis", **kwargs): super(RangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), items=kwargs.pop( "items", [ {"valType": "number", "editType": "plot"}, {"valType": "number", "editType": "plot"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class GridwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="gridwidth", parent_name="layout.geo.lataxis", **kwargs ): super(GridwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class GridcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="gridcolor", parent_name="layout.geo.lataxis", **kwargs ): super(GridcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class DtickValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="dtick", parent_name="layout.geo.lataxis", **kwargs): super(DtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/geo/projection/0000755000175000017500000000000013573746614024227 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/geo/projection/rotation/0000755000175000017500000000000013573746614026066 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/geo/projection/rotation/__init__.py0000644000175000017500000000257513573721540030177 0ustar noahfxnoahfximport _plotly_utils.basevalidators class RollValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="roll", parent_name="layout.geo.projection.rotation", **kwargs ): super(RollValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LonValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="lon", parent_name="layout.geo.projection.rotation", **kwargs ): super(LonValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LatValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="lat", parent_name="layout.geo.projection.rotation", **kwargs ): super(LatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/geo/projection/__init__.py0000644000175000017500000000671513573721540026340 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TypeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="type", parent_name="layout.geo.projection", **kwargs ): super(TypeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "equirectangular", "mercator", "orthographic", "natural earth", "kavrayskiy7", "miller", "robinson", "eckert4", "azimuthal equal area", "azimuthal equidistant", "conic equal area", "conic conformal", "conic equidistant", "gnomonic", "stereographic", "mollweide", "hammer", "transverse mercator", "albers usa", "winkel tripel", "aitoff", "sinusoidal", ], ), **kwargs ) import _plotly_utils.basevalidators class ScaleValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="scale", parent_name="layout.geo.projection", **kwargs ): super(ScaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class RotationValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="rotation", parent_name="layout.geo.projection", **kwargs ): super(RotationValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Rotation"), data_docs=kwargs.pop( "data_docs", """ lat Rotates the map along meridians (in degrees North). lon Rotates the map along parallels (in degrees East). Defaults to the center of the `lonaxis.range` values. roll Roll the map (in degrees) For example, a roll of 180 makes the map appear upside down. """, ), **kwargs ) import _plotly_utils.basevalidators class ParallelsValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="parallels", parent_name="layout.geo.projection", **kwargs ): super(ParallelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), items=kwargs.pop( "items", [ {"valType": "number", "editType": "plot"}, {"valType": "number", "editType": "plot"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/geo/__init__.py0000644000175000017500000004362713573721541024170 0ustar noahfxnoahfximport _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="layout.geo", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SubunitwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="subunitwidth", parent_name="layout.geo", **kwargs): super(SubunitwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SubunitcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="subunitcolor", parent_name="layout.geo", **kwargs): super(SubunitcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowsubunitsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showsubunits", parent_name="layout.geo", **kwargs): super(ShowsubunitsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ShowriversValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showrivers", parent_name="layout.geo", **kwargs): super(ShowriversValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ShowoceanValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showocean", parent_name="layout.geo", **kwargs): super(ShowoceanValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ShowlandValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showland", parent_name="layout.geo", **kwargs): super(ShowlandValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ShowlakesValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showlakes", parent_name="layout.geo", **kwargs): super(ShowlakesValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ShowframeValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showframe", parent_name="layout.geo", **kwargs): super(ShowframeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ShowcountriesValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showcountries", parent_name="layout.geo", **kwargs): super(ShowcountriesValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ShowcoastlinesValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showcoastlines", parent_name="layout.geo", **kwargs ): super(ShowcoastlinesValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ScopeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="scope", parent_name="layout.geo", **kwargs): super(ScopeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "world", "usa", "europe", "asia", "africa", "north america", "south america", ], ), **kwargs ) import _plotly_utils.basevalidators class RiverwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="riverwidth", parent_name="layout.geo", **kwargs): super(RiverwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class RivercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="rivercolor", parent_name="layout.geo", **kwargs): super(RivercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ResolutionValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="resolution", parent_name="layout.geo", **kwargs): super(ResolutionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, coerce_number=kwargs.pop("coerce_number", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [110, 50]), **kwargs ) import _plotly_utils.basevalidators class ProjectionValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="projection", parent_name="layout.geo", **kwargs): super(ProjectionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Projection"), data_docs=kwargs.pop( "data_docs", """ parallels For conic projection types only. Sets the parallels (tangent, secant) where the cone intersects the sphere. rotation plotly.graph_objects.layout.geo.projection.Rota tion instance or dict with compatible properties scale Zooms in or out on the map view. A scale of 1 corresponds to the largest zoom level that fits the map's lon and lat ranges. type Sets the projection type. """, ), **kwargs ) import _plotly_utils.basevalidators class OceancolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="oceancolor", parent_name="layout.geo", **kwargs): super(OceancolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LonaxisValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="lonaxis", parent_name="layout.geo", **kwargs): super(LonaxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Lonaxis"), data_docs=kwargs.pop( "data_docs", """ dtick Sets the graticule's longitude/latitude tick step. gridcolor Sets the graticule's stroke color. gridwidth Sets the graticule's stroke width (in px). range Sets the range of this axis (in degrees), sets the map's clipped coordinates. showgrid Sets whether or not graticule are shown on the map. tick0 Sets the graticule's starting tick longitude/latitude. """, ), **kwargs ) import _plotly_utils.basevalidators class LataxisValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="lataxis", parent_name="layout.geo", **kwargs): super(LataxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Lataxis"), data_docs=kwargs.pop( "data_docs", """ dtick Sets the graticule's longitude/latitude tick step. gridcolor Sets the graticule's stroke color. gridwidth Sets the graticule's stroke width (in px). range Sets the range of this axis (in degrees), sets the map's clipped coordinates. showgrid Sets whether or not graticule are shown on the map. tick0 Sets the graticule's starting tick longitude/latitude. """, ), **kwargs ) import _plotly_utils.basevalidators class LandcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="landcolor", parent_name="layout.geo", **kwargs): super(LandcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LakecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="lakecolor", parent_name="layout.geo", **kwargs): super(LakecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FramewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="framewidth", parent_name="layout.geo", **kwargs): super(FramewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FramecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="framecolor", parent_name="layout.geo", **kwargs): super(FramecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class DomainValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="domain", parent_name="layout.geo", **kwargs): super(DomainValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Domain"), data_docs=kwargs.pop( "data_docs", """ column If there is a layout grid, use the domain for this column in the grid for this geo subplot . Note that geo subplots are constrained by domain. In general, when `projection.scale` is set to 1. a map will fit either its x or y domain, but not both. row If there is a layout grid, use the domain for this row in the grid for this geo subplot . Note that geo subplots are constrained by domain. In general, when `projection.scale` is set to 1. a map will fit either its x or y domain, but not both. x Sets the horizontal domain of this geo subplot (in plot fraction). Note that geo subplots are constrained by domain. In general, when `projection.scale` is set to 1. a map will fit either its x or y domain, but not both. y Sets the vertical domain of this geo subplot (in plot fraction). Note that geo subplots are constrained by domain. In general, when `projection.scale` is set to 1. a map will fit either its x or y domain, but not both. """, ), **kwargs ) import _plotly_utils.basevalidators class CountrywidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="countrywidth", parent_name="layout.geo", **kwargs): super(CountrywidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class CountrycolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="countrycolor", parent_name="layout.geo", **kwargs): super(CountrycolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class CoastlinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="coastlinewidth", parent_name="layout.geo", **kwargs ): super(CoastlinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class CoastlinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="coastlinecolor", parent_name="layout.geo", **kwargs ): super(CoastlinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class CenterValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="center", parent_name="layout.geo", **kwargs): super(CenterValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Center"), data_docs=kwargs.pop( "data_docs", """ lat Sets the latitude of the map's center. For all projection types, the map's latitude center lies at the middle of the latitude range by default. lon Sets the longitude of the map's center. By default, the map's longitude center lies at the middle of the longitude range for scoped projection and above `projection.rotation.lon` otherwise. """, ), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="bgcolor", parent_name="layout.geo", **kwargs): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/geo/lonaxis/0000755000175000017500000000000013573746614023530 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/geo/lonaxis/__init__.py0000644000175000017500000000573513573721540025642 0ustar noahfxnoahfximport _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="tick0", parent_name="layout.geo.lonaxis", **kwargs): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ShowgridValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showgrid", parent_name="layout.geo.lonaxis", **kwargs ): super(ShowgridValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class RangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="range", parent_name="layout.geo.lonaxis", **kwargs): super(RangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), items=kwargs.pop( "items", [ {"valType": "number", "editType": "plot"}, {"valType": "number", "editType": "plot"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class GridwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="gridwidth", parent_name="layout.geo.lonaxis", **kwargs ): super(GridwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class GridcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="gridcolor", parent_name="layout.geo.lonaxis", **kwargs ): super(GridcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class DtickValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="dtick", parent_name="layout.geo.lonaxis", **kwargs): super(DtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/geo/domain/0000755000175000017500000000000013573746614023322 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/geo/domain/__init__.py0000644000175000017500000000452513573721540025430 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="y", parent_name="layout.geo.domain", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), items=kwargs.pop( "items", [ {"valType": "number", "min": 0, "max": 1, "editType": "plot"}, {"valType": "number", "min": 0, "max": 1, "editType": "plot"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="x", parent_name="layout.geo.domain", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), items=kwargs.pop( "items", [ {"valType": "number", "min": 0, "max": 1, "editType": "plot"}, {"valType": "number", "min": 0, "max": 1, "editType": "plot"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class RowValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="row", parent_name="layout.geo.domain", **kwargs): super(RowValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColumnValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="column", parent_name="layout.geo.domain", **kwargs): super(ColumnValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/geo/center/0000755000175000017500000000000013573746614023333 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/geo/center/__init__.py0000644000175000017500000000156013573721540025435 0ustar noahfxnoahfximport _plotly_utils.basevalidators class LonValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="lon", parent_name="layout.geo.center", **kwargs): super(LonValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LatValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="lat", parent_name="layout.geo.center", **kwargs): super(LatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/__init__.py0000644000175000017500000044613013573721542023413 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YAxisValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="yaxis", parent_name="layout", **kwargs): super(YAxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "YAxis"), data_docs=kwargs.pop( "data_docs", """ anchor If set to an opposite-letter axis id (e.g. `x2`, `y`), this axis is bound to the corresponding opposite-letter axis. If set to "free", this axis' position is determined by `position`. automargin Determines whether long tick labels automatically grow the figure margins. autorange Determines whether or not the range of this axis is computed in relation to the input data. See `rangemode` for more info. If `range` is provided, then `autorange` is set to False. calendar Sets the calendar system to use for `range` and `tick0` if this is a date axis. This does not set the calendar for interpreting data on this axis, that's specified in the trace or via the global `layout.calendar` categoryarray Sets the order in which categories on this axis appear. Only has an effect if `categoryorder` is set to "array". Used with `categoryorder`. categoryarraysrc Sets the source reference on plot.ly for categoryarray . categoryorder Specifies the ordering logic for the case of categorical variables. By default, plotly uses "trace", which specifies the order that is present in the data supplied. Set `categoryorder` to *category ascending* or *category descending* if order should be determined by the alphanumerical order of the category names. Set `categoryorder` to "array" to derive the ordering from the attribute `categoryarray`. If a category is not found in the `categoryarray` array, the sorting behavior for that attribute will be identical to the "trace" mode. The unspecified categories will follow the categories in `categoryarray`. Set `categoryorder` to *total ascending* or *total descending* if order should be determined by the numerical order of the values. Similarly, the order can be determined by the min, max, sum, mean or median of all the values. color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. constrain If this axis needs to be compressed (either due to its own `scaleanchor` and `scaleratio` or those of the other axis), determines how that happens: by increasing the "range" (default), or by decreasing the "domain". constraintoward If this axis needs to be compressed (either due to its own `scaleanchor` and `scaleratio` or those of the other axis), determines which direction we push the originally specified plot area. Options are "left", "center" (default), and "right" for x axes, and "top", "middle" (default), and "bottom" for y axes. dividercolor Sets the color of the dividers Only has an effect on "multicategory" axes. dividerwidth Sets the width (in px) of the dividers Only has an effect on "multicategory" axes. domain Sets the domain of this axis (in plot fraction). dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. fixedrange Determines whether or not this axis is zoom- able. If true, then zoom is disabled. gridcolor Sets the color of the grid lines. gridwidth Sets the width (in px) of the grid lines. hoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" layer Sets the layer on which this axis is displayed. If *above traces*, this axis is displayed above all the subplot's traces If *below traces*, this axis is displayed below all the subplot's traces, but above the grid lines. Useful when used together with scatter-like traces with `cliponaxis` set to False to show markers and/or text nodes above this axis. linecolor Sets the axis line color. linewidth Sets the width (in px) of the axis line. matches If set to another axis id (e.g. `x2`, `y`), the range of this axis will match the range of the corresponding axis in data-coordinates space. Moreover, matching axes share auto-range values, category lists and histogram auto-bins. Note that setting axes simultaneously in both a `scaleanchor` and a `matches` constraint is currently forbidden. Moreover, note that matching axes must have the same `type`. mirror Determines if the axis lines or/and ticks are mirrored to the opposite side of the plotting area. If True, the axis lines are mirrored. If "ticks", the axis lines and ticks are mirrored. If False, mirroring is disable. If "all", axis lines are mirrored on all shared-axes subplots. If "allticks", axis lines and ticks are mirrored on all shared-axes subplots. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". overlaying If set a same-letter axis id, this axis is overlaid on top of the corresponding same- letter axis, with traces and axes visible for both axes. If False, this axis does not overlay any same-letter axes. In this case, for axes with overlapping domains only the highest- numbered axis will be visible. position Sets the position of this axis in the plotting space (in normalized coordinates). Only has an effect if `anchor` is set to "free". range Sets the range of this axis. If the axis `type` is "log", then you must take the log of your desired range (e.g. to set the range from 1 to 100, set the range from 0 to 2). If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. rangemode If "normal", the range is computed in relation to the extrema of the input data. If *tozero*`, the range extends to 0, regardless of the input data If "nonnegative", the range is non- negative, regardless of the input data. Applies only to linear axes. scaleanchor If set to another axis id (e.g. `x2`, `y`), the range of this axis changes together with the range of the corresponding axis such that the scale of pixels per unit is in a constant ratio. Both axes are still zoomable, but when you zoom one, the other will zoom the same amount, keeping a fixed midpoint. `constrain` and `constraintoward` determine how we enforce the constraint. You can chain these, ie `yaxis: {scaleanchor: *x*}, xaxis2: {scaleanchor: *y*}` but you can only link axes of the same `type`. The linked axis can have the opposite letter (to constrain the aspect ratio) or the same letter (to match scales across subplots). Loops (`yaxis: {scaleanchor: *x*}, xaxis: {scaleanchor: *y*}` or longer) are redundant and the last constraint encountered will be ignored to avoid possible inconsistent constraints via `scaleratio`. Note that setting axes simultaneously in both a `scaleanchor` and a `matches` constraint is currently forbidden. scaleratio If this axis is linked to another by `scaleanchor`, this determines the pixel to unit scale ratio. For example, if this value is 10, then every unit on this axis spans 10 times the number of pixels as a unit on the linked axis. Use this for example to create an elevation profile where the vertical scale is exaggerated a fixed amount with respect to the horizontal. separatethousands If "true", even 4-digit integers are separated showdividers Determines whether or not a dividers are drawn between the category levels of this axis. Only has an effect on "multicategory" axes. showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showgrid Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. showline Determines whether or not a line bounding this axis is drawn. showspikes Determines whether or not spikes (aka droplines) are drawn for this axis. Note: This only takes affect when hovermode = closest showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. side Determines whether a x (y) axis is positioned at the "bottom" ("left") or "top" ("right") of the plotting area. spikecolor Sets the spike color. If undefined, will use the series color spikedash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). spikemode Determines the drawing mode for the spike line If "toaxis", the line is drawn from the data point to the axis the series is plotted on. If "across", the line is drawn across the entire plot area, and supercedes "toaxis". If "marker", then a marker dot is drawn on the axis the series is plotted on spikesnap Determines whether spikelines are stuck to the cursor or to the closest datapoints. spikethickness Sets the width (in px) of the zero line. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the tick font. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.layout.yaxis.Ti ckformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.lay out.yaxis.tickformatstopdefaults), sets the default property values to use for elements of layout.yaxis.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. tickson Determines where ticks and grid lines are drawn with respect to their corresponding tick labels. Only has an effect for axes of `type` "category" or "multicategory". When set to "boundaries", ticks and grid lines are drawn half a category to the left/bottom of labels. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.layout.yaxis.Title instance or dict with compatible properties titlefont Deprecated: Please use layout.yaxis.title.font instead. Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. type Sets the axis type. By default, plotly attempts to determined the axis type by looking into the data of the traces that referenced the axis in question. uirevision Controls persistence of user-driven changes in axis `range`, `autorange`, and `title` if in `editable: true` configuration. Defaults to `layout.uirevision`. visible A single toggle to hide the axis while preserving interaction like dragging. Default is true when a cheater plot is present on the axis, otherwise false zeroline Determines whether or not a line is drawn at along the 0 value of this axis. If True, the zero line is drawn on top of the grid lines. zerolinecolor Sets the line color of the zero line. zerolinewidth Sets the width (in px) of the zero line. """, ), **kwargs ) import _plotly_utils.basevalidators class XAxisValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="xaxis", parent_name="layout", **kwargs): super(XAxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "XAxis"), data_docs=kwargs.pop( "data_docs", """ anchor If set to an opposite-letter axis id (e.g. `x2`, `y`), this axis is bound to the corresponding opposite-letter axis. If set to "free", this axis' position is determined by `position`. automargin Determines whether long tick labels automatically grow the figure margins. autorange Determines whether or not the range of this axis is computed in relation to the input data. See `rangemode` for more info. If `range` is provided, then `autorange` is set to False. calendar Sets the calendar system to use for `range` and `tick0` if this is a date axis. This does not set the calendar for interpreting data on this axis, that's specified in the trace or via the global `layout.calendar` categoryarray Sets the order in which categories on this axis appear. Only has an effect if `categoryorder` is set to "array". Used with `categoryorder`. categoryarraysrc Sets the source reference on plot.ly for categoryarray . categoryorder Specifies the ordering logic for the case of categorical variables. By default, plotly uses "trace", which specifies the order that is present in the data supplied. Set `categoryorder` to *category ascending* or *category descending* if order should be determined by the alphanumerical order of the category names. Set `categoryorder` to "array" to derive the ordering from the attribute `categoryarray`. If a category is not found in the `categoryarray` array, the sorting behavior for that attribute will be identical to the "trace" mode. The unspecified categories will follow the categories in `categoryarray`. Set `categoryorder` to *total ascending* or *total descending* if order should be determined by the numerical order of the values. Similarly, the order can be determined by the min, max, sum, mean or median of all the values. color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. constrain If this axis needs to be compressed (either due to its own `scaleanchor` and `scaleratio` or those of the other axis), determines how that happens: by increasing the "range" (default), or by decreasing the "domain". constraintoward If this axis needs to be compressed (either due to its own `scaleanchor` and `scaleratio` or those of the other axis), determines which direction we push the originally specified plot area. Options are "left", "center" (default), and "right" for x axes, and "top", "middle" (default), and "bottom" for y axes. dividercolor Sets the color of the dividers Only has an effect on "multicategory" axes. dividerwidth Sets the width (in px) of the dividers Only has an effect on "multicategory" axes. domain Sets the domain of this axis (in plot fraction). dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. fixedrange Determines whether or not this axis is zoom- able. If true, then zoom is disabled. gridcolor Sets the color of the grid lines. gridwidth Sets the width (in px) of the grid lines. hoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" layer Sets the layer on which this axis is displayed. If *above traces*, this axis is displayed above all the subplot's traces If *below traces*, this axis is displayed below all the subplot's traces, but above the grid lines. Useful when used together with scatter-like traces with `cliponaxis` set to False to show markers and/or text nodes above this axis. linecolor Sets the axis line color. linewidth Sets the width (in px) of the axis line. matches If set to another axis id (e.g. `x2`, `y`), the range of this axis will match the range of the corresponding axis in data-coordinates space. Moreover, matching axes share auto-range values, category lists and histogram auto-bins. Note that setting axes simultaneously in both a `scaleanchor` and a `matches` constraint is currently forbidden. Moreover, note that matching axes must have the same `type`. mirror Determines if the axis lines or/and ticks are mirrored to the opposite side of the plotting area. If True, the axis lines are mirrored. If "ticks", the axis lines and ticks are mirrored. If False, mirroring is disable. If "all", axis lines are mirrored on all shared-axes subplots. If "allticks", axis lines and ticks are mirrored on all shared-axes subplots. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". overlaying If set a same-letter axis id, this axis is overlaid on top of the corresponding same- letter axis, with traces and axes visible for both axes. If False, this axis does not overlay any same-letter axes. In this case, for axes with overlapping domains only the highest- numbered axis will be visible. position Sets the position of this axis in the plotting space (in normalized coordinates). Only has an effect if `anchor` is set to "free". range Sets the range of this axis. If the axis `type` is "log", then you must take the log of your desired range (e.g. to set the range from 1 to 100, set the range from 0 to 2). If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. rangemode If "normal", the range is computed in relation to the extrema of the input data. If *tozero*`, the range extends to 0, regardless of the input data If "nonnegative", the range is non- negative, regardless of the input data. Applies only to linear axes. rangeselector plotly.graph_objects.layout.xaxis.Rangeselector instance or dict with compatible properties rangeslider plotly.graph_objects.layout.xaxis.Rangeslider instance or dict with compatible properties scaleanchor If set to another axis id (e.g. `x2`, `y`), the range of this axis changes together with the range of the corresponding axis such that the scale of pixels per unit is in a constant ratio. Both axes are still zoomable, but when you zoom one, the other will zoom the same amount, keeping a fixed midpoint. `constrain` and `constraintoward` determine how we enforce the constraint. You can chain these, ie `yaxis: {scaleanchor: *x*}, xaxis2: {scaleanchor: *y*}` but you can only link axes of the same `type`. The linked axis can have the opposite letter (to constrain the aspect ratio) or the same letter (to match scales across subplots). Loops (`yaxis: {scaleanchor: *x*}, xaxis: {scaleanchor: *y*}` or longer) are redundant and the last constraint encountered will be ignored to avoid possible inconsistent constraints via `scaleratio`. Note that setting axes simultaneously in both a `scaleanchor` and a `matches` constraint is currently forbidden. scaleratio If this axis is linked to another by `scaleanchor`, this determines the pixel to unit scale ratio. For example, if this value is 10, then every unit on this axis spans 10 times the number of pixels as a unit on the linked axis. Use this for example to create an elevation profile where the vertical scale is exaggerated a fixed amount with respect to the horizontal. separatethousands If "true", even 4-digit integers are separated showdividers Determines whether or not a dividers are drawn between the category levels of this axis. Only has an effect on "multicategory" axes. showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showgrid Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. showline Determines whether or not a line bounding this axis is drawn. showspikes Determines whether or not spikes (aka droplines) are drawn for this axis. Note: This only takes affect when hovermode = closest showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. side Determines whether a x (y) axis is positioned at the "bottom" ("left") or "top" ("right") of the plotting area. spikecolor Sets the spike color. If undefined, will use the series color spikedash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). spikemode Determines the drawing mode for the spike line If "toaxis", the line is drawn from the data point to the axis the series is plotted on. If "across", the line is drawn across the entire plot area, and supercedes "toaxis". If "marker", then a marker dot is drawn on the axis the series is plotted on spikesnap Determines whether spikelines are stuck to the cursor or to the closest datapoints. spikethickness Sets the width (in px) of the zero line. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the tick font. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.layout.xaxis.Ti ckformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.lay out.xaxis.tickformatstopdefaults), sets the default property values to use for elements of layout.xaxis.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. tickson Determines where ticks and grid lines are drawn with respect to their corresponding tick labels. Only has an effect for axes of `type` "category" or "multicategory". When set to "boundaries", ticks and grid lines are drawn half a category to the left/bottom of labels. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.layout.xaxis.Title instance or dict with compatible properties titlefont Deprecated: Please use layout.xaxis.title.font instead. Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. type Sets the axis type. By default, plotly attempts to determined the axis type by looking into the data of the traces that referenced the axis in question. uirevision Controls persistence of user-driven changes in axis `range`, `autorange`, and `title` if in `editable: true` configuration. Defaults to `layout.uirevision`. visible A single toggle to hide the axis while preserving interaction like dragging. Default is true when a cheater plot is present on the axis, otherwise false zeroline Determines whether or not a line is drawn at along the 0 value of this axis. If True, the zero line is drawn on top of the grid lines. zerolinecolor Sets the line color of the zero line. zerolinewidth Sets the width (in px) of the zero line. """, ), **kwargs ) import _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="layout", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 10), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class WaterfallmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="waterfallmode", parent_name="layout", **kwargs): super(WaterfallmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["group", "overlay"]), **kwargs ) import _plotly_utils.basevalidators class WaterfallgroupgapValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="waterfallgroupgap", parent_name="layout", **kwargs): super(WaterfallgroupgapValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class WaterfallgapValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="waterfallgap", parent_name="layout", **kwargs): super(WaterfallgapValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ViolinmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="violinmode", parent_name="layout", **kwargs): super(ViolinmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["group", "overlay"]), **kwargs ) import _plotly_utils.basevalidators class ViolingroupgapValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="violingroupgap", parent_name="layout", **kwargs): super(ViolingroupgapValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ViolingapValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="violingap", parent_name="layout", **kwargs): super(ViolingapValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class UpdatemenuValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="updatemenudefaults", parent_name="layout", **kwargs ): super(UpdatemenuValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Updatemenu"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class UpdatemenusValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__(self, plotly_name="updatemenus", parent_name="layout", **kwargs): super(UpdatemenusValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Updatemenu"), data_docs=kwargs.pop( "data_docs", """ active Determines which button (by index starting from 0) is considered active. bgcolor Sets the background color of the update menu buttons. bordercolor Sets the color of the border enclosing the update menu. borderwidth Sets the width (in px) of the border enclosing the update menu. buttons A tuple of plotly.graph_objects.layout.updatemenu.Button instances or dicts with compatible properties buttondefaults When used in a template (as layout.template.lay out.updatemenu.buttondefaults), sets the default property values to use for elements of layout.updatemenu.buttons direction Determines the direction in which the buttons are laid out, whether in a dropdown menu or a row/column of buttons. For `left` and `up`, the buttons will still appear in left-to-right or top-to-bottom order respectively. font Sets the font of the update menu button text. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. pad Sets the padding around the buttons or dropdown menu. showactive Highlights active dropdown item or active button if true. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. type Determines whether the buttons are accessible via a dropdown menu or whether the buttons are stacked horizontally or vertically visible Determines whether or not the update menu is visible. x Sets the x position (in normalized coordinates) of the update menu. xanchor Sets the update menu's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the range selector. y Sets the y position (in normalized coordinates) of the update menu. yanchor Sets the update menu's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the range selector. """, ), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="layout", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TreemapcolorwayValidator(_plotly_utils.basevalidators.ColorlistValidator): def __init__(self, plotly_name="treemapcolorway", parent_name="layout", **kwargs): super(TreemapcolorwayValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TransitionValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="transition", parent_name="layout", **kwargs): super(TransitionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Transition"), data_docs=kwargs.pop( "data_docs", """ duration The duration of the transition, in milliseconds. If equal to zero, updates are synchronous. easing The easing function used for the transition ordering Determines whether the figure's layout or traces smoothly transitions during updates that make both traces and layout change. """, ), **kwargs ) import _plotly_utils.basevalidators class TitleValidator(_plotly_utils.basevalidators.TitleValidator): def __init__(self, plotly_name="title", parent_name="layout", **kwargs): super(TitleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Title"), data_docs=kwargs.pop( "data_docs", """ font Sets the title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. pad Sets the padding of the title. Each padding value only applies when the corresponding `xanchor`/`yanchor` value is set accordingly. E.g. for left padding to take effect, `xanchor` must be set to "left". The same rule applies if `xanchor`/`yanchor` is determined automatically. Padding is muted if the respective anchor value is "middle*/*center". text Sets the plot's title. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. x Sets the x position with respect to `xref` in normalized coordinates from 0 (left) to 1 (right). xanchor Sets the title's horizontal alignment with respect to its x position. "left" means that the title starts at x, "right" means that the title ends at x and "center" means that the title's center is at x. "auto" divides `xref` by three and calculates the `xanchor` value automatically based on the value of `x`. xref Sets the container `x` refers to. "container" spans the entire `width` of the plot. "paper" refers to the width of the plotting area only. y Sets the y position with respect to `yref` in normalized coordinates from 0 (bottom) to 1 (top). "auto" places the baseline of the title onto the vertical center of the top margin. yanchor Sets the title's vertical alignment with respect to its y position. "top" means that the title's cap line is at y, "bottom" means that the title's baseline is at y and "middle" means that the title's midline is at y. "auto" divides `yref` by three and calculates the `yanchor` value automatically based on the value of `y`. yref Sets the container `y` refers to. "container" spans the entire `height` of the plot. "paper" refers to the height of the plotting area only. """, ), **kwargs ) import _plotly_utils.basevalidators class TernaryValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="ternary", parent_name="layout", **kwargs): super(TernaryValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Ternary"), data_docs=kwargs.pop( "data_docs", """ aaxis plotly.graph_objects.layout.ternary.Aaxis instance or dict with compatible properties baxis plotly.graph_objects.layout.ternary.Baxis instance or dict with compatible properties bgcolor Set the background color of the subplot caxis plotly.graph_objects.layout.ternary.Caxis instance or dict with compatible properties domain plotly.graph_objects.layout.ternary.Domain instance or dict with compatible properties sum The number each triplet should sum to, and the maximum range of each axis uirevision Controls persistence of user-driven changes in axis `min` and `title`, if not overridden in the individual axes. Defaults to `layout.uirevision`. """, ), **kwargs ) import _plotly_utils.basevalidators class TemplateValidator(_plotly_utils.basevalidators.BaseTemplateValidator): def __init__(self, plotly_name="template", parent_name="layout", **kwargs): super(TemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Template"), data_docs=kwargs.pop( "data_docs", """ data plotly.graph_objects.layout.template.Data instance or dict with compatible properties layout plotly.graph_objects.Layout instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class SunburstcolorwayValidator(_plotly_utils.basevalidators.ColorlistValidator): def __init__(self, plotly_name="sunburstcolorway", parent_name="layout", **kwargs): super(SunburstcolorwayValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SpikedistanceValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="spikedistance", parent_name="layout", **kwargs): super(SpikedistanceValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", -1), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SliderValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="sliderdefaults", parent_name="layout", **kwargs): super(SliderValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Slider"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class SlidersValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__(self, plotly_name="sliders", parent_name="layout", **kwargs): super(SlidersValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Slider"), data_docs=kwargs.pop( "data_docs", """ active Determines which button (by index starting from 0) is considered active. activebgcolor Sets the background color of the slider grip while dragging. bgcolor Sets the background color of the slider. bordercolor Sets the color of the border enclosing the slider. borderwidth Sets the width (in px) of the border enclosing the slider. currentvalue plotly.graph_objects.layout.slider.Currentvalue instance or dict with compatible properties font Sets the font of the slider step labels. len Sets the length of the slider This measure excludes the padding of both ends. That is, the slider's length is this length minus the padding on both ends. lenmode Determines whether this slider length is set in units of plot "fraction" or in *pixels. Use `len` to set the value. minorticklen Sets the length in pixels of minor step tick marks name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. pad Set the padding of the slider component along each side. steps A tuple of plotly.graph_objects.layout.slider.Step instances or dicts with compatible properties stepdefaults When used in a template (as layout.template.layout.slider.stepdefaults), sets the default property values to use for elements of layout.slider.steps templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. tickcolor Sets the color of the border enclosing the slider. ticklen Sets the length in pixels of step tick marks tickwidth Sets the tick width (in px). transition plotly.graph_objects.layout.slider.Transition instance or dict with compatible properties visible Determines whether or not the slider is visible. x Sets the x position (in normalized coordinates) of the slider. xanchor Sets the slider's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the range selector. y Sets the y position (in normalized coordinates) of the slider. yanchor Sets the slider's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the range selector. """, ), **kwargs ) import _plotly_utils.basevalidators class ShowlegendValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showlegend", parent_name="layout", **kwargs): super(ShowlegendValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "legend"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ShapeValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="shapedefaults", parent_name="layout", **kwargs): super(ShapeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Shape"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class ShapesValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__(self, plotly_name="shapes", parent_name="layout", **kwargs): super(ShapesValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Shape"), data_docs=kwargs.pop( "data_docs", """ fillcolor Sets the color filling the shape's interior. layer Specifies whether shapes are drawn below or above traces. line plotly.graph_objects.layout.shape.Line instance or dict with compatible properties name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. opacity Sets the opacity of the shape. path For `type` "path" - a valid SVG path with the pixel values replaced by data values in `xsizemode`/`ysizemode` being "scaled" and taken unmodified as pixels relative to `xanchor` and `yanchor` in case of "pixel" size mode. There are a few restrictions / quirks only absolute instructions, not relative. So the allowed segments are: M, L, H, V, Q, C, T, S, and Z arcs (A) are not allowed because radius rx and ry are relative. In the future we could consider supporting relative commands, but we would have to decide on how to handle date and log axes. Note that even as is, Q and C Bezier paths that are smooth on linear axes may not be smooth on log, and vice versa. no chained "polybezier" commands - specify the segment type for each one. On category axes, values are numbers scaled to the serial numbers of categories because using the categories themselves there would be no way to describe fractional positions On data axes: because space and T are both normal components of path strings, we can't use either to separate date from time parts. Therefore we'll use underscore for this purpose: 2015-02-21_13:45:56.789 templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. type Specifies the shape type to be drawn. If "line", a line is drawn from (`x0`,`y0`) to (`x1`,`y1`) with respect to the axes' sizing mode. If "circle", a circle is drawn from ((`x0`+`x1`)/2, (`y0`+`y1`)/2)) with radius (|(`x0`+`x1`)/2 - `x0`|, |(`y0`+`y1`)/2 -`y0`)|) with respect to the axes' sizing mode. If "rect", a rectangle is drawn linking (`x0`,`y0`), (`x1`,`y0`), (`x1`,`y1`), (`x0`,`y1`), (`x0`,`y0`) with respect to the axes' sizing mode. If "path", draw a custom SVG path using `path`. with respect to the axes' sizing mode. visible Determines whether or not this shape is visible. x0 Sets the shape's starting x position. See `type` and `xsizemode` for more info. x1 Sets the shape's end x position. See `type` and `xsizemode` for more info. xanchor Only relevant in conjunction with `xsizemode` set to "pixel". Specifies the anchor point on the x axis to which `x0`, `x1` and x coordinates within `path` are relative to. E.g. useful to attach a pixel sized shape to a certain data value. No effect when `xsizemode` not set to "pixel". xref Sets the shape's x coordinate axis. If set to an x axis id (e.g. "x" or "x2"), the `x` position refers to an x coordinate. If set to "paper", the `x` position refers to the distance from the left side of the plotting area in normalized coordinates where 0 (1) corresponds to the left (right) side. If the axis `type` is "log", then you must take the log of your desired range. If the axis `type` is "date", then you must convert the date to unix time in milliseconds. xsizemode Sets the shapes's sizing mode along the x axis. If set to "scaled", `x0`, `x1` and x coordinates within `path` refer to data values on the x axis or a fraction of the plot area's width (`xref` set to "paper"). If set to "pixel", `xanchor` specifies the x position in terms of data or plot fraction but `x0`, `x1` and x coordinates within `path` are pixels relative to `xanchor`. This way, the shape can have a fixed width while maintaining a position relative to data or plot fraction. y0 Sets the shape's starting y position. See `type` and `ysizemode` for more info. y1 Sets the shape's end y position. See `type` and `ysizemode` for more info. yanchor Only relevant in conjunction with `ysizemode` set to "pixel". Specifies the anchor point on the y axis to which `y0`, `y1` and y coordinates within `path` are relative to. E.g. useful to attach a pixel sized shape to a certain data value. No effect when `ysizemode` not set to "pixel". yref Sets the annotation's y coordinate axis. If set to an y axis id (e.g. "y" or "y2"), the `y` position refers to an y coordinate If set to "paper", the `y` position refers to the distance from the bottom of the plotting area in normalized coordinates where 0 (1) corresponds to the bottom (top). ysizemode Sets the shapes's sizing mode along the y axis. If set to "scaled", `y0`, `y1` and y coordinates within `path` refer to data values on the y axis or a fraction of the plot area's height (`yref` set to "paper"). If set to "pixel", `yanchor` specifies the y position in terms of data or plot fraction but `y0`, `y1` and y coordinates within `path` are pixels relative to `yanchor`. This way, the shape can have a fixed height while maintaining a position relative to data or plot fraction. """, ), **kwargs ) import _plotly_utils.basevalidators class SeparatorsValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="separators", parent_name="layout", **kwargs): super(SeparatorsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SelectionrevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="selectionrevision", parent_name="layout", **kwargs): super(SelectionrevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SelectdirectionValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="selectdirection", parent_name="layout", **kwargs): super(SelectdirectionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["h", "v", "d", "any"]), **kwargs ) import _plotly_utils.basevalidators class SceneValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="scene", parent_name="layout", **kwargs): super(SceneValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Scene"), data_docs=kwargs.pop( "data_docs", """ annotations A tuple of plotly.graph_objects.layout.scene.Annotation instances or dicts with compatible properties annotationdefaults When used in a template (as layout.template.lay out.scene.annotationdefaults), sets the default property values to use for elements of layout.scene.annotations aspectmode If "cube", this scene's axes are drawn as a cube, regardless of the axes' ranges. If "data", this scene's axes are drawn in proportion with the axes' ranges. If "manual", this scene's axes are drawn in proportion with the input of "aspectratio" (the default behavior if "aspectratio" is provided). If "auto", this scene's axes are drawn using the results of "data" except when one axis is more than four times the size of the two others, where in that case the results of "cube" are used. aspectratio Sets this scene's axis aspectratio. bgcolor camera plotly.graph_objects.layout.scene.Camera instance or dict with compatible properties domain plotly.graph_objects.layout.scene.Domain instance or dict with compatible properties dragmode Determines the mode of drag interactions for this scene. hovermode Determines the mode of hover interactions for this scene. uirevision Controls persistence of user-driven changes in camera attributes. Defaults to `layout.uirevision`. xaxis plotly.graph_objects.layout.scene.XAxis instance or dict with compatible properties yaxis plotly.graph_objects.layout.scene.YAxis instance or dict with compatible properties zaxis plotly.graph_objects.layout.scene.ZAxis instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class RadialAxisValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="radialaxis", parent_name="layout", **kwargs): super(RadialAxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "RadialAxis"), data_docs=kwargs.pop( "data_docs", """ domain Polar chart subplots are not supported yet. This key has currently no effect. endpadding Legacy polar charts are deprecated! Please switch to "polar" subplots. orientation Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the orientation (an angle with respect to the origin) of the radial axis. range Legacy polar charts are deprecated! Please switch to "polar" subplots. Defines the start and end point of this radial axis. showline Legacy polar charts are deprecated! Please switch to "polar" subplots. Determines whether or not the line bounding this radial axis will be shown on the figure. showticklabels Legacy polar charts are deprecated! Please switch to "polar" subplots. Determines whether or not the radial axis ticks will feature tick labels. tickcolor Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the color of the tick lines on this radial axis. ticklen Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the length of the tick lines on this radial axis. tickorientation Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the orientation (from the paper perspective) of the radial axis tick labels. ticksuffix Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the length of the tick lines on this radial axis. visible Legacy polar charts are deprecated! Please switch to "polar" subplots. Determines whether or not this axis will be visible. """, ), **kwargs ) import _plotly_utils.basevalidators class PolarValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="polar", parent_name="layout", **kwargs): super(PolarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Polar"), data_docs=kwargs.pop( "data_docs", """ angularaxis plotly.graph_objects.layout.polar.AngularAxis instance or dict with compatible properties bargap Sets the gap between bars of adjacent location coordinates. Values are unitless, they represent fractions of the minimum difference in bar positions in the data. barmode Determines how bars at the same location coordinate are displayed on the graph. With "stack", the bars are stacked on top of one another With "overlay", the bars are plotted over one another, you might need to an "opacity" to see multiple bars. bgcolor Set the background color of the subplot domain plotly.graph_objects.layout.polar.Domain instance or dict with compatible properties gridshape Determines if the radial axis grid lines and angular axis line are drawn as "circular" sectors or as "linear" (polygon) sectors. Has an effect only when the angular axis has `type` "category". Note that `radialaxis.angle` is snapped to the angle of the closest vertex when `gridshape` is "circular" (so that radial axis scale is the same as the data scale). hole Sets the fraction of the radius to cut out of the polar subplot. radialaxis plotly.graph_objects.layout.polar.RadialAxis instance or dict with compatible properties sector Sets angular span of this polar subplot with two angles (in degrees). Sector are assumed to be spanned in the counterclockwise direction with 0 corresponding to rightmost limit of the polar subplot. uirevision Controls persistence of user-driven changes in axis attributes, if not overridden in the individual axes. Defaults to `layout.uirevision`. """, ), **kwargs ) import _plotly_utils.basevalidators class PlotBgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="plot_bgcolor", parent_name="layout", **kwargs): super(PlotBgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "layoutstyle"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class PiecolorwayValidator(_plotly_utils.basevalidators.ColorlistValidator): def __init__(self, plotly_name="piecolorway", parent_name="layout", **kwargs): super(PiecolorwayValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class PaperBgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="paper_bgcolor", parent_name="layout", **kwargs): super(PaperBgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OrientationValidator(_plotly_utils.basevalidators.AngleValidator): def __init__(self, plotly_name="orientation", parent_name="layout", **kwargs): super(OrientationValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ModebarValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="modebar", parent_name="layout", **kwargs): super(ModebarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Modebar"), data_docs=kwargs.pop( "data_docs", """ activecolor Sets the color of the active or hovered on icons in the modebar. bgcolor Sets the background color of the modebar. color Sets the color of the icons in the modebar. orientation Sets the orientation of the modebar. uirevision Controls persistence of user-driven changes related to the modebar, including `hovermode`, `dragmode`, and `showspikes` at both the root level and inside subplots. Defaults to `layout.uirevision`. """, ), **kwargs ) import _plotly_utils.basevalidators class MetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="metasrc", parent_name="layout", **kwargs): super(MetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetaValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="meta", parent_name="layout", **kwargs): super(MetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MarginValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="margin", parent_name="layout", **kwargs): super(MarginValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Margin"), data_docs=kwargs.pop( "data_docs", """ autoexpand Turns on/off margin expansion computations. Legends, colorbars, updatemenus, sliders, axis rangeselector and rangeslider are allowed to push the margins by defaults. b Sets the bottom margin (in px). l Sets the left margin (in px). pad Sets the amount of padding (in px) between the plotting area and the axis lines r Sets the right margin (in px). t Sets the top margin (in px). """, ), **kwargs ) import _plotly_utils.basevalidators class MapboxValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="mapbox", parent_name="layout", **kwargs): super(MapboxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Mapbox"), data_docs=kwargs.pop( "data_docs", """ accesstoken Sets the mapbox access token to be used for this mapbox map. Alternatively, the mapbox access token can be set in the configuration options under `mapboxAccessToken`. Note that accessToken are only required when `style` (e.g with values : basic, streets, outdoors, light, dark, satellite, satellite-streets ) and/or a layout layer references the Mapbox server. bearing Sets the bearing angle of the map in degrees counter-clockwise from North (mapbox.bearing). center plotly.graph_objects.layout.mapbox.Center instance or dict with compatible properties domain plotly.graph_objects.layout.mapbox.Domain instance or dict with compatible properties layers A tuple of plotly.graph_objects.layout.mapbox.Layer instances or dicts with compatible properties layerdefaults When used in a template (as layout.template.layout.mapbox.layerdefaults), sets the default property values to use for elements of layout.mapbox.layers pitch Sets the pitch angle of the map (in degrees, where 0 means perpendicular to the surface of the map) (mapbox.pitch). style Defines the map layers that are rendered by default below the trace layers defined in `data`, which are themselves by default rendered below the layers defined in `layout.mapbox.layers`. These layers can be defined either explicitly as a Mapbox Style object which can contain multiple layer definitions that load data from any public or private Tile Map Service (TMS or XYZ) or Web Map Service (WMS) or implicitly by using one of the built-in style objects which use WMSes which do not require any access tokens, or by using a default Mapbox style or custom Mapbox style URL, both of which require a Mapbox access token Note that Mapbox access token can be set in the `accesstoken` attribute or in the `mapboxAccessToken` config option. Mapbox Style objects are of the form described in the Mapbox GL JS documentation available at https://docs.mapbox.com/mapbox-gl-js/style-spec The built-in plotly.js styles objects are: open-street-map, white-bg, carto-positron, carto-darkmatter, stamen-terrain, stamen-toner, stamen-watercolor The built-in Mapbox styles are: basic, streets, outdoors, light, dark, satellite, satellite-streets Mapbox style URLs are of the form: mapbox://mapbox.mapbox-- uirevision Controls persistence of user-driven changes in the view: `center`, `zoom`, `bearing`, `pitch`. Defaults to `layout.uirevision`. zoom Sets the zoom level of the map (mapbox.zoom). """, ), **kwargs ) import _plotly_utils.basevalidators class LegendValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="legend", parent_name="layout", **kwargs): super(LegendValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Legend"), data_docs=kwargs.pop( "data_docs", """ bgcolor Sets the legend background color. Defaults to `layout.paper_bgcolor`. bordercolor Sets the color of the border enclosing the legend. borderwidth Sets the width (in px) of the border enclosing the legend. font Sets the font used to text the legend items. itemclick Determines the behavior on legend item click. "toggle" toggles the visibility of the item clicked on the graph. "toggleothers" makes the clicked item the sole visible item on the graph. False disable legend item click interactions. itemdoubleclick Determines the behavior on legend item double- click. "toggle" toggles the visibility of the item clicked on the graph. "toggleothers" makes the clicked item the sole visible item on the graph. False disable legend item double-click interactions. itemsizing Determines if the legend items symbols scale with their corresponding "trace" attributes or remain "constant" independent of the symbol size on the graph. orientation Sets the orientation of the legend. tracegroupgap Sets the amount of vertical space (in px) between legend groups. traceorder Determines the order at which the legend items are displayed. If "normal", the items are displayed top-to-bottom in the same order as the input data. If "reversed", the items are displayed in the opposite order as "normal". If "grouped", the items are displayed in groups (when a trace `legendgroup` is provided). if "grouped+reversed", the items are displayed in the opposite order as "grouped". uirevision Controls persistence of legend-driven changes in trace and pie label visibility. Defaults to `layout.uirevision`. valign Sets the vertical alignment of the symbols with respect to their associated text. x Sets the x position (in normalized coordinates) of the legend. Defaults to 1.02 for vertical legends and defaults to 0 for horizontal legends. xanchor Sets the legend's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the legend. Value "auto" anchors legends to the right for `x` values greater than or equal to 2/3, anchors legends to the left for `x` values less than or equal to 1/3 and anchors legends with respect to their center otherwise. y Sets the y position (in normalized coordinates) of the legend. Defaults to 1 for vertical legends, defaults to "-0.1" for horizontal legends on graphs w/o range sliders and defaults to 1.1 for horizontal legends on graph with one or multiple range sliders. yanchor Sets the legend's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the legend. Value "auto" anchors legends at their bottom for `y` values less than or equal to 1/3, anchors legends to at their top for `y` values greater than or equal to 2/3 and anchors legends with respect to their middle otherwise. """, ), **kwargs ) import _plotly_utils.basevalidators class ImageValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="imagedefaults", parent_name="layout", **kwargs): super(ImageValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Image"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class ImagesValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__(self, plotly_name="images", parent_name="layout", **kwargs): super(ImagesValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Image"), data_docs=kwargs.pop( "data_docs", """ layer Specifies whether images are drawn below or above traces. When `xref` and `yref` are both set to `paper`, image is drawn below the entire plot area. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. opacity Sets the opacity of the image. sizex Sets the image container size horizontally. The image will be sized based on the `position` value. When `xref` is set to `paper`, units are sized relative to the plot width. sizey Sets the image container size vertically. The image will be sized based on the `position` value. When `yref` is set to `paper`, units are sized relative to the plot height. sizing Specifies which dimension of the image to constrain. source Specifies the URL of the image to be used. The URL must be accessible from the domain where the plot code is run, and can be either relative or absolute. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. visible Determines whether or not this image is visible. x Sets the image's x position. When `xref` is set to `paper`, units are sized relative to the plot height. See `xref` for more info xanchor Sets the anchor for the x position xref Sets the images's x coordinate axis. If set to a x axis id (e.g. "x" or "x2"), the `x` position refers to an x data coordinate If set to "paper", the `x` position refers to the distance from the left of plot in normalized coordinates where 0 (1) corresponds to the left (right). y Sets the image's y position. When `yref` is set to `paper`, units are sized relative to the plot height. See `yref` for more info yanchor Sets the anchor for the y position. yref Sets the images's y coordinate axis. If set to a y axis id (e.g. "y" or "y2"), the `y` position refers to a y data coordinate. If set to "paper", the `y` position refers to the distance from the bottom of the plot in normalized coordinates where 0 (1) corresponds to the bottom (top). """, ), **kwargs ) import _plotly_utils.basevalidators class HovermodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="hovermode", parent_name="layout", **kwargs): super(HovermodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "modebar"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["x", "y", "closest", False]), **kwargs ) import _plotly_utils.basevalidators class HoverlabelValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="hoverlabel", parent_name="layout", **kwargs): super(HoverlabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Hoverlabel"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines bgcolor Sets the background color of all hover labels on graph bordercolor Sets the border color of all hover labels on graph. font Sets the default hover label font used by all traces on the graph. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. """, ), **kwargs ) import _plotly_utils.basevalidators class HoverdistanceValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="hoverdistance", parent_name="layout", **kwargs): super(HoverdistanceValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", -1), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HidesourcesValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="hidesources", parent_name="layout", **kwargs): super(HidesourcesValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HiddenlabelssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hiddenlabelssrc", parent_name="layout", **kwargs): super(HiddenlabelssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HiddenlabelsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="hiddenlabels", parent_name="layout", **kwargs): super(HiddenlabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class HeightValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="height", parent_name="layout", **kwargs): super(HeightValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 10), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class GridValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="grid", parent_name="layout", **kwargs): super(GridValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Grid"), data_docs=kwargs.pop( "data_docs", """ columns The number of columns in the grid. If you provide a 2D `subplots` array, the length of its longest row is used as the default. If you give an `xaxes` array, its length is used as the default. But it's also possible to have a different length, if you want to leave a row at the end for non-cartesian subplots. domain plotly.graph_objects.layout.grid.Domain instance or dict with compatible properties pattern If no `subplots`, `xaxes`, or `yaxes` are given but we do have `rows` and `columns`, we can generate defaults using consecutive axis IDs, in two ways: "coupled" gives one x axis per column and one y axis per row. "independent" uses a new xy pair for each cell, left-to-right across each row then iterating rows according to `roworder`. roworder Is the first row the top or the bottom? Note that columns are always enumerated from left to right. rows The number of rows in the grid. If you provide a 2D `subplots` array or a `yaxes` array, its length is used as the default. But it's also possible to have a different length, if you want to leave a row at the end for non- cartesian subplots. subplots Used for freeform grids, where some axes may be shared across subplots but others are not. Each entry should be a cartesian subplot id, like "xy" or "x3y2", or "" to leave that cell empty. You may reuse x axes within the same column, and y axes within the same row. Non-cartesian subplots and traces that support `domain` can place themselves in this grid separately using the `gridcell` attribute. xaxes Used with `yaxes` when the x and y axes are shared across columns and rows. Each entry should be an x axis id like "x", "x2", etc., or "" to not put an x axis in that column. Entries other than "" must be unique. Ignored if `subplots` is present. If missing but `yaxes` is present, will generate consecutive IDs. xgap Horizontal space between grid cells, expressed as a fraction of the total width available to one cell. Defaults to 0.1 for coupled-axes grids and 0.2 for independent grids. xside Sets where the x axis labels and titles go. "bottom" means the very bottom of the grid. "bottom plot" is the lowest plot that each x axis is used in. "top" and "top plot" are similar. yaxes Used with `yaxes` when the x and y axes are shared across columns and rows. Each entry should be an y axis id like "y", "y2", etc., or "" to not put a y axis in that row. Entries other than "" must be unique. Ignored if `subplots` is present. If missing but `xaxes` is present, will generate consecutive IDs. ygap Vertical space between grid cells, expressed as a fraction of the total height available to one cell. Defaults to 0.1 for coupled-axes grids and 0.3 for independent grids. yside Sets where the y axis labels and titles go. "left" means the very left edge of the grid. *left plot* is the leftmost plot that each y axis is used in. "right" and *right plot* are similar. """, ), **kwargs ) import _plotly_utils.basevalidators class GeoValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="geo", parent_name="layout", **kwargs): super(GeoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Geo"), data_docs=kwargs.pop( "data_docs", """ bgcolor Set the background color of the map center plotly.graph_objects.layout.geo.Center instance or dict with compatible properties coastlinecolor Sets the coastline color. coastlinewidth Sets the coastline stroke width (in px). countrycolor Sets line color of the country boundaries. countrywidth Sets line width (in px) of the country boundaries. domain plotly.graph_objects.layout.geo.Domain instance or dict with compatible properties framecolor Sets the color the frame. framewidth Sets the stroke width (in px) of the frame. lakecolor Sets the color of the lakes. landcolor Sets the land mass color. lataxis plotly.graph_objects.layout.geo.Lataxis instance or dict with compatible properties lonaxis plotly.graph_objects.layout.geo.Lonaxis instance or dict with compatible properties oceancolor Sets the ocean color projection plotly.graph_objects.layout.geo.Projection instance or dict with compatible properties resolution Sets the resolution of the base layers. The values have units of km/mm e.g. 110 corresponds to a scale ratio of 1:110,000,000. rivercolor Sets color of the rivers. riverwidth Sets the stroke width (in px) of the rivers. scope Set the scope of the map. showcoastlines Sets whether or not the coastlines are drawn. showcountries Sets whether or not country boundaries are drawn. showframe Sets whether or not a frame is drawn around the map. showlakes Sets whether or not lakes are drawn. showland Sets whether or not land masses are filled in color. showocean Sets whether or not oceans are filled in color. showrivers Sets whether or not rivers are drawn. showsubunits Sets whether or not boundaries of subunits within countries (e.g. states, provinces) are drawn. subunitcolor Sets the color of the subunits boundaries. subunitwidth Sets the stroke width (in px) of the subunits boundaries. uirevision Controls persistence of user-driven changes in the view (projection and center). Defaults to `layout.uirevision`. """, ), **kwargs ) import _plotly_utils.basevalidators class FunnelmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="funnelmode", parent_name="layout", **kwargs): super(FunnelmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["stack", "group", "overlay"]), **kwargs ) import _plotly_utils.basevalidators class FunnelgroupgapValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="funnelgroupgap", parent_name="layout", **kwargs): super(FunnelgroupgapValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FunnelgapValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="funnelgap", parent_name="layout", **kwargs): super(FunnelgapValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FunnelareacolorwayValidator(_plotly_utils.basevalidators.ColorlistValidator): def __init__( self, plotly_name="funnelareacolorway", parent_name="layout", **kwargs ): super(FunnelareacolorwayValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="font", parent_name="layout", **kwargs): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class ExtendtreemapcolorsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="extendtreemapcolors", parent_name="layout", **kwargs ): super(ExtendtreemapcolorsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ExtendsunburstcolorsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="extendsunburstcolors", parent_name="layout", **kwargs ): super(ExtendsunburstcolorsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ExtendpiecolorsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="extendpiecolors", parent_name="layout", **kwargs): super(ExtendpiecolorsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ExtendfunnelareacolorsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="extendfunnelareacolors", parent_name="layout", **kwargs ): super(ExtendfunnelareacolorsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EditrevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="editrevision", parent_name="layout", **kwargs): super(EditrevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DragmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="dragmode", parent_name="layout", **kwargs): super(DragmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "modebar"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", ["zoom", "pan", "select", "lasso", "orbit", "turntable", False], ), **kwargs ) import _plotly_utils.basevalidators class DirectionValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="direction", parent_name="layout", **kwargs): super(DirectionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["clockwise", "counterclockwise"]), **kwargs ) import _plotly_utils.basevalidators class DatarevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="datarevision", parent_name="layout", **kwargs): super(DatarevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorwayValidator(_plotly_utils.basevalidators.ColorlistValidator): def __init__(self, plotly_name="colorway", parent_name="layout", **kwargs): super(ColorwayValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="colorscale", parent_name="layout", **kwargs): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Colorscale"), data_docs=kwargs.pop( "data_docs", """ diverging Sets the default diverging colorscale. Note that `autocolorscale` must be true for this attribute to work. sequential Sets the default sequential colorscale for positive values. Note that `autocolorscale` must be true for this attribute to work. sequentialminus Sets the default sequential colorscale for negative values. Note that `autocolorscale` must be true for this attribute to work. """, ), **kwargs ) import _plotly_utils.basevalidators class ColoraxisValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="coloraxis", parent_name="layout", **kwargs): super(ColoraxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Coloraxis"), data_docs=kwargs.pop( "data_docs", """ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here corresponding trace color array(s)) or the bounds set in `cmin` and `cmax` Defaults to `false` when `cmin` and `cmax` are set by the user. cmax Sets the upper bound of the color domain. Value should have the same units as corresponding trace color array(s) and if set, `cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `cmin` and/or `cmax` to be equidistant to this point. Value should have the same units as corresponding trace color array(s). Has no effect when `cauto` is `false`. cmin Sets the lower bound of the color domain. Value should have the same units as corresponding trace color array(s) and if set, `cmax` must be set as well. colorbar plotly.graph_objects.layout.coloraxis.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`cmin` and `cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Grey s,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Blues, Picnic,Rainbow,Portland,Jet,Hot,Blackbody,Earth ,Electric,Viridis,Cividis. reversescale Reverses the color mapping if true. If true, `cmin` will correspond to the last color in the array and `cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. """, ), **kwargs ) import _plotly_utils.basevalidators class ClickmodeValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="clickmode", parent_name="layout", **kwargs): super(ClickmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), extras=kwargs.pop("extras", ["none"]), flags=kwargs.pop("flags", ["event", "select"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CalendarValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="calendar", parent_name="layout", **kwargs): super(CalendarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "gregorian", "chinese", "coptic", "discworld", "ethiopian", "hebrew", "islamic", "julian", "mayan", "nanakshahi", "nepali", "persian", "jalali", "taiwan", "thai", "ummalqura", ], ), **kwargs ) import _plotly_utils.basevalidators class BoxmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="boxmode", parent_name="layout", **kwargs): super(BoxmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["group", "overlay"]), **kwargs ) import _plotly_utils.basevalidators class BoxgroupgapValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="boxgroupgap", parent_name="layout", **kwargs): super(BoxgroupgapValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BoxgapValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="boxgap", parent_name="layout", **kwargs): super(BoxgapValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BarnormValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="barnorm", parent_name="layout", **kwargs): super(BarnormValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["", "fraction", "percent"]), **kwargs ) import _plotly_utils.basevalidators class BarmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="barmode", parent_name="layout", **kwargs): super(BarmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["stack", "group", "overlay", "relative"]), **kwargs ) import _plotly_utils.basevalidators class BargroupgapValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="bargroupgap", parent_name="layout", **kwargs): super(BargroupgapValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BargapValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="bargap", parent_name="layout", **kwargs): super(BargapValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AutosizeValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="autosize", parent_name="layout", **kwargs): super(AutosizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AnnotationValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="annotationdefaults", parent_name="layout", **kwargs ): super(AnnotationValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Annotation"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class AnnotationsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__(self, plotly_name="annotations", parent_name="layout", **kwargs): super(AnnotationsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Annotation"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the `text` within the box. Has an effect only if `text` spans more two or more lines (i.e. `text` contains one or more
HTML tags) or if an explicit width is set to override the text width. arrowcolor Sets the color of the annotation arrow. arrowhead Sets the end annotation arrow head style. arrowside Sets the annotation arrow head position. arrowsize Sets the size of the end annotation arrow head, relative to `arrowwidth`. A value of 1 (default) gives a head about 3x as wide as the line. arrowwidth Sets the width (in px) of annotation arrow line. ax Sets the x component of the arrow tail about the arrow head. If `axref` is `pixel`, a positive (negative) component corresponds to an arrow pointing from right to left (left to right). If `axref` is an axis, this is an absolute value on that axis, like `x`, NOT a relative value. axref Indicates in what terms the tail of the annotation (ax,ay) is specified. If `pixel`, `ax` is a relative offset in pixels from `x`. If set to an x axis id (e.g. "x" or "x2"), `ax` is specified in the same terms as that axis. This is useful for trendline annotations which should continue to indicate the correct trend when zoomed. ay Sets the y component of the arrow tail about the arrow head. If `ayref` is `pixel`, a positive (negative) component corresponds to an arrow pointing from bottom to top (top to bottom). If `ayref` is an axis, this is an absolute value on that axis, like `y`, NOT a relative value. ayref Indicates in what terms the tail of the annotation (ax,ay) is specified. If `pixel`, `ay` is a relative offset in pixels from `y`. If set to a y axis id (e.g. "y" or "y2"), `ay` is specified in the same terms as that axis. This is useful for trendline annotations which should continue to indicate the correct trend when zoomed. bgcolor Sets the background color of the annotation. bordercolor Sets the color of the border enclosing the annotation `text`. borderpad Sets the padding (in px) between the `text` and the enclosing border. borderwidth Sets the width (in px) of the border enclosing the annotation `text`. captureevents Determines whether the annotation text box captures mouse move and click events, or allows those events to pass through to data points in the plot that may be behind the annotation. By default `captureevents` is False unless `hovertext` is provided. If you use the event `plotly_clickannotation` without `hovertext` you must explicitly enable `captureevents`. clicktoshow Makes this annotation respond to clicks on the plot. If you click a data point that exactly matches the `x` and `y` values of this annotation, and it is hidden (visible: false), it will appear. In "onoff" mode, you must click the same point again to make it disappear, so if you click multiple points, you can show multiple annotations. In "onout" mode, a click anywhere else in the plot (on another data point or not) will hide this annotation. If you need to show/hide this annotation in response to different `x` or `y` values, you can set `xclick` and/or `yclick`. This is useful for example to label the side of a bar. To label markers though, `standoff` is preferred over `xclick` and `yclick`. font Sets the annotation text font. height Sets an explicit height for the text box. null (default) lets the text set the box height. Taller text will be clipped. hoverlabel plotly.graph_objects.layout.annotation.Hoverlab el instance or dict with compatible properties hovertext Sets text to appear when hovering over this annotation. If omitted or blank, no hover label will appear. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. opacity Sets the opacity of the annotation (text + arrow). showarrow Determines whether or not the annotation is drawn with an arrow. If True, `text` is placed near the arrow's tail. If False, `text` lines up with the `x` and `y` provided. standoff Sets a distance, in pixels, to move the end arrowhead away from the position it is pointing at, for example to point at the edge of a marker independent of zoom. Note that this shortens the arrow from the `ax` / `ay` vector, in contrast to `xshift` / `yshift` which moves everything by this amount. startarrowhead Sets the start annotation arrow head style. startarrowsize Sets the size of the start annotation arrow head, relative to `arrowwidth`. A value of 1 (default) gives a head about 3x as wide as the line. startstandoff Sets a distance, in pixels, to move the start arrowhead away from the position it is pointing at, for example to point at the edge of a marker independent of zoom. Note that this shortens the arrow from the `ax` / `ay` vector, in contrast to `xshift` / `yshift` which moves everything by this amount. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. text Sets the text associated with this annotation. Plotly uses a subset of HTML tags to do things like newline (
), bold (), italics (), hyperlinks (). Tags , , are also supported. textangle Sets the angle at which the `text` is drawn with respect to the horizontal. valign Sets the vertical alignment of the `text` within the box. Has an effect only if an explicit height is set to override the text height. visible Determines whether or not this annotation is visible. width Sets an explicit width for the text box. null (default) lets the text set the box width. Wider text will be clipped. There is no automatic wrapping; use
to start a new line. x Sets the annotation's x position. If the axis `type` is "log", then you must take the log of your desired range. If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. xanchor Sets the text box's horizontal position anchor This anchor binds the `x` position to the "left", "center" or "right" of the annotation. For example, if `x` is set to 1, `xref` to "paper" and `xanchor` to "right" then the right-most portion of the annotation lines up with the right-most edge of the plotting area. If "auto", the anchor is equivalent to "center" for data-referenced annotations or if there is an arrow, whereas for paper-referenced with no arrow, the anchor picked corresponds to the closest side. xclick Toggle this annotation when clicking a data point whose `x` value is `xclick` rather than the annotation's `x` value. xref Sets the annotation's x coordinate axis. If set to an x axis id (e.g. "x" or "x2"), the `x` position refers to an x coordinate If set to "paper", the `x` position refers to the distance from the left side of the plotting area in normalized coordinates where 0 (1) corresponds to the left (right) side. xshift Shifts the position of the whole annotation and arrow to the right (positive) or left (negative) by this many pixels. y Sets the annotation's y position. If the axis `type` is "log", then you must take the log of your desired range. If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. yanchor Sets the text box's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the annotation. For example, if `y` is set to 1, `yref` to "paper" and `yanchor` to "top" then the top- most portion of the annotation lines up with the top-most edge of the plotting area. If "auto", the anchor is equivalent to "middle" for data-referenced annotations or if there is an arrow, whereas for paper-referenced with no arrow, the anchor picked corresponds to the closest side. yclick Toggle this annotation when clicking a data point whose `y` value is `yclick` rather than the annotation's `y` value. yref Sets the annotation's y coordinate axis. If set to an y axis id (e.g. "y" or "y2"), the `y` position refers to an y coordinate If set to "paper", the `y` position refers to the distance from the bottom of the plotting area in normalized coordinates where 0 (1) corresponds to the bottom (top). yshift Shifts the position of the whole annotation and arrow up (positive) or down (negative) by this many pixels. """, ), **kwargs ) import _plotly_utils.basevalidators class AngularAxisValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="angularaxis", parent_name="layout", **kwargs): super(AngularAxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "AngularAxis"), data_docs=kwargs.pop( "data_docs", """ domain Polar chart subplots are not supported yet. This key has currently no effect. endpadding Legacy polar charts are deprecated! Please switch to "polar" subplots. range Legacy polar charts are deprecated! Please switch to "polar" subplots. Defines the start and end point of this angular axis. showline Legacy polar charts are deprecated! Please switch to "polar" subplots. Determines whether or not the line bounding this angular axis will be shown on the figure. showticklabels Legacy polar charts are deprecated! Please switch to "polar" subplots. Determines whether or not the angular axis ticks will feature tick labels. tickcolor Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the color of the tick lines on this angular axis. ticklen Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the length of the tick lines on this angular axis. tickorientation Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the orientation (from the paper perspective) of the angular axis tick labels. ticksuffix Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the length of the tick lines on this angular axis. visible Legacy polar charts are deprecated! Please switch to "polar" subplots. Determines whether or not this axis will be visible. """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/xaxis/0000755000175000017500000000000013573746614022435 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/xaxis/tickformatstop/0000755000175000017500000000000013573746614025506 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/xaxis/tickformatstop/__init__.py0000644000175000017500000000520213573721541027606 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="value", parent_name="layout.xaxis.tickformatstop", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="layout.xaxis.tickformatstop", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="layout.xaxis.tickformatstop", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EnabledValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="enabled", parent_name="layout.xaxis.tickformatstop", **kwargs ): super(EnabledValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DtickrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="dtickrange", parent_name="layout.xaxis.tickformatstop", **kwargs ): super(DtickrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "ticks"}, {"valType": "any", "editType": "ticks"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/xaxis/rangeslider/0000755000175000017500000000000013573746614024734 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/xaxis/rangeslider/yaxis/0000755000175000017500000000000013573746614026071 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/xaxis/rangeslider/yaxis/__init__.py0000644000175000017500000000243713573721541030200 0ustar noahfxnoahfximport _plotly_utils.basevalidators class RangemodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="rangemode", parent_name="layout.xaxis.rangeslider.yaxis", **kwargs ): super(RangemodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["auto", "fixed", "match"]), **kwargs ) import _plotly_utils.basevalidators class RangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="range", parent_name="layout.xaxis.rangeslider.yaxis", **kwargs ): super(RangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "plot"}, {"valType": "any", "editType": "plot"}, ], ), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/xaxis/rangeslider/__init__.py0000644000175000017500000001213113573721541027033 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YAxisValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="yaxis", parent_name="layout.xaxis.rangeslider", **kwargs ): super(YAxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "YAxis"), data_docs=kwargs.pop( "data_docs", """ range Sets the range of this axis for the rangeslider. rangemode Determines whether or not the range of this axis in the rangeslider use the same value than in the main plot when zooming in/out. If "auto", the autorange will be used. If "fixed", the `range` is used. If "match", the current range of the corresponding y-axis on the main subplot is used. """, ), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="visible", parent_name="layout.xaxis.rangeslider", **kwargs ): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="thickness", parent_name="layout.xaxis.rangeslider", **kwargs ): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class RangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="range", parent_name="layout.xaxis.rangeslider", **kwargs ): super(RangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"autorange": False}), items=kwargs.pop( "items", [ { "valType": "any", "editType": "calc", "impliedEdits": {"^autorange": False}, }, { "valType": "any", "editType": "calc", "impliedEdits": {"^autorange": False}, }, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BorderwidthValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="borderwidth", parent_name="layout.xaxis.rangeslider", **kwargs ): super(BorderwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="layout.xaxis.rangeslider", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="layout.xaxis.rangeslider", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AutorangeValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="autorange", parent_name="layout.xaxis.rangeslider", **kwargs ): super(AutorangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/xaxis/title/0000755000175000017500000000000013573746614023556 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/xaxis/title/__init__.py0000644000175000017500000000460513573721541025664 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="text", parent_name="layout.xaxis.title", **kwargs): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class StandoffValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="standoff", parent_name="layout.xaxis.title", **kwargs ): super(StandoffValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="font", parent_name="layout.xaxis.title", **kwargs): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/xaxis/title/font/0000755000175000017500000000000013573746614024524 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/xaxis/title/font/__init__.py0000644000175000017500000000300413573721541026622 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="layout.xaxis.title.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="layout.xaxis.title.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="layout.xaxis.title.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/xaxis/rangeselector/0000755000175000017500000000000013573746614025272 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/xaxis/rangeselector/button/0000755000175000017500000000000013573746614026605 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/xaxis/rangeselector/button/__init__.py0000644000175000017500000000732013573721541030710 0ustar noahfxnoahfximport _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="visible", parent_name="layout.xaxis.rangeselector.button", **kwargs ): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="layout.xaxis.rangeselector.button", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class StepmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="stepmode", parent_name="layout.xaxis.rangeselector.button", **kwargs ): super(StepmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["backward", "todate"]), **kwargs ) import _plotly_utils.basevalidators class StepValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="step", parent_name="layout.xaxis.rangeselector.button", **kwargs ): super(StepValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", ["month", "year", "day", "hour", "minute", "second", "all"] ), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="layout.xaxis.rangeselector.button", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LabelValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="label", parent_name="layout.xaxis.rangeselector.button", **kwargs ): super(LabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CountValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="count", parent_name="layout.xaxis.rangeselector.button", **kwargs ): super(CountValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/xaxis/rangeselector/__init__.py0000644000175000017500000002273213573721541027401 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="yanchor", parent_name="layout.xaxis.rangeselector", **kwargs ): super(YanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "top", "middle", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="y", parent_name="layout.xaxis.rangeselector", **kwargs ): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="xanchor", parent_name="layout.xaxis.rangeselector", **kwargs ): super(XanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "left", "center", "right"]), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="x", parent_name="layout.xaxis.rangeselector", **kwargs ): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="visible", parent_name="layout.xaxis.rangeselector", **kwargs ): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="layout.xaxis.rangeselector", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class ButtonValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="buttondefaults", parent_name="layout.xaxis.rangeselector", **kwargs ): super(ButtonValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Button"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class ButtonsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="buttons", parent_name="layout.xaxis.rangeselector", **kwargs ): super(ButtonsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Button"), data_docs=kwargs.pop( "data_docs", """ count Sets the number of steps to take to update the range. Use with `step` to specify the update interval. label Sets the text label to appear on the button. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. step The unit of measurement that the `count` value will set the range by. stepmode Sets the range update mode. If "backward", the range update shifts the start of range back "count" times "step" milliseconds. If "todate", the range update shifts the start of range back to the first timestamp from "count" times "step" milliseconds back. For example, with `step` set to "year" and `count` set to 1 the range update shifts the start of the range back to January 01 of the current year. Month and year "todate" are currently available only for the built-in (Gregorian) calendar. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. visible Determines whether or not this button is visible. """, ), **kwargs ) import _plotly_utils.basevalidators class BorderwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="borderwidth", parent_name="layout.xaxis.rangeselector", **kwargs ): super(BorderwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="layout.xaxis.rangeselector", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="layout.xaxis.rangeselector", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ActivecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="activecolor", parent_name="layout.xaxis.rangeselector", **kwargs ): super(ActivecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/xaxis/rangeselector/font/0000755000175000017500000000000013573746614026240 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/xaxis/rangeselector/font/__init__.py0000644000175000017500000000314113573721541030340 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="layout.xaxis.rangeselector.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="layout.xaxis.rangeselector.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="layout.xaxis.rangeselector.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/xaxis/__init__.py0000644000175000017500000013270113573721542024543 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ZerolinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="zerolinewidth", parent_name="layout.xaxis", **kwargs ): super(ZerolinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ZerolinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="zerolinecolor", parent_name="layout.xaxis", **kwargs ): super(ZerolinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ZerolineValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="zeroline", parent_name="layout.xaxis", **kwargs): super(ZerolineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="visible", parent_name="layout.xaxis", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="layout.xaxis", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TypeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="type", parent_name="layout.xaxis", **kwargs): super(TypeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", ["-", "linear", "log", "date", "category", "multicategory"] ), **kwargs ) import _plotly_utils.basevalidators class TitleValidator(_plotly_utils.basevalidators.TitleValidator): def __init__(self, plotly_name="title", parent_name="layout.xaxis", **kwargs): super(TitleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Title"), data_docs=kwargs.pop( "data_docs", """ font Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. standoff Sets the standoff distance (in px) between the axis labels and the title text The default value is a function of the axis tick labels, the title `font.size` and the axis `linewidth`. Note that the axis title position is always constrained within the margins, so the actual standoff distance is always less than the set or default value. By setting `standoff` and turning on `automargin`, plotly.js will push the margins to fit the axis title at given standoff distance. text Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """, ), **kwargs ) import _plotly_utils.basevalidators class TickwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="tickwidth", parent_name="layout.xaxis", **kwargs): super(TickwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickvalssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="tickvalssrc", parent_name="layout.xaxis", **kwargs): super(TickvalssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickvalsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="tickvals", parent_name="layout.xaxis", **kwargs): super(TickvalsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="ticktextsrc", parent_name="layout.xaxis", **kwargs): super(TicktextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicktextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ticktext", parent_name="layout.xaxis", **kwargs): super(TicktextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="ticksuffix", parent_name="layout.xaxis", **kwargs): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TicksonValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="tickson", parent_name="layout.xaxis", **kwargs): super(TicksonValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["labels", "boundaries"]), **kwargs ) import _plotly_utils.basevalidators class TicksValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="ticks", parent_name="layout.xaxis", **kwargs): super(TicksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["outside", "inside", ""]), **kwargs ) import _plotly_utils.basevalidators class TickprefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="tickprefix", parent_name="layout.xaxis", **kwargs): super(TickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="tickmode", parent_name="layout.xaxis", **kwargs): super(TickmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "linear", "array"]), **kwargs ) import _plotly_utils.basevalidators class TicklenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="ticklen", parent_name="layout.xaxis", **kwargs): super(TicklenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickformatstopValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickformatstopdefaults", parent_name="layout.xaxis", **kwargs ): super(TickformatstopValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatstopsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="tickformatstops", parent_name="layout.xaxis", **kwargs ): super(TickformatstopsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="tickformat", parent_name="layout.xaxis", **kwargs): super(TickformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="tickfont", parent_name="layout.xaxis", **kwargs): super(TickfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class TickcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="tickcolor", parent_name="layout.xaxis", **kwargs): super(TickcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__(self, plotly_name="tickangle", parent_name="layout.xaxis", **kwargs): super(TickangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="tick0", parent_name="layout.xaxis", **kwargs): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SpikethicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="spikethickness", parent_name="layout.xaxis", **kwargs ): super(SpikethicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SpikesnapValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="spikesnap", parent_name="layout.xaxis", **kwargs): super(SpikesnapValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["data", "cursor"]), **kwargs ) import _plotly_utils.basevalidators class SpikemodeValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="spikemode", parent_name="layout.xaxis", **kwargs): super(SpikemodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), flags=kwargs.pop("flags", ["toaxis", "across", "marker"]), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SpikedashValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="spikedash", parent_name="layout.xaxis", **kwargs): super(SpikedashValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", ["solid", "dot", "dash", "longdash", "dashdot", "longdashdot"] ), **kwargs ) import _plotly_utils.basevalidators class SpikecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="spikecolor", parent_name="layout.xaxis", **kwargs): super(SpikecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SideValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="side", parent_name="layout.xaxis", **kwargs): super(SideValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["top", "bottom", "left", "right"]), **kwargs ) import _plotly_utils.basevalidators class ShowticksuffixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showticksuffix", parent_name="layout.xaxis", **kwargs ): super(ShowticksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowtickprefixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showtickprefix", parent_name="layout.xaxis", **kwargs ): super(ShowtickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowticklabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showticklabels", parent_name="layout.xaxis", **kwargs ): super(ShowticklabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowspikesValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showspikes", parent_name="layout.xaxis", **kwargs): super(ShowspikesValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "modebar"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowlineValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showline", parent_name="layout.xaxis", **kwargs): super(ShowlineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks+layoutstyle"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowgridValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showgrid", parent_name="layout.xaxis", **kwargs): super(ShowgridValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowexponentValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showexponent", parent_name="layout.xaxis", **kwargs ): super(ShowexponentValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowdividersValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showdividers", parent_name="layout.xaxis", **kwargs ): super(ShowdividersValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SeparatethousandsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="separatethousands", parent_name="layout.xaxis", **kwargs ): super(SeparatethousandsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ScaleratioValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="scaleratio", parent_name="layout.xaxis", **kwargs): super(ScaleratioValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ScaleanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="scaleanchor", parent_name="layout.xaxis", **kwargs): super(ScaleanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", ["/^x([2-9]|[1-9][0-9]+)?$/", "/^y([2-9]|[1-9][0-9]+)?$/"] ), **kwargs ) import _plotly_utils.basevalidators class RangesliderValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="rangeslider", parent_name="layout.xaxis", **kwargs): super(RangesliderValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Rangeslider"), data_docs=kwargs.pop( "data_docs", """ autorange Determines whether or not the range slider range is computed in relation to the input data. If `range` is provided, then `autorange` is set to False. bgcolor Sets the background color of the range slider. bordercolor Sets the border color of the range slider. borderwidth Sets the border width of the range slider. range Sets the range of the range slider. If not set, defaults to the full xaxis range. If the axis `type` is "log", then you must take the log of your desired range. If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. thickness The height of the range slider as a fraction of the total plot area height. visible Determines whether or not the range slider will be visible. If visible, perpendicular axes will be set to `fixedrange` yaxis plotly.graph_objects.layout.xaxis.rangeslider.Y Axis instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class RangeselectorValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="rangeselector", parent_name="layout.xaxis", **kwargs ): super(RangeselectorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Rangeselector"), data_docs=kwargs.pop( "data_docs", """ activecolor Sets the background color of the active range selector button. bgcolor Sets the background color of the range selector buttons. bordercolor Sets the color of the border enclosing the range selector. borderwidth Sets the width (in px) of the border enclosing the range selector. buttons Sets the specifications for each buttons. By default, a range selector comes with no buttons. buttondefaults When used in a template (as layout.template.lay out.xaxis.rangeselector.buttondefaults), sets the default property values to use for elements of layout.xaxis.rangeselector.buttons font Sets the font of the range selector button text. visible Determines whether or not this range selector is visible. Note that range selectors are only available for x axes of `type` set to or auto- typed to "date". x Sets the x position (in normalized coordinates) of the range selector. xanchor Sets the range selector's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the range selector. y Sets the y position (in normalized coordinates) of the range selector. yanchor Sets the range selector's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the range selector. """, ), **kwargs ) import _plotly_utils.basevalidators class RangemodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="rangemode", parent_name="layout.xaxis", **kwargs): super(RangemodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["normal", "tozero", "nonnegative"]), **kwargs ) import _plotly_utils.basevalidators class RangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="range", parent_name="layout.xaxis", **kwargs): super(RangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, anim=kwargs.pop("anim", True), edit_type=kwargs.pop("edit_type", "axrange"), implied_edits=kwargs.pop("implied_edits", {"autorange": False}), items=kwargs.pop( "items", [ { "valType": "any", "editType": "axrange", "impliedEdits": {"^autorange": False}, "anim": True, }, { "valType": "any", "editType": "axrange", "impliedEdits": {"^autorange": False}, "anim": True, }, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class PositionValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="position", parent_name="layout.xaxis", **kwargs): super(PositionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OverlayingValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="overlaying", parent_name="layout.xaxis", **kwargs): super(OverlayingValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", ["free", "/^x([2-9]|[1-9][0-9]+)?$/", "/^y([2-9]|[1-9][0-9]+)?$/"], ), **kwargs ) import _plotly_utils.basevalidators class NticksValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="nticks", parent_name="layout.xaxis", **kwargs): super(NticksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class MirrorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="mirror", parent_name="layout.xaxis", **kwargs): super(MirrorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks+layoutstyle"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", [True, "ticks", False, "all", "allticks"]), **kwargs ) import _plotly_utils.basevalidators class MatchesValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="matches", parent_name="layout.xaxis", **kwargs): super(MatchesValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", ["/^x([2-9]|[1-9][0-9]+)?$/", "/^y([2-9]|[1-9][0-9]+)?$/"] ), **kwargs ) import _plotly_utils.basevalidators class LinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="linewidth", parent_name="layout.xaxis", **kwargs): super(LinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks+layoutstyle"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="linecolor", parent_name="layout.xaxis", **kwargs): super(LinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "layoutstyle"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LayerValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="layer", parent_name="layout.xaxis", **kwargs): super(LayerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["above traces", "below traces"]), **kwargs ) import _plotly_utils.basevalidators class HoverformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hoverformat", parent_name="layout.xaxis", **kwargs): super(HoverformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class GridwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="gridwidth", parent_name="layout.xaxis", **kwargs): super(GridwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class GridcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="gridcolor", parent_name="layout.xaxis", **kwargs): super(GridcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FixedrangeValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="fixedrange", parent_name="layout.xaxis", **kwargs): super(FixedrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ExponentformatValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="exponentformat", parent_name="layout.xaxis", **kwargs ): super(ExponentformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "e", "E", "power", "SI", "B"]), **kwargs ) import _plotly_utils.basevalidators class DtickValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="dtick", parent_name="layout.xaxis", **kwargs): super(DtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class DomainValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="domain", parent_name="layout.xaxis", **kwargs): super(DomainValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), items=kwargs.pop( "items", [ {"valType": "number", "min": 0, "max": 1, "editType": "plot"}, {"valType": "number", "min": 0, "max": 1, "editType": "plot"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DividerwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="dividerwidth", parent_name="layout.xaxis", **kwargs ): super(DividerwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class DividercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="dividercolor", parent_name="layout.xaxis", **kwargs ): super(DividercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ConstraintowardValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="constraintoward", parent_name="layout.xaxis", **kwargs ): super(ConstraintowardValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", ["left", "center", "right", "top", "middle", "bottom"] ), **kwargs ) import _plotly_utils.basevalidators class ConstrainValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="constrain", parent_name="layout.xaxis", **kwargs): super(ConstrainValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["range", "domain"]), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="layout.xaxis", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class CategoryorderValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="categoryorder", parent_name="layout.xaxis", **kwargs ): super(CategoryorderValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "trace", "category ascending", "category descending", "array", "total ascending", "total descending", "min ascending", "min descending", "max ascending", "max descending", "sum ascending", "sum descending", "mean ascending", "mean descending", "median ascending", "median descending", ], ), **kwargs ) import _plotly_utils.basevalidators class CategoryarraysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="categoryarraysrc", parent_name="layout.xaxis", **kwargs ): super(CategoryarraysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CategoryarrayValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="categoryarray", parent_name="layout.xaxis", **kwargs ): super(CategoryarrayValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class CalendarValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="calendar", parent_name="layout.xaxis", **kwargs): super(CalendarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "gregorian", "chinese", "coptic", "discworld", "ethiopian", "hebrew", "islamic", "julian", "mayan", "nanakshahi", "nepali", "persian", "jalali", "taiwan", "thai", "ummalqura", ], ), **kwargs ) import _plotly_utils.basevalidators class AutorangeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="autorange", parent_name="layout.xaxis", **kwargs): super(AutorangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "axrange"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "reversed"]), **kwargs ) import _plotly_utils.basevalidators class AutomarginValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="automargin", parent_name="layout.xaxis", **kwargs): super(AutomarginValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AnchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="anchor", parent_name="layout.xaxis", **kwargs): super(AnchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", ["free", "/^x([2-9]|[1-9][0-9]+)?$/", "/^y([2-9]|[1-9][0-9]+)?$/"], ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/xaxis/tickfont/0000755000175000017500000000000013573746614024256 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/xaxis/tickfont/__init__.py0000644000175000017500000000277613573721541026373 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="layout.xaxis.tickfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="layout.xaxis.tickfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="layout.xaxis.tickfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "ticks"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/updatemenu/0000755000175000017500000000000013573746614023450 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/updatemenu/pad/0000755000175000017500000000000013573746614024214 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/updatemenu/pad/__init__.py0000644000175000017500000000336213573721541026321 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="t", parent_name="layout.updatemenu.pad", **kwargs): super(TValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class RValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="r", parent_name="layout.updatemenu.pad", **kwargs): super(RValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="l", parent_name="layout.updatemenu.pad", **kwargs): super(LValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="b", parent_name="layout.updatemenu.pad", **kwargs): super(BValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/updatemenu/button/0000755000175000017500000000000013573746614024763 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/updatemenu/button/__init__.py0000644000175000017500000001114013573721541027061 0ustar noahfxnoahfximport _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="visible", parent_name="layout.updatemenu.button", **kwargs ): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="layout.updatemenu.button", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="layout.updatemenu.button", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class MethodValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="method", parent_name="layout.updatemenu.button", **kwargs ): super(MethodValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", ["restyle", "relayout", "animate", "update", "skip"] ), **kwargs ) import _plotly_utils.basevalidators class LabelValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="label", parent_name="layout.updatemenu.button", **kwargs ): super(LabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ExecuteValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="execute", parent_name="layout.updatemenu.button", **kwargs ): super(ExecuteValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class Args2Validator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="args2", parent_name="layout.updatemenu.button", **kwargs ): super(Args2Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), free_length=kwargs.pop("free_length", True), items=kwargs.pop( "items", [ {"valType": "any", "editType": "arraydraw"}, {"valType": "any", "editType": "arraydraw"}, {"valType": "any", "editType": "arraydraw"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ArgsValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="args", parent_name="layout.updatemenu.button", **kwargs ): super(ArgsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), free_length=kwargs.pop("free_length", True), items=kwargs.pop( "items", [ {"valType": "any", "editType": "arraydraw"}, {"valType": "any", "editType": "arraydraw"}, {"valType": "any", "editType": "arraydraw"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/updatemenu/__init__.py0000644000175000017500000003210613573721541025553 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="yanchor", parent_name="layout.updatemenu", **kwargs ): super(YanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "top", "middle", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="y", parent_name="layout.updatemenu", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="xanchor", parent_name="layout.updatemenu", **kwargs ): super(XanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "left", "center", "right"]), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="x", parent_name="layout.updatemenu", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="visible", parent_name="layout.updatemenu", **kwargs ): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TypeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="type", parent_name="layout.updatemenu", **kwargs): super(TypeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["dropdown", "buttons"]), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="layout.updatemenu", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ShowactiveValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showactive", parent_name="layout.updatemenu", **kwargs ): super(ShowactiveValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class PadValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="pad", parent_name="layout.updatemenu", **kwargs): super(PadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Pad"), data_docs=kwargs.pop( "data_docs", """ b The amount of padding (in px) along the bottom of the component. l The amount of padding (in px) on the left side of the component. r The amount of padding (in px) on the right side of the component. t The amount of padding (in px) along the top of the component. """, ), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="layout.updatemenu", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="font", parent_name="layout.updatemenu", **kwargs): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class DirectionValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="direction", parent_name="layout.updatemenu", **kwargs ): super(DirectionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["left", "right", "up", "down"]), **kwargs ) import _plotly_utils.basevalidators class ButtonValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="buttondefaults", parent_name="layout.updatemenu", **kwargs ): super(ButtonValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Button"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class ButtonsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="buttons", parent_name="layout.updatemenu", **kwargs ): super(ButtonsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Button"), data_docs=kwargs.pop( "data_docs", """ args Sets the arguments values to be passed to the Plotly method set in `method` on click. args2 Sets a 2nd set of `args`, these arguments values are passed to the Plotly method set in `method` when clicking this button while in the active state. Use this to create toggle buttons. execute When true, the API method is executed. When false, all other behaviors are the same and command execution is skipped. This may be useful when hooking into, for example, the `plotly_buttonclicked` method and executing the API command manually without losing the benefit of the updatemenu automatically binding to the state of the plot through the specification of `method` and `args`. label Sets the text label to appear on the button. method Sets the Plotly method to be called on click. If the `skip` method is used, the API updatemenu will function as normal but will perform no API calls and will not bind automatically to state updates. This may be used to create a component interface and attach to updatemenu events manually via JavaScript. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. visible Determines whether or not this button is visible. """, ), **kwargs ) import _plotly_utils.basevalidators class BorderwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="borderwidth", parent_name="layout.updatemenu", **kwargs ): super(BorderwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="layout.updatemenu", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="layout.updatemenu", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ActiveValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="active", parent_name="layout.updatemenu", **kwargs): super(ActiveValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), min=kwargs.pop("min", -1), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/updatemenu/font/0000755000175000017500000000000013573746614024416 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/updatemenu/font/__init__.py0000644000175000017500000000301513573721541026516 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="layout.updatemenu.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="layout.updatemenu.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="layout.updatemenu.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/slider/0000755000175000017500000000000013573746614022563 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/slider/transition/0000755000175000017500000000000013573746614024755 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/slider/transition/__init__.py0000644000175000017500000000434113573721540027057 0ustar noahfxnoahfximport _plotly_utils.basevalidators class EasingValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="easing", parent_name="layout.slider.transition", **kwargs ): super(EasingValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "linear", "quad", "cubic", "sin", "exp", "circle", "elastic", "back", "bounce", "linear-in", "quad-in", "cubic-in", "sin-in", "exp-in", "circle-in", "elastic-in", "back-in", "bounce-in", "linear-out", "quad-out", "cubic-out", "sin-out", "exp-out", "circle-out", "elastic-out", "back-out", "bounce-out", "linear-in-out", "quad-in-out", "cubic-in-out", "sin-in-out", "exp-in-out", "circle-in-out", "elastic-in-out", "back-in-out", "bounce-in-out", ], ), **kwargs ) import _plotly_utils.basevalidators class DurationValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="duration", parent_name="layout.slider.transition", **kwargs ): super(DurationValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/slider/pad/0000755000175000017500000000000013573746614023327 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/slider/pad/__init__.py0000644000175000017500000000334213573721540025431 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="t", parent_name="layout.slider.pad", **kwargs): super(TValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class RValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="r", parent_name="layout.slider.pad", **kwargs): super(RValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="l", parent_name="layout.slider.pad", **kwargs): super(LValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="b", parent_name="layout.slider.pad", **kwargs): super(BValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/slider/__init__.py0000644000175000017500000004120113573721541024662 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="yanchor", parent_name="layout.slider", **kwargs): super(YanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "top", "middle", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="y", parent_name="layout.slider", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="xanchor", parent_name="layout.slider", **kwargs): super(XanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "left", "center", "right"]), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="x", parent_name="layout.slider", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="visible", parent_name="layout.slider", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TransitionValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="transition", parent_name="layout.slider", **kwargs): super(TransitionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Transition"), data_docs=kwargs.pop( "data_docs", """ duration Sets the duration of the slider transition easing Sets the easing function of the slider transition """, ), **kwargs ) import _plotly_utils.basevalidators class TickwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="tickwidth", parent_name="layout.slider", **kwargs): super(TickwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TicklenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="ticklen", parent_name="layout.slider", **kwargs): super(TicklenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="tickcolor", parent_name="layout.slider", **kwargs): super(TickcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="layout.slider", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class StepValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="stepdefaults", parent_name="layout.slider", **kwargs ): super(StepValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Step"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class StepsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__(self, plotly_name="steps", parent_name="layout.slider", **kwargs): super(StepsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Step"), data_docs=kwargs.pop( "data_docs", """ args Sets the arguments values to be passed to the Plotly method set in `method` on slide. execute When true, the API method is executed. When false, all other behaviors are the same and command execution is skipped. This may be useful when hooking into, for example, the `plotly_sliderchange` method and executing the API command manually without losing the benefit of the slider automatically binding to the state of the plot through the specification of `method` and `args`. label Sets the text label to appear on the slider method Sets the Plotly method to be called when the slider value is changed. If the `skip` method is used, the API slider will function as normal but will perform no API calls and will not bind automatically to state updates. This may be used to create a component interface and attach to slider events manually via JavaScript. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value Sets the value of the slider step, used to refer to the step programatically. Defaults to the slider label if not provided. visible Determines whether or not this step is included in the slider. """, ), **kwargs ) import _plotly_utils.basevalidators class PadValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="pad", parent_name="layout.slider", **kwargs): super(PadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Pad"), data_docs=kwargs.pop( "data_docs", """ b The amount of padding (in px) along the bottom of the component. l The amount of padding (in px) on the left side of the component. r The amount of padding (in px) on the right side of the component. t The amount of padding (in px) along the top of the component. """, ), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="layout.slider", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class MinorticklenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="minorticklen", parent_name="layout.slider", **kwargs ): super(MinorticklenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LenmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="lenmode", parent_name="layout.slider", **kwargs): super(LenmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class LenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="len", parent_name="layout.slider", **kwargs): super(LenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="font", parent_name="layout.slider", **kwargs): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class CurrentvalueValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="currentvalue", parent_name="layout.slider", **kwargs ): super(CurrentvalueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Currentvalue"), data_docs=kwargs.pop( "data_docs", """ font Sets the font of the current value label text. offset The amount of space, in pixels, between the current value label and the slider. prefix When currentvalue.visible is true, this sets the prefix of the label. suffix When currentvalue.visible is true, this sets the suffix of the label. visible Shows the currently-selected value above the slider. xanchor The alignment of the value readout relative to the length of the slider. """, ), **kwargs ) import _plotly_utils.basevalidators class BorderwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="borderwidth", parent_name="layout.slider", **kwargs ): super(BorderwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="layout.slider", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="bgcolor", parent_name="layout.slider", **kwargs): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ActivebgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="activebgcolor", parent_name="layout.slider", **kwargs ): super(ActivebgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ActiveValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="active", parent_name="layout.slider", **kwargs): super(ActiveValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/slider/currentvalue/0000755000175000017500000000000013573746614025302 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/slider/currentvalue/__init__.py0000644000175000017500000000760613573721540027413 0ustar noahfxnoahfximport _plotly_utils.basevalidators class XanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="xanchor", parent_name="layout.slider.currentvalue", **kwargs ): super(XanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["left", "center", "right"]), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="visible", parent_name="layout.slider.currentvalue", **kwargs ): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="suffix", parent_name="layout.slider.currentvalue", **kwargs ): super(SuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class PrefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="prefix", parent_name="layout.slider.currentvalue", **kwargs ): super(PrefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class OffsetValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="offset", parent_name="layout.slider.currentvalue", **kwargs ): super(OffsetValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="layout.slider.currentvalue", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/slider/currentvalue/font/0000755000175000017500000000000013573746614026250 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/slider/currentvalue/font/__init__.py0000644000175000017500000000316013573721540030350 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="layout.slider.currentvalue.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="layout.slider.currentvalue.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="layout.slider.currentvalue.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/slider/font/0000755000175000017500000000000013573746614023531 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/slider/font/__init__.py0000644000175000017500000000274513573721540025641 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="size", parent_name="layout.slider.font", **kwargs): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="layout.slider.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="layout.slider.font", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/slider/step/0000755000175000017500000000000013573746614023536 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/slider/step/__init__.py0000644000175000017500000001016613573721540025642 0ustar noahfxnoahfximport _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="visible", parent_name="layout.slider.step", **kwargs ): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="value", parent_name="layout.slider.step", **kwargs): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="layout.slider.step", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="layout.slider.step", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class MethodValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="method", parent_name="layout.slider.step", **kwargs ): super(MethodValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", ["restyle", "relayout", "animate", "update", "skip"] ), **kwargs ) import _plotly_utils.basevalidators class LabelValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="label", parent_name="layout.slider.step", **kwargs): super(LabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ExecuteValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="execute", parent_name="layout.slider.step", **kwargs ): super(ExecuteValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ArgsValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="args", parent_name="layout.slider.step", **kwargs): super(ArgsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), free_length=kwargs.pop("free_length", True), items=kwargs.pop( "items", [ {"valType": "any", "editType": "arraydraw"}, {"valType": "any", "editType": "arraydraw"}, {"valType": "any", "editType": "arraydraw"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/legend/0000755000175000017500000000000013573746614022537 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/legend/__init__.py0000644000175000017500000002205113573721540024637 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="yanchor", parent_name="layout.legend", **kwargs): super(YanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "legend"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "top", "middle", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="y", parent_name="layout.legend", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "legend"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="xanchor", parent_name="layout.legend", **kwargs): super(XanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "legend"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "left", "center", "right"]), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="x", parent_name="layout.legend", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "legend"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ValignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="valign", parent_name="layout.legend", **kwargs): super(ValignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "legend"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["top", "middle", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="layout.legend", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TraceorderValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="traceorder", parent_name="layout.legend", **kwargs): super(TraceorderValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "legend"), extras=kwargs.pop("extras", ["normal"]), flags=kwargs.pop("flags", ["reversed", "grouped"]), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TracegroupgapValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="tracegroupgap", parent_name="layout.legend", **kwargs ): super(TracegroupgapValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "legend"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OrientationValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="orientation", parent_name="layout.legend", **kwargs ): super(OrientationValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "legend"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["v", "h"]), **kwargs ) import _plotly_utils.basevalidators class ItemsizingValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="itemsizing", parent_name="layout.legend", **kwargs): super(ItemsizingValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "legend"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["trace", "constant"]), **kwargs ) import _plotly_utils.basevalidators class ItemdoubleclickValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="itemdoubleclick", parent_name="layout.legend", **kwargs ): super(ItemdoubleclickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "legend"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["toggle", "toggleothers", False]), **kwargs ) import _plotly_utils.basevalidators class ItemclickValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="itemclick", parent_name="layout.legend", **kwargs): super(ItemclickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "legend"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["toggle", "toggleothers", False]), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="font", parent_name="layout.legend", **kwargs): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class BorderwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="borderwidth", parent_name="layout.legend", **kwargs ): super(BorderwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "legend"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="layout.legend", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "legend"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="bgcolor", parent_name="layout.legend", **kwargs): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "legend"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/legend/font/0000755000175000017500000000000013573746614023505 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/legend/font/__init__.py0000644000175000017500000000273413573721540025613 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="size", parent_name="layout.legend.font", **kwargs): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "legend"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="layout.legend.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "legend"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="layout.legend.font", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "legend"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/font/0000755000175000017500000000000013573746614022247 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/font/__init__.py0000644000175000017500000000266313573721540024356 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="size", parent_name="layout.font", **kwargs): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="family", parent_name="layout.font", **kwargs): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="layout.font", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/image/0000755000175000017500000000000013573746614022363 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/image/__init__.py0000644000175000017500000001614713573721540024474 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YrefValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="yref", parent_name="layout.image", **kwargs): super(YrefValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["paper", "/^y([2-9]|[1-9][0-9]+)?$/"]), **kwargs ) import _plotly_utils.basevalidators class YanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="yanchor", parent_name="layout.image", **kwargs): super(YanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["top", "middle", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="y", parent_name="layout.image", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XrefValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="xref", parent_name="layout.image", **kwargs): super(XrefValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["paper", "/^x([2-9]|[1-9][0-9]+)?$/"]), **kwargs ) import _plotly_utils.basevalidators class XanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="xanchor", parent_name="layout.image", **kwargs): super(XanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["left", "center", "right"]), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="x", parent_name="layout.image", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="visible", parent_name="layout.image", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="layout.image", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SourceValidator(_plotly_utils.basevalidators.ImageUriValidator): def __init__(self, plotly_name="source", parent_name="layout.image", **kwargs): super(SourceValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizingValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="sizing", parent_name="layout.image", **kwargs): super(SizingValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["fill", "contain", "stretch"]), **kwargs ) import _plotly_utils.basevalidators class SizeyValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="sizey", parent_name="layout.image", **kwargs): super(SizeyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizexValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="sizex", parent_name="layout.image", **kwargs): super(SizexValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="layout.image", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="layout.image", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LayerValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="layer", parent_name="layout.image", **kwargs): super(LayerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["below", "above"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/shape/0000755000175000017500000000000013573746614022401 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/shape/__init__.py0000644000175000017500000002246513573721541024513 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YsizemodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="ysizemode", parent_name="layout.shape", **kwargs): super(YsizemodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+arraydraw"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["scaled", "pixel"]), **kwargs ) import _plotly_utils.basevalidators class YrefValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="yref", parent_name="layout.shape", **kwargs): super(YrefValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["paper", "/^y([2-9]|[1-9][0-9]+)?$/"]), **kwargs ) import _plotly_utils.basevalidators class YanchorValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="yanchor", parent_name="layout.shape", **kwargs): super(YanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+arraydraw"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class Y1Validator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="y1", parent_name="layout.shape", **kwargs): super(Y1Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+arraydraw"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class Y0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="y0", parent_name="layout.shape", **kwargs): super(Y0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+arraydraw"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XsizemodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="xsizemode", parent_name="layout.shape", **kwargs): super(XsizemodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+arraydraw"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["scaled", "pixel"]), **kwargs ) import _plotly_utils.basevalidators class XrefValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="xref", parent_name="layout.shape", **kwargs): super(XrefValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["paper", "/^x([2-9]|[1-9][0-9]+)?$/"]), **kwargs ) import _plotly_utils.basevalidators class XanchorValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="xanchor", parent_name="layout.shape", **kwargs): super(XanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+arraydraw"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class X1Validator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="x1", parent_name="layout.shape", **kwargs): super(X1Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+arraydraw"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class X0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="x0", parent_name="layout.shape", **kwargs): super(X0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+arraydraw"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="visible", parent_name="layout.shape", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+arraydraw"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TypeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="type", parent_name="layout.shape", **kwargs): super(TypeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+arraydraw"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["circle", "rect", "path", "line"]), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="layout.shape", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class PathValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="path", parent_name="layout.shape", **kwargs): super(PathValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+arraydraw"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="layout.shape", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="layout.shape", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="line", parent_name="layout.shape", **kwargs): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ color Sets the line color. dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). width Sets the line width (in px). """, ), **kwargs ) import _plotly_utils.basevalidators class LayerValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="layer", parent_name="layout.shape", **kwargs): super(LayerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["below", "above"]), **kwargs ) import _plotly_utils.basevalidators class FillcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="fillcolor", parent_name="layout.shape", **kwargs): super(FillcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/layout/shape/line/0000755000175000017500000000000013573746614023330 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/layout/shape/line/__init__.py0000644000175000017500000000312113573721540025425 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="layout.shape.line", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, anim=kwargs.pop("anim", True), edit_type=kwargs.pop("edit_type", "calc+arraydraw"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class DashValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="dash", parent_name="layout.shape.line", **kwargs): super(DashValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", ["solid", "dot", "dash", "longdash", "dashdot", "longdashdot"] ), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="layout.shape.line", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, anim=kwargs.pop("anim", True), edit_type=kwargs.pop("edit_type", "arraydraw"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/bar/0000755000175000017500000000000013573746614020530 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/bar/unselected/0000755000175000017500000000000013573746614022663 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/bar/unselected/textfont/0000755000175000017500000000000013573746614024536 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/bar/unselected/textfont/__init__.py0000644000175000017500000000072213573721536026644 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="bar.unselected.textfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/bar/unselected/marker/0000755000175000017500000000000013573746614024144 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/bar/unselected/marker/__init__.py0000644000175000017500000000176513573721536026262 0ustar noahfxnoahfximport _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="opacity", parent_name="bar.unselected.marker", **kwargs ): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="bar.unselected.marker", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/bar/unselected/__init__.py0000644000175000017500000000264713573721536025001 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="textfont", parent_name="bar.unselected", **kwargs): super(TextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Textfont"), data_docs=kwargs.pop( "data_docs", """ color Sets the text font color of unselected points, applied only when a selection exists. """, ), **kwargs ) import _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="marker", parent_name="bar.unselected", **kwargs): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/bar/textfont/0000755000175000017500000000000013573746614022403 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/bar/textfont/__init__.py0000644000175000017500000000562013573721536024513 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="sizesrc", parent_name="bar.textfont", **kwargs): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="size", parent_name="bar.textfont", **kwargs): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="familysrc", parent_name="bar.textfont", **kwargs): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="family", parent_name="bar.textfont", **kwargs): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="colorsrc", parent_name="bar.textfont", **kwargs): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="bar.textfont", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/bar/error_x/0000755000175000017500000000000013573746614022210 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/bar/error_x/__init__.py0000644000175000017500000001570213573721536024322 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="bar.error_x", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="visible", parent_name="bar.error_x", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ValueminusValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="valueminus", parent_name="bar.error_x", **kwargs): super(ValueminusValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="value", parent_name="bar.error_x", **kwargs): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TypeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="type", parent_name="bar.error_x", **kwargs): super(TypeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["percent", "constant", "sqrt", "data"]), **kwargs ) import _plotly_utils.basevalidators class TracerefminusValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="tracerefminus", parent_name="bar.error_x", **kwargs ): super(TracerefminusValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TracerefValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="traceref", parent_name="bar.error_x", **kwargs): super(TracerefValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="thickness", parent_name="bar.error_x", **kwargs): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SymmetricValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="symmetric", parent_name="bar.error_x", **kwargs): super(SymmetricValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CopyYstyleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="copy_ystyle", parent_name="bar.error_x", **kwargs): super(CopyYstyleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="bar.error_x", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ArraysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="arraysrc", parent_name="bar.error_x", **kwargs): super(ArraysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ArrayminussrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="arrayminussrc", parent_name="bar.error_x", **kwargs ): super(ArrayminussrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ArrayminusValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="arrayminus", parent_name="bar.error_x", **kwargs): super(ArrayminusValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class ArrayValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="array", parent_name="bar.error_x", **kwargs): super(ArrayValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/bar/hoverlabel/0000755000175000017500000000000013573746614022653 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/bar/hoverlabel/__init__.py0000644000175000017500000001330313573721536024760 0ustar noahfxnoahfximport _plotly_utils.basevalidators class NamelengthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="namelengthsrc", parent_name="bar.hoverlabel", **kwargs ): super(NamelengthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NamelengthValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="namelength", parent_name="bar.hoverlabel", **kwargs ): super(NamelengthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", -1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="font", parent_name="bar.hoverlabel", **kwargs): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class BordercolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bordercolorsrc", parent_name="bar.hoverlabel", **kwargs ): super(BordercolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="bar.hoverlabel", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bgcolorsrc", parent_name="bar.hoverlabel", **kwargs ): super(BgcolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="bgcolor", parent_name="bar.hoverlabel", **kwargs): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AlignsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="alignsrc", parent_name="bar.hoverlabel", **kwargs): super(AlignsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="align", parent_name="bar.hoverlabel", **kwargs): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "right", "auto"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/bar/hoverlabel/font/0000755000175000017500000000000013573746614023621 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/bar/hoverlabel/font/__init__.py0000644000175000017500000000577713573721536025746 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="bar.hoverlabel.font", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="size", parent_name="bar.hoverlabel.font", **kwargs): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="bar.hoverlabel.font", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="bar.hoverlabel.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="bar.hoverlabel.font", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="bar.hoverlabel.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/bar/outsidetextfont/0000755000175000017500000000000013573746614024000 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/bar/outsidetextfont/__init__.py0000644000175000017500000000600013573721536026101 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="bar.outsidetextfont", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="size", parent_name="bar.outsidetextfont", **kwargs): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="bar.outsidetextfont", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="bar.outsidetextfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="bar.outsidetextfont", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="bar.outsidetextfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/bar/error_y/0000755000175000017500000000000013573746614022211 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/bar/error_y/__init__.py0000644000175000017500000001476713573721536024335 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="bar.error_y", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="visible", parent_name="bar.error_y", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ValueminusValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="valueminus", parent_name="bar.error_y", **kwargs): super(ValueminusValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="value", parent_name="bar.error_y", **kwargs): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TypeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="type", parent_name="bar.error_y", **kwargs): super(TypeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["percent", "constant", "sqrt", "data"]), **kwargs ) import _plotly_utils.basevalidators class TracerefminusValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="tracerefminus", parent_name="bar.error_y", **kwargs ): super(TracerefminusValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TracerefValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="traceref", parent_name="bar.error_y", **kwargs): super(TracerefValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="thickness", parent_name="bar.error_y", **kwargs): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SymmetricValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="symmetric", parent_name="bar.error_y", **kwargs): super(SymmetricValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="bar.error_y", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ArraysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="arraysrc", parent_name="bar.error_y", **kwargs): super(ArraysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ArrayminussrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="arrayminussrc", parent_name="bar.error_y", **kwargs ): super(ArrayminussrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ArrayminusValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="arrayminus", parent_name="bar.error_y", **kwargs): super(ArrayminusValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class ArrayValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="array", parent_name="bar.error_y", **kwargs): super(ArrayValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/bar/marker/0000755000175000017500000000000013573746614022011 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/bar/marker/colorbar/0000755000175000017500000000000013573746614023614 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/bar/marker/colorbar/tickformatstop/0000755000175000017500000000000013573746614026665 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/bar/marker/colorbar/tickformatstop/__init__.py0000644000175000017500000000541313573721536030775 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="value", parent_name="bar.marker.colorbar.tickformatstop", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="bar.marker.colorbar.tickformatstop", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="bar.marker.colorbar.tickformatstop", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EnabledValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="enabled", parent_name="bar.marker.colorbar.tickformatstop", **kwargs ): super(EnabledValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DtickrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="dtickrange", parent_name="bar.marker.colorbar.tickformatstop", **kwargs ): super(DtickrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "colorbars"}, {"valType": "any", "editType": "colorbars"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/bar/marker/colorbar/title/0000755000175000017500000000000013573746614024735 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/bar/marker/colorbar/title/__init__.py0000644000175000017500000000472613573721536027053 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="text", parent_name="bar.marker.colorbar.title", **kwargs ): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SideValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="side", parent_name="bar.marker.colorbar.title", **kwargs ): super(SideValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["right", "top", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="bar.marker.colorbar.title", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/bar/marker/colorbar/title/font/0000755000175000017500000000000013573746614025703 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/bar/marker/colorbar/title/font/__init__.py0000644000175000017500000000312513573721536030011 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="bar.marker.colorbar.title.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="bar.marker.colorbar.title.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="bar.marker.colorbar.title.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/bar/marker/colorbar/__init__.py0000644000175000017500000006037613573721536025735 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="ypad", parent_name="bar.marker.colorbar", **kwargs): super(YpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class YanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="yanchor", parent_name="bar.marker.colorbar", **kwargs ): super(YanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["top", "middle", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="y", parent_name="bar.marker.colorbar", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="xpad", parent_name="bar.marker.colorbar", **kwargs): super(XpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="xanchor", parent_name="bar.marker.colorbar", **kwargs ): super(XanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "center", "right"]), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="x", parent_name="bar.marker.colorbar", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TitleValidator(_plotly_utils.basevalidators.TitleValidator): def __init__( self, plotly_name="title", parent_name="bar.marker.colorbar", **kwargs ): super(TitleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Title"), data_docs=kwargs.pop( "data_docs", """ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """, ), **kwargs ) import _plotly_utils.basevalidators class TickwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="tickwidth", parent_name="bar.marker.colorbar", **kwargs ): super(TickwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickvalssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="tickvalssrc", parent_name="bar.marker.colorbar", **kwargs ): super(TickvalssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickvalsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="tickvals", parent_name="bar.marker.colorbar", **kwargs ): super(TickvalsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="ticktextsrc", parent_name="bar.marker.colorbar", **kwargs ): super(TicktextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicktextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="ticktext", parent_name="bar.marker.colorbar", **kwargs ): super(TicktextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="ticksuffix", parent_name="bar.marker.colorbar", **kwargs ): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TicksValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="ticks", parent_name="bar.marker.colorbar", **kwargs ): super(TicksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["outside", "inside", ""]), **kwargs ) import _plotly_utils.basevalidators class TickprefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickprefix", parent_name="bar.marker.colorbar", **kwargs ): super(TickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="tickmode", parent_name="bar.marker.colorbar", **kwargs ): super(TickmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "linear", "array"]), **kwargs ) import _plotly_utils.basevalidators class TicklenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ticklen", parent_name="bar.marker.colorbar", **kwargs ): super(TicklenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickformatstopValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickformatstopdefaults", parent_name="bar.marker.colorbar", **kwargs ): super(TickformatstopValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatstopsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="tickformatstops", parent_name="bar.marker.colorbar", **kwargs ): super(TickformatstopsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickformat", parent_name="bar.marker.colorbar", **kwargs ): super(TickformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickfont", parent_name="bar.marker.colorbar", **kwargs ): super(TickfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class TickcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="tickcolor", parent_name="bar.marker.colorbar", **kwargs ): super(TickcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__( self, plotly_name="tickangle", parent_name="bar.marker.colorbar", **kwargs ): super(TickangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="tick0", parent_name="bar.marker.colorbar", **kwargs ): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ThicknessmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="thicknessmode", parent_name="bar.marker.colorbar", **kwargs ): super(ThicknessmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="thickness", parent_name="bar.marker.colorbar", **kwargs ): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowticksuffixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showticksuffix", parent_name="bar.marker.colorbar", **kwargs ): super(ShowticksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowtickprefixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showtickprefix", parent_name="bar.marker.colorbar", **kwargs ): super(ShowtickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowticklabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showticklabels", parent_name="bar.marker.colorbar", **kwargs ): super(ShowticklabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowexponentValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showexponent", parent_name="bar.marker.colorbar", **kwargs ): super(ShowexponentValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class SeparatethousandsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="separatethousands", parent_name="bar.marker.colorbar", **kwargs ): super(SeparatethousandsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="outlinewidth", parent_name="bar.marker.colorbar", **kwargs ): super(OutlinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="outlinecolor", parent_name="bar.marker.colorbar", **kwargs ): super(OutlinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NticksValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="nticks", parent_name="bar.marker.colorbar", **kwargs ): super(NticksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LenmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="lenmode", parent_name="bar.marker.colorbar", **kwargs ): super(LenmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class LenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="len", parent_name="bar.marker.colorbar", **kwargs): super(LenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ExponentformatValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="exponentformat", parent_name="bar.marker.colorbar", **kwargs ): super(ExponentformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "e", "E", "power", "SI", "B"]), **kwargs ) import _plotly_utils.basevalidators class DtickValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="dtick", parent_name="bar.marker.colorbar", **kwargs ): super(DtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BorderwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="borderwidth", parent_name="bar.marker.colorbar", **kwargs ): super(BorderwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="bar.marker.colorbar", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="bar.marker.colorbar", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/bar/marker/colorbar/tickfont/0000755000175000017500000000000013573746614025435 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/bar/marker/colorbar/tickfont/__init__.py0000644000175000017500000000303713573721536027545 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="bar.marker.colorbar.tickfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="bar.marker.colorbar.tickfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="bar.marker.colorbar.tickfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/bar/marker/__init__.py0000644000175000017500000005370713573721536024132 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ShowscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showscale", parent_name="bar.marker", **kwargs): super(ShowscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ReversescaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="reversescale", parent_name="bar.marker", **kwargs): super(ReversescaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacitysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="opacitysrc", parent_name="bar.marker", **kwargs): super(OpacitysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="bar.marker", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="line", parent_name="bar.marker", **kwargs): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,R eds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Black body,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . """, ), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="colorsrc", parent_name="bar.marker", **kwargs): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__(self, plotly_name="colorscale", parent_name="bar.marker", **kwargs): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"autocolorscale": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorBarValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="colorbar", parent_name="bar.marker", **kwargs): super(ColorBarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "ColorBar"), data_docs=kwargs.pop( "data_docs", """ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.bar.marker.colo rbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.bar.marker.colorbar.tickformatstopdefaults), sets the default property values to use for elements of bar.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.bar.marker.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use bar.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use bar.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """, ), **kwargs ) import _plotly_utils.basevalidators class ColoraxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="coloraxis", parent_name="bar.marker", **kwargs): super(ColoraxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", None), edit_type=kwargs.pop("edit_type", "calc"), regex=kwargs.pop("regex", "/^coloraxis([2-9]|[1-9][0-9]+)?$/"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="bar.marker", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), colorscale_path=kwargs.pop("colorscale_path", "bar.marker.colorscale"), **kwargs ) import _plotly_utils.basevalidators class CminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmin", parent_name="bar.marker", **kwargs): super(CminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmidValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmid", parent_name="bar.marker", **kwargs): super(CmidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmax", parent_name="bar.marker", **kwargs): super(CmaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CautoValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="cauto", parent_name="bar.marker", **kwargs): super(CautoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AutocolorscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="autocolorscale", parent_name="bar.marker", **kwargs ): super(AutocolorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/bar/marker/line/0000755000175000017500000000000013573746614022740 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/bar/marker/line/__init__.py0000644000175000017500000001421413573721536025047 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="widthsrc", parent_name="bar.marker.line", **kwargs): super(WidthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="bar.marker.line", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, anim=kwargs.pop("anim", True), array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ReversescaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="reversescale", parent_name="bar.marker.line", **kwargs ): super(ReversescaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="colorsrc", parent_name="bar.marker.line", **kwargs): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__( self, plotly_name="colorscale", parent_name="bar.marker.line", **kwargs ): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"autocolorscale": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColoraxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__( self, plotly_name="coloraxis", parent_name="bar.marker.line", **kwargs ): super(ColoraxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", None), edit_type=kwargs.pop("edit_type", "calc"), regex=kwargs.pop("regex", "/^coloraxis([2-9]|[1-9][0-9]+)?$/"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="bar.marker.line", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), colorscale_path=kwargs.pop("colorscale_path", "bar.marker.line.colorscale"), **kwargs ) import _plotly_utils.basevalidators class CminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmin", parent_name="bar.marker.line", **kwargs): super(CminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmidValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmid", parent_name="bar.marker.line", **kwargs): super(CmidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmax", parent_name="bar.marker.line", **kwargs): super(CmaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CautoValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="cauto", parent_name="bar.marker.line", **kwargs): super(CautoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AutocolorscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="autocolorscale", parent_name="bar.marker.line", **kwargs ): super(AutocolorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/bar/stream/0000755000175000017500000000000013573746614022023 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/bar/stream/__init__.py0000644000175000017500000000205413573721536024131 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TokenValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="token", parent_name="bar.stream", **kwargs): super(TokenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "info"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class MaxpointsValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="maxpoints", parent_name="bar.stream", **kwargs): super(MaxpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 10000), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/bar/__init__.py0000644000175000017500000013633713573721537022653 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="ysrc", parent_name="bar", **kwargs): super(YsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YcalendarValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="ycalendar", parent_name="bar", **kwargs): super(YcalendarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "gregorian", "chinese", "coptic", "discworld", "ethiopian", "hebrew", "islamic", "julian", "mayan", "nanakshahi", "nepali", "persian", "jalali", "taiwan", "thai", "ummalqura", ], ), **kwargs ) import _plotly_utils.basevalidators class YAxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="yaxis", parent_name="bar", **kwargs): super(YAxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "y"), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class Y0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="y0", parent_name="bar", **kwargs): super(Y0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, anim=kwargs.pop("anim", True), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="y", parent_name="bar", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, anim=kwargs.pop("anim", True), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class XsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="xsrc", parent_name="bar", **kwargs): super(XsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XcalendarValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="xcalendar", parent_name="bar", **kwargs): super(XcalendarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "gregorian", "chinese", "coptic", "discworld", "ethiopian", "hebrew", "islamic", "julian", "mayan", "nanakshahi", "nepali", "persian", "jalali", "taiwan", "thai", "ummalqura", ], ), **kwargs ) import _plotly_utils.basevalidators class XAxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="xaxis", parent_name="bar", **kwargs): super(XAxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "x"), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class X0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="x0", parent_name="bar", **kwargs): super(X0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, anim=kwargs.pop("anim", True), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="x", parent_name="bar", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, anim=kwargs.pop("anim", True), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class WidthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="widthsrc", parent_name="bar", **kwargs): super(WidthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="bar", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="visible", parent_name="bar", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "legendonly"]), **kwargs ) import _plotly_utils.basevalidators class UnselectedValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="unselected", parent_name="bar", **kwargs): super(UnselectedValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Unselected"), data_docs=kwargs.pop( "data_docs", """ marker plotly.graph_objects.bar.unselected.Marker instance or dict with compatible properties textfont plotly.graph_objects.bar.unselected.Textfont instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="bar", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UidValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="uid", parent_name="bar", **kwargs): super(UidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, anim=kwargs.pop("anim", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="tsrc", parent_name="bar", **kwargs): super(TsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TexttemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="texttemplatesrc", parent_name="bar", **kwargs): super(TexttemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TexttemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="texttemplate", parent_name="bar", **kwargs): super(TexttemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="textsrc", parent_name="bar", **kwargs): super(TextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextpositionsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="textpositionsrc", parent_name="bar", **kwargs): super(TextpositionsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextpositionValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="textposition", parent_name="bar", **kwargs): super(TextpositionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["inside", "outside", "auto", "none"]), **kwargs ) import _plotly_utils.basevalidators class TextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="textfont", parent_name="bar", **kwargs): super(TextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Textfont"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class TextangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__(self, plotly_name="textangle", parent_name="bar", **kwargs): super(TextangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="text", parent_name="bar", **kwargs): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="t", parent_name="bar", **kwargs): super(TValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class StreamValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="stream", parent_name="bar", **kwargs): super(StreamValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Stream"), data_docs=kwargs.pop( "data_docs", """ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """, ), **kwargs ) import _plotly_utils.basevalidators class ShowlegendValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showlegend", parent_name="bar", **kwargs): super(ShowlegendValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SelectedpointsValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="selectedpoints", parent_name="bar", **kwargs): super(SelectedpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SelectedValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="selected", parent_name="bar", **kwargs): super(SelectedValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Selected"), data_docs=kwargs.pop( "data_docs", """ marker plotly.graph_objects.bar.selected.Marker instance or dict with compatible properties textfont plotly.graph_objects.bar.selected.Textfont instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class RsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="rsrc", parent_name="bar", **kwargs): super(RsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class RValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="r", parent_name="bar", **kwargs): super(RValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class OutsidetextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="outsidetextfont", parent_name="bar", **kwargs): super(OutsidetextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Outsidetextfont"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class OrientationValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="orientation", parent_name="bar", **kwargs): super(OrientationValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["v", "h"]), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="bar", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OffsetsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="offsetsrc", parent_name="bar", **kwargs): super(OffsetsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class OffsetgroupValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="offsetgroup", parent_name="bar", **kwargs): super(OffsetgroupValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class OffsetValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="offset", parent_name="bar", **kwargs): super(OffsetValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="bar", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="metasrc", parent_name="bar", **kwargs): super(MetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetaValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="meta", parent_name="bar", **kwargs): super(MetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="marker", parent_name="bar", **kwargs): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.bar.marker.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . line plotly.graph_objects.bar.marker.Line instance or dict with compatible properties opacity Sets the opacity of the bars. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. """, ), **kwargs ) import _plotly_utils.basevalidators class LegendgroupValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="legendgroup", parent_name="bar", **kwargs): super(LegendgroupValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class InsidetextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="insidetextfont", parent_name="bar", **kwargs): super(InsidetextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Insidetextfont"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class InsidetextanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="insidetextanchor", parent_name="bar", **kwargs): super(InsidetextanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["end", "middle", "start"]), **kwargs ) import _plotly_utils.basevalidators class IdssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="idssrc", parent_name="bar", **kwargs): super(IdssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ids", parent_name="bar", **kwargs): super(IdsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, anim=kwargs.pop("anim", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class HovertextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hovertextsrc", parent_name="bar", **kwargs): super(HovertextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertext", parent_name="bar", **kwargs): super(HovertextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hovertemplatesrc", parent_name="bar", **kwargs): super(HovertemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertemplate", parent_name="bar", **kwargs): super(HovertemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverlabelValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="hoverlabel", parent_name="bar", **kwargs): super(HoverlabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Hoverlabel"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """, ), **kwargs ) import _plotly_utils.basevalidators class HoverinfosrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hoverinfosrc", parent_name="bar", **kwargs): super(HoverinfosrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverinfoValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="hoverinfo", parent_name="bar", **kwargs): super(HoverinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), extras=kwargs.pop("extras", ["all", "none", "skip"]), flags=kwargs.pop("flags", ["x", "y", "z", "text", "name"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ErrorYValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="error_y", parent_name="bar", **kwargs): super(ErrorYValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "ErrorY"), data_docs=kwargs.pop( "data_docs", """ array Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. arrayminus Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. arrayminussrc Sets the source reference on plot.ly for arrayminus . arraysrc Sets the source reference on plot.ly for array . color Sets the stoke color of the error bars. symmetric Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. thickness Sets the thickness (in px) of the error bars. traceref tracerefminus type Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. value Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. valueminus Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars visible Determines whether or not this set of error bars is visible. width Sets the width (in px) of the cross-bar at both ends of the error bars. """, ), **kwargs ) import _plotly_utils.basevalidators class ErrorXValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="error_x", parent_name="bar", **kwargs): super(ErrorXValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "ErrorX"), data_docs=kwargs.pop( "data_docs", """ array Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. arrayminus Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. arrayminussrc Sets the source reference on plot.ly for arrayminus . arraysrc Sets the source reference on plot.ly for array . color Sets the stoke color of the error bars. copy_ystyle symmetric Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. thickness Sets the thickness (in px) of the error bars. traceref tracerefminus type Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. value Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. valueminus Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars visible Determines whether or not this set of error bars is visible. width Sets the width (in px) of the cross-bar at both ends of the error bars. """, ), **kwargs ) import _plotly_utils.basevalidators class DyValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="dy", parent_name="bar", **kwargs): super(DyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, anim=kwargs.pop("anim", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="dx", parent_name="bar", **kwargs): super(DxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, anim=kwargs.pop("anim", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdatasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="customdatasrc", parent_name="bar", **kwargs): super(CustomdatasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdataValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="customdata", parent_name="bar", **kwargs): super(CustomdataValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class ConstraintextValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="constraintext", parent_name="bar", **kwargs): super(ConstraintextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["inside", "outside", "both", "none"]), **kwargs ) import _plotly_utils.basevalidators class CliponaxisValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="cliponaxis", parent_name="bar", **kwargs): super(CliponaxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BasesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="basesrc", parent_name="bar", **kwargs): super(BasesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BaseValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="base", parent_name="bar", **kwargs): super(BaseValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AlignmentgroupValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="alignmentgroup", parent_name="bar", **kwargs): super(AlignmentgroupValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/bar/insidetextfont/0000755000175000017500000000000013573746614023577 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/bar/insidetextfont/__init__.py0000644000175000017500000000575413573721536025717 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="bar.insidetextfont", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="size", parent_name="bar.insidetextfont", **kwargs): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="bar.insidetextfont", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="bar.insidetextfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="bar.insidetextfont", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="bar.insidetextfont", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/bar/selected/0000755000175000017500000000000013573746614022320 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/bar/selected/textfont/0000755000175000017500000000000013573746614024173 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/bar/selected/textfont/__init__.py0000644000175000017500000000072013573721536026277 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="bar.selected.textfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/bar/selected/marker/0000755000175000017500000000000013573746614023601 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/bar/selected/marker/__init__.py0000644000175000017500000000176113573721536025713 0ustar noahfxnoahfximport _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="opacity", parent_name="bar.selected.marker", **kwargs ): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="bar.selected.marker", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/bar/selected/__init__.py0000644000175000017500000000237313573721536024432 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="textfont", parent_name="bar.selected", **kwargs): super(TextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Textfont"), data_docs=kwargs.pop( "data_docs", """ color Sets the text font color of selected points. """, ), **kwargs ) import _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="marker", parent_name="bar.selected", **kwargs): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/heatmap/0000755000175000017500000000000013573746614021403 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/heatmap/hoverlabel/0000755000175000017500000000000013573746614023526 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/heatmap/hoverlabel/__init__.py0000644000175000017500000001340313573721537025635 0ustar noahfxnoahfximport _plotly_utils.basevalidators class NamelengthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="namelengthsrc", parent_name="heatmap.hoverlabel", **kwargs ): super(NamelengthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NamelengthValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="namelength", parent_name="heatmap.hoverlabel", **kwargs ): super(NamelengthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", -1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="font", parent_name="heatmap.hoverlabel", **kwargs): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class BordercolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bordercolorsrc", parent_name="heatmap.hoverlabel", **kwargs ): super(BordercolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="heatmap.hoverlabel", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bgcolorsrc", parent_name="heatmap.hoverlabel", **kwargs ): super(BgcolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="heatmap.hoverlabel", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AlignsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="alignsrc", parent_name="heatmap.hoverlabel", **kwargs ): super(AlignsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="align", parent_name="heatmap.hoverlabel", **kwargs): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "right", "auto"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/heatmap/hoverlabel/font/0000755000175000017500000000000013573746614024474 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/heatmap/hoverlabel/font/__init__.py0000644000175000017500000000604513573721537026607 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="heatmap.hoverlabel.font", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="heatmap.hoverlabel.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="heatmap.hoverlabel.font", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="heatmap.hoverlabel.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="heatmap.hoverlabel.font", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="heatmap.hoverlabel.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/heatmap/colorbar/0000755000175000017500000000000013573746614023206 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/heatmap/colorbar/tickformatstop/0000755000175000017500000000000013573746614026257 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/heatmap/colorbar/tickformatstop/__init__.py0000644000175000017500000000537413573721537030376 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="value", parent_name="heatmap.colorbar.tickformatstop", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="heatmap.colorbar.tickformatstop", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="heatmap.colorbar.tickformatstop", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EnabledValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="enabled", parent_name="heatmap.colorbar.tickformatstop", **kwargs ): super(EnabledValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DtickrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="dtickrange", parent_name="heatmap.colorbar.tickformatstop", **kwargs ): super(DtickrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "colorbars"}, {"valType": "any", "editType": "colorbars"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/heatmap/colorbar/title/0000755000175000017500000000000013573746614024327 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/heatmap/colorbar/title/__init__.py0000644000175000017500000000471513573721537026444 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="text", parent_name="heatmap.colorbar.title", **kwargs ): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SideValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="side", parent_name="heatmap.colorbar.title", **kwargs ): super(SideValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["right", "top", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="heatmap.colorbar.title", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/heatmap/colorbar/title/font/0000755000175000017500000000000013573746614025275 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/heatmap/colorbar/title/font/__init__.py0000644000175000017500000000303413573721537027403 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="heatmap.colorbar.title.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="heatmap.colorbar.title.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="heatmap.colorbar.title.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/heatmap/colorbar/__init__.py0000644000175000017500000005773713573721540025331 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="ypad", parent_name="heatmap.colorbar", **kwargs): super(YpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class YanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="yanchor", parent_name="heatmap.colorbar", **kwargs): super(YanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["top", "middle", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="y", parent_name="heatmap.colorbar", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="xpad", parent_name="heatmap.colorbar", **kwargs): super(XpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="xanchor", parent_name="heatmap.colorbar", **kwargs): super(XanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "center", "right"]), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="x", parent_name="heatmap.colorbar", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TitleValidator(_plotly_utils.basevalidators.TitleValidator): def __init__(self, plotly_name="title", parent_name="heatmap.colorbar", **kwargs): super(TitleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Title"), data_docs=kwargs.pop( "data_docs", """ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """, ), **kwargs ) import _plotly_utils.basevalidators class TickwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="tickwidth", parent_name="heatmap.colorbar", **kwargs ): super(TickwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickvalssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="tickvalssrc", parent_name="heatmap.colorbar", **kwargs ): super(TickvalssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickvalsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="tickvals", parent_name="heatmap.colorbar", **kwargs ): super(TickvalsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="ticktextsrc", parent_name="heatmap.colorbar", **kwargs ): super(TicktextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicktextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="ticktext", parent_name="heatmap.colorbar", **kwargs ): super(TicktextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="ticksuffix", parent_name="heatmap.colorbar", **kwargs ): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TicksValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="ticks", parent_name="heatmap.colorbar", **kwargs): super(TicksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["outside", "inside", ""]), **kwargs ) import _plotly_utils.basevalidators class TickprefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickprefix", parent_name="heatmap.colorbar", **kwargs ): super(TickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="tickmode", parent_name="heatmap.colorbar", **kwargs ): super(TickmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "linear", "array"]), **kwargs ) import _plotly_utils.basevalidators class TicklenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="ticklen", parent_name="heatmap.colorbar", **kwargs): super(TicklenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickformatstopValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickformatstopdefaults", parent_name="heatmap.colorbar", **kwargs ): super(TickformatstopValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatstopsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="tickformatstops", parent_name="heatmap.colorbar", **kwargs ): super(TickformatstopsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickformat", parent_name="heatmap.colorbar", **kwargs ): super(TickformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickfont", parent_name="heatmap.colorbar", **kwargs ): super(TickfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class TickcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="tickcolor", parent_name="heatmap.colorbar", **kwargs ): super(TickcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__( self, plotly_name="tickangle", parent_name="heatmap.colorbar", **kwargs ): super(TickangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="tick0", parent_name="heatmap.colorbar", **kwargs): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ThicknessmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="thicknessmode", parent_name="heatmap.colorbar", **kwargs ): super(ThicknessmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="thickness", parent_name="heatmap.colorbar", **kwargs ): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowticksuffixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showticksuffix", parent_name="heatmap.colorbar", **kwargs ): super(ShowticksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowtickprefixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showtickprefix", parent_name="heatmap.colorbar", **kwargs ): super(ShowtickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowticklabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showticklabels", parent_name="heatmap.colorbar", **kwargs ): super(ShowticklabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowexponentValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showexponent", parent_name="heatmap.colorbar", **kwargs ): super(ShowexponentValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class SeparatethousandsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="separatethousands", parent_name="heatmap.colorbar", **kwargs ): super(SeparatethousandsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="outlinewidth", parent_name="heatmap.colorbar", **kwargs ): super(OutlinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="outlinecolor", parent_name="heatmap.colorbar", **kwargs ): super(OutlinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NticksValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="nticks", parent_name="heatmap.colorbar", **kwargs): super(NticksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LenmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="lenmode", parent_name="heatmap.colorbar", **kwargs): super(LenmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class LenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="len", parent_name="heatmap.colorbar", **kwargs): super(LenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ExponentformatValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="exponentformat", parent_name="heatmap.colorbar", **kwargs ): super(ExponentformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "e", "E", "power", "SI", "B"]), **kwargs ) import _plotly_utils.basevalidators class DtickValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="dtick", parent_name="heatmap.colorbar", **kwargs): super(DtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BorderwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="borderwidth", parent_name="heatmap.colorbar", **kwargs ): super(BorderwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="heatmap.colorbar", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="bgcolor", parent_name="heatmap.colorbar", **kwargs): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/heatmap/colorbar/tickfont/0000755000175000017500000000000013573746614025027 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/heatmap/colorbar/tickfont/__init__.py0000644000175000017500000000302613573721537027136 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="heatmap.colorbar.tickfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="heatmap.colorbar.tickfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="heatmap.colorbar.tickfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/heatmap/stream/0000755000175000017500000000000013573746614022676 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/heatmap/stream/__init__.py0000644000175000017500000000206413573721537025006 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TokenValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="token", parent_name="heatmap.stream", **kwargs): super(TokenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "info"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class MaxpointsValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="maxpoints", parent_name="heatmap.stream", **kwargs): super(MaxpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 10000), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/heatmap/__init__.py0000644000175000017500000011470213573721540023510 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ZsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="zsrc", parent_name="heatmap", **kwargs): super(ZsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZsmoothValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="zsmooth", parent_name="heatmap", **kwargs): super(ZsmoothValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["fast", "best", False]), **kwargs ) import _plotly_utils.basevalidators class ZminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="zmin", parent_name="heatmap", **kwargs): super(ZminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"zauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZmidValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="zmid", parent_name="heatmap", **kwargs): super(ZmidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZmaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="zmax", parent_name="heatmap", **kwargs): super(ZmaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"zauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZhoverformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="zhoverformat", parent_name="heatmap", **kwargs): super(ZhoverformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ZautoValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="zauto", parent_name="heatmap", **kwargs): super(ZautoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="z", parent_name="heatmap", **kwargs): super(ZValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class YtypeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="ytype", parent_name="heatmap", **kwargs): super(YtypeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["array", "scaled"]), **kwargs ) import _plotly_utils.basevalidators class YsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="ysrc", parent_name="heatmap", **kwargs): super(YsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YgapValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="ygap", parent_name="heatmap", **kwargs): super(YgapValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class YcalendarValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="ycalendar", parent_name="heatmap", **kwargs): super(YcalendarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "gregorian", "chinese", "coptic", "discworld", "ethiopian", "hebrew", "islamic", "julian", "mayan", "nanakshahi", "nepali", "persian", "jalali", "taiwan", "thai", "ummalqura", ], ), **kwargs ) import _plotly_utils.basevalidators class YAxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="yaxis", parent_name="heatmap", **kwargs): super(YAxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "y"), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class Y0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="y0", parent_name="heatmap", **kwargs): super(Y0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), implied_edits=kwargs.pop("implied_edits", {"ytype": "scaled"}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="y", parent_name="heatmap", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), implied_edits=kwargs.pop("implied_edits", {"ytype": "array"}), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class XtypeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="xtype", parent_name="heatmap", **kwargs): super(XtypeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["array", "scaled"]), **kwargs ) import _plotly_utils.basevalidators class XsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="xsrc", parent_name="heatmap", **kwargs): super(XsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XgapValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="xgap", parent_name="heatmap", **kwargs): super(XgapValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XcalendarValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="xcalendar", parent_name="heatmap", **kwargs): super(XcalendarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "gregorian", "chinese", "coptic", "discworld", "ethiopian", "hebrew", "islamic", "julian", "mayan", "nanakshahi", "nepali", "persian", "jalali", "taiwan", "thai", "ummalqura", ], ), **kwargs ) import _plotly_utils.basevalidators class XAxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="xaxis", parent_name="heatmap", **kwargs): super(XAxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "x"), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class X0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="x0", parent_name="heatmap", **kwargs): super(X0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), implied_edits=kwargs.pop("implied_edits", {"xtype": "scaled"}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="x", parent_name="heatmap", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), implied_edits=kwargs.pop("implied_edits", {"xtype": "array"}), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="visible", parent_name="heatmap", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "legendonly"]), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="heatmap", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UidValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="uid", parent_name="heatmap", **kwargs): super(UidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TransposeValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="transpose", parent_name="heatmap", **kwargs): super(TransposeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="textsrc", parent_name="heatmap", **kwargs): super(TextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="text", parent_name="heatmap", **kwargs): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class StreamValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="stream", parent_name="heatmap", **kwargs): super(StreamValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Stream"), data_docs=kwargs.pop( "data_docs", """ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """, ), **kwargs ) import _plotly_utils.basevalidators class ShowscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showscale", parent_name="heatmap", **kwargs): super(ShowscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ReversescaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="reversescale", parent_name="heatmap", **kwargs): super(ReversescaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="heatmap", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="heatmap", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="metasrc", parent_name="heatmap", **kwargs): super(MetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetaValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="meta", parent_name="heatmap", **kwargs): super(MetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="idssrc", parent_name="heatmap", **kwargs): super(IdssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ids", parent_name="heatmap", **kwargs): super(IdsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class HovertextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hovertextsrc", parent_name="heatmap", **kwargs): super(HovertextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="hovertext", parent_name="heatmap", **kwargs): super(HovertextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class HovertemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hovertemplatesrc", parent_name="heatmap", **kwargs): super(HovertemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertemplate", parent_name="heatmap", **kwargs): super(HovertemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverongapsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="hoverongaps", parent_name="heatmap", **kwargs): super(HoverongapsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class HoverlabelValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="hoverlabel", parent_name="heatmap", **kwargs): super(HoverlabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Hoverlabel"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """, ), **kwargs ) import _plotly_utils.basevalidators class HoverinfosrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hoverinfosrc", parent_name="heatmap", **kwargs): super(HoverinfosrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverinfoValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="hoverinfo", parent_name="heatmap", **kwargs): super(HoverinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), extras=kwargs.pop("extras", ["all", "none", "skip"]), flags=kwargs.pop("flags", ["x", "y", "z", "text", "name"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DyValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="dy", parent_name="heatmap", **kwargs): super(DyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"ytype": "scaled"}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="dx", parent_name="heatmap", **kwargs): super(DxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"xtype": "scaled"}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdatasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="customdatasrc", parent_name="heatmap", **kwargs): super(CustomdatasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdataValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="customdata", parent_name="heatmap", **kwargs): super(CustomdataValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class ConnectgapsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="connectgaps", parent_name="heatmap", **kwargs): super(ConnectgapsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__(self, plotly_name="colorscale", parent_name="heatmap", **kwargs): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"autocolorscale": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorBarValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="colorbar", parent_name="heatmap", **kwargs): super(ColorBarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "ColorBar"), data_docs=kwargs.pop( "data_docs", """ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.heatmap.colorba r.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.heatmap.colorbar.tickformatstopdefaults), sets the default property values to use for elements of heatmap.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.heatmap.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use heatmap.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use heatmap.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """, ), **kwargs ) import _plotly_utils.basevalidators class ColoraxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="coloraxis", parent_name="heatmap", **kwargs): super(ColoraxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", None), edit_type=kwargs.pop("edit_type", "calc"), regex=kwargs.pop("regex", "/^coloraxis([2-9]|[1-9][0-9]+)?$/"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AutocolorscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="autocolorscale", parent_name="heatmap", **kwargs): super(AutocolorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/parcoords/0000755000175000017500000000000013573746614021760 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/parcoords/labelfont/0000755000175000017500000000000013573746614023726 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/parcoords/labelfont/__init__.py0000644000175000017500000000274713573721541026041 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="size", parent_name="parcoords.labelfont", **kwargs): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="parcoords.labelfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="parcoords.labelfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/parcoords/stream/0000755000175000017500000000000013573746614023253 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/parcoords/stream/__init__.py0000644000175000017500000000210613573721541025353 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TokenValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="token", parent_name="parcoords.stream", **kwargs): super(TokenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "info"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class MaxpointsValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="maxpoints", parent_name="parcoords.stream", **kwargs ): super(MaxpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 10000), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/parcoords/__init__.py0000644000175000017500000005244013573721541024066 0ustar noahfxnoahfximport _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="visible", parent_name="parcoords", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "legendonly"]), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="parcoords", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UidValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="uid", parent_name="parcoords", **kwargs): super(UidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="tickfont", parent_name="parcoords", **kwargs): super(TickfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class StreamValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="stream", parent_name="parcoords", **kwargs): super(StreamValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Stream"), data_docs=kwargs.pop( "data_docs", """ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """, ), **kwargs ) import _plotly_utils.basevalidators class RangefontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="rangefont", parent_name="parcoords", **kwargs): super(RangefontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Rangefont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="parcoords", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="metasrc", parent_name="parcoords", **kwargs): super(MetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetaValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="meta", parent_name="parcoords", **kwargs): super(MetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="line", parent_name="parcoords", **kwargs): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `line.colorscale`. Has an effect only if in `line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `line.color`) or the bounds set in `line.cmin` and `line.cmax` Has an effect only if in `line.color`is set to a numerical array. Defaults to `false` when `line.cmin` and `line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `line.color`is set to a numerical array. Value should have the same units as in `line.color` and if set, `line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `line.cmin` and/or `line.cmax` to be equidistant to this point. Has an effect only if in `line.color`is set to a numerical array. Value should have the same units as in `line.color`. Has no effect when `line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `line.color`is set to a numerical array. Value should have the same units as in `line.color` and if set, `line.cmax` must be set as well. color Sets thelinecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `line.cmin` and `line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.parcoords.line.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`line.cmin` and `line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu ,Greens,YlOrRd,Bluered,RdBu,Reds,Blues,Picnic,R ainbow,Portland,Jet,Hot,Blackbody,Earth,Electri c,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `line.color`is set to a numerical array. If true, `line.cmin` will correspond to the last color in the array and `line.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `line.color`is set to a numerical array. """, ), **kwargs ) import _plotly_utils.basevalidators class LabelsideValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="labelside", parent_name="parcoords", **kwargs): super(LabelsideValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["top", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class LabelfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="labelfont", parent_name="parcoords", **kwargs): super(LabelfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Labelfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class LabelangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__(self, plotly_name="labelangle", parent_name="parcoords", **kwargs): super(LabelangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="idssrc", parent_name="parcoords", **kwargs): super(IdssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ids", parent_name="parcoords", **kwargs): super(IdsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class DomainValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="domain", parent_name="parcoords", **kwargs): super(DomainValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Domain"), data_docs=kwargs.pop( "data_docs", """ column If there is a layout grid, use the domain for this column in the grid for this parcoords trace . row If there is a layout grid, use the domain for this row in the grid for this parcoords trace . x Sets the horizontal domain of this parcoords trace (in plot fraction). y Sets the vertical domain of this parcoords trace (in plot fraction). """, ), **kwargs ) import _plotly_utils.basevalidators class DimensionValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="dimensiondefaults", parent_name="parcoords", **kwargs ): super(DimensionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Dimension"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class DimensionsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__(self, plotly_name="dimensions", parent_name="parcoords", **kwargs): super(DimensionsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Dimension"), data_docs=kwargs.pop( "data_docs", """ constraintrange The domain range to which the filter on the dimension is constrained. Must be an array of `[fromValue, toValue]` with `fromValue <= toValue`, or if `multiselect` is not disabled, you may give an array of arrays, where each inner array is `[fromValue, toValue]`. label The shown name of the dimension. multiselect Do we allow multiple selection ranges or just a single range? name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. range The domain range that represents the full, shown axis extent. Defaults to the `values` extent. Must be an array of `[fromValue, toValue]` with finite numbers as elements. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" ticktext Sets the text displayed at the ticks position via `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. tickvalssrc Sets the source reference on plot.ly for tickvals . values Dimension values. `values[n]` represents the value of the `n`th point in the dataset, therefore the `values` vector for all dimensions must be the same (longer vectors will be truncated). Each value must be a finite number. valuessrc Sets the source reference on plot.ly for values . visible Shows the dimension when set to `true` (the default). Hides the dimension for `false`. """, ), **kwargs ) import _plotly_utils.basevalidators class CustomdatasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="customdatasrc", parent_name="parcoords", **kwargs): super(CustomdatasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdataValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="customdata", parent_name="parcoords", **kwargs): super(CustomdataValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/parcoords/dimension/0000755000175000017500000000000013573746614023745 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/parcoords/dimension/__init__.py0000644000175000017500000001611713573721541026054 0ustar noahfxnoahfximport _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="visible", parent_name="parcoords.dimension", **kwargs ): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ValuessrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="valuessrc", parent_name="parcoords.dimension", **kwargs ): super(ValuessrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ValuesValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="values", parent_name="parcoords.dimension", **kwargs ): super(ValuesValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TickvalssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="tickvalssrc", parent_name="parcoords.dimension", **kwargs ): super(TickvalssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickvalsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="tickvals", parent_name="parcoords.dimension", **kwargs ): super(TickvalsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="ticktextsrc", parent_name="parcoords.dimension", **kwargs ): super(TicktextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicktextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="ticktext", parent_name="parcoords.dimension", **kwargs ): super(TicktextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TickformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickformat", parent_name="parcoords.dimension", **kwargs ): super(TickformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="parcoords.dimension", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class RangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="range", parent_name="parcoords.dimension", **kwargs ): super(RangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), items=kwargs.pop( "items", [ {"valType": "number", "editType": "plot"}, {"valType": "number", "editType": "plot"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="parcoords.dimension", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class MultiselectValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="multiselect", parent_name="parcoords.dimension", **kwargs ): super(MultiselectValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LabelValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="label", parent_name="parcoords.dimension", **kwargs ): super(LabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ConstraintrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="constraintrange", parent_name="parcoords.dimension", **kwargs ): super(ConstraintrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dimensions=kwargs.pop("dimensions", "1-2"), edit_type=kwargs.pop("edit_type", "plot"), free_length=kwargs.pop("free_length", True), items=kwargs.pop( "items", [ {"valType": "number", "editType": "plot"}, {"valType": "number", "editType": "plot"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/parcoords/line/0000755000175000017500000000000013573746614022707 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/parcoords/line/colorbar/0000755000175000017500000000000013573746614024512 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/parcoords/line/colorbar/tickformatstop/0000755000175000017500000000000013573746614027563 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/parcoords/line/colorbar/tickformatstop/__init__.py0000644000175000017500000000543713573721541031675 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="value", parent_name="parcoords.line.colorbar.tickformatstop", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="parcoords.line.colorbar.tickformatstop", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="parcoords.line.colorbar.tickformatstop", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EnabledValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="enabled", parent_name="parcoords.line.colorbar.tickformatstop", **kwargs ): super(EnabledValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DtickrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="dtickrange", parent_name="parcoords.line.colorbar.tickformatstop", **kwargs ): super(DtickrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "colorbars"}, {"valType": "any", "editType": "colorbars"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/parcoords/line/colorbar/title/0000755000175000017500000000000013573746614025633 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/parcoords/line/colorbar/title/__init__.py0000644000175000017500000000474213573721541027743 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="text", parent_name="parcoords.line.colorbar.title", **kwargs ): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SideValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="side", parent_name="parcoords.line.colorbar.title", **kwargs ): super(SideValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["right", "top", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="parcoords.line.colorbar.title", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/parcoords/line/colorbar/title/font/0000755000175000017500000000000013573746614026601 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/parcoords/line/colorbar/title/font/__init__.py0000644000175000017500000000317113573721541030704 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="parcoords.line.colorbar.title.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="parcoords.line.colorbar.title.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="parcoords.line.colorbar.title.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/parcoords/line/colorbar/__init__.py0000644000175000017500000006130013573721542026614 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ypad", parent_name="parcoords.line.colorbar", **kwargs ): super(YpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class YanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="yanchor", parent_name="parcoords.line.colorbar", **kwargs ): super(YanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["top", "middle", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="y", parent_name="parcoords.line.colorbar", **kwargs ): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="xpad", parent_name="parcoords.line.colorbar", **kwargs ): super(XpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="xanchor", parent_name="parcoords.line.colorbar", **kwargs ): super(XanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "center", "right"]), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="x", parent_name="parcoords.line.colorbar", **kwargs ): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TitleValidator(_plotly_utils.basevalidators.TitleValidator): def __init__( self, plotly_name="title", parent_name="parcoords.line.colorbar", **kwargs ): super(TitleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Title"), data_docs=kwargs.pop( "data_docs", """ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """, ), **kwargs ) import _plotly_utils.basevalidators class TickwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="tickwidth", parent_name="parcoords.line.colorbar", **kwargs ): super(TickwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickvalssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="tickvalssrc", parent_name="parcoords.line.colorbar", **kwargs ): super(TickvalssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickvalsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="tickvals", parent_name="parcoords.line.colorbar", **kwargs ): super(TickvalsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="ticktextsrc", parent_name="parcoords.line.colorbar", **kwargs ): super(TicktextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicktextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="ticktext", parent_name="parcoords.line.colorbar", **kwargs ): super(TicktextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="ticksuffix", parent_name="parcoords.line.colorbar", **kwargs ): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TicksValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="ticks", parent_name="parcoords.line.colorbar", **kwargs ): super(TicksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["outside", "inside", ""]), **kwargs ) import _plotly_utils.basevalidators class TickprefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickprefix", parent_name="parcoords.line.colorbar", **kwargs ): super(TickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="tickmode", parent_name="parcoords.line.colorbar", **kwargs ): super(TickmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "linear", "array"]), **kwargs ) import _plotly_utils.basevalidators class TicklenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ticklen", parent_name="parcoords.line.colorbar", **kwargs ): super(TicklenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickformatstopValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickformatstopdefaults", parent_name="parcoords.line.colorbar", **kwargs ): super(TickformatstopValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatstopsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="tickformatstops", parent_name="parcoords.line.colorbar", **kwargs ): super(TickformatstopsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickformat", parent_name="parcoords.line.colorbar", **kwargs ): super(TickformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickfont", parent_name="parcoords.line.colorbar", **kwargs ): super(TickfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class TickcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="tickcolor", parent_name="parcoords.line.colorbar", **kwargs ): super(TickcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__( self, plotly_name="tickangle", parent_name="parcoords.line.colorbar", **kwargs ): super(TickangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="tick0", parent_name="parcoords.line.colorbar", **kwargs ): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ThicknessmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="thicknessmode", parent_name="parcoords.line.colorbar", **kwargs ): super(ThicknessmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="thickness", parent_name="parcoords.line.colorbar", **kwargs ): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowticksuffixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showticksuffix", parent_name="parcoords.line.colorbar", **kwargs ): super(ShowticksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowtickprefixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showtickprefix", parent_name="parcoords.line.colorbar", **kwargs ): super(ShowtickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowticklabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showticklabels", parent_name="parcoords.line.colorbar", **kwargs ): super(ShowticklabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowexponentValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showexponent", parent_name="parcoords.line.colorbar", **kwargs ): super(ShowexponentValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class SeparatethousandsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="separatethousands", parent_name="parcoords.line.colorbar", **kwargs ): super(SeparatethousandsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="outlinewidth", parent_name="parcoords.line.colorbar", **kwargs ): super(OutlinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="outlinecolor", parent_name="parcoords.line.colorbar", **kwargs ): super(OutlinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NticksValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="nticks", parent_name="parcoords.line.colorbar", **kwargs ): super(NticksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LenmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="lenmode", parent_name="parcoords.line.colorbar", **kwargs ): super(LenmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class LenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="len", parent_name="parcoords.line.colorbar", **kwargs ): super(LenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ExponentformatValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="exponentformat", parent_name="parcoords.line.colorbar", **kwargs ): super(ExponentformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "e", "E", "power", "SI", "B"]), **kwargs ) import _plotly_utils.basevalidators class DtickValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="dtick", parent_name="parcoords.line.colorbar", **kwargs ): super(DtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BorderwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="borderwidth", parent_name="parcoords.line.colorbar", **kwargs ): super(BorderwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="parcoords.line.colorbar", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="parcoords.line.colorbar", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/parcoords/line/colorbar/tickfont/0000755000175000017500000000000013573746614026333 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/parcoords/line/colorbar/tickfont/__init__.py0000644000175000017500000000316313573721541030437 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="parcoords.line.colorbar.tickfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="parcoords.line.colorbar.tickfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="parcoords.line.colorbar.tickfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/parcoords/line/__init__.py0000644000175000017500000004013013573721541025006 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ShowscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showscale", parent_name="parcoords.line", **kwargs): super(ShowscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ReversescaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="reversescale", parent_name="parcoords.line", **kwargs ): super(ReversescaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="colorsrc", parent_name="parcoords.line", **kwargs): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__( self, plotly_name="colorscale", parent_name="parcoords.line", **kwargs ): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"autocolorscale": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorBarValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="colorbar", parent_name="parcoords.line", **kwargs): super(ColorBarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "ColorBar"), data_docs=kwargs.pop( "data_docs", """ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.parcoords.line. colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.parcoords.line.colorbar.tickformatstopdefault s), sets the default property values to use for elements of parcoords.line.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.parcoords.line.colorbar.Ti tle instance or dict with compatible properties titlefont Deprecated: Please use parcoords.line.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use parcoords.line.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """, ), **kwargs ) import _plotly_utils.basevalidators class ColoraxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="coloraxis", parent_name="parcoords.line", **kwargs): super(ColoraxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", None), edit_type=kwargs.pop("edit_type", "calc"), regex=kwargs.pop("regex", "/^coloraxis([2-9]|[1-9][0-9]+)?$/"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="parcoords.line", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), colorscale_path=kwargs.pop("colorscale_path", "parcoords.line.colorscale"), **kwargs ) import _plotly_utils.basevalidators class CminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmin", parent_name="parcoords.line", **kwargs): super(CminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmidValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmid", parent_name="parcoords.line", **kwargs): super(CmidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmax", parent_name="parcoords.line", **kwargs): super(CmaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CautoValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="cauto", parent_name="parcoords.line", **kwargs): super(CautoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AutocolorscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="autocolorscale", parent_name="parcoords.line", **kwargs ): super(AutocolorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/parcoords/rangefont/0000755000175000017500000000000013573746614023743 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/parcoords/rangefont/__init__.py0000644000175000017500000000274713573721541026056 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="size", parent_name="parcoords.rangefont", **kwargs): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="parcoords.rangefont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="parcoords.rangefont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/parcoords/domain/0000755000175000017500000000000013573746614023227 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/parcoords/domain/__init__.py0000644000175000017500000000452113573721541025332 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="y", parent_name="parcoords.domain", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), items=kwargs.pop( "items", [ {"valType": "number", "min": 0, "max": 1, "editType": "plot"}, {"valType": "number", "min": 0, "max": 1, "editType": "plot"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="x", parent_name="parcoords.domain", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), items=kwargs.pop( "items", [ {"valType": "number", "min": 0, "max": 1, "editType": "plot"}, {"valType": "number", "min": 0, "max": 1, "editType": "plot"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class RowValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="row", parent_name="parcoords.domain", **kwargs): super(RowValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColumnValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="column", parent_name="parcoords.domain", **kwargs): super(ColumnValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/parcoords/tickfont/0000755000175000017500000000000013573746614023601 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/parcoords/tickfont/__init__.py0000644000175000017500000000272613573721541025711 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="size", parent_name="parcoords.tickfont", **kwargs): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="parcoords.tickfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="parcoords.tickfont", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatter/0000755000175000017500000000000013573746614021431 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatter/unselected/0000755000175000017500000000000013573746614023564 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatter/unselected/textfont/0000755000175000017500000000000013573746614025437 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatter/unselected/textfont/__init__.py0000644000175000017500000000072613573721542027546 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scatter.unselected.textfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatter/unselected/marker/0000755000175000017500000000000013573746614025045 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatter/unselected/marker/__init__.py0000644000175000017500000000276713573721542027163 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scatter.unselected.marker", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="opacity", parent_name="scatter.unselected.marker", **kwargs ): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scatter.unselected.marker", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatter/unselected/__init__.py0000644000175000017500000000311513573721542025666 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="textfont", parent_name="scatter.unselected", **kwargs ): super(TextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Textfont"), data_docs=kwargs.pop( "data_docs", """ color Sets the text font color of unselected points, applied only when a selection exists. """, ), **kwargs ) import _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="marker", parent_name="scatter.unselected", **kwargs ): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. size Sets the marker size of unselected points, applied only when a selection exists. """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatter/textfont/0000755000175000017500000000000013573746614023304 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatter/textfont/__init__.py0000644000175000017500000000570413573721542025414 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="sizesrc", parent_name="scatter.textfont", **kwargs): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="size", parent_name="scatter.textfont", **kwargs): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="scatter.textfont", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="family", parent_name="scatter.textfont", **kwargs): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="scatter.textfont", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="scatter.textfont", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatter/error_x/0000755000175000017500000000000013573746614023111 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatter/error_x/__init__.py0000644000175000017500000001610413573721542025215 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="scatter.error_x", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="visible", parent_name="scatter.error_x", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ValueminusValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="valueminus", parent_name="scatter.error_x", **kwargs ): super(ValueminusValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="value", parent_name="scatter.error_x", **kwargs): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TypeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="type", parent_name="scatter.error_x", **kwargs): super(TypeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["percent", "constant", "sqrt", "data"]), **kwargs ) import _plotly_utils.basevalidators class TracerefminusValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="tracerefminus", parent_name="scatter.error_x", **kwargs ): super(TracerefminusValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TracerefValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="traceref", parent_name="scatter.error_x", **kwargs): super(TracerefValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="thickness", parent_name="scatter.error_x", **kwargs ): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SymmetricValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="symmetric", parent_name="scatter.error_x", **kwargs ): super(SymmetricValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CopyYstyleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="copy_ystyle", parent_name="scatter.error_x", **kwargs ): super(CopyYstyleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="scatter.error_x", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ArraysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="arraysrc", parent_name="scatter.error_x", **kwargs): super(ArraysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ArrayminussrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="arrayminussrc", parent_name="scatter.error_x", **kwargs ): super(ArrayminussrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ArrayminusValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="arrayminus", parent_name="scatter.error_x", **kwargs ): super(ArrayminusValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class ArrayValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="array", parent_name="scatter.error_x", **kwargs): super(ArrayValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatter/hoverlabel/0000755000175000017500000000000013573746614023554 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatter/hoverlabel/__init__.py0000644000175000017500000001340313573721542025657 0ustar noahfxnoahfximport _plotly_utils.basevalidators class NamelengthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="namelengthsrc", parent_name="scatter.hoverlabel", **kwargs ): super(NamelengthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NamelengthValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="namelength", parent_name="scatter.hoverlabel", **kwargs ): super(NamelengthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", -1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="font", parent_name="scatter.hoverlabel", **kwargs): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class BordercolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bordercolorsrc", parent_name="scatter.hoverlabel", **kwargs ): super(BordercolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="scatter.hoverlabel", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bgcolorsrc", parent_name="scatter.hoverlabel", **kwargs ): super(BgcolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="scatter.hoverlabel", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AlignsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="alignsrc", parent_name="scatter.hoverlabel", **kwargs ): super(AlignsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="align", parent_name="scatter.hoverlabel", **kwargs): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "right", "auto"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatter/hoverlabel/font/0000755000175000017500000000000013573746614024522 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatter/hoverlabel/font/__init__.py0000644000175000017500000000604513573721542026631 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="scatter.hoverlabel.font", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scatter.hoverlabel.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="scatter.hoverlabel.font", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="scatter.hoverlabel.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="scatter.hoverlabel.font", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scatter.hoverlabel.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatter/error_y/0000755000175000017500000000000013573746614023112 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatter/error_y/__init__.py0000644000175000017500000001514713573721542025224 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="scatter.error_y", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="visible", parent_name="scatter.error_y", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ValueminusValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="valueminus", parent_name="scatter.error_y", **kwargs ): super(ValueminusValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="value", parent_name="scatter.error_y", **kwargs): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TypeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="type", parent_name="scatter.error_y", **kwargs): super(TypeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["percent", "constant", "sqrt", "data"]), **kwargs ) import _plotly_utils.basevalidators class TracerefminusValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="tracerefminus", parent_name="scatter.error_y", **kwargs ): super(TracerefminusValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TracerefValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="traceref", parent_name="scatter.error_y", **kwargs): super(TracerefValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="thickness", parent_name="scatter.error_y", **kwargs ): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SymmetricValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="symmetric", parent_name="scatter.error_y", **kwargs ): super(SymmetricValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="scatter.error_y", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ArraysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="arraysrc", parent_name="scatter.error_y", **kwargs): super(ArraysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ArrayminussrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="arrayminussrc", parent_name="scatter.error_y", **kwargs ): super(ArrayminussrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ArrayminusValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="arrayminus", parent_name="scatter.error_y", **kwargs ): super(ArrayminusValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class ArrayValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="array", parent_name="scatter.error_y", **kwargs): super(ArrayValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatter/marker/0000755000175000017500000000000013573746614022712 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatter/marker/colorbar/0000755000175000017500000000000013573746614024515 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatter/marker/colorbar/tickformatstop/0000755000175000017500000000000013573746614027566 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatter/marker/colorbar/tickformatstop/__init__.py0000644000175000017500000000543713573721542031701 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="value", parent_name="scatter.marker.colorbar.tickformatstop", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="scatter.marker.colorbar.tickformatstop", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="scatter.marker.colorbar.tickformatstop", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EnabledValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="enabled", parent_name="scatter.marker.colorbar.tickformatstop", **kwargs ): super(EnabledValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DtickrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="dtickrange", parent_name="scatter.marker.colorbar.tickformatstop", **kwargs ): super(DtickrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "colorbars"}, {"valType": "any", "editType": "colorbars"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatter/marker/colorbar/title/0000755000175000017500000000000013573746614025636 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatter/marker/colorbar/title/__init__.py0000644000175000017500000000474213573721542027747 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="text", parent_name="scatter.marker.colorbar.title", **kwargs ): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SideValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="side", parent_name="scatter.marker.colorbar.title", **kwargs ): super(SideValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["right", "top", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="scatter.marker.colorbar.title", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatter/marker/colorbar/title/font/0000755000175000017500000000000013573746614026604 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatter/marker/colorbar/title/font/__init__.py0000644000175000017500000000317113573721542030710 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scatter.marker.colorbar.title.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="scatter.marker.colorbar.title.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scatter.marker.colorbar.title.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatter/marker/colorbar/__init__.py0000644000175000017500000006130013573721542026617 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ypad", parent_name="scatter.marker.colorbar", **kwargs ): super(YpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class YanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="yanchor", parent_name="scatter.marker.colorbar", **kwargs ): super(YanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["top", "middle", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="y", parent_name="scatter.marker.colorbar", **kwargs ): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="xpad", parent_name="scatter.marker.colorbar", **kwargs ): super(XpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="xanchor", parent_name="scatter.marker.colorbar", **kwargs ): super(XanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "center", "right"]), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="x", parent_name="scatter.marker.colorbar", **kwargs ): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TitleValidator(_plotly_utils.basevalidators.TitleValidator): def __init__( self, plotly_name="title", parent_name="scatter.marker.colorbar", **kwargs ): super(TitleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Title"), data_docs=kwargs.pop( "data_docs", """ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """, ), **kwargs ) import _plotly_utils.basevalidators class TickwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="tickwidth", parent_name="scatter.marker.colorbar", **kwargs ): super(TickwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickvalssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="tickvalssrc", parent_name="scatter.marker.colorbar", **kwargs ): super(TickvalssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickvalsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="tickvals", parent_name="scatter.marker.colorbar", **kwargs ): super(TickvalsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="ticktextsrc", parent_name="scatter.marker.colorbar", **kwargs ): super(TicktextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicktextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="ticktext", parent_name="scatter.marker.colorbar", **kwargs ): super(TicktextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="ticksuffix", parent_name="scatter.marker.colorbar", **kwargs ): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TicksValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="ticks", parent_name="scatter.marker.colorbar", **kwargs ): super(TicksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["outside", "inside", ""]), **kwargs ) import _plotly_utils.basevalidators class TickprefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickprefix", parent_name="scatter.marker.colorbar", **kwargs ): super(TickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="tickmode", parent_name="scatter.marker.colorbar", **kwargs ): super(TickmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "linear", "array"]), **kwargs ) import _plotly_utils.basevalidators class TicklenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ticklen", parent_name="scatter.marker.colorbar", **kwargs ): super(TicklenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickformatstopValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickformatstopdefaults", parent_name="scatter.marker.colorbar", **kwargs ): super(TickformatstopValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatstopsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="tickformatstops", parent_name="scatter.marker.colorbar", **kwargs ): super(TickformatstopsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickformat", parent_name="scatter.marker.colorbar", **kwargs ): super(TickformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickfont", parent_name="scatter.marker.colorbar", **kwargs ): super(TickfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class TickcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="tickcolor", parent_name="scatter.marker.colorbar", **kwargs ): super(TickcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__( self, plotly_name="tickangle", parent_name="scatter.marker.colorbar", **kwargs ): super(TickangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="tick0", parent_name="scatter.marker.colorbar", **kwargs ): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ThicknessmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="thicknessmode", parent_name="scatter.marker.colorbar", **kwargs ): super(ThicknessmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="thickness", parent_name="scatter.marker.colorbar", **kwargs ): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowticksuffixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showticksuffix", parent_name="scatter.marker.colorbar", **kwargs ): super(ShowticksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowtickprefixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showtickprefix", parent_name="scatter.marker.colorbar", **kwargs ): super(ShowtickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowticklabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showticklabels", parent_name="scatter.marker.colorbar", **kwargs ): super(ShowticklabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowexponentValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showexponent", parent_name="scatter.marker.colorbar", **kwargs ): super(ShowexponentValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class SeparatethousandsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="separatethousands", parent_name="scatter.marker.colorbar", **kwargs ): super(SeparatethousandsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="outlinewidth", parent_name="scatter.marker.colorbar", **kwargs ): super(OutlinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="outlinecolor", parent_name="scatter.marker.colorbar", **kwargs ): super(OutlinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NticksValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="nticks", parent_name="scatter.marker.colorbar", **kwargs ): super(NticksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LenmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="lenmode", parent_name="scatter.marker.colorbar", **kwargs ): super(LenmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class LenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="len", parent_name="scatter.marker.colorbar", **kwargs ): super(LenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ExponentformatValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="exponentformat", parent_name="scatter.marker.colorbar", **kwargs ): super(ExponentformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "e", "E", "power", "SI", "B"]), **kwargs ) import _plotly_utils.basevalidators class DtickValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="dtick", parent_name="scatter.marker.colorbar", **kwargs ): super(DtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BorderwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="borderwidth", parent_name="scatter.marker.colorbar", **kwargs ): super(BorderwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="scatter.marker.colorbar", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="scatter.marker.colorbar", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatter/marker/colorbar/tickfont/0000755000175000017500000000000013573746614026336 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatter/marker/colorbar/tickfont/__init__.py0000644000175000017500000000316313573721542030443 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scatter.marker.colorbar.tickfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="scatter.marker.colorbar.tickfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scatter.marker.colorbar.tickfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatter/marker/gradient/0000755000175000017500000000000013573746614024507 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatter/marker/gradient/__init__.py0000644000175000017500000000402213573721542026607 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TypesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="typesrc", parent_name="scatter.marker.gradient", **kwargs ): super(TypesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TypeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="type", parent_name="scatter.marker.gradient", **kwargs ): super(TypeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["radial", "horizontal", "vertical", "none"]), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="scatter.marker.gradient", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scatter.marker.gradient", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatter/marker/__init__.py0000644000175000017500000010730713573721542025024 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SymbolsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="symbolsrc", parent_name="scatter.marker", **kwargs): super(SymbolsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SymbolValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="symbol", parent_name="scatter.marker", **kwargs): super(SymbolValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", [ 0, "circle", 100, "circle-open", 200, "circle-dot", 300, "circle-open-dot", 1, "square", 101, "square-open", 201, "square-dot", 301, "square-open-dot", 2, "diamond", 102, "diamond-open", 202, "diamond-dot", 302, "diamond-open-dot", 3, "cross", 103, "cross-open", 203, "cross-dot", 303, "cross-open-dot", 4, "x", 104, "x-open", 204, "x-dot", 304, "x-open-dot", 5, "triangle-up", 105, "triangle-up-open", 205, "triangle-up-dot", 305, "triangle-up-open-dot", 6, "triangle-down", 106, "triangle-down-open", 206, "triangle-down-dot", 306, "triangle-down-open-dot", 7, "triangle-left", 107, "triangle-left-open", 207, "triangle-left-dot", 307, "triangle-left-open-dot", 8, "triangle-right", 108, "triangle-right-open", 208, "triangle-right-dot", 308, "triangle-right-open-dot", 9, "triangle-ne", 109, "triangle-ne-open", 209, "triangle-ne-dot", 309, "triangle-ne-open-dot", 10, "triangle-se", 110, "triangle-se-open", 210, "triangle-se-dot", 310, "triangle-se-open-dot", 11, "triangle-sw", 111, "triangle-sw-open", 211, "triangle-sw-dot", 311, "triangle-sw-open-dot", 12, "triangle-nw", 112, "triangle-nw-open", 212, "triangle-nw-dot", 312, "triangle-nw-open-dot", 13, "pentagon", 113, "pentagon-open", 213, "pentagon-dot", 313, "pentagon-open-dot", 14, "hexagon", 114, "hexagon-open", 214, "hexagon-dot", 314, "hexagon-open-dot", 15, "hexagon2", 115, "hexagon2-open", 215, "hexagon2-dot", 315, "hexagon2-open-dot", 16, "octagon", 116, "octagon-open", 216, "octagon-dot", 316, "octagon-open-dot", 17, "star", 117, "star-open", 217, "star-dot", 317, "star-open-dot", 18, "hexagram", 118, "hexagram-open", 218, "hexagram-dot", 318, "hexagram-open-dot", 19, "star-triangle-up", 119, "star-triangle-up-open", 219, "star-triangle-up-dot", 319, "star-triangle-up-open-dot", 20, "star-triangle-down", 120, "star-triangle-down-open", 220, "star-triangle-down-dot", 320, "star-triangle-down-open-dot", 21, "star-square", 121, "star-square-open", 221, "star-square-dot", 321, "star-square-open-dot", 22, "star-diamond", 122, "star-diamond-open", 222, "star-diamond-dot", 322, "star-diamond-open-dot", 23, "diamond-tall", 123, "diamond-tall-open", 223, "diamond-tall-dot", 323, "diamond-tall-open-dot", 24, "diamond-wide", 124, "diamond-wide-open", 224, "diamond-wide-dot", 324, "diamond-wide-open-dot", 25, "hourglass", 125, "hourglass-open", 26, "bowtie", 126, "bowtie-open", 27, "circle-cross", 127, "circle-cross-open", 28, "circle-x", 128, "circle-x-open", 29, "square-cross", 129, "square-cross-open", 30, "square-x", 130, "square-x-open", 31, "diamond-cross", 131, "diamond-cross-open", 32, "diamond-x", 132, "diamond-x-open", 33, "cross-thin", 133, "cross-thin-open", 34, "x-thin", 134, "x-thin-open", 35, "asterisk", 135, "asterisk-open", 36, "hash", 136, "hash-open", 236, "hash-dot", 336, "hash-open-dot", 37, "y-up", 137, "y-up-open", 38, "y-down", 138, "y-down-open", 39, "y-left", 139, "y-left-open", 40, "y-right", 140, "y-right-open", 41, "line-ew", 141, "line-ew-open", 42, "line-ns", 142, "line-ns-open", 43, "line-ne", 143, "line-ne-open", 44, "line-nw", 144, "line-nw-open", ], ), **kwargs ) import _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="sizesrc", parent_name="scatter.marker", **kwargs): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizerefValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="sizeref", parent_name="scatter.marker", **kwargs): super(SizerefValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SizemodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="sizemode", parent_name="scatter.marker", **kwargs): super(SizemodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["diameter", "area"]), **kwargs ) import _plotly_utils.basevalidators class SizeminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="sizemin", parent_name="scatter.marker", **kwargs): super(SizeminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="size", parent_name="scatter.marker", **kwargs): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, anim=kwargs.pop("anim", True), array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showscale", parent_name="scatter.marker", **kwargs): super(ShowscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ReversescaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="reversescale", parent_name="scatter.marker", **kwargs ): super(ReversescaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacitysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="opacitysrc", parent_name="scatter.marker", **kwargs ): super(OpacitysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="scatter.marker", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, anim=kwargs.pop("anim", True), array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class MaxdisplayedValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="maxdisplayed", parent_name="scatter.marker", **kwargs ): super(MaxdisplayedValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="line", parent_name="scatter.marker", **kwargs): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,R eds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Black body,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . """, ), **kwargs ) import _plotly_utils.basevalidators class GradientValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="gradient", parent_name="scatter.marker", **kwargs): super(GradientValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Gradient"), data_docs=kwargs.pop( "data_docs", """ color Sets the final color of the gradient fill: the center color for radial, the right for horizontal, or the bottom for vertical. colorsrc Sets the source reference on plot.ly for color . type Sets the type of gradient used to fill the markers typesrc Sets the source reference on plot.ly for type . """, ), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="colorsrc", parent_name="scatter.marker", **kwargs): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__( self, plotly_name="colorscale", parent_name="scatter.marker", **kwargs ): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"autocolorscale": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorBarValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="colorbar", parent_name="scatter.marker", **kwargs): super(ColorBarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "ColorBar"), data_docs=kwargs.pop( "data_docs", """ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.scatter.marker. colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.scatter.marker.colorbar.tickformatstopdefault s), sets the default property values to use for elements of scatter.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.scatter.marker.colorbar.Ti tle instance or dict with compatible properties titlefont Deprecated: Please use scatter.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use scatter.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """, ), **kwargs ) import _plotly_utils.basevalidators class ColoraxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="coloraxis", parent_name="scatter.marker", **kwargs): super(ColoraxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", None), edit_type=kwargs.pop("edit_type", "calc"), regex=kwargs.pop("regex", "/^coloraxis([2-9]|[1-9][0-9]+)?$/"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="scatter.marker", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, anim=kwargs.pop("anim", True), array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), colorscale_path=kwargs.pop("colorscale_path", "scatter.marker.colorscale"), **kwargs ) import _plotly_utils.basevalidators class CminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmin", parent_name="scatter.marker", **kwargs): super(CminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmidValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmid", parent_name="scatter.marker", **kwargs): super(CmidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmax", parent_name="scatter.marker", **kwargs): super(CmaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CautoValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="cauto", parent_name="scatter.marker", **kwargs): super(CautoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AutocolorscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="autocolorscale", parent_name="scatter.marker", **kwargs ): super(AutocolorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatter/marker/line/0000755000175000017500000000000013573746614023641 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatter/marker/line/__init__.py0000644000175000017500000001451713573721542025753 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="widthsrc", parent_name="scatter.marker.line", **kwargs ): super(WidthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="width", parent_name="scatter.marker.line", **kwargs ): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, anim=kwargs.pop("anim", True), array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ReversescaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="reversescale", parent_name="scatter.marker.line", **kwargs ): super(ReversescaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="scatter.marker.line", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__( self, plotly_name="colorscale", parent_name="scatter.marker.line", **kwargs ): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"autocolorscale": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColoraxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__( self, plotly_name="coloraxis", parent_name="scatter.marker.line", **kwargs ): super(ColoraxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", None), edit_type=kwargs.pop("edit_type", "calc"), regex=kwargs.pop("regex", "/^coloraxis([2-9]|[1-9][0-9]+)?$/"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scatter.marker.line", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, anim=kwargs.pop("anim", True), array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), colorscale_path=kwargs.pop( "colorscale_path", "scatter.marker.line.colorscale" ), **kwargs ) import _plotly_utils.basevalidators class CminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmin", parent_name="scatter.marker.line", **kwargs): super(CminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmidValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmid", parent_name="scatter.marker.line", **kwargs): super(CmidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmax", parent_name="scatter.marker.line", **kwargs): super(CmaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CautoValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="cauto", parent_name="scatter.marker.line", **kwargs ): super(CautoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AutocolorscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="autocolorscale", parent_name="scatter.marker.line", **kwargs ): super(AutocolorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatter/stream/0000755000175000017500000000000013573746614022724 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatter/stream/__init__.py0000644000175000017500000000206413573721542025030 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TokenValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="token", parent_name="scatter.stream", **kwargs): super(TokenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "info"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class MaxpointsValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="maxpoints", parent_name="scatter.stream", **kwargs): super(MaxpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 10000), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatter/__init__.py0000644000175000017500000013461213573721543023543 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="ysrc", parent_name="scatter", **kwargs): super(YsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YcalendarValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="ycalendar", parent_name="scatter", **kwargs): super(YcalendarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "gregorian", "chinese", "coptic", "discworld", "ethiopian", "hebrew", "islamic", "julian", "mayan", "nanakshahi", "nepali", "persian", "jalali", "taiwan", "thai", "ummalqura", ], ), **kwargs ) import _plotly_utils.basevalidators class YAxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="yaxis", parent_name="scatter", **kwargs): super(YAxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "y"), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class Y0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="y0", parent_name="scatter", **kwargs): super(Y0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, anim=kwargs.pop("anim", True), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="y", parent_name="scatter", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, anim=kwargs.pop("anim", True), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class XsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="xsrc", parent_name="scatter", **kwargs): super(XsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XcalendarValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="xcalendar", parent_name="scatter", **kwargs): super(XcalendarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "gregorian", "chinese", "coptic", "discworld", "ethiopian", "hebrew", "islamic", "julian", "mayan", "nanakshahi", "nepali", "persian", "jalali", "taiwan", "thai", "ummalqura", ], ), **kwargs ) import _plotly_utils.basevalidators class XAxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="xaxis", parent_name="scatter", **kwargs): super(XAxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "x"), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class X0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="x0", parent_name="scatter", **kwargs): super(X0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, anim=kwargs.pop("anim", True), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="x", parent_name="scatter", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, anim=kwargs.pop("anim", True), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="visible", parent_name="scatter", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "legendonly"]), **kwargs ) import _plotly_utils.basevalidators class UnselectedValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="unselected", parent_name="scatter", **kwargs): super(UnselectedValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Unselected"), data_docs=kwargs.pop( "data_docs", """ marker plotly.graph_objects.scatter.unselected.Marker instance or dict with compatible properties textfont plotly.graph_objects.scatter.unselected.Textfon t instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="scatter", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UidValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="uid", parent_name="scatter", **kwargs): super(UidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, anim=kwargs.pop("anim", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="tsrc", parent_name="scatter", **kwargs): super(TsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TexttemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="texttemplatesrc", parent_name="scatter", **kwargs): super(TexttemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TexttemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="texttemplate", parent_name="scatter", **kwargs): super(TexttemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="textsrc", parent_name="scatter", **kwargs): super(TextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextpositionsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="textpositionsrc", parent_name="scatter", **kwargs): super(TextpositionsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextpositionValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="textposition", parent_name="scatter", **kwargs): super(TextpositionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", [ "top left", "top center", "top right", "middle left", "middle center", "middle right", "bottom left", "bottom center", "bottom right", ], ), **kwargs ) import _plotly_utils.basevalidators class TextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="textfont", parent_name="scatter", **kwargs): super(TextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Textfont"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="text", parent_name="scatter", **kwargs): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="t", parent_name="scatter", **kwargs): super(TValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class StreamValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="stream", parent_name="scatter", **kwargs): super(StreamValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Stream"), data_docs=kwargs.pop( "data_docs", """ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """, ), **kwargs ) import _plotly_utils.basevalidators class StackgroupValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="stackgroup", parent_name="scatter", **kwargs): super(StackgroupValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class StackgapsValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="stackgaps", parent_name="scatter", **kwargs): super(StackgapsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["infer zero", "interpolate"]), **kwargs ) import _plotly_utils.basevalidators class ShowlegendValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showlegend", parent_name="scatter", **kwargs): super(ShowlegendValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SelectedpointsValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="selectedpoints", parent_name="scatter", **kwargs): super(SelectedpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SelectedValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="selected", parent_name="scatter", **kwargs): super(SelectedValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Selected"), data_docs=kwargs.pop( "data_docs", """ marker plotly.graph_objects.scatter.selected.Marker instance or dict with compatible properties textfont plotly.graph_objects.scatter.selected.Textfont instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class RsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="rsrc", parent_name="scatter", **kwargs): super(RsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class RValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="r", parent_name="scatter", **kwargs): super(RValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class OrientationValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="orientation", parent_name="scatter", **kwargs): super(OrientationValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["v", "h"]), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="scatter", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="scatter", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ModeValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="mode", parent_name="scatter", **kwargs): super(ModeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), extras=kwargs.pop("extras", ["none"]), flags=kwargs.pop("flags", ["lines", "markers", "text"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="metasrc", parent_name="scatter", **kwargs): super(MetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetaValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="meta", parent_name="scatter", **kwargs): super(MetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="marker", parent_name="scatter", **kwargs): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.scatter.marker.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . gradient plotly.graph_objects.scatter.marker.Gradient instance or dict with compatible properties line plotly.graph_objects.scatter.marker.Line instance or dict with compatible properties maxdisplayed Sets a maximum number of points to be drawn on the graph. 0 corresponds to no limit. opacity Sets the marker opacity. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. size Sets the marker size (in px). sizemin Has an effect only if `marker.size` is set to a numerical array. Sets the minimum size (in px) of the rendered marker points. sizemode Has an effect only if `marker.size` is set to a numerical array. Sets the rule for which the data in `size` is converted to pixels. sizeref Has an effect only if `marker.size` is set to a numerical array. Sets the scale factor used to determine the rendered size of marker points. Use with `sizemin` and `sizemode`. sizesrc Sets the source reference on plot.ly for size . symbol Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot- open" to a symbol name. symbolsrc Sets the source reference on plot.ly for symbol . """, ), **kwargs ) import _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="line", parent_name="scatter", **kwargs): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ color Sets the line color. dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). shape Determines the line shape. With "spline" the lines are drawn using spline interpolation. The other available values correspond to step-wise line shapes. simplify Simplifies lines by removing nearly-collinear points. When transitioning lines, it may be desirable to disable this so that the number of points along the resulting SVG path is unaffected. smoothing Has an effect only if `shape` is set to "spline" Sets the amount of smoothing. 0 corresponds to no smoothing (equivalent to a "linear" shape). width Sets the line width (in px). """, ), **kwargs ) import _plotly_utils.basevalidators class LegendgroupValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="legendgroup", parent_name="scatter", **kwargs): super(LegendgroupValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="idssrc", parent_name="scatter", **kwargs): super(IdssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ids", parent_name="scatter", **kwargs): super(IdsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, anim=kwargs.pop("anim", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class HovertextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hovertextsrc", parent_name="scatter", **kwargs): super(HovertextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertext", parent_name="scatter", **kwargs): super(HovertextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hovertemplatesrc", parent_name="scatter", **kwargs): super(HovertemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertemplate", parent_name="scatter", **kwargs): super(HovertemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoveronValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="hoveron", parent_name="scatter", **kwargs): super(HoveronValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), flags=kwargs.pop("flags", ["points", "fills"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverlabelValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="hoverlabel", parent_name="scatter", **kwargs): super(HoverlabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Hoverlabel"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """, ), **kwargs ) import _plotly_utils.basevalidators class HoverinfosrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hoverinfosrc", parent_name="scatter", **kwargs): super(HoverinfosrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverinfoValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="hoverinfo", parent_name="scatter", **kwargs): super(HoverinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), extras=kwargs.pop("extras", ["all", "none", "skip"]), flags=kwargs.pop("flags", ["x", "y", "z", "text", "name"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class GroupnormValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="groupnorm", parent_name="scatter", **kwargs): super(GroupnormValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["", "fraction", "percent"]), **kwargs ) import _plotly_utils.basevalidators class FillcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="fillcolor", parent_name="scatter", **kwargs): super(FillcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, anim=kwargs.pop("anim", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FillValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="fill", parent_name="scatter", **kwargs): super(FillValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", [ "none", "tozeroy", "tozerox", "tonexty", "tonextx", "toself", "tonext", ], ), **kwargs ) import _plotly_utils.basevalidators class ErrorYValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="error_y", parent_name="scatter", **kwargs): super(ErrorYValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "ErrorY"), data_docs=kwargs.pop( "data_docs", """ array Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. arrayminus Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. arrayminussrc Sets the source reference on plot.ly for arrayminus . arraysrc Sets the source reference on plot.ly for array . color Sets the stoke color of the error bars. symmetric Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. thickness Sets the thickness (in px) of the error bars. traceref tracerefminus type Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. value Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. valueminus Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars visible Determines whether or not this set of error bars is visible. width Sets the width (in px) of the cross-bar at both ends of the error bars. """, ), **kwargs ) import _plotly_utils.basevalidators class ErrorXValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="error_x", parent_name="scatter", **kwargs): super(ErrorXValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "ErrorX"), data_docs=kwargs.pop( "data_docs", """ array Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. arrayminus Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. arrayminussrc Sets the source reference on plot.ly for arrayminus . arraysrc Sets the source reference on plot.ly for array . color Sets the stoke color of the error bars. copy_ystyle symmetric Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. thickness Sets the thickness (in px) of the error bars. traceref tracerefminus type Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. value Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. valueminus Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars visible Determines whether or not this set of error bars is visible. width Sets the width (in px) of the cross-bar at both ends of the error bars. """, ), **kwargs ) import _plotly_utils.basevalidators class DyValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="dy", parent_name="scatter", **kwargs): super(DyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, anim=kwargs.pop("anim", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="dx", parent_name="scatter", **kwargs): super(DxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, anim=kwargs.pop("anim", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdatasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="customdatasrc", parent_name="scatter", **kwargs): super(CustomdatasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdataValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="customdata", parent_name="scatter", **kwargs): super(CustomdataValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class ConnectgapsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="connectgaps", parent_name="scatter", **kwargs): super(ConnectgapsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CliponaxisValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="cliponaxis", parent_name="scatter", **kwargs): super(CliponaxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatter/line/0000755000175000017500000000000013573746614022360 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatter/line/__init__.py0000644000175000017500000000604013573721542024462 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="scatter.line", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, anim=kwargs.pop("anim", True), edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SmoothingValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="smoothing", parent_name="scatter.line", **kwargs): super(SmoothingValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), max=kwargs.pop("max", 1.3), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SimplifyValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="simplify", parent_name="scatter.line", **kwargs): super(SimplifyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ShapeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="shape", parent_name="scatter.line", **kwargs): super(ShapeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["linear", "spline", "hv", "vh", "hvh", "vhv"]), **kwargs ) import _plotly_utils.basevalidators class DashValidator(_plotly_utils.basevalidators.DashValidator): def __init__(self, plotly_name="dash", parent_name="scatter.line", **kwargs): super(DashValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", ["solid", "dot", "dash", "longdash", "dashdot", "longdashdot"] ), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="scatter.line", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, anim=kwargs.pop("anim", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatter/selected/0000755000175000017500000000000013573746614023221 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatter/selected/textfont/0000755000175000017500000000000013573746614025074 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatter/selected/textfont/__init__.py0000644000175000017500000000072413573721542027201 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scatter.selected.textfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatter/selected/marker/0000755000175000017500000000000013573746614024502 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatter/selected/marker/__init__.py0000644000175000017500000000276113573721542026612 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scatter.selected.marker", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="opacity", parent_name="scatter.selected.marker", **kwargs ): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scatter.selected.marker", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatter/selected/__init__.py0000644000175000017500000000253313573721542025326 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="textfont", parent_name="scatter.selected", **kwargs ): super(TextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Textfont"), data_docs=kwargs.pop( "data_docs", """ color Sets the text font color of selected points. """, ), **kwargs ) import _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="marker", parent_name="scatter.selected", **kwargs): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. size Sets the marker size of selected points. """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/heatmapgl/0000755000175000017500000000000013573746614021726 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/heatmapgl/hoverlabel/0000755000175000017500000000000013573746614024051 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/heatmapgl/hoverlabel/__init__.py0000644000175000017500000001346113573721537026164 0ustar noahfxnoahfximport _plotly_utils.basevalidators class NamelengthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="namelengthsrc", parent_name="heatmapgl.hoverlabel", **kwargs ): super(NamelengthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NamelengthValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="namelength", parent_name="heatmapgl.hoverlabel", **kwargs ): super(NamelengthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", -1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="heatmapgl.hoverlabel", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class BordercolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bordercolorsrc", parent_name="heatmapgl.hoverlabel", **kwargs ): super(BordercolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="heatmapgl.hoverlabel", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bgcolorsrc", parent_name="heatmapgl.hoverlabel", **kwargs ): super(BgcolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="heatmapgl.hoverlabel", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AlignsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="alignsrc", parent_name="heatmapgl.hoverlabel", **kwargs ): super(AlignsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="align", parent_name="heatmapgl.hoverlabel", **kwargs ): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "right", "auto"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/heatmapgl/hoverlabel/font/0000755000175000017500000000000013573746614025017 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/heatmapgl/hoverlabel/font/__init__.py0000644000175000017500000000606113573721537027130 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="heatmapgl.hoverlabel.font", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="heatmapgl.hoverlabel.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="heatmapgl.hoverlabel.font", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="heatmapgl.hoverlabel.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="heatmapgl.hoverlabel.font", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="heatmapgl.hoverlabel.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/heatmapgl/colorbar/0000755000175000017500000000000013573746614023531 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/heatmapgl/colorbar/tickformatstop/0000755000175000017500000000000013573746614026602 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/heatmapgl/colorbar/tickformatstop/__init__.py0000644000175000017500000000534313573721537030715 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="value", parent_name="heatmapgl.colorbar.tickformatstop", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="heatmapgl.colorbar.tickformatstop", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="heatmapgl.colorbar.tickformatstop", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EnabledValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="enabled", parent_name="heatmapgl.colorbar.tickformatstop", **kwargs ): super(EnabledValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DtickrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="dtickrange", parent_name="heatmapgl.colorbar.tickformatstop", **kwargs ): super(DtickrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "calc"}, {"valType": "any", "editType": "calc"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/heatmapgl/colorbar/title/0000755000175000017500000000000013573746614024652 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/heatmapgl/colorbar/title/__init__.py0000644000175000017500000000471113573721537026763 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="text", parent_name="heatmapgl.colorbar.title", **kwargs ): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SideValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="side", parent_name="heatmapgl.colorbar.title", **kwargs ): super(SideValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["right", "top", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="heatmapgl.colorbar.title", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/heatmapgl/colorbar/title/font/0000755000175000017500000000000013573746614025620 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/heatmapgl/colorbar/title/font/__init__.py0000644000175000017500000000305313573721537027727 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="heatmapgl.colorbar.title.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="heatmapgl.colorbar.title.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="heatmapgl.colorbar.title.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/heatmapgl/colorbar/__init__.py0000644000175000017500000005775613573721540025655 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="ypad", parent_name="heatmapgl.colorbar", **kwargs): super(YpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class YanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="yanchor", parent_name="heatmapgl.colorbar", **kwargs ): super(YanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["top", "middle", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="y", parent_name="heatmapgl.colorbar", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="xpad", parent_name="heatmapgl.colorbar", **kwargs): super(XpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="xanchor", parent_name="heatmapgl.colorbar", **kwargs ): super(XanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "center", "right"]), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="x", parent_name="heatmapgl.colorbar", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TitleValidator(_plotly_utils.basevalidators.TitleValidator): def __init__(self, plotly_name="title", parent_name="heatmapgl.colorbar", **kwargs): super(TitleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Title"), data_docs=kwargs.pop( "data_docs", """ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """, ), **kwargs ) import _plotly_utils.basevalidators class TickwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="tickwidth", parent_name="heatmapgl.colorbar", **kwargs ): super(TickwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickvalssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="tickvalssrc", parent_name="heatmapgl.colorbar", **kwargs ): super(TickvalssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickvalsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="tickvals", parent_name="heatmapgl.colorbar", **kwargs ): super(TickvalsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="ticktextsrc", parent_name="heatmapgl.colorbar", **kwargs ): super(TicktextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicktextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="ticktext", parent_name="heatmapgl.colorbar", **kwargs ): super(TicktextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="ticksuffix", parent_name="heatmapgl.colorbar", **kwargs ): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TicksValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="ticks", parent_name="heatmapgl.colorbar", **kwargs): super(TicksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["outside", "inside", ""]), **kwargs ) import _plotly_utils.basevalidators class TickprefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickprefix", parent_name="heatmapgl.colorbar", **kwargs ): super(TickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="tickmode", parent_name="heatmapgl.colorbar", **kwargs ): super(TickmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "linear", "array"]), **kwargs ) import _plotly_utils.basevalidators class TicklenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ticklen", parent_name="heatmapgl.colorbar", **kwargs ): super(TicklenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickformatstopValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickformatstopdefaults", parent_name="heatmapgl.colorbar", **kwargs ): super(TickformatstopValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatstopsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="tickformatstops", parent_name="heatmapgl.colorbar", **kwargs ): super(TickformatstopsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickformat", parent_name="heatmapgl.colorbar", **kwargs ): super(TickformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickfont", parent_name="heatmapgl.colorbar", **kwargs ): super(TickfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class TickcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="tickcolor", parent_name="heatmapgl.colorbar", **kwargs ): super(TickcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__( self, plotly_name="tickangle", parent_name="heatmapgl.colorbar", **kwargs ): super(TickangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="tick0", parent_name="heatmapgl.colorbar", **kwargs): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ThicknessmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="thicknessmode", parent_name="heatmapgl.colorbar", **kwargs ): super(ThicknessmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="thickness", parent_name="heatmapgl.colorbar", **kwargs ): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowticksuffixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showticksuffix", parent_name="heatmapgl.colorbar", **kwargs ): super(ShowticksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowtickprefixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showtickprefix", parent_name="heatmapgl.colorbar", **kwargs ): super(ShowtickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowticklabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showticklabels", parent_name="heatmapgl.colorbar", **kwargs ): super(ShowticklabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowexponentValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showexponent", parent_name="heatmapgl.colorbar", **kwargs ): super(ShowexponentValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class SeparatethousandsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="separatethousands", parent_name="heatmapgl.colorbar", **kwargs ): super(SeparatethousandsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="outlinewidth", parent_name="heatmapgl.colorbar", **kwargs ): super(OutlinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="outlinecolor", parent_name="heatmapgl.colorbar", **kwargs ): super(OutlinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NticksValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="nticks", parent_name="heatmapgl.colorbar", **kwargs ): super(NticksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LenmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="lenmode", parent_name="heatmapgl.colorbar", **kwargs ): super(LenmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class LenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="len", parent_name="heatmapgl.colorbar", **kwargs): super(LenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ExponentformatValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="exponentformat", parent_name="heatmapgl.colorbar", **kwargs ): super(ExponentformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "e", "E", "power", "SI", "B"]), **kwargs ) import _plotly_utils.basevalidators class DtickValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="dtick", parent_name="heatmapgl.colorbar", **kwargs): super(DtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BorderwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="borderwidth", parent_name="heatmapgl.colorbar", **kwargs ): super(BorderwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="heatmapgl.colorbar", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="heatmapgl.colorbar", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/heatmapgl/colorbar/tickfont/0000755000175000017500000000000013573746614025352 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/heatmapgl/colorbar/tickfont/__init__.py0000644000175000017500000000301513573721537027457 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="heatmapgl.colorbar.tickfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="heatmapgl.colorbar.tickfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="heatmapgl.colorbar.tickfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/heatmapgl/stream/0000755000175000017500000000000013573746614023221 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/heatmapgl/stream/__init__.py0000644000175000017500000000210613573721537025326 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TokenValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="token", parent_name="heatmapgl.stream", **kwargs): super(TokenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "info"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class MaxpointsValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="maxpoints", parent_name="heatmapgl.stream", **kwargs ): super(MaxpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 10000), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/heatmapgl/__init__.py0000644000175000017500000007742613573721540024046 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ZsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="zsrc", parent_name="heatmapgl", **kwargs): super(ZsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="zmin", parent_name="heatmapgl", **kwargs): super(ZminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"zauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZmidValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="zmid", parent_name="heatmapgl", **kwargs): super(ZmidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZmaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="zmax", parent_name="heatmapgl", **kwargs): super(ZmaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"zauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZautoValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="zauto", parent_name="heatmapgl", **kwargs): super(ZautoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="z", parent_name="heatmapgl", **kwargs): super(ZValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class YtypeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="ytype", parent_name="heatmapgl", **kwargs): super(YtypeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["array", "scaled"]), **kwargs ) import _plotly_utils.basevalidators class YsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="ysrc", parent_name="heatmapgl", **kwargs): super(YsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YAxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="yaxis", parent_name="heatmapgl", **kwargs): super(YAxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "y"), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class Y0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="y0", parent_name="heatmapgl", **kwargs): super(Y0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"ytype": "scaled"}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="y", parent_name="heatmapgl", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"ytype": "array"}), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class XtypeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="xtype", parent_name="heatmapgl", **kwargs): super(XtypeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["array", "scaled"]), **kwargs ) import _plotly_utils.basevalidators class XsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="xsrc", parent_name="heatmapgl", **kwargs): super(XsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XAxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="xaxis", parent_name="heatmapgl", **kwargs): super(XAxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "x"), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class X0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="x0", parent_name="heatmapgl", **kwargs): super(X0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"xtype": "scaled"}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="x", parent_name="heatmapgl", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"xtype": "array"}), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="visible", parent_name="heatmapgl", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "legendonly"]), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="heatmapgl", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UidValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="uid", parent_name="heatmapgl", **kwargs): super(UidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TransposeValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="transpose", parent_name="heatmapgl", **kwargs): super(TransposeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="textsrc", parent_name="heatmapgl", **kwargs): super(TextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="text", parent_name="heatmapgl", **kwargs): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class StreamValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="stream", parent_name="heatmapgl", **kwargs): super(StreamValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Stream"), data_docs=kwargs.pop( "data_docs", """ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """, ), **kwargs ) import _plotly_utils.basevalidators class ShowscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showscale", parent_name="heatmapgl", **kwargs): super(ShowscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ReversescaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="reversescale", parent_name="heatmapgl", **kwargs): super(ReversescaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="heatmapgl", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="heatmapgl", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="metasrc", parent_name="heatmapgl", **kwargs): super(MetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetaValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="meta", parent_name="heatmapgl", **kwargs): super(MetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="idssrc", parent_name="heatmapgl", **kwargs): super(IdssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ids", parent_name="heatmapgl", **kwargs): super(IdsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class HoverlabelValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="hoverlabel", parent_name="heatmapgl", **kwargs): super(HoverlabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Hoverlabel"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """, ), **kwargs ) import _plotly_utils.basevalidators class HoverinfosrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hoverinfosrc", parent_name="heatmapgl", **kwargs): super(HoverinfosrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverinfoValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="hoverinfo", parent_name="heatmapgl", **kwargs): super(HoverinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), extras=kwargs.pop("extras", ["all", "none", "skip"]), flags=kwargs.pop("flags", ["x", "y", "z", "text", "name"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DyValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="dy", parent_name="heatmapgl", **kwargs): super(DyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"ytype": "scaled"}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="dx", parent_name="heatmapgl", **kwargs): super(DxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"xtype": "scaled"}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdatasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="customdatasrc", parent_name="heatmapgl", **kwargs): super(CustomdatasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdataValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="customdata", parent_name="heatmapgl", **kwargs): super(CustomdataValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__(self, plotly_name="colorscale", parent_name="heatmapgl", **kwargs): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"autocolorscale": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorBarValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="colorbar", parent_name="heatmapgl", **kwargs): super(ColorBarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "ColorBar"), data_docs=kwargs.pop( "data_docs", """ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.heatmapgl.color bar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.heatmapgl.colorbar.tickformatstopdefaults), sets the default property values to use for elements of heatmapgl.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.heatmapgl.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use heatmapgl.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use heatmapgl.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """, ), **kwargs ) import _plotly_utils.basevalidators class ColoraxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="coloraxis", parent_name="heatmapgl", **kwargs): super(ColoraxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", None), edit_type=kwargs.pop("edit_type", "calc"), regex=kwargs.pop("regex", "/^coloraxis([2-9]|[1-9][0-9]+)?$/"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AutocolorscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="autocolorscale", parent_name="heatmapgl", **kwargs): super(AutocolorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/violin/0000755000175000017500000000000013573746614021264 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/violin/meanline/0000755000175000017500000000000013573746614023054 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/violin/meanline/__init__.py0000644000175000017500000000254513573721544025166 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="violin.meanline", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="visible", parent_name="violin.meanline", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="violin.meanline", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/violin/unselected/0000755000175000017500000000000013573746614023417 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/violin/unselected/marker/0000755000175000017500000000000013573746614024700 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/violin/unselected/marker/__init__.py0000644000175000017500000000276413573721544027015 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="violin.unselected.marker", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="opacity", parent_name="violin.unselected.marker", **kwargs ): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="violin.unselected.marker", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/violin/unselected/__init__.py0000644000175000017500000000162613573721544025530 0ustar noahfxnoahfximport _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="marker", parent_name="violin.unselected", **kwargs): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. size Sets the marker size of unselected points, applied only when a selection exists. """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/violin/hoverlabel/0000755000175000017500000000000013573746614023407 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/violin/hoverlabel/__init__.py0000644000175000017500000001337213573721544025521 0ustar noahfxnoahfximport _plotly_utils.basevalidators class NamelengthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="namelengthsrc", parent_name="violin.hoverlabel", **kwargs ): super(NamelengthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NamelengthValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="namelength", parent_name="violin.hoverlabel", **kwargs ): super(NamelengthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", -1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="font", parent_name="violin.hoverlabel", **kwargs): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class BordercolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bordercolorsrc", parent_name="violin.hoverlabel", **kwargs ): super(BordercolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="violin.hoverlabel", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bgcolorsrc", parent_name="violin.hoverlabel", **kwargs ): super(BgcolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="violin.hoverlabel", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AlignsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="alignsrc", parent_name="violin.hoverlabel", **kwargs ): super(AlignsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="align", parent_name="violin.hoverlabel", **kwargs): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "right", "auto"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/violin/hoverlabel/font/0000755000175000017500000000000013573746614024355 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/violin/hoverlabel/font/__init__.py0000644000175000017500000000603713573721544026467 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="violin.hoverlabel.font", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="violin.hoverlabel.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="violin.hoverlabel.font", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="violin.hoverlabel.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="violin.hoverlabel.font", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="violin.hoverlabel.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/violin/marker/0000755000175000017500000000000013573746614022545 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/violin/marker/__init__.py0000644000175000017500000003061313573721544024654 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SymbolValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="symbol", parent_name="violin.marker", **kwargs): super(SymbolValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", False), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", [ 0, "circle", 100, "circle-open", 200, "circle-dot", 300, "circle-open-dot", 1, "square", 101, "square-open", 201, "square-dot", 301, "square-open-dot", 2, "diamond", 102, "diamond-open", 202, "diamond-dot", 302, "diamond-open-dot", 3, "cross", 103, "cross-open", 203, "cross-dot", 303, "cross-open-dot", 4, "x", 104, "x-open", 204, "x-dot", 304, "x-open-dot", 5, "triangle-up", 105, "triangle-up-open", 205, "triangle-up-dot", 305, "triangle-up-open-dot", 6, "triangle-down", 106, "triangle-down-open", 206, "triangle-down-dot", 306, "triangle-down-open-dot", 7, "triangle-left", 107, "triangle-left-open", 207, "triangle-left-dot", 307, "triangle-left-open-dot", 8, "triangle-right", 108, "triangle-right-open", 208, "triangle-right-dot", 308, "triangle-right-open-dot", 9, "triangle-ne", 109, "triangle-ne-open", 209, "triangle-ne-dot", 309, "triangle-ne-open-dot", 10, "triangle-se", 110, "triangle-se-open", 210, "triangle-se-dot", 310, "triangle-se-open-dot", 11, "triangle-sw", 111, "triangle-sw-open", 211, "triangle-sw-dot", 311, "triangle-sw-open-dot", 12, "triangle-nw", 112, "triangle-nw-open", 212, "triangle-nw-dot", 312, "triangle-nw-open-dot", 13, "pentagon", 113, "pentagon-open", 213, "pentagon-dot", 313, "pentagon-open-dot", 14, "hexagon", 114, "hexagon-open", 214, "hexagon-dot", 314, "hexagon-open-dot", 15, "hexagon2", 115, "hexagon2-open", 215, "hexagon2-dot", 315, "hexagon2-open-dot", 16, "octagon", 116, "octagon-open", 216, "octagon-dot", 316, "octagon-open-dot", 17, "star", 117, "star-open", 217, "star-dot", 317, "star-open-dot", 18, "hexagram", 118, "hexagram-open", 218, "hexagram-dot", 318, "hexagram-open-dot", 19, "star-triangle-up", 119, "star-triangle-up-open", 219, "star-triangle-up-dot", 319, "star-triangle-up-open-dot", 20, "star-triangle-down", 120, "star-triangle-down-open", 220, "star-triangle-down-dot", 320, "star-triangle-down-open-dot", 21, "star-square", 121, "star-square-open", 221, "star-square-dot", 321, "star-square-open-dot", 22, "star-diamond", 122, "star-diamond-open", 222, "star-diamond-dot", 322, "star-diamond-open-dot", 23, "diamond-tall", 123, "diamond-tall-open", 223, "diamond-tall-dot", 323, "diamond-tall-open-dot", 24, "diamond-wide", 124, "diamond-wide-open", 224, "diamond-wide-dot", 324, "diamond-wide-open-dot", 25, "hourglass", 125, "hourglass-open", 26, "bowtie", 126, "bowtie-open", 27, "circle-cross", 127, "circle-cross-open", 28, "circle-x", 128, "circle-x-open", 29, "square-cross", 129, "square-cross-open", 30, "square-x", 130, "square-x-open", 31, "diamond-cross", 131, "diamond-cross-open", 32, "diamond-x", 132, "diamond-x-open", 33, "cross-thin", 133, "cross-thin-open", 34, "x-thin", 134, "x-thin-open", 35, "asterisk", 135, "asterisk-open", 36, "hash", 136, "hash-open", 236, "hash-dot", 336, "hash-open-dot", 37, "y-up", 137, "y-up-open", 38, "y-down", 138, "y-down-open", 39, "y-left", 139, "y-left-open", 40, "y-right", 140, "y-right-open", 41, "line-ew", 141, "line-ew-open", 42, "line-ns", 142, "line-ns-open", 43, "line-ne", 143, "line-ne-open", 44, "line-nw", 144, "line-nw-open", ], ), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="size", parent_name="violin.marker", **kwargs): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", False), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutliercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="outliercolor", parent_name="violin.marker", **kwargs ): super(OutliercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="violin.marker", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", False), edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="line", parent_name="violin.marker", **kwargs): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. outliercolor Sets the border line color of the outlier sample points. Defaults to marker.color outlierwidth Sets the border line width (in px) of the outlier sample points. width Sets the width (in px) of the lines bounding the marker points. """, ), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="violin.marker", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", False), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/violin/marker/line/0000755000175000017500000000000013573746614023474 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/violin/marker/line/__init__.py0000644000175000017500000000377613573721544025615 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="violin.marker.line", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", False), edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlierwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="outlierwidth", parent_name="violin.marker.line", **kwargs ): super(OutlierwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutliercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="outliercolor", parent_name="violin.marker.line", **kwargs ): super(OutliercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="violin.marker.line", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", False), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/violin/stream/0000755000175000017500000000000013573746614022557 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/violin/stream/__init__.py0000644000175000017500000000206213573721544024663 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TokenValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="token", parent_name="violin.stream", **kwargs): super(TokenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "info"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class MaxpointsValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="maxpoints", parent_name="violin.stream", **kwargs): super(MaxpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 10000), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/violin/__init__.py0000644000175000017500000007272713573721545023410 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="ysrc", parent_name="violin", **kwargs): super(YsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YAxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="yaxis", parent_name="violin", **kwargs): super(YAxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "y"), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class Y0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="y0", parent_name="violin", **kwargs): super(Y0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="y", parent_name="violin", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class XsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="xsrc", parent_name="violin", **kwargs): super(XsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XAxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="xaxis", parent_name="violin", **kwargs): super(XAxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "x"), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class X0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="x0", parent_name="violin", **kwargs): super(X0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="x", parent_name="violin", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="violin", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="visible", parent_name="violin", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "legendonly"]), **kwargs ) import _plotly_utils.basevalidators class UnselectedValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="unselected", parent_name="violin", **kwargs): super(UnselectedValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Unselected"), data_docs=kwargs.pop( "data_docs", """ marker plotly.graph_objects.violin.unselected.Marker instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="violin", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UidValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="uid", parent_name="violin", **kwargs): super(UidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="textsrc", parent_name="violin", **kwargs): super(TextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="text", parent_name="violin", **kwargs): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class StreamValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="stream", parent_name="violin", **kwargs): super(StreamValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Stream"), data_docs=kwargs.pop( "data_docs", """ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """, ), **kwargs ) import _plotly_utils.basevalidators class SpanmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="spanmode", parent_name="violin", **kwargs): super(SpanmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["soft", "hard", "manual"]), **kwargs ) import _plotly_utils.basevalidators class SpanValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="span", parent_name="violin", **kwargs): super(SpanValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "calc"}, {"valType": "any", "editType": "calc"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SideValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="side", parent_name="violin", **kwargs): super(SideValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["both", "positive", "negative"]), **kwargs ) import _plotly_utils.basevalidators class ShowlegendValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showlegend", parent_name="violin", **kwargs): super(ShowlegendValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SelectedpointsValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="selectedpoints", parent_name="violin", **kwargs): super(SelectedpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SelectedValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="selected", parent_name="violin", **kwargs): super(SelectedValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Selected"), data_docs=kwargs.pop( "data_docs", """ marker plotly.graph_objects.violin.selected.Marker instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class ScalemodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="scalemode", parent_name="violin", **kwargs): super(ScalemodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["width", "count"]), **kwargs ) import _plotly_utils.basevalidators class ScalegroupValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="scalegroup", parent_name="violin", **kwargs): super(ScalegroupValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class PointsValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="points", parent_name="violin", **kwargs): super(PointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", ["all", "outliers", "suspectedoutliers", False] ), **kwargs ) import _plotly_utils.basevalidators class PointposValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="pointpos", parent_name="violin", **kwargs): super(PointposValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 2), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OrientationValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="orientation", parent_name="violin", **kwargs): super(OrientationValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["v", "h"]), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="violin", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OffsetgroupValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="offsetgroup", parent_name="violin", **kwargs): super(OffsetgroupValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="violin", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="metasrc", parent_name="violin", **kwargs): super(MetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetaValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="meta", parent_name="violin", **kwargs): super(MetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MeanlineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="meanline", parent_name="violin", **kwargs): super(MeanlineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Meanline"), data_docs=kwargs.pop( "data_docs", """ color Sets the mean line color. visible Determines if a line corresponding to the sample's mean is shown inside the violins. If `box.visible` is turned on, the mean line is drawn inside the inner box. Otherwise, the mean line is drawn from one side of the violin to other. width Sets the mean line width. """, ), **kwargs ) import _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="marker", parent_name="violin", **kwargs): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. line plotly.graph_objects.violin.marker.Line instance or dict with compatible properties opacity Sets the marker opacity. outliercolor Sets the color of the outlier sample points. size Sets the marker size (in px). symbol Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot- open" to a symbol name. """, ), **kwargs ) import _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="line", parent_name="violin", **kwargs): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ color Sets the color of line bounding the violin(s). width Sets the width (in px) of line bounding the violin(s). """, ), **kwargs ) import _plotly_utils.basevalidators class LegendgroupValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="legendgroup", parent_name="violin", **kwargs): super(LegendgroupValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class JitterValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="jitter", parent_name="violin", **kwargs): super(JitterValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class IdssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="idssrc", parent_name="violin", **kwargs): super(IdssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ids", parent_name="violin", **kwargs): super(IdsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class HovertextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hovertextsrc", parent_name="violin", **kwargs): super(HovertextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertext", parent_name="violin", **kwargs): super(HovertextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hovertemplatesrc", parent_name="violin", **kwargs): super(HovertemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertemplate", parent_name="violin", **kwargs): super(HovertemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoveronValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="hoveron", parent_name="violin", **kwargs): super(HoveronValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), extras=kwargs.pop("extras", ["all"]), flags=kwargs.pop("flags", ["violins", "points", "kde"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverlabelValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="hoverlabel", parent_name="violin", **kwargs): super(HoverlabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Hoverlabel"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """, ), **kwargs ) import _plotly_utils.basevalidators class HoverinfosrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hoverinfosrc", parent_name="violin", **kwargs): super(HoverinfosrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverinfoValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="hoverinfo", parent_name="violin", **kwargs): super(HoverinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), extras=kwargs.pop("extras", ["all", "none", "skip"]), flags=kwargs.pop("flags", ["x", "y", "z", "text", "name"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FillcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="fillcolor", parent_name="violin", **kwargs): super(FillcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class CustomdatasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="customdatasrc", parent_name="violin", **kwargs): super(CustomdatasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdataValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="customdata", parent_name="violin", **kwargs): super(CustomdataValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class BoxValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="box", parent_name="violin", **kwargs): super(BoxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Box"), data_docs=kwargs.pop( "data_docs", """ fillcolor Sets the inner box plot fill color. line plotly.graph_objects.violin.box.Line instance or dict with compatible properties visible Determines if an miniature box plot is drawn inside the violins. width Sets the width of the inner box plots relative to the violins' width. For example, with 1, the inner box plots are as wide as the violins. """, ), **kwargs ) import _plotly_utils.basevalidators class BandwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="bandwidth", parent_name="violin", **kwargs): super(BandwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AlignmentgroupValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="alignmentgroup", parent_name="violin", **kwargs): super(AlignmentgroupValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/violin/line/0000755000175000017500000000000013573746614022213 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/violin/line/__init__.py0000644000175000017500000000163113573721544024320 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="violin.line", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="violin.line", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/violin/selected/0000755000175000017500000000000013573746614023054 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/violin/selected/marker/0000755000175000017500000000000013573746614024335 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/violin/selected/marker/__init__.py0000644000175000017500000000275613573721544026453 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="violin.selected.marker", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="opacity", parent_name="violin.selected.marker", **kwargs ): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="violin.selected.marker", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/violin/selected/__init__.py0000644000175000017500000000135413573721544025163 0ustar noahfxnoahfximport _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="marker", parent_name="violin.selected", **kwargs): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. size Sets the marker size of selected points. """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/violin/box/0000755000175000017500000000000013573746614022054 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/violin/box/__init__.py0000644000175000017500000000403713573721544024164 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="violin.box", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="visible", parent_name="violin.box", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="line", parent_name="violin.box", **kwargs): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ color Sets the inner box plot bounding line color. width Sets the inner box plot bounding line width. """, ), **kwargs ) import _plotly_utils.basevalidators class FillcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="fillcolor", parent_name="violin.box", **kwargs): super(FillcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/violin/box/line/0000755000175000017500000000000013573746614023003 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/violin/box/line/__init__.py0000644000175000017500000000164113573721544025111 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="violin.box.line", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="violin.box.line", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattergl/0000755000175000017500000000000013573746614021754 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattergl/unselected/0000755000175000017500000000000013573746614024107 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattergl/unselected/textfont/0000755000175000017500000000000013573746614025762 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattergl/unselected/textfont/__init__.py0000644000175000017500000000072713573721542030072 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scattergl.unselected.textfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattergl/unselected/marker/0000755000175000017500000000000013573746614025370 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattergl/unselected/marker/__init__.py0000644000175000017500000000277213573721542027502 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scattergl.unselected.marker", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="opacity", parent_name="scattergl.unselected.marker", **kwargs ): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scattergl.unselected.marker", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattergl/unselected/__init__.py0000644000175000017500000000312113573721542026206 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="textfont", parent_name="scattergl.unselected", **kwargs ): super(TextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Textfont"), data_docs=kwargs.pop( "data_docs", """ color Sets the text font color of unselected points, applied only when a selection exists. """, ), **kwargs ) import _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="marker", parent_name="scattergl.unselected", **kwargs ): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. size Sets the marker size of unselected points, applied only when a selection exists. """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattergl/textfont/0000755000175000017500000000000013573746614023627 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattergl/textfont/__init__.py0000644000175000017500000000575313573721542025743 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="scattergl.textfont", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="size", parent_name="scattergl.textfont", **kwargs): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="scattergl.textfont", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="scattergl.textfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="scattergl.textfont", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="scattergl.textfont", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattergl/error_x/0000755000175000017500000000000013573746614023434 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattergl/error_x/__init__.py0000644000175000017500000001621013573721542025536 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="scattergl.error_x", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="visible", parent_name="scattergl.error_x", **kwargs ): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ValueminusValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="valueminus", parent_name="scattergl.error_x", **kwargs ): super(ValueminusValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="value", parent_name="scattergl.error_x", **kwargs): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TypeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="type", parent_name="scattergl.error_x", **kwargs): super(TypeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["percent", "constant", "sqrt", "data"]), **kwargs ) import _plotly_utils.basevalidators class TracerefminusValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="tracerefminus", parent_name="scattergl.error_x", **kwargs ): super(TracerefminusValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TracerefValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="traceref", parent_name="scattergl.error_x", **kwargs ): super(TracerefValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="thickness", parent_name="scattergl.error_x", **kwargs ): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SymmetricValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="symmetric", parent_name="scattergl.error_x", **kwargs ): super(SymmetricValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CopyYstyleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="copy_ystyle", parent_name="scattergl.error_x", **kwargs ): super(CopyYstyleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="scattergl.error_x", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ArraysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="arraysrc", parent_name="scattergl.error_x", **kwargs ): super(ArraysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ArrayminussrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="arrayminussrc", parent_name="scattergl.error_x", **kwargs ): super(ArrayminussrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ArrayminusValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="arrayminus", parent_name="scattergl.error_x", **kwargs ): super(ArrayminusValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class ArrayValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="array", parent_name="scattergl.error_x", **kwargs): super(ArrayValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattergl/hoverlabel/0000755000175000017500000000000013573746614024077 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattergl/hoverlabel/__init__.py0000644000175000017500000001346113573721542026206 0ustar noahfxnoahfximport _plotly_utils.basevalidators class NamelengthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="namelengthsrc", parent_name="scattergl.hoverlabel", **kwargs ): super(NamelengthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NamelengthValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="namelength", parent_name="scattergl.hoverlabel", **kwargs ): super(NamelengthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", -1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="scattergl.hoverlabel", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class BordercolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bordercolorsrc", parent_name="scattergl.hoverlabel", **kwargs ): super(BordercolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="scattergl.hoverlabel", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bgcolorsrc", parent_name="scattergl.hoverlabel", **kwargs ): super(BgcolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="scattergl.hoverlabel", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AlignsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="alignsrc", parent_name="scattergl.hoverlabel", **kwargs ): super(AlignsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="align", parent_name="scattergl.hoverlabel", **kwargs ): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "right", "auto"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattergl/hoverlabel/font/0000755000175000017500000000000013573746614025045 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattergl/hoverlabel/font/__init__.py0000644000175000017500000000606113573721542027152 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="scattergl.hoverlabel.font", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scattergl.hoverlabel.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="scattergl.hoverlabel.font", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="scattergl.hoverlabel.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="scattergl.hoverlabel.font", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scattergl.hoverlabel.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattergl/error_y/0000755000175000017500000000000013573746614023435 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattergl/error_y/__init__.py0000644000175000017500000001525113573721543025544 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="scattergl.error_y", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="visible", parent_name="scattergl.error_y", **kwargs ): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ValueminusValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="valueminus", parent_name="scattergl.error_y", **kwargs ): super(ValueminusValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="value", parent_name="scattergl.error_y", **kwargs): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TypeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="type", parent_name="scattergl.error_y", **kwargs): super(TypeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["percent", "constant", "sqrt", "data"]), **kwargs ) import _plotly_utils.basevalidators class TracerefminusValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="tracerefminus", parent_name="scattergl.error_y", **kwargs ): super(TracerefminusValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TracerefValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="traceref", parent_name="scattergl.error_y", **kwargs ): super(TracerefValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="thickness", parent_name="scattergl.error_y", **kwargs ): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SymmetricValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="symmetric", parent_name="scattergl.error_y", **kwargs ): super(SymmetricValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="scattergl.error_y", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ArraysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="arraysrc", parent_name="scattergl.error_y", **kwargs ): super(ArraysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ArrayminussrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="arrayminussrc", parent_name="scattergl.error_y", **kwargs ): super(ArrayminussrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ArrayminusValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="arrayminus", parent_name="scattergl.error_y", **kwargs ): super(ArrayminusValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class ArrayValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="array", parent_name="scattergl.error_y", **kwargs): super(ArrayValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattergl/marker/0000755000175000017500000000000013573746614023235 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattergl/marker/colorbar/0000755000175000017500000000000013573746614025040 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattergl/marker/colorbar/tickformatstop/0000755000175000017500000000000013573746614030111 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattergl/marker/colorbar/tickformatstop/__init__.py0000644000175000017500000000540613573721542032220 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="value", parent_name="scattergl.marker.colorbar.tickformatstop", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="scattergl.marker.colorbar.tickformatstop", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="scattergl.marker.colorbar.tickformatstop", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EnabledValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="enabled", parent_name="scattergl.marker.colorbar.tickformatstop", **kwargs ): super(EnabledValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DtickrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="dtickrange", parent_name="scattergl.marker.colorbar.tickformatstop", **kwargs ): super(DtickrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "calc"}, {"valType": "any", "editType": "calc"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattergl/marker/colorbar/title/0000755000175000017500000000000013573746614026161 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattergl/marker/colorbar/title/__init__.py0000644000175000017500000000504613573721542030270 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="text", parent_name="scattergl.marker.colorbar.title", **kwargs ): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SideValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="side", parent_name="scattergl.marker.colorbar.title", **kwargs ): super(SideValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["right", "top", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="scattergl.marker.colorbar.title", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattergl/marker/colorbar/title/font/0000755000175000017500000000000013573746614027127 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattergl/marker/colorbar/title/font/__init__.py0000644000175000017500000000316013573721542031231 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scattergl.marker.colorbar.title.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="scattergl.marker.colorbar.title.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scattergl.marker.colorbar.title.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattergl/marker/colorbar/__init__.py0000644000175000017500000006141313573721543027150 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ypad", parent_name="scattergl.marker.colorbar", **kwargs ): super(YpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class YanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="yanchor", parent_name="scattergl.marker.colorbar", **kwargs ): super(YanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["top", "middle", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="y", parent_name="scattergl.marker.colorbar", **kwargs ): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="xpad", parent_name="scattergl.marker.colorbar", **kwargs ): super(XpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="xanchor", parent_name="scattergl.marker.colorbar", **kwargs ): super(XanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "center", "right"]), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="x", parent_name="scattergl.marker.colorbar", **kwargs ): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TitleValidator(_plotly_utils.basevalidators.TitleValidator): def __init__( self, plotly_name="title", parent_name="scattergl.marker.colorbar", **kwargs ): super(TitleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Title"), data_docs=kwargs.pop( "data_docs", """ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """, ), **kwargs ) import _plotly_utils.basevalidators class TickwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="tickwidth", parent_name="scattergl.marker.colorbar", **kwargs ): super(TickwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickvalssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="tickvalssrc", parent_name="scattergl.marker.colorbar", **kwargs ): super(TickvalssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickvalsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="tickvals", parent_name="scattergl.marker.colorbar", **kwargs ): super(TickvalsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="ticktextsrc", parent_name="scattergl.marker.colorbar", **kwargs ): super(TicktextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicktextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="ticktext", parent_name="scattergl.marker.colorbar", **kwargs ): super(TicktextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="ticksuffix", parent_name="scattergl.marker.colorbar", **kwargs ): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TicksValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="ticks", parent_name="scattergl.marker.colorbar", **kwargs ): super(TicksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["outside", "inside", ""]), **kwargs ) import _plotly_utils.basevalidators class TickprefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickprefix", parent_name="scattergl.marker.colorbar", **kwargs ): super(TickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="tickmode", parent_name="scattergl.marker.colorbar", **kwargs ): super(TickmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "linear", "array"]), **kwargs ) import _plotly_utils.basevalidators class TicklenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ticklen", parent_name="scattergl.marker.colorbar", **kwargs ): super(TicklenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickformatstopValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickformatstopdefaults", parent_name="scattergl.marker.colorbar", **kwargs ): super(TickformatstopValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatstopsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="tickformatstops", parent_name="scattergl.marker.colorbar", **kwargs ): super(TickformatstopsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickformat", parent_name="scattergl.marker.colorbar", **kwargs ): super(TickformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickfont", parent_name="scattergl.marker.colorbar", **kwargs ): super(TickfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class TickcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="tickcolor", parent_name="scattergl.marker.colorbar", **kwargs ): super(TickcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__( self, plotly_name="tickangle", parent_name="scattergl.marker.colorbar", **kwargs ): super(TickangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="tick0", parent_name="scattergl.marker.colorbar", **kwargs ): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ThicknessmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="thicknessmode", parent_name="scattergl.marker.colorbar", **kwargs ): super(ThicknessmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="thickness", parent_name="scattergl.marker.colorbar", **kwargs ): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowticksuffixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showticksuffix", parent_name="scattergl.marker.colorbar", **kwargs ): super(ShowticksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowtickprefixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showtickprefix", parent_name="scattergl.marker.colorbar", **kwargs ): super(ShowtickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowticklabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showticklabels", parent_name="scattergl.marker.colorbar", **kwargs ): super(ShowticklabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowexponentValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showexponent", parent_name="scattergl.marker.colorbar", **kwargs ): super(ShowexponentValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class SeparatethousandsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="separatethousands", parent_name="scattergl.marker.colorbar", **kwargs ): super(SeparatethousandsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="outlinewidth", parent_name="scattergl.marker.colorbar", **kwargs ): super(OutlinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="outlinecolor", parent_name="scattergl.marker.colorbar", **kwargs ): super(OutlinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NticksValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="nticks", parent_name="scattergl.marker.colorbar", **kwargs ): super(NticksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LenmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="lenmode", parent_name="scattergl.marker.colorbar", **kwargs ): super(LenmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class LenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="len", parent_name="scattergl.marker.colorbar", **kwargs ): super(LenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ExponentformatValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="exponentformat", parent_name="scattergl.marker.colorbar", **kwargs ): super(ExponentformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "e", "E", "power", "SI", "B"]), **kwargs ) import _plotly_utils.basevalidators class DtickValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="dtick", parent_name="scattergl.marker.colorbar", **kwargs ): super(DtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BorderwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="borderwidth", parent_name="scattergl.marker.colorbar", **kwargs ): super(BorderwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="scattergl.marker.colorbar", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="scattergl.marker.colorbar", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattergl/marker/colorbar/tickfont/0000755000175000017500000000000013573746614026661 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattergl/marker/colorbar/tickfont/__init__.py0000644000175000017500000000315213573721542030764 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scattergl.marker.colorbar.tickfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="scattergl.marker.colorbar.tickfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scattergl.marker.colorbar.tickfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattergl/marker/__init__.py0000644000175000017500000010437213573721543025347 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SymbolsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="symbolsrc", parent_name="scattergl.marker", **kwargs ): super(SymbolsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SymbolValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="symbol", parent_name="scattergl.marker", **kwargs): super(SymbolValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", [ 0, "circle", 100, "circle-open", 200, "circle-dot", 300, "circle-open-dot", 1, "square", 101, "square-open", 201, "square-dot", 301, "square-open-dot", 2, "diamond", 102, "diamond-open", 202, "diamond-dot", 302, "diamond-open-dot", 3, "cross", 103, "cross-open", 203, "cross-dot", 303, "cross-open-dot", 4, "x", 104, "x-open", 204, "x-dot", 304, "x-open-dot", 5, "triangle-up", 105, "triangle-up-open", 205, "triangle-up-dot", 305, "triangle-up-open-dot", 6, "triangle-down", 106, "triangle-down-open", 206, "triangle-down-dot", 306, "triangle-down-open-dot", 7, "triangle-left", 107, "triangle-left-open", 207, "triangle-left-dot", 307, "triangle-left-open-dot", 8, "triangle-right", 108, "triangle-right-open", 208, "triangle-right-dot", 308, "triangle-right-open-dot", 9, "triangle-ne", 109, "triangle-ne-open", 209, "triangle-ne-dot", 309, "triangle-ne-open-dot", 10, "triangle-se", 110, "triangle-se-open", 210, "triangle-se-dot", 310, "triangle-se-open-dot", 11, "triangle-sw", 111, "triangle-sw-open", 211, "triangle-sw-dot", 311, "triangle-sw-open-dot", 12, "triangle-nw", 112, "triangle-nw-open", 212, "triangle-nw-dot", 312, "triangle-nw-open-dot", 13, "pentagon", 113, "pentagon-open", 213, "pentagon-dot", 313, "pentagon-open-dot", 14, "hexagon", 114, "hexagon-open", 214, "hexagon-dot", 314, "hexagon-open-dot", 15, "hexagon2", 115, "hexagon2-open", 215, "hexagon2-dot", 315, "hexagon2-open-dot", 16, "octagon", 116, "octagon-open", 216, "octagon-dot", 316, "octagon-open-dot", 17, "star", 117, "star-open", 217, "star-dot", 317, "star-open-dot", 18, "hexagram", 118, "hexagram-open", 218, "hexagram-dot", 318, "hexagram-open-dot", 19, "star-triangle-up", 119, "star-triangle-up-open", 219, "star-triangle-up-dot", 319, "star-triangle-up-open-dot", 20, "star-triangle-down", 120, "star-triangle-down-open", 220, "star-triangle-down-dot", 320, "star-triangle-down-open-dot", 21, "star-square", 121, "star-square-open", 221, "star-square-dot", 321, "star-square-open-dot", 22, "star-diamond", 122, "star-diamond-open", 222, "star-diamond-dot", 322, "star-diamond-open-dot", 23, "diamond-tall", 123, "diamond-tall-open", 223, "diamond-tall-dot", 323, "diamond-tall-open-dot", 24, "diamond-wide", 124, "diamond-wide-open", 224, "diamond-wide-dot", 324, "diamond-wide-open-dot", 25, "hourglass", 125, "hourglass-open", 26, "bowtie", 126, "bowtie-open", 27, "circle-cross", 127, "circle-cross-open", 28, "circle-x", 128, "circle-x-open", 29, "square-cross", 129, "square-cross-open", 30, "square-x", 130, "square-x-open", 31, "diamond-cross", 131, "diamond-cross-open", 32, "diamond-x", 132, "diamond-x-open", 33, "cross-thin", 133, "cross-thin-open", 34, "x-thin", 134, "x-thin-open", 35, "asterisk", 135, "asterisk-open", 36, "hash", 136, "hash-open", 236, "hash-dot", 336, "hash-open-dot", 37, "y-up", 137, "y-up-open", 38, "y-down", 138, "y-down-open", 39, "y-left", 139, "y-left-open", 40, "y-right", 140, "y-right-open", 41, "line-ew", 141, "line-ew-open", 42, "line-ns", 142, "line-ns-open", 43, "line-ne", 143, "line-ne-open", 44, "line-nw", 144, "line-nw-open", ], ), **kwargs ) import _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="sizesrc", parent_name="scattergl.marker", **kwargs): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizerefValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="sizeref", parent_name="scattergl.marker", **kwargs): super(SizerefValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SizemodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="sizemode", parent_name="scattergl.marker", **kwargs ): super(SizemodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["diameter", "area"]), **kwargs ) import _plotly_utils.basevalidators class SizeminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="sizemin", parent_name="scattergl.marker", **kwargs): super(SizeminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="size", parent_name="scattergl.marker", **kwargs): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showscale", parent_name="scattergl.marker", **kwargs ): super(ShowscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ReversescaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="reversescale", parent_name="scattergl.marker", **kwargs ): super(ReversescaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacitysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="opacitysrc", parent_name="scattergl.marker", **kwargs ): super(OpacitysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="scattergl.marker", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="line", parent_name="scattergl.marker", **kwargs): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,R eds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Black body,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . """, ), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="scattergl.marker", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__( self, plotly_name="colorscale", parent_name="scattergl.marker", **kwargs ): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"autocolorscale": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorBarValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="colorbar", parent_name="scattergl.marker", **kwargs ): super(ColorBarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "ColorBar"), data_docs=kwargs.pop( "data_docs", """ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.scattergl.marke r.colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.scattergl.marker.colorbar.tickformatstopdefau lts), sets the default property values to use for elements of scattergl.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.scattergl.marker.colorbar. Title instance or dict with compatible properties titlefont Deprecated: Please use scattergl.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use scattergl.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """, ), **kwargs ) import _plotly_utils.basevalidators class ColoraxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__( self, plotly_name="coloraxis", parent_name="scattergl.marker", **kwargs ): super(ColoraxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", None), edit_type=kwargs.pop("edit_type", "calc"), regex=kwargs.pop("regex", "/^coloraxis([2-9]|[1-9][0-9]+)?$/"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="scattergl.marker", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), colorscale_path=kwargs.pop( "colorscale_path", "scattergl.marker.colorscale" ), **kwargs ) import _plotly_utils.basevalidators class CminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmin", parent_name="scattergl.marker", **kwargs): super(CminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmidValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmid", parent_name="scattergl.marker", **kwargs): super(CmidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmax", parent_name="scattergl.marker", **kwargs): super(CmaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CautoValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="cauto", parent_name="scattergl.marker", **kwargs): super(CautoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AutocolorscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="autocolorscale", parent_name="scattergl.marker", **kwargs ): super(AutocolorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattergl/marker/line/0000755000175000017500000000000013573746614024164 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattergl/marker/line/__init__.py0000644000175000017500000001452313573721543026274 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="widthsrc", parent_name="scattergl.marker.line", **kwargs ): super(WidthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="width", parent_name="scattergl.marker.line", **kwargs ): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ReversescaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="reversescale", parent_name="scattergl.marker.line", **kwargs ): super(ReversescaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="scattergl.marker.line", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__( self, plotly_name="colorscale", parent_name="scattergl.marker.line", **kwargs ): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"autocolorscale": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColoraxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__( self, plotly_name="coloraxis", parent_name="scattergl.marker.line", **kwargs ): super(ColoraxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", None), edit_type=kwargs.pop("edit_type", "calc"), regex=kwargs.pop("regex", "/^coloraxis([2-9]|[1-9][0-9]+)?$/"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scattergl.marker.line", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), colorscale_path=kwargs.pop( "colorscale_path", "scattergl.marker.line.colorscale" ), **kwargs ) import _plotly_utils.basevalidators class CminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="cmin", parent_name="scattergl.marker.line", **kwargs ): super(CminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmidValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="cmid", parent_name="scattergl.marker.line", **kwargs ): super(CmidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="cmax", parent_name="scattergl.marker.line", **kwargs ): super(CmaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CautoValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="cauto", parent_name="scattergl.marker.line", **kwargs ): super(CautoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AutocolorscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="autocolorscale", parent_name="scattergl.marker.line", **kwargs ): super(AutocolorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattergl/stream/0000755000175000017500000000000013573746614023247 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattergl/stream/__init__.py0000644000175000017500000000210613573721542025350 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TokenValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="token", parent_name="scattergl.stream", **kwargs): super(TokenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "info"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class MaxpointsValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="maxpoints", parent_name="scattergl.stream", **kwargs ): super(MaxpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 10000), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattergl/__init__.py0000644000175000017500000012077613573721543024074 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="ysrc", parent_name="scattergl", **kwargs): super(YsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YcalendarValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="ycalendar", parent_name="scattergl", **kwargs): super(YcalendarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "gregorian", "chinese", "coptic", "discworld", "ethiopian", "hebrew", "islamic", "julian", "mayan", "nanakshahi", "nepali", "persian", "jalali", "taiwan", "thai", "ummalqura", ], ), **kwargs ) import _plotly_utils.basevalidators class YAxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="yaxis", parent_name="scattergl", **kwargs): super(YAxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "y"), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class Y0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="y0", parent_name="scattergl", **kwargs): super(Y0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="y", parent_name="scattergl", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class XsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="xsrc", parent_name="scattergl", **kwargs): super(XsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XcalendarValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="xcalendar", parent_name="scattergl", **kwargs): super(XcalendarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "gregorian", "chinese", "coptic", "discworld", "ethiopian", "hebrew", "islamic", "julian", "mayan", "nanakshahi", "nepali", "persian", "jalali", "taiwan", "thai", "ummalqura", ], ), **kwargs ) import _plotly_utils.basevalidators class XAxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="xaxis", parent_name="scattergl", **kwargs): super(XAxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "x"), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class X0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="x0", parent_name="scattergl", **kwargs): super(X0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="x", parent_name="scattergl", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="visible", parent_name="scattergl", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "legendonly"]), **kwargs ) import _plotly_utils.basevalidators class UnselectedValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="unselected", parent_name="scattergl", **kwargs): super(UnselectedValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Unselected"), data_docs=kwargs.pop( "data_docs", """ marker plotly.graph_objects.scattergl.unselected.Marke r instance or dict with compatible properties textfont plotly.graph_objects.scattergl.unselected.Textf ont instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="scattergl", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UidValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="uid", parent_name="scattergl", **kwargs): super(UidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TexttemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="texttemplatesrc", parent_name="scattergl", **kwargs ): super(TexttemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TexttemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="texttemplate", parent_name="scattergl", **kwargs): super(TexttemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="textsrc", parent_name="scattergl", **kwargs): super(TextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextpositionsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="textpositionsrc", parent_name="scattergl", **kwargs ): super(TextpositionsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextpositionValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="textposition", parent_name="scattergl", **kwargs): super(TextpositionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", [ "top left", "top center", "top right", "middle left", "middle center", "middle right", "bottom left", "bottom center", "bottom right", ], ), **kwargs ) import _plotly_utils.basevalidators class TextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="textfont", parent_name="scattergl", **kwargs): super(TextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Textfont"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="text", parent_name="scattergl", **kwargs): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class StreamValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="stream", parent_name="scattergl", **kwargs): super(StreamValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Stream"), data_docs=kwargs.pop( "data_docs", """ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """, ), **kwargs ) import _plotly_utils.basevalidators class ShowlegendValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showlegend", parent_name="scattergl", **kwargs): super(ShowlegendValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SelectedpointsValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="selectedpoints", parent_name="scattergl", **kwargs): super(SelectedpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SelectedValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="selected", parent_name="scattergl", **kwargs): super(SelectedValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Selected"), data_docs=kwargs.pop( "data_docs", """ marker plotly.graph_objects.scattergl.selected.Marker instance or dict with compatible properties textfont plotly.graph_objects.scattergl.selected.Textfon t instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="scattergl", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="scattergl", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ModeValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="mode", parent_name="scattergl", **kwargs): super(ModeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), extras=kwargs.pop("extras", ["none"]), flags=kwargs.pop("flags", ["lines", "markers", "text"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="metasrc", parent_name="scattergl", **kwargs): super(MetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetaValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="meta", parent_name="scattergl", **kwargs): super(MetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="marker", parent_name="scattergl", **kwargs): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.scattergl.marker.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . line plotly.graph_objects.scattergl.marker.Line instance or dict with compatible properties opacity Sets the marker opacity. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. size Sets the marker size (in px). sizemin Has an effect only if `marker.size` is set to a numerical array. Sets the minimum size (in px) of the rendered marker points. sizemode Has an effect only if `marker.size` is set to a numerical array. Sets the rule for which the data in `size` is converted to pixels. sizeref Has an effect only if `marker.size` is set to a numerical array. Sets the scale factor used to determine the rendered size of marker points. Use with `sizemin` and `sizemode`. sizesrc Sets the source reference on plot.ly for size . symbol Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot- open" to a symbol name. symbolsrc Sets the source reference on plot.ly for symbol . """, ), **kwargs ) import _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="line", parent_name="scattergl", **kwargs): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ color Sets the line color. dash Sets the style of the lines. shape Determines the line shape. The values correspond to step-wise line shapes. width Sets the line width (in px). """, ), **kwargs ) import _plotly_utils.basevalidators class LegendgroupValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="legendgroup", parent_name="scattergl", **kwargs): super(LegendgroupValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="idssrc", parent_name="scattergl", **kwargs): super(IdssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ids", parent_name="scattergl", **kwargs): super(IdsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class HovertextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hovertextsrc", parent_name="scattergl", **kwargs): super(HovertextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertext", parent_name="scattergl", **kwargs): super(HovertextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="hovertemplatesrc", parent_name="scattergl", **kwargs ): super(HovertemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertemplate", parent_name="scattergl", **kwargs): super(HovertemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverlabelValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="hoverlabel", parent_name="scattergl", **kwargs): super(HoverlabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Hoverlabel"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """, ), **kwargs ) import _plotly_utils.basevalidators class HoverinfosrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hoverinfosrc", parent_name="scattergl", **kwargs): super(HoverinfosrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverinfoValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="hoverinfo", parent_name="scattergl", **kwargs): super(HoverinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), extras=kwargs.pop("extras", ["all", "none", "skip"]), flags=kwargs.pop("flags", ["x", "y", "z", "text", "name"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FillcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="fillcolor", parent_name="scattergl", **kwargs): super(FillcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FillValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="fill", parent_name="scattergl", **kwargs): super(FillValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", [ "none", "tozeroy", "tozerox", "tonexty", "tonextx", "toself", "tonext", ], ), **kwargs ) import _plotly_utils.basevalidators class ErrorYValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="error_y", parent_name="scattergl", **kwargs): super(ErrorYValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "ErrorY"), data_docs=kwargs.pop( "data_docs", """ array Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. arrayminus Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. arrayminussrc Sets the source reference on plot.ly for arrayminus . arraysrc Sets the source reference on plot.ly for array . color Sets the stoke color of the error bars. symmetric Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. thickness Sets the thickness (in px) of the error bars. traceref tracerefminus type Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. value Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. valueminus Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars visible Determines whether or not this set of error bars is visible. width Sets the width (in px) of the cross-bar at both ends of the error bars. """, ), **kwargs ) import _plotly_utils.basevalidators class ErrorXValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="error_x", parent_name="scattergl", **kwargs): super(ErrorXValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "ErrorX"), data_docs=kwargs.pop( "data_docs", """ array Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. arrayminus Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. arrayminussrc Sets the source reference on plot.ly for arrayminus . arraysrc Sets the source reference on plot.ly for array . color Sets the stoke color of the error bars. copy_ystyle symmetric Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. thickness Sets the thickness (in px) of the error bars. traceref tracerefminus type Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. value Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. valueminus Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars visible Determines whether or not this set of error bars is visible. width Sets the width (in px) of the cross-bar at both ends of the error bars. """, ), **kwargs ) import _plotly_utils.basevalidators class DyValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="dy", parent_name="scattergl", **kwargs): super(DyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="dx", parent_name="scattergl", **kwargs): super(DxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdatasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="customdatasrc", parent_name="scattergl", **kwargs): super(CustomdatasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdataValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="customdata", parent_name="scattergl", **kwargs): super(CustomdataValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class ConnectgapsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="connectgaps", parent_name="scattergl", **kwargs): super(ConnectgapsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattergl/line/0000755000175000017500000000000013573746614022703 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattergl/line/__init__.py0000644000175000017500000000376213573721542025015 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="scattergl.line", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShapeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="shape", parent_name="scattergl.line", **kwargs): super(ShapeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["linear", "hv", "vh", "hvh", "vhv"]), **kwargs ) import _plotly_utils.basevalidators class DashValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="dash", parent_name="scattergl.line", **kwargs): super(DashValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", ["solid", "dot", "dash", "longdash", "dashdot", "longdashdot"] ), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="scattergl.line", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattergl/selected/0000755000175000017500000000000013573746614023544 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattergl/selected/textfont/0000755000175000017500000000000013573746614025417 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattergl/selected/textfont/__init__.py0000644000175000017500000000072513573721542027525 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scattergl.selected.textfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattergl/selected/marker/0000755000175000017500000000000013573746614025025 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattergl/selected/marker/__init__.py0000644000175000017500000000276413573721542027140 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scattergl.selected.marker", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="opacity", parent_name="scattergl.selected.marker", **kwargs ): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scattergl.selected.marker", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattergl/selected/__init__.py0000644000175000017500000000255513573721542025655 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="textfont", parent_name="scattergl.selected", **kwargs ): super(TextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Textfont"), data_docs=kwargs.pop( "data_docs", """ color Sets the text font color of selected points. """, ), **kwargs ) import _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="marker", parent_name="scattergl.selected", **kwargs ): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. size Sets the marker size of selected points. """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/contour/0000755000175000017500000000000013573746614021455 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/contour/hoverlabel/0000755000175000017500000000000013573746614023600 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/contour/hoverlabel/__init__.py0000644000175000017500000001340313573721536025706 0ustar noahfxnoahfximport _plotly_utils.basevalidators class NamelengthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="namelengthsrc", parent_name="contour.hoverlabel", **kwargs ): super(NamelengthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NamelengthValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="namelength", parent_name="contour.hoverlabel", **kwargs ): super(NamelengthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", -1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="font", parent_name="contour.hoverlabel", **kwargs): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class BordercolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bordercolorsrc", parent_name="contour.hoverlabel", **kwargs ): super(BordercolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="contour.hoverlabel", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bgcolorsrc", parent_name="contour.hoverlabel", **kwargs ): super(BgcolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="contour.hoverlabel", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AlignsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="alignsrc", parent_name="contour.hoverlabel", **kwargs ): super(AlignsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="align", parent_name="contour.hoverlabel", **kwargs): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "right", "auto"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/contour/hoverlabel/font/0000755000175000017500000000000013573746614024546 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/contour/hoverlabel/font/__init__.py0000644000175000017500000000604513573721536026660 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="contour.hoverlabel.font", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="contour.hoverlabel.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="contour.hoverlabel.font", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="contour.hoverlabel.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="contour.hoverlabel.font", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="contour.hoverlabel.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/contour/colorbar/0000755000175000017500000000000013573746614023260 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/contour/colorbar/tickformatstop/0000755000175000017500000000000013573746614026331 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/contour/colorbar/tickformatstop/__init__.py0000644000175000017500000000537413573721536030447 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="value", parent_name="contour.colorbar.tickformatstop", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="contour.colorbar.tickformatstop", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="contour.colorbar.tickformatstop", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EnabledValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="enabled", parent_name="contour.colorbar.tickformatstop", **kwargs ): super(EnabledValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DtickrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="dtickrange", parent_name="contour.colorbar.tickformatstop", **kwargs ): super(DtickrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "colorbars"}, {"valType": "any", "editType": "colorbars"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/contour/colorbar/title/0000755000175000017500000000000013573746614024401 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/contour/colorbar/title/__init__.py0000644000175000017500000000471513573721536026515 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="text", parent_name="contour.colorbar.title", **kwargs ): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SideValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="side", parent_name="contour.colorbar.title", **kwargs ): super(SideValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["right", "top", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="contour.colorbar.title", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/contour/colorbar/title/font/0000755000175000017500000000000013573746614025347 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/contour/colorbar/title/font/__init__.py0000644000175000017500000000303413573721536027454 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="contour.colorbar.title.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="contour.colorbar.title.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="contour.colorbar.title.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/contour/colorbar/__init__.py0000644000175000017500000005773713573721537025411 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="ypad", parent_name="contour.colorbar", **kwargs): super(YpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class YanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="yanchor", parent_name="contour.colorbar", **kwargs): super(YanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["top", "middle", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="y", parent_name="contour.colorbar", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="xpad", parent_name="contour.colorbar", **kwargs): super(XpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="xanchor", parent_name="contour.colorbar", **kwargs): super(XanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "center", "right"]), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="x", parent_name="contour.colorbar", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TitleValidator(_plotly_utils.basevalidators.TitleValidator): def __init__(self, plotly_name="title", parent_name="contour.colorbar", **kwargs): super(TitleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Title"), data_docs=kwargs.pop( "data_docs", """ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """, ), **kwargs ) import _plotly_utils.basevalidators class TickwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="tickwidth", parent_name="contour.colorbar", **kwargs ): super(TickwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickvalssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="tickvalssrc", parent_name="contour.colorbar", **kwargs ): super(TickvalssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickvalsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="tickvals", parent_name="contour.colorbar", **kwargs ): super(TickvalsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="ticktextsrc", parent_name="contour.colorbar", **kwargs ): super(TicktextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicktextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="ticktext", parent_name="contour.colorbar", **kwargs ): super(TicktextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="ticksuffix", parent_name="contour.colorbar", **kwargs ): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TicksValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="ticks", parent_name="contour.colorbar", **kwargs): super(TicksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["outside", "inside", ""]), **kwargs ) import _plotly_utils.basevalidators class TickprefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickprefix", parent_name="contour.colorbar", **kwargs ): super(TickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="tickmode", parent_name="contour.colorbar", **kwargs ): super(TickmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "linear", "array"]), **kwargs ) import _plotly_utils.basevalidators class TicklenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="ticklen", parent_name="contour.colorbar", **kwargs): super(TicklenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickformatstopValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickformatstopdefaults", parent_name="contour.colorbar", **kwargs ): super(TickformatstopValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatstopsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="tickformatstops", parent_name="contour.colorbar", **kwargs ): super(TickformatstopsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickformat", parent_name="contour.colorbar", **kwargs ): super(TickformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickfont", parent_name="contour.colorbar", **kwargs ): super(TickfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class TickcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="tickcolor", parent_name="contour.colorbar", **kwargs ): super(TickcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__( self, plotly_name="tickangle", parent_name="contour.colorbar", **kwargs ): super(TickangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="tick0", parent_name="contour.colorbar", **kwargs): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ThicknessmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="thicknessmode", parent_name="contour.colorbar", **kwargs ): super(ThicknessmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="thickness", parent_name="contour.colorbar", **kwargs ): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowticksuffixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showticksuffix", parent_name="contour.colorbar", **kwargs ): super(ShowticksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowtickprefixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showtickprefix", parent_name="contour.colorbar", **kwargs ): super(ShowtickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowticklabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showticklabels", parent_name="contour.colorbar", **kwargs ): super(ShowticklabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowexponentValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showexponent", parent_name="contour.colorbar", **kwargs ): super(ShowexponentValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class SeparatethousandsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="separatethousands", parent_name="contour.colorbar", **kwargs ): super(SeparatethousandsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="outlinewidth", parent_name="contour.colorbar", **kwargs ): super(OutlinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="outlinecolor", parent_name="contour.colorbar", **kwargs ): super(OutlinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NticksValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="nticks", parent_name="contour.colorbar", **kwargs): super(NticksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LenmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="lenmode", parent_name="contour.colorbar", **kwargs): super(LenmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class LenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="len", parent_name="contour.colorbar", **kwargs): super(LenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ExponentformatValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="exponentformat", parent_name="contour.colorbar", **kwargs ): super(ExponentformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "e", "E", "power", "SI", "B"]), **kwargs ) import _plotly_utils.basevalidators class DtickValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="dtick", parent_name="contour.colorbar", **kwargs): super(DtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BorderwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="borderwidth", parent_name="contour.colorbar", **kwargs ): super(BorderwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="contour.colorbar", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="bgcolor", parent_name="contour.colorbar", **kwargs): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/contour/colorbar/tickfont/0000755000175000017500000000000013573746614025101 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/contour/colorbar/tickfont/__init__.py0000644000175000017500000000302613573721536027207 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="contour.colorbar.tickfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="contour.colorbar.tickfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="contour.colorbar.tickfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/contour/contours/0000755000175000017500000000000013573746614023331 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/contour/contours/labelfont/0000755000175000017500000000000013573746614025277 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/contour/contours/labelfont/__init__.py0000644000175000017500000000301313573721536027401 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="contour.contours.labelfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="contour.contours.labelfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="contour.contours.labelfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/contour/contours/__init__.py0000644000175000017500000001550713573721537025447 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="value", parent_name="contour.contours", **kwargs): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TypeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="type", parent_name="contour.contours", **kwargs): super(TypeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["levels", "constraint"]), **kwargs ) import _plotly_utils.basevalidators class StartValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="start", parent_name="contour.contours", **kwargs): super(StartValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"^autocontour": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="size", parent_name="contour.contours", **kwargs): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"^autocontour": False}), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowlinesValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showlines", parent_name="contour.contours", **kwargs ): super(ShowlinesValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowlabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showlabels", parent_name="contour.contours", **kwargs ): super(ShowlabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OperationValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="operation", parent_name="contour.contours", **kwargs ): super(OperationValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "=", "<", ">=", ">", "<=", "[]", "()", "[)", "(]", "][", ")(", "](", ")[", ], ), **kwargs ) import _plotly_utils.basevalidators class LabelformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="labelformat", parent_name="contour.contours", **kwargs ): super(LabelformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LabelfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="labelfont", parent_name="contour.contours", **kwargs ): super(LabelfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Labelfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class EndValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="end", parent_name="contour.contours", **kwargs): super(EndValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"^autocontour": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColoringValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="coloring", parent_name="contour.contours", **kwargs ): super(ColoringValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["fill", "heatmap", "lines", "none"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/contour/stream/0000755000175000017500000000000013573746614022750 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/contour/stream/__init__.py0000644000175000017500000000206413573721536025057 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TokenValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="token", parent_name="contour.stream", **kwargs): super(TokenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "info"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class MaxpointsValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="maxpoints", parent_name="contour.stream", **kwargs): super(MaxpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 10000), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/contour/__init__.py0000644000175000017500000013030713573721537023567 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ZsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="zsrc", parent_name="contour", **kwargs): super(ZsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="zmin", parent_name="contour", **kwargs): super(ZminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"zauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZmidValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="zmid", parent_name="contour", **kwargs): super(ZmidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZmaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="zmax", parent_name="contour", **kwargs): super(ZmaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"zauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZhoverformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="zhoverformat", parent_name="contour", **kwargs): super(ZhoverformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ZautoValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="zauto", parent_name="contour", **kwargs): super(ZautoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="z", parent_name="contour", **kwargs): super(ZValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class YtypeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="ytype", parent_name="contour", **kwargs): super(YtypeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["array", "scaled"]), **kwargs ) import _plotly_utils.basevalidators class YsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="ysrc", parent_name="contour", **kwargs): super(YsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YcalendarValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="ycalendar", parent_name="contour", **kwargs): super(YcalendarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "gregorian", "chinese", "coptic", "discworld", "ethiopian", "hebrew", "islamic", "julian", "mayan", "nanakshahi", "nepali", "persian", "jalali", "taiwan", "thai", "ummalqura", ], ), **kwargs ) import _plotly_utils.basevalidators class YAxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="yaxis", parent_name="contour", **kwargs): super(YAxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "y"), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class Y0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="y0", parent_name="contour", **kwargs): super(Y0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), implied_edits=kwargs.pop("implied_edits", {"ytype": "scaled"}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="y", parent_name="contour", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), implied_edits=kwargs.pop("implied_edits", {"ytype": "array"}), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class XtypeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="xtype", parent_name="contour", **kwargs): super(XtypeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["array", "scaled"]), **kwargs ) import _plotly_utils.basevalidators class XsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="xsrc", parent_name="contour", **kwargs): super(XsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XcalendarValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="xcalendar", parent_name="contour", **kwargs): super(XcalendarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "gregorian", "chinese", "coptic", "discworld", "ethiopian", "hebrew", "islamic", "julian", "mayan", "nanakshahi", "nepali", "persian", "jalali", "taiwan", "thai", "ummalqura", ], ), **kwargs ) import _plotly_utils.basevalidators class XAxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="xaxis", parent_name="contour", **kwargs): super(XAxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "x"), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class X0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="x0", parent_name="contour", **kwargs): super(X0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), implied_edits=kwargs.pop("implied_edits", {"xtype": "scaled"}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="x", parent_name="contour", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), implied_edits=kwargs.pop("implied_edits", {"xtype": "array"}), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="visible", parent_name="contour", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "legendonly"]), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="contour", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UidValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="uid", parent_name="contour", **kwargs): super(UidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TransposeValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="transpose", parent_name="contour", **kwargs): super(TransposeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="textsrc", parent_name="contour", **kwargs): super(TextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="text", parent_name="contour", **kwargs): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class StreamValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="stream", parent_name="contour", **kwargs): super(StreamValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Stream"), data_docs=kwargs.pop( "data_docs", """ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """, ), **kwargs ) import _plotly_utils.basevalidators class ShowscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showscale", parent_name="contour", **kwargs): super(ShowscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ShowlegendValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showlegend", parent_name="contour", **kwargs): super(ShowlegendValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ReversescaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="reversescale", parent_name="contour", **kwargs): super(ReversescaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="contour", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NcontoursValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="ncontours", parent_name="contour", **kwargs): super(NcontoursValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="contour", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="metasrc", parent_name="contour", **kwargs): super(MetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetaValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="meta", parent_name="contour", **kwargs): super(MetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="line", parent_name="contour", **kwargs): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ color Sets the color of the contour level. Has no effect if `contours.coloring` is set to "lines". dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). smoothing Sets the amount of smoothing for the contour lines, where 0 corresponds to no smoothing. width Sets the contour line width in (in px) Defaults to 0.5 when `contours.type` is "levels". Defaults to 2 when `contour.type` is "constraint". """, ), **kwargs ) import _plotly_utils.basevalidators class LegendgroupValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="legendgroup", parent_name="contour", **kwargs): super(LegendgroupValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="idssrc", parent_name="contour", **kwargs): super(IdssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ids", parent_name="contour", **kwargs): super(IdsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class HovertextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hovertextsrc", parent_name="contour", **kwargs): super(HovertextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="hovertext", parent_name="contour", **kwargs): super(HovertextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class HovertemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hovertemplatesrc", parent_name="contour", **kwargs): super(HovertemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertemplate", parent_name="contour", **kwargs): super(HovertemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverongapsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="hoverongaps", parent_name="contour", **kwargs): super(HoverongapsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class HoverlabelValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="hoverlabel", parent_name="contour", **kwargs): super(HoverlabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Hoverlabel"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """, ), **kwargs ) import _plotly_utils.basevalidators class HoverinfosrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hoverinfosrc", parent_name="contour", **kwargs): super(HoverinfosrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverinfoValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="hoverinfo", parent_name="contour", **kwargs): super(HoverinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), extras=kwargs.pop("extras", ["all", "none", "skip"]), flags=kwargs.pop("flags", ["x", "y", "z", "text", "name"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FillcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="fillcolor", parent_name="contour", **kwargs): super(FillcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), colorscale_path=kwargs.pop("colorscale_path", "contour.colorscale"), **kwargs ) import _plotly_utils.basevalidators class DyValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="dy", parent_name="contour", **kwargs): super(DyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"ytype": "scaled"}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="dx", parent_name="contour", **kwargs): super(DxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"xtype": "scaled"}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdatasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="customdatasrc", parent_name="contour", **kwargs): super(CustomdatasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdataValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="customdata", parent_name="contour", **kwargs): super(CustomdataValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class ContoursValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="contours", parent_name="contour", **kwargs): super(ContoursValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Contours"), data_docs=kwargs.pop( "data_docs", """ coloring Determines the coloring method showing the contour values. If "fill", coloring is done evenly between each contour level If "heatmap", a heatmap gradient coloring is applied between each contour level. If "lines", coloring is done on the contour lines. If "none", no coloring is applied on this trace. end Sets the end contour level value. Must be more than `contours.start` labelfont Sets the font used for labeling the contour levels. The default color comes from the lines, if shown. The default family and size come from `layout.font`. labelformat Sets the contour label formatting rule using d3 formatting mini-language which is very similar to Python, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format operation Sets the constraint operation. "=" keeps regions equal to `value` "<" and "<=" keep regions less than `value` ">" and ">=" keep regions greater than `value` "[]", "()", "[)", and "(]" keep regions inside `value[0]` to `value[1]` "][", ")(", "](", ")[" keep regions outside `value[0]` to value[1]` Open vs. closed intervals make no difference to constraint display, but all versions are allowed for consistency with filter transforms. showlabels Determines whether to label the contour lines with their values. showlines Determines whether or not the contour lines are drawn. Has an effect only if `contours.coloring` is set to "fill". size Sets the step between each contour level. Must be positive. start Sets the starting contour level value. Must be less than `contours.end` type If `levels`, the data is represented as a contour plot with multiple levels displayed. If `constraint`, the data is represented as constraints with the invalid region shaded as specified by the `operation` and `value` parameters. value Sets the value or values of the constraint boundary. When `operation` is set to one of the comparison values (=,<,>=,>,<=) "value" is expected to be a number. When `operation` is set to one of the interval values ([],(),[),(],][,)(,](,)[) "value" is expected to be an array of two numbers where the first is the lower bound and the second is the upper bound. """, ), **kwargs ) import _plotly_utils.basevalidators class ConnectgapsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="connectgaps", parent_name="contour", **kwargs): super(ConnectgapsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__(self, plotly_name="colorscale", parent_name="contour", **kwargs): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"autocolorscale": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorBarValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="colorbar", parent_name="contour", **kwargs): super(ColorBarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "ColorBar"), data_docs=kwargs.pop( "data_docs", """ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.contour.colorba r.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.contour.colorbar.tickformatstopdefaults), sets the default property values to use for elements of contour.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.contour.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use contour.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use contour.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """, ), **kwargs ) import _plotly_utils.basevalidators class ColoraxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="coloraxis", parent_name="contour", **kwargs): super(ColoraxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", None), edit_type=kwargs.pop("edit_type", "calc"), regex=kwargs.pop("regex", "/^coloraxis([2-9]|[1-9][0-9]+)?$/"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AutocontourValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="autocontour", parent_name="contour", **kwargs): super(AutocontourValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AutocolorscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="autocolorscale", parent_name="contour", **kwargs): super(AutocolorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/contour/line/0000755000175000017500000000000013573746614022404 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/contour/line/__init__.py0000644000175000017500000000400213573721536024505 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="contour.line", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style+colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SmoothingValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="smoothing", parent_name="contour.line", **kwargs): super(SmoothingValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), max=kwargs.pop("max", 1.3), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class DashValidator(_plotly_utils.basevalidators.DashValidator): def __init__(self, plotly_name="dash", parent_name="contour.line", **kwargs): super(DashValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", ["solid", "dot", "dash", "longdash", "dashdot", "longdashdot"] ), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="contour.line", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style+colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattergeo/0000755000175000017500000000000013573746614022124 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattergeo/unselected/0000755000175000017500000000000013573746614024257 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattergeo/unselected/textfont/0000755000175000017500000000000013573746614026132 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattergeo/unselected/textfont/__init__.py0000644000175000017500000000076013573721542030237 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scattergeo.unselected.textfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattergeo/unselected/marker/0000755000175000017500000000000013573746614025540 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattergeo/unselected/marker/__init__.py0000644000175000017500000000302513573721542027642 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scattergeo.unselected.marker", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="opacity", parent_name="scattergeo.unselected.marker", **kwargs ): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scattergeo.unselected.marker", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattergeo/unselected/__init__.py0000644000175000017500000000312313573721542026360 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="textfont", parent_name="scattergeo.unselected", **kwargs ): super(TextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Textfont"), data_docs=kwargs.pop( "data_docs", """ color Sets the text font color of unselected points, applied only when a selection exists. """, ), **kwargs ) import _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="marker", parent_name="scattergeo.unselected", **kwargs ): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. size Sets the marker size of unselected points, applied only when a selection exists. """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattergeo/textfont/0000755000175000017500000000000013573746614023777 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattergeo/textfont/__init__.py0000644000175000017500000000577713573721542026121 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="scattergeo.textfont", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="size", parent_name="scattergeo.textfont", **kwargs): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="scattergeo.textfont", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="scattergeo.textfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="scattergeo.textfont", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scattergeo.textfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattergeo/hoverlabel/0000755000175000017500000000000013573746614024247 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattergeo/hoverlabel/__init__.py0000644000175000017500000001352213573721542026354 0ustar noahfxnoahfximport _plotly_utils.basevalidators class NamelengthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="namelengthsrc", parent_name="scattergeo.hoverlabel", **kwargs ): super(NamelengthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NamelengthValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="namelength", parent_name="scattergeo.hoverlabel", **kwargs ): super(NamelengthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", -1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="scattergeo.hoverlabel", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class BordercolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bordercolorsrc", parent_name="scattergeo.hoverlabel", **kwargs ): super(BordercolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="scattergeo.hoverlabel", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bgcolorsrc", parent_name="scattergeo.hoverlabel", **kwargs ): super(BgcolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="scattergeo.hoverlabel", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AlignsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="alignsrc", parent_name="scattergeo.hoverlabel", **kwargs ): super(AlignsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="align", parent_name="scattergeo.hoverlabel", **kwargs ): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "right", "auto"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattergeo/hoverlabel/font/0000755000175000017500000000000013573746614025215 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattergeo/hoverlabel/font/__init__.py0000644000175000017500000000611713573721542027324 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="scattergeo.hoverlabel.font", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scattergeo.hoverlabel.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="scattergeo.hoverlabel.font", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="scattergeo.hoverlabel.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="scattergeo.hoverlabel.font", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scattergeo.hoverlabel.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattergeo/marker/0000755000175000017500000000000013573746614023405 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattergeo/marker/colorbar/0000755000175000017500000000000013573746614025210 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattergeo/marker/colorbar/tickformatstop/0000755000175000017500000000000013573746614030261 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattergeo/marker/colorbar/tickformatstop/__init__.py0000644000175000017500000000541313573721542032366 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="value", parent_name="scattergeo.marker.colorbar.tickformatstop", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="scattergeo.marker.colorbar.tickformatstop", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="scattergeo.marker.colorbar.tickformatstop", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EnabledValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="enabled", parent_name="scattergeo.marker.colorbar.tickformatstop", **kwargs ): super(EnabledValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DtickrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="dtickrange", parent_name="scattergeo.marker.colorbar.tickformatstop", **kwargs ): super(DtickrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "calc"}, {"valType": "any", "editType": "calc"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattergeo/marker/colorbar/title/0000755000175000017500000000000013573746614026331 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattergeo/marker/colorbar/title/__init__.py0000644000175000017500000000505113573721542030434 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="text", parent_name="scattergeo.marker.colorbar.title", **kwargs ): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SideValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="side", parent_name="scattergeo.marker.colorbar.title", **kwargs ): super(SideValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["right", "top", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="scattergeo.marker.colorbar.title", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattergeo/marker/colorbar/title/font/0000755000175000017500000000000013573746614027277 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattergeo/marker/colorbar/title/font/__init__.py0000644000175000017500000000316313573721542031404 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scattergeo.marker.colorbar.title.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="scattergeo.marker.colorbar.title.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scattergeo.marker.colorbar.title.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattergeo/marker/colorbar/__init__.py0000644000175000017500000006162413573721543027324 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ypad", parent_name="scattergeo.marker.colorbar", **kwargs ): super(YpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class YanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="yanchor", parent_name="scattergeo.marker.colorbar", **kwargs ): super(YanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["top", "middle", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="y", parent_name="scattergeo.marker.colorbar", **kwargs ): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="xpad", parent_name="scattergeo.marker.colorbar", **kwargs ): super(XpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="xanchor", parent_name="scattergeo.marker.colorbar", **kwargs ): super(XanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "center", "right"]), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="x", parent_name="scattergeo.marker.colorbar", **kwargs ): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TitleValidator(_plotly_utils.basevalidators.TitleValidator): def __init__( self, plotly_name="title", parent_name="scattergeo.marker.colorbar", **kwargs ): super(TitleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Title"), data_docs=kwargs.pop( "data_docs", """ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """, ), **kwargs ) import _plotly_utils.basevalidators class TickwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="tickwidth", parent_name="scattergeo.marker.colorbar", **kwargs ): super(TickwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickvalssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="tickvalssrc", parent_name="scattergeo.marker.colorbar", **kwargs ): super(TickvalssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickvalsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="tickvals", parent_name="scattergeo.marker.colorbar", **kwargs ): super(TickvalsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="ticktextsrc", parent_name="scattergeo.marker.colorbar", **kwargs ): super(TicktextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicktextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="ticktext", parent_name="scattergeo.marker.colorbar", **kwargs ): super(TicktextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="ticksuffix", parent_name="scattergeo.marker.colorbar", **kwargs ): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TicksValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="ticks", parent_name="scattergeo.marker.colorbar", **kwargs ): super(TicksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["outside", "inside", ""]), **kwargs ) import _plotly_utils.basevalidators class TickprefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickprefix", parent_name="scattergeo.marker.colorbar", **kwargs ): super(TickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="tickmode", parent_name="scattergeo.marker.colorbar", **kwargs ): super(TickmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "linear", "array"]), **kwargs ) import _plotly_utils.basevalidators class TicklenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ticklen", parent_name="scattergeo.marker.colorbar", **kwargs ): super(TicklenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickformatstopValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickformatstopdefaults", parent_name="scattergeo.marker.colorbar", **kwargs ): super(TickformatstopValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatstopsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="tickformatstops", parent_name="scattergeo.marker.colorbar", **kwargs ): super(TickformatstopsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickformat", parent_name="scattergeo.marker.colorbar", **kwargs ): super(TickformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickfont", parent_name="scattergeo.marker.colorbar", **kwargs ): super(TickfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class TickcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="tickcolor", parent_name="scattergeo.marker.colorbar", **kwargs ): super(TickcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__( self, plotly_name="tickangle", parent_name="scattergeo.marker.colorbar", **kwargs ): super(TickangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="tick0", parent_name="scattergeo.marker.colorbar", **kwargs ): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ThicknessmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="thicknessmode", parent_name="scattergeo.marker.colorbar", **kwargs ): super(ThicknessmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="thickness", parent_name="scattergeo.marker.colorbar", **kwargs ): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowticksuffixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showticksuffix", parent_name="scattergeo.marker.colorbar", **kwargs ): super(ShowticksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowtickprefixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showtickprefix", parent_name="scattergeo.marker.colorbar", **kwargs ): super(ShowtickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowticklabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showticklabels", parent_name="scattergeo.marker.colorbar", **kwargs ): super(ShowticklabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowexponentValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showexponent", parent_name="scattergeo.marker.colorbar", **kwargs ): super(ShowexponentValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class SeparatethousandsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="separatethousands", parent_name="scattergeo.marker.colorbar", **kwargs ): super(SeparatethousandsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="outlinewidth", parent_name="scattergeo.marker.colorbar", **kwargs ): super(OutlinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="outlinecolor", parent_name="scattergeo.marker.colorbar", **kwargs ): super(OutlinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NticksValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="nticks", parent_name="scattergeo.marker.colorbar", **kwargs ): super(NticksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LenmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="lenmode", parent_name="scattergeo.marker.colorbar", **kwargs ): super(LenmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class LenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="len", parent_name="scattergeo.marker.colorbar", **kwargs ): super(LenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ExponentformatValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="exponentformat", parent_name="scattergeo.marker.colorbar", **kwargs ): super(ExponentformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "e", "E", "power", "SI", "B"]), **kwargs ) import _plotly_utils.basevalidators class DtickValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="dtick", parent_name="scattergeo.marker.colorbar", **kwargs ): super(DtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BorderwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="borderwidth", parent_name="scattergeo.marker.colorbar", **kwargs ): super(BorderwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="scattergeo.marker.colorbar", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="scattergeo.marker.colorbar", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattergeo/marker/colorbar/tickfont/0000755000175000017500000000000013573746614027031 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattergeo/marker/colorbar/tickfont/__init__.py0000644000175000017500000000315513573721542031137 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scattergeo.marker.colorbar.tickfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="scattergeo.marker.colorbar.tickfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scattergeo.marker.colorbar.tickfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattergeo/marker/gradient/0000755000175000017500000000000013573746614025202 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattergeo/marker/gradient/__init__.py0000644000175000017500000000403613573721542027307 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TypesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="typesrc", parent_name="scattergeo.marker.gradient", **kwargs ): super(TypesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TypeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="type", parent_name="scattergeo.marker.gradient", **kwargs ): super(TypeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["radial", "horizontal", "vertical", "none"]), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="scattergeo.marker.gradient", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scattergeo.marker.gradient", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattergeo/marker/__init__.py0000644000175000017500000010653713573721543025524 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SymbolsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="symbolsrc", parent_name="scattergeo.marker", **kwargs ): super(SymbolsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SymbolValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="symbol", parent_name="scattergeo.marker", **kwargs): super(SymbolValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", [ 0, "circle", 100, "circle-open", 200, "circle-dot", 300, "circle-open-dot", 1, "square", 101, "square-open", 201, "square-dot", 301, "square-open-dot", 2, "diamond", 102, "diamond-open", 202, "diamond-dot", 302, "diamond-open-dot", 3, "cross", 103, "cross-open", 203, "cross-dot", 303, "cross-open-dot", 4, "x", 104, "x-open", 204, "x-dot", 304, "x-open-dot", 5, "triangle-up", 105, "triangle-up-open", 205, "triangle-up-dot", 305, "triangle-up-open-dot", 6, "triangle-down", 106, "triangle-down-open", 206, "triangle-down-dot", 306, "triangle-down-open-dot", 7, "triangle-left", 107, "triangle-left-open", 207, "triangle-left-dot", 307, "triangle-left-open-dot", 8, "triangle-right", 108, "triangle-right-open", 208, "triangle-right-dot", 308, "triangle-right-open-dot", 9, "triangle-ne", 109, "triangle-ne-open", 209, "triangle-ne-dot", 309, "triangle-ne-open-dot", 10, "triangle-se", 110, "triangle-se-open", 210, "triangle-se-dot", 310, "triangle-se-open-dot", 11, "triangle-sw", 111, "triangle-sw-open", 211, "triangle-sw-dot", 311, "triangle-sw-open-dot", 12, "triangle-nw", 112, "triangle-nw-open", 212, "triangle-nw-dot", 312, "triangle-nw-open-dot", 13, "pentagon", 113, "pentagon-open", 213, "pentagon-dot", 313, "pentagon-open-dot", 14, "hexagon", 114, "hexagon-open", 214, "hexagon-dot", 314, "hexagon-open-dot", 15, "hexagon2", 115, "hexagon2-open", 215, "hexagon2-dot", 315, "hexagon2-open-dot", 16, "octagon", 116, "octagon-open", 216, "octagon-dot", 316, "octagon-open-dot", 17, "star", 117, "star-open", 217, "star-dot", 317, "star-open-dot", 18, "hexagram", 118, "hexagram-open", 218, "hexagram-dot", 318, "hexagram-open-dot", 19, "star-triangle-up", 119, "star-triangle-up-open", 219, "star-triangle-up-dot", 319, "star-triangle-up-open-dot", 20, "star-triangle-down", 120, "star-triangle-down-open", 220, "star-triangle-down-dot", 320, "star-triangle-down-open-dot", 21, "star-square", 121, "star-square-open", 221, "star-square-dot", 321, "star-square-open-dot", 22, "star-diamond", 122, "star-diamond-open", 222, "star-diamond-dot", 322, "star-diamond-open-dot", 23, "diamond-tall", 123, "diamond-tall-open", 223, "diamond-tall-dot", 323, "diamond-tall-open-dot", 24, "diamond-wide", 124, "diamond-wide-open", 224, "diamond-wide-dot", 324, "diamond-wide-open-dot", 25, "hourglass", 125, "hourglass-open", 26, "bowtie", 126, "bowtie-open", 27, "circle-cross", 127, "circle-cross-open", 28, "circle-x", 128, "circle-x-open", 29, "square-cross", 129, "square-cross-open", 30, "square-x", 130, "square-x-open", 31, "diamond-cross", 131, "diamond-cross-open", 32, "diamond-x", 132, "diamond-x-open", 33, "cross-thin", 133, "cross-thin-open", 34, "x-thin", 134, "x-thin-open", 35, "asterisk", 135, "asterisk-open", 36, "hash", 136, "hash-open", 236, "hash-dot", 336, "hash-open-dot", 37, "y-up", 137, "y-up-open", 38, "y-down", 138, "y-down-open", 39, "y-left", 139, "y-left-open", 40, "y-right", 140, "y-right-open", 41, "line-ew", 141, "line-ew-open", 42, "line-ns", 142, "line-ns-open", 43, "line-ne", 143, "line-ne-open", 44, "line-nw", 144, "line-nw-open", ], ), **kwargs ) import _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="scattergeo.marker", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizerefValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="sizeref", parent_name="scattergeo.marker", **kwargs ): super(SizerefValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SizemodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="sizemode", parent_name="scattergeo.marker", **kwargs ): super(SizemodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["diameter", "area"]), **kwargs ) import _plotly_utils.basevalidators class SizeminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="sizemin", parent_name="scattergeo.marker", **kwargs ): super(SizeminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="size", parent_name="scattergeo.marker", **kwargs): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showscale", parent_name="scattergeo.marker", **kwargs ): super(ShowscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ReversescaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="reversescale", parent_name="scattergeo.marker", **kwargs ): super(ReversescaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacitysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="opacitysrc", parent_name="scattergeo.marker", **kwargs ): super(OpacitysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="opacity", parent_name="scattergeo.marker", **kwargs ): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="line", parent_name="scattergeo.marker", **kwargs): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,R eds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Black body,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . """, ), **kwargs ) import _plotly_utils.basevalidators class GradientValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="gradient", parent_name="scattergeo.marker", **kwargs ): super(GradientValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Gradient"), data_docs=kwargs.pop( "data_docs", """ color Sets the final color of the gradient fill: the center color for radial, the right for horizontal, or the bottom for vertical. colorsrc Sets the source reference on plot.ly for color . type Sets the type of gradient used to fill the markers typesrc Sets the source reference on plot.ly for type . """, ), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="scattergeo.marker", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__( self, plotly_name="colorscale", parent_name="scattergeo.marker", **kwargs ): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"autocolorscale": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorBarValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="colorbar", parent_name="scattergeo.marker", **kwargs ): super(ColorBarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "ColorBar"), data_docs=kwargs.pop( "data_docs", """ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.scattergeo.mark er.colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.scattergeo.marker.colorbar.tickformatstopdefa ults), sets the default property values to use for elements of scattergeo.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.scattergeo.marker.colorbar .Title instance or dict with compatible properties titlefont Deprecated: Please use scattergeo.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use scattergeo.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """, ), **kwargs ) import _plotly_utils.basevalidators class ColoraxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__( self, plotly_name="coloraxis", parent_name="scattergeo.marker", **kwargs ): super(ColoraxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", None), edit_type=kwargs.pop("edit_type", "calc"), regex=kwargs.pop("regex", "/^coloraxis([2-9]|[1-9][0-9]+)?$/"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="scattergeo.marker", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), colorscale_path=kwargs.pop( "colorscale_path", "scattergeo.marker.colorscale" ), **kwargs ) import _plotly_utils.basevalidators class CminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmin", parent_name="scattergeo.marker", **kwargs): super(CminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmidValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmid", parent_name="scattergeo.marker", **kwargs): super(CmidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmax", parent_name="scattergeo.marker", **kwargs): super(CmaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CautoValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="cauto", parent_name="scattergeo.marker", **kwargs): super(CautoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AutocolorscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="autocolorscale", parent_name="scattergeo.marker", **kwargs ): super(AutocolorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattergeo/marker/line/0000755000175000017500000000000013573746614024334 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattergeo/marker/line/__init__.py0000644000175000017500000001454013573721542026442 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="widthsrc", parent_name="scattergeo.marker.line", **kwargs ): super(WidthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="width", parent_name="scattergeo.marker.line", **kwargs ): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ReversescaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="reversescale", parent_name="scattergeo.marker.line", **kwargs ): super(ReversescaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="scattergeo.marker.line", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__( self, plotly_name="colorscale", parent_name="scattergeo.marker.line", **kwargs ): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"autocolorscale": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColoraxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__( self, plotly_name="coloraxis", parent_name="scattergeo.marker.line", **kwargs ): super(ColoraxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", None), edit_type=kwargs.pop("edit_type", "calc"), regex=kwargs.pop("regex", "/^coloraxis([2-9]|[1-9][0-9]+)?$/"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scattergeo.marker.line", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), colorscale_path=kwargs.pop( "colorscale_path", "scattergeo.marker.line.colorscale" ), **kwargs ) import _plotly_utils.basevalidators class CminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="cmin", parent_name="scattergeo.marker.line", **kwargs ): super(CminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmidValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="cmid", parent_name="scattergeo.marker.line", **kwargs ): super(CmidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="cmax", parent_name="scattergeo.marker.line", **kwargs ): super(CmaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CautoValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="cauto", parent_name="scattergeo.marker.line", **kwargs ): super(CautoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AutocolorscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="autocolorscale", parent_name="scattergeo.marker.line", **kwargs ): super(AutocolorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattergeo/stream/0000755000175000017500000000000013573746614023417 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattergeo/stream/__init__.py0000644000175000017500000000211013573721542025513 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TokenValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="token", parent_name="scattergeo.stream", **kwargs): super(TokenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "info"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class MaxpointsValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="maxpoints", parent_name="scattergeo.stream", **kwargs ): super(MaxpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 10000), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattergeo/__init__.py0000644000175000017500000007757613573721543024255 0ustar noahfxnoahfximport _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="visible", parent_name="scattergeo", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "legendonly"]), **kwargs ) import _plotly_utils.basevalidators class UnselectedValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="unselected", parent_name="scattergeo", **kwargs): super(UnselectedValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Unselected"), data_docs=kwargs.pop( "data_docs", """ marker plotly.graph_objects.scattergeo.unselected.Mark er instance or dict with compatible properties textfont plotly.graph_objects.scattergeo.unselected.Text font instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="scattergeo", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UidValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="uid", parent_name="scattergeo", **kwargs): super(UidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TexttemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="texttemplatesrc", parent_name="scattergeo", **kwargs ): super(TexttemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TexttemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="texttemplate", parent_name="scattergeo", **kwargs): super(TexttemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="textsrc", parent_name="scattergeo", **kwargs): super(TextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextpositionsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="textpositionsrc", parent_name="scattergeo", **kwargs ): super(TextpositionsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextpositionValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="textposition", parent_name="scattergeo", **kwargs): super(TextpositionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", [ "top left", "top center", "top right", "middle left", "middle center", "middle right", "bottom left", "bottom center", "bottom right", ], ), **kwargs ) import _plotly_utils.basevalidators class TextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="textfont", parent_name="scattergeo", **kwargs): super(TextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Textfont"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="text", parent_name="scattergeo", **kwargs): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class StreamValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="stream", parent_name="scattergeo", **kwargs): super(StreamValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Stream"), data_docs=kwargs.pop( "data_docs", """ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """, ), **kwargs ) import _plotly_utils.basevalidators class ShowlegendValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showlegend", parent_name="scattergeo", **kwargs): super(ShowlegendValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SelectedpointsValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="selectedpoints", parent_name="scattergeo", **kwargs ): super(SelectedpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SelectedValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="selected", parent_name="scattergeo", **kwargs): super(SelectedValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Selected"), data_docs=kwargs.pop( "data_docs", """ marker plotly.graph_objects.scattergeo.selected.Marker instance or dict with compatible properties textfont plotly.graph_objects.scattergeo.selected.Textfo nt instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="scattergeo", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="scattergeo", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ModeValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="mode", parent_name="scattergeo", **kwargs): super(ModeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), extras=kwargs.pop("extras", ["none"]), flags=kwargs.pop("flags", ["lines", "markers", "text"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="metasrc", parent_name="scattergeo", **kwargs): super(MetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetaValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="meta", parent_name="scattergeo", **kwargs): super(MetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="marker", parent_name="scattergeo", **kwargs): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.scattergeo.marker.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . gradient plotly.graph_objects.scattergeo.marker.Gradient instance or dict with compatible properties line plotly.graph_objects.scattergeo.marker.Line instance or dict with compatible properties opacity Sets the marker opacity. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. size Sets the marker size (in px). sizemin Has an effect only if `marker.size` is set to a numerical array. Sets the minimum size (in px) of the rendered marker points. sizemode Has an effect only if `marker.size` is set to a numerical array. Sets the rule for which the data in `size` is converted to pixels. sizeref Has an effect only if `marker.size` is set to a numerical array. Sets the scale factor used to determine the rendered size of marker points. Use with `sizemin` and `sizemode`. sizesrc Sets the source reference on plot.ly for size . symbol Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot- open" to a symbol name. symbolsrc Sets the source reference on plot.ly for symbol . """, ), **kwargs ) import _plotly_utils.basevalidators class LonsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="lonsrc", parent_name="scattergeo", **kwargs): super(LonsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LonValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="lon", parent_name="scattergeo", **kwargs): super(LonValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class LocationssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="locationssrc", parent_name="scattergeo", **kwargs): super(LocationssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LocationsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="locations", parent_name="scattergeo", **kwargs): super(LocationsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class LocationmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="locationmode", parent_name="scattergeo", **kwargs): super(LocationmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["ISO-3", "USA-states", "country names"]), **kwargs ) import _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="line", parent_name="scattergeo", **kwargs): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ color Sets the line color. dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). width Sets the line width (in px). """, ), **kwargs ) import _plotly_utils.basevalidators class LegendgroupValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="legendgroup", parent_name="scattergeo", **kwargs): super(LegendgroupValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LatsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="latsrc", parent_name="scattergeo", **kwargs): super(LatsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LatValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="lat", parent_name="scattergeo", **kwargs): super(LatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class IdssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="idssrc", parent_name="scattergeo", **kwargs): super(IdssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ids", parent_name="scattergeo", **kwargs): super(IdsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class HovertextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hovertextsrc", parent_name="scattergeo", **kwargs): super(HovertextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertext", parent_name="scattergeo", **kwargs): super(HovertextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="hovertemplatesrc", parent_name="scattergeo", **kwargs ): super(HovertemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertemplate", parent_name="scattergeo", **kwargs): super(HovertemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverlabelValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="hoverlabel", parent_name="scattergeo", **kwargs): super(HoverlabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Hoverlabel"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """, ), **kwargs ) import _plotly_utils.basevalidators class HoverinfosrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hoverinfosrc", parent_name="scattergeo", **kwargs): super(HoverinfosrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverinfoValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="hoverinfo", parent_name="scattergeo", **kwargs): super(HoverinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), extras=kwargs.pop("extras", ["all", "none", "skip"]), flags=kwargs.pop("flags", ["lon", "lat", "location", "text", "name"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class GeoValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="geo", parent_name="scattergeo", **kwargs): super(GeoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "geo"), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FillcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="fillcolor", parent_name="scattergeo", **kwargs): super(FillcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FillValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="fill", parent_name="scattergeo", **kwargs): super(FillValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "toself"]), **kwargs ) import _plotly_utils.basevalidators class CustomdatasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="customdatasrc", parent_name="scattergeo", **kwargs): super(CustomdatasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdataValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="customdata", parent_name="scattergeo", **kwargs): super(CustomdataValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class ConnectgapsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="connectgaps", parent_name="scattergeo", **kwargs): super(ConnectgapsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattergeo/line/0000755000175000017500000000000013573746614023053 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattergeo/line/__init__.py0000644000175000017500000000273713573721542025166 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="scattergeo.line", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class DashValidator(_plotly_utils.basevalidators.DashValidator): def __init__(self, plotly_name="dash", parent_name="scattergeo.line", **kwargs): super(DashValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", ["solid", "dot", "dash", "longdash", "dashdot", "longdashdot"] ), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="scattergeo.line", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattergeo/selected/0000755000175000017500000000000013573746614023714 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattergeo/selected/textfont/0000755000175000017500000000000013573746614025567 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattergeo/selected/textfont/__init__.py0000644000175000017500000000072613573721542027676 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scattergeo.selected.textfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattergeo/selected/marker/0000755000175000017500000000000013573746614025175 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattergeo/selected/marker/__init__.py0000644000175000017500000000276713573721542027313 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scattergeo.selected.marker", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="opacity", parent_name="scattergeo.selected.marker", **kwargs ): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scattergeo.selected.marker", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattergeo/selected/__init__.py0000644000175000017500000000255713573721542026027 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="textfont", parent_name="scattergeo.selected", **kwargs ): super(TextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Textfont"), data_docs=kwargs.pop( "data_docs", """ color Sets the text font color of selected points. """, ), **kwargs ) import _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="marker", parent_name="scattergeo.selected", **kwargs ): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. size Sets the marker size of selected points. """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/contourcarpet/0000755000175000017500000000000013573746614022654 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/contourcarpet/colorbar/0000755000175000017500000000000013573746614024457 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/contourcarpet/colorbar/tickformatstop/0000755000175000017500000000000013573746614027530 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/contourcarpet/colorbar/tickformatstop/__init__.py0000644000175000017500000000543213573721536031641 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="value", parent_name="contourcarpet.colorbar.tickformatstop", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="contourcarpet.colorbar.tickformatstop", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="contourcarpet.colorbar.tickformatstop", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EnabledValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="enabled", parent_name="contourcarpet.colorbar.tickformatstop", **kwargs ): super(EnabledValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DtickrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="dtickrange", parent_name="contourcarpet.colorbar.tickformatstop", **kwargs ): super(DtickrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "colorbars"}, {"valType": "any", "editType": "colorbars"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/contourcarpet/colorbar/title/0000755000175000017500000000000013573746614025600 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/contourcarpet/colorbar/title/__init__.py0000644000175000017500000000473713573721536027720 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="text", parent_name="contourcarpet.colorbar.title", **kwargs ): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SideValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="side", parent_name="contourcarpet.colorbar.title", **kwargs ): super(SideValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["right", "top", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="contourcarpet.colorbar.title", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/contourcarpet/colorbar/title/font/0000755000175000017500000000000013573746614026546 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/contourcarpet/colorbar/title/font/__init__.py0000644000175000017500000000316613573721536030661 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="contourcarpet.colorbar.title.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="contourcarpet.colorbar.title.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="contourcarpet.colorbar.title.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/contourcarpet/colorbar/__init__.py0000644000175000017500000006106313573721537026573 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ypad", parent_name="contourcarpet.colorbar", **kwargs ): super(YpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class YanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="yanchor", parent_name="contourcarpet.colorbar", **kwargs ): super(YanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["top", "middle", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="y", parent_name="contourcarpet.colorbar", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="xpad", parent_name="contourcarpet.colorbar", **kwargs ): super(XpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="xanchor", parent_name="contourcarpet.colorbar", **kwargs ): super(XanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "center", "right"]), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="x", parent_name="contourcarpet.colorbar", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TitleValidator(_plotly_utils.basevalidators.TitleValidator): def __init__( self, plotly_name="title", parent_name="contourcarpet.colorbar", **kwargs ): super(TitleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Title"), data_docs=kwargs.pop( "data_docs", """ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """, ), **kwargs ) import _plotly_utils.basevalidators class TickwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="tickwidth", parent_name="contourcarpet.colorbar", **kwargs ): super(TickwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickvalssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="tickvalssrc", parent_name="contourcarpet.colorbar", **kwargs ): super(TickvalssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickvalsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="tickvals", parent_name="contourcarpet.colorbar", **kwargs ): super(TickvalsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="ticktextsrc", parent_name="contourcarpet.colorbar", **kwargs ): super(TicktextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicktextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="ticktext", parent_name="contourcarpet.colorbar", **kwargs ): super(TicktextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="ticksuffix", parent_name="contourcarpet.colorbar", **kwargs ): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TicksValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="ticks", parent_name="contourcarpet.colorbar", **kwargs ): super(TicksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["outside", "inside", ""]), **kwargs ) import _plotly_utils.basevalidators class TickprefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickprefix", parent_name="contourcarpet.colorbar", **kwargs ): super(TickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="tickmode", parent_name="contourcarpet.colorbar", **kwargs ): super(TickmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "linear", "array"]), **kwargs ) import _plotly_utils.basevalidators class TicklenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ticklen", parent_name="contourcarpet.colorbar", **kwargs ): super(TicklenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickformatstopValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickformatstopdefaults", parent_name="contourcarpet.colorbar", **kwargs ): super(TickformatstopValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatstopsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="tickformatstops", parent_name="contourcarpet.colorbar", **kwargs ): super(TickformatstopsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickformat", parent_name="contourcarpet.colorbar", **kwargs ): super(TickformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickfont", parent_name="contourcarpet.colorbar", **kwargs ): super(TickfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class TickcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="tickcolor", parent_name="contourcarpet.colorbar", **kwargs ): super(TickcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__( self, plotly_name="tickangle", parent_name="contourcarpet.colorbar", **kwargs ): super(TickangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="tick0", parent_name="contourcarpet.colorbar", **kwargs ): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ThicknessmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="thicknessmode", parent_name="contourcarpet.colorbar", **kwargs ): super(ThicknessmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="thickness", parent_name="contourcarpet.colorbar", **kwargs ): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowticksuffixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showticksuffix", parent_name="contourcarpet.colorbar", **kwargs ): super(ShowticksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowtickprefixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showtickprefix", parent_name="contourcarpet.colorbar", **kwargs ): super(ShowtickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowticklabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showticklabels", parent_name="contourcarpet.colorbar", **kwargs ): super(ShowticklabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowexponentValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showexponent", parent_name="contourcarpet.colorbar", **kwargs ): super(ShowexponentValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class SeparatethousandsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="separatethousands", parent_name="contourcarpet.colorbar", **kwargs ): super(SeparatethousandsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="outlinewidth", parent_name="contourcarpet.colorbar", **kwargs ): super(OutlinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="outlinecolor", parent_name="contourcarpet.colorbar", **kwargs ): super(OutlinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NticksValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="nticks", parent_name="contourcarpet.colorbar", **kwargs ): super(NticksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LenmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="lenmode", parent_name="contourcarpet.colorbar", **kwargs ): super(LenmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class LenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="len", parent_name="contourcarpet.colorbar", **kwargs ): super(LenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ExponentformatValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="exponentformat", parent_name="contourcarpet.colorbar", **kwargs ): super(ExponentformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "e", "E", "power", "SI", "B"]), **kwargs ) import _plotly_utils.basevalidators class DtickValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="dtick", parent_name="contourcarpet.colorbar", **kwargs ): super(DtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BorderwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="borderwidth", parent_name="contourcarpet.colorbar", **kwargs ): super(BorderwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="contourcarpet.colorbar", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="contourcarpet.colorbar", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/contourcarpet/colorbar/tickfont/0000755000175000017500000000000013573746614026300 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/contourcarpet/colorbar/tickfont/__init__.py0000644000175000017500000000316013573721536030405 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="contourcarpet.colorbar.tickfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="contourcarpet.colorbar.tickfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="contourcarpet.colorbar.tickfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/contourcarpet/contours/0000755000175000017500000000000013573746614024530 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/contourcarpet/contours/labelfont/0000755000175000017500000000000013573746614026476 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/contourcarpet/contours/labelfont/__init__.py0000644000175000017500000000314513573721536030606 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="contourcarpet.contours.labelfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="contourcarpet.contours.labelfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="contourcarpet.contours.labelfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/contourcarpet/contours/__init__.py0000644000175000017500000001570413573721537026645 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="value", parent_name="contourcarpet.contours", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TypeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="type", parent_name="contourcarpet.contours", **kwargs ): super(TypeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["levels", "constraint"]), **kwargs ) import _plotly_utils.basevalidators class StartValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="start", parent_name="contourcarpet.contours", **kwargs ): super(StartValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"^autocontour": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="contourcarpet.contours", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"^autocontour": False}), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowlinesValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showlines", parent_name="contourcarpet.contours", **kwargs ): super(ShowlinesValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowlabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showlabels", parent_name="contourcarpet.contours", **kwargs ): super(ShowlabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OperationValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="operation", parent_name="contourcarpet.contours", **kwargs ): super(OperationValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "=", "<", ">=", ">", "<=", "[]", "()", "[)", "(]", "][", ")(", "](", ")[", ], ), **kwargs ) import _plotly_utils.basevalidators class LabelformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="labelformat", parent_name="contourcarpet.contours", **kwargs ): super(LabelformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LabelfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="labelfont", parent_name="contourcarpet.contours", **kwargs ): super(LabelfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Labelfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class EndValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="end", parent_name="contourcarpet.contours", **kwargs ): super(EndValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"^autocontour": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColoringValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="coloring", parent_name="contourcarpet.contours", **kwargs ): super(ColoringValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["fill", "lines", "none"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/contourcarpet/stream/0000755000175000017500000000000013573746614024147 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/contourcarpet/stream/__init__.py0000644000175000017500000000213413573721536026254 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TokenValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="token", parent_name="contourcarpet.stream", **kwargs ): super(TokenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "info"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class MaxpointsValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="maxpoints", parent_name="contourcarpet.stream", **kwargs ): super(MaxpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 10000), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/contourcarpet/__init__.py0000644000175000017500000011305713573721537024771 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ZsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="zsrc", parent_name="contourcarpet", **kwargs): super(ZsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="zmin", parent_name="contourcarpet", **kwargs): super(ZminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"zauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZmidValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="zmid", parent_name="contourcarpet", **kwargs): super(ZmidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZmaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="zmax", parent_name="contourcarpet", **kwargs): super(ZmaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"zauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZautoValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="zauto", parent_name="contourcarpet", **kwargs): super(ZautoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="z", parent_name="contourcarpet", **kwargs): super(ZValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class YAxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="yaxis", parent_name="contourcarpet", **kwargs): super(YAxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "y"), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XAxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="xaxis", parent_name="contourcarpet", **kwargs): super(XAxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "x"), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="visible", parent_name="contourcarpet", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "legendonly"]), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="contourcarpet", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UidValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="uid", parent_name="contourcarpet", **kwargs): super(UidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TransposeValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="transpose", parent_name="contourcarpet", **kwargs): super(TransposeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="textsrc", parent_name="contourcarpet", **kwargs): super(TextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="text", parent_name="contourcarpet", **kwargs): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class StreamValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="stream", parent_name="contourcarpet", **kwargs): super(StreamValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Stream"), data_docs=kwargs.pop( "data_docs", """ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """, ), **kwargs ) import _plotly_utils.basevalidators class ShowscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showscale", parent_name="contourcarpet", **kwargs): super(ShowscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ShowlegendValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showlegend", parent_name="contourcarpet", **kwargs): super(ShowlegendValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ReversescaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="reversescale", parent_name="contourcarpet", **kwargs ): super(ReversescaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="contourcarpet", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NcontoursValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="ncontours", parent_name="contourcarpet", **kwargs): super(NcontoursValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="contourcarpet", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="metasrc", parent_name="contourcarpet", **kwargs): super(MetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetaValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="meta", parent_name="contourcarpet", **kwargs): super(MetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="line", parent_name="contourcarpet", **kwargs): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ color Sets the color of the contour level. Has no effect if `contours.coloring` is set to "lines". dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). smoothing Sets the amount of smoothing for the contour lines, where 0 corresponds to no smoothing. width Sets the contour line width in (in px) Defaults to 0.5 when `contours.type` is "levels". Defaults to 2 when `contour.type` is "constraint". """, ), **kwargs ) import _plotly_utils.basevalidators class LegendgroupValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="legendgroup", parent_name="contourcarpet", **kwargs ): super(LegendgroupValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="idssrc", parent_name="contourcarpet", **kwargs): super(IdssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ids", parent_name="contourcarpet", **kwargs): super(IdsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class HovertextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="hovertextsrc", parent_name="contourcarpet", **kwargs ): super(HovertextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="hovertext", parent_name="contourcarpet", **kwargs): super(HovertextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class FillcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="fillcolor", parent_name="contourcarpet", **kwargs): super(FillcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), colorscale_path=kwargs.pop("colorscale_path", "contourcarpet.colorscale"), **kwargs ) import _plotly_utils.basevalidators class DbValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="db", parent_name="contourcarpet", **kwargs): super(DbValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"ytype": "scaled"}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DaValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="da", parent_name="contourcarpet", **kwargs): super(DaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"xtype": "scaled"}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdatasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="customdatasrc", parent_name="contourcarpet", **kwargs ): super(CustomdatasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdataValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="customdata", parent_name="contourcarpet", **kwargs): super(CustomdataValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class ContoursValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="contours", parent_name="contourcarpet", **kwargs): super(ContoursValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Contours"), data_docs=kwargs.pop( "data_docs", """ coloring Determines the coloring method showing the contour values. If "fill", coloring is done evenly between each contour level If "lines", coloring is done on the contour lines. If "none", no coloring is applied on this trace. end Sets the end contour level value. Must be more than `contours.start` labelfont Sets the font used for labeling the contour levels. The default color comes from the lines, if shown. The default family and size come from `layout.font`. labelformat Sets the contour label formatting rule using d3 formatting mini-language which is very similar to Python, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format operation Sets the constraint operation. "=" keeps regions equal to `value` "<" and "<=" keep regions less than `value` ">" and ">=" keep regions greater than `value` "[]", "()", "[)", and "(]" keep regions inside `value[0]` to `value[1]` "][", ")(", "](", ")[" keep regions outside `value[0]` to value[1]` Open vs. closed intervals make no difference to constraint display, but all versions are allowed for consistency with filter transforms. showlabels Determines whether to label the contour lines with their values. showlines Determines whether or not the contour lines are drawn. Has an effect only if `contours.coloring` is set to "fill". size Sets the step between each contour level. Must be positive. start Sets the starting contour level value. Must be less than `contours.end` type If `levels`, the data is represented as a contour plot with multiple levels displayed. If `constraint`, the data is represented as constraints with the invalid region shaded as specified by the `operation` and `value` parameters. value Sets the value or values of the constraint boundary. When `operation` is set to one of the comparison values (=,<,>=,>,<=) "value" is expected to be a number. When `operation` is set to one of the interval values ([],(),[),(],][,)(,](,)[) "value" is expected to be an array of two numbers where the first is the lower bound and the second is the upper bound. """, ), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__(self, plotly_name="colorscale", parent_name="contourcarpet", **kwargs): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"autocolorscale": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorBarValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="colorbar", parent_name="contourcarpet", **kwargs): super(ColorBarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "ColorBar"), data_docs=kwargs.pop( "data_docs", """ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.contourcarpet.c olorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.contourcarpet.colorbar.tickformatstopdefaults ), sets the default property values to use for elements of contourcarpet.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.contourcarpet.colorbar.Tit le instance or dict with compatible properties titlefont Deprecated: Please use contourcarpet.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use contourcarpet.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """, ), **kwargs ) import _plotly_utils.basevalidators class ColoraxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="coloraxis", parent_name="contourcarpet", **kwargs): super(ColoraxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", None), edit_type=kwargs.pop("edit_type", "calc"), regex=kwargs.pop("regex", "/^coloraxis([2-9]|[1-9][0-9]+)?$/"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CarpetValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="carpet", parent_name="contourcarpet", **kwargs): super(CarpetValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BtypeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="btype", parent_name="contourcarpet", **kwargs): super(BtypeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["array", "scaled"]), **kwargs ) import _plotly_utils.basevalidators class BsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="bsrc", parent_name="contourcarpet", **kwargs): super(BsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class B0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="b0", parent_name="contourcarpet", **kwargs): super(B0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), implied_edits=kwargs.pop("implied_edits", {"ytype": "scaled"}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="b", parent_name="contourcarpet", **kwargs): super(BValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), implied_edits=kwargs.pop("implied_edits", {"ytype": "array"}), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class AutocontourValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="autocontour", parent_name="contourcarpet", **kwargs ): super(AutocontourValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AutocolorscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="autocolorscale", parent_name="contourcarpet", **kwargs ): super(AutocolorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AtypeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="atype", parent_name="contourcarpet", **kwargs): super(AtypeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["array", "scaled"]), **kwargs ) import _plotly_utils.basevalidators class AsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="asrc", parent_name="contourcarpet", **kwargs): super(AsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class A0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="a0", parent_name="contourcarpet", **kwargs): super(A0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), implied_edits=kwargs.pop("implied_edits", {"xtype": "scaled"}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="a", parent_name="contourcarpet", **kwargs): super(AValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), implied_edits=kwargs.pop("implied_edits", {"xtype": "array"}), role=kwargs.pop("role", "data"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/contourcarpet/line/0000755000175000017500000000000013573746614023603 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/contourcarpet/line/__init__.py0000644000175000017500000000405013573721537025710 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="contourcarpet.line", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style+colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SmoothingValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="smoothing", parent_name="contourcarpet.line", **kwargs ): super(SmoothingValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), max=kwargs.pop("max", 1.3), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class DashValidator(_plotly_utils.basevalidators.DashValidator): def __init__(self, plotly_name="dash", parent_name="contourcarpet.line", **kwargs): super(DashValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", ["solid", "dot", "dash", "longdash", "dashdot", "longdashdot"] ), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="contourcarpet.line", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style+colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterternary/0000755000175000017500000000000013573746614023036 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterternary/unselected/0000755000175000017500000000000013573746614025171 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterternary/unselected/textfont/0000755000175000017500000000000013573746614027044 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterternary/unselected/textfont/__init__.py0000644000175000017500000000076513573721543031157 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scatterternary.unselected.textfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterternary/unselected/marker/0000755000175000017500000000000013573746614026452 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterternary/unselected/marker/__init__.py0000644000175000017500000000312413573721543030555 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scatterternary.unselected.marker", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="opacity", parent_name="scatterternary.unselected.marker", **kwargs ): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scatterternary.unselected.marker", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterternary/unselected/__init__.py0000644000175000017500000000313313573721543027274 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="textfont", parent_name="scatterternary.unselected", **kwargs ): super(TextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Textfont"), data_docs=kwargs.pop( "data_docs", """ color Sets the text font color of unselected points, applied only when a selection exists. """, ), **kwargs ) import _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="marker", parent_name="scatterternary.unselected", **kwargs ): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. size Sets the marker size of unselected points, applied only when a selection exists. """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterternary/textfont/0000755000175000017500000000000013573746614024711 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterternary/textfont/__init__.py0000644000175000017500000000604613573721543027022 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="scatterternary.textfont", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scatterternary.textfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="scatterternary.textfont", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="scatterternary.textfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="scatterternary.textfont", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scatterternary.textfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterternary/hoverlabel/0000755000175000017500000000000013573746614025161 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterternary/hoverlabel/__init__.py0000644000175000017500000001372613573721543027275 0ustar noahfxnoahfximport _plotly_utils.basevalidators class NamelengthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="namelengthsrc", parent_name="scatterternary.hoverlabel", **kwargs ): super(NamelengthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NamelengthValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="namelength", parent_name="scatterternary.hoverlabel", **kwargs ): super(NamelengthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", -1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="scatterternary.hoverlabel", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class BordercolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bordercolorsrc", parent_name="scatterternary.hoverlabel", **kwargs ): super(BordercolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="scatterternary.hoverlabel", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bgcolorsrc", parent_name="scatterternary.hoverlabel", **kwargs ): super(BgcolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="scatterternary.hoverlabel", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AlignsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="alignsrc", parent_name="scatterternary.hoverlabel", **kwargs ): super(AlignsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="align", parent_name="scatterternary.hoverlabel", **kwargs ): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "right", "auto"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterternary/hoverlabel/font/0000755000175000017500000000000013573746614026127 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterternary/hoverlabel/font/__init__.py0000644000175000017500000000630713573721543030240 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="scatterternary.hoverlabel.font", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scatterternary.hoverlabel.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="scatterternary.hoverlabel.font", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="scatterternary.hoverlabel.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="scatterternary.hoverlabel.font", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scatterternary.hoverlabel.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterternary/marker/0000755000175000017500000000000013573746614024317 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterternary/marker/colorbar/0000755000175000017500000000000013573746614026122 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterternary/marker/colorbar/tickformatstop/0000755000175000017500000000000013573746614031173 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterternary/marker/colorbar/tickformatstop/__init__.py0000644000175000017500000000550213573721543033300 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="value", parent_name="scatterternary.marker.colorbar.tickformatstop", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="scatterternary.marker.colorbar.tickformatstop", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="scatterternary.marker.colorbar.tickformatstop", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EnabledValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="enabled", parent_name="scatterternary.marker.colorbar.tickformatstop", **kwargs ): super(EnabledValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DtickrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="dtickrange", parent_name="scatterternary.marker.colorbar.tickformatstop", **kwargs ): super(DtickrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "colorbars"}, {"valType": "any", "editType": "colorbars"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterternary/marker/colorbar/title/0000755000175000017500000000000013573746614027243 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterternary/marker/colorbar/title/__init__.py0000644000175000017500000000507713573721543031357 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="text", parent_name="scatterternary.marker.colorbar.title", **kwargs ): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SideValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="side", parent_name="scatterternary.marker.colorbar.title", **kwargs ): super(SideValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["right", "top", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="scatterternary.marker.colorbar.title", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterternary/marker/colorbar/title/font/0000755000175000017500000000000013573746614030211 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterternary/marker/colorbar/title/font/__init__.py0000644000175000017500000000321613573721543032316 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scatterternary.marker.colorbar.title.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="scatterternary.marker.colorbar.title.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scatterternary.marker.colorbar.title.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterternary/marker/colorbar/__init__.py0000644000175000017500000006306713573721544030242 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ypad", parent_name="scatterternary.marker.colorbar", **kwargs ): super(YpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class YanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="yanchor", parent_name="scatterternary.marker.colorbar", **kwargs ): super(YanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["top", "middle", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="y", parent_name="scatterternary.marker.colorbar", **kwargs ): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="xpad", parent_name="scatterternary.marker.colorbar", **kwargs ): super(XpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="xanchor", parent_name="scatterternary.marker.colorbar", **kwargs ): super(XanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "center", "right"]), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="x", parent_name="scatterternary.marker.colorbar", **kwargs ): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TitleValidator(_plotly_utils.basevalidators.TitleValidator): def __init__( self, plotly_name="title", parent_name="scatterternary.marker.colorbar", **kwargs ): super(TitleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Title"), data_docs=kwargs.pop( "data_docs", """ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """, ), **kwargs ) import _plotly_utils.basevalidators class TickwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="tickwidth", parent_name="scatterternary.marker.colorbar", **kwargs ): super(TickwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickvalssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="tickvalssrc", parent_name="scatterternary.marker.colorbar", **kwargs ): super(TickvalssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickvalsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="tickvals", parent_name="scatterternary.marker.colorbar", **kwargs ): super(TickvalsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="ticktextsrc", parent_name="scatterternary.marker.colorbar", **kwargs ): super(TicktextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicktextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="ticktext", parent_name="scatterternary.marker.colorbar", **kwargs ): super(TicktextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="ticksuffix", parent_name="scatterternary.marker.colorbar", **kwargs ): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TicksValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="ticks", parent_name="scatterternary.marker.colorbar", **kwargs ): super(TicksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["outside", "inside", ""]), **kwargs ) import _plotly_utils.basevalidators class TickprefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickprefix", parent_name="scatterternary.marker.colorbar", **kwargs ): super(TickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="tickmode", parent_name="scatterternary.marker.colorbar", **kwargs ): super(TickmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "linear", "array"]), **kwargs ) import _plotly_utils.basevalidators class TicklenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ticklen", parent_name="scatterternary.marker.colorbar", **kwargs ): super(TicklenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickformatstopValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickformatstopdefaults", parent_name="scatterternary.marker.colorbar", **kwargs ): super(TickformatstopValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatstopsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="tickformatstops", parent_name="scatterternary.marker.colorbar", **kwargs ): super(TickformatstopsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickformat", parent_name="scatterternary.marker.colorbar", **kwargs ): super(TickformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickfont", parent_name="scatterternary.marker.colorbar", **kwargs ): super(TickfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class TickcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="tickcolor", parent_name="scatterternary.marker.colorbar", **kwargs ): super(TickcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__( self, plotly_name="tickangle", parent_name="scatterternary.marker.colorbar", **kwargs ): super(TickangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="tick0", parent_name="scatterternary.marker.colorbar", **kwargs ): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ThicknessmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="thicknessmode", parent_name="scatterternary.marker.colorbar", **kwargs ): super(ThicknessmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="thickness", parent_name="scatterternary.marker.colorbar", **kwargs ): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowticksuffixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showticksuffix", parent_name="scatterternary.marker.colorbar", **kwargs ): super(ShowticksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowtickprefixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showtickprefix", parent_name="scatterternary.marker.colorbar", **kwargs ): super(ShowtickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowticklabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showticklabels", parent_name="scatterternary.marker.colorbar", **kwargs ): super(ShowticklabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowexponentValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showexponent", parent_name="scatterternary.marker.colorbar", **kwargs ): super(ShowexponentValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class SeparatethousandsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="separatethousands", parent_name="scatterternary.marker.colorbar", **kwargs ): super(SeparatethousandsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="outlinewidth", parent_name="scatterternary.marker.colorbar", **kwargs ): super(OutlinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="outlinecolor", parent_name="scatterternary.marker.colorbar", **kwargs ): super(OutlinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NticksValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="nticks", parent_name="scatterternary.marker.colorbar", **kwargs ): super(NticksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LenmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="lenmode", parent_name="scatterternary.marker.colorbar", **kwargs ): super(LenmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class LenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="len", parent_name="scatterternary.marker.colorbar", **kwargs ): super(LenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ExponentformatValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="exponentformat", parent_name="scatterternary.marker.colorbar", **kwargs ): super(ExponentformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "e", "E", "power", "SI", "B"]), **kwargs ) import _plotly_utils.basevalidators class DtickValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="dtick", parent_name="scatterternary.marker.colorbar", **kwargs ): super(DtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BorderwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="borderwidth", parent_name="scatterternary.marker.colorbar", **kwargs ): super(BorderwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="scatterternary.marker.colorbar", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="scatterternary.marker.colorbar", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterternary/marker/colorbar/tickfont/0000755000175000017500000000000013573746614027743 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterternary/marker/colorbar/tickfont/__init__.py0000644000175000017500000000321013573721543032042 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scatterternary.marker.colorbar.tickfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="scatterternary.marker.colorbar.tickfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scatterternary.marker.colorbar.tickfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterternary/marker/gradient/0000755000175000017500000000000013573746614026114 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterternary/marker/gradient/__init__.py0000644000175000017500000000416613573721543030226 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TypesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="typesrc", parent_name="scatterternary.marker.gradient", **kwargs ): super(TypesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TypeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="type", parent_name="scatterternary.marker.gradient", **kwargs ): super(TypeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["radial", "horizontal", "vertical", "none"]), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="scatterternary.marker.gradient", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scatterternary.marker.gradient", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterternary/marker/__init__.py0000644000175000017500000011015713573721544026430 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SymbolsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="symbolsrc", parent_name="scatterternary.marker", **kwargs ): super(SymbolsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SymbolValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="symbol", parent_name="scatterternary.marker", **kwargs ): super(SymbolValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", [ 0, "circle", 100, "circle-open", 200, "circle-dot", 300, "circle-open-dot", 1, "square", 101, "square-open", 201, "square-dot", 301, "square-open-dot", 2, "diamond", 102, "diamond-open", 202, "diamond-dot", 302, "diamond-open-dot", 3, "cross", 103, "cross-open", 203, "cross-dot", 303, "cross-open-dot", 4, "x", 104, "x-open", 204, "x-dot", 304, "x-open-dot", 5, "triangle-up", 105, "triangle-up-open", 205, "triangle-up-dot", 305, "triangle-up-open-dot", 6, "triangle-down", 106, "triangle-down-open", 206, "triangle-down-dot", 306, "triangle-down-open-dot", 7, "triangle-left", 107, "triangle-left-open", 207, "triangle-left-dot", 307, "triangle-left-open-dot", 8, "triangle-right", 108, "triangle-right-open", 208, "triangle-right-dot", 308, "triangle-right-open-dot", 9, "triangle-ne", 109, "triangle-ne-open", 209, "triangle-ne-dot", 309, "triangle-ne-open-dot", 10, "triangle-se", 110, "triangle-se-open", 210, "triangle-se-dot", 310, "triangle-se-open-dot", 11, "triangle-sw", 111, "triangle-sw-open", 211, "triangle-sw-dot", 311, "triangle-sw-open-dot", 12, "triangle-nw", 112, "triangle-nw-open", 212, "triangle-nw-dot", 312, "triangle-nw-open-dot", 13, "pentagon", 113, "pentagon-open", 213, "pentagon-dot", 313, "pentagon-open-dot", 14, "hexagon", 114, "hexagon-open", 214, "hexagon-dot", 314, "hexagon-open-dot", 15, "hexagon2", 115, "hexagon2-open", 215, "hexagon2-dot", 315, "hexagon2-open-dot", 16, "octagon", 116, "octagon-open", 216, "octagon-dot", 316, "octagon-open-dot", 17, "star", 117, "star-open", 217, "star-dot", 317, "star-open-dot", 18, "hexagram", 118, "hexagram-open", 218, "hexagram-dot", 318, "hexagram-open-dot", 19, "star-triangle-up", 119, "star-triangle-up-open", 219, "star-triangle-up-dot", 319, "star-triangle-up-open-dot", 20, "star-triangle-down", 120, "star-triangle-down-open", 220, "star-triangle-down-dot", 320, "star-triangle-down-open-dot", 21, "star-square", 121, "star-square-open", 221, "star-square-dot", 321, "star-square-open-dot", 22, "star-diamond", 122, "star-diamond-open", 222, "star-diamond-dot", 322, "star-diamond-open-dot", 23, "diamond-tall", 123, "diamond-tall-open", 223, "diamond-tall-dot", 323, "diamond-tall-open-dot", 24, "diamond-wide", 124, "diamond-wide-open", 224, "diamond-wide-dot", 324, "diamond-wide-open-dot", 25, "hourglass", 125, "hourglass-open", 26, "bowtie", 126, "bowtie-open", 27, "circle-cross", 127, "circle-cross-open", 28, "circle-x", 128, "circle-x-open", 29, "square-cross", 129, "square-cross-open", 30, "square-x", 130, "square-x-open", 31, "diamond-cross", 131, "diamond-cross-open", 32, "diamond-x", 132, "diamond-x-open", 33, "cross-thin", 133, "cross-thin-open", 34, "x-thin", 134, "x-thin-open", 35, "asterisk", 135, "asterisk-open", 36, "hash", 136, "hash-open", 236, "hash-dot", 336, "hash-open-dot", 37, "y-up", 137, "y-up-open", 38, "y-down", 138, "y-down-open", 39, "y-left", 139, "y-left-open", 40, "y-right", 140, "y-right-open", 41, "line-ew", 141, "line-ew-open", 42, "line-ns", 142, "line-ns-open", 43, "line-ne", 143, "line-ne-open", 44, "line-nw", 144, "line-nw-open", ], ), **kwargs ) import _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="scatterternary.marker", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizerefValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="sizeref", parent_name="scatterternary.marker", **kwargs ): super(SizerefValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SizemodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="sizemode", parent_name="scatterternary.marker", **kwargs ): super(SizemodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["diameter", "area"]), **kwargs ) import _plotly_utils.basevalidators class SizeminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="sizemin", parent_name="scatterternary.marker", **kwargs ): super(SizeminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scatterternary.marker", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showscale", parent_name="scatterternary.marker", **kwargs ): super(ShowscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ReversescaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="reversescale", parent_name="scatterternary.marker", **kwargs ): super(ReversescaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacitysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="opacitysrc", parent_name="scatterternary.marker", **kwargs ): super(OpacitysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="opacity", parent_name="scatterternary.marker", **kwargs ): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class MaxdisplayedValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="maxdisplayed", parent_name="scatterternary.marker", **kwargs ): super(MaxdisplayedValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="line", parent_name="scatterternary.marker", **kwargs ): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,R eds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Black body,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . """, ), **kwargs ) import _plotly_utils.basevalidators class GradientValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="gradient", parent_name="scatterternary.marker", **kwargs ): super(GradientValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Gradient"), data_docs=kwargs.pop( "data_docs", """ color Sets the final color of the gradient fill: the center color for radial, the right for horizontal, or the bottom for vertical. colorsrc Sets the source reference on plot.ly for color . type Sets the type of gradient used to fill the markers typesrc Sets the source reference on plot.ly for type . """, ), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="scatterternary.marker", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__( self, plotly_name="colorscale", parent_name="scatterternary.marker", **kwargs ): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"autocolorscale": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorBarValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="colorbar", parent_name="scatterternary.marker", **kwargs ): super(ColorBarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "ColorBar"), data_docs=kwargs.pop( "data_docs", """ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.scatterternary. marker.colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.scatterternary.marker.colorbar.tickformatstop defaults), sets the default property values to use for elements of scatterternary.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.scatterternary.marker.colo rbar.Title instance or dict with compatible properties titlefont Deprecated: Please use scatterternary.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use scatterternary.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """, ), **kwargs ) import _plotly_utils.basevalidators class ColoraxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__( self, plotly_name="coloraxis", parent_name="scatterternary.marker", **kwargs ): super(ColoraxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", None), edit_type=kwargs.pop("edit_type", "calc"), regex=kwargs.pop("regex", "/^coloraxis([2-9]|[1-9][0-9]+)?$/"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scatterternary.marker", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), colorscale_path=kwargs.pop( "colorscale_path", "scatterternary.marker.colorscale" ), **kwargs ) import _plotly_utils.basevalidators class CminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="cmin", parent_name="scatterternary.marker", **kwargs ): super(CminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmidValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="cmid", parent_name="scatterternary.marker", **kwargs ): super(CmidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="cmax", parent_name="scatterternary.marker", **kwargs ): super(CmaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CautoValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="cauto", parent_name="scatterternary.marker", **kwargs ): super(CautoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AutocolorscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="autocolorscale", parent_name="scatterternary.marker", **kwargs ): super(AutocolorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterternary/marker/line/0000755000175000017500000000000013573746614025246 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterternary/marker/line/__init__.py0000644000175000017500000001473613573721543027364 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="widthsrc", parent_name="scatterternary.marker.line", **kwargs ): super(WidthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="width", parent_name="scatterternary.marker.line", **kwargs ): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ReversescaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="reversescale", parent_name="scatterternary.marker.line", **kwargs ): super(ReversescaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="scatterternary.marker.line", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__( self, plotly_name="colorscale", parent_name="scatterternary.marker.line", **kwargs ): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"autocolorscale": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColoraxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__( self, plotly_name="coloraxis", parent_name="scatterternary.marker.line", **kwargs ): super(ColoraxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", None), edit_type=kwargs.pop("edit_type", "calc"), regex=kwargs.pop("regex", "/^coloraxis([2-9]|[1-9][0-9]+)?$/"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scatterternary.marker.line", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), colorscale_path=kwargs.pop( "colorscale_path", "scatterternary.marker.line.colorscale" ), **kwargs ) import _plotly_utils.basevalidators class CminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="cmin", parent_name="scatterternary.marker.line", **kwargs ): super(CminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmidValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="cmid", parent_name="scatterternary.marker.line", **kwargs ): super(CmidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="cmax", parent_name="scatterternary.marker.line", **kwargs ): super(CmaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CautoValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="cauto", parent_name="scatterternary.marker.line", **kwargs ): super(CautoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AutocolorscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="autocolorscale", parent_name="scatterternary.marker.line", **kwargs ): super(AutocolorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterternary/stream/0000755000175000017500000000000013573746614024331 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterternary/stream/__init__.py0000644000175000017500000000213613573721543026436 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TokenValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="token", parent_name="scatterternary.stream", **kwargs ): super(TokenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "info"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class MaxpointsValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="maxpoints", parent_name="scatterternary.stream", **kwargs ): super(MaxpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 10000), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterternary/__init__.py0000644000175000017500000010341513573721544025146 0ustar noahfxnoahfximport _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="visible", parent_name="scatterternary", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "legendonly"]), **kwargs ) import _plotly_utils.basevalidators class UnselectedValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="unselected", parent_name="scatterternary", **kwargs ): super(UnselectedValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Unselected"), data_docs=kwargs.pop( "data_docs", """ marker plotly.graph_objects.scatterternary.unselected. Marker instance or dict with compatible properties textfont plotly.graph_objects.scatterternary.unselected. Textfont instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="uirevision", parent_name="scatterternary", **kwargs ): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UidValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="uid", parent_name="scatterternary", **kwargs): super(UidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TexttemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="texttemplatesrc", parent_name="scatterternary", **kwargs ): super(TexttemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TexttemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="texttemplate", parent_name="scatterternary", **kwargs ): super(TexttemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="textsrc", parent_name="scatterternary", **kwargs): super(TextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextpositionsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="textpositionsrc", parent_name="scatterternary", **kwargs ): super(TextpositionsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextpositionValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="textposition", parent_name="scatterternary", **kwargs ): super(TextpositionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", [ "top left", "top center", "top right", "middle left", "middle center", "middle right", "bottom left", "bottom center", "bottom right", ], ), **kwargs ) import _plotly_utils.basevalidators class TextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="textfont", parent_name="scatterternary", **kwargs): super(TextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Textfont"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="text", parent_name="scatterternary", **kwargs): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SumValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="sum", parent_name="scatterternary", **kwargs): super(SumValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SubplotValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="subplot", parent_name="scatterternary", **kwargs): super(SubplotValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "ternary"), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class StreamValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="stream", parent_name="scatterternary", **kwargs): super(StreamValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Stream"), data_docs=kwargs.pop( "data_docs", """ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """, ), **kwargs ) import _plotly_utils.basevalidators class ShowlegendValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showlegend", parent_name="scatterternary", **kwargs ): super(ShowlegendValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SelectedpointsValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="selectedpoints", parent_name="scatterternary", **kwargs ): super(SelectedpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SelectedValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="selected", parent_name="scatterternary", **kwargs): super(SelectedValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Selected"), data_docs=kwargs.pop( "data_docs", """ marker plotly.graph_objects.scatterternary.selected.Ma rker instance or dict with compatible properties textfont plotly.graph_objects.scatterternary.selected.Te xtfont instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="scatterternary", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="scatterternary", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ModeValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="mode", parent_name="scatterternary", **kwargs): super(ModeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), extras=kwargs.pop("extras", ["none"]), flags=kwargs.pop("flags", ["lines", "markers", "text"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="metasrc", parent_name="scatterternary", **kwargs): super(MetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetaValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="meta", parent_name="scatterternary", **kwargs): super(MetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="marker", parent_name="scatterternary", **kwargs): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.scatterternary.marker.Colo rBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . gradient plotly.graph_objects.scatterternary.marker.Grad ient instance or dict with compatible properties line plotly.graph_objects.scatterternary.marker.Line instance or dict with compatible properties maxdisplayed Sets a maximum number of points to be drawn on the graph. 0 corresponds to no limit. opacity Sets the marker opacity. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. size Sets the marker size (in px). sizemin Has an effect only if `marker.size` is set to a numerical array. Sets the minimum size (in px) of the rendered marker points. sizemode Has an effect only if `marker.size` is set to a numerical array. Sets the rule for which the data in `size` is converted to pixels. sizeref Has an effect only if `marker.size` is set to a numerical array. Sets the scale factor used to determine the rendered size of marker points. Use with `sizemin` and `sizemode`. sizesrc Sets the source reference on plot.ly for size . symbol Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot- open" to a symbol name. symbolsrc Sets the source reference on plot.ly for symbol . """, ), **kwargs ) import _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="line", parent_name="scatterternary", **kwargs): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ color Sets the line color. dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). shape Determines the line shape. With "spline" the lines are drawn using spline interpolation. The other available values correspond to step-wise line shapes. smoothing Has an effect only if `shape` is set to "spline" Sets the amount of smoothing. 0 corresponds to no smoothing (equivalent to a "linear" shape). width Sets the line width (in px). """, ), **kwargs ) import _plotly_utils.basevalidators class LegendgroupValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="legendgroup", parent_name="scatterternary", **kwargs ): super(LegendgroupValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="idssrc", parent_name="scatterternary", **kwargs): super(IdssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ids", parent_name="scatterternary", **kwargs): super(IdsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class HovertextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="hovertextsrc", parent_name="scatterternary", **kwargs ): super(HovertextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertext", parent_name="scatterternary", **kwargs): super(HovertextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="hovertemplatesrc", parent_name="scatterternary", **kwargs ): super(HovertemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="hovertemplate", parent_name="scatterternary", **kwargs ): super(HovertemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoveronValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="hoveron", parent_name="scatterternary", **kwargs): super(HoveronValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), flags=kwargs.pop("flags", ["points", "fills"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverlabelValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="hoverlabel", parent_name="scatterternary", **kwargs ): super(HoverlabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Hoverlabel"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """, ), **kwargs ) import _plotly_utils.basevalidators class HoverinfosrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="hoverinfosrc", parent_name="scatterternary", **kwargs ): super(HoverinfosrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverinfoValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="hoverinfo", parent_name="scatterternary", **kwargs): super(HoverinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), extras=kwargs.pop("extras", ["all", "none", "skip"]), flags=kwargs.pop("flags", ["a", "b", "c", "text", "name"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FillcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="fillcolor", parent_name="scatterternary", **kwargs): super(FillcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FillValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="fill", parent_name="scatterternary", **kwargs): super(FillValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "toself", "tonext"]), **kwargs ) import _plotly_utils.basevalidators class CustomdatasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="customdatasrc", parent_name="scatterternary", **kwargs ): super(CustomdatasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdataValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="customdata", parent_name="scatterternary", **kwargs ): super(CustomdataValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class CsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="csrc", parent_name="scatterternary", **kwargs): super(CsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ConnectgapsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="connectgaps", parent_name="scatterternary", **kwargs ): super(ConnectgapsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CliponaxisValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="cliponaxis", parent_name="scatterternary", **kwargs ): super(CliponaxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="c", parent_name="scatterternary", **kwargs): super(CValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class BsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="bsrc", parent_name="scatterternary", **kwargs): super(BsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="b", parent_name="scatterternary", **kwargs): super(BValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class AsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="asrc", parent_name="scatterternary", **kwargs): super(AsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="a", parent_name="scatterternary", **kwargs): super(AValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterternary/line/0000755000175000017500000000000013573746614023765 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterternary/line/__init__.py0000644000175000017500000000510713573721543026073 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="width", parent_name="scatterternary.line", **kwargs ): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SmoothingValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="smoothing", parent_name="scatterternary.line", **kwargs ): super(SmoothingValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), max=kwargs.pop("max", 1.3), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShapeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="shape", parent_name="scatterternary.line", **kwargs ): super(ShapeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["linear", "spline"]), **kwargs ) import _plotly_utils.basevalidators class DashValidator(_plotly_utils.basevalidators.DashValidator): def __init__(self, plotly_name="dash", parent_name="scatterternary.line", **kwargs): super(DashValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", ["solid", "dot", "dash", "longdash", "dashdot", "longdashdot"] ), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scatterternary.line", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterternary/selected/0000755000175000017500000000000013573746614024626 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterternary/selected/textfont/0000755000175000017500000000000013573746614026501 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterternary/selected/textfont/__init__.py0000644000175000017500000000076313573721543030612 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scatterternary.selected.textfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterternary/selected/marker/0000755000175000017500000000000013573746614026107 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterternary/selected/marker/__init__.py0000644000175000017500000000306613573721543030217 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scatterternary.selected.marker", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="opacity", parent_name="scatterternary.selected.marker", **kwargs ): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scatterternary.selected.marker", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterternary/selected/__init__.py0000644000175000017500000000256713573721543026743 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="textfont", parent_name="scatterternary.selected", **kwargs ): super(TextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Textfont"), data_docs=kwargs.pop( "data_docs", """ color Sets the text font color of selected points. """, ), **kwargs ) import _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="marker", parent_name="scatterternary.selected", **kwargs ): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. size Sets the marker size of selected points. """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterpolargl/0000755000175000017500000000000013573746614023012 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterpolargl/unselected/0000755000175000017500000000000013573746614025145 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterpolargl/unselected/textfont/0000755000175000017500000000000013573746614027020 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterpolargl/unselected/textfont/__init__.py0000644000175000017500000000076513573721543031133 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scatterpolargl.unselected.textfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterpolargl/unselected/marker/0000755000175000017500000000000013573746614026426 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterpolargl/unselected/marker/__init__.py0000644000175000017500000000312413573721543030531 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scatterpolargl.unselected.marker", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="opacity", parent_name="scatterpolargl.unselected.marker", **kwargs ): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scatterpolargl.unselected.marker", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterpolargl/unselected/__init__.py0000644000175000017500000000313313573721543027250 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="textfont", parent_name="scatterpolargl.unselected", **kwargs ): super(TextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Textfont"), data_docs=kwargs.pop( "data_docs", """ color Sets the text font color of unselected points, applied only when a selection exists. """, ), **kwargs ) import _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="marker", parent_name="scatterpolargl.unselected", **kwargs ): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. size Sets the marker size of unselected points, applied only when a selection exists. """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterpolargl/textfont/0000755000175000017500000000000013573746614024665 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterpolargl/textfont/__init__.py0000644000175000017500000000604513573721543026775 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="scatterpolargl.textfont", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scatterpolargl.textfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="scatterpolargl.textfont", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="scatterpolargl.textfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="scatterpolargl.textfont", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scatterpolargl.textfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterpolargl/hoverlabel/0000755000175000017500000000000013573746614025135 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterpolargl/hoverlabel/__init__.py0000644000175000017500000001372613573721543027251 0ustar noahfxnoahfximport _plotly_utils.basevalidators class NamelengthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="namelengthsrc", parent_name="scatterpolargl.hoverlabel", **kwargs ): super(NamelengthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NamelengthValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="namelength", parent_name="scatterpolargl.hoverlabel", **kwargs ): super(NamelengthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", -1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="scatterpolargl.hoverlabel", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class BordercolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bordercolorsrc", parent_name="scatterpolargl.hoverlabel", **kwargs ): super(BordercolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="scatterpolargl.hoverlabel", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bgcolorsrc", parent_name="scatterpolargl.hoverlabel", **kwargs ): super(BgcolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="scatterpolargl.hoverlabel", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AlignsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="alignsrc", parent_name="scatterpolargl.hoverlabel", **kwargs ): super(AlignsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="align", parent_name="scatterpolargl.hoverlabel", **kwargs ): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "right", "auto"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterpolargl/hoverlabel/font/0000755000175000017500000000000013573746614026103 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterpolargl/hoverlabel/font/__init__.py0000644000175000017500000000630713573721543030214 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="scatterpolargl.hoverlabel.font", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scatterpolargl.hoverlabel.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="scatterpolargl.hoverlabel.font", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="scatterpolargl.hoverlabel.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="scatterpolargl.hoverlabel.font", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scatterpolargl.hoverlabel.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterpolargl/marker/0000755000175000017500000000000013573746614024273 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterpolargl/marker/colorbar/0000755000175000017500000000000013573746614026076 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterpolargl/marker/colorbar/tickformatstop/0000755000175000017500000000000013573746614031147 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterpolargl/marker/colorbar/tickformatstop/__init__.py0000644000175000017500000000543713573721543033263 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="value", parent_name="scatterpolargl.marker.colorbar.tickformatstop", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="scatterpolargl.marker.colorbar.tickformatstop", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="scatterpolargl.marker.colorbar.tickformatstop", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EnabledValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="enabled", parent_name="scatterpolargl.marker.colorbar.tickformatstop", **kwargs ): super(EnabledValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DtickrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="dtickrange", parent_name="scatterpolargl.marker.colorbar.tickformatstop", **kwargs ): super(DtickrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "calc"}, {"valType": "any", "editType": "calc"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterpolargl/marker/colorbar/title/0000755000175000017500000000000013573746614027217 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterpolargl/marker/colorbar/title/__init__.py0000644000175000017500000000506513573721543031330 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="text", parent_name="scatterpolargl.marker.colorbar.title", **kwargs ): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SideValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="side", parent_name="scatterpolargl.marker.colorbar.title", **kwargs ): super(SideValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["right", "top", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="scatterpolargl.marker.colorbar.title", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterpolargl/marker/colorbar/title/font/0000755000175000017500000000000013573746614030165 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterpolargl/marker/colorbar/title/font/__init__.py0000644000175000017500000000317713573721543032300 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scatterpolargl.marker.colorbar.title.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="scatterpolargl.marker.colorbar.title.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scatterpolargl.marker.colorbar.title.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterpolargl/marker/colorbar/__init__.py0000644000175000017500000006261013573721543030206 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ypad", parent_name="scatterpolargl.marker.colorbar", **kwargs ): super(YpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class YanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="yanchor", parent_name="scatterpolargl.marker.colorbar", **kwargs ): super(YanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["top", "middle", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="y", parent_name="scatterpolargl.marker.colorbar", **kwargs ): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="xpad", parent_name="scatterpolargl.marker.colorbar", **kwargs ): super(XpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="xanchor", parent_name="scatterpolargl.marker.colorbar", **kwargs ): super(XanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "center", "right"]), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="x", parent_name="scatterpolargl.marker.colorbar", **kwargs ): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TitleValidator(_plotly_utils.basevalidators.TitleValidator): def __init__( self, plotly_name="title", parent_name="scatterpolargl.marker.colorbar", **kwargs ): super(TitleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Title"), data_docs=kwargs.pop( "data_docs", """ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """, ), **kwargs ) import _plotly_utils.basevalidators class TickwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="tickwidth", parent_name="scatterpolargl.marker.colorbar", **kwargs ): super(TickwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickvalssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="tickvalssrc", parent_name="scatterpolargl.marker.colorbar", **kwargs ): super(TickvalssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickvalsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="tickvals", parent_name="scatterpolargl.marker.colorbar", **kwargs ): super(TickvalsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="ticktextsrc", parent_name="scatterpolargl.marker.colorbar", **kwargs ): super(TicktextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicktextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="ticktext", parent_name="scatterpolargl.marker.colorbar", **kwargs ): super(TicktextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="ticksuffix", parent_name="scatterpolargl.marker.colorbar", **kwargs ): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TicksValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="ticks", parent_name="scatterpolargl.marker.colorbar", **kwargs ): super(TicksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["outside", "inside", ""]), **kwargs ) import _plotly_utils.basevalidators class TickprefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickprefix", parent_name="scatterpolargl.marker.colorbar", **kwargs ): super(TickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="tickmode", parent_name="scatterpolargl.marker.colorbar", **kwargs ): super(TickmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "linear", "array"]), **kwargs ) import _plotly_utils.basevalidators class TicklenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ticklen", parent_name="scatterpolargl.marker.colorbar", **kwargs ): super(TicklenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickformatstopValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickformatstopdefaults", parent_name="scatterpolargl.marker.colorbar", **kwargs ): super(TickformatstopValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatstopsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="tickformatstops", parent_name="scatterpolargl.marker.colorbar", **kwargs ): super(TickformatstopsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickformat", parent_name="scatterpolargl.marker.colorbar", **kwargs ): super(TickformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickfont", parent_name="scatterpolargl.marker.colorbar", **kwargs ): super(TickfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class TickcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="tickcolor", parent_name="scatterpolargl.marker.colorbar", **kwargs ): super(TickcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__( self, plotly_name="tickangle", parent_name="scatterpolargl.marker.colorbar", **kwargs ): super(TickangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="tick0", parent_name="scatterpolargl.marker.colorbar", **kwargs ): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ThicknessmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="thicknessmode", parent_name="scatterpolargl.marker.colorbar", **kwargs ): super(ThicknessmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="thickness", parent_name="scatterpolargl.marker.colorbar", **kwargs ): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowticksuffixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showticksuffix", parent_name="scatterpolargl.marker.colorbar", **kwargs ): super(ShowticksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowtickprefixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showtickprefix", parent_name="scatterpolargl.marker.colorbar", **kwargs ): super(ShowtickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowticklabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showticklabels", parent_name="scatterpolargl.marker.colorbar", **kwargs ): super(ShowticklabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowexponentValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showexponent", parent_name="scatterpolargl.marker.colorbar", **kwargs ): super(ShowexponentValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class SeparatethousandsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="separatethousands", parent_name="scatterpolargl.marker.colorbar", **kwargs ): super(SeparatethousandsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="outlinewidth", parent_name="scatterpolargl.marker.colorbar", **kwargs ): super(OutlinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="outlinecolor", parent_name="scatterpolargl.marker.colorbar", **kwargs ): super(OutlinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NticksValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="nticks", parent_name="scatterpolargl.marker.colorbar", **kwargs ): super(NticksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LenmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="lenmode", parent_name="scatterpolargl.marker.colorbar", **kwargs ): super(LenmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class LenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="len", parent_name="scatterpolargl.marker.colorbar", **kwargs ): super(LenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ExponentformatValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="exponentformat", parent_name="scatterpolargl.marker.colorbar", **kwargs ): super(ExponentformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "e", "E", "power", "SI", "B"]), **kwargs ) import _plotly_utils.basevalidators class DtickValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="dtick", parent_name="scatterpolargl.marker.colorbar", **kwargs ): super(DtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BorderwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="borderwidth", parent_name="scatterpolargl.marker.colorbar", **kwargs ): super(BorderwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="scatterpolargl.marker.colorbar", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="scatterpolargl.marker.colorbar", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterpolargl/marker/colorbar/tickfont/0000755000175000017500000000000013573746614027717 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterpolargl/marker/colorbar/tickfont/__init__.py0000644000175000017500000000317113573721543032024 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scatterpolargl.marker.colorbar.tickfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="scatterpolargl.marker.colorbar.tickfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scatterpolargl.marker.colorbar.tickfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterpolargl/marker/__init__.py0000644000175000017500000010511313573721543026377 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SymbolsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="symbolsrc", parent_name="scatterpolargl.marker", **kwargs ): super(SymbolsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SymbolValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="symbol", parent_name="scatterpolargl.marker", **kwargs ): super(SymbolValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", [ 0, "circle", 100, "circle-open", 200, "circle-dot", 300, "circle-open-dot", 1, "square", 101, "square-open", 201, "square-dot", 301, "square-open-dot", 2, "diamond", 102, "diamond-open", 202, "diamond-dot", 302, "diamond-open-dot", 3, "cross", 103, "cross-open", 203, "cross-dot", 303, "cross-open-dot", 4, "x", 104, "x-open", 204, "x-dot", 304, "x-open-dot", 5, "triangle-up", 105, "triangle-up-open", 205, "triangle-up-dot", 305, "triangle-up-open-dot", 6, "triangle-down", 106, "triangle-down-open", 206, "triangle-down-dot", 306, "triangle-down-open-dot", 7, "triangle-left", 107, "triangle-left-open", 207, "triangle-left-dot", 307, "triangle-left-open-dot", 8, "triangle-right", 108, "triangle-right-open", 208, "triangle-right-dot", 308, "triangle-right-open-dot", 9, "triangle-ne", 109, "triangle-ne-open", 209, "triangle-ne-dot", 309, "triangle-ne-open-dot", 10, "triangle-se", 110, "triangle-se-open", 210, "triangle-se-dot", 310, "triangle-se-open-dot", 11, "triangle-sw", 111, "triangle-sw-open", 211, "triangle-sw-dot", 311, "triangle-sw-open-dot", 12, "triangle-nw", 112, "triangle-nw-open", 212, "triangle-nw-dot", 312, "triangle-nw-open-dot", 13, "pentagon", 113, "pentagon-open", 213, "pentagon-dot", 313, "pentagon-open-dot", 14, "hexagon", 114, "hexagon-open", 214, "hexagon-dot", 314, "hexagon-open-dot", 15, "hexagon2", 115, "hexagon2-open", 215, "hexagon2-dot", 315, "hexagon2-open-dot", 16, "octagon", 116, "octagon-open", 216, "octagon-dot", 316, "octagon-open-dot", 17, "star", 117, "star-open", 217, "star-dot", 317, "star-open-dot", 18, "hexagram", 118, "hexagram-open", 218, "hexagram-dot", 318, "hexagram-open-dot", 19, "star-triangle-up", 119, "star-triangle-up-open", 219, "star-triangle-up-dot", 319, "star-triangle-up-open-dot", 20, "star-triangle-down", 120, "star-triangle-down-open", 220, "star-triangle-down-dot", 320, "star-triangle-down-open-dot", 21, "star-square", 121, "star-square-open", 221, "star-square-dot", 321, "star-square-open-dot", 22, "star-diamond", 122, "star-diamond-open", 222, "star-diamond-dot", 322, "star-diamond-open-dot", 23, "diamond-tall", 123, "diamond-tall-open", 223, "diamond-tall-dot", 323, "diamond-tall-open-dot", 24, "diamond-wide", 124, "diamond-wide-open", 224, "diamond-wide-dot", 324, "diamond-wide-open-dot", 25, "hourglass", 125, "hourglass-open", 26, "bowtie", 126, "bowtie-open", 27, "circle-cross", 127, "circle-cross-open", 28, "circle-x", 128, "circle-x-open", 29, "square-cross", 129, "square-cross-open", 30, "square-x", 130, "square-x-open", 31, "diamond-cross", 131, "diamond-cross-open", 32, "diamond-x", 132, "diamond-x-open", 33, "cross-thin", 133, "cross-thin-open", 34, "x-thin", 134, "x-thin-open", 35, "asterisk", 135, "asterisk-open", 36, "hash", 136, "hash-open", 236, "hash-dot", 336, "hash-open-dot", 37, "y-up", 137, "y-up-open", 38, "y-down", 138, "y-down-open", 39, "y-left", 139, "y-left-open", 40, "y-right", 140, "y-right-open", 41, "line-ew", 141, "line-ew-open", 42, "line-ns", 142, "line-ns-open", 43, "line-ne", 143, "line-ne-open", 44, "line-nw", 144, "line-nw-open", ], ), **kwargs ) import _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="scatterpolargl.marker", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizerefValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="sizeref", parent_name="scatterpolargl.marker", **kwargs ): super(SizerefValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SizemodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="sizemode", parent_name="scatterpolargl.marker", **kwargs ): super(SizemodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["diameter", "area"]), **kwargs ) import _plotly_utils.basevalidators class SizeminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="sizemin", parent_name="scatterpolargl.marker", **kwargs ): super(SizeminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scatterpolargl.marker", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showscale", parent_name="scatterpolargl.marker", **kwargs ): super(ShowscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ReversescaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="reversescale", parent_name="scatterpolargl.marker", **kwargs ): super(ReversescaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacitysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="opacitysrc", parent_name="scatterpolargl.marker", **kwargs ): super(OpacitysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="opacity", parent_name="scatterpolargl.marker", **kwargs ): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="line", parent_name="scatterpolargl.marker", **kwargs ): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,R eds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Black body,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . """, ), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="scatterpolargl.marker", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__( self, plotly_name="colorscale", parent_name="scatterpolargl.marker", **kwargs ): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"autocolorscale": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorBarValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="colorbar", parent_name="scatterpolargl.marker", **kwargs ): super(ColorBarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "ColorBar"), data_docs=kwargs.pop( "data_docs", """ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.scatterpolargl. marker.colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.scatterpolargl.marker.colorbar.tickformatstop defaults), sets the default property values to use for elements of scatterpolargl.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.scatterpolargl.marker.colo rbar.Title instance or dict with compatible properties titlefont Deprecated: Please use scatterpolargl.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use scatterpolargl.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """, ), **kwargs ) import _plotly_utils.basevalidators class ColoraxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__( self, plotly_name="coloraxis", parent_name="scatterpolargl.marker", **kwargs ): super(ColoraxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", None), edit_type=kwargs.pop("edit_type", "calc"), regex=kwargs.pop("regex", "/^coloraxis([2-9]|[1-9][0-9]+)?$/"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scatterpolargl.marker", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), colorscale_path=kwargs.pop( "colorscale_path", "scatterpolargl.marker.colorscale" ), **kwargs ) import _plotly_utils.basevalidators class CminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="cmin", parent_name="scatterpolargl.marker", **kwargs ): super(CminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmidValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="cmid", parent_name="scatterpolargl.marker", **kwargs ): super(CmidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="cmax", parent_name="scatterpolargl.marker", **kwargs ): super(CmaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CautoValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="cauto", parent_name="scatterpolargl.marker", **kwargs ): super(CautoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AutocolorscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="autocolorscale", parent_name="scatterpolargl.marker", **kwargs ): super(AutocolorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterpolargl/marker/line/0000755000175000017500000000000013573746614025222 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterpolargl/marker/line/__init__.py0000644000175000017500000001473413573721543027336 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="widthsrc", parent_name="scatterpolargl.marker.line", **kwargs ): super(WidthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="width", parent_name="scatterpolargl.marker.line", **kwargs ): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ReversescaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="reversescale", parent_name="scatterpolargl.marker.line", **kwargs ): super(ReversescaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="scatterpolargl.marker.line", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__( self, plotly_name="colorscale", parent_name="scatterpolargl.marker.line", **kwargs ): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"autocolorscale": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColoraxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__( self, plotly_name="coloraxis", parent_name="scatterpolargl.marker.line", **kwargs ): super(ColoraxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", None), edit_type=kwargs.pop("edit_type", "calc"), regex=kwargs.pop("regex", "/^coloraxis([2-9]|[1-9][0-9]+)?$/"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scatterpolargl.marker.line", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), colorscale_path=kwargs.pop( "colorscale_path", "scatterpolargl.marker.line.colorscale" ), **kwargs ) import _plotly_utils.basevalidators class CminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="cmin", parent_name="scatterpolargl.marker.line", **kwargs ): super(CminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmidValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="cmid", parent_name="scatterpolargl.marker.line", **kwargs ): super(CmidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="cmax", parent_name="scatterpolargl.marker.line", **kwargs ): super(CmaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CautoValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="cauto", parent_name="scatterpolargl.marker.line", **kwargs ): super(CautoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AutocolorscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="autocolorscale", parent_name="scatterpolargl.marker.line", **kwargs ): super(AutocolorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterpolargl/stream/0000755000175000017500000000000013573746614024305 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterpolargl/stream/__init__.py0000644000175000017500000000213613573721543026412 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TokenValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="token", parent_name="scatterpolargl.stream", **kwargs ): super(TokenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "info"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class MaxpointsValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="maxpoints", parent_name="scatterpolargl.stream", **kwargs ): super(MaxpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 10000), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterpolargl/__init__.py0000644000175000017500000010236413573721544025124 0ustar noahfxnoahfximport _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="visible", parent_name="scatterpolargl", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "legendonly"]), **kwargs ) import _plotly_utils.basevalidators class UnselectedValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="unselected", parent_name="scatterpolargl", **kwargs ): super(UnselectedValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Unselected"), data_docs=kwargs.pop( "data_docs", """ marker plotly.graph_objects.scatterpolargl.unselected. Marker instance or dict with compatible properties textfont plotly.graph_objects.scatterpolargl.unselected. Textfont instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="uirevision", parent_name="scatterpolargl", **kwargs ): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UidValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="uid", parent_name="scatterpolargl", **kwargs): super(UidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ThetaunitValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="thetaunit", parent_name="scatterpolargl", **kwargs): super(ThetaunitValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["radians", "degrees", "gradians"]), **kwargs ) import _plotly_utils.basevalidators class ThetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="thetasrc", parent_name="scatterpolargl", **kwargs): super(ThetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class Theta0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="theta0", parent_name="scatterpolargl", **kwargs): super(Theta0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ThetaValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="theta", parent_name="scatterpolargl", **kwargs): super(ThetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TexttemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="texttemplatesrc", parent_name="scatterpolargl", **kwargs ): super(TexttemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TexttemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="texttemplate", parent_name="scatterpolargl", **kwargs ): super(TexttemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="textsrc", parent_name="scatterpolargl", **kwargs): super(TextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextpositionsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="textpositionsrc", parent_name="scatterpolargl", **kwargs ): super(TextpositionsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextpositionValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="textposition", parent_name="scatterpolargl", **kwargs ): super(TextpositionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", [ "top left", "top center", "top right", "middle left", "middle center", "middle right", "bottom left", "bottom center", "bottom right", ], ), **kwargs ) import _plotly_utils.basevalidators class TextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="textfont", parent_name="scatterpolargl", **kwargs): super(TextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Textfont"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="text", parent_name="scatterpolargl", **kwargs): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SubplotValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="subplot", parent_name="scatterpolargl", **kwargs): super(SubplotValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "polar"), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class StreamValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="stream", parent_name="scatterpolargl", **kwargs): super(StreamValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Stream"), data_docs=kwargs.pop( "data_docs", """ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """, ), **kwargs ) import _plotly_utils.basevalidators class ShowlegendValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showlegend", parent_name="scatterpolargl", **kwargs ): super(ShowlegendValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SelectedpointsValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="selectedpoints", parent_name="scatterpolargl", **kwargs ): super(SelectedpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SelectedValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="selected", parent_name="scatterpolargl", **kwargs): super(SelectedValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Selected"), data_docs=kwargs.pop( "data_docs", """ marker plotly.graph_objects.scatterpolargl.selected.Ma rker instance or dict with compatible properties textfont plotly.graph_objects.scatterpolargl.selected.Te xtfont instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class RsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="rsrc", parent_name="scatterpolargl", **kwargs): super(RsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class R0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="r0", parent_name="scatterpolargl", **kwargs): super(R0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class RValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="r", parent_name="scatterpolargl", **kwargs): super(RValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="scatterpolargl", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="scatterpolargl", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ModeValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="mode", parent_name="scatterpolargl", **kwargs): super(ModeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), extras=kwargs.pop("extras", ["none"]), flags=kwargs.pop("flags", ["lines", "markers", "text"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="metasrc", parent_name="scatterpolargl", **kwargs): super(MetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetaValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="meta", parent_name="scatterpolargl", **kwargs): super(MetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="marker", parent_name="scatterpolargl", **kwargs): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.scatterpolargl.marker.Colo rBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . line plotly.graph_objects.scatterpolargl.marker.Line instance or dict with compatible properties opacity Sets the marker opacity. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. size Sets the marker size (in px). sizemin Has an effect only if `marker.size` is set to a numerical array. Sets the minimum size (in px) of the rendered marker points. sizemode Has an effect only if `marker.size` is set to a numerical array. Sets the rule for which the data in `size` is converted to pixels. sizeref Has an effect only if `marker.size` is set to a numerical array. Sets the scale factor used to determine the rendered size of marker points. Use with `sizemin` and `sizemode`. sizesrc Sets the source reference on plot.ly for size . symbol Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot- open" to a symbol name. symbolsrc Sets the source reference on plot.ly for symbol . """, ), **kwargs ) import _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="line", parent_name="scatterpolargl", **kwargs): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ color Sets the line color. dash Sets the style of the lines. shape Determines the line shape. The values correspond to step-wise line shapes. width Sets the line width (in px). """, ), **kwargs ) import _plotly_utils.basevalidators class LegendgroupValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="legendgroup", parent_name="scatterpolargl", **kwargs ): super(LegendgroupValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="idssrc", parent_name="scatterpolargl", **kwargs): super(IdssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ids", parent_name="scatterpolargl", **kwargs): super(IdsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class HovertextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="hovertextsrc", parent_name="scatterpolargl", **kwargs ): super(HovertextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertext", parent_name="scatterpolargl", **kwargs): super(HovertextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="hovertemplatesrc", parent_name="scatterpolargl", **kwargs ): super(HovertemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="hovertemplate", parent_name="scatterpolargl", **kwargs ): super(HovertemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverlabelValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="hoverlabel", parent_name="scatterpolargl", **kwargs ): super(HoverlabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Hoverlabel"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """, ), **kwargs ) import _plotly_utils.basevalidators class HoverinfosrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="hoverinfosrc", parent_name="scatterpolargl", **kwargs ): super(HoverinfosrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverinfoValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="hoverinfo", parent_name="scatterpolargl", **kwargs): super(HoverinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), extras=kwargs.pop("extras", ["all", "none", "skip"]), flags=kwargs.pop("flags", ["r", "theta", "text", "name"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FillcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="fillcolor", parent_name="scatterpolargl", **kwargs): super(FillcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FillValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="fill", parent_name="scatterpolargl", **kwargs): super(FillValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", [ "none", "tozeroy", "tozerox", "tonexty", "tonextx", "toself", "tonext", ], ), **kwargs ) import _plotly_utils.basevalidators class DthetaValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="dtheta", parent_name="scatterpolargl", **kwargs): super(DthetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DrValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="dr", parent_name="scatterpolargl", **kwargs): super(DrValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdatasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="customdatasrc", parent_name="scatterpolargl", **kwargs ): super(CustomdatasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdataValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="customdata", parent_name="scatterpolargl", **kwargs ): super(CustomdataValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class ConnectgapsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="connectgaps", parent_name="scatterpolargl", **kwargs ): super(ConnectgapsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterpolargl/line/0000755000175000017500000000000013573746614023741 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterpolargl/line/__init__.py0000644000175000017500000000406013573721543026044 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="width", parent_name="scatterpolargl.line", **kwargs ): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShapeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="shape", parent_name="scatterpolargl.line", **kwargs ): super(ShapeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["linear", "hv", "vh", "hvh", "vhv"]), **kwargs ) import _plotly_utils.basevalidators class DashValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="dash", parent_name="scatterpolargl.line", **kwargs): super(DashValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", ["solid", "dot", "dash", "longdash", "dashdot", "longdashdot"] ), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scatterpolargl.line", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterpolargl/selected/0000755000175000017500000000000013573746614024602 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterpolargl/selected/textfont/0000755000175000017500000000000013573746614026455 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterpolargl/selected/textfont/__init__.py0000644000175000017500000000076313573721543030566 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scatterpolargl.selected.textfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterpolargl/selected/marker/0000755000175000017500000000000013573746614026063 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterpolargl/selected/marker/__init__.py0000644000175000017500000000306613573721543030173 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scatterpolargl.selected.marker", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="opacity", parent_name="scatterpolargl.selected.marker", **kwargs ): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scatterpolargl.selected.marker", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterpolargl/selected/__init__.py0000644000175000017500000000256713573721543026717 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="textfont", parent_name="scatterpolargl.selected", **kwargs ): super(TextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Textfont"), data_docs=kwargs.pop( "data_docs", """ color Sets the text font color of selected points. """, ), **kwargs ) import _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="marker", parent_name="scatterpolargl.selected", **kwargs ): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. size Sets the marker size of selected points. """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/histogram2d/0000755000175000017500000000000013573746614022207 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/histogram2d/ybins/0000755000175000017500000000000013573746614023333 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/histogram2d/ybins/__init__.py0000644000175000017500000000245413573721537025446 0ustar noahfxnoahfximport _plotly_utils.basevalidators class StartValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="start", parent_name="histogram2d.ybins", **kwargs): super(StartValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="size", parent_name="histogram2d.ybins", **kwargs): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EndValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="end", parent_name="histogram2d.ybins", **kwargs): super(EndValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/histogram2d/hoverlabel/0000755000175000017500000000000013573746614024332 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/histogram2d/hoverlabel/__init__.py0000644000175000017500000001356313573721537026450 0ustar noahfxnoahfximport _plotly_utils.basevalidators class NamelengthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="namelengthsrc", parent_name="histogram2d.hoverlabel", **kwargs ): super(NamelengthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NamelengthValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="namelength", parent_name="histogram2d.hoverlabel", **kwargs ): super(NamelengthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", -1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="histogram2d.hoverlabel", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class BordercolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bordercolorsrc", parent_name="histogram2d.hoverlabel", **kwargs ): super(BordercolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="histogram2d.hoverlabel", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bgcolorsrc", parent_name="histogram2d.hoverlabel", **kwargs ): super(BgcolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="histogram2d.hoverlabel", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AlignsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="alignsrc", parent_name="histogram2d.hoverlabel", **kwargs ): super(AlignsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="align", parent_name="histogram2d.hoverlabel", **kwargs ): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "right", "auto"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/histogram2d/hoverlabel/font/0000755000175000017500000000000013573746614025300 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/histogram2d/hoverlabel/font/__init__.py0000644000175000017500000000615513573721537027415 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="histogram2d.hoverlabel.font", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="histogram2d.hoverlabel.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="histogram2d.hoverlabel.font", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="histogram2d.hoverlabel.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="histogram2d.hoverlabel.font", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="histogram2d.hoverlabel.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/histogram2d/colorbar/0000755000175000017500000000000013573746614024012 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/histogram2d/colorbar/tickformatstop/0000755000175000017500000000000013573746614027063 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/histogram2d/colorbar/tickformatstop/__init__.py0000644000175000017500000000542013573721537031172 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="value", parent_name="histogram2d.colorbar.tickformatstop", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="histogram2d.colorbar.tickformatstop", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="histogram2d.colorbar.tickformatstop", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EnabledValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="enabled", parent_name="histogram2d.colorbar.tickformatstop", **kwargs ): super(EnabledValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DtickrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="dtickrange", parent_name="histogram2d.colorbar.tickformatstop", **kwargs ): super(DtickrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "colorbars"}, {"valType": "any", "editType": "colorbars"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/histogram2d/colorbar/title/0000755000175000017500000000000013573746614025133 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/histogram2d/colorbar/title/__init__.py0000644000175000017500000000473113573721537027246 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="text", parent_name="histogram2d.colorbar.title", **kwargs ): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SideValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="side", parent_name="histogram2d.colorbar.title", **kwargs ): super(SideValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["right", "top", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="histogram2d.colorbar.title", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/histogram2d/colorbar/title/font/0000755000175000017500000000000013573746614026101 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/histogram2d/colorbar/title/font/__init__.py0000644000175000017500000000316013573721537030207 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="histogram2d.colorbar.title.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="histogram2d.colorbar.title.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="histogram2d.colorbar.title.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/histogram2d/colorbar/__init__.py0000644000175000017500000006053313573721540026121 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ypad", parent_name="histogram2d.colorbar", **kwargs ): super(YpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class YanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="yanchor", parent_name="histogram2d.colorbar", **kwargs ): super(YanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["top", "middle", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="y", parent_name="histogram2d.colorbar", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="xpad", parent_name="histogram2d.colorbar", **kwargs ): super(XpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="xanchor", parent_name="histogram2d.colorbar", **kwargs ): super(XanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "center", "right"]), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="x", parent_name="histogram2d.colorbar", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TitleValidator(_plotly_utils.basevalidators.TitleValidator): def __init__( self, plotly_name="title", parent_name="histogram2d.colorbar", **kwargs ): super(TitleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Title"), data_docs=kwargs.pop( "data_docs", """ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """, ), **kwargs ) import _plotly_utils.basevalidators class TickwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="tickwidth", parent_name="histogram2d.colorbar", **kwargs ): super(TickwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickvalssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="tickvalssrc", parent_name="histogram2d.colorbar", **kwargs ): super(TickvalssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickvalsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="tickvals", parent_name="histogram2d.colorbar", **kwargs ): super(TickvalsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="ticktextsrc", parent_name="histogram2d.colorbar", **kwargs ): super(TicktextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicktextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="ticktext", parent_name="histogram2d.colorbar", **kwargs ): super(TicktextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="ticksuffix", parent_name="histogram2d.colorbar", **kwargs ): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TicksValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="ticks", parent_name="histogram2d.colorbar", **kwargs ): super(TicksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["outside", "inside", ""]), **kwargs ) import _plotly_utils.basevalidators class TickprefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickprefix", parent_name="histogram2d.colorbar", **kwargs ): super(TickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="tickmode", parent_name="histogram2d.colorbar", **kwargs ): super(TickmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "linear", "array"]), **kwargs ) import _plotly_utils.basevalidators class TicklenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ticklen", parent_name="histogram2d.colorbar", **kwargs ): super(TicklenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickformatstopValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickformatstopdefaults", parent_name="histogram2d.colorbar", **kwargs ): super(TickformatstopValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatstopsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="tickformatstops", parent_name="histogram2d.colorbar", **kwargs ): super(TickformatstopsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickformat", parent_name="histogram2d.colorbar", **kwargs ): super(TickformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickfont", parent_name="histogram2d.colorbar", **kwargs ): super(TickfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class TickcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="tickcolor", parent_name="histogram2d.colorbar", **kwargs ): super(TickcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__( self, plotly_name="tickangle", parent_name="histogram2d.colorbar", **kwargs ): super(TickangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="tick0", parent_name="histogram2d.colorbar", **kwargs ): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ThicknessmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="thicknessmode", parent_name="histogram2d.colorbar", **kwargs ): super(ThicknessmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="thickness", parent_name="histogram2d.colorbar", **kwargs ): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowticksuffixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showticksuffix", parent_name="histogram2d.colorbar", **kwargs ): super(ShowticksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowtickprefixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showtickprefix", parent_name="histogram2d.colorbar", **kwargs ): super(ShowtickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowticklabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showticklabels", parent_name="histogram2d.colorbar", **kwargs ): super(ShowticklabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowexponentValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showexponent", parent_name="histogram2d.colorbar", **kwargs ): super(ShowexponentValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class SeparatethousandsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="separatethousands", parent_name="histogram2d.colorbar", **kwargs ): super(SeparatethousandsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="outlinewidth", parent_name="histogram2d.colorbar", **kwargs ): super(OutlinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="outlinecolor", parent_name="histogram2d.colorbar", **kwargs ): super(OutlinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NticksValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="nticks", parent_name="histogram2d.colorbar", **kwargs ): super(NticksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LenmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="lenmode", parent_name="histogram2d.colorbar", **kwargs ): super(LenmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class LenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="len", parent_name="histogram2d.colorbar", **kwargs): super(LenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ExponentformatValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="exponentformat", parent_name="histogram2d.colorbar", **kwargs ): super(ExponentformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "e", "E", "power", "SI", "B"]), **kwargs ) import _plotly_utils.basevalidators class DtickValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="dtick", parent_name="histogram2d.colorbar", **kwargs ): super(DtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BorderwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="borderwidth", parent_name="histogram2d.colorbar", **kwargs ): super(BorderwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="histogram2d.colorbar", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="histogram2d.colorbar", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/histogram2d/colorbar/tickfont/0000755000175000017500000000000013573746614025633 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/histogram2d/colorbar/tickfont/__init__.py0000644000175000017500000000307213573721537027743 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="histogram2d.colorbar.tickfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="histogram2d.colorbar.tickfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="histogram2d.colorbar.tickfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/histogram2d/marker/0000755000175000017500000000000013573746614023470 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/histogram2d/marker/__init__.py0000644000175000017500000000162513573721537025602 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="histogram2d.marker", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="color", parent_name="histogram2d.marker", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/histogram2d/stream/0000755000175000017500000000000013573746614023502 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/histogram2d/stream/__init__.py0000644000175000017500000000211213573721537025604 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TokenValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="token", parent_name="histogram2d.stream", **kwargs): super(TokenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "info"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class MaxpointsValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="maxpoints", parent_name="histogram2d.stream", **kwargs ): super(MaxpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 10000), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/histogram2d/__init__.py0000644000175000017500000012417513573721540024321 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ZsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="zsrc", parent_name="histogram2d", **kwargs): super(ZsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZsmoothValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="zsmooth", parent_name="histogram2d", **kwargs): super(ZsmoothValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["fast", "best", False]), **kwargs ) import _plotly_utils.basevalidators class ZminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="zmin", parent_name="histogram2d", **kwargs): super(ZminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"zauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZmidValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="zmid", parent_name="histogram2d", **kwargs): super(ZmidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZmaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="zmax", parent_name="histogram2d", **kwargs): super(ZmaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"zauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZhoverformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="zhoverformat", parent_name="histogram2d", **kwargs): super(ZhoverformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ZautoValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="zauto", parent_name="histogram2d", **kwargs): super(ZautoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="z", parent_name="histogram2d", **kwargs): super(ZValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class YsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="ysrc", parent_name="histogram2d", **kwargs): super(YsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YgapValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="ygap", parent_name="histogram2d", **kwargs): super(YgapValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class YcalendarValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="ycalendar", parent_name="histogram2d", **kwargs): super(YcalendarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "gregorian", "chinese", "coptic", "discworld", "ethiopian", "hebrew", "islamic", "julian", "mayan", "nanakshahi", "nepali", "persian", "jalali", "taiwan", "thai", "ummalqura", ], ), **kwargs ) import _plotly_utils.basevalidators class YBinsValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="ybins", parent_name="histogram2d", **kwargs): super(YBinsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "YBins"), data_docs=kwargs.pop( "data_docs", """ end Sets the end value for the y axis bins. The last bin may not end exactly at this value, we increment the bin edge by `size` from `start` until we reach or exceed `end`. Defaults to the maximum data value. Like `start`, for dates use a date string, and for category data `end` is based on the category serial numbers. size Sets the size of each y axis bin. Default behavior: If `nbinsy` is 0 or omitted, we choose a nice round bin size such that the number of bins is about the same as the typical number of samples in each bin. If `nbinsy` is provided, we choose a nice round bin size giving no more than that many bins. For date data, use milliseconds or "M" for months, as in `axis.dtick`. For category data, the number of categories to bin together (always defaults to 1). start Sets the starting value for the y axis bins. Defaults to the minimum data value, shifted down if necessary to make nice round values and to remove ambiguous bin edges. For example, if most of the data is integers we shift the bin edges 0.5 down, so a `size` of 5 would have a default `start` of -0.5, so it is clear that 0-4 are in the first bin, 5-9 in the second, but continuous data gets a start of 0 and bins [0,5), [5,10) etc. Dates behave similarly, and `start` should be a date string. For category data, `start` is based on the category serial numbers, and defaults to -0.5. """, ), **kwargs ) import _plotly_utils.basevalidators class YbingroupValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="ybingroup", parent_name="histogram2d", **kwargs): super(YbingroupValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YAxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="yaxis", parent_name="histogram2d", **kwargs): super(YAxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "y"), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="y", parent_name="histogram2d", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class XsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="xsrc", parent_name="histogram2d", **kwargs): super(XsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XgapValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="xgap", parent_name="histogram2d", **kwargs): super(XgapValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XcalendarValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="xcalendar", parent_name="histogram2d", **kwargs): super(XcalendarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "gregorian", "chinese", "coptic", "discworld", "ethiopian", "hebrew", "islamic", "julian", "mayan", "nanakshahi", "nepali", "persian", "jalali", "taiwan", "thai", "ummalqura", ], ), **kwargs ) import _plotly_utils.basevalidators class XBinsValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="xbins", parent_name="histogram2d", **kwargs): super(XBinsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "XBins"), data_docs=kwargs.pop( "data_docs", """ end Sets the end value for the x axis bins. The last bin may not end exactly at this value, we increment the bin edge by `size` from `start` until we reach or exceed `end`. Defaults to the maximum data value. Like `start`, for dates use a date string, and for category data `end` is based on the category serial numbers. size Sets the size of each x axis bin. Default behavior: If `nbinsx` is 0 or omitted, we choose a nice round bin size such that the number of bins is about the same as the typical number of samples in each bin. If `nbinsx` is provided, we choose a nice round bin size giving no more than that many bins. For date data, use milliseconds or "M" for months, as in `axis.dtick`. For category data, the number of categories to bin together (always defaults to 1). start Sets the starting value for the x axis bins. Defaults to the minimum data value, shifted down if necessary to make nice round values and to remove ambiguous bin edges. For example, if most of the data is integers we shift the bin edges 0.5 down, so a `size` of 5 would have a default `start` of -0.5, so it is clear that 0-4 are in the first bin, 5-9 in the second, but continuous data gets a start of 0 and bins [0,5), [5,10) etc. Dates behave similarly, and `start` should be a date string. For category data, `start` is based on the category serial numbers, and defaults to -0.5. """, ), **kwargs ) import _plotly_utils.basevalidators class XbingroupValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="xbingroup", parent_name="histogram2d", **kwargs): super(XbingroupValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XAxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="xaxis", parent_name="histogram2d", **kwargs): super(XAxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "x"), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="x", parent_name="histogram2d", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="visible", parent_name="histogram2d", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "legendonly"]), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="histogram2d", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UidValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="uid", parent_name="histogram2d", **kwargs): super(UidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class StreamValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="stream", parent_name="histogram2d", **kwargs): super(StreamValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Stream"), data_docs=kwargs.pop( "data_docs", """ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """, ), **kwargs ) import _plotly_utils.basevalidators class ShowscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showscale", parent_name="histogram2d", **kwargs): super(ShowscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ReversescaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="reversescale", parent_name="histogram2d", **kwargs): super(ReversescaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="histogram2d", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NbinsyValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="nbinsy", parent_name="histogram2d", **kwargs): super(NbinsyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NbinsxValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="nbinsx", parent_name="histogram2d", **kwargs): super(NbinsxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="histogram2d", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="metasrc", parent_name="histogram2d", **kwargs): super(MetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetaValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="meta", parent_name="histogram2d", **kwargs): super(MetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="marker", parent_name="histogram2d", **kwargs): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ color Sets the aggregation data. colorsrc Sets the source reference on plot.ly for color . """, ), **kwargs ) import _plotly_utils.basevalidators class IdssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="idssrc", parent_name="histogram2d", **kwargs): super(IdssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ids", parent_name="histogram2d", **kwargs): super(IdsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class HovertemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="hovertemplatesrc", parent_name="histogram2d", **kwargs ): super(HovertemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="hovertemplate", parent_name="histogram2d", **kwargs ): super(HovertemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverlabelValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="hoverlabel", parent_name="histogram2d", **kwargs): super(HoverlabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Hoverlabel"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """, ), **kwargs ) import _plotly_utils.basevalidators class HoverinfosrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hoverinfosrc", parent_name="histogram2d", **kwargs): super(HoverinfosrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverinfoValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="hoverinfo", parent_name="histogram2d", **kwargs): super(HoverinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), extras=kwargs.pop("extras", ["all", "none", "skip"]), flags=kwargs.pop("flags", ["x", "y", "z", "text", "name"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HistnormValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="histnorm", parent_name="histogram2d", **kwargs): super(HistnormValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", ["", "percent", "probability", "density", "probability density"], ), **kwargs ) import _plotly_utils.basevalidators class HistfuncValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="histfunc", parent_name="histogram2d", **kwargs): super(HistfuncValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["count", "sum", "avg", "min", "max"]), **kwargs ) import _plotly_utils.basevalidators class CustomdatasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="customdatasrc", parent_name="histogram2d", **kwargs ): super(CustomdatasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdataValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="customdata", parent_name="histogram2d", **kwargs): super(CustomdataValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__(self, plotly_name="colorscale", parent_name="histogram2d", **kwargs): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"autocolorscale": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorBarValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="colorbar", parent_name="histogram2d", **kwargs): super(ColorBarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "ColorBar"), data_docs=kwargs.pop( "data_docs", """ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.histogram2d.col orbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.histogram2d.colorbar.tickformatstopdefaults), sets the default property values to use for elements of histogram2d.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.histogram2d.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use histogram2d.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use histogram2d.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """, ), **kwargs ) import _plotly_utils.basevalidators class ColoraxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="coloraxis", parent_name="histogram2d", **kwargs): super(ColoraxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", None), edit_type=kwargs.pop("edit_type", "calc"), regex=kwargs.pop("regex", "/^coloraxis([2-9]|[1-9][0-9]+)?$/"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BingroupValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="bingroup", parent_name="histogram2d", **kwargs): super(BingroupValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AutocolorscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="autocolorscale", parent_name="histogram2d", **kwargs ): super(AutocolorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AutobinyValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="autobiny", parent_name="histogram2d", **kwargs): super(AutobinyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AutobinxValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="autobinx", parent_name="histogram2d", **kwargs): super(AutobinxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/histogram2d/xbins/0000755000175000017500000000000013573746614023332 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/histogram2d/xbins/__init__.py0000644000175000017500000000245413573721537025445 0ustar noahfxnoahfximport _plotly_utils.basevalidators class StartValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="start", parent_name="histogram2d.xbins", **kwargs): super(StartValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="size", parent_name="histogram2d.xbins", **kwargs): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EndValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="end", parent_name="histogram2d.xbins", **kwargs): super(EndValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/barpolar/0000755000175000017500000000000013573746614021566 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/barpolar/unselected/0000755000175000017500000000000013573746614023721 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/barpolar/unselected/textfont/0000755000175000017500000000000013573746614025574 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/barpolar/unselected/textfont/__init__.py0000644000175000017500000000072713573721536027707 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="barpolar.unselected.textfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/barpolar/unselected/marker/0000755000175000017500000000000013573746614025202 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/barpolar/unselected/marker/__init__.py0000644000175000017500000000177713573721536027323 0ustar noahfxnoahfximport _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="opacity", parent_name="barpolar.unselected.marker", **kwargs ): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="barpolar.unselected.marker", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/barpolar/unselected/__init__.py0000644000175000017500000000271513573721536026033 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="textfont", parent_name="barpolar.unselected", **kwargs ): super(TextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Textfont"), data_docs=kwargs.pop( "data_docs", """ color Sets the text font color of unselected points, applied only when a selection exists. """, ), **kwargs ) import _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="marker", parent_name="barpolar.unselected", **kwargs ): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/barpolar/hoverlabel/0000755000175000017500000000000013573746614023711 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/barpolar/hoverlabel/__init__.py0000644000175000017500000001343213573721536026021 0ustar noahfxnoahfximport _plotly_utils.basevalidators class NamelengthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="namelengthsrc", parent_name="barpolar.hoverlabel", **kwargs ): super(NamelengthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NamelengthValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="namelength", parent_name="barpolar.hoverlabel", **kwargs ): super(NamelengthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", -1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="font", parent_name="barpolar.hoverlabel", **kwargs): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class BordercolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bordercolorsrc", parent_name="barpolar.hoverlabel", **kwargs ): super(BordercolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="barpolar.hoverlabel", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bgcolorsrc", parent_name="barpolar.hoverlabel", **kwargs ): super(BgcolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="barpolar.hoverlabel", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AlignsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="alignsrc", parent_name="barpolar.hoverlabel", **kwargs ): super(AlignsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="align", parent_name="barpolar.hoverlabel", **kwargs ): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "right", "auto"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/barpolar/hoverlabel/font/0000755000175000017500000000000013573746614024657 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/barpolar/hoverlabel/font/__init__.py0000644000175000017500000000605313573721536026770 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="barpolar.hoverlabel.font", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="barpolar.hoverlabel.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="barpolar.hoverlabel.font", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="barpolar.hoverlabel.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="barpolar.hoverlabel.font", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="barpolar.hoverlabel.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/barpolar/marker/0000755000175000017500000000000013573746614023047 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/barpolar/marker/colorbar/0000755000175000017500000000000013573746614024652 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/barpolar/marker/colorbar/tickformatstop/0000755000175000017500000000000013573746614027723 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/barpolar/marker/colorbar/tickformatstop/__init__.py0000644000175000017500000000544413573721536032037 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="value", parent_name="barpolar.marker.colorbar.tickformatstop", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="barpolar.marker.colorbar.tickformatstop", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="barpolar.marker.colorbar.tickformatstop", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EnabledValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="enabled", parent_name="barpolar.marker.colorbar.tickformatstop", **kwargs ): super(EnabledValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DtickrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="dtickrange", parent_name="barpolar.marker.colorbar.tickformatstop", **kwargs ): super(DtickrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "colorbars"}, {"valType": "any", "editType": "colorbars"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/barpolar/marker/colorbar/title/0000755000175000017500000000000013573746614025773 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/barpolar/marker/colorbar/title/__init__.py0000644000175000017500000000474513573721536030112 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="text", parent_name="barpolar.marker.colorbar.title", **kwargs ): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SideValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="side", parent_name="barpolar.marker.colorbar.title", **kwargs ): super(SideValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["right", "top", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="barpolar.marker.colorbar.title", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/barpolar/marker/colorbar/title/font/0000755000175000017500000000000013573746614026741 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/barpolar/marker/colorbar/title/font/__init__.py0000644000175000017500000000317413573721536031053 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="barpolar.marker.colorbar.title.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="barpolar.marker.colorbar.title.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="barpolar.marker.colorbar.title.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/barpolar/marker/colorbar/__init__.py0000644000175000017500000006151113573721536026763 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ypad", parent_name="barpolar.marker.colorbar", **kwargs ): super(YpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class YanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="yanchor", parent_name="barpolar.marker.colorbar", **kwargs ): super(YanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["top", "middle", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="y", parent_name="barpolar.marker.colorbar", **kwargs ): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="xpad", parent_name="barpolar.marker.colorbar", **kwargs ): super(XpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="xanchor", parent_name="barpolar.marker.colorbar", **kwargs ): super(XanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "center", "right"]), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="x", parent_name="barpolar.marker.colorbar", **kwargs ): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TitleValidator(_plotly_utils.basevalidators.TitleValidator): def __init__( self, plotly_name="title", parent_name="barpolar.marker.colorbar", **kwargs ): super(TitleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Title"), data_docs=kwargs.pop( "data_docs", """ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """, ), **kwargs ) import _plotly_utils.basevalidators class TickwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="tickwidth", parent_name="barpolar.marker.colorbar", **kwargs ): super(TickwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickvalssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="tickvalssrc", parent_name="barpolar.marker.colorbar", **kwargs ): super(TickvalssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickvalsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="tickvals", parent_name="barpolar.marker.colorbar", **kwargs ): super(TickvalsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="ticktextsrc", parent_name="barpolar.marker.colorbar", **kwargs ): super(TicktextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicktextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="ticktext", parent_name="barpolar.marker.colorbar", **kwargs ): super(TicktextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="ticksuffix", parent_name="barpolar.marker.colorbar", **kwargs ): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TicksValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="ticks", parent_name="barpolar.marker.colorbar", **kwargs ): super(TicksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["outside", "inside", ""]), **kwargs ) import _plotly_utils.basevalidators class TickprefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickprefix", parent_name="barpolar.marker.colorbar", **kwargs ): super(TickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="tickmode", parent_name="barpolar.marker.colorbar", **kwargs ): super(TickmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "linear", "array"]), **kwargs ) import _plotly_utils.basevalidators class TicklenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ticklen", parent_name="barpolar.marker.colorbar", **kwargs ): super(TicklenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickformatstopValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickformatstopdefaults", parent_name="barpolar.marker.colorbar", **kwargs ): super(TickformatstopValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatstopsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="tickformatstops", parent_name="barpolar.marker.colorbar", **kwargs ): super(TickformatstopsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickformat", parent_name="barpolar.marker.colorbar", **kwargs ): super(TickformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickfont", parent_name="barpolar.marker.colorbar", **kwargs ): super(TickfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class TickcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="tickcolor", parent_name="barpolar.marker.colorbar", **kwargs ): super(TickcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__( self, plotly_name="tickangle", parent_name="barpolar.marker.colorbar", **kwargs ): super(TickangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="tick0", parent_name="barpolar.marker.colorbar", **kwargs ): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ThicknessmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="thicknessmode", parent_name="barpolar.marker.colorbar", **kwargs ): super(ThicknessmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="thickness", parent_name="barpolar.marker.colorbar", **kwargs ): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowticksuffixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showticksuffix", parent_name="barpolar.marker.colorbar", **kwargs ): super(ShowticksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowtickprefixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showtickprefix", parent_name="barpolar.marker.colorbar", **kwargs ): super(ShowtickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowticklabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showticklabels", parent_name="barpolar.marker.colorbar", **kwargs ): super(ShowticklabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowexponentValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showexponent", parent_name="barpolar.marker.colorbar", **kwargs ): super(ShowexponentValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class SeparatethousandsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="separatethousands", parent_name="barpolar.marker.colorbar", **kwargs ): super(SeparatethousandsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="outlinewidth", parent_name="barpolar.marker.colorbar", **kwargs ): super(OutlinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="outlinecolor", parent_name="barpolar.marker.colorbar", **kwargs ): super(OutlinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NticksValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="nticks", parent_name="barpolar.marker.colorbar", **kwargs ): super(NticksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LenmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="lenmode", parent_name="barpolar.marker.colorbar", **kwargs ): super(LenmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class LenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="len", parent_name="barpolar.marker.colorbar", **kwargs ): super(LenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ExponentformatValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="exponentformat", parent_name="barpolar.marker.colorbar", **kwargs ): super(ExponentformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "e", "E", "power", "SI", "B"]), **kwargs ) import _plotly_utils.basevalidators class DtickValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="dtick", parent_name="barpolar.marker.colorbar", **kwargs ): super(DtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BorderwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="borderwidth", parent_name="barpolar.marker.colorbar", **kwargs ): super(BorderwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="barpolar.marker.colorbar", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="barpolar.marker.colorbar", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/barpolar/marker/colorbar/tickfont/0000755000175000017500000000000013573746614026473 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/barpolar/marker/colorbar/tickfont/__init__.py0000644000175000017500000000316613573721536030606 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="barpolar.marker.colorbar.tickfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="barpolar.marker.colorbar.tickfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="barpolar.marker.colorbar.tickfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/barpolar/marker/__init__.py0000644000175000017500000005423513573721536025165 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ShowscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showscale", parent_name="barpolar.marker", **kwargs ): super(ShowscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ReversescaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="reversescale", parent_name="barpolar.marker", **kwargs ): super(ReversescaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacitysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="opacitysrc", parent_name="barpolar.marker", **kwargs ): super(OpacitysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="barpolar.marker", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="line", parent_name="barpolar.marker", **kwargs): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,R eds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Black body,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . """, ), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="colorsrc", parent_name="barpolar.marker", **kwargs): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__( self, plotly_name="colorscale", parent_name="barpolar.marker", **kwargs ): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"autocolorscale": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorBarValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="colorbar", parent_name="barpolar.marker", **kwargs): super(ColorBarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "ColorBar"), data_docs=kwargs.pop( "data_docs", """ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.barpolar.marker .colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.barpolar.marker.colorbar.tickformatstopdefaul ts), sets the default property values to use for elements of barpolar.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.barpolar.marker.colorbar.T itle instance or dict with compatible properties titlefont Deprecated: Please use barpolar.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use barpolar.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """, ), **kwargs ) import _plotly_utils.basevalidators class ColoraxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__( self, plotly_name="coloraxis", parent_name="barpolar.marker", **kwargs ): super(ColoraxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", None), edit_type=kwargs.pop("edit_type", "calc"), regex=kwargs.pop("regex", "/^coloraxis([2-9]|[1-9][0-9]+)?$/"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="barpolar.marker", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), colorscale_path=kwargs.pop("colorscale_path", "barpolar.marker.colorscale"), **kwargs ) import _plotly_utils.basevalidators class CminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmin", parent_name="barpolar.marker", **kwargs): super(CminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmidValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmid", parent_name="barpolar.marker", **kwargs): super(CmidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmax", parent_name="barpolar.marker", **kwargs): super(CmaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CautoValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="cauto", parent_name="barpolar.marker", **kwargs): super(CautoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AutocolorscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="autocolorscale", parent_name="barpolar.marker", **kwargs ): super(AutocolorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/barpolar/marker/line/0000755000175000017500000000000013573746614023776 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/barpolar/marker/line/__init__.py0000644000175000017500000001446013573721536026110 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="widthsrc", parent_name="barpolar.marker.line", **kwargs ): super(WidthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="width", parent_name="barpolar.marker.line", **kwargs ): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ReversescaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="reversescale", parent_name="barpolar.marker.line", **kwargs ): super(ReversescaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="barpolar.marker.line", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__( self, plotly_name="colorscale", parent_name="barpolar.marker.line", **kwargs ): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"autocolorscale": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColoraxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__( self, plotly_name="coloraxis", parent_name="barpolar.marker.line", **kwargs ): super(ColoraxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", None), edit_type=kwargs.pop("edit_type", "calc"), regex=kwargs.pop("regex", "/^coloraxis([2-9]|[1-9][0-9]+)?$/"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="barpolar.marker.line", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), colorscale_path=kwargs.pop( "colorscale_path", "barpolar.marker.line.colorscale" ), **kwargs ) import _plotly_utils.basevalidators class CminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="cmin", parent_name="barpolar.marker.line", **kwargs ): super(CminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmidValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="cmid", parent_name="barpolar.marker.line", **kwargs ): super(CmidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="cmax", parent_name="barpolar.marker.line", **kwargs ): super(CmaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CautoValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="cauto", parent_name="barpolar.marker.line", **kwargs ): super(CautoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AutocolorscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="autocolorscale", parent_name="barpolar.marker.line", **kwargs ): super(AutocolorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/barpolar/stream/0000755000175000017500000000000013573746614023061 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/barpolar/stream/__init__.py0000644000175000017500000000210413573721536025163 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TokenValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="token", parent_name="barpolar.stream", **kwargs): super(TokenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "info"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class MaxpointsValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="maxpoints", parent_name="barpolar.stream", **kwargs ): super(MaxpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 10000), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/barpolar/__init__.py0000644000175000017500000006616113573721536023705 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="widthsrc", parent_name="barpolar", **kwargs): super(WidthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="barpolar", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="visible", parent_name="barpolar", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "legendonly"]), **kwargs ) import _plotly_utils.basevalidators class UnselectedValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="unselected", parent_name="barpolar", **kwargs): super(UnselectedValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Unselected"), data_docs=kwargs.pop( "data_docs", """ marker plotly.graph_objects.barpolar.unselected.Marker instance or dict with compatible properties textfont plotly.graph_objects.barpolar.unselected.Textfo nt instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="barpolar", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UidValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="uid", parent_name="barpolar", **kwargs): super(UidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ThetaunitValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="thetaunit", parent_name="barpolar", **kwargs): super(ThetaunitValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["radians", "degrees", "gradians"]), **kwargs ) import _plotly_utils.basevalidators class ThetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="thetasrc", parent_name="barpolar", **kwargs): super(ThetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class Theta0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="theta0", parent_name="barpolar", **kwargs): super(Theta0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ThetaValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="theta", parent_name="barpolar", **kwargs): super(ThetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="textsrc", parent_name="barpolar", **kwargs): super(TextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="text", parent_name="barpolar", **kwargs): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SubplotValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="subplot", parent_name="barpolar", **kwargs): super(SubplotValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "polar"), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class StreamValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="stream", parent_name="barpolar", **kwargs): super(StreamValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Stream"), data_docs=kwargs.pop( "data_docs", """ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """, ), **kwargs ) import _plotly_utils.basevalidators class ShowlegendValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showlegend", parent_name="barpolar", **kwargs): super(ShowlegendValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SelectedpointsValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="selectedpoints", parent_name="barpolar", **kwargs): super(SelectedpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SelectedValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="selected", parent_name="barpolar", **kwargs): super(SelectedValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Selected"), data_docs=kwargs.pop( "data_docs", """ marker plotly.graph_objects.barpolar.selected.Marker instance or dict with compatible properties textfont plotly.graph_objects.barpolar.selected.Textfont instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class RsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="rsrc", parent_name="barpolar", **kwargs): super(RsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class R0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="r0", parent_name="barpolar", **kwargs): super(R0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class RValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="r", parent_name="barpolar", **kwargs): super(RValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="barpolar", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OffsetsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="offsetsrc", parent_name="barpolar", **kwargs): super(OffsetsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class OffsetValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="offset", parent_name="barpolar", **kwargs): super(OffsetValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="barpolar", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="metasrc", parent_name="barpolar", **kwargs): super(MetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetaValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="meta", parent_name="barpolar", **kwargs): super(MetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="marker", parent_name="barpolar", **kwargs): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.barpolar.marker.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . line plotly.graph_objects.barpolar.marker.Line instance or dict with compatible properties opacity Sets the opacity of the bars. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. """, ), **kwargs ) import _plotly_utils.basevalidators class LegendgroupValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="legendgroup", parent_name="barpolar", **kwargs): super(LegendgroupValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="idssrc", parent_name="barpolar", **kwargs): super(IdssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ids", parent_name="barpolar", **kwargs): super(IdsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class HovertextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hovertextsrc", parent_name="barpolar", **kwargs): super(HovertextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertext", parent_name="barpolar", **kwargs): super(HovertextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="hovertemplatesrc", parent_name="barpolar", **kwargs ): super(HovertemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertemplate", parent_name="barpolar", **kwargs): super(HovertemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverlabelValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="hoverlabel", parent_name="barpolar", **kwargs): super(HoverlabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Hoverlabel"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """, ), **kwargs ) import _plotly_utils.basevalidators class HoverinfosrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hoverinfosrc", parent_name="barpolar", **kwargs): super(HoverinfosrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverinfoValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="hoverinfo", parent_name="barpolar", **kwargs): super(HoverinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), extras=kwargs.pop("extras", ["all", "none", "skip"]), flags=kwargs.pop("flags", ["r", "theta", "text", "name"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DthetaValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="dtheta", parent_name="barpolar", **kwargs): super(DthetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DrValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="dr", parent_name="barpolar", **kwargs): super(DrValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdatasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="customdatasrc", parent_name="barpolar", **kwargs): super(CustomdatasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdataValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="customdata", parent_name="barpolar", **kwargs): super(CustomdataValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class BasesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="basesrc", parent_name="barpolar", **kwargs): super(BasesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BaseValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="base", parent_name="barpolar", **kwargs): super(BaseValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/barpolar/selected/0000755000175000017500000000000013573746614023356 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/barpolar/selected/textfont/0000755000175000017500000000000013573746614025231 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/barpolar/selected/textfont/__init__.py0000644000175000017500000000072513573721536027342 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="barpolar.selected.textfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/barpolar/selected/marker/0000755000175000017500000000000013573746614024637 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/barpolar/selected/marker/__init__.py0000644000175000017500000000177313573721536026754 0ustar noahfxnoahfximport _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="opacity", parent_name="barpolar.selected.marker", **kwargs ): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="barpolar.selected.marker", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/barpolar/selected/__init__.py0000644000175000017500000000242313573721536025464 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="textfont", parent_name="barpolar.selected", **kwargs ): super(TextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Textfont"), data_docs=kwargs.pop( "data_docs", """ color Sets the text font color of selected points. """, ), **kwargs ) import _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="marker", parent_name="barpolar.selected", **kwargs): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/funnelarea/0000755000175000017500000000000013573746614022104 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/funnelarea/textfont/0000755000175000017500000000000013573746614023757 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/funnelarea/textfont/__init__.py0000644000175000017500000000577713573721537026105 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="funnelarea.textfont", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="size", parent_name="funnelarea.textfont", **kwargs): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="funnelarea.textfont", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="funnelarea.textfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="funnelarea.textfont", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="funnelarea.textfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/funnelarea/title/0000755000175000017500000000000013573746614023225 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/funnelarea/title/__init__.py0000644000175000017500000000534113573721537025336 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="text", parent_name="funnelarea.title", **kwargs): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class PositionValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="position", parent_name="funnelarea.title", **kwargs ): super(PositionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["top left", "top center", "top right"]), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="font", parent_name="funnelarea.title", **kwargs): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/funnelarea/title/font/0000755000175000017500000000000013573746614024173 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/funnelarea/title/font/__init__.py0000644000175000017500000000603113573721537026301 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="funnelarea.title.font", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="funnelarea.title.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="funnelarea.title.font", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="funnelarea.title.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="funnelarea.title.font", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="funnelarea.title.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/funnelarea/hoverlabel/0000755000175000017500000000000013573746614024227 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/funnelarea/hoverlabel/__init__.py0000644000175000017500000001352213573721537026340 0ustar noahfxnoahfximport _plotly_utils.basevalidators class NamelengthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="namelengthsrc", parent_name="funnelarea.hoverlabel", **kwargs ): super(NamelengthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NamelengthValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="namelength", parent_name="funnelarea.hoverlabel", **kwargs ): super(NamelengthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", -1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="funnelarea.hoverlabel", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class BordercolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bordercolorsrc", parent_name="funnelarea.hoverlabel", **kwargs ): super(BordercolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="funnelarea.hoverlabel", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bgcolorsrc", parent_name="funnelarea.hoverlabel", **kwargs ): super(BgcolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="funnelarea.hoverlabel", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AlignsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="alignsrc", parent_name="funnelarea.hoverlabel", **kwargs ): super(AlignsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="align", parent_name="funnelarea.hoverlabel", **kwargs ): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "right", "auto"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/funnelarea/hoverlabel/font/0000755000175000017500000000000013573746614025175 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/funnelarea/hoverlabel/font/__init__.py0000644000175000017500000000611713573721537027310 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="funnelarea.hoverlabel.font", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="funnelarea.hoverlabel.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="funnelarea.hoverlabel.font", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="funnelarea.hoverlabel.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="funnelarea.hoverlabel.font", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="funnelarea.hoverlabel.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/funnelarea/marker/0000755000175000017500000000000013573746614023365 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/funnelarea/marker/__init__.py0000644000175000017500000000354013573721537025475 0ustar noahfxnoahfximport _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="line", parent_name="funnelarea.marker", **kwargs): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ color Sets the color of the line enclosing each sector. Defaults to the `paper_bgcolor` value. colorsrc Sets the source reference on plot.ly for color . width Sets the width (in px) of the line enclosing each sector. widthsrc Sets the source reference on plot.ly for width . """, ), **kwargs ) import _plotly_utils.basevalidators class ColorssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorssrc", parent_name="funnelarea.marker", **kwargs ): super(ColorssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="colors", parent_name="funnelarea.marker", **kwargs): super(ColorsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/funnelarea/marker/line/0000755000175000017500000000000013573746614024314 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/funnelarea/marker/line/__init__.py0000644000175000017500000000374113573721537026427 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="widthsrc", parent_name="funnelarea.marker.line", **kwargs ): super(WidthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="width", parent_name="funnelarea.marker.line", **kwargs ): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="funnelarea.marker.line", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="funnelarea.marker.line", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/funnelarea/stream/0000755000175000017500000000000013573746614023377 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/funnelarea/stream/__init__.py0000644000175000017500000000211013573721537025477 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TokenValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="token", parent_name="funnelarea.stream", **kwargs): super(TokenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "info"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class MaxpointsValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="maxpoints", parent_name="funnelarea.stream", **kwargs ): super(MaxpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 10000), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/funnelarea/__init__.py0000644000175000017500000006371213573721537024223 0ustar noahfxnoahfximport _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="visible", parent_name="funnelarea", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "legendonly"]), **kwargs ) import _plotly_utils.basevalidators class ValuessrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="valuessrc", parent_name="funnelarea", **kwargs): super(ValuessrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ValuesValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="values", parent_name="funnelarea", **kwargs): super(ValuesValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="funnelarea", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UidValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="uid", parent_name="funnelarea", **kwargs): super(UidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TitleValidator(_plotly_utils.basevalidators.TitleValidator): def __init__(self, plotly_name="title", parent_name="funnelarea", **kwargs): super(TitleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Title"), data_docs=kwargs.pop( "data_docs", """ font Sets the font used for `title`. Note that the title's font used to be set by the now deprecated `titlefont` attribute. position Specifies the location of the `title`. Note that the title's position used to be set by the now deprecated `titleposition` attribute. text Sets the title of the chart. If it is empty, no title is displayed. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """, ), **kwargs ) import _plotly_utils.basevalidators class TexttemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="texttemplatesrc", parent_name="funnelarea", **kwargs ): super(TexttemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TexttemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="texttemplate", parent_name="funnelarea", **kwargs): super(TexttemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="textsrc", parent_name="funnelarea", **kwargs): super(TextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextpositionsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="textpositionsrc", parent_name="funnelarea", **kwargs ): super(TextpositionsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextpositionValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="textposition", parent_name="funnelarea", **kwargs): super(TextpositionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["inside", "none"]), **kwargs ) import _plotly_utils.basevalidators class TextinfoValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="textinfo", parent_name="funnelarea", **kwargs): super(TextinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), extras=kwargs.pop("extras", ["none"]), flags=kwargs.pop("flags", ["label", "text", "value", "percent"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="textfont", parent_name="funnelarea", **kwargs): super(TextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Textfont"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="text", parent_name="funnelarea", **kwargs): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class StreamValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="stream", parent_name="funnelarea", **kwargs): super(StreamValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Stream"), data_docs=kwargs.pop( "data_docs", """ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """, ), **kwargs ) import _plotly_utils.basevalidators class ShowlegendValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showlegend", parent_name="funnelarea", **kwargs): super(ShowlegendValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ScalegroupValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="scalegroup", parent_name="funnelarea", **kwargs): super(ScalegroupValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="funnelarea", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="funnelarea", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="metasrc", parent_name="funnelarea", **kwargs): super(MetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetaValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="meta", parent_name="funnelarea", **kwargs): super(MetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="marker", parent_name="funnelarea", **kwargs): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ colors Sets the color of each sector. If not specified, the default trace color set is used to pick the sector colors. colorssrc Sets the source reference on plot.ly for colors . line plotly.graph_objects.funnelarea.marker.Line instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class LegendgroupValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="legendgroup", parent_name="funnelarea", **kwargs): super(LegendgroupValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LabelssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="labelssrc", parent_name="funnelarea", **kwargs): super(LabelssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LabelsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="labels", parent_name="funnelarea", **kwargs): super(LabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class Label0Validator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="label0", parent_name="funnelarea", **kwargs): super(Label0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class InsidetextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="insidetextfont", parent_name="funnelarea", **kwargs ): super(InsidetextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Insidetextfont"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class IdssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="idssrc", parent_name="funnelarea", **kwargs): super(IdssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ids", parent_name="funnelarea", **kwargs): super(IdsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class HovertextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hovertextsrc", parent_name="funnelarea", **kwargs): super(HovertextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertext", parent_name="funnelarea", **kwargs): super(HovertextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="hovertemplatesrc", parent_name="funnelarea", **kwargs ): super(HovertemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertemplate", parent_name="funnelarea", **kwargs): super(HovertemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverlabelValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="hoverlabel", parent_name="funnelarea", **kwargs): super(HoverlabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Hoverlabel"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """, ), **kwargs ) import _plotly_utils.basevalidators class HoverinfosrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hoverinfosrc", parent_name="funnelarea", **kwargs): super(HoverinfosrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverinfoValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="hoverinfo", parent_name="funnelarea", **kwargs): super(HoverinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), extras=kwargs.pop("extras", ["all", "none", "skip"]), flags=kwargs.pop("flags", ["label", "text", "value", "percent", "name"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DomainValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="domain", parent_name="funnelarea", **kwargs): super(DomainValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Domain"), data_docs=kwargs.pop( "data_docs", """ column If there is a layout grid, use the domain for this column in the grid for this funnelarea trace . row If there is a layout grid, use the domain for this row in the grid for this funnelarea trace . x Sets the horizontal domain of this funnelarea trace (in plot fraction). y Sets the vertical domain of this funnelarea trace (in plot fraction). """, ), **kwargs ) import _plotly_utils.basevalidators class DlabelValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="dlabel", parent_name="funnelarea", **kwargs): super(DlabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdatasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="customdatasrc", parent_name="funnelarea", **kwargs): super(CustomdatasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdataValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="customdata", parent_name="funnelarea", **kwargs): super(CustomdataValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class BaseratioValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="baseratio", parent_name="funnelarea", **kwargs): super(BaseratioValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AspectratioValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="aspectratio", parent_name="funnelarea", **kwargs): super(AspectratioValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/funnelarea/insidetextfont/0000755000175000017500000000000013573746614025153 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/funnelarea/insidetextfont/__init__.py0000644000175000017500000000606113573721537027264 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="funnelarea.insidetextfont", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="funnelarea.insidetextfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="funnelarea.insidetextfont", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="funnelarea.insidetextfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="funnelarea.insidetextfont", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="funnelarea.insidetextfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/funnelarea/domain/0000755000175000017500000000000013573746614023353 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/funnelarea/domain/__init__.py0000644000175000017500000000452513573721537025467 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="y", parent_name="funnelarea.domain", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), items=kwargs.pop( "items", [ {"valType": "number", "min": 0, "max": 1, "editType": "calc"}, {"valType": "number", "min": 0, "max": 1, "editType": "calc"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="x", parent_name="funnelarea.domain", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), items=kwargs.pop( "items", [ {"valType": "number", "min": 0, "max": 1, "editType": "calc"}, {"valType": "number", "min": 0, "max": 1, "editType": "calc"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class RowValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="row", parent_name="funnelarea.domain", **kwargs): super(RowValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColumnValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="column", parent_name="funnelarea.domain", **kwargs): super(ColumnValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/waterfall/0000755000175000017500000000000013573746614021745 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/waterfall/increasing/0000755000175000017500000000000013573746614024067 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/waterfall/increasing/marker/0000755000175000017500000000000013573746614025350 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/waterfall/increasing/marker/__init__.py0000644000175000017500000000230413573721544027453 0ustar noahfxnoahfximport _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="line", parent_name="waterfall.increasing.marker", **kwargs ): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ color Sets the line color of all increasing values. width Sets the line width of all increasing values. """, ), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="waterfall.increasing.marker", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", False), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/waterfall/increasing/marker/line/0000755000175000017500000000000013573746614026277 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/waterfall/increasing/marker/line/__init__.py0000644000175000017500000000216713573721544030411 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="width", parent_name="waterfall.increasing.marker.line", **kwargs ): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", False), edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="waterfall.increasing.marker.line", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", False), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/waterfall/increasing/__init__.py0000644000175000017500000000141713573721544026176 0ustar noahfxnoahfximport _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="marker", parent_name="waterfall.increasing", **kwargs ): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ color Sets the marker color of all increasing values. line plotly.graph_objects.waterfall.increasing.marke r.Line instance or dict with compatible properties """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/waterfall/connector/0000755000175000017500000000000013573746614023737 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/waterfall/connector/__init__.py0000644000175000017500000000352213573721544026045 0ustar noahfxnoahfximport _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="visible", parent_name="waterfall.connector", **kwargs ): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ModeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="mode", parent_name="waterfall.connector", **kwargs): super(ModeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["spanning", "between"]), **kwargs ) import _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="line", parent_name="waterfall.connector", **kwargs): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ color Sets the line color. dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). width Sets the line width (in px). """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/waterfall/connector/line/0000755000175000017500000000000013573746614024666 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/waterfall/connector/line/__init__.py0000644000175000017500000000305013573721544026770 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="width", parent_name="waterfall.connector.line", **kwargs ): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class DashValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="dash", parent_name="waterfall.connector.line", **kwargs ): super(DashValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", ["solid", "dot", "dash", "longdash", "dashdot", "longdashdot"] ), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="waterfall.connector.line", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/waterfall/textfont/0000755000175000017500000000000013573746614023620 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/waterfall/textfont/__init__.py0000644000175000017500000000575413573721544025737 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="waterfall.textfont", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="size", parent_name="waterfall.textfont", **kwargs): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="waterfall.textfont", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="waterfall.textfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="waterfall.textfont", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="waterfall.textfont", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/waterfall/hoverlabel/0000755000175000017500000000000013573746614024070 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/waterfall/hoverlabel/__init__.py0000644000175000017500000001346113573721544026201 0ustar noahfxnoahfximport _plotly_utils.basevalidators class NamelengthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="namelengthsrc", parent_name="waterfall.hoverlabel", **kwargs ): super(NamelengthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NamelengthValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="namelength", parent_name="waterfall.hoverlabel", **kwargs ): super(NamelengthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", -1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="waterfall.hoverlabel", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class BordercolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bordercolorsrc", parent_name="waterfall.hoverlabel", **kwargs ): super(BordercolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="waterfall.hoverlabel", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bgcolorsrc", parent_name="waterfall.hoverlabel", **kwargs ): super(BgcolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="waterfall.hoverlabel", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AlignsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="alignsrc", parent_name="waterfall.hoverlabel", **kwargs ): super(AlignsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="align", parent_name="waterfall.hoverlabel", **kwargs ): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "right", "auto"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/waterfall/hoverlabel/font/0000755000175000017500000000000013573746614025036 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/waterfall/hoverlabel/font/__init__.py0000644000175000017500000000606113573721544027145 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="waterfall.hoverlabel.font", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="waterfall.hoverlabel.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="waterfall.hoverlabel.font", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="waterfall.hoverlabel.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="waterfall.hoverlabel.font", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="waterfall.hoverlabel.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/waterfall/outsidetextfont/0000755000175000017500000000000013573746614025215 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/waterfall/outsidetextfont/__init__.py0000644000175000017500000000606213573721544027325 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="waterfall.outsidetextfont", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="waterfall.outsidetextfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="waterfall.outsidetextfont", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="waterfall.outsidetextfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="waterfall.outsidetextfont", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="waterfall.outsidetextfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/waterfall/totals/0000755000175000017500000000000013573746614023253 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/waterfall/totals/marker/0000755000175000017500000000000013573746614024534 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/waterfall/totals/marker/__init__.py0000644000175000017500000000237613573721544026650 0ustar noahfxnoahfximport _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="line", parent_name="waterfall.totals.marker", **kwargs ): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ color Sets the line color of all intermediate sums and total values. width Sets the line width of all intermediate sums and total values. """, ), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="waterfall.totals.marker", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", False), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/waterfall/totals/marker/line/0000755000175000017500000000000013573746614025463 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/waterfall/totals/marker/line/__init__.py0000644000175000017500000000207713573721544027575 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="width", parent_name="waterfall.totals.marker.line", **kwargs ): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", False), edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="waterfall.totals.marker.line", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", False), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/waterfall/totals/__init__.py0000644000175000017500000000141213573721544025355 0ustar noahfxnoahfximport _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="marker", parent_name="waterfall.totals", **kwargs): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ color Sets the marker color of all intermediate sums and total values. line plotly.graph_objects.waterfall.totals.marker.Li ne instance or dict with compatible properties """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/waterfall/stream/0000755000175000017500000000000013573746614023240 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/waterfall/stream/__init__.py0000644000175000017500000000210613573721544025343 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TokenValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="token", parent_name="waterfall.stream", **kwargs): super(TokenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "info"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class MaxpointsValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="maxpoints", parent_name="waterfall.stream", **kwargs ): super(MaxpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 10000), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/waterfall/__init__.py0000644000175000017500000010555613573721545024066 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="ysrc", parent_name="waterfall", **kwargs): super(YsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YAxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="yaxis", parent_name="waterfall", **kwargs): super(YAxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "y"), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class Y0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="y0", parent_name="waterfall", **kwargs): super(Y0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="y", parent_name="waterfall", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class XsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="xsrc", parent_name="waterfall", **kwargs): super(XsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XAxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="xaxis", parent_name="waterfall", **kwargs): super(XAxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "x"), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class X0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="x0", parent_name="waterfall", **kwargs): super(X0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="x", parent_name="waterfall", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class WidthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="widthsrc", parent_name="waterfall", **kwargs): super(WidthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="waterfall", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="visible", parent_name="waterfall", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "legendonly"]), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="waterfall", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UidValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="uid", parent_name="waterfall", **kwargs): super(UidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TotalsValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="totals", parent_name="waterfall", **kwargs): super(TotalsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Totals"), data_docs=kwargs.pop( "data_docs", """ marker plotly.graph_objects.waterfall.totals.Marker instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class TexttemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="texttemplatesrc", parent_name="waterfall", **kwargs ): super(TexttemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TexttemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="texttemplate", parent_name="waterfall", **kwargs): super(TexttemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="textsrc", parent_name="waterfall", **kwargs): super(TextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextpositionsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="textpositionsrc", parent_name="waterfall", **kwargs ): super(TextpositionsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextpositionValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="textposition", parent_name="waterfall", **kwargs): super(TextpositionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["inside", "outside", "auto", "none"]), **kwargs ) import _plotly_utils.basevalidators class TextinfoValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="textinfo", parent_name="waterfall", **kwargs): super(TextinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", False), edit_type=kwargs.pop("edit_type", "plot"), extras=kwargs.pop("extras", ["none"]), flags=kwargs.pop("flags", ["label", "text", "initial", "delta", "final"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="textfont", parent_name="waterfall", **kwargs): super(TextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Textfont"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class TextangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__(self, plotly_name="textangle", parent_name="waterfall", **kwargs): super(TextangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="text", parent_name="waterfall", **kwargs): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class StreamValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="stream", parent_name="waterfall", **kwargs): super(StreamValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Stream"), data_docs=kwargs.pop( "data_docs", """ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """, ), **kwargs ) import _plotly_utils.basevalidators class ShowlegendValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showlegend", parent_name="waterfall", **kwargs): super(ShowlegendValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SelectedpointsValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="selectedpoints", parent_name="waterfall", **kwargs): super(SelectedpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class OutsidetextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="outsidetextfont", parent_name="waterfall", **kwargs ): super(OutsidetextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Outsidetextfont"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class OrientationValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="orientation", parent_name="waterfall", **kwargs): super(OrientationValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["v", "h"]), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="waterfall", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OffsetsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="offsetsrc", parent_name="waterfall", **kwargs): super(OffsetsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class OffsetgroupValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="offsetgroup", parent_name="waterfall", **kwargs): super(OffsetgroupValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class OffsetValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="offset", parent_name="waterfall", **kwargs): super(OffsetValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="waterfall", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="metasrc", parent_name="waterfall", **kwargs): super(MetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetaValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="meta", parent_name="waterfall", **kwargs): super(MetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MeasuresrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="measuresrc", parent_name="waterfall", **kwargs): super(MeasuresrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MeasureValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="measure", parent_name="waterfall", **kwargs): super(MeasureValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class LegendgroupValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="legendgroup", parent_name="waterfall", **kwargs): super(LegendgroupValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class InsidetextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="insidetextfont", parent_name="waterfall", **kwargs): super(InsidetextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Insidetextfont"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class InsidetextanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="insidetextanchor", parent_name="waterfall", **kwargs ): super(InsidetextanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["end", "middle", "start"]), **kwargs ) import _plotly_utils.basevalidators class IncreasingValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="increasing", parent_name="waterfall", **kwargs): super(IncreasingValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Increasing"), data_docs=kwargs.pop( "data_docs", """ marker plotly.graph_objects.waterfall.increasing.Marke r instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class IdssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="idssrc", parent_name="waterfall", **kwargs): super(IdssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ids", parent_name="waterfall", **kwargs): super(IdsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class HovertextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hovertextsrc", parent_name="waterfall", **kwargs): super(HovertextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertext", parent_name="waterfall", **kwargs): super(HovertextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="hovertemplatesrc", parent_name="waterfall", **kwargs ): super(HovertemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertemplate", parent_name="waterfall", **kwargs): super(HovertemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverlabelValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="hoverlabel", parent_name="waterfall", **kwargs): super(HoverlabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Hoverlabel"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """, ), **kwargs ) import _plotly_utils.basevalidators class HoverinfosrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hoverinfosrc", parent_name="waterfall", **kwargs): super(HoverinfosrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverinfoValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="hoverinfo", parent_name="waterfall", **kwargs): super(HoverinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), extras=kwargs.pop("extras", ["all", "none", "skip"]), flags=kwargs.pop( "flags", ["name", "x", "y", "text", "initial", "delta", "final"] ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DyValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="dy", parent_name="waterfall", **kwargs): super(DyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="dx", parent_name="waterfall", **kwargs): super(DxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DecreasingValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="decreasing", parent_name="waterfall", **kwargs): super(DecreasingValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Decreasing"), data_docs=kwargs.pop( "data_docs", """ marker plotly.graph_objects.waterfall.decreasing.Marke r instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class CustomdatasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="customdatasrc", parent_name="waterfall", **kwargs): super(CustomdatasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdataValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="customdata", parent_name="waterfall", **kwargs): super(CustomdataValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class ConstraintextValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="constraintext", parent_name="waterfall", **kwargs): super(ConstraintextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["inside", "outside", "both", "none"]), **kwargs ) import _plotly_utils.basevalidators class ConnectorValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="connector", parent_name="waterfall", **kwargs): super(ConnectorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Connector"), data_docs=kwargs.pop( "data_docs", """ line plotly.graph_objects.waterfall.connector.Line instance or dict with compatible properties mode Sets the shape of connector lines. visible Determines if connector lines are drawn. """, ), **kwargs ) import _plotly_utils.basevalidators class CliponaxisValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="cliponaxis", parent_name="waterfall", **kwargs): super(CliponaxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BaseValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="base", parent_name="waterfall", **kwargs): super(BaseValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", False), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AlignmentgroupValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="alignmentgroup", parent_name="waterfall", **kwargs): super(AlignmentgroupValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/waterfall/decreasing/0000755000175000017500000000000013573746614024051 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/waterfall/decreasing/marker/0000755000175000017500000000000013573746614025332 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/waterfall/decreasing/marker/__init__.py0000644000175000017500000000230413573721544027435 0ustar noahfxnoahfximport _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="line", parent_name="waterfall.decreasing.marker", **kwargs ): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ color Sets the line color of all decreasing values. width Sets the line width of all decreasing values. """, ), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="waterfall.decreasing.marker", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", False), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/waterfall/decreasing/marker/line/0000755000175000017500000000000013573746614026261 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/waterfall/decreasing/marker/line/__init__.py0000644000175000017500000000216713573721544030373 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="width", parent_name="waterfall.decreasing.marker.line", **kwargs ): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", False), edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="waterfall.decreasing.marker.line", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", False), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/waterfall/decreasing/__init__.py0000644000175000017500000000141713573721544026160 0ustar noahfxnoahfximport _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="marker", parent_name="waterfall.decreasing", **kwargs ): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ color Sets the marker color of all decreasing values. line plotly.graph_objects.waterfall.decreasing.marke r.Line instance or dict with compatible properties """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/waterfall/insidetextfont/0000755000175000017500000000000013573746614025014 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/waterfall/insidetextfont/__init__.py0000644000175000017500000000605413573721544027125 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="waterfall.insidetextfont", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="waterfall.insidetextfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="waterfall.insidetextfont", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="waterfall.insidetextfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="waterfall.insidetextfont", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="waterfall.insidetextfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/sankey/0000755000175000017500000000000013573746614021256 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/sankey/textfont/0000755000175000017500000000000013573746614023131 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/sankey/textfont/__init__.py0000644000175000017500000000267713573721542025247 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="size", parent_name="sankey.textfont", **kwargs): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="family", parent_name="sankey.textfont", **kwargs): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="sankey.textfont", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/sankey/link/0000755000175000017500000000000013573746614022213 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/sankey/link/hoverlabel/0000755000175000017500000000000013573746614024336 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/sankey/link/hoverlabel/__init__.py0000644000175000017500000001356313573721542026450 0ustar noahfxnoahfximport _plotly_utils.basevalidators class NamelengthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="namelengthsrc", parent_name="sankey.link.hoverlabel", **kwargs ): super(NamelengthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NamelengthValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="namelength", parent_name="sankey.link.hoverlabel", **kwargs ): super(NamelengthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", -1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="sankey.link.hoverlabel", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class BordercolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bordercolorsrc", parent_name="sankey.link.hoverlabel", **kwargs ): super(BordercolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="sankey.link.hoverlabel", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bgcolorsrc", parent_name="sankey.link.hoverlabel", **kwargs ): super(BgcolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="sankey.link.hoverlabel", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AlignsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="alignsrc", parent_name="sankey.link.hoverlabel", **kwargs ): super(AlignsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="align", parent_name="sankey.link.hoverlabel", **kwargs ): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "right", "auto"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/sankey/link/hoverlabel/font/0000755000175000017500000000000013573746614025304 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/sankey/link/hoverlabel/font/__init__.py0000644000175000017500000000615513573721541027414 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="sankey.link.hoverlabel.font", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="sankey.link.hoverlabel.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="sankey.link.hoverlabel.font", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="sankey.link.hoverlabel.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="sankey.link.hoverlabel.font", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="sankey.link.hoverlabel.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/sankey/link/colorscale/0000755000175000017500000000000013573746614024341 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/sankey/link/colorscale/__init__.py0000644000175000017500000000560113573721541026444 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="sankey.link.colorscale", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="sankey.link.colorscale", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LabelValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="label", parent_name="sankey.link.colorscale", **kwargs ): super(LabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__( self, plotly_name="colorscale", parent_name="sankey.link.colorscale", **kwargs ): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"autocolorscale": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class CminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="cmin", parent_name="sankey.link.colorscale", **kwargs ): super(CminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="cmax", parent_name="sankey.link.colorscale", **kwargs ): super(CmaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/sankey/link/__init__.py0000644000175000017500000003007113573721542024316 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValuesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="valuesrc", parent_name="sankey.link", **kwargs): super(ValuesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="value", parent_name="sankey.link", **kwargs): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TargetsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="targetsrc", parent_name="sankey.link", **kwargs): super(TargetsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TargetValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="target", parent_name="sankey.link", **kwargs): super(TargetValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class SourcesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="sourcesrc", parent_name="sankey.link", **kwargs): super(SourcesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SourceValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="source", parent_name="sankey.link", **kwargs): super(SourceValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="line", parent_name="sankey.link", **kwargs): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ color Sets the color of the `line` around each `link`. colorsrc Sets the source reference on plot.ly for color . width Sets the width (in px) of the `line` around each `link`. widthsrc Sets the source reference on plot.ly for width . """, ), **kwargs ) import _plotly_utils.basevalidators class LabelsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="labelsrc", parent_name="sankey.link", **kwargs): super(LabelsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LabelValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="label", parent_name="sankey.link", **kwargs): super(LabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class HovertemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="hovertemplatesrc", parent_name="sankey.link", **kwargs ): super(HovertemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="hovertemplate", parent_name="sankey.link", **kwargs ): super(HovertemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverlabelValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="hoverlabel", parent_name="sankey.link", **kwargs): super(HoverlabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Hoverlabel"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """, ), **kwargs ) import _plotly_utils.basevalidators class HoverinfoValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="hoverinfo", parent_name="sankey.link", **kwargs): super(HoverinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["all", "none", "skip"]), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="colorsrc", parent_name="sankey.link", **kwargs): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="colorscaledefaults", parent_name="sankey.link", **kwargs ): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Colorscale"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class ColorscalesValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__(self, plotly_name="colorscales", parent_name="sankey.link", **kwargs): super(ColorscalesValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Colorscale"), data_docs=kwargs.pop( "data_docs", """ cmax Sets the upper bound of the color domain. cmin Sets the lower bound of the color domain. colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`cmin` and `cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Grey s,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Blues, Picnic,Rainbow,Portland,Jet,Hot,Blackbody,Earth ,Electric,Viridis,Cividis. label The label of the links to color based on their concentration within a flow. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. """, ), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="sankey.link", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/sankey/link/line/0000755000175000017500000000000013573746614023142 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/sankey/link/line/__init__.py0000644000175000017500000000365313573721541025252 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="widthsrc", parent_name="sankey.link.line", **kwargs ): super(WidthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="sankey.link.line", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="sankey.link.line", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="sankey.link.line", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/sankey/hoverlabel/0000755000175000017500000000000013573746614023401 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/sankey/hoverlabel/__init__.py0000644000175000017500000001337213573721541025510 0ustar noahfxnoahfximport _plotly_utils.basevalidators class NamelengthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="namelengthsrc", parent_name="sankey.hoverlabel", **kwargs ): super(NamelengthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NamelengthValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="namelength", parent_name="sankey.hoverlabel", **kwargs ): super(NamelengthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", -1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="font", parent_name="sankey.hoverlabel", **kwargs): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class BordercolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bordercolorsrc", parent_name="sankey.hoverlabel", **kwargs ): super(BordercolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="sankey.hoverlabel", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bgcolorsrc", parent_name="sankey.hoverlabel", **kwargs ): super(BgcolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="sankey.hoverlabel", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AlignsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="alignsrc", parent_name="sankey.hoverlabel", **kwargs ): super(AlignsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="align", parent_name="sankey.hoverlabel", **kwargs): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "right", "auto"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/sankey/hoverlabel/font/0000755000175000017500000000000013573746614024347 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/sankey/hoverlabel/font/__init__.py0000644000175000017500000000603713573721541026456 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="sankey.hoverlabel.font", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="sankey.hoverlabel.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="sankey.hoverlabel.font", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="sankey.hoverlabel.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="sankey.hoverlabel.font", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="sankey.hoverlabel.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/sankey/stream/0000755000175000017500000000000013573746614022551 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/sankey/stream/__init__.py0000644000175000017500000000206213573721541024652 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TokenValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="token", parent_name="sankey.stream", **kwargs): super(TokenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "info"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class MaxpointsValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="maxpoints", parent_name="sankey.stream", **kwargs): super(MaxpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 10000), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/sankey/__init__.py0000644000175000017500000005223213573721542023364 0ustar noahfxnoahfximport _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="visible", parent_name="sankey", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "legendonly"]), **kwargs ) import _plotly_utils.basevalidators class ValuesuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="valuesuffix", parent_name="sankey", **kwargs): super(ValuesuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ValueformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="valueformat", parent_name="sankey", **kwargs): super(ValueformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="sankey", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UidValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="uid", parent_name="sankey", **kwargs): super(UidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="textfont", parent_name="sankey", **kwargs): super(TextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Textfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class StreamValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="stream", parent_name="sankey", **kwargs): super(StreamValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Stream"), data_docs=kwargs.pop( "data_docs", """ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """, ), **kwargs ) import _plotly_utils.basevalidators class SelectedpointsValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="selectedpoints", parent_name="sankey", **kwargs): super(SelectedpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class OrientationValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="orientation", parent_name="sankey", **kwargs): super(OrientationValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["v", "h"]), **kwargs ) import _plotly_utils.basevalidators class NodeValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="node", parent_name="sankey", **kwargs): super(NodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Node"), data_docs=kwargs.pop( "data_docs", """ color Sets the `node` color. It can be a single value, or an array for specifying color for each `node`. If `node.color` is omitted, then the default `Plotly` color palette will be cycled through to have a variety of colors. These defaults are not fully opaque, to allow some visibility of what is beneath the node. colorsrc Sets the source reference on plot.ly for color . groups Groups of nodes. Each group is defined by an array with the indices of the nodes it contains. Multiple groups can be specified. hoverinfo Determines which trace information appear when hovering nodes. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverlabel plotly.graph_objects.sankey.node.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs- events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `value` and `label`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . label The shown name of the node. labelsrc Sets the source reference on plot.ly for label . line plotly.graph_objects.sankey.node.Line instance or dict with compatible properties pad Sets the padding (in px) between the `nodes`. thickness Sets the thickness (in px) of the `nodes`. x The normalized horizontal position of the node. xsrc Sets the source reference on plot.ly for x . y The normalized vertical position of the node. ysrc Sets the source reference on plot.ly for y . """, ), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="sankey", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="metasrc", parent_name="sankey", **kwargs): super(MetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetaValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="meta", parent_name="sankey", **kwargs): super(MetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LinkValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="link", parent_name="sankey", **kwargs): super(LinkValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Link"), data_docs=kwargs.pop( "data_docs", """ color Sets the `link` color. It can be a single value, or an array for specifying color for each `link`. If `link.color` is omitted, then by default, a translucent grey link will be used. colorscales A tuple of plotly.graph_objects.sankey.link.Colorscale instances or dicts with compatible properties colorscaledefaults When used in a template (as layout.template.dat a.sankey.link.colorscaledefaults), sets the default property values to use for elements of sankey.link.colorscales colorsrc Sets the source reference on plot.ly for color . hoverinfo Determines which trace information appear when hovering links. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverlabel plotly.graph_objects.sankey.link.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs- events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `value` and `label`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . label The shown name of the link. labelsrc Sets the source reference on plot.ly for label . line plotly.graph_objects.sankey.link.Line instance or dict with compatible properties source An integer number `[0..nodes.length - 1]` that represents the source node. sourcesrc Sets the source reference on plot.ly for source . target An integer number `[0..nodes.length - 1]` that represents the target node. targetsrc Sets the source reference on plot.ly for target . value A numeric value representing the flow volume value. valuesrc Sets the source reference on plot.ly for value . """, ), **kwargs ) import _plotly_utils.basevalidators class IdssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="idssrc", parent_name="sankey", **kwargs): super(IdssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ids", parent_name="sankey", **kwargs): super(IdsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class HoverlabelValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="hoverlabel", parent_name="sankey", **kwargs): super(HoverlabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Hoverlabel"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """, ), **kwargs ) import _plotly_utils.basevalidators class HoverinfoValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="hoverinfo", parent_name="sankey", **kwargs): super(HoverinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", False), edit_type=kwargs.pop("edit_type", "calc"), extras=kwargs.pop("extras", ["all", "none", "skip"]), flags=kwargs.pop("flags", []), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DomainValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="domain", parent_name="sankey", **kwargs): super(DomainValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Domain"), data_docs=kwargs.pop( "data_docs", """ column If there is a layout grid, use the domain for this column in the grid for this sankey trace . row If there is a layout grid, use the domain for this row in the grid for this sankey trace . x Sets the horizontal domain of this sankey trace (in plot fraction). y Sets the vertical domain of this sankey trace (in plot fraction). """, ), **kwargs ) import _plotly_utils.basevalidators class CustomdatasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="customdatasrc", parent_name="sankey", **kwargs): super(CustomdatasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdataValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="customdata", parent_name="sankey", **kwargs): super(CustomdataValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class ArrangementValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="arrangement", parent_name="sankey", **kwargs): super(ArrangementValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["snap", "perpendicular", "freeform", "fixed"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/sankey/domain/0000755000175000017500000000000013573746614022525 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/sankey/domain/__init__.py0000644000175000017500000000450513573721541024632 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="y", parent_name="sankey.domain", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), items=kwargs.pop( "items", [ {"valType": "number", "min": 0, "max": 1, "editType": "calc"}, {"valType": "number", "min": 0, "max": 1, "editType": "calc"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="x", parent_name="sankey.domain", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), items=kwargs.pop( "items", [ {"valType": "number", "min": 0, "max": 1, "editType": "calc"}, {"valType": "number", "min": 0, "max": 1, "editType": "calc"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class RowValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="row", parent_name="sankey.domain", **kwargs): super(RowValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColumnValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="column", parent_name="sankey.domain", **kwargs): super(ColumnValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/sankey/node/0000755000175000017500000000000013573746614022203 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/sankey/node/hoverlabel/0000755000175000017500000000000013573746614024326 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/sankey/node/hoverlabel/__init__.py0000644000175000017500000001356313573721542026440 0ustar noahfxnoahfximport _plotly_utils.basevalidators class NamelengthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="namelengthsrc", parent_name="sankey.node.hoverlabel", **kwargs ): super(NamelengthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NamelengthValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="namelength", parent_name="sankey.node.hoverlabel", **kwargs ): super(NamelengthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", -1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="sankey.node.hoverlabel", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class BordercolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bordercolorsrc", parent_name="sankey.node.hoverlabel", **kwargs ): super(BordercolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="sankey.node.hoverlabel", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bgcolorsrc", parent_name="sankey.node.hoverlabel", **kwargs ): super(BgcolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="sankey.node.hoverlabel", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AlignsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="alignsrc", parent_name="sankey.node.hoverlabel", **kwargs ): super(AlignsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="align", parent_name="sankey.node.hoverlabel", **kwargs ): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "right", "auto"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/sankey/node/hoverlabel/font/0000755000175000017500000000000013573746614025274 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/sankey/node/hoverlabel/font/__init__.py0000644000175000017500000000615513573721542027405 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="sankey.node.hoverlabel.font", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="sankey.node.hoverlabel.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="sankey.node.hoverlabel.font", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="sankey.node.hoverlabel.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="sankey.node.hoverlabel.font", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="sankey.node.hoverlabel.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/sankey/node/__init__.py0000644000175000017500000002313213573721542024306 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="ysrc", parent_name="sankey.node", **kwargs): super(YsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="y", parent_name="sankey.node", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class XsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="xsrc", parent_name="sankey.node", **kwargs): super(XsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="x", parent_name="sankey.node", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="thickness", parent_name="sankey.node", **kwargs): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", False), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class PadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="pad", parent_name="sankey.node", **kwargs): super(PadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", False), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="line", parent_name="sankey.node", **kwargs): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ color Sets the color of the `line` around each `node`. colorsrc Sets the source reference on plot.ly for color . width Sets the width (in px) of the `line` around each `node`. widthsrc Sets the source reference on plot.ly for width . """, ), **kwargs ) import _plotly_utils.basevalidators class LabelsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="labelsrc", parent_name="sankey.node", **kwargs): super(LabelsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LabelValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="label", parent_name="sankey.node", **kwargs): super(LabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class HovertemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="hovertemplatesrc", parent_name="sankey.node", **kwargs ): super(HovertemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="hovertemplate", parent_name="sankey.node", **kwargs ): super(HovertemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverlabelValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="hoverlabel", parent_name="sankey.node", **kwargs): super(HoverlabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Hoverlabel"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """, ), **kwargs ) import _plotly_utils.basevalidators class HoverinfoValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="hoverinfo", parent_name="sankey.node", **kwargs): super(HoverinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["all", "none", "skip"]), **kwargs ) import _plotly_utils.basevalidators class GroupsValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="groups", parent_name="sankey.node", **kwargs): super(GroupsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dimensions=kwargs.pop("dimensions", 2), edit_type=kwargs.pop("edit_type", "calc"), free_length=kwargs.pop("free_length", True), implied_edits=kwargs.pop("implied_edits", {"x": [], "y": []}), items=kwargs.pop("items", {"valType": "number", "editType": "calc"}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="colorsrc", parent_name="sankey.node", **kwargs): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="sankey.node", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/sankey/node/line/0000755000175000017500000000000013573746614023132 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/sankey/node/line/__init__.py0000644000175000017500000000365313573721542025243 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="widthsrc", parent_name="sankey.node.line", **kwargs ): super(WidthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="sankey.node.line", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="sankey.node.line", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="sankey.node.line", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/choropleth/0000755000175000017500000000000013573746614022133 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/choropleth/unselected/0000755000175000017500000000000013573746614024266 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/choropleth/unselected/marker/0000755000175000017500000000000013573746614025547 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/choropleth/unselected/marker/__init__.py0000644000175000017500000000110113573721536027645 0ustar noahfxnoahfximport _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="opacity", parent_name="choropleth.unselected.marker", **kwargs ): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/choropleth/unselected/__init__.py0000644000175000017500000000124213573721536026372 0ustar noahfxnoahfximport _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="marker", parent_name="choropleth.unselected", **kwargs ): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ opacity Sets the marker opacity of unselected points, applied only when a selection exists. """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/choropleth/hoverlabel/0000755000175000017500000000000013573746614024256 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/choropleth/hoverlabel/__init__.py0000644000175000017500000001352213573721536026366 0ustar noahfxnoahfximport _plotly_utils.basevalidators class NamelengthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="namelengthsrc", parent_name="choropleth.hoverlabel", **kwargs ): super(NamelengthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NamelengthValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="namelength", parent_name="choropleth.hoverlabel", **kwargs ): super(NamelengthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", -1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="choropleth.hoverlabel", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class BordercolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bordercolorsrc", parent_name="choropleth.hoverlabel", **kwargs ): super(BordercolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="choropleth.hoverlabel", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bgcolorsrc", parent_name="choropleth.hoverlabel", **kwargs ): super(BgcolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="choropleth.hoverlabel", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AlignsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="alignsrc", parent_name="choropleth.hoverlabel", **kwargs ): super(AlignsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="align", parent_name="choropleth.hoverlabel", **kwargs ): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "right", "auto"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/choropleth/hoverlabel/font/0000755000175000017500000000000013573746614025224 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/choropleth/hoverlabel/font/__init__.py0000644000175000017500000000611713573721536027336 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="choropleth.hoverlabel.font", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="choropleth.hoverlabel.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="choropleth.hoverlabel.font", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="choropleth.hoverlabel.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="choropleth.hoverlabel.font", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="choropleth.hoverlabel.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/choropleth/colorbar/0000755000175000017500000000000013573746614023736 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/choropleth/colorbar/tickformatstop/0000755000175000017500000000000013573746614027007 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/choropleth/colorbar/tickformatstop/__init__.py0000644000175000017500000000541313573721536031117 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="value", parent_name="choropleth.colorbar.tickformatstop", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="choropleth.colorbar.tickformatstop", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="choropleth.colorbar.tickformatstop", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EnabledValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="enabled", parent_name="choropleth.colorbar.tickformatstop", **kwargs ): super(EnabledValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DtickrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="dtickrange", parent_name="choropleth.colorbar.tickformatstop", **kwargs ): super(DtickrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "colorbars"}, {"valType": "any", "editType": "colorbars"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/choropleth/colorbar/title/0000755000175000017500000000000013573746614025057 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/choropleth/colorbar/title/__init__.py0000644000175000017500000000472613573721536027175 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="text", parent_name="choropleth.colorbar.title", **kwargs ): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SideValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="side", parent_name="choropleth.colorbar.title", **kwargs ): super(SideValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["right", "top", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="choropleth.colorbar.title", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/choropleth/colorbar/title/font/0000755000175000017500000000000013573746614026025 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/choropleth/colorbar/title/font/__init__.py0000644000175000017500000000312513573721536030133 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="choropleth.colorbar.title.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="choropleth.colorbar.title.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="choropleth.colorbar.title.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/choropleth/colorbar/__init__.py0000644000175000017500000006037613573721537026060 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="ypad", parent_name="choropleth.colorbar", **kwargs): super(YpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class YanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="yanchor", parent_name="choropleth.colorbar", **kwargs ): super(YanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["top", "middle", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="y", parent_name="choropleth.colorbar", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="xpad", parent_name="choropleth.colorbar", **kwargs): super(XpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="xanchor", parent_name="choropleth.colorbar", **kwargs ): super(XanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "center", "right"]), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="x", parent_name="choropleth.colorbar", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TitleValidator(_plotly_utils.basevalidators.TitleValidator): def __init__( self, plotly_name="title", parent_name="choropleth.colorbar", **kwargs ): super(TitleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Title"), data_docs=kwargs.pop( "data_docs", """ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """, ), **kwargs ) import _plotly_utils.basevalidators class TickwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="tickwidth", parent_name="choropleth.colorbar", **kwargs ): super(TickwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickvalssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="tickvalssrc", parent_name="choropleth.colorbar", **kwargs ): super(TickvalssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickvalsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="tickvals", parent_name="choropleth.colorbar", **kwargs ): super(TickvalsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="ticktextsrc", parent_name="choropleth.colorbar", **kwargs ): super(TicktextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicktextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="ticktext", parent_name="choropleth.colorbar", **kwargs ): super(TicktextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="ticksuffix", parent_name="choropleth.colorbar", **kwargs ): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TicksValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="ticks", parent_name="choropleth.colorbar", **kwargs ): super(TicksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["outside", "inside", ""]), **kwargs ) import _plotly_utils.basevalidators class TickprefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickprefix", parent_name="choropleth.colorbar", **kwargs ): super(TickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="tickmode", parent_name="choropleth.colorbar", **kwargs ): super(TickmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "linear", "array"]), **kwargs ) import _plotly_utils.basevalidators class TicklenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ticklen", parent_name="choropleth.colorbar", **kwargs ): super(TicklenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickformatstopValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickformatstopdefaults", parent_name="choropleth.colorbar", **kwargs ): super(TickformatstopValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatstopsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="tickformatstops", parent_name="choropleth.colorbar", **kwargs ): super(TickformatstopsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickformat", parent_name="choropleth.colorbar", **kwargs ): super(TickformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickfont", parent_name="choropleth.colorbar", **kwargs ): super(TickfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class TickcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="tickcolor", parent_name="choropleth.colorbar", **kwargs ): super(TickcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__( self, plotly_name="tickangle", parent_name="choropleth.colorbar", **kwargs ): super(TickangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="tick0", parent_name="choropleth.colorbar", **kwargs ): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ThicknessmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="thicknessmode", parent_name="choropleth.colorbar", **kwargs ): super(ThicknessmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="thickness", parent_name="choropleth.colorbar", **kwargs ): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowticksuffixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showticksuffix", parent_name="choropleth.colorbar", **kwargs ): super(ShowticksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowtickprefixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showtickprefix", parent_name="choropleth.colorbar", **kwargs ): super(ShowtickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowticklabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showticklabels", parent_name="choropleth.colorbar", **kwargs ): super(ShowticklabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowexponentValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showexponent", parent_name="choropleth.colorbar", **kwargs ): super(ShowexponentValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class SeparatethousandsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="separatethousands", parent_name="choropleth.colorbar", **kwargs ): super(SeparatethousandsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="outlinewidth", parent_name="choropleth.colorbar", **kwargs ): super(OutlinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="outlinecolor", parent_name="choropleth.colorbar", **kwargs ): super(OutlinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NticksValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="nticks", parent_name="choropleth.colorbar", **kwargs ): super(NticksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LenmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="lenmode", parent_name="choropleth.colorbar", **kwargs ): super(LenmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class LenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="len", parent_name="choropleth.colorbar", **kwargs): super(LenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ExponentformatValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="exponentformat", parent_name="choropleth.colorbar", **kwargs ): super(ExponentformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "e", "E", "power", "SI", "B"]), **kwargs ) import _plotly_utils.basevalidators class DtickValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="dtick", parent_name="choropleth.colorbar", **kwargs ): super(DtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BorderwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="borderwidth", parent_name="choropleth.colorbar", **kwargs ): super(BorderwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="choropleth.colorbar", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="choropleth.colorbar", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/choropleth/colorbar/tickfont/0000755000175000017500000000000013573746614025557 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/choropleth/colorbar/tickfont/__init__.py0000644000175000017500000000303713573721536027667 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="choropleth.colorbar.tickfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="choropleth.colorbar.tickfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="choropleth.colorbar.tickfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/choropleth/marker/0000755000175000017500000000000013573746614023414 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/choropleth/marker/__init__.py0000644000175000017500000000430613573721536025524 0ustar noahfxnoahfximport _plotly_utils.basevalidators class OpacitysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="opacitysrc", parent_name="choropleth.marker", **kwargs ): super(OpacitysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="opacity", parent_name="choropleth.marker", **kwargs ): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="line", parent_name="choropleth.marker", **kwargs): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. colorsrc Sets the source reference on plot.ly for color . width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/choropleth/marker/line/0000755000175000017500000000000013573746614024343 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/choropleth/marker/line/__init__.py0000644000175000017500000000373713573721536026462 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="widthsrc", parent_name="choropleth.marker.line", **kwargs ): super(WidthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="width", parent_name="choropleth.marker.line", **kwargs ): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="choropleth.marker.line", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="choropleth.marker.line", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/choropleth/stream/0000755000175000017500000000000013573746614023426 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/choropleth/stream/__init__.py0000644000175000017500000000211013573721536025525 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TokenValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="token", parent_name="choropleth.stream", **kwargs): super(TokenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "info"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class MaxpointsValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="maxpoints", parent_name="choropleth.stream", **kwargs ): super(MaxpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 10000), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/choropleth/__init__.py0000644000175000017500000007706313573721537024256 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ZsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="zsrc", parent_name="choropleth", **kwargs): super(ZsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="zmin", parent_name="choropleth", **kwargs): super(ZminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"zauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZmidValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="zmid", parent_name="choropleth", **kwargs): super(ZmidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZmaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="zmax", parent_name="choropleth", **kwargs): super(ZmaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"zauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZautoValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="zauto", parent_name="choropleth", **kwargs): super(ZautoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="z", parent_name="choropleth", **kwargs): super(ZValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="visible", parent_name="choropleth", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "legendonly"]), **kwargs ) import _plotly_utils.basevalidators class UnselectedValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="unselected", parent_name="choropleth", **kwargs): super(UnselectedValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Unselected"), data_docs=kwargs.pop( "data_docs", """ marker plotly.graph_objects.choropleth.unselected.Mark er instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="choropleth", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UidValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="uid", parent_name="choropleth", **kwargs): super(UidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="textsrc", parent_name="choropleth", **kwargs): super(TextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="text", parent_name="choropleth", **kwargs): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class StreamValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="stream", parent_name="choropleth", **kwargs): super(StreamValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Stream"), data_docs=kwargs.pop( "data_docs", """ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """, ), **kwargs ) import _plotly_utils.basevalidators class ShowscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showscale", parent_name="choropleth", **kwargs): super(ShowscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SelectedpointsValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="selectedpoints", parent_name="choropleth", **kwargs ): super(SelectedpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SelectedValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="selected", parent_name="choropleth", **kwargs): super(SelectedValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Selected"), data_docs=kwargs.pop( "data_docs", """ marker plotly.graph_objects.choropleth.selected.Marker instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class ReversescaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="reversescale", parent_name="choropleth", **kwargs): super(ReversescaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="choropleth", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="metasrc", parent_name="choropleth", **kwargs): super(MetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetaValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="meta", parent_name="choropleth", **kwargs): super(MetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="marker", parent_name="choropleth", **kwargs): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ line plotly.graph_objects.choropleth.marker.Line instance or dict with compatible properties opacity Sets the opacity of the locations. opacitysrc Sets the source reference on plot.ly for opacity . """, ), **kwargs ) import _plotly_utils.basevalidators class LocationssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="locationssrc", parent_name="choropleth", **kwargs): super(LocationssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LocationsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="locations", parent_name="choropleth", **kwargs): super(LocationsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class LocationmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="locationmode", parent_name="choropleth", **kwargs): super(LocationmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["ISO-3", "USA-states", "country names"]), **kwargs ) import _plotly_utils.basevalidators class IdssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="idssrc", parent_name="choropleth", **kwargs): super(IdssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ids", parent_name="choropleth", **kwargs): super(IdsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class HovertextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hovertextsrc", parent_name="choropleth", **kwargs): super(HovertextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertext", parent_name="choropleth", **kwargs): super(HovertextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="hovertemplatesrc", parent_name="choropleth", **kwargs ): super(HovertemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertemplate", parent_name="choropleth", **kwargs): super(HovertemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverlabelValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="hoverlabel", parent_name="choropleth", **kwargs): super(HoverlabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Hoverlabel"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """, ), **kwargs ) import _plotly_utils.basevalidators class HoverinfosrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hoverinfosrc", parent_name="choropleth", **kwargs): super(HoverinfosrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverinfoValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="hoverinfo", parent_name="choropleth", **kwargs): super(HoverinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), extras=kwargs.pop("extras", ["all", "none", "skip"]), flags=kwargs.pop("flags", ["location", "z", "text", "name"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class GeoValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="geo", parent_name="choropleth", **kwargs): super(GeoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "geo"), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdatasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="customdatasrc", parent_name="choropleth", **kwargs): super(CustomdatasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdataValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="customdata", parent_name="choropleth", **kwargs): super(CustomdataValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__(self, plotly_name="colorscale", parent_name="choropleth", **kwargs): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"autocolorscale": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorBarValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="colorbar", parent_name="choropleth", **kwargs): super(ColorBarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "ColorBar"), data_docs=kwargs.pop( "data_docs", """ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.choropleth.colo rbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.choropleth.colorbar.tickformatstopdefaults), sets the default property values to use for elements of choropleth.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.choropleth.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use choropleth.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use choropleth.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """, ), **kwargs ) import _plotly_utils.basevalidators class ColoraxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="coloraxis", parent_name="choropleth", **kwargs): super(ColoraxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", None), edit_type=kwargs.pop("edit_type", "calc"), regex=kwargs.pop("regex", "/^coloraxis([2-9]|[1-9][0-9]+)?$/"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AutocolorscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="autocolorscale", parent_name="choropleth", **kwargs ): super(AutocolorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/choropleth/selected/0000755000175000017500000000000013573746614023723 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/choropleth/selected/marker/0000755000175000017500000000000013573746614025204 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/choropleth/selected/marker/__init__.py0000644000175000017500000000104713573721536027313 0ustar noahfxnoahfximport _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="opacity", parent_name="choropleth.selected.marker", **kwargs ): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/choropleth/selected/__init__.py0000644000175000017500000000115013573721536026025 0ustar noahfxnoahfximport _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="marker", parent_name="choropleth.selected", **kwargs ): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ opacity Sets the marker opacity of selected points. """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/candlestick/0000755000175000017500000000000013573746614022250 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/candlestick/increasing/0000755000175000017500000000000013573746614024372 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/candlestick/increasing/__init__.py0000644000175000017500000000225013573721536026476 0ustar noahfxnoahfximport _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="line", parent_name="candlestick.increasing", **kwargs ): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ color Sets the color of line bounding the box(es). width Sets the width (in px) of line bounding the box(es). """, ), **kwargs ) import _plotly_utils.basevalidators class FillcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="fillcolor", parent_name="candlestick.increasing", **kwargs ): super(FillcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/candlestick/increasing/line/0000755000175000017500000000000013573746614025321 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/candlestick/increasing/line/__init__.py0000644000175000017500000000172513573721536027433 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="width", parent_name="candlestick.increasing.line", **kwargs ): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="candlestick.increasing.line", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/candlestick/hoverlabel/0000755000175000017500000000000013573746614024373 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/candlestick/hoverlabel/__init__.py0000644000175000017500000001450713573721536026507 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SplitValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="split", parent_name="candlestick.hoverlabel", **kwargs ): super(SplitValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NamelengthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="namelengthsrc", parent_name="candlestick.hoverlabel", **kwargs ): super(NamelengthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NamelengthValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="namelength", parent_name="candlestick.hoverlabel", **kwargs ): super(NamelengthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", -1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="candlestick.hoverlabel", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class BordercolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bordercolorsrc", parent_name="candlestick.hoverlabel", **kwargs ): super(BordercolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="candlestick.hoverlabel", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bgcolorsrc", parent_name="candlestick.hoverlabel", **kwargs ): super(BgcolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="candlestick.hoverlabel", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AlignsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="alignsrc", parent_name="candlestick.hoverlabel", **kwargs ): super(AlignsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="align", parent_name="candlestick.hoverlabel", **kwargs ): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "right", "auto"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/candlestick/hoverlabel/font/0000755000175000017500000000000013573746614025341 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/candlestick/hoverlabel/font/__init__.py0000644000175000017500000000615513573721536027455 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="candlestick.hoverlabel.font", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="candlestick.hoverlabel.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="candlestick.hoverlabel.font", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="candlestick.hoverlabel.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="candlestick.hoverlabel.font", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="candlestick.hoverlabel.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/candlestick/stream/0000755000175000017500000000000013573746614023543 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/candlestick/stream/__init__.py0000644000175000017500000000211213573721536025644 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TokenValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="token", parent_name="candlestick.stream", **kwargs): super(TokenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "info"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class MaxpointsValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="maxpoints", parent_name="candlestick.stream", **kwargs ): super(MaxpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 10000), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/candlestick/__init__.py0000644000175000017500000005326013573721537024364 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YAxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="yaxis", parent_name="candlestick", **kwargs): super(YAxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "y"), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="xsrc", parent_name="candlestick", **kwargs): super(XsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XcalendarValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="xcalendar", parent_name="candlestick", **kwargs): super(XcalendarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "gregorian", "chinese", "coptic", "discworld", "ethiopian", "hebrew", "islamic", "julian", "mayan", "nanakshahi", "nepali", "persian", "jalali", "taiwan", "thai", "ummalqura", ], ), **kwargs ) import _plotly_utils.basevalidators class XAxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="xaxis", parent_name="candlestick", **kwargs): super(XAxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "x"), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="x", parent_name="candlestick", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class WhiskerwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="whiskerwidth", parent_name="candlestick", **kwargs): super(WhiskerwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="visible", parent_name="candlestick", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "legendonly"]), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="candlestick", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UidValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="uid", parent_name="candlestick", **kwargs): super(UidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="textsrc", parent_name="candlestick", **kwargs): super(TextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="text", parent_name="candlestick", **kwargs): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class StreamValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="stream", parent_name="candlestick", **kwargs): super(StreamValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Stream"), data_docs=kwargs.pop( "data_docs", """ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """, ), **kwargs ) import _plotly_utils.basevalidators class ShowlegendValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showlegend", parent_name="candlestick", **kwargs): super(ShowlegendValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SelectedpointsValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="selectedpoints", parent_name="candlestick", **kwargs ): super(SelectedpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class OpensrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="opensrc", parent_name="candlestick", **kwargs): super(OpensrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class OpenValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="open", parent_name="candlestick", **kwargs): super(OpenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="candlestick", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="candlestick", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="metasrc", parent_name="candlestick", **kwargs): super(MetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetaValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="meta", parent_name="candlestick", **kwargs): super(MetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LowsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="lowsrc", parent_name="candlestick", **kwargs): super(LowsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LowValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="low", parent_name="candlestick", **kwargs): super(LowValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="line", parent_name="candlestick", **kwargs): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ width Sets the width (in px) of line bounding the box(es). Note that this style setting can also be set per direction via `increasing.line.width` and `decreasing.line.width`. """, ), **kwargs ) import _plotly_utils.basevalidators class LegendgroupValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="legendgroup", parent_name="candlestick", **kwargs): super(LegendgroupValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IncreasingValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="increasing", parent_name="candlestick", **kwargs): super(IncreasingValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Increasing"), data_docs=kwargs.pop( "data_docs", """ fillcolor Sets the fill color. Defaults to a half- transparent variant of the line color, marker color, or marker line color, whichever is available. line plotly.graph_objects.candlestick.increasing.Lin e instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class IdssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="idssrc", parent_name="candlestick", **kwargs): super(IdssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ids", parent_name="candlestick", **kwargs): super(IdsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class HovertextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hovertextsrc", parent_name="candlestick", **kwargs): super(HovertextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertext", parent_name="candlestick", **kwargs): super(HovertextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverlabelValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="hoverlabel", parent_name="candlestick", **kwargs): super(HoverlabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Hoverlabel"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . split Show hover information (open, close, high, low) in separate labels. """, ), **kwargs ) import _plotly_utils.basevalidators class HoverinfosrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hoverinfosrc", parent_name="candlestick", **kwargs): super(HoverinfosrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverinfoValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="hoverinfo", parent_name="candlestick", **kwargs): super(HoverinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), extras=kwargs.pop("extras", ["all", "none", "skip"]), flags=kwargs.pop("flags", ["x", "y", "z", "text", "name"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HighsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="highsrc", parent_name="candlestick", **kwargs): super(HighsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HighValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="high", parent_name="candlestick", **kwargs): super(HighValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class DecreasingValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="decreasing", parent_name="candlestick", **kwargs): super(DecreasingValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Decreasing"), data_docs=kwargs.pop( "data_docs", """ fillcolor Sets the fill color. Defaults to a half- transparent variant of the line color, marker color, or marker line color, whichever is available. line plotly.graph_objects.candlestick.decreasing.Lin e instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class CustomdatasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="customdatasrc", parent_name="candlestick", **kwargs ): super(CustomdatasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdataValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="customdata", parent_name="candlestick", **kwargs): super(CustomdataValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class ClosesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="closesrc", parent_name="candlestick", **kwargs): super(ClosesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CloseValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="close", parent_name="candlestick", **kwargs): super(CloseValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/candlestick/line/0000755000175000017500000000000013573746614023177 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/candlestick/line/__init__.py0000644000175000017500000000074413573721536025311 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="candlestick.line", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/candlestick/decreasing/0000755000175000017500000000000013573746614024354 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/candlestick/decreasing/__init__.py0000644000175000017500000000225013573721536026460 0ustar noahfxnoahfximport _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="line", parent_name="candlestick.decreasing", **kwargs ): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ color Sets the color of line bounding the box(es). width Sets the width (in px) of line bounding the box(es). """, ), **kwargs ) import _plotly_utils.basevalidators class FillcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="fillcolor", parent_name="candlestick.decreasing", **kwargs ): super(FillcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/candlestick/decreasing/line/0000755000175000017500000000000013573746614025303 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/candlestick/decreasing/line/__init__.py0000644000175000017500000000172513573721536027415 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="width", parent_name="candlestick.decreasing.line", **kwargs ): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="candlestick.decreasing.line", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/choroplethmapbox/0000755000175000017500000000000013573746614023342 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/choroplethmapbox/unselected/0000755000175000017500000000000013573746614025475 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/choroplethmapbox/unselected/marker/0000755000175000017500000000000013573746614026756 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/choroplethmapbox/unselected/marker/__init__.py0000644000175000017500000000110713573721536031062 0ustar noahfxnoahfximport _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="opacity", parent_name="choroplethmapbox.unselected.marker", **kwargs ): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/choroplethmapbox/unselected/__init__.py0000644000175000017500000000125013573721536027600 0ustar noahfxnoahfximport _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="marker", parent_name="choroplethmapbox.unselected", **kwargs ): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ opacity Sets the marker opacity of unselected points, applied only when a selection exists. """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/choroplethmapbox/hoverlabel/0000755000175000017500000000000013573746614025465 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/choroplethmapbox/hoverlabel/__init__.py0000644000175000017500000001400013573721536027565 0ustar noahfxnoahfximport _plotly_utils.basevalidators class NamelengthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="namelengthsrc", parent_name="choroplethmapbox.hoverlabel", **kwargs ): super(NamelengthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NamelengthValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="namelength", parent_name="choroplethmapbox.hoverlabel", **kwargs ): super(NamelengthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", -1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="choroplethmapbox.hoverlabel", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class BordercolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bordercolorsrc", parent_name="choroplethmapbox.hoverlabel", **kwargs ): super(BordercolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="choroplethmapbox.hoverlabel", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bgcolorsrc", parent_name="choroplethmapbox.hoverlabel", **kwargs ): super(BgcolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="choroplethmapbox.hoverlabel", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AlignsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="alignsrc", parent_name="choroplethmapbox.hoverlabel", **kwargs ): super(AlignsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="align", parent_name="choroplethmapbox.hoverlabel", **kwargs ): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "right", "auto"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/choroplethmapbox/hoverlabel/font/0000755000175000017500000000000013573746614026433 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/choroplethmapbox/hoverlabel/font/__init__.py0000644000175000017500000000635313573721536030547 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="choroplethmapbox.hoverlabel.font", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="choroplethmapbox.hoverlabel.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="choroplethmapbox.hoverlabel.font", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="choroplethmapbox.hoverlabel.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="choroplethmapbox.hoverlabel.font", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="choroplethmapbox.hoverlabel.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/choroplethmapbox/colorbar/0000755000175000017500000000000013573746614025145 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/choroplethmapbox/colorbar/tickformatstop/0000755000175000017500000000000013573746614030216 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/choroplethmapbox/colorbar/tickformatstop/__init__.py0000644000175000017500000000545113573721536032330 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="value", parent_name="choroplethmapbox.colorbar.tickformatstop", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="choroplethmapbox.colorbar.tickformatstop", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="choroplethmapbox.colorbar.tickformatstop", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EnabledValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="enabled", parent_name="choroplethmapbox.colorbar.tickformatstop", **kwargs ): super(EnabledValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DtickrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="dtickrange", parent_name="choroplethmapbox.colorbar.tickformatstop", **kwargs ): super(DtickrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "colorbars"}, {"valType": "any", "editType": "colorbars"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/choroplethmapbox/colorbar/title/0000755000175000017500000000000013573746614026266 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/choroplethmapbox/colorbar/title/__init__.py0000644000175000017500000000506013573721536030374 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="text", parent_name="choroplethmapbox.colorbar.title", **kwargs ): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SideValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="side", parent_name="choroplethmapbox.colorbar.title", **kwargs ): super(SideValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["right", "top", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="choroplethmapbox.colorbar.title", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/choroplethmapbox/colorbar/title/font/0000755000175000017500000000000013573746614027234 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/choroplethmapbox/colorbar/title/font/__init__.py0000644000175000017500000000317713573721536031351 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="choroplethmapbox.colorbar.title.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="choroplethmapbox.colorbar.title.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="choroplethmapbox.colorbar.title.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/choroplethmapbox/colorbar/__init__.py0000644000175000017500000006167213573721537027267 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ypad", parent_name="choroplethmapbox.colorbar", **kwargs ): super(YpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class YanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="yanchor", parent_name="choroplethmapbox.colorbar", **kwargs ): super(YanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["top", "middle", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="y", parent_name="choroplethmapbox.colorbar", **kwargs ): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="xpad", parent_name="choroplethmapbox.colorbar", **kwargs ): super(XpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="xanchor", parent_name="choroplethmapbox.colorbar", **kwargs ): super(XanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "center", "right"]), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="x", parent_name="choroplethmapbox.colorbar", **kwargs ): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TitleValidator(_plotly_utils.basevalidators.TitleValidator): def __init__( self, plotly_name="title", parent_name="choroplethmapbox.colorbar", **kwargs ): super(TitleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Title"), data_docs=kwargs.pop( "data_docs", """ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """, ), **kwargs ) import _plotly_utils.basevalidators class TickwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="tickwidth", parent_name="choroplethmapbox.colorbar", **kwargs ): super(TickwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickvalssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="tickvalssrc", parent_name="choroplethmapbox.colorbar", **kwargs ): super(TickvalssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickvalsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="tickvals", parent_name="choroplethmapbox.colorbar", **kwargs ): super(TickvalsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="ticktextsrc", parent_name="choroplethmapbox.colorbar", **kwargs ): super(TicktextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicktextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="ticktext", parent_name="choroplethmapbox.colorbar", **kwargs ): super(TicktextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="ticksuffix", parent_name="choroplethmapbox.colorbar", **kwargs ): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TicksValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="ticks", parent_name="choroplethmapbox.colorbar", **kwargs ): super(TicksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["outside", "inside", ""]), **kwargs ) import _plotly_utils.basevalidators class TickprefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickprefix", parent_name="choroplethmapbox.colorbar", **kwargs ): super(TickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="tickmode", parent_name="choroplethmapbox.colorbar", **kwargs ): super(TickmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "linear", "array"]), **kwargs ) import _plotly_utils.basevalidators class TicklenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ticklen", parent_name="choroplethmapbox.colorbar", **kwargs ): super(TicklenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickformatstopValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickformatstopdefaults", parent_name="choroplethmapbox.colorbar", **kwargs ): super(TickformatstopValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatstopsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="tickformatstops", parent_name="choroplethmapbox.colorbar", **kwargs ): super(TickformatstopsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickformat", parent_name="choroplethmapbox.colorbar", **kwargs ): super(TickformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickfont", parent_name="choroplethmapbox.colorbar", **kwargs ): super(TickfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class TickcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="tickcolor", parent_name="choroplethmapbox.colorbar", **kwargs ): super(TickcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__( self, plotly_name="tickangle", parent_name="choroplethmapbox.colorbar", **kwargs ): super(TickangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="tick0", parent_name="choroplethmapbox.colorbar", **kwargs ): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ThicknessmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="thicknessmode", parent_name="choroplethmapbox.colorbar", **kwargs ): super(ThicknessmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="thickness", parent_name="choroplethmapbox.colorbar", **kwargs ): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowticksuffixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showticksuffix", parent_name="choroplethmapbox.colorbar", **kwargs ): super(ShowticksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowtickprefixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showtickprefix", parent_name="choroplethmapbox.colorbar", **kwargs ): super(ShowtickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowticklabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showticklabels", parent_name="choroplethmapbox.colorbar", **kwargs ): super(ShowticklabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowexponentValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showexponent", parent_name="choroplethmapbox.colorbar", **kwargs ): super(ShowexponentValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class SeparatethousandsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="separatethousands", parent_name="choroplethmapbox.colorbar", **kwargs ): super(SeparatethousandsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="outlinewidth", parent_name="choroplethmapbox.colorbar", **kwargs ): super(OutlinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="outlinecolor", parent_name="choroplethmapbox.colorbar", **kwargs ): super(OutlinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NticksValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="nticks", parent_name="choroplethmapbox.colorbar", **kwargs ): super(NticksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LenmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="lenmode", parent_name="choroplethmapbox.colorbar", **kwargs ): super(LenmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class LenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="len", parent_name="choroplethmapbox.colorbar", **kwargs ): super(LenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ExponentformatValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="exponentformat", parent_name="choroplethmapbox.colorbar", **kwargs ): super(ExponentformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "e", "E", "power", "SI", "B"]), **kwargs ) import _plotly_utils.basevalidators class DtickValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="dtick", parent_name="choroplethmapbox.colorbar", **kwargs ): super(DtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BorderwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="borderwidth", parent_name="choroplethmapbox.colorbar", **kwargs ): super(BorderwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="choroplethmapbox.colorbar", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="choroplethmapbox.colorbar", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/choroplethmapbox/colorbar/tickfont/0000755000175000017500000000000013573746614026766 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/choroplethmapbox/colorbar/tickfont/__init__.py0000644000175000017500000000317113573721536031075 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="choroplethmapbox.colorbar.tickfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="choroplethmapbox.colorbar.tickfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="choroplethmapbox.colorbar.tickfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/choroplethmapbox/marker/0000755000175000017500000000000013573746614024623 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/choroplethmapbox/marker/__init__.py0000644000175000017500000000434513573721536026736 0ustar noahfxnoahfximport _plotly_utils.basevalidators class OpacitysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="opacitysrc", parent_name="choroplethmapbox.marker", **kwargs ): super(OpacitysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="opacity", parent_name="choroplethmapbox.marker", **kwargs ): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="line", parent_name="choroplethmapbox.marker", **kwargs ): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. colorsrc Sets the source reference on plot.ly for color . width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/choroplethmapbox/marker/line/0000755000175000017500000000000013573746614025552 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/choroplethmapbox/marker/line/__init__.py0000644000175000017500000000404713573721536027664 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="widthsrc", parent_name="choroplethmapbox.marker.line", **kwargs ): super(WidthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="width", parent_name="choroplethmapbox.marker.line", **kwargs ): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="choroplethmapbox.marker.line", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="choroplethmapbox.marker.line", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/choroplethmapbox/stream/0000755000175000017500000000000013573746614024635 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/choroplethmapbox/stream/__init__.py0000644000175000017500000000214213573721536026741 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TokenValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="token", parent_name="choroplethmapbox.stream", **kwargs ): super(TokenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "info"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class MaxpointsValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="maxpoints", parent_name="choroplethmapbox.stream", **kwargs ): super(MaxpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 10000), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/choroplethmapbox/__init__.py0000644000175000017500000010077513573721537025462 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ZsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="zsrc", parent_name="choroplethmapbox", **kwargs): super(ZsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="zmin", parent_name="choroplethmapbox", **kwargs): super(ZminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"zauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZmidValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="zmid", parent_name="choroplethmapbox", **kwargs): super(ZmidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZmaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="zmax", parent_name="choroplethmapbox", **kwargs): super(ZmaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"zauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZautoValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="zauto", parent_name="choroplethmapbox", **kwargs): super(ZautoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="z", parent_name="choroplethmapbox", **kwargs): super(ZValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="visible", parent_name="choroplethmapbox", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "legendonly"]), **kwargs ) import _plotly_utils.basevalidators class UnselectedValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="unselected", parent_name="choroplethmapbox", **kwargs ): super(UnselectedValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Unselected"), data_docs=kwargs.pop( "data_docs", """ marker plotly.graph_objects.choroplethmapbox.unselecte d.Marker instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="uirevision", parent_name="choroplethmapbox", **kwargs ): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UidValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="uid", parent_name="choroplethmapbox", **kwargs): super(UidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="textsrc", parent_name="choroplethmapbox", **kwargs): super(TextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="text", parent_name="choroplethmapbox", **kwargs): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SubplotValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="subplot", parent_name="choroplethmapbox", **kwargs): super(SubplotValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "mapbox"), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class StreamValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="stream", parent_name="choroplethmapbox", **kwargs): super(StreamValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Stream"), data_docs=kwargs.pop( "data_docs", """ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """, ), **kwargs ) import _plotly_utils.basevalidators class ShowscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showscale", parent_name="choroplethmapbox", **kwargs ): super(ShowscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SelectedpointsValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="selectedpoints", parent_name="choroplethmapbox", **kwargs ): super(SelectedpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SelectedValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="selected", parent_name="choroplethmapbox", **kwargs ): super(SelectedValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Selected"), data_docs=kwargs.pop( "data_docs", """ marker plotly.graph_objects.choroplethmapbox.selected. Marker instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class ReversescaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="reversescale", parent_name="choroplethmapbox", **kwargs ): super(ReversescaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="choroplethmapbox", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="metasrc", parent_name="choroplethmapbox", **kwargs): super(MetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetaValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="meta", parent_name="choroplethmapbox", **kwargs): super(MetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="marker", parent_name="choroplethmapbox", **kwargs): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ line plotly.graph_objects.choroplethmapbox.marker.Li ne instance or dict with compatible properties opacity Sets the opacity of the locations. opacitysrc Sets the source reference on plot.ly for opacity . """, ), **kwargs ) import _plotly_utils.basevalidators class LocationssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="locationssrc", parent_name="choroplethmapbox", **kwargs ): super(LocationssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LocationsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="locations", parent_name="choroplethmapbox", **kwargs ): super(LocationsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class IdssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="idssrc", parent_name="choroplethmapbox", **kwargs): super(IdssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ids", parent_name="choroplethmapbox", **kwargs): super(IdsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class HovertextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="hovertextsrc", parent_name="choroplethmapbox", **kwargs ): super(HovertextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertextValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="hovertext", parent_name="choroplethmapbox", **kwargs ): super(HovertextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="hovertemplatesrc", parent_name="choroplethmapbox", **kwargs ): super(HovertemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="hovertemplate", parent_name="choroplethmapbox", **kwargs ): super(HovertemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverlabelValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="hoverlabel", parent_name="choroplethmapbox", **kwargs ): super(HoverlabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Hoverlabel"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """, ), **kwargs ) import _plotly_utils.basevalidators class HoverinfosrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="hoverinfosrc", parent_name="choroplethmapbox", **kwargs ): super(HoverinfosrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverinfoValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__( self, plotly_name="hoverinfo", parent_name="choroplethmapbox", **kwargs ): super(HoverinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), extras=kwargs.pop("extras", ["all", "none", "skip"]), flags=kwargs.pop("flags", ["location", "z", "text", "name"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class GeojsonValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="geojson", parent_name="choroplethmapbox", **kwargs): super(GeojsonValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdatasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="customdatasrc", parent_name="choroplethmapbox", **kwargs ): super(CustomdatasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdataValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="customdata", parent_name="choroplethmapbox", **kwargs ): super(CustomdataValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__( self, plotly_name="colorscale", parent_name="choroplethmapbox", **kwargs ): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"autocolorscale": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorBarValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="colorbar", parent_name="choroplethmapbox", **kwargs ): super(ColorBarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "ColorBar"), data_docs=kwargs.pop( "data_docs", """ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.choroplethmapbo x.colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.choroplethmapbox.colorbar.tickformatstopdefau lts), sets the default property values to use for elements of choroplethmapbox.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.choroplethmapbox.colorbar. Title instance or dict with compatible properties titlefont Deprecated: Please use choroplethmapbox.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use choroplethmapbox.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """, ), **kwargs ) import _plotly_utils.basevalidators class ColoraxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__( self, plotly_name="coloraxis", parent_name="choroplethmapbox", **kwargs ): super(ColoraxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", None), edit_type=kwargs.pop("edit_type", "calc"), regex=kwargs.pop("regex", "/^coloraxis([2-9]|[1-9][0-9]+)?$/"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BelowValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="below", parent_name="choroplethmapbox", **kwargs): super(BelowValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AutocolorscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="autocolorscale", parent_name="choroplethmapbox", **kwargs ): super(AutocolorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/choroplethmapbox/selected/0000755000175000017500000000000013573746614025132 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/choroplethmapbox/selected/marker/0000755000175000017500000000000013573746614026413 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/choroplethmapbox/selected/marker/__init__.py0000644000175000017500000000110513573721536030515 0ustar noahfxnoahfximport _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="opacity", parent_name="choroplethmapbox.selected.marker", **kwargs ): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/choroplethmapbox/selected/__init__.py0000644000175000017500000000115613573721536027242 0ustar noahfxnoahfximport _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="marker", parent_name="choroplethmapbox.selected", **kwargs ): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ opacity Sets the marker opacity of selected points. """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/volume/0000755000175000017500000000000013573746614021273 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/volume/contour/0000755000175000017500000000000013573746614022764 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/volume/contour/__init__.py0000644000175000017500000000257613573721544025102 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="volume.contour", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 16), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="show", parent_name="volume.contour", **kwargs): super(ShowValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="volume.contour", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/volume/hoverlabel/0000755000175000017500000000000013573746614023416 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/volume/hoverlabel/__init__.py0000644000175000017500000001337213573721544025530 0ustar noahfxnoahfximport _plotly_utils.basevalidators class NamelengthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="namelengthsrc", parent_name="volume.hoverlabel", **kwargs ): super(NamelengthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NamelengthValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="namelength", parent_name="volume.hoverlabel", **kwargs ): super(NamelengthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", -1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="font", parent_name="volume.hoverlabel", **kwargs): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class BordercolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bordercolorsrc", parent_name="volume.hoverlabel", **kwargs ): super(BordercolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="volume.hoverlabel", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bgcolorsrc", parent_name="volume.hoverlabel", **kwargs ): super(BgcolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="volume.hoverlabel", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AlignsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="alignsrc", parent_name="volume.hoverlabel", **kwargs ): super(AlignsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="align", parent_name="volume.hoverlabel", **kwargs): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "right", "auto"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/volume/hoverlabel/font/0000755000175000017500000000000013573746614024364 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/volume/hoverlabel/font/__init__.py0000644000175000017500000000603713573721544026476 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="volume.hoverlabel.font", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="volume.hoverlabel.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="volume.hoverlabel.font", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="volume.hoverlabel.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="volume.hoverlabel.font", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="volume.hoverlabel.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/volume/colorbar/0000755000175000017500000000000013573746614023076 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/volume/colorbar/tickformatstop/0000755000175000017500000000000013573746614026147 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/volume/colorbar/tickformatstop/__init__.py0000644000175000017500000000527413573721544030263 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="value", parent_name="volume.colorbar.tickformatstop", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="volume.colorbar.tickformatstop", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="volume.colorbar.tickformatstop", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EnabledValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="enabled", parent_name="volume.colorbar.tickformatstop", **kwargs ): super(EnabledValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DtickrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="dtickrange", parent_name="volume.colorbar.tickformatstop", **kwargs ): super(DtickrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "calc"}, {"valType": "any", "editType": "calc"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/volume/colorbar/title/0000755000175000017500000000000013573746614024217 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/volume/colorbar/title/__init__.py0000644000175000017500000000470013573721544026324 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="text", parent_name="volume.colorbar.title", **kwargs ): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SideValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="side", parent_name="volume.colorbar.title", **kwargs ): super(SideValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["right", "top", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="volume.colorbar.title", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/volume/colorbar/title/font/0000755000175000017500000000000013573746614025165 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/volume/colorbar/title/font/__init__.py0000644000175000017500000000301213573721544027265 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="volume.colorbar.title.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="volume.colorbar.title.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="volume.colorbar.title.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/volume/colorbar/__init__.py0000644000175000017500000005731713573721544025217 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="ypad", parent_name="volume.colorbar", **kwargs): super(YpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class YanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="yanchor", parent_name="volume.colorbar", **kwargs): super(YanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["top", "middle", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="y", parent_name="volume.colorbar", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="xpad", parent_name="volume.colorbar", **kwargs): super(XpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="xanchor", parent_name="volume.colorbar", **kwargs): super(XanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "center", "right"]), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="x", parent_name="volume.colorbar", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TitleValidator(_plotly_utils.basevalidators.TitleValidator): def __init__(self, plotly_name="title", parent_name="volume.colorbar", **kwargs): super(TitleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Title"), data_docs=kwargs.pop( "data_docs", """ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """, ), **kwargs ) import _plotly_utils.basevalidators class TickwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="tickwidth", parent_name="volume.colorbar", **kwargs ): super(TickwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickvalssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="tickvalssrc", parent_name="volume.colorbar", **kwargs ): super(TickvalssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickvalsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="tickvals", parent_name="volume.colorbar", **kwargs): super(TickvalsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="ticktextsrc", parent_name="volume.colorbar", **kwargs ): super(TicktextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicktextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ticktext", parent_name="volume.colorbar", **kwargs): super(TicktextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="ticksuffix", parent_name="volume.colorbar", **kwargs ): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TicksValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="ticks", parent_name="volume.colorbar", **kwargs): super(TicksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["outside", "inside", ""]), **kwargs ) import _plotly_utils.basevalidators class TickprefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickprefix", parent_name="volume.colorbar", **kwargs ): super(TickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="tickmode", parent_name="volume.colorbar", **kwargs): super(TickmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "linear", "array"]), **kwargs ) import _plotly_utils.basevalidators class TicklenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="ticklen", parent_name="volume.colorbar", **kwargs): super(TicklenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickformatstopValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickformatstopdefaults", parent_name="volume.colorbar", **kwargs ): super(TickformatstopValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatstopsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="tickformatstops", parent_name="volume.colorbar", **kwargs ): super(TickformatstopsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickformat", parent_name="volume.colorbar", **kwargs ): super(TickformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="tickfont", parent_name="volume.colorbar", **kwargs): super(TickfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class TickcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="tickcolor", parent_name="volume.colorbar", **kwargs ): super(TickcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__( self, plotly_name="tickangle", parent_name="volume.colorbar", **kwargs ): super(TickangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="tick0", parent_name="volume.colorbar", **kwargs): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ThicknessmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="thicknessmode", parent_name="volume.colorbar", **kwargs ): super(ThicknessmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="thickness", parent_name="volume.colorbar", **kwargs ): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowticksuffixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showticksuffix", parent_name="volume.colorbar", **kwargs ): super(ShowticksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowtickprefixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showtickprefix", parent_name="volume.colorbar", **kwargs ): super(ShowtickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowticklabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showticklabels", parent_name="volume.colorbar", **kwargs ): super(ShowticklabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowexponentValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showexponent", parent_name="volume.colorbar", **kwargs ): super(ShowexponentValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class SeparatethousandsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="separatethousands", parent_name="volume.colorbar", **kwargs ): super(SeparatethousandsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="outlinewidth", parent_name="volume.colorbar", **kwargs ): super(OutlinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="outlinecolor", parent_name="volume.colorbar", **kwargs ): super(OutlinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NticksValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="nticks", parent_name="volume.colorbar", **kwargs): super(NticksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LenmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="lenmode", parent_name="volume.colorbar", **kwargs): super(LenmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class LenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="len", parent_name="volume.colorbar", **kwargs): super(LenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ExponentformatValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="exponentformat", parent_name="volume.colorbar", **kwargs ): super(ExponentformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "e", "E", "power", "SI", "B"]), **kwargs ) import _plotly_utils.basevalidators class DtickValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="dtick", parent_name="volume.colorbar", **kwargs): super(DtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BorderwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="borderwidth", parent_name="volume.colorbar", **kwargs ): super(BorderwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="volume.colorbar", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="bgcolor", parent_name="volume.colorbar", **kwargs): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/volume/colorbar/tickfont/0000755000175000017500000000000013573746614024717 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/volume/colorbar/tickfont/__init__.py0000644000175000017500000000300413573721544027020 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="volume.colorbar.tickfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="volume.colorbar.tickfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="volume.colorbar.tickfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/volume/caps/0000755000175000017500000000000013573746614022221 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/volume/caps/x/0000755000175000017500000000000013573746614022470 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/volume/caps/x/__init__.py0000644000175000017500000000167413573721544024604 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ShowValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="show", parent_name="volume.caps.x", **kwargs): super(ShowValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FillValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="fill", parent_name="volume.caps.x", **kwargs): super(FillValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/volume/caps/z/0000755000175000017500000000000013573746614022472 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/volume/caps/z/__init__.py0000644000175000017500000000167413573721544024606 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ShowValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="show", parent_name="volume.caps.z", **kwargs): super(ShowValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FillValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="fill", parent_name="volume.caps.z", **kwargs): super(FillValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/volume/caps/y/0000755000175000017500000000000013573746614022471 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/volume/caps/y/__init__.py0000644000175000017500000000167413573721544024605 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ShowValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="show", parent_name="volume.caps.y", **kwargs): super(ShowValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FillValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="fill", parent_name="volume.caps.y", **kwargs): super(FillValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/volume/caps/__init__.py0000644000175000017500000000670613573721544024336 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ZValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="z", parent_name="volume.caps", **kwargs): super(ZValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Z"), data_docs=kwargs.pop( "data_docs", """ fill Sets the fill ratio of the `caps`. The default fill value of the `caps` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. show Sets the fill ratio of the `slices`. The default fill value of the z `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. """, ), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="y", parent_name="volume.caps", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Y"), data_docs=kwargs.pop( "data_docs", """ fill Sets the fill ratio of the `caps`. The default fill value of the `caps` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. show Sets the fill ratio of the `slices`. The default fill value of the y `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. """, ), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="x", parent_name="volume.caps", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "X"), data_docs=kwargs.pop( "data_docs", """ fill Sets the fill ratio of the `caps`. The default fill value of the `caps` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. show Sets the fill ratio of the `slices`. The default fill value of the x `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/volume/lightposition/0000755000175000017500000000000013573746614024167 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/volume/lightposition/__init__.py0000644000175000017500000000305013573721544026271 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ZValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="z", parent_name="volume.lightposition", **kwargs): super(ZValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 100000), min=kwargs.pop("min", -100000), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="y", parent_name="volume.lightposition", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 100000), min=kwargs.pop("min", -100000), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="x", parent_name="volume.lightposition", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 100000), min=kwargs.pop("min", -100000), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/volume/slices/0000755000175000017500000000000013573746614022555 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/volume/slices/x/0000755000175000017500000000000013573746614023024 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/volume/slices/x/__init__.py0000644000175000017500000000356713573721544025143 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ShowValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="show", parent_name="volume.slices.x", **kwargs): super(ShowValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LocationssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="locationssrc", parent_name="volume.slices.x", **kwargs ): super(LocationssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LocationsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="locations", parent_name="volume.slices.x", **kwargs ): super(LocationsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class FillValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="fill", parent_name="volume.slices.x", **kwargs): super(FillValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/volume/slices/z/0000755000175000017500000000000013573746614023026 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/volume/slices/z/__init__.py0000644000175000017500000000356713573721544025145 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ShowValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="show", parent_name="volume.slices.z", **kwargs): super(ShowValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LocationssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="locationssrc", parent_name="volume.slices.z", **kwargs ): super(LocationssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LocationsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="locations", parent_name="volume.slices.z", **kwargs ): super(LocationsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class FillValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="fill", parent_name="volume.slices.z", **kwargs): super(FillValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/volume/slices/y/0000755000175000017500000000000013573746614023025 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/volume/slices/y/__init__.py0000644000175000017500000000356713573721544025144 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ShowValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="show", parent_name="volume.slices.y", **kwargs): super(ShowValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LocationssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="locationssrc", parent_name="volume.slices.y", **kwargs ): super(LocationssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LocationsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="locations", parent_name="volume.slices.y", **kwargs ): super(LocationsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class FillValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="fill", parent_name="volume.slices.y", **kwargs): super(FillValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/volume/slices/__init__.py0000644000175000017500000000751713573721544024673 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ZValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="z", parent_name="volume.slices", **kwargs): super(ZValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Z"), data_docs=kwargs.pop( "data_docs", """ fill Sets the fill ratio of the `slices`. The default fill value of the `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. locations Specifies the location(s) of slices on the axis. When not specified slices would be created for all points of the axis z except start and end. locationssrc Sets the source reference on plot.ly for locations . show Determines whether or not slice planes about the z dimension are drawn. """, ), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="y", parent_name="volume.slices", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Y"), data_docs=kwargs.pop( "data_docs", """ fill Sets the fill ratio of the `slices`. The default fill value of the `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. locations Specifies the location(s) of slices on the axis. When not specified slices would be created for all points of the axis y except start and end. locationssrc Sets the source reference on plot.ly for locations . show Determines whether or not slice planes about the y dimension are drawn. """, ), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="x", parent_name="volume.slices", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "X"), data_docs=kwargs.pop( "data_docs", """ fill Sets the fill ratio of the `slices`. The default fill value of the `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. locations Specifies the location(s) of slices on the axis. When not specified slices would be created for all points of the axis x except start and end. locationssrc Sets the source reference on plot.ly for locations . show Determines whether or not slice planes about the x dimension are drawn. """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/volume/surface/0000755000175000017500000000000013573746614022723 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/volume/surface/__init__.py0000644000175000017500000000375113573721544025035 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ShowValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="show", parent_name="volume.surface", **kwargs): super(ShowValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class PatternValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="pattern", parent_name="volume.surface", **kwargs): super(PatternValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), extras=kwargs.pop("extras", ["all", "odd", "even"]), flags=kwargs.pop("flags", ["A", "B", "C", "D", "E"]), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FillValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="fill", parent_name="volume.surface", **kwargs): super(FillValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class CountValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="count", parent_name="volume.surface", **kwargs): super(CountValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/volume/stream/0000755000175000017500000000000013573746614022566 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/volume/stream/__init__.py0000644000175000017500000000206213573721544024672 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TokenValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="token", parent_name="volume.stream", **kwargs): super(TokenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "info"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class MaxpointsValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="maxpoints", parent_name="volume.stream", **kwargs): super(MaxpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 10000), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/volume/__init__.py0000644000175000017500000011777713573721545023424 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ZsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="zsrc", parent_name="volume", **kwargs): super(ZsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="z", parent_name="volume", **kwargs): super(ZValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class YsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="ysrc", parent_name="volume", **kwargs): super(YsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="y", parent_name="volume", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class XsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="xsrc", parent_name="volume", **kwargs): super(XsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="x", parent_name="volume", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="visible", parent_name="volume", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "legendonly"]), **kwargs ) import _plotly_utils.basevalidators class ValuesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="valuesrc", parent_name="volume", **kwargs): super(ValuesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="value", parent_name="volume", **kwargs): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="volume", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UidValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="uid", parent_name="volume", **kwargs): super(UidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="textsrc", parent_name="volume", **kwargs): super(TextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="text", parent_name="volume", **kwargs): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SurfaceValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="surface", parent_name="volume", **kwargs): super(SurfaceValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Surface"), data_docs=kwargs.pop( "data_docs", """ count Sets the number of iso-surfaces between minimum and maximum iso-values. By default this value is 2 meaning that only minimum and maximum surfaces would be drawn. fill Sets the fill ratio of the iso-surface. The default fill value of the surface is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. pattern Sets the surface pattern of the iso-surface 3-D sections. The default pattern of the surface is `all` meaning that the rest of surface elements would be shaded. The check options (either 1 or 2) could be used to draw half of the squares on the surface. Using various combinations of capital `A`, `B`, `C`, `D` and `E` may also be used to reduce the number of triangles on the iso-surfaces and creating other patterns of interest. show Hides/displays surfaces between minimum and maximum iso-values. """, ), **kwargs ) import _plotly_utils.basevalidators class StreamValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="stream", parent_name="volume", **kwargs): super(StreamValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Stream"), data_docs=kwargs.pop( "data_docs", """ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """, ), **kwargs ) import _plotly_utils.basevalidators class SpaceframeValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="spaceframe", parent_name="volume", **kwargs): super(SpaceframeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Spaceframe"), data_docs=kwargs.pop( "data_docs", """ fill Sets the fill ratio of the `spaceframe` elements. The default fill value is 1 meaning that they are entirely shaded. Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. show Displays/hides tetrahedron shapes between minimum and maximum iso-values. Often useful when either caps or surfaces are disabled or filled with values less than 1. """, ), **kwargs ) import _plotly_utils.basevalidators class SlicesValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="slices", parent_name="volume", **kwargs): super(SlicesValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Slices"), data_docs=kwargs.pop( "data_docs", """ x plotly.graph_objects.volume.slices.X instance or dict with compatible properties y plotly.graph_objects.volume.slices.Y instance or dict with compatible properties z plotly.graph_objects.volume.slices.Z instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class ShowscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showscale", parent_name="volume", **kwargs): super(ShowscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SceneValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="scene", parent_name="volume", **kwargs): super(SceneValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "scene"), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ReversescaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="reversescale", parent_name="volume", **kwargs): super(ReversescaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacityscaleValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="opacityscale", parent_name="volume", **kwargs): super(OpacityscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="volume", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="volume", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="metasrc", parent_name="volume", **kwargs): super(MetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetaValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="meta", parent_name="volume", **kwargs): super(MetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LightpositionValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="lightposition", parent_name="volume", **kwargs): super(LightpositionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Lightposition"), data_docs=kwargs.pop( "data_docs", """ x Numeric vector, representing the X coordinate for each vertex. y Numeric vector, representing the Y coordinate for each vertex. z Numeric vector, representing the Z coordinate for each vertex. """, ), **kwargs ) import _plotly_utils.basevalidators class LightingValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="lighting", parent_name="volume", **kwargs): super(LightingValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Lighting"), data_docs=kwargs.pop( "data_docs", """ ambient Ambient light increases overall color visibility but can wash out the image. diffuse Represents the extent that incident rays are reflected in a range of angles. facenormalsepsilon Epsilon for face normals calculation avoids math issues arising from degenerate geometry. fresnel Represents the reflectance as a dependency of the viewing angle; e.g. paper is reflective when viewing it from the edge of the paper (almost 90 degrees), causing shine. roughness Alters specular reflection; the rougher the surface, the wider and less contrasty the shine. specular Represents the level that incident rays are reflected in a single direction, causing shine. vertexnormalsepsilon Epsilon for vertex normals calculation avoids math issues arising from degenerate geometry. """, ), **kwargs ) import _plotly_utils.basevalidators class IsominValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="isomin", parent_name="volume", **kwargs): super(IsominValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IsomaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="isomax", parent_name="volume", **kwargs): super(IsomaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="idssrc", parent_name="volume", **kwargs): super(IdssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ids", parent_name="volume", **kwargs): super(IdsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class HovertextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hovertextsrc", parent_name="volume", **kwargs): super(HovertextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertext", parent_name="volume", **kwargs): super(HovertextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hovertemplatesrc", parent_name="volume", **kwargs): super(HovertemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertemplate", parent_name="volume", **kwargs): super(HovertemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverlabelValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="hoverlabel", parent_name="volume", **kwargs): super(HoverlabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Hoverlabel"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """, ), **kwargs ) import _plotly_utils.basevalidators class HoverinfosrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hoverinfosrc", parent_name="volume", **kwargs): super(HoverinfosrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverinfoValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="hoverinfo", parent_name="volume", **kwargs): super(HoverinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), extras=kwargs.pop("extras", ["all", "none", "skip"]), flags=kwargs.pop("flags", ["x", "y", "z", "text", "name"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FlatshadingValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="flatshading", parent_name="volume", **kwargs): super(FlatshadingValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class CustomdatasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="customdatasrc", parent_name="volume", **kwargs): super(CustomdatasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdataValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="customdata", parent_name="volume", **kwargs): super(CustomdataValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class ContourValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="contour", parent_name="volume", **kwargs): super(ContourValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Contour"), data_docs=kwargs.pop( "data_docs", """ color Sets the color of the contour lines. show Sets whether or not dynamic contours are shown on hover width Sets the width of the contour lines. """, ), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__(self, plotly_name="colorscale", parent_name="volume", **kwargs): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"autocolorscale": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorBarValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="colorbar", parent_name="volume", **kwargs): super(ColorBarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "ColorBar"), data_docs=kwargs.pop( "data_docs", """ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.volume.colorbar .Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.volume.colorbar.tickformatstopdefaults), sets the default property values to use for elements of volume.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.volume.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use volume.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use volume.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """, ), **kwargs ) import _plotly_utils.basevalidators class ColoraxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="coloraxis", parent_name="volume", **kwargs): super(ColoraxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", None), edit_type=kwargs.pop("edit_type", "calc"), regex=kwargs.pop("regex", "/^coloraxis([2-9]|[1-9][0-9]+)?$/"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmin", parent_name="volume", **kwargs): super(CminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmidValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmid", parent_name="volume", **kwargs): super(CmidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmax", parent_name="volume", **kwargs): super(CmaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CautoValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="cauto", parent_name="volume", **kwargs): super(CautoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CapsValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="caps", parent_name="volume", **kwargs): super(CapsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Caps"), data_docs=kwargs.pop( "data_docs", """ x plotly.graph_objects.volume.caps.X instance or dict with compatible properties y plotly.graph_objects.volume.caps.Y instance or dict with compatible properties z plotly.graph_objects.volume.caps.Z instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class AutocolorscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="autocolorscale", parent_name="volume", **kwargs): super(AutocolorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/volume/lighting/0000755000175000017500000000000013573746614023100 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/volume/lighting/__init__.py0000644000175000017500000000740113573721544025206 0ustar noahfxnoahfximport _plotly_utils.basevalidators class VertexnormalsepsilonValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="vertexnormalsepsilon", parent_name="volume.lighting", **kwargs ): super(VertexnormalsepsilonValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SpecularValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="specular", parent_name="volume.lighting", **kwargs): super(SpecularValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 2), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class RoughnessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="roughness", parent_name="volume.lighting", **kwargs ): super(RoughnessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FresnelValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="fresnel", parent_name="volume.lighting", **kwargs): super(FresnelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 5), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FacenormalsepsilonValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="facenormalsepsilon", parent_name="volume.lighting", **kwargs ): super(FacenormalsepsilonValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class DiffuseValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="diffuse", parent_name="volume.lighting", **kwargs): super(DiffuseValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AmbientValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="ambient", parent_name="volume.lighting", **kwargs): super(AmbientValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/volume/spaceframe/0000755000175000017500000000000013573746614023401 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/volume/spaceframe/__init__.py0000644000175000017500000000170413573721544025507 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ShowValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="show", parent_name="volume.spaceframe", **kwargs): super(ShowValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FillValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="fill", parent_name="volume.spaceframe", **kwargs): super(FillValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/funnel/0000755000175000017500000000000013573746614021253 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/funnel/connector/0000755000175000017500000000000013573746614023245 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/funnel/connector/__init__.py0000644000175000017500000000342313573721537025355 0ustar noahfxnoahfximport _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="visible", parent_name="funnel.connector", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="line", parent_name="funnel.connector", **kwargs): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ color Sets the line color. dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). width Sets the line width (in px). """, ), **kwargs ) import _plotly_utils.basevalidators class FillcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="fillcolor", parent_name="funnel.connector", **kwargs ): super(FillcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/funnel/connector/line/0000755000175000017500000000000013573746614024174 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/funnel/connector/line/__init__.py0000644000175000017500000000303713573721537026305 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="width", parent_name="funnel.connector.line", **kwargs ): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class DashValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="dash", parent_name="funnel.connector.line", **kwargs ): super(DashValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", ["solid", "dot", "dash", "longdash", "dashdot", "longdashdot"] ), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="funnel.connector.line", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/funnel/textfont/0000755000175000017500000000000013573746614023126 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/funnel/textfont/__init__.py0000644000175000017500000000566013573721537025243 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="sizesrc", parent_name="funnel.textfont", **kwargs): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="size", parent_name="funnel.textfont", **kwargs): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="funnel.textfont", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="family", parent_name="funnel.textfont", **kwargs): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="colorsrc", parent_name="funnel.textfont", **kwargs): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="funnel.textfont", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/funnel/hoverlabel/0000755000175000017500000000000013573746614023376 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/funnel/hoverlabel/__init__.py0000644000175000017500000001337213573721537025512 0ustar noahfxnoahfximport _plotly_utils.basevalidators class NamelengthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="namelengthsrc", parent_name="funnel.hoverlabel", **kwargs ): super(NamelengthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NamelengthValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="namelength", parent_name="funnel.hoverlabel", **kwargs ): super(NamelengthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", -1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="font", parent_name="funnel.hoverlabel", **kwargs): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class BordercolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bordercolorsrc", parent_name="funnel.hoverlabel", **kwargs ): super(BordercolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="funnel.hoverlabel", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bgcolorsrc", parent_name="funnel.hoverlabel", **kwargs ): super(BgcolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="funnel.hoverlabel", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AlignsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="alignsrc", parent_name="funnel.hoverlabel", **kwargs ): super(AlignsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="align", parent_name="funnel.hoverlabel", **kwargs): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "right", "auto"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/funnel/hoverlabel/font/0000755000175000017500000000000013573746614024344 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/funnel/hoverlabel/font/__init__.py0000644000175000017500000000603713573721537026460 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="funnel.hoverlabel.font", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="funnel.hoverlabel.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="funnel.hoverlabel.font", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="funnel.hoverlabel.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="funnel.hoverlabel.font", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="funnel.hoverlabel.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/funnel/outsidetextfont/0000755000175000017500000000000013573746614024523 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/funnel/outsidetextfont/__init__.py0000644000175000017500000000604013573721537026631 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="funnel.outsidetextfont", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="funnel.outsidetextfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="funnel.outsidetextfont", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="funnel.outsidetextfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="funnel.outsidetextfont", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="funnel.outsidetextfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/funnel/marker/0000755000175000017500000000000013573746614022534 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/funnel/marker/colorbar/0000755000175000017500000000000013573746614024337 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/funnel/marker/colorbar/tickformatstop/0000755000175000017500000000000013573746614027410 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/funnel/marker/colorbar/tickformatstop/__init__.py0000644000175000017500000000543213573721537031522 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="value", parent_name="funnel.marker.colorbar.tickformatstop", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="funnel.marker.colorbar.tickformatstop", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="funnel.marker.colorbar.tickformatstop", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EnabledValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="enabled", parent_name="funnel.marker.colorbar.tickformatstop", **kwargs ): super(EnabledValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DtickrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="dtickrange", parent_name="funnel.marker.colorbar.tickformatstop", **kwargs ): super(DtickrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "colorbars"}, {"valType": "any", "editType": "colorbars"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/funnel/marker/colorbar/title/0000755000175000017500000000000013573746614025460 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/funnel/marker/colorbar/title/__init__.py0000644000175000017500000000473713573721537027601 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="text", parent_name="funnel.marker.colorbar.title", **kwargs ): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SideValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="side", parent_name="funnel.marker.colorbar.title", **kwargs ): super(SideValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["right", "top", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="funnel.marker.colorbar.title", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/funnel/marker/colorbar/title/font/0000755000175000017500000000000013573746614026426 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/funnel/marker/colorbar/title/font/__init__.py0000644000175000017500000000316613573721537030542 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="funnel.marker.colorbar.title.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="funnel.marker.colorbar.title.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="funnel.marker.colorbar.title.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/funnel/marker/colorbar/__init__.py0000644000175000017500000006106313573721537026453 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ypad", parent_name="funnel.marker.colorbar", **kwargs ): super(YpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class YanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="yanchor", parent_name="funnel.marker.colorbar", **kwargs ): super(YanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["top", "middle", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="y", parent_name="funnel.marker.colorbar", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="xpad", parent_name="funnel.marker.colorbar", **kwargs ): super(XpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="xanchor", parent_name="funnel.marker.colorbar", **kwargs ): super(XanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "center", "right"]), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="x", parent_name="funnel.marker.colorbar", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TitleValidator(_plotly_utils.basevalidators.TitleValidator): def __init__( self, plotly_name="title", parent_name="funnel.marker.colorbar", **kwargs ): super(TitleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Title"), data_docs=kwargs.pop( "data_docs", """ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """, ), **kwargs ) import _plotly_utils.basevalidators class TickwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="tickwidth", parent_name="funnel.marker.colorbar", **kwargs ): super(TickwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickvalssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="tickvalssrc", parent_name="funnel.marker.colorbar", **kwargs ): super(TickvalssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickvalsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="tickvals", parent_name="funnel.marker.colorbar", **kwargs ): super(TickvalsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="ticktextsrc", parent_name="funnel.marker.colorbar", **kwargs ): super(TicktextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicktextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="ticktext", parent_name="funnel.marker.colorbar", **kwargs ): super(TicktextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="ticksuffix", parent_name="funnel.marker.colorbar", **kwargs ): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TicksValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="ticks", parent_name="funnel.marker.colorbar", **kwargs ): super(TicksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["outside", "inside", ""]), **kwargs ) import _plotly_utils.basevalidators class TickprefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickprefix", parent_name="funnel.marker.colorbar", **kwargs ): super(TickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="tickmode", parent_name="funnel.marker.colorbar", **kwargs ): super(TickmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "linear", "array"]), **kwargs ) import _plotly_utils.basevalidators class TicklenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ticklen", parent_name="funnel.marker.colorbar", **kwargs ): super(TicklenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickformatstopValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickformatstopdefaults", parent_name="funnel.marker.colorbar", **kwargs ): super(TickformatstopValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatstopsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="tickformatstops", parent_name="funnel.marker.colorbar", **kwargs ): super(TickformatstopsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickformat", parent_name="funnel.marker.colorbar", **kwargs ): super(TickformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickfont", parent_name="funnel.marker.colorbar", **kwargs ): super(TickfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class TickcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="tickcolor", parent_name="funnel.marker.colorbar", **kwargs ): super(TickcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__( self, plotly_name="tickangle", parent_name="funnel.marker.colorbar", **kwargs ): super(TickangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="tick0", parent_name="funnel.marker.colorbar", **kwargs ): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ThicknessmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="thicknessmode", parent_name="funnel.marker.colorbar", **kwargs ): super(ThicknessmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="thickness", parent_name="funnel.marker.colorbar", **kwargs ): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowticksuffixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showticksuffix", parent_name="funnel.marker.colorbar", **kwargs ): super(ShowticksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowtickprefixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showtickprefix", parent_name="funnel.marker.colorbar", **kwargs ): super(ShowtickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowticklabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showticklabels", parent_name="funnel.marker.colorbar", **kwargs ): super(ShowticklabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowexponentValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showexponent", parent_name="funnel.marker.colorbar", **kwargs ): super(ShowexponentValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class SeparatethousandsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="separatethousands", parent_name="funnel.marker.colorbar", **kwargs ): super(SeparatethousandsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="outlinewidth", parent_name="funnel.marker.colorbar", **kwargs ): super(OutlinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="outlinecolor", parent_name="funnel.marker.colorbar", **kwargs ): super(OutlinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NticksValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="nticks", parent_name="funnel.marker.colorbar", **kwargs ): super(NticksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LenmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="lenmode", parent_name="funnel.marker.colorbar", **kwargs ): super(LenmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class LenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="len", parent_name="funnel.marker.colorbar", **kwargs ): super(LenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ExponentformatValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="exponentformat", parent_name="funnel.marker.colorbar", **kwargs ): super(ExponentformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "e", "E", "power", "SI", "B"]), **kwargs ) import _plotly_utils.basevalidators class DtickValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="dtick", parent_name="funnel.marker.colorbar", **kwargs ): super(DtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BorderwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="borderwidth", parent_name="funnel.marker.colorbar", **kwargs ): super(BorderwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="funnel.marker.colorbar", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="funnel.marker.colorbar", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/funnel/marker/colorbar/tickfont/0000755000175000017500000000000013573746614026160 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/funnel/marker/colorbar/tickfont/__init__.py0000644000175000017500000000316013573721537030266 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="funnel.marker.colorbar.tickfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="funnel.marker.colorbar.tickfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="funnel.marker.colorbar.tickfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/funnel/marker/__init__.py0000644000175000017500000005405113573721537024647 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ShowscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showscale", parent_name="funnel.marker", **kwargs): super(ShowscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ReversescaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="reversescale", parent_name="funnel.marker", **kwargs ): super(ReversescaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacitysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="opacitysrc", parent_name="funnel.marker", **kwargs): super(OpacitysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="funnel.marker", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="line", parent_name="funnel.marker", **kwargs): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,R eds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Black body,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . """, ), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="colorsrc", parent_name="funnel.marker", **kwargs): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__(self, plotly_name="colorscale", parent_name="funnel.marker", **kwargs): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"autocolorscale": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorBarValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="colorbar", parent_name="funnel.marker", **kwargs): super(ColorBarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "ColorBar"), data_docs=kwargs.pop( "data_docs", """ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.funnel.marker.c olorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.funnel.marker.colorbar.tickformatstopdefaults ), sets the default property values to use for elements of funnel.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.funnel.marker.colorbar.Tit le instance or dict with compatible properties titlefont Deprecated: Please use funnel.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use funnel.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """, ), **kwargs ) import _plotly_utils.basevalidators class ColoraxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="coloraxis", parent_name="funnel.marker", **kwargs): super(ColoraxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", None), edit_type=kwargs.pop("edit_type", "calc"), regex=kwargs.pop("regex", "/^coloraxis([2-9]|[1-9][0-9]+)?$/"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="funnel.marker", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), colorscale_path=kwargs.pop("colorscale_path", "funnel.marker.colorscale"), **kwargs ) import _plotly_utils.basevalidators class CminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmin", parent_name="funnel.marker", **kwargs): super(CminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmidValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmid", parent_name="funnel.marker", **kwargs): super(CmidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmax", parent_name="funnel.marker", **kwargs): super(CmaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CautoValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="cauto", parent_name="funnel.marker", **kwargs): super(CautoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AutocolorscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="autocolorscale", parent_name="funnel.marker", **kwargs ): super(AutocolorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/funnel/marker/line/0000755000175000017500000000000013573746614023463 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/funnel/marker/line/__init__.py0000644000175000017500000001430213573721537025571 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="widthsrc", parent_name="funnel.marker.line", **kwargs ): super(WidthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="funnel.marker.line", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ReversescaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="reversescale", parent_name="funnel.marker.line", **kwargs ): super(ReversescaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="funnel.marker.line", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__( self, plotly_name="colorscale", parent_name="funnel.marker.line", **kwargs ): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"autocolorscale": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColoraxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__( self, plotly_name="coloraxis", parent_name="funnel.marker.line", **kwargs ): super(ColoraxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", None), edit_type=kwargs.pop("edit_type", "calc"), regex=kwargs.pop("regex", "/^coloraxis([2-9]|[1-9][0-9]+)?$/"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="funnel.marker.line", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), colorscale_path=kwargs.pop( "colorscale_path", "funnel.marker.line.colorscale" ), **kwargs ) import _plotly_utils.basevalidators class CminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmin", parent_name="funnel.marker.line", **kwargs): super(CminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmidValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmid", parent_name="funnel.marker.line", **kwargs): super(CmidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmax", parent_name="funnel.marker.line", **kwargs): super(CmaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CautoValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="cauto", parent_name="funnel.marker.line", **kwargs): super(CautoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AutocolorscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="autocolorscale", parent_name="funnel.marker.line", **kwargs ): super(AutocolorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/funnel/stream/0000755000175000017500000000000013573746614022546 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/funnel/stream/__init__.py0000644000175000017500000000206213573721537024654 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TokenValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="token", parent_name="funnel.stream", **kwargs): super(TokenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "info"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class MaxpointsValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="maxpoints", parent_name="funnel.stream", **kwargs): super(MaxpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 10000), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/funnel/__init__.py0000644000175000017500000011015113573721540023352 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="ysrc", parent_name="funnel", **kwargs): super(YsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YAxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="yaxis", parent_name="funnel", **kwargs): super(YAxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "y"), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class Y0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="y0", parent_name="funnel", **kwargs): super(Y0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="y", parent_name="funnel", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class XsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="xsrc", parent_name="funnel", **kwargs): super(XsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XAxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="xaxis", parent_name="funnel", **kwargs): super(XAxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "x"), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class X0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="x0", parent_name="funnel", **kwargs): super(X0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="x", parent_name="funnel", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="funnel", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", False), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="visible", parent_name="funnel", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "legendonly"]), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="funnel", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UidValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="uid", parent_name="funnel", **kwargs): super(UidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TexttemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="texttemplatesrc", parent_name="funnel", **kwargs): super(TexttemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TexttemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="texttemplate", parent_name="funnel", **kwargs): super(TexttemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="textsrc", parent_name="funnel", **kwargs): super(TextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextpositionsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="textpositionsrc", parent_name="funnel", **kwargs): super(TextpositionsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextpositionValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="textposition", parent_name="funnel", **kwargs): super(TextpositionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["inside", "outside", "auto", "none"]), **kwargs ) import _plotly_utils.basevalidators class TextinfoValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="textinfo", parent_name="funnel", **kwargs): super(TextinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", False), edit_type=kwargs.pop("edit_type", "plot"), extras=kwargs.pop("extras", ["none"]), flags=kwargs.pop( "flags", [ "label", "text", "percent initial", "percent previous", "percent total", "value", ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="textfont", parent_name="funnel", **kwargs): super(TextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Textfont"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class TextangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__(self, plotly_name="textangle", parent_name="funnel", **kwargs): super(TextangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="text", parent_name="funnel", **kwargs): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class StreamValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="stream", parent_name="funnel", **kwargs): super(StreamValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Stream"), data_docs=kwargs.pop( "data_docs", """ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """, ), **kwargs ) import _plotly_utils.basevalidators class ShowlegendValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showlegend", parent_name="funnel", **kwargs): super(ShowlegendValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SelectedpointsValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="selectedpoints", parent_name="funnel", **kwargs): super(SelectedpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class OutsidetextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="outsidetextfont", parent_name="funnel", **kwargs): super(OutsidetextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Outsidetextfont"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class OrientationValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="orientation", parent_name="funnel", **kwargs): super(OrientationValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["v", "h"]), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="funnel", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OffsetgroupValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="offsetgroup", parent_name="funnel", **kwargs): super(OffsetgroupValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class OffsetValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="offset", parent_name="funnel", **kwargs): super(OffsetValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", False), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="funnel", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="metasrc", parent_name="funnel", **kwargs): super(MetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetaValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="meta", parent_name="funnel", **kwargs): super(MetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="marker", parent_name="funnel", **kwargs): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.funnel.marker.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . line plotly.graph_objects.funnel.marker.Line instance or dict with compatible properties opacity Sets the opacity of the bars. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. """, ), **kwargs ) import _plotly_utils.basevalidators class LegendgroupValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="legendgroup", parent_name="funnel", **kwargs): super(LegendgroupValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class InsidetextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="insidetextfont", parent_name="funnel", **kwargs): super(InsidetextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Insidetextfont"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class InsidetextanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="insidetextanchor", parent_name="funnel", **kwargs): super(InsidetextanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["end", "middle", "start"]), **kwargs ) import _plotly_utils.basevalidators class IdssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="idssrc", parent_name="funnel", **kwargs): super(IdssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ids", parent_name="funnel", **kwargs): super(IdsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class HovertextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hovertextsrc", parent_name="funnel", **kwargs): super(HovertextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertext", parent_name="funnel", **kwargs): super(HovertextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hovertemplatesrc", parent_name="funnel", **kwargs): super(HovertemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertemplate", parent_name="funnel", **kwargs): super(HovertemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverlabelValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="hoverlabel", parent_name="funnel", **kwargs): super(HoverlabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Hoverlabel"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """, ), **kwargs ) import _plotly_utils.basevalidators class HoverinfosrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hoverinfosrc", parent_name="funnel", **kwargs): super(HoverinfosrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverinfoValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="hoverinfo", parent_name="funnel", **kwargs): super(HoverinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), extras=kwargs.pop("extras", ["all", "none", "skip"]), flags=kwargs.pop( "flags", [ "name", "x", "y", "text", "percent initial", "percent previous", "percent total", ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DyValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="dy", parent_name="funnel", **kwargs): super(DyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="dx", parent_name="funnel", **kwargs): super(DxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdatasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="customdatasrc", parent_name="funnel", **kwargs): super(CustomdatasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdataValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="customdata", parent_name="funnel", **kwargs): super(CustomdataValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class ConstraintextValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="constraintext", parent_name="funnel", **kwargs): super(ConstraintextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["inside", "outside", "both", "none"]), **kwargs ) import _plotly_utils.basevalidators class ConnectorValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="connector", parent_name="funnel", **kwargs): super(ConnectorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Connector"), data_docs=kwargs.pop( "data_docs", """ fillcolor Sets the fill color. line plotly.graph_objects.funnel.connector.Line instance or dict with compatible properties visible Determines if connector regions and lines are drawn. """, ), **kwargs ) import _plotly_utils.basevalidators class CliponaxisValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="cliponaxis", parent_name="funnel", **kwargs): super(CliponaxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AlignmentgroupValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="alignmentgroup", parent_name="funnel", **kwargs): super(AlignmentgroupValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/funnel/insidetextfont/0000755000175000017500000000000013573746614024322 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/funnel/insidetextfont/__init__.py0000644000175000017500000000603213573721537026431 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="funnel.insidetextfont", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="funnel.insidetextfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="funnel.insidetextfont", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="funnel.insidetextfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="funnel.insidetextfont", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="funnel.insidetextfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/pie/0000755000175000017500000000000013573746614020541 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/pie/textfont/0000755000175000017500000000000013573746614022414 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/pie/textfont/__init__.py0000644000175000017500000000561713573721541024526 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="sizesrc", parent_name="pie.textfont", **kwargs): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="size", parent_name="pie.textfont", **kwargs): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="familysrc", parent_name="pie.textfont", **kwargs): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="family", parent_name="pie.textfont", **kwargs): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="colorsrc", parent_name="pie.textfont", **kwargs): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="pie.textfont", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/pie/title/0000755000175000017500000000000013573746614021662 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/pie/title/__init__.py0000644000175000017500000000571513573721541023773 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="text", parent_name="pie.title", **kwargs): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class PositionValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="position", parent_name="pie.title", **kwargs): super(PositionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "top left", "top center", "top right", "middle center", "bottom left", "bottom center", "bottom right", ], ), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="font", parent_name="pie.title", **kwargs): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/pie/title/font/0000755000175000017500000000000013573746614022630 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/pie/title/font/__init__.py0000644000175000017500000000563313573721541024740 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="sizesrc", parent_name="pie.title.font", **kwargs): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="size", parent_name="pie.title.font", **kwargs): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="familysrc", parent_name="pie.title.font", **kwargs): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="family", parent_name="pie.title.font", **kwargs): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="colorsrc", parent_name="pie.title.font", **kwargs): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="pie.title.font", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/pie/hoverlabel/0000755000175000017500000000000013573746614022664 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/pie/hoverlabel/__init__.py0000644000175000017500000001330313573721541024765 0ustar noahfxnoahfximport _plotly_utils.basevalidators class NamelengthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="namelengthsrc", parent_name="pie.hoverlabel", **kwargs ): super(NamelengthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NamelengthValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="namelength", parent_name="pie.hoverlabel", **kwargs ): super(NamelengthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", -1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="font", parent_name="pie.hoverlabel", **kwargs): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class BordercolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bordercolorsrc", parent_name="pie.hoverlabel", **kwargs ): super(BordercolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="pie.hoverlabel", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bgcolorsrc", parent_name="pie.hoverlabel", **kwargs ): super(BgcolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="bgcolor", parent_name="pie.hoverlabel", **kwargs): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AlignsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="alignsrc", parent_name="pie.hoverlabel", **kwargs): super(AlignsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="align", parent_name="pie.hoverlabel", **kwargs): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "right", "auto"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/pie/hoverlabel/font/0000755000175000017500000000000013573746614023632 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/pie/hoverlabel/font/__init__.py0000644000175000017500000000577713573721541025753 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="pie.hoverlabel.font", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="size", parent_name="pie.hoverlabel.font", **kwargs): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="pie.hoverlabel.font", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="pie.hoverlabel.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="pie.hoverlabel.font", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="pie.hoverlabel.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/pie/outsidetextfont/0000755000175000017500000000000013573746614024011 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/pie/outsidetextfont/__init__.py0000644000175000017500000000577713573721541026132 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="pie.outsidetextfont", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="size", parent_name="pie.outsidetextfont", **kwargs): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="pie.outsidetextfont", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="pie.outsidetextfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="pie.outsidetextfont", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="pie.outsidetextfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/pie/marker/0000755000175000017500000000000013573746614022022 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/pie/marker/__init__.py0000644000175000017500000000342613573721541024130 0ustar noahfxnoahfximport _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="line", parent_name="pie.marker", **kwargs): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ color Sets the color of the line enclosing each sector. colorsrc Sets the source reference on plot.ly for color . width Sets the width (in px) of the line enclosing each sector. widthsrc Sets the source reference on plot.ly for width . """, ), **kwargs ) import _plotly_utils.basevalidators class ColorssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="colorssrc", parent_name="pie.marker", **kwargs): super(ColorssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="colors", parent_name="pie.marker", **kwargs): super(ColorsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/pie/marker/line/0000755000175000017500000000000013573746614022751 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/pie/marker/line/__init__.py0000644000175000017500000000361513573721541025057 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="widthsrc", parent_name="pie.marker.line", **kwargs): super(WidthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="pie.marker.line", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="colorsrc", parent_name="pie.marker.line", **kwargs): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="pie.marker.line", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/pie/stream/0000755000175000017500000000000013573746614022034 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/pie/stream/__init__.py0000644000175000017500000000205413573721541024136 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TokenValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="token", parent_name="pie.stream", **kwargs): super(TokenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "info"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class MaxpointsValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="maxpoints", parent_name="pie.stream", **kwargs): super(MaxpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 10000), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/pie/__init__.py0000644000175000017500000007331613573721542022655 0ustar noahfxnoahfximport _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="visible", parent_name="pie", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "legendonly"]), **kwargs ) import _plotly_utils.basevalidators class ValuessrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="valuessrc", parent_name="pie", **kwargs): super(ValuessrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ValuesValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="values", parent_name="pie", **kwargs): super(ValuesValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="pie", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UidValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="uid", parent_name="pie", **kwargs): super(UidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TitleValidator(_plotly_utils.basevalidators.TitleValidator): def __init__(self, plotly_name="title", parent_name="pie", **kwargs): super(TitleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Title"), data_docs=kwargs.pop( "data_docs", """ font Sets the font used for `title`. Note that the title's font used to be set by the now deprecated `titlefont` attribute. position Specifies the location of the `title`. Note that the title's position used to be set by the now deprecated `titleposition` attribute. text Sets the title of the chart. If it is empty, no title is displayed. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """, ), **kwargs ) import _plotly_utils.basevalidators class TexttemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="texttemplatesrc", parent_name="pie", **kwargs): super(TexttemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TexttemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="texttemplate", parent_name="pie", **kwargs): super(TexttemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="textsrc", parent_name="pie", **kwargs): super(TextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextpositionsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="textpositionsrc", parent_name="pie", **kwargs): super(TextpositionsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextpositionValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="textposition", parent_name="pie", **kwargs): super(TextpositionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["inside", "outside", "auto", "none"]), **kwargs ) import _plotly_utils.basevalidators class TextinfoValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="textinfo", parent_name="pie", **kwargs): super(TextinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), extras=kwargs.pop("extras", ["none"]), flags=kwargs.pop("flags", ["label", "text", "value", "percent"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="textfont", parent_name="pie", **kwargs): super(TextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Textfont"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="text", parent_name="pie", **kwargs): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class StreamValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="stream", parent_name="pie", **kwargs): super(StreamValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Stream"), data_docs=kwargs.pop( "data_docs", """ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """, ), **kwargs ) import _plotly_utils.basevalidators class SortValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="sort", parent_name="pie", **kwargs): super(SortValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowlegendValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showlegend", parent_name="pie", **kwargs): super(ShowlegendValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ScalegroupValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="scalegroup", parent_name="pie", **kwargs): super(ScalegroupValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class RotationValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="rotation", parent_name="pie", **kwargs): super(RotationValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 360), min=kwargs.pop("min", -360), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class PullsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="pullsrc", parent_name="pie", **kwargs): super(PullsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class PullValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="pull", parent_name="pie", **kwargs): super(PullValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutsidetextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="outsidetextfont", parent_name="pie", **kwargs): super(OutsidetextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Outsidetextfont"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="pie", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="pie", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="metasrc", parent_name="pie", **kwargs): super(MetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetaValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="meta", parent_name="pie", **kwargs): super(MetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="marker", parent_name="pie", **kwargs): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ colors Sets the color of each sector. If not specified, the default trace color set is used to pick the sector colors. colorssrc Sets the source reference on plot.ly for colors . line plotly.graph_objects.pie.marker.Line instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class LegendgroupValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="legendgroup", parent_name="pie", **kwargs): super(LegendgroupValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LabelssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="labelssrc", parent_name="pie", **kwargs): super(LabelssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LabelsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="labels", parent_name="pie", **kwargs): super(LabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class Label0Validator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="label0", parent_name="pie", **kwargs): super(Label0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class InsidetextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="insidetextfont", parent_name="pie", **kwargs): super(InsidetextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Insidetextfont"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class IdssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="idssrc", parent_name="pie", **kwargs): super(IdssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ids", parent_name="pie", **kwargs): super(IdsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class HovertextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hovertextsrc", parent_name="pie", **kwargs): super(HovertextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertext", parent_name="pie", **kwargs): super(HovertextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hovertemplatesrc", parent_name="pie", **kwargs): super(HovertemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertemplate", parent_name="pie", **kwargs): super(HovertemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverlabelValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="hoverlabel", parent_name="pie", **kwargs): super(HoverlabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Hoverlabel"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """, ), **kwargs ) import _plotly_utils.basevalidators class HoverinfosrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hoverinfosrc", parent_name="pie", **kwargs): super(HoverinfosrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverinfoValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="hoverinfo", parent_name="pie", **kwargs): super(HoverinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), extras=kwargs.pop("extras", ["all", "none", "skip"]), flags=kwargs.pop("flags", ["label", "text", "value", "percent", "name"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoleValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="hole", parent_name="pie", **kwargs): super(HoleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class DomainValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="domain", parent_name="pie", **kwargs): super(DomainValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Domain"), data_docs=kwargs.pop( "data_docs", """ column If there is a layout grid, use the domain for this column in the grid for this pie trace . row If there is a layout grid, use the domain for this row in the grid for this pie trace . x Sets the horizontal domain of this pie trace (in plot fraction). y Sets the vertical domain of this pie trace (in plot fraction). """, ), **kwargs ) import _plotly_utils.basevalidators class DlabelValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="dlabel", parent_name="pie", **kwargs): super(DlabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DirectionValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="direction", parent_name="pie", **kwargs): super(DirectionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["clockwise", "counterclockwise"]), **kwargs ) import _plotly_utils.basevalidators class CustomdatasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="customdatasrc", parent_name="pie", **kwargs): super(CustomdatasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdataValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="customdata", parent_name="pie", **kwargs): super(CustomdataValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class AutomarginValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="automargin", parent_name="pie", **kwargs): super(AutomarginValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/pie/insidetextfont/0000755000175000017500000000000013573746614023610 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/pie/insidetextfont/__init__.py0000644000175000017500000000575313573721541025723 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="pie.insidetextfont", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="size", parent_name="pie.insidetextfont", **kwargs): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="pie.insidetextfont", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="pie.insidetextfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="pie.insidetextfont", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="pie.insidetextfont", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/pie/domain/0000755000175000017500000000000013573746614022010 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/pie/domain/__init__.py0000644000175000017500000000447113573721541024117 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="y", parent_name="pie.domain", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), items=kwargs.pop( "items", [ {"valType": "number", "min": 0, "max": 1, "editType": "calc"}, {"valType": "number", "min": 0, "max": 1, "editType": "calc"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="x", parent_name="pie.domain", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), items=kwargs.pop( "items", [ {"valType": "number", "min": 0, "max": 1, "editType": "calc"}, {"valType": "number", "min": 0, "max": 1, "editType": "calc"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class RowValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="row", parent_name="pie.domain", **kwargs): super(RowValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColumnValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="column", parent_name="pie.domain", **kwargs): super(ColumnValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/indicator/0000755000175000017500000000000013573746614021740 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/indicator/title/0000755000175000017500000000000013573746614023061 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/indicator/title/__init__.py0000644000175000017500000000460713573721540025170 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="text", parent_name="indicator.title", **kwargs): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="font", parent_name="indicator.title", **kwargs): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="align", parent_name="indicator.title", **kwargs): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["left", "center", "right"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/indicator/title/font/0000755000175000017500000000000013573746614024027 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/indicator/title/font/__init__.py0000644000175000017500000000277013573721540026135 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="indicator.title.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="indicator.title.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="indicator.title.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/indicator/gauge/0000755000175000017500000000000013573746614023030 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/indicator/gauge/bar/0000755000175000017500000000000013573746614023574 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/indicator/gauge/bar/__init__.py0000644000175000017500000000330713573721537025705 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="thickness", parent_name="indicator.gauge.bar", **kwargs ): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="line", parent_name="indicator.gauge.bar", **kwargs): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ color Sets the color of the line enclosing each sector. width Sets the width (in px) of the line enclosing each sector. """, ), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="indicator.gauge.bar", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/indicator/gauge/bar/line/0000755000175000017500000000000013573746614024523 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/indicator/gauge/bar/line/__init__.py0000644000175000017500000000171313573721537026633 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="width", parent_name="indicator.gauge.bar.line", **kwargs ): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="indicator.gauge.bar.line", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/indicator/gauge/axis/0000755000175000017500000000000013573746614023774 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/indicator/gauge/axis/tickformatstop/0000755000175000017500000000000013573746614027045 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/indicator/gauge/axis/tickformatstop/__init__.py0000644000175000017500000000535513573721537031163 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="value", parent_name="indicator.gauge.axis.tickformatstop", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="indicator.gauge.axis.tickformatstop", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="indicator.gauge.axis.tickformatstop", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EnabledValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="enabled", parent_name="indicator.gauge.axis.tickformatstop", **kwargs ): super(EnabledValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DtickrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="dtickrange", parent_name="indicator.gauge.axis.tickformatstop", **kwargs ): super(DtickrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "plot"}, {"valType": "any", "editType": "plot"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/indicator/gauge/axis/__init__.py0000644000175000017500000004111013573721540026071 0ustar noahfxnoahfximport _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="visible", parent_name="indicator.gauge.axis", **kwargs ): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="tickwidth", parent_name="indicator.gauge.axis", **kwargs ): super(TickwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickvalssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="tickvalssrc", parent_name="indicator.gauge.axis", **kwargs ): super(TickvalssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickvalsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="tickvals", parent_name="indicator.gauge.axis", **kwargs ): super(TickvalsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="ticktextsrc", parent_name="indicator.gauge.axis", **kwargs ): super(TicktextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicktextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="ticktext", parent_name="indicator.gauge.axis", **kwargs ): super(TicktextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="ticksuffix", parent_name="indicator.gauge.axis", **kwargs ): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TicksValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="ticks", parent_name="indicator.gauge.axis", **kwargs ): super(TicksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["outside", "inside", ""]), **kwargs ) import _plotly_utils.basevalidators class TickprefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickprefix", parent_name="indicator.gauge.axis", **kwargs ): super(TickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="tickmode", parent_name="indicator.gauge.axis", **kwargs ): super(TickmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "linear", "array"]), **kwargs ) import _plotly_utils.basevalidators class TicklenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ticklen", parent_name="indicator.gauge.axis", **kwargs ): super(TicklenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickformatstopValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickformatstopdefaults", parent_name="indicator.gauge.axis", **kwargs ): super(TickformatstopValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatstopsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="tickformatstops", parent_name="indicator.gauge.axis", **kwargs ): super(TickformatstopsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickformat", parent_name="indicator.gauge.axis", **kwargs ): super(TickformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickfont", parent_name="indicator.gauge.axis", **kwargs ): super(TickfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class TickcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="tickcolor", parent_name="indicator.gauge.axis", **kwargs ): super(TickcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__( self, plotly_name="tickangle", parent_name="indicator.gauge.axis", **kwargs ): super(TickangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="tick0", parent_name="indicator.gauge.axis", **kwargs ): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowticksuffixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showticksuffix", parent_name="indicator.gauge.axis", **kwargs ): super(ShowticksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowtickprefixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showtickprefix", parent_name="indicator.gauge.axis", **kwargs ): super(ShowtickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowticklabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showticklabels", parent_name="indicator.gauge.axis", **kwargs ): super(ShowticklabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowexponentValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showexponent", parent_name="indicator.gauge.axis", **kwargs ): super(ShowexponentValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class SeparatethousandsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="separatethousands", parent_name="indicator.gauge.axis", **kwargs ): super(SeparatethousandsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class RangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="range", parent_name="indicator.gauge.axis", **kwargs ): super(RangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), items=kwargs.pop( "items", [ {"valType": "number", "editType": "plot"}, {"valType": "number", "editType": "plot"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NticksValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="nticks", parent_name="indicator.gauge.axis", **kwargs ): super(NticksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ExponentformatValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="exponentformat", parent_name="indicator.gauge.axis", **kwargs ): super(ExponentformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "e", "E", "power", "SI", "B"]), **kwargs ) import _plotly_utils.basevalidators class DtickValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="dtick", parent_name="indicator.gauge.axis", **kwargs ): super(DtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/indicator/gauge/axis/tickfont/0000755000175000017500000000000013573746614025615 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/indicator/gauge/axis/tickfont/__init__.py0000644000175000017500000000305313573721537027724 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="indicator.gauge.axis.tickfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="indicator.gauge.axis.tickfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="indicator.gauge.axis.tickfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/indicator/gauge/__init__.py0000644000175000017500000003415713573721540025142 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ThresholdValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="threshold", parent_name="indicator.gauge", **kwargs ): super(ThresholdValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Threshold"), data_docs=kwargs.pop( "data_docs", """ line plotly.graph_objects.indicator.gauge.threshold. Line instance or dict with compatible properties thickness Sets the thickness of the threshold line as a fraction of the thickness of the gauge. value Sets a treshold value drawn as a line. """, ), **kwargs ) import _plotly_utils.basevalidators class StepValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="stepdefaults", parent_name="indicator.gauge", **kwargs ): super(StepValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Step"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class StepsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__(self, plotly_name="steps", parent_name="indicator.gauge", **kwargs): super(StepsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Step"), data_docs=kwargs.pop( "data_docs", """ color Sets the background color of the arc. line plotly.graph_objects.indicator.gauge.step.Line instance or dict with compatible properties name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. range Sets the range of this axis. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. thickness Sets the thickness of the bar as a fraction of the total thickness of the gauge. """, ), **kwargs ) import _plotly_utils.basevalidators class ShapeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="shape", parent_name="indicator.gauge", **kwargs): super(ShapeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["angular", "bullet"]), **kwargs ) import _plotly_utils.basevalidators class BorderwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="borderwidth", parent_name="indicator.gauge", **kwargs ): super(BorderwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="indicator.gauge", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="bgcolor", parent_name="indicator.gauge", **kwargs): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BarValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="bar", parent_name="indicator.gauge", **kwargs): super(BarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Bar"), data_docs=kwargs.pop( "data_docs", """ color Sets the background color of the arc. line plotly.graph_objects.indicator.gauge.bar.Line instance or dict with compatible properties thickness Sets the thickness of the bar as a fraction of the total thickness of the gauge. """, ), **kwargs ) import _plotly_utils.basevalidators class AxisValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="axis", parent_name="indicator.gauge", **kwargs): super(AxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Axis"), data_docs=kwargs.pop( "data_docs", """ dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". range Sets the range of this axis. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.indicator.gauge .axis.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.indicator.gauge.axis.tickformatstopdefaults), sets the default property values to use for elements of indicator.gauge.axis.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). visible A single toggle to hide the axis while preserving interaction like dragging. Default is true when a cheater plot is present on the axis, otherwise false """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/indicator/gauge/threshold/0000755000175000017500000000000013573746614025024 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/indicator/gauge/threshold/__init__.py0000644000175000017500000000326013573721537027133 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="value", parent_name="indicator.gauge.threshold", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="thickness", parent_name="indicator.gauge.threshold", **kwargs ): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="line", parent_name="indicator.gauge.threshold", **kwargs ): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ color Sets the color of the threshold line. width Sets the width (in px) of the threshold line. """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/indicator/gauge/threshold/line/0000755000175000017500000000000013573746614025753 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/indicator/gauge/threshold/line/__init__.py0000644000175000017500000000200713573721537030060 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="width", parent_name="indicator.gauge.threshold.line", **kwargs ): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="indicator.gauge.threshold.line", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/indicator/gauge/step/0000755000175000017500000000000013573746614024003 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/indicator/gauge/step/__init__.py0000644000175000017500000000655313573721537026122 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="thickness", parent_name="indicator.gauge.step", **kwargs ): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="indicator.gauge.step", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class RangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="range", parent_name="indicator.gauge.step", **kwargs ): super(RangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), items=kwargs.pop( "items", [ {"valType": "number", "editType": "plot"}, {"valType": "number", "editType": "plot"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="indicator.gauge.step", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="line", parent_name="indicator.gauge.step", **kwargs ): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ color Sets the color of the line enclosing each sector. width Sets the width (in px) of the line enclosing each sector. """, ), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="indicator.gauge.step", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/indicator/gauge/step/line/0000755000175000017500000000000013573746614024732 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/indicator/gauge/step/line/__init__.py0000644000175000017500000000171513573721537027044 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="width", parent_name="indicator.gauge.step.line", **kwargs ): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="indicator.gauge.step.line", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/indicator/number/0000755000175000017500000000000013573746614023230 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/indicator/number/__init__.py0000644000175000017500000000544713573721540025342 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="valueformat", parent_name="indicator.number", **kwargs ): super(ValueformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="suffix", parent_name="indicator.number", **kwargs): super(SuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class PrefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="prefix", parent_name="indicator.number", **kwargs): super(PrefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="font", parent_name="indicator.number", **kwargs): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/indicator/number/font/0000755000175000017500000000000013573746614024176 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/indicator/number/font/__init__.py0000644000175000017500000000277313573721540026307 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="indicator.number.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="indicator.number.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="indicator.number.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/indicator/stream/0000755000175000017500000000000013573746614023233 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/indicator/stream/__init__.py0000644000175000017500000000210613573721537025340 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TokenValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="token", parent_name="indicator.stream", **kwargs): super(TokenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "info"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class MaxpointsValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="maxpoints", parent_name="indicator.stream", **kwargs ): super(MaxpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 10000), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/indicator/__init__.py0000644000175000017500000003147213573721540024047 0ustar noahfxnoahfximport _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="visible", parent_name="indicator", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "legendonly"]), **kwargs ) import _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="value", parent_name="indicator", **kwargs): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, anim=kwargs.pop("anim", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="indicator", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UidValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="uid", parent_name="indicator", **kwargs): super(UidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, anim=kwargs.pop("anim", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TitleValidator(_plotly_utils.basevalidators.TitleValidator): def __init__(self, plotly_name="title", parent_name="indicator", **kwargs): super(TitleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Title"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the title. It defaults to `center` except for bullet charts for which it defaults to right. font Set the font used to display the title text Sets the title of this indicator. """, ), **kwargs ) import _plotly_utils.basevalidators class StreamValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="stream", parent_name="indicator", **kwargs): super(StreamValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Stream"), data_docs=kwargs.pop( "data_docs", """ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """, ), **kwargs ) import _plotly_utils.basevalidators class NumberValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="number", parent_name="indicator", **kwargs): super(NumberValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Number"), data_docs=kwargs.pop( "data_docs", """ font Set the font used to display main number prefix Sets a prefix appearing before the number. suffix Sets a suffix appearing next to the number. valueformat Sets the value formatting rule using d3 formatting mini-language which is similar to those of Python. See https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format """, ), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="indicator", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ModeValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="mode", parent_name="indicator", **kwargs): super(ModeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), flags=kwargs.pop("flags", ["number", "delta", "gauge"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="metasrc", parent_name="indicator", **kwargs): super(MetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetaValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="meta", parent_name="indicator", **kwargs): super(MetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="idssrc", parent_name="indicator", **kwargs): super(IdssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ids", parent_name="indicator", **kwargs): super(IdsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, anim=kwargs.pop("anim", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class GaugeValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="gauge", parent_name="indicator", **kwargs): super(GaugeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Gauge"), data_docs=kwargs.pop( "data_docs", """ axis plotly.graph_objects.indicator.gauge.Axis instance or dict with compatible properties bar Set the appearance of the gauge's value bgcolor Sets the gauge background color. bordercolor Sets the color of the border enclosing the gauge. borderwidth Sets the width (in px) of the border enclosing the gauge. shape Set the shape of the gauge steps A tuple of plotly.graph_objects.indicator.gauge.Step instances or dicts with compatible properties stepdefaults When used in a template (as layout.template.dat a.indicator.gauge.stepdefaults), sets the default property values to use for elements of indicator.gauge.steps threshold plotly.graph_objects.indicator.gauge.Threshold instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class DomainValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="domain", parent_name="indicator", **kwargs): super(DomainValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Domain"), data_docs=kwargs.pop( "data_docs", """ column If there is a layout grid, use the domain for this column in the grid for this indicator trace . row If there is a layout grid, use the domain for this row in the grid for this indicator trace . x Sets the horizontal domain of this indicator trace (in plot fraction). y Sets the vertical domain of this indicator trace (in plot fraction). """, ), **kwargs ) import _plotly_utils.basevalidators class DeltaValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="delta", parent_name="indicator", **kwargs): super(DeltaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Delta"), data_docs=kwargs.pop( "data_docs", """ decreasing plotly.graph_objects.indicator.delta.Decreasing instance or dict with compatible properties font Set the font used to display the delta increasing plotly.graph_objects.indicator.delta.Increasing instance or dict with compatible properties position Sets the position of delta with respect to the number. reference Sets the reference value to compute the delta. By default, it is set to the current value. relative Show relative change valueformat Sets the value formatting rule using d3 formatting mini-language which is similar to those of Python. See https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format """, ), **kwargs ) import _plotly_utils.basevalidators class CustomdatasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="customdatasrc", parent_name="indicator", **kwargs): super(CustomdatasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdataValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="customdata", parent_name="indicator", **kwargs): super(CustomdataValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="align", parent_name="indicator", **kwargs): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["left", "center", "right"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/indicator/delta/0000755000175000017500000000000013573746614023031 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/indicator/delta/increasing/0000755000175000017500000000000013573746614025153 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/indicator/delta/increasing/__init__.py0000644000175000017500000000165413573721537027267 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SymbolValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="symbol", parent_name="indicator.delta.increasing", **kwargs ): super(SymbolValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="indicator.delta.increasing", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/indicator/delta/__init__.py0000644000175000017500000001133013573721537025135 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="valueformat", parent_name="indicator.delta", **kwargs ): super(ValueformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class RelativeValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="relative", parent_name="indicator.delta", **kwargs): super(RelativeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ReferenceValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="reference", parent_name="indicator.delta", **kwargs ): super(ReferenceValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class PositionValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="position", parent_name="indicator.delta", **kwargs): super(PositionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["top", "bottom", "left", "right"]), **kwargs ) import _plotly_utils.basevalidators class IncreasingValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="increasing", parent_name="indicator.delta", **kwargs ): super(IncreasingValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Increasing"), data_docs=kwargs.pop( "data_docs", """ color Sets the color for increasing value. symbol Sets the symbol to display for increasing value """, ), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="font", parent_name="indicator.delta", **kwargs): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class DecreasingValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="decreasing", parent_name="indicator.delta", **kwargs ): super(DecreasingValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Decreasing"), data_docs=kwargs.pop( "data_docs", """ color Sets the color for increasing value. symbol Sets the symbol to display for increasing value """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/indicator/delta/decreasing/0000755000175000017500000000000013573746614025135 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/indicator/delta/decreasing/__init__.py0000644000175000017500000000165413573721537027251 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SymbolValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="symbol", parent_name="indicator.delta.decreasing", **kwargs ): super(SymbolValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="indicator.delta.decreasing", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/indicator/delta/font/0000755000175000017500000000000013573746614023777 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/indicator/delta/font/__init__.py0000644000175000017500000000277013573721537026113 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="indicator.delta.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="indicator.delta.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="indicator.delta.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/indicator/domain/0000755000175000017500000000000013573746614023207 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/indicator/domain/__init__.py0000644000175000017500000000452113573721540025311 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="y", parent_name="indicator.domain", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), items=kwargs.pop( "items", [ {"valType": "number", "min": 0, "max": 1, "editType": "calc"}, {"valType": "number", "min": 0, "max": 1, "editType": "calc"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="x", parent_name="indicator.domain", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), items=kwargs.pop( "items", [ {"valType": "number", "min": 0, "max": 1, "editType": "calc"}, {"valType": "number", "min": 0, "max": 1, "editType": "calc"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class RowValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="row", parent_name="indicator.domain", **kwargs): super(RowValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColumnValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="column", parent_name="indicator.domain", **kwargs): super(ColumnValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/cone/0000755000175000017500000000000013573746614020710 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/cone/hoverlabel/0000755000175000017500000000000013573746614023033 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/cone/hoverlabel/__init__.py0000644000175000017500000001331413573721536025142 0ustar noahfxnoahfximport _plotly_utils.basevalidators class NamelengthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="namelengthsrc", parent_name="cone.hoverlabel", **kwargs ): super(NamelengthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NamelengthValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="namelength", parent_name="cone.hoverlabel", **kwargs ): super(NamelengthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", -1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="font", parent_name="cone.hoverlabel", **kwargs): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class BordercolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bordercolorsrc", parent_name="cone.hoverlabel", **kwargs ): super(BordercolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="cone.hoverlabel", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bgcolorsrc", parent_name="cone.hoverlabel", **kwargs ): super(BgcolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="bgcolor", parent_name="cone.hoverlabel", **kwargs): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AlignsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="alignsrc", parent_name="cone.hoverlabel", **kwargs): super(AlignsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="align", parent_name="cone.hoverlabel", **kwargs): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "right", "auto"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/cone/hoverlabel/font/0000755000175000017500000000000013573746614024001 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/cone/hoverlabel/font/__init__.py0000644000175000017500000000602313573721536026107 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="cone.hoverlabel.font", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="cone.hoverlabel.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="cone.hoverlabel.font", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="cone.hoverlabel.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="cone.hoverlabel.font", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="cone.hoverlabel.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/cone/colorbar/0000755000175000017500000000000013573746614022513 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/cone/colorbar/tickformatstop/0000755000175000017500000000000013573746614025564 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/cone/colorbar/tickformatstop/__init__.py0000644000175000017500000000527513573721536027702 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="value", parent_name="cone.colorbar.tickformatstop", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="cone.colorbar.tickformatstop", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="cone.colorbar.tickformatstop", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EnabledValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="enabled", parent_name="cone.colorbar.tickformatstop", **kwargs ): super(EnabledValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DtickrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="dtickrange", parent_name="cone.colorbar.tickformatstop", **kwargs ): super(DtickrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "colorbars"}, {"valType": "any", "editType": "colorbars"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/cone/colorbar/title/0000755000175000017500000000000013573746614023634 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/cone/colorbar/title/__init__.py0000644000175000017500000000463213573721536025746 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="text", parent_name="cone.colorbar.title", **kwargs): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SideValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="side", parent_name="cone.colorbar.title", **kwargs): super(SideValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["right", "top", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="font", parent_name="cone.colorbar.title", **kwargs): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/cone/colorbar/title/font/0000755000175000017500000000000013573746614024602 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/cone/colorbar/title/font/__init__.py0000644000175000017500000000302313573721536026705 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="cone.colorbar.title.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="cone.colorbar.title.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="cone.colorbar.title.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/cone/colorbar/__init__.py0000644000175000017500000005731213573721537024631 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="ypad", parent_name="cone.colorbar", **kwargs): super(YpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class YanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="yanchor", parent_name="cone.colorbar", **kwargs): super(YanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["top", "middle", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="y", parent_name="cone.colorbar", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="xpad", parent_name="cone.colorbar", **kwargs): super(XpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="xanchor", parent_name="cone.colorbar", **kwargs): super(XanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "center", "right"]), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="x", parent_name="cone.colorbar", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TitleValidator(_plotly_utils.basevalidators.TitleValidator): def __init__(self, plotly_name="title", parent_name="cone.colorbar", **kwargs): super(TitleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Title"), data_docs=kwargs.pop( "data_docs", """ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """, ), **kwargs ) import _plotly_utils.basevalidators class TickwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="tickwidth", parent_name="cone.colorbar", **kwargs): super(TickwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickvalssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="tickvalssrc", parent_name="cone.colorbar", **kwargs ): super(TickvalssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickvalsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="tickvals", parent_name="cone.colorbar", **kwargs): super(TickvalsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="ticktextsrc", parent_name="cone.colorbar", **kwargs ): super(TicktextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicktextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ticktext", parent_name="cone.colorbar", **kwargs): super(TicktextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="ticksuffix", parent_name="cone.colorbar", **kwargs): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TicksValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="ticks", parent_name="cone.colorbar", **kwargs): super(TicksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["outside", "inside", ""]), **kwargs ) import _plotly_utils.basevalidators class TickprefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="tickprefix", parent_name="cone.colorbar", **kwargs): super(TickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="tickmode", parent_name="cone.colorbar", **kwargs): super(TickmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "linear", "array"]), **kwargs ) import _plotly_utils.basevalidators class TicklenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="ticklen", parent_name="cone.colorbar", **kwargs): super(TicklenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickformatstopValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickformatstopdefaults", parent_name="cone.colorbar", **kwargs ): super(TickformatstopValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatstopsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="tickformatstops", parent_name="cone.colorbar", **kwargs ): super(TickformatstopsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="tickformat", parent_name="cone.colorbar", **kwargs): super(TickformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="tickfont", parent_name="cone.colorbar", **kwargs): super(TickfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class TickcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="tickcolor", parent_name="cone.colorbar", **kwargs): super(TickcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__(self, plotly_name="tickangle", parent_name="cone.colorbar", **kwargs): super(TickangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="tick0", parent_name="cone.colorbar", **kwargs): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ThicknessmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="thicknessmode", parent_name="cone.colorbar", **kwargs ): super(ThicknessmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="thickness", parent_name="cone.colorbar", **kwargs): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowticksuffixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showticksuffix", parent_name="cone.colorbar", **kwargs ): super(ShowticksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowtickprefixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showtickprefix", parent_name="cone.colorbar", **kwargs ): super(ShowtickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowticklabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showticklabels", parent_name="cone.colorbar", **kwargs ): super(ShowticklabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowexponentValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showexponent", parent_name="cone.colorbar", **kwargs ): super(ShowexponentValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class SeparatethousandsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="separatethousands", parent_name="cone.colorbar", **kwargs ): super(SeparatethousandsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="outlinewidth", parent_name="cone.colorbar", **kwargs ): super(OutlinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="outlinecolor", parent_name="cone.colorbar", **kwargs ): super(OutlinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NticksValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="nticks", parent_name="cone.colorbar", **kwargs): super(NticksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LenmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="lenmode", parent_name="cone.colorbar", **kwargs): super(LenmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class LenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="len", parent_name="cone.colorbar", **kwargs): super(LenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ExponentformatValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="exponentformat", parent_name="cone.colorbar", **kwargs ): super(ExponentformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "e", "E", "power", "SI", "B"]), **kwargs ) import _plotly_utils.basevalidators class DtickValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="dtick", parent_name="cone.colorbar", **kwargs): super(DtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BorderwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="borderwidth", parent_name="cone.colorbar", **kwargs ): super(BorderwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="cone.colorbar", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="bgcolor", parent_name="cone.colorbar", **kwargs): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/cone/colorbar/tickfont/0000755000175000017500000000000013573746614024334 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/cone/colorbar/tickfont/__init__.py0000644000175000017500000000301513573721536026440 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="cone.colorbar.tickfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="cone.colorbar.tickfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="cone.colorbar.tickfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/cone/lightposition/0000755000175000017500000000000013573746614023604 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/cone/lightposition/__init__.py0000644000175000017500000000304213573721536025710 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ZValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="z", parent_name="cone.lightposition", **kwargs): super(ZValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 100000), min=kwargs.pop("min", -100000), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="y", parent_name="cone.lightposition", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 100000), min=kwargs.pop("min", -100000), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="x", parent_name="cone.lightposition", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 100000), min=kwargs.pop("min", -100000), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/cone/stream/0000755000175000017500000000000013573746614022203 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/cone/stream/__init__.py0000644000175000017500000000205613573721536024313 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TokenValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="token", parent_name="cone.stream", **kwargs): super(TokenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "info"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class MaxpointsValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="maxpoints", parent_name="cone.stream", **kwargs): super(MaxpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 10000), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/cone/__init__.py0000644000175000017500000010772213573721537023027 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ZsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="zsrc", parent_name="cone", **kwargs): super(ZsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="z", parent_name="cone", **kwargs): super(ZValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class YsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="ysrc", parent_name="cone", **kwargs): super(YsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="y", parent_name="cone", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class XsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="xsrc", parent_name="cone", **kwargs): super(XsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="x", parent_name="cone", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class WsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="wsrc", parent_name="cone", **kwargs): super(WsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class WValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="w", parent_name="cone", **kwargs): super(WValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class VsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="vsrc", parent_name="cone", **kwargs): super(VsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="visible", parent_name="cone", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "legendonly"]), **kwargs ) import _plotly_utils.basevalidators class VValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="v", parent_name="cone", **kwargs): super(VValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class UsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="usrc", parent_name="cone", **kwargs): super(UsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="cone", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UidValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="uid", parent_name="cone", **kwargs): super(UidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="u", parent_name="cone", **kwargs): super(UValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="textsrc", parent_name="cone", **kwargs): super(TextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="text", parent_name="cone", **kwargs): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class StreamValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="stream", parent_name="cone", **kwargs): super(StreamValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Stream"), data_docs=kwargs.pop( "data_docs", """ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """, ), **kwargs ) import _plotly_utils.basevalidators class SizerefValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="sizeref", parent_name="cone", **kwargs): super(SizerefValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizemodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="sizemode", parent_name="cone", **kwargs): super(SizemodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["scaled", "absolute"]), **kwargs ) import _plotly_utils.basevalidators class ShowscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showscale", parent_name="cone", **kwargs): super(ShowscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SceneValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="scene", parent_name="cone", **kwargs): super(SceneValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "scene"), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ReversescaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="reversescale", parent_name="cone", **kwargs): super(ReversescaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="cone", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="cone", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="metasrc", parent_name="cone", **kwargs): super(MetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetaValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="meta", parent_name="cone", **kwargs): super(MetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LightpositionValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="lightposition", parent_name="cone", **kwargs): super(LightpositionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Lightposition"), data_docs=kwargs.pop( "data_docs", """ x Numeric vector, representing the X coordinate for each vertex. y Numeric vector, representing the Y coordinate for each vertex. z Numeric vector, representing the Z coordinate for each vertex. """, ), **kwargs ) import _plotly_utils.basevalidators class LightingValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="lighting", parent_name="cone", **kwargs): super(LightingValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Lighting"), data_docs=kwargs.pop( "data_docs", """ ambient Ambient light increases overall color visibility but can wash out the image. diffuse Represents the extent that incident rays are reflected in a range of angles. facenormalsepsilon Epsilon for face normals calculation avoids math issues arising from degenerate geometry. fresnel Represents the reflectance as a dependency of the viewing angle; e.g. paper is reflective when viewing it from the edge of the paper (almost 90 degrees), causing shine. roughness Alters specular reflection; the rougher the surface, the wider and less contrasty the shine. specular Represents the level that incident rays are reflected in a single direction, causing shine. vertexnormalsepsilon Epsilon for vertex normals calculation avoids math issues arising from degenerate geometry. """, ), **kwargs ) import _plotly_utils.basevalidators class IdssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="idssrc", parent_name="cone", **kwargs): super(IdssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ids", parent_name="cone", **kwargs): super(IdsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class HovertextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hovertextsrc", parent_name="cone", **kwargs): super(HovertextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertext", parent_name="cone", **kwargs): super(HovertextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hovertemplatesrc", parent_name="cone", **kwargs): super(HovertemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertemplate", parent_name="cone", **kwargs): super(HovertemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverlabelValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="hoverlabel", parent_name="cone", **kwargs): super(HoverlabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Hoverlabel"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """, ), **kwargs ) import _plotly_utils.basevalidators class HoverinfosrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hoverinfosrc", parent_name="cone", **kwargs): super(HoverinfosrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverinfoValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="hoverinfo", parent_name="cone", **kwargs): super(HoverinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), extras=kwargs.pop("extras", ["all", "none", "skip"]), flags=kwargs.pop( "flags", ["x", "y", "z", "u", "v", "w", "norm", "text", "name"] ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdatasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="customdatasrc", parent_name="cone", **kwargs): super(CustomdatasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdataValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="customdata", parent_name="cone", **kwargs): super(CustomdataValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__(self, plotly_name="colorscale", parent_name="cone", **kwargs): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"autocolorscale": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorBarValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="colorbar", parent_name="cone", **kwargs): super(ColorBarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "ColorBar"), data_docs=kwargs.pop( "data_docs", """ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.cone.colorbar.T ickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.cone.colorbar.tickformatstopdefaults), sets the default property values to use for elements of cone.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.cone.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use cone.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use cone.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """, ), **kwargs ) import _plotly_utils.basevalidators class ColoraxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="coloraxis", parent_name="cone", **kwargs): super(ColoraxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", None), edit_type=kwargs.pop("edit_type", "calc"), regex=kwargs.pop("regex", "/^coloraxis([2-9]|[1-9][0-9]+)?$/"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmin", parent_name="cone", **kwargs): super(CminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmidValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmid", parent_name="cone", **kwargs): super(CmidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmax", parent_name="cone", **kwargs): super(CmaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CautoValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="cauto", parent_name="cone", **kwargs): super(CautoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AutocolorscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="autocolorscale", parent_name="cone", **kwargs): super(AutocolorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AnchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="anchor", parent_name="cone", **kwargs): super(AnchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["tip", "tail", "cm", "center"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/cone/lighting/0000755000175000017500000000000013573746614022515 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/cone/lighting/__init__.py0000644000175000017500000000731513573721536024630 0ustar noahfxnoahfximport _plotly_utils.basevalidators class VertexnormalsepsilonValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="vertexnormalsepsilon", parent_name="cone.lighting", **kwargs ): super(VertexnormalsepsilonValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SpecularValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="specular", parent_name="cone.lighting", **kwargs): super(SpecularValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 2), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class RoughnessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="roughness", parent_name="cone.lighting", **kwargs): super(RoughnessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FresnelValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="fresnel", parent_name="cone.lighting", **kwargs): super(FresnelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 5), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FacenormalsepsilonValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="facenormalsepsilon", parent_name="cone.lighting", **kwargs ): super(FacenormalsepsilonValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class DiffuseValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="diffuse", parent_name="cone.lighting", **kwargs): super(DiffuseValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AmbientValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="ambient", parent_name="cone.lighting", **kwargs): super(AmbientValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/streamtube/0000755000175000017500000000000013573746614022137 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/streamtube/starts/0000755000175000017500000000000013573746614023457 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/streamtube/starts/__init__.py0000644000175000017500000000511313573721543025562 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ZsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="zsrc", parent_name="streamtube.starts", **kwargs): super(ZsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="z", parent_name="streamtube.starts", **kwargs): super(ZValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class YsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="ysrc", parent_name="streamtube.starts", **kwargs): super(YsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="y", parent_name="streamtube.starts", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class XsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="xsrc", parent_name="streamtube.starts", **kwargs): super(XsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="x", parent_name="streamtube.starts", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/streamtube/hoverlabel/0000755000175000017500000000000013573746614024262 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/streamtube/hoverlabel/__init__.py0000644000175000017500000001352213573721543026370 0ustar noahfxnoahfximport _plotly_utils.basevalidators class NamelengthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="namelengthsrc", parent_name="streamtube.hoverlabel", **kwargs ): super(NamelengthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NamelengthValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="namelength", parent_name="streamtube.hoverlabel", **kwargs ): super(NamelengthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", -1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="streamtube.hoverlabel", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class BordercolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bordercolorsrc", parent_name="streamtube.hoverlabel", **kwargs ): super(BordercolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="streamtube.hoverlabel", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bgcolorsrc", parent_name="streamtube.hoverlabel", **kwargs ): super(BgcolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="streamtube.hoverlabel", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AlignsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="alignsrc", parent_name="streamtube.hoverlabel", **kwargs ): super(AlignsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="align", parent_name="streamtube.hoverlabel", **kwargs ): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "right", "auto"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/streamtube/hoverlabel/font/0000755000175000017500000000000013573746614025230 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/streamtube/hoverlabel/font/__init__.py0000644000175000017500000000611713573721543027340 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="streamtube.hoverlabel.font", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="streamtube.hoverlabel.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="streamtube.hoverlabel.font", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="streamtube.hoverlabel.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="streamtube.hoverlabel.font", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="streamtube.hoverlabel.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/streamtube/colorbar/0000755000175000017500000000000013573746614023742 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/streamtube/colorbar/tickformatstop/0000755000175000017500000000000013573746614027013 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/streamtube/colorbar/tickformatstop/__init__.py0000644000175000017500000000541313573721543031121 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="value", parent_name="streamtube.colorbar.tickformatstop", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="streamtube.colorbar.tickformatstop", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="streamtube.colorbar.tickformatstop", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EnabledValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="enabled", parent_name="streamtube.colorbar.tickformatstop", **kwargs ): super(EnabledValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DtickrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="dtickrange", parent_name="streamtube.colorbar.tickformatstop", **kwargs ): super(DtickrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "colorbars"}, {"valType": "any", "editType": "colorbars"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/streamtube/colorbar/title/0000755000175000017500000000000013573746614025063 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/streamtube/colorbar/title/__init__.py0000644000175000017500000000472613573721543027177 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="text", parent_name="streamtube.colorbar.title", **kwargs ): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SideValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="side", parent_name="streamtube.colorbar.title", **kwargs ): super(SideValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["right", "top", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="streamtube.colorbar.title", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/streamtube/colorbar/title/font/0000755000175000017500000000000013573746614026031 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/streamtube/colorbar/title/font/__init__.py0000644000175000017500000000312513573721543030135 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="streamtube.colorbar.title.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="streamtube.colorbar.title.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="streamtube.colorbar.title.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/streamtube/colorbar/__init__.py0000644000175000017500000006037613573721544026062 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="ypad", parent_name="streamtube.colorbar", **kwargs): super(YpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class YanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="yanchor", parent_name="streamtube.colorbar", **kwargs ): super(YanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["top", "middle", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="y", parent_name="streamtube.colorbar", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="xpad", parent_name="streamtube.colorbar", **kwargs): super(XpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="xanchor", parent_name="streamtube.colorbar", **kwargs ): super(XanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "center", "right"]), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="x", parent_name="streamtube.colorbar", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TitleValidator(_plotly_utils.basevalidators.TitleValidator): def __init__( self, plotly_name="title", parent_name="streamtube.colorbar", **kwargs ): super(TitleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Title"), data_docs=kwargs.pop( "data_docs", """ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """, ), **kwargs ) import _plotly_utils.basevalidators class TickwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="tickwidth", parent_name="streamtube.colorbar", **kwargs ): super(TickwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickvalssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="tickvalssrc", parent_name="streamtube.colorbar", **kwargs ): super(TickvalssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickvalsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="tickvals", parent_name="streamtube.colorbar", **kwargs ): super(TickvalsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="ticktextsrc", parent_name="streamtube.colorbar", **kwargs ): super(TicktextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicktextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="ticktext", parent_name="streamtube.colorbar", **kwargs ): super(TicktextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="ticksuffix", parent_name="streamtube.colorbar", **kwargs ): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TicksValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="ticks", parent_name="streamtube.colorbar", **kwargs ): super(TicksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["outside", "inside", ""]), **kwargs ) import _plotly_utils.basevalidators class TickprefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickprefix", parent_name="streamtube.colorbar", **kwargs ): super(TickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="tickmode", parent_name="streamtube.colorbar", **kwargs ): super(TickmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "linear", "array"]), **kwargs ) import _plotly_utils.basevalidators class TicklenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ticklen", parent_name="streamtube.colorbar", **kwargs ): super(TicklenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickformatstopValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickformatstopdefaults", parent_name="streamtube.colorbar", **kwargs ): super(TickformatstopValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatstopsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="tickformatstops", parent_name="streamtube.colorbar", **kwargs ): super(TickformatstopsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickformat", parent_name="streamtube.colorbar", **kwargs ): super(TickformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickfont", parent_name="streamtube.colorbar", **kwargs ): super(TickfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class TickcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="tickcolor", parent_name="streamtube.colorbar", **kwargs ): super(TickcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__( self, plotly_name="tickangle", parent_name="streamtube.colorbar", **kwargs ): super(TickangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="tick0", parent_name="streamtube.colorbar", **kwargs ): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ThicknessmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="thicknessmode", parent_name="streamtube.colorbar", **kwargs ): super(ThicknessmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="thickness", parent_name="streamtube.colorbar", **kwargs ): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowticksuffixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showticksuffix", parent_name="streamtube.colorbar", **kwargs ): super(ShowticksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowtickprefixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showtickprefix", parent_name="streamtube.colorbar", **kwargs ): super(ShowtickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowticklabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showticklabels", parent_name="streamtube.colorbar", **kwargs ): super(ShowticklabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowexponentValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showexponent", parent_name="streamtube.colorbar", **kwargs ): super(ShowexponentValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class SeparatethousandsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="separatethousands", parent_name="streamtube.colorbar", **kwargs ): super(SeparatethousandsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="outlinewidth", parent_name="streamtube.colorbar", **kwargs ): super(OutlinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="outlinecolor", parent_name="streamtube.colorbar", **kwargs ): super(OutlinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NticksValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="nticks", parent_name="streamtube.colorbar", **kwargs ): super(NticksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LenmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="lenmode", parent_name="streamtube.colorbar", **kwargs ): super(LenmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class LenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="len", parent_name="streamtube.colorbar", **kwargs): super(LenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ExponentformatValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="exponentformat", parent_name="streamtube.colorbar", **kwargs ): super(ExponentformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "e", "E", "power", "SI", "B"]), **kwargs ) import _plotly_utils.basevalidators class DtickValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="dtick", parent_name="streamtube.colorbar", **kwargs ): super(DtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BorderwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="borderwidth", parent_name="streamtube.colorbar", **kwargs ): super(BorderwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="streamtube.colorbar", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="streamtube.colorbar", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/streamtube/colorbar/tickfont/0000755000175000017500000000000013573746614025563 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/streamtube/colorbar/tickfont/__init__.py0000644000175000017500000000303713573721543027671 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="streamtube.colorbar.tickfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="streamtube.colorbar.tickfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="streamtube.colorbar.tickfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/streamtube/lightposition/0000755000175000017500000000000013573746614025033 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/streamtube/lightposition/__init__.py0000644000175000017500000000313613573721543027141 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ZValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="z", parent_name="streamtube.lightposition", **kwargs ): super(ZValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 100000), min=kwargs.pop("min", -100000), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="y", parent_name="streamtube.lightposition", **kwargs ): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 100000), min=kwargs.pop("min", -100000), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="x", parent_name="streamtube.lightposition", **kwargs ): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 100000), min=kwargs.pop("min", -100000), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/streamtube/stream/0000755000175000017500000000000013573746614023432 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/streamtube/stream/__init__.py0000644000175000017500000000211013573721543025527 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TokenValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="token", parent_name="streamtube.stream", **kwargs): super(TokenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "info"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class MaxpointsValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="maxpoints", parent_name="streamtube.stream", **kwargs ): super(MaxpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 10000), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/streamtube/__init__.py0000644000175000017500000010766113573721544024256 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ZsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="zsrc", parent_name="streamtube", **kwargs): super(ZsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="z", parent_name="streamtube", **kwargs): super(ZValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class YsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="ysrc", parent_name="streamtube", **kwargs): super(YsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="y", parent_name="streamtube", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class XsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="xsrc", parent_name="streamtube", **kwargs): super(XsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="x", parent_name="streamtube", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class WsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="wsrc", parent_name="streamtube", **kwargs): super(WsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class WValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="w", parent_name="streamtube", **kwargs): super(WValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class VsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="vsrc", parent_name="streamtube", **kwargs): super(VsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="visible", parent_name="streamtube", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "legendonly"]), **kwargs ) import _plotly_utils.basevalidators class VValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="v", parent_name="streamtube", **kwargs): super(VValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class UsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="usrc", parent_name="streamtube", **kwargs): super(UsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="streamtube", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UidValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="uid", parent_name="streamtube", **kwargs): super(UidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="u", parent_name="streamtube", **kwargs): super(UValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="text", parent_name="streamtube", **kwargs): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class StreamValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="stream", parent_name="streamtube", **kwargs): super(StreamValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Stream"), data_docs=kwargs.pop( "data_docs", """ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """, ), **kwargs ) import _plotly_utils.basevalidators class StartsValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="starts", parent_name="streamtube", **kwargs): super(StartsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Starts"), data_docs=kwargs.pop( "data_docs", """ x Sets the x components of the starting position of the streamtubes xsrc Sets the source reference on plot.ly for x . y Sets the y components of the starting position of the streamtubes ysrc Sets the source reference on plot.ly for y . z Sets the z components of the starting position of the streamtubes zsrc Sets the source reference on plot.ly for z . """, ), **kwargs ) import _plotly_utils.basevalidators class SizerefValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="sizeref", parent_name="streamtube", **kwargs): super(SizerefValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ShowscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showscale", parent_name="streamtube", **kwargs): super(ShowscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SceneValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="scene", parent_name="streamtube", **kwargs): super(SceneValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "scene"), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ReversescaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="reversescale", parent_name="streamtube", **kwargs): super(ReversescaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="streamtube", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="streamtube", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="metasrc", parent_name="streamtube", **kwargs): super(MetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetaValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="meta", parent_name="streamtube", **kwargs): super(MetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MaxdisplayedValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="maxdisplayed", parent_name="streamtube", **kwargs): super(MaxdisplayedValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LightpositionValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="lightposition", parent_name="streamtube", **kwargs): super(LightpositionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Lightposition"), data_docs=kwargs.pop( "data_docs", """ x Numeric vector, representing the X coordinate for each vertex. y Numeric vector, representing the Y coordinate for each vertex. z Numeric vector, representing the Z coordinate for each vertex. """, ), **kwargs ) import _plotly_utils.basevalidators class LightingValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="lighting", parent_name="streamtube", **kwargs): super(LightingValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Lighting"), data_docs=kwargs.pop( "data_docs", """ ambient Ambient light increases overall color visibility but can wash out the image. diffuse Represents the extent that incident rays are reflected in a range of angles. facenormalsepsilon Epsilon for face normals calculation avoids math issues arising from degenerate geometry. fresnel Represents the reflectance as a dependency of the viewing angle; e.g. paper is reflective when viewing it from the edge of the paper (almost 90 degrees), causing shine. roughness Alters specular reflection; the rougher the surface, the wider and less contrasty the shine. specular Represents the level that incident rays are reflected in a single direction, causing shine. vertexnormalsepsilon Epsilon for vertex normals calculation avoids math issues arising from degenerate geometry. """, ), **kwargs ) import _plotly_utils.basevalidators class IdssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="idssrc", parent_name="streamtube", **kwargs): super(IdssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ids", parent_name="streamtube", **kwargs): super(IdsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class HovertextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertext", parent_name="streamtube", **kwargs): super(HovertextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="hovertemplatesrc", parent_name="streamtube", **kwargs ): super(HovertemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertemplate", parent_name="streamtube", **kwargs): super(HovertemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverlabelValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="hoverlabel", parent_name="streamtube", **kwargs): super(HoverlabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Hoverlabel"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """, ), **kwargs ) import _plotly_utils.basevalidators class HoverinfosrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hoverinfosrc", parent_name="streamtube", **kwargs): super(HoverinfosrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverinfoValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="hoverinfo", parent_name="streamtube", **kwargs): super(HoverinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), extras=kwargs.pop("extras", ["all", "none", "skip"]), flags=kwargs.pop( "flags", ["x", "y", "z", "u", "v", "w", "norm", "divergence", "text", "name"], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdatasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="customdatasrc", parent_name="streamtube", **kwargs): super(CustomdatasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdataValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="customdata", parent_name="streamtube", **kwargs): super(CustomdataValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__(self, plotly_name="colorscale", parent_name="streamtube", **kwargs): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"autocolorscale": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorBarValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="colorbar", parent_name="streamtube", **kwargs): super(ColorBarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "ColorBar"), data_docs=kwargs.pop( "data_docs", """ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.streamtube.colo rbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.streamtube.colorbar.tickformatstopdefaults), sets the default property values to use for elements of streamtube.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.streamtube.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use streamtube.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use streamtube.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """, ), **kwargs ) import _plotly_utils.basevalidators class ColoraxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="coloraxis", parent_name="streamtube", **kwargs): super(ColoraxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", None), edit_type=kwargs.pop("edit_type", "calc"), regex=kwargs.pop("regex", "/^coloraxis([2-9]|[1-9][0-9]+)?$/"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmin", parent_name="streamtube", **kwargs): super(CminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmidValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmid", parent_name="streamtube", **kwargs): super(CmidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmax", parent_name="streamtube", **kwargs): super(CmaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CautoValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="cauto", parent_name="streamtube", **kwargs): super(CautoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AutocolorscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="autocolorscale", parent_name="streamtube", **kwargs ): super(AutocolorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/streamtube/lighting/0000755000175000017500000000000013573746614023744 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/streamtube/lighting/__init__.py0000644000175000017500000000755513573721543026063 0ustar noahfxnoahfximport _plotly_utils.basevalidators class VertexnormalsepsilonValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="vertexnormalsepsilon", parent_name="streamtube.lighting", **kwargs ): super(VertexnormalsepsilonValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SpecularValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="specular", parent_name="streamtube.lighting", **kwargs ): super(SpecularValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 2), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class RoughnessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="roughness", parent_name="streamtube.lighting", **kwargs ): super(RoughnessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FresnelValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="fresnel", parent_name="streamtube.lighting", **kwargs ): super(FresnelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 5), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FacenormalsepsilonValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="facenormalsepsilon", parent_name="streamtube.lighting", **kwargs ): super(FacenormalsepsilonValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class DiffuseValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="diffuse", parent_name="streamtube.lighting", **kwargs ): super(DiffuseValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AmbientValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ambient", parent_name="streamtube.lighting", **kwargs ): super(AmbientValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatter3d/0000755000175000017500000000000013573746614021660 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatter3d/textfont/0000755000175000017500000000000013573746614023533 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatter3d/textfont/__init__.py0000644000175000017500000000502513573721542025637 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="scatter3d.textfont", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="size", parent_name="scatter3d.textfont", **kwargs): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="scatter3d.textfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", False), edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="scatter3d.textfont", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="scatter3d.textfont", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatter3d/error_x/0000755000175000017500000000000013573746614023340 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatter3d/error_x/__init__.py0000644000175000017500000001621013573721542025442 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="scatter3d.error_x", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="visible", parent_name="scatter3d.error_x", **kwargs ): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ValueminusValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="valueminus", parent_name="scatter3d.error_x", **kwargs ): super(ValueminusValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="value", parent_name="scatter3d.error_x", **kwargs): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TypeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="type", parent_name="scatter3d.error_x", **kwargs): super(TypeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["percent", "constant", "sqrt", "data"]), **kwargs ) import _plotly_utils.basevalidators class TracerefminusValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="tracerefminus", parent_name="scatter3d.error_x", **kwargs ): super(TracerefminusValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TracerefValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="traceref", parent_name="scatter3d.error_x", **kwargs ): super(TracerefValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="thickness", parent_name="scatter3d.error_x", **kwargs ): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SymmetricValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="symmetric", parent_name="scatter3d.error_x", **kwargs ): super(SymmetricValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CopyZstyleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="copy_zstyle", parent_name="scatter3d.error_x", **kwargs ): super(CopyZstyleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="scatter3d.error_x", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ArraysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="arraysrc", parent_name="scatter3d.error_x", **kwargs ): super(ArraysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ArrayminussrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="arrayminussrc", parent_name="scatter3d.error_x", **kwargs ): super(ArrayminussrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ArrayminusValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="arrayminus", parent_name="scatter3d.error_x", **kwargs ): super(ArrayminusValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class ArrayValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="array", parent_name="scatter3d.error_x", **kwargs): super(ArrayValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatter3d/hoverlabel/0000755000175000017500000000000013573746614024003 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatter3d/hoverlabel/__init__.py0000644000175000017500000001346113573721542026112 0ustar noahfxnoahfximport _plotly_utils.basevalidators class NamelengthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="namelengthsrc", parent_name="scatter3d.hoverlabel", **kwargs ): super(NamelengthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NamelengthValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="namelength", parent_name="scatter3d.hoverlabel", **kwargs ): super(NamelengthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", -1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="scatter3d.hoverlabel", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class BordercolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bordercolorsrc", parent_name="scatter3d.hoverlabel", **kwargs ): super(BordercolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="scatter3d.hoverlabel", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bgcolorsrc", parent_name="scatter3d.hoverlabel", **kwargs ): super(BgcolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="scatter3d.hoverlabel", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AlignsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="alignsrc", parent_name="scatter3d.hoverlabel", **kwargs ): super(AlignsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="align", parent_name="scatter3d.hoverlabel", **kwargs ): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "right", "auto"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatter3d/hoverlabel/font/0000755000175000017500000000000013573746614024751 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatter3d/hoverlabel/font/__init__.py0000644000175000017500000000606113573721542027056 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="scatter3d.hoverlabel.font", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scatter3d.hoverlabel.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="scatter3d.hoverlabel.font", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="scatter3d.hoverlabel.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="scatter3d.hoverlabel.font", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scatter3d.hoverlabel.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatter3d/error_y/0000755000175000017500000000000013573746614023341 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatter3d/error_y/__init__.py0000644000175000017500000001621013573721542025443 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="scatter3d.error_y", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="visible", parent_name="scatter3d.error_y", **kwargs ): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ValueminusValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="valueminus", parent_name="scatter3d.error_y", **kwargs ): super(ValueminusValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="value", parent_name="scatter3d.error_y", **kwargs): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TypeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="type", parent_name="scatter3d.error_y", **kwargs): super(TypeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["percent", "constant", "sqrt", "data"]), **kwargs ) import _plotly_utils.basevalidators class TracerefminusValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="tracerefminus", parent_name="scatter3d.error_y", **kwargs ): super(TracerefminusValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TracerefValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="traceref", parent_name="scatter3d.error_y", **kwargs ): super(TracerefValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="thickness", parent_name="scatter3d.error_y", **kwargs ): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SymmetricValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="symmetric", parent_name="scatter3d.error_y", **kwargs ): super(SymmetricValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CopyZstyleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="copy_zstyle", parent_name="scatter3d.error_y", **kwargs ): super(CopyZstyleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="scatter3d.error_y", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ArraysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="arraysrc", parent_name="scatter3d.error_y", **kwargs ): super(ArraysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ArrayminussrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="arrayminussrc", parent_name="scatter3d.error_y", **kwargs ): super(ArrayminussrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ArrayminusValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="arrayminus", parent_name="scatter3d.error_y", **kwargs ): super(ArrayminusValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class ArrayValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="array", parent_name="scatter3d.error_y", **kwargs): super(ArrayValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatter3d/projection/0000755000175000017500000000000013573746614024034 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatter3d/projection/x/0000755000175000017500000000000013573746614024303 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatter3d/projection/x/__init__.py0000644000175000017500000000302313573721542026403 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ShowValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="show", parent_name="scatter3d.projection.x", **kwargs ): super(ShowValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ScaleValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="scale", parent_name="scatter3d.projection.x", **kwargs ): super(ScaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 10), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="opacity", parent_name="scatter3d.projection.x", **kwargs ): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatter3d/projection/z/0000755000175000017500000000000013573746614024305 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatter3d/projection/z/__init__.py0000644000175000017500000000302313573721542026405 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ShowValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="show", parent_name="scatter3d.projection.z", **kwargs ): super(ShowValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ScaleValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="scale", parent_name="scatter3d.projection.z", **kwargs ): super(ScaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 10), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="opacity", parent_name="scatter3d.projection.z", **kwargs ): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatter3d/projection/y/0000755000175000017500000000000013573746614024304 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatter3d/projection/y/__init__.py0000644000175000017500000000302313573721542026404 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ShowValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="show", parent_name="scatter3d.projection.y", **kwargs ): super(ShowValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ScaleValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="scale", parent_name="scatter3d.projection.y", **kwargs ): super(ScaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 10), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="opacity", parent_name="scatter3d.projection.y", **kwargs ): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatter3d/projection/__init__.py0000644000175000017500000000454713573721542026150 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ZValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="z", parent_name="scatter3d.projection", **kwargs): super(ZValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Z"), data_docs=kwargs.pop( "data_docs", """ opacity Sets the projection color. scale Sets the scale factor determining the size of the projection marker points. show Sets whether or not projections are shown along the z axis. """, ), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="y", parent_name="scatter3d.projection", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Y"), data_docs=kwargs.pop( "data_docs", """ opacity Sets the projection color. scale Sets the scale factor determining the size of the projection marker points. show Sets whether or not projections are shown along the y axis. """, ), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="x", parent_name="scatter3d.projection", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "X"), data_docs=kwargs.pop( "data_docs", """ opacity Sets the projection color. scale Sets the scale factor determining the size of the projection marker points. show Sets whether or not projections are shown along the x axis. """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatter3d/error_z/0000755000175000017500000000000013573746614023342 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatter3d/error_z/__init__.py0000644000175000017500000001525113573721542025450 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="scatter3d.error_z", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="visible", parent_name="scatter3d.error_z", **kwargs ): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ValueminusValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="valueminus", parent_name="scatter3d.error_z", **kwargs ): super(ValueminusValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="value", parent_name="scatter3d.error_z", **kwargs): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TypeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="type", parent_name="scatter3d.error_z", **kwargs): super(TypeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["percent", "constant", "sqrt", "data"]), **kwargs ) import _plotly_utils.basevalidators class TracerefminusValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="tracerefminus", parent_name="scatter3d.error_z", **kwargs ): super(TracerefminusValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TracerefValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="traceref", parent_name="scatter3d.error_z", **kwargs ): super(TracerefValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="thickness", parent_name="scatter3d.error_z", **kwargs ): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SymmetricValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="symmetric", parent_name="scatter3d.error_z", **kwargs ): super(SymmetricValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="scatter3d.error_z", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ArraysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="arraysrc", parent_name="scatter3d.error_z", **kwargs ): super(ArraysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ArrayminussrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="arrayminussrc", parent_name="scatter3d.error_z", **kwargs ): super(ArrayminussrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ArrayminusValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="arrayminus", parent_name="scatter3d.error_z", **kwargs ): super(ArrayminusValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class ArrayValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="array", parent_name="scatter3d.error_z", **kwargs): super(ArrayValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatter3d/marker/0000755000175000017500000000000013573746614023141 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatter3d/marker/colorbar/0000755000175000017500000000000013573746614024744 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatter3d/marker/colorbar/tickformatstop/0000755000175000017500000000000013573746614030015 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatter3d/marker/colorbar/tickformatstop/__init__.py0000644000175000017500000000540613573721542032124 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="value", parent_name="scatter3d.marker.colorbar.tickformatstop", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="scatter3d.marker.colorbar.tickformatstop", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="scatter3d.marker.colorbar.tickformatstop", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EnabledValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="enabled", parent_name="scatter3d.marker.colorbar.tickformatstop", **kwargs ): super(EnabledValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DtickrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="dtickrange", parent_name="scatter3d.marker.colorbar.tickformatstop", **kwargs ): super(DtickrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "calc"}, {"valType": "any", "editType": "calc"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatter3d/marker/colorbar/title/0000755000175000017500000000000013573746614026065 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatter3d/marker/colorbar/title/__init__.py0000644000175000017500000000504613573721542030174 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="text", parent_name="scatter3d.marker.colorbar.title", **kwargs ): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SideValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="side", parent_name="scatter3d.marker.colorbar.title", **kwargs ): super(SideValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["right", "top", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="scatter3d.marker.colorbar.title", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatter3d/marker/colorbar/title/font/0000755000175000017500000000000013573746614027033 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatter3d/marker/colorbar/title/font/__init__.py0000644000175000017500000000316013573721542031135 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scatter3d.marker.colorbar.title.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="scatter3d.marker.colorbar.title.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scatter3d.marker.colorbar.title.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatter3d/marker/colorbar/__init__.py0000644000175000017500000006141313573721543027054 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ypad", parent_name="scatter3d.marker.colorbar", **kwargs ): super(YpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class YanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="yanchor", parent_name="scatter3d.marker.colorbar", **kwargs ): super(YanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["top", "middle", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="y", parent_name="scatter3d.marker.colorbar", **kwargs ): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="xpad", parent_name="scatter3d.marker.colorbar", **kwargs ): super(XpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="xanchor", parent_name="scatter3d.marker.colorbar", **kwargs ): super(XanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "center", "right"]), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="x", parent_name="scatter3d.marker.colorbar", **kwargs ): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TitleValidator(_plotly_utils.basevalidators.TitleValidator): def __init__( self, plotly_name="title", parent_name="scatter3d.marker.colorbar", **kwargs ): super(TitleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Title"), data_docs=kwargs.pop( "data_docs", """ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """, ), **kwargs ) import _plotly_utils.basevalidators class TickwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="tickwidth", parent_name="scatter3d.marker.colorbar", **kwargs ): super(TickwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickvalssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="tickvalssrc", parent_name="scatter3d.marker.colorbar", **kwargs ): super(TickvalssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickvalsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="tickvals", parent_name="scatter3d.marker.colorbar", **kwargs ): super(TickvalsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="ticktextsrc", parent_name="scatter3d.marker.colorbar", **kwargs ): super(TicktextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicktextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="ticktext", parent_name="scatter3d.marker.colorbar", **kwargs ): super(TicktextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="ticksuffix", parent_name="scatter3d.marker.colorbar", **kwargs ): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TicksValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="ticks", parent_name="scatter3d.marker.colorbar", **kwargs ): super(TicksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["outside", "inside", ""]), **kwargs ) import _plotly_utils.basevalidators class TickprefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickprefix", parent_name="scatter3d.marker.colorbar", **kwargs ): super(TickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="tickmode", parent_name="scatter3d.marker.colorbar", **kwargs ): super(TickmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "linear", "array"]), **kwargs ) import _plotly_utils.basevalidators class TicklenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ticklen", parent_name="scatter3d.marker.colorbar", **kwargs ): super(TicklenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickformatstopValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickformatstopdefaults", parent_name="scatter3d.marker.colorbar", **kwargs ): super(TickformatstopValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatstopsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="tickformatstops", parent_name="scatter3d.marker.colorbar", **kwargs ): super(TickformatstopsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickformat", parent_name="scatter3d.marker.colorbar", **kwargs ): super(TickformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickfont", parent_name="scatter3d.marker.colorbar", **kwargs ): super(TickfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class TickcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="tickcolor", parent_name="scatter3d.marker.colorbar", **kwargs ): super(TickcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__( self, plotly_name="tickangle", parent_name="scatter3d.marker.colorbar", **kwargs ): super(TickangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="tick0", parent_name="scatter3d.marker.colorbar", **kwargs ): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ThicknessmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="thicknessmode", parent_name="scatter3d.marker.colorbar", **kwargs ): super(ThicknessmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="thickness", parent_name="scatter3d.marker.colorbar", **kwargs ): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowticksuffixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showticksuffix", parent_name="scatter3d.marker.colorbar", **kwargs ): super(ShowticksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowtickprefixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showtickprefix", parent_name="scatter3d.marker.colorbar", **kwargs ): super(ShowtickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowticklabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showticklabels", parent_name="scatter3d.marker.colorbar", **kwargs ): super(ShowticklabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowexponentValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showexponent", parent_name="scatter3d.marker.colorbar", **kwargs ): super(ShowexponentValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class SeparatethousandsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="separatethousands", parent_name="scatter3d.marker.colorbar", **kwargs ): super(SeparatethousandsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="outlinewidth", parent_name="scatter3d.marker.colorbar", **kwargs ): super(OutlinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="outlinecolor", parent_name="scatter3d.marker.colorbar", **kwargs ): super(OutlinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NticksValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="nticks", parent_name="scatter3d.marker.colorbar", **kwargs ): super(NticksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LenmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="lenmode", parent_name="scatter3d.marker.colorbar", **kwargs ): super(LenmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class LenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="len", parent_name="scatter3d.marker.colorbar", **kwargs ): super(LenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ExponentformatValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="exponentformat", parent_name="scatter3d.marker.colorbar", **kwargs ): super(ExponentformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "e", "E", "power", "SI", "B"]), **kwargs ) import _plotly_utils.basevalidators class DtickValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="dtick", parent_name="scatter3d.marker.colorbar", **kwargs ): super(DtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BorderwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="borderwidth", parent_name="scatter3d.marker.colorbar", **kwargs ): super(BorderwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="scatter3d.marker.colorbar", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="scatter3d.marker.colorbar", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatter3d/marker/colorbar/tickfont/0000755000175000017500000000000013573746614026565 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatter3d/marker/colorbar/tickfont/__init__.py0000644000175000017500000000315213573721542030670 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scatter3d.marker.colorbar.tickfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="scatter3d.marker.colorbar.tickfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scatter3d.marker.colorbar.tickfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatter3d/marker/__init__.py0000644000175000017500000006260113573721542025250 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SymbolsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="symbolsrc", parent_name="scatter3d.marker", **kwargs ): super(SymbolsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SymbolValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="symbol", parent_name="scatter3d.marker", **kwargs): super(SymbolValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", [ "circle", "circle-open", "square", "square-open", "diamond", "diamond-open", "cross", "x", ], ), **kwargs ) import _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="sizesrc", parent_name="scatter3d.marker", **kwargs): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizerefValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="sizeref", parent_name="scatter3d.marker", **kwargs): super(SizerefValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SizemodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="sizemode", parent_name="scatter3d.marker", **kwargs ): super(SizemodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["diameter", "area"]), **kwargs ) import _plotly_utils.basevalidators class SizeminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="sizemin", parent_name="scatter3d.marker", **kwargs): super(SizeminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="size", parent_name="scatter3d.marker", **kwargs): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showscale", parent_name="scatter3d.marker", **kwargs ): super(ShowscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ReversescaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="reversescale", parent_name="scatter3d.marker", **kwargs ): super(ReversescaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="scatter3d.marker", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", False), edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="line", parent_name="scatter3d.marker", **kwargs): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,R eds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Black body,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. """, ), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="scatter3d.marker", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__( self, plotly_name="colorscale", parent_name="scatter3d.marker", **kwargs ): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"autocolorscale": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorBarValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="colorbar", parent_name="scatter3d.marker", **kwargs ): super(ColorBarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "ColorBar"), data_docs=kwargs.pop( "data_docs", """ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.scatter3d.marke r.colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.scatter3d.marker.colorbar.tickformatstopdefau lts), sets the default property values to use for elements of scatter3d.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.scatter3d.marker.colorbar. Title instance or dict with compatible properties titlefont Deprecated: Please use scatter3d.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use scatter3d.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """, ), **kwargs ) import _plotly_utils.basevalidators class ColoraxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__( self, plotly_name="coloraxis", parent_name="scatter3d.marker", **kwargs ): super(ColoraxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", None), edit_type=kwargs.pop("edit_type", "calc"), regex=kwargs.pop("regex", "/^coloraxis([2-9]|[1-9][0-9]+)?$/"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="scatter3d.marker", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), colorscale_path=kwargs.pop( "colorscale_path", "scatter3d.marker.colorscale" ), **kwargs ) import _plotly_utils.basevalidators class CminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmin", parent_name="scatter3d.marker", **kwargs): super(CminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmidValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmid", parent_name="scatter3d.marker", **kwargs): super(CmidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmax", parent_name="scatter3d.marker", **kwargs): super(CmaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CautoValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="cauto", parent_name="scatter3d.marker", **kwargs): super(CautoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AutocolorscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="autocolorscale", parent_name="scatter3d.marker", **kwargs ): super(AutocolorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatter3d/marker/line/0000755000175000017500000000000013573746614024070 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatter3d/marker/line/__init__.py0000644000175000017500000001357513573721542026205 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="width", parent_name="scatter3d.marker.line", **kwargs ): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", False), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ReversescaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="reversescale", parent_name="scatter3d.marker.line", **kwargs ): super(ReversescaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="scatter3d.marker.line", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__( self, plotly_name="colorscale", parent_name="scatter3d.marker.line", **kwargs ): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"autocolorscale": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColoraxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__( self, plotly_name="coloraxis", parent_name="scatter3d.marker.line", **kwargs ): super(ColoraxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", None), edit_type=kwargs.pop("edit_type", "calc"), regex=kwargs.pop("regex", "/^coloraxis([2-9]|[1-9][0-9]+)?$/"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scatter3d.marker.line", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), colorscale_path=kwargs.pop( "colorscale_path", "scatter3d.marker.line.colorscale" ), **kwargs ) import _plotly_utils.basevalidators class CminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="cmin", parent_name="scatter3d.marker.line", **kwargs ): super(CminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmidValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="cmid", parent_name="scatter3d.marker.line", **kwargs ): super(CmidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="cmax", parent_name="scatter3d.marker.line", **kwargs ): super(CmaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CautoValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="cauto", parent_name="scatter3d.marker.line", **kwargs ): super(CautoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AutocolorscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="autocolorscale", parent_name="scatter3d.marker.line", **kwargs ): super(AutocolorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatter3d/stream/0000755000175000017500000000000013573746614023153 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatter3d/stream/__init__.py0000644000175000017500000000210613573721542025254 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TokenValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="token", parent_name="scatter3d.stream", **kwargs): super(TokenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "info"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class MaxpointsValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="maxpoints", parent_name="scatter3d.stream", **kwargs ): super(MaxpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 10000), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatter3d/__init__.py0000644000175000017500000013337013573721543023772 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ZsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="zsrc", parent_name="scatter3d", **kwargs): super(ZsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZcalendarValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="zcalendar", parent_name="scatter3d", **kwargs): super(ZcalendarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "gregorian", "chinese", "coptic", "discworld", "ethiopian", "hebrew", "islamic", "julian", "mayan", "nanakshahi", "nepali", "persian", "jalali", "taiwan", "thai", "ummalqura", ], ), **kwargs ) import _plotly_utils.basevalidators class ZValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="z", parent_name="scatter3d", **kwargs): super(ZValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class YsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="ysrc", parent_name="scatter3d", **kwargs): super(YsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YcalendarValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="ycalendar", parent_name="scatter3d", **kwargs): super(YcalendarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "gregorian", "chinese", "coptic", "discworld", "ethiopian", "hebrew", "islamic", "julian", "mayan", "nanakshahi", "nepali", "persian", "jalali", "taiwan", "thai", "ummalqura", ], ), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="y", parent_name="scatter3d", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class XsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="xsrc", parent_name="scatter3d", **kwargs): super(XsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XcalendarValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="xcalendar", parent_name="scatter3d", **kwargs): super(XcalendarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "gregorian", "chinese", "coptic", "discworld", "ethiopian", "hebrew", "islamic", "julian", "mayan", "nanakshahi", "nepali", "persian", "jalali", "taiwan", "thai", "ummalqura", ], ), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="x", parent_name="scatter3d", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="visible", parent_name="scatter3d", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "legendonly"]), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="scatter3d", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UidValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="uid", parent_name="scatter3d", **kwargs): super(UidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TexttemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="texttemplatesrc", parent_name="scatter3d", **kwargs ): super(TexttemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TexttemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="texttemplate", parent_name="scatter3d", **kwargs): super(TexttemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="textsrc", parent_name="scatter3d", **kwargs): super(TextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextpositionsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="textpositionsrc", parent_name="scatter3d", **kwargs ): super(TextpositionsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextpositionValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="textposition", parent_name="scatter3d", **kwargs): super(TextpositionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", [ "top left", "top center", "top right", "middle left", "middle center", "middle right", "bottom left", "bottom center", "bottom right", ], ), **kwargs ) import _plotly_utils.basevalidators class TextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="textfont", parent_name="scatter3d", **kwargs): super(TextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Textfont"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="text", parent_name="scatter3d", **kwargs): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SurfacecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="surfacecolor", parent_name="scatter3d", **kwargs): super(SurfacecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SurfaceaxisValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="surfaceaxis", parent_name="scatter3d", **kwargs): super(SurfaceaxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [-1, 0, 1, 2]), **kwargs ) import _plotly_utils.basevalidators class StreamValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="stream", parent_name="scatter3d", **kwargs): super(StreamValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Stream"), data_docs=kwargs.pop( "data_docs", """ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """, ), **kwargs ) import _plotly_utils.basevalidators class ShowlegendValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showlegend", parent_name="scatter3d", **kwargs): super(ShowlegendValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SceneValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="scene", parent_name="scatter3d", **kwargs): super(SceneValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "scene"), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ProjectionValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="projection", parent_name="scatter3d", **kwargs): super(ProjectionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Projection"), data_docs=kwargs.pop( "data_docs", """ x plotly.graph_objects.scatter3d.projection.X instance or dict with compatible properties y plotly.graph_objects.scatter3d.projection.Y instance or dict with compatible properties z plotly.graph_objects.scatter3d.projection.Z instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="scatter3d", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="scatter3d", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ModeValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="mode", parent_name="scatter3d", **kwargs): super(ModeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), extras=kwargs.pop("extras", ["none"]), flags=kwargs.pop("flags", ["lines", "markers", "text"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="metasrc", parent_name="scatter3d", **kwargs): super(MetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetaValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="meta", parent_name="scatter3d", **kwargs): super(MetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="marker", parent_name="scatter3d", **kwargs): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.scatter3d.marker.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . line plotly.graph_objects.scatter3d.marker.Line instance or dict with compatible properties opacity Sets the marker opacity. Note that the marker opacity for scatter3d traces must be a scalar value for performance reasons. To set a blending opacity value (i.e. which is not transparent), set "marker.color" to an rgba color and use its alpha channel. reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. size Sets the marker size (in px). sizemin Has an effect only if `marker.size` is set to a numerical array. Sets the minimum size (in px) of the rendered marker points. sizemode Has an effect only if `marker.size` is set to a numerical array. Sets the rule for which the data in `size` is converted to pixels. sizeref Has an effect only if `marker.size` is set to a numerical array. Sets the scale factor used to determine the rendered size of marker points. Use with `sizemin` and `sizemode`. sizesrc Sets the source reference on plot.ly for size . symbol Sets the marker symbol type. symbolsrc Sets the source reference on plot.ly for symbol . """, ), **kwargs ) import _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="line", parent_name="scatter3d", **kwargs): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `line.colorscale`. Has an effect only if in `line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `line.color`) or the bounds set in `line.cmin` and `line.cmax` Has an effect only if in `line.color`is set to a numerical array. Defaults to `false` when `line.cmin` and `line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `line.color`is set to a numerical array. Value should have the same units as in `line.color` and if set, `line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `line.cmin` and/or `line.cmax` to be equidistant to this point. Has an effect only if in `line.color`is set to a numerical array. Value should have the same units as in `line.color`. Has no effect when `line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `line.color`is set to a numerical array. Value should have the same units as in `line.color` and if set, `line.cmax` must be set as well. color Sets thelinecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `line.cmin` and `line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.scatter3d.line.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`line.cmin` and `line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu ,Greens,YlOrRd,Bluered,RdBu,Reds,Blues,Picnic,R ainbow,Portland,Jet,Hot,Blackbody,Earth,Electri c,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . dash Sets the dash style of the lines. reversescale Reverses the color mapping if true. Has an effect only if in `line.color`is set to a numerical array. If true, `line.cmin` will correspond to the last color in the array and `line.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `line.color`is set to a numerical array. width Sets the line width (in px). """, ), **kwargs ) import _plotly_utils.basevalidators class LegendgroupValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="legendgroup", parent_name="scatter3d", **kwargs): super(LegendgroupValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="idssrc", parent_name="scatter3d", **kwargs): super(IdssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ids", parent_name="scatter3d", **kwargs): super(IdsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class HovertextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hovertextsrc", parent_name="scatter3d", **kwargs): super(HovertextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertext", parent_name="scatter3d", **kwargs): super(HovertextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="hovertemplatesrc", parent_name="scatter3d", **kwargs ): super(HovertemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertemplate", parent_name="scatter3d", **kwargs): super(HovertemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverlabelValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="hoverlabel", parent_name="scatter3d", **kwargs): super(HoverlabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Hoverlabel"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """, ), **kwargs ) import _plotly_utils.basevalidators class HoverinfosrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hoverinfosrc", parent_name="scatter3d", **kwargs): super(HoverinfosrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverinfoValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="hoverinfo", parent_name="scatter3d", **kwargs): super(HoverinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), extras=kwargs.pop("extras", ["all", "none", "skip"]), flags=kwargs.pop("flags", ["x", "y", "z", "text", "name"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ErrorZValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="error_z", parent_name="scatter3d", **kwargs): super(ErrorZValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "ErrorZ"), data_docs=kwargs.pop( "data_docs", """ array Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. arrayminus Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. arrayminussrc Sets the source reference on plot.ly for arrayminus . arraysrc Sets the source reference on plot.ly for array . color Sets the stoke color of the error bars. symmetric Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. thickness Sets the thickness (in px) of the error bars. traceref tracerefminus type Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. value Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. valueminus Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars visible Determines whether or not this set of error bars is visible. width Sets the width (in px) of the cross-bar at both ends of the error bars. """, ), **kwargs ) import _plotly_utils.basevalidators class ErrorYValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="error_y", parent_name="scatter3d", **kwargs): super(ErrorYValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "ErrorY"), data_docs=kwargs.pop( "data_docs", """ array Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. arrayminus Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. arrayminussrc Sets the source reference on plot.ly for arrayminus . arraysrc Sets the source reference on plot.ly for array . color Sets the stoke color of the error bars. copy_zstyle symmetric Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. thickness Sets the thickness (in px) of the error bars. traceref tracerefminus type Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. value Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. valueminus Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars visible Determines whether or not this set of error bars is visible. width Sets the width (in px) of the cross-bar at both ends of the error bars. """, ), **kwargs ) import _plotly_utils.basevalidators class ErrorXValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="error_x", parent_name="scatter3d", **kwargs): super(ErrorXValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "ErrorX"), data_docs=kwargs.pop( "data_docs", """ array Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. arrayminus Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. arrayminussrc Sets the source reference on plot.ly for arrayminus . arraysrc Sets the source reference on plot.ly for array . color Sets the stoke color of the error bars. copy_zstyle symmetric Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. thickness Sets the thickness (in px) of the error bars. traceref tracerefminus type Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. value Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. valueminus Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars visible Determines whether or not this set of error bars is visible. width Sets the width (in px) of the cross-bar at both ends of the error bars. """, ), **kwargs ) import _plotly_utils.basevalidators class CustomdatasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="customdatasrc", parent_name="scatter3d", **kwargs): super(CustomdatasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdataValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="customdata", parent_name="scatter3d", **kwargs): super(CustomdataValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class ConnectgapsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="connectgaps", parent_name="scatter3d", **kwargs): super(ConnectgapsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatter3d/line/0000755000175000017500000000000013573746614022607 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatter3d/line/colorbar/0000755000175000017500000000000013573746614024412 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatter3d/line/colorbar/tickformatstop/0000755000175000017500000000000013573746614027463 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatter3d/line/colorbar/tickformatstop/__init__.py0000644000175000017500000000537413573721542031576 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="value", parent_name="scatter3d.line.colorbar.tickformatstop", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="scatter3d.line.colorbar.tickformatstop", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="scatter3d.line.colorbar.tickformatstop", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EnabledValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="enabled", parent_name="scatter3d.line.colorbar.tickformatstop", **kwargs ): super(EnabledValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DtickrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="dtickrange", parent_name="scatter3d.line.colorbar.tickformatstop", **kwargs ): super(DtickrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "calc"}, {"valType": "any", "editType": "calc"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatter3d/line/colorbar/title/0000755000175000017500000000000013573746614025533 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatter3d/line/colorbar/title/__init__.py0000644000175000017500000000473013573721542027641 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="text", parent_name="scatter3d.line.colorbar.title", **kwargs ): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SideValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="side", parent_name="scatter3d.line.colorbar.title", **kwargs ): super(SideValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["right", "top", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="scatter3d.line.colorbar.title", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatter3d/line/colorbar/title/font/0000755000175000017500000000000013573746614026501 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatter3d/line/colorbar/title/font/__init__.py0000644000175000017500000000315213573721542030604 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scatter3d.line.colorbar.title.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="scatter3d.line.colorbar.title.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scatter3d.line.colorbar.title.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatter3d/line/colorbar/__init__.py0000644000175000017500000006102113573721543026515 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ypad", parent_name="scatter3d.line.colorbar", **kwargs ): super(YpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class YanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="yanchor", parent_name="scatter3d.line.colorbar", **kwargs ): super(YanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["top", "middle", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="y", parent_name="scatter3d.line.colorbar", **kwargs ): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="xpad", parent_name="scatter3d.line.colorbar", **kwargs ): super(XpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="xanchor", parent_name="scatter3d.line.colorbar", **kwargs ): super(XanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "center", "right"]), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="x", parent_name="scatter3d.line.colorbar", **kwargs ): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TitleValidator(_plotly_utils.basevalidators.TitleValidator): def __init__( self, plotly_name="title", parent_name="scatter3d.line.colorbar", **kwargs ): super(TitleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Title"), data_docs=kwargs.pop( "data_docs", """ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """, ), **kwargs ) import _plotly_utils.basevalidators class TickwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="tickwidth", parent_name="scatter3d.line.colorbar", **kwargs ): super(TickwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickvalssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="tickvalssrc", parent_name="scatter3d.line.colorbar", **kwargs ): super(TickvalssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickvalsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="tickvals", parent_name="scatter3d.line.colorbar", **kwargs ): super(TickvalsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="ticktextsrc", parent_name="scatter3d.line.colorbar", **kwargs ): super(TicktextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicktextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="ticktext", parent_name="scatter3d.line.colorbar", **kwargs ): super(TicktextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="ticksuffix", parent_name="scatter3d.line.colorbar", **kwargs ): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TicksValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="ticks", parent_name="scatter3d.line.colorbar", **kwargs ): super(TicksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["outside", "inside", ""]), **kwargs ) import _plotly_utils.basevalidators class TickprefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickprefix", parent_name="scatter3d.line.colorbar", **kwargs ): super(TickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="tickmode", parent_name="scatter3d.line.colorbar", **kwargs ): super(TickmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "linear", "array"]), **kwargs ) import _plotly_utils.basevalidators class TicklenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ticklen", parent_name="scatter3d.line.colorbar", **kwargs ): super(TicklenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickformatstopValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickformatstopdefaults", parent_name="scatter3d.line.colorbar", **kwargs ): super(TickformatstopValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatstopsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="tickformatstops", parent_name="scatter3d.line.colorbar", **kwargs ): super(TickformatstopsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickformat", parent_name="scatter3d.line.colorbar", **kwargs ): super(TickformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickfont", parent_name="scatter3d.line.colorbar", **kwargs ): super(TickfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class TickcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="tickcolor", parent_name="scatter3d.line.colorbar", **kwargs ): super(TickcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__( self, plotly_name="tickangle", parent_name="scatter3d.line.colorbar", **kwargs ): super(TickangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="tick0", parent_name="scatter3d.line.colorbar", **kwargs ): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ThicknessmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="thicknessmode", parent_name="scatter3d.line.colorbar", **kwargs ): super(ThicknessmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="thickness", parent_name="scatter3d.line.colorbar", **kwargs ): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowticksuffixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showticksuffix", parent_name="scatter3d.line.colorbar", **kwargs ): super(ShowticksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowtickprefixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showtickprefix", parent_name="scatter3d.line.colorbar", **kwargs ): super(ShowtickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowticklabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showticklabels", parent_name="scatter3d.line.colorbar", **kwargs ): super(ShowticklabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowexponentValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showexponent", parent_name="scatter3d.line.colorbar", **kwargs ): super(ShowexponentValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class SeparatethousandsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="separatethousands", parent_name="scatter3d.line.colorbar", **kwargs ): super(SeparatethousandsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="outlinewidth", parent_name="scatter3d.line.colorbar", **kwargs ): super(OutlinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="outlinecolor", parent_name="scatter3d.line.colorbar", **kwargs ): super(OutlinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NticksValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="nticks", parent_name="scatter3d.line.colorbar", **kwargs ): super(NticksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LenmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="lenmode", parent_name="scatter3d.line.colorbar", **kwargs ): super(LenmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class LenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="len", parent_name="scatter3d.line.colorbar", **kwargs ): super(LenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ExponentformatValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="exponentformat", parent_name="scatter3d.line.colorbar", **kwargs ): super(ExponentformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "e", "E", "power", "SI", "B"]), **kwargs ) import _plotly_utils.basevalidators class DtickValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="dtick", parent_name="scatter3d.line.colorbar", **kwargs ): super(DtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BorderwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="borderwidth", parent_name="scatter3d.line.colorbar", **kwargs ): super(BorderwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="scatter3d.line.colorbar", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="scatter3d.line.colorbar", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatter3d/line/colorbar/tickfont/0000755000175000017500000000000013573746614026233 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatter3d/line/colorbar/tickfont/__init__.py0000644000175000017500000000314413573721542030337 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scatter3d.line.colorbar.tickfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="scatter3d.line.colorbar.tickfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scatter3d.line.colorbar.tickfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatter3d/line/__init__.py0000644000175000017500000004220013573721542024707 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="scatter3d.line", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showscale", parent_name="scatter3d.line", **kwargs): super(ShowscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ReversescaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="reversescale", parent_name="scatter3d.line", **kwargs ): super(ReversescaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class DashValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="dash", parent_name="scatter3d.line", **kwargs): super(DashValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", ["solid", "dot", "dash", "longdash", "dashdot", "longdashdot"] ), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="colorsrc", parent_name="scatter3d.line", **kwargs): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__( self, plotly_name="colorscale", parent_name="scatter3d.line", **kwargs ): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"autocolorscale": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorBarValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="colorbar", parent_name="scatter3d.line", **kwargs): super(ColorBarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "ColorBar"), data_docs=kwargs.pop( "data_docs", """ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.scatter3d.line. colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.scatter3d.line.colorbar.tickformatstopdefault s), sets the default property values to use for elements of scatter3d.line.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.scatter3d.line.colorbar.Ti tle instance or dict with compatible properties titlefont Deprecated: Please use scatter3d.line.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use scatter3d.line.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """, ), **kwargs ) import _plotly_utils.basevalidators class ColoraxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="coloraxis", parent_name="scatter3d.line", **kwargs): super(ColoraxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", None), edit_type=kwargs.pop("edit_type", "calc"), regex=kwargs.pop("regex", "/^coloraxis([2-9]|[1-9][0-9]+)?$/"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="scatter3d.line", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), colorscale_path=kwargs.pop("colorscale_path", "scatter3d.line.colorscale"), **kwargs ) import _plotly_utils.basevalidators class CminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmin", parent_name="scatter3d.line", **kwargs): super(CminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmidValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmid", parent_name="scatter3d.line", **kwargs): super(CmidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmax", parent_name="scatter3d.line", **kwargs): super(CmaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CautoValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="cauto", parent_name="scatter3d.line", **kwargs): super(CautoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AutocolorscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="autocolorscale", parent_name="scatter3d.line", **kwargs ): super(AutocolorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/ohlc/0000755000175000017500000000000013573746614020711 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/ohlc/increasing/0000755000175000017500000000000013573746614023033 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/ohlc/increasing/__init__.py0000644000175000017500000000156413573721541025142 0ustar noahfxnoahfximport _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="line", parent_name="ohlc.increasing", **kwargs): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ color Sets the line color. dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). width Sets the line width (in px). """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/ohlc/increasing/line/0000755000175000017500000000000013573746614023762 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/ohlc/increasing/line/__init__.py0000644000175000017500000000303313573721541026062 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="width", parent_name="ohlc.increasing.line", **kwargs ): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class DashValidator(_plotly_utils.basevalidators.DashValidator): def __init__( self, plotly_name="dash", parent_name="ohlc.increasing.line", **kwargs ): super(DashValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", ["solid", "dot", "dash", "longdash", "dashdot", "longdashdot"] ), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="ohlc.increasing.line", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/ohlc/hoverlabel/0000755000175000017500000000000013573746614023034 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/ohlc/hoverlabel/__init__.py0000644000175000017500000001421313573721541025136 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SplitValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="split", parent_name="ohlc.hoverlabel", **kwargs): super(SplitValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NamelengthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="namelengthsrc", parent_name="ohlc.hoverlabel", **kwargs ): super(NamelengthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NamelengthValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="namelength", parent_name="ohlc.hoverlabel", **kwargs ): super(NamelengthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", -1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="font", parent_name="ohlc.hoverlabel", **kwargs): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class BordercolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bordercolorsrc", parent_name="ohlc.hoverlabel", **kwargs ): super(BordercolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="ohlc.hoverlabel", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bgcolorsrc", parent_name="ohlc.hoverlabel", **kwargs ): super(BgcolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="bgcolor", parent_name="ohlc.hoverlabel", **kwargs): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AlignsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="alignsrc", parent_name="ohlc.hoverlabel", **kwargs): super(AlignsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="align", parent_name="ohlc.hoverlabel", **kwargs): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "right", "auto"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/ohlc/hoverlabel/font/0000755000175000017500000000000013573746614024002 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/ohlc/hoverlabel/font/__init__.py0000644000175000017500000000602313573721541026104 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="ohlc.hoverlabel.font", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="ohlc.hoverlabel.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="ohlc.hoverlabel.font", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="ohlc.hoverlabel.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="ohlc.hoverlabel.font", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="ohlc.hoverlabel.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/ohlc/stream/0000755000175000017500000000000013573746614022204 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/ohlc/stream/__init__.py0000644000175000017500000000205613573721541024310 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TokenValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="token", parent_name="ohlc.stream", **kwargs): super(TokenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "info"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class MaxpointsValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="maxpoints", parent_name="ohlc.stream", **kwargs): super(MaxpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 10000), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/ohlc/__init__.py0000644000175000017500000005242513573721541023022 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YAxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="yaxis", parent_name="ohlc", **kwargs): super(YAxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "y"), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="xsrc", parent_name="ohlc", **kwargs): super(XsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XcalendarValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="xcalendar", parent_name="ohlc", **kwargs): super(XcalendarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "gregorian", "chinese", "coptic", "discworld", "ethiopian", "hebrew", "islamic", "julian", "mayan", "nanakshahi", "nepali", "persian", "jalali", "taiwan", "thai", "ummalqura", ], ), **kwargs ) import _plotly_utils.basevalidators class XAxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="xaxis", parent_name="ohlc", **kwargs): super(XAxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "x"), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="x", parent_name="ohlc", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="visible", parent_name="ohlc", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "legendonly"]), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="ohlc", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UidValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="uid", parent_name="ohlc", **kwargs): super(UidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="tickwidth", parent_name="ohlc", **kwargs): super(TickwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 0.5), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="textsrc", parent_name="ohlc", **kwargs): super(TextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="text", parent_name="ohlc", **kwargs): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class StreamValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="stream", parent_name="ohlc", **kwargs): super(StreamValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Stream"), data_docs=kwargs.pop( "data_docs", """ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """, ), **kwargs ) import _plotly_utils.basevalidators class ShowlegendValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showlegend", parent_name="ohlc", **kwargs): super(ShowlegendValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SelectedpointsValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="selectedpoints", parent_name="ohlc", **kwargs): super(SelectedpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class OpensrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="opensrc", parent_name="ohlc", **kwargs): super(OpensrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class OpenValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="open", parent_name="ohlc", **kwargs): super(OpenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="ohlc", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="ohlc", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="metasrc", parent_name="ohlc", **kwargs): super(MetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetaValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="meta", parent_name="ohlc", **kwargs): super(MetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LowsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="lowsrc", parent_name="ohlc", **kwargs): super(LowsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LowValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="low", parent_name="ohlc", **kwargs): super(LowValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="line", parent_name="ohlc", **kwargs): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). Note that this style setting can also be set per direction via `increasing.line.dash` and `decreasing.line.dash`. width [object Object] Note that this style setting can also be set per direction via `increasing.line.width` and `decreasing.line.width`. """, ), **kwargs ) import _plotly_utils.basevalidators class LegendgroupValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="legendgroup", parent_name="ohlc", **kwargs): super(LegendgroupValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IncreasingValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="increasing", parent_name="ohlc", **kwargs): super(IncreasingValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Increasing"), data_docs=kwargs.pop( "data_docs", """ line plotly.graph_objects.ohlc.increasing.Line instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class IdssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="idssrc", parent_name="ohlc", **kwargs): super(IdssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ids", parent_name="ohlc", **kwargs): super(IdsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class HovertextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hovertextsrc", parent_name="ohlc", **kwargs): super(HovertextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertext", parent_name="ohlc", **kwargs): super(HovertextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverlabelValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="hoverlabel", parent_name="ohlc", **kwargs): super(HoverlabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Hoverlabel"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . split Show hover information (open, close, high, low) in separate labels. """, ), **kwargs ) import _plotly_utils.basevalidators class HoverinfosrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hoverinfosrc", parent_name="ohlc", **kwargs): super(HoverinfosrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverinfoValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="hoverinfo", parent_name="ohlc", **kwargs): super(HoverinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), extras=kwargs.pop("extras", ["all", "none", "skip"]), flags=kwargs.pop("flags", ["x", "y", "z", "text", "name"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HighsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="highsrc", parent_name="ohlc", **kwargs): super(HighsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HighValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="high", parent_name="ohlc", **kwargs): super(HighValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class DecreasingValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="decreasing", parent_name="ohlc", **kwargs): super(DecreasingValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Decreasing"), data_docs=kwargs.pop( "data_docs", """ line plotly.graph_objects.ohlc.decreasing.Line instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class CustomdatasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="customdatasrc", parent_name="ohlc", **kwargs): super(CustomdatasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdataValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="customdata", parent_name="ohlc", **kwargs): super(CustomdataValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class ClosesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="closesrc", parent_name="ohlc", **kwargs): super(ClosesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CloseValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="close", parent_name="ohlc", **kwargs): super(CloseValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/ohlc/line/0000755000175000017500000000000013573746614021640 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/ohlc/line/__init__.py0000644000175000017500000000203013573721541023734 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="ohlc.line", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class DashValidator(_plotly_utils.basevalidators.DashValidator): def __init__(self, plotly_name="dash", parent_name="ohlc.line", **kwargs): super(DashValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", ["solid", "dot", "dash", "longdash", "dashdot", "longdashdot"] ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/ohlc/decreasing/0000755000175000017500000000000013573746614023015 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/ohlc/decreasing/__init__.py0000644000175000017500000000156413573721541025124 0ustar noahfxnoahfximport _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="line", parent_name="ohlc.decreasing", **kwargs): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ color Sets the line color. dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). width Sets the line width (in px). """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/ohlc/decreasing/line/0000755000175000017500000000000013573746614023744 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/ohlc/decreasing/line/__init__.py0000644000175000017500000000303313573721541026044 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="width", parent_name="ohlc.decreasing.line", **kwargs ): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class DashValidator(_plotly_utils.basevalidators.DashValidator): def __init__( self, plotly_name="dash", parent_name="ohlc.decreasing.line", **kwargs ): super(DashValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", ["solid", "dot", "dash", "longdash", "dashdot", "longdashdot"] ), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="ohlc.decreasing.line", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattermapbox/0000755000175000017500000000000013573746614022640 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattermapbox/unselected/0000755000175000017500000000000013573746614024773 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattermapbox/unselected/marker/0000755000175000017500000000000013573746614026254 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattermapbox/unselected/marker/__init__.py0000644000175000017500000000311613573721542030357 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scattermapbox.unselected.marker", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="opacity", parent_name="scattermapbox.unselected.marker", **kwargs ): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scattermapbox.unselected.marker", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattermapbox/unselected/__init__.py0000644000175000017500000000165313573721542027102 0ustar noahfxnoahfximport _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="marker", parent_name="scattermapbox.unselected", **kwargs ): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. size Sets the marker size of unselected points, applied only when a selection exists. """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattermapbox/textfont/0000755000175000017500000000000013573746614024513 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattermapbox/textfont/__init__.py0000644000175000017500000000277613573721542026631 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scattermapbox.textfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="scattermapbox.textfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scattermapbox.textfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattermapbox/hoverlabel/0000755000175000017500000000000013573746614024763 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattermapbox/hoverlabel/__init__.py0000644000175000017500000001363513573721542027075 0ustar noahfxnoahfximport _plotly_utils.basevalidators class NamelengthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="namelengthsrc", parent_name="scattermapbox.hoverlabel", **kwargs ): super(NamelengthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NamelengthValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="namelength", parent_name="scattermapbox.hoverlabel", **kwargs ): super(NamelengthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", -1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="scattermapbox.hoverlabel", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class BordercolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bordercolorsrc", parent_name="scattermapbox.hoverlabel", **kwargs ): super(BordercolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="scattermapbox.hoverlabel", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bgcolorsrc", parent_name="scattermapbox.hoverlabel", **kwargs ): super(BgcolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="scattermapbox.hoverlabel", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AlignsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="alignsrc", parent_name="scattermapbox.hoverlabel", **kwargs ): super(AlignsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="align", parent_name="scattermapbox.hoverlabel", **kwargs ): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "right", "auto"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattermapbox/hoverlabel/font/0000755000175000017500000000000013573746614025731 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattermapbox/hoverlabel/font/__init__.py0000644000175000017500000000625113573721542030037 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="scattermapbox.hoverlabel.font", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scattermapbox.hoverlabel.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="scattermapbox.hoverlabel.font", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="scattermapbox.hoverlabel.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="scattermapbox.hoverlabel.font", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scattermapbox.hoverlabel.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattermapbox/marker/0000755000175000017500000000000013573746614024121 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattermapbox/marker/colorbar/0000755000175000017500000000000013573746614025724 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattermapbox/marker/colorbar/tickformatstop/0000755000175000017500000000000013573746614030775 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattermapbox/marker/colorbar/tickformatstop/__init__.py0000644000175000017500000000543213573721542033103 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="value", parent_name="scattermapbox.marker.colorbar.tickformatstop", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="scattermapbox.marker.colorbar.tickformatstop", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="scattermapbox.marker.colorbar.tickformatstop", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EnabledValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="enabled", parent_name="scattermapbox.marker.colorbar.tickformatstop", **kwargs ): super(EnabledValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DtickrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="dtickrange", parent_name="scattermapbox.marker.colorbar.tickformatstop", **kwargs ): super(DtickrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "calc"}, {"valType": "any", "editType": "calc"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattermapbox/marker/colorbar/title/0000755000175000017500000000000013573746614027045 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattermapbox/marker/colorbar/title/__init__.py0000644000175000017500000000506213573721542031152 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="text", parent_name="scattermapbox.marker.colorbar.title", **kwargs ): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SideValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="side", parent_name="scattermapbox.marker.colorbar.title", **kwargs ): super(SideValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["right", "top", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="scattermapbox.marker.colorbar.title", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattermapbox/marker/colorbar/title/font/0000755000175000017500000000000013573746614030013 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattermapbox/marker/colorbar/title/font/__init__.py0000644000175000017500000000317413573721542032122 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scattermapbox.marker.colorbar.title.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="scattermapbox.marker.colorbar.title.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scattermapbox.marker.colorbar.title.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattermapbox/marker/colorbar/__init__.py0000644000175000017500000006237713573721543030046 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ypad", parent_name="scattermapbox.marker.colorbar", **kwargs ): super(YpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class YanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="yanchor", parent_name="scattermapbox.marker.colorbar", **kwargs ): super(YanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["top", "middle", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="y", parent_name="scattermapbox.marker.colorbar", **kwargs ): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="xpad", parent_name="scattermapbox.marker.colorbar", **kwargs ): super(XpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="xanchor", parent_name="scattermapbox.marker.colorbar", **kwargs ): super(XanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "center", "right"]), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="x", parent_name="scattermapbox.marker.colorbar", **kwargs ): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TitleValidator(_plotly_utils.basevalidators.TitleValidator): def __init__( self, plotly_name="title", parent_name="scattermapbox.marker.colorbar", **kwargs ): super(TitleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Title"), data_docs=kwargs.pop( "data_docs", """ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """, ), **kwargs ) import _plotly_utils.basevalidators class TickwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="tickwidth", parent_name="scattermapbox.marker.colorbar", **kwargs ): super(TickwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickvalssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="tickvalssrc", parent_name="scattermapbox.marker.colorbar", **kwargs ): super(TickvalssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickvalsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="tickvals", parent_name="scattermapbox.marker.colorbar", **kwargs ): super(TickvalsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="ticktextsrc", parent_name="scattermapbox.marker.colorbar", **kwargs ): super(TicktextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicktextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="ticktext", parent_name="scattermapbox.marker.colorbar", **kwargs ): super(TicktextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="ticksuffix", parent_name="scattermapbox.marker.colorbar", **kwargs ): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TicksValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="ticks", parent_name="scattermapbox.marker.colorbar", **kwargs ): super(TicksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["outside", "inside", ""]), **kwargs ) import _plotly_utils.basevalidators class TickprefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickprefix", parent_name="scattermapbox.marker.colorbar", **kwargs ): super(TickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="tickmode", parent_name="scattermapbox.marker.colorbar", **kwargs ): super(TickmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "linear", "array"]), **kwargs ) import _plotly_utils.basevalidators class TicklenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ticklen", parent_name="scattermapbox.marker.colorbar", **kwargs ): super(TicklenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickformatstopValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickformatstopdefaults", parent_name="scattermapbox.marker.colorbar", **kwargs ): super(TickformatstopValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatstopsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="tickformatstops", parent_name="scattermapbox.marker.colorbar", **kwargs ): super(TickformatstopsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickformat", parent_name="scattermapbox.marker.colorbar", **kwargs ): super(TickformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickfont", parent_name="scattermapbox.marker.colorbar", **kwargs ): super(TickfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class TickcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="tickcolor", parent_name="scattermapbox.marker.colorbar", **kwargs ): super(TickcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__( self, plotly_name="tickangle", parent_name="scattermapbox.marker.colorbar", **kwargs ): super(TickangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="tick0", parent_name="scattermapbox.marker.colorbar", **kwargs ): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ThicknessmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="thicknessmode", parent_name="scattermapbox.marker.colorbar", **kwargs ): super(ThicknessmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="thickness", parent_name="scattermapbox.marker.colorbar", **kwargs ): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowticksuffixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showticksuffix", parent_name="scattermapbox.marker.colorbar", **kwargs ): super(ShowticksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowtickprefixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showtickprefix", parent_name="scattermapbox.marker.colorbar", **kwargs ): super(ShowtickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowticklabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showticklabels", parent_name="scattermapbox.marker.colorbar", **kwargs ): super(ShowticklabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowexponentValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showexponent", parent_name="scattermapbox.marker.colorbar", **kwargs ): super(ShowexponentValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class SeparatethousandsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="separatethousands", parent_name="scattermapbox.marker.colorbar", **kwargs ): super(SeparatethousandsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="outlinewidth", parent_name="scattermapbox.marker.colorbar", **kwargs ): super(OutlinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="outlinecolor", parent_name="scattermapbox.marker.colorbar", **kwargs ): super(OutlinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NticksValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="nticks", parent_name="scattermapbox.marker.colorbar", **kwargs ): super(NticksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LenmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="lenmode", parent_name="scattermapbox.marker.colorbar", **kwargs ): super(LenmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class LenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="len", parent_name="scattermapbox.marker.colorbar", **kwargs ): super(LenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ExponentformatValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="exponentformat", parent_name="scattermapbox.marker.colorbar", **kwargs ): super(ExponentformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "e", "E", "power", "SI", "B"]), **kwargs ) import _plotly_utils.basevalidators class DtickValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="dtick", parent_name="scattermapbox.marker.colorbar", **kwargs ): super(DtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BorderwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="borderwidth", parent_name="scattermapbox.marker.colorbar", **kwargs ): super(BorderwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="scattermapbox.marker.colorbar", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="scattermapbox.marker.colorbar", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattermapbox/marker/colorbar/tickfont/0000755000175000017500000000000013573746614027545 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattermapbox/marker/colorbar/tickfont/__init__.py0000644000175000017500000000316613573721542031655 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scattermapbox.marker.colorbar.tickfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="scattermapbox.marker.colorbar.tickfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scattermapbox.marker.colorbar.tickfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattermapbox/marker/__init__.py0000644000175000017500000005156213573721543026235 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SymbolsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="symbolsrc", parent_name="scattermapbox.marker", **kwargs ): super(SymbolsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SymbolValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="symbol", parent_name="scattermapbox.marker", **kwargs ): super(SymbolValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="scattermapbox.marker", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizerefValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="sizeref", parent_name="scattermapbox.marker", **kwargs ): super(SizerefValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SizemodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="sizemode", parent_name="scattermapbox.marker", **kwargs ): super(SizemodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["diameter", "area"]), **kwargs ) import _plotly_utils.basevalidators class SizeminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="sizemin", parent_name="scattermapbox.marker", **kwargs ): super(SizeminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scattermapbox.marker", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showscale", parent_name="scattermapbox.marker", **kwargs ): super(ShowscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ReversescaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="reversescale", parent_name="scattermapbox.marker", **kwargs ): super(ReversescaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacitysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="opacitysrc", parent_name="scattermapbox.marker", **kwargs ): super(OpacitysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="opacity", parent_name="scattermapbox.marker", **kwargs ): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="scattermapbox.marker", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__( self, plotly_name="colorscale", parent_name="scattermapbox.marker", **kwargs ): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"autocolorscale": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorBarValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="colorbar", parent_name="scattermapbox.marker", **kwargs ): super(ColorBarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "ColorBar"), data_docs=kwargs.pop( "data_docs", """ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.scattermapbox.m arker.colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.scattermapbox.marker.colorbar.tickformatstopd efaults), sets the default property values to use for elements of scattermapbox.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.scattermapbox.marker.color bar.Title instance or dict with compatible properties titlefont Deprecated: Please use scattermapbox.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use scattermapbox.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """, ), **kwargs ) import _plotly_utils.basevalidators class ColoraxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__( self, plotly_name="coloraxis", parent_name="scattermapbox.marker", **kwargs ): super(ColoraxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", None), edit_type=kwargs.pop("edit_type", "calc"), regex=kwargs.pop("regex", "/^coloraxis([2-9]|[1-9][0-9]+)?$/"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scattermapbox.marker", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), colorscale_path=kwargs.pop( "colorscale_path", "scattermapbox.marker.colorscale" ), **kwargs ) import _plotly_utils.basevalidators class CminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="cmin", parent_name="scattermapbox.marker", **kwargs ): super(CminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmidValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="cmid", parent_name="scattermapbox.marker", **kwargs ): super(CmidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="cmax", parent_name="scattermapbox.marker", **kwargs ): super(CmaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CautoValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="cauto", parent_name="scattermapbox.marker", **kwargs ): super(CautoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AutocolorscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="autocolorscale", parent_name="scattermapbox.marker", **kwargs ): super(AutocolorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattermapbox/stream/0000755000175000017500000000000013573746614024133 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattermapbox/stream/__init__.py0000644000175000017500000000213413573721542026235 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TokenValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="token", parent_name="scattermapbox.stream", **kwargs ): super(TokenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "info"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class MaxpointsValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="maxpoints", parent_name="scattermapbox.stream", **kwargs ): super(MaxpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 10000), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattermapbox/__init__.py0000644000175000017500000007267213573721543024761 0ustar noahfxnoahfximport _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="visible", parent_name="scattermapbox", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "legendonly"]), **kwargs ) import _plotly_utils.basevalidators class UnselectedValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="unselected", parent_name="scattermapbox", **kwargs): super(UnselectedValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Unselected"), data_docs=kwargs.pop( "data_docs", """ marker plotly.graph_objects.scattermapbox.unselected.M arker instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="scattermapbox", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UidValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="uid", parent_name="scattermapbox", **kwargs): super(UidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TexttemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="texttemplatesrc", parent_name="scattermapbox", **kwargs ): super(TexttemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TexttemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="texttemplate", parent_name="scattermapbox", **kwargs ): super(TexttemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="textsrc", parent_name="scattermapbox", **kwargs): super(TextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextpositionValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="textposition", parent_name="scattermapbox", **kwargs ): super(TextpositionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", False), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", [ "top left", "top center", "top right", "middle left", "middle center", "middle right", "bottom left", "bottom center", "bottom right", ], ), **kwargs ) import _plotly_utils.basevalidators class TextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="textfont", parent_name="scattermapbox", **kwargs): super(TextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Textfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="text", parent_name="scattermapbox", **kwargs): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SubplotValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="subplot", parent_name="scattermapbox", **kwargs): super(SubplotValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "mapbox"), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class StreamValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="stream", parent_name="scattermapbox", **kwargs): super(StreamValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Stream"), data_docs=kwargs.pop( "data_docs", """ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """, ), **kwargs ) import _plotly_utils.basevalidators class ShowlegendValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showlegend", parent_name="scattermapbox", **kwargs): super(ShowlegendValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SelectedpointsValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="selectedpoints", parent_name="scattermapbox", **kwargs ): super(SelectedpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SelectedValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="selected", parent_name="scattermapbox", **kwargs): super(SelectedValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Selected"), data_docs=kwargs.pop( "data_docs", """ marker plotly.graph_objects.scattermapbox.selected.Mar ker instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="scattermapbox", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="scattermapbox", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ModeValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="mode", parent_name="scattermapbox", **kwargs): super(ModeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), extras=kwargs.pop("extras", ["none"]), flags=kwargs.pop("flags", ["lines", "markers", "text"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="metasrc", parent_name="scattermapbox", **kwargs): super(MetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetaValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="meta", parent_name="scattermapbox", **kwargs): super(MetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="marker", parent_name="scattermapbox", **kwargs): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.scattermapbox.marker.Color Bar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . opacity Sets the marker opacity. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. size Sets the marker size (in px). sizemin Has an effect only if `marker.size` is set to a numerical array. Sets the minimum size (in px) of the rendered marker points. sizemode Has an effect only if `marker.size` is set to a numerical array. Sets the rule for which the data in `size` is converted to pixels. sizeref Has an effect only if `marker.size` is set to a numerical array. Sets the scale factor used to determine the rendered size of marker points. Use with `sizemin` and `sizemode`. sizesrc Sets the source reference on plot.ly for size . symbol Sets the marker symbol. Full list: https://www.mapbox.com/maki-icons/ Note that the array `marker.color` and `marker.size` are only available for "circle" symbols. symbolsrc Sets the source reference on plot.ly for symbol . """, ), **kwargs ) import _plotly_utils.basevalidators class LonsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="lonsrc", parent_name="scattermapbox", **kwargs): super(LonsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LonValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="lon", parent_name="scattermapbox", **kwargs): super(LonValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="line", parent_name="scattermapbox", **kwargs): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ color Sets the line color. width Sets the line width (in px). """, ), **kwargs ) import _plotly_utils.basevalidators class LegendgroupValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="legendgroup", parent_name="scattermapbox", **kwargs ): super(LegendgroupValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LatsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="latsrc", parent_name="scattermapbox", **kwargs): super(LatsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LatValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="lat", parent_name="scattermapbox", **kwargs): super(LatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class IdssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="idssrc", parent_name="scattermapbox", **kwargs): super(IdssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ids", parent_name="scattermapbox", **kwargs): super(IdsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class HovertextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="hovertextsrc", parent_name="scattermapbox", **kwargs ): super(HovertextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertext", parent_name="scattermapbox", **kwargs): super(HovertextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="hovertemplatesrc", parent_name="scattermapbox", **kwargs ): super(HovertemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="hovertemplate", parent_name="scattermapbox", **kwargs ): super(HovertemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverlabelValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="hoverlabel", parent_name="scattermapbox", **kwargs): super(HoverlabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Hoverlabel"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """, ), **kwargs ) import _plotly_utils.basevalidators class HoverinfosrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="hoverinfosrc", parent_name="scattermapbox", **kwargs ): super(HoverinfosrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverinfoValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="hoverinfo", parent_name="scattermapbox", **kwargs): super(HoverinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), extras=kwargs.pop("extras", ["all", "none", "skip"]), flags=kwargs.pop("flags", ["lon", "lat", "text", "name"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FillcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="fillcolor", parent_name="scattermapbox", **kwargs): super(FillcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FillValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="fill", parent_name="scattermapbox", **kwargs): super(FillValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "toself"]), **kwargs ) import _plotly_utils.basevalidators class CustomdatasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="customdatasrc", parent_name="scattermapbox", **kwargs ): super(CustomdatasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdataValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="customdata", parent_name="scattermapbox", **kwargs): super(CustomdataValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class ConnectgapsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="connectgaps", parent_name="scattermapbox", **kwargs ): super(ConnectgapsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BelowValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="below", parent_name="scattermapbox", **kwargs): super(BelowValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattermapbox/line/0000755000175000017500000000000013573746614023567 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattermapbox/line/__init__.py0000644000175000017500000000164513573721542025677 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="scattermapbox.line", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="scattermapbox.line", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattermapbox/selected/0000755000175000017500000000000013573746614024430 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattermapbox/selected/marker/0000755000175000017500000000000013573746614025711 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattermapbox/selected/marker/__init__.py0000644000175000017500000000303013573721542030007 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scattermapbox.selected.marker", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="opacity", parent_name="scattermapbox.selected.marker", **kwargs ): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scattermapbox.selected.marker", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattermapbox/selected/__init__.py0000644000175000017500000000140113573721542026526 0ustar noahfxnoahfximport _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="marker", parent_name="scattermapbox.selected", **kwargs ): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. size Sets the marker size of selected points. """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/sunburst/0000755000175000017500000000000013573746614021651 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/sunburst/textfont/0000755000175000017500000000000013573746614023524 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/sunburst/textfont/__init__.py0000644000175000017500000000572713573721543025642 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="sunburst.textfont", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="size", parent_name="sunburst.textfont", **kwargs): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="sunburst.textfont", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="family", parent_name="sunburst.textfont", **kwargs): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="sunburst.textfont", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="sunburst.textfont", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/sunburst/hoverlabel/0000755000175000017500000000000013573746614023774 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/sunburst/hoverlabel/__init__.py0000644000175000017500000001343213573721543026102 0ustar noahfxnoahfximport _plotly_utils.basevalidators class NamelengthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="namelengthsrc", parent_name="sunburst.hoverlabel", **kwargs ): super(NamelengthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NamelengthValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="namelength", parent_name="sunburst.hoverlabel", **kwargs ): super(NamelengthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", -1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="font", parent_name="sunburst.hoverlabel", **kwargs): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class BordercolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bordercolorsrc", parent_name="sunburst.hoverlabel", **kwargs ): super(BordercolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="sunburst.hoverlabel", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bgcolorsrc", parent_name="sunburst.hoverlabel", **kwargs ): super(BgcolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="sunburst.hoverlabel", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AlignsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="alignsrc", parent_name="sunburst.hoverlabel", **kwargs ): super(AlignsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="align", parent_name="sunburst.hoverlabel", **kwargs ): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "right", "auto"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/sunburst/hoverlabel/font/0000755000175000017500000000000013573746614024742 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/sunburst/hoverlabel/font/__init__.py0000644000175000017500000000605313573721543027051 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="sunburst.hoverlabel.font", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="sunburst.hoverlabel.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="sunburst.hoverlabel.font", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="sunburst.hoverlabel.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="sunburst.hoverlabel.font", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="sunburst.hoverlabel.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/sunburst/leaf/0000755000175000017500000000000013573746614022560 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/sunburst/leaf/__init__.py0000644000175000017500000000101513573721543024660 0ustar noahfxnoahfximport _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="sunburst.leaf", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/sunburst/outsidetextfont/0000755000175000017500000000000013573746614025121 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/sunburst/outsidetextfont/__init__.py0000644000175000017500000000605313573721543027230 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="sunburst.outsidetextfont", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="sunburst.outsidetextfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="sunburst.outsidetextfont", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="sunburst.outsidetextfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="sunburst.outsidetextfont", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="sunburst.outsidetextfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/sunburst/marker/0000755000175000017500000000000013573746614023132 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/sunburst/marker/colorbar/0000755000175000017500000000000013573746614024735 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/sunburst/marker/colorbar/tickformatstop/0000755000175000017500000000000013573746614030006 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/sunburst/marker/colorbar/tickformatstop/__init__.py0000644000175000017500000000544413573721543032120 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="value", parent_name="sunburst.marker.colorbar.tickformatstop", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="sunburst.marker.colorbar.tickformatstop", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="sunburst.marker.colorbar.tickformatstop", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EnabledValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="enabled", parent_name="sunburst.marker.colorbar.tickformatstop", **kwargs ): super(EnabledValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DtickrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="dtickrange", parent_name="sunburst.marker.colorbar.tickformatstop", **kwargs ): super(DtickrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "colorbars"}, {"valType": "any", "editType": "colorbars"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/sunburst/marker/colorbar/title/0000755000175000017500000000000013573746614026056 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/sunburst/marker/colorbar/title/__init__.py0000644000175000017500000000474513573721543030173 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="text", parent_name="sunburst.marker.colorbar.title", **kwargs ): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SideValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="side", parent_name="sunburst.marker.colorbar.title", **kwargs ): super(SideValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["right", "top", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="sunburst.marker.colorbar.title", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/sunburst/marker/colorbar/title/font/0000755000175000017500000000000013573746614027024 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/sunburst/marker/colorbar/title/font/__init__.py0000644000175000017500000000317413573721543031134 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="sunburst.marker.colorbar.title.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="sunburst.marker.colorbar.title.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="sunburst.marker.colorbar.title.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/sunburst/marker/colorbar/__init__.py0000644000175000017500000006151113573721544027045 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ypad", parent_name="sunburst.marker.colorbar", **kwargs ): super(YpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class YanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="yanchor", parent_name="sunburst.marker.colorbar", **kwargs ): super(YanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["top", "middle", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="y", parent_name="sunburst.marker.colorbar", **kwargs ): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="xpad", parent_name="sunburst.marker.colorbar", **kwargs ): super(XpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="xanchor", parent_name="sunburst.marker.colorbar", **kwargs ): super(XanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "center", "right"]), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="x", parent_name="sunburst.marker.colorbar", **kwargs ): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TitleValidator(_plotly_utils.basevalidators.TitleValidator): def __init__( self, plotly_name="title", parent_name="sunburst.marker.colorbar", **kwargs ): super(TitleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Title"), data_docs=kwargs.pop( "data_docs", """ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """, ), **kwargs ) import _plotly_utils.basevalidators class TickwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="tickwidth", parent_name="sunburst.marker.colorbar", **kwargs ): super(TickwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickvalssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="tickvalssrc", parent_name="sunburst.marker.colorbar", **kwargs ): super(TickvalssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickvalsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="tickvals", parent_name="sunburst.marker.colorbar", **kwargs ): super(TickvalsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="ticktextsrc", parent_name="sunburst.marker.colorbar", **kwargs ): super(TicktextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicktextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="ticktext", parent_name="sunburst.marker.colorbar", **kwargs ): super(TicktextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="ticksuffix", parent_name="sunburst.marker.colorbar", **kwargs ): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TicksValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="ticks", parent_name="sunburst.marker.colorbar", **kwargs ): super(TicksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["outside", "inside", ""]), **kwargs ) import _plotly_utils.basevalidators class TickprefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickprefix", parent_name="sunburst.marker.colorbar", **kwargs ): super(TickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="tickmode", parent_name="sunburst.marker.colorbar", **kwargs ): super(TickmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "linear", "array"]), **kwargs ) import _plotly_utils.basevalidators class TicklenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ticklen", parent_name="sunburst.marker.colorbar", **kwargs ): super(TicklenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickformatstopValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickformatstopdefaults", parent_name="sunburst.marker.colorbar", **kwargs ): super(TickformatstopValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatstopsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="tickformatstops", parent_name="sunburst.marker.colorbar", **kwargs ): super(TickformatstopsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickformat", parent_name="sunburst.marker.colorbar", **kwargs ): super(TickformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickfont", parent_name="sunburst.marker.colorbar", **kwargs ): super(TickfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class TickcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="tickcolor", parent_name="sunburst.marker.colorbar", **kwargs ): super(TickcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__( self, plotly_name="tickangle", parent_name="sunburst.marker.colorbar", **kwargs ): super(TickangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="tick0", parent_name="sunburst.marker.colorbar", **kwargs ): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ThicknessmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="thicknessmode", parent_name="sunburst.marker.colorbar", **kwargs ): super(ThicknessmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="thickness", parent_name="sunburst.marker.colorbar", **kwargs ): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowticksuffixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showticksuffix", parent_name="sunburst.marker.colorbar", **kwargs ): super(ShowticksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowtickprefixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showtickprefix", parent_name="sunburst.marker.colorbar", **kwargs ): super(ShowtickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowticklabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showticklabels", parent_name="sunburst.marker.colorbar", **kwargs ): super(ShowticklabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowexponentValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showexponent", parent_name="sunburst.marker.colorbar", **kwargs ): super(ShowexponentValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class SeparatethousandsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="separatethousands", parent_name="sunburst.marker.colorbar", **kwargs ): super(SeparatethousandsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="outlinewidth", parent_name="sunburst.marker.colorbar", **kwargs ): super(OutlinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="outlinecolor", parent_name="sunburst.marker.colorbar", **kwargs ): super(OutlinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NticksValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="nticks", parent_name="sunburst.marker.colorbar", **kwargs ): super(NticksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LenmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="lenmode", parent_name="sunburst.marker.colorbar", **kwargs ): super(LenmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class LenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="len", parent_name="sunburst.marker.colorbar", **kwargs ): super(LenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ExponentformatValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="exponentformat", parent_name="sunburst.marker.colorbar", **kwargs ): super(ExponentformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "e", "E", "power", "SI", "B"]), **kwargs ) import _plotly_utils.basevalidators class DtickValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="dtick", parent_name="sunburst.marker.colorbar", **kwargs ): super(DtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BorderwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="borderwidth", parent_name="sunburst.marker.colorbar", **kwargs ): super(BorderwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="sunburst.marker.colorbar", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="sunburst.marker.colorbar", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/sunburst/marker/colorbar/tickfont/0000755000175000017500000000000013573746614026556 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/sunburst/marker/colorbar/tickfont/__init__.py0000644000175000017500000000316613573721543030667 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="sunburst.marker.colorbar.tickfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="sunburst.marker.colorbar.tickfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="sunburst.marker.colorbar.tickfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/sunburst/marker/__init__.py0000644000175000017500000004174713573721543025252 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ShowscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showscale", parent_name="sunburst.marker", **kwargs ): super(ShowscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ReversescaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="reversescale", parent_name="sunburst.marker", **kwargs ): super(ReversescaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="line", parent_name="sunburst.marker", **kwargs): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ color Sets the color of the line enclosing each sector. Defaults to the `paper_bgcolor` value. colorsrc Sets the source reference on plot.ly for color . width Sets the width (in px) of the line enclosing each sector. widthsrc Sets the source reference on plot.ly for width . """, ), **kwargs ) import _plotly_utils.basevalidators class ColorssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorssrc", parent_name="sunburst.marker", **kwargs ): super(ColorssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__( self, plotly_name="colorscale", parent_name="sunburst.marker", **kwargs ): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"autocolorscale": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="colors", parent_name="sunburst.marker", **kwargs): super(ColorsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class ColorBarValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="colorbar", parent_name="sunburst.marker", **kwargs): super(ColorBarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "ColorBar"), data_docs=kwargs.pop( "data_docs", """ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.sunburst.marker .colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.sunburst.marker.colorbar.tickformatstopdefaul ts), sets the default property values to use for elements of sunburst.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.sunburst.marker.colorbar.T itle instance or dict with compatible properties titlefont Deprecated: Please use sunburst.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use sunburst.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """, ), **kwargs ) import _plotly_utils.basevalidators class ColoraxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__( self, plotly_name="coloraxis", parent_name="sunburst.marker", **kwargs ): super(ColoraxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", None), edit_type=kwargs.pop("edit_type", "calc"), regex=kwargs.pop("regex", "/^coloraxis([2-9]|[1-9][0-9]+)?$/"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmin", parent_name="sunburst.marker", **kwargs): super(CminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmidValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmid", parent_name="sunburst.marker", **kwargs): super(CmidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmax", parent_name="sunburst.marker", **kwargs): super(CmaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CautoValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="cauto", parent_name="sunburst.marker", **kwargs): super(CautoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AutocolorscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="autocolorscale", parent_name="sunburst.marker", **kwargs ): super(AutocolorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/sunburst/marker/line/0000755000175000017500000000000013573746614024061 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/sunburst/marker/line/__init__.py0000644000175000017500000000373113573721543026170 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="widthsrc", parent_name="sunburst.marker.line", **kwargs ): super(WidthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="width", parent_name="sunburst.marker.line", **kwargs ): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="sunburst.marker.line", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="sunburst.marker.line", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/sunburst/stream/0000755000175000017500000000000013573746614023144 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/sunburst/stream/__init__.py0000644000175000017500000000210413573721543025244 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TokenValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="token", parent_name="sunburst.stream", **kwargs): super(TokenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "info"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class MaxpointsValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="maxpoints", parent_name="sunburst.stream", **kwargs ): super(MaxpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 10000), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/sunburst/__init__.py0000644000175000017500000007421313573721544023764 0ustar noahfxnoahfximport _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="visible", parent_name="sunburst", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "legendonly"]), **kwargs ) import _plotly_utils.basevalidators class ValuessrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="valuessrc", parent_name="sunburst", **kwargs): super(ValuessrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ValuesValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="values", parent_name="sunburst", **kwargs): super(ValuesValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="sunburst", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UidValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="uid", parent_name="sunburst", **kwargs): super(UidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, anim=kwargs.pop("anim", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TexttemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="texttemplatesrc", parent_name="sunburst", **kwargs): super(TexttemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TexttemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="texttemplate", parent_name="sunburst", **kwargs): super(TexttemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="textsrc", parent_name="sunburst", **kwargs): super(TextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextinfoValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="textinfo", parent_name="sunburst", **kwargs): super(TextinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), extras=kwargs.pop("extras", ["none"]), flags=kwargs.pop( "flags", [ "label", "text", "value", "current path", "percent root", "percent entry", "percent parent", ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="textfont", parent_name="sunburst", **kwargs): super(TextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Textfont"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="text", parent_name="sunburst", **kwargs): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class StreamValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="stream", parent_name="sunburst", **kwargs): super(StreamValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Stream"), data_docs=kwargs.pop( "data_docs", """ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """, ), **kwargs ) import _plotly_utils.basevalidators class ParentssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="parentssrc", parent_name="sunburst", **kwargs): super(ParentssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ParentsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="parents", parent_name="sunburst", **kwargs): super(ParentsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class OutsidetextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="outsidetextfont", parent_name="sunburst", **kwargs): super(OutsidetextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Outsidetextfont"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="sunburst", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="sunburst", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="metasrc", parent_name="sunburst", **kwargs): super(MetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetaValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="meta", parent_name="sunburst", **kwargs): super(MetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MaxdepthValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="maxdepth", parent_name="sunburst", **kwargs): super(MaxdepthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="marker", parent_name="sunburst", **kwargs): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if colorsis set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here colors) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if colorsis set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if colorsis set to a numerical array. Value should have the same units as colors and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if colorsis set to a numerical array. Value should have the same units as colors. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if colorsis set to a numerical array. Value should have the same units as colors and if set, `marker.cmax` must be set as well. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.sunburst.marker.ColorBar instance or dict with compatible properties colors Sets the color of each sector of this trace. If not specified, the default trace color set is used to pick the sector colors. colorscale Sets the colorscale. Has an effect only if colorsis set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorssrc Sets the source reference on plot.ly for colors . line plotly.graph_objects.sunburst.marker.Line instance or dict with compatible properties reversescale Reverses the color mapping if true. Has an effect only if colorsis set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if colorsis set to a numerical array. """, ), **kwargs ) import _plotly_utils.basevalidators class LevelValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="level", parent_name="sunburst", **kwargs): super(LevelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, anim=kwargs.pop("anim", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LeafValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="leaf", parent_name="sunburst", **kwargs): super(LeafValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Leaf"), data_docs=kwargs.pop( "data_docs", """ opacity Sets the opacity of the leaves. With colorscale it is defaulted to 1; otherwise it is defaulted to 0.7 """, ), **kwargs ) import _plotly_utils.basevalidators class LabelssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="labelssrc", parent_name="sunburst", **kwargs): super(LabelssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LabelsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="labels", parent_name="sunburst", **kwargs): super(LabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class InsidetextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="insidetextfont", parent_name="sunburst", **kwargs): super(InsidetextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Insidetextfont"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class IdssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="idssrc", parent_name="sunburst", **kwargs): super(IdssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ids", parent_name="sunburst", **kwargs): super(IdsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, anim=kwargs.pop("anim", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class HovertextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hovertextsrc", parent_name="sunburst", **kwargs): super(HovertextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertext", parent_name="sunburst", **kwargs): super(HovertextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="hovertemplatesrc", parent_name="sunburst", **kwargs ): super(HovertemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertemplate", parent_name="sunburst", **kwargs): super(HovertemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverlabelValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="hoverlabel", parent_name="sunburst", **kwargs): super(HoverlabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Hoverlabel"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """, ), **kwargs ) import _plotly_utils.basevalidators class HoverinfosrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hoverinfosrc", parent_name="sunburst", **kwargs): super(HoverinfosrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverinfoValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="hoverinfo", parent_name="sunburst", **kwargs): super(HoverinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), extras=kwargs.pop("extras", ["all", "none", "skip"]), flags=kwargs.pop( "flags", [ "label", "text", "value", "name", "current path", "percent root", "percent entry", "percent parent", ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DomainValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="domain", parent_name="sunburst", **kwargs): super(DomainValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Domain"), data_docs=kwargs.pop( "data_docs", """ column If there is a layout grid, use the domain for this column in the grid for this sunburst trace . row If there is a layout grid, use the domain for this row in the grid for this sunburst trace . x Sets the horizontal domain of this sunburst trace (in plot fraction). y Sets the vertical domain of this sunburst trace (in plot fraction). """, ), **kwargs ) import _plotly_utils.basevalidators class CustomdatasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="customdatasrc", parent_name="sunburst", **kwargs): super(CustomdatasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdataValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="customdata", parent_name="sunburst", **kwargs): super(CustomdataValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class CountValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="count", parent_name="sunburst", **kwargs): super(CountValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), flags=kwargs.pop("flags", ["branches", "leaves"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BranchvaluesValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="branchvalues", parent_name="sunburst", **kwargs): super(BranchvaluesValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["remainder", "total"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/sunburst/insidetextfont/0000755000175000017500000000000013573746614024720 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/sunburst/insidetextfont/__init__.py0000644000175000017500000000604513573721543027030 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="sunburst.insidetextfont", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="sunburst.insidetextfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="sunburst.insidetextfont", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="sunburst.insidetextfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="sunburst.insidetextfont", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="sunburst.insidetextfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/sunburst/domain/0000755000175000017500000000000013573746614023120 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/sunburst/domain/__init__.py0000644000175000017500000000451513573721543025230 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="y", parent_name="sunburst.domain", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), items=kwargs.pop( "items", [ {"valType": "number", "min": 0, "max": 1, "editType": "calc"}, {"valType": "number", "min": 0, "max": 1, "editType": "calc"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="x", parent_name="sunburst.domain", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), items=kwargs.pop( "items", [ {"valType": "number", "min": 0, "max": 1, "editType": "calc"}, {"valType": "number", "min": 0, "max": 1, "editType": "calc"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class RowValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="row", parent_name="sunburst.domain", **kwargs): super(RowValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColumnValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="column", parent_name="sunburst.domain", **kwargs): super(ColumnValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/surface/0000755000175000017500000000000013573746614021414 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/surface/hoverlabel/0000755000175000017500000000000013573746614023537 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/surface/hoverlabel/__init__.py0000644000175000017500000001340313573721543025643 0ustar noahfxnoahfximport _plotly_utils.basevalidators class NamelengthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="namelengthsrc", parent_name="surface.hoverlabel", **kwargs ): super(NamelengthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NamelengthValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="namelength", parent_name="surface.hoverlabel", **kwargs ): super(NamelengthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", -1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="font", parent_name="surface.hoverlabel", **kwargs): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class BordercolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bordercolorsrc", parent_name="surface.hoverlabel", **kwargs ): super(BordercolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="surface.hoverlabel", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bgcolorsrc", parent_name="surface.hoverlabel", **kwargs ): super(BgcolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="surface.hoverlabel", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AlignsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="alignsrc", parent_name="surface.hoverlabel", **kwargs ): super(AlignsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="align", parent_name="surface.hoverlabel", **kwargs): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "right", "auto"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/surface/hoverlabel/font/0000755000175000017500000000000013573746614024505 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/surface/hoverlabel/font/__init__.py0000644000175000017500000000604513573721543026615 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="surface.hoverlabel.font", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="surface.hoverlabel.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="surface.hoverlabel.font", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="surface.hoverlabel.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="surface.hoverlabel.font", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="surface.hoverlabel.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/surface/colorbar/0000755000175000017500000000000013573746614023217 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/surface/colorbar/tickformatstop/0000755000175000017500000000000013573746614026270 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/surface/colorbar/tickformatstop/__init__.py0000644000175000017500000000533113573721543030375 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="value", parent_name="surface.colorbar.tickformatstop", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="surface.colorbar.tickformatstop", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="surface.colorbar.tickformatstop", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EnabledValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="enabled", parent_name="surface.colorbar.tickformatstop", **kwargs ): super(EnabledValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DtickrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="dtickrange", parent_name="surface.colorbar.tickformatstop", **kwargs ): super(DtickrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "calc"}, {"valType": "any", "editType": "calc"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/surface/colorbar/title/0000755000175000017500000000000013573746614024340 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/surface/colorbar/title/__init__.py0000644000175000017500000000470313573721543026447 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="text", parent_name="surface.colorbar.title", **kwargs ): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SideValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="side", parent_name="surface.colorbar.title", **kwargs ): super(SideValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["right", "top", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="surface.colorbar.title", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/surface/colorbar/title/font/0000755000175000017500000000000013573746614025306 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/surface/colorbar/title/font/__init__.py0000644000175000017500000000301513573721543027410 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="surface.colorbar.title.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="surface.colorbar.title.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="surface.colorbar.title.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/surface/colorbar/__init__.py0000644000175000017500000005746013573721544025337 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="ypad", parent_name="surface.colorbar", **kwargs): super(YpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class YanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="yanchor", parent_name="surface.colorbar", **kwargs): super(YanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["top", "middle", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="y", parent_name="surface.colorbar", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="xpad", parent_name="surface.colorbar", **kwargs): super(XpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="xanchor", parent_name="surface.colorbar", **kwargs): super(XanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "center", "right"]), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="x", parent_name="surface.colorbar", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TitleValidator(_plotly_utils.basevalidators.TitleValidator): def __init__(self, plotly_name="title", parent_name="surface.colorbar", **kwargs): super(TitleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Title"), data_docs=kwargs.pop( "data_docs", """ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """, ), **kwargs ) import _plotly_utils.basevalidators class TickwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="tickwidth", parent_name="surface.colorbar", **kwargs ): super(TickwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickvalssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="tickvalssrc", parent_name="surface.colorbar", **kwargs ): super(TickvalssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickvalsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="tickvals", parent_name="surface.colorbar", **kwargs ): super(TickvalsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="ticktextsrc", parent_name="surface.colorbar", **kwargs ): super(TicktextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicktextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="ticktext", parent_name="surface.colorbar", **kwargs ): super(TicktextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="ticksuffix", parent_name="surface.colorbar", **kwargs ): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TicksValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="ticks", parent_name="surface.colorbar", **kwargs): super(TicksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["outside", "inside", ""]), **kwargs ) import _plotly_utils.basevalidators class TickprefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickprefix", parent_name="surface.colorbar", **kwargs ): super(TickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="tickmode", parent_name="surface.colorbar", **kwargs ): super(TickmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "linear", "array"]), **kwargs ) import _plotly_utils.basevalidators class TicklenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="ticklen", parent_name="surface.colorbar", **kwargs): super(TicklenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickformatstopValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickformatstopdefaults", parent_name="surface.colorbar", **kwargs ): super(TickformatstopValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatstopsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="tickformatstops", parent_name="surface.colorbar", **kwargs ): super(TickformatstopsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickformat", parent_name="surface.colorbar", **kwargs ): super(TickformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickfont", parent_name="surface.colorbar", **kwargs ): super(TickfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class TickcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="tickcolor", parent_name="surface.colorbar", **kwargs ): super(TickcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__( self, plotly_name="tickangle", parent_name="surface.colorbar", **kwargs ): super(TickangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="tick0", parent_name="surface.colorbar", **kwargs): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ThicknessmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="thicknessmode", parent_name="surface.colorbar", **kwargs ): super(ThicknessmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="thickness", parent_name="surface.colorbar", **kwargs ): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowticksuffixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showticksuffix", parent_name="surface.colorbar", **kwargs ): super(ShowticksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowtickprefixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showtickprefix", parent_name="surface.colorbar", **kwargs ): super(ShowtickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowticklabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showticklabels", parent_name="surface.colorbar", **kwargs ): super(ShowticklabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowexponentValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showexponent", parent_name="surface.colorbar", **kwargs ): super(ShowexponentValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class SeparatethousandsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="separatethousands", parent_name="surface.colorbar", **kwargs ): super(SeparatethousandsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="outlinewidth", parent_name="surface.colorbar", **kwargs ): super(OutlinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="outlinecolor", parent_name="surface.colorbar", **kwargs ): super(OutlinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NticksValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="nticks", parent_name="surface.colorbar", **kwargs): super(NticksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LenmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="lenmode", parent_name="surface.colorbar", **kwargs): super(LenmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class LenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="len", parent_name="surface.colorbar", **kwargs): super(LenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ExponentformatValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="exponentformat", parent_name="surface.colorbar", **kwargs ): super(ExponentformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "e", "E", "power", "SI", "B"]), **kwargs ) import _plotly_utils.basevalidators class DtickValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="dtick", parent_name="surface.colorbar", **kwargs): super(DtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BorderwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="borderwidth", parent_name="surface.colorbar", **kwargs ): super(BorderwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="surface.colorbar", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="bgcolor", parent_name="surface.colorbar", **kwargs): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/surface/colorbar/tickfont/0000755000175000017500000000000013573746614025040 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/surface/colorbar/tickfont/__init__.py0000644000175000017500000000300713573721543027143 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="surface.colorbar.tickfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="surface.colorbar.tickfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="surface.colorbar.tickfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/surface/contours/0000755000175000017500000000000013573746614023270 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/surface/contours/x/0000755000175000017500000000000013573746614023537 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/surface/contours/x/__init__.py0000644000175000017500000001426513573721543025652 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="surface.contours.x", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 16), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class UsecolormapValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="usecolormap", parent_name="surface.contours.x", **kwargs ): super(UsecolormapValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class StartValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="start", parent_name="surface.contours.x", **kwargs): super(StartValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="size", parent_name="surface.contours.x", **kwargs): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="show", parent_name="surface.contours.x", **kwargs): super(ShowValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ProjectValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="project", parent_name="surface.contours.x", **kwargs ): super(ProjectValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Project"), data_docs=kwargs.pop( "data_docs", """ x Determines whether or not these contour lines are projected on the x plane. If `highlight` is set to True (the default), the projected lines are shown on hover. If `show` is set to True, the projected lines are shown in permanence. y Determines whether or not these contour lines are projected on the y plane. If `highlight` is set to True (the default), the projected lines are shown on hover. If `show` is set to True, the projected lines are shown in permanence. z Determines whether or not these contour lines are projected on the z plane. If `highlight` is set to True (the default), the projected lines are shown on hover. If `show` is set to True, the projected lines are shown in permanence. """, ), **kwargs ) import _plotly_utils.basevalidators class HighlightwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="highlightwidth", parent_name="surface.contours.x", **kwargs ): super(HighlightwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 16), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class HighlightcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="highlightcolor", parent_name="surface.contours.x", **kwargs ): super(HighlightcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class HighlightValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="highlight", parent_name="surface.contours.x", **kwargs ): super(HighlightValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class EndValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="end", parent_name="surface.contours.x", **kwargs): super(EndValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="surface.contours.x", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/surface/contours/x/project/0000755000175000017500000000000013573746614025205 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/surface/contours/x/project/__init__.py0000644000175000017500000000253713573721543027317 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ZValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="z", parent_name="surface.contours.x.project", **kwargs ): super(ZValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="y", parent_name="surface.contours.x.project", **kwargs ): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="x", parent_name="surface.contours.x.project", **kwargs ): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/surface/contours/z/0000755000175000017500000000000013573746614023541 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/surface/contours/z/__init__.py0000644000175000017500000001426513573721544025655 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="surface.contours.z", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 16), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class UsecolormapValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="usecolormap", parent_name="surface.contours.z", **kwargs ): super(UsecolormapValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class StartValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="start", parent_name="surface.contours.z", **kwargs): super(StartValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="size", parent_name="surface.contours.z", **kwargs): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="show", parent_name="surface.contours.z", **kwargs): super(ShowValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ProjectValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="project", parent_name="surface.contours.z", **kwargs ): super(ProjectValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Project"), data_docs=kwargs.pop( "data_docs", """ x Determines whether or not these contour lines are projected on the x plane. If `highlight` is set to True (the default), the projected lines are shown on hover. If `show` is set to True, the projected lines are shown in permanence. y Determines whether or not these contour lines are projected on the y plane. If `highlight` is set to True (the default), the projected lines are shown on hover. If `show` is set to True, the projected lines are shown in permanence. z Determines whether or not these contour lines are projected on the z plane. If `highlight` is set to True (the default), the projected lines are shown on hover. If `show` is set to True, the projected lines are shown in permanence. """, ), **kwargs ) import _plotly_utils.basevalidators class HighlightwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="highlightwidth", parent_name="surface.contours.z", **kwargs ): super(HighlightwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 16), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class HighlightcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="highlightcolor", parent_name="surface.contours.z", **kwargs ): super(HighlightcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class HighlightValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="highlight", parent_name="surface.contours.z", **kwargs ): super(HighlightValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class EndValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="end", parent_name="surface.contours.z", **kwargs): super(EndValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="surface.contours.z", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/surface/contours/z/project/0000755000175000017500000000000013573746614025207 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/surface/contours/z/project/__init__.py0000644000175000017500000000253713573721543027321 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ZValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="z", parent_name="surface.contours.z.project", **kwargs ): super(ZValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="y", parent_name="surface.contours.z.project", **kwargs ): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="x", parent_name="surface.contours.z.project", **kwargs ): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/surface/contours/y/0000755000175000017500000000000013573746614023540 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/surface/contours/y/__init__.py0000644000175000017500000001426513573721543025653 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="surface.contours.y", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 16), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class UsecolormapValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="usecolormap", parent_name="surface.contours.y", **kwargs ): super(UsecolormapValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class StartValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="start", parent_name="surface.contours.y", **kwargs): super(StartValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="size", parent_name="surface.contours.y", **kwargs): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="show", parent_name="surface.contours.y", **kwargs): super(ShowValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ProjectValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="project", parent_name="surface.contours.y", **kwargs ): super(ProjectValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Project"), data_docs=kwargs.pop( "data_docs", """ x Determines whether or not these contour lines are projected on the x plane. If `highlight` is set to True (the default), the projected lines are shown on hover. If `show` is set to True, the projected lines are shown in permanence. y Determines whether or not these contour lines are projected on the y plane. If `highlight` is set to True (the default), the projected lines are shown on hover. If `show` is set to True, the projected lines are shown in permanence. z Determines whether or not these contour lines are projected on the z plane. If `highlight` is set to True (the default), the projected lines are shown on hover. If `show` is set to True, the projected lines are shown in permanence. """, ), **kwargs ) import _plotly_utils.basevalidators class HighlightwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="highlightwidth", parent_name="surface.contours.y", **kwargs ): super(HighlightwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 16), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class HighlightcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="highlightcolor", parent_name="surface.contours.y", **kwargs ): super(HighlightcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class HighlightValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="highlight", parent_name="surface.contours.y", **kwargs ): super(HighlightValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class EndValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="end", parent_name="surface.contours.y", **kwargs): super(EndValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="surface.contours.y", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/surface/contours/y/project/0000755000175000017500000000000013573746614025206 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/surface/contours/y/project/__init__.py0000644000175000017500000000253713573721543027320 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ZValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="z", parent_name="surface.contours.y.project", **kwargs ): super(ZValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="y", parent_name="surface.contours.y.project", **kwargs ): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="x", parent_name="surface.contours.y.project", **kwargs ): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/surface/contours/__init__.py0000644000175000017500000001242013573721543025372 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ZValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="z", parent_name="surface.contours", **kwargs): super(ZValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Z"), data_docs=kwargs.pop( "data_docs", """ color Sets the color of the contour lines. end Sets the end contour level value. Must be more than `contours.start` highlight Determines whether or not contour lines about the z dimension are highlighted on hover. highlightcolor Sets the color of the highlighted contour lines. highlightwidth Sets the width of the highlighted contour lines. project plotly.graph_objects.surface.contours.z.Project instance or dict with compatible properties show Determines whether or not contour lines about the z dimension are drawn. size Sets the step between each contour level. Must be positive. start Sets the starting contour level value. Must be less than `contours.end` usecolormap An alternate to "color". Determines whether or not the contour lines are colored using the trace "colorscale". width Sets the width of the contour lines. """, ), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="y", parent_name="surface.contours", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Y"), data_docs=kwargs.pop( "data_docs", """ color Sets the color of the contour lines. end Sets the end contour level value. Must be more than `contours.start` highlight Determines whether or not contour lines about the y dimension are highlighted on hover. highlightcolor Sets the color of the highlighted contour lines. highlightwidth Sets the width of the highlighted contour lines. project plotly.graph_objects.surface.contours.y.Project instance or dict with compatible properties show Determines whether or not contour lines about the y dimension are drawn. size Sets the step between each contour level. Must be positive. start Sets the starting contour level value. Must be less than `contours.end` usecolormap An alternate to "color". Determines whether or not the contour lines are colored using the trace "colorscale". width Sets the width of the contour lines. """, ), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="x", parent_name="surface.contours", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "X"), data_docs=kwargs.pop( "data_docs", """ color Sets the color of the contour lines. end Sets the end contour level value. Must be more than `contours.start` highlight Determines whether or not contour lines about the x dimension are highlighted on hover. highlightcolor Sets the color of the highlighted contour lines. highlightwidth Sets the width of the highlighted contour lines. project plotly.graph_objects.surface.contours.x.Project instance or dict with compatible properties show Determines whether or not contour lines about the x dimension are drawn. size Sets the step between each contour level. Must be positive. start Sets the starting contour level value. Must be less than `contours.end` usecolormap An alternate to "color". Determines whether or not the contour lines are colored using the trace "colorscale". width Sets the width of the contour lines. """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/surface/lightposition/0000755000175000017500000000000013573746614024310 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/surface/lightposition/__init__.py0000644000175000017500000000305313573721543026414 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ZValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="z", parent_name="surface.lightposition", **kwargs): super(ZValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 100000), min=kwargs.pop("min", -100000), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="y", parent_name="surface.lightposition", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 100000), min=kwargs.pop("min", -100000), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="x", parent_name="surface.lightposition", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 100000), min=kwargs.pop("min", -100000), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/surface/stream/0000755000175000017500000000000013573746614022707 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/surface/stream/__init__.py0000644000175000017500000000206413573721543025014 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TokenValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="token", parent_name="surface.stream", **kwargs): super(TokenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "info"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class MaxpointsValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="maxpoints", parent_name="surface.stream", **kwargs): super(MaxpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 10000), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/surface/__init__.py0000644000175000017500000011312213573721544023520 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ZsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="zsrc", parent_name="surface", **kwargs): super(ZsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZcalendarValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="zcalendar", parent_name="surface", **kwargs): super(ZcalendarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "gregorian", "chinese", "coptic", "discworld", "ethiopian", "hebrew", "islamic", "julian", "mayan", "nanakshahi", "nepali", "persian", "jalali", "taiwan", "thai", "ummalqura", ], ), **kwargs ) import _plotly_utils.basevalidators class ZValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="z", parent_name="surface", **kwargs): super(ZValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class YsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="ysrc", parent_name="surface", **kwargs): super(YsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YcalendarValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="ycalendar", parent_name="surface", **kwargs): super(YcalendarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "gregorian", "chinese", "coptic", "discworld", "ethiopian", "hebrew", "islamic", "julian", "mayan", "nanakshahi", "nepali", "persian", "jalali", "taiwan", "thai", "ummalqura", ], ), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="y", parent_name="surface", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class XsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="xsrc", parent_name="surface", **kwargs): super(XsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XcalendarValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="xcalendar", parent_name="surface", **kwargs): super(XcalendarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "gregorian", "chinese", "coptic", "discworld", "ethiopian", "hebrew", "islamic", "julian", "mayan", "nanakshahi", "nepali", "persian", "jalali", "taiwan", "thai", "ummalqura", ], ), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="x", parent_name="surface", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="visible", parent_name="surface", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "legendonly"]), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="surface", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UidValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="uid", parent_name="surface", **kwargs): super(UidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="textsrc", parent_name="surface", **kwargs): super(TextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="text", parent_name="surface", **kwargs): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SurfacecolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="surfacecolorsrc", parent_name="surface", **kwargs): super(SurfacecolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SurfacecolorValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="surfacecolor", parent_name="surface", **kwargs): super(SurfacecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class StreamValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="stream", parent_name="surface", **kwargs): super(StreamValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Stream"), data_docs=kwargs.pop( "data_docs", """ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """, ), **kwargs ) import _plotly_utils.basevalidators class ShowscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showscale", parent_name="surface", **kwargs): super(ShowscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SceneValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="scene", parent_name="surface", **kwargs): super(SceneValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "scene"), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ReversescaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="reversescale", parent_name="surface", **kwargs): super(ReversescaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="surface", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="surface", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="metasrc", parent_name="surface", **kwargs): super(MetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetaValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="meta", parent_name="surface", **kwargs): super(MetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LightpositionValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="lightposition", parent_name="surface", **kwargs): super(LightpositionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Lightposition"), data_docs=kwargs.pop( "data_docs", """ x Numeric vector, representing the X coordinate for each vertex. y Numeric vector, representing the Y coordinate for each vertex. z Numeric vector, representing the Z coordinate for each vertex. """, ), **kwargs ) import _plotly_utils.basevalidators class LightingValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="lighting", parent_name="surface", **kwargs): super(LightingValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Lighting"), data_docs=kwargs.pop( "data_docs", """ ambient Ambient light increases overall color visibility but can wash out the image. diffuse Represents the extent that incident rays are reflected in a range of angles. fresnel Represents the reflectance as a dependency of the viewing angle; e.g. paper is reflective when viewing it from the edge of the paper (almost 90 degrees), causing shine. roughness Alters specular reflection; the rougher the surface, the wider and less contrasty the shine. specular Represents the level that incident rays are reflected in a single direction, causing shine. """, ), **kwargs ) import _plotly_utils.basevalidators class IdssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="idssrc", parent_name="surface", **kwargs): super(IdssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ids", parent_name="surface", **kwargs): super(IdsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class HovertextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hovertextsrc", parent_name="surface", **kwargs): super(HovertextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertext", parent_name="surface", **kwargs): super(HovertextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hovertemplatesrc", parent_name="surface", **kwargs): super(HovertemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertemplate", parent_name="surface", **kwargs): super(HovertemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverlabelValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="hoverlabel", parent_name="surface", **kwargs): super(HoverlabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Hoverlabel"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """, ), **kwargs ) import _plotly_utils.basevalidators class HoverinfosrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hoverinfosrc", parent_name="surface", **kwargs): super(HoverinfosrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverinfoValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="hoverinfo", parent_name="surface", **kwargs): super(HoverinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), extras=kwargs.pop("extras", ["all", "none", "skip"]), flags=kwargs.pop("flags", ["x", "y", "z", "text", "name"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HidesurfaceValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="hidesurface", parent_name="surface", **kwargs): super(HidesurfaceValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdatasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="customdatasrc", parent_name="surface", **kwargs): super(CustomdatasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdataValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="customdata", parent_name="surface", **kwargs): super(CustomdataValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class ContoursValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="contours", parent_name="surface", **kwargs): super(ContoursValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Contours"), data_docs=kwargs.pop( "data_docs", """ x plotly.graph_objects.surface.contours.X instance or dict with compatible properties y plotly.graph_objects.surface.contours.Y instance or dict with compatible properties z plotly.graph_objects.surface.contours.Z instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class ConnectgapsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="connectgaps", parent_name="surface", **kwargs): super(ConnectgapsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__(self, plotly_name="colorscale", parent_name="surface", **kwargs): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"autocolorscale": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorBarValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="colorbar", parent_name="surface", **kwargs): super(ColorBarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "ColorBar"), data_docs=kwargs.pop( "data_docs", """ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.surface.colorba r.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.surface.colorbar.tickformatstopdefaults), sets the default property values to use for elements of surface.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.surface.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use surface.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use surface.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """, ), **kwargs ) import _plotly_utils.basevalidators class ColoraxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="coloraxis", parent_name="surface", **kwargs): super(ColoraxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", None), edit_type=kwargs.pop("edit_type", "calc"), regex=kwargs.pop("regex", "/^coloraxis([2-9]|[1-9][0-9]+)?$/"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmin", parent_name="surface", **kwargs): super(CminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmidValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmid", parent_name="surface", **kwargs): super(CmidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmax", parent_name="surface", **kwargs): super(CmaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CautoValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="cauto", parent_name="surface", **kwargs): super(CautoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AutocolorscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="autocolorscale", parent_name="surface", **kwargs): super(AutocolorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/surface/lighting/0000755000175000017500000000000013573746614023221 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/surface/lighting/__init__.py0000644000175000017500000000517013573721543025327 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SpecularValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="specular", parent_name="surface.lighting", **kwargs ): super(SpecularValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 2), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class RoughnessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="roughness", parent_name="surface.lighting", **kwargs ): super(RoughnessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FresnelValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="fresnel", parent_name="surface.lighting", **kwargs): super(FresnelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 5), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class DiffuseValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="diffuse", parent_name="surface.lighting", **kwargs): super(DiffuseValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AmbientValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="ambient", parent_name="surface.lighting", **kwargs): super(AmbientValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/__init__.py0000644000175000017500000220015113573721537022073 0ustar noahfxnoahfximport _plotly_utils.basevalidators class LayoutValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="layout", parent_name="", **kwargs): super(LayoutValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Layout"), data_docs=kwargs.pop( "data_docs", """ angularaxis plotly.graph_objects.layout.AngularAxis instance or dict with compatible properties annotations A tuple of plotly.graph_objects.layout.Annotation instances or dicts with compatible properties annotationdefaults When used in a template (as layout.template.layout.annotationdefaults), sets the default property values to use for elements of layout.annotations autosize Determines whether or not a layout width or height that has been left undefined by the user is initialized on each relayout. Note that, regardless of this attribute, an undefined layout width or height is always initialized on the first call to plot. bargap Sets the gap (in plot fraction) between bars of adjacent location coordinates. bargroupgap Sets the gap (in plot fraction) between bars of the same location coordinate. barmode Determines how bars at the same location coordinate are displayed on the graph. With "stack", the bars are stacked on top of one another With "relative", the bars are stacked on top of one another, with negative values below the axis, positive values above With "group", the bars are plotted next to one another centered around the shared location. With "overlay", the bars are plotted over one another, you might need to an "opacity" to see multiple bars. barnorm Sets the normalization for bar traces on the graph. With "fraction", the value of each bar is divided by the sum of all values at that location coordinate. "percent" is the same but multiplied by 100 to show percentages. boxgap Sets the gap (in plot fraction) between boxes of adjacent location coordinates. Has no effect on traces that have "width" set. boxgroupgap Sets the gap (in plot fraction) between boxes of the same location coordinate. Has no effect on traces that have "width" set. boxmode Determines how boxes at the same location coordinate are displayed on the graph. If "group", the boxes are plotted next to one another centered around the shared location. If "overlay", the boxes are plotted over one another, you might need to set "opacity" to see them multiple boxes. Has no effect on traces that have "width" set. calendar Sets the default calendar system to use for interpreting and displaying dates throughout the plot. clickmode Determines the mode of single click interactions. "event" is the default value and emits the `plotly_click` event. In addition this mode emits the `plotly_selected` event in drag modes "lasso" and "select", but with no event data attached (kept for compatibility reasons). The "select" flag enables selecting single data points via click. This mode also supports persistent selections, meaning that pressing Shift while clicking, adds to / subtracts from an existing selection. "select" with `hovermode`: "x" can be confusing, consider explicitly setting `hovermode`: "closest" when using this feature. Selection events are sent accordingly as long as "event" flag is set as well. When the "event" flag is missing, `plotly_click` and `plotly_selected` events are not fired. coloraxis plotly.graph_objects.layout.Coloraxis instance or dict with compatible properties colorscale plotly.graph_objects.layout.Colorscale instance or dict with compatible properties colorway Sets the default trace colors. datarevision If provided, a changed value tells `Plotly.react` that one or more data arrays has changed. This way you can modify arrays in- place rather than making a complete new copy for an incremental change. If NOT provided, `Plotly.react` assumes that data arrays are being treated as immutable, thus any data array with a different identity from its predecessor contains new data. direction Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the direction corresponding to positive angles in legacy polar charts. dragmode Determines the mode of drag interactions. "select" and "lasso" apply only to scatter traces with markers or text. "orbit" and "turntable" apply only to 3D scenes. editrevision Controls persistence of user-driven changes in `editable: true` configuration, other than trace names and axis titles. Defaults to `layout.uirevision`. extendfunnelareacolors If `true`, the funnelarea slice colors (whether given by `funnelareacolorway` or inherited from `colorway`) will be extended to three times its original length by first repeating every color 20% lighter then each color 20% darker. This is intended to reduce the likelihood of reusing the same color when you have many slices, but you can set `false` to disable. Colors provided in the trace, using `marker.colors`, are never extended. extendpiecolors If `true`, the pie slice colors (whether given by `piecolorway` or inherited from `colorway`) will be extended to three times its original length by first repeating every color 20% lighter then each color 20% darker. This is intended to reduce the likelihood of reusing the same color when you have many slices, but you can set `false` to disable. Colors provided in the trace, using `marker.colors`, are never extended. extendsunburstcolors If `true`, the sunburst slice colors (whether given by `sunburstcolorway` or inherited from `colorway`) will be extended to three times its original length by first repeating every color 20% lighter then each color 20% darker. This is intended to reduce the likelihood of reusing the same color when you have many slices, but you can set `false` to disable. Colors provided in the trace, using `marker.colors`, are never extended. extendtreemapcolors If `true`, the treemap slice colors (whether given by `treemapcolorway` or inherited from `colorway`) will be extended to three times its original length by first repeating every color 20% lighter then each color 20% darker. This is intended to reduce the likelihood of reusing the same color when you have many slices, but you can set `false` to disable. Colors provided in the trace, using `marker.colors`, are never extended. font Sets the global font. Note that fonts used in traces and other layout components inherit from the global font. funnelareacolorway Sets the default funnelarea slice colors. Defaults to the main `colorway` used for trace colors. If you specify a new list here it can still be extended with lighter and darker colors, see `extendfunnelareacolors`. funnelgap Sets the gap (in plot fraction) between bars of adjacent location coordinates. funnelgroupgap Sets the gap (in plot fraction) between bars of the same location coordinate. funnelmode Determines how bars at the same location coordinate are displayed on the graph. With "stack", the bars are stacked on top of one another With "group", the bars are plotted next to one another centered around the shared location. With "overlay", the bars are plotted over one another, you might need to an "opacity" to see multiple bars. geo plotly.graph_objects.layout.Geo instance or dict with compatible properties grid plotly.graph_objects.layout.Grid instance or dict with compatible properties height Sets the plot's height (in px). hiddenlabels hiddenlabels is the funnelarea & pie chart analog of visible:'legendonly' but it can contain many labels, and can simultaneously hide slices from several pies/funnelarea charts hiddenlabelssrc Sets the source reference on plot.ly for hiddenlabels . hidesources Determines whether or not a text link citing the data source is placed at the bottom-right cored of the figure. Has only an effect only on graphs that have been generated via forked graphs from the plotly service (at https://plot.ly or on-premise). hoverdistance Sets the default distance (in pixels) to look for data to add hover labels (-1 means no cutoff, 0 means no looking for data). This is only a real distance for hovering on point-like objects, like scatter points. For area-like objects (bars, scatter fills, etc) hovering is on inside the area and off outside, but these objects will not supersede hover on point-like objects in case of conflict. hoverlabel plotly.graph_objects.layout.Hoverlabel instance or dict with compatible properties hovermode Determines the mode of hover interactions. If `clickmode` includes the "select" flag, `hovermode` defaults to "closest". If `clickmode` lacks the "select" flag, it defaults to "x" or "y" (depending on the trace's `orientation` value) for plots based on cartesian coordinates. For anything else the default value is "closest". images A tuple of plotly.graph_objects.layout.Image instances or dicts with compatible properties imagedefaults When used in a template (as layout.template.layout.imagedefaults), sets the default property values to use for elements of layout.images legend plotly.graph_objects.layout.Legend instance or dict with compatible properties mapbox plotly.graph_objects.layout.Mapbox instance or dict with compatible properties margin plotly.graph_objects.layout.Margin instance or dict with compatible properties meta Assigns extra meta information that can be used in various `text` attributes. Attributes such as the graph, axis and colorbar `title.text`, annotation `text` `trace.name` in legend items, `rangeselector`, `updatemenus` and `sliders` `label` text all support `meta`. One can access `meta` fields using template strings: `%{meta[i]}` where `i` is the index of the `meta` item in question. `meta` can also be an object for example `{key: value}` which can be accessed %{meta[key]}. metasrc Sets the source reference on plot.ly for meta . modebar plotly.graph_objects.layout.Modebar instance or dict with compatible properties orientation Legacy polar charts are deprecated! Please switch to "polar" subplots. Rotates the entire polar by the given angle in legacy polar charts. paper_bgcolor Sets the color of paper where the graph is drawn. piecolorway Sets the default pie slice colors. Defaults to the main `colorway` used for trace colors. If you specify a new list here it can still be extended with lighter and darker colors, see `extendpiecolors`. plot_bgcolor Sets the color of plotting area in-between x and y axes. polar plotly.graph_objects.layout.Polar instance or dict with compatible properties radialaxis plotly.graph_objects.layout.RadialAxis instance or dict with compatible properties scene plotly.graph_objects.layout.Scene instance or dict with compatible properties selectdirection When "dragmode" is set to "select", this limits the selection of the drag to horizontal, vertical or diagonal. "h" only allows horizontal selection, "v" only vertical, "d" only diagonal and "any" sets no limit. selectionrevision Controls persistence of user-driven changes in selected points from all traces. separators Sets the decimal and thousand separators. For example, *. * puts a '.' before decimals and a space between thousands. In English locales, dflt is ".," but other locales may alter this default. shapes A tuple of plotly.graph_objects.layout.Shape instances or dicts with compatible properties shapedefaults When used in a template (as layout.template.layout.shapedefaults), sets the default property values to use for elements of layout.shapes showlegend Determines whether or not a legend is drawn. Default is `true` if there is a trace to show and any of these: a) Two or more traces would by default be shown in the legend. b) One pie trace is shown in the legend. c) One trace is explicitly given with `showlegend: true`. sliders A tuple of plotly.graph_objects.layout.Slider instances or dicts with compatible properties sliderdefaults When used in a template (as layout.template.layout.sliderdefaults), sets the default property values to use for elements of layout.sliders spikedistance Sets the default distance (in pixels) to look for data to draw spikelines to (-1 means no cutoff, 0 means no looking for data). As with hoverdistance, distance does not apply to area- like objects. In addition, some objects can be hovered on but will not generate spikelines, such as scatter fills. sunburstcolorway Sets the default sunburst slice colors. Defaults to the main `colorway` used for trace colors. If you specify a new list here it can still be extended with lighter and darker colors, see `extendsunburstcolors`. template Default attributes to be applied to the plot. This should be a dict with format: `{'layout': layoutTemplate, 'data': {trace_type: [traceTemplate, ...], ...}}` where `layoutTemplate` is a dict matching the structure of `figure.layout` and `traceTemplate` is a dict matching the structure of the trace with type `trace_type` (e.g. 'scatter'). Alternatively, this may be specified as an instance of plotly.graph_objs.layout.Template. Trace templates are applied cyclically to traces of each type. Container arrays (eg `annotations`) have special handling: An object ending in `defaults` (eg `annotationdefaults`) is applied to each array item. But if an item has a `templateitemname` key we look in the template array for an item with matching `name` and apply that instead. If no matching `name` is found we mark the item invisible. Any named template item not referenced is appended to the end of the array, so this can be used to add a watermark annotation or a logo image, for example. To omit one of these items on the plot, make an item with matching `templateitemname` and `visible: false`. ternary plotly.graph_objects.layout.Ternary instance or dict with compatible properties title plotly.graph_objects.layout.Title instance or dict with compatible properties titlefont Deprecated: Please use layout.title.font instead. Sets the title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. transition Sets transition options used during Plotly.react updates. treemapcolorway Sets the default treemap slice colors. Defaults to the main `colorway` used for trace colors. If you specify a new list here it can still be extended with lighter and darker colors, see `extendtreemapcolors`. uirevision Used to allow user interactions with the plot to persist after `Plotly.react` calls that are unaware of these interactions. If `uirevision` is omitted, or if it is given and it changed from the previous `Plotly.react` call, the exact new figure is used. If `uirevision` is truthy and did NOT change, any attribute that has been affected by user interactions and did not receive a different value in the new figure will keep the interaction value. `layout.uirevision` attribute serves as the default for `uirevision` attributes in various sub-containers. For finer control you can set these sub-attributes directly. For example, if your app separately controls the data on the x and y axes you might set `xaxis.uirevision=*time*` and `yaxis.uirevision=*cost*`. Then if only the y data is changed, you can update `yaxis.uirevision=*quantity*` and the y axis range will reset but the x axis range will retain any user-driven zoom. updatemenus A tuple of plotly.graph_objects.layout.Updatemenu instances or dicts with compatible properties updatemenudefaults When used in a template (as layout.template.layout.updatemenudefaults), sets the default property values to use for elements of layout.updatemenus violingap Sets the gap (in plot fraction) between violins of adjacent location coordinates. Has no effect on traces that have "width" set. violingroupgap Sets the gap (in plot fraction) between violins of the same location coordinate. Has no effect on traces that have "width" set. violinmode Determines how violins at the same location coordinate are displayed on the graph. If "group", the violins are plotted next to one another centered around the shared location. If "overlay", the violins are plotted over one another, you might need to set "opacity" to see them multiple violins. Has no effect on traces that have "width" set. waterfallgap Sets the gap (in plot fraction) between bars of adjacent location coordinates. waterfallgroupgap Sets the gap (in plot fraction) between bars of the same location coordinate. waterfallmode Determines how bars at the same location coordinate are displayed on the graph. With "group", the bars are plotted next to one another centered around the shared location. With "overlay", the bars are plotted over one another, you might need to an "opacity" to see multiple bars. width Sets the plot's width (in px). xaxis plotly.graph_objects.layout.XAxis instance or dict with compatible properties yaxis plotly.graph_objects.layout.YAxis instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class WaterfallValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="waterfall", parent_name="", **kwargs): super(WaterfallValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Waterfall"), data_docs=kwargs.pop( "data_docs", """ alignmentgroup Set several traces linked to the same position axis or matching axes to the same alignmentgroup. This controls whether bars compute their positional range dependently or independently. base Sets where the bar base is drawn (in position axis units). cliponaxis Determines whether the text nodes are clipped about the subplot axes. To show the text nodes above axis lines and tick labels, make sure to set `xaxis.layer` and `yaxis.layer` to *below traces*. connector plotly.graph_objects.waterfall.Connector instance or dict with compatible properties constraintext Constrain the size of text inside or outside a bar to be no larger than the bar itself. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . decreasing plotly.graph_objects.waterfall.Decreasing instance or dict with compatible properties dx Sets the x coordinate step. See `x0` for more info. dy Sets the y coordinate step. See `y0` for more info. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.waterfall.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs- events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `initial`, `delta` and `final`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . increasing plotly.graph_objects.waterfall.Increasing instance or dict with compatible properties insidetextanchor Determines if texts are kept at center or start/end points in `textposition` "inside" mode. insidetextfont Sets the font used for `text` lying inside the bar. legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. measure An array containing types of values. By default the values are considered as 'relative'. However; it is possible to use 'total' to compute the sums. Also 'absolute' could be applied to reset the computed total or to declare an initial value where needed. measuresrc Sets the source reference on plot.ly for measure . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. offset Shifts the position where the bar is drawn (in position axis units). In "group" barmode, traces that set "offset" will be excluded and drawn in "overlay" mode instead. offsetgroup Set several traces linked to the same position axis or matching axes to the same offsetgroup where bars of the same position coordinate will line up. offsetsrc Sets the source reference on plot.ly for offset . opacity Sets the opacity of the trace. orientation Sets the orientation of the bars. With "v" ("h"), the value of the each bar spans along the vertical (horizontal). outsidetextfont Sets the font used for `text` lying outside the bar. selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.waterfall.Stream instance or dict with compatible properties text Sets text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textangle Sets the angle of the tick labels with respect to the bar. For example, a `tickangle` of -90 draws the tick labels vertically. With "auto" the texts may automatically be rotated to fit with the maximum size in bars. textfont Sets the font used for `text`. textinfo Determines which trace information appear on the graph. In the case of having multiple waterfalls, totals are computed separately (per trace). textposition Specifies the location of the `text`. "inside" positions `text` inside, next to the bar end (rotated and scaled if needed). "outside" positions `text` outside, next to the bar end (scaled if needed), unless there is another bar stacked on this one, then the text gets pushed inside. "auto" tries to position `text` inside the bar, but if the bar is too small and no bar is stacked on this one the text is moved outside. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. variables `initial`, `delta`, `final` and `label`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . totals plotly.graph_objects.waterfall.Totals instance or dict with compatible properties uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user- driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user- driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). width Sets the bar width (in position axis units). widthsrc Sets the source reference on plot.ly for width . x Sets the x coordinates. x0 Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xsrc Sets the source reference on plot.ly for x . y Sets the y coordinates. y0 Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ysrc Sets the source reference on plot.ly for y . """, ), **kwargs ) import _plotly_utils.basevalidators class VolumeValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="volume", parent_name="", **kwargs): super(VolumeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Volume"), data_docs=kwargs.pop( "data_docs", """ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. caps plotly.graph_objects.volume.Caps instance or dict with compatible properties cauto Determines whether or not the color domain is computed with respect to the input data (here `value`) or the bounds set in `cmin` and `cmax` Defaults to `false` when `cmin` and `cmax` are set by the user. cmax Sets the upper bound of the color domain. Value should have the same units as `value` and if set, `cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `cmin` and/or `cmax` to be equidistant to this point. Value should have the same units as `value`. Has no effect when `cauto` is `false`. cmin Sets the lower bound of the color domain. Value should have the same units as `value` and if set, `cmax` must be set as well. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.volume.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`cmin` and `cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Grey s,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Blues, Picnic,Rainbow,Portland,Jet,Hot,Blackbody,Earth ,Electric,Viridis,Cividis. contour plotly.graph_objects.volume.Contour instance or dict with compatible properties customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . flatshading Determines whether or not normal smoothing is applied to the meshes, creating meshes with an angular, low-poly look via flat reflections. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.volume.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs- events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . isomax Sets the maximum boundary for iso-surface plot. isomin Sets the minimum boundary for iso-surface plot. lighting plotly.graph_objects.volume.Lighting instance or dict with compatible properties lightposition plotly.graph_objects.volume.Lightposition instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the surface. Please note that in the case of using high `opacity` values for example a value greater than or equal to 0.5 on two surfaces (and 0.25 with four surfaces), an overlay of multiple transparent surfaces may not perfectly be sorted in depth by the webgl API. This behavior may be improved in the near future and is subject to change. opacityscale Sets the opacityscale. The opacityscale must be an array containing arrays mapping a normalized value to an opacity value. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 1], [0.5, 0.2], [1, 1]]` means that higher/lower values would have higher opacity values and those in the middle would be more transparent Alternatively, `opacityscale` may be a palette name string of the following list: 'min', 'max', 'extremes' and 'uniform'. The default is 'uniform'. reversescale Reverses the color mapping if true. If true, `cmin` will correspond to the last color in the array and `cmax` will correspond to the first color. scene Sets a reference between this trace's 3D coordinate system and a 3D scene. If "scene" (the default value), the (x,y,z) coordinates refer to `layout.scene`. If "scene2", the (x,y,z) coordinates refer to `layout.scene2`, and so on. showscale Determines whether or not a colorbar is displayed for this trace. slices plotly.graph_objects.volume.Slices instance or dict with compatible properties spaceframe plotly.graph_objects.volume.Spaceframe instance or dict with compatible properties stream plotly.graph_objects.volume.Stream instance or dict with compatible properties surface plotly.graph_objects.volume.Surface instance or dict with compatible properties text Sets the text elements associated with the vertices. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user- driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user- driven changes if you give each trace a `uid` that stays with it as it moves. value Sets the 4th dimension (value) of the vertices. valuesrc Sets the source reference on plot.ly for value . visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the X coordinates of the vertices on X axis. xsrc Sets the source reference on plot.ly for x . y Sets the Y coordinates of the vertices on Y axis. ysrc Sets the source reference on plot.ly for y . z Sets the Z coordinates of the vertices on Z axis. zsrc Sets the source reference on plot.ly for z . """, ), **kwargs ) import _plotly_utils.basevalidators class ViolinValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="violin", parent_name="", **kwargs): super(ViolinValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Violin"), data_docs=kwargs.pop( "data_docs", """ alignmentgroup Set several traces linked to the same position axis or matching axes to the same alignmentgroup. This controls whether bars compute their positional range dependently or independently. bandwidth Sets the bandwidth used to compute the kernel density estimate. By default, the bandwidth is determined by Silverman's rule of thumb. box plotly.graph_objects.violin.Box instance or dict with compatible properties customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . fillcolor Sets the fill color. Defaults to a half- transparent variant of the line color, marker color, or marker line color, whichever is available. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.violin.Hoverlabel instance or dict with compatible properties hoveron Do the hover effects highlight individual violins or sample points or the kernel density estimate or any combination of them? hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs- events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . jitter Sets the amount of jitter in the sample points drawn. If 0, the sample points align along the distribution axis. If 1, the sample points are drawn in a random jitter of width equal to the width of the violins. legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.violin.Line instance or dict with compatible properties marker plotly.graph_objects.violin.Marker instance or dict with compatible properties meanline plotly.graph_objects.violin.Meanline instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. For violin traces, the name will also be used for the position coordinate, if `x` and `x0` (`y` and `y0` if horizontal) are missing and the position axis is categorical. Note that the trace name is also used as a default value for attribute `scalegroup` (please see its description for details). offsetgroup Set several traces linked to the same position axis or matching axes to the same offsetgroup where bars of the same position coordinate will line up. opacity Sets the opacity of the trace. orientation Sets the orientation of the violin(s). If "v" ("h"), the distribution is visualized along the vertical (horizontal). pointpos Sets the position of the sample points in relation to the violins. If 0, the sample points are places over the center of the violins. Positive (negative) values correspond to positions to the right (left) for vertical violins and above (below) for horizontal violins. points If "outliers", only the sample points lying outside the whiskers are shown If "suspectedoutliers", the outlier points are shown and points either less than 4*Q1-3*Q3 or greater than 4*Q3-3*Q1 are highlighted (see `outliercolor`) If "all", all sample points are shown If False, only the violins are shown with no sample points scalegroup If there are multiple violins that should be sized according to to some metric (see `scalemode`), link them by providing a non- empty group id here shared by every trace in the same group. If a violin's `width` is undefined, `scalegroup` will default to the trace's name. In this case, violins with the same names will be linked together scalemode Sets the metric by which the width of each violin is determined."width" means each violin has the same (max) width*count* means the violins are scaled by the number of sample points makingup each violin. selected plotly.graph_objects.violin.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. side Determines on which side of the position value the density function making up one half of a violin is plotted. Useful when comparing two violin traces under "overlay" mode, where one trace has `side` set to "positive" and the other to "negative". span Sets the span in data space for which the density function will be computed. Has an effect only when `spanmode` is set to "manual". spanmode Sets the method by which the span in data space where the density function will be computed. "soft" means the span goes from the sample's minimum value minus two bandwidths to the sample's maximum value plus two bandwidths. "hard" means the span goes from the sample's minimum to its maximum value. For custom span settings, use mode "manual" and fill in the `span` attribute. stream plotly.graph_objects.violin.Stream instance or dict with compatible properties text Sets the text elements associated with each sample value. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user- driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user- driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.violin.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). width Sets the width of the violin in data coordinates. If 0 (default value) the width is automatically selected based on the positions of other violin traces in the same subplot. x Sets the x sample data or coordinates. See overview for more info. x0 Sets the x coordinate of the box. See overview for more info. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xsrc Sets the source reference on plot.ly for x . y Sets the y sample data or coordinates. See overview for more info. y0 Sets the y coordinate of the box. See overview for more info. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ysrc Sets the source reference on plot.ly for y . """, ), **kwargs ) import _plotly_utils.basevalidators class TreemapValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="treemap", parent_name="", **kwargs): super(TreemapValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Treemap"), data_docs=kwargs.pop( "data_docs", """ branchvalues Determines how the items in `values` are summed. When set to "total", items in `values` are taken to be value of all its descendants. When set to "remainder", items in `values` corresponding to the root and the branches sectors are taken to be the extra part not part of the sum of the values at their leaves. count Determines default for `values` when it is not provided, by inferring a 1 for each of the "leaves" and/or "branches", otherwise 0. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . domain plotly.graph_objects.treemap.Domain instance or dict with compatible properties hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.treemap.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs- events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `currentPath`, `root`, `entry`, `percentRoot`, `percentEntry` and `percentParent`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each sector. If a single string, the same string appears for all data points. If an array of string, the items are mapped in order of this trace's sectors. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . insidetextfont Sets the font used for `textinfo` lying inside the sector. labels Sets the labels of each of the sectors. labelssrc Sets the source reference on plot.ly for labels . level Sets the level from which this trace hierarchy is rendered. Set `level` to `''` to start from the root node in the hierarchy. Must be an "id" if `ids` is filled in, otherwise plotly attempts to find a matching item in `labels`. marker plotly.graph_objects.treemap.Marker instance or dict with compatible properties maxdepth Sets the number of rendered sectors from any given `level`. Set `maxdepth` to "-1" to render all the levels in the hierarchy. meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. outsidetextfont Sets the font used for `textinfo` lying outside the sector. parents Sets the parent sectors for each of the sectors. Empty string items '' are understood to reference the root node in the hierarchy. If `ids` is filled, `parents` items are understood to be "ids" themselves. When `ids` is not set, plotly attempts to find matching items in `labels`, but beware they must be unique. parentssrc Sets the source reference on plot.ly for parents . pathbar plotly.graph_objects.treemap.Pathbar instance or dict with compatible properties stream plotly.graph_objects.treemap.Stream instance or dict with compatible properties text Sets text elements associated with each sector. If trace `textinfo` contains a "text" flag, these elements will be seen on the chart. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the font used for `textinfo`. textinfo Determines which trace information appear on the graph. textposition Sets the positions of the `text` elements. textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. variables `currentPath`, `root`, `entry`, `percentRoot`, `percentEntry`, `percentParent`, `label` and `value`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . tiling plotly.graph_objects.treemap.Tiling instance or dict with compatible properties uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user- driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user- driven changes if you give each trace a `uid` that stays with it as it moves. values Sets the values associated with each of the sectors. Use with `branchvalues` to determine how the values are summed. valuessrc Sets the source reference on plot.ly for values . visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). """, ), **kwargs ) import _plotly_utils.basevalidators class TableValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="table", parent_name="", **kwargs): super(TableValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Table"), data_docs=kwargs.pop( "data_docs", """ cells plotly.graph_objects.table.Cells instance or dict with compatible properties columnorder Specifies the rendered order of the data columns; for example, a value `2` at position `0` means that column index `0` in the data will be rendered as the third column, as columns have an index base of zero. columnordersrc Sets the source reference on plot.ly for columnorder . columnwidth The width of columns expressed as a ratio. Columns fill the available width in proportion of their specified column widths. columnwidthsrc Sets the source reference on plot.ly for columnwidth . customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . domain plotly.graph_objects.table.Domain instance or dict with compatible properties header plotly.graph_objects.table.Header instance or dict with compatible properties hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.table.Hoverlabel instance or dict with compatible properties ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. stream plotly.graph_objects.table.Stream instance or dict with compatible properties uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user- driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user- driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). """, ), **kwargs ) import _plotly_utils.basevalidators class SurfaceValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="surface", parent_name="", **kwargs): super(SurfaceValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Surface"), data_docs=kwargs.pop( "data_docs", """ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here z or surfacecolor) or the bounds set in `cmin` and `cmax` Defaults to `false` when `cmin` and `cmax` are set by the user. cmax Sets the upper bound of the color domain. Value should have the same units as z or surfacecolor and if set, `cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `cmin` and/or `cmax` to be equidistant to this point. Value should have the same units as z or surfacecolor. Has no effect when `cauto` is `false`. cmin Sets the lower bound of the color domain. Value should have the same units as z or surfacecolor and if set, `cmax` must be set as well. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.surface.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`cmin` and `cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Grey s,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Blues, Picnic,Rainbow,Portland,Jet,Hot,Blackbody,Earth ,Electric,Viridis,Cividis. connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the `z` data are filled in. contours plotly.graph_objects.surface.Contours instance or dict with compatible properties customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . hidesurface Determines whether or not a surface is drawn. For example, set `hidesurface` to False `contours.x.show` to True and `contours.y.show` to True to draw a wire frame plot. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.surface.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs- events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . lighting plotly.graph_objects.surface.Lighting instance or dict with compatible properties lightposition plotly.graph_objects.surface.Lightposition instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the surface. Please note that in the case of using high `opacity` values for example a value greater than or equal to 0.5 on two surfaces (and 0.25 with four surfaces), an overlay of multiple transparent surfaces may not perfectly be sorted in depth by the webgl API. This behavior may be improved in the near future and is subject to change. reversescale Reverses the color mapping if true. If true, `cmin` will correspond to the last color in the array and `cmax` will correspond to the first color. scene Sets a reference between this trace's 3D coordinate system and a 3D scene. If "scene" (the default value), the (x,y,z) coordinates refer to `layout.scene`. If "scene2", the (x,y,z) coordinates refer to `layout.scene2`, and so on. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.surface.Stream instance or dict with compatible properties surfacecolor Sets the surface color values, used for setting a color scale independent of `z`. surfacecolorsrc Sets the source reference on plot.ly for surfacecolor . text Sets the text elements associated with each z value. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user- driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user- driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the x coordinates. xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . y Sets the y coordinates. ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . z Sets the z coordinates. zcalendar Sets the calendar system to use with `z` date data. zsrc Sets the source reference on plot.ly for z . """, ), **kwargs ) import _plotly_utils.basevalidators class SunburstValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="sunburst", parent_name="", **kwargs): super(SunburstValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Sunburst"), data_docs=kwargs.pop( "data_docs", """ branchvalues Determines how the items in `values` are summed. When set to "total", items in `values` are taken to be value of all its descendants. When set to "remainder", items in `values` corresponding to the root and the branches sectors are taken to be the extra part not part of the sum of the values at their leaves. count Determines default for `values` when it is not provided, by inferring a 1 for each of the "leaves" and/or "branches", otherwise 0. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . domain plotly.graph_objects.sunburst.Domain instance or dict with compatible properties hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.sunburst.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs- events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `currentPath`, `root`, `entry`, `percentRoot`, `percentEntry` and `percentParent`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each sector. If a single string, the same string appears for all data points. If an array of string, the items are mapped in order of this trace's sectors. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . insidetextfont Sets the font used for `textinfo` lying inside the sector. labels Sets the labels of each of the sectors. labelssrc Sets the source reference on plot.ly for labels . leaf plotly.graph_objects.sunburst.Leaf instance or dict with compatible properties level Sets the level from which this trace hierarchy is rendered. Set `level` to `''` to start from the root node in the hierarchy. Must be an "id" if `ids` is filled in, otherwise plotly attempts to find a matching item in `labels`. marker plotly.graph_objects.sunburst.Marker instance or dict with compatible properties maxdepth Sets the number of rendered sectors from any given `level`. Set `maxdepth` to "-1" to render all the levels in the hierarchy. meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. outsidetextfont Sets the font used for `textinfo` lying outside the sector. parents Sets the parent sectors for each of the sectors. Empty string items '' are understood to reference the root node in the hierarchy. If `ids` is filled, `parents` items are understood to be "ids" themselves. When `ids` is not set, plotly attempts to find matching items in `labels`, but beware they must be unique. parentssrc Sets the source reference on plot.ly for parents . stream plotly.graph_objects.sunburst.Stream instance or dict with compatible properties text Sets text elements associated with each sector. If trace `textinfo` contains a "text" flag, these elements will be seen on the chart. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the font used for `textinfo`. textinfo Determines which trace information appear on the graph. textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. variables `currentPath`, `root`, `entry`, `percentRoot`, `percentEntry`, `percentParent`, `label` and `value`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user- driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user- driven changes if you give each trace a `uid` that stays with it as it moves. values Sets the values associated with each of the sectors. Use with `branchvalues` to determine how the values are summed. valuessrc Sets the source reference on plot.ly for values . visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). """, ), **kwargs ) import _plotly_utils.basevalidators class StreamtubeValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="streamtube", parent_name="", **kwargs): super(StreamtubeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Streamtube"), data_docs=kwargs.pop( "data_docs", """ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here u/v/w norm) or the bounds set in `cmin` and `cmax` Defaults to `false` when `cmin` and `cmax` are set by the user. cmax Sets the upper bound of the color domain. Value should have the same units as u/v/w norm and if set, `cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `cmin` and/or `cmax` to be equidistant to this point. Value should have the same units as u/v/w norm. Has no effect when `cauto` is `false`. cmin Sets the lower bound of the color domain. Value should have the same units as u/v/w norm and if set, `cmax` must be set as well. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.streamtube.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`cmin` and `cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Grey s,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Blues, Picnic,Rainbow,Portland,Jet,Hot,Blackbody,Earth ,Electric,Viridis,Cividis. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.streamtube.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs- events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `tubex`, `tubey`, `tubez`, `tubeu`, `tubev`, `tubew`, `norm` and `divergence`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . lighting plotly.graph_objects.streamtube.Lighting instance or dict with compatible properties lightposition plotly.graph_objects.streamtube.Lightposition instance or dict with compatible properties maxdisplayed The maximum number of displayed segments in a streamtube. meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the surface. Please note that in the case of using high `opacity` values for example a value greater than or equal to 0.5 on two surfaces (and 0.25 with four surfaces), an overlay of multiple transparent surfaces may not perfectly be sorted in depth by the webgl API. This behavior may be improved in the near future and is subject to change. reversescale Reverses the color mapping if true. If true, `cmin` will correspond to the last color in the array and `cmax` will correspond to the first color. scene Sets a reference between this trace's 3D coordinate system and a 3D scene. If "scene" (the default value), the (x,y,z) coordinates refer to `layout.scene`. If "scene2", the (x,y,z) coordinates refer to `layout.scene2`, and so on. showscale Determines whether or not a colorbar is displayed for this trace. sizeref The scaling factor for the streamtubes. The default is 1, which avoids two max divergence tubes from touching at adjacent starting positions. starts plotly.graph_objects.streamtube.Starts instance or dict with compatible properties stream plotly.graph_objects.streamtube.Stream instance or dict with compatible properties text Sets a text element associated with this trace. If trace `hoverinfo` contains a "text" flag, this text element will be seen in all hover labels. Note that streamtube traces do not support array `text` values. u Sets the x components of the vector field. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user- driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user- driven changes if you give each trace a `uid` that stays with it as it moves. usrc Sets the source reference on plot.ly for u . v Sets the y components of the vector field. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). vsrc Sets the source reference on plot.ly for v . w Sets the z components of the vector field. wsrc Sets the source reference on plot.ly for w . x Sets the x coordinates of the vector field. xsrc Sets the source reference on plot.ly for x . y Sets the y coordinates of the vector field. ysrc Sets the source reference on plot.ly for y . z Sets the z coordinates of the vector field. zsrc Sets the source reference on plot.ly for z . """, ), **kwargs ) import _plotly_utils.basevalidators class SplomValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="splom", parent_name="", **kwargs): super(SplomValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Splom"), data_docs=kwargs.pop( "data_docs", """ customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . diagonal plotly.graph_objects.splom.Diagonal instance or dict with compatible properties dimensions A tuple of plotly.graph_objects.splom.Dimension instances or dicts with compatible properties dimensiondefaults When used in a template (as layout.template.data.splom.dimensiondefaults), sets the default property values to use for elements of splom.dimensions hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.splom.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs- events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. marker plotly.graph_objects.splom.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. selected plotly.graph_objects.splom.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. showlowerhalf Determines whether or not subplots on the lower half from the diagonal are displayed. showupperhalf Determines whether or not subplots on the upper half from the diagonal are displayed. stream plotly.graph_objects.splom.Stream instance or dict with compatible properties text Sets text elements associated with each (x,y) pair to appear on hover. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user- driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user- driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.splom.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). xaxes Sets the list of x axes corresponding to dimensions of this splom trace. By default, a splom will match the first N xaxes where N is the number of input dimensions. Note that, in case where `diagonal.visible` is false and `showupperhalf` or `showlowerhalf` is false, this splom trace will generate one less x-axis and one less y-axis. yaxes Sets the list of y axes corresponding to dimensions of this splom trace. By default, a splom will match the first N yaxes where N is the number of input dimensions. Note that, in case where `diagonal.visible` is false and `showupperhalf` or `showlowerhalf` is false, this splom trace will generate one less x-axis and one less y-axis. """, ), **kwargs ) import _plotly_utils.basevalidators class ScatterternaryValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="scatterternary", parent_name="", **kwargs): super(ScatterternaryValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Scatterternary"), data_docs=kwargs.pop( "data_docs", """ a Sets the quantity of component `a` in each data point. If `a`, `b`, and `c` are all provided, they need not be normalized, only the relative values matter. If only two arrays are provided they must be normalized to match `ternary.sum`. asrc Sets the source reference on plot.ly for a . b Sets the quantity of component `a` in each data point. If `a`, `b`, and `c` are all provided, they need not be normalized, only the relative values matter. If only two arrays are provided they must be normalized to match `ternary.sum`. bsrc Sets the source reference on plot.ly for b . c Sets the quantity of component `a` in each data point. If `a`, `b`, and `c` are all provided, they need not be normalized, only the relative values matter. If only two arrays are provided they must be normalized to match `ternary.sum`. cliponaxis Determines whether or not markers and text nodes are clipped about the subplot axes. To show markers and text nodes above axis lines and tick labels, make sure to set `xaxis.layer` and `yaxis.layer` to *below traces*. connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. csrc Sets the source reference on plot.ly for c . customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . fill Sets the area to fill with a solid color. Use with `fillcolor` if not "none". scatterternary has a subset of the options available to scatter. "toself" connects the endpoints of the trace (or each segment of the trace if it has gaps) into a closed shape. "tonext" fills the space between two traces if one completely encloses the other (eg consecutive contour lines), and behaves like "toself" if there is no trace before it. "tonext" should not be used if one trace does not enclose the other. fillcolor Sets the fill color. Defaults to a half- transparent variant of the line color, marker color, or marker line color, whichever is available. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.scatterternary.Hoverlabel instance or dict with compatible properties hoveron Do the hover effects highlight individual points (markers or line points) or do they highlight filled regions? If the fill is "toself" or "tonext" and there are no markers or text, then the default is "fills", otherwise it is "points". hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs- events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (a,b,c) point. If a single string, the same string appears over all the data points. If an array of strings, the items are mapped in order to the the data points in (a,b,c). To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.scatterternary.Line instance or dict with compatible properties marker plotly.graph_objects.scatterternary.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . mode Determines the drawing mode for this scatter trace. If the provided `mode` includes "text" then the `text` elements appear at the coordinates. Otherwise, the `text` elements appear on hover. If there are less than 20 points and the trace is not stacked then the default is "lines+markers". Otherwise, "lines". name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. selected plotly.graph_objects.scatterternary.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.scatterternary.Stream instance or dict with compatible properties subplot Sets a reference between this trace's data coordinates and a ternary subplot. If "ternary" (the default value), the data refer to `layout.ternary`. If "ternary2", the data refer to `layout.ternary2`, and so on. sum The number each triplet should sum to, if only two of `a`, `b`, and `c` are provided. This overrides `ternary.sum` to normalize this specific trace, but does not affect the values displayed on the axes. 0 (or missing) means to use ternary.sum text Sets text elements associated with each (a,b,c) point. If a single string, the same string appears over all the data points. If an array of strings, the items are mapped in order to the the data points in (a,b,c). If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the text font. textposition Sets the positions of the `text` elements with respects to the (x,y) coordinates. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. variables `a`, `b`, `c` and `text`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user- driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user- driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.scatterternary.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). """, ), **kwargs ) import _plotly_utils.basevalidators class ScatterpolarglValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="scatterpolargl", parent_name="", **kwargs): super(ScatterpolarglValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Scatterpolargl"), data_docs=kwargs.pop( "data_docs", """ connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dr Sets the r coordinate step. dtheta Sets the theta coordinate step. By default, the `dtheta` step equals the subplot's period divided by the length of the `r` coordinates. fill Sets the area to fill with a solid color. Defaults to "none" unless this trace is stacked, then it gets "tonexty" ("tonextx") if `orientation` is "v" ("h") Use with `fillcolor` if not "none". "tozerox" and "tozeroy" fill to x=0 and y=0 respectively. "tonextx" and "tonexty" fill between the endpoints of this trace and the endpoints of the trace before it, connecting those endpoints with straight lines (to make a stacked area graph); if there is no trace before it, they behave like "tozerox" and "tozeroy". "toself" connects the endpoints of the trace (or each segment of the trace if it has gaps) into a closed shape. "tonext" fills the space between two traces if one completely encloses the other (eg consecutive contour lines), and behaves like "toself" if there is no trace before it. "tonext" should not be used if one trace does not enclose the other. Traces in a `stackgroup` will only fill to (or be filled to) other traces in the same group. With multiple `stackgroup`s or some traces stacked and some not, if fill-linked traces are not already consecutive, the later ones will be pushed down in the drawing order. fillcolor Sets the fill color. Defaults to a half- transparent variant of the line color, marker color, or marker line color, whichever is available. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.scatterpolargl.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs- events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.scatterpolargl.Line instance or dict with compatible properties marker plotly.graph_objects.scatterpolargl.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . mode Determines the drawing mode for this scatter trace. If the provided `mode` includes "text" then the `text` elements appear at the coordinates. Otherwise, the `text` elements appear on hover. If there are less than 20 points and the trace is not stacked then the default is "lines+markers". Otherwise, "lines". name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. r Sets the radial coordinates r0 Alternate to `r`. Builds a linear space of r coordinates. Use with `dr` where `r0` is the starting coordinate and `dr` the step. rsrc Sets the source reference on plot.ly for r . selected plotly.graph_objects.scatterpolargl.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.scatterpolargl.Stream instance or dict with compatible properties subplot Sets a reference between this trace's data coordinates and a polar subplot. If "polar" (the default value), the data refer to `layout.polar`. If "polar2", the data refer to `layout.polar2`, and so on. text Sets text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the text font. textposition Sets the positions of the `text` elements with respects to the (x,y) coordinates. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. variables `r`, `theta` and `text`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . theta Sets the angular coordinates theta0 Alternate to `theta`. Builds a linear space of theta coordinates. Use with `dtheta` where `theta0` is the starting coordinate and `dtheta` the step. thetasrc Sets the source reference on plot.ly for theta . thetaunit Sets the unit of input "theta" values. Has an effect only when on "linear" angular axes. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user- driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user- driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.scatterpolargl.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). """, ), **kwargs ) import _plotly_utils.basevalidators class ScatterpolarValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="scatterpolar", parent_name="", **kwargs): super(ScatterpolarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Scatterpolar"), data_docs=kwargs.pop( "data_docs", """ cliponaxis Determines whether or not markers and text nodes are clipped about the subplot axes. To show markers and text nodes above axis lines and tick labels, make sure to set `xaxis.layer` and `yaxis.layer` to *below traces*. connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dr Sets the r coordinate step. dtheta Sets the theta coordinate step. By default, the `dtheta` step equals the subplot's period divided by the length of the `r` coordinates. fill Sets the area to fill with a solid color. Use with `fillcolor` if not "none". scatterpolar has a subset of the options available to scatter. "toself" connects the endpoints of the trace (or each segment of the trace if it has gaps) into a closed shape. "tonext" fills the space between two traces if one completely encloses the other (eg consecutive contour lines), and behaves like "toself" if there is no trace before it. "tonext" should not be used if one trace does not enclose the other. fillcolor Sets the fill color. Defaults to a half- transparent variant of the line color, marker color, or marker line color, whichever is available. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.scatterpolar.Hoverlabel instance or dict with compatible properties hoveron Do the hover effects highlight individual points (markers or line points) or do they highlight filled regions? If the fill is "toself" or "tonext" and there are no markers or text, then the default is "fills", otherwise it is "points". hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs- events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.scatterpolar.Line instance or dict with compatible properties marker plotly.graph_objects.scatterpolar.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . mode Determines the drawing mode for this scatter trace. If the provided `mode` includes "text" then the `text` elements appear at the coordinates. Otherwise, the `text` elements appear on hover. If there are less than 20 points and the trace is not stacked then the default is "lines+markers". Otherwise, "lines". name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. r Sets the radial coordinates r0 Alternate to `r`. Builds a linear space of r coordinates. Use with `dr` where `r0` is the starting coordinate and `dr` the step. rsrc Sets the source reference on plot.ly for r . selected plotly.graph_objects.scatterpolar.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.scatterpolar.Stream instance or dict with compatible properties subplot Sets a reference between this trace's data coordinates and a polar subplot. If "polar" (the default value), the data refer to `layout.polar`. If "polar2", the data refer to `layout.polar2`, and so on. text Sets text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the text font. textposition Sets the positions of the `text` elements with respects to the (x,y) coordinates. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. variables `r`, `theta` and `text`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . theta Sets the angular coordinates theta0 Alternate to `theta`. Builds a linear space of theta coordinates. Use with `dtheta` where `theta0` is the starting coordinate and `dtheta` the step. thetasrc Sets the source reference on plot.ly for theta . thetaunit Sets the unit of input "theta" values. Has an effect only when on "linear" angular axes. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user- driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user- driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.scatterpolar.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). """, ), **kwargs ) import _plotly_utils.basevalidators class ScattermapboxValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="scattermapbox", parent_name="", **kwargs): super(ScattermapboxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Scattermapbox"), data_docs=kwargs.pop( "data_docs", """ below Determines if this scattermapbox trace's layers are to be inserted before the layer with the specified ID. By default, scattermapbox layers are inserted above all the base layers. To place the scattermapbox layers above every other layer, set `below` to "''". connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . fill Sets the area to fill with a solid color. Use with `fillcolor` if not "none". "toself" connects the endpoints of the trace (or each segment of the trace if it has gaps) into a closed shape. fillcolor Sets the fill color. Defaults to a half- transparent variant of the line color, marker color, or marker line color, whichever is available. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.scattermapbox.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs- events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (lon,lat) pair If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (lon,lat) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . lat Sets the latitude coordinates (in degrees North). latsrc Sets the source reference on plot.ly for lat . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.scattermapbox.Line instance or dict with compatible properties lon Sets the longitude coordinates (in degrees East). lonsrc Sets the source reference on plot.ly for lon . marker plotly.graph_objects.scattermapbox.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . mode Determines the drawing mode for this scatter trace. If the provided `mode` includes "text" then the `text` elements appear at the coordinates. Otherwise, the `text` elements appear on hover. name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. selected plotly.graph_objects.scattermapbox.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.scattermapbox.Stream instance or dict with compatible properties subplot Sets a reference between this trace's data coordinates and a mapbox subplot. If "mapbox" (the default value), the data refer to `layout.mapbox`. If "mapbox2", the data refer to `layout.mapbox2`, and so on. text Sets text elements associated with each (lon,lat) pair If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (lon,lat) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the icon text font (color=mapbox.layer.paint.text-color, size=mapbox.layer.layout.text-size). Has an effect only when `type` is set to "symbol". textposition Sets the positions of the `text` elements with respects to the (x,y) coordinates. textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. variables `lat`, `lon` and `text`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user- driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user- driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.scattermapbox.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). """, ), **kwargs ) import _plotly_utils.basevalidators class ScatterglValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="scattergl", parent_name="", **kwargs): super(ScatterglValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Scattergl"), data_docs=kwargs.pop( "data_docs", """ connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dx Sets the x coordinate step. See `x0` for more info. dy Sets the y coordinate step. See `y0` for more info. error_x plotly.graph_objects.scattergl.ErrorX instance or dict with compatible properties error_y plotly.graph_objects.scattergl.ErrorY instance or dict with compatible properties fill Sets the area to fill with a solid color. Defaults to "none" unless this trace is stacked, then it gets "tonexty" ("tonextx") if `orientation` is "v" ("h") Use with `fillcolor` if not "none". "tozerox" and "tozeroy" fill to x=0 and y=0 respectively. "tonextx" and "tonexty" fill between the endpoints of this trace and the endpoints of the trace before it, connecting those endpoints with straight lines (to make a stacked area graph); if there is no trace before it, they behave like "tozerox" and "tozeroy". "toself" connects the endpoints of the trace (or each segment of the trace if it has gaps) into a closed shape. "tonext" fills the space between two traces if one completely encloses the other (eg consecutive contour lines), and behaves like "toself" if there is no trace before it. "tonext" should not be used if one trace does not enclose the other. Traces in a `stackgroup` will only fill to (or be filled to) other traces in the same group. With multiple `stackgroup`s or some traces stacked and some not, if fill-linked traces are not already consecutive, the later ones will be pushed down in the drawing order. fillcolor Sets the fill color. Defaults to a half- transparent variant of the line color, marker color, or marker line color, whichever is available. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.scattergl.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs- events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.scattergl.Line instance or dict with compatible properties marker plotly.graph_objects.scattergl.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . mode Determines the drawing mode for this scatter trace. name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. selected plotly.graph_objects.scattergl.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.scattergl.Stream instance or dict with compatible properties text Sets text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the text font. textposition Sets the positions of the `text` elements with respects to the (x,y) coordinates. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. texttemplatesrc Sets the source reference on plot.ly for texttemplate . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user- driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user- driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.scattergl.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the x coordinates. x0 Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . y Sets the y coordinates. y0 Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . """, ), **kwargs ) import _plotly_utils.basevalidators class ScattergeoValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="scattergeo", parent_name="", **kwargs): super(ScattergeoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Scattergeo"), data_docs=kwargs.pop( "data_docs", """ connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . fill Sets the area to fill with a solid color. Use with `fillcolor` if not "none". "toself" connects the endpoints of the trace (or each segment of the trace if it has gaps) into a closed shape. fillcolor Sets the fill color. Defaults to a half- transparent variant of the line color, marker color, or marker line color, whichever is available. geo Sets a reference between this trace's geospatial coordinates and a geographic map. If "geo" (the default value), the geospatial coordinates refer to `layout.geo`. If "geo2", the geospatial coordinates refer to `layout.geo2`, and so on. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.scattergeo.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs- events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (lon,lat) pair or item in `locations`. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (lon,lat) or `locations` coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . lat Sets the latitude coordinates (in degrees North). latsrc Sets the source reference on plot.ly for lat . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.scattergeo.Line instance or dict with compatible properties locationmode Determines the set of locations used to match entries in `locations` to regions on the map. locations Sets the coordinates via location IDs or names. Coordinates correspond to the centroid of each location given. See `locationmode` for more info. locationssrc Sets the source reference on plot.ly for locations . lon Sets the longitude coordinates (in degrees East). lonsrc Sets the source reference on plot.ly for lon . marker plotly.graph_objects.scattergeo.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . mode Determines the drawing mode for this scatter trace. If the provided `mode` includes "text" then the `text` elements appear at the coordinates. Otherwise, the `text` elements appear on hover. If there are less than 20 points and the trace is not stacked then the default is "lines+markers". Otherwise, "lines". name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. selected plotly.graph_objects.scattergeo.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.scattergeo.Stream instance or dict with compatible properties text Sets text elements associated with each (lon,lat) pair or item in `locations`. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (lon,lat) or `locations` coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the text font. textposition Sets the positions of the `text` elements with respects to the (x,y) coordinates. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. variables `lat`, `lon`, `location` and `text`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user- driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user- driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.scattergeo.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). """, ), **kwargs ) import _plotly_utils.basevalidators class ScattercarpetValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="scattercarpet", parent_name="", **kwargs): super(ScattercarpetValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Scattercarpet"), data_docs=kwargs.pop( "data_docs", """ a Sets the a-axis coordinates. asrc Sets the source reference on plot.ly for a . b Sets the b-axis coordinates. bsrc Sets the source reference on plot.ly for b . carpet An identifier for this carpet, so that `scattercarpet` and `contourcarpet` traces can specify a carpet plot on which they lie connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . fill Sets the area to fill with a solid color. Use with `fillcolor` if not "none". scatterternary has a subset of the options available to scatter. "toself" connects the endpoints of the trace (or each segment of the trace if it has gaps) into a closed shape. "tonext" fills the space between two traces if one completely encloses the other (eg consecutive contour lines), and behaves like "toself" if there is no trace before it. "tonext" should not be used if one trace does not enclose the other. fillcolor Sets the fill color. Defaults to a half- transparent variant of the line color, marker color, or marker line color, whichever is available. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.scattercarpet.Hoverlabel instance or dict with compatible properties hoveron Do the hover effects highlight individual points (markers or line points) or do they highlight filled regions? If the fill is "toself" or "tonext" and there are no markers or text, then the default is "fills", otherwise it is "points". hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs- events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (a,b) point. If a single string, the same string appears over all the data points. If an array of strings, the items are mapped in order to the the data points in (a,b). To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.scattercarpet.Line instance or dict with compatible properties marker plotly.graph_objects.scattercarpet.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . mode Determines the drawing mode for this scatter trace. If the provided `mode` includes "text" then the `text` elements appear at the coordinates. Otherwise, the `text` elements appear on hover. If there are less than 20 points and the trace is not stacked then the default is "lines+markers". Otherwise, "lines". name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. selected plotly.graph_objects.scattercarpet.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.scattercarpet.Stream instance or dict with compatible properties text Sets text elements associated with each (a,b) point. If a single string, the same string appears over all the data points. If an array of strings, the items are mapped in order to the the data points in (a,b). If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the text font. textposition Sets the positions of the `text` elements with respects to the (x,y) coordinates. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. variables `a`, `b` and `text`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user- driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user- driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.scattercarpet.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. """, ), **kwargs ) import _plotly_utils.basevalidators class Scatter3dValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="scatter3d", parent_name="", **kwargs): super(Scatter3dValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Scatter3d"), data_docs=kwargs.pop( "data_docs", """ connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . error_x plotly.graph_objects.scatter3d.ErrorX instance or dict with compatible properties error_y plotly.graph_objects.scatter3d.ErrorY instance or dict with compatible properties error_z plotly.graph_objects.scatter3d.ErrorZ instance or dict with compatible properties hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.scatter3d.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs- events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets text elements associated with each (x,y,z) triplet. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y,z) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.scatter3d.Line instance or dict with compatible properties marker plotly.graph_objects.scatter3d.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . mode Determines the drawing mode for this scatter trace. If the provided `mode` includes "text" then the `text` elements appear at the coordinates. Otherwise, the `text` elements appear on hover. If there are less than 20 points and the trace is not stacked then the default is "lines+markers". Otherwise, "lines". name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. projection plotly.graph_objects.scatter3d.Projection instance or dict with compatible properties scene Sets a reference between this trace's 3D coordinate system and a 3D scene. If "scene" (the default value), the (x,y,z) coordinates refer to `layout.scene`. If "scene2", the (x,y,z) coordinates refer to `layout.scene2`, and so on. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.scatter3d.Stream instance or dict with compatible properties surfaceaxis If "-1", the scatter points are not fill with a surface If 0, 1, 2, the scatter points are filled with a Delaunay surface about the x, y, z respectively. surfacecolor Sets the surface fill color. text Sets text elements associated with each (x,y,z) triplet. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y,z) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont plotly.graph_objects.scatter3d.Textfont instance or dict with compatible properties textposition Sets the positions of the `text` elements with respects to the (x,y) coordinates. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. texttemplatesrc Sets the source reference on plot.ly for texttemplate . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user- driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user- driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the x coordinates. xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . y Sets the y coordinates. ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . z Sets the z coordinates. zcalendar Sets the calendar system to use with `z` date data. zsrc Sets the source reference on plot.ly for z . """, ), **kwargs ) import _plotly_utils.basevalidators class ScatterValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="scatter", parent_name="", **kwargs): super(ScatterValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Scatter"), data_docs=kwargs.pop( "data_docs", """ cliponaxis Determines whether or not markers and text nodes are clipped about the subplot axes. To show markers and text nodes above axis lines and tick labels, make sure to set `xaxis.layer` and `yaxis.layer` to *below traces*. connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dx Sets the x coordinate step. See `x0` for more info. dy Sets the y coordinate step. See `y0` for more info. error_x plotly.graph_objects.scatter.ErrorX instance or dict with compatible properties error_y plotly.graph_objects.scatter.ErrorY instance or dict with compatible properties fill Sets the area to fill with a solid color. Defaults to "none" unless this trace is stacked, then it gets "tonexty" ("tonextx") if `orientation` is "v" ("h") Use with `fillcolor` if not "none". "tozerox" and "tozeroy" fill to x=0 and y=0 respectively. "tonextx" and "tonexty" fill between the endpoints of this trace and the endpoints of the trace before it, connecting those endpoints with straight lines (to make a stacked area graph); if there is no trace before it, they behave like "tozerox" and "tozeroy". "toself" connects the endpoints of the trace (or each segment of the trace if it has gaps) into a closed shape. "tonext" fills the space between two traces if one completely encloses the other (eg consecutive contour lines), and behaves like "toself" if there is no trace before it. "tonext" should not be used if one trace does not enclose the other. Traces in a `stackgroup` will only fill to (or be filled to) other traces in the same group. With multiple `stackgroup`s or some traces stacked and some not, if fill-linked traces are not already consecutive, the later ones will be pushed down in the drawing order. fillcolor Sets the fill color. Defaults to a half- transparent variant of the line color, marker color, or marker line color, whichever is available. groupnorm Only relevant when `stackgroup` is used, and only the first `groupnorm` found in the `stackgroup` will be used - including if `visible` is "legendonly" but not if it is `false`. Sets the normalization for the sum of this `stackgroup`. With "fraction", the value of each trace at each location is divided by the sum of all trace values at that location. "percent" is the same but multiplied by 100 to show percentages. If there are multiple subplots, or multiple `stackgroup`s on one subplot, each will be normalized within its own set. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.scatter.Hoverlabel instance or dict with compatible properties hoveron Do the hover effects highlight individual points (markers or line points) or do they highlight filled regions? If the fill is "toself" or "tonext" and there are no markers or text, then the default is "fills", otherwise it is "points". hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs- events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.scatter.Line instance or dict with compatible properties marker plotly.graph_objects.scatter.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . mode Determines the drawing mode for this scatter trace. If the provided `mode` includes "text" then the `text` elements appear at the coordinates. Otherwise, the `text` elements appear on hover. If there are less than 20 points and the trace is not stacked then the default is "lines+markers". Otherwise, "lines". name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. orientation Only relevant when `stackgroup` is used, and only the first `orientation` found in the `stackgroup` will be used - including if `visible` is "legendonly" but not if it is `false`. Sets the stacking direction. With "v" ("h"), the y (x) values of subsequent traces are added. Also affects the default value of `fill`. r r coordinates in scatter traces are deprecated!Please switch to the "scatterpolar" trace type.Sets the radial coordinatesfor legacy polar chart only. rsrc Sets the source reference on plot.ly for r . selected plotly.graph_objects.scatter.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stackgaps Only relevant when `stackgroup` is used, and only the first `stackgaps` found in the `stackgroup` will be used - including if `visible` is "legendonly" but not if it is `false`. Determines how we handle locations at which other traces in this group have data but this one does not. With *infer zero* we insert a zero at these locations. With "interpolate" we linearly interpolate between existing values, and extrapolate a constant beyond the existing values. stackgroup Set several scatter traces (on the same subplot) to the same stackgroup in order to add their y values (or their x values if `orientation` is "h"). If blank or omitted this trace will not be stacked. Stacking also turns `fill` on by default, using "tonexty" ("tonextx") if `orientation` is "h" ("v") and sets the default `mode` to "lines" irrespective of point count. You can only stack on a numeric (linear or log) axis. Traces in a `stackgroup` will only fill to (or be filled to) other traces in the same group. With multiple `stackgroup`s or some traces stacked and some not, if fill-linked traces are not already consecutive, the later ones will be pushed down in the drawing order. stream plotly.graph_objects.scatter.Stream instance or dict with compatible properties t t coordinates in scatter traces are deprecated!Please switch to the "scatterpolar" trace type.Sets the angular coordinatesfor legacy polar chart only. text Sets text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the text font. textposition Sets the positions of the `text` elements with respects to the (x,y) coordinates. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. texttemplatesrc Sets the source reference on plot.ly for texttemplate . tsrc Sets the source reference on plot.ly for t . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user- driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user- driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.scatter.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the x coordinates. x0 Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . y Sets the y coordinates. y0 Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . """, ), **kwargs ) import _plotly_utils.basevalidators class SankeyValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="sankey", parent_name="", **kwargs): super(SankeyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Sankey"), data_docs=kwargs.pop( "data_docs", """ arrangement If value is `snap` (the default), the node arrangement is assisted by automatic snapping of elements to preserve space between nodes specified via `nodepad`. If value is `perpendicular`, the nodes can only move along a line perpendicular to the flow. If value is `freeform`, the nodes can freely move on the plane. If value is `fixed`, the nodes are stationary. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . domain plotly.graph_objects.sankey.Domain instance or dict with compatible properties hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. Note that this attribute is superseded by `node.hoverinfo` and `node.hoverinfo` for nodes and links respectively. hoverlabel plotly.graph_objects.sankey.Hoverlabel instance or dict with compatible properties ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . link The links of the Sankey plot. meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. node The nodes of the Sankey plot. orientation Sets the orientation of the Sankey diagram. selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. stream plotly.graph_objects.sankey.Stream instance or dict with compatible properties textfont Sets the font for node labels uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user- driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user- driven changes if you give each trace a `uid` that stays with it as it moves. valueformat Sets the value formatting rule using d3 formatting mini-language which is similar to those of Python. See https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format valuesuffix Adds a unit to follow the value in the hover tooltip. Add a space if a separation is necessary from the value. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). """, ), **kwargs ) import _plotly_utils.basevalidators class PointcloudValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="pointcloud", parent_name="", **kwargs): super(PointcloudValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Pointcloud"), data_docs=kwargs.pop( "data_docs", """ customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.pointcloud.Hoverlabel instance or dict with compatible properties ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . indices A sequential value, 0..n, supply it to avoid creating this array inside plotting. If specified, it must be a typed `Int32Array` array. Its length must be equal to or greater than the number of points. For the best performance and memory use, create one large `indices` typed array that is guaranteed to be at least as long as the largest number of points during use, and reuse it on each `Plotly.restyle()` call. indicessrc Sets the source reference on plot.ly for indices . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. marker plotly.graph_objects.pointcloud.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.pointcloud.Stream instance or dict with compatible properties text Sets text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user- driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user- driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the x coordinates. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xbounds Specify `xbounds` in the shape of `[xMin, xMax] to avoid looping through the `xy` typed array. Use it in conjunction with `xy` and `ybounds` for the performance benefits. xboundssrc Sets the source reference on plot.ly for xbounds . xsrc Sets the source reference on plot.ly for x . xy Faster alternative to specifying `x` and `y` separately. If supplied, it must be a typed `Float32Array` array that represents points such that `xy[i * 2] = x[i]` and `xy[i * 2 + 1] = y[i]` xysrc Sets the source reference on plot.ly for xy . y Sets the y coordinates. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ybounds Specify `ybounds` in the shape of `[yMin, yMax] to avoid looping through the `xy` typed array. Use it in conjunction with `xy` and `xbounds` for the performance benefits. yboundssrc Sets the source reference on plot.ly for ybounds . ysrc Sets the source reference on plot.ly for y . """, ), **kwargs ) import _plotly_utils.basevalidators class PieValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="pie", parent_name="", **kwargs): super(PieValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Pie"), data_docs=kwargs.pop( "data_docs", """ automargin Determines whether outside text labels can push the margins. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . direction Specifies the direction at which succeeding sectors follow one another. dlabel Sets the label step. See `label0` for more info. domain plotly.graph_objects.pie.Domain instance or dict with compatible properties hole Sets the fraction of the radius to cut out of the pie. Use this to make a donut chart. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.pie.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs- events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `label`, `color`, `value`, `percent` and `text`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each sector. If a single string, the same string appears for all data points. If an array of string, the items are mapped in order of this trace's sectors. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . insidetextfont Sets the font used for `textinfo` lying inside the sector. label0 Alternate to `labels`. Builds a numeric set of labels. Use with `dlabel` where `label0` is the starting label and `dlabel` the step. labels Sets the sector labels. If `labels` entries are duplicated, we sum associated `values` or simply count occurrences if `values` is not provided. For other array attributes (including color) we use the first non-empty entry among all occurrences of the label. labelssrc Sets the source reference on plot.ly for labels . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. marker plotly.graph_objects.pie.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. outsidetextfont Sets the font used for `textinfo` lying outside the sector. pull Sets the fraction of larger radius to pull the sectors out from the center. This can be a constant to pull all slices apart from each other equally or an array to highlight one or more slices. pullsrc Sets the source reference on plot.ly for pull . rotation Instead of the first slice starting at 12 o'clock, rotate to some other angle. scalegroup If there are multiple pie charts that should be sized according to their totals, link them by providing a non-empty group id here shared by every trace in the same group. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. sort Determines whether or not the sectors are reordered from largest to smallest. stream plotly.graph_objects.pie.Stream instance or dict with compatible properties text Sets text elements associated with each sector. If trace `textinfo` contains a "text" flag, these elements will be seen on the chart. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the font used for `textinfo`. textinfo Determines which trace information appear on the graph. textposition Specifies the location of the `textinfo`. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. variables `label`, `color`, `value`, `percent` and `text`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . title plotly.graph_objects.pie.Title instance or dict with compatible properties titlefont Deprecated: Please use pie.title.font instead. Sets the font used for `title`. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleposition Deprecated: Please use pie.title.position instead. Specifies the location of the `title`. Note that the title's position used to be set by the now deprecated `titleposition` attribute. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user- driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user- driven changes if you give each trace a `uid` that stays with it as it moves. values Sets the values of the sectors. If omitted, we count occurrences of each label. valuessrc Sets the source reference on plot.ly for values . visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). """, ), **kwargs ) import _plotly_utils.basevalidators class ParcoordsValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="parcoords", parent_name="", **kwargs): super(ParcoordsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Parcoords"), data_docs=kwargs.pop( "data_docs", """ customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dimensions The dimensions (variables) of the parallel coordinates chart. 2..60 dimensions are supported. dimensiondefaults When used in a template (as layout.template.dat a.parcoords.dimensiondefaults), sets the default property values to use for elements of parcoords.dimensions domain plotly.graph_objects.parcoords.Domain instance or dict with compatible properties ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . labelangle Sets the angle of the labels with respect to the horizontal. For example, a `tickangle` of -90 draws the labels vertically. Tilted labels with "labelangle" may be positioned better inside margins when `labelposition` is set to "bottom". labelfont Sets the font for the `dimension` labels. labelside Specifies the location of the `label`. "top" positions labels above, next to the title "bottom" positions labels below the graph Tilted labels with "labelangle" may be positioned better inside margins when `labelposition` is set to "bottom". line plotly.graph_objects.parcoords.Line instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. rangefont Sets the font for the `dimension` range values. stream plotly.graph_objects.parcoords.Stream instance or dict with compatible properties tickfont Sets the font for the `dimension` tick values. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user- driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user- driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). """, ), **kwargs ) import _plotly_utils.basevalidators class ParcatsValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="parcats", parent_name="", **kwargs): super(ParcatsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Parcats"), data_docs=kwargs.pop( "data_docs", """ arrangement Sets the drag interaction mode for categories and dimensions. If `perpendicular`, the categories can only move along a line perpendicular to the paths. If `freeform`, the categories can freely move on the plane. If `fixed`, the categories and dimensions are stationary. bundlecolors Sort paths so that like colors are bundled together within each category. counts The number of observations represented by each state. Defaults to 1 so that each state represents one observation countssrc Sets the source reference on plot.ly for counts . dimensions The dimensions (variables) of the parallel categories diagram. dimensiondefaults When used in a template (as layout.template.dat a.parcats.dimensiondefaults), sets the default property values to use for elements of parcats.dimensions domain plotly.graph_objects.parcats.Domain instance or dict with compatible properties hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoveron Sets the hover interaction mode for the parcats diagram. If `category`, hover interaction take place per category. If `color`, hover interactions take place per color per category. If `dimension`, hover interactions take place across all categories per dimension. hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs- events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `count`, `probability`, `category`, `categorycount`, `colorcount` and `bandcolorcount`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. labelfont Sets the font for the `dimension` labels. line plotly.graph_objects.parcats.Line instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. sortpaths Sets the path sorting algorithm. If `forward`, sort paths based on dimension categories from left to right. If `backward`, sort paths based on dimensions categories from right to left. stream plotly.graph_objects.parcats.Stream instance or dict with compatible properties tickfont Sets the font for the `category` labels. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user- driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user- driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). """, ), **kwargs ) import _plotly_utils.basevalidators class OhlcValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="ohlc", parent_name="", **kwargs): super(OhlcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Ohlc"), data_docs=kwargs.pop( "data_docs", """ close Sets the close values. closesrc Sets the source reference on plot.ly for close . customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . decreasing plotly.graph_objects.ohlc.Decreasing instance or dict with compatible properties high Sets the high values. highsrc Sets the source reference on plot.ly for high . hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.ohlc.Hoverlabel instance or dict with compatible properties hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . increasing plotly.graph_objects.ohlc.Increasing instance or dict with compatible properties legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.ohlc.Line instance or dict with compatible properties low Sets the low values. lowsrc Sets the source reference on plot.ly for low . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. open Sets the open values. opensrc Sets the source reference on plot.ly for open . selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.ohlc.Stream instance or dict with compatible properties text Sets hover text elements associated with each sample point. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to this trace's sample points. textsrc Sets the source reference on plot.ly for text . tickwidth Sets the width of the open/close tick marks relative to the "x" minimal interval. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user- driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user- driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the x coordinates. If absent, linear coordinate will be generated. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. """, ), **kwargs ) import _plotly_utils.basevalidators class Mesh3dValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="mesh3d", parent_name="", **kwargs): super(Mesh3dValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Mesh3d"), data_docs=kwargs.pop( "data_docs", """ alphahull Determines how the mesh surface triangles are derived from the set of vertices (points) represented by the `x`, `y` and `z` arrays, if the `i`, `j`, `k` arrays are not supplied. For general use of `mesh3d` it is preferred that `i`, `j`, `k` are supplied. If "-1", Delaunay triangulation is used, which is mainly suitable if the mesh is a single, more or less layer surface that is perpendicular to `delaunayaxis`. In case the `delaunayaxis` intersects the mesh surface at more than one point it will result triangles that are very long in the dimension of `delaunayaxis`. If ">0", the alpha-shape algorithm is used. In this case, the positive `alphahull` value signals the use of the alpha-shape algorithm, _and_ its value acts as the parameter for the mesh fitting. If 0, the convex-hull algorithm is used. It is suitable for convex bodies or if the intention is to enclose the `x`, `y` and `z` point set into a convex hull. autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here `intensity`) or the bounds set in `cmin` and `cmax` Defaults to `false` when `cmin` and `cmax` are set by the user. cmax Sets the upper bound of the color domain. Value should have the same units as `intensity` and if set, `cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `cmin` and/or `cmax` to be equidistant to this point. Value should have the same units as `intensity`. Has no effect when `cauto` is `false`. cmin Sets the lower bound of the color domain. Value should have the same units as `intensity` and if set, `cmax` must be set as well. color Sets the color of the whole mesh coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.mesh3d.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`cmin` and `cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Grey s,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Blues, Picnic,Rainbow,Portland,Jet,Hot,Blackbody,Earth ,Electric,Viridis,Cividis. contour plotly.graph_objects.mesh3d.Contour instance or dict with compatible properties customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . delaunayaxis Sets the Delaunay axis, which is the axis that is perpendicular to the surface of the Delaunay triangulation. It has an effect if `i`, `j`, `k` are not provided and `alphahull` is set to indicate Delaunay triangulation. facecolor Sets the color of each face Overrides "color" and "vertexcolor". facecolorsrc Sets the source reference on plot.ly for facecolor . flatshading Determines whether or not normal smoothing is applied to the meshes, creating meshes with an angular, low-poly look via flat reflections. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.mesh3d.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs- events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . i A vector of vertex indices, i.e. integer values between 0 and the length of the vertex vectors, representing the "first" vertex of a triangle. For example, `{i[m], j[m], k[m]}` together represent face m (triangle m) in the mesh, where `i[m] = n` points to the triplet `{x[n], y[n], z[n]}` in the vertex arrays. Therefore, each element in `i` represents a point in space, which is the first vertex of a triangle. ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . intensity Sets the vertex intensity values, used for plotting fields on meshes intensitysrc Sets the source reference on plot.ly for intensity . isrc Sets the source reference on plot.ly for i . j A vector of vertex indices, i.e. integer values between 0 and the length of the vertex vectors, representing the "second" vertex of a triangle. For example, `{i[m], j[m], k[m]}` together represent face m (triangle m) in the mesh, where `j[m] = n` points to the triplet `{x[n], y[n], z[n]}` in the vertex arrays. Therefore, each element in `j` represents a point in space, which is the second vertex of a triangle. jsrc Sets the source reference on plot.ly for j . k A vector of vertex indices, i.e. integer values between 0 and the length of the vertex vectors, representing the "third" vertex of a triangle. For example, `{i[m], j[m], k[m]}` together represent face m (triangle m) in the mesh, where `k[m] = n` points to the triplet `{x[n], y[n], z[n]}` in the vertex arrays. Therefore, each element in `k` represents a point in space, which is the third vertex of a triangle. ksrc Sets the source reference on plot.ly for k . lighting plotly.graph_objects.mesh3d.Lighting instance or dict with compatible properties lightposition plotly.graph_objects.mesh3d.Lightposition instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the surface. Please note that in the case of using high `opacity` values for example a value greater than or equal to 0.5 on two surfaces (and 0.25 with four surfaces), an overlay of multiple transparent surfaces may not perfectly be sorted in depth by the webgl API. This behavior may be improved in the near future and is subject to change. reversescale Reverses the color mapping if true. If true, `cmin` will correspond to the last color in the array and `cmax` will correspond to the first color. scene Sets a reference between this trace's 3D coordinate system and a 3D scene. If "scene" (the default value), the (x,y,z) coordinates refer to `layout.scene`. If "scene2", the (x,y,z) coordinates refer to `layout.scene2`, and so on. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.mesh3d.Stream instance or dict with compatible properties text Sets the text elements associated with the vertices. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user- driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user- driven changes if you give each trace a `uid` that stays with it as it moves. vertexcolor Sets the color of each vertex Overrides "color". While Red, green and blue colors are in the range of 0 and 255; in the case of having vertex color data in RGBA format, the alpha color should be normalized to be between 0 and 1. vertexcolorsrc Sets the source reference on plot.ly for vertexcolor . visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the X coordinates of the vertices. The nth element of vectors `x`, `y` and `z` jointly represent the X, Y and Z coordinates of the nth vertex. xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . y Sets the Y coordinates of the vertices. The nth element of vectors `x`, `y` and `z` jointly represent the X, Y and Z coordinates of the nth vertex. ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . z Sets the Z coordinates of the vertices. The nth element of vectors `x`, `y` and `z` jointly represent the X, Y and Z coordinates of the nth vertex. zcalendar Sets the calendar system to use with `z` date data. zsrc Sets the source reference on plot.ly for z . """, ), **kwargs ) import _plotly_utils.basevalidators class IsosurfaceValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="isosurface", parent_name="", **kwargs): super(IsosurfaceValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Isosurface"), data_docs=kwargs.pop( "data_docs", """ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. caps plotly.graph_objects.isosurface.Caps instance or dict with compatible properties cauto Determines whether or not the color domain is computed with respect to the input data (here `value`) or the bounds set in `cmin` and `cmax` Defaults to `false` when `cmin` and `cmax` are set by the user. cmax Sets the upper bound of the color domain. Value should have the same units as `value` and if set, `cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `cmin` and/or `cmax` to be equidistant to this point. Value should have the same units as `value`. Has no effect when `cauto` is `false`. cmin Sets the lower bound of the color domain. Value should have the same units as `value` and if set, `cmax` must be set as well. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.isosurface.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`cmin` and `cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Grey s,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Blues, Picnic,Rainbow,Portland,Jet,Hot,Blackbody,Earth ,Electric,Viridis,Cividis. contour plotly.graph_objects.isosurface.Contour instance or dict with compatible properties customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . flatshading Determines whether or not normal smoothing is applied to the meshes, creating meshes with an angular, low-poly look via flat reflections. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.isosurface.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs- events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . isomax Sets the maximum boundary for iso-surface plot. isomin Sets the minimum boundary for iso-surface plot. lighting plotly.graph_objects.isosurface.Lighting instance or dict with compatible properties lightposition plotly.graph_objects.isosurface.Lightposition instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the surface. Please note that in the case of using high `opacity` values for example a value greater than or equal to 0.5 on two surfaces (and 0.25 with four surfaces), an overlay of multiple transparent surfaces may not perfectly be sorted in depth by the webgl API. This behavior may be improved in the near future and is subject to change. reversescale Reverses the color mapping if true. If true, `cmin` will correspond to the last color in the array and `cmax` will correspond to the first color. scene Sets a reference between this trace's 3D coordinate system and a 3D scene. If "scene" (the default value), the (x,y,z) coordinates refer to `layout.scene`. If "scene2", the (x,y,z) coordinates refer to `layout.scene2`, and so on. showscale Determines whether or not a colorbar is displayed for this trace. slices plotly.graph_objects.isosurface.Slices instance or dict with compatible properties spaceframe plotly.graph_objects.isosurface.Spaceframe instance or dict with compatible properties stream plotly.graph_objects.isosurface.Stream instance or dict with compatible properties surface plotly.graph_objects.isosurface.Surface instance or dict with compatible properties text Sets the text elements associated with the vertices. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user- driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user- driven changes if you give each trace a `uid` that stays with it as it moves. value Sets the 4th dimension (value) of the vertices. valuesrc Sets the source reference on plot.ly for value . visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the X coordinates of the vertices on X axis. xsrc Sets the source reference on plot.ly for x . y Sets the Y coordinates of the vertices on Y axis. ysrc Sets the source reference on plot.ly for y . z Sets the Z coordinates of the vertices on Z axis. zsrc Sets the source reference on plot.ly for z . """, ), **kwargs ) import _plotly_utils.basevalidators class IndicatorValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="indicator", parent_name="", **kwargs): super(IndicatorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Indicator"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the `text` within the box. Note that this attribute has no effect if an angular gauge is displayed: in this case, it is always centered customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . delta plotly.graph_objects.indicator.Delta instance or dict with compatible properties domain plotly.graph_objects.indicator.Domain instance or dict with compatible properties gauge The gauge of the Indicator plot. ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . mode Determines how the value is displayed on the graph. `number` displays the value numerically in text. `delta` displays the difference to a reference value in text. Finally, `gauge` displays the value graphically on an axis. name Sets the trace name. The trace name appear as the legend item and on hover. number plotly.graph_objects.indicator.Number instance or dict with compatible properties stream plotly.graph_objects.indicator.Stream instance or dict with compatible properties title plotly.graph_objects.indicator.Title instance or dict with compatible properties uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user- driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user- driven changes if you give each trace a `uid` that stays with it as it moves. value Sets the number to be displayed. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). """, ), **kwargs ) import _plotly_utils.basevalidators class ImageValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="image", parent_name="", **kwargs): super(ImageValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Image"), data_docs=kwargs.pop( "data_docs", """ colormodel Color model used to map the numerical color components described in `z` into colors. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dx Set the pixel's horizontal size. dy Set the pixel's vertical size hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.image.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs- events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `z`, `color` and `colormodel`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. stream plotly.graph_objects.image.Stream instance or dict with compatible properties text Sets the text elements associated with each z value. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user- driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user- driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x0 Set the image's x position. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. y0 Set the image's y position. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. z A 2-dimensional array in which each element is an array of 3 or 4 numbers representing a color. zmax Array defining the higher bound for each color component. Note that the default value will depend on the colormodel. For the `rgb` colormodel, it is [255, 255, 255]. For the `rgba` colormodel, it is [255, 255, 255, 1]. For the `hsl` colormodel, it is [360, 100, 100]. For the `hsla` colormodel, it is [360, 100, 100, 1]. zmin Array defining the lower bound for each color component. Note that the default value will depend on the colormodel. For the `rgb` colormodel, it is [0, 0, 0]. For the `rgba` colormodel, it is [0, 0, 0, 0]. For the `hsl` colormodel, it is [0, 0, 0]. For the `hsla` colormodel, it is [0, 0, 0, 0]. zsrc Sets the source reference on plot.ly for z . """, ), **kwargs ) import _plotly_utils.basevalidators class Histogram2dContourValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="histogram2dcontour", parent_name="", **kwargs): super(Histogram2dContourValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Histogram2dContour"), data_docs=kwargs.pop( "data_docs", """ autobinx Obsolete: since v1.42 each bin attribute is auto-determined separately and `autobinx` is not needed. However, we accept `autobinx: true` or `false` and will update `xbins` accordingly before deleting `autobinx` from the trace. autobiny Obsolete: since v1.42 each bin attribute is auto-determined separately and `autobiny` is not needed. However, we accept `autobiny: true` or `false` and will update `ybins` accordingly before deleting `autobiny` from the trace. autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. autocontour Determines whether or not the contour level attributes are picked by an algorithm. If True, the number of contour levels can be set in `ncontours`. If False, set the contour level attributes in `contours`. bingroup Set the `xbingroup` and `ybingroup` default prefix For example, setting a `bingroup` of 1 on two histogram2d traces will make them their x-bins and y-bins match separately. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.histogram2dcontour.ColorBa r instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Grey s,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Blues, Picnic,Rainbow,Portland,Jet,Hot,Blackbody,Earth ,Electric,Viridis,Cividis. contours plotly.graph_objects.histogram2dcontour.Contour s instance or dict with compatible properties customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . histfunc Specifies the binning function used for this histogram trace. If "count", the histogram values are computed by counting the number of values lying inside each bin. If "sum", "avg", "min", "max", the histogram values are computed using the sum, the average, the minimum or the maximum of the values lying inside each bin respectively. histnorm Specifies the type of normalization used for this histogram trace. If "", the span of each bar corresponds to the number of occurrences (i.e. the number of data points lying inside the bins). If "percent" / "probability", the span of each bar corresponds to the percentage / fraction of occurrences with respect to the total number of sample points (here, the sum of all bin HEIGHTS equals 100% / 1). If "density", the span of each bar corresponds to the number of occurrences in a bin divided by the size of the bin interval (here, the sum of all bin AREAS equals the total number of sample points). If *probability density*, the area of each bar corresponds to the probability that an event will fall into the corresponding bin (here, the sum of all bin AREAS equals 1). hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.histogram2dcontour.Hoverla bel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs- events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variable `z` Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.histogram2dcontour.Line instance or dict with compatible properties marker plotly.graph_objects.histogram2dcontour.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. nbinsx Specifies the maximum number of desired bins. This value will be used in an algorithm that will decide the optimal bin size such that the histogram best visualizes the distribution of the data. Ignored if `xbins.size` is provided. nbinsy Specifies the maximum number of desired bins. This value will be used in an algorithm that will decide the optimal bin size such that the histogram best visualizes the distribution of the data. Ignored if `ybins.size` is provided. ncontours Sets the maximum number of contour levels. The actual number of contours will be chosen automatically to be less than or equal to the value of `ncontours`. Has an effect only if `autocontour` is True or if `contours.size` is missing. opacity Sets the opacity of the trace. reversescale Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.histogram2dcontour.Stream instance or dict with compatible properties uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user- driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user- driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the sample data to be binned on the x axis. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xbingroup Set a group of histogram traces which will have compatible x-bin settings. Using `xbingroup`, histogram2d and histogram2dcontour traces (on axes of the same axis type) can have compatible x-bin settings. Note that the same `xbingroup` value can be used to set (1D) histogram `bingroup` xbins plotly.graph_objects.histogram2dcontour.XBins instance or dict with compatible properties xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . y Sets the sample data to be binned on the y axis. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ybingroup Set a group of histogram traces which will have compatible y-bin settings. Using `ybingroup`, histogram2d and histogram2dcontour traces (on axes of the same axis type) can have compatible y-bin settings. Note that the same `ybingroup` value can be used to set (1D) histogram `bingroup` ybins plotly.graph_objects.histogram2dcontour.YBins instance or dict with compatible properties ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . z Sets the aggregation data. zauto Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. zhoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. See: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format zmax Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. zmid Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. zmin Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. zsrc Sets the source reference on plot.ly for z . """, ), **kwargs ) import _plotly_utils.basevalidators class Histogram2dValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="histogram2d", parent_name="", **kwargs): super(Histogram2dValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Histogram2d"), data_docs=kwargs.pop( "data_docs", """ autobinx Obsolete: since v1.42 each bin attribute is auto-determined separately and `autobinx` is not needed. However, we accept `autobinx: true` or `false` and will update `xbins` accordingly before deleting `autobinx` from the trace. autobiny Obsolete: since v1.42 each bin attribute is auto-determined separately and `autobiny` is not needed. However, we accept `autobiny: true` or `false` and will update `ybins` accordingly before deleting `autobiny` from the trace. autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. bingroup Set the `xbingroup` and `ybingroup` default prefix For example, setting a `bingroup` of 1 on two histogram2d traces will make them their x-bins and y-bins match separately. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.histogram2d.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Grey s,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Blues, Picnic,Rainbow,Portland,Jet,Hot,Blackbody,Earth ,Electric,Viridis,Cividis. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . histfunc Specifies the binning function used for this histogram trace. If "count", the histogram values are computed by counting the number of values lying inside each bin. If "sum", "avg", "min", "max", the histogram values are computed using the sum, the average, the minimum or the maximum of the values lying inside each bin respectively. histnorm Specifies the type of normalization used for this histogram trace. If "", the span of each bar corresponds to the number of occurrences (i.e. the number of data points lying inside the bins). If "percent" / "probability", the span of each bar corresponds to the percentage / fraction of occurrences with respect to the total number of sample points (here, the sum of all bin HEIGHTS equals 100% / 1). If "density", the span of each bar corresponds to the number of occurrences in a bin divided by the size of the bin interval (here, the sum of all bin AREAS equals the total number of sample points). If *probability density*, the area of each bar corresponds to the probability that an event will fall into the corresponding bin (here, the sum of all bin AREAS equals 1). hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.histogram2d.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs- events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variable `z` Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . marker plotly.graph_objects.histogram2d.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. nbinsx Specifies the maximum number of desired bins. This value will be used in an algorithm that will decide the optimal bin size such that the histogram best visualizes the distribution of the data. Ignored if `xbins.size` is provided. nbinsy Specifies the maximum number of desired bins. This value will be used in an algorithm that will decide the optimal bin size such that the histogram best visualizes the distribution of the data. Ignored if `ybins.size` is provided. opacity Sets the opacity of the trace. reversescale Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.histogram2d.Stream instance or dict with compatible properties uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user- driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user- driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the sample data to be binned on the x axis. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xbingroup Set a group of histogram traces which will have compatible x-bin settings. Using `xbingroup`, histogram2d and histogram2dcontour traces (on axes of the same axis type) can have compatible x-bin settings. Note that the same `xbingroup` value can be used to set (1D) histogram `bingroup` xbins plotly.graph_objects.histogram2d.XBins instance or dict with compatible properties xcalendar Sets the calendar system to use with `x` date data. xgap Sets the horizontal gap (in pixels) between bricks. xsrc Sets the source reference on plot.ly for x . y Sets the sample data to be binned on the y axis. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ybingroup Set a group of histogram traces which will have compatible y-bin settings. Using `ybingroup`, histogram2d and histogram2dcontour traces (on axes of the same axis type) can have compatible y-bin settings. Note that the same `ybingroup` value can be used to set (1D) histogram `bingroup` ybins plotly.graph_objects.histogram2d.YBins instance or dict with compatible properties ycalendar Sets the calendar system to use with `y` date data. ygap Sets the vertical gap (in pixels) between bricks. ysrc Sets the source reference on plot.ly for y . z Sets the aggregation data. zauto Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. zhoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. See: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format zmax Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. zmid Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. zmin Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. zsmooth Picks a smoothing algorithm use to smooth `z` data. zsrc Sets the source reference on plot.ly for z . """, ), **kwargs ) import _plotly_utils.basevalidators class HistogramValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="histogram", parent_name="", **kwargs): super(HistogramValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Histogram"), data_docs=kwargs.pop( "data_docs", """ alignmentgroup Set several traces linked to the same position axis or matching axes to the same alignmentgroup. This controls whether bars compute their positional range dependently or independently. autobinx Obsolete: since v1.42 each bin attribute is auto-determined separately and `autobinx` is not needed. However, we accept `autobinx: true` or `false` and will update `xbins` accordingly before deleting `autobinx` from the trace. autobiny Obsolete: since v1.42 each bin attribute is auto-determined separately and `autobiny` is not needed. However, we accept `autobiny: true` or `false` and will update `ybins` accordingly before deleting `autobiny` from the trace. bingroup Set a group of histogram traces which will have compatible bin settings. Note that traces on the same subplot and with the same "orientation" under `barmode` "stack", "relative" and "group" are forced into the same bingroup, Using `bingroup`, traces under `barmode` "overlay" and on different axes (of the same axis type) can have compatible bin settings. Note that histogram and histogram2d* trace can share the same `bingroup` cumulative plotly.graph_objects.histogram.Cumulative instance or dict with compatible properties customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . error_x plotly.graph_objects.histogram.ErrorX instance or dict with compatible properties error_y plotly.graph_objects.histogram.ErrorY instance or dict with compatible properties histfunc Specifies the binning function used for this histogram trace. If "count", the histogram values are computed by counting the number of values lying inside each bin. If "sum", "avg", "min", "max", the histogram values are computed using the sum, the average, the minimum or the maximum of the values lying inside each bin respectively. histnorm Specifies the type of normalization used for this histogram trace. If "", the span of each bar corresponds to the number of occurrences (i.e. the number of data points lying inside the bins). If "percent" / "probability", the span of each bar corresponds to the percentage / fraction of occurrences with respect to the total number of sample points (here, the sum of all bin HEIGHTS equals 100% / 1). If "density", the span of each bar corresponds to the number of occurrences in a bin divided by the size of the bin interval (here, the sum of all bin AREAS equals the total number of sample points). If *probability density*, the area of each bar corresponds to the probability that an event will fall into the corresponding bin (here, the sum of all bin AREAS equals 1). hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.histogram.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs- events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variable `binNumber` Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. marker plotly.graph_objects.histogram.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. nbinsx Specifies the maximum number of desired bins. This value will be used in an algorithm that will decide the optimal bin size such that the histogram best visualizes the distribution of the data. Ignored if `xbins.size` is provided. nbinsy Specifies the maximum number of desired bins. This value will be used in an algorithm that will decide the optimal bin size such that the histogram best visualizes the distribution of the data. Ignored if `ybins.size` is provided. offsetgroup Set several traces linked to the same position axis or matching axes to the same offsetgroup where bars of the same position coordinate will line up. opacity Sets the opacity of the trace. orientation Sets the orientation of the bars. With "v" ("h"), the value of the each bar spans along the vertical (horizontal). selected plotly.graph_objects.histogram.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.histogram.Stream instance or dict with compatible properties text Sets hover text elements associated with each bar. If a single string, the same string appears over all bars. If an array of string, the items are mapped in order to the this trace's coordinates. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user- driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user- driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.histogram.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the sample data to be binned on the x axis. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xbins plotly.graph_objects.histogram.XBins instance or dict with compatible properties xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . y Sets the sample data to be binned on the y axis. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ybins plotly.graph_objects.histogram.YBins instance or dict with compatible properties ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . """, ), **kwargs ) import _plotly_utils.basevalidators class HeatmapglValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="heatmapgl", parent_name="", **kwargs): super(HeatmapglValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Heatmapgl"), data_docs=kwargs.pop( "data_docs", """ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.heatmapgl.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Grey s,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Blues, Picnic,Rainbow,Portland,Jet,Hot,Blackbody,Earth ,Electric,Viridis,Cividis. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dx Sets the x coordinate step. See `x0` for more info. dy Sets the y coordinate step. See `y0` for more info. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.heatmapgl.Hoverlabel instance or dict with compatible properties ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. reversescale Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.heatmapgl.Stream instance or dict with compatible properties text Sets the text elements associated with each z value. textsrc Sets the source reference on plot.ly for text . transpose Transposes the z data. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user- driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user- driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the x coordinates. x0 Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xsrc Sets the source reference on plot.ly for x . xtype If "array", the heatmap's x coordinates are given by "x" (the default behavior when `x` is provided). If "scaled", the heatmap's x coordinates are given by "x0" and "dx" (the default behavior when `x` is not provided). y Sets the y coordinates. y0 Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ysrc Sets the source reference on plot.ly for y . ytype If "array", the heatmap's y coordinates are given by "y" (the default behavior when `y` is provided) If "scaled", the heatmap's y coordinates are given by "y0" and "dy" (the default behavior when `y` is not provided) z Sets the z data. zauto Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. zmax Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. zmid Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. zmin Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. zsrc Sets the source reference on plot.ly for z . """, ), **kwargs ) import _plotly_utils.basevalidators class HeatmapValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="heatmap", parent_name="", **kwargs): super(HeatmapValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Heatmap"), data_docs=kwargs.pop( "data_docs", """ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.heatmap.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Grey s,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Blues, Picnic,Rainbow,Portland,Jet,Hot,Blackbody,Earth ,Electric,Viridis,Cividis. connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the `z` data are filled in. It is defaulted to true if `z` is a one dimensional array and `zsmooth` is not false; otherwise it is defaulted to false. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dx Sets the x coordinate step. See `x0` for more info. dy Sets the y coordinate step. See `y0` for more info. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.heatmap.Hoverlabel instance or dict with compatible properties hoverongaps Determines whether or not gaps (i.e. {nan} or missing values) in the `z` data have hover labels associated with them. hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs- events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. reversescale Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.heatmap.Stream instance or dict with compatible properties text Sets the text elements associated with each z value. textsrc Sets the source reference on plot.ly for text . transpose Transposes the z data. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user- driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user- driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the x coordinates. x0 Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xcalendar Sets the calendar system to use with `x` date data. xgap Sets the horizontal gap (in pixels) between bricks. xsrc Sets the source reference on plot.ly for x . xtype If "array", the heatmap's x coordinates are given by "x" (the default behavior when `x` is provided). If "scaled", the heatmap's x coordinates are given by "x0" and "dx" (the default behavior when `x` is not provided). y Sets the y coordinates. y0 Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ycalendar Sets the calendar system to use with `y` date data. ygap Sets the vertical gap (in pixels) between bricks. ysrc Sets the source reference on plot.ly for y . ytype If "array", the heatmap's y coordinates are given by "y" (the default behavior when `y` is provided) If "scaled", the heatmap's y coordinates are given by "y0" and "dy" (the default behavior when `y` is not provided) z Sets the z data. zauto Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. zhoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. See: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format zmax Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. zmid Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. zmin Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. zsmooth Picks a smoothing algorithm use to smooth `z` data. zsrc Sets the source reference on plot.ly for z . """, ), **kwargs ) import _plotly_utils.basevalidators class FunnelareaValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="funnelarea", parent_name="", **kwargs): super(FunnelareaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Funnelarea"), data_docs=kwargs.pop( "data_docs", """ aspectratio Sets the ratio between height and width baseratio Sets the ratio between bottom length and maximum top length. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dlabel Sets the label step. See `label0` for more info. domain plotly.graph_objects.funnelarea.Domain instance or dict with compatible properties hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.funnelarea.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs- events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `label`, `color`, `value`, `text` and `percent`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each sector. If a single string, the same string appears for all data points. If an array of string, the items are mapped in order of this trace's sectors. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . insidetextfont Sets the font used for `textinfo` lying inside the sector. label0 Alternate to `labels`. Builds a numeric set of labels. Use with `dlabel` where `label0` is the starting label and `dlabel` the step. labels Sets the sector labels. If `labels` entries are duplicated, we sum associated `values` or simply count occurrences if `values` is not provided. For other array attributes (including color) we use the first non-empty entry among all occurrences of the label. labelssrc Sets the source reference on plot.ly for labels . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. marker plotly.graph_objects.funnelarea.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. scalegroup If there are multiple funnelareas that should be sized according to their totals, link them by providing a non-empty group id here shared by every trace in the same group. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.funnelarea.Stream instance or dict with compatible properties text Sets text elements associated with each sector. If trace `textinfo` contains a "text" flag, these elements will be seen on the chart. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the font used for `textinfo`. textinfo Determines which trace information appear on the graph. textposition Specifies the location of the `textinfo`. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. variables `label`, `color`, `value`, `text` and `percent`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . title plotly.graph_objects.funnelarea.Title instance or dict with compatible properties uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user- driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user- driven changes if you give each trace a `uid` that stays with it as it moves. values Sets the values of the sectors. If omitted, we count occurrences of each label. valuessrc Sets the source reference on plot.ly for values . visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). """, ), **kwargs ) import _plotly_utils.basevalidators class FunnelValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="funnel", parent_name="", **kwargs): super(FunnelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Funnel"), data_docs=kwargs.pop( "data_docs", """ alignmentgroup Set several traces linked to the same position axis or matching axes to the same alignmentgroup. This controls whether bars compute their positional range dependently or independently. cliponaxis Determines whether the text nodes are clipped about the subplot axes. To show the text nodes above axis lines and tick labels, make sure to set `xaxis.layer` and `yaxis.layer` to *below traces*. connector plotly.graph_objects.funnel.Connector instance or dict with compatible properties constraintext Constrain the size of text inside or outside a bar to be no larger than the bar itself. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dx Sets the x coordinate step. See `x0` for more info. dy Sets the y coordinate step. See `y0` for more info. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.funnel.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs- events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `percentInitial`, `percentPrevious` and `percentTotal`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . insidetextanchor Determines if texts are kept at center or start/end points in `textposition` "inside" mode. insidetextfont Sets the font used for `text` lying inside the bar. legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. marker plotly.graph_objects.funnel.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. offset Shifts the position where the bar is drawn (in position axis units). In "group" barmode, traces that set "offset" will be excluded and drawn in "overlay" mode instead. offsetgroup Set several traces linked to the same position axis or matching axes to the same offsetgroup where bars of the same position coordinate will line up. opacity Sets the opacity of the trace. orientation Sets the orientation of the funnels. With "v" ("h"), the value of the each bar spans along the vertical (horizontal). By default funnels are tend to be oriented horizontally; unless only "y" array is presented or orientation is set to "v". Also regarding graphs including only 'horizontal' funnels, "autorange" on the "y-axis" are set to "reversed". outsidetextfont Sets the font used for `text` lying outside the bar. selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.funnel.Stream instance or dict with compatible properties text Sets text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textangle Sets the angle of the tick labels with respect to the bar. For example, a `tickangle` of -90 draws the tick labels vertically. With "auto" the texts may automatically be rotated to fit with the maximum size in bars. textfont Sets the font used for `text`. textinfo Determines which trace information appear on the graph. In the case of having multiple funnels, percentages & totals are computed separately (per trace). textposition Specifies the location of the `text`. "inside" positions `text` inside, next to the bar end (rotated and scaled if needed). "outside" positions `text` outside, next to the bar end (scaled if needed), unless there is another bar stacked on this one, then the text gets pushed inside. "auto" tries to position `text` inside the bar, but if the bar is too small and no bar is stacked on this one the text is moved outside. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. variables `percentInitial`, `percentPrevious`, `percentTotal`, `label` and `value`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user- driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user- driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). width Sets the bar width (in position axis units). x Sets the x coordinates. x0 Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xsrc Sets the source reference on plot.ly for x . y Sets the y coordinates. y0 Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ysrc Sets the source reference on plot.ly for y . """, ), **kwargs ) import _plotly_utils.basevalidators class DensitymapboxValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="densitymapbox", parent_name="", **kwargs): super(DensitymapboxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Densitymapbox"), data_docs=kwargs.pop( "data_docs", """ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. below Determines if the densitymapbox trace will be inserted before the layer with the specified ID. By default, densitymapbox traces are placed below the first layer of type symbol If set to '', the layer will be inserted above every existing layer. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.densitymapbox.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Grey s,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Blues, Picnic,Rainbow,Portland,Jet,Hot,Blackbody,Earth ,Electric,Viridis,Cividis. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.densitymapbox.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs- events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (lon,lat) pair If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (lon,lat) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . lat Sets the latitude coordinates (in degrees North). latsrc Sets the source reference on plot.ly for lat . lon Sets the longitude coordinates (in degrees East). lonsrc Sets the source reference on plot.ly for lon . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. radius Sets the radius of influence of one `lon` / `lat` point in pixels. Increasing the value makes the densitymapbox trace smoother, but less detailed. radiussrc Sets the source reference on plot.ly for radius . reversescale Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.densitymapbox.Stream instance or dict with compatible properties subplot Sets a reference between this trace's data coordinates and a mapbox subplot. If "mapbox" (the default value), the data refer to `layout.mapbox`. If "mapbox2", the data refer to `layout.mapbox2`, and so on. text Sets text elements associated with each (lon,lat) pair If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (lon,lat) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user- driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user- driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). z Sets the points' weight. For example, a value of 10 would be equivalent to having 10 points of weight 1 in the same spot zauto Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. zmax Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. zmid Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. zmin Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. zsrc Sets the source reference on plot.ly for z . """, ), **kwargs ) import _plotly_utils.basevalidators class ContourcarpetValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="contourcarpet", parent_name="", **kwargs): super(ContourcarpetValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Contourcarpet"), data_docs=kwargs.pop( "data_docs", """ a Sets the x coordinates. a0 Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. asrc Sets the source reference on plot.ly for a . atype If "array", the heatmap's x coordinates are given by "x" (the default behavior when `x` is provided). If "scaled", the heatmap's x coordinates are given by "x0" and "dx" (the default behavior when `x` is not provided). autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. autocontour Determines whether or not the contour level attributes are picked by an algorithm. If True, the number of contour levels can be set in `ncontours`. If False, set the contour level attributes in `contours`. b Sets the y coordinates. b0 Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. bsrc Sets the source reference on plot.ly for b . btype If "array", the heatmap's y coordinates are given by "y" (the default behavior when `y` is provided) If "scaled", the heatmap's y coordinates are given by "y0" and "dy" (the default behavior when `y` is not provided) carpet The `carpet` of the carpet axes on which this contour trace lies coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.contourcarpet.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Grey s,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Blues, Picnic,Rainbow,Portland,Jet,Hot,Blackbody,Earth ,Electric,Viridis,Cividis. contours plotly.graph_objects.contourcarpet.Contours instance or dict with compatible properties customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . da Sets the x coordinate step. See `x0` for more info. db Sets the y coordinate step. See `y0` for more info. fillcolor Sets the fill color if `contours.type` is "constraint". Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.contourcarpet.Line instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. ncontours Sets the maximum number of contour levels. The actual number of contours will be chosen automatically to be less than or equal to the value of `ncontours`. Has an effect only if `autocontour` is True or if `contours.size` is missing. opacity Sets the opacity of the trace. reversescale Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.contourcarpet.Stream instance or dict with compatible properties text Sets the text elements associated with each z value. textsrc Sets the source reference on plot.ly for text . transpose Transposes the z data. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user- driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user- driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. z Sets the z data. zauto Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. zmax Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. zmid Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. zmin Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. zsrc Sets the source reference on plot.ly for z . """, ), **kwargs ) import _plotly_utils.basevalidators class ContourValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="contour", parent_name="", **kwargs): super(ContourValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Contour"), data_docs=kwargs.pop( "data_docs", """ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. autocontour Determines whether or not the contour level attributes are picked by an algorithm. If True, the number of contour levels can be set in `ncontours`. If False, set the contour level attributes in `contours`. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.contour.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Grey s,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Blues, Picnic,Rainbow,Portland,Jet,Hot,Blackbody,Earth ,Electric,Viridis,Cividis. connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the `z` data are filled in. It is defaulted to true if `z` is a one dimensional array otherwise it is defaulted to false. contours plotly.graph_objects.contour.Contours instance or dict with compatible properties customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dx Sets the x coordinate step. See `x0` for more info. dy Sets the y coordinate step. See `y0` for more info. fillcolor Sets the fill color if `contours.type` is "constraint". Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.contour.Hoverlabel instance or dict with compatible properties hoverongaps Determines whether or not gaps (i.e. {nan} or missing values) in the `z` data have hover labels associated with them. hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs- events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.contour.Line instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. ncontours Sets the maximum number of contour levels. The actual number of contours will be chosen automatically to be less than or equal to the value of `ncontours`. Has an effect only if `autocontour` is True or if `contours.size` is missing. opacity Sets the opacity of the trace. reversescale Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.contour.Stream instance or dict with compatible properties text Sets the text elements associated with each z value. textsrc Sets the source reference on plot.ly for text . transpose Transposes the z data. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user- driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user- driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the x coordinates. x0 Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . xtype If "array", the heatmap's x coordinates are given by "x" (the default behavior when `x` is provided). If "scaled", the heatmap's x coordinates are given by "x0" and "dx" (the default behavior when `x` is not provided). y Sets the y coordinates. y0 Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . ytype If "array", the heatmap's y coordinates are given by "y" (the default behavior when `y` is provided) If "scaled", the heatmap's y coordinates are given by "y0" and "dy" (the default behavior when `y` is not provided) z Sets the z data. zauto Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. zhoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. See: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format zmax Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. zmid Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. zmin Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. zsrc Sets the source reference on plot.ly for z . """, ), **kwargs ) import _plotly_utils.basevalidators class ConeValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="cone", parent_name="", **kwargs): super(ConeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Cone"), data_docs=kwargs.pop( "data_docs", """ anchor Sets the cones' anchor with respect to their x/y/z positions. Note that "cm" denote the cone's center of mass which corresponds to 1/4 from the tail to tip. autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here u/v/w norm) or the bounds set in `cmin` and `cmax` Defaults to `false` when `cmin` and `cmax` are set by the user. cmax Sets the upper bound of the color domain. Value should have the same units as u/v/w norm and if set, `cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `cmin` and/or `cmax` to be equidistant to this point. Value should have the same units as u/v/w norm. Has no effect when `cauto` is `false`. cmin Sets the lower bound of the color domain. Value should have the same units as u/v/w norm and if set, `cmax` must be set as well. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.cone.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`cmin` and `cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Grey s,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Blues, Picnic,Rainbow,Portland,Jet,Hot,Blackbody,Earth ,Electric,Viridis,Cividis. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.cone.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs- events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variable `norm` Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . lighting plotly.graph_objects.cone.Lighting instance or dict with compatible properties lightposition plotly.graph_objects.cone.Lightposition instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the surface. Please note that in the case of using high `opacity` values for example a value greater than or equal to 0.5 on two surfaces (and 0.25 with four surfaces), an overlay of multiple transparent surfaces may not perfectly be sorted in depth by the webgl API. This behavior may be improved in the near future and is subject to change. reversescale Reverses the color mapping if true. If true, `cmin` will correspond to the last color in the array and `cmax` will correspond to the first color. scene Sets a reference between this trace's 3D coordinate system and a 3D scene. If "scene" (the default value), the (x,y,z) coordinates refer to `layout.scene`. If "scene2", the (x,y,z) coordinates refer to `layout.scene2`, and so on. showscale Determines whether or not a colorbar is displayed for this trace. sizemode Determines whether `sizeref` is set as a "scaled" (i.e unitless) scalar (normalized by the max u/v/w norm in the vector field) or as "absolute" value (in the same units as the vector field). sizeref Adjusts the cone size scaling. The size of the cones is determined by their u/v/w norm multiplied a factor and `sizeref`. This factor (computed internally) corresponds to the minimum "time" to travel across two successive x/y/z positions at the average velocity of those two successive positions. All cones in a given trace use the same factor. With `sizemode` set to "scaled", `sizeref` is unitless, its default value is 0.5 With `sizemode` set to "absolute", `sizeref` has the same units as the u/v/w vector field, its the default value is half the sample's maximum vector norm. stream plotly.graph_objects.cone.Stream instance or dict with compatible properties text Sets the text elements associated with the cones. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textsrc Sets the source reference on plot.ly for text . u Sets the x components of the vector field. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user- driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user- driven changes if you give each trace a `uid` that stays with it as it moves. usrc Sets the source reference on plot.ly for u . v Sets the y components of the vector field. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). vsrc Sets the source reference on plot.ly for v . w Sets the z components of the vector field. wsrc Sets the source reference on plot.ly for w . x Sets the x coordinates of the vector field and of the displayed cones. xsrc Sets the source reference on plot.ly for x . y Sets the y coordinates of the vector field and of the displayed cones. ysrc Sets the source reference on plot.ly for y . z Sets the z coordinates of the vector field and of the displayed cones. zsrc Sets the source reference on plot.ly for z . """, ), **kwargs ) import _plotly_utils.basevalidators class ChoroplethmapboxValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="choroplethmapbox", parent_name="", **kwargs): super(ChoroplethmapboxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Choroplethmapbox"), data_docs=kwargs.pop( "data_docs", """ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. below Determines if the choropleth polygons will be inserted before the layer with the specified ID. By default, choroplethmapbox traces are placed above the water layers. If set to '', the layer will be inserted above every existing layer. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.choroplethmapbox.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Grey s,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Blues, Picnic,Rainbow,Portland,Jet,Hot,Blackbody,Earth ,Electric,Viridis,Cividis. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . geojson Sets the GeoJSON data associated with this trace. Can be set as a valid GeoJSON object or as URL string Note that we only accept GeoJSON of type "FeatureCollection" and "Feature" with geometries of type "Polygon" and "MultiPolygon". hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.choroplethmapbox.Hoverlabe l instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs- events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variable `properties` Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . locations Sets which features found in "geojson" to plot using their feature `id` field. locationssrc Sets the source reference on plot.ly for locations . marker plotly.graph_objects.choroplethmapbox.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. reversescale Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. selected plotly.graph_objects.choroplethmapbox.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.choroplethmapbox.Stream instance or dict with compatible properties subplot Sets a reference between this trace's data coordinates and a mapbox subplot. If "mapbox" (the default value), the data refer to `layout.mapbox`. If "mapbox2", the data refer to `layout.mapbox2`, and so on. text Sets the text elements associated with each location. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user- driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user- driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.choroplethmapbox.Unselecte d instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). z Sets the color values. zauto Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. zmax Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. zmid Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. zmin Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. zsrc Sets the source reference on plot.ly for z . """, ), **kwargs ) import _plotly_utils.basevalidators class ChoroplethValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="choropleth", parent_name="", **kwargs): super(ChoroplethValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Choropleth"), data_docs=kwargs.pop( "data_docs", """ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.choropleth.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Grey s,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Blues, Picnic,Rainbow,Portland,Jet,Hot,Blackbody,Earth ,Electric,Viridis,Cividis. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . geo Sets a reference between this trace's geospatial coordinates and a geographic map. If "geo" (the default value), the geospatial coordinates refer to `layout.geo`. If "geo2", the geospatial coordinates refer to `layout.geo2`, and so on. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.choropleth.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs- events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . locationmode Determines the set of locations used to match entries in `locations` to regions on the map. locations Sets the coordinates via location IDs or names. See `locationmode` for more info. locationssrc Sets the source reference on plot.ly for locations . marker plotly.graph_objects.choropleth.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. reversescale Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. selected plotly.graph_objects.choropleth.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.choropleth.Stream instance or dict with compatible properties text Sets the text elements associated with each location. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user- driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user- driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.choropleth.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). z Sets the color values. zauto Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. zmax Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. zmid Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. zmin Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. zsrc Sets the source reference on plot.ly for z . """, ), **kwargs ) import _plotly_utils.basevalidators class CarpetValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="carpet", parent_name="", **kwargs): super(CarpetValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Carpet"), data_docs=kwargs.pop( "data_docs", """ a An array containing values of the first parameter value a0 Alternate to `a`. Builds a linear space of a coordinates. Use with `da` where `a0` is the starting coordinate and `da` the step. aaxis plotly.graph_objects.carpet.Aaxis instance or dict with compatible properties asrc Sets the source reference on plot.ly for a . b A two dimensional array of y coordinates at each carpet point. b0 Alternate to `b`. Builds a linear space of a coordinates. Use with `db` where `b0` is the starting coordinate and `db` the step. baxis plotly.graph_objects.carpet.Baxis instance or dict with compatible properties bsrc Sets the source reference on plot.ly for b . carpet An identifier for this carpet, so that `scattercarpet` and `contourcarpet` traces can specify a carpet plot on which they lie cheaterslope The shift applied to each successive row of data in creating a cheater plot. Only used if `x` is been ommitted. color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . da Sets the a coordinate step. See `a0` for more info. db Sets the b coordinate step. See `b0` for more info. font The default font used for axis & tick labels on this carpet ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. stream plotly.graph_objects.carpet.Stream instance or dict with compatible properties uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user- driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user- driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x A two dimensional array of x coordinates at each carpet point. If ommitted, the plot is a cheater plot and the xaxis is hidden by default. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xsrc Sets the source reference on plot.ly for x . y A two dimensional array of y coordinates at each carpet point. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ysrc Sets the source reference on plot.ly for y . """, ), **kwargs ) import _plotly_utils.basevalidators class CandlestickValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="candlestick", parent_name="", **kwargs): super(CandlestickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Candlestick"), data_docs=kwargs.pop( "data_docs", """ close Sets the close values. closesrc Sets the source reference on plot.ly for close . customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . decreasing plotly.graph_objects.candlestick.Decreasing instance or dict with compatible properties high Sets the high values. highsrc Sets the source reference on plot.ly for high . hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.candlestick.Hoverlabel instance or dict with compatible properties hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . increasing plotly.graph_objects.candlestick.Increasing instance or dict with compatible properties legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.candlestick.Line instance or dict with compatible properties low Sets the low values. lowsrc Sets the source reference on plot.ly for low . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. open Sets the open values. opensrc Sets the source reference on plot.ly for open . selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.candlestick.Stream instance or dict with compatible properties text Sets hover text elements associated with each sample point. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to this trace's sample points. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user- driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user- driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). whiskerwidth Sets the width of the whiskers relative to the box' width. For example, with 1, the whiskers are as wide as the box(es). x Sets the x coordinates. If absent, linear coordinate will be generated. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. """, ), **kwargs ) import _plotly_utils.basevalidators class BoxValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="box", parent_name="", **kwargs): super(BoxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Box"), data_docs=kwargs.pop( "data_docs", """ alignmentgroup Set several traces linked to the same position axis or matching axes to the same alignmentgroup. This controls whether bars compute their positional range dependently or independently. boxmean If True, the mean of the box(es)' underlying distribution is drawn as a dashed line inside the box(es). If "sd" the standard deviation is also drawn. boxpoints If "outliers", only the sample points lying outside the whiskers are shown If "suspectedoutliers", the outlier points are shown and points either less than 4*Q1-3*Q3 or greater than 4*Q3-3*Q1 are highlighted (see `outliercolor`) If "all", all sample points are shown If False, only the box(es) are shown with no sample points customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . fillcolor Sets the fill color. Defaults to a half- transparent variant of the line color, marker color, or marker line color, whichever is available. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.box.Hoverlabel instance or dict with compatible properties hoveron Do the hover effects highlight individual boxes or sample points or both? hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs- events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . jitter Sets the amount of jitter in the sample points drawn. If 0, the sample points align along the distribution axis. If 1, the sample points are drawn in a random jitter of width equal to the width of the box(es). legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.box.Line instance or dict with compatible properties marker plotly.graph_objects.box.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. For box traces, the name will also be used for the position coordinate, if `x` and `x0` (`y` and `y0` if horizontal) are missing and the position axis is categorical notched Determines whether or not notches should be drawn. notchwidth Sets the width of the notches relative to the box' width. For example, with 0, the notches are as wide as the box(es). offsetgroup Set several traces linked to the same position axis or matching axes to the same offsetgroup where bars of the same position coordinate will line up. opacity Sets the opacity of the trace. orientation Sets the orientation of the box(es). If "v" ("h"), the distribution is visualized along the vertical (horizontal). pointpos Sets the position of the sample points in relation to the box(es). If 0, the sample points are places over the center of the box(es). Positive (negative) values correspond to positions to the right (left) for vertical boxes and above (below) for horizontal boxes selected plotly.graph_objects.box.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.box.Stream instance or dict with compatible properties text Sets the text elements associated with each sample value. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user- driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user- driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.box.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). whiskerwidth Sets the width of the whiskers relative to the box' width. For example, with 1, the whiskers are as wide as the box(es). width Sets the width of the box in data coordinate If 0 (default value) the width is automatically selected based on the positions of other box traces in the same subplot. x Sets the x sample data or coordinates. See overview for more info. x0 Sets the x coordinate of the box. See overview for more info. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . y Sets the y sample data or coordinates. See overview for more info. y0 Sets the y coordinate of the box. See overview for more info. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . """, ), **kwargs ) import _plotly_utils.basevalidators class BarpolarValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="barpolar", parent_name="", **kwargs): super(BarpolarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Barpolar"), data_docs=kwargs.pop( "data_docs", """ base Sets where the bar base is drawn (in radial axis units). In "stack" barmode, traces that set "base" will be excluded and drawn in "overlay" mode instead. basesrc Sets the source reference on plot.ly for base . customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dr Sets the r coordinate step. dtheta Sets the theta coordinate step. By default, the `dtheta` step equals the subplot's period divided by the length of the `r` coordinates. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.barpolar.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs- events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. marker plotly.graph_objects.barpolar.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. offset Shifts the angular position where the bar is drawn (in "thetatunit" units). offsetsrc Sets the source reference on plot.ly for offset . opacity Sets the opacity of the trace. r Sets the radial coordinates r0 Alternate to `r`. Builds a linear space of r coordinates. Use with `dr` where `r0` is the starting coordinate and `dr` the step. rsrc Sets the source reference on plot.ly for r . selected plotly.graph_objects.barpolar.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.barpolar.Stream instance or dict with compatible properties subplot Sets a reference between this trace's data coordinates and a polar subplot. If "polar" (the default value), the data refer to `layout.polar`. If "polar2", the data refer to `layout.polar2`, and so on. text Sets hover text elements associated with each bar. If a single string, the same string appears over all bars. If an array of string, the items are mapped in order to the this trace's coordinates. textsrc Sets the source reference on plot.ly for text . theta Sets the angular coordinates theta0 Alternate to `theta`. Builds a linear space of theta coordinates. Use with `dtheta` where `theta0` is the starting coordinate and `dtheta` the step. thetasrc Sets the source reference on plot.ly for theta . thetaunit Sets the unit of input "theta" values. Has an effect only when on "linear" angular axes. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user- driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user- driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.barpolar.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). width Sets the bar angular width (in "thetaunit" units). widthsrc Sets the source reference on plot.ly for width . """, ), **kwargs ) import _plotly_utils.basevalidators class BarValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="bar", parent_name="", **kwargs): super(BarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Bar"), data_docs=kwargs.pop( "data_docs", """ alignmentgroup Set several traces linked to the same position axis or matching axes to the same alignmentgroup. This controls whether bars compute their positional range dependently or independently. base Sets where the bar base is drawn (in position axis units). In "stack" or "relative" barmode, traces that set "base" will be excluded and drawn in "overlay" mode instead. basesrc Sets the source reference on plot.ly for base . cliponaxis Determines whether the text nodes are clipped about the subplot axes. To show the text nodes above axis lines and tick labels, make sure to set `xaxis.layer` and `yaxis.layer` to *below traces*. constraintext Constrain the size of text inside or outside a bar to be no larger than the bar itself. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dx Sets the x coordinate step. See `x0` for more info. dy Sets the y coordinate step. See `y0` for more info. error_x plotly.graph_objects.bar.ErrorX instance or dict with compatible properties error_y plotly.graph_objects.bar.ErrorY instance or dict with compatible properties hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.bar.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs- events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `value` and `label`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . insidetextanchor Determines if texts are kept at center or start/end points in `textposition` "inside" mode. insidetextfont Sets the font used for `text` lying inside the bar. legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. marker plotly.graph_objects.bar.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. offset Shifts the position where the bar is drawn (in position axis units). In "group" barmode, traces that set "offset" will be excluded and drawn in "overlay" mode instead. offsetgroup Set several traces linked to the same position axis or matching axes to the same offsetgroup where bars of the same position coordinate will line up. offsetsrc Sets the source reference on plot.ly for offset . opacity Sets the opacity of the trace. orientation Sets the orientation of the bars. With "v" ("h"), the value of the each bar spans along the vertical (horizontal). outsidetextfont Sets the font used for `text` lying outside the bar. r r coordinates in scatter traces are deprecated!Please switch to the "scatterpolar" trace type.Sets the radial coordinatesfor legacy polar chart only. rsrc Sets the source reference on plot.ly for r . selected plotly.graph_objects.bar.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.bar.Stream instance or dict with compatible properties t t coordinates in scatter traces are deprecated!Please switch to the "scatterpolar" trace type.Sets the angular coordinatesfor legacy polar chart only. text Sets text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textangle Sets the angle of the tick labels with respect to the bar. For example, a `tickangle` of -90 draws the tick labels vertically. With "auto" the texts may automatically be rotated to fit with the maximum size in bars. textfont Sets the font used for `text`. textposition Specifies the location of the `text`. "inside" positions `text` inside, next to the bar end (rotated and scaled if needed). "outside" positions `text` outside, next to the bar end (scaled if needed), unless there is another bar stacked on this one, then the text gets pushed inside. "auto" tries to position `text` inside the bar, but if the bar is too small and no bar is stacked on this one the text is moved outside. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. variables `value` and `label`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . tsrc Sets the source reference on plot.ly for t . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user- driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user- driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.bar.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). width Sets the bar width (in position axis units). widthsrc Sets the source reference on plot.ly for width . x Sets the x coordinates. x0 Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . y Sets the y coordinates. y0 Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . """, ), **kwargs ) import _plotly_utils.basevalidators class AreaValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="area", parent_name="", **kwargs): super(AreaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Area"), data_docs=kwargs.pop( "data_docs", """ customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.area.Hoverlabel instance or dict with compatible properties ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. marker plotly.graph_objects.area.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. r Area traces are deprecated! Please switch to the "barpolar" trace type. Sets the radial coordinates for legacy polar chart only. rsrc Sets the source reference on plot.ly for r . showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.area.Stream instance or dict with compatible properties t Area traces are deprecated! Please switch to the "barpolar" trace type. Sets the angular coordinates for legacy polar chart only. tsrc Sets the source reference on plot.ly for t . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user- driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user- driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). """, ), **kwargs ) import _plotly_utils.basevalidators class FramesValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__(self, plotly_name="frames", parent_name="", **kwargs): super(FramesValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Frame"), data_docs=kwargs.pop( "data_docs", """ baseframe The name of the frame into which this frame's properties are merged before applying. This is used to unify properties and avoid needing to specify the same values for the same properties in multiple frames. data A list of traces this frame modifies. The format is identical to the normal trace definition. group An identifier that specifies the group to which the frame belongs, used by animate to select a subset of frames. layout Layout properties which this frame modifies. The format is identical to the normal layout definition. name A label by which to identify the frame traces A list of trace indices that identify the respective traces in the data attribute """, ), **kwargs ) import _plotly_utils.basevalidators class DataValidator(_plotly_utils.basevalidators.BaseDataValidator): def __init__(self, plotly_name="data", parent_name="", **kwargs): super(DataValidator, self).__init__( class_strs_map={ "area": "Area", "bar": "Bar", "barpolar": "Barpolar", "box": "Box", "candlestick": "Candlestick", "carpet": "Carpet", "choropleth": "Choropleth", "choroplethmapbox": "Choroplethmapbox", "cone": "Cone", "contour": "Contour", "contourcarpet": "Contourcarpet", "densitymapbox": "Densitymapbox", "funnel": "Funnel", "funnelarea": "Funnelarea", "heatmap": "Heatmap", "heatmapgl": "Heatmapgl", "histogram": "Histogram", "histogram2d": "Histogram2d", "histogram2dcontour": "Histogram2dContour", "image": "Image", "indicator": "Indicator", "isosurface": "Isosurface", "mesh3d": "Mesh3d", "ohlc": "Ohlc", "parcats": "Parcats", "parcoords": "Parcoords", "pie": "Pie", "pointcloud": "Pointcloud", "sankey": "Sankey", "scatter": "Scatter", "scatter3d": "Scatter3d", "scattercarpet": "Scattercarpet", "scattergeo": "Scattergeo", "scattergl": "Scattergl", "scattermapbox": "Scattermapbox", "scatterpolar": "Scatterpolar", "scatterpolargl": "Scatterpolargl", "scatterternary": "Scatterternary", "splom": "Splom", "streamtube": "Streamtube", "sunburst": "Sunburst", "surface": "Surface", "table": "Table", "treemap": "Treemap", "violin": "Violin", "volume": "Volume", "waterfall": "Waterfall", }, plotly_name=plotly_name, parent_name=parent_name, **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/area/0000755000175000017500000000000013573746614020674 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/area/hoverlabel/0000755000175000017500000000000013573746614023017 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/area/hoverlabel/__init__.py0000644000175000017500000001331413573721536025126 0ustar noahfxnoahfximport _plotly_utils.basevalidators class NamelengthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="namelengthsrc", parent_name="area.hoverlabel", **kwargs ): super(NamelengthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NamelengthValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="namelength", parent_name="area.hoverlabel", **kwargs ): super(NamelengthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", -1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="font", parent_name="area.hoverlabel", **kwargs): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class BordercolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bordercolorsrc", parent_name="area.hoverlabel", **kwargs ): super(BordercolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="area.hoverlabel", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bgcolorsrc", parent_name="area.hoverlabel", **kwargs ): super(BgcolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="bgcolor", parent_name="area.hoverlabel", **kwargs): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AlignsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="alignsrc", parent_name="area.hoverlabel", **kwargs): super(AlignsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="align", parent_name="area.hoverlabel", **kwargs): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "right", "auto"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/area/hoverlabel/font/0000755000175000017500000000000013573746614023765 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/area/hoverlabel/font/__init__.py0000644000175000017500000000602313573721536026073 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="area.hoverlabel.font", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="area.hoverlabel.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="area.hoverlabel.font", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="area.hoverlabel.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="area.hoverlabel.font", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="area.hoverlabel.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/area/marker/0000755000175000017500000000000013573746614022155 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/area/marker/__init__.py0000644000175000017500000003072513573721536024271 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SymbolsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="symbolsrc", parent_name="area.marker", **kwargs): super(SymbolsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SymbolValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="symbol", parent_name="area.marker", **kwargs): super(SymbolValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", [ 0, "circle", 100, "circle-open", 200, "circle-dot", 300, "circle-open-dot", 1, "square", 101, "square-open", 201, "square-dot", 301, "square-open-dot", 2, "diamond", 102, "diamond-open", 202, "diamond-dot", 302, "diamond-open-dot", 3, "cross", 103, "cross-open", 203, "cross-dot", 303, "cross-open-dot", 4, "x", 104, "x-open", 204, "x-dot", 304, "x-open-dot", 5, "triangle-up", 105, "triangle-up-open", 205, "triangle-up-dot", 305, "triangle-up-open-dot", 6, "triangle-down", 106, "triangle-down-open", 206, "triangle-down-dot", 306, "triangle-down-open-dot", 7, "triangle-left", 107, "triangle-left-open", 207, "triangle-left-dot", 307, "triangle-left-open-dot", 8, "triangle-right", 108, "triangle-right-open", 208, "triangle-right-dot", 308, "triangle-right-open-dot", 9, "triangle-ne", 109, "triangle-ne-open", 209, "triangle-ne-dot", 309, "triangle-ne-open-dot", 10, "triangle-se", 110, "triangle-se-open", 210, "triangle-se-dot", 310, "triangle-se-open-dot", 11, "triangle-sw", 111, "triangle-sw-open", 211, "triangle-sw-dot", 311, "triangle-sw-open-dot", 12, "triangle-nw", 112, "triangle-nw-open", 212, "triangle-nw-dot", 312, "triangle-nw-open-dot", 13, "pentagon", 113, "pentagon-open", 213, "pentagon-dot", 313, "pentagon-open-dot", 14, "hexagon", 114, "hexagon-open", 214, "hexagon-dot", 314, "hexagon-open-dot", 15, "hexagon2", 115, "hexagon2-open", 215, "hexagon2-dot", 315, "hexagon2-open-dot", 16, "octagon", 116, "octagon-open", 216, "octagon-dot", 316, "octagon-open-dot", 17, "star", 117, "star-open", 217, "star-dot", 317, "star-open-dot", 18, "hexagram", 118, "hexagram-open", 218, "hexagram-dot", 318, "hexagram-open-dot", 19, "star-triangle-up", 119, "star-triangle-up-open", 219, "star-triangle-up-dot", 319, "star-triangle-up-open-dot", 20, "star-triangle-down", 120, "star-triangle-down-open", 220, "star-triangle-down-dot", 320, "star-triangle-down-open-dot", 21, "star-square", 121, "star-square-open", 221, "star-square-dot", 321, "star-square-open-dot", 22, "star-diamond", 122, "star-diamond-open", 222, "star-diamond-dot", 322, "star-diamond-open-dot", 23, "diamond-tall", 123, "diamond-tall-open", 223, "diamond-tall-dot", 323, "diamond-tall-open-dot", 24, "diamond-wide", 124, "diamond-wide-open", 224, "diamond-wide-dot", 324, "diamond-wide-open-dot", 25, "hourglass", 125, "hourglass-open", 26, "bowtie", 126, "bowtie-open", 27, "circle-cross", 127, "circle-cross-open", 28, "circle-x", 128, "circle-x-open", 29, "square-cross", 129, "square-cross-open", 30, "square-x", 130, "square-x-open", 31, "diamond-cross", 131, "diamond-cross-open", 32, "diamond-x", 132, "diamond-x-open", 33, "cross-thin", 133, "cross-thin-open", 34, "x-thin", 134, "x-thin-open", 35, "asterisk", 135, "asterisk-open", 36, "hash", 136, "hash-open", 236, "hash-dot", 336, "hash-open-dot", 37, "y-up", 137, "y-up-open", 38, "y-down", 138, "y-down-open", 39, "y-left", 139, "y-left-open", 40, "y-right", 140, "y-right-open", 41, "line-ew", 141, "line-ew-open", 42, "line-ns", 142, "line-ns-open", 43, "line-ne", 143, "line-ne-open", 44, "line-nw", 144, "line-nw-open", ], ), **kwargs ) import _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="sizesrc", parent_name="area.marker", **kwargs): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="size", parent_name="area.marker", **kwargs): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacitysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="opacitysrc", parent_name="area.marker", **kwargs): super(OpacitysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="area.marker", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="colorsrc", parent_name="area.marker", **kwargs): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="area.marker", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/area/stream/0000755000175000017500000000000013573746614022167 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/area/stream/__init__.py0000644000175000017500000000205613573721536024277 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TokenValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="token", parent_name="area.stream", **kwargs): super(TokenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "info"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class MaxpointsValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="maxpoints", parent_name="area.stream", **kwargs): super(MaxpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 10000), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/area/__init__.py0000644000175000017500000003273013573721536023006 0ustar noahfxnoahfximport _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="visible", parent_name="area", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "legendonly"]), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="area", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UidValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="uid", parent_name="area", **kwargs): super(UidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="tsrc", parent_name="area", **kwargs): super(TsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="t", parent_name="area", **kwargs): super(TValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class StreamValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="stream", parent_name="area", **kwargs): super(StreamValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Stream"), data_docs=kwargs.pop( "data_docs", """ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """, ), **kwargs ) import _plotly_utils.basevalidators class ShowlegendValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showlegend", parent_name="area", **kwargs): super(ShowlegendValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class RsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="rsrc", parent_name="area", **kwargs): super(RsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class RValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="r", parent_name="area", **kwargs): super(RValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="area", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="area", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="metasrc", parent_name="area", **kwargs): super(MetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetaValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="meta", parent_name="area", **kwargs): super(MetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="marker", parent_name="area", **kwargs): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ color Area traces are deprecated! Please switch to the "barpolar" trace type. Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. colorsrc Sets the source reference on plot.ly for color . opacity Area traces are deprecated! Please switch to the "barpolar" trace type. Sets the marker opacity. opacitysrc Sets the source reference on plot.ly for opacity . size Area traces are deprecated! Please switch to the "barpolar" trace type. Sets the marker size (in px). sizesrc Sets the source reference on plot.ly for size . symbol Area traces are deprecated! Please switch to the "barpolar" trace type. Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot-open" to a symbol name. symbolsrc Sets the source reference on plot.ly for symbol . """, ), **kwargs ) import _plotly_utils.basevalidators class LegendgroupValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="legendgroup", parent_name="area", **kwargs): super(LegendgroupValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="idssrc", parent_name="area", **kwargs): super(IdssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ids", parent_name="area", **kwargs): super(IdsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class HoverlabelValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="hoverlabel", parent_name="area", **kwargs): super(HoverlabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Hoverlabel"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """, ), **kwargs ) import _plotly_utils.basevalidators class HoverinfosrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hoverinfosrc", parent_name="area", **kwargs): super(HoverinfosrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverinfoValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="hoverinfo", parent_name="area", **kwargs): super(HoverinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), extras=kwargs.pop("extras", ["all", "none", "skip"]), flags=kwargs.pop("flags", ["x", "y", "z", "text", "name"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdatasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="customdatasrc", parent_name="area", **kwargs): super(CustomdatasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdataValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="customdata", parent_name="area", **kwargs): super(CustomdataValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/histogram2dcontour/0000755000175000017500000000000013573746614023621 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/histogram2dcontour/ybins/0000755000175000017500000000000013573746614024745 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/histogram2dcontour/ybins/__init__.py0000644000175000017500000000255313573721537027060 0ustar noahfxnoahfximport _plotly_utils.basevalidators class StartValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="start", parent_name="histogram2dcontour.ybins", **kwargs ): super(StartValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="size", parent_name="histogram2dcontour.ybins", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EndValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="end", parent_name="histogram2dcontour.ybins", **kwargs ): super(EndValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/histogram2dcontour/hoverlabel/0000755000175000017500000000000013573746614025744 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/histogram2dcontour/hoverlabel/__init__.py0000644000175000017500000001405213573721537030054 0ustar noahfxnoahfximport _plotly_utils.basevalidators class NamelengthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="namelengthsrc", parent_name="histogram2dcontour.hoverlabel", **kwargs ): super(NamelengthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NamelengthValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="namelength", parent_name="histogram2dcontour.hoverlabel", **kwargs ): super(NamelengthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", -1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="histogram2dcontour.hoverlabel", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class BordercolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bordercolorsrc", parent_name="histogram2dcontour.hoverlabel", **kwargs ): super(BordercolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="histogram2dcontour.hoverlabel", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bgcolorsrc", parent_name="histogram2dcontour.hoverlabel", **kwargs ): super(BgcolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="histogram2dcontour.hoverlabel", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AlignsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="alignsrc", parent_name="histogram2dcontour.hoverlabel", **kwargs ): super(AlignsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="align", parent_name="histogram2dcontour.hoverlabel", **kwargs ): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "right", "auto"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/histogram2dcontour/hoverlabel/font/0000755000175000017500000000000013573746614026712 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/histogram2dcontour/hoverlabel/font/__init__.py0000644000175000017500000000636713573721537031034 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="histogram2dcontour.hoverlabel.font", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="histogram2dcontour.hoverlabel.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="histogram2dcontour.hoverlabel.font", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="histogram2dcontour.hoverlabel.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="histogram2dcontour.hoverlabel.font", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="histogram2dcontour.hoverlabel.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/histogram2dcontour/colorbar/0000755000175000017500000000000013573746614025424 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/histogram2dcontour/colorbar/tickformatstop/0000755000175000017500000000000013573746614030475 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/histogram2dcontour/colorbar/tickformatstop/__init__.py0000644000175000017500000000546313573721537032613 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="value", parent_name="histogram2dcontour.colorbar.tickformatstop", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="histogram2dcontour.colorbar.tickformatstop", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="histogram2dcontour.colorbar.tickformatstop", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EnabledValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="enabled", parent_name="histogram2dcontour.colorbar.tickformatstop", **kwargs ): super(EnabledValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DtickrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="dtickrange", parent_name="histogram2dcontour.colorbar.tickformatstop", **kwargs ): super(DtickrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "colorbars"}, {"valType": "any", "editType": "colorbars"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/histogram2dcontour/colorbar/title/0000755000175000017500000000000013573746614026545 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/histogram2dcontour/colorbar/title/__init__.py0000644000175000017500000000506613573721537030662 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="text", parent_name="histogram2dcontour.colorbar.title", **kwargs ): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SideValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="side", parent_name="histogram2dcontour.colorbar.title", **kwargs ): super(SideValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["right", "top", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="histogram2dcontour.colorbar.title", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/histogram2dcontour/colorbar/title/font/0000755000175000017500000000000013573746614027513 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/histogram2dcontour/colorbar/title/font/__init__.py0000644000175000017500000000320513573721537031621 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="histogram2dcontour.colorbar.title.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="histogram2dcontour.colorbar.title.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="histogram2dcontour.colorbar.title.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/histogram2dcontour/colorbar/__init__.py0000644000175000017500000006231413573721540027532 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ypad", parent_name="histogram2dcontour.colorbar", **kwargs ): super(YpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class YanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="yanchor", parent_name="histogram2dcontour.colorbar", **kwargs ): super(YanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["top", "middle", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="y", parent_name="histogram2dcontour.colorbar", **kwargs ): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="xpad", parent_name="histogram2dcontour.colorbar", **kwargs ): super(XpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="xanchor", parent_name="histogram2dcontour.colorbar", **kwargs ): super(XanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "center", "right"]), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="x", parent_name="histogram2dcontour.colorbar", **kwargs ): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TitleValidator(_plotly_utils.basevalidators.TitleValidator): def __init__( self, plotly_name="title", parent_name="histogram2dcontour.colorbar", **kwargs ): super(TitleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Title"), data_docs=kwargs.pop( "data_docs", """ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """, ), **kwargs ) import _plotly_utils.basevalidators class TickwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="tickwidth", parent_name="histogram2dcontour.colorbar", **kwargs ): super(TickwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickvalssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="tickvalssrc", parent_name="histogram2dcontour.colorbar", **kwargs ): super(TickvalssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickvalsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="tickvals", parent_name="histogram2dcontour.colorbar", **kwargs ): super(TickvalsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="ticktextsrc", parent_name="histogram2dcontour.colorbar", **kwargs ): super(TicktextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicktextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="ticktext", parent_name="histogram2dcontour.colorbar", **kwargs ): super(TicktextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="ticksuffix", parent_name="histogram2dcontour.colorbar", **kwargs ): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TicksValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="ticks", parent_name="histogram2dcontour.colorbar", **kwargs ): super(TicksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["outside", "inside", ""]), **kwargs ) import _plotly_utils.basevalidators class TickprefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickprefix", parent_name="histogram2dcontour.colorbar", **kwargs ): super(TickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="tickmode", parent_name="histogram2dcontour.colorbar", **kwargs ): super(TickmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "linear", "array"]), **kwargs ) import _plotly_utils.basevalidators class TicklenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ticklen", parent_name="histogram2dcontour.colorbar", **kwargs ): super(TicklenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickformatstopValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickformatstopdefaults", parent_name="histogram2dcontour.colorbar", **kwargs ): super(TickformatstopValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatstopsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="tickformatstops", parent_name="histogram2dcontour.colorbar", **kwargs ): super(TickformatstopsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickformat", parent_name="histogram2dcontour.colorbar", **kwargs ): super(TickformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickfont", parent_name="histogram2dcontour.colorbar", **kwargs ): super(TickfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class TickcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="tickcolor", parent_name="histogram2dcontour.colorbar", **kwargs ): super(TickcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__( self, plotly_name="tickangle", parent_name="histogram2dcontour.colorbar", **kwargs ): super(TickangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="tick0", parent_name="histogram2dcontour.colorbar", **kwargs ): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ThicknessmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="thicknessmode", parent_name="histogram2dcontour.colorbar", **kwargs ): super(ThicknessmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="thickness", parent_name="histogram2dcontour.colorbar", **kwargs ): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowticksuffixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showticksuffix", parent_name="histogram2dcontour.colorbar", **kwargs ): super(ShowticksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowtickprefixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showtickprefix", parent_name="histogram2dcontour.colorbar", **kwargs ): super(ShowtickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowticklabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showticklabels", parent_name="histogram2dcontour.colorbar", **kwargs ): super(ShowticklabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowexponentValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showexponent", parent_name="histogram2dcontour.colorbar", **kwargs ): super(ShowexponentValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class SeparatethousandsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="separatethousands", parent_name="histogram2dcontour.colorbar", **kwargs ): super(SeparatethousandsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="outlinewidth", parent_name="histogram2dcontour.colorbar", **kwargs ): super(OutlinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="outlinecolor", parent_name="histogram2dcontour.colorbar", **kwargs ): super(OutlinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NticksValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="nticks", parent_name="histogram2dcontour.colorbar", **kwargs ): super(NticksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LenmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="lenmode", parent_name="histogram2dcontour.colorbar", **kwargs ): super(LenmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class LenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="len", parent_name="histogram2dcontour.colorbar", **kwargs ): super(LenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ExponentformatValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="exponentformat", parent_name="histogram2dcontour.colorbar", **kwargs ): super(ExponentformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "e", "E", "power", "SI", "B"]), **kwargs ) import _plotly_utils.basevalidators class DtickValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="dtick", parent_name="histogram2dcontour.colorbar", **kwargs ): super(DtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BorderwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="borderwidth", parent_name="histogram2dcontour.colorbar", **kwargs ): super(BorderwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="histogram2dcontour.colorbar", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="histogram2dcontour.colorbar", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/histogram2dcontour/colorbar/tickfont/0000755000175000017500000000000013573746614027245 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/histogram2dcontour/colorbar/tickfont/__init__.py0000644000175000017500000000317713573721537031363 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="histogram2dcontour.colorbar.tickfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="histogram2dcontour.colorbar.tickfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="histogram2dcontour.colorbar.tickfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/histogram2dcontour/contours/0000755000175000017500000000000013573746614025475 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/histogram2dcontour/contours/labelfont/0000755000175000017500000000000013573746614027443 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/histogram2dcontour/contours/labelfont/__init__.py0000644000175000017500000000316413573721537031555 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="histogram2dcontour.contours.labelfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="histogram2dcontour.contours.labelfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="histogram2dcontour.contours.labelfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/histogram2dcontour/contours/__init__.py0000644000175000017500000001622613573721537027612 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="value", parent_name="histogram2dcontour.contours", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TypeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="type", parent_name="histogram2dcontour.contours", **kwargs ): super(TypeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["levels", "constraint"]), **kwargs ) import _plotly_utils.basevalidators class StartValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="start", parent_name="histogram2dcontour.contours", **kwargs ): super(StartValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"^autocontour": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="histogram2dcontour.contours", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"^autocontour": False}), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowlinesValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showlines", parent_name="histogram2dcontour.contours", **kwargs ): super(ShowlinesValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowlabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showlabels", parent_name="histogram2dcontour.contours", **kwargs ): super(ShowlabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OperationValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="operation", parent_name="histogram2dcontour.contours", **kwargs ): super(OperationValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "=", "<", ">=", ">", "<=", "[]", "()", "[)", "(]", "][", ")(", "](", ")[", ], ), **kwargs ) import _plotly_utils.basevalidators class LabelformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="labelformat", parent_name="histogram2dcontour.contours", **kwargs ): super(LabelformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LabelfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="labelfont", parent_name="histogram2dcontour.contours", **kwargs ): super(LabelfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Labelfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class EndValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="end", parent_name="histogram2dcontour.contours", **kwargs ): super(EndValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"^autocontour": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColoringValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="coloring", parent_name="histogram2dcontour.contours", **kwargs ): super(ColoringValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["fill", "heatmap", "lines", "none"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/histogram2dcontour/marker/0000755000175000017500000000000013573746614025102 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/histogram2dcontour/marker/__init__.py0000644000175000017500000000166113573721537027214 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="histogram2dcontour.marker", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="color", parent_name="histogram2dcontour.marker", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/histogram2dcontour/stream/0000755000175000017500000000000013573746614025114 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/histogram2dcontour/stream/__init__.py0000644000175000017500000000214613573721537027225 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TokenValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="token", parent_name="histogram2dcontour.stream", **kwargs ): super(TokenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "info"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class MaxpointsValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="maxpoints", parent_name="histogram2dcontour.stream", **kwargs ): super(MaxpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 10000), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/histogram2dcontour/__init__.py0000644000175000017500000014017113573721540025725 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ZsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="zsrc", parent_name="histogram2dcontour", **kwargs): super(ZsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="zmin", parent_name="histogram2dcontour", **kwargs): super(ZminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"zauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZmidValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="zmid", parent_name="histogram2dcontour", **kwargs): super(ZmidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZmaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="zmax", parent_name="histogram2dcontour", **kwargs): super(ZmaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"zauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZhoverformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="zhoverformat", parent_name="histogram2dcontour", **kwargs ): super(ZhoverformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ZautoValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="zauto", parent_name="histogram2dcontour", **kwargs): super(ZautoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="z", parent_name="histogram2dcontour", **kwargs): super(ZValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class YsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="ysrc", parent_name="histogram2dcontour", **kwargs): super(YsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YcalendarValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="ycalendar", parent_name="histogram2dcontour", **kwargs ): super(YcalendarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "gregorian", "chinese", "coptic", "discworld", "ethiopian", "hebrew", "islamic", "julian", "mayan", "nanakshahi", "nepali", "persian", "jalali", "taiwan", "thai", "ummalqura", ], ), **kwargs ) import _plotly_utils.basevalidators class YBinsValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="ybins", parent_name="histogram2dcontour", **kwargs): super(YBinsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "YBins"), data_docs=kwargs.pop( "data_docs", """ end Sets the end value for the y axis bins. The last bin may not end exactly at this value, we increment the bin edge by `size` from `start` until we reach or exceed `end`. Defaults to the maximum data value. Like `start`, for dates use a date string, and for category data `end` is based on the category serial numbers. size Sets the size of each y axis bin. Default behavior: If `nbinsy` is 0 or omitted, we choose a nice round bin size such that the number of bins is about the same as the typical number of samples in each bin. If `nbinsy` is provided, we choose a nice round bin size giving no more than that many bins. For date data, use milliseconds or "M" for months, as in `axis.dtick`. For category data, the number of categories to bin together (always defaults to 1). start Sets the starting value for the y axis bins. Defaults to the minimum data value, shifted down if necessary to make nice round values and to remove ambiguous bin edges. For example, if most of the data is integers we shift the bin edges 0.5 down, so a `size` of 5 would have a default `start` of -0.5, so it is clear that 0-4 are in the first bin, 5-9 in the second, but continuous data gets a start of 0 and bins [0,5), [5,10) etc. Dates behave similarly, and `start` should be a date string. For category data, `start` is based on the category serial numbers, and defaults to -0.5. """, ), **kwargs ) import _plotly_utils.basevalidators class YbingroupValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="ybingroup", parent_name="histogram2dcontour", **kwargs ): super(YbingroupValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YAxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="yaxis", parent_name="histogram2dcontour", **kwargs): super(YAxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "y"), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="y", parent_name="histogram2dcontour", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class XsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="xsrc", parent_name="histogram2dcontour", **kwargs): super(XsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XcalendarValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="xcalendar", parent_name="histogram2dcontour", **kwargs ): super(XcalendarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "gregorian", "chinese", "coptic", "discworld", "ethiopian", "hebrew", "islamic", "julian", "mayan", "nanakshahi", "nepali", "persian", "jalali", "taiwan", "thai", "ummalqura", ], ), **kwargs ) import _plotly_utils.basevalidators class XBinsValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="xbins", parent_name="histogram2dcontour", **kwargs): super(XBinsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "XBins"), data_docs=kwargs.pop( "data_docs", """ end Sets the end value for the x axis bins. The last bin may not end exactly at this value, we increment the bin edge by `size` from `start` until we reach or exceed `end`. Defaults to the maximum data value. Like `start`, for dates use a date string, and for category data `end` is based on the category serial numbers. size Sets the size of each x axis bin. Default behavior: If `nbinsx` is 0 or omitted, we choose a nice round bin size such that the number of bins is about the same as the typical number of samples in each bin. If `nbinsx` is provided, we choose a nice round bin size giving no more than that many bins. For date data, use milliseconds or "M" for months, as in `axis.dtick`. For category data, the number of categories to bin together (always defaults to 1). start Sets the starting value for the x axis bins. Defaults to the minimum data value, shifted down if necessary to make nice round values and to remove ambiguous bin edges. For example, if most of the data is integers we shift the bin edges 0.5 down, so a `size` of 5 would have a default `start` of -0.5, so it is clear that 0-4 are in the first bin, 5-9 in the second, but continuous data gets a start of 0 and bins [0,5), [5,10) etc. Dates behave similarly, and `start` should be a date string. For category data, `start` is based on the category serial numbers, and defaults to -0.5. """, ), **kwargs ) import _plotly_utils.basevalidators class XbingroupValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="xbingroup", parent_name="histogram2dcontour", **kwargs ): super(XbingroupValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XAxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="xaxis", parent_name="histogram2dcontour", **kwargs): super(XAxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "x"), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="x", parent_name="histogram2dcontour", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="visible", parent_name="histogram2dcontour", **kwargs ): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "legendonly"]), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="uirevision", parent_name="histogram2dcontour", **kwargs ): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UidValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="uid", parent_name="histogram2dcontour", **kwargs): super(UidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class StreamValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="stream", parent_name="histogram2dcontour", **kwargs ): super(StreamValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Stream"), data_docs=kwargs.pop( "data_docs", """ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """, ), **kwargs ) import _plotly_utils.basevalidators class ShowscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showscale", parent_name="histogram2dcontour", **kwargs ): super(ShowscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ShowlegendValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showlegend", parent_name="histogram2dcontour", **kwargs ): super(ShowlegendValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ReversescaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="reversescale", parent_name="histogram2dcontour", **kwargs ): super(ReversescaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="opacity", parent_name="histogram2dcontour", **kwargs ): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NcontoursValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="ncontours", parent_name="histogram2dcontour", **kwargs ): super(NcontoursValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NbinsyValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="nbinsy", parent_name="histogram2dcontour", **kwargs ): super(NbinsyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NbinsxValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="nbinsx", parent_name="histogram2dcontour", **kwargs ): super(NbinsxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="histogram2dcontour", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="metasrc", parent_name="histogram2dcontour", **kwargs ): super(MetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetaValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="meta", parent_name="histogram2dcontour", **kwargs): super(MetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="marker", parent_name="histogram2dcontour", **kwargs ): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ color Sets the aggregation data. colorsrc Sets the source reference on plot.ly for color . """, ), **kwargs ) import _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="line", parent_name="histogram2dcontour", **kwargs): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ color Sets the color of the contour level. Has no effect if `contours.coloring` is set to "lines". dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). smoothing Sets the amount of smoothing for the contour lines, where 0 corresponds to no smoothing. width Sets the contour line width in (in px) """, ), **kwargs ) import _plotly_utils.basevalidators class LegendgroupValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="legendgroup", parent_name="histogram2dcontour", **kwargs ): super(LegendgroupValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="idssrc", parent_name="histogram2dcontour", **kwargs ): super(IdssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ids", parent_name="histogram2dcontour", **kwargs): super(IdsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class HovertemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="hovertemplatesrc", parent_name="histogram2dcontour", **kwargs ): super(HovertemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="hovertemplate", parent_name="histogram2dcontour", **kwargs ): super(HovertemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverlabelValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="hoverlabel", parent_name="histogram2dcontour", **kwargs ): super(HoverlabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Hoverlabel"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """, ), **kwargs ) import _plotly_utils.basevalidators class HoverinfosrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="hoverinfosrc", parent_name="histogram2dcontour", **kwargs ): super(HoverinfosrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverinfoValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__( self, plotly_name="hoverinfo", parent_name="histogram2dcontour", **kwargs ): super(HoverinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), extras=kwargs.pop("extras", ["all", "none", "skip"]), flags=kwargs.pop("flags", ["x", "y", "z", "text", "name"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HistnormValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="histnorm", parent_name="histogram2dcontour", **kwargs ): super(HistnormValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", ["", "percent", "probability", "density", "probability density"], ), **kwargs ) import _plotly_utils.basevalidators class HistfuncValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="histfunc", parent_name="histogram2dcontour", **kwargs ): super(HistfuncValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["count", "sum", "avg", "min", "max"]), **kwargs ) import _plotly_utils.basevalidators class CustomdatasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="customdatasrc", parent_name="histogram2dcontour", **kwargs ): super(CustomdatasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdataValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="customdata", parent_name="histogram2dcontour", **kwargs ): super(CustomdataValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class ContoursValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="contours", parent_name="histogram2dcontour", **kwargs ): super(ContoursValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Contours"), data_docs=kwargs.pop( "data_docs", """ coloring Determines the coloring method showing the contour values. If "fill", coloring is done evenly between each contour level If "heatmap", a heatmap gradient coloring is applied between each contour level. If "lines", coloring is done on the contour lines. If "none", no coloring is applied on this trace. end Sets the end contour level value. Must be more than `contours.start` labelfont Sets the font used for labeling the contour levels. The default color comes from the lines, if shown. The default family and size come from `layout.font`. labelformat Sets the contour label formatting rule using d3 formatting mini-language which is very similar to Python, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format operation Sets the constraint operation. "=" keeps regions equal to `value` "<" and "<=" keep regions less than `value` ">" and ">=" keep regions greater than `value` "[]", "()", "[)", and "(]" keep regions inside `value[0]` to `value[1]` "][", ")(", "](", ")[" keep regions outside `value[0]` to value[1]` Open vs. closed intervals make no difference to constraint display, but all versions are allowed for consistency with filter transforms. showlabels Determines whether to label the contour lines with their values. showlines Determines whether or not the contour lines are drawn. Has an effect only if `contours.coloring` is set to "fill". size Sets the step between each contour level. Must be positive. start Sets the starting contour level value. Must be less than `contours.end` type If `levels`, the data is represented as a contour plot with multiple levels displayed. If `constraint`, the data is represented as constraints with the invalid region shaded as specified by the `operation` and `value` parameters. value Sets the value or values of the constraint boundary. When `operation` is set to one of the comparison values (=,<,>=,>,<=) "value" is expected to be a number. When `operation` is set to one of the interval values ([],(),[),(],][,)(,](,)[) "value" is expected to be an array of two numbers where the first is the lower bound and the second is the upper bound. """, ), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__( self, plotly_name="colorscale", parent_name="histogram2dcontour", **kwargs ): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"autocolorscale": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorBarValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="colorbar", parent_name="histogram2dcontour", **kwargs ): super(ColorBarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "ColorBar"), data_docs=kwargs.pop( "data_docs", """ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.histogram2dcont our.colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.histogram2dcontour.colorbar.tickformatstopdef aults), sets the default property values to use for elements of histogram2dcontour.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.histogram2dcontour.colorba r.Title instance or dict with compatible properties titlefont Deprecated: Please use histogram2dcontour.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use histogram2dcontour.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """, ), **kwargs ) import _plotly_utils.basevalidators class ColoraxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__( self, plotly_name="coloraxis", parent_name="histogram2dcontour", **kwargs ): super(ColoraxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", None), edit_type=kwargs.pop("edit_type", "calc"), regex=kwargs.pop("regex", "/^coloraxis([2-9]|[1-9][0-9]+)?$/"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BingroupValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="bingroup", parent_name="histogram2dcontour", **kwargs ): super(BingroupValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AutocontourValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="autocontour", parent_name="histogram2dcontour", **kwargs ): super(AutocontourValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AutocolorscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="autocolorscale", parent_name="histogram2dcontour", **kwargs ): super(AutocolorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AutobinyValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="autobiny", parent_name="histogram2dcontour", **kwargs ): super(AutobinyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AutobinxValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="autobinx", parent_name="histogram2dcontour", **kwargs ): super(AutobinxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/histogram2dcontour/line/0000755000175000017500000000000013573746614024550 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/histogram2dcontour/line/__init__.py0000644000175000017500000000414613573721537026663 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="width", parent_name="histogram2dcontour.line", **kwargs ): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style+colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SmoothingValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="smoothing", parent_name="histogram2dcontour.line", **kwargs ): super(SmoothingValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), max=kwargs.pop("max", 1.3), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class DashValidator(_plotly_utils.basevalidators.DashValidator): def __init__( self, plotly_name="dash", parent_name="histogram2dcontour.line", **kwargs ): super(DashValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", ["solid", "dot", "dash", "longdash", "dashdot", "longdashdot"] ), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="histogram2dcontour.line", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style+colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/histogram2dcontour/xbins/0000755000175000017500000000000013573746614024744 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/histogram2dcontour/xbins/__init__.py0000644000175000017500000000255313573721537027057 0ustar noahfxnoahfximport _plotly_utils.basevalidators class StartValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="start", parent_name="histogram2dcontour.xbins", **kwargs ): super(StartValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="size", parent_name="histogram2dcontour.xbins", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EndValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="end", parent_name="histogram2dcontour.xbins", **kwargs ): super(EndValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/frame/0000755000175000017500000000000013573746614021056 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/frame/__init__.py0000644000175000017500000000430513573721537023166 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TracesValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="traces", parent_name="frame", **kwargs): super(TracesValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="frame", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, role=kwargs.pop("role", "info"), **kwargs ) import plotly.validators class LayoutValidator(plotly.validators.LayoutValidator): def __init__(self, plotly_name="layout", parent_name="frame", **kwargs): super(LayoutValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, role=kwargs.pop("role", "object"), **kwargs ) import _plotly_utils.basevalidators class GroupValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="group", parent_name="frame", **kwargs): super(GroupValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, role=kwargs.pop("role", "info"), **kwargs ) import plotly.validators class DataValidator(plotly.validators.DataValidator): def __init__(self, plotly_name="data", parent_name="frame", **kwargs): super(DataValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, role=kwargs.pop("role", "object"), **kwargs ) import _plotly_utils.basevalidators class BaseframeValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="baseframe", parent_name="frame", **kwargs): super(BaseframeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/pointcloud/0000755000175000017500000000000013573746614022144 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/pointcloud/hoverlabel/0000755000175000017500000000000013573746614024267 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/pointcloud/hoverlabel/__init__.py0000644000175000017500000001352213573721541026373 0ustar noahfxnoahfximport _plotly_utils.basevalidators class NamelengthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="namelengthsrc", parent_name="pointcloud.hoverlabel", **kwargs ): super(NamelengthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NamelengthValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="namelength", parent_name="pointcloud.hoverlabel", **kwargs ): super(NamelengthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", -1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="pointcloud.hoverlabel", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class BordercolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bordercolorsrc", parent_name="pointcloud.hoverlabel", **kwargs ): super(BordercolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="pointcloud.hoverlabel", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bgcolorsrc", parent_name="pointcloud.hoverlabel", **kwargs ): super(BgcolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="pointcloud.hoverlabel", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AlignsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="alignsrc", parent_name="pointcloud.hoverlabel", **kwargs ): super(AlignsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="align", parent_name="pointcloud.hoverlabel", **kwargs ): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "right", "auto"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/pointcloud/hoverlabel/font/0000755000175000017500000000000013573746614025235 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/pointcloud/hoverlabel/font/__init__.py0000644000175000017500000000611713573721542027344 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="pointcloud.hoverlabel.font", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="pointcloud.hoverlabel.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="pointcloud.hoverlabel.font", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="pointcloud.hoverlabel.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="pointcloud.hoverlabel.font", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="pointcloud.hoverlabel.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/pointcloud/marker/0000755000175000017500000000000013573746614023425 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/pointcloud/marker/border/0000755000175000017500000000000013573746614024702 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/pointcloud/marker/border/__init__.py0000644000175000017500000000206313573721541027004 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="pointcloud.marker.border", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", False), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ArearatioValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="arearatio", parent_name="pointcloud.marker.border", **kwargs ): super(ArearatioValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/pointcloud/marker/__init__.py0000644000175000017500000000665213573721541025537 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="sizemin", parent_name="pointcloud.marker", **kwargs ): super(SizeminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 2), min=kwargs.pop("min", 0.1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SizemaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="sizemax", parent_name="pointcloud.marker", **kwargs ): super(SizemaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0.1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="opacity", parent_name="pointcloud.marker", **kwargs ): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", False), edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="pointcloud.marker", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", False), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BorderValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="border", parent_name="pointcloud.marker", **kwargs): super(BorderValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Border"), data_docs=kwargs.pop( "data_docs", """ arearatio Specifies what fraction of the marker area is covered with the border. color Sets the stroke color. It accepts a specific color. If the color is not fully opaque and there are hundreds of thousands of points, it may cause slower zooming and panning. """, ), **kwargs ) import _plotly_utils.basevalidators class BlendValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="blend", parent_name="pointcloud.marker", **kwargs): super(BlendValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/pointcloud/stream/0000755000175000017500000000000013573746614023437 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/pointcloud/stream/__init__.py0000644000175000017500000000211013573721541025532 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TokenValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="token", parent_name="pointcloud.stream", **kwargs): super(TokenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "info"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class MaxpointsValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="maxpoints", parent_name="pointcloud.stream", **kwargs ): super(MaxpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 10000), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/pointcloud/__init__.py0000644000175000017500000004564713573721542024266 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="ysrc", parent_name="pointcloud", **kwargs): super(YsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YboundssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="yboundssrc", parent_name="pointcloud", **kwargs): super(YboundssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YboundsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ybounds", parent_name="pointcloud", **kwargs): super(YboundsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class YAxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="yaxis", parent_name="pointcloud", **kwargs): super(YAxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "y"), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="y", parent_name="pointcloud", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class XysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="xysrc", parent_name="pointcloud", **kwargs): super(XysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XyValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="xy", parent_name="pointcloud", **kwargs): super(XyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class XsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="xsrc", parent_name="pointcloud", **kwargs): super(XsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XboundssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="xboundssrc", parent_name="pointcloud", **kwargs): super(XboundssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XboundsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="xbounds", parent_name="pointcloud", **kwargs): super(XboundsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class XAxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="xaxis", parent_name="pointcloud", **kwargs): super(XAxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "x"), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="x", parent_name="pointcloud", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="visible", parent_name="pointcloud", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "legendonly"]), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="pointcloud", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UidValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="uid", parent_name="pointcloud", **kwargs): super(UidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="textsrc", parent_name="pointcloud", **kwargs): super(TextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="text", parent_name="pointcloud", **kwargs): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class StreamValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="stream", parent_name="pointcloud", **kwargs): super(StreamValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Stream"), data_docs=kwargs.pop( "data_docs", """ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """, ), **kwargs ) import _plotly_utils.basevalidators class ShowlegendValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showlegend", parent_name="pointcloud", **kwargs): super(ShowlegendValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="pointcloud", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="pointcloud", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="metasrc", parent_name="pointcloud", **kwargs): super(MetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetaValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="meta", parent_name="pointcloud", **kwargs): super(MetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="marker", parent_name="pointcloud", **kwargs): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ blend Determines if colors are blended together for a translucency effect in case `opacity` is specified as a value less then `1`. Setting `blend` to `true` reduces zoom/pan speed if used with large numbers of points. border plotly.graph_objects.pointcloud.marker.Border instance or dict with compatible properties color Sets the marker fill color. It accepts a specific color.If the color is not fully opaque and there are hundreds of thousandsof points, it may cause slower zooming and panning. opacity Sets the marker opacity. The default value is `1` (fully opaque). If the markers are not fully opaque and there are hundreds of thousands of points, it may cause slower zooming and panning. Opacity fades the color even if `blend` is left on `false` even if there is no translucency effect in that case. sizemax Sets the maximum size (in px) of the rendered marker points. Effective when the `pointcloud` shows only few points. sizemin Sets the minimum size (in px) of the rendered marker points, effective when the `pointcloud` shows a million or more points. """, ), **kwargs ) import _plotly_utils.basevalidators class LegendgroupValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="legendgroup", parent_name="pointcloud", **kwargs): super(LegendgroupValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IndicessrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="indicessrc", parent_name="pointcloud", **kwargs): super(IndicessrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IndicesValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="indices", parent_name="pointcloud", **kwargs): super(IndicesValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class IdssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="idssrc", parent_name="pointcloud", **kwargs): super(IdssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ids", parent_name="pointcloud", **kwargs): super(IdsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class HoverlabelValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="hoverlabel", parent_name="pointcloud", **kwargs): super(HoverlabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Hoverlabel"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """, ), **kwargs ) import _plotly_utils.basevalidators class HoverinfosrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hoverinfosrc", parent_name="pointcloud", **kwargs): super(HoverinfosrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverinfoValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="hoverinfo", parent_name="pointcloud", **kwargs): super(HoverinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), extras=kwargs.pop("extras", ["all", "none", "skip"]), flags=kwargs.pop("flags", ["x", "y", "z", "text", "name"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdatasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="customdatasrc", parent_name="pointcloud", **kwargs): super(CustomdatasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdataValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="customdata", parent_name="pointcloud", **kwargs): super(CustomdataValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattercarpet/0000755000175000017500000000000013573746614022630 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattercarpet/unselected/0000755000175000017500000000000013573746614024763 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattercarpet/unselected/textfont/0000755000175000017500000000000013573746614026636 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattercarpet/unselected/textfont/__init__.py0000644000175000017500000000076413573721542030747 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scattercarpet.unselected.textfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattercarpet/unselected/marker/0000755000175000017500000000000013573746614026244 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattercarpet/unselected/marker/__init__.py0000644000175000017500000000312113573721542030343 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scattercarpet.unselected.marker", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="opacity", parent_name="scattercarpet.unselected.marker", **kwargs ): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scattercarpet.unselected.marker", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattercarpet/unselected/__init__.py0000644000175000017500000000313113573721542027063 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="textfont", parent_name="scattercarpet.unselected", **kwargs ): super(TextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Textfont"), data_docs=kwargs.pop( "data_docs", """ color Sets the text font color of unselected points, applied only when a selection exists. """, ), **kwargs ) import _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="marker", parent_name="scattercarpet.unselected", **kwargs ): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. size Sets the marker size of unselected points, applied only when a selection exists. """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattercarpet/textfont/0000755000175000017500000000000013573746614024503 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattercarpet/textfont/__init__.py0000644000175000017500000000604013573721542026605 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="scattercarpet.textfont", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scattercarpet.textfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="scattercarpet.textfont", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="scattercarpet.textfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="scattercarpet.textfont", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scattercarpet.textfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattercarpet/hoverlabel/0000755000175000017500000000000013573746614024753 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattercarpet/hoverlabel/__init__.py0000644000175000017500000001363513573721542027065 0ustar noahfxnoahfximport _plotly_utils.basevalidators class NamelengthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="namelengthsrc", parent_name="scattercarpet.hoverlabel", **kwargs ): super(NamelengthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NamelengthValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="namelength", parent_name="scattercarpet.hoverlabel", **kwargs ): super(NamelengthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", -1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="scattercarpet.hoverlabel", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class BordercolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bordercolorsrc", parent_name="scattercarpet.hoverlabel", **kwargs ): super(BordercolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="scattercarpet.hoverlabel", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bgcolorsrc", parent_name="scattercarpet.hoverlabel", **kwargs ): super(BgcolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="scattercarpet.hoverlabel", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AlignsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="alignsrc", parent_name="scattercarpet.hoverlabel", **kwargs ): super(AlignsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="align", parent_name="scattercarpet.hoverlabel", **kwargs ): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "right", "auto"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattercarpet/hoverlabel/font/0000755000175000017500000000000013573746614025721 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattercarpet/hoverlabel/font/__init__.py0000644000175000017500000000625113573721542030027 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="scattercarpet.hoverlabel.font", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scattercarpet.hoverlabel.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="scattercarpet.hoverlabel.font", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="scattercarpet.hoverlabel.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="scattercarpet.hoverlabel.font", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scattercarpet.hoverlabel.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattercarpet/marker/0000755000175000017500000000000013573746614024111 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattercarpet/marker/colorbar/0000755000175000017500000000000013573746614025714 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattercarpet/marker/colorbar/tickformatstop/0000755000175000017500000000000013573746614030765 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattercarpet/marker/colorbar/tickformatstop/__init__.py0000644000175000017500000000547513573721542033102 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="value", parent_name="scattercarpet.marker.colorbar.tickformatstop", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="scattercarpet.marker.colorbar.tickformatstop", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="scattercarpet.marker.colorbar.tickformatstop", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EnabledValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="enabled", parent_name="scattercarpet.marker.colorbar.tickformatstop", **kwargs ): super(EnabledValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DtickrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="dtickrange", parent_name="scattercarpet.marker.colorbar.tickformatstop", **kwargs ): super(DtickrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "colorbars"}, {"valType": "any", "editType": "colorbars"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattercarpet/marker/colorbar/title/0000755000175000017500000000000013573746614027035 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattercarpet/marker/colorbar/title/__init__.py0000644000175000017500000000507413573721542031145 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="text", parent_name="scattercarpet.marker.colorbar.title", **kwargs ): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SideValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="side", parent_name="scattercarpet.marker.colorbar.title", **kwargs ): super(SideValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["right", "top", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="scattercarpet.marker.colorbar.title", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattercarpet/marker/colorbar/title/font/0000755000175000017500000000000013573746614030003 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattercarpet/marker/colorbar/title/font/__init__.py0000644000175000017500000000321313573721542032104 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scattercarpet.marker.colorbar.title.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="scattercarpet.marker.colorbar.title.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scattercarpet.marker.colorbar.title.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattercarpet/marker/colorbar/__init__.py0000644000175000017500000006265613573721543030036 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ypad", parent_name="scattercarpet.marker.colorbar", **kwargs ): super(YpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class YanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="yanchor", parent_name="scattercarpet.marker.colorbar", **kwargs ): super(YanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["top", "middle", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="y", parent_name="scattercarpet.marker.colorbar", **kwargs ): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="xpad", parent_name="scattercarpet.marker.colorbar", **kwargs ): super(XpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="xanchor", parent_name="scattercarpet.marker.colorbar", **kwargs ): super(XanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "center", "right"]), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="x", parent_name="scattercarpet.marker.colorbar", **kwargs ): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TitleValidator(_plotly_utils.basevalidators.TitleValidator): def __init__( self, plotly_name="title", parent_name="scattercarpet.marker.colorbar", **kwargs ): super(TitleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Title"), data_docs=kwargs.pop( "data_docs", """ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """, ), **kwargs ) import _plotly_utils.basevalidators class TickwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="tickwidth", parent_name="scattercarpet.marker.colorbar", **kwargs ): super(TickwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickvalssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="tickvalssrc", parent_name="scattercarpet.marker.colorbar", **kwargs ): super(TickvalssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickvalsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="tickvals", parent_name="scattercarpet.marker.colorbar", **kwargs ): super(TickvalsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="ticktextsrc", parent_name="scattercarpet.marker.colorbar", **kwargs ): super(TicktextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicktextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="ticktext", parent_name="scattercarpet.marker.colorbar", **kwargs ): super(TicktextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="ticksuffix", parent_name="scattercarpet.marker.colorbar", **kwargs ): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TicksValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="ticks", parent_name="scattercarpet.marker.colorbar", **kwargs ): super(TicksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["outside", "inside", ""]), **kwargs ) import _plotly_utils.basevalidators class TickprefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickprefix", parent_name="scattercarpet.marker.colorbar", **kwargs ): super(TickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="tickmode", parent_name="scattercarpet.marker.colorbar", **kwargs ): super(TickmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "linear", "array"]), **kwargs ) import _plotly_utils.basevalidators class TicklenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ticklen", parent_name="scattercarpet.marker.colorbar", **kwargs ): super(TicklenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickformatstopValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickformatstopdefaults", parent_name="scattercarpet.marker.colorbar", **kwargs ): super(TickformatstopValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatstopsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="tickformatstops", parent_name="scattercarpet.marker.colorbar", **kwargs ): super(TickformatstopsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickformat", parent_name="scattercarpet.marker.colorbar", **kwargs ): super(TickformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickfont", parent_name="scattercarpet.marker.colorbar", **kwargs ): super(TickfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class TickcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="tickcolor", parent_name="scattercarpet.marker.colorbar", **kwargs ): super(TickcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__( self, plotly_name="tickangle", parent_name="scattercarpet.marker.colorbar", **kwargs ): super(TickangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="tick0", parent_name="scattercarpet.marker.colorbar", **kwargs ): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ThicknessmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="thicknessmode", parent_name="scattercarpet.marker.colorbar", **kwargs ): super(ThicknessmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="thickness", parent_name="scattercarpet.marker.colorbar", **kwargs ): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowticksuffixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showticksuffix", parent_name="scattercarpet.marker.colorbar", **kwargs ): super(ShowticksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowtickprefixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showtickprefix", parent_name="scattercarpet.marker.colorbar", **kwargs ): super(ShowtickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowticklabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showticklabels", parent_name="scattercarpet.marker.colorbar", **kwargs ): super(ShowticklabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowexponentValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showexponent", parent_name="scattercarpet.marker.colorbar", **kwargs ): super(ShowexponentValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class SeparatethousandsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="separatethousands", parent_name="scattercarpet.marker.colorbar", **kwargs ): super(SeparatethousandsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="outlinewidth", parent_name="scattercarpet.marker.colorbar", **kwargs ): super(OutlinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="outlinecolor", parent_name="scattercarpet.marker.colorbar", **kwargs ): super(OutlinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NticksValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="nticks", parent_name="scattercarpet.marker.colorbar", **kwargs ): super(NticksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LenmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="lenmode", parent_name="scattercarpet.marker.colorbar", **kwargs ): super(LenmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class LenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="len", parent_name="scattercarpet.marker.colorbar", **kwargs ): super(LenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ExponentformatValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="exponentformat", parent_name="scattercarpet.marker.colorbar", **kwargs ): super(ExponentformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "e", "E", "power", "SI", "B"]), **kwargs ) import _plotly_utils.basevalidators class DtickValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="dtick", parent_name="scattercarpet.marker.colorbar", **kwargs ): super(DtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BorderwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="borderwidth", parent_name="scattercarpet.marker.colorbar", **kwargs ): super(BorderwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="scattercarpet.marker.colorbar", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="scattercarpet.marker.colorbar", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattercarpet/marker/colorbar/tickfont/0000755000175000017500000000000013573746614027535 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattercarpet/marker/colorbar/tickfont/__init__.py0000644000175000017500000000320513573721542031637 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scattercarpet.marker.colorbar.tickfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="scattercarpet.marker.colorbar.tickfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scattercarpet.marker.colorbar.tickfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattercarpet/marker/gradient/0000755000175000017500000000000013573746614025706 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattercarpet/marker/gradient/__init__.py0000644000175000017500000000413213573721542030010 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TypesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="typesrc", parent_name="scattercarpet.marker.gradient", **kwargs ): super(TypesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TypeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="type", parent_name="scattercarpet.marker.gradient", **kwargs ): super(TypeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["radial", "horizontal", "vertical", "none"]), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="scattercarpet.marker.gradient", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scattercarpet.marker.gradient", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattercarpet/marker/__init__.py0000644000175000017500000011007013573721543026213 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SymbolsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="symbolsrc", parent_name="scattercarpet.marker", **kwargs ): super(SymbolsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SymbolValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="symbol", parent_name="scattercarpet.marker", **kwargs ): super(SymbolValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", [ 0, "circle", 100, "circle-open", 200, "circle-dot", 300, "circle-open-dot", 1, "square", 101, "square-open", 201, "square-dot", 301, "square-open-dot", 2, "diamond", 102, "diamond-open", 202, "diamond-dot", 302, "diamond-open-dot", 3, "cross", 103, "cross-open", 203, "cross-dot", 303, "cross-open-dot", 4, "x", 104, "x-open", 204, "x-dot", 304, "x-open-dot", 5, "triangle-up", 105, "triangle-up-open", 205, "triangle-up-dot", 305, "triangle-up-open-dot", 6, "triangle-down", 106, "triangle-down-open", 206, "triangle-down-dot", 306, "triangle-down-open-dot", 7, "triangle-left", 107, "triangle-left-open", 207, "triangle-left-dot", 307, "triangle-left-open-dot", 8, "triangle-right", 108, "triangle-right-open", 208, "triangle-right-dot", 308, "triangle-right-open-dot", 9, "triangle-ne", 109, "triangle-ne-open", 209, "triangle-ne-dot", 309, "triangle-ne-open-dot", 10, "triangle-se", 110, "triangle-se-open", 210, "triangle-se-dot", 310, "triangle-se-open-dot", 11, "triangle-sw", 111, "triangle-sw-open", 211, "triangle-sw-dot", 311, "triangle-sw-open-dot", 12, "triangle-nw", 112, "triangle-nw-open", 212, "triangle-nw-dot", 312, "triangle-nw-open-dot", 13, "pentagon", 113, "pentagon-open", 213, "pentagon-dot", 313, "pentagon-open-dot", 14, "hexagon", 114, "hexagon-open", 214, "hexagon-dot", 314, "hexagon-open-dot", 15, "hexagon2", 115, "hexagon2-open", 215, "hexagon2-dot", 315, "hexagon2-open-dot", 16, "octagon", 116, "octagon-open", 216, "octagon-dot", 316, "octagon-open-dot", 17, "star", 117, "star-open", 217, "star-dot", 317, "star-open-dot", 18, "hexagram", 118, "hexagram-open", 218, "hexagram-dot", 318, "hexagram-open-dot", 19, "star-triangle-up", 119, "star-triangle-up-open", 219, "star-triangle-up-dot", 319, "star-triangle-up-open-dot", 20, "star-triangle-down", 120, "star-triangle-down-open", 220, "star-triangle-down-dot", 320, "star-triangle-down-open-dot", 21, "star-square", 121, "star-square-open", 221, "star-square-dot", 321, "star-square-open-dot", 22, "star-diamond", 122, "star-diamond-open", 222, "star-diamond-dot", 322, "star-diamond-open-dot", 23, "diamond-tall", 123, "diamond-tall-open", 223, "diamond-tall-dot", 323, "diamond-tall-open-dot", 24, "diamond-wide", 124, "diamond-wide-open", 224, "diamond-wide-dot", 324, "diamond-wide-open-dot", 25, "hourglass", 125, "hourglass-open", 26, "bowtie", 126, "bowtie-open", 27, "circle-cross", 127, "circle-cross-open", 28, "circle-x", 128, "circle-x-open", 29, "square-cross", 129, "square-cross-open", 30, "square-x", 130, "square-x-open", 31, "diamond-cross", 131, "diamond-cross-open", 32, "diamond-x", 132, "diamond-x-open", 33, "cross-thin", 133, "cross-thin-open", 34, "x-thin", 134, "x-thin-open", 35, "asterisk", 135, "asterisk-open", 36, "hash", 136, "hash-open", 236, "hash-dot", 336, "hash-open-dot", 37, "y-up", 137, "y-up-open", 38, "y-down", 138, "y-down-open", 39, "y-left", 139, "y-left-open", 40, "y-right", 140, "y-right-open", 41, "line-ew", 141, "line-ew-open", 42, "line-ns", 142, "line-ns-open", 43, "line-ne", 143, "line-ne-open", 44, "line-nw", 144, "line-nw-open", ], ), **kwargs ) import _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="scattercarpet.marker", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizerefValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="sizeref", parent_name="scattercarpet.marker", **kwargs ): super(SizerefValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SizemodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="sizemode", parent_name="scattercarpet.marker", **kwargs ): super(SizemodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["diameter", "area"]), **kwargs ) import _plotly_utils.basevalidators class SizeminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="sizemin", parent_name="scattercarpet.marker", **kwargs ): super(SizeminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scattercarpet.marker", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showscale", parent_name="scattercarpet.marker", **kwargs ): super(ShowscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ReversescaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="reversescale", parent_name="scattercarpet.marker", **kwargs ): super(ReversescaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacitysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="opacitysrc", parent_name="scattercarpet.marker", **kwargs ): super(OpacitysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="opacity", parent_name="scattercarpet.marker", **kwargs ): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class MaxdisplayedValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="maxdisplayed", parent_name="scattercarpet.marker", **kwargs ): super(MaxdisplayedValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="line", parent_name="scattercarpet.marker", **kwargs ): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,R eds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Black body,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . """, ), **kwargs ) import _plotly_utils.basevalidators class GradientValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="gradient", parent_name="scattercarpet.marker", **kwargs ): super(GradientValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Gradient"), data_docs=kwargs.pop( "data_docs", """ color Sets the final color of the gradient fill: the center color for radial, the right for horizontal, or the bottom for vertical. colorsrc Sets the source reference on plot.ly for color . type Sets the type of gradient used to fill the markers typesrc Sets the source reference on plot.ly for type . """, ), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="scattercarpet.marker", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__( self, plotly_name="colorscale", parent_name="scattercarpet.marker", **kwargs ): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"autocolorscale": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorBarValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="colorbar", parent_name="scattercarpet.marker", **kwargs ): super(ColorBarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "ColorBar"), data_docs=kwargs.pop( "data_docs", """ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.scattercarpet.m arker.colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.scattercarpet.marker.colorbar.tickformatstopd efaults), sets the default property values to use for elements of scattercarpet.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.scattercarpet.marker.color bar.Title instance or dict with compatible properties titlefont Deprecated: Please use scattercarpet.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use scattercarpet.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """, ), **kwargs ) import _plotly_utils.basevalidators class ColoraxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__( self, plotly_name="coloraxis", parent_name="scattercarpet.marker", **kwargs ): super(ColoraxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", None), edit_type=kwargs.pop("edit_type", "calc"), regex=kwargs.pop("regex", "/^coloraxis([2-9]|[1-9][0-9]+)?$/"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scattercarpet.marker", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), colorscale_path=kwargs.pop( "colorscale_path", "scattercarpet.marker.colorscale" ), **kwargs ) import _plotly_utils.basevalidators class CminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="cmin", parent_name="scattercarpet.marker", **kwargs ): super(CminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmidValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="cmid", parent_name="scattercarpet.marker", **kwargs ): super(CmidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="cmax", parent_name="scattercarpet.marker", **kwargs ): super(CmaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CautoValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="cauto", parent_name="scattercarpet.marker", **kwargs ): super(CautoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AutocolorscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="autocolorscale", parent_name="scattercarpet.marker", **kwargs ): super(AutocolorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattercarpet/marker/line/0000755000175000017500000000000013573746614025040 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattercarpet/marker/line/__init__.py0000644000175000017500000001467113573721542027153 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="widthsrc", parent_name="scattercarpet.marker.line", **kwargs ): super(WidthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="width", parent_name="scattercarpet.marker.line", **kwargs ): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ReversescaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="reversescale", parent_name="scattercarpet.marker.line", **kwargs ): super(ReversescaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="scattercarpet.marker.line", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__( self, plotly_name="colorscale", parent_name="scattercarpet.marker.line", **kwargs ): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"autocolorscale": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColoraxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__( self, plotly_name="coloraxis", parent_name="scattercarpet.marker.line", **kwargs ): super(ColoraxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", None), edit_type=kwargs.pop("edit_type", "calc"), regex=kwargs.pop("regex", "/^coloraxis([2-9]|[1-9][0-9]+)?$/"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scattercarpet.marker.line", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), colorscale_path=kwargs.pop( "colorscale_path", "scattercarpet.marker.line.colorscale" ), **kwargs ) import _plotly_utils.basevalidators class CminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="cmin", parent_name="scattercarpet.marker.line", **kwargs ): super(CminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmidValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="cmid", parent_name="scattercarpet.marker.line", **kwargs ): super(CmidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="cmax", parent_name="scattercarpet.marker.line", **kwargs ): super(CmaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CautoValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="cauto", parent_name="scattercarpet.marker.line", **kwargs ): super(CautoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AutocolorscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="autocolorscale", parent_name="scattercarpet.marker.line", **kwargs ): super(AutocolorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattercarpet/stream/0000755000175000017500000000000013573746614024123 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattercarpet/stream/__init__.py0000644000175000017500000000213413573721542026225 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TokenValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="token", parent_name="scattercarpet.stream", **kwargs ): super(TokenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "info"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class MaxpointsValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="maxpoints", parent_name="scattercarpet.stream", **kwargs ): super(MaxpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 10000), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattercarpet/__init__.py0000644000175000017500000010137113573721543024736 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YAxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="yaxis", parent_name="scattercarpet", **kwargs): super(YAxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "y"), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XAxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="xaxis", parent_name="scattercarpet", **kwargs): super(XAxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "x"), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="visible", parent_name="scattercarpet", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "legendonly"]), **kwargs ) import _plotly_utils.basevalidators class UnselectedValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="unselected", parent_name="scattercarpet", **kwargs): super(UnselectedValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Unselected"), data_docs=kwargs.pop( "data_docs", """ marker plotly.graph_objects.scattercarpet.unselected.M arker instance or dict with compatible properties textfont plotly.graph_objects.scattercarpet.unselected.T extfont instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="scattercarpet", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UidValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="uid", parent_name="scattercarpet", **kwargs): super(UidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TexttemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="texttemplatesrc", parent_name="scattercarpet", **kwargs ): super(TexttemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TexttemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="texttemplate", parent_name="scattercarpet", **kwargs ): super(TexttemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="textsrc", parent_name="scattercarpet", **kwargs): super(TextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextpositionsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="textpositionsrc", parent_name="scattercarpet", **kwargs ): super(TextpositionsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextpositionValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="textposition", parent_name="scattercarpet", **kwargs ): super(TextpositionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", [ "top left", "top center", "top right", "middle left", "middle center", "middle right", "bottom left", "bottom center", "bottom right", ], ), **kwargs ) import _plotly_utils.basevalidators class TextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="textfont", parent_name="scattercarpet", **kwargs): super(TextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Textfont"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="text", parent_name="scattercarpet", **kwargs): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class StreamValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="stream", parent_name="scattercarpet", **kwargs): super(StreamValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Stream"), data_docs=kwargs.pop( "data_docs", """ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """, ), **kwargs ) import _plotly_utils.basevalidators class ShowlegendValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showlegend", parent_name="scattercarpet", **kwargs): super(ShowlegendValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SelectedpointsValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="selectedpoints", parent_name="scattercarpet", **kwargs ): super(SelectedpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SelectedValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="selected", parent_name="scattercarpet", **kwargs): super(SelectedValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Selected"), data_docs=kwargs.pop( "data_docs", """ marker plotly.graph_objects.scattercarpet.selected.Mar ker instance or dict with compatible properties textfont plotly.graph_objects.scattercarpet.selected.Tex tfont instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="scattercarpet", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="scattercarpet", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ModeValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="mode", parent_name="scattercarpet", **kwargs): super(ModeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), extras=kwargs.pop("extras", ["none"]), flags=kwargs.pop("flags", ["lines", "markers", "text"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="metasrc", parent_name="scattercarpet", **kwargs): super(MetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetaValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="meta", parent_name="scattercarpet", **kwargs): super(MetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="marker", parent_name="scattercarpet", **kwargs): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.scattercarpet.marker.Color Bar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . gradient plotly.graph_objects.scattercarpet.marker.Gradi ent instance or dict with compatible properties line plotly.graph_objects.scattercarpet.marker.Line instance or dict with compatible properties maxdisplayed Sets a maximum number of points to be drawn on the graph. 0 corresponds to no limit. opacity Sets the marker opacity. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. size Sets the marker size (in px). sizemin Has an effect only if `marker.size` is set to a numerical array. Sets the minimum size (in px) of the rendered marker points. sizemode Has an effect only if `marker.size` is set to a numerical array. Sets the rule for which the data in `size` is converted to pixels. sizeref Has an effect only if `marker.size` is set to a numerical array. Sets the scale factor used to determine the rendered size of marker points. Use with `sizemin` and `sizemode`. sizesrc Sets the source reference on plot.ly for size . symbol Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot- open" to a symbol name. symbolsrc Sets the source reference on plot.ly for symbol . """, ), **kwargs ) import _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="line", parent_name="scattercarpet", **kwargs): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ color Sets the line color. dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). shape Determines the line shape. With "spline" the lines are drawn using spline interpolation. The other available values correspond to step-wise line shapes. smoothing Has an effect only if `shape` is set to "spline" Sets the amount of smoothing. 0 corresponds to no smoothing (equivalent to a "linear" shape). width Sets the line width (in px). """, ), **kwargs ) import _plotly_utils.basevalidators class LegendgroupValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="legendgroup", parent_name="scattercarpet", **kwargs ): super(LegendgroupValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="idssrc", parent_name="scattercarpet", **kwargs): super(IdssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ids", parent_name="scattercarpet", **kwargs): super(IdsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class HovertextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="hovertextsrc", parent_name="scattercarpet", **kwargs ): super(HovertextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertext", parent_name="scattercarpet", **kwargs): super(HovertextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="hovertemplatesrc", parent_name="scattercarpet", **kwargs ): super(HovertemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="hovertemplate", parent_name="scattercarpet", **kwargs ): super(HovertemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoveronValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="hoveron", parent_name="scattercarpet", **kwargs): super(HoveronValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), flags=kwargs.pop("flags", ["points", "fills"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverlabelValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="hoverlabel", parent_name="scattercarpet", **kwargs): super(HoverlabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Hoverlabel"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """, ), **kwargs ) import _plotly_utils.basevalidators class HoverinfosrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="hoverinfosrc", parent_name="scattercarpet", **kwargs ): super(HoverinfosrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverinfoValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="hoverinfo", parent_name="scattercarpet", **kwargs): super(HoverinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), extras=kwargs.pop("extras", ["all", "none", "skip"]), flags=kwargs.pop("flags", ["a", "b", "text", "name"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FillcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="fillcolor", parent_name="scattercarpet", **kwargs): super(FillcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FillValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="fill", parent_name="scattercarpet", **kwargs): super(FillValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "toself", "tonext"]), **kwargs ) import _plotly_utils.basevalidators class CustomdatasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="customdatasrc", parent_name="scattercarpet", **kwargs ): super(CustomdatasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdataValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="customdata", parent_name="scattercarpet", **kwargs): super(CustomdataValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class ConnectgapsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="connectgaps", parent_name="scattercarpet", **kwargs ): super(ConnectgapsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CarpetValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="carpet", parent_name="scattercarpet", **kwargs): super(CarpetValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="bsrc", parent_name="scattercarpet", **kwargs): super(BsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="b", parent_name="scattercarpet", **kwargs): super(BValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class AsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="asrc", parent_name="scattercarpet", **kwargs): super(AsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="a", parent_name="scattercarpet", **kwargs): super(AValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattercarpet/line/0000755000175000017500000000000013573746614023557 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattercarpet/line/__init__.py0000644000175000017500000000503013573721542025657 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="scattercarpet.line", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SmoothingValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="smoothing", parent_name="scattercarpet.line", **kwargs ): super(SmoothingValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), max=kwargs.pop("max", 1.3), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShapeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="shape", parent_name="scattercarpet.line", **kwargs): super(ShapeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["linear", "spline"]), **kwargs ) import _plotly_utils.basevalidators class DashValidator(_plotly_utils.basevalidators.DashValidator): def __init__(self, plotly_name="dash", parent_name="scattercarpet.line", **kwargs): super(DashValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", ["solid", "dot", "dash", "longdash", "dashdot", "longdashdot"] ), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="scattercarpet.line", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattercarpet/selected/0000755000175000017500000000000013573746614024420 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattercarpet/selected/textfont/0000755000175000017500000000000013573746614026273 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattercarpet/selected/textfont/__init__.py0000644000175000017500000000076213573721542030402 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scattercarpet.selected.textfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattercarpet/selected/marker/0000755000175000017500000000000013573746614025701 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scattercarpet/selected/marker/__init__.py0000644000175000017500000000303313573721542030002 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scattercarpet.selected.marker", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="opacity", parent_name="scattercarpet.selected.marker", **kwargs ): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scattercarpet.selected.marker", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scattercarpet/selected/__init__.py0000644000175000017500000000256513573721542026532 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="textfont", parent_name="scattercarpet.selected", **kwargs ): super(TextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Textfont"), data_docs=kwargs.pop( "data_docs", """ color Sets the text font color of selected points. """, ), **kwargs ) import _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="marker", parent_name="scattercarpet.selected", **kwargs ): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. size Sets the marker size of selected points. """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/parcats/0000755000175000017500000000000013573746614021421 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/parcats/labelfont/0000755000175000017500000000000013573746614023367 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/parcats/labelfont/__init__.py0000644000175000017500000000270513573721541025474 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="size", parent_name="parcats.labelfont", **kwargs): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="family", parent_name="parcats.labelfont", **kwargs): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="parcats.labelfont", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/parcats/stream/0000755000175000017500000000000013573746614022714 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/parcats/stream/__init__.py0000644000175000017500000000206413573721541025017 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TokenValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="token", parent_name="parcats.stream", **kwargs): super(TokenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "info"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class MaxpointsValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="maxpoints", parent_name="parcats.stream", **kwargs): super(MaxpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 10000), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/parcats/__init__.py0000644000175000017500000005311513573721542023530 0ustar noahfxnoahfximport _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="visible", parent_name="parcats", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "legendonly"]), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="parcats", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UidValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="uid", parent_name="parcats", **kwargs): super(UidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="tickfont", parent_name="parcats", **kwargs): super(TickfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class StreamValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="stream", parent_name="parcats", **kwargs): super(StreamValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Stream"), data_docs=kwargs.pop( "data_docs", """ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """, ), **kwargs ) import _plotly_utils.basevalidators class SortpathsValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="sortpaths", parent_name="parcats", **kwargs): super(SortpathsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["forward", "backward"]), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="parcats", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="metasrc", parent_name="parcats", **kwargs): super(MetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetaValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="meta", parent_name="parcats", **kwargs): super(MetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="line", parent_name="parcats", **kwargs): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `line.colorscale`. Has an effect only if in `line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `line.color`) or the bounds set in `line.cmin` and `line.cmax` Has an effect only if in `line.color`is set to a numerical array. Defaults to `false` when `line.cmin` and `line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `line.color`is set to a numerical array. Value should have the same units as in `line.color` and if set, `line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `line.cmin` and/or `line.cmax` to be equidistant to this point. Has an effect only if in `line.color`is set to a numerical array. Value should have the same units as in `line.color`. Has no effect when `line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `line.color`is set to a numerical array. Value should have the same units as in `line.color` and if set, `line.cmax` must be set as well. color Sets thelinecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `line.cmin` and `line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.parcats.line.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`line.cmin` and `line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu ,Greens,YlOrRd,Bluered,RdBu,Reds,Blues,Picnic,R ainbow,Portland,Jet,Hot,Blackbody,Earth,Electri c,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs- events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `count` and `probability`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. reversescale Reverses the color mapping if true. Has an effect only if in `line.color`is set to a numerical array. If true, `line.cmin` will correspond to the last color in the array and `line.cmax` will correspond to the first color. shape Sets the shape of the paths. If `linear`, paths are composed of straight lines. If `hspline`, paths are composed of horizontal curved splines showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `line.color`is set to a numerical array. """, ), **kwargs ) import _plotly_utils.basevalidators class LabelfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="labelfont", parent_name="parcats", **kwargs): super(LabelfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Labelfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class HovertemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertemplate", parent_name="parcats", **kwargs): super(HovertemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoveronValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="hoveron", parent_name="parcats", **kwargs): super(HoveronValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["category", "color", "dimension"]), **kwargs ) import _plotly_utils.basevalidators class HoverinfoValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="hoverinfo", parent_name="parcats", **kwargs): super(HoverinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", False), edit_type=kwargs.pop("edit_type", "plot"), extras=kwargs.pop("extras", ["all", "none", "skip"]), flags=kwargs.pop("flags", ["count", "probability"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DomainValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="domain", parent_name="parcats", **kwargs): super(DomainValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Domain"), data_docs=kwargs.pop( "data_docs", """ column If there is a layout grid, use the domain for this column in the grid for this parcats trace . row If there is a layout grid, use the domain for this row in the grid for this parcats trace . x Sets the horizontal domain of this parcats trace (in plot fraction). y Sets the vertical domain of this parcats trace (in plot fraction). """, ), **kwargs ) import _plotly_utils.basevalidators class DimensionValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="dimensiondefaults", parent_name="parcats", **kwargs ): super(DimensionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Dimension"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class DimensionsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__(self, plotly_name="dimensions", parent_name="parcats", **kwargs): super(DimensionsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Dimension"), data_docs=kwargs.pop( "data_docs", """ categoryarray Sets the order in which categories in this dimension appear. Only has an effect if `categoryorder` is set to "array". Used with `categoryorder`. categoryarraysrc Sets the source reference on plot.ly for categoryarray . categoryorder Specifies the ordering logic for the categories in the dimension. By default, plotly uses "trace", which specifies the order that is present in the data supplied. Set `categoryorder` to *category ascending* or *category descending* if order should be determined by the alphanumerical order of the category names. Set `categoryorder` to "array" to derive the ordering from the attribute `categoryarray`. If a category is not found in the `categoryarray` array, the sorting behavior for that attribute will be identical to the "trace" mode. The unspecified categories will follow the categories in `categoryarray`. displayindex The display index of dimension, from left to right, zero indexed, defaults to dimension index. label The shown name of the dimension. ticktext Sets alternative tick labels for the categories in this dimension. Only has an effect if `categoryorder` is set to "array". Should be an array the same length as `categoryarray` Used with `categoryorder`. ticktextsrc Sets the source reference on plot.ly for ticktext . values Dimension values. `values[n]` represents the category value of the `n`th point in the dataset, therefore the `values` vector for all dimensions must be the same (longer vectors will be truncated). valuessrc Sets the source reference on plot.ly for values . visible Shows the dimension when set to `true` (the default). Hides the dimension for `false`. """, ), **kwargs ) import _plotly_utils.basevalidators class CountssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="countssrc", parent_name="parcats", **kwargs): super(CountssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CountsValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="counts", parent_name="parcats", **kwargs): super(CountsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BundlecolorsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="bundlecolors", parent_name="parcats", **kwargs): super(BundlecolorsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ArrangementValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="arrangement", parent_name="parcats", **kwargs): super(ArrangementValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["perpendicular", "freeform", "fixed"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/parcats/dimension/0000755000175000017500000000000013573746614023406 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/parcats/dimension/__init__.py0000644000175000017500000001143113573721541025507 0ustar noahfxnoahfximport _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="visible", parent_name="parcats.dimension", **kwargs ): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ValuessrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="valuessrc", parent_name="parcats.dimension", **kwargs ): super(ValuessrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ValuesValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="values", parent_name="parcats.dimension", **kwargs): super(ValuesValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="ticktextsrc", parent_name="parcats.dimension", **kwargs ): super(TicktextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicktextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="ticktext", parent_name="parcats.dimension", **kwargs ): super(TicktextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class LabelValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="label", parent_name="parcats.dimension", **kwargs): super(LabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DisplayindexValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="displayindex", parent_name="parcats.dimension", **kwargs ): super(DisplayindexValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CategoryorderValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="categoryorder", parent_name="parcats.dimension", **kwargs ): super(CategoryorderValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", ["trace", "category ascending", "category descending", "array"], ), **kwargs ) import _plotly_utils.basevalidators class CategoryarraysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="categoryarraysrc", parent_name="parcats.dimension", **kwargs ): super(CategoryarraysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CategoryarrayValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="categoryarray", parent_name="parcats.dimension", **kwargs ): super(CategoryarrayValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/parcats/line/0000755000175000017500000000000013573746614022350 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/parcats/line/colorbar/0000755000175000017500000000000013573746614024153 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/parcats/line/colorbar/tickformatstop/0000755000175000017500000000000013573746614027224 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/parcats/line/colorbar/tickformatstop/__init__.py0000644000175000017500000000542513573721541031333 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="value", parent_name="parcats.line.colorbar.tickformatstop", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="parcats.line.colorbar.tickformatstop", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="parcats.line.colorbar.tickformatstop", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EnabledValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="enabled", parent_name="parcats.line.colorbar.tickformatstop", **kwargs ): super(EnabledValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DtickrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="dtickrange", parent_name="parcats.line.colorbar.tickformatstop", **kwargs ): super(DtickrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "colorbars"}, {"valType": "any", "editType": "colorbars"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/parcats/line/colorbar/title/0000755000175000017500000000000013573746614025274 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/parcats/line/colorbar/title/__init__.py0000644000175000017500000000473413573721541027405 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="text", parent_name="parcats.line.colorbar.title", **kwargs ): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SideValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="side", parent_name="parcats.line.colorbar.title", **kwargs ): super(SideValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["right", "top", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="parcats.line.colorbar.title", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/parcats/line/colorbar/title/font/0000755000175000017500000000000013573746614026242 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/parcats/line/colorbar/title/font/__init__.py0000644000175000017500000000316313573721541030346 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="parcats.line.colorbar.title.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="parcats.line.colorbar.title.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="parcats.line.colorbar.title.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/parcats/line/colorbar/__init__.py0000644000175000017500000006076213573721542026270 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ypad", parent_name="parcats.line.colorbar", **kwargs ): super(YpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class YanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="yanchor", parent_name="parcats.line.colorbar", **kwargs ): super(YanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["top", "middle", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="y", parent_name="parcats.line.colorbar", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="xpad", parent_name="parcats.line.colorbar", **kwargs ): super(XpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="xanchor", parent_name="parcats.line.colorbar", **kwargs ): super(XanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "center", "right"]), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="x", parent_name="parcats.line.colorbar", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TitleValidator(_plotly_utils.basevalidators.TitleValidator): def __init__( self, plotly_name="title", parent_name="parcats.line.colorbar", **kwargs ): super(TitleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Title"), data_docs=kwargs.pop( "data_docs", """ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """, ), **kwargs ) import _plotly_utils.basevalidators class TickwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="tickwidth", parent_name="parcats.line.colorbar", **kwargs ): super(TickwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickvalssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="tickvalssrc", parent_name="parcats.line.colorbar", **kwargs ): super(TickvalssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickvalsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="tickvals", parent_name="parcats.line.colorbar", **kwargs ): super(TickvalsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="ticktextsrc", parent_name="parcats.line.colorbar", **kwargs ): super(TicktextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicktextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="ticktext", parent_name="parcats.line.colorbar", **kwargs ): super(TicktextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="ticksuffix", parent_name="parcats.line.colorbar", **kwargs ): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TicksValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="ticks", parent_name="parcats.line.colorbar", **kwargs ): super(TicksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["outside", "inside", ""]), **kwargs ) import _plotly_utils.basevalidators class TickprefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickprefix", parent_name="parcats.line.colorbar", **kwargs ): super(TickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="tickmode", parent_name="parcats.line.colorbar", **kwargs ): super(TickmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "linear", "array"]), **kwargs ) import _plotly_utils.basevalidators class TicklenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ticklen", parent_name="parcats.line.colorbar", **kwargs ): super(TicklenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickformatstopValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickformatstopdefaults", parent_name="parcats.line.colorbar", **kwargs ): super(TickformatstopValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatstopsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="tickformatstops", parent_name="parcats.line.colorbar", **kwargs ): super(TickformatstopsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickformat", parent_name="parcats.line.colorbar", **kwargs ): super(TickformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickfont", parent_name="parcats.line.colorbar", **kwargs ): super(TickfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class TickcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="tickcolor", parent_name="parcats.line.colorbar", **kwargs ): super(TickcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__( self, plotly_name="tickangle", parent_name="parcats.line.colorbar", **kwargs ): super(TickangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="tick0", parent_name="parcats.line.colorbar", **kwargs ): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ThicknessmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="thicknessmode", parent_name="parcats.line.colorbar", **kwargs ): super(ThicknessmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="thickness", parent_name="parcats.line.colorbar", **kwargs ): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowticksuffixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showticksuffix", parent_name="parcats.line.colorbar", **kwargs ): super(ShowticksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowtickprefixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showtickprefix", parent_name="parcats.line.colorbar", **kwargs ): super(ShowtickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowticklabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showticklabels", parent_name="parcats.line.colorbar", **kwargs ): super(ShowticklabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowexponentValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showexponent", parent_name="parcats.line.colorbar", **kwargs ): super(ShowexponentValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class SeparatethousandsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="separatethousands", parent_name="parcats.line.colorbar", **kwargs ): super(SeparatethousandsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="outlinewidth", parent_name="parcats.line.colorbar", **kwargs ): super(OutlinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="outlinecolor", parent_name="parcats.line.colorbar", **kwargs ): super(OutlinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NticksValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="nticks", parent_name="parcats.line.colorbar", **kwargs ): super(NticksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LenmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="lenmode", parent_name="parcats.line.colorbar", **kwargs ): super(LenmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class LenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="len", parent_name="parcats.line.colorbar", **kwargs ): super(LenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ExponentformatValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="exponentformat", parent_name="parcats.line.colorbar", **kwargs ): super(ExponentformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "e", "E", "power", "SI", "B"]), **kwargs ) import _plotly_utils.basevalidators class DtickValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="dtick", parent_name="parcats.line.colorbar", **kwargs ): super(DtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BorderwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="borderwidth", parent_name="parcats.line.colorbar", **kwargs ): super(BorderwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="parcats.line.colorbar", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="parcats.line.colorbar", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/parcats/line/colorbar/tickfont/0000755000175000017500000000000013573746614025774 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/parcats/line/colorbar/tickfont/__init__.py0000644000175000017500000000312513573721541030076 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="parcats.line.colorbar.tickfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="parcats.line.colorbar.tickfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="parcats.line.colorbar.tickfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/parcats/line/__init__.py0000644000175000017500000004200213573721541024447 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ShowscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showscale", parent_name="parcats.line", **kwargs): super(ShowscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ShapeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="shape", parent_name="parcats.line", **kwargs): super(ShapeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["linear", "hspline"]), **kwargs ) import _plotly_utils.basevalidators class ReversescaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="reversescale", parent_name="parcats.line", **kwargs ): super(ReversescaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class HovertemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="hovertemplate", parent_name="parcats.line", **kwargs ): super(HovertemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="colorsrc", parent_name="parcats.line", **kwargs): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__(self, plotly_name="colorscale", parent_name="parcats.line", **kwargs): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"autocolorscale": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorBarValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="colorbar", parent_name="parcats.line", **kwargs): super(ColorBarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "ColorBar"), data_docs=kwargs.pop( "data_docs", """ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.parcats.line.co lorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.parcats.line.colorbar.tickformatstopdefaults) , sets the default property values to use for elements of parcats.line.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.parcats.line.colorbar.Titl e instance or dict with compatible properties titlefont Deprecated: Please use parcats.line.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use parcats.line.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """, ), **kwargs ) import _plotly_utils.basevalidators class ColoraxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="coloraxis", parent_name="parcats.line", **kwargs): super(ColoraxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", None), edit_type=kwargs.pop("edit_type", "calc"), regex=kwargs.pop("regex", "/^coloraxis([2-9]|[1-9][0-9]+)?$/"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="parcats.line", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), colorscale_path=kwargs.pop("colorscale_path", "parcats.line.colorscale"), **kwargs ) import _plotly_utils.basevalidators class CminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmin", parent_name="parcats.line", **kwargs): super(CminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmidValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmid", parent_name="parcats.line", **kwargs): super(CmidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmax", parent_name="parcats.line", **kwargs): super(CmaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CautoValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="cauto", parent_name="parcats.line", **kwargs): super(CautoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AutocolorscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="autocolorscale", parent_name="parcats.line", **kwargs ): super(AutocolorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/parcats/domain/0000755000175000017500000000000013573746614022670 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/parcats/domain/__init__.py0000644000175000017500000000451113573721541024772 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="y", parent_name="parcats.domain", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), items=kwargs.pop( "items", [ {"valType": "number", "min": 0, "max": 1, "editType": "calc"}, {"valType": "number", "min": 0, "max": 1, "editType": "calc"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="x", parent_name="parcats.domain", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), items=kwargs.pop( "items", [ {"valType": "number", "min": 0, "max": 1, "editType": "calc"}, {"valType": "number", "min": 0, "max": 1, "editType": "calc"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class RowValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="row", parent_name="parcats.domain", **kwargs): super(RowValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColumnValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="column", parent_name="parcats.domain", **kwargs): super(ColumnValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/parcats/tickfont/0000755000175000017500000000000013573746614023242 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/parcats/tickfont/__init__.py0000644000175000017500000000270213573721541025344 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="size", parent_name="parcats.tickfont", **kwargs): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="family", parent_name="parcats.tickfont", **kwargs): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="parcats.tickfont", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterpolar/0000755000175000017500000000000013573746614022467 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterpolar/unselected/0000755000175000017500000000000013573746614024622 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterpolar/unselected/textfont/0000755000175000017500000000000013573746614026475 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterpolar/unselected/textfont/__init__.py0000644000175000017500000000076313573721543030606 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scatterpolar.unselected.textfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterpolar/unselected/marker/0000755000175000017500000000000013573746614026103 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterpolar/unselected/marker/__init__.py0000644000175000017500000000306613573721543030213 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scatterpolar.unselected.marker", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="opacity", parent_name="scatterpolar.unselected.marker", **kwargs ): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scatterpolar.unselected.marker", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterpolar/unselected/__init__.py0000644000175000017500000000312713573721543026730 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="textfont", parent_name="scatterpolar.unselected", **kwargs ): super(TextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Textfont"), data_docs=kwargs.pop( "data_docs", """ color Sets the text font color of unselected points, applied only when a selection exists. """, ), **kwargs ) import _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="marker", parent_name="scatterpolar.unselected", **kwargs ): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. size Sets the marker size of unselected points, applied only when a selection exists. """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterpolar/textfont/0000755000175000017500000000000013573746614024342 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterpolar/textfont/__init__.py0000644000175000017500000000603213573721543026446 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="scatterpolar.textfont", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scatterpolar.textfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="scatterpolar.textfont", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="scatterpolar.textfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="scatterpolar.textfont", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scatterpolar.textfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterpolar/hoverlabel/0000755000175000017500000000000013573746614024612 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterpolar/hoverlabel/__init__.py0000644000175000017500000001357413573721543026727 0ustar noahfxnoahfximport _plotly_utils.basevalidators class NamelengthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="namelengthsrc", parent_name="scatterpolar.hoverlabel", **kwargs ): super(NamelengthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NamelengthValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="namelength", parent_name="scatterpolar.hoverlabel", **kwargs ): super(NamelengthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", -1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="scatterpolar.hoverlabel", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class BordercolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bordercolorsrc", parent_name="scatterpolar.hoverlabel", **kwargs ): super(BordercolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="scatterpolar.hoverlabel", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bgcolorsrc", parent_name="scatterpolar.hoverlabel", **kwargs ): super(BgcolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="scatterpolar.hoverlabel", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AlignsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="alignsrc", parent_name="scatterpolar.hoverlabel", **kwargs ): super(AlignsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="align", parent_name="scatterpolar.hoverlabel", **kwargs ): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "right", "auto"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterpolar/hoverlabel/font/0000755000175000017500000000000013573746614025560 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterpolar/hoverlabel/font/__init__.py0000644000175000017500000000621313573721543027665 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="scatterpolar.hoverlabel.font", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scatterpolar.hoverlabel.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="scatterpolar.hoverlabel.font", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="scatterpolar.hoverlabel.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="scatterpolar.hoverlabel.font", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scatterpolar.hoverlabel.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterpolar/marker/0000755000175000017500000000000013573746614023750 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterpolar/marker/colorbar/0000755000175000017500000000000013573746614025553 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterpolar/marker/colorbar/tickformatstop/0000755000175000017500000000000013573746614030624 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterpolar/marker/colorbar/tickformatstop/__init__.py0000644000175000017500000000547013573721543032735 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="value", parent_name="scatterpolar.marker.colorbar.tickformatstop", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="scatterpolar.marker.colorbar.tickformatstop", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="scatterpolar.marker.colorbar.tickformatstop", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EnabledValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="enabled", parent_name="scatterpolar.marker.colorbar.tickformatstop", **kwargs ): super(EnabledValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DtickrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="dtickrange", parent_name="scatterpolar.marker.colorbar.tickformatstop", **kwargs ): super(DtickrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "colorbars"}, {"valType": "any", "editType": "colorbars"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterpolar/marker/colorbar/title/0000755000175000017500000000000013573746614026674 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterpolar/marker/colorbar/title/__init__.py0000644000175000017500000000507113573721543031002 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="text", parent_name="scatterpolar.marker.colorbar.title", **kwargs ): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SideValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="side", parent_name="scatterpolar.marker.colorbar.title", **kwargs ): super(SideValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["right", "top", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="scatterpolar.marker.colorbar.title", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterpolar/marker/colorbar/title/font/0000755000175000017500000000000013573746614027642 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterpolar/marker/colorbar/title/font/__init__.py0000644000175000017500000000321013573721543031741 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scatterpolar.marker.colorbar.title.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="scatterpolar.marker.colorbar.title.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scatterpolar.marker.colorbar.title.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterpolar/marker/colorbar/__init__.py0000644000175000017500000006255513573721543027673 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ypad", parent_name="scatterpolar.marker.colorbar", **kwargs ): super(YpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class YanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="yanchor", parent_name="scatterpolar.marker.colorbar", **kwargs ): super(YanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["top", "middle", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="y", parent_name="scatterpolar.marker.colorbar", **kwargs ): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="xpad", parent_name="scatterpolar.marker.colorbar", **kwargs ): super(XpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="xanchor", parent_name="scatterpolar.marker.colorbar", **kwargs ): super(XanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "center", "right"]), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="x", parent_name="scatterpolar.marker.colorbar", **kwargs ): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TitleValidator(_plotly_utils.basevalidators.TitleValidator): def __init__( self, plotly_name="title", parent_name="scatterpolar.marker.colorbar", **kwargs ): super(TitleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Title"), data_docs=kwargs.pop( "data_docs", """ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """, ), **kwargs ) import _plotly_utils.basevalidators class TickwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="tickwidth", parent_name="scatterpolar.marker.colorbar", **kwargs ): super(TickwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickvalssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="tickvalssrc", parent_name="scatterpolar.marker.colorbar", **kwargs ): super(TickvalssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickvalsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="tickvals", parent_name="scatterpolar.marker.colorbar", **kwargs ): super(TickvalsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="ticktextsrc", parent_name="scatterpolar.marker.colorbar", **kwargs ): super(TicktextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicktextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="ticktext", parent_name="scatterpolar.marker.colorbar", **kwargs ): super(TicktextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="ticksuffix", parent_name="scatterpolar.marker.colorbar", **kwargs ): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TicksValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="ticks", parent_name="scatterpolar.marker.colorbar", **kwargs ): super(TicksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["outside", "inside", ""]), **kwargs ) import _plotly_utils.basevalidators class TickprefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickprefix", parent_name="scatterpolar.marker.colorbar", **kwargs ): super(TickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="tickmode", parent_name="scatterpolar.marker.colorbar", **kwargs ): super(TickmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "linear", "array"]), **kwargs ) import _plotly_utils.basevalidators class TicklenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ticklen", parent_name="scatterpolar.marker.colorbar", **kwargs ): super(TicklenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickformatstopValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickformatstopdefaults", parent_name="scatterpolar.marker.colorbar", **kwargs ): super(TickformatstopValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatstopsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="tickformatstops", parent_name="scatterpolar.marker.colorbar", **kwargs ): super(TickformatstopsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickformat", parent_name="scatterpolar.marker.colorbar", **kwargs ): super(TickformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickfont", parent_name="scatterpolar.marker.colorbar", **kwargs ): super(TickfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class TickcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="tickcolor", parent_name="scatterpolar.marker.colorbar", **kwargs ): super(TickcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__( self, plotly_name="tickangle", parent_name="scatterpolar.marker.colorbar", **kwargs ): super(TickangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="tick0", parent_name="scatterpolar.marker.colorbar", **kwargs ): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ThicknessmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="thicknessmode", parent_name="scatterpolar.marker.colorbar", **kwargs ): super(ThicknessmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="thickness", parent_name="scatterpolar.marker.colorbar", **kwargs ): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowticksuffixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showticksuffix", parent_name="scatterpolar.marker.colorbar", **kwargs ): super(ShowticksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowtickprefixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showtickprefix", parent_name="scatterpolar.marker.colorbar", **kwargs ): super(ShowtickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowticklabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showticklabels", parent_name="scatterpolar.marker.colorbar", **kwargs ): super(ShowticklabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowexponentValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showexponent", parent_name="scatterpolar.marker.colorbar", **kwargs ): super(ShowexponentValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class SeparatethousandsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="separatethousands", parent_name="scatterpolar.marker.colorbar", **kwargs ): super(SeparatethousandsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="outlinewidth", parent_name="scatterpolar.marker.colorbar", **kwargs ): super(OutlinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="outlinecolor", parent_name="scatterpolar.marker.colorbar", **kwargs ): super(OutlinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NticksValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="nticks", parent_name="scatterpolar.marker.colorbar", **kwargs ): super(NticksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LenmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="lenmode", parent_name="scatterpolar.marker.colorbar", **kwargs ): super(LenmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class LenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="len", parent_name="scatterpolar.marker.colorbar", **kwargs ): super(LenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ExponentformatValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="exponentformat", parent_name="scatterpolar.marker.colorbar", **kwargs ): super(ExponentformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "e", "E", "power", "SI", "B"]), **kwargs ) import _plotly_utils.basevalidators class DtickValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="dtick", parent_name="scatterpolar.marker.colorbar", **kwargs ): super(DtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BorderwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="borderwidth", parent_name="scatterpolar.marker.colorbar", **kwargs ): super(BorderwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="scatterpolar.marker.colorbar", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="scatterpolar.marker.colorbar", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterpolar/marker/colorbar/tickfont/0000755000175000017500000000000013573746614027374 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterpolar/marker/colorbar/tickfont/__init__.py0000644000175000017500000000320213573721543031474 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scatterpolar.marker.colorbar.tickfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="scatterpolar.marker.colorbar.tickfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scatterpolar.marker.colorbar.tickfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterpolar/marker/gradient/0000755000175000017500000000000013573746614025545 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterpolar/marker/gradient/__init__.py0000644000175000017500000000412613573721543027653 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TypesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="typesrc", parent_name="scatterpolar.marker.gradient", **kwargs ): super(TypesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TypeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="type", parent_name="scatterpolar.marker.gradient", **kwargs ): super(TypeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["radial", "horizontal", "vertical", "none"]), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="scatterpolar.marker.gradient", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scatterpolar.marker.gradient", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterpolar/marker/__init__.py0000644000175000017500000010772313573721543026065 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SymbolsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="symbolsrc", parent_name="scatterpolar.marker", **kwargs ): super(SymbolsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SymbolValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="symbol", parent_name="scatterpolar.marker", **kwargs ): super(SymbolValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", [ 0, "circle", 100, "circle-open", 200, "circle-dot", 300, "circle-open-dot", 1, "square", 101, "square-open", 201, "square-dot", 301, "square-open-dot", 2, "diamond", 102, "diamond-open", 202, "diamond-dot", 302, "diamond-open-dot", 3, "cross", 103, "cross-open", 203, "cross-dot", 303, "cross-open-dot", 4, "x", 104, "x-open", 204, "x-dot", 304, "x-open-dot", 5, "triangle-up", 105, "triangle-up-open", 205, "triangle-up-dot", 305, "triangle-up-open-dot", 6, "triangle-down", 106, "triangle-down-open", 206, "triangle-down-dot", 306, "triangle-down-open-dot", 7, "triangle-left", 107, "triangle-left-open", 207, "triangle-left-dot", 307, "triangle-left-open-dot", 8, "triangle-right", 108, "triangle-right-open", 208, "triangle-right-dot", 308, "triangle-right-open-dot", 9, "triangle-ne", 109, "triangle-ne-open", 209, "triangle-ne-dot", 309, "triangle-ne-open-dot", 10, "triangle-se", 110, "triangle-se-open", 210, "triangle-se-dot", 310, "triangle-se-open-dot", 11, "triangle-sw", 111, "triangle-sw-open", 211, "triangle-sw-dot", 311, "triangle-sw-open-dot", 12, "triangle-nw", 112, "triangle-nw-open", 212, "triangle-nw-dot", 312, "triangle-nw-open-dot", 13, "pentagon", 113, "pentagon-open", 213, "pentagon-dot", 313, "pentagon-open-dot", 14, "hexagon", 114, "hexagon-open", 214, "hexagon-dot", 314, "hexagon-open-dot", 15, "hexagon2", 115, "hexagon2-open", 215, "hexagon2-dot", 315, "hexagon2-open-dot", 16, "octagon", 116, "octagon-open", 216, "octagon-dot", 316, "octagon-open-dot", 17, "star", 117, "star-open", 217, "star-dot", 317, "star-open-dot", 18, "hexagram", 118, "hexagram-open", 218, "hexagram-dot", 318, "hexagram-open-dot", 19, "star-triangle-up", 119, "star-triangle-up-open", 219, "star-triangle-up-dot", 319, "star-triangle-up-open-dot", 20, "star-triangle-down", 120, "star-triangle-down-open", 220, "star-triangle-down-dot", 320, "star-triangle-down-open-dot", 21, "star-square", 121, "star-square-open", 221, "star-square-dot", 321, "star-square-open-dot", 22, "star-diamond", 122, "star-diamond-open", 222, "star-diamond-dot", 322, "star-diamond-open-dot", 23, "diamond-tall", 123, "diamond-tall-open", 223, "diamond-tall-dot", 323, "diamond-tall-open-dot", 24, "diamond-wide", 124, "diamond-wide-open", 224, "diamond-wide-dot", 324, "diamond-wide-open-dot", 25, "hourglass", 125, "hourglass-open", 26, "bowtie", 126, "bowtie-open", 27, "circle-cross", 127, "circle-cross-open", 28, "circle-x", 128, "circle-x-open", 29, "square-cross", 129, "square-cross-open", 30, "square-x", 130, "square-x-open", 31, "diamond-cross", 131, "diamond-cross-open", 32, "diamond-x", 132, "diamond-x-open", 33, "cross-thin", 133, "cross-thin-open", 34, "x-thin", 134, "x-thin-open", 35, "asterisk", 135, "asterisk-open", 36, "hash", 136, "hash-open", 236, "hash-dot", 336, "hash-open-dot", 37, "y-up", 137, "y-up-open", 38, "y-down", 138, "y-down-open", 39, "y-left", 139, "y-left-open", 40, "y-right", 140, "y-right-open", 41, "line-ew", 141, "line-ew-open", 42, "line-ns", 142, "line-ns-open", 43, "line-ne", 143, "line-ne-open", 44, "line-nw", 144, "line-nw-open", ], ), **kwargs ) import _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="scatterpolar.marker", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizerefValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="sizeref", parent_name="scatterpolar.marker", **kwargs ): super(SizerefValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SizemodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="sizemode", parent_name="scatterpolar.marker", **kwargs ): super(SizemodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["diameter", "area"]), **kwargs ) import _plotly_utils.basevalidators class SizeminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="sizemin", parent_name="scatterpolar.marker", **kwargs ): super(SizeminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="size", parent_name="scatterpolar.marker", **kwargs): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showscale", parent_name="scatterpolar.marker", **kwargs ): super(ShowscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ReversescaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="reversescale", parent_name="scatterpolar.marker", **kwargs ): super(ReversescaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacitysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="opacitysrc", parent_name="scatterpolar.marker", **kwargs ): super(OpacitysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="opacity", parent_name="scatterpolar.marker", **kwargs ): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class MaxdisplayedValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="maxdisplayed", parent_name="scatterpolar.marker", **kwargs ): super(MaxdisplayedValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="line", parent_name="scatterpolar.marker", **kwargs): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,R eds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Black body,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . """, ), **kwargs ) import _plotly_utils.basevalidators class GradientValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="gradient", parent_name="scatterpolar.marker", **kwargs ): super(GradientValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Gradient"), data_docs=kwargs.pop( "data_docs", """ color Sets the final color of the gradient fill: the center color for radial, the right for horizontal, or the bottom for vertical. colorsrc Sets the source reference on plot.ly for color . type Sets the type of gradient used to fill the markers typesrc Sets the source reference on plot.ly for type . """, ), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="scatterpolar.marker", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__( self, plotly_name="colorscale", parent_name="scatterpolar.marker", **kwargs ): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"autocolorscale": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorBarValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="colorbar", parent_name="scatterpolar.marker", **kwargs ): super(ColorBarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "ColorBar"), data_docs=kwargs.pop( "data_docs", """ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.scatterpolar.ma rker.colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.scatterpolar.marker.colorbar.tickformatstopde faults), sets the default property values to use for elements of scatterpolar.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.scatterpolar.marker.colorb ar.Title instance or dict with compatible properties titlefont Deprecated: Please use scatterpolar.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use scatterpolar.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """, ), **kwargs ) import _plotly_utils.basevalidators class ColoraxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__( self, plotly_name="coloraxis", parent_name="scatterpolar.marker", **kwargs ): super(ColoraxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", None), edit_type=kwargs.pop("edit_type", "calc"), regex=kwargs.pop("regex", "/^coloraxis([2-9]|[1-9][0-9]+)?$/"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scatterpolar.marker", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), colorscale_path=kwargs.pop( "colorscale_path", "scatterpolar.marker.colorscale" ), **kwargs ) import _plotly_utils.basevalidators class CminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmin", parent_name="scatterpolar.marker", **kwargs): super(CminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmidValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmid", parent_name="scatterpolar.marker", **kwargs): super(CmidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmax", parent_name="scatterpolar.marker", **kwargs): super(CmaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CautoValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="cauto", parent_name="scatterpolar.marker", **kwargs ): super(CautoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AutocolorscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="autocolorscale", parent_name="scatterpolar.marker", **kwargs ): super(AutocolorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterpolar/marker/line/0000755000175000017500000000000013573746614024677 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterpolar/marker/line/__init__.py0000644000175000017500000001462413573721543027011 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="widthsrc", parent_name="scatterpolar.marker.line", **kwargs ): super(WidthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="width", parent_name="scatterpolar.marker.line", **kwargs ): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ReversescaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="reversescale", parent_name="scatterpolar.marker.line", **kwargs ): super(ReversescaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="scatterpolar.marker.line", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__( self, plotly_name="colorscale", parent_name="scatterpolar.marker.line", **kwargs ): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"autocolorscale": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColoraxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__( self, plotly_name="coloraxis", parent_name="scatterpolar.marker.line", **kwargs ): super(ColoraxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", None), edit_type=kwargs.pop("edit_type", "calc"), regex=kwargs.pop("regex", "/^coloraxis([2-9]|[1-9][0-9]+)?$/"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scatterpolar.marker.line", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), colorscale_path=kwargs.pop( "colorscale_path", "scatterpolar.marker.line.colorscale" ), **kwargs ) import _plotly_utils.basevalidators class CminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="cmin", parent_name="scatterpolar.marker.line", **kwargs ): super(CminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmidValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="cmid", parent_name="scatterpolar.marker.line", **kwargs ): super(CmidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="cmax", parent_name="scatterpolar.marker.line", **kwargs ): super(CmaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CautoValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="cauto", parent_name="scatterpolar.marker.line", **kwargs ): super(CautoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AutocolorscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="autocolorscale", parent_name="scatterpolar.marker.line", **kwargs ): super(AutocolorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterpolar/stream/0000755000175000017500000000000013573746614023762 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterpolar/stream/__init__.py0000644000175000017500000000213213573721543026063 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TokenValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="token", parent_name="scatterpolar.stream", **kwargs ): super(TokenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "info"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class MaxpointsValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="maxpoints", parent_name="scatterpolar.stream", **kwargs ): super(MaxpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 10000), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterpolar/__init__.py0000644000175000017500000010501713573721543024576 0ustar noahfxnoahfximport _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="visible", parent_name="scatterpolar", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "legendonly"]), **kwargs ) import _plotly_utils.basevalidators class UnselectedValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="unselected", parent_name="scatterpolar", **kwargs): super(UnselectedValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Unselected"), data_docs=kwargs.pop( "data_docs", """ marker plotly.graph_objects.scatterpolar.unselected.Ma rker instance or dict with compatible properties textfont plotly.graph_objects.scatterpolar.unselected.Te xtfont instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="scatterpolar", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UidValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="uid", parent_name="scatterpolar", **kwargs): super(UidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ThetaunitValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="thetaunit", parent_name="scatterpolar", **kwargs): super(ThetaunitValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["radians", "degrees", "gradians"]), **kwargs ) import _plotly_utils.basevalidators class ThetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="thetasrc", parent_name="scatterpolar", **kwargs): super(ThetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class Theta0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="theta0", parent_name="scatterpolar", **kwargs): super(Theta0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ThetaValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="theta", parent_name="scatterpolar", **kwargs): super(ThetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TexttemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="texttemplatesrc", parent_name="scatterpolar", **kwargs ): super(TexttemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TexttemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="texttemplate", parent_name="scatterpolar", **kwargs ): super(TexttemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="textsrc", parent_name="scatterpolar", **kwargs): super(TextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextpositionsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="textpositionsrc", parent_name="scatterpolar", **kwargs ): super(TextpositionsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextpositionValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="textposition", parent_name="scatterpolar", **kwargs ): super(TextpositionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", [ "top left", "top center", "top right", "middle left", "middle center", "middle right", "bottom left", "bottom center", "bottom right", ], ), **kwargs ) import _plotly_utils.basevalidators class TextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="textfont", parent_name="scatterpolar", **kwargs): super(TextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Textfont"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="text", parent_name="scatterpolar", **kwargs): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SubplotValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="subplot", parent_name="scatterpolar", **kwargs): super(SubplotValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "polar"), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class StreamValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="stream", parent_name="scatterpolar", **kwargs): super(StreamValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Stream"), data_docs=kwargs.pop( "data_docs", """ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """, ), **kwargs ) import _plotly_utils.basevalidators class ShowlegendValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showlegend", parent_name="scatterpolar", **kwargs): super(ShowlegendValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SelectedpointsValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="selectedpoints", parent_name="scatterpolar", **kwargs ): super(SelectedpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SelectedValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="selected", parent_name="scatterpolar", **kwargs): super(SelectedValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Selected"), data_docs=kwargs.pop( "data_docs", """ marker plotly.graph_objects.scatterpolar.selected.Mark er instance or dict with compatible properties textfont plotly.graph_objects.scatterpolar.selected.Text font instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class RsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="rsrc", parent_name="scatterpolar", **kwargs): super(RsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class R0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="r0", parent_name="scatterpolar", **kwargs): super(R0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class RValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="r", parent_name="scatterpolar", **kwargs): super(RValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="scatterpolar", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="scatterpolar", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ModeValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="mode", parent_name="scatterpolar", **kwargs): super(ModeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), extras=kwargs.pop("extras", ["none"]), flags=kwargs.pop("flags", ["lines", "markers", "text"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="metasrc", parent_name="scatterpolar", **kwargs): super(MetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetaValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="meta", parent_name="scatterpolar", **kwargs): super(MetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="marker", parent_name="scatterpolar", **kwargs): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.scatterpolar.marker.ColorB ar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . gradient plotly.graph_objects.scatterpolar.marker.Gradie nt instance or dict with compatible properties line plotly.graph_objects.scatterpolar.marker.Line instance or dict with compatible properties maxdisplayed Sets a maximum number of points to be drawn on the graph. 0 corresponds to no limit. opacity Sets the marker opacity. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. size Sets the marker size (in px). sizemin Has an effect only if `marker.size` is set to a numerical array. Sets the minimum size (in px) of the rendered marker points. sizemode Has an effect only if `marker.size` is set to a numerical array. Sets the rule for which the data in `size` is converted to pixels. sizeref Has an effect only if `marker.size` is set to a numerical array. Sets the scale factor used to determine the rendered size of marker points. Use with `sizemin` and `sizemode`. sizesrc Sets the source reference on plot.ly for size . symbol Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot- open" to a symbol name. symbolsrc Sets the source reference on plot.ly for symbol . """, ), **kwargs ) import _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="line", parent_name="scatterpolar", **kwargs): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ color Sets the line color. dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). shape Determines the line shape. With "spline" the lines are drawn using spline interpolation. The other available values correspond to step-wise line shapes. smoothing Has an effect only if `shape` is set to "spline" Sets the amount of smoothing. 0 corresponds to no smoothing (equivalent to a "linear" shape). width Sets the line width (in px). """, ), **kwargs ) import _plotly_utils.basevalidators class LegendgroupValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="legendgroup", parent_name="scatterpolar", **kwargs): super(LegendgroupValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="idssrc", parent_name="scatterpolar", **kwargs): super(IdssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ids", parent_name="scatterpolar", **kwargs): super(IdsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class HovertextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="hovertextsrc", parent_name="scatterpolar", **kwargs ): super(HovertextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertext", parent_name="scatterpolar", **kwargs): super(HovertextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="hovertemplatesrc", parent_name="scatterpolar", **kwargs ): super(HovertemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="hovertemplate", parent_name="scatterpolar", **kwargs ): super(HovertemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoveronValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="hoveron", parent_name="scatterpolar", **kwargs): super(HoveronValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), flags=kwargs.pop("flags", ["points", "fills"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverlabelValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="hoverlabel", parent_name="scatterpolar", **kwargs): super(HoverlabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Hoverlabel"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """, ), **kwargs ) import _plotly_utils.basevalidators class HoverinfosrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="hoverinfosrc", parent_name="scatterpolar", **kwargs ): super(HoverinfosrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverinfoValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="hoverinfo", parent_name="scatterpolar", **kwargs): super(HoverinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), extras=kwargs.pop("extras", ["all", "none", "skip"]), flags=kwargs.pop("flags", ["r", "theta", "text", "name"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FillcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="fillcolor", parent_name="scatterpolar", **kwargs): super(FillcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FillValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="fill", parent_name="scatterpolar", **kwargs): super(FillValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "toself", "tonext"]), **kwargs ) import _plotly_utils.basevalidators class DthetaValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="dtheta", parent_name="scatterpolar", **kwargs): super(DthetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DrValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="dr", parent_name="scatterpolar", **kwargs): super(DrValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdatasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="customdatasrc", parent_name="scatterpolar", **kwargs ): super(CustomdatasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdataValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="customdata", parent_name="scatterpolar", **kwargs): super(CustomdataValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class ConnectgapsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="connectgaps", parent_name="scatterpolar", **kwargs): super(ConnectgapsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CliponaxisValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="cliponaxis", parent_name="scatterpolar", **kwargs): super(CliponaxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterpolar/line/0000755000175000017500000000000013573746614023416 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterpolar/line/__init__.py0000644000175000017500000000502313573721543025521 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="scatterpolar.line", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SmoothingValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="smoothing", parent_name="scatterpolar.line", **kwargs ): super(SmoothingValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), max=kwargs.pop("max", 1.3), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShapeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="shape", parent_name="scatterpolar.line", **kwargs): super(ShapeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["linear", "spline"]), **kwargs ) import _plotly_utils.basevalidators class DashValidator(_plotly_utils.basevalidators.DashValidator): def __init__(self, plotly_name="dash", parent_name="scatterpolar.line", **kwargs): super(DashValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", ["solid", "dot", "dash", "longdash", "dashdot", "longdashdot"] ), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="scatterpolar.line", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterpolar/selected/0000755000175000017500000000000013573746614024257 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterpolar/selected/textfont/0000755000175000017500000000000013573746614026132 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterpolar/selected/textfont/__init__.py0000644000175000017500000000076113573721543030241 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scatterpolar.selected.textfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterpolar/selected/marker/0000755000175000017500000000000013573746614025540 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/scatterpolar/selected/marker/__init__.py0000644000175000017500000000303013573721543027637 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="scatterpolar.selected.marker", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="opacity", parent_name="scatterpolar.selected.marker", **kwargs ): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="scatterpolar.selected.marker", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/scatterpolar/selected/__init__.py0000644000175000017500000000256313573721543026370 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="textfont", parent_name="scatterpolar.selected", **kwargs ): super(TextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Textfont"), data_docs=kwargs.pop( "data_docs", """ color Sets the text font color of selected points. """, ), **kwargs ) import _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="marker", parent_name="scatterpolar.selected", **kwargs ): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. size Sets the marker size of selected points. """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/histogram/0000755000175000017500000000000013573746614021761 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/histogram/unselected/0000755000175000017500000000000013573746614024114 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/histogram/unselected/textfont/0000755000175000017500000000000013573746614025767 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/histogram/unselected/textfont/__init__.py0000644000175000017500000000073013573721537030075 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="histogram.unselected.textfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/histogram/unselected/marker/0000755000175000017500000000000013573746614025375 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/histogram/unselected/marker/__init__.py0000644000175000017500000000200113573721537027474 0ustar noahfxnoahfximport _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="opacity", parent_name="histogram.unselected.marker", **kwargs ): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="histogram.unselected.marker", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/histogram/unselected/__init__.py0000644000175000017500000000271713573721537026231 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="textfont", parent_name="histogram.unselected", **kwargs ): super(TextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Textfont"), data_docs=kwargs.pop( "data_docs", """ color Sets the text font color of unselected points, applied only when a selection exists. """, ), **kwargs ) import _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="marker", parent_name="histogram.unselected", **kwargs ): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/histogram/error_x/0000755000175000017500000000000013573746614023441 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/histogram/error_x/__init__.py0000644000175000017500000001621413573721537025553 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="histogram.error_x", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="visible", parent_name="histogram.error_x", **kwargs ): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ValueminusValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="valueminus", parent_name="histogram.error_x", **kwargs ): super(ValueminusValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="value", parent_name="histogram.error_x", **kwargs): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TypeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="type", parent_name="histogram.error_x", **kwargs): super(TypeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["percent", "constant", "sqrt", "data"]), **kwargs ) import _plotly_utils.basevalidators class TracerefminusValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="tracerefminus", parent_name="histogram.error_x", **kwargs ): super(TracerefminusValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TracerefValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="traceref", parent_name="histogram.error_x", **kwargs ): super(TracerefValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="thickness", parent_name="histogram.error_x", **kwargs ): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SymmetricValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="symmetric", parent_name="histogram.error_x", **kwargs ): super(SymmetricValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CopyYstyleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="copy_ystyle", parent_name="histogram.error_x", **kwargs ): super(CopyYstyleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="histogram.error_x", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ArraysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="arraysrc", parent_name="histogram.error_x", **kwargs ): super(ArraysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ArrayminussrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="arrayminussrc", parent_name="histogram.error_x", **kwargs ): super(ArrayminussrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ArrayminusValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="arrayminus", parent_name="histogram.error_x", **kwargs ): super(ArrayminusValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class ArrayValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="array", parent_name="histogram.error_x", **kwargs): super(ArrayValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/histogram/ybins/0000755000175000017500000000000013573746614023105 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/histogram/ybins/__init__.py0000644000175000017500000000244613573721537025221 0ustar noahfxnoahfximport _plotly_utils.basevalidators class StartValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="start", parent_name="histogram.ybins", **kwargs): super(StartValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="size", parent_name="histogram.ybins", **kwargs): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EndValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="end", parent_name="histogram.ybins", **kwargs): super(EndValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/histogram/hoverlabel/0000755000175000017500000000000013573746614024104 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/histogram/hoverlabel/__init__.py0000644000175000017500000001346113573721537026217 0ustar noahfxnoahfximport _plotly_utils.basevalidators class NamelengthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="namelengthsrc", parent_name="histogram.hoverlabel", **kwargs ): super(NamelengthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NamelengthValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="namelength", parent_name="histogram.hoverlabel", **kwargs ): super(NamelengthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", -1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="histogram.hoverlabel", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class BordercolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bordercolorsrc", parent_name="histogram.hoverlabel", **kwargs ): super(BordercolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="histogram.hoverlabel", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bgcolorsrc", parent_name="histogram.hoverlabel", **kwargs ): super(BgcolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="histogram.hoverlabel", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AlignsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="alignsrc", parent_name="histogram.hoverlabel", **kwargs ): super(AlignsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="align", parent_name="histogram.hoverlabel", **kwargs ): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "right", "auto"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/histogram/hoverlabel/font/0000755000175000017500000000000013573746614025052 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/histogram/hoverlabel/font/__init__.py0000644000175000017500000000606113573721537027163 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="histogram.hoverlabel.font", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="histogram.hoverlabel.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="histogram.hoverlabel.font", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="histogram.hoverlabel.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="histogram.hoverlabel.font", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="histogram.hoverlabel.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/histogram/error_y/0000755000175000017500000000000013573746614023442 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/histogram/error_y/__init__.py0000644000175000017500000001525513573721537025560 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="histogram.error_y", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="visible", parent_name="histogram.error_y", **kwargs ): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ValueminusValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="valueminus", parent_name="histogram.error_y", **kwargs ): super(ValueminusValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="value", parent_name="histogram.error_y", **kwargs): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TypeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="type", parent_name="histogram.error_y", **kwargs): super(TypeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["percent", "constant", "sqrt", "data"]), **kwargs ) import _plotly_utils.basevalidators class TracerefminusValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="tracerefminus", parent_name="histogram.error_y", **kwargs ): super(TracerefminusValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TracerefValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="traceref", parent_name="histogram.error_y", **kwargs ): super(TracerefValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="thickness", parent_name="histogram.error_y", **kwargs ): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SymmetricValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="symmetric", parent_name="histogram.error_y", **kwargs ): super(SymmetricValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="histogram.error_y", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ArraysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="arraysrc", parent_name="histogram.error_y", **kwargs ): super(ArraysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ArrayminussrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="arrayminussrc", parent_name="histogram.error_y", **kwargs ): super(ArrayminussrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ArrayminusValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="arrayminus", parent_name="histogram.error_y", **kwargs ): super(ArrayminusValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class ArrayValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="array", parent_name="histogram.error_y", **kwargs): super(ArrayValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/histogram/marker/0000755000175000017500000000000013573746614023242 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/histogram/marker/colorbar/0000755000175000017500000000000013573746614025045 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/histogram/marker/colorbar/tickformatstop/0000755000175000017500000000000013573746614030116 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/histogram/marker/colorbar/tickformatstop/__init__.py0000644000175000017500000000545113573721537032231 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="value", parent_name="histogram.marker.colorbar.tickformatstop", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="histogram.marker.colorbar.tickformatstop", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="histogram.marker.colorbar.tickformatstop", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EnabledValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="enabled", parent_name="histogram.marker.colorbar.tickformatstop", **kwargs ): super(EnabledValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DtickrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="dtickrange", parent_name="histogram.marker.colorbar.tickformatstop", **kwargs ): super(DtickrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "colorbars"}, {"valType": "any", "editType": "colorbars"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/histogram/marker/colorbar/title/0000755000175000017500000000000013573746614026166 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/histogram/marker/colorbar/title/__init__.py0000644000175000017500000000506013573721537030275 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="text", parent_name="histogram.marker.colorbar.title", **kwargs ): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SideValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="side", parent_name="histogram.marker.colorbar.title", **kwargs ): super(SideValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["right", "top", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="histogram.marker.colorbar.title", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/histogram/marker/colorbar/title/font/0000755000175000017500000000000013573746614027134 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/histogram/marker/colorbar/title/font/__init__.py0000644000175000017500000000317713573721537031252 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="histogram.marker.colorbar.title.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="histogram.marker.colorbar.title.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="histogram.marker.colorbar.title.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/histogram/marker/colorbar/__init__.py0000644000175000017500000006167213573721540027161 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ypad", parent_name="histogram.marker.colorbar", **kwargs ): super(YpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class YanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="yanchor", parent_name="histogram.marker.colorbar", **kwargs ): super(YanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["top", "middle", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="y", parent_name="histogram.marker.colorbar", **kwargs ): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="xpad", parent_name="histogram.marker.colorbar", **kwargs ): super(XpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="xanchor", parent_name="histogram.marker.colorbar", **kwargs ): super(XanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "center", "right"]), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="x", parent_name="histogram.marker.colorbar", **kwargs ): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TitleValidator(_plotly_utils.basevalidators.TitleValidator): def __init__( self, plotly_name="title", parent_name="histogram.marker.colorbar", **kwargs ): super(TitleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Title"), data_docs=kwargs.pop( "data_docs", """ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """, ), **kwargs ) import _plotly_utils.basevalidators class TickwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="tickwidth", parent_name="histogram.marker.colorbar", **kwargs ): super(TickwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickvalssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="tickvalssrc", parent_name="histogram.marker.colorbar", **kwargs ): super(TickvalssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickvalsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="tickvals", parent_name="histogram.marker.colorbar", **kwargs ): super(TickvalsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="ticktextsrc", parent_name="histogram.marker.colorbar", **kwargs ): super(TicktextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicktextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="ticktext", parent_name="histogram.marker.colorbar", **kwargs ): super(TicktextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="ticksuffix", parent_name="histogram.marker.colorbar", **kwargs ): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TicksValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="ticks", parent_name="histogram.marker.colorbar", **kwargs ): super(TicksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["outside", "inside", ""]), **kwargs ) import _plotly_utils.basevalidators class TickprefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickprefix", parent_name="histogram.marker.colorbar", **kwargs ): super(TickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="tickmode", parent_name="histogram.marker.colorbar", **kwargs ): super(TickmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "linear", "array"]), **kwargs ) import _plotly_utils.basevalidators class TicklenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ticklen", parent_name="histogram.marker.colorbar", **kwargs ): super(TicklenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickformatstopValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickformatstopdefaults", parent_name="histogram.marker.colorbar", **kwargs ): super(TickformatstopValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatstopsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="tickformatstops", parent_name="histogram.marker.colorbar", **kwargs ): super(TickformatstopsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickformat", parent_name="histogram.marker.colorbar", **kwargs ): super(TickformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickfont", parent_name="histogram.marker.colorbar", **kwargs ): super(TickfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class TickcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="tickcolor", parent_name="histogram.marker.colorbar", **kwargs ): super(TickcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__( self, plotly_name="tickangle", parent_name="histogram.marker.colorbar", **kwargs ): super(TickangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="tick0", parent_name="histogram.marker.colorbar", **kwargs ): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ThicknessmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="thicknessmode", parent_name="histogram.marker.colorbar", **kwargs ): super(ThicknessmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="thickness", parent_name="histogram.marker.colorbar", **kwargs ): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowticksuffixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showticksuffix", parent_name="histogram.marker.colorbar", **kwargs ): super(ShowticksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowtickprefixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showtickprefix", parent_name="histogram.marker.colorbar", **kwargs ): super(ShowtickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowticklabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showticklabels", parent_name="histogram.marker.colorbar", **kwargs ): super(ShowticklabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowexponentValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showexponent", parent_name="histogram.marker.colorbar", **kwargs ): super(ShowexponentValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class SeparatethousandsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="separatethousands", parent_name="histogram.marker.colorbar", **kwargs ): super(SeparatethousandsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="outlinewidth", parent_name="histogram.marker.colorbar", **kwargs ): super(OutlinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="outlinecolor", parent_name="histogram.marker.colorbar", **kwargs ): super(OutlinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NticksValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="nticks", parent_name="histogram.marker.colorbar", **kwargs ): super(NticksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LenmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="lenmode", parent_name="histogram.marker.colorbar", **kwargs ): super(LenmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class LenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="len", parent_name="histogram.marker.colorbar", **kwargs ): super(LenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ExponentformatValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="exponentformat", parent_name="histogram.marker.colorbar", **kwargs ): super(ExponentformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "e", "E", "power", "SI", "B"]), **kwargs ) import _plotly_utils.basevalidators class DtickValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="dtick", parent_name="histogram.marker.colorbar", **kwargs ): super(DtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BorderwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="borderwidth", parent_name="histogram.marker.colorbar", **kwargs ): super(BorderwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="histogram.marker.colorbar", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="histogram.marker.colorbar", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/histogram/marker/colorbar/tickfont/0000755000175000017500000000000013573746614026666 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/histogram/marker/colorbar/tickfont/__init__.py0000644000175000017500000000317113573721537030776 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="histogram.marker.colorbar.tickfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="histogram.marker.colorbar.tickfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="histogram.marker.colorbar.tickfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/histogram/marker/__init__.py0000644000175000017500000005435513573721540025356 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ShowscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showscale", parent_name="histogram.marker", **kwargs ): super(ShowscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ReversescaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="reversescale", parent_name="histogram.marker", **kwargs ): super(ReversescaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacitysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="opacitysrc", parent_name="histogram.marker", **kwargs ): super(OpacitysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="histogram.marker", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="line", parent_name="histogram.marker", **kwargs): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,R eds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Black body,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . """, ), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="histogram.marker", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__( self, plotly_name="colorscale", parent_name="histogram.marker", **kwargs ): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"autocolorscale": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorBarValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="colorbar", parent_name="histogram.marker", **kwargs ): super(ColorBarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "ColorBar"), data_docs=kwargs.pop( "data_docs", """ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.histogram.marke r.colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.histogram.marker.colorbar.tickformatstopdefau lts), sets the default property values to use for elements of histogram.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.histogram.marker.colorbar. Title instance or dict with compatible properties titlefont Deprecated: Please use histogram.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use histogram.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """, ), **kwargs ) import _plotly_utils.basevalidators class ColoraxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__( self, plotly_name="coloraxis", parent_name="histogram.marker", **kwargs ): super(ColoraxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", None), edit_type=kwargs.pop("edit_type", "calc"), regex=kwargs.pop("regex", "/^coloraxis([2-9]|[1-9][0-9]+)?$/"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="histogram.marker", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), colorscale_path=kwargs.pop( "colorscale_path", "histogram.marker.colorscale" ), **kwargs ) import _plotly_utils.basevalidators class CminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmin", parent_name="histogram.marker", **kwargs): super(CminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmidValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmid", parent_name="histogram.marker", **kwargs): super(CmidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmax", parent_name="histogram.marker", **kwargs): super(CmaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CautoValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="cauto", parent_name="histogram.marker", **kwargs): super(CautoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AutocolorscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="autocolorscale", parent_name="histogram.marker", **kwargs ): super(AutocolorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/histogram/marker/line/0000755000175000017500000000000013573746614024171 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/histogram/marker/line/__init__.py0000644000175000017500000001452513573721537026306 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="widthsrc", parent_name="histogram.marker.line", **kwargs ): super(WidthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="width", parent_name="histogram.marker.line", **kwargs ): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ReversescaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="reversescale", parent_name="histogram.marker.line", **kwargs ): super(ReversescaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="histogram.marker.line", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__( self, plotly_name="colorscale", parent_name="histogram.marker.line", **kwargs ): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"autocolorscale": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColoraxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__( self, plotly_name="coloraxis", parent_name="histogram.marker.line", **kwargs ): super(ColoraxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", None), edit_type=kwargs.pop("edit_type", "calc"), regex=kwargs.pop("regex", "/^coloraxis([2-9]|[1-9][0-9]+)?$/"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="histogram.marker.line", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), colorscale_path=kwargs.pop( "colorscale_path", "histogram.marker.line.colorscale" ), **kwargs ) import _plotly_utils.basevalidators class CminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="cmin", parent_name="histogram.marker.line", **kwargs ): super(CminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmidValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="cmid", parent_name="histogram.marker.line", **kwargs ): super(CmidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="cmax", parent_name="histogram.marker.line", **kwargs ): super(CmaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CautoValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="cauto", parent_name="histogram.marker.line", **kwargs ): super(CautoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AutocolorscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="autocolorscale", parent_name="histogram.marker.line", **kwargs ): super(AutocolorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/histogram/stream/0000755000175000017500000000000013573746614023254 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/histogram/stream/__init__.py0000644000175000017500000000210613573721537025361 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TokenValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="token", parent_name="histogram.stream", **kwargs): super(TokenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "info"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class MaxpointsValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="maxpoints", parent_name="histogram.stream", **kwargs ): super(MaxpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 10000), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/histogram/__init__.py0000644000175000017500000012600613573721540024066 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="ysrc", parent_name="histogram", **kwargs): super(YsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YcalendarValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="ycalendar", parent_name="histogram", **kwargs): super(YcalendarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "gregorian", "chinese", "coptic", "discworld", "ethiopian", "hebrew", "islamic", "julian", "mayan", "nanakshahi", "nepali", "persian", "jalali", "taiwan", "thai", "ummalqura", ], ), **kwargs ) import _plotly_utils.basevalidators class YBinsValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="ybins", parent_name="histogram", **kwargs): super(YBinsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "YBins"), data_docs=kwargs.pop( "data_docs", """ end Sets the end value for the y axis bins. The last bin may not end exactly at this value, we increment the bin edge by `size` from `start` until we reach or exceed `end`. Defaults to the maximum data value. Like `start`, for dates use a date string, and for category data `end` is based on the category serial numbers. size Sets the size of each y axis bin. Default behavior: If `nbinsy` is 0 or omitted, we choose a nice round bin size such that the number of bins is about the same as the typical number of samples in each bin. If `nbinsy` is provided, we choose a nice round bin size giving no more than that many bins. For date data, use milliseconds or "M" for months, as in `axis.dtick`. For category data, the number of categories to bin together (always defaults to 1). If multiple non-overlaying histograms share a subplot, the first explicit `size` is used and all others discarded. If no `size` is provided,the sample data from all traces is combined to determine `size` as described above. start Sets the starting value for the y axis bins. Defaults to the minimum data value, shifted down if necessary to make nice round values and to remove ambiguous bin edges. For example, if most of the data is integers we shift the bin edges 0.5 down, so a `size` of 5 would have a default `start` of -0.5, so it is clear that 0-4 are in the first bin, 5-9 in the second, but continuous data gets a start of 0 and bins [0,5), [5,10) etc. Dates behave similarly, and `start` should be a date string. For category data, `start` is based on the category serial numbers, and defaults to -0.5. If multiple non- overlaying histograms share a subplot, the first explicit `start` is used exactly and all others are shifted down (if necessary) to differ from that one by an integer number of bins. """, ), **kwargs ) import _plotly_utils.basevalidators class YAxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="yaxis", parent_name="histogram", **kwargs): super(YAxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "y"), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="y", parent_name="histogram", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class XsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="xsrc", parent_name="histogram", **kwargs): super(XsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XcalendarValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="xcalendar", parent_name="histogram", **kwargs): super(XcalendarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "gregorian", "chinese", "coptic", "discworld", "ethiopian", "hebrew", "islamic", "julian", "mayan", "nanakshahi", "nepali", "persian", "jalali", "taiwan", "thai", "ummalqura", ], ), **kwargs ) import _plotly_utils.basevalidators class XBinsValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="xbins", parent_name="histogram", **kwargs): super(XBinsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "XBins"), data_docs=kwargs.pop( "data_docs", """ end Sets the end value for the x axis bins. The last bin may not end exactly at this value, we increment the bin edge by `size` from `start` until we reach or exceed `end`. Defaults to the maximum data value. Like `start`, for dates use a date string, and for category data `end` is based on the category serial numbers. size Sets the size of each x axis bin. Default behavior: If `nbinsx` is 0 or omitted, we choose a nice round bin size such that the number of bins is about the same as the typical number of samples in each bin. If `nbinsx` is provided, we choose a nice round bin size giving no more than that many bins. For date data, use milliseconds or "M" for months, as in `axis.dtick`. For category data, the number of categories to bin together (always defaults to 1). If multiple non-overlaying histograms share a subplot, the first explicit `size` is used and all others discarded. If no `size` is provided,the sample data from all traces is combined to determine `size` as described above. start Sets the starting value for the x axis bins. Defaults to the minimum data value, shifted down if necessary to make nice round values and to remove ambiguous bin edges. For example, if most of the data is integers we shift the bin edges 0.5 down, so a `size` of 5 would have a default `start` of -0.5, so it is clear that 0-4 are in the first bin, 5-9 in the second, but continuous data gets a start of 0 and bins [0,5), [5,10) etc. Dates behave similarly, and `start` should be a date string. For category data, `start` is based on the category serial numbers, and defaults to -0.5. If multiple non- overlaying histograms share a subplot, the first explicit `start` is used exactly and all others are shifted down (if necessary) to differ from that one by an integer number of bins. """, ), **kwargs ) import _plotly_utils.basevalidators class XAxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="xaxis", parent_name="histogram", **kwargs): super(XAxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "x"), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="x", parent_name="histogram", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="visible", parent_name="histogram", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "legendonly"]), **kwargs ) import _plotly_utils.basevalidators class UnselectedValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="unselected", parent_name="histogram", **kwargs): super(UnselectedValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Unselected"), data_docs=kwargs.pop( "data_docs", """ marker plotly.graph_objects.histogram.unselected.Marke r instance or dict with compatible properties textfont plotly.graph_objects.histogram.unselected.Textf ont instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="histogram", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UidValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="uid", parent_name="histogram", **kwargs): super(UidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="textsrc", parent_name="histogram", **kwargs): super(TextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="text", parent_name="histogram", **kwargs): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class StreamValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="stream", parent_name="histogram", **kwargs): super(StreamValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Stream"), data_docs=kwargs.pop( "data_docs", """ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """, ), **kwargs ) import _plotly_utils.basevalidators class ShowlegendValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showlegend", parent_name="histogram", **kwargs): super(ShowlegendValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SelectedpointsValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="selectedpoints", parent_name="histogram", **kwargs): super(SelectedpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SelectedValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="selected", parent_name="histogram", **kwargs): super(SelectedValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Selected"), data_docs=kwargs.pop( "data_docs", """ marker plotly.graph_objects.histogram.selected.Marker instance or dict with compatible properties textfont plotly.graph_objects.histogram.selected.Textfon t instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class OrientationValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="orientation", parent_name="histogram", **kwargs): super(OrientationValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["v", "h"]), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="histogram", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OffsetgroupValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="offsetgroup", parent_name="histogram", **kwargs): super(OffsetgroupValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NbinsyValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="nbinsy", parent_name="histogram", **kwargs): super(NbinsyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NbinsxValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="nbinsx", parent_name="histogram", **kwargs): super(NbinsxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="histogram", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="metasrc", parent_name="histogram", **kwargs): super(MetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetaValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="meta", parent_name="histogram", **kwargs): super(MetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="marker", parent_name="histogram", **kwargs): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.histogram.marker.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . line plotly.graph_objects.histogram.marker.Line instance or dict with compatible properties opacity Sets the opacity of the bars. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. """, ), **kwargs ) import _plotly_utils.basevalidators class LegendgroupValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="legendgroup", parent_name="histogram", **kwargs): super(LegendgroupValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="idssrc", parent_name="histogram", **kwargs): super(IdssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ids", parent_name="histogram", **kwargs): super(IdsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class HovertextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hovertextsrc", parent_name="histogram", **kwargs): super(HovertextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertext", parent_name="histogram", **kwargs): super(HovertextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="hovertemplatesrc", parent_name="histogram", **kwargs ): super(HovertemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertemplate", parent_name="histogram", **kwargs): super(HovertemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverlabelValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="hoverlabel", parent_name="histogram", **kwargs): super(HoverlabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Hoverlabel"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """, ), **kwargs ) import _plotly_utils.basevalidators class HoverinfosrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hoverinfosrc", parent_name="histogram", **kwargs): super(HoverinfosrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverinfoValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="hoverinfo", parent_name="histogram", **kwargs): super(HoverinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), extras=kwargs.pop("extras", ["all", "none", "skip"]), flags=kwargs.pop("flags", ["x", "y", "z", "text", "name"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HistnormValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="histnorm", parent_name="histogram", **kwargs): super(HistnormValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", ["", "percent", "probability", "density", "probability density"], ), **kwargs ) import _plotly_utils.basevalidators class HistfuncValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="histfunc", parent_name="histogram", **kwargs): super(HistfuncValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["count", "sum", "avg", "min", "max"]), **kwargs ) import _plotly_utils.basevalidators class ErrorYValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="error_y", parent_name="histogram", **kwargs): super(ErrorYValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "ErrorY"), data_docs=kwargs.pop( "data_docs", """ array Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. arrayminus Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. arrayminussrc Sets the source reference on plot.ly for arrayminus . arraysrc Sets the source reference on plot.ly for array . color Sets the stoke color of the error bars. symmetric Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. thickness Sets the thickness (in px) of the error bars. traceref tracerefminus type Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. value Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. valueminus Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars visible Determines whether or not this set of error bars is visible. width Sets the width (in px) of the cross-bar at both ends of the error bars. """, ), **kwargs ) import _plotly_utils.basevalidators class ErrorXValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="error_x", parent_name="histogram", **kwargs): super(ErrorXValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "ErrorX"), data_docs=kwargs.pop( "data_docs", """ array Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. arrayminus Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. arrayminussrc Sets the source reference on plot.ly for arrayminus . arraysrc Sets the source reference on plot.ly for array . color Sets the stoke color of the error bars. copy_ystyle symmetric Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. thickness Sets the thickness (in px) of the error bars. traceref tracerefminus type Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. value Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. valueminus Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars visible Determines whether or not this set of error bars is visible. width Sets the width (in px) of the cross-bar at both ends of the error bars. """, ), **kwargs ) import _plotly_utils.basevalidators class CustomdatasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="customdatasrc", parent_name="histogram", **kwargs): super(CustomdatasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdataValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="customdata", parent_name="histogram", **kwargs): super(CustomdataValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class CumulativeValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="cumulative", parent_name="histogram", **kwargs): super(CumulativeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Cumulative"), data_docs=kwargs.pop( "data_docs", """ currentbin Only applies if cumulative is enabled. Sets whether the current bin is included, excluded, or has half of its value included in the current cumulative value. "include" is the default for compatibility with various other tools, however it introduces a half-bin bias to the results. "exclude" makes the opposite half- bin bias, and "half" removes it. direction Only applies if cumulative is enabled. If "increasing" (default) we sum all prior bins, so the result increases from left to right. If "decreasing" we sum later bins so the result decreases from left to right. enabled If true, display the cumulative distribution by summing the binned values. Use the `direction` and `centralbin` attributes to tune the accumulation method. Note: in this mode, the "density" `histnorm` settings behave the same as their equivalents without "density": "" and "density" both rise to the number of data points, and "probability" and *probability density* both rise to the number of sample points. """, ), **kwargs ) import _plotly_utils.basevalidators class BingroupValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="bingroup", parent_name="histogram", **kwargs): super(BingroupValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AutobinyValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="autobiny", parent_name="histogram", **kwargs): super(AutobinyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AutobinxValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="autobinx", parent_name="histogram", **kwargs): super(AutobinxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AlignmentgroupValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="alignmentgroup", parent_name="histogram", **kwargs): super(AlignmentgroupValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/histogram/selected/0000755000175000017500000000000013573746614023551 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/histogram/selected/textfont/0000755000175000017500000000000013573746614025424 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/histogram/selected/textfont/__init__.py0000644000175000017500000000072613573721537027537 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="histogram.selected.textfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/histogram/selected/marker/0000755000175000017500000000000013573746614025032 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/histogram/selected/marker/__init__.py0000644000175000017500000000177513573721537027152 0ustar noahfxnoahfximport _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="opacity", parent_name="histogram.selected.marker", **kwargs ): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="histogram.selected.marker", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/histogram/selected/__init__.py0000644000175000017500000000244313573721537025662 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="textfont", parent_name="histogram.selected", **kwargs ): super(TextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Textfont"), data_docs=kwargs.pop( "data_docs", """ color Sets the text font color of selected points. """, ), **kwargs ) import _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="marker", parent_name="histogram.selected", **kwargs ): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/histogram/cumulative/0000755000175000017500000000000013573746614024137 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/histogram/cumulative/__init__.py0000644000175000017500000000305013573721537026243 0ustar noahfxnoahfximport _plotly_utils.basevalidators class EnabledValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="enabled", parent_name="histogram.cumulative", **kwargs ): super(EnabledValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DirectionValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="direction", parent_name="histogram.cumulative", **kwargs ): super(DirectionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["increasing", "decreasing"]), **kwargs ) import _plotly_utils.basevalidators class CurrentbinValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="currentbin", parent_name="histogram.cumulative", **kwargs ): super(CurrentbinValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["include", "exclude", "half"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/histogram/xbins/0000755000175000017500000000000013573746614023104 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/histogram/xbins/__init__.py0000644000175000017500000000244613573721537025220 0ustar noahfxnoahfximport _plotly_utils.basevalidators class StartValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="start", parent_name="histogram.xbins", **kwargs): super(StartValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="size", parent_name="histogram.xbins", **kwargs): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EndValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="end", parent_name="histogram.xbins", **kwargs): super(EndValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/carpet/0000755000175000017500000000000013573746614021242 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/carpet/stream/0000755000175000017500000000000013573746614022535 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/carpet/stream/__init__.py0000644000175000017500000000206213573721536024642 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TokenValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="token", parent_name="carpet.stream", **kwargs): super(TokenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "info"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class MaxpointsValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="maxpoints", parent_name="carpet.stream", **kwargs): super(MaxpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 10000), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/carpet/__init__.py0000644000175000017500000010564613573721537023364 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="ysrc", parent_name="carpet", **kwargs): super(YsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YAxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="yaxis", parent_name="carpet", **kwargs): super(YAxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "y"), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="y", parent_name="carpet", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class XsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="xsrc", parent_name="carpet", **kwargs): super(XsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XAxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="xaxis", parent_name="carpet", **kwargs): super(XAxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "x"), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="x", parent_name="carpet", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="visible", parent_name="carpet", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "legendonly"]), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="carpet", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UidValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="uid", parent_name="carpet", **kwargs): super(UidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, anim=kwargs.pop("anim", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class StreamValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="stream", parent_name="carpet", **kwargs): super(StreamValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Stream"), data_docs=kwargs.pop( "data_docs", """ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """, ), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="carpet", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="carpet", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="metasrc", parent_name="carpet", **kwargs): super(MetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetaValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="meta", parent_name="carpet", **kwargs): super(MetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="idssrc", parent_name="carpet", **kwargs): super(IdssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ids", parent_name="carpet", **kwargs): super(IdsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, anim=kwargs.pop("anim", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="font", parent_name="carpet", **kwargs): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class DbValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="db", parent_name="carpet", **kwargs): super(DbValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DaValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="da", parent_name="carpet", **kwargs): super(DaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdatasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="customdatasrc", parent_name="carpet", **kwargs): super(CustomdatasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdataValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="customdata", parent_name="carpet", **kwargs): super(CustomdataValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="carpet", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class CheaterslopeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cheaterslope", parent_name="carpet", **kwargs): super(CheaterslopeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CarpetValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="carpet", parent_name="carpet", **kwargs): super(CarpetValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="bsrc", parent_name="carpet", **kwargs): super(BsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BaxisValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="baxis", parent_name="carpet", **kwargs): super(BaxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Baxis"), data_docs=kwargs.pop( "data_docs", """ arraydtick The stride between grid lines along the axis arraytick0 The starting index of grid lines along the axis autorange Determines whether or not the range of this axis is computed in relation to the input data. See `rangemode` for more info. If `range` is provided, then `autorange` is set to False. categoryarray Sets the order in which categories on this axis appear. Only has an effect if `categoryorder` is set to "array". Used with `categoryorder`. categoryarraysrc Sets the source reference on plot.ly for categoryarray . categoryorder Specifies the ordering logic for the case of categorical variables. By default, plotly uses "trace", which specifies the order that is present in the data supplied. Set `categoryorder` to *category ascending* or *category descending* if order should be determined by the alphanumerical order of the category names. Set `categoryorder` to "array" to derive the ordering from the attribute `categoryarray`. If a category is not found in the `categoryarray` array, the sorting behavior for that attribute will be identical to the "trace" mode. The unspecified categories will follow the categories in `categoryarray`. cheatertype color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. dtick The stride between grid lines along the axis endline Determines whether or not a line is drawn at along the final value of this axis. If True, the end line is drawn on top of the grid lines. endlinecolor Sets the line color of the end line. endlinewidth Sets the width (in px) of the end line. exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. fixedrange Determines whether or not this axis is zoom- able. If true, then zoom is disabled. gridcolor Sets the axis line color. gridwidth Sets the width (in px) of the axis line. labelpadding Extra padding between label and the axis labelprefix Sets a axis label prefix. labelsuffix Sets a axis label suffix. linecolor Sets the axis line color. linewidth Sets the width (in px) of the axis line. minorgridcolor Sets the color of the grid lines. minorgridcount Sets the number of minor grid ticks per major grid tick minorgridwidth Sets the width (in px) of the grid lines. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". range Sets the range of this axis. If the axis `type` is "log", then you must take the log of your desired range (e.g. to set the range from 1 to 100, set the range from 0 to 2). If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. rangemode If "normal", the range is computed in relation to the extrema of the input data. If *tozero*`, the range extends to 0, regardless of the input data If "nonnegative", the range is non- negative, regardless of the input data. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showgrid Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. showline Determines whether or not a line bounding this axis is drawn. showticklabels Determines whether axis labels are drawn on the low side, the high side, both, or neither side of the axis. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. smoothing startline Determines whether or not a line is drawn at along the starting value of this axis. If True, the start line is drawn on top of the grid lines. startlinecolor Sets the line color of the start line. startlinewidth Sets the width (in px) of the start line. tick0 The starting index of grid lines along the axis tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickfont Sets the tick font. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.carpet.baxis.Ti ckformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.carpet.baxis.tickformatstopdefaults), sets the default property values to use for elements of carpet.baxis.tickformatstops tickmode tickprefix Sets a tick label prefix. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . title plotly.graph_objects.carpet.baxis.Title instance or dict with compatible properties titlefont Deprecated: Please use carpet.baxis.title.font instead. Sets this axis' title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleoffset Deprecated: Please use carpet.baxis.title.offset instead. An additional amount by which to offset the title from the tick labels, given in pixels. Note that this used to be set by the now deprecated `titleoffset` attribute. type Sets the axis type. By default, plotly attempts to determined the axis type by looking into the data of the traces that referenced the axis in question. """, ), **kwargs ) import _plotly_utils.basevalidators class B0Validator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="b0", parent_name="carpet", **kwargs): super(B0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="b", parent_name="carpet", **kwargs): super(BValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class AsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="asrc", parent_name="carpet", **kwargs): super(AsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AaxisValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="aaxis", parent_name="carpet", **kwargs): super(AaxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Aaxis"), data_docs=kwargs.pop( "data_docs", """ arraydtick The stride between grid lines along the axis arraytick0 The starting index of grid lines along the axis autorange Determines whether or not the range of this axis is computed in relation to the input data. See `rangemode` for more info. If `range` is provided, then `autorange` is set to False. categoryarray Sets the order in which categories on this axis appear. Only has an effect if `categoryorder` is set to "array". Used with `categoryorder`. categoryarraysrc Sets the source reference on plot.ly for categoryarray . categoryorder Specifies the ordering logic for the case of categorical variables. By default, plotly uses "trace", which specifies the order that is present in the data supplied. Set `categoryorder` to *category ascending* or *category descending* if order should be determined by the alphanumerical order of the category names. Set `categoryorder` to "array" to derive the ordering from the attribute `categoryarray`. If a category is not found in the `categoryarray` array, the sorting behavior for that attribute will be identical to the "trace" mode. The unspecified categories will follow the categories in `categoryarray`. cheatertype color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. dtick The stride between grid lines along the axis endline Determines whether or not a line is drawn at along the final value of this axis. If True, the end line is drawn on top of the grid lines. endlinecolor Sets the line color of the end line. endlinewidth Sets the width (in px) of the end line. exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. fixedrange Determines whether or not this axis is zoom- able. If true, then zoom is disabled. gridcolor Sets the axis line color. gridwidth Sets the width (in px) of the axis line. labelpadding Extra padding between label and the axis labelprefix Sets a axis label prefix. labelsuffix Sets a axis label suffix. linecolor Sets the axis line color. linewidth Sets the width (in px) of the axis line. minorgridcolor Sets the color of the grid lines. minorgridcount Sets the number of minor grid ticks per major grid tick minorgridwidth Sets the width (in px) of the grid lines. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". range Sets the range of this axis. If the axis `type` is "log", then you must take the log of your desired range (e.g. to set the range from 1 to 100, set the range from 0 to 2). If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. rangemode If "normal", the range is computed in relation to the extrema of the input data. If *tozero*`, the range extends to 0, regardless of the input data If "nonnegative", the range is non- negative, regardless of the input data. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showgrid Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. showline Determines whether or not a line bounding this axis is drawn. showticklabels Determines whether axis labels are drawn on the low side, the high side, both, or neither side of the axis. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. smoothing startline Determines whether or not a line is drawn at along the starting value of this axis. If True, the start line is drawn on top of the grid lines. startlinecolor Sets the line color of the start line. startlinewidth Sets the width (in px) of the start line. tick0 The starting index of grid lines along the axis tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickfont Sets the tick font. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.carpet.aaxis.Ti ckformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.carpet.aaxis.tickformatstopdefaults), sets the default property values to use for elements of carpet.aaxis.tickformatstops tickmode tickprefix Sets a tick label prefix. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . title plotly.graph_objects.carpet.aaxis.Title instance or dict with compatible properties titlefont Deprecated: Please use carpet.aaxis.title.font instead. Sets this axis' title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleoffset Deprecated: Please use carpet.aaxis.title.offset instead. An additional amount by which to offset the title from the tick labels, given in pixels. Note that this used to be set by the now deprecated `titleoffset` attribute. type Sets the axis type. By default, plotly attempts to determined the axis type by looking into the data of the traces that referenced the axis in question. """, ), **kwargs ) import _plotly_utils.basevalidators class A0Validator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="a0", parent_name="carpet", **kwargs): super(A0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="a", parent_name="carpet", **kwargs): super(AValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/carpet/aaxis/0000755000175000017500000000000013573746614022347 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/carpet/aaxis/tickformatstop/0000755000175000017500000000000013573746614025420 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/carpet/aaxis/tickformatstop/__init__.py0000644000175000017500000000517513573721536027535 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="value", parent_name="carpet.aaxis.tickformatstop", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="carpet.aaxis.tickformatstop", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="carpet.aaxis.tickformatstop", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EnabledValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="enabled", parent_name="carpet.aaxis.tickformatstop", **kwargs ): super(EnabledValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DtickrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="dtickrange", parent_name="carpet.aaxis.tickformatstop", **kwargs ): super(DtickrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "calc"}, {"valType": "any", "editType": "calc"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/carpet/aaxis/title/0000755000175000017500000000000013573746614023470 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/carpet/aaxis/title/__init__.py0000644000175000017500000000452713573721536025605 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="text", parent_name="carpet.aaxis.title", **kwargs): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class OffsetValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="offset", parent_name="carpet.aaxis.title", **kwargs ): super(OffsetValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="font", parent_name="carpet.aaxis.title", **kwargs): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/carpet/aaxis/title/font/0000755000175000017500000000000013573746614024436 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/carpet/aaxis/title/font/__init__.py0000644000175000017500000000300113573721536026535 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="carpet.aaxis.title.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="carpet.aaxis.title.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="carpet.aaxis.title.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/carpet/aaxis/__init__.py0000644000175000017500000007224413573721537024466 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TypeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="type", parent_name="carpet.aaxis", **kwargs): super(TypeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["-", "linear", "date", "category"]), **kwargs ) import _plotly_utils.basevalidators class TitleValidator(_plotly_utils.basevalidators.TitleValidator): def __init__(self, plotly_name="title", parent_name="carpet.aaxis", **kwargs): super(TitleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Title"), data_docs=kwargs.pop( "data_docs", """ font Sets this axis' title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. offset An additional amount by which to offset the title from the tick labels, given in pixels. Note that this used to be set by the now deprecated `titleoffset` attribute. text Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """, ), **kwargs ) import _plotly_utils.basevalidators class TickvalssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="tickvalssrc", parent_name="carpet.aaxis", **kwargs): super(TickvalssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickvalsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="tickvals", parent_name="carpet.aaxis", **kwargs): super(TickvalsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="ticktextsrc", parent_name="carpet.aaxis", **kwargs): super(TicktextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicktextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ticktext", parent_name="carpet.aaxis", **kwargs): super(TicktextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="ticksuffix", parent_name="carpet.aaxis", **kwargs): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickprefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="tickprefix", parent_name="carpet.aaxis", **kwargs): super(TickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="tickmode", parent_name="carpet.aaxis", **kwargs): super(TickmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["linear", "array"]), **kwargs ) import _plotly_utils.basevalidators class TickformatstopValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickformatstopdefaults", parent_name="carpet.aaxis", **kwargs ): super(TickformatstopValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatstopsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="tickformatstops", parent_name="carpet.aaxis", **kwargs ): super(TickformatstopsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="tickformat", parent_name="carpet.aaxis", **kwargs): super(TickformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="tickfont", parent_name="carpet.aaxis", **kwargs): super(TickfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class TickangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__(self, plotly_name="tickangle", parent_name="carpet.aaxis", **kwargs): super(TickangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="tick0", parent_name="carpet.aaxis", **kwargs): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class StartlinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="startlinewidth", parent_name="carpet.aaxis", **kwargs ): super(StartlinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class StartlinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="startlinecolor", parent_name="carpet.aaxis", **kwargs ): super(StartlinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class StartlineValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="startline", parent_name="carpet.aaxis", **kwargs): super(StartlineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SmoothingValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="smoothing", parent_name="carpet.aaxis", **kwargs): super(SmoothingValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1.3), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ShowticksuffixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showticksuffix", parent_name="carpet.aaxis", **kwargs ): super(ShowticksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowtickprefixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showtickprefix", parent_name="carpet.aaxis", **kwargs ): super(ShowtickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowticklabelsValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showticklabels", parent_name="carpet.aaxis", **kwargs ): super(ShowticklabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["start", "end", "both", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowlineValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showline", parent_name="carpet.aaxis", **kwargs): super(ShowlineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowgridValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showgrid", parent_name="carpet.aaxis", **kwargs): super(ShowgridValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowexponentValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showexponent", parent_name="carpet.aaxis", **kwargs ): super(ShowexponentValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class SeparatethousandsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="separatethousands", parent_name="carpet.aaxis", **kwargs ): super(SeparatethousandsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class RangemodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="rangemode", parent_name="carpet.aaxis", **kwargs): super(RangemodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["normal", "tozero", "nonnegative"]), **kwargs ) import _plotly_utils.basevalidators class RangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="range", parent_name="carpet.aaxis", **kwargs): super(RangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "calc"}, {"valType": "any", "editType": "calc"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NticksValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="nticks", parent_name="carpet.aaxis", **kwargs): super(NticksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class MinorgridwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="minorgridwidth", parent_name="carpet.aaxis", **kwargs ): super(MinorgridwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class MinorgridcountValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="minorgridcount", parent_name="carpet.aaxis", **kwargs ): super(MinorgridcountValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MinorgridcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="minorgridcolor", parent_name="carpet.aaxis", **kwargs ): super(MinorgridcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="linewidth", parent_name="carpet.aaxis", **kwargs): super(LinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="linecolor", parent_name="carpet.aaxis", **kwargs): super(LinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LabelsuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="labelsuffix", parent_name="carpet.aaxis", **kwargs): super(LabelsuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LabelprefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="labelprefix", parent_name="carpet.aaxis", **kwargs): super(LabelprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LabelpaddingValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="labelpadding", parent_name="carpet.aaxis", **kwargs ): super(LabelpaddingValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class GridwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="gridwidth", parent_name="carpet.aaxis", **kwargs): super(GridwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class GridcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="gridcolor", parent_name="carpet.aaxis", **kwargs): super(GridcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FixedrangeValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="fixedrange", parent_name="carpet.aaxis", **kwargs): super(FixedrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ExponentformatValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="exponentformat", parent_name="carpet.aaxis", **kwargs ): super(ExponentformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "e", "E", "power", "SI", "B"]), **kwargs ) import _plotly_utils.basevalidators class EndlinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="endlinewidth", parent_name="carpet.aaxis", **kwargs ): super(EndlinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EndlinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="endlinecolor", parent_name="carpet.aaxis", **kwargs ): super(EndlinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EndlineValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="endline", parent_name="carpet.aaxis", **kwargs): super(EndlineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class DtickValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="dtick", parent_name="carpet.aaxis", **kwargs): super(DtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="carpet.aaxis", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class CheatertypeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="cheatertype", parent_name="carpet.aaxis", **kwargs): super(CheatertypeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["index", "value"]), **kwargs ) import _plotly_utils.basevalidators class CategoryorderValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="categoryorder", parent_name="carpet.aaxis", **kwargs ): super(CategoryorderValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", ["trace", "category ascending", "category descending", "array"], ), **kwargs ) import _plotly_utils.basevalidators class CategoryarraysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="categoryarraysrc", parent_name="carpet.aaxis", **kwargs ): super(CategoryarraysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CategoryarrayValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="categoryarray", parent_name="carpet.aaxis", **kwargs ): super(CategoryarrayValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class AutorangeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="autorange", parent_name="carpet.aaxis", **kwargs): super(AutorangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", [True, False, "reversed"]), **kwargs ) import _plotly_utils.basevalidators class Arraytick0Validator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="arraytick0", parent_name="carpet.aaxis", **kwargs): super(Arraytick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ArraydtickValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="arraydtick", parent_name="carpet.aaxis", **kwargs): super(ArraydtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/carpet/aaxis/tickfont/0000755000175000017500000000000013573746614024170 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/carpet/aaxis/tickfont/__init__.py0000644000175000017500000000277313573721536026306 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="carpet.aaxis.tickfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="carpet.aaxis.tickfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="carpet.aaxis.tickfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/carpet/font/0000755000175000017500000000000013573746614022210 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/carpet/font/__init__.py0000644000175000017500000000266313573721536024324 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="size", parent_name="carpet.font", **kwargs): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="family", parent_name="carpet.font", **kwargs): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="carpet.font", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/carpet/baxis/0000755000175000017500000000000013573746614022350 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/carpet/baxis/tickformatstop/0000755000175000017500000000000013573746614025421 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/carpet/baxis/tickformatstop/__init__.py0000644000175000017500000000517513573721536027536 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="value", parent_name="carpet.baxis.tickformatstop", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="carpet.baxis.tickformatstop", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="carpet.baxis.tickformatstop", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EnabledValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="enabled", parent_name="carpet.baxis.tickformatstop", **kwargs ): super(EnabledValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DtickrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="dtickrange", parent_name="carpet.baxis.tickformatstop", **kwargs ): super(DtickrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "calc"}, {"valType": "any", "editType": "calc"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/carpet/baxis/title/0000755000175000017500000000000013573746614023471 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/carpet/baxis/title/__init__.py0000644000175000017500000000452713573721536025606 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="text", parent_name="carpet.baxis.title", **kwargs): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class OffsetValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="offset", parent_name="carpet.baxis.title", **kwargs ): super(OffsetValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="font", parent_name="carpet.baxis.title", **kwargs): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/carpet/baxis/title/font/0000755000175000017500000000000013573746614024437 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/carpet/baxis/title/font/__init__.py0000644000175000017500000000300113573721536026536 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="carpet.baxis.title.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="carpet.baxis.title.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="carpet.baxis.title.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/carpet/baxis/__init__.py0000644000175000017500000007224413573721537024467 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TypeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="type", parent_name="carpet.baxis", **kwargs): super(TypeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["-", "linear", "date", "category"]), **kwargs ) import _plotly_utils.basevalidators class TitleValidator(_plotly_utils.basevalidators.TitleValidator): def __init__(self, plotly_name="title", parent_name="carpet.baxis", **kwargs): super(TitleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Title"), data_docs=kwargs.pop( "data_docs", """ font Sets this axis' title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. offset An additional amount by which to offset the title from the tick labels, given in pixels. Note that this used to be set by the now deprecated `titleoffset` attribute. text Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """, ), **kwargs ) import _plotly_utils.basevalidators class TickvalssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="tickvalssrc", parent_name="carpet.baxis", **kwargs): super(TickvalssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickvalsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="tickvals", parent_name="carpet.baxis", **kwargs): super(TickvalsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="ticktextsrc", parent_name="carpet.baxis", **kwargs): super(TicktextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicktextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ticktext", parent_name="carpet.baxis", **kwargs): super(TicktextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="ticksuffix", parent_name="carpet.baxis", **kwargs): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickprefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="tickprefix", parent_name="carpet.baxis", **kwargs): super(TickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="tickmode", parent_name="carpet.baxis", **kwargs): super(TickmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["linear", "array"]), **kwargs ) import _plotly_utils.basevalidators class TickformatstopValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickformatstopdefaults", parent_name="carpet.baxis", **kwargs ): super(TickformatstopValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatstopsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="tickformatstops", parent_name="carpet.baxis", **kwargs ): super(TickformatstopsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="tickformat", parent_name="carpet.baxis", **kwargs): super(TickformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="tickfont", parent_name="carpet.baxis", **kwargs): super(TickfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class TickangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__(self, plotly_name="tickangle", parent_name="carpet.baxis", **kwargs): super(TickangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="tick0", parent_name="carpet.baxis", **kwargs): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class StartlinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="startlinewidth", parent_name="carpet.baxis", **kwargs ): super(StartlinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class StartlinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="startlinecolor", parent_name="carpet.baxis", **kwargs ): super(StartlinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class StartlineValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="startline", parent_name="carpet.baxis", **kwargs): super(StartlineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SmoothingValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="smoothing", parent_name="carpet.baxis", **kwargs): super(SmoothingValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1.3), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ShowticksuffixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showticksuffix", parent_name="carpet.baxis", **kwargs ): super(ShowticksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowtickprefixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showtickprefix", parent_name="carpet.baxis", **kwargs ): super(ShowtickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowticklabelsValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showticklabels", parent_name="carpet.baxis", **kwargs ): super(ShowticklabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["start", "end", "both", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowlineValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showline", parent_name="carpet.baxis", **kwargs): super(ShowlineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowgridValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showgrid", parent_name="carpet.baxis", **kwargs): super(ShowgridValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowexponentValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showexponent", parent_name="carpet.baxis", **kwargs ): super(ShowexponentValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class SeparatethousandsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="separatethousands", parent_name="carpet.baxis", **kwargs ): super(SeparatethousandsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class RangemodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="rangemode", parent_name="carpet.baxis", **kwargs): super(RangemodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["normal", "tozero", "nonnegative"]), **kwargs ) import _plotly_utils.basevalidators class RangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="range", parent_name="carpet.baxis", **kwargs): super(RangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "calc"}, {"valType": "any", "editType": "calc"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NticksValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="nticks", parent_name="carpet.baxis", **kwargs): super(NticksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class MinorgridwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="minorgridwidth", parent_name="carpet.baxis", **kwargs ): super(MinorgridwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class MinorgridcountValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="minorgridcount", parent_name="carpet.baxis", **kwargs ): super(MinorgridcountValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MinorgridcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="minorgridcolor", parent_name="carpet.baxis", **kwargs ): super(MinorgridcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="linewidth", parent_name="carpet.baxis", **kwargs): super(LinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="linecolor", parent_name="carpet.baxis", **kwargs): super(LinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LabelsuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="labelsuffix", parent_name="carpet.baxis", **kwargs): super(LabelsuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LabelprefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="labelprefix", parent_name="carpet.baxis", **kwargs): super(LabelprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LabelpaddingValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="labelpadding", parent_name="carpet.baxis", **kwargs ): super(LabelpaddingValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class GridwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="gridwidth", parent_name="carpet.baxis", **kwargs): super(GridwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class GridcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="gridcolor", parent_name="carpet.baxis", **kwargs): super(GridcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FixedrangeValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="fixedrange", parent_name="carpet.baxis", **kwargs): super(FixedrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ExponentformatValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="exponentformat", parent_name="carpet.baxis", **kwargs ): super(ExponentformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "e", "E", "power", "SI", "B"]), **kwargs ) import _plotly_utils.basevalidators class EndlinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="endlinewidth", parent_name="carpet.baxis", **kwargs ): super(EndlinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EndlinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="endlinecolor", parent_name="carpet.baxis", **kwargs ): super(EndlinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EndlineValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="endline", parent_name="carpet.baxis", **kwargs): super(EndlineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class DtickValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="dtick", parent_name="carpet.baxis", **kwargs): super(DtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="carpet.baxis", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class CheatertypeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="cheatertype", parent_name="carpet.baxis", **kwargs): super(CheatertypeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["index", "value"]), **kwargs ) import _plotly_utils.basevalidators class CategoryorderValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="categoryorder", parent_name="carpet.baxis", **kwargs ): super(CategoryorderValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", ["trace", "category ascending", "category descending", "array"], ), **kwargs ) import _plotly_utils.basevalidators class CategoryarraysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="categoryarraysrc", parent_name="carpet.baxis", **kwargs ): super(CategoryarraysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CategoryarrayValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="categoryarray", parent_name="carpet.baxis", **kwargs ): super(CategoryarrayValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class AutorangeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="autorange", parent_name="carpet.baxis", **kwargs): super(AutorangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", [True, False, "reversed"]), **kwargs ) import _plotly_utils.basevalidators class Arraytick0Validator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="arraytick0", parent_name="carpet.baxis", **kwargs): super(Arraytick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ArraydtickValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="arraydtick", parent_name="carpet.baxis", **kwargs): super(ArraydtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/carpet/baxis/tickfont/0000755000175000017500000000000013573746614024171 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/carpet/baxis/tickfont/__init__.py0000644000175000017500000000277313573721536026307 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="carpet.baxis.tickfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="carpet.baxis.tickfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="carpet.baxis.tickfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/splom/0000755000175000017500000000000013573746614021116 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/splom/unselected/0000755000175000017500000000000013573746614023251 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/splom/unselected/marker/0000755000175000017500000000000013573746614024532 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/splom/unselected/marker/__init__.py0000644000175000017500000000275613573721543026647 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="splom.unselected.marker", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="opacity", parent_name="splom.unselected.marker", **kwargs ): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="splom.unselected.marker", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/splom/unselected/__init__.py0000644000175000017500000000162513573721543025360 0ustar noahfxnoahfximport _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="marker", parent_name="splom.unselected", **kwargs): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. size Sets the marker size of unselected points, applied only when a selection exists. """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/splom/hoverlabel/0000755000175000017500000000000013573746614023241 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/splom/hoverlabel/__init__.py0000644000175000017500000001334313573721543025350 0ustar noahfxnoahfximport _plotly_utils.basevalidators class NamelengthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="namelengthsrc", parent_name="splom.hoverlabel", **kwargs ): super(NamelengthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NamelengthValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="namelength", parent_name="splom.hoverlabel", **kwargs ): super(NamelengthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", -1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="font", parent_name="splom.hoverlabel", **kwargs): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class BordercolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bordercolorsrc", parent_name="splom.hoverlabel", **kwargs ): super(BordercolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="splom.hoverlabel", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bgcolorsrc", parent_name="splom.hoverlabel", **kwargs ): super(BgcolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="bgcolor", parent_name="splom.hoverlabel", **kwargs): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AlignsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="alignsrc", parent_name="splom.hoverlabel", **kwargs ): super(AlignsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="align", parent_name="splom.hoverlabel", **kwargs): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "right", "auto"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/splom/hoverlabel/font/0000755000175000017500000000000013573746614024207 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/splom/hoverlabel/font/__init__.py0000644000175000017500000000603113573721543026312 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="splom.hoverlabel.font", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="splom.hoverlabel.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="splom.hoverlabel.font", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="splom.hoverlabel.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="splom.hoverlabel.font", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="splom.hoverlabel.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/splom/marker/0000755000175000017500000000000013573746614022377 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/splom/marker/colorbar/0000755000175000017500000000000013573746614024202 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/splom/marker/colorbar/tickformatstop/0000755000175000017500000000000013573746614027253 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/splom/marker/colorbar/tickformatstop/__init__.py0000644000175000017500000000542513573721543031364 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="value", parent_name="splom.marker.colorbar.tickformatstop", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="splom.marker.colorbar.tickformatstop", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="splom.marker.colorbar.tickformatstop", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EnabledValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="enabled", parent_name="splom.marker.colorbar.tickformatstop", **kwargs ): super(EnabledValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DtickrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="dtickrange", parent_name="splom.marker.colorbar.tickformatstop", **kwargs ): super(DtickrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "colorbars"}, {"valType": "any", "editType": "colorbars"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/splom/marker/colorbar/title/0000755000175000017500000000000013573746614025323 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/splom/marker/colorbar/title/__init__.py0000644000175000017500000000473413573721543027436 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="text", parent_name="splom.marker.colorbar.title", **kwargs ): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SideValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="side", parent_name="splom.marker.colorbar.title", **kwargs ): super(SideValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["right", "top", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="splom.marker.colorbar.title", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/splom/marker/colorbar/title/font/0000755000175000017500000000000013573746614026271 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/splom/marker/colorbar/title/font/__init__.py0000644000175000017500000000316313573721543030377 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="splom.marker.colorbar.title.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="splom.marker.colorbar.title.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="splom.marker.colorbar.title.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/splom/marker/colorbar/__init__.py0000644000175000017500000006076213573721544026321 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ypad", parent_name="splom.marker.colorbar", **kwargs ): super(YpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class YanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="yanchor", parent_name="splom.marker.colorbar", **kwargs ): super(YanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["top", "middle", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="y", parent_name="splom.marker.colorbar", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="xpad", parent_name="splom.marker.colorbar", **kwargs ): super(XpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="xanchor", parent_name="splom.marker.colorbar", **kwargs ): super(XanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "center", "right"]), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="x", parent_name="splom.marker.colorbar", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TitleValidator(_plotly_utils.basevalidators.TitleValidator): def __init__( self, plotly_name="title", parent_name="splom.marker.colorbar", **kwargs ): super(TitleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Title"), data_docs=kwargs.pop( "data_docs", """ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """, ), **kwargs ) import _plotly_utils.basevalidators class TickwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="tickwidth", parent_name="splom.marker.colorbar", **kwargs ): super(TickwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickvalssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="tickvalssrc", parent_name="splom.marker.colorbar", **kwargs ): super(TickvalssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickvalsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="tickvals", parent_name="splom.marker.colorbar", **kwargs ): super(TickvalsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="ticktextsrc", parent_name="splom.marker.colorbar", **kwargs ): super(TicktextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicktextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="ticktext", parent_name="splom.marker.colorbar", **kwargs ): super(TicktextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="ticksuffix", parent_name="splom.marker.colorbar", **kwargs ): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TicksValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="ticks", parent_name="splom.marker.colorbar", **kwargs ): super(TicksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["outside", "inside", ""]), **kwargs ) import _plotly_utils.basevalidators class TickprefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickprefix", parent_name="splom.marker.colorbar", **kwargs ): super(TickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="tickmode", parent_name="splom.marker.colorbar", **kwargs ): super(TickmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "linear", "array"]), **kwargs ) import _plotly_utils.basevalidators class TicklenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ticklen", parent_name="splom.marker.colorbar", **kwargs ): super(TicklenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickformatstopValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickformatstopdefaults", parent_name="splom.marker.colorbar", **kwargs ): super(TickformatstopValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatstopsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="tickformatstops", parent_name="splom.marker.colorbar", **kwargs ): super(TickformatstopsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickformat", parent_name="splom.marker.colorbar", **kwargs ): super(TickformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickfont", parent_name="splom.marker.colorbar", **kwargs ): super(TickfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class TickcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="tickcolor", parent_name="splom.marker.colorbar", **kwargs ): super(TickcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__( self, plotly_name="tickangle", parent_name="splom.marker.colorbar", **kwargs ): super(TickangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="tick0", parent_name="splom.marker.colorbar", **kwargs ): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ThicknessmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="thicknessmode", parent_name="splom.marker.colorbar", **kwargs ): super(ThicknessmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="thickness", parent_name="splom.marker.colorbar", **kwargs ): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowticksuffixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showticksuffix", parent_name="splom.marker.colorbar", **kwargs ): super(ShowticksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowtickprefixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showtickprefix", parent_name="splom.marker.colorbar", **kwargs ): super(ShowtickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowticklabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showticklabels", parent_name="splom.marker.colorbar", **kwargs ): super(ShowticklabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowexponentValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showexponent", parent_name="splom.marker.colorbar", **kwargs ): super(ShowexponentValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class SeparatethousandsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="separatethousands", parent_name="splom.marker.colorbar", **kwargs ): super(SeparatethousandsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="outlinewidth", parent_name="splom.marker.colorbar", **kwargs ): super(OutlinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="outlinecolor", parent_name="splom.marker.colorbar", **kwargs ): super(OutlinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NticksValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="nticks", parent_name="splom.marker.colorbar", **kwargs ): super(NticksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LenmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="lenmode", parent_name="splom.marker.colorbar", **kwargs ): super(LenmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class LenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="len", parent_name="splom.marker.colorbar", **kwargs ): super(LenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ExponentformatValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="exponentformat", parent_name="splom.marker.colorbar", **kwargs ): super(ExponentformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "e", "E", "power", "SI", "B"]), **kwargs ) import _plotly_utils.basevalidators class DtickValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="dtick", parent_name="splom.marker.colorbar", **kwargs ): super(DtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BorderwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="borderwidth", parent_name="splom.marker.colorbar", **kwargs ): super(BorderwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="splom.marker.colorbar", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="splom.marker.colorbar", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/splom/marker/colorbar/tickfont/0000755000175000017500000000000013573746614026023 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/splom/marker/colorbar/tickfont/__init__.py0000644000175000017500000000312513573721543030127 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="splom.marker.colorbar.tickfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="splom.marker.colorbar.tickfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="splom.marker.colorbar.tickfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/splom/marker/__init__.py0000644000175000017500000010376313573721543024514 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SymbolsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="symbolsrc", parent_name="splom.marker", **kwargs): super(SymbolsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SymbolValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="symbol", parent_name="splom.marker", **kwargs): super(SymbolValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", [ 0, "circle", 100, "circle-open", 200, "circle-dot", 300, "circle-open-dot", 1, "square", 101, "square-open", 201, "square-dot", 301, "square-open-dot", 2, "diamond", 102, "diamond-open", 202, "diamond-dot", 302, "diamond-open-dot", 3, "cross", 103, "cross-open", 203, "cross-dot", 303, "cross-open-dot", 4, "x", 104, "x-open", 204, "x-dot", 304, "x-open-dot", 5, "triangle-up", 105, "triangle-up-open", 205, "triangle-up-dot", 305, "triangle-up-open-dot", 6, "triangle-down", 106, "triangle-down-open", 206, "triangle-down-dot", 306, "triangle-down-open-dot", 7, "triangle-left", 107, "triangle-left-open", 207, "triangle-left-dot", 307, "triangle-left-open-dot", 8, "triangle-right", 108, "triangle-right-open", 208, "triangle-right-dot", 308, "triangle-right-open-dot", 9, "triangle-ne", 109, "triangle-ne-open", 209, "triangle-ne-dot", 309, "triangle-ne-open-dot", 10, "triangle-se", 110, "triangle-se-open", 210, "triangle-se-dot", 310, "triangle-se-open-dot", 11, "triangle-sw", 111, "triangle-sw-open", 211, "triangle-sw-dot", 311, "triangle-sw-open-dot", 12, "triangle-nw", 112, "triangle-nw-open", 212, "triangle-nw-dot", 312, "triangle-nw-open-dot", 13, "pentagon", 113, "pentagon-open", 213, "pentagon-dot", 313, "pentagon-open-dot", 14, "hexagon", 114, "hexagon-open", 214, "hexagon-dot", 314, "hexagon-open-dot", 15, "hexagon2", 115, "hexagon2-open", 215, "hexagon2-dot", 315, "hexagon2-open-dot", 16, "octagon", 116, "octagon-open", 216, "octagon-dot", 316, "octagon-open-dot", 17, "star", 117, "star-open", 217, "star-dot", 317, "star-open-dot", 18, "hexagram", 118, "hexagram-open", 218, "hexagram-dot", 318, "hexagram-open-dot", 19, "star-triangle-up", 119, "star-triangle-up-open", 219, "star-triangle-up-dot", 319, "star-triangle-up-open-dot", 20, "star-triangle-down", 120, "star-triangle-down-open", 220, "star-triangle-down-dot", 320, "star-triangle-down-open-dot", 21, "star-square", 121, "star-square-open", 221, "star-square-dot", 321, "star-square-open-dot", 22, "star-diamond", 122, "star-diamond-open", 222, "star-diamond-dot", 322, "star-diamond-open-dot", 23, "diamond-tall", 123, "diamond-tall-open", 223, "diamond-tall-dot", 323, "diamond-tall-open-dot", 24, "diamond-wide", 124, "diamond-wide-open", 224, "diamond-wide-dot", 324, "diamond-wide-open-dot", 25, "hourglass", 125, "hourglass-open", 26, "bowtie", 126, "bowtie-open", 27, "circle-cross", 127, "circle-cross-open", 28, "circle-x", 128, "circle-x-open", 29, "square-cross", 129, "square-cross-open", 30, "square-x", 130, "square-x-open", 31, "diamond-cross", 131, "diamond-cross-open", 32, "diamond-x", 132, "diamond-x-open", 33, "cross-thin", 133, "cross-thin-open", 34, "x-thin", 134, "x-thin-open", 35, "asterisk", 135, "asterisk-open", 36, "hash", 136, "hash-open", 236, "hash-dot", 336, "hash-open-dot", 37, "y-up", 137, "y-up-open", 38, "y-down", 138, "y-down-open", 39, "y-left", 139, "y-left-open", 40, "y-right", 140, "y-right-open", 41, "line-ew", 141, "line-ew-open", 42, "line-ns", 142, "line-ns-open", 43, "line-ne", 143, "line-ne-open", 44, "line-nw", 144, "line-nw-open", ], ), **kwargs ) import _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="sizesrc", parent_name="splom.marker", **kwargs): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizerefValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="sizeref", parent_name="splom.marker", **kwargs): super(SizerefValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SizemodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="sizemode", parent_name="splom.marker", **kwargs): super(SizemodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["diameter", "area"]), **kwargs ) import _plotly_utils.basevalidators class SizeminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="sizemin", parent_name="splom.marker", **kwargs): super(SizeminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="size", parent_name="splom.marker", **kwargs): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "markerSize"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showscale", parent_name="splom.marker", **kwargs): super(ShowscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ReversescaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="reversescale", parent_name="splom.marker", **kwargs ): super(ReversescaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacitysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="opacitysrc", parent_name="splom.marker", **kwargs): super(OpacitysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="splom.marker", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="line", parent_name="splom.marker", **kwargs): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,R eds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Black body,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . """, ), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="colorsrc", parent_name="splom.marker", **kwargs): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__(self, plotly_name="colorscale", parent_name="splom.marker", **kwargs): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"autocolorscale": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorBarValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="colorbar", parent_name="splom.marker", **kwargs): super(ColorBarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "ColorBar"), data_docs=kwargs.pop( "data_docs", """ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.splom.marker.co lorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.splom.marker.colorbar.tickformatstopdefaults) , sets the default property values to use for elements of splom.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.splom.marker.colorbar.Titl e instance or dict with compatible properties titlefont Deprecated: Please use splom.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use splom.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """, ), **kwargs ) import _plotly_utils.basevalidators class ColoraxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="coloraxis", parent_name="splom.marker", **kwargs): super(ColoraxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", None), edit_type=kwargs.pop("edit_type", "calc"), regex=kwargs.pop("regex", "/^coloraxis([2-9]|[1-9][0-9]+)?$/"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="splom.marker", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), colorscale_path=kwargs.pop("colorscale_path", "splom.marker.colorscale"), **kwargs ) import _plotly_utils.basevalidators class CminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmin", parent_name="splom.marker", **kwargs): super(CminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmidValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmid", parent_name="splom.marker", **kwargs): super(CmidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmax", parent_name="splom.marker", **kwargs): super(CmaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CautoValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="cauto", parent_name="splom.marker", **kwargs): super(CautoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AutocolorscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="autocolorscale", parent_name="splom.marker", **kwargs ): super(AutocolorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/splom/marker/line/0000755000175000017500000000000013573746614023326 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/splom/marker/line/__init__.py0000644000175000017500000001426313573721543025437 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="widthsrc", parent_name="splom.marker.line", **kwargs ): super(WidthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="splom.marker.line", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ReversescaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="reversescale", parent_name="splom.marker.line", **kwargs ): super(ReversescaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="splom.marker.line", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__( self, plotly_name="colorscale", parent_name="splom.marker.line", **kwargs ): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"autocolorscale": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColoraxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__( self, plotly_name="coloraxis", parent_name="splom.marker.line", **kwargs ): super(ColoraxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", None), edit_type=kwargs.pop("edit_type", "calc"), regex=kwargs.pop("regex", "/^coloraxis([2-9]|[1-9][0-9]+)?$/"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="splom.marker.line", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), colorscale_path=kwargs.pop( "colorscale_path", "splom.marker.line.colorscale" ), **kwargs ) import _plotly_utils.basevalidators class CminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmin", parent_name="splom.marker.line", **kwargs): super(CminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmidValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmid", parent_name="splom.marker.line", **kwargs): super(CmidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmax", parent_name="splom.marker.line", **kwargs): super(CmaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CautoValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="cauto", parent_name="splom.marker.line", **kwargs): super(CautoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AutocolorscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="autocolorscale", parent_name="splom.marker.line", **kwargs ): super(AutocolorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/splom/stream/0000755000175000017500000000000013573746614022411 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/splom/stream/__init__.py0000644000175000017500000000206013573721543024512 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TokenValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="token", parent_name="splom.stream", **kwargs): super(TokenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "info"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class MaxpointsValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="maxpoints", parent_name="splom.stream", **kwargs): super(MaxpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 10000), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/splom/__init__.py0000644000175000017500000006504413573721544023233 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YaxesValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="yaxes", parent_name="splom", **kwargs): super(YaxesValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), free_length=kwargs.pop("free_length", True), items=kwargs.pop( "items", { "valType": "subplotid", "regex": "/^y([2-9]|[1-9][0-9]+)?$/", "editType": "plot", }, ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XaxesValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="xaxes", parent_name="splom", **kwargs): super(XaxesValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), free_length=kwargs.pop("free_length", True), items=kwargs.pop( "items", { "valType": "subplotid", "regex": "/^x([2-9]|[1-9][0-9]+)?$/", "editType": "plot", }, ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="visible", parent_name="splom", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "legendonly"]), **kwargs ) import _plotly_utils.basevalidators class UnselectedValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="unselected", parent_name="splom", **kwargs): super(UnselectedValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Unselected"), data_docs=kwargs.pop( "data_docs", """ marker plotly.graph_objects.splom.unselected.Marker instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="splom", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UidValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="uid", parent_name="splom", **kwargs): super(UidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="textsrc", parent_name="splom", **kwargs): super(TextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="text", parent_name="splom", **kwargs): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class StreamValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="stream", parent_name="splom", **kwargs): super(StreamValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Stream"), data_docs=kwargs.pop( "data_docs", """ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """, ), **kwargs ) import _plotly_utils.basevalidators class ShowupperhalfValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showupperhalf", parent_name="splom", **kwargs): super(ShowupperhalfValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ShowlowerhalfValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showlowerhalf", parent_name="splom", **kwargs): super(ShowlowerhalfValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ShowlegendValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showlegend", parent_name="splom", **kwargs): super(ShowlegendValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SelectedpointsValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="selectedpoints", parent_name="splom", **kwargs): super(SelectedpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SelectedValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="selected", parent_name="splom", **kwargs): super(SelectedValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Selected"), data_docs=kwargs.pop( "data_docs", """ marker plotly.graph_objects.splom.selected.Marker instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="splom", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="splom", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="metasrc", parent_name="splom", **kwargs): super(MetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetaValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="meta", parent_name="splom", **kwargs): super(MetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="marker", parent_name="splom", **kwargs): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.splom.marker.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . line plotly.graph_objects.splom.marker.Line instance or dict with compatible properties opacity Sets the marker opacity. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. size Sets the marker size (in px). sizemin Has an effect only if `marker.size` is set to a numerical array. Sets the minimum size (in px) of the rendered marker points. sizemode Has an effect only if `marker.size` is set to a numerical array. Sets the rule for which the data in `size` is converted to pixels. sizeref Has an effect only if `marker.size` is set to a numerical array. Sets the scale factor used to determine the rendered size of marker points. Use with `sizemin` and `sizemode`. sizesrc Sets the source reference on plot.ly for size . symbol Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot- open" to a symbol name. symbolsrc Sets the source reference on plot.ly for symbol . """, ), **kwargs ) import _plotly_utils.basevalidators class LegendgroupValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="legendgroup", parent_name="splom", **kwargs): super(LegendgroupValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="idssrc", parent_name="splom", **kwargs): super(IdssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ids", parent_name="splom", **kwargs): super(IdsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class HovertextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hovertextsrc", parent_name="splom", **kwargs): super(HovertextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertext", parent_name="splom", **kwargs): super(HovertextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hovertemplatesrc", parent_name="splom", **kwargs): super(HovertemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertemplate", parent_name="splom", **kwargs): super(HovertemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverlabelValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="hoverlabel", parent_name="splom", **kwargs): super(HoverlabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Hoverlabel"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """, ), **kwargs ) import _plotly_utils.basevalidators class HoverinfosrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hoverinfosrc", parent_name="splom", **kwargs): super(HoverinfosrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverinfoValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="hoverinfo", parent_name="splom", **kwargs): super(HoverinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), extras=kwargs.pop("extras", ["all", "none", "skip"]), flags=kwargs.pop("flags", ["x", "y", "z", "text", "name"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DimensionValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="dimensiondefaults", parent_name="splom", **kwargs): super(DimensionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Dimension"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class DimensionsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__(self, plotly_name="dimensions", parent_name="splom", **kwargs): super(DimensionsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Dimension"), data_docs=kwargs.pop( "data_docs", """ axis plotly.graph_objects.splom.dimension.Axis instance or dict with compatible properties label Sets the label corresponding to this splom dimension. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. values Sets the dimension values to be plotted. valuessrc Sets the source reference on plot.ly for values . visible Determines whether or not this dimension is shown on the graph. Note that even visible false dimension contribute to the default grid generate by this splom trace. """, ), **kwargs ) import _plotly_utils.basevalidators class DiagonalValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="diagonal", parent_name="splom", **kwargs): super(DiagonalValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Diagonal"), data_docs=kwargs.pop( "data_docs", """ visible Determines whether or not subplots on the diagonal are displayed. """, ), **kwargs ) import _plotly_utils.basevalidators class CustomdatasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="customdatasrc", parent_name="splom", **kwargs): super(CustomdatasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdataValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="customdata", parent_name="splom", **kwargs): super(CustomdataValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/splom/dimension/0000755000175000017500000000000013573746614023103 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/splom/dimension/axis/0000755000175000017500000000000013573746614024047 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/splom/dimension/axis/__init__.py0000644000175000017500000000200513573721543026147 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TypeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="type", parent_name="splom.dimension.axis", **kwargs ): super(TypeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["linear", "log", "date", "category"]), **kwargs ) import _plotly_utils.basevalidators class MatchesValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="matches", parent_name="splom.dimension.axis", **kwargs ): super(MatchesValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/splom/dimension/__init__.py0000644000175000017500000000725413573721543025216 0ustar noahfxnoahfximport _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="visible", parent_name="splom.dimension", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ValuessrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="valuessrc", parent_name="splom.dimension", **kwargs ): super(ValuessrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ValuesValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="values", parent_name="splom.dimension", **kwargs): super(ValuesValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="splom.dimension", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="splom.dimension", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LabelValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="label", parent_name="splom.dimension", **kwargs): super(LabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AxisValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="axis", parent_name="splom.dimension", **kwargs): super(AxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Axis"), data_docs=kwargs.pop( "data_docs", """ matches Determines whether or not the x & y axes generated by this dimension match. Equivalent to setting the `matches` axis attribute in the layout with the correct axis id. type Sets the axis type for this dimension's generated x and y axes. Note that the axis `type` values set in layout take precedence over this attribute. """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/splom/selected/0000755000175000017500000000000013573746614022706 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/splom/selected/marker/0000755000175000017500000000000013573746614024167 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/splom/selected/marker/__init__.py0000644000175000017500000000275013573721543026276 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="splom.selected.marker", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="opacity", parent_name="splom.selected.marker", **kwargs ): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="splom.selected.marker", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/splom/selected/__init__.py0000644000175000017500000000135313573721543025013 0ustar noahfxnoahfximport _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="marker", parent_name="splom.selected", **kwargs): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. size Sets the marker size of selected points. """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/splom/diagonal/0000755000175000017500000000000013573746614022674 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/splom/diagonal/__init__.py0000644000175000017500000000070113573721543024775 0ustar noahfxnoahfximport _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="visible", parent_name="splom.diagonal", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/table/0000755000175000017500000000000013573746614021053 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/table/hoverlabel/0000755000175000017500000000000013573746614023176 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/table/hoverlabel/__init__.py0000644000175000017500000001334313573721544025306 0ustar noahfxnoahfximport _plotly_utils.basevalidators class NamelengthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="namelengthsrc", parent_name="table.hoverlabel", **kwargs ): super(NamelengthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NamelengthValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="namelength", parent_name="table.hoverlabel", **kwargs ): super(NamelengthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", -1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="font", parent_name="table.hoverlabel", **kwargs): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class BordercolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bordercolorsrc", parent_name="table.hoverlabel", **kwargs ): super(BordercolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="table.hoverlabel", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bgcolorsrc", parent_name="table.hoverlabel", **kwargs ): super(BgcolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="bgcolor", parent_name="table.hoverlabel", **kwargs): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AlignsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="alignsrc", parent_name="table.hoverlabel", **kwargs ): super(AlignsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="align", parent_name="table.hoverlabel", **kwargs): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "right", "auto"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/table/hoverlabel/font/0000755000175000017500000000000013573746614024144 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/table/hoverlabel/font/__init__.py0000644000175000017500000000603113573721544026250 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="table.hoverlabel.font", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="table.hoverlabel.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="table.hoverlabel.font", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="table.hoverlabel.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="table.hoverlabel.font", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="table.hoverlabel.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/table/stream/0000755000175000017500000000000013573746614022346 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/table/stream/__init__.py0000644000175000017500000000206013573721544024450 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TokenValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="token", parent_name="table.stream", **kwargs): super(TokenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "info"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class MaxpointsValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="maxpoints", parent_name="table.stream", **kwargs): super(MaxpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 10000), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/table/__init__.py0000644000175000017500000004035513573721544023166 0ustar noahfxnoahfximport _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="visible", parent_name="table", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "legendonly"]), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="table", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UidValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="uid", parent_name="table", **kwargs): super(UidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class StreamValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="stream", parent_name="table", **kwargs): super(StreamValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Stream"), data_docs=kwargs.pop( "data_docs", """ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """, ), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="table", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="metasrc", parent_name="table", **kwargs): super(MetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetaValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="meta", parent_name="table", **kwargs): super(MetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="idssrc", parent_name="table", **kwargs): super(IdssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ids", parent_name="table", **kwargs): super(IdsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class HoverlabelValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="hoverlabel", parent_name="table", **kwargs): super(HoverlabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Hoverlabel"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """, ), **kwargs ) import _plotly_utils.basevalidators class HoverinfosrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hoverinfosrc", parent_name="table", **kwargs): super(HoverinfosrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverinfoValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="hoverinfo", parent_name="table", **kwargs): super(HoverinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), extras=kwargs.pop("extras", ["all", "none", "skip"]), flags=kwargs.pop("flags", ["x", "y", "z", "text", "name"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HeaderValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="header", parent_name="table", **kwargs): super(HeaderValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Header"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the `text` within the box. Has an effect only if `text` spans more two or more lines (i.e. `text` contains one or more
HTML tags) or if an explicit width is set to override the text width. alignsrc Sets the source reference on plot.ly for align . fill plotly.graph_objects.table.header.Fill instance or dict with compatible properties font plotly.graph_objects.table.header.Font instance or dict with compatible properties format Sets the cell value formatting rule using d3 formatting mini-language which is similar to those of Python. See https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format formatsrc Sets the source reference on plot.ly for format . height The height of cells. line plotly.graph_objects.table.header.Line instance or dict with compatible properties prefix Prefix for cell values. prefixsrc Sets the source reference on plot.ly for prefix . suffix Suffix for cell values. suffixsrc Sets the source reference on plot.ly for suffix . values Header cell values. `values[m][n]` represents the value of the `n`th point in column `m`, therefore the `values[m]` vector length for all columns must be the same (longer vectors will be truncated). Each value must be a finite number or a string. valuessrc Sets the source reference on plot.ly for values . """, ), **kwargs ) import _plotly_utils.basevalidators class DomainValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="domain", parent_name="table", **kwargs): super(DomainValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Domain"), data_docs=kwargs.pop( "data_docs", """ column If there is a layout grid, use the domain for this column in the grid for this table trace . row If there is a layout grid, use the domain for this row in the grid for this table trace . x Sets the horizontal domain of this table trace (in plot fraction). y Sets the vertical domain of this table trace (in plot fraction). """, ), **kwargs ) import _plotly_utils.basevalidators class CustomdatasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="customdatasrc", parent_name="table", **kwargs): super(CustomdatasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdataValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="customdata", parent_name="table", **kwargs): super(CustomdataValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class ColumnwidthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="columnwidthsrc", parent_name="table", **kwargs): super(ColumnwidthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColumnwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="columnwidth", parent_name="table", **kwargs): super(ColumnwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColumnordersrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="columnordersrc", parent_name="table", **kwargs): super(ColumnordersrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColumnorderValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="columnorder", parent_name="table", **kwargs): super(ColumnorderValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class CellsValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="cells", parent_name="table", **kwargs): super(CellsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Cells"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the `text` within the box. Has an effect only if `text` spans more two or more lines (i.e. `text` contains one or more
HTML tags) or if an explicit width is set to override the text width. alignsrc Sets the source reference on plot.ly for align . fill plotly.graph_objects.table.cells.Fill instance or dict with compatible properties font plotly.graph_objects.table.cells.Font instance or dict with compatible properties format Sets the cell value formatting rule using d3 formatting mini-language which is similar to those of Python. See https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format formatsrc Sets the source reference on plot.ly for format . height The height of cells. line plotly.graph_objects.table.cells.Line instance or dict with compatible properties prefix Prefix for cell values. prefixsrc Sets the source reference on plot.ly for prefix . suffix Suffix for cell values. suffixsrc Sets the source reference on plot.ly for suffix . values Cell values. `values[m][n]` represents the value of the `n`th point in column `m`, therefore the `values[m]` vector length for all columns must be the same (longer vectors will be truncated). Each value must be a finite number or a string. valuessrc Sets the source reference on plot.ly for values . """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/table/domain/0000755000175000017500000000000013573746614022322 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/table/domain/__init__.py0000644000175000017500000000450113573721544024426 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="y", parent_name="table.domain", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), items=kwargs.pop( "items", [ {"valType": "number", "min": 0, "max": 1, "editType": "calc"}, {"valType": "number", "min": 0, "max": 1, "editType": "calc"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="x", parent_name="table.domain", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), items=kwargs.pop( "items", [ {"valType": "number", "min": 0, "max": 1, "editType": "calc"}, {"valType": "number", "min": 0, "max": 1, "editType": "calc"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class RowValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="row", parent_name="table.domain", **kwargs): super(RowValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColumnValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="column", parent_name="table.domain", **kwargs): super(ColumnValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/table/cells/0000755000175000017500000000000013573746614022155 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/table/cells/fill/0000755000175000017500000000000013573746614023103 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/table/cells/fill/__init__.py0000644000175000017500000000170113573721543025205 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="table.cells.fill", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="table.cells.fill", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/table/cells/__init__.py0000644000175000017500000002042013573721544024257 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValuessrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="valuessrc", parent_name="table.cells", **kwargs): super(ValuessrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ValuesValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="values", parent_name="table.cells", **kwargs): super(ValuesValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class SuffixsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="suffixsrc", parent_name="table.cells", **kwargs): super(SuffixsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="suffix", parent_name="table.cells", **kwargs): super(SuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class PrefixsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="prefixsrc", parent_name="table.cells", **kwargs): super(PrefixsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class PrefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="prefix", parent_name="table.cells", **kwargs): super(PrefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="line", parent_name="table.cells", **kwargs): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . width widthsrc Sets the source reference on plot.ly for width . """, ), **kwargs ) import _plotly_utils.basevalidators class HeightValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="height", parent_name="table.cells", **kwargs): super(HeightValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FormatsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="formatsrc", parent_name="table.cells", **kwargs): super(FormatsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FormatValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="format", parent_name="table.cells", **kwargs): super(FormatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="font", parent_name="table.cells", **kwargs): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class FillValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="fill", parent_name="table.cells", **kwargs): super(FillValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Fill"), data_docs=kwargs.pop( "data_docs", """ color Sets the cell fill color. It accepts either a specific color or an array of colors or a 2D array of colors. colorsrc Sets the source reference on plot.ly for color . """, ), **kwargs ) import _plotly_utils.basevalidators class AlignsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="alignsrc", parent_name="table.cells", **kwargs): super(AlignsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="align", parent_name="table.cells", **kwargs): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "center", "right"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/table/cells/line/0000755000175000017500000000000013573746614023104 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/table/cells/line/__init__.py0000644000175000017500000000360513573721543025213 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="widthsrc", parent_name="table.cells.line", **kwargs ): super(WidthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="table.cells.line", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="table.cells.line", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="table.cells.line", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/table/cells/font/0000755000175000017500000000000013573746614023123 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/table/cells/font/__init__.py0000644000175000017500000000570313573721543025233 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="sizesrc", parent_name="table.cells.font", **kwargs): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="size", parent_name="table.cells.font", **kwargs): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="table.cells.font", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="family", parent_name="table.cells.font", **kwargs): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="table.cells.font", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="table.cells.font", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/table/header/0000755000175000017500000000000013573746614022303 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/table/header/fill/0000755000175000017500000000000013573746614023231 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/table/header/fill/__init__.py0000644000175000017500000000170313573721543025335 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="table.header.fill", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="table.header.fill", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/table/header/__init__.py0000644000175000017500000002043613573721544024414 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValuessrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="valuessrc", parent_name="table.header", **kwargs): super(ValuessrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ValuesValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="values", parent_name="table.header", **kwargs): super(ValuesValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class SuffixsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="suffixsrc", parent_name="table.header", **kwargs): super(SuffixsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="suffix", parent_name="table.header", **kwargs): super(SuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class PrefixsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="prefixsrc", parent_name="table.header", **kwargs): super(PrefixsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class PrefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="prefix", parent_name="table.header", **kwargs): super(PrefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="line", parent_name="table.header", **kwargs): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . width widthsrc Sets the source reference on plot.ly for width . """, ), **kwargs ) import _plotly_utils.basevalidators class HeightValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="height", parent_name="table.header", **kwargs): super(HeightValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FormatsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="formatsrc", parent_name="table.header", **kwargs): super(FormatsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FormatValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="format", parent_name="table.header", **kwargs): super(FormatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="font", parent_name="table.header", **kwargs): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class FillValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="fill", parent_name="table.header", **kwargs): super(FillValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Fill"), data_docs=kwargs.pop( "data_docs", """ color Sets the cell fill color. It accepts either a specific color or an array of colors or a 2D array of colors. colorsrc Sets the source reference on plot.ly for color . """, ), **kwargs ) import _plotly_utils.basevalidators class AlignsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="alignsrc", parent_name="table.header", **kwargs): super(AlignsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="align", parent_name="table.header", **kwargs): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "center", "right"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/table/header/line/0000755000175000017500000000000013573746614023232 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/table/header/line/__init__.py0000644000175000017500000000361113573721544025337 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="widthsrc", parent_name="table.header.line", **kwargs ): super(WidthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="table.header.line", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="table.header.line", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="table.header.line", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/table/header/font/0000755000175000017500000000000013573746614023251 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/table/header/font/__init__.py0000644000175000017500000000572713573721544025370 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="table.header.font", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="size", parent_name="table.header.font", **kwargs): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="table.header.font", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="family", parent_name="table.header.font", **kwargs): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="table.header.font", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="table.header.font", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/treemap/0000755000175000017500000000000013573746614021421 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/treemap/pathbar/0000755000175000017500000000000013573746614023042 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/treemap/pathbar/textfont/0000755000175000017500000000000013573746614024715 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/treemap/pathbar/textfont/__init__.py0000644000175000017500000000605313573721544027025 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="treemap.pathbar.textfont", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="treemap.pathbar.textfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="treemap.pathbar.textfont", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="treemap.pathbar.textfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="treemap.pathbar.textfont", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="treemap.pathbar.textfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/treemap/pathbar/__init__.py0000644000175000017500000000734713573721544025161 0ustar noahfxnoahfximport _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="visible", parent_name="treemap.pathbar", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="thickness", parent_name="treemap.pathbar", **kwargs ): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 12), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="textfont", parent_name="treemap.pathbar", **kwargs): super(TextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Textfont"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class SideValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="side", parent_name="treemap.pathbar", **kwargs): super(SideValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["top", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class EdgeshapeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="edgeshape", parent_name="treemap.pathbar", **kwargs ): super(EdgeshapeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", [">", "<", "|", "/", "\\"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/treemap/textfont/0000755000175000017500000000000013573746614023274 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/treemap/textfont/__init__.py0000644000175000017500000000570313573721544025405 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="sizesrc", parent_name="treemap.textfont", **kwargs): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="size", parent_name="treemap.textfont", **kwargs): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="treemap.textfont", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="family", parent_name="treemap.textfont", **kwargs): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="treemap.textfont", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="treemap.textfont", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/treemap/hoverlabel/0000755000175000017500000000000013573746614023544 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/treemap/hoverlabel/__init__.py0000644000175000017500000001340313573721544025651 0ustar noahfxnoahfximport _plotly_utils.basevalidators class NamelengthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="namelengthsrc", parent_name="treemap.hoverlabel", **kwargs ): super(NamelengthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NamelengthValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="namelength", parent_name="treemap.hoverlabel", **kwargs ): super(NamelengthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", -1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="font", parent_name="treemap.hoverlabel", **kwargs): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class BordercolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bordercolorsrc", parent_name="treemap.hoverlabel", **kwargs ): super(BordercolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="treemap.hoverlabel", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bgcolorsrc", parent_name="treemap.hoverlabel", **kwargs ): super(BgcolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="treemap.hoverlabel", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AlignsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="alignsrc", parent_name="treemap.hoverlabel", **kwargs ): super(AlignsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="align", parent_name="treemap.hoverlabel", **kwargs): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "right", "auto"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/treemap/hoverlabel/font/0000755000175000017500000000000013573746614024512 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/treemap/hoverlabel/font/__init__.py0000644000175000017500000000604513573721544026623 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="treemap.hoverlabel.font", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="treemap.hoverlabel.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="treemap.hoverlabel.font", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="treemap.hoverlabel.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="treemap.hoverlabel.font", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="treemap.hoverlabel.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/treemap/outsidetextfont/0000755000175000017500000000000013573746614024671 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/treemap/outsidetextfont/__init__.py0000644000175000017500000000604513573721544027002 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="treemap.outsidetextfont", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="treemap.outsidetextfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="treemap.outsidetextfont", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="treemap.outsidetextfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="treemap.outsidetextfont", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="treemap.outsidetextfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/treemap/marker/0000755000175000017500000000000013573746614022702 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/treemap/marker/pad/0000755000175000017500000000000013573746614023446 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/treemap/marker/pad/__init__.py0000644000175000017500000000355213573721544025557 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="t", parent_name="treemap.marker.pad", **kwargs): super(TValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class RValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="r", parent_name="treemap.marker.pad", **kwargs): super(RValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="l", parent_name="treemap.marker.pad", **kwargs): super(LValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="b", parent_name="treemap.marker.pad", **kwargs): super(BValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/treemap/marker/colorbar/0000755000175000017500000000000013573746614024505 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/treemap/marker/colorbar/tickformatstop/0000755000175000017500000000000013573746614027556 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/treemap/marker/colorbar/tickformatstop/__init__.py0000644000175000017500000000543713573721544031673 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="value", parent_name="treemap.marker.colorbar.tickformatstop", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="treemap.marker.colorbar.tickformatstop", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="treemap.marker.colorbar.tickformatstop", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EnabledValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="enabled", parent_name="treemap.marker.colorbar.tickformatstop", **kwargs ): super(EnabledValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DtickrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="dtickrange", parent_name="treemap.marker.colorbar.tickformatstop", **kwargs ): super(DtickrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "colorbars"}, {"valType": "any", "editType": "colorbars"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/treemap/marker/colorbar/title/0000755000175000017500000000000013573746614025626 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/treemap/marker/colorbar/title/__init__.py0000644000175000017500000000474213573721544027741 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="text", parent_name="treemap.marker.colorbar.title", **kwargs ): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SideValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="side", parent_name="treemap.marker.colorbar.title", **kwargs ): super(SideValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["right", "top", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="treemap.marker.colorbar.title", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/treemap/marker/colorbar/title/font/0000755000175000017500000000000013573746614026574 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/treemap/marker/colorbar/title/font/__init__.py0000644000175000017500000000317113573721544030702 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="treemap.marker.colorbar.title.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="treemap.marker.colorbar.title.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="treemap.marker.colorbar.title.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/treemap/marker/colorbar/__init__.py0000644000175000017500000006130013573721544026611 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ypad", parent_name="treemap.marker.colorbar", **kwargs ): super(YpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class YanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="yanchor", parent_name="treemap.marker.colorbar", **kwargs ): super(YanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["top", "middle", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="y", parent_name="treemap.marker.colorbar", **kwargs ): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="xpad", parent_name="treemap.marker.colorbar", **kwargs ): super(XpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="xanchor", parent_name="treemap.marker.colorbar", **kwargs ): super(XanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "center", "right"]), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="x", parent_name="treemap.marker.colorbar", **kwargs ): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TitleValidator(_plotly_utils.basevalidators.TitleValidator): def __init__( self, plotly_name="title", parent_name="treemap.marker.colorbar", **kwargs ): super(TitleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Title"), data_docs=kwargs.pop( "data_docs", """ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """, ), **kwargs ) import _plotly_utils.basevalidators class TickwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="tickwidth", parent_name="treemap.marker.colorbar", **kwargs ): super(TickwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickvalssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="tickvalssrc", parent_name="treemap.marker.colorbar", **kwargs ): super(TickvalssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickvalsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="tickvals", parent_name="treemap.marker.colorbar", **kwargs ): super(TickvalsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="ticktextsrc", parent_name="treemap.marker.colorbar", **kwargs ): super(TicktextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicktextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="ticktext", parent_name="treemap.marker.colorbar", **kwargs ): super(TicktextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="ticksuffix", parent_name="treemap.marker.colorbar", **kwargs ): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TicksValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="ticks", parent_name="treemap.marker.colorbar", **kwargs ): super(TicksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["outside", "inside", ""]), **kwargs ) import _plotly_utils.basevalidators class TickprefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickprefix", parent_name="treemap.marker.colorbar", **kwargs ): super(TickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="tickmode", parent_name="treemap.marker.colorbar", **kwargs ): super(TickmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "linear", "array"]), **kwargs ) import _plotly_utils.basevalidators class TicklenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ticklen", parent_name="treemap.marker.colorbar", **kwargs ): super(TicklenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickformatstopValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickformatstopdefaults", parent_name="treemap.marker.colorbar", **kwargs ): super(TickformatstopValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatstopsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="tickformatstops", parent_name="treemap.marker.colorbar", **kwargs ): super(TickformatstopsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickformat", parent_name="treemap.marker.colorbar", **kwargs ): super(TickformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickfont", parent_name="treemap.marker.colorbar", **kwargs ): super(TickfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class TickcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="tickcolor", parent_name="treemap.marker.colorbar", **kwargs ): super(TickcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__( self, plotly_name="tickangle", parent_name="treemap.marker.colorbar", **kwargs ): super(TickangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="tick0", parent_name="treemap.marker.colorbar", **kwargs ): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ThicknessmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="thicknessmode", parent_name="treemap.marker.colorbar", **kwargs ): super(ThicknessmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="thickness", parent_name="treemap.marker.colorbar", **kwargs ): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowticksuffixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showticksuffix", parent_name="treemap.marker.colorbar", **kwargs ): super(ShowticksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowtickprefixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showtickprefix", parent_name="treemap.marker.colorbar", **kwargs ): super(ShowtickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowticklabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showticklabels", parent_name="treemap.marker.colorbar", **kwargs ): super(ShowticklabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowexponentValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showexponent", parent_name="treemap.marker.colorbar", **kwargs ): super(ShowexponentValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class SeparatethousandsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="separatethousands", parent_name="treemap.marker.colorbar", **kwargs ): super(SeparatethousandsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="outlinewidth", parent_name="treemap.marker.colorbar", **kwargs ): super(OutlinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="outlinecolor", parent_name="treemap.marker.colorbar", **kwargs ): super(OutlinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NticksValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="nticks", parent_name="treemap.marker.colorbar", **kwargs ): super(NticksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LenmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="lenmode", parent_name="treemap.marker.colorbar", **kwargs ): super(LenmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class LenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="len", parent_name="treemap.marker.colorbar", **kwargs ): super(LenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ExponentformatValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="exponentformat", parent_name="treemap.marker.colorbar", **kwargs ): super(ExponentformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "e", "E", "power", "SI", "B"]), **kwargs ) import _plotly_utils.basevalidators class DtickValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="dtick", parent_name="treemap.marker.colorbar", **kwargs ): super(DtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BorderwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="borderwidth", parent_name="treemap.marker.colorbar", **kwargs ): super(BorderwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="treemap.marker.colorbar", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="treemap.marker.colorbar", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/treemap/marker/colorbar/tickfont/0000755000175000017500000000000013573746614026326 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/treemap/marker/colorbar/tickfont/__init__.py0000644000175000017500000000316313573721544030435 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="treemap.marker.colorbar.tickfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="treemap.marker.colorbar.tickfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="treemap.marker.colorbar.tickfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/treemap/marker/__init__.py0000644000175000017500000004430113573721544025010 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ShowscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showscale", parent_name="treemap.marker", **kwargs): super(ShowscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ReversescaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="reversescale", parent_name="treemap.marker", **kwargs ): super(ReversescaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class PadValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="pad", parent_name="treemap.marker", **kwargs): super(PadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Pad"), data_docs=kwargs.pop( "data_docs", """ b Sets the padding form the bottom (in px). l Sets the padding form the left (in px). r Sets the padding form the right (in px). t Sets the padding form the top (in px). """, ), **kwargs ) import _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="line", parent_name="treemap.marker", **kwargs): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ color Sets the color of the line enclosing each sector. Defaults to the `paper_bgcolor` value. colorsrc Sets the source reference on plot.ly for color . width Sets the width (in px) of the line enclosing each sector. widthsrc Sets the source reference on plot.ly for width . """, ), **kwargs ) import _plotly_utils.basevalidators class DepthfadeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="depthfade", parent_name="treemap.marker", **kwargs): super(DepthfadeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", [True, False, "reversed"]), **kwargs ) import _plotly_utils.basevalidators class ColorssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="colorssrc", parent_name="treemap.marker", **kwargs): super(ColorssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__( self, plotly_name="colorscale", parent_name="treemap.marker", **kwargs ): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"autocolorscale": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="colors", parent_name="treemap.marker", **kwargs): super(ColorsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class ColorBarValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="colorbar", parent_name="treemap.marker", **kwargs): super(ColorBarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "ColorBar"), data_docs=kwargs.pop( "data_docs", """ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.treemap.marker. colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.treemap.marker.colorbar.tickformatstopdefault s), sets the default property values to use for elements of treemap.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.treemap.marker.colorbar.Ti tle instance or dict with compatible properties titlefont Deprecated: Please use treemap.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use treemap.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """, ), **kwargs ) import _plotly_utils.basevalidators class ColoraxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="coloraxis", parent_name="treemap.marker", **kwargs): super(ColoraxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", None), edit_type=kwargs.pop("edit_type", "calc"), regex=kwargs.pop("regex", "/^coloraxis([2-9]|[1-9][0-9]+)?$/"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmin", parent_name="treemap.marker", **kwargs): super(CminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmidValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmid", parent_name="treemap.marker", **kwargs): super(CmidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CmaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="cmax", parent_name="treemap.marker", **kwargs): super(CmaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), implied_edits=kwargs.pop("implied_edits", {"cauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CautoValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="cauto", parent_name="treemap.marker", **kwargs): super(CautoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AutocolorscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="autocolorscale", parent_name="treemap.marker", **kwargs ): super(AutocolorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/treemap/marker/line/0000755000175000017500000000000013573746614023631 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/treemap/marker/line/__init__.py0000644000175000017500000000372513573721544025744 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="widthsrc", parent_name="treemap.marker.line", **kwargs ): super(WidthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="width", parent_name="treemap.marker.line", **kwargs ): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="treemap.marker.line", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="treemap.marker.line", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/treemap/tiling/0000755000175000017500000000000013573746614022707 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/treemap/tiling/__init__.py0000644000175000017500000000406413573721544025017 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SquarifyratioValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="squarifyratio", parent_name="treemap.tiling", **kwargs ): super(SquarifyratioValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class PadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="pad", parent_name="treemap.tiling", **kwargs): super(PadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class PackingValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="packing", parent_name="treemap.tiling", **kwargs): super(PackingValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", ["squarify", "binary", "dice", "slice", "slice-dice", "dice-slice"], ), **kwargs ) import _plotly_utils.basevalidators class FlipValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="flip", parent_name="treemap.tiling", **kwargs): super(FlipValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), flags=kwargs.pop("flags", ["x", "y"]), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/treemap/stream/0000755000175000017500000000000013573746614022714 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/treemap/stream/__init__.py0000644000175000017500000000206413573721544025022 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TokenValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="token", parent_name="treemap.stream", **kwargs): super(TokenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "info"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class MaxpointsValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="maxpoints", parent_name="treemap.stream", **kwargs): super(MaxpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 10000), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/treemap/__init__.py0000644000175000017500000010366113573721544023534 0ustar noahfxnoahfximport _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="visible", parent_name="treemap", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "legendonly"]), **kwargs ) import _plotly_utils.basevalidators class ValuessrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="valuessrc", parent_name="treemap", **kwargs): super(ValuessrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ValuesValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="values", parent_name="treemap", **kwargs): super(ValuesValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="treemap", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UidValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="uid", parent_name="treemap", **kwargs): super(UidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, anim=kwargs.pop("anim", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TilingValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="tiling", parent_name="treemap", **kwargs): super(TilingValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tiling"), data_docs=kwargs.pop( "data_docs", """ flip Determines if the positions obtained from solver are flipped on each axis. packing Determines d3 treemap solver. For more info please refer to https://github.com/d3/d3-hierarchy#treemap- tiling pad Sets the inner padding (in px). squarifyratio When using "squarify" `packing` algorithm, according to https://github.com/d3/d3-hierarchy /blob/master/README.md#squarify_ratio this option specifies the desired aspect ratio of the generated rectangles. The ratio must be specified as a number greater than or equal to one. Note that the orientation of the generated rectangles (tall or wide) is not implied by the ratio; for example, a ratio of two will attempt to produce a mixture of rectangles whose width:height ratio is either 2:1 or 1:2. When using "squarify", unlike d3 which uses the Golden Ratio i.e. 1.618034, Plotly applies 1 to increase squares in treemap layouts. """, ), **kwargs ) import _plotly_utils.basevalidators class TexttemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="texttemplatesrc", parent_name="treemap", **kwargs): super(TexttemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TexttemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="texttemplate", parent_name="treemap", **kwargs): super(TexttemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="textsrc", parent_name="treemap", **kwargs): super(TextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextpositionValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="textposition", parent_name="treemap", **kwargs): super(TextpositionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", [ "top left", "top center", "top right", "middle left", "middle center", "middle right", "bottom left", "bottom center", "bottom right", ], ), **kwargs ) import _plotly_utils.basevalidators class TextinfoValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="textinfo", parent_name="treemap", **kwargs): super(TextinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), extras=kwargs.pop("extras", ["none"]), flags=kwargs.pop( "flags", [ "label", "text", "value", "current path", "percent root", "percent entry", "percent parent", ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="textfont", parent_name="treemap", **kwargs): super(TextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Textfont"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="text", parent_name="treemap", **kwargs): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class StreamValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="stream", parent_name="treemap", **kwargs): super(StreamValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Stream"), data_docs=kwargs.pop( "data_docs", """ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """, ), **kwargs ) import _plotly_utils.basevalidators class PathbarValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="pathbar", parent_name="treemap", **kwargs): super(PathbarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Pathbar"), data_docs=kwargs.pop( "data_docs", """ edgeshape Determines which shape is used for edges between `barpath` labels. side Determines on which side of the the treemap the `pathbar` should be presented. textfont Sets the font used inside `pathbar`. thickness Sets the thickness of `pathbar` (in px). If not specified the `pathbar.textfont.size` is used with 3 pixles extra padding on each side. visible Determines if the path bar is drawn i.e. outside the trace `domain` and with one pixel gap. """, ), **kwargs ) import _plotly_utils.basevalidators class ParentssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="parentssrc", parent_name="treemap", **kwargs): super(ParentssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ParentsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="parents", parent_name="treemap", **kwargs): super(ParentsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class OutsidetextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="outsidetextfont", parent_name="treemap", **kwargs): super(OutsidetextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Outsidetextfont"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="treemap", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="treemap", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="metasrc", parent_name="treemap", **kwargs): super(MetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetaValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="meta", parent_name="treemap", **kwargs): super(MetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MaxdepthValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="maxdepth", parent_name="treemap", **kwargs): super(MaxdepthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="marker", parent_name="treemap", **kwargs): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if colorsis set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here colors) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if colorsis set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if colorsis set to a numerical array. Value should have the same units as colors and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if colorsis set to a numerical array. Value should have the same units as colors. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if colorsis set to a numerical array. Value should have the same units as colors and if set, `marker.cmax` must be set as well. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.treemap.marker.ColorBar instance or dict with compatible properties colors Sets the color of each sector of this trace. If not specified, the default trace color set is used to pick the sector colors. colorscale Sets the colorscale. Has an effect only if colorsis set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorssrc Sets the source reference on plot.ly for colors . depthfade Determines if the sector colors are faded towards the background from the leaves up to the headers. This option is unavailable when a `colorscale` is present, defaults to false when `marker.colors` is set, but otherwise defaults to true. When set to "reversed", the fading direction is inverted, that is the top elements within hierarchy are drawn with fully saturated colors while the leaves are faded towards the background color. line plotly.graph_objects.treemap.marker.Line instance or dict with compatible properties pad plotly.graph_objects.treemap.marker.Pad instance or dict with compatible properties reversescale Reverses the color mapping if true. Has an effect only if colorsis set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if colorsis set to a numerical array. """, ), **kwargs ) import _plotly_utils.basevalidators class LevelValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="level", parent_name="treemap", **kwargs): super(LevelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, anim=kwargs.pop("anim", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LabelssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="labelssrc", parent_name="treemap", **kwargs): super(LabelssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LabelsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="labels", parent_name="treemap", **kwargs): super(LabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class InsidetextfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="insidetextfont", parent_name="treemap", **kwargs): super(InsidetextfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Insidetextfont"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class IdssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="idssrc", parent_name="treemap", **kwargs): super(IdssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ids", parent_name="treemap", **kwargs): super(IdsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, anim=kwargs.pop("anim", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class HovertextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hovertextsrc", parent_name="treemap", **kwargs): super(HovertextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertext", parent_name="treemap", **kwargs): super(HovertextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hovertemplatesrc", parent_name="treemap", **kwargs): super(HovertemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertemplate", parent_name="treemap", **kwargs): super(HovertemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverlabelValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="hoverlabel", parent_name="treemap", **kwargs): super(HoverlabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Hoverlabel"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """, ), **kwargs ) import _plotly_utils.basevalidators class HoverinfosrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hoverinfosrc", parent_name="treemap", **kwargs): super(HoverinfosrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverinfoValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="hoverinfo", parent_name="treemap", **kwargs): super(HoverinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), extras=kwargs.pop("extras", ["all", "none", "skip"]), flags=kwargs.pop( "flags", [ "label", "text", "value", "name", "current path", "percent root", "percent entry", "percent parent", ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DomainValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="domain", parent_name="treemap", **kwargs): super(DomainValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Domain"), data_docs=kwargs.pop( "data_docs", """ column If there is a layout grid, use the domain for this column in the grid for this treemap trace . row If there is a layout grid, use the domain for this row in the grid for this treemap trace . x Sets the horizontal domain of this treemap trace (in plot fraction). y Sets the vertical domain of this treemap trace (in plot fraction). """, ), **kwargs ) import _plotly_utils.basevalidators class CustomdatasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="customdatasrc", parent_name="treemap", **kwargs): super(CustomdatasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdataValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="customdata", parent_name="treemap", **kwargs): super(CustomdataValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class CountValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="count", parent_name="treemap", **kwargs): super(CountValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), flags=kwargs.pop("flags", ["branches", "leaves"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BranchvaluesValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="branchvalues", parent_name="treemap", **kwargs): super(BranchvaluesValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["remainder", "total"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/treemap/insidetextfont/0000755000175000017500000000000013573746614024470 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/treemap/insidetextfont/__init__.py0000644000175000017500000000603713573721544026602 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="treemap.insidetextfont", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="treemap.insidetextfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="treemap.insidetextfont", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="treemap.insidetextfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="treemap.insidetextfont", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="treemap.insidetextfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/treemap/domain/0000755000175000017500000000000013573746614022670 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/treemap/domain/__init__.py0000644000175000017500000000451113573721544024775 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="y", parent_name="treemap.domain", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), items=kwargs.pop( "items", [ {"valType": "number", "min": 0, "max": 1, "editType": "calc"}, {"valType": "number", "min": 0, "max": 1, "editType": "calc"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="x", parent_name="treemap.domain", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), items=kwargs.pop( "items", [ {"valType": "number", "min": 0, "max": 1, "editType": "calc"}, {"valType": "number", "min": 0, "max": 1, "editType": "calc"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class RowValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="row", parent_name="treemap.domain", **kwargs): super(RowValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColumnValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__(self, plotly_name="column", parent_name="treemap.domain", **kwargs): super(ColumnValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/densitymapbox/0000755000175000017500000000000013573746614022652 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/densitymapbox/hoverlabel/0000755000175000017500000000000013573746614024775 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/densitymapbox/hoverlabel/__init__.py0000644000175000017500000001363513573721537027113 0ustar noahfxnoahfximport _plotly_utils.basevalidators class NamelengthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="namelengthsrc", parent_name="densitymapbox.hoverlabel", **kwargs ): super(NamelengthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NamelengthValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="namelength", parent_name="densitymapbox.hoverlabel", **kwargs ): super(NamelengthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", -1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="densitymapbox.hoverlabel", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class BordercolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bordercolorsrc", parent_name="densitymapbox.hoverlabel", **kwargs ): super(BordercolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="densitymapbox.hoverlabel", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bgcolorsrc", parent_name="densitymapbox.hoverlabel", **kwargs ): super(BgcolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="densitymapbox.hoverlabel", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AlignsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="alignsrc", parent_name="densitymapbox.hoverlabel", **kwargs ): super(AlignsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="align", parent_name="densitymapbox.hoverlabel", **kwargs ): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "right", "auto"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/densitymapbox/hoverlabel/font/0000755000175000017500000000000013573746614025743 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/densitymapbox/hoverlabel/font/__init__.py0000644000175000017500000000625113573721537030055 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="densitymapbox.hoverlabel.font", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="densitymapbox.hoverlabel.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="densitymapbox.hoverlabel.font", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="densitymapbox.hoverlabel.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="densitymapbox.hoverlabel.font", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="densitymapbox.hoverlabel.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/densitymapbox/colorbar/0000755000175000017500000000000013573746614024455 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/densitymapbox/colorbar/tickformatstop/0000755000175000017500000000000013573746614027526 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/densitymapbox/colorbar/tickformatstop/__init__.py0000644000175000017500000000543213573721536031637 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ValueValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="value", parent_name="densitymapbox.colorbar.tickformatstop", **kwargs ): super(ValueValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="templateitemname", parent_name="densitymapbox.colorbar.tickformatstop", **kwargs ): super(TemplateitemnameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="name", parent_name="densitymapbox.colorbar.tickformatstop", **kwargs ): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class EnabledValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="enabled", parent_name="densitymapbox.colorbar.tickformatstop", **kwargs ): super(EnabledValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DtickrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__( self, plotly_name="dtickrange", parent_name="densitymapbox.colorbar.tickformatstop", **kwargs ): super(DtickrangeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), items=kwargs.pop( "items", [ {"valType": "any", "editType": "colorbars"}, {"valType": "any", "editType": "colorbars"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/densitymapbox/colorbar/title/0000755000175000017500000000000013573746614025576 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/densitymapbox/colorbar/title/__init__.py0000644000175000017500000000473713573721536027716 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="text", parent_name="densitymapbox.colorbar.title", **kwargs ): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SideValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="side", parent_name="densitymapbox.colorbar.title", **kwargs ): super(SideValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["right", "top", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="font", parent_name="densitymapbox.colorbar.title", **kwargs ): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/densitymapbox/colorbar/title/font/0000755000175000017500000000000013573746614026544 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/densitymapbox/colorbar/title/font/__init__.py0000644000175000017500000000316613573721536030657 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="densitymapbox.colorbar.title.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="densitymapbox.colorbar.title.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="densitymapbox.colorbar.title.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/densitymapbox/colorbar/__init__.py0000644000175000017500000006106313573721537026571 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ypad", parent_name="densitymapbox.colorbar", **kwargs ): super(YpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class YanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="yanchor", parent_name="densitymapbox.colorbar", **kwargs ): super(YanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["top", "middle", "bottom"]), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="y", parent_name="densitymapbox.colorbar", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XpadValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="xpad", parent_name="densitymapbox.colorbar", **kwargs ): super(XpadValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class XanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="xanchor", parent_name="densitymapbox.colorbar", **kwargs ): super(XanchorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "center", "right"]), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="x", parent_name="densitymapbox.colorbar", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), max=kwargs.pop("max", 3), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TitleValidator(_plotly_utils.basevalidators.TitleValidator): def __init__( self, plotly_name="title", parent_name="densitymapbox.colorbar", **kwargs ): super(TitleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Title"), data_docs=kwargs.pop( "data_docs", """ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """, ), **kwargs ) import _plotly_utils.basevalidators class TickwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="tickwidth", parent_name="densitymapbox.colorbar", **kwargs ): super(TickwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickvalssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="tickvalssrc", parent_name="densitymapbox.colorbar", **kwargs ): super(TickvalssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TickvalsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="tickvals", parent_name="densitymapbox.colorbar", **kwargs ): super(TickvalsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="ticktextsrc", parent_name="densitymapbox.colorbar", **kwargs ): super(TicktextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TicktextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__( self, plotly_name="ticktext", parent_name="densitymapbox.colorbar", **kwargs ): super(TicktextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="ticksuffix", parent_name="densitymapbox.colorbar", **kwargs ): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TicksValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="ticks", parent_name="densitymapbox.colorbar", **kwargs ): super(TicksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["outside", "inside", ""]), **kwargs ) import _plotly_utils.basevalidators class TickprefixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickprefix", parent_name="densitymapbox.colorbar", **kwargs ): super(TickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="tickmode", parent_name="densitymapbox.colorbar", **kwargs ): super(TickmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["auto", "linear", "array"]), **kwargs ) import _plotly_utils.basevalidators class TicklenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="ticklen", parent_name="densitymapbox.colorbar", **kwargs ): super(TicklenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickformatstopValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickformatstopdefaults", parent_name="densitymapbox.colorbar", **kwargs ): super(TickformatstopValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatstopsValidator(_plotly_utils.basevalidators.CompoundArrayValidator): def __init__( self, plotly_name="tickformatstops", parent_name="densitymapbox.colorbar", **kwargs ): super(TickformatstopsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickformatstop"), data_docs=kwargs.pop( "data_docs", """ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """, ), **kwargs ) import _plotly_utils.basevalidators class TickformatValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="tickformat", parent_name="densitymapbox.colorbar", **kwargs ): super(TickformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickfontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="tickfont", parent_name="densitymapbox.colorbar", **kwargs ): super(TickfontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Tickfont"), data_docs=kwargs.pop( "data_docs", """ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """, ), **kwargs ) import _plotly_utils.basevalidators class TickcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="tickcolor", parent_name="densitymapbox.colorbar", **kwargs ): super(TickcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class TickangleValidator(_plotly_utils.basevalidators.AngleValidator): def __init__( self, plotly_name="tickangle", parent_name="densitymapbox.colorbar", **kwargs ): super(TickangleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="tick0", parent_name="densitymapbox.colorbar", **kwargs ): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ThicknessmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="thicknessmode", parent_name="densitymapbox.colorbar", **kwargs ): super(ThicknessmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class ThicknessValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="thickness", parent_name="densitymapbox.colorbar", **kwargs ): super(ThicknessValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowticksuffixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showticksuffix", parent_name="densitymapbox.colorbar", **kwargs ): super(ShowticksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowtickprefixValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showtickprefix", parent_name="densitymapbox.colorbar", **kwargs ): super(ShowtickprefixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class ShowticklabelsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="showticklabels", parent_name="densitymapbox.colorbar", **kwargs ): super(ShowticklabelsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ShowexponentValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="showexponent", parent_name="densitymapbox.colorbar", **kwargs ): super(ShowexponentValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["all", "first", "last", "none"]), **kwargs ) import _plotly_utils.basevalidators class SeparatethousandsValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="separatethousands", parent_name="densitymapbox.colorbar", **kwargs ): super(SeparatethousandsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinewidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="outlinewidth", parent_name="densitymapbox.colorbar", **kwargs ): super(OutlinewidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlinecolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="outlinecolor", parent_name="densitymapbox.colorbar", **kwargs ): super(OutlinecolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NticksValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="nticks", parent_name="densitymapbox.colorbar", **kwargs ): super(NticksValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LenmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="lenmode", parent_name="densitymapbox.colorbar", **kwargs ): super(LenmodeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["fraction", "pixels"]), **kwargs ) import _plotly_utils.basevalidators class LenValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="len", parent_name="densitymapbox.colorbar", **kwargs ): super(LenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ExponentformatValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__( self, plotly_name="exponentformat", parent_name="densitymapbox.colorbar", **kwargs ): super(ExponentformatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["none", "e", "E", "power", "SI", "B"]), **kwargs ) import _plotly_utils.basevalidators class DtickValidator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name="dtick", parent_name="densitymapbox.colorbar", **kwargs ): super(DtickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), implied_edits=kwargs.pop("implied_edits", {"tickmode": "linear"}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BorderwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="borderwidth", parent_name="densitymapbox.colorbar", **kwargs ): super(BorderwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="densitymapbox.colorbar", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bgcolor", parent_name="densitymapbox.colorbar", **kwargs ): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/densitymapbox/colorbar/tickfont/0000755000175000017500000000000013573746614026276 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/densitymapbox/colorbar/tickfont/__init__.py0000644000175000017500000000316013573721536030403 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="densitymapbox.colorbar.tickfont", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="densitymapbox.colorbar.tickfont", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="densitymapbox.colorbar.tickfont", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "colorbars"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/densitymapbox/stream/0000755000175000017500000000000013573746614024145 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/densitymapbox/stream/__init__.py0000644000175000017500000000213413573721536026252 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TokenValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="token", parent_name="densitymapbox.stream", **kwargs ): super(TokenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "info"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class MaxpointsValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="maxpoints", parent_name="densitymapbox.stream", **kwargs ): super(MaxpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 10000), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/densitymapbox/__init__.py0000644000175000017500000007661513573721537024777 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ZsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="zsrc", parent_name="densitymapbox", **kwargs): super(ZsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZminValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="zmin", parent_name="densitymapbox", **kwargs): super(ZminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"zauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZmidValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="zmid", parent_name="densitymapbox", **kwargs): super(ZmidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZmaxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="zmax", parent_name="densitymapbox", **kwargs): super(ZmaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"zauto": False}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZautoValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="zauto", parent_name="densitymapbox", **kwargs): super(ZautoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="z", parent_name="densitymapbox", **kwargs): super(ZValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="visible", parent_name="densitymapbox", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "legendonly"]), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="densitymapbox", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UidValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="uid", parent_name="densitymapbox", **kwargs): super(UidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="textsrc", parent_name="densitymapbox", **kwargs): super(TextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="text", parent_name="densitymapbox", **kwargs): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SubplotValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="subplot", parent_name="densitymapbox", **kwargs): super(SubplotValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "mapbox"), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class StreamValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="stream", parent_name="densitymapbox", **kwargs): super(StreamValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Stream"), data_docs=kwargs.pop( "data_docs", """ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """, ), **kwargs ) import _plotly_utils.basevalidators class ShowscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showscale", parent_name="densitymapbox", **kwargs): super(ShowscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ReversescaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="reversescale", parent_name="densitymapbox", **kwargs ): super(ReversescaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class RadiussrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="radiussrc", parent_name="densitymapbox", **kwargs): super(RadiussrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class RadiusValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="radius", parent_name="densitymapbox", **kwargs): super(RadiusValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="densitymapbox", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="densitymapbox", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="metasrc", parent_name="densitymapbox", **kwargs): super(MetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetaValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="meta", parent_name="densitymapbox", **kwargs): super(MetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LonsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="lonsrc", parent_name="densitymapbox", **kwargs): super(LonsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LonValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="lon", parent_name="densitymapbox", **kwargs): super(LonValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class LatsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="latsrc", parent_name="densitymapbox", **kwargs): super(LatsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class LatValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="lat", parent_name="densitymapbox", **kwargs): super(LatValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class IdssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="idssrc", parent_name="densitymapbox", **kwargs): super(IdssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ids", parent_name="densitymapbox", **kwargs): super(IdsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class HovertextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="hovertextsrc", parent_name="densitymapbox", **kwargs ): super(HovertextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertext", parent_name="densitymapbox", **kwargs): super(HovertextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="hovertemplatesrc", parent_name="densitymapbox", **kwargs ): super(HovertemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="hovertemplate", parent_name="densitymapbox", **kwargs ): super(HovertemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverlabelValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="hoverlabel", parent_name="densitymapbox", **kwargs): super(HoverlabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Hoverlabel"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """, ), **kwargs ) import _plotly_utils.basevalidators class HoverinfosrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="hoverinfosrc", parent_name="densitymapbox", **kwargs ): super(HoverinfosrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverinfoValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="hoverinfo", parent_name="densitymapbox", **kwargs): super(HoverinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), extras=kwargs.pop("extras", ["all", "none", "skip"]), flags=kwargs.pop("flags", ["lon", "lat", "z", "text", "name"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdatasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="customdatasrc", parent_name="densitymapbox", **kwargs ): super(CustomdatasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdataValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="customdata", parent_name="densitymapbox", **kwargs): super(CustomdataValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator): def __init__(self, plotly_name="colorscale", parent_name="densitymapbox", **kwargs): super(ColorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {"autocolorscale": False}), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorBarValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="colorbar", parent_name="densitymapbox", **kwargs): super(ColorBarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "ColorBar"), data_docs=kwargs.pop( "data_docs", """ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.densitymapbox.c olorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.densitymapbox.colorbar.tickformatstopdefaults ), sets the default property values to use for elements of densitymapbox.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.densitymapbox.colorbar.Tit le instance or dict with compatible properties titlefont Deprecated: Please use densitymapbox.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use densitymapbox.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """, ), **kwargs ) import _plotly_utils.basevalidators class ColoraxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="coloraxis", parent_name="densitymapbox", **kwargs): super(ColoraxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", None), edit_type=kwargs.pop("edit_type", "calc"), regex=kwargs.pop("regex", "/^coloraxis([2-9]|[1-9][0-9]+)?$/"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BelowValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="below", parent_name="densitymapbox", **kwargs): super(BelowValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AutocolorscaleValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__( self, plotly_name="autocolorscale", parent_name="densitymapbox", **kwargs ): super(AutocolorscaleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), implied_edits=kwargs.pop("implied_edits", {}), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/box/0000755000175000017500000000000013573746614020554 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/box/unselected/0000755000175000017500000000000013573746614022707 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/box/unselected/marker/0000755000175000017500000000000013573746614024170 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/box/unselected/marker/__init__.py0000644000175000017500000000275313573721536026304 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="box.unselected.marker", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="opacity", parent_name="box.unselected.marker", **kwargs ): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="box.unselected.marker", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/box/unselected/__init__.py0000644000175000017500000000162313573721536025016 0ustar noahfxnoahfximport _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="marker", parent_name="box.unselected", **kwargs): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. size Sets the marker size of unselected points, applied only when a selection exists. """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/box/hoverlabel/0000755000175000017500000000000013573746614022677 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/box/hoverlabel/__init__.py0000644000175000017500000001330313573721536025004 0ustar noahfxnoahfximport _plotly_utils.basevalidators class NamelengthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="namelengthsrc", parent_name="box.hoverlabel", **kwargs ): super(NamelengthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NamelengthValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="namelength", parent_name="box.hoverlabel", **kwargs ): super(NamelengthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", -1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="font", parent_name="box.hoverlabel", **kwargs): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class BordercolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bordercolorsrc", parent_name="box.hoverlabel", **kwargs ): super(BordercolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="box.hoverlabel", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bgcolorsrc", parent_name="box.hoverlabel", **kwargs ): super(BgcolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="bgcolor", parent_name="box.hoverlabel", **kwargs): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AlignsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="alignsrc", parent_name="box.hoverlabel", **kwargs): super(AlignsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="align", parent_name="box.hoverlabel", **kwargs): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "right", "auto"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/box/hoverlabel/font/0000755000175000017500000000000013573746614023645 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/box/hoverlabel/font/__init__.py0000644000175000017500000000577713573721536025772 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="box.hoverlabel.font", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="size", parent_name="box.hoverlabel.font", **kwargs): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="box.hoverlabel.font", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="box.hoverlabel.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="box.hoverlabel.font", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="box.hoverlabel.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/box/marker/0000755000175000017500000000000013573746614022035 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/box/marker/__init__.py0000644000175000017500000003055313573721536024150 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SymbolValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="symbol", parent_name="box.marker", **kwargs): super(SymbolValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", False), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", [ 0, "circle", 100, "circle-open", 200, "circle-dot", 300, "circle-open-dot", 1, "square", 101, "square-open", 201, "square-dot", 301, "square-open-dot", 2, "diamond", 102, "diamond-open", 202, "diamond-dot", 302, "diamond-open-dot", 3, "cross", 103, "cross-open", 203, "cross-dot", 303, "cross-open-dot", 4, "x", 104, "x-open", 204, "x-dot", 304, "x-open-dot", 5, "triangle-up", 105, "triangle-up-open", 205, "triangle-up-dot", 305, "triangle-up-open-dot", 6, "triangle-down", 106, "triangle-down-open", 206, "triangle-down-dot", 306, "triangle-down-open-dot", 7, "triangle-left", 107, "triangle-left-open", 207, "triangle-left-dot", 307, "triangle-left-open-dot", 8, "triangle-right", 108, "triangle-right-open", 208, "triangle-right-dot", 308, "triangle-right-open-dot", 9, "triangle-ne", 109, "triangle-ne-open", 209, "triangle-ne-dot", 309, "triangle-ne-open-dot", 10, "triangle-se", 110, "triangle-se-open", 210, "triangle-se-dot", 310, "triangle-se-open-dot", 11, "triangle-sw", 111, "triangle-sw-open", 211, "triangle-sw-dot", 311, "triangle-sw-open-dot", 12, "triangle-nw", 112, "triangle-nw-open", 212, "triangle-nw-dot", 312, "triangle-nw-open-dot", 13, "pentagon", 113, "pentagon-open", 213, "pentagon-dot", 313, "pentagon-open-dot", 14, "hexagon", 114, "hexagon-open", 214, "hexagon-dot", 314, "hexagon-open-dot", 15, "hexagon2", 115, "hexagon2-open", 215, "hexagon2-dot", 315, "hexagon2-open-dot", 16, "octagon", 116, "octagon-open", 216, "octagon-dot", 316, "octagon-open-dot", 17, "star", 117, "star-open", 217, "star-dot", 317, "star-open-dot", 18, "hexagram", 118, "hexagram-open", 218, "hexagram-dot", 318, "hexagram-open-dot", 19, "star-triangle-up", 119, "star-triangle-up-open", 219, "star-triangle-up-dot", 319, "star-triangle-up-open-dot", 20, "star-triangle-down", 120, "star-triangle-down-open", 220, "star-triangle-down-dot", 320, "star-triangle-down-open-dot", 21, "star-square", 121, "star-square-open", 221, "star-square-dot", 321, "star-square-open-dot", 22, "star-diamond", 122, "star-diamond-open", 222, "star-diamond-dot", 322, "star-diamond-open-dot", 23, "diamond-tall", 123, "diamond-tall-open", 223, "diamond-tall-dot", 323, "diamond-tall-open-dot", 24, "diamond-wide", 124, "diamond-wide-open", 224, "diamond-wide-dot", 324, "diamond-wide-open-dot", 25, "hourglass", 125, "hourglass-open", 26, "bowtie", 126, "bowtie-open", 27, "circle-cross", 127, "circle-cross-open", 28, "circle-x", 128, "circle-x-open", 29, "square-cross", 129, "square-cross-open", 30, "square-x", 130, "square-x-open", 31, "diamond-cross", 131, "diamond-cross-open", 32, "diamond-x", 132, "diamond-x-open", 33, "cross-thin", 133, "cross-thin-open", 34, "x-thin", 134, "x-thin-open", 35, "asterisk", 135, "asterisk-open", 36, "hash", 136, "hash-open", 236, "hash-dot", 336, "hash-open-dot", 37, "y-up", 137, "y-up-open", 38, "y-down", 138, "y-down-open", 39, "y-left", 139, "y-left-open", 40, "y-right", 140, "y-right-open", 41, "line-ew", 141, "line-ew-open", 42, "line-ns", 142, "line-ns-open", 43, "line-ne", 143, "line-ne-open", 44, "line-nw", 144, "line-nw-open", ], ), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="size", parent_name="box.marker", **kwargs): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", False), edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutliercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="outliercolor", parent_name="box.marker", **kwargs): super(OutliercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="box.marker", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", False), edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="line", parent_name="box.marker", **kwargs): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. outliercolor Sets the border line color of the outlier sample points. Defaults to marker.color outlierwidth Sets the border line width (in px) of the outlier sample points. width Sets the width (in px) of the lines bounding the marker points. """, ), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="box.marker", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", False), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/box/marker/line/0000755000175000017500000000000013573746614022764 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/box/marker/line/__init__.py0000644000175000017500000000376213573721536025101 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="box.marker.line", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", False), edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutlierwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="outlierwidth", parent_name="box.marker.line", **kwargs ): super(OutlierwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OutliercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="outliercolor", parent_name="box.marker.line", **kwargs ): super(OutliercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="box.marker.line", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", False), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/box/stream/0000755000175000017500000000000013573746614022047 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/box/stream/__init__.py0000644000175000017500000000205413573721536024155 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TokenValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="token", parent_name="box.stream", **kwargs): super(TokenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "info"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class MaxpointsValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="maxpoints", parent_name="box.stream", **kwargs): super(MaxpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 10000), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/box/__init__.py0000644000175000017500000007037613573721537022677 0ustar noahfxnoahfximport _plotly_utils.basevalidators class YsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="ysrc", parent_name="box", **kwargs): super(YsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YcalendarValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="ycalendar", parent_name="box", **kwargs): super(YcalendarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "gregorian", "chinese", "coptic", "discworld", "ethiopian", "hebrew", "islamic", "julian", "mayan", "nanakshahi", "nepali", "persian", "jalali", "taiwan", "thai", "ummalqura", ], ), **kwargs ) import _plotly_utils.basevalidators class YAxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="yaxis", parent_name="box", **kwargs): super(YAxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "y"), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class Y0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="y0", parent_name="box", **kwargs): super(Y0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class YValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="y", parent_name="box", **kwargs): super(YValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class XsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="xsrc", parent_name="box", **kwargs): super(XsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XcalendarValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="xcalendar", parent_name="box", **kwargs): super(XcalendarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop( "values", [ "gregorian", "chinese", "coptic", "discworld", "ethiopian", "hebrew", "islamic", "julian", "mayan", "nanakshahi", "nepali", "persian", "jalali", "taiwan", "thai", "ummalqura", ], ), **kwargs ) import _plotly_utils.basevalidators class XAxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="xaxis", parent_name="box", **kwargs): super(XAxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "x"), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class X0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="x0", parent_name="box", **kwargs): super(X0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="x", parent_name="box", **kwargs): super(XValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="box", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class WhiskerwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="whiskerwidth", parent_name="box", **kwargs): super(WhiskerwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="visible", parent_name="box", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "legendonly"]), **kwargs ) import _plotly_utils.basevalidators class UnselectedValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="unselected", parent_name="box", **kwargs): super(UnselectedValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Unselected"), data_docs=kwargs.pop( "data_docs", """ marker plotly.graph_objects.box.unselected.Marker instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="box", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UidValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="uid", parent_name="box", **kwargs): super(UidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="textsrc", parent_name="box", **kwargs): super(TextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="text", parent_name="box", **kwargs): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class StreamValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="stream", parent_name="box", **kwargs): super(StreamValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Stream"), data_docs=kwargs.pop( "data_docs", """ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """, ), **kwargs ) import _plotly_utils.basevalidators class ShowlegendValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="showlegend", parent_name="box", **kwargs): super(ShowlegendValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SelectedpointsValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="selectedpoints", parent_name="box", **kwargs): super(SelectedpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SelectedValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="selected", parent_name="box", **kwargs): super(SelectedValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Selected"), data_docs=kwargs.pop( "data_docs", """ marker plotly.graph_objects.box.selected.Marker instance or dict with compatible properties """, ), **kwargs ) import _plotly_utils.basevalidators class PointposValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="pointpos", parent_name="box", **kwargs): super(PointposValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 2), min=kwargs.pop("min", -2), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OrientationValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="orientation", parent_name="box", **kwargs): super(OrientationValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["v", "h"]), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="box", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OffsetgroupValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="offsetgroup", parent_name="box", **kwargs): super(OffsetgroupValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NotchwidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="notchwidth", parent_name="box", **kwargs): super(NotchwidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 0.5), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NotchedValidator(_plotly_utils.basevalidators.BooleanValidator): def __init__(self, plotly_name="notched", parent_name="box", **kwargs): super(NotchedValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="box", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="metasrc", parent_name="box", **kwargs): super(MetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetaValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="meta", parent_name="box", **kwargs): super(MetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="marker", parent_name="box", **kwargs): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. line plotly.graph_objects.box.marker.Line instance or dict with compatible properties opacity Sets the marker opacity. outliercolor Sets the color of the outlier sample points. size Sets the marker size (in px). symbol Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot- open" to a symbol name. """, ), **kwargs ) import _plotly_utils.basevalidators class LineValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="line", parent_name="box", **kwargs): super(LineValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Line"), data_docs=kwargs.pop( "data_docs", """ color Sets the color of line bounding the box(es). width Sets the width (in px) of line bounding the box(es). """, ), **kwargs ) import _plotly_utils.basevalidators class LegendgroupValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="legendgroup", parent_name="box", **kwargs): super(LegendgroupValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class JitterValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="jitter", parent_name="box", **kwargs): super(JitterValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class IdssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="idssrc", parent_name="box", **kwargs): super(IdssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ids", parent_name="box", **kwargs): super(IdsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class HovertextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hovertextsrc", parent_name="box", **kwargs): super(HovertextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertextValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertext", parent_name="box", **kwargs): super(HovertextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hovertemplatesrc", parent_name="box", **kwargs): super(HovertemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertemplate", parent_name="box", **kwargs): super(HovertemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoveronValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="hoveron", parent_name="box", **kwargs): super(HoveronValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), flags=kwargs.pop("flags", ["boxes", "points"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverlabelValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="hoverlabel", parent_name="box", **kwargs): super(HoverlabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Hoverlabel"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """, ), **kwargs ) import _plotly_utils.basevalidators class HoverinfosrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hoverinfosrc", parent_name="box", **kwargs): super(HoverinfosrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverinfoValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="hoverinfo", parent_name="box", **kwargs): super(HoverinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), extras=kwargs.pop("extras", ["all", "none", "skip"]), flags=kwargs.pop("flags", ["x", "y", "z", "text", "name"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FillcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="fillcolor", parent_name="box", **kwargs): super(FillcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class CustomdatasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="customdatasrc", parent_name="box", **kwargs): super(CustomdatasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdataValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="customdata", parent_name="box", **kwargs): super(CustomdataValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class BoxpointsValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="boxpoints", parent_name="box", **kwargs): super(BoxpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop( "values", ["all", "outliers", "suspectedoutliers", False] ), **kwargs ) import _plotly_utils.basevalidators class BoxmeanValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="boxmean", parent_name="box", **kwargs): super(BoxmeanValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", [True, "sd", False]), **kwargs ) import _plotly_utils.basevalidators class AlignmentgroupValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="alignmentgroup", parent_name="box", **kwargs): super(AlignmentgroupValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/box/line/0000755000175000017500000000000013573746614021503 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/box/line/__init__.py0000644000175000017500000000162313573721536023612 0ustar noahfxnoahfximport _plotly_utils.basevalidators class WidthValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="width", parent_name="box.line", **kwargs): super(WidthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="color", parent_name="box.line", **kwargs): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/box/selected/0000755000175000017500000000000013573746614022344 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/box/selected/marker/0000755000175000017500000000000013573746614023625 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/box/selected/marker/__init__.py0000644000175000017500000000272713573721536025742 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="size", parent_name="box.selected.marker", **kwargs): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="opacity", parent_name="box.selected.marker", **kwargs ): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="box.selected.marker", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/box/selected/__init__.py0000644000175000017500000000135113573721536024451 0ustar noahfxnoahfximport _plotly_utils.basevalidators class MarkerValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="marker", parent_name="box.selected", **kwargs): super(MarkerValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Marker"), data_docs=kwargs.pop( "data_docs", """ color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. size Sets the marker size of selected points. """, ), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/image/0000755000175000017500000000000013573746614021046 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/image/hoverlabel/0000755000175000017500000000000013573746614023171 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/image/hoverlabel/__init__.py0000644000175000017500000001334313573721537025303 0ustar noahfxnoahfximport _plotly_utils.basevalidators class NamelengthsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="namelengthsrc", parent_name="image.hoverlabel", **kwargs ): super(NamelengthsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class NamelengthValidator(_plotly_utils.basevalidators.IntegerValidator): def __init__( self, plotly_name="namelength", parent_name="image.hoverlabel", **kwargs ): super(NamelengthValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", -1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FontValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="font", parent_name="image.hoverlabel", **kwargs): super(FontValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Font"), data_docs=kwargs.pop( "data_docs", """ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """, ), **kwargs ) import _plotly_utils.basevalidators class BordercolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bordercolorsrc", parent_name="image.hoverlabel", **kwargs ): super(BordercolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="bordercolor", parent_name="image.hoverlabel", **kwargs ): super(BordercolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class BgcolorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="bgcolorsrc", parent_name="image.hoverlabel", **kwargs ): super(BgcolorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class BgcolorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__(self, plotly_name="bgcolor", parent_name="image.hoverlabel", **kwargs): super(BgcolorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class AlignsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="alignsrc", parent_name="image.hoverlabel", **kwargs ): super(AlignsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class AlignValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="align", parent_name="image.hoverlabel", **kwargs): super(AlignValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), values=kwargs.pop("values", ["left", "right", "auto"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/image/hoverlabel/font/0000755000175000017500000000000013573746614024137 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/image/hoverlabel/font/__init__.py0000644000175000017500000000603113573721537026245 0ustar noahfxnoahfximport _plotly_utils.basevalidators class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="sizesrc", parent_name="image.hoverlabel.font", **kwargs ): super(SizesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class SizeValidator(_plotly_utils.basevalidators.NumberValidator): def __init__( self, plotly_name="size", parent_name="image.hoverlabel.font", **kwargs ): super(SizeValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), min=kwargs.pop("min", 1), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="familysrc", parent_name="image.hoverlabel.font", **kwargs ): super(FamilysrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class FamilyValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="family", parent_name="image.hoverlabel.font", **kwargs ): super(FamilyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "style"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="image.hoverlabel.font", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="image.hoverlabel.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "style"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/image/stream/0000755000175000017500000000000013573746614022341 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/validators/image/stream/__init__.py0000644000175000017500000000206013573721537024445 0ustar noahfxnoahfximport _plotly_utils.basevalidators class TokenValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="token", parent_name="image.stream", **kwargs): super(TokenValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), no_blank=kwargs.pop("no_blank", True), role=kwargs.pop("role", "info"), strict=kwargs.pop("strict", True), **kwargs ) import _plotly_utils.basevalidators class MaxpointsValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="maxpoints", parent_name="image.stream", **kwargs): super(MaxpointsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), max=kwargs.pop("max", 10000), min=kwargs.pop("min", 0), role=kwargs.pop("role", "info"), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/validators/image/__init__.py0000644000175000017500000004216313573721540023154 0ustar noahfxnoahfximport _plotly_utils.basevalidators class ZsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="zsrc", parent_name="image", **kwargs): super(ZsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZminValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="zmin", parent_name="image", **kwargs): super(ZminValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), items=kwargs.pop( "items", [ {"valType": "number", "editType": "calc"}, {"valType": "number", "editType": "calc"}, {"valType": "number", "editType": "calc"}, {"valType": "number", "editType": "calc"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZmaxValidator(_plotly_utils.basevalidators.InfoArrayValidator): def __init__(self, plotly_name="zmax", parent_name="image", **kwargs): super(ZmaxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), items=kwargs.pop( "items", [ {"valType": "number", "editType": "calc"}, {"valType": "number", "editType": "calc"}, {"valType": "number", "editType": "calc"}, {"valType": "number", "editType": "calc"}, ], ), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class ZValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="z", parent_name="image", **kwargs): super(ZValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class YAxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="yaxis", parent_name="image", **kwargs): super(YAxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "y"), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class Y0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="y0", parent_name="image", **kwargs): super(Y0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class XAxisValidator(_plotly_utils.basevalidators.SubplotidValidator): def __init__(self, plotly_name="xaxis", parent_name="image", **kwargs): super(XAxisValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, dflt=kwargs.pop("dflt", "x"), edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class X0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="x0", parent_name="image", **kwargs): super(X0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc+clearAxisTypes"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class VisibleValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="visible", parent_name="image", **kwargs): super(VisibleValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", [True, False, "legendonly"]), **kwargs ) import _plotly_utils.basevalidators class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="uirevision", parent_name="image", **kwargs): super(UirevisionValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class UidValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="uid", parent_name="image", **kwargs): super(UidValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="textsrc", parent_name="image", **kwargs): super(TextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class TextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="text", parent_name="image", **kwargs): super(TextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class StreamValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="stream", parent_name="image", **kwargs): super(StreamValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Stream"), data_docs=kwargs.pop( "data_docs", """ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """, ), **kwargs ) import _plotly_utils.basevalidators class OpacityValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="opacity", parent_name="image", **kwargs): super(OpacityValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), max=kwargs.pop("max", 1), min=kwargs.pop("min", 0), role=kwargs.pop("role", "style"), **kwargs ) import _plotly_utils.basevalidators class NameValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="name", parent_name="image", **kwargs): super(NameValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "style"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="metasrc", parent_name="image", **kwargs): super(MetasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class MetaValidator(_plotly_utils.basevalidators.AnyValidator): def __init__(self, plotly_name="meta", parent_name="image", **kwargs): super(MetaValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdssrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="idssrc", parent_name="image", **kwargs): super(IdssrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class IdsValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="ids", parent_name="image", **kwargs): super(IdsValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class HovertextsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hovertextsrc", parent_name="image", **kwargs): super(HovertextsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertextValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="hovertext", parent_name="image", **kwargs): super(HovertextValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "plot"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class HovertemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hovertemplatesrc", parent_name="image", **kwargs): super(HovertemplatesrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HovertemplateValidator(_plotly_utils.basevalidators.StringValidator): def __init__(self, plotly_name="hovertemplate", parent_name="image", **kwargs): super(HovertemplateValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverlabelValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="hoverlabel", parent_name="image", **kwargs): super(HoverlabelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Hoverlabel"), data_docs=kwargs.pop( "data_docs", """ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """, ), **kwargs ) import _plotly_utils.basevalidators class HoverinfosrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="hoverinfosrc", parent_name="image", **kwargs): super(HoverinfosrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class HoverinfoValidator(_plotly_utils.basevalidators.FlaglistValidator): def __init__(self, plotly_name="hoverinfo", parent_name="image", **kwargs): super(HoverinfoValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), extras=kwargs.pop("extras", ["all", "none", "skip"]), flags=kwargs.pop("flags", ["x", "y", "z", "color", "name", "text"]), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DyValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="dy", parent_name="image", **kwargs): super(DyValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class DxValidator(_plotly_utils.basevalidators.NumberValidator): def __init__(self, plotly_name="dx", parent_name="image", **kwargs): super(DxValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdatasrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__(self, plotly_name="customdatasrc", parent_name="image", **kwargs): super(CustomdatasrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), role=kwargs.pop("role", "info"), **kwargs ) import _plotly_utils.basevalidators class CustomdataValidator(_plotly_utils.basevalidators.DataArrayValidator): def __init__(self, plotly_name="customdata", parent_name="image", **kwargs): super(CustomdataValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "data"), **kwargs ) import _plotly_utils.basevalidators class ColormodelValidator(_plotly_utils.basevalidators.EnumeratedValidator): def __init__(self, plotly_name="colormodel", parent_name="image", **kwargs): super(ColormodelValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), role=kwargs.pop("role", "info"), values=kwargs.pop("values", ["rgb", "rgba", "hsl", "hsla"]), **kwargs ) plotly-4.4.1+dfsg.orig/plotly/graph_objs/0000755000175000017500000000000013573746613017731 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/isosurface/0000755000175000017500000000000013573746613022074 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/isosurface/hoverlabel/0000755000175000017500000000000013573746613024217 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/isosurface/hoverlabel/__init__.py0000644000175000017500000002545713573721547026344 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "isosurface.hoverlabel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Font object Sets the font used in hover labels. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.isosurface.hoverlabel.Font color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.isosurface.hoverlabel.Font constructor must be a dict or an instance of plotly.graph_objs.isosurface.hoverlabel.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.isosurface.hoverlabel import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["colorsrc"] = v_font.ColorsrcValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["familysrc"] = v_font.FamilysrcValidator() self._validators["size"] = v_font.SizeValidator() self._validators["sizesrc"] = v_font.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/isosurface/colorbar/0000755000175000017500000000000013573746613023677 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/isosurface/colorbar/title/0000755000175000017500000000000013573746613025020 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/isosurface/colorbar/title/__init__.py0000644000175000017500000002054413573721547027135 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "isosurface.colorbar.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.isosurface.colorbar.title.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.isosurface.colorbar.title.Font constructor must be a dict or an instance of plotly.graph_objs.isosurface.colorbar.title.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.isosurface.colorbar.title import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/isosurface/colorbar/__init__.py0000644000175000017500000006064413573721547026021 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Title(_BaseTraceHierarchyType): # font # ---- @property def font(self): """ Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.isosurface.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.isosurface.colorbar.title.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # side # ---- @property def side(self): """ Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- Any """ return self["side"] @side.setter def side(self, val): self["side"] = val # text # ---- @property def text(self): """ Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "isosurface.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """ def __init__(self, arg=None, font=None, side=None, text=None, **kwargs): """ Construct a new Title object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.isosurface.colorbar.Title font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- Title """ super(Title, self).__init__("title") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.isosurface.colorbar.Title constructor must be a dict or an instance of plotly.graph_objs.isosurface.colorbar.Title""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.isosurface.colorbar import title as v_title # Initialize validators # --------------------- self._validators["font"] = v_title.FontValidator() self._validators["side"] = v_title.SideValidator() self._validators["text"] = v_title.TextValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("side", None) self["side"] = side if side is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickformatstop(_BaseTraceHierarchyType): # dtickrange # ---------- @property def dtickrange(self): """ range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" The 'dtickrange' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'dtickrange[0]' property accepts values of any type (1) The 'dtickrange[1]' property accepts values of any type Returns ------- list """ return self["dtickrange"] @dtickrange.setter def dtickrange(self, val): self["dtickrange"] = val # enabled # ------- @property def enabled(self): """ Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. The 'enabled' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["enabled"] @enabled.setter def enabled(self, val): self["enabled"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # value # ----- @property def value(self): """ string - dtickformat for described zoom level, the same as "tickformat" The 'value' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "isosurface.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """ def __init__( self, arg=None, dtickrange=None, enabled=None, name=None, templateitemname=None, value=None, **kwargs ): """ Construct a new Tickformatstop object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.isosurface.colorbar.Tickformatstop dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- Tickformatstop """ super(Tickformatstop, self).__init__("tickformatstops") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.isosurface.colorbar.Tickformatstop constructor must be a dict or an instance of plotly.graph_objs.isosurface.colorbar.Tickformatstop""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.isosurface.colorbar import ( tickformatstop as v_tickformatstop, ) # Initialize validators # --------------------- self._validators["dtickrange"] = v_tickformatstop.DtickrangeValidator() self._validators["enabled"] = v_tickformatstop.EnabledValidator() self._validators["name"] = v_tickformatstop.NameValidator() self._validators[ "templateitemname" ] = v_tickformatstop.TemplateitemnameValidator() self._validators["value"] = v_tickformatstop.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtickrange", None) self["dtickrange"] = dtickrange if dtickrange is not None else _v _v = arg.pop("enabled", None) self["enabled"] = enabled if enabled is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "isosurface.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Tickfont object Sets the color bar's tick label font Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.isosurface.colorbar.Tickfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Tickfont """ super(Tickfont, self).__init__("tickfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.isosurface.colorbar.Tickfont constructor must be a dict or an instance of plotly.graph_objs.isosurface.colorbar.Tickfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.isosurface.colorbar import tickfont as v_tickfont # Initialize validators # --------------------- self._validators["color"] = v_tickfont.ColorValidator() self._validators["family"] = v_tickfont.FamilyValidator() self._validators["size"] = v_tickfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Tickfont", "Tickformatstop", "Tickformatstop", "Title", "title"] from plotly.graph_objs.isosurface.colorbar import title plotly-4.4.1+dfsg.orig/plotly/graph_objs/isosurface/caps/0000755000175000017500000000000013573746613023022 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/isosurface/caps/__init__.py0000644000175000017500000003314213573721547025135 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Z(_BaseTraceHierarchyType): # fill # ---- @property def fill(self): """ Sets the fill ratio of the `caps`. The default fill value of the `caps` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. The 'fill' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["fill"] @fill.setter def fill(self, val): self["fill"] = val # show # ---- @property def show(self): """ Sets the fill ratio of the `slices`. The default fill value of the z `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. The 'show' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["show"] @show.setter def show(self, val): self["show"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "isosurface.caps" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ fill Sets the fill ratio of the `caps`. The default fill value of the `caps` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. show Sets the fill ratio of the `slices`. The default fill value of the z `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. """ def __init__(self, arg=None, fill=None, show=None, **kwargs): """ Construct a new Z object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.isosurface.caps.Z fill Sets the fill ratio of the `caps`. The default fill value of the `caps` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. show Sets the fill ratio of the `slices`. The default fill value of the z `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. Returns ------- Z """ super(Z, self).__init__("z") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.isosurface.caps.Z constructor must be a dict or an instance of plotly.graph_objs.isosurface.caps.Z""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.isosurface.caps import z as v_z # Initialize validators # --------------------- self._validators["fill"] = v_z.FillValidator() self._validators["show"] = v_z.ShowValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("fill", None) self["fill"] = fill if fill is not None else _v _v = arg.pop("show", None) self["show"] = show if show is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Y(_BaseTraceHierarchyType): # fill # ---- @property def fill(self): """ Sets the fill ratio of the `caps`. The default fill value of the `caps` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. The 'fill' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["fill"] @fill.setter def fill(self, val): self["fill"] = val # show # ---- @property def show(self): """ Sets the fill ratio of the `slices`. The default fill value of the y `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. The 'show' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["show"] @show.setter def show(self, val): self["show"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "isosurface.caps" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ fill Sets the fill ratio of the `caps`. The default fill value of the `caps` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. show Sets the fill ratio of the `slices`. The default fill value of the y `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. """ def __init__(self, arg=None, fill=None, show=None, **kwargs): """ Construct a new Y object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.isosurface.caps.Y fill Sets the fill ratio of the `caps`. The default fill value of the `caps` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. show Sets the fill ratio of the `slices`. The default fill value of the y `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. Returns ------- Y """ super(Y, self).__init__("y") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.isosurface.caps.Y constructor must be a dict or an instance of plotly.graph_objs.isosurface.caps.Y""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.isosurface.caps import y as v_y # Initialize validators # --------------------- self._validators["fill"] = v_y.FillValidator() self._validators["show"] = v_y.ShowValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("fill", None) self["fill"] = fill if fill is not None else _v _v = arg.pop("show", None) self["show"] = show if show is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class X(_BaseTraceHierarchyType): # fill # ---- @property def fill(self): """ Sets the fill ratio of the `caps`. The default fill value of the `caps` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. The 'fill' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["fill"] @fill.setter def fill(self, val): self["fill"] = val # show # ---- @property def show(self): """ Sets the fill ratio of the `slices`. The default fill value of the x `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. The 'show' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["show"] @show.setter def show(self, val): self["show"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "isosurface.caps" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ fill Sets the fill ratio of the `caps`. The default fill value of the `caps` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. show Sets the fill ratio of the `slices`. The default fill value of the x `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. """ def __init__(self, arg=None, fill=None, show=None, **kwargs): """ Construct a new X object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.isosurface.caps.X fill Sets the fill ratio of the `caps`. The default fill value of the `caps` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. show Sets the fill ratio of the `slices`. The default fill value of the x `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. Returns ------- X """ super(X, self).__init__("x") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.isosurface.caps.X constructor must be a dict or an instance of plotly.graph_objs.isosurface.caps.X""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.isosurface.caps import x as v_x # Initialize validators # --------------------- self._validators["fill"] = v_x.FillValidator() self._validators["show"] = v_x.ShowValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("fill", None) self["fill"] = fill if fill is not None else _v _v = arg.pop("show", None) self["show"] = show if show is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["X", "Y", "Z"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/isosurface/slices/0000755000175000017500000000000013573746613023356 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/isosurface/slices/__init__.py0000644000175000017500000004374713573721547025505 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Z(_BaseTraceHierarchyType): # fill # ---- @property def fill(self): """ Sets the fill ratio of the `slices`. The default fill value of the `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. The 'fill' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["fill"] @fill.setter def fill(self, val): self["fill"] = val # locations # --------- @property def locations(self): """ Specifies the location(s) of slices on the axis. When not specified slices would be created for all points of the axis z except start and end. The 'locations' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["locations"] @locations.setter def locations(self, val): self["locations"] = val # locationssrc # ------------ @property def locationssrc(self): """ Sets the source reference on plot.ly for locations . The 'locationssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["locationssrc"] @locationssrc.setter def locationssrc(self, val): self["locationssrc"] = val # show # ---- @property def show(self): """ Determines whether or not slice planes about the z dimension are drawn. The 'show' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["show"] @show.setter def show(self, val): self["show"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "isosurface.slices" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ fill Sets the fill ratio of the `slices`. The default fill value of the `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. locations Specifies the location(s) of slices on the axis. When not specified slices would be created for all points of the axis z except start and end. locationssrc Sets the source reference on plot.ly for locations . show Determines whether or not slice planes about the z dimension are drawn. """ def __init__( self, arg=None, fill=None, locations=None, locationssrc=None, show=None, **kwargs ): """ Construct a new Z object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.isosurface.slices.Z fill Sets the fill ratio of the `slices`. The default fill value of the `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. locations Specifies the location(s) of slices on the axis. When not specified slices would be created for all points of the axis z except start and end. locationssrc Sets the source reference on plot.ly for locations . show Determines whether or not slice planes about the z dimension are drawn. Returns ------- Z """ super(Z, self).__init__("z") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.isosurface.slices.Z constructor must be a dict or an instance of plotly.graph_objs.isosurface.slices.Z""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.isosurface.slices import z as v_z # Initialize validators # --------------------- self._validators["fill"] = v_z.FillValidator() self._validators["locations"] = v_z.LocationsValidator() self._validators["locationssrc"] = v_z.LocationssrcValidator() self._validators["show"] = v_z.ShowValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("fill", None) self["fill"] = fill if fill is not None else _v _v = arg.pop("locations", None) self["locations"] = locations if locations is not None else _v _v = arg.pop("locationssrc", None) self["locationssrc"] = locationssrc if locationssrc is not None else _v _v = arg.pop("show", None) self["show"] = show if show is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Y(_BaseTraceHierarchyType): # fill # ---- @property def fill(self): """ Sets the fill ratio of the `slices`. The default fill value of the `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. The 'fill' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["fill"] @fill.setter def fill(self, val): self["fill"] = val # locations # --------- @property def locations(self): """ Specifies the location(s) of slices on the axis. When not specified slices would be created for all points of the axis y except start and end. The 'locations' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["locations"] @locations.setter def locations(self, val): self["locations"] = val # locationssrc # ------------ @property def locationssrc(self): """ Sets the source reference on plot.ly for locations . The 'locationssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["locationssrc"] @locationssrc.setter def locationssrc(self, val): self["locationssrc"] = val # show # ---- @property def show(self): """ Determines whether or not slice planes about the y dimension are drawn. The 'show' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["show"] @show.setter def show(self, val): self["show"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "isosurface.slices" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ fill Sets the fill ratio of the `slices`. The default fill value of the `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. locations Specifies the location(s) of slices on the axis. When not specified slices would be created for all points of the axis y except start and end. locationssrc Sets the source reference on plot.ly for locations . show Determines whether or not slice planes about the y dimension are drawn. """ def __init__( self, arg=None, fill=None, locations=None, locationssrc=None, show=None, **kwargs ): """ Construct a new Y object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.isosurface.slices.Y fill Sets the fill ratio of the `slices`. The default fill value of the `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. locations Specifies the location(s) of slices on the axis. When not specified slices would be created for all points of the axis y except start and end. locationssrc Sets the source reference on plot.ly for locations . show Determines whether or not slice planes about the y dimension are drawn. Returns ------- Y """ super(Y, self).__init__("y") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.isosurface.slices.Y constructor must be a dict or an instance of plotly.graph_objs.isosurface.slices.Y""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.isosurface.slices import y as v_y # Initialize validators # --------------------- self._validators["fill"] = v_y.FillValidator() self._validators["locations"] = v_y.LocationsValidator() self._validators["locationssrc"] = v_y.LocationssrcValidator() self._validators["show"] = v_y.ShowValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("fill", None) self["fill"] = fill if fill is not None else _v _v = arg.pop("locations", None) self["locations"] = locations if locations is not None else _v _v = arg.pop("locationssrc", None) self["locationssrc"] = locationssrc if locationssrc is not None else _v _v = arg.pop("show", None) self["show"] = show if show is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class X(_BaseTraceHierarchyType): # fill # ---- @property def fill(self): """ Sets the fill ratio of the `slices`. The default fill value of the `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. The 'fill' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["fill"] @fill.setter def fill(self, val): self["fill"] = val # locations # --------- @property def locations(self): """ Specifies the location(s) of slices on the axis. When not specified slices would be created for all points of the axis x except start and end. The 'locations' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["locations"] @locations.setter def locations(self, val): self["locations"] = val # locationssrc # ------------ @property def locationssrc(self): """ Sets the source reference on plot.ly for locations . The 'locationssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["locationssrc"] @locationssrc.setter def locationssrc(self, val): self["locationssrc"] = val # show # ---- @property def show(self): """ Determines whether or not slice planes about the x dimension are drawn. The 'show' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["show"] @show.setter def show(self, val): self["show"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "isosurface.slices" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ fill Sets the fill ratio of the `slices`. The default fill value of the `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. locations Specifies the location(s) of slices on the axis. When not specified slices would be created for all points of the axis x except start and end. locationssrc Sets the source reference on plot.ly for locations . show Determines whether or not slice planes about the x dimension are drawn. """ def __init__( self, arg=None, fill=None, locations=None, locationssrc=None, show=None, **kwargs ): """ Construct a new X object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.isosurface.slices.X fill Sets the fill ratio of the `slices`. The default fill value of the `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. locations Specifies the location(s) of slices on the axis. When not specified slices would be created for all points of the axis x except start and end. locationssrc Sets the source reference on plot.ly for locations . show Determines whether or not slice planes about the x dimension are drawn. Returns ------- X """ super(X, self).__init__("x") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.isosurface.slices.X constructor must be a dict or an instance of plotly.graph_objs.isosurface.slices.X""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.isosurface.slices import x as v_x # Initialize validators # --------------------- self._validators["fill"] = v_x.FillValidator() self._validators["locations"] = v_x.LocationsValidator() self._validators["locationssrc"] = v_x.LocationssrcValidator() self._validators["show"] = v_x.ShowValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("fill", None) self["fill"] = fill if fill is not None else _v _v = arg.pop("locations", None) self["locations"] = locations if locations is not None else _v _v = arg.pop("locationssrc", None) self["locationssrc"] = locationssrc if locationssrc is not None else _v _v = arg.pop("show", None) self["show"] = show if show is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["X", "Y", "Z"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/isosurface/__init__.py0000644000175000017500000041521513573721550024206 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Surface(_BaseTraceHierarchyType): # count # ----- @property def count(self): """ Sets the number of iso-surfaces between minimum and maximum iso-values. By default this value is 2 meaning that only minimum and maximum surfaces would be drawn. The 'count' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [1, 9223372036854775807] Returns ------- int """ return self["count"] @count.setter def count(self, val): self["count"] = val # fill # ---- @property def fill(self): """ Sets the fill ratio of the iso-surface. The default fill value of the surface is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. The 'fill' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["fill"] @fill.setter def fill(self, val): self["fill"] = val # pattern # ------- @property def pattern(self): """ Sets the surface pattern of the iso-surface 3-D sections. The default pattern of the surface is `all` meaning that the rest of surface elements would be shaded. The check options (either 1 or 2) could be used to draw half of the squares on the surface. Using various combinations of capital `A`, `B`, `C`, `D` and `E` may also be used to reduce the number of triangles on the iso-surfaces and creating other patterns of interest. The 'pattern' property is a flaglist and may be specified as a string containing: - Any combination of ['A', 'B', 'C', 'D', 'E'] joined with '+' characters (e.g. 'A+B') OR exactly one of ['all', 'odd', 'even'] (e.g. 'even') Returns ------- Any """ return self["pattern"] @pattern.setter def pattern(self, val): self["pattern"] = val # show # ---- @property def show(self): """ Hides/displays surfaces between minimum and maximum iso-values. The 'show' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["show"] @show.setter def show(self, val): self["show"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "isosurface" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ count Sets the number of iso-surfaces between minimum and maximum iso-values. By default this value is 2 meaning that only minimum and maximum surfaces would be drawn. fill Sets the fill ratio of the iso-surface. The default fill value of the surface is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. pattern Sets the surface pattern of the iso-surface 3-D sections. The default pattern of the surface is `all` meaning that the rest of surface elements would be shaded. The check options (either 1 or 2) could be used to draw half of the squares on the surface. Using various combinations of capital `A`, `B`, `C`, `D` and `E` may also be used to reduce the number of triangles on the iso-surfaces and creating other patterns of interest. show Hides/displays surfaces between minimum and maximum iso-values. """ def __init__( self, arg=None, count=None, fill=None, pattern=None, show=None, **kwargs ): """ Construct a new Surface object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.isosurface.Surface count Sets the number of iso-surfaces between minimum and maximum iso-values. By default this value is 2 meaning that only minimum and maximum surfaces would be drawn. fill Sets the fill ratio of the iso-surface. The default fill value of the surface is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. pattern Sets the surface pattern of the iso-surface 3-D sections. The default pattern of the surface is `all` meaning that the rest of surface elements would be shaded. The check options (either 1 or 2) could be used to draw half of the squares on the surface. Using various combinations of capital `A`, `B`, `C`, `D` and `E` may also be used to reduce the number of triangles on the iso-surfaces and creating other patterns of interest. show Hides/displays surfaces between minimum and maximum iso-values. Returns ------- Surface """ super(Surface, self).__init__("surface") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.isosurface.Surface constructor must be a dict or an instance of plotly.graph_objs.isosurface.Surface""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.isosurface import surface as v_surface # Initialize validators # --------------------- self._validators["count"] = v_surface.CountValidator() self._validators["fill"] = v_surface.FillValidator() self._validators["pattern"] = v_surface.PatternValidator() self._validators["show"] = v_surface.ShowValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("count", None) self["count"] = count if count is not None else _v _v = arg.pop("fill", None) self["fill"] = fill if fill is not None else _v _v = arg.pop("pattern", None) self["pattern"] = pattern if pattern is not None else _v _v = arg.pop("show", None) self["show"] = show if show is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Stream(_BaseTraceHierarchyType): # maxpoints # --------- @property def maxpoints(self): """ Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. The 'maxpoints' property is a number and may be specified as: - An int or float in the interval [0, 10000] Returns ------- int|float """ return self["maxpoints"] @maxpoints.setter def maxpoints(self, val): self["maxpoints"] = val # token # ----- @property def token(self): """ The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. The 'token' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["token"] @token.setter def token(self, val): self["token"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "isosurface" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """ def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): """ Construct a new Stream object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.isosurface.Stream maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- Stream """ super(Stream, self).__init__("stream") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.isosurface.Stream constructor must be a dict or an instance of plotly.graph_objs.isosurface.Stream""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.isosurface import stream as v_stream # Initialize validators # --------------------- self._validators["maxpoints"] = v_stream.MaxpointsValidator() self._validators["token"] = v_stream.TokenValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("maxpoints", None) self["maxpoints"] = maxpoints if maxpoints is not None else _v _v = arg.pop("token", None) self["token"] = token if token is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Spaceframe(_BaseTraceHierarchyType): # fill # ---- @property def fill(self): """ Sets the fill ratio of the `spaceframe` elements. The default fill value is 0.15 meaning that only 15% of the area of every faces of tetras would be shaded. Applying a greater `fill` ratio would allow the creation of stronger elements or could be sued to have entirely closed areas (in case of using 1). The 'fill' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["fill"] @fill.setter def fill(self, val): self["fill"] = val # show # ---- @property def show(self): """ Displays/hides tetrahedron shapes between minimum and maximum iso-values. Often useful when either caps or surfaces are disabled or filled with values less than 1. The 'show' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["show"] @show.setter def show(self, val): self["show"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "isosurface" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ fill Sets the fill ratio of the `spaceframe` elements. The default fill value is 0.15 meaning that only 15% of the area of every faces of tetras would be shaded. Applying a greater `fill` ratio would allow the creation of stronger elements or could be sued to have entirely closed areas (in case of using 1). show Displays/hides tetrahedron shapes between minimum and maximum iso-values. Often useful when either caps or surfaces are disabled or filled with values less than 1. """ def __init__(self, arg=None, fill=None, show=None, **kwargs): """ Construct a new Spaceframe object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.isosurface.Spaceframe fill Sets the fill ratio of the `spaceframe` elements. The default fill value is 0.15 meaning that only 15% of the area of every faces of tetras would be shaded. Applying a greater `fill` ratio would allow the creation of stronger elements or could be sued to have entirely closed areas (in case of using 1). show Displays/hides tetrahedron shapes between minimum and maximum iso-values. Often useful when either caps or surfaces are disabled or filled with values less than 1. Returns ------- Spaceframe """ super(Spaceframe, self).__init__("spaceframe") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.isosurface.Spaceframe constructor must be a dict or an instance of plotly.graph_objs.isosurface.Spaceframe""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.isosurface import spaceframe as v_spaceframe # Initialize validators # --------------------- self._validators["fill"] = v_spaceframe.FillValidator() self._validators["show"] = v_spaceframe.ShowValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("fill", None) self["fill"] = fill if fill is not None else _v _v = arg.pop("show", None) self["show"] = show if show is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Slices(_BaseTraceHierarchyType): # x # - @property def x(self): """ The 'x' property is an instance of X that may be specified as: - An instance of plotly.graph_objs.isosurface.slices.X - A dict of string/value properties that will be passed to the X constructor Supported dict properties: fill Sets the fill ratio of the `slices`. The default fill value of the `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. locations Specifies the location(s) of slices on the axis. When not specified slices would be created for all points of the axis x except start and end. locationssrc Sets the source reference on plot.ly for locations . show Determines whether or not slice planes about the x dimension are drawn. Returns ------- plotly.graph_objs.isosurface.slices.X """ return self["x"] @x.setter def x(self, val): self["x"] = val # y # - @property def y(self): """ The 'y' property is an instance of Y that may be specified as: - An instance of plotly.graph_objs.isosurface.slices.Y - A dict of string/value properties that will be passed to the Y constructor Supported dict properties: fill Sets the fill ratio of the `slices`. The default fill value of the `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. locations Specifies the location(s) of slices on the axis. When not specified slices would be created for all points of the axis y except start and end. locationssrc Sets the source reference on plot.ly for locations . show Determines whether or not slice planes about the y dimension are drawn. Returns ------- plotly.graph_objs.isosurface.slices.Y """ return self["y"] @y.setter def y(self, val): self["y"] = val # z # - @property def z(self): """ The 'z' property is an instance of Z that may be specified as: - An instance of plotly.graph_objs.isosurface.slices.Z - A dict of string/value properties that will be passed to the Z constructor Supported dict properties: fill Sets the fill ratio of the `slices`. The default fill value of the `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. locations Specifies the location(s) of slices on the axis. When not specified slices would be created for all points of the axis z except start and end. locationssrc Sets the source reference on plot.ly for locations . show Determines whether or not slice planes about the z dimension are drawn. Returns ------- plotly.graph_objs.isosurface.slices.Z """ return self["z"] @z.setter def z(self, val): self["z"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "isosurface" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ x plotly.graph_objects.isosurface.slices.X instance or dict with compatible properties y plotly.graph_objects.isosurface.slices.Y instance or dict with compatible properties z plotly.graph_objects.isosurface.slices.Z instance or dict with compatible properties """ def __init__(self, arg=None, x=None, y=None, z=None, **kwargs): """ Construct a new Slices object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.isosurface.Slices x plotly.graph_objects.isosurface.slices.X instance or dict with compatible properties y plotly.graph_objects.isosurface.slices.Y instance or dict with compatible properties z plotly.graph_objects.isosurface.slices.Z instance or dict with compatible properties Returns ------- Slices """ super(Slices, self).__init__("slices") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.isosurface.Slices constructor must be a dict or an instance of plotly.graph_objs.isosurface.Slices""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.isosurface import slices as v_slices # Initialize validators # --------------------- self._validators["x"] = v_slices.XValidator() self._validators["y"] = v_slices.YValidator() self._validators["z"] = v_slices.ZValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("z", None) self["z"] = z if z is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Lightposition(_BaseTraceHierarchyType): # x # - @property def x(self): """ Numeric vector, representing the X coordinate for each vertex. The 'x' property is a number and may be specified as: - An int or float in the interval [-100000, 100000] Returns ------- int|float """ return self["x"] @x.setter def x(self, val): self["x"] = val # y # - @property def y(self): """ Numeric vector, representing the Y coordinate for each vertex. The 'y' property is a number and may be specified as: - An int or float in the interval [-100000, 100000] Returns ------- int|float """ return self["y"] @y.setter def y(self, val): self["y"] = val # z # - @property def z(self): """ Numeric vector, representing the Z coordinate for each vertex. The 'z' property is a number and may be specified as: - An int or float in the interval [-100000, 100000] Returns ------- int|float """ return self["z"] @z.setter def z(self, val): self["z"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "isosurface" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ x Numeric vector, representing the X coordinate for each vertex. y Numeric vector, representing the Y coordinate for each vertex. z Numeric vector, representing the Z coordinate for each vertex. """ def __init__(self, arg=None, x=None, y=None, z=None, **kwargs): """ Construct a new Lightposition object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.isosurface.Lightposition x Numeric vector, representing the X coordinate for each vertex. y Numeric vector, representing the Y coordinate for each vertex. z Numeric vector, representing the Z coordinate for each vertex. Returns ------- Lightposition """ super(Lightposition, self).__init__("lightposition") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.isosurface.Lightposition constructor must be a dict or an instance of plotly.graph_objs.isosurface.Lightposition""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.isosurface import lightposition as v_lightposition # Initialize validators # --------------------- self._validators["x"] = v_lightposition.XValidator() self._validators["y"] = v_lightposition.YValidator() self._validators["z"] = v_lightposition.ZValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("z", None) self["z"] = z if z is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Lighting(_BaseTraceHierarchyType): # ambient # ------- @property def ambient(self): """ Ambient light increases overall color visibility but can wash out the image. The 'ambient' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["ambient"] @ambient.setter def ambient(self, val): self["ambient"] = val # diffuse # ------- @property def diffuse(self): """ Represents the extent that incident rays are reflected in a range of angles. The 'diffuse' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["diffuse"] @diffuse.setter def diffuse(self, val): self["diffuse"] = val # facenormalsepsilon # ------------------ @property def facenormalsepsilon(self): """ Epsilon for face normals calculation avoids math issues arising from degenerate geometry. The 'facenormalsepsilon' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["facenormalsepsilon"] @facenormalsepsilon.setter def facenormalsepsilon(self, val): self["facenormalsepsilon"] = val # fresnel # ------- @property def fresnel(self): """ Represents the reflectance as a dependency of the viewing angle; e.g. paper is reflective when viewing it from the edge of the paper (almost 90 degrees), causing shine. The 'fresnel' property is a number and may be specified as: - An int or float in the interval [0, 5] Returns ------- int|float """ return self["fresnel"] @fresnel.setter def fresnel(self, val): self["fresnel"] = val # roughness # --------- @property def roughness(self): """ Alters specular reflection; the rougher the surface, the wider and less contrasty the shine. The 'roughness' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["roughness"] @roughness.setter def roughness(self, val): self["roughness"] = val # specular # -------- @property def specular(self): """ Represents the level that incident rays are reflected in a single direction, causing shine. The 'specular' property is a number and may be specified as: - An int or float in the interval [0, 2] Returns ------- int|float """ return self["specular"] @specular.setter def specular(self, val): self["specular"] = val # vertexnormalsepsilon # -------------------- @property def vertexnormalsepsilon(self): """ Epsilon for vertex normals calculation avoids math issues arising from degenerate geometry. The 'vertexnormalsepsilon' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["vertexnormalsepsilon"] @vertexnormalsepsilon.setter def vertexnormalsepsilon(self, val): self["vertexnormalsepsilon"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "isosurface" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ ambient Ambient light increases overall color visibility but can wash out the image. diffuse Represents the extent that incident rays are reflected in a range of angles. facenormalsepsilon Epsilon for face normals calculation avoids math issues arising from degenerate geometry. fresnel Represents the reflectance as a dependency of the viewing angle; e.g. paper is reflective when viewing it from the edge of the paper (almost 90 degrees), causing shine. roughness Alters specular reflection; the rougher the surface, the wider and less contrasty the shine. specular Represents the level that incident rays are reflected in a single direction, causing shine. vertexnormalsepsilon Epsilon for vertex normals calculation avoids math issues arising from degenerate geometry. """ def __init__( self, arg=None, ambient=None, diffuse=None, facenormalsepsilon=None, fresnel=None, roughness=None, specular=None, vertexnormalsepsilon=None, **kwargs ): """ Construct a new Lighting object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.isosurface.Lighting ambient Ambient light increases overall color visibility but can wash out the image. diffuse Represents the extent that incident rays are reflected in a range of angles. facenormalsepsilon Epsilon for face normals calculation avoids math issues arising from degenerate geometry. fresnel Represents the reflectance as a dependency of the viewing angle; e.g. paper is reflective when viewing it from the edge of the paper (almost 90 degrees), causing shine. roughness Alters specular reflection; the rougher the surface, the wider and less contrasty the shine. specular Represents the level that incident rays are reflected in a single direction, causing shine. vertexnormalsepsilon Epsilon for vertex normals calculation avoids math issues arising from degenerate geometry. Returns ------- Lighting """ super(Lighting, self).__init__("lighting") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.isosurface.Lighting constructor must be a dict or an instance of plotly.graph_objs.isosurface.Lighting""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.isosurface import lighting as v_lighting # Initialize validators # --------------------- self._validators["ambient"] = v_lighting.AmbientValidator() self._validators["diffuse"] = v_lighting.DiffuseValidator() self._validators[ "facenormalsepsilon" ] = v_lighting.FacenormalsepsilonValidator() self._validators["fresnel"] = v_lighting.FresnelValidator() self._validators["roughness"] = v_lighting.RoughnessValidator() self._validators["specular"] = v_lighting.SpecularValidator() self._validators[ "vertexnormalsepsilon" ] = v_lighting.VertexnormalsepsilonValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("ambient", None) self["ambient"] = ambient if ambient is not None else _v _v = arg.pop("diffuse", None) self["diffuse"] = diffuse if diffuse is not None else _v _v = arg.pop("facenormalsepsilon", None) self["facenormalsepsilon"] = ( facenormalsepsilon if facenormalsepsilon is not None else _v ) _v = arg.pop("fresnel", None) self["fresnel"] = fresnel if fresnel is not None else _v _v = arg.pop("roughness", None) self["roughness"] = roughness if roughness is not None else _v _v = arg.pop("specular", None) self["specular"] = specular if specular is not None else _v _v = arg.pop("vertexnormalsepsilon", None) self["vertexnormalsepsilon"] = ( vertexnormalsepsilon if vertexnormalsepsilon is not None else _v ) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Hoverlabel(_BaseTraceHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'right', 'auto'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["align"] @align.setter def align(self, val): self["align"] = val # alignsrc # -------- @property def alignsrc(self): """ Sets the source reference on plot.ly for align . The 'alignsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["alignsrc"] @alignsrc.setter def alignsrc(self, val): self["alignsrc"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the hover labels for this trace The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bgcolorsrc # ---------- @property def bgcolorsrc(self): """ Sets the source reference on plot.ly for bgcolor . The 'bgcolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bgcolorsrc"] @bgcolorsrc.setter def bgcolorsrc(self, val): self["bgcolorsrc"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the border color of the hover labels for this trace. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # bordercolorsrc # -------------- @property def bordercolorsrc(self): """ Sets the source reference on plot.ly for bordercolor . The 'bordercolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bordercolorsrc"] @bordercolorsrc.setter def bordercolorsrc(self, val): self["bordercolorsrc"] = val # font # ---- @property def font(self): """ Sets the font used in hover labels. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.isosurface.hoverlabel.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.isosurface.hoverlabel.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # namelength # ---------- @property def namelength(self): """ Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. The 'namelength' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [-1, 9223372036854775807] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|numpy.ndarray """ return self["namelength"] @namelength.setter def namelength(self, val): self["namelength"] = val # namelengthsrc # ------------- @property def namelengthsrc(self): """ Sets the source reference on plot.ly for namelength . The 'namelengthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["namelengthsrc"] @namelengthsrc.setter def namelengthsrc(self, val): self["namelengthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "isosurface" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """ def __init__( self, arg=None, align=None, alignsrc=None, bgcolor=None, bgcolorsrc=None, bordercolor=None, bordercolorsrc=None, font=None, namelength=None, namelengthsrc=None, **kwargs ): """ Construct a new Hoverlabel object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.isosurface.Hoverlabel align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- Hoverlabel """ super(Hoverlabel, self).__init__("hoverlabel") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.isosurface.Hoverlabel constructor must be a dict or an instance of plotly.graph_objs.isosurface.Hoverlabel""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.isosurface import hoverlabel as v_hoverlabel # Initialize validators # --------------------- self._validators["align"] = v_hoverlabel.AlignValidator() self._validators["alignsrc"] = v_hoverlabel.AlignsrcValidator() self._validators["bgcolor"] = v_hoverlabel.BgcolorValidator() self._validators["bgcolorsrc"] = v_hoverlabel.BgcolorsrcValidator() self._validators["bordercolor"] = v_hoverlabel.BordercolorValidator() self._validators["bordercolorsrc"] = v_hoverlabel.BordercolorsrcValidator() self._validators["font"] = v_hoverlabel.FontValidator() self._validators["namelength"] = v_hoverlabel.NamelengthValidator() self._validators["namelengthsrc"] = v_hoverlabel.NamelengthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("alignsrc", None) self["alignsrc"] = alignsrc if alignsrc is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bgcolorsrc", None) self["bgcolorsrc"] = bgcolorsrc if bgcolorsrc is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("bordercolorsrc", None) self["bordercolorsrc"] = bordercolorsrc if bordercolorsrc is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("namelength", None) self["namelength"] = namelength if namelength is not None else _v _v = arg.pop("namelengthsrc", None) self["namelengthsrc"] = namelengthsrc if namelengthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Contour(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the color of the contour lines. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # show # ---- @property def show(self): """ Sets whether or not dynamic contours are shown on hover The 'show' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["show"] @show.setter def show(self, val): self["show"] = val # width # ----- @property def width(self): """ Sets the width of the contour lines. The 'width' property is a number and may be specified as: - An int or float in the interval [1, 16] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "isosurface" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the color of the contour lines. show Sets whether or not dynamic contours are shown on hover width Sets the width of the contour lines. """ def __init__(self, arg=None, color=None, show=None, width=None, **kwargs): """ Construct a new Contour object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.isosurface.Contour color Sets the color of the contour lines. show Sets whether or not dynamic contours are shown on hover width Sets the width of the contour lines. Returns ------- Contour """ super(Contour, self).__init__("contour") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.isosurface.Contour constructor must be a dict or an instance of plotly.graph_objs.isosurface.Contour""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.isosurface import contour as v_contour # Initialize validators # --------------------- self._validators["color"] = v_contour.ColorValidator() self._validators["show"] = v_contour.ShowValidator() self._validators["width"] = v_contour.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("show", None) self["show"] = show if show is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class ColorBar(_BaseTraceHierarchyType): # bgcolor # ------- @property def bgcolor(self): """ Sets the color of padded area. The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the axis line color. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # borderwidth # ----------- @property def borderwidth(self): """ Sets the width (in px) or the border enclosing this color bar. The 'borderwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["borderwidth"] @borderwidth.setter def borderwidth(self, val): self["borderwidth"] = val # dtick # ----- @property def dtick(self): """ Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" The 'dtick' property accepts values of any type Returns ------- Any """ return self["dtick"] @dtick.setter def dtick(self, val): self["dtick"] = val # exponentformat # -------------- @property def exponentformat(self): """ Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. The 'exponentformat' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'e', 'E', 'power', 'SI', 'B'] Returns ------- Any """ return self["exponentformat"] @exponentformat.setter def exponentformat(self, val): self["exponentformat"] = val # len # --- @property def len(self): """ Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. The 'len' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["len"] @len.setter def len(self, val): self["len"] = val # lenmode # ------- @property def lenmode(self): """ Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. The 'lenmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["lenmode"] @lenmode.setter def lenmode(self, val): self["lenmode"] = val # nticks # ------ @property def nticks(self): """ Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". The 'nticks' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nticks"] @nticks.setter def nticks(self, val): self["nticks"] = val # outlinecolor # ------------ @property def outlinecolor(self): """ Sets the axis line color. The 'outlinecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["outlinecolor"] @outlinecolor.setter def outlinecolor(self, val): self["outlinecolor"] = val # outlinewidth # ------------ @property def outlinewidth(self): """ Sets the width (in px) of the axis line. The 'outlinewidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["outlinewidth"] @outlinewidth.setter def outlinewidth(self, val): self["outlinewidth"] = val # separatethousands # ----------------- @property def separatethousands(self): """ If "true", even 4-digit integers are separated The 'separatethousands' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["separatethousands"] @separatethousands.setter def separatethousands(self, val): self["separatethousands"] = val # showexponent # ------------ @property def showexponent(self): """ If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. The 'showexponent' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showexponent"] @showexponent.setter def showexponent(self, val): self["showexponent"] = val # showticklabels # -------------- @property def showticklabels(self): """ Determines whether or not the tick labels are drawn. The 'showticklabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showticklabels"] @showticklabels.setter def showticklabels(self, val): self["showticklabels"] = val # showtickprefix # -------------- @property def showtickprefix(self): """ If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. The 'showtickprefix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showtickprefix"] @showtickprefix.setter def showtickprefix(self, val): self["showtickprefix"] = val # showticksuffix # -------------- @property def showticksuffix(self): """ Same as `showtickprefix` but for tick suffixes. The 'showticksuffix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showticksuffix"] @showticksuffix.setter def showticksuffix(self, val): self["showticksuffix"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # thicknessmode # ------------- @property def thicknessmode(self): """ Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. The 'thicknessmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["thicknessmode"] @thicknessmode.setter def thicknessmode(self, val): self["thicknessmode"] = val # tick0 # ----- @property def tick0(self): """ Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. The 'tick0' property accepts values of any type Returns ------- Any """ return self["tick0"] @tick0.setter def tick0(self, val): self["tick0"] = val # tickangle # --------- @property def tickangle(self): """ Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. The 'tickangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["tickangle"] @tickangle.setter def tickangle(self, val): self["tickangle"] = val # tickcolor # --------- @property def tickcolor(self): """ Sets the tick color. The 'tickcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["tickcolor"] @tickcolor.setter def tickcolor(self, val): self["tickcolor"] = val # tickfont # -------- @property def tickfont(self): """ Sets the color bar's tick label font The 'tickfont' property is an instance of Tickfont that may be specified as: - An instance of plotly.graph_objs.isosurface.colorbar.Tickfont - A dict of string/value properties that will be passed to the Tickfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.isosurface.colorbar.Tickfont """ return self["tickfont"] @tickfont.setter def tickfont(self, val): self["tickfont"] = val # tickformat # ---------- @property def tickformat(self): """ Sets the tick label formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'tickformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickformat"] @tickformat.setter def tickformat(self, val): self["tickformat"] = val # tickformatstops # --------------- @property def tickformatstops(self): """ The 'tickformatstops' property is a tuple of instances of Tickformatstop that may be specified as: - A list or tuple of instances of plotly.graph_objs.isosurface.colorbar.Tickformatstop - A list or tuple of dicts of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- tuple[plotly.graph_objs.isosurface.colorbar.Tickformatstop] """ return self["tickformatstops"] @tickformatstops.setter def tickformatstops(self, val): self["tickformatstops"] = val # tickformatstopdefaults # ---------------------- @property def tickformatstopdefaults(self): """ When used in a template (as layout.template.data.isosurface.col orbar.tickformatstopdefaults), sets the default property values to use for elements of isosurface.colorbar.tickformatstops The 'tickformatstopdefaults' property is an instance of Tickformatstop that may be specified as: - An instance of plotly.graph_objs.isosurface.colorbar.Tickformatstop - A dict of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: Returns ------- plotly.graph_objs.isosurface.colorbar.Tickformatstop """ return self["tickformatstopdefaults"] @tickformatstopdefaults.setter def tickformatstopdefaults(self, val): self["tickformatstopdefaults"] = val # ticklen # ------- @property def ticklen(self): """ Sets the tick length (in px). The 'ticklen' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ticklen"] @ticklen.setter def ticklen(self, val): self["ticklen"] = val # tickmode # -------- @property def tickmode(self): """ Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). The 'tickmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'linear', 'array'] Returns ------- Any """ return self["tickmode"] @tickmode.setter def tickmode(self, val): self["tickmode"] = val # tickprefix # ---------- @property def tickprefix(self): """ Sets a tick label prefix. The 'tickprefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickprefix"] @tickprefix.setter def tickprefix(self, val): self["tickprefix"] = val # ticks # ----- @property def ticks(self): """ Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. The 'ticks' property is an enumeration that may be specified as: - One of the following enumeration values: ['outside', 'inside', ''] Returns ------- Any """ return self["ticks"] @ticks.setter def ticks(self, val): self["ticks"] = val # ticksuffix # ---------- @property def ticksuffix(self): """ Sets a tick label suffix. The 'ticksuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ticksuffix"] @ticksuffix.setter def ticksuffix(self, val): self["ticksuffix"] = val # ticktext # -------- @property def ticktext(self): """ Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. The 'ticktext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ticktext"] @ticktext.setter def ticktext(self, val): self["ticktext"] = val # ticktextsrc # ----------- @property def ticktextsrc(self): """ Sets the source reference on plot.ly for ticktext . The 'ticktextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ticktextsrc"] @ticktextsrc.setter def ticktextsrc(self, val): self["ticktextsrc"] = val # tickvals # -------- @property def tickvals(self): """ Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. The 'tickvals' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["tickvals"] @tickvals.setter def tickvals(self, val): self["tickvals"] = val # tickvalssrc # ----------- @property def tickvalssrc(self): """ Sets the source reference on plot.ly for tickvals . The 'tickvalssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tickvalssrc"] @tickvalssrc.setter def tickvalssrc(self, val): self["tickvalssrc"] = val # tickwidth # --------- @property def tickwidth(self): """ Sets the tick width (in px). The 'tickwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["tickwidth"] @tickwidth.setter def tickwidth(self, val): self["tickwidth"] = val # title # ----- @property def title(self): """ The 'title' property is an instance of Title that may be specified as: - An instance of plotly.graph_objs.isosurface.colorbar.Title - A dict of string/value properties that will be passed to the Title constructor Supported dict properties: font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- plotly.graph_objs.isosurface.colorbar.Title """ return self["title"] @title.setter def title(self, val): self["title"] = val # titlefont # --------- @property def titlefont(self): """ Deprecated: Please use isosurface.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.isosurface.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- """ return self["titlefont"] @titlefont.setter def titlefont(self, val): self["titlefont"] = val # titleside # --------- @property def titleside(self): """ Deprecated: Please use isosurface.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- """ return self["titleside"] @titleside.setter def titleside(self, val): self["titleside"] = val # x # - @property def x(self): """ Sets the x position of the color bar (in plot fraction). The 'x' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["x"] @x.setter def x(self, val): self["x"] = val # xanchor # ------- @property def xanchor(self): """ Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. The 'xanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'center', 'right'] Returns ------- Any """ return self["xanchor"] @xanchor.setter def xanchor(self, val): self["xanchor"] = val # xpad # ---- @property def xpad(self): """ Sets the amount of padding (in px) along the x direction. The 'xpad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["xpad"] @xpad.setter def xpad(self, val): self["xpad"] = val # y # - @property def y(self): """ Sets the y position of the color bar (in plot fraction). The 'y' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["y"] @y.setter def y(self, val): self["y"] = val # yanchor # ------- @property def yanchor(self): """ Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. The 'yanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['top', 'middle', 'bottom'] Returns ------- Any """ return self["yanchor"] @yanchor.setter def yanchor(self, val): self["yanchor"] = val # ypad # ---- @property def ypad(self): """ Sets the amount of padding (in px) along the y direction. The 'ypad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ypad"] @ypad.setter def ypad(self, val): self["ypad"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "isosurface" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.isosurface.colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.isosur face.colorbar.tickformatstopdefaults), sets the default property values to use for elements of isosurface.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.isosurface.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use isosurface.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use isosurface.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """ _mapped_properties = { "titlefont": ("title", "font"), "titleside": ("title", "side"), } def __init__( self, arg=None, bgcolor=None, bordercolor=None, borderwidth=None, dtick=None, exponentformat=None, len=None, lenmode=None, nticks=None, outlinecolor=None, outlinewidth=None, separatethousands=None, showexponent=None, showticklabels=None, showtickprefix=None, showticksuffix=None, thickness=None, thicknessmode=None, tick0=None, tickangle=None, tickcolor=None, tickfont=None, tickformat=None, tickformatstops=None, tickformatstopdefaults=None, ticklen=None, tickmode=None, tickprefix=None, ticks=None, ticksuffix=None, ticktext=None, ticktextsrc=None, tickvals=None, tickvalssrc=None, tickwidth=None, title=None, titlefont=None, titleside=None, x=None, xanchor=None, xpad=None, y=None, yanchor=None, ypad=None, **kwargs ): """ Construct a new ColorBar object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.isosurface.ColorBar bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.isosurface.colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.isosur face.colorbar.tickformatstopdefaults), sets the default property values to use for elements of isosurface.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.isosurface.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use isosurface.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use isosurface.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- ColorBar """ super(ColorBar, self).__init__("colorbar") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.isosurface.ColorBar constructor must be a dict or an instance of plotly.graph_objs.isosurface.ColorBar""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.isosurface import colorbar as v_colorbar # Initialize validators # --------------------- self._validators["bgcolor"] = v_colorbar.BgcolorValidator() self._validators["bordercolor"] = v_colorbar.BordercolorValidator() self._validators["borderwidth"] = v_colorbar.BorderwidthValidator() self._validators["dtick"] = v_colorbar.DtickValidator() self._validators["exponentformat"] = v_colorbar.ExponentformatValidator() self._validators["len"] = v_colorbar.LenValidator() self._validators["lenmode"] = v_colorbar.LenmodeValidator() self._validators["nticks"] = v_colorbar.NticksValidator() self._validators["outlinecolor"] = v_colorbar.OutlinecolorValidator() self._validators["outlinewidth"] = v_colorbar.OutlinewidthValidator() self._validators["separatethousands"] = v_colorbar.SeparatethousandsValidator() self._validators["showexponent"] = v_colorbar.ShowexponentValidator() self._validators["showticklabels"] = v_colorbar.ShowticklabelsValidator() self._validators["showtickprefix"] = v_colorbar.ShowtickprefixValidator() self._validators["showticksuffix"] = v_colorbar.ShowticksuffixValidator() self._validators["thickness"] = v_colorbar.ThicknessValidator() self._validators["thicknessmode"] = v_colorbar.ThicknessmodeValidator() self._validators["tick0"] = v_colorbar.Tick0Validator() self._validators["tickangle"] = v_colorbar.TickangleValidator() self._validators["tickcolor"] = v_colorbar.TickcolorValidator() self._validators["tickfont"] = v_colorbar.TickfontValidator() self._validators["tickformat"] = v_colorbar.TickformatValidator() self._validators["tickformatstops"] = v_colorbar.TickformatstopsValidator() self._validators[ "tickformatstopdefaults" ] = v_colorbar.TickformatstopValidator() self._validators["ticklen"] = v_colorbar.TicklenValidator() self._validators["tickmode"] = v_colorbar.TickmodeValidator() self._validators["tickprefix"] = v_colorbar.TickprefixValidator() self._validators["ticks"] = v_colorbar.TicksValidator() self._validators["ticksuffix"] = v_colorbar.TicksuffixValidator() self._validators["ticktext"] = v_colorbar.TicktextValidator() self._validators["ticktextsrc"] = v_colorbar.TicktextsrcValidator() self._validators["tickvals"] = v_colorbar.TickvalsValidator() self._validators["tickvalssrc"] = v_colorbar.TickvalssrcValidator() self._validators["tickwidth"] = v_colorbar.TickwidthValidator() self._validators["title"] = v_colorbar.TitleValidator() self._validators["x"] = v_colorbar.XValidator() self._validators["xanchor"] = v_colorbar.XanchorValidator() self._validators["xpad"] = v_colorbar.XpadValidator() self._validators["y"] = v_colorbar.YValidator() self._validators["yanchor"] = v_colorbar.YanchorValidator() self._validators["ypad"] = v_colorbar.YpadValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("borderwidth", None) self["borderwidth"] = borderwidth if borderwidth is not None else _v _v = arg.pop("dtick", None) self["dtick"] = dtick if dtick is not None else _v _v = arg.pop("exponentformat", None) self["exponentformat"] = exponentformat if exponentformat is not None else _v _v = arg.pop("len", None) self["len"] = len if len is not None else _v _v = arg.pop("lenmode", None) self["lenmode"] = lenmode if lenmode is not None else _v _v = arg.pop("nticks", None) self["nticks"] = nticks if nticks is not None else _v _v = arg.pop("outlinecolor", None) self["outlinecolor"] = outlinecolor if outlinecolor is not None else _v _v = arg.pop("outlinewidth", None) self["outlinewidth"] = outlinewidth if outlinewidth is not None else _v _v = arg.pop("separatethousands", None) self["separatethousands"] = ( separatethousands if separatethousands is not None else _v ) _v = arg.pop("showexponent", None) self["showexponent"] = showexponent if showexponent is not None else _v _v = arg.pop("showticklabels", None) self["showticklabels"] = showticklabels if showticklabels is not None else _v _v = arg.pop("showtickprefix", None) self["showtickprefix"] = showtickprefix if showtickprefix is not None else _v _v = arg.pop("showticksuffix", None) self["showticksuffix"] = showticksuffix if showticksuffix is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("thicknessmode", None) self["thicknessmode"] = thicknessmode if thicknessmode is not None else _v _v = arg.pop("tick0", None) self["tick0"] = tick0 if tick0 is not None else _v _v = arg.pop("tickangle", None) self["tickangle"] = tickangle if tickangle is not None else _v _v = arg.pop("tickcolor", None) self["tickcolor"] = tickcolor if tickcolor is not None else _v _v = arg.pop("tickfont", None) self["tickfont"] = tickfont if tickfont is not None else _v _v = arg.pop("tickformat", None) self["tickformat"] = tickformat if tickformat is not None else _v _v = arg.pop("tickformatstops", None) self["tickformatstops"] = tickformatstops if tickformatstops is not None else _v _v = arg.pop("tickformatstopdefaults", None) self["tickformatstopdefaults"] = ( tickformatstopdefaults if tickformatstopdefaults is not None else _v ) _v = arg.pop("ticklen", None) self["ticklen"] = ticklen if ticklen is not None else _v _v = arg.pop("tickmode", None) self["tickmode"] = tickmode if tickmode is not None else _v _v = arg.pop("tickprefix", None) self["tickprefix"] = tickprefix if tickprefix is not None else _v _v = arg.pop("ticks", None) self["ticks"] = ticks if ticks is not None else _v _v = arg.pop("ticksuffix", None) self["ticksuffix"] = ticksuffix if ticksuffix is not None else _v _v = arg.pop("ticktext", None) self["ticktext"] = ticktext if ticktext is not None else _v _v = arg.pop("ticktextsrc", None) self["ticktextsrc"] = ticktextsrc if ticktextsrc is not None else _v _v = arg.pop("tickvals", None) self["tickvals"] = tickvals if tickvals is not None else _v _v = arg.pop("tickvalssrc", None) self["tickvalssrc"] = tickvalssrc if tickvalssrc is not None else _v _v = arg.pop("tickwidth", None) self["tickwidth"] = tickwidth if tickwidth is not None else _v _v = arg.pop("title", None) self["title"] = title if title is not None else _v _v = arg.pop("titlefont", None) _v = titlefont if titlefont is not None else _v if _v is not None: self["titlefont"] = _v _v = arg.pop("titleside", None) _v = titleside if titleside is not None else _v if _v is not None: self["titleside"] = _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xanchor", None) self["xanchor"] = xanchor if xanchor is not None else _v _v = arg.pop("xpad", None) self["xpad"] = xpad if xpad is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("yanchor", None) self["yanchor"] = yanchor if yanchor is not None else _v _v = arg.pop("ypad", None) self["ypad"] = ypad if ypad is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Caps(_BaseTraceHierarchyType): # x # - @property def x(self): """ The 'x' property is an instance of X that may be specified as: - An instance of plotly.graph_objs.isosurface.caps.X - A dict of string/value properties that will be passed to the X constructor Supported dict properties: fill Sets the fill ratio of the `caps`. The default fill value of the `caps` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. show Sets the fill ratio of the `slices`. The default fill value of the x `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. Returns ------- plotly.graph_objs.isosurface.caps.X """ return self["x"] @x.setter def x(self, val): self["x"] = val # y # - @property def y(self): """ The 'y' property is an instance of Y that may be specified as: - An instance of plotly.graph_objs.isosurface.caps.Y - A dict of string/value properties that will be passed to the Y constructor Supported dict properties: fill Sets the fill ratio of the `caps`. The default fill value of the `caps` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. show Sets the fill ratio of the `slices`. The default fill value of the y `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. Returns ------- plotly.graph_objs.isosurface.caps.Y """ return self["y"] @y.setter def y(self, val): self["y"] = val # z # - @property def z(self): """ The 'z' property is an instance of Z that may be specified as: - An instance of plotly.graph_objs.isosurface.caps.Z - A dict of string/value properties that will be passed to the Z constructor Supported dict properties: fill Sets the fill ratio of the `caps`. The default fill value of the `caps` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. show Sets the fill ratio of the `slices`. The default fill value of the z `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. Returns ------- plotly.graph_objs.isosurface.caps.Z """ return self["z"] @z.setter def z(self, val): self["z"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "isosurface" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ x plotly.graph_objects.isosurface.caps.X instance or dict with compatible properties y plotly.graph_objects.isosurface.caps.Y instance or dict with compatible properties z plotly.graph_objects.isosurface.caps.Z instance or dict with compatible properties """ def __init__(self, arg=None, x=None, y=None, z=None, **kwargs): """ Construct a new Caps object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.isosurface.Caps x plotly.graph_objects.isosurface.caps.X instance or dict with compatible properties y plotly.graph_objects.isosurface.caps.Y instance or dict with compatible properties z plotly.graph_objects.isosurface.caps.Z instance or dict with compatible properties Returns ------- Caps """ super(Caps, self).__init__("caps") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.isosurface.Caps constructor must be a dict or an instance of plotly.graph_objs.isosurface.Caps""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.isosurface import caps as v_caps # Initialize validators # --------------------- self._validators["x"] = v_caps.XValidator() self._validators["y"] = v_caps.YValidator() self._validators["z"] = v_caps.ZValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("z", None) self["z"] = z if z is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = [ "Caps", "ColorBar", "Contour", "Hoverlabel", "Lighting", "Lightposition", "Slices", "Spaceframe", "Stream", "Surface", "caps", "colorbar", "hoverlabel", "slices", ] from plotly.graph_objs.isosurface import slices from plotly.graph_objs.isosurface import hoverlabel from plotly.graph_objs.isosurface import colorbar from plotly.graph_objs.isosurface import caps plotly-4.4.1+dfsg.orig/plotly/graph_objs/mesh3d/0000755000175000017500000000000013573746613021114 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/mesh3d/hoverlabel/0000755000175000017500000000000013573746613023237 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/mesh3d/hoverlabel/__init__.py0000644000175000017500000002541713573721550025352 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "mesh3d.hoverlabel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Font object Sets the font used in hover labels. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.mesh3d.hoverlabel.Font color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.mesh3d.hoverlabel.Font constructor must be a dict or an instance of plotly.graph_objs.mesh3d.hoverlabel.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.mesh3d.hoverlabel import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["colorsrc"] = v_font.ColorsrcValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["familysrc"] = v_font.FamilysrcValidator() self._validators["size"] = v_font.SizeValidator() self._validators["sizesrc"] = v_font.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/mesh3d/colorbar/0000755000175000017500000000000013573746613022717 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/mesh3d/colorbar/title/0000755000175000017500000000000013573746613024040 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/mesh3d/colorbar/title/__init__.py0000644000175000017500000002052013573721550026141 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "mesh3d.colorbar.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.mesh3d.colorbar.title.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.mesh3d.colorbar.title.Font constructor must be a dict or an instance of plotly.graph_objs.mesh3d.colorbar.title.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.mesh3d.colorbar.title import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/mesh3d/colorbar/__init__.py0000644000175000017500000006046713573721550025036 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Title(_BaseTraceHierarchyType): # font # ---- @property def font(self): """ Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.mesh3d.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.mesh3d.colorbar.title.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # side # ---- @property def side(self): """ Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- Any """ return self["side"] @side.setter def side(self, val): self["side"] = val # text # ---- @property def text(self): """ Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "mesh3d.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """ def __init__(self, arg=None, font=None, side=None, text=None, **kwargs): """ Construct a new Title object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.mesh3d.colorbar.Title font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- Title """ super(Title, self).__init__("title") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.mesh3d.colorbar.Title constructor must be a dict or an instance of plotly.graph_objs.mesh3d.colorbar.Title""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.mesh3d.colorbar import title as v_title # Initialize validators # --------------------- self._validators["font"] = v_title.FontValidator() self._validators["side"] = v_title.SideValidator() self._validators["text"] = v_title.TextValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("side", None) self["side"] = side if side is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickformatstop(_BaseTraceHierarchyType): # dtickrange # ---------- @property def dtickrange(self): """ range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" The 'dtickrange' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'dtickrange[0]' property accepts values of any type (1) The 'dtickrange[1]' property accepts values of any type Returns ------- list """ return self["dtickrange"] @dtickrange.setter def dtickrange(self, val): self["dtickrange"] = val # enabled # ------- @property def enabled(self): """ Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. The 'enabled' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["enabled"] @enabled.setter def enabled(self, val): self["enabled"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # value # ----- @property def value(self): """ string - dtickformat for described zoom level, the same as "tickformat" The 'value' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "mesh3d.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """ def __init__( self, arg=None, dtickrange=None, enabled=None, name=None, templateitemname=None, value=None, **kwargs ): """ Construct a new Tickformatstop object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.mesh3d.colorbar.Tickformatstop dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- Tickformatstop """ super(Tickformatstop, self).__init__("tickformatstops") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.mesh3d.colorbar.Tickformatstop constructor must be a dict or an instance of plotly.graph_objs.mesh3d.colorbar.Tickformatstop""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.mesh3d.colorbar import tickformatstop as v_tickformatstop # Initialize validators # --------------------- self._validators["dtickrange"] = v_tickformatstop.DtickrangeValidator() self._validators["enabled"] = v_tickformatstop.EnabledValidator() self._validators["name"] = v_tickformatstop.NameValidator() self._validators[ "templateitemname" ] = v_tickformatstop.TemplateitemnameValidator() self._validators["value"] = v_tickformatstop.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtickrange", None) self["dtickrange"] = dtickrange if dtickrange is not None else _v _v = arg.pop("enabled", None) self["enabled"] = enabled if enabled is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "mesh3d.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Tickfont object Sets the color bar's tick label font Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.mesh3d.colorbar.Tickfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Tickfont """ super(Tickfont, self).__init__("tickfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.mesh3d.colorbar.Tickfont constructor must be a dict or an instance of plotly.graph_objs.mesh3d.colorbar.Tickfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.mesh3d.colorbar import tickfont as v_tickfont # Initialize validators # --------------------- self._validators["color"] = v_tickfont.ColorValidator() self._validators["family"] = v_tickfont.FamilyValidator() self._validators["size"] = v_tickfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Tickfont", "Tickformatstop", "Tickformatstop", "Title", "title"] from plotly.graph_objs.mesh3d.colorbar import title plotly-4.4.1+dfsg.orig/plotly/graph_objs/mesh3d/__init__.py0000644000175000017500000033066213573721552023232 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Stream(_BaseTraceHierarchyType): # maxpoints # --------- @property def maxpoints(self): """ Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. The 'maxpoints' property is a number and may be specified as: - An int or float in the interval [0, 10000] Returns ------- int|float """ return self["maxpoints"] @maxpoints.setter def maxpoints(self, val): self["maxpoints"] = val # token # ----- @property def token(self): """ The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. The 'token' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["token"] @token.setter def token(self, val): self["token"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "mesh3d" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """ def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): """ Construct a new Stream object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.mesh3d.Stream maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- Stream """ super(Stream, self).__init__("stream") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.mesh3d.Stream constructor must be a dict or an instance of plotly.graph_objs.mesh3d.Stream""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.mesh3d import stream as v_stream # Initialize validators # --------------------- self._validators["maxpoints"] = v_stream.MaxpointsValidator() self._validators["token"] = v_stream.TokenValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("maxpoints", None) self["maxpoints"] = maxpoints if maxpoints is not None else _v _v = arg.pop("token", None) self["token"] = token if token is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Lightposition(_BaseTraceHierarchyType): # x # - @property def x(self): """ Numeric vector, representing the X coordinate for each vertex. The 'x' property is a number and may be specified as: - An int or float in the interval [-100000, 100000] Returns ------- int|float """ return self["x"] @x.setter def x(self, val): self["x"] = val # y # - @property def y(self): """ Numeric vector, representing the Y coordinate for each vertex. The 'y' property is a number and may be specified as: - An int or float in the interval [-100000, 100000] Returns ------- int|float """ return self["y"] @y.setter def y(self, val): self["y"] = val # z # - @property def z(self): """ Numeric vector, representing the Z coordinate for each vertex. The 'z' property is a number and may be specified as: - An int or float in the interval [-100000, 100000] Returns ------- int|float """ return self["z"] @z.setter def z(self, val): self["z"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "mesh3d" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ x Numeric vector, representing the X coordinate for each vertex. y Numeric vector, representing the Y coordinate for each vertex. z Numeric vector, representing the Z coordinate for each vertex. """ def __init__(self, arg=None, x=None, y=None, z=None, **kwargs): """ Construct a new Lightposition object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.mesh3d.Lightposition x Numeric vector, representing the X coordinate for each vertex. y Numeric vector, representing the Y coordinate for each vertex. z Numeric vector, representing the Z coordinate for each vertex. Returns ------- Lightposition """ super(Lightposition, self).__init__("lightposition") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.mesh3d.Lightposition constructor must be a dict or an instance of plotly.graph_objs.mesh3d.Lightposition""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.mesh3d import lightposition as v_lightposition # Initialize validators # --------------------- self._validators["x"] = v_lightposition.XValidator() self._validators["y"] = v_lightposition.YValidator() self._validators["z"] = v_lightposition.ZValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("z", None) self["z"] = z if z is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Lighting(_BaseTraceHierarchyType): # ambient # ------- @property def ambient(self): """ Ambient light increases overall color visibility but can wash out the image. The 'ambient' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["ambient"] @ambient.setter def ambient(self, val): self["ambient"] = val # diffuse # ------- @property def diffuse(self): """ Represents the extent that incident rays are reflected in a range of angles. The 'diffuse' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["diffuse"] @diffuse.setter def diffuse(self, val): self["diffuse"] = val # facenormalsepsilon # ------------------ @property def facenormalsepsilon(self): """ Epsilon for face normals calculation avoids math issues arising from degenerate geometry. The 'facenormalsepsilon' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["facenormalsepsilon"] @facenormalsepsilon.setter def facenormalsepsilon(self, val): self["facenormalsepsilon"] = val # fresnel # ------- @property def fresnel(self): """ Represents the reflectance as a dependency of the viewing angle; e.g. paper is reflective when viewing it from the edge of the paper (almost 90 degrees), causing shine. The 'fresnel' property is a number and may be specified as: - An int or float in the interval [0, 5] Returns ------- int|float """ return self["fresnel"] @fresnel.setter def fresnel(self, val): self["fresnel"] = val # roughness # --------- @property def roughness(self): """ Alters specular reflection; the rougher the surface, the wider and less contrasty the shine. The 'roughness' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["roughness"] @roughness.setter def roughness(self, val): self["roughness"] = val # specular # -------- @property def specular(self): """ Represents the level that incident rays are reflected in a single direction, causing shine. The 'specular' property is a number and may be specified as: - An int or float in the interval [0, 2] Returns ------- int|float """ return self["specular"] @specular.setter def specular(self, val): self["specular"] = val # vertexnormalsepsilon # -------------------- @property def vertexnormalsepsilon(self): """ Epsilon for vertex normals calculation avoids math issues arising from degenerate geometry. The 'vertexnormalsepsilon' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["vertexnormalsepsilon"] @vertexnormalsepsilon.setter def vertexnormalsepsilon(self, val): self["vertexnormalsepsilon"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "mesh3d" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ ambient Ambient light increases overall color visibility but can wash out the image. diffuse Represents the extent that incident rays are reflected in a range of angles. facenormalsepsilon Epsilon for face normals calculation avoids math issues arising from degenerate geometry. fresnel Represents the reflectance as a dependency of the viewing angle; e.g. paper is reflective when viewing it from the edge of the paper (almost 90 degrees), causing shine. roughness Alters specular reflection; the rougher the surface, the wider and less contrasty the shine. specular Represents the level that incident rays are reflected in a single direction, causing shine. vertexnormalsepsilon Epsilon for vertex normals calculation avoids math issues arising from degenerate geometry. """ def __init__( self, arg=None, ambient=None, diffuse=None, facenormalsepsilon=None, fresnel=None, roughness=None, specular=None, vertexnormalsepsilon=None, **kwargs ): """ Construct a new Lighting object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.mesh3d.Lighting ambient Ambient light increases overall color visibility but can wash out the image. diffuse Represents the extent that incident rays are reflected in a range of angles. facenormalsepsilon Epsilon for face normals calculation avoids math issues arising from degenerate geometry. fresnel Represents the reflectance as a dependency of the viewing angle; e.g. paper is reflective when viewing it from the edge of the paper (almost 90 degrees), causing shine. roughness Alters specular reflection; the rougher the surface, the wider and less contrasty the shine. specular Represents the level that incident rays are reflected in a single direction, causing shine. vertexnormalsepsilon Epsilon for vertex normals calculation avoids math issues arising from degenerate geometry. Returns ------- Lighting """ super(Lighting, self).__init__("lighting") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.mesh3d.Lighting constructor must be a dict or an instance of plotly.graph_objs.mesh3d.Lighting""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.mesh3d import lighting as v_lighting # Initialize validators # --------------------- self._validators["ambient"] = v_lighting.AmbientValidator() self._validators["diffuse"] = v_lighting.DiffuseValidator() self._validators[ "facenormalsepsilon" ] = v_lighting.FacenormalsepsilonValidator() self._validators["fresnel"] = v_lighting.FresnelValidator() self._validators["roughness"] = v_lighting.RoughnessValidator() self._validators["specular"] = v_lighting.SpecularValidator() self._validators[ "vertexnormalsepsilon" ] = v_lighting.VertexnormalsepsilonValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("ambient", None) self["ambient"] = ambient if ambient is not None else _v _v = arg.pop("diffuse", None) self["diffuse"] = diffuse if diffuse is not None else _v _v = arg.pop("facenormalsepsilon", None) self["facenormalsepsilon"] = ( facenormalsepsilon if facenormalsepsilon is not None else _v ) _v = arg.pop("fresnel", None) self["fresnel"] = fresnel if fresnel is not None else _v _v = arg.pop("roughness", None) self["roughness"] = roughness if roughness is not None else _v _v = arg.pop("specular", None) self["specular"] = specular if specular is not None else _v _v = arg.pop("vertexnormalsepsilon", None) self["vertexnormalsepsilon"] = ( vertexnormalsepsilon if vertexnormalsepsilon is not None else _v ) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Hoverlabel(_BaseTraceHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'right', 'auto'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["align"] @align.setter def align(self, val): self["align"] = val # alignsrc # -------- @property def alignsrc(self): """ Sets the source reference on plot.ly for align . The 'alignsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["alignsrc"] @alignsrc.setter def alignsrc(self, val): self["alignsrc"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the hover labels for this trace The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bgcolorsrc # ---------- @property def bgcolorsrc(self): """ Sets the source reference on plot.ly for bgcolor . The 'bgcolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bgcolorsrc"] @bgcolorsrc.setter def bgcolorsrc(self, val): self["bgcolorsrc"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the border color of the hover labels for this trace. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # bordercolorsrc # -------------- @property def bordercolorsrc(self): """ Sets the source reference on plot.ly for bordercolor . The 'bordercolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bordercolorsrc"] @bordercolorsrc.setter def bordercolorsrc(self, val): self["bordercolorsrc"] = val # font # ---- @property def font(self): """ Sets the font used in hover labels. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.mesh3d.hoverlabel.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.mesh3d.hoverlabel.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # namelength # ---------- @property def namelength(self): """ Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. The 'namelength' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [-1, 9223372036854775807] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|numpy.ndarray """ return self["namelength"] @namelength.setter def namelength(self, val): self["namelength"] = val # namelengthsrc # ------------- @property def namelengthsrc(self): """ Sets the source reference on plot.ly for namelength . The 'namelengthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["namelengthsrc"] @namelengthsrc.setter def namelengthsrc(self, val): self["namelengthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "mesh3d" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """ def __init__( self, arg=None, align=None, alignsrc=None, bgcolor=None, bgcolorsrc=None, bordercolor=None, bordercolorsrc=None, font=None, namelength=None, namelengthsrc=None, **kwargs ): """ Construct a new Hoverlabel object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.mesh3d.Hoverlabel align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- Hoverlabel """ super(Hoverlabel, self).__init__("hoverlabel") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.mesh3d.Hoverlabel constructor must be a dict or an instance of plotly.graph_objs.mesh3d.Hoverlabel""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.mesh3d import hoverlabel as v_hoverlabel # Initialize validators # --------------------- self._validators["align"] = v_hoverlabel.AlignValidator() self._validators["alignsrc"] = v_hoverlabel.AlignsrcValidator() self._validators["bgcolor"] = v_hoverlabel.BgcolorValidator() self._validators["bgcolorsrc"] = v_hoverlabel.BgcolorsrcValidator() self._validators["bordercolor"] = v_hoverlabel.BordercolorValidator() self._validators["bordercolorsrc"] = v_hoverlabel.BordercolorsrcValidator() self._validators["font"] = v_hoverlabel.FontValidator() self._validators["namelength"] = v_hoverlabel.NamelengthValidator() self._validators["namelengthsrc"] = v_hoverlabel.NamelengthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("alignsrc", None) self["alignsrc"] = alignsrc if alignsrc is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bgcolorsrc", None) self["bgcolorsrc"] = bgcolorsrc if bgcolorsrc is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("bordercolorsrc", None) self["bordercolorsrc"] = bordercolorsrc if bordercolorsrc is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("namelength", None) self["namelength"] = namelength if namelength is not None else _v _v = arg.pop("namelengthsrc", None) self["namelengthsrc"] = namelengthsrc if namelengthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Contour(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the color of the contour lines. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # show # ---- @property def show(self): """ Sets whether or not dynamic contours are shown on hover The 'show' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["show"] @show.setter def show(self, val): self["show"] = val # width # ----- @property def width(self): """ Sets the width of the contour lines. The 'width' property is a number and may be specified as: - An int or float in the interval [1, 16] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "mesh3d" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the color of the contour lines. show Sets whether or not dynamic contours are shown on hover width Sets the width of the contour lines. """ def __init__(self, arg=None, color=None, show=None, width=None, **kwargs): """ Construct a new Contour object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.mesh3d.Contour color Sets the color of the contour lines. show Sets whether or not dynamic contours are shown on hover width Sets the width of the contour lines. Returns ------- Contour """ super(Contour, self).__init__("contour") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.mesh3d.Contour constructor must be a dict or an instance of plotly.graph_objs.mesh3d.Contour""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.mesh3d import contour as v_contour # Initialize validators # --------------------- self._validators["color"] = v_contour.ColorValidator() self._validators["show"] = v_contour.ShowValidator() self._validators["width"] = v_contour.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("show", None) self["show"] = show if show is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class ColorBar(_BaseTraceHierarchyType): # bgcolor # ------- @property def bgcolor(self): """ Sets the color of padded area. The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the axis line color. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # borderwidth # ----------- @property def borderwidth(self): """ Sets the width (in px) or the border enclosing this color bar. The 'borderwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["borderwidth"] @borderwidth.setter def borderwidth(self, val): self["borderwidth"] = val # dtick # ----- @property def dtick(self): """ Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" The 'dtick' property accepts values of any type Returns ------- Any """ return self["dtick"] @dtick.setter def dtick(self, val): self["dtick"] = val # exponentformat # -------------- @property def exponentformat(self): """ Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. The 'exponentformat' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'e', 'E', 'power', 'SI', 'B'] Returns ------- Any """ return self["exponentformat"] @exponentformat.setter def exponentformat(self, val): self["exponentformat"] = val # len # --- @property def len(self): """ Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. The 'len' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["len"] @len.setter def len(self, val): self["len"] = val # lenmode # ------- @property def lenmode(self): """ Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. The 'lenmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["lenmode"] @lenmode.setter def lenmode(self, val): self["lenmode"] = val # nticks # ------ @property def nticks(self): """ Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". The 'nticks' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nticks"] @nticks.setter def nticks(self, val): self["nticks"] = val # outlinecolor # ------------ @property def outlinecolor(self): """ Sets the axis line color. The 'outlinecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["outlinecolor"] @outlinecolor.setter def outlinecolor(self, val): self["outlinecolor"] = val # outlinewidth # ------------ @property def outlinewidth(self): """ Sets the width (in px) of the axis line. The 'outlinewidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["outlinewidth"] @outlinewidth.setter def outlinewidth(self, val): self["outlinewidth"] = val # separatethousands # ----------------- @property def separatethousands(self): """ If "true", even 4-digit integers are separated The 'separatethousands' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["separatethousands"] @separatethousands.setter def separatethousands(self, val): self["separatethousands"] = val # showexponent # ------------ @property def showexponent(self): """ If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. The 'showexponent' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showexponent"] @showexponent.setter def showexponent(self, val): self["showexponent"] = val # showticklabels # -------------- @property def showticklabels(self): """ Determines whether or not the tick labels are drawn. The 'showticklabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showticklabels"] @showticklabels.setter def showticklabels(self, val): self["showticklabels"] = val # showtickprefix # -------------- @property def showtickprefix(self): """ If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. The 'showtickprefix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showtickprefix"] @showtickprefix.setter def showtickprefix(self, val): self["showtickprefix"] = val # showticksuffix # -------------- @property def showticksuffix(self): """ Same as `showtickprefix` but for tick suffixes. The 'showticksuffix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showticksuffix"] @showticksuffix.setter def showticksuffix(self, val): self["showticksuffix"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # thicknessmode # ------------- @property def thicknessmode(self): """ Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. The 'thicknessmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["thicknessmode"] @thicknessmode.setter def thicknessmode(self, val): self["thicknessmode"] = val # tick0 # ----- @property def tick0(self): """ Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. The 'tick0' property accepts values of any type Returns ------- Any """ return self["tick0"] @tick0.setter def tick0(self, val): self["tick0"] = val # tickangle # --------- @property def tickangle(self): """ Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. The 'tickangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["tickangle"] @tickangle.setter def tickangle(self, val): self["tickangle"] = val # tickcolor # --------- @property def tickcolor(self): """ Sets the tick color. The 'tickcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["tickcolor"] @tickcolor.setter def tickcolor(self, val): self["tickcolor"] = val # tickfont # -------- @property def tickfont(self): """ Sets the color bar's tick label font The 'tickfont' property is an instance of Tickfont that may be specified as: - An instance of plotly.graph_objs.mesh3d.colorbar.Tickfont - A dict of string/value properties that will be passed to the Tickfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.mesh3d.colorbar.Tickfont """ return self["tickfont"] @tickfont.setter def tickfont(self, val): self["tickfont"] = val # tickformat # ---------- @property def tickformat(self): """ Sets the tick label formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'tickformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickformat"] @tickformat.setter def tickformat(self, val): self["tickformat"] = val # tickformatstops # --------------- @property def tickformatstops(self): """ The 'tickformatstops' property is a tuple of instances of Tickformatstop that may be specified as: - A list or tuple of instances of plotly.graph_objs.mesh3d.colorbar.Tickformatstop - A list or tuple of dicts of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- tuple[plotly.graph_objs.mesh3d.colorbar.Tickformatstop] """ return self["tickformatstops"] @tickformatstops.setter def tickformatstops(self, val): self["tickformatstops"] = val # tickformatstopdefaults # ---------------------- @property def tickformatstopdefaults(self): """ When used in a template (as layout.template.data.mesh3d.colorbar.tickformatstopdefaults), sets the default property values to use for elements of mesh3d.colorbar.tickformatstops The 'tickformatstopdefaults' property is an instance of Tickformatstop that may be specified as: - An instance of plotly.graph_objs.mesh3d.colorbar.Tickformatstop - A dict of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: Returns ------- plotly.graph_objs.mesh3d.colorbar.Tickformatstop """ return self["tickformatstopdefaults"] @tickformatstopdefaults.setter def tickformatstopdefaults(self, val): self["tickformatstopdefaults"] = val # ticklen # ------- @property def ticklen(self): """ Sets the tick length (in px). The 'ticklen' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ticklen"] @ticklen.setter def ticklen(self, val): self["ticklen"] = val # tickmode # -------- @property def tickmode(self): """ Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). The 'tickmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'linear', 'array'] Returns ------- Any """ return self["tickmode"] @tickmode.setter def tickmode(self, val): self["tickmode"] = val # tickprefix # ---------- @property def tickprefix(self): """ Sets a tick label prefix. The 'tickprefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickprefix"] @tickprefix.setter def tickprefix(self, val): self["tickprefix"] = val # ticks # ----- @property def ticks(self): """ Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. The 'ticks' property is an enumeration that may be specified as: - One of the following enumeration values: ['outside', 'inside', ''] Returns ------- Any """ return self["ticks"] @ticks.setter def ticks(self, val): self["ticks"] = val # ticksuffix # ---------- @property def ticksuffix(self): """ Sets a tick label suffix. The 'ticksuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ticksuffix"] @ticksuffix.setter def ticksuffix(self, val): self["ticksuffix"] = val # ticktext # -------- @property def ticktext(self): """ Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. The 'ticktext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ticktext"] @ticktext.setter def ticktext(self, val): self["ticktext"] = val # ticktextsrc # ----------- @property def ticktextsrc(self): """ Sets the source reference on plot.ly for ticktext . The 'ticktextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ticktextsrc"] @ticktextsrc.setter def ticktextsrc(self, val): self["ticktextsrc"] = val # tickvals # -------- @property def tickvals(self): """ Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. The 'tickvals' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["tickvals"] @tickvals.setter def tickvals(self, val): self["tickvals"] = val # tickvalssrc # ----------- @property def tickvalssrc(self): """ Sets the source reference on plot.ly for tickvals . The 'tickvalssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tickvalssrc"] @tickvalssrc.setter def tickvalssrc(self, val): self["tickvalssrc"] = val # tickwidth # --------- @property def tickwidth(self): """ Sets the tick width (in px). The 'tickwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["tickwidth"] @tickwidth.setter def tickwidth(self, val): self["tickwidth"] = val # title # ----- @property def title(self): """ The 'title' property is an instance of Title that may be specified as: - An instance of plotly.graph_objs.mesh3d.colorbar.Title - A dict of string/value properties that will be passed to the Title constructor Supported dict properties: font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- plotly.graph_objs.mesh3d.colorbar.Title """ return self["title"] @title.setter def title(self, val): self["title"] = val # titlefont # --------- @property def titlefont(self): """ Deprecated: Please use mesh3d.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.mesh3d.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- """ return self["titlefont"] @titlefont.setter def titlefont(self, val): self["titlefont"] = val # titleside # --------- @property def titleside(self): """ Deprecated: Please use mesh3d.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- """ return self["titleside"] @titleside.setter def titleside(self, val): self["titleside"] = val # x # - @property def x(self): """ Sets the x position of the color bar (in plot fraction). The 'x' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["x"] @x.setter def x(self, val): self["x"] = val # xanchor # ------- @property def xanchor(self): """ Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. The 'xanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'center', 'right'] Returns ------- Any """ return self["xanchor"] @xanchor.setter def xanchor(self, val): self["xanchor"] = val # xpad # ---- @property def xpad(self): """ Sets the amount of padding (in px) along the x direction. The 'xpad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["xpad"] @xpad.setter def xpad(self, val): self["xpad"] = val # y # - @property def y(self): """ Sets the y position of the color bar (in plot fraction). The 'y' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["y"] @y.setter def y(self, val): self["y"] = val # yanchor # ------- @property def yanchor(self): """ Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. The 'yanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['top', 'middle', 'bottom'] Returns ------- Any """ return self["yanchor"] @yanchor.setter def yanchor(self, val): self["yanchor"] = val # ypad # ---- @property def ypad(self): """ Sets the amount of padding (in px) along the y direction. The 'ypad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ypad"] @ypad.setter def ypad(self, val): self["ypad"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "mesh3d" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.mesh3d.colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.mesh3d .colorbar.tickformatstopdefaults), sets the default property values to use for elements of mesh3d.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.mesh3d.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use mesh3d.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use mesh3d.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """ _mapped_properties = { "titlefont": ("title", "font"), "titleside": ("title", "side"), } def __init__( self, arg=None, bgcolor=None, bordercolor=None, borderwidth=None, dtick=None, exponentformat=None, len=None, lenmode=None, nticks=None, outlinecolor=None, outlinewidth=None, separatethousands=None, showexponent=None, showticklabels=None, showtickprefix=None, showticksuffix=None, thickness=None, thicknessmode=None, tick0=None, tickangle=None, tickcolor=None, tickfont=None, tickformat=None, tickformatstops=None, tickformatstopdefaults=None, ticklen=None, tickmode=None, tickprefix=None, ticks=None, ticksuffix=None, ticktext=None, ticktextsrc=None, tickvals=None, tickvalssrc=None, tickwidth=None, title=None, titlefont=None, titleside=None, x=None, xanchor=None, xpad=None, y=None, yanchor=None, ypad=None, **kwargs ): """ Construct a new ColorBar object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.mesh3d.ColorBar bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.mesh3d.colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.mesh3d .colorbar.tickformatstopdefaults), sets the default property values to use for elements of mesh3d.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.mesh3d.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use mesh3d.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use mesh3d.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- ColorBar """ super(ColorBar, self).__init__("colorbar") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.mesh3d.ColorBar constructor must be a dict or an instance of plotly.graph_objs.mesh3d.ColorBar""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.mesh3d import colorbar as v_colorbar # Initialize validators # --------------------- self._validators["bgcolor"] = v_colorbar.BgcolorValidator() self._validators["bordercolor"] = v_colorbar.BordercolorValidator() self._validators["borderwidth"] = v_colorbar.BorderwidthValidator() self._validators["dtick"] = v_colorbar.DtickValidator() self._validators["exponentformat"] = v_colorbar.ExponentformatValidator() self._validators["len"] = v_colorbar.LenValidator() self._validators["lenmode"] = v_colorbar.LenmodeValidator() self._validators["nticks"] = v_colorbar.NticksValidator() self._validators["outlinecolor"] = v_colorbar.OutlinecolorValidator() self._validators["outlinewidth"] = v_colorbar.OutlinewidthValidator() self._validators["separatethousands"] = v_colorbar.SeparatethousandsValidator() self._validators["showexponent"] = v_colorbar.ShowexponentValidator() self._validators["showticklabels"] = v_colorbar.ShowticklabelsValidator() self._validators["showtickprefix"] = v_colorbar.ShowtickprefixValidator() self._validators["showticksuffix"] = v_colorbar.ShowticksuffixValidator() self._validators["thickness"] = v_colorbar.ThicknessValidator() self._validators["thicknessmode"] = v_colorbar.ThicknessmodeValidator() self._validators["tick0"] = v_colorbar.Tick0Validator() self._validators["tickangle"] = v_colorbar.TickangleValidator() self._validators["tickcolor"] = v_colorbar.TickcolorValidator() self._validators["tickfont"] = v_colorbar.TickfontValidator() self._validators["tickformat"] = v_colorbar.TickformatValidator() self._validators["tickformatstops"] = v_colorbar.TickformatstopsValidator() self._validators[ "tickformatstopdefaults" ] = v_colorbar.TickformatstopValidator() self._validators["ticklen"] = v_colorbar.TicklenValidator() self._validators["tickmode"] = v_colorbar.TickmodeValidator() self._validators["tickprefix"] = v_colorbar.TickprefixValidator() self._validators["ticks"] = v_colorbar.TicksValidator() self._validators["ticksuffix"] = v_colorbar.TicksuffixValidator() self._validators["ticktext"] = v_colorbar.TicktextValidator() self._validators["ticktextsrc"] = v_colorbar.TicktextsrcValidator() self._validators["tickvals"] = v_colorbar.TickvalsValidator() self._validators["tickvalssrc"] = v_colorbar.TickvalssrcValidator() self._validators["tickwidth"] = v_colorbar.TickwidthValidator() self._validators["title"] = v_colorbar.TitleValidator() self._validators["x"] = v_colorbar.XValidator() self._validators["xanchor"] = v_colorbar.XanchorValidator() self._validators["xpad"] = v_colorbar.XpadValidator() self._validators["y"] = v_colorbar.YValidator() self._validators["yanchor"] = v_colorbar.YanchorValidator() self._validators["ypad"] = v_colorbar.YpadValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("borderwidth", None) self["borderwidth"] = borderwidth if borderwidth is not None else _v _v = arg.pop("dtick", None) self["dtick"] = dtick if dtick is not None else _v _v = arg.pop("exponentformat", None) self["exponentformat"] = exponentformat if exponentformat is not None else _v _v = arg.pop("len", None) self["len"] = len if len is not None else _v _v = arg.pop("lenmode", None) self["lenmode"] = lenmode if lenmode is not None else _v _v = arg.pop("nticks", None) self["nticks"] = nticks if nticks is not None else _v _v = arg.pop("outlinecolor", None) self["outlinecolor"] = outlinecolor if outlinecolor is not None else _v _v = arg.pop("outlinewidth", None) self["outlinewidth"] = outlinewidth if outlinewidth is not None else _v _v = arg.pop("separatethousands", None) self["separatethousands"] = ( separatethousands if separatethousands is not None else _v ) _v = arg.pop("showexponent", None) self["showexponent"] = showexponent if showexponent is not None else _v _v = arg.pop("showticklabels", None) self["showticklabels"] = showticklabels if showticklabels is not None else _v _v = arg.pop("showtickprefix", None) self["showtickprefix"] = showtickprefix if showtickprefix is not None else _v _v = arg.pop("showticksuffix", None) self["showticksuffix"] = showticksuffix if showticksuffix is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("thicknessmode", None) self["thicknessmode"] = thicknessmode if thicknessmode is not None else _v _v = arg.pop("tick0", None) self["tick0"] = tick0 if tick0 is not None else _v _v = arg.pop("tickangle", None) self["tickangle"] = tickangle if tickangle is not None else _v _v = arg.pop("tickcolor", None) self["tickcolor"] = tickcolor if tickcolor is not None else _v _v = arg.pop("tickfont", None) self["tickfont"] = tickfont if tickfont is not None else _v _v = arg.pop("tickformat", None) self["tickformat"] = tickformat if tickformat is not None else _v _v = arg.pop("tickformatstops", None) self["tickformatstops"] = tickformatstops if tickformatstops is not None else _v _v = arg.pop("tickformatstopdefaults", None) self["tickformatstopdefaults"] = ( tickformatstopdefaults if tickformatstopdefaults is not None else _v ) _v = arg.pop("ticklen", None) self["ticklen"] = ticklen if ticklen is not None else _v _v = arg.pop("tickmode", None) self["tickmode"] = tickmode if tickmode is not None else _v _v = arg.pop("tickprefix", None) self["tickprefix"] = tickprefix if tickprefix is not None else _v _v = arg.pop("ticks", None) self["ticks"] = ticks if ticks is not None else _v _v = arg.pop("ticksuffix", None) self["ticksuffix"] = ticksuffix if ticksuffix is not None else _v _v = arg.pop("ticktext", None) self["ticktext"] = ticktext if ticktext is not None else _v _v = arg.pop("ticktextsrc", None) self["ticktextsrc"] = ticktextsrc if ticktextsrc is not None else _v _v = arg.pop("tickvals", None) self["tickvals"] = tickvals if tickvals is not None else _v _v = arg.pop("tickvalssrc", None) self["tickvalssrc"] = tickvalssrc if tickvalssrc is not None else _v _v = arg.pop("tickwidth", None) self["tickwidth"] = tickwidth if tickwidth is not None else _v _v = arg.pop("title", None) self["title"] = title if title is not None else _v _v = arg.pop("titlefont", None) _v = titlefont if titlefont is not None else _v if _v is not None: self["titlefont"] = _v _v = arg.pop("titleside", None) _v = titleside if titleside is not None else _v if _v is not None: self["titleside"] = _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xanchor", None) self["xanchor"] = xanchor if xanchor is not None else _v _v = arg.pop("xpad", None) self["xpad"] = xpad if xpad is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("yanchor", None) self["yanchor"] = yanchor if yanchor is not None else _v _v = arg.pop("ypad", None) self["ypad"] = ypad if ypad is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = [ "ColorBar", "Contour", "Hoverlabel", "Lighting", "Lightposition", "Stream", "colorbar", "hoverlabel", ] from plotly.graph_objs.mesh3d import hoverlabel from plotly.graph_objs.mesh3d import colorbar plotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/0000755000175000017500000000000013573746613021246 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/template/0000755000175000017500000000000013573746613023061 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/template/__init__.py0000644000175000017500000015371213573721550025174 0ustar noahfxnoahfxfrom plotly.graph_objs import Layout from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Data(_BaseLayoutHierarchyType): # area # ---- @property def area(self): """ The 'area' property is a tuple of instances of Area that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.template.data.Area - A list or tuple of dicts of string/value properties that will be passed to the Area constructor Supported dict properties: Returns ------- tuple[plotly.graph_objs.layout.template.data.Area] """ return self["area"] @area.setter def area(self, val): self["area"] = val # barpolar # -------- @property def barpolar(self): """ The 'barpolar' property is a tuple of instances of Barpolar that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.template.data.Barpolar - A list or tuple of dicts of string/value properties that will be passed to the Barpolar constructor Supported dict properties: Returns ------- tuple[plotly.graph_objs.layout.template.data.Barpolar] """ return self["barpolar"] @barpolar.setter def barpolar(self, val): self["barpolar"] = val # bar # --- @property def bar(self): """ The 'bar' property is a tuple of instances of Bar that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.template.data.Bar - A list or tuple of dicts of string/value properties that will be passed to the Bar constructor Supported dict properties: Returns ------- tuple[plotly.graph_objs.layout.template.data.Bar] """ return self["bar"] @bar.setter def bar(self, val): self["bar"] = val # box # --- @property def box(self): """ The 'box' property is a tuple of instances of Box that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.template.data.Box - A list or tuple of dicts of string/value properties that will be passed to the Box constructor Supported dict properties: Returns ------- tuple[plotly.graph_objs.layout.template.data.Box] """ return self["box"] @box.setter def box(self, val): self["box"] = val # candlestick # ----------- @property def candlestick(self): """ The 'candlestick' property is a tuple of instances of Candlestick that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.template.data.Candlestick - A list or tuple of dicts of string/value properties that will be passed to the Candlestick constructor Supported dict properties: Returns ------- tuple[plotly.graph_objs.layout.template.data.Candlestick] """ return self["candlestick"] @candlestick.setter def candlestick(self, val): self["candlestick"] = val # carpet # ------ @property def carpet(self): """ The 'carpet' property is a tuple of instances of Carpet that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.template.data.Carpet - A list or tuple of dicts of string/value properties that will be passed to the Carpet constructor Supported dict properties: Returns ------- tuple[plotly.graph_objs.layout.template.data.Carpet] """ return self["carpet"] @carpet.setter def carpet(self, val): self["carpet"] = val # choroplethmapbox # ---------------- @property def choroplethmapbox(self): """ The 'choroplethmapbox' property is a tuple of instances of Choroplethmapbox that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.template.data.Choroplethmapbox - A list or tuple of dicts of string/value properties that will be passed to the Choroplethmapbox constructor Supported dict properties: Returns ------- tuple[plotly.graph_objs.layout.template.data.Choroplethmapbox] """ return self["choroplethmapbox"] @choroplethmapbox.setter def choroplethmapbox(self, val): self["choroplethmapbox"] = val # choropleth # ---------- @property def choropleth(self): """ The 'choropleth' property is a tuple of instances of Choropleth that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.template.data.Choropleth - A list or tuple of dicts of string/value properties that will be passed to the Choropleth constructor Supported dict properties: Returns ------- tuple[plotly.graph_objs.layout.template.data.Choropleth] """ return self["choropleth"] @choropleth.setter def choropleth(self, val): self["choropleth"] = val # cone # ---- @property def cone(self): """ The 'cone' property is a tuple of instances of Cone that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.template.data.Cone - A list or tuple of dicts of string/value properties that will be passed to the Cone constructor Supported dict properties: Returns ------- tuple[plotly.graph_objs.layout.template.data.Cone] """ return self["cone"] @cone.setter def cone(self, val): self["cone"] = val # contourcarpet # ------------- @property def contourcarpet(self): """ The 'contourcarpet' property is a tuple of instances of Contourcarpet that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.template.data.Contourcarpet - A list or tuple of dicts of string/value properties that will be passed to the Contourcarpet constructor Supported dict properties: Returns ------- tuple[plotly.graph_objs.layout.template.data.Contourcarpet] """ return self["contourcarpet"] @contourcarpet.setter def contourcarpet(self, val): self["contourcarpet"] = val # contour # ------- @property def contour(self): """ The 'contour' property is a tuple of instances of Contour that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.template.data.Contour - A list or tuple of dicts of string/value properties that will be passed to the Contour constructor Supported dict properties: Returns ------- tuple[plotly.graph_objs.layout.template.data.Contour] """ return self["contour"] @contour.setter def contour(self, val): self["contour"] = val # densitymapbox # ------------- @property def densitymapbox(self): """ The 'densitymapbox' property is a tuple of instances of Densitymapbox that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.template.data.Densitymapbox - A list or tuple of dicts of string/value properties that will be passed to the Densitymapbox constructor Supported dict properties: Returns ------- tuple[plotly.graph_objs.layout.template.data.Densitymapbox] """ return self["densitymapbox"] @densitymapbox.setter def densitymapbox(self, val): self["densitymapbox"] = val # funnelarea # ---------- @property def funnelarea(self): """ The 'funnelarea' property is a tuple of instances of Funnelarea that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.template.data.Funnelarea - A list or tuple of dicts of string/value properties that will be passed to the Funnelarea constructor Supported dict properties: Returns ------- tuple[plotly.graph_objs.layout.template.data.Funnelarea] """ return self["funnelarea"] @funnelarea.setter def funnelarea(self, val): self["funnelarea"] = val # funnel # ------ @property def funnel(self): """ The 'funnel' property is a tuple of instances of Funnel that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.template.data.Funnel - A list or tuple of dicts of string/value properties that will be passed to the Funnel constructor Supported dict properties: Returns ------- tuple[plotly.graph_objs.layout.template.data.Funnel] """ return self["funnel"] @funnel.setter def funnel(self, val): self["funnel"] = val # heatmapgl # --------- @property def heatmapgl(self): """ The 'heatmapgl' property is a tuple of instances of Heatmapgl that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.template.data.Heatmapgl - A list or tuple of dicts of string/value properties that will be passed to the Heatmapgl constructor Supported dict properties: Returns ------- tuple[plotly.graph_objs.layout.template.data.Heatmapgl] """ return self["heatmapgl"] @heatmapgl.setter def heatmapgl(self, val): self["heatmapgl"] = val # heatmap # ------- @property def heatmap(self): """ The 'heatmap' property is a tuple of instances of Heatmap that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.template.data.Heatmap - A list or tuple of dicts of string/value properties that will be passed to the Heatmap constructor Supported dict properties: Returns ------- tuple[plotly.graph_objs.layout.template.data.Heatmap] """ return self["heatmap"] @heatmap.setter def heatmap(self, val): self["heatmap"] = val # histogram2dcontour # ------------------ @property def histogram2dcontour(self): """ The 'histogram2dcontour' property is a tuple of instances of Histogram2dContour that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.template.data.Histogram2dContour - A list or tuple of dicts of string/value properties that will be passed to the Histogram2dContour constructor Supported dict properties: Returns ------- tuple[plotly.graph_objs.layout.template.data.Histogram2dContour] """ return self["histogram2dcontour"] @histogram2dcontour.setter def histogram2dcontour(self, val): self["histogram2dcontour"] = val # histogram2d # ----------- @property def histogram2d(self): """ The 'histogram2d' property is a tuple of instances of Histogram2d that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.template.data.Histogram2d - A list or tuple of dicts of string/value properties that will be passed to the Histogram2d constructor Supported dict properties: Returns ------- tuple[plotly.graph_objs.layout.template.data.Histogram2d] """ return self["histogram2d"] @histogram2d.setter def histogram2d(self, val): self["histogram2d"] = val # histogram # --------- @property def histogram(self): """ The 'histogram' property is a tuple of instances of Histogram that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.template.data.Histogram - A list or tuple of dicts of string/value properties that will be passed to the Histogram constructor Supported dict properties: Returns ------- tuple[plotly.graph_objs.layout.template.data.Histogram] """ return self["histogram"] @histogram.setter def histogram(self, val): self["histogram"] = val # image # ----- @property def image(self): """ The 'image' property is a tuple of instances of Image that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.template.data.Image - A list or tuple of dicts of string/value properties that will be passed to the Image constructor Supported dict properties: Returns ------- tuple[plotly.graph_objs.layout.template.data.Image] """ return self["image"] @image.setter def image(self, val): self["image"] = val # indicator # --------- @property def indicator(self): """ The 'indicator' property is a tuple of instances of Indicator that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.template.data.Indicator - A list or tuple of dicts of string/value properties that will be passed to the Indicator constructor Supported dict properties: Returns ------- tuple[plotly.graph_objs.layout.template.data.Indicator] """ return self["indicator"] @indicator.setter def indicator(self, val): self["indicator"] = val # isosurface # ---------- @property def isosurface(self): """ The 'isosurface' property is a tuple of instances of Isosurface that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.template.data.Isosurface - A list or tuple of dicts of string/value properties that will be passed to the Isosurface constructor Supported dict properties: Returns ------- tuple[plotly.graph_objs.layout.template.data.Isosurface] """ return self["isosurface"] @isosurface.setter def isosurface(self, val): self["isosurface"] = val # mesh3d # ------ @property def mesh3d(self): """ The 'mesh3d' property is a tuple of instances of Mesh3d that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.template.data.Mesh3d - A list or tuple of dicts of string/value properties that will be passed to the Mesh3d constructor Supported dict properties: Returns ------- tuple[plotly.graph_objs.layout.template.data.Mesh3d] """ return self["mesh3d"] @mesh3d.setter def mesh3d(self, val): self["mesh3d"] = val # ohlc # ---- @property def ohlc(self): """ The 'ohlc' property is a tuple of instances of Ohlc that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.template.data.Ohlc - A list or tuple of dicts of string/value properties that will be passed to the Ohlc constructor Supported dict properties: Returns ------- tuple[plotly.graph_objs.layout.template.data.Ohlc] """ return self["ohlc"] @ohlc.setter def ohlc(self, val): self["ohlc"] = val # parcats # ------- @property def parcats(self): """ The 'parcats' property is a tuple of instances of Parcats that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.template.data.Parcats - A list or tuple of dicts of string/value properties that will be passed to the Parcats constructor Supported dict properties: Returns ------- tuple[plotly.graph_objs.layout.template.data.Parcats] """ return self["parcats"] @parcats.setter def parcats(self, val): self["parcats"] = val # parcoords # --------- @property def parcoords(self): """ The 'parcoords' property is a tuple of instances of Parcoords that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.template.data.Parcoords - A list or tuple of dicts of string/value properties that will be passed to the Parcoords constructor Supported dict properties: Returns ------- tuple[plotly.graph_objs.layout.template.data.Parcoords] """ return self["parcoords"] @parcoords.setter def parcoords(self, val): self["parcoords"] = val # pie # --- @property def pie(self): """ The 'pie' property is a tuple of instances of Pie that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.template.data.Pie - A list or tuple of dicts of string/value properties that will be passed to the Pie constructor Supported dict properties: Returns ------- tuple[plotly.graph_objs.layout.template.data.Pie] """ return self["pie"] @pie.setter def pie(self, val): self["pie"] = val # pointcloud # ---------- @property def pointcloud(self): """ The 'pointcloud' property is a tuple of instances of Pointcloud that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.template.data.Pointcloud - A list or tuple of dicts of string/value properties that will be passed to the Pointcloud constructor Supported dict properties: Returns ------- tuple[plotly.graph_objs.layout.template.data.Pointcloud] """ return self["pointcloud"] @pointcloud.setter def pointcloud(self, val): self["pointcloud"] = val # sankey # ------ @property def sankey(self): """ The 'sankey' property is a tuple of instances of Sankey that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.template.data.Sankey - A list or tuple of dicts of string/value properties that will be passed to the Sankey constructor Supported dict properties: Returns ------- tuple[plotly.graph_objs.layout.template.data.Sankey] """ return self["sankey"] @sankey.setter def sankey(self, val): self["sankey"] = val # scatter3d # --------- @property def scatter3d(self): """ The 'scatter3d' property is a tuple of instances of Scatter3d that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.template.data.Scatter3d - A list or tuple of dicts of string/value properties that will be passed to the Scatter3d constructor Supported dict properties: Returns ------- tuple[plotly.graph_objs.layout.template.data.Scatter3d] """ return self["scatter3d"] @scatter3d.setter def scatter3d(self, val): self["scatter3d"] = val # scattercarpet # ------------- @property def scattercarpet(self): """ The 'scattercarpet' property is a tuple of instances of Scattercarpet that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.template.data.Scattercarpet - A list or tuple of dicts of string/value properties that will be passed to the Scattercarpet constructor Supported dict properties: Returns ------- tuple[plotly.graph_objs.layout.template.data.Scattercarpet] """ return self["scattercarpet"] @scattercarpet.setter def scattercarpet(self, val): self["scattercarpet"] = val # scattergeo # ---------- @property def scattergeo(self): """ The 'scattergeo' property is a tuple of instances of Scattergeo that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.template.data.Scattergeo - A list or tuple of dicts of string/value properties that will be passed to the Scattergeo constructor Supported dict properties: Returns ------- tuple[plotly.graph_objs.layout.template.data.Scattergeo] """ return self["scattergeo"] @scattergeo.setter def scattergeo(self, val): self["scattergeo"] = val # scattergl # --------- @property def scattergl(self): """ The 'scattergl' property is a tuple of instances of Scattergl that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.template.data.Scattergl - A list or tuple of dicts of string/value properties that will be passed to the Scattergl constructor Supported dict properties: Returns ------- tuple[plotly.graph_objs.layout.template.data.Scattergl] """ return self["scattergl"] @scattergl.setter def scattergl(self, val): self["scattergl"] = val # scattermapbox # ------------- @property def scattermapbox(self): """ The 'scattermapbox' property is a tuple of instances of Scattermapbox that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.template.data.Scattermapbox - A list or tuple of dicts of string/value properties that will be passed to the Scattermapbox constructor Supported dict properties: Returns ------- tuple[plotly.graph_objs.layout.template.data.Scattermapbox] """ return self["scattermapbox"] @scattermapbox.setter def scattermapbox(self, val): self["scattermapbox"] = val # scatterpolargl # -------------- @property def scatterpolargl(self): """ The 'scatterpolargl' property is a tuple of instances of Scatterpolargl that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.template.data.Scatterpolargl - A list or tuple of dicts of string/value properties that will be passed to the Scatterpolargl constructor Supported dict properties: Returns ------- tuple[plotly.graph_objs.layout.template.data.Scatterpolargl] """ return self["scatterpolargl"] @scatterpolargl.setter def scatterpolargl(self, val): self["scatterpolargl"] = val # scatterpolar # ------------ @property def scatterpolar(self): """ The 'scatterpolar' property is a tuple of instances of Scatterpolar that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.template.data.Scatterpolar - A list or tuple of dicts of string/value properties that will be passed to the Scatterpolar constructor Supported dict properties: Returns ------- tuple[plotly.graph_objs.layout.template.data.Scatterpolar] """ return self["scatterpolar"] @scatterpolar.setter def scatterpolar(self, val): self["scatterpolar"] = val # scatter # ------- @property def scatter(self): """ The 'scatter' property is a tuple of instances of Scatter that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.template.data.Scatter - A list or tuple of dicts of string/value properties that will be passed to the Scatter constructor Supported dict properties: Returns ------- tuple[plotly.graph_objs.layout.template.data.Scatter] """ return self["scatter"] @scatter.setter def scatter(self, val): self["scatter"] = val # scatterternary # -------------- @property def scatterternary(self): """ The 'scatterternary' property is a tuple of instances of Scatterternary that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.template.data.Scatterternary - A list or tuple of dicts of string/value properties that will be passed to the Scatterternary constructor Supported dict properties: Returns ------- tuple[plotly.graph_objs.layout.template.data.Scatterternary] """ return self["scatterternary"] @scatterternary.setter def scatterternary(self, val): self["scatterternary"] = val # splom # ----- @property def splom(self): """ The 'splom' property is a tuple of instances of Splom that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.template.data.Splom - A list or tuple of dicts of string/value properties that will be passed to the Splom constructor Supported dict properties: Returns ------- tuple[plotly.graph_objs.layout.template.data.Splom] """ return self["splom"] @splom.setter def splom(self, val): self["splom"] = val # streamtube # ---------- @property def streamtube(self): """ The 'streamtube' property is a tuple of instances of Streamtube that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.template.data.Streamtube - A list or tuple of dicts of string/value properties that will be passed to the Streamtube constructor Supported dict properties: Returns ------- tuple[plotly.graph_objs.layout.template.data.Streamtube] """ return self["streamtube"] @streamtube.setter def streamtube(self, val): self["streamtube"] = val # sunburst # -------- @property def sunburst(self): """ The 'sunburst' property is a tuple of instances of Sunburst that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.template.data.Sunburst - A list or tuple of dicts of string/value properties that will be passed to the Sunburst constructor Supported dict properties: Returns ------- tuple[plotly.graph_objs.layout.template.data.Sunburst] """ return self["sunburst"] @sunburst.setter def sunburst(self, val): self["sunburst"] = val # surface # ------- @property def surface(self): """ The 'surface' property is a tuple of instances of Surface that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.template.data.Surface - A list or tuple of dicts of string/value properties that will be passed to the Surface constructor Supported dict properties: Returns ------- tuple[plotly.graph_objs.layout.template.data.Surface] """ return self["surface"] @surface.setter def surface(self, val): self["surface"] = val # table # ----- @property def table(self): """ The 'table' property is a tuple of instances of Table that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.template.data.Table - A list or tuple of dicts of string/value properties that will be passed to the Table constructor Supported dict properties: Returns ------- tuple[plotly.graph_objs.layout.template.data.Table] """ return self["table"] @table.setter def table(self, val): self["table"] = val # treemap # ------- @property def treemap(self): """ The 'treemap' property is a tuple of instances of Treemap that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.template.data.Treemap - A list or tuple of dicts of string/value properties that will be passed to the Treemap constructor Supported dict properties: Returns ------- tuple[plotly.graph_objs.layout.template.data.Treemap] """ return self["treemap"] @treemap.setter def treemap(self, val): self["treemap"] = val # violin # ------ @property def violin(self): """ The 'violin' property is a tuple of instances of Violin that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.template.data.Violin - A list or tuple of dicts of string/value properties that will be passed to the Violin constructor Supported dict properties: Returns ------- tuple[plotly.graph_objs.layout.template.data.Violin] """ return self["violin"] @violin.setter def violin(self, val): self["violin"] = val # volume # ------ @property def volume(self): """ The 'volume' property is a tuple of instances of Volume that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.template.data.Volume - A list or tuple of dicts of string/value properties that will be passed to the Volume constructor Supported dict properties: Returns ------- tuple[plotly.graph_objs.layout.template.data.Volume] """ return self["volume"] @volume.setter def volume(self, val): self["volume"] = val # waterfall # --------- @property def waterfall(self): """ The 'waterfall' property is a tuple of instances of Waterfall that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.template.data.Waterfall - A list or tuple of dicts of string/value properties that will be passed to the Waterfall constructor Supported dict properties: Returns ------- tuple[plotly.graph_objs.layout.template.data.Waterfall] """ return self["waterfall"] @waterfall.setter def waterfall(self, val): self["waterfall"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.template" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ area A tuple of plotly.graph_objects.Area instances or dicts with compatible properties barpolar A tuple of plotly.graph_objects.Barpolar instances or dicts with compatible properties bar A tuple of plotly.graph_objects.Bar instances or dicts with compatible properties box A tuple of plotly.graph_objects.Box instances or dicts with compatible properties candlestick A tuple of plotly.graph_objects.Candlestick instances or dicts with compatible properties carpet A tuple of plotly.graph_objects.Carpet instances or dicts with compatible properties choroplethmapbox A tuple of plotly.graph_objects.Choroplethmapbox instances or dicts with compatible properties choropleth A tuple of plotly.graph_objects.Choropleth instances or dicts with compatible properties cone A tuple of plotly.graph_objects.Cone instances or dicts with compatible properties contourcarpet A tuple of plotly.graph_objects.Contourcarpet instances or dicts with compatible properties contour A tuple of plotly.graph_objects.Contour instances or dicts with compatible properties densitymapbox A tuple of plotly.graph_objects.Densitymapbox instances or dicts with compatible properties funnelarea A tuple of plotly.graph_objects.Funnelarea instances or dicts with compatible properties funnel A tuple of plotly.graph_objects.Funnel instances or dicts with compatible properties heatmapgl A tuple of plotly.graph_objects.Heatmapgl instances or dicts with compatible properties heatmap A tuple of plotly.graph_objects.Heatmap instances or dicts with compatible properties histogram2dcontour A tuple of plotly.graph_objects.Histogram2dContour instances or dicts with compatible properties histogram2d A tuple of plotly.graph_objects.Histogram2d instances or dicts with compatible properties histogram A tuple of plotly.graph_objects.Histogram instances or dicts with compatible properties image A tuple of plotly.graph_objects.Image instances or dicts with compatible properties indicator A tuple of plotly.graph_objects.Indicator instances or dicts with compatible properties isosurface A tuple of plotly.graph_objects.Isosurface instances or dicts with compatible properties mesh3d A tuple of plotly.graph_objects.Mesh3d instances or dicts with compatible properties ohlc A tuple of plotly.graph_objects.Ohlc instances or dicts with compatible properties parcats A tuple of plotly.graph_objects.Parcats instances or dicts with compatible properties parcoords A tuple of plotly.graph_objects.Parcoords instances or dicts with compatible properties pie A tuple of plotly.graph_objects.Pie instances or dicts with compatible properties pointcloud A tuple of plotly.graph_objects.Pointcloud instances or dicts with compatible properties sankey A tuple of plotly.graph_objects.Sankey instances or dicts with compatible properties scatter3d A tuple of plotly.graph_objects.Scatter3d instances or dicts with compatible properties scattercarpet A tuple of plotly.graph_objects.Scattercarpet instances or dicts with compatible properties scattergeo A tuple of plotly.graph_objects.Scattergeo instances or dicts with compatible properties scattergl A tuple of plotly.graph_objects.Scattergl instances or dicts with compatible properties scattermapbox A tuple of plotly.graph_objects.Scattermapbox instances or dicts with compatible properties scatterpolargl A tuple of plotly.graph_objects.Scatterpolargl instances or dicts with compatible properties scatterpolar A tuple of plotly.graph_objects.Scatterpolar instances or dicts with compatible properties scatter A tuple of plotly.graph_objects.Scatter instances or dicts with compatible properties scatterternary A tuple of plotly.graph_objects.Scatterternary instances or dicts with compatible properties splom A tuple of plotly.graph_objects.Splom instances or dicts with compatible properties streamtube A tuple of plotly.graph_objects.Streamtube instances or dicts with compatible properties sunburst A tuple of plotly.graph_objects.Sunburst instances or dicts with compatible properties surface A tuple of plotly.graph_objects.Surface instances or dicts with compatible properties table A tuple of plotly.graph_objects.Table instances or dicts with compatible properties treemap A tuple of plotly.graph_objects.Treemap instances or dicts with compatible properties violin A tuple of plotly.graph_objects.Violin instances or dicts with compatible properties volume A tuple of plotly.graph_objects.Volume instances or dicts with compatible properties waterfall A tuple of plotly.graph_objects.Waterfall instances or dicts with compatible properties """ def __init__( self, arg=None, area=None, barpolar=None, bar=None, box=None, candlestick=None, carpet=None, choroplethmapbox=None, choropleth=None, cone=None, contourcarpet=None, contour=None, densitymapbox=None, funnelarea=None, funnel=None, heatmapgl=None, heatmap=None, histogram2dcontour=None, histogram2d=None, histogram=None, image=None, indicator=None, isosurface=None, mesh3d=None, ohlc=None, parcats=None, parcoords=None, pie=None, pointcloud=None, sankey=None, scatter3d=None, scattercarpet=None, scattergeo=None, scattergl=None, scattermapbox=None, scatterpolargl=None, scatterpolar=None, scatter=None, scatterternary=None, splom=None, streamtube=None, sunburst=None, surface=None, table=None, treemap=None, violin=None, volume=None, waterfall=None, **kwargs ): """ Construct a new Data object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.template.Data area A tuple of plotly.graph_objects.Area instances or dicts with compatible properties barpolar A tuple of plotly.graph_objects.Barpolar instances or dicts with compatible properties bar A tuple of plotly.graph_objects.Bar instances or dicts with compatible properties box A tuple of plotly.graph_objects.Box instances or dicts with compatible properties candlestick A tuple of plotly.graph_objects.Candlestick instances or dicts with compatible properties carpet A tuple of plotly.graph_objects.Carpet instances or dicts with compatible properties choroplethmapbox A tuple of plotly.graph_objects.Choroplethmapbox instances or dicts with compatible properties choropleth A tuple of plotly.graph_objects.Choropleth instances or dicts with compatible properties cone A tuple of plotly.graph_objects.Cone instances or dicts with compatible properties contourcarpet A tuple of plotly.graph_objects.Contourcarpet instances or dicts with compatible properties contour A tuple of plotly.graph_objects.Contour instances or dicts with compatible properties densitymapbox A tuple of plotly.graph_objects.Densitymapbox instances or dicts with compatible properties funnelarea A tuple of plotly.graph_objects.Funnelarea instances or dicts with compatible properties funnel A tuple of plotly.graph_objects.Funnel instances or dicts with compatible properties heatmapgl A tuple of plotly.graph_objects.Heatmapgl instances or dicts with compatible properties heatmap A tuple of plotly.graph_objects.Heatmap instances or dicts with compatible properties histogram2dcontour A tuple of plotly.graph_objects.Histogram2dContour instances or dicts with compatible properties histogram2d A tuple of plotly.graph_objects.Histogram2d instances or dicts with compatible properties histogram A tuple of plotly.graph_objects.Histogram instances or dicts with compatible properties image A tuple of plotly.graph_objects.Image instances or dicts with compatible properties indicator A tuple of plotly.graph_objects.Indicator instances or dicts with compatible properties isosurface A tuple of plotly.graph_objects.Isosurface instances or dicts with compatible properties mesh3d A tuple of plotly.graph_objects.Mesh3d instances or dicts with compatible properties ohlc A tuple of plotly.graph_objects.Ohlc instances or dicts with compatible properties parcats A tuple of plotly.graph_objects.Parcats instances or dicts with compatible properties parcoords A tuple of plotly.graph_objects.Parcoords instances or dicts with compatible properties pie A tuple of plotly.graph_objects.Pie instances or dicts with compatible properties pointcloud A tuple of plotly.graph_objects.Pointcloud instances or dicts with compatible properties sankey A tuple of plotly.graph_objects.Sankey instances or dicts with compatible properties scatter3d A tuple of plotly.graph_objects.Scatter3d instances or dicts with compatible properties scattercarpet A tuple of plotly.graph_objects.Scattercarpet instances or dicts with compatible properties scattergeo A tuple of plotly.graph_objects.Scattergeo instances or dicts with compatible properties scattergl A tuple of plotly.graph_objects.Scattergl instances or dicts with compatible properties scattermapbox A tuple of plotly.graph_objects.Scattermapbox instances or dicts with compatible properties scatterpolargl A tuple of plotly.graph_objects.Scatterpolargl instances or dicts with compatible properties scatterpolar A tuple of plotly.graph_objects.Scatterpolar instances or dicts with compatible properties scatter A tuple of plotly.graph_objects.Scatter instances or dicts with compatible properties scatterternary A tuple of plotly.graph_objects.Scatterternary instances or dicts with compatible properties splom A tuple of plotly.graph_objects.Splom instances or dicts with compatible properties streamtube A tuple of plotly.graph_objects.Streamtube instances or dicts with compatible properties sunburst A tuple of plotly.graph_objects.Sunburst instances or dicts with compatible properties surface A tuple of plotly.graph_objects.Surface instances or dicts with compatible properties table A tuple of plotly.graph_objects.Table instances or dicts with compatible properties treemap A tuple of plotly.graph_objects.Treemap instances or dicts with compatible properties violin A tuple of plotly.graph_objects.Violin instances or dicts with compatible properties volume A tuple of plotly.graph_objects.Volume instances or dicts with compatible properties waterfall A tuple of plotly.graph_objects.Waterfall instances or dicts with compatible properties Returns ------- Data """ super(Data, self).__init__("data") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.template.Data constructor must be a dict or an instance of plotly.graph_objs.layout.template.Data""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.template import data as v_data # Initialize validators # --------------------- self._validators["area"] = v_data.AreasValidator() self._validators["barpolar"] = v_data.BarpolarsValidator() self._validators["bar"] = v_data.BarsValidator() self._validators["box"] = v_data.BoxsValidator() self._validators["candlestick"] = v_data.CandlesticksValidator() self._validators["carpet"] = v_data.CarpetsValidator() self._validators["choroplethmapbox"] = v_data.ChoroplethmapboxsValidator() self._validators["choropleth"] = v_data.ChoroplethsValidator() self._validators["cone"] = v_data.ConesValidator() self._validators["contourcarpet"] = v_data.ContourcarpetsValidator() self._validators["contour"] = v_data.ContoursValidator() self._validators["densitymapbox"] = v_data.DensitymapboxsValidator() self._validators["funnelarea"] = v_data.FunnelareasValidator() self._validators["funnel"] = v_data.FunnelsValidator() self._validators["heatmapgl"] = v_data.HeatmapglsValidator() self._validators["heatmap"] = v_data.HeatmapsValidator() self._validators["histogram2dcontour"] = v_data.Histogram2dContoursValidator() self._validators["histogram2d"] = v_data.Histogram2dsValidator() self._validators["histogram"] = v_data.HistogramsValidator() self._validators["image"] = v_data.ImagesValidator() self._validators["indicator"] = v_data.IndicatorsValidator() self._validators["isosurface"] = v_data.IsosurfacesValidator() self._validators["mesh3d"] = v_data.Mesh3dsValidator() self._validators["ohlc"] = v_data.OhlcsValidator() self._validators["parcats"] = v_data.ParcatssValidator() self._validators["parcoords"] = v_data.ParcoordssValidator() self._validators["pie"] = v_data.PiesValidator() self._validators["pointcloud"] = v_data.PointcloudsValidator() self._validators["sankey"] = v_data.SankeysValidator() self._validators["scatter3d"] = v_data.Scatter3dsValidator() self._validators["scattercarpet"] = v_data.ScattercarpetsValidator() self._validators["scattergeo"] = v_data.ScattergeosValidator() self._validators["scattergl"] = v_data.ScatterglsValidator() self._validators["scattermapbox"] = v_data.ScattermapboxsValidator() self._validators["scatterpolargl"] = v_data.ScatterpolarglsValidator() self._validators["scatterpolar"] = v_data.ScatterpolarsValidator() self._validators["scatter"] = v_data.ScattersValidator() self._validators["scatterternary"] = v_data.ScatterternarysValidator() self._validators["splom"] = v_data.SplomsValidator() self._validators["streamtube"] = v_data.StreamtubesValidator() self._validators["sunburst"] = v_data.SunburstsValidator() self._validators["surface"] = v_data.SurfacesValidator() self._validators["table"] = v_data.TablesValidator() self._validators["treemap"] = v_data.TreemapsValidator() self._validators["violin"] = v_data.ViolinsValidator() self._validators["volume"] = v_data.VolumesValidator() self._validators["waterfall"] = v_data.WaterfallsValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("area", None) self["area"] = area if area is not None else _v _v = arg.pop("barpolar", None) self["barpolar"] = barpolar if barpolar is not None else _v _v = arg.pop("bar", None) self["bar"] = bar if bar is not None else _v _v = arg.pop("box", None) self["box"] = box if box is not None else _v _v = arg.pop("candlestick", None) self["candlestick"] = candlestick if candlestick is not None else _v _v = arg.pop("carpet", None) self["carpet"] = carpet if carpet is not None else _v _v = arg.pop("choroplethmapbox", None) self["choroplethmapbox"] = ( choroplethmapbox if choroplethmapbox is not None else _v ) _v = arg.pop("choropleth", None) self["choropleth"] = choropleth if choropleth is not None else _v _v = arg.pop("cone", None) self["cone"] = cone if cone is not None else _v _v = arg.pop("contourcarpet", None) self["contourcarpet"] = contourcarpet if contourcarpet is not None else _v _v = arg.pop("contour", None) self["contour"] = contour if contour is not None else _v _v = arg.pop("densitymapbox", None) self["densitymapbox"] = densitymapbox if densitymapbox is not None else _v _v = arg.pop("funnelarea", None) self["funnelarea"] = funnelarea if funnelarea is not None else _v _v = arg.pop("funnel", None) self["funnel"] = funnel if funnel is not None else _v _v = arg.pop("heatmapgl", None) self["heatmapgl"] = heatmapgl if heatmapgl is not None else _v _v = arg.pop("heatmap", None) self["heatmap"] = heatmap if heatmap is not None else _v _v = arg.pop("histogram2dcontour", None) self["histogram2dcontour"] = ( histogram2dcontour if histogram2dcontour is not None else _v ) _v = arg.pop("histogram2d", None) self["histogram2d"] = histogram2d if histogram2d is not None else _v _v = arg.pop("histogram", None) self["histogram"] = histogram if histogram is not None else _v _v = arg.pop("image", None) self["image"] = image if image is not None else _v _v = arg.pop("indicator", None) self["indicator"] = indicator if indicator is not None else _v _v = arg.pop("isosurface", None) self["isosurface"] = isosurface if isosurface is not None else _v _v = arg.pop("mesh3d", None) self["mesh3d"] = mesh3d if mesh3d is not None else _v _v = arg.pop("ohlc", None) self["ohlc"] = ohlc if ohlc is not None else _v _v = arg.pop("parcats", None) self["parcats"] = parcats if parcats is not None else _v _v = arg.pop("parcoords", None) self["parcoords"] = parcoords if parcoords is not None else _v _v = arg.pop("pie", None) self["pie"] = pie if pie is not None else _v _v = arg.pop("pointcloud", None) self["pointcloud"] = pointcloud if pointcloud is not None else _v _v = arg.pop("sankey", None) self["sankey"] = sankey if sankey is not None else _v _v = arg.pop("scatter3d", None) self["scatter3d"] = scatter3d if scatter3d is not None else _v _v = arg.pop("scattercarpet", None) self["scattercarpet"] = scattercarpet if scattercarpet is not None else _v _v = arg.pop("scattergeo", None) self["scattergeo"] = scattergeo if scattergeo is not None else _v _v = arg.pop("scattergl", None) self["scattergl"] = scattergl if scattergl is not None else _v _v = arg.pop("scattermapbox", None) self["scattermapbox"] = scattermapbox if scattermapbox is not None else _v _v = arg.pop("scatterpolargl", None) self["scatterpolargl"] = scatterpolargl if scatterpolargl is not None else _v _v = arg.pop("scatterpolar", None) self["scatterpolar"] = scatterpolar if scatterpolar is not None else _v _v = arg.pop("scatter", None) self["scatter"] = scatter if scatter is not None else _v _v = arg.pop("scatterternary", None) self["scatterternary"] = scatterternary if scatterternary is not None else _v _v = arg.pop("splom", None) self["splom"] = splom if splom is not None else _v _v = arg.pop("streamtube", None) self["streamtube"] = streamtube if streamtube is not None else _v _v = arg.pop("sunburst", None) self["sunburst"] = sunburst if sunburst is not None else _v _v = arg.pop("surface", None) self["surface"] = surface if surface is not None else _v _v = arg.pop("table", None) self["table"] = table if table is not None else _v _v = arg.pop("treemap", None) self["treemap"] = treemap if treemap is not None else _v _v = arg.pop("violin", None) self["violin"] = violin if violin is not None else _v _v = arg.pop("volume", None) self["volume"] = volume if volume is not None else _v _v = arg.pop("waterfall", None) self["waterfall"] = waterfall if waterfall is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Data", "Layout", "data"] from plotly.graph_objs.layout.template import data plotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/template/data/0000755000175000017500000000000013573746613023772 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/template/data/__init__.py0000644000175000017500000000521013573721547026100 0ustar noahfxnoahfxfrom plotly.graph_objs import Waterfall from plotly.graph_objs import Volume from plotly.graph_objs import Violin from plotly.graph_objs import Treemap from plotly.graph_objs import Table from plotly.graph_objs import Surface from plotly.graph_objs import Sunburst from plotly.graph_objs import Streamtube from plotly.graph_objs import Splom from plotly.graph_objs import Scatterternary from plotly.graph_objs import Scatter from plotly.graph_objs import Scatterpolar from plotly.graph_objs import Scatterpolargl from plotly.graph_objs import Scattermapbox from plotly.graph_objs import Scattergl from plotly.graph_objs import Scattergeo from plotly.graph_objs import Scattercarpet from plotly.graph_objs import Scatter3d from plotly.graph_objs import Sankey from plotly.graph_objs import Pointcloud from plotly.graph_objs import Pie from plotly.graph_objs import Parcoords from plotly.graph_objs import Parcats from plotly.graph_objs import Ohlc from plotly.graph_objs import Mesh3d from plotly.graph_objs import Isosurface from plotly.graph_objs import Indicator from plotly.graph_objs import Image from plotly.graph_objs import Histogram from plotly.graph_objs import Histogram2d from plotly.graph_objs import Histogram2dContour from plotly.graph_objs import Heatmap from plotly.graph_objs import Heatmapgl from plotly.graph_objs import Funnel from plotly.graph_objs import Funnelarea from plotly.graph_objs import Densitymapbox from plotly.graph_objs import Contour from plotly.graph_objs import Contourcarpet from plotly.graph_objs import Cone from plotly.graph_objs import Choropleth from plotly.graph_objs import Choroplethmapbox from plotly.graph_objs import Carpet from plotly.graph_objs import Candlestick from plotly.graph_objs import Box from plotly.graph_objs import Bar from plotly.graph_objs import Barpolar from plotly.graph_objs import Area __all__ = [ "Area", "Bar", "Barpolar", "Box", "Candlestick", "Carpet", "Choropleth", "Choroplethmapbox", "Cone", "Contour", "Contourcarpet", "Densitymapbox", "Funnel", "Funnelarea", "Heatmap", "Heatmapgl", "Histogram", "Histogram2d", "Histogram2dContour", "Image", "Indicator", "Isosurface", "Mesh3d", "Ohlc", "Parcats", "Parcoords", "Pie", "Pointcloud", "Sankey", "Scatter", "Scatter3d", "Scattercarpet", "Scattergeo", "Scattergl", "Scattermapbox", "Scatterpolar", "Scatterpolargl", "Scatterternary", "Splom", "Streamtube", "Sunburst", "Surface", "Table", "Treemap", "Violin", "Volume", "Waterfall", ] plotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/polar/0000755000175000017500000000000013573746613022363 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/polar/angularaxis/0000755000175000017500000000000013573746613024701 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/polar/angularaxis/__init__.py0000644000175000017500000004354413573721547027023 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Tickformatstop(_BaseLayoutHierarchyType): # dtickrange # ---------- @property def dtickrange(self): """ range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" The 'dtickrange' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'dtickrange[0]' property accepts values of any type (1) The 'dtickrange[1]' property accepts values of any type Returns ------- list """ return self["dtickrange"] @dtickrange.setter def dtickrange(self, val): self["dtickrange"] = val # enabled # ------- @property def enabled(self): """ Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. The 'enabled' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["enabled"] @enabled.setter def enabled(self, val): self["enabled"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # value # ----- @property def value(self): """ string - dtickformat for described zoom level, the same as "tickformat" The 'value' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.polar.angularaxis" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """ def __init__( self, arg=None, dtickrange=None, enabled=None, name=None, templateitemname=None, value=None, **kwargs ): """ Construct a new Tickformatstop object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.polar.angularax is.Tickformatstop dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- Tickformatstop """ super(Tickformatstop, self).__init__("tickformatstops") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.polar.angularaxis.Tickformatstop constructor must be a dict or an instance of plotly.graph_objs.layout.polar.angularaxis.Tickformatstop""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.polar.angularaxis import ( tickformatstop as v_tickformatstop, ) # Initialize validators # --------------------- self._validators["dtickrange"] = v_tickformatstop.DtickrangeValidator() self._validators["enabled"] = v_tickformatstop.EnabledValidator() self._validators["name"] = v_tickformatstop.NameValidator() self._validators[ "templateitemname" ] = v_tickformatstop.TemplateitemnameValidator() self._validators["value"] = v_tickformatstop.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtickrange", None) self["dtickrange"] = dtickrange if dtickrange is not None else _v _v = arg.pop("enabled", None) self["enabled"] = enabled if enabled is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Tickfont(_BaseLayoutHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.polar.angularaxis" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Tickfont object Sets the tick font. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.polar.angularaxis.Tickfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Tickfont """ super(Tickfont, self).__init__("tickfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.polar.angularaxis.Tickfont constructor must be a dict or an instance of plotly.graph_objs.layout.polar.angularaxis.Tickfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.polar.angularaxis import tickfont as v_tickfont # Initialize validators # --------------------- self._validators["color"] = v_tickfont.ColorValidator() self._validators["family"] = v_tickfont.FamilyValidator() self._validators["size"] = v_tickfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Tickfont", "Tickformatstop", "Tickformatstop"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/polar/radialaxis/0000755000175000017500000000000013573746613024504 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/polar/radialaxis/title/0000755000175000017500000000000013573746613025625 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/polar/radialaxis/title/__init__.py0000644000175000017500000002057413573721547027745 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Font(_BaseLayoutHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.polar.radialaxis.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.polar.radialaxis.title.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.polar.radialaxis.title.Font constructor must be a dict or an instance of plotly.graph_objs.layout.polar.radialaxis.title.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.polar.radialaxis.title import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/polar/radialaxis/__init__.py0000644000175000017500000005644713573721547026634 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Title(_BaseLayoutHierarchyType): # font # ---- @property def font(self): """ Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.layout.polar.radialaxis.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.layout.polar.radialaxis.title.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # text # ---- @property def text(self): """ Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.polar.radialaxis" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. text Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """ def __init__(self, arg=None, font=None, text=None, **kwargs): """ Construct a new Title object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.polar.radialaxis.Title font Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. text Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- Title """ super(Title, self).__init__("title") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.polar.radialaxis.Title constructor must be a dict or an instance of plotly.graph_objs.layout.polar.radialaxis.Title""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.polar.radialaxis import title as v_title # Initialize validators # --------------------- self._validators["font"] = v_title.FontValidator() self._validators["text"] = v_title.TextValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Tickformatstop(_BaseLayoutHierarchyType): # dtickrange # ---------- @property def dtickrange(self): """ range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" The 'dtickrange' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'dtickrange[0]' property accepts values of any type (1) The 'dtickrange[1]' property accepts values of any type Returns ------- list """ return self["dtickrange"] @dtickrange.setter def dtickrange(self, val): self["dtickrange"] = val # enabled # ------- @property def enabled(self): """ Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. The 'enabled' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["enabled"] @enabled.setter def enabled(self, val): self["enabled"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # value # ----- @property def value(self): """ string - dtickformat for described zoom level, the same as "tickformat" The 'value' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.polar.radialaxis" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """ def __init__( self, arg=None, dtickrange=None, enabled=None, name=None, templateitemname=None, value=None, **kwargs ): """ Construct a new Tickformatstop object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.polar.radialaxi s.Tickformatstop dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- Tickformatstop """ super(Tickformatstop, self).__init__("tickformatstops") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.polar.radialaxis.Tickformatstop constructor must be a dict or an instance of plotly.graph_objs.layout.polar.radialaxis.Tickformatstop""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.polar.radialaxis import ( tickformatstop as v_tickformatstop, ) # Initialize validators # --------------------- self._validators["dtickrange"] = v_tickformatstop.DtickrangeValidator() self._validators["enabled"] = v_tickformatstop.EnabledValidator() self._validators["name"] = v_tickformatstop.NameValidator() self._validators[ "templateitemname" ] = v_tickformatstop.TemplateitemnameValidator() self._validators["value"] = v_tickformatstop.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtickrange", None) self["dtickrange"] = dtickrange if dtickrange is not None else _v _v = arg.pop("enabled", None) self["enabled"] = enabled if enabled is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Tickfont(_BaseLayoutHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.polar.radialaxis" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Tickfont object Sets the tick font. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.polar.radialaxis.Tickfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Tickfont """ super(Tickfont, self).__init__("tickfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.polar.radialaxis.Tickfont constructor must be a dict or an instance of plotly.graph_objs.layout.polar.radialaxis.Tickfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.polar.radialaxis import tickfont as v_tickfont # Initialize validators # --------------------- self._validators["color"] = v_tickfont.ColorValidator() self._validators["family"] = v_tickfont.FamilyValidator() self._validators["size"] = v_tickfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Tickfont", "Tickformatstop", "Tickformatstop", "Title", "title"] from plotly.graph_objs.layout.polar.radialaxis import title plotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/polar/__init__.py0000644000175000017500000050052413573721551024474 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class RadialAxis(_BaseLayoutHierarchyType): # angle # ----- @property def angle(self): """ Sets the angle (in degrees) from which the radial axis is drawn. Note that by default, radial axis line on the theta=0 line corresponds to a line pointing right (like what mathematicians prefer). Defaults to the first `polar.sector` angle. The 'angle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["angle"] @angle.setter def angle(self, val): self["angle"] = val # autorange # --------- @property def autorange(self): """ Determines whether or not the range of this axis is computed in relation to the input data. See `rangemode` for more info. If `range` is provided, then `autorange` is set to False. The 'autorange' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'reversed'] Returns ------- Any """ return self["autorange"] @autorange.setter def autorange(self, val): self["autorange"] = val # calendar # -------- @property def calendar(self): """ Sets the calendar system to use for `range` and `tick0` if this is a date axis. This does not set the calendar for interpreting data on this axis, that's specified in the trace or via the global `layout.calendar` The 'calendar' property is an enumeration that may be specified as: - One of the following enumeration values: ['gregorian', 'chinese', 'coptic', 'discworld', 'ethiopian', 'hebrew', 'islamic', 'julian', 'mayan', 'nanakshahi', 'nepali', 'persian', 'jalali', 'taiwan', 'thai', 'ummalqura'] Returns ------- Any """ return self["calendar"] @calendar.setter def calendar(self, val): self["calendar"] = val # categoryarray # ------------- @property def categoryarray(self): """ Sets the order in which categories on this axis appear. Only has an effect if `categoryorder` is set to "array". Used with `categoryorder`. The 'categoryarray' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["categoryarray"] @categoryarray.setter def categoryarray(self, val): self["categoryarray"] = val # categoryarraysrc # ---------------- @property def categoryarraysrc(self): """ Sets the source reference on plot.ly for categoryarray . The 'categoryarraysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["categoryarraysrc"] @categoryarraysrc.setter def categoryarraysrc(self, val): self["categoryarraysrc"] = val # categoryorder # ------------- @property def categoryorder(self): """ Specifies the ordering logic for the case of categorical variables. By default, plotly uses "trace", which specifies the order that is present in the data supplied. Set `categoryorder` to *category ascending* or *category descending* if order should be determined by the alphanumerical order of the category names. Set `categoryorder` to "array" to derive the ordering from the attribute `categoryarray`. If a category is not found in the `categoryarray` array, the sorting behavior for that attribute will be identical to the "trace" mode. The unspecified categories will follow the categories in `categoryarray`. Set `categoryorder` to *total ascending* or *total descending* if order should be determined by the numerical order of the values. Similarly, the order can be determined by the min, max, sum, mean or median of all the values. The 'categoryorder' property is an enumeration that may be specified as: - One of the following enumeration values: ['trace', 'category ascending', 'category descending', 'array', 'total ascending', 'total descending', 'min ascending', 'min descending', 'max ascending', 'max descending', 'sum ascending', 'sum descending', 'mean ascending', 'mean descending', 'median ascending', 'median descending'] Returns ------- Any """ return self["categoryorder"] @categoryorder.setter def categoryorder(self, val): self["categoryorder"] = val # color # ----- @property def color(self): """ Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # dtick # ----- @property def dtick(self): """ Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" The 'dtick' property accepts values of any type Returns ------- Any """ return self["dtick"] @dtick.setter def dtick(self, val): self["dtick"] = val # exponentformat # -------------- @property def exponentformat(self): """ Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. The 'exponentformat' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'e', 'E', 'power', 'SI', 'B'] Returns ------- Any """ return self["exponentformat"] @exponentformat.setter def exponentformat(self, val): self["exponentformat"] = val # gridcolor # --------- @property def gridcolor(self): """ Sets the color of the grid lines. The 'gridcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["gridcolor"] @gridcolor.setter def gridcolor(self, val): self["gridcolor"] = val # gridwidth # --------- @property def gridwidth(self): """ Sets the width (in px) of the grid lines. The 'gridwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["gridwidth"] @gridwidth.setter def gridwidth(self, val): self["gridwidth"] = val # hoverformat # ----------- @property def hoverformat(self): """ Sets the hover text formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'hoverformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["hoverformat"] @hoverformat.setter def hoverformat(self, val): self["hoverformat"] = val # layer # ----- @property def layer(self): """ Sets the layer on which this axis is displayed. If *above traces*, this axis is displayed above all the subplot's traces If *below traces*, this axis is displayed below all the subplot's traces, but above the grid lines. Useful when used together with scatter-like traces with `cliponaxis` set to False to show markers and/or text nodes above this axis. The 'layer' property is an enumeration that may be specified as: - One of the following enumeration values: ['above traces', 'below traces'] Returns ------- Any """ return self["layer"] @layer.setter def layer(self, val): self["layer"] = val # linecolor # --------- @property def linecolor(self): """ Sets the axis line color. The 'linecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["linecolor"] @linecolor.setter def linecolor(self, val): self["linecolor"] = val # linewidth # --------- @property def linewidth(self): """ Sets the width (in px) of the axis line. The 'linewidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["linewidth"] @linewidth.setter def linewidth(self, val): self["linewidth"] = val # nticks # ------ @property def nticks(self): """ Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". The 'nticks' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nticks"] @nticks.setter def nticks(self, val): self["nticks"] = val # range # ----- @property def range(self): """ Sets the range of this axis. If the axis `type` is "log", then you must take the log of your desired range (e.g. to set the range from 1 to 100, set the range from 0 to 2). If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. The 'range' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'range[0]' property accepts values of any type (1) The 'range[1]' property accepts values of any type Returns ------- list """ return self["range"] @range.setter def range(self, val): self["range"] = val # rangemode # --------- @property def rangemode(self): """ If *tozero*`, the range extends to 0, regardless of the input data If "nonnegative", the range is non-negative, regardless of the input data. If "normal", the range is computed in relation to the extrema of the input data (same behavior as for cartesian axes). The 'rangemode' property is an enumeration that may be specified as: - One of the following enumeration values: ['tozero', 'nonnegative', 'normal'] Returns ------- Any """ return self["rangemode"] @rangemode.setter def rangemode(self, val): self["rangemode"] = val # separatethousands # ----------------- @property def separatethousands(self): """ If "true", even 4-digit integers are separated The 'separatethousands' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["separatethousands"] @separatethousands.setter def separatethousands(self, val): self["separatethousands"] = val # showexponent # ------------ @property def showexponent(self): """ If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. The 'showexponent' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showexponent"] @showexponent.setter def showexponent(self, val): self["showexponent"] = val # showgrid # -------- @property def showgrid(self): """ Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. The 'showgrid' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showgrid"] @showgrid.setter def showgrid(self, val): self["showgrid"] = val # showline # -------- @property def showline(self): """ Determines whether or not a line bounding this axis is drawn. The 'showline' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showline"] @showline.setter def showline(self, val): self["showline"] = val # showticklabels # -------------- @property def showticklabels(self): """ Determines whether or not the tick labels are drawn. The 'showticklabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showticklabels"] @showticklabels.setter def showticklabels(self, val): self["showticklabels"] = val # showtickprefix # -------------- @property def showtickprefix(self): """ If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. The 'showtickprefix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showtickprefix"] @showtickprefix.setter def showtickprefix(self, val): self["showtickprefix"] = val # showticksuffix # -------------- @property def showticksuffix(self): """ Same as `showtickprefix` but for tick suffixes. The 'showticksuffix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showticksuffix"] @showticksuffix.setter def showticksuffix(self, val): self["showticksuffix"] = val # side # ---- @property def side(self): """ Determines on which side of radial axis line the tick and tick labels appear. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['clockwise', 'counterclockwise'] Returns ------- Any """ return self["side"] @side.setter def side(self, val): self["side"] = val # tick0 # ----- @property def tick0(self): """ Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. The 'tick0' property accepts values of any type Returns ------- Any """ return self["tick0"] @tick0.setter def tick0(self, val): self["tick0"] = val # tickangle # --------- @property def tickangle(self): """ Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. The 'tickangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["tickangle"] @tickangle.setter def tickangle(self, val): self["tickangle"] = val # tickcolor # --------- @property def tickcolor(self): """ Sets the tick color. The 'tickcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["tickcolor"] @tickcolor.setter def tickcolor(self, val): self["tickcolor"] = val # tickfont # -------- @property def tickfont(self): """ Sets the tick font. The 'tickfont' property is an instance of Tickfont that may be specified as: - An instance of plotly.graph_objs.layout.polar.radialaxis.Tickfont - A dict of string/value properties that will be passed to the Tickfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.layout.polar.radialaxis.Tickfont """ return self["tickfont"] @tickfont.setter def tickfont(self, val): self["tickfont"] = val # tickformat # ---------- @property def tickformat(self): """ Sets the tick label formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'tickformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickformat"] @tickformat.setter def tickformat(self, val): self["tickformat"] = val # tickformatstops # --------------- @property def tickformatstops(self): """ The 'tickformatstops' property is a tuple of instances of Tickformatstop that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.polar.radialaxis.Tickformatstop - A list or tuple of dicts of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- tuple[plotly.graph_objs.layout.polar.radialaxis.Tickformatstop] """ return self["tickformatstops"] @tickformatstops.setter def tickformatstops(self, val): self["tickformatstops"] = val # tickformatstopdefaults # ---------------------- @property def tickformatstopdefaults(self): """ When used in a template (as layout.template.layout.polar.radial axis.tickformatstopdefaults), sets the default property values to use for elements of layout.polar.radialaxis.tickformatstops The 'tickformatstopdefaults' property is an instance of Tickformatstop that may be specified as: - An instance of plotly.graph_objs.layout.polar.radialaxis.Tickformatstop - A dict of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: Returns ------- plotly.graph_objs.layout.polar.radialaxis.Tickformatstop """ return self["tickformatstopdefaults"] @tickformatstopdefaults.setter def tickformatstopdefaults(self, val): self["tickformatstopdefaults"] = val # ticklen # ------- @property def ticklen(self): """ Sets the tick length (in px). The 'ticklen' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ticklen"] @ticklen.setter def ticklen(self, val): self["ticklen"] = val # tickmode # -------- @property def tickmode(self): """ Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). The 'tickmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'linear', 'array'] Returns ------- Any """ return self["tickmode"] @tickmode.setter def tickmode(self, val): self["tickmode"] = val # tickprefix # ---------- @property def tickprefix(self): """ Sets a tick label prefix. The 'tickprefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickprefix"] @tickprefix.setter def tickprefix(self, val): self["tickprefix"] = val # ticks # ----- @property def ticks(self): """ Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. The 'ticks' property is an enumeration that may be specified as: - One of the following enumeration values: ['outside', 'inside', ''] Returns ------- Any """ return self["ticks"] @ticks.setter def ticks(self, val): self["ticks"] = val # ticksuffix # ---------- @property def ticksuffix(self): """ Sets a tick label suffix. The 'ticksuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ticksuffix"] @ticksuffix.setter def ticksuffix(self, val): self["ticksuffix"] = val # ticktext # -------- @property def ticktext(self): """ Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. The 'ticktext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ticktext"] @ticktext.setter def ticktext(self, val): self["ticktext"] = val # ticktextsrc # ----------- @property def ticktextsrc(self): """ Sets the source reference on plot.ly for ticktext . The 'ticktextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ticktextsrc"] @ticktextsrc.setter def ticktextsrc(self, val): self["ticktextsrc"] = val # tickvals # -------- @property def tickvals(self): """ Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. The 'tickvals' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["tickvals"] @tickvals.setter def tickvals(self, val): self["tickvals"] = val # tickvalssrc # ----------- @property def tickvalssrc(self): """ Sets the source reference on plot.ly for tickvals . The 'tickvalssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tickvalssrc"] @tickvalssrc.setter def tickvalssrc(self, val): self["tickvalssrc"] = val # tickwidth # --------- @property def tickwidth(self): """ Sets the tick width (in px). The 'tickwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["tickwidth"] @tickwidth.setter def tickwidth(self, val): self["tickwidth"] = val # title # ----- @property def title(self): """ The 'title' property is an instance of Title that may be specified as: - An instance of plotly.graph_objs.layout.polar.radialaxis.Title - A dict of string/value properties that will be passed to the Title constructor Supported dict properties: font Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. text Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- plotly.graph_objs.layout.polar.radialaxis.Title """ return self["title"] @title.setter def title(self, val): self["title"] = val # titlefont # --------- @property def titlefont(self): """ Deprecated: Please use layout.polar.radialaxis.title.font instead. Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.layout.polar.radialaxis.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- """ return self["titlefont"] @titlefont.setter def titlefont(self, val): self["titlefont"] = val # type # ---- @property def type(self): """ Sets the axis type. By default, plotly attempts to determined the axis type by looking into the data of the traces that referenced the axis in question. The 'type' property is an enumeration that may be specified as: - One of the following enumeration values: ['-', 'linear', 'log', 'date', 'category'] Returns ------- Any """ return self["type"] @type.setter def type(self, val): self["type"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of user-driven changes in axis `range`, `autorange`, `angle`, and `title` if in `editable: true` configuration. Defaults to `polar.uirevision`. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # visible # ------- @property def visible(self): """ A single toggle to hide the axis while preserving interaction like dragging. Default is true when a cheater plot is present on the axis, otherwise false The 'visible' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.polar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ angle Sets the angle (in degrees) from which the radial axis is drawn. Note that by default, radial axis line on the theta=0 line corresponds to a line pointing right (like what mathematicians prefer). Defaults to the first `polar.sector` angle. autorange Determines whether or not the range of this axis is computed in relation to the input data. See `rangemode` for more info. If `range` is provided, then `autorange` is set to False. calendar Sets the calendar system to use for `range` and `tick0` if this is a date axis. This does not set the calendar for interpreting data on this axis, that's specified in the trace or via the global `layout.calendar` categoryarray Sets the order in which categories on this axis appear. Only has an effect if `categoryorder` is set to "array". Used with `categoryorder`. categoryarraysrc Sets the source reference on plot.ly for categoryarray . categoryorder Specifies the ordering logic for the case of categorical variables. By default, plotly uses "trace", which specifies the order that is present in the data supplied. Set `categoryorder` to *category ascending* or *category descending* if order should be determined by the alphanumerical order of the category names. Set `categoryorder` to "array" to derive the ordering from the attribute `categoryarray`. If a category is not found in the `categoryarray` array, the sorting behavior for that attribute will be identical to the "trace" mode. The unspecified categories will follow the categories in `categoryarray`. Set `categoryorder` to *total ascending* or *total descending* if order should be determined by the numerical order of the values. Similarly, the order can be determined by the min, max, sum, mean or median of all the values. color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. gridcolor Sets the color of the grid lines. gridwidth Sets the width (in px) of the grid lines. hoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" layer Sets the layer on which this axis is displayed. If *above traces*, this axis is displayed above all the subplot's traces If *below traces*, this axis is displayed below all the subplot's traces, but above the grid lines. Useful when used together with scatter-like traces with `cliponaxis` set to False to show markers and/or text nodes above this axis. linecolor Sets the axis line color. linewidth Sets the width (in px) of the axis line. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". range Sets the range of this axis. If the axis `type` is "log", then you must take the log of your desired range (e.g. to set the range from 1 to 100, set the range from 0 to 2). If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. rangemode If *tozero*`, the range extends to 0, regardless of the input data If "nonnegative", the range is non-negative, regardless of the input data. If "normal", the range is computed in relation to the extrema of the input data (same behavior as for cartesian axes). separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showgrid Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. showline Determines whether or not a line bounding this axis is drawn. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. side Determines on which side of radial axis line the tick and tick labels appear. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the tick font. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.layout.polar.radialaxis .Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.layout.pola r.radialaxis.tickformatstopdefaults), sets the default property values to use for elements of layout.polar.radialaxis.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.layout.polar.radialaxis.Title instance or dict with compatible properties titlefont Deprecated: Please use layout.polar.radialaxis.title.font instead. Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. type Sets the axis type. By default, plotly attempts to determined the axis type by looking into the data of the traces that referenced the axis in question. uirevision Controls persistence of user-driven changes in axis `range`, `autorange`, `angle`, and `title` if in `editable: true` configuration. Defaults to `polar.uirevision`. visible A single toggle to hide the axis while preserving interaction like dragging. Default is true when a cheater plot is present on the axis, otherwise false """ _mapped_properties = {"titlefont": ("title", "font")} def __init__( self, arg=None, angle=None, autorange=None, calendar=None, categoryarray=None, categoryarraysrc=None, categoryorder=None, color=None, dtick=None, exponentformat=None, gridcolor=None, gridwidth=None, hoverformat=None, layer=None, linecolor=None, linewidth=None, nticks=None, range=None, rangemode=None, separatethousands=None, showexponent=None, showgrid=None, showline=None, showticklabels=None, showtickprefix=None, showticksuffix=None, side=None, tick0=None, tickangle=None, tickcolor=None, tickfont=None, tickformat=None, tickformatstops=None, tickformatstopdefaults=None, ticklen=None, tickmode=None, tickprefix=None, ticks=None, ticksuffix=None, ticktext=None, ticktextsrc=None, tickvals=None, tickvalssrc=None, tickwidth=None, title=None, titlefont=None, type=None, uirevision=None, visible=None, **kwargs ): """ Construct a new RadialAxis object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.polar.RadialAxis angle Sets the angle (in degrees) from which the radial axis is drawn. Note that by default, radial axis line on the theta=0 line corresponds to a line pointing right (like what mathematicians prefer). Defaults to the first `polar.sector` angle. autorange Determines whether or not the range of this axis is computed in relation to the input data. See `rangemode` for more info. If `range` is provided, then `autorange` is set to False. calendar Sets the calendar system to use for `range` and `tick0` if this is a date axis. This does not set the calendar for interpreting data on this axis, that's specified in the trace or via the global `layout.calendar` categoryarray Sets the order in which categories on this axis appear. Only has an effect if `categoryorder` is set to "array". Used with `categoryorder`. categoryarraysrc Sets the source reference on plot.ly for categoryarray . categoryorder Specifies the ordering logic for the case of categorical variables. By default, plotly uses "trace", which specifies the order that is present in the data supplied. Set `categoryorder` to *category ascending* or *category descending* if order should be determined by the alphanumerical order of the category names. Set `categoryorder` to "array" to derive the ordering from the attribute `categoryarray`. If a category is not found in the `categoryarray` array, the sorting behavior for that attribute will be identical to the "trace" mode. The unspecified categories will follow the categories in `categoryarray`. Set `categoryorder` to *total ascending* or *total descending* if order should be determined by the numerical order of the values. Similarly, the order can be determined by the min, max, sum, mean or median of all the values. color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. gridcolor Sets the color of the grid lines. gridwidth Sets the width (in px) of the grid lines. hoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" layer Sets the layer on which this axis is displayed. If *above traces*, this axis is displayed above all the subplot's traces If *below traces*, this axis is displayed below all the subplot's traces, but above the grid lines. Useful when used together with scatter-like traces with `cliponaxis` set to False to show markers and/or text nodes above this axis. linecolor Sets the axis line color. linewidth Sets the width (in px) of the axis line. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". range Sets the range of this axis. If the axis `type` is "log", then you must take the log of your desired range (e.g. to set the range from 1 to 100, set the range from 0 to 2). If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. rangemode If *tozero*`, the range extends to 0, regardless of the input data If "nonnegative", the range is non-negative, regardless of the input data. If "normal", the range is computed in relation to the extrema of the input data (same behavior as for cartesian axes). separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showgrid Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. showline Determines whether or not a line bounding this axis is drawn. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. side Determines on which side of radial axis line the tick and tick labels appear. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the tick font. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.layout.polar.radialaxis .Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.layout.pola r.radialaxis.tickformatstopdefaults), sets the default property values to use for elements of layout.polar.radialaxis.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.layout.polar.radialaxis.Title instance or dict with compatible properties titlefont Deprecated: Please use layout.polar.radialaxis.title.font instead. Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. type Sets the axis type. By default, plotly attempts to determined the axis type by looking into the data of the traces that referenced the axis in question. uirevision Controls persistence of user-driven changes in axis `range`, `autorange`, `angle`, and `title` if in `editable: true` configuration. Defaults to `polar.uirevision`. visible A single toggle to hide the axis while preserving interaction like dragging. Default is true when a cheater plot is present on the axis, otherwise false Returns ------- RadialAxis """ super(RadialAxis, self).__init__("radialaxis") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.polar.RadialAxis constructor must be a dict or an instance of plotly.graph_objs.layout.polar.RadialAxis""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.polar import radialaxis as v_radialaxis # Initialize validators # --------------------- self._validators["angle"] = v_radialaxis.AngleValidator() self._validators["autorange"] = v_radialaxis.AutorangeValidator() self._validators["calendar"] = v_radialaxis.CalendarValidator() self._validators["categoryarray"] = v_radialaxis.CategoryarrayValidator() self._validators["categoryarraysrc"] = v_radialaxis.CategoryarraysrcValidator() self._validators["categoryorder"] = v_radialaxis.CategoryorderValidator() self._validators["color"] = v_radialaxis.ColorValidator() self._validators["dtick"] = v_radialaxis.DtickValidator() self._validators["exponentformat"] = v_radialaxis.ExponentformatValidator() self._validators["gridcolor"] = v_radialaxis.GridcolorValidator() self._validators["gridwidth"] = v_radialaxis.GridwidthValidator() self._validators["hoverformat"] = v_radialaxis.HoverformatValidator() self._validators["layer"] = v_radialaxis.LayerValidator() self._validators["linecolor"] = v_radialaxis.LinecolorValidator() self._validators["linewidth"] = v_radialaxis.LinewidthValidator() self._validators["nticks"] = v_radialaxis.NticksValidator() self._validators["range"] = v_radialaxis.RangeValidator() self._validators["rangemode"] = v_radialaxis.RangemodeValidator() self._validators[ "separatethousands" ] = v_radialaxis.SeparatethousandsValidator() self._validators["showexponent"] = v_radialaxis.ShowexponentValidator() self._validators["showgrid"] = v_radialaxis.ShowgridValidator() self._validators["showline"] = v_radialaxis.ShowlineValidator() self._validators["showticklabels"] = v_radialaxis.ShowticklabelsValidator() self._validators["showtickprefix"] = v_radialaxis.ShowtickprefixValidator() self._validators["showticksuffix"] = v_radialaxis.ShowticksuffixValidator() self._validators["side"] = v_radialaxis.SideValidator() self._validators["tick0"] = v_radialaxis.Tick0Validator() self._validators["tickangle"] = v_radialaxis.TickangleValidator() self._validators["tickcolor"] = v_radialaxis.TickcolorValidator() self._validators["tickfont"] = v_radialaxis.TickfontValidator() self._validators["tickformat"] = v_radialaxis.TickformatValidator() self._validators["tickformatstops"] = v_radialaxis.TickformatstopsValidator() self._validators[ "tickformatstopdefaults" ] = v_radialaxis.TickformatstopValidator() self._validators["ticklen"] = v_radialaxis.TicklenValidator() self._validators["tickmode"] = v_radialaxis.TickmodeValidator() self._validators["tickprefix"] = v_radialaxis.TickprefixValidator() self._validators["ticks"] = v_radialaxis.TicksValidator() self._validators["ticksuffix"] = v_radialaxis.TicksuffixValidator() self._validators["ticktext"] = v_radialaxis.TicktextValidator() self._validators["ticktextsrc"] = v_radialaxis.TicktextsrcValidator() self._validators["tickvals"] = v_radialaxis.TickvalsValidator() self._validators["tickvalssrc"] = v_radialaxis.TickvalssrcValidator() self._validators["tickwidth"] = v_radialaxis.TickwidthValidator() self._validators["title"] = v_radialaxis.TitleValidator() self._validators["type"] = v_radialaxis.TypeValidator() self._validators["uirevision"] = v_radialaxis.UirevisionValidator() self._validators["visible"] = v_radialaxis.VisibleValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("angle", None) self["angle"] = angle if angle is not None else _v _v = arg.pop("autorange", None) self["autorange"] = autorange if autorange is not None else _v _v = arg.pop("calendar", None) self["calendar"] = calendar if calendar is not None else _v _v = arg.pop("categoryarray", None) self["categoryarray"] = categoryarray if categoryarray is not None else _v _v = arg.pop("categoryarraysrc", None) self["categoryarraysrc"] = ( categoryarraysrc if categoryarraysrc is not None else _v ) _v = arg.pop("categoryorder", None) self["categoryorder"] = categoryorder if categoryorder is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("dtick", None) self["dtick"] = dtick if dtick is not None else _v _v = arg.pop("exponentformat", None) self["exponentformat"] = exponentformat if exponentformat is not None else _v _v = arg.pop("gridcolor", None) self["gridcolor"] = gridcolor if gridcolor is not None else _v _v = arg.pop("gridwidth", None) self["gridwidth"] = gridwidth if gridwidth is not None else _v _v = arg.pop("hoverformat", None) self["hoverformat"] = hoverformat if hoverformat is not None else _v _v = arg.pop("layer", None) self["layer"] = layer if layer is not None else _v _v = arg.pop("linecolor", None) self["linecolor"] = linecolor if linecolor is not None else _v _v = arg.pop("linewidth", None) self["linewidth"] = linewidth if linewidth is not None else _v _v = arg.pop("nticks", None) self["nticks"] = nticks if nticks is not None else _v _v = arg.pop("range", None) self["range"] = range if range is not None else _v _v = arg.pop("rangemode", None) self["rangemode"] = rangemode if rangemode is not None else _v _v = arg.pop("separatethousands", None) self["separatethousands"] = ( separatethousands if separatethousands is not None else _v ) _v = arg.pop("showexponent", None) self["showexponent"] = showexponent if showexponent is not None else _v _v = arg.pop("showgrid", None) self["showgrid"] = showgrid if showgrid is not None else _v _v = arg.pop("showline", None) self["showline"] = showline if showline is not None else _v _v = arg.pop("showticklabels", None) self["showticklabels"] = showticklabels if showticklabels is not None else _v _v = arg.pop("showtickprefix", None) self["showtickprefix"] = showtickprefix if showtickprefix is not None else _v _v = arg.pop("showticksuffix", None) self["showticksuffix"] = showticksuffix if showticksuffix is not None else _v _v = arg.pop("side", None) self["side"] = side if side is not None else _v _v = arg.pop("tick0", None) self["tick0"] = tick0 if tick0 is not None else _v _v = arg.pop("tickangle", None) self["tickangle"] = tickangle if tickangle is not None else _v _v = arg.pop("tickcolor", None) self["tickcolor"] = tickcolor if tickcolor is not None else _v _v = arg.pop("tickfont", None) self["tickfont"] = tickfont if tickfont is not None else _v _v = arg.pop("tickformat", None) self["tickformat"] = tickformat if tickformat is not None else _v _v = arg.pop("tickformatstops", None) self["tickformatstops"] = tickformatstops if tickformatstops is not None else _v _v = arg.pop("tickformatstopdefaults", None) self["tickformatstopdefaults"] = ( tickformatstopdefaults if tickformatstopdefaults is not None else _v ) _v = arg.pop("ticklen", None) self["ticklen"] = ticklen if ticklen is not None else _v _v = arg.pop("tickmode", None) self["tickmode"] = tickmode if tickmode is not None else _v _v = arg.pop("tickprefix", None) self["tickprefix"] = tickprefix if tickprefix is not None else _v _v = arg.pop("ticks", None) self["ticks"] = ticks if ticks is not None else _v _v = arg.pop("ticksuffix", None) self["ticksuffix"] = ticksuffix if ticksuffix is not None else _v _v = arg.pop("ticktext", None) self["ticktext"] = ticktext if ticktext is not None else _v _v = arg.pop("ticktextsrc", None) self["ticktextsrc"] = ticktextsrc if ticktextsrc is not None else _v _v = arg.pop("tickvals", None) self["tickvals"] = tickvals if tickvals is not None else _v _v = arg.pop("tickvalssrc", None) self["tickvalssrc"] = tickvalssrc if tickvalssrc is not None else _v _v = arg.pop("tickwidth", None) self["tickwidth"] = tickwidth if tickwidth is not None else _v _v = arg.pop("title", None) self["title"] = title if title is not None else _v _v = arg.pop("titlefont", None) _v = titlefont if titlefont is not None else _v if _v is not None: self["titlefont"] = _v _v = arg.pop("type", None) self["type"] = type if type is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Domain(_BaseLayoutHierarchyType): # column # ------ @property def column(self): """ If there is a layout grid, use the domain for this column in the grid for this polar subplot . The 'column' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["column"] @column.setter def column(self, val): self["column"] = val # row # --- @property def row(self): """ If there is a layout grid, use the domain for this row in the grid for this polar subplot . The 'row' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["row"] @row.setter def row(self, val): self["row"] = val # x # - @property def x(self): """ Sets the horizontal domain of this polar subplot (in plot fraction). The 'x' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'x[0]' property is a number and may be specified as: - An int or float in the interval [0, 1] (1) The 'x[1]' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- list """ return self["x"] @x.setter def x(self, val): self["x"] = val # y # - @property def y(self): """ Sets the vertical domain of this polar subplot (in plot fraction). The 'y' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'y[0]' property is a number and may be specified as: - An int or float in the interval [0, 1] (1) The 'y[1]' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- list """ return self["y"] @y.setter def y(self, val): self["y"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.polar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ column If there is a layout grid, use the domain for this column in the grid for this polar subplot . row If there is a layout grid, use the domain for this row in the grid for this polar subplot . x Sets the horizontal domain of this polar subplot (in plot fraction). y Sets the vertical domain of this polar subplot (in plot fraction). """ def __init__(self, arg=None, column=None, row=None, x=None, y=None, **kwargs): """ Construct a new Domain object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.polar.Domain column If there is a layout grid, use the domain for this column in the grid for this polar subplot . row If there is a layout grid, use the domain for this row in the grid for this polar subplot . x Sets the horizontal domain of this polar subplot (in plot fraction). y Sets the vertical domain of this polar subplot (in plot fraction). Returns ------- Domain """ super(Domain, self).__init__("domain") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.polar.Domain constructor must be a dict or an instance of plotly.graph_objs.layout.polar.Domain""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.polar import domain as v_domain # Initialize validators # --------------------- self._validators["column"] = v_domain.ColumnValidator() self._validators["row"] = v_domain.RowValidator() self._validators["x"] = v_domain.XValidator() self._validators["y"] = v_domain.YValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("column", None) self["column"] = column if column is not None else _v _v = arg.pop("row", None) self["row"] = row if row is not None else _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class AngularAxis(_BaseLayoutHierarchyType): # categoryarray # ------------- @property def categoryarray(self): """ Sets the order in which categories on this axis appear. Only has an effect if `categoryorder` is set to "array". Used with `categoryorder`. The 'categoryarray' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["categoryarray"] @categoryarray.setter def categoryarray(self, val): self["categoryarray"] = val # categoryarraysrc # ---------------- @property def categoryarraysrc(self): """ Sets the source reference on plot.ly for categoryarray . The 'categoryarraysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["categoryarraysrc"] @categoryarraysrc.setter def categoryarraysrc(self, val): self["categoryarraysrc"] = val # categoryorder # ------------- @property def categoryorder(self): """ Specifies the ordering logic for the case of categorical variables. By default, plotly uses "trace", which specifies the order that is present in the data supplied. Set `categoryorder` to *category ascending* or *category descending* if order should be determined by the alphanumerical order of the category names. Set `categoryorder` to "array" to derive the ordering from the attribute `categoryarray`. If a category is not found in the `categoryarray` array, the sorting behavior for that attribute will be identical to the "trace" mode. The unspecified categories will follow the categories in `categoryarray`. Set `categoryorder` to *total ascending* or *total descending* if order should be determined by the numerical order of the values. Similarly, the order can be determined by the min, max, sum, mean or median of all the values. The 'categoryorder' property is an enumeration that may be specified as: - One of the following enumeration values: ['trace', 'category ascending', 'category descending', 'array', 'total ascending', 'total descending', 'min ascending', 'min descending', 'max ascending', 'max descending', 'sum ascending', 'sum descending', 'mean ascending', 'mean descending', 'median ascending', 'median descending'] Returns ------- Any """ return self["categoryorder"] @categoryorder.setter def categoryorder(self, val): self["categoryorder"] = val # color # ----- @property def color(self): """ Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # direction # --------- @property def direction(self): """ Sets the direction corresponding to positive angles. The 'direction' property is an enumeration that may be specified as: - One of the following enumeration values: ['counterclockwise', 'clockwise'] Returns ------- Any """ return self["direction"] @direction.setter def direction(self, val): self["direction"] = val # dtick # ----- @property def dtick(self): """ Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" The 'dtick' property accepts values of any type Returns ------- Any """ return self["dtick"] @dtick.setter def dtick(self, val): self["dtick"] = val # exponentformat # -------------- @property def exponentformat(self): """ Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. The 'exponentformat' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'e', 'E', 'power', 'SI', 'B'] Returns ------- Any """ return self["exponentformat"] @exponentformat.setter def exponentformat(self, val): self["exponentformat"] = val # gridcolor # --------- @property def gridcolor(self): """ Sets the color of the grid lines. The 'gridcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["gridcolor"] @gridcolor.setter def gridcolor(self, val): self["gridcolor"] = val # gridwidth # --------- @property def gridwidth(self): """ Sets the width (in px) of the grid lines. The 'gridwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["gridwidth"] @gridwidth.setter def gridwidth(self, val): self["gridwidth"] = val # hoverformat # ----------- @property def hoverformat(self): """ Sets the hover text formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'hoverformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["hoverformat"] @hoverformat.setter def hoverformat(self, val): self["hoverformat"] = val # layer # ----- @property def layer(self): """ Sets the layer on which this axis is displayed. If *above traces*, this axis is displayed above all the subplot's traces If *below traces*, this axis is displayed below all the subplot's traces, but above the grid lines. Useful when used together with scatter-like traces with `cliponaxis` set to False to show markers and/or text nodes above this axis. The 'layer' property is an enumeration that may be specified as: - One of the following enumeration values: ['above traces', 'below traces'] Returns ------- Any """ return self["layer"] @layer.setter def layer(self, val): self["layer"] = val # linecolor # --------- @property def linecolor(self): """ Sets the axis line color. The 'linecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["linecolor"] @linecolor.setter def linecolor(self, val): self["linecolor"] = val # linewidth # --------- @property def linewidth(self): """ Sets the width (in px) of the axis line. The 'linewidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["linewidth"] @linewidth.setter def linewidth(self, val): self["linewidth"] = val # nticks # ------ @property def nticks(self): """ Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". The 'nticks' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nticks"] @nticks.setter def nticks(self, val): self["nticks"] = val # period # ------ @property def period(self): """ Set the angular period. Has an effect only when `angularaxis.type` is "category". The 'period' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["period"] @period.setter def period(self, val): self["period"] = val # rotation # -------- @property def rotation(self): """ Sets that start position (in degrees) of the angular axis By default, polar subplots with `direction` set to "counterclockwise" get a `rotation` of 0 which corresponds to due East (like what mathematicians prefer). In turn, polar with `direction` set to "clockwise" get a rotation of 90 which corresponds to due North (like on a compass), The 'rotation' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["rotation"] @rotation.setter def rotation(self, val): self["rotation"] = val # separatethousands # ----------------- @property def separatethousands(self): """ If "true", even 4-digit integers are separated The 'separatethousands' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["separatethousands"] @separatethousands.setter def separatethousands(self, val): self["separatethousands"] = val # showexponent # ------------ @property def showexponent(self): """ If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. The 'showexponent' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showexponent"] @showexponent.setter def showexponent(self, val): self["showexponent"] = val # showgrid # -------- @property def showgrid(self): """ Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. The 'showgrid' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showgrid"] @showgrid.setter def showgrid(self, val): self["showgrid"] = val # showline # -------- @property def showline(self): """ Determines whether or not a line bounding this axis is drawn. The 'showline' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showline"] @showline.setter def showline(self, val): self["showline"] = val # showticklabels # -------------- @property def showticklabels(self): """ Determines whether or not the tick labels are drawn. The 'showticklabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showticklabels"] @showticklabels.setter def showticklabels(self, val): self["showticklabels"] = val # showtickprefix # -------------- @property def showtickprefix(self): """ If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. The 'showtickprefix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showtickprefix"] @showtickprefix.setter def showtickprefix(self, val): self["showtickprefix"] = val # showticksuffix # -------------- @property def showticksuffix(self): """ Same as `showtickprefix` but for tick suffixes. The 'showticksuffix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showticksuffix"] @showticksuffix.setter def showticksuffix(self, val): self["showticksuffix"] = val # thetaunit # --------- @property def thetaunit(self): """ Sets the format unit of the formatted "theta" values. Has an effect only when `angularaxis.type` is "linear". The 'thetaunit' property is an enumeration that may be specified as: - One of the following enumeration values: ['radians', 'degrees'] Returns ------- Any """ return self["thetaunit"] @thetaunit.setter def thetaunit(self, val): self["thetaunit"] = val # tick0 # ----- @property def tick0(self): """ Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. The 'tick0' property accepts values of any type Returns ------- Any """ return self["tick0"] @tick0.setter def tick0(self, val): self["tick0"] = val # tickangle # --------- @property def tickangle(self): """ Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. The 'tickangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["tickangle"] @tickangle.setter def tickangle(self, val): self["tickangle"] = val # tickcolor # --------- @property def tickcolor(self): """ Sets the tick color. The 'tickcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["tickcolor"] @tickcolor.setter def tickcolor(self, val): self["tickcolor"] = val # tickfont # -------- @property def tickfont(self): """ Sets the tick font. The 'tickfont' property is an instance of Tickfont that may be specified as: - An instance of plotly.graph_objs.layout.polar.angularaxis.Tickfont - A dict of string/value properties that will be passed to the Tickfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.layout.polar.angularaxis.Tickfont """ return self["tickfont"] @tickfont.setter def tickfont(self, val): self["tickfont"] = val # tickformat # ---------- @property def tickformat(self): """ Sets the tick label formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'tickformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickformat"] @tickformat.setter def tickformat(self, val): self["tickformat"] = val # tickformatstops # --------------- @property def tickformatstops(self): """ The 'tickformatstops' property is a tuple of instances of Tickformatstop that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.polar.angularaxis.Tickformatstop - A list or tuple of dicts of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- tuple[plotly.graph_objs.layout.polar.angularaxis.Tickformatstop] """ return self["tickformatstops"] @tickformatstops.setter def tickformatstops(self, val): self["tickformatstops"] = val # tickformatstopdefaults # ---------------------- @property def tickformatstopdefaults(self): """ When used in a template (as layout.template.layout.polar.angula raxis.tickformatstopdefaults), sets the default property values to use for elements of layout.polar.angularaxis.tickformatstops The 'tickformatstopdefaults' property is an instance of Tickformatstop that may be specified as: - An instance of plotly.graph_objs.layout.polar.angularaxis.Tickformatstop - A dict of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: Returns ------- plotly.graph_objs.layout.polar.angularaxis.Tickformatstop """ return self["tickformatstopdefaults"] @tickformatstopdefaults.setter def tickformatstopdefaults(self, val): self["tickformatstopdefaults"] = val # ticklen # ------- @property def ticklen(self): """ Sets the tick length (in px). The 'ticklen' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ticklen"] @ticklen.setter def ticklen(self, val): self["ticklen"] = val # tickmode # -------- @property def tickmode(self): """ Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). The 'tickmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'linear', 'array'] Returns ------- Any """ return self["tickmode"] @tickmode.setter def tickmode(self, val): self["tickmode"] = val # tickprefix # ---------- @property def tickprefix(self): """ Sets a tick label prefix. The 'tickprefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickprefix"] @tickprefix.setter def tickprefix(self, val): self["tickprefix"] = val # ticks # ----- @property def ticks(self): """ Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. The 'ticks' property is an enumeration that may be specified as: - One of the following enumeration values: ['outside', 'inside', ''] Returns ------- Any """ return self["ticks"] @ticks.setter def ticks(self, val): self["ticks"] = val # ticksuffix # ---------- @property def ticksuffix(self): """ Sets a tick label suffix. The 'ticksuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ticksuffix"] @ticksuffix.setter def ticksuffix(self, val): self["ticksuffix"] = val # ticktext # -------- @property def ticktext(self): """ Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. The 'ticktext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ticktext"] @ticktext.setter def ticktext(self, val): self["ticktext"] = val # ticktextsrc # ----------- @property def ticktextsrc(self): """ Sets the source reference on plot.ly for ticktext . The 'ticktextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ticktextsrc"] @ticktextsrc.setter def ticktextsrc(self, val): self["ticktextsrc"] = val # tickvals # -------- @property def tickvals(self): """ Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. The 'tickvals' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["tickvals"] @tickvals.setter def tickvals(self, val): self["tickvals"] = val # tickvalssrc # ----------- @property def tickvalssrc(self): """ Sets the source reference on plot.ly for tickvals . The 'tickvalssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tickvalssrc"] @tickvalssrc.setter def tickvalssrc(self, val): self["tickvalssrc"] = val # tickwidth # --------- @property def tickwidth(self): """ Sets the tick width (in px). The 'tickwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["tickwidth"] @tickwidth.setter def tickwidth(self, val): self["tickwidth"] = val # type # ---- @property def type(self): """ Sets the angular axis type. If "linear", set `thetaunit` to determine the unit in which axis value are shown. If *category, use `period` to set the number of integer coordinates around polar axis. The 'type' property is an enumeration that may be specified as: - One of the following enumeration values: ['-', 'linear', 'category'] Returns ------- Any """ return self["type"] @type.setter def type(self, val): self["type"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of user-driven changes in axis `rotation`. Defaults to `polar.uirevision`. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # visible # ------- @property def visible(self): """ A single toggle to hide the axis while preserving interaction like dragging. Default is true when a cheater plot is present on the axis, otherwise false The 'visible' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.polar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ categoryarray Sets the order in which categories on this axis appear. Only has an effect if `categoryorder` is set to "array". Used with `categoryorder`. categoryarraysrc Sets the source reference on plot.ly for categoryarray . categoryorder Specifies the ordering logic for the case of categorical variables. By default, plotly uses "trace", which specifies the order that is present in the data supplied. Set `categoryorder` to *category ascending* or *category descending* if order should be determined by the alphanumerical order of the category names. Set `categoryorder` to "array" to derive the ordering from the attribute `categoryarray`. If a category is not found in the `categoryarray` array, the sorting behavior for that attribute will be identical to the "trace" mode. The unspecified categories will follow the categories in `categoryarray`. Set `categoryorder` to *total ascending* or *total descending* if order should be determined by the numerical order of the values. Similarly, the order can be determined by the min, max, sum, mean or median of all the values. color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. direction Sets the direction corresponding to positive angles. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. gridcolor Sets the color of the grid lines. gridwidth Sets the width (in px) of the grid lines. hoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" layer Sets the layer on which this axis is displayed. If *above traces*, this axis is displayed above all the subplot's traces If *below traces*, this axis is displayed below all the subplot's traces, but above the grid lines. Useful when used together with scatter-like traces with `cliponaxis` set to False to show markers and/or text nodes above this axis. linecolor Sets the axis line color. linewidth Sets the width (in px) of the axis line. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". period Set the angular period. Has an effect only when `angularaxis.type` is "category". rotation Sets that start position (in degrees) of the angular axis By default, polar subplots with `direction` set to "counterclockwise" get a `rotation` of 0 which corresponds to due East (like what mathematicians prefer). In turn, polar with `direction` set to "clockwise" get a rotation of 90 which corresponds to due North (like on a compass), separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showgrid Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. showline Determines whether or not a line bounding this axis is drawn. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thetaunit Sets the format unit of the formatted "theta" values. Has an effect only when `angularaxis.type` is "linear". tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the tick font. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.layout.polar.angularaxi s.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.layout.pola r.angularaxis.tickformatstopdefaults), sets the default property values to use for elements of layout.polar.angularaxis.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). type Sets the angular axis type. If "linear", set `thetaunit` to determine the unit in which axis value are shown. If *category, use `period` to set the number of integer coordinates around polar axis. uirevision Controls persistence of user-driven changes in axis `rotation`. Defaults to `polar.uirevision`. visible A single toggle to hide the axis while preserving interaction like dragging. Default is true when a cheater plot is present on the axis, otherwise false """ def __init__( self, arg=None, categoryarray=None, categoryarraysrc=None, categoryorder=None, color=None, direction=None, dtick=None, exponentformat=None, gridcolor=None, gridwidth=None, hoverformat=None, layer=None, linecolor=None, linewidth=None, nticks=None, period=None, rotation=None, separatethousands=None, showexponent=None, showgrid=None, showline=None, showticklabels=None, showtickprefix=None, showticksuffix=None, thetaunit=None, tick0=None, tickangle=None, tickcolor=None, tickfont=None, tickformat=None, tickformatstops=None, tickformatstopdefaults=None, ticklen=None, tickmode=None, tickprefix=None, ticks=None, ticksuffix=None, ticktext=None, ticktextsrc=None, tickvals=None, tickvalssrc=None, tickwidth=None, type=None, uirevision=None, visible=None, **kwargs ): """ Construct a new AngularAxis object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.polar.AngularAxis categoryarray Sets the order in which categories on this axis appear. Only has an effect if `categoryorder` is set to "array". Used with `categoryorder`. categoryarraysrc Sets the source reference on plot.ly for categoryarray . categoryorder Specifies the ordering logic for the case of categorical variables. By default, plotly uses "trace", which specifies the order that is present in the data supplied. Set `categoryorder` to *category ascending* or *category descending* if order should be determined by the alphanumerical order of the category names. Set `categoryorder` to "array" to derive the ordering from the attribute `categoryarray`. If a category is not found in the `categoryarray` array, the sorting behavior for that attribute will be identical to the "trace" mode. The unspecified categories will follow the categories in `categoryarray`. Set `categoryorder` to *total ascending* or *total descending* if order should be determined by the numerical order of the values. Similarly, the order can be determined by the min, max, sum, mean or median of all the values. color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. direction Sets the direction corresponding to positive angles. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. gridcolor Sets the color of the grid lines. gridwidth Sets the width (in px) of the grid lines. hoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" layer Sets the layer on which this axis is displayed. If *above traces*, this axis is displayed above all the subplot's traces If *below traces*, this axis is displayed below all the subplot's traces, but above the grid lines. Useful when used together with scatter-like traces with `cliponaxis` set to False to show markers and/or text nodes above this axis. linecolor Sets the axis line color. linewidth Sets the width (in px) of the axis line. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". period Set the angular period. Has an effect only when `angularaxis.type` is "category". rotation Sets that start position (in degrees) of the angular axis By default, polar subplots with `direction` set to "counterclockwise" get a `rotation` of 0 which corresponds to due East (like what mathematicians prefer). In turn, polar with `direction` set to "clockwise" get a rotation of 90 which corresponds to due North (like on a compass), separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showgrid Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. showline Determines whether or not a line bounding this axis is drawn. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thetaunit Sets the format unit of the formatted "theta" values. Has an effect only when `angularaxis.type` is "linear". tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the tick font. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.layout.polar.angularaxi s.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.layout.pola r.angularaxis.tickformatstopdefaults), sets the default property values to use for elements of layout.polar.angularaxis.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). type Sets the angular axis type. If "linear", set `thetaunit` to determine the unit in which axis value are shown. If *category, use `period` to set the number of integer coordinates around polar axis. uirevision Controls persistence of user-driven changes in axis `rotation`. Defaults to `polar.uirevision`. visible A single toggle to hide the axis while preserving interaction like dragging. Default is true when a cheater plot is present on the axis, otherwise false Returns ------- AngularAxis """ super(AngularAxis, self).__init__("angularaxis") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.polar.AngularAxis constructor must be a dict or an instance of plotly.graph_objs.layout.polar.AngularAxis""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.polar import angularaxis as v_angularaxis # Initialize validators # --------------------- self._validators["categoryarray"] = v_angularaxis.CategoryarrayValidator() self._validators["categoryarraysrc"] = v_angularaxis.CategoryarraysrcValidator() self._validators["categoryorder"] = v_angularaxis.CategoryorderValidator() self._validators["color"] = v_angularaxis.ColorValidator() self._validators["direction"] = v_angularaxis.DirectionValidator() self._validators["dtick"] = v_angularaxis.DtickValidator() self._validators["exponentformat"] = v_angularaxis.ExponentformatValidator() self._validators["gridcolor"] = v_angularaxis.GridcolorValidator() self._validators["gridwidth"] = v_angularaxis.GridwidthValidator() self._validators["hoverformat"] = v_angularaxis.HoverformatValidator() self._validators["layer"] = v_angularaxis.LayerValidator() self._validators["linecolor"] = v_angularaxis.LinecolorValidator() self._validators["linewidth"] = v_angularaxis.LinewidthValidator() self._validators["nticks"] = v_angularaxis.NticksValidator() self._validators["period"] = v_angularaxis.PeriodValidator() self._validators["rotation"] = v_angularaxis.RotationValidator() self._validators[ "separatethousands" ] = v_angularaxis.SeparatethousandsValidator() self._validators["showexponent"] = v_angularaxis.ShowexponentValidator() self._validators["showgrid"] = v_angularaxis.ShowgridValidator() self._validators["showline"] = v_angularaxis.ShowlineValidator() self._validators["showticklabels"] = v_angularaxis.ShowticklabelsValidator() self._validators["showtickprefix"] = v_angularaxis.ShowtickprefixValidator() self._validators["showticksuffix"] = v_angularaxis.ShowticksuffixValidator() self._validators["thetaunit"] = v_angularaxis.ThetaunitValidator() self._validators["tick0"] = v_angularaxis.Tick0Validator() self._validators["tickangle"] = v_angularaxis.TickangleValidator() self._validators["tickcolor"] = v_angularaxis.TickcolorValidator() self._validators["tickfont"] = v_angularaxis.TickfontValidator() self._validators["tickformat"] = v_angularaxis.TickformatValidator() self._validators["tickformatstops"] = v_angularaxis.TickformatstopsValidator() self._validators[ "tickformatstopdefaults" ] = v_angularaxis.TickformatstopValidator() self._validators["ticklen"] = v_angularaxis.TicklenValidator() self._validators["tickmode"] = v_angularaxis.TickmodeValidator() self._validators["tickprefix"] = v_angularaxis.TickprefixValidator() self._validators["ticks"] = v_angularaxis.TicksValidator() self._validators["ticksuffix"] = v_angularaxis.TicksuffixValidator() self._validators["ticktext"] = v_angularaxis.TicktextValidator() self._validators["ticktextsrc"] = v_angularaxis.TicktextsrcValidator() self._validators["tickvals"] = v_angularaxis.TickvalsValidator() self._validators["tickvalssrc"] = v_angularaxis.TickvalssrcValidator() self._validators["tickwidth"] = v_angularaxis.TickwidthValidator() self._validators["type"] = v_angularaxis.TypeValidator() self._validators["uirevision"] = v_angularaxis.UirevisionValidator() self._validators["visible"] = v_angularaxis.VisibleValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("categoryarray", None) self["categoryarray"] = categoryarray if categoryarray is not None else _v _v = arg.pop("categoryarraysrc", None) self["categoryarraysrc"] = ( categoryarraysrc if categoryarraysrc is not None else _v ) _v = arg.pop("categoryorder", None) self["categoryorder"] = categoryorder if categoryorder is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("direction", None) self["direction"] = direction if direction is not None else _v _v = arg.pop("dtick", None) self["dtick"] = dtick if dtick is not None else _v _v = arg.pop("exponentformat", None) self["exponentformat"] = exponentformat if exponentformat is not None else _v _v = arg.pop("gridcolor", None) self["gridcolor"] = gridcolor if gridcolor is not None else _v _v = arg.pop("gridwidth", None) self["gridwidth"] = gridwidth if gridwidth is not None else _v _v = arg.pop("hoverformat", None) self["hoverformat"] = hoverformat if hoverformat is not None else _v _v = arg.pop("layer", None) self["layer"] = layer if layer is not None else _v _v = arg.pop("linecolor", None) self["linecolor"] = linecolor if linecolor is not None else _v _v = arg.pop("linewidth", None) self["linewidth"] = linewidth if linewidth is not None else _v _v = arg.pop("nticks", None) self["nticks"] = nticks if nticks is not None else _v _v = arg.pop("period", None) self["period"] = period if period is not None else _v _v = arg.pop("rotation", None) self["rotation"] = rotation if rotation is not None else _v _v = arg.pop("separatethousands", None) self["separatethousands"] = ( separatethousands if separatethousands is not None else _v ) _v = arg.pop("showexponent", None) self["showexponent"] = showexponent if showexponent is not None else _v _v = arg.pop("showgrid", None) self["showgrid"] = showgrid if showgrid is not None else _v _v = arg.pop("showline", None) self["showline"] = showline if showline is not None else _v _v = arg.pop("showticklabels", None) self["showticklabels"] = showticklabels if showticklabels is not None else _v _v = arg.pop("showtickprefix", None) self["showtickprefix"] = showtickprefix if showtickprefix is not None else _v _v = arg.pop("showticksuffix", None) self["showticksuffix"] = showticksuffix if showticksuffix is not None else _v _v = arg.pop("thetaunit", None) self["thetaunit"] = thetaunit if thetaunit is not None else _v _v = arg.pop("tick0", None) self["tick0"] = tick0 if tick0 is not None else _v _v = arg.pop("tickangle", None) self["tickangle"] = tickangle if tickangle is not None else _v _v = arg.pop("tickcolor", None) self["tickcolor"] = tickcolor if tickcolor is not None else _v _v = arg.pop("tickfont", None) self["tickfont"] = tickfont if tickfont is not None else _v _v = arg.pop("tickformat", None) self["tickformat"] = tickformat if tickformat is not None else _v _v = arg.pop("tickformatstops", None) self["tickformatstops"] = tickformatstops if tickformatstops is not None else _v _v = arg.pop("tickformatstopdefaults", None) self["tickformatstopdefaults"] = ( tickformatstopdefaults if tickformatstopdefaults is not None else _v ) _v = arg.pop("ticklen", None) self["ticklen"] = ticklen if ticklen is not None else _v _v = arg.pop("tickmode", None) self["tickmode"] = tickmode if tickmode is not None else _v _v = arg.pop("tickprefix", None) self["tickprefix"] = tickprefix if tickprefix is not None else _v _v = arg.pop("ticks", None) self["ticks"] = ticks if ticks is not None else _v _v = arg.pop("ticksuffix", None) self["ticksuffix"] = ticksuffix if ticksuffix is not None else _v _v = arg.pop("ticktext", None) self["ticktext"] = ticktext if ticktext is not None else _v _v = arg.pop("ticktextsrc", None) self["ticktextsrc"] = ticktextsrc if ticktextsrc is not None else _v _v = arg.pop("tickvals", None) self["tickvals"] = tickvals if tickvals is not None else _v _v = arg.pop("tickvalssrc", None) self["tickvalssrc"] = tickvalssrc if tickvalssrc is not None else _v _v = arg.pop("tickwidth", None) self["tickwidth"] = tickwidth if tickwidth is not None else _v _v = arg.pop("type", None) self["type"] = type if type is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["AngularAxis", "Domain", "RadialAxis", "angularaxis", "radialaxis"] from plotly.graph_objs.layout.polar import radialaxis from plotly.graph_objs.layout.polar import angularaxis plotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/scene/0000755000175000017500000000000013573746613022343 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/scene/annotation/0000755000175000017500000000000013573746613024515 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/scene/annotation/hoverlabel/0000755000175000017500000000000013573746613026640 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/scene/annotation/hoverlabel/__init__.py0000644000175000017500000002062613573721547030756 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Font(_BaseLayoutHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.scene.annotation.hoverlabel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets the hover label text font. By default uses the global hover font and size, with color from `hoverlabel.bordercolor`. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.scene.annotatio n.hoverlabel.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.scene.annotation.hoverlabel.Font constructor must be a dict or an instance of plotly.graph_objs.layout.scene.annotation.hoverlabel.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.scene.annotation.hoverlabel import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/scene/annotation/__init__.py0000644000175000017500000004657313573721547026644 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Hoverlabel(_BaseLayoutHierarchyType): # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the hover label. By default uses the annotation's `bgcolor` made opaque, or white if it was transparent. The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the border color of the hover label. By default uses either dark grey or white, for maximum contrast with `hoverlabel.bgcolor`. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # font # ---- @property def font(self): """ Sets the hover label text font. By default uses the global hover font and size, with color from `hoverlabel.bordercolor`. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.layout.scene.annotation.hoverlabel.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.layout.scene.annotation.hoverlabel.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.scene.annotation" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ bgcolor Sets the background color of the hover label. By default uses the annotation's `bgcolor` made opaque, or white if it was transparent. bordercolor Sets the border color of the hover label. By default uses either dark grey or white, for maximum contrast with `hoverlabel.bgcolor`. font Sets the hover label text font. By default uses the global hover font and size, with color from `hoverlabel.bordercolor`. """ def __init__(self, arg=None, bgcolor=None, bordercolor=None, font=None, **kwargs): """ Construct a new Hoverlabel object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.scene.annotation.Hoverlabel bgcolor Sets the background color of the hover label. By default uses the annotation's `bgcolor` made opaque, or white if it was transparent. bordercolor Sets the border color of the hover label. By default uses either dark grey or white, for maximum contrast with `hoverlabel.bgcolor`. font Sets the hover label text font. By default uses the global hover font and size, with color from `hoverlabel.bordercolor`. Returns ------- Hoverlabel """ super(Hoverlabel, self).__init__("hoverlabel") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.scene.annotation.Hoverlabel constructor must be a dict or an instance of plotly.graph_objs.layout.scene.annotation.Hoverlabel""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.scene.annotation import hoverlabel as v_hoverlabel # Initialize validators # --------------------- self._validators["bgcolor"] = v_hoverlabel.BgcolorValidator() self._validators["bordercolor"] = v_hoverlabel.BordercolorValidator() self._validators["font"] = v_hoverlabel.FontValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Font(_BaseLayoutHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.scene.annotation" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets the annotation text font. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.scene.annotation.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.scene.annotation.Font constructor must be a dict or an instance of plotly.graph_objs.layout.scene.annotation.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.scene.annotation import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font", "Hoverlabel", "hoverlabel"] from plotly.graph_objs.layout.scene.annotation import hoverlabel plotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/scene/yaxis/0000755000175000017500000000000013573746613023500 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/scene/yaxis/title/0000755000175000017500000000000013573746613024621 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/scene/yaxis/title/__init__.py0000644000175000017500000002054313573721547026735 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Font(_BaseLayoutHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.scene.yaxis.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.scene.yaxis.title.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.scene.yaxis.title.Font constructor must be a dict or an instance of plotly.graph_objs.layout.scene.yaxis.title.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.scene.yaxis.title import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/scene/yaxis/__init__.py0000644000175000017500000005631413573721550025613 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Title(_BaseLayoutHierarchyType): # font # ---- @property def font(self): """ Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.layout.scene.yaxis.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.layout.scene.yaxis.title.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # text # ---- @property def text(self): """ Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.scene.yaxis" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. text Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """ def __init__(self, arg=None, font=None, text=None, **kwargs): """ Construct a new Title object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.scene.yaxis.Title font Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. text Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- Title """ super(Title, self).__init__("title") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.scene.yaxis.Title constructor must be a dict or an instance of plotly.graph_objs.layout.scene.yaxis.Title""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.scene.yaxis import title as v_title # Initialize validators # --------------------- self._validators["font"] = v_title.FontValidator() self._validators["text"] = v_title.TextValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Tickformatstop(_BaseLayoutHierarchyType): # dtickrange # ---------- @property def dtickrange(self): """ range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" The 'dtickrange' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'dtickrange[0]' property accepts values of any type (1) The 'dtickrange[1]' property accepts values of any type Returns ------- list """ return self["dtickrange"] @dtickrange.setter def dtickrange(self, val): self["dtickrange"] = val # enabled # ------- @property def enabled(self): """ Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. The 'enabled' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["enabled"] @enabled.setter def enabled(self, val): self["enabled"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # value # ----- @property def value(self): """ string - dtickformat for described zoom level, the same as "tickformat" The 'value' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.scene.yaxis" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """ def __init__( self, arg=None, dtickrange=None, enabled=None, name=None, templateitemname=None, value=None, **kwargs ): """ Construct a new Tickformatstop object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.scene.yaxis.Tickformatstop dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- Tickformatstop """ super(Tickformatstop, self).__init__("tickformatstops") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.scene.yaxis.Tickformatstop constructor must be a dict or an instance of plotly.graph_objs.layout.scene.yaxis.Tickformatstop""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.scene.yaxis import ( tickformatstop as v_tickformatstop, ) # Initialize validators # --------------------- self._validators["dtickrange"] = v_tickformatstop.DtickrangeValidator() self._validators["enabled"] = v_tickformatstop.EnabledValidator() self._validators["name"] = v_tickformatstop.NameValidator() self._validators[ "templateitemname" ] = v_tickformatstop.TemplateitemnameValidator() self._validators["value"] = v_tickformatstop.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtickrange", None) self["dtickrange"] = dtickrange if dtickrange is not None else _v _v = arg.pop("enabled", None) self["enabled"] = enabled if enabled is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Tickfont(_BaseLayoutHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.scene.yaxis" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Tickfont object Sets the tick font. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.scene.yaxis.Tickfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Tickfont """ super(Tickfont, self).__init__("tickfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.scene.yaxis.Tickfont constructor must be a dict or an instance of plotly.graph_objs.layout.scene.yaxis.Tickfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.scene.yaxis import tickfont as v_tickfont # Initialize validators # --------------------- self._validators["color"] = v_tickfont.ColorValidator() self._validators["family"] = v_tickfont.FamilyValidator() self._validators["size"] = v_tickfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Tickfont", "Tickformatstop", "Tickformatstop", "Title", "title"] from plotly.graph_objs.layout.scene.yaxis import title plotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/scene/camera/0000755000175000017500000000000013573746613023573 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/scene/camera/__init__.py0000644000175000017500000003255413573721547025714 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Up(_BaseLayoutHierarchyType): # x # - @property def x(self): """ The 'x' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["x"] @x.setter def x(self, val): self["x"] = val # y # - @property def y(self): """ The 'y' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["y"] @y.setter def y(self, val): self["y"] = val # z # - @property def z(self): """ The 'z' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["z"] @z.setter def z(self, val): self["z"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.scene.camera" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ x y z """ def __init__(self, arg=None, x=None, y=None, z=None, **kwargs): """ Construct a new Up object Sets the (x,y,z) components of the 'up' camera vector. This vector determines the up direction of this scene with respect to the page. The default is *{x: 0, y: 0, z: 1}* which means that the z axis points up. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.scene.camera.Up x y z Returns ------- Up """ super(Up, self).__init__("up") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.scene.camera.Up constructor must be a dict or an instance of plotly.graph_objs.layout.scene.camera.Up""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.scene.camera import up as v_up # Initialize validators # --------------------- self._validators["x"] = v_up.XValidator() self._validators["y"] = v_up.YValidator() self._validators["z"] = v_up.ZValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("z", None) self["z"] = z if z is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Projection(_BaseLayoutHierarchyType): # type # ---- @property def type(self): """ Sets the projection type. The projection type could be either "perspective" or "orthographic". The default is "perspective". The 'type' property is an enumeration that may be specified as: - One of the following enumeration values: ['perspective', 'orthographic'] Returns ------- Any """ return self["type"] @type.setter def type(self, val): self["type"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.scene.camera" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ type Sets the projection type. The projection type could be either "perspective" or "orthographic". The default is "perspective". """ def __init__(self, arg=None, type=None, **kwargs): """ Construct a new Projection object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.scene.camera.Projection type Sets the projection type. The projection type could be either "perspective" or "orthographic". The default is "perspective". Returns ------- Projection """ super(Projection, self).__init__("projection") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.scene.camera.Projection constructor must be a dict or an instance of plotly.graph_objs.layout.scene.camera.Projection""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.scene.camera import projection as v_projection # Initialize validators # --------------------- self._validators["type"] = v_projection.TypeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("type", None) self["type"] = type if type is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Eye(_BaseLayoutHierarchyType): # x # - @property def x(self): """ The 'x' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["x"] @x.setter def x(self, val): self["x"] = val # y # - @property def y(self): """ The 'y' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["y"] @y.setter def y(self, val): self["y"] = val # z # - @property def z(self): """ The 'z' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["z"] @z.setter def z(self, val): self["z"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.scene.camera" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ x y z """ def __init__(self, arg=None, x=None, y=None, z=None, **kwargs): """ Construct a new Eye object Sets the (x,y,z) components of the 'eye' camera vector. This vector determines the view point about the origin of this scene. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.scene.camera.Eye x y z Returns ------- Eye """ super(Eye, self).__init__("eye") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.scene.camera.Eye constructor must be a dict or an instance of plotly.graph_objs.layout.scene.camera.Eye""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.scene.camera import eye as v_eye # Initialize validators # --------------------- self._validators["x"] = v_eye.XValidator() self._validators["y"] = v_eye.YValidator() self._validators["z"] = v_eye.ZValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("z", None) self["z"] = z if z is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Center(_BaseLayoutHierarchyType): # x # - @property def x(self): """ The 'x' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["x"] @x.setter def x(self, val): self["x"] = val # y # - @property def y(self): """ The 'y' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["y"] @y.setter def y(self, val): self["y"] = val # z # - @property def z(self): """ The 'z' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["z"] @z.setter def z(self, val): self["z"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.scene.camera" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ x y z """ def __init__(self, arg=None, x=None, y=None, z=None, **kwargs): """ Construct a new Center object Sets the (x,y,z) components of the 'center' camera vector This vector determines the translation (x,y,z) space about the center of this scene. By default, there is no such translation. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.scene.camera.Center x y z Returns ------- Center """ super(Center, self).__init__("center") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.scene.camera.Center constructor must be a dict or an instance of plotly.graph_objs.layout.scene.camera.Center""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.scene.camera import center as v_center # Initialize validators # --------------------- self._validators["x"] = v_center.XValidator() self._validators["y"] = v_center.YValidator() self._validators["z"] = v_center.ZValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("z", None) self["z"] = z if z is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Center", "Eye", "Projection", "Up"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/scene/__init__.py0000644000175000017500000127424513573721553024467 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class ZAxis(_BaseLayoutHierarchyType): # autorange # --------- @property def autorange(self): """ Determines whether or not the range of this axis is computed in relation to the input data. See `rangemode` for more info. If `range` is provided, then `autorange` is set to False. The 'autorange' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'reversed'] Returns ------- Any """ return self["autorange"] @autorange.setter def autorange(self, val): self["autorange"] = val # backgroundcolor # --------------- @property def backgroundcolor(self): """ Sets the background color of this axis' wall. The 'backgroundcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["backgroundcolor"] @backgroundcolor.setter def backgroundcolor(self, val): self["backgroundcolor"] = val # calendar # -------- @property def calendar(self): """ Sets the calendar system to use for `range` and `tick0` if this is a date axis. This does not set the calendar for interpreting data on this axis, that's specified in the trace or via the global `layout.calendar` The 'calendar' property is an enumeration that may be specified as: - One of the following enumeration values: ['gregorian', 'chinese', 'coptic', 'discworld', 'ethiopian', 'hebrew', 'islamic', 'julian', 'mayan', 'nanakshahi', 'nepali', 'persian', 'jalali', 'taiwan', 'thai', 'ummalqura'] Returns ------- Any """ return self["calendar"] @calendar.setter def calendar(self, val): self["calendar"] = val # categoryarray # ------------- @property def categoryarray(self): """ Sets the order in which categories on this axis appear. Only has an effect if `categoryorder` is set to "array". Used with `categoryorder`. The 'categoryarray' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["categoryarray"] @categoryarray.setter def categoryarray(self, val): self["categoryarray"] = val # categoryarraysrc # ---------------- @property def categoryarraysrc(self): """ Sets the source reference on plot.ly for categoryarray . The 'categoryarraysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["categoryarraysrc"] @categoryarraysrc.setter def categoryarraysrc(self, val): self["categoryarraysrc"] = val # categoryorder # ------------- @property def categoryorder(self): """ Specifies the ordering logic for the case of categorical variables. By default, plotly uses "trace", which specifies the order that is present in the data supplied. Set `categoryorder` to *category ascending* or *category descending* if order should be determined by the alphanumerical order of the category names. Set `categoryorder` to "array" to derive the ordering from the attribute `categoryarray`. If a category is not found in the `categoryarray` array, the sorting behavior for that attribute will be identical to the "trace" mode. The unspecified categories will follow the categories in `categoryarray`. Set `categoryorder` to *total ascending* or *total descending* if order should be determined by the numerical order of the values. Similarly, the order can be determined by the min, max, sum, mean or median of all the values. The 'categoryorder' property is an enumeration that may be specified as: - One of the following enumeration values: ['trace', 'category ascending', 'category descending', 'array', 'total ascending', 'total descending', 'min ascending', 'min descending', 'max ascending', 'max descending', 'sum ascending', 'sum descending', 'mean ascending', 'mean descending', 'median ascending', 'median descending'] Returns ------- Any """ return self["categoryorder"] @categoryorder.setter def categoryorder(self, val): self["categoryorder"] = val # color # ----- @property def color(self): """ Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # dtick # ----- @property def dtick(self): """ Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" The 'dtick' property accepts values of any type Returns ------- Any """ return self["dtick"] @dtick.setter def dtick(self, val): self["dtick"] = val # exponentformat # -------------- @property def exponentformat(self): """ Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. The 'exponentformat' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'e', 'E', 'power', 'SI', 'B'] Returns ------- Any """ return self["exponentformat"] @exponentformat.setter def exponentformat(self, val): self["exponentformat"] = val # gridcolor # --------- @property def gridcolor(self): """ Sets the color of the grid lines. The 'gridcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["gridcolor"] @gridcolor.setter def gridcolor(self, val): self["gridcolor"] = val # gridwidth # --------- @property def gridwidth(self): """ Sets the width (in px) of the grid lines. The 'gridwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["gridwidth"] @gridwidth.setter def gridwidth(self, val): self["gridwidth"] = val # hoverformat # ----------- @property def hoverformat(self): """ Sets the hover text formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'hoverformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["hoverformat"] @hoverformat.setter def hoverformat(self, val): self["hoverformat"] = val # linecolor # --------- @property def linecolor(self): """ Sets the axis line color. The 'linecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["linecolor"] @linecolor.setter def linecolor(self, val): self["linecolor"] = val # linewidth # --------- @property def linewidth(self): """ Sets the width (in px) of the axis line. The 'linewidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["linewidth"] @linewidth.setter def linewidth(self, val): self["linewidth"] = val # mirror # ------ @property def mirror(self): """ Determines if the axis lines or/and ticks are mirrored to the opposite side of the plotting area. If True, the axis lines are mirrored. If "ticks", the axis lines and ticks are mirrored. If False, mirroring is disable. If "all", axis lines are mirrored on all shared-axes subplots. If "allticks", axis lines and ticks are mirrored on all shared-axes subplots. The 'mirror' property is an enumeration that may be specified as: - One of the following enumeration values: [True, 'ticks', False, 'all', 'allticks'] Returns ------- Any """ return self["mirror"] @mirror.setter def mirror(self, val): self["mirror"] = val # nticks # ------ @property def nticks(self): """ Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". The 'nticks' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nticks"] @nticks.setter def nticks(self, val): self["nticks"] = val # range # ----- @property def range(self): """ Sets the range of this axis. If the axis `type` is "log", then you must take the log of your desired range (e.g. to set the range from 1 to 100, set the range from 0 to 2). If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. The 'range' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'range[0]' property accepts values of any type (1) The 'range[1]' property accepts values of any type Returns ------- list """ return self["range"] @range.setter def range(self, val): self["range"] = val # rangemode # --------- @property def rangemode(self): """ If "normal", the range is computed in relation to the extrema of the input data. If *tozero*`, the range extends to 0, regardless of the input data If "nonnegative", the range is non-negative, regardless of the input data. Applies only to linear axes. The 'rangemode' property is an enumeration that may be specified as: - One of the following enumeration values: ['normal', 'tozero', 'nonnegative'] Returns ------- Any """ return self["rangemode"] @rangemode.setter def rangemode(self, val): self["rangemode"] = val # separatethousands # ----------------- @property def separatethousands(self): """ If "true", even 4-digit integers are separated The 'separatethousands' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["separatethousands"] @separatethousands.setter def separatethousands(self, val): self["separatethousands"] = val # showaxeslabels # -------------- @property def showaxeslabels(self): """ Sets whether or not this axis is labeled The 'showaxeslabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showaxeslabels"] @showaxeslabels.setter def showaxeslabels(self, val): self["showaxeslabels"] = val # showbackground # -------------- @property def showbackground(self): """ Sets whether or not this axis' wall has a background color. The 'showbackground' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showbackground"] @showbackground.setter def showbackground(self, val): self["showbackground"] = val # showexponent # ------------ @property def showexponent(self): """ If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. The 'showexponent' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showexponent"] @showexponent.setter def showexponent(self, val): self["showexponent"] = val # showgrid # -------- @property def showgrid(self): """ Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. The 'showgrid' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showgrid"] @showgrid.setter def showgrid(self, val): self["showgrid"] = val # showline # -------- @property def showline(self): """ Determines whether or not a line bounding this axis is drawn. The 'showline' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showline"] @showline.setter def showline(self, val): self["showline"] = val # showspikes # ---------- @property def showspikes(self): """ Sets whether or not spikes starting from data points to this axis' wall are shown on hover. The 'showspikes' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showspikes"] @showspikes.setter def showspikes(self, val): self["showspikes"] = val # showticklabels # -------------- @property def showticklabels(self): """ Determines whether or not the tick labels are drawn. The 'showticklabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showticklabels"] @showticklabels.setter def showticklabels(self, val): self["showticklabels"] = val # showtickprefix # -------------- @property def showtickprefix(self): """ If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. The 'showtickprefix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showtickprefix"] @showtickprefix.setter def showtickprefix(self, val): self["showtickprefix"] = val # showticksuffix # -------------- @property def showticksuffix(self): """ Same as `showtickprefix` but for tick suffixes. The 'showticksuffix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showticksuffix"] @showticksuffix.setter def showticksuffix(self, val): self["showticksuffix"] = val # spikecolor # ---------- @property def spikecolor(self): """ Sets the color of the spikes. The 'spikecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["spikecolor"] @spikecolor.setter def spikecolor(self, val): self["spikecolor"] = val # spikesides # ---------- @property def spikesides(self): """ Sets whether or not spikes extending from the projection data points to this axis' wall boundaries are shown on hover. The 'spikesides' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["spikesides"] @spikesides.setter def spikesides(self, val): self["spikesides"] = val # spikethickness # -------------- @property def spikethickness(self): """ Sets the thickness (in px) of the spikes. The 'spikethickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["spikethickness"] @spikethickness.setter def spikethickness(self, val): self["spikethickness"] = val # tick0 # ----- @property def tick0(self): """ Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. The 'tick0' property accepts values of any type Returns ------- Any """ return self["tick0"] @tick0.setter def tick0(self, val): self["tick0"] = val # tickangle # --------- @property def tickangle(self): """ Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. The 'tickangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["tickangle"] @tickangle.setter def tickangle(self, val): self["tickangle"] = val # tickcolor # --------- @property def tickcolor(self): """ Sets the tick color. The 'tickcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["tickcolor"] @tickcolor.setter def tickcolor(self, val): self["tickcolor"] = val # tickfont # -------- @property def tickfont(self): """ Sets the tick font. The 'tickfont' property is an instance of Tickfont that may be specified as: - An instance of plotly.graph_objs.layout.scene.zaxis.Tickfont - A dict of string/value properties that will be passed to the Tickfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.layout.scene.zaxis.Tickfont """ return self["tickfont"] @tickfont.setter def tickfont(self, val): self["tickfont"] = val # tickformat # ---------- @property def tickformat(self): """ Sets the tick label formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'tickformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickformat"] @tickformat.setter def tickformat(self, val): self["tickformat"] = val # tickformatstops # --------------- @property def tickformatstops(self): """ The 'tickformatstops' property is a tuple of instances of Tickformatstop that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.scene.zaxis.Tickformatstop - A list or tuple of dicts of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- tuple[plotly.graph_objs.layout.scene.zaxis.Tickformatstop] """ return self["tickformatstops"] @tickformatstops.setter def tickformatstops(self, val): self["tickformatstops"] = val # tickformatstopdefaults # ---------------------- @property def tickformatstopdefaults(self): """ When used in a template (as layout.template.layout.scene.zaxis.tickformatstopdefaults), sets the default property values to use for elements of layout.scene.zaxis.tickformatstops The 'tickformatstopdefaults' property is an instance of Tickformatstop that may be specified as: - An instance of plotly.graph_objs.layout.scene.zaxis.Tickformatstop - A dict of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: Returns ------- plotly.graph_objs.layout.scene.zaxis.Tickformatstop """ return self["tickformatstopdefaults"] @tickformatstopdefaults.setter def tickformatstopdefaults(self, val): self["tickformatstopdefaults"] = val # ticklen # ------- @property def ticklen(self): """ Sets the tick length (in px). The 'ticklen' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ticklen"] @ticklen.setter def ticklen(self, val): self["ticklen"] = val # tickmode # -------- @property def tickmode(self): """ Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). The 'tickmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'linear', 'array'] Returns ------- Any """ return self["tickmode"] @tickmode.setter def tickmode(self, val): self["tickmode"] = val # tickprefix # ---------- @property def tickprefix(self): """ Sets a tick label prefix. The 'tickprefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickprefix"] @tickprefix.setter def tickprefix(self, val): self["tickprefix"] = val # ticks # ----- @property def ticks(self): """ Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. The 'ticks' property is an enumeration that may be specified as: - One of the following enumeration values: ['outside', 'inside', ''] Returns ------- Any """ return self["ticks"] @ticks.setter def ticks(self, val): self["ticks"] = val # ticksuffix # ---------- @property def ticksuffix(self): """ Sets a tick label suffix. The 'ticksuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ticksuffix"] @ticksuffix.setter def ticksuffix(self, val): self["ticksuffix"] = val # ticktext # -------- @property def ticktext(self): """ Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. The 'ticktext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ticktext"] @ticktext.setter def ticktext(self, val): self["ticktext"] = val # ticktextsrc # ----------- @property def ticktextsrc(self): """ Sets the source reference on plot.ly for ticktext . The 'ticktextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ticktextsrc"] @ticktextsrc.setter def ticktextsrc(self, val): self["ticktextsrc"] = val # tickvals # -------- @property def tickvals(self): """ Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. The 'tickvals' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["tickvals"] @tickvals.setter def tickvals(self, val): self["tickvals"] = val # tickvalssrc # ----------- @property def tickvalssrc(self): """ Sets the source reference on plot.ly for tickvals . The 'tickvalssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tickvalssrc"] @tickvalssrc.setter def tickvalssrc(self, val): self["tickvalssrc"] = val # tickwidth # --------- @property def tickwidth(self): """ Sets the tick width (in px). The 'tickwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["tickwidth"] @tickwidth.setter def tickwidth(self, val): self["tickwidth"] = val # title # ----- @property def title(self): """ The 'title' property is an instance of Title that may be specified as: - An instance of plotly.graph_objs.layout.scene.zaxis.Title - A dict of string/value properties that will be passed to the Title constructor Supported dict properties: font Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. text Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- plotly.graph_objs.layout.scene.zaxis.Title """ return self["title"] @title.setter def title(self, val): self["title"] = val # titlefont # --------- @property def titlefont(self): """ Deprecated: Please use layout.scene.zaxis.title.font instead. Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.layout.scene.zaxis.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- """ return self["titlefont"] @titlefont.setter def titlefont(self, val): self["titlefont"] = val # type # ---- @property def type(self): """ Sets the axis type. By default, plotly attempts to determined the axis type by looking into the data of the traces that referenced the axis in question. The 'type' property is an enumeration that may be specified as: - One of the following enumeration values: ['-', 'linear', 'log', 'date', 'category'] Returns ------- Any """ return self["type"] @type.setter def type(self, val): self["type"] = val # visible # ------- @property def visible(self): """ A single toggle to hide the axis while preserving interaction like dragging. Default is true when a cheater plot is present on the axis, otherwise false The 'visible' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # zeroline # -------- @property def zeroline(self): """ Determines whether or not a line is drawn at along the 0 value of this axis. If True, the zero line is drawn on top of the grid lines. The 'zeroline' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["zeroline"] @zeroline.setter def zeroline(self, val): self["zeroline"] = val # zerolinecolor # ------------- @property def zerolinecolor(self): """ Sets the line color of the zero line. The 'zerolinecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["zerolinecolor"] @zerolinecolor.setter def zerolinecolor(self, val): self["zerolinecolor"] = val # zerolinewidth # ------------- @property def zerolinewidth(self): """ Sets the width (in px) of the zero line. The 'zerolinewidth' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["zerolinewidth"] @zerolinewidth.setter def zerolinewidth(self, val): self["zerolinewidth"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.scene" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autorange Determines whether or not the range of this axis is computed in relation to the input data. See `rangemode` for more info. If `range` is provided, then `autorange` is set to False. backgroundcolor Sets the background color of this axis' wall. calendar Sets the calendar system to use for `range` and `tick0` if this is a date axis. This does not set the calendar for interpreting data on this axis, that's specified in the trace or via the global `layout.calendar` categoryarray Sets the order in which categories on this axis appear. Only has an effect if `categoryorder` is set to "array". Used with `categoryorder`. categoryarraysrc Sets the source reference on plot.ly for categoryarray . categoryorder Specifies the ordering logic for the case of categorical variables. By default, plotly uses "trace", which specifies the order that is present in the data supplied. Set `categoryorder` to *category ascending* or *category descending* if order should be determined by the alphanumerical order of the category names. Set `categoryorder` to "array" to derive the ordering from the attribute `categoryarray`. If a category is not found in the `categoryarray` array, the sorting behavior for that attribute will be identical to the "trace" mode. The unspecified categories will follow the categories in `categoryarray`. Set `categoryorder` to *total ascending* or *total descending* if order should be determined by the numerical order of the values. Similarly, the order can be determined by the min, max, sum, mean or median of all the values. color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. gridcolor Sets the color of the grid lines. gridwidth Sets the width (in px) of the grid lines. hoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" linecolor Sets the axis line color. linewidth Sets the width (in px) of the axis line. mirror Determines if the axis lines or/and ticks are mirrored to the opposite side of the plotting area. If True, the axis lines are mirrored. If "ticks", the axis lines and ticks are mirrored. If False, mirroring is disable. If "all", axis lines are mirrored on all shared-axes subplots. If "allticks", axis lines and ticks are mirrored on all shared-axes subplots. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". range Sets the range of this axis. If the axis `type` is "log", then you must take the log of your desired range (e.g. to set the range from 1 to 100, set the range from 0 to 2). If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. rangemode If "normal", the range is computed in relation to the extrema of the input data. If *tozero*`, the range extends to 0, regardless of the input data If "nonnegative", the range is non-negative, regardless of the input data. Applies only to linear axes. separatethousands If "true", even 4-digit integers are separated showaxeslabels Sets whether or not this axis is labeled showbackground Sets whether or not this axis' wall has a background color. showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showgrid Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. showline Determines whether or not a line bounding this axis is drawn. showspikes Sets whether or not spikes starting from data points to this axis' wall are shown on hover. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. spikecolor Sets the color of the spikes. spikesides Sets whether or not spikes extending from the projection data points to this axis' wall boundaries are shown on hover. spikethickness Sets the thickness (in px) of the spikes. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the tick font. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.layout.scene.zaxis.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.layout.scen e.zaxis.tickformatstopdefaults), sets the default property values to use for elements of layout.scene.zaxis.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.layout.scene.zaxis.Title instance or dict with compatible properties titlefont Deprecated: Please use layout.scene.zaxis.title.font instead. Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. type Sets the axis type. By default, plotly attempts to determined the axis type by looking into the data of the traces that referenced the axis in question. visible A single toggle to hide the axis while preserving interaction like dragging. Default is true when a cheater plot is present on the axis, otherwise false zeroline Determines whether or not a line is drawn at along the 0 value of this axis. If True, the zero line is drawn on top of the grid lines. zerolinecolor Sets the line color of the zero line. zerolinewidth Sets the width (in px) of the zero line. """ _mapped_properties = {"titlefont": ("title", "font")} def __init__( self, arg=None, autorange=None, backgroundcolor=None, calendar=None, categoryarray=None, categoryarraysrc=None, categoryorder=None, color=None, dtick=None, exponentformat=None, gridcolor=None, gridwidth=None, hoverformat=None, linecolor=None, linewidth=None, mirror=None, nticks=None, range=None, rangemode=None, separatethousands=None, showaxeslabels=None, showbackground=None, showexponent=None, showgrid=None, showline=None, showspikes=None, showticklabels=None, showtickprefix=None, showticksuffix=None, spikecolor=None, spikesides=None, spikethickness=None, tick0=None, tickangle=None, tickcolor=None, tickfont=None, tickformat=None, tickformatstops=None, tickformatstopdefaults=None, ticklen=None, tickmode=None, tickprefix=None, ticks=None, ticksuffix=None, ticktext=None, ticktextsrc=None, tickvals=None, tickvalssrc=None, tickwidth=None, title=None, titlefont=None, type=None, visible=None, zeroline=None, zerolinecolor=None, zerolinewidth=None, **kwargs ): """ Construct a new ZAxis object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.scene.ZAxis autorange Determines whether or not the range of this axis is computed in relation to the input data. See `rangemode` for more info. If `range` is provided, then `autorange` is set to False. backgroundcolor Sets the background color of this axis' wall. calendar Sets the calendar system to use for `range` and `tick0` if this is a date axis. This does not set the calendar for interpreting data on this axis, that's specified in the trace or via the global `layout.calendar` categoryarray Sets the order in which categories on this axis appear. Only has an effect if `categoryorder` is set to "array". Used with `categoryorder`. categoryarraysrc Sets the source reference on plot.ly for categoryarray . categoryorder Specifies the ordering logic for the case of categorical variables. By default, plotly uses "trace", which specifies the order that is present in the data supplied. Set `categoryorder` to *category ascending* or *category descending* if order should be determined by the alphanumerical order of the category names. Set `categoryorder` to "array" to derive the ordering from the attribute `categoryarray`. If a category is not found in the `categoryarray` array, the sorting behavior for that attribute will be identical to the "trace" mode. The unspecified categories will follow the categories in `categoryarray`. Set `categoryorder` to *total ascending* or *total descending* if order should be determined by the numerical order of the values. Similarly, the order can be determined by the min, max, sum, mean or median of all the values. color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. gridcolor Sets the color of the grid lines. gridwidth Sets the width (in px) of the grid lines. hoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" linecolor Sets the axis line color. linewidth Sets the width (in px) of the axis line. mirror Determines if the axis lines or/and ticks are mirrored to the opposite side of the plotting area. If True, the axis lines are mirrored. If "ticks", the axis lines and ticks are mirrored. If False, mirroring is disable. If "all", axis lines are mirrored on all shared-axes subplots. If "allticks", axis lines and ticks are mirrored on all shared-axes subplots. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". range Sets the range of this axis. If the axis `type` is "log", then you must take the log of your desired range (e.g. to set the range from 1 to 100, set the range from 0 to 2). If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. rangemode If "normal", the range is computed in relation to the extrema of the input data. If *tozero*`, the range extends to 0, regardless of the input data If "nonnegative", the range is non-negative, regardless of the input data. Applies only to linear axes. separatethousands If "true", even 4-digit integers are separated showaxeslabels Sets whether or not this axis is labeled showbackground Sets whether or not this axis' wall has a background color. showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showgrid Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. showline Determines whether or not a line bounding this axis is drawn. showspikes Sets whether or not spikes starting from data points to this axis' wall are shown on hover. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. spikecolor Sets the color of the spikes. spikesides Sets whether or not spikes extending from the projection data points to this axis' wall boundaries are shown on hover. spikethickness Sets the thickness (in px) of the spikes. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the tick font. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.layout.scene.zaxis.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.layout.scen e.zaxis.tickformatstopdefaults), sets the default property values to use for elements of layout.scene.zaxis.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.layout.scene.zaxis.Title instance or dict with compatible properties titlefont Deprecated: Please use layout.scene.zaxis.title.font instead. Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. type Sets the axis type. By default, plotly attempts to determined the axis type by looking into the data of the traces that referenced the axis in question. visible A single toggle to hide the axis while preserving interaction like dragging. Default is true when a cheater plot is present on the axis, otherwise false zeroline Determines whether or not a line is drawn at along the 0 value of this axis. If True, the zero line is drawn on top of the grid lines. zerolinecolor Sets the line color of the zero line. zerolinewidth Sets the width (in px) of the zero line. Returns ------- ZAxis """ super(ZAxis, self).__init__("zaxis") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.scene.ZAxis constructor must be a dict or an instance of plotly.graph_objs.layout.scene.ZAxis""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.scene import zaxis as v_zaxis # Initialize validators # --------------------- self._validators["autorange"] = v_zaxis.AutorangeValidator() self._validators["backgroundcolor"] = v_zaxis.BackgroundcolorValidator() self._validators["calendar"] = v_zaxis.CalendarValidator() self._validators["categoryarray"] = v_zaxis.CategoryarrayValidator() self._validators["categoryarraysrc"] = v_zaxis.CategoryarraysrcValidator() self._validators["categoryorder"] = v_zaxis.CategoryorderValidator() self._validators["color"] = v_zaxis.ColorValidator() self._validators["dtick"] = v_zaxis.DtickValidator() self._validators["exponentformat"] = v_zaxis.ExponentformatValidator() self._validators["gridcolor"] = v_zaxis.GridcolorValidator() self._validators["gridwidth"] = v_zaxis.GridwidthValidator() self._validators["hoverformat"] = v_zaxis.HoverformatValidator() self._validators["linecolor"] = v_zaxis.LinecolorValidator() self._validators["linewidth"] = v_zaxis.LinewidthValidator() self._validators["mirror"] = v_zaxis.MirrorValidator() self._validators["nticks"] = v_zaxis.NticksValidator() self._validators["range"] = v_zaxis.RangeValidator() self._validators["rangemode"] = v_zaxis.RangemodeValidator() self._validators["separatethousands"] = v_zaxis.SeparatethousandsValidator() self._validators["showaxeslabels"] = v_zaxis.ShowaxeslabelsValidator() self._validators["showbackground"] = v_zaxis.ShowbackgroundValidator() self._validators["showexponent"] = v_zaxis.ShowexponentValidator() self._validators["showgrid"] = v_zaxis.ShowgridValidator() self._validators["showline"] = v_zaxis.ShowlineValidator() self._validators["showspikes"] = v_zaxis.ShowspikesValidator() self._validators["showticklabels"] = v_zaxis.ShowticklabelsValidator() self._validators["showtickprefix"] = v_zaxis.ShowtickprefixValidator() self._validators["showticksuffix"] = v_zaxis.ShowticksuffixValidator() self._validators["spikecolor"] = v_zaxis.SpikecolorValidator() self._validators["spikesides"] = v_zaxis.SpikesidesValidator() self._validators["spikethickness"] = v_zaxis.SpikethicknessValidator() self._validators["tick0"] = v_zaxis.Tick0Validator() self._validators["tickangle"] = v_zaxis.TickangleValidator() self._validators["tickcolor"] = v_zaxis.TickcolorValidator() self._validators["tickfont"] = v_zaxis.TickfontValidator() self._validators["tickformat"] = v_zaxis.TickformatValidator() self._validators["tickformatstops"] = v_zaxis.TickformatstopsValidator() self._validators["tickformatstopdefaults"] = v_zaxis.TickformatstopValidator() self._validators["ticklen"] = v_zaxis.TicklenValidator() self._validators["tickmode"] = v_zaxis.TickmodeValidator() self._validators["tickprefix"] = v_zaxis.TickprefixValidator() self._validators["ticks"] = v_zaxis.TicksValidator() self._validators["ticksuffix"] = v_zaxis.TicksuffixValidator() self._validators["ticktext"] = v_zaxis.TicktextValidator() self._validators["ticktextsrc"] = v_zaxis.TicktextsrcValidator() self._validators["tickvals"] = v_zaxis.TickvalsValidator() self._validators["tickvalssrc"] = v_zaxis.TickvalssrcValidator() self._validators["tickwidth"] = v_zaxis.TickwidthValidator() self._validators["title"] = v_zaxis.TitleValidator() self._validators["type"] = v_zaxis.TypeValidator() self._validators["visible"] = v_zaxis.VisibleValidator() self._validators["zeroline"] = v_zaxis.ZerolineValidator() self._validators["zerolinecolor"] = v_zaxis.ZerolinecolorValidator() self._validators["zerolinewidth"] = v_zaxis.ZerolinewidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autorange", None) self["autorange"] = autorange if autorange is not None else _v _v = arg.pop("backgroundcolor", None) self["backgroundcolor"] = backgroundcolor if backgroundcolor is not None else _v _v = arg.pop("calendar", None) self["calendar"] = calendar if calendar is not None else _v _v = arg.pop("categoryarray", None) self["categoryarray"] = categoryarray if categoryarray is not None else _v _v = arg.pop("categoryarraysrc", None) self["categoryarraysrc"] = ( categoryarraysrc if categoryarraysrc is not None else _v ) _v = arg.pop("categoryorder", None) self["categoryorder"] = categoryorder if categoryorder is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("dtick", None) self["dtick"] = dtick if dtick is not None else _v _v = arg.pop("exponentformat", None) self["exponentformat"] = exponentformat if exponentformat is not None else _v _v = arg.pop("gridcolor", None) self["gridcolor"] = gridcolor if gridcolor is not None else _v _v = arg.pop("gridwidth", None) self["gridwidth"] = gridwidth if gridwidth is not None else _v _v = arg.pop("hoverformat", None) self["hoverformat"] = hoverformat if hoverformat is not None else _v _v = arg.pop("linecolor", None) self["linecolor"] = linecolor if linecolor is not None else _v _v = arg.pop("linewidth", None) self["linewidth"] = linewidth if linewidth is not None else _v _v = arg.pop("mirror", None) self["mirror"] = mirror if mirror is not None else _v _v = arg.pop("nticks", None) self["nticks"] = nticks if nticks is not None else _v _v = arg.pop("range", None) self["range"] = range if range is not None else _v _v = arg.pop("rangemode", None) self["rangemode"] = rangemode if rangemode is not None else _v _v = arg.pop("separatethousands", None) self["separatethousands"] = ( separatethousands if separatethousands is not None else _v ) _v = arg.pop("showaxeslabels", None) self["showaxeslabels"] = showaxeslabels if showaxeslabels is not None else _v _v = arg.pop("showbackground", None) self["showbackground"] = showbackground if showbackground is not None else _v _v = arg.pop("showexponent", None) self["showexponent"] = showexponent if showexponent is not None else _v _v = arg.pop("showgrid", None) self["showgrid"] = showgrid if showgrid is not None else _v _v = arg.pop("showline", None) self["showline"] = showline if showline is not None else _v _v = arg.pop("showspikes", None) self["showspikes"] = showspikes if showspikes is not None else _v _v = arg.pop("showticklabels", None) self["showticklabels"] = showticklabels if showticklabels is not None else _v _v = arg.pop("showtickprefix", None) self["showtickprefix"] = showtickprefix if showtickprefix is not None else _v _v = arg.pop("showticksuffix", None) self["showticksuffix"] = showticksuffix if showticksuffix is not None else _v _v = arg.pop("spikecolor", None) self["spikecolor"] = spikecolor if spikecolor is not None else _v _v = arg.pop("spikesides", None) self["spikesides"] = spikesides if spikesides is not None else _v _v = arg.pop("spikethickness", None) self["spikethickness"] = spikethickness if spikethickness is not None else _v _v = arg.pop("tick0", None) self["tick0"] = tick0 if tick0 is not None else _v _v = arg.pop("tickangle", None) self["tickangle"] = tickangle if tickangle is not None else _v _v = arg.pop("tickcolor", None) self["tickcolor"] = tickcolor if tickcolor is not None else _v _v = arg.pop("tickfont", None) self["tickfont"] = tickfont if tickfont is not None else _v _v = arg.pop("tickformat", None) self["tickformat"] = tickformat if tickformat is not None else _v _v = arg.pop("tickformatstops", None) self["tickformatstops"] = tickformatstops if tickformatstops is not None else _v _v = arg.pop("tickformatstopdefaults", None) self["tickformatstopdefaults"] = ( tickformatstopdefaults if tickformatstopdefaults is not None else _v ) _v = arg.pop("ticklen", None) self["ticklen"] = ticklen if ticklen is not None else _v _v = arg.pop("tickmode", None) self["tickmode"] = tickmode if tickmode is not None else _v _v = arg.pop("tickprefix", None) self["tickprefix"] = tickprefix if tickprefix is not None else _v _v = arg.pop("ticks", None) self["ticks"] = ticks if ticks is not None else _v _v = arg.pop("ticksuffix", None) self["ticksuffix"] = ticksuffix if ticksuffix is not None else _v _v = arg.pop("ticktext", None) self["ticktext"] = ticktext if ticktext is not None else _v _v = arg.pop("ticktextsrc", None) self["ticktextsrc"] = ticktextsrc if ticktextsrc is not None else _v _v = arg.pop("tickvals", None) self["tickvals"] = tickvals if tickvals is not None else _v _v = arg.pop("tickvalssrc", None) self["tickvalssrc"] = tickvalssrc if tickvalssrc is not None else _v _v = arg.pop("tickwidth", None) self["tickwidth"] = tickwidth if tickwidth is not None else _v _v = arg.pop("title", None) self["title"] = title if title is not None else _v _v = arg.pop("titlefont", None) _v = titlefont if titlefont is not None else _v if _v is not None: self["titlefont"] = _v _v = arg.pop("type", None) self["type"] = type if type is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("zeroline", None) self["zeroline"] = zeroline if zeroline is not None else _v _v = arg.pop("zerolinecolor", None) self["zerolinecolor"] = zerolinecolor if zerolinecolor is not None else _v _v = arg.pop("zerolinewidth", None) self["zerolinewidth"] = zerolinewidth if zerolinewidth is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class YAxis(_BaseLayoutHierarchyType): # autorange # --------- @property def autorange(self): """ Determines whether or not the range of this axis is computed in relation to the input data. See `rangemode` for more info. If `range` is provided, then `autorange` is set to False. The 'autorange' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'reversed'] Returns ------- Any """ return self["autorange"] @autorange.setter def autorange(self, val): self["autorange"] = val # backgroundcolor # --------------- @property def backgroundcolor(self): """ Sets the background color of this axis' wall. The 'backgroundcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["backgroundcolor"] @backgroundcolor.setter def backgroundcolor(self, val): self["backgroundcolor"] = val # calendar # -------- @property def calendar(self): """ Sets the calendar system to use for `range` and `tick0` if this is a date axis. This does not set the calendar for interpreting data on this axis, that's specified in the trace or via the global `layout.calendar` The 'calendar' property is an enumeration that may be specified as: - One of the following enumeration values: ['gregorian', 'chinese', 'coptic', 'discworld', 'ethiopian', 'hebrew', 'islamic', 'julian', 'mayan', 'nanakshahi', 'nepali', 'persian', 'jalali', 'taiwan', 'thai', 'ummalqura'] Returns ------- Any """ return self["calendar"] @calendar.setter def calendar(self, val): self["calendar"] = val # categoryarray # ------------- @property def categoryarray(self): """ Sets the order in which categories on this axis appear. Only has an effect if `categoryorder` is set to "array". Used with `categoryorder`. The 'categoryarray' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["categoryarray"] @categoryarray.setter def categoryarray(self, val): self["categoryarray"] = val # categoryarraysrc # ---------------- @property def categoryarraysrc(self): """ Sets the source reference on plot.ly for categoryarray . The 'categoryarraysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["categoryarraysrc"] @categoryarraysrc.setter def categoryarraysrc(self, val): self["categoryarraysrc"] = val # categoryorder # ------------- @property def categoryorder(self): """ Specifies the ordering logic for the case of categorical variables. By default, plotly uses "trace", which specifies the order that is present in the data supplied. Set `categoryorder` to *category ascending* or *category descending* if order should be determined by the alphanumerical order of the category names. Set `categoryorder` to "array" to derive the ordering from the attribute `categoryarray`. If a category is not found in the `categoryarray` array, the sorting behavior for that attribute will be identical to the "trace" mode. The unspecified categories will follow the categories in `categoryarray`. Set `categoryorder` to *total ascending* or *total descending* if order should be determined by the numerical order of the values. Similarly, the order can be determined by the min, max, sum, mean or median of all the values. The 'categoryorder' property is an enumeration that may be specified as: - One of the following enumeration values: ['trace', 'category ascending', 'category descending', 'array', 'total ascending', 'total descending', 'min ascending', 'min descending', 'max ascending', 'max descending', 'sum ascending', 'sum descending', 'mean ascending', 'mean descending', 'median ascending', 'median descending'] Returns ------- Any """ return self["categoryorder"] @categoryorder.setter def categoryorder(self, val): self["categoryorder"] = val # color # ----- @property def color(self): """ Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # dtick # ----- @property def dtick(self): """ Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" The 'dtick' property accepts values of any type Returns ------- Any """ return self["dtick"] @dtick.setter def dtick(self, val): self["dtick"] = val # exponentformat # -------------- @property def exponentformat(self): """ Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. The 'exponentformat' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'e', 'E', 'power', 'SI', 'B'] Returns ------- Any """ return self["exponentformat"] @exponentformat.setter def exponentformat(self, val): self["exponentformat"] = val # gridcolor # --------- @property def gridcolor(self): """ Sets the color of the grid lines. The 'gridcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["gridcolor"] @gridcolor.setter def gridcolor(self, val): self["gridcolor"] = val # gridwidth # --------- @property def gridwidth(self): """ Sets the width (in px) of the grid lines. The 'gridwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["gridwidth"] @gridwidth.setter def gridwidth(self, val): self["gridwidth"] = val # hoverformat # ----------- @property def hoverformat(self): """ Sets the hover text formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'hoverformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["hoverformat"] @hoverformat.setter def hoverformat(self, val): self["hoverformat"] = val # linecolor # --------- @property def linecolor(self): """ Sets the axis line color. The 'linecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["linecolor"] @linecolor.setter def linecolor(self, val): self["linecolor"] = val # linewidth # --------- @property def linewidth(self): """ Sets the width (in px) of the axis line. The 'linewidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["linewidth"] @linewidth.setter def linewidth(self, val): self["linewidth"] = val # mirror # ------ @property def mirror(self): """ Determines if the axis lines or/and ticks are mirrored to the opposite side of the plotting area. If True, the axis lines are mirrored. If "ticks", the axis lines and ticks are mirrored. If False, mirroring is disable. If "all", axis lines are mirrored on all shared-axes subplots. If "allticks", axis lines and ticks are mirrored on all shared-axes subplots. The 'mirror' property is an enumeration that may be specified as: - One of the following enumeration values: [True, 'ticks', False, 'all', 'allticks'] Returns ------- Any """ return self["mirror"] @mirror.setter def mirror(self, val): self["mirror"] = val # nticks # ------ @property def nticks(self): """ Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". The 'nticks' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nticks"] @nticks.setter def nticks(self, val): self["nticks"] = val # range # ----- @property def range(self): """ Sets the range of this axis. If the axis `type` is "log", then you must take the log of your desired range (e.g. to set the range from 1 to 100, set the range from 0 to 2). If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. The 'range' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'range[0]' property accepts values of any type (1) The 'range[1]' property accepts values of any type Returns ------- list """ return self["range"] @range.setter def range(self, val): self["range"] = val # rangemode # --------- @property def rangemode(self): """ If "normal", the range is computed in relation to the extrema of the input data. If *tozero*`, the range extends to 0, regardless of the input data If "nonnegative", the range is non-negative, regardless of the input data. Applies only to linear axes. The 'rangemode' property is an enumeration that may be specified as: - One of the following enumeration values: ['normal', 'tozero', 'nonnegative'] Returns ------- Any """ return self["rangemode"] @rangemode.setter def rangemode(self, val): self["rangemode"] = val # separatethousands # ----------------- @property def separatethousands(self): """ If "true", even 4-digit integers are separated The 'separatethousands' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["separatethousands"] @separatethousands.setter def separatethousands(self, val): self["separatethousands"] = val # showaxeslabels # -------------- @property def showaxeslabels(self): """ Sets whether or not this axis is labeled The 'showaxeslabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showaxeslabels"] @showaxeslabels.setter def showaxeslabels(self, val): self["showaxeslabels"] = val # showbackground # -------------- @property def showbackground(self): """ Sets whether or not this axis' wall has a background color. The 'showbackground' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showbackground"] @showbackground.setter def showbackground(self, val): self["showbackground"] = val # showexponent # ------------ @property def showexponent(self): """ If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. The 'showexponent' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showexponent"] @showexponent.setter def showexponent(self, val): self["showexponent"] = val # showgrid # -------- @property def showgrid(self): """ Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. The 'showgrid' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showgrid"] @showgrid.setter def showgrid(self, val): self["showgrid"] = val # showline # -------- @property def showline(self): """ Determines whether or not a line bounding this axis is drawn. The 'showline' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showline"] @showline.setter def showline(self, val): self["showline"] = val # showspikes # ---------- @property def showspikes(self): """ Sets whether or not spikes starting from data points to this axis' wall are shown on hover. The 'showspikes' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showspikes"] @showspikes.setter def showspikes(self, val): self["showspikes"] = val # showticklabels # -------------- @property def showticklabels(self): """ Determines whether or not the tick labels are drawn. The 'showticklabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showticklabels"] @showticklabels.setter def showticklabels(self, val): self["showticklabels"] = val # showtickprefix # -------------- @property def showtickprefix(self): """ If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. The 'showtickprefix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showtickprefix"] @showtickprefix.setter def showtickprefix(self, val): self["showtickprefix"] = val # showticksuffix # -------------- @property def showticksuffix(self): """ Same as `showtickprefix` but for tick suffixes. The 'showticksuffix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showticksuffix"] @showticksuffix.setter def showticksuffix(self, val): self["showticksuffix"] = val # spikecolor # ---------- @property def spikecolor(self): """ Sets the color of the spikes. The 'spikecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["spikecolor"] @spikecolor.setter def spikecolor(self, val): self["spikecolor"] = val # spikesides # ---------- @property def spikesides(self): """ Sets whether or not spikes extending from the projection data points to this axis' wall boundaries are shown on hover. The 'spikesides' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["spikesides"] @spikesides.setter def spikesides(self, val): self["spikesides"] = val # spikethickness # -------------- @property def spikethickness(self): """ Sets the thickness (in px) of the spikes. The 'spikethickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["spikethickness"] @spikethickness.setter def spikethickness(self, val): self["spikethickness"] = val # tick0 # ----- @property def tick0(self): """ Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. The 'tick0' property accepts values of any type Returns ------- Any """ return self["tick0"] @tick0.setter def tick0(self, val): self["tick0"] = val # tickangle # --------- @property def tickangle(self): """ Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. The 'tickangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["tickangle"] @tickangle.setter def tickangle(self, val): self["tickangle"] = val # tickcolor # --------- @property def tickcolor(self): """ Sets the tick color. The 'tickcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["tickcolor"] @tickcolor.setter def tickcolor(self, val): self["tickcolor"] = val # tickfont # -------- @property def tickfont(self): """ Sets the tick font. The 'tickfont' property is an instance of Tickfont that may be specified as: - An instance of plotly.graph_objs.layout.scene.yaxis.Tickfont - A dict of string/value properties that will be passed to the Tickfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.layout.scene.yaxis.Tickfont """ return self["tickfont"] @tickfont.setter def tickfont(self, val): self["tickfont"] = val # tickformat # ---------- @property def tickformat(self): """ Sets the tick label formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'tickformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickformat"] @tickformat.setter def tickformat(self, val): self["tickformat"] = val # tickformatstops # --------------- @property def tickformatstops(self): """ The 'tickformatstops' property is a tuple of instances of Tickformatstop that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.scene.yaxis.Tickformatstop - A list or tuple of dicts of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- tuple[plotly.graph_objs.layout.scene.yaxis.Tickformatstop] """ return self["tickformatstops"] @tickformatstops.setter def tickformatstops(self, val): self["tickformatstops"] = val # tickformatstopdefaults # ---------------------- @property def tickformatstopdefaults(self): """ When used in a template (as layout.template.layout.scene.yaxis.tickformatstopdefaults), sets the default property values to use for elements of layout.scene.yaxis.tickformatstops The 'tickformatstopdefaults' property is an instance of Tickformatstop that may be specified as: - An instance of plotly.graph_objs.layout.scene.yaxis.Tickformatstop - A dict of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: Returns ------- plotly.graph_objs.layout.scene.yaxis.Tickformatstop """ return self["tickformatstopdefaults"] @tickformatstopdefaults.setter def tickformatstopdefaults(self, val): self["tickformatstopdefaults"] = val # ticklen # ------- @property def ticklen(self): """ Sets the tick length (in px). The 'ticklen' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ticklen"] @ticklen.setter def ticklen(self, val): self["ticklen"] = val # tickmode # -------- @property def tickmode(self): """ Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). The 'tickmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'linear', 'array'] Returns ------- Any """ return self["tickmode"] @tickmode.setter def tickmode(self, val): self["tickmode"] = val # tickprefix # ---------- @property def tickprefix(self): """ Sets a tick label prefix. The 'tickprefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickprefix"] @tickprefix.setter def tickprefix(self, val): self["tickprefix"] = val # ticks # ----- @property def ticks(self): """ Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. The 'ticks' property is an enumeration that may be specified as: - One of the following enumeration values: ['outside', 'inside', ''] Returns ------- Any """ return self["ticks"] @ticks.setter def ticks(self, val): self["ticks"] = val # ticksuffix # ---------- @property def ticksuffix(self): """ Sets a tick label suffix. The 'ticksuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ticksuffix"] @ticksuffix.setter def ticksuffix(self, val): self["ticksuffix"] = val # ticktext # -------- @property def ticktext(self): """ Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. The 'ticktext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ticktext"] @ticktext.setter def ticktext(self, val): self["ticktext"] = val # ticktextsrc # ----------- @property def ticktextsrc(self): """ Sets the source reference on plot.ly for ticktext . The 'ticktextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ticktextsrc"] @ticktextsrc.setter def ticktextsrc(self, val): self["ticktextsrc"] = val # tickvals # -------- @property def tickvals(self): """ Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. The 'tickvals' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["tickvals"] @tickvals.setter def tickvals(self, val): self["tickvals"] = val # tickvalssrc # ----------- @property def tickvalssrc(self): """ Sets the source reference on plot.ly for tickvals . The 'tickvalssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tickvalssrc"] @tickvalssrc.setter def tickvalssrc(self, val): self["tickvalssrc"] = val # tickwidth # --------- @property def tickwidth(self): """ Sets the tick width (in px). The 'tickwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["tickwidth"] @tickwidth.setter def tickwidth(self, val): self["tickwidth"] = val # title # ----- @property def title(self): """ The 'title' property is an instance of Title that may be specified as: - An instance of plotly.graph_objs.layout.scene.yaxis.Title - A dict of string/value properties that will be passed to the Title constructor Supported dict properties: font Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. text Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- plotly.graph_objs.layout.scene.yaxis.Title """ return self["title"] @title.setter def title(self, val): self["title"] = val # titlefont # --------- @property def titlefont(self): """ Deprecated: Please use layout.scene.yaxis.title.font instead. Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.layout.scene.yaxis.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- """ return self["titlefont"] @titlefont.setter def titlefont(self, val): self["titlefont"] = val # type # ---- @property def type(self): """ Sets the axis type. By default, plotly attempts to determined the axis type by looking into the data of the traces that referenced the axis in question. The 'type' property is an enumeration that may be specified as: - One of the following enumeration values: ['-', 'linear', 'log', 'date', 'category'] Returns ------- Any """ return self["type"] @type.setter def type(self, val): self["type"] = val # visible # ------- @property def visible(self): """ A single toggle to hide the axis while preserving interaction like dragging. Default is true when a cheater plot is present on the axis, otherwise false The 'visible' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # zeroline # -------- @property def zeroline(self): """ Determines whether or not a line is drawn at along the 0 value of this axis. If True, the zero line is drawn on top of the grid lines. The 'zeroline' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["zeroline"] @zeroline.setter def zeroline(self, val): self["zeroline"] = val # zerolinecolor # ------------- @property def zerolinecolor(self): """ Sets the line color of the zero line. The 'zerolinecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["zerolinecolor"] @zerolinecolor.setter def zerolinecolor(self, val): self["zerolinecolor"] = val # zerolinewidth # ------------- @property def zerolinewidth(self): """ Sets the width (in px) of the zero line. The 'zerolinewidth' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["zerolinewidth"] @zerolinewidth.setter def zerolinewidth(self, val): self["zerolinewidth"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.scene" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autorange Determines whether or not the range of this axis is computed in relation to the input data. See `rangemode` for more info. If `range` is provided, then `autorange` is set to False. backgroundcolor Sets the background color of this axis' wall. calendar Sets the calendar system to use for `range` and `tick0` if this is a date axis. This does not set the calendar for interpreting data on this axis, that's specified in the trace or via the global `layout.calendar` categoryarray Sets the order in which categories on this axis appear. Only has an effect if `categoryorder` is set to "array". Used with `categoryorder`. categoryarraysrc Sets the source reference on plot.ly for categoryarray . categoryorder Specifies the ordering logic for the case of categorical variables. By default, plotly uses "trace", which specifies the order that is present in the data supplied. Set `categoryorder` to *category ascending* or *category descending* if order should be determined by the alphanumerical order of the category names. Set `categoryorder` to "array" to derive the ordering from the attribute `categoryarray`. If a category is not found in the `categoryarray` array, the sorting behavior for that attribute will be identical to the "trace" mode. The unspecified categories will follow the categories in `categoryarray`. Set `categoryorder` to *total ascending* or *total descending* if order should be determined by the numerical order of the values. Similarly, the order can be determined by the min, max, sum, mean or median of all the values. color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. gridcolor Sets the color of the grid lines. gridwidth Sets the width (in px) of the grid lines. hoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" linecolor Sets the axis line color. linewidth Sets the width (in px) of the axis line. mirror Determines if the axis lines or/and ticks are mirrored to the opposite side of the plotting area. If True, the axis lines are mirrored. If "ticks", the axis lines and ticks are mirrored. If False, mirroring is disable. If "all", axis lines are mirrored on all shared-axes subplots. If "allticks", axis lines and ticks are mirrored on all shared-axes subplots. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". range Sets the range of this axis. If the axis `type` is "log", then you must take the log of your desired range (e.g. to set the range from 1 to 100, set the range from 0 to 2). If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. rangemode If "normal", the range is computed in relation to the extrema of the input data. If *tozero*`, the range extends to 0, regardless of the input data If "nonnegative", the range is non-negative, regardless of the input data. Applies only to linear axes. separatethousands If "true", even 4-digit integers are separated showaxeslabels Sets whether or not this axis is labeled showbackground Sets whether or not this axis' wall has a background color. showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showgrid Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. showline Determines whether or not a line bounding this axis is drawn. showspikes Sets whether or not spikes starting from data points to this axis' wall are shown on hover. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. spikecolor Sets the color of the spikes. spikesides Sets whether or not spikes extending from the projection data points to this axis' wall boundaries are shown on hover. spikethickness Sets the thickness (in px) of the spikes. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the tick font. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.layout.scene.yaxis.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.layout.scen e.yaxis.tickformatstopdefaults), sets the default property values to use for elements of layout.scene.yaxis.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.layout.scene.yaxis.Title instance or dict with compatible properties titlefont Deprecated: Please use layout.scene.yaxis.title.font instead. Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. type Sets the axis type. By default, plotly attempts to determined the axis type by looking into the data of the traces that referenced the axis in question. visible A single toggle to hide the axis while preserving interaction like dragging. Default is true when a cheater plot is present on the axis, otherwise false zeroline Determines whether or not a line is drawn at along the 0 value of this axis. If True, the zero line is drawn on top of the grid lines. zerolinecolor Sets the line color of the zero line. zerolinewidth Sets the width (in px) of the zero line. """ _mapped_properties = {"titlefont": ("title", "font")} def __init__( self, arg=None, autorange=None, backgroundcolor=None, calendar=None, categoryarray=None, categoryarraysrc=None, categoryorder=None, color=None, dtick=None, exponentformat=None, gridcolor=None, gridwidth=None, hoverformat=None, linecolor=None, linewidth=None, mirror=None, nticks=None, range=None, rangemode=None, separatethousands=None, showaxeslabels=None, showbackground=None, showexponent=None, showgrid=None, showline=None, showspikes=None, showticklabels=None, showtickprefix=None, showticksuffix=None, spikecolor=None, spikesides=None, spikethickness=None, tick0=None, tickangle=None, tickcolor=None, tickfont=None, tickformat=None, tickformatstops=None, tickformatstopdefaults=None, ticklen=None, tickmode=None, tickprefix=None, ticks=None, ticksuffix=None, ticktext=None, ticktextsrc=None, tickvals=None, tickvalssrc=None, tickwidth=None, title=None, titlefont=None, type=None, visible=None, zeroline=None, zerolinecolor=None, zerolinewidth=None, **kwargs ): """ Construct a new YAxis object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.scene.YAxis autorange Determines whether or not the range of this axis is computed in relation to the input data. See `rangemode` for more info. If `range` is provided, then `autorange` is set to False. backgroundcolor Sets the background color of this axis' wall. calendar Sets the calendar system to use for `range` and `tick0` if this is a date axis. This does not set the calendar for interpreting data on this axis, that's specified in the trace or via the global `layout.calendar` categoryarray Sets the order in which categories on this axis appear. Only has an effect if `categoryorder` is set to "array". Used with `categoryorder`. categoryarraysrc Sets the source reference on plot.ly for categoryarray . categoryorder Specifies the ordering logic for the case of categorical variables. By default, plotly uses "trace", which specifies the order that is present in the data supplied. Set `categoryorder` to *category ascending* or *category descending* if order should be determined by the alphanumerical order of the category names. Set `categoryorder` to "array" to derive the ordering from the attribute `categoryarray`. If a category is not found in the `categoryarray` array, the sorting behavior for that attribute will be identical to the "trace" mode. The unspecified categories will follow the categories in `categoryarray`. Set `categoryorder` to *total ascending* or *total descending* if order should be determined by the numerical order of the values. Similarly, the order can be determined by the min, max, sum, mean or median of all the values. color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. gridcolor Sets the color of the grid lines. gridwidth Sets the width (in px) of the grid lines. hoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" linecolor Sets the axis line color. linewidth Sets the width (in px) of the axis line. mirror Determines if the axis lines or/and ticks are mirrored to the opposite side of the plotting area. If True, the axis lines are mirrored. If "ticks", the axis lines and ticks are mirrored. If False, mirroring is disable. If "all", axis lines are mirrored on all shared-axes subplots. If "allticks", axis lines and ticks are mirrored on all shared-axes subplots. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". range Sets the range of this axis. If the axis `type` is "log", then you must take the log of your desired range (e.g. to set the range from 1 to 100, set the range from 0 to 2). If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. rangemode If "normal", the range is computed in relation to the extrema of the input data. If *tozero*`, the range extends to 0, regardless of the input data If "nonnegative", the range is non-negative, regardless of the input data. Applies only to linear axes. separatethousands If "true", even 4-digit integers are separated showaxeslabels Sets whether or not this axis is labeled showbackground Sets whether or not this axis' wall has a background color. showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showgrid Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. showline Determines whether or not a line bounding this axis is drawn. showspikes Sets whether or not spikes starting from data points to this axis' wall are shown on hover. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. spikecolor Sets the color of the spikes. spikesides Sets whether or not spikes extending from the projection data points to this axis' wall boundaries are shown on hover. spikethickness Sets the thickness (in px) of the spikes. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the tick font. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.layout.scene.yaxis.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.layout.scen e.yaxis.tickformatstopdefaults), sets the default property values to use for elements of layout.scene.yaxis.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.layout.scene.yaxis.Title instance or dict with compatible properties titlefont Deprecated: Please use layout.scene.yaxis.title.font instead. Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. type Sets the axis type. By default, plotly attempts to determined the axis type by looking into the data of the traces that referenced the axis in question. visible A single toggle to hide the axis while preserving interaction like dragging. Default is true when a cheater plot is present on the axis, otherwise false zeroline Determines whether or not a line is drawn at along the 0 value of this axis. If True, the zero line is drawn on top of the grid lines. zerolinecolor Sets the line color of the zero line. zerolinewidth Sets the width (in px) of the zero line. Returns ------- YAxis """ super(YAxis, self).__init__("yaxis") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.scene.YAxis constructor must be a dict or an instance of plotly.graph_objs.layout.scene.YAxis""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.scene import yaxis as v_yaxis # Initialize validators # --------------------- self._validators["autorange"] = v_yaxis.AutorangeValidator() self._validators["backgroundcolor"] = v_yaxis.BackgroundcolorValidator() self._validators["calendar"] = v_yaxis.CalendarValidator() self._validators["categoryarray"] = v_yaxis.CategoryarrayValidator() self._validators["categoryarraysrc"] = v_yaxis.CategoryarraysrcValidator() self._validators["categoryorder"] = v_yaxis.CategoryorderValidator() self._validators["color"] = v_yaxis.ColorValidator() self._validators["dtick"] = v_yaxis.DtickValidator() self._validators["exponentformat"] = v_yaxis.ExponentformatValidator() self._validators["gridcolor"] = v_yaxis.GridcolorValidator() self._validators["gridwidth"] = v_yaxis.GridwidthValidator() self._validators["hoverformat"] = v_yaxis.HoverformatValidator() self._validators["linecolor"] = v_yaxis.LinecolorValidator() self._validators["linewidth"] = v_yaxis.LinewidthValidator() self._validators["mirror"] = v_yaxis.MirrorValidator() self._validators["nticks"] = v_yaxis.NticksValidator() self._validators["range"] = v_yaxis.RangeValidator() self._validators["rangemode"] = v_yaxis.RangemodeValidator() self._validators["separatethousands"] = v_yaxis.SeparatethousandsValidator() self._validators["showaxeslabels"] = v_yaxis.ShowaxeslabelsValidator() self._validators["showbackground"] = v_yaxis.ShowbackgroundValidator() self._validators["showexponent"] = v_yaxis.ShowexponentValidator() self._validators["showgrid"] = v_yaxis.ShowgridValidator() self._validators["showline"] = v_yaxis.ShowlineValidator() self._validators["showspikes"] = v_yaxis.ShowspikesValidator() self._validators["showticklabels"] = v_yaxis.ShowticklabelsValidator() self._validators["showtickprefix"] = v_yaxis.ShowtickprefixValidator() self._validators["showticksuffix"] = v_yaxis.ShowticksuffixValidator() self._validators["spikecolor"] = v_yaxis.SpikecolorValidator() self._validators["spikesides"] = v_yaxis.SpikesidesValidator() self._validators["spikethickness"] = v_yaxis.SpikethicknessValidator() self._validators["tick0"] = v_yaxis.Tick0Validator() self._validators["tickangle"] = v_yaxis.TickangleValidator() self._validators["tickcolor"] = v_yaxis.TickcolorValidator() self._validators["tickfont"] = v_yaxis.TickfontValidator() self._validators["tickformat"] = v_yaxis.TickformatValidator() self._validators["tickformatstops"] = v_yaxis.TickformatstopsValidator() self._validators["tickformatstopdefaults"] = v_yaxis.TickformatstopValidator() self._validators["ticklen"] = v_yaxis.TicklenValidator() self._validators["tickmode"] = v_yaxis.TickmodeValidator() self._validators["tickprefix"] = v_yaxis.TickprefixValidator() self._validators["ticks"] = v_yaxis.TicksValidator() self._validators["ticksuffix"] = v_yaxis.TicksuffixValidator() self._validators["ticktext"] = v_yaxis.TicktextValidator() self._validators["ticktextsrc"] = v_yaxis.TicktextsrcValidator() self._validators["tickvals"] = v_yaxis.TickvalsValidator() self._validators["tickvalssrc"] = v_yaxis.TickvalssrcValidator() self._validators["tickwidth"] = v_yaxis.TickwidthValidator() self._validators["title"] = v_yaxis.TitleValidator() self._validators["type"] = v_yaxis.TypeValidator() self._validators["visible"] = v_yaxis.VisibleValidator() self._validators["zeroline"] = v_yaxis.ZerolineValidator() self._validators["zerolinecolor"] = v_yaxis.ZerolinecolorValidator() self._validators["zerolinewidth"] = v_yaxis.ZerolinewidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autorange", None) self["autorange"] = autorange if autorange is not None else _v _v = arg.pop("backgroundcolor", None) self["backgroundcolor"] = backgroundcolor if backgroundcolor is not None else _v _v = arg.pop("calendar", None) self["calendar"] = calendar if calendar is not None else _v _v = arg.pop("categoryarray", None) self["categoryarray"] = categoryarray if categoryarray is not None else _v _v = arg.pop("categoryarraysrc", None) self["categoryarraysrc"] = ( categoryarraysrc if categoryarraysrc is not None else _v ) _v = arg.pop("categoryorder", None) self["categoryorder"] = categoryorder if categoryorder is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("dtick", None) self["dtick"] = dtick if dtick is not None else _v _v = arg.pop("exponentformat", None) self["exponentformat"] = exponentformat if exponentformat is not None else _v _v = arg.pop("gridcolor", None) self["gridcolor"] = gridcolor if gridcolor is not None else _v _v = arg.pop("gridwidth", None) self["gridwidth"] = gridwidth if gridwidth is not None else _v _v = arg.pop("hoverformat", None) self["hoverformat"] = hoverformat if hoverformat is not None else _v _v = arg.pop("linecolor", None) self["linecolor"] = linecolor if linecolor is not None else _v _v = arg.pop("linewidth", None) self["linewidth"] = linewidth if linewidth is not None else _v _v = arg.pop("mirror", None) self["mirror"] = mirror if mirror is not None else _v _v = arg.pop("nticks", None) self["nticks"] = nticks if nticks is not None else _v _v = arg.pop("range", None) self["range"] = range if range is not None else _v _v = arg.pop("rangemode", None) self["rangemode"] = rangemode if rangemode is not None else _v _v = arg.pop("separatethousands", None) self["separatethousands"] = ( separatethousands if separatethousands is not None else _v ) _v = arg.pop("showaxeslabels", None) self["showaxeslabels"] = showaxeslabels if showaxeslabels is not None else _v _v = arg.pop("showbackground", None) self["showbackground"] = showbackground if showbackground is not None else _v _v = arg.pop("showexponent", None) self["showexponent"] = showexponent if showexponent is not None else _v _v = arg.pop("showgrid", None) self["showgrid"] = showgrid if showgrid is not None else _v _v = arg.pop("showline", None) self["showline"] = showline if showline is not None else _v _v = arg.pop("showspikes", None) self["showspikes"] = showspikes if showspikes is not None else _v _v = arg.pop("showticklabels", None) self["showticklabels"] = showticklabels if showticklabels is not None else _v _v = arg.pop("showtickprefix", None) self["showtickprefix"] = showtickprefix if showtickprefix is not None else _v _v = arg.pop("showticksuffix", None) self["showticksuffix"] = showticksuffix if showticksuffix is not None else _v _v = arg.pop("spikecolor", None) self["spikecolor"] = spikecolor if spikecolor is not None else _v _v = arg.pop("spikesides", None) self["spikesides"] = spikesides if spikesides is not None else _v _v = arg.pop("spikethickness", None) self["spikethickness"] = spikethickness if spikethickness is not None else _v _v = arg.pop("tick0", None) self["tick0"] = tick0 if tick0 is not None else _v _v = arg.pop("tickangle", None) self["tickangle"] = tickangle if tickangle is not None else _v _v = arg.pop("tickcolor", None) self["tickcolor"] = tickcolor if tickcolor is not None else _v _v = arg.pop("tickfont", None) self["tickfont"] = tickfont if tickfont is not None else _v _v = arg.pop("tickformat", None) self["tickformat"] = tickformat if tickformat is not None else _v _v = arg.pop("tickformatstops", None) self["tickformatstops"] = tickformatstops if tickformatstops is not None else _v _v = arg.pop("tickformatstopdefaults", None) self["tickformatstopdefaults"] = ( tickformatstopdefaults if tickformatstopdefaults is not None else _v ) _v = arg.pop("ticklen", None) self["ticklen"] = ticklen if ticklen is not None else _v _v = arg.pop("tickmode", None) self["tickmode"] = tickmode if tickmode is not None else _v _v = arg.pop("tickprefix", None) self["tickprefix"] = tickprefix if tickprefix is not None else _v _v = arg.pop("ticks", None) self["ticks"] = ticks if ticks is not None else _v _v = arg.pop("ticksuffix", None) self["ticksuffix"] = ticksuffix if ticksuffix is not None else _v _v = arg.pop("ticktext", None) self["ticktext"] = ticktext if ticktext is not None else _v _v = arg.pop("ticktextsrc", None) self["ticktextsrc"] = ticktextsrc if ticktextsrc is not None else _v _v = arg.pop("tickvals", None) self["tickvals"] = tickvals if tickvals is not None else _v _v = arg.pop("tickvalssrc", None) self["tickvalssrc"] = tickvalssrc if tickvalssrc is not None else _v _v = arg.pop("tickwidth", None) self["tickwidth"] = tickwidth if tickwidth is not None else _v _v = arg.pop("title", None) self["title"] = title if title is not None else _v _v = arg.pop("titlefont", None) _v = titlefont if titlefont is not None else _v if _v is not None: self["titlefont"] = _v _v = arg.pop("type", None) self["type"] = type if type is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("zeroline", None) self["zeroline"] = zeroline if zeroline is not None else _v _v = arg.pop("zerolinecolor", None) self["zerolinecolor"] = zerolinecolor if zerolinecolor is not None else _v _v = arg.pop("zerolinewidth", None) self["zerolinewidth"] = zerolinewidth if zerolinewidth is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class XAxis(_BaseLayoutHierarchyType): # autorange # --------- @property def autorange(self): """ Determines whether or not the range of this axis is computed in relation to the input data. See `rangemode` for more info. If `range` is provided, then `autorange` is set to False. The 'autorange' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'reversed'] Returns ------- Any """ return self["autorange"] @autorange.setter def autorange(self, val): self["autorange"] = val # backgroundcolor # --------------- @property def backgroundcolor(self): """ Sets the background color of this axis' wall. The 'backgroundcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["backgroundcolor"] @backgroundcolor.setter def backgroundcolor(self, val): self["backgroundcolor"] = val # calendar # -------- @property def calendar(self): """ Sets the calendar system to use for `range` and `tick0` if this is a date axis. This does not set the calendar for interpreting data on this axis, that's specified in the trace or via the global `layout.calendar` The 'calendar' property is an enumeration that may be specified as: - One of the following enumeration values: ['gregorian', 'chinese', 'coptic', 'discworld', 'ethiopian', 'hebrew', 'islamic', 'julian', 'mayan', 'nanakshahi', 'nepali', 'persian', 'jalali', 'taiwan', 'thai', 'ummalqura'] Returns ------- Any """ return self["calendar"] @calendar.setter def calendar(self, val): self["calendar"] = val # categoryarray # ------------- @property def categoryarray(self): """ Sets the order in which categories on this axis appear. Only has an effect if `categoryorder` is set to "array". Used with `categoryorder`. The 'categoryarray' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["categoryarray"] @categoryarray.setter def categoryarray(self, val): self["categoryarray"] = val # categoryarraysrc # ---------------- @property def categoryarraysrc(self): """ Sets the source reference on plot.ly for categoryarray . The 'categoryarraysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["categoryarraysrc"] @categoryarraysrc.setter def categoryarraysrc(self, val): self["categoryarraysrc"] = val # categoryorder # ------------- @property def categoryorder(self): """ Specifies the ordering logic for the case of categorical variables. By default, plotly uses "trace", which specifies the order that is present in the data supplied. Set `categoryorder` to *category ascending* or *category descending* if order should be determined by the alphanumerical order of the category names. Set `categoryorder` to "array" to derive the ordering from the attribute `categoryarray`. If a category is not found in the `categoryarray` array, the sorting behavior for that attribute will be identical to the "trace" mode. The unspecified categories will follow the categories in `categoryarray`. Set `categoryorder` to *total ascending* or *total descending* if order should be determined by the numerical order of the values. Similarly, the order can be determined by the min, max, sum, mean or median of all the values. The 'categoryorder' property is an enumeration that may be specified as: - One of the following enumeration values: ['trace', 'category ascending', 'category descending', 'array', 'total ascending', 'total descending', 'min ascending', 'min descending', 'max ascending', 'max descending', 'sum ascending', 'sum descending', 'mean ascending', 'mean descending', 'median ascending', 'median descending'] Returns ------- Any """ return self["categoryorder"] @categoryorder.setter def categoryorder(self, val): self["categoryorder"] = val # color # ----- @property def color(self): """ Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # dtick # ----- @property def dtick(self): """ Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" The 'dtick' property accepts values of any type Returns ------- Any """ return self["dtick"] @dtick.setter def dtick(self, val): self["dtick"] = val # exponentformat # -------------- @property def exponentformat(self): """ Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. The 'exponentformat' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'e', 'E', 'power', 'SI', 'B'] Returns ------- Any """ return self["exponentformat"] @exponentformat.setter def exponentformat(self, val): self["exponentformat"] = val # gridcolor # --------- @property def gridcolor(self): """ Sets the color of the grid lines. The 'gridcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["gridcolor"] @gridcolor.setter def gridcolor(self, val): self["gridcolor"] = val # gridwidth # --------- @property def gridwidth(self): """ Sets the width (in px) of the grid lines. The 'gridwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["gridwidth"] @gridwidth.setter def gridwidth(self, val): self["gridwidth"] = val # hoverformat # ----------- @property def hoverformat(self): """ Sets the hover text formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'hoverformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["hoverformat"] @hoverformat.setter def hoverformat(self, val): self["hoverformat"] = val # linecolor # --------- @property def linecolor(self): """ Sets the axis line color. The 'linecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["linecolor"] @linecolor.setter def linecolor(self, val): self["linecolor"] = val # linewidth # --------- @property def linewidth(self): """ Sets the width (in px) of the axis line. The 'linewidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["linewidth"] @linewidth.setter def linewidth(self, val): self["linewidth"] = val # mirror # ------ @property def mirror(self): """ Determines if the axis lines or/and ticks are mirrored to the opposite side of the plotting area. If True, the axis lines are mirrored. If "ticks", the axis lines and ticks are mirrored. If False, mirroring is disable. If "all", axis lines are mirrored on all shared-axes subplots. If "allticks", axis lines and ticks are mirrored on all shared-axes subplots. The 'mirror' property is an enumeration that may be specified as: - One of the following enumeration values: [True, 'ticks', False, 'all', 'allticks'] Returns ------- Any """ return self["mirror"] @mirror.setter def mirror(self, val): self["mirror"] = val # nticks # ------ @property def nticks(self): """ Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". The 'nticks' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nticks"] @nticks.setter def nticks(self, val): self["nticks"] = val # range # ----- @property def range(self): """ Sets the range of this axis. If the axis `type` is "log", then you must take the log of your desired range (e.g. to set the range from 1 to 100, set the range from 0 to 2). If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. The 'range' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'range[0]' property accepts values of any type (1) The 'range[1]' property accepts values of any type Returns ------- list """ return self["range"] @range.setter def range(self, val): self["range"] = val # rangemode # --------- @property def rangemode(self): """ If "normal", the range is computed in relation to the extrema of the input data. If *tozero*`, the range extends to 0, regardless of the input data If "nonnegative", the range is non-negative, regardless of the input data. Applies only to linear axes. The 'rangemode' property is an enumeration that may be specified as: - One of the following enumeration values: ['normal', 'tozero', 'nonnegative'] Returns ------- Any """ return self["rangemode"] @rangemode.setter def rangemode(self, val): self["rangemode"] = val # separatethousands # ----------------- @property def separatethousands(self): """ If "true", even 4-digit integers are separated The 'separatethousands' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["separatethousands"] @separatethousands.setter def separatethousands(self, val): self["separatethousands"] = val # showaxeslabels # -------------- @property def showaxeslabels(self): """ Sets whether or not this axis is labeled The 'showaxeslabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showaxeslabels"] @showaxeslabels.setter def showaxeslabels(self, val): self["showaxeslabels"] = val # showbackground # -------------- @property def showbackground(self): """ Sets whether or not this axis' wall has a background color. The 'showbackground' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showbackground"] @showbackground.setter def showbackground(self, val): self["showbackground"] = val # showexponent # ------------ @property def showexponent(self): """ If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. The 'showexponent' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showexponent"] @showexponent.setter def showexponent(self, val): self["showexponent"] = val # showgrid # -------- @property def showgrid(self): """ Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. The 'showgrid' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showgrid"] @showgrid.setter def showgrid(self, val): self["showgrid"] = val # showline # -------- @property def showline(self): """ Determines whether or not a line bounding this axis is drawn. The 'showline' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showline"] @showline.setter def showline(self, val): self["showline"] = val # showspikes # ---------- @property def showspikes(self): """ Sets whether or not spikes starting from data points to this axis' wall are shown on hover. The 'showspikes' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showspikes"] @showspikes.setter def showspikes(self, val): self["showspikes"] = val # showticklabels # -------------- @property def showticklabels(self): """ Determines whether or not the tick labels are drawn. The 'showticklabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showticklabels"] @showticklabels.setter def showticklabels(self, val): self["showticklabels"] = val # showtickprefix # -------------- @property def showtickprefix(self): """ If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. The 'showtickprefix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showtickprefix"] @showtickprefix.setter def showtickprefix(self, val): self["showtickprefix"] = val # showticksuffix # -------------- @property def showticksuffix(self): """ Same as `showtickprefix` but for tick suffixes. The 'showticksuffix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showticksuffix"] @showticksuffix.setter def showticksuffix(self, val): self["showticksuffix"] = val # spikecolor # ---------- @property def spikecolor(self): """ Sets the color of the spikes. The 'spikecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["spikecolor"] @spikecolor.setter def spikecolor(self, val): self["spikecolor"] = val # spikesides # ---------- @property def spikesides(self): """ Sets whether or not spikes extending from the projection data points to this axis' wall boundaries are shown on hover. The 'spikesides' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["spikesides"] @spikesides.setter def spikesides(self, val): self["spikesides"] = val # spikethickness # -------------- @property def spikethickness(self): """ Sets the thickness (in px) of the spikes. The 'spikethickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["spikethickness"] @spikethickness.setter def spikethickness(self, val): self["spikethickness"] = val # tick0 # ----- @property def tick0(self): """ Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. The 'tick0' property accepts values of any type Returns ------- Any """ return self["tick0"] @tick0.setter def tick0(self, val): self["tick0"] = val # tickangle # --------- @property def tickangle(self): """ Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. The 'tickangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["tickangle"] @tickangle.setter def tickangle(self, val): self["tickangle"] = val # tickcolor # --------- @property def tickcolor(self): """ Sets the tick color. The 'tickcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["tickcolor"] @tickcolor.setter def tickcolor(self, val): self["tickcolor"] = val # tickfont # -------- @property def tickfont(self): """ Sets the tick font. The 'tickfont' property is an instance of Tickfont that may be specified as: - An instance of plotly.graph_objs.layout.scene.xaxis.Tickfont - A dict of string/value properties that will be passed to the Tickfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.layout.scene.xaxis.Tickfont """ return self["tickfont"] @tickfont.setter def tickfont(self, val): self["tickfont"] = val # tickformat # ---------- @property def tickformat(self): """ Sets the tick label formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'tickformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickformat"] @tickformat.setter def tickformat(self, val): self["tickformat"] = val # tickformatstops # --------------- @property def tickformatstops(self): """ The 'tickformatstops' property is a tuple of instances of Tickformatstop that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.scene.xaxis.Tickformatstop - A list or tuple of dicts of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- tuple[plotly.graph_objs.layout.scene.xaxis.Tickformatstop] """ return self["tickformatstops"] @tickformatstops.setter def tickformatstops(self, val): self["tickformatstops"] = val # tickformatstopdefaults # ---------------------- @property def tickformatstopdefaults(self): """ When used in a template (as layout.template.layout.scene.xaxis.tickformatstopdefaults), sets the default property values to use for elements of layout.scene.xaxis.tickformatstops The 'tickformatstopdefaults' property is an instance of Tickformatstop that may be specified as: - An instance of plotly.graph_objs.layout.scene.xaxis.Tickformatstop - A dict of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: Returns ------- plotly.graph_objs.layout.scene.xaxis.Tickformatstop """ return self["tickformatstopdefaults"] @tickformatstopdefaults.setter def tickformatstopdefaults(self, val): self["tickformatstopdefaults"] = val # ticklen # ------- @property def ticklen(self): """ Sets the tick length (in px). The 'ticklen' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ticklen"] @ticklen.setter def ticklen(self, val): self["ticklen"] = val # tickmode # -------- @property def tickmode(self): """ Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). The 'tickmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'linear', 'array'] Returns ------- Any """ return self["tickmode"] @tickmode.setter def tickmode(self, val): self["tickmode"] = val # tickprefix # ---------- @property def tickprefix(self): """ Sets a tick label prefix. The 'tickprefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickprefix"] @tickprefix.setter def tickprefix(self, val): self["tickprefix"] = val # ticks # ----- @property def ticks(self): """ Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. The 'ticks' property is an enumeration that may be specified as: - One of the following enumeration values: ['outside', 'inside', ''] Returns ------- Any """ return self["ticks"] @ticks.setter def ticks(self, val): self["ticks"] = val # ticksuffix # ---------- @property def ticksuffix(self): """ Sets a tick label suffix. The 'ticksuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ticksuffix"] @ticksuffix.setter def ticksuffix(self, val): self["ticksuffix"] = val # ticktext # -------- @property def ticktext(self): """ Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. The 'ticktext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ticktext"] @ticktext.setter def ticktext(self, val): self["ticktext"] = val # ticktextsrc # ----------- @property def ticktextsrc(self): """ Sets the source reference on plot.ly for ticktext . The 'ticktextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ticktextsrc"] @ticktextsrc.setter def ticktextsrc(self, val): self["ticktextsrc"] = val # tickvals # -------- @property def tickvals(self): """ Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. The 'tickvals' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["tickvals"] @tickvals.setter def tickvals(self, val): self["tickvals"] = val # tickvalssrc # ----------- @property def tickvalssrc(self): """ Sets the source reference on plot.ly for tickvals . The 'tickvalssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tickvalssrc"] @tickvalssrc.setter def tickvalssrc(self, val): self["tickvalssrc"] = val # tickwidth # --------- @property def tickwidth(self): """ Sets the tick width (in px). The 'tickwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["tickwidth"] @tickwidth.setter def tickwidth(self, val): self["tickwidth"] = val # title # ----- @property def title(self): """ The 'title' property is an instance of Title that may be specified as: - An instance of plotly.graph_objs.layout.scene.xaxis.Title - A dict of string/value properties that will be passed to the Title constructor Supported dict properties: font Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. text Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- plotly.graph_objs.layout.scene.xaxis.Title """ return self["title"] @title.setter def title(self, val): self["title"] = val # titlefont # --------- @property def titlefont(self): """ Deprecated: Please use layout.scene.xaxis.title.font instead. Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.layout.scene.xaxis.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- """ return self["titlefont"] @titlefont.setter def titlefont(self, val): self["titlefont"] = val # type # ---- @property def type(self): """ Sets the axis type. By default, plotly attempts to determined the axis type by looking into the data of the traces that referenced the axis in question. The 'type' property is an enumeration that may be specified as: - One of the following enumeration values: ['-', 'linear', 'log', 'date', 'category'] Returns ------- Any """ return self["type"] @type.setter def type(self, val): self["type"] = val # visible # ------- @property def visible(self): """ A single toggle to hide the axis while preserving interaction like dragging. Default is true when a cheater plot is present on the axis, otherwise false The 'visible' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # zeroline # -------- @property def zeroline(self): """ Determines whether or not a line is drawn at along the 0 value of this axis. If True, the zero line is drawn on top of the grid lines. The 'zeroline' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["zeroline"] @zeroline.setter def zeroline(self, val): self["zeroline"] = val # zerolinecolor # ------------- @property def zerolinecolor(self): """ Sets the line color of the zero line. The 'zerolinecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["zerolinecolor"] @zerolinecolor.setter def zerolinecolor(self, val): self["zerolinecolor"] = val # zerolinewidth # ------------- @property def zerolinewidth(self): """ Sets the width (in px) of the zero line. The 'zerolinewidth' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["zerolinewidth"] @zerolinewidth.setter def zerolinewidth(self, val): self["zerolinewidth"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.scene" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autorange Determines whether or not the range of this axis is computed in relation to the input data. See `rangemode` for more info. If `range` is provided, then `autorange` is set to False. backgroundcolor Sets the background color of this axis' wall. calendar Sets the calendar system to use for `range` and `tick0` if this is a date axis. This does not set the calendar for interpreting data on this axis, that's specified in the trace or via the global `layout.calendar` categoryarray Sets the order in which categories on this axis appear. Only has an effect if `categoryorder` is set to "array". Used with `categoryorder`. categoryarraysrc Sets the source reference on plot.ly for categoryarray . categoryorder Specifies the ordering logic for the case of categorical variables. By default, plotly uses "trace", which specifies the order that is present in the data supplied. Set `categoryorder` to *category ascending* or *category descending* if order should be determined by the alphanumerical order of the category names. Set `categoryorder` to "array" to derive the ordering from the attribute `categoryarray`. If a category is not found in the `categoryarray` array, the sorting behavior for that attribute will be identical to the "trace" mode. The unspecified categories will follow the categories in `categoryarray`. Set `categoryorder` to *total ascending* or *total descending* if order should be determined by the numerical order of the values. Similarly, the order can be determined by the min, max, sum, mean or median of all the values. color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. gridcolor Sets the color of the grid lines. gridwidth Sets the width (in px) of the grid lines. hoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" linecolor Sets the axis line color. linewidth Sets the width (in px) of the axis line. mirror Determines if the axis lines or/and ticks are mirrored to the opposite side of the plotting area. If True, the axis lines are mirrored. If "ticks", the axis lines and ticks are mirrored. If False, mirroring is disable. If "all", axis lines are mirrored on all shared-axes subplots. If "allticks", axis lines and ticks are mirrored on all shared-axes subplots. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". range Sets the range of this axis. If the axis `type` is "log", then you must take the log of your desired range (e.g. to set the range from 1 to 100, set the range from 0 to 2). If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. rangemode If "normal", the range is computed in relation to the extrema of the input data. If *tozero*`, the range extends to 0, regardless of the input data If "nonnegative", the range is non-negative, regardless of the input data. Applies only to linear axes. separatethousands If "true", even 4-digit integers are separated showaxeslabels Sets whether or not this axis is labeled showbackground Sets whether or not this axis' wall has a background color. showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showgrid Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. showline Determines whether or not a line bounding this axis is drawn. showspikes Sets whether or not spikes starting from data points to this axis' wall are shown on hover. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. spikecolor Sets the color of the spikes. spikesides Sets whether or not spikes extending from the projection data points to this axis' wall boundaries are shown on hover. spikethickness Sets the thickness (in px) of the spikes. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the tick font. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.layout.scene.xaxis.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.layout.scen e.xaxis.tickformatstopdefaults), sets the default property values to use for elements of layout.scene.xaxis.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.layout.scene.xaxis.Title instance or dict with compatible properties titlefont Deprecated: Please use layout.scene.xaxis.title.font instead. Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. type Sets the axis type. By default, plotly attempts to determined the axis type by looking into the data of the traces that referenced the axis in question. visible A single toggle to hide the axis while preserving interaction like dragging. Default is true when a cheater plot is present on the axis, otherwise false zeroline Determines whether or not a line is drawn at along the 0 value of this axis. If True, the zero line is drawn on top of the grid lines. zerolinecolor Sets the line color of the zero line. zerolinewidth Sets the width (in px) of the zero line. """ _mapped_properties = {"titlefont": ("title", "font")} def __init__( self, arg=None, autorange=None, backgroundcolor=None, calendar=None, categoryarray=None, categoryarraysrc=None, categoryorder=None, color=None, dtick=None, exponentformat=None, gridcolor=None, gridwidth=None, hoverformat=None, linecolor=None, linewidth=None, mirror=None, nticks=None, range=None, rangemode=None, separatethousands=None, showaxeslabels=None, showbackground=None, showexponent=None, showgrid=None, showline=None, showspikes=None, showticklabels=None, showtickprefix=None, showticksuffix=None, spikecolor=None, spikesides=None, spikethickness=None, tick0=None, tickangle=None, tickcolor=None, tickfont=None, tickformat=None, tickformatstops=None, tickformatstopdefaults=None, ticklen=None, tickmode=None, tickprefix=None, ticks=None, ticksuffix=None, ticktext=None, ticktextsrc=None, tickvals=None, tickvalssrc=None, tickwidth=None, title=None, titlefont=None, type=None, visible=None, zeroline=None, zerolinecolor=None, zerolinewidth=None, **kwargs ): """ Construct a new XAxis object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.scene.XAxis autorange Determines whether or not the range of this axis is computed in relation to the input data. See `rangemode` for more info. If `range` is provided, then `autorange` is set to False. backgroundcolor Sets the background color of this axis' wall. calendar Sets the calendar system to use for `range` and `tick0` if this is a date axis. This does not set the calendar for interpreting data on this axis, that's specified in the trace or via the global `layout.calendar` categoryarray Sets the order in which categories on this axis appear. Only has an effect if `categoryorder` is set to "array". Used with `categoryorder`. categoryarraysrc Sets the source reference on plot.ly for categoryarray . categoryorder Specifies the ordering logic for the case of categorical variables. By default, plotly uses "trace", which specifies the order that is present in the data supplied. Set `categoryorder` to *category ascending* or *category descending* if order should be determined by the alphanumerical order of the category names. Set `categoryorder` to "array" to derive the ordering from the attribute `categoryarray`. If a category is not found in the `categoryarray` array, the sorting behavior for that attribute will be identical to the "trace" mode. The unspecified categories will follow the categories in `categoryarray`. Set `categoryorder` to *total ascending* or *total descending* if order should be determined by the numerical order of the values. Similarly, the order can be determined by the min, max, sum, mean or median of all the values. color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. gridcolor Sets the color of the grid lines. gridwidth Sets the width (in px) of the grid lines. hoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" linecolor Sets the axis line color. linewidth Sets the width (in px) of the axis line. mirror Determines if the axis lines or/and ticks are mirrored to the opposite side of the plotting area. If True, the axis lines are mirrored. If "ticks", the axis lines and ticks are mirrored. If False, mirroring is disable. If "all", axis lines are mirrored on all shared-axes subplots. If "allticks", axis lines and ticks are mirrored on all shared-axes subplots. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". range Sets the range of this axis. If the axis `type` is "log", then you must take the log of your desired range (e.g. to set the range from 1 to 100, set the range from 0 to 2). If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. rangemode If "normal", the range is computed in relation to the extrema of the input data. If *tozero*`, the range extends to 0, regardless of the input data If "nonnegative", the range is non-negative, regardless of the input data. Applies only to linear axes. separatethousands If "true", even 4-digit integers are separated showaxeslabels Sets whether or not this axis is labeled showbackground Sets whether or not this axis' wall has a background color. showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showgrid Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. showline Determines whether or not a line bounding this axis is drawn. showspikes Sets whether or not spikes starting from data points to this axis' wall are shown on hover. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. spikecolor Sets the color of the spikes. spikesides Sets whether or not spikes extending from the projection data points to this axis' wall boundaries are shown on hover. spikethickness Sets the thickness (in px) of the spikes. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the tick font. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.layout.scene.xaxis.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.layout.scen e.xaxis.tickformatstopdefaults), sets the default property values to use for elements of layout.scene.xaxis.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.layout.scene.xaxis.Title instance or dict with compatible properties titlefont Deprecated: Please use layout.scene.xaxis.title.font instead. Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. type Sets the axis type. By default, plotly attempts to determined the axis type by looking into the data of the traces that referenced the axis in question. visible A single toggle to hide the axis while preserving interaction like dragging. Default is true when a cheater plot is present on the axis, otherwise false zeroline Determines whether or not a line is drawn at along the 0 value of this axis. If True, the zero line is drawn on top of the grid lines. zerolinecolor Sets the line color of the zero line. zerolinewidth Sets the width (in px) of the zero line. Returns ------- XAxis """ super(XAxis, self).__init__("xaxis") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.scene.XAxis constructor must be a dict or an instance of plotly.graph_objs.layout.scene.XAxis""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.scene import xaxis as v_xaxis # Initialize validators # --------------------- self._validators["autorange"] = v_xaxis.AutorangeValidator() self._validators["backgroundcolor"] = v_xaxis.BackgroundcolorValidator() self._validators["calendar"] = v_xaxis.CalendarValidator() self._validators["categoryarray"] = v_xaxis.CategoryarrayValidator() self._validators["categoryarraysrc"] = v_xaxis.CategoryarraysrcValidator() self._validators["categoryorder"] = v_xaxis.CategoryorderValidator() self._validators["color"] = v_xaxis.ColorValidator() self._validators["dtick"] = v_xaxis.DtickValidator() self._validators["exponentformat"] = v_xaxis.ExponentformatValidator() self._validators["gridcolor"] = v_xaxis.GridcolorValidator() self._validators["gridwidth"] = v_xaxis.GridwidthValidator() self._validators["hoverformat"] = v_xaxis.HoverformatValidator() self._validators["linecolor"] = v_xaxis.LinecolorValidator() self._validators["linewidth"] = v_xaxis.LinewidthValidator() self._validators["mirror"] = v_xaxis.MirrorValidator() self._validators["nticks"] = v_xaxis.NticksValidator() self._validators["range"] = v_xaxis.RangeValidator() self._validators["rangemode"] = v_xaxis.RangemodeValidator() self._validators["separatethousands"] = v_xaxis.SeparatethousandsValidator() self._validators["showaxeslabels"] = v_xaxis.ShowaxeslabelsValidator() self._validators["showbackground"] = v_xaxis.ShowbackgroundValidator() self._validators["showexponent"] = v_xaxis.ShowexponentValidator() self._validators["showgrid"] = v_xaxis.ShowgridValidator() self._validators["showline"] = v_xaxis.ShowlineValidator() self._validators["showspikes"] = v_xaxis.ShowspikesValidator() self._validators["showticklabels"] = v_xaxis.ShowticklabelsValidator() self._validators["showtickprefix"] = v_xaxis.ShowtickprefixValidator() self._validators["showticksuffix"] = v_xaxis.ShowticksuffixValidator() self._validators["spikecolor"] = v_xaxis.SpikecolorValidator() self._validators["spikesides"] = v_xaxis.SpikesidesValidator() self._validators["spikethickness"] = v_xaxis.SpikethicknessValidator() self._validators["tick0"] = v_xaxis.Tick0Validator() self._validators["tickangle"] = v_xaxis.TickangleValidator() self._validators["tickcolor"] = v_xaxis.TickcolorValidator() self._validators["tickfont"] = v_xaxis.TickfontValidator() self._validators["tickformat"] = v_xaxis.TickformatValidator() self._validators["tickformatstops"] = v_xaxis.TickformatstopsValidator() self._validators["tickformatstopdefaults"] = v_xaxis.TickformatstopValidator() self._validators["ticklen"] = v_xaxis.TicklenValidator() self._validators["tickmode"] = v_xaxis.TickmodeValidator() self._validators["tickprefix"] = v_xaxis.TickprefixValidator() self._validators["ticks"] = v_xaxis.TicksValidator() self._validators["ticksuffix"] = v_xaxis.TicksuffixValidator() self._validators["ticktext"] = v_xaxis.TicktextValidator() self._validators["ticktextsrc"] = v_xaxis.TicktextsrcValidator() self._validators["tickvals"] = v_xaxis.TickvalsValidator() self._validators["tickvalssrc"] = v_xaxis.TickvalssrcValidator() self._validators["tickwidth"] = v_xaxis.TickwidthValidator() self._validators["title"] = v_xaxis.TitleValidator() self._validators["type"] = v_xaxis.TypeValidator() self._validators["visible"] = v_xaxis.VisibleValidator() self._validators["zeroline"] = v_xaxis.ZerolineValidator() self._validators["zerolinecolor"] = v_xaxis.ZerolinecolorValidator() self._validators["zerolinewidth"] = v_xaxis.ZerolinewidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autorange", None) self["autorange"] = autorange if autorange is not None else _v _v = arg.pop("backgroundcolor", None) self["backgroundcolor"] = backgroundcolor if backgroundcolor is not None else _v _v = arg.pop("calendar", None) self["calendar"] = calendar if calendar is not None else _v _v = arg.pop("categoryarray", None) self["categoryarray"] = categoryarray if categoryarray is not None else _v _v = arg.pop("categoryarraysrc", None) self["categoryarraysrc"] = ( categoryarraysrc if categoryarraysrc is not None else _v ) _v = arg.pop("categoryorder", None) self["categoryorder"] = categoryorder if categoryorder is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("dtick", None) self["dtick"] = dtick if dtick is not None else _v _v = arg.pop("exponentformat", None) self["exponentformat"] = exponentformat if exponentformat is not None else _v _v = arg.pop("gridcolor", None) self["gridcolor"] = gridcolor if gridcolor is not None else _v _v = arg.pop("gridwidth", None) self["gridwidth"] = gridwidth if gridwidth is not None else _v _v = arg.pop("hoverformat", None) self["hoverformat"] = hoverformat if hoverformat is not None else _v _v = arg.pop("linecolor", None) self["linecolor"] = linecolor if linecolor is not None else _v _v = arg.pop("linewidth", None) self["linewidth"] = linewidth if linewidth is not None else _v _v = arg.pop("mirror", None) self["mirror"] = mirror if mirror is not None else _v _v = arg.pop("nticks", None) self["nticks"] = nticks if nticks is not None else _v _v = arg.pop("range", None) self["range"] = range if range is not None else _v _v = arg.pop("rangemode", None) self["rangemode"] = rangemode if rangemode is not None else _v _v = arg.pop("separatethousands", None) self["separatethousands"] = ( separatethousands if separatethousands is not None else _v ) _v = arg.pop("showaxeslabels", None) self["showaxeslabels"] = showaxeslabels if showaxeslabels is not None else _v _v = arg.pop("showbackground", None) self["showbackground"] = showbackground if showbackground is not None else _v _v = arg.pop("showexponent", None) self["showexponent"] = showexponent if showexponent is not None else _v _v = arg.pop("showgrid", None) self["showgrid"] = showgrid if showgrid is not None else _v _v = arg.pop("showline", None) self["showline"] = showline if showline is not None else _v _v = arg.pop("showspikes", None) self["showspikes"] = showspikes if showspikes is not None else _v _v = arg.pop("showticklabels", None) self["showticklabels"] = showticklabels if showticklabels is not None else _v _v = arg.pop("showtickprefix", None) self["showtickprefix"] = showtickprefix if showtickprefix is not None else _v _v = arg.pop("showticksuffix", None) self["showticksuffix"] = showticksuffix if showticksuffix is not None else _v _v = arg.pop("spikecolor", None) self["spikecolor"] = spikecolor if spikecolor is not None else _v _v = arg.pop("spikesides", None) self["spikesides"] = spikesides if spikesides is not None else _v _v = arg.pop("spikethickness", None) self["spikethickness"] = spikethickness if spikethickness is not None else _v _v = arg.pop("tick0", None) self["tick0"] = tick0 if tick0 is not None else _v _v = arg.pop("tickangle", None) self["tickangle"] = tickangle if tickangle is not None else _v _v = arg.pop("tickcolor", None) self["tickcolor"] = tickcolor if tickcolor is not None else _v _v = arg.pop("tickfont", None) self["tickfont"] = tickfont if tickfont is not None else _v _v = arg.pop("tickformat", None) self["tickformat"] = tickformat if tickformat is not None else _v _v = arg.pop("tickformatstops", None) self["tickformatstops"] = tickformatstops if tickformatstops is not None else _v _v = arg.pop("tickformatstopdefaults", None) self["tickformatstopdefaults"] = ( tickformatstopdefaults if tickformatstopdefaults is not None else _v ) _v = arg.pop("ticklen", None) self["ticklen"] = ticklen if ticklen is not None else _v _v = arg.pop("tickmode", None) self["tickmode"] = tickmode if tickmode is not None else _v _v = arg.pop("tickprefix", None) self["tickprefix"] = tickprefix if tickprefix is not None else _v _v = arg.pop("ticks", None) self["ticks"] = ticks if ticks is not None else _v _v = arg.pop("ticksuffix", None) self["ticksuffix"] = ticksuffix if ticksuffix is not None else _v _v = arg.pop("ticktext", None) self["ticktext"] = ticktext if ticktext is not None else _v _v = arg.pop("ticktextsrc", None) self["ticktextsrc"] = ticktextsrc if ticktextsrc is not None else _v _v = arg.pop("tickvals", None) self["tickvals"] = tickvals if tickvals is not None else _v _v = arg.pop("tickvalssrc", None) self["tickvalssrc"] = tickvalssrc if tickvalssrc is not None else _v _v = arg.pop("tickwidth", None) self["tickwidth"] = tickwidth if tickwidth is not None else _v _v = arg.pop("title", None) self["title"] = title if title is not None else _v _v = arg.pop("titlefont", None) _v = titlefont if titlefont is not None else _v if _v is not None: self["titlefont"] = _v _v = arg.pop("type", None) self["type"] = type if type is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("zeroline", None) self["zeroline"] = zeroline if zeroline is not None else _v _v = arg.pop("zerolinecolor", None) self["zerolinecolor"] = zerolinecolor if zerolinecolor is not None else _v _v = arg.pop("zerolinewidth", None) self["zerolinewidth"] = zerolinewidth if zerolinewidth is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Domain(_BaseLayoutHierarchyType): # column # ------ @property def column(self): """ If there is a layout grid, use the domain for this column in the grid for this scene subplot . The 'column' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["column"] @column.setter def column(self, val): self["column"] = val # row # --- @property def row(self): """ If there is a layout grid, use the domain for this row in the grid for this scene subplot . The 'row' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["row"] @row.setter def row(self, val): self["row"] = val # x # - @property def x(self): """ Sets the horizontal domain of this scene subplot (in plot fraction). The 'x' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'x[0]' property is a number and may be specified as: - An int or float in the interval [0, 1] (1) The 'x[1]' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- list """ return self["x"] @x.setter def x(self, val): self["x"] = val # y # - @property def y(self): """ Sets the vertical domain of this scene subplot (in plot fraction). The 'y' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'y[0]' property is a number and may be specified as: - An int or float in the interval [0, 1] (1) The 'y[1]' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- list """ return self["y"] @y.setter def y(self, val): self["y"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.scene" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ column If there is a layout grid, use the domain for this column in the grid for this scene subplot . row If there is a layout grid, use the domain for this row in the grid for this scene subplot . x Sets the horizontal domain of this scene subplot (in plot fraction). y Sets the vertical domain of this scene subplot (in plot fraction). """ def __init__(self, arg=None, column=None, row=None, x=None, y=None, **kwargs): """ Construct a new Domain object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.scene.Domain column If there is a layout grid, use the domain for this column in the grid for this scene subplot . row If there is a layout grid, use the domain for this row in the grid for this scene subplot . x Sets the horizontal domain of this scene subplot (in plot fraction). y Sets the vertical domain of this scene subplot (in plot fraction). Returns ------- Domain """ super(Domain, self).__init__("domain") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.scene.Domain constructor must be a dict or an instance of plotly.graph_objs.layout.scene.Domain""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.scene import domain as v_domain # Initialize validators # --------------------- self._validators["column"] = v_domain.ColumnValidator() self._validators["row"] = v_domain.RowValidator() self._validators["x"] = v_domain.XValidator() self._validators["y"] = v_domain.YValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("column", None) self["column"] = column if column is not None else _v _v = arg.pop("row", None) self["row"] = row if row is not None else _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Camera(_BaseLayoutHierarchyType): # center # ------ @property def center(self): """ Sets the (x,y,z) components of the 'center' camera vector This vector determines the translation (x,y,z) space about the center of this scene. By default, there is no such translation. The 'center' property is an instance of Center that may be specified as: - An instance of plotly.graph_objs.layout.scene.camera.Center - A dict of string/value properties that will be passed to the Center constructor Supported dict properties: x y z Returns ------- plotly.graph_objs.layout.scene.camera.Center """ return self["center"] @center.setter def center(self, val): self["center"] = val # eye # --- @property def eye(self): """ Sets the (x,y,z) components of the 'eye' camera vector. This vector determines the view point about the origin of this scene. The 'eye' property is an instance of Eye that may be specified as: - An instance of plotly.graph_objs.layout.scene.camera.Eye - A dict of string/value properties that will be passed to the Eye constructor Supported dict properties: x y z Returns ------- plotly.graph_objs.layout.scene.camera.Eye """ return self["eye"] @eye.setter def eye(self, val): self["eye"] = val # projection # ---------- @property def projection(self): """ The 'projection' property is an instance of Projection that may be specified as: - An instance of plotly.graph_objs.layout.scene.camera.Projection - A dict of string/value properties that will be passed to the Projection constructor Supported dict properties: type Sets the projection type. The projection type could be either "perspective" or "orthographic". The default is "perspective". Returns ------- plotly.graph_objs.layout.scene.camera.Projection """ return self["projection"] @projection.setter def projection(self, val): self["projection"] = val # up # -- @property def up(self): """ Sets the (x,y,z) components of the 'up' camera vector. This vector determines the up direction of this scene with respect to the page. The default is *{x: 0, y: 0, z: 1}* which means that the z axis points up. The 'up' property is an instance of Up that may be specified as: - An instance of plotly.graph_objs.layout.scene.camera.Up - A dict of string/value properties that will be passed to the Up constructor Supported dict properties: x y z Returns ------- plotly.graph_objs.layout.scene.camera.Up """ return self["up"] @up.setter def up(self, val): self["up"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.scene" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ center Sets the (x,y,z) components of the 'center' camera vector This vector determines the translation (x,y,z) space about the center of this scene. By default, there is no such translation. eye Sets the (x,y,z) components of the 'eye' camera vector. This vector determines the view point about the origin of this scene. projection plotly.graph_objects.layout.scene.camera.Projection instance or dict with compatible properties up Sets the (x,y,z) components of the 'up' camera vector. This vector determines the up direction of this scene with respect to the page. The default is *{x: 0, y: 0, z: 1}* which means that the z axis points up. """ def __init__( self, arg=None, center=None, eye=None, projection=None, up=None, **kwargs ): """ Construct a new Camera object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.scene.Camera center Sets the (x,y,z) components of the 'center' camera vector This vector determines the translation (x,y,z) space about the center of this scene. By default, there is no such translation. eye Sets the (x,y,z) components of the 'eye' camera vector. This vector determines the view point about the origin of this scene. projection plotly.graph_objects.layout.scene.camera.Projection instance or dict with compatible properties up Sets the (x,y,z) components of the 'up' camera vector. This vector determines the up direction of this scene with respect to the page. The default is *{x: 0, y: 0, z: 1}* which means that the z axis points up. Returns ------- Camera """ super(Camera, self).__init__("camera") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.scene.Camera constructor must be a dict or an instance of plotly.graph_objs.layout.scene.Camera""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.scene import camera as v_camera # Initialize validators # --------------------- self._validators["center"] = v_camera.CenterValidator() self._validators["eye"] = v_camera.EyeValidator() self._validators["projection"] = v_camera.ProjectionValidator() self._validators["up"] = v_camera.UpValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("center", None) self["center"] = center if center is not None else _v _v = arg.pop("eye", None) self["eye"] = eye if eye is not None else _v _v = arg.pop("projection", None) self["projection"] = projection if projection is not None else _v _v = arg.pop("up", None) self["up"] = up if up is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Aspectratio(_BaseLayoutHierarchyType): # x # - @property def x(self): """ The 'x' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["x"] @x.setter def x(self, val): self["x"] = val # y # - @property def y(self): """ The 'y' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["y"] @y.setter def y(self, val): self["y"] = val # z # - @property def z(self): """ The 'z' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["z"] @z.setter def z(self, val): self["z"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.scene" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ x y z """ def __init__(self, arg=None, x=None, y=None, z=None, **kwargs): """ Construct a new Aspectratio object Sets this scene's axis aspectratio. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.scene.Aspectratio x y z Returns ------- Aspectratio """ super(Aspectratio, self).__init__("aspectratio") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.scene.Aspectratio constructor must be a dict or an instance of plotly.graph_objs.layout.scene.Aspectratio""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.scene import aspectratio as v_aspectratio # Initialize validators # --------------------- self._validators["x"] = v_aspectratio.XValidator() self._validators["y"] = v_aspectratio.YValidator() self._validators["z"] = v_aspectratio.ZValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("z", None) self["z"] = z if z is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Annotation(_BaseLayoutHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the `text` within the box. Has an effect only if `text` spans more two or more lines (i.e. `text` contains one or more
HTML tags) or if an explicit width is set to override the text width. The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'center', 'right'] Returns ------- Any """ return self["align"] @align.setter def align(self, val): self["align"] = val # arrowcolor # ---------- @property def arrowcolor(self): """ Sets the color of the annotation arrow. The 'arrowcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["arrowcolor"] @arrowcolor.setter def arrowcolor(self, val): self["arrowcolor"] = val # arrowhead # --------- @property def arrowhead(self): """ Sets the end annotation arrow head style. The 'arrowhead' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 8] Returns ------- int """ return self["arrowhead"] @arrowhead.setter def arrowhead(self, val): self["arrowhead"] = val # arrowside # --------- @property def arrowside(self): """ Sets the annotation arrow head position. The 'arrowside' property is a flaglist and may be specified as a string containing: - Any combination of ['end', 'start'] joined with '+' characters (e.g. 'end+start') OR exactly one of ['none'] (e.g. 'none') Returns ------- Any """ return self["arrowside"] @arrowside.setter def arrowside(self, val): self["arrowside"] = val # arrowsize # --------- @property def arrowsize(self): """ Sets the size of the end annotation arrow head, relative to `arrowwidth`. A value of 1 (default) gives a head about 3x as wide as the line. The 'arrowsize' property is a number and may be specified as: - An int or float in the interval [0.3, inf] Returns ------- int|float """ return self["arrowsize"] @arrowsize.setter def arrowsize(self, val): self["arrowsize"] = val # arrowwidth # ---------- @property def arrowwidth(self): """ Sets the width (in px) of annotation arrow line. The 'arrowwidth' property is a number and may be specified as: - An int or float in the interval [0.1, inf] Returns ------- int|float """ return self["arrowwidth"] @arrowwidth.setter def arrowwidth(self, val): self["arrowwidth"] = val # ax # -- @property def ax(self): """ Sets the x component of the arrow tail about the arrow head (in pixels). The 'ax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["ax"] @ax.setter def ax(self, val): self["ax"] = val # ay # -- @property def ay(self): """ Sets the y component of the arrow tail about the arrow head (in pixels). The 'ay' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["ay"] @ay.setter def ay(self, val): self["ay"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the annotation. The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the color of the border enclosing the annotation `text`. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # borderpad # --------- @property def borderpad(self): """ Sets the padding (in px) between the `text` and the enclosing border. The 'borderpad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["borderpad"] @borderpad.setter def borderpad(self, val): self["borderpad"] = val # borderwidth # ----------- @property def borderwidth(self): """ Sets the width (in px) of the border enclosing the annotation `text`. The 'borderwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["borderwidth"] @borderwidth.setter def borderwidth(self, val): self["borderwidth"] = val # captureevents # ------------- @property def captureevents(self): """ Determines whether the annotation text box captures mouse move and click events, or allows those events to pass through to data points in the plot that may be behind the annotation. By default `captureevents` is False unless `hovertext` is provided. If you use the event `plotly_clickannotation` without `hovertext` you must explicitly enable `captureevents`. The 'captureevents' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["captureevents"] @captureevents.setter def captureevents(self, val): self["captureevents"] = val # font # ---- @property def font(self): """ Sets the annotation text font. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.layout.scene.annotation.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.layout.scene.annotation.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # height # ------ @property def height(self): """ Sets an explicit height for the text box. null (default) lets the text set the box height. Taller text will be clipped. The 'height' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["height"] @height.setter def height(self, val): self["height"] = val # hoverlabel # ---------- @property def hoverlabel(self): """ The 'hoverlabel' property is an instance of Hoverlabel that may be specified as: - An instance of plotly.graph_objs.layout.scene.annotation.Hoverlabel - A dict of string/value properties that will be passed to the Hoverlabel constructor Supported dict properties: bgcolor Sets the background color of the hover label. By default uses the annotation's `bgcolor` made opaque, or white if it was transparent. bordercolor Sets the border color of the hover label. By default uses either dark grey or white, for maximum contrast with `hoverlabel.bgcolor`. font Sets the hover label text font. By default uses the global hover font and size, with color from `hoverlabel.bordercolor`. Returns ------- plotly.graph_objs.layout.scene.annotation.Hoverlabel """ return self["hoverlabel"] @hoverlabel.setter def hoverlabel(self, val): self["hoverlabel"] = val # hovertext # --------- @property def hovertext(self): """ Sets text to appear when hovering over this annotation. If omitted or blank, no hover label will appear. The 'hovertext' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["hovertext"] @hovertext.setter def hovertext(self, val): self["hovertext"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the annotation (text + arrow). The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # showarrow # --------- @property def showarrow(self): """ Determines whether or not the annotation is drawn with an arrow. If True, `text` is placed near the arrow's tail. If False, `text` lines up with the `x` and `y` provided. The 'showarrow' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showarrow"] @showarrow.setter def showarrow(self, val): self["showarrow"] = val # standoff # -------- @property def standoff(self): """ Sets a distance, in pixels, to move the end arrowhead away from the position it is pointing at, for example to point at the edge of a marker independent of zoom. Note that this shortens the arrow from the `ax` / `ay` vector, in contrast to `xshift` / `yshift` which moves everything by this amount. The 'standoff' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["standoff"] @standoff.setter def standoff(self, val): self["standoff"] = val # startarrowhead # -------------- @property def startarrowhead(self): """ Sets the start annotation arrow head style. The 'startarrowhead' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 8] Returns ------- int """ return self["startarrowhead"] @startarrowhead.setter def startarrowhead(self, val): self["startarrowhead"] = val # startarrowsize # -------------- @property def startarrowsize(self): """ Sets the size of the start annotation arrow head, relative to `arrowwidth`. A value of 1 (default) gives a head about 3x as wide as the line. The 'startarrowsize' property is a number and may be specified as: - An int or float in the interval [0.3, inf] Returns ------- int|float """ return self["startarrowsize"] @startarrowsize.setter def startarrowsize(self, val): self["startarrowsize"] = val # startstandoff # ------------- @property def startstandoff(self): """ Sets a distance, in pixels, to move the start arrowhead away from the position it is pointing at, for example to point at the edge of a marker independent of zoom. Note that this shortens the arrow from the `ax` / `ay` vector, in contrast to `xshift` / `yshift` which moves everything by this amount. The 'startstandoff' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["startstandoff"] @startstandoff.setter def startstandoff(self, val): self["startstandoff"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # text # ---- @property def text(self): """ Sets the text associated with this annotation. Plotly uses a subset of HTML tags to do things like newline (
), bold (), italics (), hyperlinks (). Tags , , are also supported. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # textangle # --------- @property def textangle(self): """ Sets the angle at which the `text` is drawn with respect to the horizontal. The 'textangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["textangle"] @textangle.setter def textangle(self, val): self["textangle"] = val # valign # ------ @property def valign(self): """ Sets the vertical alignment of the `text` within the box. Has an effect only if an explicit height is set to override the text height. The 'valign' property is an enumeration that may be specified as: - One of the following enumeration values: ['top', 'middle', 'bottom'] Returns ------- Any """ return self["valign"] @valign.setter def valign(self, val): self["valign"] = val # visible # ------- @property def visible(self): """ Determines whether or not this annotation is visible. The 'visible' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # width # ----- @property def width(self): """ Sets an explicit width for the text box. null (default) lets the text set the box width. Wider text will be clipped. There is no automatic wrapping; use
to start a new line. The 'width' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # x # - @property def x(self): """ Sets the annotation's x position. The 'x' property accepts values of any type Returns ------- Any """ return self["x"] @x.setter def x(self, val): self["x"] = val # xanchor # ------- @property def xanchor(self): """ Sets the text box's horizontal position anchor This anchor binds the `x` position to the "left", "center" or "right" of the annotation. For example, if `x` is set to 1, `xref` to "paper" and `xanchor` to "right" then the right-most portion of the annotation lines up with the right-most edge of the plotting area. If "auto", the anchor is equivalent to "center" for data-referenced annotations or if there is an arrow, whereas for paper-referenced with no arrow, the anchor picked corresponds to the closest side. The 'xanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'left', 'center', 'right'] Returns ------- Any """ return self["xanchor"] @xanchor.setter def xanchor(self, val): self["xanchor"] = val # xshift # ------ @property def xshift(self): """ Shifts the position of the whole annotation and arrow to the right (positive) or left (negative) by this many pixels. The 'xshift' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["xshift"] @xshift.setter def xshift(self, val): self["xshift"] = val # y # - @property def y(self): """ Sets the annotation's y position. The 'y' property accepts values of any type Returns ------- Any """ return self["y"] @y.setter def y(self, val): self["y"] = val # yanchor # ------- @property def yanchor(self): """ Sets the text box's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the annotation. For example, if `y` is set to 1, `yref` to "paper" and `yanchor` to "top" then the top-most portion of the annotation lines up with the top-most edge of the plotting area. If "auto", the anchor is equivalent to "middle" for data- referenced annotations or if there is an arrow, whereas for paper-referenced with no arrow, the anchor picked corresponds to the closest side. The 'yanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'top', 'middle', 'bottom'] Returns ------- Any """ return self["yanchor"] @yanchor.setter def yanchor(self, val): self["yanchor"] = val # yshift # ------ @property def yshift(self): """ Shifts the position of the whole annotation and arrow up (positive) or down (negative) by this many pixels. The 'yshift' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["yshift"] @yshift.setter def yshift(self, val): self["yshift"] = val # z # - @property def z(self): """ Sets the annotation's z position. The 'z' property accepts values of any type Returns ------- Any """ return self["z"] @z.setter def z(self, val): self["z"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.scene" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the `text` within the box. Has an effect only if `text` spans more two or more lines (i.e. `text` contains one or more
HTML tags) or if an explicit width is set to override the text width. arrowcolor Sets the color of the annotation arrow. arrowhead Sets the end annotation arrow head style. arrowside Sets the annotation arrow head position. arrowsize Sets the size of the end annotation arrow head, relative to `arrowwidth`. A value of 1 (default) gives a head about 3x as wide as the line. arrowwidth Sets the width (in px) of annotation arrow line. ax Sets the x component of the arrow tail about the arrow head (in pixels). ay Sets the y component of the arrow tail about the arrow head (in pixels). bgcolor Sets the background color of the annotation. bordercolor Sets the color of the border enclosing the annotation `text`. borderpad Sets the padding (in px) between the `text` and the enclosing border. borderwidth Sets the width (in px) of the border enclosing the annotation `text`. captureevents Determines whether the annotation text box captures mouse move and click events, or allows those events to pass through to data points in the plot that may be behind the annotation. By default `captureevents` is False unless `hovertext` is provided. If you use the event `plotly_clickannotation` without `hovertext` you must explicitly enable `captureevents`. font Sets the annotation text font. height Sets an explicit height for the text box. null (default) lets the text set the box height. Taller text will be clipped. hoverlabel plotly.graph_objects.layout.scene.annotation.Hoverlabel instance or dict with compatible properties hovertext Sets text to appear when hovering over this annotation. If omitted or blank, no hover label will appear. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. opacity Sets the opacity of the annotation (text + arrow). showarrow Determines whether or not the annotation is drawn with an arrow. If True, `text` is placed near the arrow's tail. If False, `text` lines up with the `x` and `y` provided. standoff Sets a distance, in pixels, to move the end arrowhead away from the position it is pointing at, for example to point at the edge of a marker independent of zoom. Note that this shortens the arrow from the `ax` / `ay` vector, in contrast to `xshift` / `yshift` which moves everything by this amount. startarrowhead Sets the start annotation arrow head style. startarrowsize Sets the size of the start annotation arrow head, relative to `arrowwidth`. A value of 1 (default) gives a head about 3x as wide as the line. startstandoff Sets a distance, in pixels, to move the start arrowhead away from the position it is pointing at, for example to point at the edge of a marker independent of zoom. Note that this shortens the arrow from the `ax` / `ay` vector, in contrast to `xshift` / `yshift` which moves everything by this amount. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. text Sets the text associated with this annotation. Plotly uses a subset of HTML tags to do things like newline (
), bold (), italics (), hyperlinks (). Tags , , are also supported. textangle Sets the angle at which the `text` is drawn with respect to the horizontal. valign Sets the vertical alignment of the `text` within the box. Has an effect only if an explicit height is set to override the text height. visible Determines whether or not this annotation is visible. width Sets an explicit width for the text box. null (default) lets the text set the box width. Wider text will be clipped. There is no automatic wrapping; use
to start a new line. x Sets the annotation's x position. xanchor Sets the text box's horizontal position anchor This anchor binds the `x` position to the "left", "center" or "right" of the annotation. For example, if `x` is set to 1, `xref` to "paper" and `xanchor` to "right" then the right-most portion of the annotation lines up with the right-most edge of the plotting area. If "auto", the anchor is equivalent to "center" for data- referenced annotations or if there is an arrow, whereas for paper-referenced with no arrow, the anchor picked corresponds to the closest side. xshift Shifts the position of the whole annotation and arrow to the right (positive) or left (negative) by this many pixels. y Sets the annotation's y position. yanchor Sets the text box's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the annotation. For example, if `y` is set to 1, `yref` to "paper" and `yanchor` to "top" then the top-most portion of the annotation lines up with the top-most edge of the plotting area. If "auto", the anchor is equivalent to "middle" for data-referenced annotations or if there is an arrow, whereas for paper- referenced with no arrow, the anchor picked corresponds to the closest side. yshift Shifts the position of the whole annotation and arrow up (positive) or down (negative) by this many pixels. z Sets the annotation's z position. """ def __init__( self, arg=None, align=None, arrowcolor=None, arrowhead=None, arrowside=None, arrowsize=None, arrowwidth=None, ax=None, ay=None, bgcolor=None, bordercolor=None, borderpad=None, borderwidth=None, captureevents=None, font=None, height=None, hoverlabel=None, hovertext=None, name=None, opacity=None, showarrow=None, standoff=None, startarrowhead=None, startarrowsize=None, startstandoff=None, templateitemname=None, text=None, textangle=None, valign=None, visible=None, width=None, x=None, xanchor=None, xshift=None, y=None, yanchor=None, yshift=None, z=None, **kwargs ): """ Construct a new Annotation object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.scene.Annotation align Sets the horizontal alignment of the `text` within the box. Has an effect only if `text` spans more two or more lines (i.e. `text` contains one or more
HTML tags) or if an explicit width is set to override the text width. arrowcolor Sets the color of the annotation arrow. arrowhead Sets the end annotation arrow head style. arrowside Sets the annotation arrow head position. arrowsize Sets the size of the end annotation arrow head, relative to `arrowwidth`. A value of 1 (default) gives a head about 3x as wide as the line. arrowwidth Sets the width (in px) of annotation arrow line. ax Sets the x component of the arrow tail about the arrow head (in pixels). ay Sets the y component of the arrow tail about the arrow head (in pixels). bgcolor Sets the background color of the annotation. bordercolor Sets the color of the border enclosing the annotation `text`. borderpad Sets the padding (in px) between the `text` and the enclosing border. borderwidth Sets the width (in px) of the border enclosing the annotation `text`. captureevents Determines whether the annotation text box captures mouse move and click events, or allows those events to pass through to data points in the plot that may be behind the annotation. By default `captureevents` is False unless `hovertext` is provided. If you use the event `plotly_clickannotation` without `hovertext` you must explicitly enable `captureevents`. font Sets the annotation text font. height Sets an explicit height for the text box. null (default) lets the text set the box height. Taller text will be clipped. hoverlabel plotly.graph_objects.layout.scene.annotation.Hoverlabel instance or dict with compatible properties hovertext Sets text to appear when hovering over this annotation. If omitted or blank, no hover label will appear. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. opacity Sets the opacity of the annotation (text + arrow). showarrow Determines whether or not the annotation is drawn with an arrow. If True, `text` is placed near the arrow's tail. If False, `text` lines up with the `x` and `y` provided. standoff Sets a distance, in pixels, to move the end arrowhead away from the position it is pointing at, for example to point at the edge of a marker independent of zoom. Note that this shortens the arrow from the `ax` / `ay` vector, in contrast to `xshift` / `yshift` which moves everything by this amount. startarrowhead Sets the start annotation arrow head style. startarrowsize Sets the size of the start annotation arrow head, relative to `arrowwidth`. A value of 1 (default) gives a head about 3x as wide as the line. startstandoff Sets a distance, in pixels, to move the start arrowhead away from the position it is pointing at, for example to point at the edge of a marker independent of zoom. Note that this shortens the arrow from the `ax` / `ay` vector, in contrast to `xshift` / `yshift` which moves everything by this amount. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. text Sets the text associated with this annotation. Plotly uses a subset of HTML tags to do things like newline (
), bold (), italics (), hyperlinks (). Tags , , are also supported. textangle Sets the angle at which the `text` is drawn with respect to the horizontal. valign Sets the vertical alignment of the `text` within the box. Has an effect only if an explicit height is set to override the text height. visible Determines whether or not this annotation is visible. width Sets an explicit width for the text box. null (default) lets the text set the box width. Wider text will be clipped. There is no automatic wrapping; use
to start a new line. x Sets the annotation's x position. xanchor Sets the text box's horizontal position anchor This anchor binds the `x` position to the "left", "center" or "right" of the annotation. For example, if `x` is set to 1, `xref` to "paper" and `xanchor` to "right" then the right-most portion of the annotation lines up with the right-most edge of the plotting area. If "auto", the anchor is equivalent to "center" for data- referenced annotations or if there is an arrow, whereas for paper-referenced with no arrow, the anchor picked corresponds to the closest side. xshift Shifts the position of the whole annotation and arrow to the right (positive) or left (negative) by this many pixels. y Sets the annotation's y position. yanchor Sets the text box's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the annotation. For example, if `y` is set to 1, `yref` to "paper" and `yanchor` to "top" then the top-most portion of the annotation lines up with the top-most edge of the plotting area. If "auto", the anchor is equivalent to "middle" for data-referenced annotations or if there is an arrow, whereas for paper- referenced with no arrow, the anchor picked corresponds to the closest side. yshift Shifts the position of the whole annotation and arrow up (positive) or down (negative) by this many pixels. z Sets the annotation's z position. Returns ------- Annotation """ super(Annotation, self).__init__("annotations") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.scene.Annotation constructor must be a dict or an instance of plotly.graph_objs.layout.scene.Annotation""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.scene import annotation as v_annotation # Initialize validators # --------------------- self._validators["align"] = v_annotation.AlignValidator() self._validators["arrowcolor"] = v_annotation.ArrowcolorValidator() self._validators["arrowhead"] = v_annotation.ArrowheadValidator() self._validators["arrowside"] = v_annotation.ArrowsideValidator() self._validators["arrowsize"] = v_annotation.ArrowsizeValidator() self._validators["arrowwidth"] = v_annotation.ArrowwidthValidator() self._validators["ax"] = v_annotation.AxValidator() self._validators["ay"] = v_annotation.AyValidator() self._validators["bgcolor"] = v_annotation.BgcolorValidator() self._validators["bordercolor"] = v_annotation.BordercolorValidator() self._validators["borderpad"] = v_annotation.BorderpadValidator() self._validators["borderwidth"] = v_annotation.BorderwidthValidator() self._validators["captureevents"] = v_annotation.CaptureeventsValidator() self._validators["font"] = v_annotation.FontValidator() self._validators["height"] = v_annotation.HeightValidator() self._validators["hoverlabel"] = v_annotation.HoverlabelValidator() self._validators["hovertext"] = v_annotation.HovertextValidator() self._validators["name"] = v_annotation.NameValidator() self._validators["opacity"] = v_annotation.OpacityValidator() self._validators["showarrow"] = v_annotation.ShowarrowValidator() self._validators["standoff"] = v_annotation.StandoffValidator() self._validators["startarrowhead"] = v_annotation.StartarrowheadValidator() self._validators["startarrowsize"] = v_annotation.StartarrowsizeValidator() self._validators["startstandoff"] = v_annotation.StartstandoffValidator() self._validators["templateitemname"] = v_annotation.TemplateitemnameValidator() self._validators["text"] = v_annotation.TextValidator() self._validators["textangle"] = v_annotation.TextangleValidator() self._validators["valign"] = v_annotation.ValignValidator() self._validators["visible"] = v_annotation.VisibleValidator() self._validators["width"] = v_annotation.WidthValidator() self._validators["x"] = v_annotation.XValidator() self._validators["xanchor"] = v_annotation.XanchorValidator() self._validators["xshift"] = v_annotation.XshiftValidator() self._validators["y"] = v_annotation.YValidator() self._validators["yanchor"] = v_annotation.YanchorValidator() self._validators["yshift"] = v_annotation.YshiftValidator() self._validators["z"] = v_annotation.ZValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("arrowcolor", None) self["arrowcolor"] = arrowcolor if arrowcolor is not None else _v _v = arg.pop("arrowhead", None) self["arrowhead"] = arrowhead if arrowhead is not None else _v _v = arg.pop("arrowside", None) self["arrowside"] = arrowside if arrowside is not None else _v _v = arg.pop("arrowsize", None) self["arrowsize"] = arrowsize if arrowsize is not None else _v _v = arg.pop("arrowwidth", None) self["arrowwidth"] = arrowwidth if arrowwidth is not None else _v _v = arg.pop("ax", None) self["ax"] = ax if ax is not None else _v _v = arg.pop("ay", None) self["ay"] = ay if ay is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("borderpad", None) self["borderpad"] = borderpad if borderpad is not None else _v _v = arg.pop("borderwidth", None) self["borderwidth"] = borderwidth if borderwidth is not None else _v _v = arg.pop("captureevents", None) self["captureevents"] = captureevents if captureevents is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("height", None) self["height"] = height if height is not None else _v _v = arg.pop("hoverlabel", None) self["hoverlabel"] = hoverlabel if hoverlabel is not None else _v _v = arg.pop("hovertext", None) self["hovertext"] = hovertext if hovertext is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("showarrow", None) self["showarrow"] = showarrow if showarrow is not None else _v _v = arg.pop("standoff", None) self["standoff"] = standoff if standoff is not None else _v _v = arg.pop("startarrowhead", None) self["startarrowhead"] = startarrowhead if startarrowhead is not None else _v _v = arg.pop("startarrowsize", None) self["startarrowsize"] = startarrowsize if startarrowsize is not None else _v _v = arg.pop("startstandoff", None) self["startstandoff"] = startstandoff if startstandoff is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("text", None) self["text"] = text if text is not None else _v _v = arg.pop("textangle", None) self["textangle"] = textangle if textangle is not None else _v _v = arg.pop("valign", None) self["valign"] = valign if valign is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xanchor", None) self["xanchor"] = xanchor if xanchor is not None else _v _v = arg.pop("xshift", None) self["xshift"] = xshift if xshift is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("yanchor", None) self["yanchor"] = yanchor if yanchor is not None else _v _v = arg.pop("yshift", None) self["yshift"] = yshift if yshift is not None else _v _v = arg.pop("z", None) self["z"] = z if z is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = [ "Annotation", "Annotation", "Aspectratio", "Camera", "Domain", "XAxis", "YAxis", "ZAxis", "annotation", "camera", "xaxis", "yaxis", "zaxis", ] from plotly.graph_objs.layout.scene import zaxis from plotly.graph_objs.layout.scene import yaxis from plotly.graph_objs.layout.scene import xaxis from plotly.graph_objs.layout.scene import camera from plotly.graph_objs.layout.scene import annotation plotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/scene/xaxis/0000755000175000017500000000000013573746613023477 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/scene/xaxis/title/0000755000175000017500000000000013573746613024620 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/scene/xaxis/title/__init__.py0000644000175000017500000002054313573721547026734 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Font(_BaseLayoutHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.scene.xaxis.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.scene.xaxis.title.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.scene.xaxis.title.Font constructor must be a dict or an instance of plotly.graph_objs.layout.scene.xaxis.title.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.scene.xaxis.title import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/scene/xaxis/__init__.py0000644000175000017500000005631413573721547025620 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Title(_BaseLayoutHierarchyType): # font # ---- @property def font(self): """ Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.layout.scene.xaxis.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.layout.scene.xaxis.title.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # text # ---- @property def text(self): """ Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.scene.xaxis" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. text Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """ def __init__(self, arg=None, font=None, text=None, **kwargs): """ Construct a new Title object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.scene.xaxis.Title font Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. text Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- Title """ super(Title, self).__init__("title") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.scene.xaxis.Title constructor must be a dict or an instance of plotly.graph_objs.layout.scene.xaxis.Title""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.scene.xaxis import title as v_title # Initialize validators # --------------------- self._validators["font"] = v_title.FontValidator() self._validators["text"] = v_title.TextValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Tickformatstop(_BaseLayoutHierarchyType): # dtickrange # ---------- @property def dtickrange(self): """ range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" The 'dtickrange' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'dtickrange[0]' property accepts values of any type (1) The 'dtickrange[1]' property accepts values of any type Returns ------- list """ return self["dtickrange"] @dtickrange.setter def dtickrange(self, val): self["dtickrange"] = val # enabled # ------- @property def enabled(self): """ Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. The 'enabled' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["enabled"] @enabled.setter def enabled(self, val): self["enabled"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # value # ----- @property def value(self): """ string - dtickformat for described zoom level, the same as "tickformat" The 'value' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.scene.xaxis" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """ def __init__( self, arg=None, dtickrange=None, enabled=None, name=None, templateitemname=None, value=None, **kwargs ): """ Construct a new Tickformatstop object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.scene.xaxis.Tickformatstop dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- Tickformatstop """ super(Tickformatstop, self).__init__("tickformatstops") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.scene.xaxis.Tickformatstop constructor must be a dict or an instance of plotly.graph_objs.layout.scene.xaxis.Tickformatstop""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.scene.xaxis import ( tickformatstop as v_tickformatstop, ) # Initialize validators # --------------------- self._validators["dtickrange"] = v_tickformatstop.DtickrangeValidator() self._validators["enabled"] = v_tickformatstop.EnabledValidator() self._validators["name"] = v_tickformatstop.NameValidator() self._validators[ "templateitemname" ] = v_tickformatstop.TemplateitemnameValidator() self._validators["value"] = v_tickformatstop.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtickrange", None) self["dtickrange"] = dtickrange if dtickrange is not None else _v _v = arg.pop("enabled", None) self["enabled"] = enabled if enabled is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Tickfont(_BaseLayoutHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.scene.xaxis" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Tickfont object Sets the tick font. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.scene.xaxis.Tickfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Tickfont """ super(Tickfont, self).__init__("tickfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.scene.xaxis.Tickfont constructor must be a dict or an instance of plotly.graph_objs.layout.scene.xaxis.Tickfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.scene.xaxis import tickfont as v_tickfont # Initialize validators # --------------------- self._validators["color"] = v_tickfont.ColorValidator() self._validators["family"] = v_tickfont.FamilyValidator() self._validators["size"] = v_tickfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Tickfont", "Tickformatstop", "Tickformatstop", "Title", "title"] from plotly.graph_objs.layout.scene.xaxis import title plotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/scene/zaxis/0000755000175000017500000000000013573746613023501 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/scene/zaxis/title/0000755000175000017500000000000013573746613024622 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/scene/zaxis/title/__init__.py0000644000175000017500000002054313573721547026736 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Font(_BaseLayoutHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.scene.zaxis.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.scene.zaxis.title.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.scene.zaxis.title.Font constructor must be a dict or an instance of plotly.graph_objs.layout.scene.zaxis.title.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.scene.zaxis.title import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/scene/zaxis/__init__.py0000644000175000017500000005631413573721547025622 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Title(_BaseLayoutHierarchyType): # font # ---- @property def font(self): """ Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.layout.scene.zaxis.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.layout.scene.zaxis.title.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # text # ---- @property def text(self): """ Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.scene.zaxis" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. text Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """ def __init__(self, arg=None, font=None, text=None, **kwargs): """ Construct a new Title object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.scene.zaxis.Title font Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. text Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- Title """ super(Title, self).__init__("title") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.scene.zaxis.Title constructor must be a dict or an instance of plotly.graph_objs.layout.scene.zaxis.Title""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.scene.zaxis import title as v_title # Initialize validators # --------------------- self._validators["font"] = v_title.FontValidator() self._validators["text"] = v_title.TextValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Tickformatstop(_BaseLayoutHierarchyType): # dtickrange # ---------- @property def dtickrange(self): """ range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" The 'dtickrange' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'dtickrange[0]' property accepts values of any type (1) The 'dtickrange[1]' property accepts values of any type Returns ------- list """ return self["dtickrange"] @dtickrange.setter def dtickrange(self, val): self["dtickrange"] = val # enabled # ------- @property def enabled(self): """ Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. The 'enabled' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["enabled"] @enabled.setter def enabled(self, val): self["enabled"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # value # ----- @property def value(self): """ string - dtickformat for described zoom level, the same as "tickformat" The 'value' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.scene.zaxis" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """ def __init__( self, arg=None, dtickrange=None, enabled=None, name=None, templateitemname=None, value=None, **kwargs ): """ Construct a new Tickformatstop object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.scene.zaxis.Tickformatstop dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- Tickformatstop """ super(Tickformatstop, self).__init__("tickformatstops") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.scene.zaxis.Tickformatstop constructor must be a dict or an instance of plotly.graph_objs.layout.scene.zaxis.Tickformatstop""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.scene.zaxis import ( tickformatstop as v_tickformatstop, ) # Initialize validators # --------------------- self._validators["dtickrange"] = v_tickformatstop.DtickrangeValidator() self._validators["enabled"] = v_tickformatstop.EnabledValidator() self._validators["name"] = v_tickformatstop.NameValidator() self._validators[ "templateitemname" ] = v_tickformatstop.TemplateitemnameValidator() self._validators["value"] = v_tickformatstop.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtickrange", None) self["dtickrange"] = dtickrange if dtickrange is not None else _v _v = arg.pop("enabled", None) self["enabled"] = enabled if enabled is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Tickfont(_BaseLayoutHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.scene.zaxis" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Tickfont object Sets the tick font. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.scene.zaxis.Tickfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Tickfont """ super(Tickfont, self).__init__("tickfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.scene.zaxis.Tickfont constructor must be a dict or an instance of plotly.graph_objs.layout.scene.zaxis.Tickfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.scene.zaxis import tickfont as v_tickfont # Initialize validators # --------------------- self._validators["color"] = v_tickfont.ColorValidator() self._validators["family"] = v_tickfont.FamilyValidator() self._validators["size"] = v_tickfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Tickfont", "Tickformatstop", "Tickformatstop", "Title", "title"] from plotly.graph_objs.layout.scene.zaxis import title plotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/annotation/0000755000175000017500000000000013573746613023420 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/annotation/hoverlabel/0000755000175000017500000000000013573746613025543 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/annotation/hoverlabel/__init__.py0000644000175000017500000002056713573721547027665 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Font(_BaseLayoutHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.annotation.hoverlabel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets the hover label text font. By default uses the global hover font and size, with color from `hoverlabel.bordercolor`. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.annotation.hoverlabel.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.annotation.hoverlabel.Font constructor must be a dict or an instance of plotly.graph_objs.layout.annotation.hoverlabel.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.annotation.hoverlabel import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/annotation/__init__.py0000644000175000017500000004644113573721547025541 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Hoverlabel(_BaseLayoutHierarchyType): # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the hover label. By default uses the annotation's `bgcolor` made opaque, or white if it was transparent. The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the border color of the hover label. By default uses either dark grey or white, for maximum contrast with `hoverlabel.bgcolor`. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # font # ---- @property def font(self): """ Sets the hover label text font. By default uses the global hover font and size, with color from `hoverlabel.bordercolor`. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.layout.annotation.hoverlabel.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.layout.annotation.hoverlabel.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.annotation" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ bgcolor Sets the background color of the hover label. By default uses the annotation's `bgcolor` made opaque, or white if it was transparent. bordercolor Sets the border color of the hover label. By default uses either dark grey or white, for maximum contrast with `hoverlabel.bgcolor`. font Sets the hover label text font. By default uses the global hover font and size, with color from `hoverlabel.bordercolor`. """ def __init__(self, arg=None, bgcolor=None, bordercolor=None, font=None, **kwargs): """ Construct a new Hoverlabel object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.annotation.Hoverlabel bgcolor Sets the background color of the hover label. By default uses the annotation's `bgcolor` made opaque, or white if it was transparent. bordercolor Sets the border color of the hover label. By default uses either dark grey or white, for maximum contrast with `hoverlabel.bgcolor`. font Sets the hover label text font. By default uses the global hover font and size, with color from `hoverlabel.bordercolor`. Returns ------- Hoverlabel """ super(Hoverlabel, self).__init__("hoverlabel") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.annotation.Hoverlabel constructor must be a dict or an instance of plotly.graph_objs.layout.annotation.Hoverlabel""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.annotation import hoverlabel as v_hoverlabel # Initialize validators # --------------------- self._validators["bgcolor"] = v_hoverlabel.BgcolorValidator() self._validators["bordercolor"] = v_hoverlabel.BordercolorValidator() self._validators["font"] = v_hoverlabel.FontValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Font(_BaseLayoutHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.annotation" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets the annotation text font. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.annotation.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.annotation.Font constructor must be a dict or an instance of plotly.graph_objs.layout.annotation.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.annotation import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font", "Hoverlabel", "hoverlabel"] from plotly.graph_objs.layout.annotation import hoverlabel plotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/title/0000755000175000017500000000000013573746613022367 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/title/__init__.py0000644000175000017500000003250013573721550024471 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Pad(_BaseLayoutHierarchyType): # b # - @property def b(self): """ The amount of padding (in px) along the bottom of the component. The 'b' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["b"] @b.setter def b(self, val): self["b"] = val # l # - @property def l(self): """ The amount of padding (in px) on the left side of the component. The 'l' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["l"] @l.setter def l(self, val): self["l"] = val # r # - @property def r(self): """ The amount of padding (in px) on the right side of the component. The 'r' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["r"] @r.setter def r(self, val): self["r"] = val # t # - @property def t(self): """ The amount of padding (in px) along the top of the component. The 't' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["t"] @t.setter def t(self, val): self["t"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ b The amount of padding (in px) along the bottom of the component. l The amount of padding (in px) on the left side of the component. r The amount of padding (in px) on the right side of the component. t The amount of padding (in px) along the top of the component. """ def __init__(self, arg=None, b=None, l=None, r=None, t=None, **kwargs): """ Construct a new Pad object Sets the padding of the title. Each padding value only applies when the corresponding `xanchor`/`yanchor` value is set accordingly. E.g. for left padding to take effect, `xanchor` must be set to "left". The same rule applies if `xanchor`/`yanchor` is determined automatically. Padding is muted if the respective anchor value is "middle*/*center". Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.title.Pad b The amount of padding (in px) along the bottom of the component. l The amount of padding (in px) on the left side of the component. r The amount of padding (in px) on the right side of the component. t The amount of padding (in px) along the top of the component. Returns ------- Pad """ super(Pad, self).__init__("pad") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.title.Pad constructor must be a dict or an instance of plotly.graph_objs.layout.title.Pad""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.title import pad as v_pad # Initialize validators # --------------------- self._validators["b"] = v_pad.BValidator() self._validators["l"] = v_pad.LValidator() self._validators["r"] = v_pad.RValidator() self._validators["t"] = v_pad.TValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("b", None) self["b"] = b if b is not None else _v _v = arg.pop("l", None) self["l"] = l if l is not None else _v _v = arg.pop("r", None) self["r"] = r if r is not None else _v _v = arg.pop("t", None) self["t"] = t if t is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Font(_BaseLayoutHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets the title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.title.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.title.Font constructor must be a dict or an instance of plotly.graph_objs.layout.title.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.title import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font", "Pad"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/ternary/0000755000175000017500000000000013573746613022732 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/ternary/__init__.py0000644000175000017500000061741113573721552025050 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Domain(_BaseLayoutHierarchyType): # column # ------ @property def column(self): """ If there is a layout grid, use the domain for this column in the grid for this ternary subplot . The 'column' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["column"] @column.setter def column(self, val): self["column"] = val # row # --- @property def row(self): """ If there is a layout grid, use the domain for this row in the grid for this ternary subplot . The 'row' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["row"] @row.setter def row(self, val): self["row"] = val # x # - @property def x(self): """ Sets the horizontal domain of this ternary subplot (in plot fraction). The 'x' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'x[0]' property is a number and may be specified as: - An int or float in the interval [0, 1] (1) The 'x[1]' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- list """ return self["x"] @x.setter def x(self, val): self["x"] = val # y # - @property def y(self): """ Sets the vertical domain of this ternary subplot (in plot fraction). The 'y' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'y[0]' property is a number and may be specified as: - An int or float in the interval [0, 1] (1) The 'y[1]' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- list """ return self["y"] @y.setter def y(self, val): self["y"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.ternary" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ column If there is a layout grid, use the domain for this column in the grid for this ternary subplot . row If there is a layout grid, use the domain for this row in the grid for this ternary subplot . x Sets the horizontal domain of this ternary subplot (in plot fraction). y Sets the vertical domain of this ternary subplot (in plot fraction). """ def __init__(self, arg=None, column=None, row=None, x=None, y=None, **kwargs): """ Construct a new Domain object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.ternary.Domain column If there is a layout grid, use the domain for this column in the grid for this ternary subplot . row If there is a layout grid, use the domain for this row in the grid for this ternary subplot . x Sets the horizontal domain of this ternary subplot (in plot fraction). y Sets the vertical domain of this ternary subplot (in plot fraction). Returns ------- Domain """ super(Domain, self).__init__("domain") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.ternary.Domain constructor must be a dict or an instance of plotly.graph_objs.layout.ternary.Domain""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.ternary import domain as v_domain # Initialize validators # --------------------- self._validators["column"] = v_domain.ColumnValidator() self._validators["row"] = v_domain.RowValidator() self._validators["x"] = v_domain.XValidator() self._validators["y"] = v_domain.YValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("column", None) self["column"] = column if column is not None else _v _v = arg.pop("row", None) self["row"] = row if row is not None else _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Caxis(_BaseLayoutHierarchyType): # color # ----- @property def color(self): """ Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # dtick # ----- @property def dtick(self): """ Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" The 'dtick' property accepts values of any type Returns ------- Any """ return self["dtick"] @dtick.setter def dtick(self, val): self["dtick"] = val # exponentformat # -------------- @property def exponentformat(self): """ Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. The 'exponentformat' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'e', 'E', 'power', 'SI', 'B'] Returns ------- Any """ return self["exponentformat"] @exponentformat.setter def exponentformat(self, val): self["exponentformat"] = val # gridcolor # --------- @property def gridcolor(self): """ Sets the color of the grid lines. The 'gridcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["gridcolor"] @gridcolor.setter def gridcolor(self, val): self["gridcolor"] = val # gridwidth # --------- @property def gridwidth(self): """ Sets the width (in px) of the grid lines. The 'gridwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["gridwidth"] @gridwidth.setter def gridwidth(self, val): self["gridwidth"] = val # hoverformat # ----------- @property def hoverformat(self): """ Sets the hover text formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'hoverformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["hoverformat"] @hoverformat.setter def hoverformat(self, val): self["hoverformat"] = val # layer # ----- @property def layer(self): """ Sets the layer on which this axis is displayed. If *above traces*, this axis is displayed above all the subplot's traces If *below traces*, this axis is displayed below all the subplot's traces, but above the grid lines. Useful when used together with scatter-like traces with `cliponaxis` set to False to show markers and/or text nodes above this axis. The 'layer' property is an enumeration that may be specified as: - One of the following enumeration values: ['above traces', 'below traces'] Returns ------- Any """ return self["layer"] @layer.setter def layer(self, val): self["layer"] = val # linecolor # --------- @property def linecolor(self): """ Sets the axis line color. The 'linecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["linecolor"] @linecolor.setter def linecolor(self, val): self["linecolor"] = val # linewidth # --------- @property def linewidth(self): """ Sets the width (in px) of the axis line. The 'linewidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["linewidth"] @linewidth.setter def linewidth(self, val): self["linewidth"] = val # min # --- @property def min(self): """ The minimum value visible on this axis. The maximum is determined by the sum minus the minimum values of the other two axes. The full view corresponds to all the minima set to zero. The 'min' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["min"] @min.setter def min(self, val): self["min"] = val # nticks # ------ @property def nticks(self): """ Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". The 'nticks' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [1, 9223372036854775807] Returns ------- int """ return self["nticks"] @nticks.setter def nticks(self, val): self["nticks"] = val # separatethousands # ----------------- @property def separatethousands(self): """ If "true", even 4-digit integers are separated The 'separatethousands' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["separatethousands"] @separatethousands.setter def separatethousands(self, val): self["separatethousands"] = val # showexponent # ------------ @property def showexponent(self): """ If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. The 'showexponent' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showexponent"] @showexponent.setter def showexponent(self, val): self["showexponent"] = val # showgrid # -------- @property def showgrid(self): """ Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. The 'showgrid' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showgrid"] @showgrid.setter def showgrid(self, val): self["showgrid"] = val # showline # -------- @property def showline(self): """ Determines whether or not a line bounding this axis is drawn. The 'showline' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showline"] @showline.setter def showline(self, val): self["showline"] = val # showticklabels # -------------- @property def showticklabels(self): """ Determines whether or not the tick labels are drawn. The 'showticklabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showticklabels"] @showticklabels.setter def showticklabels(self, val): self["showticklabels"] = val # showtickprefix # -------------- @property def showtickprefix(self): """ If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. The 'showtickprefix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showtickprefix"] @showtickprefix.setter def showtickprefix(self, val): self["showtickprefix"] = val # showticksuffix # -------------- @property def showticksuffix(self): """ Same as `showtickprefix` but for tick suffixes. The 'showticksuffix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showticksuffix"] @showticksuffix.setter def showticksuffix(self, val): self["showticksuffix"] = val # tick0 # ----- @property def tick0(self): """ Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. The 'tick0' property accepts values of any type Returns ------- Any """ return self["tick0"] @tick0.setter def tick0(self, val): self["tick0"] = val # tickangle # --------- @property def tickangle(self): """ Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. The 'tickangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["tickangle"] @tickangle.setter def tickangle(self, val): self["tickangle"] = val # tickcolor # --------- @property def tickcolor(self): """ Sets the tick color. The 'tickcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["tickcolor"] @tickcolor.setter def tickcolor(self, val): self["tickcolor"] = val # tickfont # -------- @property def tickfont(self): """ Sets the tick font. The 'tickfont' property is an instance of Tickfont that may be specified as: - An instance of plotly.graph_objs.layout.ternary.caxis.Tickfont - A dict of string/value properties that will be passed to the Tickfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.layout.ternary.caxis.Tickfont """ return self["tickfont"] @tickfont.setter def tickfont(self, val): self["tickfont"] = val # tickformat # ---------- @property def tickformat(self): """ Sets the tick label formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'tickformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickformat"] @tickformat.setter def tickformat(self, val): self["tickformat"] = val # tickformatstops # --------------- @property def tickformatstops(self): """ The 'tickformatstops' property is a tuple of instances of Tickformatstop that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.ternary.caxis.Tickformatstop - A list or tuple of dicts of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- tuple[plotly.graph_objs.layout.ternary.caxis.Tickformatstop] """ return self["tickformatstops"] @tickformatstops.setter def tickformatstops(self, val): self["tickformatstops"] = val # tickformatstopdefaults # ---------------------- @property def tickformatstopdefaults(self): """ When used in a template (as layout.template.layout.ternary.caxis.tickformatstopdefaults), sets the default property values to use for elements of layout.ternary.caxis.tickformatstops The 'tickformatstopdefaults' property is an instance of Tickformatstop that may be specified as: - An instance of plotly.graph_objs.layout.ternary.caxis.Tickformatstop - A dict of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: Returns ------- plotly.graph_objs.layout.ternary.caxis.Tickformatstop """ return self["tickformatstopdefaults"] @tickformatstopdefaults.setter def tickformatstopdefaults(self, val): self["tickformatstopdefaults"] = val # ticklen # ------- @property def ticklen(self): """ Sets the tick length (in px). The 'ticklen' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ticklen"] @ticklen.setter def ticklen(self, val): self["ticklen"] = val # tickmode # -------- @property def tickmode(self): """ Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). The 'tickmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'linear', 'array'] Returns ------- Any """ return self["tickmode"] @tickmode.setter def tickmode(self, val): self["tickmode"] = val # tickprefix # ---------- @property def tickprefix(self): """ Sets a tick label prefix. The 'tickprefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickprefix"] @tickprefix.setter def tickprefix(self, val): self["tickprefix"] = val # ticks # ----- @property def ticks(self): """ Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. The 'ticks' property is an enumeration that may be specified as: - One of the following enumeration values: ['outside', 'inside', ''] Returns ------- Any """ return self["ticks"] @ticks.setter def ticks(self, val): self["ticks"] = val # ticksuffix # ---------- @property def ticksuffix(self): """ Sets a tick label suffix. The 'ticksuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ticksuffix"] @ticksuffix.setter def ticksuffix(self, val): self["ticksuffix"] = val # ticktext # -------- @property def ticktext(self): """ Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. The 'ticktext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ticktext"] @ticktext.setter def ticktext(self, val): self["ticktext"] = val # ticktextsrc # ----------- @property def ticktextsrc(self): """ Sets the source reference on plot.ly for ticktext . The 'ticktextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ticktextsrc"] @ticktextsrc.setter def ticktextsrc(self, val): self["ticktextsrc"] = val # tickvals # -------- @property def tickvals(self): """ Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. The 'tickvals' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["tickvals"] @tickvals.setter def tickvals(self, val): self["tickvals"] = val # tickvalssrc # ----------- @property def tickvalssrc(self): """ Sets the source reference on plot.ly for tickvals . The 'tickvalssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tickvalssrc"] @tickvalssrc.setter def tickvalssrc(self, val): self["tickvalssrc"] = val # tickwidth # --------- @property def tickwidth(self): """ Sets the tick width (in px). The 'tickwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["tickwidth"] @tickwidth.setter def tickwidth(self, val): self["tickwidth"] = val # title # ----- @property def title(self): """ The 'title' property is an instance of Title that may be specified as: - An instance of plotly.graph_objs.layout.ternary.caxis.Title - A dict of string/value properties that will be passed to the Title constructor Supported dict properties: font Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. text Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- plotly.graph_objs.layout.ternary.caxis.Title """ return self["title"] @title.setter def title(self, val): self["title"] = val # titlefont # --------- @property def titlefont(self): """ Deprecated: Please use layout.ternary.caxis.title.font instead. Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.layout.ternary.caxis.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- """ return self["titlefont"] @titlefont.setter def titlefont(self, val): self["titlefont"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of user-driven changes in axis `min`, and `title` if in `editable: true` configuration. Defaults to `ternary.uirevision`. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.ternary" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. gridcolor Sets the color of the grid lines. gridwidth Sets the width (in px) of the grid lines. hoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" layer Sets the layer on which this axis is displayed. If *above traces*, this axis is displayed above all the subplot's traces If *below traces*, this axis is displayed below all the subplot's traces, but above the grid lines. Useful when used together with scatter-like traces with `cliponaxis` set to False to show markers and/or text nodes above this axis. linecolor Sets the axis line color. linewidth Sets the width (in px) of the axis line. min The minimum value visible on this axis. The maximum is determined by the sum minus the minimum values of the other two axes. The full view corresponds to all the minima set to zero. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showgrid Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. showline Determines whether or not a line bounding this axis is drawn. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the tick font. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.layout.ternary.caxis.Ti ckformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.layout.tern ary.caxis.tickformatstopdefaults), sets the default property values to use for elements of layout.ternary.caxis.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.layout.ternary.caxis.Title instance or dict with compatible properties titlefont Deprecated: Please use layout.ternary.caxis.title.font instead. Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. uirevision Controls persistence of user-driven changes in axis `min`, and `title` if in `editable: true` configuration. Defaults to `ternary.uirevision`. """ _mapped_properties = {"titlefont": ("title", "font")} def __init__( self, arg=None, color=None, dtick=None, exponentformat=None, gridcolor=None, gridwidth=None, hoverformat=None, layer=None, linecolor=None, linewidth=None, min=None, nticks=None, separatethousands=None, showexponent=None, showgrid=None, showline=None, showticklabels=None, showtickprefix=None, showticksuffix=None, tick0=None, tickangle=None, tickcolor=None, tickfont=None, tickformat=None, tickformatstops=None, tickformatstopdefaults=None, ticklen=None, tickmode=None, tickprefix=None, ticks=None, ticksuffix=None, ticktext=None, ticktextsrc=None, tickvals=None, tickvalssrc=None, tickwidth=None, title=None, titlefont=None, uirevision=None, **kwargs ): """ Construct a new Caxis object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.ternary.Caxis color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. gridcolor Sets the color of the grid lines. gridwidth Sets the width (in px) of the grid lines. hoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" layer Sets the layer on which this axis is displayed. If *above traces*, this axis is displayed above all the subplot's traces If *below traces*, this axis is displayed below all the subplot's traces, but above the grid lines. Useful when used together with scatter-like traces with `cliponaxis` set to False to show markers and/or text nodes above this axis. linecolor Sets the axis line color. linewidth Sets the width (in px) of the axis line. min The minimum value visible on this axis. The maximum is determined by the sum minus the minimum values of the other two axes. The full view corresponds to all the minima set to zero. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showgrid Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. showline Determines whether or not a line bounding this axis is drawn. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the tick font. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.layout.ternary.caxis.Ti ckformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.layout.tern ary.caxis.tickformatstopdefaults), sets the default property values to use for elements of layout.ternary.caxis.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.layout.ternary.caxis.Title instance or dict with compatible properties titlefont Deprecated: Please use layout.ternary.caxis.title.font instead. Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. uirevision Controls persistence of user-driven changes in axis `min`, and `title` if in `editable: true` configuration. Defaults to `ternary.uirevision`. Returns ------- Caxis """ super(Caxis, self).__init__("caxis") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.ternary.Caxis constructor must be a dict or an instance of plotly.graph_objs.layout.ternary.Caxis""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.ternary import caxis as v_caxis # Initialize validators # --------------------- self._validators["color"] = v_caxis.ColorValidator() self._validators["dtick"] = v_caxis.DtickValidator() self._validators["exponentformat"] = v_caxis.ExponentformatValidator() self._validators["gridcolor"] = v_caxis.GridcolorValidator() self._validators["gridwidth"] = v_caxis.GridwidthValidator() self._validators["hoverformat"] = v_caxis.HoverformatValidator() self._validators["layer"] = v_caxis.LayerValidator() self._validators["linecolor"] = v_caxis.LinecolorValidator() self._validators["linewidth"] = v_caxis.LinewidthValidator() self._validators["min"] = v_caxis.MinValidator() self._validators["nticks"] = v_caxis.NticksValidator() self._validators["separatethousands"] = v_caxis.SeparatethousandsValidator() self._validators["showexponent"] = v_caxis.ShowexponentValidator() self._validators["showgrid"] = v_caxis.ShowgridValidator() self._validators["showline"] = v_caxis.ShowlineValidator() self._validators["showticklabels"] = v_caxis.ShowticklabelsValidator() self._validators["showtickprefix"] = v_caxis.ShowtickprefixValidator() self._validators["showticksuffix"] = v_caxis.ShowticksuffixValidator() self._validators["tick0"] = v_caxis.Tick0Validator() self._validators["tickangle"] = v_caxis.TickangleValidator() self._validators["tickcolor"] = v_caxis.TickcolorValidator() self._validators["tickfont"] = v_caxis.TickfontValidator() self._validators["tickformat"] = v_caxis.TickformatValidator() self._validators["tickformatstops"] = v_caxis.TickformatstopsValidator() self._validators["tickformatstopdefaults"] = v_caxis.TickformatstopValidator() self._validators["ticklen"] = v_caxis.TicklenValidator() self._validators["tickmode"] = v_caxis.TickmodeValidator() self._validators["tickprefix"] = v_caxis.TickprefixValidator() self._validators["ticks"] = v_caxis.TicksValidator() self._validators["ticksuffix"] = v_caxis.TicksuffixValidator() self._validators["ticktext"] = v_caxis.TicktextValidator() self._validators["ticktextsrc"] = v_caxis.TicktextsrcValidator() self._validators["tickvals"] = v_caxis.TickvalsValidator() self._validators["tickvalssrc"] = v_caxis.TickvalssrcValidator() self._validators["tickwidth"] = v_caxis.TickwidthValidator() self._validators["title"] = v_caxis.TitleValidator() self._validators["uirevision"] = v_caxis.UirevisionValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("dtick", None) self["dtick"] = dtick if dtick is not None else _v _v = arg.pop("exponentformat", None) self["exponentformat"] = exponentformat if exponentformat is not None else _v _v = arg.pop("gridcolor", None) self["gridcolor"] = gridcolor if gridcolor is not None else _v _v = arg.pop("gridwidth", None) self["gridwidth"] = gridwidth if gridwidth is not None else _v _v = arg.pop("hoverformat", None) self["hoverformat"] = hoverformat if hoverformat is not None else _v _v = arg.pop("layer", None) self["layer"] = layer if layer is not None else _v _v = arg.pop("linecolor", None) self["linecolor"] = linecolor if linecolor is not None else _v _v = arg.pop("linewidth", None) self["linewidth"] = linewidth if linewidth is not None else _v _v = arg.pop("min", None) self["min"] = min if min is not None else _v _v = arg.pop("nticks", None) self["nticks"] = nticks if nticks is not None else _v _v = arg.pop("separatethousands", None) self["separatethousands"] = ( separatethousands if separatethousands is not None else _v ) _v = arg.pop("showexponent", None) self["showexponent"] = showexponent if showexponent is not None else _v _v = arg.pop("showgrid", None) self["showgrid"] = showgrid if showgrid is not None else _v _v = arg.pop("showline", None) self["showline"] = showline if showline is not None else _v _v = arg.pop("showticklabels", None) self["showticklabels"] = showticklabels if showticklabels is not None else _v _v = arg.pop("showtickprefix", None) self["showtickprefix"] = showtickprefix if showtickprefix is not None else _v _v = arg.pop("showticksuffix", None) self["showticksuffix"] = showticksuffix if showticksuffix is not None else _v _v = arg.pop("tick0", None) self["tick0"] = tick0 if tick0 is not None else _v _v = arg.pop("tickangle", None) self["tickangle"] = tickangle if tickangle is not None else _v _v = arg.pop("tickcolor", None) self["tickcolor"] = tickcolor if tickcolor is not None else _v _v = arg.pop("tickfont", None) self["tickfont"] = tickfont if tickfont is not None else _v _v = arg.pop("tickformat", None) self["tickformat"] = tickformat if tickformat is not None else _v _v = arg.pop("tickformatstops", None) self["tickformatstops"] = tickformatstops if tickformatstops is not None else _v _v = arg.pop("tickformatstopdefaults", None) self["tickformatstopdefaults"] = ( tickformatstopdefaults if tickformatstopdefaults is not None else _v ) _v = arg.pop("ticklen", None) self["ticklen"] = ticklen if ticklen is not None else _v _v = arg.pop("tickmode", None) self["tickmode"] = tickmode if tickmode is not None else _v _v = arg.pop("tickprefix", None) self["tickprefix"] = tickprefix if tickprefix is not None else _v _v = arg.pop("ticks", None) self["ticks"] = ticks if ticks is not None else _v _v = arg.pop("ticksuffix", None) self["ticksuffix"] = ticksuffix if ticksuffix is not None else _v _v = arg.pop("ticktext", None) self["ticktext"] = ticktext if ticktext is not None else _v _v = arg.pop("ticktextsrc", None) self["ticktextsrc"] = ticktextsrc if ticktextsrc is not None else _v _v = arg.pop("tickvals", None) self["tickvals"] = tickvals if tickvals is not None else _v _v = arg.pop("tickvalssrc", None) self["tickvalssrc"] = tickvalssrc if tickvalssrc is not None else _v _v = arg.pop("tickwidth", None) self["tickwidth"] = tickwidth if tickwidth is not None else _v _v = arg.pop("title", None) self["title"] = title if title is not None else _v _v = arg.pop("titlefont", None) _v = titlefont if titlefont is not None else _v if _v is not None: self["titlefont"] = _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Baxis(_BaseLayoutHierarchyType): # color # ----- @property def color(self): """ Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # dtick # ----- @property def dtick(self): """ Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" The 'dtick' property accepts values of any type Returns ------- Any """ return self["dtick"] @dtick.setter def dtick(self, val): self["dtick"] = val # exponentformat # -------------- @property def exponentformat(self): """ Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. The 'exponentformat' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'e', 'E', 'power', 'SI', 'B'] Returns ------- Any """ return self["exponentformat"] @exponentformat.setter def exponentformat(self, val): self["exponentformat"] = val # gridcolor # --------- @property def gridcolor(self): """ Sets the color of the grid lines. The 'gridcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["gridcolor"] @gridcolor.setter def gridcolor(self, val): self["gridcolor"] = val # gridwidth # --------- @property def gridwidth(self): """ Sets the width (in px) of the grid lines. The 'gridwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["gridwidth"] @gridwidth.setter def gridwidth(self, val): self["gridwidth"] = val # hoverformat # ----------- @property def hoverformat(self): """ Sets the hover text formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'hoverformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["hoverformat"] @hoverformat.setter def hoverformat(self, val): self["hoverformat"] = val # layer # ----- @property def layer(self): """ Sets the layer on which this axis is displayed. If *above traces*, this axis is displayed above all the subplot's traces If *below traces*, this axis is displayed below all the subplot's traces, but above the grid lines. Useful when used together with scatter-like traces with `cliponaxis` set to False to show markers and/or text nodes above this axis. The 'layer' property is an enumeration that may be specified as: - One of the following enumeration values: ['above traces', 'below traces'] Returns ------- Any """ return self["layer"] @layer.setter def layer(self, val): self["layer"] = val # linecolor # --------- @property def linecolor(self): """ Sets the axis line color. The 'linecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["linecolor"] @linecolor.setter def linecolor(self, val): self["linecolor"] = val # linewidth # --------- @property def linewidth(self): """ Sets the width (in px) of the axis line. The 'linewidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["linewidth"] @linewidth.setter def linewidth(self, val): self["linewidth"] = val # min # --- @property def min(self): """ The minimum value visible on this axis. The maximum is determined by the sum minus the minimum values of the other two axes. The full view corresponds to all the minima set to zero. The 'min' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["min"] @min.setter def min(self, val): self["min"] = val # nticks # ------ @property def nticks(self): """ Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". The 'nticks' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [1, 9223372036854775807] Returns ------- int """ return self["nticks"] @nticks.setter def nticks(self, val): self["nticks"] = val # separatethousands # ----------------- @property def separatethousands(self): """ If "true", even 4-digit integers are separated The 'separatethousands' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["separatethousands"] @separatethousands.setter def separatethousands(self, val): self["separatethousands"] = val # showexponent # ------------ @property def showexponent(self): """ If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. The 'showexponent' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showexponent"] @showexponent.setter def showexponent(self, val): self["showexponent"] = val # showgrid # -------- @property def showgrid(self): """ Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. The 'showgrid' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showgrid"] @showgrid.setter def showgrid(self, val): self["showgrid"] = val # showline # -------- @property def showline(self): """ Determines whether or not a line bounding this axis is drawn. The 'showline' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showline"] @showline.setter def showline(self, val): self["showline"] = val # showticklabels # -------------- @property def showticklabels(self): """ Determines whether or not the tick labels are drawn. The 'showticklabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showticklabels"] @showticklabels.setter def showticklabels(self, val): self["showticklabels"] = val # showtickprefix # -------------- @property def showtickprefix(self): """ If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. The 'showtickprefix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showtickprefix"] @showtickprefix.setter def showtickprefix(self, val): self["showtickprefix"] = val # showticksuffix # -------------- @property def showticksuffix(self): """ Same as `showtickprefix` but for tick suffixes. The 'showticksuffix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showticksuffix"] @showticksuffix.setter def showticksuffix(self, val): self["showticksuffix"] = val # tick0 # ----- @property def tick0(self): """ Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. The 'tick0' property accepts values of any type Returns ------- Any """ return self["tick0"] @tick0.setter def tick0(self, val): self["tick0"] = val # tickangle # --------- @property def tickangle(self): """ Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. The 'tickangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["tickangle"] @tickangle.setter def tickangle(self, val): self["tickangle"] = val # tickcolor # --------- @property def tickcolor(self): """ Sets the tick color. The 'tickcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["tickcolor"] @tickcolor.setter def tickcolor(self, val): self["tickcolor"] = val # tickfont # -------- @property def tickfont(self): """ Sets the tick font. The 'tickfont' property is an instance of Tickfont that may be specified as: - An instance of plotly.graph_objs.layout.ternary.baxis.Tickfont - A dict of string/value properties that will be passed to the Tickfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.layout.ternary.baxis.Tickfont """ return self["tickfont"] @tickfont.setter def tickfont(self, val): self["tickfont"] = val # tickformat # ---------- @property def tickformat(self): """ Sets the tick label formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'tickformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickformat"] @tickformat.setter def tickformat(self, val): self["tickformat"] = val # tickformatstops # --------------- @property def tickformatstops(self): """ The 'tickformatstops' property is a tuple of instances of Tickformatstop that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.ternary.baxis.Tickformatstop - A list or tuple of dicts of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- tuple[plotly.graph_objs.layout.ternary.baxis.Tickformatstop] """ return self["tickformatstops"] @tickformatstops.setter def tickformatstops(self, val): self["tickformatstops"] = val # tickformatstopdefaults # ---------------------- @property def tickformatstopdefaults(self): """ When used in a template (as layout.template.layout.ternary.baxis.tickformatstopdefaults), sets the default property values to use for elements of layout.ternary.baxis.tickformatstops The 'tickformatstopdefaults' property is an instance of Tickformatstop that may be specified as: - An instance of plotly.graph_objs.layout.ternary.baxis.Tickformatstop - A dict of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: Returns ------- plotly.graph_objs.layout.ternary.baxis.Tickformatstop """ return self["tickformatstopdefaults"] @tickformatstopdefaults.setter def tickformatstopdefaults(self, val): self["tickformatstopdefaults"] = val # ticklen # ------- @property def ticklen(self): """ Sets the tick length (in px). The 'ticklen' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ticklen"] @ticklen.setter def ticklen(self, val): self["ticklen"] = val # tickmode # -------- @property def tickmode(self): """ Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). The 'tickmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'linear', 'array'] Returns ------- Any """ return self["tickmode"] @tickmode.setter def tickmode(self, val): self["tickmode"] = val # tickprefix # ---------- @property def tickprefix(self): """ Sets a tick label prefix. The 'tickprefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickprefix"] @tickprefix.setter def tickprefix(self, val): self["tickprefix"] = val # ticks # ----- @property def ticks(self): """ Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. The 'ticks' property is an enumeration that may be specified as: - One of the following enumeration values: ['outside', 'inside', ''] Returns ------- Any """ return self["ticks"] @ticks.setter def ticks(self, val): self["ticks"] = val # ticksuffix # ---------- @property def ticksuffix(self): """ Sets a tick label suffix. The 'ticksuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ticksuffix"] @ticksuffix.setter def ticksuffix(self, val): self["ticksuffix"] = val # ticktext # -------- @property def ticktext(self): """ Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. The 'ticktext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ticktext"] @ticktext.setter def ticktext(self, val): self["ticktext"] = val # ticktextsrc # ----------- @property def ticktextsrc(self): """ Sets the source reference on plot.ly for ticktext . The 'ticktextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ticktextsrc"] @ticktextsrc.setter def ticktextsrc(self, val): self["ticktextsrc"] = val # tickvals # -------- @property def tickvals(self): """ Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. The 'tickvals' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["tickvals"] @tickvals.setter def tickvals(self, val): self["tickvals"] = val # tickvalssrc # ----------- @property def tickvalssrc(self): """ Sets the source reference on plot.ly for tickvals . The 'tickvalssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tickvalssrc"] @tickvalssrc.setter def tickvalssrc(self, val): self["tickvalssrc"] = val # tickwidth # --------- @property def tickwidth(self): """ Sets the tick width (in px). The 'tickwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["tickwidth"] @tickwidth.setter def tickwidth(self, val): self["tickwidth"] = val # title # ----- @property def title(self): """ The 'title' property is an instance of Title that may be specified as: - An instance of plotly.graph_objs.layout.ternary.baxis.Title - A dict of string/value properties that will be passed to the Title constructor Supported dict properties: font Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. text Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- plotly.graph_objs.layout.ternary.baxis.Title """ return self["title"] @title.setter def title(self, val): self["title"] = val # titlefont # --------- @property def titlefont(self): """ Deprecated: Please use layout.ternary.baxis.title.font instead. Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.layout.ternary.baxis.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- """ return self["titlefont"] @titlefont.setter def titlefont(self, val): self["titlefont"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of user-driven changes in axis `min`, and `title` if in `editable: true` configuration. Defaults to `ternary.uirevision`. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.ternary" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. gridcolor Sets the color of the grid lines. gridwidth Sets the width (in px) of the grid lines. hoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" layer Sets the layer on which this axis is displayed. If *above traces*, this axis is displayed above all the subplot's traces If *below traces*, this axis is displayed below all the subplot's traces, but above the grid lines. Useful when used together with scatter-like traces with `cliponaxis` set to False to show markers and/or text nodes above this axis. linecolor Sets the axis line color. linewidth Sets the width (in px) of the axis line. min The minimum value visible on this axis. The maximum is determined by the sum minus the minimum values of the other two axes. The full view corresponds to all the minima set to zero. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showgrid Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. showline Determines whether or not a line bounding this axis is drawn. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the tick font. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.layout.ternary.baxis.Ti ckformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.layout.tern ary.baxis.tickformatstopdefaults), sets the default property values to use for elements of layout.ternary.baxis.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.layout.ternary.baxis.Title instance or dict with compatible properties titlefont Deprecated: Please use layout.ternary.baxis.title.font instead. Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. uirevision Controls persistence of user-driven changes in axis `min`, and `title` if in `editable: true` configuration. Defaults to `ternary.uirevision`. """ _mapped_properties = {"titlefont": ("title", "font")} def __init__( self, arg=None, color=None, dtick=None, exponentformat=None, gridcolor=None, gridwidth=None, hoverformat=None, layer=None, linecolor=None, linewidth=None, min=None, nticks=None, separatethousands=None, showexponent=None, showgrid=None, showline=None, showticklabels=None, showtickprefix=None, showticksuffix=None, tick0=None, tickangle=None, tickcolor=None, tickfont=None, tickformat=None, tickformatstops=None, tickformatstopdefaults=None, ticklen=None, tickmode=None, tickprefix=None, ticks=None, ticksuffix=None, ticktext=None, ticktextsrc=None, tickvals=None, tickvalssrc=None, tickwidth=None, title=None, titlefont=None, uirevision=None, **kwargs ): """ Construct a new Baxis object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.ternary.Baxis color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. gridcolor Sets the color of the grid lines. gridwidth Sets the width (in px) of the grid lines. hoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" layer Sets the layer on which this axis is displayed. If *above traces*, this axis is displayed above all the subplot's traces If *below traces*, this axis is displayed below all the subplot's traces, but above the grid lines. Useful when used together with scatter-like traces with `cliponaxis` set to False to show markers and/or text nodes above this axis. linecolor Sets the axis line color. linewidth Sets the width (in px) of the axis line. min The minimum value visible on this axis. The maximum is determined by the sum minus the minimum values of the other two axes. The full view corresponds to all the minima set to zero. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showgrid Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. showline Determines whether or not a line bounding this axis is drawn. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the tick font. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.layout.ternary.baxis.Ti ckformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.layout.tern ary.baxis.tickformatstopdefaults), sets the default property values to use for elements of layout.ternary.baxis.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.layout.ternary.baxis.Title instance or dict with compatible properties titlefont Deprecated: Please use layout.ternary.baxis.title.font instead. Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. uirevision Controls persistence of user-driven changes in axis `min`, and `title` if in `editable: true` configuration. Defaults to `ternary.uirevision`. Returns ------- Baxis """ super(Baxis, self).__init__("baxis") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.ternary.Baxis constructor must be a dict or an instance of plotly.graph_objs.layout.ternary.Baxis""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.ternary import baxis as v_baxis # Initialize validators # --------------------- self._validators["color"] = v_baxis.ColorValidator() self._validators["dtick"] = v_baxis.DtickValidator() self._validators["exponentformat"] = v_baxis.ExponentformatValidator() self._validators["gridcolor"] = v_baxis.GridcolorValidator() self._validators["gridwidth"] = v_baxis.GridwidthValidator() self._validators["hoverformat"] = v_baxis.HoverformatValidator() self._validators["layer"] = v_baxis.LayerValidator() self._validators["linecolor"] = v_baxis.LinecolorValidator() self._validators["linewidth"] = v_baxis.LinewidthValidator() self._validators["min"] = v_baxis.MinValidator() self._validators["nticks"] = v_baxis.NticksValidator() self._validators["separatethousands"] = v_baxis.SeparatethousandsValidator() self._validators["showexponent"] = v_baxis.ShowexponentValidator() self._validators["showgrid"] = v_baxis.ShowgridValidator() self._validators["showline"] = v_baxis.ShowlineValidator() self._validators["showticklabels"] = v_baxis.ShowticklabelsValidator() self._validators["showtickprefix"] = v_baxis.ShowtickprefixValidator() self._validators["showticksuffix"] = v_baxis.ShowticksuffixValidator() self._validators["tick0"] = v_baxis.Tick0Validator() self._validators["tickangle"] = v_baxis.TickangleValidator() self._validators["tickcolor"] = v_baxis.TickcolorValidator() self._validators["tickfont"] = v_baxis.TickfontValidator() self._validators["tickformat"] = v_baxis.TickformatValidator() self._validators["tickformatstops"] = v_baxis.TickformatstopsValidator() self._validators["tickformatstopdefaults"] = v_baxis.TickformatstopValidator() self._validators["ticklen"] = v_baxis.TicklenValidator() self._validators["tickmode"] = v_baxis.TickmodeValidator() self._validators["tickprefix"] = v_baxis.TickprefixValidator() self._validators["ticks"] = v_baxis.TicksValidator() self._validators["ticksuffix"] = v_baxis.TicksuffixValidator() self._validators["ticktext"] = v_baxis.TicktextValidator() self._validators["ticktextsrc"] = v_baxis.TicktextsrcValidator() self._validators["tickvals"] = v_baxis.TickvalsValidator() self._validators["tickvalssrc"] = v_baxis.TickvalssrcValidator() self._validators["tickwidth"] = v_baxis.TickwidthValidator() self._validators["title"] = v_baxis.TitleValidator() self._validators["uirevision"] = v_baxis.UirevisionValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("dtick", None) self["dtick"] = dtick if dtick is not None else _v _v = arg.pop("exponentformat", None) self["exponentformat"] = exponentformat if exponentformat is not None else _v _v = arg.pop("gridcolor", None) self["gridcolor"] = gridcolor if gridcolor is not None else _v _v = arg.pop("gridwidth", None) self["gridwidth"] = gridwidth if gridwidth is not None else _v _v = arg.pop("hoverformat", None) self["hoverformat"] = hoverformat if hoverformat is not None else _v _v = arg.pop("layer", None) self["layer"] = layer if layer is not None else _v _v = arg.pop("linecolor", None) self["linecolor"] = linecolor if linecolor is not None else _v _v = arg.pop("linewidth", None) self["linewidth"] = linewidth if linewidth is not None else _v _v = arg.pop("min", None) self["min"] = min if min is not None else _v _v = arg.pop("nticks", None) self["nticks"] = nticks if nticks is not None else _v _v = arg.pop("separatethousands", None) self["separatethousands"] = ( separatethousands if separatethousands is not None else _v ) _v = arg.pop("showexponent", None) self["showexponent"] = showexponent if showexponent is not None else _v _v = arg.pop("showgrid", None) self["showgrid"] = showgrid if showgrid is not None else _v _v = arg.pop("showline", None) self["showline"] = showline if showline is not None else _v _v = arg.pop("showticklabels", None) self["showticklabels"] = showticklabels if showticklabels is not None else _v _v = arg.pop("showtickprefix", None) self["showtickprefix"] = showtickprefix if showtickprefix is not None else _v _v = arg.pop("showticksuffix", None) self["showticksuffix"] = showticksuffix if showticksuffix is not None else _v _v = arg.pop("tick0", None) self["tick0"] = tick0 if tick0 is not None else _v _v = arg.pop("tickangle", None) self["tickangle"] = tickangle if tickangle is not None else _v _v = arg.pop("tickcolor", None) self["tickcolor"] = tickcolor if tickcolor is not None else _v _v = arg.pop("tickfont", None) self["tickfont"] = tickfont if tickfont is not None else _v _v = arg.pop("tickformat", None) self["tickformat"] = tickformat if tickformat is not None else _v _v = arg.pop("tickformatstops", None) self["tickformatstops"] = tickformatstops if tickformatstops is not None else _v _v = arg.pop("tickformatstopdefaults", None) self["tickformatstopdefaults"] = ( tickformatstopdefaults if tickformatstopdefaults is not None else _v ) _v = arg.pop("ticklen", None) self["ticklen"] = ticklen if ticklen is not None else _v _v = arg.pop("tickmode", None) self["tickmode"] = tickmode if tickmode is not None else _v _v = arg.pop("tickprefix", None) self["tickprefix"] = tickprefix if tickprefix is not None else _v _v = arg.pop("ticks", None) self["ticks"] = ticks if ticks is not None else _v _v = arg.pop("ticksuffix", None) self["ticksuffix"] = ticksuffix if ticksuffix is not None else _v _v = arg.pop("ticktext", None) self["ticktext"] = ticktext if ticktext is not None else _v _v = arg.pop("ticktextsrc", None) self["ticktextsrc"] = ticktextsrc if ticktextsrc is not None else _v _v = arg.pop("tickvals", None) self["tickvals"] = tickvals if tickvals is not None else _v _v = arg.pop("tickvalssrc", None) self["tickvalssrc"] = tickvalssrc if tickvalssrc is not None else _v _v = arg.pop("tickwidth", None) self["tickwidth"] = tickwidth if tickwidth is not None else _v _v = arg.pop("title", None) self["title"] = title if title is not None else _v _v = arg.pop("titlefont", None) _v = titlefont if titlefont is not None else _v if _v is not None: self["titlefont"] = _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Aaxis(_BaseLayoutHierarchyType): # color # ----- @property def color(self): """ Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # dtick # ----- @property def dtick(self): """ Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" The 'dtick' property accepts values of any type Returns ------- Any """ return self["dtick"] @dtick.setter def dtick(self, val): self["dtick"] = val # exponentformat # -------------- @property def exponentformat(self): """ Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. The 'exponentformat' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'e', 'E', 'power', 'SI', 'B'] Returns ------- Any """ return self["exponentformat"] @exponentformat.setter def exponentformat(self, val): self["exponentformat"] = val # gridcolor # --------- @property def gridcolor(self): """ Sets the color of the grid lines. The 'gridcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["gridcolor"] @gridcolor.setter def gridcolor(self, val): self["gridcolor"] = val # gridwidth # --------- @property def gridwidth(self): """ Sets the width (in px) of the grid lines. The 'gridwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["gridwidth"] @gridwidth.setter def gridwidth(self, val): self["gridwidth"] = val # hoverformat # ----------- @property def hoverformat(self): """ Sets the hover text formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'hoverformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["hoverformat"] @hoverformat.setter def hoverformat(self, val): self["hoverformat"] = val # layer # ----- @property def layer(self): """ Sets the layer on which this axis is displayed. If *above traces*, this axis is displayed above all the subplot's traces If *below traces*, this axis is displayed below all the subplot's traces, but above the grid lines. Useful when used together with scatter-like traces with `cliponaxis` set to False to show markers and/or text nodes above this axis. The 'layer' property is an enumeration that may be specified as: - One of the following enumeration values: ['above traces', 'below traces'] Returns ------- Any """ return self["layer"] @layer.setter def layer(self, val): self["layer"] = val # linecolor # --------- @property def linecolor(self): """ Sets the axis line color. The 'linecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["linecolor"] @linecolor.setter def linecolor(self, val): self["linecolor"] = val # linewidth # --------- @property def linewidth(self): """ Sets the width (in px) of the axis line. The 'linewidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["linewidth"] @linewidth.setter def linewidth(self, val): self["linewidth"] = val # min # --- @property def min(self): """ The minimum value visible on this axis. The maximum is determined by the sum minus the minimum values of the other two axes. The full view corresponds to all the minima set to zero. The 'min' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["min"] @min.setter def min(self, val): self["min"] = val # nticks # ------ @property def nticks(self): """ Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". The 'nticks' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [1, 9223372036854775807] Returns ------- int """ return self["nticks"] @nticks.setter def nticks(self, val): self["nticks"] = val # separatethousands # ----------------- @property def separatethousands(self): """ If "true", even 4-digit integers are separated The 'separatethousands' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["separatethousands"] @separatethousands.setter def separatethousands(self, val): self["separatethousands"] = val # showexponent # ------------ @property def showexponent(self): """ If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. The 'showexponent' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showexponent"] @showexponent.setter def showexponent(self, val): self["showexponent"] = val # showgrid # -------- @property def showgrid(self): """ Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. The 'showgrid' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showgrid"] @showgrid.setter def showgrid(self, val): self["showgrid"] = val # showline # -------- @property def showline(self): """ Determines whether or not a line bounding this axis is drawn. The 'showline' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showline"] @showline.setter def showline(self, val): self["showline"] = val # showticklabels # -------------- @property def showticklabels(self): """ Determines whether or not the tick labels are drawn. The 'showticklabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showticklabels"] @showticklabels.setter def showticklabels(self, val): self["showticklabels"] = val # showtickprefix # -------------- @property def showtickprefix(self): """ If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. The 'showtickprefix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showtickprefix"] @showtickprefix.setter def showtickprefix(self, val): self["showtickprefix"] = val # showticksuffix # -------------- @property def showticksuffix(self): """ Same as `showtickprefix` but for tick suffixes. The 'showticksuffix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showticksuffix"] @showticksuffix.setter def showticksuffix(self, val): self["showticksuffix"] = val # tick0 # ----- @property def tick0(self): """ Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. The 'tick0' property accepts values of any type Returns ------- Any """ return self["tick0"] @tick0.setter def tick0(self, val): self["tick0"] = val # tickangle # --------- @property def tickangle(self): """ Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. The 'tickangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["tickangle"] @tickangle.setter def tickangle(self, val): self["tickangle"] = val # tickcolor # --------- @property def tickcolor(self): """ Sets the tick color. The 'tickcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["tickcolor"] @tickcolor.setter def tickcolor(self, val): self["tickcolor"] = val # tickfont # -------- @property def tickfont(self): """ Sets the tick font. The 'tickfont' property is an instance of Tickfont that may be specified as: - An instance of plotly.graph_objs.layout.ternary.aaxis.Tickfont - A dict of string/value properties that will be passed to the Tickfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.layout.ternary.aaxis.Tickfont """ return self["tickfont"] @tickfont.setter def tickfont(self, val): self["tickfont"] = val # tickformat # ---------- @property def tickformat(self): """ Sets the tick label formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'tickformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickformat"] @tickformat.setter def tickformat(self, val): self["tickformat"] = val # tickformatstops # --------------- @property def tickformatstops(self): """ The 'tickformatstops' property is a tuple of instances of Tickformatstop that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.ternary.aaxis.Tickformatstop - A list or tuple of dicts of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- tuple[plotly.graph_objs.layout.ternary.aaxis.Tickformatstop] """ return self["tickformatstops"] @tickformatstops.setter def tickformatstops(self, val): self["tickformatstops"] = val # tickformatstopdefaults # ---------------------- @property def tickformatstopdefaults(self): """ When used in a template (as layout.template.layout.ternary.aaxis.tickformatstopdefaults), sets the default property values to use for elements of layout.ternary.aaxis.tickformatstops The 'tickformatstopdefaults' property is an instance of Tickformatstop that may be specified as: - An instance of plotly.graph_objs.layout.ternary.aaxis.Tickformatstop - A dict of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: Returns ------- plotly.graph_objs.layout.ternary.aaxis.Tickformatstop """ return self["tickformatstopdefaults"] @tickformatstopdefaults.setter def tickformatstopdefaults(self, val): self["tickformatstopdefaults"] = val # ticklen # ------- @property def ticklen(self): """ Sets the tick length (in px). The 'ticklen' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ticklen"] @ticklen.setter def ticklen(self, val): self["ticklen"] = val # tickmode # -------- @property def tickmode(self): """ Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). The 'tickmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'linear', 'array'] Returns ------- Any """ return self["tickmode"] @tickmode.setter def tickmode(self, val): self["tickmode"] = val # tickprefix # ---------- @property def tickprefix(self): """ Sets a tick label prefix. The 'tickprefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickprefix"] @tickprefix.setter def tickprefix(self, val): self["tickprefix"] = val # ticks # ----- @property def ticks(self): """ Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. The 'ticks' property is an enumeration that may be specified as: - One of the following enumeration values: ['outside', 'inside', ''] Returns ------- Any """ return self["ticks"] @ticks.setter def ticks(self, val): self["ticks"] = val # ticksuffix # ---------- @property def ticksuffix(self): """ Sets a tick label suffix. The 'ticksuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ticksuffix"] @ticksuffix.setter def ticksuffix(self, val): self["ticksuffix"] = val # ticktext # -------- @property def ticktext(self): """ Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. The 'ticktext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ticktext"] @ticktext.setter def ticktext(self, val): self["ticktext"] = val # ticktextsrc # ----------- @property def ticktextsrc(self): """ Sets the source reference on plot.ly for ticktext . The 'ticktextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ticktextsrc"] @ticktextsrc.setter def ticktextsrc(self, val): self["ticktextsrc"] = val # tickvals # -------- @property def tickvals(self): """ Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. The 'tickvals' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["tickvals"] @tickvals.setter def tickvals(self, val): self["tickvals"] = val # tickvalssrc # ----------- @property def tickvalssrc(self): """ Sets the source reference on plot.ly for tickvals . The 'tickvalssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tickvalssrc"] @tickvalssrc.setter def tickvalssrc(self, val): self["tickvalssrc"] = val # tickwidth # --------- @property def tickwidth(self): """ Sets the tick width (in px). The 'tickwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["tickwidth"] @tickwidth.setter def tickwidth(self, val): self["tickwidth"] = val # title # ----- @property def title(self): """ The 'title' property is an instance of Title that may be specified as: - An instance of plotly.graph_objs.layout.ternary.aaxis.Title - A dict of string/value properties that will be passed to the Title constructor Supported dict properties: font Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. text Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- plotly.graph_objs.layout.ternary.aaxis.Title """ return self["title"] @title.setter def title(self, val): self["title"] = val # titlefont # --------- @property def titlefont(self): """ Deprecated: Please use layout.ternary.aaxis.title.font instead. Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.layout.ternary.aaxis.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- """ return self["titlefont"] @titlefont.setter def titlefont(self, val): self["titlefont"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of user-driven changes in axis `min`, and `title` if in `editable: true` configuration. Defaults to `ternary.uirevision`. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.ternary" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. gridcolor Sets the color of the grid lines. gridwidth Sets the width (in px) of the grid lines. hoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" layer Sets the layer on which this axis is displayed. If *above traces*, this axis is displayed above all the subplot's traces If *below traces*, this axis is displayed below all the subplot's traces, but above the grid lines. Useful when used together with scatter-like traces with `cliponaxis` set to False to show markers and/or text nodes above this axis. linecolor Sets the axis line color. linewidth Sets the width (in px) of the axis line. min The minimum value visible on this axis. The maximum is determined by the sum minus the minimum values of the other two axes. The full view corresponds to all the minima set to zero. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showgrid Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. showline Determines whether or not a line bounding this axis is drawn. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the tick font. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.layout.ternary.aaxis.Ti ckformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.layout.tern ary.aaxis.tickformatstopdefaults), sets the default property values to use for elements of layout.ternary.aaxis.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.layout.ternary.aaxis.Title instance or dict with compatible properties titlefont Deprecated: Please use layout.ternary.aaxis.title.font instead. Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. uirevision Controls persistence of user-driven changes in axis `min`, and `title` if in `editable: true` configuration. Defaults to `ternary.uirevision`. """ _mapped_properties = {"titlefont": ("title", "font")} def __init__( self, arg=None, color=None, dtick=None, exponentformat=None, gridcolor=None, gridwidth=None, hoverformat=None, layer=None, linecolor=None, linewidth=None, min=None, nticks=None, separatethousands=None, showexponent=None, showgrid=None, showline=None, showticklabels=None, showtickprefix=None, showticksuffix=None, tick0=None, tickangle=None, tickcolor=None, tickfont=None, tickformat=None, tickformatstops=None, tickformatstopdefaults=None, ticklen=None, tickmode=None, tickprefix=None, ticks=None, ticksuffix=None, ticktext=None, ticktextsrc=None, tickvals=None, tickvalssrc=None, tickwidth=None, title=None, titlefont=None, uirevision=None, **kwargs ): """ Construct a new Aaxis object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.ternary.Aaxis color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. gridcolor Sets the color of the grid lines. gridwidth Sets the width (in px) of the grid lines. hoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" layer Sets the layer on which this axis is displayed. If *above traces*, this axis is displayed above all the subplot's traces If *below traces*, this axis is displayed below all the subplot's traces, but above the grid lines. Useful when used together with scatter-like traces with `cliponaxis` set to False to show markers and/or text nodes above this axis. linecolor Sets the axis line color. linewidth Sets the width (in px) of the axis line. min The minimum value visible on this axis. The maximum is determined by the sum minus the minimum values of the other two axes. The full view corresponds to all the minima set to zero. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showgrid Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. showline Determines whether or not a line bounding this axis is drawn. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the tick font. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.layout.ternary.aaxis.Ti ckformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.layout.tern ary.aaxis.tickformatstopdefaults), sets the default property values to use for elements of layout.ternary.aaxis.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.layout.ternary.aaxis.Title instance or dict with compatible properties titlefont Deprecated: Please use layout.ternary.aaxis.title.font instead. Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. uirevision Controls persistence of user-driven changes in axis `min`, and `title` if in `editable: true` configuration. Defaults to `ternary.uirevision`. Returns ------- Aaxis """ super(Aaxis, self).__init__("aaxis") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.ternary.Aaxis constructor must be a dict or an instance of plotly.graph_objs.layout.ternary.Aaxis""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.ternary import aaxis as v_aaxis # Initialize validators # --------------------- self._validators["color"] = v_aaxis.ColorValidator() self._validators["dtick"] = v_aaxis.DtickValidator() self._validators["exponentformat"] = v_aaxis.ExponentformatValidator() self._validators["gridcolor"] = v_aaxis.GridcolorValidator() self._validators["gridwidth"] = v_aaxis.GridwidthValidator() self._validators["hoverformat"] = v_aaxis.HoverformatValidator() self._validators["layer"] = v_aaxis.LayerValidator() self._validators["linecolor"] = v_aaxis.LinecolorValidator() self._validators["linewidth"] = v_aaxis.LinewidthValidator() self._validators["min"] = v_aaxis.MinValidator() self._validators["nticks"] = v_aaxis.NticksValidator() self._validators["separatethousands"] = v_aaxis.SeparatethousandsValidator() self._validators["showexponent"] = v_aaxis.ShowexponentValidator() self._validators["showgrid"] = v_aaxis.ShowgridValidator() self._validators["showline"] = v_aaxis.ShowlineValidator() self._validators["showticklabels"] = v_aaxis.ShowticklabelsValidator() self._validators["showtickprefix"] = v_aaxis.ShowtickprefixValidator() self._validators["showticksuffix"] = v_aaxis.ShowticksuffixValidator() self._validators["tick0"] = v_aaxis.Tick0Validator() self._validators["tickangle"] = v_aaxis.TickangleValidator() self._validators["tickcolor"] = v_aaxis.TickcolorValidator() self._validators["tickfont"] = v_aaxis.TickfontValidator() self._validators["tickformat"] = v_aaxis.TickformatValidator() self._validators["tickformatstops"] = v_aaxis.TickformatstopsValidator() self._validators["tickformatstopdefaults"] = v_aaxis.TickformatstopValidator() self._validators["ticklen"] = v_aaxis.TicklenValidator() self._validators["tickmode"] = v_aaxis.TickmodeValidator() self._validators["tickprefix"] = v_aaxis.TickprefixValidator() self._validators["ticks"] = v_aaxis.TicksValidator() self._validators["ticksuffix"] = v_aaxis.TicksuffixValidator() self._validators["ticktext"] = v_aaxis.TicktextValidator() self._validators["ticktextsrc"] = v_aaxis.TicktextsrcValidator() self._validators["tickvals"] = v_aaxis.TickvalsValidator() self._validators["tickvalssrc"] = v_aaxis.TickvalssrcValidator() self._validators["tickwidth"] = v_aaxis.TickwidthValidator() self._validators["title"] = v_aaxis.TitleValidator() self._validators["uirevision"] = v_aaxis.UirevisionValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("dtick", None) self["dtick"] = dtick if dtick is not None else _v _v = arg.pop("exponentformat", None) self["exponentformat"] = exponentformat if exponentformat is not None else _v _v = arg.pop("gridcolor", None) self["gridcolor"] = gridcolor if gridcolor is not None else _v _v = arg.pop("gridwidth", None) self["gridwidth"] = gridwidth if gridwidth is not None else _v _v = arg.pop("hoverformat", None) self["hoverformat"] = hoverformat if hoverformat is not None else _v _v = arg.pop("layer", None) self["layer"] = layer if layer is not None else _v _v = arg.pop("linecolor", None) self["linecolor"] = linecolor if linecolor is not None else _v _v = arg.pop("linewidth", None) self["linewidth"] = linewidth if linewidth is not None else _v _v = arg.pop("min", None) self["min"] = min if min is not None else _v _v = arg.pop("nticks", None) self["nticks"] = nticks if nticks is not None else _v _v = arg.pop("separatethousands", None) self["separatethousands"] = ( separatethousands if separatethousands is not None else _v ) _v = arg.pop("showexponent", None) self["showexponent"] = showexponent if showexponent is not None else _v _v = arg.pop("showgrid", None) self["showgrid"] = showgrid if showgrid is not None else _v _v = arg.pop("showline", None) self["showline"] = showline if showline is not None else _v _v = arg.pop("showticklabels", None) self["showticklabels"] = showticklabels if showticklabels is not None else _v _v = arg.pop("showtickprefix", None) self["showtickprefix"] = showtickprefix if showtickprefix is not None else _v _v = arg.pop("showticksuffix", None) self["showticksuffix"] = showticksuffix if showticksuffix is not None else _v _v = arg.pop("tick0", None) self["tick0"] = tick0 if tick0 is not None else _v _v = arg.pop("tickangle", None) self["tickangle"] = tickangle if tickangle is not None else _v _v = arg.pop("tickcolor", None) self["tickcolor"] = tickcolor if tickcolor is not None else _v _v = arg.pop("tickfont", None) self["tickfont"] = tickfont if tickfont is not None else _v _v = arg.pop("tickformat", None) self["tickformat"] = tickformat if tickformat is not None else _v _v = arg.pop("tickformatstops", None) self["tickformatstops"] = tickformatstops if tickformatstops is not None else _v _v = arg.pop("tickformatstopdefaults", None) self["tickformatstopdefaults"] = ( tickformatstopdefaults if tickformatstopdefaults is not None else _v ) _v = arg.pop("ticklen", None) self["ticklen"] = ticklen if ticklen is not None else _v _v = arg.pop("tickmode", None) self["tickmode"] = tickmode if tickmode is not None else _v _v = arg.pop("tickprefix", None) self["tickprefix"] = tickprefix if tickprefix is not None else _v _v = arg.pop("ticks", None) self["ticks"] = ticks if ticks is not None else _v _v = arg.pop("ticksuffix", None) self["ticksuffix"] = ticksuffix if ticksuffix is not None else _v _v = arg.pop("ticktext", None) self["ticktext"] = ticktext if ticktext is not None else _v _v = arg.pop("ticktextsrc", None) self["ticktextsrc"] = ticktextsrc if ticktextsrc is not None else _v _v = arg.pop("tickvals", None) self["tickvals"] = tickvals if tickvals is not None else _v _v = arg.pop("tickvalssrc", None) self["tickvalssrc"] = tickvalssrc if tickvalssrc is not None else _v _v = arg.pop("tickwidth", None) self["tickwidth"] = tickwidth if tickwidth is not None else _v _v = arg.pop("title", None) self["title"] = title if title is not None else _v _v = arg.pop("titlefont", None) _v = titlefont if titlefont is not None else _v if _v is not None: self["titlefont"] = _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Aaxis", "Baxis", "Caxis", "Domain", "aaxis", "baxis", "caxis"] from plotly.graph_objs.layout.ternary import caxis from plotly.graph_objs.layout.ternary import baxis from plotly.graph_objs.layout.ternary import aaxis plotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/ternary/aaxis/0000755000175000017500000000000013573746613024037 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/ternary/aaxis/title/0000755000175000017500000000000013573746613025160 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/ternary/aaxis/title/__init__.py0000644000175000017500000002055513573721547027277 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Font(_BaseLayoutHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.ternary.aaxis.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.ternary.aaxis.title.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.ternary.aaxis.title.Font constructor must be a dict or an instance of plotly.graph_objs.layout.ternary.aaxis.title.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.ternary.aaxis.title import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/ternary/aaxis/__init__.py0000644000175000017500000005636013573721547026161 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Title(_BaseLayoutHierarchyType): # font # ---- @property def font(self): """ Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.layout.ternary.aaxis.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.layout.ternary.aaxis.title.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # text # ---- @property def text(self): """ Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.ternary.aaxis" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. text Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """ def __init__(self, arg=None, font=None, text=None, **kwargs): """ Construct a new Title object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.ternary.aaxis.Title font Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. text Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- Title """ super(Title, self).__init__("title") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.ternary.aaxis.Title constructor must be a dict or an instance of plotly.graph_objs.layout.ternary.aaxis.Title""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.ternary.aaxis import title as v_title # Initialize validators # --------------------- self._validators["font"] = v_title.FontValidator() self._validators["text"] = v_title.TextValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Tickformatstop(_BaseLayoutHierarchyType): # dtickrange # ---------- @property def dtickrange(self): """ range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" The 'dtickrange' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'dtickrange[0]' property accepts values of any type (1) The 'dtickrange[1]' property accepts values of any type Returns ------- list """ return self["dtickrange"] @dtickrange.setter def dtickrange(self, val): self["dtickrange"] = val # enabled # ------- @property def enabled(self): """ Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. The 'enabled' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["enabled"] @enabled.setter def enabled(self, val): self["enabled"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # value # ----- @property def value(self): """ string - dtickformat for described zoom level, the same as "tickformat" The 'value' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.ternary.aaxis" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """ def __init__( self, arg=None, dtickrange=None, enabled=None, name=None, templateitemname=None, value=None, **kwargs ): """ Construct a new Tickformatstop object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.ternary.aaxis.Tickformatstop dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- Tickformatstop """ super(Tickformatstop, self).__init__("tickformatstops") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.ternary.aaxis.Tickformatstop constructor must be a dict or an instance of plotly.graph_objs.layout.ternary.aaxis.Tickformatstop""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.ternary.aaxis import ( tickformatstop as v_tickformatstop, ) # Initialize validators # --------------------- self._validators["dtickrange"] = v_tickformatstop.DtickrangeValidator() self._validators["enabled"] = v_tickformatstop.EnabledValidator() self._validators["name"] = v_tickformatstop.NameValidator() self._validators[ "templateitemname" ] = v_tickformatstop.TemplateitemnameValidator() self._validators["value"] = v_tickformatstop.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtickrange", None) self["dtickrange"] = dtickrange if dtickrange is not None else _v _v = arg.pop("enabled", None) self["enabled"] = enabled if enabled is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Tickfont(_BaseLayoutHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.ternary.aaxis" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Tickfont object Sets the tick font. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.ternary.aaxis.Tickfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Tickfont """ super(Tickfont, self).__init__("tickfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.ternary.aaxis.Tickfont constructor must be a dict or an instance of plotly.graph_objs.layout.ternary.aaxis.Tickfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.ternary.aaxis import tickfont as v_tickfont # Initialize validators # --------------------- self._validators["color"] = v_tickfont.ColorValidator() self._validators["family"] = v_tickfont.FamilyValidator() self._validators["size"] = v_tickfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Tickfont", "Tickformatstop", "Tickformatstop", "Title", "title"] from plotly.graph_objs.layout.ternary.aaxis import title plotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/ternary/caxis/0000755000175000017500000000000013573746613024041 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/ternary/caxis/title/0000755000175000017500000000000013573746613025162 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/ternary/caxis/title/__init__.py0000644000175000017500000002055513573721547027301 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Font(_BaseLayoutHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.ternary.caxis.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.ternary.caxis.title.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.ternary.caxis.title.Font constructor must be a dict or an instance of plotly.graph_objs.layout.ternary.caxis.title.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.ternary.caxis.title import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/ternary/caxis/__init__.py0000644000175000017500000005636013573721550026155 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Title(_BaseLayoutHierarchyType): # font # ---- @property def font(self): """ Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.layout.ternary.caxis.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.layout.ternary.caxis.title.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # text # ---- @property def text(self): """ Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.ternary.caxis" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. text Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """ def __init__(self, arg=None, font=None, text=None, **kwargs): """ Construct a new Title object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.ternary.caxis.Title font Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. text Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- Title """ super(Title, self).__init__("title") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.ternary.caxis.Title constructor must be a dict or an instance of plotly.graph_objs.layout.ternary.caxis.Title""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.ternary.caxis import title as v_title # Initialize validators # --------------------- self._validators["font"] = v_title.FontValidator() self._validators["text"] = v_title.TextValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Tickformatstop(_BaseLayoutHierarchyType): # dtickrange # ---------- @property def dtickrange(self): """ range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" The 'dtickrange' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'dtickrange[0]' property accepts values of any type (1) The 'dtickrange[1]' property accepts values of any type Returns ------- list """ return self["dtickrange"] @dtickrange.setter def dtickrange(self, val): self["dtickrange"] = val # enabled # ------- @property def enabled(self): """ Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. The 'enabled' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["enabled"] @enabled.setter def enabled(self, val): self["enabled"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # value # ----- @property def value(self): """ string - dtickformat for described zoom level, the same as "tickformat" The 'value' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.ternary.caxis" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """ def __init__( self, arg=None, dtickrange=None, enabled=None, name=None, templateitemname=None, value=None, **kwargs ): """ Construct a new Tickformatstop object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.ternary.caxis.Tickformatstop dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- Tickformatstop """ super(Tickformatstop, self).__init__("tickformatstops") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.ternary.caxis.Tickformatstop constructor must be a dict or an instance of plotly.graph_objs.layout.ternary.caxis.Tickformatstop""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.ternary.caxis import ( tickformatstop as v_tickformatstop, ) # Initialize validators # --------------------- self._validators["dtickrange"] = v_tickformatstop.DtickrangeValidator() self._validators["enabled"] = v_tickformatstop.EnabledValidator() self._validators["name"] = v_tickformatstop.NameValidator() self._validators[ "templateitemname" ] = v_tickformatstop.TemplateitemnameValidator() self._validators["value"] = v_tickformatstop.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtickrange", None) self["dtickrange"] = dtickrange if dtickrange is not None else _v _v = arg.pop("enabled", None) self["enabled"] = enabled if enabled is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Tickfont(_BaseLayoutHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.ternary.caxis" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Tickfont object Sets the tick font. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.ternary.caxis.Tickfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Tickfont """ super(Tickfont, self).__init__("tickfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.ternary.caxis.Tickfont constructor must be a dict or an instance of plotly.graph_objs.layout.ternary.caxis.Tickfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.ternary.caxis import tickfont as v_tickfont # Initialize validators # --------------------- self._validators["color"] = v_tickfont.ColorValidator() self._validators["family"] = v_tickfont.FamilyValidator() self._validators["size"] = v_tickfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Tickfont", "Tickformatstop", "Tickformatstop", "Title", "title"] from plotly.graph_objs.layout.ternary.caxis import title plotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/ternary/baxis/0000755000175000017500000000000013573746613024040 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/ternary/baxis/title/0000755000175000017500000000000013573746613025161 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/ternary/baxis/title/__init__.py0000644000175000017500000002055513573721547027300 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Font(_BaseLayoutHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.ternary.baxis.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.ternary.baxis.title.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.ternary.baxis.title.Font constructor must be a dict or an instance of plotly.graph_objs.layout.ternary.baxis.title.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.ternary.baxis.title import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/ternary/baxis/__init__.py0000644000175000017500000005636013573721550026154 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Title(_BaseLayoutHierarchyType): # font # ---- @property def font(self): """ Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.layout.ternary.baxis.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.layout.ternary.baxis.title.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # text # ---- @property def text(self): """ Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.ternary.baxis" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. text Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """ def __init__(self, arg=None, font=None, text=None, **kwargs): """ Construct a new Title object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.ternary.baxis.Title font Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. text Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- Title """ super(Title, self).__init__("title") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.ternary.baxis.Title constructor must be a dict or an instance of plotly.graph_objs.layout.ternary.baxis.Title""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.ternary.baxis import title as v_title # Initialize validators # --------------------- self._validators["font"] = v_title.FontValidator() self._validators["text"] = v_title.TextValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Tickformatstop(_BaseLayoutHierarchyType): # dtickrange # ---------- @property def dtickrange(self): """ range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" The 'dtickrange' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'dtickrange[0]' property accepts values of any type (1) The 'dtickrange[1]' property accepts values of any type Returns ------- list """ return self["dtickrange"] @dtickrange.setter def dtickrange(self, val): self["dtickrange"] = val # enabled # ------- @property def enabled(self): """ Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. The 'enabled' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["enabled"] @enabled.setter def enabled(self, val): self["enabled"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # value # ----- @property def value(self): """ string - dtickformat for described zoom level, the same as "tickformat" The 'value' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.ternary.baxis" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """ def __init__( self, arg=None, dtickrange=None, enabled=None, name=None, templateitemname=None, value=None, **kwargs ): """ Construct a new Tickformatstop object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.ternary.baxis.Tickformatstop dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- Tickformatstop """ super(Tickformatstop, self).__init__("tickformatstops") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.ternary.baxis.Tickformatstop constructor must be a dict or an instance of plotly.graph_objs.layout.ternary.baxis.Tickformatstop""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.ternary.baxis import ( tickformatstop as v_tickformatstop, ) # Initialize validators # --------------------- self._validators["dtickrange"] = v_tickformatstop.DtickrangeValidator() self._validators["enabled"] = v_tickformatstop.EnabledValidator() self._validators["name"] = v_tickformatstop.NameValidator() self._validators[ "templateitemname" ] = v_tickformatstop.TemplateitemnameValidator() self._validators["value"] = v_tickformatstop.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtickrange", None) self["dtickrange"] = dtickrange if dtickrange is not None else _v _v = arg.pop("enabled", None) self["enabled"] = enabled if enabled is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Tickfont(_BaseLayoutHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.ternary.baxis" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Tickfont object Sets the tick font. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.ternary.baxis.Tickfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Tickfont """ super(Tickfont, self).__init__("tickfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.ternary.baxis.Tickfont constructor must be a dict or an instance of plotly.graph_objs.layout.ternary.baxis.Tickfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.ternary.baxis import tickfont as v_tickfont # Initialize validators # --------------------- self._validators["color"] = v_tickfont.ColorValidator() self._validators["family"] = v_tickfont.FamilyValidator() self._validators["size"] = v_tickfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Tickfont", "Tickformatstop", "Tickformatstop", "Title", "title"] from plotly.graph_objs.layout.ternary.baxis import title plotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/hoverlabel/0000755000175000017500000000000013573746613023371 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/hoverlabel/__init__.py0000644000175000017500000002037513573721547025510 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Font(_BaseLayoutHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.hoverlabel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets the default hover label font used by all traces on the graph. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.hoverlabel.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.hoverlabel.Font constructor must be a dict or an instance of plotly.graph_objs.layout.hoverlabel.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.hoverlabel import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/grid/0000755000175000017500000000000013573746613022173 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/grid/__init__.py0000644000175000017500000001064313573721547024307 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Domain(_BaseLayoutHierarchyType): # x # - @property def x(self): """ Sets the horizontal domain of this grid subplot (in plot fraction). The first and last cells end exactly at the domain edges, with no grout around the edges. The 'x' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'x[0]' property is a number and may be specified as: - An int or float in the interval [0, 1] (1) The 'x[1]' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- list """ return self["x"] @x.setter def x(self, val): self["x"] = val # y # - @property def y(self): """ Sets the vertical domain of this grid subplot (in plot fraction). The first and last cells end exactly at the domain edges, with no grout around the edges. The 'y' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'y[0]' property is a number and may be specified as: - An int or float in the interval [0, 1] (1) The 'y[1]' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- list """ return self["y"] @y.setter def y(self, val): self["y"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.grid" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ x Sets the horizontal domain of this grid subplot (in plot fraction). The first and last cells end exactly at the domain edges, with no grout around the edges. y Sets the vertical domain of this grid subplot (in plot fraction). The first and last cells end exactly at the domain edges, with no grout around the edges. """ def __init__(self, arg=None, x=None, y=None, **kwargs): """ Construct a new Domain object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.grid.Domain x Sets the horizontal domain of this grid subplot (in plot fraction). The first and last cells end exactly at the domain edges, with no grout around the edges. y Sets the vertical domain of this grid subplot (in plot fraction). The first and last cells end exactly at the domain edges, with no grout around the edges. Returns ------- Domain """ super(Domain, self).__init__("domain") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.grid.Domain constructor must be a dict or an instance of plotly.graph_objs.layout.grid.Domain""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.grid import domain as v_domain # Initialize validators # --------------------- self._validators["x"] = v_domain.XValidator() self._validators["y"] = v_domain.YValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Domain"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/mapbox/0000755000175000017500000000000013573746613022534 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/mapbox/layer/0000755000175000017500000000000013573746613023650 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/mapbox/layer/__init__.py0000644000175000017500000005540313573721547025767 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Symbol(_BaseLayoutHierarchyType): # icon # ---- @property def icon(self): """ Sets the symbol icon image (mapbox.layer.layout.icon-image). Full list: https://www.mapbox.com/maki-icons/ The 'icon' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["icon"] @icon.setter def icon(self, val): self["icon"] = val # iconsize # -------- @property def iconsize(self): """ Sets the symbol icon size (mapbox.layer.layout.icon-size). Has an effect only when `type` is set to "symbol". The 'iconsize' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["iconsize"] @iconsize.setter def iconsize(self, val): self["iconsize"] = val # placement # --------- @property def placement(self): """ Sets the symbol and/or text placement (mapbox.layer.layout.symbol-placement). If `placement` is "point", the label is placed where the geometry is located If `placement` is "line", the label is placed along the line of the geometry If `placement` is "line-center", the label is placed on the center of the geometry The 'placement' property is an enumeration that may be specified as: - One of the following enumeration values: ['point', 'line', 'line-center'] Returns ------- Any """ return self["placement"] @placement.setter def placement(self, val): self["placement"] = val # text # ---- @property def text(self): """ Sets the symbol text (mapbox.layer.layout.text-field). The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # textfont # -------- @property def textfont(self): """ Sets the icon text font (color=mapbox.layer.paint.text-color, size=mapbox.layer.layout.text-size). Has an effect only when `type` is set to "symbol". The 'textfont' property is an instance of Textfont that may be specified as: - An instance of plotly.graph_objs.layout.mapbox.layer.symbol.Textfont - A dict of string/value properties that will be passed to the Textfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.layout.mapbox.layer.symbol.Textfont """ return self["textfont"] @textfont.setter def textfont(self, val): self["textfont"] = val # textposition # ------------ @property def textposition(self): """ Sets the positions of the `text` elements with respects to the (x,y) coordinates. The 'textposition' property is an enumeration that may be specified as: - One of the following enumeration values: ['top left', 'top center', 'top right', 'middle left', 'middle center', 'middle right', 'bottom left', 'bottom center', 'bottom right'] Returns ------- Any """ return self["textposition"] @textposition.setter def textposition(self, val): self["textposition"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.mapbox.layer" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ icon Sets the symbol icon image (mapbox.layer.layout.icon- image). Full list: https://www.mapbox.com/maki-icons/ iconsize Sets the symbol icon size (mapbox.layer.layout.icon- size). Has an effect only when `type` is set to "symbol". placement Sets the symbol and/or text placement (mapbox.layer.layout.symbol-placement). If `placement` is "point", the label is placed where the geometry is located If `placement` is "line", the label is placed along the line of the geometry If `placement` is "line- center", the label is placed on the center of the geometry text Sets the symbol text (mapbox.layer.layout.text-field). textfont Sets the icon text font (color=mapbox.layer.paint.text- color, size=mapbox.layer.layout.text-size). Has an effect only when `type` is set to "symbol". textposition Sets the positions of the `text` elements with respects to the (x,y) coordinates. """ def __init__( self, arg=None, icon=None, iconsize=None, placement=None, text=None, textfont=None, textposition=None, **kwargs ): """ Construct a new Symbol object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.mapbox.layer.Symbol icon Sets the symbol icon image (mapbox.layer.layout.icon- image). Full list: https://www.mapbox.com/maki-icons/ iconsize Sets the symbol icon size (mapbox.layer.layout.icon- size). Has an effect only when `type` is set to "symbol". placement Sets the symbol and/or text placement (mapbox.layer.layout.symbol-placement). If `placement` is "point", the label is placed where the geometry is located If `placement` is "line", the label is placed along the line of the geometry If `placement` is "line- center", the label is placed on the center of the geometry text Sets the symbol text (mapbox.layer.layout.text-field). textfont Sets the icon text font (color=mapbox.layer.paint.text- color, size=mapbox.layer.layout.text-size). Has an effect only when `type` is set to "symbol". textposition Sets the positions of the `text` elements with respects to the (x,y) coordinates. Returns ------- Symbol """ super(Symbol, self).__init__("symbol") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.mapbox.layer.Symbol constructor must be a dict or an instance of plotly.graph_objs.layout.mapbox.layer.Symbol""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.mapbox.layer import symbol as v_symbol # Initialize validators # --------------------- self._validators["icon"] = v_symbol.IconValidator() self._validators["iconsize"] = v_symbol.IconsizeValidator() self._validators["placement"] = v_symbol.PlacementValidator() self._validators["text"] = v_symbol.TextValidator() self._validators["textfont"] = v_symbol.TextfontValidator() self._validators["textposition"] = v_symbol.TextpositionValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("icon", None) self["icon"] = icon if icon is not None else _v _v = arg.pop("iconsize", None) self["iconsize"] = iconsize if iconsize is not None else _v _v = arg.pop("placement", None) self["placement"] = placement if placement is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v _v = arg.pop("textfont", None) self["textfont"] = textfont if textfont is not None else _v _v = arg.pop("textposition", None) self["textposition"] = textposition if textposition is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Line(_BaseLayoutHierarchyType): # dash # ---- @property def dash(self): """ Sets the length of dashes and gaps (mapbox.layer.paint.line- dasharray). Has an effect only when `type` is set to "line". The 'dash' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["dash"] @dash.setter def dash(self, val): self["dash"] = val # dashsrc # ------- @property def dashsrc(self): """ Sets the source reference on plot.ly for dash . The 'dashsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["dashsrc"] @dashsrc.setter def dashsrc(self, val): self["dashsrc"] = val # width # ----- @property def width(self): """ Sets the line width (mapbox.layer.paint.line-width). Has an effect only when `type` is set to "line". The 'width' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.mapbox.layer" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dash Sets the length of dashes and gaps (mapbox.layer.paint.line-dasharray). Has an effect only when `type` is set to "line". dashsrc Sets the source reference on plot.ly for dash . width Sets the line width (mapbox.layer.paint.line-width). Has an effect only when `type` is set to "line". """ def __init__(self, arg=None, dash=None, dashsrc=None, width=None, **kwargs): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.mapbox.layer.Line dash Sets the length of dashes and gaps (mapbox.layer.paint.line-dasharray). Has an effect only when `type` is set to "line". dashsrc Sets the source reference on plot.ly for dash . width Sets the line width (mapbox.layer.paint.line-width). Has an effect only when `type` is set to "line". Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.mapbox.layer.Line constructor must be a dict or an instance of plotly.graph_objs.layout.mapbox.layer.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.mapbox.layer import line as v_line # Initialize validators # --------------------- self._validators["dash"] = v_line.DashValidator() self._validators["dashsrc"] = v_line.DashsrcValidator() self._validators["width"] = v_line.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dash", None) self["dash"] = dash if dash is not None else _v _v = arg.pop("dashsrc", None) self["dashsrc"] = dashsrc if dashsrc is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Fill(_BaseLayoutHierarchyType): # outlinecolor # ------------ @property def outlinecolor(self): """ Sets the fill outline color (mapbox.layer.paint.fill-outline- color). Has an effect only when `type` is set to "fill". The 'outlinecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["outlinecolor"] @outlinecolor.setter def outlinecolor(self, val): self["outlinecolor"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.mapbox.layer" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ outlinecolor Sets the fill outline color (mapbox.layer.paint.fill- outline-color). Has an effect only when `type` is set to "fill". """ def __init__(self, arg=None, outlinecolor=None, **kwargs): """ Construct a new Fill object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.mapbox.layer.Fill outlinecolor Sets the fill outline color (mapbox.layer.paint.fill- outline-color). Has an effect only when `type` is set to "fill". Returns ------- Fill """ super(Fill, self).__init__("fill") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.mapbox.layer.Fill constructor must be a dict or an instance of plotly.graph_objs.layout.mapbox.layer.Fill""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.mapbox.layer import fill as v_fill # Initialize validators # --------------------- self._validators["outlinecolor"] = v_fill.OutlinecolorValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("outlinecolor", None) self["outlinecolor"] = outlinecolor if outlinecolor is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Circle(_BaseLayoutHierarchyType): # radius # ------ @property def radius(self): """ Sets the circle radius (mapbox.layer.paint.circle-radius). Has an effect only when `type` is set to "circle". The 'radius' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["radius"] @radius.setter def radius(self, val): self["radius"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.mapbox.layer" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ radius Sets the circle radius (mapbox.layer.paint.circle- radius). Has an effect only when `type` is set to "circle". """ def __init__(self, arg=None, radius=None, **kwargs): """ Construct a new Circle object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.mapbox.layer.Circle radius Sets the circle radius (mapbox.layer.paint.circle- radius). Has an effect only when `type` is set to "circle". Returns ------- Circle """ super(Circle, self).__init__("circle") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.mapbox.layer.Circle constructor must be a dict or an instance of plotly.graph_objs.layout.mapbox.layer.Circle""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.mapbox.layer import circle as v_circle # Initialize validators # --------------------- self._validators["radius"] = v_circle.RadiusValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("radius", None) self["radius"] = radius if radius is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Circle", "Fill", "Line", "Symbol", "symbol"] from plotly.graph_objs.layout.mapbox.layer import symbol plotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/mapbox/layer/symbol/0000755000175000017500000000000013573746613025155 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/mapbox/layer/symbol/__init__.py0000644000175000017500000002071113573721547027266 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Textfont(_BaseLayoutHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.mapbox.layer.symbol" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Textfont object Sets the icon text font (color=mapbox.layer.paint.text-color, size=mapbox.layer.layout.text-size). Has an effect only when `type` is set to "symbol". Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.mapbox.layer.symbol.Textfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Textfont """ super(Textfont, self).__init__("textfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.mapbox.layer.symbol.Textfont constructor must be a dict or an instance of plotly.graph_objs.layout.mapbox.layer.symbol.Textfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.mapbox.layer.symbol import textfont as v_textfont # Initialize validators # --------------------- self._validators["color"] = v_textfont.ColorValidator() self._validators["family"] = v_textfont.FamilyValidator() self._validators["size"] = v_textfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Textfont"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/mapbox/__init__.py0000644000175000017500000012030613573721547024646 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Layer(_BaseLayoutHierarchyType): # below # ----- @property def below(self): """ Determines if the layer will be inserted before the layer with the specified ID. If omitted or set to '', the layer will be inserted above every existing layer. The 'below' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["below"] @below.setter def below(self, val): self["below"] = val # circle # ------ @property def circle(self): """ The 'circle' property is an instance of Circle that may be specified as: - An instance of plotly.graph_objs.layout.mapbox.layer.Circle - A dict of string/value properties that will be passed to the Circle constructor Supported dict properties: radius Sets the circle radius (mapbox.layer.paint.circle-radius). Has an effect only when `type` is set to "circle". Returns ------- plotly.graph_objs.layout.mapbox.layer.Circle """ return self["circle"] @circle.setter def circle(self, val): self["circle"] = val # color # ----- @property def color(self): """ Sets the primary layer color. If `type` is "circle", color corresponds to the circle color (mapbox.layer.paint.circle- color) If `type` is "line", color corresponds to the line color (mapbox.layer.paint.line-color) If `type` is "fill", color corresponds to the fill color (mapbox.layer.paint.fill-color) If `type` is "symbol", color corresponds to the icon color (mapbox.layer.paint.icon-color) The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # coordinates # ----------- @property def coordinates(self): """ Sets the coordinates array contains [longitude, latitude] pairs for the image corners listed in clockwise order: top left, top right, bottom right, bottom left. Only has an effect for "image" `sourcetype`. The 'coordinates' property accepts values of any type Returns ------- Any """ return self["coordinates"] @coordinates.setter def coordinates(self, val): self["coordinates"] = val # fill # ---- @property def fill(self): """ The 'fill' property is an instance of Fill that may be specified as: - An instance of plotly.graph_objs.layout.mapbox.layer.Fill - A dict of string/value properties that will be passed to the Fill constructor Supported dict properties: outlinecolor Sets the fill outline color (mapbox.layer.paint.fill-outline-color). Has an effect only when `type` is set to "fill". Returns ------- plotly.graph_objs.layout.mapbox.layer.Fill """ return self["fill"] @fill.setter def fill(self, val): self["fill"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.layout.mapbox.layer.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: dash Sets the length of dashes and gaps (mapbox.layer.paint.line-dasharray). Has an effect only when `type` is set to "line". dashsrc Sets the source reference on plot.ly for dash . width Sets the line width (mapbox.layer.paint.line- width). Has an effect only when `type` is set to "line". Returns ------- plotly.graph_objs.layout.mapbox.layer.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # maxzoom # ------- @property def maxzoom(self): """ Sets the maximum zoom level (mapbox.layer.maxzoom). At zoom levels equal to or greater than the maxzoom, the layer will be hidden. The 'maxzoom' property is a number and may be specified as: - An int or float in the interval [0, 24] Returns ------- int|float """ return self["maxzoom"] @maxzoom.setter def maxzoom(self, val): self["maxzoom"] = val # minzoom # ------- @property def minzoom(self): """ Sets the minimum zoom level (mapbox.layer.minzoom). At zoom levels less than the minzoom, the layer will be hidden. The 'minzoom' property is a number and may be specified as: - An int or float in the interval [0, 24] Returns ------- int|float """ return self["minzoom"] @minzoom.setter def minzoom(self, val): self["minzoom"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the layer. If `type` is "circle", opacity corresponds to the circle opacity (mapbox.layer.paint.circle- opacity) If `type` is "line", opacity corresponds to the line opacity (mapbox.layer.paint.line-opacity) If `type` is "fill", opacity corresponds to the fill opacity (mapbox.layer.paint.fill-opacity) If `type` is "symbol", opacity corresponds to the icon/text opacity (mapbox.layer.paint.text-opacity) The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # source # ------ @property def source(self): """ Sets the source data for this layer (mapbox.layer.source). When `sourcetype` is set to "geojson", `source` can be a URL to a GeoJSON or a GeoJSON object. When `sourcetype` is set to "vector" or "raster", `source` can be a URL or an array of tile URLs. When `sourcetype` is set to "image", `source` can be a URL to an image. The 'source' property accepts values of any type Returns ------- Any """ return self["source"] @source.setter def source(self, val): self["source"] = val # sourceattribution # ----------------- @property def sourceattribution(self): """ Sets the attribution for this source. The 'sourceattribution' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["sourceattribution"] @sourceattribution.setter def sourceattribution(self, val): self["sourceattribution"] = val # sourcelayer # ----------- @property def sourcelayer(self): """ Specifies the layer to use from a vector tile source (mapbox.layer.source-layer). Required for "vector" source type that supports multiple layers. The 'sourcelayer' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["sourcelayer"] @sourcelayer.setter def sourcelayer(self, val): self["sourcelayer"] = val # sourcetype # ---------- @property def sourcetype(self): """ Sets the source type for this layer, that is the type of the layer data. The 'sourcetype' property is an enumeration that may be specified as: - One of the following enumeration values: ['geojson', 'vector', 'raster', 'image'] Returns ------- Any """ return self["sourcetype"] @sourcetype.setter def sourcetype(self, val): self["sourcetype"] = val # symbol # ------ @property def symbol(self): """ The 'symbol' property is an instance of Symbol that may be specified as: - An instance of plotly.graph_objs.layout.mapbox.layer.Symbol - A dict of string/value properties that will be passed to the Symbol constructor Supported dict properties: icon Sets the symbol icon image (mapbox.layer.layout.icon-image). Full list: https://www.mapbox.com/maki-icons/ iconsize Sets the symbol icon size (mapbox.layer.layout.icon-size). Has an effect only when `type` is set to "symbol". placement Sets the symbol and/or text placement (mapbox.layer.layout.symbol-placement). If `placement` is "point", the label is placed where the geometry is located If `placement` is "line", the label is placed along the line of the geometry If `placement` is "line-center", the label is placed on the center of the geometry text Sets the symbol text (mapbox.layer.layout.text- field). textfont Sets the icon text font (color=mapbox.layer.paint.text-color, size=mapbox.layer.layout.text-size). Has an effect only when `type` is set to "symbol". textposition Sets the positions of the `text` elements with respects to the (x,y) coordinates. Returns ------- plotly.graph_objs.layout.mapbox.layer.Symbol """ return self["symbol"] @symbol.setter def symbol(self, val): self["symbol"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # type # ---- @property def type(self): """ Sets the layer type, that is the how the layer data set in `source` will be rendered With `sourcetype` set to "geojson", the following values are allowed: "circle", "line", "fill" and "symbol". but note that "line" and "fill" are not compatible with Point GeoJSON geometries. With `sourcetype` set to "vector", the following values are allowed: "circle", "line", "fill" and "symbol". With `sourcetype` set to "raster" or `*image*`, only the "raster" value is allowed. The 'type' property is an enumeration that may be specified as: - One of the following enumeration values: ['circle', 'line', 'fill', 'symbol', 'raster'] Returns ------- Any """ return self["type"] @type.setter def type(self, val): self["type"] = val # visible # ------- @property def visible(self): """ Determines whether this layer is displayed The 'visible' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.mapbox" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ below Determines if the layer will be inserted before the layer with the specified ID. If omitted or set to '', the layer will be inserted above every existing layer. circle plotly.graph_objects.layout.mapbox.layer.Circle instance or dict with compatible properties color Sets the primary layer color. If `type` is "circle", color corresponds to the circle color (mapbox.layer.paint.circle-color) If `type` is "line", color corresponds to the line color (mapbox.layer.paint.line-color) If `type` is "fill", color corresponds to the fill color (mapbox.layer.paint.fill-color) If `type` is "symbol", color corresponds to the icon color (mapbox.layer.paint.icon-color) coordinates Sets the coordinates array contains [longitude, latitude] pairs for the image corners listed in clockwise order: top left, top right, bottom right, bottom left. Only has an effect for "image" `sourcetype`. fill plotly.graph_objects.layout.mapbox.layer.Fill instance or dict with compatible properties line plotly.graph_objects.layout.mapbox.layer.Line instance or dict with compatible properties maxzoom Sets the maximum zoom level (mapbox.layer.maxzoom). At zoom levels equal to or greater than the maxzoom, the layer will be hidden. minzoom Sets the minimum zoom level (mapbox.layer.minzoom). At zoom levels less than the minzoom, the layer will be hidden. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. opacity Sets the opacity of the layer. If `type` is "circle", opacity corresponds to the circle opacity (mapbox.layer.paint.circle-opacity) If `type` is "line", opacity corresponds to the line opacity (mapbox.layer.paint.line-opacity) If `type` is "fill", opacity corresponds to the fill opacity (mapbox.layer.paint.fill-opacity) If `type` is "symbol", opacity corresponds to the icon/text opacity (mapbox.layer.paint.text-opacity) source Sets the source data for this layer (mapbox.layer.source). When `sourcetype` is set to "geojson", `source` can be a URL to a GeoJSON or a GeoJSON object. When `sourcetype` is set to "vector" or "raster", `source` can be a URL or an array of tile URLs. When `sourcetype` is set to "image", `source` can be a URL to an image. sourceattribution Sets the attribution for this source. sourcelayer Specifies the layer to use from a vector tile source (mapbox.layer.source-layer). Required for "vector" source type that supports multiple layers. sourcetype Sets the source type for this layer, that is the type of the layer data. symbol plotly.graph_objects.layout.mapbox.layer.Symbol instance or dict with compatible properties templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. type Sets the layer type, that is the how the layer data set in `source` will be rendered With `sourcetype` set to "geojson", the following values are allowed: "circle", "line", "fill" and "symbol". but note that "line" and "fill" are not compatible with Point GeoJSON geometries. With `sourcetype` set to "vector", the following values are allowed: "circle", "line", "fill" and "symbol". With `sourcetype` set to "raster" or `*image*`, only the "raster" value is allowed. visible Determines whether this layer is displayed """ def __init__( self, arg=None, below=None, circle=None, color=None, coordinates=None, fill=None, line=None, maxzoom=None, minzoom=None, name=None, opacity=None, source=None, sourceattribution=None, sourcelayer=None, sourcetype=None, symbol=None, templateitemname=None, type=None, visible=None, **kwargs ): """ Construct a new Layer object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.mapbox.Layer below Determines if the layer will be inserted before the layer with the specified ID. If omitted or set to '', the layer will be inserted above every existing layer. circle plotly.graph_objects.layout.mapbox.layer.Circle instance or dict with compatible properties color Sets the primary layer color. If `type` is "circle", color corresponds to the circle color (mapbox.layer.paint.circle-color) If `type` is "line", color corresponds to the line color (mapbox.layer.paint.line-color) If `type` is "fill", color corresponds to the fill color (mapbox.layer.paint.fill-color) If `type` is "symbol", color corresponds to the icon color (mapbox.layer.paint.icon-color) coordinates Sets the coordinates array contains [longitude, latitude] pairs for the image corners listed in clockwise order: top left, top right, bottom right, bottom left. Only has an effect for "image" `sourcetype`. fill plotly.graph_objects.layout.mapbox.layer.Fill instance or dict with compatible properties line plotly.graph_objects.layout.mapbox.layer.Line instance or dict with compatible properties maxzoom Sets the maximum zoom level (mapbox.layer.maxzoom). At zoom levels equal to or greater than the maxzoom, the layer will be hidden. minzoom Sets the minimum zoom level (mapbox.layer.minzoom). At zoom levels less than the minzoom, the layer will be hidden. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. opacity Sets the opacity of the layer. If `type` is "circle", opacity corresponds to the circle opacity (mapbox.layer.paint.circle-opacity) If `type` is "line", opacity corresponds to the line opacity (mapbox.layer.paint.line-opacity) If `type` is "fill", opacity corresponds to the fill opacity (mapbox.layer.paint.fill-opacity) If `type` is "symbol", opacity corresponds to the icon/text opacity (mapbox.layer.paint.text-opacity) source Sets the source data for this layer (mapbox.layer.source). When `sourcetype` is set to "geojson", `source` can be a URL to a GeoJSON or a GeoJSON object. When `sourcetype` is set to "vector" or "raster", `source` can be a URL or an array of tile URLs. When `sourcetype` is set to "image", `source` can be a URL to an image. sourceattribution Sets the attribution for this source. sourcelayer Specifies the layer to use from a vector tile source (mapbox.layer.source-layer). Required for "vector" source type that supports multiple layers. sourcetype Sets the source type for this layer, that is the type of the layer data. symbol plotly.graph_objects.layout.mapbox.layer.Symbol instance or dict with compatible properties templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. type Sets the layer type, that is the how the layer data set in `source` will be rendered With `sourcetype` set to "geojson", the following values are allowed: "circle", "line", "fill" and "symbol". but note that "line" and "fill" are not compatible with Point GeoJSON geometries. With `sourcetype` set to "vector", the following values are allowed: "circle", "line", "fill" and "symbol". With `sourcetype` set to "raster" or `*image*`, only the "raster" value is allowed. visible Determines whether this layer is displayed Returns ------- Layer """ super(Layer, self).__init__("layers") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.mapbox.Layer constructor must be a dict or an instance of plotly.graph_objs.layout.mapbox.Layer""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.mapbox import layer as v_layer # Initialize validators # --------------------- self._validators["below"] = v_layer.BelowValidator() self._validators["circle"] = v_layer.CircleValidator() self._validators["color"] = v_layer.ColorValidator() self._validators["coordinates"] = v_layer.CoordinatesValidator() self._validators["fill"] = v_layer.FillValidator() self._validators["line"] = v_layer.LineValidator() self._validators["maxzoom"] = v_layer.MaxzoomValidator() self._validators["minzoom"] = v_layer.MinzoomValidator() self._validators["name"] = v_layer.NameValidator() self._validators["opacity"] = v_layer.OpacityValidator() self._validators["source"] = v_layer.SourceValidator() self._validators["sourceattribution"] = v_layer.SourceattributionValidator() self._validators["sourcelayer"] = v_layer.SourcelayerValidator() self._validators["sourcetype"] = v_layer.SourcetypeValidator() self._validators["symbol"] = v_layer.SymbolValidator() self._validators["templateitemname"] = v_layer.TemplateitemnameValidator() self._validators["type"] = v_layer.TypeValidator() self._validators["visible"] = v_layer.VisibleValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("below", None) self["below"] = below if below is not None else _v _v = arg.pop("circle", None) self["circle"] = circle if circle is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("coordinates", None) self["coordinates"] = coordinates if coordinates is not None else _v _v = arg.pop("fill", None) self["fill"] = fill if fill is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v _v = arg.pop("maxzoom", None) self["maxzoom"] = maxzoom if maxzoom is not None else _v _v = arg.pop("minzoom", None) self["minzoom"] = minzoom if minzoom is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("source", None) self["source"] = source if source is not None else _v _v = arg.pop("sourceattribution", None) self["sourceattribution"] = ( sourceattribution if sourceattribution is not None else _v ) _v = arg.pop("sourcelayer", None) self["sourcelayer"] = sourcelayer if sourcelayer is not None else _v _v = arg.pop("sourcetype", None) self["sourcetype"] = sourcetype if sourcetype is not None else _v _v = arg.pop("symbol", None) self["symbol"] = symbol if symbol is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("type", None) self["type"] = type if type is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Domain(_BaseLayoutHierarchyType): # column # ------ @property def column(self): """ If there is a layout grid, use the domain for this column in the grid for this mapbox subplot . The 'column' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["column"] @column.setter def column(self, val): self["column"] = val # row # --- @property def row(self): """ If there is a layout grid, use the domain for this row in the grid for this mapbox subplot . The 'row' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["row"] @row.setter def row(self, val): self["row"] = val # x # - @property def x(self): """ Sets the horizontal domain of this mapbox subplot (in plot fraction). The 'x' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'x[0]' property is a number and may be specified as: - An int or float in the interval [0, 1] (1) The 'x[1]' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- list """ return self["x"] @x.setter def x(self, val): self["x"] = val # y # - @property def y(self): """ Sets the vertical domain of this mapbox subplot (in plot fraction). The 'y' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'y[0]' property is a number and may be specified as: - An int or float in the interval [0, 1] (1) The 'y[1]' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- list """ return self["y"] @y.setter def y(self, val): self["y"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.mapbox" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ column If there is a layout grid, use the domain for this column in the grid for this mapbox subplot . row If there is a layout grid, use the domain for this row in the grid for this mapbox subplot . x Sets the horizontal domain of this mapbox subplot (in plot fraction). y Sets the vertical domain of this mapbox subplot (in plot fraction). """ def __init__(self, arg=None, column=None, row=None, x=None, y=None, **kwargs): """ Construct a new Domain object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.mapbox.Domain column If there is a layout grid, use the domain for this column in the grid for this mapbox subplot . row If there is a layout grid, use the domain for this row in the grid for this mapbox subplot . x Sets the horizontal domain of this mapbox subplot (in plot fraction). y Sets the vertical domain of this mapbox subplot (in plot fraction). Returns ------- Domain """ super(Domain, self).__init__("domain") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.mapbox.Domain constructor must be a dict or an instance of plotly.graph_objs.layout.mapbox.Domain""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.mapbox import domain as v_domain # Initialize validators # --------------------- self._validators["column"] = v_domain.ColumnValidator() self._validators["row"] = v_domain.RowValidator() self._validators["x"] = v_domain.XValidator() self._validators["y"] = v_domain.YValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("column", None) self["column"] = column if column is not None else _v _v = arg.pop("row", None) self["row"] = row if row is not None else _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Center(_BaseLayoutHierarchyType): # lat # --- @property def lat(self): """ Sets the latitude of the center of the map (in degrees North). The 'lat' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["lat"] @lat.setter def lat(self, val): self["lat"] = val # lon # --- @property def lon(self): """ Sets the longitude of the center of the map (in degrees East). The 'lon' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["lon"] @lon.setter def lon(self, val): self["lon"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.mapbox" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ lat Sets the latitude of the center of the map (in degrees North). lon Sets the longitude of the center of the map (in degrees East). """ def __init__(self, arg=None, lat=None, lon=None, **kwargs): """ Construct a new Center object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.mapbox.Center lat Sets the latitude of the center of the map (in degrees North). lon Sets the longitude of the center of the map (in degrees East). Returns ------- Center """ super(Center, self).__init__("center") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.mapbox.Center constructor must be a dict or an instance of plotly.graph_objs.layout.mapbox.Center""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.mapbox import center as v_center # Initialize validators # --------------------- self._validators["lat"] = v_center.LatValidator() self._validators["lon"] = v_center.LonValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("lat", None) self["lat"] = lat if lat is not None else _v _v = arg.pop("lon", None) self["lon"] = lon if lon is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Center", "Domain", "Layer", "Layer", "layer"] from plotly.graph_objs.layout.mapbox import layer plotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/coloraxis/0000755000175000017500000000000013573746613023251 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/coloraxis/colorbar/0000755000175000017500000000000013573746613025054 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/coloraxis/colorbar/title/0000755000175000017500000000000013573746613026175 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/coloraxis/colorbar/title/__init__.py0000644000175000017500000002060513573721547030310 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Font(_BaseLayoutHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.coloraxis.colorbar.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.coloraxis.colorbar.title.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.coloraxis.colorbar.title.Font constructor must be a dict or an instance of plotly.graph_objs.layout.coloraxis.colorbar.title.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.coloraxis.colorbar.title import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/coloraxis/colorbar/__init__.py0000644000175000017500000006103213573721547027166 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Title(_BaseLayoutHierarchyType): # font # ---- @property def font(self): """ Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.layout.coloraxis.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.layout.coloraxis.colorbar.title.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # side # ---- @property def side(self): """ Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- Any """ return self["side"] @side.setter def side(self, val): self["side"] = val # text # ---- @property def text(self): """ Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.coloraxis.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """ def __init__(self, arg=None, font=None, side=None, text=None, **kwargs): """ Construct a new Title object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.coloraxis.colorbar.Title font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- Title """ super(Title, self).__init__("title") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.coloraxis.colorbar.Title constructor must be a dict or an instance of plotly.graph_objs.layout.coloraxis.colorbar.Title""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.coloraxis.colorbar import title as v_title # Initialize validators # --------------------- self._validators["font"] = v_title.FontValidator() self._validators["side"] = v_title.SideValidator() self._validators["text"] = v_title.TextValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("side", None) self["side"] = side if side is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Tickformatstop(_BaseLayoutHierarchyType): # dtickrange # ---------- @property def dtickrange(self): """ range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" The 'dtickrange' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'dtickrange[0]' property accepts values of any type (1) The 'dtickrange[1]' property accepts values of any type Returns ------- list """ return self["dtickrange"] @dtickrange.setter def dtickrange(self, val): self["dtickrange"] = val # enabled # ------- @property def enabled(self): """ Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. The 'enabled' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["enabled"] @enabled.setter def enabled(self, val): self["enabled"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # value # ----- @property def value(self): """ string - dtickformat for described zoom level, the same as "tickformat" The 'value' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.coloraxis.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """ def __init__( self, arg=None, dtickrange=None, enabled=None, name=None, templateitemname=None, value=None, **kwargs ): """ Construct a new Tickformatstop object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.coloraxis.color bar.Tickformatstop dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- Tickformatstop """ super(Tickformatstop, self).__init__("tickformatstops") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.coloraxis.colorbar.Tickformatstop constructor must be a dict or an instance of plotly.graph_objs.layout.coloraxis.colorbar.Tickformatstop""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.coloraxis.colorbar import ( tickformatstop as v_tickformatstop, ) # Initialize validators # --------------------- self._validators["dtickrange"] = v_tickformatstop.DtickrangeValidator() self._validators["enabled"] = v_tickformatstop.EnabledValidator() self._validators["name"] = v_tickformatstop.NameValidator() self._validators[ "templateitemname" ] = v_tickformatstop.TemplateitemnameValidator() self._validators["value"] = v_tickformatstop.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtickrange", None) self["dtickrange"] = dtickrange if dtickrange is not None else _v _v = arg.pop("enabled", None) self["enabled"] = enabled if enabled is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Tickfont(_BaseLayoutHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.coloraxis.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Tickfont object Sets the color bar's tick label font Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.coloraxis.colorbar.Tickfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Tickfont """ super(Tickfont, self).__init__("tickfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.coloraxis.colorbar.Tickfont constructor must be a dict or an instance of plotly.graph_objs.layout.coloraxis.colorbar.Tickfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.coloraxis.colorbar import tickfont as v_tickfont # Initialize validators # --------------------- self._validators["color"] = v_tickfont.ColorValidator() self._validators["family"] = v_tickfont.FamilyValidator() self._validators["size"] = v_tickfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Tickfont", "Tickformatstop", "Tickformatstop", "Title", "title"] from plotly.graph_objs.layout.coloraxis.colorbar import title plotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/coloraxis/__init__.py0000644000175000017500000021013113573721550025351 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class ColorBar(_BaseLayoutHierarchyType): # bgcolor # ------- @property def bgcolor(self): """ Sets the color of padded area. The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the axis line color. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # borderwidth # ----------- @property def borderwidth(self): """ Sets the width (in px) or the border enclosing this color bar. The 'borderwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["borderwidth"] @borderwidth.setter def borderwidth(self, val): self["borderwidth"] = val # dtick # ----- @property def dtick(self): """ Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" The 'dtick' property accepts values of any type Returns ------- Any """ return self["dtick"] @dtick.setter def dtick(self, val): self["dtick"] = val # exponentformat # -------------- @property def exponentformat(self): """ Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. The 'exponentformat' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'e', 'E', 'power', 'SI', 'B'] Returns ------- Any """ return self["exponentformat"] @exponentformat.setter def exponentformat(self, val): self["exponentformat"] = val # len # --- @property def len(self): """ Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. The 'len' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["len"] @len.setter def len(self, val): self["len"] = val # lenmode # ------- @property def lenmode(self): """ Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. The 'lenmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["lenmode"] @lenmode.setter def lenmode(self, val): self["lenmode"] = val # nticks # ------ @property def nticks(self): """ Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". The 'nticks' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nticks"] @nticks.setter def nticks(self, val): self["nticks"] = val # outlinecolor # ------------ @property def outlinecolor(self): """ Sets the axis line color. The 'outlinecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["outlinecolor"] @outlinecolor.setter def outlinecolor(self, val): self["outlinecolor"] = val # outlinewidth # ------------ @property def outlinewidth(self): """ Sets the width (in px) of the axis line. The 'outlinewidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["outlinewidth"] @outlinewidth.setter def outlinewidth(self, val): self["outlinewidth"] = val # separatethousands # ----------------- @property def separatethousands(self): """ If "true", even 4-digit integers are separated The 'separatethousands' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["separatethousands"] @separatethousands.setter def separatethousands(self, val): self["separatethousands"] = val # showexponent # ------------ @property def showexponent(self): """ If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. The 'showexponent' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showexponent"] @showexponent.setter def showexponent(self, val): self["showexponent"] = val # showticklabels # -------------- @property def showticklabels(self): """ Determines whether or not the tick labels are drawn. The 'showticklabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showticklabels"] @showticklabels.setter def showticklabels(self, val): self["showticklabels"] = val # showtickprefix # -------------- @property def showtickprefix(self): """ If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. The 'showtickprefix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showtickprefix"] @showtickprefix.setter def showtickprefix(self, val): self["showtickprefix"] = val # showticksuffix # -------------- @property def showticksuffix(self): """ Same as `showtickprefix` but for tick suffixes. The 'showticksuffix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showticksuffix"] @showticksuffix.setter def showticksuffix(self, val): self["showticksuffix"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # thicknessmode # ------------- @property def thicknessmode(self): """ Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. The 'thicknessmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["thicknessmode"] @thicknessmode.setter def thicknessmode(self, val): self["thicknessmode"] = val # tick0 # ----- @property def tick0(self): """ Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. The 'tick0' property accepts values of any type Returns ------- Any """ return self["tick0"] @tick0.setter def tick0(self, val): self["tick0"] = val # tickangle # --------- @property def tickangle(self): """ Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. The 'tickangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["tickangle"] @tickangle.setter def tickangle(self, val): self["tickangle"] = val # tickcolor # --------- @property def tickcolor(self): """ Sets the tick color. The 'tickcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["tickcolor"] @tickcolor.setter def tickcolor(self, val): self["tickcolor"] = val # tickfont # -------- @property def tickfont(self): """ Sets the color bar's tick label font The 'tickfont' property is an instance of Tickfont that may be specified as: - An instance of plotly.graph_objs.layout.coloraxis.colorbar.Tickfont - A dict of string/value properties that will be passed to the Tickfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.layout.coloraxis.colorbar.Tickfont """ return self["tickfont"] @tickfont.setter def tickfont(self, val): self["tickfont"] = val # tickformat # ---------- @property def tickformat(self): """ Sets the tick label formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'tickformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickformat"] @tickformat.setter def tickformat(self, val): self["tickformat"] = val # tickformatstops # --------------- @property def tickformatstops(self): """ The 'tickformatstops' property is a tuple of instances of Tickformatstop that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.coloraxis.colorbar.Tickformatstop - A list or tuple of dicts of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- tuple[plotly.graph_objs.layout.coloraxis.colorbar.Tickformatstop] """ return self["tickformatstops"] @tickformatstops.setter def tickformatstops(self, val): self["tickformatstops"] = val # tickformatstopdefaults # ---------------------- @property def tickformatstopdefaults(self): """ When used in a template (as layout.template.layout.coloraxis.co lorbar.tickformatstopdefaults), sets the default property values to use for elements of layout.coloraxis.colorbar.tickformatstops The 'tickformatstopdefaults' property is an instance of Tickformatstop that may be specified as: - An instance of plotly.graph_objs.layout.coloraxis.colorbar.Tickformatstop - A dict of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: Returns ------- plotly.graph_objs.layout.coloraxis.colorbar.Tickformatstop """ return self["tickformatstopdefaults"] @tickformatstopdefaults.setter def tickformatstopdefaults(self, val): self["tickformatstopdefaults"] = val # ticklen # ------- @property def ticklen(self): """ Sets the tick length (in px). The 'ticklen' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ticklen"] @ticklen.setter def ticklen(self, val): self["ticklen"] = val # tickmode # -------- @property def tickmode(self): """ Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). The 'tickmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'linear', 'array'] Returns ------- Any """ return self["tickmode"] @tickmode.setter def tickmode(self, val): self["tickmode"] = val # tickprefix # ---------- @property def tickprefix(self): """ Sets a tick label prefix. The 'tickprefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickprefix"] @tickprefix.setter def tickprefix(self, val): self["tickprefix"] = val # ticks # ----- @property def ticks(self): """ Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. The 'ticks' property is an enumeration that may be specified as: - One of the following enumeration values: ['outside', 'inside', ''] Returns ------- Any """ return self["ticks"] @ticks.setter def ticks(self, val): self["ticks"] = val # ticksuffix # ---------- @property def ticksuffix(self): """ Sets a tick label suffix. The 'ticksuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ticksuffix"] @ticksuffix.setter def ticksuffix(self, val): self["ticksuffix"] = val # ticktext # -------- @property def ticktext(self): """ Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. The 'ticktext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ticktext"] @ticktext.setter def ticktext(self, val): self["ticktext"] = val # ticktextsrc # ----------- @property def ticktextsrc(self): """ Sets the source reference on plot.ly for ticktext . The 'ticktextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ticktextsrc"] @ticktextsrc.setter def ticktextsrc(self, val): self["ticktextsrc"] = val # tickvals # -------- @property def tickvals(self): """ Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. The 'tickvals' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["tickvals"] @tickvals.setter def tickvals(self, val): self["tickvals"] = val # tickvalssrc # ----------- @property def tickvalssrc(self): """ Sets the source reference on plot.ly for tickvals . The 'tickvalssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tickvalssrc"] @tickvalssrc.setter def tickvalssrc(self, val): self["tickvalssrc"] = val # tickwidth # --------- @property def tickwidth(self): """ Sets the tick width (in px). The 'tickwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["tickwidth"] @tickwidth.setter def tickwidth(self, val): self["tickwidth"] = val # title # ----- @property def title(self): """ The 'title' property is an instance of Title that may be specified as: - An instance of plotly.graph_objs.layout.coloraxis.colorbar.Title - A dict of string/value properties that will be passed to the Title constructor Supported dict properties: font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- plotly.graph_objs.layout.coloraxis.colorbar.Title """ return self["title"] @title.setter def title(self, val): self["title"] = val # titlefont # --------- @property def titlefont(self): """ Deprecated: Please use layout.coloraxis.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.layout.coloraxis.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- """ return self["titlefont"] @titlefont.setter def titlefont(self, val): self["titlefont"] = val # titleside # --------- @property def titleside(self): """ Deprecated: Please use layout.coloraxis.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- """ return self["titleside"] @titleside.setter def titleside(self, val): self["titleside"] = val # x # - @property def x(self): """ Sets the x position of the color bar (in plot fraction). The 'x' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["x"] @x.setter def x(self, val): self["x"] = val # xanchor # ------- @property def xanchor(self): """ Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. The 'xanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'center', 'right'] Returns ------- Any """ return self["xanchor"] @xanchor.setter def xanchor(self, val): self["xanchor"] = val # xpad # ---- @property def xpad(self): """ Sets the amount of padding (in px) along the x direction. The 'xpad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["xpad"] @xpad.setter def xpad(self, val): self["xpad"] = val # y # - @property def y(self): """ Sets the y position of the color bar (in plot fraction). The 'y' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["y"] @y.setter def y(self, val): self["y"] = val # yanchor # ------- @property def yanchor(self): """ Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. The 'yanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['top', 'middle', 'bottom'] Returns ------- Any """ return self["yanchor"] @yanchor.setter def yanchor(self, val): self["yanchor"] = val # ypad # ---- @property def ypad(self): """ Sets the amount of padding (in px) along the y direction. The 'ypad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ypad"] @ypad.setter def ypad(self, val): self["ypad"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.coloraxis" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.layout.coloraxis.colorb ar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.layout.colo raxis.colorbar.tickformatstopdefaults), sets the default property values to use for elements of layout.coloraxis.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.layout.coloraxis.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use layout.coloraxis.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use layout.coloraxis.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """ _mapped_properties = { "titlefont": ("title", "font"), "titleside": ("title", "side"), } def __init__( self, arg=None, bgcolor=None, bordercolor=None, borderwidth=None, dtick=None, exponentformat=None, len=None, lenmode=None, nticks=None, outlinecolor=None, outlinewidth=None, separatethousands=None, showexponent=None, showticklabels=None, showtickprefix=None, showticksuffix=None, thickness=None, thicknessmode=None, tick0=None, tickangle=None, tickcolor=None, tickfont=None, tickformat=None, tickformatstops=None, tickformatstopdefaults=None, ticklen=None, tickmode=None, tickprefix=None, ticks=None, ticksuffix=None, ticktext=None, ticktextsrc=None, tickvals=None, tickvalssrc=None, tickwidth=None, title=None, titlefont=None, titleside=None, x=None, xanchor=None, xpad=None, y=None, yanchor=None, ypad=None, **kwargs ): """ Construct a new ColorBar object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.coloraxis.ColorBar bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.layout.coloraxis.colorb ar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.layout.colo raxis.colorbar.tickformatstopdefaults), sets the default property values to use for elements of layout.coloraxis.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.layout.coloraxis.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use layout.coloraxis.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use layout.coloraxis.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- ColorBar """ super(ColorBar, self).__init__("colorbar") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.coloraxis.ColorBar constructor must be a dict or an instance of plotly.graph_objs.layout.coloraxis.ColorBar""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.coloraxis import colorbar as v_colorbar # Initialize validators # --------------------- self._validators["bgcolor"] = v_colorbar.BgcolorValidator() self._validators["bordercolor"] = v_colorbar.BordercolorValidator() self._validators["borderwidth"] = v_colorbar.BorderwidthValidator() self._validators["dtick"] = v_colorbar.DtickValidator() self._validators["exponentformat"] = v_colorbar.ExponentformatValidator() self._validators["len"] = v_colorbar.LenValidator() self._validators["lenmode"] = v_colorbar.LenmodeValidator() self._validators["nticks"] = v_colorbar.NticksValidator() self._validators["outlinecolor"] = v_colorbar.OutlinecolorValidator() self._validators["outlinewidth"] = v_colorbar.OutlinewidthValidator() self._validators["separatethousands"] = v_colorbar.SeparatethousandsValidator() self._validators["showexponent"] = v_colorbar.ShowexponentValidator() self._validators["showticklabels"] = v_colorbar.ShowticklabelsValidator() self._validators["showtickprefix"] = v_colorbar.ShowtickprefixValidator() self._validators["showticksuffix"] = v_colorbar.ShowticksuffixValidator() self._validators["thickness"] = v_colorbar.ThicknessValidator() self._validators["thicknessmode"] = v_colorbar.ThicknessmodeValidator() self._validators["tick0"] = v_colorbar.Tick0Validator() self._validators["tickangle"] = v_colorbar.TickangleValidator() self._validators["tickcolor"] = v_colorbar.TickcolorValidator() self._validators["tickfont"] = v_colorbar.TickfontValidator() self._validators["tickformat"] = v_colorbar.TickformatValidator() self._validators["tickformatstops"] = v_colorbar.TickformatstopsValidator() self._validators[ "tickformatstopdefaults" ] = v_colorbar.TickformatstopValidator() self._validators["ticklen"] = v_colorbar.TicklenValidator() self._validators["tickmode"] = v_colorbar.TickmodeValidator() self._validators["tickprefix"] = v_colorbar.TickprefixValidator() self._validators["ticks"] = v_colorbar.TicksValidator() self._validators["ticksuffix"] = v_colorbar.TicksuffixValidator() self._validators["ticktext"] = v_colorbar.TicktextValidator() self._validators["ticktextsrc"] = v_colorbar.TicktextsrcValidator() self._validators["tickvals"] = v_colorbar.TickvalsValidator() self._validators["tickvalssrc"] = v_colorbar.TickvalssrcValidator() self._validators["tickwidth"] = v_colorbar.TickwidthValidator() self._validators["title"] = v_colorbar.TitleValidator() self._validators["x"] = v_colorbar.XValidator() self._validators["xanchor"] = v_colorbar.XanchorValidator() self._validators["xpad"] = v_colorbar.XpadValidator() self._validators["y"] = v_colorbar.YValidator() self._validators["yanchor"] = v_colorbar.YanchorValidator() self._validators["ypad"] = v_colorbar.YpadValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("borderwidth", None) self["borderwidth"] = borderwidth if borderwidth is not None else _v _v = arg.pop("dtick", None) self["dtick"] = dtick if dtick is not None else _v _v = arg.pop("exponentformat", None) self["exponentformat"] = exponentformat if exponentformat is not None else _v _v = arg.pop("len", None) self["len"] = len if len is not None else _v _v = arg.pop("lenmode", None) self["lenmode"] = lenmode if lenmode is not None else _v _v = arg.pop("nticks", None) self["nticks"] = nticks if nticks is not None else _v _v = arg.pop("outlinecolor", None) self["outlinecolor"] = outlinecolor if outlinecolor is not None else _v _v = arg.pop("outlinewidth", None) self["outlinewidth"] = outlinewidth if outlinewidth is not None else _v _v = arg.pop("separatethousands", None) self["separatethousands"] = ( separatethousands if separatethousands is not None else _v ) _v = arg.pop("showexponent", None) self["showexponent"] = showexponent if showexponent is not None else _v _v = arg.pop("showticklabels", None) self["showticklabels"] = showticklabels if showticklabels is not None else _v _v = arg.pop("showtickprefix", None) self["showtickprefix"] = showtickprefix if showtickprefix is not None else _v _v = arg.pop("showticksuffix", None) self["showticksuffix"] = showticksuffix if showticksuffix is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("thicknessmode", None) self["thicknessmode"] = thicknessmode if thicknessmode is not None else _v _v = arg.pop("tick0", None) self["tick0"] = tick0 if tick0 is not None else _v _v = arg.pop("tickangle", None) self["tickangle"] = tickangle if tickangle is not None else _v _v = arg.pop("tickcolor", None) self["tickcolor"] = tickcolor if tickcolor is not None else _v _v = arg.pop("tickfont", None) self["tickfont"] = tickfont if tickfont is not None else _v _v = arg.pop("tickformat", None) self["tickformat"] = tickformat if tickformat is not None else _v _v = arg.pop("tickformatstops", None) self["tickformatstops"] = tickformatstops if tickformatstops is not None else _v _v = arg.pop("tickformatstopdefaults", None) self["tickformatstopdefaults"] = ( tickformatstopdefaults if tickformatstopdefaults is not None else _v ) _v = arg.pop("ticklen", None) self["ticklen"] = ticklen if ticklen is not None else _v _v = arg.pop("tickmode", None) self["tickmode"] = tickmode if tickmode is not None else _v _v = arg.pop("tickprefix", None) self["tickprefix"] = tickprefix if tickprefix is not None else _v _v = arg.pop("ticks", None) self["ticks"] = ticks if ticks is not None else _v _v = arg.pop("ticksuffix", None) self["ticksuffix"] = ticksuffix if ticksuffix is not None else _v _v = arg.pop("ticktext", None) self["ticktext"] = ticktext if ticktext is not None else _v _v = arg.pop("ticktextsrc", None) self["ticktextsrc"] = ticktextsrc if ticktextsrc is not None else _v _v = arg.pop("tickvals", None) self["tickvals"] = tickvals if tickvals is not None else _v _v = arg.pop("tickvalssrc", None) self["tickvalssrc"] = tickvalssrc if tickvalssrc is not None else _v _v = arg.pop("tickwidth", None) self["tickwidth"] = tickwidth if tickwidth is not None else _v _v = arg.pop("title", None) self["title"] = title if title is not None else _v _v = arg.pop("titlefont", None) _v = titlefont if titlefont is not None else _v if _v is not None: self["titlefont"] = _v _v = arg.pop("titleside", None) _v = titleside if titleside is not None else _v if _v is not None: self["titleside"] = _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xanchor", None) self["xanchor"] = xanchor if xanchor is not None else _v _v = arg.pop("xpad", None) self["xpad"] = xpad if xpad is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("yanchor", None) self["yanchor"] = yanchor if yanchor is not None else _v _v = arg.pop("ypad", None) self["ypad"] = ypad if ypad is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["ColorBar", "colorbar"] from plotly.graph_objs.layout.coloraxis import colorbar plotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/yaxis/0000755000175000017500000000000013573746613022403 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/yaxis/title/0000755000175000017500000000000013573746613023524 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/yaxis/title/__init__.py0000644000175000017500000002050513573721550025630 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Font(_BaseLayoutHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.yaxis.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.yaxis.title.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.yaxis.title.Font constructor must be a dict or an instance of plotly.graph_objs.layout.yaxis.title.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.yaxis.title import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/yaxis/__init__.py0000644000175000017500000006245113573721550024515 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Title(_BaseLayoutHierarchyType): # font # ---- @property def font(self): """ Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.layout.yaxis.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.layout.yaxis.title.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # standoff # -------- @property def standoff(self): """ Sets the standoff distance (in px) between the axis labels and the title text The default value is a function of the axis tick labels, the title `font.size` and the axis `linewidth`. Note that the axis title position is always constrained within the margins, so the actual standoff distance is always less than the set or default value. By setting `standoff` and turning on `automargin`, plotly.js will push the margins to fit the axis title at given standoff distance. The 'standoff' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["standoff"] @standoff.setter def standoff(self, val): self["standoff"] = val # text # ---- @property def text(self): """ Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.yaxis" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. standoff Sets the standoff distance (in px) between the axis labels and the title text The default value is a function of the axis tick labels, the title `font.size` and the axis `linewidth`. Note that the axis title position is always constrained within the margins, so the actual standoff distance is always less than the set or default value. By setting `standoff` and turning on `automargin`, plotly.js will push the margins to fit the axis title at given standoff distance. text Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """ def __init__(self, arg=None, font=None, standoff=None, text=None, **kwargs): """ Construct a new Title object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.yaxis.Title font Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. standoff Sets the standoff distance (in px) between the axis labels and the title text The default value is a function of the axis tick labels, the title `font.size` and the axis `linewidth`. Note that the axis title position is always constrained within the margins, so the actual standoff distance is always less than the set or default value. By setting `standoff` and turning on `automargin`, plotly.js will push the margins to fit the axis title at given standoff distance. text Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- Title """ super(Title, self).__init__("title") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.yaxis.Title constructor must be a dict or an instance of plotly.graph_objs.layout.yaxis.Title""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.yaxis import title as v_title # Initialize validators # --------------------- self._validators["font"] = v_title.FontValidator() self._validators["standoff"] = v_title.StandoffValidator() self._validators["text"] = v_title.TextValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("standoff", None) self["standoff"] = standoff if standoff is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Tickformatstop(_BaseLayoutHierarchyType): # dtickrange # ---------- @property def dtickrange(self): """ range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" The 'dtickrange' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'dtickrange[0]' property accepts values of any type (1) The 'dtickrange[1]' property accepts values of any type Returns ------- list """ return self["dtickrange"] @dtickrange.setter def dtickrange(self, val): self["dtickrange"] = val # enabled # ------- @property def enabled(self): """ Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. The 'enabled' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["enabled"] @enabled.setter def enabled(self, val): self["enabled"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # value # ----- @property def value(self): """ string - dtickformat for described zoom level, the same as "tickformat" The 'value' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.yaxis" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """ def __init__( self, arg=None, dtickrange=None, enabled=None, name=None, templateitemname=None, value=None, **kwargs ): """ Construct a new Tickformatstop object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.yaxis.Tickformatstop dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- Tickformatstop """ super(Tickformatstop, self).__init__("tickformatstops") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.yaxis.Tickformatstop constructor must be a dict or an instance of plotly.graph_objs.layout.yaxis.Tickformatstop""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.yaxis import tickformatstop as v_tickformatstop # Initialize validators # --------------------- self._validators["dtickrange"] = v_tickformatstop.DtickrangeValidator() self._validators["enabled"] = v_tickformatstop.EnabledValidator() self._validators["name"] = v_tickformatstop.NameValidator() self._validators[ "templateitemname" ] = v_tickformatstop.TemplateitemnameValidator() self._validators["value"] = v_tickformatstop.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtickrange", None) self["dtickrange"] = dtickrange if dtickrange is not None else _v _v = arg.pop("enabled", None) self["enabled"] = enabled if enabled is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Tickfont(_BaseLayoutHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.yaxis" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Tickfont object Sets the tick font. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.yaxis.Tickfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Tickfont """ super(Tickfont, self).__init__("tickfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.yaxis.Tickfont constructor must be a dict or an instance of plotly.graph_objs.layout.yaxis.Tickfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.yaxis import tickfont as v_tickfont # Initialize validators # --------------------- self._validators["color"] = v_tickfont.ColorValidator() self._validators["family"] = v_tickfont.FamilyValidator() self._validators["size"] = v_tickfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Tickfont", "Tickformatstop", "Tickformatstop", "Title", "title"] from plotly.graph_objs.layout.yaxis import title plotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/geo/0000755000175000017500000000000013573746613022020 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/geo/projection/0000755000175000017500000000000013573746613024174 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/geo/projection/__init__.py0000644000175000017500000001052113573721547026303 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Rotation(_BaseLayoutHierarchyType): # lat # --- @property def lat(self): """ Rotates the map along meridians (in degrees North). The 'lat' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["lat"] @lat.setter def lat(self, val): self["lat"] = val # lon # --- @property def lon(self): """ Rotates the map along parallels (in degrees East). Defaults to the center of the `lonaxis.range` values. The 'lon' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["lon"] @lon.setter def lon(self, val): self["lon"] = val # roll # ---- @property def roll(self): """ Roll the map (in degrees) For example, a roll of 180 makes the map appear upside down. The 'roll' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["roll"] @roll.setter def roll(self, val): self["roll"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.geo.projection" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ lat Rotates the map along meridians (in degrees North). lon Rotates the map along parallels (in degrees East). Defaults to the center of the `lonaxis.range` values. roll Roll the map (in degrees) For example, a roll of 180 makes the map appear upside down. """ def __init__(self, arg=None, lat=None, lon=None, roll=None, **kwargs): """ Construct a new Rotation object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.geo.projection.Rotation lat Rotates the map along meridians (in degrees North). lon Rotates the map along parallels (in degrees East). Defaults to the center of the `lonaxis.range` values. roll Roll the map (in degrees) For example, a roll of 180 makes the map appear upside down. Returns ------- Rotation """ super(Rotation, self).__init__("rotation") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.geo.projection.Rotation constructor must be a dict or an instance of plotly.graph_objs.layout.geo.projection.Rotation""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.geo.projection import rotation as v_rotation # Initialize validators # --------------------- self._validators["lat"] = v_rotation.LatValidator() self._validators["lon"] = v_rotation.LonValidator() self._validators["roll"] = v_rotation.RollValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("lat", None) self["lat"] = lat if lat is not None else _v _v = arg.pop("lon", None) self["lon"] = lon if lon is not None else _v _v = arg.pop("roll", None) self["roll"] = roll if roll is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Rotation"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/geo/__init__.py0000644000175000017500000011112513573721550024123 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Projection(_BaseLayoutHierarchyType): # parallels # --------- @property def parallels(self): """ For conic projection types only. Sets the parallels (tangent, secant) where the cone intersects the sphere. The 'parallels' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'parallels[0]' property is a number and may be specified as: - An int or float (1) The 'parallels[1]' property is a number and may be specified as: - An int or float Returns ------- list """ return self["parallels"] @parallels.setter def parallels(self, val): self["parallels"] = val # rotation # -------- @property def rotation(self): """ The 'rotation' property is an instance of Rotation that may be specified as: - An instance of plotly.graph_objs.layout.geo.projection.Rotation - A dict of string/value properties that will be passed to the Rotation constructor Supported dict properties: lat Rotates the map along meridians (in degrees North). lon Rotates the map along parallels (in degrees East). Defaults to the center of the `lonaxis.range` values. roll Roll the map (in degrees) For example, a roll of 180 makes the map appear upside down. Returns ------- plotly.graph_objs.layout.geo.projection.Rotation """ return self["rotation"] @rotation.setter def rotation(self, val): self["rotation"] = val # scale # ----- @property def scale(self): """ Zooms in or out on the map view. A scale of 1 corresponds to the largest zoom level that fits the map's lon and lat ranges. The 'scale' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["scale"] @scale.setter def scale(self, val): self["scale"] = val # type # ---- @property def type(self): """ Sets the projection type. The 'type' property is an enumeration that may be specified as: - One of the following enumeration values: ['equirectangular', 'mercator', 'orthographic', 'natural earth', 'kavrayskiy7', 'miller', 'robinson', 'eckert4', 'azimuthal equal area', 'azimuthal equidistant', 'conic equal area', 'conic conformal', 'conic equidistant', 'gnomonic', 'stereographic', 'mollweide', 'hammer', 'transverse mercator', 'albers usa', 'winkel tripel', 'aitoff', 'sinusoidal'] Returns ------- Any """ return self["type"] @type.setter def type(self, val): self["type"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.geo" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ parallels For conic projection types only. Sets the parallels (tangent, secant) where the cone intersects the sphere. rotation plotly.graph_objects.layout.geo.projection.Rotation instance or dict with compatible properties scale Zooms in or out on the map view. A scale of 1 corresponds to the largest zoom level that fits the map's lon and lat ranges. type Sets the projection type. """ def __init__( self, arg=None, parallels=None, rotation=None, scale=None, type=None, **kwargs ): """ Construct a new Projection object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.geo.Projection parallels For conic projection types only. Sets the parallels (tangent, secant) where the cone intersects the sphere. rotation plotly.graph_objects.layout.geo.projection.Rotation instance or dict with compatible properties scale Zooms in or out on the map view. A scale of 1 corresponds to the largest zoom level that fits the map's lon and lat ranges. type Sets the projection type. Returns ------- Projection """ super(Projection, self).__init__("projection") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.geo.Projection constructor must be a dict or an instance of plotly.graph_objs.layout.geo.Projection""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.geo import projection as v_projection # Initialize validators # --------------------- self._validators["parallels"] = v_projection.ParallelsValidator() self._validators["rotation"] = v_projection.RotationValidator() self._validators["scale"] = v_projection.ScaleValidator() self._validators["type"] = v_projection.TypeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("parallels", None) self["parallels"] = parallels if parallels is not None else _v _v = arg.pop("rotation", None) self["rotation"] = rotation if rotation is not None else _v _v = arg.pop("scale", None) self["scale"] = scale if scale is not None else _v _v = arg.pop("type", None) self["type"] = type if type is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Lonaxis(_BaseLayoutHierarchyType): # dtick # ----- @property def dtick(self): """ Sets the graticule's longitude/latitude tick step. The 'dtick' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["dtick"] @dtick.setter def dtick(self, val): self["dtick"] = val # gridcolor # --------- @property def gridcolor(self): """ Sets the graticule's stroke color. The 'gridcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["gridcolor"] @gridcolor.setter def gridcolor(self, val): self["gridcolor"] = val # gridwidth # --------- @property def gridwidth(self): """ Sets the graticule's stroke width (in px). The 'gridwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["gridwidth"] @gridwidth.setter def gridwidth(self, val): self["gridwidth"] = val # range # ----- @property def range(self): """ Sets the range of this axis (in degrees), sets the map's clipped coordinates. The 'range' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'range[0]' property is a number and may be specified as: - An int or float (1) The 'range[1]' property is a number and may be specified as: - An int or float Returns ------- list """ return self["range"] @range.setter def range(self, val): self["range"] = val # showgrid # -------- @property def showgrid(self): """ Sets whether or not graticule are shown on the map. The 'showgrid' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showgrid"] @showgrid.setter def showgrid(self, val): self["showgrid"] = val # tick0 # ----- @property def tick0(self): """ Sets the graticule's starting tick longitude/latitude. The 'tick0' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["tick0"] @tick0.setter def tick0(self, val): self["tick0"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.geo" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtick Sets the graticule's longitude/latitude tick step. gridcolor Sets the graticule's stroke color. gridwidth Sets the graticule's stroke width (in px). range Sets the range of this axis (in degrees), sets the map's clipped coordinates. showgrid Sets whether or not graticule are shown on the map. tick0 Sets the graticule's starting tick longitude/latitude. """ def __init__( self, arg=None, dtick=None, gridcolor=None, gridwidth=None, range=None, showgrid=None, tick0=None, **kwargs ): """ Construct a new Lonaxis object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.geo.Lonaxis dtick Sets the graticule's longitude/latitude tick step. gridcolor Sets the graticule's stroke color. gridwidth Sets the graticule's stroke width (in px). range Sets the range of this axis (in degrees), sets the map's clipped coordinates. showgrid Sets whether or not graticule are shown on the map. tick0 Sets the graticule's starting tick longitude/latitude. Returns ------- Lonaxis """ super(Lonaxis, self).__init__("lonaxis") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.geo.Lonaxis constructor must be a dict or an instance of plotly.graph_objs.layout.geo.Lonaxis""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.geo import lonaxis as v_lonaxis # Initialize validators # --------------------- self._validators["dtick"] = v_lonaxis.DtickValidator() self._validators["gridcolor"] = v_lonaxis.GridcolorValidator() self._validators["gridwidth"] = v_lonaxis.GridwidthValidator() self._validators["range"] = v_lonaxis.RangeValidator() self._validators["showgrid"] = v_lonaxis.ShowgridValidator() self._validators["tick0"] = v_lonaxis.Tick0Validator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtick", None) self["dtick"] = dtick if dtick is not None else _v _v = arg.pop("gridcolor", None) self["gridcolor"] = gridcolor if gridcolor is not None else _v _v = arg.pop("gridwidth", None) self["gridwidth"] = gridwidth if gridwidth is not None else _v _v = arg.pop("range", None) self["range"] = range if range is not None else _v _v = arg.pop("showgrid", None) self["showgrid"] = showgrid if showgrid is not None else _v _v = arg.pop("tick0", None) self["tick0"] = tick0 if tick0 is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Lataxis(_BaseLayoutHierarchyType): # dtick # ----- @property def dtick(self): """ Sets the graticule's longitude/latitude tick step. The 'dtick' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["dtick"] @dtick.setter def dtick(self, val): self["dtick"] = val # gridcolor # --------- @property def gridcolor(self): """ Sets the graticule's stroke color. The 'gridcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["gridcolor"] @gridcolor.setter def gridcolor(self, val): self["gridcolor"] = val # gridwidth # --------- @property def gridwidth(self): """ Sets the graticule's stroke width (in px). The 'gridwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["gridwidth"] @gridwidth.setter def gridwidth(self, val): self["gridwidth"] = val # range # ----- @property def range(self): """ Sets the range of this axis (in degrees), sets the map's clipped coordinates. The 'range' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'range[0]' property is a number and may be specified as: - An int or float (1) The 'range[1]' property is a number and may be specified as: - An int or float Returns ------- list """ return self["range"] @range.setter def range(self, val): self["range"] = val # showgrid # -------- @property def showgrid(self): """ Sets whether or not graticule are shown on the map. The 'showgrid' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showgrid"] @showgrid.setter def showgrid(self, val): self["showgrid"] = val # tick0 # ----- @property def tick0(self): """ Sets the graticule's starting tick longitude/latitude. The 'tick0' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["tick0"] @tick0.setter def tick0(self, val): self["tick0"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.geo" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtick Sets the graticule's longitude/latitude tick step. gridcolor Sets the graticule's stroke color. gridwidth Sets the graticule's stroke width (in px). range Sets the range of this axis (in degrees), sets the map's clipped coordinates. showgrid Sets whether or not graticule are shown on the map. tick0 Sets the graticule's starting tick longitude/latitude. """ def __init__( self, arg=None, dtick=None, gridcolor=None, gridwidth=None, range=None, showgrid=None, tick0=None, **kwargs ): """ Construct a new Lataxis object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.geo.Lataxis dtick Sets the graticule's longitude/latitude tick step. gridcolor Sets the graticule's stroke color. gridwidth Sets the graticule's stroke width (in px). range Sets the range of this axis (in degrees), sets the map's clipped coordinates. showgrid Sets whether or not graticule are shown on the map. tick0 Sets the graticule's starting tick longitude/latitude. Returns ------- Lataxis """ super(Lataxis, self).__init__("lataxis") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.geo.Lataxis constructor must be a dict or an instance of plotly.graph_objs.layout.geo.Lataxis""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.geo import lataxis as v_lataxis # Initialize validators # --------------------- self._validators["dtick"] = v_lataxis.DtickValidator() self._validators["gridcolor"] = v_lataxis.GridcolorValidator() self._validators["gridwidth"] = v_lataxis.GridwidthValidator() self._validators["range"] = v_lataxis.RangeValidator() self._validators["showgrid"] = v_lataxis.ShowgridValidator() self._validators["tick0"] = v_lataxis.Tick0Validator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtick", None) self["dtick"] = dtick if dtick is not None else _v _v = arg.pop("gridcolor", None) self["gridcolor"] = gridcolor if gridcolor is not None else _v _v = arg.pop("gridwidth", None) self["gridwidth"] = gridwidth if gridwidth is not None else _v _v = arg.pop("range", None) self["range"] = range if range is not None else _v _v = arg.pop("showgrid", None) self["showgrid"] = showgrid if showgrid is not None else _v _v = arg.pop("tick0", None) self["tick0"] = tick0 if tick0 is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Domain(_BaseLayoutHierarchyType): # column # ------ @property def column(self): """ If there is a layout grid, use the domain for this column in the grid for this geo subplot . Note that geo subplots are constrained by domain. In general, when `projection.scale` is set to 1. a map will fit either its x or y domain, but not both. The 'column' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["column"] @column.setter def column(self, val): self["column"] = val # row # --- @property def row(self): """ If there is a layout grid, use the domain for this row in the grid for this geo subplot . Note that geo subplots are constrained by domain. In general, when `projection.scale` is set to 1. a map will fit either its x or y domain, but not both. The 'row' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["row"] @row.setter def row(self, val): self["row"] = val # x # - @property def x(self): """ Sets the horizontal domain of this geo subplot (in plot fraction). Note that geo subplots are constrained by domain. In general, when `projection.scale` is set to 1. a map will fit either its x or y domain, but not both. The 'x' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'x[0]' property is a number and may be specified as: - An int or float in the interval [0, 1] (1) The 'x[1]' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- list """ return self["x"] @x.setter def x(self, val): self["x"] = val # y # - @property def y(self): """ Sets the vertical domain of this geo subplot (in plot fraction). Note that geo subplots are constrained by domain. In general, when `projection.scale` is set to 1. a map will fit either its x or y domain, but not both. The 'y' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'y[0]' property is a number and may be specified as: - An int or float in the interval [0, 1] (1) The 'y[1]' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- list """ return self["y"] @y.setter def y(self, val): self["y"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.geo" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ column If there is a layout grid, use the domain for this column in the grid for this geo subplot . Note that geo subplots are constrained by domain. In general, when `projection.scale` is set to 1. a map will fit either its x or y domain, but not both. row If there is a layout grid, use the domain for this row in the grid for this geo subplot . Note that geo subplots are constrained by domain. In general, when `projection.scale` is set to 1. a map will fit either its x or y domain, but not both. x Sets the horizontal domain of this geo subplot (in plot fraction). Note that geo subplots are constrained by domain. In general, when `projection.scale` is set to 1. a map will fit either its x or y domain, but not both. y Sets the vertical domain of this geo subplot (in plot fraction). Note that geo subplots are constrained by domain. In general, when `projection.scale` is set to 1. a map will fit either its x or y domain, but not both. """ def __init__(self, arg=None, column=None, row=None, x=None, y=None, **kwargs): """ Construct a new Domain object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.geo.Domain column If there is a layout grid, use the domain for this column in the grid for this geo subplot . Note that geo subplots are constrained by domain. In general, when `projection.scale` is set to 1. a map will fit either its x or y domain, but not both. row If there is a layout grid, use the domain for this row in the grid for this geo subplot . Note that geo subplots are constrained by domain. In general, when `projection.scale` is set to 1. a map will fit either its x or y domain, but not both. x Sets the horizontal domain of this geo subplot (in plot fraction). Note that geo subplots are constrained by domain. In general, when `projection.scale` is set to 1. a map will fit either its x or y domain, but not both. y Sets the vertical domain of this geo subplot (in plot fraction). Note that geo subplots are constrained by domain. In general, when `projection.scale` is set to 1. a map will fit either its x or y domain, but not both. Returns ------- Domain """ super(Domain, self).__init__("domain") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.geo.Domain constructor must be a dict or an instance of plotly.graph_objs.layout.geo.Domain""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.geo import domain as v_domain # Initialize validators # --------------------- self._validators["column"] = v_domain.ColumnValidator() self._validators["row"] = v_domain.RowValidator() self._validators["x"] = v_domain.XValidator() self._validators["y"] = v_domain.YValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("column", None) self["column"] = column if column is not None else _v _v = arg.pop("row", None) self["row"] = row if row is not None else _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Center(_BaseLayoutHierarchyType): # lat # --- @property def lat(self): """ Sets the latitude of the map's center. For all projection types, the map's latitude center lies at the middle of the latitude range by default. The 'lat' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["lat"] @lat.setter def lat(self, val): self["lat"] = val # lon # --- @property def lon(self): """ Sets the longitude of the map's center. By default, the map's longitude center lies at the middle of the longitude range for scoped projection and above `projection.rotation.lon` otherwise. The 'lon' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["lon"] @lon.setter def lon(self, val): self["lon"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.geo" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ lat Sets the latitude of the map's center. For all projection types, the map's latitude center lies at the middle of the latitude range by default. lon Sets the longitude of the map's center. By default, the map's longitude center lies at the middle of the longitude range for scoped projection and above `projection.rotation.lon` otherwise. """ def __init__(self, arg=None, lat=None, lon=None, **kwargs): """ Construct a new Center object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.geo.Center lat Sets the latitude of the map's center. For all projection types, the map's latitude center lies at the middle of the latitude range by default. lon Sets the longitude of the map's center. By default, the map's longitude center lies at the middle of the longitude range for scoped projection and above `projection.rotation.lon` otherwise. Returns ------- Center """ super(Center, self).__init__("center") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.geo.Center constructor must be a dict or an instance of plotly.graph_objs.layout.geo.Center""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.geo import center as v_center # Initialize validators # --------------------- self._validators["lat"] = v_center.LatValidator() self._validators["lon"] = v_center.LonValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("lat", None) self["lat"] = lat if lat is not None else _v _v = arg.pop("lon", None) self["lon"] = lon if lon is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Center", "Domain", "Lataxis", "Lonaxis", "Projection", "projection"] from plotly.graph_objs.layout.geo import projection plotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/__init__.py0000644000175000017500000332552313573721557023374 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class YAxis(_BaseLayoutHierarchyType): # anchor # ------ @property def anchor(self): """ If set to an opposite-letter axis id (e.g. `x2`, `y`), this axis is bound to the corresponding opposite-letter axis. If set to "free", this axis' position is determined by `position`. The 'anchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['free'] - A string that matches one of the following regular expressions: ['^x([2-9]|[1-9][0-9]+)?$', '^y([2-9]|[1-9][0-9]+)?$'] Returns ------- Any """ return self["anchor"] @anchor.setter def anchor(self, val): self["anchor"] = val # automargin # ---------- @property def automargin(self): """ Determines whether long tick labels automatically grow the figure margins. The 'automargin' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["automargin"] @automargin.setter def automargin(self, val): self["automargin"] = val # autorange # --------- @property def autorange(self): """ Determines whether or not the range of this axis is computed in relation to the input data. See `rangemode` for more info. If `range` is provided, then `autorange` is set to False. The 'autorange' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'reversed'] Returns ------- Any """ return self["autorange"] @autorange.setter def autorange(self, val): self["autorange"] = val # calendar # -------- @property def calendar(self): """ Sets the calendar system to use for `range` and `tick0` if this is a date axis. This does not set the calendar for interpreting data on this axis, that's specified in the trace or via the global `layout.calendar` The 'calendar' property is an enumeration that may be specified as: - One of the following enumeration values: ['gregorian', 'chinese', 'coptic', 'discworld', 'ethiopian', 'hebrew', 'islamic', 'julian', 'mayan', 'nanakshahi', 'nepali', 'persian', 'jalali', 'taiwan', 'thai', 'ummalqura'] Returns ------- Any """ return self["calendar"] @calendar.setter def calendar(self, val): self["calendar"] = val # categoryarray # ------------- @property def categoryarray(self): """ Sets the order in which categories on this axis appear. Only has an effect if `categoryorder` is set to "array". Used with `categoryorder`. The 'categoryarray' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["categoryarray"] @categoryarray.setter def categoryarray(self, val): self["categoryarray"] = val # categoryarraysrc # ---------------- @property def categoryarraysrc(self): """ Sets the source reference on plot.ly for categoryarray . The 'categoryarraysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["categoryarraysrc"] @categoryarraysrc.setter def categoryarraysrc(self, val): self["categoryarraysrc"] = val # categoryorder # ------------- @property def categoryorder(self): """ Specifies the ordering logic for the case of categorical variables. By default, plotly uses "trace", which specifies the order that is present in the data supplied. Set `categoryorder` to *category ascending* or *category descending* if order should be determined by the alphanumerical order of the category names. Set `categoryorder` to "array" to derive the ordering from the attribute `categoryarray`. If a category is not found in the `categoryarray` array, the sorting behavior for that attribute will be identical to the "trace" mode. The unspecified categories will follow the categories in `categoryarray`. Set `categoryorder` to *total ascending* or *total descending* if order should be determined by the numerical order of the values. Similarly, the order can be determined by the min, max, sum, mean or median of all the values. The 'categoryorder' property is an enumeration that may be specified as: - One of the following enumeration values: ['trace', 'category ascending', 'category descending', 'array', 'total ascending', 'total descending', 'min ascending', 'min descending', 'max ascending', 'max descending', 'sum ascending', 'sum descending', 'mean ascending', 'mean descending', 'median ascending', 'median descending'] Returns ------- Any """ return self["categoryorder"] @categoryorder.setter def categoryorder(self, val): self["categoryorder"] = val # color # ----- @property def color(self): """ Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # constrain # --------- @property def constrain(self): """ If this axis needs to be compressed (either due to its own `scaleanchor` and `scaleratio` or those of the other axis), determines how that happens: by increasing the "range" (default), or by decreasing the "domain". The 'constrain' property is an enumeration that may be specified as: - One of the following enumeration values: ['range', 'domain'] Returns ------- Any """ return self["constrain"] @constrain.setter def constrain(self, val): self["constrain"] = val # constraintoward # --------------- @property def constraintoward(self): """ If this axis needs to be compressed (either due to its own `scaleanchor` and `scaleratio` or those of the other axis), determines which direction we push the originally specified plot area. Options are "left", "center" (default), and "right" for x axes, and "top", "middle" (default), and "bottom" for y axes. The 'constraintoward' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'center', 'right', 'top', 'middle', 'bottom'] Returns ------- Any """ return self["constraintoward"] @constraintoward.setter def constraintoward(self, val): self["constraintoward"] = val # dividercolor # ------------ @property def dividercolor(self): """ Sets the color of the dividers Only has an effect on "multicategory" axes. The 'dividercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["dividercolor"] @dividercolor.setter def dividercolor(self, val): self["dividercolor"] = val # dividerwidth # ------------ @property def dividerwidth(self): """ Sets the width (in px) of the dividers Only has an effect on "multicategory" axes. The 'dividerwidth' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["dividerwidth"] @dividerwidth.setter def dividerwidth(self, val): self["dividerwidth"] = val # domain # ------ @property def domain(self): """ Sets the domain of this axis (in plot fraction). The 'domain' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'domain[0]' property is a number and may be specified as: - An int or float in the interval [0, 1] (1) The 'domain[1]' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- list """ return self["domain"] @domain.setter def domain(self, val): self["domain"] = val # dtick # ----- @property def dtick(self): """ Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" The 'dtick' property accepts values of any type Returns ------- Any """ return self["dtick"] @dtick.setter def dtick(self, val): self["dtick"] = val # exponentformat # -------------- @property def exponentformat(self): """ Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. The 'exponentformat' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'e', 'E', 'power', 'SI', 'B'] Returns ------- Any """ return self["exponentformat"] @exponentformat.setter def exponentformat(self, val): self["exponentformat"] = val # fixedrange # ---------- @property def fixedrange(self): """ Determines whether or not this axis is zoom-able. If true, then zoom is disabled. The 'fixedrange' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["fixedrange"] @fixedrange.setter def fixedrange(self, val): self["fixedrange"] = val # gridcolor # --------- @property def gridcolor(self): """ Sets the color of the grid lines. The 'gridcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["gridcolor"] @gridcolor.setter def gridcolor(self, val): self["gridcolor"] = val # gridwidth # --------- @property def gridwidth(self): """ Sets the width (in px) of the grid lines. The 'gridwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["gridwidth"] @gridwidth.setter def gridwidth(self, val): self["gridwidth"] = val # hoverformat # ----------- @property def hoverformat(self): """ Sets the hover text formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'hoverformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["hoverformat"] @hoverformat.setter def hoverformat(self, val): self["hoverformat"] = val # layer # ----- @property def layer(self): """ Sets the layer on which this axis is displayed. If *above traces*, this axis is displayed above all the subplot's traces If *below traces*, this axis is displayed below all the subplot's traces, but above the grid lines. Useful when used together with scatter-like traces with `cliponaxis` set to False to show markers and/or text nodes above this axis. The 'layer' property is an enumeration that may be specified as: - One of the following enumeration values: ['above traces', 'below traces'] Returns ------- Any """ return self["layer"] @layer.setter def layer(self, val): self["layer"] = val # linecolor # --------- @property def linecolor(self): """ Sets the axis line color. The 'linecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["linecolor"] @linecolor.setter def linecolor(self, val): self["linecolor"] = val # linewidth # --------- @property def linewidth(self): """ Sets the width (in px) of the axis line. The 'linewidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["linewidth"] @linewidth.setter def linewidth(self, val): self["linewidth"] = val # matches # ------- @property def matches(self): """ If set to another axis id (e.g. `x2`, `y`), the range of this axis will match the range of the corresponding axis in data- coordinates space. Moreover, matching axes share auto-range values, category lists and histogram auto-bins. Note that setting axes simultaneously in both a `scaleanchor` and a `matches` constraint is currently forbidden. Moreover, note that matching axes must have the same `type`. The 'matches' property is an enumeration that may be specified as: - A string that matches one of the following regular expressions: ['^x([2-9]|[1-9][0-9]+)?$', '^y([2-9]|[1-9][0-9]+)?$'] Returns ------- Any """ return self["matches"] @matches.setter def matches(self, val): self["matches"] = val # mirror # ------ @property def mirror(self): """ Determines if the axis lines or/and ticks are mirrored to the opposite side of the plotting area. If True, the axis lines are mirrored. If "ticks", the axis lines and ticks are mirrored. If False, mirroring is disable. If "all", axis lines are mirrored on all shared-axes subplots. If "allticks", axis lines and ticks are mirrored on all shared-axes subplots. The 'mirror' property is an enumeration that may be specified as: - One of the following enumeration values: [True, 'ticks', False, 'all', 'allticks'] Returns ------- Any """ return self["mirror"] @mirror.setter def mirror(self, val): self["mirror"] = val # nticks # ------ @property def nticks(self): """ Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". The 'nticks' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nticks"] @nticks.setter def nticks(self, val): self["nticks"] = val # overlaying # ---------- @property def overlaying(self): """ If set a same-letter axis id, this axis is overlaid on top of the corresponding same-letter axis, with traces and axes visible for both axes. If False, this axis does not overlay any same-letter axes. In this case, for axes with overlapping domains only the highest-numbered axis will be visible. The 'overlaying' property is an enumeration that may be specified as: - One of the following enumeration values: ['free'] - A string that matches one of the following regular expressions: ['^x([2-9]|[1-9][0-9]+)?$', '^y([2-9]|[1-9][0-9]+)?$'] Returns ------- Any """ return self["overlaying"] @overlaying.setter def overlaying(self, val): self["overlaying"] = val # position # -------- @property def position(self): """ Sets the position of this axis in the plotting space (in normalized coordinates). Only has an effect if `anchor` is set to "free". The 'position' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["position"] @position.setter def position(self, val): self["position"] = val # range # ----- @property def range(self): """ Sets the range of this axis. If the axis `type` is "log", then you must take the log of your desired range (e.g. to set the range from 1 to 100, set the range from 0 to 2). If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. The 'range' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'range[0]' property accepts values of any type (1) The 'range[1]' property accepts values of any type Returns ------- list """ return self["range"] @range.setter def range(self, val): self["range"] = val # rangemode # --------- @property def rangemode(self): """ If "normal", the range is computed in relation to the extrema of the input data. If *tozero*`, the range extends to 0, regardless of the input data If "nonnegative", the range is non-negative, regardless of the input data. Applies only to linear axes. The 'rangemode' property is an enumeration that may be specified as: - One of the following enumeration values: ['normal', 'tozero', 'nonnegative'] Returns ------- Any """ return self["rangemode"] @rangemode.setter def rangemode(self, val): self["rangemode"] = val # scaleanchor # ----------- @property def scaleanchor(self): """ If set to another axis id (e.g. `x2`, `y`), the range of this axis changes together with the range of the corresponding axis such that the scale of pixels per unit is in a constant ratio. Both axes are still zoomable, but when you zoom one, the other will zoom the same amount, keeping a fixed midpoint. `constrain` and `constraintoward` determine how we enforce the constraint. You can chain these, ie `yaxis: {scaleanchor: *x*}, xaxis2: {scaleanchor: *y*}` but you can only link axes of the same `type`. The linked axis can have the opposite letter (to constrain the aspect ratio) or the same letter (to match scales across subplots). Loops (`yaxis: {scaleanchor: *x*}, xaxis: {scaleanchor: *y*}` or longer) are redundant and the last constraint encountered will be ignored to avoid possible inconsistent constraints via `scaleratio`. Note that setting axes simultaneously in both a `scaleanchor` and a `matches` constraint is currently forbidden. The 'scaleanchor' property is an enumeration that may be specified as: - A string that matches one of the following regular expressions: ['^x([2-9]|[1-9][0-9]+)?$', '^y([2-9]|[1-9][0-9]+)?$'] Returns ------- Any """ return self["scaleanchor"] @scaleanchor.setter def scaleanchor(self, val): self["scaleanchor"] = val # scaleratio # ---------- @property def scaleratio(self): """ If this axis is linked to another by `scaleanchor`, this determines the pixel to unit scale ratio. For example, if this value is 10, then every unit on this axis spans 10 times the number of pixels as a unit on the linked axis. Use this for example to create an elevation profile where the vertical scale is exaggerated a fixed amount with respect to the horizontal. The 'scaleratio' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["scaleratio"] @scaleratio.setter def scaleratio(self, val): self["scaleratio"] = val # separatethousands # ----------------- @property def separatethousands(self): """ If "true", even 4-digit integers are separated The 'separatethousands' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["separatethousands"] @separatethousands.setter def separatethousands(self, val): self["separatethousands"] = val # showdividers # ------------ @property def showdividers(self): """ Determines whether or not a dividers are drawn between the category levels of this axis. Only has an effect on "multicategory" axes. The 'showdividers' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showdividers"] @showdividers.setter def showdividers(self, val): self["showdividers"] = val # showexponent # ------------ @property def showexponent(self): """ If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. The 'showexponent' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showexponent"] @showexponent.setter def showexponent(self, val): self["showexponent"] = val # showgrid # -------- @property def showgrid(self): """ Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. The 'showgrid' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showgrid"] @showgrid.setter def showgrid(self, val): self["showgrid"] = val # showline # -------- @property def showline(self): """ Determines whether or not a line bounding this axis is drawn. The 'showline' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showline"] @showline.setter def showline(self, val): self["showline"] = val # showspikes # ---------- @property def showspikes(self): """ Determines whether or not spikes (aka droplines) are drawn for this axis. Note: This only takes affect when hovermode = closest The 'showspikes' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showspikes"] @showspikes.setter def showspikes(self, val): self["showspikes"] = val # showticklabels # -------------- @property def showticklabels(self): """ Determines whether or not the tick labels are drawn. The 'showticklabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showticklabels"] @showticklabels.setter def showticklabels(self, val): self["showticklabels"] = val # showtickprefix # -------------- @property def showtickprefix(self): """ If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. The 'showtickprefix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showtickprefix"] @showtickprefix.setter def showtickprefix(self, val): self["showtickprefix"] = val # showticksuffix # -------------- @property def showticksuffix(self): """ Same as `showtickprefix` but for tick suffixes. The 'showticksuffix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showticksuffix"] @showticksuffix.setter def showticksuffix(self, val): self["showticksuffix"] = val # side # ---- @property def side(self): """ Determines whether a x (y) axis is positioned at the "bottom" ("left") or "top" ("right") of the plotting area. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['top', 'bottom', 'left', 'right'] Returns ------- Any """ return self["side"] @side.setter def side(self, val): self["side"] = val # spikecolor # ---------- @property def spikecolor(self): """ Sets the spike color. If undefined, will use the series color The 'spikecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["spikecolor"] @spikecolor.setter def spikecolor(self, val): self["spikecolor"] = val # spikedash # --------- @property def spikedash(self): """ Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). The 'spikedash' property is a string and must be specified as: - One of the following strings: ['solid', 'dot', 'dash', 'longdash', 'dashdot', 'longdashdot'] - A number that will be converted to a string Returns ------- str """ return self["spikedash"] @spikedash.setter def spikedash(self, val): self["spikedash"] = val # spikemode # --------- @property def spikemode(self): """ Determines the drawing mode for the spike line If "toaxis", the line is drawn from the data point to the axis the series is plotted on. If "across", the line is drawn across the entire plot area, and supercedes "toaxis". If "marker", then a marker dot is drawn on the axis the series is plotted on The 'spikemode' property is a flaglist and may be specified as a string containing: - Any combination of ['toaxis', 'across', 'marker'] joined with '+' characters (e.g. 'toaxis+across') Returns ------- Any """ return self["spikemode"] @spikemode.setter def spikemode(self, val): self["spikemode"] = val # spikesnap # --------- @property def spikesnap(self): """ Determines whether spikelines are stuck to the cursor or to the closest datapoints. The 'spikesnap' property is an enumeration that may be specified as: - One of the following enumeration values: ['data', 'cursor'] Returns ------- Any """ return self["spikesnap"] @spikesnap.setter def spikesnap(self, val): self["spikesnap"] = val # spikethickness # -------------- @property def spikethickness(self): """ Sets the width (in px) of the zero line. The 'spikethickness' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["spikethickness"] @spikethickness.setter def spikethickness(self, val): self["spikethickness"] = val # tick0 # ----- @property def tick0(self): """ Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. The 'tick0' property accepts values of any type Returns ------- Any """ return self["tick0"] @tick0.setter def tick0(self, val): self["tick0"] = val # tickangle # --------- @property def tickangle(self): """ Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. The 'tickangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["tickangle"] @tickangle.setter def tickangle(self, val): self["tickangle"] = val # tickcolor # --------- @property def tickcolor(self): """ Sets the tick color. The 'tickcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["tickcolor"] @tickcolor.setter def tickcolor(self, val): self["tickcolor"] = val # tickfont # -------- @property def tickfont(self): """ Sets the tick font. The 'tickfont' property is an instance of Tickfont that may be specified as: - An instance of plotly.graph_objs.layout.yaxis.Tickfont - A dict of string/value properties that will be passed to the Tickfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.layout.yaxis.Tickfont """ return self["tickfont"] @tickfont.setter def tickfont(self, val): self["tickfont"] = val # tickformat # ---------- @property def tickformat(self): """ Sets the tick label formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'tickformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickformat"] @tickformat.setter def tickformat(self, val): self["tickformat"] = val # tickformatstops # --------------- @property def tickformatstops(self): """ The 'tickformatstops' property is a tuple of instances of Tickformatstop that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.yaxis.Tickformatstop - A list or tuple of dicts of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- tuple[plotly.graph_objs.layout.yaxis.Tickformatstop] """ return self["tickformatstops"] @tickformatstops.setter def tickformatstops(self, val): self["tickformatstops"] = val # tickformatstopdefaults # ---------------------- @property def tickformatstopdefaults(self): """ When used in a template (as layout.template.layout.yaxis.tickformatstopdefaults), sets the default property values to use for elements of layout.yaxis.tickformatstops The 'tickformatstopdefaults' property is an instance of Tickformatstop that may be specified as: - An instance of plotly.graph_objs.layout.yaxis.Tickformatstop - A dict of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: Returns ------- plotly.graph_objs.layout.yaxis.Tickformatstop """ return self["tickformatstopdefaults"] @tickformatstopdefaults.setter def tickformatstopdefaults(self, val): self["tickformatstopdefaults"] = val # ticklen # ------- @property def ticklen(self): """ Sets the tick length (in px). The 'ticklen' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ticklen"] @ticklen.setter def ticklen(self, val): self["ticklen"] = val # tickmode # -------- @property def tickmode(self): """ Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). The 'tickmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'linear', 'array'] Returns ------- Any """ return self["tickmode"] @tickmode.setter def tickmode(self, val): self["tickmode"] = val # tickprefix # ---------- @property def tickprefix(self): """ Sets a tick label prefix. The 'tickprefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickprefix"] @tickprefix.setter def tickprefix(self, val): self["tickprefix"] = val # ticks # ----- @property def ticks(self): """ Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. The 'ticks' property is an enumeration that may be specified as: - One of the following enumeration values: ['outside', 'inside', ''] Returns ------- Any """ return self["ticks"] @ticks.setter def ticks(self, val): self["ticks"] = val # tickson # ------- @property def tickson(self): """ Determines where ticks and grid lines are drawn with respect to their corresponding tick labels. Only has an effect for axes of `type` "category" or "multicategory". When set to "boundaries", ticks and grid lines are drawn half a category to the left/bottom of labels. The 'tickson' property is an enumeration that may be specified as: - One of the following enumeration values: ['labels', 'boundaries'] Returns ------- Any """ return self["tickson"] @tickson.setter def tickson(self, val): self["tickson"] = val # ticksuffix # ---------- @property def ticksuffix(self): """ Sets a tick label suffix. The 'ticksuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ticksuffix"] @ticksuffix.setter def ticksuffix(self, val): self["ticksuffix"] = val # ticktext # -------- @property def ticktext(self): """ Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. The 'ticktext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ticktext"] @ticktext.setter def ticktext(self, val): self["ticktext"] = val # ticktextsrc # ----------- @property def ticktextsrc(self): """ Sets the source reference on plot.ly for ticktext . The 'ticktextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ticktextsrc"] @ticktextsrc.setter def ticktextsrc(self, val): self["ticktextsrc"] = val # tickvals # -------- @property def tickvals(self): """ Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. The 'tickvals' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["tickvals"] @tickvals.setter def tickvals(self, val): self["tickvals"] = val # tickvalssrc # ----------- @property def tickvalssrc(self): """ Sets the source reference on plot.ly for tickvals . The 'tickvalssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tickvalssrc"] @tickvalssrc.setter def tickvalssrc(self, val): self["tickvalssrc"] = val # tickwidth # --------- @property def tickwidth(self): """ Sets the tick width (in px). The 'tickwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["tickwidth"] @tickwidth.setter def tickwidth(self, val): self["tickwidth"] = val # title # ----- @property def title(self): """ The 'title' property is an instance of Title that may be specified as: - An instance of plotly.graph_objs.layout.yaxis.Title - A dict of string/value properties that will be passed to the Title constructor Supported dict properties: font Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. standoff Sets the standoff distance (in px) between the axis labels and the title text The default value is a function of the axis tick labels, the title `font.size` and the axis `linewidth`. Note that the axis title position is always constrained within the margins, so the actual standoff distance is always less than the set or default value. By setting `standoff` and turning on `automargin`, plotly.js will push the margins to fit the axis title at given standoff distance. text Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- plotly.graph_objs.layout.yaxis.Title """ return self["title"] @title.setter def title(self, val): self["title"] = val # titlefont # --------- @property def titlefont(self): """ Deprecated: Please use layout.yaxis.title.font instead. Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.layout.yaxis.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- """ return self["titlefont"] @titlefont.setter def titlefont(self, val): self["titlefont"] = val # type # ---- @property def type(self): """ Sets the axis type. By default, plotly attempts to determined the axis type by looking into the data of the traces that referenced the axis in question. The 'type' property is an enumeration that may be specified as: - One of the following enumeration values: ['-', 'linear', 'log', 'date', 'category', 'multicategory'] Returns ------- Any """ return self["type"] @type.setter def type(self, val): self["type"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of user-driven changes in axis `range`, `autorange`, and `title` if in `editable: true` configuration. Defaults to `layout.uirevision`. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # visible # ------- @property def visible(self): """ A single toggle to hide the axis while preserving interaction like dragging. Default is true when a cheater plot is present on the axis, otherwise false The 'visible' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # zeroline # -------- @property def zeroline(self): """ Determines whether or not a line is drawn at along the 0 value of this axis. If True, the zero line is drawn on top of the grid lines. The 'zeroline' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["zeroline"] @zeroline.setter def zeroline(self, val): self["zeroline"] = val # zerolinecolor # ------------- @property def zerolinecolor(self): """ Sets the line color of the zero line. The 'zerolinecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["zerolinecolor"] @zerolinecolor.setter def zerolinecolor(self, val): self["zerolinecolor"] = val # zerolinewidth # ------------- @property def zerolinewidth(self): """ Sets the width (in px) of the zero line. The 'zerolinewidth' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["zerolinewidth"] @zerolinewidth.setter def zerolinewidth(self, val): self["zerolinewidth"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ anchor If set to an opposite-letter axis id (e.g. `x2`, `y`), this axis is bound to the corresponding opposite-letter axis. If set to "free", this axis' position is determined by `position`. automargin Determines whether long tick labels automatically grow the figure margins. autorange Determines whether or not the range of this axis is computed in relation to the input data. See `rangemode` for more info. If `range` is provided, then `autorange` is set to False. calendar Sets the calendar system to use for `range` and `tick0` if this is a date axis. This does not set the calendar for interpreting data on this axis, that's specified in the trace or via the global `layout.calendar` categoryarray Sets the order in which categories on this axis appear. Only has an effect if `categoryorder` is set to "array". Used with `categoryorder`. categoryarraysrc Sets the source reference on plot.ly for categoryarray . categoryorder Specifies the ordering logic for the case of categorical variables. By default, plotly uses "trace", which specifies the order that is present in the data supplied. Set `categoryorder` to *category ascending* or *category descending* if order should be determined by the alphanumerical order of the category names. Set `categoryorder` to "array" to derive the ordering from the attribute `categoryarray`. If a category is not found in the `categoryarray` array, the sorting behavior for that attribute will be identical to the "trace" mode. The unspecified categories will follow the categories in `categoryarray`. Set `categoryorder` to *total ascending* or *total descending* if order should be determined by the numerical order of the values. Similarly, the order can be determined by the min, max, sum, mean or median of all the values. color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. constrain If this axis needs to be compressed (either due to its own `scaleanchor` and `scaleratio` or those of the other axis), determines how that happens: by increasing the "range" (default), or by decreasing the "domain". constraintoward If this axis needs to be compressed (either due to its own `scaleanchor` and `scaleratio` or those of the other axis), determines which direction we push the originally specified plot area. Options are "left", "center" (default), and "right" for x axes, and "top", "middle" (default), and "bottom" for y axes. dividercolor Sets the color of the dividers Only has an effect on "multicategory" axes. dividerwidth Sets the width (in px) of the dividers Only has an effect on "multicategory" axes. domain Sets the domain of this axis (in plot fraction). dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. fixedrange Determines whether or not this axis is zoom-able. If true, then zoom is disabled. gridcolor Sets the color of the grid lines. gridwidth Sets the width (in px) of the grid lines. hoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" layer Sets the layer on which this axis is displayed. If *above traces*, this axis is displayed above all the subplot's traces If *below traces*, this axis is displayed below all the subplot's traces, but above the grid lines. Useful when used together with scatter-like traces with `cliponaxis` set to False to show markers and/or text nodes above this axis. linecolor Sets the axis line color. linewidth Sets the width (in px) of the axis line. matches If set to another axis id (e.g. `x2`, `y`), the range of this axis will match the range of the corresponding axis in data-coordinates space. Moreover, matching axes share auto-range values, category lists and histogram auto-bins. Note that setting axes simultaneously in both a `scaleanchor` and a `matches` constraint is currently forbidden. Moreover, note that matching axes must have the same `type`. mirror Determines if the axis lines or/and ticks are mirrored to the opposite side of the plotting area. If True, the axis lines are mirrored. If "ticks", the axis lines and ticks are mirrored. If False, mirroring is disable. If "all", axis lines are mirrored on all shared-axes subplots. If "allticks", axis lines and ticks are mirrored on all shared-axes subplots. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". overlaying If set a same-letter axis id, this axis is overlaid on top of the corresponding same-letter axis, with traces and axes visible for both axes. If False, this axis does not overlay any same-letter axes. In this case, for axes with overlapping domains only the highest- numbered axis will be visible. position Sets the position of this axis in the plotting space (in normalized coordinates). Only has an effect if `anchor` is set to "free". range Sets the range of this axis. If the axis `type` is "log", then you must take the log of your desired range (e.g. to set the range from 1 to 100, set the range from 0 to 2). If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. rangemode If "normal", the range is computed in relation to the extrema of the input data. If *tozero*`, the range extends to 0, regardless of the input data If "nonnegative", the range is non-negative, regardless of the input data. Applies only to linear axes. scaleanchor If set to another axis id (e.g. `x2`, `y`), the range of this axis changes together with the range of the corresponding axis such that the scale of pixels per unit is in a constant ratio. Both axes are still zoomable, but when you zoom one, the other will zoom the same amount, keeping a fixed midpoint. `constrain` and `constraintoward` determine how we enforce the constraint. You can chain these, ie `yaxis: {scaleanchor: *x*}, xaxis2: {scaleanchor: *y*}` but you can only link axes of the same `type`. The linked axis can have the opposite letter (to constrain the aspect ratio) or the same letter (to match scales across subplots). Loops (`yaxis: {scaleanchor: *x*}, xaxis: {scaleanchor: *y*}` or longer) are redundant and the last constraint encountered will be ignored to avoid possible inconsistent constraints via `scaleratio`. Note that setting axes simultaneously in both a `scaleanchor` and a `matches` constraint is currently forbidden. scaleratio If this axis is linked to another by `scaleanchor`, this determines the pixel to unit scale ratio. For example, if this value is 10, then every unit on this axis spans 10 times the number of pixels as a unit on the linked axis. Use this for example to create an elevation profile where the vertical scale is exaggerated a fixed amount with respect to the horizontal. separatethousands If "true", even 4-digit integers are separated showdividers Determines whether or not a dividers are drawn between the category levels of this axis. Only has an effect on "multicategory" axes. showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showgrid Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. showline Determines whether or not a line bounding this axis is drawn. showspikes Determines whether or not spikes (aka droplines) are drawn for this axis. Note: This only takes affect when hovermode = closest showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. side Determines whether a x (y) axis is positioned at the "bottom" ("left") or "top" ("right") of the plotting area. spikecolor Sets the spike color. If undefined, will use the series color spikedash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). spikemode Determines the drawing mode for the spike line If "toaxis", the line is drawn from the data point to the axis the series is plotted on. If "across", the line is drawn across the entire plot area, and supercedes "toaxis". If "marker", then a marker dot is drawn on the axis the series is plotted on spikesnap Determines whether spikelines are stuck to the cursor or to the closest datapoints. spikethickness Sets the width (in px) of the zero line. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the tick font. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.layout.yaxis.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.layout.yaxis.tickformatstopdefaults), sets the default property values to use for elements of layout.yaxis.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. tickson Determines where ticks and grid lines are drawn with respect to their corresponding tick labels. Only has an effect for axes of `type` "category" or "multicategory". When set to "boundaries", ticks and grid lines are drawn half a category to the left/bottom of labels. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.layout.yaxis.Title instance or dict with compatible properties titlefont Deprecated: Please use layout.yaxis.title.font instead. Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. type Sets the axis type. By default, plotly attempts to determined the axis type by looking into the data of the traces that referenced the axis in question. uirevision Controls persistence of user-driven changes in axis `range`, `autorange`, and `title` if in `editable: true` configuration. Defaults to `layout.uirevision`. visible A single toggle to hide the axis while preserving interaction like dragging. Default is true when a cheater plot is present on the axis, otherwise false zeroline Determines whether or not a line is drawn at along the 0 value of this axis. If True, the zero line is drawn on top of the grid lines. zerolinecolor Sets the line color of the zero line. zerolinewidth Sets the width (in px) of the zero line. """ _mapped_properties = {"titlefont": ("title", "font")} def __init__( self, arg=None, anchor=None, automargin=None, autorange=None, calendar=None, categoryarray=None, categoryarraysrc=None, categoryorder=None, color=None, constrain=None, constraintoward=None, dividercolor=None, dividerwidth=None, domain=None, dtick=None, exponentformat=None, fixedrange=None, gridcolor=None, gridwidth=None, hoverformat=None, layer=None, linecolor=None, linewidth=None, matches=None, mirror=None, nticks=None, overlaying=None, position=None, range=None, rangemode=None, scaleanchor=None, scaleratio=None, separatethousands=None, showdividers=None, showexponent=None, showgrid=None, showline=None, showspikes=None, showticklabels=None, showtickprefix=None, showticksuffix=None, side=None, spikecolor=None, spikedash=None, spikemode=None, spikesnap=None, spikethickness=None, tick0=None, tickangle=None, tickcolor=None, tickfont=None, tickformat=None, tickformatstops=None, tickformatstopdefaults=None, ticklen=None, tickmode=None, tickprefix=None, ticks=None, tickson=None, ticksuffix=None, ticktext=None, ticktextsrc=None, tickvals=None, tickvalssrc=None, tickwidth=None, title=None, titlefont=None, type=None, uirevision=None, visible=None, zeroline=None, zerolinecolor=None, zerolinewidth=None, **kwargs ): """ Construct a new YAxis object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.YAxis anchor If set to an opposite-letter axis id (e.g. `x2`, `y`), this axis is bound to the corresponding opposite-letter axis. If set to "free", this axis' position is determined by `position`. automargin Determines whether long tick labels automatically grow the figure margins. autorange Determines whether or not the range of this axis is computed in relation to the input data. See `rangemode` for more info. If `range` is provided, then `autorange` is set to False. calendar Sets the calendar system to use for `range` and `tick0` if this is a date axis. This does not set the calendar for interpreting data on this axis, that's specified in the trace or via the global `layout.calendar` categoryarray Sets the order in which categories on this axis appear. Only has an effect if `categoryorder` is set to "array". Used with `categoryorder`. categoryarraysrc Sets the source reference on plot.ly for categoryarray . categoryorder Specifies the ordering logic for the case of categorical variables. By default, plotly uses "trace", which specifies the order that is present in the data supplied. Set `categoryorder` to *category ascending* or *category descending* if order should be determined by the alphanumerical order of the category names. Set `categoryorder` to "array" to derive the ordering from the attribute `categoryarray`. If a category is not found in the `categoryarray` array, the sorting behavior for that attribute will be identical to the "trace" mode. The unspecified categories will follow the categories in `categoryarray`. Set `categoryorder` to *total ascending* or *total descending* if order should be determined by the numerical order of the values. Similarly, the order can be determined by the min, max, sum, mean or median of all the values. color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. constrain If this axis needs to be compressed (either due to its own `scaleanchor` and `scaleratio` or those of the other axis), determines how that happens: by increasing the "range" (default), or by decreasing the "domain". constraintoward If this axis needs to be compressed (either due to its own `scaleanchor` and `scaleratio` or those of the other axis), determines which direction we push the originally specified plot area. Options are "left", "center" (default), and "right" for x axes, and "top", "middle" (default), and "bottom" for y axes. dividercolor Sets the color of the dividers Only has an effect on "multicategory" axes. dividerwidth Sets the width (in px) of the dividers Only has an effect on "multicategory" axes. domain Sets the domain of this axis (in plot fraction). dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. fixedrange Determines whether or not this axis is zoom-able. If true, then zoom is disabled. gridcolor Sets the color of the grid lines. gridwidth Sets the width (in px) of the grid lines. hoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" layer Sets the layer on which this axis is displayed. If *above traces*, this axis is displayed above all the subplot's traces If *below traces*, this axis is displayed below all the subplot's traces, but above the grid lines. Useful when used together with scatter-like traces with `cliponaxis` set to False to show markers and/or text nodes above this axis. linecolor Sets the axis line color. linewidth Sets the width (in px) of the axis line. matches If set to another axis id (e.g. `x2`, `y`), the range of this axis will match the range of the corresponding axis in data-coordinates space. Moreover, matching axes share auto-range values, category lists and histogram auto-bins. Note that setting axes simultaneously in both a `scaleanchor` and a `matches` constraint is currently forbidden. Moreover, note that matching axes must have the same `type`. mirror Determines if the axis lines or/and ticks are mirrored to the opposite side of the plotting area. If True, the axis lines are mirrored. If "ticks", the axis lines and ticks are mirrored. If False, mirroring is disable. If "all", axis lines are mirrored on all shared-axes subplots. If "allticks", axis lines and ticks are mirrored on all shared-axes subplots. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". overlaying If set a same-letter axis id, this axis is overlaid on top of the corresponding same-letter axis, with traces and axes visible for both axes. If False, this axis does not overlay any same-letter axes. In this case, for axes with overlapping domains only the highest- numbered axis will be visible. position Sets the position of this axis in the plotting space (in normalized coordinates). Only has an effect if `anchor` is set to "free". range Sets the range of this axis. If the axis `type` is "log", then you must take the log of your desired range (e.g. to set the range from 1 to 100, set the range from 0 to 2). If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. rangemode If "normal", the range is computed in relation to the extrema of the input data. If *tozero*`, the range extends to 0, regardless of the input data If "nonnegative", the range is non-negative, regardless of the input data. Applies only to linear axes. scaleanchor If set to another axis id (e.g. `x2`, `y`), the range of this axis changes together with the range of the corresponding axis such that the scale of pixels per unit is in a constant ratio. Both axes are still zoomable, but when you zoom one, the other will zoom the same amount, keeping a fixed midpoint. `constrain` and `constraintoward` determine how we enforce the constraint. You can chain these, ie `yaxis: {scaleanchor: *x*}, xaxis2: {scaleanchor: *y*}` but you can only link axes of the same `type`. The linked axis can have the opposite letter (to constrain the aspect ratio) or the same letter (to match scales across subplots). Loops (`yaxis: {scaleanchor: *x*}, xaxis: {scaleanchor: *y*}` or longer) are redundant and the last constraint encountered will be ignored to avoid possible inconsistent constraints via `scaleratio`. Note that setting axes simultaneously in both a `scaleanchor` and a `matches` constraint is currently forbidden. scaleratio If this axis is linked to another by `scaleanchor`, this determines the pixel to unit scale ratio. For example, if this value is 10, then every unit on this axis spans 10 times the number of pixels as a unit on the linked axis. Use this for example to create an elevation profile where the vertical scale is exaggerated a fixed amount with respect to the horizontal. separatethousands If "true", even 4-digit integers are separated showdividers Determines whether or not a dividers are drawn between the category levels of this axis. Only has an effect on "multicategory" axes. showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showgrid Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. showline Determines whether or not a line bounding this axis is drawn. showspikes Determines whether or not spikes (aka droplines) are drawn for this axis. Note: This only takes affect when hovermode = closest showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. side Determines whether a x (y) axis is positioned at the "bottom" ("left") or "top" ("right") of the plotting area. spikecolor Sets the spike color. If undefined, will use the series color spikedash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). spikemode Determines the drawing mode for the spike line If "toaxis", the line is drawn from the data point to the axis the series is plotted on. If "across", the line is drawn across the entire plot area, and supercedes "toaxis". If "marker", then a marker dot is drawn on the axis the series is plotted on spikesnap Determines whether spikelines are stuck to the cursor or to the closest datapoints. spikethickness Sets the width (in px) of the zero line. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the tick font. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.layout.yaxis.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.layout.yaxis.tickformatstopdefaults), sets the default property values to use for elements of layout.yaxis.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. tickson Determines where ticks and grid lines are drawn with respect to their corresponding tick labels. Only has an effect for axes of `type` "category" or "multicategory". When set to "boundaries", ticks and grid lines are drawn half a category to the left/bottom of labels. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.layout.yaxis.Title instance or dict with compatible properties titlefont Deprecated: Please use layout.yaxis.title.font instead. Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. type Sets the axis type. By default, plotly attempts to determined the axis type by looking into the data of the traces that referenced the axis in question. uirevision Controls persistence of user-driven changes in axis `range`, `autorange`, and `title` if in `editable: true` configuration. Defaults to `layout.uirevision`. visible A single toggle to hide the axis while preserving interaction like dragging. Default is true when a cheater plot is present on the axis, otherwise false zeroline Determines whether or not a line is drawn at along the 0 value of this axis. If True, the zero line is drawn on top of the grid lines. zerolinecolor Sets the line color of the zero line. zerolinewidth Sets the width (in px) of the zero line. Returns ------- YAxis """ super(YAxis, self).__init__("yaxis") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.YAxis constructor must be a dict or an instance of plotly.graph_objs.layout.YAxis""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout import yaxis as v_yaxis # Initialize validators # --------------------- self._validators["anchor"] = v_yaxis.AnchorValidator() self._validators["automargin"] = v_yaxis.AutomarginValidator() self._validators["autorange"] = v_yaxis.AutorangeValidator() self._validators["calendar"] = v_yaxis.CalendarValidator() self._validators["categoryarray"] = v_yaxis.CategoryarrayValidator() self._validators["categoryarraysrc"] = v_yaxis.CategoryarraysrcValidator() self._validators["categoryorder"] = v_yaxis.CategoryorderValidator() self._validators["color"] = v_yaxis.ColorValidator() self._validators["constrain"] = v_yaxis.ConstrainValidator() self._validators["constraintoward"] = v_yaxis.ConstraintowardValidator() self._validators["dividercolor"] = v_yaxis.DividercolorValidator() self._validators["dividerwidth"] = v_yaxis.DividerwidthValidator() self._validators["domain"] = v_yaxis.DomainValidator() self._validators["dtick"] = v_yaxis.DtickValidator() self._validators["exponentformat"] = v_yaxis.ExponentformatValidator() self._validators["fixedrange"] = v_yaxis.FixedrangeValidator() self._validators["gridcolor"] = v_yaxis.GridcolorValidator() self._validators["gridwidth"] = v_yaxis.GridwidthValidator() self._validators["hoverformat"] = v_yaxis.HoverformatValidator() self._validators["layer"] = v_yaxis.LayerValidator() self._validators["linecolor"] = v_yaxis.LinecolorValidator() self._validators["linewidth"] = v_yaxis.LinewidthValidator() self._validators["matches"] = v_yaxis.MatchesValidator() self._validators["mirror"] = v_yaxis.MirrorValidator() self._validators["nticks"] = v_yaxis.NticksValidator() self._validators["overlaying"] = v_yaxis.OverlayingValidator() self._validators["position"] = v_yaxis.PositionValidator() self._validators["range"] = v_yaxis.RangeValidator() self._validators["rangemode"] = v_yaxis.RangemodeValidator() self._validators["scaleanchor"] = v_yaxis.ScaleanchorValidator() self._validators["scaleratio"] = v_yaxis.ScaleratioValidator() self._validators["separatethousands"] = v_yaxis.SeparatethousandsValidator() self._validators["showdividers"] = v_yaxis.ShowdividersValidator() self._validators["showexponent"] = v_yaxis.ShowexponentValidator() self._validators["showgrid"] = v_yaxis.ShowgridValidator() self._validators["showline"] = v_yaxis.ShowlineValidator() self._validators["showspikes"] = v_yaxis.ShowspikesValidator() self._validators["showticklabels"] = v_yaxis.ShowticklabelsValidator() self._validators["showtickprefix"] = v_yaxis.ShowtickprefixValidator() self._validators["showticksuffix"] = v_yaxis.ShowticksuffixValidator() self._validators["side"] = v_yaxis.SideValidator() self._validators["spikecolor"] = v_yaxis.SpikecolorValidator() self._validators["spikedash"] = v_yaxis.SpikedashValidator() self._validators["spikemode"] = v_yaxis.SpikemodeValidator() self._validators["spikesnap"] = v_yaxis.SpikesnapValidator() self._validators["spikethickness"] = v_yaxis.SpikethicknessValidator() self._validators["tick0"] = v_yaxis.Tick0Validator() self._validators["tickangle"] = v_yaxis.TickangleValidator() self._validators["tickcolor"] = v_yaxis.TickcolorValidator() self._validators["tickfont"] = v_yaxis.TickfontValidator() self._validators["tickformat"] = v_yaxis.TickformatValidator() self._validators["tickformatstops"] = v_yaxis.TickformatstopsValidator() self._validators["tickformatstopdefaults"] = v_yaxis.TickformatstopValidator() self._validators["ticklen"] = v_yaxis.TicklenValidator() self._validators["tickmode"] = v_yaxis.TickmodeValidator() self._validators["tickprefix"] = v_yaxis.TickprefixValidator() self._validators["ticks"] = v_yaxis.TicksValidator() self._validators["tickson"] = v_yaxis.TicksonValidator() self._validators["ticksuffix"] = v_yaxis.TicksuffixValidator() self._validators["ticktext"] = v_yaxis.TicktextValidator() self._validators["ticktextsrc"] = v_yaxis.TicktextsrcValidator() self._validators["tickvals"] = v_yaxis.TickvalsValidator() self._validators["tickvalssrc"] = v_yaxis.TickvalssrcValidator() self._validators["tickwidth"] = v_yaxis.TickwidthValidator() self._validators["title"] = v_yaxis.TitleValidator() self._validators["type"] = v_yaxis.TypeValidator() self._validators["uirevision"] = v_yaxis.UirevisionValidator() self._validators["visible"] = v_yaxis.VisibleValidator() self._validators["zeroline"] = v_yaxis.ZerolineValidator() self._validators["zerolinecolor"] = v_yaxis.ZerolinecolorValidator() self._validators["zerolinewidth"] = v_yaxis.ZerolinewidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("anchor", None) self["anchor"] = anchor if anchor is not None else _v _v = arg.pop("automargin", None) self["automargin"] = automargin if automargin is not None else _v _v = arg.pop("autorange", None) self["autorange"] = autorange if autorange is not None else _v _v = arg.pop("calendar", None) self["calendar"] = calendar if calendar is not None else _v _v = arg.pop("categoryarray", None) self["categoryarray"] = categoryarray if categoryarray is not None else _v _v = arg.pop("categoryarraysrc", None) self["categoryarraysrc"] = ( categoryarraysrc if categoryarraysrc is not None else _v ) _v = arg.pop("categoryorder", None) self["categoryorder"] = categoryorder if categoryorder is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("constrain", None) self["constrain"] = constrain if constrain is not None else _v _v = arg.pop("constraintoward", None) self["constraintoward"] = constraintoward if constraintoward is not None else _v _v = arg.pop("dividercolor", None) self["dividercolor"] = dividercolor if dividercolor is not None else _v _v = arg.pop("dividerwidth", None) self["dividerwidth"] = dividerwidth if dividerwidth is not None else _v _v = arg.pop("domain", None) self["domain"] = domain if domain is not None else _v _v = arg.pop("dtick", None) self["dtick"] = dtick if dtick is not None else _v _v = arg.pop("exponentformat", None) self["exponentformat"] = exponentformat if exponentformat is not None else _v _v = arg.pop("fixedrange", None) self["fixedrange"] = fixedrange if fixedrange is not None else _v _v = arg.pop("gridcolor", None) self["gridcolor"] = gridcolor if gridcolor is not None else _v _v = arg.pop("gridwidth", None) self["gridwidth"] = gridwidth if gridwidth is not None else _v _v = arg.pop("hoverformat", None) self["hoverformat"] = hoverformat if hoverformat is not None else _v _v = arg.pop("layer", None) self["layer"] = layer if layer is not None else _v _v = arg.pop("linecolor", None) self["linecolor"] = linecolor if linecolor is not None else _v _v = arg.pop("linewidth", None) self["linewidth"] = linewidth if linewidth is not None else _v _v = arg.pop("matches", None) self["matches"] = matches if matches is not None else _v _v = arg.pop("mirror", None) self["mirror"] = mirror if mirror is not None else _v _v = arg.pop("nticks", None) self["nticks"] = nticks if nticks is not None else _v _v = arg.pop("overlaying", None) self["overlaying"] = overlaying if overlaying is not None else _v _v = arg.pop("position", None) self["position"] = position if position is not None else _v _v = arg.pop("range", None) self["range"] = range if range is not None else _v _v = arg.pop("rangemode", None) self["rangemode"] = rangemode if rangemode is not None else _v _v = arg.pop("scaleanchor", None) self["scaleanchor"] = scaleanchor if scaleanchor is not None else _v _v = arg.pop("scaleratio", None) self["scaleratio"] = scaleratio if scaleratio is not None else _v _v = arg.pop("separatethousands", None) self["separatethousands"] = ( separatethousands if separatethousands is not None else _v ) _v = arg.pop("showdividers", None) self["showdividers"] = showdividers if showdividers is not None else _v _v = arg.pop("showexponent", None) self["showexponent"] = showexponent if showexponent is not None else _v _v = arg.pop("showgrid", None) self["showgrid"] = showgrid if showgrid is not None else _v _v = arg.pop("showline", None) self["showline"] = showline if showline is not None else _v _v = arg.pop("showspikes", None) self["showspikes"] = showspikes if showspikes is not None else _v _v = arg.pop("showticklabels", None) self["showticklabels"] = showticklabels if showticklabels is not None else _v _v = arg.pop("showtickprefix", None) self["showtickprefix"] = showtickprefix if showtickprefix is not None else _v _v = arg.pop("showticksuffix", None) self["showticksuffix"] = showticksuffix if showticksuffix is not None else _v _v = arg.pop("side", None) self["side"] = side if side is not None else _v _v = arg.pop("spikecolor", None) self["spikecolor"] = spikecolor if spikecolor is not None else _v _v = arg.pop("spikedash", None) self["spikedash"] = spikedash if spikedash is not None else _v _v = arg.pop("spikemode", None) self["spikemode"] = spikemode if spikemode is not None else _v _v = arg.pop("spikesnap", None) self["spikesnap"] = spikesnap if spikesnap is not None else _v _v = arg.pop("spikethickness", None) self["spikethickness"] = spikethickness if spikethickness is not None else _v _v = arg.pop("tick0", None) self["tick0"] = tick0 if tick0 is not None else _v _v = arg.pop("tickangle", None) self["tickangle"] = tickangle if tickangle is not None else _v _v = arg.pop("tickcolor", None) self["tickcolor"] = tickcolor if tickcolor is not None else _v _v = arg.pop("tickfont", None) self["tickfont"] = tickfont if tickfont is not None else _v _v = arg.pop("tickformat", None) self["tickformat"] = tickformat if tickformat is not None else _v _v = arg.pop("tickformatstops", None) self["tickformatstops"] = tickformatstops if tickformatstops is not None else _v _v = arg.pop("tickformatstopdefaults", None) self["tickformatstopdefaults"] = ( tickformatstopdefaults if tickformatstopdefaults is not None else _v ) _v = arg.pop("ticklen", None) self["ticklen"] = ticklen if ticklen is not None else _v _v = arg.pop("tickmode", None) self["tickmode"] = tickmode if tickmode is not None else _v _v = arg.pop("tickprefix", None) self["tickprefix"] = tickprefix if tickprefix is not None else _v _v = arg.pop("ticks", None) self["ticks"] = ticks if ticks is not None else _v _v = arg.pop("tickson", None) self["tickson"] = tickson if tickson is not None else _v _v = arg.pop("ticksuffix", None) self["ticksuffix"] = ticksuffix if ticksuffix is not None else _v _v = arg.pop("ticktext", None) self["ticktext"] = ticktext if ticktext is not None else _v _v = arg.pop("ticktextsrc", None) self["ticktextsrc"] = ticktextsrc if ticktextsrc is not None else _v _v = arg.pop("tickvals", None) self["tickvals"] = tickvals if tickvals is not None else _v _v = arg.pop("tickvalssrc", None) self["tickvalssrc"] = tickvalssrc if tickvalssrc is not None else _v _v = arg.pop("tickwidth", None) self["tickwidth"] = tickwidth if tickwidth is not None else _v _v = arg.pop("title", None) self["title"] = title if title is not None else _v _v = arg.pop("titlefont", None) _v = titlefont if titlefont is not None else _v if _v is not None: self["titlefont"] = _v _v = arg.pop("type", None) self["type"] = type if type is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("zeroline", None) self["zeroline"] = zeroline if zeroline is not None else _v _v = arg.pop("zerolinecolor", None) self["zerolinecolor"] = zerolinecolor if zerolinecolor is not None else _v _v = arg.pop("zerolinewidth", None) self["zerolinewidth"] = zerolinewidth if zerolinewidth is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class XAxis(_BaseLayoutHierarchyType): # anchor # ------ @property def anchor(self): """ If set to an opposite-letter axis id (e.g. `x2`, `y`), this axis is bound to the corresponding opposite-letter axis. If set to "free", this axis' position is determined by `position`. The 'anchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['free'] - A string that matches one of the following regular expressions: ['^x([2-9]|[1-9][0-9]+)?$', '^y([2-9]|[1-9][0-9]+)?$'] Returns ------- Any """ return self["anchor"] @anchor.setter def anchor(self, val): self["anchor"] = val # automargin # ---------- @property def automargin(self): """ Determines whether long tick labels automatically grow the figure margins. The 'automargin' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["automargin"] @automargin.setter def automargin(self, val): self["automargin"] = val # autorange # --------- @property def autorange(self): """ Determines whether or not the range of this axis is computed in relation to the input data. See `rangemode` for more info. If `range` is provided, then `autorange` is set to False. The 'autorange' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'reversed'] Returns ------- Any """ return self["autorange"] @autorange.setter def autorange(self, val): self["autorange"] = val # calendar # -------- @property def calendar(self): """ Sets the calendar system to use for `range` and `tick0` if this is a date axis. This does not set the calendar for interpreting data on this axis, that's specified in the trace or via the global `layout.calendar` The 'calendar' property is an enumeration that may be specified as: - One of the following enumeration values: ['gregorian', 'chinese', 'coptic', 'discworld', 'ethiopian', 'hebrew', 'islamic', 'julian', 'mayan', 'nanakshahi', 'nepali', 'persian', 'jalali', 'taiwan', 'thai', 'ummalqura'] Returns ------- Any """ return self["calendar"] @calendar.setter def calendar(self, val): self["calendar"] = val # categoryarray # ------------- @property def categoryarray(self): """ Sets the order in which categories on this axis appear. Only has an effect if `categoryorder` is set to "array". Used with `categoryorder`. The 'categoryarray' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["categoryarray"] @categoryarray.setter def categoryarray(self, val): self["categoryarray"] = val # categoryarraysrc # ---------------- @property def categoryarraysrc(self): """ Sets the source reference on plot.ly for categoryarray . The 'categoryarraysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["categoryarraysrc"] @categoryarraysrc.setter def categoryarraysrc(self, val): self["categoryarraysrc"] = val # categoryorder # ------------- @property def categoryorder(self): """ Specifies the ordering logic for the case of categorical variables. By default, plotly uses "trace", which specifies the order that is present in the data supplied. Set `categoryorder` to *category ascending* or *category descending* if order should be determined by the alphanumerical order of the category names. Set `categoryorder` to "array" to derive the ordering from the attribute `categoryarray`. If a category is not found in the `categoryarray` array, the sorting behavior for that attribute will be identical to the "trace" mode. The unspecified categories will follow the categories in `categoryarray`. Set `categoryorder` to *total ascending* or *total descending* if order should be determined by the numerical order of the values. Similarly, the order can be determined by the min, max, sum, mean or median of all the values. The 'categoryorder' property is an enumeration that may be specified as: - One of the following enumeration values: ['trace', 'category ascending', 'category descending', 'array', 'total ascending', 'total descending', 'min ascending', 'min descending', 'max ascending', 'max descending', 'sum ascending', 'sum descending', 'mean ascending', 'mean descending', 'median ascending', 'median descending'] Returns ------- Any """ return self["categoryorder"] @categoryorder.setter def categoryorder(self, val): self["categoryorder"] = val # color # ----- @property def color(self): """ Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # constrain # --------- @property def constrain(self): """ If this axis needs to be compressed (either due to its own `scaleanchor` and `scaleratio` or those of the other axis), determines how that happens: by increasing the "range" (default), or by decreasing the "domain". The 'constrain' property is an enumeration that may be specified as: - One of the following enumeration values: ['range', 'domain'] Returns ------- Any """ return self["constrain"] @constrain.setter def constrain(self, val): self["constrain"] = val # constraintoward # --------------- @property def constraintoward(self): """ If this axis needs to be compressed (either due to its own `scaleanchor` and `scaleratio` or those of the other axis), determines which direction we push the originally specified plot area. Options are "left", "center" (default), and "right" for x axes, and "top", "middle" (default), and "bottom" for y axes. The 'constraintoward' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'center', 'right', 'top', 'middle', 'bottom'] Returns ------- Any """ return self["constraintoward"] @constraintoward.setter def constraintoward(self, val): self["constraintoward"] = val # dividercolor # ------------ @property def dividercolor(self): """ Sets the color of the dividers Only has an effect on "multicategory" axes. The 'dividercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["dividercolor"] @dividercolor.setter def dividercolor(self, val): self["dividercolor"] = val # dividerwidth # ------------ @property def dividerwidth(self): """ Sets the width (in px) of the dividers Only has an effect on "multicategory" axes. The 'dividerwidth' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["dividerwidth"] @dividerwidth.setter def dividerwidth(self, val): self["dividerwidth"] = val # domain # ------ @property def domain(self): """ Sets the domain of this axis (in plot fraction). The 'domain' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'domain[0]' property is a number and may be specified as: - An int or float in the interval [0, 1] (1) The 'domain[1]' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- list """ return self["domain"] @domain.setter def domain(self, val): self["domain"] = val # dtick # ----- @property def dtick(self): """ Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" The 'dtick' property accepts values of any type Returns ------- Any """ return self["dtick"] @dtick.setter def dtick(self, val): self["dtick"] = val # exponentformat # -------------- @property def exponentformat(self): """ Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. The 'exponentformat' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'e', 'E', 'power', 'SI', 'B'] Returns ------- Any """ return self["exponentformat"] @exponentformat.setter def exponentformat(self, val): self["exponentformat"] = val # fixedrange # ---------- @property def fixedrange(self): """ Determines whether or not this axis is zoom-able. If true, then zoom is disabled. The 'fixedrange' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["fixedrange"] @fixedrange.setter def fixedrange(self, val): self["fixedrange"] = val # gridcolor # --------- @property def gridcolor(self): """ Sets the color of the grid lines. The 'gridcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["gridcolor"] @gridcolor.setter def gridcolor(self, val): self["gridcolor"] = val # gridwidth # --------- @property def gridwidth(self): """ Sets the width (in px) of the grid lines. The 'gridwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["gridwidth"] @gridwidth.setter def gridwidth(self, val): self["gridwidth"] = val # hoverformat # ----------- @property def hoverformat(self): """ Sets the hover text formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'hoverformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["hoverformat"] @hoverformat.setter def hoverformat(self, val): self["hoverformat"] = val # layer # ----- @property def layer(self): """ Sets the layer on which this axis is displayed. If *above traces*, this axis is displayed above all the subplot's traces If *below traces*, this axis is displayed below all the subplot's traces, but above the grid lines. Useful when used together with scatter-like traces with `cliponaxis` set to False to show markers and/or text nodes above this axis. The 'layer' property is an enumeration that may be specified as: - One of the following enumeration values: ['above traces', 'below traces'] Returns ------- Any """ return self["layer"] @layer.setter def layer(self, val): self["layer"] = val # linecolor # --------- @property def linecolor(self): """ Sets the axis line color. The 'linecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["linecolor"] @linecolor.setter def linecolor(self, val): self["linecolor"] = val # linewidth # --------- @property def linewidth(self): """ Sets the width (in px) of the axis line. The 'linewidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["linewidth"] @linewidth.setter def linewidth(self, val): self["linewidth"] = val # matches # ------- @property def matches(self): """ If set to another axis id (e.g. `x2`, `y`), the range of this axis will match the range of the corresponding axis in data- coordinates space. Moreover, matching axes share auto-range values, category lists and histogram auto-bins. Note that setting axes simultaneously in both a `scaleanchor` and a `matches` constraint is currently forbidden. Moreover, note that matching axes must have the same `type`. The 'matches' property is an enumeration that may be specified as: - A string that matches one of the following regular expressions: ['^x([2-9]|[1-9][0-9]+)?$', '^y([2-9]|[1-9][0-9]+)?$'] Returns ------- Any """ return self["matches"] @matches.setter def matches(self, val): self["matches"] = val # mirror # ------ @property def mirror(self): """ Determines if the axis lines or/and ticks are mirrored to the opposite side of the plotting area. If True, the axis lines are mirrored. If "ticks", the axis lines and ticks are mirrored. If False, mirroring is disable. If "all", axis lines are mirrored on all shared-axes subplots. If "allticks", axis lines and ticks are mirrored on all shared-axes subplots. The 'mirror' property is an enumeration that may be specified as: - One of the following enumeration values: [True, 'ticks', False, 'all', 'allticks'] Returns ------- Any """ return self["mirror"] @mirror.setter def mirror(self, val): self["mirror"] = val # nticks # ------ @property def nticks(self): """ Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". The 'nticks' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nticks"] @nticks.setter def nticks(self, val): self["nticks"] = val # overlaying # ---------- @property def overlaying(self): """ If set a same-letter axis id, this axis is overlaid on top of the corresponding same-letter axis, with traces and axes visible for both axes. If False, this axis does not overlay any same-letter axes. In this case, for axes with overlapping domains only the highest-numbered axis will be visible. The 'overlaying' property is an enumeration that may be specified as: - One of the following enumeration values: ['free'] - A string that matches one of the following regular expressions: ['^x([2-9]|[1-9][0-9]+)?$', '^y([2-9]|[1-9][0-9]+)?$'] Returns ------- Any """ return self["overlaying"] @overlaying.setter def overlaying(self, val): self["overlaying"] = val # position # -------- @property def position(self): """ Sets the position of this axis in the plotting space (in normalized coordinates). Only has an effect if `anchor` is set to "free". The 'position' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["position"] @position.setter def position(self, val): self["position"] = val # range # ----- @property def range(self): """ Sets the range of this axis. If the axis `type` is "log", then you must take the log of your desired range (e.g. to set the range from 1 to 100, set the range from 0 to 2). If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. The 'range' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'range[0]' property accepts values of any type (1) The 'range[1]' property accepts values of any type Returns ------- list """ return self["range"] @range.setter def range(self, val): self["range"] = val # rangemode # --------- @property def rangemode(self): """ If "normal", the range is computed in relation to the extrema of the input data. If *tozero*`, the range extends to 0, regardless of the input data If "nonnegative", the range is non-negative, regardless of the input data. Applies only to linear axes. The 'rangemode' property is an enumeration that may be specified as: - One of the following enumeration values: ['normal', 'tozero', 'nonnegative'] Returns ------- Any """ return self["rangemode"] @rangemode.setter def rangemode(self, val): self["rangemode"] = val # rangeselector # ------------- @property def rangeselector(self): """ The 'rangeselector' property is an instance of Rangeselector that may be specified as: - An instance of plotly.graph_objs.layout.xaxis.Rangeselector - A dict of string/value properties that will be passed to the Rangeselector constructor Supported dict properties: activecolor Sets the background color of the active range selector button. bgcolor Sets the background color of the range selector buttons. bordercolor Sets the color of the border enclosing the range selector. borderwidth Sets the width (in px) of the border enclosing the range selector. buttons Sets the specifications for each buttons. By default, a range selector comes with no buttons. buttondefaults When used in a template (as layout.template.lay out.xaxis.rangeselector.buttondefaults), sets the default property values to use for elements of layout.xaxis.rangeselector.buttons font Sets the font of the range selector button text. visible Determines whether or not this range selector is visible. Note that range selectors are only available for x axes of `type` set to or auto- typed to "date". x Sets the x position (in normalized coordinates) of the range selector. xanchor Sets the range selector's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the range selector. y Sets the y position (in normalized coordinates) of the range selector. yanchor Sets the range selector's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the range selector. Returns ------- plotly.graph_objs.layout.xaxis.Rangeselector """ return self["rangeselector"] @rangeselector.setter def rangeselector(self, val): self["rangeselector"] = val # rangeslider # ----------- @property def rangeslider(self): """ The 'rangeslider' property is an instance of Rangeslider that may be specified as: - An instance of plotly.graph_objs.layout.xaxis.Rangeslider - A dict of string/value properties that will be passed to the Rangeslider constructor Supported dict properties: autorange Determines whether or not the range slider range is computed in relation to the input data. If `range` is provided, then `autorange` is set to False. bgcolor Sets the background color of the range slider. bordercolor Sets the border color of the range slider. borderwidth Sets the border width of the range slider. range Sets the range of the range slider. If not set, defaults to the full xaxis range. If the axis `type` is "log", then you must take the log of your desired range. If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. thickness The height of the range slider as a fraction of the total plot area height. visible Determines whether or not the range slider will be visible. If visible, perpendicular axes will be set to `fixedrange` yaxis plotly.graph_objects.layout.xaxis.rangeslider.Y Axis instance or dict with compatible properties Returns ------- plotly.graph_objs.layout.xaxis.Rangeslider """ return self["rangeslider"] @rangeslider.setter def rangeslider(self, val): self["rangeslider"] = val # scaleanchor # ----------- @property def scaleanchor(self): """ If set to another axis id (e.g. `x2`, `y`), the range of this axis changes together with the range of the corresponding axis such that the scale of pixels per unit is in a constant ratio. Both axes are still zoomable, but when you zoom one, the other will zoom the same amount, keeping a fixed midpoint. `constrain` and `constraintoward` determine how we enforce the constraint. You can chain these, ie `yaxis: {scaleanchor: *x*}, xaxis2: {scaleanchor: *y*}` but you can only link axes of the same `type`. The linked axis can have the opposite letter (to constrain the aspect ratio) or the same letter (to match scales across subplots). Loops (`yaxis: {scaleanchor: *x*}, xaxis: {scaleanchor: *y*}` or longer) are redundant and the last constraint encountered will be ignored to avoid possible inconsistent constraints via `scaleratio`. Note that setting axes simultaneously in both a `scaleanchor` and a `matches` constraint is currently forbidden. The 'scaleanchor' property is an enumeration that may be specified as: - A string that matches one of the following regular expressions: ['^x([2-9]|[1-9][0-9]+)?$', '^y([2-9]|[1-9][0-9]+)?$'] Returns ------- Any """ return self["scaleanchor"] @scaleanchor.setter def scaleanchor(self, val): self["scaleanchor"] = val # scaleratio # ---------- @property def scaleratio(self): """ If this axis is linked to another by `scaleanchor`, this determines the pixel to unit scale ratio. For example, if this value is 10, then every unit on this axis spans 10 times the number of pixels as a unit on the linked axis. Use this for example to create an elevation profile where the vertical scale is exaggerated a fixed amount with respect to the horizontal. The 'scaleratio' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["scaleratio"] @scaleratio.setter def scaleratio(self, val): self["scaleratio"] = val # separatethousands # ----------------- @property def separatethousands(self): """ If "true", even 4-digit integers are separated The 'separatethousands' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["separatethousands"] @separatethousands.setter def separatethousands(self, val): self["separatethousands"] = val # showdividers # ------------ @property def showdividers(self): """ Determines whether or not a dividers are drawn between the category levels of this axis. Only has an effect on "multicategory" axes. The 'showdividers' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showdividers"] @showdividers.setter def showdividers(self, val): self["showdividers"] = val # showexponent # ------------ @property def showexponent(self): """ If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. The 'showexponent' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showexponent"] @showexponent.setter def showexponent(self, val): self["showexponent"] = val # showgrid # -------- @property def showgrid(self): """ Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. The 'showgrid' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showgrid"] @showgrid.setter def showgrid(self, val): self["showgrid"] = val # showline # -------- @property def showline(self): """ Determines whether or not a line bounding this axis is drawn. The 'showline' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showline"] @showline.setter def showline(self, val): self["showline"] = val # showspikes # ---------- @property def showspikes(self): """ Determines whether or not spikes (aka droplines) are drawn for this axis. Note: This only takes affect when hovermode = closest The 'showspikes' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showspikes"] @showspikes.setter def showspikes(self, val): self["showspikes"] = val # showticklabels # -------------- @property def showticklabels(self): """ Determines whether or not the tick labels are drawn. The 'showticklabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showticklabels"] @showticklabels.setter def showticklabels(self, val): self["showticklabels"] = val # showtickprefix # -------------- @property def showtickprefix(self): """ If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. The 'showtickprefix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showtickprefix"] @showtickprefix.setter def showtickprefix(self, val): self["showtickprefix"] = val # showticksuffix # -------------- @property def showticksuffix(self): """ Same as `showtickprefix` but for tick suffixes. The 'showticksuffix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showticksuffix"] @showticksuffix.setter def showticksuffix(self, val): self["showticksuffix"] = val # side # ---- @property def side(self): """ Determines whether a x (y) axis is positioned at the "bottom" ("left") or "top" ("right") of the plotting area. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['top', 'bottom', 'left', 'right'] Returns ------- Any """ return self["side"] @side.setter def side(self, val): self["side"] = val # spikecolor # ---------- @property def spikecolor(self): """ Sets the spike color. If undefined, will use the series color The 'spikecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["spikecolor"] @spikecolor.setter def spikecolor(self, val): self["spikecolor"] = val # spikedash # --------- @property def spikedash(self): """ Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). The 'spikedash' property is a string and must be specified as: - One of the following strings: ['solid', 'dot', 'dash', 'longdash', 'dashdot', 'longdashdot'] - A number that will be converted to a string Returns ------- str """ return self["spikedash"] @spikedash.setter def spikedash(self, val): self["spikedash"] = val # spikemode # --------- @property def spikemode(self): """ Determines the drawing mode for the spike line If "toaxis", the line is drawn from the data point to the axis the series is plotted on. If "across", the line is drawn across the entire plot area, and supercedes "toaxis". If "marker", then a marker dot is drawn on the axis the series is plotted on The 'spikemode' property is a flaglist and may be specified as a string containing: - Any combination of ['toaxis', 'across', 'marker'] joined with '+' characters (e.g. 'toaxis+across') Returns ------- Any """ return self["spikemode"] @spikemode.setter def spikemode(self, val): self["spikemode"] = val # spikesnap # --------- @property def spikesnap(self): """ Determines whether spikelines are stuck to the cursor or to the closest datapoints. The 'spikesnap' property is an enumeration that may be specified as: - One of the following enumeration values: ['data', 'cursor'] Returns ------- Any """ return self["spikesnap"] @spikesnap.setter def spikesnap(self, val): self["spikesnap"] = val # spikethickness # -------------- @property def spikethickness(self): """ Sets the width (in px) of the zero line. The 'spikethickness' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["spikethickness"] @spikethickness.setter def spikethickness(self, val): self["spikethickness"] = val # tick0 # ----- @property def tick0(self): """ Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. The 'tick0' property accepts values of any type Returns ------- Any """ return self["tick0"] @tick0.setter def tick0(self, val): self["tick0"] = val # tickangle # --------- @property def tickangle(self): """ Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. The 'tickangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["tickangle"] @tickangle.setter def tickangle(self, val): self["tickangle"] = val # tickcolor # --------- @property def tickcolor(self): """ Sets the tick color. The 'tickcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["tickcolor"] @tickcolor.setter def tickcolor(self, val): self["tickcolor"] = val # tickfont # -------- @property def tickfont(self): """ Sets the tick font. The 'tickfont' property is an instance of Tickfont that may be specified as: - An instance of plotly.graph_objs.layout.xaxis.Tickfont - A dict of string/value properties that will be passed to the Tickfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.layout.xaxis.Tickfont """ return self["tickfont"] @tickfont.setter def tickfont(self, val): self["tickfont"] = val # tickformat # ---------- @property def tickformat(self): """ Sets the tick label formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'tickformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickformat"] @tickformat.setter def tickformat(self, val): self["tickformat"] = val # tickformatstops # --------------- @property def tickformatstops(self): """ The 'tickformatstops' property is a tuple of instances of Tickformatstop that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.xaxis.Tickformatstop - A list or tuple of dicts of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- tuple[plotly.graph_objs.layout.xaxis.Tickformatstop] """ return self["tickformatstops"] @tickformatstops.setter def tickformatstops(self, val): self["tickformatstops"] = val # tickformatstopdefaults # ---------------------- @property def tickformatstopdefaults(self): """ When used in a template (as layout.template.layout.xaxis.tickformatstopdefaults), sets the default property values to use for elements of layout.xaxis.tickformatstops The 'tickformatstopdefaults' property is an instance of Tickformatstop that may be specified as: - An instance of plotly.graph_objs.layout.xaxis.Tickformatstop - A dict of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: Returns ------- plotly.graph_objs.layout.xaxis.Tickformatstop """ return self["tickformatstopdefaults"] @tickformatstopdefaults.setter def tickformatstopdefaults(self, val): self["tickformatstopdefaults"] = val # ticklen # ------- @property def ticklen(self): """ Sets the tick length (in px). The 'ticklen' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ticklen"] @ticklen.setter def ticklen(self, val): self["ticklen"] = val # tickmode # -------- @property def tickmode(self): """ Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). The 'tickmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'linear', 'array'] Returns ------- Any """ return self["tickmode"] @tickmode.setter def tickmode(self, val): self["tickmode"] = val # tickprefix # ---------- @property def tickprefix(self): """ Sets a tick label prefix. The 'tickprefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickprefix"] @tickprefix.setter def tickprefix(self, val): self["tickprefix"] = val # ticks # ----- @property def ticks(self): """ Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. The 'ticks' property is an enumeration that may be specified as: - One of the following enumeration values: ['outside', 'inside', ''] Returns ------- Any """ return self["ticks"] @ticks.setter def ticks(self, val): self["ticks"] = val # tickson # ------- @property def tickson(self): """ Determines where ticks and grid lines are drawn with respect to their corresponding tick labels. Only has an effect for axes of `type` "category" or "multicategory". When set to "boundaries", ticks and grid lines are drawn half a category to the left/bottom of labels. The 'tickson' property is an enumeration that may be specified as: - One of the following enumeration values: ['labels', 'boundaries'] Returns ------- Any """ return self["tickson"] @tickson.setter def tickson(self, val): self["tickson"] = val # ticksuffix # ---------- @property def ticksuffix(self): """ Sets a tick label suffix. The 'ticksuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ticksuffix"] @ticksuffix.setter def ticksuffix(self, val): self["ticksuffix"] = val # ticktext # -------- @property def ticktext(self): """ Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. The 'ticktext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ticktext"] @ticktext.setter def ticktext(self, val): self["ticktext"] = val # ticktextsrc # ----------- @property def ticktextsrc(self): """ Sets the source reference on plot.ly for ticktext . The 'ticktextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ticktextsrc"] @ticktextsrc.setter def ticktextsrc(self, val): self["ticktextsrc"] = val # tickvals # -------- @property def tickvals(self): """ Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. The 'tickvals' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["tickvals"] @tickvals.setter def tickvals(self, val): self["tickvals"] = val # tickvalssrc # ----------- @property def tickvalssrc(self): """ Sets the source reference on plot.ly for tickvals . The 'tickvalssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tickvalssrc"] @tickvalssrc.setter def tickvalssrc(self, val): self["tickvalssrc"] = val # tickwidth # --------- @property def tickwidth(self): """ Sets the tick width (in px). The 'tickwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["tickwidth"] @tickwidth.setter def tickwidth(self, val): self["tickwidth"] = val # title # ----- @property def title(self): """ The 'title' property is an instance of Title that may be specified as: - An instance of plotly.graph_objs.layout.xaxis.Title - A dict of string/value properties that will be passed to the Title constructor Supported dict properties: font Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. standoff Sets the standoff distance (in px) between the axis labels and the title text The default value is a function of the axis tick labels, the title `font.size` and the axis `linewidth`. Note that the axis title position is always constrained within the margins, so the actual standoff distance is always less than the set or default value. By setting `standoff` and turning on `automargin`, plotly.js will push the margins to fit the axis title at given standoff distance. text Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- plotly.graph_objs.layout.xaxis.Title """ return self["title"] @title.setter def title(self, val): self["title"] = val # titlefont # --------- @property def titlefont(self): """ Deprecated: Please use layout.xaxis.title.font instead. Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.layout.xaxis.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- """ return self["titlefont"] @titlefont.setter def titlefont(self, val): self["titlefont"] = val # type # ---- @property def type(self): """ Sets the axis type. By default, plotly attempts to determined the axis type by looking into the data of the traces that referenced the axis in question. The 'type' property is an enumeration that may be specified as: - One of the following enumeration values: ['-', 'linear', 'log', 'date', 'category', 'multicategory'] Returns ------- Any """ return self["type"] @type.setter def type(self, val): self["type"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of user-driven changes in axis `range`, `autorange`, and `title` if in `editable: true` configuration. Defaults to `layout.uirevision`. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # visible # ------- @property def visible(self): """ A single toggle to hide the axis while preserving interaction like dragging. Default is true when a cheater plot is present on the axis, otherwise false The 'visible' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # zeroline # -------- @property def zeroline(self): """ Determines whether or not a line is drawn at along the 0 value of this axis. If True, the zero line is drawn on top of the grid lines. The 'zeroline' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["zeroline"] @zeroline.setter def zeroline(self, val): self["zeroline"] = val # zerolinecolor # ------------- @property def zerolinecolor(self): """ Sets the line color of the zero line. The 'zerolinecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["zerolinecolor"] @zerolinecolor.setter def zerolinecolor(self, val): self["zerolinecolor"] = val # zerolinewidth # ------------- @property def zerolinewidth(self): """ Sets the width (in px) of the zero line. The 'zerolinewidth' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["zerolinewidth"] @zerolinewidth.setter def zerolinewidth(self, val): self["zerolinewidth"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ anchor If set to an opposite-letter axis id (e.g. `x2`, `y`), this axis is bound to the corresponding opposite-letter axis. If set to "free", this axis' position is determined by `position`. automargin Determines whether long tick labels automatically grow the figure margins. autorange Determines whether or not the range of this axis is computed in relation to the input data. See `rangemode` for more info. If `range` is provided, then `autorange` is set to False. calendar Sets the calendar system to use for `range` and `tick0` if this is a date axis. This does not set the calendar for interpreting data on this axis, that's specified in the trace or via the global `layout.calendar` categoryarray Sets the order in which categories on this axis appear. Only has an effect if `categoryorder` is set to "array". Used with `categoryorder`. categoryarraysrc Sets the source reference on plot.ly for categoryarray . categoryorder Specifies the ordering logic for the case of categorical variables. By default, plotly uses "trace", which specifies the order that is present in the data supplied. Set `categoryorder` to *category ascending* or *category descending* if order should be determined by the alphanumerical order of the category names. Set `categoryorder` to "array" to derive the ordering from the attribute `categoryarray`. If a category is not found in the `categoryarray` array, the sorting behavior for that attribute will be identical to the "trace" mode. The unspecified categories will follow the categories in `categoryarray`. Set `categoryorder` to *total ascending* or *total descending* if order should be determined by the numerical order of the values. Similarly, the order can be determined by the min, max, sum, mean or median of all the values. color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. constrain If this axis needs to be compressed (either due to its own `scaleanchor` and `scaleratio` or those of the other axis), determines how that happens: by increasing the "range" (default), or by decreasing the "domain". constraintoward If this axis needs to be compressed (either due to its own `scaleanchor` and `scaleratio` or those of the other axis), determines which direction we push the originally specified plot area. Options are "left", "center" (default), and "right" for x axes, and "top", "middle" (default), and "bottom" for y axes. dividercolor Sets the color of the dividers Only has an effect on "multicategory" axes. dividerwidth Sets the width (in px) of the dividers Only has an effect on "multicategory" axes. domain Sets the domain of this axis (in plot fraction). dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. fixedrange Determines whether or not this axis is zoom-able. If true, then zoom is disabled. gridcolor Sets the color of the grid lines. gridwidth Sets the width (in px) of the grid lines. hoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" layer Sets the layer on which this axis is displayed. If *above traces*, this axis is displayed above all the subplot's traces If *below traces*, this axis is displayed below all the subplot's traces, but above the grid lines. Useful when used together with scatter-like traces with `cliponaxis` set to False to show markers and/or text nodes above this axis. linecolor Sets the axis line color. linewidth Sets the width (in px) of the axis line. matches If set to another axis id (e.g. `x2`, `y`), the range of this axis will match the range of the corresponding axis in data-coordinates space. Moreover, matching axes share auto-range values, category lists and histogram auto-bins. Note that setting axes simultaneously in both a `scaleanchor` and a `matches` constraint is currently forbidden. Moreover, note that matching axes must have the same `type`. mirror Determines if the axis lines or/and ticks are mirrored to the opposite side of the plotting area. If True, the axis lines are mirrored. If "ticks", the axis lines and ticks are mirrored. If False, mirroring is disable. If "all", axis lines are mirrored on all shared-axes subplots. If "allticks", axis lines and ticks are mirrored on all shared-axes subplots. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". overlaying If set a same-letter axis id, this axis is overlaid on top of the corresponding same-letter axis, with traces and axes visible for both axes. If False, this axis does not overlay any same-letter axes. In this case, for axes with overlapping domains only the highest- numbered axis will be visible. position Sets the position of this axis in the plotting space (in normalized coordinates). Only has an effect if `anchor` is set to "free". range Sets the range of this axis. If the axis `type` is "log", then you must take the log of your desired range (e.g. to set the range from 1 to 100, set the range from 0 to 2). If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. rangemode If "normal", the range is computed in relation to the extrema of the input data. If *tozero*`, the range extends to 0, regardless of the input data If "nonnegative", the range is non-negative, regardless of the input data. Applies only to linear axes. rangeselector plotly.graph_objects.layout.xaxis.Rangeselector instance or dict with compatible properties rangeslider plotly.graph_objects.layout.xaxis.Rangeslider instance or dict with compatible properties scaleanchor If set to another axis id (e.g. `x2`, `y`), the range of this axis changes together with the range of the corresponding axis such that the scale of pixels per unit is in a constant ratio. Both axes are still zoomable, but when you zoom one, the other will zoom the same amount, keeping a fixed midpoint. `constrain` and `constraintoward` determine how we enforce the constraint. You can chain these, ie `yaxis: {scaleanchor: *x*}, xaxis2: {scaleanchor: *y*}` but you can only link axes of the same `type`. The linked axis can have the opposite letter (to constrain the aspect ratio) or the same letter (to match scales across subplots). Loops (`yaxis: {scaleanchor: *x*}, xaxis: {scaleanchor: *y*}` or longer) are redundant and the last constraint encountered will be ignored to avoid possible inconsistent constraints via `scaleratio`. Note that setting axes simultaneously in both a `scaleanchor` and a `matches` constraint is currently forbidden. scaleratio If this axis is linked to another by `scaleanchor`, this determines the pixel to unit scale ratio. For example, if this value is 10, then every unit on this axis spans 10 times the number of pixels as a unit on the linked axis. Use this for example to create an elevation profile where the vertical scale is exaggerated a fixed amount with respect to the horizontal. separatethousands If "true", even 4-digit integers are separated showdividers Determines whether or not a dividers are drawn between the category levels of this axis. Only has an effect on "multicategory" axes. showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showgrid Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. showline Determines whether or not a line bounding this axis is drawn. showspikes Determines whether or not spikes (aka droplines) are drawn for this axis. Note: This only takes affect when hovermode = closest showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. side Determines whether a x (y) axis is positioned at the "bottom" ("left") or "top" ("right") of the plotting area. spikecolor Sets the spike color. If undefined, will use the series color spikedash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). spikemode Determines the drawing mode for the spike line If "toaxis", the line is drawn from the data point to the axis the series is plotted on. If "across", the line is drawn across the entire plot area, and supercedes "toaxis". If "marker", then a marker dot is drawn on the axis the series is plotted on spikesnap Determines whether spikelines are stuck to the cursor or to the closest datapoints. spikethickness Sets the width (in px) of the zero line. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the tick font. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.layout.xaxis.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.layout.xaxis.tickformatstopdefaults), sets the default property values to use for elements of layout.xaxis.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. tickson Determines where ticks and grid lines are drawn with respect to their corresponding tick labels. Only has an effect for axes of `type` "category" or "multicategory". When set to "boundaries", ticks and grid lines are drawn half a category to the left/bottom of labels. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.layout.xaxis.Title instance or dict with compatible properties titlefont Deprecated: Please use layout.xaxis.title.font instead. Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. type Sets the axis type. By default, plotly attempts to determined the axis type by looking into the data of the traces that referenced the axis in question. uirevision Controls persistence of user-driven changes in axis `range`, `autorange`, and `title` if in `editable: true` configuration. Defaults to `layout.uirevision`. visible A single toggle to hide the axis while preserving interaction like dragging. Default is true when a cheater plot is present on the axis, otherwise false zeroline Determines whether or not a line is drawn at along the 0 value of this axis. If True, the zero line is drawn on top of the grid lines. zerolinecolor Sets the line color of the zero line. zerolinewidth Sets the width (in px) of the zero line. """ _mapped_properties = {"titlefont": ("title", "font")} def __init__( self, arg=None, anchor=None, automargin=None, autorange=None, calendar=None, categoryarray=None, categoryarraysrc=None, categoryorder=None, color=None, constrain=None, constraintoward=None, dividercolor=None, dividerwidth=None, domain=None, dtick=None, exponentformat=None, fixedrange=None, gridcolor=None, gridwidth=None, hoverformat=None, layer=None, linecolor=None, linewidth=None, matches=None, mirror=None, nticks=None, overlaying=None, position=None, range=None, rangemode=None, rangeselector=None, rangeslider=None, scaleanchor=None, scaleratio=None, separatethousands=None, showdividers=None, showexponent=None, showgrid=None, showline=None, showspikes=None, showticklabels=None, showtickprefix=None, showticksuffix=None, side=None, spikecolor=None, spikedash=None, spikemode=None, spikesnap=None, spikethickness=None, tick0=None, tickangle=None, tickcolor=None, tickfont=None, tickformat=None, tickformatstops=None, tickformatstopdefaults=None, ticklen=None, tickmode=None, tickprefix=None, ticks=None, tickson=None, ticksuffix=None, ticktext=None, ticktextsrc=None, tickvals=None, tickvalssrc=None, tickwidth=None, title=None, titlefont=None, type=None, uirevision=None, visible=None, zeroline=None, zerolinecolor=None, zerolinewidth=None, **kwargs ): """ Construct a new XAxis object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.XAxis anchor If set to an opposite-letter axis id (e.g. `x2`, `y`), this axis is bound to the corresponding opposite-letter axis. If set to "free", this axis' position is determined by `position`. automargin Determines whether long tick labels automatically grow the figure margins. autorange Determines whether or not the range of this axis is computed in relation to the input data. See `rangemode` for more info. If `range` is provided, then `autorange` is set to False. calendar Sets the calendar system to use for `range` and `tick0` if this is a date axis. This does not set the calendar for interpreting data on this axis, that's specified in the trace or via the global `layout.calendar` categoryarray Sets the order in which categories on this axis appear. Only has an effect if `categoryorder` is set to "array". Used with `categoryorder`. categoryarraysrc Sets the source reference on plot.ly for categoryarray . categoryorder Specifies the ordering logic for the case of categorical variables. By default, plotly uses "trace", which specifies the order that is present in the data supplied. Set `categoryorder` to *category ascending* or *category descending* if order should be determined by the alphanumerical order of the category names. Set `categoryorder` to "array" to derive the ordering from the attribute `categoryarray`. If a category is not found in the `categoryarray` array, the sorting behavior for that attribute will be identical to the "trace" mode. The unspecified categories will follow the categories in `categoryarray`. Set `categoryorder` to *total ascending* or *total descending* if order should be determined by the numerical order of the values. Similarly, the order can be determined by the min, max, sum, mean or median of all the values. color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. constrain If this axis needs to be compressed (either due to its own `scaleanchor` and `scaleratio` or those of the other axis), determines how that happens: by increasing the "range" (default), or by decreasing the "domain". constraintoward If this axis needs to be compressed (either due to its own `scaleanchor` and `scaleratio` or those of the other axis), determines which direction we push the originally specified plot area. Options are "left", "center" (default), and "right" for x axes, and "top", "middle" (default), and "bottom" for y axes. dividercolor Sets the color of the dividers Only has an effect on "multicategory" axes. dividerwidth Sets the width (in px) of the dividers Only has an effect on "multicategory" axes. domain Sets the domain of this axis (in plot fraction). dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. fixedrange Determines whether or not this axis is zoom-able. If true, then zoom is disabled. gridcolor Sets the color of the grid lines. gridwidth Sets the width (in px) of the grid lines. hoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" layer Sets the layer on which this axis is displayed. If *above traces*, this axis is displayed above all the subplot's traces If *below traces*, this axis is displayed below all the subplot's traces, but above the grid lines. Useful when used together with scatter-like traces with `cliponaxis` set to False to show markers and/or text nodes above this axis. linecolor Sets the axis line color. linewidth Sets the width (in px) of the axis line. matches If set to another axis id (e.g. `x2`, `y`), the range of this axis will match the range of the corresponding axis in data-coordinates space. Moreover, matching axes share auto-range values, category lists and histogram auto-bins. Note that setting axes simultaneously in both a `scaleanchor` and a `matches` constraint is currently forbidden. Moreover, note that matching axes must have the same `type`. mirror Determines if the axis lines or/and ticks are mirrored to the opposite side of the plotting area. If True, the axis lines are mirrored. If "ticks", the axis lines and ticks are mirrored. If False, mirroring is disable. If "all", axis lines are mirrored on all shared-axes subplots. If "allticks", axis lines and ticks are mirrored on all shared-axes subplots. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". overlaying If set a same-letter axis id, this axis is overlaid on top of the corresponding same-letter axis, with traces and axes visible for both axes. If False, this axis does not overlay any same-letter axes. In this case, for axes with overlapping domains only the highest- numbered axis will be visible. position Sets the position of this axis in the plotting space (in normalized coordinates). Only has an effect if `anchor` is set to "free". range Sets the range of this axis. If the axis `type` is "log", then you must take the log of your desired range (e.g. to set the range from 1 to 100, set the range from 0 to 2). If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. rangemode If "normal", the range is computed in relation to the extrema of the input data. If *tozero*`, the range extends to 0, regardless of the input data If "nonnegative", the range is non-negative, regardless of the input data. Applies only to linear axes. rangeselector plotly.graph_objects.layout.xaxis.Rangeselector instance or dict with compatible properties rangeslider plotly.graph_objects.layout.xaxis.Rangeslider instance or dict with compatible properties scaleanchor If set to another axis id (e.g. `x2`, `y`), the range of this axis changes together with the range of the corresponding axis such that the scale of pixels per unit is in a constant ratio. Both axes are still zoomable, but when you zoom one, the other will zoom the same amount, keeping a fixed midpoint. `constrain` and `constraintoward` determine how we enforce the constraint. You can chain these, ie `yaxis: {scaleanchor: *x*}, xaxis2: {scaleanchor: *y*}` but you can only link axes of the same `type`. The linked axis can have the opposite letter (to constrain the aspect ratio) or the same letter (to match scales across subplots). Loops (`yaxis: {scaleanchor: *x*}, xaxis: {scaleanchor: *y*}` or longer) are redundant and the last constraint encountered will be ignored to avoid possible inconsistent constraints via `scaleratio`. Note that setting axes simultaneously in both a `scaleanchor` and a `matches` constraint is currently forbidden. scaleratio If this axis is linked to another by `scaleanchor`, this determines the pixel to unit scale ratio. For example, if this value is 10, then every unit on this axis spans 10 times the number of pixels as a unit on the linked axis. Use this for example to create an elevation profile where the vertical scale is exaggerated a fixed amount with respect to the horizontal. separatethousands If "true", even 4-digit integers are separated showdividers Determines whether or not a dividers are drawn between the category levels of this axis. Only has an effect on "multicategory" axes. showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showgrid Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. showline Determines whether or not a line bounding this axis is drawn. showspikes Determines whether or not spikes (aka droplines) are drawn for this axis. Note: This only takes affect when hovermode = closest showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. side Determines whether a x (y) axis is positioned at the "bottom" ("left") or "top" ("right") of the plotting area. spikecolor Sets the spike color. If undefined, will use the series color spikedash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). spikemode Determines the drawing mode for the spike line If "toaxis", the line is drawn from the data point to the axis the series is plotted on. If "across", the line is drawn across the entire plot area, and supercedes "toaxis". If "marker", then a marker dot is drawn on the axis the series is plotted on spikesnap Determines whether spikelines are stuck to the cursor or to the closest datapoints. spikethickness Sets the width (in px) of the zero line. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the tick font. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.layout.xaxis.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.layout.xaxis.tickformatstopdefaults), sets the default property values to use for elements of layout.xaxis.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. tickson Determines where ticks and grid lines are drawn with respect to their corresponding tick labels. Only has an effect for axes of `type` "category" or "multicategory". When set to "boundaries", ticks and grid lines are drawn half a category to the left/bottom of labels. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.layout.xaxis.Title instance or dict with compatible properties titlefont Deprecated: Please use layout.xaxis.title.font instead. Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. type Sets the axis type. By default, plotly attempts to determined the axis type by looking into the data of the traces that referenced the axis in question. uirevision Controls persistence of user-driven changes in axis `range`, `autorange`, and `title` if in `editable: true` configuration. Defaults to `layout.uirevision`. visible A single toggle to hide the axis while preserving interaction like dragging. Default is true when a cheater plot is present on the axis, otherwise false zeroline Determines whether or not a line is drawn at along the 0 value of this axis. If True, the zero line is drawn on top of the grid lines. zerolinecolor Sets the line color of the zero line. zerolinewidth Sets the width (in px) of the zero line. Returns ------- XAxis """ super(XAxis, self).__init__("xaxis") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.XAxis constructor must be a dict or an instance of plotly.graph_objs.layout.XAxis""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout import xaxis as v_xaxis # Initialize validators # --------------------- self._validators["anchor"] = v_xaxis.AnchorValidator() self._validators["automargin"] = v_xaxis.AutomarginValidator() self._validators["autorange"] = v_xaxis.AutorangeValidator() self._validators["calendar"] = v_xaxis.CalendarValidator() self._validators["categoryarray"] = v_xaxis.CategoryarrayValidator() self._validators["categoryarraysrc"] = v_xaxis.CategoryarraysrcValidator() self._validators["categoryorder"] = v_xaxis.CategoryorderValidator() self._validators["color"] = v_xaxis.ColorValidator() self._validators["constrain"] = v_xaxis.ConstrainValidator() self._validators["constraintoward"] = v_xaxis.ConstraintowardValidator() self._validators["dividercolor"] = v_xaxis.DividercolorValidator() self._validators["dividerwidth"] = v_xaxis.DividerwidthValidator() self._validators["domain"] = v_xaxis.DomainValidator() self._validators["dtick"] = v_xaxis.DtickValidator() self._validators["exponentformat"] = v_xaxis.ExponentformatValidator() self._validators["fixedrange"] = v_xaxis.FixedrangeValidator() self._validators["gridcolor"] = v_xaxis.GridcolorValidator() self._validators["gridwidth"] = v_xaxis.GridwidthValidator() self._validators["hoverformat"] = v_xaxis.HoverformatValidator() self._validators["layer"] = v_xaxis.LayerValidator() self._validators["linecolor"] = v_xaxis.LinecolorValidator() self._validators["linewidth"] = v_xaxis.LinewidthValidator() self._validators["matches"] = v_xaxis.MatchesValidator() self._validators["mirror"] = v_xaxis.MirrorValidator() self._validators["nticks"] = v_xaxis.NticksValidator() self._validators["overlaying"] = v_xaxis.OverlayingValidator() self._validators["position"] = v_xaxis.PositionValidator() self._validators["range"] = v_xaxis.RangeValidator() self._validators["rangemode"] = v_xaxis.RangemodeValidator() self._validators["rangeselector"] = v_xaxis.RangeselectorValidator() self._validators["rangeslider"] = v_xaxis.RangesliderValidator() self._validators["scaleanchor"] = v_xaxis.ScaleanchorValidator() self._validators["scaleratio"] = v_xaxis.ScaleratioValidator() self._validators["separatethousands"] = v_xaxis.SeparatethousandsValidator() self._validators["showdividers"] = v_xaxis.ShowdividersValidator() self._validators["showexponent"] = v_xaxis.ShowexponentValidator() self._validators["showgrid"] = v_xaxis.ShowgridValidator() self._validators["showline"] = v_xaxis.ShowlineValidator() self._validators["showspikes"] = v_xaxis.ShowspikesValidator() self._validators["showticklabels"] = v_xaxis.ShowticklabelsValidator() self._validators["showtickprefix"] = v_xaxis.ShowtickprefixValidator() self._validators["showticksuffix"] = v_xaxis.ShowticksuffixValidator() self._validators["side"] = v_xaxis.SideValidator() self._validators["spikecolor"] = v_xaxis.SpikecolorValidator() self._validators["spikedash"] = v_xaxis.SpikedashValidator() self._validators["spikemode"] = v_xaxis.SpikemodeValidator() self._validators["spikesnap"] = v_xaxis.SpikesnapValidator() self._validators["spikethickness"] = v_xaxis.SpikethicknessValidator() self._validators["tick0"] = v_xaxis.Tick0Validator() self._validators["tickangle"] = v_xaxis.TickangleValidator() self._validators["tickcolor"] = v_xaxis.TickcolorValidator() self._validators["tickfont"] = v_xaxis.TickfontValidator() self._validators["tickformat"] = v_xaxis.TickformatValidator() self._validators["tickformatstops"] = v_xaxis.TickformatstopsValidator() self._validators["tickformatstopdefaults"] = v_xaxis.TickformatstopValidator() self._validators["ticklen"] = v_xaxis.TicklenValidator() self._validators["tickmode"] = v_xaxis.TickmodeValidator() self._validators["tickprefix"] = v_xaxis.TickprefixValidator() self._validators["ticks"] = v_xaxis.TicksValidator() self._validators["tickson"] = v_xaxis.TicksonValidator() self._validators["ticksuffix"] = v_xaxis.TicksuffixValidator() self._validators["ticktext"] = v_xaxis.TicktextValidator() self._validators["ticktextsrc"] = v_xaxis.TicktextsrcValidator() self._validators["tickvals"] = v_xaxis.TickvalsValidator() self._validators["tickvalssrc"] = v_xaxis.TickvalssrcValidator() self._validators["tickwidth"] = v_xaxis.TickwidthValidator() self._validators["title"] = v_xaxis.TitleValidator() self._validators["type"] = v_xaxis.TypeValidator() self._validators["uirevision"] = v_xaxis.UirevisionValidator() self._validators["visible"] = v_xaxis.VisibleValidator() self._validators["zeroline"] = v_xaxis.ZerolineValidator() self._validators["zerolinecolor"] = v_xaxis.ZerolinecolorValidator() self._validators["zerolinewidth"] = v_xaxis.ZerolinewidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("anchor", None) self["anchor"] = anchor if anchor is not None else _v _v = arg.pop("automargin", None) self["automargin"] = automargin if automargin is not None else _v _v = arg.pop("autorange", None) self["autorange"] = autorange if autorange is not None else _v _v = arg.pop("calendar", None) self["calendar"] = calendar if calendar is not None else _v _v = arg.pop("categoryarray", None) self["categoryarray"] = categoryarray if categoryarray is not None else _v _v = arg.pop("categoryarraysrc", None) self["categoryarraysrc"] = ( categoryarraysrc if categoryarraysrc is not None else _v ) _v = arg.pop("categoryorder", None) self["categoryorder"] = categoryorder if categoryorder is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("constrain", None) self["constrain"] = constrain if constrain is not None else _v _v = arg.pop("constraintoward", None) self["constraintoward"] = constraintoward if constraintoward is not None else _v _v = arg.pop("dividercolor", None) self["dividercolor"] = dividercolor if dividercolor is not None else _v _v = arg.pop("dividerwidth", None) self["dividerwidth"] = dividerwidth if dividerwidth is not None else _v _v = arg.pop("domain", None) self["domain"] = domain if domain is not None else _v _v = arg.pop("dtick", None) self["dtick"] = dtick if dtick is not None else _v _v = arg.pop("exponentformat", None) self["exponentformat"] = exponentformat if exponentformat is not None else _v _v = arg.pop("fixedrange", None) self["fixedrange"] = fixedrange if fixedrange is not None else _v _v = arg.pop("gridcolor", None) self["gridcolor"] = gridcolor if gridcolor is not None else _v _v = arg.pop("gridwidth", None) self["gridwidth"] = gridwidth if gridwidth is not None else _v _v = arg.pop("hoverformat", None) self["hoverformat"] = hoverformat if hoverformat is not None else _v _v = arg.pop("layer", None) self["layer"] = layer if layer is not None else _v _v = arg.pop("linecolor", None) self["linecolor"] = linecolor if linecolor is not None else _v _v = arg.pop("linewidth", None) self["linewidth"] = linewidth if linewidth is not None else _v _v = arg.pop("matches", None) self["matches"] = matches if matches is not None else _v _v = arg.pop("mirror", None) self["mirror"] = mirror if mirror is not None else _v _v = arg.pop("nticks", None) self["nticks"] = nticks if nticks is not None else _v _v = arg.pop("overlaying", None) self["overlaying"] = overlaying if overlaying is not None else _v _v = arg.pop("position", None) self["position"] = position if position is not None else _v _v = arg.pop("range", None) self["range"] = range if range is not None else _v _v = arg.pop("rangemode", None) self["rangemode"] = rangemode if rangemode is not None else _v _v = arg.pop("rangeselector", None) self["rangeselector"] = rangeselector if rangeselector is not None else _v _v = arg.pop("rangeslider", None) self["rangeslider"] = rangeslider if rangeslider is not None else _v _v = arg.pop("scaleanchor", None) self["scaleanchor"] = scaleanchor if scaleanchor is not None else _v _v = arg.pop("scaleratio", None) self["scaleratio"] = scaleratio if scaleratio is not None else _v _v = arg.pop("separatethousands", None) self["separatethousands"] = ( separatethousands if separatethousands is not None else _v ) _v = arg.pop("showdividers", None) self["showdividers"] = showdividers if showdividers is not None else _v _v = arg.pop("showexponent", None) self["showexponent"] = showexponent if showexponent is not None else _v _v = arg.pop("showgrid", None) self["showgrid"] = showgrid if showgrid is not None else _v _v = arg.pop("showline", None) self["showline"] = showline if showline is not None else _v _v = arg.pop("showspikes", None) self["showspikes"] = showspikes if showspikes is not None else _v _v = arg.pop("showticklabels", None) self["showticklabels"] = showticklabels if showticklabels is not None else _v _v = arg.pop("showtickprefix", None) self["showtickprefix"] = showtickprefix if showtickprefix is not None else _v _v = arg.pop("showticksuffix", None) self["showticksuffix"] = showticksuffix if showticksuffix is not None else _v _v = arg.pop("side", None) self["side"] = side if side is not None else _v _v = arg.pop("spikecolor", None) self["spikecolor"] = spikecolor if spikecolor is not None else _v _v = arg.pop("spikedash", None) self["spikedash"] = spikedash if spikedash is not None else _v _v = arg.pop("spikemode", None) self["spikemode"] = spikemode if spikemode is not None else _v _v = arg.pop("spikesnap", None) self["spikesnap"] = spikesnap if spikesnap is not None else _v _v = arg.pop("spikethickness", None) self["spikethickness"] = spikethickness if spikethickness is not None else _v _v = arg.pop("tick0", None) self["tick0"] = tick0 if tick0 is not None else _v _v = arg.pop("tickangle", None) self["tickangle"] = tickangle if tickangle is not None else _v _v = arg.pop("tickcolor", None) self["tickcolor"] = tickcolor if tickcolor is not None else _v _v = arg.pop("tickfont", None) self["tickfont"] = tickfont if tickfont is not None else _v _v = arg.pop("tickformat", None) self["tickformat"] = tickformat if tickformat is not None else _v _v = arg.pop("tickformatstops", None) self["tickformatstops"] = tickformatstops if tickformatstops is not None else _v _v = arg.pop("tickformatstopdefaults", None) self["tickformatstopdefaults"] = ( tickformatstopdefaults if tickformatstopdefaults is not None else _v ) _v = arg.pop("ticklen", None) self["ticklen"] = ticklen if ticklen is not None else _v _v = arg.pop("tickmode", None) self["tickmode"] = tickmode if tickmode is not None else _v _v = arg.pop("tickprefix", None) self["tickprefix"] = tickprefix if tickprefix is not None else _v _v = arg.pop("ticks", None) self["ticks"] = ticks if ticks is not None else _v _v = arg.pop("tickson", None) self["tickson"] = tickson if tickson is not None else _v _v = arg.pop("ticksuffix", None) self["ticksuffix"] = ticksuffix if ticksuffix is not None else _v _v = arg.pop("ticktext", None) self["ticktext"] = ticktext if ticktext is not None else _v _v = arg.pop("ticktextsrc", None) self["ticktextsrc"] = ticktextsrc if ticktextsrc is not None else _v _v = arg.pop("tickvals", None) self["tickvals"] = tickvals if tickvals is not None else _v _v = arg.pop("tickvalssrc", None) self["tickvalssrc"] = tickvalssrc if tickvalssrc is not None else _v _v = arg.pop("tickwidth", None) self["tickwidth"] = tickwidth if tickwidth is not None else _v _v = arg.pop("title", None) self["title"] = title if title is not None else _v _v = arg.pop("titlefont", None) _v = titlefont if titlefont is not None else _v if _v is not None: self["titlefont"] = _v _v = arg.pop("type", None) self["type"] = type if type is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("zeroline", None) self["zeroline"] = zeroline if zeroline is not None else _v _v = arg.pop("zerolinecolor", None) self["zerolinecolor"] = zerolinecolor if zerolinecolor is not None else _v _v = arg.pop("zerolinewidth", None) self["zerolinewidth"] = zerolinewidth if zerolinewidth is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Updatemenu(_BaseLayoutHierarchyType): # active # ------ @property def active(self): """ Determines which button (by index starting from 0) is considered active. The 'active' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [-1, 9223372036854775807] Returns ------- int """ return self["active"] @active.setter def active(self, val): self["active"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the update menu buttons. The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the color of the border enclosing the update menu. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # borderwidth # ----------- @property def borderwidth(self): """ Sets the width (in px) of the border enclosing the update menu. The 'borderwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["borderwidth"] @borderwidth.setter def borderwidth(self, val): self["borderwidth"] = val # buttons # ------- @property def buttons(self): """ The 'buttons' property is a tuple of instances of Button that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.updatemenu.Button - A list or tuple of dicts of string/value properties that will be passed to the Button constructor Supported dict properties: args Sets the arguments values to be passed to the Plotly method set in `method` on click. args2 Sets a 2nd set of `args`, these arguments values are passed to the Plotly method set in `method` when clicking this button while in the active state. Use this to create toggle buttons. execute When true, the API method is executed. When false, all other behaviors are the same and command execution is skipped. This may be useful when hooking into, for example, the `plotly_buttonclicked` method and executing the API command manually without losing the benefit of the updatemenu automatically binding to the state of the plot through the specification of `method` and `args`. label Sets the text label to appear on the button. method Sets the Plotly method to be called on click. If the `skip` method is used, the API updatemenu will function as normal but will perform no API calls and will not bind automatically to state updates. This may be used to create a component interface and attach to updatemenu events manually via JavaScript. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. visible Determines whether or not this button is visible. Returns ------- tuple[plotly.graph_objs.layout.updatemenu.Button] """ return self["buttons"] @buttons.setter def buttons(self, val): self["buttons"] = val # buttondefaults # -------------- @property def buttondefaults(self): """ When used in a template (as layout.template.layout.updatemenu.buttondefaults), sets the default property values to use for elements of layout.updatemenu.buttons The 'buttondefaults' property is an instance of Button that may be specified as: - An instance of plotly.graph_objs.layout.updatemenu.Button - A dict of string/value properties that will be passed to the Button constructor Supported dict properties: Returns ------- plotly.graph_objs.layout.updatemenu.Button """ return self["buttondefaults"] @buttondefaults.setter def buttondefaults(self, val): self["buttondefaults"] = val # direction # --------- @property def direction(self): """ Determines the direction in which the buttons are laid out, whether in a dropdown menu or a row/column of buttons. For `left` and `up`, the buttons will still appear in left-to-right or top-to-bottom order respectively. The 'direction' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'right', 'up', 'down'] Returns ------- Any """ return self["direction"] @direction.setter def direction(self, val): self["direction"] = val # font # ---- @property def font(self): """ Sets the font of the update menu button text. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.layout.updatemenu.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.layout.updatemenu.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # pad # --- @property def pad(self): """ Sets the padding around the buttons or dropdown menu. The 'pad' property is an instance of Pad that may be specified as: - An instance of plotly.graph_objs.layout.updatemenu.Pad - A dict of string/value properties that will be passed to the Pad constructor Supported dict properties: b The amount of padding (in px) along the bottom of the component. l The amount of padding (in px) on the left side of the component. r The amount of padding (in px) on the right side of the component. t The amount of padding (in px) along the top of the component. Returns ------- plotly.graph_objs.layout.updatemenu.Pad """ return self["pad"] @pad.setter def pad(self, val): self["pad"] = val # showactive # ---------- @property def showactive(self): """ Highlights active dropdown item or active button if true. The 'showactive' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showactive"] @showactive.setter def showactive(self, val): self["showactive"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # type # ---- @property def type(self): """ Determines whether the buttons are accessible via a dropdown menu or whether the buttons are stacked horizontally or vertically The 'type' property is an enumeration that may be specified as: - One of the following enumeration values: ['dropdown', 'buttons'] Returns ------- Any """ return self["type"] @type.setter def type(self, val): self["type"] = val # visible # ------- @property def visible(self): """ Determines whether or not the update menu is visible. The 'visible' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # x # - @property def x(self): """ Sets the x position (in normalized coordinates) of the update menu. The 'x' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["x"] @x.setter def x(self, val): self["x"] = val # xanchor # ------- @property def xanchor(self): """ Sets the update menu's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the range selector. The 'xanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'left', 'center', 'right'] Returns ------- Any """ return self["xanchor"] @xanchor.setter def xanchor(self, val): self["xanchor"] = val # y # - @property def y(self): """ Sets the y position (in normalized coordinates) of the update menu. The 'y' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["y"] @y.setter def y(self, val): self["y"] = val # yanchor # ------- @property def yanchor(self): """ Sets the update menu's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the range selector. The 'yanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'top', 'middle', 'bottom'] Returns ------- Any """ return self["yanchor"] @yanchor.setter def yanchor(self, val): self["yanchor"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ active Determines which button (by index starting from 0) is considered active. bgcolor Sets the background color of the update menu buttons. bordercolor Sets the color of the border enclosing the update menu. borderwidth Sets the width (in px) of the border enclosing the update menu. buttons A tuple of plotly.graph_objects.layout.updatemenu.Button instances or dicts with compatible properties buttondefaults When used in a template (as layout.template.layout.updatemenu.buttondefaults), sets the default property values to use for elements of layout.updatemenu.buttons direction Determines the direction in which the buttons are laid out, whether in a dropdown menu or a row/column of buttons. For `left` and `up`, the buttons will still appear in left-to-right or top-to-bottom order respectively. font Sets the font of the update menu button text. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. pad Sets the padding around the buttons or dropdown menu. showactive Highlights active dropdown item or active button if true. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. type Determines whether the buttons are accessible via a dropdown menu or whether the buttons are stacked horizontally or vertically visible Determines whether or not the update menu is visible. x Sets the x position (in normalized coordinates) of the update menu. xanchor Sets the update menu's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the range selector. y Sets the y position (in normalized coordinates) of the update menu. yanchor Sets the update menu's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the range selector. """ def __init__( self, arg=None, active=None, bgcolor=None, bordercolor=None, borderwidth=None, buttons=None, buttondefaults=None, direction=None, font=None, name=None, pad=None, showactive=None, templateitemname=None, type=None, visible=None, x=None, xanchor=None, y=None, yanchor=None, **kwargs ): """ Construct a new Updatemenu object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.Updatemenu active Determines which button (by index starting from 0) is considered active. bgcolor Sets the background color of the update menu buttons. bordercolor Sets the color of the border enclosing the update menu. borderwidth Sets the width (in px) of the border enclosing the update menu. buttons A tuple of plotly.graph_objects.layout.updatemenu.Button instances or dicts with compatible properties buttondefaults When used in a template (as layout.template.layout.updatemenu.buttondefaults), sets the default property values to use for elements of layout.updatemenu.buttons direction Determines the direction in which the buttons are laid out, whether in a dropdown menu or a row/column of buttons. For `left` and `up`, the buttons will still appear in left-to-right or top-to-bottom order respectively. font Sets the font of the update menu button text. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. pad Sets the padding around the buttons or dropdown menu. showactive Highlights active dropdown item or active button if true. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. type Determines whether the buttons are accessible via a dropdown menu or whether the buttons are stacked horizontally or vertically visible Determines whether or not the update menu is visible. x Sets the x position (in normalized coordinates) of the update menu. xanchor Sets the update menu's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the range selector. y Sets the y position (in normalized coordinates) of the update menu. yanchor Sets the update menu's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the range selector. Returns ------- Updatemenu """ super(Updatemenu, self).__init__("updatemenus") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.Updatemenu constructor must be a dict or an instance of plotly.graph_objs.layout.Updatemenu""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout import updatemenu as v_updatemenu # Initialize validators # --------------------- self._validators["active"] = v_updatemenu.ActiveValidator() self._validators["bgcolor"] = v_updatemenu.BgcolorValidator() self._validators["bordercolor"] = v_updatemenu.BordercolorValidator() self._validators["borderwidth"] = v_updatemenu.BorderwidthValidator() self._validators["buttons"] = v_updatemenu.ButtonsValidator() self._validators["buttondefaults"] = v_updatemenu.ButtonValidator() self._validators["direction"] = v_updatemenu.DirectionValidator() self._validators["font"] = v_updatemenu.FontValidator() self._validators["name"] = v_updatemenu.NameValidator() self._validators["pad"] = v_updatemenu.PadValidator() self._validators["showactive"] = v_updatemenu.ShowactiveValidator() self._validators["templateitemname"] = v_updatemenu.TemplateitemnameValidator() self._validators["type"] = v_updatemenu.TypeValidator() self._validators["visible"] = v_updatemenu.VisibleValidator() self._validators["x"] = v_updatemenu.XValidator() self._validators["xanchor"] = v_updatemenu.XanchorValidator() self._validators["y"] = v_updatemenu.YValidator() self._validators["yanchor"] = v_updatemenu.YanchorValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("active", None) self["active"] = active if active is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("borderwidth", None) self["borderwidth"] = borderwidth if borderwidth is not None else _v _v = arg.pop("buttons", None) self["buttons"] = buttons if buttons is not None else _v _v = arg.pop("buttondefaults", None) self["buttondefaults"] = buttondefaults if buttondefaults is not None else _v _v = arg.pop("direction", None) self["direction"] = direction if direction is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("pad", None) self["pad"] = pad if pad is not None else _v _v = arg.pop("showactive", None) self["showactive"] = showactive if showactive is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("type", None) self["type"] = type if type is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xanchor", None) self["xanchor"] = xanchor if xanchor is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("yanchor", None) self["yanchor"] = yanchor if yanchor is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Transition(_BaseLayoutHierarchyType): # duration # -------- @property def duration(self): """ The duration of the transition, in milliseconds. If equal to zero, updates are synchronous. The 'duration' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["duration"] @duration.setter def duration(self, val): self["duration"] = val # easing # ------ @property def easing(self): """ The easing function used for the transition The 'easing' property is an enumeration that may be specified as: - One of the following enumeration values: ['linear', 'quad', 'cubic', 'sin', 'exp', 'circle', 'elastic', 'back', 'bounce', 'linear-in', 'quad-in', 'cubic-in', 'sin-in', 'exp-in', 'circle-in', 'elastic-in', 'back-in', 'bounce-in', 'linear-out', 'quad-out', 'cubic-out', 'sin-out', 'exp-out', 'circle-out', 'elastic-out', 'back-out', 'bounce-out', 'linear-in-out', 'quad-in-out', 'cubic-in-out', 'sin-in-out', 'exp-in-out', 'circle-in-out', 'elastic-in-out', 'back-in-out', 'bounce-in-out'] Returns ------- Any """ return self["easing"] @easing.setter def easing(self, val): self["easing"] = val # ordering # -------- @property def ordering(self): """ Determines whether the figure's layout or traces smoothly transitions during updates that make both traces and layout change. The 'ordering' property is an enumeration that may be specified as: - One of the following enumeration values: ['layout first', 'traces first'] Returns ------- Any """ return self["ordering"] @ordering.setter def ordering(self, val): self["ordering"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ duration The duration of the transition, in milliseconds. If equal to zero, updates are synchronous. easing The easing function used for the transition ordering Determines whether the figure's layout or traces smoothly transitions during updates that make both traces and layout change. """ def __init__(self, arg=None, duration=None, easing=None, ordering=None, **kwargs): """ Construct a new Transition object Sets transition options used during Plotly.react updates. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.Transition duration The duration of the transition, in milliseconds. If equal to zero, updates are synchronous. easing The easing function used for the transition ordering Determines whether the figure's layout or traces smoothly transitions during updates that make both traces and layout change. Returns ------- Transition """ super(Transition, self).__init__("transition") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.Transition constructor must be a dict or an instance of plotly.graph_objs.layout.Transition""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout import transition as v_transition # Initialize validators # --------------------- self._validators["duration"] = v_transition.DurationValidator() self._validators["easing"] = v_transition.EasingValidator() self._validators["ordering"] = v_transition.OrderingValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("duration", None) self["duration"] = duration if duration is not None else _v _v = arg.pop("easing", None) self["easing"] = easing if easing is not None else _v _v = arg.pop("ordering", None) self["ordering"] = ordering if ordering is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Title(_BaseLayoutHierarchyType): # font # ---- @property def font(self): """ Sets the title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.layout.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.layout.title.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # pad # --- @property def pad(self): """ Sets the padding of the title. Each padding value only applies when the corresponding `xanchor`/`yanchor` value is set accordingly. E.g. for left padding to take effect, `xanchor` must be set to "left". The same rule applies if `xanchor`/`yanchor` is determined automatically. Padding is muted if the respective anchor value is "middle*/*center". The 'pad' property is an instance of Pad that may be specified as: - An instance of plotly.graph_objs.layout.title.Pad - A dict of string/value properties that will be passed to the Pad constructor Supported dict properties: b The amount of padding (in px) along the bottom of the component. l The amount of padding (in px) on the left side of the component. r The amount of padding (in px) on the right side of the component. t The amount of padding (in px) along the top of the component. Returns ------- plotly.graph_objs.layout.title.Pad """ return self["pad"] @pad.setter def pad(self, val): self["pad"] = val # text # ---- @property def text(self): """ Sets the plot's title. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # x # - @property def x(self): """ Sets the x position with respect to `xref` in normalized coordinates from 0 (left) to 1 (right). The 'x' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["x"] @x.setter def x(self, val): self["x"] = val # xanchor # ------- @property def xanchor(self): """ Sets the title's horizontal alignment with respect to its x position. "left" means that the title starts at x, "right" means that the title ends at x and "center" means that the title's center is at x. "auto" divides `xref` by three and calculates the `xanchor` value automatically based on the value of `x`. The 'xanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'left', 'center', 'right'] Returns ------- Any """ return self["xanchor"] @xanchor.setter def xanchor(self, val): self["xanchor"] = val # xref # ---- @property def xref(self): """ Sets the container `x` refers to. "container" spans the entire `width` of the plot. "paper" refers to the width of the plotting area only. The 'xref' property is an enumeration that may be specified as: - One of the following enumeration values: ['container', 'paper'] Returns ------- Any """ return self["xref"] @xref.setter def xref(self, val): self["xref"] = val # y # - @property def y(self): """ Sets the y position with respect to `yref` in normalized coordinates from 0 (bottom) to 1 (top). "auto" places the baseline of the title onto the vertical center of the top margin. The 'y' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["y"] @y.setter def y(self, val): self["y"] = val # yanchor # ------- @property def yanchor(self): """ Sets the title's vertical alignment with respect to its y position. "top" means that the title's cap line is at y, "bottom" means that the title's baseline is at y and "middle" means that the title's midline is at y. "auto" divides `yref` by three and calculates the `yanchor` value automatically based on the value of `y`. The 'yanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'top', 'middle', 'bottom'] Returns ------- Any """ return self["yanchor"] @yanchor.setter def yanchor(self, val): self["yanchor"] = val # yref # ---- @property def yref(self): """ Sets the container `y` refers to. "container" spans the entire `height` of the plot. "paper" refers to the height of the plotting area only. The 'yref' property is an enumeration that may be specified as: - One of the following enumeration values: ['container', 'paper'] Returns ------- Any """ return self["yref"] @yref.setter def yref(self, val): self["yref"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Sets the title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. pad Sets the padding of the title. Each padding value only applies when the corresponding `xanchor`/`yanchor` value is set accordingly. E.g. for left padding to take effect, `xanchor` must be set to "left". The same rule applies if `xanchor`/`yanchor` is determined automatically. Padding is muted if the respective anchor value is "middle*/*center". text Sets the plot's title. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. x Sets the x position with respect to `xref` in normalized coordinates from 0 (left) to 1 (right). xanchor Sets the title's horizontal alignment with respect to its x position. "left" means that the title starts at x, "right" means that the title ends at x and "center" means that the title's center is at x. "auto" divides `xref` by three and calculates the `xanchor` value automatically based on the value of `x`. xref Sets the container `x` refers to. "container" spans the entire `width` of the plot. "paper" refers to the width of the plotting area only. y Sets the y position with respect to `yref` in normalized coordinates from 0 (bottom) to 1 (top). "auto" places the baseline of the title onto the vertical center of the top margin. yanchor Sets the title's vertical alignment with respect to its y position. "top" means that the title's cap line is at y, "bottom" means that the title's baseline is at y and "middle" means that the title's midline is at y. "auto" divides `yref` by three and calculates the `yanchor` value automatically based on the value of `y`. yref Sets the container `y` refers to. "container" spans the entire `height` of the plot. "paper" refers to the height of the plotting area only. """ def __init__( self, arg=None, font=None, pad=None, text=None, x=None, xanchor=None, xref=None, y=None, yanchor=None, yref=None, **kwargs ): """ Construct a new Title object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.Title font Sets the title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. pad Sets the padding of the title. Each padding value only applies when the corresponding `xanchor`/`yanchor` value is set accordingly. E.g. for left padding to take effect, `xanchor` must be set to "left". The same rule applies if `xanchor`/`yanchor` is determined automatically. Padding is muted if the respective anchor value is "middle*/*center". text Sets the plot's title. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. x Sets the x position with respect to `xref` in normalized coordinates from 0 (left) to 1 (right). xanchor Sets the title's horizontal alignment with respect to its x position. "left" means that the title starts at x, "right" means that the title ends at x and "center" means that the title's center is at x. "auto" divides `xref` by three and calculates the `xanchor` value automatically based on the value of `x`. xref Sets the container `x` refers to. "container" spans the entire `width` of the plot. "paper" refers to the width of the plotting area only. y Sets the y position with respect to `yref` in normalized coordinates from 0 (bottom) to 1 (top). "auto" places the baseline of the title onto the vertical center of the top margin. yanchor Sets the title's vertical alignment with respect to its y position. "top" means that the title's cap line is at y, "bottom" means that the title's baseline is at y and "middle" means that the title's midline is at y. "auto" divides `yref` by three and calculates the `yanchor` value automatically based on the value of `y`. yref Sets the container `y` refers to. "container" spans the entire `height` of the plot. "paper" refers to the height of the plotting area only. Returns ------- Title """ super(Title, self).__init__("title") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.Title constructor must be a dict or an instance of plotly.graph_objs.layout.Title""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout import title as v_title # Initialize validators # --------------------- self._validators["font"] = v_title.FontValidator() self._validators["pad"] = v_title.PadValidator() self._validators["text"] = v_title.TextValidator() self._validators["x"] = v_title.XValidator() self._validators["xanchor"] = v_title.XanchorValidator() self._validators["xref"] = v_title.XrefValidator() self._validators["y"] = v_title.YValidator() self._validators["yanchor"] = v_title.YanchorValidator() self._validators["yref"] = v_title.YrefValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("pad", None) self["pad"] = pad if pad is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xanchor", None) self["xanchor"] = xanchor if xanchor is not None else _v _v = arg.pop("xref", None) self["xref"] = xref if xref is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("yanchor", None) self["yanchor"] = yanchor if yanchor is not None else _v _v = arg.pop("yref", None) self["yref"] = yref if yref is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Ternary(_BaseLayoutHierarchyType): # aaxis # ----- @property def aaxis(self): """ The 'aaxis' property is an instance of Aaxis that may be specified as: - An instance of plotly.graph_objs.layout.ternary.Aaxis - A dict of string/value properties that will be passed to the Aaxis constructor Supported dict properties: color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. gridcolor Sets the color of the grid lines. gridwidth Sets the width (in px) of the grid lines. hoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" layer Sets the layer on which this axis is displayed. If *above traces*, this axis is displayed above all the subplot's traces If *below traces*, this axis is displayed below all the subplot's traces, but above the grid lines. Useful when used together with scatter-like traces with `cliponaxis` set to False to show markers and/or text nodes above this axis. linecolor Sets the axis line color. linewidth Sets the width (in px) of the axis line. min The minimum value visible on this axis. The maximum is determined by the sum minus the minimum values of the other two axes. The full view corresponds to all the minima set to zero. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showgrid Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. showline Determines whether or not a line bounding this axis is drawn. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the tick font. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.layout.ternary. aaxis.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.lay out.ternary.aaxis.tickformatstopdefaults), sets the default property values to use for elements of layout.ternary.aaxis.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.layout.ternary.aaxis.Title instance or dict with compatible properties titlefont Deprecated: Please use layout.ternary.aaxis.title.font instead. Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. uirevision Controls persistence of user-driven changes in axis `min`, and `title` if in `editable: true` configuration. Defaults to `ternary.uirevision`. Returns ------- plotly.graph_objs.layout.ternary.Aaxis """ return self["aaxis"] @aaxis.setter def aaxis(self, val): self["aaxis"] = val # baxis # ----- @property def baxis(self): """ The 'baxis' property is an instance of Baxis that may be specified as: - An instance of plotly.graph_objs.layout.ternary.Baxis - A dict of string/value properties that will be passed to the Baxis constructor Supported dict properties: color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. gridcolor Sets the color of the grid lines. gridwidth Sets the width (in px) of the grid lines. hoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" layer Sets the layer on which this axis is displayed. If *above traces*, this axis is displayed above all the subplot's traces If *below traces*, this axis is displayed below all the subplot's traces, but above the grid lines. Useful when used together with scatter-like traces with `cliponaxis` set to False to show markers and/or text nodes above this axis. linecolor Sets the axis line color. linewidth Sets the width (in px) of the axis line. min The minimum value visible on this axis. The maximum is determined by the sum minus the minimum values of the other two axes. The full view corresponds to all the minima set to zero. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showgrid Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. showline Determines whether or not a line bounding this axis is drawn. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the tick font. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.layout.ternary. baxis.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.lay out.ternary.baxis.tickformatstopdefaults), sets the default property values to use for elements of layout.ternary.baxis.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.layout.ternary.baxis.Title instance or dict with compatible properties titlefont Deprecated: Please use layout.ternary.baxis.title.font instead. Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. uirevision Controls persistence of user-driven changes in axis `min`, and `title` if in `editable: true` configuration. Defaults to `ternary.uirevision`. Returns ------- plotly.graph_objs.layout.ternary.Baxis """ return self["baxis"] @baxis.setter def baxis(self, val): self["baxis"] = val # bgcolor # ------- @property def bgcolor(self): """ Set the background color of the subplot The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # caxis # ----- @property def caxis(self): """ The 'caxis' property is an instance of Caxis that may be specified as: - An instance of plotly.graph_objs.layout.ternary.Caxis - A dict of string/value properties that will be passed to the Caxis constructor Supported dict properties: color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. gridcolor Sets the color of the grid lines. gridwidth Sets the width (in px) of the grid lines. hoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" layer Sets the layer on which this axis is displayed. If *above traces*, this axis is displayed above all the subplot's traces If *below traces*, this axis is displayed below all the subplot's traces, but above the grid lines. Useful when used together with scatter-like traces with `cliponaxis` set to False to show markers and/or text nodes above this axis. linecolor Sets the axis line color. linewidth Sets the width (in px) of the axis line. min The minimum value visible on this axis. The maximum is determined by the sum minus the minimum values of the other two axes. The full view corresponds to all the minima set to zero. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showgrid Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. showline Determines whether or not a line bounding this axis is drawn. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the tick font. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.layout.ternary. caxis.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.lay out.ternary.caxis.tickformatstopdefaults), sets the default property values to use for elements of layout.ternary.caxis.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.layout.ternary.caxis.Title instance or dict with compatible properties titlefont Deprecated: Please use layout.ternary.caxis.title.font instead. Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. uirevision Controls persistence of user-driven changes in axis `min`, and `title` if in `editable: true` configuration. Defaults to `ternary.uirevision`. Returns ------- plotly.graph_objs.layout.ternary.Caxis """ return self["caxis"] @caxis.setter def caxis(self, val): self["caxis"] = val # domain # ------ @property def domain(self): """ The 'domain' property is an instance of Domain that may be specified as: - An instance of plotly.graph_objs.layout.ternary.Domain - A dict of string/value properties that will be passed to the Domain constructor Supported dict properties: column If there is a layout grid, use the domain for this column in the grid for this ternary subplot . row If there is a layout grid, use the domain for this row in the grid for this ternary subplot . x Sets the horizontal domain of this ternary subplot (in plot fraction). y Sets the vertical domain of this ternary subplot (in plot fraction). Returns ------- plotly.graph_objs.layout.ternary.Domain """ return self["domain"] @domain.setter def domain(self, val): self["domain"] = val # sum # --- @property def sum(self): """ The number each triplet should sum to, and the maximum range of each axis The 'sum' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["sum"] @sum.setter def sum(self, val): self["sum"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of user-driven changes in axis `min` and `title`, if not overridden in the individual axes. Defaults to `layout.uirevision`. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ aaxis plotly.graph_objects.layout.ternary.Aaxis instance or dict with compatible properties baxis plotly.graph_objects.layout.ternary.Baxis instance or dict with compatible properties bgcolor Set the background color of the subplot caxis plotly.graph_objects.layout.ternary.Caxis instance or dict with compatible properties domain plotly.graph_objects.layout.ternary.Domain instance or dict with compatible properties sum The number each triplet should sum to, and the maximum range of each axis uirevision Controls persistence of user-driven changes in axis `min` and `title`, if not overridden in the individual axes. Defaults to `layout.uirevision`. """ def __init__( self, arg=None, aaxis=None, baxis=None, bgcolor=None, caxis=None, domain=None, sum=None, uirevision=None, **kwargs ): """ Construct a new Ternary object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.Ternary aaxis plotly.graph_objects.layout.ternary.Aaxis instance or dict with compatible properties baxis plotly.graph_objects.layout.ternary.Baxis instance or dict with compatible properties bgcolor Set the background color of the subplot caxis plotly.graph_objects.layout.ternary.Caxis instance or dict with compatible properties domain plotly.graph_objects.layout.ternary.Domain instance or dict with compatible properties sum The number each triplet should sum to, and the maximum range of each axis uirevision Controls persistence of user-driven changes in axis `min` and `title`, if not overridden in the individual axes. Defaults to `layout.uirevision`. Returns ------- Ternary """ super(Ternary, self).__init__("ternary") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.Ternary constructor must be a dict or an instance of plotly.graph_objs.layout.Ternary""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout import ternary as v_ternary # Initialize validators # --------------------- self._validators["aaxis"] = v_ternary.AaxisValidator() self._validators["baxis"] = v_ternary.BaxisValidator() self._validators["bgcolor"] = v_ternary.BgcolorValidator() self._validators["caxis"] = v_ternary.CaxisValidator() self._validators["domain"] = v_ternary.DomainValidator() self._validators["sum"] = v_ternary.SumValidator() self._validators["uirevision"] = v_ternary.UirevisionValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("aaxis", None) self["aaxis"] = aaxis if aaxis is not None else _v _v = arg.pop("baxis", None) self["baxis"] = baxis if baxis is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("caxis", None) self["caxis"] = caxis if caxis is not None else _v _v = arg.pop("domain", None) self["domain"] = domain if domain is not None else _v _v = arg.pop("sum", None) self["sum"] = sum if sum is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Template(_BaseLayoutHierarchyType): # data # ---- @property def data(self): """ The 'data' property is an instance of Data that may be specified as: - An instance of plotly.graph_objs.layout.template.Data - A dict of string/value properties that will be passed to the Data constructor Supported dict properties: area A tuple of plotly.graph_objects.Area instances or dicts with compatible properties barpolar A tuple of plotly.graph_objects.Barpolar instances or dicts with compatible properties bar A tuple of plotly.graph_objects.Bar instances or dicts with compatible properties box A tuple of plotly.graph_objects.Box instances or dicts with compatible properties candlestick A tuple of plotly.graph_objects.Candlestick instances or dicts with compatible properties carpet A tuple of plotly.graph_objects.Carpet instances or dicts with compatible properties choroplethmapbox A tuple of plotly.graph_objects.Choroplethmapbox instances or dicts with compatible properties choropleth A tuple of plotly.graph_objects.Choropleth instances or dicts with compatible properties cone A tuple of plotly.graph_objects.Cone instances or dicts with compatible properties contourcarpet A tuple of plotly.graph_objects.Contourcarpet instances or dicts with compatible properties contour A tuple of plotly.graph_objects.Contour instances or dicts with compatible properties densitymapbox A tuple of plotly.graph_objects.Densitymapbox instances or dicts with compatible properties funnelarea A tuple of plotly.graph_objects.Funnelarea instances or dicts with compatible properties funnel A tuple of plotly.graph_objects.Funnel instances or dicts with compatible properties heatmapgl A tuple of plotly.graph_objects.Heatmapgl instances or dicts with compatible properties heatmap A tuple of plotly.graph_objects.Heatmap instances or dicts with compatible properties histogram2dcontour A tuple of plotly.graph_objects.Histogram2dContour instances or dicts with compatible properties histogram2d A tuple of plotly.graph_objects.Histogram2d instances or dicts with compatible properties histogram A tuple of plotly.graph_objects.Histogram instances or dicts with compatible properties image A tuple of plotly.graph_objects.Image instances or dicts with compatible properties indicator A tuple of plotly.graph_objects.Indicator instances or dicts with compatible properties isosurface A tuple of plotly.graph_objects.Isosurface instances or dicts with compatible properties mesh3d A tuple of plotly.graph_objects.Mesh3d instances or dicts with compatible properties ohlc A tuple of plotly.graph_objects.Ohlc instances or dicts with compatible properties parcats A tuple of plotly.graph_objects.Parcats instances or dicts with compatible properties parcoords A tuple of plotly.graph_objects.Parcoords instances or dicts with compatible properties pie A tuple of plotly.graph_objects.Pie instances or dicts with compatible properties pointcloud A tuple of plotly.graph_objects.Pointcloud instances or dicts with compatible properties sankey A tuple of plotly.graph_objects.Sankey instances or dicts with compatible properties scatter3d A tuple of plotly.graph_objects.Scatter3d instances or dicts with compatible properties scattercarpet A tuple of plotly.graph_objects.Scattercarpet instances or dicts with compatible properties scattergeo A tuple of plotly.graph_objects.Scattergeo instances or dicts with compatible properties scattergl A tuple of plotly.graph_objects.Scattergl instances or dicts with compatible properties scattermapbox A tuple of plotly.graph_objects.Scattermapbox instances or dicts with compatible properties scatterpolargl A tuple of plotly.graph_objects.Scatterpolargl instances or dicts with compatible properties scatterpolar A tuple of plotly.graph_objects.Scatterpolar instances or dicts with compatible properties scatter A tuple of plotly.graph_objects.Scatter instances or dicts with compatible properties scatterternary A tuple of plotly.graph_objects.Scatterternary instances or dicts with compatible properties splom A tuple of plotly.graph_objects.Splom instances or dicts with compatible properties streamtube A tuple of plotly.graph_objects.Streamtube instances or dicts with compatible properties sunburst A tuple of plotly.graph_objects.Sunburst instances or dicts with compatible properties surface A tuple of plotly.graph_objects.Surface instances or dicts with compatible properties table A tuple of plotly.graph_objects.Table instances or dicts with compatible properties treemap A tuple of plotly.graph_objects.Treemap instances or dicts with compatible properties violin A tuple of plotly.graph_objects.Violin instances or dicts with compatible properties volume A tuple of plotly.graph_objects.Volume instances or dicts with compatible properties waterfall A tuple of plotly.graph_objects.Waterfall instances or dicts with compatible properties Returns ------- plotly.graph_objs.layout.template.Data """ return self["data"] @data.setter def data(self, val): self["data"] = val # layout # ------ @property def layout(self): """ The 'layout' property is an instance of Layout that may be specified as: - An instance of plotly.graph_objs.Layout - A dict of string/value properties that will be passed to the Layout constructor Supported dict properties: Returns ------- plotly.graph_objs.layout.template.Layout """ return self["layout"] @layout.setter def layout(self, val): self["layout"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ data plotly.graph_objects.layout.template.Data instance or dict with compatible properties layout plotly.graph_objects.Layout instance or dict with compatible properties """ def __init__(self, arg=None, data=None, layout=None, **kwargs): """ Construct a new Template object Default attributes to be applied to the plot. This should be a dict with format: `{'layout': layoutTemplate, 'data': {trace_type: [traceTemplate, ...], ...}}` where `layoutTemplate` is a dict matching the structure of `figure.layout` and `traceTemplate` is a dict matching the structure of the trace with type `trace_type` (e.g. 'scatter'). Alternatively, this may be specified as an instance of plotly.graph_objs.layout.Template. Trace templates are applied cyclically to traces of each type. Container arrays (eg `annotations`) have special handling: An object ending in `defaults` (eg `annotationdefaults`) is applied to each array item. But if an item has a `templateitemname` key we look in the template array for an item with matching `name` and apply that instead. If no matching `name` is found we mark the item invisible. Any named template item not referenced is appended to the end of the array, so this can be used to add a watermark annotation or a logo image, for example. To omit one of these items on the plot, make an item with matching `templateitemname` and `visible: false`. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.Template data plotly.graph_objects.layout.template.Data instance or dict with compatible properties layout plotly.graph_objects.Layout instance or dict with compatible properties Returns ------- Template """ super(Template, self).__init__("template") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.Template constructor must be a dict or an instance of plotly.graph_objs.layout.Template""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout import template as v_template # Initialize validators # --------------------- self._validators["data"] = v_template.DataValidator() self._validators["layout"] = v_template.LayoutValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("data", None) self["data"] = data if data is not None else _v _v = arg.pop("layout", None) self["layout"] = layout if layout is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Slider(_BaseLayoutHierarchyType): # active # ------ @property def active(self): """ Determines which button (by index starting from 0) is considered active. The 'active' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["active"] @active.setter def active(self, val): self["active"] = val # activebgcolor # ------------- @property def activebgcolor(self): """ Sets the background color of the slider grip while dragging. The 'activebgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["activebgcolor"] @activebgcolor.setter def activebgcolor(self, val): self["activebgcolor"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the slider. The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the color of the border enclosing the slider. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # borderwidth # ----------- @property def borderwidth(self): """ Sets the width (in px) of the border enclosing the slider. The 'borderwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["borderwidth"] @borderwidth.setter def borderwidth(self, val): self["borderwidth"] = val # currentvalue # ------------ @property def currentvalue(self): """ The 'currentvalue' property is an instance of Currentvalue that may be specified as: - An instance of plotly.graph_objs.layout.slider.Currentvalue - A dict of string/value properties that will be passed to the Currentvalue constructor Supported dict properties: font Sets the font of the current value label text. offset The amount of space, in pixels, between the current value label and the slider. prefix When currentvalue.visible is true, this sets the prefix of the label. suffix When currentvalue.visible is true, this sets the suffix of the label. visible Shows the currently-selected value above the slider. xanchor The alignment of the value readout relative to the length of the slider. Returns ------- plotly.graph_objs.layout.slider.Currentvalue """ return self["currentvalue"] @currentvalue.setter def currentvalue(self, val): self["currentvalue"] = val # font # ---- @property def font(self): """ Sets the font of the slider step labels. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.layout.slider.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.layout.slider.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # len # --- @property def len(self): """ Sets the length of the slider This measure excludes the padding of both ends. That is, the slider's length is this length minus the padding on both ends. The 'len' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["len"] @len.setter def len(self, val): self["len"] = val # lenmode # ------- @property def lenmode(self): """ Determines whether this slider length is set in units of plot "fraction" or in *pixels. Use `len` to set the value. The 'lenmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["lenmode"] @lenmode.setter def lenmode(self, val): self["lenmode"] = val # minorticklen # ------------ @property def minorticklen(self): """ Sets the length in pixels of minor step tick marks The 'minorticklen' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["minorticklen"] @minorticklen.setter def minorticklen(self, val): self["minorticklen"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # pad # --- @property def pad(self): """ Set the padding of the slider component along each side. The 'pad' property is an instance of Pad that may be specified as: - An instance of plotly.graph_objs.layout.slider.Pad - A dict of string/value properties that will be passed to the Pad constructor Supported dict properties: b The amount of padding (in px) along the bottom of the component. l The amount of padding (in px) on the left side of the component. r The amount of padding (in px) on the right side of the component. t The amount of padding (in px) along the top of the component. Returns ------- plotly.graph_objs.layout.slider.Pad """ return self["pad"] @pad.setter def pad(self, val): self["pad"] = val # steps # ----- @property def steps(self): """ The 'steps' property is a tuple of instances of Step that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.slider.Step - A list or tuple of dicts of string/value properties that will be passed to the Step constructor Supported dict properties: args Sets the arguments values to be passed to the Plotly method set in `method` on slide. execute When true, the API method is executed. When false, all other behaviors are the same and command execution is skipped. This may be useful when hooking into, for example, the `plotly_sliderchange` method and executing the API command manually without losing the benefit of the slider automatically binding to the state of the plot through the specification of `method` and `args`. label Sets the text label to appear on the slider method Sets the Plotly method to be called when the slider value is changed. If the `skip` method is used, the API slider will function as normal but will perform no API calls and will not bind automatically to state updates. This may be used to create a component interface and attach to slider events manually via JavaScript. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value Sets the value of the slider step, used to refer to the step programatically. Defaults to the slider label if not provided. visible Determines whether or not this step is included in the slider. Returns ------- tuple[plotly.graph_objs.layout.slider.Step] """ return self["steps"] @steps.setter def steps(self, val): self["steps"] = val # stepdefaults # ------------ @property def stepdefaults(self): """ When used in a template (as layout.template.layout.slider.stepdefaults), sets the default property values to use for elements of layout.slider.steps The 'stepdefaults' property is an instance of Step that may be specified as: - An instance of plotly.graph_objs.layout.slider.Step - A dict of string/value properties that will be passed to the Step constructor Supported dict properties: Returns ------- plotly.graph_objs.layout.slider.Step """ return self["stepdefaults"] @stepdefaults.setter def stepdefaults(self, val): self["stepdefaults"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # tickcolor # --------- @property def tickcolor(self): """ Sets the color of the border enclosing the slider. The 'tickcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["tickcolor"] @tickcolor.setter def tickcolor(self, val): self["tickcolor"] = val # ticklen # ------- @property def ticklen(self): """ Sets the length in pixels of step tick marks The 'ticklen' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ticklen"] @ticklen.setter def ticklen(self, val): self["ticklen"] = val # tickwidth # --------- @property def tickwidth(self): """ Sets the tick width (in px). The 'tickwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["tickwidth"] @tickwidth.setter def tickwidth(self, val): self["tickwidth"] = val # transition # ---------- @property def transition(self): """ The 'transition' property is an instance of Transition that may be specified as: - An instance of plotly.graph_objs.layout.slider.Transition - A dict of string/value properties that will be passed to the Transition constructor Supported dict properties: duration Sets the duration of the slider transition easing Sets the easing function of the slider transition Returns ------- plotly.graph_objs.layout.slider.Transition """ return self["transition"] @transition.setter def transition(self, val): self["transition"] = val # visible # ------- @property def visible(self): """ Determines whether or not the slider is visible. The 'visible' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # x # - @property def x(self): """ Sets the x position (in normalized coordinates) of the slider. The 'x' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["x"] @x.setter def x(self, val): self["x"] = val # xanchor # ------- @property def xanchor(self): """ Sets the slider's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the range selector. The 'xanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'left', 'center', 'right'] Returns ------- Any """ return self["xanchor"] @xanchor.setter def xanchor(self, val): self["xanchor"] = val # y # - @property def y(self): """ Sets the y position (in normalized coordinates) of the slider. The 'y' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["y"] @y.setter def y(self, val): self["y"] = val # yanchor # ------- @property def yanchor(self): """ Sets the slider's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the range selector. The 'yanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'top', 'middle', 'bottom'] Returns ------- Any """ return self["yanchor"] @yanchor.setter def yanchor(self, val): self["yanchor"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ active Determines which button (by index starting from 0) is considered active. activebgcolor Sets the background color of the slider grip while dragging. bgcolor Sets the background color of the slider. bordercolor Sets the color of the border enclosing the slider. borderwidth Sets the width (in px) of the border enclosing the slider. currentvalue plotly.graph_objects.layout.slider.Currentvalue instance or dict with compatible properties font Sets the font of the slider step labels. len Sets the length of the slider This measure excludes the padding of both ends. That is, the slider's length is this length minus the padding on both ends. lenmode Determines whether this slider length is set in units of plot "fraction" or in *pixels. Use `len` to set the value. minorticklen Sets the length in pixels of minor step tick marks name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. pad Set the padding of the slider component along each side. steps A tuple of plotly.graph_objects.layout.slider.Step instances or dicts with compatible properties stepdefaults When used in a template (as layout.template.layout.slider.stepdefaults), sets the default property values to use for elements of layout.slider.steps templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. tickcolor Sets the color of the border enclosing the slider. ticklen Sets the length in pixels of step tick marks tickwidth Sets the tick width (in px). transition plotly.graph_objects.layout.slider.Transition instance or dict with compatible properties visible Determines whether or not the slider is visible. x Sets the x position (in normalized coordinates) of the slider. xanchor Sets the slider's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the range selector. y Sets the y position (in normalized coordinates) of the slider. yanchor Sets the slider's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the range selector. """ def __init__( self, arg=None, active=None, activebgcolor=None, bgcolor=None, bordercolor=None, borderwidth=None, currentvalue=None, font=None, len=None, lenmode=None, minorticklen=None, name=None, pad=None, steps=None, stepdefaults=None, templateitemname=None, tickcolor=None, ticklen=None, tickwidth=None, transition=None, visible=None, x=None, xanchor=None, y=None, yanchor=None, **kwargs ): """ Construct a new Slider object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.Slider active Determines which button (by index starting from 0) is considered active. activebgcolor Sets the background color of the slider grip while dragging. bgcolor Sets the background color of the slider. bordercolor Sets the color of the border enclosing the slider. borderwidth Sets the width (in px) of the border enclosing the slider. currentvalue plotly.graph_objects.layout.slider.Currentvalue instance or dict with compatible properties font Sets the font of the slider step labels. len Sets the length of the slider This measure excludes the padding of both ends. That is, the slider's length is this length minus the padding on both ends. lenmode Determines whether this slider length is set in units of plot "fraction" or in *pixels. Use `len` to set the value. minorticklen Sets the length in pixels of minor step tick marks name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. pad Set the padding of the slider component along each side. steps A tuple of plotly.graph_objects.layout.slider.Step instances or dicts with compatible properties stepdefaults When used in a template (as layout.template.layout.slider.stepdefaults), sets the default property values to use for elements of layout.slider.steps templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. tickcolor Sets the color of the border enclosing the slider. ticklen Sets the length in pixels of step tick marks tickwidth Sets the tick width (in px). transition plotly.graph_objects.layout.slider.Transition instance or dict with compatible properties visible Determines whether or not the slider is visible. x Sets the x position (in normalized coordinates) of the slider. xanchor Sets the slider's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the range selector. y Sets the y position (in normalized coordinates) of the slider. yanchor Sets the slider's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the range selector. Returns ------- Slider """ super(Slider, self).__init__("sliders") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.Slider constructor must be a dict or an instance of plotly.graph_objs.layout.Slider""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout import slider as v_slider # Initialize validators # --------------------- self._validators["active"] = v_slider.ActiveValidator() self._validators["activebgcolor"] = v_slider.ActivebgcolorValidator() self._validators["bgcolor"] = v_slider.BgcolorValidator() self._validators["bordercolor"] = v_slider.BordercolorValidator() self._validators["borderwidth"] = v_slider.BorderwidthValidator() self._validators["currentvalue"] = v_slider.CurrentvalueValidator() self._validators["font"] = v_slider.FontValidator() self._validators["len"] = v_slider.LenValidator() self._validators["lenmode"] = v_slider.LenmodeValidator() self._validators["minorticklen"] = v_slider.MinorticklenValidator() self._validators["name"] = v_slider.NameValidator() self._validators["pad"] = v_slider.PadValidator() self._validators["steps"] = v_slider.StepsValidator() self._validators["stepdefaults"] = v_slider.StepValidator() self._validators["templateitemname"] = v_slider.TemplateitemnameValidator() self._validators["tickcolor"] = v_slider.TickcolorValidator() self._validators["ticklen"] = v_slider.TicklenValidator() self._validators["tickwidth"] = v_slider.TickwidthValidator() self._validators["transition"] = v_slider.TransitionValidator() self._validators["visible"] = v_slider.VisibleValidator() self._validators["x"] = v_slider.XValidator() self._validators["xanchor"] = v_slider.XanchorValidator() self._validators["y"] = v_slider.YValidator() self._validators["yanchor"] = v_slider.YanchorValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("active", None) self["active"] = active if active is not None else _v _v = arg.pop("activebgcolor", None) self["activebgcolor"] = activebgcolor if activebgcolor is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("borderwidth", None) self["borderwidth"] = borderwidth if borderwidth is not None else _v _v = arg.pop("currentvalue", None) self["currentvalue"] = currentvalue if currentvalue is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("len", None) self["len"] = len if len is not None else _v _v = arg.pop("lenmode", None) self["lenmode"] = lenmode if lenmode is not None else _v _v = arg.pop("minorticklen", None) self["minorticklen"] = minorticklen if minorticklen is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("pad", None) self["pad"] = pad if pad is not None else _v _v = arg.pop("steps", None) self["steps"] = steps if steps is not None else _v _v = arg.pop("stepdefaults", None) self["stepdefaults"] = stepdefaults if stepdefaults is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("tickcolor", None) self["tickcolor"] = tickcolor if tickcolor is not None else _v _v = arg.pop("ticklen", None) self["ticklen"] = ticklen if ticklen is not None else _v _v = arg.pop("tickwidth", None) self["tickwidth"] = tickwidth if tickwidth is not None else _v _v = arg.pop("transition", None) self["transition"] = transition if transition is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xanchor", None) self["xanchor"] = xanchor if xanchor is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("yanchor", None) self["yanchor"] = yanchor if yanchor is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Shape(_BaseLayoutHierarchyType): # fillcolor # --------- @property def fillcolor(self): """ Sets the color filling the shape's interior. The 'fillcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["fillcolor"] @fillcolor.setter def fillcolor(self, val): self["fillcolor"] = val # layer # ----- @property def layer(self): """ Specifies whether shapes are drawn below or above traces. The 'layer' property is an enumeration that may be specified as: - One of the following enumeration values: ['below', 'above'] Returns ------- Any """ return self["layer"] @layer.setter def layer(self, val): self["layer"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.layout.shape.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: color Sets the line color. dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). width Sets the line width (in px). Returns ------- plotly.graph_objs.layout.shape.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the shape. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # path # ---- @property def path(self): """ For `type` "path" - a valid SVG path with the pixel values replaced by data values in `xsizemode`/`ysizemode` being "scaled" and taken unmodified as pixels relative to `xanchor` and `yanchor` in case of "pixel" size mode. There are a few restrictions / quirks only absolute instructions, not relative. So the allowed segments are: M, L, H, V, Q, C, T, S, and Z arcs (A) are not allowed because radius rx and ry are relative. In the future we could consider supporting relative commands, but we would have to decide on how to handle date and log axes. Note that even as is, Q and C Bezier paths that are smooth on linear axes may not be smooth on log, and vice versa. no chained "polybezier" commands - specify the segment type for each one. On category axes, values are numbers scaled to the serial numbers of categories because using the categories themselves there would be no way to describe fractional positions On data axes: because space and T are both normal components of path strings, we can't use either to separate date from time parts. Therefore we'll use underscore for this purpose: 2015-02-21_13:45:56.789 The 'path' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["path"] @path.setter def path(self, val): self["path"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # type # ---- @property def type(self): """ Specifies the shape type to be drawn. If "line", a line is drawn from (`x0`,`y0`) to (`x1`,`y1`) with respect to the axes' sizing mode. If "circle", a circle is drawn from ((`x0`+`x1`)/2, (`y0`+`y1`)/2)) with radius (|(`x0`+`x1`)/2 - `x0`|, |(`y0`+`y1`)/2 -`y0`)|) with respect to the axes' sizing mode. If "rect", a rectangle is drawn linking (`x0`,`y0`), (`x1`,`y0`), (`x1`,`y1`), (`x0`,`y1`), (`x0`,`y0`) with respect to the axes' sizing mode. If "path", draw a custom SVG path using `path`. with respect to the axes' sizing mode. The 'type' property is an enumeration that may be specified as: - One of the following enumeration values: ['circle', 'rect', 'path', 'line'] Returns ------- Any """ return self["type"] @type.setter def type(self, val): self["type"] = val # visible # ------- @property def visible(self): """ Determines whether or not this shape is visible. The 'visible' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # x0 # -- @property def x0(self): """ Sets the shape's starting x position. See `type` and `xsizemode` for more info. The 'x0' property accepts values of any type Returns ------- Any """ return self["x0"] @x0.setter def x0(self, val): self["x0"] = val # x1 # -- @property def x1(self): """ Sets the shape's end x position. See `type` and `xsizemode` for more info. The 'x1' property accepts values of any type Returns ------- Any """ return self["x1"] @x1.setter def x1(self, val): self["x1"] = val # xanchor # ------- @property def xanchor(self): """ Only relevant in conjunction with `xsizemode` set to "pixel". Specifies the anchor point on the x axis to which `x0`, `x1` and x coordinates within `path` are relative to. E.g. useful to attach a pixel sized shape to a certain data value. No effect when `xsizemode` not set to "pixel". The 'xanchor' property accepts values of any type Returns ------- Any """ return self["xanchor"] @xanchor.setter def xanchor(self, val): self["xanchor"] = val # xref # ---- @property def xref(self): """ Sets the shape's x coordinate axis. If set to an x axis id (e.g. "x" or "x2"), the `x` position refers to an x coordinate. If set to "paper", the `x` position refers to the distance from the left side of the plotting area in normalized coordinates where 0 (1) corresponds to the left (right) side. If the axis `type` is "log", then you must take the log of your desired range. If the axis `type` is "date", then you must convert the date to unix time in milliseconds. The 'xref' property is an enumeration that may be specified as: - One of the following enumeration values: ['paper'] - A string that matches one of the following regular expressions: ['^x([2-9]|[1-9][0-9]+)?$'] Returns ------- Any """ return self["xref"] @xref.setter def xref(self, val): self["xref"] = val # xsizemode # --------- @property def xsizemode(self): """ Sets the shapes's sizing mode along the x axis. If set to "scaled", `x0`, `x1` and x coordinates within `path` refer to data values on the x axis or a fraction of the plot area's width (`xref` set to "paper"). If set to "pixel", `xanchor` specifies the x position in terms of data or plot fraction but `x0`, `x1` and x coordinates within `path` are pixels relative to `xanchor`. This way, the shape can have a fixed width while maintaining a position relative to data or plot fraction. The 'xsizemode' property is an enumeration that may be specified as: - One of the following enumeration values: ['scaled', 'pixel'] Returns ------- Any """ return self["xsizemode"] @xsizemode.setter def xsizemode(self, val): self["xsizemode"] = val # y0 # -- @property def y0(self): """ Sets the shape's starting y position. See `type` and `ysizemode` for more info. The 'y0' property accepts values of any type Returns ------- Any """ return self["y0"] @y0.setter def y0(self, val): self["y0"] = val # y1 # -- @property def y1(self): """ Sets the shape's end y position. See `type` and `ysizemode` for more info. The 'y1' property accepts values of any type Returns ------- Any """ return self["y1"] @y1.setter def y1(self, val): self["y1"] = val # yanchor # ------- @property def yanchor(self): """ Only relevant in conjunction with `ysizemode` set to "pixel". Specifies the anchor point on the y axis to which `y0`, `y1` and y coordinates within `path` are relative to. E.g. useful to attach a pixel sized shape to a certain data value. No effect when `ysizemode` not set to "pixel". The 'yanchor' property accepts values of any type Returns ------- Any """ return self["yanchor"] @yanchor.setter def yanchor(self, val): self["yanchor"] = val # yref # ---- @property def yref(self): """ Sets the annotation's y coordinate axis. If set to an y axis id (e.g. "y" or "y2"), the `y` position refers to an y coordinate If set to "paper", the `y` position refers to the distance from the bottom of the plotting area in normalized coordinates where 0 (1) corresponds to the bottom (top). The 'yref' property is an enumeration that may be specified as: - One of the following enumeration values: ['paper'] - A string that matches one of the following regular expressions: ['^y([2-9]|[1-9][0-9]+)?$'] Returns ------- Any """ return self["yref"] @yref.setter def yref(self, val): self["yref"] = val # ysizemode # --------- @property def ysizemode(self): """ Sets the shapes's sizing mode along the y axis. If set to "scaled", `y0`, `y1` and y coordinates within `path` refer to data values on the y axis or a fraction of the plot area's height (`yref` set to "paper"). If set to "pixel", `yanchor` specifies the y position in terms of data or plot fraction but `y0`, `y1` and y coordinates within `path` are pixels relative to `yanchor`. This way, the shape can have a fixed height while maintaining a position relative to data or plot fraction. The 'ysizemode' property is an enumeration that may be specified as: - One of the following enumeration values: ['scaled', 'pixel'] Returns ------- Any """ return self["ysizemode"] @ysizemode.setter def ysizemode(self, val): self["ysizemode"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ fillcolor Sets the color filling the shape's interior. layer Specifies whether shapes are drawn below or above traces. line plotly.graph_objects.layout.shape.Line instance or dict with compatible properties name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. opacity Sets the opacity of the shape. path For `type` "path" - a valid SVG path with the pixel values replaced by data values in `xsizemode`/`ysizemode` being "scaled" and taken unmodified as pixels relative to `xanchor` and `yanchor` in case of "pixel" size mode. There are a few restrictions / quirks only absolute instructions, not relative. So the allowed segments are: M, L, H, V, Q, C, T, S, and Z arcs (A) are not allowed because radius rx and ry are relative. In the future we could consider supporting relative commands, but we would have to decide on how to handle date and log axes. Note that even as is, Q and C Bezier paths that are smooth on linear axes may not be smooth on log, and vice versa. no chained "polybezier" commands - specify the segment type for each one. On category axes, values are numbers scaled to the serial numbers of categories because using the categories themselves there would be no way to describe fractional positions On data axes: because space and T are both normal components of path strings, we can't use either to separate date from time parts. Therefore we'll use underscore for this purpose: 2015-02-21_13:45:56.789 templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. type Specifies the shape type to be drawn. If "line", a line is drawn from (`x0`,`y0`) to (`x1`,`y1`) with respect to the axes' sizing mode. If "circle", a circle is drawn from ((`x0`+`x1`)/2, (`y0`+`y1`)/2)) with radius (|(`x0`+`x1`)/2 - `x0`|, |(`y0`+`y1`)/2 -`y0`)|) with respect to the axes' sizing mode. If "rect", a rectangle is drawn linking (`x0`,`y0`), (`x1`,`y0`), (`x1`,`y1`), (`x0`,`y1`), (`x0`,`y0`) with respect to the axes' sizing mode. If "path", draw a custom SVG path using `path`. with respect to the axes' sizing mode. visible Determines whether or not this shape is visible. x0 Sets the shape's starting x position. See `type` and `xsizemode` for more info. x1 Sets the shape's end x position. See `type` and `xsizemode` for more info. xanchor Only relevant in conjunction with `xsizemode` set to "pixel". Specifies the anchor point on the x axis to which `x0`, `x1` and x coordinates within `path` are relative to. E.g. useful to attach a pixel sized shape to a certain data value. No effect when `xsizemode` not set to "pixel". xref Sets the shape's x coordinate axis. If set to an x axis id (e.g. "x" or "x2"), the `x` position refers to an x coordinate. If set to "paper", the `x` position refers to the distance from the left side of the plotting area in normalized coordinates where 0 (1) corresponds to the left (right) side. If the axis `type` is "log", then you must take the log of your desired range. If the axis `type` is "date", then you must convert the date to unix time in milliseconds. xsizemode Sets the shapes's sizing mode along the x axis. If set to "scaled", `x0`, `x1` and x coordinates within `path` refer to data values on the x axis or a fraction of the plot area's width (`xref` set to "paper"). If set to "pixel", `xanchor` specifies the x position in terms of data or plot fraction but `x0`, `x1` and x coordinates within `path` are pixels relative to `xanchor`. This way, the shape can have a fixed width while maintaining a position relative to data or plot fraction. y0 Sets the shape's starting y position. See `type` and `ysizemode` for more info. y1 Sets the shape's end y position. See `type` and `ysizemode` for more info. yanchor Only relevant in conjunction with `ysizemode` set to "pixel". Specifies the anchor point on the y axis to which `y0`, `y1` and y coordinates within `path` are relative to. E.g. useful to attach a pixel sized shape to a certain data value. No effect when `ysizemode` not set to "pixel". yref Sets the annotation's y coordinate axis. If set to an y axis id (e.g. "y" or "y2"), the `y` position refers to an y coordinate If set to "paper", the `y` position refers to the distance from the bottom of the plotting area in normalized coordinates where 0 (1) corresponds to the bottom (top). ysizemode Sets the shapes's sizing mode along the y axis. If set to "scaled", `y0`, `y1` and y coordinates within `path` refer to data values on the y axis or a fraction of the plot area's height (`yref` set to "paper"). If set to "pixel", `yanchor` specifies the y position in terms of data or plot fraction but `y0`, `y1` and y coordinates within `path` are pixels relative to `yanchor`. This way, the shape can have a fixed height while maintaining a position relative to data or plot fraction. """ def __init__( self, arg=None, fillcolor=None, layer=None, line=None, name=None, opacity=None, path=None, templateitemname=None, type=None, visible=None, x0=None, x1=None, xanchor=None, xref=None, xsizemode=None, y0=None, y1=None, yanchor=None, yref=None, ysizemode=None, **kwargs ): """ Construct a new Shape object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.Shape fillcolor Sets the color filling the shape's interior. layer Specifies whether shapes are drawn below or above traces. line plotly.graph_objects.layout.shape.Line instance or dict with compatible properties name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. opacity Sets the opacity of the shape. path For `type` "path" - a valid SVG path with the pixel values replaced by data values in `xsizemode`/`ysizemode` being "scaled" and taken unmodified as pixels relative to `xanchor` and `yanchor` in case of "pixel" size mode. There are a few restrictions / quirks only absolute instructions, not relative. So the allowed segments are: M, L, H, V, Q, C, T, S, and Z arcs (A) are not allowed because radius rx and ry are relative. In the future we could consider supporting relative commands, but we would have to decide on how to handle date and log axes. Note that even as is, Q and C Bezier paths that are smooth on linear axes may not be smooth on log, and vice versa. no chained "polybezier" commands - specify the segment type for each one. On category axes, values are numbers scaled to the serial numbers of categories because using the categories themselves there would be no way to describe fractional positions On data axes: because space and T are both normal components of path strings, we can't use either to separate date from time parts. Therefore we'll use underscore for this purpose: 2015-02-21_13:45:56.789 templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. type Specifies the shape type to be drawn. If "line", a line is drawn from (`x0`,`y0`) to (`x1`,`y1`) with respect to the axes' sizing mode. If "circle", a circle is drawn from ((`x0`+`x1`)/2, (`y0`+`y1`)/2)) with radius (|(`x0`+`x1`)/2 - `x0`|, |(`y0`+`y1`)/2 -`y0`)|) with respect to the axes' sizing mode. If "rect", a rectangle is drawn linking (`x0`,`y0`), (`x1`,`y0`), (`x1`,`y1`), (`x0`,`y1`), (`x0`,`y0`) with respect to the axes' sizing mode. If "path", draw a custom SVG path using `path`. with respect to the axes' sizing mode. visible Determines whether or not this shape is visible. x0 Sets the shape's starting x position. See `type` and `xsizemode` for more info. x1 Sets the shape's end x position. See `type` and `xsizemode` for more info. xanchor Only relevant in conjunction with `xsizemode` set to "pixel". Specifies the anchor point on the x axis to which `x0`, `x1` and x coordinates within `path` are relative to. E.g. useful to attach a pixel sized shape to a certain data value. No effect when `xsizemode` not set to "pixel". xref Sets the shape's x coordinate axis. If set to an x axis id (e.g. "x" or "x2"), the `x` position refers to an x coordinate. If set to "paper", the `x` position refers to the distance from the left side of the plotting area in normalized coordinates where 0 (1) corresponds to the left (right) side. If the axis `type` is "log", then you must take the log of your desired range. If the axis `type` is "date", then you must convert the date to unix time in milliseconds. xsizemode Sets the shapes's sizing mode along the x axis. If set to "scaled", `x0`, `x1` and x coordinates within `path` refer to data values on the x axis or a fraction of the plot area's width (`xref` set to "paper"). If set to "pixel", `xanchor` specifies the x position in terms of data or plot fraction but `x0`, `x1` and x coordinates within `path` are pixels relative to `xanchor`. This way, the shape can have a fixed width while maintaining a position relative to data or plot fraction. y0 Sets the shape's starting y position. See `type` and `ysizemode` for more info. y1 Sets the shape's end y position. See `type` and `ysizemode` for more info. yanchor Only relevant in conjunction with `ysizemode` set to "pixel". Specifies the anchor point on the y axis to which `y0`, `y1` and y coordinates within `path` are relative to. E.g. useful to attach a pixel sized shape to a certain data value. No effect when `ysizemode` not set to "pixel". yref Sets the annotation's y coordinate axis. If set to an y axis id (e.g. "y" or "y2"), the `y` position refers to an y coordinate If set to "paper", the `y` position refers to the distance from the bottom of the plotting area in normalized coordinates where 0 (1) corresponds to the bottom (top). ysizemode Sets the shapes's sizing mode along the y axis. If set to "scaled", `y0`, `y1` and y coordinates within `path` refer to data values on the y axis or a fraction of the plot area's height (`yref` set to "paper"). If set to "pixel", `yanchor` specifies the y position in terms of data or plot fraction but `y0`, `y1` and y coordinates within `path` are pixels relative to `yanchor`. This way, the shape can have a fixed height while maintaining a position relative to data or plot fraction. Returns ------- Shape """ super(Shape, self).__init__("shapes") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.Shape constructor must be a dict or an instance of plotly.graph_objs.layout.Shape""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout import shape as v_shape # Initialize validators # --------------------- self._validators["fillcolor"] = v_shape.FillcolorValidator() self._validators["layer"] = v_shape.LayerValidator() self._validators["line"] = v_shape.LineValidator() self._validators["name"] = v_shape.NameValidator() self._validators["opacity"] = v_shape.OpacityValidator() self._validators["path"] = v_shape.PathValidator() self._validators["templateitemname"] = v_shape.TemplateitemnameValidator() self._validators["type"] = v_shape.TypeValidator() self._validators["visible"] = v_shape.VisibleValidator() self._validators["x0"] = v_shape.X0Validator() self._validators["x1"] = v_shape.X1Validator() self._validators["xanchor"] = v_shape.XanchorValidator() self._validators["xref"] = v_shape.XrefValidator() self._validators["xsizemode"] = v_shape.XsizemodeValidator() self._validators["y0"] = v_shape.Y0Validator() self._validators["y1"] = v_shape.Y1Validator() self._validators["yanchor"] = v_shape.YanchorValidator() self._validators["yref"] = v_shape.YrefValidator() self._validators["ysizemode"] = v_shape.YsizemodeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("fillcolor", None) self["fillcolor"] = fillcolor if fillcolor is not None else _v _v = arg.pop("layer", None) self["layer"] = layer if layer is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("path", None) self["path"] = path if path is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("type", None) self["type"] = type if type is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("x0", None) self["x0"] = x0 if x0 is not None else _v _v = arg.pop("x1", None) self["x1"] = x1 if x1 is not None else _v _v = arg.pop("xanchor", None) self["xanchor"] = xanchor if xanchor is not None else _v _v = arg.pop("xref", None) self["xref"] = xref if xref is not None else _v _v = arg.pop("xsizemode", None) self["xsizemode"] = xsizemode if xsizemode is not None else _v _v = arg.pop("y0", None) self["y0"] = y0 if y0 is not None else _v _v = arg.pop("y1", None) self["y1"] = y1 if y1 is not None else _v _v = arg.pop("yanchor", None) self["yanchor"] = yanchor if yanchor is not None else _v _v = arg.pop("yref", None) self["yref"] = yref if yref is not None else _v _v = arg.pop("ysizemode", None) self["ysizemode"] = ysizemode if ysizemode is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Scene(_BaseLayoutHierarchyType): # annotations # ----------- @property def annotations(self): """ The 'annotations' property is a tuple of instances of Annotation that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.scene.Annotation - A list or tuple of dicts of string/value properties that will be passed to the Annotation constructor Supported dict properties: align Sets the horizontal alignment of the `text` within the box. Has an effect only if `text` spans more two or more lines (i.e. `text` contains one or more
HTML tags) or if an explicit width is set to override the text width. arrowcolor Sets the color of the annotation arrow. arrowhead Sets the end annotation arrow head style. arrowside Sets the annotation arrow head position. arrowsize Sets the size of the end annotation arrow head, relative to `arrowwidth`. A value of 1 (default) gives a head about 3x as wide as the line. arrowwidth Sets the width (in px) of annotation arrow line. ax Sets the x component of the arrow tail about the arrow head (in pixels). ay Sets the y component of the arrow tail about the arrow head (in pixels). bgcolor Sets the background color of the annotation. bordercolor Sets the color of the border enclosing the annotation `text`. borderpad Sets the padding (in px) between the `text` and the enclosing border. borderwidth Sets the width (in px) of the border enclosing the annotation `text`. captureevents Determines whether the annotation text box captures mouse move and click events, or allows those events to pass through to data points in the plot that may be behind the annotation. By default `captureevents` is False unless `hovertext` is provided. If you use the event `plotly_clickannotation` without `hovertext` you must explicitly enable `captureevents`. font Sets the annotation text font. height Sets an explicit height for the text box. null (default) lets the text set the box height. Taller text will be clipped. hoverlabel plotly.graph_objects.layout.scene.annotation.Ho verlabel instance or dict with compatible properties hovertext Sets text to appear when hovering over this annotation. If omitted or blank, no hover label will appear. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. opacity Sets the opacity of the annotation (text + arrow). showarrow Determines whether or not the annotation is drawn with an arrow. If True, `text` is placed near the arrow's tail. If False, `text` lines up with the `x` and `y` provided. standoff Sets a distance, in pixels, to move the end arrowhead away from the position it is pointing at, for example to point at the edge of a marker independent of zoom. Note that this shortens the arrow from the `ax` / `ay` vector, in contrast to `xshift` / `yshift` which moves everything by this amount. startarrowhead Sets the start annotation arrow head style. startarrowsize Sets the size of the start annotation arrow head, relative to `arrowwidth`. A value of 1 (default) gives a head about 3x as wide as the line. startstandoff Sets a distance, in pixels, to move the start arrowhead away from the position it is pointing at, for example to point at the edge of a marker independent of zoom. Note that this shortens the arrow from the `ax` / `ay` vector, in contrast to `xshift` / `yshift` which moves everything by this amount. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. text Sets the text associated with this annotation. Plotly uses a subset of HTML tags to do things like newline (
), bold (), italics (), hyperlinks (). Tags , , are also supported. textangle Sets the angle at which the `text` is drawn with respect to the horizontal. valign Sets the vertical alignment of the `text` within the box. Has an effect only if an explicit height is set to override the text height. visible Determines whether or not this annotation is visible. width Sets an explicit width for the text box. null (default) lets the text set the box width. Wider text will be clipped. There is no automatic wrapping; use
to start a new line. x Sets the annotation's x position. xanchor Sets the text box's horizontal position anchor This anchor binds the `x` position to the "left", "center" or "right" of the annotation. For example, if `x` is set to 1, `xref` to "paper" and `xanchor` to "right" then the right-most portion of the annotation lines up with the right-most edge of the plotting area. If "auto", the anchor is equivalent to "center" for data-referenced annotations or if there is an arrow, whereas for paper-referenced with no arrow, the anchor picked corresponds to the closest side. xshift Shifts the position of the whole annotation and arrow to the right (positive) or left (negative) by this many pixels. y Sets the annotation's y position. yanchor Sets the text box's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the annotation. For example, if `y` is set to 1, `yref` to "paper" and `yanchor` to "top" then the top- most portion of the annotation lines up with the top-most edge of the plotting area. If "auto", the anchor is equivalent to "middle" for data-referenced annotations or if there is an arrow, whereas for paper-referenced with no arrow, the anchor picked corresponds to the closest side. yshift Shifts the position of the whole annotation and arrow up (positive) or down (negative) by this many pixels. z Sets the annotation's z position. Returns ------- tuple[plotly.graph_objs.layout.scene.Annotation] """ return self["annotations"] @annotations.setter def annotations(self, val): self["annotations"] = val # annotationdefaults # ------------------ @property def annotationdefaults(self): """ When used in a template (as layout.template.layout.scene.annotationdefaults), sets the default property values to use for elements of layout.scene.annotations The 'annotationdefaults' property is an instance of Annotation that may be specified as: - An instance of plotly.graph_objs.layout.scene.Annotation - A dict of string/value properties that will be passed to the Annotation constructor Supported dict properties: Returns ------- plotly.graph_objs.layout.scene.Annotation """ return self["annotationdefaults"] @annotationdefaults.setter def annotationdefaults(self, val): self["annotationdefaults"] = val # aspectmode # ---------- @property def aspectmode(self): """ If "cube", this scene's axes are drawn as a cube, regardless of the axes' ranges. If "data", this scene's axes are drawn in proportion with the axes' ranges. If "manual", this scene's axes are drawn in proportion with the input of "aspectratio" (the default behavior if "aspectratio" is provided). If "auto", this scene's axes are drawn using the results of "data" except when one axis is more than four times the size of the two others, where in that case the results of "cube" are used. The 'aspectmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'cube', 'data', 'manual'] Returns ------- Any """ return self["aspectmode"] @aspectmode.setter def aspectmode(self, val): self["aspectmode"] = val # aspectratio # ----------- @property def aspectratio(self): """ Sets this scene's axis aspectratio. The 'aspectratio' property is an instance of Aspectratio that may be specified as: - An instance of plotly.graph_objs.layout.scene.Aspectratio - A dict of string/value properties that will be passed to the Aspectratio constructor Supported dict properties: x y z Returns ------- plotly.graph_objs.layout.scene.Aspectratio """ return self["aspectratio"] @aspectratio.setter def aspectratio(self, val): self["aspectratio"] = val # bgcolor # ------- @property def bgcolor(self): """ The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # camera # ------ @property def camera(self): """ The 'camera' property is an instance of Camera that may be specified as: - An instance of plotly.graph_objs.layout.scene.Camera - A dict of string/value properties that will be passed to the Camera constructor Supported dict properties: center Sets the (x,y,z) components of the 'center' camera vector This vector determines the translation (x,y,z) space about the center of this scene. By default, there is no such translation. eye Sets the (x,y,z) components of the 'eye' camera vector. This vector determines the view point about the origin of this scene. projection plotly.graph_objects.layout.scene.camera.Projec tion instance or dict with compatible properties up Sets the (x,y,z) components of the 'up' camera vector. This vector determines the up direction of this scene with respect to the page. The default is *{x: 0, y: 0, z: 1}* which means that the z axis points up. Returns ------- plotly.graph_objs.layout.scene.Camera """ return self["camera"] @camera.setter def camera(self, val): self["camera"] = val # domain # ------ @property def domain(self): """ The 'domain' property is an instance of Domain that may be specified as: - An instance of plotly.graph_objs.layout.scene.Domain - A dict of string/value properties that will be passed to the Domain constructor Supported dict properties: column If there is a layout grid, use the domain for this column in the grid for this scene subplot . row If there is a layout grid, use the domain for this row in the grid for this scene subplot . x Sets the horizontal domain of this scene subplot (in plot fraction). y Sets the vertical domain of this scene subplot (in plot fraction). Returns ------- plotly.graph_objs.layout.scene.Domain """ return self["domain"] @domain.setter def domain(self, val): self["domain"] = val # dragmode # -------- @property def dragmode(self): """ Determines the mode of drag interactions for this scene. The 'dragmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['orbit', 'turntable', 'zoom', 'pan', False] Returns ------- Any """ return self["dragmode"] @dragmode.setter def dragmode(self, val): self["dragmode"] = val # hovermode # --------- @property def hovermode(self): """ Determines the mode of hover interactions for this scene. The 'hovermode' property is an enumeration that may be specified as: - One of the following enumeration values: ['closest', False] Returns ------- Any """ return self["hovermode"] @hovermode.setter def hovermode(self, val): self["hovermode"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of user-driven changes in camera attributes. Defaults to `layout.uirevision`. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # xaxis # ----- @property def xaxis(self): """ The 'xaxis' property is an instance of XAxis that may be specified as: - An instance of plotly.graph_objs.layout.scene.XAxis - A dict of string/value properties that will be passed to the XAxis constructor Supported dict properties: autorange Determines whether or not the range of this axis is computed in relation to the input data. See `rangemode` for more info. If `range` is provided, then `autorange` is set to False. backgroundcolor Sets the background color of this axis' wall. calendar Sets the calendar system to use for `range` and `tick0` if this is a date axis. This does not set the calendar for interpreting data on this axis, that's specified in the trace or via the global `layout.calendar` categoryarray Sets the order in which categories on this axis appear. Only has an effect if `categoryorder` is set to "array". Used with `categoryorder`. categoryarraysrc Sets the source reference on plot.ly for categoryarray . categoryorder Specifies the ordering logic for the case of categorical variables. By default, plotly uses "trace", which specifies the order that is present in the data supplied. Set `categoryorder` to *category ascending* or *category descending* if order should be determined by the alphanumerical order of the category names. Set `categoryorder` to "array" to derive the ordering from the attribute `categoryarray`. If a category is not found in the `categoryarray` array, the sorting behavior for that attribute will be identical to the "trace" mode. The unspecified categories will follow the categories in `categoryarray`. Set `categoryorder` to *total ascending* or *total descending* if order should be determined by the numerical order of the values. Similarly, the order can be determined by the min, max, sum, mean or median of all the values. color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. gridcolor Sets the color of the grid lines. gridwidth Sets the width (in px) of the grid lines. hoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" linecolor Sets the axis line color. linewidth Sets the width (in px) of the axis line. mirror Determines if the axis lines or/and ticks are mirrored to the opposite side of the plotting area. If True, the axis lines are mirrored. If "ticks", the axis lines and ticks are mirrored. If False, mirroring is disable. If "all", axis lines are mirrored on all shared-axes subplots. If "allticks", axis lines and ticks are mirrored on all shared-axes subplots. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". range Sets the range of this axis. If the axis `type` is "log", then you must take the log of your desired range (e.g. to set the range from 1 to 100, set the range from 0 to 2). If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. rangemode If "normal", the range is computed in relation to the extrema of the input data. If *tozero*`, the range extends to 0, regardless of the input data If "nonnegative", the range is non- negative, regardless of the input data. Applies only to linear axes. separatethousands If "true", even 4-digit integers are separated showaxeslabels Sets whether or not this axis is labeled showbackground Sets whether or not this axis' wall has a background color. showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showgrid Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. showline Determines whether or not a line bounding this axis is drawn. showspikes Sets whether or not spikes starting from data points to this axis' wall are shown on hover. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. spikecolor Sets the color of the spikes. spikesides Sets whether or not spikes extending from the projection data points to this axis' wall boundaries are shown on hover. spikethickness Sets the thickness (in px) of the spikes. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the tick font. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.layout.scene.xa xis.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.lay out.scene.xaxis.tickformatstopdefaults), sets the default property values to use for elements of layout.scene.xaxis.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.layout.scene.xaxis.Title instance or dict with compatible properties titlefont Deprecated: Please use layout.scene.xaxis.title.font instead. Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. type Sets the axis type. By default, plotly attempts to determined the axis type by looking into the data of the traces that referenced the axis in question. visible A single toggle to hide the axis while preserving interaction like dragging. Default is true when a cheater plot is present on the axis, otherwise false zeroline Determines whether or not a line is drawn at along the 0 value of this axis. If True, the zero line is drawn on top of the grid lines. zerolinecolor Sets the line color of the zero line. zerolinewidth Sets the width (in px) of the zero line. Returns ------- plotly.graph_objs.layout.scene.XAxis """ return self["xaxis"] @xaxis.setter def xaxis(self, val): self["xaxis"] = val # yaxis # ----- @property def yaxis(self): """ The 'yaxis' property is an instance of YAxis that may be specified as: - An instance of plotly.graph_objs.layout.scene.YAxis - A dict of string/value properties that will be passed to the YAxis constructor Supported dict properties: autorange Determines whether or not the range of this axis is computed in relation to the input data. See `rangemode` for more info. If `range` is provided, then `autorange` is set to False. backgroundcolor Sets the background color of this axis' wall. calendar Sets the calendar system to use for `range` and `tick0` if this is a date axis. This does not set the calendar for interpreting data on this axis, that's specified in the trace or via the global `layout.calendar` categoryarray Sets the order in which categories on this axis appear. Only has an effect if `categoryorder` is set to "array". Used with `categoryorder`. categoryarraysrc Sets the source reference on plot.ly for categoryarray . categoryorder Specifies the ordering logic for the case of categorical variables. By default, plotly uses "trace", which specifies the order that is present in the data supplied. Set `categoryorder` to *category ascending* or *category descending* if order should be determined by the alphanumerical order of the category names. Set `categoryorder` to "array" to derive the ordering from the attribute `categoryarray`. If a category is not found in the `categoryarray` array, the sorting behavior for that attribute will be identical to the "trace" mode. The unspecified categories will follow the categories in `categoryarray`. Set `categoryorder` to *total ascending* or *total descending* if order should be determined by the numerical order of the values. Similarly, the order can be determined by the min, max, sum, mean or median of all the values. color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. gridcolor Sets the color of the grid lines. gridwidth Sets the width (in px) of the grid lines. hoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" linecolor Sets the axis line color. linewidth Sets the width (in px) of the axis line. mirror Determines if the axis lines or/and ticks are mirrored to the opposite side of the plotting area. If True, the axis lines are mirrored. If "ticks", the axis lines and ticks are mirrored. If False, mirroring is disable. If "all", axis lines are mirrored on all shared-axes subplots. If "allticks", axis lines and ticks are mirrored on all shared-axes subplots. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". range Sets the range of this axis. If the axis `type` is "log", then you must take the log of your desired range (e.g. to set the range from 1 to 100, set the range from 0 to 2). If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. rangemode If "normal", the range is computed in relation to the extrema of the input data. If *tozero*`, the range extends to 0, regardless of the input data If "nonnegative", the range is non- negative, regardless of the input data. Applies only to linear axes. separatethousands If "true", even 4-digit integers are separated showaxeslabels Sets whether or not this axis is labeled showbackground Sets whether or not this axis' wall has a background color. showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showgrid Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. showline Determines whether or not a line bounding this axis is drawn. showspikes Sets whether or not spikes starting from data points to this axis' wall are shown on hover. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. spikecolor Sets the color of the spikes. spikesides Sets whether or not spikes extending from the projection data points to this axis' wall boundaries are shown on hover. spikethickness Sets the thickness (in px) of the spikes. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the tick font. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.layout.scene.ya xis.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.lay out.scene.yaxis.tickformatstopdefaults), sets the default property values to use for elements of layout.scene.yaxis.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.layout.scene.yaxis.Title instance or dict with compatible properties titlefont Deprecated: Please use layout.scene.yaxis.title.font instead. Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. type Sets the axis type. By default, plotly attempts to determined the axis type by looking into the data of the traces that referenced the axis in question. visible A single toggle to hide the axis while preserving interaction like dragging. Default is true when a cheater plot is present on the axis, otherwise false zeroline Determines whether or not a line is drawn at along the 0 value of this axis. If True, the zero line is drawn on top of the grid lines. zerolinecolor Sets the line color of the zero line. zerolinewidth Sets the width (in px) of the zero line. Returns ------- plotly.graph_objs.layout.scene.YAxis """ return self["yaxis"] @yaxis.setter def yaxis(self, val): self["yaxis"] = val # zaxis # ----- @property def zaxis(self): """ The 'zaxis' property is an instance of ZAxis that may be specified as: - An instance of plotly.graph_objs.layout.scene.ZAxis - A dict of string/value properties that will be passed to the ZAxis constructor Supported dict properties: autorange Determines whether or not the range of this axis is computed in relation to the input data. See `rangemode` for more info. If `range` is provided, then `autorange` is set to False. backgroundcolor Sets the background color of this axis' wall. calendar Sets the calendar system to use for `range` and `tick0` if this is a date axis. This does not set the calendar for interpreting data on this axis, that's specified in the trace or via the global `layout.calendar` categoryarray Sets the order in which categories on this axis appear. Only has an effect if `categoryorder` is set to "array". Used with `categoryorder`. categoryarraysrc Sets the source reference on plot.ly for categoryarray . categoryorder Specifies the ordering logic for the case of categorical variables. By default, plotly uses "trace", which specifies the order that is present in the data supplied. Set `categoryorder` to *category ascending* or *category descending* if order should be determined by the alphanumerical order of the category names. Set `categoryorder` to "array" to derive the ordering from the attribute `categoryarray`. If a category is not found in the `categoryarray` array, the sorting behavior for that attribute will be identical to the "trace" mode. The unspecified categories will follow the categories in `categoryarray`. Set `categoryorder` to *total ascending* or *total descending* if order should be determined by the numerical order of the values. Similarly, the order can be determined by the min, max, sum, mean or median of all the values. color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. gridcolor Sets the color of the grid lines. gridwidth Sets the width (in px) of the grid lines. hoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" linecolor Sets the axis line color. linewidth Sets the width (in px) of the axis line. mirror Determines if the axis lines or/and ticks are mirrored to the opposite side of the plotting area. If True, the axis lines are mirrored. If "ticks", the axis lines and ticks are mirrored. If False, mirroring is disable. If "all", axis lines are mirrored on all shared-axes subplots. If "allticks", axis lines and ticks are mirrored on all shared-axes subplots. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". range Sets the range of this axis. If the axis `type` is "log", then you must take the log of your desired range (e.g. to set the range from 1 to 100, set the range from 0 to 2). If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. rangemode If "normal", the range is computed in relation to the extrema of the input data. If *tozero*`, the range extends to 0, regardless of the input data If "nonnegative", the range is non- negative, regardless of the input data. Applies only to linear axes. separatethousands If "true", even 4-digit integers are separated showaxeslabels Sets whether or not this axis is labeled showbackground Sets whether or not this axis' wall has a background color. showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showgrid Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. showline Determines whether or not a line bounding this axis is drawn. showspikes Sets whether or not spikes starting from data points to this axis' wall are shown on hover. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. spikecolor Sets the color of the spikes. spikesides Sets whether or not spikes extending from the projection data points to this axis' wall boundaries are shown on hover. spikethickness Sets the thickness (in px) of the spikes. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the tick font. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.layout.scene.za xis.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.lay out.scene.zaxis.tickformatstopdefaults), sets the default property values to use for elements of layout.scene.zaxis.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.layout.scene.zaxis.Title instance or dict with compatible properties titlefont Deprecated: Please use layout.scene.zaxis.title.font instead. Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. type Sets the axis type. By default, plotly attempts to determined the axis type by looking into the data of the traces that referenced the axis in question. visible A single toggle to hide the axis while preserving interaction like dragging. Default is true when a cheater plot is present on the axis, otherwise false zeroline Determines whether or not a line is drawn at along the 0 value of this axis. If True, the zero line is drawn on top of the grid lines. zerolinecolor Sets the line color of the zero line. zerolinewidth Sets the width (in px) of the zero line. Returns ------- plotly.graph_objs.layout.scene.ZAxis """ return self["zaxis"] @zaxis.setter def zaxis(self, val): self["zaxis"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ annotations A tuple of plotly.graph_objects.layout.scene.Annotation instances or dicts with compatible properties annotationdefaults When used in a template (as layout.template.layout.scene.annotationdefaults), sets the default property values to use for elements of layout.scene.annotations aspectmode If "cube", this scene's axes are drawn as a cube, regardless of the axes' ranges. If "data", this scene's axes are drawn in proportion with the axes' ranges. If "manual", this scene's axes are drawn in proportion with the input of "aspectratio" (the default behavior if "aspectratio" is provided). If "auto", this scene's axes are drawn using the results of "data" except when one axis is more than four times the size of the two others, where in that case the results of "cube" are used. aspectratio Sets this scene's axis aspectratio. bgcolor camera plotly.graph_objects.layout.scene.Camera instance or dict with compatible properties domain plotly.graph_objects.layout.scene.Domain instance or dict with compatible properties dragmode Determines the mode of drag interactions for this scene. hovermode Determines the mode of hover interactions for this scene. uirevision Controls persistence of user-driven changes in camera attributes. Defaults to `layout.uirevision`. xaxis plotly.graph_objects.layout.scene.XAxis instance or dict with compatible properties yaxis plotly.graph_objects.layout.scene.YAxis instance or dict with compatible properties zaxis plotly.graph_objects.layout.scene.ZAxis instance or dict with compatible properties """ def __init__( self, arg=None, annotations=None, annotationdefaults=None, aspectmode=None, aspectratio=None, bgcolor=None, camera=None, domain=None, dragmode=None, hovermode=None, uirevision=None, xaxis=None, yaxis=None, zaxis=None, **kwargs ): """ Construct a new Scene object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.Scene annotations A tuple of plotly.graph_objects.layout.scene.Annotation instances or dicts with compatible properties annotationdefaults When used in a template (as layout.template.layout.scene.annotationdefaults), sets the default property values to use for elements of layout.scene.annotations aspectmode If "cube", this scene's axes are drawn as a cube, regardless of the axes' ranges. If "data", this scene's axes are drawn in proportion with the axes' ranges. If "manual", this scene's axes are drawn in proportion with the input of "aspectratio" (the default behavior if "aspectratio" is provided). If "auto", this scene's axes are drawn using the results of "data" except when one axis is more than four times the size of the two others, where in that case the results of "cube" are used. aspectratio Sets this scene's axis aspectratio. bgcolor camera plotly.graph_objects.layout.scene.Camera instance or dict with compatible properties domain plotly.graph_objects.layout.scene.Domain instance or dict with compatible properties dragmode Determines the mode of drag interactions for this scene. hovermode Determines the mode of hover interactions for this scene. uirevision Controls persistence of user-driven changes in camera attributes. Defaults to `layout.uirevision`. xaxis plotly.graph_objects.layout.scene.XAxis instance or dict with compatible properties yaxis plotly.graph_objects.layout.scene.YAxis instance or dict with compatible properties zaxis plotly.graph_objects.layout.scene.ZAxis instance or dict with compatible properties Returns ------- Scene """ super(Scene, self).__init__("scene") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.Scene constructor must be a dict or an instance of plotly.graph_objs.layout.Scene""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout import scene as v_scene # Initialize validators # --------------------- self._validators["annotations"] = v_scene.AnnotationsValidator() self._validators["annotationdefaults"] = v_scene.AnnotationValidator() self._validators["aspectmode"] = v_scene.AspectmodeValidator() self._validators["aspectratio"] = v_scene.AspectratioValidator() self._validators["bgcolor"] = v_scene.BgcolorValidator() self._validators["camera"] = v_scene.CameraValidator() self._validators["domain"] = v_scene.DomainValidator() self._validators["dragmode"] = v_scene.DragmodeValidator() self._validators["hovermode"] = v_scene.HovermodeValidator() self._validators["uirevision"] = v_scene.UirevisionValidator() self._validators["xaxis"] = v_scene.XAxisValidator() self._validators["yaxis"] = v_scene.YAxisValidator() self._validators["zaxis"] = v_scene.ZAxisValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("annotations", None) self["annotations"] = annotations if annotations is not None else _v _v = arg.pop("annotationdefaults", None) self["annotationdefaults"] = ( annotationdefaults if annotationdefaults is not None else _v ) _v = arg.pop("aspectmode", None) self["aspectmode"] = aspectmode if aspectmode is not None else _v _v = arg.pop("aspectratio", None) self["aspectratio"] = aspectratio if aspectratio is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("camera", None) self["camera"] = camera if camera is not None else _v _v = arg.pop("domain", None) self["domain"] = domain if domain is not None else _v _v = arg.pop("dragmode", None) self["dragmode"] = dragmode if dragmode is not None else _v _v = arg.pop("hovermode", None) self["hovermode"] = hovermode if hovermode is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("xaxis", None) self["xaxis"] = xaxis if xaxis is not None else _v _v = arg.pop("yaxis", None) self["yaxis"] = yaxis if yaxis is not None else _v _v = arg.pop("zaxis", None) self["zaxis"] = zaxis if zaxis is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class RadialAxis(_BaseLayoutHierarchyType): # domain # ------ @property def domain(self): """ Polar chart subplots are not supported yet. This key has currently no effect. The 'domain' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'domain[0]' property is a number and may be specified as: - An int or float in the interval [0, 1] (1) The 'domain[1]' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- list """ return self["domain"] @domain.setter def domain(self, val): self["domain"] = val # endpadding # ---------- @property def endpadding(self): """ Legacy polar charts are deprecated! Please switch to "polar" subplots. The 'endpadding' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["endpadding"] @endpadding.setter def endpadding(self, val): self["endpadding"] = val # orientation # ----------- @property def orientation(self): """ Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the orientation (an angle with respect to the origin) of the radial axis. The 'orientation' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["orientation"] @orientation.setter def orientation(self, val): self["orientation"] = val # range # ----- @property def range(self): """ Legacy polar charts are deprecated! Please switch to "polar" subplots. Defines the start and end point of this radial axis. The 'range' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'range[0]' property is a number and may be specified as: - An int or float (1) The 'range[1]' property is a number and may be specified as: - An int or float Returns ------- list """ return self["range"] @range.setter def range(self, val): self["range"] = val # showline # -------- @property def showline(self): """ Legacy polar charts are deprecated! Please switch to "polar" subplots. Determines whether or not the line bounding this radial axis will be shown on the figure. The 'showline' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showline"] @showline.setter def showline(self, val): self["showline"] = val # showticklabels # -------------- @property def showticklabels(self): """ Legacy polar charts are deprecated! Please switch to "polar" subplots. Determines whether or not the radial axis ticks will feature tick labels. The 'showticklabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showticklabels"] @showticklabels.setter def showticklabels(self, val): self["showticklabels"] = val # tickcolor # --------- @property def tickcolor(self): """ Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the color of the tick lines on this radial axis. The 'tickcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["tickcolor"] @tickcolor.setter def tickcolor(self, val): self["tickcolor"] = val # ticklen # ------- @property def ticklen(self): """ Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the length of the tick lines on this radial axis. The 'ticklen' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ticklen"] @ticklen.setter def ticklen(self, val): self["ticklen"] = val # tickorientation # --------------- @property def tickorientation(self): """ Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the orientation (from the paper perspective) of the radial axis tick labels. The 'tickorientation' property is an enumeration that may be specified as: - One of the following enumeration values: ['horizontal', 'vertical'] Returns ------- Any """ return self["tickorientation"] @tickorientation.setter def tickorientation(self, val): self["tickorientation"] = val # ticksuffix # ---------- @property def ticksuffix(self): """ Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the length of the tick lines on this radial axis. The 'ticksuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ticksuffix"] @ticksuffix.setter def ticksuffix(self, val): self["ticksuffix"] = val # visible # ------- @property def visible(self): """ Legacy polar charts are deprecated! Please switch to "polar" subplots. Determines whether or not this axis will be visible. The 'visible' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ domain Polar chart subplots are not supported yet. This key has currently no effect. endpadding Legacy polar charts are deprecated! Please switch to "polar" subplots. orientation Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the orientation (an angle with respect to the origin) of the radial axis. range Legacy polar charts are deprecated! Please switch to "polar" subplots. Defines the start and end point of this radial axis. showline Legacy polar charts are deprecated! Please switch to "polar" subplots. Determines whether or not the line bounding this radial axis will be shown on the figure. showticklabels Legacy polar charts are deprecated! Please switch to "polar" subplots. Determines whether or not the radial axis ticks will feature tick labels. tickcolor Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the color of the tick lines on this radial axis. ticklen Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the length of the tick lines on this radial axis. tickorientation Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the orientation (from the paper perspective) of the radial axis tick labels. ticksuffix Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the length of the tick lines on this radial axis. visible Legacy polar charts are deprecated! Please switch to "polar" subplots. Determines whether or not this axis will be visible. """ def __init__( self, arg=None, domain=None, endpadding=None, orientation=None, range=None, showline=None, showticklabels=None, tickcolor=None, ticklen=None, tickorientation=None, ticksuffix=None, visible=None, **kwargs ): """ Construct a new RadialAxis object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.RadialAxis domain Polar chart subplots are not supported yet. This key has currently no effect. endpadding Legacy polar charts are deprecated! Please switch to "polar" subplots. orientation Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the orientation (an angle with respect to the origin) of the radial axis. range Legacy polar charts are deprecated! Please switch to "polar" subplots. Defines the start and end point of this radial axis. showline Legacy polar charts are deprecated! Please switch to "polar" subplots. Determines whether or not the line bounding this radial axis will be shown on the figure. showticklabels Legacy polar charts are deprecated! Please switch to "polar" subplots. Determines whether or not the radial axis ticks will feature tick labels. tickcolor Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the color of the tick lines on this radial axis. ticklen Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the length of the tick lines on this radial axis. tickorientation Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the orientation (from the paper perspective) of the radial axis tick labels. ticksuffix Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the length of the tick lines on this radial axis. visible Legacy polar charts are deprecated! Please switch to "polar" subplots. Determines whether or not this axis will be visible. Returns ------- RadialAxis """ super(RadialAxis, self).__init__("radialaxis") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.RadialAxis constructor must be a dict or an instance of plotly.graph_objs.layout.RadialAxis""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout import radialaxis as v_radialaxis # Initialize validators # --------------------- self._validators["domain"] = v_radialaxis.DomainValidator() self._validators["endpadding"] = v_radialaxis.EndpaddingValidator() self._validators["orientation"] = v_radialaxis.OrientationValidator() self._validators["range"] = v_radialaxis.RangeValidator() self._validators["showline"] = v_radialaxis.ShowlineValidator() self._validators["showticklabels"] = v_radialaxis.ShowticklabelsValidator() self._validators["tickcolor"] = v_radialaxis.TickcolorValidator() self._validators["ticklen"] = v_radialaxis.TicklenValidator() self._validators["tickorientation"] = v_radialaxis.TickorientationValidator() self._validators["ticksuffix"] = v_radialaxis.TicksuffixValidator() self._validators["visible"] = v_radialaxis.VisibleValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("domain", None) self["domain"] = domain if domain is not None else _v _v = arg.pop("endpadding", None) self["endpadding"] = endpadding if endpadding is not None else _v _v = arg.pop("orientation", None) self["orientation"] = orientation if orientation is not None else _v _v = arg.pop("range", None) self["range"] = range if range is not None else _v _v = arg.pop("showline", None) self["showline"] = showline if showline is not None else _v _v = arg.pop("showticklabels", None) self["showticklabels"] = showticklabels if showticklabels is not None else _v _v = arg.pop("tickcolor", None) self["tickcolor"] = tickcolor if tickcolor is not None else _v _v = arg.pop("ticklen", None) self["ticklen"] = ticklen if ticklen is not None else _v _v = arg.pop("tickorientation", None) self["tickorientation"] = tickorientation if tickorientation is not None else _v _v = arg.pop("ticksuffix", None) self["ticksuffix"] = ticksuffix if ticksuffix is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Polar(_BaseLayoutHierarchyType): # angularaxis # ----------- @property def angularaxis(self): """ The 'angularaxis' property is an instance of AngularAxis that may be specified as: - An instance of plotly.graph_objs.layout.polar.AngularAxis - A dict of string/value properties that will be passed to the AngularAxis constructor Supported dict properties: categoryarray Sets the order in which categories on this axis appear. Only has an effect if `categoryorder` is set to "array". Used with `categoryorder`. categoryarraysrc Sets the source reference on plot.ly for categoryarray . categoryorder Specifies the ordering logic for the case of categorical variables. By default, plotly uses "trace", which specifies the order that is present in the data supplied. Set `categoryorder` to *category ascending* or *category descending* if order should be determined by the alphanumerical order of the category names. Set `categoryorder` to "array" to derive the ordering from the attribute `categoryarray`. If a category is not found in the `categoryarray` array, the sorting behavior for that attribute will be identical to the "trace" mode. The unspecified categories will follow the categories in `categoryarray`. Set `categoryorder` to *total ascending* or *total descending* if order should be determined by the numerical order of the values. Similarly, the order can be determined by the min, max, sum, mean or median of all the values. color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. direction Sets the direction corresponding to positive angles. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. gridcolor Sets the color of the grid lines. gridwidth Sets the width (in px) of the grid lines. hoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" layer Sets the layer on which this axis is displayed. If *above traces*, this axis is displayed above all the subplot's traces If *below traces*, this axis is displayed below all the subplot's traces, but above the grid lines. Useful when used together with scatter-like traces with `cliponaxis` set to False to show markers and/or text nodes above this axis. linecolor Sets the axis line color. linewidth Sets the width (in px) of the axis line. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". period Set the angular period. Has an effect only when `angularaxis.type` is "category". rotation Sets that start position (in degrees) of the angular axis By default, polar subplots with `direction` set to "counterclockwise" get a `rotation` of 0 which corresponds to due East (like what mathematicians prefer). In turn, polar with `direction` set to "clockwise" get a rotation of 90 which corresponds to due North (like on a compass), separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showgrid Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. showline Determines whether or not a line bounding this axis is drawn. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thetaunit Sets the format unit of the formatted "theta" values. Has an effect only when `angularaxis.type` is "linear". tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the tick font. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.layout.polar.an gularaxis.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.lay out.polar.angularaxis.tickformatstopdefaults), sets the default property values to use for elements of layout.polar.angularaxis.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). type Sets the angular axis type. If "linear", set `thetaunit` to determine the unit in which axis value are shown. If *category, use `period` to set the number of integer coordinates around polar axis. uirevision Controls persistence of user-driven changes in axis `rotation`. Defaults to `polar.uirevision`. visible A single toggle to hide the axis while preserving interaction like dragging. Default is true when a cheater plot is present on the axis, otherwise false Returns ------- plotly.graph_objs.layout.polar.AngularAxis """ return self["angularaxis"] @angularaxis.setter def angularaxis(self, val): self["angularaxis"] = val # bargap # ------ @property def bargap(self): """ Sets the gap between bars of adjacent location coordinates. Values are unitless, they represent fractions of the minimum difference in bar positions in the data. The 'bargap' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["bargap"] @bargap.setter def bargap(self, val): self["bargap"] = val # barmode # ------- @property def barmode(self): """ Determines how bars at the same location coordinate are displayed on the graph. With "stack", the bars are stacked on top of one another With "overlay", the bars are plotted over one another, you might need to an "opacity" to see multiple bars. The 'barmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['stack', 'overlay'] Returns ------- Any """ return self["barmode"] @barmode.setter def barmode(self, val): self["barmode"] = val # bgcolor # ------- @property def bgcolor(self): """ Set the background color of the subplot The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # domain # ------ @property def domain(self): """ The 'domain' property is an instance of Domain that may be specified as: - An instance of plotly.graph_objs.layout.polar.Domain - A dict of string/value properties that will be passed to the Domain constructor Supported dict properties: column If there is a layout grid, use the domain for this column in the grid for this polar subplot . row If there is a layout grid, use the domain for this row in the grid for this polar subplot . x Sets the horizontal domain of this polar subplot (in plot fraction). y Sets the vertical domain of this polar subplot (in plot fraction). Returns ------- plotly.graph_objs.layout.polar.Domain """ return self["domain"] @domain.setter def domain(self, val): self["domain"] = val # gridshape # --------- @property def gridshape(self): """ Determines if the radial axis grid lines and angular axis line are drawn as "circular" sectors or as "linear" (polygon) sectors. Has an effect only when the angular axis has `type` "category". Note that `radialaxis.angle` is snapped to the angle of the closest vertex when `gridshape` is "circular" (so that radial axis scale is the same as the data scale). The 'gridshape' property is an enumeration that may be specified as: - One of the following enumeration values: ['circular', 'linear'] Returns ------- Any """ return self["gridshape"] @gridshape.setter def gridshape(self, val): self["gridshape"] = val # hole # ---- @property def hole(self): """ Sets the fraction of the radius to cut out of the polar subplot. The 'hole' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["hole"] @hole.setter def hole(self, val): self["hole"] = val # radialaxis # ---------- @property def radialaxis(self): """ The 'radialaxis' property is an instance of RadialAxis that may be specified as: - An instance of plotly.graph_objs.layout.polar.RadialAxis - A dict of string/value properties that will be passed to the RadialAxis constructor Supported dict properties: angle Sets the angle (in degrees) from which the radial axis is drawn. Note that by default, radial axis line on the theta=0 line corresponds to a line pointing right (like what mathematicians prefer). Defaults to the first `polar.sector` angle. autorange Determines whether or not the range of this axis is computed in relation to the input data. See `rangemode` for more info. If `range` is provided, then `autorange` is set to False. calendar Sets the calendar system to use for `range` and `tick0` if this is a date axis. This does not set the calendar for interpreting data on this axis, that's specified in the trace or via the global `layout.calendar` categoryarray Sets the order in which categories on this axis appear. Only has an effect if `categoryorder` is set to "array". Used with `categoryorder`. categoryarraysrc Sets the source reference on plot.ly for categoryarray . categoryorder Specifies the ordering logic for the case of categorical variables. By default, plotly uses "trace", which specifies the order that is present in the data supplied. Set `categoryorder` to *category ascending* or *category descending* if order should be determined by the alphanumerical order of the category names. Set `categoryorder` to "array" to derive the ordering from the attribute `categoryarray`. If a category is not found in the `categoryarray` array, the sorting behavior for that attribute will be identical to the "trace" mode. The unspecified categories will follow the categories in `categoryarray`. Set `categoryorder` to *total ascending* or *total descending* if order should be determined by the numerical order of the values. Similarly, the order can be determined by the min, max, sum, mean or median of all the values. color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. gridcolor Sets the color of the grid lines. gridwidth Sets the width (in px) of the grid lines. hoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" layer Sets the layer on which this axis is displayed. If *above traces*, this axis is displayed above all the subplot's traces If *below traces*, this axis is displayed below all the subplot's traces, but above the grid lines. Useful when used together with scatter-like traces with `cliponaxis` set to False to show markers and/or text nodes above this axis. linecolor Sets the axis line color. linewidth Sets the width (in px) of the axis line. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". range Sets the range of this axis. If the axis `type` is "log", then you must take the log of your desired range (e.g. to set the range from 1 to 100, set the range from 0 to 2). If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. rangemode If *tozero*`, the range extends to 0, regardless of the input data If "nonnegative", the range is non-negative, regardless of the input data. If "normal", the range is computed in relation to the extrema of the input data (same behavior as for cartesian axes). separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showgrid Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. showline Determines whether or not a line bounding this axis is drawn. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. side Determines on which side of radial axis line the tick and tick labels appear. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the tick font. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.layout.polar.ra dialaxis.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.lay out.polar.radialaxis.tickformatstopdefaults), sets the default property values to use for elements of layout.polar.radialaxis.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.layout.polar.radialaxis.Ti tle instance or dict with compatible properties titlefont Deprecated: Please use layout.polar.radialaxis.title.font instead. Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. type Sets the axis type. By default, plotly attempts to determined the axis type by looking into the data of the traces that referenced the axis in question. uirevision Controls persistence of user-driven changes in axis `range`, `autorange`, `angle`, and `title` if in `editable: true` configuration. Defaults to `polar.uirevision`. visible A single toggle to hide the axis while preserving interaction like dragging. Default is true when a cheater plot is present on the axis, otherwise false Returns ------- plotly.graph_objs.layout.polar.RadialAxis """ return self["radialaxis"] @radialaxis.setter def radialaxis(self, val): self["radialaxis"] = val # sector # ------ @property def sector(self): """ Sets angular span of this polar subplot with two angles (in degrees). Sector are assumed to be spanned in the counterclockwise direction with 0 corresponding to rightmost limit of the polar subplot. The 'sector' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'sector[0]' property is a number and may be specified as: - An int or float (1) The 'sector[1]' property is a number and may be specified as: - An int or float Returns ------- list """ return self["sector"] @sector.setter def sector(self, val): self["sector"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of user-driven changes in axis attributes, if not overridden in the individual axes. Defaults to `layout.uirevision`. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ angularaxis plotly.graph_objects.layout.polar.AngularAxis instance or dict with compatible properties bargap Sets the gap between bars of adjacent location coordinates. Values are unitless, they represent fractions of the minimum difference in bar positions in the data. barmode Determines how bars at the same location coordinate are displayed on the graph. With "stack", the bars are stacked on top of one another With "overlay", the bars are plotted over one another, you might need to an "opacity" to see multiple bars. bgcolor Set the background color of the subplot domain plotly.graph_objects.layout.polar.Domain instance or dict with compatible properties gridshape Determines if the radial axis grid lines and angular axis line are drawn as "circular" sectors or as "linear" (polygon) sectors. Has an effect only when the angular axis has `type` "category". Note that `radialaxis.angle` is snapped to the angle of the closest vertex when `gridshape` is "circular" (so that radial axis scale is the same as the data scale). hole Sets the fraction of the radius to cut out of the polar subplot. radialaxis plotly.graph_objects.layout.polar.RadialAxis instance or dict with compatible properties sector Sets angular span of this polar subplot with two angles (in degrees). Sector are assumed to be spanned in the counterclockwise direction with 0 corresponding to rightmost limit of the polar subplot. uirevision Controls persistence of user-driven changes in axis attributes, if not overridden in the individual axes. Defaults to `layout.uirevision`. """ def __init__( self, arg=None, angularaxis=None, bargap=None, barmode=None, bgcolor=None, domain=None, gridshape=None, hole=None, radialaxis=None, sector=None, uirevision=None, **kwargs ): """ Construct a new Polar object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.Polar angularaxis plotly.graph_objects.layout.polar.AngularAxis instance or dict with compatible properties bargap Sets the gap between bars of adjacent location coordinates. Values are unitless, they represent fractions of the minimum difference in bar positions in the data. barmode Determines how bars at the same location coordinate are displayed on the graph. With "stack", the bars are stacked on top of one another With "overlay", the bars are plotted over one another, you might need to an "opacity" to see multiple bars. bgcolor Set the background color of the subplot domain plotly.graph_objects.layout.polar.Domain instance or dict with compatible properties gridshape Determines if the radial axis grid lines and angular axis line are drawn as "circular" sectors or as "linear" (polygon) sectors. Has an effect only when the angular axis has `type` "category". Note that `radialaxis.angle` is snapped to the angle of the closest vertex when `gridshape` is "circular" (so that radial axis scale is the same as the data scale). hole Sets the fraction of the radius to cut out of the polar subplot. radialaxis plotly.graph_objects.layout.polar.RadialAxis instance or dict with compatible properties sector Sets angular span of this polar subplot with two angles (in degrees). Sector are assumed to be spanned in the counterclockwise direction with 0 corresponding to rightmost limit of the polar subplot. uirevision Controls persistence of user-driven changes in axis attributes, if not overridden in the individual axes. Defaults to `layout.uirevision`. Returns ------- Polar """ super(Polar, self).__init__("polar") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.Polar constructor must be a dict or an instance of plotly.graph_objs.layout.Polar""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout import polar as v_polar # Initialize validators # --------------------- self._validators["angularaxis"] = v_polar.AngularAxisValidator() self._validators["bargap"] = v_polar.BargapValidator() self._validators["barmode"] = v_polar.BarmodeValidator() self._validators["bgcolor"] = v_polar.BgcolorValidator() self._validators["domain"] = v_polar.DomainValidator() self._validators["gridshape"] = v_polar.GridshapeValidator() self._validators["hole"] = v_polar.HoleValidator() self._validators["radialaxis"] = v_polar.RadialAxisValidator() self._validators["sector"] = v_polar.SectorValidator() self._validators["uirevision"] = v_polar.UirevisionValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("angularaxis", None) self["angularaxis"] = angularaxis if angularaxis is not None else _v _v = arg.pop("bargap", None) self["bargap"] = bargap if bargap is not None else _v _v = arg.pop("barmode", None) self["barmode"] = barmode if barmode is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("domain", None) self["domain"] = domain if domain is not None else _v _v = arg.pop("gridshape", None) self["gridshape"] = gridshape if gridshape is not None else _v _v = arg.pop("hole", None) self["hole"] = hole if hole is not None else _v _v = arg.pop("radialaxis", None) self["radialaxis"] = radialaxis if radialaxis is not None else _v _v = arg.pop("sector", None) self["sector"] = sector if sector is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Modebar(_BaseLayoutHierarchyType): # activecolor # ----------- @property def activecolor(self): """ Sets the color of the active or hovered on icons in the modebar. The 'activecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["activecolor"] @activecolor.setter def activecolor(self, val): self["activecolor"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the modebar. The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # color # ----- @property def color(self): """ Sets the color of the icons in the modebar. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # orientation # ----------- @property def orientation(self): """ Sets the orientation of the modebar. The 'orientation' property is an enumeration that may be specified as: - One of the following enumeration values: ['v', 'h'] Returns ------- Any """ return self["orientation"] @orientation.setter def orientation(self, val): self["orientation"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of user-driven changes related to the modebar, including `hovermode`, `dragmode`, and `showspikes` at both the root level and inside subplots. Defaults to `layout.uirevision`. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ activecolor Sets the color of the active or hovered on icons in the modebar. bgcolor Sets the background color of the modebar. color Sets the color of the icons in the modebar. orientation Sets the orientation of the modebar. uirevision Controls persistence of user-driven changes related to the modebar, including `hovermode`, `dragmode`, and `showspikes` at both the root level and inside subplots. Defaults to `layout.uirevision`. """ def __init__( self, arg=None, activecolor=None, bgcolor=None, color=None, orientation=None, uirevision=None, **kwargs ): """ Construct a new Modebar object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.Modebar activecolor Sets the color of the active or hovered on icons in the modebar. bgcolor Sets the background color of the modebar. color Sets the color of the icons in the modebar. orientation Sets the orientation of the modebar. uirevision Controls persistence of user-driven changes related to the modebar, including `hovermode`, `dragmode`, and `showspikes` at both the root level and inside subplots. Defaults to `layout.uirevision`. Returns ------- Modebar """ super(Modebar, self).__init__("modebar") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.Modebar constructor must be a dict or an instance of plotly.graph_objs.layout.Modebar""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout import modebar as v_modebar # Initialize validators # --------------------- self._validators["activecolor"] = v_modebar.ActivecolorValidator() self._validators["bgcolor"] = v_modebar.BgcolorValidator() self._validators["color"] = v_modebar.ColorValidator() self._validators["orientation"] = v_modebar.OrientationValidator() self._validators["uirevision"] = v_modebar.UirevisionValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("activecolor", None) self["activecolor"] = activecolor if activecolor is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("orientation", None) self["orientation"] = orientation if orientation is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Margin(_BaseLayoutHierarchyType): # autoexpand # ---------- @property def autoexpand(self): """ Turns on/off margin expansion computations. Legends, colorbars, updatemenus, sliders, axis rangeselector and rangeslider are allowed to push the margins by defaults. The 'autoexpand' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autoexpand"] @autoexpand.setter def autoexpand(self, val): self["autoexpand"] = val # b # - @property def b(self): """ Sets the bottom margin (in px). The 'b' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["b"] @b.setter def b(self, val): self["b"] = val # l # - @property def l(self): """ Sets the left margin (in px). The 'l' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["l"] @l.setter def l(self, val): self["l"] = val # pad # --- @property def pad(self): """ Sets the amount of padding (in px) between the plotting area and the axis lines The 'pad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["pad"] @pad.setter def pad(self, val): self["pad"] = val # r # - @property def r(self): """ Sets the right margin (in px). The 'r' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["r"] @r.setter def r(self, val): self["r"] = val # t # - @property def t(self): """ Sets the top margin (in px). The 't' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["t"] @t.setter def t(self, val): self["t"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autoexpand Turns on/off margin expansion computations. Legends, colorbars, updatemenus, sliders, axis rangeselector and rangeslider are allowed to push the margins by defaults. b Sets the bottom margin (in px). l Sets the left margin (in px). pad Sets the amount of padding (in px) between the plotting area and the axis lines r Sets the right margin (in px). t Sets the top margin (in px). """ def __init__( self, arg=None, autoexpand=None, b=None, l=None, pad=None, r=None, t=None, **kwargs ): """ Construct a new Margin object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.Margin autoexpand Turns on/off margin expansion computations. Legends, colorbars, updatemenus, sliders, axis rangeselector and rangeslider are allowed to push the margins by defaults. b Sets the bottom margin (in px). l Sets the left margin (in px). pad Sets the amount of padding (in px) between the plotting area and the axis lines r Sets the right margin (in px). t Sets the top margin (in px). Returns ------- Margin """ super(Margin, self).__init__("margin") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.Margin constructor must be a dict or an instance of plotly.graph_objs.layout.Margin""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout import margin as v_margin # Initialize validators # --------------------- self._validators["autoexpand"] = v_margin.AutoexpandValidator() self._validators["b"] = v_margin.BValidator() self._validators["l"] = v_margin.LValidator() self._validators["pad"] = v_margin.PadValidator() self._validators["r"] = v_margin.RValidator() self._validators["t"] = v_margin.TValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autoexpand", None) self["autoexpand"] = autoexpand if autoexpand is not None else _v _v = arg.pop("b", None) self["b"] = b if b is not None else _v _v = arg.pop("l", None) self["l"] = l if l is not None else _v _v = arg.pop("pad", None) self["pad"] = pad if pad is not None else _v _v = arg.pop("r", None) self["r"] = r if r is not None else _v _v = arg.pop("t", None) self["t"] = t if t is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Mapbox(_BaseLayoutHierarchyType): # accesstoken # ----------- @property def accesstoken(self): """ Sets the mapbox access token to be used for this mapbox map. Alternatively, the mapbox access token can be set in the configuration options under `mapboxAccessToken`. Note that accessToken are only required when `style` (e.g with values : basic, streets, outdoors, light, dark, satellite, satellite- streets ) and/or a layout layer references the Mapbox server. The 'accesstoken' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["accesstoken"] @accesstoken.setter def accesstoken(self, val): self["accesstoken"] = val # bearing # ------- @property def bearing(self): """ Sets the bearing angle of the map in degrees counter-clockwise from North (mapbox.bearing). The 'bearing' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["bearing"] @bearing.setter def bearing(self, val): self["bearing"] = val # center # ------ @property def center(self): """ The 'center' property is an instance of Center that may be specified as: - An instance of plotly.graph_objs.layout.mapbox.Center - A dict of string/value properties that will be passed to the Center constructor Supported dict properties: lat Sets the latitude of the center of the map (in degrees North). lon Sets the longitude of the center of the map (in degrees East). Returns ------- plotly.graph_objs.layout.mapbox.Center """ return self["center"] @center.setter def center(self, val): self["center"] = val # domain # ------ @property def domain(self): """ The 'domain' property is an instance of Domain that may be specified as: - An instance of plotly.graph_objs.layout.mapbox.Domain - A dict of string/value properties that will be passed to the Domain constructor Supported dict properties: column If there is a layout grid, use the domain for this column in the grid for this mapbox subplot . row If there is a layout grid, use the domain for this row in the grid for this mapbox subplot . x Sets the horizontal domain of this mapbox subplot (in plot fraction). y Sets the vertical domain of this mapbox subplot (in plot fraction). Returns ------- plotly.graph_objs.layout.mapbox.Domain """ return self["domain"] @domain.setter def domain(self, val): self["domain"] = val # layers # ------ @property def layers(self): """ The 'layers' property is a tuple of instances of Layer that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.mapbox.Layer - A list or tuple of dicts of string/value properties that will be passed to the Layer constructor Supported dict properties: below Determines if the layer will be inserted before the layer with the specified ID. If omitted or set to '', the layer will be inserted above every existing layer. circle plotly.graph_objects.layout.mapbox.layer.Circle instance or dict with compatible properties color Sets the primary layer color. If `type` is "circle", color corresponds to the circle color (mapbox.layer.paint.circle-color) If `type` is "line", color corresponds to the line color (mapbox.layer.paint.line-color) If `type` is "fill", color corresponds to the fill color (mapbox.layer.paint.fill-color) If `type` is "symbol", color corresponds to the icon color (mapbox.layer.paint.icon-color) coordinates Sets the coordinates array contains [longitude, latitude] pairs for the image corners listed in clockwise order: top left, top right, bottom right, bottom left. Only has an effect for "image" `sourcetype`. fill plotly.graph_objects.layout.mapbox.layer.Fill instance or dict with compatible properties line plotly.graph_objects.layout.mapbox.layer.Line instance or dict with compatible properties maxzoom Sets the maximum zoom level (mapbox.layer.maxzoom). At zoom levels equal to or greater than the maxzoom, the layer will be hidden. minzoom Sets the minimum zoom level (mapbox.layer.minzoom). At zoom levels less than the minzoom, the layer will be hidden. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. opacity Sets the opacity of the layer. If `type` is "circle", opacity corresponds to the circle opacity (mapbox.layer.paint.circle-opacity) If `type` is "line", opacity corresponds to the line opacity (mapbox.layer.paint.line-opacity) If `type` is "fill", opacity corresponds to the fill opacity (mapbox.layer.paint.fill-opacity) If `type` is "symbol", opacity corresponds to the icon/text opacity (mapbox.layer.paint.text- opacity) source Sets the source data for this layer (mapbox.layer.source). When `sourcetype` is set to "geojson", `source` can be a URL to a GeoJSON or a GeoJSON object. When `sourcetype` is set to "vector" or "raster", `source` can be a URL or an array of tile URLs. When `sourcetype` is set to "image", `source` can be a URL to an image. sourceattribution Sets the attribution for this source. sourcelayer Specifies the layer to use from a vector tile source (mapbox.layer.source-layer). Required for "vector" source type that supports multiple layers. sourcetype Sets the source type for this layer, that is the type of the layer data. symbol plotly.graph_objects.layout.mapbox.layer.Symbol instance or dict with compatible properties templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. type Sets the layer type, that is the how the layer data set in `source` will be rendered With `sourcetype` set to "geojson", the following values are allowed: "circle", "line", "fill" and "symbol". but note that "line" and "fill" are not compatible with Point GeoJSON geometries. With `sourcetype` set to "vector", the following values are allowed: "circle", "line", "fill" and "symbol". With `sourcetype` set to "raster" or `*image*`, only the "raster" value is allowed. visible Determines whether this layer is displayed Returns ------- tuple[plotly.graph_objs.layout.mapbox.Layer] """ return self["layers"] @layers.setter def layers(self, val): self["layers"] = val # layerdefaults # ------------- @property def layerdefaults(self): """ When used in a template (as layout.template.layout.mapbox.layerdefaults), sets the default property values to use for elements of layout.mapbox.layers The 'layerdefaults' property is an instance of Layer that may be specified as: - An instance of plotly.graph_objs.layout.mapbox.Layer - A dict of string/value properties that will be passed to the Layer constructor Supported dict properties: Returns ------- plotly.graph_objs.layout.mapbox.Layer """ return self["layerdefaults"] @layerdefaults.setter def layerdefaults(self, val): self["layerdefaults"] = val # pitch # ----- @property def pitch(self): """ Sets the pitch angle of the map (in degrees, where 0 means perpendicular to the surface of the map) (mapbox.pitch). The 'pitch' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["pitch"] @pitch.setter def pitch(self, val): self["pitch"] = val # style # ----- @property def style(self): """ Defines the map layers that are rendered by default below the trace layers defined in `data`, which are themselves by default rendered below the layers defined in `layout.mapbox.layers`. These layers can be defined either explicitly as a Mapbox Style object which can contain multiple layer definitions that load data from any public or private Tile Map Service (TMS or XYZ) or Web Map Service (WMS) or implicitly by using one of the built-in style objects which use WMSes which do not require any access tokens, or by using a default Mapbox style or custom Mapbox style URL, both of which require a Mapbox access token Note that Mapbox access token can be set in the `accesstoken` attribute or in the `mapboxAccessToken` config option. Mapbox Style objects are of the form described in the Mapbox GL JS documentation available at https://docs.mapbox.com/mapbox-gl- js/style-spec The built-in plotly.js styles objects are: open- street-map, white-bg, carto-positron, carto-darkmatter, stamen- terrain, stamen-toner, stamen-watercolor The built-in Mapbox styles are: basic, streets, outdoors, light, dark, satellite, satellite-streets Mapbox style URLs are of the form: mapbox://mapbox.mapbox-- The 'style' property accepts values of any type Returns ------- Any """ return self["style"] @style.setter def style(self, val): self["style"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of user-driven changes in the view: `center`, `zoom`, `bearing`, `pitch`. Defaults to `layout.uirevision`. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # zoom # ---- @property def zoom(self): """ Sets the zoom level of the map (mapbox.zoom). The 'zoom' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["zoom"] @zoom.setter def zoom(self, val): self["zoom"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ accesstoken Sets the mapbox access token to be used for this mapbox map. Alternatively, the mapbox access token can be set in the configuration options under `mapboxAccessToken`. Note that accessToken are only required when `style` (e.g with values : basic, streets, outdoors, light, dark, satellite, satellite-streets ) and/or a layout layer references the Mapbox server. bearing Sets the bearing angle of the map in degrees counter- clockwise from North (mapbox.bearing). center plotly.graph_objects.layout.mapbox.Center instance or dict with compatible properties domain plotly.graph_objects.layout.mapbox.Domain instance or dict with compatible properties layers A tuple of plotly.graph_objects.layout.mapbox.Layer instances or dicts with compatible properties layerdefaults When used in a template (as layout.template.layout.mapbox.layerdefaults), sets the default property values to use for elements of layout.mapbox.layers pitch Sets the pitch angle of the map (in degrees, where 0 means perpendicular to the surface of the map) (mapbox.pitch). style Defines the map layers that are rendered by default below the trace layers defined in `data`, which are themselves by default rendered below the layers defined in `layout.mapbox.layers`. These layers can be defined either explicitly as a Mapbox Style object which can contain multiple layer definitions that load data from any public or private Tile Map Service (TMS or XYZ) or Web Map Service (WMS) or implicitly by using one of the built-in style objects which use WMSes which do not require any access tokens, or by using a default Mapbox style or custom Mapbox style URL, both of which require a Mapbox access token Note that Mapbox access token can be set in the `accesstoken` attribute or in the `mapboxAccessToken` config option. Mapbox Style objects are of the form described in the Mapbox GL JS documentation available at https://docs.mapbox.com/mapbox-gl-js/style-spec The built-in plotly.js styles objects are: open-street-map, white-bg, carto-positron, carto-darkmatter, stamen- terrain, stamen-toner, stamen-watercolor The built-in Mapbox styles are: basic, streets, outdoors, light, dark, satellite, satellite-streets Mapbox style URLs are of the form: mapbox://mapbox.mapbox-- uirevision Controls persistence of user-driven changes in the view: `center`, `zoom`, `bearing`, `pitch`. Defaults to `layout.uirevision`. zoom Sets the zoom level of the map (mapbox.zoom). """ def __init__( self, arg=None, accesstoken=None, bearing=None, center=None, domain=None, layers=None, layerdefaults=None, pitch=None, style=None, uirevision=None, zoom=None, **kwargs ): """ Construct a new Mapbox object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.Mapbox accesstoken Sets the mapbox access token to be used for this mapbox map. Alternatively, the mapbox access token can be set in the configuration options under `mapboxAccessToken`. Note that accessToken are only required when `style` (e.g with values : basic, streets, outdoors, light, dark, satellite, satellite-streets ) and/or a layout layer references the Mapbox server. bearing Sets the bearing angle of the map in degrees counter- clockwise from North (mapbox.bearing). center plotly.graph_objects.layout.mapbox.Center instance or dict with compatible properties domain plotly.graph_objects.layout.mapbox.Domain instance or dict with compatible properties layers A tuple of plotly.graph_objects.layout.mapbox.Layer instances or dicts with compatible properties layerdefaults When used in a template (as layout.template.layout.mapbox.layerdefaults), sets the default property values to use for elements of layout.mapbox.layers pitch Sets the pitch angle of the map (in degrees, where 0 means perpendicular to the surface of the map) (mapbox.pitch). style Defines the map layers that are rendered by default below the trace layers defined in `data`, which are themselves by default rendered below the layers defined in `layout.mapbox.layers`. These layers can be defined either explicitly as a Mapbox Style object which can contain multiple layer definitions that load data from any public or private Tile Map Service (TMS or XYZ) or Web Map Service (WMS) or implicitly by using one of the built-in style objects which use WMSes which do not require any access tokens, or by using a default Mapbox style or custom Mapbox style URL, both of which require a Mapbox access token Note that Mapbox access token can be set in the `accesstoken` attribute or in the `mapboxAccessToken` config option. Mapbox Style objects are of the form described in the Mapbox GL JS documentation available at https://docs.mapbox.com/mapbox-gl-js/style-spec The built-in plotly.js styles objects are: open-street-map, white-bg, carto-positron, carto-darkmatter, stamen- terrain, stamen-toner, stamen-watercolor The built-in Mapbox styles are: basic, streets, outdoors, light, dark, satellite, satellite-streets Mapbox style URLs are of the form: mapbox://mapbox.mapbox-- uirevision Controls persistence of user-driven changes in the view: `center`, `zoom`, `bearing`, `pitch`. Defaults to `layout.uirevision`. zoom Sets the zoom level of the map (mapbox.zoom). Returns ------- Mapbox """ super(Mapbox, self).__init__("mapbox") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.Mapbox constructor must be a dict or an instance of plotly.graph_objs.layout.Mapbox""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout import mapbox as v_mapbox # Initialize validators # --------------------- self._validators["accesstoken"] = v_mapbox.AccesstokenValidator() self._validators["bearing"] = v_mapbox.BearingValidator() self._validators["center"] = v_mapbox.CenterValidator() self._validators["domain"] = v_mapbox.DomainValidator() self._validators["layers"] = v_mapbox.LayersValidator() self._validators["layerdefaults"] = v_mapbox.LayerValidator() self._validators["pitch"] = v_mapbox.PitchValidator() self._validators["style"] = v_mapbox.StyleValidator() self._validators["uirevision"] = v_mapbox.UirevisionValidator() self._validators["zoom"] = v_mapbox.ZoomValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("accesstoken", None) self["accesstoken"] = accesstoken if accesstoken is not None else _v _v = arg.pop("bearing", None) self["bearing"] = bearing if bearing is not None else _v _v = arg.pop("center", None) self["center"] = center if center is not None else _v _v = arg.pop("domain", None) self["domain"] = domain if domain is not None else _v _v = arg.pop("layers", None) self["layers"] = layers if layers is not None else _v _v = arg.pop("layerdefaults", None) self["layerdefaults"] = layerdefaults if layerdefaults is not None else _v _v = arg.pop("pitch", None) self["pitch"] = pitch if pitch is not None else _v _v = arg.pop("style", None) self["style"] = style if style is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("zoom", None) self["zoom"] = zoom if zoom is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Legend(_BaseLayoutHierarchyType): # bgcolor # ------- @property def bgcolor(self): """ Sets the legend background color. Defaults to `layout.paper_bgcolor`. The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the color of the border enclosing the legend. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # borderwidth # ----------- @property def borderwidth(self): """ Sets the width (in px) of the border enclosing the legend. The 'borderwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["borderwidth"] @borderwidth.setter def borderwidth(self, val): self["borderwidth"] = val # font # ---- @property def font(self): """ Sets the font used to text the legend items. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.layout.legend.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.layout.legend.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # itemclick # --------- @property def itemclick(self): """ Determines the behavior on legend item click. "toggle" toggles the visibility of the item clicked on the graph. "toggleothers" makes the clicked item the sole visible item on the graph. False disable legend item click interactions. The 'itemclick' property is an enumeration that may be specified as: - One of the following enumeration values: ['toggle', 'toggleothers', False] Returns ------- Any """ return self["itemclick"] @itemclick.setter def itemclick(self, val): self["itemclick"] = val # itemdoubleclick # --------------- @property def itemdoubleclick(self): """ Determines the behavior on legend item double-click. "toggle" toggles the visibility of the item clicked on the graph. "toggleothers" makes the clicked item the sole visible item on the graph. False disable legend item double-click interactions. The 'itemdoubleclick' property is an enumeration that may be specified as: - One of the following enumeration values: ['toggle', 'toggleothers', False] Returns ------- Any """ return self["itemdoubleclick"] @itemdoubleclick.setter def itemdoubleclick(self, val): self["itemdoubleclick"] = val # itemsizing # ---------- @property def itemsizing(self): """ Determines if the legend items symbols scale with their corresponding "trace" attributes or remain "constant" independent of the symbol size on the graph. The 'itemsizing' property is an enumeration that may be specified as: - One of the following enumeration values: ['trace', 'constant'] Returns ------- Any """ return self["itemsizing"] @itemsizing.setter def itemsizing(self, val): self["itemsizing"] = val # orientation # ----------- @property def orientation(self): """ Sets the orientation of the legend. The 'orientation' property is an enumeration that may be specified as: - One of the following enumeration values: ['v', 'h'] Returns ------- Any """ return self["orientation"] @orientation.setter def orientation(self, val): self["orientation"] = val # tracegroupgap # ------------- @property def tracegroupgap(self): """ Sets the amount of vertical space (in px) between legend groups. The 'tracegroupgap' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["tracegroupgap"] @tracegroupgap.setter def tracegroupgap(self, val): self["tracegroupgap"] = val # traceorder # ---------- @property def traceorder(self): """ Determines the order at which the legend items are displayed. If "normal", the items are displayed top-to-bottom in the same order as the input data. If "reversed", the items are displayed in the opposite order as "normal". If "grouped", the items are displayed in groups (when a trace `legendgroup` is provided). if "grouped+reversed", the items are displayed in the opposite order as "grouped". The 'traceorder' property is a flaglist and may be specified as a string containing: - Any combination of ['reversed', 'grouped'] joined with '+' characters (e.g. 'reversed+grouped') OR exactly one of ['normal'] (e.g. 'normal') Returns ------- Any """ return self["traceorder"] @traceorder.setter def traceorder(self, val): self["traceorder"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of legend-driven changes in trace and pie label visibility. Defaults to `layout.uirevision`. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # valign # ------ @property def valign(self): """ Sets the vertical alignment of the symbols with respect to their associated text. The 'valign' property is an enumeration that may be specified as: - One of the following enumeration values: ['top', 'middle', 'bottom'] Returns ------- Any """ return self["valign"] @valign.setter def valign(self, val): self["valign"] = val # x # - @property def x(self): """ Sets the x position (in normalized coordinates) of the legend. Defaults to 1.02 for vertical legends and defaults to 0 for horizontal legends. The 'x' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["x"] @x.setter def x(self, val): self["x"] = val # xanchor # ------- @property def xanchor(self): """ Sets the legend's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the legend. Value "auto" anchors legends to the right for `x` values greater than or equal to 2/3, anchors legends to the left for `x` values less than or equal to 1/3 and anchors legends with respect to their center otherwise. The 'xanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'left', 'center', 'right'] Returns ------- Any """ return self["xanchor"] @xanchor.setter def xanchor(self, val): self["xanchor"] = val # y # - @property def y(self): """ Sets the y position (in normalized coordinates) of the legend. Defaults to 1 for vertical legends, defaults to "-0.1" for horizontal legends on graphs w/o range sliders and defaults to 1.1 for horizontal legends on graph with one or multiple range sliders. The 'y' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["y"] @y.setter def y(self, val): self["y"] = val # yanchor # ------- @property def yanchor(self): """ Sets the legend's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the legend. Value "auto" anchors legends at their bottom for `y` values less than or equal to 1/3, anchors legends to at their top for `y` values greater than or equal to 2/3 and anchors legends with respect to their middle otherwise. The 'yanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'top', 'middle', 'bottom'] Returns ------- Any """ return self["yanchor"] @yanchor.setter def yanchor(self, val): self["yanchor"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ bgcolor Sets the legend background color. Defaults to `layout.paper_bgcolor`. bordercolor Sets the color of the border enclosing the legend. borderwidth Sets the width (in px) of the border enclosing the legend. font Sets the font used to text the legend items. itemclick Determines the behavior on legend item click. "toggle" toggles the visibility of the item clicked on the graph. "toggleothers" makes the clicked item the sole visible item on the graph. False disable legend item click interactions. itemdoubleclick Determines the behavior on legend item double-click. "toggle" toggles the visibility of the item clicked on the graph. "toggleothers" makes the clicked item the sole visible item on the graph. False disable legend item double-click interactions. itemsizing Determines if the legend items symbols scale with their corresponding "trace" attributes or remain "constant" independent of the symbol size on the graph. orientation Sets the orientation of the legend. tracegroupgap Sets the amount of vertical space (in px) between legend groups. traceorder Determines the order at which the legend items are displayed. If "normal", the items are displayed top-to- bottom in the same order as the input data. If "reversed", the items are displayed in the opposite order as "normal". If "grouped", the items are displayed in groups (when a trace `legendgroup` is provided). if "grouped+reversed", the items are displayed in the opposite order as "grouped". uirevision Controls persistence of legend-driven changes in trace and pie label visibility. Defaults to `layout.uirevision`. valign Sets the vertical alignment of the symbols with respect to their associated text. x Sets the x position (in normalized coordinates) of the legend. Defaults to 1.02 for vertical legends and defaults to 0 for horizontal legends. xanchor Sets the legend's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the legend. Value "auto" anchors legends to the right for `x` values greater than or equal to 2/3, anchors legends to the left for `x` values less than or equal to 1/3 and anchors legends with respect to their center otherwise. y Sets the y position (in normalized coordinates) of the legend. Defaults to 1 for vertical legends, defaults to "-0.1" for horizontal legends on graphs w/o range sliders and defaults to 1.1 for horizontal legends on graph with one or multiple range sliders. yanchor Sets the legend's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the legend. Value "auto" anchors legends at their bottom for `y` values less than or equal to 1/3, anchors legends to at their top for `y` values greater than or equal to 2/3 and anchors legends with respect to their middle otherwise. """ def __init__( self, arg=None, bgcolor=None, bordercolor=None, borderwidth=None, font=None, itemclick=None, itemdoubleclick=None, itemsizing=None, orientation=None, tracegroupgap=None, traceorder=None, uirevision=None, valign=None, x=None, xanchor=None, y=None, yanchor=None, **kwargs ): """ Construct a new Legend object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.Legend bgcolor Sets the legend background color. Defaults to `layout.paper_bgcolor`. bordercolor Sets the color of the border enclosing the legend. borderwidth Sets the width (in px) of the border enclosing the legend. font Sets the font used to text the legend items. itemclick Determines the behavior on legend item click. "toggle" toggles the visibility of the item clicked on the graph. "toggleothers" makes the clicked item the sole visible item on the graph. False disable legend item click interactions. itemdoubleclick Determines the behavior on legend item double-click. "toggle" toggles the visibility of the item clicked on the graph. "toggleothers" makes the clicked item the sole visible item on the graph. False disable legend item double-click interactions. itemsizing Determines if the legend items symbols scale with their corresponding "trace" attributes or remain "constant" independent of the symbol size on the graph. orientation Sets the orientation of the legend. tracegroupgap Sets the amount of vertical space (in px) between legend groups. traceorder Determines the order at which the legend items are displayed. If "normal", the items are displayed top-to- bottom in the same order as the input data. If "reversed", the items are displayed in the opposite order as "normal". If "grouped", the items are displayed in groups (when a trace `legendgroup` is provided). if "grouped+reversed", the items are displayed in the opposite order as "grouped". uirevision Controls persistence of legend-driven changes in trace and pie label visibility. Defaults to `layout.uirevision`. valign Sets the vertical alignment of the symbols with respect to their associated text. x Sets the x position (in normalized coordinates) of the legend. Defaults to 1.02 for vertical legends and defaults to 0 for horizontal legends. xanchor Sets the legend's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the legend. Value "auto" anchors legends to the right for `x` values greater than or equal to 2/3, anchors legends to the left for `x` values less than or equal to 1/3 and anchors legends with respect to their center otherwise. y Sets the y position (in normalized coordinates) of the legend. Defaults to 1 for vertical legends, defaults to "-0.1" for horizontal legends on graphs w/o range sliders and defaults to 1.1 for horizontal legends on graph with one or multiple range sliders. yanchor Sets the legend's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the legend. Value "auto" anchors legends at their bottom for `y` values less than or equal to 1/3, anchors legends to at their top for `y` values greater than or equal to 2/3 and anchors legends with respect to their middle otherwise. Returns ------- Legend """ super(Legend, self).__init__("legend") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.Legend constructor must be a dict or an instance of plotly.graph_objs.layout.Legend""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout import legend as v_legend # Initialize validators # --------------------- self._validators["bgcolor"] = v_legend.BgcolorValidator() self._validators["bordercolor"] = v_legend.BordercolorValidator() self._validators["borderwidth"] = v_legend.BorderwidthValidator() self._validators["font"] = v_legend.FontValidator() self._validators["itemclick"] = v_legend.ItemclickValidator() self._validators["itemdoubleclick"] = v_legend.ItemdoubleclickValidator() self._validators["itemsizing"] = v_legend.ItemsizingValidator() self._validators["orientation"] = v_legend.OrientationValidator() self._validators["tracegroupgap"] = v_legend.TracegroupgapValidator() self._validators["traceorder"] = v_legend.TraceorderValidator() self._validators["uirevision"] = v_legend.UirevisionValidator() self._validators["valign"] = v_legend.ValignValidator() self._validators["x"] = v_legend.XValidator() self._validators["xanchor"] = v_legend.XanchorValidator() self._validators["y"] = v_legend.YValidator() self._validators["yanchor"] = v_legend.YanchorValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("borderwidth", None) self["borderwidth"] = borderwidth if borderwidth is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("itemclick", None) self["itemclick"] = itemclick if itemclick is not None else _v _v = arg.pop("itemdoubleclick", None) self["itemdoubleclick"] = itemdoubleclick if itemdoubleclick is not None else _v _v = arg.pop("itemsizing", None) self["itemsizing"] = itemsizing if itemsizing is not None else _v _v = arg.pop("orientation", None) self["orientation"] = orientation if orientation is not None else _v _v = arg.pop("tracegroupgap", None) self["tracegroupgap"] = tracegroupgap if tracegroupgap is not None else _v _v = arg.pop("traceorder", None) self["traceorder"] = traceorder if traceorder is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("valign", None) self["valign"] = valign if valign is not None else _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xanchor", None) self["xanchor"] = xanchor if xanchor is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("yanchor", None) self["yanchor"] = yanchor if yanchor is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Image(_BaseLayoutHierarchyType): # layer # ----- @property def layer(self): """ Specifies whether images are drawn below or above traces. When `xref` and `yref` are both set to `paper`, image is drawn below the entire plot area. The 'layer' property is an enumeration that may be specified as: - One of the following enumeration values: ['below', 'above'] Returns ------- Any """ return self["layer"] @layer.setter def layer(self, val): self["layer"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the image. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # sizex # ----- @property def sizex(self): """ Sets the image container size horizontally. The image will be sized based on the `position` value. When `xref` is set to `paper`, units are sized relative to the plot width. The 'sizex' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["sizex"] @sizex.setter def sizex(self, val): self["sizex"] = val # sizey # ----- @property def sizey(self): """ Sets the image container size vertically. The image will be sized based on the `position` value. When `yref` is set to `paper`, units are sized relative to the plot height. The 'sizey' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["sizey"] @sizey.setter def sizey(self, val): self["sizey"] = val # sizing # ------ @property def sizing(self): """ Specifies which dimension of the image to constrain. The 'sizing' property is an enumeration that may be specified as: - One of the following enumeration values: ['fill', 'contain', 'stretch'] Returns ------- Any """ return self["sizing"] @sizing.setter def sizing(self, val): self["sizing"] = val # source # ------ @property def source(self): """ Specifies the URL of the image to be used. The URL must be accessible from the domain where the plot code is run, and can be either relative or absolute. The 'source' property is an image URI that may be specified as: - A remote image URI string (e.g. 'http://www.somewhere.com/image.png') - A data URI image string (e.g. 'data:image/png;base64,iVBORw0KGgoAAAANSU') - A PIL.Image.Image object which will be immediately converted to a data URI image string See http://pillow.readthedocs.io/en/latest/reference/Image.html Returns ------- str """ return self["source"] @source.setter def source(self, val): self["source"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # visible # ------- @property def visible(self): """ Determines whether or not this image is visible. The 'visible' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # x # - @property def x(self): """ Sets the image's x position. When `xref` is set to `paper`, units are sized relative to the plot height. See `xref` for more info The 'x' property accepts values of any type Returns ------- Any """ return self["x"] @x.setter def x(self, val): self["x"] = val # xanchor # ------- @property def xanchor(self): """ Sets the anchor for the x position The 'xanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'center', 'right'] Returns ------- Any """ return self["xanchor"] @xanchor.setter def xanchor(self, val): self["xanchor"] = val # xref # ---- @property def xref(self): """ Sets the images's x coordinate axis. If set to a x axis id (e.g. "x" or "x2"), the `x` position refers to an x data coordinate If set to "paper", the `x` position refers to the distance from the left of plot in normalized coordinates where 0 (1) corresponds to the left (right). The 'xref' property is an enumeration that may be specified as: - One of the following enumeration values: ['paper'] - A string that matches one of the following regular expressions: ['^x([2-9]|[1-9][0-9]+)?$'] Returns ------- Any """ return self["xref"] @xref.setter def xref(self, val): self["xref"] = val # y # - @property def y(self): """ Sets the image's y position. When `yref` is set to `paper`, units are sized relative to the plot height. See `yref` for more info The 'y' property accepts values of any type Returns ------- Any """ return self["y"] @y.setter def y(self, val): self["y"] = val # yanchor # ------- @property def yanchor(self): """ Sets the anchor for the y position. The 'yanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['top', 'middle', 'bottom'] Returns ------- Any """ return self["yanchor"] @yanchor.setter def yanchor(self, val): self["yanchor"] = val # yref # ---- @property def yref(self): """ Sets the images's y coordinate axis. If set to a y axis id (e.g. "y" or "y2"), the `y` position refers to a y data coordinate. If set to "paper", the `y` position refers to the distance from the bottom of the plot in normalized coordinates where 0 (1) corresponds to the bottom (top). The 'yref' property is an enumeration that may be specified as: - One of the following enumeration values: ['paper'] - A string that matches one of the following regular expressions: ['^y([2-9]|[1-9][0-9]+)?$'] Returns ------- Any """ return self["yref"] @yref.setter def yref(self, val): self["yref"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ layer Specifies whether images are drawn below or above traces. When `xref` and `yref` are both set to `paper`, image is drawn below the entire plot area. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. opacity Sets the opacity of the image. sizex Sets the image container size horizontally. The image will be sized based on the `position` value. When `xref` is set to `paper`, units are sized relative to the plot width. sizey Sets the image container size vertically. The image will be sized based on the `position` value. When `yref` is set to `paper`, units are sized relative to the plot height. sizing Specifies which dimension of the image to constrain. source Specifies the URL of the image to be used. The URL must be accessible from the domain where the plot code is run, and can be either relative or absolute. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. visible Determines whether or not this image is visible. x Sets the image's x position. When `xref` is set to `paper`, units are sized relative to the plot height. See `xref` for more info xanchor Sets the anchor for the x position xref Sets the images's x coordinate axis. If set to a x axis id (e.g. "x" or "x2"), the `x` position refers to an x data coordinate If set to "paper", the `x` position refers to the distance from the left of plot in normalized coordinates where 0 (1) corresponds to the left (right). y Sets the image's y position. When `yref` is set to `paper`, units are sized relative to the plot height. See `yref` for more info yanchor Sets the anchor for the y position. yref Sets the images's y coordinate axis. If set to a y axis id (e.g. "y" or "y2"), the `y` position refers to a y data coordinate. If set to "paper", the `y` position refers to the distance from the bottom of the plot in normalized coordinates where 0 (1) corresponds to the bottom (top). """ def __init__( self, arg=None, layer=None, name=None, opacity=None, sizex=None, sizey=None, sizing=None, source=None, templateitemname=None, visible=None, x=None, xanchor=None, xref=None, y=None, yanchor=None, yref=None, **kwargs ): """ Construct a new Image object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.Image layer Specifies whether images are drawn below or above traces. When `xref` and `yref` are both set to `paper`, image is drawn below the entire plot area. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. opacity Sets the opacity of the image. sizex Sets the image container size horizontally. The image will be sized based on the `position` value. When `xref` is set to `paper`, units are sized relative to the plot width. sizey Sets the image container size vertically. The image will be sized based on the `position` value. When `yref` is set to `paper`, units are sized relative to the plot height. sizing Specifies which dimension of the image to constrain. source Specifies the URL of the image to be used. The URL must be accessible from the domain where the plot code is run, and can be either relative or absolute. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. visible Determines whether or not this image is visible. x Sets the image's x position. When `xref` is set to `paper`, units are sized relative to the plot height. See `xref` for more info xanchor Sets the anchor for the x position xref Sets the images's x coordinate axis. If set to a x axis id (e.g. "x" or "x2"), the `x` position refers to an x data coordinate If set to "paper", the `x` position refers to the distance from the left of plot in normalized coordinates where 0 (1) corresponds to the left (right). y Sets the image's y position. When `yref` is set to `paper`, units are sized relative to the plot height. See `yref` for more info yanchor Sets the anchor for the y position. yref Sets the images's y coordinate axis. If set to a y axis id (e.g. "y" or "y2"), the `y` position refers to a y data coordinate. If set to "paper", the `y` position refers to the distance from the bottom of the plot in normalized coordinates where 0 (1) corresponds to the bottom (top). Returns ------- Image """ super(Image, self).__init__("images") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.Image constructor must be a dict or an instance of plotly.graph_objs.layout.Image""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout import image as v_image # Initialize validators # --------------------- self._validators["layer"] = v_image.LayerValidator() self._validators["name"] = v_image.NameValidator() self._validators["opacity"] = v_image.OpacityValidator() self._validators["sizex"] = v_image.SizexValidator() self._validators["sizey"] = v_image.SizeyValidator() self._validators["sizing"] = v_image.SizingValidator() self._validators["source"] = v_image.SourceValidator() self._validators["templateitemname"] = v_image.TemplateitemnameValidator() self._validators["visible"] = v_image.VisibleValidator() self._validators["x"] = v_image.XValidator() self._validators["xanchor"] = v_image.XanchorValidator() self._validators["xref"] = v_image.XrefValidator() self._validators["y"] = v_image.YValidator() self._validators["yanchor"] = v_image.YanchorValidator() self._validators["yref"] = v_image.YrefValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("layer", None) self["layer"] = layer if layer is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("sizex", None) self["sizex"] = sizex if sizex is not None else _v _v = arg.pop("sizey", None) self["sizey"] = sizey if sizey is not None else _v _v = arg.pop("sizing", None) self["sizing"] = sizing if sizing is not None else _v _v = arg.pop("source", None) self["source"] = source if source is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xanchor", None) self["xanchor"] = xanchor if xanchor is not None else _v _v = arg.pop("xref", None) self["xref"] = xref if xref is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("yanchor", None) self["yanchor"] = yanchor if yanchor is not None else _v _v = arg.pop("yref", None) self["yref"] = yref if yref is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Hoverlabel(_BaseLayoutHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'right', 'auto'] Returns ------- Any """ return self["align"] @align.setter def align(self, val): self["align"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of all hover labels on graph The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the border color of all hover labels on graph. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # font # ---- @property def font(self): """ Sets the default hover label font used by all traces on the graph. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.layout.hoverlabel.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.layout.hoverlabel.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # namelength # ---------- @property def namelength(self): """ Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. The 'namelength' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [-1, 9223372036854775807] Returns ------- int """ return self["namelength"] @namelength.setter def namelength(self, val): self["namelength"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines bgcolor Sets the background color of all hover labels on graph bordercolor Sets the border color of all hover labels on graph. font Sets the default hover label font used by all traces on the graph. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. """ def __init__( self, arg=None, align=None, bgcolor=None, bordercolor=None, font=None, namelength=None, **kwargs ): """ Construct a new Hoverlabel object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.Hoverlabel align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines bgcolor Sets the background color of all hover labels on graph bordercolor Sets the border color of all hover labels on graph. font Sets the default hover label font used by all traces on the graph. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. Returns ------- Hoverlabel """ super(Hoverlabel, self).__init__("hoverlabel") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.Hoverlabel constructor must be a dict or an instance of plotly.graph_objs.layout.Hoverlabel""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout import hoverlabel as v_hoverlabel # Initialize validators # --------------------- self._validators["align"] = v_hoverlabel.AlignValidator() self._validators["bgcolor"] = v_hoverlabel.BgcolorValidator() self._validators["bordercolor"] = v_hoverlabel.BordercolorValidator() self._validators["font"] = v_hoverlabel.FontValidator() self._validators["namelength"] = v_hoverlabel.NamelengthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("namelength", None) self["namelength"] = namelength if namelength is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Grid(_BaseLayoutHierarchyType): # columns # ------- @property def columns(self): """ The number of columns in the grid. If you provide a 2D `subplots` array, the length of its longest row is used as the default. If you give an `xaxes` array, its length is used as the default. But it's also possible to have a different length, if you want to leave a row at the end for non-cartesian subplots. The 'columns' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [1, 9223372036854775807] Returns ------- int """ return self["columns"] @columns.setter def columns(self, val): self["columns"] = val # domain # ------ @property def domain(self): """ The 'domain' property is an instance of Domain that may be specified as: - An instance of plotly.graph_objs.layout.grid.Domain - A dict of string/value properties that will be passed to the Domain constructor Supported dict properties: x Sets the horizontal domain of this grid subplot (in plot fraction). The first and last cells end exactly at the domain edges, with no grout around the edges. y Sets the vertical domain of this grid subplot (in plot fraction). The first and last cells end exactly at the domain edges, with no grout around the edges. Returns ------- plotly.graph_objs.layout.grid.Domain """ return self["domain"] @domain.setter def domain(self, val): self["domain"] = val # pattern # ------- @property def pattern(self): """ If no `subplots`, `xaxes`, or `yaxes` are given but we do have `rows` and `columns`, we can generate defaults using consecutive axis IDs, in two ways: "coupled" gives one x axis per column and one y axis per row. "independent" uses a new xy pair for each cell, left-to-right across each row then iterating rows according to `roworder`. The 'pattern' property is an enumeration that may be specified as: - One of the following enumeration values: ['independent', 'coupled'] Returns ------- Any """ return self["pattern"] @pattern.setter def pattern(self, val): self["pattern"] = val # roworder # -------- @property def roworder(self): """ Is the first row the top or the bottom? Note that columns are always enumerated from left to right. The 'roworder' property is an enumeration that may be specified as: - One of the following enumeration values: ['top to bottom', 'bottom to top'] Returns ------- Any """ return self["roworder"] @roworder.setter def roworder(self, val): self["roworder"] = val # rows # ---- @property def rows(self): """ The number of rows in the grid. If you provide a 2D `subplots` array or a `yaxes` array, its length is used as the default. But it's also possible to have a different length, if you want to leave a row at the end for non-cartesian subplots. The 'rows' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [1, 9223372036854775807] Returns ------- int """ return self["rows"] @rows.setter def rows(self, val): self["rows"] = val # subplots # -------- @property def subplots(self): """ Used for freeform grids, where some axes may be shared across subplots but others are not. Each entry should be a cartesian subplot id, like "xy" or "x3y2", or "" to leave that cell empty. You may reuse x axes within the same column, and y axes within the same row. Non-cartesian subplots and traces that support `domain` can place themselves in this grid separately using the `gridcell` attribute. The 'subplots' property is an info array that may be specified as: * a 2D list where: The 'subplots[i][j]' property is an enumeration that may be specified as: - One of the following enumeration values: [''] - A string that matches one of the following regular expressions: ['^x([2-9]|[1-9][0-9]+)?y([2-9]|[1-9][0-9]+)?$'] Returns ------- list """ return self["subplots"] @subplots.setter def subplots(self, val): self["subplots"] = val # xaxes # ----- @property def xaxes(self): """ Used with `yaxes` when the x and y axes are shared across columns and rows. Each entry should be an x axis id like "x", "x2", etc., or "" to not put an x axis in that column. Entries other than "" must be unique. Ignored if `subplots` is present. If missing but `yaxes` is present, will generate consecutive IDs. The 'xaxes' property is an info array that may be specified as: * a list of elements where: The 'xaxes[i]' property is an enumeration that may be specified as: - One of the following enumeration values: [''] - A string that matches one of the following regular expressions: ['^x([2-9]|[1-9][0-9]+)?$'] Returns ------- list """ return self["xaxes"] @xaxes.setter def xaxes(self, val): self["xaxes"] = val # xgap # ---- @property def xgap(self): """ Horizontal space between grid cells, expressed as a fraction of the total width available to one cell. Defaults to 0.1 for coupled-axes grids and 0.2 for independent grids. The 'xgap' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["xgap"] @xgap.setter def xgap(self, val): self["xgap"] = val # xside # ----- @property def xside(self): """ Sets where the x axis labels and titles go. "bottom" means the very bottom of the grid. "bottom plot" is the lowest plot that each x axis is used in. "top" and "top plot" are similar. The 'xside' property is an enumeration that may be specified as: - One of the following enumeration values: ['bottom', 'bottom plot', 'top plot', 'top'] Returns ------- Any """ return self["xside"] @xside.setter def xside(self, val): self["xside"] = val # yaxes # ----- @property def yaxes(self): """ Used with `yaxes` when the x and y axes are shared across columns and rows. Each entry should be an y axis id like "y", "y2", etc., or "" to not put a y axis in that row. Entries other than "" must be unique. Ignored if `subplots` is present. If missing but `xaxes` is present, will generate consecutive IDs. The 'yaxes' property is an info array that may be specified as: * a list of elements where: The 'yaxes[i]' property is an enumeration that may be specified as: - One of the following enumeration values: [''] - A string that matches one of the following regular expressions: ['^y([2-9]|[1-9][0-9]+)?$'] Returns ------- list """ return self["yaxes"] @yaxes.setter def yaxes(self, val): self["yaxes"] = val # ygap # ---- @property def ygap(self): """ Vertical space between grid cells, expressed as a fraction of the total height available to one cell. Defaults to 0.1 for coupled-axes grids and 0.3 for independent grids. The 'ygap' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["ygap"] @ygap.setter def ygap(self, val): self["ygap"] = val # yside # ----- @property def yside(self): """ Sets where the y axis labels and titles go. "left" means the very left edge of the grid. *left plot* is the leftmost plot that each y axis is used in. "right" and *right plot* are similar. The 'yside' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'left plot', 'right plot', 'right'] Returns ------- Any """ return self["yside"] @yside.setter def yside(self, val): self["yside"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ columns The number of columns in the grid. If you provide a 2D `subplots` array, the length of its longest row is used as the default. If you give an `xaxes` array, its length is used as the default. But it's also possible to have a different length, if you want to leave a row at the end for non-cartesian subplots. domain plotly.graph_objects.layout.grid.Domain instance or dict with compatible properties pattern If no `subplots`, `xaxes`, or `yaxes` are given but we do have `rows` and `columns`, we can generate defaults using consecutive axis IDs, in two ways: "coupled" gives one x axis per column and one y axis per row. "independent" uses a new xy pair for each cell, left- to-right across each row then iterating rows according to `roworder`. roworder Is the first row the top or the bottom? Note that columns are always enumerated from left to right. rows The number of rows in the grid. If you provide a 2D `subplots` array or a `yaxes` array, its length is used as the default. But it's also possible to have a different length, if you want to leave a row at the end for non-cartesian subplots. subplots Used for freeform grids, where some axes may be shared across subplots but others are not. Each entry should be a cartesian subplot id, like "xy" or "x3y2", or "" to leave that cell empty. You may reuse x axes within the same column, and y axes within the same row. Non- cartesian subplots and traces that support `domain` can place themselves in this grid separately using the `gridcell` attribute. xaxes Used with `yaxes` when the x and y axes are shared across columns and rows. Each entry should be an x axis id like "x", "x2", etc., or "" to not put an x axis in that column. Entries other than "" must be unique. Ignored if `subplots` is present. If missing but `yaxes` is present, will generate consecutive IDs. xgap Horizontal space between grid cells, expressed as a fraction of the total width available to one cell. Defaults to 0.1 for coupled-axes grids and 0.2 for independent grids. xside Sets where the x axis labels and titles go. "bottom" means the very bottom of the grid. "bottom plot" is the lowest plot that each x axis is used in. "top" and "top plot" are similar. yaxes Used with `yaxes` when the x and y axes are shared across columns and rows. Each entry should be an y axis id like "y", "y2", etc., or "" to not put a y axis in that row. Entries other than "" must be unique. Ignored if `subplots` is present. If missing but `xaxes` is present, will generate consecutive IDs. ygap Vertical space between grid cells, expressed as a fraction of the total height available to one cell. Defaults to 0.1 for coupled-axes grids and 0.3 for independent grids. yside Sets where the y axis labels and titles go. "left" means the very left edge of the grid. *left plot* is the leftmost plot that each y axis is used in. "right" and *right plot* are similar. """ def __init__( self, arg=None, columns=None, domain=None, pattern=None, roworder=None, rows=None, subplots=None, xaxes=None, xgap=None, xside=None, yaxes=None, ygap=None, yside=None, **kwargs ): """ Construct a new Grid object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.Grid columns The number of columns in the grid. If you provide a 2D `subplots` array, the length of its longest row is used as the default. If you give an `xaxes` array, its length is used as the default. But it's also possible to have a different length, if you want to leave a row at the end for non-cartesian subplots. domain plotly.graph_objects.layout.grid.Domain instance or dict with compatible properties pattern If no `subplots`, `xaxes`, or `yaxes` are given but we do have `rows` and `columns`, we can generate defaults using consecutive axis IDs, in two ways: "coupled" gives one x axis per column and one y axis per row. "independent" uses a new xy pair for each cell, left- to-right across each row then iterating rows according to `roworder`. roworder Is the first row the top or the bottom? Note that columns are always enumerated from left to right. rows The number of rows in the grid. If you provide a 2D `subplots` array or a `yaxes` array, its length is used as the default. But it's also possible to have a different length, if you want to leave a row at the end for non-cartesian subplots. subplots Used for freeform grids, where some axes may be shared across subplots but others are not. Each entry should be a cartesian subplot id, like "xy" or "x3y2", or "" to leave that cell empty. You may reuse x axes within the same column, and y axes within the same row. Non- cartesian subplots and traces that support `domain` can place themselves in this grid separately using the `gridcell` attribute. xaxes Used with `yaxes` when the x and y axes are shared across columns and rows. Each entry should be an x axis id like "x", "x2", etc., or "" to not put an x axis in that column. Entries other than "" must be unique. Ignored if `subplots` is present. If missing but `yaxes` is present, will generate consecutive IDs. xgap Horizontal space between grid cells, expressed as a fraction of the total width available to one cell. Defaults to 0.1 for coupled-axes grids and 0.2 for independent grids. xside Sets where the x axis labels and titles go. "bottom" means the very bottom of the grid. "bottom plot" is the lowest plot that each x axis is used in. "top" and "top plot" are similar. yaxes Used with `yaxes` when the x and y axes are shared across columns and rows. Each entry should be an y axis id like "y", "y2", etc., or "" to not put a y axis in that row. Entries other than "" must be unique. Ignored if `subplots` is present. If missing but `xaxes` is present, will generate consecutive IDs. ygap Vertical space between grid cells, expressed as a fraction of the total height available to one cell. Defaults to 0.1 for coupled-axes grids and 0.3 for independent grids. yside Sets where the y axis labels and titles go. "left" means the very left edge of the grid. *left plot* is the leftmost plot that each y axis is used in. "right" and *right plot* are similar. Returns ------- Grid """ super(Grid, self).__init__("grid") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.Grid constructor must be a dict or an instance of plotly.graph_objs.layout.Grid""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout import grid as v_grid # Initialize validators # --------------------- self._validators["columns"] = v_grid.ColumnsValidator() self._validators["domain"] = v_grid.DomainValidator() self._validators["pattern"] = v_grid.PatternValidator() self._validators["roworder"] = v_grid.RoworderValidator() self._validators["rows"] = v_grid.RowsValidator() self._validators["subplots"] = v_grid.SubplotsValidator() self._validators["xaxes"] = v_grid.XaxesValidator() self._validators["xgap"] = v_grid.XgapValidator() self._validators["xside"] = v_grid.XsideValidator() self._validators["yaxes"] = v_grid.YaxesValidator() self._validators["ygap"] = v_grid.YgapValidator() self._validators["yside"] = v_grid.YsideValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("columns", None) self["columns"] = columns if columns is not None else _v _v = arg.pop("domain", None) self["domain"] = domain if domain is not None else _v _v = arg.pop("pattern", None) self["pattern"] = pattern if pattern is not None else _v _v = arg.pop("roworder", None) self["roworder"] = roworder if roworder is not None else _v _v = arg.pop("rows", None) self["rows"] = rows if rows is not None else _v _v = arg.pop("subplots", None) self["subplots"] = subplots if subplots is not None else _v _v = arg.pop("xaxes", None) self["xaxes"] = xaxes if xaxes is not None else _v _v = arg.pop("xgap", None) self["xgap"] = xgap if xgap is not None else _v _v = arg.pop("xside", None) self["xside"] = xside if xside is not None else _v _v = arg.pop("yaxes", None) self["yaxes"] = yaxes if yaxes is not None else _v _v = arg.pop("ygap", None) self["ygap"] = ygap if ygap is not None else _v _v = arg.pop("yside", None) self["yside"] = yside if yside is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Geo(_BaseLayoutHierarchyType): # bgcolor # ------- @property def bgcolor(self): """ Set the background color of the map The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # center # ------ @property def center(self): """ The 'center' property is an instance of Center that may be specified as: - An instance of plotly.graph_objs.layout.geo.Center - A dict of string/value properties that will be passed to the Center constructor Supported dict properties: lat Sets the latitude of the map's center. For all projection types, the map's latitude center lies at the middle of the latitude range by default. lon Sets the longitude of the map's center. By default, the map's longitude center lies at the middle of the longitude range for scoped projection and above `projection.rotation.lon` otherwise. Returns ------- plotly.graph_objs.layout.geo.Center """ return self["center"] @center.setter def center(self, val): self["center"] = val # coastlinecolor # -------------- @property def coastlinecolor(self): """ Sets the coastline color. The 'coastlinecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["coastlinecolor"] @coastlinecolor.setter def coastlinecolor(self, val): self["coastlinecolor"] = val # coastlinewidth # -------------- @property def coastlinewidth(self): """ Sets the coastline stroke width (in px). The 'coastlinewidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["coastlinewidth"] @coastlinewidth.setter def coastlinewidth(self, val): self["coastlinewidth"] = val # countrycolor # ------------ @property def countrycolor(self): """ Sets line color of the country boundaries. The 'countrycolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["countrycolor"] @countrycolor.setter def countrycolor(self, val): self["countrycolor"] = val # countrywidth # ------------ @property def countrywidth(self): """ Sets line width (in px) of the country boundaries. The 'countrywidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["countrywidth"] @countrywidth.setter def countrywidth(self, val): self["countrywidth"] = val # domain # ------ @property def domain(self): """ The 'domain' property is an instance of Domain that may be specified as: - An instance of plotly.graph_objs.layout.geo.Domain - A dict of string/value properties that will be passed to the Domain constructor Supported dict properties: column If there is a layout grid, use the domain for this column in the grid for this geo subplot . Note that geo subplots are constrained by domain. In general, when `projection.scale` is set to 1. a map will fit either its x or y domain, but not both. row If there is a layout grid, use the domain for this row in the grid for this geo subplot . Note that geo subplots are constrained by domain. In general, when `projection.scale` is set to 1. a map will fit either its x or y domain, but not both. x Sets the horizontal domain of this geo subplot (in plot fraction). Note that geo subplots are constrained by domain. In general, when `projection.scale` is set to 1. a map will fit either its x or y domain, but not both. y Sets the vertical domain of this geo subplot (in plot fraction). Note that geo subplots are constrained by domain. In general, when `projection.scale` is set to 1. a map will fit either its x or y domain, but not both. Returns ------- plotly.graph_objs.layout.geo.Domain """ return self["domain"] @domain.setter def domain(self, val): self["domain"] = val # framecolor # ---------- @property def framecolor(self): """ Sets the color the frame. The 'framecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["framecolor"] @framecolor.setter def framecolor(self, val): self["framecolor"] = val # framewidth # ---------- @property def framewidth(self): """ Sets the stroke width (in px) of the frame. The 'framewidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["framewidth"] @framewidth.setter def framewidth(self, val): self["framewidth"] = val # lakecolor # --------- @property def lakecolor(self): """ Sets the color of the lakes. The 'lakecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["lakecolor"] @lakecolor.setter def lakecolor(self, val): self["lakecolor"] = val # landcolor # --------- @property def landcolor(self): """ Sets the land mass color. The 'landcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["landcolor"] @landcolor.setter def landcolor(self, val): self["landcolor"] = val # lataxis # ------- @property def lataxis(self): """ The 'lataxis' property is an instance of Lataxis that may be specified as: - An instance of plotly.graph_objs.layout.geo.Lataxis - A dict of string/value properties that will be passed to the Lataxis constructor Supported dict properties: dtick Sets the graticule's longitude/latitude tick step. gridcolor Sets the graticule's stroke color. gridwidth Sets the graticule's stroke width (in px). range Sets the range of this axis (in degrees), sets the map's clipped coordinates. showgrid Sets whether or not graticule are shown on the map. tick0 Sets the graticule's starting tick longitude/latitude. Returns ------- plotly.graph_objs.layout.geo.Lataxis """ return self["lataxis"] @lataxis.setter def lataxis(self, val): self["lataxis"] = val # lonaxis # ------- @property def lonaxis(self): """ The 'lonaxis' property is an instance of Lonaxis that may be specified as: - An instance of plotly.graph_objs.layout.geo.Lonaxis - A dict of string/value properties that will be passed to the Lonaxis constructor Supported dict properties: dtick Sets the graticule's longitude/latitude tick step. gridcolor Sets the graticule's stroke color. gridwidth Sets the graticule's stroke width (in px). range Sets the range of this axis (in degrees), sets the map's clipped coordinates. showgrid Sets whether or not graticule are shown on the map. tick0 Sets the graticule's starting tick longitude/latitude. Returns ------- plotly.graph_objs.layout.geo.Lonaxis """ return self["lonaxis"] @lonaxis.setter def lonaxis(self, val): self["lonaxis"] = val # oceancolor # ---------- @property def oceancolor(self): """ Sets the ocean color The 'oceancolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["oceancolor"] @oceancolor.setter def oceancolor(self, val): self["oceancolor"] = val # projection # ---------- @property def projection(self): """ The 'projection' property is an instance of Projection that may be specified as: - An instance of plotly.graph_objs.layout.geo.Projection - A dict of string/value properties that will be passed to the Projection constructor Supported dict properties: parallels For conic projection types only. Sets the parallels (tangent, secant) where the cone intersects the sphere. rotation plotly.graph_objects.layout.geo.projection.Rota tion instance or dict with compatible properties scale Zooms in or out on the map view. A scale of 1 corresponds to the largest zoom level that fits the map's lon and lat ranges. type Sets the projection type. Returns ------- plotly.graph_objs.layout.geo.Projection """ return self["projection"] @projection.setter def projection(self, val): self["projection"] = val # resolution # ---------- @property def resolution(self): """ Sets the resolution of the base layers. The values have units of km/mm e.g. 110 corresponds to a scale ratio of 1:110,000,000. The 'resolution' property is an enumeration that may be specified as: - One of the following enumeration values: [110, 50] Returns ------- Any """ return self["resolution"] @resolution.setter def resolution(self, val): self["resolution"] = val # rivercolor # ---------- @property def rivercolor(self): """ Sets color of the rivers. The 'rivercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["rivercolor"] @rivercolor.setter def rivercolor(self, val): self["rivercolor"] = val # riverwidth # ---------- @property def riverwidth(self): """ Sets the stroke width (in px) of the rivers. The 'riverwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["riverwidth"] @riverwidth.setter def riverwidth(self, val): self["riverwidth"] = val # scope # ----- @property def scope(self): """ Set the scope of the map. The 'scope' property is an enumeration that may be specified as: - One of the following enumeration values: ['world', 'usa', 'europe', 'asia', 'africa', 'north america', 'south america'] Returns ------- Any """ return self["scope"] @scope.setter def scope(self, val): self["scope"] = val # showcoastlines # -------------- @property def showcoastlines(self): """ Sets whether or not the coastlines are drawn. The 'showcoastlines' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showcoastlines"] @showcoastlines.setter def showcoastlines(self, val): self["showcoastlines"] = val # showcountries # ------------- @property def showcountries(self): """ Sets whether or not country boundaries are drawn. The 'showcountries' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showcountries"] @showcountries.setter def showcountries(self, val): self["showcountries"] = val # showframe # --------- @property def showframe(self): """ Sets whether or not a frame is drawn around the map. The 'showframe' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showframe"] @showframe.setter def showframe(self, val): self["showframe"] = val # showlakes # --------- @property def showlakes(self): """ Sets whether or not lakes are drawn. The 'showlakes' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showlakes"] @showlakes.setter def showlakes(self, val): self["showlakes"] = val # showland # -------- @property def showland(self): """ Sets whether or not land masses are filled in color. The 'showland' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showland"] @showland.setter def showland(self, val): self["showland"] = val # showocean # --------- @property def showocean(self): """ Sets whether or not oceans are filled in color. The 'showocean' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showocean"] @showocean.setter def showocean(self, val): self["showocean"] = val # showrivers # ---------- @property def showrivers(self): """ Sets whether or not rivers are drawn. The 'showrivers' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showrivers"] @showrivers.setter def showrivers(self, val): self["showrivers"] = val # showsubunits # ------------ @property def showsubunits(self): """ Sets whether or not boundaries of subunits within countries (e.g. states, provinces) are drawn. The 'showsubunits' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showsubunits"] @showsubunits.setter def showsubunits(self, val): self["showsubunits"] = val # subunitcolor # ------------ @property def subunitcolor(self): """ Sets the color of the subunits boundaries. The 'subunitcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["subunitcolor"] @subunitcolor.setter def subunitcolor(self, val): self["subunitcolor"] = val # subunitwidth # ------------ @property def subunitwidth(self): """ Sets the stroke width (in px) of the subunits boundaries. The 'subunitwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["subunitwidth"] @subunitwidth.setter def subunitwidth(self, val): self["subunitwidth"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of user-driven changes in the view (projection and center). Defaults to `layout.uirevision`. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ bgcolor Set the background color of the map center plotly.graph_objects.layout.geo.Center instance or dict with compatible properties coastlinecolor Sets the coastline color. coastlinewidth Sets the coastline stroke width (in px). countrycolor Sets line color of the country boundaries. countrywidth Sets line width (in px) of the country boundaries. domain plotly.graph_objects.layout.geo.Domain instance or dict with compatible properties framecolor Sets the color the frame. framewidth Sets the stroke width (in px) of the frame. lakecolor Sets the color of the lakes. landcolor Sets the land mass color. lataxis plotly.graph_objects.layout.geo.Lataxis instance or dict with compatible properties lonaxis plotly.graph_objects.layout.geo.Lonaxis instance or dict with compatible properties oceancolor Sets the ocean color projection plotly.graph_objects.layout.geo.Projection instance or dict with compatible properties resolution Sets the resolution of the base layers. The values have units of km/mm e.g. 110 corresponds to a scale ratio of 1:110,000,000. rivercolor Sets color of the rivers. riverwidth Sets the stroke width (in px) of the rivers. scope Set the scope of the map. showcoastlines Sets whether or not the coastlines are drawn. showcountries Sets whether or not country boundaries are drawn. showframe Sets whether or not a frame is drawn around the map. showlakes Sets whether or not lakes are drawn. showland Sets whether or not land masses are filled in color. showocean Sets whether or not oceans are filled in color. showrivers Sets whether or not rivers are drawn. showsubunits Sets whether or not boundaries of subunits within countries (e.g. states, provinces) are drawn. subunitcolor Sets the color of the subunits boundaries. subunitwidth Sets the stroke width (in px) of the subunits boundaries. uirevision Controls persistence of user-driven changes in the view (projection and center). Defaults to `layout.uirevision`. """ def __init__( self, arg=None, bgcolor=None, center=None, coastlinecolor=None, coastlinewidth=None, countrycolor=None, countrywidth=None, domain=None, framecolor=None, framewidth=None, lakecolor=None, landcolor=None, lataxis=None, lonaxis=None, oceancolor=None, projection=None, resolution=None, rivercolor=None, riverwidth=None, scope=None, showcoastlines=None, showcountries=None, showframe=None, showlakes=None, showland=None, showocean=None, showrivers=None, showsubunits=None, subunitcolor=None, subunitwidth=None, uirevision=None, **kwargs ): """ Construct a new Geo object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.Geo bgcolor Set the background color of the map center plotly.graph_objects.layout.geo.Center instance or dict with compatible properties coastlinecolor Sets the coastline color. coastlinewidth Sets the coastline stroke width (in px). countrycolor Sets line color of the country boundaries. countrywidth Sets line width (in px) of the country boundaries. domain plotly.graph_objects.layout.geo.Domain instance or dict with compatible properties framecolor Sets the color the frame. framewidth Sets the stroke width (in px) of the frame. lakecolor Sets the color of the lakes. landcolor Sets the land mass color. lataxis plotly.graph_objects.layout.geo.Lataxis instance or dict with compatible properties lonaxis plotly.graph_objects.layout.geo.Lonaxis instance or dict with compatible properties oceancolor Sets the ocean color projection plotly.graph_objects.layout.geo.Projection instance or dict with compatible properties resolution Sets the resolution of the base layers. The values have units of km/mm e.g. 110 corresponds to a scale ratio of 1:110,000,000. rivercolor Sets color of the rivers. riverwidth Sets the stroke width (in px) of the rivers. scope Set the scope of the map. showcoastlines Sets whether or not the coastlines are drawn. showcountries Sets whether or not country boundaries are drawn. showframe Sets whether or not a frame is drawn around the map. showlakes Sets whether or not lakes are drawn. showland Sets whether or not land masses are filled in color. showocean Sets whether or not oceans are filled in color. showrivers Sets whether or not rivers are drawn. showsubunits Sets whether or not boundaries of subunits within countries (e.g. states, provinces) are drawn. subunitcolor Sets the color of the subunits boundaries. subunitwidth Sets the stroke width (in px) of the subunits boundaries. uirevision Controls persistence of user-driven changes in the view (projection and center). Defaults to `layout.uirevision`. Returns ------- Geo """ super(Geo, self).__init__("geo") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.Geo constructor must be a dict or an instance of plotly.graph_objs.layout.Geo""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout import geo as v_geo # Initialize validators # --------------------- self._validators["bgcolor"] = v_geo.BgcolorValidator() self._validators["center"] = v_geo.CenterValidator() self._validators["coastlinecolor"] = v_geo.CoastlinecolorValidator() self._validators["coastlinewidth"] = v_geo.CoastlinewidthValidator() self._validators["countrycolor"] = v_geo.CountrycolorValidator() self._validators["countrywidth"] = v_geo.CountrywidthValidator() self._validators["domain"] = v_geo.DomainValidator() self._validators["framecolor"] = v_geo.FramecolorValidator() self._validators["framewidth"] = v_geo.FramewidthValidator() self._validators["lakecolor"] = v_geo.LakecolorValidator() self._validators["landcolor"] = v_geo.LandcolorValidator() self._validators["lataxis"] = v_geo.LataxisValidator() self._validators["lonaxis"] = v_geo.LonaxisValidator() self._validators["oceancolor"] = v_geo.OceancolorValidator() self._validators["projection"] = v_geo.ProjectionValidator() self._validators["resolution"] = v_geo.ResolutionValidator() self._validators["rivercolor"] = v_geo.RivercolorValidator() self._validators["riverwidth"] = v_geo.RiverwidthValidator() self._validators["scope"] = v_geo.ScopeValidator() self._validators["showcoastlines"] = v_geo.ShowcoastlinesValidator() self._validators["showcountries"] = v_geo.ShowcountriesValidator() self._validators["showframe"] = v_geo.ShowframeValidator() self._validators["showlakes"] = v_geo.ShowlakesValidator() self._validators["showland"] = v_geo.ShowlandValidator() self._validators["showocean"] = v_geo.ShowoceanValidator() self._validators["showrivers"] = v_geo.ShowriversValidator() self._validators["showsubunits"] = v_geo.ShowsubunitsValidator() self._validators["subunitcolor"] = v_geo.SubunitcolorValidator() self._validators["subunitwidth"] = v_geo.SubunitwidthValidator() self._validators["uirevision"] = v_geo.UirevisionValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("center", None) self["center"] = center if center is not None else _v _v = arg.pop("coastlinecolor", None) self["coastlinecolor"] = coastlinecolor if coastlinecolor is not None else _v _v = arg.pop("coastlinewidth", None) self["coastlinewidth"] = coastlinewidth if coastlinewidth is not None else _v _v = arg.pop("countrycolor", None) self["countrycolor"] = countrycolor if countrycolor is not None else _v _v = arg.pop("countrywidth", None) self["countrywidth"] = countrywidth if countrywidth is not None else _v _v = arg.pop("domain", None) self["domain"] = domain if domain is not None else _v _v = arg.pop("framecolor", None) self["framecolor"] = framecolor if framecolor is not None else _v _v = arg.pop("framewidth", None) self["framewidth"] = framewidth if framewidth is not None else _v _v = arg.pop("lakecolor", None) self["lakecolor"] = lakecolor if lakecolor is not None else _v _v = arg.pop("landcolor", None) self["landcolor"] = landcolor if landcolor is not None else _v _v = arg.pop("lataxis", None) self["lataxis"] = lataxis if lataxis is not None else _v _v = arg.pop("lonaxis", None) self["lonaxis"] = lonaxis if lonaxis is not None else _v _v = arg.pop("oceancolor", None) self["oceancolor"] = oceancolor if oceancolor is not None else _v _v = arg.pop("projection", None) self["projection"] = projection if projection is not None else _v _v = arg.pop("resolution", None) self["resolution"] = resolution if resolution is not None else _v _v = arg.pop("rivercolor", None) self["rivercolor"] = rivercolor if rivercolor is not None else _v _v = arg.pop("riverwidth", None) self["riverwidth"] = riverwidth if riverwidth is not None else _v _v = arg.pop("scope", None) self["scope"] = scope if scope is not None else _v _v = arg.pop("showcoastlines", None) self["showcoastlines"] = showcoastlines if showcoastlines is not None else _v _v = arg.pop("showcountries", None) self["showcountries"] = showcountries if showcountries is not None else _v _v = arg.pop("showframe", None) self["showframe"] = showframe if showframe is not None else _v _v = arg.pop("showlakes", None) self["showlakes"] = showlakes if showlakes is not None else _v _v = arg.pop("showland", None) self["showland"] = showland if showland is not None else _v _v = arg.pop("showocean", None) self["showocean"] = showocean if showocean is not None else _v _v = arg.pop("showrivers", None) self["showrivers"] = showrivers if showrivers is not None else _v _v = arg.pop("showsubunits", None) self["showsubunits"] = showsubunits if showsubunits is not None else _v _v = arg.pop("subunitcolor", None) self["subunitcolor"] = subunitcolor if subunitcolor is not None else _v _v = arg.pop("subunitwidth", None) self["subunitwidth"] = subunitwidth if subunitwidth is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Font(_BaseLayoutHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets the global font. Note that fonts used in traces and other layout components inherit from the global font. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.Font constructor must be a dict or an instance of plotly.graph_objs.layout.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Colorscale(_BaseLayoutHierarchyType): # diverging # --------- @property def diverging(self): """ Sets the default diverging colorscale. Note that `autocolorscale` must be true for this attribute to work. The 'diverging' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["diverging"] @diverging.setter def diverging(self, val): self["diverging"] = val # sequential # ---------- @property def sequential(self): """ Sets the default sequential colorscale for positive values. Note that `autocolorscale` must be true for this attribute to work. The 'sequential' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["sequential"] @sequential.setter def sequential(self, val): self["sequential"] = val # sequentialminus # --------------- @property def sequentialminus(self): """ Sets the default sequential colorscale for negative values. Note that `autocolorscale` must be true for this attribute to work. The 'sequentialminus' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["sequentialminus"] @sequentialminus.setter def sequentialminus(self, val): self["sequentialminus"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ diverging Sets the default diverging colorscale. Note that `autocolorscale` must be true for this attribute to work. sequential Sets the default sequential colorscale for positive values. Note that `autocolorscale` must be true for this attribute to work. sequentialminus Sets the default sequential colorscale for negative values. Note that `autocolorscale` must be true for this attribute to work. """ def __init__( self, arg=None, diverging=None, sequential=None, sequentialminus=None, **kwargs ): """ Construct a new Colorscale object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.Colorscale diverging Sets the default diverging colorscale. Note that `autocolorscale` must be true for this attribute to work. sequential Sets the default sequential colorscale for positive values. Note that `autocolorscale` must be true for this attribute to work. sequentialminus Sets the default sequential colorscale for negative values. Note that `autocolorscale` must be true for this attribute to work. Returns ------- Colorscale """ super(Colorscale, self).__init__("colorscale") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.Colorscale constructor must be a dict or an instance of plotly.graph_objs.layout.Colorscale""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout import colorscale as v_colorscale # Initialize validators # --------------------- self._validators["diverging"] = v_colorscale.DivergingValidator() self._validators["sequential"] = v_colorscale.SequentialValidator() self._validators["sequentialminus"] = v_colorscale.SequentialminusValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("diverging", None) self["diverging"] = diverging if diverging is not None else _v _v = arg.pop("sequential", None) self["sequential"] = sequential if sequential is not None else _v _v = arg.pop("sequentialminus", None) self["sequentialminus"] = sequentialminus if sequentialminus is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Coloraxis(_BaseLayoutHierarchyType): # autocolorscale # -------------- @property def autocolorscale(self): """ Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. The 'autocolorscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocolorscale"] @autocolorscale.setter def autocolorscale(self, val): self["autocolorscale"] = val # cauto # ----- @property def cauto(self): """ Determines whether or not the color domain is computed with respect to the input data (here corresponding trace color array(s)) or the bounds set in `cmin` and `cmax` Defaults to `false` when `cmin` and `cmax` are set by the user. The 'cauto' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["cauto"] @cauto.setter def cauto(self, val): self["cauto"] = val # cmax # ---- @property def cmax(self): """ Sets the upper bound of the color domain. Value should have the same units as corresponding trace color array(s) and if set, `cmin` must be set as well. The 'cmax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmax"] @cmax.setter def cmax(self, val): self["cmax"] = val # cmid # ---- @property def cmid(self): """ Sets the mid-point of the color domain by scaling `cmin` and/or `cmax` to be equidistant to this point. Value should have the same units as corresponding trace color array(s). Has no effect when `cauto` is `false`. The 'cmid' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmid"] @cmid.setter def cmid(self, val): self["cmid"] = val # cmin # ---- @property def cmin(self): """ Sets the lower bound of the color domain. Value should have the same units as corresponding trace color array(s) and if set, `cmax` must be set as well. The 'cmin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmin"] @cmin.setter def cmin(self, val): self["cmin"] = val # colorbar # -------- @property def colorbar(self): """ The 'colorbar' property is an instance of ColorBar that may be specified as: - An instance of plotly.graph_objs.layout.coloraxis.ColorBar - A dict of string/value properties that will be passed to the ColorBar constructor Supported dict properties: bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.layout.coloraxi s.colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.lay out.coloraxis.colorbar.tickformatstopdefaults), sets the default property values to use for elements of layout.coloraxis.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.layout.coloraxis.colorbar. Title instance or dict with compatible properties titlefont Deprecated: Please use layout.coloraxis.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use layout.coloraxis.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- plotly.graph_objs.layout.coloraxis.ColorBar """ return self["colorbar"] @colorbar.setter def colorbar(self, val): self["colorbar"] = val # colorscale # ---------- @property def colorscale(self): """ Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`cmin` and `cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,Earth,Electric,Vi ridis,Cividis. The 'colorscale' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # reversescale # ------------ @property def reversescale(self): """ Reverses the color mapping if true. If true, `cmin` will correspond to the last color in the array and `cmax` will correspond to the first color. The 'reversescale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["reversescale"] @reversescale.setter def reversescale(self, val): self["reversescale"] = val # showscale # --------- @property def showscale(self): """ Determines whether or not a colorbar is displayed for this trace. The 'showscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showscale"] @showscale.setter def showscale(self, val): self["showscale"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here corresponding trace color array(s)) or the bounds set in `cmin` and `cmax` Defaults to `false` when `cmin` and `cmax` are set by the user. cmax Sets the upper bound of the color domain. Value should have the same units as corresponding trace color array(s) and if set, `cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `cmin` and/or `cmax` to be equidistant to this point. Value should have the same units as corresponding trace color array(s). Has no effect when `cauto` is `false`. cmin Sets the lower bound of the color domain. Value should have the same units as corresponding trace color array(s) and if set, `cmax` must be set as well. colorbar plotly.graph_objects.layout.coloraxis.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`cmin` and `cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. reversescale Reverses the color mapping if true. If true, `cmin` will correspond to the last color in the array and `cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. """ def __init__( self, arg=None, autocolorscale=None, cauto=None, cmax=None, cmid=None, cmin=None, colorbar=None, colorscale=None, reversescale=None, showscale=None, **kwargs ): """ Construct a new Coloraxis object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.Coloraxis autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here corresponding trace color array(s)) or the bounds set in `cmin` and `cmax` Defaults to `false` when `cmin` and `cmax` are set by the user. cmax Sets the upper bound of the color domain. Value should have the same units as corresponding trace color array(s) and if set, `cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `cmin` and/or `cmax` to be equidistant to this point. Value should have the same units as corresponding trace color array(s). Has no effect when `cauto` is `false`. cmin Sets the lower bound of the color domain. Value should have the same units as corresponding trace color array(s) and if set, `cmax` must be set as well. colorbar plotly.graph_objects.layout.coloraxis.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`cmin` and `cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. reversescale Reverses the color mapping if true. If true, `cmin` will correspond to the last color in the array and `cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Returns ------- Coloraxis """ super(Coloraxis, self).__init__("coloraxis") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.Coloraxis constructor must be a dict or an instance of plotly.graph_objs.layout.Coloraxis""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout import coloraxis as v_coloraxis # Initialize validators # --------------------- self._validators["autocolorscale"] = v_coloraxis.AutocolorscaleValidator() self._validators["cauto"] = v_coloraxis.CautoValidator() self._validators["cmax"] = v_coloraxis.CmaxValidator() self._validators["cmid"] = v_coloraxis.CmidValidator() self._validators["cmin"] = v_coloraxis.CminValidator() self._validators["colorbar"] = v_coloraxis.ColorBarValidator() self._validators["colorscale"] = v_coloraxis.ColorscaleValidator() self._validators["reversescale"] = v_coloraxis.ReversescaleValidator() self._validators["showscale"] = v_coloraxis.ShowscaleValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autocolorscale", None) self["autocolorscale"] = autocolorscale if autocolorscale is not None else _v _v = arg.pop("cauto", None) self["cauto"] = cauto if cauto is not None else _v _v = arg.pop("cmax", None) self["cmax"] = cmax if cmax is not None else _v _v = arg.pop("cmid", None) self["cmid"] = cmid if cmid is not None else _v _v = arg.pop("cmin", None) self["cmin"] = cmin if cmin is not None else _v _v = arg.pop("colorbar", None) self["colorbar"] = colorbar if colorbar is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("reversescale", None) self["reversescale"] = reversescale if reversescale is not None else _v _v = arg.pop("showscale", None) self["showscale"] = showscale if showscale is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Annotation(_BaseLayoutHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the `text` within the box. Has an effect only if `text` spans more two or more lines (i.e. `text` contains one or more
HTML tags) or if an explicit width is set to override the text width. The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'center', 'right'] Returns ------- Any """ return self["align"] @align.setter def align(self, val): self["align"] = val # arrowcolor # ---------- @property def arrowcolor(self): """ Sets the color of the annotation arrow. The 'arrowcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["arrowcolor"] @arrowcolor.setter def arrowcolor(self, val): self["arrowcolor"] = val # arrowhead # --------- @property def arrowhead(self): """ Sets the end annotation arrow head style. The 'arrowhead' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 8] Returns ------- int """ return self["arrowhead"] @arrowhead.setter def arrowhead(self, val): self["arrowhead"] = val # arrowside # --------- @property def arrowside(self): """ Sets the annotation arrow head position. The 'arrowside' property is a flaglist and may be specified as a string containing: - Any combination of ['end', 'start'] joined with '+' characters (e.g. 'end+start') OR exactly one of ['none'] (e.g. 'none') Returns ------- Any """ return self["arrowside"] @arrowside.setter def arrowside(self, val): self["arrowside"] = val # arrowsize # --------- @property def arrowsize(self): """ Sets the size of the end annotation arrow head, relative to `arrowwidth`. A value of 1 (default) gives a head about 3x as wide as the line. The 'arrowsize' property is a number and may be specified as: - An int or float in the interval [0.3, inf] Returns ------- int|float """ return self["arrowsize"] @arrowsize.setter def arrowsize(self, val): self["arrowsize"] = val # arrowwidth # ---------- @property def arrowwidth(self): """ Sets the width (in px) of annotation arrow line. The 'arrowwidth' property is a number and may be specified as: - An int or float in the interval [0.1, inf] Returns ------- int|float """ return self["arrowwidth"] @arrowwidth.setter def arrowwidth(self, val): self["arrowwidth"] = val # ax # -- @property def ax(self): """ Sets the x component of the arrow tail about the arrow head. If `axref` is `pixel`, a positive (negative) component corresponds to an arrow pointing from right to left (left to right). If `axref` is an axis, this is an absolute value on that axis, like `x`, NOT a relative value. The 'ax' property accepts values of any type Returns ------- Any """ return self["ax"] @ax.setter def ax(self, val): self["ax"] = val # axref # ----- @property def axref(self): """ Indicates in what terms the tail of the annotation (ax,ay) is specified. If `pixel`, `ax` is a relative offset in pixels from `x`. If set to an x axis id (e.g. "x" or "x2"), `ax` is specified in the same terms as that axis. This is useful for trendline annotations which should continue to indicate the correct trend when zoomed. The 'axref' property is an enumeration that may be specified as: - One of the following enumeration values: ['pixel'] - A string that matches one of the following regular expressions: ['^x([2-9]|[1-9][0-9]+)?$'] Returns ------- Any """ return self["axref"] @axref.setter def axref(self, val): self["axref"] = val # ay # -- @property def ay(self): """ Sets the y component of the arrow tail about the arrow head. If `ayref` is `pixel`, a positive (negative) component corresponds to an arrow pointing from bottom to top (top to bottom). If `ayref` is an axis, this is an absolute value on that axis, like `y`, NOT a relative value. The 'ay' property accepts values of any type Returns ------- Any """ return self["ay"] @ay.setter def ay(self, val): self["ay"] = val # ayref # ----- @property def ayref(self): """ Indicates in what terms the tail of the annotation (ax,ay) is specified. If `pixel`, `ay` is a relative offset in pixels from `y`. If set to a y axis id (e.g. "y" or "y2"), `ay` is specified in the same terms as that axis. This is useful for trendline annotations which should continue to indicate the correct trend when zoomed. The 'ayref' property is an enumeration that may be specified as: - One of the following enumeration values: ['pixel'] - A string that matches one of the following regular expressions: ['^y([2-9]|[1-9][0-9]+)?$'] Returns ------- Any """ return self["ayref"] @ayref.setter def ayref(self, val): self["ayref"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the annotation. The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the color of the border enclosing the annotation `text`. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # borderpad # --------- @property def borderpad(self): """ Sets the padding (in px) between the `text` and the enclosing border. The 'borderpad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["borderpad"] @borderpad.setter def borderpad(self, val): self["borderpad"] = val # borderwidth # ----------- @property def borderwidth(self): """ Sets the width (in px) of the border enclosing the annotation `text`. The 'borderwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["borderwidth"] @borderwidth.setter def borderwidth(self, val): self["borderwidth"] = val # captureevents # ------------- @property def captureevents(self): """ Determines whether the annotation text box captures mouse move and click events, or allows those events to pass through to data points in the plot that may be behind the annotation. By default `captureevents` is False unless `hovertext` is provided. If you use the event `plotly_clickannotation` without `hovertext` you must explicitly enable `captureevents`. The 'captureevents' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["captureevents"] @captureevents.setter def captureevents(self, val): self["captureevents"] = val # clicktoshow # ----------- @property def clicktoshow(self): """ Makes this annotation respond to clicks on the plot. If you click a data point that exactly matches the `x` and `y` values of this annotation, and it is hidden (visible: false), it will appear. In "onoff" mode, you must click the same point again to make it disappear, so if you click multiple points, you can show multiple annotations. In "onout" mode, a click anywhere else in the plot (on another data point or not) will hide this annotation. If you need to show/hide this annotation in response to different `x` or `y` values, you can set `xclick` and/or `yclick`. This is useful for example to label the side of a bar. To label markers though, `standoff` is preferred over `xclick` and `yclick`. The 'clicktoshow' property is an enumeration that may be specified as: - One of the following enumeration values: [False, 'onoff', 'onout'] Returns ------- Any """ return self["clicktoshow"] @clicktoshow.setter def clicktoshow(self, val): self["clicktoshow"] = val # font # ---- @property def font(self): """ Sets the annotation text font. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.layout.annotation.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.layout.annotation.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # height # ------ @property def height(self): """ Sets an explicit height for the text box. null (default) lets the text set the box height. Taller text will be clipped. The 'height' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["height"] @height.setter def height(self, val): self["height"] = val # hoverlabel # ---------- @property def hoverlabel(self): """ The 'hoverlabel' property is an instance of Hoverlabel that may be specified as: - An instance of plotly.graph_objs.layout.annotation.Hoverlabel - A dict of string/value properties that will be passed to the Hoverlabel constructor Supported dict properties: bgcolor Sets the background color of the hover label. By default uses the annotation's `bgcolor` made opaque, or white if it was transparent. bordercolor Sets the border color of the hover label. By default uses either dark grey or white, for maximum contrast with `hoverlabel.bgcolor`. font Sets the hover label text font. By default uses the global hover font and size, with color from `hoverlabel.bordercolor`. Returns ------- plotly.graph_objs.layout.annotation.Hoverlabel """ return self["hoverlabel"] @hoverlabel.setter def hoverlabel(self, val): self["hoverlabel"] = val # hovertext # --------- @property def hovertext(self): """ Sets text to appear when hovering over this annotation. If omitted or blank, no hover label will appear. The 'hovertext' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["hovertext"] @hovertext.setter def hovertext(self, val): self["hovertext"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the annotation (text + arrow). The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # showarrow # --------- @property def showarrow(self): """ Determines whether or not the annotation is drawn with an arrow. If True, `text` is placed near the arrow's tail. If False, `text` lines up with the `x` and `y` provided. The 'showarrow' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showarrow"] @showarrow.setter def showarrow(self, val): self["showarrow"] = val # standoff # -------- @property def standoff(self): """ Sets a distance, in pixels, to move the end arrowhead away from the position it is pointing at, for example to point at the edge of a marker independent of zoom. Note that this shortens the arrow from the `ax` / `ay` vector, in contrast to `xshift` / `yshift` which moves everything by this amount. The 'standoff' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["standoff"] @standoff.setter def standoff(self, val): self["standoff"] = val # startarrowhead # -------------- @property def startarrowhead(self): """ Sets the start annotation arrow head style. The 'startarrowhead' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 8] Returns ------- int """ return self["startarrowhead"] @startarrowhead.setter def startarrowhead(self, val): self["startarrowhead"] = val # startarrowsize # -------------- @property def startarrowsize(self): """ Sets the size of the start annotation arrow head, relative to `arrowwidth`. A value of 1 (default) gives a head about 3x as wide as the line. The 'startarrowsize' property is a number and may be specified as: - An int or float in the interval [0.3, inf] Returns ------- int|float """ return self["startarrowsize"] @startarrowsize.setter def startarrowsize(self, val): self["startarrowsize"] = val # startstandoff # ------------- @property def startstandoff(self): """ Sets a distance, in pixels, to move the start arrowhead away from the position it is pointing at, for example to point at the edge of a marker independent of zoom. Note that this shortens the arrow from the `ax` / `ay` vector, in contrast to `xshift` / `yshift` which moves everything by this amount. The 'startstandoff' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["startstandoff"] @startstandoff.setter def startstandoff(self, val): self["startstandoff"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # text # ---- @property def text(self): """ Sets the text associated with this annotation. Plotly uses a subset of HTML tags to do things like newline (
), bold (), italics (), hyperlinks (). Tags , , are also supported. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # textangle # --------- @property def textangle(self): """ Sets the angle at which the `text` is drawn with respect to the horizontal. The 'textangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["textangle"] @textangle.setter def textangle(self, val): self["textangle"] = val # valign # ------ @property def valign(self): """ Sets the vertical alignment of the `text` within the box. Has an effect only if an explicit height is set to override the text height. The 'valign' property is an enumeration that may be specified as: - One of the following enumeration values: ['top', 'middle', 'bottom'] Returns ------- Any """ return self["valign"] @valign.setter def valign(self, val): self["valign"] = val # visible # ------- @property def visible(self): """ Determines whether or not this annotation is visible. The 'visible' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # width # ----- @property def width(self): """ Sets an explicit width for the text box. null (default) lets the text set the box width. Wider text will be clipped. There is no automatic wrapping; use
to start a new line. The 'width' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # x # - @property def x(self): """ Sets the annotation's x position. If the axis `type` is "log", then you must take the log of your desired range. If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. The 'x' property accepts values of any type Returns ------- Any """ return self["x"] @x.setter def x(self, val): self["x"] = val # xanchor # ------- @property def xanchor(self): """ Sets the text box's horizontal position anchor This anchor binds the `x` position to the "left", "center" or "right" of the annotation. For example, if `x` is set to 1, `xref` to "paper" and `xanchor` to "right" then the right-most portion of the annotation lines up with the right-most edge of the plotting area. If "auto", the anchor is equivalent to "center" for data-referenced annotations or if there is an arrow, whereas for paper-referenced with no arrow, the anchor picked corresponds to the closest side. The 'xanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'left', 'center', 'right'] Returns ------- Any """ return self["xanchor"] @xanchor.setter def xanchor(self, val): self["xanchor"] = val # xclick # ------ @property def xclick(self): """ Toggle this annotation when clicking a data point whose `x` value is `xclick` rather than the annotation's `x` value. The 'xclick' property accepts values of any type Returns ------- Any """ return self["xclick"] @xclick.setter def xclick(self, val): self["xclick"] = val # xref # ---- @property def xref(self): """ Sets the annotation's x coordinate axis. If set to an x axis id (e.g. "x" or "x2"), the `x` position refers to an x coordinate If set to "paper", the `x` position refers to the distance from the left side of the plotting area in normalized coordinates where 0 (1) corresponds to the left (right) side. The 'xref' property is an enumeration that may be specified as: - One of the following enumeration values: ['paper'] - A string that matches one of the following regular expressions: ['^x([2-9]|[1-9][0-9]+)?$'] Returns ------- Any """ return self["xref"] @xref.setter def xref(self, val): self["xref"] = val # xshift # ------ @property def xshift(self): """ Shifts the position of the whole annotation and arrow to the right (positive) or left (negative) by this many pixels. The 'xshift' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["xshift"] @xshift.setter def xshift(self, val): self["xshift"] = val # y # - @property def y(self): """ Sets the annotation's y position. If the axis `type` is "log", then you must take the log of your desired range. If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. The 'y' property accepts values of any type Returns ------- Any """ return self["y"] @y.setter def y(self, val): self["y"] = val # yanchor # ------- @property def yanchor(self): """ Sets the text box's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the annotation. For example, if `y` is set to 1, `yref` to "paper" and `yanchor` to "top" then the top-most portion of the annotation lines up with the top-most edge of the plotting area. If "auto", the anchor is equivalent to "middle" for data- referenced annotations or if there is an arrow, whereas for paper-referenced with no arrow, the anchor picked corresponds to the closest side. The 'yanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'top', 'middle', 'bottom'] Returns ------- Any """ return self["yanchor"] @yanchor.setter def yanchor(self, val): self["yanchor"] = val # yclick # ------ @property def yclick(self): """ Toggle this annotation when clicking a data point whose `y` value is `yclick` rather than the annotation's `y` value. The 'yclick' property accepts values of any type Returns ------- Any """ return self["yclick"] @yclick.setter def yclick(self, val): self["yclick"] = val # yref # ---- @property def yref(self): """ Sets the annotation's y coordinate axis. If set to an y axis id (e.g. "y" or "y2"), the `y` position refers to an y coordinate If set to "paper", the `y` position refers to the distance from the bottom of the plotting area in normalized coordinates where 0 (1) corresponds to the bottom (top). The 'yref' property is an enumeration that may be specified as: - One of the following enumeration values: ['paper'] - A string that matches one of the following regular expressions: ['^y([2-9]|[1-9][0-9]+)?$'] Returns ------- Any """ return self["yref"] @yref.setter def yref(self, val): self["yref"] = val # yshift # ------ @property def yshift(self): """ Shifts the position of the whole annotation and arrow up (positive) or down (negative) by this many pixels. The 'yshift' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["yshift"] @yshift.setter def yshift(self, val): self["yshift"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the `text` within the box. Has an effect only if `text` spans more two or more lines (i.e. `text` contains one or more
HTML tags) or if an explicit width is set to override the text width. arrowcolor Sets the color of the annotation arrow. arrowhead Sets the end annotation arrow head style. arrowside Sets the annotation arrow head position. arrowsize Sets the size of the end annotation arrow head, relative to `arrowwidth`. A value of 1 (default) gives a head about 3x as wide as the line. arrowwidth Sets the width (in px) of annotation arrow line. ax Sets the x component of the arrow tail about the arrow head. If `axref` is `pixel`, a positive (negative) component corresponds to an arrow pointing from right to left (left to right). If `axref` is an axis, this is an absolute value on that axis, like `x`, NOT a relative value. axref Indicates in what terms the tail of the annotation (ax,ay) is specified. If `pixel`, `ax` is a relative offset in pixels from `x`. If set to an x axis id (e.g. "x" or "x2"), `ax` is specified in the same terms as that axis. This is useful for trendline annotations which should continue to indicate the correct trend when zoomed. ay Sets the y component of the arrow tail about the arrow head. If `ayref` is `pixel`, a positive (negative) component corresponds to an arrow pointing from bottom to top (top to bottom). If `ayref` is an axis, this is an absolute value on that axis, like `y`, NOT a relative value. ayref Indicates in what terms the tail of the annotation (ax,ay) is specified. If `pixel`, `ay` is a relative offset in pixels from `y`. If set to a y axis id (e.g. "y" or "y2"), `ay` is specified in the same terms as that axis. This is useful for trendline annotations which should continue to indicate the correct trend when zoomed. bgcolor Sets the background color of the annotation. bordercolor Sets the color of the border enclosing the annotation `text`. borderpad Sets the padding (in px) between the `text` and the enclosing border. borderwidth Sets the width (in px) of the border enclosing the annotation `text`. captureevents Determines whether the annotation text box captures mouse move and click events, or allows those events to pass through to data points in the plot that may be behind the annotation. By default `captureevents` is False unless `hovertext` is provided. If you use the event `plotly_clickannotation` without `hovertext` you must explicitly enable `captureevents`. clicktoshow Makes this annotation respond to clicks on the plot. If you click a data point that exactly matches the `x` and `y` values of this annotation, and it is hidden (visible: false), it will appear. In "onoff" mode, you must click the same point again to make it disappear, so if you click multiple points, you can show multiple annotations. In "onout" mode, a click anywhere else in the plot (on another data point or not) will hide this annotation. If you need to show/hide this annotation in response to different `x` or `y` values, you can set `xclick` and/or `yclick`. This is useful for example to label the side of a bar. To label markers though, `standoff` is preferred over `xclick` and `yclick`. font Sets the annotation text font. height Sets an explicit height for the text box. null (default) lets the text set the box height. Taller text will be clipped. hoverlabel plotly.graph_objects.layout.annotation.Hoverlabel instance or dict with compatible properties hovertext Sets text to appear when hovering over this annotation. If omitted or blank, no hover label will appear. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. opacity Sets the opacity of the annotation (text + arrow). showarrow Determines whether or not the annotation is drawn with an arrow. If True, `text` is placed near the arrow's tail. If False, `text` lines up with the `x` and `y` provided. standoff Sets a distance, in pixels, to move the end arrowhead away from the position it is pointing at, for example to point at the edge of a marker independent of zoom. Note that this shortens the arrow from the `ax` / `ay` vector, in contrast to `xshift` / `yshift` which moves everything by this amount. startarrowhead Sets the start annotation arrow head style. startarrowsize Sets the size of the start annotation arrow head, relative to `arrowwidth`. A value of 1 (default) gives a head about 3x as wide as the line. startstandoff Sets a distance, in pixels, to move the start arrowhead away from the position it is pointing at, for example to point at the edge of a marker independent of zoom. Note that this shortens the arrow from the `ax` / `ay` vector, in contrast to `xshift` / `yshift` which moves everything by this amount. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. text Sets the text associated with this annotation. Plotly uses a subset of HTML tags to do things like newline (
), bold (), italics (), hyperlinks (). Tags , , are also supported. textangle Sets the angle at which the `text` is drawn with respect to the horizontal. valign Sets the vertical alignment of the `text` within the box. Has an effect only if an explicit height is set to override the text height. visible Determines whether or not this annotation is visible. width Sets an explicit width for the text box. null (default) lets the text set the box width. Wider text will be clipped. There is no automatic wrapping; use
to start a new line. x Sets the annotation's x position. If the axis `type` is "log", then you must take the log of your desired range. If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. xanchor Sets the text box's horizontal position anchor This anchor binds the `x` position to the "left", "center" or "right" of the annotation. For example, if `x` is set to 1, `xref` to "paper" and `xanchor` to "right" then the right-most portion of the annotation lines up with the right-most edge of the plotting area. If "auto", the anchor is equivalent to "center" for data- referenced annotations or if there is an arrow, whereas for paper-referenced with no arrow, the anchor picked corresponds to the closest side. xclick Toggle this annotation when clicking a data point whose `x` value is `xclick` rather than the annotation's `x` value. xref Sets the annotation's x coordinate axis. If set to an x axis id (e.g. "x" or "x2"), the `x` position refers to an x coordinate If set to "paper", the `x` position refers to the distance from the left side of the plotting area in normalized coordinates where 0 (1) corresponds to the left (right) side. xshift Shifts the position of the whole annotation and arrow to the right (positive) or left (negative) by this many pixels. y Sets the annotation's y position. If the axis `type` is "log", then you must take the log of your desired range. If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. yanchor Sets the text box's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the annotation. For example, if `y` is set to 1, `yref` to "paper" and `yanchor` to "top" then the top-most portion of the annotation lines up with the top-most edge of the plotting area. If "auto", the anchor is equivalent to "middle" for data-referenced annotations or if there is an arrow, whereas for paper- referenced with no arrow, the anchor picked corresponds to the closest side. yclick Toggle this annotation when clicking a data point whose `y` value is `yclick` rather than the annotation's `y` value. yref Sets the annotation's y coordinate axis. If set to an y axis id (e.g. "y" or "y2"), the `y` position refers to an y coordinate If set to "paper", the `y` position refers to the distance from the bottom of the plotting area in normalized coordinates where 0 (1) corresponds to the bottom (top). yshift Shifts the position of the whole annotation and arrow up (positive) or down (negative) by this many pixels. """ def __init__( self, arg=None, align=None, arrowcolor=None, arrowhead=None, arrowside=None, arrowsize=None, arrowwidth=None, ax=None, axref=None, ay=None, ayref=None, bgcolor=None, bordercolor=None, borderpad=None, borderwidth=None, captureevents=None, clicktoshow=None, font=None, height=None, hoverlabel=None, hovertext=None, name=None, opacity=None, showarrow=None, standoff=None, startarrowhead=None, startarrowsize=None, startstandoff=None, templateitemname=None, text=None, textangle=None, valign=None, visible=None, width=None, x=None, xanchor=None, xclick=None, xref=None, xshift=None, y=None, yanchor=None, yclick=None, yref=None, yshift=None, **kwargs ): """ Construct a new Annotation object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.Annotation align Sets the horizontal alignment of the `text` within the box. Has an effect only if `text` spans more two or more lines (i.e. `text` contains one or more
HTML tags) or if an explicit width is set to override the text width. arrowcolor Sets the color of the annotation arrow. arrowhead Sets the end annotation arrow head style. arrowside Sets the annotation arrow head position. arrowsize Sets the size of the end annotation arrow head, relative to `arrowwidth`. A value of 1 (default) gives a head about 3x as wide as the line. arrowwidth Sets the width (in px) of annotation arrow line. ax Sets the x component of the arrow tail about the arrow head. If `axref` is `pixel`, a positive (negative) component corresponds to an arrow pointing from right to left (left to right). If `axref` is an axis, this is an absolute value on that axis, like `x`, NOT a relative value. axref Indicates in what terms the tail of the annotation (ax,ay) is specified. If `pixel`, `ax` is a relative offset in pixels from `x`. If set to an x axis id (e.g. "x" or "x2"), `ax` is specified in the same terms as that axis. This is useful for trendline annotations which should continue to indicate the correct trend when zoomed. ay Sets the y component of the arrow tail about the arrow head. If `ayref` is `pixel`, a positive (negative) component corresponds to an arrow pointing from bottom to top (top to bottom). If `ayref` is an axis, this is an absolute value on that axis, like `y`, NOT a relative value. ayref Indicates in what terms the tail of the annotation (ax,ay) is specified. If `pixel`, `ay` is a relative offset in pixels from `y`. If set to a y axis id (e.g. "y" or "y2"), `ay` is specified in the same terms as that axis. This is useful for trendline annotations which should continue to indicate the correct trend when zoomed. bgcolor Sets the background color of the annotation. bordercolor Sets the color of the border enclosing the annotation `text`. borderpad Sets the padding (in px) between the `text` and the enclosing border. borderwidth Sets the width (in px) of the border enclosing the annotation `text`. captureevents Determines whether the annotation text box captures mouse move and click events, or allows those events to pass through to data points in the plot that may be behind the annotation. By default `captureevents` is False unless `hovertext` is provided. If you use the event `plotly_clickannotation` without `hovertext` you must explicitly enable `captureevents`. clicktoshow Makes this annotation respond to clicks on the plot. If you click a data point that exactly matches the `x` and `y` values of this annotation, and it is hidden (visible: false), it will appear. In "onoff" mode, you must click the same point again to make it disappear, so if you click multiple points, you can show multiple annotations. In "onout" mode, a click anywhere else in the plot (on another data point or not) will hide this annotation. If you need to show/hide this annotation in response to different `x` or `y` values, you can set `xclick` and/or `yclick`. This is useful for example to label the side of a bar. To label markers though, `standoff` is preferred over `xclick` and `yclick`. font Sets the annotation text font. height Sets an explicit height for the text box. null (default) lets the text set the box height. Taller text will be clipped. hoverlabel plotly.graph_objects.layout.annotation.Hoverlabel instance or dict with compatible properties hovertext Sets text to appear when hovering over this annotation. If omitted or blank, no hover label will appear. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. opacity Sets the opacity of the annotation (text + arrow). showarrow Determines whether or not the annotation is drawn with an arrow. If True, `text` is placed near the arrow's tail. If False, `text` lines up with the `x` and `y` provided. standoff Sets a distance, in pixels, to move the end arrowhead away from the position it is pointing at, for example to point at the edge of a marker independent of zoom. Note that this shortens the arrow from the `ax` / `ay` vector, in contrast to `xshift` / `yshift` which moves everything by this amount. startarrowhead Sets the start annotation arrow head style. startarrowsize Sets the size of the start annotation arrow head, relative to `arrowwidth`. A value of 1 (default) gives a head about 3x as wide as the line. startstandoff Sets a distance, in pixels, to move the start arrowhead away from the position it is pointing at, for example to point at the edge of a marker independent of zoom. Note that this shortens the arrow from the `ax` / `ay` vector, in contrast to `xshift` / `yshift` which moves everything by this amount. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. text Sets the text associated with this annotation. Plotly uses a subset of HTML tags to do things like newline (
), bold (), italics (), hyperlinks (). Tags , , are also supported. textangle Sets the angle at which the `text` is drawn with respect to the horizontal. valign Sets the vertical alignment of the `text` within the box. Has an effect only if an explicit height is set to override the text height. visible Determines whether or not this annotation is visible. width Sets an explicit width for the text box. null (default) lets the text set the box width. Wider text will be clipped. There is no automatic wrapping; use
to start a new line. x Sets the annotation's x position. If the axis `type` is "log", then you must take the log of your desired range. If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. xanchor Sets the text box's horizontal position anchor This anchor binds the `x` position to the "left", "center" or "right" of the annotation. For example, if `x` is set to 1, `xref` to "paper" and `xanchor` to "right" then the right-most portion of the annotation lines up with the right-most edge of the plotting area. If "auto", the anchor is equivalent to "center" for data- referenced annotations or if there is an arrow, whereas for paper-referenced with no arrow, the anchor picked corresponds to the closest side. xclick Toggle this annotation when clicking a data point whose `x` value is `xclick` rather than the annotation's `x` value. xref Sets the annotation's x coordinate axis. If set to an x axis id (e.g. "x" or "x2"), the `x` position refers to an x coordinate If set to "paper", the `x` position refers to the distance from the left side of the plotting area in normalized coordinates where 0 (1) corresponds to the left (right) side. xshift Shifts the position of the whole annotation and arrow to the right (positive) or left (negative) by this many pixels. y Sets the annotation's y position. If the axis `type` is "log", then you must take the log of your desired range. If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. yanchor Sets the text box's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the annotation. For example, if `y` is set to 1, `yref` to "paper" and `yanchor` to "top" then the top-most portion of the annotation lines up with the top-most edge of the plotting area. If "auto", the anchor is equivalent to "middle" for data-referenced annotations or if there is an arrow, whereas for paper- referenced with no arrow, the anchor picked corresponds to the closest side. yclick Toggle this annotation when clicking a data point whose `y` value is `yclick` rather than the annotation's `y` value. yref Sets the annotation's y coordinate axis. If set to an y axis id (e.g. "y" or "y2"), the `y` position refers to an y coordinate If set to "paper", the `y` position refers to the distance from the bottom of the plotting area in normalized coordinates where 0 (1) corresponds to the bottom (top). yshift Shifts the position of the whole annotation and arrow up (positive) or down (negative) by this many pixels. Returns ------- Annotation """ super(Annotation, self).__init__("annotations") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.Annotation constructor must be a dict or an instance of plotly.graph_objs.layout.Annotation""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout import annotation as v_annotation # Initialize validators # --------------------- self._validators["align"] = v_annotation.AlignValidator() self._validators["arrowcolor"] = v_annotation.ArrowcolorValidator() self._validators["arrowhead"] = v_annotation.ArrowheadValidator() self._validators["arrowside"] = v_annotation.ArrowsideValidator() self._validators["arrowsize"] = v_annotation.ArrowsizeValidator() self._validators["arrowwidth"] = v_annotation.ArrowwidthValidator() self._validators["ax"] = v_annotation.AxValidator() self._validators["axref"] = v_annotation.AxrefValidator() self._validators["ay"] = v_annotation.AyValidator() self._validators["ayref"] = v_annotation.AyrefValidator() self._validators["bgcolor"] = v_annotation.BgcolorValidator() self._validators["bordercolor"] = v_annotation.BordercolorValidator() self._validators["borderpad"] = v_annotation.BorderpadValidator() self._validators["borderwidth"] = v_annotation.BorderwidthValidator() self._validators["captureevents"] = v_annotation.CaptureeventsValidator() self._validators["clicktoshow"] = v_annotation.ClicktoshowValidator() self._validators["font"] = v_annotation.FontValidator() self._validators["height"] = v_annotation.HeightValidator() self._validators["hoverlabel"] = v_annotation.HoverlabelValidator() self._validators["hovertext"] = v_annotation.HovertextValidator() self._validators["name"] = v_annotation.NameValidator() self._validators["opacity"] = v_annotation.OpacityValidator() self._validators["showarrow"] = v_annotation.ShowarrowValidator() self._validators["standoff"] = v_annotation.StandoffValidator() self._validators["startarrowhead"] = v_annotation.StartarrowheadValidator() self._validators["startarrowsize"] = v_annotation.StartarrowsizeValidator() self._validators["startstandoff"] = v_annotation.StartstandoffValidator() self._validators["templateitemname"] = v_annotation.TemplateitemnameValidator() self._validators["text"] = v_annotation.TextValidator() self._validators["textangle"] = v_annotation.TextangleValidator() self._validators["valign"] = v_annotation.ValignValidator() self._validators["visible"] = v_annotation.VisibleValidator() self._validators["width"] = v_annotation.WidthValidator() self._validators["x"] = v_annotation.XValidator() self._validators["xanchor"] = v_annotation.XanchorValidator() self._validators["xclick"] = v_annotation.XclickValidator() self._validators["xref"] = v_annotation.XrefValidator() self._validators["xshift"] = v_annotation.XshiftValidator() self._validators["y"] = v_annotation.YValidator() self._validators["yanchor"] = v_annotation.YanchorValidator() self._validators["yclick"] = v_annotation.YclickValidator() self._validators["yref"] = v_annotation.YrefValidator() self._validators["yshift"] = v_annotation.YshiftValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("arrowcolor", None) self["arrowcolor"] = arrowcolor if arrowcolor is not None else _v _v = arg.pop("arrowhead", None) self["arrowhead"] = arrowhead if arrowhead is not None else _v _v = arg.pop("arrowside", None) self["arrowside"] = arrowside if arrowside is not None else _v _v = arg.pop("arrowsize", None) self["arrowsize"] = arrowsize if arrowsize is not None else _v _v = arg.pop("arrowwidth", None) self["arrowwidth"] = arrowwidth if arrowwidth is not None else _v _v = arg.pop("ax", None) self["ax"] = ax if ax is not None else _v _v = arg.pop("axref", None) self["axref"] = axref if axref is not None else _v _v = arg.pop("ay", None) self["ay"] = ay if ay is not None else _v _v = arg.pop("ayref", None) self["ayref"] = ayref if ayref is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("borderpad", None) self["borderpad"] = borderpad if borderpad is not None else _v _v = arg.pop("borderwidth", None) self["borderwidth"] = borderwidth if borderwidth is not None else _v _v = arg.pop("captureevents", None) self["captureevents"] = captureevents if captureevents is not None else _v _v = arg.pop("clicktoshow", None) self["clicktoshow"] = clicktoshow if clicktoshow is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("height", None) self["height"] = height if height is not None else _v _v = arg.pop("hoverlabel", None) self["hoverlabel"] = hoverlabel if hoverlabel is not None else _v _v = arg.pop("hovertext", None) self["hovertext"] = hovertext if hovertext is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("showarrow", None) self["showarrow"] = showarrow if showarrow is not None else _v _v = arg.pop("standoff", None) self["standoff"] = standoff if standoff is not None else _v _v = arg.pop("startarrowhead", None) self["startarrowhead"] = startarrowhead if startarrowhead is not None else _v _v = arg.pop("startarrowsize", None) self["startarrowsize"] = startarrowsize if startarrowsize is not None else _v _v = arg.pop("startstandoff", None) self["startstandoff"] = startstandoff if startstandoff is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("text", None) self["text"] = text if text is not None else _v _v = arg.pop("textangle", None) self["textangle"] = textangle if textangle is not None else _v _v = arg.pop("valign", None) self["valign"] = valign if valign is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xanchor", None) self["xanchor"] = xanchor if xanchor is not None else _v _v = arg.pop("xclick", None) self["xclick"] = xclick if xclick is not None else _v _v = arg.pop("xref", None) self["xref"] = xref if xref is not None else _v _v = arg.pop("xshift", None) self["xshift"] = xshift if xshift is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("yanchor", None) self["yanchor"] = yanchor if yanchor is not None else _v _v = arg.pop("yclick", None) self["yclick"] = yclick if yclick is not None else _v _v = arg.pop("yref", None) self["yref"] = yref if yref is not None else _v _v = arg.pop("yshift", None) self["yshift"] = yshift if yshift is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class AngularAxis(_BaseLayoutHierarchyType): # domain # ------ @property def domain(self): """ Polar chart subplots are not supported yet. This key has currently no effect. The 'domain' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'domain[0]' property is a number and may be specified as: - An int or float in the interval [0, 1] (1) The 'domain[1]' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- list """ return self["domain"] @domain.setter def domain(self, val): self["domain"] = val # endpadding # ---------- @property def endpadding(self): """ Legacy polar charts are deprecated! Please switch to "polar" subplots. The 'endpadding' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["endpadding"] @endpadding.setter def endpadding(self, val): self["endpadding"] = val # range # ----- @property def range(self): """ Legacy polar charts are deprecated! Please switch to "polar" subplots. Defines the start and end point of this angular axis. The 'range' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'range[0]' property is a number and may be specified as: - An int or float (1) The 'range[1]' property is a number and may be specified as: - An int or float Returns ------- list """ return self["range"] @range.setter def range(self, val): self["range"] = val # showline # -------- @property def showline(self): """ Legacy polar charts are deprecated! Please switch to "polar" subplots. Determines whether or not the line bounding this angular axis will be shown on the figure. The 'showline' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showline"] @showline.setter def showline(self, val): self["showline"] = val # showticklabels # -------------- @property def showticklabels(self): """ Legacy polar charts are deprecated! Please switch to "polar" subplots. Determines whether or not the angular axis ticks will feature tick labels. The 'showticklabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showticklabels"] @showticklabels.setter def showticklabels(self, val): self["showticklabels"] = val # tickcolor # --------- @property def tickcolor(self): """ Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the color of the tick lines on this angular axis. The 'tickcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["tickcolor"] @tickcolor.setter def tickcolor(self, val): self["tickcolor"] = val # ticklen # ------- @property def ticklen(self): """ Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the length of the tick lines on this angular axis. The 'ticklen' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ticklen"] @ticklen.setter def ticklen(self, val): self["ticklen"] = val # tickorientation # --------------- @property def tickorientation(self): """ Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the orientation (from the paper perspective) of the angular axis tick labels. The 'tickorientation' property is an enumeration that may be specified as: - One of the following enumeration values: ['horizontal', 'vertical'] Returns ------- Any """ return self["tickorientation"] @tickorientation.setter def tickorientation(self, val): self["tickorientation"] = val # ticksuffix # ---------- @property def ticksuffix(self): """ Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the length of the tick lines on this angular axis. The 'ticksuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ticksuffix"] @ticksuffix.setter def ticksuffix(self, val): self["ticksuffix"] = val # visible # ------- @property def visible(self): """ Legacy polar charts are deprecated! Please switch to "polar" subplots. Determines whether or not this axis will be visible. The 'visible' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ domain Polar chart subplots are not supported yet. This key has currently no effect. endpadding Legacy polar charts are deprecated! Please switch to "polar" subplots. range Legacy polar charts are deprecated! Please switch to "polar" subplots. Defines the start and end point of this angular axis. showline Legacy polar charts are deprecated! Please switch to "polar" subplots. Determines whether or not the line bounding this angular axis will be shown on the figure. showticklabels Legacy polar charts are deprecated! Please switch to "polar" subplots. Determines whether or not the angular axis ticks will feature tick labels. tickcolor Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the color of the tick lines on this angular axis. ticklen Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the length of the tick lines on this angular axis. tickorientation Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the orientation (from the paper perspective) of the angular axis tick labels. ticksuffix Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the length of the tick lines on this angular axis. visible Legacy polar charts are deprecated! Please switch to "polar" subplots. Determines whether or not this axis will be visible. """ def __init__( self, arg=None, domain=None, endpadding=None, range=None, showline=None, showticklabels=None, tickcolor=None, ticklen=None, tickorientation=None, ticksuffix=None, visible=None, **kwargs ): """ Construct a new AngularAxis object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.AngularAxis domain Polar chart subplots are not supported yet. This key has currently no effect. endpadding Legacy polar charts are deprecated! Please switch to "polar" subplots. range Legacy polar charts are deprecated! Please switch to "polar" subplots. Defines the start and end point of this angular axis. showline Legacy polar charts are deprecated! Please switch to "polar" subplots. Determines whether or not the line bounding this angular axis will be shown on the figure. showticklabels Legacy polar charts are deprecated! Please switch to "polar" subplots. Determines whether or not the angular axis ticks will feature tick labels. tickcolor Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the color of the tick lines on this angular axis. ticklen Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the length of the tick lines on this angular axis. tickorientation Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the orientation (from the paper perspective) of the angular axis tick labels. ticksuffix Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the length of the tick lines on this angular axis. visible Legacy polar charts are deprecated! Please switch to "polar" subplots. Determines whether or not this axis will be visible. Returns ------- AngularAxis """ super(AngularAxis, self).__init__("angularaxis") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.AngularAxis constructor must be a dict or an instance of plotly.graph_objs.layout.AngularAxis""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout import angularaxis as v_angularaxis # Initialize validators # --------------------- self._validators["domain"] = v_angularaxis.DomainValidator() self._validators["endpadding"] = v_angularaxis.EndpaddingValidator() self._validators["range"] = v_angularaxis.RangeValidator() self._validators["showline"] = v_angularaxis.ShowlineValidator() self._validators["showticklabels"] = v_angularaxis.ShowticklabelsValidator() self._validators["tickcolor"] = v_angularaxis.TickcolorValidator() self._validators["ticklen"] = v_angularaxis.TicklenValidator() self._validators["tickorientation"] = v_angularaxis.TickorientationValidator() self._validators["ticksuffix"] = v_angularaxis.TicksuffixValidator() self._validators["visible"] = v_angularaxis.VisibleValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("domain", None) self["domain"] = domain if domain is not None else _v _v = arg.pop("endpadding", None) self["endpadding"] = endpadding if endpadding is not None else _v _v = arg.pop("range", None) self["range"] = range if range is not None else _v _v = arg.pop("showline", None) self["showline"] = showline if showline is not None else _v _v = arg.pop("showticklabels", None) self["showticklabels"] = showticklabels if showticklabels is not None else _v _v = arg.pop("tickcolor", None) self["tickcolor"] = tickcolor if tickcolor is not None else _v _v = arg.pop("ticklen", None) self["ticklen"] = ticklen if ticklen is not None else _v _v = arg.pop("tickorientation", None) self["tickorientation"] = tickorientation if tickorientation is not None else _v _v = arg.pop("ticksuffix", None) self["ticksuffix"] = ticksuffix if ticksuffix is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = [ "AngularAxis", "Annotation", "Annotation", "Coloraxis", "Colorscale", "Font", "Geo", "Grid", "Hoverlabel", "Image", "Image", "Legend", "Mapbox", "Margin", "Modebar", "Polar", "RadialAxis", "Scene", "Shape", "Shape", "Slider", "Slider", "Template", "Ternary", "Title", "Transition", "Updatemenu", "Updatemenu", "XAxis", "YAxis", "annotation", "coloraxis", "geo", "grid", "hoverlabel", "legend", "mapbox", "polar", "scene", "shape", "slider", "template", "ternary", "title", "updatemenu", "xaxis", "yaxis", ] from plotly.graph_objs.layout import yaxis from plotly.graph_objs.layout import xaxis from plotly.graph_objs.layout import updatemenu from plotly.graph_objs.layout import title from plotly.graph_objs.layout import ternary from plotly.graph_objs.layout import template from plotly.graph_objs.layout import slider from plotly.graph_objs.layout import shape from plotly.graph_objs.layout import scene from plotly.graph_objs.layout import polar from plotly.graph_objs.layout import mapbox from plotly.graph_objs.layout import legend from plotly.graph_objs.layout import hoverlabel from plotly.graph_objs.layout import grid from plotly.graph_objs.layout import geo from plotly.graph_objs.layout import coloraxis from plotly.graph_objs.layout import annotation plotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/xaxis/0000755000175000017500000000000013573746613022402 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/xaxis/rangeslider/0000755000175000017500000000000013573746613024701 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/xaxis/rangeslider/__init__.py0000644000175000017500000001074113573721550027006 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class YAxis(_BaseLayoutHierarchyType): # range # ----- @property def range(self): """ Sets the range of this axis for the rangeslider. The 'range' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'range[0]' property accepts values of any type (1) The 'range[1]' property accepts values of any type Returns ------- list """ return self["range"] @range.setter def range(self, val): self["range"] = val # rangemode # --------- @property def rangemode(self): """ Determines whether or not the range of this axis in the rangeslider use the same value than in the main plot when zooming in/out. If "auto", the autorange will be used. If "fixed", the `range` is used. If "match", the current range of the corresponding y-axis on the main subplot is used. The 'rangemode' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'fixed', 'match'] Returns ------- Any """ return self["rangemode"] @rangemode.setter def rangemode(self, val): self["rangemode"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.xaxis.rangeslider" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ range Sets the range of this axis for the rangeslider. rangemode Determines whether or not the range of this axis in the rangeslider use the same value than in the main plot when zooming in/out. If "auto", the autorange will be used. If "fixed", the `range` is used. If "match", the current range of the corresponding y-axis on the main subplot is used. """ def __init__(self, arg=None, range=None, rangemode=None, **kwargs): """ Construct a new YAxis object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.xaxis.rangeslider.YAxis range Sets the range of this axis for the rangeslider. rangemode Determines whether or not the range of this axis in the rangeslider use the same value than in the main plot when zooming in/out. If "auto", the autorange will be used. If "fixed", the `range` is used. If "match", the current range of the corresponding y-axis on the main subplot is used. Returns ------- YAxis """ super(YAxis, self).__init__("yaxis") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.xaxis.rangeslider.YAxis constructor must be a dict or an instance of plotly.graph_objs.layout.xaxis.rangeslider.YAxis""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.xaxis.rangeslider import yaxis as v_yaxis # Initialize validators # --------------------- self._validators["range"] = v_yaxis.RangeValidator() self._validators["rangemode"] = v_yaxis.RangemodeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("range", None) self["range"] = range if range is not None else _v _v = arg.pop("rangemode", None) self["rangemode"] = rangemode if rangemode is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["YAxis"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/xaxis/title/0000755000175000017500000000000013573746613023523 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/xaxis/title/__init__.py0000644000175000017500000002050513573721550025627 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Font(_BaseLayoutHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.xaxis.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.xaxis.title.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.xaxis.title.Font constructor must be a dict or an instance of plotly.graph_objs.layout.xaxis.title.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.xaxis.title import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/xaxis/rangeselector/0000755000175000017500000000000013573746613025237 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/xaxis/rangeselector/__init__.py0000644000175000017500000005053713573721550027353 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Font(_BaseLayoutHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.xaxis.rangeselector" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets the font of the range selector button text. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.xaxis.rangeselector.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.xaxis.rangeselector.Font constructor must be a dict or an instance of plotly.graph_objs.layout.xaxis.rangeselector.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.xaxis.rangeselector import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Button(_BaseLayoutHierarchyType): # count # ----- @property def count(self): """ Sets the number of steps to take to update the range. Use with `step` to specify the update interval. The 'count' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["count"] @count.setter def count(self, val): self["count"] = val # label # ----- @property def label(self): """ Sets the text label to appear on the button. The 'label' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["label"] @label.setter def label(self, val): self["label"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # step # ---- @property def step(self): """ The unit of measurement that the `count` value will set the range by. The 'step' property is an enumeration that may be specified as: - One of the following enumeration values: ['month', 'year', 'day', 'hour', 'minute', 'second', 'all'] Returns ------- Any """ return self["step"] @step.setter def step(self, val): self["step"] = val # stepmode # -------- @property def stepmode(self): """ Sets the range update mode. If "backward", the range update shifts the start of range back "count" times "step" milliseconds. If "todate", the range update shifts the start of range back to the first timestamp from "count" times "step" milliseconds back. For example, with `step` set to "year" and `count` set to 1 the range update shifts the start of the range back to January 01 of the current year. Month and year "todate" are currently available only for the built-in (Gregorian) calendar. The 'stepmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['backward', 'todate'] Returns ------- Any """ return self["stepmode"] @stepmode.setter def stepmode(self, val): self["stepmode"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # visible # ------- @property def visible(self): """ Determines whether or not this button is visible. The 'visible' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.xaxis.rangeselector" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ count Sets the number of steps to take to update the range. Use with `step` to specify the update interval. label Sets the text label to appear on the button. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. step The unit of measurement that the `count` value will set the range by. stepmode Sets the range update mode. If "backward", the range update shifts the start of range back "count" times "step" milliseconds. If "todate", the range update shifts the start of range back to the first timestamp from "count" times "step" milliseconds back. For example, with `step` set to "year" and `count` set to 1 the range update shifts the start of the range back to January 01 of the current year. Month and year "todate" are currently available only for the built-in (Gregorian) calendar. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. visible Determines whether or not this button is visible. """ def __init__( self, arg=None, count=None, label=None, name=None, step=None, stepmode=None, templateitemname=None, visible=None, **kwargs ): """ Construct a new Button object Sets the specifications for each buttons. By default, a range selector comes with no buttons. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.xaxis.rangeselector.Button count Sets the number of steps to take to update the range. Use with `step` to specify the update interval. label Sets the text label to appear on the button. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. step The unit of measurement that the `count` value will set the range by. stepmode Sets the range update mode. If "backward", the range update shifts the start of range back "count" times "step" milliseconds. If "todate", the range update shifts the start of range back to the first timestamp from "count" times "step" milliseconds back. For example, with `step` set to "year" and `count` set to 1 the range update shifts the start of the range back to January 01 of the current year. Month and year "todate" are currently available only for the built-in (Gregorian) calendar. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. visible Determines whether or not this button is visible. Returns ------- Button """ super(Button, self).__init__("buttons") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.xaxis.rangeselector.Button constructor must be a dict or an instance of plotly.graph_objs.layout.xaxis.rangeselector.Button""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.xaxis.rangeselector import button as v_button # Initialize validators # --------------------- self._validators["count"] = v_button.CountValidator() self._validators["label"] = v_button.LabelValidator() self._validators["name"] = v_button.NameValidator() self._validators["step"] = v_button.StepValidator() self._validators["stepmode"] = v_button.StepmodeValidator() self._validators["templateitemname"] = v_button.TemplateitemnameValidator() self._validators["visible"] = v_button.VisibleValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("count", None) self["count"] = count if count is not None else _v _v = arg.pop("label", None) self["label"] = label if label is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("step", None) self["step"] = step if step is not None else _v _v = arg.pop("stepmode", None) self["stepmode"] = stepmode if stepmode is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Button", "Button", "Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/xaxis/__init__.py0000644000175000017500000020410613573721550024507 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Title(_BaseLayoutHierarchyType): # font # ---- @property def font(self): """ Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.layout.xaxis.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.layout.xaxis.title.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # standoff # -------- @property def standoff(self): """ Sets the standoff distance (in px) between the axis labels and the title text The default value is a function of the axis tick labels, the title `font.size` and the axis `linewidth`. Note that the axis title position is always constrained within the margins, so the actual standoff distance is always less than the set or default value. By setting `standoff` and turning on `automargin`, plotly.js will push the margins to fit the axis title at given standoff distance. The 'standoff' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["standoff"] @standoff.setter def standoff(self, val): self["standoff"] = val # text # ---- @property def text(self): """ Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.xaxis" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. standoff Sets the standoff distance (in px) between the axis labels and the title text The default value is a function of the axis tick labels, the title `font.size` and the axis `linewidth`. Note that the axis title position is always constrained within the margins, so the actual standoff distance is always less than the set or default value. By setting `standoff` and turning on `automargin`, plotly.js will push the margins to fit the axis title at given standoff distance. text Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """ def __init__(self, arg=None, font=None, standoff=None, text=None, **kwargs): """ Construct a new Title object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.xaxis.Title font Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. standoff Sets the standoff distance (in px) between the axis labels and the title text The default value is a function of the axis tick labels, the title `font.size` and the axis `linewidth`. Note that the axis title position is always constrained within the margins, so the actual standoff distance is always less than the set or default value. By setting `standoff` and turning on `automargin`, plotly.js will push the margins to fit the axis title at given standoff distance. text Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- Title """ super(Title, self).__init__("title") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.xaxis.Title constructor must be a dict or an instance of plotly.graph_objs.layout.xaxis.Title""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.xaxis import title as v_title # Initialize validators # --------------------- self._validators["font"] = v_title.FontValidator() self._validators["standoff"] = v_title.StandoffValidator() self._validators["text"] = v_title.TextValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("standoff", None) self["standoff"] = standoff if standoff is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Tickformatstop(_BaseLayoutHierarchyType): # dtickrange # ---------- @property def dtickrange(self): """ range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" The 'dtickrange' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'dtickrange[0]' property accepts values of any type (1) The 'dtickrange[1]' property accepts values of any type Returns ------- list """ return self["dtickrange"] @dtickrange.setter def dtickrange(self, val): self["dtickrange"] = val # enabled # ------- @property def enabled(self): """ Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. The 'enabled' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["enabled"] @enabled.setter def enabled(self, val): self["enabled"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # value # ----- @property def value(self): """ string - dtickformat for described zoom level, the same as "tickformat" The 'value' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.xaxis" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """ def __init__( self, arg=None, dtickrange=None, enabled=None, name=None, templateitemname=None, value=None, **kwargs ): """ Construct a new Tickformatstop object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.xaxis.Tickformatstop dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- Tickformatstop """ super(Tickformatstop, self).__init__("tickformatstops") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.xaxis.Tickformatstop constructor must be a dict or an instance of plotly.graph_objs.layout.xaxis.Tickformatstop""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.xaxis import tickformatstop as v_tickformatstop # Initialize validators # --------------------- self._validators["dtickrange"] = v_tickformatstop.DtickrangeValidator() self._validators["enabled"] = v_tickformatstop.EnabledValidator() self._validators["name"] = v_tickformatstop.NameValidator() self._validators[ "templateitemname" ] = v_tickformatstop.TemplateitemnameValidator() self._validators["value"] = v_tickformatstop.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtickrange", None) self["dtickrange"] = dtickrange if dtickrange is not None else _v _v = arg.pop("enabled", None) self["enabled"] = enabled if enabled is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Tickfont(_BaseLayoutHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.xaxis" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Tickfont object Sets the tick font. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.xaxis.Tickfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Tickfont """ super(Tickfont, self).__init__("tickfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.xaxis.Tickfont constructor must be a dict or an instance of plotly.graph_objs.layout.xaxis.Tickfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.xaxis import tickfont as v_tickfont # Initialize validators # --------------------- self._validators["color"] = v_tickfont.ColorValidator() self._validators["family"] = v_tickfont.FamilyValidator() self._validators["size"] = v_tickfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Rangeslider(_BaseLayoutHierarchyType): # autorange # --------- @property def autorange(self): """ Determines whether or not the range slider range is computed in relation to the input data. If `range` is provided, then `autorange` is set to False. The 'autorange' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autorange"] @autorange.setter def autorange(self, val): self["autorange"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the range slider. The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the border color of the range slider. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # borderwidth # ----------- @property def borderwidth(self): """ Sets the border width of the range slider. The 'borderwidth' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["borderwidth"] @borderwidth.setter def borderwidth(self, val): self["borderwidth"] = val # range # ----- @property def range(self): """ Sets the range of the range slider. If not set, defaults to the full xaxis range. If the axis `type` is "log", then you must take the log of your desired range. If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. The 'range' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'range[0]' property accepts values of any type (1) The 'range[1]' property accepts values of any type Returns ------- list """ return self["range"] @range.setter def range(self, val): self["range"] = val # thickness # --------- @property def thickness(self): """ The height of the range slider as a fraction of the total plot area height. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # visible # ------- @property def visible(self): """ Determines whether or not the range slider will be visible. If visible, perpendicular axes will be set to `fixedrange` The 'visible' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # yaxis # ----- @property def yaxis(self): """ The 'yaxis' property is an instance of YAxis that may be specified as: - An instance of plotly.graph_objs.layout.xaxis.rangeslider.YAxis - A dict of string/value properties that will be passed to the YAxis constructor Supported dict properties: range Sets the range of this axis for the rangeslider. rangemode Determines whether or not the range of this axis in the rangeslider use the same value than in the main plot when zooming in/out. If "auto", the autorange will be used. If "fixed", the `range` is used. If "match", the current range of the corresponding y-axis on the main subplot is used. Returns ------- plotly.graph_objs.layout.xaxis.rangeslider.YAxis """ return self["yaxis"] @yaxis.setter def yaxis(self, val): self["yaxis"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.xaxis" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autorange Determines whether or not the range slider range is computed in relation to the input data. If `range` is provided, then `autorange` is set to False. bgcolor Sets the background color of the range slider. bordercolor Sets the border color of the range slider. borderwidth Sets the border width of the range slider. range Sets the range of the range slider. If not set, defaults to the full xaxis range. If the axis `type` is "log", then you must take the log of your desired range. If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. thickness The height of the range slider as a fraction of the total plot area height. visible Determines whether or not the range slider will be visible. If visible, perpendicular axes will be set to `fixedrange` yaxis plotly.graph_objects.layout.xaxis.rangeslider.YAxis instance or dict with compatible properties """ def __init__( self, arg=None, autorange=None, bgcolor=None, bordercolor=None, borderwidth=None, range=None, thickness=None, visible=None, yaxis=None, **kwargs ): """ Construct a new Rangeslider object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.xaxis.Rangeslider autorange Determines whether or not the range slider range is computed in relation to the input data. If `range` is provided, then `autorange` is set to False. bgcolor Sets the background color of the range slider. bordercolor Sets the border color of the range slider. borderwidth Sets the border width of the range slider. range Sets the range of the range slider. If not set, defaults to the full xaxis range. If the axis `type` is "log", then you must take the log of your desired range. If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. thickness The height of the range slider as a fraction of the total plot area height. visible Determines whether or not the range slider will be visible. If visible, perpendicular axes will be set to `fixedrange` yaxis plotly.graph_objects.layout.xaxis.rangeslider.YAxis instance or dict with compatible properties Returns ------- Rangeslider """ super(Rangeslider, self).__init__("rangeslider") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.xaxis.Rangeslider constructor must be a dict or an instance of plotly.graph_objs.layout.xaxis.Rangeslider""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.xaxis import rangeslider as v_rangeslider # Initialize validators # --------------------- self._validators["autorange"] = v_rangeslider.AutorangeValidator() self._validators["bgcolor"] = v_rangeslider.BgcolorValidator() self._validators["bordercolor"] = v_rangeslider.BordercolorValidator() self._validators["borderwidth"] = v_rangeslider.BorderwidthValidator() self._validators["range"] = v_rangeslider.RangeValidator() self._validators["thickness"] = v_rangeslider.ThicknessValidator() self._validators["visible"] = v_rangeslider.VisibleValidator() self._validators["yaxis"] = v_rangeslider.YAxisValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autorange", None) self["autorange"] = autorange if autorange is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("borderwidth", None) self["borderwidth"] = borderwidth if borderwidth is not None else _v _v = arg.pop("range", None) self["range"] = range if range is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("yaxis", None) self["yaxis"] = yaxis if yaxis is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Rangeselector(_BaseLayoutHierarchyType): # activecolor # ----------- @property def activecolor(self): """ Sets the background color of the active range selector button. The 'activecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["activecolor"] @activecolor.setter def activecolor(self, val): self["activecolor"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the range selector buttons. The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the color of the border enclosing the range selector. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # borderwidth # ----------- @property def borderwidth(self): """ Sets the width (in px) of the border enclosing the range selector. The 'borderwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["borderwidth"] @borderwidth.setter def borderwidth(self, val): self["borderwidth"] = val # buttons # ------- @property def buttons(self): """ Sets the specifications for each buttons. By default, a range selector comes with no buttons. The 'buttons' property is a tuple of instances of Button that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.xaxis.rangeselector.Button - A list or tuple of dicts of string/value properties that will be passed to the Button constructor Supported dict properties: count Sets the number of steps to take to update the range. Use with `step` to specify the update interval. label Sets the text label to appear on the button. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. step The unit of measurement that the `count` value will set the range by. stepmode Sets the range update mode. If "backward", the range update shifts the start of range back "count" times "step" milliseconds. If "todate", the range update shifts the start of range back to the first timestamp from "count" times "step" milliseconds back. For example, with `step` set to "year" and `count` set to 1 the range update shifts the start of the range back to January 01 of the current year. Month and year "todate" are currently available only for the built-in (Gregorian) calendar. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. visible Determines whether or not this button is visible. Returns ------- tuple[plotly.graph_objs.layout.xaxis.rangeselector.Button] """ return self["buttons"] @buttons.setter def buttons(self, val): self["buttons"] = val # buttondefaults # -------------- @property def buttondefaults(self): """ When used in a template (as layout.template.layout.xaxis.rangeselector.buttondefaults), sets the default property values to use for elements of layout.xaxis.rangeselector.buttons The 'buttondefaults' property is an instance of Button that may be specified as: - An instance of plotly.graph_objs.layout.xaxis.rangeselector.Button - A dict of string/value properties that will be passed to the Button constructor Supported dict properties: Returns ------- plotly.graph_objs.layout.xaxis.rangeselector.Button """ return self["buttondefaults"] @buttondefaults.setter def buttondefaults(self, val): self["buttondefaults"] = val # font # ---- @property def font(self): """ Sets the font of the range selector button text. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.layout.xaxis.rangeselector.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.layout.xaxis.rangeselector.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # visible # ------- @property def visible(self): """ Determines whether or not this range selector is visible. Note that range selectors are only available for x axes of `type` set to or auto-typed to "date". The 'visible' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # x # - @property def x(self): """ Sets the x position (in normalized coordinates) of the range selector. The 'x' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["x"] @x.setter def x(self, val): self["x"] = val # xanchor # ------- @property def xanchor(self): """ Sets the range selector's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the range selector. The 'xanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'left', 'center', 'right'] Returns ------- Any """ return self["xanchor"] @xanchor.setter def xanchor(self, val): self["xanchor"] = val # y # - @property def y(self): """ Sets the y position (in normalized coordinates) of the range selector. The 'y' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["y"] @y.setter def y(self, val): self["y"] = val # yanchor # ------- @property def yanchor(self): """ Sets the range selector's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the range selector. The 'yanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'top', 'middle', 'bottom'] Returns ------- Any """ return self["yanchor"] @yanchor.setter def yanchor(self, val): self["yanchor"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.xaxis" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ activecolor Sets the background color of the active range selector button. bgcolor Sets the background color of the range selector buttons. bordercolor Sets the color of the border enclosing the range selector. borderwidth Sets the width (in px) of the border enclosing the range selector. buttons Sets the specifications for each buttons. By default, a range selector comes with no buttons. buttondefaults When used in a template (as layout.template.layout.xaxi s.rangeselector.buttondefaults), sets the default property values to use for elements of layout.xaxis.rangeselector.buttons font Sets the font of the range selector button text. visible Determines whether or not this range selector is visible. Note that range selectors are only available for x axes of `type` set to or auto-typed to "date". x Sets the x position (in normalized coordinates) of the range selector. xanchor Sets the range selector's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the range selector. y Sets the y position (in normalized coordinates) of the range selector. yanchor Sets the range selector's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the range selector. """ def __init__( self, arg=None, activecolor=None, bgcolor=None, bordercolor=None, borderwidth=None, buttons=None, buttondefaults=None, font=None, visible=None, x=None, xanchor=None, y=None, yanchor=None, **kwargs ): """ Construct a new Rangeselector object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.xaxis.Rangeselector activecolor Sets the background color of the active range selector button. bgcolor Sets the background color of the range selector buttons. bordercolor Sets the color of the border enclosing the range selector. borderwidth Sets the width (in px) of the border enclosing the range selector. buttons Sets the specifications for each buttons. By default, a range selector comes with no buttons. buttondefaults When used in a template (as layout.template.layout.xaxi s.rangeselector.buttondefaults), sets the default property values to use for elements of layout.xaxis.rangeselector.buttons font Sets the font of the range selector button text. visible Determines whether or not this range selector is visible. Note that range selectors are only available for x axes of `type` set to or auto-typed to "date". x Sets the x position (in normalized coordinates) of the range selector. xanchor Sets the range selector's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the range selector. y Sets the y position (in normalized coordinates) of the range selector. yanchor Sets the range selector's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the range selector. Returns ------- Rangeselector """ super(Rangeselector, self).__init__("rangeselector") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.xaxis.Rangeselector constructor must be a dict or an instance of plotly.graph_objs.layout.xaxis.Rangeselector""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.xaxis import rangeselector as v_rangeselector # Initialize validators # --------------------- self._validators["activecolor"] = v_rangeselector.ActivecolorValidator() self._validators["bgcolor"] = v_rangeselector.BgcolorValidator() self._validators["bordercolor"] = v_rangeselector.BordercolorValidator() self._validators["borderwidth"] = v_rangeselector.BorderwidthValidator() self._validators["buttons"] = v_rangeselector.ButtonsValidator() self._validators["buttondefaults"] = v_rangeselector.ButtonValidator() self._validators["font"] = v_rangeselector.FontValidator() self._validators["visible"] = v_rangeselector.VisibleValidator() self._validators["x"] = v_rangeselector.XValidator() self._validators["xanchor"] = v_rangeselector.XanchorValidator() self._validators["y"] = v_rangeselector.YValidator() self._validators["yanchor"] = v_rangeselector.YanchorValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("activecolor", None) self["activecolor"] = activecolor if activecolor is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("borderwidth", None) self["borderwidth"] = borderwidth if borderwidth is not None else _v _v = arg.pop("buttons", None) self["buttons"] = buttons if buttons is not None else _v _v = arg.pop("buttondefaults", None) self["buttondefaults"] = buttondefaults if buttondefaults is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xanchor", None) self["xanchor"] = xanchor if xanchor is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("yanchor", None) self["yanchor"] = yanchor if yanchor is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = [ "Rangeselector", "Rangeslider", "Tickfont", "Tickformatstop", "Tickformatstop", "Title", "rangeselector", "rangeslider", "title", ] from plotly.graph_objs.layout.xaxis import title from plotly.graph_objs.layout.xaxis import rangeslider from plotly.graph_objs.layout.xaxis import rangeselector plotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/updatemenu/0000755000175000017500000000000013573746613023415 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/updatemenu/__init__.py0000644000175000017500000006534013573721550025527 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Pad(_BaseLayoutHierarchyType): # b # - @property def b(self): """ The amount of padding (in px) along the bottom of the component. The 'b' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["b"] @b.setter def b(self, val): self["b"] = val # l # - @property def l(self): """ The amount of padding (in px) on the left side of the component. The 'l' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["l"] @l.setter def l(self, val): self["l"] = val # r # - @property def r(self): """ The amount of padding (in px) on the right side of the component. The 'r' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["r"] @r.setter def r(self, val): self["r"] = val # t # - @property def t(self): """ The amount of padding (in px) along the top of the component. The 't' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["t"] @t.setter def t(self, val): self["t"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.updatemenu" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ b The amount of padding (in px) along the bottom of the component. l The amount of padding (in px) on the left side of the component. r The amount of padding (in px) on the right side of the component. t The amount of padding (in px) along the top of the component. """ def __init__(self, arg=None, b=None, l=None, r=None, t=None, **kwargs): """ Construct a new Pad object Sets the padding around the buttons or dropdown menu. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.updatemenu.Pad b The amount of padding (in px) along the bottom of the component. l The amount of padding (in px) on the left side of the component. r The amount of padding (in px) on the right side of the component. t The amount of padding (in px) along the top of the component. Returns ------- Pad """ super(Pad, self).__init__("pad") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.updatemenu.Pad constructor must be a dict or an instance of plotly.graph_objs.layout.updatemenu.Pad""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.updatemenu import pad as v_pad # Initialize validators # --------------------- self._validators["b"] = v_pad.BValidator() self._validators["l"] = v_pad.LValidator() self._validators["r"] = v_pad.RValidator() self._validators["t"] = v_pad.TValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("b", None) self["b"] = b if b is not None else _v _v = arg.pop("l", None) self["l"] = l if l is not None else _v _v = arg.pop("r", None) self["r"] = r if r is not None else _v _v = arg.pop("t", None) self["t"] = t if t is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Font(_BaseLayoutHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.updatemenu" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets the font of the update menu button text. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.updatemenu.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.updatemenu.Font constructor must be a dict or an instance of plotly.graph_objs.layout.updatemenu.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.updatemenu import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Button(_BaseLayoutHierarchyType): # args # ---- @property def args(self): """ Sets the arguments values to be passed to the Plotly method set in `method` on click. The 'args' property is an info array that may be specified as: * a list or tuple of up to 3 elements where: (0) The 'args[0]' property accepts values of any type (1) The 'args[1]' property accepts values of any type (2) The 'args[2]' property accepts values of any type Returns ------- list """ return self["args"] @args.setter def args(self, val): self["args"] = val # args2 # ----- @property def args2(self): """ Sets a 2nd set of `args`, these arguments values are passed to the Plotly method set in `method` when clicking this button while in the active state. Use this to create toggle buttons. The 'args2' property is an info array that may be specified as: * a list or tuple of up to 3 elements where: (0) The 'args2[0]' property accepts values of any type (1) The 'args2[1]' property accepts values of any type (2) The 'args2[2]' property accepts values of any type Returns ------- list """ return self["args2"] @args2.setter def args2(self, val): self["args2"] = val # execute # ------- @property def execute(self): """ When true, the API method is executed. When false, all other behaviors are the same and command execution is skipped. This may be useful when hooking into, for example, the `plotly_buttonclicked` method and executing the API command manually without losing the benefit of the updatemenu automatically binding to the state of the plot through the specification of `method` and `args`. The 'execute' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["execute"] @execute.setter def execute(self, val): self["execute"] = val # label # ----- @property def label(self): """ Sets the text label to appear on the button. The 'label' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["label"] @label.setter def label(self, val): self["label"] = val # method # ------ @property def method(self): """ Sets the Plotly method to be called on click. If the `skip` method is used, the API updatemenu will function as normal but will perform no API calls and will not bind automatically to state updates. This may be used to create a component interface and attach to updatemenu events manually via JavaScript. The 'method' property is an enumeration that may be specified as: - One of the following enumeration values: ['restyle', 'relayout', 'animate', 'update', 'skip'] Returns ------- Any """ return self["method"] @method.setter def method(self, val): self["method"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # visible # ------- @property def visible(self): """ Determines whether or not this button is visible. The 'visible' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.updatemenu" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ args Sets the arguments values to be passed to the Plotly method set in `method` on click. args2 Sets a 2nd set of `args`, these arguments values are passed to the Plotly method set in `method` when clicking this button while in the active state. Use this to create toggle buttons. execute When true, the API method is executed. When false, all other behaviors are the same and command execution is skipped. This may be useful when hooking into, for example, the `plotly_buttonclicked` method and executing the API command manually without losing the benefit of the updatemenu automatically binding to the state of the plot through the specification of `method` and `args`. label Sets the text label to appear on the button. method Sets the Plotly method to be called on click. If the `skip` method is used, the API updatemenu will function as normal but will perform no API calls and will not bind automatically to state updates. This may be used to create a component interface and attach to updatemenu events manually via JavaScript. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. visible Determines whether or not this button is visible. """ def __init__( self, arg=None, args=None, args2=None, execute=None, label=None, method=None, name=None, templateitemname=None, visible=None, **kwargs ): """ Construct a new Button object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.updatemenu.Button args Sets the arguments values to be passed to the Plotly method set in `method` on click. args2 Sets a 2nd set of `args`, these arguments values are passed to the Plotly method set in `method` when clicking this button while in the active state. Use this to create toggle buttons. execute When true, the API method is executed. When false, all other behaviors are the same and command execution is skipped. This may be useful when hooking into, for example, the `plotly_buttonclicked` method and executing the API command manually without losing the benefit of the updatemenu automatically binding to the state of the plot through the specification of `method` and `args`. label Sets the text label to appear on the button. method Sets the Plotly method to be called on click. If the `skip` method is used, the API updatemenu will function as normal but will perform no API calls and will not bind automatically to state updates. This may be used to create a component interface and attach to updatemenu events manually via JavaScript. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. visible Determines whether or not this button is visible. Returns ------- Button """ super(Button, self).__init__("buttons") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.updatemenu.Button constructor must be a dict or an instance of plotly.graph_objs.layout.updatemenu.Button""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.updatemenu import button as v_button # Initialize validators # --------------------- self._validators["args"] = v_button.ArgsValidator() self._validators["args2"] = v_button.Args2Validator() self._validators["execute"] = v_button.ExecuteValidator() self._validators["label"] = v_button.LabelValidator() self._validators["method"] = v_button.MethodValidator() self._validators["name"] = v_button.NameValidator() self._validators["templateitemname"] = v_button.TemplateitemnameValidator() self._validators["visible"] = v_button.VisibleValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("args", None) self["args"] = args if args is not None else _v _v = arg.pop("args2", None) self["args2"] = args2 if args2 is not None else _v _v = arg.pop("execute", None) self["execute"] = execute if execute is not None else _v _v = arg.pop("label", None) self["label"] = label if label is not None else _v _v = arg.pop("method", None) self["method"] = method if method is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Button", "Button", "Font", "Pad"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/slider/0000755000175000017500000000000013573746613022530 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/slider/__init__.py0000644000175000017500000011514713573721550024643 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Transition(_BaseLayoutHierarchyType): # duration # -------- @property def duration(self): """ Sets the duration of the slider transition The 'duration' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["duration"] @duration.setter def duration(self, val): self["duration"] = val # easing # ------ @property def easing(self): """ Sets the easing function of the slider transition The 'easing' property is an enumeration that may be specified as: - One of the following enumeration values: ['linear', 'quad', 'cubic', 'sin', 'exp', 'circle', 'elastic', 'back', 'bounce', 'linear-in', 'quad-in', 'cubic-in', 'sin-in', 'exp-in', 'circle-in', 'elastic-in', 'back-in', 'bounce-in', 'linear-out', 'quad-out', 'cubic-out', 'sin-out', 'exp-out', 'circle-out', 'elastic-out', 'back-out', 'bounce-out', 'linear-in-out', 'quad-in-out', 'cubic-in-out', 'sin-in-out', 'exp-in-out', 'circle-in-out', 'elastic-in-out', 'back-in-out', 'bounce-in-out'] Returns ------- Any """ return self["easing"] @easing.setter def easing(self, val): self["easing"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.slider" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ duration Sets the duration of the slider transition easing Sets the easing function of the slider transition """ def __init__(self, arg=None, duration=None, easing=None, **kwargs): """ Construct a new Transition object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.slider.Transition duration Sets the duration of the slider transition easing Sets the easing function of the slider transition Returns ------- Transition """ super(Transition, self).__init__("transition") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.slider.Transition constructor must be a dict or an instance of plotly.graph_objs.layout.slider.Transition""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.slider import transition as v_transition # Initialize validators # --------------------- self._validators["duration"] = v_transition.DurationValidator() self._validators["easing"] = v_transition.EasingValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("duration", None) self["duration"] = duration if duration is not None else _v _v = arg.pop("easing", None) self["easing"] = easing if easing is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Step(_BaseLayoutHierarchyType): # args # ---- @property def args(self): """ Sets the arguments values to be passed to the Plotly method set in `method` on slide. The 'args' property is an info array that may be specified as: * a list or tuple of up to 3 elements where: (0) The 'args[0]' property accepts values of any type (1) The 'args[1]' property accepts values of any type (2) The 'args[2]' property accepts values of any type Returns ------- list """ return self["args"] @args.setter def args(self, val): self["args"] = val # execute # ------- @property def execute(self): """ When true, the API method is executed. When false, all other behaviors are the same and command execution is skipped. This may be useful when hooking into, for example, the `plotly_sliderchange` method and executing the API command manually without losing the benefit of the slider automatically binding to the state of the plot through the specification of `method` and `args`. The 'execute' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["execute"] @execute.setter def execute(self, val): self["execute"] = val # label # ----- @property def label(self): """ Sets the text label to appear on the slider The 'label' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["label"] @label.setter def label(self, val): self["label"] = val # method # ------ @property def method(self): """ Sets the Plotly method to be called when the slider value is changed. If the `skip` method is used, the API slider will function as normal but will perform no API calls and will not bind automatically to state updates. This may be used to create a component interface and attach to slider events manually via JavaScript. The 'method' property is an enumeration that may be specified as: - One of the following enumeration values: ['restyle', 'relayout', 'animate', 'update', 'skip'] Returns ------- Any """ return self["method"] @method.setter def method(self, val): self["method"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # value # ----- @property def value(self): """ Sets the value of the slider step, used to refer to the step programatically. Defaults to the slider label if not provided. The 'value' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["value"] @value.setter def value(self, val): self["value"] = val # visible # ------- @property def visible(self): """ Determines whether or not this step is included in the slider. The 'visible' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.slider" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ args Sets the arguments values to be passed to the Plotly method set in `method` on slide. execute When true, the API method is executed. When false, all other behaviors are the same and command execution is skipped. This may be useful when hooking into, for example, the `plotly_sliderchange` method and executing the API command manually without losing the benefit of the slider automatically binding to the state of the plot through the specification of `method` and `args`. label Sets the text label to appear on the slider method Sets the Plotly method to be called when the slider value is changed. If the `skip` method is used, the API slider will function as normal but will perform no API calls and will not bind automatically to state updates. This may be used to create a component interface and attach to slider events manually via JavaScript. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value Sets the value of the slider step, used to refer to the step programatically. Defaults to the slider label if not provided. visible Determines whether or not this step is included in the slider. """ def __init__( self, arg=None, args=None, execute=None, label=None, method=None, name=None, templateitemname=None, value=None, visible=None, **kwargs ): """ Construct a new Step object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.slider.Step args Sets the arguments values to be passed to the Plotly method set in `method` on slide. execute When true, the API method is executed. When false, all other behaviors are the same and command execution is skipped. This may be useful when hooking into, for example, the `plotly_sliderchange` method and executing the API command manually without losing the benefit of the slider automatically binding to the state of the plot through the specification of `method` and `args`. label Sets the text label to appear on the slider method Sets the Plotly method to be called when the slider value is changed. If the `skip` method is used, the API slider will function as normal but will perform no API calls and will not bind automatically to state updates. This may be used to create a component interface and attach to slider events manually via JavaScript. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value Sets the value of the slider step, used to refer to the step programatically. Defaults to the slider label if not provided. visible Determines whether or not this step is included in the slider. Returns ------- Step """ super(Step, self).__init__("steps") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.slider.Step constructor must be a dict or an instance of plotly.graph_objs.layout.slider.Step""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.slider import step as v_step # Initialize validators # --------------------- self._validators["args"] = v_step.ArgsValidator() self._validators["execute"] = v_step.ExecuteValidator() self._validators["label"] = v_step.LabelValidator() self._validators["method"] = v_step.MethodValidator() self._validators["name"] = v_step.NameValidator() self._validators["templateitemname"] = v_step.TemplateitemnameValidator() self._validators["value"] = v_step.ValueValidator() self._validators["visible"] = v_step.VisibleValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("args", None) self["args"] = args if args is not None else _v _v = arg.pop("execute", None) self["execute"] = execute if execute is not None else _v _v = arg.pop("label", None) self["label"] = label if label is not None else _v _v = arg.pop("method", None) self["method"] = method if method is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("value", None) self["value"] = value if value is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Pad(_BaseLayoutHierarchyType): # b # - @property def b(self): """ The amount of padding (in px) along the bottom of the component. The 'b' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["b"] @b.setter def b(self, val): self["b"] = val # l # - @property def l(self): """ The amount of padding (in px) on the left side of the component. The 'l' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["l"] @l.setter def l(self, val): self["l"] = val # r # - @property def r(self): """ The amount of padding (in px) on the right side of the component. The 'r' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["r"] @r.setter def r(self, val): self["r"] = val # t # - @property def t(self): """ The amount of padding (in px) along the top of the component. The 't' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["t"] @t.setter def t(self, val): self["t"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.slider" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ b The amount of padding (in px) along the bottom of the component. l The amount of padding (in px) on the left side of the component. r The amount of padding (in px) on the right side of the component. t The amount of padding (in px) along the top of the component. """ def __init__(self, arg=None, b=None, l=None, r=None, t=None, **kwargs): """ Construct a new Pad object Set the padding of the slider component along each side. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.slider.Pad b The amount of padding (in px) along the bottom of the component. l The amount of padding (in px) on the left side of the component. r The amount of padding (in px) on the right side of the component. t The amount of padding (in px) along the top of the component. Returns ------- Pad """ super(Pad, self).__init__("pad") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.slider.Pad constructor must be a dict or an instance of plotly.graph_objs.layout.slider.Pad""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.slider import pad as v_pad # Initialize validators # --------------------- self._validators["b"] = v_pad.BValidator() self._validators["l"] = v_pad.LValidator() self._validators["r"] = v_pad.RValidator() self._validators["t"] = v_pad.TValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("b", None) self["b"] = b if b is not None else _v _v = arg.pop("l", None) self["l"] = l if l is not None else _v _v = arg.pop("r", None) self["r"] = r if r is not None else _v _v = arg.pop("t", None) self["t"] = t if t is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Font(_BaseLayoutHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.slider" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets the font of the slider step labels. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.slider.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.slider.Font constructor must be a dict or an instance of plotly.graph_objs.layout.slider.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.slider import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Currentvalue(_BaseLayoutHierarchyType): # font # ---- @property def font(self): """ Sets the font of the current value label text. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.layout.slider.currentvalue.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.layout.slider.currentvalue.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # offset # ------ @property def offset(self): """ The amount of space, in pixels, between the current value label and the slider. The 'offset' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["offset"] @offset.setter def offset(self, val): self["offset"] = val # prefix # ------ @property def prefix(self): """ When currentvalue.visible is true, this sets the prefix of the label. The 'prefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["prefix"] @prefix.setter def prefix(self, val): self["prefix"] = val # suffix # ------ @property def suffix(self): """ When currentvalue.visible is true, this sets the suffix of the label. The 'suffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["suffix"] @suffix.setter def suffix(self, val): self["suffix"] = val # visible # ------- @property def visible(self): """ Shows the currently-selected value above the slider. The 'visible' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # xanchor # ------- @property def xanchor(self): """ The alignment of the value readout relative to the length of the slider. The 'xanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'center', 'right'] Returns ------- Any """ return self["xanchor"] @xanchor.setter def xanchor(self, val): self["xanchor"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.slider" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Sets the font of the current value label text. offset The amount of space, in pixels, between the current value label and the slider. prefix When currentvalue.visible is true, this sets the prefix of the label. suffix When currentvalue.visible is true, this sets the suffix of the label. visible Shows the currently-selected value above the slider. xanchor The alignment of the value readout relative to the length of the slider. """ def __init__( self, arg=None, font=None, offset=None, prefix=None, suffix=None, visible=None, xanchor=None, **kwargs ): """ Construct a new Currentvalue object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.slider.Currentvalue font Sets the font of the current value label text. offset The amount of space, in pixels, between the current value label and the slider. prefix When currentvalue.visible is true, this sets the prefix of the label. suffix When currentvalue.visible is true, this sets the suffix of the label. visible Shows the currently-selected value above the slider. xanchor The alignment of the value readout relative to the length of the slider. Returns ------- Currentvalue """ super(Currentvalue, self).__init__("currentvalue") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.slider.Currentvalue constructor must be a dict or an instance of plotly.graph_objs.layout.slider.Currentvalue""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.slider import currentvalue as v_currentvalue # Initialize validators # --------------------- self._validators["font"] = v_currentvalue.FontValidator() self._validators["offset"] = v_currentvalue.OffsetValidator() self._validators["prefix"] = v_currentvalue.PrefixValidator() self._validators["suffix"] = v_currentvalue.SuffixValidator() self._validators["visible"] = v_currentvalue.VisibleValidator() self._validators["xanchor"] = v_currentvalue.XanchorValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("offset", None) self["offset"] = offset if offset is not None else _v _v = arg.pop("prefix", None) self["prefix"] = prefix if prefix is not None else _v _v = arg.pop("suffix", None) self["suffix"] = suffix if suffix is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("xanchor", None) self["xanchor"] = xanchor if xanchor is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Currentvalue", "Font", "Pad", "Step", "Step", "Transition", "currentvalue"] from plotly.graph_objs.layout.slider import currentvalue plotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/slider/currentvalue/0000755000175000017500000000000013573746613025247 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/slider/currentvalue/__init__.py0000644000175000017500000002043213573721547027360 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Font(_BaseLayoutHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.slider.currentvalue" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets the font of the current value label text. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.slider.currentvalue.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.slider.currentvalue.Font constructor must be a dict or an instance of plotly.graph_objs.layout.slider.currentvalue.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.slider.currentvalue import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/legend/0000755000175000017500000000000013573746613022504 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/legend/__init__.py0000644000175000017500000002031313573721547024613 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Font(_BaseLayoutHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.legend" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets the font used to text the legend items. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.legend.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.legend.Font constructor must be a dict or an instance of plotly.graph_objs.layout.legend.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.legend import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/shape/0000755000175000017500000000000013573746613022346 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/layout/shape/__init__.py0000644000175000017500000001542113573721547024461 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType import copy as _copy class Line(_BaseLayoutHierarchyType): # color # ----- @property def color(self): """ Sets the line color. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # dash # ---- @property def dash(self): """ Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). The 'dash' property is a string and must be specified as: - One of the following strings: ['solid', 'dot', 'dash', 'longdash', 'dashdot', 'longdashdot'] - A number that will be converted to a string Returns ------- str """ return self["dash"] @dash.setter def dash(self, val): self["dash"] = val # width # ----- @property def width(self): """ Sets the line width (in px). The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "layout.shape" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the line color. dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). width Sets the line width (in px). """ def __init__(self, arg=None, color=None, dash=None, width=None, **kwargs): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.layout.shape.Line color Sets the line color. dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). width Sets the line width (in px). Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.layout.shape.Line constructor must be a dict or an instance of plotly.graph_objs.layout.shape.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.layout.shape import line as v_line # Initialize validators # --------------------- self._validators["color"] = v_line.ColorValidator() self._validators["dash"] = v_line.DashValidator() self._validators["width"] = v_line.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("dash", None) self["dash"] = dash if dash is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Line"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/bar/0000755000175000017500000000000013573746613020475 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/bar/unselected/0000755000175000017500000000000013573746613022630 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/bar/unselected/__init__.py0000644000175000017500000002602613573721545024744 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Textfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the text font color of unselected points, applied only when a selection exists. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "bar.unselected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the text font color of unselected points, applied only when a selection exists. """ def __init__(self, arg=None, color=None, **kwargs): """ Construct a new Textfont object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.bar.unselected.Textfont color Sets the text font color of unselected points, applied only when a selection exists. Returns ------- Textfont """ super(Textfont, self).__init__("textfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.bar.unselected.Textfont constructor must be a dict or an instance of plotly.graph_objs.bar.unselected.Textfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.bar.unselected import textfont as v_textfont # Initialize validators # --------------------- self._validators["color"] = v_textfont.ColorValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the marker color of unselected points, applied only when a selection exists. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # opacity # ------- @property def opacity(self): """ Sets the marker opacity of unselected points, applied only when a selection exists. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "bar.unselected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. """ def __init__(self, arg=None, color=None, opacity=None, **kwargs): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.bar.unselected.Marker color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.bar.unselected.Marker constructor must be a dict or an instance of plotly.graph_objs.bar.unselected.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.bar.unselected import marker as v_marker # Initialize validators # --------------------- self._validators["color"] = v_marker.ColorValidator() self._validators["opacity"] = v_marker.OpacityValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Marker", "Textfont"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/bar/hoverlabel/0000755000175000017500000000000013573746613022620 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/bar/hoverlabel/__init__.py0000644000175000017500000002540013573721545024727 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "bar.hoverlabel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Font object Sets the font used in hover labels. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.bar.hoverlabel.Font color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.bar.hoverlabel.Font constructor must be a dict or an instance of plotly.graph_objs.bar.hoverlabel.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.bar.hoverlabel import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["colorsrc"] = v_font.ColorsrcValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["familysrc"] = v_font.FamilysrcValidator() self._validators["size"] = v_font.SizeValidator() self._validators["sizesrc"] = v_font.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/bar/marker/0000755000175000017500000000000013573746613021756 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/bar/marker/colorbar/0000755000175000017500000000000013573746613023561 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/bar/marker/colorbar/title/0000755000175000017500000000000013573746613024702 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/bar/marker/colorbar/title/__init__.py0000644000175000017500000002054413573721545027015 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "bar.marker.colorbar.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.bar.marker.colorbar.title.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.bar.marker.colorbar.title.Font constructor must be a dict or an instance of plotly.graph_objs.bar.marker.colorbar.title.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.bar.marker.colorbar.title import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/bar/marker/colorbar/__init__.py0000644000175000017500000006064413573721545025701 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Title(_BaseTraceHierarchyType): # font # ---- @property def font(self): """ Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.bar.marker.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.bar.marker.colorbar.title.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # side # ---- @property def side(self): """ Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- Any """ return self["side"] @side.setter def side(self, val): self["side"] = val # text # ---- @property def text(self): """ Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "bar.marker.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """ def __init__(self, arg=None, font=None, side=None, text=None, **kwargs): """ Construct a new Title object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.bar.marker.colorbar.Title font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- Title """ super(Title, self).__init__("title") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.bar.marker.colorbar.Title constructor must be a dict or an instance of plotly.graph_objs.bar.marker.colorbar.Title""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.bar.marker.colorbar import title as v_title # Initialize validators # --------------------- self._validators["font"] = v_title.FontValidator() self._validators["side"] = v_title.SideValidator() self._validators["text"] = v_title.TextValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("side", None) self["side"] = side if side is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickformatstop(_BaseTraceHierarchyType): # dtickrange # ---------- @property def dtickrange(self): """ range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" The 'dtickrange' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'dtickrange[0]' property accepts values of any type (1) The 'dtickrange[1]' property accepts values of any type Returns ------- list """ return self["dtickrange"] @dtickrange.setter def dtickrange(self, val): self["dtickrange"] = val # enabled # ------- @property def enabled(self): """ Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. The 'enabled' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["enabled"] @enabled.setter def enabled(self, val): self["enabled"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # value # ----- @property def value(self): """ string - dtickformat for described zoom level, the same as "tickformat" The 'value' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "bar.marker.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """ def __init__( self, arg=None, dtickrange=None, enabled=None, name=None, templateitemname=None, value=None, **kwargs ): """ Construct a new Tickformatstop object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.bar.marker.colorbar.Tickformatstop dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- Tickformatstop """ super(Tickformatstop, self).__init__("tickformatstops") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.bar.marker.colorbar.Tickformatstop constructor must be a dict or an instance of plotly.graph_objs.bar.marker.colorbar.Tickformatstop""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.bar.marker.colorbar import ( tickformatstop as v_tickformatstop, ) # Initialize validators # --------------------- self._validators["dtickrange"] = v_tickformatstop.DtickrangeValidator() self._validators["enabled"] = v_tickformatstop.EnabledValidator() self._validators["name"] = v_tickformatstop.NameValidator() self._validators[ "templateitemname" ] = v_tickformatstop.TemplateitemnameValidator() self._validators["value"] = v_tickformatstop.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtickrange", None) self["dtickrange"] = dtickrange if dtickrange is not None else _v _v = arg.pop("enabled", None) self["enabled"] = enabled if enabled is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "bar.marker.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Tickfont object Sets the color bar's tick label font Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.bar.marker.colorbar.Tickfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Tickfont """ super(Tickfont, self).__init__("tickfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.bar.marker.colorbar.Tickfont constructor must be a dict or an instance of plotly.graph_objs.bar.marker.colorbar.Tickfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.bar.marker.colorbar import tickfont as v_tickfont # Initialize validators # --------------------- self._validators["color"] = v_tickfont.ColorValidator() self._validators["family"] = v_tickfont.FamilyValidator() self._validators["size"] = v_tickfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Tickfont", "Tickformatstop", "Tickformatstop", "Title", "title"] from plotly.graph_objs.bar.marker.colorbar import title plotly-4.4.1+dfsg.orig/plotly/graph_objs/bar/marker/__init__.py0000644000175000017500000027011413573721546024072 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # autocolorscale # -------------- @property def autocolorscale(self): """ Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. The 'autocolorscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocolorscale"] @autocolorscale.setter def autocolorscale(self, val): self["autocolorscale"] = val # cauto # ----- @property def cauto(self): """ Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. The 'cauto' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["cauto"] @cauto.setter def cauto(self, val): self["cauto"] = val # cmax # ---- @property def cmax(self): """ Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. The 'cmax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmax"] @cmax.setter def cmax(self, val): self["cmax"] = val # cmid # ---- @property def cmid(self): """ Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. The 'cmid' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmid"] @cmid.setter def cmid(self, val): self["cmid"] = val # cmin # ---- @property def cmin(self): """ Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. The 'cmin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmin"] @cmin.setter def cmin(self, val): self["cmin"] = val # color # ----- @property def color(self): """ Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A number that will be interpreted as a color according to bar.marker.line.colorscale - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # coloraxis # --------- @property def coloraxis(self): """ Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. The 'coloraxis' property is an identifier of a particular subplot, of type 'coloraxis', that may be specified as the string 'coloraxis' optionally followed by an integer >= 1 (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) Returns ------- str """ return self["coloraxis"] @coloraxis.setter def coloraxis(self, val): self["coloraxis"] = val # colorscale # ---------- @property def colorscale(self): """ Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,Earth,Electric,Vi ridis,Cividis. The 'colorscale' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # reversescale # ------------ @property def reversescale(self): """ Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. The 'reversescale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["reversescale"] @reversescale.setter def reversescale(self, val): self["reversescale"] = val # width # ----- @property def width(self): """ Sets the width (in px) of the lines bounding the marker points. The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["width"] @width.setter def width(self, val): self["width"] = val # widthsrc # -------- @property def widthsrc(self): """ Sets the source reference on plot.ly for width . The 'widthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["widthsrc"] @widthsrc.setter def widthsrc(self, val): self["widthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "bar.marker" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . """ def __init__( self, arg=None, autocolorscale=None, cauto=None, cmax=None, cmid=None, cmin=None, color=None, coloraxis=None, colorscale=None, colorsrc=None, reversescale=None, width=None, widthsrc=None, **kwargs ): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.bar.marker.Line autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.bar.marker.Line constructor must be a dict or an instance of plotly.graph_objs.bar.marker.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.bar.marker import line as v_line # Initialize validators # --------------------- self._validators["autocolorscale"] = v_line.AutocolorscaleValidator() self._validators["cauto"] = v_line.CautoValidator() self._validators["cmax"] = v_line.CmaxValidator() self._validators["cmid"] = v_line.CmidValidator() self._validators["cmin"] = v_line.CminValidator() self._validators["color"] = v_line.ColorValidator() self._validators["coloraxis"] = v_line.ColoraxisValidator() self._validators["colorscale"] = v_line.ColorscaleValidator() self._validators["colorsrc"] = v_line.ColorsrcValidator() self._validators["reversescale"] = v_line.ReversescaleValidator() self._validators["width"] = v_line.WidthValidator() self._validators["widthsrc"] = v_line.WidthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autocolorscale", None) self["autocolorscale"] = autocolorscale if autocolorscale is not None else _v _v = arg.pop("cauto", None) self["cauto"] = cauto if cauto is not None else _v _v = arg.pop("cmax", None) self["cmax"] = cmax if cmax is not None else _v _v = arg.pop("cmid", None) self["cmid"] = cmid if cmid is not None else _v _v = arg.pop("cmin", None) self["cmin"] = cmin if cmin is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("coloraxis", None) self["coloraxis"] = coloraxis if coloraxis is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("reversescale", None) self["reversescale"] = reversescale if reversescale is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v _v = arg.pop("widthsrc", None) self["widthsrc"] = widthsrc if widthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class ColorBar(_BaseTraceHierarchyType): # bgcolor # ------- @property def bgcolor(self): """ Sets the color of padded area. The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the axis line color. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # borderwidth # ----------- @property def borderwidth(self): """ Sets the width (in px) or the border enclosing this color bar. The 'borderwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["borderwidth"] @borderwidth.setter def borderwidth(self, val): self["borderwidth"] = val # dtick # ----- @property def dtick(self): """ Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" The 'dtick' property accepts values of any type Returns ------- Any """ return self["dtick"] @dtick.setter def dtick(self, val): self["dtick"] = val # exponentformat # -------------- @property def exponentformat(self): """ Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. The 'exponentformat' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'e', 'E', 'power', 'SI', 'B'] Returns ------- Any """ return self["exponentformat"] @exponentformat.setter def exponentformat(self, val): self["exponentformat"] = val # len # --- @property def len(self): """ Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. The 'len' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["len"] @len.setter def len(self, val): self["len"] = val # lenmode # ------- @property def lenmode(self): """ Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. The 'lenmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["lenmode"] @lenmode.setter def lenmode(self, val): self["lenmode"] = val # nticks # ------ @property def nticks(self): """ Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". The 'nticks' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nticks"] @nticks.setter def nticks(self, val): self["nticks"] = val # outlinecolor # ------------ @property def outlinecolor(self): """ Sets the axis line color. The 'outlinecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["outlinecolor"] @outlinecolor.setter def outlinecolor(self, val): self["outlinecolor"] = val # outlinewidth # ------------ @property def outlinewidth(self): """ Sets the width (in px) of the axis line. The 'outlinewidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["outlinewidth"] @outlinewidth.setter def outlinewidth(self, val): self["outlinewidth"] = val # separatethousands # ----------------- @property def separatethousands(self): """ If "true", even 4-digit integers are separated The 'separatethousands' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["separatethousands"] @separatethousands.setter def separatethousands(self, val): self["separatethousands"] = val # showexponent # ------------ @property def showexponent(self): """ If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. The 'showexponent' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showexponent"] @showexponent.setter def showexponent(self, val): self["showexponent"] = val # showticklabels # -------------- @property def showticklabels(self): """ Determines whether or not the tick labels are drawn. The 'showticklabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showticklabels"] @showticklabels.setter def showticklabels(self, val): self["showticklabels"] = val # showtickprefix # -------------- @property def showtickprefix(self): """ If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. The 'showtickprefix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showtickprefix"] @showtickprefix.setter def showtickprefix(self, val): self["showtickprefix"] = val # showticksuffix # -------------- @property def showticksuffix(self): """ Same as `showtickprefix` but for tick suffixes. The 'showticksuffix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showticksuffix"] @showticksuffix.setter def showticksuffix(self, val): self["showticksuffix"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # thicknessmode # ------------- @property def thicknessmode(self): """ Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. The 'thicknessmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["thicknessmode"] @thicknessmode.setter def thicknessmode(self, val): self["thicknessmode"] = val # tick0 # ----- @property def tick0(self): """ Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. The 'tick0' property accepts values of any type Returns ------- Any """ return self["tick0"] @tick0.setter def tick0(self, val): self["tick0"] = val # tickangle # --------- @property def tickangle(self): """ Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. The 'tickangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["tickangle"] @tickangle.setter def tickangle(self, val): self["tickangle"] = val # tickcolor # --------- @property def tickcolor(self): """ Sets the tick color. The 'tickcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["tickcolor"] @tickcolor.setter def tickcolor(self, val): self["tickcolor"] = val # tickfont # -------- @property def tickfont(self): """ Sets the color bar's tick label font The 'tickfont' property is an instance of Tickfont that may be specified as: - An instance of plotly.graph_objs.bar.marker.colorbar.Tickfont - A dict of string/value properties that will be passed to the Tickfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.bar.marker.colorbar.Tickfont """ return self["tickfont"] @tickfont.setter def tickfont(self, val): self["tickfont"] = val # tickformat # ---------- @property def tickformat(self): """ Sets the tick label formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'tickformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickformat"] @tickformat.setter def tickformat(self, val): self["tickformat"] = val # tickformatstops # --------------- @property def tickformatstops(self): """ The 'tickformatstops' property is a tuple of instances of Tickformatstop that may be specified as: - A list or tuple of instances of plotly.graph_objs.bar.marker.colorbar.Tickformatstop - A list or tuple of dicts of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- tuple[plotly.graph_objs.bar.marker.colorbar.Tickformatstop] """ return self["tickformatstops"] @tickformatstops.setter def tickformatstops(self, val): self["tickformatstops"] = val # tickformatstopdefaults # ---------------------- @property def tickformatstopdefaults(self): """ When used in a template (as layout.template.data.bar.marker.col orbar.tickformatstopdefaults), sets the default property values to use for elements of bar.marker.colorbar.tickformatstops The 'tickformatstopdefaults' property is an instance of Tickformatstop that may be specified as: - An instance of plotly.graph_objs.bar.marker.colorbar.Tickformatstop - A dict of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: Returns ------- plotly.graph_objs.bar.marker.colorbar.Tickformatstop """ return self["tickformatstopdefaults"] @tickformatstopdefaults.setter def tickformatstopdefaults(self, val): self["tickformatstopdefaults"] = val # ticklen # ------- @property def ticklen(self): """ Sets the tick length (in px). The 'ticklen' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ticklen"] @ticklen.setter def ticklen(self, val): self["ticklen"] = val # tickmode # -------- @property def tickmode(self): """ Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). The 'tickmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'linear', 'array'] Returns ------- Any """ return self["tickmode"] @tickmode.setter def tickmode(self, val): self["tickmode"] = val # tickprefix # ---------- @property def tickprefix(self): """ Sets a tick label prefix. The 'tickprefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickprefix"] @tickprefix.setter def tickprefix(self, val): self["tickprefix"] = val # ticks # ----- @property def ticks(self): """ Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. The 'ticks' property is an enumeration that may be specified as: - One of the following enumeration values: ['outside', 'inside', ''] Returns ------- Any """ return self["ticks"] @ticks.setter def ticks(self, val): self["ticks"] = val # ticksuffix # ---------- @property def ticksuffix(self): """ Sets a tick label suffix. The 'ticksuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ticksuffix"] @ticksuffix.setter def ticksuffix(self, val): self["ticksuffix"] = val # ticktext # -------- @property def ticktext(self): """ Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. The 'ticktext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ticktext"] @ticktext.setter def ticktext(self, val): self["ticktext"] = val # ticktextsrc # ----------- @property def ticktextsrc(self): """ Sets the source reference on plot.ly for ticktext . The 'ticktextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ticktextsrc"] @ticktextsrc.setter def ticktextsrc(self, val): self["ticktextsrc"] = val # tickvals # -------- @property def tickvals(self): """ Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. The 'tickvals' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["tickvals"] @tickvals.setter def tickvals(self, val): self["tickvals"] = val # tickvalssrc # ----------- @property def tickvalssrc(self): """ Sets the source reference on plot.ly for tickvals . The 'tickvalssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tickvalssrc"] @tickvalssrc.setter def tickvalssrc(self, val): self["tickvalssrc"] = val # tickwidth # --------- @property def tickwidth(self): """ Sets the tick width (in px). The 'tickwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["tickwidth"] @tickwidth.setter def tickwidth(self, val): self["tickwidth"] = val # title # ----- @property def title(self): """ The 'title' property is an instance of Title that may be specified as: - An instance of plotly.graph_objs.bar.marker.colorbar.Title - A dict of string/value properties that will be passed to the Title constructor Supported dict properties: font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- plotly.graph_objs.bar.marker.colorbar.Title """ return self["title"] @title.setter def title(self, val): self["title"] = val # titlefont # --------- @property def titlefont(self): """ Deprecated: Please use bar.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.bar.marker.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- """ return self["titlefont"] @titlefont.setter def titlefont(self, val): self["titlefont"] = val # titleside # --------- @property def titleside(self): """ Deprecated: Please use bar.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- """ return self["titleside"] @titleside.setter def titleside(self, val): self["titleside"] = val # x # - @property def x(self): """ Sets the x position of the color bar (in plot fraction). The 'x' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["x"] @x.setter def x(self, val): self["x"] = val # xanchor # ------- @property def xanchor(self): """ Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. The 'xanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'center', 'right'] Returns ------- Any """ return self["xanchor"] @xanchor.setter def xanchor(self, val): self["xanchor"] = val # xpad # ---- @property def xpad(self): """ Sets the amount of padding (in px) along the x direction. The 'xpad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["xpad"] @xpad.setter def xpad(self, val): self["xpad"] = val # y # - @property def y(self): """ Sets the y position of the color bar (in plot fraction). The 'y' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["y"] @y.setter def y(self, val): self["y"] = val # yanchor # ------- @property def yanchor(self): """ Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. The 'yanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['top', 'middle', 'bottom'] Returns ------- Any """ return self["yanchor"] @yanchor.setter def yanchor(self, val): self["yanchor"] = val # ypad # ---- @property def ypad(self): """ Sets the amount of padding (in px) along the y direction. The 'ypad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ypad"] @ypad.setter def ypad(self, val): self["ypad"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "bar.marker" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.bar.marker.colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.bar.ma rker.colorbar.tickformatstopdefaults), sets the default property values to use for elements of bar.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.bar.marker.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use bar.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use bar.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """ _mapped_properties = { "titlefont": ("title", "font"), "titleside": ("title", "side"), } def __init__( self, arg=None, bgcolor=None, bordercolor=None, borderwidth=None, dtick=None, exponentformat=None, len=None, lenmode=None, nticks=None, outlinecolor=None, outlinewidth=None, separatethousands=None, showexponent=None, showticklabels=None, showtickprefix=None, showticksuffix=None, thickness=None, thicknessmode=None, tick0=None, tickangle=None, tickcolor=None, tickfont=None, tickformat=None, tickformatstops=None, tickformatstopdefaults=None, ticklen=None, tickmode=None, tickprefix=None, ticks=None, ticksuffix=None, ticktext=None, ticktextsrc=None, tickvals=None, tickvalssrc=None, tickwidth=None, title=None, titlefont=None, titleside=None, x=None, xanchor=None, xpad=None, y=None, yanchor=None, ypad=None, **kwargs ): """ Construct a new ColorBar object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.bar.marker.ColorBar bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.bar.marker.colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.bar.ma rker.colorbar.tickformatstopdefaults), sets the default property values to use for elements of bar.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.bar.marker.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use bar.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use bar.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- ColorBar """ super(ColorBar, self).__init__("colorbar") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.bar.marker.ColorBar constructor must be a dict or an instance of plotly.graph_objs.bar.marker.ColorBar""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.bar.marker import colorbar as v_colorbar # Initialize validators # --------------------- self._validators["bgcolor"] = v_colorbar.BgcolorValidator() self._validators["bordercolor"] = v_colorbar.BordercolorValidator() self._validators["borderwidth"] = v_colorbar.BorderwidthValidator() self._validators["dtick"] = v_colorbar.DtickValidator() self._validators["exponentformat"] = v_colorbar.ExponentformatValidator() self._validators["len"] = v_colorbar.LenValidator() self._validators["lenmode"] = v_colorbar.LenmodeValidator() self._validators["nticks"] = v_colorbar.NticksValidator() self._validators["outlinecolor"] = v_colorbar.OutlinecolorValidator() self._validators["outlinewidth"] = v_colorbar.OutlinewidthValidator() self._validators["separatethousands"] = v_colorbar.SeparatethousandsValidator() self._validators["showexponent"] = v_colorbar.ShowexponentValidator() self._validators["showticklabels"] = v_colorbar.ShowticklabelsValidator() self._validators["showtickprefix"] = v_colorbar.ShowtickprefixValidator() self._validators["showticksuffix"] = v_colorbar.ShowticksuffixValidator() self._validators["thickness"] = v_colorbar.ThicknessValidator() self._validators["thicknessmode"] = v_colorbar.ThicknessmodeValidator() self._validators["tick0"] = v_colorbar.Tick0Validator() self._validators["tickangle"] = v_colorbar.TickangleValidator() self._validators["tickcolor"] = v_colorbar.TickcolorValidator() self._validators["tickfont"] = v_colorbar.TickfontValidator() self._validators["tickformat"] = v_colorbar.TickformatValidator() self._validators["tickformatstops"] = v_colorbar.TickformatstopsValidator() self._validators[ "tickformatstopdefaults" ] = v_colorbar.TickformatstopValidator() self._validators["ticklen"] = v_colorbar.TicklenValidator() self._validators["tickmode"] = v_colorbar.TickmodeValidator() self._validators["tickprefix"] = v_colorbar.TickprefixValidator() self._validators["ticks"] = v_colorbar.TicksValidator() self._validators["ticksuffix"] = v_colorbar.TicksuffixValidator() self._validators["ticktext"] = v_colorbar.TicktextValidator() self._validators["ticktextsrc"] = v_colorbar.TicktextsrcValidator() self._validators["tickvals"] = v_colorbar.TickvalsValidator() self._validators["tickvalssrc"] = v_colorbar.TickvalssrcValidator() self._validators["tickwidth"] = v_colorbar.TickwidthValidator() self._validators["title"] = v_colorbar.TitleValidator() self._validators["x"] = v_colorbar.XValidator() self._validators["xanchor"] = v_colorbar.XanchorValidator() self._validators["xpad"] = v_colorbar.XpadValidator() self._validators["y"] = v_colorbar.YValidator() self._validators["yanchor"] = v_colorbar.YanchorValidator() self._validators["ypad"] = v_colorbar.YpadValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("borderwidth", None) self["borderwidth"] = borderwidth if borderwidth is not None else _v _v = arg.pop("dtick", None) self["dtick"] = dtick if dtick is not None else _v _v = arg.pop("exponentformat", None) self["exponentformat"] = exponentformat if exponentformat is not None else _v _v = arg.pop("len", None) self["len"] = len if len is not None else _v _v = arg.pop("lenmode", None) self["lenmode"] = lenmode if lenmode is not None else _v _v = arg.pop("nticks", None) self["nticks"] = nticks if nticks is not None else _v _v = arg.pop("outlinecolor", None) self["outlinecolor"] = outlinecolor if outlinecolor is not None else _v _v = arg.pop("outlinewidth", None) self["outlinewidth"] = outlinewidth if outlinewidth is not None else _v _v = arg.pop("separatethousands", None) self["separatethousands"] = ( separatethousands if separatethousands is not None else _v ) _v = arg.pop("showexponent", None) self["showexponent"] = showexponent if showexponent is not None else _v _v = arg.pop("showticklabels", None) self["showticklabels"] = showticklabels if showticklabels is not None else _v _v = arg.pop("showtickprefix", None) self["showtickprefix"] = showtickprefix if showtickprefix is not None else _v _v = arg.pop("showticksuffix", None) self["showticksuffix"] = showticksuffix if showticksuffix is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("thicknessmode", None) self["thicknessmode"] = thicknessmode if thicknessmode is not None else _v _v = arg.pop("tick0", None) self["tick0"] = tick0 if tick0 is not None else _v _v = arg.pop("tickangle", None) self["tickangle"] = tickangle if tickangle is not None else _v _v = arg.pop("tickcolor", None) self["tickcolor"] = tickcolor if tickcolor is not None else _v _v = arg.pop("tickfont", None) self["tickfont"] = tickfont if tickfont is not None else _v _v = arg.pop("tickformat", None) self["tickformat"] = tickformat if tickformat is not None else _v _v = arg.pop("tickformatstops", None) self["tickformatstops"] = tickformatstops if tickformatstops is not None else _v _v = arg.pop("tickformatstopdefaults", None) self["tickformatstopdefaults"] = ( tickformatstopdefaults if tickformatstopdefaults is not None else _v ) _v = arg.pop("ticklen", None) self["ticklen"] = ticklen if ticklen is not None else _v _v = arg.pop("tickmode", None) self["tickmode"] = tickmode if tickmode is not None else _v _v = arg.pop("tickprefix", None) self["tickprefix"] = tickprefix if tickprefix is not None else _v _v = arg.pop("ticks", None) self["ticks"] = ticks if ticks is not None else _v _v = arg.pop("ticksuffix", None) self["ticksuffix"] = ticksuffix if ticksuffix is not None else _v _v = arg.pop("ticktext", None) self["ticktext"] = ticktext if ticktext is not None else _v _v = arg.pop("ticktextsrc", None) self["ticktextsrc"] = ticktextsrc if ticktextsrc is not None else _v _v = arg.pop("tickvals", None) self["tickvals"] = tickvals if tickvals is not None else _v _v = arg.pop("tickvalssrc", None) self["tickvalssrc"] = tickvalssrc if tickvalssrc is not None else _v _v = arg.pop("tickwidth", None) self["tickwidth"] = tickwidth if tickwidth is not None else _v _v = arg.pop("title", None) self["title"] = title if title is not None else _v _v = arg.pop("titlefont", None) _v = titlefont if titlefont is not None else _v if _v is not None: self["titlefont"] = _v _v = arg.pop("titleside", None) _v = titleside if titleside is not None else _v if _v is not None: self["titleside"] = _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xanchor", None) self["xanchor"] = xanchor if xanchor is not None else _v _v = arg.pop("xpad", None) self["xpad"] = xpad if xpad is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("yanchor", None) self["yanchor"] = yanchor if yanchor is not None else _v _v = arg.pop("ypad", None) self["ypad"] = ypad if ypad is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["ColorBar", "Line", "colorbar"] from plotly.graph_objs.bar.marker import colorbar plotly-4.4.1+dfsg.orig/plotly/graph_objs/bar/__init__.py0000644000175000017500000043334313573721547022617 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Unselected(_BaseTraceHierarchyType): # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.bar.unselected.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. Returns ------- plotly.graph_objs.bar.unselected.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # textfont # -------- @property def textfont(self): """ The 'textfont' property is an instance of Textfont that may be specified as: - An instance of plotly.graph_objs.bar.unselected.Textfont - A dict of string/value properties that will be passed to the Textfont constructor Supported dict properties: color Sets the text font color of unselected points, applied only when a selection exists. Returns ------- plotly.graph_objs.bar.unselected.Textfont """ return self["textfont"] @textfont.setter def textfont(self, val): self["textfont"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "bar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ marker plotly.graph_objects.bar.unselected.Marker instance or dict with compatible properties textfont plotly.graph_objects.bar.unselected.Textfont instance or dict with compatible properties """ def __init__(self, arg=None, marker=None, textfont=None, **kwargs): """ Construct a new Unselected object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.bar.Unselected marker plotly.graph_objects.bar.unselected.Marker instance or dict with compatible properties textfont plotly.graph_objects.bar.unselected.Textfont instance or dict with compatible properties Returns ------- Unselected """ super(Unselected, self).__init__("unselected") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.bar.Unselected constructor must be a dict or an instance of plotly.graph_objs.bar.Unselected""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.bar import unselected as v_unselected # Initialize validators # --------------------- self._validators["marker"] = v_unselected.MarkerValidator() self._validators["textfont"] = v_unselected.TextfontValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v _v = arg.pop("textfont", None) self["textfont"] = textfont if textfont is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Textfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "bar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Textfont object Sets the font used for `text`. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.bar.Textfont color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Textfont """ super(Textfont, self).__init__("textfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.bar.Textfont constructor must be a dict or an instance of plotly.graph_objs.bar.Textfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.bar import textfont as v_textfont # Initialize validators # --------------------- self._validators["color"] = v_textfont.ColorValidator() self._validators["colorsrc"] = v_textfont.ColorsrcValidator() self._validators["family"] = v_textfont.FamilyValidator() self._validators["familysrc"] = v_textfont.FamilysrcValidator() self._validators["size"] = v_textfont.SizeValidator() self._validators["sizesrc"] = v_textfont.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Stream(_BaseTraceHierarchyType): # maxpoints # --------- @property def maxpoints(self): """ Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. The 'maxpoints' property is a number and may be specified as: - An int or float in the interval [0, 10000] Returns ------- int|float """ return self["maxpoints"] @maxpoints.setter def maxpoints(self, val): self["maxpoints"] = val # token # ----- @property def token(self): """ The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. The 'token' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["token"] @token.setter def token(self, val): self["token"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "bar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """ def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): """ Construct a new Stream object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.bar.Stream maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- Stream """ super(Stream, self).__init__("stream") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.bar.Stream constructor must be a dict or an instance of plotly.graph_objs.bar.Stream""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.bar import stream as v_stream # Initialize validators # --------------------- self._validators["maxpoints"] = v_stream.MaxpointsValidator() self._validators["token"] = v_stream.TokenValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("maxpoints", None) self["maxpoints"] = maxpoints if maxpoints is not None else _v _v = arg.pop("token", None) self["token"] = token if token is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Selected(_BaseTraceHierarchyType): # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.bar.selected.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. Returns ------- plotly.graph_objs.bar.selected.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # textfont # -------- @property def textfont(self): """ The 'textfont' property is an instance of Textfont that may be specified as: - An instance of plotly.graph_objs.bar.selected.Textfont - A dict of string/value properties that will be passed to the Textfont constructor Supported dict properties: color Sets the text font color of selected points. Returns ------- plotly.graph_objs.bar.selected.Textfont """ return self["textfont"] @textfont.setter def textfont(self, val): self["textfont"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "bar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ marker plotly.graph_objects.bar.selected.Marker instance or dict with compatible properties textfont plotly.graph_objects.bar.selected.Textfont instance or dict with compatible properties """ def __init__(self, arg=None, marker=None, textfont=None, **kwargs): """ Construct a new Selected object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.bar.Selected marker plotly.graph_objects.bar.selected.Marker instance or dict with compatible properties textfont plotly.graph_objects.bar.selected.Textfont instance or dict with compatible properties Returns ------- Selected """ super(Selected, self).__init__("selected") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.bar.Selected constructor must be a dict or an instance of plotly.graph_objs.bar.Selected""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.bar import selected as v_selected # Initialize validators # --------------------- self._validators["marker"] = v_selected.MarkerValidator() self._validators["textfont"] = v_selected.TextfontValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v _v = arg.pop("textfont", None) self["textfont"] = textfont if textfont is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Outsidetextfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "bar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Outsidetextfont object Sets the font used for `text` lying outside the bar. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.bar.Outsidetextfont color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Outsidetextfont """ super(Outsidetextfont, self).__init__("outsidetextfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.bar.Outsidetextfont constructor must be a dict or an instance of plotly.graph_objs.bar.Outsidetextfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.bar import outsidetextfont as v_outsidetextfont # Initialize validators # --------------------- self._validators["color"] = v_outsidetextfont.ColorValidator() self._validators["colorsrc"] = v_outsidetextfont.ColorsrcValidator() self._validators["family"] = v_outsidetextfont.FamilyValidator() self._validators["familysrc"] = v_outsidetextfont.FamilysrcValidator() self._validators["size"] = v_outsidetextfont.SizeValidator() self._validators["sizesrc"] = v_outsidetextfont.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # autocolorscale # -------------- @property def autocolorscale(self): """ Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. The 'autocolorscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocolorscale"] @autocolorscale.setter def autocolorscale(self, val): self["autocolorscale"] = val # cauto # ----- @property def cauto(self): """ Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. The 'cauto' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["cauto"] @cauto.setter def cauto(self, val): self["cauto"] = val # cmax # ---- @property def cmax(self): """ Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. The 'cmax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmax"] @cmax.setter def cmax(self, val): self["cmax"] = val # cmid # ---- @property def cmid(self): """ Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. The 'cmid' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmid"] @cmid.setter def cmid(self, val): self["cmid"] = val # cmin # ---- @property def cmin(self): """ Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. The 'cmin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmin"] @cmin.setter def cmin(self, val): self["cmin"] = val # color # ----- @property def color(self): """ Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A number that will be interpreted as a color according to bar.marker.colorscale - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # coloraxis # --------- @property def coloraxis(self): """ Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. The 'coloraxis' property is an identifier of a particular subplot, of type 'coloraxis', that may be specified as the string 'coloraxis' optionally followed by an integer >= 1 (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) Returns ------- str """ return self["coloraxis"] @coloraxis.setter def coloraxis(self, val): self["coloraxis"] = val # colorbar # -------- @property def colorbar(self): """ The 'colorbar' property is an instance of ColorBar that may be specified as: - An instance of plotly.graph_objs.bar.marker.ColorBar - A dict of string/value properties that will be passed to the ColorBar constructor Supported dict properties: bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.bar.marker.colo rbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.bar.marker.colorbar.tickformatstopdefaults), sets the default property values to use for elements of bar.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.bar.marker.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use bar.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use bar.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- plotly.graph_objs.bar.marker.ColorBar """ return self["colorbar"] @colorbar.setter def colorbar(self, val): self["colorbar"] = val # colorscale # ---------- @property def colorscale(self): """ Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnB u,Greens,YlOrRd,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland ,Jet,Hot,Blackbody,Earth,Electric,Viridis,Cividis. The 'colorscale' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.bar.marker.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,R eds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Black body,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . Returns ------- plotly.graph_objs.bar.marker.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the bars. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # opacitysrc # ---------- @property def opacitysrc(self): """ Sets the source reference on plot.ly for opacity . The 'opacitysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["opacitysrc"] @opacitysrc.setter def opacitysrc(self, val): self["opacitysrc"] = val # reversescale # ------------ @property def reversescale(self): """ Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. The 'reversescale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["reversescale"] @reversescale.setter def reversescale(self, val): self["reversescale"] = val # showscale # --------- @property def showscale(self): """ Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. The 'showscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showscale"] @showscale.setter def showscale(self, val): self["showscale"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "bar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.bar.marker.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu ,Reds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . line plotly.graph_objects.bar.marker.Line instance or dict with compatible properties opacity Sets the opacity of the bars. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. """ def __init__( self, arg=None, autocolorscale=None, cauto=None, cmax=None, cmid=None, cmin=None, color=None, coloraxis=None, colorbar=None, colorscale=None, colorsrc=None, line=None, opacity=None, opacitysrc=None, reversescale=None, showscale=None, **kwargs ): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.bar.Marker autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.bar.marker.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu ,Reds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . line plotly.graph_objects.bar.marker.Line instance or dict with compatible properties opacity Sets the opacity of the bars. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.bar.Marker constructor must be a dict or an instance of plotly.graph_objs.bar.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.bar import marker as v_marker # Initialize validators # --------------------- self._validators["autocolorscale"] = v_marker.AutocolorscaleValidator() self._validators["cauto"] = v_marker.CautoValidator() self._validators["cmax"] = v_marker.CmaxValidator() self._validators["cmid"] = v_marker.CmidValidator() self._validators["cmin"] = v_marker.CminValidator() self._validators["color"] = v_marker.ColorValidator() self._validators["coloraxis"] = v_marker.ColoraxisValidator() self._validators["colorbar"] = v_marker.ColorBarValidator() self._validators["colorscale"] = v_marker.ColorscaleValidator() self._validators["colorsrc"] = v_marker.ColorsrcValidator() self._validators["line"] = v_marker.LineValidator() self._validators["opacity"] = v_marker.OpacityValidator() self._validators["opacitysrc"] = v_marker.OpacitysrcValidator() self._validators["reversescale"] = v_marker.ReversescaleValidator() self._validators["showscale"] = v_marker.ShowscaleValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autocolorscale", None) self["autocolorscale"] = autocolorscale if autocolorscale is not None else _v _v = arg.pop("cauto", None) self["cauto"] = cauto if cauto is not None else _v _v = arg.pop("cmax", None) self["cmax"] = cmax if cmax is not None else _v _v = arg.pop("cmid", None) self["cmid"] = cmid if cmid is not None else _v _v = arg.pop("cmin", None) self["cmin"] = cmin if cmin is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("coloraxis", None) self["coloraxis"] = coloraxis if coloraxis is not None else _v _v = arg.pop("colorbar", None) self["colorbar"] = colorbar if colorbar is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("opacitysrc", None) self["opacitysrc"] = opacitysrc if opacitysrc is not None else _v _v = arg.pop("reversescale", None) self["reversescale"] = reversescale if reversescale is not None else _v _v = arg.pop("showscale", None) self["showscale"] = showscale if showscale is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Insidetextfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "bar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Insidetextfont object Sets the font used for `text` lying inside the bar. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.bar.Insidetextfont color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Insidetextfont """ super(Insidetextfont, self).__init__("insidetextfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.bar.Insidetextfont constructor must be a dict or an instance of plotly.graph_objs.bar.Insidetextfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.bar import insidetextfont as v_insidetextfont # Initialize validators # --------------------- self._validators["color"] = v_insidetextfont.ColorValidator() self._validators["colorsrc"] = v_insidetextfont.ColorsrcValidator() self._validators["family"] = v_insidetextfont.FamilyValidator() self._validators["familysrc"] = v_insidetextfont.FamilysrcValidator() self._validators["size"] = v_insidetextfont.SizeValidator() self._validators["sizesrc"] = v_insidetextfont.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Hoverlabel(_BaseTraceHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'right', 'auto'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["align"] @align.setter def align(self, val): self["align"] = val # alignsrc # -------- @property def alignsrc(self): """ Sets the source reference on plot.ly for align . The 'alignsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["alignsrc"] @alignsrc.setter def alignsrc(self, val): self["alignsrc"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the hover labels for this trace The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bgcolorsrc # ---------- @property def bgcolorsrc(self): """ Sets the source reference on plot.ly for bgcolor . The 'bgcolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bgcolorsrc"] @bgcolorsrc.setter def bgcolorsrc(self, val): self["bgcolorsrc"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the border color of the hover labels for this trace. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # bordercolorsrc # -------------- @property def bordercolorsrc(self): """ Sets the source reference on plot.ly for bordercolor . The 'bordercolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bordercolorsrc"] @bordercolorsrc.setter def bordercolorsrc(self, val): self["bordercolorsrc"] = val # font # ---- @property def font(self): """ Sets the font used in hover labels. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.bar.hoverlabel.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.bar.hoverlabel.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # namelength # ---------- @property def namelength(self): """ Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. The 'namelength' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [-1, 9223372036854775807] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|numpy.ndarray """ return self["namelength"] @namelength.setter def namelength(self, val): self["namelength"] = val # namelengthsrc # ------------- @property def namelengthsrc(self): """ Sets the source reference on plot.ly for namelength . The 'namelengthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["namelengthsrc"] @namelengthsrc.setter def namelengthsrc(self, val): self["namelengthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "bar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """ def __init__( self, arg=None, align=None, alignsrc=None, bgcolor=None, bgcolorsrc=None, bordercolor=None, bordercolorsrc=None, font=None, namelength=None, namelengthsrc=None, **kwargs ): """ Construct a new Hoverlabel object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.bar.Hoverlabel align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- Hoverlabel """ super(Hoverlabel, self).__init__("hoverlabel") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.bar.Hoverlabel constructor must be a dict or an instance of plotly.graph_objs.bar.Hoverlabel""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.bar import hoverlabel as v_hoverlabel # Initialize validators # --------------------- self._validators["align"] = v_hoverlabel.AlignValidator() self._validators["alignsrc"] = v_hoverlabel.AlignsrcValidator() self._validators["bgcolor"] = v_hoverlabel.BgcolorValidator() self._validators["bgcolorsrc"] = v_hoverlabel.BgcolorsrcValidator() self._validators["bordercolor"] = v_hoverlabel.BordercolorValidator() self._validators["bordercolorsrc"] = v_hoverlabel.BordercolorsrcValidator() self._validators["font"] = v_hoverlabel.FontValidator() self._validators["namelength"] = v_hoverlabel.NamelengthValidator() self._validators["namelengthsrc"] = v_hoverlabel.NamelengthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("alignsrc", None) self["alignsrc"] = alignsrc if alignsrc is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bgcolorsrc", None) self["bgcolorsrc"] = bgcolorsrc if bgcolorsrc is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("bordercolorsrc", None) self["bordercolorsrc"] = bordercolorsrc if bordercolorsrc is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("namelength", None) self["namelength"] = namelength if namelength is not None else _v _v = arg.pop("namelengthsrc", None) self["namelengthsrc"] = namelengthsrc if namelengthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class ErrorY(_BaseTraceHierarchyType): # array # ----- @property def array(self): """ Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. The 'array' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["array"] @array.setter def array(self, val): self["array"] = val # arrayminus # ---------- @property def arrayminus(self): """ Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. The 'arrayminus' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["arrayminus"] @arrayminus.setter def arrayminus(self, val): self["arrayminus"] = val # arrayminussrc # ------------- @property def arrayminussrc(self): """ Sets the source reference on plot.ly for arrayminus . The 'arrayminussrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["arrayminussrc"] @arrayminussrc.setter def arrayminussrc(self, val): self["arrayminussrc"] = val # arraysrc # -------- @property def arraysrc(self): """ Sets the source reference on plot.ly for array . The 'arraysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["arraysrc"] @arraysrc.setter def arraysrc(self, val): self["arraysrc"] = val # color # ----- @property def color(self): """ Sets the stoke color of the error bars. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # symmetric # --------- @property def symmetric(self): """ Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. The 'symmetric' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["symmetric"] @symmetric.setter def symmetric(self, val): self["symmetric"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness (in px) of the error bars. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # traceref # -------- @property def traceref(self): """ The 'traceref' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["traceref"] @traceref.setter def traceref(self, val): self["traceref"] = val # tracerefminus # ------------- @property def tracerefminus(self): """ The 'tracerefminus' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["tracerefminus"] @tracerefminus.setter def tracerefminus(self, val): self["tracerefminus"] = val # type # ---- @property def type(self): """ Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. The 'type' property is an enumeration that may be specified as: - One of the following enumeration values: ['percent', 'constant', 'sqrt', 'data'] Returns ------- Any """ return self["type"] @type.setter def type(self, val): self["type"] = val # value # ----- @property def value(self): """ Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. The 'value' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["value"] @value.setter def value(self, val): self["value"] = val # valueminus # ---------- @property def valueminus(self): """ Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars The 'valueminus' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["valueminus"] @valueminus.setter def valueminus(self, val): self["valueminus"] = val # visible # ------- @property def visible(self): """ Determines whether or not this set of error bars is visible. The 'visible' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # width # ----- @property def width(self): """ Sets the width (in px) of the cross-bar at both ends of the error bars. The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "bar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ array Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. arrayminus Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. arrayminussrc Sets the source reference on plot.ly for arrayminus . arraysrc Sets the source reference on plot.ly for array . color Sets the stoke color of the error bars. symmetric Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. thickness Sets the thickness (in px) of the error bars. traceref tracerefminus type Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. value Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. valueminus Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars visible Determines whether or not this set of error bars is visible. width Sets the width (in px) of the cross-bar at both ends of the error bars. """ def __init__( self, arg=None, array=None, arrayminus=None, arrayminussrc=None, arraysrc=None, color=None, symmetric=None, thickness=None, traceref=None, tracerefminus=None, type=None, value=None, valueminus=None, visible=None, width=None, **kwargs ): """ Construct a new ErrorY object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.bar.ErrorY array Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. arrayminus Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. arrayminussrc Sets the source reference on plot.ly for arrayminus . arraysrc Sets the source reference on plot.ly for array . color Sets the stoke color of the error bars. symmetric Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. thickness Sets the thickness (in px) of the error bars. traceref tracerefminus type Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. value Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. valueminus Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars visible Determines whether or not this set of error bars is visible. width Sets the width (in px) of the cross-bar at both ends of the error bars. Returns ------- ErrorY """ super(ErrorY, self).__init__("error_y") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.bar.ErrorY constructor must be a dict or an instance of plotly.graph_objs.bar.ErrorY""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.bar import error_y as v_error_y # Initialize validators # --------------------- self._validators["array"] = v_error_y.ArrayValidator() self._validators["arrayminus"] = v_error_y.ArrayminusValidator() self._validators["arrayminussrc"] = v_error_y.ArrayminussrcValidator() self._validators["arraysrc"] = v_error_y.ArraysrcValidator() self._validators["color"] = v_error_y.ColorValidator() self._validators["symmetric"] = v_error_y.SymmetricValidator() self._validators["thickness"] = v_error_y.ThicknessValidator() self._validators["traceref"] = v_error_y.TracerefValidator() self._validators["tracerefminus"] = v_error_y.TracerefminusValidator() self._validators["type"] = v_error_y.TypeValidator() self._validators["value"] = v_error_y.ValueValidator() self._validators["valueminus"] = v_error_y.ValueminusValidator() self._validators["visible"] = v_error_y.VisibleValidator() self._validators["width"] = v_error_y.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("array", None) self["array"] = array if array is not None else _v _v = arg.pop("arrayminus", None) self["arrayminus"] = arrayminus if arrayminus is not None else _v _v = arg.pop("arrayminussrc", None) self["arrayminussrc"] = arrayminussrc if arrayminussrc is not None else _v _v = arg.pop("arraysrc", None) self["arraysrc"] = arraysrc if arraysrc is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("symmetric", None) self["symmetric"] = symmetric if symmetric is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("traceref", None) self["traceref"] = traceref if traceref is not None else _v _v = arg.pop("tracerefminus", None) self["tracerefminus"] = tracerefminus if tracerefminus is not None else _v _v = arg.pop("type", None) self["type"] = type if type is not None else _v _v = arg.pop("value", None) self["value"] = value if value is not None else _v _v = arg.pop("valueminus", None) self["valueminus"] = valueminus if valueminus is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class ErrorX(_BaseTraceHierarchyType): # array # ----- @property def array(self): """ Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. The 'array' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["array"] @array.setter def array(self, val): self["array"] = val # arrayminus # ---------- @property def arrayminus(self): """ Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. The 'arrayminus' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["arrayminus"] @arrayminus.setter def arrayminus(self, val): self["arrayminus"] = val # arrayminussrc # ------------- @property def arrayminussrc(self): """ Sets the source reference on plot.ly for arrayminus . The 'arrayminussrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["arrayminussrc"] @arrayminussrc.setter def arrayminussrc(self, val): self["arrayminussrc"] = val # arraysrc # -------- @property def arraysrc(self): """ Sets the source reference on plot.ly for array . The 'arraysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["arraysrc"] @arraysrc.setter def arraysrc(self, val): self["arraysrc"] = val # color # ----- @property def color(self): """ Sets the stoke color of the error bars. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # copy_ystyle # ----------- @property def copy_ystyle(self): """ The 'copy_ystyle' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["copy_ystyle"] @copy_ystyle.setter def copy_ystyle(self, val): self["copy_ystyle"] = val # symmetric # --------- @property def symmetric(self): """ Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. The 'symmetric' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["symmetric"] @symmetric.setter def symmetric(self, val): self["symmetric"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness (in px) of the error bars. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # traceref # -------- @property def traceref(self): """ The 'traceref' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["traceref"] @traceref.setter def traceref(self, val): self["traceref"] = val # tracerefminus # ------------- @property def tracerefminus(self): """ The 'tracerefminus' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["tracerefminus"] @tracerefminus.setter def tracerefminus(self, val): self["tracerefminus"] = val # type # ---- @property def type(self): """ Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. The 'type' property is an enumeration that may be specified as: - One of the following enumeration values: ['percent', 'constant', 'sqrt', 'data'] Returns ------- Any """ return self["type"] @type.setter def type(self, val): self["type"] = val # value # ----- @property def value(self): """ Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. The 'value' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["value"] @value.setter def value(self, val): self["value"] = val # valueminus # ---------- @property def valueminus(self): """ Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars The 'valueminus' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["valueminus"] @valueminus.setter def valueminus(self, val): self["valueminus"] = val # visible # ------- @property def visible(self): """ Determines whether or not this set of error bars is visible. The 'visible' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # width # ----- @property def width(self): """ Sets the width (in px) of the cross-bar at both ends of the error bars. The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "bar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ array Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. arrayminus Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. arrayminussrc Sets the source reference on plot.ly for arrayminus . arraysrc Sets the source reference on plot.ly for array . color Sets the stoke color of the error bars. copy_ystyle symmetric Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. thickness Sets the thickness (in px) of the error bars. traceref tracerefminus type Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. value Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. valueminus Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars visible Determines whether or not this set of error bars is visible. width Sets the width (in px) of the cross-bar at both ends of the error bars. """ def __init__( self, arg=None, array=None, arrayminus=None, arrayminussrc=None, arraysrc=None, color=None, copy_ystyle=None, symmetric=None, thickness=None, traceref=None, tracerefminus=None, type=None, value=None, valueminus=None, visible=None, width=None, **kwargs ): """ Construct a new ErrorX object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.bar.ErrorX array Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. arrayminus Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. arrayminussrc Sets the source reference on plot.ly for arrayminus . arraysrc Sets the source reference on plot.ly for array . color Sets the stoke color of the error bars. copy_ystyle symmetric Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. thickness Sets the thickness (in px) of the error bars. traceref tracerefminus type Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. value Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. valueminus Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars visible Determines whether or not this set of error bars is visible. width Sets the width (in px) of the cross-bar at both ends of the error bars. Returns ------- ErrorX """ super(ErrorX, self).__init__("error_x") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.bar.ErrorX constructor must be a dict or an instance of plotly.graph_objs.bar.ErrorX""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.bar import error_x as v_error_x # Initialize validators # --------------------- self._validators["array"] = v_error_x.ArrayValidator() self._validators["arrayminus"] = v_error_x.ArrayminusValidator() self._validators["arrayminussrc"] = v_error_x.ArrayminussrcValidator() self._validators["arraysrc"] = v_error_x.ArraysrcValidator() self._validators["color"] = v_error_x.ColorValidator() self._validators["copy_ystyle"] = v_error_x.CopyYstyleValidator() self._validators["symmetric"] = v_error_x.SymmetricValidator() self._validators["thickness"] = v_error_x.ThicknessValidator() self._validators["traceref"] = v_error_x.TracerefValidator() self._validators["tracerefminus"] = v_error_x.TracerefminusValidator() self._validators["type"] = v_error_x.TypeValidator() self._validators["value"] = v_error_x.ValueValidator() self._validators["valueminus"] = v_error_x.ValueminusValidator() self._validators["visible"] = v_error_x.VisibleValidator() self._validators["width"] = v_error_x.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("array", None) self["array"] = array if array is not None else _v _v = arg.pop("arrayminus", None) self["arrayminus"] = arrayminus if arrayminus is not None else _v _v = arg.pop("arrayminussrc", None) self["arrayminussrc"] = arrayminussrc if arrayminussrc is not None else _v _v = arg.pop("arraysrc", None) self["arraysrc"] = arraysrc if arraysrc is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("copy_ystyle", None) self["copy_ystyle"] = copy_ystyle if copy_ystyle is not None else _v _v = arg.pop("symmetric", None) self["symmetric"] = symmetric if symmetric is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("traceref", None) self["traceref"] = traceref if traceref is not None else _v _v = arg.pop("tracerefminus", None) self["tracerefminus"] = tracerefminus if tracerefminus is not None else _v _v = arg.pop("type", None) self["type"] = type if type is not None else _v _v = arg.pop("value", None) self["value"] = value if value is not None else _v _v = arg.pop("valueminus", None) self["valueminus"] = valueminus if valueminus is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = [ "ErrorX", "ErrorY", "Hoverlabel", "Insidetextfont", "Marker", "Outsidetextfont", "Selected", "Stream", "Textfont", "Unselected", "hoverlabel", "marker", "selected", "unselected", ] from plotly.graph_objs.bar import unselected from plotly.graph_objs.bar import selected from plotly.graph_objs.bar import marker from plotly.graph_objs.bar import hoverlabel plotly-4.4.1+dfsg.orig/plotly/graph_objs/bar/selected/0000755000175000017500000000000013573746613022265 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/bar/selected/__init__.py0000644000175000017500000002505613573721545024403 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Textfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the text font color of selected points. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "bar.selected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the text font color of selected points. """ def __init__(self, arg=None, color=None, **kwargs): """ Construct a new Textfont object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.bar.selected.Textfont color Sets the text font color of selected points. Returns ------- Textfont """ super(Textfont, self).__init__("textfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.bar.selected.Textfont constructor must be a dict or an instance of plotly.graph_objs.bar.selected.Textfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.bar.selected import textfont as v_textfont # Initialize validators # --------------------- self._validators["color"] = v_textfont.ColorValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the marker color of selected points. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # opacity # ------- @property def opacity(self): """ Sets the marker opacity of selected points. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "bar.selected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. """ def __init__(self, arg=None, color=None, opacity=None, **kwargs): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.bar.selected.Marker color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.bar.selected.Marker constructor must be a dict or an instance of plotly.graph_objs.bar.selected.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.bar.selected import marker as v_marker # Initialize validators # --------------------- self._validators["color"] = v_marker.ColorValidator() self._validators["opacity"] = v_marker.OpacityValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Marker", "Textfont"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/heatmap/0000755000175000017500000000000013573746613021350 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/heatmap/hoverlabel/0000755000175000017500000000000013573746613023473 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/heatmap/hoverlabel/__init__.py0000644000175000017500000002544013573721546025607 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "heatmap.hoverlabel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Font object Sets the font used in hover labels. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.heatmap.hoverlabel.Font color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.heatmap.hoverlabel.Font constructor must be a dict or an instance of plotly.graph_objs.heatmap.hoverlabel.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.heatmap.hoverlabel import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["colorsrc"] = v_font.ColorsrcValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["familysrc"] = v_font.FamilysrcValidator() self._validators["size"] = v_font.SizeValidator() self._validators["sizesrc"] = v_font.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/heatmap/colorbar/0000755000175000017500000000000013573746613023153 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/heatmap/colorbar/title/0000755000175000017500000000000013573746613024274 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/heatmap/colorbar/title/__init__.py0000644000175000017500000002052513573721546026407 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "heatmap.colorbar.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.heatmap.colorbar.title.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.heatmap.colorbar.title.Font constructor must be a dict or an instance of plotly.graph_objs.heatmap.colorbar.title.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.heatmap.colorbar.title import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/heatmap/colorbar/__init__.py0000644000175000017500000006054213573721546025271 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Title(_BaseTraceHierarchyType): # font # ---- @property def font(self): """ Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.heatmap.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.heatmap.colorbar.title.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # side # ---- @property def side(self): """ Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- Any """ return self["side"] @side.setter def side(self, val): self["side"] = val # text # ---- @property def text(self): """ Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "heatmap.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """ def __init__(self, arg=None, font=None, side=None, text=None, **kwargs): """ Construct a new Title object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.heatmap.colorbar.Title font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- Title """ super(Title, self).__init__("title") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.heatmap.colorbar.Title constructor must be a dict or an instance of plotly.graph_objs.heatmap.colorbar.Title""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.heatmap.colorbar import title as v_title # Initialize validators # --------------------- self._validators["font"] = v_title.FontValidator() self._validators["side"] = v_title.SideValidator() self._validators["text"] = v_title.TextValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("side", None) self["side"] = side if side is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickformatstop(_BaseTraceHierarchyType): # dtickrange # ---------- @property def dtickrange(self): """ range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" The 'dtickrange' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'dtickrange[0]' property accepts values of any type (1) The 'dtickrange[1]' property accepts values of any type Returns ------- list """ return self["dtickrange"] @dtickrange.setter def dtickrange(self, val): self["dtickrange"] = val # enabled # ------- @property def enabled(self): """ Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. The 'enabled' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["enabled"] @enabled.setter def enabled(self, val): self["enabled"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # value # ----- @property def value(self): """ string - dtickformat for described zoom level, the same as "tickformat" The 'value' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "heatmap.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """ def __init__( self, arg=None, dtickrange=None, enabled=None, name=None, templateitemname=None, value=None, **kwargs ): """ Construct a new Tickformatstop object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.heatmap.colorbar.Tickformatstop dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- Tickformatstop """ super(Tickformatstop, self).__init__("tickformatstops") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.heatmap.colorbar.Tickformatstop constructor must be a dict or an instance of plotly.graph_objs.heatmap.colorbar.Tickformatstop""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.heatmap.colorbar import ( tickformatstop as v_tickformatstop, ) # Initialize validators # --------------------- self._validators["dtickrange"] = v_tickformatstop.DtickrangeValidator() self._validators["enabled"] = v_tickformatstop.EnabledValidator() self._validators["name"] = v_tickformatstop.NameValidator() self._validators[ "templateitemname" ] = v_tickformatstop.TemplateitemnameValidator() self._validators["value"] = v_tickformatstop.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtickrange", None) self["dtickrange"] = dtickrange if dtickrange is not None else _v _v = arg.pop("enabled", None) self["enabled"] = enabled if enabled is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "heatmap.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Tickfont object Sets the color bar's tick label font Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.heatmap.colorbar.Tickfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Tickfont """ super(Tickfont, self).__init__("tickfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.heatmap.colorbar.Tickfont constructor must be a dict or an instance of plotly.graph_objs.heatmap.colorbar.Tickfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.heatmap.colorbar import tickfont as v_tickfont # Initialize validators # --------------------- self._validators["color"] = v_tickfont.ColorValidator() self._validators["family"] = v_tickfont.FamilyValidator() self._validators["size"] = v_tickfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Tickfont", "Tickformatstop", "Tickformatstop", "Title", "title"] from plotly.graph_objs.heatmap.colorbar import title plotly-4.4.1+dfsg.orig/plotly/graph_objs/heatmap/__init__.py0000644000175000017500000026202513573721547023467 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Stream(_BaseTraceHierarchyType): # maxpoints # --------- @property def maxpoints(self): """ Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. The 'maxpoints' property is a number and may be specified as: - An int or float in the interval [0, 10000] Returns ------- int|float """ return self["maxpoints"] @maxpoints.setter def maxpoints(self, val): self["maxpoints"] = val # token # ----- @property def token(self): """ The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. The 'token' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["token"] @token.setter def token(self, val): self["token"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "heatmap" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """ def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): """ Construct a new Stream object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.heatmap.Stream maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- Stream """ super(Stream, self).__init__("stream") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.heatmap.Stream constructor must be a dict or an instance of plotly.graph_objs.heatmap.Stream""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.heatmap import stream as v_stream # Initialize validators # --------------------- self._validators["maxpoints"] = v_stream.MaxpointsValidator() self._validators["token"] = v_stream.TokenValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("maxpoints", None) self["maxpoints"] = maxpoints if maxpoints is not None else _v _v = arg.pop("token", None) self["token"] = token if token is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Hoverlabel(_BaseTraceHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'right', 'auto'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["align"] @align.setter def align(self, val): self["align"] = val # alignsrc # -------- @property def alignsrc(self): """ Sets the source reference on plot.ly for align . The 'alignsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["alignsrc"] @alignsrc.setter def alignsrc(self, val): self["alignsrc"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the hover labels for this trace The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bgcolorsrc # ---------- @property def bgcolorsrc(self): """ Sets the source reference on plot.ly for bgcolor . The 'bgcolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bgcolorsrc"] @bgcolorsrc.setter def bgcolorsrc(self, val): self["bgcolorsrc"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the border color of the hover labels for this trace. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # bordercolorsrc # -------------- @property def bordercolorsrc(self): """ Sets the source reference on plot.ly for bordercolor . The 'bordercolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bordercolorsrc"] @bordercolorsrc.setter def bordercolorsrc(self, val): self["bordercolorsrc"] = val # font # ---- @property def font(self): """ Sets the font used in hover labels. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.heatmap.hoverlabel.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.heatmap.hoverlabel.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # namelength # ---------- @property def namelength(self): """ Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. The 'namelength' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [-1, 9223372036854775807] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|numpy.ndarray """ return self["namelength"] @namelength.setter def namelength(self, val): self["namelength"] = val # namelengthsrc # ------------- @property def namelengthsrc(self): """ Sets the source reference on plot.ly for namelength . The 'namelengthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["namelengthsrc"] @namelengthsrc.setter def namelengthsrc(self, val): self["namelengthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "heatmap" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """ def __init__( self, arg=None, align=None, alignsrc=None, bgcolor=None, bgcolorsrc=None, bordercolor=None, bordercolorsrc=None, font=None, namelength=None, namelengthsrc=None, **kwargs ): """ Construct a new Hoverlabel object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.heatmap.Hoverlabel align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- Hoverlabel """ super(Hoverlabel, self).__init__("hoverlabel") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.heatmap.Hoverlabel constructor must be a dict or an instance of plotly.graph_objs.heatmap.Hoverlabel""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.heatmap import hoverlabel as v_hoverlabel # Initialize validators # --------------------- self._validators["align"] = v_hoverlabel.AlignValidator() self._validators["alignsrc"] = v_hoverlabel.AlignsrcValidator() self._validators["bgcolor"] = v_hoverlabel.BgcolorValidator() self._validators["bgcolorsrc"] = v_hoverlabel.BgcolorsrcValidator() self._validators["bordercolor"] = v_hoverlabel.BordercolorValidator() self._validators["bordercolorsrc"] = v_hoverlabel.BordercolorsrcValidator() self._validators["font"] = v_hoverlabel.FontValidator() self._validators["namelength"] = v_hoverlabel.NamelengthValidator() self._validators["namelengthsrc"] = v_hoverlabel.NamelengthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("alignsrc", None) self["alignsrc"] = alignsrc if alignsrc is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bgcolorsrc", None) self["bgcolorsrc"] = bgcolorsrc if bgcolorsrc is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("bordercolorsrc", None) self["bordercolorsrc"] = bordercolorsrc if bordercolorsrc is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("namelength", None) self["namelength"] = namelength if namelength is not None else _v _v = arg.pop("namelengthsrc", None) self["namelengthsrc"] = namelengthsrc if namelengthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class ColorBar(_BaseTraceHierarchyType): # bgcolor # ------- @property def bgcolor(self): """ Sets the color of padded area. The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the axis line color. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # borderwidth # ----------- @property def borderwidth(self): """ Sets the width (in px) or the border enclosing this color bar. The 'borderwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["borderwidth"] @borderwidth.setter def borderwidth(self, val): self["borderwidth"] = val # dtick # ----- @property def dtick(self): """ Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" The 'dtick' property accepts values of any type Returns ------- Any """ return self["dtick"] @dtick.setter def dtick(self, val): self["dtick"] = val # exponentformat # -------------- @property def exponentformat(self): """ Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. The 'exponentformat' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'e', 'E', 'power', 'SI', 'B'] Returns ------- Any """ return self["exponentformat"] @exponentformat.setter def exponentformat(self, val): self["exponentformat"] = val # len # --- @property def len(self): """ Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. The 'len' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["len"] @len.setter def len(self, val): self["len"] = val # lenmode # ------- @property def lenmode(self): """ Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. The 'lenmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["lenmode"] @lenmode.setter def lenmode(self, val): self["lenmode"] = val # nticks # ------ @property def nticks(self): """ Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". The 'nticks' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nticks"] @nticks.setter def nticks(self, val): self["nticks"] = val # outlinecolor # ------------ @property def outlinecolor(self): """ Sets the axis line color. The 'outlinecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["outlinecolor"] @outlinecolor.setter def outlinecolor(self, val): self["outlinecolor"] = val # outlinewidth # ------------ @property def outlinewidth(self): """ Sets the width (in px) of the axis line. The 'outlinewidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["outlinewidth"] @outlinewidth.setter def outlinewidth(self, val): self["outlinewidth"] = val # separatethousands # ----------------- @property def separatethousands(self): """ If "true", even 4-digit integers are separated The 'separatethousands' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["separatethousands"] @separatethousands.setter def separatethousands(self, val): self["separatethousands"] = val # showexponent # ------------ @property def showexponent(self): """ If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. The 'showexponent' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showexponent"] @showexponent.setter def showexponent(self, val): self["showexponent"] = val # showticklabels # -------------- @property def showticklabels(self): """ Determines whether or not the tick labels are drawn. The 'showticklabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showticklabels"] @showticklabels.setter def showticklabels(self, val): self["showticklabels"] = val # showtickprefix # -------------- @property def showtickprefix(self): """ If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. The 'showtickprefix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showtickprefix"] @showtickprefix.setter def showtickprefix(self, val): self["showtickprefix"] = val # showticksuffix # -------------- @property def showticksuffix(self): """ Same as `showtickprefix` but for tick suffixes. The 'showticksuffix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showticksuffix"] @showticksuffix.setter def showticksuffix(self, val): self["showticksuffix"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # thicknessmode # ------------- @property def thicknessmode(self): """ Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. The 'thicknessmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["thicknessmode"] @thicknessmode.setter def thicknessmode(self, val): self["thicknessmode"] = val # tick0 # ----- @property def tick0(self): """ Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. The 'tick0' property accepts values of any type Returns ------- Any """ return self["tick0"] @tick0.setter def tick0(self, val): self["tick0"] = val # tickangle # --------- @property def tickangle(self): """ Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. The 'tickangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["tickangle"] @tickangle.setter def tickangle(self, val): self["tickangle"] = val # tickcolor # --------- @property def tickcolor(self): """ Sets the tick color. The 'tickcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["tickcolor"] @tickcolor.setter def tickcolor(self, val): self["tickcolor"] = val # tickfont # -------- @property def tickfont(self): """ Sets the color bar's tick label font The 'tickfont' property is an instance of Tickfont that may be specified as: - An instance of plotly.graph_objs.heatmap.colorbar.Tickfont - A dict of string/value properties that will be passed to the Tickfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.heatmap.colorbar.Tickfont """ return self["tickfont"] @tickfont.setter def tickfont(self, val): self["tickfont"] = val # tickformat # ---------- @property def tickformat(self): """ Sets the tick label formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'tickformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickformat"] @tickformat.setter def tickformat(self, val): self["tickformat"] = val # tickformatstops # --------------- @property def tickformatstops(self): """ The 'tickformatstops' property is a tuple of instances of Tickformatstop that may be specified as: - A list or tuple of instances of plotly.graph_objs.heatmap.colorbar.Tickformatstop - A list or tuple of dicts of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- tuple[plotly.graph_objs.heatmap.colorbar.Tickformatstop] """ return self["tickformatstops"] @tickformatstops.setter def tickformatstops(self, val): self["tickformatstops"] = val # tickformatstopdefaults # ---------------------- @property def tickformatstopdefaults(self): """ When used in a template (as layout.template.data.heatmap.colorbar.tickformatstopdefaults), sets the default property values to use for elements of heatmap.colorbar.tickformatstops The 'tickformatstopdefaults' property is an instance of Tickformatstop that may be specified as: - An instance of plotly.graph_objs.heatmap.colorbar.Tickformatstop - A dict of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: Returns ------- plotly.graph_objs.heatmap.colorbar.Tickformatstop """ return self["tickformatstopdefaults"] @tickformatstopdefaults.setter def tickformatstopdefaults(self, val): self["tickformatstopdefaults"] = val # ticklen # ------- @property def ticklen(self): """ Sets the tick length (in px). The 'ticklen' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ticklen"] @ticklen.setter def ticklen(self, val): self["ticklen"] = val # tickmode # -------- @property def tickmode(self): """ Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). The 'tickmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'linear', 'array'] Returns ------- Any """ return self["tickmode"] @tickmode.setter def tickmode(self, val): self["tickmode"] = val # tickprefix # ---------- @property def tickprefix(self): """ Sets a tick label prefix. The 'tickprefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickprefix"] @tickprefix.setter def tickprefix(self, val): self["tickprefix"] = val # ticks # ----- @property def ticks(self): """ Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. The 'ticks' property is an enumeration that may be specified as: - One of the following enumeration values: ['outside', 'inside', ''] Returns ------- Any """ return self["ticks"] @ticks.setter def ticks(self, val): self["ticks"] = val # ticksuffix # ---------- @property def ticksuffix(self): """ Sets a tick label suffix. The 'ticksuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ticksuffix"] @ticksuffix.setter def ticksuffix(self, val): self["ticksuffix"] = val # ticktext # -------- @property def ticktext(self): """ Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. The 'ticktext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ticktext"] @ticktext.setter def ticktext(self, val): self["ticktext"] = val # ticktextsrc # ----------- @property def ticktextsrc(self): """ Sets the source reference on plot.ly for ticktext . The 'ticktextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ticktextsrc"] @ticktextsrc.setter def ticktextsrc(self, val): self["ticktextsrc"] = val # tickvals # -------- @property def tickvals(self): """ Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. The 'tickvals' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["tickvals"] @tickvals.setter def tickvals(self, val): self["tickvals"] = val # tickvalssrc # ----------- @property def tickvalssrc(self): """ Sets the source reference on plot.ly for tickvals . The 'tickvalssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tickvalssrc"] @tickvalssrc.setter def tickvalssrc(self, val): self["tickvalssrc"] = val # tickwidth # --------- @property def tickwidth(self): """ Sets the tick width (in px). The 'tickwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["tickwidth"] @tickwidth.setter def tickwidth(self, val): self["tickwidth"] = val # title # ----- @property def title(self): """ The 'title' property is an instance of Title that may be specified as: - An instance of plotly.graph_objs.heatmap.colorbar.Title - A dict of string/value properties that will be passed to the Title constructor Supported dict properties: font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- plotly.graph_objs.heatmap.colorbar.Title """ return self["title"] @title.setter def title(self, val): self["title"] = val # titlefont # --------- @property def titlefont(self): """ Deprecated: Please use heatmap.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.heatmap.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- """ return self["titlefont"] @titlefont.setter def titlefont(self, val): self["titlefont"] = val # titleside # --------- @property def titleside(self): """ Deprecated: Please use heatmap.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- """ return self["titleside"] @titleside.setter def titleside(self, val): self["titleside"] = val # x # - @property def x(self): """ Sets the x position of the color bar (in plot fraction). The 'x' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["x"] @x.setter def x(self, val): self["x"] = val # xanchor # ------- @property def xanchor(self): """ Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. The 'xanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'center', 'right'] Returns ------- Any """ return self["xanchor"] @xanchor.setter def xanchor(self, val): self["xanchor"] = val # xpad # ---- @property def xpad(self): """ Sets the amount of padding (in px) along the x direction. The 'xpad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["xpad"] @xpad.setter def xpad(self, val): self["xpad"] = val # y # - @property def y(self): """ Sets the y position of the color bar (in plot fraction). The 'y' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["y"] @y.setter def y(self, val): self["y"] = val # yanchor # ------- @property def yanchor(self): """ Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. The 'yanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['top', 'middle', 'bottom'] Returns ------- Any """ return self["yanchor"] @yanchor.setter def yanchor(self, val): self["yanchor"] = val # ypad # ---- @property def ypad(self): """ Sets the amount of padding (in px) along the y direction. The 'ypad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ypad"] @ypad.setter def ypad(self, val): self["ypad"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "heatmap" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.heatmap.colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.heatma p.colorbar.tickformatstopdefaults), sets the default property values to use for elements of heatmap.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.heatmap.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use heatmap.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use heatmap.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """ _mapped_properties = { "titlefont": ("title", "font"), "titleside": ("title", "side"), } def __init__( self, arg=None, bgcolor=None, bordercolor=None, borderwidth=None, dtick=None, exponentformat=None, len=None, lenmode=None, nticks=None, outlinecolor=None, outlinewidth=None, separatethousands=None, showexponent=None, showticklabels=None, showtickprefix=None, showticksuffix=None, thickness=None, thicknessmode=None, tick0=None, tickangle=None, tickcolor=None, tickfont=None, tickformat=None, tickformatstops=None, tickformatstopdefaults=None, ticklen=None, tickmode=None, tickprefix=None, ticks=None, ticksuffix=None, ticktext=None, ticktextsrc=None, tickvals=None, tickvalssrc=None, tickwidth=None, title=None, titlefont=None, titleside=None, x=None, xanchor=None, xpad=None, y=None, yanchor=None, ypad=None, **kwargs ): """ Construct a new ColorBar object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.heatmap.ColorBar bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.heatmap.colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.heatma p.colorbar.tickformatstopdefaults), sets the default property values to use for elements of heatmap.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.heatmap.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use heatmap.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use heatmap.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- ColorBar """ super(ColorBar, self).__init__("colorbar") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.heatmap.ColorBar constructor must be a dict or an instance of plotly.graph_objs.heatmap.ColorBar""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.heatmap import colorbar as v_colorbar # Initialize validators # --------------------- self._validators["bgcolor"] = v_colorbar.BgcolorValidator() self._validators["bordercolor"] = v_colorbar.BordercolorValidator() self._validators["borderwidth"] = v_colorbar.BorderwidthValidator() self._validators["dtick"] = v_colorbar.DtickValidator() self._validators["exponentformat"] = v_colorbar.ExponentformatValidator() self._validators["len"] = v_colorbar.LenValidator() self._validators["lenmode"] = v_colorbar.LenmodeValidator() self._validators["nticks"] = v_colorbar.NticksValidator() self._validators["outlinecolor"] = v_colorbar.OutlinecolorValidator() self._validators["outlinewidth"] = v_colorbar.OutlinewidthValidator() self._validators["separatethousands"] = v_colorbar.SeparatethousandsValidator() self._validators["showexponent"] = v_colorbar.ShowexponentValidator() self._validators["showticklabels"] = v_colorbar.ShowticklabelsValidator() self._validators["showtickprefix"] = v_colorbar.ShowtickprefixValidator() self._validators["showticksuffix"] = v_colorbar.ShowticksuffixValidator() self._validators["thickness"] = v_colorbar.ThicknessValidator() self._validators["thicknessmode"] = v_colorbar.ThicknessmodeValidator() self._validators["tick0"] = v_colorbar.Tick0Validator() self._validators["tickangle"] = v_colorbar.TickangleValidator() self._validators["tickcolor"] = v_colorbar.TickcolorValidator() self._validators["tickfont"] = v_colorbar.TickfontValidator() self._validators["tickformat"] = v_colorbar.TickformatValidator() self._validators["tickformatstops"] = v_colorbar.TickformatstopsValidator() self._validators[ "tickformatstopdefaults" ] = v_colorbar.TickformatstopValidator() self._validators["ticklen"] = v_colorbar.TicklenValidator() self._validators["tickmode"] = v_colorbar.TickmodeValidator() self._validators["tickprefix"] = v_colorbar.TickprefixValidator() self._validators["ticks"] = v_colorbar.TicksValidator() self._validators["ticksuffix"] = v_colorbar.TicksuffixValidator() self._validators["ticktext"] = v_colorbar.TicktextValidator() self._validators["ticktextsrc"] = v_colorbar.TicktextsrcValidator() self._validators["tickvals"] = v_colorbar.TickvalsValidator() self._validators["tickvalssrc"] = v_colorbar.TickvalssrcValidator() self._validators["tickwidth"] = v_colorbar.TickwidthValidator() self._validators["title"] = v_colorbar.TitleValidator() self._validators["x"] = v_colorbar.XValidator() self._validators["xanchor"] = v_colorbar.XanchorValidator() self._validators["xpad"] = v_colorbar.XpadValidator() self._validators["y"] = v_colorbar.YValidator() self._validators["yanchor"] = v_colorbar.YanchorValidator() self._validators["ypad"] = v_colorbar.YpadValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("borderwidth", None) self["borderwidth"] = borderwidth if borderwidth is not None else _v _v = arg.pop("dtick", None) self["dtick"] = dtick if dtick is not None else _v _v = arg.pop("exponentformat", None) self["exponentformat"] = exponentformat if exponentformat is not None else _v _v = arg.pop("len", None) self["len"] = len if len is not None else _v _v = arg.pop("lenmode", None) self["lenmode"] = lenmode if lenmode is not None else _v _v = arg.pop("nticks", None) self["nticks"] = nticks if nticks is not None else _v _v = arg.pop("outlinecolor", None) self["outlinecolor"] = outlinecolor if outlinecolor is not None else _v _v = arg.pop("outlinewidth", None) self["outlinewidth"] = outlinewidth if outlinewidth is not None else _v _v = arg.pop("separatethousands", None) self["separatethousands"] = ( separatethousands if separatethousands is not None else _v ) _v = arg.pop("showexponent", None) self["showexponent"] = showexponent if showexponent is not None else _v _v = arg.pop("showticklabels", None) self["showticklabels"] = showticklabels if showticklabels is not None else _v _v = arg.pop("showtickprefix", None) self["showtickprefix"] = showtickprefix if showtickprefix is not None else _v _v = arg.pop("showticksuffix", None) self["showticksuffix"] = showticksuffix if showticksuffix is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("thicknessmode", None) self["thicknessmode"] = thicknessmode if thicknessmode is not None else _v _v = arg.pop("tick0", None) self["tick0"] = tick0 if tick0 is not None else _v _v = arg.pop("tickangle", None) self["tickangle"] = tickangle if tickangle is not None else _v _v = arg.pop("tickcolor", None) self["tickcolor"] = tickcolor if tickcolor is not None else _v _v = arg.pop("tickfont", None) self["tickfont"] = tickfont if tickfont is not None else _v _v = arg.pop("tickformat", None) self["tickformat"] = tickformat if tickformat is not None else _v _v = arg.pop("tickformatstops", None) self["tickformatstops"] = tickformatstops if tickformatstops is not None else _v _v = arg.pop("tickformatstopdefaults", None) self["tickformatstopdefaults"] = ( tickformatstopdefaults if tickformatstopdefaults is not None else _v ) _v = arg.pop("ticklen", None) self["ticklen"] = ticklen if ticklen is not None else _v _v = arg.pop("tickmode", None) self["tickmode"] = tickmode if tickmode is not None else _v _v = arg.pop("tickprefix", None) self["tickprefix"] = tickprefix if tickprefix is not None else _v _v = arg.pop("ticks", None) self["ticks"] = ticks if ticks is not None else _v _v = arg.pop("ticksuffix", None) self["ticksuffix"] = ticksuffix if ticksuffix is not None else _v _v = arg.pop("ticktext", None) self["ticktext"] = ticktext if ticktext is not None else _v _v = arg.pop("ticktextsrc", None) self["ticktextsrc"] = ticktextsrc if ticktextsrc is not None else _v _v = arg.pop("tickvals", None) self["tickvals"] = tickvals if tickvals is not None else _v _v = arg.pop("tickvalssrc", None) self["tickvalssrc"] = tickvalssrc if tickvalssrc is not None else _v _v = arg.pop("tickwidth", None) self["tickwidth"] = tickwidth if tickwidth is not None else _v _v = arg.pop("title", None) self["title"] = title if title is not None else _v _v = arg.pop("titlefont", None) _v = titlefont if titlefont is not None else _v if _v is not None: self["titlefont"] = _v _v = arg.pop("titleside", None) _v = titleside if titleside is not None else _v if _v is not None: self["titleside"] = _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xanchor", None) self["xanchor"] = xanchor if xanchor is not None else _v _v = arg.pop("xpad", None) self["xpad"] = xpad if xpad is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("yanchor", None) self["yanchor"] = yanchor if yanchor is not None else _v _v = arg.pop("ypad", None) self["ypad"] = ypad if ypad is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["ColorBar", "Hoverlabel", "Stream", "colorbar", "hoverlabel"] from plotly.graph_objs.heatmap import hoverlabel from plotly.graph_objs.heatmap import colorbar plotly-4.4.1+dfsg.orig/plotly/graph_objs/parcoords/0000755000175000017500000000000013573746613021725 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/parcoords/__init__.py0000644000175000017500000026273413573721551024046 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "parcoords" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Tickfont object Sets the font for the `dimension` tick values. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.parcoords.Tickfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Tickfont """ super(Tickfont, self).__init__("tickfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.parcoords.Tickfont constructor must be a dict or an instance of plotly.graph_objs.parcoords.Tickfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.parcoords import tickfont as v_tickfont # Initialize validators # --------------------- self._validators["color"] = v_tickfont.ColorValidator() self._validators["family"] = v_tickfont.FamilyValidator() self._validators["size"] = v_tickfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Stream(_BaseTraceHierarchyType): # maxpoints # --------- @property def maxpoints(self): """ Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. The 'maxpoints' property is a number and may be specified as: - An int or float in the interval [0, 10000] Returns ------- int|float """ return self["maxpoints"] @maxpoints.setter def maxpoints(self, val): self["maxpoints"] = val # token # ----- @property def token(self): """ The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. The 'token' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["token"] @token.setter def token(self, val): self["token"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "parcoords" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """ def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): """ Construct a new Stream object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.parcoords.Stream maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- Stream """ super(Stream, self).__init__("stream") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.parcoords.Stream constructor must be a dict or an instance of plotly.graph_objs.parcoords.Stream""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.parcoords import stream as v_stream # Initialize validators # --------------------- self._validators["maxpoints"] = v_stream.MaxpointsValidator() self._validators["token"] = v_stream.TokenValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("maxpoints", None) self["maxpoints"] = maxpoints if maxpoints is not None else _v _v = arg.pop("token", None) self["token"] = token if token is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Rangefont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "parcoords" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Rangefont object Sets the font for the `dimension` range values. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.parcoords.Rangefont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Rangefont """ super(Rangefont, self).__init__("rangefont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.parcoords.Rangefont constructor must be a dict or an instance of plotly.graph_objs.parcoords.Rangefont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.parcoords import rangefont as v_rangefont # Initialize validators # --------------------- self._validators["color"] = v_rangefont.ColorValidator() self._validators["family"] = v_rangefont.FamilyValidator() self._validators["size"] = v_rangefont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # autocolorscale # -------------- @property def autocolorscale(self): """ Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `line.colorscale`. Has an effect only if in `line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. The 'autocolorscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocolorscale"] @autocolorscale.setter def autocolorscale(self, val): self["autocolorscale"] = val # cauto # ----- @property def cauto(self): """ Determines whether or not the color domain is computed with respect to the input data (here in `line.color`) or the bounds set in `line.cmin` and `line.cmax` Has an effect only if in `line.color`is set to a numerical array. Defaults to `false` when `line.cmin` and `line.cmax` are set by the user. The 'cauto' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["cauto"] @cauto.setter def cauto(self, val): self["cauto"] = val # cmax # ---- @property def cmax(self): """ Sets the upper bound of the color domain. Has an effect only if in `line.color`is set to a numerical array. Value should have the same units as in `line.color` and if set, `line.cmin` must be set as well. The 'cmax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmax"] @cmax.setter def cmax(self, val): self["cmax"] = val # cmid # ---- @property def cmid(self): """ Sets the mid-point of the color domain by scaling `line.cmin` and/or `line.cmax` to be equidistant to this point. Has an effect only if in `line.color`is set to a numerical array. Value should have the same units as in `line.color`. Has no effect when `line.cauto` is `false`. The 'cmid' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmid"] @cmid.setter def cmid(self, val): self["cmid"] = val # cmin # ---- @property def cmin(self): """ Sets the lower bound of the color domain. Has an effect only if in `line.color`is set to a numerical array. Value should have the same units as in `line.color` and if set, `line.cmax` must be set as well. The 'cmin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmin"] @cmin.setter def cmin(self, val): self["cmin"] = val # color # ----- @property def color(self): """ Sets thelinecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `line.cmin` and `line.cmax` if set. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A number that will be interpreted as a color according to parcoords.line.colorscale - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # coloraxis # --------- @property def coloraxis(self): """ Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. The 'coloraxis' property is an identifier of a particular subplot, of type 'coloraxis', that may be specified as the string 'coloraxis' optionally followed by an integer >= 1 (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) Returns ------- str """ return self["coloraxis"] @coloraxis.setter def coloraxis(self, val): self["coloraxis"] = val # colorbar # -------- @property def colorbar(self): """ The 'colorbar' property is an instance of ColorBar that may be specified as: - An instance of plotly.graph_objs.parcoords.line.ColorBar - A dict of string/value properties that will be passed to the ColorBar constructor Supported dict properties: bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.parcoords.line. colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.parcoords.line.colorbar.tickformatstopdefault s), sets the default property values to use for elements of parcoords.line.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.parcoords.line.colorbar.Ti tle instance or dict with compatible properties titlefont Deprecated: Please use parcoords.line.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use parcoords.line.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- plotly.graph_objs.parcoords.line.ColorBar """ return self["colorbar"] @colorbar.setter def colorbar(self, val): self["colorbar"] = val # colorscale # ---------- @property def colorscale(self): """ Sets the colorscale. Has an effect only if in `line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`line.cmin` and `line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Gr eens,YlOrRd,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet ,Hot,Blackbody,Earth,Electric,Viridis,Cividis. The 'colorscale' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # reversescale # ------------ @property def reversescale(self): """ Reverses the color mapping if true. Has an effect only if in `line.color`is set to a numerical array. If true, `line.cmin` will correspond to the last color in the array and `line.cmax` will correspond to the first color. The 'reversescale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["reversescale"] @reversescale.setter def reversescale(self, val): self["reversescale"] = val # showscale # --------- @property def showscale(self): """ Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `line.color`is set to a numerical array. The 'showscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showscale"] @showscale.setter def showscale(self, val): self["showscale"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "parcoords" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `line.colorscale`. Has an effect only if in `line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `line.color`) or the bounds set in `line.cmin` and `line.cmax` Has an effect only if in `line.color`is set to a numerical array. Defaults to `false` when `line.cmin` and `line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `line.color`is set to a numerical array. Value should have the same units as in `line.color` and if set, `line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `line.cmin` and/or `line.cmax` to be equidistant to this point. Has an effect only if in `line.color`is set to a numerical array. Value should have the same units as in `line.color`. Has no effect when `line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `line.color`is set to a numerical array. Value should have the same units as in `line.color` and if set, `line.cmax` must be set as well. color Sets thelinecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `line.cmin` and `line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.parcoords.line.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`line.cmin` and `line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu ,Greens,YlOrRd,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,P ortland,Jet,Hot,Blackbody,Earth,Electric,Viridis,Cividi s. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `line.color`is set to a numerical array. If true, `line.cmin` will correspond to the last color in the array and `line.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `line.color`is set to a numerical array. """ def __init__( self, arg=None, autocolorscale=None, cauto=None, cmax=None, cmid=None, cmin=None, color=None, coloraxis=None, colorbar=None, colorscale=None, colorsrc=None, reversescale=None, showscale=None, **kwargs ): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.parcoords.Line autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `line.colorscale`. Has an effect only if in `line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `line.color`) or the bounds set in `line.cmin` and `line.cmax` Has an effect only if in `line.color`is set to a numerical array. Defaults to `false` when `line.cmin` and `line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `line.color`is set to a numerical array. Value should have the same units as in `line.color` and if set, `line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `line.cmin` and/or `line.cmax` to be equidistant to this point. Has an effect only if in `line.color`is set to a numerical array. Value should have the same units as in `line.color`. Has no effect when `line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `line.color`is set to a numerical array. Value should have the same units as in `line.color` and if set, `line.cmax` must be set as well. color Sets thelinecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `line.cmin` and `line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.parcoords.line.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`line.cmin` and `line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu ,Greens,YlOrRd,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,P ortland,Jet,Hot,Blackbody,Earth,Electric,Viridis,Cividi s. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `line.color`is set to a numerical array. If true, `line.cmin` will correspond to the last color in the array and `line.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `line.color`is set to a numerical array. Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.parcoords.Line constructor must be a dict or an instance of plotly.graph_objs.parcoords.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.parcoords import line as v_line # Initialize validators # --------------------- self._validators["autocolorscale"] = v_line.AutocolorscaleValidator() self._validators["cauto"] = v_line.CautoValidator() self._validators["cmax"] = v_line.CmaxValidator() self._validators["cmid"] = v_line.CmidValidator() self._validators["cmin"] = v_line.CminValidator() self._validators["color"] = v_line.ColorValidator() self._validators["coloraxis"] = v_line.ColoraxisValidator() self._validators["colorbar"] = v_line.ColorBarValidator() self._validators["colorscale"] = v_line.ColorscaleValidator() self._validators["colorsrc"] = v_line.ColorsrcValidator() self._validators["reversescale"] = v_line.ReversescaleValidator() self._validators["showscale"] = v_line.ShowscaleValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autocolorscale", None) self["autocolorscale"] = autocolorscale if autocolorscale is not None else _v _v = arg.pop("cauto", None) self["cauto"] = cauto if cauto is not None else _v _v = arg.pop("cmax", None) self["cmax"] = cmax if cmax is not None else _v _v = arg.pop("cmid", None) self["cmid"] = cmid if cmid is not None else _v _v = arg.pop("cmin", None) self["cmin"] = cmin if cmin is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("coloraxis", None) self["coloraxis"] = coloraxis if coloraxis is not None else _v _v = arg.pop("colorbar", None) self["colorbar"] = colorbar if colorbar is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("reversescale", None) self["reversescale"] = reversescale if reversescale is not None else _v _v = arg.pop("showscale", None) self["showscale"] = showscale if showscale is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Labelfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "parcoords" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Labelfont object Sets the font for the `dimension` labels. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.parcoords.Labelfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Labelfont """ super(Labelfont, self).__init__("labelfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.parcoords.Labelfont constructor must be a dict or an instance of plotly.graph_objs.parcoords.Labelfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.parcoords import labelfont as v_labelfont # Initialize validators # --------------------- self._validators["color"] = v_labelfont.ColorValidator() self._validators["family"] = v_labelfont.FamilyValidator() self._validators["size"] = v_labelfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Domain(_BaseTraceHierarchyType): # column # ------ @property def column(self): """ If there is a layout grid, use the domain for this column in the grid for this parcoords trace . The 'column' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["column"] @column.setter def column(self, val): self["column"] = val # row # --- @property def row(self): """ If there is a layout grid, use the domain for this row in the grid for this parcoords trace . The 'row' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["row"] @row.setter def row(self, val): self["row"] = val # x # - @property def x(self): """ Sets the horizontal domain of this parcoords trace (in plot fraction). The 'x' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'x[0]' property is a number and may be specified as: - An int or float in the interval [0, 1] (1) The 'x[1]' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- list """ return self["x"] @x.setter def x(self, val): self["x"] = val # y # - @property def y(self): """ Sets the vertical domain of this parcoords trace (in plot fraction). The 'y' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'y[0]' property is a number and may be specified as: - An int or float in the interval [0, 1] (1) The 'y[1]' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- list """ return self["y"] @y.setter def y(self, val): self["y"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "parcoords" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ column If there is a layout grid, use the domain for this column in the grid for this parcoords trace . row If there is a layout grid, use the domain for this row in the grid for this parcoords trace . x Sets the horizontal domain of this parcoords trace (in plot fraction). y Sets the vertical domain of this parcoords trace (in plot fraction). """ def __init__(self, arg=None, column=None, row=None, x=None, y=None, **kwargs): """ Construct a new Domain object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.parcoords.Domain column If there is a layout grid, use the domain for this column in the grid for this parcoords trace . row If there is a layout grid, use the domain for this row in the grid for this parcoords trace . x Sets the horizontal domain of this parcoords trace (in plot fraction). y Sets the vertical domain of this parcoords trace (in plot fraction). Returns ------- Domain """ super(Domain, self).__init__("domain") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.parcoords.Domain constructor must be a dict or an instance of plotly.graph_objs.parcoords.Domain""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.parcoords import domain as v_domain # Initialize validators # --------------------- self._validators["column"] = v_domain.ColumnValidator() self._validators["row"] = v_domain.RowValidator() self._validators["x"] = v_domain.XValidator() self._validators["y"] = v_domain.YValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("column", None) self["column"] = column if column is not None else _v _v = arg.pop("row", None) self["row"] = row if row is not None else _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Dimension(_BaseTraceHierarchyType): # constraintrange # --------------- @property def constraintrange(self): """ The domain range to which the filter on the dimension is constrained. Must be an array of `[fromValue, toValue]` with `fromValue <= toValue`, or if `multiselect` is not disabled, you may give an array of arrays, where each inner array is `[fromValue, toValue]`. The 'constraintrange' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'constraintrange[0]' property is a number and may be specified as: - An int or float (1) The 'constraintrange[1]' property is a number and may be specified as: - An int or float * a 2D list where: (0) The 'constraintrange[i][0]' property is a number and may be specified as: - An int or float (1) The 'constraintrange[i][1]' property is a number and may be specified as: - An int or float Returns ------- list """ return self["constraintrange"] @constraintrange.setter def constraintrange(self, val): self["constraintrange"] = val # label # ----- @property def label(self): """ The shown name of the dimension. The 'label' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["label"] @label.setter def label(self, val): self["label"] = val # multiselect # ----------- @property def multiselect(self): """ Do we allow multiple selection ranges or just a single range? The 'multiselect' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["multiselect"] @multiselect.setter def multiselect(self, val): self["multiselect"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # range # ----- @property def range(self): """ The domain range that represents the full, shown axis extent. Defaults to the `values` extent. Must be an array of `[fromValue, toValue]` with finite numbers as elements. The 'range' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'range[0]' property is a number and may be specified as: - An int or float (1) The 'range[1]' property is a number and may be specified as: - An int or float Returns ------- list """ return self["range"] @range.setter def range(self, val): self["range"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # tickformat # ---------- @property def tickformat(self): """ Sets the tick label formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'tickformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickformat"] @tickformat.setter def tickformat(self, val): self["tickformat"] = val # ticktext # -------- @property def ticktext(self): """ Sets the text displayed at the ticks position via `tickvals`. The 'ticktext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ticktext"] @ticktext.setter def ticktext(self, val): self["ticktext"] = val # ticktextsrc # ----------- @property def ticktextsrc(self): """ Sets the source reference on plot.ly for ticktext . The 'ticktextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ticktextsrc"] @ticktextsrc.setter def ticktextsrc(self, val): self["ticktextsrc"] = val # tickvals # -------- @property def tickvals(self): """ Sets the values at which ticks on this axis appear. The 'tickvals' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["tickvals"] @tickvals.setter def tickvals(self, val): self["tickvals"] = val # tickvalssrc # ----------- @property def tickvalssrc(self): """ Sets the source reference on plot.ly for tickvals . The 'tickvalssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tickvalssrc"] @tickvalssrc.setter def tickvalssrc(self, val): self["tickvalssrc"] = val # values # ------ @property def values(self): """ Dimension values. `values[n]` represents the value of the `n`th point in the dataset, therefore the `values` vector for all dimensions must be the same (longer vectors will be truncated). Each value must be a finite number. The 'values' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["values"] @values.setter def values(self, val): self["values"] = val # valuessrc # --------- @property def valuessrc(self): """ Sets the source reference on plot.ly for values . The 'valuessrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["valuessrc"] @valuessrc.setter def valuessrc(self, val): self["valuessrc"] = val # visible # ------- @property def visible(self): """ Shows the dimension when set to `true` (the default). Hides the dimension for `false`. The 'visible' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "parcoords" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ constraintrange The domain range to which the filter on the dimension is constrained. Must be an array of `[fromValue, toValue]` with `fromValue <= toValue`, or if `multiselect` is not disabled, you may give an array of arrays, where each inner array is `[fromValue, toValue]`. label The shown name of the dimension. multiselect Do we allow multiple selection ranges or just a single range? name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. range The domain range that represents the full, shown axis extent. Defaults to the `values` extent. Must be an array of `[fromValue, toValue]` with finite numbers as elements. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" ticktext Sets the text displayed at the ticks position via `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. tickvalssrc Sets the source reference on plot.ly for tickvals . values Dimension values. `values[n]` represents the value of the `n`th point in the dataset, therefore the `values` vector for all dimensions must be the same (longer vectors will be truncated). Each value must be a finite number. valuessrc Sets the source reference on plot.ly for values . visible Shows the dimension when set to `true` (the default). Hides the dimension for `false`. """ def __init__( self, arg=None, constraintrange=None, label=None, multiselect=None, name=None, range=None, templateitemname=None, tickformat=None, ticktext=None, ticktextsrc=None, tickvals=None, tickvalssrc=None, values=None, valuessrc=None, visible=None, **kwargs ): """ Construct a new Dimension object The dimensions (variables) of the parallel coordinates chart. 2..60 dimensions are supported. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.parcoords.Dimension constraintrange The domain range to which the filter on the dimension is constrained. Must be an array of `[fromValue, toValue]` with `fromValue <= toValue`, or if `multiselect` is not disabled, you may give an array of arrays, where each inner array is `[fromValue, toValue]`. label The shown name of the dimension. multiselect Do we allow multiple selection ranges or just a single range? name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. range The domain range that represents the full, shown axis extent. Defaults to the `values` extent. Must be an array of `[fromValue, toValue]` with finite numbers as elements. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" ticktext Sets the text displayed at the ticks position via `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. tickvalssrc Sets the source reference on plot.ly for tickvals . values Dimension values. `values[n]` represents the value of the `n`th point in the dataset, therefore the `values` vector for all dimensions must be the same (longer vectors will be truncated). Each value must be a finite number. valuessrc Sets the source reference on plot.ly for values . visible Shows the dimension when set to `true` (the default). Hides the dimension for `false`. Returns ------- Dimension """ super(Dimension, self).__init__("dimensions") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.parcoords.Dimension constructor must be a dict or an instance of plotly.graph_objs.parcoords.Dimension""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.parcoords import dimension as v_dimension # Initialize validators # --------------------- self._validators["constraintrange"] = v_dimension.ConstraintrangeValidator() self._validators["label"] = v_dimension.LabelValidator() self._validators["multiselect"] = v_dimension.MultiselectValidator() self._validators["name"] = v_dimension.NameValidator() self._validators["range"] = v_dimension.RangeValidator() self._validators["templateitemname"] = v_dimension.TemplateitemnameValidator() self._validators["tickformat"] = v_dimension.TickformatValidator() self._validators["ticktext"] = v_dimension.TicktextValidator() self._validators["ticktextsrc"] = v_dimension.TicktextsrcValidator() self._validators["tickvals"] = v_dimension.TickvalsValidator() self._validators["tickvalssrc"] = v_dimension.TickvalssrcValidator() self._validators["values"] = v_dimension.ValuesValidator() self._validators["valuessrc"] = v_dimension.ValuessrcValidator() self._validators["visible"] = v_dimension.VisibleValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("constraintrange", None) self["constraintrange"] = constraintrange if constraintrange is not None else _v _v = arg.pop("label", None) self["label"] = label if label is not None else _v _v = arg.pop("multiselect", None) self["multiselect"] = multiselect if multiselect is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("range", None) self["range"] = range if range is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("tickformat", None) self["tickformat"] = tickformat if tickformat is not None else _v _v = arg.pop("ticktext", None) self["ticktext"] = ticktext if ticktext is not None else _v _v = arg.pop("ticktextsrc", None) self["ticktextsrc"] = ticktextsrc if ticktextsrc is not None else _v _v = arg.pop("tickvals", None) self["tickvals"] = tickvals if tickvals is not None else _v _v = arg.pop("tickvalssrc", None) self["tickvalssrc"] = tickvalssrc if tickvalssrc is not None else _v _v = arg.pop("values", None) self["values"] = values if values is not None else _v _v = arg.pop("valuessrc", None) self["valuessrc"] = valuessrc if valuessrc is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = [ "Dimension", "Dimension", "Domain", "Labelfont", "Line", "Rangefont", "Stream", "Tickfont", "line", ] from plotly.graph_objs.parcoords import line plotly-4.4.1+dfsg.orig/plotly/graph_objs/parcoords/line/0000755000175000017500000000000013573746613022654 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/parcoords/line/colorbar/0000755000175000017500000000000013573746613024457 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/parcoords/line/colorbar/title/0000755000175000017500000000000013573746613025600 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/parcoords/line/colorbar/title/__init__.py0000644000175000017500000002057013573721550027706 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "parcoords.line.colorbar.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.parcoords.line.colorbar.title.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.parcoords.line.colorbar.title.Font constructor must be a dict or an instance of plotly.graph_objs.parcoords.line.colorbar.title.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.parcoords.line.colorbar.title import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/parcoords/line/colorbar/__init__.py0000644000175000017500000006075513573721550026576 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Title(_BaseTraceHierarchyType): # font # ---- @property def font(self): """ Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.parcoords.line.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.parcoords.line.colorbar.title.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # side # ---- @property def side(self): """ Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- Any """ return self["side"] @side.setter def side(self, val): self["side"] = val # text # ---- @property def text(self): """ Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "parcoords.line.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """ def __init__(self, arg=None, font=None, side=None, text=None, **kwargs): """ Construct a new Title object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.parcoords.line.colorbar.Title font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- Title """ super(Title, self).__init__("title") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.parcoords.line.colorbar.Title constructor must be a dict or an instance of plotly.graph_objs.parcoords.line.colorbar.Title""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.parcoords.line.colorbar import title as v_title # Initialize validators # --------------------- self._validators["font"] = v_title.FontValidator() self._validators["side"] = v_title.SideValidator() self._validators["text"] = v_title.TextValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("side", None) self["side"] = side if side is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickformatstop(_BaseTraceHierarchyType): # dtickrange # ---------- @property def dtickrange(self): """ range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" The 'dtickrange' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'dtickrange[0]' property accepts values of any type (1) The 'dtickrange[1]' property accepts values of any type Returns ------- list """ return self["dtickrange"] @dtickrange.setter def dtickrange(self, val): self["dtickrange"] = val # enabled # ------- @property def enabled(self): """ Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. The 'enabled' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["enabled"] @enabled.setter def enabled(self, val): self["enabled"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # value # ----- @property def value(self): """ string - dtickformat for described zoom level, the same as "tickformat" The 'value' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "parcoords.line.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """ def __init__( self, arg=None, dtickrange=None, enabled=None, name=None, templateitemname=None, value=None, **kwargs ): """ Construct a new Tickformatstop object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.parcoords.line.colorba r.Tickformatstop dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- Tickformatstop """ super(Tickformatstop, self).__init__("tickformatstops") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.parcoords.line.colorbar.Tickformatstop constructor must be a dict or an instance of plotly.graph_objs.parcoords.line.colorbar.Tickformatstop""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.parcoords.line.colorbar import ( tickformatstop as v_tickformatstop, ) # Initialize validators # --------------------- self._validators["dtickrange"] = v_tickformatstop.DtickrangeValidator() self._validators["enabled"] = v_tickformatstop.EnabledValidator() self._validators["name"] = v_tickformatstop.NameValidator() self._validators[ "templateitemname" ] = v_tickformatstop.TemplateitemnameValidator() self._validators["value"] = v_tickformatstop.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtickrange", None) self["dtickrange"] = dtickrange if dtickrange is not None else _v _v = arg.pop("enabled", None) self["enabled"] = enabled if enabled is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "parcoords.line.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Tickfont object Sets the color bar's tick label font Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.parcoords.line.colorbar.Tickfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Tickfont """ super(Tickfont, self).__init__("tickfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.parcoords.line.colorbar.Tickfont constructor must be a dict or an instance of plotly.graph_objs.parcoords.line.colorbar.Tickfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.parcoords.line.colorbar import tickfont as v_tickfont # Initialize validators # --------------------- self._validators["color"] = v_tickfont.ColorValidator() self._validators["family"] = v_tickfont.FamilyValidator() self._validators["size"] = v_tickfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Tickfont", "Tickformatstop", "Tickformatstop", "Title", "title"] from plotly.graph_objs.parcoords.line.colorbar import title plotly-4.4.1+dfsg.orig/plotly/graph_objs/parcoords/line/__init__.py0000644000175000017500000021001713573721550024757 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class ColorBar(_BaseTraceHierarchyType): # bgcolor # ------- @property def bgcolor(self): """ Sets the color of padded area. The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the axis line color. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # borderwidth # ----------- @property def borderwidth(self): """ Sets the width (in px) or the border enclosing this color bar. The 'borderwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["borderwidth"] @borderwidth.setter def borderwidth(self, val): self["borderwidth"] = val # dtick # ----- @property def dtick(self): """ Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" The 'dtick' property accepts values of any type Returns ------- Any """ return self["dtick"] @dtick.setter def dtick(self, val): self["dtick"] = val # exponentformat # -------------- @property def exponentformat(self): """ Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. The 'exponentformat' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'e', 'E', 'power', 'SI', 'B'] Returns ------- Any """ return self["exponentformat"] @exponentformat.setter def exponentformat(self, val): self["exponentformat"] = val # len # --- @property def len(self): """ Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. The 'len' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["len"] @len.setter def len(self, val): self["len"] = val # lenmode # ------- @property def lenmode(self): """ Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. The 'lenmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["lenmode"] @lenmode.setter def lenmode(self, val): self["lenmode"] = val # nticks # ------ @property def nticks(self): """ Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". The 'nticks' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nticks"] @nticks.setter def nticks(self, val): self["nticks"] = val # outlinecolor # ------------ @property def outlinecolor(self): """ Sets the axis line color. The 'outlinecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["outlinecolor"] @outlinecolor.setter def outlinecolor(self, val): self["outlinecolor"] = val # outlinewidth # ------------ @property def outlinewidth(self): """ Sets the width (in px) of the axis line. The 'outlinewidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["outlinewidth"] @outlinewidth.setter def outlinewidth(self, val): self["outlinewidth"] = val # separatethousands # ----------------- @property def separatethousands(self): """ If "true", even 4-digit integers are separated The 'separatethousands' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["separatethousands"] @separatethousands.setter def separatethousands(self, val): self["separatethousands"] = val # showexponent # ------------ @property def showexponent(self): """ If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. The 'showexponent' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showexponent"] @showexponent.setter def showexponent(self, val): self["showexponent"] = val # showticklabels # -------------- @property def showticklabels(self): """ Determines whether or not the tick labels are drawn. The 'showticklabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showticklabels"] @showticklabels.setter def showticklabels(self, val): self["showticklabels"] = val # showtickprefix # -------------- @property def showtickprefix(self): """ If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. The 'showtickprefix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showtickprefix"] @showtickprefix.setter def showtickprefix(self, val): self["showtickprefix"] = val # showticksuffix # -------------- @property def showticksuffix(self): """ Same as `showtickprefix` but for tick suffixes. The 'showticksuffix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showticksuffix"] @showticksuffix.setter def showticksuffix(self, val): self["showticksuffix"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # thicknessmode # ------------- @property def thicknessmode(self): """ Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. The 'thicknessmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["thicknessmode"] @thicknessmode.setter def thicknessmode(self, val): self["thicknessmode"] = val # tick0 # ----- @property def tick0(self): """ Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. The 'tick0' property accepts values of any type Returns ------- Any """ return self["tick0"] @tick0.setter def tick0(self, val): self["tick0"] = val # tickangle # --------- @property def tickangle(self): """ Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. The 'tickangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["tickangle"] @tickangle.setter def tickangle(self, val): self["tickangle"] = val # tickcolor # --------- @property def tickcolor(self): """ Sets the tick color. The 'tickcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["tickcolor"] @tickcolor.setter def tickcolor(self, val): self["tickcolor"] = val # tickfont # -------- @property def tickfont(self): """ Sets the color bar's tick label font The 'tickfont' property is an instance of Tickfont that may be specified as: - An instance of plotly.graph_objs.parcoords.line.colorbar.Tickfont - A dict of string/value properties that will be passed to the Tickfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.parcoords.line.colorbar.Tickfont """ return self["tickfont"] @tickfont.setter def tickfont(self, val): self["tickfont"] = val # tickformat # ---------- @property def tickformat(self): """ Sets the tick label formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'tickformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickformat"] @tickformat.setter def tickformat(self, val): self["tickformat"] = val # tickformatstops # --------------- @property def tickformatstops(self): """ The 'tickformatstops' property is a tuple of instances of Tickformatstop that may be specified as: - A list or tuple of instances of plotly.graph_objs.parcoords.line.colorbar.Tickformatstop - A list or tuple of dicts of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- tuple[plotly.graph_objs.parcoords.line.colorbar.Tickformatstop] """ return self["tickformatstops"] @tickformatstops.setter def tickformatstops(self, val): self["tickformatstops"] = val # tickformatstopdefaults # ---------------------- @property def tickformatstopdefaults(self): """ When used in a template (as layout.template.data.parcoords.line .colorbar.tickformatstopdefaults), sets the default property values to use for elements of parcoords.line.colorbar.tickformatstops The 'tickformatstopdefaults' property is an instance of Tickformatstop that may be specified as: - An instance of plotly.graph_objs.parcoords.line.colorbar.Tickformatstop - A dict of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: Returns ------- plotly.graph_objs.parcoords.line.colorbar.Tickformatstop """ return self["tickformatstopdefaults"] @tickformatstopdefaults.setter def tickformatstopdefaults(self, val): self["tickformatstopdefaults"] = val # ticklen # ------- @property def ticklen(self): """ Sets the tick length (in px). The 'ticklen' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ticklen"] @ticklen.setter def ticklen(self, val): self["ticklen"] = val # tickmode # -------- @property def tickmode(self): """ Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). The 'tickmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'linear', 'array'] Returns ------- Any """ return self["tickmode"] @tickmode.setter def tickmode(self, val): self["tickmode"] = val # tickprefix # ---------- @property def tickprefix(self): """ Sets a tick label prefix. The 'tickprefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickprefix"] @tickprefix.setter def tickprefix(self, val): self["tickprefix"] = val # ticks # ----- @property def ticks(self): """ Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. The 'ticks' property is an enumeration that may be specified as: - One of the following enumeration values: ['outside', 'inside', ''] Returns ------- Any """ return self["ticks"] @ticks.setter def ticks(self, val): self["ticks"] = val # ticksuffix # ---------- @property def ticksuffix(self): """ Sets a tick label suffix. The 'ticksuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ticksuffix"] @ticksuffix.setter def ticksuffix(self, val): self["ticksuffix"] = val # ticktext # -------- @property def ticktext(self): """ Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. The 'ticktext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ticktext"] @ticktext.setter def ticktext(self, val): self["ticktext"] = val # ticktextsrc # ----------- @property def ticktextsrc(self): """ Sets the source reference on plot.ly for ticktext . The 'ticktextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ticktextsrc"] @ticktextsrc.setter def ticktextsrc(self, val): self["ticktextsrc"] = val # tickvals # -------- @property def tickvals(self): """ Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. The 'tickvals' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["tickvals"] @tickvals.setter def tickvals(self, val): self["tickvals"] = val # tickvalssrc # ----------- @property def tickvalssrc(self): """ Sets the source reference on plot.ly for tickvals . The 'tickvalssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tickvalssrc"] @tickvalssrc.setter def tickvalssrc(self, val): self["tickvalssrc"] = val # tickwidth # --------- @property def tickwidth(self): """ Sets the tick width (in px). The 'tickwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["tickwidth"] @tickwidth.setter def tickwidth(self, val): self["tickwidth"] = val # title # ----- @property def title(self): """ The 'title' property is an instance of Title that may be specified as: - An instance of plotly.graph_objs.parcoords.line.colorbar.Title - A dict of string/value properties that will be passed to the Title constructor Supported dict properties: font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- plotly.graph_objs.parcoords.line.colorbar.Title """ return self["title"] @title.setter def title(self, val): self["title"] = val # titlefont # --------- @property def titlefont(self): """ Deprecated: Please use parcoords.line.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.parcoords.line.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- """ return self["titlefont"] @titlefont.setter def titlefont(self, val): self["titlefont"] = val # titleside # --------- @property def titleside(self): """ Deprecated: Please use parcoords.line.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- """ return self["titleside"] @titleside.setter def titleside(self, val): self["titleside"] = val # x # - @property def x(self): """ Sets the x position of the color bar (in plot fraction). The 'x' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["x"] @x.setter def x(self, val): self["x"] = val # xanchor # ------- @property def xanchor(self): """ Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. The 'xanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'center', 'right'] Returns ------- Any """ return self["xanchor"] @xanchor.setter def xanchor(self, val): self["xanchor"] = val # xpad # ---- @property def xpad(self): """ Sets the amount of padding (in px) along the x direction. The 'xpad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["xpad"] @xpad.setter def xpad(self, val): self["xpad"] = val # y # - @property def y(self): """ Sets the y position of the color bar (in plot fraction). The 'y' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["y"] @y.setter def y(self, val): self["y"] = val # yanchor # ------- @property def yanchor(self): """ Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. The 'yanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['top', 'middle', 'bottom'] Returns ------- Any """ return self["yanchor"] @yanchor.setter def yanchor(self, val): self["yanchor"] = val # ypad # ---- @property def ypad(self): """ Sets the amount of padding (in px) along the y direction. The 'ypad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ypad"] @ypad.setter def ypad(self, val): self["ypad"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "parcoords.line" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.parcoords.line.colorbar .Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.parcoo rds.line.colorbar.tickformatstopdefaults), sets the default property values to use for elements of parcoords.line.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.parcoords.line.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use parcoords.line.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use parcoords.line.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """ _mapped_properties = { "titlefont": ("title", "font"), "titleside": ("title", "side"), } def __init__( self, arg=None, bgcolor=None, bordercolor=None, borderwidth=None, dtick=None, exponentformat=None, len=None, lenmode=None, nticks=None, outlinecolor=None, outlinewidth=None, separatethousands=None, showexponent=None, showticklabels=None, showtickprefix=None, showticksuffix=None, thickness=None, thicknessmode=None, tick0=None, tickangle=None, tickcolor=None, tickfont=None, tickformat=None, tickformatstops=None, tickformatstopdefaults=None, ticklen=None, tickmode=None, tickprefix=None, ticks=None, ticksuffix=None, ticktext=None, ticktextsrc=None, tickvals=None, tickvalssrc=None, tickwidth=None, title=None, titlefont=None, titleside=None, x=None, xanchor=None, xpad=None, y=None, yanchor=None, ypad=None, **kwargs ): """ Construct a new ColorBar object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.parcoords.line.ColorBar bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.parcoords.line.colorbar .Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.parcoo rds.line.colorbar.tickformatstopdefaults), sets the default property values to use for elements of parcoords.line.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.parcoords.line.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use parcoords.line.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use parcoords.line.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- ColorBar """ super(ColorBar, self).__init__("colorbar") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.parcoords.line.ColorBar constructor must be a dict or an instance of plotly.graph_objs.parcoords.line.ColorBar""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.parcoords.line import colorbar as v_colorbar # Initialize validators # --------------------- self._validators["bgcolor"] = v_colorbar.BgcolorValidator() self._validators["bordercolor"] = v_colorbar.BordercolorValidator() self._validators["borderwidth"] = v_colorbar.BorderwidthValidator() self._validators["dtick"] = v_colorbar.DtickValidator() self._validators["exponentformat"] = v_colorbar.ExponentformatValidator() self._validators["len"] = v_colorbar.LenValidator() self._validators["lenmode"] = v_colorbar.LenmodeValidator() self._validators["nticks"] = v_colorbar.NticksValidator() self._validators["outlinecolor"] = v_colorbar.OutlinecolorValidator() self._validators["outlinewidth"] = v_colorbar.OutlinewidthValidator() self._validators["separatethousands"] = v_colorbar.SeparatethousandsValidator() self._validators["showexponent"] = v_colorbar.ShowexponentValidator() self._validators["showticklabels"] = v_colorbar.ShowticklabelsValidator() self._validators["showtickprefix"] = v_colorbar.ShowtickprefixValidator() self._validators["showticksuffix"] = v_colorbar.ShowticksuffixValidator() self._validators["thickness"] = v_colorbar.ThicknessValidator() self._validators["thicknessmode"] = v_colorbar.ThicknessmodeValidator() self._validators["tick0"] = v_colorbar.Tick0Validator() self._validators["tickangle"] = v_colorbar.TickangleValidator() self._validators["tickcolor"] = v_colorbar.TickcolorValidator() self._validators["tickfont"] = v_colorbar.TickfontValidator() self._validators["tickformat"] = v_colorbar.TickformatValidator() self._validators["tickformatstops"] = v_colorbar.TickformatstopsValidator() self._validators[ "tickformatstopdefaults" ] = v_colorbar.TickformatstopValidator() self._validators["ticklen"] = v_colorbar.TicklenValidator() self._validators["tickmode"] = v_colorbar.TickmodeValidator() self._validators["tickprefix"] = v_colorbar.TickprefixValidator() self._validators["ticks"] = v_colorbar.TicksValidator() self._validators["ticksuffix"] = v_colorbar.TicksuffixValidator() self._validators["ticktext"] = v_colorbar.TicktextValidator() self._validators["ticktextsrc"] = v_colorbar.TicktextsrcValidator() self._validators["tickvals"] = v_colorbar.TickvalsValidator() self._validators["tickvalssrc"] = v_colorbar.TickvalssrcValidator() self._validators["tickwidth"] = v_colorbar.TickwidthValidator() self._validators["title"] = v_colorbar.TitleValidator() self._validators["x"] = v_colorbar.XValidator() self._validators["xanchor"] = v_colorbar.XanchorValidator() self._validators["xpad"] = v_colorbar.XpadValidator() self._validators["y"] = v_colorbar.YValidator() self._validators["yanchor"] = v_colorbar.YanchorValidator() self._validators["ypad"] = v_colorbar.YpadValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("borderwidth", None) self["borderwidth"] = borderwidth if borderwidth is not None else _v _v = arg.pop("dtick", None) self["dtick"] = dtick if dtick is not None else _v _v = arg.pop("exponentformat", None) self["exponentformat"] = exponentformat if exponentformat is not None else _v _v = arg.pop("len", None) self["len"] = len if len is not None else _v _v = arg.pop("lenmode", None) self["lenmode"] = lenmode if lenmode is not None else _v _v = arg.pop("nticks", None) self["nticks"] = nticks if nticks is not None else _v _v = arg.pop("outlinecolor", None) self["outlinecolor"] = outlinecolor if outlinecolor is not None else _v _v = arg.pop("outlinewidth", None) self["outlinewidth"] = outlinewidth if outlinewidth is not None else _v _v = arg.pop("separatethousands", None) self["separatethousands"] = ( separatethousands if separatethousands is not None else _v ) _v = arg.pop("showexponent", None) self["showexponent"] = showexponent if showexponent is not None else _v _v = arg.pop("showticklabels", None) self["showticklabels"] = showticklabels if showticklabels is not None else _v _v = arg.pop("showtickprefix", None) self["showtickprefix"] = showtickprefix if showtickprefix is not None else _v _v = arg.pop("showticksuffix", None) self["showticksuffix"] = showticksuffix if showticksuffix is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("thicknessmode", None) self["thicknessmode"] = thicknessmode if thicknessmode is not None else _v _v = arg.pop("tick0", None) self["tick0"] = tick0 if tick0 is not None else _v _v = arg.pop("tickangle", None) self["tickangle"] = tickangle if tickangle is not None else _v _v = arg.pop("tickcolor", None) self["tickcolor"] = tickcolor if tickcolor is not None else _v _v = arg.pop("tickfont", None) self["tickfont"] = tickfont if tickfont is not None else _v _v = arg.pop("tickformat", None) self["tickformat"] = tickformat if tickformat is not None else _v _v = arg.pop("tickformatstops", None) self["tickformatstops"] = tickformatstops if tickformatstops is not None else _v _v = arg.pop("tickformatstopdefaults", None) self["tickformatstopdefaults"] = ( tickformatstopdefaults if tickformatstopdefaults is not None else _v ) _v = arg.pop("ticklen", None) self["ticklen"] = ticklen if ticklen is not None else _v _v = arg.pop("tickmode", None) self["tickmode"] = tickmode if tickmode is not None else _v _v = arg.pop("tickprefix", None) self["tickprefix"] = tickprefix if tickprefix is not None else _v _v = arg.pop("ticks", None) self["ticks"] = ticks if ticks is not None else _v _v = arg.pop("ticksuffix", None) self["ticksuffix"] = ticksuffix if ticksuffix is not None else _v _v = arg.pop("ticktext", None) self["ticktext"] = ticktext if ticktext is not None else _v _v = arg.pop("ticktextsrc", None) self["ticktextsrc"] = ticktextsrc if ticktextsrc is not None else _v _v = arg.pop("tickvals", None) self["tickvals"] = tickvals if tickvals is not None else _v _v = arg.pop("tickvalssrc", None) self["tickvalssrc"] = tickvalssrc if tickvalssrc is not None else _v _v = arg.pop("tickwidth", None) self["tickwidth"] = tickwidth if tickwidth is not None else _v _v = arg.pop("title", None) self["title"] = title if title is not None else _v _v = arg.pop("titlefont", None) _v = titlefont if titlefont is not None else _v if _v is not None: self["titlefont"] = _v _v = arg.pop("titleside", None) _v = titleside if titleside is not None else _v if _v is not None: self["titleside"] = _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xanchor", None) self["xanchor"] = xanchor if xanchor is not None else _v _v = arg.pop("xpad", None) self["xpad"] = xpad if xpad is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("yanchor", None) self["yanchor"] = yanchor if yanchor is not None else _v _v = arg.pop("ypad", None) self["ypad"] = ypad if ypad is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["ColorBar", "colorbar"] from plotly.graph_objs.parcoords.line import colorbar plotly-4.4.1+dfsg.orig/plotly/graph_objs/scatter/0000755000175000017500000000000013573746613021376 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scatter/unselected/0000755000175000017500000000000013573746613023531 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scatter/unselected/__init__.py0000644000175000017500000002763213573721550025645 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Textfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the text font color of unselected points, applied only when a selection exists. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatter.unselected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the text font color of unselected points, applied only when a selection exists. """ def __init__(self, arg=None, color=None, **kwargs): """ Construct a new Textfont object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatter.unselected.Textfont color Sets the text font color of unselected points, applied only when a selection exists. Returns ------- Textfont """ super(Textfont, self).__init__("textfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatter.unselected.Textfont constructor must be a dict or an instance of plotly.graph_objs.scatter.unselected.Textfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatter.unselected import textfont as v_textfont # Initialize validators # --------------------- self._validators["color"] = v_textfont.ColorValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the marker color of unselected points, applied only when a selection exists. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # opacity # ------- @property def opacity(self): """ Sets the marker opacity of unselected points, applied only when a selection exists. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # size # ---- @property def size(self): """ Sets the marker size of unselected points, applied only when a selection exists. The 'size' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatter.unselected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. size Sets the marker size of unselected points, applied only when a selection exists. """ def __init__(self, arg=None, color=None, opacity=None, size=None, **kwargs): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatter.unselected.Marker color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. size Sets the marker size of unselected points, applied only when a selection exists. Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatter.unselected.Marker constructor must be a dict or an instance of plotly.graph_objs.scatter.unselected.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatter.unselected import marker as v_marker # Initialize validators # --------------------- self._validators["color"] = v_marker.ColorValidator() self._validators["opacity"] = v_marker.OpacityValidator() self._validators["size"] = v_marker.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Marker", "Textfont"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/scatter/hoverlabel/0000755000175000017500000000000013573746613023521 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scatter/hoverlabel/__init__.py0000644000175000017500000002544013573721550025630 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatter.hoverlabel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Font object Sets the font used in hover labels. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatter.hoverlabel.Font color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatter.hoverlabel.Font constructor must be a dict or an instance of plotly.graph_objs.scatter.hoverlabel.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatter.hoverlabel import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["colorsrc"] = v_font.ColorsrcValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["familysrc"] = v_font.FamilysrcValidator() self._validators["size"] = v_font.SizeValidator() self._validators["sizesrc"] = v_font.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/scatter/marker/0000755000175000017500000000000013573746613022657 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scatter/marker/colorbar/0000755000175000017500000000000013573746613024462 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scatter/marker/colorbar/title/0000755000175000017500000000000013573746613025603 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scatter/marker/colorbar/title/__init__.py0000644000175000017500000002057013573721550027711 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatter.marker.colorbar.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatter.marker.colorbar.title.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatter.marker.colorbar.title.Font constructor must be a dict or an instance of plotly.graph_objs.scatter.marker.colorbar.title.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatter.marker.colorbar.title import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/scatter/marker/colorbar/__init__.py0000644000175000017500000006075513573721550026601 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Title(_BaseTraceHierarchyType): # font # ---- @property def font(self): """ Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.scatter.marker.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.scatter.marker.colorbar.title.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # side # ---- @property def side(self): """ Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- Any """ return self["side"] @side.setter def side(self, val): self["side"] = val # text # ---- @property def text(self): """ Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatter.marker.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """ def __init__(self, arg=None, font=None, side=None, text=None, **kwargs): """ Construct a new Title object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatter.marker.colorbar.Title font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- Title """ super(Title, self).__init__("title") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatter.marker.colorbar.Title constructor must be a dict or an instance of plotly.graph_objs.scatter.marker.colorbar.Title""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatter.marker.colorbar import title as v_title # Initialize validators # --------------------- self._validators["font"] = v_title.FontValidator() self._validators["side"] = v_title.SideValidator() self._validators["text"] = v_title.TextValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("side", None) self["side"] = side if side is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickformatstop(_BaseTraceHierarchyType): # dtickrange # ---------- @property def dtickrange(self): """ range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" The 'dtickrange' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'dtickrange[0]' property accepts values of any type (1) The 'dtickrange[1]' property accepts values of any type Returns ------- list """ return self["dtickrange"] @dtickrange.setter def dtickrange(self, val): self["dtickrange"] = val # enabled # ------- @property def enabled(self): """ Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. The 'enabled' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["enabled"] @enabled.setter def enabled(self, val): self["enabled"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # value # ----- @property def value(self): """ string - dtickformat for described zoom level, the same as "tickformat" The 'value' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatter.marker.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """ def __init__( self, arg=None, dtickrange=None, enabled=None, name=None, templateitemname=None, value=None, **kwargs ): """ Construct a new Tickformatstop object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatter.marker.colorba r.Tickformatstop dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- Tickformatstop """ super(Tickformatstop, self).__init__("tickformatstops") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatter.marker.colorbar.Tickformatstop constructor must be a dict or an instance of plotly.graph_objs.scatter.marker.colorbar.Tickformatstop""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatter.marker.colorbar import ( tickformatstop as v_tickformatstop, ) # Initialize validators # --------------------- self._validators["dtickrange"] = v_tickformatstop.DtickrangeValidator() self._validators["enabled"] = v_tickformatstop.EnabledValidator() self._validators["name"] = v_tickformatstop.NameValidator() self._validators[ "templateitemname" ] = v_tickformatstop.TemplateitemnameValidator() self._validators["value"] = v_tickformatstop.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtickrange", None) self["dtickrange"] = dtickrange if dtickrange is not None else _v _v = arg.pop("enabled", None) self["enabled"] = enabled if enabled is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatter.marker.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Tickfont object Sets the color bar's tick label font Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatter.marker.colorbar.Tickfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Tickfont """ super(Tickfont, self).__init__("tickfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatter.marker.colorbar.Tickfont constructor must be a dict or an instance of plotly.graph_objs.scatter.marker.colorbar.Tickfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatter.marker.colorbar import tickfont as v_tickfont # Initialize validators # --------------------- self._validators["color"] = v_tickfont.ColorValidator() self._validators["family"] = v_tickfont.FamilyValidator() self._validators["size"] = v_tickfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Tickfont", "Tickformatstop", "Tickformatstop", "Title", "title"] from plotly.graph_objs.scatter.marker.colorbar import title plotly-4.4.1+dfsg.orig/plotly/graph_objs/scatter/marker/__init__.py0000644000175000017500000030762713573721551025001 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # autocolorscale # -------------- @property def autocolorscale(self): """ Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. The 'autocolorscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocolorscale"] @autocolorscale.setter def autocolorscale(self, val): self["autocolorscale"] = val # cauto # ----- @property def cauto(self): """ Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. The 'cauto' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["cauto"] @cauto.setter def cauto(self, val): self["cauto"] = val # cmax # ---- @property def cmax(self): """ Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. The 'cmax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmax"] @cmax.setter def cmax(self, val): self["cmax"] = val # cmid # ---- @property def cmid(self): """ Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. The 'cmid' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmid"] @cmid.setter def cmid(self, val): self["cmid"] = val # cmin # ---- @property def cmin(self): """ Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. The 'cmin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmin"] @cmin.setter def cmin(self, val): self["cmin"] = val # color # ----- @property def color(self): """ Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A number that will be interpreted as a color according to scatter.marker.line.colorscale - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # coloraxis # --------- @property def coloraxis(self): """ Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. The 'coloraxis' property is an identifier of a particular subplot, of type 'coloraxis', that may be specified as the string 'coloraxis' optionally followed by an integer >= 1 (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) Returns ------- str """ return self["coloraxis"] @coloraxis.setter def coloraxis(self, val): self["coloraxis"] = val # colorscale # ---------- @property def colorscale(self): """ Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,Earth,Electric,Vi ridis,Cividis. The 'colorscale' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # reversescale # ------------ @property def reversescale(self): """ Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. The 'reversescale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["reversescale"] @reversescale.setter def reversescale(self, val): self["reversescale"] = val # width # ----- @property def width(self): """ Sets the width (in px) of the lines bounding the marker points. The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["width"] @width.setter def width(self, val): self["width"] = val # widthsrc # -------- @property def widthsrc(self): """ Sets the source reference on plot.ly for width . The 'widthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["widthsrc"] @widthsrc.setter def widthsrc(self, val): self["widthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatter.marker" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . """ def __init__( self, arg=None, autocolorscale=None, cauto=None, cmax=None, cmid=None, cmin=None, color=None, coloraxis=None, colorscale=None, colorsrc=None, reversescale=None, width=None, widthsrc=None, **kwargs ): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatter.marker.Line autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatter.marker.Line constructor must be a dict or an instance of plotly.graph_objs.scatter.marker.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatter.marker import line as v_line # Initialize validators # --------------------- self._validators["autocolorscale"] = v_line.AutocolorscaleValidator() self._validators["cauto"] = v_line.CautoValidator() self._validators["cmax"] = v_line.CmaxValidator() self._validators["cmid"] = v_line.CmidValidator() self._validators["cmin"] = v_line.CminValidator() self._validators["color"] = v_line.ColorValidator() self._validators["coloraxis"] = v_line.ColoraxisValidator() self._validators["colorscale"] = v_line.ColorscaleValidator() self._validators["colorsrc"] = v_line.ColorsrcValidator() self._validators["reversescale"] = v_line.ReversescaleValidator() self._validators["width"] = v_line.WidthValidator() self._validators["widthsrc"] = v_line.WidthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autocolorscale", None) self["autocolorscale"] = autocolorscale if autocolorscale is not None else _v _v = arg.pop("cauto", None) self["cauto"] = cauto if cauto is not None else _v _v = arg.pop("cmax", None) self["cmax"] = cmax if cmax is not None else _v _v = arg.pop("cmid", None) self["cmid"] = cmid if cmid is not None else _v _v = arg.pop("cmin", None) self["cmin"] = cmin if cmin is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("coloraxis", None) self["coloraxis"] = coloraxis if coloraxis is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("reversescale", None) self["reversescale"] = reversescale if reversescale is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v _v = arg.pop("widthsrc", None) self["widthsrc"] = widthsrc if widthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Gradient(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the final color of the gradient fill: the center color for radial, the right for horizontal, or the bottom for vertical. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # type # ---- @property def type(self): """ Sets the type of gradient used to fill the markers The 'type' property is an enumeration that may be specified as: - One of the following enumeration values: ['radial', 'horizontal', 'vertical', 'none'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["type"] @type.setter def type(self, val): self["type"] = val # typesrc # ------- @property def typesrc(self): """ Sets the source reference on plot.ly for type . The 'typesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["typesrc"] @typesrc.setter def typesrc(self, val): self["typesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatter.marker" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the final color of the gradient fill: the center color for radial, the right for horizontal, or the bottom for vertical. colorsrc Sets the source reference on plot.ly for color . type Sets the type of gradient used to fill the markers typesrc Sets the source reference on plot.ly for type . """ def __init__( self, arg=None, color=None, colorsrc=None, type=None, typesrc=None, **kwargs ): """ Construct a new Gradient object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatter.marker.Gradient color Sets the final color of the gradient fill: the center color for radial, the right for horizontal, or the bottom for vertical. colorsrc Sets the source reference on plot.ly for color . type Sets the type of gradient used to fill the markers typesrc Sets the source reference on plot.ly for type . Returns ------- Gradient """ super(Gradient, self).__init__("gradient") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatter.marker.Gradient constructor must be a dict or an instance of plotly.graph_objs.scatter.marker.Gradient""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatter.marker import gradient as v_gradient # Initialize validators # --------------------- self._validators["color"] = v_gradient.ColorValidator() self._validators["colorsrc"] = v_gradient.ColorsrcValidator() self._validators["type"] = v_gradient.TypeValidator() self._validators["typesrc"] = v_gradient.TypesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("type", None) self["type"] = type if type is not None else _v _v = arg.pop("typesrc", None) self["typesrc"] = typesrc if typesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class ColorBar(_BaseTraceHierarchyType): # bgcolor # ------- @property def bgcolor(self): """ Sets the color of padded area. The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the axis line color. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # borderwidth # ----------- @property def borderwidth(self): """ Sets the width (in px) or the border enclosing this color bar. The 'borderwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["borderwidth"] @borderwidth.setter def borderwidth(self, val): self["borderwidth"] = val # dtick # ----- @property def dtick(self): """ Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" The 'dtick' property accepts values of any type Returns ------- Any """ return self["dtick"] @dtick.setter def dtick(self, val): self["dtick"] = val # exponentformat # -------------- @property def exponentformat(self): """ Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. The 'exponentformat' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'e', 'E', 'power', 'SI', 'B'] Returns ------- Any """ return self["exponentformat"] @exponentformat.setter def exponentformat(self, val): self["exponentformat"] = val # len # --- @property def len(self): """ Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. The 'len' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["len"] @len.setter def len(self, val): self["len"] = val # lenmode # ------- @property def lenmode(self): """ Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. The 'lenmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["lenmode"] @lenmode.setter def lenmode(self, val): self["lenmode"] = val # nticks # ------ @property def nticks(self): """ Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". The 'nticks' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nticks"] @nticks.setter def nticks(self, val): self["nticks"] = val # outlinecolor # ------------ @property def outlinecolor(self): """ Sets the axis line color. The 'outlinecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["outlinecolor"] @outlinecolor.setter def outlinecolor(self, val): self["outlinecolor"] = val # outlinewidth # ------------ @property def outlinewidth(self): """ Sets the width (in px) of the axis line. The 'outlinewidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["outlinewidth"] @outlinewidth.setter def outlinewidth(self, val): self["outlinewidth"] = val # separatethousands # ----------------- @property def separatethousands(self): """ If "true", even 4-digit integers are separated The 'separatethousands' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["separatethousands"] @separatethousands.setter def separatethousands(self, val): self["separatethousands"] = val # showexponent # ------------ @property def showexponent(self): """ If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. The 'showexponent' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showexponent"] @showexponent.setter def showexponent(self, val): self["showexponent"] = val # showticklabels # -------------- @property def showticklabels(self): """ Determines whether or not the tick labels are drawn. The 'showticklabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showticklabels"] @showticklabels.setter def showticklabels(self, val): self["showticklabels"] = val # showtickprefix # -------------- @property def showtickprefix(self): """ If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. The 'showtickprefix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showtickprefix"] @showtickprefix.setter def showtickprefix(self, val): self["showtickprefix"] = val # showticksuffix # -------------- @property def showticksuffix(self): """ Same as `showtickprefix` but for tick suffixes. The 'showticksuffix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showticksuffix"] @showticksuffix.setter def showticksuffix(self, val): self["showticksuffix"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # thicknessmode # ------------- @property def thicknessmode(self): """ Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. The 'thicknessmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["thicknessmode"] @thicknessmode.setter def thicknessmode(self, val): self["thicknessmode"] = val # tick0 # ----- @property def tick0(self): """ Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. The 'tick0' property accepts values of any type Returns ------- Any """ return self["tick0"] @tick0.setter def tick0(self, val): self["tick0"] = val # tickangle # --------- @property def tickangle(self): """ Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. The 'tickangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["tickangle"] @tickangle.setter def tickangle(self, val): self["tickangle"] = val # tickcolor # --------- @property def tickcolor(self): """ Sets the tick color. The 'tickcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["tickcolor"] @tickcolor.setter def tickcolor(self, val): self["tickcolor"] = val # tickfont # -------- @property def tickfont(self): """ Sets the color bar's tick label font The 'tickfont' property is an instance of Tickfont that may be specified as: - An instance of plotly.graph_objs.scatter.marker.colorbar.Tickfont - A dict of string/value properties that will be passed to the Tickfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.scatter.marker.colorbar.Tickfont """ return self["tickfont"] @tickfont.setter def tickfont(self, val): self["tickfont"] = val # tickformat # ---------- @property def tickformat(self): """ Sets the tick label formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'tickformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickformat"] @tickformat.setter def tickformat(self, val): self["tickformat"] = val # tickformatstops # --------------- @property def tickformatstops(self): """ The 'tickformatstops' property is a tuple of instances of Tickformatstop that may be specified as: - A list or tuple of instances of plotly.graph_objs.scatter.marker.colorbar.Tickformatstop - A list or tuple of dicts of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- tuple[plotly.graph_objs.scatter.marker.colorbar.Tickformatstop] """ return self["tickformatstops"] @tickformatstops.setter def tickformatstops(self, val): self["tickformatstops"] = val # tickformatstopdefaults # ---------------------- @property def tickformatstopdefaults(self): """ When used in a template (as layout.template.data.scatter.marker .colorbar.tickformatstopdefaults), sets the default property values to use for elements of scatter.marker.colorbar.tickformatstops The 'tickformatstopdefaults' property is an instance of Tickformatstop that may be specified as: - An instance of plotly.graph_objs.scatter.marker.colorbar.Tickformatstop - A dict of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: Returns ------- plotly.graph_objs.scatter.marker.colorbar.Tickformatstop """ return self["tickformatstopdefaults"] @tickformatstopdefaults.setter def tickformatstopdefaults(self, val): self["tickformatstopdefaults"] = val # ticklen # ------- @property def ticklen(self): """ Sets the tick length (in px). The 'ticklen' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ticklen"] @ticklen.setter def ticklen(self, val): self["ticklen"] = val # tickmode # -------- @property def tickmode(self): """ Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). The 'tickmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'linear', 'array'] Returns ------- Any """ return self["tickmode"] @tickmode.setter def tickmode(self, val): self["tickmode"] = val # tickprefix # ---------- @property def tickprefix(self): """ Sets a tick label prefix. The 'tickprefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickprefix"] @tickprefix.setter def tickprefix(self, val): self["tickprefix"] = val # ticks # ----- @property def ticks(self): """ Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. The 'ticks' property is an enumeration that may be specified as: - One of the following enumeration values: ['outside', 'inside', ''] Returns ------- Any """ return self["ticks"] @ticks.setter def ticks(self, val): self["ticks"] = val # ticksuffix # ---------- @property def ticksuffix(self): """ Sets a tick label suffix. The 'ticksuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ticksuffix"] @ticksuffix.setter def ticksuffix(self, val): self["ticksuffix"] = val # ticktext # -------- @property def ticktext(self): """ Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. The 'ticktext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ticktext"] @ticktext.setter def ticktext(self, val): self["ticktext"] = val # ticktextsrc # ----------- @property def ticktextsrc(self): """ Sets the source reference on plot.ly for ticktext . The 'ticktextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ticktextsrc"] @ticktextsrc.setter def ticktextsrc(self, val): self["ticktextsrc"] = val # tickvals # -------- @property def tickvals(self): """ Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. The 'tickvals' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["tickvals"] @tickvals.setter def tickvals(self, val): self["tickvals"] = val # tickvalssrc # ----------- @property def tickvalssrc(self): """ Sets the source reference on plot.ly for tickvals . The 'tickvalssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tickvalssrc"] @tickvalssrc.setter def tickvalssrc(self, val): self["tickvalssrc"] = val # tickwidth # --------- @property def tickwidth(self): """ Sets the tick width (in px). The 'tickwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["tickwidth"] @tickwidth.setter def tickwidth(self, val): self["tickwidth"] = val # title # ----- @property def title(self): """ The 'title' property is an instance of Title that may be specified as: - An instance of plotly.graph_objs.scatter.marker.colorbar.Title - A dict of string/value properties that will be passed to the Title constructor Supported dict properties: font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- plotly.graph_objs.scatter.marker.colorbar.Title """ return self["title"] @title.setter def title(self, val): self["title"] = val # titlefont # --------- @property def titlefont(self): """ Deprecated: Please use scatter.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.scatter.marker.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- """ return self["titlefont"] @titlefont.setter def titlefont(self, val): self["titlefont"] = val # titleside # --------- @property def titleside(self): """ Deprecated: Please use scatter.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- """ return self["titleside"] @titleside.setter def titleside(self, val): self["titleside"] = val # x # - @property def x(self): """ Sets the x position of the color bar (in plot fraction). The 'x' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["x"] @x.setter def x(self, val): self["x"] = val # xanchor # ------- @property def xanchor(self): """ Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. The 'xanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'center', 'right'] Returns ------- Any """ return self["xanchor"] @xanchor.setter def xanchor(self, val): self["xanchor"] = val # xpad # ---- @property def xpad(self): """ Sets the amount of padding (in px) along the x direction. The 'xpad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["xpad"] @xpad.setter def xpad(self, val): self["xpad"] = val # y # - @property def y(self): """ Sets the y position of the color bar (in plot fraction). The 'y' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["y"] @y.setter def y(self, val): self["y"] = val # yanchor # ------- @property def yanchor(self): """ Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. The 'yanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['top', 'middle', 'bottom'] Returns ------- Any """ return self["yanchor"] @yanchor.setter def yanchor(self, val): self["yanchor"] = val # ypad # ---- @property def ypad(self): """ Sets the amount of padding (in px) along the y direction. The 'ypad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ypad"] @ypad.setter def ypad(self, val): self["ypad"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatter.marker" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.scatter.marker.colorbar .Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.scatte r.marker.colorbar.tickformatstopdefaults), sets the default property values to use for elements of scatter.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.scatter.marker.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use scatter.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use scatter.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """ _mapped_properties = { "titlefont": ("title", "font"), "titleside": ("title", "side"), } def __init__( self, arg=None, bgcolor=None, bordercolor=None, borderwidth=None, dtick=None, exponentformat=None, len=None, lenmode=None, nticks=None, outlinecolor=None, outlinewidth=None, separatethousands=None, showexponent=None, showticklabels=None, showtickprefix=None, showticksuffix=None, thickness=None, thicknessmode=None, tick0=None, tickangle=None, tickcolor=None, tickfont=None, tickformat=None, tickformatstops=None, tickformatstopdefaults=None, ticklen=None, tickmode=None, tickprefix=None, ticks=None, ticksuffix=None, ticktext=None, ticktextsrc=None, tickvals=None, tickvalssrc=None, tickwidth=None, title=None, titlefont=None, titleside=None, x=None, xanchor=None, xpad=None, y=None, yanchor=None, ypad=None, **kwargs ): """ Construct a new ColorBar object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatter.marker.ColorBar bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.scatter.marker.colorbar .Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.scatte r.marker.colorbar.tickformatstopdefaults), sets the default property values to use for elements of scatter.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.scatter.marker.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use scatter.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use scatter.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- ColorBar """ super(ColorBar, self).__init__("colorbar") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatter.marker.ColorBar constructor must be a dict or an instance of plotly.graph_objs.scatter.marker.ColorBar""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatter.marker import colorbar as v_colorbar # Initialize validators # --------------------- self._validators["bgcolor"] = v_colorbar.BgcolorValidator() self._validators["bordercolor"] = v_colorbar.BordercolorValidator() self._validators["borderwidth"] = v_colorbar.BorderwidthValidator() self._validators["dtick"] = v_colorbar.DtickValidator() self._validators["exponentformat"] = v_colorbar.ExponentformatValidator() self._validators["len"] = v_colorbar.LenValidator() self._validators["lenmode"] = v_colorbar.LenmodeValidator() self._validators["nticks"] = v_colorbar.NticksValidator() self._validators["outlinecolor"] = v_colorbar.OutlinecolorValidator() self._validators["outlinewidth"] = v_colorbar.OutlinewidthValidator() self._validators["separatethousands"] = v_colorbar.SeparatethousandsValidator() self._validators["showexponent"] = v_colorbar.ShowexponentValidator() self._validators["showticklabels"] = v_colorbar.ShowticklabelsValidator() self._validators["showtickprefix"] = v_colorbar.ShowtickprefixValidator() self._validators["showticksuffix"] = v_colorbar.ShowticksuffixValidator() self._validators["thickness"] = v_colorbar.ThicknessValidator() self._validators["thicknessmode"] = v_colorbar.ThicknessmodeValidator() self._validators["tick0"] = v_colorbar.Tick0Validator() self._validators["tickangle"] = v_colorbar.TickangleValidator() self._validators["tickcolor"] = v_colorbar.TickcolorValidator() self._validators["tickfont"] = v_colorbar.TickfontValidator() self._validators["tickformat"] = v_colorbar.TickformatValidator() self._validators["tickformatstops"] = v_colorbar.TickformatstopsValidator() self._validators[ "tickformatstopdefaults" ] = v_colorbar.TickformatstopValidator() self._validators["ticklen"] = v_colorbar.TicklenValidator() self._validators["tickmode"] = v_colorbar.TickmodeValidator() self._validators["tickprefix"] = v_colorbar.TickprefixValidator() self._validators["ticks"] = v_colorbar.TicksValidator() self._validators["ticksuffix"] = v_colorbar.TicksuffixValidator() self._validators["ticktext"] = v_colorbar.TicktextValidator() self._validators["ticktextsrc"] = v_colorbar.TicktextsrcValidator() self._validators["tickvals"] = v_colorbar.TickvalsValidator() self._validators["tickvalssrc"] = v_colorbar.TickvalssrcValidator() self._validators["tickwidth"] = v_colorbar.TickwidthValidator() self._validators["title"] = v_colorbar.TitleValidator() self._validators["x"] = v_colorbar.XValidator() self._validators["xanchor"] = v_colorbar.XanchorValidator() self._validators["xpad"] = v_colorbar.XpadValidator() self._validators["y"] = v_colorbar.YValidator() self._validators["yanchor"] = v_colorbar.YanchorValidator() self._validators["ypad"] = v_colorbar.YpadValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("borderwidth", None) self["borderwidth"] = borderwidth if borderwidth is not None else _v _v = arg.pop("dtick", None) self["dtick"] = dtick if dtick is not None else _v _v = arg.pop("exponentformat", None) self["exponentformat"] = exponentformat if exponentformat is not None else _v _v = arg.pop("len", None) self["len"] = len if len is not None else _v _v = arg.pop("lenmode", None) self["lenmode"] = lenmode if lenmode is not None else _v _v = arg.pop("nticks", None) self["nticks"] = nticks if nticks is not None else _v _v = arg.pop("outlinecolor", None) self["outlinecolor"] = outlinecolor if outlinecolor is not None else _v _v = arg.pop("outlinewidth", None) self["outlinewidth"] = outlinewidth if outlinewidth is not None else _v _v = arg.pop("separatethousands", None) self["separatethousands"] = ( separatethousands if separatethousands is not None else _v ) _v = arg.pop("showexponent", None) self["showexponent"] = showexponent if showexponent is not None else _v _v = arg.pop("showticklabels", None) self["showticklabels"] = showticklabels if showticklabels is not None else _v _v = arg.pop("showtickprefix", None) self["showtickprefix"] = showtickprefix if showtickprefix is not None else _v _v = arg.pop("showticksuffix", None) self["showticksuffix"] = showticksuffix if showticksuffix is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("thicknessmode", None) self["thicknessmode"] = thicknessmode if thicknessmode is not None else _v _v = arg.pop("tick0", None) self["tick0"] = tick0 if tick0 is not None else _v _v = arg.pop("tickangle", None) self["tickangle"] = tickangle if tickangle is not None else _v _v = arg.pop("tickcolor", None) self["tickcolor"] = tickcolor if tickcolor is not None else _v _v = arg.pop("tickfont", None) self["tickfont"] = tickfont if tickfont is not None else _v _v = arg.pop("tickformat", None) self["tickformat"] = tickformat if tickformat is not None else _v _v = arg.pop("tickformatstops", None) self["tickformatstops"] = tickformatstops if tickformatstops is not None else _v _v = arg.pop("tickformatstopdefaults", None) self["tickformatstopdefaults"] = ( tickformatstopdefaults if tickformatstopdefaults is not None else _v ) _v = arg.pop("ticklen", None) self["ticklen"] = ticklen if ticklen is not None else _v _v = arg.pop("tickmode", None) self["tickmode"] = tickmode if tickmode is not None else _v _v = arg.pop("tickprefix", None) self["tickprefix"] = tickprefix if tickprefix is not None else _v _v = arg.pop("ticks", None) self["ticks"] = ticks if ticks is not None else _v _v = arg.pop("ticksuffix", None) self["ticksuffix"] = ticksuffix if ticksuffix is not None else _v _v = arg.pop("ticktext", None) self["ticktext"] = ticktext if ticktext is not None else _v _v = arg.pop("ticktextsrc", None) self["ticktextsrc"] = ticktextsrc if ticktextsrc is not None else _v _v = arg.pop("tickvals", None) self["tickvals"] = tickvals if tickvals is not None else _v _v = arg.pop("tickvalssrc", None) self["tickvalssrc"] = tickvalssrc if tickvalssrc is not None else _v _v = arg.pop("tickwidth", None) self["tickwidth"] = tickwidth if tickwidth is not None else _v _v = arg.pop("title", None) self["title"] = title if title is not None else _v _v = arg.pop("titlefont", None) _v = titlefont if titlefont is not None else _v if _v is not None: self["titlefont"] = _v _v = arg.pop("titleside", None) _v = titleside if titleside is not None else _v if _v is not None: self["titleside"] = _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xanchor", None) self["xanchor"] = xanchor if xanchor is not None else _v _v = arg.pop("xpad", None) self["xpad"] = xpad if xpad is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("yanchor", None) self["yanchor"] = yanchor if yanchor is not None else _v _v = arg.pop("ypad", None) self["ypad"] = ypad if ypad is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["ColorBar", "Gradient", "Line", "colorbar"] from plotly.graph_objs.scatter.marker import colorbar plotly-4.4.1+dfsg.orig/plotly/graph_objs/scatter/__init__.py0000644000175000017500000044104513573721552023512 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Unselected(_BaseTraceHierarchyType): # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.scatter.unselected.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. size Sets the marker size of unselected points, applied only when a selection exists. Returns ------- plotly.graph_objs.scatter.unselected.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # textfont # -------- @property def textfont(self): """ The 'textfont' property is an instance of Textfont that may be specified as: - An instance of plotly.graph_objs.scatter.unselected.Textfont - A dict of string/value properties that will be passed to the Textfont constructor Supported dict properties: color Sets the text font color of unselected points, applied only when a selection exists. Returns ------- plotly.graph_objs.scatter.unselected.Textfont """ return self["textfont"] @textfont.setter def textfont(self, val): self["textfont"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatter" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ marker plotly.graph_objects.scatter.unselected.Marker instance or dict with compatible properties textfont plotly.graph_objects.scatter.unselected.Textfont instance or dict with compatible properties """ def __init__(self, arg=None, marker=None, textfont=None, **kwargs): """ Construct a new Unselected object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatter.Unselected marker plotly.graph_objects.scatter.unselected.Marker instance or dict with compatible properties textfont plotly.graph_objects.scatter.unselected.Textfont instance or dict with compatible properties Returns ------- Unselected """ super(Unselected, self).__init__("unselected") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatter.Unselected constructor must be a dict or an instance of plotly.graph_objs.scatter.Unselected""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatter import unselected as v_unselected # Initialize validators # --------------------- self._validators["marker"] = v_unselected.MarkerValidator() self._validators["textfont"] = v_unselected.TextfontValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v _v = arg.pop("textfont", None) self["textfont"] = textfont if textfont is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Textfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatter" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Textfont object Sets the text font. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatter.Textfont color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Textfont """ super(Textfont, self).__init__("textfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatter.Textfont constructor must be a dict or an instance of plotly.graph_objs.scatter.Textfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatter import textfont as v_textfont # Initialize validators # --------------------- self._validators["color"] = v_textfont.ColorValidator() self._validators["colorsrc"] = v_textfont.ColorsrcValidator() self._validators["family"] = v_textfont.FamilyValidator() self._validators["familysrc"] = v_textfont.FamilysrcValidator() self._validators["size"] = v_textfont.SizeValidator() self._validators["sizesrc"] = v_textfont.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Stream(_BaseTraceHierarchyType): # maxpoints # --------- @property def maxpoints(self): """ Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. The 'maxpoints' property is a number and may be specified as: - An int or float in the interval [0, 10000] Returns ------- int|float """ return self["maxpoints"] @maxpoints.setter def maxpoints(self, val): self["maxpoints"] = val # token # ----- @property def token(self): """ The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. The 'token' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["token"] @token.setter def token(self, val): self["token"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatter" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """ def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): """ Construct a new Stream object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatter.Stream maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- Stream """ super(Stream, self).__init__("stream") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatter.Stream constructor must be a dict or an instance of plotly.graph_objs.scatter.Stream""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatter import stream as v_stream # Initialize validators # --------------------- self._validators["maxpoints"] = v_stream.MaxpointsValidator() self._validators["token"] = v_stream.TokenValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("maxpoints", None) self["maxpoints"] = maxpoints if maxpoints is not None else _v _v = arg.pop("token", None) self["token"] = token if token is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Selected(_BaseTraceHierarchyType): # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.scatter.selected.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. size Sets the marker size of selected points. Returns ------- plotly.graph_objs.scatter.selected.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # textfont # -------- @property def textfont(self): """ The 'textfont' property is an instance of Textfont that may be specified as: - An instance of plotly.graph_objs.scatter.selected.Textfont - A dict of string/value properties that will be passed to the Textfont constructor Supported dict properties: color Sets the text font color of selected points. Returns ------- plotly.graph_objs.scatter.selected.Textfont """ return self["textfont"] @textfont.setter def textfont(self, val): self["textfont"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatter" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ marker plotly.graph_objects.scatter.selected.Marker instance or dict with compatible properties textfont plotly.graph_objects.scatter.selected.Textfont instance or dict with compatible properties """ def __init__(self, arg=None, marker=None, textfont=None, **kwargs): """ Construct a new Selected object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatter.Selected marker plotly.graph_objects.scatter.selected.Marker instance or dict with compatible properties textfont plotly.graph_objects.scatter.selected.Textfont instance or dict with compatible properties Returns ------- Selected """ super(Selected, self).__init__("selected") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatter.Selected constructor must be a dict or an instance of plotly.graph_objs.scatter.Selected""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatter import selected as v_selected # Initialize validators # --------------------- self._validators["marker"] = v_selected.MarkerValidator() self._validators["textfont"] = v_selected.TextfontValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v _v = arg.pop("textfont", None) self["textfont"] = textfont if textfont is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # autocolorscale # -------------- @property def autocolorscale(self): """ Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. The 'autocolorscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocolorscale"] @autocolorscale.setter def autocolorscale(self, val): self["autocolorscale"] = val # cauto # ----- @property def cauto(self): """ Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. The 'cauto' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["cauto"] @cauto.setter def cauto(self, val): self["cauto"] = val # cmax # ---- @property def cmax(self): """ Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. The 'cmax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmax"] @cmax.setter def cmax(self, val): self["cmax"] = val # cmid # ---- @property def cmid(self): """ Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. The 'cmid' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmid"] @cmid.setter def cmid(self, val): self["cmid"] = val # cmin # ---- @property def cmin(self): """ Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. The 'cmin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmin"] @cmin.setter def cmin(self, val): self["cmin"] = val # color # ----- @property def color(self): """ Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A number that will be interpreted as a color according to scatter.marker.colorscale - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # coloraxis # --------- @property def coloraxis(self): """ Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. The 'coloraxis' property is an identifier of a particular subplot, of type 'coloraxis', that may be specified as the string 'coloraxis' optionally followed by an integer >= 1 (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) Returns ------- str """ return self["coloraxis"] @coloraxis.setter def coloraxis(self, val): self["coloraxis"] = val # colorbar # -------- @property def colorbar(self): """ The 'colorbar' property is an instance of ColorBar that may be specified as: - An instance of plotly.graph_objs.scatter.marker.ColorBar - A dict of string/value properties that will be passed to the ColorBar constructor Supported dict properties: bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.scatter.marker. colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.scatter.marker.colorbar.tickformatstopdefault s), sets the default property values to use for elements of scatter.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.scatter.marker.colorbar.Ti tle instance or dict with compatible properties titlefont Deprecated: Please use scatter.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use scatter.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- plotly.graph_objs.scatter.marker.ColorBar """ return self["colorbar"] @colorbar.setter def colorbar(self, val): self["colorbar"] = val # colorscale # ---------- @property def colorscale(self): """ Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnB u,Greens,YlOrRd,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland ,Jet,Hot,Blackbody,Earth,Electric,Viridis,Cividis. The 'colorscale' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # gradient # -------- @property def gradient(self): """ The 'gradient' property is an instance of Gradient that may be specified as: - An instance of plotly.graph_objs.scatter.marker.Gradient - A dict of string/value properties that will be passed to the Gradient constructor Supported dict properties: color Sets the final color of the gradient fill: the center color for radial, the right for horizontal, or the bottom for vertical. colorsrc Sets the source reference on plot.ly for color . type Sets the type of gradient used to fill the markers typesrc Sets the source reference on plot.ly for type . Returns ------- plotly.graph_objs.scatter.marker.Gradient """ return self["gradient"] @gradient.setter def gradient(self, val): self["gradient"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.scatter.marker.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,R eds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Black body,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . Returns ------- plotly.graph_objs.scatter.marker.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # maxdisplayed # ------------ @property def maxdisplayed(self): """ Sets a maximum number of points to be drawn on the graph. 0 corresponds to no limit. The 'maxdisplayed' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["maxdisplayed"] @maxdisplayed.setter def maxdisplayed(self, val): self["maxdisplayed"] = val # opacity # ------- @property def opacity(self): """ Sets the marker opacity. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # opacitysrc # ---------- @property def opacitysrc(self): """ Sets the source reference on plot.ly for opacity . The 'opacitysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["opacitysrc"] @opacitysrc.setter def opacitysrc(self, val): self["opacitysrc"] = val # reversescale # ------------ @property def reversescale(self): """ Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. The 'reversescale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["reversescale"] @reversescale.setter def reversescale(self, val): self["reversescale"] = val # showscale # --------- @property def showscale(self): """ Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. The 'showscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showscale"] @showscale.setter def showscale(self, val): self["showscale"] = val # size # ---- @property def size(self): """ Sets the marker size (in px). The 'size' property is a number and may be specified as: - An int or float in the interval [0, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizemin # ------- @property def sizemin(self): """ Has an effect only if `marker.size` is set to a numerical array. Sets the minimum size (in px) of the rendered marker points. The 'sizemin' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["sizemin"] @sizemin.setter def sizemin(self, val): self["sizemin"] = val # sizemode # -------- @property def sizemode(self): """ Has an effect only if `marker.size` is set to a numerical array. Sets the rule for which the data in `size` is converted to pixels. The 'sizemode' property is an enumeration that may be specified as: - One of the following enumeration values: ['diameter', 'area'] Returns ------- Any """ return self["sizemode"] @sizemode.setter def sizemode(self, val): self["sizemode"] = val # sizeref # ------- @property def sizeref(self): """ Has an effect only if `marker.size` is set to a numerical array. Sets the scale factor used to determine the rendered size of marker points. Use with `sizemin` and `sizemode`. The 'sizeref' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["sizeref"] @sizeref.setter def sizeref(self, val): self["sizeref"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # symbol # ------ @property def symbol(self): """ Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot-open" to a symbol name. The 'symbol' property is an enumeration that may be specified as: - One of the following enumeration values: [0, 'circle', 100, 'circle-open', 200, 'circle-dot', 300, 'circle-open-dot', 1, 'square', 101, 'square-open', 201, 'square-dot', 301, 'square-open-dot', 2, 'diamond', 102, 'diamond-open', 202, 'diamond-dot', 302, 'diamond-open-dot', 3, 'cross', 103, 'cross-open', 203, 'cross-dot', 303, 'cross-open-dot', 4, 'x', 104, 'x-open', 204, 'x-dot', 304, 'x-open-dot', 5, 'triangle-up', 105, 'triangle-up-open', 205, 'triangle-up-dot', 305, 'triangle-up-open-dot', 6, 'triangle-down', 106, 'triangle-down-open', 206, 'triangle-down-dot', 306, 'triangle-down-open-dot', 7, 'triangle-left', 107, 'triangle-left-open', 207, 'triangle-left-dot', 307, 'triangle-left-open-dot', 8, 'triangle-right', 108, 'triangle-right-open', 208, 'triangle-right-dot', 308, 'triangle-right-open-dot', 9, 'triangle-ne', 109, 'triangle-ne-open', 209, 'triangle-ne-dot', 309, 'triangle-ne-open-dot', 10, 'triangle-se', 110, 'triangle-se-open', 210, 'triangle-se-dot', 310, 'triangle-se-open-dot', 11, 'triangle-sw', 111, 'triangle-sw-open', 211, 'triangle-sw-dot', 311, 'triangle-sw-open-dot', 12, 'triangle-nw', 112, 'triangle-nw-open', 212, 'triangle-nw-dot', 312, 'triangle-nw-open-dot', 13, 'pentagon', 113, 'pentagon-open', 213, 'pentagon-dot', 313, 'pentagon-open-dot', 14, 'hexagon', 114, 'hexagon-open', 214, 'hexagon-dot', 314, 'hexagon-open-dot', 15, 'hexagon2', 115, 'hexagon2-open', 215, 'hexagon2-dot', 315, 'hexagon2-open-dot', 16, 'octagon', 116, 'octagon-open', 216, 'octagon-dot', 316, 'octagon-open-dot', 17, 'star', 117, 'star-open', 217, 'star-dot', 317, 'star-open-dot', 18, 'hexagram', 118, 'hexagram-open', 218, 'hexagram-dot', 318, 'hexagram-open-dot', 19, 'star-triangle-up', 119, 'star-triangle-up-open', 219, 'star-triangle-up-dot', 319, 'star-triangle-up-open-dot', 20, 'star-triangle-down', 120, 'star-triangle-down-open', 220, 'star-triangle-down-dot', 320, 'star-triangle-down-open-dot', 21, 'star-square', 121, 'star-square-open', 221, 'star-square-dot', 321, 'star-square-open-dot', 22, 'star-diamond', 122, 'star-diamond-open', 222, 'star-diamond-dot', 322, 'star-diamond-open-dot', 23, 'diamond-tall', 123, 'diamond-tall-open', 223, 'diamond-tall-dot', 323, 'diamond-tall-open-dot', 24, 'diamond-wide', 124, 'diamond-wide-open', 224, 'diamond-wide-dot', 324, 'diamond-wide-open-dot', 25, 'hourglass', 125, 'hourglass-open', 26, 'bowtie', 126, 'bowtie-open', 27, 'circle-cross', 127, 'circle-cross-open', 28, 'circle-x', 128, 'circle-x-open', 29, 'square-cross', 129, 'square-cross-open', 30, 'square-x', 130, 'square-x-open', 31, 'diamond-cross', 131, 'diamond-cross-open', 32, 'diamond-x', 132, 'diamond-x-open', 33, 'cross-thin', 133, 'cross-thin-open', 34, 'x-thin', 134, 'x-thin-open', 35, 'asterisk', 135, 'asterisk-open', 36, 'hash', 136, 'hash-open', 236, 'hash-dot', 336, 'hash-open-dot', 37, 'y-up', 137, 'y-up-open', 38, 'y-down', 138, 'y-down-open', 39, 'y-left', 139, 'y-left-open', 40, 'y-right', 140, 'y-right-open', 41, 'line-ew', 141, 'line-ew-open', 42, 'line-ns', 142, 'line-ns-open', 43, 'line-ne', 143, 'line-ne-open', 44, 'line-nw', 144, 'line-nw-open'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["symbol"] @symbol.setter def symbol(self, val): self["symbol"] = val # symbolsrc # --------- @property def symbolsrc(self): """ Sets the source reference on plot.ly for symbol . The 'symbolsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["symbolsrc"] @symbolsrc.setter def symbolsrc(self, val): self["symbolsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatter" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.scatter.marker.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu ,Reds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . gradient plotly.graph_objects.scatter.marker.Gradient instance or dict with compatible properties line plotly.graph_objects.scatter.marker.Line instance or dict with compatible properties maxdisplayed Sets a maximum number of points to be drawn on the graph. 0 corresponds to no limit. opacity Sets the marker opacity. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. size Sets the marker size (in px). sizemin Has an effect only if `marker.size` is set to a numerical array. Sets the minimum size (in px) of the rendered marker points. sizemode Has an effect only if `marker.size` is set to a numerical array. Sets the rule for which the data in `size` is converted to pixels. sizeref Has an effect only if `marker.size` is set to a numerical array. Sets the scale factor used to determine the rendered size of marker points. Use with `sizemin` and `sizemode`. sizesrc Sets the source reference on plot.ly for size . symbol Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot- open" to a symbol name. symbolsrc Sets the source reference on plot.ly for symbol . """ def __init__( self, arg=None, autocolorscale=None, cauto=None, cmax=None, cmid=None, cmin=None, color=None, coloraxis=None, colorbar=None, colorscale=None, colorsrc=None, gradient=None, line=None, maxdisplayed=None, opacity=None, opacitysrc=None, reversescale=None, showscale=None, size=None, sizemin=None, sizemode=None, sizeref=None, sizesrc=None, symbol=None, symbolsrc=None, **kwargs ): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatter.Marker autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.scatter.marker.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu ,Reds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . gradient plotly.graph_objects.scatter.marker.Gradient instance or dict with compatible properties line plotly.graph_objects.scatter.marker.Line instance or dict with compatible properties maxdisplayed Sets a maximum number of points to be drawn on the graph. 0 corresponds to no limit. opacity Sets the marker opacity. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. size Sets the marker size (in px). sizemin Has an effect only if `marker.size` is set to a numerical array. Sets the minimum size (in px) of the rendered marker points. sizemode Has an effect only if `marker.size` is set to a numerical array. Sets the rule for which the data in `size` is converted to pixels. sizeref Has an effect only if `marker.size` is set to a numerical array. Sets the scale factor used to determine the rendered size of marker points. Use with `sizemin` and `sizemode`. sizesrc Sets the source reference on plot.ly for size . symbol Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot- open" to a symbol name. symbolsrc Sets the source reference on plot.ly for symbol . Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatter.Marker constructor must be a dict or an instance of plotly.graph_objs.scatter.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatter import marker as v_marker # Initialize validators # --------------------- self._validators["autocolorscale"] = v_marker.AutocolorscaleValidator() self._validators["cauto"] = v_marker.CautoValidator() self._validators["cmax"] = v_marker.CmaxValidator() self._validators["cmid"] = v_marker.CmidValidator() self._validators["cmin"] = v_marker.CminValidator() self._validators["color"] = v_marker.ColorValidator() self._validators["coloraxis"] = v_marker.ColoraxisValidator() self._validators["colorbar"] = v_marker.ColorBarValidator() self._validators["colorscale"] = v_marker.ColorscaleValidator() self._validators["colorsrc"] = v_marker.ColorsrcValidator() self._validators["gradient"] = v_marker.GradientValidator() self._validators["line"] = v_marker.LineValidator() self._validators["maxdisplayed"] = v_marker.MaxdisplayedValidator() self._validators["opacity"] = v_marker.OpacityValidator() self._validators["opacitysrc"] = v_marker.OpacitysrcValidator() self._validators["reversescale"] = v_marker.ReversescaleValidator() self._validators["showscale"] = v_marker.ShowscaleValidator() self._validators["size"] = v_marker.SizeValidator() self._validators["sizemin"] = v_marker.SizeminValidator() self._validators["sizemode"] = v_marker.SizemodeValidator() self._validators["sizeref"] = v_marker.SizerefValidator() self._validators["sizesrc"] = v_marker.SizesrcValidator() self._validators["symbol"] = v_marker.SymbolValidator() self._validators["symbolsrc"] = v_marker.SymbolsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autocolorscale", None) self["autocolorscale"] = autocolorscale if autocolorscale is not None else _v _v = arg.pop("cauto", None) self["cauto"] = cauto if cauto is not None else _v _v = arg.pop("cmax", None) self["cmax"] = cmax if cmax is not None else _v _v = arg.pop("cmid", None) self["cmid"] = cmid if cmid is not None else _v _v = arg.pop("cmin", None) self["cmin"] = cmin if cmin is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("coloraxis", None) self["coloraxis"] = coloraxis if coloraxis is not None else _v _v = arg.pop("colorbar", None) self["colorbar"] = colorbar if colorbar is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("gradient", None) self["gradient"] = gradient if gradient is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v _v = arg.pop("maxdisplayed", None) self["maxdisplayed"] = maxdisplayed if maxdisplayed is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("opacitysrc", None) self["opacitysrc"] = opacitysrc if opacitysrc is not None else _v _v = arg.pop("reversescale", None) self["reversescale"] = reversescale if reversescale is not None else _v _v = arg.pop("showscale", None) self["showscale"] = showscale if showscale is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizemin", None) self["sizemin"] = sizemin if sizemin is not None else _v _v = arg.pop("sizemode", None) self["sizemode"] = sizemode if sizemode is not None else _v _v = arg.pop("sizeref", None) self["sizeref"] = sizeref if sizeref is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v _v = arg.pop("symbol", None) self["symbol"] = symbol if symbol is not None else _v _v = arg.pop("symbolsrc", None) self["symbolsrc"] = symbolsrc if symbolsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the line color. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # dash # ---- @property def dash(self): """ Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). The 'dash' property is an enumeration that may be specified as: - One of the following dash styles: ['solid', 'dot', 'dash', 'longdash', 'dashdot', 'longdashdot'] - A string containing a dash length list in pixels or percentages (e.g. '5px 10px 2px 2px', '5, 10, 2, 2', '10% 20% 40%', etc.) Returns ------- str """ return self["dash"] @dash.setter def dash(self, val): self["dash"] = val # shape # ----- @property def shape(self): """ Determines the line shape. With "spline" the lines are drawn using spline interpolation. The other available values correspond to step-wise line shapes. The 'shape' property is an enumeration that may be specified as: - One of the following enumeration values: ['linear', 'spline', 'hv', 'vh', 'hvh', 'vhv'] Returns ------- Any """ return self["shape"] @shape.setter def shape(self, val): self["shape"] = val # simplify # -------- @property def simplify(self): """ Simplifies lines by removing nearly-collinear points. When transitioning lines, it may be desirable to disable this so that the number of points along the resulting SVG path is unaffected. The 'simplify' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["simplify"] @simplify.setter def simplify(self, val): self["simplify"] = val # smoothing # --------- @property def smoothing(self): """ Has an effect only if `shape` is set to "spline" Sets the amount of smoothing. 0 corresponds to no smoothing (equivalent to a "linear" shape). The 'smoothing' property is a number and may be specified as: - An int or float in the interval [0, 1.3] Returns ------- int|float """ return self["smoothing"] @smoothing.setter def smoothing(self, val): self["smoothing"] = val # width # ----- @property def width(self): """ Sets the line width (in px). The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatter" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the line color. dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). shape Determines the line shape. With "spline" the lines are drawn using spline interpolation. The other available values correspond to step-wise line shapes. simplify Simplifies lines by removing nearly-collinear points. When transitioning lines, it may be desirable to disable this so that the number of points along the resulting SVG path is unaffected. smoothing Has an effect only if `shape` is set to "spline" Sets the amount of smoothing. 0 corresponds to no smoothing (equivalent to a "linear" shape). width Sets the line width (in px). """ def __init__( self, arg=None, color=None, dash=None, shape=None, simplify=None, smoothing=None, width=None, **kwargs ): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatter.Line color Sets the line color. dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). shape Determines the line shape. With "spline" the lines are drawn using spline interpolation. The other available values correspond to step-wise line shapes. simplify Simplifies lines by removing nearly-collinear points. When transitioning lines, it may be desirable to disable this so that the number of points along the resulting SVG path is unaffected. smoothing Has an effect only if `shape` is set to "spline" Sets the amount of smoothing. 0 corresponds to no smoothing (equivalent to a "linear" shape). width Sets the line width (in px). Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatter.Line constructor must be a dict or an instance of plotly.graph_objs.scatter.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatter import line as v_line # Initialize validators # --------------------- self._validators["color"] = v_line.ColorValidator() self._validators["dash"] = v_line.DashValidator() self._validators["shape"] = v_line.ShapeValidator() self._validators["simplify"] = v_line.SimplifyValidator() self._validators["smoothing"] = v_line.SmoothingValidator() self._validators["width"] = v_line.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("dash", None) self["dash"] = dash if dash is not None else _v _v = arg.pop("shape", None) self["shape"] = shape if shape is not None else _v _v = arg.pop("simplify", None) self["simplify"] = simplify if simplify is not None else _v _v = arg.pop("smoothing", None) self["smoothing"] = smoothing if smoothing is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Hoverlabel(_BaseTraceHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'right', 'auto'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["align"] @align.setter def align(self, val): self["align"] = val # alignsrc # -------- @property def alignsrc(self): """ Sets the source reference on plot.ly for align . The 'alignsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["alignsrc"] @alignsrc.setter def alignsrc(self, val): self["alignsrc"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the hover labels for this trace The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bgcolorsrc # ---------- @property def bgcolorsrc(self): """ Sets the source reference on plot.ly for bgcolor . The 'bgcolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bgcolorsrc"] @bgcolorsrc.setter def bgcolorsrc(self, val): self["bgcolorsrc"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the border color of the hover labels for this trace. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # bordercolorsrc # -------------- @property def bordercolorsrc(self): """ Sets the source reference on plot.ly for bordercolor . The 'bordercolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bordercolorsrc"] @bordercolorsrc.setter def bordercolorsrc(self, val): self["bordercolorsrc"] = val # font # ---- @property def font(self): """ Sets the font used in hover labels. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.scatter.hoverlabel.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.scatter.hoverlabel.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # namelength # ---------- @property def namelength(self): """ Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. The 'namelength' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [-1, 9223372036854775807] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|numpy.ndarray """ return self["namelength"] @namelength.setter def namelength(self, val): self["namelength"] = val # namelengthsrc # ------------- @property def namelengthsrc(self): """ Sets the source reference on plot.ly for namelength . The 'namelengthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["namelengthsrc"] @namelengthsrc.setter def namelengthsrc(self, val): self["namelengthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatter" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """ def __init__( self, arg=None, align=None, alignsrc=None, bgcolor=None, bgcolorsrc=None, bordercolor=None, bordercolorsrc=None, font=None, namelength=None, namelengthsrc=None, **kwargs ): """ Construct a new Hoverlabel object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatter.Hoverlabel align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- Hoverlabel """ super(Hoverlabel, self).__init__("hoverlabel") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatter.Hoverlabel constructor must be a dict or an instance of plotly.graph_objs.scatter.Hoverlabel""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatter import hoverlabel as v_hoverlabel # Initialize validators # --------------------- self._validators["align"] = v_hoverlabel.AlignValidator() self._validators["alignsrc"] = v_hoverlabel.AlignsrcValidator() self._validators["bgcolor"] = v_hoverlabel.BgcolorValidator() self._validators["bgcolorsrc"] = v_hoverlabel.BgcolorsrcValidator() self._validators["bordercolor"] = v_hoverlabel.BordercolorValidator() self._validators["bordercolorsrc"] = v_hoverlabel.BordercolorsrcValidator() self._validators["font"] = v_hoverlabel.FontValidator() self._validators["namelength"] = v_hoverlabel.NamelengthValidator() self._validators["namelengthsrc"] = v_hoverlabel.NamelengthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("alignsrc", None) self["alignsrc"] = alignsrc if alignsrc is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bgcolorsrc", None) self["bgcolorsrc"] = bgcolorsrc if bgcolorsrc is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("bordercolorsrc", None) self["bordercolorsrc"] = bordercolorsrc if bordercolorsrc is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("namelength", None) self["namelength"] = namelength if namelength is not None else _v _v = arg.pop("namelengthsrc", None) self["namelengthsrc"] = namelengthsrc if namelengthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class ErrorY(_BaseTraceHierarchyType): # array # ----- @property def array(self): """ Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. The 'array' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["array"] @array.setter def array(self, val): self["array"] = val # arrayminus # ---------- @property def arrayminus(self): """ Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. The 'arrayminus' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["arrayminus"] @arrayminus.setter def arrayminus(self, val): self["arrayminus"] = val # arrayminussrc # ------------- @property def arrayminussrc(self): """ Sets the source reference on plot.ly for arrayminus . The 'arrayminussrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["arrayminussrc"] @arrayminussrc.setter def arrayminussrc(self, val): self["arrayminussrc"] = val # arraysrc # -------- @property def arraysrc(self): """ Sets the source reference on plot.ly for array . The 'arraysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["arraysrc"] @arraysrc.setter def arraysrc(self, val): self["arraysrc"] = val # color # ----- @property def color(self): """ Sets the stoke color of the error bars. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # symmetric # --------- @property def symmetric(self): """ Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. The 'symmetric' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["symmetric"] @symmetric.setter def symmetric(self, val): self["symmetric"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness (in px) of the error bars. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # traceref # -------- @property def traceref(self): """ The 'traceref' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["traceref"] @traceref.setter def traceref(self, val): self["traceref"] = val # tracerefminus # ------------- @property def tracerefminus(self): """ The 'tracerefminus' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["tracerefminus"] @tracerefminus.setter def tracerefminus(self, val): self["tracerefminus"] = val # type # ---- @property def type(self): """ Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. The 'type' property is an enumeration that may be specified as: - One of the following enumeration values: ['percent', 'constant', 'sqrt', 'data'] Returns ------- Any """ return self["type"] @type.setter def type(self, val): self["type"] = val # value # ----- @property def value(self): """ Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. The 'value' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["value"] @value.setter def value(self, val): self["value"] = val # valueminus # ---------- @property def valueminus(self): """ Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars The 'valueminus' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["valueminus"] @valueminus.setter def valueminus(self, val): self["valueminus"] = val # visible # ------- @property def visible(self): """ Determines whether or not this set of error bars is visible. The 'visible' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # width # ----- @property def width(self): """ Sets the width (in px) of the cross-bar at both ends of the error bars. The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatter" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ array Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. arrayminus Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. arrayminussrc Sets the source reference on plot.ly for arrayminus . arraysrc Sets the source reference on plot.ly for array . color Sets the stoke color of the error bars. symmetric Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. thickness Sets the thickness (in px) of the error bars. traceref tracerefminus type Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. value Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. valueminus Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars visible Determines whether or not this set of error bars is visible. width Sets the width (in px) of the cross-bar at both ends of the error bars. """ def __init__( self, arg=None, array=None, arrayminus=None, arrayminussrc=None, arraysrc=None, color=None, symmetric=None, thickness=None, traceref=None, tracerefminus=None, type=None, value=None, valueminus=None, visible=None, width=None, **kwargs ): """ Construct a new ErrorY object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatter.ErrorY array Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. arrayminus Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. arrayminussrc Sets the source reference on plot.ly for arrayminus . arraysrc Sets the source reference on plot.ly for array . color Sets the stoke color of the error bars. symmetric Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. thickness Sets the thickness (in px) of the error bars. traceref tracerefminus type Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. value Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. valueminus Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars visible Determines whether or not this set of error bars is visible. width Sets the width (in px) of the cross-bar at both ends of the error bars. Returns ------- ErrorY """ super(ErrorY, self).__init__("error_y") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatter.ErrorY constructor must be a dict or an instance of plotly.graph_objs.scatter.ErrorY""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatter import error_y as v_error_y # Initialize validators # --------------------- self._validators["array"] = v_error_y.ArrayValidator() self._validators["arrayminus"] = v_error_y.ArrayminusValidator() self._validators["arrayminussrc"] = v_error_y.ArrayminussrcValidator() self._validators["arraysrc"] = v_error_y.ArraysrcValidator() self._validators["color"] = v_error_y.ColorValidator() self._validators["symmetric"] = v_error_y.SymmetricValidator() self._validators["thickness"] = v_error_y.ThicknessValidator() self._validators["traceref"] = v_error_y.TracerefValidator() self._validators["tracerefminus"] = v_error_y.TracerefminusValidator() self._validators["type"] = v_error_y.TypeValidator() self._validators["value"] = v_error_y.ValueValidator() self._validators["valueminus"] = v_error_y.ValueminusValidator() self._validators["visible"] = v_error_y.VisibleValidator() self._validators["width"] = v_error_y.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("array", None) self["array"] = array if array is not None else _v _v = arg.pop("arrayminus", None) self["arrayminus"] = arrayminus if arrayminus is not None else _v _v = arg.pop("arrayminussrc", None) self["arrayminussrc"] = arrayminussrc if arrayminussrc is not None else _v _v = arg.pop("arraysrc", None) self["arraysrc"] = arraysrc if arraysrc is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("symmetric", None) self["symmetric"] = symmetric if symmetric is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("traceref", None) self["traceref"] = traceref if traceref is not None else _v _v = arg.pop("tracerefminus", None) self["tracerefminus"] = tracerefminus if tracerefminus is not None else _v _v = arg.pop("type", None) self["type"] = type if type is not None else _v _v = arg.pop("value", None) self["value"] = value if value is not None else _v _v = arg.pop("valueminus", None) self["valueminus"] = valueminus if valueminus is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class ErrorX(_BaseTraceHierarchyType): # array # ----- @property def array(self): """ Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. The 'array' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["array"] @array.setter def array(self, val): self["array"] = val # arrayminus # ---------- @property def arrayminus(self): """ Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. The 'arrayminus' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["arrayminus"] @arrayminus.setter def arrayminus(self, val): self["arrayminus"] = val # arrayminussrc # ------------- @property def arrayminussrc(self): """ Sets the source reference on plot.ly for arrayminus . The 'arrayminussrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["arrayminussrc"] @arrayminussrc.setter def arrayminussrc(self, val): self["arrayminussrc"] = val # arraysrc # -------- @property def arraysrc(self): """ Sets the source reference on plot.ly for array . The 'arraysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["arraysrc"] @arraysrc.setter def arraysrc(self, val): self["arraysrc"] = val # color # ----- @property def color(self): """ Sets the stoke color of the error bars. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # copy_ystyle # ----------- @property def copy_ystyle(self): """ The 'copy_ystyle' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["copy_ystyle"] @copy_ystyle.setter def copy_ystyle(self, val): self["copy_ystyle"] = val # symmetric # --------- @property def symmetric(self): """ Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. The 'symmetric' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["symmetric"] @symmetric.setter def symmetric(self, val): self["symmetric"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness (in px) of the error bars. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # traceref # -------- @property def traceref(self): """ The 'traceref' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["traceref"] @traceref.setter def traceref(self, val): self["traceref"] = val # tracerefminus # ------------- @property def tracerefminus(self): """ The 'tracerefminus' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["tracerefminus"] @tracerefminus.setter def tracerefminus(self, val): self["tracerefminus"] = val # type # ---- @property def type(self): """ Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. The 'type' property is an enumeration that may be specified as: - One of the following enumeration values: ['percent', 'constant', 'sqrt', 'data'] Returns ------- Any """ return self["type"] @type.setter def type(self, val): self["type"] = val # value # ----- @property def value(self): """ Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. The 'value' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["value"] @value.setter def value(self, val): self["value"] = val # valueminus # ---------- @property def valueminus(self): """ Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars The 'valueminus' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["valueminus"] @valueminus.setter def valueminus(self, val): self["valueminus"] = val # visible # ------- @property def visible(self): """ Determines whether or not this set of error bars is visible. The 'visible' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # width # ----- @property def width(self): """ Sets the width (in px) of the cross-bar at both ends of the error bars. The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatter" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ array Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. arrayminus Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. arrayminussrc Sets the source reference on plot.ly for arrayminus . arraysrc Sets the source reference on plot.ly for array . color Sets the stoke color of the error bars. copy_ystyle symmetric Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. thickness Sets the thickness (in px) of the error bars. traceref tracerefminus type Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. value Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. valueminus Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars visible Determines whether or not this set of error bars is visible. width Sets the width (in px) of the cross-bar at both ends of the error bars. """ def __init__( self, arg=None, array=None, arrayminus=None, arrayminussrc=None, arraysrc=None, color=None, copy_ystyle=None, symmetric=None, thickness=None, traceref=None, tracerefminus=None, type=None, value=None, valueminus=None, visible=None, width=None, **kwargs ): """ Construct a new ErrorX object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatter.ErrorX array Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. arrayminus Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. arrayminussrc Sets the source reference on plot.ly for arrayminus . arraysrc Sets the source reference on plot.ly for array . color Sets the stoke color of the error bars. copy_ystyle symmetric Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. thickness Sets the thickness (in px) of the error bars. traceref tracerefminus type Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. value Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. valueminus Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars visible Determines whether or not this set of error bars is visible. width Sets the width (in px) of the cross-bar at both ends of the error bars. Returns ------- ErrorX """ super(ErrorX, self).__init__("error_x") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatter.ErrorX constructor must be a dict or an instance of plotly.graph_objs.scatter.ErrorX""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatter import error_x as v_error_x # Initialize validators # --------------------- self._validators["array"] = v_error_x.ArrayValidator() self._validators["arrayminus"] = v_error_x.ArrayminusValidator() self._validators["arrayminussrc"] = v_error_x.ArrayminussrcValidator() self._validators["arraysrc"] = v_error_x.ArraysrcValidator() self._validators["color"] = v_error_x.ColorValidator() self._validators["copy_ystyle"] = v_error_x.CopyYstyleValidator() self._validators["symmetric"] = v_error_x.SymmetricValidator() self._validators["thickness"] = v_error_x.ThicknessValidator() self._validators["traceref"] = v_error_x.TracerefValidator() self._validators["tracerefminus"] = v_error_x.TracerefminusValidator() self._validators["type"] = v_error_x.TypeValidator() self._validators["value"] = v_error_x.ValueValidator() self._validators["valueminus"] = v_error_x.ValueminusValidator() self._validators["visible"] = v_error_x.VisibleValidator() self._validators["width"] = v_error_x.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("array", None) self["array"] = array if array is not None else _v _v = arg.pop("arrayminus", None) self["arrayminus"] = arrayminus if arrayminus is not None else _v _v = arg.pop("arrayminussrc", None) self["arrayminussrc"] = arrayminussrc if arrayminussrc is not None else _v _v = arg.pop("arraysrc", None) self["arraysrc"] = arraysrc if arraysrc is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("copy_ystyle", None) self["copy_ystyle"] = copy_ystyle if copy_ystyle is not None else _v _v = arg.pop("symmetric", None) self["symmetric"] = symmetric if symmetric is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("traceref", None) self["traceref"] = traceref if traceref is not None else _v _v = arg.pop("tracerefminus", None) self["tracerefminus"] = tracerefminus if tracerefminus is not None else _v _v = arg.pop("type", None) self["type"] = type if type is not None else _v _v = arg.pop("value", None) self["value"] = value if value is not None else _v _v = arg.pop("valueminus", None) self["valueminus"] = valueminus if valueminus is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = [ "ErrorX", "ErrorY", "Hoverlabel", "Line", "Marker", "Selected", "Stream", "Textfont", "Unselected", "hoverlabel", "marker", "selected", "unselected", ] from plotly.graph_objs.scatter import unselected from plotly.graph_objs.scatter import selected from plotly.graph_objs.scatter import marker from plotly.graph_objs.scatter import hoverlabel plotly-4.4.1+dfsg.orig/plotly/graph_objs/scatter/selected/0000755000175000017500000000000013573746613023166 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scatter/selected/__init__.py0000644000175000017500000002644613573721550025304 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Textfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the text font color of selected points. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatter.selected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the text font color of selected points. """ def __init__(self, arg=None, color=None, **kwargs): """ Construct a new Textfont object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatter.selected.Textfont color Sets the text font color of selected points. Returns ------- Textfont """ super(Textfont, self).__init__("textfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatter.selected.Textfont constructor must be a dict or an instance of plotly.graph_objs.scatter.selected.Textfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatter.selected import textfont as v_textfont # Initialize validators # --------------------- self._validators["color"] = v_textfont.ColorValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the marker color of selected points. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # opacity # ------- @property def opacity(self): """ Sets the marker opacity of selected points. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # size # ---- @property def size(self): """ Sets the marker size of selected points. The 'size' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatter.selected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. size Sets the marker size of selected points. """ def __init__(self, arg=None, color=None, opacity=None, size=None, **kwargs): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatter.selected.Marker color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. size Sets the marker size of selected points. Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatter.selected.Marker constructor must be a dict or an instance of plotly.graph_objs.scatter.selected.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatter.selected import marker as v_marker # Initialize validators # --------------------- self._validators["color"] = v_marker.ColorValidator() self._validators["opacity"] = v_marker.OpacityValidator() self._validators["size"] = v_marker.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Marker", "Textfont"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/heatmapgl/0000755000175000017500000000000013573746613021673 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/heatmapgl/hoverlabel/0000755000175000017500000000000013573746613024016 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/heatmapgl/hoverlabel/__init__.py0000644000175000017500000002545213573721546026135 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "heatmapgl.hoverlabel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Font object Sets the font used in hover labels. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.heatmapgl.hoverlabel.Font color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.heatmapgl.hoverlabel.Font constructor must be a dict or an instance of plotly.graph_objs.heatmapgl.hoverlabel.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.heatmapgl.hoverlabel import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["colorsrc"] = v_font.ColorsrcValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["familysrc"] = v_font.FamilysrcValidator() self._validators["size"] = v_font.SizeValidator() self._validators["sizesrc"] = v_font.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/heatmapgl/colorbar/0000755000175000017500000000000013573746613023476 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/heatmapgl/colorbar/title/0000755000175000017500000000000013573746613024617 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/heatmapgl/colorbar/title/__init__.py0000644000175000017500000002053713573721546026735 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "heatmapgl.colorbar.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.heatmapgl.colorbar.title.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.heatmapgl.colorbar.title.Font constructor must be a dict or an instance of plotly.graph_objs.heatmapgl.colorbar.title.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.heatmapgl.colorbar.title import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/heatmapgl/colorbar/__init__.py0000644000175000017500000006062213573721546025613 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Title(_BaseTraceHierarchyType): # font # ---- @property def font(self): """ Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.heatmapgl.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.heatmapgl.colorbar.title.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # side # ---- @property def side(self): """ Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- Any """ return self["side"] @side.setter def side(self, val): self["side"] = val # text # ---- @property def text(self): """ Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "heatmapgl.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """ def __init__(self, arg=None, font=None, side=None, text=None, **kwargs): """ Construct a new Title object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.heatmapgl.colorbar.Title font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- Title """ super(Title, self).__init__("title") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.heatmapgl.colorbar.Title constructor must be a dict or an instance of plotly.graph_objs.heatmapgl.colorbar.Title""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.heatmapgl.colorbar import title as v_title # Initialize validators # --------------------- self._validators["font"] = v_title.FontValidator() self._validators["side"] = v_title.SideValidator() self._validators["text"] = v_title.TextValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("side", None) self["side"] = side if side is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickformatstop(_BaseTraceHierarchyType): # dtickrange # ---------- @property def dtickrange(self): """ range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" The 'dtickrange' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'dtickrange[0]' property accepts values of any type (1) The 'dtickrange[1]' property accepts values of any type Returns ------- list """ return self["dtickrange"] @dtickrange.setter def dtickrange(self, val): self["dtickrange"] = val # enabled # ------- @property def enabled(self): """ Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. The 'enabled' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["enabled"] @enabled.setter def enabled(self, val): self["enabled"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # value # ----- @property def value(self): """ string - dtickformat for described zoom level, the same as "tickformat" The 'value' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "heatmapgl.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """ def __init__( self, arg=None, dtickrange=None, enabled=None, name=None, templateitemname=None, value=None, **kwargs ): """ Construct a new Tickformatstop object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.heatmapgl.colorbar.Tickformatstop dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- Tickformatstop """ super(Tickformatstop, self).__init__("tickformatstops") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.heatmapgl.colorbar.Tickformatstop constructor must be a dict or an instance of plotly.graph_objs.heatmapgl.colorbar.Tickformatstop""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.heatmapgl.colorbar import ( tickformatstop as v_tickformatstop, ) # Initialize validators # --------------------- self._validators["dtickrange"] = v_tickformatstop.DtickrangeValidator() self._validators["enabled"] = v_tickformatstop.EnabledValidator() self._validators["name"] = v_tickformatstop.NameValidator() self._validators[ "templateitemname" ] = v_tickformatstop.TemplateitemnameValidator() self._validators["value"] = v_tickformatstop.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtickrange", None) self["dtickrange"] = dtickrange if dtickrange is not None else _v _v = arg.pop("enabled", None) self["enabled"] = enabled if enabled is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "heatmapgl.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Tickfont object Sets the color bar's tick label font Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.heatmapgl.colorbar.Tickfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Tickfont """ super(Tickfont, self).__init__("tickfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.heatmapgl.colorbar.Tickfont constructor must be a dict or an instance of plotly.graph_objs.heatmapgl.colorbar.Tickfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.heatmapgl.colorbar import tickfont as v_tickfont # Initialize validators # --------------------- self._validators["color"] = v_tickfont.ColorValidator() self._validators["family"] = v_tickfont.FamilyValidator() self._validators["size"] = v_tickfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Tickfont", "Tickformatstop", "Tickformatstop", "Title", "title"] from plotly.graph_objs.heatmapgl.colorbar import title plotly-4.4.1+dfsg.orig/plotly/graph_objs/heatmapgl/__init__.py0000644000175000017500000026214613573721547024016 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Stream(_BaseTraceHierarchyType): # maxpoints # --------- @property def maxpoints(self): """ Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. The 'maxpoints' property is a number and may be specified as: - An int or float in the interval [0, 10000] Returns ------- int|float """ return self["maxpoints"] @maxpoints.setter def maxpoints(self, val): self["maxpoints"] = val # token # ----- @property def token(self): """ The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. The 'token' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["token"] @token.setter def token(self, val): self["token"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "heatmapgl" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """ def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): """ Construct a new Stream object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.heatmapgl.Stream maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- Stream """ super(Stream, self).__init__("stream") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.heatmapgl.Stream constructor must be a dict or an instance of plotly.graph_objs.heatmapgl.Stream""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.heatmapgl import stream as v_stream # Initialize validators # --------------------- self._validators["maxpoints"] = v_stream.MaxpointsValidator() self._validators["token"] = v_stream.TokenValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("maxpoints", None) self["maxpoints"] = maxpoints if maxpoints is not None else _v _v = arg.pop("token", None) self["token"] = token if token is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Hoverlabel(_BaseTraceHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'right', 'auto'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["align"] @align.setter def align(self, val): self["align"] = val # alignsrc # -------- @property def alignsrc(self): """ Sets the source reference on plot.ly for align . The 'alignsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["alignsrc"] @alignsrc.setter def alignsrc(self, val): self["alignsrc"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the hover labels for this trace The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bgcolorsrc # ---------- @property def bgcolorsrc(self): """ Sets the source reference on plot.ly for bgcolor . The 'bgcolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bgcolorsrc"] @bgcolorsrc.setter def bgcolorsrc(self, val): self["bgcolorsrc"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the border color of the hover labels for this trace. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # bordercolorsrc # -------------- @property def bordercolorsrc(self): """ Sets the source reference on plot.ly for bordercolor . The 'bordercolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bordercolorsrc"] @bordercolorsrc.setter def bordercolorsrc(self, val): self["bordercolorsrc"] = val # font # ---- @property def font(self): """ Sets the font used in hover labels. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.heatmapgl.hoverlabel.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.heatmapgl.hoverlabel.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # namelength # ---------- @property def namelength(self): """ Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. The 'namelength' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [-1, 9223372036854775807] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|numpy.ndarray """ return self["namelength"] @namelength.setter def namelength(self, val): self["namelength"] = val # namelengthsrc # ------------- @property def namelengthsrc(self): """ Sets the source reference on plot.ly for namelength . The 'namelengthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["namelengthsrc"] @namelengthsrc.setter def namelengthsrc(self, val): self["namelengthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "heatmapgl" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """ def __init__( self, arg=None, align=None, alignsrc=None, bgcolor=None, bgcolorsrc=None, bordercolor=None, bordercolorsrc=None, font=None, namelength=None, namelengthsrc=None, **kwargs ): """ Construct a new Hoverlabel object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.heatmapgl.Hoverlabel align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- Hoverlabel """ super(Hoverlabel, self).__init__("hoverlabel") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.heatmapgl.Hoverlabel constructor must be a dict or an instance of plotly.graph_objs.heatmapgl.Hoverlabel""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.heatmapgl import hoverlabel as v_hoverlabel # Initialize validators # --------------------- self._validators["align"] = v_hoverlabel.AlignValidator() self._validators["alignsrc"] = v_hoverlabel.AlignsrcValidator() self._validators["bgcolor"] = v_hoverlabel.BgcolorValidator() self._validators["bgcolorsrc"] = v_hoverlabel.BgcolorsrcValidator() self._validators["bordercolor"] = v_hoverlabel.BordercolorValidator() self._validators["bordercolorsrc"] = v_hoverlabel.BordercolorsrcValidator() self._validators["font"] = v_hoverlabel.FontValidator() self._validators["namelength"] = v_hoverlabel.NamelengthValidator() self._validators["namelengthsrc"] = v_hoverlabel.NamelengthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("alignsrc", None) self["alignsrc"] = alignsrc if alignsrc is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bgcolorsrc", None) self["bgcolorsrc"] = bgcolorsrc if bgcolorsrc is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("bordercolorsrc", None) self["bordercolorsrc"] = bordercolorsrc if bordercolorsrc is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("namelength", None) self["namelength"] = namelength if namelength is not None else _v _v = arg.pop("namelengthsrc", None) self["namelengthsrc"] = namelengthsrc if namelengthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class ColorBar(_BaseTraceHierarchyType): # bgcolor # ------- @property def bgcolor(self): """ Sets the color of padded area. The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the axis line color. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # borderwidth # ----------- @property def borderwidth(self): """ Sets the width (in px) or the border enclosing this color bar. The 'borderwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["borderwidth"] @borderwidth.setter def borderwidth(self, val): self["borderwidth"] = val # dtick # ----- @property def dtick(self): """ Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" The 'dtick' property accepts values of any type Returns ------- Any """ return self["dtick"] @dtick.setter def dtick(self, val): self["dtick"] = val # exponentformat # -------------- @property def exponentformat(self): """ Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. The 'exponentformat' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'e', 'E', 'power', 'SI', 'B'] Returns ------- Any """ return self["exponentformat"] @exponentformat.setter def exponentformat(self, val): self["exponentformat"] = val # len # --- @property def len(self): """ Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. The 'len' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["len"] @len.setter def len(self, val): self["len"] = val # lenmode # ------- @property def lenmode(self): """ Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. The 'lenmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["lenmode"] @lenmode.setter def lenmode(self, val): self["lenmode"] = val # nticks # ------ @property def nticks(self): """ Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". The 'nticks' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nticks"] @nticks.setter def nticks(self, val): self["nticks"] = val # outlinecolor # ------------ @property def outlinecolor(self): """ Sets the axis line color. The 'outlinecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["outlinecolor"] @outlinecolor.setter def outlinecolor(self, val): self["outlinecolor"] = val # outlinewidth # ------------ @property def outlinewidth(self): """ Sets the width (in px) of the axis line. The 'outlinewidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["outlinewidth"] @outlinewidth.setter def outlinewidth(self, val): self["outlinewidth"] = val # separatethousands # ----------------- @property def separatethousands(self): """ If "true", even 4-digit integers are separated The 'separatethousands' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["separatethousands"] @separatethousands.setter def separatethousands(self, val): self["separatethousands"] = val # showexponent # ------------ @property def showexponent(self): """ If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. The 'showexponent' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showexponent"] @showexponent.setter def showexponent(self, val): self["showexponent"] = val # showticklabels # -------------- @property def showticklabels(self): """ Determines whether or not the tick labels are drawn. The 'showticklabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showticklabels"] @showticklabels.setter def showticklabels(self, val): self["showticklabels"] = val # showtickprefix # -------------- @property def showtickprefix(self): """ If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. The 'showtickprefix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showtickprefix"] @showtickprefix.setter def showtickprefix(self, val): self["showtickprefix"] = val # showticksuffix # -------------- @property def showticksuffix(self): """ Same as `showtickprefix` but for tick suffixes. The 'showticksuffix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showticksuffix"] @showticksuffix.setter def showticksuffix(self, val): self["showticksuffix"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # thicknessmode # ------------- @property def thicknessmode(self): """ Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. The 'thicknessmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["thicknessmode"] @thicknessmode.setter def thicknessmode(self, val): self["thicknessmode"] = val # tick0 # ----- @property def tick0(self): """ Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. The 'tick0' property accepts values of any type Returns ------- Any """ return self["tick0"] @tick0.setter def tick0(self, val): self["tick0"] = val # tickangle # --------- @property def tickangle(self): """ Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. The 'tickangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["tickangle"] @tickangle.setter def tickangle(self, val): self["tickangle"] = val # tickcolor # --------- @property def tickcolor(self): """ Sets the tick color. The 'tickcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["tickcolor"] @tickcolor.setter def tickcolor(self, val): self["tickcolor"] = val # tickfont # -------- @property def tickfont(self): """ Sets the color bar's tick label font The 'tickfont' property is an instance of Tickfont that may be specified as: - An instance of plotly.graph_objs.heatmapgl.colorbar.Tickfont - A dict of string/value properties that will be passed to the Tickfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.heatmapgl.colorbar.Tickfont """ return self["tickfont"] @tickfont.setter def tickfont(self, val): self["tickfont"] = val # tickformat # ---------- @property def tickformat(self): """ Sets the tick label formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'tickformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickformat"] @tickformat.setter def tickformat(self, val): self["tickformat"] = val # tickformatstops # --------------- @property def tickformatstops(self): """ The 'tickformatstops' property is a tuple of instances of Tickformatstop that may be specified as: - A list or tuple of instances of plotly.graph_objs.heatmapgl.colorbar.Tickformatstop - A list or tuple of dicts of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- tuple[plotly.graph_objs.heatmapgl.colorbar.Tickformatstop] """ return self["tickformatstops"] @tickformatstops.setter def tickformatstops(self, val): self["tickformatstops"] = val # tickformatstopdefaults # ---------------------- @property def tickformatstopdefaults(self): """ When used in a template (as layout.template.data.heatmapgl.colo rbar.tickformatstopdefaults), sets the default property values to use for elements of heatmapgl.colorbar.tickformatstops The 'tickformatstopdefaults' property is an instance of Tickformatstop that may be specified as: - An instance of plotly.graph_objs.heatmapgl.colorbar.Tickformatstop - A dict of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: Returns ------- plotly.graph_objs.heatmapgl.colorbar.Tickformatstop """ return self["tickformatstopdefaults"] @tickformatstopdefaults.setter def tickformatstopdefaults(self, val): self["tickformatstopdefaults"] = val # ticklen # ------- @property def ticklen(self): """ Sets the tick length (in px). The 'ticklen' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ticklen"] @ticklen.setter def ticklen(self, val): self["ticklen"] = val # tickmode # -------- @property def tickmode(self): """ Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). The 'tickmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'linear', 'array'] Returns ------- Any """ return self["tickmode"] @tickmode.setter def tickmode(self, val): self["tickmode"] = val # tickprefix # ---------- @property def tickprefix(self): """ Sets a tick label prefix. The 'tickprefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickprefix"] @tickprefix.setter def tickprefix(self, val): self["tickprefix"] = val # ticks # ----- @property def ticks(self): """ Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. The 'ticks' property is an enumeration that may be specified as: - One of the following enumeration values: ['outside', 'inside', ''] Returns ------- Any """ return self["ticks"] @ticks.setter def ticks(self, val): self["ticks"] = val # ticksuffix # ---------- @property def ticksuffix(self): """ Sets a tick label suffix. The 'ticksuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ticksuffix"] @ticksuffix.setter def ticksuffix(self, val): self["ticksuffix"] = val # ticktext # -------- @property def ticktext(self): """ Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. The 'ticktext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ticktext"] @ticktext.setter def ticktext(self, val): self["ticktext"] = val # ticktextsrc # ----------- @property def ticktextsrc(self): """ Sets the source reference on plot.ly for ticktext . The 'ticktextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ticktextsrc"] @ticktextsrc.setter def ticktextsrc(self, val): self["ticktextsrc"] = val # tickvals # -------- @property def tickvals(self): """ Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. The 'tickvals' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["tickvals"] @tickvals.setter def tickvals(self, val): self["tickvals"] = val # tickvalssrc # ----------- @property def tickvalssrc(self): """ Sets the source reference on plot.ly for tickvals . The 'tickvalssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tickvalssrc"] @tickvalssrc.setter def tickvalssrc(self, val): self["tickvalssrc"] = val # tickwidth # --------- @property def tickwidth(self): """ Sets the tick width (in px). The 'tickwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["tickwidth"] @tickwidth.setter def tickwidth(self, val): self["tickwidth"] = val # title # ----- @property def title(self): """ The 'title' property is an instance of Title that may be specified as: - An instance of plotly.graph_objs.heatmapgl.colorbar.Title - A dict of string/value properties that will be passed to the Title constructor Supported dict properties: font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- plotly.graph_objs.heatmapgl.colorbar.Title """ return self["title"] @title.setter def title(self, val): self["title"] = val # titlefont # --------- @property def titlefont(self): """ Deprecated: Please use heatmapgl.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.heatmapgl.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- """ return self["titlefont"] @titlefont.setter def titlefont(self, val): self["titlefont"] = val # titleside # --------- @property def titleside(self): """ Deprecated: Please use heatmapgl.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- """ return self["titleside"] @titleside.setter def titleside(self, val): self["titleside"] = val # x # - @property def x(self): """ Sets the x position of the color bar (in plot fraction). The 'x' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["x"] @x.setter def x(self, val): self["x"] = val # xanchor # ------- @property def xanchor(self): """ Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. The 'xanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'center', 'right'] Returns ------- Any """ return self["xanchor"] @xanchor.setter def xanchor(self, val): self["xanchor"] = val # xpad # ---- @property def xpad(self): """ Sets the amount of padding (in px) along the x direction. The 'xpad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["xpad"] @xpad.setter def xpad(self, val): self["xpad"] = val # y # - @property def y(self): """ Sets the y position of the color bar (in plot fraction). The 'y' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["y"] @y.setter def y(self, val): self["y"] = val # yanchor # ------- @property def yanchor(self): """ Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. The 'yanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['top', 'middle', 'bottom'] Returns ------- Any """ return self["yanchor"] @yanchor.setter def yanchor(self, val): self["yanchor"] = val # ypad # ---- @property def ypad(self): """ Sets the amount of padding (in px) along the y direction. The 'ypad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ypad"] @ypad.setter def ypad(self, val): self["ypad"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "heatmapgl" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.heatmapgl.colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.heatma pgl.colorbar.tickformatstopdefaults), sets the default property values to use for elements of heatmapgl.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.heatmapgl.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use heatmapgl.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use heatmapgl.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """ _mapped_properties = { "titlefont": ("title", "font"), "titleside": ("title", "side"), } def __init__( self, arg=None, bgcolor=None, bordercolor=None, borderwidth=None, dtick=None, exponentformat=None, len=None, lenmode=None, nticks=None, outlinecolor=None, outlinewidth=None, separatethousands=None, showexponent=None, showticklabels=None, showtickprefix=None, showticksuffix=None, thickness=None, thicknessmode=None, tick0=None, tickangle=None, tickcolor=None, tickfont=None, tickformat=None, tickformatstops=None, tickformatstopdefaults=None, ticklen=None, tickmode=None, tickprefix=None, ticks=None, ticksuffix=None, ticktext=None, ticktextsrc=None, tickvals=None, tickvalssrc=None, tickwidth=None, title=None, titlefont=None, titleside=None, x=None, xanchor=None, xpad=None, y=None, yanchor=None, ypad=None, **kwargs ): """ Construct a new ColorBar object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.heatmapgl.ColorBar bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.heatmapgl.colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.heatma pgl.colorbar.tickformatstopdefaults), sets the default property values to use for elements of heatmapgl.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.heatmapgl.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use heatmapgl.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use heatmapgl.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- ColorBar """ super(ColorBar, self).__init__("colorbar") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.heatmapgl.ColorBar constructor must be a dict or an instance of plotly.graph_objs.heatmapgl.ColorBar""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.heatmapgl import colorbar as v_colorbar # Initialize validators # --------------------- self._validators["bgcolor"] = v_colorbar.BgcolorValidator() self._validators["bordercolor"] = v_colorbar.BordercolorValidator() self._validators["borderwidth"] = v_colorbar.BorderwidthValidator() self._validators["dtick"] = v_colorbar.DtickValidator() self._validators["exponentformat"] = v_colorbar.ExponentformatValidator() self._validators["len"] = v_colorbar.LenValidator() self._validators["lenmode"] = v_colorbar.LenmodeValidator() self._validators["nticks"] = v_colorbar.NticksValidator() self._validators["outlinecolor"] = v_colorbar.OutlinecolorValidator() self._validators["outlinewidth"] = v_colorbar.OutlinewidthValidator() self._validators["separatethousands"] = v_colorbar.SeparatethousandsValidator() self._validators["showexponent"] = v_colorbar.ShowexponentValidator() self._validators["showticklabels"] = v_colorbar.ShowticklabelsValidator() self._validators["showtickprefix"] = v_colorbar.ShowtickprefixValidator() self._validators["showticksuffix"] = v_colorbar.ShowticksuffixValidator() self._validators["thickness"] = v_colorbar.ThicknessValidator() self._validators["thicknessmode"] = v_colorbar.ThicknessmodeValidator() self._validators["tick0"] = v_colorbar.Tick0Validator() self._validators["tickangle"] = v_colorbar.TickangleValidator() self._validators["tickcolor"] = v_colorbar.TickcolorValidator() self._validators["tickfont"] = v_colorbar.TickfontValidator() self._validators["tickformat"] = v_colorbar.TickformatValidator() self._validators["tickformatstops"] = v_colorbar.TickformatstopsValidator() self._validators[ "tickformatstopdefaults" ] = v_colorbar.TickformatstopValidator() self._validators["ticklen"] = v_colorbar.TicklenValidator() self._validators["tickmode"] = v_colorbar.TickmodeValidator() self._validators["tickprefix"] = v_colorbar.TickprefixValidator() self._validators["ticks"] = v_colorbar.TicksValidator() self._validators["ticksuffix"] = v_colorbar.TicksuffixValidator() self._validators["ticktext"] = v_colorbar.TicktextValidator() self._validators["ticktextsrc"] = v_colorbar.TicktextsrcValidator() self._validators["tickvals"] = v_colorbar.TickvalsValidator() self._validators["tickvalssrc"] = v_colorbar.TickvalssrcValidator() self._validators["tickwidth"] = v_colorbar.TickwidthValidator() self._validators["title"] = v_colorbar.TitleValidator() self._validators["x"] = v_colorbar.XValidator() self._validators["xanchor"] = v_colorbar.XanchorValidator() self._validators["xpad"] = v_colorbar.XpadValidator() self._validators["y"] = v_colorbar.YValidator() self._validators["yanchor"] = v_colorbar.YanchorValidator() self._validators["ypad"] = v_colorbar.YpadValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("borderwidth", None) self["borderwidth"] = borderwidth if borderwidth is not None else _v _v = arg.pop("dtick", None) self["dtick"] = dtick if dtick is not None else _v _v = arg.pop("exponentformat", None) self["exponentformat"] = exponentformat if exponentformat is not None else _v _v = arg.pop("len", None) self["len"] = len if len is not None else _v _v = arg.pop("lenmode", None) self["lenmode"] = lenmode if lenmode is not None else _v _v = arg.pop("nticks", None) self["nticks"] = nticks if nticks is not None else _v _v = arg.pop("outlinecolor", None) self["outlinecolor"] = outlinecolor if outlinecolor is not None else _v _v = arg.pop("outlinewidth", None) self["outlinewidth"] = outlinewidth if outlinewidth is not None else _v _v = arg.pop("separatethousands", None) self["separatethousands"] = ( separatethousands if separatethousands is not None else _v ) _v = arg.pop("showexponent", None) self["showexponent"] = showexponent if showexponent is not None else _v _v = arg.pop("showticklabels", None) self["showticklabels"] = showticklabels if showticklabels is not None else _v _v = arg.pop("showtickprefix", None) self["showtickprefix"] = showtickprefix if showtickprefix is not None else _v _v = arg.pop("showticksuffix", None) self["showticksuffix"] = showticksuffix if showticksuffix is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("thicknessmode", None) self["thicknessmode"] = thicknessmode if thicknessmode is not None else _v _v = arg.pop("tick0", None) self["tick0"] = tick0 if tick0 is not None else _v _v = arg.pop("tickangle", None) self["tickangle"] = tickangle if tickangle is not None else _v _v = arg.pop("tickcolor", None) self["tickcolor"] = tickcolor if tickcolor is not None else _v _v = arg.pop("tickfont", None) self["tickfont"] = tickfont if tickfont is not None else _v _v = arg.pop("tickformat", None) self["tickformat"] = tickformat if tickformat is not None else _v _v = arg.pop("tickformatstops", None) self["tickformatstops"] = tickformatstops if tickformatstops is not None else _v _v = arg.pop("tickformatstopdefaults", None) self["tickformatstopdefaults"] = ( tickformatstopdefaults if tickformatstopdefaults is not None else _v ) _v = arg.pop("ticklen", None) self["ticklen"] = ticklen if ticklen is not None else _v _v = arg.pop("tickmode", None) self["tickmode"] = tickmode if tickmode is not None else _v _v = arg.pop("tickprefix", None) self["tickprefix"] = tickprefix if tickprefix is not None else _v _v = arg.pop("ticks", None) self["ticks"] = ticks if ticks is not None else _v _v = arg.pop("ticksuffix", None) self["ticksuffix"] = ticksuffix if ticksuffix is not None else _v _v = arg.pop("ticktext", None) self["ticktext"] = ticktext if ticktext is not None else _v _v = arg.pop("ticktextsrc", None) self["ticktextsrc"] = ticktextsrc if ticktextsrc is not None else _v _v = arg.pop("tickvals", None) self["tickvals"] = tickvals if tickvals is not None else _v _v = arg.pop("tickvalssrc", None) self["tickvalssrc"] = tickvalssrc if tickvalssrc is not None else _v _v = arg.pop("tickwidth", None) self["tickwidth"] = tickwidth if tickwidth is not None else _v _v = arg.pop("title", None) self["title"] = title if title is not None else _v _v = arg.pop("titlefont", None) _v = titlefont if titlefont is not None else _v if _v is not None: self["titlefont"] = _v _v = arg.pop("titleside", None) _v = titleside if titleside is not None else _v if _v is not None: self["titleside"] = _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xanchor", None) self["xanchor"] = xanchor if xanchor is not None else _v _v = arg.pop("xpad", None) self["xpad"] = xpad if xpad is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("yanchor", None) self["yanchor"] = yanchor if yanchor is not None else _v _v = arg.pop("ypad", None) self["ypad"] = ypad if ypad is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["ColorBar", "Hoverlabel", "Stream", "colorbar", "hoverlabel"] from plotly.graph_objs.heatmapgl import hoverlabel from plotly.graph_objs.heatmapgl import colorbar plotly-4.4.1+dfsg.orig/plotly/graph_objs/violin/0000755000175000017500000000000013573746613021231 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/violin/unselected/0000755000175000017500000000000013573746613023364 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/violin/unselected/__init__.py0000644000175000017500000001545213573721553025500 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the marker color of unselected points, applied only when a selection exists. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # opacity # ------- @property def opacity(self): """ Sets the marker opacity of unselected points, applied only when a selection exists. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # size # ---- @property def size(self): """ Sets the marker size of unselected points, applied only when a selection exists. The 'size' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "violin.unselected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. size Sets the marker size of unselected points, applied only when a selection exists. """ def __init__(self, arg=None, color=None, opacity=None, size=None, **kwargs): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.violin.unselected.Marker color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. size Sets the marker size of unselected points, applied only when a selection exists. Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.violin.unselected.Marker constructor must be a dict or an instance of plotly.graph_objs.violin.unselected.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.violin.unselected import marker as v_marker # Initialize validators # --------------------- self._validators["color"] = v_marker.ColorValidator() self._validators["opacity"] = v_marker.OpacityValidator() self._validators["size"] = v_marker.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Marker"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/violin/hoverlabel/0000755000175000017500000000000013573746613023354 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/violin/hoverlabel/__init__.py0000644000175000017500000002541713573721552025471 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "violin.hoverlabel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Font object Sets the font used in hover labels. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.violin.hoverlabel.Font color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.violin.hoverlabel.Font constructor must be a dict or an instance of plotly.graph_objs.violin.hoverlabel.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.violin.hoverlabel import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["colorsrc"] = v_font.ColorsrcValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["familysrc"] = v_font.FamilysrcValidator() self._validators["size"] = v_font.SizeValidator() self._validators["sizesrc"] = v_font.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/violin/marker/0000755000175000017500000000000013573746613022512 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/violin/marker/__init__.py0000644000175000017500000002510413573721552024620 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # outliercolor # ------------ @property def outliercolor(self): """ Sets the border line color of the outlier sample points. Defaults to marker.color The 'outliercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["outliercolor"] @outliercolor.setter def outliercolor(self, val): self["outliercolor"] = val # outlierwidth # ------------ @property def outlierwidth(self): """ Sets the border line width (in px) of the outlier sample points. The 'outlierwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["outlierwidth"] @outlierwidth.setter def outlierwidth(self, val): self["outlierwidth"] = val # width # ----- @property def width(self): """ Sets the width (in px) of the lines bounding the marker points. The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "violin.marker" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. outliercolor Sets the border line color of the outlier sample points. Defaults to marker.color outlierwidth Sets the border line width (in px) of the outlier sample points. width Sets the width (in px) of the lines bounding the marker points. """ def __init__( self, arg=None, color=None, outliercolor=None, outlierwidth=None, width=None, **kwargs ): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.violin.marker.Line color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. outliercolor Sets the border line color of the outlier sample points. Defaults to marker.color outlierwidth Sets the border line width (in px) of the outlier sample points. width Sets the width (in px) of the lines bounding the marker points. Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.violin.marker.Line constructor must be a dict or an instance of plotly.graph_objs.violin.marker.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.violin.marker import line as v_line # Initialize validators # --------------------- self._validators["color"] = v_line.ColorValidator() self._validators["outliercolor"] = v_line.OutliercolorValidator() self._validators["outlierwidth"] = v_line.OutlierwidthValidator() self._validators["width"] = v_line.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("outliercolor", None) self["outliercolor"] = outliercolor if outliercolor is not None else _v _v = arg.pop("outlierwidth", None) self["outlierwidth"] = outlierwidth if outlierwidth is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Line"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/violin/__init__.py0000644000175000017500000020252313573721553023342 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Unselected(_BaseTraceHierarchyType): # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.violin.unselected.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. size Sets the marker size of unselected points, applied only when a selection exists. Returns ------- plotly.graph_objs.violin.unselected.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "violin" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ marker plotly.graph_objects.violin.unselected.Marker instance or dict with compatible properties """ def __init__(self, arg=None, marker=None, **kwargs): """ Construct a new Unselected object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.violin.Unselected marker plotly.graph_objects.violin.unselected.Marker instance or dict with compatible properties Returns ------- Unselected """ super(Unselected, self).__init__("unselected") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.violin.Unselected constructor must be a dict or an instance of plotly.graph_objs.violin.Unselected""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.violin import unselected as v_unselected # Initialize validators # --------------------- self._validators["marker"] = v_unselected.MarkerValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Stream(_BaseTraceHierarchyType): # maxpoints # --------- @property def maxpoints(self): """ Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. The 'maxpoints' property is a number and may be specified as: - An int or float in the interval [0, 10000] Returns ------- int|float """ return self["maxpoints"] @maxpoints.setter def maxpoints(self, val): self["maxpoints"] = val # token # ----- @property def token(self): """ The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. The 'token' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["token"] @token.setter def token(self, val): self["token"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "violin" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """ def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): """ Construct a new Stream object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.violin.Stream maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- Stream """ super(Stream, self).__init__("stream") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.violin.Stream constructor must be a dict or an instance of plotly.graph_objs.violin.Stream""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.violin import stream as v_stream # Initialize validators # --------------------- self._validators["maxpoints"] = v_stream.MaxpointsValidator() self._validators["token"] = v_stream.TokenValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("maxpoints", None) self["maxpoints"] = maxpoints if maxpoints is not None else _v _v = arg.pop("token", None) self["token"] = token if token is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Selected(_BaseTraceHierarchyType): # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.violin.selected.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. size Sets the marker size of selected points. Returns ------- plotly.graph_objs.violin.selected.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "violin" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ marker plotly.graph_objects.violin.selected.Marker instance or dict with compatible properties """ def __init__(self, arg=None, marker=None, **kwargs): """ Construct a new Selected object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.violin.Selected marker plotly.graph_objects.violin.selected.Marker instance or dict with compatible properties Returns ------- Selected """ super(Selected, self).__init__("selected") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.violin.Selected constructor must be a dict or an instance of plotly.graph_objs.violin.Selected""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.violin import selected as v_selected # Initialize validators # --------------------- self._validators["marker"] = v_selected.MarkerValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Meanline(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the mean line color. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # visible # ------- @property def visible(self): """ Determines if a line corresponding to the sample's mean is shown inside the violins. If `box.visible` is turned on, the mean line is drawn inside the inner box. Otherwise, the mean line is drawn from one side of the violin to other. The 'visible' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # width # ----- @property def width(self): """ Sets the mean line width. The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "violin" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the mean line color. visible Determines if a line corresponding to the sample's mean is shown inside the violins. If `box.visible` is turned on, the mean line is drawn inside the inner box. Otherwise, the mean line is drawn from one side of the violin to other. width Sets the mean line width. """ def __init__(self, arg=None, color=None, visible=None, width=None, **kwargs): """ Construct a new Meanline object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.violin.Meanline color Sets the mean line color. visible Determines if a line corresponding to the sample's mean is shown inside the violins. If `box.visible` is turned on, the mean line is drawn inside the inner box. Otherwise, the mean line is drawn from one side of the violin to other. width Sets the mean line width. Returns ------- Meanline """ super(Meanline, self).__init__("meanline") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.violin.Meanline constructor must be a dict or an instance of plotly.graph_objs.violin.Meanline""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.violin import meanline as v_meanline # Initialize validators # --------------------- self._validators["color"] = v_meanline.ColorValidator() self._validators["visible"] = v_meanline.VisibleValidator() self._validators["width"] = v_meanline.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.violin.marker.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. outliercolor Sets the border line color of the outlier sample points. Defaults to marker.color outlierwidth Sets the border line width (in px) of the outlier sample points. width Sets the width (in px) of the lines bounding the marker points. Returns ------- plotly.graph_objs.violin.marker.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # opacity # ------- @property def opacity(self): """ Sets the marker opacity. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # outliercolor # ------------ @property def outliercolor(self): """ Sets the color of the outlier sample points. The 'outliercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["outliercolor"] @outliercolor.setter def outliercolor(self, val): self["outliercolor"] = val # size # ---- @property def size(self): """ Sets the marker size (in px). The 'size' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # symbol # ------ @property def symbol(self): """ Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot-open" to a symbol name. The 'symbol' property is an enumeration that may be specified as: - One of the following enumeration values: [0, 'circle', 100, 'circle-open', 200, 'circle-dot', 300, 'circle-open-dot', 1, 'square', 101, 'square-open', 201, 'square-dot', 301, 'square-open-dot', 2, 'diamond', 102, 'diamond-open', 202, 'diamond-dot', 302, 'diamond-open-dot', 3, 'cross', 103, 'cross-open', 203, 'cross-dot', 303, 'cross-open-dot', 4, 'x', 104, 'x-open', 204, 'x-dot', 304, 'x-open-dot', 5, 'triangle-up', 105, 'triangle-up-open', 205, 'triangle-up-dot', 305, 'triangle-up-open-dot', 6, 'triangle-down', 106, 'triangle-down-open', 206, 'triangle-down-dot', 306, 'triangle-down-open-dot', 7, 'triangle-left', 107, 'triangle-left-open', 207, 'triangle-left-dot', 307, 'triangle-left-open-dot', 8, 'triangle-right', 108, 'triangle-right-open', 208, 'triangle-right-dot', 308, 'triangle-right-open-dot', 9, 'triangle-ne', 109, 'triangle-ne-open', 209, 'triangle-ne-dot', 309, 'triangle-ne-open-dot', 10, 'triangle-se', 110, 'triangle-se-open', 210, 'triangle-se-dot', 310, 'triangle-se-open-dot', 11, 'triangle-sw', 111, 'triangle-sw-open', 211, 'triangle-sw-dot', 311, 'triangle-sw-open-dot', 12, 'triangle-nw', 112, 'triangle-nw-open', 212, 'triangle-nw-dot', 312, 'triangle-nw-open-dot', 13, 'pentagon', 113, 'pentagon-open', 213, 'pentagon-dot', 313, 'pentagon-open-dot', 14, 'hexagon', 114, 'hexagon-open', 214, 'hexagon-dot', 314, 'hexagon-open-dot', 15, 'hexagon2', 115, 'hexagon2-open', 215, 'hexagon2-dot', 315, 'hexagon2-open-dot', 16, 'octagon', 116, 'octagon-open', 216, 'octagon-dot', 316, 'octagon-open-dot', 17, 'star', 117, 'star-open', 217, 'star-dot', 317, 'star-open-dot', 18, 'hexagram', 118, 'hexagram-open', 218, 'hexagram-dot', 318, 'hexagram-open-dot', 19, 'star-triangle-up', 119, 'star-triangle-up-open', 219, 'star-triangle-up-dot', 319, 'star-triangle-up-open-dot', 20, 'star-triangle-down', 120, 'star-triangle-down-open', 220, 'star-triangle-down-dot', 320, 'star-triangle-down-open-dot', 21, 'star-square', 121, 'star-square-open', 221, 'star-square-dot', 321, 'star-square-open-dot', 22, 'star-diamond', 122, 'star-diamond-open', 222, 'star-diamond-dot', 322, 'star-diamond-open-dot', 23, 'diamond-tall', 123, 'diamond-tall-open', 223, 'diamond-tall-dot', 323, 'diamond-tall-open-dot', 24, 'diamond-wide', 124, 'diamond-wide-open', 224, 'diamond-wide-dot', 324, 'diamond-wide-open-dot', 25, 'hourglass', 125, 'hourglass-open', 26, 'bowtie', 126, 'bowtie-open', 27, 'circle-cross', 127, 'circle-cross-open', 28, 'circle-x', 128, 'circle-x-open', 29, 'square-cross', 129, 'square-cross-open', 30, 'square-x', 130, 'square-x-open', 31, 'diamond-cross', 131, 'diamond-cross-open', 32, 'diamond-x', 132, 'diamond-x-open', 33, 'cross-thin', 133, 'cross-thin-open', 34, 'x-thin', 134, 'x-thin-open', 35, 'asterisk', 135, 'asterisk-open', 36, 'hash', 136, 'hash-open', 236, 'hash-dot', 336, 'hash-open-dot', 37, 'y-up', 137, 'y-up-open', 38, 'y-down', 138, 'y-down-open', 39, 'y-left', 139, 'y-left-open', 40, 'y-right', 140, 'y-right-open', 41, 'line-ew', 141, 'line-ew-open', 42, 'line-ns', 142, 'line-ns-open', 43, 'line-ne', 143, 'line-ne-open', 44, 'line-nw', 144, 'line-nw-open'] Returns ------- Any """ return self["symbol"] @symbol.setter def symbol(self, val): self["symbol"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "violin" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. line plotly.graph_objects.violin.marker.Line instance or dict with compatible properties opacity Sets the marker opacity. outliercolor Sets the color of the outlier sample points. size Sets the marker size (in px). symbol Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot- open" to a symbol name. """ def __init__( self, arg=None, color=None, line=None, opacity=None, outliercolor=None, size=None, symbol=None, **kwargs ): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.violin.Marker color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. line plotly.graph_objects.violin.marker.Line instance or dict with compatible properties opacity Sets the marker opacity. outliercolor Sets the color of the outlier sample points. size Sets the marker size (in px). symbol Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot- open" to a symbol name. Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.violin.Marker constructor must be a dict or an instance of plotly.graph_objs.violin.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.violin import marker as v_marker # Initialize validators # --------------------- self._validators["color"] = v_marker.ColorValidator() self._validators["line"] = v_marker.LineValidator() self._validators["opacity"] = v_marker.OpacityValidator() self._validators["outliercolor"] = v_marker.OutliercolorValidator() self._validators["size"] = v_marker.SizeValidator() self._validators["symbol"] = v_marker.SymbolValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("outliercolor", None) self["outliercolor"] = outliercolor if outliercolor is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("symbol", None) self["symbol"] = symbol if symbol is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the color of line bounding the violin(s). The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # width # ----- @property def width(self): """ Sets the width (in px) of line bounding the violin(s). The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "violin" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the color of line bounding the violin(s). width Sets the width (in px) of line bounding the violin(s). """ def __init__(self, arg=None, color=None, width=None, **kwargs): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.violin.Line color Sets the color of line bounding the violin(s). width Sets the width (in px) of line bounding the violin(s). Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.violin.Line constructor must be a dict or an instance of plotly.graph_objs.violin.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.violin import line as v_line # Initialize validators # --------------------- self._validators["color"] = v_line.ColorValidator() self._validators["width"] = v_line.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Hoverlabel(_BaseTraceHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'right', 'auto'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["align"] @align.setter def align(self, val): self["align"] = val # alignsrc # -------- @property def alignsrc(self): """ Sets the source reference on plot.ly for align . The 'alignsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["alignsrc"] @alignsrc.setter def alignsrc(self, val): self["alignsrc"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the hover labels for this trace The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bgcolorsrc # ---------- @property def bgcolorsrc(self): """ Sets the source reference on plot.ly for bgcolor . The 'bgcolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bgcolorsrc"] @bgcolorsrc.setter def bgcolorsrc(self, val): self["bgcolorsrc"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the border color of the hover labels for this trace. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # bordercolorsrc # -------------- @property def bordercolorsrc(self): """ Sets the source reference on plot.ly for bordercolor . The 'bordercolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bordercolorsrc"] @bordercolorsrc.setter def bordercolorsrc(self, val): self["bordercolorsrc"] = val # font # ---- @property def font(self): """ Sets the font used in hover labels. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.violin.hoverlabel.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.violin.hoverlabel.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # namelength # ---------- @property def namelength(self): """ Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. The 'namelength' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [-1, 9223372036854775807] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|numpy.ndarray """ return self["namelength"] @namelength.setter def namelength(self, val): self["namelength"] = val # namelengthsrc # ------------- @property def namelengthsrc(self): """ Sets the source reference on plot.ly for namelength . The 'namelengthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["namelengthsrc"] @namelengthsrc.setter def namelengthsrc(self, val): self["namelengthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "violin" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """ def __init__( self, arg=None, align=None, alignsrc=None, bgcolor=None, bgcolorsrc=None, bordercolor=None, bordercolorsrc=None, font=None, namelength=None, namelengthsrc=None, **kwargs ): """ Construct a new Hoverlabel object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.violin.Hoverlabel align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- Hoverlabel """ super(Hoverlabel, self).__init__("hoverlabel") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.violin.Hoverlabel constructor must be a dict or an instance of plotly.graph_objs.violin.Hoverlabel""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.violin import hoverlabel as v_hoverlabel # Initialize validators # --------------------- self._validators["align"] = v_hoverlabel.AlignValidator() self._validators["alignsrc"] = v_hoverlabel.AlignsrcValidator() self._validators["bgcolor"] = v_hoverlabel.BgcolorValidator() self._validators["bgcolorsrc"] = v_hoverlabel.BgcolorsrcValidator() self._validators["bordercolor"] = v_hoverlabel.BordercolorValidator() self._validators["bordercolorsrc"] = v_hoverlabel.BordercolorsrcValidator() self._validators["font"] = v_hoverlabel.FontValidator() self._validators["namelength"] = v_hoverlabel.NamelengthValidator() self._validators["namelengthsrc"] = v_hoverlabel.NamelengthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("alignsrc", None) self["alignsrc"] = alignsrc if alignsrc is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bgcolorsrc", None) self["bgcolorsrc"] = bgcolorsrc if bgcolorsrc is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("bordercolorsrc", None) self["bordercolorsrc"] = bordercolorsrc if bordercolorsrc is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("namelength", None) self["namelength"] = namelength if namelength is not None else _v _v = arg.pop("namelengthsrc", None) self["namelengthsrc"] = namelengthsrc if namelengthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Box(_BaseTraceHierarchyType): # fillcolor # --------- @property def fillcolor(self): """ Sets the inner box plot fill color. The 'fillcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["fillcolor"] @fillcolor.setter def fillcolor(self, val): self["fillcolor"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.violin.box.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: color Sets the inner box plot bounding line color. width Sets the inner box plot bounding line width. Returns ------- plotly.graph_objs.violin.box.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # visible # ------- @property def visible(self): """ Determines if an miniature box plot is drawn inside the violins. The 'visible' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # width # ----- @property def width(self): """ Sets the width of the inner box plots relative to the violins' width. For example, with 1, the inner box plots are as wide as the violins. The 'width' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "violin" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ fillcolor Sets the inner box plot fill color. line plotly.graph_objects.violin.box.Line instance or dict with compatible properties visible Determines if an miniature box plot is drawn inside the violins. width Sets the width of the inner box plots relative to the violins' width. For example, with 1, the inner box plots are as wide as the violins. """ def __init__( self, arg=None, fillcolor=None, line=None, visible=None, width=None, **kwargs ): """ Construct a new Box object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.violin.Box fillcolor Sets the inner box plot fill color. line plotly.graph_objects.violin.box.Line instance or dict with compatible properties visible Determines if an miniature box plot is drawn inside the violins. width Sets the width of the inner box plots relative to the violins' width. For example, with 1, the inner box plots are as wide as the violins. Returns ------- Box """ super(Box, self).__init__("box") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.violin.Box constructor must be a dict or an instance of plotly.graph_objs.violin.Box""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.violin import box as v_box # Initialize validators # --------------------- self._validators["fillcolor"] = v_box.FillcolorValidator() self._validators["line"] = v_box.LineValidator() self._validators["visible"] = v_box.VisibleValidator() self._validators["width"] = v_box.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("fillcolor", None) self["fillcolor"] = fillcolor if fillcolor is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = [ "Box", "Hoverlabel", "Line", "Marker", "Meanline", "Selected", "Stream", "Unselected", "box", "hoverlabel", "marker", "selected", "unselected", ] from plotly.graph_objs.violin import unselected from plotly.graph_objs.violin import selected from plotly.graph_objs.violin import marker from plotly.graph_objs.violin import hoverlabel from plotly.graph_objs.violin import box plotly-4.4.1+dfsg.orig/plotly/graph_objs/violin/selected/0000755000175000017500000000000013573746613023021 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/violin/selected/__init__.py0000644000175000017500000001451413573721553025133 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the marker color of selected points. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # opacity # ------- @property def opacity(self): """ Sets the marker opacity of selected points. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # size # ---- @property def size(self): """ Sets the marker size of selected points. The 'size' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "violin.selected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. size Sets the marker size of selected points. """ def __init__(self, arg=None, color=None, opacity=None, size=None, **kwargs): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.violin.selected.Marker color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. size Sets the marker size of selected points. Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.violin.selected.Marker constructor must be a dict or an instance of plotly.graph_objs.violin.selected.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.violin.selected import marker as v_marker # Initialize validators # --------------------- self._validators["color"] = v_marker.ColorValidator() self._validators["opacity"] = v_marker.OpacityValidator() self._validators["size"] = v_marker.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Marker"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/violin/box/0000755000175000017500000000000013573746613022021 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/violin/box/__init__.py0000644000175000017500000001311513573721552024126 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the inner box plot bounding line color. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # width # ----- @property def width(self): """ Sets the inner box plot bounding line width. The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "violin.box" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the inner box plot bounding line color. width Sets the inner box plot bounding line width. """ def __init__(self, arg=None, color=None, width=None, **kwargs): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.violin.box.Line color Sets the inner box plot bounding line color. width Sets the inner box plot bounding line width. Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.violin.box.Line constructor must be a dict or an instance of plotly.graph_objs.violin.box.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.violin.box import line as v_line # Initialize validators # --------------------- self._validators["color"] = v_line.ColorValidator() self._validators["width"] = v_line.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Line"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/scattergl/0000755000175000017500000000000013573746613021721 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scattergl/unselected/0000755000175000017500000000000013573746613024054 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scattergl/unselected/__init__.py0000644000175000017500000002765613573721551026177 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Textfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the text font color of unselected points, applied only when a selection exists. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattergl.unselected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the text font color of unselected points, applied only when a selection exists. """ def __init__(self, arg=None, color=None, **kwargs): """ Construct a new Textfont object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattergl.unselected.Textfont color Sets the text font color of unselected points, applied only when a selection exists. Returns ------- Textfont """ super(Textfont, self).__init__("textfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattergl.unselected.Textfont constructor must be a dict or an instance of plotly.graph_objs.scattergl.unselected.Textfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattergl.unselected import textfont as v_textfont # Initialize validators # --------------------- self._validators["color"] = v_textfont.ColorValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the marker color of unselected points, applied only when a selection exists. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # opacity # ------- @property def opacity(self): """ Sets the marker opacity of unselected points, applied only when a selection exists. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # size # ---- @property def size(self): """ Sets the marker size of unselected points, applied only when a selection exists. The 'size' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattergl.unselected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. size Sets the marker size of unselected points, applied only when a selection exists. """ def __init__(self, arg=None, color=None, opacity=None, size=None, **kwargs): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattergl.unselected.Marker color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. size Sets the marker size of unselected points, applied only when a selection exists. Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattergl.unselected.Marker constructor must be a dict or an instance of plotly.graph_objs.scattergl.unselected.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattergl.unselected import marker as v_marker # Initialize validators # --------------------- self._validators["color"] = v_marker.ColorValidator() self._validators["opacity"] = v_marker.OpacityValidator() self._validators["size"] = v_marker.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Marker", "Textfont"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/scattergl/hoverlabel/0000755000175000017500000000000013573746613024044 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scattergl/hoverlabel/__init__.py0000644000175000017500000002545213573721551026157 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattergl.hoverlabel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Font object Sets the font used in hover labels. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattergl.hoverlabel.Font color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattergl.hoverlabel.Font constructor must be a dict or an instance of plotly.graph_objs.scattergl.hoverlabel.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattergl.hoverlabel import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["colorsrc"] = v_font.ColorsrcValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["familysrc"] = v_font.FamilysrcValidator() self._validators["size"] = v_font.SizeValidator() self._validators["sizesrc"] = v_font.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/scattergl/marker/0000755000175000017500000000000013573746613023202 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scattergl/marker/colorbar/0000755000175000017500000000000013573746613025005 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scattergl/marker/colorbar/title/0000755000175000017500000000000013573746613026126 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scattergl/marker/colorbar/title/__init__.py0000644000175000017500000002060213573721551030231 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattergl.marker.colorbar.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattergl.marker.colorbar.title.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattergl.marker.colorbar.title.Font constructor must be a dict or an instance of plotly.graph_objs.scattergl.marker.colorbar.title.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattergl.marker.colorbar.title import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/scattergl/marker/colorbar/__init__.py0000644000175000017500000006102113573721551027110 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Title(_BaseTraceHierarchyType): # font # ---- @property def font(self): """ Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.scattergl.marker.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.scattergl.marker.colorbar.title.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # side # ---- @property def side(self): """ Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- Any """ return self["side"] @side.setter def side(self, val): self["side"] = val # text # ---- @property def text(self): """ Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattergl.marker.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """ def __init__(self, arg=None, font=None, side=None, text=None, **kwargs): """ Construct a new Title object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattergl.marker.colorbar.Title font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- Title """ super(Title, self).__init__("title") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattergl.marker.colorbar.Title constructor must be a dict or an instance of plotly.graph_objs.scattergl.marker.colorbar.Title""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattergl.marker.colorbar import title as v_title # Initialize validators # --------------------- self._validators["font"] = v_title.FontValidator() self._validators["side"] = v_title.SideValidator() self._validators["text"] = v_title.TextValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("side", None) self["side"] = side if side is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickformatstop(_BaseTraceHierarchyType): # dtickrange # ---------- @property def dtickrange(self): """ range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" The 'dtickrange' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'dtickrange[0]' property accepts values of any type (1) The 'dtickrange[1]' property accepts values of any type Returns ------- list """ return self["dtickrange"] @dtickrange.setter def dtickrange(self, val): self["dtickrange"] = val # enabled # ------- @property def enabled(self): """ Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. The 'enabled' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["enabled"] @enabled.setter def enabled(self, val): self["enabled"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # value # ----- @property def value(self): """ string - dtickformat for described zoom level, the same as "tickformat" The 'value' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattergl.marker.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """ def __init__( self, arg=None, dtickrange=None, enabled=None, name=None, templateitemname=None, value=None, **kwargs ): """ Construct a new Tickformatstop object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattergl.marker.color bar.Tickformatstop dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- Tickformatstop """ super(Tickformatstop, self).__init__("tickformatstops") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattergl.marker.colorbar.Tickformatstop constructor must be a dict or an instance of plotly.graph_objs.scattergl.marker.colorbar.Tickformatstop""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattergl.marker.colorbar import ( tickformatstop as v_tickformatstop, ) # Initialize validators # --------------------- self._validators["dtickrange"] = v_tickformatstop.DtickrangeValidator() self._validators["enabled"] = v_tickformatstop.EnabledValidator() self._validators["name"] = v_tickformatstop.NameValidator() self._validators[ "templateitemname" ] = v_tickformatstop.TemplateitemnameValidator() self._validators["value"] = v_tickformatstop.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtickrange", None) self["dtickrange"] = dtickrange if dtickrange is not None else _v _v = arg.pop("enabled", None) self["enabled"] = enabled if enabled is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattergl.marker.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Tickfont object Sets the color bar's tick label font Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattergl.marker.colorbar.Tickfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Tickfont """ super(Tickfont, self).__init__("tickfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattergl.marker.colorbar.Tickfont constructor must be a dict or an instance of plotly.graph_objs.scattergl.marker.colorbar.Tickfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattergl.marker.colorbar import tickfont as v_tickfont # Initialize validators # --------------------- self._validators["color"] = v_tickfont.ColorValidator() self._validators["family"] = v_tickfont.FamilyValidator() self._validators["size"] = v_tickfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Tickfont", "Tickformatstop", "Tickformatstop", "Title", "title"] from plotly.graph_objs.scattergl.marker.colorbar import title plotly-4.4.1+dfsg.orig/plotly/graph_objs/scattergl/marker/__init__.py0000644000175000017500000027054013573721552025316 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # autocolorscale # -------------- @property def autocolorscale(self): """ Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. The 'autocolorscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocolorscale"] @autocolorscale.setter def autocolorscale(self, val): self["autocolorscale"] = val # cauto # ----- @property def cauto(self): """ Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. The 'cauto' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["cauto"] @cauto.setter def cauto(self, val): self["cauto"] = val # cmax # ---- @property def cmax(self): """ Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. The 'cmax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmax"] @cmax.setter def cmax(self, val): self["cmax"] = val # cmid # ---- @property def cmid(self): """ Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. The 'cmid' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmid"] @cmid.setter def cmid(self, val): self["cmid"] = val # cmin # ---- @property def cmin(self): """ Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. The 'cmin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmin"] @cmin.setter def cmin(self, val): self["cmin"] = val # color # ----- @property def color(self): """ Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A number that will be interpreted as a color according to scattergl.marker.line.colorscale - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # coloraxis # --------- @property def coloraxis(self): """ Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. The 'coloraxis' property is an identifier of a particular subplot, of type 'coloraxis', that may be specified as the string 'coloraxis' optionally followed by an integer >= 1 (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) Returns ------- str """ return self["coloraxis"] @coloraxis.setter def coloraxis(self, val): self["coloraxis"] = val # colorscale # ---------- @property def colorscale(self): """ Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,Earth,Electric,Vi ridis,Cividis. The 'colorscale' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # reversescale # ------------ @property def reversescale(self): """ Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. The 'reversescale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["reversescale"] @reversescale.setter def reversescale(self, val): self["reversescale"] = val # width # ----- @property def width(self): """ Sets the width (in px) of the lines bounding the marker points. The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["width"] @width.setter def width(self, val): self["width"] = val # widthsrc # -------- @property def widthsrc(self): """ Sets the source reference on plot.ly for width . The 'widthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["widthsrc"] @widthsrc.setter def widthsrc(self, val): self["widthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattergl.marker" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . """ def __init__( self, arg=None, autocolorscale=None, cauto=None, cmax=None, cmid=None, cmin=None, color=None, coloraxis=None, colorscale=None, colorsrc=None, reversescale=None, width=None, widthsrc=None, **kwargs ): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattergl.marker.Line autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattergl.marker.Line constructor must be a dict or an instance of plotly.graph_objs.scattergl.marker.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattergl.marker import line as v_line # Initialize validators # --------------------- self._validators["autocolorscale"] = v_line.AutocolorscaleValidator() self._validators["cauto"] = v_line.CautoValidator() self._validators["cmax"] = v_line.CmaxValidator() self._validators["cmid"] = v_line.CmidValidator() self._validators["cmin"] = v_line.CminValidator() self._validators["color"] = v_line.ColorValidator() self._validators["coloraxis"] = v_line.ColoraxisValidator() self._validators["colorscale"] = v_line.ColorscaleValidator() self._validators["colorsrc"] = v_line.ColorsrcValidator() self._validators["reversescale"] = v_line.ReversescaleValidator() self._validators["width"] = v_line.WidthValidator() self._validators["widthsrc"] = v_line.WidthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autocolorscale", None) self["autocolorscale"] = autocolorscale if autocolorscale is not None else _v _v = arg.pop("cauto", None) self["cauto"] = cauto if cauto is not None else _v _v = arg.pop("cmax", None) self["cmax"] = cmax if cmax is not None else _v _v = arg.pop("cmid", None) self["cmid"] = cmid if cmid is not None else _v _v = arg.pop("cmin", None) self["cmin"] = cmin if cmin is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("coloraxis", None) self["coloraxis"] = coloraxis if coloraxis is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("reversescale", None) self["reversescale"] = reversescale if reversescale is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v _v = arg.pop("widthsrc", None) self["widthsrc"] = widthsrc if widthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class ColorBar(_BaseTraceHierarchyType): # bgcolor # ------- @property def bgcolor(self): """ Sets the color of padded area. The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the axis line color. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # borderwidth # ----------- @property def borderwidth(self): """ Sets the width (in px) or the border enclosing this color bar. The 'borderwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["borderwidth"] @borderwidth.setter def borderwidth(self, val): self["borderwidth"] = val # dtick # ----- @property def dtick(self): """ Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" The 'dtick' property accepts values of any type Returns ------- Any """ return self["dtick"] @dtick.setter def dtick(self, val): self["dtick"] = val # exponentformat # -------------- @property def exponentformat(self): """ Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. The 'exponentformat' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'e', 'E', 'power', 'SI', 'B'] Returns ------- Any """ return self["exponentformat"] @exponentformat.setter def exponentformat(self, val): self["exponentformat"] = val # len # --- @property def len(self): """ Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. The 'len' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["len"] @len.setter def len(self, val): self["len"] = val # lenmode # ------- @property def lenmode(self): """ Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. The 'lenmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["lenmode"] @lenmode.setter def lenmode(self, val): self["lenmode"] = val # nticks # ------ @property def nticks(self): """ Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". The 'nticks' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nticks"] @nticks.setter def nticks(self, val): self["nticks"] = val # outlinecolor # ------------ @property def outlinecolor(self): """ Sets the axis line color. The 'outlinecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["outlinecolor"] @outlinecolor.setter def outlinecolor(self, val): self["outlinecolor"] = val # outlinewidth # ------------ @property def outlinewidth(self): """ Sets the width (in px) of the axis line. The 'outlinewidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["outlinewidth"] @outlinewidth.setter def outlinewidth(self, val): self["outlinewidth"] = val # separatethousands # ----------------- @property def separatethousands(self): """ If "true", even 4-digit integers are separated The 'separatethousands' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["separatethousands"] @separatethousands.setter def separatethousands(self, val): self["separatethousands"] = val # showexponent # ------------ @property def showexponent(self): """ If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. The 'showexponent' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showexponent"] @showexponent.setter def showexponent(self, val): self["showexponent"] = val # showticklabels # -------------- @property def showticklabels(self): """ Determines whether or not the tick labels are drawn. The 'showticklabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showticklabels"] @showticklabels.setter def showticklabels(self, val): self["showticklabels"] = val # showtickprefix # -------------- @property def showtickprefix(self): """ If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. The 'showtickprefix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showtickprefix"] @showtickprefix.setter def showtickprefix(self, val): self["showtickprefix"] = val # showticksuffix # -------------- @property def showticksuffix(self): """ Same as `showtickprefix` but for tick suffixes. The 'showticksuffix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showticksuffix"] @showticksuffix.setter def showticksuffix(self, val): self["showticksuffix"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # thicknessmode # ------------- @property def thicknessmode(self): """ Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. The 'thicknessmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["thicknessmode"] @thicknessmode.setter def thicknessmode(self, val): self["thicknessmode"] = val # tick0 # ----- @property def tick0(self): """ Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. The 'tick0' property accepts values of any type Returns ------- Any """ return self["tick0"] @tick0.setter def tick0(self, val): self["tick0"] = val # tickangle # --------- @property def tickangle(self): """ Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. The 'tickangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["tickangle"] @tickangle.setter def tickangle(self, val): self["tickangle"] = val # tickcolor # --------- @property def tickcolor(self): """ Sets the tick color. The 'tickcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["tickcolor"] @tickcolor.setter def tickcolor(self, val): self["tickcolor"] = val # tickfont # -------- @property def tickfont(self): """ Sets the color bar's tick label font The 'tickfont' property is an instance of Tickfont that may be specified as: - An instance of plotly.graph_objs.scattergl.marker.colorbar.Tickfont - A dict of string/value properties that will be passed to the Tickfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.scattergl.marker.colorbar.Tickfont """ return self["tickfont"] @tickfont.setter def tickfont(self, val): self["tickfont"] = val # tickformat # ---------- @property def tickformat(self): """ Sets the tick label formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'tickformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickformat"] @tickformat.setter def tickformat(self, val): self["tickformat"] = val # tickformatstops # --------------- @property def tickformatstops(self): """ The 'tickformatstops' property is a tuple of instances of Tickformatstop that may be specified as: - A list or tuple of instances of plotly.graph_objs.scattergl.marker.colorbar.Tickformatstop - A list or tuple of dicts of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- tuple[plotly.graph_objs.scattergl.marker.colorbar.Tickformatstop] """ return self["tickformatstops"] @tickformatstops.setter def tickformatstops(self, val): self["tickformatstops"] = val # tickformatstopdefaults # ---------------------- @property def tickformatstopdefaults(self): """ When used in a template (as layout.template.data.scattergl.mark er.colorbar.tickformatstopdefaults), sets the default property values to use for elements of scattergl.marker.colorbar.tickformatstops The 'tickformatstopdefaults' property is an instance of Tickformatstop that may be specified as: - An instance of plotly.graph_objs.scattergl.marker.colorbar.Tickformatstop - A dict of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: Returns ------- plotly.graph_objs.scattergl.marker.colorbar.Tickformatstop """ return self["tickformatstopdefaults"] @tickformatstopdefaults.setter def tickformatstopdefaults(self, val): self["tickformatstopdefaults"] = val # ticklen # ------- @property def ticklen(self): """ Sets the tick length (in px). The 'ticklen' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ticklen"] @ticklen.setter def ticklen(self, val): self["ticklen"] = val # tickmode # -------- @property def tickmode(self): """ Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). The 'tickmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'linear', 'array'] Returns ------- Any """ return self["tickmode"] @tickmode.setter def tickmode(self, val): self["tickmode"] = val # tickprefix # ---------- @property def tickprefix(self): """ Sets a tick label prefix. The 'tickprefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickprefix"] @tickprefix.setter def tickprefix(self, val): self["tickprefix"] = val # ticks # ----- @property def ticks(self): """ Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. The 'ticks' property is an enumeration that may be specified as: - One of the following enumeration values: ['outside', 'inside', ''] Returns ------- Any """ return self["ticks"] @ticks.setter def ticks(self, val): self["ticks"] = val # ticksuffix # ---------- @property def ticksuffix(self): """ Sets a tick label suffix. The 'ticksuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ticksuffix"] @ticksuffix.setter def ticksuffix(self, val): self["ticksuffix"] = val # ticktext # -------- @property def ticktext(self): """ Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. The 'ticktext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ticktext"] @ticktext.setter def ticktext(self, val): self["ticktext"] = val # ticktextsrc # ----------- @property def ticktextsrc(self): """ Sets the source reference on plot.ly for ticktext . The 'ticktextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ticktextsrc"] @ticktextsrc.setter def ticktextsrc(self, val): self["ticktextsrc"] = val # tickvals # -------- @property def tickvals(self): """ Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. The 'tickvals' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["tickvals"] @tickvals.setter def tickvals(self, val): self["tickvals"] = val # tickvalssrc # ----------- @property def tickvalssrc(self): """ Sets the source reference on plot.ly for tickvals . The 'tickvalssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tickvalssrc"] @tickvalssrc.setter def tickvalssrc(self, val): self["tickvalssrc"] = val # tickwidth # --------- @property def tickwidth(self): """ Sets the tick width (in px). The 'tickwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["tickwidth"] @tickwidth.setter def tickwidth(self, val): self["tickwidth"] = val # title # ----- @property def title(self): """ The 'title' property is an instance of Title that may be specified as: - An instance of plotly.graph_objs.scattergl.marker.colorbar.Title - A dict of string/value properties that will be passed to the Title constructor Supported dict properties: font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- plotly.graph_objs.scattergl.marker.colorbar.Title """ return self["title"] @title.setter def title(self, val): self["title"] = val # titlefont # --------- @property def titlefont(self): """ Deprecated: Please use scattergl.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.scattergl.marker.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- """ return self["titlefont"] @titlefont.setter def titlefont(self, val): self["titlefont"] = val # titleside # --------- @property def titleside(self): """ Deprecated: Please use scattergl.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- """ return self["titleside"] @titleside.setter def titleside(self, val): self["titleside"] = val # x # - @property def x(self): """ Sets the x position of the color bar (in plot fraction). The 'x' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["x"] @x.setter def x(self, val): self["x"] = val # xanchor # ------- @property def xanchor(self): """ Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. The 'xanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'center', 'right'] Returns ------- Any """ return self["xanchor"] @xanchor.setter def xanchor(self, val): self["xanchor"] = val # xpad # ---- @property def xpad(self): """ Sets the amount of padding (in px) along the x direction. The 'xpad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["xpad"] @xpad.setter def xpad(self, val): self["xpad"] = val # y # - @property def y(self): """ Sets the y position of the color bar (in plot fraction). The 'y' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["y"] @y.setter def y(self, val): self["y"] = val # yanchor # ------- @property def yanchor(self): """ Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. The 'yanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['top', 'middle', 'bottom'] Returns ------- Any """ return self["yanchor"] @yanchor.setter def yanchor(self, val): self["yanchor"] = val # ypad # ---- @property def ypad(self): """ Sets the amount of padding (in px) along the y direction. The 'ypad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ypad"] @ypad.setter def ypad(self, val): self["ypad"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattergl.marker" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.scattergl.marker.colorb ar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.scatte rgl.marker.colorbar.tickformatstopdefaults), sets the default property values to use for elements of scattergl.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.scattergl.marker.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use scattergl.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use scattergl.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """ _mapped_properties = { "titlefont": ("title", "font"), "titleside": ("title", "side"), } def __init__( self, arg=None, bgcolor=None, bordercolor=None, borderwidth=None, dtick=None, exponentformat=None, len=None, lenmode=None, nticks=None, outlinecolor=None, outlinewidth=None, separatethousands=None, showexponent=None, showticklabels=None, showtickprefix=None, showticksuffix=None, thickness=None, thicknessmode=None, tick0=None, tickangle=None, tickcolor=None, tickfont=None, tickformat=None, tickformatstops=None, tickformatstopdefaults=None, ticklen=None, tickmode=None, tickprefix=None, ticks=None, ticksuffix=None, ticktext=None, ticktextsrc=None, tickvals=None, tickvalssrc=None, tickwidth=None, title=None, titlefont=None, titleside=None, x=None, xanchor=None, xpad=None, y=None, yanchor=None, ypad=None, **kwargs ): """ Construct a new ColorBar object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattergl.marker.ColorBar bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.scattergl.marker.colorb ar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.scatte rgl.marker.colorbar.tickformatstopdefaults), sets the default property values to use for elements of scattergl.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.scattergl.marker.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use scattergl.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use scattergl.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- ColorBar """ super(ColorBar, self).__init__("colorbar") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattergl.marker.ColorBar constructor must be a dict or an instance of plotly.graph_objs.scattergl.marker.ColorBar""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattergl.marker import colorbar as v_colorbar # Initialize validators # --------------------- self._validators["bgcolor"] = v_colorbar.BgcolorValidator() self._validators["bordercolor"] = v_colorbar.BordercolorValidator() self._validators["borderwidth"] = v_colorbar.BorderwidthValidator() self._validators["dtick"] = v_colorbar.DtickValidator() self._validators["exponentformat"] = v_colorbar.ExponentformatValidator() self._validators["len"] = v_colorbar.LenValidator() self._validators["lenmode"] = v_colorbar.LenmodeValidator() self._validators["nticks"] = v_colorbar.NticksValidator() self._validators["outlinecolor"] = v_colorbar.OutlinecolorValidator() self._validators["outlinewidth"] = v_colorbar.OutlinewidthValidator() self._validators["separatethousands"] = v_colorbar.SeparatethousandsValidator() self._validators["showexponent"] = v_colorbar.ShowexponentValidator() self._validators["showticklabels"] = v_colorbar.ShowticklabelsValidator() self._validators["showtickprefix"] = v_colorbar.ShowtickprefixValidator() self._validators["showticksuffix"] = v_colorbar.ShowticksuffixValidator() self._validators["thickness"] = v_colorbar.ThicknessValidator() self._validators["thicknessmode"] = v_colorbar.ThicknessmodeValidator() self._validators["tick0"] = v_colorbar.Tick0Validator() self._validators["tickangle"] = v_colorbar.TickangleValidator() self._validators["tickcolor"] = v_colorbar.TickcolorValidator() self._validators["tickfont"] = v_colorbar.TickfontValidator() self._validators["tickformat"] = v_colorbar.TickformatValidator() self._validators["tickformatstops"] = v_colorbar.TickformatstopsValidator() self._validators[ "tickformatstopdefaults" ] = v_colorbar.TickformatstopValidator() self._validators["ticklen"] = v_colorbar.TicklenValidator() self._validators["tickmode"] = v_colorbar.TickmodeValidator() self._validators["tickprefix"] = v_colorbar.TickprefixValidator() self._validators["ticks"] = v_colorbar.TicksValidator() self._validators["ticksuffix"] = v_colorbar.TicksuffixValidator() self._validators["ticktext"] = v_colorbar.TicktextValidator() self._validators["ticktextsrc"] = v_colorbar.TicktextsrcValidator() self._validators["tickvals"] = v_colorbar.TickvalsValidator() self._validators["tickvalssrc"] = v_colorbar.TickvalssrcValidator() self._validators["tickwidth"] = v_colorbar.TickwidthValidator() self._validators["title"] = v_colorbar.TitleValidator() self._validators["x"] = v_colorbar.XValidator() self._validators["xanchor"] = v_colorbar.XanchorValidator() self._validators["xpad"] = v_colorbar.XpadValidator() self._validators["y"] = v_colorbar.YValidator() self._validators["yanchor"] = v_colorbar.YanchorValidator() self._validators["ypad"] = v_colorbar.YpadValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("borderwidth", None) self["borderwidth"] = borderwidth if borderwidth is not None else _v _v = arg.pop("dtick", None) self["dtick"] = dtick if dtick is not None else _v _v = arg.pop("exponentformat", None) self["exponentformat"] = exponentformat if exponentformat is not None else _v _v = arg.pop("len", None) self["len"] = len if len is not None else _v _v = arg.pop("lenmode", None) self["lenmode"] = lenmode if lenmode is not None else _v _v = arg.pop("nticks", None) self["nticks"] = nticks if nticks is not None else _v _v = arg.pop("outlinecolor", None) self["outlinecolor"] = outlinecolor if outlinecolor is not None else _v _v = arg.pop("outlinewidth", None) self["outlinewidth"] = outlinewidth if outlinewidth is not None else _v _v = arg.pop("separatethousands", None) self["separatethousands"] = ( separatethousands if separatethousands is not None else _v ) _v = arg.pop("showexponent", None) self["showexponent"] = showexponent if showexponent is not None else _v _v = arg.pop("showticklabels", None) self["showticklabels"] = showticklabels if showticklabels is not None else _v _v = arg.pop("showtickprefix", None) self["showtickprefix"] = showtickprefix if showtickprefix is not None else _v _v = arg.pop("showticksuffix", None) self["showticksuffix"] = showticksuffix if showticksuffix is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("thicknessmode", None) self["thicknessmode"] = thicknessmode if thicknessmode is not None else _v _v = arg.pop("tick0", None) self["tick0"] = tick0 if tick0 is not None else _v _v = arg.pop("tickangle", None) self["tickangle"] = tickangle if tickangle is not None else _v _v = arg.pop("tickcolor", None) self["tickcolor"] = tickcolor if tickcolor is not None else _v _v = arg.pop("tickfont", None) self["tickfont"] = tickfont if tickfont is not None else _v _v = arg.pop("tickformat", None) self["tickformat"] = tickformat if tickformat is not None else _v _v = arg.pop("tickformatstops", None) self["tickformatstops"] = tickformatstops if tickformatstops is not None else _v _v = arg.pop("tickformatstopdefaults", None) self["tickformatstopdefaults"] = ( tickformatstopdefaults if tickformatstopdefaults is not None else _v ) _v = arg.pop("ticklen", None) self["ticklen"] = ticklen if ticklen is not None else _v _v = arg.pop("tickmode", None) self["tickmode"] = tickmode if tickmode is not None else _v _v = arg.pop("tickprefix", None) self["tickprefix"] = tickprefix if tickprefix is not None else _v _v = arg.pop("ticks", None) self["ticks"] = ticks if ticks is not None else _v _v = arg.pop("ticksuffix", None) self["ticksuffix"] = ticksuffix if ticksuffix is not None else _v _v = arg.pop("ticktext", None) self["ticktext"] = ticktext if ticktext is not None else _v _v = arg.pop("ticktextsrc", None) self["ticktextsrc"] = ticktextsrc if ticktextsrc is not None else _v _v = arg.pop("tickvals", None) self["tickvals"] = tickvals if tickvals is not None else _v _v = arg.pop("tickvalssrc", None) self["tickvalssrc"] = tickvalssrc if tickvalssrc is not None else _v _v = arg.pop("tickwidth", None) self["tickwidth"] = tickwidth if tickwidth is not None else _v _v = arg.pop("title", None) self["title"] = title if title is not None else _v _v = arg.pop("titlefont", None) _v = titlefont if titlefont is not None else _v if _v is not None: self["titlefont"] = _v _v = arg.pop("titleside", None) _v = titleside if titleside is not None else _v if _v is not None: self["titleside"] = _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xanchor", None) self["xanchor"] = xanchor if xanchor is not None else _v _v = arg.pop("xpad", None) self["xpad"] = xpad if xpad is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("yanchor", None) self["yanchor"] = yanchor if yanchor is not None else _v _v = arg.pop("ypad", None) self["ypad"] = ypad if ypad is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["ColorBar", "Line", "colorbar"] from plotly.graph_objs.scattergl.marker import colorbar plotly-4.4.1+dfsg.orig/plotly/graph_objs/scattergl/__init__.py0000644000175000017500000042547313573721553024045 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Unselected(_BaseTraceHierarchyType): # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.scattergl.unselected.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. size Sets the marker size of unselected points, applied only when a selection exists. Returns ------- plotly.graph_objs.scattergl.unselected.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # textfont # -------- @property def textfont(self): """ The 'textfont' property is an instance of Textfont that may be specified as: - An instance of plotly.graph_objs.scattergl.unselected.Textfont - A dict of string/value properties that will be passed to the Textfont constructor Supported dict properties: color Sets the text font color of unselected points, applied only when a selection exists. Returns ------- plotly.graph_objs.scattergl.unselected.Textfont """ return self["textfont"] @textfont.setter def textfont(self, val): self["textfont"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattergl" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ marker plotly.graph_objects.scattergl.unselected.Marker instance or dict with compatible properties textfont plotly.graph_objects.scattergl.unselected.Textfont instance or dict with compatible properties """ def __init__(self, arg=None, marker=None, textfont=None, **kwargs): """ Construct a new Unselected object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattergl.Unselected marker plotly.graph_objects.scattergl.unselected.Marker instance or dict with compatible properties textfont plotly.graph_objects.scattergl.unselected.Textfont instance or dict with compatible properties Returns ------- Unselected """ super(Unselected, self).__init__("unselected") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattergl.Unselected constructor must be a dict or an instance of plotly.graph_objs.scattergl.Unselected""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattergl import unselected as v_unselected # Initialize validators # --------------------- self._validators["marker"] = v_unselected.MarkerValidator() self._validators["textfont"] = v_unselected.TextfontValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v _v = arg.pop("textfont", None) self["textfont"] = textfont if textfont is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Textfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattergl" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Textfont object Sets the text font. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattergl.Textfont color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Textfont """ super(Textfont, self).__init__("textfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattergl.Textfont constructor must be a dict or an instance of plotly.graph_objs.scattergl.Textfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattergl import textfont as v_textfont # Initialize validators # --------------------- self._validators["color"] = v_textfont.ColorValidator() self._validators["colorsrc"] = v_textfont.ColorsrcValidator() self._validators["family"] = v_textfont.FamilyValidator() self._validators["familysrc"] = v_textfont.FamilysrcValidator() self._validators["size"] = v_textfont.SizeValidator() self._validators["sizesrc"] = v_textfont.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Stream(_BaseTraceHierarchyType): # maxpoints # --------- @property def maxpoints(self): """ Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. The 'maxpoints' property is a number and may be specified as: - An int or float in the interval [0, 10000] Returns ------- int|float """ return self["maxpoints"] @maxpoints.setter def maxpoints(self, val): self["maxpoints"] = val # token # ----- @property def token(self): """ The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. The 'token' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["token"] @token.setter def token(self, val): self["token"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattergl" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """ def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): """ Construct a new Stream object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattergl.Stream maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- Stream """ super(Stream, self).__init__("stream") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattergl.Stream constructor must be a dict or an instance of plotly.graph_objs.scattergl.Stream""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattergl import stream as v_stream # Initialize validators # --------------------- self._validators["maxpoints"] = v_stream.MaxpointsValidator() self._validators["token"] = v_stream.TokenValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("maxpoints", None) self["maxpoints"] = maxpoints if maxpoints is not None else _v _v = arg.pop("token", None) self["token"] = token if token is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Selected(_BaseTraceHierarchyType): # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.scattergl.selected.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. size Sets the marker size of selected points. Returns ------- plotly.graph_objs.scattergl.selected.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # textfont # -------- @property def textfont(self): """ The 'textfont' property is an instance of Textfont that may be specified as: - An instance of plotly.graph_objs.scattergl.selected.Textfont - A dict of string/value properties that will be passed to the Textfont constructor Supported dict properties: color Sets the text font color of selected points. Returns ------- plotly.graph_objs.scattergl.selected.Textfont """ return self["textfont"] @textfont.setter def textfont(self, val): self["textfont"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattergl" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ marker plotly.graph_objects.scattergl.selected.Marker instance or dict with compatible properties textfont plotly.graph_objects.scattergl.selected.Textfont instance or dict with compatible properties """ def __init__(self, arg=None, marker=None, textfont=None, **kwargs): """ Construct a new Selected object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattergl.Selected marker plotly.graph_objects.scattergl.selected.Marker instance or dict with compatible properties textfont plotly.graph_objects.scattergl.selected.Textfont instance or dict with compatible properties Returns ------- Selected """ super(Selected, self).__init__("selected") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattergl.Selected constructor must be a dict or an instance of plotly.graph_objs.scattergl.Selected""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattergl import selected as v_selected # Initialize validators # --------------------- self._validators["marker"] = v_selected.MarkerValidator() self._validators["textfont"] = v_selected.TextfontValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v _v = arg.pop("textfont", None) self["textfont"] = textfont if textfont is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # autocolorscale # -------------- @property def autocolorscale(self): """ Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. The 'autocolorscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocolorscale"] @autocolorscale.setter def autocolorscale(self, val): self["autocolorscale"] = val # cauto # ----- @property def cauto(self): """ Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. The 'cauto' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["cauto"] @cauto.setter def cauto(self, val): self["cauto"] = val # cmax # ---- @property def cmax(self): """ Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. The 'cmax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmax"] @cmax.setter def cmax(self, val): self["cmax"] = val # cmid # ---- @property def cmid(self): """ Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. The 'cmid' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmid"] @cmid.setter def cmid(self, val): self["cmid"] = val # cmin # ---- @property def cmin(self): """ Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. The 'cmin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmin"] @cmin.setter def cmin(self, val): self["cmin"] = val # color # ----- @property def color(self): """ Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A number that will be interpreted as a color according to scattergl.marker.colorscale - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # coloraxis # --------- @property def coloraxis(self): """ Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. The 'coloraxis' property is an identifier of a particular subplot, of type 'coloraxis', that may be specified as the string 'coloraxis' optionally followed by an integer >= 1 (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) Returns ------- str """ return self["coloraxis"] @coloraxis.setter def coloraxis(self, val): self["coloraxis"] = val # colorbar # -------- @property def colorbar(self): """ The 'colorbar' property is an instance of ColorBar that may be specified as: - An instance of plotly.graph_objs.scattergl.marker.ColorBar - A dict of string/value properties that will be passed to the ColorBar constructor Supported dict properties: bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.scattergl.marke r.colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.scattergl.marker.colorbar.tickformatstopdefau lts), sets the default property values to use for elements of scattergl.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.scattergl.marker.colorbar. Title instance or dict with compatible properties titlefont Deprecated: Please use scattergl.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use scattergl.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- plotly.graph_objs.scattergl.marker.ColorBar """ return self["colorbar"] @colorbar.setter def colorbar(self, val): self["colorbar"] = val # colorscale # ---------- @property def colorscale(self): """ Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnB u,Greens,YlOrRd,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland ,Jet,Hot,Blackbody,Earth,Electric,Viridis,Cividis. The 'colorscale' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.scattergl.marker.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,R eds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Black body,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . Returns ------- plotly.graph_objs.scattergl.marker.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # opacity # ------- @property def opacity(self): """ Sets the marker opacity. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # opacitysrc # ---------- @property def opacitysrc(self): """ Sets the source reference on plot.ly for opacity . The 'opacitysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["opacitysrc"] @opacitysrc.setter def opacitysrc(self, val): self["opacitysrc"] = val # reversescale # ------------ @property def reversescale(self): """ Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. The 'reversescale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["reversescale"] @reversescale.setter def reversescale(self, val): self["reversescale"] = val # showscale # --------- @property def showscale(self): """ Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. The 'showscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showscale"] @showscale.setter def showscale(self, val): self["showscale"] = val # size # ---- @property def size(self): """ Sets the marker size (in px). The 'size' property is a number and may be specified as: - An int or float in the interval [0, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizemin # ------- @property def sizemin(self): """ Has an effect only if `marker.size` is set to a numerical array. Sets the minimum size (in px) of the rendered marker points. The 'sizemin' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["sizemin"] @sizemin.setter def sizemin(self, val): self["sizemin"] = val # sizemode # -------- @property def sizemode(self): """ Has an effect only if `marker.size` is set to a numerical array. Sets the rule for which the data in `size` is converted to pixels. The 'sizemode' property is an enumeration that may be specified as: - One of the following enumeration values: ['diameter', 'area'] Returns ------- Any """ return self["sizemode"] @sizemode.setter def sizemode(self, val): self["sizemode"] = val # sizeref # ------- @property def sizeref(self): """ Has an effect only if `marker.size` is set to a numerical array. Sets the scale factor used to determine the rendered size of marker points. Use with `sizemin` and `sizemode`. The 'sizeref' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["sizeref"] @sizeref.setter def sizeref(self, val): self["sizeref"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # symbol # ------ @property def symbol(self): """ Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot-open" to a symbol name. The 'symbol' property is an enumeration that may be specified as: - One of the following enumeration values: [0, 'circle', 100, 'circle-open', 200, 'circle-dot', 300, 'circle-open-dot', 1, 'square', 101, 'square-open', 201, 'square-dot', 301, 'square-open-dot', 2, 'diamond', 102, 'diamond-open', 202, 'diamond-dot', 302, 'diamond-open-dot', 3, 'cross', 103, 'cross-open', 203, 'cross-dot', 303, 'cross-open-dot', 4, 'x', 104, 'x-open', 204, 'x-dot', 304, 'x-open-dot', 5, 'triangle-up', 105, 'triangle-up-open', 205, 'triangle-up-dot', 305, 'triangle-up-open-dot', 6, 'triangle-down', 106, 'triangle-down-open', 206, 'triangle-down-dot', 306, 'triangle-down-open-dot', 7, 'triangle-left', 107, 'triangle-left-open', 207, 'triangle-left-dot', 307, 'triangle-left-open-dot', 8, 'triangle-right', 108, 'triangle-right-open', 208, 'triangle-right-dot', 308, 'triangle-right-open-dot', 9, 'triangle-ne', 109, 'triangle-ne-open', 209, 'triangle-ne-dot', 309, 'triangle-ne-open-dot', 10, 'triangle-se', 110, 'triangle-se-open', 210, 'triangle-se-dot', 310, 'triangle-se-open-dot', 11, 'triangle-sw', 111, 'triangle-sw-open', 211, 'triangle-sw-dot', 311, 'triangle-sw-open-dot', 12, 'triangle-nw', 112, 'triangle-nw-open', 212, 'triangle-nw-dot', 312, 'triangle-nw-open-dot', 13, 'pentagon', 113, 'pentagon-open', 213, 'pentagon-dot', 313, 'pentagon-open-dot', 14, 'hexagon', 114, 'hexagon-open', 214, 'hexagon-dot', 314, 'hexagon-open-dot', 15, 'hexagon2', 115, 'hexagon2-open', 215, 'hexagon2-dot', 315, 'hexagon2-open-dot', 16, 'octagon', 116, 'octagon-open', 216, 'octagon-dot', 316, 'octagon-open-dot', 17, 'star', 117, 'star-open', 217, 'star-dot', 317, 'star-open-dot', 18, 'hexagram', 118, 'hexagram-open', 218, 'hexagram-dot', 318, 'hexagram-open-dot', 19, 'star-triangle-up', 119, 'star-triangle-up-open', 219, 'star-triangle-up-dot', 319, 'star-triangle-up-open-dot', 20, 'star-triangle-down', 120, 'star-triangle-down-open', 220, 'star-triangle-down-dot', 320, 'star-triangle-down-open-dot', 21, 'star-square', 121, 'star-square-open', 221, 'star-square-dot', 321, 'star-square-open-dot', 22, 'star-diamond', 122, 'star-diamond-open', 222, 'star-diamond-dot', 322, 'star-diamond-open-dot', 23, 'diamond-tall', 123, 'diamond-tall-open', 223, 'diamond-tall-dot', 323, 'diamond-tall-open-dot', 24, 'diamond-wide', 124, 'diamond-wide-open', 224, 'diamond-wide-dot', 324, 'diamond-wide-open-dot', 25, 'hourglass', 125, 'hourglass-open', 26, 'bowtie', 126, 'bowtie-open', 27, 'circle-cross', 127, 'circle-cross-open', 28, 'circle-x', 128, 'circle-x-open', 29, 'square-cross', 129, 'square-cross-open', 30, 'square-x', 130, 'square-x-open', 31, 'diamond-cross', 131, 'diamond-cross-open', 32, 'diamond-x', 132, 'diamond-x-open', 33, 'cross-thin', 133, 'cross-thin-open', 34, 'x-thin', 134, 'x-thin-open', 35, 'asterisk', 135, 'asterisk-open', 36, 'hash', 136, 'hash-open', 236, 'hash-dot', 336, 'hash-open-dot', 37, 'y-up', 137, 'y-up-open', 38, 'y-down', 138, 'y-down-open', 39, 'y-left', 139, 'y-left-open', 40, 'y-right', 140, 'y-right-open', 41, 'line-ew', 141, 'line-ew-open', 42, 'line-ns', 142, 'line-ns-open', 43, 'line-ne', 143, 'line-ne-open', 44, 'line-nw', 144, 'line-nw-open'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["symbol"] @symbol.setter def symbol(self, val): self["symbol"] = val # symbolsrc # --------- @property def symbolsrc(self): """ Sets the source reference on plot.ly for symbol . The 'symbolsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["symbolsrc"] @symbolsrc.setter def symbolsrc(self, val): self["symbolsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattergl" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.scattergl.marker.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu ,Reds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . line plotly.graph_objects.scattergl.marker.Line instance or dict with compatible properties opacity Sets the marker opacity. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. size Sets the marker size (in px). sizemin Has an effect only if `marker.size` is set to a numerical array. Sets the minimum size (in px) of the rendered marker points. sizemode Has an effect only if `marker.size` is set to a numerical array. Sets the rule for which the data in `size` is converted to pixels. sizeref Has an effect only if `marker.size` is set to a numerical array. Sets the scale factor used to determine the rendered size of marker points. Use with `sizemin` and `sizemode`. sizesrc Sets the source reference on plot.ly for size . symbol Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot- open" to a symbol name. symbolsrc Sets the source reference on plot.ly for symbol . """ def __init__( self, arg=None, autocolorscale=None, cauto=None, cmax=None, cmid=None, cmin=None, color=None, coloraxis=None, colorbar=None, colorscale=None, colorsrc=None, line=None, opacity=None, opacitysrc=None, reversescale=None, showscale=None, size=None, sizemin=None, sizemode=None, sizeref=None, sizesrc=None, symbol=None, symbolsrc=None, **kwargs ): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattergl.Marker autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.scattergl.marker.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu ,Reds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . line plotly.graph_objects.scattergl.marker.Line instance or dict with compatible properties opacity Sets the marker opacity. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. size Sets the marker size (in px). sizemin Has an effect only if `marker.size` is set to a numerical array. Sets the minimum size (in px) of the rendered marker points. sizemode Has an effect only if `marker.size` is set to a numerical array. Sets the rule for which the data in `size` is converted to pixels. sizeref Has an effect only if `marker.size` is set to a numerical array. Sets the scale factor used to determine the rendered size of marker points. Use with `sizemin` and `sizemode`. sizesrc Sets the source reference on plot.ly for size . symbol Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot- open" to a symbol name. symbolsrc Sets the source reference on plot.ly for symbol . Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattergl.Marker constructor must be a dict or an instance of plotly.graph_objs.scattergl.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattergl import marker as v_marker # Initialize validators # --------------------- self._validators["autocolorscale"] = v_marker.AutocolorscaleValidator() self._validators["cauto"] = v_marker.CautoValidator() self._validators["cmax"] = v_marker.CmaxValidator() self._validators["cmid"] = v_marker.CmidValidator() self._validators["cmin"] = v_marker.CminValidator() self._validators["color"] = v_marker.ColorValidator() self._validators["coloraxis"] = v_marker.ColoraxisValidator() self._validators["colorbar"] = v_marker.ColorBarValidator() self._validators["colorscale"] = v_marker.ColorscaleValidator() self._validators["colorsrc"] = v_marker.ColorsrcValidator() self._validators["line"] = v_marker.LineValidator() self._validators["opacity"] = v_marker.OpacityValidator() self._validators["opacitysrc"] = v_marker.OpacitysrcValidator() self._validators["reversescale"] = v_marker.ReversescaleValidator() self._validators["showscale"] = v_marker.ShowscaleValidator() self._validators["size"] = v_marker.SizeValidator() self._validators["sizemin"] = v_marker.SizeminValidator() self._validators["sizemode"] = v_marker.SizemodeValidator() self._validators["sizeref"] = v_marker.SizerefValidator() self._validators["sizesrc"] = v_marker.SizesrcValidator() self._validators["symbol"] = v_marker.SymbolValidator() self._validators["symbolsrc"] = v_marker.SymbolsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autocolorscale", None) self["autocolorscale"] = autocolorscale if autocolorscale is not None else _v _v = arg.pop("cauto", None) self["cauto"] = cauto if cauto is not None else _v _v = arg.pop("cmax", None) self["cmax"] = cmax if cmax is not None else _v _v = arg.pop("cmid", None) self["cmid"] = cmid if cmid is not None else _v _v = arg.pop("cmin", None) self["cmin"] = cmin if cmin is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("coloraxis", None) self["coloraxis"] = coloraxis if coloraxis is not None else _v _v = arg.pop("colorbar", None) self["colorbar"] = colorbar if colorbar is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("opacitysrc", None) self["opacitysrc"] = opacitysrc if opacitysrc is not None else _v _v = arg.pop("reversescale", None) self["reversescale"] = reversescale if reversescale is not None else _v _v = arg.pop("showscale", None) self["showscale"] = showscale if showscale is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizemin", None) self["sizemin"] = sizemin if sizemin is not None else _v _v = arg.pop("sizemode", None) self["sizemode"] = sizemode if sizemode is not None else _v _v = arg.pop("sizeref", None) self["sizeref"] = sizeref if sizeref is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v _v = arg.pop("symbol", None) self["symbol"] = symbol if symbol is not None else _v _v = arg.pop("symbolsrc", None) self["symbolsrc"] = symbolsrc if symbolsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the line color. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # dash # ---- @property def dash(self): """ Sets the style of the lines. The 'dash' property is an enumeration that may be specified as: - One of the following enumeration values: ['solid', 'dot', 'dash', 'longdash', 'dashdot', 'longdashdot'] Returns ------- Any """ return self["dash"] @dash.setter def dash(self, val): self["dash"] = val # shape # ----- @property def shape(self): """ Determines the line shape. The values correspond to step-wise line shapes. The 'shape' property is an enumeration that may be specified as: - One of the following enumeration values: ['linear', 'hv', 'vh', 'hvh', 'vhv'] Returns ------- Any """ return self["shape"] @shape.setter def shape(self, val): self["shape"] = val # width # ----- @property def width(self): """ Sets the line width (in px). The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattergl" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the line color. dash Sets the style of the lines. shape Determines the line shape. The values correspond to step-wise line shapes. width Sets the line width (in px). """ def __init__( self, arg=None, color=None, dash=None, shape=None, width=None, **kwargs ): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattergl.Line color Sets the line color. dash Sets the style of the lines. shape Determines the line shape. The values correspond to step-wise line shapes. width Sets the line width (in px). Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattergl.Line constructor must be a dict or an instance of plotly.graph_objs.scattergl.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattergl import line as v_line # Initialize validators # --------------------- self._validators["color"] = v_line.ColorValidator() self._validators["dash"] = v_line.DashValidator() self._validators["shape"] = v_line.ShapeValidator() self._validators["width"] = v_line.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("dash", None) self["dash"] = dash if dash is not None else _v _v = arg.pop("shape", None) self["shape"] = shape if shape is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Hoverlabel(_BaseTraceHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'right', 'auto'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["align"] @align.setter def align(self, val): self["align"] = val # alignsrc # -------- @property def alignsrc(self): """ Sets the source reference on plot.ly for align . The 'alignsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["alignsrc"] @alignsrc.setter def alignsrc(self, val): self["alignsrc"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the hover labels for this trace The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bgcolorsrc # ---------- @property def bgcolorsrc(self): """ Sets the source reference on plot.ly for bgcolor . The 'bgcolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bgcolorsrc"] @bgcolorsrc.setter def bgcolorsrc(self, val): self["bgcolorsrc"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the border color of the hover labels for this trace. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # bordercolorsrc # -------------- @property def bordercolorsrc(self): """ Sets the source reference on plot.ly for bordercolor . The 'bordercolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bordercolorsrc"] @bordercolorsrc.setter def bordercolorsrc(self, val): self["bordercolorsrc"] = val # font # ---- @property def font(self): """ Sets the font used in hover labels. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.scattergl.hoverlabel.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.scattergl.hoverlabel.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # namelength # ---------- @property def namelength(self): """ Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. The 'namelength' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [-1, 9223372036854775807] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|numpy.ndarray """ return self["namelength"] @namelength.setter def namelength(self, val): self["namelength"] = val # namelengthsrc # ------------- @property def namelengthsrc(self): """ Sets the source reference on plot.ly for namelength . The 'namelengthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["namelengthsrc"] @namelengthsrc.setter def namelengthsrc(self, val): self["namelengthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattergl" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """ def __init__( self, arg=None, align=None, alignsrc=None, bgcolor=None, bgcolorsrc=None, bordercolor=None, bordercolorsrc=None, font=None, namelength=None, namelengthsrc=None, **kwargs ): """ Construct a new Hoverlabel object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattergl.Hoverlabel align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- Hoverlabel """ super(Hoverlabel, self).__init__("hoverlabel") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattergl.Hoverlabel constructor must be a dict or an instance of plotly.graph_objs.scattergl.Hoverlabel""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattergl import hoverlabel as v_hoverlabel # Initialize validators # --------------------- self._validators["align"] = v_hoverlabel.AlignValidator() self._validators["alignsrc"] = v_hoverlabel.AlignsrcValidator() self._validators["bgcolor"] = v_hoverlabel.BgcolorValidator() self._validators["bgcolorsrc"] = v_hoverlabel.BgcolorsrcValidator() self._validators["bordercolor"] = v_hoverlabel.BordercolorValidator() self._validators["bordercolorsrc"] = v_hoverlabel.BordercolorsrcValidator() self._validators["font"] = v_hoverlabel.FontValidator() self._validators["namelength"] = v_hoverlabel.NamelengthValidator() self._validators["namelengthsrc"] = v_hoverlabel.NamelengthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("alignsrc", None) self["alignsrc"] = alignsrc if alignsrc is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bgcolorsrc", None) self["bgcolorsrc"] = bgcolorsrc if bgcolorsrc is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("bordercolorsrc", None) self["bordercolorsrc"] = bordercolorsrc if bordercolorsrc is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("namelength", None) self["namelength"] = namelength if namelength is not None else _v _v = arg.pop("namelengthsrc", None) self["namelengthsrc"] = namelengthsrc if namelengthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class ErrorY(_BaseTraceHierarchyType): # array # ----- @property def array(self): """ Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. The 'array' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["array"] @array.setter def array(self, val): self["array"] = val # arrayminus # ---------- @property def arrayminus(self): """ Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. The 'arrayminus' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["arrayminus"] @arrayminus.setter def arrayminus(self, val): self["arrayminus"] = val # arrayminussrc # ------------- @property def arrayminussrc(self): """ Sets the source reference on plot.ly for arrayminus . The 'arrayminussrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["arrayminussrc"] @arrayminussrc.setter def arrayminussrc(self, val): self["arrayminussrc"] = val # arraysrc # -------- @property def arraysrc(self): """ Sets the source reference on plot.ly for array . The 'arraysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["arraysrc"] @arraysrc.setter def arraysrc(self, val): self["arraysrc"] = val # color # ----- @property def color(self): """ Sets the stoke color of the error bars. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # symmetric # --------- @property def symmetric(self): """ Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. The 'symmetric' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["symmetric"] @symmetric.setter def symmetric(self, val): self["symmetric"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness (in px) of the error bars. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # traceref # -------- @property def traceref(self): """ The 'traceref' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["traceref"] @traceref.setter def traceref(self, val): self["traceref"] = val # tracerefminus # ------------- @property def tracerefminus(self): """ The 'tracerefminus' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["tracerefminus"] @tracerefminus.setter def tracerefminus(self, val): self["tracerefminus"] = val # type # ---- @property def type(self): """ Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. The 'type' property is an enumeration that may be specified as: - One of the following enumeration values: ['percent', 'constant', 'sqrt', 'data'] Returns ------- Any """ return self["type"] @type.setter def type(self, val): self["type"] = val # value # ----- @property def value(self): """ Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. The 'value' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["value"] @value.setter def value(self, val): self["value"] = val # valueminus # ---------- @property def valueminus(self): """ Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars The 'valueminus' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["valueminus"] @valueminus.setter def valueminus(self, val): self["valueminus"] = val # visible # ------- @property def visible(self): """ Determines whether or not this set of error bars is visible. The 'visible' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # width # ----- @property def width(self): """ Sets the width (in px) of the cross-bar at both ends of the error bars. The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattergl" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ array Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. arrayminus Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. arrayminussrc Sets the source reference on plot.ly for arrayminus . arraysrc Sets the source reference on plot.ly for array . color Sets the stoke color of the error bars. symmetric Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. thickness Sets the thickness (in px) of the error bars. traceref tracerefminus type Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. value Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. valueminus Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars visible Determines whether or not this set of error bars is visible. width Sets the width (in px) of the cross-bar at both ends of the error bars. """ def __init__( self, arg=None, array=None, arrayminus=None, arrayminussrc=None, arraysrc=None, color=None, symmetric=None, thickness=None, traceref=None, tracerefminus=None, type=None, value=None, valueminus=None, visible=None, width=None, **kwargs ): """ Construct a new ErrorY object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattergl.ErrorY array Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. arrayminus Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. arrayminussrc Sets the source reference on plot.ly for arrayminus . arraysrc Sets the source reference on plot.ly for array . color Sets the stoke color of the error bars. symmetric Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. thickness Sets the thickness (in px) of the error bars. traceref tracerefminus type Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. value Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. valueminus Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars visible Determines whether or not this set of error bars is visible. width Sets the width (in px) of the cross-bar at both ends of the error bars. Returns ------- ErrorY """ super(ErrorY, self).__init__("error_y") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattergl.ErrorY constructor must be a dict or an instance of plotly.graph_objs.scattergl.ErrorY""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattergl import error_y as v_error_y # Initialize validators # --------------------- self._validators["array"] = v_error_y.ArrayValidator() self._validators["arrayminus"] = v_error_y.ArrayminusValidator() self._validators["arrayminussrc"] = v_error_y.ArrayminussrcValidator() self._validators["arraysrc"] = v_error_y.ArraysrcValidator() self._validators["color"] = v_error_y.ColorValidator() self._validators["symmetric"] = v_error_y.SymmetricValidator() self._validators["thickness"] = v_error_y.ThicknessValidator() self._validators["traceref"] = v_error_y.TracerefValidator() self._validators["tracerefminus"] = v_error_y.TracerefminusValidator() self._validators["type"] = v_error_y.TypeValidator() self._validators["value"] = v_error_y.ValueValidator() self._validators["valueminus"] = v_error_y.ValueminusValidator() self._validators["visible"] = v_error_y.VisibleValidator() self._validators["width"] = v_error_y.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("array", None) self["array"] = array if array is not None else _v _v = arg.pop("arrayminus", None) self["arrayminus"] = arrayminus if arrayminus is not None else _v _v = arg.pop("arrayminussrc", None) self["arrayminussrc"] = arrayminussrc if arrayminussrc is not None else _v _v = arg.pop("arraysrc", None) self["arraysrc"] = arraysrc if arraysrc is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("symmetric", None) self["symmetric"] = symmetric if symmetric is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("traceref", None) self["traceref"] = traceref if traceref is not None else _v _v = arg.pop("tracerefminus", None) self["tracerefminus"] = tracerefminus if tracerefminus is not None else _v _v = arg.pop("type", None) self["type"] = type if type is not None else _v _v = arg.pop("value", None) self["value"] = value if value is not None else _v _v = arg.pop("valueminus", None) self["valueminus"] = valueminus if valueminus is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class ErrorX(_BaseTraceHierarchyType): # array # ----- @property def array(self): """ Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. The 'array' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["array"] @array.setter def array(self, val): self["array"] = val # arrayminus # ---------- @property def arrayminus(self): """ Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. The 'arrayminus' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["arrayminus"] @arrayminus.setter def arrayminus(self, val): self["arrayminus"] = val # arrayminussrc # ------------- @property def arrayminussrc(self): """ Sets the source reference on plot.ly for arrayminus . The 'arrayminussrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["arrayminussrc"] @arrayminussrc.setter def arrayminussrc(self, val): self["arrayminussrc"] = val # arraysrc # -------- @property def arraysrc(self): """ Sets the source reference on plot.ly for array . The 'arraysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["arraysrc"] @arraysrc.setter def arraysrc(self, val): self["arraysrc"] = val # color # ----- @property def color(self): """ Sets the stoke color of the error bars. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # copy_ystyle # ----------- @property def copy_ystyle(self): """ The 'copy_ystyle' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["copy_ystyle"] @copy_ystyle.setter def copy_ystyle(self, val): self["copy_ystyle"] = val # symmetric # --------- @property def symmetric(self): """ Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. The 'symmetric' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["symmetric"] @symmetric.setter def symmetric(self, val): self["symmetric"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness (in px) of the error bars. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # traceref # -------- @property def traceref(self): """ The 'traceref' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["traceref"] @traceref.setter def traceref(self, val): self["traceref"] = val # tracerefminus # ------------- @property def tracerefminus(self): """ The 'tracerefminus' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["tracerefminus"] @tracerefminus.setter def tracerefminus(self, val): self["tracerefminus"] = val # type # ---- @property def type(self): """ Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. The 'type' property is an enumeration that may be specified as: - One of the following enumeration values: ['percent', 'constant', 'sqrt', 'data'] Returns ------- Any """ return self["type"] @type.setter def type(self, val): self["type"] = val # value # ----- @property def value(self): """ Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. The 'value' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["value"] @value.setter def value(self, val): self["value"] = val # valueminus # ---------- @property def valueminus(self): """ Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars The 'valueminus' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["valueminus"] @valueminus.setter def valueminus(self, val): self["valueminus"] = val # visible # ------- @property def visible(self): """ Determines whether or not this set of error bars is visible. The 'visible' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # width # ----- @property def width(self): """ Sets the width (in px) of the cross-bar at both ends of the error bars. The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattergl" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ array Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. arrayminus Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. arrayminussrc Sets the source reference on plot.ly for arrayminus . arraysrc Sets the source reference on plot.ly for array . color Sets the stoke color of the error bars. copy_ystyle symmetric Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. thickness Sets the thickness (in px) of the error bars. traceref tracerefminus type Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. value Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. valueminus Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars visible Determines whether or not this set of error bars is visible. width Sets the width (in px) of the cross-bar at both ends of the error bars. """ def __init__( self, arg=None, array=None, arrayminus=None, arrayminussrc=None, arraysrc=None, color=None, copy_ystyle=None, symmetric=None, thickness=None, traceref=None, tracerefminus=None, type=None, value=None, valueminus=None, visible=None, width=None, **kwargs ): """ Construct a new ErrorX object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattergl.ErrorX array Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. arrayminus Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. arrayminussrc Sets the source reference on plot.ly for arrayminus . arraysrc Sets the source reference on plot.ly for array . color Sets the stoke color of the error bars. copy_ystyle symmetric Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. thickness Sets the thickness (in px) of the error bars. traceref tracerefminus type Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. value Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. valueminus Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars visible Determines whether or not this set of error bars is visible. width Sets the width (in px) of the cross-bar at both ends of the error bars. Returns ------- ErrorX """ super(ErrorX, self).__init__("error_x") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattergl.ErrorX constructor must be a dict or an instance of plotly.graph_objs.scattergl.ErrorX""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattergl import error_x as v_error_x # Initialize validators # --------------------- self._validators["array"] = v_error_x.ArrayValidator() self._validators["arrayminus"] = v_error_x.ArrayminusValidator() self._validators["arrayminussrc"] = v_error_x.ArrayminussrcValidator() self._validators["arraysrc"] = v_error_x.ArraysrcValidator() self._validators["color"] = v_error_x.ColorValidator() self._validators["copy_ystyle"] = v_error_x.CopyYstyleValidator() self._validators["symmetric"] = v_error_x.SymmetricValidator() self._validators["thickness"] = v_error_x.ThicknessValidator() self._validators["traceref"] = v_error_x.TracerefValidator() self._validators["tracerefminus"] = v_error_x.TracerefminusValidator() self._validators["type"] = v_error_x.TypeValidator() self._validators["value"] = v_error_x.ValueValidator() self._validators["valueminus"] = v_error_x.ValueminusValidator() self._validators["visible"] = v_error_x.VisibleValidator() self._validators["width"] = v_error_x.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("array", None) self["array"] = array if array is not None else _v _v = arg.pop("arrayminus", None) self["arrayminus"] = arrayminus if arrayminus is not None else _v _v = arg.pop("arrayminussrc", None) self["arrayminussrc"] = arrayminussrc if arrayminussrc is not None else _v _v = arg.pop("arraysrc", None) self["arraysrc"] = arraysrc if arraysrc is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("copy_ystyle", None) self["copy_ystyle"] = copy_ystyle if copy_ystyle is not None else _v _v = arg.pop("symmetric", None) self["symmetric"] = symmetric if symmetric is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("traceref", None) self["traceref"] = traceref if traceref is not None else _v _v = arg.pop("tracerefminus", None) self["tracerefminus"] = tracerefminus if tracerefminus is not None else _v _v = arg.pop("type", None) self["type"] = type if type is not None else _v _v = arg.pop("value", None) self["value"] = value if value is not None else _v _v = arg.pop("valueminus", None) self["valueminus"] = valueminus if valueminus is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = [ "ErrorX", "ErrorY", "Hoverlabel", "Line", "Marker", "Selected", "Stream", "Textfont", "Unselected", "hoverlabel", "marker", "selected", "unselected", ] from plotly.graph_objs.scattergl import unselected from plotly.graph_objs.scattergl import selected from plotly.graph_objs.scattergl import marker from plotly.graph_objs.scattergl import hoverlabel plotly-4.4.1+dfsg.orig/plotly/graph_objs/scattergl/selected/0000755000175000017500000000000013573746613023511 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scattergl/selected/__init__.py0000644000175000017500000002647213573721551025627 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Textfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the text font color of selected points. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattergl.selected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the text font color of selected points. """ def __init__(self, arg=None, color=None, **kwargs): """ Construct a new Textfont object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattergl.selected.Textfont color Sets the text font color of selected points. Returns ------- Textfont """ super(Textfont, self).__init__("textfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattergl.selected.Textfont constructor must be a dict or an instance of plotly.graph_objs.scattergl.selected.Textfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattergl.selected import textfont as v_textfont # Initialize validators # --------------------- self._validators["color"] = v_textfont.ColorValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the marker color of selected points. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # opacity # ------- @property def opacity(self): """ Sets the marker opacity of selected points. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # size # ---- @property def size(self): """ Sets the marker size of selected points. The 'size' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattergl.selected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. size Sets the marker size of selected points. """ def __init__(self, arg=None, color=None, opacity=None, size=None, **kwargs): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattergl.selected.Marker color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. size Sets the marker size of selected points. Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattergl.selected.Marker constructor must be a dict or an instance of plotly.graph_objs.scattergl.selected.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattergl.selected import marker as v_marker # Initialize validators # --------------------- self._validators["color"] = v_marker.ColorValidator() self._validators["opacity"] = v_marker.OpacityValidator() self._validators["size"] = v_marker.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Marker", "Textfont"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/contour/0000755000175000017500000000000013573746613021422 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/contour/hoverlabel/0000755000175000017500000000000013573746613023545 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/contour/hoverlabel/__init__.py0000644000175000017500000002544013573721546025661 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "contour.hoverlabel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Font object Sets the font used in hover labels. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.contour.hoverlabel.Font color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.contour.hoverlabel.Font constructor must be a dict or an instance of plotly.graph_objs.contour.hoverlabel.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.contour.hoverlabel import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["colorsrc"] = v_font.ColorsrcValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["familysrc"] = v_font.FamilysrcValidator() self._validators["size"] = v_font.SizeValidator() self._validators["sizesrc"] = v_font.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/contour/colorbar/0000755000175000017500000000000013573746613023225 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/contour/colorbar/title/0000755000175000017500000000000013573746613024346 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/contour/colorbar/title/__init__.py0000644000175000017500000002052513573721546026461 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "contour.colorbar.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.contour.colorbar.title.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.contour.colorbar.title.Font constructor must be a dict or an instance of plotly.graph_objs.contour.colorbar.title.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.contour.colorbar.title import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/contour/colorbar/__init__.py0000644000175000017500000006054213573721546025343 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Title(_BaseTraceHierarchyType): # font # ---- @property def font(self): """ Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.contour.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.contour.colorbar.title.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # side # ---- @property def side(self): """ Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- Any """ return self["side"] @side.setter def side(self, val): self["side"] = val # text # ---- @property def text(self): """ Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "contour.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """ def __init__(self, arg=None, font=None, side=None, text=None, **kwargs): """ Construct a new Title object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.contour.colorbar.Title font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- Title """ super(Title, self).__init__("title") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.contour.colorbar.Title constructor must be a dict or an instance of plotly.graph_objs.contour.colorbar.Title""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.contour.colorbar import title as v_title # Initialize validators # --------------------- self._validators["font"] = v_title.FontValidator() self._validators["side"] = v_title.SideValidator() self._validators["text"] = v_title.TextValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("side", None) self["side"] = side if side is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickformatstop(_BaseTraceHierarchyType): # dtickrange # ---------- @property def dtickrange(self): """ range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" The 'dtickrange' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'dtickrange[0]' property accepts values of any type (1) The 'dtickrange[1]' property accepts values of any type Returns ------- list """ return self["dtickrange"] @dtickrange.setter def dtickrange(self, val): self["dtickrange"] = val # enabled # ------- @property def enabled(self): """ Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. The 'enabled' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["enabled"] @enabled.setter def enabled(self, val): self["enabled"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # value # ----- @property def value(self): """ string - dtickformat for described zoom level, the same as "tickformat" The 'value' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "contour.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """ def __init__( self, arg=None, dtickrange=None, enabled=None, name=None, templateitemname=None, value=None, **kwargs ): """ Construct a new Tickformatstop object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.contour.colorbar.Tickformatstop dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- Tickformatstop """ super(Tickformatstop, self).__init__("tickformatstops") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.contour.colorbar.Tickformatstop constructor must be a dict or an instance of plotly.graph_objs.contour.colorbar.Tickformatstop""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.contour.colorbar import ( tickformatstop as v_tickformatstop, ) # Initialize validators # --------------------- self._validators["dtickrange"] = v_tickformatstop.DtickrangeValidator() self._validators["enabled"] = v_tickformatstop.EnabledValidator() self._validators["name"] = v_tickformatstop.NameValidator() self._validators[ "templateitemname" ] = v_tickformatstop.TemplateitemnameValidator() self._validators["value"] = v_tickformatstop.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtickrange", None) self["dtickrange"] = dtickrange if dtickrange is not None else _v _v = arg.pop("enabled", None) self["enabled"] = enabled if enabled is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "contour.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Tickfont object Sets the color bar's tick label font Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.contour.colorbar.Tickfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Tickfont """ super(Tickfont, self).__init__("tickfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.contour.colorbar.Tickfont constructor must be a dict or an instance of plotly.graph_objs.contour.colorbar.Tickfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.contour.colorbar import tickfont as v_tickfont # Initialize validators # --------------------- self._validators["color"] = v_tickfont.ColorValidator() self._validators["family"] = v_tickfont.FamilyValidator() self._validators["size"] = v_tickfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Tickfont", "Tickformatstop", "Tickformatstop", "Title", "title"] from plotly.graph_objs.contour.colorbar import title plotly-4.4.1+dfsg.orig/plotly/graph_objs/contour/contours/0000755000175000017500000000000013573746613023276 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/contour/contours/__init__.py0000644000175000017500000002064713573721546025416 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Labelfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "contour.contours" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Labelfont object Sets the font used for labeling the contour levels. The default color comes from the lines, if shown. The default family and size come from `layout.font`. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.contour.contours.Labelfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Labelfont """ super(Labelfont, self).__init__("labelfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.contour.contours.Labelfont constructor must be a dict or an instance of plotly.graph_objs.contour.contours.Labelfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.contour.contours import labelfont as v_labelfont # Initialize validators # --------------------- self._validators["color"] = v_labelfont.ColorValidator() self._validators["family"] = v_labelfont.FamilyValidator() self._validators["size"] = v_labelfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Labelfont"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/contour/__init__.py0000644000175000017500000034504113573721550023533 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Stream(_BaseTraceHierarchyType): # maxpoints # --------- @property def maxpoints(self): """ Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. The 'maxpoints' property is a number and may be specified as: - An int or float in the interval [0, 10000] Returns ------- int|float """ return self["maxpoints"] @maxpoints.setter def maxpoints(self, val): self["maxpoints"] = val # token # ----- @property def token(self): """ The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. The 'token' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["token"] @token.setter def token(self, val): self["token"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "contour" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """ def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): """ Construct a new Stream object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.contour.Stream maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- Stream """ super(Stream, self).__init__("stream") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.contour.Stream constructor must be a dict or an instance of plotly.graph_objs.contour.Stream""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.contour import stream as v_stream # Initialize validators # --------------------- self._validators["maxpoints"] = v_stream.MaxpointsValidator() self._validators["token"] = v_stream.TokenValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("maxpoints", None) self["maxpoints"] = maxpoints if maxpoints is not None else _v _v = arg.pop("token", None) self["token"] = token if token is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the color of the contour level. Has no effect if `contours.coloring` is set to "lines". The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # dash # ---- @property def dash(self): """ Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). The 'dash' property is an enumeration that may be specified as: - One of the following dash styles: ['solid', 'dot', 'dash', 'longdash', 'dashdot', 'longdashdot'] - A string containing a dash length list in pixels or percentages (e.g. '5px 10px 2px 2px', '5, 10, 2, 2', '10% 20% 40%', etc.) Returns ------- str """ return self["dash"] @dash.setter def dash(self, val): self["dash"] = val # smoothing # --------- @property def smoothing(self): """ Sets the amount of smoothing for the contour lines, where 0 corresponds to no smoothing. The 'smoothing' property is a number and may be specified as: - An int or float in the interval [0, 1.3] Returns ------- int|float """ return self["smoothing"] @smoothing.setter def smoothing(self, val): self["smoothing"] = val # width # ----- @property def width(self): """ Sets the contour line width in (in px) Defaults to 0.5 when `contours.type` is "levels". Defaults to 2 when `contour.type` is "constraint". The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "contour" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the color of the contour level. Has no effect if `contours.coloring` is set to "lines". dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). smoothing Sets the amount of smoothing for the contour lines, where 0 corresponds to no smoothing. width Sets the contour line width in (in px) Defaults to 0.5 when `contours.type` is "levels". Defaults to 2 when `contour.type` is "constraint". """ def __init__( self, arg=None, color=None, dash=None, smoothing=None, width=None, **kwargs ): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.contour.Line color Sets the color of the contour level. Has no effect if `contours.coloring` is set to "lines". dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). smoothing Sets the amount of smoothing for the contour lines, where 0 corresponds to no smoothing. width Sets the contour line width in (in px) Defaults to 0.5 when `contours.type` is "levels". Defaults to 2 when `contour.type` is "constraint". Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.contour.Line constructor must be a dict or an instance of plotly.graph_objs.contour.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.contour import line as v_line # Initialize validators # --------------------- self._validators["color"] = v_line.ColorValidator() self._validators["dash"] = v_line.DashValidator() self._validators["smoothing"] = v_line.SmoothingValidator() self._validators["width"] = v_line.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("dash", None) self["dash"] = dash if dash is not None else _v _v = arg.pop("smoothing", None) self["smoothing"] = smoothing if smoothing is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Hoverlabel(_BaseTraceHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'right', 'auto'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["align"] @align.setter def align(self, val): self["align"] = val # alignsrc # -------- @property def alignsrc(self): """ Sets the source reference on plot.ly for align . The 'alignsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["alignsrc"] @alignsrc.setter def alignsrc(self, val): self["alignsrc"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the hover labels for this trace The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bgcolorsrc # ---------- @property def bgcolorsrc(self): """ Sets the source reference on plot.ly for bgcolor . The 'bgcolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bgcolorsrc"] @bgcolorsrc.setter def bgcolorsrc(self, val): self["bgcolorsrc"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the border color of the hover labels for this trace. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # bordercolorsrc # -------------- @property def bordercolorsrc(self): """ Sets the source reference on plot.ly for bordercolor . The 'bordercolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bordercolorsrc"] @bordercolorsrc.setter def bordercolorsrc(self, val): self["bordercolorsrc"] = val # font # ---- @property def font(self): """ Sets the font used in hover labels. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.contour.hoverlabel.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.contour.hoverlabel.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # namelength # ---------- @property def namelength(self): """ Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. The 'namelength' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [-1, 9223372036854775807] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|numpy.ndarray """ return self["namelength"] @namelength.setter def namelength(self, val): self["namelength"] = val # namelengthsrc # ------------- @property def namelengthsrc(self): """ Sets the source reference on plot.ly for namelength . The 'namelengthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["namelengthsrc"] @namelengthsrc.setter def namelengthsrc(self, val): self["namelengthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "contour" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """ def __init__( self, arg=None, align=None, alignsrc=None, bgcolor=None, bgcolorsrc=None, bordercolor=None, bordercolorsrc=None, font=None, namelength=None, namelengthsrc=None, **kwargs ): """ Construct a new Hoverlabel object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.contour.Hoverlabel align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- Hoverlabel """ super(Hoverlabel, self).__init__("hoverlabel") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.contour.Hoverlabel constructor must be a dict or an instance of plotly.graph_objs.contour.Hoverlabel""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.contour import hoverlabel as v_hoverlabel # Initialize validators # --------------------- self._validators["align"] = v_hoverlabel.AlignValidator() self._validators["alignsrc"] = v_hoverlabel.AlignsrcValidator() self._validators["bgcolor"] = v_hoverlabel.BgcolorValidator() self._validators["bgcolorsrc"] = v_hoverlabel.BgcolorsrcValidator() self._validators["bordercolor"] = v_hoverlabel.BordercolorValidator() self._validators["bordercolorsrc"] = v_hoverlabel.BordercolorsrcValidator() self._validators["font"] = v_hoverlabel.FontValidator() self._validators["namelength"] = v_hoverlabel.NamelengthValidator() self._validators["namelengthsrc"] = v_hoverlabel.NamelengthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("alignsrc", None) self["alignsrc"] = alignsrc if alignsrc is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bgcolorsrc", None) self["bgcolorsrc"] = bgcolorsrc if bgcolorsrc is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("bordercolorsrc", None) self["bordercolorsrc"] = bordercolorsrc if bordercolorsrc is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("namelength", None) self["namelength"] = namelength if namelength is not None else _v _v = arg.pop("namelengthsrc", None) self["namelengthsrc"] = namelengthsrc if namelengthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Contours(_BaseTraceHierarchyType): # coloring # -------- @property def coloring(self): """ Determines the coloring method showing the contour values. If "fill", coloring is done evenly between each contour level If "heatmap", a heatmap gradient coloring is applied between each contour level. If "lines", coloring is done on the contour lines. If "none", no coloring is applied on this trace. The 'coloring' property is an enumeration that may be specified as: - One of the following enumeration values: ['fill', 'heatmap', 'lines', 'none'] Returns ------- Any """ return self["coloring"] @coloring.setter def coloring(self, val): self["coloring"] = val # end # --- @property def end(self): """ Sets the end contour level value. Must be more than `contours.start` The 'end' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["end"] @end.setter def end(self, val): self["end"] = val # labelfont # --------- @property def labelfont(self): """ Sets the font used for labeling the contour levels. The default color comes from the lines, if shown. The default family and size come from `layout.font`. The 'labelfont' property is an instance of Labelfont that may be specified as: - An instance of plotly.graph_objs.contour.contours.Labelfont - A dict of string/value properties that will be passed to the Labelfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.contour.contours.Labelfont """ return self["labelfont"] @labelfont.setter def labelfont(self, val): self["labelfont"] = val # labelformat # ----------- @property def labelformat(self): """ Sets the contour label formatting rule using d3 formatting mini-language which is very similar to Python, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format The 'labelformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["labelformat"] @labelformat.setter def labelformat(self, val): self["labelformat"] = val # operation # --------- @property def operation(self): """ Sets the constraint operation. "=" keeps regions equal to `value` "<" and "<=" keep regions less than `value` ">" and ">=" keep regions greater than `value` "[]", "()", "[)", and "(]" keep regions inside `value[0]` to `value[1]` "][", ")(", "](", ")[" keep regions outside `value[0]` to value[1]` Open vs. closed intervals make no difference to constraint display, but all versions are allowed for consistency with filter transforms. The 'operation' property is an enumeration that may be specified as: - One of the following enumeration values: ['=', '<', '>=', '>', '<=', '[]', '()', '[)', '(]', '][', ')(', '](', ')['] Returns ------- Any """ return self["operation"] @operation.setter def operation(self, val): self["operation"] = val # showlabels # ---------- @property def showlabels(self): """ Determines whether to label the contour lines with their values. The 'showlabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showlabels"] @showlabels.setter def showlabels(self, val): self["showlabels"] = val # showlines # --------- @property def showlines(self): """ Determines whether or not the contour lines are drawn. Has an effect only if `contours.coloring` is set to "fill". The 'showlines' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showlines"] @showlines.setter def showlines(self, val): self["showlines"] = val # size # ---- @property def size(self): """ Sets the step between each contour level. Must be positive. The 'size' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # start # ----- @property def start(self): """ Sets the starting contour level value. Must be less than `contours.end` The 'start' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["start"] @start.setter def start(self, val): self["start"] = val # type # ---- @property def type(self): """ If `levels`, the data is represented as a contour plot with multiple levels displayed. If `constraint`, the data is represented as constraints with the invalid region shaded as specified by the `operation` and `value` parameters. The 'type' property is an enumeration that may be specified as: - One of the following enumeration values: ['levels', 'constraint'] Returns ------- Any """ return self["type"] @type.setter def type(self, val): self["type"] = val # value # ----- @property def value(self): """ Sets the value or values of the constraint boundary. When `operation` is set to one of the comparison values (=,<,>=,>,<=) "value" is expected to be a number. When `operation` is set to one of the interval values ([],(),[),(],][,)(,](,)[) "value" is expected to be an array of two numbers where the first is the lower bound and the second is the upper bound. The 'value' property accepts values of any type Returns ------- Any """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "contour" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ coloring Determines the coloring method showing the contour values. If "fill", coloring is done evenly between each contour level If "heatmap", a heatmap gradient coloring is applied between each contour level. If "lines", coloring is done on the contour lines. If "none", no coloring is applied on this trace. end Sets the end contour level value. Must be more than `contours.start` labelfont Sets the font used for labeling the contour levels. The default color comes from the lines, if shown. The default family and size come from `layout.font`. labelformat Sets the contour label formatting rule using d3 formatting mini-language which is very similar to Python, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format operation Sets the constraint operation. "=" keeps regions equal to `value` "<" and "<=" keep regions less than `value` ">" and ">=" keep regions greater than `value` "[]", "()", "[)", and "(]" keep regions inside `value[0]` to `value[1]` "][", ")(", "](", ")[" keep regions outside `value[0]` to value[1]` Open vs. closed intervals make no difference to constraint display, but all versions are allowed for consistency with filter transforms. showlabels Determines whether to label the contour lines with their values. showlines Determines whether or not the contour lines are drawn. Has an effect only if `contours.coloring` is set to "fill". size Sets the step between each contour level. Must be positive. start Sets the starting contour level value. Must be less than `contours.end` type If `levels`, the data is represented as a contour plot with multiple levels displayed. If `constraint`, the data is represented as constraints with the invalid region shaded as specified by the `operation` and `value` parameters. value Sets the value or values of the constraint boundary. When `operation` is set to one of the comparison values (=,<,>=,>,<=) "value" is expected to be a number. When `operation` is set to one of the interval values ([],(),[),(],][,)(,](,)[) "value" is expected to be an array of two numbers where the first is the lower bound and the second is the upper bound. """ def __init__( self, arg=None, coloring=None, end=None, labelfont=None, labelformat=None, operation=None, showlabels=None, showlines=None, size=None, start=None, type=None, value=None, **kwargs ): """ Construct a new Contours object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.contour.Contours coloring Determines the coloring method showing the contour values. If "fill", coloring is done evenly between each contour level If "heatmap", a heatmap gradient coloring is applied between each contour level. If "lines", coloring is done on the contour lines. If "none", no coloring is applied on this trace. end Sets the end contour level value. Must be more than `contours.start` labelfont Sets the font used for labeling the contour levels. The default color comes from the lines, if shown. The default family and size come from `layout.font`. labelformat Sets the contour label formatting rule using d3 formatting mini-language which is very similar to Python, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format operation Sets the constraint operation. "=" keeps regions equal to `value` "<" and "<=" keep regions less than `value` ">" and ">=" keep regions greater than `value` "[]", "()", "[)", and "(]" keep regions inside `value[0]` to `value[1]` "][", ")(", "](", ")[" keep regions outside `value[0]` to value[1]` Open vs. closed intervals make no difference to constraint display, but all versions are allowed for consistency with filter transforms. showlabels Determines whether to label the contour lines with their values. showlines Determines whether or not the contour lines are drawn. Has an effect only if `contours.coloring` is set to "fill". size Sets the step between each contour level. Must be positive. start Sets the starting contour level value. Must be less than `contours.end` type If `levels`, the data is represented as a contour plot with multiple levels displayed. If `constraint`, the data is represented as constraints with the invalid region shaded as specified by the `operation` and `value` parameters. value Sets the value or values of the constraint boundary. When `operation` is set to one of the comparison values (=,<,>=,>,<=) "value" is expected to be a number. When `operation` is set to one of the interval values ([],(),[),(],][,)(,](,)[) "value" is expected to be an array of two numbers where the first is the lower bound and the second is the upper bound. Returns ------- Contours """ super(Contours, self).__init__("contours") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.contour.Contours constructor must be a dict or an instance of plotly.graph_objs.contour.Contours""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.contour import contours as v_contours # Initialize validators # --------------------- self._validators["coloring"] = v_contours.ColoringValidator() self._validators["end"] = v_contours.EndValidator() self._validators["labelfont"] = v_contours.LabelfontValidator() self._validators["labelformat"] = v_contours.LabelformatValidator() self._validators["operation"] = v_contours.OperationValidator() self._validators["showlabels"] = v_contours.ShowlabelsValidator() self._validators["showlines"] = v_contours.ShowlinesValidator() self._validators["size"] = v_contours.SizeValidator() self._validators["start"] = v_contours.StartValidator() self._validators["type"] = v_contours.TypeValidator() self._validators["value"] = v_contours.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("coloring", None) self["coloring"] = coloring if coloring is not None else _v _v = arg.pop("end", None) self["end"] = end if end is not None else _v _v = arg.pop("labelfont", None) self["labelfont"] = labelfont if labelfont is not None else _v _v = arg.pop("labelformat", None) self["labelformat"] = labelformat if labelformat is not None else _v _v = arg.pop("operation", None) self["operation"] = operation if operation is not None else _v _v = arg.pop("showlabels", None) self["showlabels"] = showlabels if showlabels is not None else _v _v = arg.pop("showlines", None) self["showlines"] = showlines if showlines is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("start", None) self["start"] = start if start is not None else _v _v = arg.pop("type", None) self["type"] = type if type is not None else _v _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class ColorBar(_BaseTraceHierarchyType): # bgcolor # ------- @property def bgcolor(self): """ Sets the color of padded area. The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the axis line color. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # borderwidth # ----------- @property def borderwidth(self): """ Sets the width (in px) or the border enclosing this color bar. The 'borderwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["borderwidth"] @borderwidth.setter def borderwidth(self, val): self["borderwidth"] = val # dtick # ----- @property def dtick(self): """ Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" The 'dtick' property accepts values of any type Returns ------- Any """ return self["dtick"] @dtick.setter def dtick(self, val): self["dtick"] = val # exponentformat # -------------- @property def exponentformat(self): """ Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. The 'exponentformat' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'e', 'E', 'power', 'SI', 'B'] Returns ------- Any """ return self["exponentformat"] @exponentformat.setter def exponentformat(self, val): self["exponentformat"] = val # len # --- @property def len(self): """ Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. The 'len' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["len"] @len.setter def len(self, val): self["len"] = val # lenmode # ------- @property def lenmode(self): """ Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. The 'lenmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["lenmode"] @lenmode.setter def lenmode(self, val): self["lenmode"] = val # nticks # ------ @property def nticks(self): """ Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". The 'nticks' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nticks"] @nticks.setter def nticks(self, val): self["nticks"] = val # outlinecolor # ------------ @property def outlinecolor(self): """ Sets the axis line color. The 'outlinecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["outlinecolor"] @outlinecolor.setter def outlinecolor(self, val): self["outlinecolor"] = val # outlinewidth # ------------ @property def outlinewidth(self): """ Sets the width (in px) of the axis line. The 'outlinewidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["outlinewidth"] @outlinewidth.setter def outlinewidth(self, val): self["outlinewidth"] = val # separatethousands # ----------------- @property def separatethousands(self): """ If "true", even 4-digit integers are separated The 'separatethousands' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["separatethousands"] @separatethousands.setter def separatethousands(self, val): self["separatethousands"] = val # showexponent # ------------ @property def showexponent(self): """ If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. The 'showexponent' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showexponent"] @showexponent.setter def showexponent(self, val): self["showexponent"] = val # showticklabels # -------------- @property def showticklabels(self): """ Determines whether or not the tick labels are drawn. The 'showticklabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showticklabels"] @showticklabels.setter def showticklabels(self, val): self["showticklabels"] = val # showtickprefix # -------------- @property def showtickprefix(self): """ If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. The 'showtickprefix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showtickprefix"] @showtickprefix.setter def showtickprefix(self, val): self["showtickprefix"] = val # showticksuffix # -------------- @property def showticksuffix(self): """ Same as `showtickprefix` but for tick suffixes. The 'showticksuffix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showticksuffix"] @showticksuffix.setter def showticksuffix(self, val): self["showticksuffix"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # thicknessmode # ------------- @property def thicknessmode(self): """ Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. The 'thicknessmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["thicknessmode"] @thicknessmode.setter def thicknessmode(self, val): self["thicknessmode"] = val # tick0 # ----- @property def tick0(self): """ Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. The 'tick0' property accepts values of any type Returns ------- Any """ return self["tick0"] @tick0.setter def tick0(self, val): self["tick0"] = val # tickangle # --------- @property def tickangle(self): """ Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. The 'tickangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["tickangle"] @tickangle.setter def tickangle(self, val): self["tickangle"] = val # tickcolor # --------- @property def tickcolor(self): """ Sets the tick color. The 'tickcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["tickcolor"] @tickcolor.setter def tickcolor(self, val): self["tickcolor"] = val # tickfont # -------- @property def tickfont(self): """ Sets the color bar's tick label font The 'tickfont' property is an instance of Tickfont that may be specified as: - An instance of plotly.graph_objs.contour.colorbar.Tickfont - A dict of string/value properties that will be passed to the Tickfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.contour.colorbar.Tickfont """ return self["tickfont"] @tickfont.setter def tickfont(self, val): self["tickfont"] = val # tickformat # ---------- @property def tickformat(self): """ Sets the tick label formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'tickformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickformat"] @tickformat.setter def tickformat(self, val): self["tickformat"] = val # tickformatstops # --------------- @property def tickformatstops(self): """ The 'tickformatstops' property is a tuple of instances of Tickformatstop that may be specified as: - A list or tuple of instances of plotly.graph_objs.contour.colorbar.Tickformatstop - A list or tuple of dicts of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- tuple[plotly.graph_objs.contour.colorbar.Tickformatstop] """ return self["tickformatstops"] @tickformatstops.setter def tickformatstops(self, val): self["tickformatstops"] = val # tickformatstopdefaults # ---------------------- @property def tickformatstopdefaults(self): """ When used in a template (as layout.template.data.contour.colorbar.tickformatstopdefaults), sets the default property values to use for elements of contour.colorbar.tickformatstops The 'tickformatstopdefaults' property is an instance of Tickformatstop that may be specified as: - An instance of plotly.graph_objs.contour.colorbar.Tickformatstop - A dict of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: Returns ------- plotly.graph_objs.contour.colorbar.Tickformatstop """ return self["tickformatstopdefaults"] @tickformatstopdefaults.setter def tickformatstopdefaults(self, val): self["tickformatstopdefaults"] = val # ticklen # ------- @property def ticklen(self): """ Sets the tick length (in px). The 'ticklen' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ticklen"] @ticklen.setter def ticklen(self, val): self["ticklen"] = val # tickmode # -------- @property def tickmode(self): """ Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). The 'tickmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'linear', 'array'] Returns ------- Any """ return self["tickmode"] @tickmode.setter def tickmode(self, val): self["tickmode"] = val # tickprefix # ---------- @property def tickprefix(self): """ Sets a tick label prefix. The 'tickprefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickprefix"] @tickprefix.setter def tickprefix(self, val): self["tickprefix"] = val # ticks # ----- @property def ticks(self): """ Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. The 'ticks' property is an enumeration that may be specified as: - One of the following enumeration values: ['outside', 'inside', ''] Returns ------- Any """ return self["ticks"] @ticks.setter def ticks(self, val): self["ticks"] = val # ticksuffix # ---------- @property def ticksuffix(self): """ Sets a tick label suffix. The 'ticksuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ticksuffix"] @ticksuffix.setter def ticksuffix(self, val): self["ticksuffix"] = val # ticktext # -------- @property def ticktext(self): """ Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. The 'ticktext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ticktext"] @ticktext.setter def ticktext(self, val): self["ticktext"] = val # ticktextsrc # ----------- @property def ticktextsrc(self): """ Sets the source reference on plot.ly for ticktext . The 'ticktextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ticktextsrc"] @ticktextsrc.setter def ticktextsrc(self, val): self["ticktextsrc"] = val # tickvals # -------- @property def tickvals(self): """ Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. The 'tickvals' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["tickvals"] @tickvals.setter def tickvals(self, val): self["tickvals"] = val # tickvalssrc # ----------- @property def tickvalssrc(self): """ Sets the source reference on plot.ly for tickvals . The 'tickvalssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tickvalssrc"] @tickvalssrc.setter def tickvalssrc(self, val): self["tickvalssrc"] = val # tickwidth # --------- @property def tickwidth(self): """ Sets the tick width (in px). The 'tickwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["tickwidth"] @tickwidth.setter def tickwidth(self, val): self["tickwidth"] = val # title # ----- @property def title(self): """ The 'title' property is an instance of Title that may be specified as: - An instance of plotly.graph_objs.contour.colorbar.Title - A dict of string/value properties that will be passed to the Title constructor Supported dict properties: font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- plotly.graph_objs.contour.colorbar.Title """ return self["title"] @title.setter def title(self, val): self["title"] = val # titlefont # --------- @property def titlefont(self): """ Deprecated: Please use contour.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.contour.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- """ return self["titlefont"] @titlefont.setter def titlefont(self, val): self["titlefont"] = val # titleside # --------- @property def titleside(self): """ Deprecated: Please use contour.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- """ return self["titleside"] @titleside.setter def titleside(self, val): self["titleside"] = val # x # - @property def x(self): """ Sets the x position of the color bar (in plot fraction). The 'x' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["x"] @x.setter def x(self, val): self["x"] = val # xanchor # ------- @property def xanchor(self): """ Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. The 'xanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'center', 'right'] Returns ------- Any """ return self["xanchor"] @xanchor.setter def xanchor(self, val): self["xanchor"] = val # xpad # ---- @property def xpad(self): """ Sets the amount of padding (in px) along the x direction. The 'xpad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["xpad"] @xpad.setter def xpad(self, val): self["xpad"] = val # y # - @property def y(self): """ Sets the y position of the color bar (in plot fraction). The 'y' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["y"] @y.setter def y(self, val): self["y"] = val # yanchor # ------- @property def yanchor(self): """ Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. The 'yanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['top', 'middle', 'bottom'] Returns ------- Any """ return self["yanchor"] @yanchor.setter def yanchor(self, val): self["yanchor"] = val # ypad # ---- @property def ypad(self): """ Sets the amount of padding (in px) along the y direction. The 'ypad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ypad"] @ypad.setter def ypad(self, val): self["ypad"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "contour" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.contour.colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.contou r.colorbar.tickformatstopdefaults), sets the default property values to use for elements of contour.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.contour.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use contour.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use contour.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """ _mapped_properties = { "titlefont": ("title", "font"), "titleside": ("title", "side"), } def __init__( self, arg=None, bgcolor=None, bordercolor=None, borderwidth=None, dtick=None, exponentformat=None, len=None, lenmode=None, nticks=None, outlinecolor=None, outlinewidth=None, separatethousands=None, showexponent=None, showticklabels=None, showtickprefix=None, showticksuffix=None, thickness=None, thicknessmode=None, tick0=None, tickangle=None, tickcolor=None, tickfont=None, tickformat=None, tickformatstops=None, tickformatstopdefaults=None, ticklen=None, tickmode=None, tickprefix=None, ticks=None, ticksuffix=None, ticktext=None, ticktextsrc=None, tickvals=None, tickvalssrc=None, tickwidth=None, title=None, titlefont=None, titleside=None, x=None, xanchor=None, xpad=None, y=None, yanchor=None, ypad=None, **kwargs ): """ Construct a new ColorBar object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.contour.ColorBar bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.contour.colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.contou r.colorbar.tickformatstopdefaults), sets the default property values to use for elements of contour.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.contour.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use contour.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use contour.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- ColorBar """ super(ColorBar, self).__init__("colorbar") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.contour.ColorBar constructor must be a dict or an instance of plotly.graph_objs.contour.ColorBar""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.contour import colorbar as v_colorbar # Initialize validators # --------------------- self._validators["bgcolor"] = v_colorbar.BgcolorValidator() self._validators["bordercolor"] = v_colorbar.BordercolorValidator() self._validators["borderwidth"] = v_colorbar.BorderwidthValidator() self._validators["dtick"] = v_colorbar.DtickValidator() self._validators["exponentformat"] = v_colorbar.ExponentformatValidator() self._validators["len"] = v_colorbar.LenValidator() self._validators["lenmode"] = v_colorbar.LenmodeValidator() self._validators["nticks"] = v_colorbar.NticksValidator() self._validators["outlinecolor"] = v_colorbar.OutlinecolorValidator() self._validators["outlinewidth"] = v_colorbar.OutlinewidthValidator() self._validators["separatethousands"] = v_colorbar.SeparatethousandsValidator() self._validators["showexponent"] = v_colorbar.ShowexponentValidator() self._validators["showticklabels"] = v_colorbar.ShowticklabelsValidator() self._validators["showtickprefix"] = v_colorbar.ShowtickprefixValidator() self._validators["showticksuffix"] = v_colorbar.ShowticksuffixValidator() self._validators["thickness"] = v_colorbar.ThicknessValidator() self._validators["thicknessmode"] = v_colorbar.ThicknessmodeValidator() self._validators["tick0"] = v_colorbar.Tick0Validator() self._validators["tickangle"] = v_colorbar.TickangleValidator() self._validators["tickcolor"] = v_colorbar.TickcolorValidator() self._validators["tickfont"] = v_colorbar.TickfontValidator() self._validators["tickformat"] = v_colorbar.TickformatValidator() self._validators["tickformatstops"] = v_colorbar.TickformatstopsValidator() self._validators[ "tickformatstopdefaults" ] = v_colorbar.TickformatstopValidator() self._validators["ticklen"] = v_colorbar.TicklenValidator() self._validators["tickmode"] = v_colorbar.TickmodeValidator() self._validators["tickprefix"] = v_colorbar.TickprefixValidator() self._validators["ticks"] = v_colorbar.TicksValidator() self._validators["ticksuffix"] = v_colorbar.TicksuffixValidator() self._validators["ticktext"] = v_colorbar.TicktextValidator() self._validators["ticktextsrc"] = v_colorbar.TicktextsrcValidator() self._validators["tickvals"] = v_colorbar.TickvalsValidator() self._validators["tickvalssrc"] = v_colorbar.TickvalssrcValidator() self._validators["tickwidth"] = v_colorbar.TickwidthValidator() self._validators["title"] = v_colorbar.TitleValidator() self._validators["x"] = v_colorbar.XValidator() self._validators["xanchor"] = v_colorbar.XanchorValidator() self._validators["xpad"] = v_colorbar.XpadValidator() self._validators["y"] = v_colorbar.YValidator() self._validators["yanchor"] = v_colorbar.YanchorValidator() self._validators["ypad"] = v_colorbar.YpadValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("borderwidth", None) self["borderwidth"] = borderwidth if borderwidth is not None else _v _v = arg.pop("dtick", None) self["dtick"] = dtick if dtick is not None else _v _v = arg.pop("exponentformat", None) self["exponentformat"] = exponentformat if exponentformat is not None else _v _v = arg.pop("len", None) self["len"] = len if len is not None else _v _v = arg.pop("lenmode", None) self["lenmode"] = lenmode if lenmode is not None else _v _v = arg.pop("nticks", None) self["nticks"] = nticks if nticks is not None else _v _v = arg.pop("outlinecolor", None) self["outlinecolor"] = outlinecolor if outlinecolor is not None else _v _v = arg.pop("outlinewidth", None) self["outlinewidth"] = outlinewidth if outlinewidth is not None else _v _v = arg.pop("separatethousands", None) self["separatethousands"] = ( separatethousands if separatethousands is not None else _v ) _v = arg.pop("showexponent", None) self["showexponent"] = showexponent if showexponent is not None else _v _v = arg.pop("showticklabels", None) self["showticklabels"] = showticklabels if showticklabels is not None else _v _v = arg.pop("showtickprefix", None) self["showtickprefix"] = showtickprefix if showtickprefix is not None else _v _v = arg.pop("showticksuffix", None) self["showticksuffix"] = showticksuffix if showticksuffix is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("thicknessmode", None) self["thicknessmode"] = thicknessmode if thicknessmode is not None else _v _v = arg.pop("tick0", None) self["tick0"] = tick0 if tick0 is not None else _v _v = arg.pop("tickangle", None) self["tickangle"] = tickangle if tickangle is not None else _v _v = arg.pop("tickcolor", None) self["tickcolor"] = tickcolor if tickcolor is not None else _v _v = arg.pop("tickfont", None) self["tickfont"] = tickfont if tickfont is not None else _v _v = arg.pop("tickformat", None) self["tickformat"] = tickformat if tickformat is not None else _v _v = arg.pop("tickformatstops", None) self["tickformatstops"] = tickformatstops if tickformatstops is not None else _v _v = arg.pop("tickformatstopdefaults", None) self["tickformatstopdefaults"] = ( tickformatstopdefaults if tickformatstopdefaults is not None else _v ) _v = arg.pop("ticklen", None) self["ticklen"] = ticklen if ticklen is not None else _v _v = arg.pop("tickmode", None) self["tickmode"] = tickmode if tickmode is not None else _v _v = arg.pop("tickprefix", None) self["tickprefix"] = tickprefix if tickprefix is not None else _v _v = arg.pop("ticks", None) self["ticks"] = ticks if ticks is not None else _v _v = arg.pop("ticksuffix", None) self["ticksuffix"] = ticksuffix if ticksuffix is not None else _v _v = arg.pop("ticktext", None) self["ticktext"] = ticktext if ticktext is not None else _v _v = arg.pop("ticktextsrc", None) self["ticktextsrc"] = ticktextsrc if ticktextsrc is not None else _v _v = arg.pop("tickvals", None) self["tickvals"] = tickvals if tickvals is not None else _v _v = arg.pop("tickvalssrc", None) self["tickvalssrc"] = tickvalssrc if tickvalssrc is not None else _v _v = arg.pop("tickwidth", None) self["tickwidth"] = tickwidth if tickwidth is not None else _v _v = arg.pop("title", None) self["title"] = title if title is not None else _v _v = arg.pop("titlefont", None) _v = titlefont if titlefont is not None else _v if _v is not None: self["titlefont"] = _v _v = arg.pop("titleside", None) _v = titleside if titleside is not None else _v if _v is not None: self["titleside"] = _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xanchor", None) self["xanchor"] = xanchor if xanchor is not None else _v _v = arg.pop("xpad", None) self["xpad"] = xpad if xpad is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("yanchor", None) self["yanchor"] = yanchor if yanchor is not None else _v _v = arg.pop("ypad", None) self["ypad"] = ypad if ypad is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = [ "ColorBar", "Contours", "Hoverlabel", "Line", "Stream", "colorbar", "contours", "hoverlabel", ] from plotly.graph_objs.contour import hoverlabel from plotly.graph_objs.contour import contours from plotly.graph_objs.contour import colorbar plotly-4.4.1+dfsg.orig/plotly/graph_objs/scattergeo/0000755000175000017500000000000013573746613022071 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scattergeo/unselected/0000755000175000017500000000000013573746613024224 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scattergeo/unselected/__init__.py0000644000175000017500000002767013573721551026343 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Textfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the text font color of unselected points, applied only when a selection exists. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattergeo.unselected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the text font color of unselected points, applied only when a selection exists. """ def __init__(self, arg=None, color=None, **kwargs): """ Construct a new Textfont object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattergeo.unselected.Textfont color Sets the text font color of unselected points, applied only when a selection exists. Returns ------- Textfont """ super(Textfont, self).__init__("textfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattergeo.unselected.Textfont constructor must be a dict or an instance of plotly.graph_objs.scattergeo.unselected.Textfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattergeo.unselected import textfont as v_textfont # Initialize validators # --------------------- self._validators["color"] = v_textfont.ColorValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the marker color of unselected points, applied only when a selection exists. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # opacity # ------- @property def opacity(self): """ Sets the marker opacity of unselected points, applied only when a selection exists. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # size # ---- @property def size(self): """ Sets the marker size of unselected points, applied only when a selection exists. The 'size' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattergeo.unselected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. size Sets the marker size of unselected points, applied only when a selection exists. """ def __init__(self, arg=None, color=None, opacity=None, size=None, **kwargs): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattergeo.unselected.Marker color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. size Sets the marker size of unselected points, applied only when a selection exists. Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattergeo.unselected.Marker constructor must be a dict or an instance of plotly.graph_objs.scattergeo.unselected.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattergeo.unselected import marker as v_marker # Initialize validators # --------------------- self._validators["color"] = v_marker.ColorValidator() self._validators["opacity"] = v_marker.OpacityValidator() self._validators["size"] = v_marker.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Marker", "Textfont"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/scattergeo/hoverlabel/0000755000175000017500000000000013573746613024214 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scattergeo/hoverlabel/__init__.py0000644000175000017500000002545713573721551026334 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattergeo.hoverlabel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Font object Sets the font used in hover labels. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattergeo.hoverlabel.Font color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattergeo.hoverlabel.Font constructor must be a dict or an instance of plotly.graph_objs.scattergeo.hoverlabel.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattergeo.hoverlabel import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["colorsrc"] = v_font.ColorsrcValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["familysrc"] = v_font.FamilysrcValidator() self._validators["size"] = v_font.SizeValidator() self._validators["sizesrc"] = v_font.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/scattergeo/marker/0000755000175000017500000000000013573746613023352 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scattergeo/marker/colorbar/0000755000175000017500000000000013573746613025155 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scattergeo/marker/colorbar/title/0000755000175000017500000000000013573746613026276 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scattergeo/marker/colorbar/title/__init__.py0000644000175000017500000002060713573721551030406 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattergeo.marker.colorbar.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattergeo.marker.colorbar.title.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattergeo.marker.colorbar.title.Font constructor must be a dict or an instance of plotly.graph_objs.scattergeo.marker.colorbar.title.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattergeo.marker.colorbar.title import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/scattergeo/marker/colorbar/__init__.py0000644000175000017500000006104313573721551027264 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Title(_BaseTraceHierarchyType): # font # ---- @property def font(self): """ Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.scattergeo.marker.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.scattergeo.marker.colorbar.title.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # side # ---- @property def side(self): """ Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- Any """ return self["side"] @side.setter def side(self, val): self["side"] = val # text # ---- @property def text(self): """ Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattergeo.marker.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """ def __init__(self, arg=None, font=None, side=None, text=None, **kwargs): """ Construct a new Title object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattergeo.marker.colorbar.Title font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- Title """ super(Title, self).__init__("title") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattergeo.marker.colorbar.Title constructor must be a dict or an instance of plotly.graph_objs.scattergeo.marker.colorbar.Title""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattergeo.marker.colorbar import title as v_title # Initialize validators # --------------------- self._validators["font"] = v_title.FontValidator() self._validators["side"] = v_title.SideValidator() self._validators["text"] = v_title.TextValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("side", None) self["side"] = side if side is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickformatstop(_BaseTraceHierarchyType): # dtickrange # ---------- @property def dtickrange(self): """ range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" The 'dtickrange' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'dtickrange[0]' property accepts values of any type (1) The 'dtickrange[1]' property accepts values of any type Returns ------- list """ return self["dtickrange"] @dtickrange.setter def dtickrange(self, val): self["dtickrange"] = val # enabled # ------- @property def enabled(self): """ Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. The 'enabled' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["enabled"] @enabled.setter def enabled(self, val): self["enabled"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # value # ----- @property def value(self): """ string - dtickformat for described zoom level, the same as "tickformat" The 'value' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattergeo.marker.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """ def __init__( self, arg=None, dtickrange=None, enabled=None, name=None, templateitemname=None, value=None, **kwargs ): """ Construct a new Tickformatstop object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattergeo.marker.colo rbar.Tickformatstop dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- Tickformatstop """ super(Tickformatstop, self).__init__("tickformatstops") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattergeo.marker.colorbar.Tickformatstop constructor must be a dict or an instance of plotly.graph_objs.scattergeo.marker.colorbar.Tickformatstop""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattergeo.marker.colorbar import ( tickformatstop as v_tickformatstop, ) # Initialize validators # --------------------- self._validators["dtickrange"] = v_tickformatstop.DtickrangeValidator() self._validators["enabled"] = v_tickformatstop.EnabledValidator() self._validators["name"] = v_tickformatstop.NameValidator() self._validators[ "templateitemname" ] = v_tickformatstop.TemplateitemnameValidator() self._validators["value"] = v_tickformatstop.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtickrange", None) self["dtickrange"] = dtickrange if dtickrange is not None else _v _v = arg.pop("enabled", None) self["enabled"] = enabled if enabled is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattergeo.marker.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Tickfont object Sets the color bar's tick label font Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattergeo.marker.colorbar.Tickfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Tickfont """ super(Tickfont, self).__init__("tickfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattergeo.marker.colorbar.Tickfont constructor must be a dict or an instance of plotly.graph_objs.scattergeo.marker.colorbar.Tickfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattergeo.marker.colorbar import tickfont as v_tickfont # Initialize validators # --------------------- self._validators["color"] = v_tickfont.ColorValidator() self._validators["family"] = v_tickfont.FamilyValidator() self._validators["size"] = v_tickfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Tickfont", "Tickformatstop", "Tickformatstop", "Title", "title"] from plotly.graph_objs.scattergeo.marker.colorbar import title plotly-4.4.1+dfsg.orig/plotly/graph_objs/scattergeo/marker/__init__.py0000644000175000017500000031010513573721552025456 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # autocolorscale # -------------- @property def autocolorscale(self): """ Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. The 'autocolorscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocolorscale"] @autocolorscale.setter def autocolorscale(self, val): self["autocolorscale"] = val # cauto # ----- @property def cauto(self): """ Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. The 'cauto' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["cauto"] @cauto.setter def cauto(self, val): self["cauto"] = val # cmax # ---- @property def cmax(self): """ Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. The 'cmax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmax"] @cmax.setter def cmax(self, val): self["cmax"] = val # cmid # ---- @property def cmid(self): """ Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. The 'cmid' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmid"] @cmid.setter def cmid(self, val): self["cmid"] = val # cmin # ---- @property def cmin(self): """ Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. The 'cmin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmin"] @cmin.setter def cmin(self, val): self["cmin"] = val # color # ----- @property def color(self): """ Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A number that will be interpreted as a color according to scattergeo.marker.line.colorscale - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # coloraxis # --------- @property def coloraxis(self): """ Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. The 'coloraxis' property is an identifier of a particular subplot, of type 'coloraxis', that may be specified as the string 'coloraxis' optionally followed by an integer >= 1 (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) Returns ------- str """ return self["coloraxis"] @coloraxis.setter def coloraxis(self, val): self["coloraxis"] = val # colorscale # ---------- @property def colorscale(self): """ Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,Earth,Electric,Vi ridis,Cividis. The 'colorscale' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # reversescale # ------------ @property def reversescale(self): """ Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. The 'reversescale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["reversescale"] @reversescale.setter def reversescale(self, val): self["reversescale"] = val # width # ----- @property def width(self): """ Sets the width (in px) of the lines bounding the marker points. The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["width"] @width.setter def width(self, val): self["width"] = val # widthsrc # -------- @property def widthsrc(self): """ Sets the source reference on plot.ly for width . The 'widthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["widthsrc"] @widthsrc.setter def widthsrc(self, val): self["widthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattergeo.marker" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . """ def __init__( self, arg=None, autocolorscale=None, cauto=None, cmax=None, cmid=None, cmin=None, color=None, coloraxis=None, colorscale=None, colorsrc=None, reversescale=None, width=None, widthsrc=None, **kwargs ): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattergeo.marker.Line autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattergeo.marker.Line constructor must be a dict or an instance of plotly.graph_objs.scattergeo.marker.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattergeo.marker import line as v_line # Initialize validators # --------------------- self._validators["autocolorscale"] = v_line.AutocolorscaleValidator() self._validators["cauto"] = v_line.CautoValidator() self._validators["cmax"] = v_line.CmaxValidator() self._validators["cmid"] = v_line.CmidValidator() self._validators["cmin"] = v_line.CminValidator() self._validators["color"] = v_line.ColorValidator() self._validators["coloraxis"] = v_line.ColoraxisValidator() self._validators["colorscale"] = v_line.ColorscaleValidator() self._validators["colorsrc"] = v_line.ColorsrcValidator() self._validators["reversescale"] = v_line.ReversescaleValidator() self._validators["width"] = v_line.WidthValidator() self._validators["widthsrc"] = v_line.WidthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autocolorscale", None) self["autocolorscale"] = autocolorscale if autocolorscale is not None else _v _v = arg.pop("cauto", None) self["cauto"] = cauto if cauto is not None else _v _v = arg.pop("cmax", None) self["cmax"] = cmax if cmax is not None else _v _v = arg.pop("cmid", None) self["cmid"] = cmid if cmid is not None else _v _v = arg.pop("cmin", None) self["cmin"] = cmin if cmin is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("coloraxis", None) self["coloraxis"] = coloraxis if coloraxis is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("reversescale", None) self["reversescale"] = reversescale if reversescale is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v _v = arg.pop("widthsrc", None) self["widthsrc"] = widthsrc if widthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Gradient(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the final color of the gradient fill: the center color for radial, the right for horizontal, or the bottom for vertical. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # type # ---- @property def type(self): """ Sets the type of gradient used to fill the markers The 'type' property is an enumeration that may be specified as: - One of the following enumeration values: ['radial', 'horizontal', 'vertical', 'none'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["type"] @type.setter def type(self, val): self["type"] = val # typesrc # ------- @property def typesrc(self): """ Sets the source reference on plot.ly for type . The 'typesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["typesrc"] @typesrc.setter def typesrc(self, val): self["typesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattergeo.marker" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the final color of the gradient fill: the center color for radial, the right for horizontal, or the bottom for vertical. colorsrc Sets the source reference on plot.ly for color . type Sets the type of gradient used to fill the markers typesrc Sets the source reference on plot.ly for type . """ def __init__( self, arg=None, color=None, colorsrc=None, type=None, typesrc=None, **kwargs ): """ Construct a new Gradient object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattergeo.marker.Gradient color Sets the final color of the gradient fill: the center color for radial, the right for horizontal, or the bottom for vertical. colorsrc Sets the source reference on plot.ly for color . type Sets the type of gradient used to fill the markers typesrc Sets the source reference on plot.ly for type . Returns ------- Gradient """ super(Gradient, self).__init__("gradient") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattergeo.marker.Gradient constructor must be a dict or an instance of plotly.graph_objs.scattergeo.marker.Gradient""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattergeo.marker import gradient as v_gradient # Initialize validators # --------------------- self._validators["color"] = v_gradient.ColorValidator() self._validators["colorsrc"] = v_gradient.ColorsrcValidator() self._validators["type"] = v_gradient.TypeValidator() self._validators["typesrc"] = v_gradient.TypesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("type", None) self["type"] = type if type is not None else _v _v = arg.pop("typesrc", None) self["typesrc"] = typesrc if typesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class ColorBar(_BaseTraceHierarchyType): # bgcolor # ------- @property def bgcolor(self): """ Sets the color of padded area. The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the axis line color. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # borderwidth # ----------- @property def borderwidth(self): """ Sets the width (in px) or the border enclosing this color bar. The 'borderwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["borderwidth"] @borderwidth.setter def borderwidth(self, val): self["borderwidth"] = val # dtick # ----- @property def dtick(self): """ Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" The 'dtick' property accepts values of any type Returns ------- Any """ return self["dtick"] @dtick.setter def dtick(self, val): self["dtick"] = val # exponentformat # -------------- @property def exponentformat(self): """ Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. The 'exponentformat' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'e', 'E', 'power', 'SI', 'B'] Returns ------- Any """ return self["exponentformat"] @exponentformat.setter def exponentformat(self, val): self["exponentformat"] = val # len # --- @property def len(self): """ Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. The 'len' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["len"] @len.setter def len(self, val): self["len"] = val # lenmode # ------- @property def lenmode(self): """ Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. The 'lenmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["lenmode"] @lenmode.setter def lenmode(self, val): self["lenmode"] = val # nticks # ------ @property def nticks(self): """ Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". The 'nticks' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nticks"] @nticks.setter def nticks(self, val): self["nticks"] = val # outlinecolor # ------------ @property def outlinecolor(self): """ Sets the axis line color. The 'outlinecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["outlinecolor"] @outlinecolor.setter def outlinecolor(self, val): self["outlinecolor"] = val # outlinewidth # ------------ @property def outlinewidth(self): """ Sets the width (in px) of the axis line. The 'outlinewidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["outlinewidth"] @outlinewidth.setter def outlinewidth(self, val): self["outlinewidth"] = val # separatethousands # ----------------- @property def separatethousands(self): """ If "true", even 4-digit integers are separated The 'separatethousands' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["separatethousands"] @separatethousands.setter def separatethousands(self, val): self["separatethousands"] = val # showexponent # ------------ @property def showexponent(self): """ If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. The 'showexponent' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showexponent"] @showexponent.setter def showexponent(self, val): self["showexponent"] = val # showticklabels # -------------- @property def showticklabels(self): """ Determines whether or not the tick labels are drawn. The 'showticklabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showticklabels"] @showticklabels.setter def showticklabels(self, val): self["showticklabels"] = val # showtickprefix # -------------- @property def showtickprefix(self): """ If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. The 'showtickprefix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showtickprefix"] @showtickprefix.setter def showtickprefix(self, val): self["showtickprefix"] = val # showticksuffix # -------------- @property def showticksuffix(self): """ Same as `showtickprefix` but for tick suffixes. The 'showticksuffix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showticksuffix"] @showticksuffix.setter def showticksuffix(self, val): self["showticksuffix"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # thicknessmode # ------------- @property def thicknessmode(self): """ Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. The 'thicknessmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["thicknessmode"] @thicknessmode.setter def thicknessmode(self, val): self["thicknessmode"] = val # tick0 # ----- @property def tick0(self): """ Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. The 'tick0' property accepts values of any type Returns ------- Any """ return self["tick0"] @tick0.setter def tick0(self, val): self["tick0"] = val # tickangle # --------- @property def tickangle(self): """ Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. The 'tickangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["tickangle"] @tickangle.setter def tickangle(self, val): self["tickangle"] = val # tickcolor # --------- @property def tickcolor(self): """ Sets the tick color. The 'tickcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["tickcolor"] @tickcolor.setter def tickcolor(self, val): self["tickcolor"] = val # tickfont # -------- @property def tickfont(self): """ Sets the color bar's tick label font The 'tickfont' property is an instance of Tickfont that may be specified as: - An instance of plotly.graph_objs.scattergeo.marker.colorbar.Tickfont - A dict of string/value properties that will be passed to the Tickfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.scattergeo.marker.colorbar.Tickfont """ return self["tickfont"] @tickfont.setter def tickfont(self, val): self["tickfont"] = val # tickformat # ---------- @property def tickformat(self): """ Sets the tick label formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'tickformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickformat"] @tickformat.setter def tickformat(self, val): self["tickformat"] = val # tickformatstops # --------------- @property def tickformatstops(self): """ The 'tickformatstops' property is a tuple of instances of Tickformatstop that may be specified as: - A list or tuple of instances of plotly.graph_objs.scattergeo.marker.colorbar.Tickformatstop - A list or tuple of dicts of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- tuple[plotly.graph_objs.scattergeo.marker.colorbar.Tickformatstop] """ return self["tickformatstops"] @tickformatstops.setter def tickformatstops(self, val): self["tickformatstops"] = val # tickformatstopdefaults # ---------------------- @property def tickformatstopdefaults(self): """ When used in a template (as layout.template.data.scattergeo.mar ker.colorbar.tickformatstopdefaults), sets the default property values to use for elements of scattergeo.marker.colorbar.tickformatstops The 'tickformatstopdefaults' property is an instance of Tickformatstop that may be specified as: - An instance of plotly.graph_objs.scattergeo.marker.colorbar.Tickformatstop - A dict of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: Returns ------- plotly.graph_objs.scattergeo.marker.colorbar.Tickformatstop """ return self["tickformatstopdefaults"] @tickformatstopdefaults.setter def tickformatstopdefaults(self, val): self["tickformatstopdefaults"] = val # ticklen # ------- @property def ticklen(self): """ Sets the tick length (in px). The 'ticklen' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ticklen"] @ticklen.setter def ticklen(self, val): self["ticklen"] = val # tickmode # -------- @property def tickmode(self): """ Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). The 'tickmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'linear', 'array'] Returns ------- Any """ return self["tickmode"] @tickmode.setter def tickmode(self, val): self["tickmode"] = val # tickprefix # ---------- @property def tickprefix(self): """ Sets a tick label prefix. The 'tickprefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickprefix"] @tickprefix.setter def tickprefix(self, val): self["tickprefix"] = val # ticks # ----- @property def ticks(self): """ Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. The 'ticks' property is an enumeration that may be specified as: - One of the following enumeration values: ['outside', 'inside', ''] Returns ------- Any """ return self["ticks"] @ticks.setter def ticks(self, val): self["ticks"] = val # ticksuffix # ---------- @property def ticksuffix(self): """ Sets a tick label suffix. The 'ticksuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ticksuffix"] @ticksuffix.setter def ticksuffix(self, val): self["ticksuffix"] = val # ticktext # -------- @property def ticktext(self): """ Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. The 'ticktext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ticktext"] @ticktext.setter def ticktext(self, val): self["ticktext"] = val # ticktextsrc # ----------- @property def ticktextsrc(self): """ Sets the source reference on plot.ly for ticktext . The 'ticktextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ticktextsrc"] @ticktextsrc.setter def ticktextsrc(self, val): self["ticktextsrc"] = val # tickvals # -------- @property def tickvals(self): """ Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. The 'tickvals' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["tickvals"] @tickvals.setter def tickvals(self, val): self["tickvals"] = val # tickvalssrc # ----------- @property def tickvalssrc(self): """ Sets the source reference on plot.ly for tickvals . The 'tickvalssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tickvalssrc"] @tickvalssrc.setter def tickvalssrc(self, val): self["tickvalssrc"] = val # tickwidth # --------- @property def tickwidth(self): """ Sets the tick width (in px). The 'tickwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["tickwidth"] @tickwidth.setter def tickwidth(self, val): self["tickwidth"] = val # title # ----- @property def title(self): """ The 'title' property is an instance of Title that may be specified as: - An instance of plotly.graph_objs.scattergeo.marker.colorbar.Title - A dict of string/value properties that will be passed to the Title constructor Supported dict properties: font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- plotly.graph_objs.scattergeo.marker.colorbar.Title """ return self["title"] @title.setter def title(self, val): self["title"] = val # titlefont # --------- @property def titlefont(self): """ Deprecated: Please use scattergeo.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.scattergeo.marker.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- """ return self["titlefont"] @titlefont.setter def titlefont(self, val): self["titlefont"] = val # titleside # --------- @property def titleside(self): """ Deprecated: Please use scattergeo.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- """ return self["titleside"] @titleside.setter def titleside(self, val): self["titleside"] = val # x # - @property def x(self): """ Sets the x position of the color bar (in plot fraction). The 'x' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["x"] @x.setter def x(self, val): self["x"] = val # xanchor # ------- @property def xanchor(self): """ Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. The 'xanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'center', 'right'] Returns ------- Any """ return self["xanchor"] @xanchor.setter def xanchor(self, val): self["xanchor"] = val # xpad # ---- @property def xpad(self): """ Sets the amount of padding (in px) along the x direction. The 'xpad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["xpad"] @xpad.setter def xpad(self, val): self["xpad"] = val # y # - @property def y(self): """ Sets the y position of the color bar (in plot fraction). The 'y' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["y"] @y.setter def y(self, val): self["y"] = val # yanchor # ------- @property def yanchor(self): """ Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. The 'yanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['top', 'middle', 'bottom'] Returns ------- Any """ return self["yanchor"] @yanchor.setter def yanchor(self, val): self["yanchor"] = val # ypad # ---- @property def ypad(self): """ Sets the amount of padding (in px) along the y direction. The 'ypad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ypad"] @ypad.setter def ypad(self, val): self["ypad"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattergeo.marker" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.scattergeo.marker.color bar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.scatte rgeo.marker.colorbar.tickformatstopdefaults), sets the default property values to use for elements of scattergeo.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.scattergeo.marker.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use scattergeo.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use scattergeo.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """ _mapped_properties = { "titlefont": ("title", "font"), "titleside": ("title", "side"), } def __init__( self, arg=None, bgcolor=None, bordercolor=None, borderwidth=None, dtick=None, exponentformat=None, len=None, lenmode=None, nticks=None, outlinecolor=None, outlinewidth=None, separatethousands=None, showexponent=None, showticklabels=None, showtickprefix=None, showticksuffix=None, thickness=None, thicknessmode=None, tick0=None, tickangle=None, tickcolor=None, tickfont=None, tickformat=None, tickformatstops=None, tickformatstopdefaults=None, ticklen=None, tickmode=None, tickprefix=None, ticks=None, ticksuffix=None, ticktext=None, ticktextsrc=None, tickvals=None, tickvalssrc=None, tickwidth=None, title=None, titlefont=None, titleside=None, x=None, xanchor=None, xpad=None, y=None, yanchor=None, ypad=None, **kwargs ): """ Construct a new ColorBar object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattergeo.marker.ColorBar bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.scattergeo.marker.color bar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.scatte rgeo.marker.colorbar.tickformatstopdefaults), sets the default property values to use for elements of scattergeo.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.scattergeo.marker.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use scattergeo.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use scattergeo.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- ColorBar """ super(ColorBar, self).__init__("colorbar") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattergeo.marker.ColorBar constructor must be a dict or an instance of plotly.graph_objs.scattergeo.marker.ColorBar""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattergeo.marker import colorbar as v_colorbar # Initialize validators # --------------------- self._validators["bgcolor"] = v_colorbar.BgcolorValidator() self._validators["bordercolor"] = v_colorbar.BordercolorValidator() self._validators["borderwidth"] = v_colorbar.BorderwidthValidator() self._validators["dtick"] = v_colorbar.DtickValidator() self._validators["exponentformat"] = v_colorbar.ExponentformatValidator() self._validators["len"] = v_colorbar.LenValidator() self._validators["lenmode"] = v_colorbar.LenmodeValidator() self._validators["nticks"] = v_colorbar.NticksValidator() self._validators["outlinecolor"] = v_colorbar.OutlinecolorValidator() self._validators["outlinewidth"] = v_colorbar.OutlinewidthValidator() self._validators["separatethousands"] = v_colorbar.SeparatethousandsValidator() self._validators["showexponent"] = v_colorbar.ShowexponentValidator() self._validators["showticklabels"] = v_colorbar.ShowticklabelsValidator() self._validators["showtickprefix"] = v_colorbar.ShowtickprefixValidator() self._validators["showticksuffix"] = v_colorbar.ShowticksuffixValidator() self._validators["thickness"] = v_colorbar.ThicknessValidator() self._validators["thicknessmode"] = v_colorbar.ThicknessmodeValidator() self._validators["tick0"] = v_colorbar.Tick0Validator() self._validators["tickangle"] = v_colorbar.TickangleValidator() self._validators["tickcolor"] = v_colorbar.TickcolorValidator() self._validators["tickfont"] = v_colorbar.TickfontValidator() self._validators["tickformat"] = v_colorbar.TickformatValidator() self._validators["tickformatstops"] = v_colorbar.TickformatstopsValidator() self._validators[ "tickformatstopdefaults" ] = v_colorbar.TickformatstopValidator() self._validators["ticklen"] = v_colorbar.TicklenValidator() self._validators["tickmode"] = v_colorbar.TickmodeValidator() self._validators["tickprefix"] = v_colorbar.TickprefixValidator() self._validators["ticks"] = v_colorbar.TicksValidator() self._validators["ticksuffix"] = v_colorbar.TicksuffixValidator() self._validators["ticktext"] = v_colorbar.TicktextValidator() self._validators["ticktextsrc"] = v_colorbar.TicktextsrcValidator() self._validators["tickvals"] = v_colorbar.TickvalsValidator() self._validators["tickvalssrc"] = v_colorbar.TickvalssrcValidator() self._validators["tickwidth"] = v_colorbar.TickwidthValidator() self._validators["title"] = v_colorbar.TitleValidator() self._validators["x"] = v_colorbar.XValidator() self._validators["xanchor"] = v_colorbar.XanchorValidator() self._validators["xpad"] = v_colorbar.XpadValidator() self._validators["y"] = v_colorbar.YValidator() self._validators["yanchor"] = v_colorbar.YanchorValidator() self._validators["ypad"] = v_colorbar.YpadValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("borderwidth", None) self["borderwidth"] = borderwidth if borderwidth is not None else _v _v = arg.pop("dtick", None) self["dtick"] = dtick if dtick is not None else _v _v = arg.pop("exponentformat", None) self["exponentformat"] = exponentformat if exponentformat is not None else _v _v = arg.pop("len", None) self["len"] = len if len is not None else _v _v = arg.pop("lenmode", None) self["lenmode"] = lenmode if lenmode is not None else _v _v = arg.pop("nticks", None) self["nticks"] = nticks if nticks is not None else _v _v = arg.pop("outlinecolor", None) self["outlinecolor"] = outlinecolor if outlinecolor is not None else _v _v = arg.pop("outlinewidth", None) self["outlinewidth"] = outlinewidth if outlinewidth is not None else _v _v = arg.pop("separatethousands", None) self["separatethousands"] = ( separatethousands if separatethousands is not None else _v ) _v = arg.pop("showexponent", None) self["showexponent"] = showexponent if showexponent is not None else _v _v = arg.pop("showticklabels", None) self["showticklabels"] = showticklabels if showticklabels is not None else _v _v = arg.pop("showtickprefix", None) self["showtickprefix"] = showtickprefix if showtickprefix is not None else _v _v = arg.pop("showticksuffix", None) self["showticksuffix"] = showticksuffix if showticksuffix is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("thicknessmode", None) self["thicknessmode"] = thicknessmode if thicknessmode is not None else _v _v = arg.pop("tick0", None) self["tick0"] = tick0 if tick0 is not None else _v _v = arg.pop("tickangle", None) self["tickangle"] = tickangle if tickangle is not None else _v _v = arg.pop("tickcolor", None) self["tickcolor"] = tickcolor if tickcolor is not None else _v _v = arg.pop("tickfont", None) self["tickfont"] = tickfont if tickfont is not None else _v _v = arg.pop("tickformat", None) self["tickformat"] = tickformat if tickformat is not None else _v _v = arg.pop("tickformatstops", None) self["tickformatstops"] = tickformatstops if tickformatstops is not None else _v _v = arg.pop("tickformatstopdefaults", None) self["tickformatstopdefaults"] = ( tickformatstopdefaults if tickformatstopdefaults is not None else _v ) _v = arg.pop("ticklen", None) self["ticklen"] = ticklen if ticklen is not None else _v _v = arg.pop("tickmode", None) self["tickmode"] = tickmode if tickmode is not None else _v _v = arg.pop("tickprefix", None) self["tickprefix"] = tickprefix if tickprefix is not None else _v _v = arg.pop("ticks", None) self["ticks"] = ticks if ticks is not None else _v _v = arg.pop("ticksuffix", None) self["ticksuffix"] = ticksuffix if ticksuffix is not None else _v _v = arg.pop("ticktext", None) self["ticktext"] = ticktext if ticktext is not None else _v _v = arg.pop("ticktextsrc", None) self["ticktextsrc"] = ticktextsrc if ticktextsrc is not None else _v _v = arg.pop("tickvals", None) self["tickvals"] = tickvals if tickvals is not None else _v _v = arg.pop("tickvalssrc", None) self["tickvalssrc"] = tickvalssrc if tickvalssrc is not None else _v _v = arg.pop("tickwidth", None) self["tickwidth"] = tickwidth if tickwidth is not None else _v _v = arg.pop("title", None) self["title"] = title if title is not None else _v _v = arg.pop("titlefont", None) _v = titlefont if titlefont is not None else _v if _v is not None: self["titlefont"] = _v _v = arg.pop("titleside", None) _v = titleside if titleside is not None else _v if _v is not None: self["titleside"] = _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xanchor", None) self["xanchor"] = xanchor if xanchor is not None else _v _v = arg.pop("xpad", None) self["xpad"] = xpad if xpad is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("yanchor", None) self["yanchor"] = yanchor if yanchor is not None else _v _v = arg.pop("ypad", None) self["ypad"] = ypad if ypad is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["ColorBar", "Gradient", "Line", "colorbar"] from plotly.graph_objs.scattergeo.marker import colorbar plotly-4.4.1+dfsg.orig/plotly/graph_objs/scattergeo/__init__.py0000644000175000017500000031627013573721552024206 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Unselected(_BaseTraceHierarchyType): # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.scattergeo.unselected.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. size Sets the marker size of unselected points, applied only when a selection exists. Returns ------- plotly.graph_objs.scattergeo.unselected.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # textfont # -------- @property def textfont(self): """ The 'textfont' property is an instance of Textfont that may be specified as: - An instance of plotly.graph_objs.scattergeo.unselected.Textfont - A dict of string/value properties that will be passed to the Textfont constructor Supported dict properties: color Sets the text font color of unselected points, applied only when a selection exists. Returns ------- plotly.graph_objs.scattergeo.unselected.Textfont """ return self["textfont"] @textfont.setter def textfont(self, val): self["textfont"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattergeo" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ marker plotly.graph_objects.scattergeo.unselected.Marker instance or dict with compatible properties textfont plotly.graph_objects.scattergeo.unselected.Textfont instance or dict with compatible properties """ def __init__(self, arg=None, marker=None, textfont=None, **kwargs): """ Construct a new Unselected object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattergeo.Unselected marker plotly.graph_objects.scattergeo.unselected.Marker instance or dict with compatible properties textfont plotly.graph_objects.scattergeo.unselected.Textfont instance or dict with compatible properties Returns ------- Unselected """ super(Unselected, self).__init__("unselected") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattergeo.Unselected constructor must be a dict or an instance of plotly.graph_objs.scattergeo.Unselected""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattergeo import unselected as v_unselected # Initialize validators # --------------------- self._validators["marker"] = v_unselected.MarkerValidator() self._validators["textfont"] = v_unselected.TextfontValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v _v = arg.pop("textfont", None) self["textfont"] = textfont if textfont is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Textfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattergeo" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Textfont object Sets the text font. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattergeo.Textfont color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Textfont """ super(Textfont, self).__init__("textfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattergeo.Textfont constructor must be a dict or an instance of plotly.graph_objs.scattergeo.Textfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattergeo import textfont as v_textfont # Initialize validators # --------------------- self._validators["color"] = v_textfont.ColorValidator() self._validators["colorsrc"] = v_textfont.ColorsrcValidator() self._validators["family"] = v_textfont.FamilyValidator() self._validators["familysrc"] = v_textfont.FamilysrcValidator() self._validators["size"] = v_textfont.SizeValidator() self._validators["sizesrc"] = v_textfont.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Stream(_BaseTraceHierarchyType): # maxpoints # --------- @property def maxpoints(self): """ Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. The 'maxpoints' property is a number and may be specified as: - An int or float in the interval [0, 10000] Returns ------- int|float """ return self["maxpoints"] @maxpoints.setter def maxpoints(self, val): self["maxpoints"] = val # token # ----- @property def token(self): """ The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. The 'token' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["token"] @token.setter def token(self, val): self["token"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattergeo" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """ def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): """ Construct a new Stream object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattergeo.Stream maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- Stream """ super(Stream, self).__init__("stream") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattergeo.Stream constructor must be a dict or an instance of plotly.graph_objs.scattergeo.Stream""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattergeo import stream as v_stream # Initialize validators # --------------------- self._validators["maxpoints"] = v_stream.MaxpointsValidator() self._validators["token"] = v_stream.TokenValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("maxpoints", None) self["maxpoints"] = maxpoints if maxpoints is not None else _v _v = arg.pop("token", None) self["token"] = token if token is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Selected(_BaseTraceHierarchyType): # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.scattergeo.selected.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. size Sets the marker size of selected points. Returns ------- plotly.graph_objs.scattergeo.selected.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # textfont # -------- @property def textfont(self): """ The 'textfont' property is an instance of Textfont that may be specified as: - An instance of plotly.graph_objs.scattergeo.selected.Textfont - A dict of string/value properties that will be passed to the Textfont constructor Supported dict properties: color Sets the text font color of selected points. Returns ------- plotly.graph_objs.scattergeo.selected.Textfont """ return self["textfont"] @textfont.setter def textfont(self, val): self["textfont"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattergeo" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ marker plotly.graph_objects.scattergeo.selected.Marker instance or dict with compatible properties textfont plotly.graph_objects.scattergeo.selected.Textfont instance or dict with compatible properties """ def __init__(self, arg=None, marker=None, textfont=None, **kwargs): """ Construct a new Selected object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattergeo.Selected marker plotly.graph_objects.scattergeo.selected.Marker instance or dict with compatible properties textfont plotly.graph_objects.scattergeo.selected.Textfont instance or dict with compatible properties Returns ------- Selected """ super(Selected, self).__init__("selected") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattergeo.Selected constructor must be a dict or an instance of plotly.graph_objs.scattergeo.Selected""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattergeo import selected as v_selected # Initialize validators # --------------------- self._validators["marker"] = v_selected.MarkerValidator() self._validators["textfont"] = v_selected.TextfontValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v _v = arg.pop("textfont", None) self["textfont"] = textfont if textfont is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # autocolorscale # -------------- @property def autocolorscale(self): """ Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. The 'autocolorscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocolorscale"] @autocolorscale.setter def autocolorscale(self, val): self["autocolorscale"] = val # cauto # ----- @property def cauto(self): """ Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. The 'cauto' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["cauto"] @cauto.setter def cauto(self, val): self["cauto"] = val # cmax # ---- @property def cmax(self): """ Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. The 'cmax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmax"] @cmax.setter def cmax(self, val): self["cmax"] = val # cmid # ---- @property def cmid(self): """ Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. The 'cmid' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmid"] @cmid.setter def cmid(self, val): self["cmid"] = val # cmin # ---- @property def cmin(self): """ Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. The 'cmin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmin"] @cmin.setter def cmin(self, val): self["cmin"] = val # color # ----- @property def color(self): """ Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A number that will be interpreted as a color according to scattergeo.marker.colorscale - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # coloraxis # --------- @property def coloraxis(self): """ Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. The 'coloraxis' property is an identifier of a particular subplot, of type 'coloraxis', that may be specified as the string 'coloraxis' optionally followed by an integer >= 1 (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) Returns ------- str """ return self["coloraxis"] @coloraxis.setter def coloraxis(self, val): self["coloraxis"] = val # colorbar # -------- @property def colorbar(self): """ The 'colorbar' property is an instance of ColorBar that may be specified as: - An instance of plotly.graph_objs.scattergeo.marker.ColorBar - A dict of string/value properties that will be passed to the ColorBar constructor Supported dict properties: bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.scattergeo.mark er.colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.scattergeo.marker.colorbar.tickformatstopdefa ults), sets the default property values to use for elements of scattergeo.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.scattergeo.marker.colorbar .Title instance or dict with compatible properties titlefont Deprecated: Please use scattergeo.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use scattergeo.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- plotly.graph_objs.scattergeo.marker.ColorBar """ return self["colorbar"] @colorbar.setter def colorbar(self, val): self["colorbar"] = val # colorscale # ---------- @property def colorscale(self): """ Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnB u,Greens,YlOrRd,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland ,Jet,Hot,Blackbody,Earth,Electric,Viridis,Cividis. The 'colorscale' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # gradient # -------- @property def gradient(self): """ The 'gradient' property is an instance of Gradient that may be specified as: - An instance of plotly.graph_objs.scattergeo.marker.Gradient - A dict of string/value properties that will be passed to the Gradient constructor Supported dict properties: color Sets the final color of the gradient fill: the center color for radial, the right for horizontal, or the bottom for vertical. colorsrc Sets the source reference on plot.ly for color . type Sets the type of gradient used to fill the markers typesrc Sets the source reference on plot.ly for type . Returns ------- plotly.graph_objs.scattergeo.marker.Gradient """ return self["gradient"] @gradient.setter def gradient(self, val): self["gradient"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.scattergeo.marker.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,R eds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Black body,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . Returns ------- plotly.graph_objs.scattergeo.marker.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # opacity # ------- @property def opacity(self): """ Sets the marker opacity. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # opacitysrc # ---------- @property def opacitysrc(self): """ Sets the source reference on plot.ly for opacity . The 'opacitysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["opacitysrc"] @opacitysrc.setter def opacitysrc(self, val): self["opacitysrc"] = val # reversescale # ------------ @property def reversescale(self): """ Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. The 'reversescale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["reversescale"] @reversescale.setter def reversescale(self, val): self["reversescale"] = val # showscale # --------- @property def showscale(self): """ Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. The 'showscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showscale"] @showscale.setter def showscale(self, val): self["showscale"] = val # size # ---- @property def size(self): """ Sets the marker size (in px). The 'size' property is a number and may be specified as: - An int or float in the interval [0, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizemin # ------- @property def sizemin(self): """ Has an effect only if `marker.size` is set to a numerical array. Sets the minimum size (in px) of the rendered marker points. The 'sizemin' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["sizemin"] @sizemin.setter def sizemin(self, val): self["sizemin"] = val # sizemode # -------- @property def sizemode(self): """ Has an effect only if `marker.size` is set to a numerical array. Sets the rule for which the data in `size` is converted to pixels. The 'sizemode' property is an enumeration that may be specified as: - One of the following enumeration values: ['diameter', 'area'] Returns ------- Any """ return self["sizemode"] @sizemode.setter def sizemode(self, val): self["sizemode"] = val # sizeref # ------- @property def sizeref(self): """ Has an effect only if `marker.size` is set to a numerical array. Sets the scale factor used to determine the rendered size of marker points. Use with `sizemin` and `sizemode`. The 'sizeref' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["sizeref"] @sizeref.setter def sizeref(self, val): self["sizeref"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # symbol # ------ @property def symbol(self): """ Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot-open" to a symbol name. The 'symbol' property is an enumeration that may be specified as: - One of the following enumeration values: [0, 'circle', 100, 'circle-open', 200, 'circle-dot', 300, 'circle-open-dot', 1, 'square', 101, 'square-open', 201, 'square-dot', 301, 'square-open-dot', 2, 'diamond', 102, 'diamond-open', 202, 'diamond-dot', 302, 'diamond-open-dot', 3, 'cross', 103, 'cross-open', 203, 'cross-dot', 303, 'cross-open-dot', 4, 'x', 104, 'x-open', 204, 'x-dot', 304, 'x-open-dot', 5, 'triangle-up', 105, 'triangle-up-open', 205, 'triangle-up-dot', 305, 'triangle-up-open-dot', 6, 'triangle-down', 106, 'triangle-down-open', 206, 'triangle-down-dot', 306, 'triangle-down-open-dot', 7, 'triangle-left', 107, 'triangle-left-open', 207, 'triangle-left-dot', 307, 'triangle-left-open-dot', 8, 'triangle-right', 108, 'triangle-right-open', 208, 'triangle-right-dot', 308, 'triangle-right-open-dot', 9, 'triangle-ne', 109, 'triangle-ne-open', 209, 'triangle-ne-dot', 309, 'triangle-ne-open-dot', 10, 'triangle-se', 110, 'triangle-se-open', 210, 'triangle-se-dot', 310, 'triangle-se-open-dot', 11, 'triangle-sw', 111, 'triangle-sw-open', 211, 'triangle-sw-dot', 311, 'triangle-sw-open-dot', 12, 'triangle-nw', 112, 'triangle-nw-open', 212, 'triangle-nw-dot', 312, 'triangle-nw-open-dot', 13, 'pentagon', 113, 'pentagon-open', 213, 'pentagon-dot', 313, 'pentagon-open-dot', 14, 'hexagon', 114, 'hexagon-open', 214, 'hexagon-dot', 314, 'hexagon-open-dot', 15, 'hexagon2', 115, 'hexagon2-open', 215, 'hexagon2-dot', 315, 'hexagon2-open-dot', 16, 'octagon', 116, 'octagon-open', 216, 'octagon-dot', 316, 'octagon-open-dot', 17, 'star', 117, 'star-open', 217, 'star-dot', 317, 'star-open-dot', 18, 'hexagram', 118, 'hexagram-open', 218, 'hexagram-dot', 318, 'hexagram-open-dot', 19, 'star-triangle-up', 119, 'star-triangle-up-open', 219, 'star-triangle-up-dot', 319, 'star-triangle-up-open-dot', 20, 'star-triangle-down', 120, 'star-triangle-down-open', 220, 'star-triangle-down-dot', 320, 'star-triangle-down-open-dot', 21, 'star-square', 121, 'star-square-open', 221, 'star-square-dot', 321, 'star-square-open-dot', 22, 'star-diamond', 122, 'star-diamond-open', 222, 'star-diamond-dot', 322, 'star-diamond-open-dot', 23, 'diamond-tall', 123, 'diamond-tall-open', 223, 'diamond-tall-dot', 323, 'diamond-tall-open-dot', 24, 'diamond-wide', 124, 'diamond-wide-open', 224, 'diamond-wide-dot', 324, 'diamond-wide-open-dot', 25, 'hourglass', 125, 'hourglass-open', 26, 'bowtie', 126, 'bowtie-open', 27, 'circle-cross', 127, 'circle-cross-open', 28, 'circle-x', 128, 'circle-x-open', 29, 'square-cross', 129, 'square-cross-open', 30, 'square-x', 130, 'square-x-open', 31, 'diamond-cross', 131, 'diamond-cross-open', 32, 'diamond-x', 132, 'diamond-x-open', 33, 'cross-thin', 133, 'cross-thin-open', 34, 'x-thin', 134, 'x-thin-open', 35, 'asterisk', 135, 'asterisk-open', 36, 'hash', 136, 'hash-open', 236, 'hash-dot', 336, 'hash-open-dot', 37, 'y-up', 137, 'y-up-open', 38, 'y-down', 138, 'y-down-open', 39, 'y-left', 139, 'y-left-open', 40, 'y-right', 140, 'y-right-open', 41, 'line-ew', 141, 'line-ew-open', 42, 'line-ns', 142, 'line-ns-open', 43, 'line-ne', 143, 'line-ne-open', 44, 'line-nw', 144, 'line-nw-open'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["symbol"] @symbol.setter def symbol(self, val): self["symbol"] = val # symbolsrc # --------- @property def symbolsrc(self): """ Sets the source reference on plot.ly for symbol . The 'symbolsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["symbolsrc"] @symbolsrc.setter def symbolsrc(self, val): self["symbolsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattergeo" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.scattergeo.marker.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu ,Reds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . gradient plotly.graph_objects.scattergeo.marker.Gradient instance or dict with compatible properties line plotly.graph_objects.scattergeo.marker.Line instance or dict with compatible properties opacity Sets the marker opacity. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. size Sets the marker size (in px). sizemin Has an effect only if `marker.size` is set to a numerical array. Sets the minimum size (in px) of the rendered marker points. sizemode Has an effect only if `marker.size` is set to a numerical array. Sets the rule for which the data in `size` is converted to pixels. sizeref Has an effect only if `marker.size` is set to a numerical array. Sets the scale factor used to determine the rendered size of marker points. Use with `sizemin` and `sizemode`. sizesrc Sets the source reference on plot.ly for size . symbol Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot- open" to a symbol name. symbolsrc Sets the source reference on plot.ly for symbol . """ def __init__( self, arg=None, autocolorscale=None, cauto=None, cmax=None, cmid=None, cmin=None, color=None, coloraxis=None, colorbar=None, colorscale=None, colorsrc=None, gradient=None, line=None, opacity=None, opacitysrc=None, reversescale=None, showscale=None, size=None, sizemin=None, sizemode=None, sizeref=None, sizesrc=None, symbol=None, symbolsrc=None, **kwargs ): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattergeo.Marker autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.scattergeo.marker.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu ,Reds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . gradient plotly.graph_objects.scattergeo.marker.Gradient instance or dict with compatible properties line plotly.graph_objects.scattergeo.marker.Line instance or dict with compatible properties opacity Sets the marker opacity. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. size Sets the marker size (in px). sizemin Has an effect only if `marker.size` is set to a numerical array. Sets the minimum size (in px) of the rendered marker points. sizemode Has an effect only if `marker.size` is set to a numerical array. Sets the rule for which the data in `size` is converted to pixels. sizeref Has an effect only if `marker.size` is set to a numerical array. Sets the scale factor used to determine the rendered size of marker points. Use with `sizemin` and `sizemode`. sizesrc Sets the source reference on plot.ly for size . symbol Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot- open" to a symbol name. symbolsrc Sets the source reference on plot.ly for symbol . Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattergeo.Marker constructor must be a dict or an instance of plotly.graph_objs.scattergeo.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattergeo import marker as v_marker # Initialize validators # --------------------- self._validators["autocolorscale"] = v_marker.AutocolorscaleValidator() self._validators["cauto"] = v_marker.CautoValidator() self._validators["cmax"] = v_marker.CmaxValidator() self._validators["cmid"] = v_marker.CmidValidator() self._validators["cmin"] = v_marker.CminValidator() self._validators["color"] = v_marker.ColorValidator() self._validators["coloraxis"] = v_marker.ColoraxisValidator() self._validators["colorbar"] = v_marker.ColorBarValidator() self._validators["colorscale"] = v_marker.ColorscaleValidator() self._validators["colorsrc"] = v_marker.ColorsrcValidator() self._validators["gradient"] = v_marker.GradientValidator() self._validators["line"] = v_marker.LineValidator() self._validators["opacity"] = v_marker.OpacityValidator() self._validators["opacitysrc"] = v_marker.OpacitysrcValidator() self._validators["reversescale"] = v_marker.ReversescaleValidator() self._validators["showscale"] = v_marker.ShowscaleValidator() self._validators["size"] = v_marker.SizeValidator() self._validators["sizemin"] = v_marker.SizeminValidator() self._validators["sizemode"] = v_marker.SizemodeValidator() self._validators["sizeref"] = v_marker.SizerefValidator() self._validators["sizesrc"] = v_marker.SizesrcValidator() self._validators["symbol"] = v_marker.SymbolValidator() self._validators["symbolsrc"] = v_marker.SymbolsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autocolorscale", None) self["autocolorscale"] = autocolorscale if autocolorscale is not None else _v _v = arg.pop("cauto", None) self["cauto"] = cauto if cauto is not None else _v _v = arg.pop("cmax", None) self["cmax"] = cmax if cmax is not None else _v _v = arg.pop("cmid", None) self["cmid"] = cmid if cmid is not None else _v _v = arg.pop("cmin", None) self["cmin"] = cmin if cmin is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("coloraxis", None) self["coloraxis"] = coloraxis if coloraxis is not None else _v _v = arg.pop("colorbar", None) self["colorbar"] = colorbar if colorbar is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("gradient", None) self["gradient"] = gradient if gradient is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("opacitysrc", None) self["opacitysrc"] = opacitysrc if opacitysrc is not None else _v _v = arg.pop("reversescale", None) self["reversescale"] = reversescale if reversescale is not None else _v _v = arg.pop("showscale", None) self["showscale"] = showscale if showscale is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizemin", None) self["sizemin"] = sizemin if sizemin is not None else _v _v = arg.pop("sizemode", None) self["sizemode"] = sizemode if sizemode is not None else _v _v = arg.pop("sizeref", None) self["sizeref"] = sizeref if sizeref is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v _v = arg.pop("symbol", None) self["symbol"] = symbol if symbol is not None else _v _v = arg.pop("symbolsrc", None) self["symbolsrc"] = symbolsrc if symbolsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the line color. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # dash # ---- @property def dash(self): """ Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). The 'dash' property is an enumeration that may be specified as: - One of the following dash styles: ['solid', 'dot', 'dash', 'longdash', 'dashdot', 'longdashdot'] - A string containing a dash length list in pixels or percentages (e.g. '5px 10px 2px 2px', '5, 10, 2, 2', '10% 20% 40%', etc.) Returns ------- str """ return self["dash"] @dash.setter def dash(self, val): self["dash"] = val # width # ----- @property def width(self): """ Sets the line width (in px). The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattergeo" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the line color. dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). width Sets the line width (in px). """ def __init__(self, arg=None, color=None, dash=None, width=None, **kwargs): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattergeo.Line color Sets the line color. dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). width Sets the line width (in px). Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattergeo.Line constructor must be a dict or an instance of plotly.graph_objs.scattergeo.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattergeo import line as v_line # Initialize validators # --------------------- self._validators["color"] = v_line.ColorValidator() self._validators["dash"] = v_line.DashValidator() self._validators["width"] = v_line.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("dash", None) self["dash"] = dash if dash is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Hoverlabel(_BaseTraceHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'right', 'auto'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["align"] @align.setter def align(self, val): self["align"] = val # alignsrc # -------- @property def alignsrc(self): """ Sets the source reference on plot.ly for align . The 'alignsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["alignsrc"] @alignsrc.setter def alignsrc(self, val): self["alignsrc"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the hover labels for this trace The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bgcolorsrc # ---------- @property def bgcolorsrc(self): """ Sets the source reference on plot.ly for bgcolor . The 'bgcolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bgcolorsrc"] @bgcolorsrc.setter def bgcolorsrc(self, val): self["bgcolorsrc"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the border color of the hover labels for this trace. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # bordercolorsrc # -------------- @property def bordercolorsrc(self): """ Sets the source reference on plot.ly for bordercolor . The 'bordercolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bordercolorsrc"] @bordercolorsrc.setter def bordercolorsrc(self, val): self["bordercolorsrc"] = val # font # ---- @property def font(self): """ Sets the font used in hover labels. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.scattergeo.hoverlabel.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.scattergeo.hoverlabel.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # namelength # ---------- @property def namelength(self): """ Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. The 'namelength' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [-1, 9223372036854775807] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|numpy.ndarray """ return self["namelength"] @namelength.setter def namelength(self, val): self["namelength"] = val # namelengthsrc # ------------- @property def namelengthsrc(self): """ Sets the source reference on plot.ly for namelength . The 'namelengthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["namelengthsrc"] @namelengthsrc.setter def namelengthsrc(self, val): self["namelengthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattergeo" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """ def __init__( self, arg=None, align=None, alignsrc=None, bgcolor=None, bgcolorsrc=None, bordercolor=None, bordercolorsrc=None, font=None, namelength=None, namelengthsrc=None, **kwargs ): """ Construct a new Hoverlabel object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattergeo.Hoverlabel align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- Hoverlabel """ super(Hoverlabel, self).__init__("hoverlabel") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattergeo.Hoverlabel constructor must be a dict or an instance of plotly.graph_objs.scattergeo.Hoverlabel""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattergeo import hoverlabel as v_hoverlabel # Initialize validators # --------------------- self._validators["align"] = v_hoverlabel.AlignValidator() self._validators["alignsrc"] = v_hoverlabel.AlignsrcValidator() self._validators["bgcolor"] = v_hoverlabel.BgcolorValidator() self._validators["bgcolorsrc"] = v_hoverlabel.BgcolorsrcValidator() self._validators["bordercolor"] = v_hoverlabel.BordercolorValidator() self._validators["bordercolorsrc"] = v_hoverlabel.BordercolorsrcValidator() self._validators["font"] = v_hoverlabel.FontValidator() self._validators["namelength"] = v_hoverlabel.NamelengthValidator() self._validators["namelengthsrc"] = v_hoverlabel.NamelengthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("alignsrc", None) self["alignsrc"] = alignsrc if alignsrc is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bgcolorsrc", None) self["bgcolorsrc"] = bgcolorsrc if bgcolorsrc is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("bordercolorsrc", None) self["bordercolorsrc"] = bordercolorsrc if bordercolorsrc is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("namelength", None) self["namelength"] = namelength if namelength is not None else _v _v = arg.pop("namelengthsrc", None) self["namelengthsrc"] = namelengthsrc if namelengthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = [ "Hoverlabel", "Line", "Marker", "Selected", "Stream", "Textfont", "Unselected", "hoverlabel", "marker", "selected", "unselected", ] from plotly.graph_objs.scattergeo import unselected from plotly.graph_objs.scattergeo import selected from plotly.graph_objs.scattergeo import marker from plotly.graph_objs.scattergeo import hoverlabel plotly-4.4.1+dfsg.orig/plotly/graph_objs/scattergeo/selected/0000755000175000017500000000000013573746613023661 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scattergeo/selected/__init__.py0000644000175000017500000002650413573721551025773 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Textfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the text font color of selected points. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattergeo.selected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the text font color of selected points. """ def __init__(self, arg=None, color=None, **kwargs): """ Construct a new Textfont object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattergeo.selected.Textfont color Sets the text font color of selected points. Returns ------- Textfont """ super(Textfont, self).__init__("textfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattergeo.selected.Textfont constructor must be a dict or an instance of plotly.graph_objs.scattergeo.selected.Textfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattergeo.selected import textfont as v_textfont # Initialize validators # --------------------- self._validators["color"] = v_textfont.ColorValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the marker color of selected points. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # opacity # ------- @property def opacity(self): """ Sets the marker opacity of selected points. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # size # ---- @property def size(self): """ Sets the marker size of selected points. The 'size' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattergeo.selected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. size Sets the marker size of selected points. """ def __init__(self, arg=None, color=None, opacity=None, size=None, **kwargs): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattergeo.selected.Marker color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. size Sets the marker size of selected points. Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattergeo.selected.Marker constructor must be a dict or an instance of plotly.graph_objs.scattergeo.selected.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattergeo.selected import marker as v_marker # Initialize validators # --------------------- self._validators["color"] = v_marker.ColorValidator() self._validators["opacity"] = v_marker.OpacityValidator() self._validators["size"] = v_marker.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Marker", "Textfont"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/contourcarpet/0000755000175000017500000000000013573746613022621 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/contourcarpet/colorbar/0000755000175000017500000000000013573746613024424 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/contourcarpet/colorbar/title/0000755000175000017500000000000013573746613025545 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/contourcarpet/colorbar/title/__init__.py0000644000175000017500000002056313573721546027662 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "contourcarpet.colorbar.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.contourcarpet.colorbar.title.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.contourcarpet.colorbar.title.Font constructor must be a dict or an instance of plotly.graph_objs.contourcarpet.colorbar.title.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.contourcarpet.colorbar.title import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/contourcarpet/colorbar/__init__.py0000644000175000017500000006073213573721546026543 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Title(_BaseTraceHierarchyType): # font # ---- @property def font(self): """ Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.contourcarpet.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.contourcarpet.colorbar.title.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # side # ---- @property def side(self): """ Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- Any """ return self["side"] @side.setter def side(self, val): self["side"] = val # text # ---- @property def text(self): """ Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "contourcarpet.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """ def __init__(self, arg=None, font=None, side=None, text=None, **kwargs): """ Construct a new Title object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.contourcarpet.colorbar.Title font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- Title """ super(Title, self).__init__("title") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.contourcarpet.colorbar.Title constructor must be a dict or an instance of plotly.graph_objs.contourcarpet.colorbar.Title""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.contourcarpet.colorbar import title as v_title # Initialize validators # --------------------- self._validators["font"] = v_title.FontValidator() self._validators["side"] = v_title.SideValidator() self._validators["text"] = v_title.TextValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("side", None) self["side"] = side if side is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickformatstop(_BaseTraceHierarchyType): # dtickrange # ---------- @property def dtickrange(self): """ range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" The 'dtickrange' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'dtickrange[0]' property accepts values of any type (1) The 'dtickrange[1]' property accepts values of any type Returns ------- list """ return self["dtickrange"] @dtickrange.setter def dtickrange(self, val): self["dtickrange"] = val # enabled # ------- @property def enabled(self): """ Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. The 'enabled' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["enabled"] @enabled.setter def enabled(self, val): self["enabled"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # value # ----- @property def value(self): """ string - dtickformat for described zoom level, the same as "tickformat" The 'value' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "contourcarpet.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """ def __init__( self, arg=None, dtickrange=None, enabled=None, name=None, templateitemname=None, value=None, **kwargs ): """ Construct a new Tickformatstop object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.contourcarpet.colorbar.Tickformatstop dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- Tickformatstop """ super(Tickformatstop, self).__init__("tickformatstops") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.contourcarpet.colorbar.Tickformatstop constructor must be a dict or an instance of plotly.graph_objs.contourcarpet.colorbar.Tickformatstop""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.contourcarpet.colorbar import ( tickformatstop as v_tickformatstop, ) # Initialize validators # --------------------- self._validators["dtickrange"] = v_tickformatstop.DtickrangeValidator() self._validators["enabled"] = v_tickformatstop.EnabledValidator() self._validators["name"] = v_tickformatstop.NameValidator() self._validators[ "templateitemname" ] = v_tickformatstop.TemplateitemnameValidator() self._validators["value"] = v_tickformatstop.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtickrange", None) self["dtickrange"] = dtickrange if dtickrange is not None else _v _v = arg.pop("enabled", None) self["enabled"] = enabled if enabled is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "contourcarpet.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Tickfont object Sets the color bar's tick label font Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.contourcarpet.colorbar.Tickfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Tickfont """ super(Tickfont, self).__init__("tickfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.contourcarpet.colorbar.Tickfont constructor must be a dict or an instance of plotly.graph_objs.contourcarpet.colorbar.Tickfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.contourcarpet.colorbar import tickfont as v_tickfont # Initialize validators # --------------------- self._validators["color"] = v_tickfont.ColorValidator() self._validators["family"] = v_tickfont.FamilyValidator() self._validators["size"] = v_tickfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Tickfont", "Tickformatstop", "Tickformatstop", "Title", "title"] from plotly.graph_objs.contourcarpet.colorbar import title plotly-4.4.1+dfsg.orig/plotly/graph_objs/contourcarpet/contours/0000755000175000017500000000000013573746613024475 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/contourcarpet/contours/__init__.py0000644000175000017500000002070513573721546026610 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Labelfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "contourcarpet.contours" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Labelfont object Sets the font used for labeling the contour levels. The default color comes from the lines, if shown. The default family and size come from `layout.font`. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.contourcarpet.contours.Labelfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Labelfont """ super(Labelfont, self).__init__("labelfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.contourcarpet.contours.Labelfont constructor must be a dict or an instance of plotly.graph_objs.contourcarpet.contours.Labelfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.contourcarpet.contours import labelfont as v_labelfont # Initialize validators # --------------------- self._validators["color"] = v_labelfont.ColorValidator() self._validators["family"] = v_labelfont.FamilyValidator() self._validators["size"] = v_labelfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Labelfont"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/contourcarpet/__init__.py0000644000175000017500000030244313573721547024737 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Stream(_BaseTraceHierarchyType): # maxpoints # --------- @property def maxpoints(self): """ Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. The 'maxpoints' property is a number and may be specified as: - An int or float in the interval [0, 10000] Returns ------- int|float """ return self["maxpoints"] @maxpoints.setter def maxpoints(self, val): self["maxpoints"] = val # token # ----- @property def token(self): """ The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. The 'token' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["token"] @token.setter def token(self, val): self["token"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "contourcarpet" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """ def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): """ Construct a new Stream object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.contourcarpet.Stream maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- Stream """ super(Stream, self).__init__("stream") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.contourcarpet.Stream constructor must be a dict or an instance of plotly.graph_objs.contourcarpet.Stream""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.contourcarpet import stream as v_stream # Initialize validators # --------------------- self._validators["maxpoints"] = v_stream.MaxpointsValidator() self._validators["token"] = v_stream.TokenValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("maxpoints", None) self["maxpoints"] = maxpoints if maxpoints is not None else _v _v = arg.pop("token", None) self["token"] = token if token is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the color of the contour level. Has no effect if `contours.coloring` is set to "lines". The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # dash # ---- @property def dash(self): """ Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). The 'dash' property is an enumeration that may be specified as: - One of the following dash styles: ['solid', 'dot', 'dash', 'longdash', 'dashdot', 'longdashdot'] - A string containing a dash length list in pixels or percentages (e.g. '5px 10px 2px 2px', '5, 10, 2, 2', '10% 20% 40%', etc.) Returns ------- str """ return self["dash"] @dash.setter def dash(self, val): self["dash"] = val # smoothing # --------- @property def smoothing(self): """ Sets the amount of smoothing for the contour lines, where 0 corresponds to no smoothing. The 'smoothing' property is a number and may be specified as: - An int or float in the interval [0, 1.3] Returns ------- int|float """ return self["smoothing"] @smoothing.setter def smoothing(self, val): self["smoothing"] = val # width # ----- @property def width(self): """ Sets the contour line width in (in px) Defaults to 0.5 when `contours.type` is "levels". Defaults to 2 when `contour.type` is "constraint". The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "contourcarpet" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the color of the contour level. Has no effect if `contours.coloring` is set to "lines". dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). smoothing Sets the amount of smoothing for the contour lines, where 0 corresponds to no smoothing. width Sets the contour line width in (in px) Defaults to 0.5 when `contours.type` is "levels". Defaults to 2 when `contour.type` is "constraint". """ def __init__( self, arg=None, color=None, dash=None, smoothing=None, width=None, **kwargs ): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.contourcarpet.Line color Sets the color of the contour level. Has no effect if `contours.coloring` is set to "lines". dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). smoothing Sets the amount of smoothing for the contour lines, where 0 corresponds to no smoothing. width Sets the contour line width in (in px) Defaults to 0.5 when `contours.type` is "levels". Defaults to 2 when `contour.type` is "constraint". Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.contourcarpet.Line constructor must be a dict or an instance of plotly.graph_objs.contourcarpet.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.contourcarpet import line as v_line # Initialize validators # --------------------- self._validators["color"] = v_line.ColorValidator() self._validators["dash"] = v_line.DashValidator() self._validators["smoothing"] = v_line.SmoothingValidator() self._validators["width"] = v_line.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("dash", None) self["dash"] = dash if dash is not None else _v _v = arg.pop("smoothing", None) self["smoothing"] = smoothing if smoothing is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Contours(_BaseTraceHierarchyType): # coloring # -------- @property def coloring(self): """ Determines the coloring method showing the contour values. If "fill", coloring is done evenly between each contour level If "lines", coloring is done on the contour lines. If "none", no coloring is applied on this trace. The 'coloring' property is an enumeration that may be specified as: - One of the following enumeration values: ['fill', 'lines', 'none'] Returns ------- Any """ return self["coloring"] @coloring.setter def coloring(self, val): self["coloring"] = val # end # --- @property def end(self): """ Sets the end contour level value. Must be more than `contours.start` The 'end' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["end"] @end.setter def end(self, val): self["end"] = val # labelfont # --------- @property def labelfont(self): """ Sets the font used for labeling the contour levels. The default color comes from the lines, if shown. The default family and size come from `layout.font`. The 'labelfont' property is an instance of Labelfont that may be specified as: - An instance of plotly.graph_objs.contourcarpet.contours.Labelfont - A dict of string/value properties that will be passed to the Labelfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.contourcarpet.contours.Labelfont """ return self["labelfont"] @labelfont.setter def labelfont(self, val): self["labelfont"] = val # labelformat # ----------- @property def labelformat(self): """ Sets the contour label formatting rule using d3 formatting mini-language which is very similar to Python, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format The 'labelformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["labelformat"] @labelformat.setter def labelformat(self, val): self["labelformat"] = val # operation # --------- @property def operation(self): """ Sets the constraint operation. "=" keeps regions equal to `value` "<" and "<=" keep regions less than `value` ">" and ">=" keep regions greater than `value` "[]", "()", "[)", and "(]" keep regions inside `value[0]` to `value[1]` "][", ")(", "](", ")[" keep regions outside `value[0]` to value[1]` Open vs. closed intervals make no difference to constraint display, but all versions are allowed for consistency with filter transforms. The 'operation' property is an enumeration that may be specified as: - One of the following enumeration values: ['=', '<', '>=', '>', '<=', '[]', '()', '[)', '(]', '][', ')(', '](', ')['] Returns ------- Any """ return self["operation"] @operation.setter def operation(self, val): self["operation"] = val # showlabels # ---------- @property def showlabels(self): """ Determines whether to label the contour lines with their values. The 'showlabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showlabels"] @showlabels.setter def showlabels(self, val): self["showlabels"] = val # showlines # --------- @property def showlines(self): """ Determines whether or not the contour lines are drawn. Has an effect only if `contours.coloring` is set to "fill". The 'showlines' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showlines"] @showlines.setter def showlines(self, val): self["showlines"] = val # size # ---- @property def size(self): """ Sets the step between each contour level. Must be positive. The 'size' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # start # ----- @property def start(self): """ Sets the starting contour level value. Must be less than `contours.end` The 'start' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["start"] @start.setter def start(self, val): self["start"] = val # type # ---- @property def type(self): """ If `levels`, the data is represented as a contour plot with multiple levels displayed. If `constraint`, the data is represented as constraints with the invalid region shaded as specified by the `operation` and `value` parameters. The 'type' property is an enumeration that may be specified as: - One of the following enumeration values: ['levels', 'constraint'] Returns ------- Any """ return self["type"] @type.setter def type(self, val): self["type"] = val # value # ----- @property def value(self): """ Sets the value or values of the constraint boundary. When `operation` is set to one of the comparison values (=,<,>=,>,<=) "value" is expected to be a number. When `operation` is set to one of the interval values ([],(),[),(],][,)(,](,)[) "value" is expected to be an array of two numbers where the first is the lower bound and the second is the upper bound. The 'value' property accepts values of any type Returns ------- Any """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "contourcarpet" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ coloring Determines the coloring method showing the contour values. If "fill", coloring is done evenly between each contour level If "lines", coloring is done on the contour lines. If "none", no coloring is applied on this trace. end Sets the end contour level value. Must be more than `contours.start` labelfont Sets the font used for labeling the contour levels. The default color comes from the lines, if shown. The default family and size come from `layout.font`. labelformat Sets the contour label formatting rule using d3 formatting mini-language which is very similar to Python, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format operation Sets the constraint operation. "=" keeps regions equal to `value` "<" and "<=" keep regions less than `value` ">" and ">=" keep regions greater than `value` "[]", "()", "[)", and "(]" keep regions inside `value[0]` to `value[1]` "][", ")(", "](", ")[" keep regions outside `value[0]` to value[1]` Open vs. closed intervals make no difference to constraint display, but all versions are allowed for consistency with filter transforms. showlabels Determines whether to label the contour lines with their values. showlines Determines whether or not the contour lines are drawn. Has an effect only if `contours.coloring` is set to "fill". size Sets the step between each contour level. Must be positive. start Sets the starting contour level value. Must be less than `contours.end` type If `levels`, the data is represented as a contour plot with multiple levels displayed. If `constraint`, the data is represented as constraints with the invalid region shaded as specified by the `operation` and `value` parameters. value Sets the value or values of the constraint boundary. When `operation` is set to one of the comparison values (=,<,>=,>,<=) "value" is expected to be a number. When `operation` is set to one of the interval values ([],(),[),(],][,)(,](,)[) "value" is expected to be an array of two numbers where the first is the lower bound and the second is the upper bound. """ def __init__( self, arg=None, coloring=None, end=None, labelfont=None, labelformat=None, operation=None, showlabels=None, showlines=None, size=None, start=None, type=None, value=None, **kwargs ): """ Construct a new Contours object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.contourcarpet.Contours coloring Determines the coloring method showing the contour values. If "fill", coloring is done evenly between each contour level If "lines", coloring is done on the contour lines. If "none", no coloring is applied on this trace. end Sets the end contour level value. Must be more than `contours.start` labelfont Sets the font used for labeling the contour levels. The default color comes from the lines, if shown. The default family and size come from `layout.font`. labelformat Sets the contour label formatting rule using d3 formatting mini-language which is very similar to Python, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format operation Sets the constraint operation. "=" keeps regions equal to `value` "<" and "<=" keep regions less than `value` ">" and ">=" keep regions greater than `value` "[]", "()", "[)", and "(]" keep regions inside `value[0]` to `value[1]` "][", ")(", "](", ")[" keep regions outside `value[0]` to value[1]` Open vs. closed intervals make no difference to constraint display, but all versions are allowed for consistency with filter transforms. showlabels Determines whether to label the contour lines with their values. showlines Determines whether or not the contour lines are drawn. Has an effect only if `contours.coloring` is set to "fill". size Sets the step between each contour level. Must be positive. start Sets the starting contour level value. Must be less than `contours.end` type If `levels`, the data is represented as a contour plot with multiple levels displayed. If `constraint`, the data is represented as constraints with the invalid region shaded as specified by the `operation` and `value` parameters. value Sets the value or values of the constraint boundary. When `operation` is set to one of the comparison values (=,<,>=,>,<=) "value" is expected to be a number. When `operation` is set to one of the interval values ([],(),[),(],][,)(,](,)[) "value" is expected to be an array of two numbers where the first is the lower bound and the second is the upper bound. Returns ------- Contours """ super(Contours, self).__init__("contours") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.contourcarpet.Contours constructor must be a dict or an instance of plotly.graph_objs.contourcarpet.Contours""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.contourcarpet import contours as v_contours # Initialize validators # --------------------- self._validators["coloring"] = v_contours.ColoringValidator() self._validators["end"] = v_contours.EndValidator() self._validators["labelfont"] = v_contours.LabelfontValidator() self._validators["labelformat"] = v_contours.LabelformatValidator() self._validators["operation"] = v_contours.OperationValidator() self._validators["showlabels"] = v_contours.ShowlabelsValidator() self._validators["showlines"] = v_contours.ShowlinesValidator() self._validators["size"] = v_contours.SizeValidator() self._validators["start"] = v_contours.StartValidator() self._validators["type"] = v_contours.TypeValidator() self._validators["value"] = v_contours.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("coloring", None) self["coloring"] = coloring if coloring is not None else _v _v = arg.pop("end", None) self["end"] = end if end is not None else _v _v = arg.pop("labelfont", None) self["labelfont"] = labelfont if labelfont is not None else _v _v = arg.pop("labelformat", None) self["labelformat"] = labelformat if labelformat is not None else _v _v = arg.pop("operation", None) self["operation"] = operation if operation is not None else _v _v = arg.pop("showlabels", None) self["showlabels"] = showlabels if showlabels is not None else _v _v = arg.pop("showlines", None) self["showlines"] = showlines if showlines is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("start", None) self["start"] = start if start is not None else _v _v = arg.pop("type", None) self["type"] = type if type is not None else _v _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class ColorBar(_BaseTraceHierarchyType): # bgcolor # ------- @property def bgcolor(self): """ Sets the color of padded area. The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the axis line color. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # borderwidth # ----------- @property def borderwidth(self): """ Sets the width (in px) or the border enclosing this color bar. The 'borderwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["borderwidth"] @borderwidth.setter def borderwidth(self, val): self["borderwidth"] = val # dtick # ----- @property def dtick(self): """ Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" The 'dtick' property accepts values of any type Returns ------- Any """ return self["dtick"] @dtick.setter def dtick(self, val): self["dtick"] = val # exponentformat # -------------- @property def exponentformat(self): """ Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. The 'exponentformat' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'e', 'E', 'power', 'SI', 'B'] Returns ------- Any """ return self["exponentformat"] @exponentformat.setter def exponentformat(self, val): self["exponentformat"] = val # len # --- @property def len(self): """ Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. The 'len' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["len"] @len.setter def len(self, val): self["len"] = val # lenmode # ------- @property def lenmode(self): """ Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. The 'lenmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["lenmode"] @lenmode.setter def lenmode(self, val): self["lenmode"] = val # nticks # ------ @property def nticks(self): """ Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". The 'nticks' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nticks"] @nticks.setter def nticks(self, val): self["nticks"] = val # outlinecolor # ------------ @property def outlinecolor(self): """ Sets the axis line color. The 'outlinecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["outlinecolor"] @outlinecolor.setter def outlinecolor(self, val): self["outlinecolor"] = val # outlinewidth # ------------ @property def outlinewidth(self): """ Sets the width (in px) of the axis line. The 'outlinewidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["outlinewidth"] @outlinewidth.setter def outlinewidth(self, val): self["outlinewidth"] = val # separatethousands # ----------------- @property def separatethousands(self): """ If "true", even 4-digit integers are separated The 'separatethousands' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["separatethousands"] @separatethousands.setter def separatethousands(self, val): self["separatethousands"] = val # showexponent # ------------ @property def showexponent(self): """ If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. The 'showexponent' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showexponent"] @showexponent.setter def showexponent(self, val): self["showexponent"] = val # showticklabels # -------------- @property def showticklabels(self): """ Determines whether or not the tick labels are drawn. The 'showticklabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showticklabels"] @showticklabels.setter def showticklabels(self, val): self["showticklabels"] = val # showtickprefix # -------------- @property def showtickprefix(self): """ If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. The 'showtickprefix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showtickprefix"] @showtickprefix.setter def showtickprefix(self, val): self["showtickprefix"] = val # showticksuffix # -------------- @property def showticksuffix(self): """ Same as `showtickprefix` but for tick suffixes. The 'showticksuffix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showticksuffix"] @showticksuffix.setter def showticksuffix(self, val): self["showticksuffix"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # thicknessmode # ------------- @property def thicknessmode(self): """ Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. The 'thicknessmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["thicknessmode"] @thicknessmode.setter def thicknessmode(self, val): self["thicknessmode"] = val # tick0 # ----- @property def tick0(self): """ Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. The 'tick0' property accepts values of any type Returns ------- Any """ return self["tick0"] @tick0.setter def tick0(self, val): self["tick0"] = val # tickangle # --------- @property def tickangle(self): """ Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. The 'tickangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["tickangle"] @tickangle.setter def tickangle(self, val): self["tickangle"] = val # tickcolor # --------- @property def tickcolor(self): """ Sets the tick color. The 'tickcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["tickcolor"] @tickcolor.setter def tickcolor(self, val): self["tickcolor"] = val # tickfont # -------- @property def tickfont(self): """ Sets the color bar's tick label font The 'tickfont' property is an instance of Tickfont that may be specified as: - An instance of plotly.graph_objs.contourcarpet.colorbar.Tickfont - A dict of string/value properties that will be passed to the Tickfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.contourcarpet.colorbar.Tickfont """ return self["tickfont"] @tickfont.setter def tickfont(self, val): self["tickfont"] = val # tickformat # ---------- @property def tickformat(self): """ Sets the tick label formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'tickformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickformat"] @tickformat.setter def tickformat(self, val): self["tickformat"] = val # tickformatstops # --------------- @property def tickformatstops(self): """ The 'tickformatstops' property is a tuple of instances of Tickformatstop that may be specified as: - A list or tuple of instances of plotly.graph_objs.contourcarpet.colorbar.Tickformatstop - A list or tuple of dicts of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- tuple[plotly.graph_objs.contourcarpet.colorbar.Tickformatstop] """ return self["tickformatstops"] @tickformatstops.setter def tickformatstops(self, val): self["tickformatstops"] = val # tickformatstopdefaults # ---------------------- @property def tickformatstopdefaults(self): """ When used in a template (as layout.template.data.contourcarpet. colorbar.tickformatstopdefaults), sets the default property values to use for elements of contourcarpet.colorbar.tickformatstops The 'tickformatstopdefaults' property is an instance of Tickformatstop that may be specified as: - An instance of plotly.graph_objs.contourcarpet.colorbar.Tickformatstop - A dict of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: Returns ------- plotly.graph_objs.contourcarpet.colorbar.Tickformatstop """ return self["tickformatstopdefaults"] @tickformatstopdefaults.setter def tickformatstopdefaults(self, val): self["tickformatstopdefaults"] = val # ticklen # ------- @property def ticklen(self): """ Sets the tick length (in px). The 'ticklen' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ticklen"] @ticklen.setter def ticklen(self, val): self["ticklen"] = val # tickmode # -------- @property def tickmode(self): """ Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). The 'tickmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'linear', 'array'] Returns ------- Any """ return self["tickmode"] @tickmode.setter def tickmode(self, val): self["tickmode"] = val # tickprefix # ---------- @property def tickprefix(self): """ Sets a tick label prefix. The 'tickprefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickprefix"] @tickprefix.setter def tickprefix(self, val): self["tickprefix"] = val # ticks # ----- @property def ticks(self): """ Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. The 'ticks' property is an enumeration that may be specified as: - One of the following enumeration values: ['outside', 'inside', ''] Returns ------- Any """ return self["ticks"] @ticks.setter def ticks(self, val): self["ticks"] = val # ticksuffix # ---------- @property def ticksuffix(self): """ Sets a tick label suffix. The 'ticksuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ticksuffix"] @ticksuffix.setter def ticksuffix(self, val): self["ticksuffix"] = val # ticktext # -------- @property def ticktext(self): """ Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. The 'ticktext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ticktext"] @ticktext.setter def ticktext(self, val): self["ticktext"] = val # ticktextsrc # ----------- @property def ticktextsrc(self): """ Sets the source reference on plot.ly for ticktext . The 'ticktextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ticktextsrc"] @ticktextsrc.setter def ticktextsrc(self, val): self["ticktextsrc"] = val # tickvals # -------- @property def tickvals(self): """ Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. The 'tickvals' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["tickvals"] @tickvals.setter def tickvals(self, val): self["tickvals"] = val # tickvalssrc # ----------- @property def tickvalssrc(self): """ Sets the source reference on plot.ly for tickvals . The 'tickvalssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tickvalssrc"] @tickvalssrc.setter def tickvalssrc(self, val): self["tickvalssrc"] = val # tickwidth # --------- @property def tickwidth(self): """ Sets the tick width (in px). The 'tickwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["tickwidth"] @tickwidth.setter def tickwidth(self, val): self["tickwidth"] = val # title # ----- @property def title(self): """ The 'title' property is an instance of Title that may be specified as: - An instance of plotly.graph_objs.contourcarpet.colorbar.Title - A dict of string/value properties that will be passed to the Title constructor Supported dict properties: font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- plotly.graph_objs.contourcarpet.colorbar.Title """ return self["title"] @title.setter def title(self, val): self["title"] = val # titlefont # --------- @property def titlefont(self): """ Deprecated: Please use contourcarpet.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.contourcarpet.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- """ return self["titlefont"] @titlefont.setter def titlefont(self, val): self["titlefont"] = val # titleside # --------- @property def titleside(self): """ Deprecated: Please use contourcarpet.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- """ return self["titleside"] @titleside.setter def titleside(self, val): self["titleside"] = val # x # - @property def x(self): """ Sets the x position of the color bar (in plot fraction). The 'x' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["x"] @x.setter def x(self, val): self["x"] = val # xanchor # ------- @property def xanchor(self): """ Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. The 'xanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'center', 'right'] Returns ------- Any """ return self["xanchor"] @xanchor.setter def xanchor(self, val): self["xanchor"] = val # xpad # ---- @property def xpad(self): """ Sets the amount of padding (in px) along the x direction. The 'xpad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["xpad"] @xpad.setter def xpad(self, val): self["xpad"] = val # y # - @property def y(self): """ Sets the y position of the color bar (in plot fraction). The 'y' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["y"] @y.setter def y(self, val): self["y"] = val # yanchor # ------- @property def yanchor(self): """ Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. The 'yanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['top', 'middle', 'bottom'] Returns ------- Any """ return self["yanchor"] @yanchor.setter def yanchor(self, val): self["yanchor"] = val # ypad # ---- @property def ypad(self): """ Sets the amount of padding (in px) along the y direction. The 'ypad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ypad"] @ypad.setter def ypad(self, val): self["ypad"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "contourcarpet" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.contourcarpet.colorbar. Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.contou rcarpet.colorbar.tickformatstopdefaults), sets the default property values to use for elements of contourcarpet.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.contourcarpet.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use contourcarpet.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use contourcarpet.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """ _mapped_properties = { "titlefont": ("title", "font"), "titleside": ("title", "side"), } def __init__( self, arg=None, bgcolor=None, bordercolor=None, borderwidth=None, dtick=None, exponentformat=None, len=None, lenmode=None, nticks=None, outlinecolor=None, outlinewidth=None, separatethousands=None, showexponent=None, showticklabels=None, showtickprefix=None, showticksuffix=None, thickness=None, thicknessmode=None, tick0=None, tickangle=None, tickcolor=None, tickfont=None, tickformat=None, tickformatstops=None, tickformatstopdefaults=None, ticklen=None, tickmode=None, tickprefix=None, ticks=None, ticksuffix=None, ticktext=None, ticktextsrc=None, tickvals=None, tickvalssrc=None, tickwidth=None, title=None, titlefont=None, titleside=None, x=None, xanchor=None, xpad=None, y=None, yanchor=None, ypad=None, **kwargs ): """ Construct a new ColorBar object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.contourcarpet.ColorBar bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.contourcarpet.colorbar. Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.contou rcarpet.colorbar.tickformatstopdefaults), sets the default property values to use for elements of contourcarpet.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.contourcarpet.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use contourcarpet.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use contourcarpet.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- ColorBar """ super(ColorBar, self).__init__("colorbar") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.contourcarpet.ColorBar constructor must be a dict or an instance of plotly.graph_objs.contourcarpet.ColorBar""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.contourcarpet import colorbar as v_colorbar # Initialize validators # --------------------- self._validators["bgcolor"] = v_colorbar.BgcolorValidator() self._validators["bordercolor"] = v_colorbar.BordercolorValidator() self._validators["borderwidth"] = v_colorbar.BorderwidthValidator() self._validators["dtick"] = v_colorbar.DtickValidator() self._validators["exponentformat"] = v_colorbar.ExponentformatValidator() self._validators["len"] = v_colorbar.LenValidator() self._validators["lenmode"] = v_colorbar.LenmodeValidator() self._validators["nticks"] = v_colorbar.NticksValidator() self._validators["outlinecolor"] = v_colorbar.OutlinecolorValidator() self._validators["outlinewidth"] = v_colorbar.OutlinewidthValidator() self._validators["separatethousands"] = v_colorbar.SeparatethousandsValidator() self._validators["showexponent"] = v_colorbar.ShowexponentValidator() self._validators["showticklabels"] = v_colorbar.ShowticklabelsValidator() self._validators["showtickprefix"] = v_colorbar.ShowtickprefixValidator() self._validators["showticksuffix"] = v_colorbar.ShowticksuffixValidator() self._validators["thickness"] = v_colorbar.ThicknessValidator() self._validators["thicknessmode"] = v_colorbar.ThicknessmodeValidator() self._validators["tick0"] = v_colorbar.Tick0Validator() self._validators["tickangle"] = v_colorbar.TickangleValidator() self._validators["tickcolor"] = v_colorbar.TickcolorValidator() self._validators["tickfont"] = v_colorbar.TickfontValidator() self._validators["tickformat"] = v_colorbar.TickformatValidator() self._validators["tickformatstops"] = v_colorbar.TickformatstopsValidator() self._validators[ "tickformatstopdefaults" ] = v_colorbar.TickformatstopValidator() self._validators["ticklen"] = v_colorbar.TicklenValidator() self._validators["tickmode"] = v_colorbar.TickmodeValidator() self._validators["tickprefix"] = v_colorbar.TickprefixValidator() self._validators["ticks"] = v_colorbar.TicksValidator() self._validators["ticksuffix"] = v_colorbar.TicksuffixValidator() self._validators["ticktext"] = v_colorbar.TicktextValidator() self._validators["ticktextsrc"] = v_colorbar.TicktextsrcValidator() self._validators["tickvals"] = v_colorbar.TickvalsValidator() self._validators["tickvalssrc"] = v_colorbar.TickvalssrcValidator() self._validators["tickwidth"] = v_colorbar.TickwidthValidator() self._validators["title"] = v_colorbar.TitleValidator() self._validators["x"] = v_colorbar.XValidator() self._validators["xanchor"] = v_colorbar.XanchorValidator() self._validators["xpad"] = v_colorbar.XpadValidator() self._validators["y"] = v_colorbar.YValidator() self._validators["yanchor"] = v_colorbar.YanchorValidator() self._validators["ypad"] = v_colorbar.YpadValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("borderwidth", None) self["borderwidth"] = borderwidth if borderwidth is not None else _v _v = arg.pop("dtick", None) self["dtick"] = dtick if dtick is not None else _v _v = arg.pop("exponentformat", None) self["exponentformat"] = exponentformat if exponentformat is not None else _v _v = arg.pop("len", None) self["len"] = len if len is not None else _v _v = arg.pop("lenmode", None) self["lenmode"] = lenmode if lenmode is not None else _v _v = arg.pop("nticks", None) self["nticks"] = nticks if nticks is not None else _v _v = arg.pop("outlinecolor", None) self["outlinecolor"] = outlinecolor if outlinecolor is not None else _v _v = arg.pop("outlinewidth", None) self["outlinewidth"] = outlinewidth if outlinewidth is not None else _v _v = arg.pop("separatethousands", None) self["separatethousands"] = ( separatethousands if separatethousands is not None else _v ) _v = arg.pop("showexponent", None) self["showexponent"] = showexponent if showexponent is not None else _v _v = arg.pop("showticklabels", None) self["showticklabels"] = showticklabels if showticklabels is not None else _v _v = arg.pop("showtickprefix", None) self["showtickprefix"] = showtickprefix if showtickprefix is not None else _v _v = arg.pop("showticksuffix", None) self["showticksuffix"] = showticksuffix if showticksuffix is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("thicknessmode", None) self["thicknessmode"] = thicknessmode if thicknessmode is not None else _v _v = arg.pop("tick0", None) self["tick0"] = tick0 if tick0 is not None else _v _v = arg.pop("tickangle", None) self["tickangle"] = tickangle if tickangle is not None else _v _v = arg.pop("tickcolor", None) self["tickcolor"] = tickcolor if tickcolor is not None else _v _v = arg.pop("tickfont", None) self["tickfont"] = tickfont if tickfont is not None else _v _v = arg.pop("tickformat", None) self["tickformat"] = tickformat if tickformat is not None else _v _v = arg.pop("tickformatstops", None) self["tickformatstops"] = tickformatstops if tickformatstops is not None else _v _v = arg.pop("tickformatstopdefaults", None) self["tickformatstopdefaults"] = ( tickformatstopdefaults if tickformatstopdefaults is not None else _v ) _v = arg.pop("ticklen", None) self["ticklen"] = ticklen if ticklen is not None else _v _v = arg.pop("tickmode", None) self["tickmode"] = tickmode if tickmode is not None else _v _v = arg.pop("tickprefix", None) self["tickprefix"] = tickprefix if tickprefix is not None else _v _v = arg.pop("ticks", None) self["ticks"] = ticks if ticks is not None else _v _v = arg.pop("ticksuffix", None) self["ticksuffix"] = ticksuffix if ticksuffix is not None else _v _v = arg.pop("ticktext", None) self["ticktext"] = ticktext if ticktext is not None else _v _v = arg.pop("ticktextsrc", None) self["ticktextsrc"] = ticktextsrc if ticktextsrc is not None else _v _v = arg.pop("tickvals", None) self["tickvals"] = tickvals if tickvals is not None else _v _v = arg.pop("tickvalssrc", None) self["tickvalssrc"] = tickvalssrc if tickvalssrc is not None else _v _v = arg.pop("tickwidth", None) self["tickwidth"] = tickwidth if tickwidth is not None else _v _v = arg.pop("title", None) self["title"] = title if title is not None else _v _v = arg.pop("titlefont", None) _v = titlefont if titlefont is not None else _v if _v is not None: self["titlefont"] = _v _v = arg.pop("titleside", None) _v = titleside if titleside is not None else _v if _v is not None: self["titleside"] = _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xanchor", None) self["xanchor"] = xanchor if xanchor is not None else _v _v = arg.pop("xpad", None) self["xpad"] = xpad if xpad is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("yanchor", None) self["yanchor"] = yanchor if yanchor is not None else _v _v = arg.pop("ypad", None) self["ypad"] = ypad if ypad is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["ColorBar", "Contours", "Line", "Stream", "colorbar", "contours"] from plotly.graph_objs.contourcarpet import contours from plotly.graph_objs.contourcarpet import colorbar plotly-4.4.1+dfsg.orig/plotly/graph_objs/scatterternary/0000755000175000017500000000000013573746613023003 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scatterternary/unselected/0000755000175000017500000000000013573746613025136 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scatterternary/unselected/__init__.py0000644000175000017500000002774013573721552027254 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Textfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the text font color of unselected points, applied only when a selection exists. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterternary.unselected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the text font color of unselected points, applied only when a selection exists. """ def __init__(self, arg=None, color=None, **kwargs): """ Construct a new Textfont object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterternary.unselected.Textfont color Sets the text font color of unselected points, applied only when a selection exists. Returns ------- Textfont """ super(Textfont, self).__init__("textfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterternary.unselected.Textfont constructor must be a dict or an instance of plotly.graph_objs.scatterternary.unselected.Textfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterternary.unselected import textfont as v_textfont # Initialize validators # --------------------- self._validators["color"] = v_textfont.ColorValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the marker color of unselected points, applied only when a selection exists. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # opacity # ------- @property def opacity(self): """ Sets the marker opacity of unselected points, applied only when a selection exists. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # size # ---- @property def size(self): """ Sets the marker size of unselected points, applied only when a selection exists. The 'size' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterternary.unselected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. size Sets the marker size of unselected points, applied only when a selection exists. """ def __init__(self, arg=None, color=None, opacity=None, size=None, **kwargs): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterternary.unselected.Marker color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. size Sets the marker size of unselected points, applied only when a selection exists. Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterternary.unselected.Marker constructor must be a dict or an instance of plotly.graph_objs.scatterternary.unselected.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterternary.unselected import marker as v_marker # Initialize validators # --------------------- self._validators["color"] = v_marker.ColorValidator() self._validators["opacity"] = v_marker.OpacityValidator() self._validators["size"] = v_marker.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Marker", "Textfont"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/scatterternary/hoverlabel/0000755000175000017500000000000013573746613025126 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scatterternary/hoverlabel/__init__.py0000644000175000017500000002550313573721552027237 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterternary.hoverlabel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Font object Sets the font used in hover labels. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterternary.hoverlabel.Font color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterternary.hoverlabel.Font constructor must be a dict or an instance of plotly.graph_objs.scatterternary.hoverlabel.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterternary.hoverlabel import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["colorsrc"] = v_font.ColorsrcValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["familysrc"] = v_font.FamilysrcValidator() self._validators["size"] = v_font.SizeValidator() self._validators["sizesrc"] = v_font.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/scatterternary/marker/0000755000175000017500000000000013573746613024264 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scatterternary/marker/colorbar/0000755000175000017500000000000013573746613026067 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scatterternary/marker/colorbar/title/0000755000175000017500000000000013573746613027210 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scatterternary/marker/colorbar/title/__init__.py0000644000175000017500000002066513573721552031325 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterternary.marker.colorbar.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterternary.marker. colorbar.title.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterternary.marker.colorbar.title.Font constructor must be a dict or an instance of plotly.graph_objs.scatterternary.marker.colorbar.title.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterternary.marker.colorbar.title import ( font as v_font, ) # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/scatterternary/marker/colorbar/__init__.py0000644000175000017500000006120513573721552030177 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Title(_BaseTraceHierarchyType): # font # ---- @property def font(self): """ Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.scatterternary.marker.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.scatterternary.marker.colorbar.title.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # side # ---- @property def side(self): """ Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- Any """ return self["side"] @side.setter def side(self, val): self["side"] = val # text # ---- @property def text(self): """ Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterternary.marker.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """ def __init__(self, arg=None, font=None, side=None, text=None, **kwargs): """ Construct a new Title object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterternary.marker.colorbar.Title font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- Title """ super(Title, self).__init__("title") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterternary.marker.colorbar.Title constructor must be a dict or an instance of plotly.graph_objs.scatterternary.marker.colorbar.Title""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterternary.marker.colorbar import title as v_title # Initialize validators # --------------------- self._validators["font"] = v_title.FontValidator() self._validators["side"] = v_title.SideValidator() self._validators["text"] = v_title.TextValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("side", None) self["side"] = side if side is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickformatstop(_BaseTraceHierarchyType): # dtickrange # ---------- @property def dtickrange(self): """ range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" The 'dtickrange' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'dtickrange[0]' property accepts values of any type (1) The 'dtickrange[1]' property accepts values of any type Returns ------- list """ return self["dtickrange"] @dtickrange.setter def dtickrange(self, val): self["dtickrange"] = val # enabled # ------- @property def enabled(self): """ Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. The 'enabled' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["enabled"] @enabled.setter def enabled(self, val): self["enabled"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # value # ----- @property def value(self): """ string - dtickformat for described zoom level, the same as "tickformat" The 'value' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterternary.marker.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """ def __init__( self, arg=None, dtickrange=None, enabled=None, name=None, templateitemname=None, value=None, **kwargs ): """ Construct a new Tickformatstop object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterternary.marker. colorbar.Tickformatstop dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- Tickformatstop """ super(Tickformatstop, self).__init__("tickformatstops") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterternary.marker.colorbar.Tickformatstop constructor must be a dict or an instance of plotly.graph_objs.scatterternary.marker.colorbar.Tickformatstop""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterternary.marker.colorbar import ( tickformatstop as v_tickformatstop, ) # Initialize validators # --------------------- self._validators["dtickrange"] = v_tickformatstop.DtickrangeValidator() self._validators["enabled"] = v_tickformatstop.EnabledValidator() self._validators["name"] = v_tickformatstop.NameValidator() self._validators[ "templateitemname" ] = v_tickformatstop.TemplateitemnameValidator() self._validators["value"] = v_tickformatstop.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtickrange", None) self["dtickrange"] = dtickrange if dtickrange is not None else _v _v = arg.pop("enabled", None) self["enabled"] = enabled if enabled is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterternary.marker.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Tickfont object Sets the color bar's tick label font Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterternary.marker. colorbar.Tickfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Tickfont """ super(Tickfont, self).__init__("tickfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterternary.marker.colorbar.Tickfont constructor must be a dict or an instance of plotly.graph_objs.scatterternary.marker.colorbar.Tickfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterternary.marker.colorbar import ( tickfont as v_tickfont, ) # Initialize validators # --------------------- self._validators["color"] = v_tickfont.ColorValidator() self._validators["family"] = v_tickfont.FamilyValidator() self._validators["size"] = v_tickfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Tickfont", "Tickformatstop", "Tickformatstop", "Title", "title"] from plotly.graph_objs.scatterternary.marker.colorbar import title plotly-4.4.1+dfsg.orig/plotly/graph_objs/scatterternary/marker/__init__.py0000644000175000017500000031040313573721553026372 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # autocolorscale # -------------- @property def autocolorscale(self): """ Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. The 'autocolorscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocolorscale"] @autocolorscale.setter def autocolorscale(self, val): self["autocolorscale"] = val # cauto # ----- @property def cauto(self): """ Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. The 'cauto' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["cauto"] @cauto.setter def cauto(self, val): self["cauto"] = val # cmax # ---- @property def cmax(self): """ Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. The 'cmax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmax"] @cmax.setter def cmax(self, val): self["cmax"] = val # cmid # ---- @property def cmid(self): """ Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. The 'cmid' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmid"] @cmid.setter def cmid(self, val): self["cmid"] = val # cmin # ---- @property def cmin(self): """ Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. The 'cmin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmin"] @cmin.setter def cmin(self, val): self["cmin"] = val # color # ----- @property def color(self): """ Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A number that will be interpreted as a color according to scatterternary.marker.line.colorscale - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # coloraxis # --------- @property def coloraxis(self): """ Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. The 'coloraxis' property is an identifier of a particular subplot, of type 'coloraxis', that may be specified as the string 'coloraxis' optionally followed by an integer >= 1 (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) Returns ------- str """ return self["coloraxis"] @coloraxis.setter def coloraxis(self, val): self["coloraxis"] = val # colorscale # ---------- @property def colorscale(self): """ Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,Earth,Electric,Vi ridis,Cividis. The 'colorscale' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # reversescale # ------------ @property def reversescale(self): """ Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. The 'reversescale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["reversescale"] @reversescale.setter def reversescale(self, val): self["reversescale"] = val # width # ----- @property def width(self): """ Sets the width (in px) of the lines bounding the marker points. The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["width"] @width.setter def width(self, val): self["width"] = val # widthsrc # -------- @property def widthsrc(self): """ Sets the source reference on plot.ly for width . The 'widthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["widthsrc"] @widthsrc.setter def widthsrc(self, val): self["widthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterternary.marker" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . """ def __init__( self, arg=None, autocolorscale=None, cauto=None, cmax=None, cmid=None, cmin=None, color=None, coloraxis=None, colorscale=None, colorsrc=None, reversescale=None, width=None, widthsrc=None, **kwargs ): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterternary.marker.Line autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterternary.marker.Line constructor must be a dict or an instance of plotly.graph_objs.scatterternary.marker.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterternary.marker import line as v_line # Initialize validators # --------------------- self._validators["autocolorscale"] = v_line.AutocolorscaleValidator() self._validators["cauto"] = v_line.CautoValidator() self._validators["cmax"] = v_line.CmaxValidator() self._validators["cmid"] = v_line.CmidValidator() self._validators["cmin"] = v_line.CminValidator() self._validators["color"] = v_line.ColorValidator() self._validators["coloraxis"] = v_line.ColoraxisValidator() self._validators["colorscale"] = v_line.ColorscaleValidator() self._validators["colorsrc"] = v_line.ColorsrcValidator() self._validators["reversescale"] = v_line.ReversescaleValidator() self._validators["width"] = v_line.WidthValidator() self._validators["widthsrc"] = v_line.WidthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autocolorscale", None) self["autocolorscale"] = autocolorscale if autocolorscale is not None else _v _v = arg.pop("cauto", None) self["cauto"] = cauto if cauto is not None else _v _v = arg.pop("cmax", None) self["cmax"] = cmax if cmax is not None else _v _v = arg.pop("cmid", None) self["cmid"] = cmid if cmid is not None else _v _v = arg.pop("cmin", None) self["cmin"] = cmin if cmin is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("coloraxis", None) self["coloraxis"] = coloraxis if coloraxis is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("reversescale", None) self["reversescale"] = reversescale if reversescale is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v _v = arg.pop("widthsrc", None) self["widthsrc"] = widthsrc if widthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Gradient(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the final color of the gradient fill: the center color for radial, the right for horizontal, or the bottom for vertical. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # type # ---- @property def type(self): """ Sets the type of gradient used to fill the markers The 'type' property is an enumeration that may be specified as: - One of the following enumeration values: ['radial', 'horizontal', 'vertical', 'none'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["type"] @type.setter def type(self, val): self["type"] = val # typesrc # ------- @property def typesrc(self): """ Sets the source reference on plot.ly for type . The 'typesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["typesrc"] @typesrc.setter def typesrc(self, val): self["typesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterternary.marker" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the final color of the gradient fill: the center color for radial, the right for horizontal, or the bottom for vertical. colorsrc Sets the source reference on plot.ly for color . type Sets the type of gradient used to fill the markers typesrc Sets the source reference on plot.ly for type . """ def __init__( self, arg=None, color=None, colorsrc=None, type=None, typesrc=None, **kwargs ): """ Construct a new Gradient object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterternary.marker.Gradient color Sets the final color of the gradient fill: the center color for radial, the right for horizontal, or the bottom for vertical. colorsrc Sets the source reference on plot.ly for color . type Sets the type of gradient used to fill the markers typesrc Sets the source reference on plot.ly for type . Returns ------- Gradient """ super(Gradient, self).__init__("gradient") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterternary.marker.Gradient constructor must be a dict or an instance of plotly.graph_objs.scatterternary.marker.Gradient""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterternary.marker import gradient as v_gradient # Initialize validators # --------------------- self._validators["color"] = v_gradient.ColorValidator() self._validators["colorsrc"] = v_gradient.ColorsrcValidator() self._validators["type"] = v_gradient.TypeValidator() self._validators["typesrc"] = v_gradient.TypesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("type", None) self["type"] = type if type is not None else _v _v = arg.pop("typesrc", None) self["typesrc"] = typesrc if typesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class ColorBar(_BaseTraceHierarchyType): # bgcolor # ------- @property def bgcolor(self): """ Sets the color of padded area. The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the axis line color. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # borderwidth # ----------- @property def borderwidth(self): """ Sets the width (in px) or the border enclosing this color bar. The 'borderwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["borderwidth"] @borderwidth.setter def borderwidth(self, val): self["borderwidth"] = val # dtick # ----- @property def dtick(self): """ Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" The 'dtick' property accepts values of any type Returns ------- Any """ return self["dtick"] @dtick.setter def dtick(self, val): self["dtick"] = val # exponentformat # -------------- @property def exponentformat(self): """ Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. The 'exponentformat' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'e', 'E', 'power', 'SI', 'B'] Returns ------- Any """ return self["exponentformat"] @exponentformat.setter def exponentformat(self, val): self["exponentformat"] = val # len # --- @property def len(self): """ Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. The 'len' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["len"] @len.setter def len(self, val): self["len"] = val # lenmode # ------- @property def lenmode(self): """ Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. The 'lenmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["lenmode"] @lenmode.setter def lenmode(self, val): self["lenmode"] = val # nticks # ------ @property def nticks(self): """ Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". The 'nticks' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nticks"] @nticks.setter def nticks(self, val): self["nticks"] = val # outlinecolor # ------------ @property def outlinecolor(self): """ Sets the axis line color. The 'outlinecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["outlinecolor"] @outlinecolor.setter def outlinecolor(self, val): self["outlinecolor"] = val # outlinewidth # ------------ @property def outlinewidth(self): """ Sets the width (in px) of the axis line. The 'outlinewidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["outlinewidth"] @outlinewidth.setter def outlinewidth(self, val): self["outlinewidth"] = val # separatethousands # ----------------- @property def separatethousands(self): """ If "true", even 4-digit integers are separated The 'separatethousands' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["separatethousands"] @separatethousands.setter def separatethousands(self, val): self["separatethousands"] = val # showexponent # ------------ @property def showexponent(self): """ If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. The 'showexponent' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showexponent"] @showexponent.setter def showexponent(self, val): self["showexponent"] = val # showticklabels # -------------- @property def showticklabels(self): """ Determines whether or not the tick labels are drawn. The 'showticklabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showticklabels"] @showticklabels.setter def showticklabels(self, val): self["showticklabels"] = val # showtickprefix # -------------- @property def showtickprefix(self): """ If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. The 'showtickprefix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showtickprefix"] @showtickprefix.setter def showtickprefix(self, val): self["showtickprefix"] = val # showticksuffix # -------------- @property def showticksuffix(self): """ Same as `showtickprefix` but for tick suffixes. The 'showticksuffix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showticksuffix"] @showticksuffix.setter def showticksuffix(self, val): self["showticksuffix"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # thicknessmode # ------------- @property def thicknessmode(self): """ Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. The 'thicknessmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["thicknessmode"] @thicknessmode.setter def thicknessmode(self, val): self["thicknessmode"] = val # tick0 # ----- @property def tick0(self): """ Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. The 'tick0' property accepts values of any type Returns ------- Any """ return self["tick0"] @tick0.setter def tick0(self, val): self["tick0"] = val # tickangle # --------- @property def tickangle(self): """ Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. The 'tickangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["tickangle"] @tickangle.setter def tickangle(self, val): self["tickangle"] = val # tickcolor # --------- @property def tickcolor(self): """ Sets the tick color. The 'tickcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["tickcolor"] @tickcolor.setter def tickcolor(self, val): self["tickcolor"] = val # tickfont # -------- @property def tickfont(self): """ Sets the color bar's tick label font The 'tickfont' property is an instance of Tickfont that may be specified as: - An instance of plotly.graph_objs.scatterternary.marker.colorbar.Tickfont - A dict of string/value properties that will be passed to the Tickfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.scatterternary.marker.colorbar.Tickfont """ return self["tickfont"] @tickfont.setter def tickfont(self, val): self["tickfont"] = val # tickformat # ---------- @property def tickformat(self): """ Sets the tick label formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'tickformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickformat"] @tickformat.setter def tickformat(self, val): self["tickformat"] = val # tickformatstops # --------------- @property def tickformatstops(self): """ The 'tickformatstops' property is a tuple of instances of Tickformatstop that may be specified as: - A list or tuple of instances of plotly.graph_objs.scatterternary.marker.colorbar.Tickformatstop - A list or tuple of dicts of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- tuple[plotly.graph_objs.scatterternary.marker.colorbar.Tickformatstop] """ return self["tickformatstops"] @tickformatstops.setter def tickformatstops(self, val): self["tickformatstops"] = val # tickformatstopdefaults # ---------------------- @property def tickformatstopdefaults(self): """ When used in a template (as layout.template.data.scatterternary .marker.colorbar.tickformatstopdefaults), sets the default property values to use for elements of scatterternary.marker.colorbar.tickformatstops The 'tickformatstopdefaults' property is an instance of Tickformatstop that may be specified as: - An instance of plotly.graph_objs.scatterternary.marker.colorbar.Tickformatstop - A dict of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: Returns ------- plotly.graph_objs.scatterternary.marker.colorbar.Tickformatstop """ return self["tickformatstopdefaults"] @tickformatstopdefaults.setter def tickformatstopdefaults(self, val): self["tickformatstopdefaults"] = val # ticklen # ------- @property def ticklen(self): """ Sets the tick length (in px). The 'ticklen' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ticklen"] @ticklen.setter def ticklen(self, val): self["ticklen"] = val # tickmode # -------- @property def tickmode(self): """ Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). The 'tickmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'linear', 'array'] Returns ------- Any """ return self["tickmode"] @tickmode.setter def tickmode(self, val): self["tickmode"] = val # tickprefix # ---------- @property def tickprefix(self): """ Sets a tick label prefix. The 'tickprefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickprefix"] @tickprefix.setter def tickprefix(self, val): self["tickprefix"] = val # ticks # ----- @property def ticks(self): """ Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. The 'ticks' property is an enumeration that may be specified as: - One of the following enumeration values: ['outside', 'inside', ''] Returns ------- Any """ return self["ticks"] @ticks.setter def ticks(self, val): self["ticks"] = val # ticksuffix # ---------- @property def ticksuffix(self): """ Sets a tick label suffix. The 'ticksuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ticksuffix"] @ticksuffix.setter def ticksuffix(self, val): self["ticksuffix"] = val # ticktext # -------- @property def ticktext(self): """ Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. The 'ticktext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ticktext"] @ticktext.setter def ticktext(self, val): self["ticktext"] = val # ticktextsrc # ----------- @property def ticktextsrc(self): """ Sets the source reference on plot.ly for ticktext . The 'ticktextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ticktextsrc"] @ticktextsrc.setter def ticktextsrc(self, val): self["ticktextsrc"] = val # tickvals # -------- @property def tickvals(self): """ Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. The 'tickvals' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["tickvals"] @tickvals.setter def tickvals(self, val): self["tickvals"] = val # tickvalssrc # ----------- @property def tickvalssrc(self): """ Sets the source reference on plot.ly for tickvals . The 'tickvalssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tickvalssrc"] @tickvalssrc.setter def tickvalssrc(self, val): self["tickvalssrc"] = val # tickwidth # --------- @property def tickwidth(self): """ Sets the tick width (in px). The 'tickwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["tickwidth"] @tickwidth.setter def tickwidth(self, val): self["tickwidth"] = val # title # ----- @property def title(self): """ The 'title' property is an instance of Title that may be specified as: - An instance of plotly.graph_objs.scatterternary.marker.colorbar.Title - A dict of string/value properties that will be passed to the Title constructor Supported dict properties: font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- plotly.graph_objs.scatterternary.marker.colorbar.Title """ return self["title"] @title.setter def title(self, val): self["title"] = val # titlefont # --------- @property def titlefont(self): """ Deprecated: Please use scatterternary.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.scatterternary.marker.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- """ return self["titlefont"] @titlefont.setter def titlefont(self, val): self["titlefont"] = val # titleside # --------- @property def titleside(self): """ Deprecated: Please use scatterternary.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- """ return self["titleside"] @titleside.setter def titleside(self, val): self["titleside"] = val # x # - @property def x(self): """ Sets the x position of the color bar (in plot fraction). The 'x' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["x"] @x.setter def x(self, val): self["x"] = val # xanchor # ------- @property def xanchor(self): """ Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. The 'xanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'center', 'right'] Returns ------- Any """ return self["xanchor"] @xanchor.setter def xanchor(self, val): self["xanchor"] = val # xpad # ---- @property def xpad(self): """ Sets the amount of padding (in px) along the x direction. The 'xpad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["xpad"] @xpad.setter def xpad(self, val): self["xpad"] = val # y # - @property def y(self): """ Sets the y position of the color bar (in plot fraction). The 'y' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["y"] @y.setter def y(self, val): self["y"] = val # yanchor # ------- @property def yanchor(self): """ Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. The 'yanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['top', 'middle', 'bottom'] Returns ------- Any """ return self["yanchor"] @yanchor.setter def yanchor(self, val): self["yanchor"] = val # ypad # ---- @property def ypad(self): """ Sets the amount of padding (in px) along the y direction. The 'ypad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ypad"] @ypad.setter def ypad(self, val): self["ypad"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterternary.marker" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.scatterternary.marker.c olorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.scatte rternary.marker.colorbar.tickformatstopdefaults), sets the default property values to use for elements of scatterternary.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.scatterternary.marker.colorbar.Tit le instance or dict with compatible properties titlefont Deprecated: Please use scatterternary.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use scatterternary.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """ _mapped_properties = { "titlefont": ("title", "font"), "titleside": ("title", "side"), } def __init__( self, arg=None, bgcolor=None, bordercolor=None, borderwidth=None, dtick=None, exponentformat=None, len=None, lenmode=None, nticks=None, outlinecolor=None, outlinewidth=None, separatethousands=None, showexponent=None, showticklabels=None, showtickprefix=None, showticksuffix=None, thickness=None, thicknessmode=None, tick0=None, tickangle=None, tickcolor=None, tickfont=None, tickformat=None, tickformatstops=None, tickformatstopdefaults=None, ticklen=None, tickmode=None, tickprefix=None, ticks=None, ticksuffix=None, ticktext=None, ticktextsrc=None, tickvals=None, tickvalssrc=None, tickwidth=None, title=None, titlefont=None, titleside=None, x=None, xanchor=None, xpad=None, y=None, yanchor=None, ypad=None, **kwargs ): """ Construct a new ColorBar object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterternary.marker.ColorBar bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.scatterternary.marker.c olorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.scatte rternary.marker.colorbar.tickformatstopdefaults), sets the default property values to use for elements of scatterternary.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.scatterternary.marker.colorbar.Tit le instance or dict with compatible properties titlefont Deprecated: Please use scatterternary.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use scatterternary.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- ColorBar """ super(ColorBar, self).__init__("colorbar") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterternary.marker.ColorBar constructor must be a dict or an instance of plotly.graph_objs.scatterternary.marker.ColorBar""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterternary.marker import colorbar as v_colorbar # Initialize validators # --------------------- self._validators["bgcolor"] = v_colorbar.BgcolorValidator() self._validators["bordercolor"] = v_colorbar.BordercolorValidator() self._validators["borderwidth"] = v_colorbar.BorderwidthValidator() self._validators["dtick"] = v_colorbar.DtickValidator() self._validators["exponentformat"] = v_colorbar.ExponentformatValidator() self._validators["len"] = v_colorbar.LenValidator() self._validators["lenmode"] = v_colorbar.LenmodeValidator() self._validators["nticks"] = v_colorbar.NticksValidator() self._validators["outlinecolor"] = v_colorbar.OutlinecolorValidator() self._validators["outlinewidth"] = v_colorbar.OutlinewidthValidator() self._validators["separatethousands"] = v_colorbar.SeparatethousandsValidator() self._validators["showexponent"] = v_colorbar.ShowexponentValidator() self._validators["showticklabels"] = v_colorbar.ShowticklabelsValidator() self._validators["showtickprefix"] = v_colorbar.ShowtickprefixValidator() self._validators["showticksuffix"] = v_colorbar.ShowticksuffixValidator() self._validators["thickness"] = v_colorbar.ThicknessValidator() self._validators["thicknessmode"] = v_colorbar.ThicknessmodeValidator() self._validators["tick0"] = v_colorbar.Tick0Validator() self._validators["tickangle"] = v_colorbar.TickangleValidator() self._validators["tickcolor"] = v_colorbar.TickcolorValidator() self._validators["tickfont"] = v_colorbar.TickfontValidator() self._validators["tickformat"] = v_colorbar.TickformatValidator() self._validators["tickformatstops"] = v_colorbar.TickformatstopsValidator() self._validators[ "tickformatstopdefaults" ] = v_colorbar.TickformatstopValidator() self._validators["ticklen"] = v_colorbar.TicklenValidator() self._validators["tickmode"] = v_colorbar.TickmodeValidator() self._validators["tickprefix"] = v_colorbar.TickprefixValidator() self._validators["ticks"] = v_colorbar.TicksValidator() self._validators["ticksuffix"] = v_colorbar.TicksuffixValidator() self._validators["ticktext"] = v_colorbar.TicktextValidator() self._validators["ticktextsrc"] = v_colorbar.TicktextsrcValidator() self._validators["tickvals"] = v_colorbar.TickvalsValidator() self._validators["tickvalssrc"] = v_colorbar.TickvalssrcValidator() self._validators["tickwidth"] = v_colorbar.TickwidthValidator() self._validators["title"] = v_colorbar.TitleValidator() self._validators["x"] = v_colorbar.XValidator() self._validators["xanchor"] = v_colorbar.XanchorValidator() self._validators["xpad"] = v_colorbar.XpadValidator() self._validators["y"] = v_colorbar.YValidator() self._validators["yanchor"] = v_colorbar.YanchorValidator() self._validators["ypad"] = v_colorbar.YpadValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("borderwidth", None) self["borderwidth"] = borderwidth if borderwidth is not None else _v _v = arg.pop("dtick", None) self["dtick"] = dtick if dtick is not None else _v _v = arg.pop("exponentformat", None) self["exponentformat"] = exponentformat if exponentformat is not None else _v _v = arg.pop("len", None) self["len"] = len if len is not None else _v _v = arg.pop("lenmode", None) self["lenmode"] = lenmode if lenmode is not None else _v _v = arg.pop("nticks", None) self["nticks"] = nticks if nticks is not None else _v _v = arg.pop("outlinecolor", None) self["outlinecolor"] = outlinecolor if outlinecolor is not None else _v _v = arg.pop("outlinewidth", None) self["outlinewidth"] = outlinewidth if outlinewidth is not None else _v _v = arg.pop("separatethousands", None) self["separatethousands"] = ( separatethousands if separatethousands is not None else _v ) _v = arg.pop("showexponent", None) self["showexponent"] = showexponent if showexponent is not None else _v _v = arg.pop("showticklabels", None) self["showticklabels"] = showticklabels if showticklabels is not None else _v _v = arg.pop("showtickprefix", None) self["showtickprefix"] = showtickprefix if showtickprefix is not None else _v _v = arg.pop("showticksuffix", None) self["showticksuffix"] = showticksuffix if showticksuffix is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("thicknessmode", None) self["thicknessmode"] = thicknessmode if thicknessmode is not None else _v _v = arg.pop("tick0", None) self["tick0"] = tick0 if tick0 is not None else _v _v = arg.pop("tickangle", None) self["tickangle"] = tickangle if tickangle is not None else _v _v = arg.pop("tickcolor", None) self["tickcolor"] = tickcolor if tickcolor is not None else _v _v = arg.pop("tickfont", None) self["tickfont"] = tickfont if tickfont is not None else _v _v = arg.pop("tickformat", None) self["tickformat"] = tickformat if tickformat is not None else _v _v = arg.pop("tickformatstops", None) self["tickformatstops"] = tickformatstops if tickformatstops is not None else _v _v = arg.pop("tickformatstopdefaults", None) self["tickformatstopdefaults"] = ( tickformatstopdefaults if tickformatstopdefaults is not None else _v ) _v = arg.pop("ticklen", None) self["ticklen"] = ticklen if ticklen is not None else _v _v = arg.pop("tickmode", None) self["tickmode"] = tickmode if tickmode is not None else _v _v = arg.pop("tickprefix", None) self["tickprefix"] = tickprefix if tickprefix is not None else _v _v = arg.pop("ticks", None) self["ticks"] = ticks if ticks is not None else _v _v = arg.pop("ticksuffix", None) self["ticksuffix"] = ticksuffix if ticksuffix is not None else _v _v = arg.pop("ticktext", None) self["ticktext"] = ticktext if ticktext is not None else _v _v = arg.pop("ticktextsrc", None) self["ticktextsrc"] = ticktextsrc if ticktextsrc is not None else _v _v = arg.pop("tickvals", None) self["tickvals"] = tickvals if tickvals is not None else _v _v = arg.pop("tickvalssrc", None) self["tickvalssrc"] = tickvalssrc if tickvalssrc is not None else _v _v = arg.pop("tickwidth", None) self["tickwidth"] = tickwidth if tickwidth is not None else _v _v = arg.pop("title", None) self["title"] = title if title is not None else _v _v = arg.pop("titlefont", None) _v = titlefont if titlefont is not None else _v if _v is not None: self["titlefont"] = _v _v = arg.pop("titleside", None) _v = titleside if titleside is not None else _v if _v is not None: self["titleside"] = _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xanchor", None) self["xanchor"] = xanchor if xanchor is not None else _v _v = arg.pop("xpad", None) self["xpad"] = xpad if xpad is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("yanchor", None) self["yanchor"] = yanchor if yanchor is not None else _v _v = arg.pop("ypad", None) self["ypad"] = ypad if ypad is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["ColorBar", "Gradient", "Line", "colorbar"] from plotly.graph_objs.scatterternary.marker import colorbar plotly-4.4.1+dfsg.orig/plotly/graph_objs/scatterternary/__init__.py0000644000175000017500000032550413573721553025121 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Unselected(_BaseTraceHierarchyType): # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.scatterternary.unselected.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. size Sets the marker size of unselected points, applied only when a selection exists. Returns ------- plotly.graph_objs.scatterternary.unselected.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # textfont # -------- @property def textfont(self): """ The 'textfont' property is an instance of Textfont that may be specified as: - An instance of plotly.graph_objs.scatterternary.unselected.Textfont - A dict of string/value properties that will be passed to the Textfont constructor Supported dict properties: color Sets the text font color of unselected points, applied only when a selection exists. Returns ------- plotly.graph_objs.scatterternary.unselected.Textfont """ return self["textfont"] @textfont.setter def textfont(self, val): self["textfont"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterternary" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ marker plotly.graph_objects.scatterternary.unselected.Marker instance or dict with compatible properties textfont plotly.graph_objects.scatterternary.unselected.Textfont instance or dict with compatible properties """ def __init__(self, arg=None, marker=None, textfont=None, **kwargs): """ Construct a new Unselected object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterternary.Unselected marker plotly.graph_objects.scatterternary.unselected.Marker instance or dict with compatible properties textfont plotly.graph_objects.scatterternary.unselected.Textfont instance or dict with compatible properties Returns ------- Unselected """ super(Unselected, self).__init__("unselected") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterternary.Unselected constructor must be a dict or an instance of plotly.graph_objs.scatterternary.Unselected""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterternary import unselected as v_unselected # Initialize validators # --------------------- self._validators["marker"] = v_unselected.MarkerValidator() self._validators["textfont"] = v_unselected.TextfontValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v _v = arg.pop("textfont", None) self["textfont"] = textfont if textfont is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Textfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterternary" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Textfont object Sets the text font. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterternary.Textfont color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Textfont """ super(Textfont, self).__init__("textfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterternary.Textfont constructor must be a dict or an instance of plotly.graph_objs.scatterternary.Textfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterternary import textfont as v_textfont # Initialize validators # --------------------- self._validators["color"] = v_textfont.ColorValidator() self._validators["colorsrc"] = v_textfont.ColorsrcValidator() self._validators["family"] = v_textfont.FamilyValidator() self._validators["familysrc"] = v_textfont.FamilysrcValidator() self._validators["size"] = v_textfont.SizeValidator() self._validators["sizesrc"] = v_textfont.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Stream(_BaseTraceHierarchyType): # maxpoints # --------- @property def maxpoints(self): """ Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. The 'maxpoints' property is a number and may be specified as: - An int or float in the interval [0, 10000] Returns ------- int|float """ return self["maxpoints"] @maxpoints.setter def maxpoints(self, val): self["maxpoints"] = val # token # ----- @property def token(self): """ The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. The 'token' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["token"] @token.setter def token(self, val): self["token"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterternary" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """ def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): """ Construct a new Stream object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterternary.Stream maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- Stream """ super(Stream, self).__init__("stream") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterternary.Stream constructor must be a dict or an instance of plotly.graph_objs.scatterternary.Stream""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterternary import stream as v_stream # Initialize validators # --------------------- self._validators["maxpoints"] = v_stream.MaxpointsValidator() self._validators["token"] = v_stream.TokenValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("maxpoints", None) self["maxpoints"] = maxpoints if maxpoints is not None else _v _v = arg.pop("token", None) self["token"] = token if token is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Selected(_BaseTraceHierarchyType): # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.scatterternary.selected.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. size Sets the marker size of selected points. Returns ------- plotly.graph_objs.scatterternary.selected.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # textfont # -------- @property def textfont(self): """ The 'textfont' property is an instance of Textfont that may be specified as: - An instance of plotly.graph_objs.scatterternary.selected.Textfont - A dict of string/value properties that will be passed to the Textfont constructor Supported dict properties: color Sets the text font color of selected points. Returns ------- plotly.graph_objs.scatterternary.selected.Textfont """ return self["textfont"] @textfont.setter def textfont(self, val): self["textfont"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterternary" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ marker plotly.graph_objects.scatterternary.selected.Marker instance or dict with compatible properties textfont plotly.graph_objects.scatterternary.selected.Textfont instance or dict with compatible properties """ def __init__(self, arg=None, marker=None, textfont=None, **kwargs): """ Construct a new Selected object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterternary.Selected marker plotly.graph_objects.scatterternary.selected.Marker instance or dict with compatible properties textfont plotly.graph_objects.scatterternary.selected.Textfont instance or dict with compatible properties Returns ------- Selected """ super(Selected, self).__init__("selected") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterternary.Selected constructor must be a dict or an instance of plotly.graph_objs.scatterternary.Selected""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterternary import selected as v_selected # Initialize validators # --------------------- self._validators["marker"] = v_selected.MarkerValidator() self._validators["textfont"] = v_selected.TextfontValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v _v = arg.pop("textfont", None) self["textfont"] = textfont if textfont is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # autocolorscale # -------------- @property def autocolorscale(self): """ Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. The 'autocolorscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocolorscale"] @autocolorscale.setter def autocolorscale(self, val): self["autocolorscale"] = val # cauto # ----- @property def cauto(self): """ Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. The 'cauto' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["cauto"] @cauto.setter def cauto(self, val): self["cauto"] = val # cmax # ---- @property def cmax(self): """ Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. The 'cmax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmax"] @cmax.setter def cmax(self, val): self["cmax"] = val # cmid # ---- @property def cmid(self): """ Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. The 'cmid' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmid"] @cmid.setter def cmid(self, val): self["cmid"] = val # cmin # ---- @property def cmin(self): """ Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. The 'cmin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmin"] @cmin.setter def cmin(self, val): self["cmin"] = val # color # ----- @property def color(self): """ Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A number that will be interpreted as a color according to scatterternary.marker.colorscale - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # coloraxis # --------- @property def coloraxis(self): """ Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. The 'coloraxis' property is an identifier of a particular subplot, of type 'coloraxis', that may be specified as the string 'coloraxis' optionally followed by an integer >= 1 (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) Returns ------- str """ return self["coloraxis"] @coloraxis.setter def coloraxis(self, val): self["coloraxis"] = val # colorbar # -------- @property def colorbar(self): """ The 'colorbar' property is an instance of ColorBar that may be specified as: - An instance of plotly.graph_objs.scatterternary.marker.ColorBar - A dict of string/value properties that will be passed to the ColorBar constructor Supported dict properties: bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.scatterternary. marker.colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.scatterternary.marker.colorbar.tickformatstop defaults), sets the default property values to use for elements of scatterternary.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.scatterternary.marker.colo rbar.Title instance or dict with compatible properties titlefont Deprecated: Please use scatterternary.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use scatterternary.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- plotly.graph_objs.scatterternary.marker.ColorBar """ return self["colorbar"] @colorbar.setter def colorbar(self, val): self["colorbar"] = val # colorscale # ---------- @property def colorscale(self): """ Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnB u,Greens,YlOrRd,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland ,Jet,Hot,Blackbody,Earth,Electric,Viridis,Cividis. The 'colorscale' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # gradient # -------- @property def gradient(self): """ The 'gradient' property is an instance of Gradient that may be specified as: - An instance of plotly.graph_objs.scatterternary.marker.Gradient - A dict of string/value properties that will be passed to the Gradient constructor Supported dict properties: color Sets the final color of the gradient fill: the center color for radial, the right for horizontal, or the bottom for vertical. colorsrc Sets the source reference on plot.ly for color . type Sets the type of gradient used to fill the markers typesrc Sets the source reference on plot.ly for type . Returns ------- plotly.graph_objs.scatterternary.marker.Gradient """ return self["gradient"] @gradient.setter def gradient(self, val): self["gradient"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.scatterternary.marker.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,R eds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Black body,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . Returns ------- plotly.graph_objs.scatterternary.marker.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # maxdisplayed # ------------ @property def maxdisplayed(self): """ Sets a maximum number of points to be drawn on the graph. 0 corresponds to no limit. The 'maxdisplayed' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["maxdisplayed"] @maxdisplayed.setter def maxdisplayed(self, val): self["maxdisplayed"] = val # opacity # ------- @property def opacity(self): """ Sets the marker opacity. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # opacitysrc # ---------- @property def opacitysrc(self): """ Sets the source reference on plot.ly for opacity . The 'opacitysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["opacitysrc"] @opacitysrc.setter def opacitysrc(self, val): self["opacitysrc"] = val # reversescale # ------------ @property def reversescale(self): """ Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. The 'reversescale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["reversescale"] @reversescale.setter def reversescale(self, val): self["reversescale"] = val # showscale # --------- @property def showscale(self): """ Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. The 'showscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showscale"] @showscale.setter def showscale(self, val): self["showscale"] = val # size # ---- @property def size(self): """ Sets the marker size (in px). The 'size' property is a number and may be specified as: - An int or float in the interval [0, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizemin # ------- @property def sizemin(self): """ Has an effect only if `marker.size` is set to a numerical array. Sets the minimum size (in px) of the rendered marker points. The 'sizemin' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["sizemin"] @sizemin.setter def sizemin(self, val): self["sizemin"] = val # sizemode # -------- @property def sizemode(self): """ Has an effect only if `marker.size` is set to a numerical array. Sets the rule for which the data in `size` is converted to pixels. The 'sizemode' property is an enumeration that may be specified as: - One of the following enumeration values: ['diameter', 'area'] Returns ------- Any """ return self["sizemode"] @sizemode.setter def sizemode(self, val): self["sizemode"] = val # sizeref # ------- @property def sizeref(self): """ Has an effect only if `marker.size` is set to a numerical array. Sets the scale factor used to determine the rendered size of marker points. Use with `sizemin` and `sizemode`. The 'sizeref' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["sizeref"] @sizeref.setter def sizeref(self, val): self["sizeref"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # symbol # ------ @property def symbol(self): """ Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot-open" to a symbol name. The 'symbol' property is an enumeration that may be specified as: - One of the following enumeration values: [0, 'circle', 100, 'circle-open', 200, 'circle-dot', 300, 'circle-open-dot', 1, 'square', 101, 'square-open', 201, 'square-dot', 301, 'square-open-dot', 2, 'diamond', 102, 'diamond-open', 202, 'diamond-dot', 302, 'diamond-open-dot', 3, 'cross', 103, 'cross-open', 203, 'cross-dot', 303, 'cross-open-dot', 4, 'x', 104, 'x-open', 204, 'x-dot', 304, 'x-open-dot', 5, 'triangle-up', 105, 'triangle-up-open', 205, 'triangle-up-dot', 305, 'triangle-up-open-dot', 6, 'triangle-down', 106, 'triangle-down-open', 206, 'triangle-down-dot', 306, 'triangle-down-open-dot', 7, 'triangle-left', 107, 'triangle-left-open', 207, 'triangle-left-dot', 307, 'triangle-left-open-dot', 8, 'triangle-right', 108, 'triangle-right-open', 208, 'triangle-right-dot', 308, 'triangle-right-open-dot', 9, 'triangle-ne', 109, 'triangle-ne-open', 209, 'triangle-ne-dot', 309, 'triangle-ne-open-dot', 10, 'triangle-se', 110, 'triangle-se-open', 210, 'triangle-se-dot', 310, 'triangle-se-open-dot', 11, 'triangle-sw', 111, 'triangle-sw-open', 211, 'triangle-sw-dot', 311, 'triangle-sw-open-dot', 12, 'triangle-nw', 112, 'triangle-nw-open', 212, 'triangle-nw-dot', 312, 'triangle-nw-open-dot', 13, 'pentagon', 113, 'pentagon-open', 213, 'pentagon-dot', 313, 'pentagon-open-dot', 14, 'hexagon', 114, 'hexagon-open', 214, 'hexagon-dot', 314, 'hexagon-open-dot', 15, 'hexagon2', 115, 'hexagon2-open', 215, 'hexagon2-dot', 315, 'hexagon2-open-dot', 16, 'octagon', 116, 'octagon-open', 216, 'octagon-dot', 316, 'octagon-open-dot', 17, 'star', 117, 'star-open', 217, 'star-dot', 317, 'star-open-dot', 18, 'hexagram', 118, 'hexagram-open', 218, 'hexagram-dot', 318, 'hexagram-open-dot', 19, 'star-triangle-up', 119, 'star-triangle-up-open', 219, 'star-triangle-up-dot', 319, 'star-triangle-up-open-dot', 20, 'star-triangle-down', 120, 'star-triangle-down-open', 220, 'star-triangle-down-dot', 320, 'star-triangle-down-open-dot', 21, 'star-square', 121, 'star-square-open', 221, 'star-square-dot', 321, 'star-square-open-dot', 22, 'star-diamond', 122, 'star-diamond-open', 222, 'star-diamond-dot', 322, 'star-diamond-open-dot', 23, 'diamond-tall', 123, 'diamond-tall-open', 223, 'diamond-tall-dot', 323, 'diamond-tall-open-dot', 24, 'diamond-wide', 124, 'diamond-wide-open', 224, 'diamond-wide-dot', 324, 'diamond-wide-open-dot', 25, 'hourglass', 125, 'hourglass-open', 26, 'bowtie', 126, 'bowtie-open', 27, 'circle-cross', 127, 'circle-cross-open', 28, 'circle-x', 128, 'circle-x-open', 29, 'square-cross', 129, 'square-cross-open', 30, 'square-x', 130, 'square-x-open', 31, 'diamond-cross', 131, 'diamond-cross-open', 32, 'diamond-x', 132, 'diamond-x-open', 33, 'cross-thin', 133, 'cross-thin-open', 34, 'x-thin', 134, 'x-thin-open', 35, 'asterisk', 135, 'asterisk-open', 36, 'hash', 136, 'hash-open', 236, 'hash-dot', 336, 'hash-open-dot', 37, 'y-up', 137, 'y-up-open', 38, 'y-down', 138, 'y-down-open', 39, 'y-left', 139, 'y-left-open', 40, 'y-right', 140, 'y-right-open', 41, 'line-ew', 141, 'line-ew-open', 42, 'line-ns', 142, 'line-ns-open', 43, 'line-ne', 143, 'line-ne-open', 44, 'line-nw', 144, 'line-nw-open'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["symbol"] @symbol.setter def symbol(self, val): self["symbol"] = val # symbolsrc # --------- @property def symbolsrc(self): """ Sets the source reference on plot.ly for symbol . The 'symbolsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["symbolsrc"] @symbolsrc.setter def symbolsrc(self, val): self["symbolsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterternary" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.scatterternary.marker.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu ,Reds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . gradient plotly.graph_objects.scatterternary.marker.Gradient instance or dict with compatible properties line plotly.graph_objects.scatterternary.marker.Line instance or dict with compatible properties maxdisplayed Sets a maximum number of points to be drawn on the graph. 0 corresponds to no limit. opacity Sets the marker opacity. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. size Sets the marker size (in px). sizemin Has an effect only if `marker.size` is set to a numerical array. Sets the minimum size (in px) of the rendered marker points. sizemode Has an effect only if `marker.size` is set to a numerical array. Sets the rule for which the data in `size` is converted to pixels. sizeref Has an effect only if `marker.size` is set to a numerical array. Sets the scale factor used to determine the rendered size of marker points. Use with `sizemin` and `sizemode`. sizesrc Sets the source reference on plot.ly for size . symbol Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot- open" to a symbol name. symbolsrc Sets the source reference on plot.ly for symbol . """ def __init__( self, arg=None, autocolorscale=None, cauto=None, cmax=None, cmid=None, cmin=None, color=None, coloraxis=None, colorbar=None, colorscale=None, colorsrc=None, gradient=None, line=None, maxdisplayed=None, opacity=None, opacitysrc=None, reversescale=None, showscale=None, size=None, sizemin=None, sizemode=None, sizeref=None, sizesrc=None, symbol=None, symbolsrc=None, **kwargs ): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterternary.Marker autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.scatterternary.marker.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu ,Reds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . gradient plotly.graph_objects.scatterternary.marker.Gradient instance or dict with compatible properties line plotly.graph_objects.scatterternary.marker.Line instance or dict with compatible properties maxdisplayed Sets a maximum number of points to be drawn on the graph. 0 corresponds to no limit. opacity Sets the marker opacity. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. size Sets the marker size (in px). sizemin Has an effect only if `marker.size` is set to a numerical array. Sets the minimum size (in px) of the rendered marker points. sizemode Has an effect only if `marker.size` is set to a numerical array. Sets the rule for which the data in `size` is converted to pixels. sizeref Has an effect only if `marker.size` is set to a numerical array. Sets the scale factor used to determine the rendered size of marker points. Use with `sizemin` and `sizemode`. sizesrc Sets the source reference on plot.ly for size . symbol Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot- open" to a symbol name. symbolsrc Sets the source reference on plot.ly for symbol . Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterternary.Marker constructor must be a dict or an instance of plotly.graph_objs.scatterternary.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterternary import marker as v_marker # Initialize validators # --------------------- self._validators["autocolorscale"] = v_marker.AutocolorscaleValidator() self._validators["cauto"] = v_marker.CautoValidator() self._validators["cmax"] = v_marker.CmaxValidator() self._validators["cmid"] = v_marker.CmidValidator() self._validators["cmin"] = v_marker.CminValidator() self._validators["color"] = v_marker.ColorValidator() self._validators["coloraxis"] = v_marker.ColoraxisValidator() self._validators["colorbar"] = v_marker.ColorBarValidator() self._validators["colorscale"] = v_marker.ColorscaleValidator() self._validators["colorsrc"] = v_marker.ColorsrcValidator() self._validators["gradient"] = v_marker.GradientValidator() self._validators["line"] = v_marker.LineValidator() self._validators["maxdisplayed"] = v_marker.MaxdisplayedValidator() self._validators["opacity"] = v_marker.OpacityValidator() self._validators["opacitysrc"] = v_marker.OpacitysrcValidator() self._validators["reversescale"] = v_marker.ReversescaleValidator() self._validators["showscale"] = v_marker.ShowscaleValidator() self._validators["size"] = v_marker.SizeValidator() self._validators["sizemin"] = v_marker.SizeminValidator() self._validators["sizemode"] = v_marker.SizemodeValidator() self._validators["sizeref"] = v_marker.SizerefValidator() self._validators["sizesrc"] = v_marker.SizesrcValidator() self._validators["symbol"] = v_marker.SymbolValidator() self._validators["symbolsrc"] = v_marker.SymbolsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autocolorscale", None) self["autocolorscale"] = autocolorscale if autocolorscale is not None else _v _v = arg.pop("cauto", None) self["cauto"] = cauto if cauto is not None else _v _v = arg.pop("cmax", None) self["cmax"] = cmax if cmax is not None else _v _v = arg.pop("cmid", None) self["cmid"] = cmid if cmid is not None else _v _v = arg.pop("cmin", None) self["cmin"] = cmin if cmin is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("coloraxis", None) self["coloraxis"] = coloraxis if coloraxis is not None else _v _v = arg.pop("colorbar", None) self["colorbar"] = colorbar if colorbar is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("gradient", None) self["gradient"] = gradient if gradient is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v _v = arg.pop("maxdisplayed", None) self["maxdisplayed"] = maxdisplayed if maxdisplayed is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("opacitysrc", None) self["opacitysrc"] = opacitysrc if opacitysrc is not None else _v _v = arg.pop("reversescale", None) self["reversescale"] = reversescale if reversescale is not None else _v _v = arg.pop("showscale", None) self["showscale"] = showscale if showscale is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizemin", None) self["sizemin"] = sizemin if sizemin is not None else _v _v = arg.pop("sizemode", None) self["sizemode"] = sizemode if sizemode is not None else _v _v = arg.pop("sizeref", None) self["sizeref"] = sizeref if sizeref is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v _v = arg.pop("symbol", None) self["symbol"] = symbol if symbol is not None else _v _v = arg.pop("symbolsrc", None) self["symbolsrc"] = symbolsrc if symbolsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the line color. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # dash # ---- @property def dash(self): """ Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). The 'dash' property is an enumeration that may be specified as: - One of the following dash styles: ['solid', 'dot', 'dash', 'longdash', 'dashdot', 'longdashdot'] - A string containing a dash length list in pixels or percentages (e.g. '5px 10px 2px 2px', '5, 10, 2, 2', '10% 20% 40%', etc.) Returns ------- str """ return self["dash"] @dash.setter def dash(self, val): self["dash"] = val # shape # ----- @property def shape(self): """ Determines the line shape. With "spline" the lines are drawn using spline interpolation. The other available values correspond to step-wise line shapes. The 'shape' property is an enumeration that may be specified as: - One of the following enumeration values: ['linear', 'spline'] Returns ------- Any """ return self["shape"] @shape.setter def shape(self, val): self["shape"] = val # smoothing # --------- @property def smoothing(self): """ Has an effect only if `shape` is set to "spline" Sets the amount of smoothing. 0 corresponds to no smoothing (equivalent to a "linear" shape). The 'smoothing' property is a number and may be specified as: - An int or float in the interval [0, 1.3] Returns ------- int|float """ return self["smoothing"] @smoothing.setter def smoothing(self, val): self["smoothing"] = val # width # ----- @property def width(self): """ Sets the line width (in px). The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterternary" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the line color. dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). shape Determines the line shape. With "spline" the lines are drawn using spline interpolation. The other available values correspond to step-wise line shapes. smoothing Has an effect only if `shape` is set to "spline" Sets the amount of smoothing. 0 corresponds to no smoothing (equivalent to a "linear" shape). width Sets the line width (in px). """ def __init__( self, arg=None, color=None, dash=None, shape=None, smoothing=None, width=None, **kwargs ): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterternary.Line color Sets the line color. dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). shape Determines the line shape. With "spline" the lines are drawn using spline interpolation. The other available values correspond to step-wise line shapes. smoothing Has an effect only if `shape` is set to "spline" Sets the amount of smoothing. 0 corresponds to no smoothing (equivalent to a "linear" shape). width Sets the line width (in px). Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterternary.Line constructor must be a dict or an instance of plotly.graph_objs.scatterternary.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterternary import line as v_line # Initialize validators # --------------------- self._validators["color"] = v_line.ColorValidator() self._validators["dash"] = v_line.DashValidator() self._validators["shape"] = v_line.ShapeValidator() self._validators["smoothing"] = v_line.SmoothingValidator() self._validators["width"] = v_line.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("dash", None) self["dash"] = dash if dash is not None else _v _v = arg.pop("shape", None) self["shape"] = shape if shape is not None else _v _v = arg.pop("smoothing", None) self["smoothing"] = smoothing if smoothing is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Hoverlabel(_BaseTraceHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'right', 'auto'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["align"] @align.setter def align(self, val): self["align"] = val # alignsrc # -------- @property def alignsrc(self): """ Sets the source reference on plot.ly for align . The 'alignsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["alignsrc"] @alignsrc.setter def alignsrc(self, val): self["alignsrc"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the hover labels for this trace The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bgcolorsrc # ---------- @property def bgcolorsrc(self): """ Sets the source reference on plot.ly for bgcolor . The 'bgcolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bgcolorsrc"] @bgcolorsrc.setter def bgcolorsrc(self, val): self["bgcolorsrc"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the border color of the hover labels for this trace. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # bordercolorsrc # -------------- @property def bordercolorsrc(self): """ Sets the source reference on plot.ly for bordercolor . The 'bordercolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bordercolorsrc"] @bordercolorsrc.setter def bordercolorsrc(self, val): self["bordercolorsrc"] = val # font # ---- @property def font(self): """ Sets the font used in hover labels. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.scatterternary.hoverlabel.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.scatterternary.hoverlabel.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # namelength # ---------- @property def namelength(self): """ Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. The 'namelength' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [-1, 9223372036854775807] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|numpy.ndarray """ return self["namelength"] @namelength.setter def namelength(self, val): self["namelength"] = val # namelengthsrc # ------------- @property def namelengthsrc(self): """ Sets the source reference on plot.ly for namelength . The 'namelengthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["namelengthsrc"] @namelengthsrc.setter def namelengthsrc(self, val): self["namelengthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterternary" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """ def __init__( self, arg=None, align=None, alignsrc=None, bgcolor=None, bgcolorsrc=None, bordercolor=None, bordercolorsrc=None, font=None, namelength=None, namelengthsrc=None, **kwargs ): """ Construct a new Hoverlabel object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterternary.Hoverlabel align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- Hoverlabel """ super(Hoverlabel, self).__init__("hoverlabel") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterternary.Hoverlabel constructor must be a dict or an instance of plotly.graph_objs.scatterternary.Hoverlabel""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterternary import hoverlabel as v_hoverlabel # Initialize validators # --------------------- self._validators["align"] = v_hoverlabel.AlignValidator() self._validators["alignsrc"] = v_hoverlabel.AlignsrcValidator() self._validators["bgcolor"] = v_hoverlabel.BgcolorValidator() self._validators["bgcolorsrc"] = v_hoverlabel.BgcolorsrcValidator() self._validators["bordercolor"] = v_hoverlabel.BordercolorValidator() self._validators["bordercolorsrc"] = v_hoverlabel.BordercolorsrcValidator() self._validators["font"] = v_hoverlabel.FontValidator() self._validators["namelength"] = v_hoverlabel.NamelengthValidator() self._validators["namelengthsrc"] = v_hoverlabel.NamelengthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("alignsrc", None) self["alignsrc"] = alignsrc if alignsrc is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bgcolorsrc", None) self["bgcolorsrc"] = bgcolorsrc if bgcolorsrc is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("bordercolorsrc", None) self["bordercolorsrc"] = bordercolorsrc if bordercolorsrc is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("namelength", None) self["namelength"] = namelength if namelength is not None else _v _v = arg.pop("namelengthsrc", None) self["namelengthsrc"] = namelengthsrc if namelengthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = [ "Hoverlabel", "Line", "Marker", "Selected", "Stream", "Textfont", "Unselected", "hoverlabel", "marker", "selected", "unselected", ] from plotly.graph_objs.scatterternary import unselected from plotly.graph_objs.scatterternary import selected from plotly.graph_objs.scatterternary import marker from plotly.graph_objs.scatterternary import hoverlabel plotly-4.4.1+dfsg.orig/plotly/graph_objs/scatterternary/selected/0000755000175000017500000000000013573746613024573 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scatterternary/selected/__init__.py0000644000175000017500000002655413573721552026713 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Textfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the text font color of selected points. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterternary.selected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the text font color of selected points. """ def __init__(self, arg=None, color=None, **kwargs): """ Construct a new Textfont object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterternary.selected.Textfont color Sets the text font color of selected points. Returns ------- Textfont """ super(Textfont, self).__init__("textfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterternary.selected.Textfont constructor must be a dict or an instance of plotly.graph_objs.scatterternary.selected.Textfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterternary.selected import textfont as v_textfont # Initialize validators # --------------------- self._validators["color"] = v_textfont.ColorValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the marker color of selected points. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # opacity # ------- @property def opacity(self): """ Sets the marker opacity of selected points. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # size # ---- @property def size(self): """ Sets the marker size of selected points. The 'size' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterternary.selected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. size Sets the marker size of selected points. """ def __init__(self, arg=None, color=None, opacity=None, size=None, **kwargs): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterternary.selected.Marker color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. size Sets the marker size of selected points. Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterternary.selected.Marker constructor must be a dict or an instance of plotly.graph_objs.scatterternary.selected.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterternary.selected import marker as v_marker # Initialize validators # --------------------- self._validators["color"] = v_marker.ColorValidator() self._validators["opacity"] = v_marker.OpacityValidator() self._validators["size"] = v_marker.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Marker", "Textfont"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/scatterpolargl/0000755000175000017500000000000013573746613022757 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scatterpolargl/unselected/0000755000175000017500000000000013573746613025112 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scatterpolargl/unselected/__init__.py0000644000175000017500000002774013573721551027227 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Textfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the text font color of unselected points, applied only when a selection exists. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterpolargl.unselected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the text font color of unselected points, applied only when a selection exists. """ def __init__(self, arg=None, color=None, **kwargs): """ Construct a new Textfont object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterpolargl.unselected.Textfont color Sets the text font color of unselected points, applied only when a selection exists. Returns ------- Textfont """ super(Textfont, self).__init__("textfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterpolargl.unselected.Textfont constructor must be a dict or an instance of plotly.graph_objs.scatterpolargl.unselected.Textfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterpolargl.unselected import textfont as v_textfont # Initialize validators # --------------------- self._validators["color"] = v_textfont.ColorValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the marker color of unselected points, applied only when a selection exists. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # opacity # ------- @property def opacity(self): """ Sets the marker opacity of unselected points, applied only when a selection exists. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # size # ---- @property def size(self): """ Sets the marker size of unselected points, applied only when a selection exists. The 'size' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterpolargl.unselected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. size Sets the marker size of unselected points, applied only when a selection exists. """ def __init__(self, arg=None, color=None, opacity=None, size=None, **kwargs): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterpolargl.unselected.Marker color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. size Sets the marker size of unselected points, applied only when a selection exists. Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterpolargl.unselected.Marker constructor must be a dict or an instance of plotly.graph_objs.scatterpolargl.unselected.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterpolargl.unselected import marker as v_marker # Initialize validators # --------------------- self._validators["color"] = v_marker.ColorValidator() self._validators["opacity"] = v_marker.OpacityValidator() self._validators["size"] = v_marker.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Marker", "Textfont"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/scatterpolargl/hoverlabel/0000755000175000017500000000000013573746613025102 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scatterpolargl/hoverlabel/__init__.py0000644000175000017500000002550313573721551027212 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterpolargl.hoverlabel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Font object Sets the font used in hover labels. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterpolargl.hoverlabel.Font color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterpolargl.hoverlabel.Font constructor must be a dict or an instance of plotly.graph_objs.scatterpolargl.hoverlabel.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterpolargl.hoverlabel import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["colorsrc"] = v_font.ColorsrcValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["familysrc"] = v_font.FamilysrcValidator() self._validators["size"] = v_font.SizeValidator() self._validators["sizesrc"] = v_font.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/scatterpolargl/marker/0000755000175000017500000000000013573746613024240 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scatterpolargl/marker/colorbar/0000755000175000017500000000000013573746613026043 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scatterpolargl/marker/colorbar/title/0000755000175000017500000000000013573746613027164 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scatterpolargl/marker/colorbar/title/__init__.py0000644000175000017500000002066513573721551031300 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterpolargl.marker.colorbar.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterpolargl.marker. colorbar.title.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterpolargl.marker.colorbar.title.Font constructor must be a dict or an instance of plotly.graph_objs.scatterpolargl.marker.colorbar.title.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterpolargl.marker.colorbar.title import ( font as v_font, ) # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/scatterpolargl/marker/colorbar/__init__.py0000644000175000017500000006120513573721552030153 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Title(_BaseTraceHierarchyType): # font # ---- @property def font(self): """ Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.scatterpolargl.marker.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.scatterpolargl.marker.colorbar.title.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # side # ---- @property def side(self): """ Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- Any """ return self["side"] @side.setter def side(self, val): self["side"] = val # text # ---- @property def text(self): """ Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterpolargl.marker.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """ def __init__(self, arg=None, font=None, side=None, text=None, **kwargs): """ Construct a new Title object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterpolargl.marker.colorbar.Title font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- Title """ super(Title, self).__init__("title") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterpolargl.marker.colorbar.Title constructor must be a dict or an instance of plotly.graph_objs.scatterpolargl.marker.colorbar.Title""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterpolargl.marker.colorbar import title as v_title # Initialize validators # --------------------- self._validators["font"] = v_title.FontValidator() self._validators["side"] = v_title.SideValidator() self._validators["text"] = v_title.TextValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("side", None) self["side"] = side if side is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickformatstop(_BaseTraceHierarchyType): # dtickrange # ---------- @property def dtickrange(self): """ range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" The 'dtickrange' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'dtickrange[0]' property accepts values of any type (1) The 'dtickrange[1]' property accepts values of any type Returns ------- list """ return self["dtickrange"] @dtickrange.setter def dtickrange(self, val): self["dtickrange"] = val # enabled # ------- @property def enabled(self): """ Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. The 'enabled' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["enabled"] @enabled.setter def enabled(self, val): self["enabled"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # value # ----- @property def value(self): """ string - dtickformat for described zoom level, the same as "tickformat" The 'value' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterpolargl.marker.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """ def __init__( self, arg=None, dtickrange=None, enabled=None, name=None, templateitemname=None, value=None, **kwargs ): """ Construct a new Tickformatstop object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterpolargl.marker. colorbar.Tickformatstop dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- Tickformatstop """ super(Tickformatstop, self).__init__("tickformatstops") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterpolargl.marker.colorbar.Tickformatstop constructor must be a dict or an instance of plotly.graph_objs.scatterpolargl.marker.colorbar.Tickformatstop""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterpolargl.marker.colorbar import ( tickformatstop as v_tickformatstop, ) # Initialize validators # --------------------- self._validators["dtickrange"] = v_tickformatstop.DtickrangeValidator() self._validators["enabled"] = v_tickformatstop.EnabledValidator() self._validators["name"] = v_tickformatstop.NameValidator() self._validators[ "templateitemname" ] = v_tickformatstop.TemplateitemnameValidator() self._validators["value"] = v_tickformatstop.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtickrange", None) self["dtickrange"] = dtickrange if dtickrange is not None else _v _v = arg.pop("enabled", None) self["enabled"] = enabled if enabled is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterpolargl.marker.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Tickfont object Sets the color bar's tick label font Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterpolargl.marker. colorbar.Tickfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Tickfont """ super(Tickfont, self).__init__("tickfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterpolargl.marker.colorbar.Tickfont constructor must be a dict or an instance of plotly.graph_objs.scatterpolargl.marker.colorbar.Tickfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterpolargl.marker.colorbar import ( tickfont as v_tickfont, ) # Initialize validators # --------------------- self._validators["color"] = v_tickfont.ColorValidator() self._validators["family"] = v_tickfont.FamilyValidator() self._validators["size"] = v_tickfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Tickfont", "Tickformatstop", "Tickformatstop", "Title", "title"] from plotly.graph_objs.scatterpolargl.marker.colorbar import title plotly-4.4.1+dfsg.orig/plotly/graph_objs/scatterpolargl/marker/__init__.py0000644000175000017500000027110713573721553026355 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # autocolorscale # -------------- @property def autocolorscale(self): """ Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. The 'autocolorscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocolorscale"] @autocolorscale.setter def autocolorscale(self, val): self["autocolorscale"] = val # cauto # ----- @property def cauto(self): """ Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. The 'cauto' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["cauto"] @cauto.setter def cauto(self, val): self["cauto"] = val # cmax # ---- @property def cmax(self): """ Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. The 'cmax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmax"] @cmax.setter def cmax(self, val): self["cmax"] = val # cmid # ---- @property def cmid(self): """ Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. The 'cmid' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmid"] @cmid.setter def cmid(self, val): self["cmid"] = val # cmin # ---- @property def cmin(self): """ Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. The 'cmin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmin"] @cmin.setter def cmin(self, val): self["cmin"] = val # color # ----- @property def color(self): """ Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A number that will be interpreted as a color according to scatterpolargl.marker.line.colorscale - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # coloraxis # --------- @property def coloraxis(self): """ Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. The 'coloraxis' property is an identifier of a particular subplot, of type 'coloraxis', that may be specified as the string 'coloraxis' optionally followed by an integer >= 1 (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) Returns ------- str """ return self["coloraxis"] @coloraxis.setter def coloraxis(self, val): self["coloraxis"] = val # colorscale # ---------- @property def colorscale(self): """ Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,Earth,Electric,Vi ridis,Cividis. The 'colorscale' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # reversescale # ------------ @property def reversescale(self): """ Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. The 'reversescale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["reversescale"] @reversescale.setter def reversescale(self, val): self["reversescale"] = val # width # ----- @property def width(self): """ Sets the width (in px) of the lines bounding the marker points. The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["width"] @width.setter def width(self, val): self["width"] = val # widthsrc # -------- @property def widthsrc(self): """ Sets the source reference on plot.ly for width . The 'widthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["widthsrc"] @widthsrc.setter def widthsrc(self, val): self["widthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterpolargl.marker" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . """ def __init__( self, arg=None, autocolorscale=None, cauto=None, cmax=None, cmid=None, cmin=None, color=None, coloraxis=None, colorscale=None, colorsrc=None, reversescale=None, width=None, widthsrc=None, **kwargs ): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterpolargl.marker.Line autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterpolargl.marker.Line constructor must be a dict or an instance of plotly.graph_objs.scatterpolargl.marker.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterpolargl.marker import line as v_line # Initialize validators # --------------------- self._validators["autocolorscale"] = v_line.AutocolorscaleValidator() self._validators["cauto"] = v_line.CautoValidator() self._validators["cmax"] = v_line.CmaxValidator() self._validators["cmid"] = v_line.CmidValidator() self._validators["cmin"] = v_line.CminValidator() self._validators["color"] = v_line.ColorValidator() self._validators["coloraxis"] = v_line.ColoraxisValidator() self._validators["colorscale"] = v_line.ColorscaleValidator() self._validators["colorsrc"] = v_line.ColorsrcValidator() self._validators["reversescale"] = v_line.ReversescaleValidator() self._validators["width"] = v_line.WidthValidator() self._validators["widthsrc"] = v_line.WidthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autocolorscale", None) self["autocolorscale"] = autocolorscale if autocolorscale is not None else _v _v = arg.pop("cauto", None) self["cauto"] = cauto if cauto is not None else _v _v = arg.pop("cmax", None) self["cmax"] = cmax if cmax is not None else _v _v = arg.pop("cmid", None) self["cmid"] = cmid if cmid is not None else _v _v = arg.pop("cmin", None) self["cmin"] = cmin if cmin is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("coloraxis", None) self["coloraxis"] = coloraxis if coloraxis is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("reversescale", None) self["reversescale"] = reversescale if reversescale is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v _v = arg.pop("widthsrc", None) self["widthsrc"] = widthsrc if widthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class ColorBar(_BaseTraceHierarchyType): # bgcolor # ------- @property def bgcolor(self): """ Sets the color of padded area. The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the axis line color. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # borderwidth # ----------- @property def borderwidth(self): """ Sets the width (in px) or the border enclosing this color bar. The 'borderwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["borderwidth"] @borderwidth.setter def borderwidth(self, val): self["borderwidth"] = val # dtick # ----- @property def dtick(self): """ Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" The 'dtick' property accepts values of any type Returns ------- Any """ return self["dtick"] @dtick.setter def dtick(self, val): self["dtick"] = val # exponentformat # -------------- @property def exponentformat(self): """ Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. The 'exponentformat' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'e', 'E', 'power', 'SI', 'B'] Returns ------- Any """ return self["exponentformat"] @exponentformat.setter def exponentformat(self, val): self["exponentformat"] = val # len # --- @property def len(self): """ Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. The 'len' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["len"] @len.setter def len(self, val): self["len"] = val # lenmode # ------- @property def lenmode(self): """ Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. The 'lenmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["lenmode"] @lenmode.setter def lenmode(self, val): self["lenmode"] = val # nticks # ------ @property def nticks(self): """ Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". The 'nticks' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nticks"] @nticks.setter def nticks(self, val): self["nticks"] = val # outlinecolor # ------------ @property def outlinecolor(self): """ Sets the axis line color. The 'outlinecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["outlinecolor"] @outlinecolor.setter def outlinecolor(self, val): self["outlinecolor"] = val # outlinewidth # ------------ @property def outlinewidth(self): """ Sets the width (in px) of the axis line. The 'outlinewidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["outlinewidth"] @outlinewidth.setter def outlinewidth(self, val): self["outlinewidth"] = val # separatethousands # ----------------- @property def separatethousands(self): """ If "true", even 4-digit integers are separated The 'separatethousands' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["separatethousands"] @separatethousands.setter def separatethousands(self, val): self["separatethousands"] = val # showexponent # ------------ @property def showexponent(self): """ If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. The 'showexponent' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showexponent"] @showexponent.setter def showexponent(self, val): self["showexponent"] = val # showticklabels # -------------- @property def showticklabels(self): """ Determines whether or not the tick labels are drawn. The 'showticklabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showticklabels"] @showticklabels.setter def showticklabels(self, val): self["showticklabels"] = val # showtickprefix # -------------- @property def showtickprefix(self): """ If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. The 'showtickprefix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showtickprefix"] @showtickprefix.setter def showtickprefix(self, val): self["showtickprefix"] = val # showticksuffix # -------------- @property def showticksuffix(self): """ Same as `showtickprefix` but for tick suffixes. The 'showticksuffix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showticksuffix"] @showticksuffix.setter def showticksuffix(self, val): self["showticksuffix"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # thicknessmode # ------------- @property def thicknessmode(self): """ Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. The 'thicknessmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["thicknessmode"] @thicknessmode.setter def thicknessmode(self, val): self["thicknessmode"] = val # tick0 # ----- @property def tick0(self): """ Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. The 'tick0' property accepts values of any type Returns ------- Any """ return self["tick0"] @tick0.setter def tick0(self, val): self["tick0"] = val # tickangle # --------- @property def tickangle(self): """ Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. The 'tickangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["tickangle"] @tickangle.setter def tickangle(self, val): self["tickangle"] = val # tickcolor # --------- @property def tickcolor(self): """ Sets the tick color. The 'tickcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["tickcolor"] @tickcolor.setter def tickcolor(self, val): self["tickcolor"] = val # tickfont # -------- @property def tickfont(self): """ Sets the color bar's tick label font The 'tickfont' property is an instance of Tickfont that may be specified as: - An instance of plotly.graph_objs.scatterpolargl.marker.colorbar.Tickfont - A dict of string/value properties that will be passed to the Tickfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.scatterpolargl.marker.colorbar.Tickfont """ return self["tickfont"] @tickfont.setter def tickfont(self, val): self["tickfont"] = val # tickformat # ---------- @property def tickformat(self): """ Sets the tick label formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'tickformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickformat"] @tickformat.setter def tickformat(self, val): self["tickformat"] = val # tickformatstops # --------------- @property def tickformatstops(self): """ The 'tickformatstops' property is a tuple of instances of Tickformatstop that may be specified as: - A list or tuple of instances of plotly.graph_objs.scatterpolargl.marker.colorbar.Tickformatstop - A list or tuple of dicts of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- tuple[plotly.graph_objs.scatterpolargl.marker.colorbar.Tickformatstop] """ return self["tickformatstops"] @tickformatstops.setter def tickformatstops(self, val): self["tickformatstops"] = val # tickformatstopdefaults # ---------------------- @property def tickformatstopdefaults(self): """ When used in a template (as layout.template.data.scatterpolargl .marker.colorbar.tickformatstopdefaults), sets the default property values to use for elements of scatterpolargl.marker.colorbar.tickformatstops The 'tickformatstopdefaults' property is an instance of Tickformatstop that may be specified as: - An instance of plotly.graph_objs.scatterpolargl.marker.colorbar.Tickformatstop - A dict of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: Returns ------- plotly.graph_objs.scatterpolargl.marker.colorbar.Tickformatstop """ return self["tickformatstopdefaults"] @tickformatstopdefaults.setter def tickformatstopdefaults(self, val): self["tickformatstopdefaults"] = val # ticklen # ------- @property def ticklen(self): """ Sets the tick length (in px). The 'ticklen' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ticklen"] @ticklen.setter def ticklen(self, val): self["ticklen"] = val # tickmode # -------- @property def tickmode(self): """ Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). The 'tickmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'linear', 'array'] Returns ------- Any """ return self["tickmode"] @tickmode.setter def tickmode(self, val): self["tickmode"] = val # tickprefix # ---------- @property def tickprefix(self): """ Sets a tick label prefix. The 'tickprefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickprefix"] @tickprefix.setter def tickprefix(self, val): self["tickprefix"] = val # ticks # ----- @property def ticks(self): """ Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. The 'ticks' property is an enumeration that may be specified as: - One of the following enumeration values: ['outside', 'inside', ''] Returns ------- Any """ return self["ticks"] @ticks.setter def ticks(self, val): self["ticks"] = val # ticksuffix # ---------- @property def ticksuffix(self): """ Sets a tick label suffix. The 'ticksuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ticksuffix"] @ticksuffix.setter def ticksuffix(self, val): self["ticksuffix"] = val # ticktext # -------- @property def ticktext(self): """ Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. The 'ticktext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ticktext"] @ticktext.setter def ticktext(self, val): self["ticktext"] = val # ticktextsrc # ----------- @property def ticktextsrc(self): """ Sets the source reference on plot.ly for ticktext . The 'ticktextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ticktextsrc"] @ticktextsrc.setter def ticktextsrc(self, val): self["ticktextsrc"] = val # tickvals # -------- @property def tickvals(self): """ Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. The 'tickvals' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["tickvals"] @tickvals.setter def tickvals(self, val): self["tickvals"] = val # tickvalssrc # ----------- @property def tickvalssrc(self): """ Sets the source reference on plot.ly for tickvals . The 'tickvalssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tickvalssrc"] @tickvalssrc.setter def tickvalssrc(self, val): self["tickvalssrc"] = val # tickwidth # --------- @property def tickwidth(self): """ Sets the tick width (in px). The 'tickwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["tickwidth"] @tickwidth.setter def tickwidth(self, val): self["tickwidth"] = val # title # ----- @property def title(self): """ The 'title' property is an instance of Title that may be specified as: - An instance of plotly.graph_objs.scatterpolargl.marker.colorbar.Title - A dict of string/value properties that will be passed to the Title constructor Supported dict properties: font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- plotly.graph_objs.scatterpolargl.marker.colorbar.Title """ return self["title"] @title.setter def title(self, val): self["title"] = val # titlefont # --------- @property def titlefont(self): """ Deprecated: Please use scatterpolargl.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.scatterpolargl.marker.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- """ return self["titlefont"] @titlefont.setter def titlefont(self, val): self["titlefont"] = val # titleside # --------- @property def titleside(self): """ Deprecated: Please use scatterpolargl.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- """ return self["titleside"] @titleside.setter def titleside(self, val): self["titleside"] = val # x # - @property def x(self): """ Sets the x position of the color bar (in plot fraction). The 'x' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["x"] @x.setter def x(self, val): self["x"] = val # xanchor # ------- @property def xanchor(self): """ Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. The 'xanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'center', 'right'] Returns ------- Any """ return self["xanchor"] @xanchor.setter def xanchor(self, val): self["xanchor"] = val # xpad # ---- @property def xpad(self): """ Sets the amount of padding (in px) along the x direction. The 'xpad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["xpad"] @xpad.setter def xpad(self, val): self["xpad"] = val # y # - @property def y(self): """ Sets the y position of the color bar (in plot fraction). The 'y' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["y"] @y.setter def y(self, val): self["y"] = val # yanchor # ------- @property def yanchor(self): """ Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. The 'yanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['top', 'middle', 'bottom'] Returns ------- Any """ return self["yanchor"] @yanchor.setter def yanchor(self, val): self["yanchor"] = val # ypad # ---- @property def ypad(self): """ Sets the amount of padding (in px) along the y direction. The 'ypad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ypad"] @ypad.setter def ypad(self, val): self["ypad"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterpolargl.marker" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.scatterpolargl.marker.c olorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.scatte rpolargl.marker.colorbar.tickformatstopdefaults), sets the default property values to use for elements of scatterpolargl.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.scatterpolargl.marker.colorbar.Tit le instance or dict with compatible properties titlefont Deprecated: Please use scatterpolargl.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use scatterpolargl.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """ _mapped_properties = { "titlefont": ("title", "font"), "titleside": ("title", "side"), } def __init__( self, arg=None, bgcolor=None, bordercolor=None, borderwidth=None, dtick=None, exponentformat=None, len=None, lenmode=None, nticks=None, outlinecolor=None, outlinewidth=None, separatethousands=None, showexponent=None, showticklabels=None, showtickprefix=None, showticksuffix=None, thickness=None, thicknessmode=None, tick0=None, tickangle=None, tickcolor=None, tickfont=None, tickformat=None, tickformatstops=None, tickformatstopdefaults=None, ticklen=None, tickmode=None, tickprefix=None, ticks=None, ticksuffix=None, ticktext=None, ticktextsrc=None, tickvals=None, tickvalssrc=None, tickwidth=None, title=None, titlefont=None, titleside=None, x=None, xanchor=None, xpad=None, y=None, yanchor=None, ypad=None, **kwargs ): """ Construct a new ColorBar object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterpolargl.marker.ColorBar bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.scatterpolargl.marker.c olorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.scatte rpolargl.marker.colorbar.tickformatstopdefaults), sets the default property values to use for elements of scatterpolargl.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.scatterpolargl.marker.colorbar.Tit le instance or dict with compatible properties titlefont Deprecated: Please use scatterpolargl.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use scatterpolargl.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- ColorBar """ super(ColorBar, self).__init__("colorbar") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterpolargl.marker.ColorBar constructor must be a dict or an instance of plotly.graph_objs.scatterpolargl.marker.ColorBar""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterpolargl.marker import colorbar as v_colorbar # Initialize validators # --------------------- self._validators["bgcolor"] = v_colorbar.BgcolorValidator() self._validators["bordercolor"] = v_colorbar.BordercolorValidator() self._validators["borderwidth"] = v_colorbar.BorderwidthValidator() self._validators["dtick"] = v_colorbar.DtickValidator() self._validators["exponentformat"] = v_colorbar.ExponentformatValidator() self._validators["len"] = v_colorbar.LenValidator() self._validators["lenmode"] = v_colorbar.LenmodeValidator() self._validators["nticks"] = v_colorbar.NticksValidator() self._validators["outlinecolor"] = v_colorbar.OutlinecolorValidator() self._validators["outlinewidth"] = v_colorbar.OutlinewidthValidator() self._validators["separatethousands"] = v_colorbar.SeparatethousandsValidator() self._validators["showexponent"] = v_colorbar.ShowexponentValidator() self._validators["showticklabels"] = v_colorbar.ShowticklabelsValidator() self._validators["showtickprefix"] = v_colorbar.ShowtickprefixValidator() self._validators["showticksuffix"] = v_colorbar.ShowticksuffixValidator() self._validators["thickness"] = v_colorbar.ThicknessValidator() self._validators["thicknessmode"] = v_colorbar.ThicknessmodeValidator() self._validators["tick0"] = v_colorbar.Tick0Validator() self._validators["tickangle"] = v_colorbar.TickangleValidator() self._validators["tickcolor"] = v_colorbar.TickcolorValidator() self._validators["tickfont"] = v_colorbar.TickfontValidator() self._validators["tickformat"] = v_colorbar.TickformatValidator() self._validators["tickformatstops"] = v_colorbar.TickformatstopsValidator() self._validators[ "tickformatstopdefaults" ] = v_colorbar.TickformatstopValidator() self._validators["ticklen"] = v_colorbar.TicklenValidator() self._validators["tickmode"] = v_colorbar.TickmodeValidator() self._validators["tickprefix"] = v_colorbar.TickprefixValidator() self._validators["ticks"] = v_colorbar.TicksValidator() self._validators["ticksuffix"] = v_colorbar.TicksuffixValidator() self._validators["ticktext"] = v_colorbar.TicktextValidator() self._validators["ticktextsrc"] = v_colorbar.TicktextsrcValidator() self._validators["tickvals"] = v_colorbar.TickvalsValidator() self._validators["tickvalssrc"] = v_colorbar.TickvalssrcValidator() self._validators["tickwidth"] = v_colorbar.TickwidthValidator() self._validators["title"] = v_colorbar.TitleValidator() self._validators["x"] = v_colorbar.XValidator() self._validators["xanchor"] = v_colorbar.XanchorValidator() self._validators["xpad"] = v_colorbar.XpadValidator() self._validators["y"] = v_colorbar.YValidator() self._validators["yanchor"] = v_colorbar.YanchorValidator() self._validators["ypad"] = v_colorbar.YpadValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("borderwidth", None) self["borderwidth"] = borderwidth if borderwidth is not None else _v _v = arg.pop("dtick", None) self["dtick"] = dtick if dtick is not None else _v _v = arg.pop("exponentformat", None) self["exponentformat"] = exponentformat if exponentformat is not None else _v _v = arg.pop("len", None) self["len"] = len if len is not None else _v _v = arg.pop("lenmode", None) self["lenmode"] = lenmode if lenmode is not None else _v _v = arg.pop("nticks", None) self["nticks"] = nticks if nticks is not None else _v _v = arg.pop("outlinecolor", None) self["outlinecolor"] = outlinecolor if outlinecolor is not None else _v _v = arg.pop("outlinewidth", None) self["outlinewidth"] = outlinewidth if outlinewidth is not None else _v _v = arg.pop("separatethousands", None) self["separatethousands"] = ( separatethousands if separatethousands is not None else _v ) _v = arg.pop("showexponent", None) self["showexponent"] = showexponent if showexponent is not None else _v _v = arg.pop("showticklabels", None) self["showticklabels"] = showticklabels if showticklabels is not None else _v _v = arg.pop("showtickprefix", None) self["showtickprefix"] = showtickprefix if showtickprefix is not None else _v _v = arg.pop("showticksuffix", None) self["showticksuffix"] = showticksuffix if showticksuffix is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("thicknessmode", None) self["thicknessmode"] = thicknessmode if thicknessmode is not None else _v _v = arg.pop("tick0", None) self["tick0"] = tick0 if tick0 is not None else _v _v = arg.pop("tickangle", None) self["tickangle"] = tickangle if tickangle is not None else _v _v = arg.pop("tickcolor", None) self["tickcolor"] = tickcolor if tickcolor is not None else _v _v = arg.pop("tickfont", None) self["tickfont"] = tickfont if tickfont is not None else _v _v = arg.pop("tickformat", None) self["tickformat"] = tickformat if tickformat is not None else _v _v = arg.pop("tickformatstops", None) self["tickformatstops"] = tickformatstops if tickformatstops is not None else _v _v = arg.pop("tickformatstopdefaults", None) self["tickformatstopdefaults"] = ( tickformatstopdefaults if tickformatstopdefaults is not None else _v ) _v = arg.pop("ticklen", None) self["ticklen"] = ticklen if ticklen is not None else _v _v = arg.pop("tickmode", None) self["tickmode"] = tickmode if tickmode is not None else _v _v = arg.pop("tickprefix", None) self["tickprefix"] = tickprefix if tickprefix is not None else _v _v = arg.pop("ticks", None) self["ticks"] = ticks if ticks is not None else _v _v = arg.pop("ticksuffix", None) self["ticksuffix"] = ticksuffix if ticksuffix is not None else _v _v = arg.pop("ticktext", None) self["ticktext"] = ticktext if ticktext is not None else _v _v = arg.pop("ticktextsrc", None) self["ticktextsrc"] = ticktextsrc if ticktextsrc is not None else _v _v = arg.pop("tickvals", None) self["tickvals"] = tickvals if tickvals is not None else _v _v = arg.pop("tickvalssrc", None) self["tickvalssrc"] = tickvalssrc if tickvalssrc is not None else _v _v = arg.pop("tickwidth", None) self["tickwidth"] = tickwidth if tickwidth is not None else _v _v = arg.pop("title", None) self["title"] = title if title is not None else _v _v = arg.pop("titlefont", None) _v = titlefont if titlefont is not None else _v if _v is not None: self["titlefont"] = _v _v = arg.pop("titleside", None) _v = titleside if titleside is not None else _v if _v is not None: self["titleside"] = _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xanchor", None) self["xanchor"] = xanchor if xanchor is not None else _v _v = arg.pop("xpad", None) self["xpad"] = xpad if xpad is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("yanchor", None) self["yanchor"] = yanchor if yanchor is not None else _v _v = arg.pop("ypad", None) self["ypad"] = ypad if ypad is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["ColorBar", "Line", "colorbar"] from plotly.graph_objs.scatterpolargl.marker import colorbar plotly-4.4.1+dfsg.orig/plotly/graph_objs/scatterpolargl/__init__.py0000644000175000017500000031423313573721552025071 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Unselected(_BaseTraceHierarchyType): # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.scatterpolargl.unselected.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. size Sets the marker size of unselected points, applied only when a selection exists. Returns ------- plotly.graph_objs.scatterpolargl.unselected.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # textfont # -------- @property def textfont(self): """ The 'textfont' property is an instance of Textfont that may be specified as: - An instance of plotly.graph_objs.scatterpolargl.unselected.Textfont - A dict of string/value properties that will be passed to the Textfont constructor Supported dict properties: color Sets the text font color of unselected points, applied only when a selection exists. Returns ------- plotly.graph_objs.scatterpolargl.unselected.Textfont """ return self["textfont"] @textfont.setter def textfont(self, val): self["textfont"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterpolargl" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ marker plotly.graph_objects.scatterpolargl.unselected.Marker instance or dict with compatible properties textfont plotly.graph_objects.scatterpolargl.unselected.Textfont instance or dict with compatible properties """ def __init__(self, arg=None, marker=None, textfont=None, **kwargs): """ Construct a new Unselected object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterpolargl.Unselected marker plotly.graph_objects.scatterpolargl.unselected.Marker instance or dict with compatible properties textfont plotly.graph_objects.scatterpolargl.unselected.Textfont instance or dict with compatible properties Returns ------- Unselected """ super(Unselected, self).__init__("unselected") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterpolargl.Unselected constructor must be a dict or an instance of plotly.graph_objs.scatterpolargl.Unselected""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterpolargl import unselected as v_unselected # Initialize validators # --------------------- self._validators["marker"] = v_unselected.MarkerValidator() self._validators["textfont"] = v_unselected.TextfontValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v _v = arg.pop("textfont", None) self["textfont"] = textfont if textfont is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Textfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterpolargl" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Textfont object Sets the text font. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterpolargl.Textfont color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Textfont """ super(Textfont, self).__init__("textfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterpolargl.Textfont constructor must be a dict or an instance of plotly.graph_objs.scatterpolargl.Textfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterpolargl import textfont as v_textfont # Initialize validators # --------------------- self._validators["color"] = v_textfont.ColorValidator() self._validators["colorsrc"] = v_textfont.ColorsrcValidator() self._validators["family"] = v_textfont.FamilyValidator() self._validators["familysrc"] = v_textfont.FamilysrcValidator() self._validators["size"] = v_textfont.SizeValidator() self._validators["sizesrc"] = v_textfont.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Stream(_BaseTraceHierarchyType): # maxpoints # --------- @property def maxpoints(self): """ Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. The 'maxpoints' property is a number and may be specified as: - An int or float in the interval [0, 10000] Returns ------- int|float """ return self["maxpoints"] @maxpoints.setter def maxpoints(self, val): self["maxpoints"] = val # token # ----- @property def token(self): """ The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. The 'token' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["token"] @token.setter def token(self, val): self["token"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterpolargl" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """ def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): """ Construct a new Stream object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterpolargl.Stream maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- Stream """ super(Stream, self).__init__("stream") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterpolargl.Stream constructor must be a dict or an instance of plotly.graph_objs.scatterpolargl.Stream""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterpolargl import stream as v_stream # Initialize validators # --------------------- self._validators["maxpoints"] = v_stream.MaxpointsValidator() self._validators["token"] = v_stream.TokenValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("maxpoints", None) self["maxpoints"] = maxpoints if maxpoints is not None else _v _v = arg.pop("token", None) self["token"] = token if token is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Selected(_BaseTraceHierarchyType): # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.scatterpolargl.selected.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. size Sets the marker size of selected points. Returns ------- plotly.graph_objs.scatterpolargl.selected.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # textfont # -------- @property def textfont(self): """ The 'textfont' property is an instance of Textfont that may be specified as: - An instance of plotly.graph_objs.scatterpolargl.selected.Textfont - A dict of string/value properties that will be passed to the Textfont constructor Supported dict properties: color Sets the text font color of selected points. Returns ------- plotly.graph_objs.scatterpolargl.selected.Textfont """ return self["textfont"] @textfont.setter def textfont(self, val): self["textfont"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterpolargl" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ marker plotly.graph_objects.scatterpolargl.selected.Marker instance or dict with compatible properties textfont plotly.graph_objects.scatterpolargl.selected.Textfont instance or dict with compatible properties """ def __init__(self, arg=None, marker=None, textfont=None, **kwargs): """ Construct a new Selected object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterpolargl.Selected marker plotly.graph_objects.scatterpolargl.selected.Marker instance or dict with compatible properties textfont plotly.graph_objects.scatterpolargl.selected.Textfont instance or dict with compatible properties Returns ------- Selected """ super(Selected, self).__init__("selected") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterpolargl.Selected constructor must be a dict or an instance of plotly.graph_objs.scatterpolargl.Selected""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterpolargl import selected as v_selected # Initialize validators # --------------------- self._validators["marker"] = v_selected.MarkerValidator() self._validators["textfont"] = v_selected.TextfontValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v _v = arg.pop("textfont", None) self["textfont"] = textfont if textfont is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # autocolorscale # -------------- @property def autocolorscale(self): """ Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. The 'autocolorscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocolorscale"] @autocolorscale.setter def autocolorscale(self, val): self["autocolorscale"] = val # cauto # ----- @property def cauto(self): """ Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. The 'cauto' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["cauto"] @cauto.setter def cauto(self, val): self["cauto"] = val # cmax # ---- @property def cmax(self): """ Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. The 'cmax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmax"] @cmax.setter def cmax(self, val): self["cmax"] = val # cmid # ---- @property def cmid(self): """ Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. The 'cmid' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmid"] @cmid.setter def cmid(self, val): self["cmid"] = val # cmin # ---- @property def cmin(self): """ Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. The 'cmin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmin"] @cmin.setter def cmin(self, val): self["cmin"] = val # color # ----- @property def color(self): """ Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A number that will be interpreted as a color according to scatterpolargl.marker.colorscale - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # coloraxis # --------- @property def coloraxis(self): """ Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. The 'coloraxis' property is an identifier of a particular subplot, of type 'coloraxis', that may be specified as the string 'coloraxis' optionally followed by an integer >= 1 (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) Returns ------- str """ return self["coloraxis"] @coloraxis.setter def coloraxis(self, val): self["coloraxis"] = val # colorbar # -------- @property def colorbar(self): """ The 'colorbar' property is an instance of ColorBar that may be specified as: - An instance of plotly.graph_objs.scatterpolargl.marker.ColorBar - A dict of string/value properties that will be passed to the ColorBar constructor Supported dict properties: bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.scatterpolargl. marker.colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.scatterpolargl.marker.colorbar.tickformatstop defaults), sets the default property values to use for elements of scatterpolargl.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.scatterpolargl.marker.colo rbar.Title instance or dict with compatible properties titlefont Deprecated: Please use scatterpolargl.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use scatterpolargl.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- plotly.graph_objs.scatterpolargl.marker.ColorBar """ return self["colorbar"] @colorbar.setter def colorbar(self, val): self["colorbar"] = val # colorscale # ---------- @property def colorscale(self): """ Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnB u,Greens,YlOrRd,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland ,Jet,Hot,Blackbody,Earth,Electric,Viridis,Cividis. The 'colorscale' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.scatterpolargl.marker.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,R eds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Black body,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . Returns ------- plotly.graph_objs.scatterpolargl.marker.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # opacity # ------- @property def opacity(self): """ Sets the marker opacity. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # opacitysrc # ---------- @property def opacitysrc(self): """ Sets the source reference on plot.ly for opacity . The 'opacitysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["opacitysrc"] @opacitysrc.setter def opacitysrc(self, val): self["opacitysrc"] = val # reversescale # ------------ @property def reversescale(self): """ Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. The 'reversescale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["reversescale"] @reversescale.setter def reversescale(self, val): self["reversescale"] = val # showscale # --------- @property def showscale(self): """ Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. The 'showscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showscale"] @showscale.setter def showscale(self, val): self["showscale"] = val # size # ---- @property def size(self): """ Sets the marker size (in px). The 'size' property is a number and may be specified as: - An int or float in the interval [0, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizemin # ------- @property def sizemin(self): """ Has an effect only if `marker.size` is set to a numerical array. Sets the minimum size (in px) of the rendered marker points. The 'sizemin' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["sizemin"] @sizemin.setter def sizemin(self, val): self["sizemin"] = val # sizemode # -------- @property def sizemode(self): """ Has an effect only if `marker.size` is set to a numerical array. Sets the rule for which the data in `size` is converted to pixels. The 'sizemode' property is an enumeration that may be specified as: - One of the following enumeration values: ['diameter', 'area'] Returns ------- Any """ return self["sizemode"] @sizemode.setter def sizemode(self, val): self["sizemode"] = val # sizeref # ------- @property def sizeref(self): """ Has an effect only if `marker.size` is set to a numerical array. Sets the scale factor used to determine the rendered size of marker points. Use with `sizemin` and `sizemode`. The 'sizeref' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["sizeref"] @sizeref.setter def sizeref(self, val): self["sizeref"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # symbol # ------ @property def symbol(self): """ Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot-open" to a symbol name. The 'symbol' property is an enumeration that may be specified as: - One of the following enumeration values: [0, 'circle', 100, 'circle-open', 200, 'circle-dot', 300, 'circle-open-dot', 1, 'square', 101, 'square-open', 201, 'square-dot', 301, 'square-open-dot', 2, 'diamond', 102, 'diamond-open', 202, 'diamond-dot', 302, 'diamond-open-dot', 3, 'cross', 103, 'cross-open', 203, 'cross-dot', 303, 'cross-open-dot', 4, 'x', 104, 'x-open', 204, 'x-dot', 304, 'x-open-dot', 5, 'triangle-up', 105, 'triangle-up-open', 205, 'triangle-up-dot', 305, 'triangle-up-open-dot', 6, 'triangle-down', 106, 'triangle-down-open', 206, 'triangle-down-dot', 306, 'triangle-down-open-dot', 7, 'triangle-left', 107, 'triangle-left-open', 207, 'triangle-left-dot', 307, 'triangle-left-open-dot', 8, 'triangle-right', 108, 'triangle-right-open', 208, 'triangle-right-dot', 308, 'triangle-right-open-dot', 9, 'triangle-ne', 109, 'triangle-ne-open', 209, 'triangle-ne-dot', 309, 'triangle-ne-open-dot', 10, 'triangle-se', 110, 'triangle-se-open', 210, 'triangle-se-dot', 310, 'triangle-se-open-dot', 11, 'triangle-sw', 111, 'triangle-sw-open', 211, 'triangle-sw-dot', 311, 'triangle-sw-open-dot', 12, 'triangle-nw', 112, 'triangle-nw-open', 212, 'triangle-nw-dot', 312, 'triangle-nw-open-dot', 13, 'pentagon', 113, 'pentagon-open', 213, 'pentagon-dot', 313, 'pentagon-open-dot', 14, 'hexagon', 114, 'hexagon-open', 214, 'hexagon-dot', 314, 'hexagon-open-dot', 15, 'hexagon2', 115, 'hexagon2-open', 215, 'hexagon2-dot', 315, 'hexagon2-open-dot', 16, 'octagon', 116, 'octagon-open', 216, 'octagon-dot', 316, 'octagon-open-dot', 17, 'star', 117, 'star-open', 217, 'star-dot', 317, 'star-open-dot', 18, 'hexagram', 118, 'hexagram-open', 218, 'hexagram-dot', 318, 'hexagram-open-dot', 19, 'star-triangle-up', 119, 'star-triangle-up-open', 219, 'star-triangle-up-dot', 319, 'star-triangle-up-open-dot', 20, 'star-triangle-down', 120, 'star-triangle-down-open', 220, 'star-triangle-down-dot', 320, 'star-triangle-down-open-dot', 21, 'star-square', 121, 'star-square-open', 221, 'star-square-dot', 321, 'star-square-open-dot', 22, 'star-diamond', 122, 'star-diamond-open', 222, 'star-diamond-dot', 322, 'star-diamond-open-dot', 23, 'diamond-tall', 123, 'diamond-tall-open', 223, 'diamond-tall-dot', 323, 'diamond-tall-open-dot', 24, 'diamond-wide', 124, 'diamond-wide-open', 224, 'diamond-wide-dot', 324, 'diamond-wide-open-dot', 25, 'hourglass', 125, 'hourglass-open', 26, 'bowtie', 126, 'bowtie-open', 27, 'circle-cross', 127, 'circle-cross-open', 28, 'circle-x', 128, 'circle-x-open', 29, 'square-cross', 129, 'square-cross-open', 30, 'square-x', 130, 'square-x-open', 31, 'diamond-cross', 131, 'diamond-cross-open', 32, 'diamond-x', 132, 'diamond-x-open', 33, 'cross-thin', 133, 'cross-thin-open', 34, 'x-thin', 134, 'x-thin-open', 35, 'asterisk', 135, 'asterisk-open', 36, 'hash', 136, 'hash-open', 236, 'hash-dot', 336, 'hash-open-dot', 37, 'y-up', 137, 'y-up-open', 38, 'y-down', 138, 'y-down-open', 39, 'y-left', 139, 'y-left-open', 40, 'y-right', 140, 'y-right-open', 41, 'line-ew', 141, 'line-ew-open', 42, 'line-ns', 142, 'line-ns-open', 43, 'line-ne', 143, 'line-ne-open', 44, 'line-nw', 144, 'line-nw-open'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["symbol"] @symbol.setter def symbol(self, val): self["symbol"] = val # symbolsrc # --------- @property def symbolsrc(self): """ Sets the source reference on plot.ly for symbol . The 'symbolsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["symbolsrc"] @symbolsrc.setter def symbolsrc(self, val): self["symbolsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterpolargl" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.scatterpolargl.marker.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu ,Reds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . line plotly.graph_objects.scatterpolargl.marker.Line instance or dict with compatible properties opacity Sets the marker opacity. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. size Sets the marker size (in px). sizemin Has an effect only if `marker.size` is set to a numerical array. Sets the minimum size (in px) of the rendered marker points. sizemode Has an effect only if `marker.size` is set to a numerical array. Sets the rule for which the data in `size` is converted to pixels. sizeref Has an effect only if `marker.size` is set to a numerical array. Sets the scale factor used to determine the rendered size of marker points. Use with `sizemin` and `sizemode`. sizesrc Sets the source reference on plot.ly for size . symbol Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot- open" to a symbol name. symbolsrc Sets the source reference on plot.ly for symbol . """ def __init__( self, arg=None, autocolorscale=None, cauto=None, cmax=None, cmid=None, cmin=None, color=None, coloraxis=None, colorbar=None, colorscale=None, colorsrc=None, line=None, opacity=None, opacitysrc=None, reversescale=None, showscale=None, size=None, sizemin=None, sizemode=None, sizeref=None, sizesrc=None, symbol=None, symbolsrc=None, **kwargs ): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterpolargl.Marker autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.scatterpolargl.marker.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu ,Reds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . line plotly.graph_objects.scatterpolargl.marker.Line instance or dict with compatible properties opacity Sets the marker opacity. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. size Sets the marker size (in px). sizemin Has an effect only if `marker.size` is set to a numerical array. Sets the minimum size (in px) of the rendered marker points. sizemode Has an effect only if `marker.size` is set to a numerical array. Sets the rule for which the data in `size` is converted to pixels. sizeref Has an effect only if `marker.size` is set to a numerical array. Sets the scale factor used to determine the rendered size of marker points. Use with `sizemin` and `sizemode`. sizesrc Sets the source reference on plot.ly for size . symbol Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot- open" to a symbol name. symbolsrc Sets the source reference on plot.ly for symbol . Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterpolargl.Marker constructor must be a dict or an instance of plotly.graph_objs.scatterpolargl.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterpolargl import marker as v_marker # Initialize validators # --------------------- self._validators["autocolorscale"] = v_marker.AutocolorscaleValidator() self._validators["cauto"] = v_marker.CautoValidator() self._validators["cmax"] = v_marker.CmaxValidator() self._validators["cmid"] = v_marker.CmidValidator() self._validators["cmin"] = v_marker.CminValidator() self._validators["color"] = v_marker.ColorValidator() self._validators["coloraxis"] = v_marker.ColoraxisValidator() self._validators["colorbar"] = v_marker.ColorBarValidator() self._validators["colorscale"] = v_marker.ColorscaleValidator() self._validators["colorsrc"] = v_marker.ColorsrcValidator() self._validators["line"] = v_marker.LineValidator() self._validators["opacity"] = v_marker.OpacityValidator() self._validators["opacitysrc"] = v_marker.OpacitysrcValidator() self._validators["reversescale"] = v_marker.ReversescaleValidator() self._validators["showscale"] = v_marker.ShowscaleValidator() self._validators["size"] = v_marker.SizeValidator() self._validators["sizemin"] = v_marker.SizeminValidator() self._validators["sizemode"] = v_marker.SizemodeValidator() self._validators["sizeref"] = v_marker.SizerefValidator() self._validators["sizesrc"] = v_marker.SizesrcValidator() self._validators["symbol"] = v_marker.SymbolValidator() self._validators["symbolsrc"] = v_marker.SymbolsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autocolorscale", None) self["autocolorscale"] = autocolorscale if autocolorscale is not None else _v _v = arg.pop("cauto", None) self["cauto"] = cauto if cauto is not None else _v _v = arg.pop("cmax", None) self["cmax"] = cmax if cmax is not None else _v _v = arg.pop("cmid", None) self["cmid"] = cmid if cmid is not None else _v _v = arg.pop("cmin", None) self["cmin"] = cmin if cmin is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("coloraxis", None) self["coloraxis"] = coloraxis if coloraxis is not None else _v _v = arg.pop("colorbar", None) self["colorbar"] = colorbar if colorbar is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("opacitysrc", None) self["opacitysrc"] = opacitysrc if opacitysrc is not None else _v _v = arg.pop("reversescale", None) self["reversescale"] = reversescale if reversescale is not None else _v _v = arg.pop("showscale", None) self["showscale"] = showscale if showscale is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizemin", None) self["sizemin"] = sizemin if sizemin is not None else _v _v = arg.pop("sizemode", None) self["sizemode"] = sizemode if sizemode is not None else _v _v = arg.pop("sizeref", None) self["sizeref"] = sizeref if sizeref is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v _v = arg.pop("symbol", None) self["symbol"] = symbol if symbol is not None else _v _v = arg.pop("symbolsrc", None) self["symbolsrc"] = symbolsrc if symbolsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the line color. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # dash # ---- @property def dash(self): """ Sets the style of the lines. The 'dash' property is an enumeration that may be specified as: - One of the following enumeration values: ['solid', 'dot', 'dash', 'longdash', 'dashdot', 'longdashdot'] Returns ------- Any """ return self["dash"] @dash.setter def dash(self, val): self["dash"] = val # shape # ----- @property def shape(self): """ Determines the line shape. The values correspond to step-wise line shapes. The 'shape' property is an enumeration that may be specified as: - One of the following enumeration values: ['linear', 'hv', 'vh', 'hvh', 'vhv'] Returns ------- Any """ return self["shape"] @shape.setter def shape(self, val): self["shape"] = val # width # ----- @property def width(self): """ Sets the line width (in px). The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterpolargl" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the line color. dash Sets the style of the lines. shape Determines the line shape. The values correspond to step-wise line shapes. width Sets the line width (in px). """ def __init__( self, arg=None, color=None, dash=None, shape=None, width=None, **kwargs ): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterpolargl.Line color Sets the line color. dash Sets the style of the lines. shape Determines the line shape. The values correspond to step-wise line shapes. width Sets the line width (in px). Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterpolargl.Line constructor must be a dict or an instance of plotly.graph_objs.scatterpolargl.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterpolargl import line as v_line # Initialize validators # --------------------- self._validators["color"] = v_line.ColorValidator() self._validators["dash"] = v_line.DashValidator() self._validators["shape"] = v_line.ShapeValidator() self._validators["width"] = v_line.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("dash", None) self["dash"] = dash if dash is not None else _v _v = arg.pop("shape", None) self["shape"] = shape if shape is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Hoverlabel(_BaseTraceHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'right', 'auto'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["align"] @align.setter def align(self, val): self["align"] = val # alignsrc # -------- @property def alignsrc(self): """ Sets the source reference on plot.ly for align . The 'alignsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["alignsrc"] @alignsrc.setter def alignsrc(self, val): self["alignsrc"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the hover labels for this trace The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bgcolorsrc # ---------- @property def bgcolorsrc(self): """ Sets the source reference on plot.ly for bgcolor . The 'bgcolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bgcolorsrc"] @bgcolorsrc.setter def bgcolorsrc(self, val): self["bgcolorsrc"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the border color of the hover labels for this trace. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # bordercolorsrc # -------------- @property def bordercolorsrc(self): """ Sets the source reference on plot.ly for bordercolor . The 'bordercolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bordercolorsrc"] @bordercolorsrc.setter def bordercolorsrc(self, val): self["bordercolorsrc"] = val # font # ---- @property def font(self): """ Sets the font used in hover labels. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.scatterpolargl.hoverlabel.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.scatterpolargl.hoverlabel.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # namelength # ---------- @property def namelength(self): """ Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. The 'namelength' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [-1, 9223372036854775807] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|numpy.ndarray """ return self["namelength"] @namelength.setter def namelength(self, val): self["namelength"] = val # namelengthsrc # ------------- @property def namelengthsrc(self): """ Sets the source reference on plot.ly for namelength . The 'namelengthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["namelengthsrc"] @namelengthsrc.setter def namelengthsrc(self, val): self["namelengthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterpolargl" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """ def __init__( self, arg=None, align=None, alignsrc=None, bgcolor=None, bgcolorsrc=None, bordercolor=None, bordercolorsrc=None, font=None, namelength=None, namelengthsrc=None, **kwargs ): """ Construct a new Hoverlabel object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterpolargl.Hoverlabel align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- Hoverlabel """ super(Hoverlabel, self).__init__("hoverlabel") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterpolargl.Hoverlabel constructor must be a dict or an instance of plotly.graph_objs.scatterpolargl.Hoverlabel""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterpolargl import hoverlabel as v_hoverlabel # Initialize validators # --------------------- self._validators["align"] = v_hoverlabel.AlignValidator() self._validators["alignsrc"] = v_hoverlabel.AlignsrcValidator() self._validators["bgcolor"] = v_hoverlabel.BgcolorValidator() self._validators["bgcolorsrc"] = v_hoverlabel.BgcolorsrcValidator() self._validators["bordercolor"] = v_hoverlabel.BordercolorValidator() self._validators["bordercolorsrc"] = v_hoverlabel.BordercolorsrcValidator() self._validators["font"] = v_hoverlabel.FontValidator() self._validators["namelength"] = v_hoverlabel.NamelengthValidator() self._validators["namelengthsrc"] = v_hoverlabel.NamelengthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("alignsrc", None) self["alignsrc"] = alignsrc if alignsrc is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bgcolorsrc", None) self["bgcolorsrc"] = bgcolorsrc if bgcolorsrc is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("bordercolorsrc", None) self["bordercolorsrc"] = bordercolorsrc if bordercolorsrc is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("namelength", None) self["namelength"] = namelength if namelength is not None else _v _v = arg.pop("namelengthsrc", None) self["namelengthsrc"] = namelengthsrc if namelengthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = [ "Hoverlabel", "Line", "Marker", "Selected", "Stream", "Textfont", "Unselected", "hoverlabel", "marker", "selected", "unselected", ] from plotly.graph_objs.scatterpolargl import unselected from plotly.graph_objs.scatterpolargl import selected from plotly.graph_objs.scatterpolargl import marker from plotly.graph_objs.scatterpolargl import hoverlabel plotly-4.4.1+dfsg.orig/plotly/graph_objs/scatterpolargl/selected/0000755000175000017500000000000013573746613024547 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scatterpolargl/selected/__init__.py0000644000175000017500000002655413573721551026666 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Textfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the text font color of selected points. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterpolargl.selected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the text font color of selected points. """ def __init__(self, arg=None, color=None, **kwargs): """ Construct a new Textfont object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterpolargl.selected.Textfont color Sets the text font color of selected points. Returns ------- Textfont """ super(Textfont, self).__init__("textfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterpolargl.selected.Textfont constructor must be a dict or an instance of plotly.graph_objs.scatterpolargl.selected.Textfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterpolargl.selected import textfont as v_textfont # Initialize validators # --------------------- self._validators["color"] = v_textfont.ColorValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the marker color of selected points. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # opacity # ------- @property def opacity(self): """ Sets the marker opacity of selected points. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # size # ---- @property def size(self): """ Sets the marker size of selected points. The 'size' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterpolargl.selected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. size Sets the marker size of selected points. """ def __init__(self, arg=None, color=None, opacity=None, size=None, **kwargs): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterpolargl.selected.Marker color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. size Sets the marker size of selected points. Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterpolargl.selected.Marker constructor must be a dict or an instance of plotly.graph_objs.scatterpolargl.selected.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterpolargl.selected import marker as v_marker # Initialize validators # --------------------- self._validators["color"] = v_marker.ColorValidator() self._validators["opacity"] = v_marker.OpacityValidator() self._validators["size"] = v_marker.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Marker", "Textfont"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/graph_objs.py0000644000175000017500000000004013573721535022407 0ustar noahfxnoahfxfrom plotly.graph_objs import * plotly-4.4.1+dfsg.orig/plotly/graph_objs/histogram2d/0000755000175000017500000000000013573746613022154 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/histogram2d/hoverlabel/0000755000175000017500000000000013573746613024277 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/histogram2d/hoverlabel/__init__.py0000644000175000017500000002546413573721546026421 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram2d.hoverlabel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Font object Sets the font used in hover labels. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.histogram2d.hoverlabel.Font color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.histogram2d.hoverlabel.Font constructor must be a dict or an instance of plotly.graph_objs.histogram2d.hoverlabel.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram2d.hoverlabel import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["colorsrc"] = v_font.ColorsrcValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["familysrc"] = v_font.FamilysrcValidator() self._validators["size"] = v_font.SizeValidator() self._validators["sizesrc"] = v_font.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/histogram2d/colorbar/0000755000175000017500000000000013573746613023757 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/histogram2d/colorbar/title/0000755000175000017500000000000013573746613025100 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/histogram2d/colorbar/title/__init__.py0000644000175000017500000002055113573721546027212 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram2d.colorbar.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.histogram2d.colorbar.title.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.histogram2d.colorbar.title.Font constructor must be a dict or an instance of plotly.graph_objs.histogram2d.colorbar.title.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram2d.colorbar.title import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/histogram2d/colorbar/__init__.py0000644000175000017500000006066613573721546026104 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Title(_BaseTraceHierarchyType): # font # ---- @property def font(self): """ Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.histogram2d.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.histogram2d.colorbar.title.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # side # ---- @property def side(self): """ Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- Any """ return self["side"] @side.setter def side(self, val): self["side"] = val # text # ---- @property def text(self): """ Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram2d.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """ def __init__(self, arg=None, font=None, side=None, text=None, **kwargs): """ Construct a new Title object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.histogram2d.colorbar.Title font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- Title """ super(Title, self).__init__("title") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.histogram2d.colorbar.Title constructor must be a dict or an instance of plotly.graph_objs.histogram2d.colorbar.Title""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram2d.colorbar import title as v_title # Initialize validators # --------------------- self._validators["font"] = v_title.FontValidator() self._validators["side"] = v_title.SideValidator() self._validators["text"] = v_title.TextValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("side", None) self["side"] = side if side is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickformatstop(_BaseTraceHierarchyType): # dtickrange # ---------- @property def dtickrange(self): """ range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" The 'dtickrange' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'dtickrange[0]' property accepts values of any type (1) The 'dtickrange[1]' property accepts values of any type Returns ------- list """ return self["dtickrange"] @dtickrange.setter def dtickrange(self, val): self["dtickrange"] = val # enabled # ------- @property def enabled(self): """ Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. The 'enabled' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["enabled"] @enabled.setter def enabled(self, val): self["enabled"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # value # ----- @property def value(self): """ string - dtickformat for described zoom level, the same as "tickformat" The 'value' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram2d.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """ def __init__( self, arg=None, dtickrange=None, enabled=None, name=None, templateitemname=None, value=None, **kwargs ): """ Construct a new Tickformatstop object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.histogram2d.colorbar.Tickformatstop dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- Tickformatstop """ super(Tickformatstop, self).__init__("tickformatstops") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.histogram2d.colorbar.Tickformatstop constructor must be a dict or an instance of plotly.graph_objs.histogram2d.colorbar.Tickformatstop""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram2d.colorbar import ( tickformatstop as v_tickformatstop, ) # Initialize validators # --------------------- self._validators["dtickrange"] = v_tickformatstop.DtickrangeValidator() self._validators["enabled"] = v_tickformatstop.EnabledValidator() self._validators["name"] = v_tickformatstop.NameValidator() self._validators[ "templateitemname" ] = v_tickformatstop.TemplateitemnameValidator() self._validators["value"] = v_tickformatstop.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtickrange", None) self["dtickrange"] = dtickrange if dtickrange is not None else _v _v = arg.pop("enabled", None) self["enabled"] = enabled if enabled is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram2d.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Tickfont object Sets the color bar's tick label font Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.histogram2d.colorbar.Tickfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Tickfont """ super(Tickfont, self).__init__("tickfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.histogram2d.colorbar.Tickfont constructor must be a dict or an instance of plotly.graph_objs.histogram2d.colorbar.Tickfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram2d.colorbar import tickfont as v_tickfont # Initialize validators # --------------------- self._validators["color"] = v_tickfont.ColorValidator() self._validators["family"] = v_tickfont.FamilyValidator() self._validators["size"] = v_tickfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Tickfont", "Tickformatstop", "Tickformatstop", "Title", "title"] from plotly.graph_objs.histogram2d.colorbar import title plotly-4.4.1+dfsg.orig/plotly/graph_objs/histogram2d/__init__.py0000644000175000017500000033107513573721550024267 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class YBins(_BaseTraceHierarchyType): # end # --- @property def end(self): """ Sets the end value for the y axis bins. The last bin may not end exactly at this value, we increment the bin edge by `size` from `start` until we reach or exceed `end`. Defaults to the maximum data value. Like `start`, for dates use a date string, and for category data `end` is based on the category serial numbers. The 'end' property accepts values of any type Returns ------- Any """ return self["end"] @end.setter def end(self, val): self["end"] = val # size # ---- @property def size(self): """ Sets the size of each y axis bin. Default behavior: If `nbinsy` is 0 or omitted, we choose a nice round bin size such that the number of bins is about the same as the typical number of samples in each bin. If `nbinsy` is provided, we choose a nice round bin size giving no more than that many bins. For date data, use milliseconds or "M" for months, as in `axis.dtick`. For category data, the number of categories to bin together (always defaults to 1). The 'size' property accepts values of any type Returns ------- Any """ return self["size"] @size.setter def size(self, val): self["size"] = val # start # ----- @property def start(self): """ Sets the starting value for the y axis bins. Defaults to the minimum data value, shifted down if necessary to make nice round values and to remove ambiguous bin edges. For example, if most of the data is integers we shift the bin edges 0.5 down, so a `size` of 5 would have a default `start` of -0.5, so it is clear that 0-4 are in the first bin, 5-9 in the second, but continuous data gets a start of 0 and bins [0,5), [5,10) etc. Dates behave similarly, and `start` should be a date string. For category data, `start` is based on the category serial numbers, and defaults to -0.5. The 'start' property accepts values of any type Returns ------- Any """ return self["start"] @start.setter def start(self, val): self["start"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram2d" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ end Sets the end value for the y axis bins. The last bin may not end exactly at this value, we increment the bin edge by `size` from `start` until we reach or exceed `end`. Defaults to the maximum data value. Like `start`, for dates use a date string, and for category data `end` is based on the category serial numbers. size Sets the size of each y axis bin. Default behavior: If `nbinsy` is 0 or omitted, we choose a nice round bin size such that the number of bins is about the same as the typical number of samples in each bin. If `nbinsy` is provided, we choose a nice round bin size giving no more than that many bins. For date data, use milliseconds or "M" for months, as in `axis.dtick`. For category data, the number of categories to bin together (always defaults to 1). start Sets the starting value for the y axis bins. Defaults to the minimum data value, shifted down if necessary to make nice round values and to remove ambiguous bin edges. For example, if most of the data is integers we shift the bin edges 0.5 down, so a `size` of 5 would have a default `start` of -0.5, so it is clear that 0-4 are in the first bin, 5-9 in the second, but continuous data gets a start of 0 and bins [0,5), [5,10) etc. Dates behave similarly, and `start` should be a date string. For category data, `start` is based on the category serial numbers, and defaults to -0.5. """ def __init__(self, arg=None, end=None, size=None, start=None, **kwargs): """ Construct a new YBins object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.histogram2d.YBins end Sets the end value for the y axis bins. The last bin may not end exactly at this value, we increment the bin edge by `size` from `start` until we reach or exceed `end`. Defaults to the maximum data value. Like `start`, for dates use a date string, and for category data `end` is based on the category serial numbers. size Sets the size of each y axis bin. Default behavior: If `nbinsy` is 0 or omitted, we choose a nice round bin size such that the number of bins is about the same as the typical number of samples in each bin. If `nbinsy` is provided, we choose a nice round bin size giving no more than that many bins. For date data, use milliseconds or "M" for months, as in `axis.dtick`. For category data, the number of categories to bin together (always defaults to 1). start Sets the starting value for the y axis bins. Defaults to the minimum data value, shifted down if necessary to make nice round values and to remove ambiguous bin edges. For example, if most of the data is integers we shift the bin edges 0.5 down, so a `size` of 5 would have a default `start` of -0.5, so it is clear that 0-4 are in the first bin, 5-9 in the second, but continuous data gets a start of 0 and bins [0,5), [5,10) etc. Dates behave similarly, and `start` should be a date string. For category data, `start` is based on the category serial numbers, and defaults to -0.5. Returns ------- YBins """ super(YBins, self).__init__("ybins") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.histogram2d.YBins constructor must be a dict or an instance of plotly.graph_objs.histogram2d.YBins""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram2d import ybins as v_ybins # Initialize validators # --------------------- self._validators["end"] = v_ybins.EndValidator() self._validators["size"] = v_ybins.SizeValidator() self._validators["start"] = v_ybins.StartValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("end", None) self["end"] = end if end is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("start", None) self["start"] = start if start is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class XBins(_BaseTraceHierarchyType): # end # --- @property def end(self): """ Sets the end value for the x axis bins. The last bin may not end exactly at this value, we increment the bin edge by `size` from `start` until we reach or exceed `end`. Defaults to the maximum data value. Like `start`, for dates use a date string, and for category data `end` is based on the category serial numbers. The 'end' property accepts values of any type Returns ------- Any """ return self["end"] @end.setter def end(self, val): self["end"] = val # size # ---- @property def size(self): """ Sets the size of each x axis bin. Default behavior: If `nbinsx` is 0 or omitted, we choose a nice round bin size such that the number of bins is about the same as the typical number of samples in each bin. If `nbinsx` is provided, we choose a nice round bin size giving no more than that many bins. For date data, use milliseconds or "M" for months, as in `axis.dtick`. For category data, the number of categories to bin together (always defaults to 1). The 'size' property accepts values of any type Returns ------- Any """ return self["size"] @size.setter def size(self, val): self["size"] = val # start # ----- @property def start(self): """ Sets the starting value for the x axis bins. Defaults to the minimum data value, shifted down if necessary to make nice round values and to remove ambiguous bin edges. For example, if most of the data is integers we shift the bin edges 0.5 down, so a `size` of 5 would have a default `start` of -0.5, so it is clear that 0-4 are in the first bin, 5-9 in the second, but continuous data gets a start of 0 and bins [0,5), [5,10) etc. Dates behave similarly, and `start` should be a date string. For category data, `start` is based on the category serial numbers, and defaults to -0.5. The 'start' property accepts values of any type Returns ------- Any """ return self["start"] @start.setter def start(self, val): self["start"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram2d" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ end Sets the end value for the x axis bins. The last bin may not end exactly at this value, we increment the bin edge by `size` from `start` until we reach or exceed `end`. Defaults to the maximum data value. Like `start`, for dates use a date string, and for category data `end` is based on the category serial numbers. size Sets the size of each x axis bin. Default behavior: If `nbinsx` is 0 or omitted, we choose a nice round bin size such that the number of bins is about the same as the typical number of samples in each bin. If `nbinsx` is provided, we choose a nice round bin size giving no more than that many bins. For date data, use milliseconds or "M" for months, as in `axis.dtick`. For category data, the number of categories to bin together (always defaults to 1). start Sets the starting value for the x axis bins. Defaults to the minimum data value, shifted down if necessary to make nice round values and to remove ambiguous bin edges. For example, if most of the data is integers we shift the bin edges 0.5 down, so a `size` of 5 would have a default `start` of -0.5, so it is clear that 0-4 are in the first bin, 5-9 in the second, but continuous data gets a start of 0 and bins [0,5), [5,10) etc. Dates behave similarly, and `start` should be a date string. For category data, `start` is based on the category serial numbers, and defaults to -0.5. """ def __init__(self, arg=None, end=None, size=None, start=None, **kwargs): """ Construct a new XBins object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.histogram2d.XBins end Sets the end value for the x axis bins. The last bin may not end exactly at this value, we increment the bin edge by `size` from `start` until we reach or exceed `end`. Defaults to the maximum data value. Like `start`, for dates use a date string, and for category data `end` is based on the category serial numbers. size Sets the size of each x axis bin. Default behavior: If `nbinsx` is 0 or omitted, we choose a nice round bin size such that the number of bins is about the same as the typical number of samples in each bin. If `nbinsx` is provided, we choose a nice round bin size giving no more than that many bins. For date data, use milliseconds or "M" for months, as in `axis.dtick`. For category data, the number of categories to bin together (always defaults to 1). start Sets the starting value for the x axis bins. Defaults to the minimum data value, shifted down if necessary to make nice round values and to remove ambiguous bin edges. For example, if most of the data is integers we shift the bin edges 0.5 down, so a `size` of 5 would have a default `start` of -0.5, so it is clear that 0-4 are in the first bin, 5-9 in the second, but continuous data gets a start of 0 and bins [0,5), [5,10) etc. Dates behave similarly, and `start` should be a date string. For category data, `start` is based on the category serial numbers, and defaults to -0.5. Returns ------- XBins """ super(XBins, self).__init__("xbins") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.histogram2d.XBins constructor must be a dict or an instance of plotly.graph_objs.histogram2d.XBins""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram2d import xbins as v_xbins # Initialize validators # --------------------- self._validators["end"] = v_xbins.EndValidator() self._validators["size"] = v_xbins.SizeValidator() self._validators["start"] = v_xbins.StartValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("end", None) self["end"] = end if end is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("start", None) self["start"] = start if start is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Stream(_BaseTraceHierarchyType): # maxpoints # --------- @property def maxpoints(self): """ Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. The 'maxpoints' property is a number and may be specified as: - An int or float in the interval [0, 10000] Returns ------- int|float """ return self["maxpoints"] @maxpoints.setter def maxpoints(self, val): self["maxpoints"] = val # token # ----- @property def token(self): """ The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. The 'token' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["token"] @token.setter def token(self, val): self["token"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram2d" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """ def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): """ Construct a new Stream object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.histogram2d.Stream maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- Stream """ super(Stream, self).__init__("stream") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.histogram2d.Stream constructor must be a dict or an instance of plotly.graph_objs.histogram2d.Stream""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram2d import stream as v_stream # Initialize validators # --------------------- self._validators["maxpoints"] = v_stream.MaxpointsValidator() self._validators["token"] = v_stream.TokenValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("maxpoints", None) self["maxpoints"] = maxpoints if maxpoints is not None else _v _v = arg.pop("token", None) self["token"] = token if token is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the aggregation data. The 'color' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram2d" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the aggregation data. colorsrc Sets the source reference on plot.ly for color . """ def __init__(self, arg=None, color=None, colorsrc=None, **kwargs): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.histogram2d.Marker color Sets the aggregation data. colorsrc Sets the source reference on plot.ly for color . Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.histogram2d.Marker constructor must be a dict or an instance of plotly.graph_objs.histogram2d.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram2d import marker as v_marker # Initialize validators # --------------------- self._validators["color"] = v_marker.ColorValidator() self._validators["colorsrc"] = v_marker.ColorsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Hoverlabel(_BaseTraceHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'right', 'auto'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["align"] @align.setter def align(self, val): self["align"] = val # alignsrc # -------- @property def alignsrc(self): """ Sets the source reference on plot.ly for align . The 'alignsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["alignsrc"] @alignsrc.setter def alignsrc(self, val): self["alignsrc"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the hover labels for this trace The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bgcolorsrc # ---------- @property def bgcolorsrc(self): """ Sets the source reference on plot.ly for bgcolor . The 'bgcolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bgcolorsrc"] @bgcolorsrc.setter def bgcolorsrc(self, val): self["bgcolorsrc"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the border color of the hover labels for this trace. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # bordercolorsrc # -------------- @property def bordercolorsrc(self): """ Sets the source reference on plot.ly for bordercolor . The 'bordercolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bordercolorsrc"] @bordercolorsrc.setter def bordercolorsrc(self, val): self["bordercolorsrc"] = val # font # ---- @property def font(self): """ Sets the font used in hover labels. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.histogram2d.hoverlabel.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.histogram2d.hoverlabel.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # namelength # ---------- @property def namelength(self): """ Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. The 'namelength' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [-1, 9223372036854775807] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|numpy.ndarray """ return self["namelength"] @namelength.setter def namelength(self, val): self["namelength"] = val # namelengthsrc # ------------- @property def namelengthsrc(self): """ Sets the source reference on plot.ly for namelength . The 'namelengthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["namelengthsrc"] @namelengthsrc.setter def namelengthsrc(self, val): self["namelengthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram2d" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """ def __init__( self, arg=None, align=None, alignsrc=None, bgcolor=None, bgcolorsrc=None, bordercolor=None, bordercolorsrc=None, font=None, namelength=None, namelengthsrc=None, **kwargs ): """ Construct a new Hoverlabel object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.histogram2d.Hoverlabel align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- Hoverlabel """ super(Hoverlabel, self).__init__("hoverlabel") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.histogram2d.Hoverlabel constructor must be a dict or an instance of plotly.graph_objs.histogram2d.Hoverlabel""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram2d import hoverlabel as v_hoverlabel # Initialize validators # --------------------- self._validators["align"] = v_hoverlabel.AlignValidator() self._validators["alignsrc"] = v_hoverlabel.AlignsrcValidator() self._validators["bgcolor"] = v_hoverlabel.BgcolorValidator() self._validators["bgcolorsrc"] = v_hoverlabel.BgcolorsrcValidator() self._validators["bordercolor"] = v_hoverlabel.BordercolorValidator() self._validators["bordercolorsrc"] = v_hoverlabel.BordercolorsrcValidator() self._validators["font"] = v_hoverlabel.FontValidator() self._validators["namelength"] = v_hoverlabel.NamelengthValidator() self._validators["namelengthsrc"] = v_hoverlabel.NamelengthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("alignsrc", None) self["alignsrc"] = alignsrc if alignsrc is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bgcolorsrc", None) self["bgcolorsrc"] = bgcolorsrc if bgcolorsrc is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("bordercolorsrc", None) self["bordercolorsrc"] = bordercolorsrc if bordercolorsrc is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("namelength", None) self["namelength"] = namelength if namelength is not None else _v _v = arg.pop("namelengthsrc", None) self["namelengthsrc"] = namelengthsrc if namelengthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class ColorBar(_BaseTraceHierarchyType): # bgcolor # ------- @property def bgcolor(self): """ Sets the color of padded area. The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the axis line color. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # borderwidth # ----------- @property def borderwidth(self): """ Sets the width (in px) or the border enclosing this color bar. The 'borderwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["borderwidth"] @borderwidth.setter def borderwidth(self, val): self["borderwidth"] = val # dtick # ----- @property def dtick(self): """ Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" The 'dtick' property accepts values of any type Returns ------- Any """ return self["dtick"] @dtick.setter def dtick(self, val): self["dtick"] = val # exponentformat # -------------- @property def exponentformat(self): """ Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. The 'exponentformat' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'e', 'E', 'power', 'SI', 'B'] Returns ------- Any """ return self["exponentformat"] @exponentformat.setter def exponentformat(self, val): self["exponentformat"] = val # len # --- @property def len(self): """ Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. The 'len' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["len"] @len.setter def len(self, val): self["len"] = val # lenmode # ------- @property def lenmode(self): """ Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. The 'lenmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["lenmode"] @lenmode.setter def lenmode(self, val): self["lenmode"] = val # nticks # ------ @property def nticks(self): """ Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". The 'nticks' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nticks"] @nticks.setter def nticks(self, val): self["nticks"] = val # outlinecolor # ------------ @property def outlinecolor(self): """ Sets the axis line color. The 'outlinecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["outlinecolor"] @outlinecolor.setter def outlinecolor(self, val): self["outlinecolor"] = val # outlinewidth # ------------ @property def outlinewidth(self): """ Sets the width (in px) of the axis line. The 'outlinewidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["outlinewidth"] @outlinewidth.setter def outlinewidth(self, val): self["outlinewidth"] = val # separatethousands # ----------------- @property def separatethousands(self): """ If "true", even 4-digit integers are separated The 'separatethousands' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["separatethousands"] @separatethousands.setter def separatethousands(self, val): self["separatethousands"] = val # showexponent # ------------ @property def showexponent(self): """ If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. The 'showexponent' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showexponent"] @showexponent.setter def showexponent(self, val): self["showexponent"] = val # showticklabels # -------------- @property def showticklabels(self): """ Determines whether or not the tick labels are drawn. The 'showticklabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showticklabels"] @showticklabels.setter def showticklabels(self, val): self["showticklabels"] = val # showtickprefix # -------------- @property def showtickprefix(self): """ If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. The 'showtickprefix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showtickprefix"] @showtickprefix.setter def showtickprefix(self, val): self["showtickprefix"] = val # showticksuffix # -------------- @property def showticksuffix(self): """ Same as `showtickprefix` but for tick suffixes. The 'showticksuffix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showticksuffix"] @showticksuffix.setter def showticksuffix(self, val): self["showticksuffix"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # thicknessmode # ------------- @property def thicknessmode(self): """ Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. The 'thicknessmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["thicknessmode"] @thicknessmode.setter def thicknessmode(self, val): self["thicknessmode"] = val # tick0 # ----- @property def tick0(self): """ Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. The 'tick0' property accepts values of any type Returns ------- Any """ return self["tick0"] @tick0.setter def tick0(self, val): self["tick0"] = val # tickangle # --------- @property def tickangle(self): """ Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. The 'tickangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["tickangle"] @tickangle.setter def tickangle(self, val): self["tickangle"] = val # tickcolor # --------- @property def tickcolor(self): """ Sets the tick color. The 'tickcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["tickcolor"] @tickcolor.setter def tickcolor(self, val): self["tickcolor"] = val # tickfont # -------- @property def tickfont(self): """ Sets the color bar's tick label font The 'tickfont' property is an instance of Tickfont that may be specified as: - An instance of plotly.graph_objs.histogram2d.colorbar.Tickfont - A dict of string/value properties that will be passed to the Tickfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.histogram2d.colorbar.Tickfont """ return self["tickfont"] @tickfont.setter def tickfont(self, val): self["tickfont"] = val # tickformat # ---------- @property def tickformat(self): """ Sets the tick label formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'tickformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickformat"] @tickformat.setter def tickformat(self, val): self["tickformat"] = val # tickformatstops # --------------- @property def tickformatstops(self): """ The 'tickformatstops' property is a tuple of instances of Tickformatstop that may be specified as: - A list or tuple of instances of plotly.graph_objs.histogram2d.colorbar.Tickformatstop - A list or tuple of dicts of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- tuple[plotly.graph_objs.histogram2d.colorbar.Tickformatstop] """ return self["tickformatstops"] @tickformatstops.setter def tickformatstops(self, val): self["tickformatstops"] = val # tickformatstopdefaults # ---------------------- @property def tickformatstopdefaults(self): """ When used in a template (as layout.template.data.histogram2d.co lorbar.tickformatstopdefaults), sets the default property values to use for elements of histogram2d.colorbar.tickformatstops The 'tickformatstopdefaults' property is an instance of Tickformatstop that may be specified as: - An instance of plotly.graph_objs.histogram2d.colorbar.Tickformatstop - A dict of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: Returns ------- plotly.graph_objs.histogram2d.colorbar.Tickformatstop """ return self["tickformatstopdefaults"] @tickformatstopdefaults.setter def tickformatstopdefaults(self, val): self["tickformatstopdefaults"] = val # ticklen # ------- @property def ticklen(self): """ Sets the tick length (in px). The 'ticklen' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ticklen"] @ticklen.setter def ticklen(self, val): self["ticklen"] = val # tickmode # -------- @property def tickmode(self): """ Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). The 'tickmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'linear', 'array'] Returns ------- Any """ return self["tickmode"] @tickmode.setter def tickmode(self, val): self["tickmode"] = val # tickprefix # ---------- @property def tickprefix(self): """ Sets a tick label prefix. The 'tickprefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickprefix"] @tickprefix.setter def tickprefix(self, val): self["tickprefix"] = val # ticks # ----- @property def ticks(self): """ Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. The 'ticks' property is an enumeration that may be specified as: - One of the following enumeration values: ['outside', 'inside', ''] Returns ------- Any """ return self["ticks"] @ticks.setter def ticks(self, val): self["ticks"] = val # ticksuffix # ---------- @property def ticksuffix(self): """ Sets a tick label suffix. The 'ticksuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ticksuffix"] @ticksuffix.setter def ticksuffix(self, val): self["ticksuffix"] = val # ticktext # -------- @property def ticktext(self): """ Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. The 'ticktext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ticktext"] @ticktext.setter def ticktext(self, val): self["ticktext"] = val # ticktextsrc # ----------- @property def ticktextsrc(self): """ Sets the source reference on plot.ly for ticktext . The 'ticktextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ticktextsrc"] @ticktextsrc.setter def ticktextsrc(self, val): self["ticktextsrc"] = val # tickvals # -------- @property def tickvals(self): """ Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. The 'tickvals' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["tickvals"] @tickvals.setter def tickvals(self, val): self["tickvals"] = val # tickvalssrc # ----------- @property def tickvalssrc(self): """ Sets the source reference on plot.ly for tickvals . The 'tickvalssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tickvalssrc"] @tickvalssrc.setter def tickvalssrc(self, val): self["tickvalssrc"] = val # tickwidth # --------- @property def tickwidth(self): """ Sets the tick width (in px). The 'tickwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["tickwidth"] @tickwidth.setter def tickwidth(self, val): self["tickwidth"] = val # title # ----- @property def title(self): """ The 'title' property is an instance of Title that may be specified as: - An instance of plotly.graph_objs.histogram2d.colorbar.Title - A dict of string/value properties that will be passed to the Title constructor Supported dict properties: font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- plotly.graph_objs.histogram2d.colorbar.Title """ return self["title"] @title.setter def title(self, val): self["title"] = val # titlefont # --------- @property def titlefont(self): """ Deprecated: Please use histogram2d.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.histogram2d.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- """ return self["titlefont"] @titlefont.setter def titlefont(self, val): self["titlefont"] = val # titleside # --------- @property def titleside(self): """ Deprecated: Please use histogram2d.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- """ return self["titleside"] @titleside.setter def titleside(self, val): self["titleside"] = val # x # - @property def x(self): """ Sets the x position of the color bar (in plot fraction). The 'x' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["x"] @x.setter def x(self, val): self["x"] = val # xanchor # ------- @property def xanchor(self): """ Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. The 'xanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'center', 'right'] Returns ------- Any """ return self["xanchor"] @xanchor.setter def xanchor(self, val): self["xanchor"] = val # xpad # ---- @property def xpad(self): """ Sets the amount of padding (in px) along the x direction. The 'xpad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["xpad"] @xpad.setter def xpad(self, val): self["xpad"] = val # y # - @property def y(self): """ Sets the y position of the color bar (in plot fraction). The 'y' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["y"] @y.setter def y(self, val): self["y"] = val # yanchor # ------- @property def yanchor(self): """ Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. The 'yanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['top', 'middle', 'bottom'] Returns ------- Any """ return self["yanchor"] @yanchor.setter def yanchor(self, val): self["yanchor"] = val # ypad # ---- @property def ypad(self): """ Sets the amount of padding (in px) along the y direction. The 'ypad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ypad"] @ypad.setter def ypad(self, val): self["ypad"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram2d" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.histogram2d.colorbar.Ti ckformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.histog ram2d.colorbar.tickformatstopdefaults), sets the default property values to use for elements of histogram2d.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.histogram2d.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use histogram2d.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use histogram2d.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """ _mapped_properties = { "titlefont": ("title", "font"), "titleside": ("title", "side"), } def __init__( self, arg=None, bgcolor=None, bordercolor=None, borderwidth=None, dtick=None, exponentformat=None, len=None, lenmode=None, nticks=None, outlinecolor=None, outlinewidth=None, separatethousands=None, showexponent=None, showticklabels=None, showtickprefix=None, showticksuffix=None, thickness=None, thicknessmode=None, tick0=None, tickangle=None, tickcolor=None, tickfont=None, tickformat=None, tickformatstops=None, tickformatstopdefaults=None, ticklen=None, tickmode=None, tickprefix=None, ticks=None, ticksuffix=None, ticktext=None, ticktextsrc=None, tickvals=None, tickvalssrc=None, tickwidth=None, title=None, titlefont=None, titleside=None, x=None, xanchor=None, xpad=None, y=None, yanchor=None, ypad=None, **kwargs ): """ Construct a new ColorBar object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.histogram2d.ColorBar bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.histogram2d.colorbar.Ti ckformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.histog ram2d.colorbar.tickformatstopdefaults), sets the default property values to use for elements of histogram2d.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.histogram2d.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use histogram2d.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use histogram2d.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- ColorBar """ super(ColorBar, self).__init__("colorbar") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.histogram2d.ColorBar constructor must be a dict or an instance of plotly.graph_objs.histogram2d.ColorBar""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram2d import colorbar as v_colorbar # Initialize validators # --------------------- self._validators["bgcolor"] = v_colorbar.BgcolorValidator() self._validators["bordercolor"] = v_colorbar.BordercolorValidator() self._validators["borderwidth"] = v_colorbar.BorderwidthValidator() self._validators["dtick"] = v_colorbar.DtickValidator() self._validators["exponentformat"] = v_colorbar.ExponentformatValidator() self._validators["len"] = v_colorbar.LenValidator() self._validators["lenmode"] = v_colorbar.LenmodeValidator() self._validators["nticks"] = v_colorbar.NticksValidator() self._validators["outlinecolor"] = v_colorbar.OutlinecolorValidator() self._validators["outlinewidth"] = v_colorbar.OutlinewidthValidator() self._validators["separatethousands"] = v_colorbar.SeparatethousandsValidator() self._validators["showexponent"] = v_colorbar.ShowexponentValidator() self._validators["showticklabels"] = v_colorbar.ShowticklabelsValidator() self._validators["showtickprefix"] = v_colorbar.ShowtickprefixValidator() self._validators["showticksuffix"] = v_colorbar.ShowticksuffixValidator() self._validators["thickness"] = v_colorbar.ThicknessValidator() self._validators["thicknessmode"] = v_colorbar.ThicknessmodeValidator() self._validators["tick0"] = v_colorbar.Tick0Validator() self._validators["tickangle"] = v_colorbar.TickangleValidator() self._validators["tickcolor"] = v_colorbar.TickcolorValidator() self._validators["tickfont"] = v_colorbar.TickfontValidator() self._validators["tickformat"] = v_colorbar.TickformatValidator() self._validators["tickformatstops"] = v_colorbar.TickformatstopsValidator() self._validators[ "tickformatstopdefaults" ] = v_colorbar.TickformatstopValidator() self._validators["ticklen"] = v_colorbar.TicklenValidator() self._validators["tickmode"] = v_colorbar.TickmodeValidator() self._validators["tickprefix"] = v_colorbar.TickprefixValidator() self._validators["ticks"] = v_colorbar.TicksValidator() self._validators["ticksuffix"] = v_colorbar.TicksuffixValidator() self._validators["ticktext"] = v_colorbar.TicktextValidator() self._validators["ticktextsrc"] = v_colorbar.TicktextsrcValidator() self._validators["tickvals"] = v_colorbar.TickvalsValidator() self._validators["tickvalssrc"] = v_colorbar.TickvalssrcValidator() self._validators["tickwidth"] = v_colorbar.TickwidthValidator() self._validators["title"] = v_colorbar.TitleValidator() self._validators["x"] = v_colorbar.XValidator() self._validators["xanchor"] = v_colorbar.XanchorValidator() self._validators["xpad"] = v_colorbar.XpadValidator() self._validators["y"] = v_colorbar.YValidator() self._validators["yanchor"] = v_colorbar.YanchorValidator() self._validators["ypad"] = v_colorbar.YpadValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("borderwidth", None) self["borderwidth"] = borderwidth if borderwidth is not None else _v _v = arg.pop("dtick", None) self["dtick"] = dtick if dtick is not None else _v _v = arg.pop("exponentformat", None) self["exponentformat"] = exponentformat if exponentformat is not None else _v _v = arg.pop("len", None) self["len"] = len if len is not None else _v _v = arg.pop("lenmode", None) self["lenmode"] = lenmode if lenmode is not None else _v _v = arg.pop("nticks", None) self["nticks"] = nticks if nticks is not None else _v _v = arg.pop("outlinecolor", None) self["outlinecolor"] = outlinecolor if outlinecolor is not None else _v _v = arg.pop("outlinewidth", None) self["outlinewidth"] = outlinewidth if outlinewidth is not None else _v _v = arg.pop("separatethousands", None) self["separatethousands"] = ( separatethousands if separatethousands is not None else _v ) _v = arg.pop("showexponent", None) self["showexponent"] = showexponent if showexponent is not None else _v _v = arg.pop("showticklabels", None) self["showticklabels"] = showticklabels if showticklabels is not None else _v _v = arg.pop("showtickprefix", None) self["showtickprefix"] = showtickprefix if showtickprefix is not None else _v _v = arg.pop("showticksuffix", None) self["showticksuffix"] = showticksuffix if showticksuffix is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("thicknessmode", None) self["thicknessmode"] = thicknessmode if thicknessmode is not None else _v _v = arg.pop("tick0", None) self["tick0"] = tick0 if tick0 is not None else _v _v = arg.pop("tickangle", None) self["tickangle"] = tickangle if tickangle is not None else _v _v = arg.pop("tickcolor", None) self["tickcolor"] = tickcolor if tickcolor is not None else _v _v = arg.pop("tickfont", None) self["tickfont"] = tickfont if tickfont is not None else _v _v = arg.pop("tickformat", None) self["tickformat"] = tickformat if tickformat is not None else _v _v = arg.pop("tickformatstops", None) self["tickformatstops"] = tickformatstops if tickformatstops is not None else _v _v = arg.pop("tickformatstopdefaults", None) self["tickformatstopdefaults"] = ( tickformatstopdefaults if tickformatstopdefaults is not None else _v ) _v = arg.pop("ticklen", None) self["ticklen"] = ticklen if ticklen is not None else _v _v = arg.pop("tickmode", None) self["tickmode"] = tickmode if tickmode is not None else _v _v = arg.pop("tickprefix", None) self["tickprefix"] = tickprefix if tickprefix is not None else _v _v = arg.pop("ticks", None) self["ticks"] = ticks if ticks is not None else _v _v = arg.pop("ticksuffix", None) self["ticksuffix"] = ticksuffix if ticksuffix is not None else _v _v = arg.pop("ticktext", None) self["ticktext"] = ticktext if ticktext is not None else _v _v = arg.pop("ticktextsrc", None) self["ticktextsrc"] = ticktextsrc if ticktextsrc is not None else _v _v = arg.pop("tickvals", None) self["tickvals"] = tickvals if tickvals is not None else _v _v = arg.pop("tickvalssrc", None) self["tickvalssrc"] = tickvalssrc if tickvalssrc is not None else _v _v = arg.pop("tickwidth", None) self["tickwidth"] = tickwidth if tickwidth is not None else _v _v = arg.pop("title", None) self["title"] = title if title is not None else _v _v = arg.pop("titlefont", None) _v = titlefont if titlefont is not None else _v if _v is not None: self["titlefont"] = _v _v = arg.pop("titleside", None) _v = titleside if titleside is not None else _v if _v is not None: self["titleside"] = _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xanchor", None) self["xanchor"] = xanchor if xanchor is not None else _v _v = arg.pop("xpad", None) self["xpad"] = xpad if xpad is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("yanchor", None) self["yanchor"] = yanchor if yanchor is not None else _v _v = arg.pop("ypad", None) self["ypad"] = ypad if ypad is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = [ "ColorBar", "Hoverlabel", "Marker", "Stream", "XBins", "YBins", "colorbar", "hoverlabel", ] from plotly.graph_objs.histogram2d import hoverlabel from plotly.graph_objs.histogram2d import colorbar plotly-4.4.1+dfsg.orig/plotly/graph_objs/barpolar/0000755000175000017500000000000013573746613021533 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/barpolar/unselected/0000755000175000017500000000000013573746613023666 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/barpolar/unselected/__init__.py0000644000175000017500000002612413573721545026001 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Textfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the text font color of unselected points, applied only when a selection exists. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "barpolar.unselected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the text font color of unselected points, applied only when a selection exists. """ def __init__(self, arg=None, color=None, **kwargs): """ Construct a new Textfont object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.barpolar.unselected.Textfont color Sets the text font color of unselected points, applied only when a selection exists. Returns ------- Textfont """ super(Textfont, self).__init__("textfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.barpolar.unselected.Textfont constructor must be a dict or an instance of plotly.graph_objs.barpolar.unselected.Textfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.barpolar.unselected import textfont as v_textfont # Initialize validators # --------------------- self._validators["color"] = v_textfont.ColorValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the marker color of unselected points, applied only when a selection exists. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # opacity # ------- @property def opacity(self): """ Sets the marker opacity of unselected points, applied only when a selection exists. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "barpolar.unselected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. """ def __init__(self, arg=None, color=None, opacity=None, **kwargs): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.barpolar.unselected.Marker color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.barpolar.unselected.Marker constructor must be a dict or an instance of plotly.graph_objs.barpolar.unselected.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.barpolar.unselected import marker as v_marker # Initialize validators # --------------------- self._validators["color"] = v_marker.ColorValidator() self._validators["opacity"] = v_marker.OpacityValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Marker", "Textfont"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/barpolar/hoverlabel/0000755000175000017500000000000013573746613023656 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/barpolar/hoverlabel/__init__.py0000644000175000017500000002544513573721545025776 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "barpolar.hoverlabel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Font object Sets the font used in hover labels. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.barpolar.hoverlabel.Font color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.barpolar.hoverlabel.Font constructor must be a dict or an instance of plotly.graph_objs.barpolar.hoverlabel.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.barpolar.hoverlabel import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["colorsrc"] = v_font.ColorsrcValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["familysrc"] = v_font.FamilysrcValidator() self._validators["size"] = v_font.SizeValidator() self._validators["sizesrc"] = v_font.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/barpolar/marker/0000755000175000017500000000000013573746613023014 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/barpolar/marker/colorbar/0000755000175000017500000000000013573746613024617 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/barpolar/marker/colorbar/title/0000755000175000017500000000000013573746613025740 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/barpolar/marker/colorbar/title/__init__.py0000644000175000017500000002057513573721545030057 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "barpolar.marker.colorbar.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.barpolar.marker.colorbar.title.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.barpolar.marker.colorbar.title.Font constructor must be a dict or an instance of plotly.graph_objs.barpolar.marker.colorbar.title.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.barpolar.marker.colorbar.title import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/barpolar/marker/colorbar/__init__.py0000644000175000017500000006077713573721546026747 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Title(_BaseTraceHierarchyType): # font # ---- @property def font(self): """ Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.barpolar.marker.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.barpolar.marker.colorbar.title.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # side # ---- @property def side(self): """ Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- Any """ return self["side"] @side.setter def side(self, val): self["side"] = val # text # ---- @property def text(self): """ Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "barpolar.marker.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """ def __init__(self, arg=None, font=None, side=None, text=None, **kwargs): """ Construct a new Title object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.barpolar.marker.colorbar.Title font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- Title """ super(Title, self).__init__("title") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.barpolar.marker.colorbar.Title constructor must be a dict or an instance of plotly.graph_objs.barpolar.marker.colorbar.Title""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.barpolar.marker.colorbar import title as v_title # Initialize validators # --------------------- self._validators["font"] = v_title.FontValidator() self._validators["side"] = v_title.SideValidator() self._validators["text"] = v_title.TextValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("side", None) self["side"] = side if side is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickformatstop(_BaseTraceHierarchyType): # dtickrange # ---------- @property def dtickrange(self): """ range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" The 'dtickrange' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'dtickrange[0]' property accepts values of any type (1) The 'dtickrange[1]' property accepts values of any type Returns ------- list """ return self["dtickrange"] @dtickrange.setter def dtickrange(self, val): self["dtickrange"] = val # enabled # ------- @property def enabled(self): """ Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. The 'enabled' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["enabled"] @enabled.setter def enabled(self, val): self["enabled"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # value # ----- @property def value(self): """ string - dtickformat for described zoom level, the same as "tickformat" The 'value' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "barpolar.marker.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """ def __init__( self, arg=None, dtickrange=None, enabled=None, name=None, templateitemname=None, value=None, **kwargs ): """ Construct a new Tickformatstop object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.barpolar.marker.colorb ar.Tickformatstop dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- Tickformatstop """ super(Tickformatstop, self).__init__("tickformatstops") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.barpolar.marker.colorbar.Tickformatstop constructor must be a dict or an instance of plotly.graph_objs.barpolar.marker.colorbar.Tickformatstop""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.barpolar.marker.colorbar import ( tickformatstop as v_tickformatstop, ) # Initialize validators # --------------------- self._validators["dtickrange"] = v_tickformatstop.DtickrangeValidator() self._validators["enabled"] = v_tickformatstop.EnabledValidator() self._validators["name"] = v_tickformatstop.NameValidator() self._validators[ "templateitemname" ] = v_tickformatstop.TemplateitemnameValidator() self._validators["value"] = v_tickformatstop.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtickrange", None) self["dtickrange"] = dtickrange if dtickrange is not None else _v _v = arg.pop("enabled", None) self["enabled"] = enabled if enabled is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "barpolar.marker.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Tickfont object Sets the color bar's tick label font Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.barpolar.marker.colorbar.Tickfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Tickfont """ super(Tickfont, self).__init__("tickfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.barpolar.marker.colorbar.Tickfont constructor must be a dict or an instance of plotly.graph_objs.barpolar.marker.colorbar.Tickfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.barpolar.marker.colorbar import tickfont as v_tickfont # Initialize validators # --------------------- self._validators["color"] = v_tickfont.ColorValidator() self._validators["family"] = v_tickfont.FamilyValidator() self._validators["size"] = v_tickfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Tickfont", "Tickformatstop", "Tickformatstop", "Title", "title"] from plotly.graph_objs.barpolar.marker.colorbar import title plotly-4.4.1+dfsg.orig/plotly/graph_objs/barpolar/marker/__init__.py0000644000175000017500000027044313573721546025135 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # autocolorscale # -------------- @property def autocolorscale(self): """ Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. The 'autocolorscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocolorscale"] @autocolorscale.setter def autocolorscale(self, val): self["autocolorscale"] = val # cauto # ----- @property def cauto(self): """ Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. The 'cauto' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["cauto"] @cauto.setter def cauto(self, val): self["cauto"] = val # cmax # ---- @property def cmax(self): """ Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. The 'cmax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmax"] @cmax.setter def cmax(self, val): self["cmax"] = val # cmid # ---- @property def cmid(self): """ Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. The 'cmid' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmid"] @cmid.setter def cmid(self, val): self["cmid"] = val # cmin # ---- @property def cmin(self): """ Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. The 'cmin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmin"] @cmin.setter def cmin(self, val): self["cmin"] = val # color # ----- @property def color(self): """ Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A number that will be interpreted as a color according to barpolar.marker.line.colorscale - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # coloraxis # --------- @property def coloraxis(self): """ Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. The 'coloraxis' property is an identifier of a particular subplot, of type 'coloraxis', that may be specified as the string 'coloraxis' optionally followed by an integer >= 1 (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) Returns ------- str """ return self["coloraxis"] @coloraxis.setter def coloraxis(self, val): self["coloraxis"] = val # colorscale # ---------- @property def colorscale(self): """ Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,Earth,Electric,Vi ridis,Cividis. The 'colorscale' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # reversescale # ------------ @property def reversescale(self): """ Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. The 'reversescale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["reversescale"] @reversescale.setter def reversescale(self, val): self["reversescale"] = val # width # ----- @property def width(self): """ Sets the width (in px) of the lines bounding the marker points. The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["width"] @width.setter def width(self, val): self["width"] = val # widthsrc # -------- @property def widthsrc(self): """ Sets the source reference on plot.ly for width . The 'widthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["widthsrc"] @widthsrc.setter def widthsrc(self, val): self["widthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "barpolar.marker" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . """ def __init__( self, arg=None, autocolorscale=None, cauto=None, cmax=None, cmid=None, cmin=None, color=None, coloraxis=None, colorscale=None, colorsrc=None, reversescale=None, width=None, widthsrc=None, **kwargs ): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.barpolar.marker.Line autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.barpolar.marker.Line constructor must be a dict or an instance of plotly.graph_objs.barpolar.marker.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.barpolar.marker import line as v_line # Initialize validators # --------------------- self._validators["autocolorscale"] = v_line.AutocolorscaleValidator() self._validators["cauto"] = v_line.CautoValidator() self._validators["cmax"] = v_line.CmaxValidator() self._validators["cmid"] = v_line.CmidValidator() self._validators["cmin"] = v_line.CminValidator() self._validators["color"] = v_line.ColorValidator() self._validators["coloraxis"] = v_line.ColoraxisValidator() self._validators["colorscale"] = v_line.ColorscaleValidator() self._validators["colorsrc"] = v_line.ColorsrcValidator() self._validators["reversescale"] = v_line.ReversescaleValidator() self._validators["width"] = v_line.WidthValidator() self._validators["widthsrc"] = v_line.WidthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autocolorscale", None) self["autocolorscale"] = autocolorscale if autocolorscale is not None else _v _v = arg.pop("cauto", None) self["cauto"] = cauto if cauto is not None else _v _v = arg.pop("cmax", None) self["cmax"] = cmax if cmax is not None else _v _v = arg.pop("cmid", None) self["cmid"] = cmid if cmid is not None else _v _v = arg.pop("cmin", None) self["cmin"] = cmin if cmin is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("coloraxis", None) self["coloraxis"] = coloraxis if coloraxis is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("reversescale", None) self["reversescale"] = reversescale if reversescale is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v _v = arg.pop("widthsrc", None) self["widthsrc"] = widthsrc if widthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class ColorBar(_BaseTraceHierarchyType): # bgcolor # ------- @property def bgcolor(self): """ Sets the color of padded area. The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the axis line color. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # borderwidth # ----------- @property def borderwidth(self): """ Sets the width (in px) or the border enclosing this color bar. The 'borderwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["borderwidth"] @borderwidth.setter def borderwidth(self, val): self["borderwidth"] = val # dtick # ----- @property def dtick(self): """ Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" The 'dtick' property accepts values of any type Returns ------- Any """ return self["dtick"] @dtick.setter def dtick(self, val): self["dtick"] = val # exponentformat # -------------- @property def exponentformat(self): """ Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. The 'exponentformat' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'e', 'E', 'power', 'SI', 'B'] Returns ------- Any """ return self["exponentformat"] @exponentformat.setter def exponentformat(self, val): self["exponentformat"] = val # len # --- @property def len(self): """ Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. The 'len' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["len"] @len.setter def len(self, val): self["len"] = val # lenmode # ------- @property def lenmode(self): """ Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. The 'lenmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["lenmode"] @lenmode.setter def lenmode(self, val): self["lenmode"] = val # nticks # ------ @property def nticks(self): """ Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". The 'nticks' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nticks"] @nticks.setter def nticks(self, val): self["nticks"] = val # outlinecolor # ------------ @property def outlinecolor(self): """ Sets the axis line color. The 'outlinecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["outlinecolor"] @outlinecolor.setter def outlinecolor(self, val): self["outlinecolor"] = val # outlinewidth # ------------ @property def outlinewidth(self): """ Sets the width (in px) of the axis line. The 'outlinewidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["outlinewidth"] @outlinewidth.setter def outlinewidth(self, val): self["outlinewidth"] = val # separatethousands # ----------------- @property def separatethousands(self): """ If "true", even 4-digit integers are separated The 'separatethousands' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["separatethousands"] @separatethousands.setter def separatethousands(self, val): self["separatethousands"] = val # showexponent # ------------ @property def showexponent(self): """ If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. The 'showexponent' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showexponent"] @showexponent.setter def showexponent(self, val): self["showexponent"] = val # showticklabels # -------------- @property def showticklabels(self): """ Determines whether or not the tick labels are drawn. The 'showticklabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showticklabels"] @showticklabels.setter def showticklabels(self, val): self["showticklabels"] = val # showtickprefix # -------------- @property def showtickprefix(self): """ If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. The 'showtickprefix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showtickprefix"] @showtickprefix.setter def showtickprefix(self, val): self["showtickprefix"] = val # showticksuffix # -------------- @property def showticksuffix(self): """ Same as `showtickprefix` but for tick suffixes. The 'showticksuffix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showticksuffix"] @showticksuffix.setter def showticksuffix(self, val): self["showticksuffix"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # thicknessmode # ------------- @property def thicknessmode(self): """ Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. The 'thicknessmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["thicknessmode"] @thicknessmode.setter def thicknessmode(self, val): self["thicknessmode"] = val # tick0 # ----- @property def tick0(self): """ Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. The 'tick0' property accepts values of any type Returns ------- Any """ return self["tick0"] @tick0.setter def tick0(self, val): self["tick0"] = val # tickangle # --------- @property def tickangle(self): """ Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. The 'tickangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["tickangle"] @tickangle.setter def tickangle(self, val): self["tickangle"] = val # tickcolor # --------- @property def tickcolor(self): """ Sets the tick color. The 'tickcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["tickcolor"] @tickcolor.setter def tickcolor(self, val): self["tickcolor"] = val # tickfont # -------- @property def tickfont(self): """ Sets the color bar's tick label font The 'tickfont' property is an instance of Tickfont that may be specified as: - An instance of plotly.graph_objs.barpolar.marker.colorbar.Tickfont - A dict of string/value properties that will be passed to the Tickfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.barpolar.marker.colorbar.Tickfont """ return self["tickfont"] @tickfont.setter def tickfont(self, val): self["tickfont"] = val # tickformat # ---------- @property def tickformat(self): """ Sets the tick label formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'tickformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickformat"] @tickformat.setter def tickformat(self, val): self["tickformat"] = val # tickformatstops # --------------- @property def tickformatstops(self): """ The 'tickformatstops' property is a tuple of instances of Tickformatstop that may be specified as: - A list or tuple of instances of plotly.graph_objs.barpolar.marker.colorbar.Tickformatstop - A list or tuple of dicts of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- tuple[plotly.graph_objs.barpolar.marker.colorbar.Tickformatstop] """ return self["tickformatstops"] @tickformatstops.setter def tickformatstops(self, val): self["tickformatstops"] = val # tickformatstopdefaults # ---------------------- @property def tickformatstopdefaults(self): """ When used in a template (as layout.template.data.barpolar.marke r.colorbar.tickformatstopdefaults), sets the default property values to use for elements of barpolar.marker.colorbar.tickformatstops The 'tickformatstopdefaults' property is an instance of Tickformatstop that may be specified as: - An instance of plotly.graph_objs.barpolar.marker.colorbar.Tickformatstop - A dict of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: Returns ------- plotly.graph_objs.barpolar.marker.colorbar.Tickformatstop """ return self["tickformatstopdefaults"] @tickformatstopdefaults.setter def tickformatstopdefaults(self, val): self["tickformatstopdefaults"] = val # ticklen # ------- @property def ticklen(self): """ Sets the tick length (in px). The 'ticklen' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ticklen"] @ticklen.setter def ticklen(self, val): self["ticklen"] = val # tickmode # -------- @property def tickmode(self): """ Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). The 'tickmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'linear', 'array'] Returns ------- Any """ return self["tickmode"] @tickmode.setter def tickmode(self, val): self["tickmode"] = val # tickprefix # ---------- @property def tickprefix(self): """ Sets a tick label prefix. The 'tickprefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickprefix"] @tickprefix.setter def tickprefix(self, val): self["tickprefix"] = val # ticks # ----- @property def ticks(self): """ Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. The 'ticks' property is an enumeration that may be specified as: - One of the following enumeration values: ['outside', 'inside', ''] Returns ------- Any """ return self["ticks"] @ticks.setter def ticks(self, val): self["ticks"] = val # ticksuffix # ---------- @property def ticksuffix(self): """ Sets a tick label suffix. The 'ticksuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ticksuffix"] @ticksuffix.setter def ticksuffix(self, val): self["ticksuffix"] = val # ticktext # -------- @property def ticktext(self): """ Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. The 'ticktext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ticktext"] @ticktext.setter def ticktext(self, val): self["ticktext"] = val # ticktextsrc # ----------- @property def ticktextsrc(self): """ Sets the source reference on plot.ly for ticktext . The 'ticktextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ticktextsrc"] @ticktextsrc.setter def ticktextsrc(self, val): self["ticktextsrc"] = val # tickvals # -------- @property def tickvals(self): """ Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. The 'tickvals' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["tickvals"] @tickvals.setter def tickvals(self, val): self["tickvals"] = val # tickvalssrc # ----------- @property def tickvalssrc(self): """ Sets the source reference on plot.ly for tickvals . The 'tickvalssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tickvalssrc"] @tickvalssrc.setter def tickvalssrc(self, val): self["tickvalssrc"] = val # tickwidth # --------- @property def tickwidth(self): """ Sets the tick width (in px). The 'tickwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["tickwidth"] @tickwidth.setter def tickwidth(self, val): self["tickwidth"] = val # title # ----- @property def title(self): """ The 'title' property is an instance of Title that may be specified as: - An instance of plotly.graph_objs.barpolar.marker.colorbar.Title - A dict of string/value properties that will be passed to the Title constructor Supported dict properties: font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- plotly.graph_objs.barpolar.marker.colorbar.Title """ return self["title"] @title.setter def title(self, val): self["title"] = val # titlefont # --------- @property def titlefont(self): """ Deprecated: Please use barpolar.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.barpolar.marker.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- """ return self["titlefont"] @titlefont.setter def titlefont(self, val): self["titlefont"] = val # titleside # --------- @property def titleside(self): """ Deprecated: Please use barpolar.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- """ return self["titleside"] @titleside.setter def titleside(self, val): self["titleside"] = val # x # - @property def x(self): """ Sets the x position of the color bar (in plot fraction). The 'x' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["x"] @x.setter def x(self, val): self["x"] = val # xanchor # ------- @property def xanchor(self): """ Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. The 'xanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'center', 'right'] Returns ------- Any """ return self["xanchor"] @xanchor.setter def xanchor(self, val): self["xanchor"] = val # xpad # ---- @property def xpad(self): """ Sets the amount of padding (in px) along the x direction. The 'xpad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["xpad"] @xpad.setter def xpad(self, val): self["xpad"] = val # y # - @property def y(self): """ Sets the y position of the color bar (in plot fraction). The 'y' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["y"] @y.setter def y(self, val): self["y"] = val # yanchor # ------- @property def yanchor(self): """ Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. The 'yanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['top', 'middle', 'bottom'] Returns ------- Any """ return self["yanchor"] @yanchor.setter def yanchor(self, val): self["yanchor"] = val # ypad # ---- @property def ypad(self): """ Sets the amount of padding (in px) along the y direction. The 'ypad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ypad"] @ypad.setter def ypad(self, val): self["ypad"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "barpolar.marker" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.barpolar.marker.colorba r.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.barpol ar.marker.colorbar.tickformatstopdefaults), sets the default property values to use for elements of barpolar.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.barpolar.marker.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use barpolar.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use barpolar.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """ _mapped_properties = { "titlefont": ("title", "font"), "titleside": ("title", "side"), } def __init__( self, arg=None, bgcolor=None, bordercolor=None, borderwidth=None, dtick=None, exponentformat=None, len=None, lenmode=None, nticks=None, outlinecolor=None, outlinewidth=None, separatethousands=None, showexponent=None, showticklabels=None, showtickprefix=None, showticksuffix=None, thickness=None, thicknessmode=None, tick0=None, tickangle=None, tickcolor=None, tickfont=None, tickformat=None, tickformatstops=None, tickformatstopdefaults=None, ticklen=None, tickmode=None, tickprefix=None, ticks=None, ticksuffix=None, ticktext=None, ticktextsrc=None, tickvals=None, tickvalssrc=None, tickwidth=None, title=None, titlefont=None, titleside=None, x=None, xanchor=None, xpad=None, y=None, yanchor=None, ypad=None, **kwargs ): """ Construct a new ColorBar object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.barpolar.marker.ColorBar bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.barpolar.marker.colorba r.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.barpol ar.marker.colorbar.tickformatstopdefaults), sets the default property values to use for elements of barpolar.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.barpolar.marker.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use barpolar.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use barpolar.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- ColorBar """ super(ColorBar, self).__init__("colorbar") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.barpolar.marker.ColorBar constructor must be a dict or an instance of plotly.graph_objs.barpolar.marker.ColorBar""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.barpolar.marker import colorbar as v_colorbar # Initialize validators # --------------------- self._validators["bgcolor"] = v_colorbar.BgcolorValidator() self._validators["bordercolor"] = v_colorbar.BordercolorValidator() self._validators["borderwidth"] = v_colorbar.BorderwidthValidator() self._validators["dtick"] = v_colorbar.DtickValidator() self._validators["exponentformat"] = v_colorbar.ExponentformatValidator() self._validators["len"] = v_colorbar.LenValidator() self._validators["lenmode"] = v_colorbar.LenmodeValidator() self._validators["nticks"] = v_colorbar.NticksValidator() self._validators["outlinecolor"] = v_colorbar.OutlinecolorValidator() self._validators["outlinewidth"] = v_colorbar.OutlinewidthValidator() self._validators["separatethousands"] = v_colorbar.SeparatethousandsValidator() self._validators["showexponent"] = v_colorbar.ShowexponentValidator() self._validators["showticklabels"] = v_colorbar.ShowticklabelsValidator() self._validators["showtickprefix"] = v_colorbar.ShowtickprefixValidator() self._validators["showticksuffix"] = v_colorbar.ShowticksuffixValidator() self._validators["thickness"] = v_colorbar.ThicknessValidator() self._validators["thicknessmode"] = v_colorbar.ThicknessmodeValidator() self._validators["tick0"] = v_colorbar.Tick0Validator() self._validators["tickangle"] = v_colorbar.TickangleValidator() self._validators["tickcolor"] = v_colorbar.TickcolorValidator() self._validators["tickfont"] = v_colorbar.TickfontValidator() self._validators["tickformat"] = v_colorbar.TickformatValidator() self._validators["tickformatstops"] = v_colorbar.TickformatstopsValidator() self._validators[ "tickformatstopdefaults" ] = v_colorbar.TickformatstopValidator() self._validators["ticklen"] = v_colorbar.TicklenValidator() self._validators["tickmode"] = v_colorbar.TickmodeValidator() self._validators["tickprefix"] = v_colorbar.TickprefixValidator() self._validators["ticks"] = v_colorbar.TicksValidator() self._validators["ticksuffix"] = v_colorbar.TicksuffixValidator() self._validators["ticktext"] = v_colorbar.TicktextValidator() self._validators["ticktextsrc"] = v_colorbar.TicktextsrcValidator() self._validators["tickvals"] = v_colorbar.TickvalsValidator() self._validators["tickvalssrc"] = v_colorbar.TickvalssrcValidator() self._validators["tickwidth"] = v_colorbar.TickwidthValidator() self._validators["title"] = v_colorbar.TitleValidator() self._validators["x"] = v_colorbar.XValidator() self._validators["xanchor"] = v_colorbar.XanchorValidator() self._validators["xpad"] = v_colorbar.XpadValidator() self._validators["y"] = v_colorbar.YValidator() self._validators["yanchor"] = v_colorbar.YanchorValidator() self._validators["ypad"] = v_colorbar.YpadValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("borderwidth", None) self["borderwidth"] = borderwidth if borderwidth is not None else _v _v = arg.pop("dtick", None) self["dtick"] = dtick if dtick is not None else _v _v = arg.pop("exponentformat", None) self["exponentformat"] = exponentformat if exponentformat is not None else _v _v = arg.pop("len", None) self["len"] = len if len is not None else _v _v = arg.pop("lenmode", None) self["lenmode"] = lenmode if lenmode is not None else _v _v = arg.pop("nticks", None) self["nticks"] = nticks if nticks is not None else _v _v = arg.pop("outlinecolor", None) self["outlinecolor"] = outlinecolor if outlinecolor is not None else _v _v = arg.pop("outlinewidth", None) self["outlinewidth"] = outlinewidth if outlinewidth is not None else _v _v = arg.pop("separatethousands", None) self["separatethousands"] = ( separatethousands if separatethousands is not None else _v ) _v = arg.pop("showexponent", None) self["showexponent"] = showexponent if showexponent is not None else _v _v = arg.pop("showticklabels", None) self["showticklabels"] = showticklabels if showticklabels is not None else _v _v = arg.pop("showtickprefix", None) self["showtickprefix"] = showtickprefix if showtickprefix is not None else _v _v = arg.pop("showticksuffix", None) self["showticksuffix"] = showticksuffix if showticksuffix is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("thicknessmode", None) self["thicknessmode"] = thicknessmode if thicknessmode is not None else _v _v = arg.pop("tick0", None) self["tick0"] = tick0 if tick0 is not None else _v _v = arg.pop("tickangle", None) self["tickangle"] = tickangle if tickangle is not None else _v _v = arg.pop("tickcolor", None) self["tickcolor"] = tickcolor if tickcolor is not None else _v _v = arg.pop("tickfont", None) self["tickfont"] = tickfont if tickfont is not None else _v _v = arg.pop("tickformat", None) self["tickformat"] = tickformat if tickformat is not None else _v _v = arg.pop("tickformatstops", None) self["tickformatstops"] = tickformatstops if tickformatstops is not None else _v _v = arg.pop("tickformatstopdefaults", None) self["tickformatstopdefaults"] = ( tickformatstopdefaults if tickformatstopdefaults is not None else _v ) _v = arg.pop("ticklen", None) self["ticklen"] = ticklen if ticklen is not None else _v _v = arg.pop("tickmode", None) self["tickmode"] = tickmode if tickmode is not None else _v _v = arg.pop("tickprefix", None) self["tickprefix"] = tickprefix if tickprefix is not None else _v _v = arg.pop("ticks", None) self["ticks"] = ticks if ticks is not None else _v _v = arg.pop("ticksuffix", None) self["ticksuffix"] = ticksuffix if ticksuffix is not None else _v _v = arg.pop("ticktext", None) self["ticktext"] = ticktext if ticktext is not None else _v _v = arg.pop("ticktextsrc", None) self["ticktextsrc"] = ticktextsrc if ticktextsrc is not None else _v _v = arg.pop("tickvals", None) self["tickvals"] = tickvals if tickvals is not None else _v _v = arg.pop("tickvalssrc", None) self["tickvalssrc"] = tickvalssrc if tickvalssrc is not None else _v _v = arg.pop("tickwidth", None) self["tickwidth"] = tickwidth if tickwidth is not None else _v _v = arg.pop("title", None) self["title"] = title if title is not None else _v _v = arg.pop("titlefont", None) _v = titlefont if titlefont is not None else _v if _v is not None: self["titlefont"] = _v _v = arg.pop("titleside", None) _v = titleside if titleside is not None else _v if _v is not None: self["titleside"] = _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xanchor", None) self["xanchor"] = xanchor if xanchor is not None else _v _v = arg.pop("xpad", None) self["xpad"] = xpad if xpad is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("yanchor", None) self["yanchor"] = yanchor if yanchor is not None else _v _v = arg.pop("ypad", None) self["ypad"] = ypad if ypad is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["ColorBar", "Line", "colorbar"] from plotly.graph_objs.barpolar.marker import colorbar plotly-4.4.1+dfsg.orig/plotly/graph_objs/barpolar/__init__.py0000644000175000017500000022107413573721546023650 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Unselected(_BaseTraceHierarchyType): # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.barpolar.unselected.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. Returns ------- plotly.graph_objs.barpolar.unselected.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # textfont # -------- @property def textfont(self): """ The 'textfont' property is an instance of Textfont that may be specified as: - An instance of plotly.graph_objs.barpolar.unselected.Textfont - A dict of string/value properties that will be passed to the Textfont constructor Supported dict properties: color Sets the text font color of unselected points, applied only when a selection exists. Returns ------- plotly.graph_objs.barpolar.unselected.Textfont """ return self["textfont"] @textfont.setter def textfont(self, val): self["textfont"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "barpolar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ marker plotly.graph_objects.barpolar.unselected.Marker instance or dict with compatible properties textfont plotly.graph_objects.barpolar.unselected.Textfont instance or dict with compatible properties """ def __init__(self, arg=None, marker=None, textfont=None, **kwargs): """ Construct a new Unselected object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.barpolar.Unselected marker plotly.graph_objects.barpolar.unselected.Marker instance or dict with compatible properties textfont plotly.graph_objects.barpolar.unselected.Textfont instance or dict with compatible properties Returns ------- Unselected """ super(Unselected, self).__init__("unselected") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.barpolar.Unselected constructor must be a dict or an instance of plotly.graph_objs.barpolar.Unselected""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.barpolar import unselected as v_unselected # Initialize validators # --------------------- self._validators["marker"] = v_unselected.MarkerValidator() self._validators["textfont"] = v_unselected.TextfontValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v _v = arg.pop("textfont", None) self["textfont"] = textfont if textfont is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Stream(_BaseTraceHierarchyType): # maxpoints # --------- @property def maxpoints(self): """ Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. The 'maxpoints' property is a number and may be specified as: - An int or float in the interval [0, 10000] Returns ------- int|float """ return self["maxpoints"] @maxpoints.setter def maxpoints(self, val): self["maxpoints"] = val # token # ----- @property def token(self): """ The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. The 'token' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["token"] @token.setter def token(self, val): self["token"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "barpolar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """ def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): """ Construct a new Stream object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.barpolar.Stream maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- Stream """ super(Stream, self).__init__("stream") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.barpolar.Stream constructor must be a dict or an instance of plotly.graph_objs.barpolar.Stream""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.barpolar import stream as v_stream # Initialize validators # --------------------- self._validators["maxpoints"] = v_stream.MaxpointsValidator() self._validators["token"] = v_stream.TokenValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("maxpoints", None) self["maxpoints"] = maxpoints if maxpoints is not None else _v _v = arg.pop("token", None) self["token"] = token if token is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Selected(_BaseTraceHierarchyType): # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.barpolar.selected.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. Returns ------- plotly.graph_objs.barpolar.selected.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # textfont # -------- @property def textfont(self): """ The 'textfont' property is an instance of Textfont that may be specified as: - An instance of plotly.graph_objs.barpolar.selected.Textfont - A dict of string/value properties that will be passed to the Textfont constructor Supported dict properties: color Sets the text font color of selected points. Returns ------- plotly.graph_objs.barpolar.selected.Textfont """ return self["textfont"] @textfont.setter def textfont(self, val): self["textfont"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "barpolar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ marker plotly.graph_objects.barpolar.selected.Marker instance or dict with compatible properties textfont plotly.graph_objects.barpolar.selected.Textfont instance or dict with compatible properties """ def __init__(self, arg=None, marker=None, textfont=None, **kwargs): """ Construct a new Selected object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.barpolar.Selected marker plotly.graph_objects.barpolar.selected.Marker instance or dict with compatible properties textfont plotly.graph_objects.barpolar.selected.Textfont instance or dict with compatible properties Returns ------- Selected """ super(Selected, self).__init__("selected") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.barpolar.Selected constructor must be a dict or an instance of plotly.graph_objs.barpolar.Selected""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.barpolar import selected as v_selected # Initialize validators # --------------------- self._validators["marker"] = v_selected.MarkerValidator() self._validators["textfont"] = v_selected.TextfontValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v _v = arg.pop("textfont", None) self["textfont"] = textfont if textfont is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # autocolorscale # -------------- @property def autocolorscale(self): """ Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. The 'autocolorscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocolorscale"] @autocolorscale.setter def autocolorscale(self, val): self["autocolorscale"] = val # cauto # ----- @property def cauto(self): """ Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. The 'cauto' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["cauto"] @cauto.setter def cauto(self, val): self["cauto"] = val # cmax # ---- @property def cmax(self): """ Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. The 'cmax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmax"] @cmax.setter def cmax(self, val): self["cmax"] = val # cmid # ---- @property def cmid(self): """ Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. The 'cmid' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmid"] @cmid.setter def cmid(self, val): self["cmid"] = val # cmin # ---- @property def cmin(self): """ Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. The 'cmin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmin"] @cmin.setter def cmin(self, val): self["cmin"] = val # color # ----- @property def color(self): """ Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A number that will be interpreted as a color according to barpolar.marker.colorscale - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # coloraxis # --------- @property def coloraxis(self): """ Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. The 'coloraxis' property is an identifier of a particular subplot, of type 'coloraxis', that may be specified as the string 'coloraxis' optionally followed by an integer >= 1 (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) Returns ------- str """ return self["coloraxis"] @coloraxis.setter def coloraxis(self, val): self["coloraxis"] = val # colorbar # -------- @property def colorbar(self): """ The 'colorbar' property is an instance of ColorBar that may be specified as: - An instance of plotly.graph_objs.barpolar.marker.ColorBar - A dict of string/value properties that will be passed to the ColorBar constructor Supported dict properties: bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.barpolar.marker .colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.barpolar.marker.colorbar.tickformatstopdefaul ts), sets the default property values to use for elements of barpolar.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.barpolar.marker.colorbar.T itle instance or dict with compatible properties titlefont Deprecated: Please use barpolar.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use barpolar.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- plotly.graph_objs.barpolar.marker.ColorBar """ return self["colorbar"] @colorbar.setter def colorbar(self, val): self["colorbar"] = val # colorscale # ---------- @property def colorscale(self): """ Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnB u,Greens,YlOrRd,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland ,Jet,Hot,Blackbody,Earth,Electric,Viridis,Cividis. The 'colorscale' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.barpolar.marker.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,R eds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Black body,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . Returns ------- plotly.graph_objs.barpolar.marker.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the bars. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # opacitysrc # ---------- @property def opacitysrc(self): """ Sets the source reference on plot.ly for opacity . The 'opacitysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["opacitysrc"] @opacitysrc.setter def opacitysrc(self, val): self["opacitysrc"] = val # reversescale # ------------ @property def reversescale(self): """ Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. The 'reversescale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["reversescale"] @reversescale.setter def reversescale(self, val): self["reversescale"] = val # showscale # --------- @property def showscale(self): """ Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. The 'showscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showscale"] @showscale.setter def showscale(self, val): self["showscale"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "barpolar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.barpolar.marker.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu ,Reds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . line plotly.graph_objects.barpolar.marker.Line instance or dict with compatible properties opacity Sets the opacity of the bars. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. """ def __init__( self, arg=None, autocolorscale=None, cauto=None, cmax=None, cmid=None, cmin=None, color=None, coloraxis=None, colorbar=None, colorscale=None, colorsrc=None, line=None, opacity=None, opacitysrc=None, reversescale=None, showscale=None, **kwargs ): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.barpolar.Marker autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.barpolar.marker.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu ,Reds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . line plotly.graph_objects.barpolar.marker.Line instance or dict with compatible properties opacity Sets the opacity of the bars. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.barpolar.Marker constructor must be a dict or an instance of plotly.graph_objs.barpolar.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.barpolar import marker as v_marker # Initialize validators # --------------------- self._validators["autocolorscale"] = v_marker.AutocolorscaleValidator() self._validators["cauto"] = v_marker.CautoValidator() self._validators["cmax"] = v_marker.CmaxValidator() self._validators["cmid"] = v_marker.CmidValidator() self._validators["cmin"] = v_marker.CminValidator() self._validators["color"] = v_marker.ColorValidator() self._validators["coloraxis"] = v_marker.ColoraxisValidator() self._validators["colorbar"] = v_marker.ColorBarValidator() self._validators["colorscale"] = v_marker.ColorscaleValidator() self._validators["colorsrc"] = v_marker.ColorsrcValidator() self._validators["line"] = v_marker.LineValidator() self._validators["opacity"] = v_marker.OpacityValidator() self._validators["opacitysrc"] = v_marker.OpacitysrcValidator() self._validators["reversescale"] = v_marker.ReversescaleValidator() self._validators["showscale"] = v_marker.ShowscaleValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autocolorscale", None) self["autocolorscale"] = autocolorscale if autocolorscale is not None else _v _v = arg.pop("cauto", None) self["cauto"] = cauto if cauto is not None else _v _v = arg.pop("cmax", None) self["cmax"] = cmax if cmax is not None else _v _v = arg.pop("cmid", None) self["cmid"] = cmid if cmid is not None else _v _v = arg.pop("cmin", None) self["cmin"] = cmin if cmin is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("coloraxis", None) self["coloraxis"] = coloraxis if coloraxis is not None else _v _v = arg.pop("colorbar", None) self["colorbar"] = colorbar if colorbar is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("opacitysrc", None) self["opacitysrc"] = opacitysrc if opacitysrc is not None else _v _v = arg.pop("reversescale", None) self["reversescale"] = reversescale if reversescale is not None else _v _v = arg.pop("showscale", None) self["showscale"] = showscale if showscale is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Hoverlabel(_BaseTraceHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'right', 'auto'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["align"] @align.setter def align(self, val): self["align"] = val # alignsrc # -------- @property def alignsrc(self): """ Sets the source reference on plot.ly for align . The 'alignsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["alignsrc"] @alignsrc.setter def alignsrc(self, val): self["alignsrc"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the hover labels for this trace The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bgcolorsrc # ---------- @property def bgcolorsrc(self): """ Sets the source reference on plot.ly for bgcolor . The 'bgcolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bgcolorsrc"] @bgcolorsrc.setter def bgcolorsrc(self, val): self["bgcolorsrc"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the border color of the hover labels for this trace. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # bordercolorsrc # -------------- @property def bordercolorsrc(self): """ Sets the source reference on plot.ly for bordercolor . The 'bordercolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bordercolorsrc"] @bordercolorsrc.setter def bordercolorsrc(self, val): self["bordercolorsrc"] = val # font # ---- @property def font(self): """ Sets the font used in hover labels. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.barpolar.hoverlabel.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.barpolar.hoverlabel.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # namelength # ---------- @property def namelength(self): """ Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. The 'namelength' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [-1, 9223372036854775807] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|numpy.ndarray """ return self["namelength"] @namelength.setter def namelength(self, val): self["namelength"] = val # namelengthsrc # ------------- @property def namelengthsrc(self): """ Sets the source reference on plot.ly for namelength . The 'namelengthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["namelengthsrc"] @namelengthsrc.setter def namelengthsrc(self, val): self["namelengthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "barpolar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """ def __init__( self, arg=None, align=None, alignsrc=None, bgcolor=None, bgcolorsrc=None, bordercolor=None, bordercolorsrc=None, font=None, namelength=None, namelengthsrc=None, **kwargs ): """ Construct a new Hoverlabel object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.barpolar.Hoverlabel align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- Hoverlabel """ super(Hoverlabel, self).__init__("hoverlabel") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.barpolar.Hoverlabel constructor must be a dict or an instance of plotly.graph_objs.barpolar.Hoverlabel""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.barpolar import hoverlabel as v_hoverlabel # Initialize validators # --------------------- self._validators["align"] = v_hoverlabel.AlignValidator() self._validators["alignsrc"] = v_hoverlabel.AlignsrcValidator() self._validators["bgcolor"] = v_hoverlabel.BgcolorValidator() self._validators["bgcolorsrc"] = v_hoverlabel.BgcolorsrcValidator() self._validators["bordercolor"] = v_hoverlabel.BordercolorValidator() self._validators["bordercolorsrc"] = v_hoverlabel.BordercolorsrcValidator() self._validators["font"] = v_hoverlabel.FontValidator() self._validators["namelength"] = v_hoverlabel.NamelengthValidator() self._validators["namelengthsrc"] = v_hoverlabel.NamelengthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("alignsrc", None) self["alignsrc"] = alignsrc if alignsrc is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bgcolorsrc", None) self["bgcolorsrc"] = bgcolorsrc if bgcolorsrc is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("bordercolorsrc", None) self["bordercolorsrc"] = bordercolorsrc if bordercolorsrc is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("namelength", None) self["namelength"] = namelength if namelength is not None else _v _v = arg.pop("namelengthsrc", None) self["namelengthsrc"] = namelengthsrc if namelengthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = [ "Hoverlabel", "Marker", "Selected", "Stream", "Unselected", "hoverlabel", "marker", "selected", "unselected", ] from plotly.graph_objs.barpolar import unselected from plotly.graph_objs.barpolar import selected from plotly.graph_objs.barpolar import marker from plotly.graph_objs.barpolar import hoverlabel plotly-4.4.1+dfsg.orig/plotly/graph_objs/barpolar/selected/0000755000175000017500000000000013573746613023323 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/barpolar/selected/__init__.py0000644000175000017500000002517013573721545025436 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Textfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the text font color of selected points. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "barpolar.selected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the text font color of selected points. """ def __init__(self, arg=None, color=None, **kwargs): """ Construct a new Textfont object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.barpolar.selected.Textfont color Sets the text font color of selected points. Returns ------- Textfont """ super(Textfont, self).__init__("textfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.barpolar.selected.Textfont constructor must be a dict or an instance of plotly.graph_objs.barpolar.selected.Textfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.barpolar.selected import textfont as v_textfont # Initialize validators # --------------------- self._validators["color"] = v_textfont.ColorValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the marker color of selected points. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # opacity # ------- @property def opacity(self): """ Sets the marker opacity of selected points. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "barpolar.selected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. """ def __init__(self, arg=None, color=None, opacity=None, **kwargs): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.barpolar.selected.Marker color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.barpolar.selected.Marker constructor must be a dict or an instance of plotly.graph_objs.barpolar.selected.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.barpolar.selected import marker as v_marker # Initialize validators # --------------------- self._validators["color"] = v_marker.ColorValidator() self._validators["opacity"] = v_marker.OpacityValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Marker", "Textfont"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/funnelarea/0000755000175000017500000000000013573746613022051 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/funnelarea/title/0000755000175000017500000000000013573746613023172 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/funnelarea/title/__init__.py0000644000175000017500000002554513573721546025314 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "funnelarea.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Font object Sets the font used for `title`. Note that the title's font used to be set by the now deprecated `titlefont` attribute. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.funnelarea.title.Font color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.funnelarea.title.Font constructor must be a dict or an instance of plotly.graph_objs.funnelarea.title.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.funnelarea.title import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["colorsrc"] = v_font.ColorsrcValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["familysrc"] = v_font.FamilysrcValidator() self._validators["size"] = v_font.SizeValidator() self._validators["sizesrc"] = v_font.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/funnelarea/hoverlabel/0000755000175000017500000000000013573746613024174 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/funnelarea/hoverlabel/__init__.py0000644000175000017500000002545713573721546026320 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "funnelarea.hoverlabel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Font object Sets the font used in hover labels. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.funnelarea.hoverlabel.Font color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.funnelarea.hoverlabel.Font constructor must be a dict or an instance of plotly.graph_objs.funnelarea.hoverlabel.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.funnelarea.hoverlabel import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["colorsrc"] = v_font.ColorsrcValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["familysrc"] = v_font.FamilysrcValidator() self._validators["size"] = v_font.SizeValidator() self._validators["sizesrc"] = v_font.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/funnelarea/marker/0000755000175000017500000000000013573746613023332 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/funnelarea/marker/__init__.py0000644000175000017500000001677013573721546025454 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the color of the line enclosing each sector. Defaults to the `paper_bgcolor` value. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # width # ----- @property def width(self): """ Sets the width (in px) of the line enclosing each sector. The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["width"] @width.setter def width(self, val): self["width"] = val # widthsrc # -------- @property def widthsrc(self): """ Sets the source reference on plot.ly for width . The 'widthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["widthsrc"] @widthsrc.setter def widthsrc(self, val): self["widthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "funnelarea.marker" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the color of the line enclosing each sector. Defaults to the `paper_bgcolor` value. colorsrc Sets the source reference on plot.ly for color . width Sets the width (in px) of the line enclosing each sector. widthsrc Sets the source reference on plot.ly for width . """ def __init__( self, arg=None, color=None, colorsrc=None, width=None, widthsrc=None, **kwargs ): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.funnelarea.marker.Line color Sets the color of the line enclosing each sector. Defaults to the `paper_bgcolor` value. colorsrc Sets the source reference on plot.ly for color . width Sets the width (in px) of the line enclosing each sector. widthsrc Sets the source reference on plot.ly for width . Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.funnelarea.marker.Line constructor must be a dict or an instance of plotly.graph_objs.funnelarea.marker.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.funnelarea.marker import line as v_line # Initialize validators # --------------------- self._validators["color"] = v_line.ColorValidator() self._validators["colorsrc"] = v_line.ColorsrcValidator() self._validators["width"] = v_line.WidthValidator() self._validators["widthsrc"] = v_line.WidthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v _v = arg.pop("widthsrc", None) self["widthsrc"] = widthsrc if widthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Line"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/funnelarea/__init__.py0000644000175000017500000017150013573721547024165 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Title(_BaseTraceHierarchyType): # font # ---- @property def font(self): """ Sets the font used for `title`. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.funnelarea.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.funnelarea.title.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # position # -------- @property def position(self): """ Specifies the location of the `title`. Note that the title's position used to be set by the now deprecated `titleposition` attribute. The 'position' property is an enumeration that may be specified as: - One of the following enumeration values: ['top left', 'top center', 'top right'] Returns ------- Any """ return self["position"] @position.setter def position(self, val): self["position"] = val # text # ---- @property def text(self): """ Sets the title of the chart. If it is empty, no title is displayed. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "funnelarea" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Sets the font used for `title`. Note that the title's font used to be set by the now deprecated `titlefont` attribute. position Specifies the location of the `title`. Note that the title's position used to be set by the now deprecated `titleposition` attribute. text Sets the title of the chart. If it is empty, no title is displayed. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """ def __init__(self, arg=None, font=None, position=None, text=None, **kwargs): """ Construct a new Title object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.funnelarea.Title font Sets the font used for `title`. Note that the title's font used to be set by the now deprecated `titlefont` attribute. position Specifies the location of the `title`. Note that the title's position used to be set by the now deprecated `titleposition` attribute. text Sets the title of the chart. If it is empty, no title is displayed. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- Title """ super(Title, self).__init__("title") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.funnelarea.Title constructor must be a dict or an instance of plotly.graph_objs.funnelarea.Title""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.funnelarea import title as v_title # Initialize validators # --------------------- self._validators["font"] = v_title.FontValidator() self._validators["position"] = v_title.PositionValidator() self._validators["text"] = v_title.TextValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("position", None) self["position"] = position if position is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Textfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "funnelarea" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Textfont object Sets the font used for `textinfo`. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.funnelarea.Textfont color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Textfont """ super(Textfont, self).__init__("textfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.funnelarea.Textfont constructor must be a dict or an instance of plotly.graph_objs.funnelarea.Textfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.funnelarea import textfont as v_textfont # Initialize validators # --------------------- self._validators["color"] = v_textfont.ColorValidator() self._validators["colorsrc"] = v_textfont.ColorsrcValidator() self._validators["family"] = v_textfont.FamilyValidator() self._validators["familysrc"] = v_textfont.FamilysrcValidator() self._validators["size"] = v_textfont.SizeValidator() self._validators["sizesrc"] = v_textfont.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Stream(_BaseTraceHierarchyType): # maxpoints # --------- @property def maxpoints(self): """ Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. The 'maxpoints' property is a number and may be specified as: - An int or float in the interval [0, 10000] Returns ------- int|float """ return self["maxpoints"] @maxpoints.setter def maxpoints(self, val): self["maxpoints"] = val # token # ----- @property def token(self): """ The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. The 'token' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["token"] @token.setter def token(self, val): self["token"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "funnelarea" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """ def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): """ Construct a new Stream object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.funnelarea.Stream maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- Stream """ super(Stream, self).__init__("stream") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.funnelarea.Stream constructor must be a dict or an instance of plotly.graph_objs.funnelarea.Stream""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.funnelarea import stream as v_stream # Initialize validators # --------------------- self._validators["maxpoints"] = v_stream.MaxpointsValidator() self._validators["token"] = v_stream.TokenValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("maxpoints", None) self["maxpoints"] = maxpoints if maxpoints is not None else _v _v = arg.pop("token", None) self["token"] = token if token is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # colors # ------ @property def colors(self): """ Sets the color of each sector. If not specified, the default trace color set is used to pick the sector colors. The 'colors' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["colors"] @colors.setter def colors(self, val): self["colors"] = val # colorssrc # --------- @property def colorssrc(self): """ Sets the source reference on plot.ly for colors . The 'colorssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorssrc"] @colorssrc.setter def colorssrc(self, val): self["colorssrc"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.funnelarea.marker.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: color Sets the color of the line enclosing each sector. Defaults to the `paper_bgcolor` value. colorsrc Sets the source reference on plot.ly for color . width Sets the width (in px) of the line enclosing each sector. widthsrc Sets the source reference on plot.ly for width . Returns ------- plotly.graph_objs.funnelarea.marker.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "funnelarea" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ colors Sets the color of each sector. If not specified, the default trace color set is used to pick the sector colors. colorssrc Sets the source reference on plot.ly for colors . line plotly.graph_objects.funnelarea.marker.Line instance or dict with compatible properties """ def __init__(self, arg=None, colors=None, colorssrc=None, line=None, **kwargs): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.funnelarea.Marker colors Sets the color of each sector. If not specified, the default trace color set is used to pick the sector colors. colorssrc Sets the source reference on plot.ly for colors . line plotly.graph_objects.funnelarea.marker.Line instance or dict with compatible properties Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.funnelarea.Marker constructor must be a dict or an instance of plotly.graph_objs.funnelarea.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.funnelarea import marker as v_marker # Initialize validators # --------------------- self._validators["colors"] = v_marker.ColorsValidator() self._validators["colorssrc"] = v_marker.ColorssrcValidator() self._validators["line"] = v_marker.LineValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("colors", None) self["colors"] = colors if colors is not None else _v _v = arg.pop("colorssrc", None) self["colorssrc"] = colorssrc if colorssrc is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Insidetextfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "funnelarea" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Insidetextfont object Sets the font used for `textinfo` lying inside the sector. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.funnelarea.Insidetextfont color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Insidetextfont """ super(Insidetextfont, self).__init__("insidetextfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.funnelarea.Insidetextfont constructor must be a dict or an instance of plotly.graph_objs.funnelarea.Insidetextfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.funnelarea import insidetextfont as v_insidetextfont # Initialize validators # --------------------- self._validators["color"] = v_insidetextfont.ColorValidator() self._validators["colorsrc"] = v_insidetextfont.ColorsrcValidator() self._validators["family"] = v_insidetextfont.FamilyValidator() self._validators["familysrc"] = v_insidetextfont.FamilysrcValidator() self._validators["size"] = v_insidetextfont.SizeValidator() self._validators["sizesrc"] = v_insidetextfont.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Hoverlabel(_BaseTraceHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'right', 'auto'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["align"] @align.setter def align(self, val): self["align"] = val # alignsrc # -------- @property def alignsrc(self): """ Sets the source reference on plot.ly for align . The 'alignsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["alignsrc"] @alignsrc.setter def alignsrc(self, val): self["alignsrc"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the hover labels for this trace The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bgcolorsrc # ---------- @property def bgcolorsrc(self): """ Sets the source reference on plot.ly for bgcolor . The 'bgcolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bgcolorsrc"] @bgcolorsrc.setter def bgcolorsrc(self, val): self["bgcolorsrc"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the border color of the hover labels for this trace. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # bordercolorsrc # -------------- @property def bordercolorsrc(self): """ Sets the source reference on plot.ly for bordercolor . The 'bordercolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bordercolorsrc"] @bordercolorsrc.setter def bordercolorsrc(self, val): self["bordercolorsrc"] = val # font # ---- @property def font(self): """ Sets the font used in hover labels. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.funnelarea.hoverlabel.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.funnelarea.hoverlabel.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # namelength # ---------- @property def namelength(self): """ Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. The 'namelength' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [-1, 9223372036854775807] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|numpy.ndarray """ return self["namelength"] @namelength.setter def namelength(self, val): self["namelength"] = val # namelengthsrc # ------------- @property def namelengthsrc(self): """ Sets the source reference on plot.ly for namelength . The 'namelengthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["namelengthsrc"] @namelengthsrc.setter def namelengthsrc(self, val): self["namelengthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "funnelarea" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """ def __init__( self, arg=None, align=None, alignsrc=None, bgcolor=None, bgcolorsrc=None, bordercolor=None, bordercolorsrc=None, font=None, namelength=None, namelengthsrc=None, **kwargs ): """ Construct a new Hoverlabel object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.funnelarea.Hoverlabel align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- Hoverlabel """ super(Hoverlabel, self).__init__("hoverlabel") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.funnelarea.Hoverlabel constructor must be a dict or an instance of plotly.graph_objs.funnelarea.Hoverlabel""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.funnelarea import hoverlabel as v_hoverlabel # Initialize validators # --------------------- self._validators["align"] = v_hoverlabel.AlignValidator() self._validators["alignsrc"] = v_hoverlabel.AlignsrcValidator() self._validators["bgcolor"] = v_hoverlabel.BgcolorValidator() self._validators["bgcolorsrc"] = v_hoverlabel.BgcolorsrcValidator() self._validators["bordercolor"] = v_hoverlabel.BordercolorValidator() self._validators["bordercolorsrc"] = v_hoverlabel.BordercolorsrcValidator() self._validators["font"] = v_hoverlabel.FontValidator() self._validators["namelength"] = v_hoverlabel.NamelengthValidator() self._validators["namelengthsrc"] = v_hoverlabel.NamelengthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("alignsrc", None) self["alignsrc"] = alignsrc if alignsrc is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bgcolorsrc", None) self["bgcolorsrc"] = bgcolorsrc if bgcolorsrc is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("bordercolorsrc", None) self["bordercolorsrc"] = bordercolorsrc if bordercolorsrc is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("namelength", None) self["namelength"] = namelength if namelength is not None else _v _v = arg.pop("namelengthsrc", None) self["namelengthsrc"] = namelengthsrc if namelengthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Domain(_BaseTraceHierarchyType): # column # ------ @property def column(self): """ If there is a layout grid, use the domain for this column in the grid for this funnelarea trace . The 'column' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["column"] @column.setter def column(self, val): self["column"] = val # row # --- @property def row(self): """ If there is a layout grid, use the domain for this row in the grid for this funnelarea trace . The 'row' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["row"] @row.setter def row(self, val): self["row"] = val # x # - @property def x(self): """ Sets the horizontal domain of this funnelarea trace (in plot fraction). The 'x' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'x[0]' property is a number and may be specified as: - An int or float in the interval [0, 1] (1) The 'x[1]' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- list """ return self["x"] @x.setter def x(self, val): self["x"] = val # y # - @property def y(self): """ Sets the vertical domain of this funnelarea trace (in plot fraction). The 'y' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'y[0]' property is a number and may be specified as: - An int or float in the interval [0, 1] (1) The 'y[1]' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- list """ return self["y"] @y.setter def y(self, val): self["y"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "funnelarea" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ column If there is a layout grid, use the domain for this column in the grid for this funnelarea trace . row If there is a layout grid, use the domain for this row in the grid for this funnelarea trace . x Sets the horizontal domain of this funnelarea trace (in plot fraction). y Sets the vertical domain of this funnelarea trace (in plot fraction). """ def __init__(self, arg=None, column=None, row=None, x=None, y=None, **kwargs): """ Construct a new Domain object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.funnelarea.Domain column If there is a layout grid, use the domain for this column in the grid for this funnelarea trace . row If there is a layout grid, use the domain for this row in the grid for this funnelarea trace . x Sets the horizontal domain of this funnelarea trace (in plot fraction). y Sets the vertical domain of this funnelarea trace (in plot fraction). Returns ------- Domain """ super(Domain, self).__init__("domain") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.funnelarea.Domain constructor must be a dict or an instance of plotly.graph_objs.funnelarea.Domain""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.funnelarea import domain as v_domain # Initialize validators # --------------------- self._validators["column"] = v_domain.ColumnValidator() self._validators["row"] = v_domain.RowValidator() self._validators["x"] = v_domain.XValidator() self._validators["y"] = v_domain.YValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("column", None) self["column"] = column if column is not None else _v _v = arg.pop("row", None) self["row"] = row if row is not None else _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = [ "Domain", "Hoverlabel", "Insidetextfont", "Marker", "Stream", "Textfont", "Title", "hoverlabel", "marker", "title", ] from plotly.graph_objs.funnelarea import title from plotly.graph_objs.funnelarea import marker from plotly.graph_objs.funnelarea import hoverlabel plotly-4.4.1+dfsg.orig/plotly/graph_objs/waterfall/0000755000175000017500000000000013573746613021712 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/waterfall/increasing/0000755000175000017500000000000013573746613024034 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/waterfall/increasing/marker/0000755000175000017500000000000013573746613025315 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/waterfall/increasing/marker/__init__.py0000644000175000017500000001326413573721553027430 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the line color of all increasing values. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # width # ----- @property def width(self): """ Sets the line width of all increasing values. The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "waterfall.increasing.marker" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the line color of all increasing values. width Sets the line width of all increasing values. """ def __init__(self, arg=None, color=None, width=None, **kwargs): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.waterfall.increasing.marker.Line color Sets the line color of all increasing values. width Sets the line width of all increasing values. Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.waterfall.increasing.marker.Line constructor must be a dict or an instance of plotly.graph_objs.waterfall.increasing.marker.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.waterfall.increasing.marker import line as v_line # Initialize validators # --------------------- self._validators["color"] = v_line.ColorValidator() self._validators["width"] = v_line.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Line"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/waterfall/increasing/__init__.py0000644000175000017500000001432313573721553026144 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the marker color of all increasing values. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.waterfall.increasing.marker.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: color Sets the line color of all increasing values. width Sets the line width of all increasing values. Returns ------- plotly.graph_objs.waterfall.increasing.marker.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "waterfall.increasing" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the marker color of all increasing values. line plotly.graph_objects.waterfall.increasing.marker.Line instance or dict with compatible properties """ def __init__(self, arg=None, color=None, line=None, **kwargs): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.waterfall.increasing.Marker color Sets the marker color of all increasing values. line plotly.graph_objects.waterfall.increasing.marker.Line instance or dict with compatible properties Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.waterfall.increasing.Marker constructor must be a dict or an instance of plotly.graph_objs.waterfall.increasing.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.waterfall.increasing import marker as v_marker # Initialize validators # --------------------- self._validators["color"] = v_marker.ColorValidator() self._validators["line"] = v_marker.LineValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Marker", "marker"] from plotly.graph_objs.waterfall.increasing import marker plotly-4.4.1+dfsg.orig/plotly/graph_objs/waterfall/connector/0000755000175000017500000000000013573746613023704 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/waterfall/connector/__init__.py0000644000175000017500000001547513573721553026025 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the line color. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # dash # ---- @property def dash(self): """ Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). The 'dash' property is a string and must be specified as: - One of the following strings: ['solid', 'dot', 'dash', 'longdash', 'dashdot', 'longdashdot'] - A number that will be converted to a string Returns ------- str """ return self["dash"] @dash.setter def dash(self, val): self["dash"] = val # width # ----- @property def width(self): """ Sets the line width (in px). The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "waterfall.connector" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the line color. dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). width Sets the line width (in px). """ def __init__(self, arg=None, color=None, dash=None, width=None, **kwargs): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.waterfall.connector.Line color Sets the line color. dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). width Sets the line width (in px). Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.waterfall.connector.Line constructor must be a dict or an instance of plotly.graph_objs.waterfall.connector.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.waterfall.connector import line as v_line # Initialize validators # --------------------- self._validators["color"] = v_line.ColorValidator() self._validators["dash"] = v_line.DashValidator() self._validators["width"] = v_line.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("dash", None) self["dash"] = dash if dash is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Line"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/waterfall/hoverlabel/0000755000175000017500000000000013573746613024035 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/waterfall/hoverlabel/__init__.py0000644000175000017500000002545213573721553026152 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "waterfall.hoverlabel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Font object Sets the font used in hover labels. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.waterfall.hoverlabel.Font color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.waterfall.hoverlabel.Font constructor must be a dict or an instance of plotly.graph_objs.waterfall.hoverlabel.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.waterfall.hoverlabel import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["colorsrc"] = v_font.ColorsrcValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["familysrc"] = v_font.FamilysrcValidator() self._validators["size"] = v_font.SizeValidator() self._validators["sizesrc"] = v_font.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/waterfall/totals/0000755000175000017500000000000013573746613023220 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/waterfall/totals/marker/0000755000175000017500000000000013573746613024501 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/waterfall/totals/marker/__init__.py0000644000175000017500000001346613573721553026620 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the line color of all intermediate sums and total values. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # width # ----- @property def width(self): """ Sets the line width of all intermediate sums and total values. The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "waterfall.totals.marker" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the line color of all intermediate sums and total values. width Sets the line width of all intermediate sums and total values. """ def __init__(self, arg=None, color=None, width=None, **kwargs): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.waterfall.totals.marker.Line color Sets the line color of all intermediate sums and total values. width Sets the line width of all intermediate sums and total values. Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.waterfall.totals.marker.Line constructor must be a dict or an instance of plotly.graph_objs.waterfall.totals.marker.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.waterfall.totals.marker import line as v_line # Initialize validators # --------------------- self._validators["color"] = v_line.ColorValidator() self._validators["width"] = v_line.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Line"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/waterfall/totals/__init__.py0000644000175000017500000001451013573721553025326 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the marker color of all intermediate sums and total values. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.waterfall.totals.marker.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: color Sets the line color of all intermediate sums and total values. width Sets the line width of all intermediate sums and total values. Returns ------- plotly.graph_objs.waterfall.totals.marker.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "waterfall.totals" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the marker color of all intermediate sums and total values. line plotly.graph_objects.waterfall.totals.marker.Line instance or dict with compatible properties """ def __init__(self, arg=None, color=None, line=None, **kwargs): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.waterfall.totals.Marker color Sets the marker color of all intermediate sums and total values. line plotly.graph_objects.waterfall.totals.marker.Line instance or dict with compatible properties Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.waterfall.totals.Marker constructor must be a dict or an instance of plotly.graph_objs.waterfall.totals.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.waterfall.totals import marker as v_marker # Initialize validators # --------------------- self._validators["color"] = v_marker.ColorValidator() self._validators["line"] = v_marker.LineValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Marker", "marker"] from plotly.graph_objs.waterfall.totals import marker plotly-4.4.1+dfsg.orig/plotly/graph_objs/waterfall/__init__.py0000644000175000017500000021066213573721553024026 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Totals(_BaseTraceHierarchyType): # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.waterfall.totals.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: color Sets the marker color of all intermediate sums and total values. line plotly.graph_objects.waterfall.totals.marker.Li ne instance or dict with compatible properties Returns ------- plotly.graph_objs.waterfall.totals.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "waterfall" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ marker plotly.graph_objects.waterfall.totals.Marker instance or dict with compatible properties """ def __init__(self, arg=None, marker=None, **kwargs): """ Construct a new Totals object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.waterfall.Totals marker plotly.graph_objects.waterfall.totals.Marker instance or dict with compatible properties Returns ------- Totals """ super(Totals, self).__init__("totals") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.waterfall.Totals constructor must be a dict or an instance of plotly.graph_objs.waterfall.Totals""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.waterfall import totals as v_totals # Initialize validators # --------------------- self._validators["marker"] = v_totals.MarkerValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Textfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "waterfall" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Textfont object Sets the font used for `text`. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.waterfall.Textfont color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Textfont """ super(Textfont, self).__init__("textfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.waterfall.Textfont constructor must be a dict or an instance of plotly.graph_objs.waterfall.Textfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.waterfall import textfont as v_textfont # Initialize validators # --------------------- self._validators["color"] = v_textfont.ColorValidator() self._validators["colorsrc"] = v_textfont.ColorsrcValidator() self._validators["family"] = v_textfont.FamilyValidator() self._validators["familysrc"] = v_textfont.FamilysrcValidator() self._validators["size"] = v_textfont.SizeValidator() self._validators["sizesrc"] = v_textfont.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Stream(_BaseTraceHierarchyType): # maxpoints # --------- @property def maxpoints(self): """ Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. The 'maxpoints' property is a number and may be specified as: - An int or float in the interval [0, 10000] Returns ------- int|float """ return self["maxpoints"] @maxpoints.setter def maxpoints(self, val): self["maxpoints"] = val # token # ----- @property def token(self): """ The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. The 'token' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["token"] @token.setter def token(self, val): self["token"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "waterfall" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """ def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): """ Construct a new Stream object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.waterfall.Stream maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- Stream """ super(Stream, self).__init__("stream") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.waterfall.Stream constructor must be a dict or an instance of plotly.graph_objs.waterfall.Stream""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.waterfall import stream as v_stream # Initialize validators # --------------------- self._validators["maxpoints"] = v_stream.MaxpointsValidator() self._validators["token"] = v_stream.TokenValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("maxpoints", None) self["maxpoints"] = maxpoints if maxpoints is not None else _v _v = arg.pop("token", None) self["token"] = token if token is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Outsidetextfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "waterfall" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Outsidetextfont object Sets the font used for `text` lying outside the bar. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.waterfall.Outsidetextfont color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Outsidetextfont """ super(Outsidetextfont, self).__init__("outsidetextfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.waterfall.Outsidetextfont constructor must be a dict or an instance of plotly.graph_objs.waterfall.Outsidetextfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.waterfall import outsidetextfont as v_outsidetextfont # Initialize validators # --------------------- self._validators["color"] = v_outsidetextfont.ColorValidator() self._validators["colorsrc"] = v_outsidetextfont.ColorsrcValidator() self._validators["family"] = v_outsidetextfont.FamilyValidator() self._validators["familysrc"] = v_outsidetextfont.FamilysrcValidator() self._validators["size"] = v_outsidetextfont.SizeValidator() self._validators["sizesrc"] = v_outsidetextfont.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Insidetextfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "waterfall" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Insidetextfont object Sets the font used for `text` lying inside the bar. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.waterfall.Insidetextfont color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Insidetextfont """ super(Insidetextfont, self).__init__("insidetextfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.waterfall.Insidetextfont constructor must be a dict or an instance of plotly.graph_objs.waterfall.Insidetextfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.waterfall import insidetextfont as v_insidetextfont # Initialize validators # --------------------- self._validators["color"] = v_insidetextfont.ColorValidator() self._validators["colorsrc"] = v_insidetextfont.ColorsrcValidator() self._validators["family"] = v_insidetextfont.FamilyValidator() self._validators["familysrc"] = v_insidetextfont.FamilysrcValidator() self._validators["size"] = v_insidetextfont.SizeValidator() self._validators["sizesrc"] = v_insidetextfont.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Increasing(_BaseTraceHierarchyType): # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.waterfall.increasing.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: color Sets the marker color of all increasing values. line plotly.graph_objects.waterfall.increasing.marke r.Line instance or dict with compatible properties Returns ------- plotly.graph_objs.waterfall.increasing.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "waterfall" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ marker plotly.graph_objects.waterfall.increasing.Marker instance or dict with compatible properties """ def __init__(self, arg=None, marker=None, **kwargs): """ Construct a new Increasing object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.waterfall.Increasing marker plotly.graph_objects.waterfall.increasing.Marker instance or dict with compatible properties Returns ------- Increasing """ super(Increasing, self).__init__("increasing") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.waterfall.Increasing constructor must be a dict or an instance of plotly.graph_objs.waterfall.Increasing""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.waterfall import increasing as v_increasing # Initialize validators # --------------------- self._validators["marker"] = v_increasing.MarkerValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Hoverlabel(_BaseTraceHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'right', 'auto'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["align"] @align.setter def align(self, val): self["align"] = val # alignsrc # -------- @property def alignsrc(self): """ Sets the source reference on plot.ly for align . The 'alignsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["alignsrc"] @alignsrc.setter def alignsrc(self, val): self["alignsrc"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the hover labels for this trace The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bgcolorsrc # ---------- @property def bgcolorsrc(self): """ Sets the source reference on plot.ly for bgcolor . The 'bgcolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bgcolorsrc"] @bgcolorsrc.setter def bgcolorsrc(self, val): self["bgcolorsrc"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the border color of the hover labels for this trace. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # bordercolorsrc # -------------- @property def bordercolorsrc(self): """ Sets the source reference on plot.ly for bordercolor . The 'bordercolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bordercolorsrc"] @bordercolorsrc.setter def bordercolorsrc(self, val): self["bordercolorsrc"] = val # font # ---- @property def font(self): """ Sets the font used in hover labels. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.waterfall.hoverlabel.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.waterfall.hoverlabel.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # namelength # ---------- @property def namelength(self): """ Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. The 'namelength' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [-1, 9223372036854775807] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|numpy.ndarray """ return self["namelength"] @namelength.setter def namelength(self, val): self["namelength"] = val # namelengthsrc # ------------- @property def namelengthsrc(self): """ Sets the source reference on plot.ly for namelength . The 'namelengthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["namelengthsrc"] @namelengthsrc.setter def namelengthsrc(self, val): self["namelengthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "waterfall" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """ def __init__( self, arg=None, align=None, alignsrc=None, bgcolor=None, bgcolorsrc=None, bordercolor=None, bordercolorsrc=None, font=None, namelength=None, namelengthsrc=None, **kwargs ): """ Construct a new Hoverlabel object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.waterfall.Hoverlabel align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- Hoverlabel """ super(Hoverlabel, self).__init__("hoverlabel") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.waterfall.Hoverlabel constructor must be a dict or an instance of plotly.graph_objs.waterfall.Hoverlabel""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.waterfall import hoverlabel as v_hoverlabel # Initialize validators # --------------------- self._validators["align"] = v_hoverlabel.AlignValidator() self._validators["alignsrc"] = v_hoverlabel.AlignsrcValidator() self._validators["bgcolor"] = v_hoverlabel.BgcolorValidator() self._validators["bgcolorsrc"] = v_hoverlabel.BgcolorsrcValidator() self._validators["bordercolor"] = v_hoverlabel.BordercolorValidator() self._validators["bordercolorsrc"] = v_hoverlabel.BordercolorsrcValidator() self._validators["font"] = v_hoverlabel.FontValidator() self._validators["namelength"] = v_hoverlabel.NamelengthValidator() self._validators["namelengthsrc"] = v_hoverlabel.NamelengthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("alignsrc", None) self["alignsrc"] = alignsrc if alignsrc is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bgcolorsrc", None) self["bgcolorsrc"] = bgcolorsrc if bgcolorsrc is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("bordercolorsrc", None) self["bordercolorsrc"] = bordercolorsrc if bordercolorsrc is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("namelength", None) self["namelength"] = namelength if namelength is not None else _v _v = arg.pop("namelengthsrc", None) self["namelengthsrc"] = namelengthsrc if namelengthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Decreasing(_BaseTraceHierarchyType): # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.waterfall.decreasing.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: color Sets the marker color of all decreasing values. line plotly.graph_objects.waterfall.decreasing.marke r.Line instance or dict with compatible properties Returns ------- plotly.graph_objs.waterfall.decreasing.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "waterfall" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ marker plotly.graph_objects.waterfall.decreasing.Marker instance or dict with compatible properties """ def __init__(self, arg=None, marker=None, **kwargs): """ Construct a new Decreasing object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.waterfall.Decreasing marker plotly.graph_objects.waterfall.decreasing.Marker instance or dict with compatible properties Returns ------- Decreasing """ super(Decreasing, self).__init__("decreasing") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.waterfall.Decreasing constructor must be a dict or an instance of plotly.graph_objs.waterfall.Decreasing""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.waterfall import decreasing as v_decreasing # Initialize validators # --------------------- self._validators["marker"] = v_decreasing.MarkerValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Connector(_BaseTraceHierarchyType): # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.waterfall.connector.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: color Sets the line color. dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). width Sets the line width (in px). Returns ------- plotly.graph_objs.waterfall.connector.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # mode # ---- @property def mode(self): """ Sets the shape of connector lines. The 'mode' property is an enumeration that may be specified as: - One of the following enumeration values: ['spanning', 'between'] Returns ------- Any """ return self["mode"] @mode.setter def mode(self, val): self["mode"] = val # visible # ------- @property def visible(self): """ Determines if connector lines are drawn. The 'visible' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "waterfall" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ line plotly.graph_objects.waterfall.connector.Line instance or dict with compatible properties mode Sets the shape of connector lines. visible Determines if connector lines are drawn. """ def __init__(self, arg=None, line=None, mode=None, visible=None, **kwargs): """ Construct a new Connector object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.waterfall.Connector line plotly.graph_objects.waterfall.connector.Line instance or dict with compatible properties mode Sets the shape of connector lines. visible Determines if connector lines are drawn. Returns ------- Connector """ super(Connector, self).__init__("connector") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.waterfall.Connector constructor must be a dict or an instance of plotly.graph_objs.waterfall.Connector""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.waterfall import connector as v_connector # Initialize validators # --------------------- self._validators["line"] = v_connector.LineValidator() self._validators["mode"] = v_connector.ModeValidator() self._validators["visible"] = v_connector.VisibleValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("line", None) self["line"] = line if line is not None else _v _v = arg.pop("mode", None) self["mode"] = mode if mode is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = [ "Connector", "Decreasing", "Hoverlabel", "Increasing", "Insidetextfont", "Outsidetextfont", "Stream", "Textfont", "Totals", "connector", "decreasing", "hoverlabel", "increasing", "totals", ] from plotly.graph_objs.waterfall import totals from plotly.graph_objs.waterfall import increasing from plotly.graph_objs.waterfall import hoverlabel from plotly.graph_objs.waterfall import decreasing from plotly.graph_objs.waterfall import connector plotly-4.4.1+dfsg.orig/plotly/graph_objs/waterfall/decreasing/0000755000175000017500000000000013573746613024016 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/waterfall/decreasing/marker/0000755000175000017500000000000013573746613025277 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/waterfall/decreasing/marker/__init__.py0000644000175000017500000001326413573721553027412 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the line color of all decreasing values. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # width # ----- @property def width(self): """ Sets the line width of all decreasing values. The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "waterfall.decreasing.marker" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the line color of all decreasing values. width Sets the line width of all decreasing values. """ def __init__(self, arg=None, color=None, width=None, **kwargs): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.waterfall.decreasing.marker.Line color Sets the line color of all decreasing values. width Sets the line width of all decreasing values. Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.waterfall.decreasing.marker.Line constructor must be a dict or an instance of plotly.graph_objs.waterfall.decreasing.marker.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.waterfall.decreasing.marker import line as v_line # Initialize validators # --------------------- self._validators["color"] = v_line.ColorValidator() self._validators["width"] = v_line.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Line"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/waterfall/decreasing/__init__.py0000644000175000017500000001432313573721553026126 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the marker color of all decreasing values. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.waterfall.decreasing.marker.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: color Sets the line color of all decreasing values. width Sets the line width of all decreasing values. Returns ------- plotly.graph_objs.waterfall.decreasing.marker.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "waterfall.decreasing" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the marker color of all decreasing values. line plotly.graph_objects.waterfall.decreasing.marker.Line instance or dict with compatible properties """ def __init__(self, arg=None, color=None, line=None, **kwargs): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.waterfall.decreasing.Marker color Sets the marker color of all decreasing values. line plotly.graph_objects.waterfall.decreasing.marker.Line instance or dict with compatible properties Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.waterfall.decreasing.Marker constructor must be a dict or an instance of plotly.graph_objs.waterfall.decreasing.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.waterfall.decreasing import marker as v_marker # Initialize validators # --------------------- self._validators["color"] = v_marker.ColorValidator() self._validators["line"] = v_marker.LineValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Marker", "marker"] from plotly.graph_objs.waterfall.decreasing import marker plotly-4.4.1+dfsg.orig/plotly/graph_objs/sankey/0000755000175000017500000000000013573746613021223 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/sankey/link/0000755000175000017500000000000013573746613022160 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/sankey/link/hoverlabel/0000755000175000017500000000000013573746613024303 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/sankey/link/hoverlabel/__init__.py0000644000175000017500000002546413573721550026420 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "sankey.link.hoverlabel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Font object Sets the font used in hover labels. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.sankey.link.hoverlabel.Font color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.sankey.link.hoverlabel.Font constructor must be a dict or an instance of plotly.graph_objs.sankey.link.hoverlabel.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.sankey.link.hoverlabel import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["colorsrc"] = v_font.ColorsrcValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["familysrc"] = v_font.FamilysrcValidator() self._validators["size"] = v_font.SizeValidator() self._validators["sizesrc"] = v_font.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/sankey/link/__init__.py0000644000175000017500000011253713573721550024273 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the color of the `line` around each `link`. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # width # ----- @property def width(self): """ Sets the width (in px) of the `line` around each `link`. The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["width"] @width.setter def width(self, val): self["width"] = val # widthsrc # -------- @property def widthsrc(self): """ Sets the source reference on plot.ly for width . The 'widthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["widthsrc"] @widthsrc.setter def widthsrc(self, val): self["widthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "sankey.link" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the color of the `line` around each `link`. colorsrc Sets the source reference on plot.ly for color . width Sets the width (in px) of the `line` around each `link`. widthsrc Sets the source reference on plot.ly for width . """ def __init__( self, arg=None, color=None, colorsrc=None, width=None, widthsrc=None, **kwargs ): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.sankey.link.Line color Sets the color of the `line` around each `link`. colorsrc Sets the source reference on plot.ly for color . width Sets the width (in px) of the `line` around each `link`. widthsrc Sets the source reference on plot.ly for width . Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.sankey.link.Line constructor must be a dict or an instance of plotly.graph_objs.sankey.link.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.sankey.link import line as v_line # Initialize validators # --------------------- self._validators["color"] = v_line.ColorValidator() self._validators["colorsrc"] = v_line.ColorsrcValidator() self._validators["width"] = v_line.WidthValidator() self._validators["widthsrc"] = v_line.WidthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v _v = arg.pop("widthsrc", None) self["widthsrc"] = widthsrc if widthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Hoverlabel(_BaseTraceHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'right', 'auto'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["align"] @align.setter def align(self, val): self["align"] = val # alignsrc # -------- @property def alignsrc(self): """ Sets the source reference on plot.ly for align . The 'alignsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["alignsrc"] @alignsrc.setter def alignsrc(self, val): self["alignsrc"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the hover labels for this trace The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bgcolorsrc # ---------- @property def bgcolorsrc(self): """ Sets the source reference on plot.ly for bgcolor . The 'bgcolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bgcolorsrc"] @bgcolorsrc.setter def bgcolorsrc(self, val): self["bgcolorsrc"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the border color of the hover labels for this trace. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # bordercolorsrc # -------------- @property def bordercolorsrc(self): """ Sets the source reference on plot.ly for bordercolor . The 'bordercolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bordercolorsrc"] @bordercolorsrc.setter def bordercolorsrc(self, val): self["bordercolorsrc"] = val # font # ---- @property def font(self): """ Sets the font used in hover labels. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.sankey.link.hoverlabel.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.sankey.link.hoverlabel.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # namelength # ---------- @property def namelength(self): """ Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. The 'namelength' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [-1, 9223372036854775807] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|numpy.ndarray """ return self["namelength"] @namelength.setter def namelength(self, val): self["namelength"] = val # namelengthsrc # ------------- @property def namelengthsrc(self): """ Sets the source reference on plot.ly for namelength . The 'namelengthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["namelengthsrc"] @namelengthsrc.setter def namelengthsrc(self, val): self["namelengthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "sankey.link" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """ def __init__( self, arg=None, align=None, alignsrc=None, bgcolor=None, bgcolorsrc=None, bordercolor=None, bordercolorsrc=None, font=None, namelength=None, namelengthsrc=None, **kwargs ): """ Construct a new Hoverlabel object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.sankey.link.Hoverlabel align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- Hoverlabel """ super(Hoverlabel, self).__init__("hoverlabel") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.sankey.link.Hoverlabel constructor must be a dict or an instance of plotly.graph_objs.sankey.link.Hoverlabel""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.sankey.link import hoverlabel as v_hoverlabel # Initialize validators # --------------------- self._validators["align"] = v_hoverlabel.AlignValidator() self._validators["alignsrc"] = v_hoverlabel.AlignsrcValidator() self._validators["bgcolor"] = v_hoverlabel.BgcolorValidator() self._validators["bgcolorsrc"] = v_hoverlabel.BgcolorsrcValidator() self._validators["bordercolor"] = v_hoverlabel.BordercolorValidator() self._validators["bordercolorsrc"] = v_hoverlabel.BordercolorsrcValidator() self._validators["font"] = v_hoverlabel.FontValidator() self._validators["namelength"] = v_hoverlabel.NamelengthValidator() self._validators["namelengthsrc"] = v_hoverlabel.NamelengthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("alignsrc", None) self["alignsrc"] = alignsrc if alignsrc is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bgcolorsrc", None) self["bgcolorsrc"] = bgcolorsrc if bgcolorsrc is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("bordercolorsrc", None) self["bordercolorsrc"] = bordercolorsrc if bordercolorsrc is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("namelength", None) self["namelength"] = namelength if namelength is not None else _v _v = arg.pop("namelengthsrc", None) self["namelengthsrc"] = namelengthsrc if namelengthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Colorscale(_BaseTraceHierarchyType): # cmax # ---- @property def cmax(self): """ Sets the upper bound of the color domain. The 'cmax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmax"] @cmax.setter def cmax(self, val): self["cmax"] = val # cmin # ---- @property def cmin(self): """ Sets the lower bound of the color domain. The 'cmin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmin"] @cmin.setter def cmin(self, val): self["cmin"] = val # colorscale # ---------- @property def colorscale(self): """ Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`cmin` and `cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,Earth,Electric,Vi ridis,Cividis. The 'colorscale' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # label # ----- @property def label(self): """ The label of the links to color based on their concentration within a flow. The 'label' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["label"] @label.setter def label(self, val): self["label"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "sankey.link" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ cmax Sets the upper bound of the color domain. cmin Sets the lower bound of the color domain. colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`cmin` and `cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. label The label of the links to color based on their concentration within a flow. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. """ def __init__( self, arg=None, cmax=None, cmin=None, colorscale=None, label=None, name=None, templateitemname=None, **kwargs ): """ Construct a new Colorscale object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.sankey.link.Colorscale cmax Sets the upper bound of the color domain. cmin Sets the lower bound of the color domain. colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`cmin` and `cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. label The label of the links to color based on their concentration within a flow. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. Returns ------- Colorscale """ super(Colorscale, self).__init__("colorscales") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.sankey.link.Colorscale constructor must be a dict or an instance of plotly.graph_objs.sankey.link.Colorscale""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.sankey.link import colorscale as v_colorscale # Initialize validators # --------------------- self._validators["cmax"] = v_colorscale.CmaxValidator() self._validators["cmin"] = v_colorscale.CminValidator() self._validators["colorscale"] = v_colorscale.ColorscaleValidator() self._validators["label"] = v_colorscale.LabelValidator() self._validators["name"] = v_colorscale.NameValidator() self._validators["templateitemname"] = v_colorscale.TemplateitemnameValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("cmax", None) self["cmax"] = cmax if cmax is not None else _v _v = arg.pop("cmin", None) self["cmin"] = cmin if cmin is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("label", None) self["label"] = label if label is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Colorscale", "Colorscale", "Hoverlabel", "Line", "hoverlabel"] from plotly.graph_objs.sankey.link import hoverlabel plotly-4.4.1+dfsg.orig/plotly/graph_objs/sankey/hoverlabel/0000755000175000017500000000000013573746613023346 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/sankey/hoverlabel/__init__.py0000644000175000017500000002541713573721550025461 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "sankey.hoverlabel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Font object Sets the font used in hover labels. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.sankey.hoverlabel.Font color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.sankey.hoverlabel.Font constructor must be a dict or an instance of plotly.graph_objs.sankey.hoverlabel.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.sankey.hoverlabel import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["colorsrc"] = v_font.ColorsrcValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["familysrc"] = v_font.FamilysrcValidator() self._validators["size"] = v_font.SizeValidator() self._validators["sizesrc"] = v_font.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/sankey/__init__.py0000644000175000017500000026101413573721551023332 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Textfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "sankey" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Textfont object Sets the font for node labels Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.sankey.Textfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Textfont """ super(Textfont, self).__init__("textfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.sankey.Textfont constructor must be a dict or an instance of plotly.graph_objs.sankey.Textfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.sankey import textfont as v_textfont # Initialize validators # --------------------- self._validators["color"] = v_textfont.ColorValidator() self._validators["family"] = v_textfont.FamilyValidator() self._validators["size"] = v_textfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Stream(_BaseTraceHierarchyType): # maxpoints # --------- @property def maxpoints(self): """ Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. The 'maxpoints' property is a number and may be specified as: - An int or float in the interval [0, 10000] Returns ------- int|float """ return self["maxpoints"] @maxpoints.setter def maxpoints(self, val): self["maxpoints"] = val # token # ----- @property def token(self): """ The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. The 'token' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["token"] @token.setter def token(self, val): self["token"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "sankey" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """ def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): """ Construct a new Stream object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.sankey.Stream maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- Stream """ super(Stream, self).__init__("stream") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.sankey.Stream constructor must be a dict or an instance of plotly.graph_objs.sankey.Stream""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.sankey import stream as v_stream # Initialize validators # --------------------- self._validators["maxpoints"] = v_stream.MaxpointsValidator() self._validators["token"] = v_stream.TokenValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("maxpoints", None) self["maxpoints"] = maxpoints if maxpoints is not None else _v _v = arg.pop("token", None) self["token"] = token if token is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Node(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the `node` color. It can be a single value, or an array for specifying color for each `node`. If `node.color` is omitted, then the default `Plotly` color palette will be cycled through to have a variety of colors. These defaults are not fully opaque, to allow some visibility of what is beneath the node. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # groups # ------ @property def groups(self): """ Groups of nodes. Each group is defined by an array with the indices of the nodes it contains. Multiple groups can be specified. The 'groups' property is an info array that may be specified as: * a 2D list where: The 'groups[i][j]' property is a number and may be specified as: - An int or float Returns ------- list """ return self["groups"] @groups.setter def groups(self, val): self["groups"] = val # hoverinfo # --------- @property def hoverinfo(self): """ Determines which trace information appear when hovering nodes. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. The 'hoverinfo' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'none', 'skip'] Returns ------- Any """ return self["hoverinfo"] @hoverinfo.setter def hoverinfo(self, val): self["hoverinfo"] = val # hoverlabel # ---------- @property def hoverlabel(self): """ The 'hoverlabel' property is an instance of Hoverlabel that may be specified as: - An instance of plotly.graph_objs.sankey.node.Hoverlabel - A dict of string/value properties that will be passed to the Hoverlabel constructor Supported dict properties: align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- plotly.graph_objs.sankey.node.Hoverlabel """ return self["hoverlabel"] @hoverlabel.setter def hoverlabel(self, val): self["hoverlabel"] = val # hovertemplate # ------------- @property def hovertemplate(self): """ Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event- data. Additionally, every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. variables `value` and `label`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. The 'hovertemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertemplate"] @hovertemplate.setter def hovertemplate(self, val): self["hovertemplate"] = val # hovertemplatesrc # ---------------- @property def hovertemplatesrc(self): """ Sets the source reference on plot.ly for hovertemplate . The 'hovertemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertemplatesrc"] @hovertemplatesrc.setter def hovertemplatesrc(self, val): self["hovertemplatesrc"] = val # label # ----- @property def label(self): """ The shown name of the node. The 'label' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["label"] @label.setter def label(self, val): self["label"] = val # labelsrc # -------- @property def labelsrc(self): """ Sets the source reference on plot.ly for label . The 'labelsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["labelsrc"] @labelsrc.setter def labelsrc(self, val): self["labelsrc"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.sankey.node.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: color Sets the color of the `line` around each `node`. colorsrc Sets the source reference on plot.ly for color . width Sets the width (in px) of the `line` around each `node`. widthsrc Sets the source reference on plot.ly for width . Returns ------- plotly.graph_objs.sankey.node.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # pad # --- @property def pad(self): """ Sets the padding (in px) between the `nodes`. The 'pad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["pad"] @pad.setter def pad(self, val): self["pad"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness (in px) of the `nodes`. The 'thickness' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # x # - @property def x(self): """ The normalized horizontal position of the node. The 'x' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["x"] @x.setter def x(self, val): self["x"] = val # xsrc # ---- @property def xsrc(self): """ Sets the source reference on plot.ly for x . The 'xsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["xsrc"] @xsrc.setter def xsrc(self, val): self["xsrc"] = val # y # - @property def y(self): """ The normalized vertical position of the node. The 'y' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["y"] @y.setter def y(self, val): self["y"] = val # ysrc # ---- @property def ysrc(self): """ Sets the source reference on plot.ly for y . The 'ysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ysrc"] @ysrc.setter def ysrc(self, val): self["ysrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "sankey" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the `node` color. It can be a single value, or an array for specifying color for each `node`. If `node.color` is omitted, then the default `Plotly` color palette will be cycled through to have a variety of colors. These defaults are not fully opaque, to allow some visibility of what is beneath the node. colorsrc Sets the source reference on plot.ly for color . groups Groups of nodes. Each group is defined by an array with the indices of the nodes it contains. Multiple groups can be specified. hoverinfo Determines which trace information appear when hovering nodes. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverlabel plotly.graph_objects.sankey.node.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `value` and `label`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . label The shown name of the node. labelsrc Sets the source reference on plot.ly for label . line plotly.graph_objects.sankey.node.Line instance or dict with compatible properties pad Sets the padding (in px) between the `nodes`. thickness Sets the thickness (in px) of the `nodes`. x The normalized horizontal position of the node. xsrc Sets the source reference on plot.ly for x . y The normalized vertical position of the node. ysrc Sets the source reference on plot.ly for y . """ def __init__( self, arg=None, color=None, colorsrc=None, groups=None, hoverinfo=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, label=None, labelsrc=None, line=None, pad=None, thickness=None, x=None, xsrc=None, y=None, ysrc=None, **kwargs ): """ Construct a new Node object The nodes of the Sankey plot. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.sankey.Node color Sets the `node` color. It can be a single value, or an array for specifying color for each `node`. If `node.color` is omitted, then the default `Plotly` color palette will be cycled through to have a variety of colors. These defaults are not fully opaque, to allow some visibility of what is beneath the node. colorsrc Sets the source reference on plot.ly for color . groups Groups of nodes. Each group is defined by an array with the indices of the nodes it contains. Multiple groups can be specified. hoverinfo Determines which trace information appear when hovering nodes. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverlabel plotly.graph_objects.sankey.node.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `value` and `label`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . label The shown name of the node. labelsrc Sets the source reference on plot.ly for label . line plotly.graph_objects.sankey.node.Line instance or dict with compatible properties pad Sets the padding (in px) between the `nodes`. thickness Sets the thickness (in px) of the `nodes`. x The normalized horizontal position of the node. xsrc Sets the source reference on plot.ly for x . y The normalized vertical position of the node. ysrc Sets the source reference on plot.ly for y . Returns ------- Node """ super(Node, self).__init__("node") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.sankey.Node constructor must be a dict or an instance of plotly.graph_objs.sankey.Node""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.sankey import node as v_node # Initialize validators # --------------------- self._validators["color"] = v_node.ColorValidator() self._validators["colorsrc"] = v_node.ColorsrcValidator() self._validators["groups"] = v_node.GroupsValidator() self._validators["hoverinfo"] = v_node.HoverinfoValidator() self._validators["hoverlabel"] = v_node.HoverlabelValidator() self._validators["hovertemplate"] = v_node.HovertemplateValidator() self._validators["hovertemplatesrc"] = v_node.HovertemplatesrcValidator() self._validators["label"] = v_node.LabelValidator() self._validators["labelsrc"] = v_node.LabelsrcValidator() self._validators["line"] = v_node.LineValidator() self._validators["pad"] = v_node.PadValidator() self._validators["thickness"] = v_node.ThicknessValidator() self._validators["x"] = v_node.XValidator() self._validators["xsrc"] = v_node.XsrcValidator() self._validators["y"] = v_node.YValidator() self._validators["ysrc"] = v_node.YsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("groups", None) self["groups"] = groups if groups is not None else _v _v = arg.pop("hoverinfo", None) self["hoverinfo"] = hoverinfo if hoverinfo is not None else _v _v = arg.pop("hoverlabel", None) self["hoverlabel"] = hoverlabel if hoverlabel is not None else _v _v = arg.pop("hovertemplate", None) self["hovertemplate"] = hovertemplate if hovertemplate is not None else _v _v = arg.pop("hovertemplatesrc", None) self["hovertemplatesrc"] = ( hovertemplatesrc if hovertemplatesrc is not None else _v ) _v = arg.pop("label", None) self["label"] = label if label is not None else _v _v = arg.pop("labelsrc", None) self["labelsrc"] = labelsrc if labelsrc is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v _v = arg.pop("pad", None) self["pad"] = pad if pad is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xsrc", None) self["xsrc"] = xsrc if xsrc is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("ysrc", None) self["ysrc"] = ysrc if ysrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Link(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the `link` color. It can be a single value, or an array for specifying color for each `link`. If `link.color` is omitted, then by default, a translucent grey link will be used. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorscales # ----------- @property def colorscales(self): """ The 'colorscales' property is a tuple of instances of Colorscale that may be specified as: - A list or tuple of instances of plotly.graph_objs.sankey.link.Colorscale - A list or tuple of dicts of string/value properties that will be passed to the Colorscale constructor Supported dict properties: cmax Sets the upper bound of the color domain. cmin Sets the lower bound of the color domain. colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`cmin` and `cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Grey s,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Blues, Picnic,Rainbow,Portland,Jet,Hot,Blackbody,Earth ,Electric,Viridis,Cividis. label The label of the links to color based on their concentration within a flow. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. Returns ------- tuple[plotly.graph_objs.sankey.link.Colorscale] """ return self["colorscales"] @colorscales.setter def colorscales(self, val): self["colorscales"] = val # colorscaledefaults # ------------------ @property def colorscaledefaults(self): """ When used in a template (as layout.template.data.sankey.link.colorscaledefaults), sets the default property values to use for elements of sankey.link.colorscales The 'colorscaledefaults' property is an instance of Colorscale that may be specified as: - An instance of plotly.graph_objs.sankey.link.Colorscale - A dict of string/value properties that will be passed to the Colorscale constructor Supported dict properties: Returns ------- plotly.graph_objs.sankey.link.Colorscale """ return self["colorscaledefaults"] @colorscaledefaults.setter def colorscaledefaults(self, val): self["colorscaledefaults"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # hoverinfo # --------- @property def hoverinfo(self): """ Determines which trace information appear when hovering links. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. The 'hoverinfo' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'none', 'skip'] Returns ------- Any """ return self["hoverinfo"] @hoverinfo.setter def hoverinfo(self, val): self["hoverinfo"] = val # hoverlabel # ---------- @property def hoverlabel(self): """ The 'hoverlabel' property is an instance of Hoverlabel that may be specified as: - An instance of plotly.graph_objs.sankey.link.Hoverlabel - A dict of string/value properties that will be passed to the Hoverlabel constructor Supported dict properties: align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- plotly.graph_objs.sankey.link.Hoverlabel """ return self["hoverlabel"] @hoverlabel.setter def hoverlabel(self, val): self["hoverlabel"] = val # hovertemplate # ------------- @property def hovertemplate(self): """ Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event- data. Additionally, every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. variables `value` and `label`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. The 'hovertemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertemplate"] @hovertemplate.setter def hovertemplate(self, val): self["hovertemplate"] = val # hovertemplatesrc # ---------------- @property def hovertemplatesrc(self): """ Sets the source reference on plot.ly for hovertemplate . The 'hovertemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertemplatesrc"] @hovertemplatesrc.setter def hovertemplatesrc(self, val): self["hovertemplatesrc"] = val # label # ----- @property def label(self): """ The shown name of the link. The 'label' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["label"] @label.setter def label(self, val): self["label"] = val # labelsrc # -------- @property def labelsrc(self): """ Sets the source reference on plot.ly for label . The 'labelsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["labelsrc"] @labelsrc.setter def labelsrc(self, val): self["labelsrc"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.sankey.link.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: color Sets the color of the `line` around each `link`. colorsrc Sets the source reference on plot.ly for color . width Sets the width (in px) of the `line` around each `link`. widthsrc Sets the source reference on plot.ly for width . Returns ------- plotly.graph_objs.sankey.link.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # source # ------ @property def source(self): """ An integer number `[0..nodes.length - 1]` that represents the source node. The 'source' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["source"] @source.setter def source(self, val): self["source"] = val # sourcesrc # --------- @property def sourcesrc(self): """ Sets the source reference on plot.ly for source . The 'sourcesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sourcesrc"] @sourcesrc.setter def sourcesrc(self, val): self["sourcesrc"] = val # target # ------ @property def target(self): """ An integer number `[0..nodes.length - 1]` that represents the target node. The 'target' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["target"] @target.setter def target(self, val): self["target"] = val # targetsrc # --------- @property def targetsrc(self): """ Sets the source reference on plot.ly for target . The 'targetsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["targetsrc"] @targetsrc.setter def targetsrc(self, val): self["targetsrc"] = val # value # ----- @property def value(self): """ A numeric value representing the flow volume value. The 'value' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["value"] @value.setter def value(self, val): self["value"] = val # valuesrc # -------- @property def valuesrc(self): """ Sets the source reference on plot.ly for value . The 'valuesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["valuesrc"] @valuesrc.setter def valuesrc(self, val): self["valuesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "sankey" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the `link` color. It can be a single value, or an array for specifying color for each `link`. If `link.color` is omitted, then by default, a translucent grey link will be used. colorscales A tuple of plotly.graph_objects.sankey.link.Colorscale instances or dicts with compatible properties colorscaledefaults When used in a template (as layout.template.data.sankey.link.colorscaledefaults), sets the default property values to use for elements of sankey.link.colorscales colorsrc Sets the source reference on plot.ly for color . hoverinfo Determines which trace information appear when hovering links. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverlabel plotly.graph_objects.sankey.link.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `value` and `label`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . label The shown name of the link. labelsrc Sets the source reference on plot.ly for label . line plotly.graph_objects.sankey.link.Line instance or dict with compatible properties source An integer number `[0..nodes.length - 1]` that represents the source node. sourcesrc Sets the source reference on plot.ly for source . target An integer number `[0..nodes.length - 1]` that represents the target node. targetsrc Sets the source reference on plot.ly for target . value A numeric value representing the flow volume value. valuesrc Sets the source reference on plot.ly for value . """ def __init__( self, arg=None, color=None, colorscales=None, colorscaledefaults=None, colorsrc=None, hoverinfo=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, label=None, labelsrc=None, line=None, source=None, sourcesrc=None, target=None, targetsrc=None, value=None, valuesrc=None, **kwargs ): """ Construct a new Link object The links of the Sankey plot. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.sankey.Link color Sets the `link` color. It can be a single value, or an array for specifying color for each `link`. If `link.color` is omitted, then by default, a translucent grey link will be used. colorscales A tuple of plotly.graph_objects.sankey.link.Colorscale instances or dicts with compatible properties colorscaledefaults When used in a template (as layout.template.data.sankey.link.colorscaledefaults), sets the default property values to use for elements of sankey.link.colorscales colorsrc Sets the source reference on plot.ly for color . hoverinfo Determines which trace information appear when hovering links. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverlabel plotly.graph_objects.sankey.link.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `value` and `label`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . label The shown name of the link. labelsrc Sets the source reference on plot.ly for label . line plotly.graph_objects.sankey.link.Line instance or dict with compatible properties source An integer number `[0..nodes.length - 1]` that represents the source node. sourcesrc Sets the source reference on plot.ly for source . target An integer number `[0..nodes.length - 1]` that represents the target node. targetsrc Sets the source reference on plot.ly for target . value A numeric value representing the flow volume value. valuesrc Sets the source reference on plot.ly for value . Returns ------- Link """ super(Link, self).__init__("link") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.sankey.Link constructor must be a dict or an instance of plotly.graph_objs.sankey.Link""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.sankey import link as v_link # Initialize validators # --------------------- self._validators["color"] = v_link.ColorValidator() self._validators["colorscales"] = v_link.ColorscalesValidator() self._validators["colorscaledefaults"] = v_link.ColorscaleValidator() self._validators["colorsrc"] = v_link.ColorsrcValidator() self._validators["hoverinfo"] = v_link.HoverinfoValidator() self._validators["hoverlabel"] = v_link.HoverlabelValidator() self._validators["hovertemplate"] = v_link.HovertemplateValidator() self._validators["hovertemplatesrc"] = v_link.HovertemplatesrcValidator() self._validators["label"] = v_link.LabelValidator() self._validators["labelsrc"] = v_link.LabelsrcValidator() self._validators["line"] = v_link.LineValidator() self._validators["source"] = v_link.SourceValidator() self._validators["sourcesrc"] = v_link.SourcesrcValidator() self._validators["target"] = v_link.TargetValidator() self._validators["targetsrc"] = v_link.TargetsrcValidator() self._validators["value"] = v_link.ValueValidator() self._validators["valuesrc"] = v_link.ValuesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorscales", None) self["colorscales"] = colorscales if colorscales is not None else _v _v = arg.pop("colorscaledefaults", None) self["colorscaledefaults"] = ( colorscaledefaults if colorscaledefaults is not None else _v ) _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("hoverinfo", None) self["hoverinfo"] = hoverinfo if hoverinfo is not None else _v _v = arg.pop("hoverlabel", None) self["hoverlabel"] = hoverlabel if hoverlabel is not None else _v _v = arg.pop("hovertemplate", None) self["hovertemplate"] = hovertemplate if hovertemplate is not None else _v _v = arg.pop("hovertemplatesrc", None) self["hovertemplatesrc"] = ( hovertemplatesrc if hovertemplatesrc is not None else _v ) _v = arg.pop("label", None) self["label"] = label if label is not None else _v _v = arg.pop("labelsrc", None) self["labelsrc"] = labelsrc if labelsrc is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v _v = arg.pop("source", None) self["source"] = source if source is not None else _v _v = arg.pop("sourcesrc", None) self["sourcesrc"] = sourcesrc if sourcesrc is not None else _v _v = arg.pop("target", None) self["target"] = target if target is not None else _v _v = arg.pop("targetsrc", None) self["targetsrc"] = targetsrc if targetsrc is not None else _v _v = arg.pop("value", None) self["value"] = value if value is not None else _v _v = arg.pop("valuesrc", None) self["valuesrc"] = valuesrc if valuesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Hoverlabel(_BaseTraceHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'right', 'auto'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["align"] @align.setter def align(self, val): self["align"] = val # alignsrc # -------- @property def alignsrc(self): """ Sets the source reference on plot.ly for align . The 'alignsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["alignsrc"] @alignsrc.setter def alignsrc(self, val): self["alignsrc"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the hover labels for this trace The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bgcolorsrc # ---------- @property def bgcolorsrc(self): """ Sets the source reference on plot.ly for bgcolor . The 'bgcolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bgcolorsrc"] @bgcolorsrc.setter def bgcolorsrc(self, val): self["bgcolorsrc"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the border color of the hover labels for this trace. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # bordercolorsrc # -------------- @property def bordercolorsrc(self): """ Sets the source reference on plot.ly for bordercolor . The 'bordercolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bordercolorsrc"] @bordercolorsrc.setter def bordercolorsrc(self, val): self["bordercolorsrc"] = val # font # ---- @property def font(self): """ Sets the font used in hover labels. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.sankey.hoverlabel.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.sankey.hoverlabel.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # namelength # ---------- @property def namelength(self): """ Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. The 'namelength' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [-1, 9223372036854775807] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|numpy.ndarray """ return self["namelength"] @namelength.setter def namelength(self, val): self["namelength"] = val # namelengthsrc # ------------- @property def namelengthsrc(self): """ Sets the source reference on plot.ly for namelength . The 'namelengthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["namelengthsrc"] @namelengthsrc.setter def namelengthsrc(self, val): self["namelengthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "sankey" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """ def __init__( self, arg=None, align=None, alignsrc=None, bgcolor=None, bgcolorsrc=None, bordercolor=None, bordercolorsrc=None, font=None, namelength=None, namelengthsrc=None, **kwargs ): """ Construct a new Hoverlabel object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.sankey.Hoverlabel align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- Hoverlabel """ super(Hoverlabel, self).__init__("hoverlabel") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.sankey.Hoverlabel constructor must be a dict or an instance of plotly.graph_objs.sankey.Hoverlabel""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.sankey import hoverlabel as v_hoverlabel # Initialize validators # --------------------- self._validators["align"] = v_hoverlabel.AlignValidator() self._validators["alignsrc"] = v_hoverlabel.AlignsrcValidator() self._validators["bgcolor"] = v_hoverlabel.BgcolorValidator() self._validators["bgcolorsrc"] = v_hoverlabel.BgcolorsrcValidator() self._validators["bordercolor"] = v_hoverlabel.BordercolorValidator() self._validators["bordercolorsrc"] = v_hoverlabel.BordercolorsrcValidator() self._validators["font"] = v_hoverlabel.FontValidator() self._validators["namelength"] = v_hoverlabel.NamelengthValidator() self._validators["namelengthsrc"] = v_hoverlabel.NamelengthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("alignsrc", None) self["alignsrc"] = alignsrc if alignsrc is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bgcolorsrc", None) self["bgcolorsrc"] = bgcolorsrc if bgcolorsrc is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("bordercolorsrc", None) self["bordercolorsrc"] = bordercolorsrc if bordercolorsrc is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("namelength", None) self["namelength"] = namelength if namelength is not None else _v _v = arg.pop("namelengthsrc", None) self["namelengthsrc"] = namelengthsrc if namelengthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Domain(_BaseTraceHierarchyType): # column # ------ @property def column(self): """ If there is a layout grid, use the domain for this column in the grid for this sankey trace . The 'column' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["column"] @column.setter def column(self, val): self["column"] = val # row # --- @property def row(self): """ If there is a layout grid, use the domain for this row in the grid for this sankey trace . The 'row' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["row"] @row.setter def row(self, val): self["row"] = val # x # - @property def x(self): """ Sets the horizontal domain of this sankey trace (in plot fraction). The 'x' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'x[0]' property is a number and may be specified as: - An int or float in the interval [0, 1] (1) The 'x[1]' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- list """ return self["x"] @x.setter def x(self, val): self["x"] = val # y # - @property def y(self): """ Sets the vertical domain of this sankey trace (in plot fraction). The 'y' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'y[0]' property is a number and may be specified as: - An int or float in the interval [0, 1] (1) The 'y[1]' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- list """ return self["y"] @y.setter def y(self, val): self["y"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "sankey" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ column If there is a layout grid, use the domain for this column in the grid for this sankey trace . row If there is a layout grid, use the domain for this row in the grid for this sankey trace . x Sets the horizontal domain of this sankey trace (in plot fraction). y Sets the vertical domain of this sankey trace (in plot fraction). """ def __init__(self, arg=None, column=None, row=None, x=None, y=None, **kwargs): """ Construct a new Domain object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.sankey.Domain column If there is a layout grid, use the domain for this column in the grid for this sankey trace . row If there is a layout grid, use the domain for this row in the grid for this sankey trace . x Sets the horizontal domain of this sankey trace (in plot fraction). y Sets the vertical domain of this sankey trace (in plot fraction). Returns ------- Domain """ super(Domain, self).__init__("domain") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.sankey.Domain constructor must be a dict or an instance of plotly.graph_objs.sankey.Domain""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.sankey import domain as v_domain # Initialize validators # --------------------- self._validators["column"] = v_domain.ColumnValidator() self._validators["row"] = v_domain.RowValidator() self._validators["x"] = v_domain.XValidator() self._validators["y"] = v_domain.YValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("column", None) self["column"] = column if column is not None else _v _v = arg.pop("row", None) self["row"] = row if row is not None else _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = [ "Domain", "Hoverlabel", "Link", "Node", "Stream", "Textfont", "hoverlabel", "link", "node", ] from plotly.graph_objs.sankey import node from plotly.graph_objs.sankey import link from plotly.graph_objs.sankey import hoverlabel plotly-4.4.1+dfsg.orig/plotly/graph_objs/sankey/node/0000755000175000017500000000000013573746613022150 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/sankey/node/hoverlabel/0000755000175000017500000000000013573746613024273 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/sankey/node/hoverlabel/__init__.py0000644000175000017500000002546413573721550026410 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "sankey.node.hoverlabel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Font object Sets the font used in hover labels. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.sankey.node.hoverlabel.Font color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.sankey.node.hoverlabel.Font constructor must be a dict or an instance of plotly.graph_objs.sankey.node.hoverlabel.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.sankey.node.hoverlabel import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["colorsrc"] = v_font.ColorsrcValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["familysrc"] = v_font.FamilysrcValidator() self._validators["size"] = v_font.SizeValidator() self._validators["sizesrc"] = v_font.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/sankey/node/__init__.py0000644000175000017500000006111613573721550024257 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the color of the `line` around each `node`. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # width # ----- @property def width(self): """ Sets the width (in px) of the `line` around each `node`. The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["width"] @width.setter def width(self, val): self["width"] = val # widthsrc # -------- @property def widthsrc(self): """ Sets the source reference on plot.ly for width . The 'widthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["widthsrc"] @widthsrc.setter def widthsrc(self, val): self["widthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "sankey.node" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the color of the `line` around each `node`. colorsrc Sets the source reference on plot.ly for color . width Sets the width (in px) of the `line` around each `node`. widthsrc Sets the source reference on plot.ly for width . """ def __init__( self, arg=None, color=None, colorsrc=None, width=None, widthsrc=None, **kwargs ): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.sankey.node.Line color Sets the color of the `line` around each `node`. colorsrc Sets the source reference on plot.ly for color . width Sets the width (in px) of the `line` around each `node`. widthsrc Sets the source reference on plot.ly for width . Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.sankey.node.Line constructor must be a dict or an instance of plotly.graph_objs.sankey.node.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.sankey.node import line as v_line # Initialize validators # --------------------- self._validators["color"] = v_line.ColorValidator() self._validators["colorsrc"] = v_line.ColorsrcValidator() self._validators["width"] = v_line.WidthValidator() self._validators["widthsrc"] = v_line.WidthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v _v = arg.pop("widthsrc", None) self["widthsrc"] = widthsrc if widthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Hoverlabel(_BaseTraceHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'right', 'auto'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["align"] @align.setter def align(self, val): self["align"] = val # alignsrc # -------- @property def alignsrc(self): """ Sets the source reference on plot.ly for align . The 'alignsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["alignsrc"] @alignsrc.setter def alignsrc(self, val): self["alignsrc"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the hover labels for this trace The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bgcolorsrc # ---------- @property def bgcolorsrc(self): """ Sets the source reference on plot.ly for bgcolor . The 'bgcolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bgcolorsrc"] @bgcolorsrc.setter def bgcolorsrc(self, val): self["bgcolorsrc"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the border color of the hover labels for this trace. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # bordercolorsrc # -------------- @property def bordercolorsrc(self): """ Sets the source reference on plot.ly for bordercolor . The 'bordercolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bordercolorsrc"] @bordercolorsrc.setter def bordercolorsrc(self, val): self["bordercolorsrc"] = val # font # ---- @property def font(self): """ Sets the font used in hover labels. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.sankey.node.hoverlabel.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.sankey.node.hoverlabel.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # namelength # ---------- @property def namelength(self): """ Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. The 'namelength' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [-1, 9223372036854775807] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|numpy.ndarray """ return self["namelength"] @namelength.setter def namelength(self, val): self["namelength"] = val # namelengthsrc # ------------- @property def namelengthsrc(self): """ Sets the source reference on plot.ly for namelength . The 'namelengthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["namelengthsrc"] @namelengthsrc.setter def namelengthsrc(self, val): self["namelengthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "sankey.node" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """ def __init__( self, arg=None, align=None, alignsrc=None, bgcolor=None, bgcolorsrc=None, bordercolor=None, bordercolorsrc=None, font=None, namelength=None, namelengthsrc=None, **kwargs ): """ Construct a new Hoverlabel object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.sankey.node.Hoverlabel align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- Hoverlabel """ super(Hoverlabel, self).__init__("hoverlabel") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.sankey.node.Hoverlabel constructor must be a dict or an instance of plotly.graph_objs.sankey.node.Hoverlabel""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.sankey.node import hoverlabel as v_hoverlabel # Initialize validators # --------------------- self._validators["align"] = v_hoverlabel.AlignValidator() self._validators["alignsrc"] = v_hoverlabel.AlignsrcValidator() self._validators["bgcolor"] = v_hoverlabel.BgcolorValidator() self._validators["bgcolorsrc"] = v_hoverlabel.BgcolorsrcValidator() self._validators["bordercolor"] = v_hoverlabel.BordercolorValidator() self._validators["bordercolorsrc"] = v_hoverlabel.BordercolorsrcValidator() self._validators["font"] = v_hoverlabel.FontValidator() self._validators["namelength"] = v_hoverlabel.NamelengthValidator() self._validators["namelengthsrc"] = v_hoverlabel.NamelengthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("alignsrc", None) self["alignsrc"] = alignsrc if alignsrc is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bgcolorsrc", None) self["bgcolorsrc"] = bgcolorsrc if bgcolorsrc is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("bordercolorsrc", None) self["bordercolorsrc"] = bordercolorsrc if bordercolorsrc is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("namelength", None) self["namelength"] = namelength if namelength is not None else _v _v = arg.pop("namelengthsrc", None) self["namelengthsrc"] = namelengthsrc if namelengthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Hoverlabel", "Line", "hoverlabel"] from plotly.graph_objs.sankey.node import hoverlabel plotly-4.4.1+dfsg.orig/plotly/graph_objs/choropleth/0000755000175000017500000000000013573746613022100 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/choropleth/unselected/0000755000175000017500000000000013573746613024233 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/choropleth/unselected/__init__.py0000644000175000017500000000552613573721545026351 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # opacity # ------- @property def opacity(self): """ Sets the marker opacity of unselected points, applied only when a selection exists. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "choropleth.unselected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ opacity Sets the marker opacity of unselected points, applied only when a selection exists. """ def __init__(self, arg=None, opacity=None, **kwargs): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.choropleth.unselected.Marker opacity Sets the marker opacity of unselected points, applied only when a selection exists. Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.choropleth.unselected.Marker constructor must be a dict or an instance of plotly.graph_objs.choropleth.unselected.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.choropleth.unselected import marker as v_marker # Initialize validators # --------------------- self._validators["opacity"] = v_marker.OpacityValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Marker"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/choropleth/hoverlabel/0000755000175000017500000000000013573746613024223 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/choropleth/hoverlabel/__init__.py0000644000175000017500000002545713573721545026346 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "choropleth.hoverlabel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Font object Sets the font used in hover labels. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.choropleth.hoverlabel.Font color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.choropleth.hoverlabel.Font constructor must be a dict or an instance of plotly.graph_objs.choropleth.hoverlabel.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.choropleth.hoverlabel import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["colorsrc"] = v_font.ColorsrcValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["familysrc"] = v_font.FamilysrcValidator() self._validators["size"] = v_font.SizeValidator() self._validators["sizesrc"] = v_font.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/choropleth/colorbar/0000755000175000017500000000000013573746613023703 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/choropleth/colorbar/title/0000755000175000017500000000000013573746613025024 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/choropleth/colorbar/title/__init__.py0000644000175000017500000002054413573721545027137 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "choropleth.colorbar.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.choropleth.colorbar.title.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.choropleth.colorbar.title.Font constructor must be a dict or an instance of plotly.graph_objs.choropleth.colorbar.title.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.choropleth.colorbar.title import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/choropleth/colorbar/__init__.py0000644000175000017500000006064413573721546026024 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Title(_BaseTraceHierarchyType): # font # ---- @property def font(self): """ Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.choropleth.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.choropleth.colorbar.title.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # side # ---- @property def side(self): """ Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- Any """ return self["side"] @side.setter def side(self, val): self["side"] = val # text # ---- @property def text(self): """ Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "choropleth.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """ def __init__(self, arg=None, font=None, side=None, text=None, **kwargs): """ Construct a new Title object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.choropleth.colorbar.Title font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- Title """ super(Title, self).__init__("title") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.choropleth.colorbar.Title constructor must be a dict or an instance of plotly.graph_objs.choropleth.colorbar.Title""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.choropleth.colorbar import title as v_title # Initialize validators # --------------------- self._validators["font"] = v_title.FontValidator() self._validators["side"] = v_title.SideValidator() self._validators["text"] = v_title.TextValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("side", None) self["side"] = side if side is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickformatstop(_BaseTraceHierarchyType): # dtickrange # ---------- @property def dtickrange(self): """ range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" The 'dtickrange' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'dtickrange[0]' property accepts values of any type (1) The 'dtickrange[1]' property accepts values of any type Returns ------- list """ return self["dtickrange"] @dtickrange.setter def dtickrange(self, val): self["dtickrange"] = val # enabled # ------- @property def enabled(self): """ Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. The 'enabled' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["enabled"] @enabled.setter def enabled(self, val): self["enabled"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # value # ----- @property def value(self): """ string - dtickformat for described zoom level, the same as "tickformat" The 'value' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "choropleth.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """ def __init__( self, arg=None, dtickrange=None, enabled=None, name=None, templateitemname=None, value=None, **kwargs ): """ Construct a new Tickformatstop object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.choropleth.colorbar.Tickformatstop dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- Tickformatstop """ super(Tickformatstop, self).__init__("tickformatstops") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.choropleth.colorbar.Tickformatstop constructor must be a dict or an instance of plotly.graph_objs.choropleth.colorbar.Tickformatstop""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.choropleth.colorbar import ( tickformatstop as v_tickformatstop, ) # Initialize validators # --------------------- self._validators["dtickrange"] = v_tickformatstop.DtickrangeValidator() self._validators["enabled"] = v_tickformatstop.EnabledValidator() self._validators["name"] = v_tickformatstop.NameValidator() self._validators[ "templateitemname" ] = v_tickformatstop.TemplateitemnameValidator() self._validators["value"] = v_tickformatstop.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtickrange", None) self["dtickrange"] = dtickrange if dtickrange is not None else _v _v = arg.pop("enabled", None) self["enabled"] = enabled if enabled is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "choropleth.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Tickfont object Sets the color bar's tick label font Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.choropleth.colorbar.Tickfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Tickfont """ super(Tickfont, self).__init__("tickfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.choropleth.colorbar.Tickfont constructor must be a dict or an instance of plotly.graph_objs.choropleth.colorbar.Tickfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.choropleth.colorbar import tickfont as v_tickfont # Initialize validators # --------------------- self._validators["color"] = v_tickfont.ColorValidator() self._validators["family"] = v_tickfont.FamilyValidator() self._validators["size"] = v_tickfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Tickfont", "Tickformatstop", "Tickformatstop", "Title", "title"] from plotly.graph_objs.choropleth.colorbar import title plotly-4.4.1+dfsg.orig/plotly/graph_objs/choropleth/marker/0000755000175000017500000000000013573746613023361 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/choropleth/marker/__init__.py0000644000175000017500000002001413573721545025464 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # width # ----- @property def width(self): """ Sets the width (in px) of the lines bounding the marker points. The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["width"] @width.setter def width(self, val): self["width"] = val # widthsrc # -------- @property def widthsrc(self): """ Sets the source reference on plot.ly for width . The 'widthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["widthsrc"] @widthsrc.setter def widthsrc(self, val): self["widthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "choropleth.marker" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. colorsrc Sets the source reference on plot.ly for color . width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . """ def __init__( self, arg=None, color=None, colorsrc=None, width=None, widthsrc=None, **kwargs ): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.choropleth.marker.Line color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. colorsrc Sets the source reference on plot.ly for color . width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.choropleth.marker.Line constructor must be a dict or an instance of plotly.graph_objs.choropleth.marker.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.choropleth.marker import line as v_line # Initialize validators # --------------------- self._validators["color"] = v_line.ColorValidator() self._validators["colorsrc"] = v_line.ColorsrcValidator() self._validators["width"] = v_line.WidthValidator() self._validators["widthsrc"] = v_line.WidthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v _v = arg.pop("widthsrc", None) self["widthsrc"] = widthsrc if widthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Line"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/choropleth/__init__.py0000644000175000017500000031114513573721547024215 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Unselected(_BaseTraceHierarchyType): # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.choropleth.unselected.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: opacity Sets the marker opacity of unselected points, applied only when a selection exists. Returns ------- plotly.graph_objs.choropleth.unselected.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "choropleth" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ marker plotly.graph_objects.choropleth.unselected.Marker instance or dict with compatible properties """ def __init__(self, arg=None, marker=None, **kwargs): """ Construct a new Unselected object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.choropleth.Unselected marker plotly.graph_objects.choropleth.unselected.Marker instance or dict with compatible properties Returns ------- Unselected """ super(Unselected, self).__init__("unselected") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.choropleth.Unselected constructor must be a dict or an instance of plotly.graph_objs.choropleth.Unselected""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.choropleth import unselected as v_unselected # Initialize validators # --------------------- self._validators["marker"] = v_unselected.MarkerValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Stream(_BaseTraceHierarchyType): # maxpoints # --------- @property def maxpoints(self): """ Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. The 'maxpoints' property is a number and may be specified as: - An int or float in the interval [0, 10000] Returns ------- int|float """ return self["maxpoints"] @maxpoints.setter def maxpoints(self, val): self["maxpoints"] = val # token # ----- @property def token(self): """ The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. The 'token' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["token"] @token.setter def token(self, val): self["token"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "choropleth" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """ def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): """ Construct a new Stream object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.choropleth.Stream maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- Stream """ super(Stream, self).__init__("stream") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.choropleth.Stream constructor must be a dict or an instance of plotly.graph_objs.choropleth.Stream""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.choropleth import stream as v_stream # Initialize validators # --------------------- self._validators["maxpoints"] = v_stream.MaxpointsValidator() self._validators["token"] = v_stream.TokenValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("maxpoints", None) self["maxpoints"] = maxpoints if maxpoints is not None else _v _v = arg.pop("token", None) self["token"] = token if token is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Selected(_BaseTraceHierarchyType): # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.choropleth.selected.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: opacity Sets the marker opacity of selected points. Returns ------- plotly.graph_objs.choropleth.selected.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "choropleth" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ marker plotly.graph_objects.choropleth.selected.Marker instance or dict with compatible properties """ def __init__(self, arg=None, marker=None, **kwargs): """ Construct a new Selected object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.choropleth.Selected marker plotly.graph_objects.choropleth.selected.Marker instance or dict with compatible properties Returns ------- Selected """ super(Selected, self).__init__("selected") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.choropleth.Selected constructor must be a dict or an instance of plotly.graph_objs.choropleth.Selected""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.choropleth import selected as v_selected # Initialize validators # --------------------- self._validators["marker"] = v_selected.MarkerValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.choropleth.marker.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. colorsrc Sets the source reference on plot.ly for color . width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . Returns ------- plotly.graph_objs.choropleth.marker.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the locations. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # opacitysrc # ---------- @property def opacitysrc(self): """ Sets the source reference on plot.ly for opacity . The 'opacitysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["opacitysrc"] @opacitysrc.setter def opacitysrc(self, val): self["opacitysrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "choropleth" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ line plotly.graph_objects.choropleth.marker.Line instance or dict with compatible properties opacity Sets the opacity of the locations. opacitysrc Sets the source reference on plot.ly for opacity . """ def __init__(self, arg=None, line=None, opacity=None, opacitysrc=None, **kwargs): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.choropleth.Marker line plotly.graph_objects.choropleth.marker.Line instance or dict with compatible properties opacity Sets the opacity of the locations. opacitysrc Sets the source reference on plot.ly for opacity . Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.choropleth.Marker constructor must be a dict or an instance of plotly.graph_objs.choropleth.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.choropleth import marker as v_marker # Initialize validators # --------------------- self._validators["line"] = v_marker.LineValidator() self._validators["opacity"] = v_marker.OpacityValidator() self._validators["opacitysrc"] = v_marker.OpacitysrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("line", None) self["line"] = line if line is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("opacitysrc", None) self["opacitysrc"] = opacitysrc if opacitysrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Hoverlabel(_BaseTraceHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'right', 'auto'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["align"] @align.setter def align(self, val): self["align"] = val # alignsrc # -------- @property def alignsrc(self): """ Sets the source reference on plot.ly for align . The 'alignsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["alignsrc"] @alignsrc.setter def alignsrc(self, val): self["alignsrc"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the hover labels for this trace The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bgcolorsrc # ---------- @property def bgcolorsrc(self): """ Sets the source reference on plot.ly for bgcolor . The 'bgcolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bgcolorsrc"] @bgcolorsrc.setter def bgcolorsrc(self, val): self["bgcolorsrc"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the border color of the hover labels for this trace. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # bordercolorsrc # -------------- @property def bordercolorsrc(self): """ Sets the source reference on plot.ly for bordercolor . The 'bordercolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bordercolorsrc"] @bordercolorsrc.setter def bordercolorsrc(self, val): self["bordercolorsrc"] = val # font # ---- @property def font(self): """ Sets the font used in hover labels. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.choropleth.hoverlabel.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.choropleth.hoverlabel.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # namelength # ---------- @property def namelength(self): """ Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. The 'namelength' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [-1, 9223372036854775807] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|numpy.ndarray """ return self["namelength"] @namelength.setter def namelength(self, val): self["namelength"] = val # namelengthsrc # ------------- @property def namelengthsrc(self): """ Sets the source reference on plot.ly for namelength . The 'namelengthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["namelengthsrc"] @namelengthsrc.setter def namelengthsrc(self, val): self["namelengthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "choropleth" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """ def __init__( self, arg=None, align=None, alignsrc=None, bgcolor=None, bgcolorsrc=None, bordercolor=None, bordercolorsrc=None, font=None, namelength=None, namelengthsrc=None, **kwargs ): """ Construct a new Hoverlabel object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.choropleth.Hoverlabel align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- Hoverlabel """ super(Hoverlabel, self).__init__("hoverlabel") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.choropleth.Hoverlabel constructor must be a dict or an instance of plotly.graph_objs.choropleth.Hoverlabel""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.choropleth import hoverlabel as v_hoverlabel # Initialize validators # --------------------- self._validators["align"] = v_hoverlabel.AlignValidator() self._validators["alignsrc"] = v_hoverlabel.AlignsrcValidator() self._validators["bgcolor"] = v_hoverlabel.BgcolorValidator() self._validators["bgcolorsrc"] = v_hoverlabel.BgcolorsrcValidator() self._validators["bordercolor"] = v_hoverlabel.BordercolorValidator() self._validators["bordercolorsrc"] = v_hoverlabel.BordercolorsrcValidator() self._validators["font"] = v_hoverlabel.FontValidator() self._validators["namelength"] = v_hoverlabel.NamelengthValidator() self._validators["namelengthsrc"] = v_hoverlabel.NamelengthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("alignsrc", None) self["alignsrc"] = alignsrc if alignsrc is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bgcolorsrc", None) self["bgcolorsrc"] = bgcolorsrc if bgcolorsrc is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("bordercolorsrc", None) self["bordercolorsrc"] = bordercolorsrc if bordercolorsrc is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("namelength", None) self["namelength"] = namelength if namelength is not None else _v _v = arg.pop("namelengthsrc", None) self["namelengthsrc"] = namelengthsrc if namelengthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class ColorBar(_BaseTraceHierarchyType): # bgcolor # ------- @property def bgcolor(self): """ Sets the color of padded area. The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the axis line color. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # borderwidth # ----------- @property def borderwidth(self): """ Sets the width (in px) or the border enclosing this color bar. The 'borderwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["borderwidth"] @borderwidth.setter def borderwidth(self, val): self["borderwidth"] = val # dtick # ----- @property def dtick(self): """ Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" The 'dtick' property accepts values of any type Returns ------- Any """ return self["dtick"] @dtick.setter def dtick(self, val): self["dtick"] = val # exponentformat # -------------- @property def exponentformat(self): """ Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. The 'exponentformat' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'e', 'E', 'power', 'SI', 'B'] Returns ------- Any """ return self["exponentformat"] @exponentformat.setter def exponentformat(self, val): self["exponentformat"] = val # len # --- @property def len(self): """ Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. The 'len' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["len"] @len.setter def len(self, val): self["len"] = val # lenmode # ------- @property def lenmode(self): """ Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. The 'lenmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["lenmode"] @lenmode.setter def lenmode(self, val): self["lenmode"] = val # nticks # ------ @property def nticks(self): """ Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". The 'nticks' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nticks"] @nticks.setter def nticks(self, val): self["nticks"] = val # outlinecolor # ------------ @property def outlinecolor(self): """ Sets the axis line color. The 'outlinecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["outlinecolor"] @outlinecolor.setter def outlinecolor(self, val): self["outlinecolor"] = val # outlinewidth # ------------ @property def outlinewidth(self): """ Sets the width (in px) of the axis line. The 'outlinewidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["outlinewidth"] @outlinewidth.setter def outlinewidth(self, val): self["outlinewidth"] = val # separatethousands # ----------------- @property def separatethousands(self): """ If "true", even 4-digit integers are separated The 'separatethousands' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["separatethousands"] @separatethousands.setter def separatethousands(self, val): self["separatethousands"] = val # showexponent # ------------ @property def showexponent(self): """ If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. The 'showexponent' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showexponent"] @showexponent.setter def showexponent(self, val): self["showexponent"] = val # showticklabels # -------------- @property def showticklabels(self): """ Determines whether or not the tick labels are drawn. The 'showticklabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showticklabels"] @showticklabels.setter def showticklabels(self, val): self["showticklabels"] = val # showtickprefix # -------------- @property def showtickprefix(self): """ If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. The 'showtickprefix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showtickprefix"] @showtickprefix.setter def showtickprefix(self, val): self["showtickprefix"] = val # showticksuffix # -------------- @property def showticksuffix(self): """ Same as `showtickprefix` but for tick suffixes. The 'showticksuffix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showticksuffix"] @showticksuffix.setter def showticksuffix(self, val): self["showticksuffix"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # thicknessmode # ------------- @property def thicknessmode(self): """ Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. The 'thicknessmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["thicknessmode"] @thicknessmode.setter def thicknessmode(self, val): self["thicknessmode"] = val # tick0 # ----- @property def tick0(self): """ Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. The 'tick0' property accepts values of any type Returns ------- Any """ return self["tick0"] @tick0.setter def tick0(self, val): self["tick0"] = val # tickangle # --------- @property def tickangle(self): """ Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. The 'tickangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["tickangle"] @tickangle.setter def tickangle(self, val): self["tickangle"] = val # tickcolor # --------- @property def tickcolor(self): """ Sets the tick color. The 'tickcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["tickcolor"] @tickcolor.setter def tickcolor(self, val): self["tickcolor"] = val # tickfont # -------- @property def tickfont(self): """ Sets the color bar's tick label font The 'tickfont' property is an instance of Tickfont that may be specified as: - An instance of plotly.graph_objs.choropleth.colorbar.Tickfont - A dict of string/value properties that will be passed to the Tickfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.choropleth.colorbar.Tickfont """ return self["tickfont"] @tickfont.setter def tickfont(self, val): self["tickfont"] = val # tickformat # ---------- @property def tickformat(self): """ Sets the tick label formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'tickformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickformat"] @tickformat.setter def tickformat(self, val): self["tickformat"] = val # tickformatstops # --------------- @property def tickformatstops(self): """ The 'tickformatstops' property is a tuple of instances of Tickformatstop that may be specified as: - A list or tuple of instances of plotly.graph_objs.choropleth.colorbar.Tickformatstop - A list or tuple of dicts of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- tuple[plotly.graph_objs.choropleth.colorbar.Tickformatstop] """ return self["tickformatstops"] @tickformatstops.setter def tickformatstops(self, val): self["tickformatstops"] = val # tickformatstopdefaults # ---------------------- @property def tickformatstopdefaults(self): """ When used in a template (as layout.template.data.choropleth.col orbar.tickformatstopdefaults), sets the default property values to use for elements of choropleth.colorbar.tickformatstops The 'tickformatstopdefaults' property is an instance of Tickformatstop that may be specified as: - An instance of plotly.graph_objs.choropleth.colorbar.Tickformatstop - A dict of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: Returns ------- plotly.graph_objs.choropleth.colorbar.Tickformatstop """ return self["tickformatstopdefaults"] @tickformatstopdefaults.setter def tickformatstopdefaults(self, val): self["tickformatstopdefaults"] = val # ticklen # ------- @property def ticklen(self): """ Sets the tick length (in px). The 'ticklen' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ticklen"] @ticklen.setter def ticklen(self, val): self["ticklen"] = val # tickmode # -------- @property def tickmode(self): """ Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). The 'tickmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'linear', 'array'] Returns ------- Any """ return self["tickmode"] @tickmode.setter def tickmode(self, val): self["tickmode"] = val # tickprefix # ---------- @property def tickprefix(self): """ Sets a tick label prefix. The 'tickprefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickprefix"] @tickprefix.setter def tickprefix(self, val): self["tickprefix"] = val # ticks # ----- @property def ticks(self): """ Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. The 'ticks' property is an enumeration that may be specified as: - One of the following enumeration values: ['outside', 'inside', ''] Returns ------- Any """ return self["ticks"] @ticks.setter def ticks(self, val): self["ticks"] = val # ticksuffix # ---------- @property def ticksuffix(self): """ Sets a tick label suffix. The 'ticksuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ticksuffix"] @ticksuffix.setter def ticksuffix(self, val): self["ticksuffix"] = val # ticktext # -------- @property def ticktext(self): """ Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. The 'ticktext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ticktext"] @ticktext.setter def ticktext(self, val): self["ticktext"] = val # ticktextsrc # ----------- @property def ticktextsrc(self): """ Sets the source reference on plot.ly for ticktext . The 'ticktextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ticktextsrc"] @ticktextsrc.setter def ticktextsrc(self, val): self["ticktextsrc"] = val # tickvals # -------- @property def tickvals(self): """ Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. The 'tickvals' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["tickvals"] @tickvals.setter def tickvals(self, val): self["tickvals"] = val # tickvalssrc # ----------- @property def tickvalssrc(self): """ Sets the source reference on plot.ly for tickvals . The 'tickvalssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tickvalssrc"] @tickvalssrc.setter def tickvalssrc(self, val): self["tickvalssrc"] = val # tickwidth # --------- @property def tickwidth(self): """ Sets the tick width (in px). The 'tickwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["tickwidth"] @tickwidth.setter def tickwidth(self, val): self["tickwidth"] = val # title # ----- @property def title(self): """ The 'title' property is an instance of Title that may be specified as: - An instance of plotly.graph_objs.choropleth.colorbar.Title - A dict of string/value properties that will be passed to the Title constructor Supported dict properties: font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- plotly.graph_objs.choropleth.colorbar.Title """ return self["title"] @title.setter def title(self, val): self["title"] = val # titlefont # --------- @property def titlefont(self): """ Deprecated: Please use choropleth.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.choropleth.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- """ return self["titlefont"] @titlefont.setter def titlefont(self, val): self["titlefont"] = val # titleside # --------- @property def titleside(self): """ Deprecated: Please use choropleth.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- """ return self["titleside"] @titleside.setter def titleside(self, val): self["titleside"] = val # x # - @property def x(self): """ Sets the x position of the color bar (in plot fraction). The 'x' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["x"] @x.setter def x(self, val): self["x"] = val # xanchor # ------- @property def xanchor(self): """ Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. The 'xanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'center', 'right'] Returns ------- Any """ return self["xanchor"] @xanchor.setter def xanchor(self, val): self["xanchor"] = val # xpad # ---- @property def xpad(self): """ Sets the amount of padding (in px) along the x direction. The 'xpad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["xpad"] @xpad.setter def xpad(self, val): self["xpad"] = val # y # - @property def y(self): """ Sets the y position of the color bar (in plot fraction). The 'y' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["y"] @y.setter def y(self, val): self["y"] = val # yanchor # ------- @property def yanchor(self): """ Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. The 'yanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['top', 'middle', 'bottom'] Returns ------- Any """ return self["yanchor"] @yanchor.setter def yanchor(self, val): self["yanchor"] = val # ypad # ---- @property def ypad(self): """ Sets the amount of padding (in px) along the y direction. The 'ypad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ypad"] @ypad.setter def ypad(self, val): self["ypad"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "choropleth" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.choropleth.colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.chorop leth.colorbar.tickformatstopdefaults), sets the default property values to use for elements of choropleth.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.choropleth.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use choropleth.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use choropleth.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """ _mapped_properties = { "titlefont": ("title", "font"), "titleside": ("title", "side"), } def __init__( self, arg=None, bgcolor=None, bordercolor=None, borderwidth=None, dtick=None, exponentformat=None, len=None, lenmode=None, nticks=None, outlinecolor=None, outlinewidth=None, separatethousands=None, showexponent=None, showticklabels=None, showtickprefix=None, showticksuffix=None, thickness=None, thicknessmode=None, tick0=None, tickangle=None, tickcolor=None, tickfont=None, tickformat=None, tickformatstops=None, tickformatstopdefaults=None, ticklen=None, tickmode=None, tickprefix=None, ticks=None, ticksuffix=None, ticktext=None, ticktextsrc=None, tickvals=None, tickvalssrc=None, tickwidth=None, title=None, titlefont=None, titleside=None, x=None, xanchor=None, xpad=None, y=None, yanchor=None, ypad=None, **kwargs ): """ Construct a new ColorBar object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.choropleth.ColorBar bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.choropleth.colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.chorop leth.colorbar.tickformatstopdefaults), sets the default property values to use for elements of choropleth.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.choropleth.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use choropleth.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use choropleth.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- ColorBar """ super(ColorBar, self).__init__("colorbar") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.choropleth.ColorBar constructor must be a dict or an instance of plotly.graph_objs.choropleth.ColorBar""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.choropleth import colorbar as v_colorbar # Initialize validators # --------------------- self._validators["bgcolor"] = v_colorbar.BgcolorValidator() self._validators["bordercolor"] = v_colorbar.BordercolorValidator() self._validators["borderwidth"] = v_colorbar.BorderwidthValidator() self._validators["dtick"] = v_colorbar.DtickValidator() self._validators["exponentformat"] = v_colorbar.ExponentformatValidator() self._validators["len"] = v_colorbar.LenValidator() self._validators["lenmode"] = v_colorbar.LenmodeValidator() self._validators["nticks"] = v_colorbar.NticksValidator() self._validators["outlinecolor"] = v_colorbar.OutlinecolorValidator() self._validators["outlinewidth"] = v_colorbar.OutlinewidthValidator() self._validators["separatethousands"] = v_colorbar.SeparatethousandsValidator() self._validators["showexponent"] = v_colorbar.ShowexponentValidator() self._validators["showticklabels"] = v_colorbar.ShowticklabelsValidator() self._validators["showtickprefix"] = v_colorbar.ShowtickprefixValidator() self._validators["showticksuffix"] = v_colorbar.ShowticksuffixValidator() self._validators["thickness"] = v_colorbar.ThicknessValidator() self._validators["thicknessmode"] = v_colorbar.ThicknessmodeValidator() self._validators["tick0"] = v_colorbar.Tick0Validator() self._validators["tickangle"] = v_colorbar.TickangleValidator() self._validators["tickcolor"] = v_colorbar.TickcolorValidator() self._validators["tickfont"] = v_colorbar.TickfontValidator() self._validators["tickformat"] = v_colorbar.TickformatValidator() self._validators["tickformatstops"] = v_colorbar.TickformatstopsValidator() self._validators[ "tickformatstopdefaults" ] = v_colorbar.TickformatstopValidator() self._validators["ticklen"] = v_colorbar.TicklenValidator() self._validators["tickmode"] = v_colorbar.TickmodeValidator() self._validators["tickprefix"] = v_colorbar.TickprefixValidator() self._validators["ticks"] = v_colorbar.TicksValidator() self._validators["ticksuffix"] = v_colorbar.TicksuffixValidator() self._validators["ticktext"] = v_colorbar.TicktextValidator() self._validators["ticktextsrc"] = v_colorbar.TicktextsrcValidator() self._validators["tickvals"] = v_colorbar.TickvalsValidator() self._validators["tickvalssrc"] = v_colorbar.TickvalssrcValidator() self._validators["tickwidth"] = v_colorbar.TickwidthValidator() self._validators["title"] = v_colorbar.TitleValidator() self._validators["x"] = v_colorbar.XValidator() self._validators["xanchor"] = v_colorbar.XanchorValidator() self._validators["xpad"] = v_colorbar.XpadValidator() self._validators["y"] = v_colorbar.YValidator() self._validators["yanchor"] = v_colorbar.YanchorValidator() self._validators["ypad"] = v_colorbar.YpadValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("borderwidth", None) self["borderwidth"] = borderwidth if borderwidth is not None else _v _v = arg.pop("dtick", None) self["dtick"] = dtick if dtick is not None else _v _v = arg.pop("exponentformat", None) self["exponentformat"] = exponentformat if exponentformat is not None else _v _v = arg.pop("len", None) self["len"] = len if len is not None else _v _v = arg.pop("lenmode", None) self["lenmode"] = lenmode if lenmode is not None else _v _v = arg.pop("nticks", None) self["nticks"] = nticks if nticks is not None else _v _v = arg.pop("outlinecolor", None) self["outlinecolor"] = outlinecolor if outlinecolor is not None else _v _v = arg.pop("outlinewidth", None) self["outlinewidth"] = outlinewidth if outlinewidth is not None else _v _v = arg.pop("separatethousands", None) self["separatethousands"] = ( separatethousands if separatethousands is not None else _v ) _v = arg.pop("showexponent", None) self["showexponent"] = showexponent if showexponent is not None else _v _v = arg.pop("showticklabels", None) self["showticklabels"] = showticklabels if showticklabels is not None else _v _v = arg.pop("showtickprefix", None) self["showtickprefix"] = showtickprefix if showtickprefix is not None else _v _v = arg.pop("showticksuffix", None) self["showticksuffix"] = showticksuffix if showticksuffix is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("thicknessmode", None) self["thicknessmode"] = thicknessmode if thicknessmode is not None else _v _v = arg.pop("tick0", None) self["tick0"] = tick0 if tick0 is not None else _v _v = arg.pop("tickangle", None) self["tickangle"] = tickangle if tickangle is not None else _v _v = arg.pop("tickcolor", None) self["tickcolor"] = tickcolor if tickcolor is not None else _v _v = arg.pop("tickfont", None) self["tickfont"] = tickfont if tickfont is not None else _v _v = arg.pop("tickformat", None) self["tickformat"] = tickformat if tickformat is not None else _v _v = arg.pop("tickformatstops", None) self["tickformatstops"] = tickformatstops if tickformatstops is not None else _v _v = arg.pop("tickformatstopdefaults", None) self["tickformatstopdefaults"] = ( tickformatstopdefaults if tickformatstopdefaults is not None else _v ) _v = arg.pop("ticklen", None) self["ticklen"] = ticklen if ticklen is not None else _v _v = arg.pop("tickmode", None) self["tickmode"] = tickmode if tickmode is not None else _v _v = arg.pop("tickprefix", None) self["tickprefix"] = tickprefix if tickprefix is not None else _v _v = arg.pop("ticks", None) self["ticks"] = ticks if ticks is not None else _v _v = arg.pop("ticksuffix", None) self["ticksuffix"] = ticksuffix if ticksuffix is not None else _v _v = arg.pop("ticktext", None) self["ticktext"] = ticktext if ticktext is not None else _v _v = arg.pop("ticktextsrc", None) self["ticktextsrc"] = ticktextsrc if ticktextsrc is not None else _v _v = arg.pop("tickvals", None) self["tickvals"] = tickvals if tickvals is not None else _v _v = arg.pop("tickvalssrc", None) self["tickvalssrc"] = tickvalssrc if tickvalssrc is not None else _v _v = arg.pop("tickwidth", None) self["tickwidth"] = tickwidth if tickwidth is not None else _v _v = arg.pop("title", None) self["title"] = title if title is not None else _v _v = arg.pop("titlefont", None) _v = titlefont if titlefont is not None else _v if _v is not None: self["titlefont"] = _v _v = arg.pop("titleside", None) _v = titleside if titleside is not None else _v if _v is not None: self["titleside"] = _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xanchor", None) self["xanchor"] = xanchor if xanchor is not None else _v _v = arg.pop("xpad", None) self["xpad"] = xpad if xpad is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("yanchor", None) self["yanchor"] = yanchor if yanchor is not None else _v _v = arg.pop("ypad", None) self["ypad"] = ypad if ypad is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = [ "ColorBar", "Hoverlabel", "Marker", "Selected", "Stream", "Unselected", "colorbar", "hoverlabel", "marker", "selected", "unselected", ] from plotly.graph_objs.choropleth import unselected from plotly.graph_objs.choropleth import selected from plotly.graph_objs.choropleth import marker from plotly.graph_objs.choropleth import hoverlabel from plotly.graph_objs.choropleth import colorbar plotly-4.4.1+dfsg.orig/plotly/graph_objs/choropleth/selected/0000755000175000017500000000000013573746613023670 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/choropleth/selected/__init__.py0000644000175000017500000000526413573721545026005 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # opacity # ------- @property def opacity(self): """ Sets the marker opacity of selected points. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "choropleth.selected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ opacity Sets the marker opacity of selected points. """ def __init__(self, arg=None, opacity=None, **kwargs): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.choropleth.selected.Marker opacity Sets the marker opacity of selected points. Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.choropleth.selected.Marker constructor must be a dict or an instance of plotly.graph_objs.choropleth.selected.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.choropleth.selected import marker as v_marker # Initialize validators # --------------------- self._validators["opacity"] = v_marker.OpacityValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Marker"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/candlestick/0000755000175000017500000000000013573746613022215 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/candlestick/increasing/0000755000175000017500000000000013573746613024337 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/candlestick/increasing/__init__.py0000644000175000017500000001325513573721545026453 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the color of line bounding the box(es). The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # width # ----- @property def width(self): """ Sets the width (in px) of line bounding the box(es). The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "candlestick.increasing" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the color of line bounding the box(es). width Sets the width (in px) of line bounding the box(es). """ def __init__(self, arg=None, color=None, width=None, **kwargs): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.candlestick.increasing.Line color Sets the color of line bounding the box(es). width Sets the width (in px) of line bounding the box(es). Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.candlestick.increasing.Line constructor must be a dict or an instance of plotly.graph_objs.candlestick.increasing.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.candlestick.increasing import line as v_line # Initialize validators # --------------------- self._validators["color"] = v_line.ColorValidator() self._validators["width"] = v_line.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Line"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/candlestick/hoverlabel/0000755000175000017500000000000013573746613024340 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/candlestick/hoverlabel/__init__.py0000644000175000017500000002546413573721545026461 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "candlestick.hoverlabel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Font object Sets the font used in hover labels. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.candlestick.hoverlabel.Font color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.candlestick.hoverlabel.Font constructor must be a dict or an instance of plotly.graph_objs.candlestick.hoverlabel.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.candlestick.hoverlabel import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["colorsrc"] = v_font.ColorsrcValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["familysrc"] = v_font.FamilysrcValidator() self._validators["size"] = v_font.SizeValidator() self._validators["sizesrc"] = v_font.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/candlestick/__init__.py0000644000175000017500000011450013573721546024325 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Stream(_BaseTraceHierarchyType): # maxpoints # --------- @property def maxpoints(self): """ Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. The 'maxpoints' property is a number and may be specified as: - An int or float in the interval [0, 10000] Returns ------- int|float """ return self["maxpoints"] @maxpoints.setter def maxpoints(self, val): self["maxpoints"] = val # token # ----- @property def token(self): """ The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. The 'token' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["token"] @token.setter def token(self, val): self["token"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "candlestick" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """ def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): """ Construct a new Stream object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.candlestick.Stream maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- Stream """ super(Stream, self).__init__("stream") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.candlestick.Stream constructor must be a dict or an instance of plotly.graph_objs.candlestick.Stream""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.candlestick import stream as v_stream # Initialize validators # --------------------- self._validators["maxpoints"] = v_stream.MaxpointsValidator() self._validators["token"] = v_stream.TokenValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("maxpoints", None) self["maxpoints"] = maxpoints if maxpoints is not None else _v _v = arg.pop("token", None) self["token"] = token if token is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # width # ----- @property def width(self): """ Sets the width (in px) of line bounding the box(es). Note that this style setting can also be set per direction via `increasing.line.width` and `decreasing.line.width`. The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "candlestick" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ width Sets the width (in px) of line bounding the box(es). Note that this style setting can also be set per direction via `increasing.line.width` and `decreasing.line.width`. """ def __init__(self, arg=None, width=None, **kwargs): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.candlestick.Line width Sets the width (in px) of line bounding the box(es). Note that this style setting can also be set per direction via `increasing.line.width` and `decreasing.line.width`. Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.candlestick.Line constructor must be a dict or an instance of plotly.graph_objs.candlestick.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.candlestick import line as v_line # Initialize validators # --------------------- self._validators["width"] = v_line.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Increasing(_BaseTraceHierarchyType): # fillcolor # --------- @property def fillcolor(self): """ Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. The 'fillcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["fillcolor"] @fillcolor.setter def fillcolor(self, val): self["fillcolor"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.candlestick.increasing.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: color Sets the color of line bounding the box(es). width Sets the width (in px) of line bounding the box(es). Returns ------- plotly.graph_objs.candlestick.increasing.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "candlestick" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ fillcolor Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. line plotly.graph_objects.candlestick.increasing.Line instance or dict with compatible properties """ def __init__(self, arg=None, fillcolor=None, line=None, **kwargs): """ Construct a new Increasing object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.candlestick.Increasing fillcolor Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. line plotly.graph_objects.candlestick.increasing.Line instance or dict with compatible properties Returns ------- Increasing """ super(Increasing, self).__init__("increasing") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.candlestick.Increasing constructor must be a dict or an instance of plotly.graph_objs.candlestick.Increasing""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.candlestick import increasing as v_increasing # Initialize validators # --------------------- self._validators["fillcolor"] = v_increasing.FillcolorValidator() self._validators["line"] = v_increasing.LineValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("fillcolor", None) self["fillcolor"] = fillcolor if fillcolor is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Hoverlabel(_BaseTraceHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'right', 'auto'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["align"] @align.setter def align(self, val): self["align"] = val # alignsrc # -------- @property def alignsrc(self): """ Sets the source reference on plot.ly for align . The 'alignsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["alignsrc"] @alignsrc.setter def alignsrc(self, val): self["alignsrc"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the hover labels for this trace The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bgcolorsrc # ---------- @property def bgcolorsrc(self): """ Sets the source reference on plot.ly for bgcolor . The 'bgcolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bgcolorsrc"] @bgcolorsrc.setter def bgcolorsrc(self, val): self["bgcolorsrc"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the border color of the hover labels for this trace. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # bordercolorsrc # -------------- @property def bordercolorsrc(self): """ Sets the source reference on plot.ly for bordercolor . The 'bordercolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bordercolorsrc"] @bordercolorsrc.setter def bordercolorsrc(self, val): self["bordercolorsrc"] = val # font # ---- @property def font(self): """ Sets the font used in hover labels. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.candlestick.hoverlabel.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.candlestick.hoverlabel.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # namelength # ---------- @property def namelength(self): """ Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. The 'namelength' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [-1, 9223372036854775807] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|numpy.ndarray """ return self["namelength"] @namelength.setter def namelength(self, val): self["namelength"] = val # namelengthsrc # ------------- @property def namelengthsrc(self): """ Sets the source reference on plot.ly for namelength . The 'namelengthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["namelengthsrc"] @namelengthsrc.setter def namelengthsrc(self, val): self["namelengthsrc"] = val # split # ----- @property def split(self): """ Show hover information (open, close, high, low) in separate labels. The 'split' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["split"] @split.setter def split(self, val): self["split"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "candlestick" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . split Show hover information (open, close, high, low) in separate labels. """ def __init__( self, arg=None, align=None, alignsrc=None, bgcolor=None, bgcolorsrc=None, bordercolor=None, bordercolorsrc=None, font=None, namelength=None, namelengthsrc=None, split=None, **kwargs ): """ Construct a new Hoverlabel object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.candlestick.Hoverlabel align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . split Show hover information (open, close, high, low) in separate labels. Returns ------- Hoverlabel """ super(Hoverlabel, self).__init__("hoverlabel") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.candlestick.Hoverlabel constructor must be a dict or an instance of plotly.graph_objs.candlestick.Hoverlabel""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.candlestick import hoverlabel as v_hoverlabel # Initialize validators # --------------------- self._validators["align"] = v_hoverlabel.AlignValidator() self._validators["alignsrc"] = v_hoverlabel.AlignsrcValidator() self._validators["bgcolor"] = v_hoverlabel.BgcolorValidator() self._validators["bgcolorsrc"] = v_hoverlabel.BgcolorsrcValidator() self._validators["bordercolor"] = v_hoverlabel.BordercolorValidator() self._validators["bordercolorsrc"] = v_hoverlabel.BordercolorsrcValidator() self._validators["font"] = v_hoverlabel.FontValidator() self._validators["namelength"] = v_hoverlabel.NamelengthValidator() self._validators["namelengthsrc"] = v_hoverlabel.NamelengthsrcValidator() self._validators["split"] = v_hoverlabel.SplitValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("alignsrc", None) self["alignsrc"] = alignsrc if alignsrc is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bgcolorsrc", None) self["bgcolorsrc"] = bgcolorsrc if bgcolorsrc is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("bordercolorsrc", None) self["bordercolorsrc"] = bordercolorsrc if bordercolorsrc is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("namelength", None) self["namelength"] = namelength if namelength is not None else _v _v = arg.pop("namelengthsrc", None) self["namelengthsrc"] = namelengthsrc if namelengthsrc is not None else _v _v = arg.pop("split", None) self["split"] = split if split is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Decreasing(_BaseTraceHierarchyType): # fillcolor # --------- @property def fillcolor(self): """ Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. The 'fillcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["fillcolor"] @fillcolor.setter def fillcolor(self, val): self["fillcolor"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.candlestick.decreasing.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: color Sets the color of line bounding the box(es). width Sets the width (in px) of line bounding the box(es). Returns ------- plotly.graph_objs.candlestick.decreasing.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "candlestick" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ fillcolor Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. line plotly.graph_objects.candlestick.decreasing.Line instance or dict with compatible properties """ def __init__(self, arg=None, fillcolor=None, line=None, **kwargs): """ Construct a new Decreasing object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.candlestick.Decreasing fillcolor Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. line plotly.graph_objects.candlestick.decreasing.Line instance or dict with compatible properties Returns ------- Decreasing """ super(Decreasing, self).__init__("decreasing") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.candlestick.Decreasing constructor must be a dict or an instance of plotly.graph_objs.candlestick.Decreasing""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.candlestick import decreasing as v_decreasing # Initialize validators # --------------------- self._validators["fillcolor"] = v_decreasing.FillcolorValidator() self._validators["line"] = v_decreasing.LineValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("fillcolor", None) self["fillcolor"] = fillcolor if fillcolor is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = [ "Decreasing", "Hoverlabel", "Increasing", "Line", "Stream", "decreasing", "hoverlabel", "increasing", ] from plotly.graph_objs.candlestick import increasing from plotly.graph_objs.candlestick import hoverlabel from plotly.graph_objs.candlestick import decreasing plotly-4.4.1+dfsg.orig/plotly/graph_objs/candlestick/decreasing/0000755000175000017500000000000013573746613024321 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/candlestick/decreasing/__init__.py0000644000175000017500000001325513573721545026435 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the color of line bounding the box(es). The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # width # ----- @property def width(self): """ Sets the width (in px) of line bounding the box(es). The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "candlestick.decreasing" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the color of line bounding the box(es). width Sets the width (in px) of line bounding the box(es). """ def __init__(self, arg=None, color=None, width=None, **kwargs): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.candlestick.decreasing.Line color Sets the color of line bounding the box(es). width Sets the width (in px) of line bounding the box(es). Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.candlestick.decreasing.Line constructor must be a dict or an instance of plotly.graph_objs.candlestick.decreasing.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.candlestick.decreasing import line as v_line # Initialize validators # --------------------- self._validators["color"] = v_line.ColorValidator() self._validators["width"] = v_line.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Line"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/choroplethmapbox/0000755000175000017500000000000013573746613023307 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/choroplethmapbox/unselected/0000755000175000017500000000000013573746613025442 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/choroplethmapbox/unselected/__init__.py0000644000175000017500000000556413573721545027562 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # opacity # ------- @property def opacity(self): """ Sets the marker opacity of unselected points, applied only when a selection exists. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "choroplethmapbox.unselected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ opacity Sets the marker opacity of unselected points, applied only when a selection exists. """ def __init__(self, arg=None, opacity=None, **kwargs): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.choroplethmapbox.unselected.Marker opacity Sets the marker opacity of unselected points, applied only when a selection exists. Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.choroplethmapbox.unselected.Marker constructor must be a dict or an instance of plotly.graph_objs.choroplethmapbox.unselected.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.choroplethmapbox.unselected import marker as v_marker # Initialize validators # --------------------- self._validators["opacity"] = v_marker.OpacityValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Marker"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/choroplethmapbox/hoverlabel/0000755000175000017500000000000013573746613025432 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/choroplethmapbox/hoverlabel/__init__.py0000644000175000017500000002551513573721546027551 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "choroplethmapbox.hoverlabel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Font object Sets the font used in hover labels. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.choroplethmapbox.hoverlabel.Font color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.choroplethmapbox.hoverlabel.Font constructor must be a dict or an instance of plotly.graph_objs.choroplethmapbox.hoverlabel.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.choroplethmapbox.hoverlabel import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["colorsrc"] = v_font.ColorsrcValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["familysrc"] = v_font.FamilysrcValidator() self._validators["size"] = v_font.SizeValidator() self._validators["sizesrc"] = v_font.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/choroplethmapbox/colorbar/0000755000175000017500000000000013573746613025112 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/choroplethmapbox/colorbar/title/0000755000175000017500000000000013573746613026233 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/choroplethmapbox/colorbar/title/__init__.py0000644000175000017500000002060213573721546030342 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "choroplethmapbox.colorbar.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.choroplethmapbox.colorbar.title.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.choroplethmapbox.colorbar.title.Font constructor must be a dict or an instance of plotly.graph_objs.choroplethmapbox.colorbar.title.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.choroplethmapbox.colorbar.title import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/choroplethmapbox/colorbar/__init__.py0000644000175000017500000006102113573721546027221 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Title(_BaseTraceHierarchyType): # font # ---- @property def font(self): """ Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.choroplethmapbox.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.choroplethmapbox.colorbar.title.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # side # ---- @property def side(self): """ Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- Any """ return self["side"] @side.setter def side(self, val): self["side"] = val # text # ---- @property def text(self): """ Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "choroplethmapbox.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """ def __init__(self, arg=None, font=None, side=None, text=None, **kwargs): """ Construct a new Title object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.choroplethmapbox.colorbar.Title font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- Title """ super(Title, self).__init__("title") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.choroplethmapbox.colorbar.Title constructor must be a dict or an instance of plotly.graph_objs.choroplethmapbox.colorbar.Title""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.choroplethmapbox.colorbar import title as v_title # Initialize validators # --------------------- self._validators["font"] = v_title.FontValidator() self._validators["side"] = v_title.SideValidator() self._validators["text"] = v_title.TextValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("side", None) self["side"] = side if side is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickformatstop(_BaseTraceHierarchyType): # dtickrange # ---------- @property def dtickrange(self): """ range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" The 'dtickrange' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'dtickrange[0]' property accepts values of any type (1) The 'dtickrange[1]' property accepts values of any type Returns ------- list """ return self["dtickrange"] @dtickrange.setter def dtickrange(self, val): self["dtickrange"] = val # enabled # ------- @property def enabled(self): """ Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. The 'enabled' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["enabled"] @enabled.setter def enabled(self, val): self["enabled"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # value # ----- @property def value(self): """ string - dtickformat for described zoom level, the same as "tickformat" The 'value' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "choroplethmapbox.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """ def __init__( self, arg=None, dtickrange=None, enabled=None, name=None, templateitemname=None, value=None, **kwargs ): """ Construct a new Tickformatstop object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.choroplethmapbox.color bar.Tickformatstop dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- Tickformatstop """ super(Tickformatstop, self).__init__("tickformatstops") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.choroplethmapbox.colorbar.Tickformatstop constructor must be a dict or an instance of plotly.graph_objs.choroplethmapbox.colorbar.Tickformatstop""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.choroplethmapbox.colorbar import ( tickformatstop as v_tickformatstop, ) # Initialize validators # --------------------- self._validators["dtickrange"] = v_tickformatstop.DtickrangeValidator() self._validators["enabled"] = v_tickformatstop.EnabledValidator() self._validators["name"] = v_tickformatstop.NameValidator() self._validators[ "templateitemname" ] = v_tickformatstop.TemplateitemnameValidator() self._validators["value"] = v_tickformatstop.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtickrange", None) self["dtickrange"] = dtickrange if dtickrange is not None else _v _v = arg.pop("enabled", None) self["enabled"] = enabled if enabled is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "choroplethmapbox.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Tickfont object Sets the color bar's tick label font Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.choroplethmapbox.colorbar.Tickfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Tickfont """ super(Tickfont, self).__init__("tickfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.choroplethmapbox.colorbar.Tickfont constructor must be a dict or an instance of plotly.graph_objs.choroplethmapbox.colorbar.Tickfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.choroplethmapbox.colorbar import tickfont as v_tickfont # Initialize validators # --------------------- self._validators["color"] = v_tickfont.ColorValidator() self._validators["family"] = v_tickfont.FamilyValidator() self._validators["size"] = v_tickfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Tickfont", "Tickformatstop", "Tickformatstop", "Title", "title"] from plotly.graph_objs.choroplethmapbox.colorbar import title plotly-4.4.1+dfsg.orig/plotly/graph_objs/choroplethmapbox/marker/0000755000175000017500000000000013573746613024570 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/choroplethmapbox/marker/__init__.py0000644000175000017500000002006613573721545026702 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # width # ----- @property def width(self): """ Sets the width (in px) of the lines bounding the marker points. The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["width"] @width.setter def width(self, val): self["width"] = val # widthsrc # -------- @property def widthsrc(self): """ Sets the source reference on plot.ly for width . The 'widthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["widthsrc"] @widthsrc.setter def widthsrc(self, val): self["widthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "choroplethmapbox.marker" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. colorsrc Sets the source reference on plot.ly for color . width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . """ def __init__( self, arg=None, color=None, colorsrc=None, width=None, widthsrc=None, **kwargs ): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.choroplethmapbox.marker.Line color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. colorsrc Sets the source reference on plot.ly for color . width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.choroplethmapbox.marker.Line constructor must be a dict or an instance of plotly.graph_objs.choroplethmapbox.marker.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.choroplethmapbox.marker import line as v_line # Initialize validators # --------------------- self._validators["color"] = v_line.ColorValidator() self._validators["colorsrc"] = v_line.ColorsrcValidator() self._validators["width"] = v_line.WidthValidator() self._validators["widthsrc"] = v_line.WidthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v _v = arg.pop("widthsrc", None) self["widthsrc"] = widthsrc if widthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Line"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/choroplethmapbox/__init__.py0000644000175000017500000031222313573721547025422 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Unselected(_BaseTraceHierarchyType): # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.choroplethmapbox.unselected.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: opacity Sets the marker opacity of unselected points, applied only when a selection exists. Returns ------- plotly.graph_objs.choroplethmapbox.unselected.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "choroplethmapbox" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ marker plotly.graph_objects.choroplethmapbox.unselected.Marker instance or dict with compatible properties """ def __init__(self, arg=None, marker=None, **kwargs): """ Construct a new Unselected object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.choroplethmapbox.Unselected marker plotly.graph_objects.choroplethmapbox.unselected.Marker instance or dict with compatible properties Returns ------- Unselected """ super(Unselected, self).__init__("unselected") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.choroplethmapbox.Unselected constructor must be a dict or an instance of plotly.graph_objs.choroplethmapbox.Unselected""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.choroplethmapbox import unselected as v_unselected # Initialize validators # --------------------- self._validators["marker"] = v_unselected.MarkerValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Stream(_BaseTraceHierarchyType): # maxpoints # --------- @property def maxpoints(self): """ Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. The 'maxpoints' property is a number and may be specified as: - An int or float in the interval [0, 10000] Returns ------- int|float """ return self["maxpoints"] @maxpoints.setter def maxpoints(self, val): self["maxpoints"] = val # token # ----- @property def token(self): """ The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. The 'token' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["token"] @token.setter def token(self, val): self["token"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "choroplethmapbox" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """ def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): """ Construct a new Stream object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.choroplethmapbox.Stream maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- Stream """ super(Stream, self).__init__("stream") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.choroplethmapbox.Stream constructor must be a dict or an instance of plotly.graph_objs.choroplethmapbox.Stream""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.choroplethmapbox import stream as v_stream # Initialize validators # --------------------- self._validators["maxpoints"] = v_stream.MaxpointsValidator() self._validators["token"] = v_stream.TokenValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("maxpoints", None) self["maxpoints"] = maxpoints if maxpoints is not None else _v _v = arg.pop("token", None) self["token"] = token if token is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Selected(_BaseTraceHierarchyType): # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.choroplethmapbox.selected.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: opacity Sets the marker opacity of selected points. Returns ------- plotly.graph_objs.choroplethmapbox.selected.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "choroplethmapbox" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ marker plotly.graph_objects.choroplethmapbox.selected.Marker instance or dict with compatible properties """ def __init__(self, arg=None, marker=None, **kwargs): """ Construct a new Selected object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.choroplethmapbox.Selected marker plotly.graph_objects.choroplethmapbox.selected.Marker instance or dict with compatible properties Returns ------- Selected """ super(Selected, self).__init__("selected") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.choroplethmapbox.Selected constructor must be a dict or an instance of plotly.graph_objs.choroplethmapbox.Selected""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.choroplethmapbox import selected as v_selected # Initialize validators # --------------------- self._validators["marker"] = v_selected.MarkerValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.choroplethmapbox.marker.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. colorsrc Sets the source reference on plot.ly for color . width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . Returns ------- plotly.graph_objs.choroplethmapbox.marker.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the locations. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # opacitysrc # ---------- @property def opacitysrc(self): """ Sets the source reference on plot.ly for opacity . The 'opacitysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["opacitysrc"] @opacitysrc.setter def opacitysrc(self, val): self["opacitysrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "choroplethmapbox" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ line plotly.graph_objects.choroplethmapbox.marker.Line instance or dict with compatible properties opacity Sets the opacity of the locations. opacitysrc Sets the source reference on plot.ly for opacity . """ def __init__(self, arg=None, line=None, opacity=None, opacitysrc=None, **kwargs): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.choroplethmapbox.Marker line plotly.graph_objects.choroplethmapbox.marker.Line instance or dict with compatible properties opacity Sets the opacity of the locations. opacitysrc Sets the source reference on plot.ly for opacity . Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.choroplethmapbox.Marker constructor must be a dict or an instance of plotly.graph_objs.choroplethmapbox.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.choroplethmapbox import marker as v_marker # Initialize validators # --------------------- self._validators["line"] = v_marker.LineValidator() self._validators["opacity"] = v_marker.OpacityValidator() self._validators["opacitysrc"] = v_marker.OpacitysrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("line", None) self["line"] = line if line is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("opacitysrc", None) self["opacitysrc"] = opacitysrc if opacitysrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Hoverlabel(_BaseTraceHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'right', 'auto'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["align"] @align.setter def align(self, val): self["align"] = val # alignsrc # -------- @property def alignsrc(self): """ Sets the source reference on plot.ly for align . The 'alignsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["alignsrc"] @alignsrc.setter def alignsrc(self, val): self["alignsrc"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the hover labels for this trace The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bgcolorsrc # ---------- @property def bgcolorsrc(self): """ Sets the source reference on plot.ly for bgcolor . The 'bgcolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bgcolorsrc"] @bgcolorsrc.setter def bgcolorsrc(self, val): self["bgcolorsrc"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the border color of the hover labels for this trace. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # bordercolorsrc # -------------- @property def bordercolorsrc(self): """ Sets the source reference on plot.ly for bordercolor . The 'bordercolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bordercolorsrc"] @bordercolorsrc.setter def bordercolorsrc(self, val): self["bordercolorsrc"] = val # font # ---- @property def font(self): """ Sets the font used in hover labels. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.choroplethmapbox.hoverlabel.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.choroplethmapbox.hoverlabel.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # namelength # ---------- @property def namelength(self): """ Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. The 'namelength' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [-1, 9223372036854775807] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|numpy.ndarray """ return self["namelength"] @namelength.setter def namelength(self, val): self["namelength"] = val # namelengthsrc # ------------- @property def namelengthsrc(self): """ Sets the source reference on plot.ly for namelength . The 'namelengthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["namelengthsrc"] @namelengthsrc.setter def namelengthsrc(self, val): self["namelengthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "choroplethmapbox" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """ def __init__( self, arg=None, align=None, alignsrc=None, bgcolor=None, bgcolorsrc=None, bordercolor=None, bordercolorsrc=None, font=None, namelength=None, namelengthsrc=None, **kwargs ): """ Construct a new Hoverlabel object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.choroplethmapbox.Hoverlabel align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- Hoverlabel """ super(Hoverlabel, self).__init__("hoverlabel") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.choroplethmapbox.Hoverlabel constructor must be a dict or an instance of plotly.graph_objs.choroplethmapbox.Hoverlabel""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.choroplethmapbox import hoverlabel as v_hoverlabel # Initialize validators # --------------------- self._validators["align"] = v_hoverlabel.AlignValidator() self._validators["alignsrc"] = v_hoverlabel.AlignsrcValidator() self._validators["bgcolor"] = v_hoverlabel.BgcolorValidator() self._validators["bgcolorsrc"] = v_hoverlabel.BgcolorsrcValidator() self._validators["bordercolor"] = v_hoverlabel.BordercolorValidator() self._validators["bordercolorsrc"] = v_hoverlabel.BordercolorsrcValidator() self._validators["font"] = v_hoverlabel.FontValidator() self._validators["namelength"] = v_hoverlabel.NamelengthValidator() self._validators["namelengthsrc"] = v_hoverlabel.NamelengthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("alignsrc", None) self["alignsrc"] = alignsrc if alignsrc is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bgcolorsrc", None) self["bgcolorsrc"] = bgcolorsrc if bgcolorsrc is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("bordercolorsrc", None) self["bordercolorsrc"] = bordercolorsrc if bordercolorsrc is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("namelength", None) self["namelength"] = namelength if namelength is not None else _v _v = arg.pop("namelengthsrc", None) self["namelengthsrc"] = namelengthsrc if namelengthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class ColorBar(_BaseTraceHierarchyType): # bgcolor # ------- @property def bgcolor(self): """ Sets the color of padded area. The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the axis line color. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # borderwidth # ----------- @property def borderwidth(self): """ Sets the width (in px) or the border enclosing this color bar. The 'borderwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["borderwidth"] @borderwidth.setter def borderwidth(self, val): self["borderwidth"] = val # dtick # ----- @property def dtick(self): """ Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" The 'dtick' property accepts values of any type Returns ------- Any """ return self["dtick"] @dtick.setter def dtick(self, val): self["dtick"] = val # exponentformat # -------------- @property def exponentformat(self): """ Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. The 'exponentformat' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'e', 'E', 'power', 'SI', 'B'] Returns ------- Any """ return self["exponentformat"] @exponentformat.setter def exponentformat(self, val): self["exponentformat"] = val # len # --- @property def len(self): """ Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. The 'len' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["len"] @len.setter def len(self, val): self["len"] = val # lenmode # ------- @property def lenmode(self): """ Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. The 'lenmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["lenmode"] @lenmode.setter def lenmode(self, val): self["lenmode"] = val # nticks # ------ @property def nticks(self): """ Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". The 'nticks' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nticks"] @nticks.setter def nticks(self, val): self["nticks"] = val # outlinecolor # ------------ @property def outlinecolor(self): """ Sets the axis line color. The 'outlinecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["outlinecolor"] @outlinecolor.setter def outlinecolor(self, val): self["outlinecolor"] = val # outlinewidth # ------------ @property def outlinewidth(self): """ Sets the width (in px) of the axis line. The 'outlinewidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["outlinewidth"] @outlinewidth.setter def outlinewidth(self, val): self["outlinewidth"] = val # separatethousands # ----------------- @property def separatethousands(self): """ If "true", even 4-digit integers are separated The 'separatethousands' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["separatethousands"] @separatethousands.setter def separatethousands(self, val): self["separatethousands"] = val # showexponent # ------------ @property def showexponent(self): """ If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. The 'showexponent' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showexponent"] @showexponent.setter def showexponent(self, val): self["showexponent"] = val # showticklabels # -------------- @property def showticklabels(self): """ Determines whether or not the tick labels are drawn. The 'showticklabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showticklabels"] @showticklabels.setter def showticklabels(self, val): self["showticklabels"] = val # showtickprefix # -------------- @property def showtickprefix(self): """ If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. The 'showtickprefix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showtickprefix"] @showtickprefix.setter def showtickprefix(self, val): self["showtickprefix"] = val # showticksuffix # -------------- @property def showticksuffix(self): """ Same as `showtickprefix` but for tick suffixes. The 'showticksuffix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showticksuffix"] @showticksuffix.setter def showticksuffix(self, val): self["showticksuffix"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # thicknessmode # ------------- @property def thicknessmode(self): """ Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. The 'thicknessmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["thicknessmode"] @thicknessmode.setter def thicknessmode(self, val): self["thicknessmode"] = val # tick0 # ----- @property def tick0(self): """ Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. The 'tick0' property accepts values of any type Returns ------- Any """ return self["tick0"] @tick0.setter def tick0(self, val): self["tick0"] = val # tickangle # --------- @property def tickangle(self): """ Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. The 'tickangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["tickangle"] @tickangle.setter def tickangle(self, val): self["tickangle"] = val # tickcolor # --------- @property def tickcolor(self): """ Sets the tick color. The 'tickcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["tickcolor"] @tickcolor.setter def tickcolor(self, val): self["tickcolor"] = val # tickfont # -------- @property def tickfont(self): """ Sets the color bar's tick label font The 'tickfont' property is an instance of Tickfont that may be specified as: - An instance of plotly.graph_objs.choroplethmapbox.colorbar.Tickfont - A dict of string/value properties that will be passed to the Tickfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.choroplethmapbox.colorbar.Tickfont """ return self["tickfont"] @tickfont.setter def tickfont(self, val): self["tickfont"] = val # tickformat # ---------- @property def tickformat(self): """ Sets the tick label formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'tickformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickformat"] @tickformat.setter def tickformat(self, val): self["tickformat"] = val # tickformatstops # --------------- @property def tickformatstops(self): """ The 'tickformatstops' property is a tuple of instances of Tickformatstop that may be specified as: - A list or tuple of instances of plotly.graph_objs.choroplethmapbox.colorbar.Tickformatstop - A list or tuple of dicts of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- tuple[plotly.graph_objs.choroplethmapbox.colorbar.Tickformatstop] """ return self["tickformatstops"] @tickformatstops.setter def tickformatstops(self, val): self["tickformatstops"] = val # tickformatstopdefaults # ---------------------- @property def tickformatstopdefaults(self): """ When used in a template (as layout.template.data.choroplethmapb ox.colorbar.tickformatstopdefaults), sets the default property values to use for elements of choroplethmapbox.colorbar.tickformatstops The 'tickformatstopdefaults' property is an instance of Tickformatstop that may be specified as: - An instance of plotly.graph_objs.choroplethmapbox.colorbar.Tickformatstop - A dict of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: Returns ------- plotly.graph_objs.choroplethmapbox.colorbar.Tickformatstop """ return self["tickformatstopdefaults"] @tickformatstopdefaults.setter def tickformatstopdefaults(self, val): self["tickformatstopdefaults"] = val # ticklen # ------- @property def ticklen(self): """ Sets the tick length (in px). The 'ticklen' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ticklen"] @ticklen.setter def ticklen(self, val): self["ticklen"] = val # tickmode # -------- @property def tickmode(self): """ Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). The 'tickmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'linear', 'array'] Returns ------- Any """ return self["tickmode"] @tickmode.setter def tickmode(self, val): self["tickmode"] = val # tickprefix # ---------- @property def tickprefix(self): """ Sets a tick label prefix. The 'tickprefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickprefix"] @tickprefix.setter def tickprefix(self, val): self["tickprefix"] = val # ticks # ----- @property def ticks(self): """ Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. The 'ticks' property is an enumeration that may be specified as: - One of the following enumeration values: ['outside', 'inside', ''] Returns ------- Any """ return self["ticks"] @ticks.setter def ticks(self, val): self["ticks"] = val # ticksuffix # ---------- @property def ticksuffix(self): """ Sets a tick label suffix. The 'ticksuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ticksuffix"] @ticksuffix.setter def ticksuffix(self, val): self["ticksuffix"] = val # ticktext # -------- @property def ticktext(self): """ Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. The 'ticktext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ticktext"] @ticktext.setter def ticktext(self, val): self["ticktext"] = val # ticktextsrc # ----------- @property def ticktextsrc(self): """ Sets the source reference on plot.ly for ticktext . The 'ticktextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ticktextsrc"] @ticktextsrc.setter def ticktextsrc(self, val): self["ticktextsrc"] = val # tickvals # -------- @property def tickvals(self): """ Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. The 'tickvals' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["tickvals"] @tickvals.setter def tickvals(self, val): self["tickvals"] = val # tickvalssrc # ----------- @property def tickvalssrc(self): """ Sets the source reference on plot.ly for tickvals . The 'tickvalssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tickvalssrc"] @tickvalssrc.setter def tickvalssrc(self, val): self["tickvalssrc"] = val # tickwidth # --------- @property def tickwidth(self): """ Sets the tick width (in px). The 'tickwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["tickwidth"] @tickwidth.setter def tickwidth(self, val): self["tickwidth"] = val # title # ----- @property def title(self): """ The 'title' property is an instance of Title that may be specified as: - An instance of plotly.graph_objs.choroplethmapbox.colorbar.Title - A dict of string/value properties that will be passed to the Title constructor Supported dict properties: font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- plotly.graph_objs.choroplethmapbox.colorbar.Title """ return self["title"] @title.setter def title(self, val): self["title"] = val # titlefont # --------- @property def titlefont(self): """ Deprecated: Please use choroplethmapbox.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.choroplethmapbox.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- """ return self["titlefont"] @titlefont.setter def titlefont(self, val): self["titlefont"] = val # titleside # --------- @property def titleside(self): """ Deprecated: Please use choroplethmapbox.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- """ return self["titleside"] @titleside.setter def titleside(self, val): self["titleside"] = val # x # - @property def x(self): """ Sets the x position of the color bar (in plot fraction). The 'x' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["x"] @x.setter def x(self, val): self["x"] = val # xanchor # ------- @property def xanchor(self): """ Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. The 'xanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'center', 'right'] Returns ------- Any """ return self["xanchor"] @xanchor.setter def xanchor(self, val): self["xanchor"] = val # xpad # ---- @property def xpad(self): """ Sets the amount of padding (in px) along the x direction. The 'xpad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["xpad"] @xpad.setter def xpad(self, val): self["xpad"] = val # y # - @property def y(self): """ Sets the y position of the color bar (in plot fraction). The 'y' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["y"] @y.setter def y(self, val): self["y"] = val # yanchor # ------- @property def yanchor(self): """ Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. The 'yanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['top', 'middle', 'bottom'] Returns ------- Any """ return self["yanchor"] @yanchor.setter def yanchor(self, val): self["yanchor"] = val # ypad # ---- @property def ypad(self): """ Sets the amount of padding (in px) along the y direction. The 'ypad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ypad"] @ypad.setter def ypad(self, val): self["ypad"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "choroplethmapbox" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.choroplethmapbox.colorb ar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.chorop lethmapbox.colorbar.tickformatstopdefaults), sets the default property values to use for elements of choroplethmapbox.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.choroplethmapbox.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use choroplethmapbox.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use choroplethmapbox.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """ _mapped_properties = { "titlefont": ("title", "font"), "titleside": ("title", "side"), } def __init__( self, arg=None, bgcolor=None, bordercolor=None, borderwidth=None, dtick=None, exponentformat=None, len=None, lenmode=None, nticks=None, outlinecolor=None, outlinewidth=None, separatethousands=None, showexponent=None, showticklabels=None, showtickprefix=None, showticksuffix=None, thickness=None, thicknessmode=None, tick0=None, tickangle=None, tickcolor=None, tickfont=None, tickformat=None, tickformatstops=None, tickformatstopdefaults=None, ticklen=None, tickmode=None, tickprefix=None, ticks=None, ticksuffix=None, ticktext=None, ticktextsrc=None, tickvals=None, tickvalssrc=None, tickwidth=None, title=None, titlefont=None, titleside=None, x=None, xanchor=None, xpad=None, y=None, yanchor=None, ypad=None, **kwargs ): """ Construct a new ColorBar object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.choroplethmapbox.ColorBar bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.choroplethmapbox.colorb ar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.chorop lethmapbox.colorbar.tickformatstopdefaults), sets the default property values to use for elements of choroplethmapbox.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.choroplethmapbox.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use choroplethmapbox.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use choroplethmapbox.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- ColorBar """ super(ColorBar, self).__init__("colorbar") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.choroplethmapbox.ColorBar constructor must be a dict or an instance of plotly.graph_objs.choroplethmapbox.ColorBar""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.choroplethmapbox import colorbar as v_colorbar # Initialize validators # --------------------- self._validators["bgcolor"] = v_colorbar.BgcolorValidator() self._validators["bordercolor"] = v_colorbar.BordercolorValidator() self._validators["borderwidth"] = v_colorbar.BorderwidthValidator() self._validators["dtick"] = v_colorbar.DtickValidator() self._validators["exponentformat"] = v_colorbar.ExponentformatValidator() self._validators["len"] = v_colorbar.LenValidator() self._validators["lenmode"] = v_colorbar.LenmodeValidator() self._validators["nticks"] = v_colorbar.NticksValidator() self._validators["outlinecolor"] = v_colorbar.OutlinecolorValidator() self._validators["outlinewidth"] = v_colorbar.OutlinewidthValidator() self._validators["separatethousands"] = v_colorbar.SeparatethousandsValidator() self._validators["showexponent"] = v_colorbar.ShowexponentValidator() self._validators["showticklabels"] = v_colorbar.ShowticklabelsValidator() self._validators["showtickprefix"] = v_colorbar.ShowtickprefixValidator() self._validators["showticksuffix"] = v_colorbar.ShowticksuffixValidator() self._validators["thickness"] = v_colorbar.ThicknessValidator() self._validators["thicknessmode"] = v_colorbar.ThicknessmodeValidator() self._validators["tick0"] = v_colorbar.Tick0Validator() self._validators["tickangle"] = v_colorbar.TickangleValidator() self._validators["tickcolor"] = v_colorbar.TickcolorValidator() self._validators["tickfont"] = v_colorbar.TickfontValidator() self._validators["tickformat"] = v_colorbar.TickformatValidator() self._validators["tickformatstops"] = v_colorbar.TickformatstopsValidator() self._validators[ "tickformatstopdefaults" ] = v_colorbar.TickformatstopValidator() self._validators["ticklen"] = v_colorbar.TicklenValidator() self._validators["tickmode"] = v_colorbar.TickmodeValidator() self._validators["tickprefix"] = v_colorbar.TickprefixValidator() self._validators["ticks"] = v_colorbar.TicksValidator() self._validators["ticksuffix"] = v_colorbar.TicksuffixValidator() self._validators["ticktext"] = v_colorbar.TicktextValidator() self._validators["ticktextsrc"] = v_colorbar.TicktextsrcValidator() self._validators["tickvals"] = v_colorbar.TickvalsValidator() self._validators["tickvalssrc"] = v_colorbar.TickvalssrcValidator() self._validators["tickwidth"] = v_colorbar.TickwidthValidator() self._validators["title"] = v_colorbar.TitleValidator() self._validators["x"] = v_colorbar.XValidator() self._validators["xanchor"] = v_colorbar.XanchorValidator() self._validators["xpad"] = v_colorbar.XpadValidator() self._validators["y"] = v_colorbar.YValidator() self._validators["yanchor"] = v_colorbar.YanchorValidator() self._validators["ypad"] = v_colorbar.YpadValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("borderwidth", None) self["borderwidth"] = borderwidth if borderwidth is not None else _v _v = arg.pop("dtick", None) self["dtick"] = dtick if dtick is not None else _v _v = arg.pop("exponentformat", None) self["exponentformat"] = exponentformat if exponentformat is not None else _v _v = arg.pop("len", None) self["len"] = len if len is not None else _v _v = arg.pop("lenmode", None) self["lenmode"] = lenmode if lenmode is not None else _v _v = arg.pop("nticks", None) self["nticks"] = nticks if nticks is not None else _v _v = arg.pop("outlinecolor", None) self["outlinecolor"] = outlinecolor if outlinecolor is not None else _v _v = arg.pop("outlinewidth", None) self["outlinewidth"] = outlinewidth if outlinewidth is not None else _v _v = arg.pop("separatethousands", None) self["separatethousands"] = ( separatethousands if separatethousands is not None else _v ) _v = arg.pop("showexponent", None) self["showexponent"] = showexponent if showexponent is not None else _v _v = arg.pop("showticklabels", None) self["showticklabels"] = showticklabels if showticklabels is not None else _v _v = arg.pop("showtickprefix", None) self["showtickprefix"] = showtickprefix if showtickprefix is not None else _v _v = arg.pop("showticksuffix", None) self["showticksuffix"] = showticksuffix if showticksuffix is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("thicknessmode", None) self["thicknessmode"] = thicknessmode if thicknessmode is not None else _v _v = arg.pop("tick0", None) self["tick0"] = tick0 if tick0 is not None else _v _v = arg.pop("tickangle", None) self["tickangle"] = tickangle if tickangle is not None else _v _v = arg.pop("tickcolor", None) self["tickcolor"] = tickcolor if tickcolor is not None else _v _v = arg.pop("tickfont", None) self["tickfont"] = tickfont if tickfont is not None else _v _v = arg.pop("tickformat", None) self["tickformat"] = tickformat if tickformat is not None else _v _v = arg.pop("tickformatstops", None) self["tickformatstops"] = tickformatstops if tickformatstops is not None else _v _v = arg.pop("tickformatstopdefaults", None) self["tickformatstopdefaults"] = ( tickformatstopdefaults if tickformatstopdefaults is not None else _v ) _v = arg.pop("ticklen", None) self["ticklen"] = ticklen if ticklen is not None else _v _v = arg.pop("tickmode", None) self["tickmode"] = tickmode if tickmode is not None else _v _v = arg.pop("tickprefix", None) self["tickprefix"] = tickprefix if tickprefix is not None else _v _v = arg.pop("ticks", None) self["ticks"] = ticks if ticks is not None else _v _v = arg.pop("ticksuffix", None) self["ticksuffix"] = ticksuffix if ticksuffix is not None else _v _v = arg.pop("ticktext", None) self["ticktext"] = ticktext if ticktext is not None else _v _v = arg.pop("ticktextsrc", None) self["ticktextsrc"] = ticktextsrc if ticktextsrc is not None else _v _v = arg.pop("tickvals", None) self["tickvals"] = tickvals if tickvals is not None else _v _v = arg.pop("tickvalssrc", None) self["tickvalssrc"] = tickvalssrc if tickvalssrc is not None else _v _v = arg.pop("tickwidth", None) self["tickwidth"] = tickwidth if tickwidth is not None else _v _v = arg.pop("title", None) self["title"] = title if title is not None else _v _v = arg.pop("titlefont", None) _v = titlefont if titlefont is not None else _v if _v is not None: self["titlefont"] = _v _v = arg.pop("titleside", None) _v = titleside if titleside is not None else _v if _v is not None: self["titleside"] = _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xanchor", None) self["xanchor"] = xanchor if xanchor is not None else _v _v = arg.pop("xpad", None) self["xpad"] = xpad if xpad is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("yanchor", None) self["yanchor"] = yanchor if yanchor is not None else _v _v = arg.pop("ypad", None) self["ypad"] = ypad if ypad is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = [ "ColorBar", "Hoverlabel", "Marker", "Selected", "Stream", "Unselected", "colorbar", "hoverlabel", "marker", "selected", "unselected", ] from plotly.graph_objs.choroplethmapbox import unselected from plotly.graph_objs.choroplethmapbox import selected from plotly.graph_objs.choroplethmapbox import marker from plotly.graph_objs.choroplethmapbox import hoverlabel from plotly.graph_objs.choroplethmapbox import colorbar plotly-4.4.1+dfsg.orig/plotly/graph_objs/choroplethmapbox/selected/0000755000175000017500000000000013573746613025077 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/choroplethmapbox/selected/__init__.py0000644000175000017500000000532213573721545027207 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # opacity # ------- @property def opacity(self): """ Sets the marker opacity of selected points. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "choroplethmapbox.selected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ opacity Sets the marker opacity of selected points. """ def __init__(self, arg=None, opacity=None, **kwargs): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.choroplethmapbox.selected.Marker opacity Sets the marker opacity of selected points. Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.choroplethmapbox.selected.Marker constructor must be a dict or an instance of plotly.graph_objs.choroplethmapbox.selected.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.choroplethmapbox.selected import marker as v_marker # Initialize validators # --------------------- self._validators["opacity"] = v_marker.OpacityValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Marker"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/volume/0000755000175000017500000000000013573746613021240 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/volume/hoverlabel/0000755000175000017500000000000013573746613023363 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/volume/hoverlabel/__init__.py0000644000175000017500000002541713573721553025501 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "volume.hoverlabel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Font object Sets the font used in hover labels. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.volume.hoverlabel.Font color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.volume.hoverlabel.Font constructor must be a dict or an instance of plotly.graph_objs.volume.hoverlabel.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.volume.hoverlabel import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["colorsrc"] = v_font.ColorsrcValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["familysrc"] = v_font.FamilysrcValidator() self._validators["size"] = v_font.SizeValidator() self._validators["sizesrc"] = v_font.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/volume/colorbar/0000755000175000017500000000000013573746613023043 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/volume/colorbar/title/0000755000175000017500000000000013573746613024164 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/volume/colorbar/title/__init__.py0000644000175000017500000002052013573721553026270 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "volume.colorbar.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.volume.colorbar.title.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.volume.colorbar.title.Font constructor must be a dict or an instance of plotly.graph_objs.volume.colorbar.title.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.volume.colorbar.title import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/volume/colorbar/__init__.py0000644000175000017500000006046713573721553025165 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Title(_BaseTraceHierarchyType): # font # ---- @property def font(self): """ Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.volume.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.volume.colorbar.title.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # side # ---- @property def side(self): """ Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- Any """ return self["side"] @side.setter def side(self, val): self["side"] = val # text # ---- @property def text(self): """ Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "volume.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """ def __init__(self, arg=None, font=None, side=None, text=None, **kwargs): """ Construct a new Title object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.volume.colorbar.Title font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- Title """ super(Title, self).__init__("title") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.volume.colorbar.Title constructor must be a dict or an instance of plotly.graph_objs.volume.colorbar.Title""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.volume.colorbar import title as v_title # Initialize validators # --------------------- self._validators["font"] = v_title.FontValidator() self._validators["side"] = v_title.SideValidator() self._validators["text"] = v_title.TextValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("side", None) self["side"] = side if side is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickformatstop(_BaseTraceHierarchyType): # dtickrange # ---------- @property def dtickrange(self): """ range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" The 'dtickrange' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'dtickrange[0]' property accepts values of any type (1) The 'dtickrange[1]' property accepts values of any type Returns ------- list """ return self["dtickrange"] @dtickrange.setter def dtickrange(self, val): self["dtickrange"] = val # enabled # ------- @property def enabled(self): """ Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. The 'enabled' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["enabled"] @enabled.setter def enabled(self, val): self["enabled"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # value # ----- @property def value(self): """ string - dtickformat for described zoom level, the same as "tickformat" The 'value' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "volume.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """ def __init__( self, arg=None, dtickrange=None, enabled=None, name=None, templateitemname=None, value=None, **kwargs ): """ Construct a new Tickformatstop object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.volume.colorbar.Tickformatstop dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- Tickformatstop """ super(Tickformatstop, self).__init__("tickformatstops") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.volume.colorbar.Tickformatstop constructor must be a dict or an instance of plotly.graph_objs.volume.colorbar.Tickformatstop""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.volume.colorbar import tickformatstop as v_tickformatstop # Initialize validators # --------------------- self._validators["dtickrange"] = v_tickformatstop.DtickrangeValidator() self._validators["enabled"] = v_tickformatstop.EnabledValidator() self._validators["name"] = v_tickformatstop.NameValidator() self._validators[ "templateitemname" ] = v_tickformatstop.TemplateitemnameValidator() self._validators["value"] = v_tickformatstop.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtickrange", None) self["dtickrange"] = dtickrange if dtickrange is not None else _v _v = arg.pop("enabled", None) self["enabled"] = enabled if enabled is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "volume.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Tickfont object Sets the color bar's tick label font Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.volume.colorbar.Tickfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Tickfont """ super(Tickfont, self).__init__("tickfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.volume.colorbar.Tickfont constructor must be a dict or an instance of plotly.graph_objs.volume.colorbar.Tickfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.volume.colorbar import tickfont as v_tickfont # Initialize validators # --------------------- self._validators["color"] = v_tickfont.ColorValidator() self._validators["family"] = v_tickfont.FamilyValidator() self._validators["size"] = v_tickfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Tickfont", "Tickformatstop", "Tickformatstop", "Title", "title"] from plotly.graph_objs.volume.colorbar import title plotly-4.4.1+dfsg.orig/plotly/graph_objs/volume/caps/0000755000175000017500000000000013573746613022166 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/volume/caps/__init__.py0000644000175000017500000003304613573721553024301 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Z(_BaseTraceHierarchyType): # fill # ---- @property def fill(self): """ Sets the fill ratio of the `caps`. The default fill value of the `caps` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. The 'fill' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["fill"] @fill.setter def fill(self, val): self["fill"] = val # show # ---- @property def show(self): """ Sets the fill ratio of the `slices`. The default fill value of the z `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. The 'show' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["show"] @show.setter def show(self, val): self["show"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "volume.caps" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ fill Sets the fill ratio of the `caps`. The default fill value of the `caps` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. show Sets the fill ratio of the `slices`. The default fill value of the z `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. """ def __init__(self, arg=None, fill=None, show=None, **kwargs): """ Construct a new Z object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.volume.caps.Z fill Sets the fill ratio of the `caps`. The default fill value of the `caps` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. show Sets the fill ratio of the `slices`. The default fill value of the z `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. Returns ------- Z """ super(Z, self).__init__("z") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.volume.caps.Z constructor must be a dict or an instance of plotly.graph_objs.volume.caps.Z""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.volume.caps import z as v_z # Initialize validators # --------------------- self._validators["fill"] = v_z.FillValidator() self._validators["show"] = v_z.ShowValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("fill", None) self["fill"] = fill if fill is not None else _v _v = arg.pop("show", None) self["show"] = show if show is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Y(_BaseTraceHierarchyType): # fill # ---- @property def fill(self): """ Sets the fill ratio of the `caps`. The default fill value of the `caps` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. The 'fill' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["fill"] @fill.setter def fill(self, val): self["fill"] = val # show # ---- @property def show(self): """ Sets the fill ratio of the `slices`. The default fill value of the y `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. The 'show' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["show"] @show.setter def show(self, val): self["show"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "volume.caps" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ fill Sets the fill ratio of the `caps`. The default fill value of the `caps` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. show Sets the fill ratio of the `slices`. The default fill value of the y `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. """ def __init__(self, arg=None, fill=None, show=None, **kwargs): """ Construct a new Y object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.volume.caps.Y fill Sets the fill ratio of the `caps`. The default fill value of the `caps` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. show Sets the fill ratio of the `slices`. The default fill value of the y `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. Returns ------- Y """ super(Y, self).__init__("y") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.volume.caps.Y constructor must be a dict or an instance of plotly.graph_objs.volume.caps.Y""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.volume.caps import y as v_y # Initialize validators # --------------------- self._validators["fill"] = v_y.FillValidator() self._validators["show"] = v_y.ShowValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("fill", None) self["fill"] = fill if fill is not None else _v _v = arg.pop("show", None) self["show"] = show if show is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class X(_BaseTraceHierarchyType): # fill # ---- @property def fill(self): """ Sets the fill ratio of the `caps`. The default fill value of the `caps` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. The 'fill' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["fill"] @fill.setter def fill(self, val): self["fill"] = val # show # ---- @property def show(self): """ Sets the fill ratio of the `slices`. The default fill value of the x `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. The 'show' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["show"] @show.setter def show(self, val): self["show"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "volume.caps" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ fill Sets the fill ratio of the `caps`. The default fill value of the `caps` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. show Sets the fill ratio of the `slices`. The default fill value of the x `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. """ def __init__(self, arg=None, fill=None, show=None, **kwargs): """ Construct a new X object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.volume.caps.X fill Sets the fill ratio of the `caps`. The default fill value of the `caps` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. show Sets the fill ratio of the `slices`. The default fill value of the x `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. Returns ------- X """ super(X, self).__init__("x") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.volume.caps.X constructor must be a dict or an instance of plotly.graph_objs.volume.caps.X""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.volume.caps import x as v_x # Initialize validators # --------------------- self._validators["fill"] = v_x.FillValidator() self._validators["show"] = v_x.ShowValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("fill", None) self["fill"] = fill if fill is not None else _v _v = arg.pop("show", None) self["show"] = show if show is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["X", "Y", "Z"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/volume/slices/0000755000175000017500000000000013573746613022522 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/volume/slices/__init__.py0000644000175000017500000004365313573721553024642 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Z(_BaseTraceHierarchyType): # fill # ---- @property def fill(self): """ Sets the fill ratio of the `slices`. The default fill value of the `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. The 'fill' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["fill"] @fill.setter def fill(self, val): self["fill"] = val # locations # --------- @property def locations(self): """ Specifies the location(s) of slices on the axis. When not specified slices would be created for all points of the axis z except start and end. The 'locations' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["locations"] @locations.setter def locations(self, val): self["locations"] = val # locationssrc # ------------ @property def locationssrc(self): """ Sets the source reference on plot.ly for locations . The 'locationssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["locationssrc"] @locationssrc.setter def locationssrc(self, val): self["locationssrc"] = val # show # ---- @property def show(self): """ Determines whether or not slice planes about the z dimension are drawn. The 'show' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["show"] @show.setter def show(self, val): self["show"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "volume.slices" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ fill Sets the fill ratio of the `slices`. The default fill value of the `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. locations Specifies the location(s) of slices on the axis. When not specified slices would be created for all points of the axis z except start and end. locationssrc Sets the source reference on plot.ly for locations . show Determines whether or not slice planes about the z dimension are drawn. """ def __init__( self, arg=None, fill=None, locations=None, locationssrc=None, show=None, **kwargs ): """ Construct a new Z object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.volume.slices.Z fill Sets the fill ratio of the `slices`. The default fill value of the `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. locations Specifies the location(s) of slices on the axis. When not specified slices would be created for all points of the axis z except start and end. locationssrc Sets the source reference on plot.ly for locations . show Determines whether or not slice planes about the z dimension are drawn. Returns ------- Z """ super(Z, self).__init__("z") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.volume.slices.Z constructor must be a dict or an instance of plotly.graph_objs.volume.slices.Z""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.volume.slices import z as v_z # Initialize validators # --------------------- self._validators["fill"] = v_z.FillValidator() self._validators["locations"] = v_z.LocationsValidator() self._validators["locationssrc"] = v_z.LocationssrcValidator() self._validators["show"] = v_z.ShowValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("fill", None) self["fill"] = fill if fill is not None else _v _v = arg.pop("locations", None) self["locations"] = locations if locations is not None else _v _v = arg.pop("locationssrc", None) self["locationssrc"] = locationssrc if locationssrc is not None else _v _v = arg.pop("show", None) self["show"] = show if show is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Y(_BaseTraceHierarchyType): # fill # ---- @property def fill(self): """ Sets the fill ratio of the `slices`. The default fill value of the `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. The 'fill' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["fill"] @fill.setter def fill(self, val): self["fill"] = val # locations # --------- @property def locations(self): """ Specifies the location(s) of slices on the axis. When not specified slices would be created for all points of the axis y except start and end. The 'locations' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["locations"] @locations.setter def locations(self, val): self["locations"] = val # locationssrc # ------------ @property def locationssrc(self): """ Sets the source reference on plot.ly for locations . The 'locationssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["locationssrc"] @locationssrc.setter def locationssrc(self, val): self["locationssrc"] = val # show # ---- @property def show(self): """ Determines whether or not slice planes about the y dimension are drawn. The 'show' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["show"] @show.setter def show(self, val): self["show"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "volume.slices" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ fill Sets the fill ratio of the `slices`. The default fill value of the `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. locations Specifies the location(s) of slices on the axis. When not specified slices would be created for all points of the axis y except start and end. locationssrc Sets the source reference on plot.ly for locations . show Determines whether or not slice planes about the y dimension are drawn. """ def __init__( self, arg=None, fill=None, locations=None, locationssrc=None, show=None, **kwargs ): """ Construct a new Y object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.volume.slices.Y fill Sets the fill ratio of the `slices`. The default fill value of the `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. locations Specifies the location(s) of slices on the axis. When not specified slices would be created for all points of the axis y except start and end. locationssrc Sets the source reference on plot.ly for locations . show Determines whether or not slice planes about the y dimension are drawn. Returns ------- Y """ super(Y, self).__init__("y") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.volume.slices.Y constructor must be a dict or an instance of plotly.graph_objs.volume.slices.Y""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.volume.slices import y as v_y # Initialize validators # --------------------- self._validators["fill"] = v_y.FillValidator() self._validators["locations"] = v_y.LocationsValidator() self._validators["locationssrc"] = v_y.LocationssrcValidator() self._validators["show"] = v_y.ShowValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("fill", None) self["fill"] = fill if fill is not None else _v _v = arg.pop("locations", None) self["locations"] = locations if locations is not None else _v _v = arg.pop("locationssrc", None) self["locationssrc"] = locationssrc if locationssrc is not None else _v _v = arg.pop("show", None) self["show"] = show if show is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class X(_BaseTraceHierarchyType): # fill # ---- @property def fill(self): """ Sets the fill ratio of the `slices`. The default fill value of the `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. The 'fill' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["fill"] @fill.setter def fill(self, val): self["fill"] = val # locations # --------- @property def locations(self): """ Specifies the location(s) of slices on the axis. When not specified slices would be created for all points of the axis x except start and end. The 'locations' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["locations"] @locations.setter def locations(self, val): self["locations"] = val # locationssrc # ------------ @property def locationssrc(self): """ Sets the source reference on plot.ly for locations . The 'locationssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["locationssrc"] @locationssrc.setter def locationssrc(self, val): self["locationssrc"] = val # show # ---- @property def show(self): """ Determines whether or not slice planes about the x dimension are drawn. The 'show' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["show"] @show.setter def show(self, val): self["show"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "volume.slices" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ fill Sets the fill ratio of the `slices`. The default fill value of the `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. locations Specifies the location(s) of slices on the axis. When not specified slices would be created for all points of the axis x except start and end. locationssrc Sets the source reference on plot.ly for locations . show Determines whether or not slice planes about the x dimension are drawn. """ def __init__( self, arg=None, fill=None, locations=None, locationssrc=None, show=None, **kwargs ): """ Construct a new X object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.volume.slices.X fill Sets the fill ratio of the `slices`. The default fill value of the `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. locations Specifies the location(s) of slices on the axis. When not specified slices would be created for all points of the axis x except start and end. locationssrc Sets the source reference on plot.ly for locations . show Determines whether or not slice planes about the x dimension are drawn. Returns ------- X """ super(X, self).__init__("x") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.volume.slices.X constructor must be a dict or an instance of plotly.graph_objs.volume.slices.X""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.volume.slices import x as v_x # Initialize validators # --------------------- self._validators["fill"] = v_x.FillValidator() self._validators["locations"] = v_x.LocationsValidator() self._validators["locationssrc"] = v_x.LocationssrcValidator() self._validators["show"] = v_x.ShowValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("fill", None) self["fill"] = fill if fill is not None else _v _v = arg.pop("locations", None) self["locations"] = locations if locations is not None else _v _v = arg.pop("locationssrc", None) self["locationssrc"] = locationssrc if locationssrc is not None else _v _v = arg.pop("show", None) self["show"] = show if show is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["X", "Y", "Z"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/volume/__init__.py0000644000175000017500000041364113573721554023357 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Surface(_BaseTraceHierarchyType): # count # ----- @property def count(self): """ Sets the number of iso-surfaces between minimum and maximum iso-values. By default this value is 2 meaning that only minimum and maximum surfaces would be drawn. The 'count' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [1, 9223372036854775807] Returns ------- int """ return self["count"] @count.setter def count(self, val): self["count"] = val # fill # ---- @property def fill(self): """ Sets the fill ratio of the iso-surface. The default fill value of the surface is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. The 'fill' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["fill"] @fill.setter def fill(self, val): self["fill"] = val # pattern # ------- @property def pattern(self): """ Sets the surface pattern of the iso-surface 3-D sections. The default pattern of the surface is `all` meaning that the rest of surface elements would be shaded. The check options (either 1 or 2) could be used to draw half of the squares on the surface. Using various combinations of capital `A`, `B`, `C`, `D` and `E` may also be used to reduce the number of triangles on the iso-surfaces and creating other patterns of interest. The 'pattern' property is a flaglist and may be specified as a string containing: - Any combination of ['A', 'B', 'C', 'D', 'E'] joined with '+' characters (e.g. 'A+B') OR exactly one of ['all', 'odd', 'even'] (e.g. 'even') Returns ------- Any """ return self["pattern"] @pattern.setter def pattern(self, val): self["pattern"] = val # show # ---- @property def show(self): """ Hides/displays surfaces between minimum and maximum iso-values. The 'show' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["show"] @show.setter def show(self, val): self["show"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "volume" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ count Sets the number of iso-surfaces between minimum and maximum iso-values. By default this value is 2 meaning that only minimum and maximum surfaces would be drawn. fill Sets the fill ratio of the iso-surface. The default fill value of the surface is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. pattern Sets the surface pattern of the iso-surface 3-D sections. The default pattern of the surface is `all` meaning that the rest of surface elements would be shaded. The check options (either 1 or 2) could be used to draw half of the squares on the surface. Using various combinations of capital `A`, `B`, `C`, `D` and `E` may also be used to reduce the number of triangles on the iso-surfaces and creating other patterns of interest. show Hides/displays surfaces between minimum and maximum iso-values. """ def __init__( self, arg=None, count=None, fill=None, pattern=None, show=None, **kwargs ): """ Construct a new Surface object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.volume.Surface count Sets the number of iso-surfaces between minimum and maximum iso-values. By default this value is 2 meaning that only minimum and maximum surfaces would be drawn. fill Sets the fill ratio of the iso-surface. The default fill value of the surface is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. pattern Sets the surface pattern of the iso-surface 3-D sections. The default pattern of the surface is `all` meaning that the rest of surface elements would be shaded. The check options (either 1 or 2) could be used to draw half of the squares on the surface. Using various combinations of capital `A`, `B`, `C`, `D` and `E` may also be used to reduce the number of triangles on the iso-surfaces and creating other patterns of interest. show Hides/displays surfaces between minimum and maximum iso-values. Returns ------- Surface """ super(Surface, self).__init__("surface") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.volume.Surface constructor must be a dict or an instance of plotly.graph_objs.volume.Surface""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.volume import surface as v_surface # Initialize validators # --------------------- self._validators["count"] = v_surface.CountValidator() self._validators["fill"] = v_surface.FillValidator() self._validators["pattern"] = v_surface.PatternValidator() self._validators["show"] = v_surface.ShowValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("count", None) self["count"] = count if count is not None else _v _v = arg.pop("fill", None) self["fill"] = fill if fill is not None else _v _v = arg.pop("pattern", None) self["pattern"] = pattern if pattern is not None else _v _v = arg.pop("show", None) self["show"] = show if show is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Stream(_BaseTraceHierarchyType): # maxpoints # --------- @property def maxpoints(self): """ Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. The 'maxpoints' property is a number and may be specified as: - An int or float in the interval [0, 10000] Returns ------- int|float """ return self["maxpoints"] @maxpoints.setter def maxpoints(self, val): self["maxpoints"] = val # token # ----- @property def token(self): """ The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. The 'token' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["token"] @token.setter def token(self, val): self["token"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "volume" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """ def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): """ Construct a new Stream object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.volume.Stream maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- Stream """ super(Stream, self).__init__("stream") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.volume.Stream constructor must be a dict or an instance of plotly.graph_objs.volume.Stream""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.volume import stream as v_stream # Initialize validators # --------------------- self._validators["maxpoints"] = v_stream.MaxpointsValidator() self._validators["token"] = v_stream.TokenValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("maxpoints", None) self["maxpoints"] = maxpoints if maxpoints is not None else _v _v = arg.pop("token", None) self["token"] = token if token is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Spaceframe(_BaseTraceHierarchyType): # fill # ---- @property def fill(self): """ Sets the fill ratio of the `spaceframe` elements. The default fill value is 1 meaning that they are entirely shaded. Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. The 'fill' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["fill"] @fill.setter def fill(self, val): self["fill"] = val # show # ---- @property def show(self): """ Displays/hides tetrahedron shapes between minimum and maximum iso-values. Often useful when either caps or surfaces are disabled or filled with values less than 1. The 'show' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["show"] @show.setter def show(self, val): self["show"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "volume" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ fill Sets the fill ratio of the `spaceframe` elements. The default fill value is 1 meaning that they are entirely shaded. Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. show Displays/hides tetrahedron shapes between minimum and maximum iso-values. Often useful when either caps or surfaces are disabled or filled with values less than 1. """ def __init__(self, arg=None, fill=None, show=None, **kwargs): """ Construct a new Spaceframe object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.volume.Spaceframe fill Sets the fill ratio of the `spaceframe` elements. The default fill value is 1 meaning that they are entirely shaded. Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. show Displays/hides tetrahedron shapes between minimum and maximum iso-values. Often useful when either caps or surfaces are disabled or filled with values less than 1. Returns ------- Spaceframe """ super(Spaceframe, self).__init__("spaceframe") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.volume.Spaceframe constructor must be a dict or an instance of plotly.graph_objs.volume.Spaceframe""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.volume import spaceframe as v_spaceframe # Initialize validators # --------------------- self._validators["fill"] = v_spaceframe.FillValidator() self._validators["show"] = v_spaceframe.ShowValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("fill", None) self["fill"] = fill if fill is not None else _v _v = arg.pop("show", None) self["show"] = show if show is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Slices(_BaseTraceHierarchyType): # x # - @property def x(self): """ The 'x' property is an instance of X that may be specified as: - An instance of plotly.graph_objs.volume.slices.X - A dict of string/value properties that will be passed to the X constructor Supported dict properties: fill Sets the fill ratio of the `slices`. The default fill value of the `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. locations Specifies the location(s) of slices on the axis. When not specified slices would be created for all points of the axis x except start and end. locationssrc Sets the source reference on plot.ly for locations . show Determines whether or not slice planes about the x dimension are drawn. Returns ------- plotly.graph_objs.volume.slices.X """ return self["x"] @x.setter def x(self, val): self["x"] = val # y # - @property def y(self): """ The 'y' property is an instance of Y that may be specified as: - An instance of plotly.graph_objs.volume.slices.Y - A dict of string/value properties that will be passed to the Y constructor Supported dict properties: fill Sets the fill ratio of the `slices`. The default fill value of the `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. locations Specifies the location(s) of slices on the axis. When not specified slices would be created for all points of the axis y except start and end. locationssrc Sets the source reference on plot.ly for locations . show Determines whether or not slice planes about the y dimension are drawn. Returns ------- plotly.graph_objs.volume.slices.Y """ return self["y"] @y.setter def y(self, val): self["y"] = val # z # - @property def z(self): """ The 'z' property is an instance of Z that may be specified as: - An instance of plotly.graph_objs.volume.slices.Z - A dict of string/value properties that will be passed to the Z constructor Supported dict properties: fill Sets the fill ratio of the `slices`. The default fill value of the `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. locations Specifies the location(s) of slices on the axis. When not specified slices would be created for all points of the axis z except start and end. locationssrc Sets the source reference on plot.ly for locations . show Determines whether or not slice planes about the z dimension are drawn. Returns ------- plotly.graph_objs.volume.slices.Z """ return self["z"] @z.setter def z(self, val): self["z"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "volume" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ x plotly.graph_objects.volume.slices.X instance or dict with compatible properties y plotly.graph_objects.volume.slices.Y instance or dict with compatible properties z plotly.graph_objects.volume.slices.Z instance or dict with compatible properties """ def __init__(self, arg=None, x=None, y=None, z=None, **kwargs): """ Construct a new Slices object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.volume.Slices x plotly.graph_objects.volume.slices.X instance or dict with compatible properties y plotly.graph_objects.volume.slices.Y instance or dict with compatible properties z plotly.graph_objects.volume.slices.Z instance or dict with compatible properties Returns ------- Slices """ super(Slices, self).__init__("slices") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.volume.Slices constructor must be a dict or an instance of plotly.graph_objs.volume.Slices""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.volume import slices as v_slices # Initialize validators # --------------------- self._validators["x"] = v_slices.XValidator() self._validators["y"] = v_slices.YValidator() self._validators["z"] = v_slices.ZValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("z", None) self["z"] = z if z is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Lightposition(_BaseTraceHierarchyType): # x # - @property def x(self): """ Numeric vector, representing the X coordinate for each vertex. The 'x' property is a number and may be specified as: - An int or float in the interval [-100000, 100000] Returns ------- int|float """ return self["x"] @x.setter def x(self, val): self["x"] = val # y # - @property def y(self): """ Numeric vector, representing the Y coordinate for each vertex. The 'y' property is a number and may be specified as: - An int or float in the interval [-100000, 100000] Returns ------- int|float """ return self["y"] @y.setter def y(self, val): self["y"] = val # z # - @property def z(self): """ Numeric vector, representing the Z coordinate for each vertex. The 'z' property is a number and may be specified as: - An int or float in the interval [-100000, 100000] Returns ------- int|float """ return self["z"] @z.setter def z(self, val): self["z"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "volume" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ x Numeric vector, representing the X coordinate for each vertex. y Numeric vector, representing the Y coordinate for each vertex. z Numeric vector, representing the Z coordinate for each vertex. """ def __init__(self, arg=None, x=None, y=None, z=None, **kwargs): """ Construct a new Lightposition object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.volume.Lightposition x Numeric vector, representing the X coordinate for each vertex. y Numeric vector, representing the Y coordinate for each vertex. z Numeric vector, representing the Z coordinate for each vertex. Returns ------- Lightposition """ super(Lightposition, self).__init__("lightposition") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.volume.Lightposition constructor must be a dict or an instance of plotly.graph_objs.volume.Lightposition""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.volume import lightposition as v_lightposition # Initialize validators # --------------------- self._validators["x"] = v_lightposition.XValidator() self._validators["y"] = v_lightposition.YValidator() self._validators["z"] = v_lightposition.ZValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("z", None) self["z"] = z if z is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Lighting(_BaseTraceHierarchyType): # ambient # ------- @property def ambient(self): """ Ambient light increases overall color visibility but can wash out the image. The 'ambient' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["ambient"] @ambient.setter def ambient(self, val): self["ambient"] = val # diffuse # ------- @property def diffuse(self): """ Represents the extent that incident rays are reflected in a range of angles. The 'diffuse' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["diffuse"] @diffuse.setter def diffuse(self, val): self["diffuse"] = val # facenormalsepsilon # ------------------ @property def facenormalsepsilon(self): """ Epsilon for face normals calculation avoids math issues arising from degenerate geometry. The 'facenormalsepsilon' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["facenormalsepsilon"] @facenormalsepsilon.setter def facenormalsepsilon(self, val): self["facenormalsepsilon"] = val # fresnel # ------- @property def fresnel(self): """ Represents the reflectance as a dependency of the viewing angle; e.g. paper is reflective when viewing it from the edge of the paper (almost 90 degrees), causing shine. The 'fresnel' property is a number and may be specified as: - An int or float in the interval [0, 5] Returns ------- int|float """ return self["fresnel"] @fresnel.setter def fresnel(self, val): self["fresnel"] = val # roughness # --------- @property def roughness(self): """ Alters specular reflection; the rougher the surface, the wider and less contrasty the shine. The 'roughness' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["roughness"] @roughness.setter def roughness(self, val): self["roughness"] = val # specular # -------- @property def specular(self): """ Represents the level that incident rays are reflected in a single direction, causing shine. The 'specular' property is a number and may be specified as: - An int or float in the interval [0, 2] Returns ------- int|float """ return self["specular"] @specular.setter def specular(self, val): self["specular"] = val # vertexnormalsepsilon # -------------------- @property def vertexnormalsepsilon(self): """ Epsilon for vertex normals calculation avoids math issues arising from degenerate geometry. The 'vertexnormalsepsilon' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["vertexnormalsepsilon"] @vertexnormalsepsilon.setter def vertexnormalsepsilon(self, val): self["vertexnormalsepsilon"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "volume" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ ambient Ambient light increases overall color visibility but can wash out the image. diffuse Represents the extent that incident rays are reflected in a range of angles. facenormalsepsilon Epsilon for face normals calculation avoids math issues arising from degenerate geometry. fresnel Represents the reflectance as a dependency of the viewing angle; e.g. paper is reflective when viewing it from the edge of the paper (almost 90 degrees), causing shine. roughness Alters specular reflection; the rougher the surface, the wider and less contrasty the shine. specular Represents the level that incident rays are reflected in a single direction, causing shine. vertexnormalsepsilon Epsilon for vertex normals calculation avoids math issues arising from degenerate geometry. """ def __init__( self, arg=None, ambient=None, diffuse=None, facenormalsepsilon=None, fresnel=None, roughness=None, specular=None, vertexnormalsepsilon=None, **kwargs ): """ Construct a new Lighting object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.volume.Lighting ambient Ambient light increases overall color visibility but can wash out the image. diffuse Represents the extent that incident rays are reflected in a range of angles. facenormalsepsilon Epsilon for face normals calculation avoids math issues arising from degenerate geometry. fresnel Represents the reflectance as a dependency of the viewing angle; e.g. paper is reflective when viewing it from the edge of the paper (almost 90 degrees), causing shine. roughness Alters specular reflection; the rougher the surface, the wider and less contrasty the shine. specular Represents the level that incident rays are reflected in a single direction, causing shine. vertexnormalsepsilon Epsilon for vertex normals calculation avoids math issues arising from degenerate geometry. Returns ------- Lighting """ super(Lighting, self).__init__("lighting") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.volume.Lighting constructor must be a dict or an instance of plotly.graph_objs.volume.Lighting""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.volume import lighting as v_lighting # Initialize validators # --------------------- self._validators["ambient"] = v_lighting.AmbientValidator() self._validators["diffuse"] = v_lighting.DiffuseValidator() self._validators[ "facenormalsepsilon" ] = v_lighting.FacenormalsepsilonValidator() self._validators["fresnel"] = v_lighting.FresnelValidator() self._validators["roughness"] = v_lighting.RoughnessValidator() self._validators["specular"] = v_lighting.SpecularValidator() self._validators[ "vertexnormalsepsilon" ] = v_lighting.VertexnormalsepsilonValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("ambient", None) self["ambient"] = ambient if ambient is not None else _v _v = arg.pop("diffuse", None) self["diffuse"] = diffuse if diffuse is not None else _v _v = arg.pop("facenormalsepsilon", None) self["facenormalsepsilon"] = ( facenormalsepsilon if facenormalsepsilon is not None else _v ) _v = arg.pop("fresnel", None) self["fresnel"] = fresnel if fresnel is not None else _v _v = arg.pop("roughness", None) self["roughness"] = roughness if roughness is not None else _v _v = arg.pop("specular", None) self["specular"] = specular if specular is not None else _v _v = arg.pop("vertexnormalsepsilon", None) self["vertexnormalsepsilon"] = ( vertexnormalsepsilon if vertexnormalsepsilon is not None else _v ) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Hoverlabel(_BaseTraceHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'right', 'auto'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["align"] @align.setter def align(self, val): self["align"] = val # alignsrc # -------- @property def alignsrc(self): """ Sets the source reference on plot.ly for align . The 'alignsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["alignsrc"] @alignsrc.setter def alignsrc(self, val): self["alignsrc"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the hover labels for this trace The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bgcolorsrc # ---------- @property def bgcolorsrc(self): """ Sets the source reference on plot.ly for bgcolor . The 'bgcolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bgcolorsrc"] @bgcolorsrc.setter def bgcolorsrc(self, val): self["bgcolorsrc"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the border color of the hover labels for this trace. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # bordercolorsrc # -------------- @property def bordercolorsrc(self): """ Sets the source reference on plot.ly for bordercolor . The 'bordercolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bordercolorsrc"] @bordercolorsrc.setter def bordercolorsrc(self, val): self["bordercolorsrc"] = val # font # ---- @property def font(self): """ Sets the font used in hover labels. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.volume.hoverlabel.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.volume.hoverlabel.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # namelength # ---------- @property def namelength(self): """ Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. The 'namelength' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [-1, 9223372036854775807] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|numpy.ndarray """ return self["namelength"] @namelength.setter def namelength(self, val): self["namelength"] = val # namelengthsrc # ------------- @property def namelengthsrc(self): """ Sets the source reference on plot.ly for namelength . The 'namelengthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["namelengthsrc"] @namelengthsrc.setter def namelengthsrc(self, val): self["namelengthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "volume" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """ def __init__( self, arg=None, align=None, alignsrc=None, bgcolor=None, bgcolorsrc=None, bordercolor=None, bordercolorsrc=None, font=None, namelength=None, namelengthsrc=None, **kwargs ): """ Construct a new Hoverlabel object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.volume.Hoverlabel align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- Hoverlabel """ super(Hoverlabel, self).__init__("hoverlabel") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.volume.Hoverlabel constructor must be a dict or an instance of plotly.graph_objs.volume.Hoverlabel""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.volume import hoverlabel as v_hoverlabel # Initialize validators # --------------------- self._validators["align"] = v_hoverlabel.AlignValidator() self._validators["alignsrc"] = v_hoverlabel.AlignsrcValidator() self._validators["bgcolor"] = v_hoverlabel.BgcolorValidator() self._validators["bgcolorsrc"] = v_hoverlabel.BgcolorsrcValidator() self._validators["bordercolor"] = v_hoverlabel.BordercolorValidator() self._validators["bordercolorsrc"] = v_hoverlabel.BordercolorsrcValidator() self._validators["font"] = v_hoverlabel.FontValidator() self._validators["namelength"] = v_hoverlabel.NamelengthValidator() self._validators["namelengthsrc"] = v_hoverlabel.NamelengthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("alignsrc", None) self["alignsrc"] = alignsrc if alignsrc is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bgcolorsrc", None) self["bgcolorsrc"] = bgcolorsrc if bgcolorsrc is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("bordercolorsrc", None) self["bordercolorsrc"] = bordercolorsrc if bordercolorsrc is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("namelength", None) self["namelength"] = namelength if namelength is not None else _v _v = arg.pop("namelengthsrc", None) self["namelengthsrc"] = namelengthsrc if namelengthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Contour(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the color of the contour lines. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # show # ---- @property def show(self): """ Sets whether or not dynamic contours are shown on hover The 'show' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["show"] @show.setter def show(self, val): self["show"] = val # width # ----- @property def width(self): """ Sets the width of the contour lines. The 'width' property is a number and may be specified as: - An int or float in the interval [1, 16] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "volume" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the color of the contour lines. show Sets whether or not dynamic contours are shown on hover width Sets the width of the contour lines. """ def __init__(self, arg=None, color=None, show=None, width=None, **kwargs): """ Construct a new Contour object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.volume.Contour color Sets the color of the contour lines. show Sets whether or not dynamic contours are shown on hover width Sets the width of the contour lines. Returns ------- Contour """ super(Contour, self).__init__("contour") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.volume.Contour constructor must be a dict or an instance of plotly.graph_objs.volume.Contour""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.volume import contour as v_contour # Initialize validators # --------------------- self._validators["color"] = v_contour.ColorValidator() self._validators["show"] = v_contour.ShowValidator() self._validators["width"] = v_contour.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("show", None) self["show"] = show if show is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class ColorBar(_BaseTraceHierarchyType): # bgcolor # ------- @property def bgcolor(self): """ Sets the color of padded area. The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the axis line color. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # borderwidth # ----------- @property def borderwidth(self): """ Sets the width (in px) or the border enclosing this color bar. The 'borderwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["borderwidth"] @borderwidth.setter def borderwidth(self, val): self["borderwidth"] = val # dtick # ----- @property def dtick(self): """ Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" The 'dtick' property accepts values of any type Returns ------- Any """ return self["dtick"] @dtick.setter def dtick(self, val): self["dtick"] = val # exponentformat # -------------- @property def exponentformat(self): """ Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. The 'exponentformat' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'e', 'E', 'power', 'SI', 'B'] Returns ------- Any """ return self["exponentformat"] @exponentformat.setter def exponentformat(self, val): self["exponentformat"] = val # len # --- @property def len(self): """ Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. The 'len' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["len"] @len.setter def len(self, val): self["len"] = val # lenmode # ------- @property def lenmode(self): """ Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. The 'lenmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["lenmode"] @lenmode.setter def lenmode(self, val): self["lenmode"] = val # nticks # ------ @property def nticks(self): """ Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". The 'nticks' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nticks"] @nticks.setter def nticks(self, val): self["nticks"] = val # outlinecolor # ------------ @property def outlinecolor(self): """ Sets the axis line color. The 'outlinecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["outlinecolor"] @outlinecolor.setter def outlinecolor(self, val): self["outlinecolor"] = val # outlinewidth # ------------ @property def outlinewidth(self): """ Sets the width (in px) of the axis line. The 'outlinewidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["outlinewidth"] @outlinewidth.setter def outlinewidth(self, val): self["outlinewidth"] = val # separatethousands # ----------------- @property def separatethousands(self): """ If "true", even 4-digit integers are separated The 'separatethousands' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["separatethousands"] @separatethousands.setter def separatethousands(self, val): self["separatethousands"] = val # showexponent # ------------ @property def showexponent(self): """ If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. The 'showexponent' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showexponent"] @showexponent.setter def showexponent(self, val): self["showexponent"] = val # showticklabels # -------------- @property def showticklabels(self): """ Determines whether or not the tick labels are drawn. The 'showticklabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showticklabels"] @showticklabels.setter def showticklabels(self, val): self["showticklabels"] = val # showtickprefix # -------------- @property def showtickprefix(self): """ If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. The 'showtickprefix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showtickprefix"] @showtickprefix.setter def showtickprefix(self, val): self["showtickprefix"] = val # showticksuffix # -------------- @property def showticksuffix(self): """ Same as `showtickprefix` but for tick suffixes. The 'showticksuffix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showticksuffix"] @showticksuffix.setter def showticksuffix(self, val): self["showticksuffix"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # thicknessmode # ------------- @property def thicknessmode(self): """ Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. The 'thicknessmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["thicknessmode"] @thicknessmode.setter def thicknessmode(self, val): self["thicknessmode"] = val # tick0 # ----- @property def tick0(self): """ Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. The 'tick0' property accepts values of any type Returns ------- Any """ return self["tick0"] @tick0.setter def tick0(self, val): self["tick0"] = val # tickangle # --------- @property def tickangle(self): """ Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. The 'tickangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["tickangle"] @tickangle.setter def tickangle(self, val): self["tickangle"] = val # tickcolor # --------- @property def tickcolor(self): """ Sets the tick color. The 'tickcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["tickcolor"] @tickcolor.setter def tickcolor(self, val): self["tickcolor"] = val # tickfont # -------- @property def tickfont(self): """ Sets the color bar's tick label font The 'tickfont' property is an instance of Tickfont that may be specified as: - An instance of plotly.graph_objs.volume.colorbar.Tickfont - A dict of string/value properties that will be passed to the Tickfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.volume.colorbar.Tickfont """ return self["tickfont"] @tickfont.setter def tickfont(self, val): self["tickfont"] = val # tickformat # ---------- @property def tickformat(self): """ Sets the tick label formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'tickformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickformat"] @tickformat.setter def tickformat(self, val): self["tickformat"] = val # tickformatstops # --------------- @property def tickformatstops(self): """ The 'tickformatstops' property is a tuple of instances of Tickformatstop that may be specified as: - A list or tuple of instances of plotly.graph_objs.volume.colorbar.Tickformatstop - A list or tuple of dicts of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- tuple[plotly.graph_objs.volume.colorbar.Tickformatstop] """ return self["tickformatstops"] @tickformatstops.setter def tickformatstops(self, val): self["tickformatstops"] = val # tickformatstopdefaults # ---------------------- @property def tickformatstopdefaults(self): """ When used in a template (as layout.template.data.volume.colorbar.tickformatstopdefaults), sets the default property values to use for elements of volume.colorbar.tickformatstops The 'tickformatstopdefaults' property is an instance of Tickformatstop that may be specified as: - An instance of plotly.graph_objs.volume.colorbar.Tickformatstop - A dict of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: Returns ------- plotly.graph_objs.volume.colorbar.Tickformatstop """ return self["tickformatstopdefaults"] @tickformatstopdefaults.setter def tickformatstopdefaults(self, val): self["tickformatstopdefaults"] = val # ticklen # ------- @property def ticklen(self): """ Sets the tick length (in px). The 'ticklen' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ticklen"] @ticklen.setter def ticklen(self, val): self["ticklen"] = val # tickmode # -------- @property def tickmode(self): """ Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). The 'tickmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'linear', 'array'] Returns ------- Any """ return self["tickmode"] @tickmode.setter def tickmode(self, val): self["tickmode"] = val # tickprefix # ---------- @property def tickprefix(self): """ Sets a tick label prefix. The 'tickprefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickprefix"] @tickprefix.setter def tickprefix(self, val): self["tickprefix"] = val # ticks # ----- @property def ticks(self): """ Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. The 'ticks' property is an enumeration that may be specified as: - One of the following enumeration values: ['outside', 'inside', ''] Returns ------- Any """ return self["ticks"] @ticks.setter def ticks(self, val): self["ticks"] = val # ticksuffix # ---------- @property def ticksuffix(self): """ Sets a tick label suffix. The 'ticksuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ticksuffix"] @ticksuffix.setter def ticksuffix(self, val): self["ticksuffix"] = val # ticktext # -------- @property def ticktext(self): """ Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. The 'ticktext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ticktext"] @ticktext.setter def ticktext(self, val): self["ticktext"] = val # ticktextsrc # ----------- @property def ticktextsrc(self): """ Sets the source reference on plot.ly for ticktext . The 'ticktextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ticktextsrc"] @ticktextsrc.setter def ticktextsrc(self, val): self["ticktextsrc"] = val # tickvals # -------- @property def tickvals(self): """ Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. The 'tickvals' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["tickvals"] @tickvals.setter def tickvals(self, val): self["tickvals"] = val # tickvalssrc # ----------- @property def tickvalssrc(self): """ Sets the source reference on plot.ly for tickvals . The 'tickvalssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tickvalssrc"] @tickvalssrc.setter def tickvalssrc(self, val): self["tickvalssrc"] = val # tickwidth # --------- @property def tickwidth(self): """ Sets the tick width (in px). The 'tickwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["tickwidth"] @tickwidth.setter def tickwidth(self, val): self["tickwidth"] = val # title # ----- @property def title(self): """ The 'title' property is an instance of Title that may be specified as: - An instance of plotly.graph_objs.volume.colorbar.Title - A dict of string/value properties that will be passed to the Title constructor Supported dict properties: font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- plotly.graph_objs.volume.colorbar.Title """ return self["title"] @title.setter def title(self, val): self["title"] = val # titlefont # --------- @property def titlefont(self): """ Deprecated: Please use volume.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.volume.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- """ return self["titlefont"] @titlefont.setter def titlefont(self, val): self["titlefont"] = val # titleside # --------- @property def titleside(self): """ Deprecated: Please use volume.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- """ return self["titleside"] @titleside.setter def titleside(self, val): self["titleside"] = val # x # - @property def x(self): """ Sets the x position of the color bar (in plot fraction). The 'x' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["x"] @x.setter def x(self, val): self["x"] = val # xanchor # ------- @property def xanchor(self): """ Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. The 'xanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'center', 'right'] Returns ------- Any """ return self["xanchor"] @xanchor.setter def xanchor(self, val): self["xanchor"] = val # xpad # ---- @property def xpad(self): """ Sets the amount of padding (in px) along the x direction. The 'xpad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["xpad"] @xpad.setter def xpad(self, val): self["xpad"] = val # y # - @property def y(self): """ Sets the y position of the color bar (in plot fraction). The 'y' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["y"] @y.setter def y(self, val): self["y"] = val # yanchor # ------- @property def yanchor(self): """ Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. The 'yanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['top', 'middle', 'bottom'] Returns ------- Any """ return self["yanchor"] @yanchor.setter def yanchor(self, val): self["yanchor"] = val # ypad # ---- @property def ypad(self): """ Sets the amount of padding (in px) along the y direction. The 'ypad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ypad"] @ypad.setter def ypad(self, val): self["ypad"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "volume" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.volume.colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.volume .colorbar.tickformatstopdefaults), sets the default property values to use for elements of volume.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.volume.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use volume.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use volume.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """ _mapped_properties = { "titlefont": ("title", "font"), "titleside": ("title", "side"), } def __init__( self, arg=None, bgcolor=None, bordercolor=None, borderwidth=None, dtick=None, exponentformat=None, len=None, lenmode=None, nticks=None, outlinecolor=None, outlinewidth=None, separatethousands=None, showexponent=None, showticklabels=None, showtickprefix=None, showticksuffix=None, thickness=None, thicknessmode=None, tick0=None, tickangle=None, tickcolor=None, tickfont=None, tickformat=None, tickformatstops=None, tickformatstopdefaults=None, ticklen=None, tickmode=None, tickprefix=None, ticks=None, ticksuffix=None, ticktext=None, ticktextsrc=None, tickvals=None, tickvalssrc=None, tickwidth=None, title=None, titlefont=None, titleside=None, x=None, xanchor=None, xpad=None, y=None, yanchor=None, ypad=None, **kwargs ): """ Construct a new ColorBar object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.volume.ColorBar bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.volume.colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.volume .colorbar.tickformatstopdefaults), sets the default property values to use for elements of volume.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.volume.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use volume.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use volume.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- ColorBar """ super(ColorBar, self).__init__("colorbar") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.volume.ColorBar constructor must be a dict or an instance of plotly.graph_objs.volume.ColorBar""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.volume import colorbar as v_colorbar # Initialize validators # --------------------- self._validators["bgcolor"] = v_colorbar.BgcolorValidator() self._validators["bordercolor"] = v_colorbar.BordercolorValidator() self._validators["borderwidth"] = v_colorbar.BorderwidthValidator() self._validators["dtick"] = v_colorbar.DtickValidator() self._validators["exponentformat"] = v_colorbar.ExponentformatValidator() self._validators["len"] = v_colorbar.LenValidator() self._validators["lenmode"] = v_colorbar.LenmodeValidator() self._validators["nticks"] = v_colorbar.NticksValidator() self._validators["outlinecolor"] = v_colorbar.OutlinecolorValidator() self._validators["outlinewidth"] = v_colorbar.OutlinewidthValidator() self._validators["separatethousands"] = v_colorbar.SeparatethousandsValidator() self._validators["showexponent"] = v_colorbar.ShowexponentValidator() self._validators["showticklabels"] = v_colorbar.ShowticklabelsValidator() self._validators["showtickprefix"] = v_colorbar.ShowtickprefixValidator() self._validators["showticksuffix"] = v_colorbar.ShowticksuffixValidator() self._validators["thickness"] = v_colorbar.ThicknessValidator() self._validators["thicknessmode"] = v_colorbar.ThicknessmodeValidator() self._validators["tick0"] = v_colorbar.Tick0Validator() self._validators["tickangle"] = v_colorbar.TickangleValidator() self._validators["tickcolor"] = v_colorbar.TickcolorValidator() self._validators["tickfont"] = v_colorbar.TickfontValidator() self._validators["tickformat"] = v_colorbar.TickformatValidator() self._validators["tickformatstops"] = v_colorbar.TickformatstopsValidator() self._validators[ "tickformatstopdefaults" ] = v_colorbar.TickformatstopValidator() self._validators["ticklen"] = v_colorbar.TicklenValidator() self._validators["tickmode"] = v_colorbar.TickmodeValidator() self._validators["tickprefix"] = v_colorbar.TickprefixValidator() self._validators["ticks"] = v_colorbar.TicksValidator() self._validators["ticksuffix"] = v_colorbar.TicksuffixValidator() self._validators["ticktext"] = v_colorbar.TicktextValidator() self._validators["ticktextsrc"] = v_colorbar.TicktextsrcValidator() self._validators["tickvals"] = v_colorbar.TickvalsValidator() self._validators["tickvalssrc"] = v_colorbar.TickvalssrcValidator() self._validators["tickwidth"] = v_colorbar.TickwidthValidator() self._validators["title"] = v_colorbar.TitleValidator() self._validators["x"] = v_colorbar.XValidator() self._validators["xanchor"] = v_colorbar.XanchorValidator() self._validators["xpad"] = v_colorbar.XpadValidator() self._validators["y"] = v_colorbar.YValidator() self._validators["yanchor"] = v_colorbar.YanchorValidator() self._validators["ypad"] = v_colorbar.YpadValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("borderwidth", None) self["borderwidth"] = borderwidth if borderwidth is not None else _v _v = arg.pop("dtick", None) self["dtick"] = dtick if dtick is not None else _v _v = arg.pop("exponentformat", None) self["exponentformat"] = exponentformat if exponentformat is not None else _v _v = arg.pop("len", None) self["len"] = len if len is not None else _v _v = arg.pop("lenmode", None) self["lenmode"] = lenmode if lenmode is not None else _v _v = arg.pop("nticks", None) self["nticks"] = nticks if nticks is not None else _v _v = arg.pop("outlinecolor", None) self["outlinecolor"] = outlinecolor if outlinecolor is not None else _v _v = arg.pop("outlinewidth", None) self["outlinewidth"] = outlinewidth if outlinewidth is not None else _v _v = arg.pop("separatethousands", None) self["separatethousands"] = ( separatethousands if separatethousands is not None else _v ) _v = arg.pop("showexponent", None) self["showexponent"] = showexponent if showexponent is not None else _v _v = arg.pop("showticklabels", None) self["showticklabels"] = showticklabels if showticklabels is not None else _v _v = arg.pop("showtickprefix", None) self["showtickprefix"] = showtickprefix if showtickprefix is not None else _v _v = arg.pop("showticksuffix", None) self["showticksuffix"] = showticksuffix if showticksuffix is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("thicknessmode", None) self["thicknessmode"] = thicknessmode if thicknessmode is not None else _v _v = arg.pop("tick0", None) self["tick0"] = tick0 if tick0 is not None else _v _v = arg.pop("tickangle", None) self["tickangle"] = tickangle if tickangle is not None else _v _v = arg.pop("tickcolor", None) self["tickcolor"] = tickcolor if tickcolor is not None else _v _v = arg.pop("tickfont", None) self["tickfont"] = tickfont if tickfont is not None else _v _v = arg.pop("tickformat", None) self["tickformat"] = tickformat if tickformat is not None else _v _v = arg.pop("tickformatstops", None) self["tickformatstops"] = tickformatstops if tickformatstops is not None else _v _v = arg.pop("tickformatstopdefaults", None) self["tickformatstopdefaults"] = ( tickformatstopdefaults if tickformatstopdefaults is not None else _v ) _v = arg.pop("ticklen", None) self["ticklen"] = ticklen if ticklen is not None else _v _v = arg.pop("tickmode", None) self["tickmode"] = tickmode if tickmode is not None else _v _v = arg.pop("tickprefix", None) self["tickprefix"] = tickprefix if tickprefix is not None else _v _v = arg.pop("ticks", None) self["ticks"] = ticks if ticks is not None else _v _v = arg.pop("ticksuffix", None) self["ticksuffix"] = ticksuffix if ticksuffix is not None else _v _v = arg.pop("ticktext", None) self["ticktext"] = ticktext if ticktext is not None else _v _v = arg.pop("ticktextsrc", None) self["ticktextsrc"] = ticktextsrc if ticktextsrc is not None else _v _v = arg.pop("tickvals", None) self["tickvals"] = tickvals if tickvals is not None else _v _v = arg.pop("tickvalssrc", None) self["tickvalssrc"] = tickvalssrc if tickvalssrc is not None else _v _v = arg.pop("tickwidth", None) self["tickwidth"] = tickwidth if tickwidth is not None else _v _v = arg.pop("title", None) self["title"] = title if title is not None else _v _v = arg.pop("titlefont", None) _v = titlefont if titlefont is not None else _v if _v is not None: self["titlefont"] = _v _v = arg.pop("titleside", None) _v = titleside if titleside is not None else _v if _v is not None: self["titleside"] = _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xanchor", None) self["xanchor"] = xanchor if xanchor is not None else _v _v = arg.pop("xpad", None) self["xpad"] = xpad if xpad is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("yanchor", None) self["yanchor"] = yanchor if yanchor is not None else _v _v = arg.pop("ypad", None) self["ypad"] = ypad if ypad is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Caps(_BaseTraceHierarchyType): # x # - @property def x(self): """ The 'x' property is an instance of X that may be specified as: - An instance of plotly.graph_objs.volume.caps.X - A dict of string/value properties that will be passed to the X constructor Supported dict properties: fill Sets the fill ratio of the `caps`. The default fill value of the `caps` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. show Sets the fill ratio of the `slices`. The default fill value of the x `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. Returns ------- plotly.graph_objs.volume.caps.X """ return self["x"] @x.setter def x(self, val): self["x"] = val # y # - @property def y(self): """ The 'y' property is an instance of Y that may be specified as: - An instance of plotly.graph_objs.volume.caps.Y - A dict of string/value properties that will be passed to the Y constructor Supported dict properties: fill Sets the fill ratio of the `caps`. The default fill value of the `caps` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. show Sets the fill ratio of the `slices`. The default fill value of the y `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. Returns ------- plotly.graph_objs.volume.caps.Y """ return self["y"] @y.setter def y(self, val): self["y"] = val # z # - @property def z(self): """ The 'z' property is an instance of Z that may be specified as: - An instance of plotly.graph_objs.volume.caps.Z - A dict of string/value properties that will be passed to the Z constructor Supported dict properties: fill Sets the fill ratio of the `caps`. The default fill value of the `caps` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. show Sets the fill ratio of the `slices`. The default fill value of the z `slices` is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. Returns ------- plotly.graph_objs.volume.caps.Z """ return self["z"] @z.setter def z(self, val): self["z"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "volume" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ x plotly.graph_objects.volume.caps.X instance or dict with compatible properties y plotly.graph_objects.volume.caps.Y instance or dict with compatible properties z plotly.graph_objects.volume.caps.Z instance or dict with compatible properties """ def __init__(self, arg=None, x=None, y=None, z=None, **kwargs): """ Construct a new Caps object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.volume.Caps x plotly.graph_objects.volume.caps.X instance or dict with compatible properties y plotly.graph_objects.volume.caps.Y instance or dict with compatible properties z plotly.graph_objects.volume.caps.Z instance or dict with compatible properties Returns ------- Caps """ super(Caps, self).__init__("caps") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.volume.Caps constructor must be a dict or an instance of plotly.graph_objs.volume.Caps""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.volume import caps as v_caps # Initialize validators # --------------------- self._validators["x"] = v_caps.XValidator() self._validators["y"] = v_caps.YValidator() self._validators["z"] = v_caps.ZValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("z", None) self["z"] = z if z is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = [ "Caps", "ColorBar", "Contour", "Hoverlabel", "Lighting", "Lightposition", "Slices", "Spaceframe", "Stream", "Surface", "caps", "colorbar", "hoverlabel", "slices", ] from plotly.graph_objs.volume import slices from plotly.graph_objs.volume import hoverlabel from plotly.graph_objs.volume import colorbar from plotly.graph_objs.volume import caps plotly-4.4.1+dfsg.orig/plotly/graph_objs/funnel/0000755000175000017500000000000013573746613021220 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/funnel/connector/0000755000175000017500000000000013573746613023212 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/funnel/connector/__init__.py0000644000175000017500000001544213573721546025327 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the line color. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # dash # ---- @property def dash(self): """ Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). The 'dash' property is a string and must be specified as: - One of the following strings: ['solid', 'dot', 'dash', 'longdash', 'dashdot', 'longdashdot'] - A number that will be converted to a string Returns ------- str """ return self["dash"] @dash.setter def dash(self, val): self["dash"] = val # width # ----- @property def width(self): """ Sets the line width (in px). The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "funnel.connector" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the line color. dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). width Sets the line width (in px). """ def __init__(self, arg=None, color=None, dash=None, width=None, **kwargs): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.funnel.connector.Line color Sets the line color. dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). width Sets the line width (in px). Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.funnel.connector.Line constructor must be a dict or an instance of plotly.graph_objs.funnel.connector.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.funnel.connector import line as v_line # Initialize validators # --------------------- self._validators["color"] = v_line.ColorValidator() self._validators["dash"] = v_line.DashValidator() self._validators["width"] = v_line.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("dash", None) self["dash"] = dash if dash is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Line"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/funnel/hoverlabel/0000755000175000017500000000000013573746613023343 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/funnel/hoverlabel/__init__.py0000644000175000017500000002541713573721546025463 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "funnel.hoverlabel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Font object Sets the font used in hover labels. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.funnel.hoverlabel.Font color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.funnel.hoverlabel.Font constructor must be a dict or an instance of plotly.graph_objs.funnel.hoverlabel.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.funnel.hoverlabel import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["colorsrc"] = v_font.ColorsrcValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["familysrc"] = v_font.FamilysrcValidator() self._validators["size"] = v_font.SizeValidator() self._validators["sizesrc"] = v_font.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/funnel/marker/0000755000175000017500000000000013573746613022501 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/funnel/marker/colorbar/0000755000175000017500000000000013573746613024304 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/funnel/marker/colorbar/title/0000755000175000017500000000000013573746613025425 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/funnel/marker/colorbar/title/__init__.py0000644000175000017500000002056313573721546027542 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "funnel.marker.colorbar.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.funnel.marker.colorbar.title.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.funnel.marker.colorbar.title.Font constructor must be a dict or an instance of plotly.graph_objs.funnel.marker.colorbar.title.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.funnel.marker.colorbar.title import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/funnel/marker/colorbar/__init__.py0000644000175000017500000006073213573721546026423 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Title(_BaseTraceHierarchyType): # font # ---- @property def font(self): """ Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.funnel.marker.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.funnel.marker.colorbar.title.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # side # ---- @property def side(self): """ Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- Any """ return self["side"] @side.setter def side(self, val): self["side"] = val # text # ---- @property def text(self): """ Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "funnel.marker.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """ def __init__(self, arg=None, font=None, side=None, text=None, **kwargs): """ Construct a new Title object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.funnel.marker.colorbar.Title font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- Title """ super(Title, self).__init__("title") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.funnel.marker.colorbar.Title constructor must be a dict or an instance of plotly.graph_objs.funnel.marker.colorbar.Title""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.funnel.marker.colorbar import title as v_title # Initialize validators # --------------------- self._validators["font"] = v_title.FontValidator() self._validators["side"] = v_title.SideValidator() self._validators["text"] = v_title.TextValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("side", None) self["side"] = side if side is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickformatstop(_BaseTraceHierarchyType): # dtickrange # ---------- @property def dtickrange(self): """ range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" The 'dtickrange' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'dtickrange[0]' property accepts values of any type (1) The 'dtickrange[1]' property accepts values of any type Returns ------- list """ return self["dtickrange"] @dtickrange.setter def dtickrange(self, val): self["dtickrange"] = val # enabled # ------- @property def enabled(self): """ Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. The 'enabled' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["enabled"] @enabled.setter def enabled(self, val): self["enabled"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # value # ----- @property def value(self): """ string - dtickformat for described zoom level, the same as "tickformat" The 'value' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "funnel.marker.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """ def __init__( self, arg=None, dtickrange=None, enabled=None, name=None, templateitemname=None, value=None, **kwargs ): """ Construct a new Tickformatstop object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.funnel.marker.colorbar.Tickformatstop dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- Tickformatstop """ super(Tickformatstop, self).__init__("tickformatstops") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.funnel.marker.colorbar.Tickformatstop constructor must be a dict or an instance of plotly.graph_objs.funnel.marker.colorbar.Tickformatstop""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.funnel.marker.colorbar import ( tickformatstop as v_tickformatstop, ) # Initialize validators # --------------------- self._validators["dtickrange"] = v_tickformatstop.DtickrangeValidator() self._validators["enabled"] = v_tickformatstop.EnabledValidator() self._validators["name"] = v_tickformatstop.NameValidator() self._validators[ "templateitemname" ] = v_tickformatstop.TemplateitemnameValidator() self._validators["value"] = v_tickformatstop.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtickrange", None) self["dtickrange"] = dtickrange if dtickrange is not None else _v _v = arg.pop("enabled", None) self["enabled"] = enabled if enabled is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "funnel.marker.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Tickfont object Sets the color bar's tick label font Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.funnel.marker.colorbar.Tickfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Tickfont """ super(Tickfont, self).__init__("tickfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.funnel.marker.colorbar.Tickfont constructor must be a dict or an instance of plotly.graph_objs.funnel.marker.colorbar.Tickfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.funnel.marker.colorbar import tickfont as v_tickfont # Initialize validators # --------------------- self._validators["color"] = v_tickfont.ColorValidator() self._validators["family"] = v_tickfont.FamilyValidator() self._validators["size"] = v_tickfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Tickfont", "Tickformatstop", "Tickformatstop", "Title", "title"] from plotly.graph_objs.funnel.marker.colorbar import title plotly-4.4.1+dfsg.orig/plotly/graph_objs/funnel/marker/__init__.py0000644000175000017500000027031513573721547024621 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # autocolorscale # -------------- @property def autocolorscale(self): """ Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. The 'autocolorscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocolorscale"] @autocolorscale.setter def autocolorscale(self, val): self["autocolorscale"] = val # cauto # ----- @property def cauto(self): """ Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. The 'cauto' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["cauto"] @cauto.setter def cauto(self, val): self["cauto"] = val # cmax # ---- @property def cmax(self): """ Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. The 'cmax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmax"] @cmax.setter def cmax(self, val): self["cmax"] = val # cmid # ---- @property def cmid(self): """ Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. The 'cmid' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmid"] @cmid.setter def cmid(self, val): self["cmid"] = val # cmin # ---- @property def cmin(self): """ Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. The 'cmin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmin"] @cmin.setter def cmin(self, val): self["cmin"] = val # color # ----- @property def color(self): """ Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A number that will be interpreted as a color according to funnel.marker.line.colorscale - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # coloraxis # --------- @property def coloraxis(self): """ Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. The 'coloraxis' property is an identifier of a particular subplot, of type 'coloraxis', that may be specified as the string 'coloraxis' optionally followed by an integer >= 1 (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) Returns ------- str """ return self["coloraxis"] @coloraxis.setter def coloraxis(self, val): self["coloraxis"] = val # colorscale # ---------- @property def colorscale(self): """ Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,Earth,Electric,Vi ridis,Cividis. The 'colorscale' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # reversescale # ------------ @property def reversescale(self): """ Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. The 'reversescale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["reversescale"] @reversescale.setter def reversescale(self, val): self["reversescale"] = val # width # ----- @property def width(self): """ Sets the width (in px) of the lines bounding the marker points. The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["width"] @width.setter def width(self, val): self["width"] = val # widthsrc # -------- @property def widthsrc(self): """ Sets the source reference on plot.ly for width . The 'widthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["widthsrc"] @widthsrc.setter def widthsrc(self, val): self["widthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "funnel.marker" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . """ def __init__( self, arg=None, autocolorscale=None, cauto=None, cmax=None, cmid=None, cmin=None, color=None, coloraxis=None, colorscale=None, colorsrc=None, reversescale=None, width=None, widthsrc=None, **kwargs ): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.funnel.marker.Line autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.funnel.marker.Line constructor must be a dict or an instance of plotly.graph_objs.funnel.marker.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.funnel.marker import line as v_line # Initialize validators # --------------------- self._validators["autocolorscale"] = v_line.AutocolorscaleValidator() self._validators["cauto"] = v_line.CautoValidator() self._validators["cmax"] = v_line.CmaxValidator() self._validators["cmid"] = v_line.CmidValidator() self._validators["cmin"] = v_line.CminValidator() self._validators["color"] = v_line.ColorValidator() self._validators["coloraxis"] = v_line.ColoraxisValidator() self._validators["colorscale"] = v_line.ColorscaleValidator() self._validators["colorsrc"] = v_line.ColorsrcValidator() self._validators["reversescale"] = v_line.ReversescaleValidator() self._validators["width"] = v_line.WidthValidator() self._validators["widthsrc"] = v_line.WidthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autocolorscale", None) self["autocolorscale"] = autocolorscale if autocolorscale is not None else _v _v = arg.pop("cauto", None) self["cauto"] = cauto if cauto is not None else _v _v = arg.pop("cmax", None) self["cmax"] = cmax if cmax is not None else _v _v = arg.pop("cmid", None) self["cmid"] = cmid if cmid is not None else _v _v = arg.pop("cmin", None) self["cmin"] = cmin if cmin is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("coloraxis", None) self["coloraxis"] = coloraxis if coloraxis is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("reversescale", None) self["reversescale"] = reversescale if reversescale is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v _v = arg.pop("widthsrc", None) self["widthsrc"] = widthsrc if widthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class ColorBar(_BaseTraceHierarchyType): # bgcolor # ------- @property def bgcolor(self): """ Sets the color of padded area. The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the axis line color. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # borderwidth # ----------- @property def borderwidth(self): """ Sets the width (in px) or the border enclosing this color bar. The 'borderwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["borderwidth"] @borderwidth.setter def borderwidth(self, val): self["borderwidth"] = val # dtick # ----- @property def dtick(self): """ Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" The 'dtick' property accepts values of any type Returns ------- Any """ return self["dtick"] @dtick.setter def dtick(self, val): self["dtick"] = val # exponentformat # -------------- @property def exponentformat(self): """ Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. The 'exponentformat' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'e', 'E', 'power', 'SI', 'B'] Returns ------- Any """ return self["exponentformat"] @exponentformat.setter def exponentformat(self, val): self["exponentformat"] = val # len # --- @property def len(self): """ Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. The 'len' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["len"] @len.setter def len(self, val): self["len"] = val # lenmode # ------- @property def lenmode(self): """ Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. The 'lenmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["lenmode"] @lenmode.setter def lenmode(self, val): self["lenmode"] = val # nticks # ------ @property def nticks(self): """ Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". The 'nticks' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nticks"] @nticks.setter def nticks(self, val): self["nticks"] = val # outlinecolor # ------------ @property def outlinecolor(self): """ Sets the axis line color. The 'outlinecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["outlinecolor"] @outlinecolor.setter def outlinecolor(self, val): self["outlinecolor"] = val # outlinewidth # ------------ @property def outlinewidth(self): """ Sets the width (in px) of the axis line. The 'outlinewidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["outlinewidth"] @outlinewidth.setter def outlinewidth(self, val): self["outlinewidth"] = val # separatethousands # ----------------- @property def separatethousands(self): """ If "true", even 4-digit integers are separated The 'separatethousands' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["separatethousands"] @separatethousands.setter def separatethousands(self, val): self["separatethousands"] = val # showexponent # ------------ @property def showexponent(self): """ If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. The 'showexponent' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showexponent"] @showexponent.setter def showexponent(self, val): self["showexponent"] = val # showticklabels # -------------- @property def showticklabels(self): """ Determines whether or not the tick labels are drawn. The 'showticklabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showticklabels"] @showticklabels.setter def showticklabels(self, val): self["showticklabels"] = val # showtickprefix # -------------- @property def showtickprefix(self): """ If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. The 'showtickprefix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showtickprefix"] @showtickprefix.setter def showtickprefix(self, val): self["showtickprefix"] = val # showticksuffix # -------------- @property def showticksuffix(self): """ Same as `showtickprefix` but for tick suffixes. The 'showticksuffix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showticksuffix"] @showticksuffix.setter def showticksuffix(self, val): self["showticksuffix"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # thicknessmode # ------------- @property def thicknessmode(self): """ Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. The 'thicknessmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["thicknessmode"] @thicknessmode.setter def thicknessmode(self, val): self["thicknessmode"] = val # tick0 # ----- @property def tick0(self): """ Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. The 'tick0' property accepts values of any type Returns ------- Any """ return self["tick0"] @tick0.setter def tick0(self, val): self["tick0"] = val # tickangle # --------- @property def tickangle(self): """ Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. The 'tickangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["tickangle"] @tickangle.setter def tickangle(self, val): self["tickangle"] = val # tickcolor # --------- @property def tickcolor(self): """ Sets the tick color. The 'tickcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["tickcolor"] @tickcolor.setter def tickcolor(self, val): self["tickcolor"] = val # tickfont # -------- @property def tickfont(self): """ Sets the color bar's tick label font The 'tickfont' property is an instance of Tickfont that may be specified as: - An instance of plotly.graph_objs.funnel.marker.colorbar.Tickfont - A dict of string/value properties that will be passed to the Tickfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.funnel.marker.colorbar.Tickfont """ return self["tickfont"] @tickfont.setter def tickfont(self, val): self["tickfont"] = val # tickformat # ---------- @property def tickformat(self): """ Sets the tick label formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'tickformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickformat"] @tickformat.setter def tickformat(self, val): self["tickformat"] = val # tickformatstops # --------------- @property def tickformatstops(self): """ The 'tickformatstops' property is a tuple of instances of Tickformatstop that may be specified as: - A list or tuple of instances of plotly.graph_objs.funnel.marker.colorbar.Tickformatstop - A list or tuple of dicts of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- tuple[plotly.graph_objs.funnel.marker.colorbar.Tickformatstop] """ return self["tickformatstops"] @tickformatstops.setter def tickformatstops(self, val): self["tickformatstops"] = val # tickformatstopdefaults # ---------------------- @property def tickformatstopdefaults(self): """ When used in a template (as layout.template.data.funnel.marker. colorbar.tickformatstopdefaults), sets the default property values to use for elements of funnel.marker.colorbar.tickformatstops The 'tickformatstopdefaults' property is an instance of Tickformatstop that may be specified as: - An instance of plotly.graph_objs.funnel.marker.colorbar.Tickformatstop - A dict of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: Returns ------- plotly.graph_objs.funnel.marker.colorbar.Tickformatstop """ return self["tickformatstopdefaults"] @tickformatstopdefaults.setter def tickformatstopdefaults(self, val): self["tickformatstopdefaults"] = val # ticklen # ------- @property def ticklen(self): """ Sets the tick length (in px). The 'ticklen' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ticklen"] @ticklen.setter def ticklen(self, val): self["ticklen"] = val # tickmode # -------- @property def tickmode(self): """ Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). The 'tickmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'linear', 'array'] Returns ------- Any """ return self["tickmode"] @tickmode.setter def tickmode(self, val): self["tickmode"] = val # tickprefix # ---------- @property def tickprefix(self): """ Sets a tick label prefix. The 'tickprefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickprefix"] @tickprefix.setter def tickprefix(self, val): self["tickprefix"] = val # ticks # ----- @property def ticks(self): """ Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. The 'ticks' property is an enumeration that may be specified as: - One of the following enumeration values: ['outside', 'inside', ''] Returns ------- Any """ return self["ticks"] @ticks.setter def ticks(self, val): self["ticks"] = val # ticksuffix # ---------- @property def ticksuffix(self): """ Sets a tick label suffix. The 'ticksuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ticksuffix"] @ticksuffix.setter def ticksuffix(self, val): self["ticksuffix"] = val # ticktext # -------- @property def ticktext(self): """ Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. The 'ticktext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ticktext"] @ticktext.setter def ticktext(self, val): self["ticktext"] = val # ticktextsrc # ----------- @property def ticktextsrc(self): """ Sets the source reference on plot.ly for ticktext . The 'ticktextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ticktextsrc"] @ticktextsrc.setter def ticktextsrc(self, val): self["ticktextsrc"] = val # tickvals # -------- @property def tickvals(self): """ Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. The 'tickvals' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["tickvals"] @tickvals.setter def tickvals(self, val): self["tickvals"] = val # tickvalssrc # ----------- @property def tickvalssrc(self): """ Sets the source reference on plot.ly for tickvals . The 'tickvalssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tickvalssrc"] @tickvalssrc.setter def tickvalssrc(self, val): self["tickvalssrc"] = val # tickwidth # --------- @property def tickwidth(self): """ Sets the tick width (in px). The 'tickwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["tickwidth"] @tickwidth.setter def tickwidth(self, val): self["tickwidth"] = val # title # ----- @property def title(self): """ The 'title' property is an instance of Title that may be specified as: - An instance of plotly.graph_objs.funnel.marker.colorbar.Title - A dict of string/value properties that will be passed to the Title constructor Supported dict properties: font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- plotly.graph_objs.funnel.marker.colorbar.Title """ return self["title"] @title.setter def title(self, val): self["title"] = val # titlefont # --------- @property def titlefont(self): """ Deprecated: Please use funnel.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.funnel.marker.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- """ return self["titlefont"] @titlefont.setter def titlefont(self, val): self["titlefont"] = val # titleside # --------- @property def titleside(self): """ Deprecated: Please use funnel.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- """ return self["titleside"] @titleside.setter def titleside(self, val): self["titleside"] = val # x # - @property def x(self): """ Sets the x position of the color bar (in plot fraction). The 'x' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["x"] @x.setter def x(self, val): self["x"] = val # xanchor # ------- @property def xanchor(self): """ Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. The 'xanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'center', 'right'] Returns ------- Any """ return self["xanchor"] @xanchor.setter def xanchor(self, val): self["xanchor"] = val # xpad # ---- @property def xpad(self): """ Sets the amount of padding (in px) along the x direction. The 'xpad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["xpad"] @xpad.setter def xpad(self, val): self["xpad"] = val # y # - @property def y(self): """ Sets the y position of the color bar (in plot fraction). The 'y' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["y"] @y.setter def y(self, val): self["y"] = val # yanchor # ------- @property def yanchor(self): """ Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. The 'yanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['top', 'middle', 'bottom'] Returns ------- Any """ return self["yanchor"] @yanchor.setter def yanchor(self, val): self["yanchor"] = val # ypad # ---- @property def ypad(self): """ Sets the amount of padding (in px) along the y direction. The 'ypad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ypad"] @ypad.setter def ypad(self, val): self["ypad"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "funnel.marker" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.funnel.marker.colorbar. Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.funnel .marker.colorbar.tickformatstopdefaults), sets the default property values to use for elements of funnel.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.funnel.marker.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use funnel.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use funnel.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """ _mapped_properties = { "titlefont": ("title", "font"), "titleside": ("title", "side"), } def __init__( self, arg=None, bgcolor=None, bordercolor=None, borderwidth=None, dtick=None, exponentformat=None, len=None, lenmode=None, nticks=None, outlinecolor=None, outlinewidth=None, separatethousands=None, showexponent=None, showticklabels=None, showtickprefix=None, showticksuffix=None, thickness=None, thicknessmode=None, tick0=None, tickangle=None, tickcolor=None, tickfont=None, tickformat=None, tickformatstops=None, tickformatstopdefaults=None, ticklen=None, tickmode=None, tickprefix=None, ticks=None, ticksuffix=None, ticktext=None, ticktextsrc=None, tickvals=None, tickvalssrc=None, tickwidth=None, title=None, titlefont=None, titleside=None, x=None, xanchor=None, xpad=None, y=None, yanchor=None, ypad=None, **kwargs ): """ Construct a new ColorBar object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.funnel.marker.ColorBar bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.funnel.marker.colorbar. Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.funnel .marker.colorbar.tickformatstopdefaults), sets the default property values to use for elements of funnel.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.funnel.marker.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use funnel.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use funnel.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- ColorBar """ super(ColorBar, self).__init__("colorbar") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.funnel.marker.ColorBar constructor must be a dict or an instance of plotly.graph_objs.funnel.marker.ColorBar""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.funnel.marker import colorbar as v_colorbar # Initialize validators # --------------------- self._validators["bgcolor"] = v_colorbar.BgcolorValidator() self._validators["bordercolor"] = v_colorbar.BordercolorValidator() self._validators["borderwidth"] = v_colorbar.BorderwidthValidator() self._validators["dtick"] = v_colorbar.DtickValidator() self._validators["exponentformat"] = v_colorbar.ExponentformatValidator() self._validators["len"] = v_colorbar.LenValidator() self._validators["lenmode"] = v_colorbar.LenmodeValidator() self._validators["nticks"] = v_colorbar.NticksValidator() self._validators["outlinecolor"] = v_colorbar.OutlinecolorValidator() self._validators["outlinewidth"] = v_colorbar.OutlinewidthValidator() self._validators["separatethousands"] = v_colorbar.SeparatethousandsValidator() self._validators["showexponent"] = v_colorbar.ShowexponentValidator() self._validators["showticklabels"] = v_colorbar.ShowticklabelsValidator() self._validators["showtickprefix"] = v_colorbar.ShowtickprefixValidator() self._validators["showticksuffix"] = v_colorbar.ShowticksuffixValidator() self._validators["thickness"] = v_colorbar.ThicknessValidator() self._validators["thicknessmode"] = v_colorbar.ThicknessmodeValidator() self._validators["tick0"] = v_colorbar.Tick0Validator() self._validators["tickangle"] = v_colorbar.TickangleValidator() self._validators["tickcolor"] = v_colorbar.TickcolorValidator() self._validators["tickfont"] = v_colorbar.TickfontValidator() self._validators["tickformat"] = v_colorbar.TickformatValidator() self._validators["tickformatstops"] = v_colorbar.TickformatstopsValidator() self._validators[ "tickformatstopdefaults" ] = v_colorbar.TickformatstopValidator() self._validators["ticklen"] = v_colorbar.TicklenValidator() self._validators["tickmode"] = v_colorbar.TickmodeValidator() self._validators["tickprefix"] = v_colorbar.TickprefixValidator() self._validators["ticks"] = v_colorbar.TicksValidator() self._validators["ticksuffix"] = v_colorbar.TicksuffixValidator() self._validators["ticktext"] = v_colorbar.TicktextValidator() self._validators["ticktextsrc"] = v_colorbar.TicktextsrcValidator() self._validators["tickvals"] = v_colorbar.TickvalsValidator() self._validators["tickvalssrc"] = v_colorbar.TickvalssrcValidator() self._validators["tickwidth"] = v_colorbar.TickwidthValidator() self._validators["title"] = v_colorbar.TitleValidator() self._validators["x"] = v_colorbar.XValidator() self._validators["xanchor"] = v_colorbar.XanchorValidator() self._validators["xpad"] = v_colorbar.XpadValidator() self._validators["y"] = v_colorbar.YValidator() self._validators["yanchor"] = v_colorbar.YanchorValidator() self._validators["ypad"] = v_colorbar.YpadValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("borderwidth", None) self["borderwidth"] = borderwidth if borderwidth is not None else _v _v = arg.pop("dtick", None) self["dtick"] = dtick if dtick is not None else _v _v = arg.pop("exponentformat", None) self["exponentformat"] = exponentformat if exponentformat is not None else _v _v = arg.pop("len", None) self["len"] = len if len is not None else _v _v = arg.pop("lenmode", None) self["lenmode"] = lenmode if lenmode is not None else _v _v = arg.pop("nticks", None) self["nticks"] = nticks if nticks is not None else _v _v = arg.pop("outlinecolor", None) self["outlinecolor"] = outlinecolor if outlinecolor is not None else _v _v = arg.pop("outlinewidth", None) self["outlinewidth"] = outlinewidth if outlinewidth is not None else _v _v = arg.pop("separatethousands", None) self["separatethousands"] = ( separatethousands if separatethousands is not None else _v ) _v = arg.pop("showexponent", None) self["showexponent"] = showexponent if showexponent is not None else _v _v = arg.pop("showticklabels", None) self["showticklabels"] = showticklabels if showticklabels is not None else _v _v = arg.pop("showtickprefix", None) self["showtickprefix"] = showtickprefix if showtickprefix is not None else _v _v = arg.pop("showticksuffix", None) self["showticksuffix"] = showticksuffix if showticksuffix is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("thicknessmode", None) self["thicknessmode"] = thicknessmode if thicknessmode is not None else _v _v = arg.pop("tick0", None) self["tick0"] = tick0 if tick0 is not None else _v _v = arg.pop("tickangle", None) self["tickangle"] = tickangle if tickangle is not None else _v _v = arg.pop("tickcolor", None) self["tickcolor"] = tickcolor if tickcolor is not None else _v _v = arg.pop("tickfont", None) self["tickfont"] = tickfont if tickfont is not None else _v _v = arg.pop("tickformat", None) self["tickformat"] = tickformat if tickformat is not None else _v _v = arg.pop("tickformatstops", None) self["tickformatstops"] = tickformatstops if tickformatstops is not None else _v _v = arg.pop("tickformatstopdefaults", None) self["tickformatstopdefaults"] = ( tickformatstopdefaults if tickformatstopdefaults is not None else _v ) _v = arg.pop("ticklen", None) self["ticklen"] = ticklen if ticklen is not None else _v _v = arg.pop("tickmode", None) self["tickmode"] = tickmode if tickmode is not None else _v _v = arg.pop("tickprefix", None) self["tickprefix"] = tickprefix if tickprefix is not None else _v _v = arg.pop("ticks", None) self["ticks"] = ticks if ticks is not None else _v _v = arg.pop("ticksuffix", None) self["ticksuffix"] = ticksuffix if ticksuffix is not None else _v _v = arg.pop("ticktext", None) self["ticktext"] = ticktext if ticktext is not None else _v _v = arg.pop("ticktextsrc", None) self["ticktextsrc"] = ticktextsrc if ticktextsrc is not None else _v _v = arg.pop("tickvals", None) self["tickvals"] = tickvals if tickvals is not None else _v _v = arg.pop("tickvalssrc", None) self["tickvalssrc"] = tickvalssrc if tickvalssrc is not None else _v _v = arg.pop("tickwidth", None) self["tickwidth"] = tickwidth if tickwidth is not None else _v _v = arg.pop("title", None) self["title"] = title if title is not None else _v _v = arg.pop("titlefont", None) _v = titlefont if titlefont is not None else _v if _v is not None: self["titlefont"] = _v _v = arg.pop("titleside", None) _v = titleside if titleside is not None else _v if _v is not None: self["titleside"] = _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xanchor", None) self["xanchor"] = xanchor if xanchor is not None else _v _v = arg.pop("xpad", None) self["xpad"] = xpad if xpad is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("yanchor", None) self["yanchor"] = yanchor if yanchor is not None else _v _v = arg.pop("ypad", None) self["ypad"] = ypad if ypad is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["ColorBar", "Line", "colorbar"] from plotly.graph_objs.funnel.marker import colorbar plotly-4.4.1+dfsg.orig/plotly/graph_objs/funnel/__init__.py0000644000175000017500000031650413573721547023341 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Textfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "funnel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Textfont object Sets the font used for `text`. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.funnel.Textfont color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Textfont """ super(Textfont, self).__init__("textfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.funnel.Textfont constructor must be a dict or an instance of plotly.graph_objs.funnel.Textfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.funnel import textfont as v_textfont # Initialize validators # --------------------- self._validators["color"] = v_textfont.ColorValidator() self._validators["colorsrc"] = v_textfont.ColorsrcValidator() self._validators["family"] = v_textfont.FamilyValidator() self._validators["familysrc"] = v_textfont.FamilysrcValidator() self._validators["size"] = v_textfont.SizeValidator() self._validators["sizesrc"] = v_textfont.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Stream(_BaseTraceHierarchyType): # maxpoints # --------- @property def maxpoints(self): """ Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. The 'maxpoints' property is a number and may be specified as: - An int or float in the interval [0, 10000] Returns ------- int|float """ return self["maxpoints"] @maxpoints.setter def maxpoints(self, val): self["maxpoints"] = val # token # ----- @property def token(self): """ The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. The 'token' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["token"] @token.setter def token(self, val): self["token"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "funnel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """ def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): """ Construct a new Stream object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.funnel.Stream maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- Stream """ super(Stream, self).__init__("stream") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.funnel.Stream constructor must be a dict or an instance of plotly.graph_objs.funnel.Stream""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.funnel import stream as v_stream # Initialize validators # --------------------- self._validators["maxpoints"] = v_stream.MaxpointsValidator() self._validators["token"] = v_stream.TokenValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("maxpoints", None) self["maxpoints"] = maxpoints if maxpoints is not None else _v _v = arg.pop("token", None) self["token"] = token if token is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Outsidetextfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "funnel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Outsidetextfont object Sets the font used for `text` lying outside the bar. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.funnel.Outsidetextfont color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Outsidetextfont """ super(Outsidetextfont, self).__init__("outsidetextfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.funnel.Outsidetextfont constructor must be a dict or an instance of plotly.graph_objs.funnel.Outsidetextfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.funnel import outsidetextfont as v_outsidetextfont # Initialize validators # --------------------- self._validators["color"] = v_outsidetextfont.ColorValidator() self._validators["colorsrc"] = v_outsidetextfont.ColorsrcValidator() self._validators["family"] = v_outsidetextfont.FamilyValidator() self._validators["familysrc"] = v_outsidetextfont.FamilysrcValidator() self._validators["size"] = v_outsidetextfont.SizeValidator() self._validators["sizesrc"] = v_outsidetextfont.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # autocolorscale # -------------- @property def autocolorscale(self): """ Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. The 'autocolorscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocolorscale"] @autocolorscale.setter def autocolorscale(self, val): self["autocolorscale"] = val # cauto # ----- @property def cauto(self): """ Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. The 'cauto' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["cauto"] @cauto.setter def cauto(self, val): self["cauto"] = val # cmax # ---- @property def cmax(self): """ Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. The 'cmax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmax"] @cmax.setter def cmax(self, val): self["cmax"] = val # cmid # ---- @property def cmid(self): """ Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. The 'cmid' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmid"] @cmid.setter def cmid(self, val): self["cmid"] = val # cmin # ---- @property def cmin(self): """ Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. The 'cmin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmin"] @cmin.setter def cmin(self, val): self["cmin"] = val # color # ----- @property def color(self): """ Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A number that will be interpreted as a color according to funnel.marker.colorscale - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # coloraxis # --------- @property def coloraxis(self): """ Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. The 'coloraxis' property is an identifier of a particular subplot, of type 'coloraxis', that may be specified as the string 'coloraxis' optionally followed by an integer >= 1 (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) Returns ------- str """ return self["coloraxis"] @coloraxis.setter def coloraxis(self, val): self["coloraxis"] = val # colorbar # -------- @property def colorbar(self): """ The 'colorbar' property is an instance of ColorBar that may be specified as: - An instance of plotly.graph_objs.funnel.marker.ColorBar - A dict of string/value properties that will be passed to the ColorBar constructor Supported dict properties: bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.funnel.marker.c olorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.funnel.marker.colorbar.tickformatstopdefaults ), sets the default property values to use for elements of funnel.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.funnel.marker.colorbar.Tit le instance or dict with compatible properties titlefont Deprecated: Please use funnel.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use funnel.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- plotly.graph_objs.funnel.marker.ColorBar """ return self["colorbar"] @colorbar.setter def colorbar(self, val): self["colorbar"] = val # colorscale # ---------- @property def colorscale(self): """ Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnB u,Greens,YlOrRd,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland ,Jet,Hot,Blackbody,Earth,Electric,Viridis,Cividis. The 'colorscale' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.funnel.marker.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,R eds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Black body,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . Returns ------- plotly.graph_objs.funnel.marker.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the bars. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # opacitysrc # ---------- @property def opacitysrc(self): """ Sets the source reference on plot.ly for opacity . The 'opacitysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["opacitysrc"] @opacitysrc.setter def opacitysrc(self, val): self["opacitysrc"] = val # reversescale # ------------ @property def reversescale(self): """ Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. The 'reversescale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["reversescale"] @reversescale.setter def reversescale(self, val): self["reversescale"] = val # showscale # --------- @property def showscale(self): """ Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. The 'showscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showscale"] @showscale.setter def showscale(self, val): self["showscale"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "funnel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.funnel.marker.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu ,Reds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . line plotly.graph_objects.funnel.marker.Line instance or dict with compatible properties opacity Sets the opacity of the bars. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. """ def __init__( self, arg=None, autocolorscale=None, cauto=None, cmax=None, cmid=None, cmin=None, color=None, coloraxis=None, colorbar=None, colorscale=None, colorsrc=None, line=None, opacity=None, opacitysrc=None, reversescale=None, showscale=None, **kwargs ): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.funnel.Marker autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.funnel.marker.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu ,Reds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . line plotly.graph_objects.funnel.marker.Line instance or dict with compatible properties opacity Sets the opacity of the bars. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.funnel.Marker constructor must be a dict or an instance of plotly.graph_objs.funnel.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.funnel import marker as v_marker # Initialize validators # --------------------- self._validators["autocolorscale"] = v_marker.AutocolorscaleValidator() self._validators["cauto"] = v_marker.CautoValidator() self._validators["cmax"] = v_marker.CmaxValidator() self._validators["cmid"] = v_marker.CmidValidator() self._validators["cmin"] = v_marker.CminValidator() self._validators["color"] = v_marker.ColorValidator() self._validators["coloraxis"] = v_marker.ColoraxisValidator() self._validators["colorbar"] = v_marker.ColorBarValidator() self._validators["colorscale"] = v_marker.ColorscaleValidator() self._validators["colorsrc"] = v_marker.ColorsrcValidator() self._validators["line"] = v_marker.LineValidator() self._validators["opacity"] = v_marker.OpacityValidator() self._validators["opacitysrc"] = v_marker.OpacitysrcValidator() self._validators["reversescale"] = v_marker.ReversescaleValidator() self._validators["showscale"] = v_marker.ShowscaleValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autocolorscale", None) self["autocolorscale"] = autocolorscale if autocolorscale is not None else _v _v = arg.pop("cauto", None) self["cauto"] = cauto if cauto is not None else _v _v = arg.pop("cmax", None) self["cmax"] = cmax if cmax is not None else _v _v = arg.pop("cmid", None) self["cmid"] = cmid if cmid is not None else _v _v = arg.pop("cmin", None) self["cmin"] = cmin if cmin is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("coloraxis", None) self["coloraxis"] = coloraxis if coloraxis is not None else _v _v = arg.pop("colorbar", None) self["colorbar"] = colorbar if colorbar is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("opacitysrc", None) self["opacitysrc"] = opacitysrc if opacitysrc is not None else _v _v = arg.pop("reversescale", None) self["reversescale"] = reversescale if reversescale is not None else _v _v = arg.pop("showscale", None) self["showscale"] = showscale if showscale is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Insidetextfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "funnel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Insidetextfont object Sets the font used for `text` lying inside the bar. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.funnel.Insidetextfont color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Insidetextfont """ super(Insidetextfont, self).__init__("insidetextfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.funnel.Insidetextfont constructor must be a dict or an instance of plotly.graph_objs.funnel.Insidetextfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.funnel import insidetextfont as v_insidetextfont # Initialize validators # --------------------- self._validators["color"] = v_insidetextfont.ColorValidator() self._validators["colorsrc"] = v_insidetextfont.ColorsrcValidator() self._validators["family"] = v_insidetextfont.FamilyValidator() self._validators["familysrc"] = v_insidetextfont.FamilysrcValidator() self._validators["size"] = v_insidetextfont.SizeValidator() self._validators["sizesrc"] = v_insidetextfont.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Hoverlabel(_BaseTraceHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'right', 'auto'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["align"] @align.setter def align(self, val): self["align"] = val # alignsrc # -------- @property def alignsrc(self): """ Sets the source reference on plot.ly for align . The 'alignsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["alignsrc"] @alignsrc.setter def alignsrc(self, val): self["alignsrc"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the hover labels for this trace The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bgcolorsrc # ---------- @property def bgcolorsrc(self): """ Sets the source reference on plot.ly for bgcolor . The 'bgcolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bgcolorsrc"] @bgcolorsrc.setter def bgcolorsrc(self, val): self["bgcolorsrc"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the border color of the hover labels for this trace. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # bordercolorsrc # -------------- @property def bordercolorsrc(self): """ Sets the source reference on plot.ly for bordercolor . The 'bordercolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bordercolorsrc"] @bordercolorsrc.setter def bordercolorsrc(self, val): self["bordercolorsrc"] = val # font # ---- @property def font(self): """ Sets the font used in hover labels. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.funnel.hoverlabel.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.funnel.hoverlabel.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # namelength # ---------- @property def namelength(self): """ Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. The 'namelength' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [-1, 9223372036854775807] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|numpy.ndarray """ return self["namelength"] @namelength.setter def namelength(self, val): self["namelength"] = val # namelengthsrc # ------------- @property def namelengthsrc(self): """ Sets the source reference on plot.ly for namelength . The 'namelengthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["namelengthsrc"] @namelengthsrc.setter def namelengthsrc(self, val): self["namelengthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "funnel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """ def __init__( self, arg=None, align=None, alignsrc=None, bgcolor=None, bgcolorsrc=None, bordercolor=None, bordercolorsrc=None, font=None, namelength=None, namelengthsrc=None, **kwargs ): """ Construct a new Hoverlabel object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.funnel.Hoverlabel align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- Hoverlabel """ super(Hoverlabel, self).__init__("hoverlabel") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.funnel.Hoverlabel constructor must be a dict or an instance of plotly.graph_objs.funnel.Hoverlabel""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.funnel import hoverlabel as v_hoverlabel # Initialize validators # --------------------- self._validators["align"] = v_hoverlabel.AlignValidator() self._validators["alignsrc"] = v_hoverlabel.AlignsrcValidator() self._validators["bgcolor"] = v_hoverlabel.BgcolorValidator() self._validators["bgcolorsrc"] = v_hoverlabel.BgcolorsrcValidator() self._validators["bordercolor"] = v_hoverlabel.BordercolorValidator() self._validators["bordercolorsrc"] = v_hoverlabel.BordercolorsrcValidator() self._validators["font"] = v_hoverlabel.FontValidator() self._validators["namelength"] = v_hoverlabel.NamelengthValidator() self._validators["namelengthsrc"] = v_hoverlabel.NamelengthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("alignsrc", None) self["alignsrc"] = alignsrc if alignsrc is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bgcolorsrc", None) self["bgcolorsrc"] = bgcolorsrc if bgcolorsrc is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("bordercolorsrc", None) self["bordercolorsrc"] = bordercolorsrc if bordercolorsrc is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("namelength", None) self["namelength"] = namelength if namelength is not None else _v _v = arg.pop("namelengthsrc", None) self["namelengthsrc"] = namelengthsrc if namelengthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Connector(_BaseTraceHierarchyType): # fillcolor # --------- @property def fillcolor(self): """ Sets the fill color. The 'fillcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["fillcolor"] @fillcolor.setter def fillcolor(self, val): self["fillcolor"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.funnel.connector.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: color Sets the line color. dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). width Sets the line width (in px). Returns ------- plotly.graph_objs.funnel.connector.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # visible # ------- @property def visible(self): """ Determines if connector regions and lines are drawn. The 'visible' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "funnel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ fillcolor Sets the fill color. line plotly.graph_objects.funnel.connector.Line instance or dict with compatible properties visible Determines if connector regions and lines are drawn. """ def __init__(self, arg=None, fillcolor=None, line=None, visible=None, **kwargs): """ Construct a new Connector object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.funnel.Connector fillcolor Sets the fill color. line plotly.graph_objects.funnel.connector.Line instance or dict with compatible properties visible Determines if connector regions and lines are drawn. Returns ------- Connector """ super(Connector, self).__init__("connector") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.funnel.Connector constructor must be a dict or an instance of plotly.graph_objs.funnel.Connector""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.funnel import connector as v_connector # Initialize validators # --------------------- self._validators["fillcolor"] = v_connector.FillcolorValidator() self._validators["line"] = v_connector.LineValidator() self._validators["visible"] = v_connector.VisibleValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("fillcolor", None) self["fillcolor"] = fillcolor if fillcolor is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = [ "Connector", "Hoverlabel", "Insidetextfont", "Marker", "Outsidetextfont", "Stream", "Textfont", "connector", "hoverlabel", "marker", ] from plotly.graph_objs.funnel import marker from plotly.graph_objs.funnel import hoverlabel from plotly.graph_objs.funnel import connector plotly-4.4.1+dfsg.orig/plotly/graph_objs/pie/0000755000175000017500000000000013573746613020506 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/pie/title/0000755000175000017500000000000013573746613021627 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/pie/title/__init__.py0000644000175000017500000002550213573721550023735 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "pie.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Font object Sets the font used for `title`. Note that the title's font used to be set by the now deprecated `titlefont` attribute. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.pie.title.Font color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.pie.title.Font constructor must be a dict or an instance of plotly.graph_objs.pie.title.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.pie.title import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["colorsrc"] = v_font.ColorsrcValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["familysrc"] = v_font.FamilysrcValidator() self._validators["size"] = v_font.SizeValidator() self._validators["sizesrc"] = v_font.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/pie/hoverlabel/0000755000175000017500000000000013573746613022631 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/pie/hoverlabel/__init__.py0000644000175000017500000002540013573721550024734 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "pie.hoverlabel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Font object Sets the font used in hover labels. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.pie.hoverlabel.Font color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.pie.hoverlabel.Font constructor must be a dict or an instance of plotly.graph_objs.pie.hoverlabel.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.pie.hoverlabel import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["colorsrc"] = v_font.ColorsrcValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["familysrc"] = v_font.FamilysrcValidator() self._validators["size"] = v_font.SizeValidator() self._validators["sizesrc"] = v_font.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/pie/marker/0000755000175000017500000000000013573746613021767 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/pie/marker/__init__.py0000644000175000017500000001650013573721550024073 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the color of the line enclosing each sector. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # width # ----- @property def width(self): """ Sets the width (in px) of the line enclosing each sector. The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["width"] @width.setter def width(self, val): self["width"] = val # widthsrc # -------- @property def widthsrc(self): """ Sets the source reference on plot.ly for width . The 'widthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["widthsrc"] @widthsrc.setter def widthsrc(self, val): self["widthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "pie.marker" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the color of the line enclosing each sector. colorsrc Sets the source reference on plot.ly for color . width Sets the width (in px) of the line enclosing each sector. widthsrc Sets the source reference on plot.ly for width . """ def __init__( self, arg=None, color=None, colorsrc=None, width=None, widthsrc=None, **kwargs ): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.pie.marker.Line color Sets the color of the line enclosing each sector. colorsrc Sets the source reference on plot.ly for color . width Sets the width (in px) of the line enclosing each sector. widthsrc Sets the source reference on plot.ly for width . Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.pie.marker.Line constructor must be a dict or an instance of plotly.graph_objs.pie.marker.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.pie.marker import line as v_line # Initialize validators # --------------------- self._validators["color"] = v_line.ColorValidator() self._validators["colorsrc"] = v_line.ColorsrcValidator() self._validators["width"] = v_line.WidthValidator() self._validators["widthsrc"] = v_line.WidthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v _v = arg.pop("widthsrc", None) self["widthsrc"] = widthsrc if widthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Line"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/pie/__init__.py0000644000175000017500000021652513573721551022624 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Title(_BaseTraceHierarchyType): # font # ---- @property def font(self): """ Sets the font used for `title`. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.pie.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.pie.title.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # position # -------- @property def position(self): """ Specifies the location of the `title`. Note that the title's position used to be set by the now deprecated `titleposition` attribute. The 'position' property is an enumeration that may be specified as: - One of the following enumeration values: ['top left', 'top center', 'top right', 'middle center', 'bottom left', 'bottom center', 'bottom right'] Returns ------- Any """ return self["position"] @position.setter def position(self, val): self["position"] = val # text # ---- @property def text(self): """ Sets the title of the chart. If it is empty, no title is displayed. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "pie" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Sets the font used for `title`. Note that the title's font used to be set by the now deprecated `titlefont` attribute. position Specifies the location of the `title`. Note that the title's position used to be set by the now deprecated `titleposition` attribute. text Sets the title of the chart. If it is empty, no title is displayed. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """ def __init__(self, arg=None, font=None, position=None, text=None, **kwargs): """ Construct a new Title object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.pie.Title font Sets the font used for `title`. Note that the title's font used to be set by the now deprecated `titlefont` attribute. position Specifies the location of the `title`. Note that the title's position used to be set by the now deprecated `titleposition` attribute. text Sets the title of the chart. If it is empty, no title is displayed. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- Title """ super(Title, self).__init__("title") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.pie.Title constructor must be a dict or an instance of plotly.graph_objs.pie.Title""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.pie import title as v_title # Initialize validators # --------------------- self._validators["font"] = v_title.FontValidator() self._validators["position"] = v_title.PositionValidator() self._validators["text"] = v_title.TextValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("position", None) self["position"] = position if position is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Textfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "pie" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Textfont object Sets the font used for `textinfo`. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.pie.Textfont color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Textfont """ super(Textfont, self).__init__("textfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.pie.Textfont constructor must be a dict or an instance of plotly.graph_objs.pie.Textfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.pie import textfont as v_textfont # Initialize validators # --------------------- self._validators["color"] = v_textfont.ColorValidator() self._validators["colorsrc"] = v_textfont.ColorsrcValidator() self._validators["family"] = v_textfont.FamilyValidator() self._validators["familysrc"] = v_textfont.FamilysrcValidator() self._validators["size"] = v_textfont.SizeValidator() self._validators["sizesrc"] = v_textfont.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Stream(_BaseTraceHierarchyType): # maxpoints # --------- @property def maxpoints(self): """ Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. The 'maxpoints' property is a number and may be specified as: - An int or float in the interval [0, 10000] Returns ------- int|float """ return self["maxpoints"] @maxpoints.setter def maxpoints(self, val): self["maxpoints"] = val # token # ----- @property def token(self): """ The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. The 'token' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["token"] @token.setter def token(self, val): self["token"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "pie" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """ def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): """ Construct a new Stream object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.pie.Stream maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- Stream """ super(Stream, self).__init__("stream") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.pie.Stream constructor must be a dict or an instance of plotly.graph_objs.pie.Stream""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.pie import stream as v_stream # Initialize validators # --------------------- self._validators["maxpoints"] = v_stream.MaxpointsValidator() self._validators["token"] = v_stream.TokenValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("maxpoints", None) self["maxpoints"] = maxpoints if maxpoints is not None else _v _v = arg.pop("token", None) self["token"] = token if token is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Outsidetextfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "pie" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Outsidetextfont object Sets the font used for `textinfo` lying outside the sector. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.pie.Outsidetextfont color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Outsidetextfont """ super(Outsidetextfont, self).__init__("outsidetextfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.pie.Outsidetextfont constructor must be a dict or an instance of plotly.graph_objs.pie.Outsidetextfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.pie import outsidetextfont as v_outsidetextfont # Initialize validators # --------------------- self._validators["color"] = v_outsidetextfont.ColorValidator() self._validators["colorsrc"] = v_outsidetextfont.ColorsrcValidator() self._validators["family"] = v_outsidetextfont.FamilyValidator() self._validators["familysrc"] = v_outsidetextfont.FamilysrcValidator() self._validators["size"] = v_outsidetextfont.SizeValidator() self._validators["sizesrc"] = v_outsidetextfont.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # colors # ------ @property def colors(self): """ Sets the color of each sector. If not specified, the default trace color set is used to pick the sector colors. The 'colors' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["colors"] @colors.setter def colors(self, val): self["colors"] = val # colorssrc # --------- @property def colorssrc(self): """ Sets the source reference on plot.ly for colors . The 'colorssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorssrc"] @colorssrc.setter def colorssrc(self, val): self["colorssrc"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.pie.marker.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: color Sets the color of the line enclosing each sector. colorsrc Sets the source reference on plot.ly for color . width Sets the width (in px) of the line enclosing each sector. widthsrc Sets the source reference on plot.ly for width . Returns ------- plotly.graph_objs.pie.marker.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "pie" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ colors Sets the color of each sector. If not specified, the default trace color set is used to pick the sector colors. colorssrc Sets the source reference on plot.ly for colors . line plotly.graph_objects.pie.marker.Line instance or dict with compatible properties """ def __init__(self, arg=None, colors=None, colorssrc=None, line=None, **kwargs): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.pie.Marker colors Sets the color of each sector. If not specified, the default trace color set is used to pick the sector colors. colorssrc Sets the source reference on plot.ly for colors . line plotly.graph_objects.pie.marker.Line instance or dict with compatible properties Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.pie.Marker constructor must be a dict or an instance of plotly.graph_objs.pie.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.pie import marker as v_marker # Initialize validators # --------------------- self._validators["colors"] = v_marker.ColorsValidator() self._validators["colorssrc"] = v_marker.ColorssrcValidator() self._validators["line"] = v_marker.LineValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("colors", None) self["colors"] = colors if colors is not None else _v _v = arg.pop("colorssrc", None) self["colorssrc"] = colorssrc if colorssrc is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Insidetextfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "pie" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Insidetextfont object Sets the font used for `textinfo` lying inside the sector. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.pie.Insidetextfont color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Insidetextfont """ super(Insidetextfont, self).__init__("insidetextfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.pie.Insidetextfont constructor must be a dict or an instance of plotly.graph_objs.pie.Insidetextfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.pie import insidetextfont as v_insidetextfont # Initialize validators # --------------------- self._validators["color"] = v_insidetextfont.ColorValidator() self._validators["colorsrc"] = v_insidetextfont.ColorsrcValidator() self._validators["family"] = v_insidetextfont.FamilyValidator() self._validators["familysrc"] = v_insidetextfont.FamilysrcValidator() self._validators["size"] = v_insidetextfont.SizeValidator() self._validators["sizesrc"] = v_insidetextfont.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Hoverlabel(_BaseTraceHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'right', 'auto'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["align"] @align.setter def align(self, val): self["align"] = val # alignsrc # -------- @property def alignsrc(self): """ Sets the source reference on plot.ly for align . The 'alignsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["alignsrc"] @alignsrc.setter def alignsrc(self, val): self["alignsrc"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the hover labels for this trace The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bgcolorsrc # ---------- @property def bgcolorsrc(self): """ Sets the source reference on plot.ly for bgcolor . The 'bgcolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bgcolorsrc"] @bgcolorsrc.setter def bgcolorsrc(self, val): self["bgcolorsrc"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the border color of the hover labels for this trace. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # bordercolorsrc # -------------- @property def bordercolorsrc(self): """ Sets the source reference on plot.ly for bordercolor . The 'bordercolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bordercolorsrc"] @bordercolorsrc.setter def bordercolorsrc(self, val): self["bordercolorsrc"] = val # font # ---- @property def font(self): """ Sets the font used in hover labels. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.pie.hoverlabel.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.pie.hoverlabel.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # namelength # ---------- @property def namelength(self): """ Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. The 'namelength' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [-1, 9223372036854775807] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|numpy.ndarray """ return self["namelength"] @namelength.setter def namelength(self, val): self["namelength"] = val # namelengthsrc # ------------- @property def namelengthsrc(self): """ Sets the source reference on plot.ly for namelength . The 'namelengthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["namelengthsrc"] @namelengthsrc.setter def namelengthsrc(self, val): self["namelengthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "pie" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """ def __init__( self, arg=None, align=None, alignsrc=None, bgcolor=None, bgcolorsrc=None, bordercolor=None, bordercolorsrc=None, font=None, namelength=None, namelengthsrc=None, **kwargs ): """ Construct a new Hoverlabel object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.pie.Hoverlabel align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- Hoverlabel """ super(Hoverlabel, self).__init__("hoverlabel") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.pie.Hoverlabel constructor must be a dict or an instance of plotly.graph_objs.pie.Hoverlabel""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.pie import hoverlabel as v_hoverlabel # Initialize validators # --------------------- self._validators["align"] = v_hoverlabel.AlignValidator() self._validators["alignsrc"] = v_hoverlabel.AlignsrcValidator() self._validators["bgcolor"] = v_hoverlabel.BgcolorValidator() self._validators["bgcolorsrc"] = v_hoverlabel.BgcolorsrcValidator() self._validators["bordercolor"] = v_hoverlabel.BordercolorValidator() self._validators["bordercolorsrc"] = v_hoverlabel.BordercolorsrcValidator() self._validators["font"] = v_hoverlabel.FontValidator() self._validators["namelength"] = v_hoverlabel.NamelengthValidator() self._validators["namelengthsrc"] = v_hoverlabel.NamelengthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("alignsrc", None) self["alignsrc"] = alignsrc if alignsrc is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bgcolorsrc", None) self["bgcolorsrc"] = bgcolorsrc if bgcolorsrc is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("bordercolorsrc", None) self["bordercolorsrc"] = bordercolorsrc if bordercolorsrc is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("namelength", None) self["namelength"] = namelength if namelength is not None else _v _v = arg.pop("namelengthsrc", None) self["namelengthsrc"] = namelengthsrc if namelengthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Domain(_BaseTraceHierarchyType): # column # ------ @property def column(self): """ If there is a layout grid, use the domain for this column in the grid for this pie trace . The 'column' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["column"] @column.setter def column(self, val): self["column"] = val # row # --- @property def row(self): """ If there is a layout grid, use the domain for this row in the grid for this pie trace . The 'row' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["row"] @row.setter def row(self, val): self["row"] = val # x # - @property def x(self): """ Sets the horizontal domain of this pie trace (in plot fraction). The 'x' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'x[0]' property is a number and may be specified as: - An int or float in the interval [0, 1] (1) The 'x[1]' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- list """ return self["x"] @x.setter def x(self, val): self["x"] = val # y # - @property def y(self): """ Sets the vertical domain of this pie trace (in plot fraction). The 'y' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'y[0]' property is a number and may be specified as: - An int or float in the interval [0, 1] (1) The 'y[1]' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- list """ return self["y"] @y.setter def y(self, val): self["y"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "pie" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ column If there is a layout grid, use the domain for this column in the grid for this pie trace . row If there is a layout grid, use the domain for this row in the grid for this pie trace . x Sets the horizontal domain of this pie trace (in plot fraction). y Sets the vertical domain of this pie trace (in plot fraction). """ def __init__(self, arg=None, column=None, row=None, x=None, y=None, **kwargs): """ Construct a new Domain object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.pie.Domain column If there is a layout grid, use the domain for this column in the grid for this pie trace . row If there is a layout grid, use the domain for this row in the grid for this pie trace . x Sets the horizontal domain of this pie trace (in plot fraction). y Sets the vertical domain of this pie trace (in plot fraction). Returns ------- Domain """ super(Domain, self).__init__("domain") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.pie.Domain constructor must be a dict or an instance of plotly.graph_objs.pie.Domain""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.pie import domain as v_domain # Initialize validators # --------------------- self._validators["column"] = v_domain.ColumnValidator() self._validators["row"] = v_domain.RowValidator() self._validators["x"] = v_domain.XValidator() self._validators["y"] = v_domain.YValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("column", None) self["column"] = column if column is not None else _v _v = arg.pop("row", None) self["row"] = row if row is not None else _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = [ "Domain", "Hoverlabel", "Insidetextfont", "Marker", "Outsidetextfont", "Stream", "Textfont", "Title", "hoverlabel", "marker", "title", ] from plotly.graph_objs.pie import title from plotly.graph_objs.pie import marker from plotly.graph_objs.pie import hoverlabel plotly-4.4.1+dfsg.orig/plotly/graph_objs/_figure.py0000644000175000017500000273551613573721553021742 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseFigure from plotly.graph_objs import ( Area, Bar, Barpolar, Box, Candlestick, Carpet, Choropleth, Choroplethmapbox, Cone, Contour, Contourcarpet, Densitymapbox, Funnel, Funnelarea, Heatmap, Heatmapgl, Histogram, Histogram2d, Histogram2dContour, Image, Indicator, Isosurface, Mesh3d, Ohlc, Parcats, Parcoords, Pie, Pointcloud, Sankey, Scatter, Scatter3d, Scattercarpet, Scattergeo, Scattergl, Scattermapbox, Scatterpolar, Scatterpolargl, Scatterternary, Splom, Streamtube, Sunburst, Surface, Table, Treemap, Violin, Volume, Waterfall, layout as _layout, ) class Figure(BaseFigure): def __init__( self, data=None, layout=None, frames=None, skip_invalid=False, **kwargs ): """ Create a new Figure instance Parameters ---------- data The 'data' property is a tuple of trace instances that may be specified as: - A list or tuple of trace instances (e.g. [Scatter(...), Bar(...)]) - A single trace instance (e.g. Scatter(...), Bar(...), etc.) - A list or tuple of dicts of string/value properties where: - The 'type' property specifies the trace type One of: ['area', 'bar', 'barpolar', 'box', 'candlestick', 'carpet', 'choropleth', 'choroplethmapbox', 'cone', 'contour', 'contourcarpet', 'densitymapbox', 'funnel', 'funnelarea', 'heatmap', 'heatmapgl', 'histogram', 'histogram2d', 'histogram2dcontour', 'image', 'indicator', 'isosurface', 'mesh3d', 'ohlc', 'parcats', 'parcoords', 'pie', 'pointcloud', 'sankey', 'scatter', 'scatter3d', 'scattercarpet', 'scattergeo', 'scattergl', 'scattermapbox', 'scatterpolar', 'scatterpolargl', 'scatterternary', 'splom', 'streamtube', 'sunburst', 'surface', 'table', 'treemap', 'violin', 'volume', 'waterfall'] - All remaining properties are passed to the constructor of the specified trace type (e.g. [{'type': 'scatter', ...}, {'type': 'bar, ...}]) layout The 'layout' property is an instance of Layout that may be specified as: - An instance of plotly.graph_objs.Layout - A dict of string/value properties that will be passed to the Layout constructor Supported dict properties: angularaxis plotly.graph_objects.layout.AngularAxis instance or dict with compatible properties annotations A tuple of plotly.graph_objects.layout.Annotation instances or dicts with compatible properties annotationdefaults When used in a template (as layout.template.layout.annotationdefaults), sets the default property values to use for elements of layout.annotations autosize Determines whether or not a layout width or height that has been left undefined by the user is initialized on each relayout. Note that, regardless of this attribute, an undefined layout width or height is always initialized on the first call to plot. bargap Sets the gap (in plot fraction) between bars of adjacent location coordinates. bargroupgap Sets the gap (in plot fraction) between bars of the same location coordinate. barmode Determines how bars at the same location coordinate are displayed on the graph. With "stack", the bars are stacked on top of one another With "relative", the bars are stacked on top of one another, with negative values below the axis, positive values above With "group", the bars are plotted next to one another centered around the shared location. With "overlay", the bars are plotted over one another, you might need to an "opacity" to see multiple bars. barnorm Sets the normalization for bar traces on the graph. With "fraction", the value of each bar is divided by the sum of all values at that location coordinate. "percent" is the same but multiplied by 100 to show percentages. boxgap Sets the gap (in plot fraction) between boxes of adjacent location coordinates. Has no effect on traces that have "width" set. boxgroupgap Sets the gap (in plot fraction) between boxes of the same location coordinate. Has no effect on traces that have "width" set. boxmode Determines how boxes at the same location coordinate are displayed on the graph. If "group", the boxes are plotted next to one another centered around the shared location. If "overlay", the boxes are plotted over one another, you might need to set "opacity" to see them multiple boxes. Has no effect on traces that have "width" set. calendar Sets the default calendar system to use for interpreting and displaying dates throughout the plot. clickmode Determines the mode of single click interactions. "event" is the default value and emits the `plotly_click` event. In addition this mode emits the `plotly_selected` event in drag modes "lasso" and "select", but with no event data attached (kept for compatibility reasons). The "select" flag enables selecting single data points via click. This mode also supports persistent selections, meaning that pressing Shift while clicking, adds to / subtracts from an existing selection. "select" with `hovermode`: "x" can be confusing, consider explicitly setting `hovermode`: "closest" when using this feature. Selection events are sent accordingly as long as "event" flag is set as well. When the "event" flag is missing, `plotly_click` and `plotly_selected` events are not fired. coloraxis plotly.graph_objects.layout.Coloraxis instance or dict with compatible properties colorscale plotly.graph_objects.layout.Colorscale instance or dict with compatible properties colorway Sets the default trace colors. datarevision If provided, a changed value tells `Plotly.react` that one or more data arrays has changed. This way you can modify arrays in- place rather than making a complete new copy for an incremental change. If NOT provided, `Plotly.react` assumes that data arrays are being treated as immutable, thus any data array with a different identity from its predecessor contains new data. direction Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the direction corresponding to positive angles in legacy polar charts. dragmode Determines the mode of drag interactions. "select" and "lasso" apply only to scatter traces with markers or text. "orbit" and "turntable" apply only to 3D scenes. editrevision Controls persistence of user-driven changes in `editable: true` configuration, other than trace names and axis titles. Defaults to `layout.uirevision`. extendfunnelareacolors If `true`, the funnelarea slice colors (whether given by `funnelareacolorway` or inherited from `colorway`) will be extended to three times its original length by first repeating every color 20% lighter then each color 20% darker. This is intended to reduce the likelihood of reusing the same color when you have many slices, but you can set `false` to disable. Colors provided in the trace, using `marker.colors`, are never extended. extendpiecolors If `true`, the pie slice colors (whether given by `piecolorway` or inherited from `colorway`) will be extended to three times its original length by first repeating every color 20% lighter then each color 20% darker. This is intended to reduce the likelihood of reusing the same color when you have many slices, but you can set `false` to disable. Colors provided in the trace, using `marker.colors`, are never extended. extendsunburstcolors If `true`, the sunburst slice colors (whether given by `sunburstcolorway` or inherited from `colorway`) will be extended to three times its original length by first repeating every color 20% lighter then each color 20% darker. This is intended to reduce the likelihood of reusing the same color when you have many slices, but you can set `false` to disable. Colors provided in the trace, using `marker.colors`, are never extended. extendtreemapcolors If `true`, the treemap slice colors (whether given by `treemapcolorway` or inherited from `colorway`) will be extended to three times its original length by first repeating every color 20% lighter then each color 20% darker. This is intended to reduce the likelihood of reusing the same color when you have many slices, but you can set `false` to disable. Colors provided in the trace, using `marker.colors`, are never extended. font Sets the global font. Note that fonts used in traces and other layout components inherit from the global font. funnelareacolorway Sets the default funnelarea slice colors. Defaults to the main `colorway` used for trace colors. If you specify a new list here it can still be extended with lighter and darker colors, see `extendfunnelareacolors`. funnelgap Sets the gap (in plot fraction) between bars of adjacent location coordinates. funnelgroupgap Sets the gap (in plot fraction) between bars of the same location coordinate. funnelmode Determines how bars at the same location coordinate are displayed on the graph. With "stack", the bars are stacked on top of one another With "group", the bars are plotted next to one another centered around the shared location. With "overlay", the bars are plotted over one another, you might need to an "opacity" to see multiple bars. geo plotly.graph_objects.layout.Geo instance or dict with compatible properties grid plotly.graph_objects.layout.Grid instance or dict with compatible properties height Sets the plot's height (in px). hiddenlabels hiddenlabels is the funnelarea & pie chart analog of visible:'legendonly' but it can contain many labels, and can simultaneously hide slices from several pies/funnelarea charts hiddenlabelssrc Sets the source reference on plot.ly for hiddenlabels . hidesources Determines whether or not a text link citing the data source is placed at the bottom-right cored of the figure. Has only an effect only on graphs that have been generated via forked graphs from the plotly service (at https://plot.ly or on-premise). hoverdistance Sets the default distance (in pixels) to look for data to add hover labels (-1 means no cutoff, 0 means no looking for data). This is only a real distance for hovering on point-like objects, like scatter points. For area-like objects (bars, scatter fills, etc) hovering is on inside the area and off outside, but these objects will not supersede hover on point-like objects in case of conflict. hoverlabel plotly.graph_objects.layout.Hoverlabel instance or dict with compatible properties hovermode Determines the mode of hover interactions. If `clickmode` includes the "select" flag, `hovermode` defaults to "closest". If `clickmode` lacks the "select" flag, it defaults to "x" or "y" (depending on the trace's `orientation` value) for plots based on cartesian coordinates. For anything else the default value is "closest". images A tuple of plotly.graph_objects.layout.Image instances or dicts with compatible properties imagedefaults When used in a template (as layout.template.layout.imagedefaults), sets the default property values to use for elements of layout.images legend plotly.graph_objects.layout.Legend instance or dict with compatible properties mapbox plotly.graph_objects.layout.Mapbox instance or dict with compatible properties margin plotly.graph_objects.layout.Margin instance or dict with compatible properties meta Assigns extra meta information that can be used in various `text` attributes. Attributes such as the graph, axis and colorbar `title.text`, annotation `text` `trace.name` in legend items, `rangeselector`, `updatemenus` and `sliders` `label` text all support `meta`. One can access `meta` fields using template strings: `%{meta[i]}` where `i` is the index of the `meta` item in question. `meta` can also be an object for example `{key: value}` which can be accessed %{meta[key]}. metasrc Sets the source reference on plot.ly for meta . modebar plotly.graph_objects.layout.Modebar instance or dict with compatible properties orientation Legacy polar charts are deprecated! Please switch to "polar" subplots. Rotates the entire polar by the given angle in legacy polar charts. paper_bgcolor Sets the color of paper where the graph is drawn. piecolorway Sets the default pie slice colors. Defaults to the main `colorway` used for trace colors. If you specify a new list here it can still be extended with lighter and darker colors, see `extendpiecolors`. plot_bgcolor Sets the color of plotting area in-between x and y axes. polar plotly.graph_objects.layout.Polar instance or dict with compatible properties radialaxis plotly.graph_objects.layout.RadialAxis instance or dict with compatible properties scene plotly.graph_objects.layout.Scene instance or dict with compatible properties selectdirection When "dragmode" is set to "select", this limits the selection of the drag to horizontal, vertical or diagonal. "h" only allows horizontal selection, "v" only vertical, "d" only diagonal and "any" sets no limit. selectionrevision Controls persistence of user-driven changes in selected points from all traces. separators Sets the decimal and thousand separators. For example, *. * puts a '.' before decimals and a space between thousands. In English locales, dflt is ".," but other locales may alter this default. shapes A tuple of plotly.graph_objects.layout.Shape instances or dicts with compatible properties shapedefaults When used in a template (as layout.template.layout.shapedefaults), sets the default property values to use for elements of layout.shapes showlegend Determines whether or not a legend is drawn. Default is `true` if there is a trace to show and any of these: a) Two or more traces would by default be shown in the legend. b) One pie trace is shown in the legend. c) One trace is explicitly given with `showlegend: true`. sliders A tuple of plotly.graph_objects.layout.Slider instances or dicts with compatible properties sliderdefaults When used in a template (as layout.template.layout.sliderdefaults), sets the default property values to use for elements of layout.sliders spikedistance Sets the default distance (in pixels) to look for data to draw spikelines to (-1 means no cutoff, 0 means no looking for data). As with hoverdistance, distance does not apply to area- like objects. In addition, some objects can be hovered on but will not generate spikelines, such as scatter fills. sunburstcolorway Sets the default sunburst slice colors. Defaults to the main `colorway` used for trace colors. If you specify a new list here it can still be extended with lighter and darker colors, see `extendsunburstcolors`. template Default attributes to be applied to the plot. This should be a dict with format: `{'layout': layoutTemplate, 'data': {trace_type: [traceTemplate, ...], ...}}` where `layoutTemplate` is a dict matching the structure of `figure.layout` and `traceTemplate` is a dict matching the structure of the trace with type `trace_type` (e.g. 'scatter'). Alternatively, this may be specified as an instance of plotly.graph_objs.layout.Template. Trace templates are applied cyclically to traces of each type. Container arrays (eg `annotations`) have special handling: An object ending in `defaults` (eg `annotationdefaults`) is applied to each array item. But if an item has a `templateitemname` key we look in the template array for an item with matching `name` and apply that instead. If no matching `name` is found we mark the item invisible. Any named template item not referenced is appended to the end of the array, so this can be used to add a watermark annotation or a logo image, for example. To omit one of these items on the plot, make an item with matching `templateitemname` and `visible: false`. ternary plotly.graph_objects.layout.Ternary instance or dict with compatible properties title plotly.graph_objects.layout.Title instance or dict with compatible properties titlefont Deprecated: Please use layout.title.font instead. Sets the title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. transition Sets transition options used during Plotly.react updates. treemapcolorway Sets the default treemap slice colors. Defaults to the main `colorway` used for trace colors. If you specify a new list here it can still be extended with lighter and darker colors, see `extendtreemapcolors`. uirevision Used to allow user interactions with the plot to persist after `Plotly.react` calls that are unaware of these interactions. If `uirevision` is omitted, or if it is given and it changed from the previous `Plotly.react` call, the exact new figure is used. If `uirevision` is truthy and did NOT change, any attribute that has been affected by user interactions and did not receive a different value in the new figure will keep the interaction value. `layout.uirevision` attribute serves as the default for `uirevision` attributes in various sub-containers. For finer control you can set these sub-attributes directly. For example, if your app separately controls the data on the x and y axes you might set `xaxis.uirevision=*time*` and `yaxis.uirevision=*cost*`. Then if only the y data is changed, you can update `yaxis.uirevision=*quantity*` and the y axis range will reset but the x axis range will retain any user-driven zoom. updatemenus A tuple of plotly.graph_objects.layout.Updatemenu instances or dicts with compatible properties updatemenudefaults When used in a template (as layout.template.layout.updatemenudefaults), sets the default property values to use for elements of layout.updatemenus violingap Sets the gap (in plot fraction) between violins of adjacent location coordinates. Has no effect on traces that have "width" set. violingroupgap Sets the gap (in plot fraction) between violins of the same location coordinate. Has no effect on traces that have "width" set. violinmode Determines how violins at the same location coordinate are displayed on the graph. If "group", the violins are plotted next to one another centered around the shared location. If "overlay", the violins are plotted over one another, you might need to set "opacity" to see them multiple violins. Has no effect on traces that have "width" set. waterfallgap Sets the gap (in plot fraction) between bars of adjacent location coordinates. waterfallgroupgap Sets the gap (in plot fraction) between bars of the same location coordinate. waterfallmode Determines how bars at the same location coordinate are displayed on the graph. With "group", the bars are plotted next to one another centered around the shared location. With "overlay", the bars are plotted over one another, you might need to an "opacity" to see multiple bars. width Sets the plot's width (in px). xaxis plotly.graph_objects.layout.XAxis instance or dict with compatible properties yaxis plotly.graph_objects.layout.YAxis instance or dict with compatible properties frames The 'frames' property is a tuple of instances of Frame that may be specified as: - A list or tuple of instances of plotly.graph_objs.Frame - A list or tuple of dicts of string/value properties that will be passed to the Frame constructor Supported dict properties: baseframe The name of the frame into which this frame's properties are merged before applying. This is used to unify properties and avoid needing to specify the same values for the same properties in multiple frames. data A list of traces this frame modifies. The format is identical to the normal trace definition. group An identifier that specifies the group to which the frame belongs, used by animate to select a subset of frames. layout Layout properties which this frame modifies. The format is identical to the normal layout definition. name A label by which to identify the frame traces A list of trace indices that identify the respective traces in the data attribute skip_invalid: bool If True, invalid properties in the figure specification will be skipped silently. If False (default) invalid properties in the figure specification will result in a ValueError Raises ------ ValueError if a property in the specification of data, layout, or frames is invalid AND skip_invalid is False """ super(Figure, self).__init__(data, layout, frames, skip_invalid, **kwargs) def add_area( self, customdata=None, customdatasrc=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, ids=None, idssrc=None, legendgroup=None, marker=None, meta=None, metasrc=None, name=None, opacity=None, r=None, rsrc=None, showlegend=None, stream=None, t=None, tsrc=None, uid=None, uirevision=None, visible=None, row=None, col=None, **kwargs ): """ Add a new Area trace Parameters ---------- customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.area.Hoverlabel instance or dict with compatible properties ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. marker plotly.graph_objects.area.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. r Area traces are deprecated! Please switch to the "barpolar" trace type. Sets the radial coordinates for legacy polar chart only. rsrc Sets the source reference on plot.ly for r . showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.area.Stream instance or dict with compatible properties t Area traces are deprecated! Please switch to the "barpolar" trace type. Sets the angular coordinates for legacy polar chart only. tsrc Sets the source reference on plot.ly for t . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- Figure """ new_trace = Area( customdata=customdata, customdatasrc=customdatasrc, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, ids=ids, idssrc=idssrc, legendgroup=legendgroup, marker=marker, meta=meta, metasrc=metasrc, name=name, opacity=opacity, r=r, rsrc=rsrc, showlegend=showlegend, stream=stream, t=t, tsrc=tsrc, uid=uid, uirevision=uirevision, visible=visible, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_bar( self, alignmentgroup=None, base=None, basesrc=None, cliponaxis=None, constraintext=None, customdata=None, customdatasrc=None, dx=None, dy=None, error_x=None, error_y=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, insidetextanchor=None, insidetextfont=None, legendgroup=None, marker=None, meta=None, metasrc=None, name=None, offset=None, offsetgroup=None, offsetsrc=None, opacity=None, orientation=None, outsidetextfont=None, r=None, rsrc=None, selected=None, selectedpoints=None, showlegend=None, stream=None, t=None, text=None, textangle=None, textfont=None, textposition=None, textpositionsrc=None, textsrc=None, texttemplate=None, texttemplatesrc=None, tsrc=None, uid=None, uirevision=None, unselected=None, visible=None, width=None, widthsrc=None, x=None, x0=None, xaxis=None, xcalendar=None, xsrc=None, y=None, y0=None, yaxis=None, ycalendar=None, ysrc=None, row=None, col=None, secondary_y=None, **kwargs ): """ Add a new Bar trace The data visualized by the span of the bars is set in `y` if `orientation` is set th "v" (the default) and the labels are set in `x`. By setting `orientation` to "h", the roles are interchanged. Parameters ---------- alignmentgroup Set several traces linked to the same position axis or matching axes to the same alignmentgroup. This controls whether bars compute their positional range dependently or independently. base Sets where the bar base is drawn (in position axis units). In "stack" or "relative" barmode, traces that set "base" will be excluded and drawn in "overlay" mode instead. basesrc Sets the source reference on plot.ly for base . cliponaxis Determines whether the text nodes are clipped about the subplot axes. To show the text nodes above axis lines and tick labels, make sure to set `xaxis.layer` and `yaxis.layer` to *below traces*. constraintext Constrain the size of text inside or outside a bar to be no larger than the bar itself. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dx Sets the x coordinate step. See `x0` for more info. dy Sets the y coordinate step. See `y0` for more info. error_x plotly.graph_objects.bar.ErrorX instance or dict with compatible properties error_y plotly.graph_objects.bar.ErrorY instance or dict with compatible properties hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.bar.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `value` and `label`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . insidetextanchor Determines if texts are kept at center or start/end points in `textposition` "inside" mode. insidetextfont Sets the font used for `text` lying inside the bar. legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. marker plotly.graph_objects.bar.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. offset Shifts the position where the bar is drawn (in position axis units). In "group" barmode, traces that set "offset" will be excluded and drawn in "overlay" mode instead. offsetgroup Set several traces linked to the same position axis or matching axes to the same offsetgroup where bars of the same position coordinate will line up. offsetsrc Sets the source reference on plot.ly for offset . opacity Sets the opacity of the trace. orientation Sets the orientation of the bars. With "v" ("h"), the value of the each bar spans along the vertical (horizontal). outsidetextfont Sets the font used for `text` lying outside the bar. r r coordinates in scatter traces are deprecated!Please switch to the "scatterpolar" trace type.Sets the radial coordinatesfor legacy polar chart only. rsrc Sets the source reference on plot.ly for r . selected plotly.graph_objects.bar.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.bar.Stream instance or dict with compatible properties t t coordinates in scatter traces are deprecated!Please switch to the "scatterpolar" trace type.Sets the angular coordinatesfor legacy polar chart only. text Sets text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textangle Sets the angle of the tick labels with respect to the bar. For example, a `tickangle` of -90 draws the tick labels vertically. With "auto" the texts may automatically be rotated to fit with the maximum size in bars. textfont Sets the font used for `text`. textposition Specifies the location of the `text`. "inside" positions `text` inside, next to the bar end (rotated and scaled if needed). "outside" positions `text` outside, next to the bar end (scaled if needed), unless there is another bar stacked on this one, then the text gets pushed inside. "auto" tries to position `text` inside the bar, but if the bar is too small and no bar is stacked on this one the text is moved outside. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `value` and `label`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . tsrc Sets the source reference on plot.ly for t . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.bar.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). width Sets the bar width (in position axis units). widthsrc Sets the source reference on plot.ly for width . x Sets the x coordinates. x0 Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . y Sets the y coordinates. y0 Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` secondary_y: boolean or None (default None) If True, associate this trace with the secondary y-axis of the subplot at the specified row and col. Only valid if all of the following conditions are satisfied: * The figure was created using `plotly.subplots.make_subplots`. * The row and col arguments are not None * The subplot at the specified row and col has type xy (which is the default) and secondary_y True. These properties are specified in the specs argument to make_subplots. See the make_subplots docstring for more info. Returns ------- Figure """ new_trace = Bar( alignmentgroup=alignmentgroup, base=base, basesrc=basesrc, cliponaxis=cliponaxis, constraintext=constraintext, customdata=customdata, customdatasrc=customdatasrc, dx=dx, dy=dy, error_x=error_x, error_y=error_y, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, insidetextanchor=insidetextanchor, insidetextfont=insidetextfont, legendgroup=legendgroup, marker=marker, meta=meta, metasrc=metasrc, name=name, offset=offset, offsetgroup=offsetgroup, offsetsrc=offsetsrc, opacity=opacity, orientation=orientation, outsidetextfont=outsidetextfont, r=r, rsrc=rsrc, selected=selected, selectedpoints=selectedpoints, showlegend=showlegend, stream=stream, t=t, text=text, textangle=textangle, textfont=textfont, textposition=textposition, textpositionsrc=textpositionsrc, textsrc=textsrc, texttemplate=texttemplate, texttemplatesrc=texttemplatesrc, tsrc=tsrc, uid=uid, uirevision=uirevision, unselected=unselected, visible=visible, width=width, widthsrc=widthsrc, x=x, x0=x0, xaxis=xaxis, xcalendar=xcalendar, xsrc=xsrc, y=y, y0=y0, yaxis=yaxis, ycalendar=ycalendar, ysrc=ysrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) def add_barpolar( self, base=None, basesrc=None, customdata=None, customdatasrc=None, dr=None, dtheta=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, legendgroup=None, marker=None, meta=None, metasrc=None, name=None, offset=None, offsetsrc=None, opacity=None, r=None, r0=None, rsrc=None, selected=None, selectedpoints=None, showlegend=None, stream=None, subplot=None, text=None, textsrc=None, theta=None, theta0=None, thetasrc=None, thetaunit=None, uid=None, uirevision=None, unselected=None, visible=None, width=None, widthsrc=None, row=None, col=None, **kwargs ): """ Add a new Barpolar trace The data visualized by the radial span of the bars is set in `r` Parameters ---------- base Sets where the bar base is drawn (in radial axis units). In "stack" barmode, traces that set "base" will be excluded and drawn in "overlay" mode instead. basesrc Sets the source reference on plot.ly for base . customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dr Sets the r coordinate step. dtheta Sets the theta coordinate step. By default, the `dtheta` step equals the subplot's period divided by the length of the `r` coordinates. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.barpolar.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. marker plotly.graph_objects.barpolar.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. offset Shifts the angular position where the bar is drawn (in "thetatunit" units). offsetsrc Sets the source reference on plot.ly for offset . opacity Sets the opacity of the trace. r Sets the radial coordinates r0 Alternate to `r`. Builds a linear space of r coordinates. Use with `dr` where `r0` is the starting coordinate and `dr` the step. rsrc Sets the source reference on plot.ly for r . selected plotly.graph_objects.barpolar.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.barpolar.Stream instance or dict with compatible properties subplot Sets a reference between this trace's data coordinates and a polar subplot. If "polar" (the default value), the data refer to `layout.polar`. If "polar2", the data refer to `layout.polar2`, and so on. text Sets hover text elements associated with each bar. If a single string, the same string appears over all bars. If an array of string, the items are mapped in order to the this trace's coordinates. textsrc Sets the source reference on plot.ly for text . theta Sets the angular coordinates theta0 Alternate to `theta`. Builds a linear space of theta coordinates. Use with `dtheta` where `theta0` is the starting coordinate and `dtheta` the step. thetasrc Sets the source reference on plot.ly for theta . thetaunit Sets the unit of input "theta" values. Has an effect only when on "linear" angular axes. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.barpolar.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). width Sets the bar angular width (in "thetaunit" units). widthsrc Sets the source reference on plot.ly for width . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- Figure """ new_trace = Barpolar( base=base, basesrc=basesrc, customdata=customdata, customdatasrc=customdatasrc, dr=dr, dtheta=dtheta, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, legendgroup=legendgroup, marker=marker, meta=meta, metasrc=metasrc, name=name, offset=offset, offsetsrc=offsetsrc, opacity=opacity, r=r, r0=r0, rsrc=rsrc, selected=selected, selectedpoints=selectedpoints, showlegend=showlegend, stream=stream, subplot=subplot, text=text, textsrc=textsrc, theta=theta, theta0=theta0, thetasrc=thetasrc, thetaunit=thetaunit, uid=uid, uirevision=uirevision, unselected=unselected, visible=visible, width=width, widthsrc=widthsrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_box( self, alignmentgroup=None, boxmean=None, boxpoints=None, customdata=None, customdatasrc=None, fillcolor=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hoveron=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, jitter=None, legendgroup=None, line=None, marker=None, meta=None, metasrc=None, name=None, notched=None, notchwidth=None, offsetgroup=None, opacity=None, orientation=None, pointpos=None, selected=None, selectedpoints=None, showlegend=None, stream=None, text=None, textsrc=None, uid=None, uirevision=None, unselected=None, visible=None, whiskerwidth=None, width=None, x=None, x0=None, xaxis=None, xcalendar=None, xsrc=None, y=None, y0=None, yaxis=None, ycalendar=None, ysrc=None, row=None, col=None, secondary_y=None, **kwargs ): """ Add a new Box trace In vertical (horizontal) box plots, statistics are computed using `y` (`x`) values. By supplying an `x` (`y`) array, one box per distinct x (y) value is drawn If no `x` (`y`) list is provided, a single box is drawn. That box position is then positioned with with `name` or with `x0` (`y0`) if provided. Each box spans from quartile 1 (Q1) to quartile 3 (Q3). The second quartile (Q2) is marked by a line inside the box. By default, the whiskers correspond to the box' edges +/- 1.5 times the interquartile range (IQR: Q3-Q1), see "boxpoints" for other options. Parameters ---------- alignmentgroup Set several traces linked to the same position axis or matching axes to the same alignmentgroup. This controls whether bars compute their positional range dependently or independently. boxmean If True, the mean of the box(es)' underlying distribution is drawn as a dashed line inside the box(es). If "sd" the standard deviation is also drawn. boxpoints If "outliers", only the sample points lying outside the whiskers are shown If "suspectedoutliers", the outlier points are shown and points either less than 4*Q1-3*Q3 or greater than 4*Q3-3*Q1 are highlighted (see `outliercolor`) If "all", all sample points are shown If False, only the box(es) are shown with no sample points customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . fillcolor Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.box.Hoverlabel instance or dict with compatible properties hoveron Do the hover effects highlight individual boxes or sample points or both? hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . jitter Sets the amount of jitter in the sample points drawn. If 0, the sample points align along the distribution axis. If 1, the sample points are drawn in a random jitter of width equal to the width of the box(es). legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.box.Line instance or dict with compatible properties marker plotly.graph_objects.box.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. For box traces, the name will also be used for the position coordinate, if `x` and `x0` (`y` and `y0` if horizontal) are missing and the position axis is categorical notched Determines whether or not notches should be drawn. notchwidth Sets the width of the notches relative to the box' width. For example, with 0, the notches are as wide as the box(es). offsetgroup Set several traces linked to the same position axis or matching axes to the same offsetgroup where bars of the same position coordinate will line up. opacity Sets the opacity of the trace. orientation Sets the orientation of the box(es). If "v" ("h"), the distribution is visualized along the vertical (horizontal). pointpos Sets the position of the sample points in relation to the box(es). If 0, the sample points are places over the center of the box(es). Positive (negative) values correspond to positions to the right (left) for vertical boxes and above (below) for horizontal boxes selected plotly.graph_objects.box.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.box.Stream instance or dict with compatible properties text Sets the text elements associated with each sample value. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.box.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). whiskerwidth Sets the width of the whiskers relative to the box' width. For example, with 1, the whiskers are as wide as the box(es). width Sets the width of the box in data coordinate If 0 (default value) the width is automatically selected based on the positions of other box traces in the same subplot. x Sets the x sample data or coordinates. See overview for more info. x0 Sets the x coordinate of the box. See overview for more info. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . y Sets the y sample data or coordinates. See overview for more info. y0 Sets the y coordinate of the box. See overview for more info. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` secondary_y: boolean or None (default None) If True, associate this trace with the secondary y-axis of the subplot at the specified row and col. Only valid if all of the following conditions are satisfied: * The figure was created using `plotly.subplots.make_subplots`. * The row and col arguments are not None * The subplot at the specified row and col has type xy (which is the default) and secondary_y True. These properties are specified in the specs argument to make_subplots. See the make_subplots docstring for more info. Returns ------- Figure """ new_trace = Box( alignmentgroup=alignmentgroup, boxmean=boxmean, boxpoints=boxpoints, customdata=customdata, customdatasrc=customdatasrc, fillcolor=fillcolor, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hoveron=hoveron, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, jitter=jitter, legendgroup=legendgroup, line=line, marker=marker, meta=meta, metasrc=metasrc, name=name, notched=notched, notchwidth=notchwidth, offsetgroup=offsetgroup, opacity=opacity, orientation=orientation, pointpos=pointpos, selected=selected, selectedpoints=selectedpoints, showlegend=showlegend, stream=stream, text=text, textsrc=textsrc, uid=uid, uirevision=uirevision, unselected=unselected, visible=visible, whiskerwidth=whiskerwidth, width=width, x=x, x0=x0, xaxis=xaxis, xcalendar=xcalendar, xsrc=xsrc, y=y, y0=y0, yaxis=yaxis, ycalendar=ycalendar, ysrc=ysrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) def add_candlestick( self, close=None, closesrc=None, customdata=None, customdatasrc=None, decreasing=None, high=None, highsrc=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, increasing=None, legendgroup=None, line=None, low=None, lowsrc=None, meta=None, metasrc=None, name=None, opacity=None, open=None, opensrc=None, selectedpoints=None, showlegend=None, stream=None, text=None, textsrc=None, uid=None, uirevision=None, visible=None, whiskerwidth=None, x=None, xaxis=None, xcalendar=None, xsrc=None, yaxis=None, row=None, col=None, secondary_y=None, **kwargs ): """ Add a new Candlestick trace The candlestick is a style of financial chart describing open, high, low and close for a given `x` coordinate (most likely time). The boxes represent the spread between the `open` and `close` values and the lines represent the spread between the `low` and `high` values Sample points where the close value is higher (lower) then the open value are called increasing (decreasing). By default, increasing candles are drawn in green whereas decreasing are drawn in red. Parameters ---------- close Sets the close values. closesrc Sets the source reference on plot.ly for close . customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . decreasing plotly.graph_objects.candlestick.Decreasing instance or dict with compatible properties high Sets the high values. highsrc Sets the source reference on plot.ly for high . hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.candlestick.Hoverlabel instance or dict with compatible properties hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . increasing plotly.graph_objects.candlestick.Increasing instance or dict with compatible properties legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.candlestick.Line instance or dict with compatible properties low Sets the low values. lowsrc Sets the source reference on plot.ly for low . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. open Sets the open values. opensrc Sets the source reference on plot.ly for open . selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.candlestick.Stream instance or dict with compatible properties text Sets hover text elements associated with each sample point. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to this trace's sample points. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). whiskerwidth Sets the width of the whiskers relative to the box' width. For example, with 1, the whiskers are as wide as the box(es). x Sets the x coordinates. If absent, linear coordinate will be generated. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` secondary_y: boolean or None (default None) If True, associate this trace with the secondary y-axis of the subplot at the specified row and col. Only valid if all of the following conditions are satisfied: * The figure was created using `plotly.subplots.make_subplots`. * The row and col arguments are not None * The subplot at the specified row and col has type xy (which is the default) and secondary_y True. These properties are specified in the specs argument to make_subplots. See the make_subplots docstring for more info. Returns ------- Figure """ new_trace = Candlestick( close=close, closesrc=closesrc, customdata=customdata, customdatasrc=customdatasrc, decreasing=decreasing, high=high, highsrc=highsrc, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, increasing=increasing, legendgroup=legendgroup, line=line, low=low, lowsrc=lowsrc, meta=meta, metasrc=metasrc, name=name, opacity=opacity, open=open, opensrc=opensrc, selectedpoints=selectedpoints, showlegend=showlegend, stream=stream, text=text, textsrc=textsrc, uid=uid, uirevision=uirevision, visible=visible, whiskerwidth=whiskerwidth, x=x, xaxis=xaxis, xcalendar=xcalendar, xsrc=xsrc, yaxis=yaxis, **kwargs ) return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) def add_carpet( self, a=None, a0=None, aaxis=None, asrc=None, b=None, b0=None, baxis=None, bsrc=None, carpet=None, cheaterslope=None, color=None, customdata=None, customdatasrc=None, da=None, db=None, font=None, ids=None, idssrc=None, meta=None, metasrc=None, name=None, opacity=None, stream=None, uid=None, uirevision=None, visible=None, x=None, xaxis=None, xsrc=None, y=None, yaxis=None, ysrc=None, row=None, col=None, secondary_y=None, **kwargs ): """ Add a new Carpet trace The data describing carpet axis layout is set in `y` and (optionally) also `x`. If only `y` is present, `x` the plot is interpreted as a cheater plot and is filled in using the `y` values. `x` and `y` may either be 2D arrays matching with each dimension matching that of `a` and `b`, or they may be 1D arrays with total length equal to that of `a` and `b`. Parameters ---------- a An array containing values of the first parameter value a0 Alternate to `a`. Builds a linear space of a coordinates. Use with `da` where `a0` is the starting coordinate and `da` the step. aaxis plotly.graph_objects.carpet.Aaxis instance or dict with compatible properties asrc Sets the source reference on plot.ly for a . b A two dimensional array of y coordinates at each carpet point. b0 Alternate to `b`. Builds a linear space of a coordinates. Use with `db` where `b0` is the starting coordinate and `db` the step. baxis plotly.graph_objects.carpet.Baxis instance or dict with compatible properties bsrc Sets the source reference on plot.ly for b . carpet An identifier for this carpet, so that `scattercarpet` and `contourcarpet` traces can specify a carpet plot on which they lie cheaterslope The shift applied to each successive row of data in creating a cheater plot. Only used if `x` is been ommitted. color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . da Sets the a coordinate step. See `a0` for more info. db Sets the b coordinate step. See `b0` for more info. font The default font used for axis & tick labels on this carpet ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. stream plotly.graph_objects.carpet.Stream instance or dict with compatible properties uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x A two dimensional array of x coordinates at each carpet point. If ommitted, the plot is a cheater plot and the xaxis is hidden by default. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xsrc Sets the source reference on plot.ly for x . y A two dimensional array of y coordinates at each carpet point. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ysrc Sets the source reference on plot.ly for y . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` secondary_y: boolean or None (default None) If True, associate this trace with the secondary y-axis of the subplot at the specified row and col. Only valid if all of the following conditions are satisfied: * The figure was created using `plotly.subplots.make_subplots`. * The row and col arguments are not None * The subplot at the specified row and col has type xy (which is the default) and secondary_y True. These properties are specified in the specs argument to make_subplots. See the make_subplots docstring for more info. Returns ------- Figure """ new_trace = Carpet( a=a, a0=a0, aaxis=aaxis, asrc=asrc, b=b, b0=b0, baxis=baxis, bsrc=bsrc, carpet=carpet, cheaterslope=cheaterslope, color=color, customdata=customdata, customdatasrc=customdatasrc, da=da, db=db, font=font, ids=ids, idssrc=idssrc, meta=meta, metasrc=metasrc, name=name, opacity=opacity, stream=stream, uid=uid, uirevision=uirevision, visible=visible, x=x, xaxis=xaxis, xsrc=xsrc, y=y, yaxis=yaxis, ysrc=ysrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) def add_choropleth( self, autocolorscale=None, coloraxis=None, colorbar=None, colorscale=None, customdata=None, customdatasrc=None, geo=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, locationmode=None, locations=None, locationssrc=None, marker=None, meta=None, metasrc=None, name=None, reversescale=None, selected=None, selectedpoints=None, showscale=None, stream=None, text=None, textsrc=None, uid=None, uirevision=None, unselected=None, visible=None, z=None, zauto=None, zmax=None, zmid=None, zmin=None, zsrc=None, row=None, col=None, **kwargs ): """ Add a new Choropleth trace The data that describes the choropleth value-to-color mapping is set in `z`. The geographic locations corresponding to each value in `z` are set in `locations`. Parameters ---------- autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.choropleth.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . geo Sets a reference between this trace's geospatial coordinates and a geographic map. If "geo" (the default value), the geospatial coordinates refer to `layout.geo`. If "geo2", the geospatial coordinates refer to `layout.geo2`, and so on. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.choropleth.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . locationmode Determines the set of locations used to match entries in `locations` to regions on the map. locations Sets the coordinates via location IDs or names. See `locationmode` for more info. locationssrc Sets the source reference on plot.ly for locations . marker plotly.graph_objects.choropleth.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. reversescale Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. selected plotly.graph_objects.choropleth.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.choropleth.Stream instance or dict with compatible properties text Sets the text elements associated with each location. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.choropleth.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). z Sets the color values. zauto Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. zmax Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. zmid Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. zmin Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. zsrc Sets the source reference on plot.ly for z . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- Figure """ new_trace = Choropleth( autocolorscale=autocolorscale, coloraxis=coloraxis, colorbar=colorbar, colorscale=colorscale, customdata=customdata, customdatasrc=customdatasrc, geo=geo, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, locationmode=locationmode, locations=locations, locationssrc=locationssrc, marker=marker, meta=meta, metasrc=metasrc, name=name, reversescale=reversescale, selected=selected, selectedpoints=selectedpoints, showscale=showscale, stream=stream, text=text, textsrc=textsrc, uid=uid, uirevision=uirevision, unselected=unselected, visible=visible, z=z, zauto=zauto, zmax=zmax, zmid=zmid, zmin=zmin, zsrc=zsrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_choroplethmapbox( self, autocolorscale=None, below=None, coloraxis=None, colorbar=None, colorscale=None, customdata=None, customdatasrc=None, geojson=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, locations=None, locationssrc=None, marker=None, meta=None, metasrc=None, name=None, reversescale=None, selected=None, selectedpoints=None, showscale=None, stream=None, subplot=None, text=None, textsrc=None, uid=None, uirevision=None, unselected=None, visible=None, z=None, zauto=None, zmax=None, zmid=None, zmin=None, zsrc=None, row=None, col=None, **kwargs ): """ Add a new Choroplethmapbox trace GeoJSON features to be filled are set in `geojson` The data that describes the choropleth value-to-color mapping is set in `locations` and `z`. Parameters ---------- autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. below Determines if the choropleth polygons will be inserted before the layer with the specified ID. By default, choroplethmapbox traces are placed above the water layers. If set to '', the layer will be inserted above every existing layer. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.choroplethmapbox.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . geojson Sets the GeoJSON data associated with this trace. Can be set as a valid GeoJSON object or as URL string Note that we only accept GeoJSON of type "FeatureCollection" and "Feature" with geometries of type "Polygon" and "MultiPolygon". hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.choroplethmapbox.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variable `properties` Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . locations Sets which features found in "geojson" to plot using their feature `id` field. locationssrc Sets the source reference on plot.ly for locations . marker plotly.graph_objects.choroplethmapbox.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. reversescale Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. selected plotly.graph_objects.choroplethmapbox.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.choroplethmapbox.Stream instance or dict with compatible properties subplot Sets a reference between this trace's data coordinates and a mapbox subplot. If "mapbox" (the default value), the data refer to `layout.mapbox`. If "mapbox2", the data refer to `layout.mapbox2`, and so on. text Sets the text elements associated with each location. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.choroplethmapbox.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). z Sets the color values. zauto Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. zmax Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. zmid Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. zmin Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. zsrc Sets the source reference on plot.ly for z . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- Figure """ new_trace = Choroplethmapbox( autocolorscale=autocolorscale, below=below, coloraxis=coloraxis, colorbar=colorbar, colorscale=colorscale, customdata=customdata, customdatasrc=customdatasrc, geojson=geojson, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, locations=locations, locationssrc=locationssrc, marker=marker, meta=meta, metasrc=metasrc, name=name, reversescale=reversescale, selected=selected, selectedpoints=selectedpoints, showscale=showscale, stream=stream, subplot=subplot, text=text, textsrc=textsrc, uid=uid, uirevision=uirevision, unselected=unselected, visible=visible, z=z, zauto=zauto, zmax=zmax, zmid=zmid, zmin=zmin, zsrc=zsrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_cone( self, anchor=None, autocolorscale=None, cauto=None, cmax=None, cmid=None, cmin=None, coloraxis=None, colorbar=None, colorscale=None, customdata=None, customdatasrc=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, lighting=None, lightposition=None, meta=None, metasrc=None, name=None, opacity=None, reversescale=None, scene=None, showscale=None, sizemode=None, sizeref=None, stream=None, text=None, textsrc=None, u=None, uid=None, uirevision=None, usrc=None, v=None, visible=None, vsrc=None, w=None, wsrc=None, x=None, xsrc=None, y=None, ysrc=None, z=None, zsrc=None, row=None, col=None, **kwargs ): """ Add a new Cone trace Use cone traces to visualize vector fields. Specify a vector field using 6 1D arrays, 3 position arrays `x`, `y` and `z` and 3 vector component arrays `u`, `v`, `w`. The cones are drawn exactly at the positions given by `x`, `y` and `z`. Parameters ---------- anchor Sets the cones' anchor with respect to their x/y/z positions. Note that "cm" denote the cone's center of mass which corresponds to 1/4 from the tail to tip. autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here u/v/w norm) or the bounds set in `cmin` and `cmax` Defaults to `false` when `cmin` and `cmax` are set by the user. cmax Sets the upper bound of the color domain. Value should have the same units as u/v/w norm and if set, `cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `cmin` and/or `cmax` to be equidistant to this point. Value should have the same units as u/v/w norm. Has no effect when `cauto` is `false`. cmin Sets the lower bound of the color domain. Value should have the same units as u/v/w norm and if set, `cmax` must be set as well. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.cone.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`cmin` and `cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.cone.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variable `norm` Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . lighting plotly.graph_objects.cone.Lighting instance or dict with compatible properties lightposition plotly.graph_objects.cone.Lightposition instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the surface. Please note that in the case of using high `opacity` values for example a value greater than or equal to 0.5 on two surfaces (and 0.25 with four surfaces), an overlay of multiple transparent surfaces may not perfectly be sorted in depth by the webgl API. This behavior may be improved in the near future and is subject to change. reversescale Reverses the color mapping if true. If true, `cmin` will correspond to the last color in the array and `cmax` will correspond to the first color. scene Sets a reference between this trace's 3D coordinate system and a 3D scene. If "scene" (the default value), the (x,y,z) coordinates refer to `layout.scene`. If "scene2", the (x,y,z) coordinates refer to `layout.scene2`, and so on. showscale Determines whether or not a colorbar is displayed for this trace. sizemode Determines whether `sizeref` is set as a "scaled" (i.e unitless) scalar (normalized by the max u/v/w norm in the vector field) or as "absolute" value (in the same units as the vector field). sizeref Adjusts the cone size scaling. The size of the cones is determined by their u/v/w norm multiplied a factor and `sizeref`. This factor (computed internally) corresponds to the minimum "time" to travel across two successive x/y/z positions at the average velocity of those two successive positions. All cones in a given trace use the same factor. With `sizemode` set to "scaled", `sizeref` is unitless, its default value is 0.5 With `sizemode` set to "absolute", `sizeref` has the same units as the u/v/w vector field, its the default value is half the sample's maximum vector norm. stream plotly.graph_objects.cone.Stream instance or dict with compatible properties text Sets the text elements associated with the cones. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textsrc Sets the source reference on plot.ly for text . u Sets the x components of the vector field. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. usrc Sets the source reference on plot.ly for u . v Sets the y components of the vector field. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). vsrc Sets the source reference on plot.ly for v . w Sets the z components of the vector field. wsrc Sets the source reference on plot.ly for w . x Sets the x coordinates of the vector field and of the displayed cones. xsrc Sets the source reference on plot.ly for x . y Sets the y coordinates of the vector field and of the displayed cones. ysrc Sets the source reference on plot.ly for y . z Sets the z coordinates of the vector field and of the displayed cones. zsrc Sets the source reference on plot.ly for z . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- Figure """ new_trace = Cone( anchor=anchor, autocolorscale=autocolorscale, cauto=cauto, cmax=cmax, cmid=cmid, cmin=cmin, coloraxis=coloraxis, colorbar=colorbar, colorscale=colorscale, customdata=customdata, customdatasrc=customdatasrc, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, lighting=lighting, lightposition=lightposition, meta=meta, metasrc=metasrc, name=name, opacity=opacity, reversescale=reversescale, scene=scene, showscale=showscale, sizemode=sizemode, sizeref=sizeref, stream=stream, text=text, textsrc=textsrc, u=u, uid=uid, uirevision=uirevision, usrc=usrc, v=v, visible=visible, vsrc=vsrc, w=w, wsrc=wsrc, x=x, xsrc=xsrc, y=y, ysrc=ysrc, z=z, zsrc=zsrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_contour( self, autocolorscale=None, autocontour=None, coloraxis=None, colorbar=None, colorscale=None, connectgaps=None, contours=None, customdata=None, customdatasrc=None, dx=None, dy=None, fillcolor=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hoverongaps=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, legendgroup=None, line=None, meta=None, metasrc=None, name=None, ncontours=None, opacity=None, reversescale=None, showlegend=None, showscale=None, stream=None, text=None, textsrc=None, transpose=None, uid=None, uirevision=None, visible=None, x=None, x0=None, xaxis=None, xcalendar=None, xsrc=None, xtype=None, y=None, y0=None, yaxis=None, ycalendar=None, ysrc=None, ytype=None, z=None, zauto=None, zhoverformat=None, zmax=None, zmid=None, zmin=None, zsrc=None, row=None, col=None, secondary_y=None, **kwargs ): """ Add a new Contour trace The data from which contour lines are computed is set in `z`. Data in `z` must be a 2D list of numbers. Say that `z` has N rows and M columns, then by default, these N rows correspond to N y coordinates (set in `y` or auto-generated) and the M columns correspond to M x coordinates (set in `x` or auto- generated). By setting `transpose` to True, the above behavior is flipped. Parameters ---------- autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. autocontour Determines whether or not the contour level attributes are picked by an algorithm. If True, the number of contour levels can be set in `ncontours`. If False, set the contour level attributes in `contours`. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.contour.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the `z` data are filled in. It is defaulted to true if `z` is a one dimensional array otherwise it is defaulted to false. contours plotly.graph_objects.contour.Contours instance or dict with compatible properties customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dx Sets the x coordinate step. See `x0` for more info. dy Sets the y coordinate step. See `y0` for more info. fillcolor Sets the fill color if `contours.type` is "constraint". Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.contour.Hoverlabel instance or dict with compatible properties hoverongaps Determines whether or not gaps (i.e. {nan} or missing values) in the `z` data have hover labels associated with them. hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.contour.Line instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. ncontours Sets the maximum number of contour levels. The actual number of contours will be chosen automatically to be less than or equal to the value of `ncontours`. Has an effect only if `autocontour` is True or if `contours.size` is missing. opacity Sets the opacity of the trace. reversescale Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.contour.Stream instance or dict with compatible properties text Sets the text elements associated with each z value. textsrc Sets the source reference on plot.ly for text . transpose Transposes the z data. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the x coordinates. x0 Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . xtype If "array", the heatmap's x coordinates are given by "x" (the default behavior when `x` is provided). If "scaled", the heatmap's x coordinates are given by "x0" and "dx" (the default behavior when `x` is not provided). y Sets the y coordinates. y0 Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . ytype If "array", the heatmap's y coordinates are given by "y" (the default behavior when `y` is provided) If "scaled", the heatmap's y coordinates are given by "y0" and "dy" (the default behavior when `y` is not provided) z Sets the z data. zauto Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. zhoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. See: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format zmax Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. zmid Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. zmin Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. zsrc Sets the source reference on plot.ly for z . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` secondary_y: boolean or None (default None) If True, associate this trace with the secondary y-axis of the subplot at the specified row and col. Only valid if all of the following conditions are satisfied: * The figure was created using `plotly.subplots.make_subplots`. * The row and col arguments are not None * The subplot at the specified row and col has type xy (which is the default) and secondary_y True. These properties are specified in the specs argument to make_subplots. See the make_subplots docstring for more info. Returns ------- Figure """ new_trace = Contour( autocolorscale=autocolorscale, autocontour=autocontour, coloraxis=coloraxis, colorbar=colorbar, colorscale=colorscale, connectgaps=connectgaps, contours=contours, customdata=customdata, customdatasrc=customdatasrc, dx=dx, dy=dy, fillcolor=fillcolor, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hoverongaps=hoverongaps, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, legendgroup=legendgroup, line=line, meta=meta, metasrc=metasrc, name=name, ncontours=ncontours, opacity=opacity, reversescale=reversescale, showlegend=showlegend, showscale=showscale, stream=stream, text=text, textsrc=textsrc, transpose=transpose, uid=uid, uirevision=uirevision, visible=visible, x=x, x0=x0, xaxis=xaxis, xcalendar=xcalendar, xsrc=xsrc, xtype=xtype, y=y, y0=y0, yaxis=yaxis, ycalendar=ycalendar, ysrc=ysrc, ytype=ytype, z=z, zauto=zauto, zhoverformat=zhoverformat, zmax=zmax, zmid=zmid, zmin=zmin, zsrc=zsrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) def add_contourcarpet( self, a=None, a0=None, asrc=None, atype=None, autocolorscale=None, autocontour=None, b=None, b0=None, bsrc=None, btype=None, carpet=None, coloraxis=None, colorbar=None, colorscale=None, contours=None, customdata=None, customdatasrc=None, da=None, db=None, fillcolor=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, legendgroup=None, line=None, meta=None, metasrc=None, name=None, ncontours=None, opacity=None, reversescale=None, showlegend=None, showscale=None, stream=None, text=None, textsrc=None, transpose=None, uid=None, uirevision=None, visible=None, xaxis=None, yaxis=None, z=None, zauto=None, zmax=None, zmid=None, zmin=None, zsrc=None, row=None, col=None, secondary_y=None, **kwargs ): """ Add a new Contourcarpet trace Plots contours on either the first carpet axis or the carpet axis with a matching `carpet` attribute. Data `z` is interpreted as matching that of the corresponding carpet axis. Parameters ---------- a Sets the x coordinates. a0 Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. asrc Sets the source reference on plot.ly for a . atype If "array", the heatmap's x coordinates are given by "x" (the default behavior when `x` is provided). If "scaled", the heatmap's x coordinates are given by "x0" and "dx" (the default behavior when `x` is not provided). autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. autocontour Determines whether or not the contour level attributes are picked by an algorithm. If True, the number of contour levels can be set in `ncontours`. If False, set the contour level attributes in `contours`. b Sets the y coordinates. b0 Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. bsrc Sets the source reference on plot.ly for b . btype If "array", the heatmap's y coordinates are given by "y" (the default behavior when `y` is provided) If "scaled", the heatmap's y coordinates are given by "y0" and "dy" (the default behavior when `y` is not provided) carpet The `carpet` of the carpet axes on which this contour trace lies coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.contourcarpet.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. contours plotly.graph_objects.contourcarpet.Contours instance or dict with compatible properties customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . da Sets the x coordinate step. See `x0` for more info. db Sets the y coordinate step. See `y0` for more info. fillcolor Sets the fill color if `contours.type` is "constraint". Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.contourcarpet.Line instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. ncontours Sets the maximum number of contour levels. The actual number of contours will be chosen automatically to be less than or equal to the value of `ncontours`. Has an effect only if `autocontour` is True or if `contours.size` is missing. opacity Sets the opacity of the trace. reversescale Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.contourcarpet.Stream instance or dict with compatible properties text Sets the text elements associated with each z value. textsrc Sets the source reference on plot.ly for text . transpose Transposes the z data. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. z Sets the z data. zauto Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. zmax Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. zmid Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. zmin Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. zsrc Sets the source reference on plot.ly for z . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` secondary_y: boolean or None (default None) If True, associate this trace with the secondary y-axis of the subplot at the specified row and col. Only valid if all of the following conditions are satisfied: * The figure was created using `plotly.subplots.make_subplots`. * The row and col arguments are not None * The subplot at the specified row and col has type xy (which is the default) and secondary_y True. These properties are specified in the specs argument to make_subplots. See the make_subplots docstring for more info. Returns ------- Figure """ new_trace = Contourcarpet( a=a, a0=a0, asrc=asrc, atype=atype, autocolorscale=autocolorscale, autocontour=autocontour, b=b, b0=b0, bsrc=bsrc, btype=btype, carpet=carpet, coloraxis=coloraxis, colorbar=colorbar, colorscale=colorscale, contours=contours, customdata=customdata, customdatasrc=customdatasrc, da=da, db=db, fillcolor=fillcolor, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, legendgroup=legendgroup, line=line, meta=meta, metasrc=metasrc, name=name, ncontours=ncontours, opacity=opacity, reversescale=reversescale, showlegend=showlegend, showscale=showscale, stream=stream, text=text, textsrc=textsrc, transpose=transpose, uid=uid, uirevision=uirevision, visible=visible, xaxis=xaxis, yaxis=yaxis, z=z, zauto=zauto, zmax=zmax, zmid=zmid, zmin=zmin, zsrc=zsrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) def add_densitymapbox( self, autocolorscale=None, below=None, coloraxis=None, colorbar=None, colorscale=None, customdata=None, customdatasrc=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, lat=None, latsrc=None, lon=None, lonsrc=None, meta=None, metasrc=None, name=None, opacity=None, radius=None, radiussrc=None, reversescale=None, showscale=None, stream=None, subplot=None, text=None, textsrc=None, uid=None, uirevision=None, visible=None, z=None, zauto=None, zmax=None, zmid=None, zmin=None, zsrc=None, row=None, col=None, **kwargs ): """ Add a new Densitymapbox trace Draws a bivariate kernel density estimation with a Gaussian kernel from `lon` and `lat` coordinates and optional `z` values using a colorscale. Parameters ---------- autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. below Determines if the densitymapbox trace will be inserted before the layer with the specified ID. By default, densitymapbox traces are placed below the first layer of type symbol If set to '', the layer will be inserted above every existing layer. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.densitymapbox.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.densitymapbox.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (lon,lat) pair If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (lon,lat) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . lat Sets the latitude coordinates (in degrees North). latsrc Sets the source reference on plot.ly for lat . lon Sets the longitude coordinates (in degrees East). lonsrc Sets the source reference on plot.ly for lon . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. radius Sets the radius of influence of one `lon` / `lat` point in pixels. Increasing the value makes the densitymapbox trace smoother, but less detailed. radiussrc Sets the source reference on plot.ly for radius . reversescale Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.densitymapbox.Stream instance or dict with compatible properties subplot Sets a reference between this trace's data coordinates and a mapbox subplot. If "mapbox" (the default value), the data refer to `layout.mapbox`. If "mapbox2", the data refer to `layout.mapbox2`, and so on. text Sets text elements associated with each (lon,lat) pair If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (lon,lat) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). z Sets the points' weight. For example, a value of 10 would be equivalent to having 10 points of weight 1 in the same spot zauto Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. zmax Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. zmid Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. zmin Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. zsrc Sets the source reference on plot.ly for z . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- Figure """ new_trace = Densitymapbox( autocolorscale=autocolorscale, below=below, coloraxis=coloraxis, colorbar=colorbar, colorscale=colorscale, customdata=customdata, customdatasrc=customdatasrc, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, lat=lat, latsrc=latsrc, lon=lon, lonsrc=lonsrc, meta=meta, metasrc=metasrc, name=name, opacity=opacity, radius=radius, radiussrc=radiussrc, reversescale=reversescale, showscale=showscale, stream=stream, subplot=subplot, text=text, textsrc=textsrc, uid=uid, uirevision=uirevision, visible=visible, z=z, zauto=zauto, zmax=zmax, zmid=zmid, zmin=zmin, zsrc=zsrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_funnel( self, alignmentgroup=None, cliponaxis=None, connector=None, constraintext=None, customdata=None, customdatasrc=None, dx=None, dy=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, insidetextanchor=None, insidetextfont=None, legendgroup=None, marker=None, meta=None, metasrc=None, name=None, offset=None, offsetgroup=None, opacity=None, orientation=None, outsidetextfont=None, selectedpoints=None, showlegend=None, stream=None, text=None, textangle=None, textfont=None, textinfo=None, textposition=None, textpositionsrc=None, textsrc=None, texttemplate=None, texttemplatesrc=None, uid=None, uirevision=None, visible=None, width=None, x=None, x0=None, xaxis=None, xsrc=None, y=None, y0=None, yaxis=None, ysrc=None, row=None, col=None, secondary_y=None, **kwargs ): """ Add a new Funnel trace Visualize stages in a process using length-encoded bars. This trace can be used to show data in either a part-to-whole representation wherein each item appears in a single stage, or in a "drop-off" representation wherein each item appears in each stage it traversed. See also the "funnelarea" trace type for a different approach to visualizing funnel data. Parameters ---------- alignmentgroup Set several traces linked to the same position axis or matching axes to the same alignmentgroup. This controls whether bars compute their positional range dependently or independently. cliponaxis Determines whether the text nodes are clipped about the subplot axes. To show the text nodes above axis lines and tick labels, make sure to set `xaxis.layer` and `yaxis.layer` to *below traces*. connector plotly.graph_objects.funnel.Connector instance or dict with compatible properties constraintext Constrain the size of text inside or outside a bar to be no larger than the bar itself. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dx Sets the x coordinate step. See `x0` for more info. dy Sets the y coordinate step. See `y0` for more info. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.funnel.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `percentInitial`, `percentPrevious` and `percentTotal`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . insidetextanchor Determines if texts are kept at center or start/end points in `textposition` "inside" mode. insidetextfont Sets the font used for `text` lying inside the bar. legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. marker plotly.graph_objects.funnel.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. offset Shifts the position where the bar is drawn (in position axis units). In "group" barmode, traces that set "offset" will be excluded and drawn in "overlay" mode instead. offsetgroup Set several traces linked to the same position axis or matching axes to the same offsetgroup where bars of the same position coordinate will line up. opacity Sets the opacity of the trace. orientation Sets the orientation of the funnels. With "v" ("h"), the value of the each bar spans along the vertical (horizontal). By default funnels are tend to be oriented horizontally; unless only "y" array is presented or orientation is set to "v". Also regarding graphs including only 'horizontal' funnels, "autorange" on the "y-axis" are set to "reversed". outsidetextfont Sets the font used for `text` lying outside the bar. selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.funnel.Stream instance or dict with compatible properties text Sets text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textangle Sets the angle of the tick labels with respect to the bar. For example, a `tickangle` of -90 draws the tick labels vertically. With "auto" the texts may automatically be rotated to fit with the maximum size in bars. textfont Sets the font used for `text`. textinfo Determines which trace information appear on the graph. In the case of having multiple funnels, percentages & totals are computed separately (per trace). textposition Specifies the location of the `text`. "inside" positions `text` inside, next to the bar end (rotated and scaled if needed). "outside" positions `text` outside, next to the bar end (scaled if needed), unless there is another bar stacked on this one, then the text gets pushed inside. "auto" tries to position `text` inside the bar, but if the bar is too small and no bar is stacked on this one the text is moved outside. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `percentInitial`, `percentPrevious`, `percentTotal`, `label` and `value`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). width Sets the bar width (in position axis units). x Sets the x coordinates. x0 Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xsrc Sets the source reference on plot.ly for x . y Sets the y coordinates. y0 Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ysrc Sets the source reference on plot.ly for y . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` secondary_y: boolean or None (default None) If True, associate this trace with the secondary y-axis of the subplot at the specified row and col. Only valid if all of the following conditions are satisfied: * The figure was created using `plotly.subplots.make_subplots`. * The row and col arguments are not None * The subplot at the specified row and col has type xy (which is the default) and secondary_y True. These properties are specified in the specs argument to make_subplots. See the make_subplots docstring for more info. Returns ------- Figure """ new_trace = Funnel( alignmentgroup=alignmentgroup, cliponaxis=cliponaxis, connector=connector, constraintext=constraintext, customdata=customdata, customdatasrc=customdatasrc, dx=dx, dy=dy, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, insidetextanchor=insidetextanchor, insidetextfont=insidetextfont, legendgroup=legendgroup, marker=marker, meta=meta, metasrc=metasrc, name=name, offset=offset, offsetgroup=offsetgroup, opacity=opacity, orientation=orientation, outsidetextfont=outsidetextfont, selectedpoints=selectedpoints, showlegend=showlegend, stream=stream, text=text, textangle=textangle, textfont=textfont, textinfo=textinfo, textposition=textposition, textpositionsrc=textpositionsrc, textsrc=textsrc, texttemplate=texttemplate, texttemplatesrc=texttemplatesrc, uid=uid, uirevision=uirevision, visible=visible, width=width, x=x, x0=x0, xaxis=xaxis, xsrc=xsrc, y=y, y0=y0, yaxis=yaxis, ysrc=ysrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) def add_funnelarea( self, aspectratio=None, baseratio=None, customdata=None, customdatasrc=None, dlabel=None, domain=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, insidetextfont=None, label0=None, labels=None, labelssrc=None, legendgroup=None, marker=None, meta=None, metasrc=None, name=None, opacity=None, scalegroup=None, showlegend=None, stream=None, text=None, textfont=None, textinfo=None, textposition=None, textpositionsrc=None, textsrc=None, texttemplate=None, texttemplatesrc=None, title=None, uid=None, uirevision=None, values=None, valuessrc=None, visible=None, row=None, col=None, **kwargs ): """ Add a new Funnelarea trace Visualize stages in a process using area-encoded trapezoids. This trace can be used to show data in a part-to-whole representation similar to a "pie" trace, wherein each item appears in a single stage. See also the "funnel" trace type for a different approach to visualizing funnel data. Parameters ---------- aspectratio Sets the ratio between height and width baseratio Sets the ratio between bottom length and maximum top length. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dlabel Sets the label step. See `label0` for more info. domain plotly.graph_objects.funnelarea.Domain instance or dict with compatible properties hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.funnelarea.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `label`, `color`, `value`, `text` and `percent`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each sector. If a single string, the same string appears for all data points. If an array of string, the items are mapped in order of this trace's sectors. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . insidetextfont Sets the font used for `textinfo` lying inside the sector. label0 Alternate to `labels`. Builds a numeric set of labels. Use with `dlabel` where `label0` is the starting label and `dlabel` the step. labels Sets the sector labels. If `labels` entries are duplicated, we sum associated `values` or simply count occurrences if `values` is not provided. For other array attributes (including color) we use the first non-empty entry among all occurrences of the label. labelssrc Sets the source reference on plot.ly for labels . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. marker plotly.graph_objects.funnelarea.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. scalegroup If there are multiple funnelareas that should be sized according to their totals, link them by providing a non-empty group id here shared by every trace in the same group. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.funnelarea.Stream instance or dict with compatible properties text Sets text elements associated with each sector. If trace `textinfo` contains a "text" flag, these elements will be seen on the chart. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the font used for `textinfo`. textinfo Determines which trace information appear on the graph. textposition Specifies the location of the `textinfo`. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `label`, `color`, `value`, `text` and `percent`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . title plotly.graph_objects.funnelarea.Title instance or dict with compatible properties uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. values Sets the values of the sectors. If omitted, we count occurrences of each label. valuessrc Sets the source reference on plot.ly for values . visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- Figure """ new_trace = Funnelarea( aspectratio=aspectratio, baseratio=baseratio, customdata=customdata, customdatasrc=customdatasrc, dlabel=dlabel, domain=domain, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, insidetextfont=insidetextfont, label0=label0, labels=labels, labelssrc=labelssrc, legendgroup=legendgroup, marker=marker, meta=meta, metasrc=metasrc, name=name, opacity=opacity, scalegroup=scalegroup, showlegend=showlegend, stream=stream, text=text, textfont=textfont, textinfo=textinfo, textposition=textposition, textpositionsrc=textpositionsrc, textsrc=textsrc, texttemplate=texttemplate, texttemplatesrc=texttemplatesrc, title=title, uid=uid, uirevision=uirevision, values=values, valuessrc=valuessrc, visible=visible, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_heatmap( self, autocolorscale=None, coloraxis=None, colorbar=None, colorscale=None, connectgaps=None, customdata=None, customdatasrc=None, dx=None, dy=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hoverongaps=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, meta=None, metasrc=None, name=None, opacity=None, reversescale=None, showscale=None, stream=None, text=None, textsrc=None, transpose=None, uid=None, uirevision=None, visible=None, x=None, x0=None, xaxis=None, xcalendar=None, xgap=None, xsrc=None, xtype=None, y=None, y0=None, yaxis=None, ycalendar=None, ygap=None, ysrc=None, ytype=None, z=None, zauto=None, zhoverformat=None, zmax=None, zmid=None, zmin=None, zsmooth=None, zsrc=None, row=None, col=None, secondary_y=None, **kwargs ): """ Add a new Heatmap trace The data that describes the heatmap value-to-color mapping is set in `z`. Data in `z` can either be a 2D list of values (ragged or not) or a 1D array of values. In the case where `z` is a 2D list, say that `z` has N rows and M columns. Then, by default, the resulting heatmap will have N partitions along the y axis and M partitions along the x axis. In other words, the i-th row/ j-th column cell in `z` is mapped to the i-th partition of the y axis (starting from the bottom of the plot) and the j-th partition of the x-axis (starting from the left of the plot). This behavior can be flipped by using `transpose`. Moreover, `x` (`y`) can be provided with M or M+1 (N or N+1) elements. If M (N), then the coordinates correspond to the center of the heatmap cells and the cells have equal width. If M+1 (N+1), then the coordinates correspond to the edges of the heatmap cells. In the case where `z` is a 1D list, the x and y coordinates must be provided in `x` and `y` respectively to form data triplets. Parameters ---------- autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.heatmap.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the `z` data are filled in. It is defaulted to true if `z` is a one dimensional array and `zsmooth` is not false; otherwise it is defaulted to false. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dx Sets the x coordinate step. See `x0` for more info. dy Sets the y coordinate step. See `y0` for more info. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.heatmap.Hoverlabel instance or dict with compatible properties hoverongaps Determines whether or not gaps (i.e. {nan} or missing values) in the `z` data have hover labels associated with them. hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. reversescale Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.heatmap.Stream instance or dict with compatible properties text Sets the text elements associated with each z value. textsrc Sets the source reference on plot.ly for text . transpose Transposes the z data. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the x coordinates. x0 Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xcalendar Sets the calendar system to use with `x` date data. xgap Sets the horizontal gap (in pixels) between bricks. xsrc Sets the source reference on plot.ly for x . xtype If "array", the heatmap's x coordinates are given by "x" (the default behavior when `x` is provided). If "scaled", the heatmap's x coordinates are given by "x0" and "dx" (the default behavior when `x` is not provided). y Sets the y coordinates. y0 Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ycalendar Sets the calendar system to use with `y` date data. ygap Sets the vertical gap (in pixels) between bricks. ysrc Sets the source reference on plot.ly for y . ytype If "array", the heatmap's y coordinates are given by "y" (the default behavior when `y` is provided) If "scaled", the heatmap's y coordinates are given by "y0" and "dy" (the default behavior when `y` is not provided) z Sets the z data. zauto Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. zhoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. See: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format zmax Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. zmid Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. zmin Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. zsmooth Picks a smoothing algorithm use to smooth `z` data. zsrc Sets the source reference on plot.ly for z . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` secondary_y: boolean or None (default None) If True, associate this trace with the secondary y-axis of the subplot at the specified row and col. Only valid if all of the following conditions are satisfied: * The figure was created using `plotly.subplots.make_subplots`. * The row and col arguments are not None * The subplot at the specified row and col has type xy (which is the default) and secondary_y True. These properties are specified in the specs argument to make_subplots. See the make_subplots docstring for more info. Returns ------- Figure """ new_trace = Heatmap( autocolorscale=autocolorscale, coloraxis=coloraxis, colorbar=colorbar, colorscale=colorscale, connectgaps=connectgaps, customdata=customdata, customdatasrc=customdatasrc, dx=dx, dy=dy, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hoverongaps=hoverongaps, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, meta=meta, metasrc=metasrc, name=name, opacity=opacity, reversescale=reversescale, showscale=showscale, stream=stream, text=text, textsrc=textsrc, transpose=transpose, uid=uid, uirevision=uirevision, visible=visible, x=x, x0=x0, xaxis=xaxis, xcalendar=xcalendar, xgap=xgap, xsrc=xsrc, xtype=xtype, y=y, y0=y0, yaxis=yaxis, ycalendar=ycalendar, ygap=ygap, ysrc=ysrc, ytype=ytype, z=z, zauto=zauto, zhoverformat=zhoverformat, zmax=zmax, zmid=zmid, zmin=zmin, zsmooth=zsmooth, zsrc=zsrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) def add_heatmapgl( self, autocolorscale=None, coloraxis=None, colorbar=None, colorscale=None, customdata=None, customdatasrc=None, dx=None, dy=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, ids=None, idssrc=None, meta=None, metasrc=None, name=None, opacity=None, reversescale=None, showscale=None, stream=None, text=None, textsrc=None, transpose=None, uid=None, uirevision=None, visible=None, x=None, x0=None, xaxis=None, xsrc=None, xtype=None, y=None, y0=None, yaxis=None, ysrc=None, ytype=None, z=None, zauto=None, zmax=None, zmid=None, zmin=None, zsrc=None, row=None, col=None, secondary_y=None, **kwargs ): """ Add a new Heatmapgl trace WebGL version of the heatmap trace type. Parameters ---------- autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.heatmapgl.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dx Sets the x coordinate step. See `x0` for more info. dy Sets the y coordinate step. See `y0` for more info. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.heatmapgl.Hoverlabel instance or dict with compatible properties ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. reversescale Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.heatmapgl.Stream instance or dict with compatible properties text Sets the text elements associated with each z value. textsrc Sets the source reference on plot.ly for text . transpose Transposes the z data. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the x coordinates. x0 Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xsrc Sets the source reference on plot.ly for x . xtype If "array", the heatmap's x coordinates are given by "x" (the default behavior when `x` is provided). If "scaled", the heatmap's x coordinates are given by "x0" and "dx" (the default behavior when `x` is not provided). y Sets the y coordinates. y0 Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ysrc Sets the source reference on plot.ly for y . ytype If "array", the heatmap's y coordinates are given by "y" (the default behavior when `y` is provided) If "scaled", the heatmap's y coordinates are given by "y0" and "dy" (the default behavior when `y` is not provided) z Sets the z data. zauto Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. zmax Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. zmid Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. zmin Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. zsrc Sets the source reference on plot.ly for z . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` secondary_y: boolean or None (default None) If True, associate this trace with the secondary y-axis of the subplot at the specified row and col. Only valid if all of the following conditions are satisfied: * The figure was created using `plotly.subplots.make_subplots`. * The row and col arguments are not None * The subplot at the specified row and col has type xy (which is the default) and secondary_y True. These properties are specified in the specs argument to make_subplots. See the make_subplots docstring for more info. Returns ------- Figure """ new_trace = Heatmapgl( autocolorscale=autocolorscale, coloraxis=coloraxis, colorbar=colorbar, colorscale=colorscale, customdata=customdata, customdatasrc=customdatasrc, dx=dx, dy=dy, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, ids=ids, idssrc=idssrc, meta=meta, metasrc=metasrc, name=name, opacity=opacity, reversescale=reversescale, showscale=showscale, stream=stream, text=text, textsrc=textsrc, transpose=transpose, uid=uid, uirevision=uirevision, visible=visible, x=x, x0=x0, xaxis=xaxis, xsrc=xsrc, xtype=xtype, y=y, y0=y0, yaxis=yaxis, ysrc=ysrc, ytype=ytype, z=z, zauto=zauto, zmax=zmax, zmid=zmid, zmin=zmin, zsrc=zsrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) def add_histogram( self, alignmentgroup=None, autobinx=None, autobiny=None, bingroup=None, cumulative=None, customdata=None, customdatasrc=None, error_x=None, error_y=None, histfunc=None, histnorm=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, legendgroup=None, marker=None, meta=None, metasrc=None, name=None, nbinsx=None, nbinsy=None, offsetgroup=None, opacity=None, orientation=None, selected=None, selectedpoints=None, showlegend=None, stream=None, text=None, textsrc=None, uid=None, uirevision=None, unselected=None, visible=None, x=None, xaxis=None, xbins=None, xcalendar=None, xsrc=None, y=None, yaxis=None, ybins=None, ycalendar=None, ysrc=None, row=None, col=None, secondary_y=None, **kwargs ): """ Add a new Histogram trace The sample data from which statistics are computed is set in `x` for vertically spanning histograms and in `y` for horizontally spanning histograms. Binning options are set `xbins` and `ybins` respectively if no aggregation data is provided. Parameters ---------- alignmentgroup Set several traces linked to the same position axis or matching axes to the same alignmentgroup. This controls whether bars compute their positional range dependently or independently. autobinx Obsolete: since v1.42 each bin attribute is auto- determined separately and `autobinx` is not needed. However, we accept `autobinx: true` or `false` and will update `xbins` accordingly before deleting `autobinx` from the trace. autobiny Obsolete: since v1.42 each bin attribute is auto- determined separately and `autobiny` is not needed. However, we accept `autobiny: true` or `false` and will update `ybins` accordingly before deleting `autobiny` from the trace. bingroup Set a group of histogram traces which will have compatible bin settings. Note that traces on the same subplot and with the same "orientation" under `barmode` "stack", "relative" and "group" are forced into the same bingroup, Using `bingroup`, traces under `barmode` "overlay" and on different axes (of the same axis type) can have compatible bin settings. Note that histogram and histogram2d* trace can share the same `bingroup` cumulative plotly.graph_objects.histogram.Cumulative instance or dict with compatible properties customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . error_x plotly.graph_objects.histogram.ErrorX instance or dict with compatible properties error_y plotly.graph_objects.histogram.ErrorY instance or dict with compatible properties histfunc Specifies the binning function used for this histogram trace. If "count", the histogram values are computed by counting the number of values lying inside each bin. If "sum", "avg", "min", "max", the histogram values are computed using the sum, the average, the minimum or the maximum of the values lying inside each bin respectively. histnorm Specifies the type of normalization used for this histogram trace. If "", the span of each bar corresponds to the number of occurrences (i.e. the number of data points lying inside the bins). If "percent" / "probability", the span of each bar corresponds to the percentage / fraction of occurrences with respect to the total number of sample points (here, the sum of all bin HEIGHTS equals 100% / 1). If "density", the span of each bar corresponds to the number of occurrences in a bin divided by the size of the bin interval (here, the sum of all bin AREAS equals the total number of sample points). If *probability density*, the area of each bar corresponds to the probability that an event will fall into the corresponding bin (here, the sum of all bin AREAS equals 1). hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.histogram.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variable `binNumber` Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. marker plotly.graph_objects.histogram.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. nbinsx Specifies the maximum number of desired bins. This value will be used in an algorithm that will decide the optimal bin size such that the histogram best visualizes the distribution of the data. Ignored if `xbins.size` is provided. nbinsy Specifies the maximum number of desired bins. This value will be used in an algorithm that will decide the optimal bin size such that the histogram best visualizes the distribution of the data. Ignored if `ybins.size` is provided. offsetgroup Set several traces linked to the same position axis or matching axes to the same offsetgroup where bars of the same position coordinate will line up. opacity Sets the opacity of the trace. orientation Sets the orientation of the bars. With "v" ("h"), the value of the each bar spans along the vertical (horizontal). selected plotly.graph_objects.histogram.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.histogram.Stream instance or dict with compatible properties text Sets hover text elements associated with each bar. If a single string, the same string appears over all bars. If an array of string, the items are mapped in order to the this trace's coordinates. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.histogram.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the sample data to be binned on the x axis. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xbins plotly.graph_objects.histogram.XBins instance or dict with compatible properties xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . y Sets the sample data to be binned on the y axis. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ybins plotly.graph_objects.histogram.YBins instance or dict with compatible properties ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` secondary_y: boolean or None (default None) If True, associate this trace with the secondary y-axis of the subplot at the specified row and col. Only valid if all of the following conditions are satisfied: * The figure was created using `plotly.subplots.make_subplots`. * The row and col arguments are not None * The subplot at the specified row and col has type xy (which is the default) and secondary_y True. These properties are specified in the specs argument to make_subplots. See the make_subplots docstring for more info. Returns ------- Figure """ new_trace = Histogram( alignmentgroup=alignmentgroup, autobinx=autobinx, autobiny=autobiny, bingroup=bingroup, cumulative=cumulative, customdata=customdata, customdatasrc=customdatasrc, error_x=error_x, error_y=error_y, histfunc=histfunc, histnorm=histnorm, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, legendgroup=legendgroup, marker=marker, meta=meta, metasrc=metasrc, name=name, nbinsx=nbinsx, nbinsy=nbinsy, offsetgroup=offsetgroup, opacity=opacity, orientation=orientation, selected=selected, selectedpoints=selectedpoints, showlegend=showlegend, stream=stream, text=text, textsrc=textsrc, uid=uid, uirevision=uirevision, unselected=unselected, visible=visible, x=x, xaxis=xaxis, xbins=xbins, xcalendar=xcalendar, xsrc=xsrc, y=y, yaxis=yaxis, ybins=ybins, ycalendar=ycalendar, ysrc=ysrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) def add_histogram2d( self, autobinx=None, autobiny=None, autocolorscale=None, bingroup=None, coloraxis=None, colorbar=None, colorscale=None, customdata=None, customdatasrc=None, histfunc=None, histnorm=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, ids=None, idssrc=None, marker=None, meta=None, metasrc=None, name=None, nbinsx=None, nbinsy=None, opacity=None, reversescale=None, showscale=None, stream=None, uid=None, uirevision=None, visible=None, x=None, xaxis=None, xbingroup=None, xbins=None, xcalendar=None, xgap=None, xsrc=None, y=None, yaxis=None, ybingroup=None, ybins=None, ycalendar=None, ygap=None, ysrc=None, z=None, zauto=None, zhoverformat=None, zmax=None, zmid=None, zmin=None, zsmooth=None, zsrc=None, row=None, col=None, secondary_y=None, **kwargs ): """ Add a new Histogram2d trace The sample data from which statistics are computed is set in `x` and `y` (where `x` and `y` represent marginal distributions, binning is set in `xbins` and `ybins` in this case) or `z` (where `z` represent the 2D distribution and binning set, binning is set by `x` and `y` in this case). The resulting distribution is visualized as a heatmap. Parameters ---------- autobinx Obsolete: since v1.42 each bin attribute is auto- determined separately and `autobinx` is not needed. However, we accept `autobinx: true` or `false` and will update `xbins` accordingly before deleting `autobinx` from the trace. autobiny Obsolete: since v1.42 each bin attribute is auto- determined separately and `autobiny` is not needed. However, we accept `autobiny: true` or `false` and will update `ybins` accordingly before deleting `autobiny` from the trace. autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. bingroup Set the `xbingroup` and `ybingroup` default prefix For example, setting a `bingroup` of 1 on two histogram2d traces will make them their x-bins and y-bins match separately. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.histogram2d.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . histfunc Specifies the binning function used for this histogram trace. If "count", the histogram values are computed by counting the number of values lying inside each bin. If "sum", "avg", "min", "max", the histogram values are computed using the sum, the average, the minimum or the maximum of the values lying inside each bin respectively. histnorm Specifies the type of normalization used for this histogram trace. If "", the span of each bar corresponds to the number of occurrences (i.e. the number of data points lying inside the bins). If "percent" / "probability", the span of each bar corresponds to the percentage / fraction of occurrences with respect to the total number of sample points (here, the sum of all bin HEIGHTS equals 100% / 1). If "density", the span of each bar corresponds to the number of occurrences in a bin divided by the size of the bin interval (here, the sum of all bin AREAS equals the total number of sample points). If *probability density*, the area of each bar corresponds to the probability that an event will fall into the corresponding bin (here, the sum of all bin AREAS equals 1). hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.histogram2d.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variable `z` Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . marker plotly.graph_objects.histogram2d.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. nbinsx Specifies the maximum number of desired bins. This value will be used in an algorithm that will decide the optimal bin size such that the histogram best visualizes the distribution of the data. Ignored if `xbins.size` is provided. nbinsy Specifies the maximum number of desired bins. This value will be used in an algorithm that will decide the optimal bin size such that the histogram best visualizes the distribution of the data. Ignored if `ybins.size` is provided. opacity Sets the opacity of the trace. reversescale Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.histogram2d.Stream instance or dict with compatible properties uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the sample data to be binned on the x axis. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xbingroup Set a group of histogram traces which will have compatible x-bin settings. Using `xbingroup`, histogram2d and histogram2dcontour traces (on axes of the same axis type) can have compatible x-bin settings. Note that the same `xbingroup` value can be used to set (1D) histogram `bingroup` xbins plotly.graph_objects.histogram2d.XBins instance or dict with compatible properties xcalendar Sets the calendar system to use with `x` date data. xgap Sets the horizontal gap (in pixels) between bricks. xsrc Sets the source reference on plot.ly for x . y Sets the sample data to be binned on the y axis. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ybingroup Set a group of histogram traces which will have compatible y-bin settings. Using `ybingroup`, histogram2d and histogram2dcontour traces (on axes of the same axis type) can have compatible y-bin settings. Note that the same `ybingroup` value can be used to set (1D) histogram `bingroup` ybins plotly.graph_objects.histogram2d.YBins instance or dict with compatible properties ycalendar Sets the calendar system to use with `y` date data. ygap Sets the vertical gap (in pixels) between bricks. ysrc Sets the source reference on plot.ly for y . z Sets the aggregation data. zauto Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. zhoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. See: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format zmax Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. zmid Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. zmin Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. zsmooth Picks a smoothing algorithm use to smooth `z` data. zsrc Sets the source reference on plot.ly for z . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` secondary_y: boolean or None (default None) If True, associate this trace with the secondary y-axis of the subplot at the specified row and col. Only valid if all of the following conditions are satisfied: * The figure was created using `plotly.subplots.make_subplots`. * The row and col arguments are not None * The subplot at the specified row and col has type xy (which is the default) and secondary_y True. These properties are specified in the specs argument to make_subplots. See the make_subplots docstring for more info. Returns ------- Figure """ new_trace = Histogram2d( autobinx=autobinx, autobiny=autobiny, autocolorscale=autocolorscale, bingroup=bingroup, coloraxis=coloraxis, colorbar=colorbar, colorscale=colorscale, customdata=customdata, customdatasrc=customdatasrc, histfunc=histfunc, histnorm=histnorm, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, ids=ids, idssrc=idssrc, marker=marker, meta=meta, metasrc=metasrc, name=name, nbinsx=nbinsx, nbinsy=nbinsy, opacity=opacity, reversescale=reversescale, showscale=showscale, stream=stream, uid=uid, uirevision=uirevision, visible=visible, x=x, xaxis=xaxis, xbingroup=xbingroup, xbins=xbins, xcalendar=xcalendar, xgap=xgap, xsrc=xsrc, y=y, yaxis=yaxis, ybingroup=ybingroup, ybins=ybins, ycalendar=ycalendar, ygap=ygap, ysrc=ysrc, z=z, zauto=zauto, zhoverformat=zhoverformat, zmax=zmax, zmid=zmid, zmin=zmin, zsmooth=zsmooth, zsrc=zsrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) def add_histogram2dcontour( self, autobinx=None, autobiny=None, autocolorscale=None, autocontour=None, bingroup=None, coloraxis=None, colorbar=None, colorscale=None, contours=None, customdata=None, customdatasrc=None, histfunc=None, histnorm=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, ids=None, idssrc=None, legendgroup=None, line=None, marker=None, meta=None, metasrc=None, name=None, nbinsx=None, nbinsy=None, ncontours=None, opacity=None, reversescale=None, showlegend=None, showscale=None, stream=None, uid=None, uirevision=None, visible=None, x=None, xaxis=None, xbingroup=None, xbins=None, xcalendar=None, xsrc=None, y=None, yaxis=None, ybingroup=None, ybins=None, ycalendar=None, ysrc=None, z=None, zauto=None, zhoverformat=None, zmax=None, zmid=None, zmin=None, zsrc=None, row=None, col=None, secondary_y=None, **kwargs ): """ Add a new Histogram2dContour trace The sample data from which statistics are computed is set in `x` and `y` (where `x` and `y` represent marginal distributions, binning is set in `xbins` and `ybins` in this case) or `z` (where `z` represent the 2D distribution and binning set, binning is set by `x` and `y` in this case). The resulting distribution is visualized as a contour plot. Parameters ---------- autobinx Obsolete: since v1.42 each bin attribute is auto- determined separately and `autobinx` is not needed. However, we accept `autobinx: true` or `false` and will update `xbins` accordingly before deleting `autobinx` from the trace. autobiny Obsolete: since v1.42 each bin attribute is auto- determined separately and `autobiny` is not needed. However, we accept `autobiny: true` or `false` and will update `ybins` accordingly before deleting `autobiny` from the trace. autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. autocontour Determines whether or not the contour level attributes are picked by an algorithm. If True, the number of contour levels can be set in `ncontours`. If False, set the contour level attributes in `contours`. bingroup Set the `xbingroup` and `ybingroup` default prefix For example, setting a `bingroup` of 1 on two histogram2d traces will make them their x-bins and y-bins match separately. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.histogram2dcontour.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. contours plotly.graph_objects.histogram2dcontour.Contours instance or dict with compatible properties customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . histfunc Specifies the binning function used for this histogram trace. If "count", the histogram values are computed by counting the number of values lying inside each bin. If "sum", "avg", "min", "max", the histogram values are computed using the sum, the average, the minimum or the maximum of the values lying inside each bin respectively. histnorm Specifies the type of normalization used for this histogram trace. If "", the span of each bar corresponds to the number of occurrences (i.e. the number of data points lying inside the bins). If "percent" / "probability", the span of each bar corresponds to the percentage / fraction of occurrences with respect to the total number of sample points (here, the sum of all bin HEIGHTS equals 100% / 1). If "density", the span of each bar corresponds to the number of occurrences in a bin divided by the size of the bin interval (here, the sum of all bin AREAS equals the total number of sample points). If *probability density*, the area of each bar corresponds to the probability that an event will fall into the corresponding bin (here, the sum of all bin AREAS equals 1). hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.histogram2dcontour.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variable `z` Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.histogram2dcontour.Line instance or dict with compatible properties marker plotly.graph_objects.histogram2dcontour.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. nbinsx Specifies the maximum number of desired bins. This value will be used in an algorithm that will decide the optimal bin size such that the histogram best visualizes the distribution of the data. Ignored if `xbins.size` is provided. nbinsy Specifies the maximum number of desired bins. This value will be used in an algorithm that will decide the optimal bin size such that the histogram best visualizes the distribution of the data. Ignored if `ybins.size` is provided. ncontours Sets the maximum number of contour levels. The actual number of contours will be chosen automatically to be less than or equal to the value of `ncontours`. Has an effect only if `autocontour` is True or if `contours.size` is missing. opacity Sets the opacity of the trace. reversescale Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.histogram2dcontour.Stream instance or dict with compatible properties uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the sample data to be binned on the x axis. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xbingroup Set a group of histogram traces which will have compatible x-bin settings. Using `xbingroup`, histogram2d and histogram2dcontour traces (on axes of the same axis type) can have compatible x-bin settings. Note that the same `xbingroup` value can be used to set (1D) histogram `bingroup` xbins plotly.graph_objects.histogram2dcontour.XBins instance or dict with compatible properties xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . y Sets the sample data to be binned on the y axis. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ybingroup Set a group of histogram traces which will have compatible y-bin settings. Using `ybingroup`, histogram2d and histogram2dcontour traces (on axes of the same axis type) can have compatible y-bin settings. Note that the same `ybingroup` value can be used to set (1D) histogram `bingroup` ybins plotly.graph_objects.histogram2dcontour.YBins instance or dict with compatible properties ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . z Sets the aggregation data. zauto Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. zhoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. See: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format zmax Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. zmid Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. zmin Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. zsrc Sets the source reference on plot.ly for z . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` secondary_y: boolean or None (default None) If True, associate this trace with the secondary y-axis of the subplot at the specified row and col. Only valid if all of the following conditions are satisfied: * The figure was created using `plotly.subplots.make_subplots`. * The row and col arguments are not None * The subplot at the specified row and col has type xy (which is the default) and secondary_y True. These properties are specified in the specs argument to make_subplots. See the make_subplots docstring for more info. Returns ------- Figure """ new_trace = Histogram2dContour( autobinx=autobinx, autobiny=autobiny, autocolorscale=autocolorscale, autocontour=autocontour, bingroup=bingroup, coloraxis=coloraxis, colorbar=colorbar, colorscale=colorscale, contours=contours, customdata=customdata, customdatasrc=customdatasrc, histfunc=histfunc, histnorm=histnorm, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, ids=ids, idssrc=idssrc, legendgroup=legendgroup, line=line, marker=marker, meta=meta, metasrc=metasrc, name=name, nbinsx=nbinsx, nbinsy=nbinsy, ncontours=ncontours, opacity=opacity, reversescale=reversescale, showlegend=showlegend, showscale=showscale, stream=stream, uid=uid, uirevision=uirevision, visible=visible, x=x, xaxis=xaxis, xbingroup=xbingroup, xbins=xbins, xcalendar=xcalendar, xsrc=xsrc, y=y, yaxis=yaxis, ybingroup=ybingroup, ybins=ybins, ycalendar=ycalendar, ysrc=ysrc, z=z, zauto=zauto, zhoverformat=zhoverformat, zmax=zmax, zmid=zmid, zmin=zmin, zsrc=zsrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) def add_image( self, colormodel=None, customdata=None, customdatasrc=None, dx=None, dy=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, meta=None, metasrc=None, name=None, opacity=None, stream=None, text=None, textsrc=None, uid=None, uirevision=None, visible=None, x0=None, xaxis=None, y0=None, yaxis=None, z=None, zmax=None, zmin=None, zsrc=None, row=None, col=None, secondary_y=None, **kwargs ): """ Add a new Image trace Display an image, i.e. data on a 2D regular raster. By default, when an image is displayed in a subplot, its y axis will be reversed (ie. `autorange: 'reversed'`), constrained to the domain (ie. `constrain: 'domain'`) and it will have the same scale as its x axis (ie. `scaleanchor: 'x,`) in order for pixels to be rendered as squares. Parameters ---------- colormodel Color model used to map the numerical color components described in `z` into colors. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dx Set the pixel's horizontal size. dy Set the pixel's vertical size hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.image.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `z`, `color` and `colormodel`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. stream plotly.graph_objects.image.Stream instance or dict with compatible properties text Sets the text elements associated with each z value. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x0 Set the image's x position. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. y0 Set the image's y position. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. z A 2-dimensional array in which each element is an array of 3 or 4 numbers representing a color. zmax Array defining the higher bound for each color component. Note that the default value will depend on the colormodel. For the `rgb` colormodel, it is [255, 255, 255]. For the `rgba` colormodel, it is [255, 255, 255, 1]. For the `hsl` colormodel, it is [360, 100, 100]. For the `hsla` colormodel, it is [360, 100, 100, 1]. zmin Array defining the lower bound for each color component. Note that the default value will depend on the colormodel. For the `rgb` colormodel, it is [0, 0, 0]. For the `rgba` colormodel, it is [0, 0, 0, 0]. For the `hsl` colormodel, it is [0, 0, 0]. For the `hsla` colormodel, it is [0, 0, 0, 0]. zsrc Sets the source reference on plot.ly for z . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` secondary_y: boolean or None (default None) If True, associate this trace with the secondary y-axis of the subplot at the specified row and col. Only valid if all of the following conditions are satisfied: * The figure was created using `plotly.subplots.make_subplots`. * The row and col arguments are not None * The subplot at the specified row and col has type xy (which is the default) and secondary_y True. These properties are specified in the specs argument to make_subplots. See the make_subplots docstring for more info. Returns ------- Figure """ new_trace = Image( colormodel=colormodel, customdata=customdata, customdatasrc=customdatasrc, dx=dx, dy=dy, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, meta=meta, metasrc=metasrc, name=name, opacity=opacity, stream=stream, text=text, textsrc=textsrc, uid=uid, uirevision=uirevision, visible=visible, x0=x0, xaxis=xaxis, y0=y0, yaxis=yaxis, z=z, zmax=zmax, zmin=zmin, zsrc=zsrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) def add_indicator( self, align=None, customdata=None, customdatasrc=None, delta=None, domain=None, gauge=None, ids=None, idssrc=None, meta=None, metasrc=None, mode=None, name=None, number=None, stream=None, title=None, uid=None, uirevision=None, value=None, visible=None, row=None, col=None, **kwargs ): """ Add a new Indicator trace An indicator is used to visualize a single `value` along with some contextual information such as `steps` or a `threshold`, using a combination of three visual elements: a number, a delta, and/or a gauge. Deltas are taken with respect to a `reference`. Gauges can be either angular or bullet (aka linear) gauges. Parameters ---------- align Sets the horizontal alignment of the `text` within the box. Note that this attribute has no effect if an angular gauge is displayed: in this case, it is always centered customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . delta plotly.graph_objects.indicator.Delta instance or dict with compatible properties domain plotly.graph_objects.indicator.Domain instance or dict with compatible properties gauge The gauge of the Indicator plot. ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . mode Determines how the value is displayed on the graph. `number` displays the value numerically in text. `delta` displays the difference to a reference value in text. Finally, `gauge` displays the value graphically on an axis. name Sets the trace name. The trace name appear as the legend item and on hover. number plotly.graph_objects.indicator.Number instance or dict with compatible properties stream plotly.graph_objects.indicator.Stream instance or dict with compatible properties title plotly.graph_objects.indicator.Title instance or dict with compatible properties uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. value Sets the number to be displayed. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- Figure """ new_trace = Indicator( align=align, customdata=customdata, customdatasrc=customdatasrc, delta=delta, domain=domain, gauge=gauge, ids=ids, idssrc=idssrc, meta=meta, metasrc=metasrc, mode=mode, name=name, number=number, stream=stream, title=title, uid=uid, uirevision=uirevision, value=value, visible=visible, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_isosurface( self, autocolorscale=None, caps=None, cauto=None, cmax=None, cmid=None, cmin=None, coloraxis=None, colorbar=None, colorscale=None, contour=None, customdata=None, customdatasrc=None, flatshading=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, isomax=None, isomin=None, lighting=None, lightposition=None, meta=None, metasrc=None, name=None, opacity=None, reversescale=None, scene=None, showscale=None, slices=None, spaceframe=None, stream=None, surface=None, text=None, textsrc=None, uid=None, uirevision=None, value=None, valuesrc=None, visible=None, x=None, xsrc=None, y=None, ysrc=None, z=None, zsrc=None, row=None, col=None, **kwargs ): """ Add a new Isosurface trace Draws isosurfaces between iso-min and iso-max values with coordinates given by four 1-dimensional arrays containing the `value`, `x`, `y` and `z` of every vertex of a uniform or non- uniform 3-D grid. Horizontal or vertical slices, caps as well as spaceframe between iso-min and iso-max values could also be drawn using this trace. Parameters ---------- autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. caps plotly.graph_objects.isosurface.Caps instance or dict with compatible properties cauto Determines whether or not the color domain is computed with respect to the input data (here `value`) or the bounds set in `cmin` and `cmax` Defaults to `false` when `cmin` and `cmax` are set by the user. cmax Sets the upper bound of the color domain. Value should have the same units as `value` and if set, `cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `cmin` and/or `cmax` to be equidistant to this point. Value should have the same units as `value`. Has no effect when `cauto` is `false`. cmin Sets the lower bound of the color domain. Value should have the same units as `value` and if set, `cmax` must be set as well. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.isosurface.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`cmin` and `cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. contour plotly.graph_objects.isosurface.Contour instance or dict with compatible properties customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . flatshading Determines whether or not normal smoothing is applied to the meshes, creating meshes with an angular, low- poly look via flat reflections. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.isosurface.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . isomax Sets the maximum boundary for iso-surface plot. isomin Sets the minimum boundary for iso-surface plot. lighting plotly.graph_objects.isosurface.Lighting instance or dict with compatible properties lightposition plotly.graph_objects.isosurface.Lightposition instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the surface. Please note that in the case of using high `opacity` values for example a value greater than or equal to 0.5 on two surfaces (and 0.25 with four surfaces), an overlay of multiple transparent surfaces may not perfectly be sorted in depth by the webgl API. This behavior may be improved in the near future and is subject to change. reversescale Reverses the color mapping if true. If true, `cmin` will correspond to the last color in the array and `cmax` will correspond to the first color. scene Sets a reference between this trace's 3D coordinate system and a 3D scene. If "scene" (the default value), the (x,y,z) coordinates refer to `layout.scene`. If "scene2", the (x,y,z) coordinates refer to `layout.scene2`, and so on. showscale Determines whether or not a colorbar is displayed for this trace. slices plotly.graph_objects.isosurface.Slices instance or dict with compatible properties spaceframe plotly.graph_objects.isosurface.Spaceframe instance or dict with compatible properties stream plotly.graph_objects.isosurface.Stream instance or dict with compatible properties surface plotly.graph_objects.isosurface.Surface instance or dict with compatible properties text Sets the text elements associated with the vertices. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. value Sets the 4th dimension (value) of the vertices. valuesrc Sets the source reference on plot.ly for value . visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the X coordinates of the vertices on X axis. xsrc Sets the source reference on plot.ly for x . y Sets the Y coordinates of the vertices on Y axis. ysrc Sets the source reference on plot.ly for y . z Sets the Z coordinates of the vertices on Z axis. zsrc Sets the source reference on plot.ly for z . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- Figure """ new_trace = Isosurface( autocolorscale=autocolorscale, caps=caps, cauto=cauto, cmax=cmax, cmid=cmid, cmin=cmin, coloraxis=coloraxis, colorbar=colorbar, colorscale=colorscale, contour=contour, customdata=customdata, customdatasrc=customdatasrc, flatshading=flatshading, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, isomax=isomax, isomin=isomin, lighting=lighting, lightposition=lightposition, meta=meta, metasrc=metasrc, name=name, opacity=opacity, reversescale=reversescale, scene=scene, showscale=showscale, slices=slices, spaceframe=spaceframe, stream=stream, surface=surface, text=text, textsrc=textsrc, uid=uid, uirevision=uirevision, value=value, valuesrc=valuesrc, visible=visible, x=x, xsrc=xsrc, y=y, ysrc=ysrc, z=z, zsrc=zsrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_mesh3d( self, alphahull=None, autocolorscale=None, cauto=None, cmax=None, cmid=None, cmin=None, color=None, coloraxis=None, colorbar=None, colorscale=None, contour=None, customdata=None, customdatasrc=None, delaunayaxis=None, facecolor=None, facecolorsrc=None, flatshading=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, i=None, ids=None, idssrc=None, intensity=None, intensitysrc=None, isrc=None, j=None, jsrc=None, k=None, ksrc=None, lighting=None, lightposition=None, meta=None, metasrc=None, name=None, opacity=None, reversescale=None, scene=None, showscale=None, stream=None, text=None, textsrc=None, uid=None, uirevision=None, vertexcolor=None, vertexcolorsrc=None, visible=None, x=None, xcalendar=None, xsrc=None, y=None, ycalendar=None, ysrc=None, z=None, zcalendar=None, zsrc=None, row=None, col=None, **kwargs ): """ Add a new Mesh3d trace Draws sets of triangles with coordinates given by three 1-dimensional arrays in `x`, `y`, `z` and (1) a sets of `i`, `j`, `k` indices (2) Delaunay triangulation or (3) the Alpha- shape algorithm or (4) the Convex-hull algorithm Parameters ---------- alphahull Determines how the mesh surface triangles are derived from the set of vertices (points) represented by the `x`, `y` and `z` arrays, if the `i`, `j`, `k` arrays are not supplied. For general use of `mesh3d` it is preferred that `i`, `j`, `k` are supplied. If "-1", Delaunay triangulation is used, which is mainly suitable if the mesh is a single, more or less layer surface that is perpendicular to `delaunayaxis`. In case the `delaunayaxis` intersects the mesh surface at more than one point it will result triangles that are very long in the dimension of `delaunayaxis`. If ">0", the alpha-shape algorithm is used. In this case, the positive `alphahull` value signals the use of the alpha-shape algorithm, _and_ its value acts as the parameter for the mesh fitting. If 0, the convex-hull algorithm is used. It is suitable for convex bodies or if the intention is to enclose the `x`, `y` and `z` point set into a convex hull. autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here `intensity`) or the bounds set in `cmin` and `cmax` Defaults to `false` when `cmin` and `cmax` are set by the user. cmax Sets the upper bound of the color domain. Value should have the same units as `intensity` and if set, `cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `cmin` and/or `cmax` to be equidistant to this point. Value should have the same units as `intensity`. Has no effect when `cauto` is `false`. cmin Sets the lower bound of the color domain. Value should have the same units as `intensity` and if set, `cmax` must be set as well. color Sets the color of the whole mesh coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.mesh3d.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`cmin` and `cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. contour plotly.graph_objects.mesh3d.Contour instance or dict with compatible properties customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . delaunayaxis Sets the Delaunay axis, which is the axis that is perpendicular to the surface of the Delaunay triangulation. It has an effect if `i`, `j`, `k` are not provided and `alphahull` is set to indicate Delaunay triangulation. facecolor Sets the color of each face Overrides "color" and "vertexcolor". facecolorsrc Sets the source reference on plot.ly for facecolor . flatshading Determines whether or not normal smoothing is applied to the meshes, creating meshes with an angular, low- poly look via flat reflections. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.mesh3d.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . i A vector of vertex indices, i.e. integer values between 0 and the length of the vertex vectors, representing the "first" vertex of a triangle. For example, `{i[m], j[m], k[m]}` together represent face m (triangle m) in the mesh, where `i[m] = n` points to the triplet `{x[n], y[n], z[n]}` in the vertex arrays. Therefore, each element in `i` represents a point in space, which is the first vertex of a triangle. ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . intensity Sets the vertex intensity values, used for plotting fields on meshes intensitysrc Sets the source reference on plot.ly for intensity . isrc Sets the source reference on plot.ly for i . j A vector of vertex indices, i.e. integer values between 0 and the length of the vertex vectors, representing the "second" vertex of a triangle. For example, `{i[m], j[m], k[m]}` together represent face m (triangle m) in the mesh, where `j[m] = n` points to the triplet `{x[n], y[n], z[n]}` in the vertex arrays. Therefore, each element in `j` represents a point in space, which is the second vertex of a triangle. jsrc Sets the source reference on plot.ly for j . k A vector of vertex indices, i.e. integer values between 0 and the length of the vertex vectors, representing the "third" vertex of a triangle. For example, `{i[m], j[m], k[m]}` together represent face m (triangle m) in the mesh, where `k[m] = n` points to the triplet `{x[n], y[n], z[n]}` in the vertex arrays. Therefore, each element in `k` represents a point in space, which is the third vertex of a triangle. ksrc Sets the source reference on plot.ly for k . lighting plotly.graph_objects.mesh3d.Lighting instance or dict with compatible properties lightposition plotly.graph_objects.mesh3d.Lightposition instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the surface. Please note that in the case of using high `opacity` values for example a value greater than or equal to 0.5 on two surfaces (and 0.25 with four surfaces), an overlay of multiple transparent surfaces may not perfectly be sorted in depth by the webgl API. This behavior may be improved in the near future and is subject to change. reversescale Reverses the color mapping if true. If true, `cmin` will correspond to the last color in the array and `cmax` will correspond to the first color. scene Sets a reference between this trace's 3D coordinate system and a 3D scene. If "scene" (the default value), the (x,y,z) coordinates refer to `layout.scene`. If "scene2", the (x,y,z) coordinates refer to `layout.scene2`, and so on. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.mesh3d.Stream instance or dict with compatible properties text Sets the text elements associated with the vertices. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. vertexcolor Sets the color of each vertex Overrides "color". While Red, green and blue colors are in the range of 0 and 255; in the case of having vertex color data in RGBA format, the alpha color should be normalized to be between 0 and 1. vertexcolorsrc Sets the source reference on plot.ly for vertexcolor . visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the X coordinates of the vertices. The nth element of vectors `x`, `y` and `z` jointly represent the X, Y and Z coordinates of the nth vertex. xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . y Sets the Y coordinates of the vertices. The nth element of vectors `x`, `y` and `z` jointly represent the X, Y and Z coordinates of the nth vertex. ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . z Sets the Z coordinates of the vertices. The nth element of vectors `x`, `y` and `z` jointly represent the X, Y and Z coordinates of the nth vertex. zcalendar Sets the calendar system to use with `z` date data. zsrc Sets the source reference on plot.ly for z . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- Figure """ new_trace = Mesh3d( alphahull=alphahull, autocolorscale=autocolorscale, cauto=cauto, cmax=cmax, cmid=cmid, cmin=cmin, color=color, coloraxis=coloraxis, colorbar=colorbar, colorscale=colorscale, contour=contour, customdata=customdata, customdatasrc=customdatasrc, delaunayaxis=delaunayaxis, facecolor=facecolor, facecolorsrc=facecolorsrc, flatshading=flatshading, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, i=i, ids=ids, idssrc=idssrc, intensity=intensity, intensitysrc=intensitysrc, isrc=isrc, j=j, jsrc=jsrc, k=k, ksrc=ksrc, lighting=lighting, lightposition=lightposition, meta=meta, metasrc=metasrc, name=name, opacity=opacity, reversescale=reversescale, scene=scene, showscale=showscale, stream=stream, text=text, textsrc=textsrc, uid=uid, uirevision=uirevision, vertexcolor=vertexcolor, vertexcolorsrc=vertexcolorsrc, visible=visible, x=x, xcalendar=xcalendar, xsrc=xsrc, y=y, ycalendar=ycalendar, ysrc=ysrc, z=z, zcalendar=zcalendar, zsrc=zsrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_ohlc( self, close=None, closesrc=None, customdata=None, customdatasrc=None, decreasing=None, high=None, highsrc=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, increasing=None, legendgroup=None, line=None, low=None, lowsrc=None, meta=None, metasrc=None, name=None, opacity=None, open=None, opensrc=None, selectedpoints=None, showlegend=None, stream=None, text=None, textsrc=None, tickwidth=None, uid=None, uirevision=None, visible=None, x=None, xaxis=None, xcalendar=None, xsrc=None, yaxis=None, row=None, col=None, secondary_y=None, **kwargs ): """ Add a new Ohlc trace The ohlc (short for Open-High-Low-Close) is a style of financial chart describing open, high, low and close for a given `x` coordinate (most likely time). The tip of the lines represent the `low` and `high` values and the horizontal segments represent the `open` and `close` values. Sample points where the close value is higher (lower) then the open value are called increasing (decreasing). By default, increasing items are drawn in green whereas decreasing are drawn in red. Parameters ---------- close Sets the close values. closesrc Sets the source reference on plot.ly for close . customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . decreasing plotly.graph_objects.ohlc.Decreasing instance or dict with compatible properties high Sets the high values. highsrc Sets the source reference on plot.ly for high . hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.ohlc.Hoverlabel instance or dict with compatible properties hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . increasing plotly.graph_objects.ohlc.Increasing instance or dict with compatible properties legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.ohlc.Line instance or dict with compatible properties low Sets the low values. lowsrc Sets the source reference on plot.ly for low . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. open Sets the open values. opensrc Sets the source reference on plot.ly for open . selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.ohlc.Stream instance or dict with compatible properties text Sets hover text elements associated with each sample point. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to this trace's sample points. textsrc Sets the source reference on plot.ly for text . tickwidth Sets the width of the open/close tick marks relative to the "x" minimal interval. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the x coordinates. If absent, linear coordinate will be generated. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` secondary_y: boolean or None (default None) If True, associate this trace with the secondary y-axis of the subplot at the specified row and col. Only valid if all of the following conditions are satisfied: * The figure was created using `plotly.subplots.make_subplots`. * The row and col arguments are not None * The subplot at the specified row and col has type xy (which is the default) and secondary_y True. These properties are specified in the specs argument to make_subplots. See the make_subplots docstring for more info. Returns ------- Figure """ new_trace = Ohlc( close=close, closesrc=closesrc, customdata=customdata, customdatasrc=customdatasrc, decreasing=decreasing, high=high, highsrc=highsrc, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, increasing=increasing, legendgroup=legendgroup, line=line, low=low, lowsrc=lowsrc, meta=meta, metasrc=metasrc, name=name, opacity=opacity, open=open, opensrc=opensrc, selectedpoints=selectedpoints, showlegend=showlegend, stream=stream, text=text, textsrc=textsrc, tickwidth=tickwidth, uid=uid, uirevision=uirevision, visible=visible, x=x, xaxis=xaxis, xcalendar=xcalendar, xsrc=xsrc, yaxis=yaxis, **kwargs ) return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) def add_parcats( self, arrangement=None, bundlecolors=None, counts=None, countssrc=None, dimensions=None, dimensiondefaults=None, domain=None, hoverinfo=None, hoveron=None, hovertemplate=None, labelfont=None, line=None, meta=None, metasrc=None, name=None, sortpaths=None, stream=None, tickfont=None, uid=None, uirevision=None, visible=None, row=None, col=None, **kwargs ): """ Add a new Parcats trace Parallel categories diagram for multidimensional categorical data. Parameters ---------- arrangement Sets the drag interaction mode for categories and dimensions. If `perpendicular`, the categories can only move along a line perpendicular to the paths. If `freeform`, the categories can freely move on the plane. If `fixed`, the categories and dimensions are stationary. bundlecolors Sort paths so that like colors are bundled together within each category. counts The number of observations represented by each state. Defaults to 1 so that each state represents one observation countssrc Sets the source reference on plot.ly for counts . dimensions The dimensions (variables) of the parallel categories diagram. dimensiondefaults When used in a template (as layout.template.data.parcats.dimensiondefaults), sets the default property values to use for elements of parcats.dimensions domain plotly.graph_objects.parcats.Domain instance or dict with compatible properties hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoveron Sets the hover interaction mode for the parcats diagram. If `category`, hover interaction take place per category. If `color`, hover interactions take place per color per category. If `dimension`, hover interactions take place across all categories per dimension. hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `count`, `probability`, `category`, `categorycount`, `colorcount` and `bandcolorcount`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. labelfont Sets the font for the `dimension` labels. line plotly.graph_objects.parcats.Line instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. sortpaths Sets the path sorting algorithm. If `forward`, sort paths based on dimension categories from left to right. If `backward`, sort paths based on dimensions categories from right to left. stream plotly.graph_objects.parcats.Stream instance or dict with compatible properties tickfont Sets the font for the `category` labels. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- Figure """ new_trace = Parcats( arrangement=arrangement, bundlecolors=bundlecolors, counts=counts, countssrc=countssrc, dimensions=dimensions, dimensiondefaults=dimensiondefaults, domain=domain, hoverinfo=hoverinfo, hoveron=hoveron, hovertemplate=hovertemplate, labelfont=labelfont, line=line, meta=meta, metasrc=metasrc, name=name, sortpaths=sortpaths, stream=stream, tickfont=tickfont, uid=uid, uirevision=uirevision, visible=visible, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_parcoords( self, customdata=None, customdatasrc=None, dimensions=None, dimensiondefaults=None, domain=None, ids=None, idssrc=None, labelangle=None, labelfont=None, labelside=None, line=None, meta=None, metasrc=None, name=None, rangefont=None, stream=None, tickfont=None, uid=None, uirevision=None, visible=None, row=None, col=None, **kwargs ): """ Add a new Parcoords trace Parallel coordinates for multidimensional exploratory data analysis. The samples are specified in `dimensions`. The colors are set in `line.color`. Parameters ---------- customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dimensions The dimensions (variables) of the parallel coordinates chart. 2..60 dimensions are supported. dimensiondefaults When used in a template (as layout.template.data.parcoords.dimensiondefaults), sets the default property values to use for elements of parcoords.dimensions domain plotly.graph_objects.parcoords.Domain instance or dict with compatible properties ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . labelangle Sets the angle of the labels with respect to the horizontal. For example, a `tickangle` of -90 draws the labels vertically. Tilted labels with "labelangle" may be positioned better inside margins when `labelposition` is set to "bottom". labelfont Sets the font for the `dimension` labels. labelside Specifies the location of the `label`. "top" positions labels above, next to the title "bottom" positions labels below the graph Tilted labels with "labelangle" may be positioned better inside margins when `labelposition` is set to "bottom". line plotly.graph_objects.parcoords.Line instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. rangefont Sets the font for the `dimension` range values. stream plotly.graph_objects.parcoords.Stream instance or dict with compatible properties tickfont Sets the font for the `dimension` tick values. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- Figure """ new_trace = Parcoords( customdata=customdata, customdatasrc=customdatasrc, dimensions=dimensions, dimensiondefaults=dimensiondefaults, domain=domain, ids=ids, idssrc=idssrc, labelangle=labelangle, labelfont=labelfont, labelside=labelside, line=line, meta=meta, metasrc=metasrc, name=name, rangefont=rangefont, stream=stream, tickfont=tickfont, uid=uid, uirevision=uirevision, visible=visible, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_pie( self, automargin=None, customdata=None, customdatasrc=None, direction=None, dlabel=None, domain=None, hole=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, insidetextfont=None, label0=None, labels=None, labelssrc=None, legendgroup=None, marker=None, meta=None, metasrc=None, name=None, opacity=None, outsidetextfont=None, pull=None, pullsrc=None, rotation=None, scalegroup=None, showlegend=None, sort=None, stream=None, text=None, textfont=None, textinfo=None, textposition=None, textpositionsrc=None, textsrc=None, texttemplate=None, texttemplatesrc=None, title=None, titlefont=None, titleposition=None, uid=None, uirevision=None, values=None, valuessrc=None, visible=None, row=None, col=None, **kwargs ): """ Add a new Pie trace A data visualized by the sectors of the pie is set in `values`. The sector labels are set in `labels`. The sector colors are set in `marker.colors` Parameters ---------- automargin Determines whether outside text labels can push the margins. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . direction Specifies the direction at which succeeding sectors follow one another. dlabel Sets the label step. See `label0` for more info. domain plotly.graph_objects.pie.Domain instance or dict with compatible properties hole Sets the fraction of the radius to cut out of the pie. Use this to make a donut chart. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.pie.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `label`, `color`, `value`, `percent` and `text`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each sector. If a single string, the same string appears for all data points. If an array of string, the items are mapped in order of this trace's sectors. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . insidetextfont Sets the font used for `textinfo` lying inside the sector. label0 Alternate to `labels`. Builds a numeric set of labels. Use with `dlabel` where `label0` is the starting label and `dlabel` the step. labels Sets the sector labels. If `labels` entries are duplicated, we sum associated `values` or simply count occurrences if `values` is not provided. For other array attributes (including color) we use the first non-empty entry among all occurrences of the label. labelssrc Sets the source reference on plot.ly for labels . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. marker plotly.graph_objects.pie.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. outsidetextfont Sets the font used for `textinfo` lying outside the sector. pull Sets the fraction of larger radius to pull the sectors out from the center. This can be a constant to pull all slices apart from each other equally or an array to highlight one or more slices. pullsrc Sets the source reference on plot.ly for pull . rotation Instead of the first slice starting at 12 o'clock, rotate to some other angle. scalegroup If there are multiple pie charts that should be sized according to their totals, link them by providing a non-empty group id here shared by every trace in the same group. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. sort Determines whether or not the sectors are reordered from largest to smallest. stream plotly.graph_objects.pie.Stream instance or dict with compatible properties text Sets text elements associated with each sector. If trace `textinfo` contains a "text" flag, these elements will be seen on the chart. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the font used for `textinfo`. textinfo Determines which trace information appear on the graph. textposition Specifies the location of the `textinfo`. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `label`, `color`, `value`, `percent` and `text`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . title plotly.graph_objects.pie.Title instance or dict with compatible properties titlefont Deprecated: Please use pie.title.font instead. Sets the font used for `title`. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleposition Deprecated: Please use pie.title.position instead. Specifies the location of the `title`. Note that the title's position used to be set by the now deprecated `titleposition` attribute. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. values Sets the values of the sectors. If omitted, we count occurrences of each label. valuessrc Sets the source reference on plot.ly for values . visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- Figure """ new_trace = Pie( automargin=automargin, customdata=customdata, customdatasrc=customdatasrc, direction=direction, dlabel=dlabel, domain=domain, hole=hole, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, insidetextfont=insidetextfont, label0=label0, labels=labels, labelssrc=labelssrc, legendgroup=legendgroup, marker=marker, meta=meta, metasrc=metasrc, name=name, opacity=opacity, outsidetextfont=outsidetextfont, pull=pull, pullsrc=pullsrc, rotation=rotation, scalegroup=scalegroup, showlegend=showlegend, sort=sort, stream=stream, text=text, textfont=textfont, textinfo=textinfo, textposition=textposition, textpositionsrc=textpositionsrc, textsrc=textsrc, texttemplate=texttemplate, texttemplatesrc=texttemplatesrc, title=title, titlefont=titlefont, titleposition=titleposition, uid=uid, uirevision=uirevision, values=values, valuessrc=valuessrc, visible=visible, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_pointcloud( self, customdata=None, customdatasrc=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, ids=None, idssrc=None, indices=None, indicessrc=None, legendgroup=None, marker=None, meta=None, metasrc=None, name=None, opacity=None, showlegend=None, stream=None, text=None, textsrc=None, uid=None, uirevision=None, visible=None, x=None, xaxis=None, xbounds=None, xboundssrc=None, xsrc=None, xy=None, xysrc=None, y=None, yaxis=None, ybounds=None, yboundssrc=None, ysrc=None, row=None, col=None, secondary_y=None, **kwargs ): """ Add a new Pointcloud trace The data visualized as a point cloud set in `x` and `y` using the WebGl plotting engine. Parameters ---------- customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.pointcloud.Hoverlabel instance or dict with compatible properties ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . indices A sequential value, 0..n, supply it to avoid creating this array inside plotting. If specified, it must be a typed `Int32Array` array. Its length must be equal to or greater than the number of points. For the best performance and memory use, create one large `indices` typed array that is guaranteed to be at least as long as the largest number of points during use, and reuse it on each `Plotly.restyle()` call. indicessrc Sets the source reference on plot.ly for indices . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. marker plotly.graph_objects.pointcloud.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.pointcloud.Stream instance or dict with compatible properties text Sets text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the x coordinates. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xbounds Specify `xbounds` in the shape of `[xMin, xMax] to avoid looping through the `xy` typed array. Use it in conjunction with `xy` and `ybounds` for the performance benefits. xboundssrc Sets the source reference on plot.ly for xbounds . xsrc Sets the source reference on plot.ly for x . xy Faster alternative to specifying `x` and `y` separately. If supplied, it must be a typed `Float32Array` array that represents points such that `xy[i * 2] = x[i]` and `xy[i * 2 + 1] = y[i]` xysrc Sets the source reference on plot.ly for xy . y Sets the y coordinates. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ybounds Specify `ybounds` in the shape of `[yMin, yMax] to avoid looping through the `xy` typed array. Use it in conjunction with `xy` and `xbounds` for the performance benefits. yboundssrc Sets the source reference on plot.ly for ybounds . ysrc Sets the source reference on plot.ly for y . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` secondary_y: boolean or None (default None) If True, associate this trace with the secondary y-axis of the subplot at the specified row and col. Only valid if all of the following conditions are satisfied: * The figure was created using `plotly.subplots.make_subplots`. * The row and col arguments are not None * The subplot at the specified row and col has type xy (which is the default) and secondary_y True. These properties are specified in the specs argument to make_subplots. See the make_subplots docstring for more info. Returns ------- Figure """ new_trace = Pointcloud( customdata=customdata, customdatasrc=customdatasrc, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, ids=ids, idssrc=idssrc, indices=indices, indicessrc=indicessrc, legendgroup=legendgroup, marker=marker, meta=meta, metasrc=metasrc, name=name, opacity=opacity, showlegend=showlegend, stream=stream, text=text, textsrc=textsrc, uid=uid, uirevision=uirevision, visible=visible, x=x, xaxis=xaxis, xbounds=xbounds, xboundssrc=xboundssrc, xsrc=xsrc, xy=xy, xysrc=xysrc, y=y, yaxis=yaxis, ybounds=ybounds, yboundssrc=yboundssrc, ysrc=ysrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) def add_sankey( self, arrangement=None, customdata=None, customdatasrc=None, domain=None, hoverinfo=None, hoverlabel=None, ids=None, idssrc=None, link=None, meta=None, metasrc=None, name=None, node=None, orientation=None, selectedpoints=None, stream=None, textfont=None, uid=None, uirevision=None, valueformat=None, valuesuffix=None, visible=None, row=None, col=None, **kwargs ): """ Add a new Sankey trace Sankey plots for network flow data analysis. The nodes are specified in `nodes` and the links between sources and targets in `links`. The colors are set in `nodes[i].color` and `links[i].color`, otherwise defaults are used. Parameters ---------- arrangement If value is `snap` (the default), the node arrangement is assisted by automatic snapping of elements to preserve space between nodes specified via `nodepad`. If value is `perpendicular`, the nodes can only move along a line perpendicular to the flow. If value is `freeform`, the nodes can freely move on the plane. If value is `fixed`, the nodes are stationary. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . domain plotly.graph_objects.sankey.Domain instance or dict with compatible properties hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. Note that this attribute is superseded by `node.hoverinfo` and `node.hoverinfo` for nodes and links respectively. hoverlabel plotly.graph_objects.sankey.Hoverlabel instance or dict with compatible properties ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . link The links of the Sankey plot. meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. node The nodes of the Sankey plot. orientation Sets the orientation of the Sankey diagram. selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. stream plotly.graph_objects.sankey.Stream instance or dict with compatible properties textfont Sets the font for node labels uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. valueformat Sets the value formatting rule using d3 formatting mini-language which is similar to those of Python. See https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format valuesuffix Adds a unit to follow the value in the hover tooltip. Add a space if a separation is necessary from the value. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- Figure """ new_trace = Sankey( arrangement=arrangement, customdata=customdata, customdatasrc=customdatasrc, domain=domain, hoverinfo=hoverinfo, hoverlabel=hoverlabel, ids=ids, idssrc=idssrc, link=link, meta=meta, metasrc=metasrc, name=name, node=node, orientation=orientation, selectedpoints=selectedpoints, stream=stream, textfont=textfont, uid=uid, uirevision=uirevision, valueformat=valueformat, valuesuffix=valuesuffix, visible=visible, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_scatter( self, cliponaxis=None, connectgaps=None, customdata=None, customdatasrc=None, dx=None, dy=None, error_x=None, error_y=None, fill=None, fillcolor=None, groupnorm=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hoveron=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, legendgroup=None, line=None, marker=None, meta=None, metasrc=None, mode=None, name=None, opacity=None, orientation=None, r=None, rsrc=None, selected=None, selectedpoints=None, showlegend=None, stackgaps=None, stackgroup=None, stream=None, t=None, text=None, textfont=None, textposition=None, textpositionsrc=None, textsrc=None, texttemplate=None, texttemplatesrc=None, tsrc=None, uid=None, uirevision=None, unselected=None, visible=None, x=None, x0=None, xaxis=None, xcalendar=None, xsrc=None, y=None, y0=None, yaxis=None, ycalendar=None, ysrc=None, row=None, col=None, secondary_y=None, **kwargs ): """ Add a new Scatter trace The scatter trace type encompasses line charts, scatter charts, text charts, and bubble charts. The data visualized as scatter point or lines is set in `x` and `y`. Text (appearing either on the chart or on hover only) is via `text`. Bubble charts are achieved by setting `marker.size` and/or `marker.color` to numerical arrays. Parameters ---------- cliponaxis Determines whether or not markers and text nodes are clipped about the subplot axes. To show markers and text nodes above axis lines and tick labels, make sure to set `xaxis.layer` and `yaxis.layer` to *below traces*. connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dx Sets the x coordinate step. See `x0` for more info. dy Sets the y coordinate step. See `y0` for more info. error_x plotly.graph_objects.scatter.ErrorX instance or dict with compatible properties error_y plotly.graph_objects.scatter.ErrorY instance or dict with compatible properties fill Sets the area to fill with a solid color. Defaults to "none" unless this trace is stacked, then it gets "tonexty" ("tonextx") if `orientation` is "v" ("h") Use with `fillcolor` if not "none". "tozerox" and "tozeroy" fill to x=0 and y=0 respectively. "tonextx" and "tonexty" fill between the endpoints of this trace and the endpoints of the trace before it, connecting those endpoints with straight lines (to make a stacked area graph); if there is no trace before it, they behave like "tozerox" and "tozeroy". "toself" connects the endpoints of the trace (or each segment of the trace if it has gaps) into a closed shape. "tonext" fills the space between two traces if one completely encloses the other (eg consecutive contour lines), and behaves like "toself" if there is no trace before it. "tonext" should not be used if one trace does not enclose the other. Traces in a `stackgroup` will only fill to (or be filled to) other traces in the same group. With multiple `stackgroup`s or some traces stacked and some not, if fill-linked traces are not already consecutive, the later ones will be pushed down in the drawing order. fillcolor Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. groupnorm Only relevant when `stackgroup` is used, and only the first `groupnorm` found in the `stackgroup` will be used - including if `visible` is "legendonly" but not if it is `false`. Sets the normalization for the sum of this `stackgroup`. With "fraction", the value of each trace at each location is divided by the sum of all trace values at that location. "percent" is the same but multiplied by 100 to show percentages. If there are multiple subplots, or multiple `stackgroup`s on one subplot, each will be normalized within its own set. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.scatter.Hoverlabel instance or dict with compatible properties hoveron Do the hover effects highlight individual points (markers or line points) or do they highlight filled regions? If the fill is "toself" or "tonext" and there are no markers or text, then the default is "fills", otherwise it is "points". hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.scatter.Line instance or dict with compatible properties marker plotly.graph_objects.scatter.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . mode Determines the drawing mode for this scatter trace. If the provided `mode` includes "text" then the `text` elements appear at the coordinates. Otherwise, the `text` elements appear on hover. If there are less than 20 points and the trace is not stacked then the default is "lines+markers". Otherwise, "lines". name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. orientation Only relevant when `stackgroup` is used, and only the first `orientation` found in the `stackgroup` will be used - including if `visible` is "legendonly" but not if it is `false`. Sets the stacking direction. With "v" ("h"), the y (x) values of subsequent traces are added. Also affects the default value of `fill`. r r coordinates in scatter traces are deprecated!Please switch to the "scatterpolar" trace type.Sets the radial coordinatesfor legacy polar chart only. rsrc Sets the source reference on plot.ly for r . selected plotly.graph_objects.scatter.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stackgaps Only relevant when `stackgroup` is used, and only the first `stackgaps` found in the `stackgroup` will be used - including if `visible` is "legendonly" but not if it is `false`. Determines how we handle locations at which other traces in this group have data but this one does not. With *infer zero* we insert a zero at these locations. With "interpolate" we linearly interpolate between existing values, and extrapolate a constant beyond the existing values. stackgroup Set several scatter traces (on the same subplot) to the same stackgroup in order to add their y values (or their x values if `orientation` is "h"). If blank or omitted this trace will not be stacked. Stacking also turns `fill` on by default, using "tonexty" ("tonextx") if `orientation` is "h" ("v") and sets the default `mode` to "lines" irrespective of point count. You can only stack on a numeric (linear or log) axis. Traces in a `stackgroup` will only fill to (or be filled to) other traces in the same group. With multiple `stackgroup`s or some traces stacked and some not, if fill-linked traces are not already consecutive, the later ones will be pushed down in the drawing order. stream plotly.graph_objects.scatter.Stream instance or dict with compatible properties t t coordinates in scatter traces are deprecated!Please switch to the "scatterpolar" trace type.Sets the angular coordinatesfor legacy polar chart only. text Sets text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the text font. textposition Sets the positions of the `text` elements with respects to the (x,y) coordinates. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. texttemplatesrc Sets the source reference on plot.ly for texttemplate . tsrc Sets the source reference on plot.ly for t . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.scatter.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the x coordinates. x0 Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . y Sets the y coordinates. y0 Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` secondary_y: boolean or None (default None) If True, associate this trace with the secondary y-axis of the subplot at the specified row and col. Only valid if all of the following conditions are satisfied: * The figure was created using `plotly.subplots.make_subplots`. * The row and col arguments are not None * The subplot at the specified row and col has type xy (which is the default) and secondary_y True. These properties are specified in the specs argument to make_subplots. See the make_subplots docstring for more info. Returns ------- Figure """ new_trace = Scatter( cliponaxis=cliponaxis, connectgaps=connectgaps, customdata=customdata, customdatasrc=customdatasrc, dx=dx, dy=dy, error_x=error_x, error_y=error_y, fill=fill, fillcolor=fillcolor, groupnorm=groupnorm, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hoveron=hoveron, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, legendgroup=legendgroup, line=line, marker=marker, meta=meta, metasrc=metasrc, mode=mode, name=name, opacity=opacity, orientation=orientation, r=r, rsrc=rsrc, selected=selected, selectedpoints=selectedpoints, showlegend=showlegend, stackgaps=stackgaps, stackgroup=stackgroup, stream=stream, t=t, text=text, textfont=textfont, textposition=textposition, textpositionsrc=textpositionsrc, textsrc=textsrc, texttemplate=texttemplate, texttemplatesrc=texttemplatesrc, tsrc=tsrc, uid=uid, uirevision=uirevision, unselected=unselected, visible=visible, x=x, x0=x0, xaxis=xaxis, xcalendar=xcalendar, xsrc=xsrc, y=y, y0=y0, yaxis=yaxis, ycalendar=ycalendar, ysrc=ysrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) def add_scatter3d( self, connectgaps=None, customdata=None, customdatasrc=None, error_x=None, error_y=None, error_z=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, legendgroup=None, line=None, marker=None, meta=None, metasrc=None, mode=None, name=None, opacity=None, projection=None, scene=None, showlegend=None, stream=None, surfaceaxis=None, surfacecolor=None, text=None, textfont=None, textposition=None, textpositionsrc=None, textsrc=None, texttemplate=None, texttemplatesrc=None, uid=None, uirevision=None, visible=None, x=None, xcalendar=None, xsrc=None, y=None, ycalendar=None, ysrc=None, z=None, zcalendar=None, zsrc=None, row=None, col=None, **kwargs ): """ Add a new Scatter3d trace The data visualized as scatter point or lines in 3D dimension is set in `x`, `y`, `z`. Text (appearing either on the chart or on hover only) is via `text`. Bubble charts are achieved by setting `marker.size` and/or `marker.color` Projections are achieved via `projection`. Surface fills are achieved via `surfaceaxis`. Parameters ---------- connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . error_x plotly.graph_objects.scatter3d.ErrorX instance or dict with compatible properties error_y plotly.graph_objects.scatter3d.ErrorY instance or dict with compatible properties error_z plotly.graph_objects.scatter3d.ErrorZ instance or dict with compatible properties hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.scatter3d.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets text elements associated with each (x,y,z) triplet. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y,z) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.scatter3d.Line instance or dict with compatible properties marker plotly.graph_objects.scatter3d.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . mode Determines the drawing mode for this scatter trace. If the provided `mode` includes "text" then the `text` elements appear at the coordinates. Otherwise, the `text` elements appear on hover. If there are less than 20 points and the trace is not stacked then the default is "lines+markers". Otherwise, "lines". name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. projection plotly.graph_objects.scatter3d.Projection instance or dict with compatible properties scene Sets a reference between this trace's 3D coordinate system and a 3D scene. If "scene" (the default value), the (x,y,z) coordinates refer to `layout.scene`. If "scene2", the (x,y,z) coordinates refer to `layout.scene2`, and so on. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.scatter3d.Stream instance or dict with compatible properties surfaceaxis If "-1", the scatter points are not fill with a surface If 0, 1, 2, the scatter points are filled with a Delaunay surface about the x, y, z respectively. surfacecolor Sets the surface fill color. text Sets text elements associated with each (x,y,z) triplet. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y,z) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont plotly.graph_objects.scatter3d.Textfont instance or dict with compatible properties textposition Sets the positions of the `text` elements with respects to the (x,y) coordinates. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. texttemplatesrc Sets the source reference on plot.ly for texttemplate . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the x coordinates. xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . y Sets the y coordinates. ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . z Sets the z coordinates. zcalendar Sets the calendar system to use with `z` date data. zsrc Sets the source reference on plot.ly for z . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- Figure """ new_trace = Scatter3d( connectgaps=connectgaps, customdata=customdata, customdatasrc=customdatasrc, error_x=error_x, error_y=error_y, error_z=error_z, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, legendgroup=legendgroup, line=line, marker=marker, meta=meta, metasrc=metasrc, mode=mode, name=name, opacity=opacity, projection=projection, scene=scene, showlegend=showlegend, stream=stream, surfaceaxis=surfaceaxis, surfacecolor=surfacecolor, text=text, textfont=textfont, textposition=textposition, textpositionsrc=textpositionsrc, textsrc=textsrc, texttemplate=texttemplate, texttemplatesrc=texttemplatesrc, uid=uid, uirevision=uirevision, visible=visible, x=x, xcalendar=xcalendar, xsrc=xsrc, y=y, ycalendar=ycalendar, ysrc=ysrc, z=z, zcalendar=zcalendar, zsrc=zsrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_scattercarpet( self, a=None, asrc=None, b=None, bsrc=None, carpet=None, connectgaps=None, customdata=None, customdatasrc=None, fill=None, fillcolor=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hoveron=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, legendgroup=None, line=None, marker=None, meta=None, metasrc=None, mode=None, name=None, opacity=None, selected=None, selectedpoints=None, showlegend=None, stream=None, text=None, textfont=None, textposition=None, textpositionsrc=None, textsrc=None, texttemplate=None, texttemplatesrc=None, uid=None, uirevision=None, unselected=None, visible=None, xaxis=None, yaxis=None, row=None, col=None, secondary_y=None, **kwargs ): """ Add a new Scattercarpet trace Plots a scatter trace on either the first carpet axis or the carpet axis with a matching `carpet` attribute. Parameters ---------- a Sets the a-axis coordinates. asrc Sets the source reference on plot.ly for a . b Sets the b-axis coordinates. bsrc Sets the source reference on plot.ly for b . carpet An identifier for this carpet, so that `scattercarpet` and `contourcarpet` traces can specify a carpet plot on which they lie connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . fill Sets the area to fill with a solid color. Use with `fillcolor` if not "none". scatterternary has a subset of the options available to scatter. "toself" connects the endpoints of the trace (or each segment of the trace if it has gaps) into a closed shape. "tonext" fills the space between two traces if one completely encloses the other (eg consecutive contour lines), and behaves like "toself" if there is no trace before it. "tonext" should not be used if one trace does not enclose the other. fillcolor Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.scattercarpet.Hoverlabel instance or dict with compatible properties hoveron Do the hover effects highlight individual points (markers or line points) or do they highlight filled regions? If the fill is "toself" or "tonext" and there are no markers or text, then the default is "fills", otherwise it is "points". hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (a,b) point. If a single string, the same string appears over all the data points. If an array of strings, the items are mapped in order to the the data points in (a,b). To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.scattercarpet.Line instance or dict with compatible properties marker plotly.graph_objects.scattercarpet.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . mode Determines the drawing mode for this scatter trace. If the provided `mode` includes "text" then the `text` elements appear at the coordinates. Otherwise, the `text` elements appear on hover. If there are less than 20 points and the trace is not stacked then the default is "lines+markers". Otherwise, "lines". name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. selected plotly.graph_objects.scattercarpet.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.scattercarpet.Stream instance or dict with compatible properties text Sets text elements associated with each (a,b) point. If a single string, the same string appears over all the data points. If an array of strings, the items are mapped in order to the the data points in (a,b). If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the text font. textposition Sets the positions of the `text` elements with respects to the (x,y) coordinates. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `a`, `b` and `text`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.scattercarpet.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` secondary_y: boolean or None (default None) If True, associate this trace with the secondary y-axis of the subplot at the specified row and col. Only valid if all of the following conditions are satisfied: * The figure was created using `plotly.subplots.make_subplots`. * The row and col arguments are not None * The subplot at the specified row and col has type xy (which is the default) and secondary_y True. These properties are specified in the specs argument to make_subplots. See the make_subplots docstring for more info. Returns ------- Figure """ new_trace = Scattercarpet( a=a, asrc=asrc, b=b, bsrc=bsrc, carpet=carpet, connectgaps=connectgaps, customdata=customdata, customdatasrc=customdatasrc, fill=fill, fillcolor=fillcolor, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hoveron=hoveron, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, legendgroup=legendgroup, line=line, marker=marker, meta=meta, metasrc=metasrc, mode=mode, name=name, opacity=opacity, selected=selected, selectedpoints=selectedpoints, showlegend=showlegend, stream=stream, text=text, textfont=textfont, textposition=textposition, textpositionsrc=textpositionsrc, textsrc=textsrc, texttemplate=texttemplate, texttemplatesrc=texttemplatesrc, uid=uid, uirevision=uirevision, unselected=unselected, visible=visible, xaxis=xaxis, yaxis=yaxis, **kwargs ) return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) def add_scattergeo( self, connectgaps=None, customdata=None, customdatasrc=None, fill=None, fillcolor=None, geo=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, lat=None, latsrc=None, legendgroup=None, line=None, locationmode=None, locations=None, locationssrc=None, lon=None, lonsrc=None, marker=None, meta=None, metasrc=None, mode=None, name=None, opacity=None, selected=None, selectedpoints=None, showlegend=None, stream=None, text=None, textfont=None, textposition=None, textpositionsrc=None, textsrc=None, texttemplate=None, texttemplatesrc=None, uid=None, uirevision=None, unselected=None, visible=None, row=None, col=None, **kwargs ): """ Add a new Scattergeo trace The data visualized as scatter point or lines on a geographic map is provided either by longitude/latitude pairs in `lon` and `lat` respectively or by geographic location IDs or names in `locations`. Parameters ---------- connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . fill Sets the area to fill with a solid color. Use with `fillcolor` if not "none". "toself" connects the endpoints of the trace (or each segment of the trace if it has gaps) into a closed shape. fillcolor Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. geo Sets a reference between this trace's geospatial coordinates and a geographic map. If "geo" (the default value), the geospatial coordinates refer to `layout.geo`. If "geo2", the geospatial coordinates refer to `layout.geo2`, and so on. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.scattergeo.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (lon,lat) pair or item in `locations`. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (lon,lat) or `locations` coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . lat Sets the latitude coordinates (in degrees North). latsrc Sets the source reference on plot.ly for lat . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.scattergeo.Line instance or dict with compatible properties locationmode Determines the set of locations used to match entries in `locations` to regions on the map. locations Sets the coordinates via location IDs or names. Coordinates correspond to the centroid of each location given. See `locationmode` for more info. locationssrc Sets the source reference on plot.ly for locations . lon Sets the longitude coordinates (in degrees East). lonsrc Sets the source reference on plot.ly for lon . marker plotly.graph_objects.scattergeo.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . mode Determines the drawing mode for this scatter trace. If the provided `mode` includes "text" then the `text` elements appear at the coordinates. Otherwise, the `text` elements appear on hover. If there are less than 20 points and the trace is not stacked then the default is "lines+markers". Otherwise, "lines". name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. selected plotly.graph_objects.scattergeo.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.scattergeo.Stream instance or dict with compatible properties text Sets text elements associated with each (lon,lat) pair or item in `locations`. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (lon,lat) or `locations` coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the text font. textposition Sets the positions of the `text` elements with respects to the (x,y) coordinates. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `lat`, `lon`, `location` and `text`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.scattergeo.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- Figure """ new_trace = Scattergeo( connectgaps=connectgaps, customdata=customdata, customdatasrc=customdatasrc, fill=fill, fillcolor=fillcolor, geo=geo, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, lat=lat, latsrc=latsrc, legendgroup=legendgroup, line=line, locationmode=locationmode, locations=locations, locationssrc=locationssrc, lon=lon, lonsrc=lonsrc, marker=marker, meta=meta, metasrc=metasrc, mode=mode, name=name, opacity=opacity, selected=selected, selectedpoints=selectedpoints, showlegend=showlegend, stream=stream, text=text, textfont=textfont, textposition=textposition, textpositionsrc=textpositionsrc, textsrc=textsrc, texttemplate=texttemplate, texttemplatesrc=texttemplatesrc, uid=uid, uirevision=uirevision, unselected=unselected, visible=visible, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_scattergl( self, connectgaps=None, customdata=None, customdatasrc=None, dx=None, dy=None, error_x=None, error_y=None, fill=None, fillcolor=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, legendgroup=None, line=None, marker=None, meta=None, metasrc=None, mode=None, name=None, opacity=None, selected=None, selectedpoints=None, showlegend=None, stream=None, text=None, textfont=None, textposition=None, textpositionsrc=None, textsrc=None, texttemplate=None, texttemplatesrc=None, uid=None, uirevision=None, unselected=None, visible=None, x=None, x0=None, xaxis=None, xcalendar=None, xsrc=None, y=None, y0=None, yaxis=None, ycalendar=None, ysrc=None, row=None, col=None, secondary_y=None, **kwargs ): """ Add a new Scattergl trace The data visualized as scatter point or lines is set in `x` and `y` using the WebGL plotting engine. Bubble charts are achieved by setting `marker.size` and/or `marker.color` to a numerical arrays. Parameters ---------- connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dx Sets the x coordinate step. See `x0` for more info. dy Sets the y coordinate step. See `y0` for more info. error_x plotly.graph_objects.scattergl.ErrorX instance or dict with compatible properties error_y plotly.graph_objects.scattergl.ErrorY instance or dict with compatible properties fill Sets the area to fill with a solid color. Defaults to "none" unless this trace is stacked, then it gets "tonexty" ("tonextx") if `orientation` is "v" ("h") Use with `fillcolor` if not "none". "tozerox" and "tozeroy" fill to x=0 and y=0 respectively. "tonextx" and "tonexty" fill between the endpoints of this trace and the endpoints of the trace before it, connecting those endpoints with straight lines (to make a stacked area graph); if there is no trace before it, they behave like "tozerox" and "tozeroy". "toself" connects the endpoints of the trace (or each segment of the trace if it has gaps) into a closed shape. "tonext" fills the space between two traces if one completely encloses the other (eg consecutive contour lines), and behaves like "toself" if there is no trace before it. "tonext" should not be used if one trace does not enclose the other. Traces in a `stackgroup` will only fill to (or be filled to) other traces in the same group. With multiple `stackgroup`s or some traces stacked and some not, if fill-linked traces are not already consecutive, the later ones will be pushed down in the drawing order. fillcolor Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.scattergl.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.scattergl.Line instance or dict with compatible properties marker plotly.graph_objects.scattergl.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . mode Determines the drawing mode for this scatter trace. name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. selected plotly.graph_objects.scattergl.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.scattergl.Stream instance or dict with compatible properties text Sets text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the text font. textposition Sets the positions of the `text` elements with respects to the (x,y) coordinates. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. texttemplatesrc Sets the source reference on plot.ly for texttemplate . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.scattergl.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the x coordinates. x0 Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . y Sets the y coordinates. y0 Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` secondary_y: boolean or None (default None) If True, associate this trace with the secondary y-axis of the subplot at the specified row and col. Only valid if all of the following conditions are satisfied: * The figure was created using `plotly.subplots.make_subplots`. * The row and col arguments are not None * The subplot at the specified row and col has type xy (which is the default) and secondary_y True. These properties are specified in the specs argument to make_subplots. See the make_subplots docstring for more info. Returns ------- Figure """ new_trace = Scattergl( connectgaps=connectgaps, customdata=customdata, customdatasrc=customdatasrc, dx=dx, dy=dy, error_x=error_x, error_y=error_y, fill=fill, fillcolor=fillcolor, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, legendgroup=legendgroup, line=line, marker=marker, meta=meta, metasrc=metasrc, mode=mode, name=name, opacity=opacity, selected=selected, selectedpoints=selectedpoints, showlegend=showlegend, stream=stream, text=text, textfont=textfont, textposition=textposition, textpositionsrc=textpositionsrc, textsrc=textsrc, texttemplate=texttemplate, texttemplatesrc=texttemplatesrc, uid=uid, uirevision=uirevision, unselected=unselected, visible=visible, x=x, x0=x0, xaxis=xaxis, xcalendar=xcalendar, xsrc=xsrc, y=y, y0=y0, yaxis=yaxis, ycalendar=ycalendar, ysrc=ysrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) def add_scattermapbox( self, below=None, connectgaps=None, customdata=None, customdatasrc=None, fill=None, fillcolor=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, lat=None, latsrc=None, legendgroup=None, line=None, lon=None, lonsrc=None, marker=None, meta=None, metasrc=None, mode=None, name=None, opacity=None, selected=None, selectedpoints=None, showlegend=None, stream=None, subplot=None, text=None, textfont=None, textposition=None, textsrc=None, texttemplate=None, texttemplatesrc=None, uid=None, uirevision=None, unselected=None, visible=None, row=None, col=None, **kwargs ): """ Add a new Scattermapbox trace The data visualized as scatter point, lines or marker symbols on a Mapbox GL geographic map is provided by longitude/latitude pairs in `lon` and `lat`. Parameters ---------- below Determines if this scattermapbox trace's layers are to be inserted before the layer with the specified ID. By default, scattermapbox layers are inserted above all the base layers. To place the scattermapbox layers above every other layer, set `below` to "''". connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . fill Sets the area to fill with a solid color. Use with `fillcolor` if not "none". "toself" connects the endpoints of the trace (or each segment of the trace if it has gaps) into a closed shape. fillcolor Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.scattermapbox.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (lon,lat) pair If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (lon,lat) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . lat Sets the latitude coordinates (in degrees North). latsrc Sets the source reference on plot.ly for lat . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.scattermapbox.Line instance or dict with compatible properties lon Sets the longitude coordinates (in degrees East). lonsrc Sets the source reference on plot.ly for lon . marker plotly.graph_objects.scattermapbox.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . mode Determines the drawing mode for this scatter trace. If the provided `mode` includes "text" then the `text` elements appear at the coordinates. Otherwise, the `text` elements appear on hover. name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. selected plotly.graph_objects.scattermapbox.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.scattermapbox.Stream instance or dict with compatible properties subplot Sets a reference between this trace's data coordinates and a mapbox subplot. If "mapbox" (the default value), the data refer to `layout.mapbox`. If "mapbox2", the data refer to `layout.mapbox2`, and so on. text Sets text elements associated with each (lon,lat) pair If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (lon,lat) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the icon text font (color=mapbox.layer.paint.text- color, size=mapbox.layer.layout.text-size). Has an effect only when `type` is set to "symbol". textposition Sets the positions of the `text` elements with respects to the (x,y) coordinates. textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `lat`, `lon` and `text`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.scattermapbox.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- Figure """ new_trace = Scattermapbox( below=below, connectgaps=connectgaps, customdata=customdata, customdatasrc=customdatasrc, fill=fill, fillcolor=fillcolor, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, lat=lat, latsrc=latsrc, legendgroup=legendgroup, line=line, lon=lon, lonsrc=lonsrc, marker=marker, meta=meta, metasrc=metasrc, mode=mode, name=name, opacity=opacity, selected=selected, selectedpoints=selectedpoints, showlegend=showlegend, stream=stream, subplot=subplot, text=text, textfont=textfont, textposition=textposition, textsrc=textsrc, texttemplate=texttemplate, texttemplatesrc=texttemplatesrc, uid=uid, uirevision=uirevision, unselected=unselected, visible=visible, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_scatterpolar( self, cliponaxis=None, connectgaps=None, customdata=None, customdatasrc=None, dr=None, dtheta=None, fill=None, fillcolor=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hoveron=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, legendgroup=None, line=None, marker=None, meta=None, metasrc=None, mode=None, name=None, opacity=None, r=None, r0=None, rsrc=None, selected=None, selectedpoints=None, showlegend=None, stream=None, subplot=None, text=None, textfont=None, textposition=None, textpositionsrc=None, textsrc=None, texttemplate=None, texttemplatesrc=None, theta=None, theta0=None, thetasrc=None, thetaunit=None, uid=None, uirevision=None, unselected=None, visible=None, row=None, col=None, **kwargs ): """ Add a new Scatterpolar trace The scatterpolar trace type encompasses line charts, scatter charts, text charts, and bubble charts in polar coordinates. The data visualized as scatter point or lines is set in `r` (radial) and `theta` (angular) coordinates Text (appearing either on the chart or on hover only) is via `text`. Bubble charts are achieved by setting `marker.size` and/or `marker.color` to numerical arrays. Parameters ---------- cliponaxis Determines whether or not markers and text nodes are clipped about the subplot axes. To show markers and text nodes above axis lines and tick labels, make sure to set `xaxis.layer` and `yaxis.layer` to *below traces*. connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dr Sets the r coordinate step. dtheta Sets the theta coordinate step. By default, the `dtheta` step equals the subplot's period divided by the length of the `r` coordinates. fill Sets the area to fill with a solid color. Use with `fillcolor` if not "none". scatterpolar has a subset of the options available to scatter. "toself" connects the endpoints of the trace (or each segment of the trace if it has gaps) into a closed shape. "tonext" fills the space between two traces if one completely encloses the other (eg consecutive contour lines), and behaves like "toself" if there is no trace before it. "tonext" should not be used if one trace does not enclose the other. fillcolor Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.scatterpolar.Hoverlabel instance or dict with compatible properties hoveron Do the hover effects highlight individual points (markers or line points) or do they highlight filled regions? If the fill is "toself" or "tonext" and there are no markers or text, then the default is "fills", otherwise it is "points". hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.scatterpolar.Line instance or dict with compatible properties marker plotly.graph_objects.scatterpolar.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . mode Determines the drawing mode for this scatter trace. If the provided `mode` includes "text" then the `text` elements appear at the coordinates. Otherwise, the `text` elements appear on hover. If there are less than 20 points and the trace is not stacked then the default is "lines+markers". Otherwise, "lines". name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. r Sets the radial coordinates r0 Alternate to `r`. Builds a linear space of r coordinates. Use with `dr` where `r0` is the starting coordinate and `dr` the step. rsrc Sets the source reference on plot.ly for r . selected plotly.graph_objects.scatterpolar.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.scatterpolar.Stream instance or dict with compatible properties subplot Sets a reference between this trace's data coordinates and a polar subplot. If "polar" (the default value), the data refer to `layout.polar`. If "polar2", the data refer to `layout.polar2`, and so on. text Sets text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the text font. textposition Sets the positions of the `text` elements with respects to the (x,y) coordinates. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `r`, `theta` and `text`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . theta Sets the angular coordinates theta0 Alternate to `theta`. Builds a linear space of theta coordinates. Use with `dtheta` where `theta0` is the starting coordinate and `dtheta` the step. thetasrc Sets the source reference on plot.ly for theta . thetaunit Sets the unit of input "theta" values. Has an effect only when on "linear" angular axes. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.scatterpolar.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- Figure """ new_trace = Scatterpolar( cliponaxis=cliponaxis, connectgaps=connectgaps, customdata=customdata, customdatasrc=customdatasrc, dr=dr, dtheta=dtheta, fill=fill, fillcolor=fillcolor, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hoveron=hoveron, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, legendgroup=legendgroup, line=line, marker=marker, meta=meta, metasrc=metasrc, mode=mode, name=name, opacity=opacity, r=r, r0=r0, rsrc=rsrc, selected=selected, selectedpoints=selectedpoints, showlegend=showlegend, stream=stream, subplot=subplot, text=text, textfont=textfont, textposition=textposition, textpositionsrc=textpositionsrc, textsrc=textsrc, texttemplate=texttemplate, texttemplatesrc=texttemplatesrc, theta=theta, theta0=theta0, thetasrc=thetasrc, thetaunit=thetaunit, uid=uid, uirevision=uirevision, unselected=unselected, visible=visible, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_scatterpolargl( self, connectgaps=None, customdata=None, customdatasrc=None, dr=None, dtheta=None, fill=None, fillcolor=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, legendgroup=None, line=None, marker=None, meta=None, metasrc=None, mode=None, name=None, opacity=None, r=None, r0=None, rsrc=None, selected=None, selectedpoints=None, showlegend=None, stream=None, subplot=None, text=None, textfont=None, textposition=None, textpositionsrc=None, textsrc=None, texttemplate=None, texttemplatesrc=None, theta=None, theta0=None, thetasrc=None, thetaunit=None, uid=None, uirevision=None, unselected=None, visible=None, row=None, col=None, **kwargs ): """ Add a new Scatterpolargl trace The scatterpolargl trace type encompasses line charts, scatter charts, and bubble charts in polar coordinates using the WebGL plotting engine. The data visualized as scatter point or lines is set in `r` (radial) and `theta` (angular) coordinates Bubble charts are achieved by setting `marker.size` and/or `marker.color` to numerical arrays. Parameters ---------- connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dr Sets the r coordinate step. dtheta Sets the theta coordinate step. By default, the `dtheta` step equals the subplot's period divided by the length of the `r` coordinates. fill Sets the area to fill with a solid color. Defaults to "none" unless this trace is stacked, then it gets "tonexty" ("tonextx") if `orientation` is "v" ("h") Use with `fillcolor` if not "none". "tozerox" and "tozeroy" fill to x=0 and y=0 respectively. "tonextx" and "tonexty" fill between the endpoints of this trace and the endpoints of the trace before it, connecting those endpoints with straight lines (to make a stacked area graph); if there is no trace before it, they behave like "tozerox" and "tozeroy". "toself" connects the endpoints of the trace (or each segment of the trace if it has gaps) into a closed shape. "tonext" fills the space between two traces if one completely encloses the other (eg consecutive contour lines), and behaves like "toself" if there is no trace before it. "tonext" should not be used if one trace does not enclose the other. Traces in a `stackgroup` will only fill to (or be filled to) other traces in the same group. With multiple `stackgroup`s or some traces stacked and some not, if fill-linked traces are not already consecutive, the later ones will be pushed down in the drawing order. fillcolor Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.scatterpolargl.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.scatterpolargl.Line instance or dict with compatible properties marker plotly.graph_objects.scatterpolargl.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . mode Determines the drawing mode for this scatter trace. If the provided `mode` includes "text" then the `text` elements appear at the coordinates. Otherwise, the `text` elements appear on hover. If there are less than 20 points and the trace is not stacked then the default is "lines+markers". Otherwise, "lines". name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. r Sets the radial coordinates r0 Alternate to `r`. Builds a linear space of r coordinates. Use with `dr` where `r0` is the starting coordinate and `dr` the step. rsrc Sets the source reference on plot.ly for r . selected plotly.graph_objects.scatterpolargl.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.scatterpolargl.Stream instance or dict with compatible properties subplot Sets a reference between this trace's data coordinates and a polar subplot. If "polar" (the default value), the data refer to `layout.polar`. If "polar2", the data refer to `layout.polar2`, and so on. text Sets text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the text font. textposition Sets the positions of the `text` elements with respects to the (x,y) coordinates. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `r`, `theta` and `text`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . theta Sets the angular coordinates theta0 Alternate to `theta`. Builds a linear space of theta coordinates. Use with `dtheta` where `theta0` is the starting coordinate and `dtheta` the step. thetasrc Sets the source reference on plot.ly for theta . thetaunit Sets the unit of input "theta" values. Has an effect only when on "linear" angular axes. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.scatterpolargl.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- Figure """ new_trace = Scatterpolargl( connectgaps=connectgaps, customdata=customdata, customdatasrc=customdatasrc, dr=dr, dtheta=dtheta, fill=fill, fillcolor=fillcolor, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, legendgroup=legendgroup, line=line, marker=marker, meta=meta, metasrc=metasrc, mode=mode, name=name, opacity=opacity, r=r, r0=r0, rsrc=rsrc, selected=selected, selectedpoints=selectedpoints, showlegend=showlegend, stream=stream, subplot=subplot, text=text, textfont=textfont, textposition=textposition, textpositionsrc=textpositionsrc, textsrc=textsrc, texttemplate=texttemplate, texttemplatesrc=texttemplatesrc, theta=theta, theta0=theta0, thetasrc=thetasrc, thetaunit=thetaunit, uid=uid, uirevision=uirevision, unselected=unselected, visible=visible, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_scatterternary( self, a=None, asrc=None, b=None, bsrc=None, c=None, cliponaxis=None, connectgaps=None, csrc=None, customdata=None, customdatasrc=None, fill=None, fillcolor=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hoveron=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, legendgroup=None, line=None, marker=None, meta=None, metasrc=None, mode=None, name=None, opacity=None, selected=None, selectedpoints=None, showlegend=None, stream=None, subplot=None, sum=None, text=None, textfont=None, textposition=None, textpositionsrc=None, textsrc=None, texttemplate=None, texttemplatesrc=None, uid=None, uirevision=None, unselected=None, visible=None, row=None, col=None, **kwargs ): """ Add a new Scatterternary trace Provides similar functionality to the "scatter" type but on a ternary phase diagram. The data is provided by at least two arrays out of `a`, `b`, `c` triplets. Parameters ---------- a Sets the quantity of component `a` in each data point. If `a`, `b`, and `c` are all provided, they need not be normalized, only the relative values matter. If only two arrays are provided they must be normalized to match `ternary.sum`. asrc Sets the source reference on plot.ly for a . b Sets the quantity of component `a` in each data point. If `a`, `b`, and `c` are all provided, they need not be normalized, only the relative values matter. If only two arrays are provided they must be normalized to match `ternary.sum`. bsrc Sets the source reference on plot.ly for b . c Sets the quantity of component `a` in each data point. If `a`, `b`, and `c` are all provided, they need not be normalized, only the relative values matter. If only two arrays are provided they must be normalized to match `ternary.sum`. cliponaxis Determines whether or not markers and text nodes are clipped about the subplot axes. To show markers and text nodes above axis lines and tick labels, make sure to set `xaxis.layer` and `yaxis.layer` to *below traces*. connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. csrc Sets the source reference on plot.ly for c . customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . fill Sets the area to fill with a solid color. Use with `fillcolor` if not "none". scatterternary has a subset of the options available to scatter. "toself" connects the endpoints of the trace (or each segment of the trace if it has gaps) into a closed shape. "tonext" fills the space between two traces if one completely encloses the other (eg consecutive contour lines), and behaves like "toself" if there is no trace before it. "tonext" should not be used if one trace does not enclose the other. fillcolor Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.scatterternary.Hoverlabel instance or dict with compatible properties hoveron Do the hover effects highlight individual points (markers or line points) or do they highlight filled regions? If the fill is "toself" or "tonext" and there are no markers or text, then the default is "fills", otherwise it is "points". hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (a,b,c) point. If a single string, the same string appears over all the data points. If an array of strings, the items are mapped in order to the the data points in (a,b,c). To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.scatterternary.Line instance or dict with compatible properties marker plotly.graph_objects.scatterternary.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . mode Determines the drawing mode for this scatter trace. If the provided `mode` includes "text" then the `text` elements appear at the coordinates. Otherwise, the `text` elements appear on hover. If there are less than 20 points and the trace is not stacked then the default is "lines+markers". Otherwise, "lines". name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. selected plotly.graph_objects.scatterternary.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.scatterternary.Stream instance or dict with compatible properties subplot Sets a reference between this trace's data coordinates and a ternary subplot. If "ternary" (the default value), the data refer to `layout.ternary`. If "ternary2", the data refer to `layout.ternary2`, and so on. sum The number each triplet should sum to, if only two of `a`, `b`, and `c` are provided. This overrides `ternary.sum` to normalize this specific trace, but does not affect the values displayed on the axes. 0 (or missing) means to use ternary.sum text Sets text elements associated with each (a,b,c) point. If a single string, the same string appears over all the data points. If an array of strings, the items are mapped in order to the the data points in (a,b,c). If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the text font. textposition Sets the positions of the `text` elements with respects to the (x,y) coordinates. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `a`, `b`, `c` and `text`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.scatterternary.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- Figure """ new_trace = Scatterternary( a=a, asrc=asrc, b=b, bsrc=bsrc, c=c, cliponaxis=cliponaxis, connectgaps=connectgaps, csrc=csrc, customdata=customdata, customdatasrc=customdatasrc, fill=fill, fillcolor=fillcolor, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hoveron=hoveron, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, legendgroup=legendgroup, line=line, marker=marker, meta=meta, metasrc=metasrc, mode=mode, name=name, opacity=opacity, selected=selected, selectedpoints=selectedpoints, showlegend=showlegend, stream=stream, subplot=subplot, sum=sum, text=text, textfont=textfont, textposition=textposition, textpositionsrc=textpositionsrc, textsrc=textsrc, texttemplate=texttemplate, texttemplatesrc=texttemplatesrc, uid=uid, uirevision=uirevision, unselected=unselected, visible=visible, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_splom( self, customdata=None, customdatasrc=None, diagonal=None, dimensions=None, dimensiondefaults=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, legendgroup=None, marker=None, meta=None, metasrc=None, name=None, opacity=None, selected=None, selectedpoints=None, showlegend=None, showlowerhalf=None, showupperhalf=None, stream=None, text=None, textsrc=None, uid=None, uirevision=None, unselected=None, visible=None, xaxes=None, yaxes=None, row=None, col=None, **kwargs ): """ Add a new Splom trace Splom traces generate scatter plot matrix visualizations. Each splom `dimensions` items correspond to a generated axis. Values for each of those dimensions are set in `dimensions[i].values`. Splom traces support all `scattergl` marker style attributes. Specify `layout.grid` attributes and/or layout x-axis and y-axis attributes for more control over the axis positioning and style. Parameters ---------- customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . diagonal plotly.graph_objects.splom.Diagonal instance or dict with compatible properties dimensions A tuple of plotly.graph_objects.splom.Dimension instances or dicts with compatible properties dimensiondefaults When used in a template (as layout.template.data.splom.dimensiondefaults), sets the default property values to use for elements of splom.dimensions hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.splom.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. marker plotly.graph_objects.splom.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. selected plotly.graph_objects.splom.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. showlowerhalf Determines whether or not subplots on the lower half from the diagonal are displayed. showupperhalf Determines whether or not subplots on the upper half from the diagonal are displayed. stream plotly.graph_objects.splom.Stream instance or dict with compatible properties text Sets text elements associated with each (x,y) pair to appear on hover. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.splom.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). xaxes Sets the list of x axes corresponding to dimensions of this splom trace. By default, a splom will match the first N xaxes where N is the number of input dimensions. Note that, in case where `diagonal.visible` is false and `showupperhalf` or `showlowerhalf` is false, this splom trace will generate one less x-axis and one less y-axis. yaxes Sets the list of y axes corresponding to dimensions of this splom trace. By default, a splom will match the first N yaxes where N is the number of input dimensions. Note that, in case where `diagonal.visible` is false and `showupperhalf` or `showlowerhalf` is false, this splom trace will generate one less x-axis and one less y-axis. row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- Figure """ new_trace = Splom( customdata=customdata, customdatasrc=customdatasrc, diagonal=diagonal, dimensions=dimensions, dimensiondefaults=dimensiondefaults, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, legendgroup=legendgroup, marker=marker, meta=meta, metasrc=metasrc, name=name, opacity=opacity, selected=selected, selectedpoints=selectedpoints, showlegend=showlegend, showlowerhalf=showlowerhalf, showupperhalf=showupperhalf, stream=stream, text=text, textsrc=textsrc, uid=uid, uirevision=uirevision, unselected=unselected, visible=visible, xaxes=xaxes, yaxes=yaxes, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_streamtube( self, autocolorscale=None, cauto=None, cmax=None, cmid=None, cmin=None, coloraxis=None, colorbar=None, colorscale=None, customdata=None, customdatasrc=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, ids=None, idssrc=None, lighting=None, lightposition=None, maxdisplayed=None, meta=None, metasrc=None, name=None, opacity=None, reversescale=None, scene=None, showscale=None, sizeref=None, starts=None, stream=None, text=None, u=None, uid=None, uirevision=None, usrc=None, v=None, visible=None, vsrc=None, w=None, wsrc=None, x=None, xsrc=None, y=None, ysrc=None, z=None, zsrc=None, row=None, col=None, **kwargs ): """ Add a new Streamtube trace Use a streamtube trace to visualize flow in a vector field. Specify a vector field using 6 1D arrays of equal length, 3 position arrays `x`, `y` and `z` and 3 vector component arrays `u`, `v`, and `w`. By default, the tubes' starting positions will be cut from the vector field's x-z plane at its minimum y value. To specify your own starting position, use attributes `starts.x`, `starts.y` and `starts.z`. The color is encoded by the norm of (u, v, w), and the local radius by the divergence of (u, v, w). Parameters ---------- autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here u/v/w norm) or the bounds set in `cmin` and `cmax` Defaults to `false` when `cmin` and `cmax` are set by the user. cmax Sets the upper bound of the color domain. Value should have the same units as u/v/w norm and if set, `cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `cmin` and/or `cmax` to be equidistant to this point. Value should have the same units as u/v/w norm. Has no effect when `cauto` is `false`. cmin Sets the lower bound of the color domain. Value should have the same units as u/v/w norm and if set, `cmax` must be set as well. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.streamtube.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`cmin` and `cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.streamtube.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `tubex`, `tubey`, `tubez`, `tubeu`, `tubev`, `tubew`, `norm` and `divergence`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . lighting plotly.graph_objects.streamtube.Lighting instance or dict with compatible properties lightposition plotly.graph_objects.streamtube.Lightposition instance or dict with compatible properties maxdisplayed The maximum number of displayed segments in a streamtube. meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the surface. Please note that in the case of using high `opacity` values for example a value greater than or equal to 0.5 on two surfaces (and 0.25 with four surfaces), an overlay of multiple transparent surfaces may not perfectly be sorted in depth by the webgl API. This behavior may be improved in the near future and is subject to change. reversescale Reverses the color mapping if true. If true, `cmin` will correspond to the last color in the array and `cmax` will correspond to the first color. scene Sets a reference between this trace's 3D coordinate system and a 3D scene. If "scene" (the default value), the (x,y,z) coordinates refer to `layout.scene`. If "scene2", the (x,y,z) coordinates refer to `layout.scene2`, and so on. showscale Determines whether or not a colorbar is displayed for this trace. sizeref The scaling factor for the streamtubes. The default is 1, which avoids two max divergence tubes from touching at adjacent starting positions. starts plotly.graph_objects.streamtube.Starts instance or dict with compatible properties stream plotly.graph_objects.streamtube.Stream instance or dict with compatible properties text Sets a text element associated with this trace. If trace `hoverinfo` contains a "text" flag, this text element will be seen in all hover labels. Note that streamtube traces do not support array `text` values. u Sets the x components of the vector field. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. usrc Sets the source reference on plot.ly for u . v Sets the y components of the vector field. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). vsrc Sets the source reference on plot.ly for v . w Sets the z components of the vector field. wsrc Sets the source reference on plot.ly for w . x Sets the x coordinates of the vector field. xsrc Sets the source reference on plot.ly for x . y Sets the y coordinates of the vector field. ysrc Sets the source reference on plot.ly for y . z Sets the z coordinates of the vector field. zsrc Sets the source reference on plot.ly for z . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- Figure """ new_trace = Streamtube( autocolorscale=autocolorscale, cauto=cauto, cmax=cmax, cmid=cmid, cmin=cmin, coloraxis=coloraxis, colorbar=colorbar, colorscale=colorscale, customdata=customdata, customdatasrc=customdatasrc, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, ids=ids, idssrc=idssrc, lighting=lighting, lightposition=lightposition, maxdisplayed=maxdisplayed, meta=meta, metasrc=metasrc, name=name, opacity=opacity, reversescale=reversescale, scene=scene, showscale=showscale, sizeref=sizeref, starts=starts, stream=stream, text=text, u=u, uid=uid, uirevision=uirevision, usrc=usrc, v=v, visible=visible, vsrc=vsrc, w=w, wsrc=wsrc, x=x, xsrc=xsrc, y=y, ysrc=ysrc, z=z, zsrc=zsrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_sunburst( self, branchvalues=None, count=None, customdata=None, customdatasrc=None, domain=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, insidetextfont=None, labels=None, labelssrc=None, leaf=None, level=None, marker=None, maxdepth=None, meta=None, metasrc=None, name=None, opacity=None, outsidetextfont=None, parents=None, parentssrc=None, stream=None, text=None, textfont=None, textinfo=None, textsrc=None, texttemplate=None, texttemplatesrc=None, uid=None, uirevision=None, values=None, valuessrc=None, visible=None, row=None, col=None, **kwargs ): """ Add a new Sunburst trace Visualize hierarchal data spanning outward radially from root to leaves. The sunburst sectors are determined by the entries in "labels" or "ids" and in "parents". Parameters ---------- branchvalues Determines how the items in `values` are summed. When set to "total", items in `values` are taken to be value of all its descendants. When set to "remainder", items in `values` corresponding to the root and the branches sectors are taken to be the extra part not part of the sum of the values at their leaves. count Determines default for `values` when it is not provided, by inferring a 1 for each of the "leaves" and/or "branches", otherwise 0. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . domain plotly.graph_objects.sunburst.Domain instance or dict with compatible properties hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.sunburst.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `currentPath`, `root`, `entry`, `percentRoot`, `percentEntry` and `percentParent`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each sector. If a single string, the same string appears for all data points. If an array of string, the items are mapped in order of this trace's sectors. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . insidetextfont Sets the font used for `textinfo` lying inside the sector. labels Sets the labels of each of the sectors. labelssrc Sets the source reference on plot.ly for labels . leaf plotly.graph_objects.sunburst.Leaf instance or dict with compatible properties level Sets the level from which this trace hierarchy is rendered. Set `level` to `''` to start from the root node in the hierarchy. Must be an "id" if `ids` is filled in, otherwise plotly attempts to find a matching item in `labels`. marker plotly.graph_objects.sunburst.Marker instance or dict with compatible properties maxdepth Sets the number of rendered sectors from any given `level`. Set `maxdepth` to "-1" to render all the levels in the hierarchy. meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. outsidetextfont Sets the font used for `textinfo` lying outside the sector. parents Sets the parent sectors for each of the sectors. Empty string items '' are understood to reference the root node in the hierarchy. If `ids` is filled, `parents` items are understood to be "ids" themselves. When `ids` is not set, plotly attempts to find matching items in `labels`, but beware they must be unique. parentssrc Sets the source reference on plot.ly for parents . stream plotly.graph_objects.sunburst.Stream instance or dict with compatible properties text Sets text elements associated with each sector. If trace `textinfo` contains a "text" flag, these elements will be seen on the chart. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the font used for `textinfo`. textinfo Determines which trace information appear on the graph. textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `currentPath`, `root`, `entry`, `percentRoot`, `percentEntry`, `percentParent`, `label` and `value`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. values Sets the values associated with each of the sectors. Use with `branchvalues` to determine how the values are summed. valuessrc Sets the source reference on plot.ly for values . visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- Figure """ new_trace = Sunburst( branchvalues=branchvalues, count=count, customdata=customdata, customdatasrc=customdatasrc, domain=domain, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, insidetextfont=insidetextfont, labels=labels, labelssrc=labelssrc, leaf=leaf, level=level, marker=marker, maxdepth=maxdepth, meta=meta, metasrc=metasrc, name=name, opacity=opacity, outsidetextfont=outsidetextfont, parents=parents, parentssrc=parentssrc, stream=stream, text=text, textfont=textfont, textinfo=textinfo, textsrc=textsrc, texttemplate=texttemplate, texttemplatesrc=texttemplatesrc, uid=uid, uirevision=uirevision, values=values, valuessrc=valuessrc, visible=visible, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_surface( self, autocolorscale=None, cauto=None, cmax=None, cmid=None, cmin=None, coloraxis=None, colorbar=None, colorscale=None, connectgaps=None, contours=None, customdata=None, customdatasrc=None, hidesurface=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, lighting=None, lightposition=None, meta=None, metasrc=None, name=None, opacity=None, reversescale=None, scene=None, showscale=None, stream=None, surfacecolor=None, surfacecolorsrc=None, text=None, textsrc=None, uid=None, uirevision=None, visible=None, x=None, xcalendar=None, xsrc=None, y=None, ycalendar=None, ysrc=None, z=None, zcalendar=None, zsrc=None, row=None, col=None, **kwargs ): """ Add a new Surface trace The data the describes the coordinates of the surface is set in `z`. Data in `z` should be a 2D list. Coordinates in `x` and `y` can either be 1D lists or 2D lists (e.g. to graph parametric surfaces). If not provided in `x` and `y`, the x and y coordinates are assumed to be linear starting at 0 with a unit step. The color scale corresponds to the `z` values by default. For custom color scales, use `surfacecolor` which should be a 2D list, where its bounds can be controlled using `cmin` and `cmax`. Parameters ---------- autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here z or surfacecolor) or the bounds set in `cmin` and `cmax` Defaults to `false` when `cmin` and `cmax` are set by the user. cmax Sets the upper bound of the color domain. Value should have the same units as z or surfacecolor and if set, `cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `cmin` and/or `cmax` to be equidistant to this point. Value should have the same units as z or surfacecolor. Has no effect when `cauto` is `false`. cmin Sets the lower bound of the color domain. Value should have the same units as z or surfacecolor and if set, `cmax` must be set as well. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.surface.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`cmin` and `cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the `z` data are filled in. contours plotly.graph_objects.surface.Contours instance or dict with compatible properties customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . hidesurface Determines whether or not a surface is drawn. For example, set `hidesurface` to False `contours.x.show` to True and `contours.y.show` to True to draw a wire frame plot. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.surface.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . lighting plotly.graph_objects.surface.Lighting instance or dict with compatible properties lightposition plotly.graph_objects.surface.Lightposition instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the surface. Please note that in the case of using high `opacity` values for example a value greater than or equal to 0.5 on two surfaces (and 0.25 with four surfaces), an overlay of multiple transparent surfaces may not perfectly be sorted in depth by the webgl API. This behavior may be improved in the near future and is subject to change. reversescale Reverses the color mapping if true. If true, `cmin` will correspond to the last color in the array and `cmax` will correspond to the first color. scene Sets a reference between this trace's 3D coordinate system and a 3D scene. If "scene" (the default value), the (x,y,z) coordinates refer to `layout.scene`. If "scene2", the (x,y,z) coordinates refer to `layout.scene2`, and so on. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.surface.Stream instance or dict with compatible properties surfacecolor Sets the surface color values, used for setting a color scale independent of `z`. surfacecolorsrc Sets the source reference on plot.ly for surfacecolor . text Sets the text elements associated with each z value. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the x coordinates. xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . y Sets the y coordinates. ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . z Sets the z coordinates. zcalendar Sets the calendar system to use with `z` date data. zsrc Sets the source reference on plot.ly for z . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- Figure """ new_trace = Surface( autocolorscale=autocolorscale, cauto=cauto, cmax=cmax, cmid=cmid, cmin=cmin, coloraxis=coloraxis, colorbar=colorbar, colorscale=colorscale, connectgaps=connectgaps, contours=contours, customdata=customdata, customdatasrc=customdatasrc, hidesurface=hidesurface, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, lighting=lighting, lightposition=lightposition, meta=meta, metasrc=metasrc, name=name, opacity=opacity, reversescale=reversescale, scene=scene, showscale=showscale, stream=stream, surfacecolor=surfacecolor, surfacecolorsrc=surfacecolorsrc, text=text, textsrc=textsrc, uid=uid, uirevision=uirevision, visible=visible, x=x, xcalendar=xcalendar, xsrc=xsrc, y=y, ycalendar=ycalendar, ysrc=ysrc, z=z, zcalendar=zcalendar, zsrc=zsrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_table( self, cells=None, columnorder=None, columnordersrc=None, columnwidth=None, columnwidthsrc=None, customdata=None, customdatasrc=None, domain=None, header=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, ids=None, idssrc=None, meta=None, metasrc=None, name=None, stream=None, uid=None, uirevision=None, visible=None, row=None, col=None, **kwargs ): """ Add a new Table trace Table view for detailed data viewing. The data are arranged in a grid of rows and columns. Most styling can be specified for columns, rows or individual cells. Table is using a column- major order, ie. the grid is represented as a vector of column vectors. Parameters ---------- cells plotly.graph_objects.table.Cells instance or dict with compatible properties columnorder Specifies the rendered order of the data columns; for example, a value `2` at position `0` means that column index `0` in the data will be rendered as the third column, as columns have an index base of zero. columnordersrc Sets the source reference on plot.ly for columnorder . columnwidth The width of columns expressed as a ratio. Columns fill the available width in proportion of their specified column widths. columnwidthsrc Sets the source reference on plot.ly for columnwidth . customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . domain plotly.graph_objects.table.Domain instance or dict with compatible properties header plotly.graph_objects.table.Header instance or dict with compatible properties hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.table.Hoverlabel instance or dict with compatible properties ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. stream plotly.graph_objects.table.Stream instance or dict with compatible properties uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- Figure """ new_trace = Table( cells=cells, columnorder=columnorder, columnordersrc=columnordersrc, columnwidth=columnwidth, columnwidthsrc=columnwidthsrc, customdata=customdata, customdatasrc=customdatasrc, domain=domain, header=header, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, ids=ids, idssrc=idssrc, meta=meta, metasrc=metasrc, name=name, stream=stream, uid=uid, uirevision=uirevision, visible=visible, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_treemap( self, branchvalues=None, count=None, customdata=None, customdatasrc=None, domain=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, insidetextfont=None, labels=None, labelssrc=None, level=None, marker=None, maxdepth=None, meta=None, metasrc=None, name=None, opacity=None, outsidetextfont=None, parents=None, parentssrc=None, pathbar=None, stream=None, text=None, textfont=None, textinfo=None, textposition=None, textsrc=None, texttemplate=None, texttemplatesrc=None, tiling=None, uid=None, uirevision=None, values=None, valuessrc=None, visible=None, row=None, col=None, **kwargs ): """ Add a new Treemap trace Visualize hierarchal data from leaves (and/or outer branches) towards root with rectangles. The treemap sectors are determined by the entries in "labels" or "ids" and in "parents". Parameters ---------- branchvalues Determines how the items in `values` are summed. When set to "total", items in `values` are taken to be value of all its descendants. When set to "remainder", items in `values` corresponding to the root and the branches sectors are taken to be the extra part not part of the sum of the values at their leaves. count Determines default for `values` when it is not provided, by inferring a 1 for each of the "leaves" and/or "branches", otherwise 0. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . domain plotly.graph_objects.treemap.Domain instance or dict with compatible properties hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.treemap.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `currentPath`, `root`, `entry`, `percentRoot`, `percentEntry` and `percentParent`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each sector. If a single string, the same string appears for all data points. If an array of string, the items are mapped in order of this trace's sectors. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . insidetextfont Sets the font used for `textinfo` lying inside the sector. labels Sets the labels of each of the sectors. labelssrc Sets the source reference on plot.ly for labels . level Sets the level from which this trace hierarchy is rendered. Set `level` to `''` to start from the root node in the hierarchy. Must be an "id" if `ids` is filled in, otherwise plotly attempts to find a matching item in `labels`. marker plotly.graph_objects.treemap.Marker instance or dict with compatible properties maxdepth Sets the number of rendered sectors from any given `level`. Set `maxdepth` to "-1" to render all the levels in the hierarchy. meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. outsidetextfont Sets the font used for `textinfo` lying outside the sector. parents Sets the parent sectors for each of the sectors. Empty string items '' are understood to reference the root node in the hierarchy. If `ids` is filled, `parents` items are understood to be "ids" themselves. When `ids` is not set, plotly attempts to find matching items in `labels`, but beware they must be unique. parentssrc Sets the source reference on plot.ly for parents . pathbar plotly.graph_objects.treemap.Pathbar instance or dict with compatible properties stream plotly.graph_objects.treemap.Stream instance or dict with compatible properties text Sets text elements associated with each sector. If trace `textinfo` contains a "text" flag, these elements will be seen on the chart. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the font used for `textinfo`. textinfo Determines which trace information appear on the graph. textposition Sets the positions of the `text` elements. textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `currentPath`, `root`, `entry`, `percentRoot`, `percentEntry`, `percentParent`, `label` and `value`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . tiling plotly.graph_objects.treemap.Tiling instance or dict with compatible properties uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. values Sets the values associated with each of the sectors. Use with `branchvalues` to determine how the values are summed. valuessrc Sets the source reference on plot.ly for values . visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- Figure """ new_trace = Treemap( branchvalues=branchvalues, count=count, customdata=customdata, customdatasrc=customdatasrc, domain=domain, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, insidetextfont=insidetextfont, labels=labels, labelssrc=labelssrc, level=level, marker=marker, maxdepth=maxdepth, meta=meta, metasrc=metasrc, name=name, opacity=opacity, outsidetextfont=outsidetextfont, parents=parents, parentssrc=parentssrc, pathbar=pathbar, stream=stream, text=text, textfont=textfont, textinfo=textinfo, textposition=textposition, textsrc=textsrc, texttemplate=texttemplate, texttemplatesrc=texttemplatesrc, tiling=tiling, uid=uid, uirevision=uirevision, values=values, valuessrc=valuessrc, visible=visible, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_violin( self, alignmentgroup=None, bandwidth=None, box=None, customdata=None, customdatasrc=None, fillcolor=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hoveron=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, jitter=None, legendgroup=None, line=None, marker=None, meanline=None, meta=None, metasrc=None, name=None, offsetgroup=None, opacity=None, orientation=None, pointpos=None, points=None, scalegroup=None, scalemode=None, selected=None, selectedpoints=None, showlegend=None, side=None, span=None, spanmode=None, stream=None, text=None, textsrc=None, uid=None, uirevision=None, unselected=None, visible=None, width=None, x=None, x0=None, xaxis=None, xsrc=None, y=None, y0=None, yaxis=None, ysrc=None, row=None, col=None, secondary_y=None, **kwargs ): """ Add a new Violin trace In vertical (horizontal) violin plots, statistics are computed using `y` (`x`) values. By supplying an `x` (`y`) array, one violin per distinct x (y) value is drawn If no `x` (`y`) list is provided, a single violin is drawn. That violin position is then positioned with with `name` or with `x0` (`y0`) if provided. Parameters ---------- alignmentgroup Set several traces linked to the same position axis or matching axes to the same alignmentgroup. This controls whether bars compute their positional range dependently or independently. bandwidth Sets the bandwidth used to compute the kernel density estimate. By default, the bandwidth is determined by Silverman's rule of thumb. box plotly.graph_objects.violin.Box instance or dict with compatible properties customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . fillcolor Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.violin.Hoverlabel instance or dict with compatible properties hoveron Do the hover effects highlight individual violins or sample points or the kernel density estimate or any combination of them? hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . jitter Sets the amount of jitter in the sample points drawn. If 0, the sample points align along the distribution axis. If 1, the sample points are drawn in a random jitter of width equal to the width of the violins. legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.violin.Line instance or dict with compatible properties marker plotly.graph_objects.violin.Marker instance or dict with compatible properties meanline plotly.graph_objects.violin.Meanline instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. For violin traces, the name will also be used for the position coordinate, if `x` and `x0` (`y` and `y0` if horizontal) are missing and the position axis is categorical. Note that the trace name is also used as a default value for attribute `scalegroup` (please see its description for details). offsetgroup Set several traces linked to the same position axis or matching axes to the same offsetgroup where bars of the same position coordinate will line up. opacity Sets the opacity of the trace. orientation Sets the orientation of the violin(s). If "v" ("h"), the distribution is visualized along the vertical (horizontal). pointpos Sets the position of the sample points in relation to the violins. If 0, the sample points are places over the center of the violins. Positive (negative) values correspond to positions to the right (left) for vertical violins and above (below) for horizontal violins. points If "outliers", only the sample points lying outside the whiskers are shown If "suspectedoutliers", the outlier points are shown and points either less than 4*Q1-3*Q3 or greater than 4*Q3-3*Q1 are highlighted (see `outliercolor`) If "all", all sample points are shown If False, only the violins are shown with no sample points scalegroup If there are multiple violins that should be sized according to to some metric (see `scalemode`), link them by providing a non-empty group id here shared by every trace in the same group. If a violin's `width` is undefined, `scalegroup` will default to the trace's name. In this case, violins with the same names will be linked together scalemode Sets the metric by which the width of each violin is determined."width" means each violin has the same (max) width*count* means the violins are scaled by the number of sample points makingup each violin. selected plotly.graph_objects.violin.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. side Determines on which side of the position value the density function making up one half of a violin is plotted. Useful when comparing two violin traces under "overlay" mode, where one trace has `side` set to "positive" and the other to "negative". span Sets the span in data space for which the density function will be computed. Has an effect only when `spanmode` is set to "manual". spanmode Sets the method by which the span in data space where the density function will be computed. "soft" means the span goes from the sample's minimum value minus two bandwidths to the sample's maximum value plus two bandwidths. "hard" means the span goes from the sample's minimum to its maximum value. For custom span settings, use mode "manual" and fill in the `span` attribute. stream plotly.graph_objects.violin.Stream instance or dict with compatible properties text Sets the text elements associated with each sample value. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.violin.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). width Sets the width of the violin in data coordinates. If 0 (default value) the width is automatically selected based on the positions of other violin traces in the same subplot. x Sets the x sample data or coordinates. See overview for more info. x0 Sets the x coordinate of the box. See overview for more info. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xsrc Sets the source reference on plot.ly for x . y Sets the y sample data or coordinates. See overview for more info. y0 Sets the y coordinate of the box. See overview for more info. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ysrc Sets the source reference on plot.ly for y . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` secondary_y: boolean or None (default None) If True, associate this trace with the secondary y-axis of the subplot at the specified row and col. Only valid if all of the following conditions are satisfied: * The figure was created using `plotly.subplots.make_subplots`. * The row and col arguments are not None * The subplot at the specified row and col has type xy (which is the default) and secondary_y True. These properties are specified in the specs argument to make_subplots. See the make_subplots docstring for more info. Returns ------- Figure """ new_trace = Violin( alignmentgroup=alignmentgroup, bandwidth=bandwidth, box=box, customdata=customdata, customdatasrc=customdatasrc, fillcolor=fillcolor, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hoveron=hoveron, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, jitter=jitter, legendgroup=legendgroup, line=line, marker=marker, meanline=meanline, meta=meta, metasrc=metasrc, name=name, offsetgroup=offsetgroup, opacity=opacity, orientation=orientation, pointpos=pointpos, points=points, scalegroup=scalegroup, scalemode=scalemode, selected=selected, selectedpoints=selectedpoints, showlegend=showlegend, side=side, span=span, spanmode=spanmode, stream=stream, text=text, textsrc=textsrc, uid=uid, uirevision=uirevision, unselected=unselected, visible=visible, width=width, x=x, x0=x0, xaxis=xaxis, xsrc=xsrc, y=y, y0=y0, yaxis=yaxis, ysrc=ysrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) def add_volume( self, autocolorscale=None, caps=None, cauto=None, cmax=None, cmid=None, cmin=None, coloraxis=None, colorbar=None, colorscale=None, contour=None, customdata=None, customdatasrc=None, flatshading=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, isomax=None, isomin=None, lighting=None, lightposition=None, meta=None, metasrc=None, name=None, opacity=None, opacityscale=None, reversescale=None, scene=None, showscale=None, slices=None, spaceframe=None, stream=None, surface=None, text=None, textsrc=None, uid=None, uirevision=None, value=None, valuesrc=None, visible=None, x=None, xsrc=None, y=None, ysrc=None, z=None, zsrc=None, row=None, col=None, **kwargs ): """ Add a new Volume trace Draws volume trace between iso-min and iso-max values with coordinates given by four 1-dimensional arrays containing the `value`, `x`, `y` and `z` of every vertex of a uniform or non- uniform 3-D grid. Horizontal or vertical slices, caps as well as spaceframe between iso-min and iso-max values could also be drawn using this trace. Parameters ---------- autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. caps plotly.graph_objects.volume.Caps instance or dict with compatible properties cauto Determines whether or not the color domain is computed with respect to the input data (here `value`) or the bounds set in `cmin` and `cmax` Defaults to `false` when `cmin` and `cmax` are set by the user. cmax Sets the upper bound of the color domain. Value should have the same units as `value` and if set, `cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `cmin` and/or `cmax` to be equidistant to this point. Value should have the same units as `value`. Has no effect when `cauto` is `false`. cmin Sets the lower bound of the color domain. Value should have the same units as `value` and if set, `cmax` must be set as well. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.volume.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`cmin` and `cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. contour plotly.graph_objects.volume.Contour instance or dict with compatible properties customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . flatshading Determines whether or not normal smoothing is applied to the meshes, creating meshes with an angular, low- poly look via flat reflections. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.volume.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . isomax Sets the maximum boundary for iso-surface plot. isomin Sets the minimum boundary for iso-surface plot. lighting plotly.graph_objects.volume.Lighting instance or dict with compatible properties lightposition plotly.graph_objects.volume.Lightposition instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the surface. Please note that in the case of using high `opacity` values for example a value greater than or equal to 0.5 on two surfaces (and 0.25 with four surfaces), an overlay of multiple transparent surfaces may not perfectly be sorted in depth by the webgl API. This behavior may be improved in the near future and is subject to change. opacityscale Sets the opacityscale. The opacityscale must be an array containing arrays mapping a normalized value to an opacity value. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 1], [0.5, 0.2], [1, 1]]` means that higher/lower values would have higher opacity values and those in the middle would be more transparent Alternatively, `opacityscale` may be a palette name string of the following list: 'min', 'max', 'extremes' and 'uniform'. The default is 'uniform'. reversescale Reverses the color mapping if true. If true, `cmin` will correspond to the last color in the array and `cmax` will correspond to the first color. scene Sets a reference between this trace's 3D coordinate system and a 3D scene. If "scene" (the default value), the (x,y,z) coordinates refer to `layout.scene`. If "scene2", the (x,y,z) coordinates refer to `layout.scene2`, and so on. showscale Determines whether or not a colorbar is displayed for this trace. slices plotly.graph_objects.volume.Slices instance or dict with compatible properties spaceframe plotly.graph_objects.volume.Spaceframe instance or dict with compatible properties stream plotly.graph_objects.volume.Stream instance or dict with compatible properties surface plotly.graph_objects.volume.Surface instance or dict with compatible properties text Sets the text elements associated with the vertices. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. value Sets the 4th dimension (value) of the vertices. valuesrc Sets the source reference on plot.ly for value . visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the X coordinates of the vertices on X axis. xsrc Sets the source reference on plot.ly for x . y Sets the Y coordinates of the vertices on Y axis. ysrc Sets the source reference on plot.ly for y . z Sets the Z coordinates of the vertices on Z axis. zsrc Sets the source reference on plot.ly for z . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- Figure """ new_trace = Volume( autocolorscale=autocolorscale, caps=caps, cauto=cauto, cmax=cmax, cmid=cmid, cmin=cmin, coloraxis=coloraxis, colorbar=colorbar, colorscale=colorscale, contour=contour, customdata=customdata, customdatasrc=customdatasrc, flatshading=flatshading, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, isomax=isomax, isomin=isomin, lighting=lighting, lightposition=lightposition, meta=meta, metasrc=metasrc, name=name, opacity=opacity, opacityscale=opacityscale, reversescale=reversescale, scene=scene, showscale=showscale, slices=slices, spaceframe=spaceframe, stream=stream, surface=surface, text=text, textsrc=textsrc, uid=uid, uirevision=uirevision, value=value, valuesrc=valuesrc, visible=visible, x=x, xsrc=xsrc, y=y, ysrc=ysrc, z=z, zsrc=zsrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_waterfall( self, alignmentgroup=None, base=None, cliponaxis=None, connector=None, constraintext=None, customdata=None, customdatasrc=None, decreasing=None, dx=None, dy=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, increasing=None, insidetextanchor=None, insidetextfont=None, legendgroup=None, measure=None, measuresrc=None, meta=None, metasrc=None, name=None, offset=None, offsetgroup=None, offsetsrc=None, opacity=None, orientation=None, outsidetextfont=None, selectedpoints=None, showlegend=None, stream=None, text=None, textangle=None, textfont=None, textinfo=None, textposition=None, textpositionsrc=None, textsrc=None, texttemplate=None, texttemplatesrc=None, totals=None, uid=None, uirevision=None, visible=None, width=None, widthsrc=None, x=None, x0=None, xaxis=None, xsrc=None, y=None, y0=None, yaxis=None, ysrc=None, row=None, col=None, secondary_y=None, **kwargs ): """ Add a new Waterfall trace Draws waterfall trace which is useful graph to displays the contribution of various elements (either positive or negative) in a bar chart. The data visualized by the span of the bars is set in `y` if `orientation` is set th "v" (the default) and the labels are set in `x`. By setting `orientation` to "h", the roles are interchanged. Parameters ---------- alignmentgroup Set several traces linked to the same position axis or matching axes to the same alignmentgroup. This controls whether bars compute their positional range dependently or independently. base Sets where the bar base is drawn (in position axis units). cliponaxis Determines whether the text nodes are clipped about the subplot axes. To show the text nodes above axis lines and tick labels, make sure to set `xaxis.layer` and `yaxis.layer` to *below traces*. connector plotly.graph_objects.waterfall.Connector instance or dict with compatible properties constraintext Constrain the size of text inside or outside a bar to be no larger than the bar itself. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . decreasing plotly.graph_objects.waterfall.Decreasing instance or dict with compatible properties dx Sets the x coordinate step. See `x0` for more info. dy Sets the y coordinate step. See `y0` for more info. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.waterfall.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `initial`, `delta` and `final`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . increasing plotly.graph_objects.waterfall.Increasing instance or dict with compatible properties insidetextanchor Determines if texts are kept at center or start/end points in `textposition` "inside" mode. insidetextfont Sets the font used for `text` lying inside the bar. legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. measure An array containing types of values. By default the values are considered as 'relative'. However; it is possible to use 'total' to compute the sums. Also 'absolute' could be applied to reset the computed total or to declare an initial value where needed. measuresrc Sets the source reference on plot.ly for measure . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. offset Shifts the position where the bar is drawn (in position axis units). In "group" barmode, traces that set "offset" will be excluded and drawn in "overlay" mode instead. offsetgroup Set several traces linked to the same position axis or matching axes to the same offsetgroup where bars of the same position coordinate will line up. offsetsrc Sets the source reference on plot.ly for offset . opacity Sets the opacity of the trace. orientation Sets the orientation of the bars. With "v" ("h"), the value of the each bar spans along the vertical (horizontal). outsidetextfont Sets the font used for `text` lying outside the bar. selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.waterfall.Stream instance or dict with compatible properties text Sets text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textangle Sets the angle of the tick labels with respect to the bar. For example, a `tickangle` of -90 draws the tick labels vertically. With "auto" the texts may automatically be rotated to fit with the maximum size in bars. textfont Sets the font used for `text`. textinfo Determines which trace information appear on the graph. In the case of having multiple waterfalls, totals are computed separately (per trace). textposition Specifies the location of the `text`. "inside" positions `text` inside, next to the bar end (rotated and scaled if needed). "outside" positions `text` outside, next to the bar end (scaled if needed), unless there is another bar stacked on this one, then the text gets pushed inside. "auto" tries to position `text` inside the bar, but if the bar is too small and no bar is stacked on this one the text is moved outside. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `initial`, `delta`, `final` and `label`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . totals plotly.graph_objects.waterfall.Totals instance or dict with compatible properties uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). width Sets the bar width (in position axis units). widthsrc Sets the source reference on plot.ly for width . x Sets the x coordinates. x0 Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xsrc Sets the source reference on plot.ly for x . y Sets the y coordinates. y0 Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ysrc Sets the source reference on plot.ly for y . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` secondary_y: boolean or None (default None) If True, associate this trace with the secondary y-axis of the subplot at the specified row and col. Only valid if all of the following conditions are satisfied: * The figure was created using `plotly.subplots.make_subplots`. * The row and col arguments are not None * The subplot at the specified row and col has type xy (which is the default) and secondary_y True. These properties are specified in the specs argument to make_subplots. See the make_subplots docstring for more info. Returns ------- Figure """ new_trace = Waterfall( alignmentgroup=alignmentgroup, base=base, cliponaxis=cliponaxis, connector=connector, constraintext=constraintext, customdata=customdata, customdatasrc=customdatasrc, decreasing=decreasing, dx=dx, dy=dy, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, increasing=increasing, insidetextanchor=insidetextanchor, insidetextfont=insidetextfont, legendgroup=legendgroup, measure=measure, measuresrc=measuresrc, meta=meta, metasrc=metasrc, name=name, offset=offset, offsetgroup=offsetgroup, offsetsrc=offsetsrc, opacity=opacity, orientation=orientation, outsidetextfont=outsidetextfont, selectedpoints=selectedpoints, showlegend=showlegend, stream=stream, text=text, textangle=textangle, textfont=textfont, textinfo=textinfo, textposition=textposition, textpositionsrc=textpositionsrc, textsrc=textsrc, texttemplate=texttemplate, texttemplatesrc=texttemplatesrc, totals=totals, uid=uid, uirevision=uirevision, visible=visible, width=width, widthsrc=widthsrc, x=x, x0=x0, xaxis=xaxis, xsrc=xsrc, y=y, y0=y0, yaxis=yaxis, ysrc=ysrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) def select_coloraxes(self, selector=None, row=None, col=None): """ Select coloraxis subplot objects from a particular subplot cell and/or coloraxis subplot objects that satisfy custom selection criteria. Parameters ---------- selector: dict or None (default None) Dict to use as selection criteria. coloraxis objects will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all coloraxis objects are selected. row, col: int or None (default None) Subplot row and column index of coloraxis objects to select. To select coloraxis objects by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all coloraxis objects are selected. Returns ------- generator Generator that iterates through all of the coloraxis objects that satisfy all of the specified selection criteria """ return self._select_layout_subplots_by_prefix("coloraxis", selector, row, col) def for_each_coloraxis(self, fn, selector=None, row=None, col=None): """ Apply a function to all coloraxis objects that satisfy the specified selection criteria Parameters ---------- fn: Function that inputs a single coloraxis object. selector: dict or None (default None) Dict to use as selection criteria. coloraxis objects will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all coloraxis objects are selected. row, col: int or None (default None) Subplot row and column index of coloraxis objects to select. To select coloraxis objects by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all coloraxis objects are selected. Returns ------- self Returns the Figure object that the method was called on """ for obj in self.select_coloraxes(selector=selector, row=row, col=col): fn(obj) return self def update_coloraxes( self, patch=None, selector=None, overwrite=False, row=None, col=None, **kwargs ): """ Perform a property update operation on all coloraxis objects that satisfy the specified selection criteria Parameters ---------- patch: dict Dictionary of property updates to be applied to all coloraxis objects that satisfy the selection criteria. selector: dict or None (default None) Dict to use as selection criteria. coloraxis objects will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all coloraxis objects are selected. overwrite: bool If True, overwrite existing properties. If False, apply updates to existing properties recursively, preserving existing properties that are not specified in the update operation. row, col: int or None (default None) Subplot row and column index of coloraxis objects to select. To select coloraxis objects by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all coloraxis objects are selected. **kwargs Additional property updates to apply to each selected coloraxis object. If a property is specified in both patch and in **kwargs then the one in **kwargs takes precedence. Returns ------- self Returns the Figure object that the method was called on """ for obj in self.select_coloraxes(selector=selector, row=row, col=col): obj.update(patch, overwrite=overwrite, **kwargs) return self def select_geos(self, selector=None, row=None, col=None): """ Select geo subplot objects from a particular subplot cell and/or geo subplot objects that satisfy custom selection criteria. Parameters ---------- selector: dict or None (default None) Dict to use as selection criteria. geo objects will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all geo objects are selected. row, col: int or None (default None) Subplot row and column index of geo objects to select. To select geo objects by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all geo objects are selected. Returns ------- generator Generator that iterates through all of the geo objects that satisfy all of the specified selection criteria """ return self._select_layout_subplots_by_prefix("geo", selector, row, col) def for_each_geo(self, fn, selector=None, row=None, col=None): """ Apply a function to all geo objects that satisfy the specified selection criteria Parameters ---------- fn: Function that inputs a single geo object. selector: dict or None (default None) Dict to use as selection criteria. geo objects will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all geo objects are selected. row, col: int or None (default None) Subplot row and column index of geo objects to select. To select geo objects by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all geo objects are selected. Returns ------- self Returns the Figure object that the method was called on """ for obj in self.select_geos(selector=selector, row=row, col=col): fn(obj) return self def update_geos( self, patch=None, selector=None, overwrite=False, row=None, col=None, **kwargs ): """ Perform a property update operation on all geo objects that satisfy the specified selection criteria Parameters ---------- patch: dict Dictionary of property updates to be applied to all geo objects that satisfy the selection criteria. selector: dict or None (default None) Dict to use as selection criteria. geo objects will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all geo objects are selected. overwrite: bool If True, overwrite existing properties. If False, apply updates to existing properties recursively, preserving existing properties that are not specified in the update operation. row, col: int or None (default None) Subplot row and column index of geo objects to select. To select geo objects by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all geo objects are selected. **kwargs Additional property updates to apply to each selected geo object. If a property is specified in both patch and in **kwargs then the one in **kwargs takes precedence. Returns ------- self Returns the Figure object that the method was called on """ for obj in self.select_geos(selector=selector, row=row, col=col): obj.update(patch, overwrite=overwrite, **kwargs) return self def select_mapboxes(self, selector=None, row=None, col=None): """ Select mapbox subplot objects from a particular subplot cell and/or mapbox subplot objects that satisfy custom selection criteria. Parameters ---------- selector: dict or None (default None) Dict to use as selection criteria. mapbox objects will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all mapbox objects are selected. row, col: int or None (default None) Subplot row and column index of mapbox objects to select. To select mapbox objects by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all mapbox objects are selected. Returns ------- generator Generator that iterates through all of the mapbox objects that satisfy all of the specified selection criteria """ return self._select_layout_subplots_by_prefix("mapbox", selector, row, col) def for_each_mapbox(self, fn, selector=None, row=None, col=None): """ Apply a function to all mapbox objects that satisfy the specified selection criteria Parameters ---------- fn: Function that inputs a single mapbox object. selector: dict or None (default None) Dict to use as selection criteria. mapbox objects will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all mapbox objects are selected. row, col: int or None (default None) Subplot row and column index of mapbox objects to select. To select mapbox objects by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all mapbox objects are selected. Returns ------- self Returns the Figure object that the method was called on """ for obj in self.select_mapboxes(selector=selector, row=row, col=col): fn(obj) return self def update_mapboxes( self, patch=None, selector=None, overwrite=False, row=None, col=None, **kwargs ): """ Perform a property update operation on all mapbox objects that satisfy the specified selection criteria Parameters ---------- patch: dict Dictionary of property updates to be applied to all mapbox objects that satisfy the selection criteria. selector: dict or None (default None) Dict to use as selection criteria. mapbox objects will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all mapbox objects are selected. overwrite: bool If True, overwrite existing properties. If False, apply updates to existing properties recursively, preserving existing properties that are not specified in the update operation. row, col: int or None (default None) Subplot row and column index of mapbox objects to select. To select mapbox objects by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all mapbox objects are selected. **kwargs Additional property updates to apply to each selected mapbox object. If a property is specified in both patch and in **kwargs then the one in **kwargs takes precedence. Returns ------- self Returns the Figure object that the method was called on """ for obj in self.select_mapboxes(selector=selector, row=row, col=col): obj.update(patch, overwrite=overwrite, **kwargs) return self def select_polars(self, selector=None, row=None, col=None): """ Select polar subplot objects from a particular subplot cell and/or polar subplot objects that satisfy custom selection criteria. Parameters ---------- selector: dict or None (default None) Dict to use as selection criteria. polar objects will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all polar objects are selected. row, col: int or None (default None) Subplot row and column index of polar objects to select. To select polar objects by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all polar objects are selected. Returns ------- generator Generator that iterates through all of the polar objects that satisfy all of the specified selection criteria """ return self._select_layout_subplots_by_prefix("polar", selector, row, col) def for_each_polar(self, fn, selector=None, row=None, col=None): """ Apply a function to all polar objects that satisfy the specified selection criteria Parameters ---------- fn: Function that inputs a single polar object. selector: dict or None (default None) Dict to use as selection criteria. polar objects will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all polar objects are selected. row, col: int or None (default None) Subplot row and column index of polar objects to select. To select polar objects by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all polar objects are selected. Returns ------- self Returns the Figure object that the method was called on """ for obj in self.select_polars(selector=selector, row=row, col=col): fn(obj) return self def update_polars( self, patch=None, selector=None, overwrite=False, row=None, col=None, **kwargs ): """ Perform a property update operation on all polar objects that satisfy the specified selection criteria Parameters ---------- patch: dict Dictionary of property updates to be applied to all polar objects that satisfy the selection criteria. selector: dict or None (default None) Dict to use as selection criteria. polar objects will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all polar objects are selected. overwrite: bool If True, overwrite existing properties. If False, apply updates to existing properties recursively, preserving existing properties that are not specified in the update operation. row, col: int or None (default None) Subplot row and column index of polar objects to select. To select polar objects by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all polar objects are selected. **kwargs Additional property updates to apply to each selected polar object. If a property is specified in both patch and in **kwargs then the one in **kwargs takes precedence. Returns ------- self Returns the Figure object that the method was called on """ for obj in self.select_polars(selector=selector, row=row, col=col): obj.update(patch, overwrite=overwrite, **kwargs) return self def select_scenes(self, selector=None, row=None, col=None): """ Select scene subplot objects from a particular subplot cell and/or scene subplot objects that satisfy custom selection criteria. Parameters ---------- selector: dict or None (default None) Dict to use as selection criteria. scene objects will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all scene objects are selected. row, col: int or None (default None) Subplot row and column index of scene objects to select. To select scene objects by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all scene objects are selected. Returns ------- generator Generator that iterates through all of the scene objects that satisfy all of the specified selection criteria """ return self._select_layout_subplots_by_prefix("scene", selector, row, col) def for_each_scene(self, fn, selector=None, row=None, col=None): """ Apply a function to all scene objects that satisfy the specified selection criteria Parameters ---------- fn: Function that inputs a single scene object. selector: dict or None (default None) Dict to use as selection criteria. scene objects will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all scene objects are selected. row, col: int or None (default None) Subplot row and column index of scene objects to select. To select scene objects by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all scene objects are selected. Returns ------- self Returns the Figure object that the method was called on """ for obj in self.select_scenes(selector=selector, row=row, col=col): fn(obj) return self def update_scenes( self, patch=None, selector=None, overwrite=False, row=None, col=None, **kwargs ): """ Perform a property update operation on all scene objects that satisfy the specified selection criteria Parameters ---------- patch: dict Dictionary of property updates to be applied to all scene objects that satisfy the selection criteria. selector: dict or None (default None) Dict to use as selection criteria. scene objects will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all scene objects are selected. overwrite: bool If True, overwrite existing properties. If False, apply updates to existing properties recursively, preserving existing properties that are not specified in the update operation. row, col: int or None (default None) Subplot row and column index of scene objects to select. To select scene objects by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all scene objects are selected. **kwargs Additional property updates to apply to each selected scene object. If a property is specified in both patch and in **kwargs then the one in **kwargs takes precedence. Returns ------- self Returns the Figure object that the method was called on """ for obj in self.select_scenes(selector=selector, row=row, col=col): obj.update(patch, overwrite=overwrite, **kwargs) return self def select_ternaries(self, selector=None, row=None, col=None): """ Select ternary subplot objects from a particular subplot cell and/or ternary subplot objects that satisfy custom selection criteria. Parameters ---------- selector: dict or None (default None) Dict to use as selection criteria. ternary objects will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all ternary objects are selected. row, col: int or None (default None) Subplot row and column index of ternary objects to select. To select ternary objects by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all ternary objects are selected. Returns ------- generator Generator that iterates through all of the ternary objects that satisfy all of the specified selection criteria """ return self._select_layout_subplots_by_prefix("ternary", selector, row, col) def for_each_ternary(self, fn, selector=None, row=None, col=None): """ Apply a function to all ternary objects that satisfy the specified selection criteria Parameters ---------- fn: Function that inputs a single ternary object. selector: dict or None (default None) Dict to use as selection criteria. ternary objects will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all ternary objects are selected. row, col: int or None (default None) Subplot row and column index of ternary objects to select. To select ternary objects by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all ternary objects are selected. Returns ------- self Returns the Figure object that the method was called on """ for obj in self.select_ternaries(selector=selector, row=row, col=col): fn(obj) return self def update_ternaries( self, patch=None, selector=None, overwrite=False, row=None, col=None, **kwargs ): """ Perform a property update operation on all ternary objects that satisfy the specified selection criteria Parameters ---------- patch: dict Dictionary of property updates to be applied to all ternary objects that satisfy the selection criteria. selector: dict or None (default None) Dict to use as selection criteria. ternary objects will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all ternary objects are selected. overwrite: bool If True, overwrite existing properties. If False, apply updates to existing properties recursively, preserving existing properties that are not specified in the update operation. row, col: int or None (default None) Subplot row and column index of ternary objects to select. To select ternary objects by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all ternary objects are selected. **kwargs Additional property updates to apply to each selected ternary object. If a property is specified in both patch and in **kwargs then the one in **kwargs takes precedence. Returns ------- self Returns the Figure object that the method was called on """ for obj in self.select_ternaries(selector=selector, row=row, col=col): obj.update(patch, overwrite=overwrite, **kwargs) return self def select_xaxes(self, selector=None, row=None, col=None): """ Select xaxis subplot objects from a particular subplot cell and/or xaxis subplot objects that satisfy custom selection criteria. Parameters ---------- selector: dict or None (default None) Dict to use as selection criteria. xaxis objects will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all xaxis objects are selected. row, col: int or None (default None) Subplot row and column index of xaxis objects to select. To select xaxis objects by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all xaxis objects are selected. Returns ------- generator Generator that iterates through all of the xaxis objects that satisfy all of the specified selection criteria """ return self._select_layout_subplots_by_prefix("xaxis", selector, row, col) def for_each_xaxis(self, fn, selector=None, row=None, col=None): """ Apply a function to all xaxis objects that satisfy the specified selection criteria Parameters ---------- fn: Function that inputs a single xaxis object. selector: dict or None (default None) Dict to use as selection criteria. xaxis objects will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all xaxis objects are selected. row, col: int or None (default None) Subplot row and column index of xaxis objects to select. To select xaxis objects by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all xaxis objects are selected. Returns ------- self Returns the Figure object that the method was called on """ for obj in self.select_xaxes(selector=selector, row=row, col=col): fn(obj) return self def update_xaxes( self, patch=None, selector=None, overwrite=False, row=None, col=None, **kwargs ): """ Perform a property update operation on all xaxis objects that satisfy the specified selection criteria Parameters ---------- patch: dict Dictionary of property updates to be applied to all xaxis objects that satisfy the selection criteria. selector: dict or None (default None) Dict to use as selection criteria. xaxis objects will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all xaxis objects are selected. overwrite: bool If True, overwrite existing properties. If False, apply updates to existing properties recursively, preserving existing properties that are not specified in the update operation. row, col: int or None (default None) Subplot row and column index of xaxis objects to select. To select xaxis objects by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all xaxis objects are selected. **kwargs Additional property updates to apply to each selected xaxis object. If a property is specified in both patch and in **kwargs then the one in **kwargs takes precedence. Returns ------- self Returns the Figure object that the method was called on """ for obj in self.select_xaxes(selector=selector, row=row, col=col): obj.update(patch, overwrite=overwrite, **kwargs) return self def select_yaxes(self, selector=None, row=None, col=None, secondary_y=None): """ Select yaxis subplot objects from a particular subplot cell and/or yaxis subplot objects that satisfy custom selection criteria. Parameters ---------- selector: dict or None (default None) Dict to use as selection criteria. yaxis objects will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all yaxis objects are selected. row, col: int or None (default None) Subplot row and column index of yaxis objects to select. To select yaxis objects by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all yaxis objects are selected. secondary_y: boolean or None (default None) * If True, only select yaxis objects associated with the secondary y-axis of the subplot. * If False, only select yaxis objects associated with the primary y-axis of the subplot. * If None (the default), do not filter yaxis objects based on a secondary y-axis condition. To select yaxis objects by secondary y-axis, the Figure must have been created using plotly.subplots.make_subplots. See the docstring for the specs argument to make_subplots for more info on creating subplots with secondary y-axes. Returns ------- generator Generator that iterates through all of the yaxis objects that satisfy all of the specified selection criteria """ return self._select_layout_subplots_by_prefix( "yaxis", selector, row, col, secondary_y=secondary_y ) def for_each_yaxis(self, fn, selector=None, row=None, col=None, secondary_y=None): """ Apply a function to all yaxis objects that satisfy the specified selection criteria Parameters ---------- fn: Function that inputs a single yaxis object. selector: dict or None (default None) Dict to use as selection criteria. yaxis objects will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all yaxis objects are selected. row, col: int or None (default None) Subplot row and column index of yaxis objects to select. To select yaxis objects by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all yaxis objects are selected. secondary_y: boolean or None (default None) * If True, only select yaxis objects associated with the secondary y-axis of the subplot. * If False, only select yaxis objects associated with the primary y-axis of the subplot. * If None (the default), do not filter yaxis objects based on a secondary y-axis condition. To select yaxis objects by secondary y-axis, the Figure must have been created using plotly.subplots.make_subplots. See the docstring for the specs argument to make_subplots for more info on creating subplots with secondary y-axes. Returns ------- self Returns the Figure object that the method was called on """ for obj in self.select_yaxes( selector=selector, row=row, col=col, secondary_y=secondary_y ): fn(obj) return self def update_yaxes( self, patch=None, selector=None, overwrite=False, row=None, col=None, secondary_y=None, **kwargs ): """ Perform a property update operation on all yaxis objects that satisfy the specified selection criteria Parameters ---------- patch: dict Dictionary of property updates to be applied to all yaxis objects that satisfy the selection criteria. selector: dict or None (default None) Dict to use as selection criteria. yaxis objects will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all yaxis objects are selected. overwrite: bool If True, overwrite existing properties. If False, apply updates to existing properties recursively, preserving existing properties that are not specified in the update operation. row, col: int or None (default None) Subplot row and column index of yaxis objects to select. To select yaxis objects by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all yaxis objects are selected. secondary_y: boolean or None (default None) * If True, only select yaxis objects associated with the secondary y-axis of the subplot. * If False, only select yaxis objects associated with the primary y-axis of the subplot. * If None (the default), do not filter yaxis objects based on a secondary y-axis condition. To select yaxis objects by secondary y-axis, the Figure must have been created using plotly.subplots.make_subplots. See the docstring for the specs argument to make_subplots for more info on creating subplots with secondary y-axes. **kwargs Additional property updates to apply to each selected yaxis object. If a property is specified in both patch and in **kwargs then the one in **kwargs takes precedence. Returns ------- self Returns the Figure object that the method was called on """ for obj in self.select_yaxes( selector=selector, row=row, col=col, secondary_y=secondary_y ): obj.update(patch, overwrite=overwrite, **kwargs) return self def select_annotations(self, selector=None, row=None, col=None, secondary_y=None): """ Select annotations from a particular subplot cell and/or annotations that satisfy custom selection criteria. Parameters ---------- selector: dict or None (default None) Dict to use as selection criteria. Annotations will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all annotations are selected. row, col: int or None (default None) Subplot row and column index of annotations to select. To select annotations by row and column, the Figure must have been created using plotly.subplots.make_subplots. To select only those annotation that are in paper coordinates, set row and col to the string 'paper'. If None (the default), all annotations are selected. secondary_y: boolean or None (default None) * If True, only select annotations associated with the secondary y-axis of the subplot. * If False, only select annotations associated with the primary y-axis of the subplot. * If None (the default), do not filter annotations based on secondary y-axis. To select annotations by secondary y-axis, the Figure must have been created using plotly.subplots.make_subplots. See the docstring for the specs argument to make_subplots for more info on creating subplots with secondary y-axes. Returns ------- generator Generator that iterates through all of the annotations that satisfy all of the specified selection criteria """ return self._select_annotations_like( "annotations", selector=selector, row=row, col=col, secondary_y=secondary_y ) def for_each_annotation( self, fn, selector=None, row=None, col=None, secondary_y=None ): """ Apply a function to all annotations that satisfy the specified selection criteria Parameters ---------- fn: Function that inputs a single annotation object. selector: dict or None (default None) Dict to use as selection criteria. Traces will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all annotations are selected. row, col: int or None (default None) Subplot row and column index of annotations to select. To select annotations by row and column, the Figure must have been created using plotly.subplots.make_subplots. To select only those annotations that are in paper coordinates, set row and col to the string 'paper'. If None (the default), all annotations are selected. secondary_y: boolean or None (default None) * If True, only select annotations associated with the secondary y-axis of the subplot. * If False, only select annotations associated with the primary y-axis of the subplot. * If None (the default), do not filter annotations based on secondary y-axis. To select annotations by secondary y-axis, the Figure must have been created using plotly.subplots.make_subplots. See the docstring for the specs argument to make_subplots for more info on creating subplots with secondary y-axes. Returns ------- self Returns the Figure object that the method was called on """ for obj in self._select_annotations_like( prop="annotations", selector=selector, row=row, col=col, secondary_y=secondary_y, ): fn(obj) return self def update_annotations( self, patch, selector=None, row=None, col=None, secondary_y=None, **kwargs ): """ Perform a property update operation on all annotations that satisfy the specified selection criteria Parameters ---------- patch: dict or None (default None) Dictionary of property updates to be applied to all annotations that satisfy the selection criteria. selector: dict or None (default None) Dict to use as selection criteria. Traces will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all annotations are selected. row, col: int or None (default None) Subplot row and column index of annotations to select. To select annotations by row and column, the Figure must have been created using plotly.subplots.make_subplots. To select only those annotation that are in paper coordinates, set row and col to the string 'paper'. If None (the default), all annotations are selected. secondary_y: boolean or None (default None) * If True, only select annotations associated with the secondary y-axis of the subplot. * If False, only select annotations associated with the primary y-axis of the subplot. * If None (the default), do not filter annotations based on secondary y-axis. To select annotations by secondary y-axis, the Figure must have been created using plotly.subplots.make_subplots. See the docstring for the specs argument to make_subplots for more info on creating subplots with secondary y-axes. **kwargs Additional property updates to apply to each selected annotation. If a property is specified in both patch and in **kwargs then the one in **kwargs takes precedence. Returns ------- self Returns the Figure object that the method was called on """ for obj in self._select_annotations_like( prop="annotations", selector=selector, row=row, col=col, secondary_y=secondary_y, ): obj.update(patch, **kwargs) return self def add_annotation( self, arg=None, align=None, arrowcolor=None, arrowhead=None, arrowside=None, arrowsize=None, arrowwidth=None, ax=None, axref=None, ay=None, ayref=None, bgcolor=None, bordercolor=None, borderpad=None, borderwidth=None, captureevents=None, clicktoshow=None, font=None, height=None, hoverlabel=None, hovertext=None, name=None, opacity=None, showarrow=None, standoff=None, startarrowhead=None, startarrowsize=None, startstandoff=None, templateitemname=None, text=None, textangle=None, valign=None, visible=None, width=None, x=None, xanchor=None, xclick=None, xref=None, xshift=None, y=None, yanchor=None, yclick=None, yref=None, yshift=None, row=None, col=None, secondary_y=None, **kwargs ): """ Create and add a new annotation to the figure's layout Parameters ---------- arg instance of Annotation or dict with compatible properties align Sets the horizontal alignment of the `text` within the box. Has an effect only if `text` spans more two or more lines (i.e. `text` contains one or more
HTML tags) or if an explicit width is set to override the text width. arrowcolor Sets the color of the annotation arrow. arrowhead Sets the end annotation arrow head style. arrowside Sets the annotation arrow head position. arrowsize Sets the size of the end annotation arrow head, relative to `arrowwidth`. A value of 1 (default) gives a head about 3x as wide as the line. arrowwidth Sets the width (in px) of annotation arrow line. ax Sets the x component of the arrow tail about the arrow head. If `axref` is `pixel`, a positive (negative) component corresponds to an arrow pointing from right to left (left to right). If `axref` is an axis, this is an absolute value on that axis, like `x`, NOT a relative value. axref Indicates in what terms the tail of the annotation (ax,ay) is specified. If `pixel`, `ax` is a relative offset in pixels from `x`. If set to an x axis id (e.g. "x" or "x2"), `ax` is specified in the same terms as that axis. This is useful for trendline annotations which should continue to indicate the correct trend when zoomed. ay Sets the y component of the arrow tail about the arrow head. If `ayref` is `pixel`, a positive (negative) component corresponds to an arrow pointing from bottom to top (top to bottom). If `ayref` is an axis, this is an absolute value on that axis, like `y`, NOT a relative value. ayref Indicates in what terms the tail of the annotation (ax,ay) is specified. If `pixel`, `ay` is a relative offset in pixels from `y`. If set to a y axis id (e.g. "y" or "y2"), `ay` is specified in the same terms as that axis. This is useful for trendline annotations which should continue to indicate the correct trend when zoomed. bgcolor Sets the background color of the annotation. bordercolor Sets the color of the border enclosing the annotation `text`. borderpad Sets the padding (in px) between the `text` and the enclosing border. borderwidth Sets the width (in px) of the border enclosing the annotation `text`. captureevents Determines whether the annotation text box captures mouse move and click events, or allows those events to pass through to data points in the plot that may be behind the annotation. By default `captureevents` is False unless `hovertext` is provided. If you use the event `plotly_clickannotation` without `hovertext` you must explicitly enable `captureevents`. clicktoshow Makes this annotation respond to clicks on the plot. If you click a data point that exactly matches the `x` and `y` values of this annotation, and it is hidden (visible: false), it will appear. In "onoff" mode, you must click the same point again to make it disappear, so if you click multiple points, you can show multiple annotations. In "onout" mode, a click anywhere else in the plot (on another data point or not) will hide this annotation. If you need to show/hide this annotation in response to different `x` or `y` values, you can set `xclick` and/or `yclick`. This is useful for example to label the side of a bar. To label markers though, `standoff` is preferred over `xclick` and `yclick`. font Sets the annotation text font. height Sets an explicit height for the text box. null (default) lets the text set the box height. Taller text will be clipped. hoverlabel plotly.graph_objects.layout.annotation.Hoverlabel instance or dict with compatible properties hovertext Sets text to appear when hovering over this annotation. If omitted or blank, no hover label will appear. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. opacity Sets the opacity of the annotation (text + arrow). showarrow Determines whether or not the annotation is drawn with an arrow. If True, `text` is placed near the arrow's tail. If False, `text` lines up with the `x` and `y` provided. standoff Sets a distance, in pixels, to move the end arrowhead away from the position it is pointing at, for example to point at the edge of a marker independent of zoom. Note that this shortens the arrow from the `ax` / `ay` vector, in contrast to `xshift` / `yshift` which moves everything by this amount. startarrowhead Sets the start annotation arrow head style. startarrowsize Sets the size of the start annotation arrow head, relative to `arrowwidth`. A value of 1 (default) gives a head about 3x as wide as the line. startstandoff Sets a distance, in pixels, to move the start arrowhead away from the position it is pointing at, for example to point at the edge of a marker independent of zoom. Note that this shortens the arrow from the `ax` / `ay` vector, in contrast to `xshift` / `yshift` which moves everything by this amount. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. text Sets the text associated with this annotation. Plotly uses a subset of HTML tags to do things like newline (
), bold (), italics (), hyperlinks (). Tags , , are also supported. textangle Sets the angle at which the `text` is drawn with respect to the horizontal. valign Sets the vertical alignment of the `text` within the box. Has an effect only if an explicit height is set to override the text height. visible Determines whether or not this annotation is visible. width Sets an explicit width for the text box. null (default) lets the text set the box width. Wider text will be clipped. There is no automatic wrapping; use
to start a new line. x Sets the annotation's x position. If the axis `type` is "log", then you must take the log of your desired range. If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. xanchor Sets the text box's horizontal position anchor This anchor binds the `x` position to the "left", "center" or "right" of the annotation. For example, if `x` is set to 1, `xref` to "paper" and `xanchor` to "right" then the right-most portion of the annotation lines up with the right-most edge of the plotting area. If "auto", the anchor is equivalent to "center" for data- referenced annotations or if there is an arrow, whereas for paper-referenced with no arrow, the anchor picked corresponds to the closest side. xclick Toggle this annotation when clicking a data point whose `x` value is `xclick` rather than the annotation's `x` value. xref Sets the annotation's x coordinate axis. If set to an x axis id (e.g. "x" or "x2"), the `x` position refers to an x coordinate If set to "paper", the `x` position refers to the distance from the left side of the plotting area in normalized coordinates where 0 (1) corresponds to the left (right) side. xshift Shifts the position of the whole annotation and arrow to the right (positive) or left (negative) by this many pixels. y Sets the annotation's y position. If the axis `type` is "log", then you must take the log of your desired range. If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. yanchor Sets the text box's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the annotation. For example, if `y` is set to 1, `yref` to "paper" and `yanchor` to "top" then the top-most portion of the annotation lines up with the top-most edge of the plotting area. If "auto", the anchor is equivalent to "middle" for data-referenced annotations or if there is an arrow, whereas for paper- referenced with no arrow, the anchor picked corresponds to the closest side. yclick Toggle this annotation when clicking a data point whose `y` value is `yclick` rather than the annotation's `y` value. yref Sets the annotation's y coordinate axis. If set to an y axis id (e.g. "y" or "y2"), the `y` position refers to an y coordinate If set to "paper", the `y` position refers to the distance from the bottom of the plotting area in normalized coordinates where 0 (1) corresponds to the bottom (top). yshift Shifts the position of the whole annotation and arrow up (positive) or down (negative) by this many pixels. row Subplot row for annotation col Subplot column for annotation secondary_y Whether to add annotation to secondary y-axis Returns ------- Figure """ new_obj = _layout.Annotation( arg, align=align, arrowcolor=arrowcolor, arrowhead=arrowhead, arrowside=arrowside, arrowsize=arrowsize, arrowwidth=arrowwidth, ax=ax, axref=axref, ay=ay, ayref=ayref, bgcolor=bgcolor, bordercolor=bordercolor, borderpad=borderpad, borderwidth=borderwidth, captureevents=captureevents, clicktoshow=clicktoshow, font=font, height=height, hoverlabel=hoverlabel, hovertext=hovertext, name=name, opacity=opacity, showarrow=showarrow, standoff=standoff, startarrowhead=startarrowhead, startarrowsize=startarrowsize, startstandoff=startstandoff, templateitemname=templateitemname, text=text, textangle=textangle, valign=valign, visible=visible, width=width, x=x, xanchor=xanchor, xclick=xclick, xref=xref, xshift=xshift, y=y, yanchor=yanchor, yclick=yclick, yref=yref, yshift=yshift, **kwargs ) return self._add_annotation_like( "annotation", "annotations", new_obj, row=row, col=col, secondary_y=secondary_y, ) def select_layout_images(self, selector=None, row=None, col=None, secondary_y=None): """ Select images from a particular subplot cell and/or images that satisfy custom selection criteria. Parameters ---------- selector: dict or None (default None) Dict to use as selection criteria. Annotations will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all images are selected. row, col: int or None (default None) Subplot row and column index of images to select. To select images by row and column, the Figure must have been created using plotly.subplots.make_subplots. To select only those image that are in paper coordinates, set row and col to the string 'paper'. If None (the default), all images are selected. secondary_y: boolean or None (default None) * If True, only select images associated with the secondary y-axis of the subplot. * If False, only select images associated with the primary y-axis of the subplot. * If None (the default), do not filter images based on secondary y-axis. To select images by secondary y-axis, the Figure must have been created using plotly.subplots.make_subplots. See the docstring for the specs argument to make_subplots for more info on creating subplots with secondary y-axes. Returns ------- generator Generator that iterates through all of the images that satisfy all of the specified selection criteria """ return self._select_annotations_like( "images", selector=selector, row=row, col=col, secondary_y=secondary_y ) def for_each_layout_image( self, fn, selector=None, row=None, col=None, secondary_y=None ): """ Apply a function to all images that satisfy the specified selection criteria Parameters ---------- fn: Function that inputs a single image object. selector: dict or None (default None) Dict to use as selection criteria. Traces will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all images are selected. row, col: int or None (default None) Subplot row and column index of images to select. To select images by row and column, the Figure must have been created using plotly.subplots.make_subplots. To select only those images that are in paper coordinates, set row and col to the string 'paper'. If None (the default), all images are selected. secondary_y: boolean or None (default None) * If True, only select images associated with the secondary y-axis of the subplot. * If False, only select images associated with the primary y-axis of the subplot. * If None (the default), do not filter images based on secondary y-axis. To select images by secondary y-axis, the Figure must have been created using plotly.subplots.make_subplots. See the docstring for the specs argument to make_subplots for more info on creating subplots with secondary y-axes. Returns ------- self Returns the Figure object that the method was called on """ for obj in self._select_annotations_like( prop="images", selector=selector, row=row, col=col, secondary_y=secondary_y, ): fn(obj) return self def update_layout_images( self, patch, selector=None, row=None, col=None, secondary_y=None, **kwargs ): """ Perform a property update operation on all images that satisfy the specified selection criteria Parameters ---------- patch: dict or None (default None) Dictionary of property updates to be applied to all images that satisfy the selection criteria. selector: dict or None (default None) Dict to use as selection criteria. Traces will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all images are selected. row, col: int or None (default None) Subplot row and column index of images to select. To select images by row and column, the Figure must have been created using plotly.subplots.make_subplots. To select only those image that are in paper coordinates, set row and col to the string 'paper'. If None (the default), all images are selected. secondary_y: boolean or None (default None) * If True, only select images associated with the secondary y-axis of the subplot. * If False, only select images associated with the primary y-axis of the subplot. * If None (the default), do not filter images based on secondary y-axis. To select images by secondary y-axis, the Figure must have been created using plotly.subplots.make_subplots. See the docstring for the specs argument to make_subplots for more info on creating subplots with secondary y-axes. **kwargs Additional property updates to apply to each selected image. If a property is specified in both patch and in **kwargs then the one in **kwargs takes precedence. Returns ------- self Returns the Figure object that the method was called on """ for obj in self._select_annotations_like( prop="images", selector=selector, row=row, col=col, secondary_y=secondary_y, ): obj.update(patch, **kwargs) return self def add_layout_image( self, arg=None, layer=None, name=None, opacity=None, sizex=None, sizey=None, sizing=None, source=None, templateitemname=None, visible=None, x=None, xanchor=None, xref=None, y=None, yanchor=None, yref=None, row=None, col=None, secondary_y=None, **kwargs ): """ Create and add a new image to the figure's layout Parameters ---------- arg instance of Image or dict with compatible properties layer Specifies whether images are drawn below or above traces. When `xref` and `yref` are both set to `paper`, image is drawn below the entire plot area. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. opacity Sets the opacity of the image. sizex Sets the image container size horizontally. The image will be sized based on the `position` value. When `xref` is set to `paper`, units are sized relative to the plot width. sizey Sets the image container size vertically. The image will be sized based on the `position` value. When `yref` is set to `paper`, units are sized relative to the plot height. sizing Specifies which dimension of the image to constrain. source Specifies the URL of the image to be used. The URL must be accessible from the domain where the plot code is run, and can be either relative or absolute. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. visible Determines whether or not this image is visible. x Sets the image's x position. When `xref` is set to `paper`, units are sized relative to the plot height. See `xref` for more info xanchor Sets the anchor for the x position xref Sets the images's x coordinate axis. If set to a x axis id (e.g. "x" or "x2"), the `x` position refers to an x data coordinate If set to "paper", the `x` position refers to the distance from the left of plot in normalized coordinates where 0 (1) corresponds to the left (right). y Sets the image's y position. When `yref` is set to `paper`, units are sized relative to the plot height. See `yref` for more info yanchor Sets the anchor for the y position. yref Sets the images's y coordinate axis. If set to a y axis id (e.g. "y" or "y2"), the `y` position refers to a y data coordinate. If set to "paper", the `y` position refers to the distance from the bottom of the plot in normalized coordinates where 0 (1) corresponds to the bottom (top). row Subplot row for image col Subplot column for image secondary_y Whether to add image to secondary y-axis Returns ------- Figure """ new_obj = _layout.Image( arg, layer=layer, name=name, opacity=opacity, sizex=sizex, sizey=sizey, sizing=sizing, source=source, templateitemname=templateitemname, visible=visible, x=x, xanchor=xanchor, xref=xref, y=y, yanchor=yanchor, yref=yref, **kwargs ) return self._add_annotation_like( "image", "images", new_obj, row=row, col=col, secondary_y=secondary_y, ) def select_shapes(self, selector=None, row=None, col=None, secondary_y=None): """ Select shapes from a particular subplot cell and/or shapes that satisfy custom selection criteria. Parameters ---------- selector: dict or None (default None) Dict to use as selection criteria. Annotations will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all shapes are selected. row, col: int or None (default None) Subplot row and column index of shapes to select. To select shapes by row and column, the Figure must have been created using plotly.subplots.make_subplots. To select only those shape that are in paper coordinates, set row and col to the string 'paper'. If None (the default), all shapes are selected. secondary_y: boolean or None (default None) * If True, only select shapes associated with the secondary y-axis of the subplot. * If False, only select shapes associated with the primary y-axis of the subplot. * If None (the default), do not filter shapes based on secondary y-axis. To select shapes by secondary y-axis, the Figure must have been created using plotly.subplots.make_subplots. See the docstring for the specs argument to make_subplots for more info on creating subplots with secondary y-axes. Returns ------- generator Generator that iterates through all of the shapes that satisfy all of the specified selection criteria """ return self._select_annotations_like( "shapes", selector=selector, row=row, col=col, secondary_y=secondary_y ) def for_each_shape(self, fn, selector=None, row=None, col=None, secondary_y=None): """ Apply a function to all shapes that satisfy the specified selection criteria Parameters ---------- fn: Function that inputs a single shape object. selector: dict or None (default None) Dict to use as selection criteria. Traces will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all shapes are selected. row, col: int or None (default None) Subplot row and column index of shapes to select. To select shapes by row and column, the Figure must have been created using plotly.subplots.make_subplots. To select only those shapes that are in paper coordinates, set row and col to the string 'paper'. If None (the default), all shapes are selected. secondary_y: boolean or None (default None) * If True, only select shapes associated with the secondary y-axis of the subplot. * If False, only select shapes associated with the primary y-axis of the subplot. * If None (the default), do not filter shapes based on secondary y-axis. To select shapes by secondary y-axis, the Figure must have been created using plotly.subplots.make_subplots. See the docstring for the specs argument to make_subplots for more info on creating subplots with secondary y-axes. Returns ------- self Returns the Figure object that the method was called on """ for obj in self._select_annotations_like( prop="shapes", selector=selector, row=row, col=col, secondary_y=secondary_y, ): fn(obj) return self def update_shapes( self, patch, selector=None, row=None, col=None, secondary_y=None, **kwargs ): """ Perform a property update operation on all shapes that satisfy the specified selection criteria Parameters ---------- patch: dict or None (default None) Dictionary of property updates to be applied to all shapes that satisfy the selection criteria. selector: dict or None (default None) Dict to use as selection criteria. Traces will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all shapes are selected. row, col: int or None (default None) Subplot row and column index of shapes to select. To select shapes by row and column, the Figure must have been created using plotly.subplots.make_subplots. To select only those shape that are in paper coordinates, set row and col to the string 'paper'. If None (the default), all shapes are selected. secondary_y: boolean or None (default None) * If True, only select shapes associated with the secondary y-axis of the subplot. * If False, only select shapes associated with the primary y-axis of the subplot. * If None (the default), do not filter shapes based on secondary y-axis. To select shapes by secondary y-axis, the Figure must have been created using plotly.subplots.make_subplots. See the docstring for the specs argument to make_subplots for more info on creating subplots with secondary y-axes. **kwargs Additional property updates to apply to each selected shape. If a property is specified in both patch and in **kwargs then the one in **kwargs takes precedence. Returns ------- self Returns the Figure object that the method was called on """ for obj in self._select_annotations_like( prop="shapes", selector=selector, row=row, col=col, secondary_y=secondary_y, ): obj.update(patch, **kwargs) return self def add_shape( self, arg=None, fillcolor=None, layer=None, line=None, name=None, opacity=None, path=None, templateitemname=None, type=None, visible=None, x0=None, x1=None, xanchor=None, xref=None, xsizemode=None, y0=None, y1=None, yanchor=None, yref=None, ysizemode=None, row=None, col=None, secondary_y=None, **kwargs ): """ Create and add a new shape to the figure's layout Parameters ---------- arg instance of Shape or dict with compatible properties fillcolor Sets the color filling the shape's interior. layer Specifies whether shapes are drawn below or above traces. line plotly.graph_objects.layout.shape.Line instance or dict with compatible properties name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. opacity Sets the opacity of the shape. path For `type` "path" - a valid SVG path with the pixel values replaced by data values in `xsizemode`/`ysizemode` being "scaled" and taken unmodified as pixels relative to `xanchor` and `yanchor` in case of "pixel" size mode. There are a few restrictions / quirks only absolute instructions, not relative. So the allowed segments are: M, L, H, V, Q, C, T, S, and Z arcs (A) are not allowed because radius rx and ry are relative. In the future we could consider supporting relative commands, but we would have to decide on how to handle date and log axes. Note that even as is, Q and C Bezier paths that are smooth on linear axes may not be smooth on log, and vice versa. no chained "polybezier" commands - specify the segment type for each one. On category axes, values are numbers scaled to the serial numbers of categories because using the categories themselves there would be no way to describe fractional positions On data axes: because space and T are both normal components of path strings, we can't use either to separate date from time parts. Therefore we'll use underscore for this purpose: 2015-02-21_13:45:56.789 templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. type Specifies the shape type to be drawn. If "line", a line is drawn from (`x0`,`y0`) to (`x1`,`y1`) with respect to the axes' sizing mode. If "circle", a circle is drawn from ((`x0`+`x1`)/2, (`y0`+`y1`)/2)) with radius (|(`x0`+`x1`)/2 - `x0`|, |(`y0`+`y1`)/2 -`y0`)|) with respect to the axes' sizing mode. If "rect", a rectangle is drawn linking (`x0`,`y0`), (`x1`,`y0`), (`x1`,`y1`), (`x0`,`y1`), (`x0`,`y0`) with respect to the axes' sizing mode. If "path", draw a custom SVG path using `path`. with respect to the axes' sizing mode. visible Determines whether or not this shape is visible. x0 Sets the shape's starting x position. See `type` and `xsizemode` for more info. x1 Sets the shape's end x position. See `type` and `xsizemode` for more info. xanchor Only relevant in conjunction with `xsizemode` set to "pixel". Specifies the anchor point on the x axis to which `x0`, `x1` and x coordinates within `path` are relative to. E.g. useful to attach a pixel sized shape to a certain data value. No effect when `xsizemode` not set to "pixel". xref Sets the shape's x coordinate axis. If set to an x axis id (e.g. "x" or "x2"), the `x` position refers to an x coordinate. If set to "paper", the `x` position refers to the distance from the left side of the plotting area in normalized coordinates where 0 (1) corresponds to the left (right) side. If the axis `type` is "log", then you must take the log of your desired range. If the axis `type` is "date", then you must convert the date to unix time in milliseconds. xsizemode Sets the shapes's sizing mode along the x axis. If set to "scaled", `x0`, `x1` and x coordinates within `path` refer to data values on the x axis or a fraction of the plot area's width (`xref` set to "paper"). If set to "pixel", `xanchor` specifies the x position in terms of data or plot fraction but `x0`, `x1` and x coordinates within `path` are pixels relative to `xanchor`. This way, the shape can have a fixed width while maintaining a position relative to data or plot fraction. y0 Sets the shape's starting y position. See `type` and `ysizemode` for more info. y1 Sets the shape's end y position. See `type` and `ysizemode` for more info. yanchor Only relevant in conjunction with `ysizemode` set to "pixel". Specifies the anchor point on the y axis to which `y0`, `y1` and y coordinates within `path` are relative to. E.g. useful to attach a pixel sized shape to a certain data value. No effect when `ysizemode` not set to "pixel". yref Sets the annotation's y coordinate axis. If set to an y axis id (e.g. "y" or "y2"), the `y` position refers to an y coordinate If set to "paper", the `y` position refers to the distance from the bottom of the plotting area in normalized coordinates where 0 (1) corresponds to the bottom (top). ysizemode Sets the shapes's sizing mode along the y axis. If set to "scaled", `y0`, `y1` and y coordinates within `path` refer to data values on the y axis or a fraction of the plot area's height (`yref` set to "paper"). If set to "pixel", `yanchor` specifies the y position in terms of data or plot fraction but `y0`, `y1` and y coordinates within `path` are pixels relative to `yanchor`. This way, the shape can have a fixed height while maintaining a position relative to data or plot fraction. row Subplot row for shape col Subplot column for shape secondary_y Whether to add shape to secondary y-axis Returns ------- Figure """ new_obj = _layout.Shape( arg, fillcolor=fillcolor, layer=layer, line=line, name=name, opacity=opacity, path=path, templateitemname=templateitemname, type=type, visible=visible, x0=x0, x1=x1, xanchor=xanchor, xref=xref, xsizemode=xsizemode, y0=y0, y1=y1, yanchor=yanchor, yref=yref, ysizemode=ysizemode, **kwargs ) return self._add_annotation_like( "shape", "shapes", new_obj, row=row, col=col, secondary_y=secondary_y, ) plotly-4.4.1+dfsg.orig/plotly/graph_objs/indicator/0000755000175000017500000000000013573746613021705 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/indicator/title/0000755000175000017500000000000013573746613023026 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/indicator/title/__init__.py0000644000175000017500000002031413573721547025136 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "indicator.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Set the font used to display the title Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.indicator.title.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.indicator.title.Font constructor must be a dict or an instance of plotly.graph_objs.indicator.title.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.indicator.title import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/indicator/gauge/0000755000175000017500000000000013573746613022775 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/indicator/gauge/bar/0000755000175000017500000000000013573746613023541 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/indicator/gauge/bar/__init__.py0000644000175000017500000001332413573721546025653 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the color of the line enclosing each sector. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # width # ----- @property def width(self): """ Sets the width (in px) of the line enclosing each sector. The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "indicator.gauge.bar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the color of the line enclosing each sector. width Sets the width (in px) of the line enclosing each sector. """ def __init__(self, arg=None, color=None, width=None, **kwargs): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.indicator.gauge.bar.Line color Sets the color of the line enclosing each sector. width Sets the width (in px) of the line enclosing each sector. Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.indicator.gauge.bar.Line constructor must be a dict or an instance of plotly.graph_objs.indicator.gauge.bar.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.indicator.gauge.bar import line as v_line # Initialize validators # --------------------- self._validators["color"] = v_line.ColorValidator() self._validators["width"] = v_line.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Line"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/indicator/gauge/axis/0000755000175000017500000000000013573746613023741 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/indicator/gauge/axis/__init__.py0000644000175000017500000004350613573721547026061 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickformatstop(_BaseTraceHierarchyType): # dtickrange # ---------- @property def dtickrange(self): """ range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" The 'dtickrange' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'dtickrange[0]' property accepts values of any type (1) The 'dtickrange[1]' property accepts values of any type Returns ------- list """ return self["dtickrange"] @dtickrange.setter def dtickrange(self, val): self["dtickrange"] = val # enabled # ------- @property def enabled(self): """ Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. The 'enabled' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["enabled"] @enabled.setter def enabled(self, val): self["enabled"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # value # ----- @property def value(self): """ string - dtickformat for described zoom level, the same as "tickformat" The 'value' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "indicator.gauge.axis" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """ def __init__( self, arg=None, dtickrange=None, enabled=None, name=None, templateitemname=None, value=None, **kwargs ): """ Construct a new Tickformatstop object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.indicator.gauge.axis.Tickformatstop dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- Tickformatstop """ super(Tickformatstop, self).__init__("tickformatstops") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.indicator.gauge.axis.Tickformatstop constructor must be a dict or an instance of plotly.graph_objs.indicator.gauge.axis.Tickformatstop""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.indicator.gauge.axis import ( tickformatstop as v_tickformatstop, ) # Initialize validators # --------------------- self._validators["dtickrange"] = v_tickformatstop.DtickrangeValidator() self._validators["enabled"] = v_tickformatstop.EnabledValidator() self._validators["name"] = v_tickformatstop.NameValidator() self._validators[ "templateitemname" ] = v_tickformatstop.TemplateitemnameValidator() self._validators["value"] = v_tickformatstop.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtickrange", None) self["dtickrange"] = dtickrange if dtickrange is not None else _v _v = arg.pop("enabled", None) self["enabled"] = enabled if enabled is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "indicator.gauge.axis" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Tickfont object Sets the color bar's tick label font Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.indicator.gauge.axis.Tickfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Tickfont """ super(Tickfont, self).__init__("tickfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.indicator.gauge.axis.Tickfont constructor must be a dict or an instance of plotly.graph_objs.indicator.gauge.axis.Tickfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.indicator.gauge.axis import tickfont as v_tickfont # Initialize validators # --------------------- self._validators["color"] = v_tickfont.ColorValidator() self._validators["family"] = v_tickfont.FamilyValidator() self._validators["size"] = v_tickfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Tickfont", "Tickformatstop", "Tickformatstop"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/indicator/gauge/__init__.py0000644000175000017500000020637613573721547025123 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Threshold(_BaseTraceHierarchyType): # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.indicator.gauge.threshold.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: color Sets the color of the threshold line. width Sets the width (in px) of the threshold line. Returns ------- plotly.graph_objs.indicator.gauge.threshold.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness of the threshold line as a fraction of the thickness of the gauge. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # value # ----- @property def value(self): """ Sets a treshold value drawn as a line. The 'value' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "indicator.gauge" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ line plotly.graph_objects.indicator.gauge.threshold.Line instance or dict with compatible properties thickness Sets the thickness of the threshold line as a fraction of the thickness of the gauge. value Sets a treshold value drawn as a line. """ def __init__(self, arg=None, line=None, thickness=None, value=None, **kwargs): """ Construct a new Threshold object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.indicator.gauge.Threshold line plotly.graph_objects.indicator.gauge.threshold.Line instance or dict with compatible properties thickness Sets the thickness of the threshold line as a fraction of the thickness of the gauge. value Sets a treshold value drawn as a line. Returns ------- Threshold """ super(Threshold, self).__init__("threshold") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.indicator.gauge.Threshold constructor must be a dict or an instance of plotly.graph_objs.indicator.gauge.Threshold""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.indicator.gauge import threshold as v_threshold # Initialize validators # --------------------- self._validators["line"] = v_threshold.LineValidator() self._validators["thickness"] = v_threshold.ThicknessValidator() self._validators["value"] = v_threshold.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("line", None) self["line"] = line if line is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Step(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the background color of the arc. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.indicator.gauge.step.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: color Sets the color of the line enclosing each sector. width Sets the width (in px) of the line enclosing each sector. Returns ------- plotly.graph_objs.indicator.gauge.step.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # range # ----- @property def range(self): """ Sets the range of this axis. The 'range' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'range[0]' property is a number and may be specified as: - An int or float (1) The 'range[1]' property is a number and may be specified as: - An int or float Returns ------- list """ return self["range"] @range.setter def range(self, val): self["range"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness of the bar as a fraction of the total thickness of the gauge. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "indicator.gauge" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the background color of the arc. line plotly.graph_objects.indicator.gauge.step.Line instance or dict with compatible properties name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. range Sets the range of this axis. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. thickness Sets the thickness of the bar as a fraction of the total thickness of the gauge. """ def __init__( self, arg=None, color=None, line=None, name=None, range=None, templateitemname=None, thickness=None, **kwargs ): """ Construct a new Step object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.indicator.gauge.Step color Sets the background color of the arc. line plotly.graph_objects.indicator.gauge.step.Line instance or dict with compatible properties name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. range Sets the range of this axis. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. thickness Sets the thickness of the bar as a fraction of the total thickness of the gauge. Returns ------- Step """ super(Step, self).__init__("steps") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.indicator.gauge.Step constructor must be a dict or an instance of plotly.graph_objs.indicator.gauge.Step""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.indicator.gauge import step as v_step # Initialize validators # --------------------- self._validators["color"] = v_step.ColorValidator() self._validators["line"] = v_step.LineValidator() self._validators["name"] = v_step.NameValidator() self._validators["range"] = v_step.RangeValidator() self._validators["templateitemname"] = v_step.TemplateitemnameValidator() self._validators["thickness"] = v_step.ThicknessValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("range", None) self["range"] = range if range is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Bar(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the background color of the arc. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.indicator.gauge.bar.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: color Sets the color of the line enclosing each sector. width Sets the width (in px) of the line enclosing each sector. Returns ------- plotly.graph_objs.indicator.gauge.bar.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness of the bar as a fraction of the total thickness of the gauge. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "indicator.gauge" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the background color of the arc. line plotly.graph_objects.indicator.gauge.bar.Line instance or dict with compatible properties thickness Sets the thickness of the bar as a fraction of the total thickness of the gauge. """ def __init__(self, arg=None, color=None, line=None, thickness=None, **kwargs): """ Construct a new Bar object Set the appearance of the gauge's value Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.indicator.gauge.Bar color Sets the background color of the arc. line plotly.graph_objects.indicator.gauge.bar.Line instance or dict with compatible properties thickness Sets the thickness of the bar as a fraction of the total thickness of the gauge. Returns ------- Bar """ super(Bar, self).__init__("bar") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.indicator.gauge.Bar constructor must be a dict or an instance of plotly.graph_objs.indicator.gauge.Bar""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.indicator.gauge import bar as v_bar # Initialize validators # --------------------- self._validators["color"] = v_bar.ColorValidator() self._validators["line"] = v_bar.LineValidator() self._validators["thickness"] = v_bar.ThicknessValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Axis(_BaseTraceHierarchyType): # dtick # ----- @property def dtick(self): """ Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" The 'dtick' property accepts values of any type Returns ------- Any """ return self["dtick"] @dtick.setter def dtick(self, val): self["dtick"] = val # exponentformat # -------------- @property def exponentformat(self): """ Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. The 'exponentformat' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'e', 'E', 'power', 'SI', 'B'] Returns ------- Any """ return self["exponentformat"] @exponentformat.setter def exponentformat(self, val): self["exponentformat"] = val # nticks # ------ @property def nticks(self): """ Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". The 'nticks' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nticks"] @nticks.setter def nticks(self, val): self["nticks"] = val # range # ----- @property def range(self): """ Sets the range of this axis. The 'range' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'range[0]' property is a number and may be specified as: - An int or float (1) The 'range[1]' property is a number and may be specified as: - An int or float Returns ------- list """ return self["range"] @range.setter def range(self, val): self["range"] = val # separatethousands # ----------------- @property def separatethousands(self): """ If "true", even 4-digit integers are separated The 'separatethousands' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["separatethousands"] @separatethousands.setter def separatethousands(self, val): self["separatethousands"] = val # showexponent # ------------ @property def showexponent(self): """ If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. The 'showexponent' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showexponent"] @showexponent.setter def showexponent(self, val): self["showexponent"] = val # showticklabels # -------------- @property def showticklabels(self): """ Determines whether or not the tick labels are drawn. The 'showticklabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showticklabels"] @showticklabels.setter def showticklabels(self, val): self["showticklabels"] = val # showtickprefix # -------------- @property def showtickprefix(self): """ If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. The 'showtickprefix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showtickprefix"] @showtickprefix.setter def showtickprefix(self, val): self["showtickprefix"] = val # showticksuffix # -------------- @property def showticksuffix(self): """ Same as `showtickprefix` but for tick suffixes. The 'showticksuffix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showticksuffix"] @showticksuffix.setter def showticksuffix(self, val): self["showticksuffix"] = val # tick0 # ----- @property def tick0(self): """ Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. The 'tick0' property accepts values of any type Returns ------- Any """ return self["tick0"] @tick0.setter def tick0(self, val): self["tick0"] = val # tickangle # --------- @property def tickangle(self): """ Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. The 'tickangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["tickangle"] @tickangle.setter def tickangle(self, val): self["tickangle"] = val # tickcolor # --------- @property def tickcolor(self): """ Sets the tick color. The 'tickcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["tickcolor"] @tickcolor.setter def tickcolor(self, val): self["tickcolor"] = val # tickfont # -------- @property def tickfont(self): """ Sets the color bar's tick label font The 'tickfont' property is an instance of Tickfont that may be specified as: - An instance of plotly.graph_objs.indicator.gauge.axis.Tickfont - A dict of string/value properties that will be passed to the Tickfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.indicator.gauge.axis.Tickfont """ return self["tickfont"] @tickfont.setter def tickfont(self, val): self["tickfont"] = val # tickformat # ---------- @property def tickformat(self): """ Sets the tick label formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'tickformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickformat"] @tickformat.setter def tickformat(self, val): self["tickformat"] = val # tickformatstops # --------------- @property def tickformatstops(self): """ The 'tickformatstops' property is a tuple of instances of Tickformatstop that may be specified as: - A list or tuple of instances of plotly.graph_objs.indicator.gauge.axis.Tickformatstop - A list or tuple of dicts of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- tuple[plotly.graph_objs.indicator.gauge.axis.Tickformatstop] """ return self["tickformatstops"] @tickformatstops.setter def tickformatstops(self, val): self["tickformatstops"] = val # tickformatstopdefaults # ---------------------- @property def tickformatstopdefaults(self): """ When used in a template (as layout.template.data.indicator.gaug e.axis.tickformatstopdefaults), sets the default property values to use for elements of indicator.gauge.axis.tickformatstops The 'tickformatstopdefaults' property is an instance of Tickformatstop that may be specified as: - An instance of plotly.graph_objs.indicator.gauge.axis.Tickformatstop - A dict of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: Returns ------- plotly.graph_objs.indicator.gauge.axis.Tickformatstop """ return self["tickformatstopdefaults"] @tickformatstopdefaults.setter def tickformatstopdefaults(self, val): self["tickformatstopdefaults"] = val # ticklen # ------- @property def ticklen(self): """ Sets the tick length (in px). The 'ticklen' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ticklen"] @ticklen.setter def ticklen(self, val): self["ticklen"] = val # tickmode # -------- @property def tickmode(self): """ Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). The 'tickmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'linear', 'array'] Returns ------- Any """ return self["tickmode"] @tickmode.setter def tickmode(self, val): self["tickmode"] = val # tickprefix # ---------- @property def tickprefix(self): """ Sets a tick label prefix. The 'tickprefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickprefix"] @tickprefix.setter def tickprefix(self, val): self["tickprefix"] = val # ticks # ----- @property def ticks(self): """ Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. The 'ticks' property is an enumeration that may be specified as: - One of the following enumeration values: ['outside', 'inside', ''] Returns ------- Any """ return self["ticks"] @ticks.setter def ticks(self, val): self["ticks"] = val # ticksuffix # ---------- @property def ticksuffix(self): """ Sets a tick label suffix. The 'ticksuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ticksuffix"] @ticksuffix.setter def ticksuffix(self, val): self["ticksuffix"] = val # ticktext # -------- @property def ticktext(self): """ Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. The 'ticktext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ticktext"] @ticktext.setter def ticktext(self, val): self["ticktext"] = val # ticktextsrc # ----------- @property def ticktextsrc(self): """ Sets the source reference on plot.ly for ticktext . The 'ticktextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ticktextsrc"] @ticktextsrc.setter def ticktextsrc(self, val): self["ticktextsrc"] = val # tickvals # -------- @property def tickvals(self): """ Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. The 'tickvals' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["tickvals"] @tickvals.setter def tickvals(self, val): self["tickvals"] = val # tickvalssrc # ----------- @property def tickvalssrc(self): """ Sets the source reference on plot.ly for tickvals . The 'tickvalssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tickvalssrc"] @tickvalssrc.setter def tickvalssrc(self, val): self["tickvalssrc"] = val # tickwidth # --------- @property def tickwidth(self): """ Sets the tick width (in px). The 'tickwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["tickwidth"] @tickwidth.setter def tickwidth(self, val): self["tickwidth"] = val # visible # ------- @property def visible(self): """ A single toggle to hide the axis while preserving interaction like dragging. Default is true when a cheater plot is present on the axis, otherwise false The 'visible' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "indicator.gauge" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". range Sets the range of this axis. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.indicator.gauge.axis.Ti ckformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.indica tor.gauge.axis.tickformatstopdefaults), sets the default property values to use for elements of indicator.gauge.axis.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). visible A single toggle to hide the axis while preserving interaction like dragging. Default is true when a cheater plot is present on the axis, otherwise false """ def __init__( self, arg=None, dtick=None, exponentformat=None, nticks=None, range=None, separatethousands=None, showexponent=None, showticklabels=None, showtickprefix=None, showticksuffix=None, tick0=None, tickangle=None, tickcolor=None, tickfont=None, tickformat=None, tickformatstops=None, tickformatstopdefaults=None, ticklen=None, tickmode=None, tickprefix=None, ticks=None, ticksuffix=None, ticktext=None, ticktextsrc=None, tickvals=None, tickvalssrc=None, tickwidth=None, visible=None, **kwargs ): """ Construct a new Axis object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.indicator.gauge.Axis dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". range Sets the range of this axis. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.indicator.gauge.axis.Ti ckformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.indica tor.gauge.axis.tickformatstopdefaults), sets the default property values to use for elements of indicator.gauge.axis.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). visible A single toggle to hide the axis while preserving interaction like dragging. Default is true when a cheater plot is present on the axis, otherwise false Returns ------- Axis """ super(Axis, self).__init__("axis") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.indicator.gauge.Axis constructor must be a dict or an instance of plotly.graph_objs.indicator.gauge.Axis""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.indicator.gauge import axis as v_axis # Initialize validators # --------------------- self._validators["dtick"] = v_axis.DtickValidator() self._validators["exponentformat"] = v_axis.ExponentformatValidator() self._validators["nticks"] = v_axis.NticksValidator() self._validators["range"] = v_axis.RangeValidator() self._validators["separatethousands"] = v_axis.SeparatethousandsValidator() self._validators["showexponent"] = v_axis.ShowexponentValidator() self._validators["showticklabels"] = v_axis.ShowticklabelsValidator() self._validators["showtickprefix"] = v_axis.ShowtickprefixValidator() self._validators["showticksuffix"] = v_axis.ShowticksuffixValidator() self._validators["tick0"] = v_axis.Tick0Validator() self._validators["tickangle"] = v_axis.TickangleValidator() self._validators["tickcolor"] = v_axis.TickcolorValidator() self._validators["tickfont"] = v_axis.TickfontValidator() self._validators["tickformat"] = v_axis.TickformatValidator() self._validators["tickformatstops"] = v_axis.TickformatstopsValidator() self._validators["tickformatstopdefaults"] = v_axis.TickformatstopValidator() self._validators["ticklen"] = v_axis.TicklenValidator() self._validators["tickmode"] = v_axis.TickmodeValidator() self._validators["tickprefix"] = v_axis.TickprefixValidator() self._validators["ticks"] = v_axis.TicksValidator() self._validators["ticksuffix"] = v_axis.TicksuffixValidator() self._validators["ticktext"] = v_axis.TicktextValidator() self._validators["ticktextsrc"] = v_axis.TicktextsrcValidator() self._validators["tickvals"] = v_axis.TickvalsValidator() self._validators["tickvalssrc"] = v_axis.TickvalssrcValidator() self._validators["tickwidth"] = v_axis.TickwidthValidator() self._validators["visible"] = v_axis.VisibleValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtick", None) self["dtick"] = dtick if dtick is not None else _v _v = arg.pop("exponentformat", None) self["exponentformat"] = exponentformat if exponentformat is not None else _v _v = arg.pop("nticks", None) self["nticks"] = nticks if nticks is not None else _v _v = arg.pop("range", None) self["range"] = range if range is not None else _v _v = arg.pop("separatethousands", None) self["separatethousands"] = ( separatethousands if separatethousands is not None else _v ) _v = arg.pop("showexponent", None) self["showexponent"] = showexponent if showexponent is not None else _v _v = arg.pop("showticklabels", None) self["showticklabels"] = showticklabels if showticklabels is not None else _v _v = arg.pop("showtickprefix", None) self["showtickprefix"] = showtickprefix if showtickprefix is not None else _v _v = arg.pop("showticksuffix", None) self["showticksuffix"] = showticksuffix if showticksuffix is not None else _v _v = arg.pop("tick0", None) self["tick0"] = tick0 if tick0 is not None else _v _v = arg.pop("tickangle", None) self["tickangle"] = tickangle if tickangle is not None else _v _v = arg.pop("tickcolor", None) self["tickcolor"] = tickcolor if tickcolor is not None else _v _v = arg.pop("tickfont", None) self["tickfont"] = tickfont if tickfont is not None else _v _v = arg.pop("tickformat", None) self["tickformat"] = tickformat if tickformat is not None else _v _v = arg.pop("tickformatstops", None) self["tickformatstops"] = tickformatstops if tickformatstops is not None else _v _v = arg.pop("tickformatstopdefaults", None) self["tickformatstopdefaults"] = ( tickformatstopdefaults if tickformatstopdefaults is not None else _v ) _v = arg.pop("ticklen", None) self["ticklen"] = ticklen if ticklen is not None else _v _v = arg.pop("tickmode", None) self["tickmode"] = tickmode if tickmode is not None else _v _v = arg.pop("tickprefix", None) self["tickprefix"] = tickprefix if tickprefix is not None else _v _v = arg.pop("ticks", None) self["ticks"] = ticks if ticks is not None else _v _v = arg.pop("ticksuffix", None) self["ticksuffix"] = ticksuffix if ticksuffix is not None else _v _v = arg.pop("ticktext", None) self["ticktext"] = ticktext if ticktext is not None else _v _v = arg.pop("ticktextsrc", None) self["ticktextsrc"] = ticktextsrc if ticktextsrc is not None else _v _v = arg.pop("tickvals", None) self["tickvals"] = tickvals if tickvals is not None else _v _v = arg.pop("tickvalssrc", None) self["tickvalssrc"] = tickvalssrc if tickvalssrc is not None else _v _v = arg.pop("tickwidth", None) self["tickwidth"] = tickwidth if tickwidth is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = [ "Axis", "Bar", "Step", "Step", "Threshold", "axis", "bar", "step", "threshold", ] from plotly.graph_objs.indicator.gauge import threshold from plotly.graph_objs.indicator.gauge import step from plotly.graph_objs.indicator.gauge import bar from plotly.graph_objs.indicator.gauge import axis plotly-4.4.1+dfsg.orig/plotly/graph_objs/indicator/gauge/threshold/0000755000175000017500000000000013573746613024771 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/indicator/gauge/threshold/__init__.py0000644000175000017500000001322213573721546027100 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the color of the threshold line. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # width # ----- @property def width(self): """ Sets the width (in px) of the threshold line. The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "indicator.gauge.threshold" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the color of the threshold line. width Sets the width (in px) of the threshold line. """ def __init__(self, arg=None, color=None, width=None, **kwargs): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.indicator.gauge.threshold.Line color Sets the color of the threshold line. width Sets the width (in px) of the threshold line. Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.indicator.gauge.threshold.Line constructor must be a dict or an instance of plotly.graph_objs.indicator.gauge.threshold.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.indicator.gauge.threshold import line as v_line # Initialize validators # --------------------- self._validators["color"] = v_line.ColorValidator() self._validators["width"] = v_line.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Line"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/indicator/gauge/step/0000755000175000017500000000000013573746613023750 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/indicator/gauge/step/__init__.py0000644000175000017500000001333113573721546026060 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the color of the line enclosing each sector. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # width # ----- @property def width(self): """ Sets the width (in px) of the line enclosing each sector. The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "indicator.gauge.step" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the color of the line enclosing each sector. width Sets the width (in px) of the line enclosing each sector. """ def __init__(self, arg=None, color=None, width=None, **kwargs): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.indicator.gauge.step.Line color Sets the color of the line enclosing each sector. width Sets the width (in px) of the line enclosing each sector. Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.indicator.gauge.step.Line constructor must be a dict or an instance of plotly.graph_objs.indicator.gauge.step.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.indicator.gauge.step import line as v_line # Initialize validators # --------------------- self._validators["color"] = v_line.ColorValidator() self._validators["width"] = v_line.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Line"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/indicator/number/0000755000175000017500000000000013573746613023175 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/indicator/number/__init__.py0000644000175000017500000002032313573721547025305 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "indicator.number" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Set the font used to display main number Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.indicator.number.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.indicator.number.Font constructor must be a dict or an instance of plotly.graph_objs.indicator.number.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.indicator.number import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/indicator/__init__.py0000644000175000017500000016326013573721547024025 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Title(_BaseTraceHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the title. It defaults to `center` except for bullet charts for which it defaults to right. The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'center', 'right'] Returns ------- Any """ return self["align"] @align.setter def align(self, val): self["align"] = val # font # ---- @property def font(self): """ Set the font used to display the title The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.indicator.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.indicator.title.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # text # ---- @property def text(self): """ Sets the title of this indicator. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "indicator" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the title. It defaults to `center` except for bullet charts for which it defaults to right. font Set the font used to display the title text Sets the title of this indicator. """ def __init__(self, arg=None, align=None, font=None, text=None, **kwargs): """ Construct a new Title object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.indicator.Title align Sets the horizontal alignment of the title. It defaults to `center` except for bullet charts for which it defaults to right. font Set the font used to display the title text Sets the title of this indicator. Returns ------- Title """ super(Title, self).__init__("title") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.indicator.Title constructor must be a dict or an instance of plotly.graph_objs.indicator.Title""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.indicator import title as v_title # Initialize validators # --------------------- self._validators["align"] = v_title.AlignValidator() self._validators["font"] = v_title.FontValidator() self._validators["text"] = v_title.TextValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Stream(_BaseTraceHierarchyType): # maxpoints # --------- @property def maxpoints(self): """ Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. The 'maxpoints' property is a number and may be specified as: - An int or float in the interval [0, 10000] Returns ------- int|float """ return self["maxpoints"] @maxpoints.setter def maxpoints(self, val): self["maxpoints"] = val # token # ----- @property def token(self): """ The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. The 'token' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["token"] @token.setter def token(self, val): self["token"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "indicator" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """ def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): """ Construct a new Stream object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.indicator.Stream maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- Stream """ super(Stream, self).__init__("stream") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.indicator.Stream constructor must be a dict or an instance of plotly.graph_objs.indicator.Stream""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.indicator import stream as v_stream # Initialize validators # --------------------- self._validators["maxpoints"] = v_stream.MaxpointsValidator() self._validators["token"] = v_stream.TokenValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("maxpoints", None) self["maxpoints"] = maxpoints if maxpoints is not None else _v _v = arg.pop("token", None) self["token"] = token if token is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Number(_BaseTraceHierarchyType): # font # ---- @property def font(self): """ Set the font used to display main number The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.indicator.number.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.indicator.number.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # prefix # ------ @property def prefix(self): """ Sets a prefix appearing before the number. The 'prefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["prefix"] @prefix.setter def prefix(self, val): self["prefix"] = val # suffix # ------ @property def suffix(self): """ Sets a suffix appearing next to the number. The 'suffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["suffix"] @suffix.setter def suffix(self, val): self["suffix"] = val # valueformat # ----------- @property def valueformat(self): """ Sets the value formatting rule using d3 formatting mini- language which is similar to those of Python. See https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format The 'valueformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["valueformat"] @valueformat.setter def valueformat(self, val): self["valueformat"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "indicator" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Set the font used to display main number prefix Sets a prefix appearing before the number. suffix Sets a suffix appearing next to the number. valueformat Sets the value formatting rule using d3 formatting mini-language which is similar to those of Python. See https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format """ def __init__( self, arg=None, font=None, prefix=None, suffix=None, valueformat=None, **kwargs ): """ Construct a new Number object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.indicator.Number font Set the font used to display main number prefix Sets a prefix appearing before the number. suffix Sets a suffix appearing next to the number. valueformat Sets the value formatting rule using d3 formatting mini-language which is similar to those of Python. See https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format Returns ------- Number """ super(Number, self).__init__("number") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.indicator.Number constructor must be a dict or an instance of plotly.graph_objs.indicator.Number""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.indicator import number as v_number # Initialize validators # --------------------- self._validators["font"] = v_number.FontValidator() self._validators["prefix"] = v_number.PrefixValidator() self._validators["suffix"] = v_number.SuffixValidator() self._validators["valueformat"] = v_number.ValueformatValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("prefix", None) self["prefix"] = prefix if prefix is not None else _v _v = arg.pop("suffix", None) self["suffix"] = suffix if suffix is not None else _v _v = arg.pop("valueformat", None) self["valueformat"] = valueformat if valueformat is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Gauge(_BaseTraceHierarchyType): # axis # ---- @property def axis(self): """ The 'axis' property is an instance of Axis that may be specified as: - An instance of plotly.graph_objs.indicator.gauge.Axis - A dict of string/value properties that will be passed to the Axis constructor Supported dict properties: dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". range Sets the range of this axis. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.indicator.gauge .axis.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.indicator.gauge.axis.tickformatstopdefaults), sets the default property values to use for elements of indicator.gauge.axis.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). visible A single toggle to hide the axis while preserving interaction like dragging. Default is true when a cheater plot is present on the axis, otherwise false Returns ------- plotly.graph_objs.indicator.gauge.Axis """ return self["axis"] @axis.setter def axis(self, val): self["axis"] = val # bar # --- @property def bar(self): """ Set the appearance of the gauge's value The 'bar' property is an instance of Bar that may be specified as: - An instance of plotly.graph_objs.indicator.gauge.Bar - A dict of string/value properties that will be passed to the Bar constructor Supported dict properties: color Sets the background color of the arc. line plotly.graph_objects.indicator.gauge.bar.Line instance or dict with compatible properties thickness Sets the thickness of the bar as a fraction of the total thickness of the gauge. Returns ------- plotly.graph_objs.indicator.gauge.Bar """ return self["bar"] @bar.setter def bar(self, val): self["bar"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the gauge background color. The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the color of the border enclosing the gauge. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # borderwidth # ----------- @property def borderwidth(self): """ Sets the width (in px) of the border enclosing the gauge. The 'borderwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["borderwidth"] @borderwidth.setter def borderwidth(self, val): self["borderwidth"] = val # shape # ----- @property def shape(self): """ Set the shape of the gauge The 'shape' property is an enumeration that may be specified as: - One of the following enumeration values: ['angular', 'bullet'] Returns ------- Any """ return self["shape"] @shape.setter def shape(self, val): self["shape"] = val # steps # ----- @property def steps(self): """ The 'steps' property is a tuple of instances of Step that may be specified as: - A list or tuple of instances of plotly.graph_objs.indicator.gauge.Step - A list or tuple of dicts of string/value properties that will be passed to the Step constructor Supported dict properties: color Sets the background color of the arc. line plotly.graph_objects.indicator.gauge.step.Line instance or dict with compatible properties name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. range Sets the range of this axis. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. thickness Sets the thickness of the bar as a fraction of the total thickness of the gauge. Returns ------- tuple[plotly.graph_objs.indicator.gauge.Step] """ return self["steps"] @steps.setter def steps(self, val): self["steps"] = val # stepdefaults # ------------ @property def stepdefaults(self): """ When used in a template (as layout.template.data.indicator.gauge.stepdefaults), sets the default property values to use for elements of indicator.gauge.steps The 'stepdefaults' property is an instance of Step that may be specified as: - An instance of plotly.graph_objs.indicator.gauge.Step - A dict of string/value properties that will be passed to the Step constructor Supported dict properties: Returns ------- plotly.graph_objs.indicator.gauge.Step """ return self["stepdefaults"] @stepdefaults.setter def stepdefaults(self, val): self["stepdefaults"] = val # threshold # --------- @property def threshold(self): """ The 'threshold' property is an instance of Threshold that may be specified as: - An instance of plotly.graph_objs.indicator.gauge.Threshold - A dict of string/value properties that will be passed to the Threshold constructor Supported dict properties: line plotly.graph_objects.indicator.gauge.threshold. Line instance or dict with compatible properties thickness Sets the thickness of the threshold line as a fraction of the thickness of the gauge. value Sets a treshold value drawn as a line. Returns ------- plotly.graph_objs.indicator.gauge.Threshold """ return self["threshold"] @threshold.setter def threshold(self, val): self["threshold"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "indicator" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ axis plotly.graph_objects.indicator.gauge.Axis instance or dict with compatible properties bar Set the appearance of the gauge's value bgcolor Sets the gauge background color. bordercolor Sets the color of the border enclosing the gauge. borderwidth Sets the width (in px) of the border enclosing the gauge. shape Set the shape of the gauge steps A tuple of plotly.graph_objects.indicator.gauge.Step instances or dicts with compatible properties stepdefaults When used in a template (as layout.template.data.indicator.gauge.stepdefaults), sets the default property values to use for elements of indicator.gauge.steps threshold plotly.graph_objects.indicator.gauge.Threshold instance or dict with compatible properties """ def __init__( self, arg=None, axis=None, bar=None, bgcolor=None, bordercolor=None, borderwidth=None, shape=None, steps=None, stepdefaults=None, threshold=None, **kwargs ): """ Construct a new Gauge object The gauge of the Indicator plot. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.indicator.Gauge axis plotly.graph_objects.indicator.gauge.Axis instance or dict with compatible properties bar Set the appearance of the gauge's value bgcolor Sets the gauge background color. bordercolor Sets the color of the border enclosing the gauge. borderwidth Sets the width (in px) of the border enclosing the gauge. shape Set the shape of the gauge steps A tuple of plotly.graph_objects.indicator.gauge.Step instances or dicts with compatible properties stepdefaults When used in a template (as layout.template.data.indicator.gauge.stepdefaults), sets the default property values to use for elements of indicator.gauge.steps threshold plotly.graph_objects.indicator.gauge.Threshold instance or dict with compatible properties Returns ------- Gauge """ super(Gauge, self).__init__("gauge") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.indicator.Gauge constructor must be a dict or an instance of plotly.graph_objs.indicator.Gauge""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.indicator import gauge as v_gauge # Initialize validators # --------------------- self._validators["axis"] = v_gauge.AxisValidator() self._validators["bar"] = v_gauge.BarValidator() self._validators["bgcolor"] = v_gauge.BgcolorValidator() self._validators["bordercolor"] = v_gauge.BordercolorValidator() self._validators["borderwidth"] = v_gauge.BorderwidthValidator() self._validators["shape"] = v_gauge.ShapeValidator() self._validators["steps"] = v_gauge.StepsValidator() self._validators["stepdefaults"] = v_gauge.StepValidator() self._validators["threshold"] = v_gauge.ThresholdValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("axis", None) self["axis"] = axis if axis is not None else _v _v = arg.pop("bar", None) self["bar"] = bar if bar is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("borderwidth", None) self["borderwidth"] = borderwidth if borderwidth is not None else _v _v = arg.pop("shape", None) self["shape"] = shape if shape is not None else _v _v = arg.pop("steps", None) self["steps"] = steps if steps is not None else _v _v = arg.pop("stepdefaults", None) self["stepdefaults"] = stepdefaults if stepdefaults is not None else _v _v = arg.pop("threshold", None) self["threshold"] = threshold if threshold is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Domain(_BaseTraceHierarchyType): # column # ------ @property def column(self): """ If there is a layout grid, use the domain for this column in the grid for this indicator trace . The 'column' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["column"] @column.setter def column(self, val): self["column"] = val # row # --- @property def row(self): """ If there is a layout grid, use the domain for this row in the grid for this indicator trace . The 'row' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["row"] @row.setter def row(self, val): self["row"] = val # x # - @property def x(self): """ Sets the horizontal domain of this indicator trace (in plot fraction). The 'x' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'x[0]' property is a number and may be specified as: - An int or float in the interval [0, 1] (1) The 'x[1]' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- list """ return self["x"] @x.setter def x(self, val): self["x"] = val # y # - @property def y(self): """ Sets the vertical domain of this indicator trace (in plot fraction). The 'y' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'y[0]' property is a number and may be specified as: - An int or float in the interval [0, 1] (1) The 'y[1]' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- list """ return self["y"] @y.setter def y(self, val): self["y"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "indicator" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ column If there is a layout grid, use the domain for this column in the grid for this indicator trace . row If there is a layout grid, use the domain for this row in the grid for this indicator trace . x Sets the horizontal domain of this indicator trace (in plot fraction). y Sets the vertical domain of this indicator trace (in plot fraction). """ def __init__(self, arg=None, column=None, row=None, x=None, y=None, **kwargs): """ Construct a new Domain object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.indicator.Domain column If there is a layout grid, use the domain for this column in the grid for this indicator trace . row If there is a layout grid, use the domain for this row in the grid for this indicator trace . x Sets the horizontal domain of this indicator trace (in plot fraction). y Sets the vertical domain of this indicator trace (in plot fraction). Returns ------- Domain """ super(Domain, self).__init__("domain") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.indicator.Domain constructor must be a dict or an instance of plotly.graph_objs.indicator.Domain""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.indicator import domain as v_domain # Initialize validators # --------------------- self._validators["column"] = v_domain.ColumnValidator() self._validators["row"] = v_domain.RowValidator() self._validators["x"] = v_domain.XValidator() self._validators["y"] = v_domain.YValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("column", None) self["column"] = column if column is not None else _v _v = arg.pop("row", None) self["row"] = row if row is not None else _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Delta(_BaseTraceHierarchyType): # decreasing # ---------- @property def decreasing(self): """ The 'decreasing' property is an instance of Decreasing that may be specified as: - An instance of plotly.graph_objs.indicator.delta.Decreasing - A dict of string/value properties that will be passed to the Decreasing constructor Supported dict properties: color Sets the color for increasing value. symbol Sets the symbol to display for increasing value Returns ------- plotly.graph_objs.indicator.delta.Decreasing """ return self["decreasing"] @decreasing.setter def decreasing(self, val): self["decreasing"] = val # font # ---- @property def font(self): """ Set the font used to display the delta The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.indicator.delta.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.indicator.delta.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # increasing # ---------- @property def increasing(self): """ The 'increasing' property is an instance of Increasing that may be specified as: - An instance of plotly.graph_objs.indicator.delta.Increasing - A dict of string/value properties that will be passed to the Increasing constructor Supported dict properties: color Sets the color for increasing value. symbol Sets the symbol to display for increasing value Returns ------- plotly.graph_objs.indicator.delta.Increasing """ return self["increasing"] @increasing.setter def increasing(self, val): self["increasing"] = val # position # -------- @property def position(self): """ Sets the position of delta with respect to the number. The 'position' property is an enumeration that may be specified as: - One of the following enumeration values: ['top', 'bottom', 'left', 'right'] Returns ------- Any """ return self["position"] @position.setter def position(self, val): self["position"] = val # reference # --------- @property def reference(self): """ Sets the reference value to compute the delta. By default, it is set to the current value. The 'reference' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["reference"] @reference.setter def reference(self, val): self["reference"] = val # relative # -------- @property def relative(self): """ Show relative change The 'relative' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["relative"] @relative.setter def relative(self, val): self["relative"] = val # valueformat # ----------- @property def valueformat(self): """ Sets the value formatting rule using d3 formatting mini- language which is similar to those of Python. See https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format The 'valueformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["valueformat"] @valueformat.setter def valueformat(self, val): self["valueformat"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "indicator" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ decreasing plotly.graph_objects.indicator.delta.Decreasing instance or dict with compatible properties font Set the font used to display the delta increasing plotly.graph_objects.indicator.delta.Increasing instance or dict with compatible properties position Sets the position of delta with respect to the number. reference Sets the reference value to compute the delta. By default, it is set to the current value. relative Show relative change valueformat Sets the value formatting rule using d3 formatting mini-language which is similar to those of Python. See https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format """ def __init__( self, arg=None, decreasing=None, font=None, increasing=None, position=None, reference=None, relative=None, valueformat=None, **kwargs ): """ Construct a new Delta object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.indicator.Delta decreasing plotly.graph_objects.indicator.delta.Decreasing instance or dict with compatible properties font Set the font used to display the delta increasing plotly.graph_objects.indicator.delta.Increasing instance or dict with compatible properties position Sets the position of delta with respect to the number. reference Sets the reference value to compute the delta. By default, it is set to the current value. relative Show relative change valueformat Sets the value formatting rule using d3 formatting mini-language which is similar to those of Python. See https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format Returns ------- Delta """ super(Delta, self).__init__("delta") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.indicator.Delta constructor must be a dict or an instance of plotly.graph_objs.indicator.Delta""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.indicator import delta as v_delta # Initialize validators # --------------------- self._validators["decreasing"] = v_delta.DecreasingValidator() self._validators["font"] = v_delta.FontValidator() self._validators["increasing"] = v_delta.IncreasingValidator() self._validators["position"] = v_delta.PositionValidator() self._validators["reference"] = v_delta.ReferenceValidator() self._validators["relative"] = v_delta.RelativeValidator() self._validators["valueformat"] = v_delta.ValueformatValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("decreasing", None) self["decreasing"] = decreasing if decreasing is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("increasing", None) self["increasing"] = increasing if increasing is not None else _v _v = arg.pop("position", None) self["position"] = position if position is not None else _v _v = arg.pop("reference", None) self["reference"] = reference if reference is not None else _v _v = arg.pop("relative", None) self["relative"] = relative if relative is not None else _v _v = arg.pop("valueformat", None) self["valueformat"] = valueformat if valueformat is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = [ "Delta", "Domain", "Gauge", "Number", "Stream", "Title", "delta", "gauge", "number", "title", ] from plotly.graph_objs.indicator import title from plotly.graph_objs.indicator import number from plotly.graph_objs.indicator import gauge from plotly.graph_objs.indicator import delta plotly-4.4.1+dfsg.orig/plotly/graph_objs/indicator/delta/0000755000175000017500000000000013573746613022776 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/indicator/delta/__init__.py0000644000175000017500000004714013573721546025113 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Increasing(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the color for increasing value. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # symbol # ------ @property def symbol(self): """ Sets the symbol to display for increasing value The 'symbol' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["symbol"] @symbol.setter def symbol(self, val): self["symbol"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "indicator.delta" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the color for increasing value. symbol Sets the symbol to display for increasing value """ def __init__(self, arg=None, color=None, symbol=None, **kwargs): """ Construct a new Increasing object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.indicator.delta.Increasing color Sets the color for increasing value. symbol Sets the symbol to display for increasing value Returns ------- Increasing """ super(Increasing, self).__init__("increasing") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.indicator.delta.Increasing constructor must be a dict or an instance of plotly.graph_objs.indicator.delta.Increasing""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.indicator.delta import increasing as v_increasing # Initialize validators # --------------------- self._validators["color"] = v_increasing.ColorValidator() self._validators["symbol"] = v_increasing.SymbolValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("symbol", None) self["symbol"] = symbol if symbol is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "indicator.delta" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Set the font used to display the delta Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.indicator.delta.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.indicator.delta.Font constructor must be a dict or an instance of plotly.graph_objs.indicator.delta.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.indicator.delta import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Decreasing(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the color for increasing value. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # symbol # ------ @property def symbol(self): """ Sets the symbol to display for increasing value The 'symbol' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["symbol"] @symbol.setter def symbol(self, val): self["symbol"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "indicator.delta" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the color for increasing value. symbol Sets the symbol to display for increasing value """ def __init__(self, arg=None, color=None, symbol=None, **kwargs): """ Construct a new Decreasing object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.indicator.delta.Decreasing color Sets the color for increasing value. symbol Sets the symbol to display for increasing value Returns ------- Decreasing """ super(Decreasing, self).__init__("decreasing") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.indicator.delta.Decreasing constructor must be a dict or an instance of plotly.graph_objs.indicator.delta.Decreasing""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.indicator.delta import decreasing as v_decreasing # Initialize validators # --------------------- self._validators["color"] = v_decreasing.ColorValidator() self._validators["symbol"] = v_decreasing.SymbolValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("symbol", None) self["symbol"] = symbol if symbol is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Decreasing", "Font", "Increasing"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/cone/0000755000175000017500000000000013573746613020655 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/cone/hoverlabel/0000755000175000017500000000000013573746613023000 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/cone/hoverlabel/__init__.py0000644000175000017500000002540513573721546025115 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "cone.hoverlabel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Font object Sets the font used in hover labels. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.cone.hoverlabel.Font color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.cone.hoverlabel.Font constructor must be a dict or an instance of plotly.graph_objs.cone.hoverlabel.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.cone.hoverlabel import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["colorsrc"] = v_font.ColorsrcValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["familysrc"] = v_font.FamilysrcValidator() self._validators["size"] = v_font.SizeValidator() self._validators["sizesrc"] = v_font.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/cone/colorbar/0000755000175000017500000000000013573746613022460 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/cone/colorbar/title/0000755000175000017500000000000013573746613023601 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/cone/colorbar/title/__init__.py0000644000175000017500000002050613573721546025713 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "cone.colorbar.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.cone.colorbar.title.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.cone.colorbar.title.Font constructor must be a dict or an instance of plotly.graph_objs.cone.colorbar.title.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.cone.colorbar.title import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/cone/colorbar/__init__.py0000644000175000017500000006040713573721546024576 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Title(_BaseTraceHierarchyType): # font # ---- @property def font(self): """ Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.cone.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.cone.colorbar.title.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # side # ---- @property def side(self): """ Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- Any """ return self["side"] @side.setter def side(self, val): self["side"] = val # text # ---- @property def text(self): """ Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "cone.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """ def __init__(self, arg=None, font=None, side=None, text=None, **kwargs): """ Construct a new Title object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.cone.colorbar.Title font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- Title """ super(Title, self).__init__("title") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.cone.colorbar.Title constructor must be a dict or an instance of plotly.graph_objs.cone.colorbar.Title""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.cone.colorbar import title as v_title # Initialize validators # --------------------- self._validators["font"] = v_title.FontValidator() self._validators["side"] = v_title.SideValidator() self._validators["text"] = v_title.TextValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("side", None) self["side"] = side if side is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickformatstop(_BaseTraceHierarchyType): # dtickrange # ---------- @property def dtickrange(self): """ range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" The 'dtickrange' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'dtickrange[0]' property accepts values of any type (1) The 'dtickrange[1]' property accepts values of any type Returns ------- list """ return self["dtickrange"] @dtickrange.setter def dtickrange(self, val): self["dtickrange"] = val # enabled # ------- @property def enabled(self): """ Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. The 'enabled' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["enabled"] @enabled.setter def enabled(self, val): self["enabled"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # value # ----- @property def value(self): """ string - dtickformat for described zoom level, the same as "tickformat" The 'value' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "cone.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """ def __init__( self, arg=None, dtickrange=None, enabled=None, name=None, templateitemname=None, value=None, **kwargs ): """ Construct a new Tickformatstop object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.cone.colorbar.Tickformatstop dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- Tickformatstop """ super(Tickformatstop, self).__init__("tickformatstops") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.cone.colorbar.Tickformatstop constructor must be a dict or an instance of plotly.graph_objs.cone.colorbar.Tickformatstop""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.cone.colorbar import tickformatstop as v_tickformatstop # Initialize validators # --------------------- self._validators["dtickrange"] = v_tickformatstop.DtickrangeValidator() self._validators["enabled"] = v_tickformatstop.EnabledValidator() self._validators["name"] = v_tickformatstop.NameValidator() self._validators[ "templateitemname" ] = v_tickformatstop.TemplateitemnameValidator() self._validators["value"] = v_tickformatstop.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtickrange", None) self["dtickrange"] = dtickrange if dtickrange is not None else _v _v = arg.pop("enabled", None) self["enabled"] = enabled if enabled is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "cone.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Tickfont object Sets the color bar's tick label font Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.cone.colorbar.Tickfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Tickfont """ super(Tickfont, self).__init__("tickfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.cone.colorbar.Tickfont constructor must be a dict or an instance of plotly.graph_objs.cone.colorbar.Tickfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.cone.colorbar import tickfont as v_tickfont # Initialize validators # --------------------- self._validators["color"] = v_tickfont.ColorValidator() self._validators["family"] = v_tickfont.FamilyValidator() self._validators["size"] = v_tickfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Tickfont", "Tickformatstop", "Tickformatstop", "Title", "title"] from plotly.graph_objs.cone.colorbar import title plotly-4.4.1+dfsg.orig/plotly/graph_objs/cone/__init__.py0000644000175000017500000031413313573721547022772 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Stream(_BaseTraceHierarchyType): # maxpoints # --------- @property def maxpoints(self): """ Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. The 'maxpoints' property is a number and may be specified as: - An int or float in the interval [0, 10000] Returns ------- int|float """ return self["maxpoints"] @maxpoints.setter def maxpoints(self, val): self["maxpoints"] = val # token # ----- @property def token(self): """ The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. The 'token' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["token"] @token.setter def token(self, val): self["token"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "cone" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """ def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): """ Construct a new Stream object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.cone.Stream maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- Stream """ super(Stream, self).__init__("stream") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.cone.Stream constructor must be a dict or an instance of plotly.graph_objs.cone.Stream""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.cone import stream as v_stream # Initialize validators # --------------------- self._validators["maxpoints"] = v_stream.MaxpointsValidator() self._validators["token"] = v_stream.TokenValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("maxpoints", None) self["maxpoints"] = maxpoints if maxpoints is not None else _v _v = arg.pop("token", None) self["token"] = token if token is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Lightposition(_BaseTraceHierarchyType): # x # - @property def x(self): """ Numeric vector, representing the X coordinate for each vertex. The 'x' property is a number and may be specified as: - An int or float in the interval [-100000, 100000] Returns ------- int|float """ return self["x"] @x.setter def x(self, val): self["x"] = val # y # - @property def y(self): """ Numeric vector, representing the Y coordinate for each vertex. The 'y' property is a number and may be specified as: - An int or float in the interval [-100000, 100000] Returns ------- int|float """ return self["y"] @y.setter def y(self, val): self["y"] = val # z # - @property def z(self): """ Numeric vector, representing the Z coordinate for each vertex. The 'z' property is a number and may be specified as: - An int or float in the interval [-100000, 100000] Returns ------- int|float """ return self["z"] @z.setter def z(self, val): self["z"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "cone" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ x Numeric vector, representing the X coordinate for each vertex. y Numeric vector, representing the Y coordinate for each vertex. z Numeric vector, representing the Z coordinate for each vertex. """ def __init__(self, arg=None, x=None, y=None, z=None, **kwargs): """ Construct a new Lightposition object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.cone.Lightposition x Numeric vector, representing the X coordinate for each vertex. y Numeric vector, representing the Y coordinate for each vertex. z Numeric vector, representing the Z coordinate for each vertex. Returns ------- Lightposition """ super(Lightposition, self).__init__("lightposition") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.cone.Lightposition constructor must be a dict or an instance of plotly.graph_objs.cone.Lightposition""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.cone import lightposition as v_lightposition # Initialize validators # --------------------- self._validators["x"] = v_lightposition.XValidator() self._validators["y"] = v_lightposition.YValidator() self._validators["z"] = v_lightposition.ZValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("z", None) self["z"] = z if z is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Lighting(_BaseTraceHierarchyType): # ambient # ------- @property def ambient(self): """ Ambient light increases overall color visibility but can wash out the image. The 'ambient' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["ambient"] @ambient.setter def ambient(self, val): self["ambient"] = val # diffuse # ------- @property def diffuse(self): """ Represents the extent that incident rays are reflected in a range of angles. The 'diffuse' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["diffuse"] @diffuse.setter def diffuse(self, val): self["diffuse"] = val # facenormalsepsilon # ------------------ @property def facenormalsepsilon(self): """ Epsilon for face normals calculation avoids math issues arising from degenerate geometry. The 'facenormalsepsilon' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["facenormalsepsilon"] @facenormalsepsilon.setter def facenormalsepsilon(self, val): self["facenormalsepsilon"] = val # fresnel # ------- @property def fresnel(self): """ Represents the reflectance as a dependency of the viewing angle; e.g. paper is reflective when viewing it from the edge of the paper (almost 90 degrees), causing shine. The 'fresnel' property is a number and may be specified as: - An int or float in the interval [0, 5] Returns ------- int|float """ return self["fresnel"] @fresnel.setter def fresnel(self, val): self["fresnel"] = val # roughness # --------- @property def roughness(self): """ Alters specular reflection; the rougher the surface, the wider and less contrasty the shine. The 'roughness' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["roughness"] @roughness.setter def roughness(self, val): self["roughness"] = val # specular # -------- @property def specular(self): """ Represents the level that incident rays are reflected in a single direction, causing shine. The 'specular' property is a number and may be specified as: - An int or float in the interval [0, 2] Returns ------- int|float """ return self["specular"] @specular.setter def specular(self, val): self["specular"] = val # vertexnormalsepsilon # -------------------- @property def vertexnormalsepsilon(self): """ Epsilon for vertex normals calculation avoids math issues arising from degenerate geometry. The 'vertexnormalsepsilon' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["vertexnormalsepsilon"] @vertexnormalsepsilon.setter def vertexnormalsepsilon(self, val): self["vertexnormalsepsilon"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "cone" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ ambient Ambient light increases overall color visibility but can wash out the image. diffuse Represents the extent that incident rays are reflected in a range of angles. facenormalsepsilon Epsilon for face normals calculation avoids math issues arising from degenerate geometry. fresnel Represents the reflectance as a dependency of the viewing angle; e.g. paper is reflective when viewing it from the edge of the paper (almost 90 degrees), causing shine. roughness Alters specular reflection; the rougher the surface, the wider and less contrasty the shine. specular Represents the level that incident rays are reflected in a single direction, causing shine. vertexnormalsepsilon Epsilon for vertex normals calculation avoids math issues arising from degenerate geometry. """ def __init__( self, arg=None, ambient=None, diffuse=None, facenormalsepsilon=None, fresnel=None, roughness=None, specular=None, vertexnormalsepsilon=None, **kwargs ): """ Construct a new Lighting object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.cone.Lighting ambient Ambient light increases overall color visibility but can wash out the image. diffuse Represents the extent that incident rays are reflected in a range of angles. facenormalsepsilon Epsilon for face normals calculation avoids math issues arising from degenerate geometry. fresnel Represents the reflectance as a dependency of the viewing angle; e.g. paper is reflective when viewing it from the edge of the paper (almost 90 degrees), causing shine. roughness Alters specular reflection; the rougher the surface, the wider and less contrasty the shine. specular Represents the level that incident rays are reflected in a single direction, causing shine. vertexnormalsepsilon Epsilon for vertex normals calculation avoids math issues arising from degenerate geometry. Returns ------- Lighting """ super(Lighting, self).__init__("lighting") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.cone.Lighting constructor must be a dict or an instance of plotly.graph_objs.cone.Lighting""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.cone import lighting as v_lighting # Initialize validators # --------------------- self._validators["ambient"] = v_lighting.AmbientValidator() self._validators["diffuse"] = v_lighting.DiffuseValidator() self._validators[ "facenormalsepsilon" ] = v_lighting.FacenormalsepsilonValidator() self._validators["fresnel"] = v_lighting.FresnelValidator() self._validators["roughness"] = v_lighting.RoughnessValidator() self._validators["specular"] = v_lighting.SpecularValidator() self._validators[ "vertexnormalsepsilon" ] = v_lighting.VertexnormalsepsilonValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("ambient", None) self["ambient"] = ambient if ambient is not None else _v _v = arg.pop("diffuse", None) self["diffuse"] = diffuse if diffuse is not None else _v _v = arg.pop("facenormalsepsilon", None) self["facenormalsepsilon"] = ( facenormalsepsilon if facenormalsepsilon is not None else _v ) _v = arg.pop("fresnel", None) self["fresnel"] = fresnel if fresnel is not None else _v _v = arg.pop("roughness", None) self["roughness"] = roughness if roughness is not None else _v _v = arg.pop("specular", None) self["specular"] = specular if specular is not None else _v _v = arg.pop("vertexnormalsepsilon", None) self["vertexnormalsepsilon"] = ( vertexnormalsepsilon if vertexnormalsepsilon is not None else _v ) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Hoverlabel(_BaseTraceHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'right', 'auto'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["align"] @align.setter def align(self, val): self["align"] = val # alignsrc # -------- @property def alignsrc(self): """ Sets the source reference on plot.ly for align . The 'alignsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["alignsrc"] @alignsrc.setter def alignsrc(self, val): self["alignsrc"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the hover labels for this trace The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bgcolorsrc # ---------- @property def bgcolorsrc(self): """ Sets the source reference on plot.ly for bgcolor . The 'bgcolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bgcolorsrc"] @bgcolorsrc.setter def bgcolorsrc(self, val): self["bgcolorsrc"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the border color of the hover labels for this trace. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # bordercolorsrc # -------------- @property def bordercolorsrc(self): """ Sets the source reference on plot.ly for bordercolor . The 'bordercolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bordercolorsrc"] @bordercolorsrc.setter def bordercolorsrc(self, val): self["bordercolorsrc"] = val # font # ---- @property def font(self): """ Sets the font used in hover labels. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.cone.hoverlabel.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.cone.hoverlabel.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # namelength # ---------- @property def namelength(self): """ Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. The 'namelength' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [-1, 9223372036854775807] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|numpy.ndarray """ return self["namelength"] @namelength.setter def namelength(self, val): self["namelength"] = val # namelengthsrc # ------------- @property def namelengthsrc(self): """ Sets the source reference on plot.ly for namelength . The 'namelengthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["namelengthsrc"] @namelengthsrc.setter def namelengthsrc(self, val): self["namelengthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "cone" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """ def __init__( self, arg=None, align=None, alignsrc=None, bgcolor=None, bgcolorsrc=None, bordercolor=None, bordercolorsrc=None, font=None, namelength=None, namelengthsrc=None, **kwargs ): """ Construct a new Hoverlabel object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.cone.Hoverlabel align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- Hoverlabel """ super(Hoverlabel, self).__init__("hoverlabel") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.cone.Hoverlabel constructor must be a dict or an instance of plotly.graph_objs.cone.Hoverlabel""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.cone import hoverlabel as v_hoverlabel # Initialize validators # --------------------- self._validators["align"] = v_hoverlabel.AlignValidator() self._validators["alignsrc"] = v_hoverlabel.AlignsrcValidator() self._validators["bgcolor"] = v_hoverlabel.BgcolorValidator() self._validators["bgcolorsrc"] = v_hoverlabel.BgcolorsrcValidator() self._validators["bordercolor"] = v_hoverlabel.BordercolorValidator() self._validators["bordercolorsrc"] = v_hoverlabel.BordercolorsrcValidator() self._validators["font"] = v_hoverlabel.FontValidator() self._validators["namelength"] = v_hoverlabel.NamelengthValidator() self._validators["namelengthsrc"] = v_hoverlabel.NamelengthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("alignsrc", None) self["alignsrc"] = alignsrc if alignsrc is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bgcolorsrc", None) self["bgcolorsrc"] = bgcolorsrc if bgcolorsrc is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("bordercolorsrc", None) self["bordercolorsrc"] = bordercolorsrc if bordercolorsrc is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("namelength", None) self["namelength"] = namelength if namelength is not None else _v _v = arg.pop("namelengthsrc", None) self["namelengthsrc"] = namelengthsrc if namelengthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class ColorBar(_BaseTraceHierarchyType): # bgcolor # ------- @property def bgcolor(self): """ Sets the color of padded area. The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the axis line color. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # borderwidth # ----------- @property def borderwidth(self): """ Sets the width (in px) or the border enclosing this color bar. The 'borderwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["borderwidth"] @borderwidth.setter def borderwidth(self, val): self["borderwidth"] = val # dtick # ----- @property def dtick(self): """ Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" The 'dtick' property accepts values of any type Returns ------- Any """ return self["dtick"] @dtick.setter def dtick(self, val): self["dtick"] = val # exponentformat # -------------- @property def exponentformat(self): """ Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. The 'exponentformat' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'e', 'E', 'power', 'SI', 'B'] Returns ------- Any """ return self["exponentformat"] @exponentformat.setter def exponentformat(self, val): self["exponentformat"] = val # len # --- @property def len(self): """ Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. The 'len' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["len"] @len.setter def len(self, val): self["len"] = val # lenmode # ------- @property def lenmode(self): """ Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. The 'lenmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["lenmode"] @lenmode.setter def lenmode(self, val): self["lenmode"] = val # nticks # ------ @property def nticks(self): """ Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". The 'nticks' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nticks"] @nticks.setter def nticks(self, val): self["nticks"] = val # outlinecolor # ------------ @property def outlinecolor(self): """ Sets the axis line color. The 'outlinecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["outlinecolor"] @outlinecolor.setter def outlinecolor(self, val): self["outlinecolor"] = val # outlinewidth # ------------ @property def outlinewidth(self): """ Sets the width (in px) of the axis line. The 'outlinewidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["outlinewidth"] @outlinewidth.setter def outlinewidth(self, val): self["outlinewidth"] = val # separatethousands # ----------------- @property def separatethousands(self): """ If "true", even 4-digit integers are separated The 'separatethousands' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["separatethousands"] @separatethousands.setter def separatethousands(self, val): self["separatethousands"] = val # showexponent # ------------ @property def showexponent(self): """ If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. The 'showexponent' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showexponent"] @showexponent.setter def showexponent(self, val): self["showexponent"] = val # showticklabels # -------------- @property def showticklabels(self): """ Determines whether or not the tick labels are drawn. The 'showticklabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showticklabels"] @showticklabels.setter def showticklabels(self, val): self["showticklabels"] = val # showtickprefix # -------------- @property def showtickprefix(self): """ If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. The 'showtickprefix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showtickprefix"] @showtickprefix.setter def showtickprefix(self, val): self["showtickprefix"] = val # showticksuffix # -------------- @property def showticksuffix(self): """ Same as `showtickprefix` but for tick suffixes. The 'showticksuffix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showticksuffix"] @showticksuffix.setter def showticksuffix(self, val): self["showticksuffix"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # thicknessmode # ------------- @property def thicknessmode(self): """ Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. The 'thicknessmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["thicknessmode"] @thicknessmode.setter def thicknessmode(self, val): self["thicknessmode"] = val # tick0 # ----- @property def tick0(self): """ Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. The 'tick0' property accepts values of any type Returns ------- Any """ return self["tick0"] @tick0.setter def tick0(self, val): self["tick0"] = val # tickangle # --------- @property def tickangle(self): """ Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. The 'tickangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["tickangle"] @tickangle.setter def tickangle(self, val): self["tickangle"] = val # tickcolor # --------- @property def tickcolor(self): """ Sets the tick color. The 'tickcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["tickcolor"] @tickcolor.setter def tickcolor(self, val): self["tickcolor"] = val # tickfont # -------- @property def tickfont(self): """ Sets the color bar's tick label font The 'tickfont' property is an instance of Tickfont that may be specified as: - An instance of plotly.graph_objs.cone.colorbar.Tickfont - A dict of string/value properties that will be passed to the Tickfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.cone.colorbar.Tickfont """ return self["tickfont"] @tickfont.setter def tickfont(self, val): self["tickfont"] = val # tickformat # ---------- @property def tickformat(self): """ Sets the tick label formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'tickformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickformat"] @tickformat.setter def tickformat(self, val): self["tickformat"] = val # tickformatstops # --------------- @property def tickformatstops(self): """ The 'tickformatstops' property is a tuple of instances of Tickformatstop that may be specified as: - A list or tuple of instances of plotly.graph_objs.cone.colorbar.Tickformatstop - A list or tuple of dicts of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- tuple[plotly.graph_objs.cone.colorbar.Tickformatstop] """ return self["tickformatstops"] @tickformatstops.setter def tickformatstops(self, val): self["tickformatstops"] = val # tickformatstopdefaults # ---------------------- @property def tickformatstopdefaults(self): """ When used in a template (as layout.template.data.cone.colorbar.tickformatstopdefaults), sets the default property values to use for elements of cone.colorbar.tickformatstops The 'tickformatstopdefaults' property is an instance of Tickformatstop that may be specified as: - An instance of plotly.graph_objs.cone.colorbar.Tickformatstop - A dict of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: Returns ------- plotly.graph_objs.cone.colorbar.Tickformatstop """ return self["tickformatstopdefaults"] @tickformatstopdefaults.setter def tickformatstopdefaults(self, val): self["tickformatstopdefaults"] = val # ticklen # ------- @property def ticklen(self): """ Sets the tick length (in px). The 'ticklen' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ticklen"] @ticklen.setter def ticklen(self, val): self["ticklen"] = val # tickmode # -------- @property def tickmode(self): """ Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). The 'tickmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'linear', 'array'] Returns ------- Any """ return self["tickmode"] @tickmode.setter def tickmode(self, val): self["tickmode"] = val # tickprefix # ---------- @property def tickprefix(self): """ Sets a tick label prefix. The 'tickprefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickprefix"] @tickprefix.setter def tickprefix(self, val): self["tickprefix"] = val # ticks # ----- @property def ticks(self): """ Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. The 'ticks' property is an enumeration that may be specified as: - One of the following enumeration values: ['outside', 'inside', ''] Returns ------- Any """ return self["ticks"] @ticks.setter def ticks(self, val): self["ticks"] = val # ticksuffix # ---------- @property def ticksuffix(self): """ Sets a tick label suffix. The 'ticksuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ticksuffix"] @ticksuffix.setter def ticksuffix(self, val): self["ticksuffix"] = val # ticktext # -------- @property def ticktext(self): """ Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. The 'ticktext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ticktext"] @ticktext.setter def ticktext(self, val): self["ticktext"] = val # ticktextsrc # ----------- @property def ticktextsrc(self): """ Sets the source reference on plot.ly for ticktext . The 'ticktextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ticktextsrc"] @ticktextsrc.setter def ticktextsrc(self, val): self["ticktextsrc"] = val # tickvals # -------- @property def tickvals(self): """ Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. The 'tickvals' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["tickvals"] @tickvals.setter def tickvals(self, val): self["tickvals"] = val # tickvalssrc # ----------- @property def tickvalssrc(self): """ Sets the source reference on plot.ly for tickvals . The 'tickvalssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tickvalssrc"] @tickvalssrc.setter def tickvalssrc(self, val): self["tickvalssrc"] = val # tickwidth # --------- @property def tickwidth(self): """ Sets the tick width (in px). The 'tickwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["tickwidth"] @tickwidth.setter def tickwidth(self, val): self["tickwidth"] = val # title # ----- @property def title(self): """ The 'title' property is an instance of Title that may be specified as: - An instance of plotly.graph_objs.cone.colorbar.Title - A dict of string/value properties that will be passed to the Title constructor Supported dict properties: font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- plotly.graph_objs.cone.colorbar.Title """ return self["title"] @title.setter def title(self, val): self["title"] = val # titlefont # --------- @property def titlefont(self): """ Deprecated: Please use cone.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.cone.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- """ return self["titlefont"] @titlefont.setter def titlefont(self, val): self["titlefont"] = val # titleside # --------- @property def titleside(self): """ Deprecated: Please use cone.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- """ return self["titleside"] @titleside.setter def titleside(self, val): self["titleside"] = val # x # - @property def x(self): """ Sets the x position of the color bar (in plot fraction). The 'x' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["x"] @x.setter def x(self, val): self["x"] = val # xanchor # ------- @property def xanchor(self): """ Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. The 'xanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'center', 'right'] Returns ------- Any """ return self["xanchor"] @xanchor.setter def xanchor(self, val): self["xanchor"] = val # xpad # ---- @property def xpad(self): """ Sets the amount of padding (in px) along the x direction. The 'xpad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["xpad"] @xpad.setter def xpad(self, val): self["xpad"] = val # y # - @property def y(self): """ Sets the y position of the color bar (in plot fraction). The 'y' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["y"] @y.setter def y(self, val): self["y"] = val # yanchor # ------- @property def yanchor(self): """ Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. The 'yanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['top', 'middle', 'bottom'] Returns ------- Any """ return self["yanchor"] @yanchor.setter def yanchor(self, val): self["yanchor"] = val # ypad # ---- @property def ypad(self): """ Sets the amount of padding (in px) along the y direction. The 'ypad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ypad"] @ypad.setter def ypad(self, val): self["ypad"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "cone" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.cone.colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.cone.c olorbar.tickformatstopdefaults), sets the default property values to use for elements of cone.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.cone.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use cone.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use cone.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """ _mapped_properties = { "titlefont": ("title", "font"), "titleside": ("title", "side"), } def __init__( self, arg=None, bgcolor=None, bordercolor=None, borderwidth=None, dtick=None, exponentformat=None, len=None, lenmode=None, nticks=None, outlinecolor=None, outlinewidth=None, separatethousands=None, showexponent=None, showticklabels=None, showtickprefix=None, showticksuffix=None, thickness=None, thicknessmode=None, tick0=None, tickangle=None, tickcolor=None, tickfont=None, tickformat=None, tickformatstops=None, tickformatstopdefaults=None, ticklen=None, tickmode=None, tickprefix=None, ticks=None, ticksuffix=None, ticktext=None, ticktextsrc=None, tickvals=None, tickvalssrc=None, tickwidth=None, title=None, titlefont=None, titleside=None, x=None, xanchor=None, xpad=None, y=None, yanchor=None, ypad=None, **kwargs ): """ Construct a new ColorBar object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.cone.ColorBar bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.cone.colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.cone.c olorbar.tickformatstopdefaults), sets the default property values to use for elements of cone.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.cone.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use cone.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use cone.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- ColorBar """ super(ColorBar, self).__init__("colorbar") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.cone.ColorBar constructor must be a dict or an instance of plotly.graph_objs.cone.ColorBar""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.cone import colorbar as v_colorbar # Initialize validators # --------------------- self._validators["bgcolor"] = v_colorbar.BgcolorValidator() self._validators["bordercolor"] = v_colorbar.BordercolorValidator() self._validators["borderwidth"] = v_colorbar.BorderwidthValidator() self._validators["dtick"] = v_colorbar.DtickValidator() self._validators["exponentformat"] = v_colorbar.ExponentformatValidator() self._validators["len"] = v_colorbar.LenValidator() self._validators["lenmode"] = v_colorbar.LenmodeValidator() self._validators["nticks"] = v_colorbar.NticksValidator() self._validators["outlinecolor"] = v_colorbar.OutlinecolorValidator() self._validators["outlinewidth"] = v_colorbar.OutlinewidthValidator() self._validators["separatethousands"] = v_colorbar.SeparatethousandsValidator() self._validators["showexponent"] = v_colorbar.ShowexponentValidator() self._validators["showticklabels"] = v_colorbar.ShowticklabelsValidator() self._validators["showtickprefix"] = v_colorbar.ShowtickprefixValidator() self._validators["showticksuffix"] = v_colorbar.ShowticksuffixValidator() self._validators["thickness"] = v_colorbar.ThicknessValidator() self._validators["thicknessmode"] = v_colorbar.ThicknessmodeValidator() self._validators["tick0"] = v_colorbar.Tick0Validator() self._validators["tickangle"] = v_colorbar.TickangleValidator() self._validators["tickcolor"] = v_colorbar.TickcolorValidator() self._validators["tickfont"] = v_colorbar.TickfontValidator() self._validators["tickformat"] = v_colorbar.TickformatValidator() self._validators["tickformatstops"] = v_colorbar.TickformatstopsValidator() self._validators[ "tickformatstopdefaults" ] = v_colorbar.TickformatstopValidator() self._validators["ticklen"] = v_colorbar.TicklenValidator() self._validators["tickmode"] = v_colorbar.TickmodeValidator() self._validators["tickprefix"] = v_colorbar.TickprefixValidator() self._validators["ticks"] = v_colorbar.TicksValidator() self._validators["ticksuffix"] = v_colorbar.TicksuffixValidator() self._validators["ticktext"] = v_colorbar.TicktextValidator() self._validators["ticktextsrc"] = v_colorbar.TicktextsrcValidator() self._validators["tickvals"] = v_colorbar.TickvalsValidator() self._validators["tickvalssrc"] = v_colorbar.TickvalssrcValidator() self._validators["tickwidth"] = v_colorbar.TickwidthValidator() self._validators["title"] = v_colorbar.TitleValidator() self._validators["x"] = v_colorbar.XValidator() self._validators["xanchor"] = v_colorbar.XanchorValidator() self._validators["xpad"] = v_colorbar.XpadValidator() self._validators["y"] = v_colorbar.YValidator() self._validators["yanchor"] = v_colorbar.YanchorValidator() self._validators["ypad"] = v_colorbar.YpadValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("borderwidth", None) self["borderwidth"] = borderwidth if borderwidth is not None else _v _v = arg.pop("dtick", None) self["dtick"] = dtick if dtick is not None else _v _v = arg.pop("exponentformat", None) self["exponentformat"] = exponentformat if exponentformat is not None else _v _v = arg.pop("len", None) self["len"] = len if len is not None else _v _v = arg.pop("lenmode", None) self["lenmode"] = lenmode if lenmode is not None else _v _v = arg.pop("nticks", None) self["nticks"] = nticks if nticks is not None else _v _v = arg.pop("outlinecolor", None) self["outlinecolor"] = outlinecolor if outlinecolor is not None else _v _v = arg.pop("outlinewidth", None) self["outlinewidth"] = outlinewidth if outlinewidth is not None else _v _v = arg.pop("separatethousands", None) self["separatethousands"] = ( separatethousands if separatethousands is not None else _v ) _v = arg.pop("showexponent", None) self["showexponent"] = showexponent if showexponent is not None else _v _v = arg.pop("showticklabels", None) self["showticklabels"] = showticklabels if showticklabels is not None else _v _v = arg.pop("showtickprefix", None) self["showtickprefix"] = showtickprefix if showtickprefix is not None else _v _v = arg.pop("showticksuffix", None) self["showticksuffix"] = showticksuffix if showticksuffix is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("thicknessmode", None) self["thicknessmode"] = thicknessmode if thicknessmode is not None else _v _v = arg.pop("tick0", None) self["tick0"] = tick0 if tick0 is not None else _v _v = arg.pop("tickangle", None) self["tickangle"] = tickangle if tickangle is not None else _v _v = arg.pop("tickcolor", None) self["tickcolor"] = tickcolor if tickcolor is not None else _v _v = arg.pop("tickfont", None) self["tickfont"] = tickfont if tickfont is not None else _v _v = arg.pop("tickformat", None) self["tickformat"] = tickformat if tickformat is not None else _v _v = arg.pop("tickformatstops", None) self["tickformatstops"] = tickformatstops if tickformatstops is not None else _v _v = arg.pop("tickformatstopdefaults", None) self["tickformatstopdefaults"] = ( tickformatstopdefaults if tickformatstopdefaults is not None else _v ) _v = arg.pop("ticklen", None) self["ticklen"] = ticklen if ticklen is not None else _v _v = arg.pop("tickmode", None) self["tickmode"] = tickmode if tickmode is not None else _v _v = arg.pop("tickprefix", None) self["tickprefix"] = tickprefix if tickprefix is not None else _v _v = arg.pop("ticks", None) self["ticks"] = ticks if ticks is not None else _v _v = arg.pop("ticksuffix", None) self["ticksuffix"] = ticksuffix if ticksuffix is not None else _v _v = arg.pop("ticktext", None) self["ticktext"] = ticktext if ticktext is not None else _v _v = arg.pop("ticktextsrc", None) self["ticktextsrc"] = ticktextsrc if ticktextsrc is not None else _v _v = arg.pop("tickvals", None) self["tickvals"] = tickvals if tickvals is not None else _v _v = arg.pop("tickvalssrc", None) self["tickvalssrc"] = tickvalssrc if tickvalssrc is not None else _v _v = arg.pop("tickwidth", None) self["tickwidth"] = tickwidth if tickwidth is not None else _v _v = arg.pop("title", None) self["title"] = title if title is not None else _v _v = arg.pop("titlefont", None) _v = titlefont if titlefont is not None else _v if _v is not None: self["titlefont"] = _v _v = arg.pop("titleside", None) _v = titleside if titleside is not None else _v if _v is not None: self["titleside"] = _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xanchor", None) self["xanchor"] = xanchor if xanchor is not None else _v _v = arg.pop("xpad", None) self["xpad"] = xpad if xpad is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("yanchor", None) self["yanchor"] = yanchor if yanchor is not None else _v _v = arg.pop("ypad", None) self["ypad"] = ypad if ypad is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = [ "ColorBar", "Hoverlabel", "Lighting", "Lightposition", "Stream", "colorbar", "hoverlabel", ] from plotly.graph_objs.cone import hoverlabel from plotly.graph_objs.cone import colorbar plotly-4.4.1+dfsg.orig/plotly/graph_objs/streamtube/0000755000175000017500000000000013573746613022104 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/streamtube/hoverlabel/0000755000175000017500000000000013573746613024227 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/streamtube/hoverlabel/__init__.py0000644000175000017500000002545713573721552026350 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "streamtube.hoverlabel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Font object Sets the font used in hover labels. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.streamtube.hoverlabel.Font color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.streamtube.hoverlabel.Font constructor must be a dict or an instance of plotly.graph_objs.streamtube.hoverlabel.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.streamtube.hoverlabel import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["colorsrc"] = v_font.ColorsrcValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["familysrc"] = v_font.FamilysrcValidator() self._validators["size"] = v_font.SizeValidator() self._validators["sizesrc"] = v_font.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/streamtube/colorbar/0000755000175000017500000000000013573746613023707 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/streamtube/colorbar/title/0000755000175000017500000000000013573746613025030 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/streamtube/colorbar/title/__init__.py0000644000175000017500000002054413573721552027141 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "streamtube.colorbar.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.streamtube.colorbar.title.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.streamtube.colorbar.title.Font constructor must be a dict or an instance of plotly.graph_objs.streamtube.colorbar.title.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.streamtube.colorbar.title import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/streamtube/colorbar/__init__.py0000644000175000017500000006064413573721552026025 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Title(_BaseTraceHierarchyType): # font # ---- @property def font(self): """ Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.streamtube.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.streamtube.colorbar.title.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # side # ---- @property def side(self): """ Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- Any """ return self["side"] @side.setter def side(self, val): self["side"] = val # text # ---- @property def text(self): """ Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "streamtube.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """ def __init__(self, arg=None, font=None, side=None, text=None, **kwargs): """ Construct a new Title object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.streamtube.colorbar.Title font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- Title """ super(Title, self).__init__("title") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.streamtube.colorbar.Title constructor must be a dict or an instance of plotly.graph_objs.streamtube.colorbar.Title""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.streamtube.colorbar import title as v_title # Initialize validators # --------------------- self._validators["font"] = v_title.FontValidator() self._validators["side"] = v_title.SideValidator() self._validators["text"] = v_title.TextValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("side", None) self["side"] = side if side is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickformatstop(_BaseTraceHierarchyType): # dtickrange # ---------- @property def dtickrange(self): """ range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" The 'dtickrange' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'dtickrange[0]' property accepts values of any type (1) The 'dtickrange[1]' property accepts values of any type Returns ------- list """ return self["dtickrange"] @dtickrange.setter def dtickrange(self, val): self["dtickrange"] = val # enabled # ------- @property def enabled(self): """ Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. The 'enabled' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["enabled"] @enabled.setter def enabled(self, val): self["enabled"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # value # ----- @property def value(self): """ string - dtickformat for described zoom level, the same as "tickformat" The 'value' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "streamtube.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """ def __init__( self, arg=None, dtickrange=None, enabled=None, name=None, templateitemname=None, value=None, **kwargs ): """ Construct a new Tickformatstop object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.streamtube.colorbar.Tickformatstop dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- Tickformatstop """ super(Tickformatstop, self).__init__("tickformatstops") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.streamtube.colorbar.Tickformatstop constructor must be a dict or an instance of plotly.graph_objs.streamtube.colorbar.Tickformatstop""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.streamtube.colorbar import ( tickformatstop as v_tickformatstop, ) # Initialize validators # --------------------- self._validators["dtickrange"] = v_tickformatstop.DtickrangeValidator() self._validators["enabled"] = v_tickformatstop.EnabledValidator() self._validators["name"] = v_tickformatstop.NameValidator() self._validators[ "templateitemname" ] = v_tickformatstop.TemplateitemnameValidator() self._validators["value"] = v_tickformatstop.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtickrange", None) self["dtickrange"] = dtickrange if dtickrange is not None else _v _v = arg.pop("enabled", None) self["enabled"] = enabled if enabled is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "streamtube.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Tickfont object Sets the color bar's tick label font Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.streamtube.colorbar.Tickfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Tickfont """ super(Tickfont, self).__init__("tickfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.streamtube.colorbar.Tickfont constructor must be a dict or an instance of plotly.graph_objs.streamtube.colorbar.Tickfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.streamtube.colorbar import tickfont as v_tickfont # Initialize validators # --------------------- self._validators["color"] = v_tickfont.ColorValidator() self._validators["family"] = v_tickfont.FamilyValidator() self._validators["size"] = v_tickfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Tickfont", "Tickformatstop", "Tickformatstop", "Title", "title"] from plotly.graph_objs.streamtube.colorbar import title plotly-4.4.1+dfsg.orig/plotly/graph_objs/streamtube/__init__.py0000644000175000017500000033115413573721553024220 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Stream(_BaseTraceHierarchyType): # maxpoints # --------- @property def maxpoints(self): """ Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. The 'maxpoints' property is a number and may be specified as: - An int or float in the interval [0, 10000] Returns ------- int|float """ return self["maxpoints"] @maxpoints.setter def maxpoints(self, val): self["maxpoints"] = val # token # ----- @property def token(self): """ The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. The 'token' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["token"] @token.setter def token(self, val): self["token"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "streamtube" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """ def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): """ Construct a new Stream object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.streamtube.Stream maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- Stream """ super(Stream, self).__init__("stream") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.streamtube.Stream constructor must be a dict or an instance of plotly.graph_objs.streamtube.Stream""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.streamtube import stream as v_stream # Initialize validators # --------------------- self._validators["maxpoints"] = v_stream.MaxpointsValidator() self._validators["token"] = v_stream.TokenValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("maxpoints", None) self["maxpoints"] = maxpoints if maxpoints is not None else _v _v = arg.pop("token", None) self["token"] = token if token is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Starts(_BaseTraceHierarchyType): # x # - @property def x(self): """ Sets the x components of the starting position of the streamtubes The 'x' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["x"] @x.setter def x(self, val): self["x"] = val # xsrc # ---- @property def xsrc(self): """ Sets the source reference on plot.ly for x . The 'xsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["xsrc"] @xsrc.setter def xsrc(self, val): self["xsrc"] = val # y # - @property def y(self): """ Sets the y components of the starting position of the streamtubes The 'y' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["y"] @y.setter def y(self, val): self["y"] = val # ysrc # ---- @property def ysrc(self): """ Sets the source reference on plot.ly for y . The 'ysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ysrc"] @ysrc.setter def ysrc(self, val): self["ysrc"] = val # z # - @property def z(self): """ Sets the z components of the starting position of the streamtubes The 'z' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["z"] @z.setter def z(self, val): self["z"] = val # zsrc # ---- @property def zsrc(self): """ Sets the source reference on plot.ly for z . The 'zsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["zsrc"] @zsrc.setter def zsrc(self, val): self["zsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "streamtube" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ x Sets the x components of the starting position of the streamtubes xsrc Sets the source reference on plot.ly for x . y Sets the y components of the starting position of the streamtubes ysrc Sets the source reference on plot.ly for y . z Sets the z components of the starting position of the streamtubes zsrc Sets the source reference on plot.ly for z . """ def __init__( self, arg=None, x=None, xsrc=None, y=None, ysrc=None, z=None, zsrc=None, **kwargs ): """ Construct a new Starts object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.streamtube.Starts x Sets the x components of the starting position of the streamtubes xsrc Sets the source reference on plot.ly for x . y Sets the y components of the starting position of the streamtubes ysrc Sets the source reference on plot.ly for y . z Sets the z components of the starting position of the streamtubes zsrc Sets the source reference on plot.ly for z . Returns ------- Starts """ super(Starts, self).__init__("starts") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.streamtube.Starts constructor must be a dict or an instance of plotly.graph_objs.streamtube.Starts""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.streamtube import starts as v_starts # Initialize validators # --------------------- self._validators["x"] = v_starts.XValidator() self._validators["xsrc"] = v_starts.XsrcValidator() self._validators["y"] = v_starts.YValidator() self._validators["ysrc"] = v_starts.YsrcValidator() self._validators["z"] = v_starts.ZValidator() self._validators["zsrc"] = v_starts.ZsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xsrc", None) self["xsrc"] = xsrc if xsrc is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("ysrc", None) self["ysrc"] = ysrc if ysrc is not None else _v _v = arg.pop("z", None) self["z"] = z if z is not None else _v _v = arg.pop("zsrc", None) self["zsrc"] = zsrc if zsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Lightposition(_BaseTraceHierarchyType): # x # - @property def x(self): """ Numeric vector, representing the X coordinate for each vertex. The 'x' property is a number and may be specified as: - An int or float in the interval [-100000, 100000] Returns ------- int|float """ return self["x"] @x.setter def x(self, val): self["x"] = val # y # - @property def y(self): """ Numeric vector, representing the Y coordinate for each vertex. The 'y' property is a number and may be specified as: - An int or float in the interval [-100000, 100000] Returns ------- int|float """ return self["y"] @y.setter def y(self, val): self["y"] = val # z # - @property def z(self): """ Numeric vector, representing the Z coordinate for each vertex. The 'z' property is a number and may be specified as: - An int or float in the interval [-100000, 100000] Returns ------- int|float """ return self["z"] @z.setter def z(self, val): self["z"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "streamtube" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ x Numeric vector, representing the X coordinate for each vertex. y Numeric vector, representing the Y coordinate for each vertex. z Numeric vector, representing the Z coordinate for each vertex. """ def __init__(self, arg=None, x=None, y=None, z=None, **kwargs): """ Construct a new Lightposition object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.streamtube.Lightposition x Numeric vector, representing the X coordinate for each vertex. y Numeric vector, representing the Y coordinate for each vertex. z Numeric vector, representing the Z coordinate for each vertex. Returns ------- Lightposition """ super(Lightposition, self).__init__("lightposition") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.streamtube.Lightposition constructor must be a dict or an instance of plotly.graph_objs.streamtube.Lightposition""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.streamtube import lightposition as v_lightposition # Initialize validators # --------------------- self._validators["x"] = v_lightposition.XValidator() self._validators["y"] = v_lightposition.YValidator() self._validators["z"] = v_lightposition.ZValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("z", None) self["z"] = z if z is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Lighting(_BaseTraceHierarchyType): # ambient # ------- @property def ambient(self): """ Ambient light increases overall color visibility but can wash out the image. The 'ambient' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["ambient"] @ambient.setter def ambient(self, val): self["ambient"] = val # diffuse # ------- @property def diffuse(self): """ Represents the extent that incident rays are reflected in a range of angles. The 'diffuse' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["diffuse"] @diffuse.setter def diffuse(self, val): self["diffuse"] = val # facenormalsepsilon # ------------------ @property def facenormalsepsilon(self): """ Epsilon for face normals calculation avoids math issues arising from degenerate geometry. The 'facenormalsepsilon' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["facenormalsepsilon"] @facenormalsepsilon.setter def facenormalsepsilon(self, val): self["facenormalsepsilon"] = val # fresnel # ------- @property def fresnel(self): """ Represents the reflectance as a dependency of the viewing angle; e.g. paper is reflective when viewing it from the edge of the paper (almost 90 degrees), causing shine. The 'fresnel' property is a number and may be specified as: - An int or float in the interval [0, 5] Returns ------- int|float """ return self["fresnel"] @fresnel.setter def fresnel(self, val): self["fresnel"] = val # roughness # --------- @property def roughness(self): """ Alters specular reflection; the rougher the surface, the wider and less contrasty the shine. The 'roughness' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["roughness"] @roughness.setter def roughness(self, val): self["roughness"] = val # specular # -------- @property def specular(self): """ Represents the level that incident rays are reflected in a single direction, causing shine. The 'specular' property is a number and may be specified as: - An int or float in the interval [0, 2] Returns ------- int|float """ return self["specular"] @specular.setter def specular(self, val): self["specular"] = val # vertexnormalsepsilon # -------------------- @property def vertexnormalsepsilon(self): """ Epsilon for vertex normals calculation avoids math issues arising from degenerate geometry. The 'vertexnormalsepsilon' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["vertexnormalsepsilon"] @vertexnormalsepsilon.setter def vertexnormalsepsilon(self, val): self["vertexnormalsepsilon"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "streamtube" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ ambient Ambient light increases overall color visibility but can wash out the image. diffuse Represents the extent that incident rays are reflected in a range of angles. facenormalsepsilon Epsilon for face normals calculation avoids math issues arising from degenerate geometry. fresnel Represents the reflectance as a dependency of the viewing angle; e.g. paper is reflective when viewing it from the edge of the paper (almost 90 degrees), causing shine. roughness Alters specular reflection; the rougher the surface, the wider and less contrasty the shine. specular Represents the level that incident rays are reflected in a single direction, causing shine. vertexnormalsepsilon Epsilon for vertex normals calculation avoids math issues arising from degenerate geometry. """ def __init__( self, arg=None, ambient=None, diffuse=None, facenormalsepsilon=None, fresnel=None, roughness=None, specular=None, vertexnormalsepsilon=None, **kwargs ): """ Construct a new Lighting object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.streamtube.Lighting ambient Ambient light increases overall color visibility but can wash out the image. diffuse Represents the extent that incident rays are reflected in a range of angles. facenormalsepsilon Epsilon for face normals calculation avoids math issues arising from degenerate geometry. fresnel Represents the reflectance as a dependency of the viewing angle; e.g. paper is reflective when viewing it from the edge of the paper (almost 90 degrees), causing shine. roughness Alters specular reflection; the rougher the surface, the wider and less contrasty the shine. specular Represents the level that incident rays are reflected in a single direction, causing shine. vertexnormalsepsilon Epsilon for vertex normals calculation avoids math issues arising from degenerate geometry. Returns ------- Lighting """ super(Lighting, self).__init__("lighting") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.streamtube.Lighting constructor must be a dict or an instance of plotly.graph_objs.streamtube.Lighting""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.streamtube import lighting as v_lighting # Initialize validators # --------------------- self._validators["ambient"] = v_lighting.AmbientValidator() self._validators["diffuse"] = v_lighting.DiffuseValidator() self._validators[ "facenormalsepsilon" ] = v_lighting.FacenormalsepsilonValidator() self._validators["fresnel"] = v_lighting.FresnelValidator() self._validators["roughness"] = v_lighting.RoughnessValidator() self._validators["specular"] = v_lighting.SpecularValidator() self._validators[ "vertexnormalsepsilon" ] = v_lighting.VertexnormalsepsilonValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("ambient", None) self["ambient"] = ambient if ambient is not None else _v _v = arg.pop("diffuse", None) self["diffuse"] = diffuse if diffuse is not None else _v _v = arg.pop("facenormalsepsilon", None) self["facenormalsepsilon"] = ( facenormalsepsilon if facenormalsepsilon is not None else _v ) _v = arg.pop("fresnel", None) self["fresnel"] = fresnel if fresnel is not None else _v _v = arg.pop("roughness", None) self["roughness"] = roughness if roughness is not None else _v _v = arg.pop("specular", None) self["specular"] = specular if specular is not None else _v _v = arg.pop("vertexnormalsepsilon", None) self["vertexnormalsepsilon"] = ( vertexnormalsepsilon if vertexnormalsepsilon is not None else _v ) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Hoverlabel(_BaseTraceHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'right', 'auto'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["align"] @align.setter def align(self, val): self["align"] = val # alignsrc # -------- @property def alignsrc(self): """ Sets the source reference on plot.ly for align . The 'alignsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["alignsrc"] @alignsrc.setter def alignsrc(self, val): self["alignsrc"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the hover labels for this trace The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bgcolorsrc # ---------- @property def bgcolorsrc(self): """ Sets the source reference on plot.ly for bgcolor . The 'bgcolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bgcolorsrc"] @bgcolorsrc.setter def bgcolorsrc(self, val): self["bgcolorsrc"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the border color of the hover labels for this trace. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # bordercolorsrc # -------------- @property def bordercolorsrc(self): """ Sets the source reference on plot.ly for bordercolor . The 'bordercolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bordercolorsrc"] @bordercolorsrc.setter def bordercolorsrc(self, val): self["bordercolorsrc"] = val # font # ---- @property def font(self): """ Sets the font used in hover labels. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.streamtube.hoverlabel.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.streamtube.hoverlabel.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # namelength # ---------- @property def namelength(self): """ Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. The 'namelength' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [-1, 9223372036854775807] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|numpy.ndarray """ return self["namelength"] @namelength.setter def namelength(self, val): self["namelength"] = val # namelengthsrc # ------------- @property def namelengthsrc(self): """ Sets the source reference on plot.ly for namelength . The 'namelengthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["namelengthsrc"] @namelengthsrc.setter def namelengthsrc(self, val): self["namelengthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "streamtube" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """ def __init__( self, arg=None, align=None, alignsrc=None, bgcolor=None, bgcolorsrc=None, bordercolor=None, bordercolorsrc=None, font=None, namelength=None, namelengthsrc=None, **kwargs ): """ Construct a new Hoverlabel object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.streamtube.Hoverlabel align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- Hoverlabel """ super(Hoverlabel, self).__init__("hoverlabel") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.streamtube.Hoverlabel constructor must be a dict or an instance of plotly.graph_objs.streamtube.Hoverlabel""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.streamtube import hoverlabel as v_hoverlabel # Initialize validators # --------------------- self._validators["align"] = v_hoverlabel.AlignValidator() self._validators["alignsrc"] = v_hoverlabel.AlignsrcValidator() self._validators["bgcolor"] = v_hoverlabel.BgcolorValidator() self._validators["bgcolorsrc"] = v_hoverlabel.BgcolorsrcValidator() self._validators["bordercolor"] = v_hoverlabel.BordercolorValidator() self._validators["bordercolorsrc"] = v_hoverlabel.BordercolorsrcValidator() self._validators["font"] = v_hoverlabel.FontValidator() self._validators["namelength"] = v_hoverlabel.NamelengthValidator() self._validators["namelengthsrc"] = v_hoverlabel.NamelengthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("alignsrc", None) self["alignsrc"] = alignsrc if alignsrc is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bgcolorsrc", None) self["bgcolorsrc"] = bgcolorsrc if bgcolorsrc is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("bordercolorsrc", None) self["bordercolorsrc"] = bordercolorsrc if bordercolorsrc is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("namelength", None) self["namelength"] = namelength if namelength is not None else _v _v = arg.pop("namelengthsrc", None) self["namelengthsrc"] = namelengthsrc if namelengthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class ColorBar(_BaseTraceHierarchyType): # bgcolor # ------- @property def bgcolor(self): """ Sets the color of padded area. The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the axis line color. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # borderwidth # ----------- @property def borderwidth(self): """ Sets the width (in px) or the border enclosing this color bar. The 'borderwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["borderwidth"] @borderwidth.setter def borderwidth(self, val): self["borderwidth"] = val # dtick # ----- @property def dtick(self): """ Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" The 'dtick' property accepts values of any type Returns ------- Any """ return self["dtick"] @dtick.setter def dtick(self, val): self["dtick"] = val # exponentformat # -------------- @property def exponentformat(self): """ Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. The 'exponentformat' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'e', 'E', 'power', 'SI', 'B'] Returns ------- Any """ return self["exponentformat"] @exponentformat.setter def exponentformat(self, val): self["exponentformat"] = val # len # --- @property def len(self): """ Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. The 'len' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["len"] @len.setter def len(self, val): self["len"] = val # lenmode # ------- @property def lenmode(self): """ Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. The 'lenmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["lenmode"] @lenmode.setter def lenmode(self, val): self["lenmode"] = val # nticks # ------ @property def nticks(self): """ Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". The 'nticks' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nticks"] @nticks.setter def nticks(self, val): self["nticks"] = val # outlinecolor # ------------ @property def outlinecolor(self): """ Sets the axis line color. The 'outlinecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["outlinecolor"] @outlinecolor.setter def outlinecolor(self, val): self["outlinecolor"] = val # outlinewidth # ------------ @property def outlinewidth(self): """ Sets the width (in px) of the axis line. The 'outlinewidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["outlinewidth"] @outlinewidth.setter def outlinewidth(self, val): self["outlinewidth"] = val # separatethousands # ----------------- @property def separatethousands(self): """ If "true", even 4-digit integers are separated The 'separatethousands' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["separatethousands"] @separatethousands.setter def separatethousands(self, val): self["separatethousands"] = val # showexponent # ------------ @property def showexponent(self): """ If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. The 'showexponent' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showexponent"] @showexponent.setter def showexponent(self, val): self["showexponent"] = val # showticklabels # -------------- @property def showticklabels(self): """ Determines whether or not the tick labels are drawn. The 'showticklabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showticklabels"] @showticklabels.setter def showticklabels(self, val): self["showticklabels"] = val # showtickprefix # -------------- @property def showtickprefix(self): """ If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. The 'showtickprefix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showtickprefix"] @showtickprefix.setter def showtickprefix(self, val): self["showtickprefix"] = val # showticksuffix # -------------- @property def showticksuffix(self): """ Same as `showtickprefix` but for tick suffixes. The 'showticksuffix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showticksuffix"] @showticksuffix.setter def showticksuffix(self, val): self["showticksuffix"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # thicknessmode # ------------- @property def thicknessmode(self): """ Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. The 'thicknessmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["thicknessmode"] @thicknessmode.setter def thicknessmode(self, val): self["thicknessmode"] = val # tick0 # ----- @property def tick0(self): """ Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. The 'tick0' property accepts values of any type Returns ------- Any """ return self["tick0"] @tick0.setter def tick0(self, val): self["tick0"] = val # tickangle # --------- @property def tickangle(self): """ Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. The 'tickangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["tickangle"] @tickangle.setter def tickangle(self, val): self["tickangle"] = val # tickcolor # --------- @property def tickcolor(self): """ Sets the tick color. The 'tickcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["tickcolor"] @tickcolor.setter def tickcolor(self, val): self["tickcolor"] = val # tickfont # -------- @property def tickfont(self): """ Sets the color bar's tick label font The 'tickfont' property is an instance of Tickfont that may be specified as: - An instance of plotly.graph_objs.streamtube.colorbar.Tickfont - A dict of string/value properties that will be passed to the Tickfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.streamtube.colorbar.Tickfont """ return self["tickfont"] @tickfont.setter def tickfont(self, val): self["tickfont"] = val # tickformat # ---------- @property def tickformat(self): """ Sets the tick label formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'tickformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickformat"] @tickformat.setter def tickformat(self, val): self["tickformat"] = val # tickformatstops # --------------- @property def tickformatstops(self): """ The 'tickformatstops' property is a tuple of instances of Tickformatstop that may be specified as: - A list or tuple of instances of plotly.graph_objs.streamtube.colorbar.Tickformatstop - A list or tuple of dicts of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- tuple[plotly.graph_objs.streamtube.colorbar.Tickformatstop] """ return self["tickformatstops"] @tickformatstops.setter def tickformatstops(self, val): self["tickformatstops"] = val # tickformatstopdefaults # ---------------------- @property def tickformatstopdefaults(self): """ When used in a template (as layout.template.data.streamtube.col orbar.tickformatstopdefaults), sets the default property values to use for elements of streamtube.colorbar.tickformatstops The 'tickformatstopdefaults' property is an instance of Tickformatstop that may be specified as: - An instance of plotly.graph_objs.streamtube.colorbar.Tickformatstop - A dict of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: Returns ------- plotly.graph_objs.streamtube.colorbar.Tickformatstop """ return self["tickformatstopdefaults"] @tickformatstopdefaults.setter def tickformatstopdefaults(self, val): self["tickformatstopdefaults"] = val # ticklen # ------- @property def ticklen(self): """ Sets the tick length (in px). The 'ticklen' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ticklen"] @ticklen.setter def ticklen(self, val): self["ticklen"] = val # tickmode # -------- @property def tickmode(self): """ Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). The 'tickmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'linear', 'array'] Returns ------- Any """ return self["tickmode"] @tickmode.setter def tickmode(self, val): self["tickmode"] = val # tickprefix # ---------- @property def tickprefix(self): """ Sets a tick label prefix. The 'tickprefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickprefix"] @tickprefix.setter def tickprefix(self, val): self["tickprefix"] = val # ticks # ----- @property def ticks(self): """ Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. The 'ticks' property is an enumeration that may be specified as: - One of the following enumeration values: ['outside', 'inside', ''] Returns ------- Any """ return self["ticks"] @ticks.setter def ticks(self, val): self["ticks"] = val # ticksuffix # ---------- @property def ticksuffix(self): """ Sets a tick label suffix. The 'ticksuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ticksuffix"] @ticksuffix.setter def ticksuffix(self, val): self["ticksuffix"] = val # ticktext # -------- @property def ticktext(self): """ Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. The 'ticktext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ticktext"] @ticktext.setter def ticktext(self, val): self["ticktext"] = val # ticktextsrc # ----------- @property def ticktextsrc(self): """ Sets the source reference on plot.ly for ticktext . The 'ticktextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ticktextsrc"] @ticktextsrc.setter def ticktextsrc(self, val): self["ticktextsrc"] = val # tickvals # -------- @property def tickvals(self): """ Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. The 'tickvals' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["tickvals"] @tickvals.setter def tickvals(self, val): self["tickvals"] = val # tickvalssrc # ----------- @property def tickvalssrc(self): """ Sets the source reference on plot.ly for tickvals . The 'tickvalssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tickvalssrc"] @tickvalssrc.setter def tickvalssrc(self, val): self["tickvalssrc"] = val # tickwidth # --------- @property def tickwidth(self): """ Sets the tick width (in px). The 'tickwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["tickwidth"] @tickwidth.setter def tickwidth(self, val): self["tickwidth"] = val # title # ----- @property def title(self): """ The 'title' property is an instance of Title that may be specified as: - An instance of plotly.graph_objs.streamtube.colorbar.Title - A dict of string/value properties that will be passed to the Title constructor Supported dict properties: font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- plotly.graph_objs.streamtube.colorbar.Title """ return self["title"] @title.setter def title(self, val): self["title"] = val # titlefont # --------- @property def titlefont(self): """ Deprecated: Please use streamtube.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.streamtube.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- """ return self["titlefont"] @titlefont.setter def titlefont(self, val): self["titlefont"] = val # titleside # --------- @property def titleside(self): """ Deprecated: Please use streamtube.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- """ return self["titleside"] @titleside.setter def titleside(self, val): self["titleside"] = val # x # - @property def x(self): """ Sets the x position of the color bar (in plot fraction). The 'x' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["x"] @x.setter def x(self, val): self["x"] = val # xanchor # ------- @property def xanchor(self): """ Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. The 'xanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'center', 'right'] Returns ------- Any """ return self["xanchor"] @xanchor.setter def xanchor(self, val): self["xanchor"] = val # xpad # ---- @property def xpad(self): """ Sets the amount of padding (in px) along the x direction. The 'xpad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["xpad"] @xpad.setter def xpad(self, val): self["xpad"] = val # y # - @property def y(self): """ Sets the y position of the color bar (in plot fraction). The 'y' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["y"] @y.setter def y(self, val): self["y"] = val # yanchor # ------- @property def yanchor(self): """ Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. The 'yanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['top', 'middle', 'bottom'] Returns ------- Any """ return self["yanchor"] @yanchor.setter def yanchor(self, val): self["yanchor"] = val # ypad # ---- @property def ypad(self): """ Sets the amount of padding (in px) along the y direction. The 'ypad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ypad"] @ypad.setter def ypad(self, val): self["ypad"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "streamtube" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.streamtube.colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.stream tube.colorbar.tickformatstopdefaults), sets the default property values to use for elements of streamtube.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.streamtube.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use streamtube.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use streamtube.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """ _mapped_properties = { "titlefont": ("title", "font"), "titleside": ("title", "side"), } def __init__( self, arg=None, bgcolor=None, bordercolor=None, borderwidth=None, dtick=None, exponentformat=None, len=None, lenmode=None, nticks=None, outlinecolor=None, outlinewidth=None, separatethousands=None, showexponent=None, showticklabels=None, showtickprefix=None, showticksuffix=None, thickness=None, thicknessmode=None, tick0=None, tickangle=None, tickcolor=None, tickfont=None, tickformat=None, tickformatstops=None, tickformatstopdefaults=None, ticklen=None, tickmode=None, tickprefix=None, ticks=None, ticksuffix=None, ticktext=None, ticktextsrc=None, tickvals=None, tickvalssrc=None, tickwidth=None, title=None, titlefont=None, titleside=None, x=None, xanchor=None, xpad=None, y=None, yanchor=None, ypad=None, **kwargs ): """ Construct a new ColorBar object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.streamtube.ColorBar bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.streamtube.colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.stream tube.colorbar.tickformatstopdefaults), sets the default property values to use for elements of streamtube.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.streamtube.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use streamtube.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use streamtube.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- ColorBar """ super(ColorBar, self).__init__("colorbar") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.streamtube.ColorBar constructor must be a dict or an instance of plotly.graph_objs.streamtube.ColorBar""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.streamtube import colorbar as v_colorbar # Initialize validators # --------------------- self._validators["bgcolor"] = v_colorbar.BgcolorValidator() self._validators["bordercolor"] = v_colorbar.BordercolorValidator() self._validators["borderwidth"] = v_colorbar.BorderwidthValidator() self._validators["dtick"] = v_colorbar.DtickValidator() self._validators["exponentformat"] = v_colorbar.ExponentformatValidator() self._validators["len"] = v_colorbar.LenValidator() self._validators["lenmode"] = v_colorbar.LenmodeValidator() self._validators["nticks"] = v_colorbar.NticksValidator() self._validators["outlinecolor"] = v_colorbar.OutlinecolorValidator() self._validators["outlinewidth"] = v_colorbar.OutlinewidthValidator() self._validators["separatethousands"] = v_colorbar.SeparatethousandsValidator() self._validators["showexponent"] = v_colorbar.ShowexponentValidator() self._validators["showticklabels"] = v_colorbar.ShowticklabelsValidator() self._validators["showtickprefix"] = v_colorbar.ShowtickprefixValidator() self._validators["showticksuffix"] = v_colorbar.ShowticksuffixValidator() self._validators["thickness"] = v_colorbar.ThicknessValidator() self._validators["thicknessmode"] = v_colorbar.ThicknessmodeValidator() self._validators["tick0"] = v_colorbar.Tick0Validator() self._validators["tickangle"] = v_colorbar.TickangleValidator() self._validators["tickcolor"] = v_colorbar.TickcolorValidator() self._validators["tickfont"] = v_colorbar.TickfontValidator() self._validators["tickformat"] = v_colorbar.TickformatValidator() self._validators["tickformatstops"] = v_colorbar.TickformatstopsValidator() self._validators[ "tickformatstopdefaults" ] = v_colorbar.TickformatstopValidator() self._validators["ticklen"] = v_colorbar.TicklenValidator() self._validators["tickmode"] = v_colorbar.TickmodeValidator() self._validators["tickprefix"] = v_colorbar.TickprefixValidator() self._validators["ticks"] = v_colorbar.TicksValidator() self._validators["ticksuffix"] = v_colorbar.TicksuffixValidator() self._validators["ticktext"] = v_colorbar.TicktextValidator() self._validators["ticktextsrc"] = v_colorbar.TicktextsrcValidator() self._validators["tickvals"] = v_colorbar.TickvalsValidator() self._validators["tickvalssrc"] = v_colorbar.TickvalssrcValidator() self._validators["tickwidth"] = v_colorbar.TickwidthValidator() self._validators["title"] = v_colorbar.TitleValidator() self._validators["x"] = v_colorbar.XValidator() self._validators["xanchor"] = v_colorbar.XanchorValidator() self._validators["xpad"] = v_colorbar.XpadValidator() self._validators["y"] = v_colorbar.YValidator() self._validators["yanchor"] = v_colorbar.YanchorValidator() self._validators["ypad"] = v_colorbar.YpadValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("borderwidth", None) self["borderwidth"] = borderwidth if borderwidth is not None else _v _v = arg.pop("dtick", None) self["dtick"] = dtick if dtick is not None else _v _v = arg.pop("exponentformat", None) self["exponentformat"] = exponentformat if exponentformat is not None else _v _v = arg.pop("len", None) self["len"] = len if len is not None else _v _v = arg.pop("lenmode", None) self["lenmode"] = lenmode if lenmode is not None else _v _v = arg.pop("nticks", None) self["nticks"] = nticks if nticks is not None else _v _v = arg.pop("outlinecolor", None) self["outlinecolor"] = outlinecolor if outlinecolor is not None else _v _v = arg.pop("outlinewidth", None) self["outlinewidth"] = outlinewidth if outlinewidth is not None else _v _v = arg.pop("separatethousands", None) self["separatethousands"] = ( separatethousands if separatethousands is not None else _v ) _v = arg.pop("showexponent", None) self["showexponent"] = showexponent if showexponent is not None else _v _v = arg.pop("showticklabels", None) self["showticklabels"] = showticklabels if showticklabels is not None else _v _v = arg.pop("showtickprefix", None) self["showtickprefix"] = showtickprefix if showtickprefix is not None else _v _v = arg.pop("showticksuffix", None) self["showticksuffix"] = showticksuffix if showticksuffix is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("thicknessmode", None) self["thicknessmode"] = thicknessmode if thicknessmode is not None else _v _v = arg.pop("tick0", None) self["tick0"] = tick0 if tick0 is not None else _v _v = arg.pop("tickangle", None) self["tickangle"] = tickangle if tickangle is not None else _v _v = arg.pop("tickcolor", None) self["tickcolor"] = tickcolor if tickcolor is not None else _v _v = arg.pop("tickfont", None) self["tickfont"] = tickfont if tickfont is not None else _v _v = arg.pop("tickformat", None) self["tickformat"] = tickformat if tickformat is not None else _v _v = arg.pop("tickformatstops", None) self["tickformatstops"] = tickformatstops if tickformatstops is not None else _v _v = arg.pop("tickformatstopdefaults", None) self["tickformatstopdefaults"] = ( tickformatstopdefaults if tickformatstopdefaults is not None else _v ) _v = arg.pop("ticklen", None) self["ticklen"] = ticklen if ticklen is not None else _v _v = arg.pop("tickmode", None) self["tickmode"] = tickmode if tickmode is not None else _v _v = arg.pop("tickprefix", None) self["tickprefix"] = tickprefix if tickprefix is not None else _v _v = arg.pop("ticks", None) self["ticks"] = ticks if ticks is not None else _v _v = arg.pop("ticksuffix", None) self["ticksuffix"] = ticksuffix if ticksuffix is not None else _v _v = arg.pop("ticktext", None) self["ticktext"] = ticktext if ticktext is not None else _v _v = arg.pop("ticktextsrc", None) self["ticktextsrc"] = ticktextsrc if ticktextsrc is not None else _v _v = arg.pop("tickvals", None) self["tickvals"] = tickvals if tickvals is not None else _v _v = arg.pop("tickvalssrc", None) self["tickvalssrc"] = tickvalssrc if tickvalssrc is not None else _v _v = arg.pop("tickwidth", None) self["tickwidth"] = tickwidth if tickwidth is not None else _v _v = arg.pop("title", None) self["title"] = title if title is not None else _v _v = arg.pop("titlefont", None) _v = titlefont if titlefont is not None else _v if _v is not None: self["titlefont"] = _v _v = arg.pop("titleside", None) _v = titleside if titleside is not None else _v if _v is not None: self["titleside"] = _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xanchor", None) self["xanchor"] = xanchor if xanchor is not None else _v _v = arg.pop("xpad", None) self["xpad"] = xpad if xpad is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("yanchor", None) self["yanchor"] = yanchor if yanchor is not None else _v _v = arg.pop("ypad", None) self["ypad"] = ypad if ypad is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = [ "ColorBar", "Hoverlabel", "Lighting", "Lightposition", "Starts", "Stream", "colorbar", "hoverlabel", ] from plotly.graph_objs.streamtube import hoverlabel from plotly.graph_objs.streamtube import colorbar plotly-4.4.1+dfsg.orig/plotly/graph_objs/scatter3d/0000755000175000017500000000000013573746613021625 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scatter3d/hoverlabel/0000755000175000017500000000000013573746613023750 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scatter3d/hoverlabel/__init__.py0000644000175000017500000002545213573721550026062 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatter3d.hoverlabel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Font object Sets the font used in hover labels. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatter3d.hoverlabel.Font color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatter3d.hoverlabel.Font constructor must be a dict or an instance of plotly.graph_objs.scatter3d.hoverlabel.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatter3d.hoverlabel import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["colorsrc"] = v_font.ColorsrcValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["familysrc"] = v_font.FamilysrcValidator() self._validators["size"] = v_font.SizeValidator() self._validators["sizesrc"] = v_font.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/scatter3d/projection/0000755000175000017500000000000013573746613024001 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scatter3d/projection/__init__.py0000644000175000017500000003045313573721551026111 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Z(_BaseTraceHierarchyType): # opacity # ------- @property def opacity(self): """ Sets the projection color. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # scale # ----- @property def scale(self): """ Sets the scale factor determining the size of the projection marker points. The 'scale' property is a number and may be specified as: - An int or float in the interval [0, 10] Returns ------- int|float """ return self["scale"] @scale.setter def scale(self, val): self["scale"] = val # show # ---- @property def show(self): """ Sets whether or not projections are shown along the z axis. The 'show' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["show"] @show.setter def show(self, val): self["show"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatter3d.projection" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ opacity Sets the projection color. scale Sets the scale factor determining the size of the projection marker points. show Sets whether or not projections are shown along the z axis. """ def __init__(self, arg=None, opacity=None, scale=None, show=None, **kwargs): """ Construct a new Z object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatter3d.projection.Z opacity Sets the projection color. scale Sets the scale factor determining the size of the projection marker points. show Sets whether or not projections are shown along the z axis. Returns ------- Z """ super(Z, self).__init__("z") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatter3d.projection.Z constructor must be a dict or an instance of plotly.graph_objs.scatter3d.projection.Z""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatter3d.projection import z as v_z # Initialize validators # --------------------- self._validators["opacity"] = v_z.OpacityValidator() self._validators["scale"] = v_z.ScaleValidator() self._validators["show"] = v_z.ShowValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("scale", None) self["scale"] = scale if scale is not None else _v _v = arg.pop("show", None) self["show"] = show if show is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Y(_BaseTraceHierarchyType): # opacity # ------- @property def opacity(self): """ Sets the projection color. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # scale # ----- @property def scale(self): """ Sets the scale factor determining the size of the projection marker points. The 'scale' property is a number and may be specified as: - An int or float in the interval [0, 10] Returns ------- int|float """ return self["scale"] @scale.setter def scale(self, val): self["scale"] = val # show # ---- @property def show(self): """ Sets whether or not projections are shown along the y axis. The 'show' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["show"] @show.setter def show(self, val): self["show"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatter3d.projection" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ opacity Sets the projection color. scale Sets the scale factor determining the size of the projection marker points. show Sets whether or not projections are shown along the y axis. """ def __init__(self, arg=None, opacity=None, scale=None, show=None, **kwargs): """ Construct a new Y object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatter3d.projection.Y opacity Sets the projection color. scale Sets the scale factor determining the size of the projection marker points. show Sets whether or not projections are shown along the y axis. Returns ------- Y """ super(Y, self).__init__("y") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatter3d.projection.Y constructor must be a dict or an instance of plotly.graph_objs.scatter3d.projection.Y""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatter3d.projection import y as v_y # Initialize validators # --------------------- self._validators["opacity"] = v_y.OpacityValidator() self._validators["scale"] = v_y.ScaleValidator() self._validators["show"] = v_y.ShowValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("scale", None) self["scale"] = scale if scale is not None else _v _v = arg.pop("show", None) self["show"] = show if show is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class X(_BaseTraceHierarchyType): # opacity # ------- @property def opacity(self): """ Sets the projection color. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # scale # ----- @property def scale(self): """ Sets the scale factor determining the size of the projection marker points. The 'scale' property is a number and may be specified as: - An int or float in the interval [0, 10] Returns ------- int|float """ return self["scale"] @scale.setter def scale(self, val): self["scale"] = val # show # ---- @property def show(self): """ Sets whether or not projections are shown along the x axis. The 'show' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["show"] @show.setter def show(self, val): self["show"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatter3d.projection" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ opacity Sets the projection color. scale Sets the scale factor determining the size of the projection marker points. show Sets whether or not projections are shown along the x axis. """ def __init__(self, arg=None, opacity=None, scale=None, show=None, **kwargs): """ Construct a new X object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatter3d.projection.X opacity Sets the projection color. scale Sets the scale factor determining the size of the projection marker points. show Sets whether or not projections are shown along the x axis. Returns ------- X """ super(X, self).__init__("x") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatter3d.projection.X constructor must be a dict or an instance of plotly.graph_objs.scatter3d.projection.X""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatter3d.projection import x as v_x # Initialize validators # --------------------- self._validators["opacity"] = v_x.OpacityValidator() self._validators["scale"] = v_x.ScaleValidator() self._validators["show"] = v_x.ShowValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("scale", None) self["scale"] = scale if scale is not None else _v _v = arg.pop("show", None) self["show"] = show if show is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["X", "Y", "Z"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/scatter3d/marker/0000755000175000017500000000000013573746613023106 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scatter3d/marker/colorbar/0000755000175000017500000000000013573746613024711 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scatter3d/marker/colorbar/title/0000755000175000017500000000000013573746613026032 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scatter3d/marker/colorbar/title/__init__.py0000644000175000017500000002060213573721550030134 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatter3d.marker.colorbar.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatter3d.marker.colorbar.title.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatter3d.marker.colorbar.title.Font constructor must be a dict or an instance of plotly.graph_objs.scatter3d.marker.colorbar.title.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatter3d.marker.colorbar.title import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/scatter3d/marker/colorbar/__init__.py0000644000175000017500000006102113573721551027014 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Title(_BaseTraceHierarchyType): # font # ---- @property def font(self): """ Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.scatter3d.marker.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.scatter3d.marker.colorbar.title.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # side # ---- @property def side(self): """ Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- Any """ return self["side"] @side.setter def side(self, val): self["side"] = val # text # ---- @property def text(self): """ Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatter3d.marker.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """ def __init__(self, arg=None, font=None, side=None, text=None, **kwargs): """ Construct a new Title object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatter3d.marker.colorbar.Title font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- Title """ super(Title, self).__init__("title") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatter3d.marker.colorbar.Title constructor must be a dict or an instance of plotly.graph_objs.scatter3d.marker.colorbar.Title""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatter3d.marker.colorbar import title as v_title # Initialize validators # --------------------- self._validators["font"] = v_title.FontValidator() self._validators["side"] = v_title.SideValidator() self._validators["text"] = v_title.TextValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("side", None) self["side"] = side if side is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickformatstop(_BaseTraceHierarchyType): # dtickrange # ---------- @property def dtickrange(self): """ range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" The 'dtickrange' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'dtickrange[0]' property accepts values of any type (1) The 'dtickrange[1]' property accepts values of any type Returns ------- list """ return self["dtickrange"] @dtickrange.setter def dtickrange(self, val): self["dtickrange"] = val # enabled # ------- @property def enabled(self): """ Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. The 'enabled' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["enabled"] @enabled.setter def enabled(self, val): self["enabled"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # value # ----- @property def value(self): """ string - dtickformat for described zoom level, the same as "tickformat" The 'value' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatter3d.marker.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """ def __init__( self, arg=None, dtickrange=None, enabled=None, name=None, templateitemname=None, value=None, **kwargs ): """ Construct a new Tickformatstop object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatter3d.marker.color bar.Tickformatstop dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- Tickformatstop """ super(Tickformatstop, self).__init__("tickformatstops") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatter3d.marker.colorbar.Tickformatstop constructor must be a dict or an instance of plotly.graph_objs.scatter3d.marker.colorbar.Tickformatstop""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatter3d.marker.colorbar import ( tickformatstop as v_tickformatstop, ) # Initialize validators # --------------------- self._validators["dtickrange"] = v_tickformatstop.DtickrangeValidator() self._validators["enabled"] = v_tickformatstop.EnabledValidator() self._validators["name"] = v_tickformatstop.NameValidator() self._validators[ "templateitemname" ] = v_tickformatstop.TemplateitemnameValidator() self._validators["value"] = v_tickformatstop.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtickrange", None) self["dtickrange"] = dtickrange if dtickrange is not None else _v _v = arg.pop("enabled", None) self["enabled"] = enabled if enabled is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatter3d.marker.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Tickfont object Sets the color bar's tick label font Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatter3d.marker.colorbar.Tickfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Tickfont """ super(Tickfont, self).__init__("tickfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatter3d.marker.colorbar.Tickfont constructor must be a dict or an instance of plotly.graph_objs.scatter3d.marker.colorbar.Tickfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatter3d.marker.colorbar import tickfont as v_tickfont # Initialize validators # --------------------- self._validators["color"] = v_tickfont.ColorValidator() self._validators["family"] = v_tickfont.FamilyValidator() self._validators["size"] = v_tickfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Tickfont", "Tickformatstop", "Tickformatstop", "Title", "title"] from plotly.graph_objs.scatter3d.marker.colorbar import title plotly-4.4.1+dfsg.orig/plotly/graph_objs/scatter3d/marker/__init__.py0000644000175000017500000026700113573721552025220 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # autocolorscale # -------------- @property def autocolorscale(self): """ Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. The 'autocolorscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocolorscale"] @autocolorscale.setter def autocolorscale(self, val): self["autocolorscale"] = val # cauto # ----- @property def cauto(self): """ Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. The 'cauto' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["cauto"] @cauto.setter def cauto(self, val): self["cauto"] = val # cmax # ---- @property def cmax(self): """ Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. The 'cmax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmax"] @cmax.setter def cmax(self, val): self["cmax"] = val # cmid # ---- @property def cmid(self): """ Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. The 'cmid' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmid"] @cmid.setter def cmid(self, val): self["cmid"] = val # cmin # ---- @property def cmin(self): """ Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. The 'cmin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmin"] @cmin.setter def cmin(self, val): self["cmin"] = val # color # ----- @property def color(self): """ Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A number that will be interpreted as a color according to scatter3d.marker.line.colorscale - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # coloraxis # --------- @property def coloraxis(self): """ Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. The 'coloraxis' property is an identifier of a particular subplot, of type 'coloraxis', that may be specified as the string 'coloraxis' optionally followed by an integer >= 1 (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) Returns ------- str """ return self["coloraxis"] @coloraxis.setter def coloraxis(self, val): self["coloraxis"] = val # colorscale # ---------- @property def colorscale(self): """ Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,Earth,Electric,Vi ridis,Cividis. The 'colorscale' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # reversescale # ------------ @property def reversescale(self): """ Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. The 'reversescale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["reversescale"] @reversescale.setter def reversescale(self, val): self["reversescale"] = val # width # ----- @property def width(self): """ Sets the width (in px) of the lines bounding the marker points. The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatter3d.marker" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. """ def __init__( self, arg=None, autocolorscale=None, cauto=None, cmax=None, cmid=None, cmin=None, color=None, coloraxis=None, colorscale=None, colorsrc=None, reversescale=None, width=None, **kwargs ): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatter3d.marker.Line autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatter3d.marker.Line constructor must be a dict or an instance of plotly.graph_objs.scatter3d.marker.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatter3d.marker import line as v_line # Initialize validators # --------------------- self._validators["autocolorscale"] = v_line.AutocolorscaleValidator() self._validators["cauto"] = v_line.CautoValidator() self._validators["cmax"] = v_line.CmaxValidator() self._validators["cmid"] = v_line.CmidValidator() self._validators["cmin"] = v_line.CminValidator() self._validators["color"] = v_line.ColorValidator() self._validators["coloraxis"] = v_line.ColoraxisValidator() self._validators["colorscale"] = v_line.ColorscaleValidator() self._validators["colorsrc"] = v_line.ColorsrcValidator() self._validators["reversescale"] = v_line.ReversescaleValidator() self._validators["width"] = v_line.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autocolorscale", None) self["autocolorscale"] = autocolorscale if autocolorscale is not None else _v _v = arg.pop("cauto", None) self["cauto"] = cauto if cauto is not None else _v _v = arg.pop("cmax", None) self["cmax"] = cmax if cmax is not None else _v _v = arg.pop("cmid", None) self["cmid"] = cmid if cmid is not None else _v _v = arg.pop("cmin", None) self["cmin"] = cmin if cmin is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("coloraxis", None) self["coloraxis"] = coloraxis if coloraxis is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("reversescale", None) self["reversescale"] = reversescale if reversescale is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class ColorBar(_BaseTraceHierarchyType): # bgcolor # ------- @property def bgcolor(self): """ Sets the color of padded area. The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the axis line color. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # borderwidth # ----------- @property def borderwidth(self): """ Sets the width (in px) or the border enclosing this color bar. The 'borderwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["borderwidth"] @borderwidth.setter def borderwidth(self, val): self["borderwidth"] = val # dtick # ----- @property def dtick(self): """ Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" The 'dtick' property accepts values of any type Returns ------- Any """ return self["dtick"] @dtick.setter def dtick(self, val): self["dtick"] = val # exponentformat # -------------- @property def exponentformat(self): """ Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. The 'exponentformat' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'e', 'E', 'power', 'SI', 'B'] Returns ------- Any """ return self["exponentformat"] @exponentformat.setter def exponentformat(self, val): self["exponentformat"] = val # len # --- @property def len(self): """ Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. The 'len' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["len"] @len.setter def len(self, val): self["len"] = val # lenmode # ------- @property def lenmode(self): """ Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. The 'lenmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["lenmode"] @lenmode.setter def lenmode(self, val): self["lenmode"] = val # nticks # ------ @property def nticks(self): """ Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". The 'nticks' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nticks"] @nticks.setter def nticks(self, val): self["nticks"] = val # outlinecolor # ------------ @property def outlinecolor(self): """ Sets the axis line color. The 'outlinecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["outlinecolor"] @outlinecolor.setter def outlinecolor(self, val): self["outlinecolor"] = val # outlinewidth # ------------ @property def outlinewidth(self): """ Sets the width (in px) of the axis line. The 'outlinewidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["outlinewidth"] @outlinewidth.setter def outlinewidth(self, val): self["outlinewidth"] = val # separatethousands # ----------------- @property def separatethousands(self): """ If "true", even 4-digit integers are separated The 'separatethousands' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["separatethousands"] @separatethousands.setter def separatethousands(self, val): self["separatethousands"] = val # showexponent # ------------ @property def showexponent(self): """ If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. The 'showexponent' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showexponent"] @showexponent.setter def showexponent(self, val): self["showexponent"] = val # showticklabels # -------------- @property def showticklabels(self): """ Determines whether or not the tick labels are drawn. The 'showticklabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showticklabels"] @showticklabels.setter def showticklabels(self, val): self["showticklabels"] = val # showtickprefix # -------------- @property def showtickprefix(self): """ If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. The 'showtickprefix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showtickprefix"] @showtickprefix.setter def showtickprefix(self, val): self["showtickprefix"] = val # showticksuffix # -------------- @property def showticksuffix(self): """ Same as `showtickprefix` but for tick suffixes. The 'showticksuffix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showticksuffix"] @showticksuffix.setter def showticksuffix(self, val): self["showticksuffix"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # thicknessmode # ------------- @property def thicknessmode(self): """ Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. The 'thicknessmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["thicknessmode"] @thicknessmode.setter def thicknessmode(self, val): self["thicknessmode"] = val # tick0 # ----- @property def tick0(self): """ Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. The 'tick0' property accepts values of any type Returns ------- Any """ return self["tick0"] @tick0.setter def tick0(self, val): self["tick0"] = val # tickangle # --------- @property def tickangle(self): """ Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. The 'tickangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["tickangle"] @tickangle.setter def tickangle(self, val): self["tickangle"] = val # tickcolor # --------- @property def tickcolor(self): """ Sets the tick color. The 'tickcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["tickcolor"] @tickcolor.setter def tickcolor(self, val): self["tickcolor"] = val # tickfont # -------- @property def tickfont(self): """ Sets the color bar's tick label font The 'tickfont' property is an instance of Tickfont that may be specified as: - An instance of plotly.graph_objs.scatter3d.marker.colorbar.Tickfont - A dict of string/value properties that will be passed to the Tickfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.scatter3d.marker.colorbar.Tickfont """ return self["tickfont"] @tickfont.setter def tickfont(self, val): self["tickfont"] = val # tickformat # ---------- @property def tickformat(self): """ Sets the tick label formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'tickformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickformat"] @tickformat.setter def tickformat(self, val): self["tickformat"] = val # tickformatstops # --------------- @property def tickformatstops(self): """ The 'tickformatstops' property is a tuple of instances of Tickformatstop that may be specified as: - A list or tuple of instances of plotly.graph_objs.scatter3d.marker.colorbar.Tickformatstop - A list or tuple of dicts of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- tuple[plotly.graph_objs.scatter3d.marker.colorbar.Tickformatstop] """ return self["tickformatstops"] @tickformatstops.setter def tickformatstops(self, val): self["tickformatstops"] = val # tickformatstopdefaults # ---------------------- @property def tickformatstopdefaults(self): """ When used in a template (as layout.template.data.scatter3d.mark er.colorbar.tickformatstopdefaults), sets the default property values to use for elements of scatter3d.marker.colorbar.tickformatstops The 'tickformatstopdefaults' property is an instance of Tickformatstop that may be specified as: - An instance of plotly.graph_objs.scatter3d.marker.colorbar.Tickformatstop - A dict of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: Returns ------- plotly.graph_objs.scatter3d.marker.colorbar.Tickformatstop """ return self["tickformatstopdefaults"] @tickformatstopdefaults.setter def tickformatstopdefaults(self, val): self["tickformatstopdefaults"] = val # ticklen # ------- @property def ticklen(self): """ Sets the tick length (in px). The 'ticklen' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ticklen"] @ticklen.setter def ticklen(self, val): self["ticklen"] = val # tickmode # -------- @property def tickmode(self): """ Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). The 'tickmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'linear', 'array'] Returns ------- Any """ return self["tickmode"] @tickmode.setter def tickmode(self, val): self["tickmode"] = val # tickprefix # ---------- @property def tickprefix(self): """ Sets a tick label prefix. The 'tickprefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickprefix"] @tickprefix.setter def tickprefix(self, val): self["tickprefix"] = val # ticks # ----- @property def ticks(self): """ Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. The 'ticks' property is an enumeration that may be specified as: - One of the following enumeration values: ['outside', 'inside', ''] Returns ------- Any """ return self["ticks"] @ticks.setter def ticks(self, val): self["ticks"] = val # ticksuffix # ---------- @property def ticksuffix(self): """ Sets a tick label suffix. The 'ticksuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ticksuffix"] @ticksuffix.setter def ticksuffix(self, val): self["ticksuffix"] = val # ticktext # -------- @property def ticktext(self): """ Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. The 'ticktext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ticktext"] @ticktext.setter def ticktext(self, val): self["ticktext"] = val # ticktextsrc # ----------- @property def ticktextsrc(self): """ Sets the source reference on plot.ly for ticktext . The 'ticktextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ticktextsrc"] @ticktextsrc.setter def ticktextsrc(self, val): self["ticktextsrc"] = val # tickvals # -------- @property def tickvals(self): """ Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. The 'tickvals' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["tickvals"] @tickvals.setter def tickvals(self, val): self["tickvals"] = val # tickvalssrc # ----------- @property def tickvalssrc(self): """ Sets the source reference on plot.ly for tickvals . The 'tickvalssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tickvalssrc"] @tickvalssrc.setter def tickvalssrc(self, val): self["tickvalssrc"] = val # tickwidth # --------- @property def tickwidth(self): """ Sets the tick width (in px). The 'tickwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["tickwidth"] @tickwidth.setter def tickwidth(self, val): self["tickwidth"] = val # title # ----- @property def title(self): """ The 'title' property is an instance of Title that may be specified as: - An instance of plotly.graph_objs.scatter3d.marker.colorbar.Title - A dict of string/value properties that will be passed to the Title constructor Supported dict properties: font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- plotly.graph_objs.scatter3d.marker.colorbar.Title """ return self["title"] @title.setter def title(self, val): self["title"] = val # titlefont # --------- @property def titlefont(self): """ Deprecated: Please use scatter3d.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.scatter3d.marker.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- """ return self["titlefont"] @titlefont.setter def titlefont(self, val): self["titlefont"] = val # titleside # --------- @property def titleside(self): """ Deprecated: Please use scatter3d.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- """ return self["titleside"] @titleside.setter def titleside(self, val): self["titleside"] = val # x # - @property def x(self): """ Sets the x position of the color bar (in plot fraction). The 'x' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["x"] @x.setter def x(self, val): self["x"] = val # xanchor # ------- @property def xanchor(self): """ Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. The 'xanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'center', 'right'] Returns ------- Any """ return self["xanchor"] @xanchor.setter def xanchor(self, val): self["xanchor"] = val # xpad # ---- @property def xpad(self): """ Sets the amount of padding (in px) along the x direction. The 'xpad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["xpad"] @xpad.setter def xpad(self, val): self["xpad"] = val # y # - @property def y(self): """ Sets the y position of the color bar (in plot fraction). The 'y' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["y"] @y.setter def y(self, val): self["y"] = val # yanchor # ------- @property def yanchor(self): """ Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. The 'yanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['top', 'middle', 'bottom'] Returns ------- Any """ return self["yanchor"] @yanchor.setter def yanchor(self, val): self["yanchor"] = val # ypad # ---- @property def ypad(self): """ Sets the amount of padding (in px) along the y direction. The 'ypad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ypad"] @ypad.setter def ypad(self, val): self["ypad"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatter3d.marker" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.scatter3d.marker.colorb ar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.scatte r3d.marker.colorbar.tickformatstopdefaults), sets the default property values to use for elements of scatter3d.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.scatter3d.marker.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use scatter3d.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use scatter3d.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """ _mapped_properties = { "titlefont": ("title", "font"), "titleside": ("title", "side"), } def __init__( self, arg=None, bgcolor=None, bordercolor=None, borderwidth=None, dtick=None, exponentformat=None, len=None, lenmode=None, nticks=None, outlinecolor=None, outlinewidth=None, separatethousands=None, showexponent=None, showticklabels=None, showtickprefix=None, showticksuffix=None, thickness=None, thicknessmode=None, tick0=None, tickangle=None, tickcolor=None, tickfont=None, tickformat=None, tickformatstops=None, tickformatstopdefaults=None, ticklen=None, tickmode=None, tickprefix=None, ticks=None, ticksuffix=None, ticktext=None, ticktextsrc=None, tickvals=None, tickvalssrc=None, tickwidth=None, title=None, titlefont=None, titleside=None, x=None, xanchor=None, xpad=None, y=None, yanchor=None, ypad=None, **kwargs ): """ Construct a new ColorBar object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatter3d.marker.ColorBar bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.scatter3d.marker.colorb ar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.scatte r3d.marker.colorbar.tickformatstopdefaults), sets the default property values to use for elements of scatter3d.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.scatter3d.marker.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use scatter3d.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use scatter3d.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- ColorBar """ super(ColorBar, self).__init__("colorbar") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatter3d.marker.ColorBar constructor must be a dict or an instance of plotly.graph_objs.scatter3d.marker.ColorBar""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatter3d.marker import colorbar as v_colorbar # Initialize validators # --------------------- self._validators["bgcolor"] = v_colorbar.BgcolorValidator() self._validators["bordercolor"] = v_colorbar.BordercolorValidator() self._validators["borderwidth"] = v_colorbar.BorderwidthValidator() self._validators["dtick"] = v_colorbar.DtickValidator() self._validators["exponentformat"] = v_colorbar.ExponentformatValidator() self._validators["len"] = v_colorbar.LenValidator() self._validators["lenmode"] = v_colorbar.LenmodeValidator() self._validators["nticks"] = v_colorbar.NticksValidator() self._validators["outlinecolor"] = v_colorbar.OutlinecolorValidator() self._validators["outlinewidth"] = v_colorbar.OutlinewidthValidator() self._validators["separatethousands"] = v_colorbar.SeparatethousandsValidator() self._validators["showexponent"] = v_colorbar.ShowexponentValidator() self._validators["showticklabels"] = v_colorbar.ShowticklabelsValidator() self._validators["showtickprefix"] = v_colorbar.ShowtickprefixValidator() self._validators["showticksuffix"] = v_colorbar.ShowticksuffixValidator() self._validators["thickness"] = v_colorbar.ThicknessValidator() self._validators["thicknessmode"] = v_colorbar.ThicknessmodeValidator() self._validators["tick0"] = v_colorbar.Tick0Validator() self._validators["tickangle"] = v_colorbar.TickangleValidator() self._validators["tickcolor"] = v_colorbar.TickcolorValidator() self._validators["tickfont"] = v_colorbar.TickfontValidator() self._validators["tickformat"] = v_colorbar.TickformatValidator() self._validators["tickformatstops"] = v_colorbar.TickformatstopsValidator() self._validators[ "tickformatstopdefaults" ] = v_colorbar.TickformatstopValidator() self._validators["ticklen"] = v_colorbar.TicklenValidator() self._validators["tickmode"] = v_colorbar.TickmodeValidator() self._validators["tickprefix"] = v_colorbar.TickprefixValidator() self._validators["ticks"] = v_colorbar.TicksValidator() self._validators["ticksuffix"] = v_colorbar.TicksuffixValidator() self._validators["ticktext"] = v_colorbar.TicktextValidator() self._validators["ticktextsrc"] = v_colorbar.TicktextsrcValidator() self._validators["tickvals"] = v_colorbar.TickvalsValidator() self._validators["tickvalssrc"] = v_colorbar.TickvalssrcValidator() self._validators["tickwidth"] = v_colorbar.TickwidthValidator() self._validators["title"] = v_colorbar.TitleValidator() self._validators["x"] = v_colorbar.XValidator() self._validators["xanchor"] = v_colorbar.XanchorValidator() self._validators["xpad"] = v_colorbar.XpadValidator() self._validators["y"] = v_colorbar.YValidator() self._validators["yanchor"] = v_colorbar.YanchorValidator() self._validators["ypad"] = v_colorbar.YpadValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("borderwidth", None) self["borderwidth"] = borderwidth if borderwidth is not None else _v _v = arg.pop("dtick", None) self["dtick"] = dtick if dtick is not None else _v _v = arg.pop("exponentformat", None) self["exponentformat"] = exponentformat if exponentformat is not None else _v _v = arg.pop("len", None) self["len"] = len if len is not None else _v _v = arg.pop("lenmode", None) self["lenmode"] = lenmode if lenmode is not None else _v _v = arg.pop("nticks", None) self["nticks"] = nticks if nticks is not None else _v _v = arg.pop("outlinecolor", None) self["outlinecolor"] = outlinecolor if outlinecolor is not None else _v _v = arg.pop("outlinewidth", None) self["outlinewidth"] = outlinewidth if outlinewidth is not None else _v _v = arg.pop("separatethousands", None) self["separatethousands"] = ( separatethousands if separatethousands is not None else _v ) _v = arg.pop("showexponent", None) self["showexponent"] = showexponent if showexponent is not None else _v _v = arg.pop("showticklabels", None) self["showticklabels"] = showticklabels if showticklabels is not None else _v _v = arg.pop("showtickprefix", None) self["showtickprefix"] = showtickprefix if showtickprefix is not None else _v _v = arg.pop("showticksuffix", None) self["showticksuffix"] = showticksuffix if showticksuffix is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("thicknessmode", None) self["thicknessmode"] = thicknessmode if thicknessmode is not None else _v _v = arg.pop("tick0", None) self["tick0"] = tick0 if tick0 is not None else _v _v = arg.pop("tickangle", None) self["tickangle"] = tickangle if tickangle is not None else _v _v = arg.pop("tickcolor", None) self["tickcolor"] = tickcolor if tickcolor is not None else _v _v = arg.pop("tickfont", None) self["tickfont"] = tickfont if tickfont is not None else _v _v = arg.pop("tickformat", None) self["tickformat"] = tickformat if tickformat is not None else _v _v = arg.pop("tickformatstops", None) self["tickformatstops"] = tickformatstops if tickformatstops is not None else _v _v = arg.pop("tickformatstopdefaults", None) self["tickformatstopdefaults"] = ( tickformatstopdefaults if tickformatstopdefaults is not None else _v ) _v = arg.pop("ticklen", None) self["ticklen"] = ticklen if ticklen is not None else _v _v = arg.pop("tickmode", None) self["tickmode"] = tickmode if tickmode is not None else _v _v = arg.pop("tickprefix", None) self["tickprefix"] = tickprefix if tickprefix is not None else _v _v = arg.pop("ticks", None) self["ticks"] = ticks if ticks is not None else _v _v = arg.pop("ticksuffix", None) self["ticksuffix"] = ticksuffix if ticksuffix is not None else _v _v = arg.pop("ticktext", None) self["ticktext"] = ticktext if ticktext is not None else _v _v = arg.pop("ticktextsrc", None) self["ticktextsrc"] = ticktextsrc if ticktextsrc is not None else _v _v = arg.pop("tickvals", None) self["tickvals"] = tickvals if tickvals is not None else _v _v = arg.pop("tickvalssrc", None) self["tickvalssrc"] = tickvalssrc if tickvalssrc is not None else _v _v = arg.pop("tickwidth", None) self["tickwidth"] = tickwidth if tickwidth is not None else _v _v = arg.pop("title", None) self["title"] = title if title is not None else _v _v = arg.pop("titlefont", None) _v = titlefont if titlefont is not None else _v if _v is not None: self["titlefont"] = _v _v = arg.pop("titleside", None) _v = titleside if titleside is not None else _v if _v is not None: self["titleside"] = _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xanchor", None) self["xanchor"] = xanchor if xanchor is not None else _v _v = arg.pop("xpad", None) self["xpad"] = xpad if xpad is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("yanchor", None) self["yanchor"] = yanchor if yanchor is not None else _v _v = arg.pop("ypad", None) self["ypad"] = ypad if ypad is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["ColorBar", "Line", "colorbar"] from plotly.graph_objs.scatter3d.marker import colorbar plotly-4.4.1+dfsg.orig/plotly/graph_objs/scatter3d/__init__.py0000644000175000017500000054361113573721553023744 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Textfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatter3d" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Textfont object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatter3d.Textfont color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size sizesrc Sets the source reference on plot.ly for size . Returns ------- Textfont """ super(Textfont, self).__init__("textfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatter3d.Textfont constructor must be a dict or an instance of plotly.graph_objs.scatter3d.Textfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatter3d import textfont as v_textfont # Initialize validators # --------------------- self._validators["color"] = v_textfont.ColorValidator() self._validators["colorsrc"] = v_textfont.ColorsrcValidator() self._validators["family"] = v_textfont.FamilyValidator() self._validators["size"] = v_textfont.SizeValidator() self._validators["sizesrc"] = v_textfont.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Stream(_BaseTraceHierarchyType): # maxpoints # --------- @property def maxpoints(self): """ Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. The 'maxpoints' property is a number and may be specified as: - An int or float in the interval [0, 10000] Returns ------- int|float """ return self["maxpoints"] @maxpoints.setter def maxpoints(self, val): self["maxpoints"] = val # token # ----- @property def token(self): """ The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. The 'token' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["token"] @token.setter def token(self, val): self["token"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatter3d" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """ def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): """ Construct a new Stream object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatter3d.Stream maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- Stream """ super(Stream, self).__init__("stream") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatter3d.Stream constructor must be a dict or an instance of plotly.graph_objs.scatter3d.Stream""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatter3d import stream as v_stream # Initialize validators # --------------------- self._validators["maxpoints"] = v_stream.MaxpointsValidator() self._validators["token"] = v_stream.TokenValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("maxpoints", None) self["maxpoints"] = maxpoints if maxpoints is not None else _v _v = arg.pop("token", None) self["token"] = token if token is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Projection(_BaseTraceHierarchyType): # x # - @property def x(self): """ The 'x' property is an instance of X that may be specified as: - An instance of plotly.graph_objs.scatter3d.projection.X - A dict of string/value properties that will be passed to the X constructor Supported dict properties: opacity Sets the projection color. scale Sets the scale factor determining the size of the projection marker points. show Sets whether or not projections are shown along the x axis. Returns ------- plotly.graph_objs.scatter3d.projection.X """ return self["x"] @x.setter def x(self, val): self["x"] = val # y # - @property def y(self): """ The 'y' property is an instance of Y that may be specified as: - An instance of plotly.graph_objs.scatter3d.projection.Y - A dict of string/value properties that will be passed to the Y constructor Supported dict properties: opacity Sets the projection color. scale Sets the scale factor determining the size of the projection marker points. show Sets whether or not projections are shown along the y axis. Returns ------- plotly.graph_objs.scatter3d.projection.Y """ return self["y"] @y.setter def y(self, val): self["y"] = val # z # - @property def z(self): """ The 'z' property is an instance of Z that may be specified as: - An instance of plotly.graph_objs.scatter3d.projection.Z - A dict of string/value properties that will be passed to the Z constructor Supported dict properties: opacity Sets the projection color. scale Sets the scale factor determining the size of the projection marker points. show Sets whether or not projections are shown along the z axis. Returns ------- plotly.graph_objs.scatter3d.projection.Z """ return self["z"] @z.setter def z(self, val): self["z"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatter3d" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ x plotly.graph_objects.scatter3d.projection.X instance or dict with compatible properties y plotly.graph_objects.scatter3d.projection.Y instance or dict with compatible properties z plotly.graph_objects.scatter3d.projection.Z instance or dict with compatible properties """ def __init__(self, arg=None, x=None, y=None, z=None, **kwargs): """ Construct a new Projection object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatter3d.Projection x plotly.graph_objects.scatter3d.projection.X instance or dict with compatible properties y plotly.graph_objects.scatter3d.projection.Y instance or dict with compatible properties z plotly.graph_objects.scatter3d.projection.Z instance or dict with compatible properties Returns ------- Projection """ super(Projection, self).__init__("projection") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatter3d.Projection constructor must be a dict or an instance of plotly.graph_objs.scatter3d.Projection""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatter3d import projection as v_projection # Initialize validators # --------------------- self._validators["x"] = v_projection.XValidator() self._validators["y"] = v_projection.YValidator() self._validators["z"] = v_projection.ZValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("z", None) self["z"] = z if z is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # autocolorscale # -------------- @property def autocolorscale(self): """ Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. The 'autocolorscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocolorscale"] @autocolorscale.setter def autocolorscale(self, val): self["autocolorscale"] = val # cauto # ----- @property def cauto(self): """ Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. The 'cauto' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["cauto"] @cauto.setter def cauto(self, val): self["cauto"] = val # cmax # ---- @property def cmax(self): """ Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. The 'cmax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmax"] @cmax.setter def cmax(self, val): self["cmax"] = val # cmid # ---- @property def cmid(self): """ Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. The 'cmid' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmid"] @cmid.setter def cmid(self, val): self["cmid"] = val # cmin # ---- @property def cmin(self): """ Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. The 'cmin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmin"] @cmin.setter def cmin(self, val): self["cmin"] = val # color # ----- @property def color(self): """ Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A number that will be interpreted as a color according to scatter3d.marker.colorscale - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # coloraxis # --------- @property def coloraxis(self): """ Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. The 'coloraxis' property is an identifier of a particular subplot, of type 'coloraxis', that may be specified as the string 'coloraxis' optionally followed by an integer >= 1 (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) Returns ------- str """ return self["coloraxis"] @coloraxis.setter def coloraxis(self, val): self["coloraxis"] = val # colorbar # -------- @property def colorbar(self): """ The 'colorbar' property is an instance of ColorBar that may be specified as: - An instance of plotly.graph_objs.scatter3d.marker.ColorBar - A dict of string/value properties that will be passed to the ColorBar constructor Supported dict properties: bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.scatter3d.marke r.colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.scatter3d.marker.colorbar.tickformatstopdefau lts), sets the default property values to use for elements of scatter3d.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.scatter3d.marker.colorbar. Title instance or dict with compatible properties titlefont Deprecated: Please use scatter3d.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use scatter3d.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- plotly.graph_objs.scatter3d.marker.ColorBar """ return self["colorbar"] @colorbar.setter def colorbar(self, val): self["colorbar"] = val # colorscale # ---------- @property def colorscale(self): """ Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnB u,Greens,YlOrRd,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland ,Jet,Hot,Blackbody,Earth,Electric,Viridis,Cividis. The 'colorscale' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.scatter3d.marker.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,R eds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Black body,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. Returns ------- plotly.graph_objs.scatter3d.marker.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # opacity # ------- @property def opacity(self): """ Sets the marker opacity. Note that the marker opacity for scatter3d traces must be a scalar value for performance reasons. To set a blending opacity value (i.e. which is not transparent), set "marker.color" to an rgba color and use its alpha channel. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # reversescale # ------------ @property def reversescale(self): """ Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. The 'reversescale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["reversescale"] @reversescale.setter def reversescale(self, val): self["reversescale"] = val # showscale # --------- @property def showscale(self): """ Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. The 'showscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showscale"] @showscale.setter def showscale(self, val): self["showscale"] = val # size # ---- @property def size(self): """ Sets the marker size (in px). The 'size' property is a number and may be specified as: - An int or float in the interval [0, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizemin # ------- @property def sizemin(self): """ Has an effect only if `marker.size` is set to a numerical array. Sets the minimum size (in px) of the rendered marker points. The 'sizemin' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["sizemin"] @sizemin.setter def sizemin(self, val): self["sizemin"] = val # sizemode # -------- @property def sizemode(self): """ Has an effect only if `marker.size` is set to a numerical array. Sets the rule for which the data in `size` is converted to pixels. The 'sizemode' property is an enumeration that may be specified as: - One of the following enumeration values: ['diameter', 'area'] Returns ------- Any """ return self["sizemode"] @sizemode.setter def sizemode(self, val): self["sizemode"] = val # sizeref # ------- @property def sizeref(self): """ Has an effect only if `marker.size` is set to a numerical array. Sets the scale factor used to determine the rendered size of marker points. Use with `sizemin` and `sizemode`. The 'sizeref' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["sizeref"] @sizeref.setter def sizeref(self, val): self["sizeref"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # symbol # ------ @property def symbol(self): """ Sets the marker symbol type. The 'symbol' property is an enumeration that may be specified as: - One of the following enumeration values: ['circle', 'circle-open', 'square', 'square-open', 'diamond', 'diamond-open', 'cross', 'x'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["symbol"] @symbol.setter def symbol(self, val): self["symbol"] = val # symbolsrc # --------- @property def symbolsrc(self): """ Sets the source reference on plot.ly for symbol . The 'symbolsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["symbolsrc"] @symbolsrc.setter def symbolsrc(self, val): self["symbolsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatter3d" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.scatter3d.marker.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu ,Reds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . line plotly.graph_objects.scatter3d.marker.Line instance or dict with compatible properties opacity Sets the marker opacity. Note that the marker opacity for scatter3d traces must be a scalar value for performance reasons. To set a blending opacity value (i.e. which is not transparent), set "marker.color" to an rgba color and use its alpha channel. reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. size Sets the marker size (in px). sizemin Has an effect only if `marker.size` is set to a numerical array. Sets the minimum size (in px) of the rendered marker points. sizemode Has an effect only if `marker.size` is set to a numerical array. Sets the rule for which the data in `size` is converted to pixels. sizeref Has an effect only if `marker.size` is set to a numerical array. Sets the scale factor used to determine the rendered size of marker points. Use with `sizemin` and `sizemode`. sizesrc Sets the source reference on plot.ly for size . symbol Sets the marker symbol type. symbolsrc Sets the source reference on plot.ly for symbol . """ def __init__( self, arg=None, autocolorscale=None, cauto=None, cmax=None, cmid=None, cmin=None, color=None, coloraxis=None, colorbar=None, colorscale=None, colorsrc=None, line=None, opacity=None, reversescale=None, showscale=None, size=None, sizemin=None, sizemode=None, sizeref=None, sizesrc=None, symbol=None, symbolsrc=None, **kwargs ): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatter3d.Marker autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.scatter3d.marker.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu ,Reds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . line plotly.graph_objects.scatter3d.marker.Line instance or dict with compatible properties opacity Sets the marker opacity. Note that the marker opacity for scatter3d traces must be a scalar value for performance reasons. To set a blending opacity value (i.e. which is not transparent), set "marker.color" to an rgba color and use its alpha channel. reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. size Sets the marker size (in px). sizemin Has an effect only if `marker.size` is set to a numerical array. Sets the minimum size (in px) of the rendered marker points. sizemode Has an effect only if `marker.size` is set to a numerical array. Sets the rule for which the data in `size` is converted to pixels. sizeref Has an effect only if `marker.size` is set to a numerical array. Sets the scale factor used to determine the rendered size of marker points. Use with `sizemin` and `sizemode`. sizesrc Sets the source reference on plot.ly for size . symbol Sets the marker symbol type. symbolsrc Sets the source reference on plot.ly for symbol . Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatter3d.Marker constructor must be a dict or an instance of plotly.graph_objs.scatter3d.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatter3d import marker as v_marker # Initialize validators # --------------------- self._validators["autocolorscale"] = v_marker.AutocolorscaleValidator() self._validators["cauto"] = v_marker.CautoValidator() self._validators["cmax"] = v_marker.CmaxValidator() self._validators["cmid"] = v_marker.CmidValidator() self._validators["cmin"] = v_marker.CminValidator() self._validators["color"] = v_marker.ColorValidator() self._validators["coloraxis"] = v_marker.ColoraxisValidator() self._validators["colorbar"] = v_marker.ColorBarValidator() self._validators["colorscale"] = v_marker.ColorscaleValidator() self._validators["colorsrc"] = v_marker.ColorsrcValidator() self._validators["line"] = v_marker.LineValidator() self._validators["opacity"] = v_marker.OpacityValidator() self._validators["reversescale"] = v_marker.ReversescaleValidator() self._validators["showscale"] = v_marker.ShowscaleValidator() self._validators["size"] = v_marker.SizeValidator() self._validators["sizemin"] = v_marker.SizeminValidator() self._validators["sizemode"] = v_marker.SizemodeValidator() self._validators["sizeref"] = v_marker.SizerefValidator() self._validators["sizesrc"] = v_marker.SizesrcValidator() self._validators["symbol"] = v_marker.SymbolValidator() self._validators["symbolsrc"] = v_marker.SymbolsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autocolorscale", None) self["autocolorscale"] = autocolorscale if autocolorscale is not None else _v _v = arg.pop("cauto", None) self["cauto"] = cauto if cauto is not None else _v _v = arg.pop("cmax", None) self["cmax"] = cmax if cmax is not None else _v _v = arg.pop("cmid", None) self["cmid"] = cmid if cmid is not None else _v _v = arg.pop("cmin", None) self["cmin"] = cmin if cmin is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("coloraxis", None) self["coloraxis"] = coloraxis if coloraxis is not None else _v _v = arg.pop("colorbar", None) self["colorbar"] = colorbar if colorbar is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("reversescale", None) self["reversescale"] = reversescale if reversescale is not None else _v _v = arg.pop("showscale", None) self["showscale"] = showscale if showscale is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizemin", None) self["sizemin"] = sizemin if sizemin is not None else _v _v = arg.pop("sizemode", None) self["sizemode"] = sizemode if sizemode is not None else _v _v = arg.pop("sizeref", None) self["sizeref"] = sizeref if sizeref is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v _v = arg.pop("symbol", None) self["symbol"] = symbol if symbol is not None else _v _v = arg.pop("symbolsrc", None) self["symbolsrc"] = symbolsrc if symbolsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # autocolorscale # -------------- @property def autocolorscale(self): """ Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `line.colorscale`. Has an effect only if in `line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. The 'autocolorscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocolorscale"] @autocolorscale.setter def autocolorscale(self, val): self["autocolorscale"] = val # cauto # ----- @property def cauto(self): """ Determines whether or not the color domain is computed with respect to the input data (here in `line.color`) or the bounds set in `line.cmin` and `line.cmax` Has an effect only if in `line.color`is set to a numerical array. Defaults to `false` when `line.cmin` and `line.cmax` are set by the user. The 'cauto' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["cauto"] @cauto.setter def cauto(self, val): self["cauto"] = val # cmax # ---- @property def cmax(self): """ Sets the upper bound of the color domain. Has an effect only if in `line.color`is set to a numerical array. Value should have the same units as in `line.color` and if set, `line.cmin` must be set as well. The 'cmax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmax"] @cmax.setter def cmax(self, val): self["cmax"] = val # cmid # ---- @property def cmid(self): """ Sets the mid-point of the color domain by scaling `line.cmin` and/or `line.cmax` to be equidistant to this point. Has an effect only if in `line.color`is set to a numerical array. Value should have the same units as in `line.color`. Has no effect when `line.cauto` is `false`. The 'cmid' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmid"] @cmid.setter def cmid(self, val): self["cmid"] = val # cmin # ---- @property def cmin(self): """ Sets the lower bound of the color domain. Has an effect only if in `line.color`is set to a numerical array. Value should have the same units as in `line.color` and if set, `line.cmax` must be set as well. The 'cmin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmin"] @cmin.setter def cmin(self, val): self["cmin"] = val # color # ----- @property def color(self): """ Sets thelinecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `line.cmin` and `line.cmax` if set. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A number that will be interpreted as a color according to scatter3d.line.colorscale - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # coloraxis # --------- @property def coloraxis(self): """ Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. The 'coloraxis' property is an identifier of a particular subplot, of type 'coloraxis', that may be specified as the string 'coloraxis' optionally followed by an integer >= 1 (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) Returns ------- str """ return self["coloraxis"] @coloraxis.setter def coloraxis(self, val): self["coloraxis"] = val # colorbar # -------- @property def colorbar(self): """ The 'colorbar' property is an instance of ColorBar that may be specified as: - An instance of plotly.graph_objs.scatter3d.line.ColorBar - A dict of string/value properties that will be passed to the ColorBar constructor Supported dict properties: bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.scatter3d.line. colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.scatter3d.line.colorbar.tickformatstopdefault s), sets the default property values to use for elements of scatter3d.line.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.scatter3d.line.colorbar.Ti tle instance or dict with compatible properties titlefont Deprecated: Please use scatter3d.line.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use scatter3d.line.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- plotly.graph_objs.scatter3d.line.ColorBar """ return self["colorbar"] @colorbar.setter def colorbar(self, val): self["colorbar"] = val # colorscale # ---------- @property def colorscale(self): """ Sets the colorscale. Has an effect only if in `line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`line.cmin` and `line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Gr eens,YlOrRd,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet ,Hot,Blackbody,Earth,Electric,Viridis,Cividis. The 'colorscale' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # dash # ---- @property def dash(self): """ Sets the dash style of the lines. The 'dash' property is an enumeration that may be specified as: - One of the following enumeration values: ['solid', 'dot', 'dash', 'longdash', 'dashdot', 'longdashdot'] Returns ------- Any """ return self["dash"] @dash.setter def dash(self, val): self["dash"] = val # reversescale # ------------ @property def reversescale(self): """ Reverses the color mapping if true. Has an effect only if in `line.color`is set to a numerical array. If true, `line.cmin` will correspond to the last color in the array and `line.cmax` will correspond to the first color. The 'reversescale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["reversescale"] @reversescale.setter def reversescale(self, val): self["reversescale"] = val # showscale # --------- @property def showscale(self): """ Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `line.color`is set to a numerical array. The 'showscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showscale"] @showscale.setter def showscale(self, val): self["showscale"] = val # width # ----- @property def width(self): """ Sets the line width (in px). The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatter3d" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `line.colorscale`. Has an effect only if in `line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `line.color`) or the bounds set in `line.cmin` and `line.cmax` Has an effect only if in `line.color`is set to a numerical array. Defaults to `false` when `line.cmin` and `line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `line.color`is set to a numerical array. Value should have the same units as in `line.color` and if set, `line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `line.cmin` and/or `line.cmax` to be equidistant to this point. Has an effect only if in `line.color`is set to a numerical array. Value should have the same units as in `line.color`. Has no effect when `line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `line.color`is set to a numerical array. Value should have the same units as in `line.color` and if set, `line.cmax` must be set as well. color Sets thelinecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `line.cmin` and `line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.scatter3d.line.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`line.cmin` and `line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu ,Greens,YlOrRd,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,P ortland,Jet,Hot,Blackbody,Earth,Electric,Viridis,Cividi s. colorsrc Sets the source reference on plot.ly for color . dash Sets the dash style of the lines. reversescale Reverses the color mapping if true. Has an effect only if in `line.color`is set to a numerical array. If true, `line.cmin` will correspond to the last color in the array and `line.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `line.color`is set to a numerical array. width Sets the line width (in px). """ def __init__( self, arg=None, autocolorscale=None, cauto=None, cmax=None, cmid=None, cmin=None, color=None, coloraxis=None, colorbar=None, colorscale=None, colorsrc=None, dash=None, reversescale=None, showscale=None, width=None, **kwargs ): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatter3d.Line autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `line.colorscale`. Has an effect only if in `line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `line.color`) or the bounds set in `line.cmin` and `line.cmax` Has an effect only if in `line.color`is set to a numerical array. Defaults to `false` when `line.cmin` and `line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `line.color`is set to a numerical array. Value should have the same units as in `line.color` and if set, `line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `line.cmin` and/or `line.cmax` to be equidistant to this point. Has an effect only if in `line.color`is set to a numerical array. Value should have the same units as in `line.color`. Has no effect when `line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `line.color`is set to a numerical array. Value should have the same units as in `line.color` and if set, `line.cmax` must be set as well. color Sets thelinecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `line.cmin` and `line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.scatter3d.line.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`line.cmin` and `line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu ,Greens,YlOrRd,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,P ortland,Jet,Hot,Blackbody,Earth,Electric,Viridis,Cividi s. colorsrc Sets the source reference on plot.ly for color . dash Sets the dash style of the lines. reversescale Reverses the color mapping if true. Has an effect only if in `line.color`is set to a numerical array. If true, `line.cmin` will correspond to the last color in the array and `line.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `line.color`is set to a numerical array. width Sets the line width (in px). Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatter3d.Line constructor must be a dict or an instance of plotly.graph_objs.scatter3d.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatter3d import line as v_line # Initialize validators # --------------------- self._validators["autocolorscale"] = v_line.AutocolorscaleValidator() self._validators["cauto"] = v_line.CautoValidator() self._validators["cmax"] = v_line.CmaxValidator() self._validators["cmid"] = v_line.CmidValidator() self._validators["cmin"] = v_line.CminValidator() self._validators["color"] = v_line.ColorValidator() self._validators["coloraxis"] = v_line.ColoraxisValidator() self._validators["colorbar"] = v_line.ColorBarValidator() self._validators["colorscale"] = v_line.ColorscaleValidator() self._validators["colorsrc"] = v_line.ColorsrcValidator() self._validators["dash"] = v_line.DashValidator() self._validators["reversescale"] = v_line.ReversescaleValidator() self._validators["showscale"] = v_line.ShowscaleValidator() self._validators["width"] = v_line.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autocolorscale", None) self["autocolorscale"] = autocolorscale if autocolorscale is not None else _v _v = arg.pop("cauto", None) self["cauto"] = cauto if cauto is not None else _v _v = arg.pop("cmax", None) self["cmax"] = cmax if cmax is not None else _v _v = arg.pop("cmid", None) self["cmid"] = cmid if cmid is not None else _v _v = arg.pop("cmin", None) self["cmin"] = cmin if cmin is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("coloraxis", None) self["coloraxis"] = coloraxis if coloraxis is not None else _v _v = arg.pop("colorbar", None) self["colorbar"] = colorbar if colorbar is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("dash", None) self["dash"] = dash if dash is not None else _v _v = arg.pop("reversescale", None) self["reversescale"] = reversescale if reversescale is not None else _v _v = arg.pop("showscale", None) self["showscale"] = showscale if showscale is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Hoverlabel(_BaseTraceHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'right', 'auto'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["align"] @align.setter def align(self, val): self["align"] = val # alignsrc # -------- @property def alignsrc(self): """ Sets the source reference on plot.ly for align . The 'alignsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["alignsrc"] @alignsrc.setter def alignsrc(self, val): self["alignsrc"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the hover labels for this trace The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bgcolorsrc # ---------- @property def bgcolorsrc(self): """ Sets the source reference on plot.ly for bgcolor . The 'bgcolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bgcolorsrc"] @bgcolorsrc.setter def bgcolorsrc(self, val): self["bgcolorsrc"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the border color of the hover labels for this trace. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # bordercolorsrc # -------------- @property def bordercolorsrc(self): """ Sets the source reference on plot.ly for bordercolor . The 'bordercolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bordercolorsrc"] @bordercolorsrc.setter def bordercolorsrc(self, val): self["bordercolorsrc"] = val # font # ---- @property def font(self): """ Sets the font used in hover labels. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.scatter3d.hoverlabel.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.scatter3d.hoverlabel.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # namelength # ---------- @property def namelength(self): """ Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. The 'namelength' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [-1, 9223372036854775807] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|numpy.ndarray """ return self["namelength"] @namelength.setter def namelength(self, val): self["namelength"] = val # namelengthsrc # ------------- @property def namelengthsrc(self): """ Sets the source reference on plot.ly for namelength . The 'namelengthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["namelengthsrc"] @namelengthsrc.setter def namelengthsrc(self, val): self["namelengthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatter3d" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """ def __init__( self, arg=None, align=None, alignsrc=None, bgcolor=None, bgcolorsrc=None, bordercolor=None, bordercolorsrc=None, font=None, namelength=None, namelengthsrc=None, **kwargs ): """ Construct a new Hoverlabel object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatter3d.Hoverlabel align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- Hoverlabel """ super(Hoverlabel, self).__init__("hoverlabel") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatter3d.Hoverlabel constructor must be a dict or an instance of plotly.graph_objs.scatter3d.Hoverlabel""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatter3d import hoverlabel as v_hoverlabel # Initialize validators # --------------------- self._validators["align"] = v_hoverlabel.AlignValidator() self._validators["alignsrc"] = v_hoverlabel.AlignsrcValidator() self._validators["bgcolor"] = v_hoverlabel.BgcolorValidator() self._validators["bgcolorsrc"] = v_hoverlabel.BgcolorsrcValidator() self._validators["bordercolor"] = v_hoverlabel.BordercolorValidator() self._validators["bordercolorsrc"] = v_hoverlabel.BordercolorsrcValidator() self._validators["font"] = v_hoverlabel.FontValidator() self._validators["namelength"] = v_hoverlabel.NamelengthValidator() self._validators["namelengthsrc"] = v_hoverlabel.NamelengthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("alignsrc", None) self["alignsrc"] = alignsrc if alignsrc is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bgcolorsrc", None) self["bgcolorsrc"] = bgcolorsrc if bgcolorsrc is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("bordercolorsrc", None) self["bordercolorsrc"] = bordercolorsrc if bordercolorsrc is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("namelength", None) self["namelength"] = namelength if namelength is not None else _v _v = arg.pop("namelengthsrc", None) self["namelengthsrc"] = namelengthsrc if namelengthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class ErrorZ(_BaseTraceHierarchyType): # array # ----- @property def array(self): """ Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. The 'array' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["array"] @array.setter def array(self, val): self["array"] = val # arrayminus # ---------- @property def arrayminus(self): """ Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. The 'arrayminus' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["arrayminus"] @arrayminus.setter def arrayminus(self, val): self["arrayminus"] = val # arrayminussrc # ------------- @property def arrayminussrc(self): """ Sets the source reference on plot.ly for arrayminus . The 'arrayminussrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["arrayminussrc"] @arrayminussrc.setter def arrayminussrc(self, val): self["arrayminussrc"] = val # arraysrc # -------- @property def arraysrc(self): """ Sets the source reference on plot.ly for array . The 'arraysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["arraysrc"] @arraysrc.setter def arraysrc(self, val): self["arraysrc"] = val # color # ----- @property def color(self): """ Sets the stoke color of the error bars. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # symmetric # --------- @property def symmetric(self): """ Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. The 'symmetric' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["symmetric"] @symmetric.setter def symmetric(self, val): self["symmetric"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness (in px) of the error bars. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # traceref # -------- @property def traceref(self): """ The 'traceref' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["traceref"] @traceref.setter def traceref(self, val): self["traceref"] = val # tracerefminus # ------------- @property def tracerefminus(self): """ The 'tracerefminus' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["tracerefminus"] @tracerefminus.setter def tracerefminus(self, val): self["tracerefminus"] = val # type # ---- @property def type(self): """ Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. The 'type' property is an enumeration that may be specified as: - One of the following enumeration values: ['percent', 'constant', 'sqrt', 'data'] Returns ------- Any """ return self["type"] @type.setter def type(self, val): self["type"] = val # value # ----- @property def value(self): """ Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. The 'value' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["value"] @value.setter def value(self, val): self["value"] = val # valueminus # ---------- @property def valueminus(self): """ Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars The 'valueminus' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["valueminus"] @valueminus.setter def valueminus(self, val): self["valueminus"] = val # visible # ------- @property def visible(self): """ Determines whether or not this set of error bars is visible. The 'visible' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # width # ----- @property def width(self): """ Sets the width (in px) of the cross-bar at both ends of the error bars. The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatter3d" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ array Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. arrayminus Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. arrayminussrc Sets the source reference on plot.ly for arrayminus . arraysrc Sets the source reference on plot.ly for array . color Sets the stoke color of the error bars. symmetric Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. thickness Sets the thickness (in px) of the error bars. traceref tracerefminus type Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. value Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. valueminus Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars visible Determines whether or not this set of error bars is visible. width Sets the width (in px) of the cross-bar at both ends of the error bars. """ def __init__( self, arg=None, array=None, arrayminus=None, arrayminussrc=None, arraysrc=None, color=None, symmetric=None, thickness=None, traceref=None, tracerefminus=None, type=None, value=None, valueminus=None, visible=None, width=None, **kwargs ): """ Construct a new ErrorZ object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatter3d.ErrorZ array Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. arrayminus Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. arrayminussrc Sets the source reference on plot.ly for arrayminus . arraysrc Sets the source reference on plot.ly for array . color Sets the stoke color of the error bars. symmetric Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. thickness Sets the thickness (in px) of the error bars. traceref tracerefminus type Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. value Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. valueminus Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars visible Determines whether or not this set of error bars is visible. width Sets the width (in px) of the cross-bar at both ends of the error bars. Returns ------- ErrorZ """ super(ErrorZ, self).__init__("error_z") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatter3d.ErrorZ constructor must be a dict or an instance of plotly.graph_objs.scatter3d.ErrorZ""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatter3d import error_z as v_error_z # Initialize validators # --------------------- self._validators["array"] = v_error_z.ArrayValidator() self._validators["arrayminus"] = v_error_z.ArrayminusValidator() self._validators["arrayminussrc"] = v_error_z.ArrayminussrcValidator() self._validators["arraysrc"] = v_error_z.ArraysrcValidator() self._validators["color"] = v_error_z.ColorValidator() self._validators["symmetric"] = v_error_z.SymmetricValidator() self._validators["thickness"] = v_error_z.ThicknessValidator() self._validators["traceref"] = v_error_z.TracerefValidator() self._validators["tracerefminus"] = v_error_z.TracerefminusValidator() self._validators["type"] = v_error_z.TypeValidator() self._validators["value"] = v_error_z.ValueValidator() self._validators["valueminus"] = v_error_z.ValueminusValidator() self._validators["visible"] = v_error_z.VisibleValidator() self._validators["width"] = v_error_z.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("array", None) self["array"] = array if array is not None else _v _v = arg.pop("arrayminus", None) self["arrayminus"] = arrayminus if arrayminus is not None else _v _v = arg.pop("arrayminussrc", None) self["arrayminussrc"] = arrayminussrc if arrayminussrc is not None else _v _v = arg.pop("arraysrc", None) self["arraysrc"] = arraysrc if arraysrc is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("symmetric", None) self["symmetric"] = symmetric if symmetric is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("traceref", None) self["traceref"] = traceref if traceref is not None else _v _v = arg.pop("tracerefminus", None) self["tracerefminus"] = tracerefminus if tracerefminus is not None else _v _v = arg.pop("type", None) self["type"] = type if type is not None else _v _v = arg.pop("value", None) self["value"] = value if value is not None else _v _v = arg.pop("valueminus", None) self["valueminus"] = valueminus if valueminus is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class ErrorY(_BaseTraceHierarchyType): # array # ----- @property def array(self): """ Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. The 'array' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["array"] @array.setter def array(self, val): self["array"] = val # arrayminus # ---------- @property def arrayminus(self): """ Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. The 'arrayminus' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["arrayminus"] @arrayminus.setter def arrayminus(self, val): self["arrayminus"] = val # arrayminussrc # ------------- @property def arrayminussrc(self): """ Sets the source reference on plot.ly for arrayminus . The 'arrayminussrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["arrayminussrc"] @arrayminussrc.setter def arrayminussrc(self, val): self["arrayminussrc"] = val # arraysrc # -------- @property def arraysrc(self): """ Sets the source reference on plot.ly for array . The 'arraysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["arraysrc"] @arraysrc.setter def arraysrc(self, val): self["arraysrc"] = val # color # ----- @property def color(self): """ Sets the stoke color of the error bars. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # copy_zstyle # ----------- @property def copy_zstyle(self): """ The 'copy_zstyle' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["copy_zstyle"] @copy_zstyle.setter def copy_zstyle(self, val): self["copy_zstyle"] = val # symmetric # --------- @property def symmetric(self): """ Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. The 'symmetric' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["symmetric"] @symmetric.setter def symmetric(self, val): self["symmetric"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness (in px) of the error bars. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # traceref # -------- @property def traceref(self): """ The 'traceref' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["traceref"] @traceref.setter def traceref(self, val): self["traceref"] = val # tracerefminus # ------------- @property def tracerefminus(self): """ The 'tracerefminus' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["tracerefminus"] @tracerefminus.setter def tracerefminus(self, val): self["tracerefminus"] = val # type # ---- @property def type(self): """ Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. The 'type' property is an enumeration that may be specified as: - One of the following enumeration values: ['percent', 'constant', 'sqrt', 'data'] Returns ------- Any """ return self["type"] @type.setter def type(self, val): self["type"] = val # value # ----- @property def value(self): """ Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. The 'value' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["value"] @value.setter def value(self, val): self["value"] = val # valueminus # ---------- @property def valueminus(self): """ Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars The 'valueminus' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["valueminus"] @valueminus.setter def valueminus(self, val): self["valueminus"] = val # visible # ------- @property def visible(self): """ Determines whether or not this set of error bars is visible. The 'visible' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # width # ----- @property def width(self): """ Sets the width (in px) of the cross-bar at both ends of the error bars. The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatter3d" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ array Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. arrayminus Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. arrayminussrc Sets the source reference on plot.ly for arrayminus . arraysrc Sets the source reference on plot.ly for array . color Sets the stoke color of the error bars. copy_zstyle symmetric Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. thickness Sets the thickness (in px) of the error bars. traceref tracerefminus type Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. value Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. valueminus Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars visible Determines whether or not this set of error bars is visible. width Sets the width (in px) of the cross-bar at both ends of the error bars. """ def __init__( self, arg=None, array=None, arrayminus=None, arrayminussrc=None, arraysrc=None, color=None, copy_zstyle=None, symmetric=None, thickness=None, traceref=None, tracerefminus=None, type=None, value=None, valueminus=None, visible=None, width=None, **kwargs ): """ Construct a new ErrorY object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatter3d.ErrorY array Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. arrayminus Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. arrayminussrc Sets the source reference on plot.ly for arrayminus . arraysrc Sets the source reference on plot.ly for array . color Sets the stoke color of the error bars. copy_zstyle symmetric Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. thickness Sets the thickness (in px) of the error bars. traceref tracerefminus type Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. value Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. valueminus Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars visible Determines whether or not this set of error bars is visible. width Sets the width (in px) of the cross-bar at both ends of the error bars. Returns ------- ErrorY """ super(ErrorY, self).__init__("error_y") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatter3d.ErrorY constructor must be a dict or an instance of plotly.graph_objs.scatter3d.ErrorY""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatter3d import error_y as v_error_y # Initialize validators # --------------------- self._validators["array"] = v_error_y.ArrayValidator() self._validators["arrayminus"] = v_error_y.ArrayminusValidator() self._validators["arrayminussrc"] = v_error_y.ArrayminussrcValidator() self._validators["arraysrc"] = v_error_y.ArraysrcValidator() self._validators["color"] = v_error_y.ColorValidator() self._validators["copy_zstyle"] = v_error_y.CopyZstyleValidator() self._validators["symmetric"] = v_error_y.SymmetricValidator() self._validators["thickness"] = v_error_y.ThicknessValidator() self._validators["traceref"] = v_error_y.TracerefValidator() self._validators["tracerefminus"] = v_error_y.TracerefminusValidator() self._validators["type"] = v_error_y.TypeValidator() self._validators["value"] = v_error_y.ValueValidator() self._validators["valueminus"] = v_error_y.ValueminusValidator() self._validators["visible"] = v_error_y.VisibleValidator() self._validators["width"] = v_error_y.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("array", None) self["array"] = array if array is not None else _v _v = arg.pop("arrayminus", None) self["arrayminus"] = arrayminus if arrayminus is not None else _v _v = arg.pop("arrayminussrc", None) self["arrayminussrc"] = arrayminussrc if arrayminussrc is not None else _v _v = arg.pop("arraysrc", None) self["arraysrc"] = arraysrc if arraysrc is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("copy_zstyle", None) self["copy_zstyle"] = copy_zstyle if copy_zstyle is not None else _v _v = arg.pop("symmetric", None) self["symmetric"] = symmetric if symmetric is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("traceref", None) self["traceref"] = traceref if traceref is not None else _v _v = arg.pop("tracerefminus", None) self["tracerefminus"] = tracerefminus if tracerefminus is not None else _v _v = arg.pop("type", None) self["type"] = type if type is not None else _v _v = arg.pop("value", None) self["value"] = value if value is not None else _v _v = arg.pop("valueminus", None) self["valueminus"] = valueminus if valueminus is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class ErrorX(_BaseTraceHierarchyType): # array # ----- @property def array(self): """ Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. The 'array' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["array"] @array.setter def array(self, val): self["array"] = val # arrayminus # ---------- @property def arrayminus(self): """ Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. The 'arrayminus' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["arrayminus"] @arrayminus.setter def arrayminus(self, val): self["arrayminus"] = val # arrayminussrc # ------------- @property def arrayminussrc(self): """ Sets the source reference on plot.ly for arrayminus . The 'arrayminussrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["arrayminussrc"] @arrayminussrc.setter def arrayminussrc(self, val): self["arrayminussrc"] = val # arraysrc # -------- @property def arraysrc(self): """ Sets the source reference on plot.ly for array . The 'arraysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["arraysrc"] @arraysrc.setter def arraysrc(self, val): self["arraysrc"] = val # color # ----- @property def color(self): """ Sets the stoke color of the error bars. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # copy_zstyle # ----------- @property def copy_zstyle(self): """ The 'copy_zstyle' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["copy_zstyle"] @copy_zstyle.setter def copy_zstyle(self, val): self["copy_zstyle"] = val # symmetric # --------- @property def symmetric(self): """ Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. The 'symmetric' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["symmetric"] @symmetric.setter def symmetric(self, val): self["symmetric"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness (in px) of the error bars. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # traceref # -------- @property def traceref(self): """ The 'traceref' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["traceref"] @traceref.setter def traceref(self, val): self["traceref"] = val # tracerefminus # ------------- @property def tracerefminus(self): """ The 'tracerefminus' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["tracerefminus"] @tracerefminus.setter def tracerefminus(self, val): self["tracerefminus"] = val # type # ---- @property def type(self): """ Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. The 'type' property is an enumeration that may be specified as: - One of the following enumeration values: ['percent', 'constant', 'sqrt', 'data'] Returns ------- Any """ return self["type"] @type.setter def type(self, val): self["type"] = val # value # ----- @property def value(self): """ Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. The 'value' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["value"] @value.setter def value(self, val): self["value"] = val # valueminus # ---------- @property def valueminus(self): """ Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars The 'valueminus' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["valueminus"] @valueminus.setter def valueminus(self, val): self["valueminus"] = val # visible # ------- @property def visible(self): """ Determines whether or not this set of error bars is visible. The 'visible' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # width # ----- @property def width(self): """ Sets the width (in px) of the cross-bar at both ends of the error bars. The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatter3d" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ array Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. arrayminus Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. arrayminussrc Sets the source reference on plot.ly for arrayminus . arraysrc Sets the source reference on plot.ly for array . color Sets the stoke color of the error bars. copy_zstyle symmetric Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. thickness Sets the thickness (in px) of the error bars. traceref tracerefminus type Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. value Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. valueminus Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars visible Determines whether or not this set of error bars is visible. width Sets the width (in px) of the cross-bar at both ends of the error bars. """ def __init__( self, arg=None, array=None, arrayminus=None, arrayminussrc=None, arraysrc=None, color=None, copy_zstyle=None, symmetric=None, thickness=None, traceref=None, tracerefminus=None, type=None, value=None, valueminus=None, visible=None, width=None, **kwargs ): """ Construct a new ErrorX object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatter3d.ErrorX array Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. arrayminus Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. arrayminussrc Sets the source reference on plot.ly for arrayminus . arraysrc Sets the source reference on plot.ly for array . color Sets the stoke color of the error bars. copy_zstyle symmetric Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. thickness Sets the thickness (in px) of the error bars. traceref tracerefminus type Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. value Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. valueminus Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars visible Determines whether or not this set of error bars is visible. width Sets the width (in px) of the cross-bar at both ends of the error bars. Returns ------- ErrorX """ super(ErrorX, self).__init__("error_x") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatter3d.ErrorX constructor must be a dict or an instance of plotly.graph_objs.scatter3d.ErrorX""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatter3d import error_x as v_error_x # Initialize validators # --------------------- self._validators["array"] = v_error_x.ArrayValidator() self._validators["arrayminus"] = v_error_x.ArrayminusValidator() self._validators["arrayminussrc"] = v_error_x.ArrayminussrcValidator() self._validators["arraysrc"] = v_error_x.ArraysrcValidator() self._validators["color"] = v_error_x.ColorValidator() self._validators["copy_zstyle"] = v_error_x.CopyZstyleValidator() self._validators["symmetric"] = v_error_x.SymmetricValidator() self._validators["thickness"] = v_error_x.ThicknessValidator() self._validators["traceref"] = v_error_x.TracerefValidator() self._validators["tracerefminus"] = v_error_x.TracerefminusValidator() self._validators["type"] = v_error_x.TypeValidator() self._validators["value"] = v_error_x.ValueValidator() self._validators["valueminus"] = v_error_x.ValueminusValidator() self._validators["visible"] = v_error_x.VisibleValidator() self._validators["width"] = v_error_x.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("array", None) self["array"] = array if array is not None else _v _v = arg.pop("arrayminus", None) self["arrayminus"] = arrayminus if arrayminus is not None else _v _v = arg.pop("arrayminussrc", None) self["arrayminussrc"] = arrayminussrc if arrayminussrc is not None else _v _v = arg.pop("arraysrc", None) self["arraysrc"] = arraysrc if arraysrc is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("copy_zstyle", None) self["copy_zstyle"] = copy_zstyle if copy_zstyle is not None else _v _v = arg.pop("symmetric", None) self["symmetric"] = symmetric if symmetric is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("traceref", None) self["traceref"] = traceref if traceref is not None else _v _v = arg.pop("tracerefminus", None) self["tracerefminus"] = tracerefminus if tracerefminus is not None else _v _v = arg.pop("type", None) self["type"] = type if type is not None else _v _v = arg.pop("value", None) self["value"] = value if value is not None else _v _v = arg.pop("valueminus", None) self["valueminus"] = valueminus if valueminus is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = [ "ErrorX", "ErrorY", "ErrorZ", "Hoverlabel", "Line", "Marker", "Projection", "Stream", "Textfont", "hoverlabel", "line", "marker", "projection", ] from plotly.graph_objs.scatter3d import projection from plotly.graph_objs.scatter3d import marker from plotly.graph_objs.scatter3d import line from plotly.graph_objs.scatter3d import hoverlabel plotly-4.4.1+dfsg.orig/plotly/graph_objs/scatter3d/line/0000755000175000017500000000000013573746613022554 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scatter3d/line/colorbar/0000755000175000017500000000000013573746613024357 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scatter3d/line/colorbar/title/0000755000175000017500000000000013573746613025500 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scatter3d/line/colorbar/title/__init__.py0000644000175000017500000002057013573721550027606 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatter3d.line.colorbar.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatter3d.line.colorbar.title.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatter3d.line.colorbar.title.Font constructor must be a dict or an instance of plotly.graph_objs.scatter3d.line.colorbar.title.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatter3d.line.colorbar.title import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/scatter3d/line/colorbar/__init__.py0000644000175000017500000006075513573721551026477 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Title(_BaseTraceHierarchyType): # font # ---- @property def font(self): """ Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.scatter3d.line.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.scatter3d.line.colorbar.title.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # side # ---- @property def side(self): """ Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- Any """ return self["side"] @side.setter def side(self, val): self["side"] = val # text # ---- @property def text(self): """ Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatter3d.line.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """ def __init__(self, arg=None, font=None, side=None, text=None, **kwargs): """ Construct a new Title object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatter3d.line.colorbar.Title font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- Title """ super(Title, self).__init__("title") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatter3d.line.colorbar.Title constructor must be a dict or an instance of plotly.graph_objs.scatter3d.line.colorbar.Title""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatter3d.line.colorbar import title as v_title # Initialize validators # --------------------- self._validators["font"] = v_title.FontValidator() self._validators["side"] = v_title.SideValidator() self._validators["text"] = v_title.TextValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("side", None) self["side"] = side if side is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickformatstop(_BaseTraceHierarchyType): # dtickrange # ---------- @property def dtickrange(self): """ range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" The 'dtickrange' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'dtickrange[0]' property accepts values of any type (1) The 'dtickrange[1]' property accepts values of any type Returns ------- list """ return self["dtickrange"] @dtickrange.setter def dtickrange(self, val): self["dtickrange"] = val # enabled # ------- @property def enabled(self): """ Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. The 'enabled' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["enabled"] @enabled.setter def enabled(self, val): self["enabled"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # value # ----- @property def value(self): """ string - dtickformat for described zoom level, the same as "tickformat" The 'value' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatter3d.line.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """ def __init__( self, arg=None, dtickrange=None, enabled=None, name=None, templateitemname=None, value=None, **kwargs ): """ Construct a new Tickformatstop object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatter3d.line.colorba r.Tickformatstop dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- Tickformatstop """ super(Tickformatstop, self).__init__("tickformatstops") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatter3d.line.colorbar.Tickformatstop constructor must be a dict or an instance of plotly.graph_objs.scatter3d.line.colorbar.Tickformatstop""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatter3d.line.colorbar import ( tickformatstop as v_tickformatstop, ) # Initialize validators # --------------------- self._validators["dtickrange"] = v_tickformatstop.DtickrangeValidator() self._validators["enabled"] = v_tickformatstop.EnabledValidator() self._validators["name"] = v_tickformatstop.NameValidator() self._validators[ "templateitemname" ] = v_tickformatstop.TemplateitemnameValidator() self._validators["value"] = v_tickformatstop.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtickrange", None) self["dtickrange"] = dtickrange if dtickrange is not None else _v _v = arg.pop("enabled", None) self["enabled"] = enabled if enabled is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatter3d.line.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Tickfont object Sets the color bar's tick label font Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatter3d.line.colorbar.Tickfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Tickfont """ super(Tickfont, self).__init__("tickfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatter3d.line.colorbar.Tickfont constructor must be a dict or an instance of plotly.graph_objs.scatter3d.line.colorbar.Tickfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatter3d.line.colorbar import tickfont as v_tickfont # Initialize validators # --------------------- self._validators["color"] = v_tickfont.ColorValidator() self._validators["family"] = v_tickfont.FamilyValidator() self._validators["size"] = v_tickfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Tickfont", "Tickformatstop", "Tickformatstop", "Title", "title"] from plotly.graph_objs.scatter3d.line.colorbar import title plotly-4.4.1+dfsg.orig/plotly/graph_objs/scatter3d/line/__init__.py0000644000175000017500000021001713573721552024661 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class ColorBar(_BaseTraceHierarchyType): # bgcolor # ------- @property def bgcolor(self): """ Sets the color of padded area. The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the axis line color. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # borderwidth # ----------- @property def borderwidth(self): """ Sets the width (in px) or the border enclosing this color bar. The 'borderwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["borderwidth"] @borderwidth.setter def borderwidth(self, val): self["borderwidth"] = val # dtick # ----- @property def dtick(self): """ Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" The 'dtick' property accepts values of any type Returns ------- Any """ return self["dtick"] @dtick.setter def dtick(self, val): self["dtick"] = val # exponentformat # -------------- @property def exponentformat(self): """ Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. The 'exponentformat' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'e', 'E', 'power', 'SI', 'B'] Returns ------- Any """ return self["exponentformat"] @exponentformat.setter def exponentformat(self, val): self["exponentformat"] = val # len # --- @property def len(self): """ Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. The 'len' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["len"] @len.setter def len(self, val): self["len"] = val # lenmode # ------- @property def lenmode(self): """ Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. The 'lenmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["lenmode"] @lenmode.setter def lenmode(self, val): self["lenmode"] = val # nticks # ------ @property def nticks(self): """ Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". The 'nticks' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nticks"] @nticks.setter def nticks(self, val): self["nticks"] = val # outlinecolor # ------------ @property def outlinecolor(self): """ Sets the axis line color. The 'outlinecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["outlinecolor"] @outlinecolor.setter def outlinecolor(self, val): self["outlinecolor"] = val # outlinewidth # ------------ @property def outlinewidth(self): """ Sets the width (in px) of the axis line. The 'outlinewidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["outlinewidth"] @outlinewidth.setter def outlinewidth(self, val): self["outlinewidth"] = val # separatethousands # ----------------- @property def separatethousands(self): """ If "true", even 4-digit integers are separated The 'separatethousands' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["separatethousands"] @separatethousands.setter def separatethousands(self, val): self["separatethousands"] = val # showexponent # ------------ @property def showexponent(self): """ If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. The 'showexponent' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showexponent"] @showexponent.setter def showexponent(self, val): self["showexponent"] = val # showticklabels # -------------- @property def showticklabels(self): """ Determines whether or not the tick labels are drawn. The 'showticklabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showticklabels"] @showticklabels.setter def showticklabels(self, val): self["showticklabels"] = val # showtickprefix # -------------- @property def showtickprefix(self): """ If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. The 'showtickprefix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showtickprefix"] @showtickprefix.setter def showtickprefix(self, val): self["showtickprefix"] = val # showticksuffix # -------------- @property def showticksuffix(self): """ Same as `showtickprefix` but for tick suffixes. The 'showticksuffix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showticksuffix"] @showticksuffix.setter def showticksuffix(self, val): self["showticksuffix"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # thicknessmode # ------------- @property def thicknessmode(self): """ Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. The 'thicknessmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["thicknessmode"] @thicknessmode.setter def thicknessmode(self, val): self["thicknessmode"] = val # tick0 # ----- @property def tick0(self): """ Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. The 'tick0' property accepts values of any type Returns ------- Any """ return self["tick0"] @tick0.setter def tick0(self, val): self["tick0"] = val # tickangle # --------- @property def tickangle(self): """ Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. The 'tickangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["tickangle"] @tickangle.setter def tickangle(self, val): self["tickangle"] = val # tickcolor # --------- @property def tickcolor(self): """ Sets the tick color. The 'tickcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["tickcolor"] @tickcolor.setter def tickcolor(self, val): self["tickcolor"] = val # tickfont # -------- @property def tickfont(self): """ Sets the color bar's tick label font The 'tickfont' property is an instance of Tickfont that may be specified as: - An instance of plotly.graph_objs.scatter3d.line.colorbar.Tickfont - A dict of string/value properties that will be passed to the Tickfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.scatter3d.line.colorbar.Tickfont """ return self["tickfont"] @tickfont.setter def tickfont(self, val): self["tickfont"] = val # tickformat # ---------- @property def tickformat(self): """ Sets the tick label formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'tickformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickformat"] @tickformat.setter def tickformat(self, val): self["tickformat"] = val # tickformatstops # --------------- @property def tickformatstops(self): """ The 'tickformatstops' property is a tuple of instances of Tickformatstop that may be specified as: - A list or tuple of instances of plotly.graph_objs.scatter3d.line.colorbar.Tickformatstop - A list or tuple of dicts of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- tuple[plotly.graph_objs.scatter3d.line.colorbar.Tickformatstop] """ return self["tickformatstops"] @tickformatstops.setter def tickformatstops(self, val): self["tickformatstops"] = val # tickformatstopdefaults # ---------------------- @property def tickformatstopdefaults(self): """ When used in a template (as layout.template.data.scatter3d.line .colorbar.tickformatstopdefaults), sets the default property values to use for elements of scatter3d.line.colorbar.tickformatstops The 'tickformatstopdefaults' property is an instance of Tickformatstop that may be specified as: - An instance of plotly.graph_objs.scatter3d.line.colorbar.Tickformatstop - A dict of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: Returns ------- plotly.graph_objs.scatter3d.line.colorbar.Tickformatstop """ return self["tickformatstopdefaults"] @tickformatstopdefaults.setter def tickformatstopdefaults(self, val): self["tickformatstopdefaults"] = val # ticklen # ------- @property def ticklen(self): """ Sets the tick length (in px). The 'ticklen' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ticklen"] @ticklen.setter def ticklen(self, val): self["ticklen"] = val # tickmode # -------- @property def tickmode(self): """ Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). The 'tickmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'linear', 'array'] Returns ------- Any """ return self["tickmode"] @tickmode.setter def tickmode(self, val): self["tickmode"] = val # tickprefix # ---------- @property def tickprefix(self): """ Sets a tick label prefix. The 'tickprefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickprefix"] @tickprefix.setter def tickprefix(self, val): self["tickprefix"] = val # ticks # ----- @property def ticks(self): """ Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. The 'ticks' property is an enumeration that may be specified as: - One of the following enumeration values: ['outside', 'inside', ''] Returns ------- Any """ return self["ticks"] @ticks.setter def ticks(self, val): self["ticks"] = val # ticksuffix # ---------- @property def ticksuffix(self): """ Sets a tick label suffix. The 'ticksuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ticksuffix"] @ticksuffix.setter def ticksuffix(self, val): self["ticksuffix"] = val # ticktext # -------- @property def ticktext(self): """ Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. The 'ticktext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ticktext"] @ticktext.setter def ticktext(self, val): self["ticktext"] = val # ticktextsrc # ----------- @property def ticktextsrc(self): """ Sets the source reference on plot.ly for ticktext . The 'ticktextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ticktextsrc"] @ticktextsrc.setter def ticktextsrc(self, val): self["ticktextsrc"] = val # tickvals # -------- @property def tickvals(self): """ Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. The 'tickvals' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["tickvals"] @tickvals.setter def tickvals(self, val): self["tickvals"] = val # tickvalssrc # ----------- @property def tickvalssrc(self): """ Sets the source reference on plot.ly for tickvals . The 'tickvalssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tickvalssrc"] @tickvalssrc.setter def tickvalssrc(self, val): self["tickvalssrc"] = val # tickwidth # --------- @property def tickwidth(self): """ Sets the tick width (in px). The 'tickwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["tickwidth"] @tickwidth.setter def tickwidth(self, val): self["tickwidth"] = val # title # ----- @property def title(self): """ The 'title' property is an instance of Title that may be specified as: - An instance of plotly.graph_objs.scatter3d.line.colorbar.Title - A dict of string/value properties that will be passed to the Title constructor Supported dict properties: font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- plotly.graph_objs.scatter3d.line.colorbar.Title """ return self["title"] @title.setter def title(self, val): self["title"] = val # titlefont # --------- @property def titlefont(self): """ Deprecated: Please use scatter3d.line.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.scatter3d.line.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- """ return self["titlefont"] @titlefont.setter def titlefont(self, val): self["titlefont"] = val # titleside # --------- @property def titleside(self): """ Deprecated: Please use scatter3d.line.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- """ return self["titleside"] @titleside.setter def titleside(self, val): self["titleside"] = val # x # - @property def x(self): """ Sets the x position of the color bar (in plot fraction). The 'x' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["x"] @x.setter def x(self, val): self["x"] = val # xanchor # ------- @property def xanchor(self): """ Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. The 'xanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'center', 'right'] Returns ------- Any """ return self["xanchor"] @xanchor.setter def xanchor(self, val): self["xanchor"] = val # xpad # ---- @property def xpad(self): """ Sets the amount of padding (in px) along the x direction. The 'xpad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["xpad"] @xpad.setter def xpad(self, val): self["xpad"] = val # y # - @property def y(self): """ Sets the y position of the color bar (in plot fraction). The 'y' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["y"] @y.setter def y(self, val): self["y"] = val # yanchor # ------- @property def yanchor(self): """ Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. The 'yanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['top', 'middle', 'bottom'] Returns ------- Any """ return self["yanchor"] @yanchor.setter def yanchor(self, val): self["yanchor"] = val # ypad # ---- @property def ypad(self): """ Sets the amount of padding (in px) along the y direction. The 'ypad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ypad"] @ypad.setter def ypad(self, val): self["ypad"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatter3d.line" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.scatter3d.line.colorbar .Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.scatte r3d.line.colorbar.tickformatstopdefaults), sets the default property values to use for elements of scatter3d.line.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.scatter3d.line.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use scatter3d.line.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use scatter3d.line.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """ _mapped_properties = { "titlefont": ("title", "font"), "titleside": ("title", "side"), } def __init__( self, arg=None, bgcolor=None, bordercolor=None, borderwidth=None, dtick=None, exponentformat=None, len=None, lenmode=None, nticks=None, outlinecolor=None, outlinewidth=None, separatethousands=None, showexponent=None, showticklabels=None, showtickprefix=None, showticksuffix=None, thickness=None, thicknessmode=None, tick0=None, tickangle=None, tickcolor=None, tickfont=None, tickformat=None, tickformatstops=None, tickformatstopdefaults=None, ticklen=None, tickmode=None, tickprefix=None, ticks=None, ticksuffix=None, ticktext=None, ticktextsrc=None, tickvals=None, tickvalssrc=None, tickwidth=None, title=None, titlefont=None, titleside=None, x=None, xanchor=None, xpad=None, y=None, yanchor=None, ypad=None, **kwargs ): """ Construct a new ColorBar object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatter3d.line.ColorBar bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.scatter3d.line.colorbar .Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.scatte r3d.line.colorbar.tickformatstopdefaults), sets the default property values to use for elements of scatter3d.line.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.scatter3d.line.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use scatter3d.line.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use scatter3d.line.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- ColorBar """ super(ColorBar, self).__init__("colorbar") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatter3d.line.ColorBar constructor must be a dict or an instance of plotly.graph_objs.scatter3d.line.ColorBar""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatter3d.line import colorbar as v_colorbar # Initialize validators # --------------------- self._validators["bgcolor"] = v_colorbar.BgcolorValidator() self._validators["bordercolor"] = v_colorbar.BordercolorValidator() self._validators["borderwidth"] = v_colorbar.BorderwidthValidator() self._validators["dtick"] = v_colorbar.DtickValidator() self._validators["exponentformat"] = v_colorbar.ExponentformatValidator() self._validators["len"] = v_colorbar.LenValidator() self._validators["lenmode"] = v_colorbar.LenmodeValidator() self._validators["nticks"] = v_colorbar.NticksValidator() self._validators["outlinecolor"] = v_colorbar.OutlinecolorValidator() self._validators["outlinewidth"] = v_colorbar.OutlinewidthValidator() self._validators["separatethousands"] = v_colorbar.SeparatethousandsValidator() self._validators["showexponent"] = v_colorbar.ShowexponentValidator() self._validators["showticklabels"] = v_colorbar.ShowticklabelsValidator() self._validators["showtickprefix"] = v_colorbar.ShowtickprefixValidator() self._validators["showticksuffix"] = v_colorbar.ShowticksuffixValidator() self._validators["thickness"] = v_colorbar.ThicknessValidator() self._validators["thicknessmode"] = v_colorbar.ThicknessmodeValidator() self._validators["tick0"] = v_colorbar.Tick0Validator() self._validators["tickangle"] = v_colorbar.TickangleValidator() self._validators["tickcolor"] = v_colorbar.TickcolorValidator() self._validators["tickfont"] = v_colorbar.TickfontValidator() self._validators["tickformat"] = v_colorbar.TickformatValidator() self._validators["tickformatstops"] = v_colorbar.TickformatstopsValidator() self._validators[ "tickformatstopdefaults" ] = v_colorbar.TickformatstopValidator() self._validators["ticklen"] = v_colorbar.TicklenValidator() self._validators["tickmode"] = v_colorbar.TickmodeValidator() self._validators["tickprefix"] = v_colorbar.TickprefixValidator() self._validators["ticks"] = v_colorbar.TicksValidator() self._validators["ticksuffix"] = v_colorbar.TicksuffixValidator() self._validators["ticktext"] = v_colorbar.TicktextValidator() self._validators["ticktextsrc"] = v_colorbar.TicktextsrcValidator() self._validators["tickvals"] = v_colorbar.TickvalsValidator() self._validators["tickvalssrc"] = v_colorbar.TickvalssrcValidator() self._validators["tickwidth"] = v_colorbar.TickwidthValidator() self._validators["title"] = v_colorbar.TitleValidator() self._validators["x"] = v_colorbar.XValidator() self._validators["xanchor"] = v_colorbar.XanchorValidator() self._validators["xpad"] = v_colorbar.XpadValidator() self._validators["y"] = v_colorbar.YValidator() self._validators["yanchor"] = v_colorbar.YanchorValidator() self._validators["ypad"] = v_colorbar.YpadValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("borderwidth", None) self["borderwidth"] = borderwidth if borderwidth is not None else _v _v = arg.pop("dtick", None) self["dtick"] = dtick if dtick is not None else _v _v = arg.pop("exponentformat", None) self["exponentformat"] = exponentformat if exponentformat is not None else _v _v = arg.pop("len", None) self["len"] = len if len is not None else _v _v = arg.pop("lenmode", None) self["lenmode"] = lenmode if lenmode is not None else _v _v = arg.pop("nticks", None) self["nticks"] = nticks if nticks is not None else _v _v = arg.pop("outlinecolor", None) self["outlinecolor"] = outlinecolor if outlinecolor is not None else _v _v = arg.pop("outlinewidth", None) self["outlinewidth"] = outlinewidth if outlinewidth is not None else _v _v = arg.pop("separatethousands", None) self["separatethousands"] = ( separatethousands if separatethousands is not None else _v ) _v = arg.pop("showexponent", None) self["showexponent"] = showexponent if showexponent is not None else _v _v = arg.pop("showticklabels", None) self["showticklabels"] = showticklabels if showticklabels is not None else _v _v = arg.pop("showtickprefix", None) self["showtickprefix"] = showtickprefix if showtickprefix is not None else _v _v = arg.pop("showticksuffix", None) self["showticksuffix"] = showticksuffix if showticksuffix is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("thicknessmode", None) self["thicknessmode"] = thicknessmode if thicknessmode is not None else _v _v = arg.pop("tick0", None) self["tick0"] = tick0 if tick0 is not None else _v _v = arg.pop("tickangle", None) self["tickangle"] = tickangle if tickangle is not None else _v _v = arg.pop("tickcolor", None) self["tickcolor"] = tickcolor if tickcolor is not None else _v _v = arg.pop("tickfont", None) self["tickfont"] = tickfont if tickfont is not None else _v _v = arg.pop("tickformat", None) self["tickformat"] = tickformat if tickformat is not None else _v _v = arg.pop("tickformatstops", None) self["tickformatstops"] = tickformatstops if tickformatstops is not None else _v _v = arg.pop("tickformatstopdefaults", None) self["tickformatstopdefaults"] = ( tickformatstopdefaults if tickformatstopdefaults is not None else _v ) _v = arg.pop("ticklen", None) self["ticklen"] = ticklen if ticklen is not None else _v _v = arg.pop("tickmode", None) self["tickmode"] = tickmode if tickmode is not None else _v _v = arg.pop("tickprefix", None) self["tickprefix"] = tickprefix if tickprefix is not None else _v _v = arg.pop("ticks", None) self["ticks"] = ticks if ticks is not None else _v _v = arg.pop("ticksuffix", None) self["ticksuffix"] = ticksuffix if ticksuffix is not None else _v _v = arg.pop("ticktext", None) self["ticktext"] = ticktext if ticktext is not None else _v _v = arg.pop("ticktextsrc", None) self["ticktextsrc"] = ticktextsrc if ticktextsrc is not None else _v _v = arg.pop("tickvals", None) self["tickvals"] = tickvals if tickvals is not None else _v _v = arg.pop("tickvalssrc", None) self["tickvalssrc"] = tickvalssrc if tickvalssrc is not None else _v _v = arg.pop("tickwidth", None) self["tickwidth"] = tickwidth if tickwidth is not None else _v _v = arg.pop("title", None) self["title"] = title if title is not None else _v _v = arg.pop("titlefont", None) _v = titlefont if titlefont is not None else _v if _v is not None: self["titlefont"] = _v _v = arg.pop("titleside", None) _v = titleside if titleside is not None else _v if _v is not None: self["titleside"] = _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xanchor", None) self["xanchor"] = xanchor if xanchor is not None else _v _v = arg.pop("xpad", None) self["xpad"] = xpad if xpad is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("yanchor", None) self["yanchor"] = yanchor if yanchor is not None else _v _v = arg.pop("ypad", None) self["ypad"] = ypad if ypad is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["ColorBar", "colorbar"] from plotly.graph_objs.scatter3d.line import colorbar plotly-4.4.1+dfsg.orig/plotly/graph_objs/ohlc/0000755000175000017500000000000013573746613020656 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/ohlc/increasing/0000755000175000017500000000000013573746613023000 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/ohlc/increasing/__init__.py0000644000175000017500000001557113573721550025113 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the line color. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # dash # ---- @property def dash(self): """ Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). The 'dash' property is an enumeration that may be specified as: - One of the following dash styles: ['solid', 'dot', 'dash', 'longdash', 'dashdot', 'longdashdot'] - A string containing a dash length list in pixels or percentages (e.g. '5px 10px 2px 2px', '5, 10, 2, 2', '10% 20% 40%', etc.) Returns ------- str """ return self["dash"] @dash.setter def dash(self, val): self["dash"] = val # width # ----- @property def width(self): """ Sets the line width (in px). The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "ohlc.increasing" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the line color. dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). width Sets the line width (in px). """ def __init__(self, arg=None, color=None, dash=None, width=None, **kwargs): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.ohlc.increasing.Line color Sets the line color. dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). width Sets the line width (in px). Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.ohlc.increasing.Line constructor must be a dict or an instance of plotly.graph_objs.ohlc.increasing.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.ohlc.increasing import line as v_line # Initialize validators # --------------------- self._validators["color"] = v_line.ColorValidator() self._validators["dash"] = v_line.DashValidator() self._validators["width"] = v_line.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("dash", None) self["dash"] = dash if dash is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Line"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/ohlc/hoverlabel/0000755000175000017500000000000013573746613023001 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/ohlc/hoverlabel/__init__.py0000644000175000017500000002540513573721550025111 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "ohlc.hoverlabel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Font object Sets the font used in hover labels. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.ohlc.hoverlabel.Font color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.ohlc.hoverlabel.Font constructor must be a dict or an instance of plotly.graph_objs.ohlc.hoverlabel.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.ohlc.hoverlabel import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["colorsrc"] = v_font.ColorsrcValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["familysrc"] = v_font.FamilysrcValidator() self._validators["size"] = v_font.SizeValidator() self._validators["sizesrc"] = v_font.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/ohlc/__init__.py0000644000175000017500000010243213573721550022762 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Stream(_BaseTraceHierarchyType): # maxpoints # --------- @property def maxpoints(self): """ Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. The 'maxpoints' property is a number and may be specified as: - An int or float in the interval [0, 10000] Returns ------- int|float """ return self["maxpoints"] @maxpoints.setter def maxpoints(self, val): self["maxpoints"] = val # token # ----- @property def token(self): """ The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. The 'token' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["token"] @token.setter def token(self, val): self["token"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "ohlc" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """ def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): """ Construct a new Stream object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.ohlc.Stream maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- Stream """ super(Stream, self).__init__("stream") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.ohlc.Stream constructor must be a dict or an instance of plotly.graph_objs.ohlc.Stream""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.ohlc import stream as v_stream # Initialize validators # --------------------- self._validators["maxpoints"] = v_stream.MaxpointsValidator() self._validators["token"] = v_stream.TokenValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("maxpoints", None) self["maxpoints"] = maxpoints if maxpoints is not None else _v _v = arg.pop("token", None) self["token"] = token if token is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # dash # ---- @property def dash(self): """ Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). Note that this style setting can also be set per direction via `increasing.line.dash` and `decreasing.line.dash`. The 'dash' property is an enumeration that may be specified as: - One of the following dash styles: ['solid', 'dot', 'dash', 'longdash', 'dashdot', 'longdashdot'] - A string containing a dash length list in pixels or percentages (e.g. '5px 10px 2px 2px', '5, 10, 2, 2', '10% 20% 40%', etc.) Returns ------- str """ return self["dash"] @dash.setter def dash(self, val): self["dash"] = val # width # ----- @property def width(self): """ [object Object] Note that this style setting can also be set per direction via `increasing.line.width` and `decreasing.line.width`. The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "ohlc" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). Note that this style setting can also be set per direction via `increasing.line.dash` and `decreasing.line.dash`. width [object Object] Note that this style setting can also be set per direction via `increasing.line.width` and `decreasing.line.width`. """ def __init__(self, arg=None, dash=None, width=None, **kwargs): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.ohlc.Line dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). Note that this style setting can also be set per direction via `increasing.line.dash` and `decreasing.line.dash`. width [object Object] Note that this style setting can also be set per direction via `increasing.line.width` and `decreasing.line.width`. Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.ohlc.Line constructor must be a dict or an instance of plotly.graph_objs.ohlc.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.ohlc import line as v_line # Initialize validators # --------------------- self._validators["dash"] = v_line.DashValidator() self._validators["width"] = v_line.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dash", None) self["dash"] = dash if dash is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Increasing(_BaseTraceHierarchyType): # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.ohlc.increasing.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: color Sets the line color. dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). width Sets the line width (in px). Returns ------- plotly.graph_objs.ohlc.increasing.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "ohlc" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ line plotly.graph_objects.ohlc.increasing.Line instance or dict with compatible properties """ def __init__(self, arg=None, line=None, **kwargs): """ Construct a new Increasing object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.ohlc.Increasing line plotly.graph_objects.ohlc.increasing.Line instance or dict with compatible properties Returns ------- Increasing """ super(Increasing, self).__init__("increasing") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.ohlc.Increasing constructor must be a dict or an instance of plotly.graph_objs.ohlc.Increasing""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.ohlc import increasing as v_increasing # Initialize validators # --------------------- self._validators["line"] = v_increasing.LineValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("line", None) self["line"] = line if line is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Hoverlabel(_BaseTraceHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'right', 'auto'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["align"] @align.setter def align(self, val): self["align"] = val # alignsrc # -------- @property def alignsrc(self): """ Sets the source reference on plot.ly for align . The 'alignsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["alignsrc"] @alignsrc.setter def alignsrc(self, val): self["alignsrc"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the hover labels for this trace The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bgcolorsrc # ---------- @property def bgcolorsrc(self): """ Sets the source reference on plot.ly for bgcolor . The 'bgcolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bgcolorsrc"] @bgcolorsrc.setter def bgcolorsrc(self, val): self["bgcolorsrc"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the border color of the hover labels for this trace. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # bordercolorsrc # -------------- @property def bordercolorsrc(self): """ Sets the source reference on plot.ly for bordercolor . The 'bordercolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bordercolorsrc"] @bordercolorsrc.setter def bordercolorsrc(self, val): self["bordercolorsrc"] = val # font # ---- @property def font(self): """ Sets the font used in hover labels. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.ohlc.hoverlabel.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.ohlc.hoverlabel.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # namelength # ---------- @property def namelength(self): """ Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. The 'namelength' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [-1, 9223372036854775807] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|numpy.ndarray """ return self["namelength"] @namelength.setter def namelength(self, val): self["namelength"] = val # namelengthsrc # ------------- @property def namelengthsrc(self): """ Sets the source reference on plot.ly for namelength . The 'namelengthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["namelengthsrc"] @namelengthsrc.setter def namelengthsrc(self, val): self["namelengthsrc"] = val # split # ----- @property def split(self): """ Show hover information (open, close, high, low) in separate labels. The 'split' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["split"] @split.setter def split(self, val): self["split"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "ohlc" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . split Show hover information (open, close, high, low) in separate labels. """ def __init__( self, arg=None, align=None, alignsrc=None, bgcolor=None, bgcolorsrc=None, bordercolor=None, bordercolorsrc=None, font=None, namelength=None, namelengthsrc=None, split=None, **kwargs ): """ Construct a new Hoverlabel object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.ohlc.Hoverlabel align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . split Show hover information (open, close, high, low) in separate labels. Returns ------- Hoverlabel """ super(Hoverlabel, self).__init__("hoverlabel") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.ohlc.Hoverlabel constructor must be a dict or an instance of plotly.graph_objs.ohlc.Hoverlabel""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.ohlc import hoverlabel as v_hoverlabel # Initialize validators # --------------------- self._validators["align"] = v_hoverlabel.AlignValidator() self._validators["alignsrc"] = v_hoverlabel.AlignsrcValidator() self._validators["bgcolor"] = v_hoverlabel.BgcolorValidator() self._validators["bgcolorsrc"] = v_hoverlabel.BgcolorsrcValidator() self._validators["bordercolor"] = v_hoverlabel.BordercolorValidator() self._validators["bordercolorsrc"] = v_hoverlabel.BordercolorsrcValidator() self._validators["font"] = v_hoverlabel.FontValidator() self._validators["namelength"] = v_hoverlabel.NamelengthValidator() self._validators["namelengthsrc"] = v_hoverlabel.NamelengthsrcValidator() self._validators["split"] = v_hoverlabel.SplitValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("alignsrc", None) self["alignsrc"] = alignsrc if alignsrc is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bgcolorsrc", None) self["bgcolorsrc"] = bgcolorsrc if bgcolorsrc is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("bordercolorsrc", None) self["bordercolorsrc"] = bordercolorsrc if bordercolorsrc is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("namelength", None) self["namelength"] = namelength if namelength is not None else _v _v = arg.pop("namelengthsrc", None) self["namelengthsrc"] = namelengthsrc if namelengthsrc is not None else _v _v = arg.pop("split", None) self["split"] = split if split is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Decreasing(_BaseTraceHierarchyType): # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.ohlc.decreasing.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: color Sets the line color. dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). width Sets the line width (in px). Returns ------- plotly.graph_objs.ohlc.decreasing.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "ohlc" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ line plotly.graph_objects.ohlc.decreasing.Line instance or dict with compatible properties """ def __init__(self, arg=None, line=None, **kwargs): """ Construct a new Decreasing object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.ohlc.Decreasing line plotly.graph_objects.ohlc.decreasing.Line instance or dict with compatible properties Returns ------- Decreasing """ super(Decreasing, self).__init__("decreasing") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.ohlc.Decreasing constructor must be a dict or an instance of plotly.graph_objs.ohlc.Decreasing""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.ohlc import decreasing as v_decreasing # Initialize validators # --------------------- self._validators["line"] = v_decreasing.LineValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("line", None) self["line"] = line if line is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = [ "Decreasing", "Hoverlabel", "Increasing", "Line", "Stream", "decreasing", "hoverlabel", "increasing", ] from plotly.graph_objs.ohlc import increasing from plotly.graph_objs.ohlc import hoverlabel from plotly.graph_objs.ohlc import decreasing plotly-4.4.1+dfsg.orig/plotly/graph_objs/ohlc/decreasing/0000755000175000017500000000000013573746613022762 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/ohlc/decreasing/__init__.py0000644000175000017500000001557113573721550025075 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the line color. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # dash # ---- @property def dash(self): """ Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). The 'dash' property is an enumeration that may be specified as: - One of the following dash styles: ['solid', 'dot', 'dash', 'longdash', 'dashdot', 'longdashdot'] - A string containing a dash length list in pixels or percentages (e.g. '5px 10px 2px 2px', '5, 10, 2, 2', '10% 20% 40%', etc.) Returns ------- str """ return self["dash"] @dash.setter def dash(self, val): self["dash"] = val # width # ----- @property def width(self): """ Sets the line width (in px). The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "ohlc.decreasing" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the line color. dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). width Sets the line width (in px). """ def __init__(self, arg=None, color=None, dash=None, width=None, **kwargs): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.ohlc.decreasing.Line color Sets the line color. dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). width Sets the line width (in px). Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.ohlc.decreasing.Line constructor must be a dict or an instance of plotly.graph_objs.ohlc.decreasing.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.ohlc.decreasing import line as v_line # Initialize validators # --------------------- self._validators["color"] = v_line.ColorValidator() self._validators["dash"] = v_line.DashValidator() self._validators["width"] = v_line.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("dash", None) self["dash"] = dash if dash is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Line"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/scattermapbox/0000755000175000017500000000000013573746613022605 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scattermapbox/unselected/0000755000175000017500000000000013573746613024740 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scattermapbox/unselected/__init__.py0000644000175000017500000001551513573721551027052 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the marker color of unselected points, applied only when a selection exists. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # opacity # ------- @property def opacity(self): """ Sets the marker opacity of unselected points, applied only when a selection exists. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # size # ---- @property def size(self): """ Sets the marker size of unselected points, applied only when a selection exists. The 'size' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattermapbox.unselected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. size Sets the marker size of unselected points, applied only when a selection exists. """ def __init__(self, arg=None, color=None, opacity=None, size=None, **kwargs): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattermapbox.unselected.Marker color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. size Sets the marker size of unselected points, applied only when a selection exists. Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattermapbox.unselected.Marker constructor must be a dict or an instance of plotly.graph_objs.scattermapbox.unselected.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattermapbox.unselected import marker as v_marker # Initialize validators # --------------------- self._validators["color"] = v_marker.ColorValidator() self._validators["opacity"] = v_marker.OpacityValidator() self._validators["size"] = v_marker.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Marker"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/scattermapbox/hoverlabel/0000755000175000017500000000000013573746613024730 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scattermapbox/hoverlabel/__init__.py0000644000175000017500000002547613573721551027051 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattermapbox.hoverlabel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Font object Sets the font used in hover labels. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattermapbox.hoverlabel.Font color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattermapbox.hoverlabel.Font constructor must be a dict or an instance of plotly.graph_objs.scattermapbox.hoverlabel.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattermapbox.hoverlabel import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["colorsrc"] = v_font.ColorsrcValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["familysrc"] = v_font.FamilysrcValidator() self._validators["size"] = v_font.SizeValidator() self._validators["sizesrc"] = v_font.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/scattermapbox/marker/0000755000175000017500000000000013573746613024066 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scattermapbox/marker/colorbar/0000755000175000017500000000000013573746613025671 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scattermapbox/marker/colorbar/title/0000755000175000017500000000000013573746613027012 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scattermapbox/marker/colorbar/title/__init__.py0000644000175000017500000002062713573721551031124 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattermapbox.marker.colorbar.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattermapbox.marker.c olorbar.title.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattermapbox.marker.colorbar.title.Font constructor must be a dict or an instance of plotly.graph_objs.scattermapbox.marker.colorbar.title.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattermapbox.marker.colorbar.title import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/scattermapbox/marker/colorbar/__init__.py0000644000175000017500000006116313573721551030003 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Title(_BaseTraceHierarchyType): # font # ---- @property def font(self): """ Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.scattermapbox.marker.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.scattermapbox.marker.colorbar.title.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # side # ---- @property def side(self): """ Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- Any """ return self["side"] @side.setter def side(self, val): self["side"] = val # text # ---- @property def text(self): """ Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattermapbox.marker.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """ def __init__(self, arg=None, font=None, side=None, text=None, **kwargs): """ Construct a new Title object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattermapbox.marker.colorbar.Title font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- Title """ super(Title, self).__init__("title") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattermapbox.marker.colorbar.Title constructor must be a dict or an instance of plotly.graph_objs.scattermapbox.marker.colorbar.Title""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattermapbox.marker.colorbar import title as v_title # Initialize validators # --------------------- self._validators["font"] = v_title.FontValidator() self._validators["side"] = v_title.SideValidator() self._validators["text"] = v_title.TextValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("side", None) self["side"] = side if side is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickformatstop(_BaseTraceHierarchyType): # dtickrange # ---------- @property def dtickrange(self): """ range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" The 'dtickrange' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'dtickrange[0]' property accepts values of any type (1) The 'dtickrange[1]' property accepts values of any type Returns ------- list """ return self["dtickrange"] @dtickrange.setter def dtickrange(self, val): self["dtickrange"] = val # enabled # ------- @property def enabled(self): """ Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. The 'enabled' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["enabled"] @enabled.setter def enabled(self, val): self["enabled"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # value # ----- @property def value(self): """ string - dtickformat for described zoom level, the same as "tickformat" The 'value' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattermapbox.marker.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """ def __init__( self, arg=None, dtickrange=None, enabled=None, name=None, templateitemname=None, value=None, **kwargs ): """ Construct a new Tickformatstop object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattermapbox.marker.c olorbar.Tickformatstop dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- Tickformatstop """ super(Tickformatstop, self).__init__("tickformatstops") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattermapbox.marker.colorbar.Tickformatstop constructor must be a dict or an instance of plotly.graph_objs.scattermapbox.marker.colorbar.Tickformatstop""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattermapbox.marker.colorbar import ( tickformatstop as v_tickformatstop, ) # Initialize validators # --------------------- self._validators["dtickrange"] = v_tickformatstop.DtickrangeValidator() self._validators["enabled"] = v_tickformatstop.EnabledValidator() self._validators["name"] = v_tickformatstop.NameValidator() self._validators[ "templateitemname" ] = v_tickformatstop.TemplateitemnameValidator() self._validators["value"] = v_tickformatstop.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtickrange", None) self["dtickrange"] = dtickrange if dtickrange is not None else _v _v = arg.pop("enabled", None) self["enabled"] = enabled if enabled is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattermapbox.marker.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Tickfont object Sets the color bar's tick label font Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattermapbox.marker.c olorbar.Tickfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Tickfont """ super(Tickfont, self).__init__("tickfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattermapbox.marker.colorbar.Tickfont constructor must be a dict or an instance of plotly.graph_objs.scattermapbox.marker.colorbar.Tickfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattermapbox.marker.colorbar import ( tickfont as v_tickfont, ) # Initialize validators # --------------------- self._validators["color"] = v_tickfont.ColorValidator() self._validators["family"] = v_tickfont.FamilyValidator() self._validators["size"] = v_tickfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Tickfont", "Tickformatstop", "Tickformatstop", "Title", "title"] from plotly.graph_objs.scattermapbox.marker.colorbar import title plotly-4.4.1+dfsg.orig/plotly/graph_objs/scattermapbox/marker/__init__.py0000644000175000017500000021037313573721552026200 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class ColorBar(_BaseTraceHierarchyType): # bgcolor # ------- @property def bgcolor(self): """ Sets the color of padded area. The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the axis line color. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # borderwidth # ----------- @property def borderwidth(self): """ Sets the width (in px) or the border enclosing this color bar. The 'borderwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["borderwidth"] @borderwidth.setter def borderwidth(self, val): self["borderwidth"] = val # dtick # ----- @property def dtick(self): """ Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" The 'dtick' property accepts values of any type Returns ------- Any """ return self["dtick"] @dtick.setter def dtick(self, val): self["dtick"] = val # exponentformat # -------------- @property def exponentformat(self): """ Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. The 'exponentformat' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'e', 'E', 'power', 'SI', 'B'] Returns ------- Any """ return self["exponentformat"] @exponentformat.setter def exponentformat(self, val): self["exponentformat"] = val # len # --- @property def len(self): """ Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. The 'len' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["len"] @len.setter def len(self, val): self["len"] = val # lenmode # ------- @property def lenmode(self): """ Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. The 'lenmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["lenmode"] @lenmode.setter def lenmode(self, val): self["lenmode"] = val # nticks # ------ @property def nticks(self): """ Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". The 'nticks' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nticks"] @nticks.setter def nticks(self, val): self["nticks"] = val # outlinecolor # ------------ @property def outlinecolor(self): """ Sets the axis line color. The 'outlinecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["outlinecolor"] @outlinecolor.setter def outlinecolor(self, val): self["outlinecolor"] = val # outlinewidth # ------------ @property def outlinewidth(self): """ Sets the width (in px) of the axis line. The 'outlinewidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["outlinewidth"] @outlinewidth.setter def outlinewidth(self, val): self["outlinewidth"] = val # separatethousands # ----------------- @property def separatethousands(self): """ If "true", even 4-digit integers are separated The 'separatethousands' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["separatethousands"] @separatethousands.setter def separatethousands(self, val): self["separatethousands"] = val # showexponent # ------------ @property def showexponent(self): """ If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. The 'showexponent' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showexponent"] @showexponent.setter def showexponent(self, val): self["showexponent"] = val # showticklabels # -------------- @property def showticklabels(self): """ Determines whether or not the tick labels are drawn. The 'showticklabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showticklabels"] @showticklabels.setter def showticklabels(self, val): self["showticklabels"] = val # showtickprefix # -------------- @property def showtickprefix(self): """ If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. The 'showtickprefix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showtickprefix"] @showtickprefix.setter def showtickprefix(self, val): self["showtickprefix"] = val # showticksuffix # -------------- @property def showticksuffix(self): """ Same as `showtickprefix` but for tick suffixes. The 'showticksuffix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showticksuffix"] @showticksuffix.setter def showticksuffix(self, val): self["showticksuffix"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # thicknessmode # ------------- @property def thicknessmode(self): """ Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. The 'thicknessmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["thicknessmode"] @thicknessmode.setter def thicknessmode(self, val): self["thicknessmode"] = val # tick0 # ----- @property def tick0(self): """ Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. The 'tick0' property accepts values of any type Returns ------- Any """ return self["tick0"] @tick0.setter def tick0(self, val): self["tick0"] = val # tickangle # --------- @property def tickangle(self): """ Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. The 'tickangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["tickangle"] @tickangle.setter def tickangle(self, val): self["tickangle"] = val # tickcolor # --------- @property def tickcolor(self): """ Sets the tick color. The 'tickcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["tickcolor"] @tickcolor.setter def tickcolor(self, val): self["tickcolor"] = val # tickfont # -------- @property def tickfont(self): """ Sets the color bar's tick label font The 'tickfont' property is an instance of Tickfont that may be specified as: - An instance of plotly.graph_objs.scattermapbox.marker.colorbar.Tickfont - A dict of string/value properties that will be passed to the Tickfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.scattermapbox.marker.colorbar.Tickfont """ return self["tickfont"] @tickfont.setter def tickfont(self, val): self["tickfont"] = val # tickformat # ---------- @property def tickformat(self): """ Sets the tick label formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'tickformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickformat"] @tickformat.setter def tickformat(self, val): self["tickformat"] = val # tickformatstops # --------------- @property def tickformatstops(self): """ The 'tickformatstops' property is a tuple of instances of Tickformatstop that may be specified as: - A list or tuple of instances of plotly.graph_objs.scattermapbox.marker.colorbar.Tickformatstop - A list or tuple of dicts of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- tuple[plotly.graph_objs.scattermapbox.marker.colorbar.Tickformatstop] """ return self["tickformatstops"] @tickformatstops.setter def tickformatstops(self, val): self["tickformatstops"] = val # tickformatstopdefaults # ---------------------- @property def tickformatstopdefaults(self): """ When used in a template (as layout.template.data.scattermapbox. marker.colorbar.tickformatstopdefaults), sets the default property values to use for elements of scattermapbox.marker.colorbar.tickformatstops The 'tickformatstopdefaults' property is an instance of Tickformatstop that may be specified as: - An instance of plotly.graph_objs.scattermapbox.marker.colorbar.Tickformatstop - A dict of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: Returns ------- plotly.graph_objs.scattermapbox.marker.colorbar.Tickformatstop """ return self["tickformatstopdefaults"] @tickformatstopdefaults.setter def tickformatstopdefaults(self, val): self["tickformatstopdefaults"] = val # ticklen # ------- @property def ticklen(self): """ Sets the tick length (in px). The 'ticklen' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ticklen"] @ticklen.setter def ticklen(self, val): self["ticklen"] = val # tickmode # -------- @property def tickmode(self): """ Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). The 'tickmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'linear', 'array'] Returns ------- Any """ return self["tickmode"] @tickmode.setter def tickmode(self, val): self["tickmode"] = val # tickprefix # ---------- @property def tickprefix(self): """ Sets a tick label prefix. The 'tickprefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickprefix"] @tickprefix.setter def tickprefix(self, val): self["tickprefix"] = val # ticks # ----- @property def ticks(self): """ Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. The 'ticks' property is an enumeration that may be specified as: - One of the following enumeration values: ['outside', 'inside', ''] Returns ------- Any """ return self["ticks"] @ticks.setter def ticks(self, val): self["ticks"] = val # ticksuffix # ---------- @property def ticksuffix(self): """ Sets a tick label suffix. The 'ticksuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ticksuffix"] @ticksuffix.setter def ticksuffix(self, val): self["ticksuffix"] = val # ticktext # -------- @property def ticktext(self): """ Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. The 'ticktext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ticktext"] @ticktext.setter def ticktext(self, val): self["ticktext"] = val # ticktextsrc # ----------- @property def ticktextsrc(self): """ Sets the source reference on plot.ly for ticktext . The 'ticktextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ticktextsrc"] @ticktextsrc.setter def ticktextsrc(self, val): self["ticktextsrc"] = val # tickvals # -------- @property def tickvals(self): """ Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. The 'tickvals' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["tickvals"] @tickvals.setter def tickvals(self, val): self["tickvals"] = val # tickvalssrc # ----------- @property def tickvalssrc(self): """ Sets the source reference on plot.ly for tickvals . The 'tickvalssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tickvalssrc"] @tickvalssrc.setter def tickvalssrc(self, val): self["tickvalssrc"] = val # tickwidth # --------- @property def tickwidth(self): """ Sets the tick width (in px). The 'tickwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["tickwidth"] @tickwidth.setter def tickwidth(self, val): self["tickwidth"] = val # title # ----- @property def title(self): """ The 'title' property is an instance of Title that may be specified as: - An instance of plotly.graph_objs.scattermapbox.marker.colorbar.Title - A dict of string/value properties that will be passed to the Title constructor Supported dict properties: font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- plotly.graph_objs.scattermapbox.marker.colorbar.Title """ return self["title"] @title.setter def title(self, val): self["title"] = val # titlefont # --------- @property def titlefont(self): """ Deprecated: Please use scattermapbox.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.scattermapbox.marker.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- """ return self["titlefont"] @titlefont.setter def titlefont(self, val): self["titlefont"] = val # titleside # --------- @property def titleside(self): """ Deprecated: Please use scattermapbox.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- """ return self["titleside"] @titleside.setter def titleside(self, val): self["titleside"] = val # x # - @property def x(self): """ Sets the x position of the color bar (in plot fraction). The 'x' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["x"] @x.setter def x(self, val): self["x"] = val # xanchor # ------- @property def xanchor(self): """ Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. The 'xanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'center', 'right'] Returns ------- Any """ return self["xanchor"] @xanchor.setter def xanchor(self, val): self["xanchor"] = val # xpad # ---- @property def xpad(self): """ Sets the amount of padding (in px) along the x direction. The 'xpad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["xpad"] @xpad.setter def xpad(self, val): self["xpad"] = val # y # - @property def y(self): """ Sets the y position of the color bar (in plot fraction). The 'y' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["y"] @y.setter def y(self, val): self["y"] = val # yanchor # ------- @property def yanchor(self): """ Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. The 'yanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['top', 'middle', 'bottom'] Returns ------- Any """ return self["yanchor"] @yanchor.setter def yanchor(self, val): self["yanchor"] = val # ypad # ---- @property def ypad(self): """ Sets the amount of padding (in px) along the y direction. The 'ypad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ypad"] @ypad.setter def ypad(self, val): self["ypad"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattermapbox.marker" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.scattermapbox.marker.co lorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.scatte rmapbox.marker.colorbar.tickformatstopdefaults), sets the default property values to use for elements of scattermapbox.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.scattermapbox.marker.colorbar.Titl e instance or dict with compatible properties titlefont Deprecated: Please use scattermapbox.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use scattermapbox.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """ _mapped_properties = { "titlefont": ("title", "font"), "titleside": ("title", "side"), } def __init__( self, arg=None, bgcolor=None, bordercolor=None, borderwidth=None, dtick=None, exponentformat=None, len=None, lenmode=None, nticks=None, outlinecolor=None, outlinewidth=None, separatethousands=None, showexponent=None, showticklabels=None, showtickprefix=None, showticksuffix=None, thickness=None, thicknessmode=None, tick0=None, tickangle=None, tickcolor=None, tickfont=None, tickformat=None, tickformatstops=None, tickformatstopdefaults=None, ticklen=None, tickmode=None, tickprefix=None, ticks=None, ticksuffix=None, ticktext=None, ticktextsrc=None, tickvals=None, tickvalssrc=None, tickwidth=None, title=None, titlefont=None, titleside=None, x=None, xanchor=None, xpad=None, y=None, yanchor=None, ypad=None, **kwargs ): """ Construct a new ColorBar object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattermapbox.marker.ColorBar bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.scattermapbox.marker.co lorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.scatte rmapbox.marker.colorbar.tickformatstopdefaults), sets the default property values to use for elements of scattermapbox.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.scattermapbox.marker.colorbar.Titl e instance or dict with compatible properties titlefont Deprecated: Please use scattermapbox.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use scattermapbox.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- ColorBar """ super(ColorBar, self).__init__("colorbar") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattermapbox.marker.ColorBar constructor must be a dict or an instance of plotly.graph_objs.scattermapbox.marker.ColorBar""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattermapbox.marker import colorbar as v_colorbar # Initialize validators # --------------------- self._validators["bgcolor"] = v_colorbar.BgcolorValidator() self._validators["bordercolor"] = v_colorbar.BordercolorValidator() self._validators["borderwidth"] = v_colorbar.BorderwidthValidator() self._validators["dtick"] = v_colorbar.DtickValidator() self._validators["exponentformat"] = v_colorbar.ExponentformatValidator() self._validators["len"] = v_colorbar.LenValidator() self._validators["lenmode"] = v_colorbar.LenmodeValidator() self._validators["nticks"] = v_colorbar.NticksValidator() self._validators["outlinecolor"] = v_colorbar.OutlinecolorValidator() self._validators["outlinewidth"] = v_colorbar.OutlinewidthValidator() self._validators["separatethousands"] = v_colorbar.SeparatethousandsValidator() self._validators["showexponent"] = v_colorbar.ShowexponentValidator() self._validators["showticklabels"] = v_colorbar.ShowticklabelsValidator() self._validators["showtickprefix"] = v_colorbar.ShowtickprefixValidator() self._validators["showticksuffix"] = v_colorbar.ShowticksuffixValidator() self._validators["thickness"] = v_colorbar.ThicknessValidator() self._validators["thicknessmode"] = v_colorbar.ThicknessmodeValidator() self._validators["tick0"] = v_colorbar.Tick0Validator() self._validators["tickangle"] = v_colorbar.TickangleValidator() self._validators["tickcolor"] = v_colorbar.TickcolorValidator() self._validators["tickfont"] = v_colorbar.TickfontValidator() self._validators["tickformat"] = v_colorbar.TickformatValidator() self._validators["tickformatstops"] = v_colorbar.TickformatstopsValidator() self._validators[ "tickformatstopdefaults" ] = v_colorbar.TickformatstopValidator() self._validators["ticklen"] = v_colorbar.TicklenValidator() self._validators["tickmode"] = v_colorbar.TickmodeValidator() self._validators["tickprefix"] = v_colorbar.TickprefixValidator() self._validators["ticks"] = v_colorbar.TicksValidator() self._validators["ticksuffix"] = v_colorbar.TicksuffixValidator() self._validators["ticktext"] = v_colorbar.TicktextValidator() self._validators["ticktextsrc"] = v_colorbar.TicktextsrcValidator() self._validators["tickvals"] = v_colorbar.TickvalsValidator() self._validators["tickvalssrc"] = v_colorbar.TickvalssrcValidator() self._validators["tickwidth"] = v_colorbar.TickwidthValidator() self._validators["title"] = v_colorbar.TitleValidator() self._validators["x"] = v_colorbar.XValidator() self._validators["xanchor"] = v_colorbar.XanchorValidator() self._validators["xpad"] = v_colorbar.XpadValidator() self._validators["y"] = v_colorbar.YValidator() self._validators["yanchor"] = v_colorbar.YanchorValidator() self._validators["ypad"] = v_colorbar.YpadValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("borderwidth", None) self["borderwidth"] = borderwidth if borderwidth is not None else _v _v = arg.pop("dtick", None) self["dtick"] = dtick if dtick is not None else _v _v = arg.pop("exponentformat", None) self["exponentformat"] = exponentformat if exponentformat is not None else _v _v = arg.pop("len", None) self["len"] = len if len is not None else _v _v = arg.pop("lenmode", None) self["lenmode"] = lenmode if lenmode is not None else _v _v = arg.pop("nticks", None) self["nticks"] = nticks if nticks is not None else _v _v = arg.pop("outlinecolor", None) self["outlinecolor"] = outlinecolor if outlinecolor is not None else _v _v = arg.pop("outlinewidth", None) self["outlinewidth"] = outlinewidth if outlinewidth is not None else _v _v = arg.pop("separatethousands", None) self["separatethousands"] = ( separatethousands if separatethousands is not None else _v ) _v = arg.pop("showexponent", None) self["showexponent"] = showexponent if showexponent is not None else _v _v = arg.pop("showticklabels", None) self["showticklabels"] = showticklabels if showticklabels is not None else _v _v = arg.pop("showtickprefix", None) self["showtickprefix"] = showtickprefix if showtickprefix is not None else _v _v = arg.pop("showticksuffix", None) self["showticksuffix"] = showticksuffix if showticksuffix is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("thicknessmode", None) self["thicknessmode"] = thicknessmode if thicknessmode is not None else _v _v = arg.pop("tick0", None) self["tick0"] = tick0 if tick0 is not None else _v _v = arg.pop("tickangle", None) self["tickangle"] = tickangle if tickangle is not None else _v _v = arg.pop("tickcolor", None) self["tickcolor"] = tickcolor if tickcolor is not None else _v _v = arg.pop("tickfont", None) self["tickfont"] = tickfont if tickfont is not None else _v _v = arg.pop("tickformat", None) self["tickformat"] = tickformat if tickformat is not None else _v _v = arg.pop("tickformatstops", None) self["tickformatstops"] = tickformatstops if tickformatstops is not None else _v _v = arg.pop("tickformatstopdefaults", None) self["tickformatstopdefaults"] = ( tickformatstopdefaults if tickformatstopdefaults is not None else _v ) _v = arg.pop("ticklen", None) self["ticklen"] = ticklen if ticklen is not None else _v _v = arg.pop("tickmode", None) self["tickmode"] = tickmode if tickmode is not None else _v _v = arg.pop("tickprefix", None) self["tickprefix"] = tickprefix if tickprefix is not None else _v _v = arg.pop("ticks", None) self["ticks"] = ticks if ticks is not None else _v _v = arg.pop("ticksuffix", None) self["ticksuffix"] = ticksuffix if ticksuffix is not None else _v _v = arg.pop("ticktext", None) self["ticktext"] = ticktext if ticktext is not None else _v _v = arg.pop("ticktextsrc", None) self["ticktextsrc"] = ticktextsrc if ticktextsrc is not None else _v _v = arg.pop("tickvals", None) self["tickvals"] = tickvals if tickvals is not None else _v _v = arg.pop("tickvalssrc", None) self["tickvalssrc"] = tickvalssrc if tickvalssrc is not None else _v _v = arg.pop("tickwidth", None) self["tickwidth"] = tickwidth if tickwidth is not None else _v _v = arg.pop("title", None) self["title"] = title if title is not None else _v _v = arg.pop("titlefont", None) _v = titlefont if titlefont is not None else _v if _v is not None: self["titlefont"] = _v _v = arg.pop("titleside", None) _v = titleside if titleside is not None else _v if _v is not None: self["titleside"] = _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xanchor", None) self["xanchor"] = xanchor if xanchor is not None else _v _v = arg.pop("xpad", None) self["xpad"] = xpad if xpad is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("yanchor", None) self["yanchor"] = yanchor if yanchor is not None else _v _v = arg.pop("ypad", None) self["ypad"] = ypad if ypad is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["ColorBar", "colorbar"] from plotly.graph_objs.scattermapbox.marker import colorbar plotly-4.4.1+dfsg.orig/plotly/graph_objs/scattermapbox/__init__.py0000644000175000017500000025316113573721552024721 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Unselected(_BaseTraceHierarchyType): # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.scattermapbox.unselected.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. size Sets the marker size of unselected points, applied only when a selection exists. Returns ------- plotly.graph_objs.scattermapbox.unselected.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattermapbox" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ marker plotly.graph_objects.scattermapbox.unselected.Marker instance or dict with compatible properties """ def __init__(self, arg=None, marker=None, **kwargs): """ Construct a new Unselected object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattermapbox.Unselected marker plotly.graph_objects.scattermapbox.unselected.Marker instance or dict with compatible properties Returns ------- Unselected """ super(Unselected, self).__init__("unselected") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattermapbox.Unselected constructor must be a dict or an instance of plotly.graph_objs.scattermapbox.Unselected""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattermapbox import unselected as v_unselected # Initialize validators # --------------------- self._validators["marker"] = v_unselected.MarkerValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Textfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattermapbox" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Textfont object Sets the icon text font (color=mapbox.layer.paint.text-color, size=mapbox.layer.layout.text-size). Has an effect only when `type` is set to "symbol". Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattermapbox.Textfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Textfont """ super(Textfont, self).__init__("textfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattermapbox.Textfont constructor must be a dict or an instance of plotly.graph_objs.scattermapbox.Textfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattermapbox import textfont as v_textfont # Initialize validators # --------------------- self._validators["color"] = v_textfont.ColorValidator() self._validators["family"] = v_textfont.FamilyValidator() self._validators["size"] = v_textfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Stream(_BaseTraceHierarchyType): # maxpoints # --------- @property def maxpoints(self): """ Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. The 'maxpoints' property is a number and may be specified as: - An int or float in the interval [0, 10000] Returns ------- int|float """ return self["maxpoints"] @maxpoints.setter def maxpoints(self, val): self["maxpoints"] = val # token # ----- @property def token(self): """ The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. The 'token' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["token"] @token.setter def token(self, val): self["token"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattermapbox" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """ def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): """ Construct a new Stream object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattermapbox.Stream maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- Stream """ super(Stream, self).__init__("stream") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattermapbox.Stream constructor must be a dict or an instance of plotly.graph_objs.scattermapbox.Stream""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattermapbox import stream as v_stream # Initialize validators # --------------------- self._validators["maxpoints"] = v_stream.MaxpointsValidator() self._validators["token"] = v_stream.TokenValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("maxpoints", None) self["maxpoints"] = maxpoints if maxpoints is not None else _v _v = arg.pop("token", None) self["token"] = token if token is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Selected(_BaseTraceHierarchyType): # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.scattermapbox.selected.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. size Sets the marker size of selected points. Returns ------- plotly.graph_objs.scattermapbox.selected.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattermapbox" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ marker plotly.graph_objects.scattermapbox.selected.Marker instance or dict with compatible properties """ def __init__(self, arg=None, marker=None, **kwargs): """ Construct a new Selected object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattermapbox.Selected marker plotly.graph_objects.scattermapbox.selected.Marker instance or dict with compatible properties Returns ------- Selected """ super(Selected, self).__init__("selected") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattermapbox.Selected constructor must be a dict or an instance of plotly.graph_objs.scattermapbox.Selected""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattermapbox import selected as v_selected # Initialize validators # --------------------- self._validators["marker"] = v_selected.MarkerValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # autocolorscale # -------------- @property def autocolorscale(self): """ Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. The 'autocolorscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocolorscale"] @autocolorscale.setter def autocolorscale(self, val): self["autocolorscale"] = val # cauto # ----- @property def cauto(self): """ Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. The 'cauto' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["cauto"] @cauto.setter def cauto(self, val): self["cauto"] = val # cmax # ---- @property def cmax(self): """ Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. The 'cmax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmax"] @cmax.setter def cmax(self, val): self["cmax"] = val # cmid # ---- @property def cmid(self): """ Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. The 'cmid' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmid"] @cmid.setter def cmid(self, val): self["cmid"] = val # cmin # ---- @property def cmin(self): """ Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. The 'cmin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmin"] @cmin.setter def cmin(self, val): self["cmin"] = val # color # ----- @property def color(self): """ Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A number that will be interpreted as a color according to scattermapbox.marker.colorscale - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # coloraxis # --------- @property def coloraxis(self): """ Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. The 'coloraxis' property is an identifier of a particular subplot, of type 'coloraxis', that may be specified as the string 'coloraxis' optionally followed by an integer >= 1 (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) Returns ------- str """ return self["coloraxis"] @coloraxis.setter def coloraxis(self, val): self["coloraxis"] = val # colorbar # -------- @property def colorbar(self): """ The 'colorbar' property is an instance of ColorBar that may be specified as: - An instance of plotly.graph_objs.scattermapbox.marker.ColorBar - A dict of string/value properties that will be passed to the ColorBar constructor Supported dict properties: bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.scattermapbox.m arker.colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.scattermapbox.marker.colorbar.tickformatstopd efaults), sets the default property values to use for elements of scattermapbox.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.scattermapbox.marker.color bar.Title instance or dict with compatible properties titlefont Deprecated: Please use scattermapbox.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use scattermapbox.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- plotly.graph_objs.scattermapbox.marker.ColorBar """ return self["colorbar"] @colorbar.setter def colorbar(self, val): self["colorbar"] = val # colorscale # ---------- @property def colorscale(self): """ Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnB u,Greens,YlOrRd,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland ,Jet,Hot,Blackbody,Earth,Electric,Viridis,Cividis. The 'colorscale' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # opacity # ------- @property def opacity(self): """ Sets the marker opacity. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # opacitysrc # ---------- @property def opacitysrc(self): """ Sets the source reference on plot.ly for opacity . The 'opacitysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["opacitysrc"] @opacitysrc.setter def opacitysrc(self, val): self["opacitysrc"] = val # reversescale # ------------ @property def reversescale(self): """ Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. The 'reversescale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["reversescale"] @reversescale.setter def reversescale(self, val): self["reversescale"] = val # showscale # --------- @property def showscale(self): """ Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. The 'showscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showscale"] @showscale.setter def showscale(self, val): self["showscale"] = val # size # ---- @property def size(self): """ Sets the marker size (in px). The 'size' property is a number and may be specified as: - An int or float in the interval [0, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizemin # ------- @property def sizemin(self): """ Has an effect only if `marker.size` is set to a numerical array. Sets the minimum size (in px) of the rendered marker points. The 'sizemin' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["sizemin"] @sizemin.setter def sizemin(self, val): self["sizemin"] = val # sizemode # -------- @property def sizemode(self): """ Has an effect only if `marker.size` is set to a numerical array. Sets the rule for which the data in `size` is converted to pixels. The 'sizemode' property is an enumeration that may be specified as: - One of the following enumeration values: ['diameter', 'area'] Returns ------- Any """ return self["sizemode"] @sizemode.setter def sizemode(self, val): self["sizemode"] = val # sizeref # ------- @property def sizeref(self): """ Has an effect only if `marker.size` is set to a numerical array. Sets the scale factor used to determine the rendered size of marker points. Use with `sizemin` and `sizemode`. The 'sizeref' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["sizeref"] @sizeref.setter def sizeref(self, val): self["sizeref"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # symbol # ------ @property def symbol(self): """ Sets the marker symbol. Full list: https://www.mapbox.com/maki- icons/ Note that the array `marker.color` and `marker.size` are only available for "circle" symbols. The 'symbol' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["symbol"] @symbol.setter def symbol(self, val): self["symbol"] = val # symbolsrc # --------- @property def symbolsrc(self): """ Sets the source reference on plot.ly for symbol . The 'symbolsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["symbolsrc"] @symbolsrc.setter def symbolsrc(self, val): self["symbolsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattermapbox" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.scattermapbox.marker.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu ,Reds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . opacity Sets the marker opacity. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. size Sets the marker size (in px). sizemin Has an effect only if `marker.size` is set to a numerical array. Sets the minimum size (in px) of the rendered marker points. sizemode Has an effect only if `marker.size` is set to a numerical array. Sets the rule for which the data in `size` is converted to pixels. sizeref Has an effect only if `marker.size` is set to a numerical array. Sets the scale factor used to determine the rendered size of marker points. Use with `sizemin` and `sizemode`. sizesrc Sets the source reference on plot.ly for size . symbol Sets the marker symbol. Full list: https://www.mapbox.com/maki-icons/ Note that the array `marker.color` and `marker.size` are only available for "circle" symbols. symbolsrc Sets the source reference on plot.ly for symbol . """ def __init__( self, arg=None, autocolorscale=None, cauto=None, cmax=None, cmid=None, cmin=None, color=None, coloraxis=None, colorbar=None, colorscale=None, colorsrc=None, opacity=None, opacitysrc=None, reversescale=None, showscale=None, size=None, sizemin=None, sizemode=None, sizeref=None, sizesrc=None, symbol=None, symbolsrc=None, **kwargs ): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattermapbox.Marker autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.scattermapbox.marker.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu ,Reds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . opacity Sets the marker opacity. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. size Sets the marker size (in px). sizemin Has an effect only if `marker.size` is set to a numerical array. Sets the minimum size (in px) of the rendered marker points. sizemode Has an effect only if `marker.size` is set to a numerical array. Sets the rule for which the data in `size` is converted to pixels. sizeref Has an effect only if `marker.size` is set to a numerical array. Sets the scale factor used to determine the rendered size of marker points. Use with `sizemin` and `sizemode`. sizesrc Sets the source reference on plot.ly for size . symbol Sets the marker symbol. Full list: https://www.mapbox.com/maki-icons/ Note that the array `marker.color` and `marker.size` are only available for "circle" symbols. symbolsrc Sets the source reference on plot.ly for symbol . Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattermapbox.Marker constructor must be a dict or an instance of plotly.graph_objs.scattermapbox.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattermapbox import marker as v_marker # Initialize validators # --------------------- self._validators["autocolorscale"] = v_marker.AutocolorscaleValidator() self._validators["cauto"] = v_marker.CautoValidator() self._validators["cmax"] = v_marker.CmaxValidator() self._validators["cmid"] = v_marker.CmidValidator() self._validators["cmin"] = v_marker.CminValidator() self._validators["color"] = v_marker.ColorValidator() self._validators["coloraxis"] = v_marker.ColoraxisValidator() self._validators["colorbar"] = v_marker.ColorBarValidator() self._validators["colorscale"] = v_marker.ColorscaleValidator() self._validators["colorsrc"] = v_marker.ColorsrcValidator() self._validators["opacity"] = v_marker.OpacityValidator() self._validators["opacitysrc"] = v_marker.OpacitysrcValidator() self._validators["reversescale"] = v_marker.ReversescaleValidator() self._validators["showscale"] = v_marker.ShowscaleValidator() self._validators["size"] = v_marker.SizeValidator() self._validators["sizemin"] = v_marker.SizeminValidator() self._validators["sizemode"] = v_marker.SizemodeValidator() self._validators["sizeref"] = v_marker.SizerefValidator() self._validators["sizesrc"] = v_marker.SizesrcValidator() self._validators["symbol"] = v_marker.SymbolValidator() self._validators["symbolsrc"] = v_marker.SymbolsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autocolorscale", None) self["autocolorscale"] = autocolorscale if autocolorscale is not None else _v _v = arg.pop("cauto", None) self["cauto"] = cauto if cauto is not None else _v _v = arg.pop("cmax", None) self["cmax"] = cmax if cmax is not None else _v _v = arg.pop("cmid", None) self["cmid"] = cmid if cmid is not None else _v _v = arg.pop("cmin", None) self["cmin"] = cmin if cmin is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("coloraxis", None) self["coloraxis"] = coloraxis if coloraxis is not None else _v _v = arg.pop("colorbar", None) self["colorbar"] = colorbar if colorbar is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("opacitysrc", None) self["opacitysrc"] = opacitysrc if opacitysrc is not None else _v _v = arg.pop("reversescale", None) self["reversescale"] = reversescale if reversescale is not None else _v _v = arg.pop("showscale", None) self["showscale"] = showscale if showscale is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizemin", None) self["sizemin"] = sizemin if sizemin is not None else _v _v = arg.pop("sizemode", None) self["sizemode"] = sizemode if sizemode is not None else _v _v = arg.pop("sizeref", None) self["sizeref"] = sizeref if sizeref is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v _v = arg.pop("symbol", None) self["symbol"] = symbol if symbol is not None else _v _v = arg.pop("symbolsrc", None) self["symbolsrc"] = symbolsrc if symbolsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the line color. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # width # ----- @property def width(self): """ Sets the line width (in px). The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattermapbox" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the line color. width Sets the line width (in px). """ def __init__(self, arg=None, color=None, width=None, **kwargs): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattermapbox.Line color Sets the line color. width Sets the line width (in px). Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattermapbox.Line constructor must be a dict or an instance of plotly.graph_objs.scattermapbox.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattermapbox import line as v_line # Initialize validators # --------------------- self._validators["color"] = v_line.ColorValidator() self._validators["width"] = v_line.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Hoverlabel(_BaseTraceHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'right', 'auto'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["align"] @align.setter def align(self, val): self["align"] = val # alignsrc # -------- @property def alignsrc(self): """ Sets the source reference on plot.ly for align . The 'alignsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["alignsrc"] @alignsrc.setter def alignsrc(self, val): self["alignsrc"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the hover labels for this trace The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bgcolorsrc # ---------- @property def bgcolorsrc(self): """ Sets the source reference on plot.ly for bgcolor . The 'bgcolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bgcolorsrc"] @bgcolorsrc.setter def bgcolorsrc(self, val): self["bgcolorsrc"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the border color of the hover labels for this trace. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # bordercolorsrc # -------------- @property def bordercolorsrc(self): """ Sets the source reference on plot.ly for bordercolor . The 'bordercolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bordercolorsrc"] @bordercolorsrc.setter def bordercolorsrc(self, val): self["bordercolorsrc"] = val # font # ---- @property def font(self): """ Sets the font used in hover labels. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.scattermapbox.hoverlabel.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.scattermapbox.hoverlabel.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # namelength # ---------- @property def namelength(self): """ Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. The 'namelength' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [-1, 9223372036854775807] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|numpy.ndarray """ return self["namelength"] @namelength.setter def namelength(self, val): self["namelength"] = val # namelengthsrc # ------------- @property def namelengthsrc(self): """ Sets the source reference on plot.ly for namelength . The 'namelengthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["namelengthsrc"] @namelengthsrc.setter def namelengthsrc(self, val): self["namelengthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattermapbox" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """ def __init__( self, arg=None, align=None, alignsrc=None, bgcolor=None, bgcolorsrc=None, bordercolor=None, bordercolorsrc=None, font=None, namelength=None, namelengthsrc=None, **kwargs ): """ Construct a new Hoverlabel object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattermapbox.Hoverlabel align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- Hoverlabel """ super(Hoverlabel, self).__init__("hoverlabel") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattermapbox.Hoverlabel constructor must be a dict or an instance of plotly.graph_objs.scattermapbox.Hoverlabel""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattermapbox import hoverlabel as v_hoverlabel # Initialize validators # --------------------- self._validators["align"] = v_hoverlabel.AlignValidator() self._validators["alignsrc"] = v_hoverlabel.AlignsrcValidator() self._validators["bgcolor"] = v_hoverlabel.BgcolorValidator() self._validators["bgcolorsrc"] = v_hoverlabel.BgcolorsrcValidator() self._validators["bordercolor"] = v_hoverlabel.BordercolorValidator() self._validators["bordercolorsrc"] = v_hoverlabel.BordercolorsrcValidator() self._validators["font"] = v_hoverlabel.FontValidator() self._validators["namelength"] = v_hoverlabel.NamelengthValidator() self._validators["namelengthsrc"] = v_hoverlabel.NamelengthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("alignsrc", None) self["alignsrc"] = alignsrc if alignsrc is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bgcolorsrc", None) self["bgcolorsrc"] = bgcolorsrc if bgcolorsrc is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("bordercolorsrc", None) self["bordercolorsrc"] = bordercolorsrc if bordercolorsrc is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("namelength", None) self["namelength"] = namelength if namelength is not None else _v _v = arg.pop("namelengthsrc", None) self["namelengthsrc"] = namelengthsrc if namelengthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = [ "Hoverlabel", "Line", "Marker", "Selected", "Stream", "Textfont", "Unselected", "hoverlabel", "marker", "selected", "unselected", ] from plotly.graph_objs.scattermapbox import unselected from plotly.graph_objs.scattermapbox import selected from plotly.graph_objs.scattermapbox import marker from plotly.graph_objs.scattermapbox import hoverlabel plotly-4.4.1+dfsg.orig/plotly/graph_objs/scattermapbox/selected/0000755000175000017500000000000013573746613024375 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scattermapbox/selected/__init__.py0000644000175000017500000001457313573721551026512 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the marker color of selected points. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # opacity # ------- @property def opacity(self): """ Sets the marker opacity of selected points. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # size # ---- @property def size(self): """ Sets the marker size of selected points. The 'size' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattermapbox.selected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. size Sets the marker size of selected points. """ def __init__(self, arg=None, color=None, opacity=None, size=None, **kwargs): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattermapbox.selected.Marker color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. size Sets the marker size of selected points. Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattermapbox.selected.Marker constructor must be a dict or an instance of plotly.graph_objs.scattermapbox.selected.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattermapbox.selected import marker as v_marker # Initialize validators # --------------------- self._validators["color"] = v_marker.ColorValidator() self._validators["opacity"] = v_marker.OpacityValidator() self._validators["size"] = v_marker.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Marker"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/sunburst/0000755000175000017500000000000013573746613021616 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/sunburst/hoverlabel/0000755000175000017500000000000013573746613023741 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/sunburst/hoverlabel/__init__.py0000644000175000017500000002544513573721552026057 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "sunburst.hoverlabel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Font object Sets the font used in hover labels. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.sunburst.hoverlabel.Font color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.sunburst.hoverlabel.Font constructor must be a dict or an instance of plotly.graph_objs.sunburst.hoverlabel.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.sunburst.hoverlabel import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["colorsrc"] = v_font.ColorsrcValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["familysrc"] = v_font.FamilysrcValidator() self._validators["size"] = v_font.SizeValidator() self._validators["sizesrc"] = v_font.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/sunburst/marker/0000755000175000017500000000000013573746613023077 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/sunburst/marker/colorbar/0000755000175000017500000000000013573746613024702 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/sunburst/marker/colorbar/title/0000755000175000017500000000000013573746613026023 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/sunburst/marker/colorbar/title/__init__.py0000644000175000017500000002057513573721552030140 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "sunburst.marker.colorbar.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.sunburst.marker.colorbar.title.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.sunburst.marker.colorbar.title.Font constructor must be a dict or an instance of plotly.graph_objs.sunburst.marker.colorbar.title.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.sunburst.marker.colorbar.title import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/sunburst/marker/colorbar/__init__.py0000644000175000017500000006077713573721552027027 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Title(_BaseTraceHierarchyType): # font # ---- @property def font(self): """ Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.sunburst.marker.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.sunburst.marker.colorbar.title.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # side # ---- @property def side(self): """ Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- Any """ return self["side"] @side.setter def side(self, val): self["side"] = val # text # ---- @property def text(self): """ Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "sunburst.marker.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """ def __init__(self, arg=None, font=None, side=None, text=None, **kwargs): """ Construct a new Title object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.sunburst.marker.colorbar.Title font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- Title """ super(Title, self).__init__("title") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.sunburst.marker.colorbar.Title constructor must be a dict or an instance of plotly.graph_objs.sunburst.marker.colorbar.Title""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.sunburst.marker.colorbar import title as v_title # Initialize validators # --------------------- self._validators["font"] = v_title.FontValidator() self._validators["side"] = v_title.SideValidator() self._validators["text"] = v_title.TextValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("side", None) self["side"] = side if side is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickformatstop(_BaseTraceHierarchyType): # dtickrange # ---------- @property def dtickrange(self): """ range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" The 'dtickrange' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'dtickrange[0]' property accepts values of any type (1) The 'dtickrange[1]' property accepts values of any type Returns ------- list """ return self["dtickrange"] @dtickrange.setter def dtickrange(self, val): self["dtickrange"] = val # enabled # ------- @property def enabled(self): """ Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. The 'enabled' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["enabled"] @enabled.setter def enabled(self, val): self["enabled"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # value # ----- @property def value(self): """ string - dtickformat for described zoom level, the same as "tickformat" The 'value' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "sunburst.marker.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """ def __init__( self, arg=None, dtickrange=None, enabled=None, name=None, templateitemname=None, value=None, **kwargs ): """ Construct a new Tickformatstop object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.sunburst.marker.colorb ar.Tickformatstop dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- Tickformatstop """ super(Tickformatstop, self).__init__("tickformatstops") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.sunburst.marker.colorbar.Tickformatstop constructor must be a dict or an instance of plotly.graph_objs.sunburst.marker.colorbar.Tickformatstop""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.sunburst.marker.colorbar import ( tickformatstop as v_tickformatstop, ) # Initialize validators # --------------------- self._validators["dtickrange"] = v_tickformatstop.DtickrangeValidator() self._validators["enabled"] = v_tickformatstop.EnabledValidator() self._validators["name"] = v_tickformatstop.NameValidator() self._validators[ "templateitemname" ] = v_tickformatstop.TemplateitemnameValidator() self._validators["value"] = v_tickformatstop.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtickrange", None) self["dtickrange"] = dtickrange if dtickrange is not None else _v _v = arg.pop("enabled", None) self["enabled"] = enabled if enabled is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "sunburst.marker.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Tickfont object Sets the color bar's tick label font Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.sunburst.marker.colorbar.Tickfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Tickfont """ super(Tickfont, self).__init__("tickfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.sunburst.marker.colorbar.Tickfont constructor must be a dict or an instance of plotly.graph_objs.sunburst.marker.colorbar.Tickfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.sunburst.marker.colorbar import tickfont as v_tickfont # Initialize validators # --------------------- self._validators["color"] = v_tickfont.ColorValidator() self._validators["family"] = v_tickfont.FamilyValidator() self._validators["size"] = v_tickfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Tickfont", "Tickformatstop", "Tickformatstop", "Title", "title"] from plotly.graph_objs.sunburst.marker.colorbar import title plotly-4.4.1+dfsg.orig/plotly/graph_objs/sunburst/marker/__init__.py0000644000175000017500000022702113573721553025210 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the color of the line enclosing each sector. Defaults to the `paper_bgcolor` value. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # width # ----- @property def width(self): """ Sets the width (in px) of the line enclosing each sector. The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["width"] @width.setter def width(self, val): self["width"] = val # widthsrc # -------- @property def widthsrc(self): """ Sets the source reference on plot.ly for width . The 'widthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["widthsrc"] @widthsrc.setter def widthsrc(self, val): self["widthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "sunburst.marker" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the color of the line enclosing each sector. Defaults to the `paper_bgcolor` value. colorsrc Sets the source reference on plot.ly for color . width Sets the width (in px) of the line enclosing each sector. widthsrc Sets the source reference on plot.ly for width . """ def __init__( self, arg=None, color=None, colorsrc=None, width=None, widthsrc=None, **kwargs ): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.sunburst.marker.Line color Sets the color of the line enclosing each sector. Defaults to the `paper_bgcolor` value. colorsrc Sets the source reference on plot.ly for color . width Sets the width (in px) of the line enclosing each sector. widthsrc Sets the source reference on plot.ly for width . Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.sunburst.marker.Line constructor must be a dict or an instance of plotly.graph_objs.sunburst.marker.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.sunburst.marker import line as v_line # Initialize validators # --------------------- self._validators["color"] = v_line.ColorValidator() self._validators["colorsrc"] = v_line.ColorsrcValidator() self._validators["width"] = v_line.WidthValidator() self._validators["widthsrc"] = v_line.WidthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v _v = arg.pop("widthsrc", None) self["widthsrc"] = widthsrc if widthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class ColorBar(_BaseTraceHierarchyType): # bgcolor # ------- @property def bgcolor(self): """ Sets the color of padded area. The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the axis line color. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # borderwidth # ----------- @property def borderwidth(self): """ Sets the width (in px) or the border enclosing this color bar. The 'borderwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["borderwidth"] @borderwidth.setter def borderwidth(self, val): self["borderwidth"] = val # dtick # ----- @property def dtick(self): """ Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" The 'dtick' property accepts values of any type Returns ------- Any """ return self["dtick"] @dtick.setter def dtick(self, val): self["dtick"] = val # exponentformat # -------------- @property def exponentformat(self): """ Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. The 'exponentformat' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'e', 'E', 'power', 'SI', 'B'] Returns ------- Any """ return self["exponentformat"] @exponentformat.setter def exponentformat(self, val): self["exponentformat"] = val # len # --- @property def len(self): """ Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. The 'len' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["len"] @len.setter def len(self, val): self["len"] = val # lenmode # ------- @property def lenmode(self): """ Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. The 'lenmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["lenmode"] @lenmode.setter def lenmode(self, val): self["lenmode"] = val # nticks # ------ @property def nticks(self): """ Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". The 'nticks' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nticks"] @nticks.setter def nticks(self, val): self["nticks"] = val # outlinecolor # ------------ @property def outlinecolor(self): """ Sets the axis line color. The 'outlinecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["outlinecolor"] @outlinecolor.setter def outlinecolor(self, val): self["outlinecolor"] = val # outlinewidth # ------------ @property def outlinewidth(self): """ Sets the width (in px) of the axis line. The 'outlinewidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["outlinewidth"] @outlinewidth.setter def outlinewidth(self, val): self["outlinewidth"] = val # separatethousands # ----------------- @property def separatethousands(self): """ If "true", even 4-digit integers are separated The 'separatethousands' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["separatethousands"] @separatethousands.setter def separatethousands(self, val): self["separatethousands"] = val # showexponent # ------------ @property def showexponent(self): """ If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. The 'showexponent' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showexponent"] @showexponent.setter def showexponent(self, val): self["showexponent"] = val # showticklabels # -------------- @property def showticklabels(self): """ Determines whether or not the tick labels are drawn. The 'showticklabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showticklabels"] @showticklabels.setter def showticklabels(self, val): self["showticklabels"] = val # showtickprefix # -------------- @property def showtickprefix(self): """ If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. The 'showtickprefix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showtickprefix"] @showtickprefix.setter def showtickprefix(self, val): self["showtickprefix"] = val # showticksuffix # -------------- @property def showticksuffix(self): """ Same as `showtickprefix` but for tick suffixes. The 'showticksuffix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showticksuffix"] @showticksuffix.setter def showticksuffix(self, val): self["showticksuffix"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # thicknessmode # ------------- @property def thicknessmode(self): """ Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. The 'thicknessmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["thicknessmode"] @thicknessmode.setter def thicknessmode(self, val): self["thicknessmode"] = val # tick0 # ----- @property def tick0(self): """ Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. The 'tick0' property accepts values of any type Returns ------- Any """ return self["tick0"] @tick0.setter def tick0(self, val): self["tick0"] = val # tickangle # --------- @property def tickangle(self): """ Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. The 'tickangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["tickangle"] @tickangle.setter def tickangle(self, val): self["tickangle"] = val # tickcolor # --------- @property def tickcolor(self): """ Sets the tick color. The 'tickcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["tickcolor"] @tickcolor.setter def tickcolor(self, val): self["tickcolor"] = val # tickfont # -------- @property def tickfont(self): """ Sets the color bar's tick label font The 'tickfont' property is an instance of Tickfont that may be specified as: - An instance of plotly.graph_objs.sunburst.marker.colorbar.Tickfont - A dict of string/value properties that will be passed to the Tickfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.sunburst.marker.colorbar.Tickfont """ return self["tickfont"] @tickfont.setter def tickfont(self, val): self["tickfont"] = val # tickformat # ---------- @property def tickformat(self): """ Sets the tick label formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'tickformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickformat"] @tickformat.setter def tickformat(self, val): self["tickformat"] = val # tickformatstops # --------------- @property def tickformatstops(self): """ The 'tickformatstops' property is a tuple of instances of Tickformatstop that may be specified as: - A list or tuple of instances of plotly.graph_objs.sunburst.marker.colorbar.Tickformatstop - A list or tuple of dicts of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- tuple[plotly.graph_objs.sunburst.marker.colorbar.Tickformatstop] """ return self["tickformatstops"] @tickformatstops.setter def tickformatstops(self, val): self["tickformatstops"] = val # tickformatstopdefaults # ---------------------- @property def tickformatstopdefaults(self): """ When used in a template (as layout.template.data.sunburst.marke r.colorbar.tickformatstopdefaults), sets the default property values to use for elements of sunburst.marker.colorbar.tickformatstops The 'tickformatstopdefaults' property is an instance of Tickformatstop that may be specified as: - An instance of plotly.graph_objs.sunburst.marker.colorbar.Tickformatstop - A dict of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: Returns ------- plotly.graph_objs.sunburst.marker.colorbar.Tickformatstop """ return self["tickformatstopdefaults"] @tickformatstopdefaults.setter def tickformatstopdefaults(self, val): self["tickformatstopdefaults"] = val # ticklen # ------- @property def ticklen(self): """ Sets the tick length (in px). The 'ticklen' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ticklen"] @ticklen.setter def ticklen(self, val): self["ticklen"] = val # tickmode # -------- @property def tickmode(self): """ Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). The 'tickmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'linear', 'array'] Returns ------- Any """ return self["tickmode"] @tickmode.setter def tickmode(self, val): self["tickmode"] = val # tickprefix # ---------- @property def tickprefix(self): """ Sets a tick label prefix. The 'tickprefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickprefix"] @tickprefix.setter def tickprefix(self, val): self["tickprefix"] = val # ticks # ----- @property def ticks(self): """ Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. The 'ticks' property is an enumeration that may be specified as: - One of the following enumeration values: ['outside', 'inside', ''] Returns ------- Any """ return self["ticks"] @ticks.setter def ticks(self, val): self["ticks"] = val # ticksuffix # ---------- @property def ticksuffix(self): """ Sets a tick label suffix. The 'ticksuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ticksuffix"] @ticksuffix.setter def ticksuffix(self, val): self["ticksuffix"] = val # ticktext # -------- @property def ticktext(self): """ Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. The 'ticktext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ticktext"] @ticktext.setter def ticktext(self, val): self["ticktext"] = val # ticktextsrc # ----------- @property def ticktextsrc(self): """ Sets the source reference on plot.ly for ticktext . The 'ticktextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ticktextsrc"] @ticktextsrc.setter def ticktextsrc(self, val): self["ticktextsrc"] = val # tickvals # -------- @property def tickvals(self): """ Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. The 'tickvals' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["tickvals"] @tickvals.setter def tickvals(self, val): self["tickvals"] = val # tickvalssrc # ----------- @property def tickvalssrc(self): """ Sets the source reference on plot.ly for tickvals . The 'tickvalssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tickvalssrc"] @tickvalssrc.setter def tickvalssrc(self, val): self["tickvalssrc"] = val # tickwidth # --------- @property def tickwidth(self): """ Sets the tick width (in px). The 'tickwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["tickwidth"] @tickwidth.setter def tickwidth(self, val): self["tickwidth"] = val # title # ----- @property def title(self): """ The 'title' property is an instance of Title that may be specified as: - An instance of plotly.graph_objs.sunburst.marker.colorbar.Title - A dict of string/value properties that will be passed to the Title constructor Supported dict properties: font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- plotly.graph_objs.sunburst.marker.colorbar.Title """ return self["title"] @title.setter def title(self, val): self["title"] = val # titlefont # --------- @property def titlefont(self): """ Deprecated: Please use sunburst.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.sunburst.marker.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- """ return self["titlefont"] @titlefont.setter def titlefont(self, val): self["titlefont"] = val # titleside # --------- @property def titleside(self): """ Deprecated: Please use sunburst.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- """ return self["titleside"] @titleside.setter def titleside(self, val): self["titleside"] = val # x # - @property def x(self): """ Sets the x position of the color bar (in plot fraction). The 'x' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["x"] @x.setter def x(self, val): self["x"] = val # xanchor # ------- @property def xanchor(self): """ Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. The 'xanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'center', 'right'] Returns ------- Any """ return self["xanchor"] @xanchor.setter def xanchor(self, val): self["xanchor"] = val # xpad # ---- @property def xpad(self): """ Sets the amount of padding (in px) along the x direction. The 'xpad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["xpad"] @xpad.setter def xpad(self, val): self["xpad"] = val # y # - @property def y(self): """ Sets the y position of the color bar (in plot fraction). The 'y' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["y"] @y.setter def y(self, val): self["y"] = val # yanchor # ------- @property def yanchor(self): """ Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. The 'yanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['top', 'middle', 'bottom'] Returns ------- Any """ return self["yanchor"] @yanchor.setter def yanchor(self, val): self["yanchor"] = val # ypad # ---- @property def ypad(self): """ Sets the amount of padding (in px) along the y direction. The 'ypad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ypad"] @ypad.setter def ypad(self, val): self["ypad"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "sunburst.marker" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.sunburst.marker.colorba r.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.sunbur st.marker.colorbar.tickformatstopdefaults), sets the default property values to use for elements of sunburst.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.sunburst.marker.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use sunburst.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use sunburst.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """ _mapped_properties = { "titlefont": ("title", "font"), "titleside": ("title", "side"), } def __init__( self, arg=None, bgcolor=None, bordercolor=None, borderwidth=None, dtick=None, exponentformat=None, len=None, lenmode=None, nticks=None, outlinecolor=None, outlinewidth=None, separatethousands=None, showexponent=None, showticklabels=None, showtickprefix=None, showticksuffix=None, thickness=None, thicknessmode=None, tick0=None, tickangle=None, tickcolor=None, tickfont=None, tickformat=None, tickformatstops=None, tickformatstopdefaults=None, ticklen=None, tickmode=None, tickprefix=None, ticks=None, ticksuffix=None, ticktext=None, ticktextsrc=None, tickvals=None, tickvalssrc=None, tickwidth=None, title=None, titlefont=None, titleside=None, x=None, xanchor=None, xpad=None, y=None, yanchor=None, ypad=None, **kwargs ): """ Construct a new ColorBar object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.sunburst.marker.ColorBar bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.sunburst.marker.colorba r.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.sunbur st.marker.colorbar.tickformatstopdefaults), sets the default property values to use for elements of sunburst.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.sunburst.marker.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use sunburst.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use sunburst.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- ColorBar """ super(ColorBar, self).__init__("colorbar") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.sunburst.marker.ColorBar constructor must be a dict or an instance of plotly.graph_objs.sunburst.marker.ColorBar""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.sunburst.marker import colorbar as v_colorbar # Initialize validators # --------------------- self._validators["bgcolor"] = v_colorbar.BgcolorValidator() self._validators["bordercolor"] = v_colorbar.BordercolorValidator() self._validators["borderwidth"] = v_colorbar.BorderwidthValidator() self._validators["dtick"] = v_colorbar.DtickValidator() self._validators["exponentformat"] = v_colorbar.ExponentformatValidator() self._validators["len"] = v_colorbar.LenValidator() self._validators["lenmode"] = v_colorbar.LenmodeValidator() self._validators["nticks"] = v_colorbar.NticksValidator() self._validators["outlinecolor"] = v_colorbar.OutlinecolorValidator() self._validators["outlinewidth"] = v_colorbar.OutlinewidthValidator() self._validators["separatethousands"] = v_colorbar.SeparatethousandsValidator() self._validators["showexponent"] = v_colorbar.ShowexponentValidator() self._validators["showticklabels"] = v_colorbar.ShowticklabelsValidator() self._validators["showtickprefix"] = v_colorbar.ShowtickprefixValidator() self._validators["showticksuffix"] = v_colorbar.ShowticksuffixValidator() self._validators["thickness"] = v_colorbar.ThicknessValidator() self._validators["thicknessmode"] = v_colorbar.ThicknessmodeValidator() self._validators["tick0"] = v_colorbar.Tick0Validator() self._validators["tickangle"] = v_colorbar.TickangleValidator() self._validators["tickcolor"] = v_colorbar.TickcolorValidator() self._validators["tickfont"] = v_colorbar.TickfontValidator() self._validators["tickformat"] = v_colorbar.TickformatValidator() self._validators["tickformatstops"] = v_colorbar.TickformatstopsValidator() self._validators[ "tickformatstopdefaults" ] = v_colorbar.TickformatstopValidator() self._validators["ticklen"] = v_colorbar.TicklenValidator() self._validators["tickmode"] = v_colorbar.TickmodeValidator() self._validators["tickprefix"] = v_colorbar.TickprefixValidator() self._validators["ticks"] = v_colorbar.TicksValidator() self._validators["ticksuffix"] = v_colorbar.TicksuffixValidator() self._validators["ticktext"] = v_colorbar.TicktextValidator() self._validators["ticktextsrc"] = v_colorbar.TicktextsrcValidator() self._validators["tickvals"] = v_colorbar.TickvalsValidator() self._validators["tickvalssrc"] = v_colorbar.TickvalssrcValidator() self._validators["tickwidth"] = v_colorbar.TickwidthValidator() self._validators["title"] = v_colorbar.TitleValidator() self._validators["x"] = v_colorbar.XValidator() self._validators["xanchor"] = v_colorbar.XanchorValidator() self._validators["xpad"] = v_colorbar.XpadValidator() self._validators["y"] = v_colorbar.YValidator() self._validators["yanchor"] = v_colorbar.YanchorValidator() self._validators["ypad"] = v_colorbar.YpadValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("borderwidth", None) self["borderwidth"] = borderwidth if borderwidth is not None else _v _v = arg.pop("dtick", None) self["dtick"] = dtick if dtick is not None else _v _v = arg.pop("exponentformat", None) self["exponentformat"] = exponentformat if exponentformat is not None else _v _v = arg.pop("len", None) self["len"] = len if len is not None else _v _v = arg.pop("lenmode", None) self["lenmode"] = lenmode if lenmode is not None else _v _v = arg.pop("nticks", None) self["nticks"] = nticks if nticks is not None else _v _v = arg.pop("outlinecolor", None) self["outlinecolor"] = outlinecolor if outlinecolor is not None else _v _v = arg.pop("outlinewidth", None) self["outlinewidth"] = outlinewidth if outlinewidth is not None else _v _v = arg.pop("separatethousands", None) self["separatethousands"] = ( separatethousands if separatethousands is not None else _v ) _v = arg.pop("showexponent", None) self["showexponent"] = showexponent if showexponent is not None else _v _v = arg.pop("showticklabels", None) self["showticklabels"] = showticklabels if showticklabels is not None else _v _v = arg.pop("showtickprefix", None) self["showtickprefix"] = showtickprefix if showtickprefix is not None else _v _v = arg.pop("showticksuffix", None) self["showticksuffix"] = showticksuffix if showticksuffix is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("thicknessmode", None) self["thicknessmode"] = thicknessmode if thicknessmode is not None else _v _v = arg.pop("tick0", None) self["tick0"] = tick0 if tick0 is not None else _v _v = arg.pop("tickangle", None) self["tickangle"] = tickangle if tickangle is not None else _v _v = arg.pop("tickcolor", None) self["tickcolor"] = tickcolor if tickcolor is not None else _v _v = arg.pop("tickfont", None) self["tickfont"] = tickfont if tickfont is not None else _v _v = arg.pop("tickformat", None) self["tickformat"] = tickformat if tickformat is not None else _v _v = arg.pop("tickformatstops", None) self["tickformatstops"] = tickformatstops if tickformatstops is not None else _v _v = arg.pop("tickformatstopdefaults", None) self["tickformatstopdefaults"] = ( tickformatstopdefaults if tickformatstopdefaults is not None else _v ) _v = arg.pop("ticklen", None) self["ticklen"] = ticklen if ticklen is not None else _v _v = arg.pop("tickmode", None) self["tickmode"] = tickmode if tickmode is not None else _v _v = arg.pop("tickprefix", None) self["tickprefix"] = tickprefix if tickprefix is not None else _v _v = arg.pop("ticks", None) self["ticks"] = ticks if ticks is not None else _v _v = arg.pop("ticksuffix", None) self["ticksuffix"] = ticksuffix if ticksuffix is not None else _v _v = arg.pop("ticktext", None) self["ticktext"] = ticktext if ticktext is not None else _v _v = arg.pop("ticktextsrc", None) self["ticktextsrc"] = ticktextsrc if ticktextsrc is not None else _v _v = arg.pop("tickvals", None) self["tickvals"] = tickvals if tickvals is not None else _v _v = arg.pop("tickvalssrc", None) self["tickvalssrc"] = tickvalssrc if tickvalssrc is not None else _v _v = arg.pop("tickwidth", None) self["tickwidth"] = tickwidth if tickwidth is not None else _v _v = arg.pop("title", None) self["title"] = title if title is not None else _v _v = arg.pop("titlefont", None) _v = titlefont if titlefont is not None else _v if _v is not None: self["titlefont"] = _v _v = arg.pop("titleside", None) _v = titleside if titleside is not None else _v if _v is not None: self["titleside"] = _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xanchor", None) self["xanchor"] = xanchor if xanchor is not None else _v _v = arg.pop("xpad", None) self["xpad"] = xpad if xpad is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("yanchor", None) self["yanchor"] = yanchor if yanchor is not None else _v _v = arg.pop("ypad", None) self["ypad"] = ypad if ypad is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["ColorBar", "Line", "colorbar"] from plotly.graph_objs.sunburst.marker import colorbar plotly-4.4.1+dfsg.orig/plotly/graph_objs/sunburst/__init__.py0000644000175000017500000027737513573721553023750 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Textfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "sunburst" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Textfont object Sets the font used for `textinfo`. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.sunburst.Textfont color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Textfont """ super(Textfont, self).__init__("textfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.sunburst.Textfont constructor must be a dict or an instance of plotly.graph_objs.sunburst.Textfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.sunburst import textfont as v_textfont # Initialize validators # --------------------- self._validators["color"] = v_textfont.ColorValidator() self._validators["colorsrc"] = v_textfont.ColorsrcValidator() self._validators["family"] = v_textfont.FamilyValidator() self._validators["familysrc"] = v_textfont.FamilysrcValidator() self._validators["size"] = v_textfont.SizeValidator() self._validators["sizesrc"] = v_textfont.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Stream(_BaseTraceHierarchyType): # maxpoints # --------- @property def maxpoints(self): """ Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. The 'maxpoints' property is a number and may be specified as: - An int or float in the interval [0, 10000] Returns ------- int|float """ return self["maxpoints"] @maxpoints.setter def maxpoints(self, val): self["maxpoints"] = val # token # ----- @property def token(self): """ The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. The 'token' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["token"] @token.setter def token(self, val): self["token"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "sunburst" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """ def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): """ Construct a new Stream object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.sunburst.Stream maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- Stream """ super(Stream, self).__init__("stream") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.sunburst.Stream constructor must be a dict or an instance of plotly.graph_objs.sunburst.Stream""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.sunburst import stream as v_stream # Initialize validators # --------------------- self._validators["maxpoints"] = v_stream.MaxpointsValidator() self._validators["token"] = v_stream.TokenValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("maxpoints", None) self["maxpoints"] = maxpoints if maxpoints is not None else _v _v = arg.pop("token", None) self["token"] = token if token is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Outsidetextfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "sunburst" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Outsidetextfont object Sets the font used for `textinfo` lying outside the sector. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.sunburst.Outsidetextfont color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Outsidetextfont """ super(Outsidetextfont, self).__init__("outsidetextfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.sunburst.Outsidetextfont constructor must be a dict or an instance of plotly.graph_objs.sunburst.Outsidetextfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.sunburst import outsidetextfont as v_outsidetextfont # Initialize validators # --------------------- self._validators["color"] = v_outsidetextfont.ColorValidator() self._validators["colorsrc"] = v_outsidetextfont.ColorsrcValidator() self._validators["family"] = v_outsidetextfont.FamilyValidator() self._validators["familysrc"] = v_outsidetextfont.FamilysrcValidator() self._validators["size"] = v_outsidetextfont.SizeValidator() self._validators["sizesrc"] = v_outsidetextfont.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # autocolorscale # -------------- @property def autocolorscale(self): """ Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if colorsis set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. The 'autocolorscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocolorscale"] @autocolorscale.setter def autocolorscale(self, val): self["autocolorscale"] = val # cauto # ----- @property def cauto(self): """ Determines whether or not the color domain is computed with respect to the input data (here colors) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if colorsis set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. The 'cauto' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["cauto"] @cauto.setter def cauto(self, val): self["cauto"] = val # cmax # ---- @property def cmax(self): """ Sets the upper bound of the color domain. Has an effect only if colorsis set to a numerical array. Value should have the same units as colors and if set, `marker.cmin` must be set as well. The 'cmax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmax"] @cmax.setter def cmax(self, val): self["cmax"] = val # cmid # ---- @property def cmid(self): """ Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if colorsis set to a numerical array. Value should have the same units as colors. Has no effect when `marker.cauto` is `false`. The 'cmid' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmid"] @cmid.setter def cmid(self, val): self["cmid"] = val # cmin # ---- @property def cmin(self): """ Sets the lower bound of the color domain. Has an effect only if colorsis set to a numerical array. Value should have the same units as colors and if set, `marker.cmax` must be set as well. The 'cmin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmin"] @cmin.setter def cmin(self, val): self["cmin"] = val # coloraxis # --------- @property def coloraxis(self): """ Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. The 'coloraxis' property is an identifier of a particular subplot, of type 'coloraxis', that may be specified as the string 'coloraxis' optionally followed by an integer >= 1 (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) Returns ------- str """ return self["coloraxis"] @coloraxis.setter def coloraxis(self, val): self["coloraxis"] = val # colorbar # -------- @property def colorbar(self): """ The 'colorbar' property is an instance of ColorBar that may be specified as: - An instance of plotly.graph_objs.sunburst.marker.ColorBar - A dict of string/value properties that will be passed to the ColorBar constructor Supported dict properties: bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.sunburst.marker .colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.sunburst.marker.colorbar.tickformatstopdefaul ts), sets the default property values to use for elements of sunburst.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.sunburst.marker.colorbar.T itle instance or dict with compatible properties titlefont Deprecated: Please use sunburst.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use sunburst.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- plotly.graph_objs.sunburst.marker.ColorBar """ return self["colorbar"] @colorbar.setter def colorbar(self, val): self["colorbar"] = val # colors # ------ @property def colors(self): """ Sets the color of each sector of this trace. If not specified, the default trace color set is used to pick the sector colors. The 'colors' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["colors"] @colors.setter def colors(self, val): self["colors"] = val # colorscale # ---------- @property def colorscale(self): """ Sets the colorscale. Has an effect only if colorsis set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,B luered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Blackbod y,Earth,Electric,Viridis,Cividis. The 'colorscale' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # colorssrc # --------- @property def colorssrc(self): """ Sets the source reference on plot.ly for colors . The 'colorssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorssrc"] @colorssrc.setter def colorssrc(self, val): self["colorssrc"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.sunburst.marker.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: color Sets the color of the line enclosing each sector. Defaults to the `paper_bgcolor` value. colorsrc Sets the source reference on plot.ly for color . width Sets the width (in px) of the line enclosing each sector. widthsrc Sets the source reference on plot.ly for width . Returns ------- plotly.graph_objs.sunburst.marker.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # reversescale # ------------ @property def reversescale(self): """ Reverses the color mapping if true. Has an effect only if colorsis set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. The 'reversescale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["reversescale"] @reversescale.setter def reversescale(self, val): self["reversescale"] = val # showscale # --------- @property def showscale(self): """ Determines whether or not a colorbar is displayed for this trace. Has an effect only if colorsis set to a numerical array. The 'showscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showscale"] @showscale.setter def showscale(self, val): self["showscale"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "sunburst" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if colorsis set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here colors) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if colorsis set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if colorsis set to a numerical array. Value should have the same units as colors and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if colorsis set to a numerical array. Value should have the same units as colors. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if colorsis set to a numerical array. Value should have the same units as colors and if set, `marker.cmax` must be set as well. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.sunburst.marker.ColorBar instance or dict with compatible properties colors Sets the color of each sector of this trace. If not specified, the default trace color set is used to pick the sector colors. colorscale Sets the colorscale. Has an effect only if colorsis set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu ,Greens,YlOrRd,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,P ortland,Jet,Hot,Blackbody,Earth,Electric,Viridis,Cividi s. colorssrc Sets the source reference on plot.ly for colors . line plotly.graph_objects.sunburst.marker.Line instance or dict with compatible properties reversescale Reverses the color mapping if true. Has an effect only if colorsis set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if colorsis set to a numerical array. """ def __init__( self, arg=None, autocolorscale=None, cauto=None, cmax=None, cmid=None, cmin=None, coloraxis=None, colorbar=None, colors=None, colorscale=None, colorssrc=None, line=None, reversescale=None, showscale=None, **kwargs ): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.sunburst.Marker autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if colorsis set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here colors) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if colorsis set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if colorsis set to a numerical array. Value should have the same units as colors and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if colorsis set to a numerical array. Value should have the same units as colors. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if colorsis set to a numerical array. Value should have the same units as colors and if set, `marker.cmax` must be set as well. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.sunburst.marker.ColorBar instance or dict with compatible properties colors Sets the color of each sector of this trace. If not specified, the default trace color set is used to pick the sector colors. colorscale Sets the colorscale. Has an effect only if colorsis set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu ,Greens,YlOrRd,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,P ortland,Jet,Hot,Blackbody,Earth,Electric,Viridis,Cividi s. colorssrc Sets the source reference on plot.ly for colors . line plotly.graph_objects.sunburst.marker.Line instance or dict with compatible properties reversescale Reverses the color mapping if true. Has an effect only if colorsis set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if colorsis set to a numerical array. Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.sunburst.Marker constructor must be a dict or an instance of plotly.graph_objs.sunburst.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.sunburst import marker as v_marker # Initialize validators # --------------------- self._validators["autocolorscale"] = v_marker.AutocolorscaleValidator() self._validators["cauto"] = v_marker.CautoValidator() self._validators["cmax"] = v_marker.CmaxValidator() self._validators["cmid"] = v_marker.CmidValidator() self._validators["cmin"] = v_marker.CminValidator() self._validators["coloraxis"] = v_marker.ColoraxisValidator() self._validators["colorbar"] = v_marker.ColorBarValidator() self._validators["colors"] = v_marker.ColorsValidator() self._validators["colorscale"] = v_marker.ColorscaleValidator() self._validators["colorssrc"] = v_marker.ColorssrcValidator() self._validators["line"] = v_marker.LineValidator() self._validators["reversescale"] = v_marker.ReversescaleValidator() self._validators["showscale"] = v_marker.ShowscaleValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autocolorscale", None) self["autocolorscale"] = autocolorscale if autocolorscale is not None else _v _v = arg.pop("cauto", None) self["cauto"] = cauto if cauto is not None else _v _v = arg.pop("cmax", None) self["cmax"] = cmax if cmax is not None else _v _v = arg.pop("cmid", None) self["cmid"] = cmid if cmid is not None else _v _v = arg.pop("cmin", None) self["cmin"] = cmin if cmin is not None else _v _v = arg.pop("coloraxis", None) self["coloraxis"] = coloraxis if coloraxis is not None else _v _v = arg.pop("colorbar", None) self["colorbar"] = colorbar if colorbar is not None else _v _v = arg.pop("colors", None) self["colors"] = colors if colors is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("colorssrc", None) self["colorssrc"] = colorssrc if colorssrc is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v _v = arg.pop("reversescale", None) self["reversescale"] = reversescale if reversescale is not None else _v _v = arg.pop("showscale", None) self["showscale"] = showscale if showscale is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Leaf(_BaseTraceHierarchyType): # opacity # ------- @property def opacity(self): """ Sets the opacity of the leaves. With colorscale it is defaulted to 1; otherwise it is defaulted to 0.7 The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "sunburst" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ opacity Sets the opacity of the leaves. With colorscale it is defaulted to 1; otherwise it is defaulted to 0.7 """ def __init__(self, arg=None, opacity=None, **kwargs): """ Construct a new Leaf object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.sunburst.Leaf opacity Sets the opacity of the leaves. With colorscale it is defaulted to 1; otherwise it is defaulted to 0.7 Returns ------- Leaf """ super(Leaf, self).__init__("leaf") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.sunburst.Leaf constructor must be a dict or an instance of plotly.graph_objs.sunburst.Leaf""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.sunburst import leaf as v_leaf # Initialize validators # --------------------- self._validators["opacity"] = v_leaf.OpacityValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Insidetextfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "sunburst" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Insidetextfont object Sets the font used for `textinfo` lying inside the sector. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.sunburst.Insidetextfont color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Insidetextfont """ super(Insidetextfont, self).__init__("insidetextfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.sunburst.Insidetextfont constructor must be a dict or an instance of plotly.graph_objs.sunburst.Insidetextfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.sunburst import insidetextfont as v_insidetextfont # Initialize validators # --------------------- self._validators["color"] = v_insidetextfont.ColorValidator() self._validators["colorsrc"] = v_insidetextfont.ColorsrcValidator() self._validators["family"] = v_insidetextfont.FamilyValidator() self._validators["familysrc"] = v_insidetextfont.FamilysrcValidator() self._validators["size"] = v_insidetextfont.SizeValidator() self._validators["sizesrc"] = v_insidetextfont.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Hoverlabel(_BaseTraceHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'right', 'auto'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["align"] @align.setter def align(self, val): self["align"] = val # alignsrc # -------- @property def alignsrc(self): """ Sets the source reference on plot.ly for align . The 'alignsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["alignsrc"] @alignsrc.setter def alignsrc(self, val): self["alignsrc"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the hover labels for this trace The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bgcolorsrc # ---------- @property def bgcolorsrc(self): """ Sets the source reference on plot.ly for bgcolor . The 'bgcolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bgcolorsrc"] @bgcolorsrc.setter def bgcolorsrc(self, val): self["bgcolorsrc"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the border color of the hover labels for this trace. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # bordercolorsrc # -------------- @property def bordercolorsrc(self): """ Sets the source reference on plot.ly for bordercolor . The 'bordercolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bordercolorsrc"] @bordercolorsrc.setter def bordercolorsrc(self, val): self["bordercolorsrc"] = val # font # ---- @property def font(self): """ Sets the font used in hover labels. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.sunburst.hoverlabel.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.sunburst.hoverlabel.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # namelength # ---------- @property def namelength(self): """ Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. The 'namelength' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [-1, 9223372036854775807] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|numpy.ndarray """ return self["namelength"] @namelength.setter def namelength(self, val): self["namelength"] = val # namelengthsrc # ------------- @property def namelengthsrc(self): """ Sets the source reference on plot.ly for namelength . The 'namelengthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["namelengthsrc"] @namelengthsrc.setter def namelengthsrc(self, val): self["namelengthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "sunburst" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """ def __init__( self, arg=None, align=None, alignsrc=None, bgcolor=None, bgcolorsrc=None, bordercolor=None, bordercolorsrc=None, font=None, namelength=None, namelengthsrc=None, **kwargs ): """ Construct a new Hoverlabel object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.sunburst.Hoverlabel align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- Hoverlabel """ super(Hoverlabel, self).__init__("hoverlabel") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.sunburst.Hoverlabel constructor must be a dict or an instance of plotly.graph_objs.sunburst.Hoverlabel""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.sunburst import hoverlabel as v_hoverlabel # Initialize validators # --------------------- self._validators["align"] = v_hoverlabel.AlignValidator() self._validators["alignsrc"] = v_hoverlabel.AlignsrcValidator() self._validators["bgcolor"] = v_hoverlabel.BgcolorValidator() self._validators["bgcolorsrc"] = v_hoverlabel.BgcolorsrcValidator() self._validators["bordercolor"] = v_hoverlabel.BordercolorValidator() self._validators["bordercolorsrc"] = v_hoverlabel.BordercolorsrcValidator() self._validators["font"] = v_hoverlabel.FontValidator() self._validators["namelength"] = v_hoverlabel.NamelengthValidator() self._validators["namelengthsrc"] = v_hoverlabel.NamelengthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("alignsrc", None) self["alignsrc"] = alignsrc if alignsrc is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bgcolorsrc", None) self["bgcolorsrc"] = bgcolorsrc if bgcolorsrc is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("bordercolorsrc", None) self["bordercolorsrc"] = bordercolorsrc if bordercolorsrc is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("namelength", None) self["namelength"] = namelength if namelength is not None else _v _v = arg.pop("namelengthsrc", None) self["namelengthsrc"] = namelengthsrc if namelengthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Domain(_BaseTraceHierarchyType): # column # ------ @property def column(self): """ If there is a layout grid, use the domain for this column in the grid for this sunburst trace . The 'column' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["column"] @column.setter def column(self, val): self["column"] = val # row # --- @property def row(self): """ If there is a layout grid, use the domain for this row in the grid for this sunburst trace . The 'row' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["row"] @row.setter def row(self, val): self["row"] = val # x # - @property def x(self): """ Sets the horizontal domain of this sunburst trace (in plot fraction). The 'x' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'x[0]' property is a number and may be specified as: - An int or float in the interval [0, 1] (1) The 'x[1]' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- list """ return self["x"] @x.setter def x(self, val): self["x"] = val # y # - @property def y(self): """ Sets the vertical domain of this sunburst trace (in plot fraction). The 'y' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'y[0]' property is a number and may be specified as: - An int or float in the interval [0, 1] (1) The 'y[1]' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- list """ return self["y"] @y.setter def y(self, val): self["y"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "sunburst" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ column If there is a layout grid, use the domain for this column in the grid for this sunburst trace . row If there is a layout grid, use the domain for this row in the grid for this sunburst trace . x Sets the horizontal domain of this sunburst trace (in plot fraction). y Sets the vertical domain of this sunburst trace (in plot fraction). """ def __init__(self, arg=None, column=None, row=None, x=None, y=None, **kwargs): """ Construct a new Domain object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.sunburst.Domain column If there is a layout grid, use the domain for this column in the grid for this sunburst trace . row If there is a layout grid, use the domain for this row in the grid for this sunburst trace . x Sets the horizontal domain of this sunburst trace (in plot fraction). y Sets the vertical domain of this sunburst trace (in plot fraction). Returns ------- Domain """ super(Domain, self).__init__("domain") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.sunburst.Domain constructor must be a dict or an instance of plotly.graph_objs.sunburst.Domain""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.sunburst import domain as v_domain # Initialize validators # --------------------- self._validators["column"] = v_domain.ColumnValidator() self._validators["row"] = v_domain.RowValidator() self._validators["x"] = v_domain.XValidator() self._validators["y"] = v_domain.YValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("column", None) self["column"] = column if column is not None else _v _v = arg.pop("row", None) self["row"] = row if row is not None else _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = [ "Domain", "Hoverlabel", "Insidetextfont", "Leaf", "Marker", "Outsidetextfont", "Stream", "Textfont", "hoverlabel", "marker", ] from plotly.graph_objs.sunburst import marker from plotly.graph_objs.sunburst import hoverlabel plotly-4.4.1+dfsg.orig/plotly/graph_objs/surface/0000755000175000017500000000000013573746613021361 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/surface/hoverlabel/0000755000175000017500000000000013573746613023504 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/surface/hoverlabel/__init__.py0000644000175000017500000002544013573721552025615 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "surface.hoverlabel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Font object Sets the font used in hover labels. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.surface.hoverlabel.Font color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.surface.hoverlabel.Font constructor must be a dict or an instance of plotly.graph_objs.surface.hoverlabel.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.surface.hoverlabel import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["colorsrc"] = v_font.ColorsrcValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["familysrc"] = v_font.FamilysrcValidator() self._validators["size"] = v_font.SizeValidator() self._validators["sizesrc"] = v_font.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/surface/colorbar/0000755000175000017500000000000013573746613023164 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/surface/colorbar/title/0000755000175000017500000000000013573746613024305 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/surface/colorbar/title/__init__.py0000644000175000017500000002052513573721552026415 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "surface.colorbar.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.surface.colorbar.title.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.surface.colorbar.title.Font constructor must be a dict or an instance of plotly.graph_objs.surface.colorbar.title.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.surface.colorbar.title import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/surface/colorbar/__init__.py0000644000175000017500000006054213573721552025277 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Title(_BaseTraceHierarchyType): # font # ---- @property def font(self): """ Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.surface.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.surface.colorbar.title.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # side # ---- @property def side(self): """ Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- Any """ return self["side"] @side.setter def side(self, val): self["side"] = val # text # ---- @property def text(self): """ Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "surface.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """ def __init__(self, arg=None, font=None, side=None, text=None, **kwargs): """ Construct a new Title object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.surface.colorbar.Title font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- Title """ super(Title, self).__init__("title") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.surface.colorbar.Title constructor must be a dict or an instance of plotly.graph_objs.surface.colorbar.Title""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.surface.colorbar import title as v_title # Initialize validators # --------------------- self._validators["font"] = v_title.FontValidator() self._validators["side"] = v_title.SideValidator() self._validators["text"] = v_title.TextValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("side", None) self["side"] = side if side is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickformatstop(_BaseTraceHierarchyType): # dtickrange # ---------- @property def dtickrange(self): """ range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" The 'dtickrange' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'dtickrange[0]' property accepts values of any type (1) The 'dtickrange[1]' property accepts values of any type Returns ------- list """ return self["dtickrange"] @dtickrange.setter def dtickrange(self, val): self["dtickrange"] = val # enabled # ------- @property def enabled(self): """ Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. The 'enabled' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["enabled"] @enabled.setter def enabled(self, val): self["enabled"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # value # ----- @property def value(self): """ string - dtickformat for described zoom level, the same as "tickformat" The 'value' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "surface.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """ def __init__( self, arg=None, dtickrange=None, enabled=None, name=None, templateitemname=None, value=None, **kwargs ): """ Construct a new Tickformatstop object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.surface.colorbar.Tickformatstop dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- Tickformatstop """ super(Tickformatstop, self).__init__("tickformatstops") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.surface.colorbar.Tickformatstop constructor must be a dict or an instance of plotly.graph_objs.surface.colorbar.Tickformatstop""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.surface.colorbar import ( tickformatstop as v_tickformatstop, ) # Initialize validators # --------------------- self._validators["dtickrange"] = v_tickformatstop.DtickrangeValidator() self._validators["enabled"] = v_tickformatstop.EnabledValidator() self._validators["name"] = v_tickformatstop.NameValidator() self._validators[ "templateitemname" ] = v_tickformatstop.TemplateitemnameValidator() self._validators["value"] = v_tickformatstop.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtickrange", None) self["dtickrange"] = dtickrange if dtickrange is not None else _v _v = arg.pop("enabled", None) self["enabled"] = enabled if enabled is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "surface.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Tickfont object Sets the color bar's tick label font Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.surface.colorbar.Tickfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Tickfont """ super(Tickfont, self).__init__("tickfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.surface.colorbar.Tickfont constructor must be a dict or an instance of plotly.graph_objs.surface.colorbar.Tickfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.surface.colorbar import tickfont as v_tickfont # Initialize validators # --------------------- self._validators["color"] = v_tickfont.ColorValidator() self._validators["family"] = v_tickfont.FamilyValidator() self._validators["size"] = v_tickfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Tickfont", "Tickformatstop", "Tickformatstop", "Title", "title"] from plotly.graph_objs.surface.colorbar import title plotly-4.4.1+dfsg.orig/plotly/graph_objs/surface/contours/0000755000175000017500000000000013573746613023235 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/surface/contours/x/0000755000175000017500000000000013573746613023504 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/surface/contours/x/__init__.py0000644000175000017500000001342013573721552025610 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Project(_BaseTraceHierarchyType): # x # - @property def x(self): """ Determines whether or not these contour lines are projected on the x plane. If `highlight` is set to True (the default), the projected lines are shown on hover. If `show` is set to True, the projected lines are shown in permanence. The 'x' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["x"] @x.setter def x(self, val): self["x"] = val # y # - @property def y(self): """ Determines whether or not these contour lines are projected on the y plane. If `highlight` is set to True (the default), the projected lines are shown on hover. If `show` is set to True, the projected lines are shown in permanence. The 'y' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["y"] @y.setter def y(self, val): self["y"] = val # z # - @property def z(self): """ Determines whether or not these contour lines are projected on the z plane. If `highlight` is set to True (the default), the projected lines are shown on hover. If `show` is set to True, the projected lines are shown in permanence. The 'z' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["z"] @z.setter def z(self, val): self["z"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "surface.contours.x" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ x Determines whether or not these contour lines are projected on the x plane. If `highlight` is set to True (the default), the projected lines are shown on hover. If `show` is set to True, the projected lines are shown in permanence. y Determines whether or not these contour lines are projected on the y plane. If `highlight` is set to True (the default), the projected lines are shown on hover. If `show` is set to True, the projected lines are shown in permanence. z Determines whether or not these contour lines are projected on the z plane. If `highlight` is set to True (the default), the projected lines are shown on hover. If `show` is set to True, the projected lines are shown in permanence. """ def __init__(self, arg=None, x=None, y=None, z=None, **kwargs): """ Construct a new Project object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.surface.contours.x.Project x Determines whether or not these contour lines are projected on the x plane. If `highlight` is set to True (the default), the projected lines are shown on hover. If `show` is set to True, the projected lines are shown in permanence. y Determines whether or not these contour lines are projected on the y plane. If `highlight` is set to True (the default), the projected lines are shown on hover. If `show` is set to True, the projected lines are shown in permanence. z Determines whether or not these contour lines are projected on the z plane. If `highlight` is set to True (the default), the projected lines are shown on hover. If `show` is set to True, the projected lines are shown in permanence. Returns ------- Project """ super(Project, self).__init__("project") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.surface.contours.x.Project constructor must be a dict or an instance of plotly.graph_objs.surface.contours.x.Project""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.surface.contours.x import project as v_project # Initialize validators # --------------------- self._validators["x"] = v_project.XValidator() self._validators["y"] = v_project.YValidator() self._validators["z"] = v_project.ZValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("z", None) self["z"] = z if z is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Project"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/surface/contours/z/0000755000175000017500000000000013573746613023506 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/surface/contours/z/__init__.py0000644000175000017500000001342013573721552025612 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Project(_BaseTraceHierarchyType): # x # - @property def x(self): """ Determines whether or not these contour lines are projected on the x plane. If `highlight` is set to True (the default), the projected lines are shown on hover. If `show` is set to True, the projected lines are shown in permanence. The 'x' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["x"] @x.setter def x(self, val): self["x"] = val # y # - @property def y(self): """ Determines whether or not these contour lines are projected on the y plane. If `highlight` is set to True (the default), the projected lines are shown on hover. If `show` is set to True, the projected lines are shown in permanence. The 'y' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["y"] @y.setter def y(self, val): self["y"] = val # z # - @property def z(self): """ Determines whether or not these contour lines are projected on the z plane. If `highlight` is set to True (the default), the projected lines are shown on hover. If `show` is set to True, the projected lines are shown in permanence. The 'z' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["z"] @z.setter def z(self, val): self["z"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "surface.contours.z" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ x Determines whether or not these contour lines are projected on the x plane. If `highlight` is set to True (the default), the projected lines are shown on hover. If `show` is set to True, the projected lines are shown in permanence. y Determines whether or not these contour lines are projected on the y plane. If `highlight` is set to True (the default), the projected lines are shown on hover. If `show` is set to True, the projected lines are shown in permanence. z Determines whether or not these contour lines are projected on the z plane. If `highlight` is set to True (the default), the projected lines are shown on hover. If `show` is set to True, the projected lines are shown in permanence. """ def __init__(self, arg=None, x=None, y=None, z=None, **kwargs): """ Construct a new Project object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.surface.contours.z.Project x Determines whether or not these contour lines are projected on the x plane. If `highlight` is set to True (the default), the projected lines are shown on hover. If `show` is set to True, the projected lines are shown in permanence. y Determines whether or not these contour lines are projected on the y plane. If `highlight` is set to True (the default), the projected lines are shown on hover. If `show` is set to True, the projected lines are shown in permanence. z Determines whether or not these contour lines are projected on the z plane. If `highlight` is set to True (the default), the projected lines are shown on hover. If `show` is set to True, the projected lines are shown in permanence. Returns ------- Project """ super(Project, self).__init__("project") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.surface.contours.z.Project constructor must be a dict or an instance of plotly.graph_objs.surface.contours.z.Project""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.surface.contours.z import project as v_project # Initialize validators # --------------------- self._validators["x"] = v_project.XValidator() self._validators["y"] = v_project.YValidator() self._validators["z"] = v_project.ZValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("z", None) self["z"] = z if z is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Project"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/surface/contours/y/0000755000175000017500000000000013573746613023505 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/surface/contours/y/__init__.py0000644000175000017500000001342013573721552025611 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Project(_BaseTraceHierarchyType): # x # - @property def x(self): """ Determines whether or not these contour lines are projected on the x plane. If `highlight` is set to True (the default), the projected lines are shown on hover. If `show` is set to True, the projected lines are shown in permanence. The 'x' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["x"] @x.setter def x(self, val): self["x"] = val # y # - @property def y(self): """ Determines whether or not these contour lines are projected on the y plane. If `highlight` is set to True (the default), the projected lines are shown on hover. If `show` is set to True, the projected lines are shown in permanence. The 'y' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["y"] @y.setter def y(self, val): self["y"] = val # z # - @property def z(self): """ Determines whether or not these contour lines are projected on the z plane. If `highlight` is set to True (the default), the projected lines are shown on hover. If `show` is set to True, the projected lines are shown in permanence. The 'z' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["z"] @z.setter def z(self, val): self["z"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "surface.contours.y" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ x Determines whether or not these contour lines are projected on the x plane. If `highlight` is set to True (the default), the projected lines are shown on hover. If `show` is set to True, the projected lines are shown in permanence. y Determines whether or not these contour lines are projected on the y plane. If `highlight` is set to True (the default), the projected lines are shown on hover. If `show` is set to True, the projected lines are shown in permanence. z Determines whether or not these contour lines are projected on the z plane. If `highlight` is set to True (the default), the projected lines are shown on hover. If `show` is set to True, the projected lines are shown in permanence. """ def __init__(self, arg=None, x=None, y=None, z=None, **kwargs): """ Construct a new Project object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.surface.contours.y.Project x Determines whether or not these contour lines are projected on the x plane. If `highlight` is set to True (the default), the projected lines are shown on hover. If `show` is set to True, the projected lines are shown in permanence. y Determines whether or not these contour lines are projected on the y plane. If `highlight` is set to True (the default), the projected lines are shown on hover. If `show` is set to True, the projected lines are shown in permanence. z Determines whether or not these contour lines are projected on the z plane. If `highlight` is set to True (the default), the projected lines are shown on hover. If `show` is set to True, the projected lines are shown in permanence. Returns ------- Project """ super(Project, self).__init__("project") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.surface.contours.y.Project constructor must be a dict or an instance of plotly.graph_objs.surface.contours.y.Project""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.surface.contours.y import project as v_project # Initialize validators # --------------------- self._validators["x"] = v_project.XValidator() self._validators["y"] = v_project.YValidator() self._validators["z"] = v_project.ZValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("z", None) self["z"] = z if z is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Project"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/surface/contours/__init__.py0000644000175000017500000014417413573721553025355 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Z(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the color of the contour lines. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # end # --- @property def end(self): """ Sets the end contour level value. Must be more than `contours.start` The 'end' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["end"] @end.setter def end(self, val): self["end"] = val # highlight # --------- @property def highlight(self): """ Determines whether or not contour lines about the z dimension are highlighted on hover. The 'highlight' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["highlight"] @highlight.setter def highlight(self, val): self["highlight"] = val # highlightcolor # -------------- @property def highlightcolor(self): """ Sets the color of the highlighted contour lines. The 'highlightcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["highlightcolor"] @highlightcolor.setter def highlightcolor(self, val): self["highlightcolor"] = val # highlightwidth # -------------- @property def highlightwidth(self): """ Sets the width of the highlighted contour lines. The 'highlightwidth' property is a number and may be specified as: - An int or float in the interval [1, 16] Returns ------- int|float """ return self["highlightwidth"] @highlightwidth.setter def highlightwidth(self, val): self["highlightwidth"] = val # project # ------- @property def project(self): """ The 'project' property is an instance of Project that may be specified as: - An instance of plotly.graph_objs.surface.contours.z.Project - A dict of string/value properties that will be passed to the Project constructor Supported dict properties: x Determines whether or not these contour lines are projected on the x plane. If `highlight` is set to True (the default), the projected lines are shown on hover. If `show` is set to True, the projected lines are shown in permanence. y Determines whether or not these contour lines are projected on the y plane. If `highlight` is set to True (the default), the projected lines are shown on hover. If `show` is set to True, the projected lines are shown in permanence. z Determines whether or not these contour lines are projected on the z plane. If `highlight` is set to True (the default), the projected lines are shown on hover. If `show` is set to True, the projected lines are shown in permanence. Returns ------- plotly.graph_objs.surface.contours.z.Project """ return self["project"] @project.setter def project(self, val): self["project"] = val # show # ---- @property def show(self): """ Determines whether or not contour lines about the z dimension are drawn. The 'show' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["show"] @show.setter def show(self, val): self["show"] = val # size # ---- @property def size(self): """ Sets the step between each contour level. Must be positive. The 'size' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # start # ----- @property def start(self): """ Sets the starting contour level value. Must be less than `contours.end` The 'start' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["start"] @start.setter def start(self, val): self["start"] = val # usecolormap # ----------- @property def usecolormap(self): """ An alternate to "color". Determines whether or not the contour lines are colored using the trace "colorscale". The 'usecolormap' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["usecolormap"] @usecolormap.setter def usecolormap(self, val): self["usecolormap"] = val # width # ----- @property def width(self): """ Sets the width of the contour lines. The 'width' property is a number and may be specified as: - An int or float in the interval [1, 16] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "surface.contours" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the color of the contour lines. end Sets the end contour level value. Must be more than `contours.start` highlight Determines whether or not contour lines about the z dimension are highlighted on hover. highlightcolor Sets the color of the highlighted contour lines. highlightwidth Sets the width of the highlighted contour lines. project plotly.graph_objects.surface.contours.z.Project instance or dict with compatible properties show Determines whether or not contour lines about the z dimension are drawn. size Sets the step between each contour level. Must be positive. start Sets the starting contour level value. Must be less than `contours.end` usecolormap An alternate to "color". Determines whether or not the contour lines are colored using the trace "colorscale". width Sets the width of the contour lines. """ def __init__( self, arg=None, color=None, end=None, highlight=None, highlightcolor=None, highlightwidth=None, project=None, show=None, size=None, start=None, usecolormap=None, width=None, **kwargs ): """ Construct a new Z object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.surface.contours.Z color Sets the color of the contour lines. end Sets the end contour level value. Must be more than `contours.start` highlight Determines whether or not contour lines about the z dimension are highlighted on hover. highlightcolor Sets the color of the highlighted contour lines. highlightwidth Sets the width of the highlighted contour lines. project plotly.graph_objects.surface.contours.z.Project instance or dict with compatible properties show Determines whether or not contour lines about the z dimension are drawn. size Sets the step between each contour level. Must be positive. start Sets the starting contour level value. Must be less than `contours.end` usecolormap An alternate to "color". Determines whether or not the contour lines are colored using the trace "colorscale". width Sets the width of the contour lines. Returns ------- Z """ super(Z, self).__init__("z") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.surface.contours.Z constructor must be a dict or an instance of plotly.graph_objs.surface.contours.Z""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.surface.contours import z as v_z # Initialize validators # --------------------- self._validators["color"] = v_z.ColorValidator() self._validators["end"] = v_z.EndValidator() self._validators["highlight"] = v_z.HighlightValidator() self._validators["highlightcolor"] = v_z.HighlightcolorValidator() self._validators["highlightwidth"] = v_z.HighlightwidthValidator() self._validators["project"] = v_z.ProjectValidator() self._validators["show"] = v_z.ShowValidator() self._validators["size"] = v_z.SizeValidator() self._validators["start"] = v_z.StartValidator() self._validators["usecolormap"] = v_z.UsecolormapValidator() self._validators["width"] = v_z.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("end", None) self["end"] = end if end is not None else _v _v = arg.pop("highlight", None) self["highlight"] = highlight if highlight is not None else _v _v = arg.pop("highlightcolor", None) self["highlightcolor"] = highlightcolor if highlightcolor is not None else _v _v = arg.pop("highlightwidth", None) self["highlightwidth"] = highlightwidth if highlightwidth is not None else _v _v = arg.pop("project", None) self["project"] = project if project is not None else _v _v = arg.pop("show", None) self["show"] = show if show is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("start", None) self["start"] = start if start is not None else _v _v = arg.pop("usecolormap", None) self["usecolormap"] = usecolormap if usecolormap is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Y(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the color of the contour lines. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # end # --- @property def end(self): """ Sets the end contour level value. Must be more than `contours.start` The 'end' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["end"] @end.setter def end(self, val): self["end"] = val # highlight # --------- @property def highlight(self): """ Determines whether or not contour lines about the y dimension are highlighted on hover. The 'highlight' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["highlight"] @highlight.setter def highlight(self, val): self["highlight"] = val # highlightcolor # -------------- @property def highlightcolor(self): """ Sets the color of the highlighted contour lines. The 'highlightcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["highlightcolor"] @highlightcolor.setter def highlightcolor(self, val): self["highlightcolor"] = val # highlightwidth # -------------- @property def highlightwidth(self): """ Sets the width of the highlighted contour lines. The 'highlightwidth' property is a number and may be specified as: - An int or float in the interval [1, 16] Returns ------- int|float """ return self["highlightwidth"] @highlightwidth.setter def highlightwidth(self, val): self["highlightwidth"] = val # project # ------- @property def project(self): """ The 'project' property is an instance of Project that may be specified as: - An instance of plotly.graph_objs.surface.contours.y.Project - A dict of string/value properties that will be passed to the Project constructor Supported dict properties: x Determines whether or not these contour lines are projected on the x plane. If `highlight` is set to True (the default), the projected lines are shown on hover. If `show` is set to True, the projected lines are shown in permanence. y Determines whether or not these contour lines are projected on the y plane. If `highlight` is set to True (the default), the projected lines are shown on hover. If `show` is set to True, the projected lines are shown in permanence. z Determines whether or not these contour lines are projected on the z plane. If `highlight` is set to True (the default), the projected lines are shown on hover. If `show` is set to True, the projected lines are shown in permanence. Returns ------- plotly.graph_objs.surface.contours.y.Project """ return self["project"] @project.setter def project(self, val): self["project"] = val # show # ---- @property def show(self): """ Determines whether or not contour lines about the y dimension are drawn. The 'show' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["show"] @show.setter def show(self, val): self["show"] = val # size # ---- @property def size(self): """ Sets the step between each contour level. Must be positive. The 'size' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # start # ----- @property def start(self): """ Sets the starting contour level value. Must be less than `contours.end` The 'start' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["start"] @start.setter def start(self, val): self["start"] = val # usecolormap # ----------- @property def usecolormap(self): """ An alternate to "color". Determines whether or not the contour lines are colored using the trace "colorscale". The 'usecolormap' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["usecolormap"] @usecolormap.setter def usecolormap(self, val): self["usecolormap"] = val # width # ----- @property def width(self): """ Sets the width of the contour lines. The 'width' property is a number and may be specified as: - An int or float in the interval [1, 16] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "surface.contours" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the color of the contour lines. end Sets the end contour level value. Must be more than `contours.start` highlight Determines whether or not contour lines about the y dimension are highlighted on hover. highlightcolor Sets the color of the highlighted contour lines. highlightwidth Sets the width of the highlighted contour lines. project plotly.graph_objects.surface.contours.y.Project instance or dict with compatible properties show Determines whether or not contour lines about the y dimension are drawn. size Sets the step between each contour level. Must be positive. start Sets the starting contour level value. Must be less than `contours.end` usecolormap An alternate to "color". Determines whether or not the contour lines are colored using the trace "colorscale". width Sets the width of the contour lines. """ def __init__( self, arg=None, color=None, end=None, highlight=None, highlightcolor=None, highlightwidth=None, project=None, show=None, size=None, start=None, usecolormap=None, width=None, **kwargs ): """ Construct a new Y object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.surface.contours.Y color Sets the color of the contour lines. end Sets the end contour level value. Must be more than `contours.start` highlight Determines whether or not contour lines about the y dimension are highlighted on hover. highlightcolor Sets the color of the highlighted contour lines. highlightwidth Sets the width of the highlighted contour lines. project plotly.graph_objects.surface.contours.y.Project instance or dict with compatible properties show Determines whether or not contour lines about the y dimension are drawn. size Sets the step between each contour level. Must be positive. start Sets the starting contour level value. Must be less than `contours.end` usecolormap An alternate to "color". Determines whether or not the contour lines are colored using the trace "colorscale". width Sets the width of the contour lines. Returns ------- Y """ super(Y, self).__init__("y") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.surface.contours.Y constructor must be a dict or an instance of plotly.graph_objs.surface.contours.Y""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.surface.contours import y as v_y # Initialize validators # --------------------- self._validators["color"] = v_y.ColorValidator() self._validators["end"] = v_y.EndValidator() self._validators["highlight"] = v_y.HighlightValidator() self._validators["highlightcolor"] = v_y.HighlightcolorValidator() self._validators["highlightwidth"] = v_y.HighlightwidthValidator() self._validators["project"] = v_y.ProjectValidator() self._validators["show"] = v_y.ShowValidator() self._validators["size"] = v_y.SizeValidator() self._validators["start"] = v_y.StartValidator() self._validators["usecolormap"] = v_y.UsecolormapValidator() self._validators["width"] = v_y.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("end", None) self["end"] = end if end is not None else _v _v = arg.pop("highlight", None) self["highlight"] = highlight if highlight is not None else _v _v = arg.pop("highlightcolor", None) self["highlightcolor"] = highlightcolor if highlightcolor is not None else _v _v = arg.pop("highlightwidth", None) self["highlightwidth"] = highlightwidth if highlightwidth is not None else _v _v = arg.pop("project", None) self["project"] = project if project is not None else _v _v = arg.pop("show", None) self["show"] = show if show is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("start", None) self["start"] = start if start is not None else _v _v = arg.pop("usecolormap", None) self["usecolormap"] = usecolormap if usecolormap is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class X(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the color of the contour lines. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # end # --- @property def end(self): """ Sets the end contour level value. Must be more than `contours.start` The 'end' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["end"] @end.setter def end(self, val): self["end"] = val # highlight # --------- @property def highlight(self): """ Determines whether or not contour lines about the x dimension are highlighted on hover. The 'highlight' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["highlight"] @highlight.setter def highlight(self, val): self["highlight"] = val # highlightcolor # -------------- @property def highlightcolor(self): """ Sets the color of the highlighted contour lines. The 'highlightcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["highlightcolor"] @highlightcolor.setter def highlightcolor(self, val): self["highlightcolor"] = val # highlightwidth # -------------- @property def highlightwidth(self): """ Sets the width of the highlighted contour lines. The 'highlightwidth' property is a number and may be specified as: - An int or float in the interval [1, 16] Returns ------- int|float """ return self["highlightwidth"] @highlightwidth.setter def highlightwidth(self, val): self["highlightwidth"] = val # project # ------- @property def project(self): """ The 'project' property is an instance of Project that may be specified as: - An instance of plotly.graph_objs.surface.contours.x.Project - A dict of string/value properties that will be passed to the Project constructor Supported dict properties: x Determines whether or not these contour lines are projected on the x plane. If `highlight` is set to True (the default), the projected lines are shown on hover. If `show` is set to True, the projected lines are shown in permanence. y Determines whether or not these contour lines are projected on the y plane. If `highlight` is set to True (the default), the projected lines are shown on hover. If `show` is set to True, the projected lines are shown in permanence. z Determines whether or not these contour lines are projected on the z plane. If `highlight` is set to True (the default), the projected lines are shown on hover. If `show` is set to True, the projected lines are shown in permanence. Returns ------- plotly.graph_objs.surface.contours.x.Project """ return self["project"] @project.setter def project(self, val): self["project"] = val # show # ---- @property def show(self): """ Determines whether or not contour lines about the x dimension are drawn. The 'show' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["show"] @show.setter def show(self, val): self["show"] = val # size # ---- @property def size(self): """ Sets the step between each contour level. Must be positive. The 'size' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # start # ----- @property def start(self): """ Sets the starting contour level value. Must be less than `contours.end` The 'start' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["start"] @start.setter def start(self, val): self["start"] = val # usecolormap # ----------- @property def usecolormap(self): """ An alternate to "color". Determines whether or not the contour lines are colored using the trace "colorscale". The 'usecolormap' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["usecolormap"] @usecolormap.setter def usecolormap(self, val): self["usecolormap"] = val # width # ----- @property def width(self): """ Sets the width of the contour lines. The 'width' property is a number and may be specified as: - An int or float in the interval [1, 16] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "surface.contours" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the color of the contour lines. end Sets the end contour level value. Must be more than `contours.start` highlight Determines whether or not contour lines about the x dimension are highlighted on hover. highlightcolor Sets the color of the highlighted contour lines. highlightwidth Sets the width of the highlighted contour lines. project plotly.graph_objects.surface.contours.x.Project instance or dict with compatible properties show Determines whether or not contour lines about the x dimension are drawn. size Sets the step between each contour level. Must be positive. start Sets the starting contour level value. Must be less than `contours.end` usecolormap An alternate to "color". Determines whether or not the contour lines are colored using the trace "colorscale". width Sets the width of the contour lines. """ def __init__( self, arg=None, color=None, end=None, highlight=None, highlightcolor=None, highlightwidth=None, project=None, show=None, size=None, start=None, usecolormap=None, width=None, **kwargs ): """ Construct a new X object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.surface.contours.X color Sets the color of the contour lines. end Sets the end contour level value. Must be more than `contours.start` highlight Determines whether or not contour lines about the x dimension are highlighted on hover. highlightcolor Sets the color of the highlighted contour lines. highlightwidth Sets the width of the highlighted contour lines. project plotly.graph_objects.surface.contours.x.Project instance or dict with compatible properties show Determines whether or not contour lines about the x dimension are drawn. size Sets the step between each contour level. Must be positive. start Sets the starting contour level value. Must be less than `contours.end` usecolormap An alternate to "color". Determines whether or not the contour lines are colored using the trace "colorscale". width Sets the width of the contour lines. Returns ------- X """ super(X, self).__init__("x") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.surface.contours.X constructor must be a dict or an instance of plotly.graph_objs.surface.contours.X""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.surface.contours import x as v_x # Initialize validators # --------------------- self._validators["color"] = v_x.ColorValidator() self._validators["end"] = v_x.EndValidator() self._validators["highlight"] = v_x.HighlightValidator() self._validators["highlightcolor"] = v_x.HighlightcolorValidator() self._validators["highlightwidth"] = v_x.HighlightwidthValidator() self._validators["project"] = v_x.ProjectValidator() self._validators["show"] = v_x.ShowValidator() self._validators["size"] = v_x.SizeValidator() self._validators["start"] = v_x.StartValidator() self._validators["usecolormap"] = v_x.UsecolormapValidator() self._validators["width"] = v_x.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("end", None) self["end"] = end if end is not None else _v _v = arg.pop("highlight", None) self["highlight"] = highlight if highlight is not None else _v _v = arg.pop("highlightcolor", None) self["highlightcolor"] = highlightcolor if highlightcolor is not None else _v _v = arg.pop("highlightwidth", None) self["highlightwidth"] = highlightwidth if highlightwidth is not None else _v _v = arg.pop("project", None) self["project"] = project if project is not None else _v _v = arg.pop("show", None) self["show"] = show if show is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("start", None) self["start"] = start if start is not None else _v _v = arg.pop("usecolormap", None) self["usecolormap"] = usecolormap if usecolormap is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["X", "Y", "Z", "x", "y", "z"] from plotly.graph_objs.surface.contours import z from plotly.graph_objs.surface.contours import y from plotly.graph_objs.surface.contours import x plotly-4.4.1+dfsg.orig/plotly/graph_objs/surface/__init__.py0000644000175000017500000033136413573721553023500 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Stream(_BaseTraceHierarchyType): # maxpoints # --------- @property def maxpoints(self): """ Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. The 'maxpoints' property is a number and may be specified as: - An int or float in the interval [0, 10000] Returns ------- int|float """ return self["maxpoints"] @maxpoints.setter def maxpoints(self, val): self["maxpoints"] = val # token # ----- @property def token(self): """ The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. The 'token' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["token"] @token.setter def token(self, val): self["token"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "surface" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """ def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): """ Construct a new Stream object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.surface.Stream maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- Stream """ super(Stream, self).__init__("stream") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.surface.Stream constructor must be a dict or an instance of plotly.graph_objs.surface.Stream""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.surface import stream as v_stream # Initialize validators # --------------------- self._validators["maxpoints"] = v_stream.MaxpointsValidator() self._validators["token"] = v_stream.TokenValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("maxpoints", None) self["maxpoints"] = maxpoints if maxpoints is not None else _v _v = arg.pop("token", None) self["token"] = token if token is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Lightposition(_BaseTraceHierarchyType): # x # - @property def x(self): """ Numeric vector, representing the X coordinate for each vertex. The 'x' property is a number and may be specified as: - An int or float in the interval [-100000, 100000] Returns ------- int|float """ return self["x"] @x.setter def x(self, val): self["x"] = val # y # - @property def y(self): """ Numeric vector, representing the Y coordinate for each vertex. The 'y' property is a number and may be specified as: - An int or float in the interval [-100000, 100000] Returns ------- int|float """ return self["y"] @y.setter def y(self, val): self["y"] = val # z # - @property def z(self): """ Numeric vector, representing the Z coordinate for each vertex. The 'z' property is a number and may be specified as: - An int or float in the interval [-100000, 100000] Returns ------- int|float """ return self["z"] @z.setter def z(self, val): self["z"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "surface" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ x Numeric vector, representing the X coordinate for each vertex. y Numeric vector, representing the Y coordinate for each vertex. z Numeric vector, representing the Z coordinate for each vertex. """ def __init__(self, arg=None, x=None, y=None, z=None, **kwargs): """ Construct a new Lightposition object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.surface.Lightposition x Numeric vector, representing the X coordinate for each vertex. y Numeric vector, representing the Y coordinate for each vertex. z Numeric vector, representing the Z coordinate for each vertex. Returns ------- Lightposition """ super(Lightposition, self).__init__("lightposition") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.surface.Lightposition constructor must be a dict or an instance of plotly.graph_objs.surface.Lightposition""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.surface import lightposition as v_lightposition # Initialize validators # --------------------- self._validators["x"] = v_lightposition.XValidator() self._validators["y"] = v_lightposition.YValidator() self._validators["z"] = v_lightposition.ZValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("z", None) self["z"] = z if z is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Lighting(_BaseTraceHierarchyType): # ambient # ------- @property def ambient(self): """ Ambient light increases overall color visibility but can wash out the image. The 'ambient' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["ambient"] @ambient.setter def ambient(self, val): self["ambient"] = val # diffuse # ------- @property def diffuse(self): """ Represents the extent that incident rays are reflected in a range of angles. The 'diffuse' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["diffuse"] @diffuse.setter def diffuse(self, val): self["diffuse"] = val # fresnel # ------- @property def fresnel(self): """ Represents the reflectance as a dependency of the viewing angle; e.g. paper is reflective when viewing it from the edge of the paper (almost 90 degrees), causing shine. The 'fresnel' property is a number and may be specified as: - An int or float in the interval [0, 5] Returns ------- int|float """ return self["fresnel"] @fresnel.setter def fresnel(self, val): self["fresnel"] = val # roughness # --------- @property def roughness(self): """ Alters specular reflection; the rougher the surface, the wider and less contrasty the shine. The 'roughness' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["roughness"] @roughness.setter def roughness(self, val): self["roughness"] = val # specular # -------- @property def specular(self): """ Represents the level that incident rays are reflected in a single direction, causing shine. The 'specular' property is a number and may be specified as: - An int or float in the interval [0, 2] Returns ------- int|float """ return self["specular"] @specular.setter def specular(self, val): self["specular"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "surface" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ ambient Ambient light increases overall color visibility but can wash out the image. diffuse Represents the extent that incident rays are reflected in a range of angles. fresnel Represents the reflectance as a dependency of the viewing angle; e.g. paper is reflective when viewing it from the edge of the paper (almost 90 degrees), causing shine. roughness Alters specular reflection; the rougher the surface, the wider and less contrasty the shine. specular Represents the level that incident rays are reflected in a single direction, causing shine. """ def __init__( self, arg=None, ambient=None, diffuse=None, fresnel=None, roughness=None, specular=None, **kwargs ): """ Construct a new Lighting object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.surface.Lighting ambient Ambient light increases overall color visibility but can wash out the image. diffuse Represents the extent that incident rays are reflected in a range of angles. fresnel Represents the reflectance as a dependency of the viewing angle; e.g. paper is reflective when viewing it from the edge of the paper (almost 90 degrees), causing shine. roughness Alters specular reflection; the rougher the surface, the wider and less contrasty the shine. specular Represents the level that incident rays are reflected in a single direction, causing shine. Returns ------- Lighting """ super(Lighting, self).__init__("lighting") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.surface.Lighting constructor must be a dict or an instance of plotly.graph_objs.surface.Lighting""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.surface import lighting as v_lighting # Initialize validators # --------------------- self._validators["ambient"] = v_lighting.AmbientValidator() self._validators["diffuse"] = v_lighting.DiffuseValidator() self._validators["fresnel"] = v_lighting.FresnelValidator() self._validators["roughness"] = v_lighting.RoughnessValidator() self._validators["specular"] = v_lighting.SpecularValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("ambient", None) self["ambient"] = ambient if ambient is not None else _v _v = arg.pop("diffuse", None) self["diffuse"] = diffuse if diffuse is not None else _v _v = arg.pop("fresnel", None) self["fresnel"] = fresnel if fresnel is not None else _v _v = arg.pop("roughness", None) self["roughness"] = roughness if roughness is not None else _v _v = arg.pop("specular", None) self["specular"] = specular if specular is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Hoverlabel(_BaseTraceHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'right', 'auto'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["align"] @align.setter def align(self, val): self["align"] = val # alignsrc # -------- @property def alignsrc(self): """ Sets the source reference on plot.ly for align . The 'alignsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["alignsrc"] @alignsrc.setter def alignsrc(self, val): self["alignsrc"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the hover labels for this trace The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bgcolorsrc # ---------- @property def bgcolorsrc(self): """ Sets the source reference on plot.ly for bgcolor . The 'bgcolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bgcolorsrc"] @bgcolorsrc.setter def bgcolorsrc(self, val): self["bgcolorsrc"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the border color of the hover labels for this trace. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # bordercolorsrc # -------------- @property def bordercolorsrc(self): """ Sets the source reference on plot.ly for bordercolor . The 'bordercolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bordercolorsrc"] @bordercolorsrc.setter def bordercolorsrc(self, val): self["bordercolorsrc"] = val # font # ---- @property def font(self): """ Sets the font used in hover labels. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.surface.hoverlabel.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.surface.hoverlabel.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # namelength # ---------- @property def namelength(self): """ Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. The 'namelength' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [-1, 9223372036854775807] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|numpy.ndarray """ return self["namelength"] @namelength.setter def namelength(self, val): self["namelength"] = val # namelengthsrc # ------------- @property def namelengthsrc(self): """ Sets the source reference on plot.ly for namelength . The 'namelengthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["namelengthsrc"] @namelengthsrc.setter def namelengthsrc(self, val): self["namelengthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "surface" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """ def __init__( self, arg=None, align=None, alignsrc=None, bgcolor=None, bgcolorsrc=None, bordercolor=None, bordercolorsrc=None, font=None, namelength=None, namelengthsrc=None, **kwargs ): """ Construct a new Hoverlabel object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.surface.Hoverlabel align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- Hoverlabel """ super(Hoverlabel, self).__init__("hoverlabel") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.surface.Hoverlabel constructor must be a dict or an instance of plotly.graph_objs.surface.Hoverlabel""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.surface import hoverlabel as v_hoverlabel # Initialize validators # --------------------- self._validators["align"] = v_hoverlabel.AlignValidator() self._validators["alignsrc"] = v_hoverlabel.AlignsrcValidator() self._validators["bgcolor"] = v_hoverlabel.BgcolorValidator() self._validators["bgcolorsrc"] = v_hoverlabel.BgcolorsrcValidator() self._validators["bordercolor"] = v_hoverlabel.BordercolorValidator() self._validators["bordercolorsrc"] = v_hoverlabel.BordercolorsrcValidator() self._validators["font"] = v_hoverlabel.FontValidator() self._validators["namelength"] = v_hoverlabel.NamelengthValidator() self._validators["namelengthsrc"] = v_hoverlabel.NamelengthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("alignsrc", None) self["alignsrc"] = alignsrc if alignsrc is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bgcolorsrc", None) self["bgcolorsrc"] = bgcolorsrc if bgcolorsrc is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("bordercolorsrc", None) self["bordercolorsrc"] = bordercolorsrc if bordercolorsrc is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("namelength", None) self["namelength"] = namelength if namelength is not None else _v _v = arg.pop("namelengthsrc", None) self["namelengthsrc"] = namelengthsrc if namelengthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Contours(_BaseTraceHierarchyType): # x # - @property def x(self): """ The 'x' property is an instance of X that may be specified as: - An instance of plotly.graph_objs.surface.contours.X - A dict of string/value properties that will be passed to the X constructor Supported dict properties: color Sets the color of the contour lines. end Sets the end contour level value. Must be more than `contours.start` highlight Determines whether or not contour lines about the x dimension are highlighted on hover. highlightcolor Sets the color of the highlighted contour lines. highlightwidth Sets the width of the highlighted contour lines. project plotly.graph_objects.surface.contours.x.Project instance or dict with compatible properties show Determines whether or not contour lines about the x dimension are drawn. size Sets the step between each contour level. Must be positive. start Sets the starting contour level value. Must be less than `contours.end` usecolormap An alternate to "color". Determines whether or not the contour lines are colored using the trace "colorscale". width Sets the width of the contour lines. Returns ------- plotly.graph_objs.surface.contours.X """ return self["x"] @x.setter def x(self, val): self["x"] = val # y # - @property def y(self): """ The 'y' property is an instance of Y that may be specified as: - An instance of plotly.graph_objs.surface.contours.Y - A dict of string/value properties that will be passed to the Y constructor Supported dict properties: color Sets the color of the contour lines. end Sets the end contour level value. Must be more than `contours.start` highlight Determines whether or not contour lines about the y dimension are highlighted on hover. highlightcolor Sets the color of the highlighted contour lines. highlightwidth Sets the width of the highlighted contour lines. project plotly.graph_objects.surface.contours.y.Project instance or dict with compatible properties show Determines whether or not contour lines about the y dimension are drawn. size Sets the step between each contour level. Must be positive. start Sets the starting contour level value. Must be less than `contours.end` usecolormap An alternate to "color". Determines whether or not the contour lines are colored using the trace "colorscale". width Sets the width of the contour lines. Returns ------- plotly.graph_objs.surface.contours.Y """ return self["y"] @y.setter def y(self, val): self["y"] = val # z # - @property def z(self): """ The 'z' property is an instance of Z that may be specified as: - An instance of plotly.graph_objs.surface.contours.Z - A dict of string/value properties that will be passed to the Z constructor Supported dict properties: color Sets the color of the contour lines. end Sets the end contour level value. Must be more than `contours.start` highlight Determines whether or not contour lines about the z dimension are highlighted on hover. highlightcolor Sets the color of the highlighted contour lines. highlightwidth Sets the width of the highlighted contour lines. project plotly.graph_objects.surface.contours.z.Project instance or dict with compatible properties show Determines whether or not contour lines about the z dimension are drawn. size Sets the step between each contour level. Must be positive. start Sets the starting contour level value. Must be less than `contours.end` usecolormap An alternate to "color". Determines whether or not the contour lines are colored using the trace "colorscale". width Sets the width of the contour lines. Returns ------- plotly.graph_objs.surface.contours.Z """ return self["z"] @z.setter def z(self, val): self["z"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "surface" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ x plotly.graph_objects.surface.contours.X instance or dict with compatible properties y plotly.graph_objects.surface.contours.Y instance or dict with compatible properties z plotly.graph_objects.surface.contours.Z instance or dict with compatible properties """ def __init__(self, arg=None, x=None, y=None, z=None, **kwargs): """ Construct a new Contours object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.surface.Contours x plotly.graph_objects.surface.contours.X instance or dict with compatible properties y plotly.graph_objects.surface.contours.Y instance or dict with compatible properties z plotly.graph_objects.surface.contours.Z instance or dict with compatible properties Returns ------- Contours """ super(Contours, self).__init__("contours") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.surface.Contours constructor must be a dict or an instance of plotly.graph_objs.surface.Contours""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.surface import contours as v_contours # Initialize validators # --------------------- self._validators["x"] = v_contours.XValidator() self._validators["y"] = v_contours.YValidator() self._validators["z"] = v_contours.ZValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("z", None) self["z"] = z if z is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class ColorBar(_BaseTraceHierarchyType): # bgcolor # ------- @property def bgcolor(self): """ Sets the color of padded area. The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the axis line color. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # borderwidth # ----------- @property def borderwidth(self): """ Sets the width (in px) or the border enclosing this color bar. The 'borderwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["borderwidth"] @borderwidth.setter def borderwidth(self, val): self["borderwidth"] = val # dtick # ----- @property def dtick(self): """ Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" The 'dtick' property accepts values of any type Returns ------- Any """ return self["dtick"] @dtick.setter def dtick(self, val): self["dtick"] = val # exponentformat # -------------- @property def exponentformat(self): """ Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. The 'exponentformat' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'e', 'E', 'power', 'SI', 'B'] Returns ------- Any """ return self["exponentformat"] @exponentformat.setter def exponentformat(self, val): self["exponentformat"] = val # len # --- @property def len(self): """ Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. The 'len' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["len"] @len.setter def len(self, val): self["len"] = val # lenmode # ------- @property def lenmode(self): """ Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. The 'lenmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["lenmode"] @lenmode.setter def lenmode(self, val): self["lenmode"] = val # nticks # ------ @property def nticks(self): """ Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". The 'nticks' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nticks"] @nticks.setter def nticks(self, val): self["nticks"] = val # outlinecolor # ------------ @property def outlinecolor(self): """ Sets the axis line color. The 'outlinecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["outlinecolor"] @outlinecolor.setter def outlinecolor(self, val): self["outlinecolor"] = val # outlinewidth # ------------ @property def outlinewidth(self): """ Sets the width (in px) of the axis line. The 'outlinewidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["outlinewidth"] @outlinewidth.setter def outlinewidth(self, val): self["outlinewidth"] = val # separatethousands # ----------------- @property def separatethousands(self): """ If "true", even 4-digit integers are separated The 'separatethousands' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["separatethousands"] @separatethousands.setter def separatethousands(self, val): self["separatethousands"] = val # showexponent # ------------ @property def showexponent(self): """ If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. The 'showexponent' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showexponent"] @showexponent.setter def showexponent(self, val): self["showexponent"] = val # showticklabels # -------------- @property def showticklabels(self): """ Determines whether or not the tick labels are drawn. The 'showticklabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showticklabels"] @showticklabels.setter def showticklabels(self, val): self["showticklabels"] = val # showtickprefix # -------------- @property def showtickprefix(self): """ If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. The 'showtickprefix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showtickprefix"] @showtickprefix.setter def showtickprefix(self, val): self["showtickprefix"] = val # showticksuffix # -------------- @property def showticksuffix(self): """ Same as `showtickprefix` but for tick suffixes. The 'showticksuffix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showticksuffix"] @showticksuffix.setter def showticksuffix(self, val): self["showticksuffix"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # thicknessmode # ------------- @property def thicknessmode(self): """ Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. The 'thicknessmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["thicknessmode"] @thicknessmode.setter def thicknessmode(self, val): self["thicknessmode"] = val # tick0 # ----- @property def tick0(self): """ Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. The 'tick0' property accepts values of any type Returns ------- Any """ return self["tick0"] @tick0.setter def tick0(self, val): self["tick0"] = val # tickangle # --------- @property def tickangle(self): """ Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. The 'tickangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["tickangle"] @tickangle.setter def tickangle(self, val): self["tickangle"] = val # tickcolor # --------- @property def tickcolor(self): """ Sets the tick color. The 'tickcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["tickcolor"] @tickcolor.setter def tickcolor(self, val): self["tickcolor"] = val # tickfont # -------- @property def tickfont(self): """ Sets the color bar's tick label font The 'tickfont' property is an instance of Tickfont that may be specified as: - An instance of plotly.graph_objs.surface.colorbar.Tickfont - A dict of string/value properties that will be passed to the Tickfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.surface.colorbar.Tickfont """ return self["tickfont"] @tickfont.setter def tickfont(self, val): self["tickfont"] = val # tickformat # ---------- @property def tickformat(self): """ Sets the tick label formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'tickformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickformat"] @tickformat.setter def tickformat(self, val): self["tickformat"] = val # tickformatstops # --------------- @property def tickformatstops(self): """ The 'tickformatstops' property is a tuple of instances of Tickformatstop that may be specified as: - A list or tuple of instances of plotly.graph_objs.surface.colorbar.Tickformatstop - A list or tuple of dicts of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- tuple[plotly.graph_objs.surface.colorbar.Tickformatstop] """ return self["tickformatstops"] @tickformatstops.setter def tickformatstops(self, val): self["tickformatstops"] = val # tickformatstopdefaults # ---------------------- @property def tickformatstopdefaults(self): """ When used in a template (as layout.template.data.surface.colorbar.tickformatstopdefaults), sets the default property values to use for elements of surface.colorbar.tickformatstops The 'tickformatstopdefaults' property is an instance of Tickformatstop that may be specified as: - An instance of plotly.graph_objs.surface.colorbar.Tickformatstop - A dict of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: Returns ------- plotly.graph_objs.surface.colorbar.Tickformatstop """ return self["tickformatstopdefaults"] @tickformatstopdefaults.setter def tickformatstopdefaults(self, val): self["tickformatstopdefaults"] = val # ticklen # ------- @property def ticklen(self): """ Sets the tick length (in px). The 'ticklen' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ticklen"] @ticklen.setter def ticklen(self, val): self["ticklen"] = val # tickmode # -------- @property def tickmode(self): """ Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). The 'tickmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'linear', 'array'] Returns ------- Any """ return self["tickmode"] @tickmode.setter def tickmode(self, val): self["tickmode"] = val # tickprefix # ---------- @property def tickprefix(self): """ Sets a tick label prefix. The 'tickprefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickprefix"] @tickprefix.setter def tickprefix(self, val): self["tickprefix"] = val # ticks # ----- @property def ticks(self): """ Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. The 'ticks' property is an enumeration that may be specified as: - One of the following enumeration values: ['outside', 'inside', ''] Returns ------- Any """ return self["ticks"] @ticks.setter def ticks(self, val): self["ticks"] = val # ticksuffix # ---------- @property def ticksuffix(self): """ Sets a tick label suffix. The 'ticksuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ticksuffix"] @ticksuffix.setter def ticksuffix(self, val): self["ticksuffix"] = val # ticktext # -------- @property def ticktext(self): """ Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. The 'ticktext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ticktext"] @ticktext.setter def ticktext(self, val): self["ticktext"] = val # ticktextsrc # ----------- @property def ticktextsrc(self): """ Sets the source reference on plot.ly for ticktext . The 'ticktextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ticktextsrc"] @ticktextsrc.setter def ticktextsrc(self, val): self["ticktextsrc"] = val # tickvals # -------- @property def tickvals(self): """ Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. The 'tickvals' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["tickvals"] @tickvals.setter def tickvals(self, val): self["tickvals"] = val # tickvalssrc # ----------- @property def tickvalssrc(self): """ Sets the source reference on plot.ly for tickvals . The 'tickvalssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tickvalssrc"] @tickvalssrc.setter def tickvalssrc(self, val): self["tickvalssrc"] = val # tickwidth # --------- @property def tickwidth(self): """ Sets the tick width (in px). The 'tickwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["tickwidth"] @tickwidth.setter def tickwidth(self, val): self["tickwidth"] = val # title # ----- @property def title(self): """ The 'title' property is an instance of Title that may be specified as: - An instance of plotly.graph_objs.surface.colorbar.Title - A dict of string/value properties that will be passed to the Title constructor Supported dict properties: font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- plotly.graph_objs.surface.colorbar.Title """ return self["title"] @title.setter def title(self, val): self["title"] = val # titlefont # --------- @property def titlefont(self): """ Deprecated: Please use surface.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.surface.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- """ return self["titlefont"] @titlefont.setter def titlefont(self, val): self["titlefont"] = val # titleside # --------- @property def titleside(self): """ Deprecated: Please use surface.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- """ return self["titleside"] @titleside.setter def titleside(self, val): self["titleside"] = val # x # - @property def x(self): """ Sets the x position of the color bar (in plot fraction). The 'x' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["x"] @x.setter def x(self, val): self["x"] = val # xanchor # ------- @property def xanchor(self): """ Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. The 'xanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'center', 'right'] Returns ------- Any """ return self["xanchor"] @xanchor.setter def xanchor(self, val): self["xanchor"] = val # xpad # ---- @property def xpad(self): """ Sets the amount of padding (in px) along the x direction. The 'xpad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["xpad"] @xpad.setter def xpad(self, val): self["xpad"] = val # y # - @property def y(self): """ Sets the y position of the color bar (in plot fraction). The 'y' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["y"] @y.setter def y(self, val): self["y"] = val # yanchor # ------- @property def yanchor(self): """ Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. The 'yanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['top', 'middle', 'bottom'] Returns ------- Any """ return self["yanchor"] @yanchor.setter def yanchor(self, val): self["yanchor"] = val # ypad # ---- @property def ypad(self): """ Sets the amount of padding (in px) along the y direction. The 'ypad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ypad"] @ypad.setter def ypad(self, val): self["ypad"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "surface" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.surface.colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.surfac e.colorbar.tickformatstopdefaults), sets the default property values to use for elements of surface.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.surface.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use surface.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use surface.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """ _mapped_properties = { "titlefont": ("title", "font"), "titleside": ("title", "side"), } def __init__( self, arg=None, bgcolor=None, bordercolor=None, borderwidth=None, dtick=None, exponentformat=None, len=None, lenmode=None, nticks=None, outlinecolor=None, outlinewidth=None, separatethousands=None, showexponent=None, showticklabels=None, showtickprefix=None, showticksuffix=None, thickness=None, thicknessmode=None, tick0=None, tickangle=None, tickcolor=None, tickfont=None, tickformat=None, tickformatstops=None, tickformatstopdefaults=None, ticklen=None, tickmode=None, tickprefix=None, ticks=None, ticksuffix=None, ticktext=None, ticktextsrc=None, tickvals=None, tickvalssrc=None, tickwidth=None, title=None, titlefont=None, titleside=None, x=None, xanchor=None, xpad=None, y=None, yanchor=None, ypad=None, **kwargs ): """ Construct a new ColorBar object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.surface.ColorBar bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.surface.colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.surfac e.colorbar.tickformatstopdefaults), sets the default property values to use for elements of surface.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.surface.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use surface.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use surface.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- ColorBar """ super(ColorBar, self).__init__("colorbar") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.surface.ColorBar constructor must be a dict or an instance of plotly.graph_objs.surface.ColorBar""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.surface import colorbar as v_colorbar # Initialize validators # --------------------- self._validators["bgcolor"] = v_colorbar.BgcolorValidator() self._validators["bordercolor"] = v_colorbar.BordercolorValidator() self._validators["borderwidth"] = v_colorbar.BorderwidthValidator() self._validators["dtick"] = v_colorbar.DtickValidator() self._validators["exponentformat"] = v_colorbar.ExponentformatValidator() self._validators["len"] = v_colorbar.LenValidator() self._validators["lenmode"] = v_colorbar.LenmodeValidator() self._validators["nticks"] = v_colorbar.NticksValidator() self._validators["outlinecolor"] = v_colorbar.OutlinecolorValidator() self._validators["outlinewidth"] = v_colorbar.OutlinewidthValidator() self._validators["separatethousands"] = v_colorbar.SeparatethousandsValidator() self._validators["showexponent"] = v_colorbar.ShowexponentValidator() self._validators["showticklabels"] = v_colorbar.ShowticklabelsValidator() self._validators["showtickprefix"] = v_colorbar.ShowtickprefixValidator() self._validators["showticksuffix"] = v_colorbar.ShowticksuffixValidator() self._validators["thickness"] = v_colorbar.ThicknessValidator() self._validators["thicknessmode"] = v_colorbar.ThicknessmodeValidator() self._validators["tick0"] = v_colorbar.Tick0Validator() self._validators["tickangle"] = v_colorbar.TickangleValidator() self._validators["tickcolor"] = v_colorbar.TickcolorValidator() self._validators["tickfont"] = v_colorbar.TickfontValidator() self._validators["tickformat"] = v_colorbar.TickformatValidator() self._validators["tickformatstops"] = v_colorbar.TickformatstopsValidator() self._validators[ "tickformatstopdefaults" ] = v_colorbar.TickformatstopValidator() self._validators["ticklen"] = v_colorbar.TicklenValidator() self._validators["tickmode"] = v_colorbar.TickmodeValidator() self._validators["tickprefix"] = v_colorbar.TickprefixValidator() self._validators["ticks"] = v_colorbar.TicksValidator() self._validators["ticksuffix"] = v_colorbar.TicksuffixValidator() self._validators["ticktext"] = v_colorbar.TicktextValidator() self._validators["ticktextsrc"] = v_colorbar.TicktextsrcValidator() self._validators["tickvals"] = v_colorbar.TickvalsValidator() self._validators["tickvalssrc"] = v_colorbar.TickvalssrcValidator() self._validators["tickwidth"] = v_colorbar.TickwidthValidator() self._validators["title"] = v_colorbar.TitleValidator() self._validators["x"] = v_colorbar.XValidator() self._validators["xanchor"] = v_colorbar.XanchorValidator() self._validators["xpad"] = v_colorbar.XpadValidator() self._validators["y"] = v_colorbar.YValidator() self._validators["yanchor"] = v_colorbar.YanchorValidator() self._validators["ypad"] = v_colorbar.YpadValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("borderwidth", None) self["borderwidth"] = borderwidth if borderwidth is not None else _v _v = arg.pop("dtick", None) self["dtick"] = dtick if dtick is not None else _v _v = arg.pop("exponentformat", None) self["exponentformat"] = exponentformat if exponentformat is not None else _v _v = arg.pop("len", None) self["len"] = len if len is not None else _v _v = arg.pop("lenmode", None) self["lenmode"] = lenmode if lenmode is not None else _v _v = arg.pop("nticks", None) self["nticks"] = nticks if nticks is not None else _v _v = arg.pop("outlinecolor", None) self["outlinecolor"] = outlinecolor if outlinecolor is not None else _v _v = arg.pop("outlinewidth", None) self["outlinewidth"] = outlinewidth if outlinewidth is not None else _v _v = arg.pop("separatethousands", None) self["separatethousands"] = ( separatethousands if separatethousands is not None else _v ) _v = arg.pop("showexponent", None) self["showexponent"] = showexponent if showexponent is not None else _v _v = arg.pop("showticklabels", None) self["showticklabels"] = showticklabels if showticklabels is not None else _v _v = arg.pop("showtickprefix", None) self["showtickprefix"] = showtickprefix if showtickprefix is not None else _v _v = arg.pop("showticksuffix", None) self["showticksuffix"] = showticksuffix if showticksuffix is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("thicknessmode", None) self["thicknessmode"] = thicknessmode if thicknessmode is not None else _v _v = arg.pop("tick0", None) self["tick0"] = tick0 if tick0 is not None else _v _v = arg.pop("tickangle", None) self["tickangle"] = tickangle if tickangle is not None else _v _v = arg.pop("tickcolor", None) self["tickcolor"] = tickcolor if tickcolor is not None else _v _v = arg.pop("tickfont", None) self["tickfont"] = tickfont if tickfont is not None else _v _v = arg.pop("tickformat", None) self["tickformat"] = tickformat if tickformat is not None else _v _v = arg.pop("tickformatstops", None) self["tickformatstops"] = tickformatstops if tickformatstops is not None else _v _v = arg.pop("tickformatstopdefaults", None) self["tickformatstopdefaults"] = ( tickformatstopdefaults if tickformatstopdefaults is not None else _v ) _v = arg.pop("ticklen", None) self["ticklen"] = ticklen if ticklen is not None else _v _v = arg.pop("tickmode", None) self["tickmode"] = tickmode if tickmode is not None else _v _v = arg.pop("tickprefix", None) self["tickprefix"] = tickprefix if tickprefix is not None else _v _v = arg.pop("ticks", None) self["ticks"] = ticks if ticks is not None else _v _v = arg.pop("ticksuffix", None) self["ticksuffix"] = ticksuffix if ticksuffix is not None else _v _v = arg.pop("ticktext", None) self["ticktext"] = ticktext if ticktext is not None else _v _v = arg.pop("ticktextsrc", None) self["ticktextsrc"] = ticktextsrc if ticktextsrc is not None else _v _v = arg.pop("tickvals", None) self["tickvals"] = tickvals if tickvals is not None else _v _v = arg.pop("tickvalssrc", None) self["tickvalssrc"] = tickvalssrc if tickvalssrc is not None else _v _v = arg.pop("tickwidth", None) self["tickwidth"] = tickwidth if tickwidth is not None else _v _v = arg.pop("title", None) self["title"] = title if title is not None else _v _v = arg.pop("titlefont", None) _v = titlefont if titlefont is not None else _v if _v is not None: self["titlefont"] = _v _v = arg.pop("titleside", None) _v = titleside if titleside is not None else _v if _v is not None: self["titleside"] = _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xanchor", None) self["xanchor"] = xanchor if xanchor is not None else _v _v = arg.pop("xpad", None) self["xpad"] = xpad if xpad is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("yanchor", None) self["yanchor"] = yanchor if yanchor is not None else _v _v = arg.pop("ypad", None) self["ypad"] = ypad if ypad is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = [ "ColorBar", "Contours", "Hoverlabel", "Lighting", "Lightposition", "Stream", "colorbar", "contours", "hoverlabel", ] from plotly.graph_objs.surface import hoverlabel from plotly.graph_objs.surface import contours from plotly.graph_objs.surface import colorbar plotly-4.4.1+dfsg.orig/plotly/graph_objs/_deprecations.py0000644000175000017500000004716713573721545023136 0ustar noahfxnoahfximport warnings warnings.filterwarnings( "default", r"plotly\.graph_objs\.\w+ is deprecated", DeprecationWarning ) class Data(list): """ plotly.graph_objs.Data is deprecated. Please replace it with a list or tuple of instances of the following types - plotly.graph_objs.Scatter - plotly.graph_objs.Bar - plotly.graph_objs.Area - plotly.graph_objs.Histogram - etc. """ def __init__(self, *args, **kwargs): """ plotly.graph_objs.Data is deprecated. Please replace it with a list or tuple of instances of the following types - plotly.graph_objs.Scatter - plotly.graph_objs.Bar - plotly.graph_objs.Area - plotly.graph_objs.Histogram - etc. """ warnings.warn( """plotly.graph_objs.Data is deprecated. Please replace it with a list or tuple of instances of the following types - plotly.graph_objs.Scatter - plotly.graph_objs.Bar - plotly.graph_objs.Area - plotly.graph_objs.Histogram - etc. """, DeprecationWarning, ) super(Data, self).__init__(*args, **kwargs) class Annotations(list): """ plotly.graph_objs.Annotations is deprecated. Please replace it with a list or tuple of instances of the following types - plotly.graph_objs.layout.Annotation - plotly.graph_objs.layout.scene.Annotation """ def __init__(self, *args, **kwargs): """ plotly.graph_objs.Annotations is deprecated. Please replace it with a list or tuple of instances of the following types - plotly.graph_objs.layout.Annotation - plotly.graph_objs.layout.scene.Annotation """ warnings.warn( """plotly.graph_objs.Annotations is deprecated. Please replace it with a list or tuple of instances of the following types - plotly.graph_objs.layout.Annotation - plotly.graph_objs.layout.scene.Annotation """, DeprecationWarning, ) super(Annotations, self).__init__(*args, **kwargs) class Frames(list): """ plotly.graph_objs.Frames is deprecated. Please replace it with a list or tuple of instances of the following types - plotly.graph_objs.Frame """ def __init__(self, *args, **kwargs): """ plotly.graph_objs.Frames is deprecated. Please replace it with a list or tuple of instances of the following types - plotly.graph_objs.Frame """ warnings.warn( """plotly.graph_objs.Frames is deprecated. Please replace it with a list or tuple of instances of the following types - plotly.graph_objs.Frame """, DeprecationWarning, ) super(Frames, self).__init__(*args, **kwargs) class AngularAxis(dict): """ plotly.graph_objs.AngularAxis is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.layout.AngularAxis - plotly.graph_objs.layout.polar.AngularAxis """ def __init__(self, *args, **kwargs): """ plotly.graph_objs.AngularAxis is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.layout.AngularAxis - plotly.graph_objs.layout.polar.AngularAxis """ warnings.warn( """plotly.graph_objs.AngularAxis is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.layout.AngularAxis - plotly.graph_objs.layout.polar.AngularAxis """, DeprecationWarning, ) super(AngularAxis, self).__init__(*args, **kwargs) class Annotation(dict): """ plotly.graph_objs.Annotation is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.layout.Annotation - plotly.graph_objs.layout.scene.Annotation """ def __init__(self, *args, **kwargs): """ plotly.graph_objs.Annotation is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.layout.Annotation - plotly.graph_objs.layout.scene.Annotation """ warnings.warn( """plotly.graph_objs.Annotation is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.layout.Annotation - plotly.graph_objs.layout.scene.Annotation """, DeprecationWarning, ) super(Annotation, self).__init__(*args, **kwargs) class ColorBar(dict): """ plotly.graph_objs.ColorBar is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.scatter.marker.ColorBar - plotly.graph_objs.surface.ColorBar - etc. """ def __init__(self, *args, **kwargs): """ plotly.graph_objs.ColorBar is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.scatter.marker.ColorBar - plotly.graph_objs.surface.ColorBar - etc. """ warnings.warn( """plotly.graph_objs.ColorBar is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.scatter.marker.ColorBar - plotly.graph_objs.surface.ColorBar - etc. """, DeprecationWarning, ) super(ColorBar, self).__init__(*args, **kwargs) class Contours(dict): """ plotly.graph_objs.Contours is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.contour.Contours - plotly.graph_objs.surface.Contours - etc. """ def __init__(self, *args, **kwargs): """ plotly.graph_objs.Contours is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.contour.Contours - plotly.graph_objs.surface.Contours - etc. """ warnings.warn( """plotly.graph_objs.Contours is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.contour.Contours - plotly.graph_objs.surface.Contours - etc. """, DeprecationWarning, ) super(Contours, self).__init__(*args, **kwargs) class ErrorX(dict): """ plotly.graph_objs.ErrorX is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.scatter.ErrorX - plotly.graph_objs.histogram.ErrorX - etc. """ def __init__(self, *args, **kwargs): """ plotly.graph_objs.ErrorX is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.scatter.ErrorX - plotly.graph_objs.histogram.ErrorX - etc. """ warnings.warn( """plotly.graph_objs.ErrorX is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.scatter.ErrorX - plotly.graph_objs.histogram.ErrorX - etc. """, DeprecationWarning, ) super(ErrorX, self).__init__(*args, **kwargs) class ErrorY(dict): """ plotly.graph_objs.ErrorY is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.scatter.ErrorY - plotly.graph_objs.histogram.ErrorY - etc. """ def __init__(self, *args, **kwargs): """ plotly.graph_objs.ErrorY is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.scatter.ErrorY - plotly.graph_objs.histogram.ErrorY - etc. """ warnings.warn( """plotly.graph_objs.ErrorY is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.scatter.ErrorY - plotly.graph_objs.histogram.ErrorY - etc. """, DeprecationWarning, ) super(ErrorY, self).__init__(*args, **kwargs) class ErrorZ(dict): """ plotly.graph_objs.ErrorZ is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.scatter3d.ErrorZ """ def __init__(self, *args, **kwargs): """ plotly.graph_objs.ErrorZ is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.scatter3d.ErrorZ """ warnings.warn( """plotly.graph_objs.ErrorZ is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.scatter3d.ErrorZ """, DeprecationWarning, ) super(ErrorZ, self).__init__(*args, **kwargs) class Font(dict): """ plotly.graph_objs.Font is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.layout.Font - plotly.graph_objs.layout.hoverlabel.Font - etc. """ def __init__(self, *args, **kwargs): """ plotly.graph_objs.Font is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.layout.Font - plotly.graph_objs.layout.hoverlabel.Font - etc. """ warnings.warn( """plotly.graph_objs.Font is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.layout.Font - plotly.graph_objs.layout.hoverlabel.Font - etc. """, DeprecationWarning, ) super(Font, self).__init__(*args, **kwargs) class Legend(dict): """ plotly.graph_objs.Legend is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.layout.Legend """ def __init__(self, *args, **kwargs): """ plotly.graph_objs.Legend is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.layout.Legend """ warnings.warn( """plotly.graph_objs.Legend is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.layout.Legend """, DeprecationWarning, ) super(Legend, self).__init__(*args, **kwargs) class Line(dict): """ plotly.graph_objs.Line is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.scatter.Line - plotly.graph_objs.layout.shape.Line - etc. """ def __init__(self, *args, **kwargs): """ plotly.graph_objs.Line is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.scatter.Line - plotly.graph_objs.layout.shape.Line - etc. """ warnings.warn( """plotly.graph_objs.Line is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.scatter.Line - plotly.graph_objs.layout.shape.Line - etc. """, DeprecationWarning, ) super(Line, self).__init__(*args, **kwargs) class Margin(dict): """ plotly.graph_objs.Margin is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.layout.Margin """ def __init__(self, *args, **kwargs): """ plotly.graph_objs.Margin is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.layout.Margin """ warnings.warn( """plotly.graph_objs.Margin is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.layout.Margin """, DeprecationWarning, ) super(Margin, self).__init__(*args, **kwargs) class Marker(dict): """ plotly.graph_objs.Marker is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.scatter.Marker - plotly.graph_objs.histogram.selected.Marker - etc. """ def __init__(self, *args, **kwargs): """ plotly.graph_objs.Marker is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.scatter.Marker - plotly.graph_objs.histogram.selected.Marker - etc. """ warnings.warn( """plotly.graph_objs.Marker is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.scatter.Marker - plotly.graph_objs.histogram.selected.Marker - etc. """, DeprecationWarning, ) super(Marker, self).__init__(*args, **kwargs) class RadialAxis(dict): """ plotly.graph_objs.RadialAxis is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.layout.RadialAxis - plotly.graph_objs.layout.polar.RadialAxis """ def __init__(self, *args, **kwargs): """ plotly.graph_objs.RadialAxis is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.layout.RadialAxis - plotly.graph_objs.layout.polar.RadialAxis """ warnings.warn( """plotly.graph_objs.RadialAxis is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.layout.RadialAxis - plotly.graph_objs.layout.polar.RadialAxis """, DeprecationWarning, ) super(RadialAxis, self).__init__(*args, **kwargs) class Scene(dict): """ plotly.graph_objs.Scene is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.layout.Scene """ def __init__(self, *args, **kwargs): """ plotly.graph_objs.Scene is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.layout.Scene """ warnings.warn( """plotly.graph_objs.Scene is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.layout.Scene """, DeprecationWarning, ) super(Scene, self).__init__(*args, **kwargs) class Stream(dict): """ plotly.graph_objs.Stream is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.scatter.Stream - plotly.graph_objs.area.Stream """ def __init__(self, *args, **kwargs): """ plotly.graph_objs.Stream is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.scatter.Stream - plotly.graph_objs.area.Stream """ warnings.warn( """plotly.graph_objs.Stream is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.scatter.Stream - plotly.graph_objs.area.Stream """, DeprecationWarning, ) super(Stream, self).__init__(*args, **kwargs) class XAxis(dict): """ plotly.graph_objs.XAxis is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.layout.XAxis - plotly.graph_objs.layout.scene.XAxis """ def __init__(self, *args, **kwargs): """ plotly.graph_objs.XAxis is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.layout.XAxis - plotly.graph_objs.layout.scene.XAxis """ warnings.warn( """plotly.graph_objs.XAxis is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.layout.XAxis - plotly.graph_objs.layout.scene.XAxis """, DeprecationWarning, ) super(XAxis, self).__init__(*args, **kwargs) class YAxis(dict): """ plotly.graph_objs.YAxis is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.layout.YAxis - plotly.graph_objs.layout.scene.YAxis """ def __init__(self, *args, **kwargs): """ plotly.graph_objs.YAxis is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.layout.YAxis - plotly.graph_objs.layout.scene.YAxis """ warnings.warn( """plotly.graph_objs.YAxis is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.layout.YAxis - plotly.graph_objs.layout.scene.YAxis """, DeprecationWarning, ) super(YAxis, self).__init__(*args, **kwargs) class ZAxis(dict): """ plotly.graph_objs.ZAxis is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.layout.scene.ZAxis """ def __init__(self, *args, **kwargs): """ plotly.graph_objs.ZAxis is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.layout.scene.ZAxis """ warnings.warn( """plotly.graph_objs.ZAxis is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.layout.scene.ZAxis """, DeprecationWarning, ) super(ZAxis, self).__init__(*args, **kwargs) class XBins(dict): """ plotly.graph_objs.XBins is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.histogram.XBins - plotly.graph_objs.histogram2d.XBins """ def __init__(self, *args, **kwargs): """ plotly.graph_objs.XBins is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.histogram.XBins - plotly.graph_objs.histogram2d.XBins """ warnings.warn( """plotly.graph_objs.XBins is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.histogram.XBins - plotly.graph_objs.histogram2d.XBins """, DeprecationWarning, ) super(XBins, self).__init__(*args, **kwargs) class YBins(dict): """ plotly.graph_objs.YBins is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.histogram.YBins - plotly.graph_objs.histogram2d.YBins """ def __init__(self, *args, **kwargs): """ plotly.graph_objs.YBins is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.histogram.YBins - plotly.graph_objs.histogram2d.YBins """ warnings.warn( """plotly.graph_objs.YBins is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.histogram.YBins - plotly.graph_objs.histogram2d.YBins """, DeprecationWarning, ) super(YBins, self).__init__(*args, **kwargs) class Trace(dict): """ plotly.graph_objs.Trace is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.Scatter - plotly.graph_objs.Bar - plotly.graph_objs.Area - plotly.graph_objs.Histogram - etc. """ def __init__(self, *args, **kwargs): """ plotly.graph_objs.Trace is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.Scatter - plotly.graph_objs.Bar - plotly.graph_objs.Area - plotly.graph_objs.Histogram - etc. """ warnings.warn( """plotly.graph_objs.Trace is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.Scatter - plotly.graph_objs.Bar - plotly.graph_objs.Area - plotly.graph_objs.Histogram - etc. """, DeprecationWarning, ) super(Trace, self).__init__(*args, **kwargs) class Histogram2dcontour(dict): """ plotly.graph_objs.Histogram2dcontour is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.Histogram2dContour """ def __init__(self, *args, **kwargs): """ plotly.graph_objs.Histogram2dcontour is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.Histogram2dContour """ warnings.warn( """plotly.graph_objs.Histogram2dcontour is deprecated. Please replace it with one of the following more specific types - plotly.graph_objs.Histogram2dContour """, DeprecationWarning, ) super(Histogram2dcontour, self).__init__(*args, **kwargs) plotly-4.4.1+dfsg.orig/plotly/graph_objs/__init__.py0000644000175000017500001571072713573721602022055 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceType as _BaseTraceType import copy as _copy class Waterfall(_BaseTraceType): # alignmentgroup # -------------- @property def alignmentgroup(self): """ Set several traces linked to the same position axis or matching axes to the same alignmentgroup. This controls whether bars compute their positional range dependently or independently. The 'alignmentgroup' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["alignmentgroup"] @alignmentgroup.setter def alignmentgroup(self, val): self["alignmentgroup"] = val # base # ---- @property def base(self): """ Sets where the bar base is drawn (in position axis units). The 'base' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["base"] @base.setter def base(self, val): self["base"] = val # cliponaxis # ---------- @property def cliponaxis(self): """ Determines whether the text nodes are clipped about the subplot axes. To show the text nodes above axis lines and tick labels, make sure to set `xaxis.layer` and `yaxis.layer` to *below traces*. The 'cliponaxis' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["cliponaxis"] @cliponaxis.setter def cliponaxis(self, val): self["cliponaxis"] = val # connector # --------- @property def connector(self): """ The 'connector' property is an instance of Connector that may be specified as: - An instance of plotly.graph_objs.waterfall.Connector - A dict of string/value properties that will be passed to the Connector constructor Supported dict properties: line plotly.graph_objects.waterfall.connector.Line instance or dict with compatible properties mode Sets the shape of connector lines. visible Determines if connector lines are drawn. Returns ------- plotly.graph_objs.waterfall.Connector """ return self["connector"] @connector.setter def connector(self, val): self["connector"] = val # constraintext # ------------- @property def constraintext(self): """ Constrain the size of text inside or outside a bar to be no larger than the bar itself. The 'constraintext' property is an enumeration that may be specified as: - One of the following enumeration values: ['inside', 'outside', 'both', 'none'] Returns ------- Any """ return self["constraintext"] @constraintext.setter def constraintext(self, val): self["constraintext"] = val # customdata # ---------- @property def customdata(self): """ Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements The 'customdata' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["customdata"] @customdata.setter def customdata(self, val): self["customdata"] = val # customdatasrc # ------------- @property def customdatasrc(self): """ Sets the source reference on plot.ly for customdata . The 'customdatasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["customdatasrc"] @customdatasrc.setter def customdatasrc(self, val): self["customdatasrc"] = val # decreasing # ---------- @property def decreasing(self): """ The 'decreasing' property is an instance of Decreasing that may be specified as: - An instance of plotly.graph_objs.waterfall.Decreasing - A dict of string/value properties that will be passed to the Decreasing constructor Supported dict properties: marker plotly.graph_objects.waterfall.decreasing.Marke r instance or dict with compatible properties Returns ------- plotly.graph_objs.waterfall.Decreasing """ return self["decreasing"] @decreasing.setter def decreasing(self, val): self["decreasing"] = val # dx # -- @property def dx(self): """ Sets the x coordinate step. See `x0` for more info. The 'dx' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["dx"] @dx.setter def dx(self, val): self["dx"] = val # dy # -- @property def dy(self): """ Sets the y coordinate step. See `y0` for more info. The 'dy' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["dy"] @dy.setter def dy(self, val): self["dy"] = val # hoverinfo # --------- @property def hoverinfo(self): """ Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. The 'hoverinfo' property is a flaglist and may be specified as a string containing: - Any combination of ['name', 'x', 'y', 'text', 'initial', 'delta', 'final'] joined with '+' characters (e.g. 'name+x') OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') - A list or array of the above Returns ------- Any|numpy.ndarray """ return self["hoverinfo"] @hoverinfo.setter def hoverinfo(self, val): self["hoverinfo"] = val # hoverinfosrc # ------------ @property def hoverinfosrc(self): """ Sets the source reference on plot.ly for hoverinfo . The 'hoverinfosrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hoverinfosrc"] @hoverinfosrc.setter def hoverinfosrc(self, val): self["hoverinfosrc"] = val # hoverlabel # ---------- @property def hoverlabel(self): """ The 'hoverlabel' property is an instance of Hoverlabel that may be specified as: - An instance of plotly.graph_objs.waterfall.Hoverlabel - A dict of string/value properties that will be passed to the Hoverlabel constructor Supported dict properties: align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- plotly.graph_objs.waterfall.Hoverlabel """ return self["hoverlabel"] @hoverlabel.setter def hoverlabel(self, val): self["hoverlabel"] = val # hovertemplate # ------------- @property def hovertemplate(self): """ Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event- data. Additionally, every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. variables `initial`, `delta` and `final`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. The 'hovertemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertemplate"] @hovertemplate.setter def hovertemplate(self, val): self["hovertemplate"] = val # hovertemplatesrc # ---------------- @property def hovertemplatesrc(self): """ Sets the source reference on plot.ly for hovertemplate . The 'hovertemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertemplatesrc"] @hovertemplatesrc.setter def hovertemplatesrc(self, val): self["hovertemplatesrc"] = val # hovertext # --------- @property def hovertext(self): """ Sets hover text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. The 'hovertext' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertext"] @hovertext.setter def hovertext(self, val): self["hovertext"] = val # hovertextsrc # ------------ @property def hovertextsrc(self): """ Sets the source reference on plot.ly for hovertext . The 'hovertextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertextsrc"] @hovertextsrc.setter def hovertextsrc(self, val): self["hovertextsrc"] = val # ids # --- @property def ids(self): """ Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. The 'ids' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ids"] @ids.setter def ids(self, val): self["ids"] = val # idssrc # ------ @property def idssrc(self): """ Sets the source reference on plot.ly for ids . The 'idssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["idssrc"] @idssrc.setter def idssrc(self, val): self["idssrc"] = val # increasing # ---------- @property def increasing(self): """ The 'increasing' property is an instance of Increasing that may be specified as: - An instance of plotly.graph_objs.waterfall.Increasing - A dict of string/value properties that will be passed to the Increasing constructor Supported dict properties: marker plotly.graph_objects.waterfall.increasing.Marke r instance or dict with compatible properties Returns ------- plotly.graph_objs.waterfall.Increasing """ return self["increasing"] @increasing.setter def increasing(self, val): self["increasing"] = val # insidetextanchor # ---------------- @property def insidetextanchor(self): """ Determines if texts are kept at center or start/end points in `textposition` "inside" mode. The 'insidetextanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['end', 'middle', 'start'] Returns ------- Any """ return self["insidetextanchor"] @insidetextanchor.setter def insidetextanchor(self, val): self["insidetextanchor"] = val # insidetextfont # -------------- @property def insidetextfont(self): """ Sets the font used for `text` lying inside the bar. The 'insidetextfont' property is an instance of Insidetextfont that may be specified as: - An instance of plotly.graph_objs.waterfall.Insidetextfont - A dict of string/value properties that will be passed to the Insidetextfont constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.waterfall.Insidetextfont """ return self["insidetextfont"] @insidetextfont.setter def insidetextfont(self, val): self["insidetextfont"] = val # legendgroup # ----------- @property def legendgroup(self): """ Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. The 'legendgroup' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["legendgroup"] @legendgroup.setter def legendgroup(self, val): self["legendgroup"] = val # measure # ------- @property def measure(self): """ An array containing types of values. By default the values are considered as 'relative'. However; it is possible to use 'total' to compute the sums. Also 'absolute' could be applied to reset the computed total or to declare an initial value where needed. The 'measure' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["measure"] @measure.setter def measure(self, val): self["measure"] = val # measuresrc # ---------- @property def measuresrc(self): """ Sets the source reference on plot.ly for measure . The 'measuresrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["measuresrc"] @measuresrc.setter def measuresrc(self, val): self["measuresrc"] = val # meta # ---- @property def meta(self): """ Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. The 'meta' property accepts values of any type Returns ------- Any|numpy.ndarray """ return self["meta"] @meta.setter def meta(self, val): self["meta"] = val # metasrc # ------- @property def metasrc(self): """ Sets the source reference on plot.ly for meta . The 'metasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["metasrc"] @metasrc.setter def metasrc(self, val): self["metasrc"] = val # name # ---- @property def name(self): """ Sets the trace name. The trace name appear as the legend item and on hover. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # offset # ------ @property def offset(self): """ Shifts the position where the bar is drawn (in position axis units). In "group" barmode, traces that set "offset" will be excluded and drawn in "overlay" mode instead. The 'offset' property is a number and may be specified as: - An int or float - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["offset"] @offset.setter def offset(self, val): self["offset"] = val # offsetgroup # ----------- @property def offsetgroup(self): """ Set several traces linked to the same position axis or matching axes to the same offsetgroup where bars of the same position coordinate will line up. The 'offsetgroup' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["offsetgroup"] @offsetgroup.setter def offsetgroup(self, val): self["offsetgroup"] = val # offsetsrc # --------- @property def offsetsrc(self): """ Sets the source reference on plot.ly for offset . The 'offsetsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["offsetsrc"] @offsetsrc.setter def offsetsrc(self, val): self["offsetsrc"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the trace. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # orientation # ----------- @property def orientation(self): """ Sets the orientation of the bars. With "v" ("h"), the value of the each bar spans along the vertical (horizontal). The 'orientation' property is an enumeration that may be specified as: - One of the following enumeration values: ['v', 'h'] Returns ------- Any """ return self["orientation"] @orientation.setter def orientation(self, val): self["orientation"] = val # outsidetextfont # --------------- @property def outsidetextfont(self): """ Sets the font used for `text` lying outside the bar. The 'outsidetextfont' property is an instance of Outsidetextfont that may be specified as: - An instance of plotly.graph_objs.waterfall.Outsidetextfont - A dict of string/value properties that will be passed to the Outsidetextfont constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.waterfall.Outsidetextfont """ return self["outsidetextfont"] @outsidetextfont.setter def outsidetextfont(self, val): self["outsidetextfont"] = val # selectedpoints # -------------- @property def selectedpoints(self): """ Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. The 'selectedpoints' property accepts values of any type Returns ------- Any """ return self["selectedpoints"] @selectedpoints.setter def selectedpoints(self, val): self["selectedpoints"] = val # showlegend # ---------- @property def showlegend(self): """ Determines whether or not an item corresponding to this trace is shown in the legend. The 'showlegend' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showlegend"] @showlegend.setter def showlegend(self, val): self["showlegend"] = val # stream # ------ @property def stream(self): """ The 'stream' property is an instance of Stream that may be specified as: - An instance of plotly.graph_objs.waterfall.Stream - A dict of string/value properties that will be passed to the Stream constructor Supported dict properties: maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- plotly.graph_objs.waterfall.Stream """ return self["stream"] @stream.setter def stream(self, val): self["stream"] = val # text # ---- @property def text(self): """ Sets text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["text"] @text.setter def text(self, val): self["text"] = val # textangle # --------- @property def textangle(self): """ Sets the angle of the tick labels with respect to the bar. For example, a `tickangle` of -90 draws the tick labels vertically. With "auto" the texts may automatically be rotated to fit with the maximum size in bars. The 'textangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["textangle"] @textangle.setter def textangle(self, val): self["textangle"] = val # textfont # -------- @property def textfont(self): """ Sets the font used for `text`. The 'textfont' property is an instance of Textfont that may be specified as: - An instance of plotly.graph_objs.waterfall.Textfont - A dict of string/value properties that will be passed to the Textfont constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.waterfall.Textfont """ return self["textfont"] @textfont.setter def textfont(self, val): self["textfont"] = val # textinfo # -------- @property def textinfo(self): """ Determines which trace information appear on the graph. In the case of having multiple waterfalls, totals are computed separately (per trace). The 'textinfo' property is a flaglist and may be specified as a string containing: - Any combination of ['label', 'text', 'initial', 'delta', 'final'] joined with '+' characters (e.g. 'label+text') OR exactly one of ['none'] (e.g. 'none') Returns ------- Any """ return self["textinfo"] @textinfo.setter def textinfo(self, val): self["textinfo"] = val # textposition # ------------ @property def textposition(self): """ Specifies the location of the `text`. "inside" positions `text` inside, next to the bar end (rotated and scaled if needed). "outside" positions `text` outside, next to the bar end (scaled if needed), unless there is another bar stacked on this one, then the text gets pushed inside. "auto" tries to position `text` inside the bar, but if the bar is too small and no bar is stacked on this one the text is moved outside. The 'textposition' property is an enumeration that may be specified as: - One of the following enumeration values: ['inside', 'outside', 'auto', 'none'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["textposition"] @textposition.setter def textposition(self, val): self["textposition"] = val # textpositionsrc # --------------- @property def textpositionsrc(self): """ Sets the source reference on plot.ly for textposition . The 'textpositionsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["textpositionsrc"] @textpositionsrc.setter def textpositionsrc(self, val): self["textpositionsrc"] = val # textsrc # ------- @property def textsrc(self): """ Sets the source reference on plot.ly for text . The 'textsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["textsrc"] @textsrc.setter def textsrc(self, val): self["textsrc"] = val # texttemplate # ------------ @property def texttemplate(self): """ Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `initial`, `delta`, `final` and `label`. The 'texttemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["texttemplate"] @texttemplate.setter def texttemplate(self, val): self["texttemplate"] = val # texttemplatesrc # --------------- @property def texttemplatesrc(self): """ Sets the source reference on plot.ly for texttemplate . The 'texttemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["texttemplatesrc"] @texttemplatesrc.setter def texttemplatesrc(self, val): self["texttemplatesrc"] = val # totals # ------ @property def totals(self): """ The 'totals' property is an instance of Totals that may be specified as: - An instance of plotly.graph_objs.waterfall.Totals - A dict of string/value properties that will be passed to the Totals constructor Supported dict properties: marker plotly.graph_objects.waterfall.totals.Marker instance or dict with compatible properties Returns ------- plotly.graph_objs.waterfall.Totals """ return self["totals"] @totals.setter def totals(self, val): self["totals"] = val # uid # --- @property def uid(self): """ Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. The 'uid' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["uid"] @uid.setter def uid(self, val): self["uid"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # visible # ------- @property def visible(self): """ Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). The 'visible' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'legendonly'] Returns ------- Any """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # width # ----- @property def width(self): """ Sets the bar width (in position axis units). The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["width"] @width.setter def width(self, val): self["width"] = val # widthsrc # -------- @property def widthsrc(self): """ Sets the source reference on plot.ly for width . The 'widthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["widthsrc"] @widthsrc.setter def widthsrc(self, val): self["widthsrc"] = val # x # - @property def x(self): """ Sets the x coordinates. The 'x' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["x"] @x.setter def x(self, val): self["x"] = val # x0 # -- @property def x0(self): """ Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. The 'x0' property accepts values of any type Returns ------- Any """ return self["x0"] @x0.setter def x0(self, val): self["x0"] = val # xaxis # ----- @property def xaxis(self): """ Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. The 'xaxis' property is an identifier of a particular subplot, of type 'x', that may be specified as the string 'x' optionally followed by an integer >= 1 (e.g. 'x', 'x1', 'x2', 'x3', etc.) Returns ------- str """ return self["xaxis"] @xaxis.setter def xaxis(self, val): self["xaxis"] = val # xsrc # ---- @property def xsrc(self): """ Sets the source reference on plot.ly for x . The 'xsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["xsrc"] @xsrc.setter def xsrc(self, val): self["xsrc"] = val # y # - @property def y(self): """ Sets the y coordinates. The 'y' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["y"] @y.setter def y(self, val): self["y"] = val # y0 # -- @property def y0(self): """ Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. The 'y0' property accepts values of any type Returns ------- Any """ return self["y0"] @y0.setter def y0(self, val): self["y0"] = val # yaxis # ----- @property def yaxis(self): """ Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. The 'yaxis' property is an identifier of a particular subplot, of type 'y', that may be specified as the string 'y' optionally followed by an integer >= 1 (e.g. 'y', 'y1', 'y2', 'y3', etc.) Returns ------- str """ return self["yaxis"] @yaxis.setter def yaxis(self, val): self["yaxis"] = val # ysrc # ---- @property def ysrc(self): """ Sets the source reference on plot.ly for y . The 'ysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ysrc"] @ysrc.setter def ysrc(self, val): self["ysrc"] = val # type # ---- @property def type(self): return self._props["type"] # property parent name # -------------------- @property def _parent_path_str(self): return "" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ alignmentgroup Set several traces linked to the same position axis or matching axes to the same alignmentgroup. This controls whether bars compute their positional range dependently or independently. base Sets where the bar base is drawn (in position axis units). cliponaxis Determines whether the text nodes are clipped about the subplot axes. To show the text nodes above axis lines and tick labels, make sure to set `xaxis.layer` and `yaxis.layer` to *below traces*. connector plotly.graph_objects.waterfall.Connector instance or dict with compatible properties constraintext Constrain the size of text inside or outside a bar to be no larger than the bar itself. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . decreasing plotly.graph_objects.waterfall.Decreasing instance or dict with compatible properties dx Sets the x coordinate step. See `x0` for more info. dy Sets the y coordinate step. See `y0` for more info. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.waterfall.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `initial`, `delta` and `final`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . increasing plotly.graph_objects.waterfall.Increasing instance or dict with compatible properties insidetextanchor Determines if texts are kept at center or start/end points in `textposition` "inside" mode. insidetextfont Sets the font used for `text` lying inside the bar. legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. measure An array containing types of values. By default the values are considered as 'relative'. However; it is possible to use 'total' to compute the sums. Also 'absolute' could be applied to reset the computed total or to declare an initial value where needed. measuresrc Sets the source reference on plot.ly for measure . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. offset Shifts the position where the bar is drawn (in position axis units). In "group" barmode, traces that set "offset" will be excluded and drawn in "overlay" mode instead. offsetgroup Set several traces linked to the same position axis or matching axes to the same offsetgroup where bars of the same position coordinate will line up. offsetsrc Sets the source reference on plot.ly for offset . opacity Sets the opacity of the trace. orientation Sets the orientation of the bars. With "v" ("h"), the value of the each bar spans along the vertical (horizontal). outsidetextfont Sets the font used for `text` lying outside the bar. selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.waterfall.Stream instance or dict with compatible properties text Sets text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textangle Sets the angle of the tick labels with respect to the bar. For example, a `tickangle` of -90 draws the tick labels vertically. With "auto" the texts may automatically be rotated to fit with the maximum size in bars. textfont Sets the font used for `text`. textinfo Determines which trace information appear on the graph. In the case of having multiple waterfalls, totals are computed separately (per trace). textposition Specifies the location of the `text`. "inside" positions `text` inside, next to the bar end (rotated and scaled if needed). "outside" positions `text` outside, next to the bar end (scaled if needed), unless there is another bar stacked on this one, then the text gets pushed inside. "auto" tries to position `text` inside the bar, but if the bar is too small and no bar is stacked on this one the text is moved outside. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `initial`, `delta`, `final` and `label`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . totals plotly.graph_objects.waterfall.Totals instance or dict with compatible properties uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). width Sets the bar width (in position axis units). widthsrc Sets the source reference on plot.ly for width . x Sets the x coordinates. x0 Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xsrc Sets the source reference on plot.ly for x . y Sets the y coordinates. y0 Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ysrc Sets the source reference on plot.ly for y . """ def __init__( self, arg=None, alignmentgroup=None, base=None, cliponaxis=None, connector=None, constraintext=None, customdata=None, customdatasrc=None, decreasing=None, dx=None, dy=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, increasing=None, insidetextanchor=None, insidetextfont=None, legendgroup=None, measure=None, measuresrc=None, meta=None, metasrc=None, name=None, offset=None, offsetgroup=None, offsetsrc=None, opacity=None, orientation=None, outsidetextfont=None, selectedpoints=None, showlegend=None, stream=None, text=None, textangle=None, textfont=None, textinfo=None, textposition=None, textpositionsrc=None, textsrc=None, texttemplate=None, texttemplatesrc=None, totals=None, uid=None, uirevision=None, visible=None, width=None, widthsrc=None, x=None, x0=None, xaxis=None, xsrc=None, y=None, y0=None, yaxis=None, ysrc=None, **kwargs ): """ Construct a new Waterfall object Draws waterfall trace which is useful graph to displays the contribution of various elements (either positive or negative) in a bar chart. The data visualized by the span of the bars is set in `y` if `orientation` is set th "v" (the default) and the labels are set in `x`. By setting `orientation` to "h", the roles are interchanged. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.Waterfall alignmentgroup Set several traces linked to the same position axis or matching axes to the same alignmentgroup. This controls whether bars compute their positional range dependently or independently. base Sets where the bar base is drawn (in position axis units). cliponaxis Determines whether the text nodes are clipped about the subplot axes. To show the text nodes above axis lines and tick labels, make sure to set `xaxis.layer` and `yaxis.layer` to *below traces*. connector plotly.graph_objects.waterfall.Connector instance or dict with compatible properties constraintext Constrain the size of text inside or outside a bar to be no larger than the bar itself. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . decreasing plotly.graph_objects.waterfall.Decreasing instance or dict with compatible properties dx Sets the x coordinate step. See `x0` for more info. dy Sets the y coordinate step. See `y0` for more info. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.waterfall.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `initial`, `delta` and `final`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . increasing plotly.graph_objects.waterfall.Increasing instance or dict with compatible properties insidetextanchor Determines if texts are kept at center or start/end points in `textposition` "inside" mode. insidetextfont Sets the font used for `text` lying inside the bar. legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. measure An array containing types of values. By default the values are considered as 'relative'. However; it is possible to use 'total' to compute the sums. Also 'absolute' could be applied to reset the computed total or to declare an initial value where needed. measuresrc Sets the source reference on plot.ly for measure . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. offset Shifts the position where the bar is drawn (in position axis units). In "group" barmode, traces that set "offset" will be excluded and drawn in "overlay" mode instead. offsetgroup Set several traces linked to the same position axis or matching axes to the same offsetgroup where bars of the same position coordinate will line up. offsetsrc Sets the source reference on plot.ly for offset . opacity Sets the opacity of the trace. orientation Sets the orientation of the bars. With "v" ("h"), the value of the each bar spans along the vertical (horizontal). outsidetextfont Sets the font used for `text` lying outside the bar. selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.waterfall.Stream instance or dict with compatible properties text Sets text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textangle Sets the angle of the tick labels with respect to the bar. For example, a `tickangle` of -90 draws the tick labels vertically. With "auto" the texts may automatically be rotated to fit with the maximum size in bars. textfont Sets the font used for `text`. textinfo Determines which trace information appear on the graph. In the case of having multiple waterfalls, totals are computed separately (per trace). textposition Specifies the location of the `text`. "inside" positions `text` inside, next to the bar end (rotated and scaled if needed). "outside" positions `text` outside, next to the bar end (scaled if needed), unless there is another bar stacked on this one, then the text gets pushed inside. "auto" tries to position `text` inside the bar, but if the bar is too small and no bar is stacked on this one the text is moved outside. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `initial`, `delta`, `final` and `label`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . totals plotly.graph_objects.waterfall.Totals instance or dict with compatible properties uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). width Sets the bar width (in position axis units). widthsrc Sets the source reference on plot.ly for width . x Sets the x coordinates. x0 Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xsrc Sets the source reference on plot.ly for x . y Sets the y coordinates. y0 Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ysrc Sets the source reference on plot.ly for y . Returns ------- Waterfall """ super(Waterfall, self).__init__("waterfall") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.Waterfall constructor must be a dict or an instance of plotly.graph_objs.Waterfall""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators import waterfall as v_waterfall # Initialize validators # --------------------- self._validators["alignmentgroup"] = v_waterfall.AlignmentgroupValidator() self._validators["base"] = v_waterfall.BaseValidator() self._validators["cliponaxis"] = v_waterfall.CliponaxisValidator() self._validators["connector"] = v_waterfall.ConnectorValidator() self._validators["constraintext"] = v_waterfall.ConstraintextValidator() self._validators["customdata"] = v_waterfall.CustomdataValidator() self._validators["customdatasrc"] = v_waterfall.CustomdatasrcValidator() self._validators["decreasing"] = v_waterfall.DecreasingValidator() self._validators["dx"] = v_waterfall.DxValidator() self._validators["dy"] = v_waterfall.DyValidator() self._validators["hoverinfo"] = v_waterfall.HoverinfoValidator() self._validators["hoverinfosrc"] = v_waterfall.HoverinfosrcValidator() self._validators["hoverlabel"] = v_waterfall.HoverlabelValidator() self._validators["hovertemplate"] = v_waterfall.HovertemplateValidator() self._validators["hovertemplatesrc"] = v_waterfall.HovertemplatesrcValidator() self._validators["hovertext"] = v_waterfall.HovertextValidator() self._validators["hovertextsrc"] = v_waterfall.HovertextsrcValidator() self._validators["ids"] = v_waterfall.IdsValidator() self._validators["idssrc"] = v_waterfall.IdssrcValidator() self._validators["increasing"] = v_waterfall.IncreasingValidator() self._validators["insidetextanchor"] = v_waterfall.InsidetextanchorValidator() self._validators["insidetextfont"] = v_waterfall.InsidetextfontValidator() self._validators["legendgroup"] = v_waterfall.LegendgroupValidator() self._validators["measure"] = v_waterfall.MeasureValidator() self._validators["measuresrc"] = v_waterfall.MeasuresrcValidator() self._validators["meta"] = v_waterfall.MetaValidator() self._validators["metasrc"] = v_waterfall.MetasrcValidator() self._validators["name"] = v_waterfall.NameValidator() self._validators["offset"] = v_waterfall.OffsetValidator() self._validators["offsetgroup"] = v_waterfall.OffsetgroupValidator() self._validators["offsetsrc"] = v_waterfall.OffsetsrcValidator() self._validators["opacity"] = v_waterfall.OpacityValidator() self._validators["orientation"] = v_waterfall.OrientationValidator() self._validators["outsidetextfont"] = v_waterfall.OutsidetextfontValidator() self._validators["selectedpoints"] = v_waterfall.SelectedpointsValidator() self._validators["showlegend"] = v_waterfall.ShowlegendValidator() self._validators["stream"] = v_waterfall.StreamValidator() self._validators["text"] = v_waterfall.TextValidator() self._validators["textangle"] = v_waterfall.TextangleValidator() self._validators["textfont"] = v_waterfall.TextfontValidator() self._validators["textinfo"] = v_waterfall.TextinfoValidator() self._validators["textposition"] = v_waterfall.TextpositionValidator() self._validators["textpositionsrc"] = v_waterfall.TextpositionsrcValidator() self._validators["textsrc"] = v_waterfall.TextsrcValidator() self._validators["texttemplate"] = v_waterfall.TexttemplateValidator() self._validators["texttemplatesrc"] = v_waterfall.TexttemplatesrcValidator() self._validators["totals"] = v_waterfall.TotalsValidator() self._validators["uid"] = v_waterfall.UidValidator() self._validators["uirevision"] = v_waterfall.UirevisionValidator() self._validators["visible"] = v_waterfall.VisibleValidator() self._validators["width"] = v_waterfall.WidthValidator() self._validators["widthsrc"] = v_waterfall.WidthsrcValidator() self._validators["x"] = v_waterfall.XValidator() self._validators["x0"] = v_waterfall.X0Validator() self._validators["xaxis"] = v_waterfall.XAxisValidator() self._validators["xsrc"] = v_waterfall.XsrcValidator() self._validators["y"] = v_waterfall.YValidator() self._validators["y0"] = v_waterfall.Y0Validator() self._validators["yaxis"] = v_waterfall.YAxisValidator() self._validators["ysrc"] = v_waterfall.YsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("alignmentgroup", None) self["alignmentgroup"] = alignmentgroup if alignmentgroup is not None else _v _v = arg.pop("base", None) self["base"] = base if base is not None else _v _v = arg.pop("cliponaxis", None) self["cliponaxis"] = cliponaxis if cliponaxis is not None else _v _v = arg.pop("connector", None) self["connector"] = connector if connector is not None else _v _v = arg.pop("constraintext", None) self["constraintext"] = constraintext if constraintext is not None else _v _v = arg.pop("customdata", None) self["customdata"] = customdata if customdata is not None else _v _v = arg.pop("customdatasrc", None) self["customdatasrc"] = customdatasrc if customdatasrc is not None else _v _v = arg.pop("decreasing", None) self["decreasing"] = decreasing if decreasing is not None else _v _v = arg.pop("dx", None) self["dx"] = dx if dx is not None else _v _v = arg.pop("dy", None) self["dy"] = dy if dy is not None else _v _v = arg.pop("hoverinfo", None) self["hoverinfo"] = hoverinfo if hoverinfo is not None else _v _v = arg.pop("hoverinfosrc", None) self["hoverinfosrc"] = hoverinfosrc if hoverinfosrc is not None else _v _v = arg.pop("hoverlabel", None) self["hoverlabel"] = hoverlabel if hoverlabel is not None else _v _v = arg.pop("hovertemplate", None) self["hovertemplate"] = hovertemplate if hovertemplate is not None else _v _v = arg.pop("hovertemplatesrc", None) self["hovertemplatesrc"] = ( hovertemplatesrc if hovertemplatesrc is not None else _v ) _v = arg.pop("hovertext", None) self["hovertext"] = hovertext if hovertext is not None else _v _v = arg.pop("hovertextsrc", None) self["hovertextsrc"] = hovertextsrc if hovertextsrc is not None else _v _v = arg.pop("ids", None) self["ids"] = ids if ids is not None else _v _v = arg.pop("idssrc", None) self["idssrc"] = idssrc if idssrc is not None else _v _v = arg.pop("increasing", None) self["increasing"] = increasing if increasing is not None else _v _v = arg.pop("insidetextanchor", None) self["insidetextanchor"] = ( insidetextanchor if insidetextanchor is not None else _v ) _v = arg.pop("insidetextfont", None) self["insidetextfont"] = insidetextfont if insidetextfont is not None else _v _v = arg.pop("legendgroup", None) self["legendgroup"] = legendgroup if legendgroup is not None else _v _v = arg.pop("measure", None) self["measure"] = measure if measure is not None else _v _v = arg.pop("measuresrc", None) self["measuresrc"] = measuresrc if measuresrc is not None else _v _v = arg.pop("meta", None) self["meta"] = meta if meta is not None else _v _v = arg.pop("metasrc", None) self["metasrc"] = metasrc if metasrc is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("offset", None) self["offset"] = offset if offset is not None else _v _v = arg.pop("offsetgroup", None) self["offsetgroup"] = offsetgroup if offsetgroup is not None else _v _v = arg.pop("offsetsrc", None) self["offsetsrc"] = offsetsrc if offsetsrc is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("orientation", None) self["orientation"] = orientation if orientation is not None else _v _v = arg.pop("outsidetextfont", None) self["outsidetextfont"] = outsidetextfont if outsidetextfont is not None else _v _v = arg.pop("selectedpoints", None) self["selectedpoints"] = selectedpoints if selectedpoints is not None else _v _v = arg.pop("showlegend", None) self["showlegend"] = showlegend if showlegend is not None else _v _v = arg.pop("stream", None) self["stream"] = stream if stream is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v _v = arg.pop("textangle", None) self["textangle"] = textangle if textangle is not None else _v _v = arg.pop("textfont", None) self["textfont"] = textfont if textfont is not None else _v _v = arg.pop("textinfo", None) self["textinfo"] = textinfo if textinfo is not None else _v _v = arg.pop("textposition", None) self["textposition"] = textposition if textposition is not None else _v _v = arg.pop("textpositionsrc", None) self["textpositionsrc"] = textpositionsrc if textpositionsrc is not None else _v _v = arg.pop("textsrc", None) self["textsrc"] = textsrc if textsrc is not None else _v _v = arg.pop("texttemplate", None) self["texttemplate"] = texttemplate if texttemplate is not None else _v _v = arg.pop("texttemplatesrc", None) self["texttemplatesrc"] = texttemplatesrc if texttemplatesrc is not None else _v _v = arg.pop("totals", None) self["totals"] = totals if totals is not None else _v _v = arg.pop("uid", None) self["uid"] = uid if uid is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v _v = arg.pop("widthsrc", None) self["widthsrc"] = widthsrc if widthsrc is not None else _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("x0", None) self["x0"] = x0 if x0 is not None else _v _v = arg.pop("xaxis", None) self["xaxis"] = xaxis if xaxis is not None else _v _v = arg.pop("xsrc", None) self["xsrc"] = xsrc if xsrc is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("y0", None) self["y0"] = y0 if y0 is not None else _v _v = arg.pop("yaxis", None) self["yaxis"] = yaxis if yaxis is not None else _v _v = arg.pop("ysrc", None) self["ysrc"] = ysrc if ysrc is not None else _v # Read-only literals # ------------------ from _plotly_utils.basevalidators import LiteralValidator self._props["type"] = "waterfall" self._validators["type"] = LiteralValidator( plotly_name="type", parent_name="waterfall", val="waterfall" ) arg.pop("type", None) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceType as _BaseTraceType import copy as _copy class Volume(_BaseTraceType): # autocolorscale # -------------- @property def autocolorscale(self): """ Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. The 'autocolorscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocolorscale"] @autocolorscale.setter def autocolorscale(self, val): self["autocolorscale"] = val # caps # ---- @property def caps(self): """ The 'caps' property is an instance of Caps that may be specified as: - An instance of plotly.graph_objs.volume.Caps - A dict of string/value properties that will be passed to the Caps constructor Supported dict properties: x plotly.graph_objects.volume.caps.X instance or dict with compatible properties y plotly.graph_objects.volume.caps.Y instance or dict with compatible properties z plotly.graph_objects.volume.caps.Z instance or dict with compatible properties Returns ------- plotly.graph_objs.volume.Caps """ return self["caps"] @caps.setter def caps(self, val): self["caps"] = val # cauto # ----- @property def cauto(self): """ Determines whether or not the color domain is computed with respect to the input data (here `value`) or the bounds set in `cmin` and `cmax` Defaults to `false` when `cmin` and `cmax` are set by the user. The 'cauto' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["cauto"] @cauto.setter def cauto(self, val): self["cauto"] = val # cmax # ---- @property def cmax(self): """ Sets the upper bound of the color domain. Value should have the same units as `value` and if set, `cmin` must be set as well. The 'cmax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmax"] @cmax.setter def cmax(self, val): self["cmax"] = val # cmid # ---- @property def cmid(self): """ Sets the mid-point of the color domain by scaling `cmin` and/or `cmax` to be equidistant to this point. Value should have the same units as `value`. Has no effect when `cauto` is `false`. The 'cmid' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmid"] @cmid.setter def cmid(self, val): self["cmid"] = val # cmin # ---- @property def cmin(self): """ Sets the lower bound of the color domain. Value should have the same units as `value` and if set, `cmax` must be set as well. The 'cmin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmin"] @cmin.setter def cmin(self, val): self["cmin"] = val # coloraxis # --------- @property def coloraxis(self): """ Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. The 'coloraxis' property is an identifier of a particular subplot, of type 'coloraxis', that may be specified as the string 'coloraxis' optionally followed by an integer >= 1 (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) Returns ------- str """ return self["coloraxis"] @coloraxis.setter def coloraxis(self, val): self["coloraxis"] = val # colorbar # -------- @property def colorbar(self): """ The 'colorbar' property is an instance of ColorBar that may be specified as: - An instance of plotly.graph_objs.volume.ColorBar - A dict of string/value properties that will be passed to the ColorBar constructor Supported dict properties: bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.volume.colorbar .Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.volume.colorbar.tickformatstopdefaults), sets the default property values to use for elements of volume.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.volume.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use volume.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use volume.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- plotly.graph_objs.volume.ColorBar """ return self["colorbar"] @colorbar.setter def colorbar(self, val): self["colorbar"] = val # colorscale # ---------- @property def colorscale(self): """ Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`cmin` and `cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,Earth,Electric,Vi ridis,Cividis. The 'colorscale' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # contour # ------- @property def contour(self): """ The 'contour' property is an instance of Contour that may be specified as: - An instance of plotly.graph_objs.volume.Contour - A dict of string/value properties that will be passed to the Contour constructor Supported dict properties: color Sets the color of the contour lines. show Sets whether or not dynamic contours are shown on hover width Sets the width of the contour lines. Returns ------- plotly.graph_objs.volume.Contour """ return self["contour"] @contour.setter def contour(self, val): self["contour"] = val # customdata # ---------- @property def customdata(self): """ Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements The 'customdata' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["customdata"] @customdata.setter def customdata(self, val): self["customdata"] = val # customdatasrc # ------------- @property def customdatasrc(self): """ Sets the source reference on plot.ly for customdata . The 'customdatasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["customdatasrc"] @customdatasrc.setter def customdatasrc(self, val): self["customdatasrc"] = val # flatshading # ----------- @property def flatshading(self): """ Determines whether or not normal smoothing is applied to the meshes, creating meshes with an angular, low-poly look via flat reflections. The 'flatshading' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["flatshading"] @flatshading.setter def flatshading(self, val): self["flatshading"] = val # hoverinfo # --------- @property def hoverinfo(self): """ Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. The 'hoverinfo' property is a flaglist and may be specified as a string containing: - Any combination of ['x', 'y', 'z', 'text', 'name'] joined with '+' characters (e.g. 'x+y') OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') - A list or array of the above Returns ------- Any|numpy.ndarray """ return self["hoverinfo"] @hoverinfo.setter def hoverinfo(self, val): self["hoverinfo"] = val # hoverinfosrc # ------------ @property def hoverinfosrc(self): """ Sets the source reference on plot.ly for hoverinfo . The 'hoverinfosrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hoverinfosrc"] @hoverinfosrc.setter def hoverinfosrc(self, val): self["hoverinfosrc"] = val # hoverlabel # ---------- @property def hoverlabel(self): """ The 'hoverlabel' property is an instance of Hoverlabel that may be specified as: - An instance of plotly.graph_objs.volume.Hoverlabel - A dict of string/value properties that will be passed to the Hoverlabel constructor Supported dict properties: align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- plotly.graph_objs.volume.Hoverlabel """ return self["hoverlabel"] @hoverlabel.setter def hoverlabel(self, val): self["hoverlabel"] = val # hovertemplate # ------------- @property def hovertemplate(self): """ Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event- data. Additionally, every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. The 'hovertemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertemplate"] @hovertemplate.setter def hovertemplate(self, val): self["hovertemplate"] = val # hovertemplatesrc # ---------------- @property def hovertemplatesrc(self): """ Sets the source reference on plot.ly for hovertemplate . The 'hovertemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertemplatesrc"] @hovertemplatesrc.setter def hovertemplatesrc(self, val): self["hovertemplatesrc"] = val # hovertext # --------- @property def hovertext(self): """ Same as `text`. The 'hovertext' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertext"] @hovertext.setter def hovertext(self, val): self["hovertext"] = val # hovertextsrc # ------------ @property def hovertextsrc(self): """ Sets the source reference on plot.ly for hovertext . The 'hovertextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertextsrc"] @hovertextsrc.setter def hovertextsrc(self, val): self["hovertextsrc"] = val # ids # --- @property def ids(self): """ Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. The 'ids' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ids"] @ids.setter def ids(self, val): self["ids"] = val # idssrc # ------ @property def idssrc(self): """ Sets the source reference on plot.ly for ids . The 'idssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["idssrc"] @idssrc.setter def idssrc(self, val): self["idssrc"] = val # isomax # ------ @property def isomax(self): """ Sets the maximum boundary for iso-surface plot. The 'isomax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["isomax"] @isomax.setter def isomax(self, val): self["isomax"] = val # isomin # ------ @property def isomin(self): """ Sets the minimum boundary for iso-surface plot. The 'isomin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["isomin"] @isomin.setter def isomin(self, val): self["isomin"] = val # lighting # -------- @property def lighting(self): """ The 'lighting' property is an instance of Lighting that may be specified as: - An instance of plotly.graph_objs.volume.Lighting - A dict of string/value properties that will be passed to the Lighting constructor Supported dict properties: ambient Ambient light increases overall color visibility but can wash out the image. diffuse Represents the extent that incident rays are reflected in a range of angles. facenormalsepsilon Epsilon for face normals calculation avoids math issues arising from degenerate geometry. fresnel Represents the reflectance as a dependency of the viewing angle; e.g. paper is reflective when viewing it from the edge of the paper (almost 90 degrees), causing shine. roughness Alters specular reflection; the rougher the surface, the wider and less contrasty the shine. specular Represents the level that incident rays are reflected in a single direction, causing shine. vertexnormalsepsilon Epsilon for vertex normals calculation avoids math issues arising from degenerate geometry. Returns ------- plotly.graph_objs.volume.Lighting """ return self["lighting"] @lighting.setter def lighting(self, val): self["lighting"] = val # lightposition # ------------- @property def lightposition(self): """ The 'lightposition' property is an instance of Lightposition that may be specified as: - An instance of plotly.graph_objs.volume.Lightposition - A dict of string/value properties that will be passed to the Lightposition constructor Supported dict properties: x Numeric vector, representing the X coordinate for each vertex. y Numeric vector, representing the Y coordinate for each vertex. z Numeric vector, representing the Z coordinate for each vertex. Returns ------- plotly.graph_objs.volume.Lightposition """ return self["lightposition"] @lightposition.setter def lightposition(self, val): self["lightposition"] = val # meta # ---- @property def meta(self): """ Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. The 'meta' property accepts values of any type Returns ------- Any|numpy.ndarray """ return self["meta"] @meta.setter def meta(self, val): self["meta"] = val # metasrc # ------- @property def metasrc(self): """ Sets the source reference on plot.ly for meta . The 'metasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["metasrc"] @metasrc.setter def metasrc(self, val): self["metasrc"] = val # name # ---- @property def name(self): """ Sets the trace name. The trace name appear as the legend item and on hover. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the surface. Please note that in the case of using high `opacity` values for example a value greater than or equal to 0.5 on two surfaces (and 0.25 with four surfaces), an overlay of multiple transparent surfaces may not perfectly be sorted in depth by the webgl API. This behavior may be improved in the near future and is subject to change. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # opacityscale # ------------ @property def opacityscale(self): """ Sets the opacityscale. The opacityscale must be an array containing arrays mapping a normalized value to an opacity value. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 1], [0.5, 0.2], [1, 1]]` means that higher/lower values would have higher opacity values and those in the middle would be more transparent Alternatively, `opacityscale` may be a palette name string of the following list: 'min', 'max', 'extremes' and 'uniform'. The default is 'uniform'. The 'opacityscale' property accepts values of any type Returns ------- Any """ return self["opacityscale"] @opacityscale.setter def opacityscale(self, val): self["opacityscale"] = val # reversescale # ------------ @property def reversescale(self): """ Reverses the color mapping if true. If true, `cmin` will correspond to the last color in the array and `cmax` will correspond to the first color. The 'reversescale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["reversescale"] @reversescale.setter def reversescale(self, val): self["reversescale"] = val # scene # ----- @property def scene(self): """ Sets a reference between this trace's 3D coordinate system and a 3D scene. If "scene" (the default value), the (x,y,z) coordinates refer to `layout.scene`. If "scene2", the (x,y,z) coordinates refer to `layout.scene2`, and so on. The 'scene' property is an identifier of a particular subplot, of type 'scene', that may be specified as the string 'scene' optionally followed by an integer >= 1 (e.g. 'scene', 'scene1', 'scene2', 'scene3', etc.) Returns ------- str """ return self["scene"] @scene.setter def scene(self, val): self["scene"] = val # showscale # --------- @property def showscale(self): """ Determines whether or not a colorbar is displayed for this trace. The 'showscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showscale"] @showscale.setter def showscale(self, val): self["showscale"] = val # slices # ------ @property def slices(self): """ The 'slices' property is an instance of Slices that may be specified as: - An instance of plotly.graph_objs.volume.Slices - A dict of string/value properties that will be passed to the Slices constructor Supported dict properties: x plotly.graph_objects.volume.slices.X instance or dict with compatible properties y plotly.graph_objects.volume.slices.Y instance or dict with compatible properties z plotly.graph_objects.volume.slices.Z instance or dict with compatible properties Returns ------- plotly.graph_objs.volume.Slices """ return self["slices"] @slices.setter def slices(self, val): self["slices"] = val # spaceframe # ---------- @property def spaceframe(self): """ The 'spaceframe' property is an instance of Spaceframe that may be specified as: - An instance of plotly.graph_objs.volume.Spaceframe - A dict of string/value properties that will be passed to the Spaceframe constructor Supported dict properties: fill Sets the fill ratio of the `spaceframe` elements. The default fill value is 1 meaning that they are entirely shaded. Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. show Displays/hides tetrahedron shapes between minimum and maximum iso-values. Often useful when either caps or surfaces are disabled or filled with values less than 1. Returns ------- plotly.graph_objs.volume.Spaceframe """ return self["spaceframe"] @spaceframe.setter def spaceframe(self, val): self["spaceframe"] = val # stream # ------ @property def stream(self): """ The 'stream' property is an instance of Stream that may be specified as: - An instance of plotly.graph_objs.volume.Stream - A dict of string/value properties that will be passed to the Stream constructor Supported dict properties: maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- plotly.graph_objs.volume.Stream """ return self["stream"] @stream.setter def stream(self, val): self["stream"] = val # surface # ------- @property def surface(self): """ The 'surface' property is an instance of Surface that may be specified as: - An instance of plotly.graph_objs.volume.Surface - A dict of string/value properties that will be passed to the Surface constructor Supported dict properties: count Sets the number of iso-surfaces between minimum and maximum iso-values. By default this value is 2 meaning that only minimum and maximum surfaces would be drawn. fill Sets the fill ratio of the iso-surface. The default fill value of the surface is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. pattern Sets the surface pattern of the iso-surface 3-D sections. The default pattern of the surface is `all` meaning that the rest of surface elements would be shaded. The check options (either 1 or 2) could be used to draw half of the squares on the surface. Using various combinations of capital `A`, `B`, `C`, `D` and `E` may also be used to reduce the number of triangles on the iso-surfaces and creating other patterns of interest. show Hides/displays surfaces between minimum and maximum iso-values. Returns ------- plotly.graph_objs.volume.Surface """ return self["surface"] @surface.setter def surface(self, val): self["surface"] = val # text # ---- @property def text(self): """ Sets the text elements associated with the vertices. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["text"] @text.setter def text(self, val): self["text"] = val # textsrc # ------- @property def textsrc(self): """ Sets the source reference on plot.ly for text . The 'textsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["textsrc"] @textsrc.setter def textsrc(self, val): self["textsrc"] = val # uid # --- @property def uid(self): """ Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. The 'uid' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["uid"] @uid.setter def uid(self, val): self["uid"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # value # ----- @property def value(self): """ Sets the 4th dimension (value) of the vertices. The 'value' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["value"] @value.setter def value(self, val): self["value"] = val # valuesrc # -------- @property def valuesrc(self): """ Sets the source reference on plot.ly for value . The 'valuesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["valuesrc"] @valuesrc.setter def valuesrc(self, val): self["valuesrc"] = val # visible # ------- @property def visible(self): """ Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). The 'visible' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'legendonly'] Returns ------- Any """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # x # - @property def x(self): """ Sets the X coordinates of the vertices on X axis. The 'x' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["x"] @x.setter def x(self, val): self["x"] = val # xsrc # ---- @property def xsrc(self): """ Sets the source reference on plot.ly for x . The 'xsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["xsrc"] @xsrc.setter def xsrc(self, val): self["xsrc"] = val # y # - @property def y(self): """ Sets the Y coordinates of the vertices on Y axis. The 'y' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["y"] @y.setter def y(self, val): self["y"] = val # ysrc # ---- @property def ysrc(self): """ Sets the source reference on plot.ly for y . The 'ysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ysrc"] @ysrc.setter def ysrc(self, val): self["ysrc"] = val # z # - @property def z(self): """ Sets the Z coordinates of the vertices on Z axis. The 'z' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["z"] @z.setter def z(self, val): self["z"] = val # zsrc # ---- @property def zsrc(self): """ Sets the source reference on plot.ly for z . The 'zsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["zsrc"] @zsrc.setter def zsrc(self, val): self["zsrc"] = val # type # ---- @property def type(self): return self._props["type"] # property parent name # -------------------- @property def _parent_path_str(self): return "" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. caps plotly.graph_objects.volume.Caps instance or dict with compatible properties cauto Determines whether or not the color domain is computed with respect to the input data (here `value`) or the bounds set in `cmin` and `cmax` Defaults to `false` when `cmin` and `cmax` are set by the user. cmax Sets the upper bound of the color domain. Value should have the same units as `value` and if set, `cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `cmin` and/or `cmax` to be equidistant to this point. Value should have the same units as `value`. Has no effect when `cauto` is `false`. cmin Sets the lower bound of the color domain. Value should have the same units as `value` and if set, `cmax` must be set as well. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.volume.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`cmin` and `cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. contour plotly.graph_objects.volume.Contour instance or dict with compatible properties customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . flatshading Determines whether or not normal smoothing is applied to the meshes, creating meshes with an angular, low- poly look via flat reflections. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.volume.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . isomax Sets the maximum boundary for iso-surface plot. isomin Sets the minimum boundary for iso-surface plot. lighting plotly.graph_objects.volume.Lighting instance or dict with compatible properties lightposition plotly.graph_objects.volume.Lightposition instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the surface. Please note that in the case of using high `opacity` values for example a value greater than or equal to 0.5 on two surfaces (and 0.25 with four surfaces), an overlay of multiple transparent surfaces may not perfectly be sorted in depth by the webgl API. This behavior may be improved in the near future and is subject to change. opacityscale Sets the opacityscale. The opacityscale must be an array containing arrays mapping a normalized value to an opacity value. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 1], [0.5, 0.2], [1, 1]]` means that higher/lower values would have higher opacity values and those in the middle would be more transparent Alternatively, `opacityscale` may be a palette name string of the following list: 'min', 'max', 'extremes' and 'uniform'. The default is 'uniform'. reversescale Reverses the color mapping if true. If true, `cmin` will correspond to the last color in the array and `cmax` will correspond to the first color. scene Sets a reference between this trace's 3D coordinate system and a 3D scene. If "scene" (the default value), the (x,y,z) coordinates refer to `layout.scene`. If "scene2", the (x,y,z) coordinates refer to `layout.scene2`, and so on. showscale Determines whether or not a colorbar is displayed for this trace. slices plotly.graph_objects.volume.Slices instance or dict with compatible properties spaceframe plotly.graph_objects.volume.Spaceframe instance or dict with compatible properties stream plotly.graph_objects.volume.Stream instance or dict with compatible properties surface plotly.graph_objects.volume.Surface instance or dict with compatible properties text Sets the text elements associated with the vertices. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. value Sets the 4th dimension (value) of the vertices. valuesrc Sets the source reference on plot.ly for value . visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the X coordinates of the vertices on X axis. xsrc Sets the source reference on plot.ly for x . y Sets the Y coordinates of the vertices on Y axis. ysrc Sets the source reference on plot.ly for y . z Sets the Z coordinates of the vertices on Z axis. zsrc Sets the source reference on plot.ly for z . """ def __init__( self, arg=None, autocolorscale=None, caps=None, cauto=None, cmax=None, cmid=None, cmin=None, coloraxis=None, colorbar=None, colorscale=None, contour=None, customdata=None, customdatasrc=None, flatshading=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, isomax=None, isomin=None, lighting=None, lightposition=None, meta=None, metasrc=None, name=None, opacity=None, opacityscale=None, reversescale=None, scene=None, showscale=None, slices=None, spaceframe=None, stream=None, surface=None, text=None, textsrc=None, uid=None, uirevision=None, value=None, valuesrc=None, visible=None, x=None, xsrc=None, y=None, ysrc=None, z=None, zsrc=None, **kwargs ): """ Construct a new Volume object Draws volume trace between iso-min and iso-max values with coordinates given by four 1-dimensional arrays containing the `value`, `x`, `y` and `z` of every vertex of a uniform or non- uniform 3-D grid. Horizontal or vertical slices, caps as well as spaceframe between iso-min and iso-max values could also be drawn using this trace. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.Volume autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. caps plotly.graph_objects.volume.Caps instance or dict with compatible properties cauto Determines whether or not the color domain is computed with respect to the input data (here `value`) or the bounds set in `cmin` and `cmax` Defaults to `false` when `cmin` and `cmax` are set by the user. cmax Sets the upper bound of the color domain. Value should have the same units as `value` and if set, `cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `cmin` and/or `cmax` to be equidistant to this point. Value should have the same units as `value`. Has no effect when `cauto` is `false`. cmin Sets the lower bound of the color domain. Value should have the same units as `value` and if set, `cmax` must be set as well. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.volume.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`cmin` and `cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. contour plotly.graph_objects.volume.Contour instance or dict with compatible properties customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . flatshading Determines whether or not normal smoothing is applied to the meshes, creating meshes with an angular, low- poly look via flat reflections. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.volume.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . isomax Sets the maximum boundary for iso-surface plot. isomin Sets the minimum boundary for iso-surface plot. lighting plotly.graph_objects.volume.Lighting instance or dict with compatible properties lightposition plotly.graph_objects.volume.Lightposition instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the surface. Please note that in the case of using high `opacity` values for example a value greater than or equal to 0.5 on two surfaces (and 0.25 with four surfaces), an overlay of multiple transparent surfaces may not perfectly be sorted in depth by the webgl API. This behavior may be improved in the near future and is subject to change. opacityscale Sets the opacityscale. The opacityscale must be an array containing arrays mapping a normalized value to an opacity value. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 1], [0.5, 0.2], [1, 1]]` means that higher/lower values would have higher opacity values and those in the middle would be more transparent Alternatively, `opacityscale` may be a palette name string of the following list: 'min', 'max', 'extremes' and 'uniform'. The default is 'uniform'. reversescale Reverses the color mapping if true. If true, `cmin` will correspond to the last color in the array and `cmax` will correspond to the first color. scene Sets a reference between this trace's 3D coordinate system and a 3D scene. If "scene" (the default value), the (x,y,z) coordinates refer to `layout.scene`. If "scene2", the (x,y,z) coordinates refer to `layout.scene2`, and so on. showscale Determines whether or not a colorbar is displayed for this trace. slices plotly.graph_objects.volume.Slices instance or dict with compatible properties spaceframe plotly.graph_objects.volume.Spaceframe instance or dict with compatible properties stream plotly.graph_objects.volume.Stream instance or dict with compatible properties surface plotly.graph_objects.volume.Surface instance or dict with compatible properties text Sets the text elements associated with the vertices. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. value Sets the 4th dimension (value) of the vertices. valuesrc Sets the source reference on plot.ly for value . visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the X coordinates of the vertices on X axis. xsrc Sets the source reference on plot.ly for x . y Sets the Y coordinates of the vertices on Y axis. ysrc Sets the source reference on plot.ly for y . z Sets the Z coordinates of the vertices on Z axis. zsrc Sets the source reference on plot.ly for z . Returns ------- Volume """ super(Volume, self).__init__("volume") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.Volume constructor must be a dict or an instance of plotly.graph_objs.Volume""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators import volume as v_volume # Initialize validators # --------------------- self._validators["autocolorscale"] = v_volume.AutocolorscaleValidator() self._validators["caps"] = v_volume.CapsValidator() self._validators["cauto"] = v_volume.CautoValidator() self._validators["cmax"] = v_volume.CmaxValidator() self._validators["cmid"] = v_volume.CmidValidator() self._validators["cmin"] = v_volume.CminValidator() self._validators["coloraxis"] = v_volume.ColoraxisValidator() self._validators["colorbar"] = v_volume.ColorBarValidator() self._validators["colorscale"] = v_volume.ColorscaleValidator() self._validators["contour"] = v_volume.ContourValidator() self._validators["customdata"] = v_volume.CustomdataValidator() self._validators["customdatasrc"] = v_volume.CustomdatasrcValidator() self._validators["flatshading"] = v_volume.FlatshadingValidator() self._validators["hoverinfo"] = v_volume.HoverinfoValidator() self._validators["hoverinfosrc"] = v_volume.HoverinfosrcValidator() self._validators["hoverlabel"] = v_volume.HoverlabelValidator() self._validators["hovertemplate"] = v_volume.HovertemplateValidator() self._validators["hovertemplatesrc"] = v_volume.HovertemplatesrcValidator() self._validators["hovertext"] = v_volume.HovertextValidator() self._validators["hovertextsrc"] = v_volume.HovertextsrcValidator() self._validators["ids"] = v_volume.IdsValidator() self._validators["idssrc"] = v_volume.IdssrcValidator() self._validators["isomax"] = v_volume.IsomaxValidator() self._validators["isomin"] = v_volume.IsominValidator() self._validators["lighting"] = v_volume.LightingValidator() self._validators["lightposition"] = v_volume.LightpositionValidator() self._validators["meta"] = v_volume.MetaValidator() self._validators["metasrc"] = v_volume.MetasrcValidator() self._validators["name"] = v_volume.NameValidator() self._validators["opacity"] = v_volume.OpacityValidator() self._validators["opacityscale"] = v_volume.OpacityscaleValidator() self._validators["reversescale"] = v_volume.ReversescaleValidator() self._validators["scene"] = v_volume.SceneValidator() self._validators["showscale"] = v_volume.ShowscaleValidator() self._validators["slices"] = v_volume.SlicesValidator() self._validators["spaceframe"] = v_volume.SpaceframeValidator() self._validators["stream"] = v_volume.StreamValidator() self._validators["surface"] = v_volume.SurfaceValidator() self._validators["text"] = v_volume.TextValidator() self._validators["textsrc"] = v_volume.TextsrcValidator() self._validators["uid"] = v_volume.UidValidator() self._validators["uirevision"] = v_volume.UirevisionValidator() self._validators["value"] = v_volume.ValueValidator() self._validators["valuesrc"] = v_volume.ValuesrcValidator() self._validators["visible"] = v_volume.VisibleValidator() self._validators["x"] = v_volume.XValidator() self._validators["xsrc"] = v_volume.XsrcValidator() self._validators["y"] = v_volume.YValidator() self._validators["ysrc"] = v_volume.YsrcValidator() self._validators["z"] = v_volume.ZValidator() self._validators["zsrc"] = v_volume.ZsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autocolorscale", None) self["autocolorscale"] = autocolorscale if autocolorscale is not None else _v _v = arg.pop("caps", None) self["caps"] = caps if caps is not None else _v _v = arg.pop("cauto", None) self["cauto"] = cauto if cauto is not None else _v _v = arg.pop("cmax", None) self["cmax"] = cmax if cmax is not None else _v _v = arg.pop("cmid", None) self["cmid"] = cmid if cmid is not None else _v _v = arg.pop("cmin", None) self["cmin"] = cmin if cmin is not None else _v _v = arg.pop("coloraxis", None) self["coloraxis"] = coloraxis if coloraxis is not None else _v _v = arg.pop("colorbar", None) self["colorbar"] = colorbar if colorbar is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("contour", None) self["contour"] = contour if contour is not None else _v _v = arg.pop("customdata", None) self["customdata"] = customdata if customdata is not None else _v _v = arg.pop("customdatasrc", None) self["customdatasrc"] = customdatasrc if customdatasrc is not None else _v _v = arg.pop("flatshading", None) self["flatshading"] = flatshading if flatshading is not None else _v _v = arg.pop("hoverinfo", None) self["hoverinfo"] = hoverinfo if hoverinfo is not None else _v _v = arg.pop("hoverinfosrc", None) self["hoverinfosrc"] = hoverinfosrc if hoverinfosrc is not None else _v _v = arg.pop("hoverlabel", None) self["hoverlabel"] = hoverlabel if hoverlabel is not None else _v _v = arg.pop("hovertemplate", None) self["hovertemplate"] = hovertemplate if hovertemplate is not None else _v _v = arg.pop("hovertemplatesrc", None) self["hovertemplatesrc"] = ( hovertemplatesrc if hovertemplatesrc is not None else _v ) _v = arg.pop("hovertext", None) self["hovertext"] = hovertext if hovertext is not None else _v _v = arg.pop("hovertextsrc", None) self["hovertextsrc"] = hovertextsrc if hovertextsrc is not None else _v _v = arg.pop("ids", None) self["ids"] = ids if ids is not None else _v _v = arg.pop("idssrc", None) self["idssrc"] = idssrc if idssrc is not None else _v _v = arg.pop("isomax", None) self["isomax"] = isomax if isomax is not None else _v _v = arg.pop("isomin", None) self["isomin"] = isomin if isomin is not None else _v _v = arg.pop("lighting", None) self["lighting"] = lighting if lighting is not None else _v _v = arg.pop("lightposition", None) self["lightposition"] = lightposition if lightposition is not None else _v _v = arg.pop("meta", None) self["meta"] = meta if meta is not None else _v _v = arg.pop("metasrc", None) self["metasrc"] = metasrc if metasrc is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("opacityscale", None) self["opacityscale"] = opacityscale if opacityscale is not None else _v _v = arg.pop("reversescale", None) self["reversescale"] = reversescale if reversescale is not None else _v _v = arg.pop("scene", None) self["scene"] = scene if scene is not None else _v _v = arg.pop("showscale", None) self["showscale"] = showscale if showscale is not None else _v _v = arg.pop("slices", None) self["slices"] = slices if slices is not None else _v _v = arg.pop("spaceframe", None) self["spaceframe"] = spaceframe if spaceframe is not None else _v _v = arg.pop("stream", None) self["stream"] = stream if stream is not None else _v _v = arg.pop("surface", None) self["surface"] = surface if surface is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v _v = arg.pop("textsrc", None) self["textsrc"] = textsrc if textsrc is not None else _v _v = arg.pop("uid", None) self["uid"] = uid if uid is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("value", None) self["value"] = value if value is not None else _v _v = arg.pop("valuesrc", None) self["valuesrc"] = valuesrc if valuesrc is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xsrc", None) self["xsrc"] = xsrc if xsrc is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("ysrc", None) self["ysrc"] = ysrc if ysrc is not None else _v _v = arg.pop("z", None) self["z"] = z if z is not None else _v _v = arg.pop("zsrc", None) self["zsrc"] = zsrc if zsrc is not None else _v # Read-only literals # ------------------ from _plotly_utils.basevalidators import LiteralValidator self._props["type"] = "volume" self._validators["type"] = LiteralValidator( plotly_name="type", parent_name="volume", val="volume" ) arg.pop("type", None) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceType as _BaseTraceType import copy as _copy class Violin(_BaseTraceType): # alignmentgroup # -------------- @property def alignmentgroup(self): """ Set several traces linked to the same position axis or matching axes to the same alignmentgroup. This controls whether bars compute their positional range dependently or independently. The 'alignmentgroup' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["alignmentgroup"] @alignmentgroup.setter def alignmentgroup(self, val): self["alignmentgroup"] = val # bandwidth # --------- @property def bandwidth(self): """ Sets the bandwidth used to compute the kernel density estimate. By default, the bandwidth is determined by Silverman's rule of thumb. The 'bandwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["bandwidth"] @bandwidth.setter def bandwidth(self, val): self["bandwidth"] = val # box # --- @property def box(self): """ The 'box' property is an instance of Box that may be specified as: - An instance of plotly.graph_objs.violin.Box - A dict of string/value properties that will be passed to the Box constructor Supported dict properties: fillcolor Sets the inner box plot fill color. line plotly.graph_objects.violin.box.Line instance or dict with compatible properties visible Determines if an miniature box plot is drawn inside the violins. width Sets the width of the inner box plots relative to the violins' width. For example, with 1, the inner box plots are as wide as the violins. Returns ------- plotly.graph_objs.violin.Box """ return self["box"] @box.setter def box(self, val): self["box"] = val # customdata # ---------- @property def customdata(self): """ Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements The 'customdata' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["customdata"] @customdata.setter def customdata(self, val): self["customdata"] = val # customdatasrc # ------------- @property def customdatasrc(self): """ Sets the source reference on plot.ly for customdata . The 'customdatasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["customdatasrc"] @customdatasrc.setter def customdatasrc(self, val): self["customdatasrc"] = val # fillcolor # --------- @property def fillcolor(self): """ Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. The 'fillcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["fillcolor"] @fillcolor.setter def fillcolor(self, val): self["fillcolor"] = val # hoverinfo # --------- @property def hoverinfo(self): """ Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. The 'hoverinfo' property is a flaglist and may be specified as a string containing: - Any combination of ['x', 'y', 'z', 'text', 'name'] joined with '+' characters (e.g. 'x+y') OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') - A list or array of the above Returns ------- Any|numpy.ndarray """ return self["hoverinfo"] @hoverinfo.setter def hoverinfo(self, val): self["hoverinfo"] = val # hoverinfosrc # ------------ @property def hoverinfosrc(self): """ Sets the source reference on plot.ly for hoverinfo . The 'hoverinfosrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hoverinfosrc"] @hoverinfosrc.setter def hoverinfosrc(self, val): self["hoverinfosrc"] = val # hoverlabel # ---------- @property def hoverlabel(self): """ The 'hoverlabel' property is an instance of Hoverlabel that may be specified as: - An instance of plotly.graph_objs.violin.Hoverlabel - A dict of string/value properties that will be passed to the Hoverlabel constructor Supported dict properties: align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- plotly.graph_objs.violin.Hoverlabel """ return self["hoverlabel"] @hoverlabel.setter def hoverlabel(self, val): self["hoverlabel"] = val # hoveron # ------- @property def hoveron(self): """ Do the hover effects highlight individual violins or sample points or the kernel density estimate or any combination of them? The 'hoveron' property is a flaglist and may be specified as a string containing: - Any combination of ['violins', 'points', 'kde'] joined with '+' characters (e.g. 'violins+points') OR exactly one of ['all'] (e.g. 'all') Returns ------- Any """ return self["hoveron"] @hoveron.setter def hoveron(self, val): self["hoveron"] = val # hovertemplate # ------------- @property def hovertemplate(self): """ Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event- data. Additionally, every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. The 'hovertemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertemplate"] @hovertemplate.setter def hovertemplate(self, val): self["hovertemplate"] = val # hovertemplatesrc # ---------------- @property def hovertemplatesrc(self): """ Sets the source reference on plot.ly for hovertemplate . The 'hovertemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertemplatesrc"] @hovertemplatesrc.setter def hovertemplatesrc(self, val): self["hovertemplatesrc"] = val # hovertext # --------- @property def hovertext(self): """ Same as `text`. The 'hovertext' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertext"] @hovertext.setter def hovertext(self, val): self["hovertext"] = val # hovertextsrc # ------------ @property def hovertextsrc(self): """ Sets the source reference on plot.ly for hovertext . The 'hovertextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertextsrc"] @hovertextsrc.setter def hovertextsrc(self, val): self["hovertextsrc"] = val # ids # --- @property def ids(self): """ Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. The 'ids' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ids"] @ids.setter def ids(self, val): self["ids"] = val # idssrc # ------ @property def idssrc(self): """ Sets the source reference on plot.ly for ids . The 'idssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["idssrc"] @idssrc.setter def idssrc(self, val): self["idssrc"] = val # jitter # ------ @property def jitter(self): """ Sets the amount of jitter in the sample points drawn. If 0, the sample points align along the distribution axis. If 1, the sample points are drawn in a random jitter of width equal to the width of the violins. The 'jitter' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["jitter"] @jitter.setter def jitter(self, val): self["jitter"] = val # legendgroup # ----------- @property def legendgroup(self): """ Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. The 'legendgroup' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["legendgroup"] @legendgroup.setter def legendgroup(self, val): self["legendgroup"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.violin.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: color Sets the color of line bounding the violin(s). width Sets the width (in px) of line bounding the violin(s). Returns ------- plotly.graph_objs.violin.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.violin.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. line plotly.graph_objects.violin.marker.Line instance or dict with compatible properties opacity Sets the marker opacity. outliercolor Sets the color of the outlier sample points. size Sets the marker size (in px). symbol Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot- open" to a symbol name. Returns ------- plotly.graph_objs.violin.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # meanline # -------- @property def meanline(self): """ The 'meanline' property is an instance of Meanline that may be specified as: - An instance of plotly.graph_objs.violin.Meanline - A dict of string/value properties that will be passed to the Meanline constructor Supported dict properties: color Sets the mean line color. visible Determines if a line corresponding to the sample's mean is shown inside the violins. If `box.visible` is turned on, the mean line is drawn inside the inner box. Otherwise, the mean line is drawn from one side of the violin to other. width Sets the mean line width. Returns ------- plotly.graph_objs.violin.Meanline """ return self["meanline"] @meanline.setter def meanline(self, val): self["meanline"] = val # meta # ---- @property def meta(self): """ Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. The 'meta' property accepts values of any type Returns ------- Any|numpy.ndarray """ return self["meta"] @meta.setter def meta(self, val): self["meta"] = val # metasrc # ------- @property def metasrc(self): """ Sets the source reference on plot.ly for meta . The 'metasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["metasrc"] @metasrc.setter def metasrc(self, val): self["metasrc"] = val # name # ---- @property def name(self): """ Sets the trace name. The trace name appear as the legend item and on hover. For violin traces, the name will also be used for the position coordinate, if `x` and `x0` (`y` and `y0` if horizontal) are missing and the position axis is categorical. Note that the trace name is also used as a default value for attribute `scalegroup` (please see its description for details). The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # offsetgroup # ----------- @property def offsetgroup(self): """ Set several traces linked to the same position axis or matching axes to the same offsetgroup where bars of the same position coordinate will line up. The 'offsetgroup' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["offsetgroup"] @offsetgroup.setter def offsetgroup(self, val): self["offsetgroup"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the trace. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # orientation # ----------- @property def orientation(self): """ Sets the orientation of the violin(s). If "v" ("h"), the distribution is visualized along the vertical (horizontal). The 'orientation' property is an enumeration that may be specified as: - One of the following enumeration values: ['v', 'h'] Returns ------- Any """ return self["orientation"] @orientation.setter def orientation(self, val): self["orientation"] = val # pointpos # -------- @property def pointpos(self): """ Sets the position of the sample points in relation to the violins. If 0, the sample points are places over the center of the violins. Positive (negative) values correspond to positions to the right (left) for vertical violins and above (below) for horizontal violins. The 'pointpos' property is a number and may be specified as: - An int or float in the interval [-2, 2] Returns ------- int|float """ return self["pointpos"] @pointpos.setter def pointpos(self, val): self["pointpos"] = val # points # ------ @property def points(self): """ If "outliers", only the sample points lying outside the whiskers are shown If "suspectedoutliers", the outlier points are shown and points either less than 4*Q1-3*Q3 or greater than 4*Q3-3*Q1 are highlighted (see `outliercolor`) If "all", all sample points are shown If False, only the violins are shown with no sample points The 'points' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'outliers', 'suspectedoutliers', False] Returns ------- Any """ return self["points"] @points.setter def points(self, val): self["points"] = val # scalegroup # ---------- @property def scalegroup(self): """ If there are multiple violins that should be sized according to to some metric (see `scalemode`), link them by providing a non- empty group id here shared by every trace in the same group. If a violin's `width` is undefined, `scalegroup` will default to the trace's name. In this case, violins with the same names will be linked together The 'scalegroup' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["scalegroup"] @scalegroup.setter def scalegroup(self, val): self["scalegroup"] = val # scalemode # --------- @property def scalemode(self): """ Sets the metric by which the width of each violin is determined."width" means each violin has the same (max) width*count* means the violins are scaled by the number of sample points makingup each violin. The 'scalemode' property is an enumeration that may be specified as: - One of the following enumeration values: ['width', 'count'] Returns ------- Any """ return self["scalemode"] @scalemode.setter def scalemode(self, val): self["scalemode"] = val # selected # -------- @property def selected(self): """ The 'selected' property is an instance of Selected that may be specified as: - An instance of plotly.graph_objs.violin.Selected - A dict of string/value properties that will be passed to the Selected constructor Supported dict properties: marker plotly.graph_objects.violin.selected.Marker instance or dict with compatible properties Returns ------- plotly.graph_objs.violin.Selected """ return self["selected"] @selected.setter def selected(self, val): self["selected"] = val # selectedpoints # -------------- @property def selectedpoints(self): """ Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. The 'selectedpoints' property accepts values of any type Returns ------- Any """ return self["selectedpoints"] @selectedpoints.setter def selectedpoints(self, val): self["selectedpoints"] = val # showlegend # ---------- @property def showlegend(self): """ Determines whether or not an item corresponding to this trace is shown in the legend. The 'showlegend' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showlegend"] @showlegend.setter def showlegend(self, val): self["showlegend"] = val # side # ---- @property def side(self): """ Determines on which side of the position value the density function making up one half of a violin is plotted. Useful when comparing two violin traces under "overlay" mode, where one trace has `side` set to "positive" and the other to "negative". The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['both', 'positive', 'negative'] Returns ------- Any """ return self["side"] @side.setter def side(self, val): self["side"] = val # span # ---- @property def span(self): """ Sets the span in data space for which the density function will be computed. Has an effect only when `spanmode` is set to "manual". The 'span' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'span[0]' property accepts values of any type (1) The 'span[1]' property accepts values of any type Returns ------- list """ return self["span"] @span.setter def span(self, val): self["span"] = val # spanmode # -------- @property def spanmode(self): """ Sets the method by which the span in data space where the density function will be computed. "soft" means the span goes from the sample's minimum value minus two bandwidths to the sample's maximum value plus two bandwidths. "hard" means the span goes from the sample's minimum to its maximum value. For custom span settings, use mode "manual" and fill in the `span` attribute. The 'spanmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['soft', 'hard', 'manual'] Returns ------- Any """ return self["spanmode"] @spanmode.setter def spanmode(self, val): self["spanmode"] = val # stream # ------ @property def stream(self): """ The 'stream' property is an instance of Stream that may be specified as: - An instance of plotly.graph_objs.violin.Stream - A dict of string/value properties that will be passed to the Stream constructor Supported dict properties: maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- plotly.graph_objs.violin.Stream """ return self["stream"] @stream.setter def stream(self, val): self["stream"] = val # text # ---- @property def text(self): """ Sets the text elements associated with each sample value. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["text"] @text.setter def text(self, val): self["text"] = val # textsrc # ------- @property def textsrc(self): """ Sets the source reference on plot.ly for text . The 'textsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["textsrc"] @textsrc.setter def textsrc(self, val): self["textsrc"] = val # uid # --- @property def uid(self): """ Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. The 'uid' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["uid"] @uid.setter def uid(self, val): self["uid"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # unselected # ---------- @property def unselected(self): """ The 'unselected' property is an instance of Unselected that may be specified as: - An instance of plotly.graph_objs.violin.Unselected - A dict of string/value properties that will be passed to the Unselected constructor Supported dict properties: marker plotly.graph_objects.violin.unselected.Marker instance or dict with compatible properties Returns ------- plotly.graph_objs.violin.Unselected """ return self["unselected"] @unselected.setter def unselected(self, val): self["unselected"] = val # visible # ------- @property def visible(self): """ Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). The 'visible' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'legendonly'] Returns ------- Any """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # width # ----- @property def width(self): """ Sets the width of the violin in data coordinates. If 0 (default value) the width is automatically selected based on the positions of other violin traces in the same subplot. The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # x # - @property def x(self): """ Sets the x sample data or coordinates. See overview for more info. The 'x' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["x"] @x.setter def x(self, val): self["x"] = val # x0 # -- @property def x0(self): """ Sets the x coordinate of the box. See overview for more info. The 'x0' property accepts values of any type Returns ------- Any """ return self["x0"] @x0.setter def x0(self, val): self["x0"] = val # xaxis # ----- @property def xaxis(self): """ Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. The 'xaxis' property is an identifier of a particular subplot, of type 'x', that may be specified as the string 'x' optionally followed by an integer >= 1 (e.g. 'x', 'x1', 'x2', 'x3', etc.) Returns ------- str """ return self["xaxis"] @xaxis.setter def xaxis(self, val): self["xaxis"] = val # xsrc # ---- @property def xsrc(self): """ Sets the source reference on plot.ly for x . The 'xsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["xsrc"] @xsrc.setter def xsrc(self, val): self["xsrc"] = val # y # - @property def y(self): """ Sets the y sample data or coordinates. See overview for more info. The 'y' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["y"] @y.setter def y(self, val): self["y"] = val # y0 # -- @property def y0(self): """ Sets the y coordinate of the box. See overview for more info. The 'y0' property accepts values of any type Returns ------- Any """ return self["y0"] @y0.setter def y0(self, val): self["y0"] = val # yaxis # ----- @property def yaxis(self): """ Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. The 'yaxis' property is an identifier of a particular subplot, of type 'y', that may be specified as the string 'y' optionally followed by an integer >= 1 (e.g. 'y', 'y1', 'y2', 'y3', etc.) Returns ------- str """ return self["yaxis"] @yaxis.setter def yaxis(self, val): self["yaxis"] = val # ysrc # ---- @property def ysrc(self): """ Sets the source reference on plot.ly for y . The 'ysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ysrc"] @ysrc.setter def ysrc(self, val): self["ysrc"] = val # type # ---- @property def type(self): return self._props["type"] # property parent name # -------------------- @property def _parent_path_str(self): return "" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ alignmentgroup Set several traces linked to the same position axis or matching axes to the same alignmentgroup. This controls whether bars compute their positional range dependently or independently. bandwidth Sets the bandwidth used to compute the kernel density estimate. By default, the bandwidth is determined by Silverman's rule of thumb. box plotly.graph_objects.violin.Box instance or dict with compatible properties customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . fillcolor Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.violin.Hoverlabel instance or dict with compatible properties hoveron Do the hover effects highlight individual violins or sample points or the kernel density estimate or any combination of them? hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . jitter Sets the amount of jitter in the sample points drawn. If 0, the sample points align along the distribution axis. If 1, the sample points are drawn in a random jitter of width equal to the width of the violins. legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.violin.Line instance or dict with compatible properties marker plotly.graph_objects.violin.Marker instance or dict with compatible properties meanline plotly.graph_objects.violin.Meanline instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. For violin traces, the name will also be used for the position coordinate, if `x` and `x0` (`y` and `y0` if horizontal) are missing and the position axis is categorical. Note that the trace name is also used as a default value for attribute `scalegroup` (please see its description for details). offsetgroup Set several traces linked to the same position axis or matching axes to the same offsetgroup where bars of the same position coordinate will line up. opacity Sets the opacity of the trace. orientation Sets the orientation of the violin(s). If "v" ("h"), the distribution is visualized along the vertical (horizontal). pointpos Sets the position of the sample points in relation to the violins. If 0, the sample points are places over the center of the violins. Positive (negative) values correspond to positions to the right (left) for vertical violins and above (below) for horizontal violins. points If "outliers", only the sample points lying outside the whiskers are shown If "suspectedoutliers", the outlier points are shown and points either less than 4*Q1-3*Q3 or greater than 4*Q3-3*Q1 are highlighted (see `outliercolor`) If "all", all sample points are shown If False, only the violins are shown with no sample points scalegroup If there are multiple violins that should be sized according to to some metric (see `scalemode`), link them by providing a non-empty group id here shared by every trace in the same group. If a violin's `width` is undefined, `scalegroup` will default to the trace's name. In this case, violins with the same names will be linked together scalemode Sets the metric by which the width of each violin is determined."width" means each violin has the same (max) width*count* means the violins are scaled by the number of sample points makingup each violin. selected plotly.graph_objects.violin.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. side Determines on which side of the position value the density function making up one half of a violin is plotted. Useful when comparing two violin traces under "overlay" mode, where one trace has `side` set to "positive" and the other to "negative". span Sets the span in data space for which the density function will be computed. Has an effect only when `spanmode` is set to "manual". spanmode Sets the method by which the span in data space where the density function will be computed. "soft" means the span goes from the sample's minimum value minus two bandwidths to the sample's maximum value plus two bandwidths. "hard" means the span goes from the sample's minimum to its maximum value. For custom span settings, use mode "manual" and fill in the `span` attribute. stream plotly.graph_objects.violin.Stream instance or dict with compatible properties text Sets the text elements associated with each sample value. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.violin.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). width Sets the width of the violin in data coordinates. If 0 (default value) the width is automatically selected based on the positions of other violin traces in the same subplot. x Sets the x sample data or coordinates. See overview for more info. x0 Sets the x coordinate of the box. See overview for more info. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xsrc Sets the source reference on plot.ly for x . y Sets the y sample data or coordinates. See overview for more info. y0 Sets the y coordinate of the box. See overview for more info. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ysrc Sets the source reference on plot.ly for y . """ def __init__( self, arg=None, alignmentgroup=None, bandwidth=None, box=None, customdata=None, customdatasrc=None, fillcolor=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hoveron=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, jitter=None, legendgroup=None, line=None, marker=None, meanline=None, meta=None, metasrc=None, name=None, offsetgroup=None, opacity=None, orientation=None, pointpos=None, points=None, scalegroup=None, scalemode=None, selected=None, selectedpoints=None, showlegend=None, side=None, span=None, spanmode=None, stream=None, text=None, textsrc=None, uid=None, uirevision=None, unselected=None, visible=None, width=None, x=None, x0=None, xaxis=None, xsrc=None, y=None, y0=None, yaxis=None, ysrc=None, **kwargs ): """ Construct a new Violin object In vertical (horizontal) violin plots, statistics are computed using `y` (`x`) values. By supplying an `x` (`y`) array, one violin per distinct x (y) value is drawn If no `x` (`y`) list is provided, a single violin is drawn. That violin position is then positioned with with `name` or with `x0` (`y0`) if provided. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.Violin alignmentgroup Set several traces linked to the same position axis or matching axes to the same alignmentgroup. This controls whether bars compute their positional range dependently or independently. bandwidth Sets the bandwidth used to compute the kernel density estimate. By default, the bandwidth is determined by Silverman's rule of thumb. box plotly.graph_objects.violin.Box instance or dict with compatible properties customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . fillcolor Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.violin.Hoverlabel instance or dict with compatible properties hoveron Do the hover effects highlight individual violins or sample points or the kernel density estimate or any combination of them? hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . jitter Sets the amount of jitter in the sample points drawn. If 0, the sample points align along the distribution axis. If 1, the sample points are drawn in a random jitter of width equal to the width of the violins. legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.violin.Line instance or dict with compatible properties marker plotly.graph_objects.violin.Marker instance or dict with compatible properties meanline plotly.graph_objects.violin.Meanline instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. For violin traces, the name will also be used for the position coordinate, if `x` and `x0` (`y` and `y0` if horizontal) are missing and the position axis is categorical. Note that the trace name is also used as a default value for attribute `scalegroup` (please see its description for details). offsetgroup Set several traces linked to the same position axis or matching axes to the same offsetgroup where bars of the same position coordinate will line up. opacity Sets the opacity of the trace. orientation Sets the orientation of the violin(s). If "v" ("h"), the distribution is visualized along the vertical (horizontal). pointpos Sets the position of the sample points in relation to the violins. If 0, the sample points are places over the center of the violins. Positive (negative) values correspond to positions to the right (left) for vertical violins and above (below) for horizontal violins. points If "outliers", only the sample points lying outside the whiskers are shown If "suspectedoutliers", the outlier points are shown and points either less than 4*Q1-3*Q3 or greater than 4*Q3-3*Q1 are highlighted (see `outliercolor`) If "all", all sample points are shown If False, only the violins are shown with no sample points scalegroup If there are multiple violins that should be sized according to to some metric (see `scalemode`), link them by providing a non-empty group id here shared by every trace in the same group. If a violin's `width` is undefined, `scalegroup` will default to the trace's name. In this case, violins with the same names will be linked together scalemode Sets the metric by which the width of each violin is determined."width" means each violin has the same (max) width*count* means the violins are scaled by the number of sample points makingup each violin. selected plotly.graph_objects.violin.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. side Determines on which side of the position value the density function making up one half of a violin is plotted. Useful when comparing two violin traces under "overlay" mode, where one trace has `side` set to "positive" and the other to "negative". span Sets the span in data space for which the density function will be computed. Has an effect only when `spanmode` is set to "manual". spanmode Sets the method by which the span in data space where the density function will be computed. "soft" means the span goes from the sample's minimum value minus two bandwidths to the sample's maximum value plus two bandwidths. "hard" means the span goes from the sample's minimum to its maximum value. For custom span settings, use mode "manual" and fill in the `span` attribute. stream plotly.graph_objects.violin.Stream instance or dict with compatible properties text Sets the text elements associated with each sample value. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.violin.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). width Sets the width of the violin in data coordinates. If 0 (default value) the width is automatically selected based on the positions of other violin traces in the same subplot. x Sets the x sample data or coordinates. See overview for more info. x0 Sets the x coordinate of the box. See overview for more info. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xsrc Sets the source reference on plot.ly for x . y Sets the y sample data or coordinates. See overview for more info. y0 Sets the y coordinate of the box. See overview for more info. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ysrc Sets the source reference on plot.ly for y . Returns ------- Violin """ super(Violin, self).__init__("violin") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.Violin constructor must be a dict or an instance of plotly.graph_objs.Violin""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators import violin as v_violin # Initialize validators # --------------------- self._validators["alignmentgroup"] = v_violin.AlignmentgroupValidator() self._validators["bandwidth"] = v_violin.BandwidthValidator() self._validators["box"] = v_violin.BoxValidator() self._validators["customdata"] = v_violin.CustomdataValidator() self._validators["customdatasrc"] = v_violin.CustomdatasrcValidator() self._validators["fillcolor"] = v_violin.FillcolorValidator() self._validators["hoverinfo"] = v_violin.HoverinfoValidator() self._validators["hoverinfosrc"] = v_violin.HoverinfosrcValidator() self._validators["hoverlabel"] = v_violin.HoverlabelValidator() self._validators["hoveron"] = v_violin.HoveronValidator() self._validators["hovertemplate"] = v_violin.HovertemplateValidator() self._validators["hovertemplatesrc"] = v_violin.HovertemplatesrcValidator() self._validators["hovertext"] = v_violin.HovertextValidator() self._validators["hovertextsrc"] = v_violin.HovertextsrcValidator() self._validators["ids"] = v_violin.IdsValidator() self._validators["idssrc"] = v_violin.IdssrcValidator() self._validators["jitter"] = v_violin.JitterValidator() self._validators["legendgroup"] = v_violin.LegendgroupValidator() self._validators["line"] = v_violin.LineValidator() self._validators["marker"] = v_violin.MarkerValidator() self._validators["meanline"] = v_violin.MeanlineValidator() self._validators["meta"] = v_violin.MetaValidator() self._validators["metasrc"] = v_violin.MetasrcValidator() self._validators["name"] = v_violin.NameValidator() self._validators["offsetgroup"] = v_violin.OffsetgroupValidator() self._validators["opacity"] = v_violin.OpacityValidator() self._validators["orientation"] = v_violin.OrientationValidator() self._validators["pointpos"] = v_violin.PointposValidator() self._validators["points"] = v_violin.PointsValidator() self._validators["scalegroup"] = v_violin.ScalegroupValidator() self._validators["scalemode"] = v_violin.ScalemodeValidator() self._validators["selected"] = v_violin.SelectedValidator() self._validators["selectedpoints"] = v_violin.SelectedpointsValidator() self._validators["showlegend"] = v_violin.ShowlegendValidator() self._validators["side"] = v_violin.SideValidator() self._validators["span"] = v_violin.SpanValidator() self._validators["spanmode"] = v_violin.SpanmodeValidator() self._validators["stream"] = v_violin.StreamValidator() self._validators["text"] = v_violin.TextValidator() self._validators["textsrc"] = v_violin.TextsrcValidator() self._validators["uid"] = v_violin.UidValidator() self._validators["uirevision"] = v_violin.UirevisionValidator() self._validators["unselected"] = v_violin.UnselectedValidator() self._validators["visible"] = v_violin.VisibleValidator() self._validators["width"] = v_violin.WidthValidator() self._validators["x"] = v_violin.XValidator() self._validators["x0"] = v_violin.X0Validator() self._validators["xaxis"] = v_violin.XAxisValidator() self._validators["xsrc"] = v_violin.XsrcValidator() self._validators["y"] = v_violin.YValidator() self._validators["y0"] = v_violin.Y0Validator() self._validators["yaxis"] = v_violin.YAxisValidator() self._validators["ysrc"] = v_violin.YsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("alignmentgroup", None) self["alignmentgroup"] = alignmentgroup if alignmentgroup is not None else _v _v = arg.pop("bandwidth", None) self["bandwidth"] = bandwidth if bandwidth is not None else _v _v = arg.pop("box", None) self["box"] = box if box is not None else _v _v = arg.pop("customdata", None) self["customdata"] = customdata if customdata is not None else _v _v = arg.pop("customdatasrc", None) self["customdatasrc"] = customdatasrc if customdatasrc is not None else _v _v = arg.pop("fillcolor", None) self["fillcolor"] = fillcolor if fillcolor is not None else _v _v = arg.pop("hoverinfo", None) self["hoverinfo"] = hoverinfo if hoverinfo is not None else _v _v = arg.pop("hoverinfosrc", None) self["hoverinfosrc"] = hoverinfosrc if hoverinfosrc is not None else _v _v = arg.pop("hoverlabel", None) self["hoverlabel"] = hoverlabel if hoverlabel is not None else _v _v = arg.pop("hoveron", None) self["hoveron"] = hoveron if hoveron is not None else _v _v = arg.pop("hovertemplate", None) self["hovertemplate"] = hovertemplate if hovertemplate is not None else _v _v = arg.pop("hovertemplatesrc", None) self["hovertemplatesrc"] = ( hovertemplatesrc if hovertemplatesrc is not None else _v ) _v = arg.pop("hovertext", None) self["hovertext"] = hovertext if hovertext is not None else _v _v = arg.pop("hovertextsrc", None) self["hovertextsrc"] = hovertextsrc if hovertextsrc is not None else _v _v = arg.pop("ids", None) self["ids"] = ids if ids is not None else _v _v = arg.pop("idssrc", None) self["idssrc"] = idssrc if idssrc is not None else _v _v = arg.pop("jitter", None) self["jitter"] = jitter if jitter is not None else _v _v = arg.pop("legendgroup", None) self["legendgroup"] = legendgroup if legendgroup is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v _v = arg.pop("meanline", None) self["meanline"] = meanline if meanline is not None else _v _v = arg.pop("meta", None) self["meta"] = meta if meta is not None else _v _v = arg.pop("metasrc", None) self["metasrc"] = metasrc if metasrc is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("offsetgroup", None) self["offsetgroup"] = offsetgroup if offsetgroup is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("orientation", None) self["orientation"] = orientation if orientation is not None else _v _v = arg.pop("pointpos", None) self["pointpos"] = pointpos if pointpos is not None else _v _v = arg.pop("points", None) self["points"] = points if points is not None else _v _v = arg.pop("scalegroup", None) self["scalegroup"] = scalegroup if scalegroup is not None else _v _v = arg.pop("scalemode", None) self["scalemode"] = scalemode if scalemode is not None else _v _v = arg.pop("selected", None) self["selected"] = selected if selected is not None else _v _v = arg.pop("selectedpoints", None) self["selectedpoints"] = selectedpoints if selectedpoints is not None else _v _v = arg.pop("showlegend", None) self["showlegend"] = showlegend if showlegend is not None else _v _v = arg.pop("side", None) self["side"] = side if side is not None else _v _v = arg.pop("span", None) self["span"] = span if span is not None else _v _v = arg.pop("spanmode", None) self["spanmode"] = spanmode if spanmode is not None else _v _v = arg.pop("stream", None) self["stream"] = stream if stream is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v _v = arg.pop("textsrc", None) self["textsrc"] = textsrc if textsrc is not None else _v _v = arg.pop("uid", None) self["uid"] = uid if uid is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("unselected", None) self["unselected"] = unselected if unselected is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("x0", None) self["x0"] = x0 if x0 is not None else _v _v = arg.pop("xaxis", None) self["xaxis"] = xaxis if xaxis is not None else _v _v = arg.pop("xsrc", None) self["xsrc"] = xsrc if xsrc is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("y0", None) self["y0"] = y0 if y0 is not None else _v _v = arg.pop("yaxis", None) self["yaxis"] = yaxis if yaxis is not None else _v _v = arg.pop("ysrc", None) self["ysrc"] = ysrc if ysrc is not None else _v # Read-only literals # ------------------ from _plotly_utils.basevalidators import LiteralValidator self._props["type"] = "violin" self._validators["type"] = LiteralValidator( plotly_name="type", parent_name="violin", val="violin" ) arg.pop("type", None) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceType as _BaseTraceType import copy as _copy class Treemap(_BaseTraceType): # branchvalues # ------------ @property def branchvalues(self): """ Determines how the items in `values` are summed. When set to "total", items in `values` are taken to be value of all its descendants. When set to "remainder", items in `values` corresponding to the root and the branches sectors are taken to be the extra part not part of the sum of the values at their leaves. The 'branchvalues' property is an enumeration that may be specified as: - One of the following enumeration values: ['remainder', 'total'] Returns ------- Any """ return self["branchvalues"] @branchvalues.setter def branchvalues(self, val): self["branchvalues"] = val # count # ----- @property def count(self): """ Determines default for `values` when it is not provided, by inferring a 1 for each of the "leaves" and/or "branches", otherwise 0. The 'count' property is a flaglist and may be specified as a string containing: - Any combination of ['branches', 'leaves'] joined with '+' characters (e.g. 'branches+leaves') Returns ------- Any """ return self["count"] @count.setter def count(self, val): self["count"] = val # customdata # ---------- @property def customdata(self): """ Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements The 'customdata' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["customdata"] @customdata.setter def customdata(self, val): self["customdata"] = val # customdatasrc # ------------- @property def customdatasrc(self): """ Sets the source reference on plot.ly for customdata . The 'customdatasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["customdatasrc"] @customdatasrc.setter def customdatasrc(self, val): self["customdatasrc"] = val # domain # ------ @property def domain(self): """ The 'domain' property is an instance of Domain that may be specified as: - An instance of plotly.graph_objs.treemap.Domain - A dict of string/value properties that will be passed to the Domain constructor Supported dict properties: column If there is a layout grid, use the domain for this column in the grid for this treemap trace . row If there is a layout grid, use the domain for this row in the grid for this treemap trace . x Sets the horizontal domain of this treemap trace (in plot fraction). y Sets the vertical domain of this treemap trace (in plot fraction). Returns ------- plotly.graph_objs.treemap.Domain """ return self["domain"] @domain.setter def domain(self, val): self["domain"] = val # hoverinfo # --------- @property def hoverinfo(self): """ Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. The 'hoverinfo' property is a flaglist and may be specified as a string containing: - Any combination of ['label', 'text', 'value', 'name', 'current path', 'percent root', 'percent entry', 'percent parent'] joined with '+' characters (e.g. 'label+text') OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') - A list or array of the above Returns ------- Any|numpy.ndarray """ return self["hoverinfo"] @hoverinfo.setter def hoverinfo(self, val): self["hoverinfo"] = val # hoverinfosrc # ------------ @property def hoverinfosrc(self): """ Sets the source reference on plot.ly for hoverinfo . The 'hoverinfosrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hoverinfosrc"] @hoverinfosrc.setter def hoverinfosrc(self, val): self["hoverinfosrc"] = val # hoverlabel # ---------- @property def hoverlabel(self): """ The 'hoverlabel' property is an instance of Hoverlabel that may be specified as: - An instance of plotly.graph_objs.treemap.Hoverlabel - A dict of string/value properties that will be passed to the Hoverlabel constructor Supported dict properties: align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- plotly.graph_objs.treemap.Hoverlabel """ return self["hoverlabel"] @hoverlabel.setter def hoverlabel(self, val): self["hoverlabel"] = val # hovertemplate # ------------- @property def hovertemplate(self): """ Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event- data. Additionally, every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. variables `currentPath`, `root`, `entry`, `percentRoot`, `percentEntry` and `percentParent`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. The 'hovertemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertemplate"] @hovertemplate.setter def hovertemplate(self, val): self["hovertemplate"] = val # hovertemplatesrc # ---------------- @property def hovertemplatesrc(self): """ Sets the source reference on plot.ly for hovertemplate . The 'hovertemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertemplatesrc"] @hovertemplatesrc.setter def hovertemplatesrc(self, val): self["hovertemplatesrc"] = val # hovertext # --------- @property def hovertext(self): """ Sets hover text elements associated with each sector. If a single string, the same string appears for all data points. If an array of string, the items are mapped in order of this trace's sectors. To be seen, trace `hoverinfo` must contain a "text" flag. The 'hovertext' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertext"] @hovertext.setter def hovertext(self, val): self["hovertext"] = val # hovertextsrc # ------------ @property def hovertextsrc(self): """ Sets the source reference on plot.ly for hovertext . The 'hovertextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertextsrc"] @hovertextsrc.setter def hovertextsrc(self, val): self["hovertextsrc"] = val # ids # --- @property def ids(self): """ Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. The 'ids' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ids"] @ids.setter def ids(self, val): self["ids"] = val # idssrc # ------ @property def idssrc(self): """ Sets the source reference on plot.ly for ids . The 'idssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["idssrc"] @idssrc.setter def idssrc(self, val): self["idssrc"] = val # insidetextfont # -------------- @property def insidetextfont(self): """ Sets the font used for `textinfo` lying inside the sector. The 'insidetextfont' property is an instance of Insidetextfont that may be specified as: - An instance of plotly.graph_objs.treemap.Insidetextfont - A dict of string/value properties that will be passed to the Insidetextfont constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.treemap.Insidetextfont """ return self["insidetextfont"] @insidetextfont.setter def insidetextfont(self, val): self["insidetextfont"] = val # labels # ------ @property def labels(self): """ Sets the labels of each of the sectors. The 'labels' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["labels"] @labels.setter def labels(self, val): self["labels"] = val # labelssrc # --------- @property def labelssrc(self): """ Sets the source reference on plot.ly for labels . The 'labelssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["labelssrc"] @labelssrc.setter def labelssrc(self, val): self["labelssrc"] = val # level # ----- @property def level(self): """ Sets the level from which this trace hierarchy is rendered. Set `level` to `''` to start from the root node in the hierarchy. Must be an "id" if `ids` is filled in, otherwise plotly attempts to find a matching item in `labels`. The 'level' property accepts values of any type Returns ------- Any """ return self["level"] @level.setter def level(self, val): self["level"] = val # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.treemap.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if colorsis set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here colors) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if colorsis set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if colorsis set to a numerical array. Value should have the same units as colors and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if colorsis set to a numerical array. Value should have the same units as colors. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if colorsis set to a numerical array. Value should have the same units as colors and if set, `marker.cmax` must be set as well. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.treemap.marker.ColorBar instance or dict with compatible properties colors Sets the color of each sector of this trace. If not specified, the default trace color set is used to pick the sector colors. colorscale Sets the colorscale. Has an effect only if colorsis set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorssrc Sets the source reference on plot.ly for colors . depthfade Determines if the sector colors are faded towards the background from the leaves up to the headers. This option is unavailable when a `colorscale` is present, defaults to false when `marker.colors` is set, but otherwise defaults to true. When set to "reversed", the fading direction is inverted, that is the top elements within hierarchy are drawn with fully saturated colors while the leaves are faded towards the background color. line plotly.graph_objects.treemap.marker.Line instance or dict with compatible properties pad plotly.graph_objects.treemap.marker.Pad instance or dict with compatible properties reversescale Reverses the color mapping if true. Has an effect only if colorsis set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if colorsis set to a numerical array. Returns ------- plotly.graph_objs.treemap.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # maxdepth # -------- @property def maxdepth(self): """ Sets the number of rendered sectors from any given `level`. Set `maxdepth` to "-1" to render all the levels in the hierarchy. The 'maxdepth' property is a integer and may be specified as: - An int (or float that will be cast to an int) Returns ------- int """ return self["maxdepth"] @maxdepth.setter def maxdepth(self, val): self["maxdepth"] = val # meta # ---- @property def meta(self): """ Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. The 'meta' property accepts values of any type Returns ------- Any|numpy.ndarray """ return self["meta"] @meta.setter def meta(self, val): self["meta"] = val # metasrc # ------- @property def metasrc(self): """ Sets the source reference on plot.ly for meta . The 'metasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["metasrc"] @metasrc.setter def metasrc(self, val): self["metasrc"] = val # name # ---- @property def name(self): """ Sets the trace name. The trace name appear as the legend item and on hover. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the trace. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # outsidetextfont # --------------- @property def outsidetextfont(self): """ Sets the font used for `textinfo` lying outside the sector. The 'outsidetextfont' property is an instance of Outsidetextfont that may be specified as: - An instance of plotly.graph_objs.treemap.Outsidetextfont - A dict of string/value properties that will be passed to the Outsidetextfont constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.treemap.Outsidetextfont """ return self["outsidetextfont"] @outsidetextfont.setter def outsidetextfont(self, val): self["outsidetextfont"] = val # parents # ------- @property def parents(self): """ Sets the parent sectors for each of the sectors. Empty string items '' are understood to reference the root node in the hierarchy. If `ids` is filled, `parents` items are understood to be "ids" themselves. When `ids` is not set, plotly attempts to find matching items in `labels`, but beware they must be unique. The 'parents' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["parents"] @parents.setter def parents(self, val): self["parents"] = val # parentssrc # ---------- @property def parentssrc(self): """ Sets the source reference on plot.ly for parents . The 'parentssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["parentssrc"] @parentssrc.setter def parentssrc(self, val): self["parentssrc"] = val # pathbar # ------- @property def pathbar(self): """ The 'pathbar' property is an instance of Pathbar that may be specified as: - An instance of plotly.graph_objs.treemap.Pathbar - A dict of string/value properties that will be passed to the Pathbar constructor Supported dict properties: edgeshape Determines which shape is used for edges between `barpath` labels. side Determines on which side of the the treemap the `pathbar` should be presented. textfont Sets the font used inside `pathbar`. thickness Sets the thickness of `pathbar` (in px). If not specified the `pathbar.textfont.size` is used with 3 pixles extra padding on each side. visible Determines if the path bar is drawn i.e. outside the trace `domain` and with one pixel gap. Returns ------- plotly.graph_objs.treemap.Pathbar """ return self["pathbar"] @pathbar.setter def pathbar(self, val): self["pathbar"] = val # stream # ------ @property def stream(self): """ The 'stream' property is an instance of Stream that may be specified as: - An instance of plotly.graph_objs.treemap.Stream - A dict of string/value properties that will be passed to the Stream constructor Supported dict properties: maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- plotly.graph_objs.treemap.Stream """ return self["stream"] @stream.setter def stream(self, val): self["stream"] = val # text # ---- @property def text(self): """ Sets text elements associated with each sector. If trace `textinfo` contains a "text" flag, these elements will be seen on the chart. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. The 'text' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["text"] @text.setter def text(self, val): self["text"] = val # textfont # -------- @property def textfont(self): """ Sets the font used for `textinfo`. The 'textfont' property is an instance of Textfont that may be specified as: - An instance of plotly.graph_objs.treemap.Textfont - A dict of string/value properties that will be passed to the Textfont constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.treemap.Textfont """ return self["textfont"] @textfont.setter def textfont(self, val): self["textfont"] = val # textinfo # -------- @property def textinfo(self): """ Determines which trace information appear on the graph. The 'textinfo' property is a flaglist and may be specified as a string containing: - Any combination of ['label', 'text', 'value', 'current path', 'percent root', 'percent entry', 'percent parent'] joined with '+' characters (e.g. 'label+text') OR exactly one of ['none'] (e.g. 'none') Returns ------- Any """ return self["textinfo"] @textinfo.setter def textinfo(self, val): self["textinfo"] = val # textposition # ------------ @property def textposition(self): """ Sets the positions of the `text` elements. The 'textposition' property is an enumeration that may be specified as: - One of the following enumeration values: ['top left', 'top center', 'top right', 'middle left', 'middle center', 'middle right', 'bottom left', 'bottom center', 'bottom right'] Returns ------- Any """ return self["textposition"] @textposition.setter def textposition(self, val): self["textposition"] = val # textsrc # ------- @property def textsrc(self): """ Sets the source reference on plot.ly for text . The 'textsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["textsrc"] @textsrc.setter def textsrc(self, val): self["textsrc"] = val # texttemplate # ------------ @property def texttemplate(self): """ Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `currentPath`, `root`, `entry`, `percentRoot`, `percentEntry`, `percentParent`, `label` and `value`. The 'texttemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["texttemplate"] @texttemplate.setter def texttemplate(self, val): self["texttemplate"] = val # texttemplatesrc # --------------- @property def texttemplatesrc(self): """ Sets the source reference on plot.ly for texttemplate . The 'texttemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["texttemplatesrc"] @texttemplatesrc.setter def texttemplatesrc(self, val): self["texttemplatesrc"] = val # tiling # ------ @property def tiling(self): """ The 'tiling' property is an instance of Tiling that may be specified as: - An instance of plotly.graph_objs.treemap.Tiling - A dict of string/value properties that will be passed to the Tiling constructor Supported dict properties: flip Determines if the positions obtained from solver are flipped on each axis. packing Determines d3 treemap solver. For more info please refer to https://github.com/d3/d3-hierarchy#treemap- tiling pad Sets the inner padding (in px). squarifyratio When using "squarify" `packing` algorithm, according to https://github.com/d3/d3-hierarchy /blob/master/README.md#squarify_ratio this option specifies the desired aspect ratio of the generated rectangles. The ratio must be specified as a number greater than or equal to one. Note that the orientation of the generated rectangles (tall or wide) is not implied by the ratio; for example, a ratio of two will attempt to produce a mixture of rectangles whose width:height ratio is either 2:1 or 1:2. When using "squarify", unlike d3 which uses the Golden Ratio i.e. 1.618034, Plotly applies 1 to increase squares in treemap layouts. Returns ------- plotly.graph_objs.treemap.Tiling """ return self["tiling"] @tiling.setter def tiling(self, val): self["tiling"] = val # uid # --- @property def uid(self): """ Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. The 'uid' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["uid"] @uid.setter def uid(self, val): self["uid"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # values # ------ @property def values(self): """ Sets the values associated with each of the sectors. Use with `branchvalues` to determine how the values are summed. The 'values' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["values"] @values.setter def values(self, val): self["values"] = val # valuessrc # --------- @property def valuessrc(self): """ Sets the source reference on plot.ly for values . The 'valuessrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["valuessrc"] @valuessrc.setter def valuessrc(self, val): self["valuessrc"] = val # visible # ------- @property def visible(self): """ Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). The 'visible' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'legendonly'] Returns ------- Any """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # type # ---- @property def type(self): return self._props["type"] # property parent name # -------------------- @property def _parent_path_str(self): return "" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ branchvalues Determines how the items in `values` are summed. When set to "total", items in `values` are taken to be value of all its descendants. When set to "remainder", items in `values` corresponding to the root and the branches sectors are taken to be the extra part not part of the sum of the values at their leaves. count Determines default for `values` when it is not provided, by inferring a 1 for each of the "leaves" and/or "branches", otherwise 0. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . domain plotly.graph_objects.treemap.Domain instance or dict with compatible properties hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.treemap.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `currentPath`, `root`, `entry`, `percentRoot`, `percentEntry` and `percentParent`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each sector. If a single string, the same string appears for all data points. If an array of string, the items are mapped in order of this trace's sectors. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . insidetextfont Sets the font used for `textinfo` lying inside the sector. labels Sets the labels of each of the sectors. labelssrc Sets the source reference on plot.ly for labels . level Sets the level from which this trace hierarchy is rendered. Set `level` to `''` to start from the root node in the hierarchy. Must be an "id" if `ids` is filled in, otherwise plotly attempts to find a matching item in `labels`. marker plotly.graph_objects.treemap.Marker instance or dict with compatible properties maxdepth Sets the number of rendered sectors from any given `level`. Set `maxdepth` to "-1" to render all the levels in the hierarchy. meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. outsidetextfont Sets the font used for `textinfo` lying outside the sector. parents Sets the parent sectors for each of the sectors. Empty string items '' are understood to reference the root node in the hierarchy. If `ids` is filled, `parents` items are understood to be "ids" themselves. When `ids` is not set, plotly attempts to find matching items in `labels`, but beware they must be unique. parentssrc Sets the source reference on plot.ly for parents . pathbar plotly.graph_objects.treemap.Pathbar instance or dict with compatible properties stream plotly.graph_objects.treemap.Stream instance or dict with compatible properties text Sets text elements associated with each sector. If trace `textinfo` contains a "text" flag, these elements will be seen on the chart. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the font used for `textinfo`. textinfo Determines which trace information appear on the graph. textposition Sets the positions of the `text` elements. textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `currentPath`, `root`, `entry`, `percentRoot`, `percentEntry`, `percentParent`, `label` and `value`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . tiling plotly.graph_objects.treemap.Tiling instance or dict with compatible properties uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. values Sets the values associated with each of the sectors. Use with `branchvalues` to determine how the values are summed. valuessrc Sets the source reference on plot.ly for values . visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). """ def __init__( self, arg=None, branchvalues=None, count=None, customdata=None, customdatasrc=None, domain=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, insidetextfont=None, labels=None, labelssrc=None, level=None, marker=None, maxdepth=None, meta=None, metasrc=None, name=None, opacity=None, outsidetextfont=None, parents=None, parentssrc=None, pathbar=None, stream=None, text=None, textfont=None, textinfo=None, textposition=None, textsrc=None, texttemplate=None, texttemplatesrc=None, tiling=None, uid=None, uirevision=None, values=None, valuessrc=None, visible=None, **kwargs ): """ Construct a new Treemap object Visualize hierarchal data from leaves (and/or outer branches) towards root with rectangles. The treemap sectors are determined by the entries in "labels" or "ids" and in "parents". Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.Treemap branchvalues Determines how the items in `values` are summed. When set to "total", items in `values` are taken to be value of all its descendants. When set to "remainder", items in `values` corresponding to the root and the branches sectors are taken to be the extra part not part of the sum of the values at their leaves. count Determines default for `values` when it is not provided, by inferring a 1 for each of the "leaves" and/or "branches", otherwise 0. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . domain plotly.graph_objects.treemap.Domain instance or dict with compatible properties hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.treemap.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `currentPath`, `root`, `entry`, `percentRoot`, `percentEntry` and `percentParent`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each sector. If a single string, the same string appears for all data points. If an array of string, the items are mapped in order of this trace's sectors. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . insidetextfont Sets the font used for `textinfo` lying inside the sector. labels Sets the labels of each of the sectors. labelssrc Sets the source reference on plot.ly for labels . level Sets the level from which this trace hierarchy is rendered. Set `level` to `''` to start from the root node in the hierarchy. Must be an "id" if `ids` is filled in, otherwise plotly attempts to find a matching item in `labels`. marker plotly.graph_objects.treemap.Marker instance or dict with compatible properties maxdepth Sets the number of rendered sectors from any given `level`. Set `maxdepth` to "-1" to render all the levels in the hierarchy. meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. outsidetextfont Sets the font used for `textinfo` lying outside the sector. parents Sets the parent sectors for each of the sectors. Empty string items '' are understood to reference the root node in the hierarchy. If `ids` is filled, `parents` items are understood to be "ids" themselves. When `ids` is not set, plotly attempts to find matching items in `labels`, but beware they must be unique. parentssrc Sets the source reference on plot.ly for parents . pathbar plotly.graph_objects.treemap.Pathbar instance or dict with compatible properties stream plotly.graph_objects.treemap.Stream instance or dict with compatible properties text Sets text elements associated with each sector. If trace `textinfo` contains a "text" flag, these elements will be seen on the chart. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the font used for `textinfo`. textinfo Determines which trace information appear on the graph. textposition Sets the positions of the `text` elements. textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `currentPath`, `root`, `entry`, `percentRoot`, `percentEntry`, `percentParent`, `label` and `value`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . tiling plotly.graph_objects.treemap.Tiling instance or dict with compatible properties uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. values Sets the values associated with each of the sectors. Use with `branchvalues` to determine how the values are summed. valuessrc Sets the source reference on plot.ly for values . visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). Returns ------- Treemap """ super(Treemap, self).__init__("treemap") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.Treemap constructor must be a dict or an instance of plotly.graph_objs.Treemap""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators import treemap as v_treemap # Initialize validators # --------------------- self._validators["branchvalues"] = v_treemap.BranchvaluesValidator() self._validators["count"] = v_treemap.CountValidator() self._validators["customdata"] = v_treemap.CustomdataValidator() self._validators["customdatasrc"] = v_treemap.CustomdatasrcValidator() self._validators["domain"] = v_treemap.DomainValidator() self._validators["hoverinfo"] = v_treemap.HoverinfoValidator() self._validators["hoverinfosrc"] = v_treemap.HoverinfosrcValidator() self._validators["hoverlabel"] = v_treemap.HoverlabelValidator() self._validators["hovertemplate"] = v_treemap.HovertemplateValidator() self._validators["hovertemplatesrc"] = v_treemap.HovertemplatesrcValidator() self._validators["hovertext"] = v_treemap.HovertextValidator() self._validators["hovertextsrc"] = v_treemap.HovertextsrcValidator() self._validators["ids"] = v_treemap.IdsValidator() self._validators["idssrc"] = v_treemap.IdssrcValidator() self._validators["insidetextfont"] = v_treemap.InsidetextfontValidator() self._validators["labels"] = v_treemap.LabelsValidator() self._validators["labelssrc"] = v_treemap.LabelssrcValidator() self._validators["level"] = v_treemap.LevelValidator() self._validators["marker"] = v_treemap.MarkerValidator() self._validators["maxdepth"] = v_treemap.MaxdepthValidator() self._validators["meta"] = v_treemap.MetaValidator() self._validators["metasrc"] = v_treemap.MetasrcValidator() self._validators["name"] = v_treemap.NameValidator() self._validators["opacity"] = v_treemap.OpacityValidator() self._validators["outsidetextfont"] = v_treemap.OutsidetextfontValidator() self._validators["parents"] = v_treemap.ParentsValidator() self._validators["parentssrc"] = v_treemap.ParentssrcValidator() self._validators["pathbar"] = v_treemap.PathbarValidator() self._validators["stream"] = v_treemap.StreamValidator() self._validators["text"] = v_treemap.TextValidator() self._validators["textfont"] = v_treemap.TextfontValidator() self._validators["textinfo"] = v_treemap.TextinfoValidator() self._validators["textposition"] = v_treemap.TextpositionValidator() self._validators["textsrc"] = v_treemap.TextsrcValidator() self._validators["texttemplate"] = v_treemap.TexttemplateValidator() self._validators["texttemplatesrc"] = v_treemap.TexttemplatesrcValidator() self._validators["tiling"] = v_treemap.TilingValidator() self._validators["uid"] = v_treemap.UidValidator() self._validators["uirevision"] = v_treemap.UirevisionValidator() self._validators["values"] = v_treemap.ValuesValidator() self._validators["valuessrc"] = v_treemap.ValuessrcValidator() self._validators["visible"] = v_treemap.VisibleValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("branchvalues", None) self["branchvalues"] = branchvalues if branchvalues is not None else _v _v = arg.pop("count", None) self["count"] = count if count is not None else _v _v = arg.pop("customdata", None) self["customdata"] = customdata if customdata is not None else _v _v = arg.pop("customdatasrc", None) self["customdatasrc"] = customdatasrc if customdatasrc is not None else _v _v = arg.pop("domain", None) self["domain"] = domain if domain is not None else _v _v = arg.pop("hoverinfo", None) self["hoverinfo"] = hoverinfo if hoverinfo is not None else _v _v = arg.pop("hoverinfosrc", None) self["hoverinfosrc"] = hoverinfosrc if hoverinfosrc is not None else _v _v = arg.pop("hoverlabel", None) self["hoverlabel"] = hoverlabel if hoverlabel is not None else _v _v = arg.pop("hovertemplate", None) self["hovertemplate"] = hovertemplate if hovertemplate is not None else _v _v = arg.pop("hovertemplatesrc", None) self["hovertemplatesrc"] = ( hovertemplatesrc if hovertemplatesrc is not None else _v ) _v = arg.pop("hovertext", None) self["hovertext"] = hovertext if hovertext is not None else _v _v = arg.pop("hovertextsrc", None) self["hovertextsrc"] = hovertextsrc if hovertextsrc is not None else _v _v = arg.pop("ids", None) self["ids"] = ids if ids is not None else _v _v = arg.pop("idssrc", None) self["idssrc"] = idssrc if idssrc is not None else _v _v = arg.pop("insidetextfont", None) self["insidetextfont"] = insidetextfont if insidetextfont is not None else _v _v = arg.pop("labels", None) self["labels"] = labels if labels is not None else _v _v = arg.pop("labelssrc", None) self["labelssrc"] = labelssrc if labelssrc is not None else _v _v = arg.pop("level", None) self["level"] = level if level is not None else _v _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v _v = arg.pop("maxdepth", None) self["maxdepth"] = maxdepth if maxdepth is not None else _v _v = arg.pop("meta", None) self["meta"] = meta if meta is not None else _v _v = arg.pop("metasrc", None) self["metasrc"] = metasrc if metasrc is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("outsidetextfont", None) self["outsidetextfont"] = outsidetextfont if outsidetextfont is not None else _v _v = arg.pop("parents", None) self["parents"] = parents if parents is not None else _v _v = arg.pop("parentssrc", None) self["parentssrc"] = parentssrc if parentssrc is not None else _v _v = arg.pop("pathbar", None) self["pathbar"] = pathbar if pathbar is not None else _v _v = arg.pop("stream", None) self["stream"] = stream if stream is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v _v = arg.pop("textfont", None) self["textfont"] = textfont if textfont is not None else _v _v = arg.pop("textinfo", None) self["textinfo"] = textinfo if textinfo is not None else _v _v = arg.pop("textposition", None) self["textposition"] = textposition if textposition is not None else _v _v = arg.pop("textsrc", None) self["textsrc"] = textsrc if textsrc is not None else _v _v = arg.pop("texttemplate", None) self["texttemplate"] = texttemplate if texttemplate is not None else _v _v = arg.pop("texttemplatesrc", None) self["texttemplatesrc"] = texttemplatesrc if texttemplatesrc is not None else _v _v = arg.pop("tiling", None) self["tiling"] = tiling if tiling is not None else _v _v = arg.pop("uid", None) self["uid"] = uid if uid is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("values", None) self["values"] = values if values is not None else _v _v = arg.pop("valuessrc", None) self["valuessrc"] = valuessrc if valuessrc is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v # Read-only literals # ------------------ from _plotly_utils.basevalidators import LiteralValidator self._props["type"] = "treemap" self._validators["type"] = LiteralValidator( plotly_name="type", parent_name="treemap", val="treemap" ) arg.pop("type", None) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceType as _BaseTraceType import copy as _copy class Table(_BaseTraceType): # cells # ----- @property def cells(self): """ The 'cells' property is an instance of Cells that may be specified as: - An instance of plotly.graph_objs.table.Cells - A dict of string/value properties that will be passed to the Cells constructor Supported dict properties: align Sets the horizontal alignment of the `text` within the box. Has an effect only if `text` spans more two or more lines (i.e. `text` contains one or more
HTML tags) or if an explicit width is set to override the text width. alignsrc Sets the source reference on plot.ly for align . fill plotly.graph_objects.table.cells.Fill instance or dict with compatible properties font plotly.graph_objects.table.cells.Font instance or dict with compatible properties format Sets the cell value formatting rule using d3 formatting mini-language which is similar to those of Python. See https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format formatsrc Sets the source reference on plot.ly for format . height The height of cells. line plotly.graph_objects.table.cells.Line instance or dict with compatible properties prefix Prefix for cell values. prefixsrc Sets the source reference on plot.ly for prefix . suffix Suffix for cell values. suffixsrc Sets the source reference on plot.ly for suffix . values Cell values. `values[m][n]` represents the value of the `n`th point in column `m`, therefore the `values[m]` vector length for all columns must be the same (longer vectors will be truncated). Each value must be a finite number or a string. valuessrc Sets the source reference on plot.ly for values . Returns ------- plotly.graph_objs.table.Cells """ return self["cells"] @cells.setter def cells(self, val): self["cells"] = val # columnorder # ----------- @property def columnorder(self): """ Specifies the rendered order of the data columns; for example, a value `2` at position `0` means that column index `0` in the data will be rendered as the third column, as columns have an index base of zero. The 'columnorder' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["columnorder"] @columnorder.setter def columnorder(self, val): self["columnorder"] = val # columnordersrc # -------------- @property def columnordersrc(self): """ Sets the source reference on plot.ly for columnorder . The 'columnordersrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["columnordersrc"] @columnordersrc.setter def columnordersrc(self, val): self["columnordersrc"] = val # columnwidth # ----------- @property def columnwidth(self): """ The width of columns expressed as a ratio. Columns fill the available width in proportion of their specified column widths. The 'columnwidth' property is a number and may be specified as: - An int or float - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["columnwidth"] @columnwidth.setter def columnwidth(self, val): self["columnwidth"] = val # columnwidthsrc # -------------- @property def columnwidthsrc(self): """ Sets the source reference on plot.ly for columnwidth . The 'columnwidthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["columnwidthsrc"] @columnwidthsrc.setter def columnwidthsrc(self, val): self["columnwidthsrc"] = val # customdata # ---------- @property def customdata(self): """ Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements The 'customdata' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["customdata"] @customdata.setter def customdata(self, val): self["customdata"] = val # customdatasrc # ------------- @property def customdatasrc(self): """ Sets the source reference on plot.ly for customdata . The 'customdatasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["customdatasrc"] @customdatasrc.setter def customdatasrc(self, val): self["customdatasrc"] = val # domain # ------ @property def domain(self): """ The 'domain' property is an instance of Domain that may be specified as: - An instance of plotly.graph_objs.table.Domain - A dict of string/value properties that will be passed to the Domain constructor Supported dict properties: column If there is a layout grid, use the domain for this column in the grid for this table trace . row If there is a layout grid, use the domain for this row in the grid for this table trace . x Sets the horizontal domain of this table trace (in plot fraction). y Sets the vertical domain of this table trace (in plot fraction). Returns ------- plotly.graph_objs.table.Domain """ return self["domain"] @domain.setter def domain(self, val): self["domain"] = val # header # ------ @property def header(self): """ The 'header' property is an instance of Header that may be specified as: - An instance of plotly.graph_objs.table.Header - A dict of string/value properties that will be passed to the Header constructor Supported dict properties: align Sets the horizontal alignment of the `text` within the box. Has an effect only if `text` spans more two or more lines (i.e. `text` contains one or more
HTML tags) or if an explicit width is set to override the text width. alignsrc Sets the source reference on plot.ly for align . fill plotly.graph_objects.table.header.Fill instance or dict with compatible properties font plotly.graph_objects.table.header.Font instance or dict with compatible properties format Sets the cell value formatting rule using d3 formatting mini-language which is similar to those of Python. See https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format formatsrc Sets the source reference on plot.ly for format . height The height of cells. line plotly.graph_objects.table.header.Line instance or dict with compatible properties prefix Prefix for cell values. prefixsrc Sets the source reference on plot.ly for prefix . suffix Suffix for cell values. suffixsrc Sets the source reference on plot.ly for suffix . values Header cell values. `values[m][n]` represents the value of the `n`th point in column `m`, therefore the `values[m]` vector length for all columns must be the same (longer vectors will be truncated). Each value must be a finite number or a string. valuessrc Sets the source reference on plot.ly for values . Returns ------- plotly.graph_objs.table.Header """ return self["header"] @header.setter def header(self, val): self["header"] = val # hoverinfo # --------- @property def hoverinfo(self): """ Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. The 'hoverinfo' property is a flaglist and may be specified as a string containing: - Any combination of ['x', 'y', 'z', 'text', 'name'] joined with '+' characters (e.g. 'x+y') OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') - A list or array of the above Returns ------- Any|numpy.ndarray """ return self["hoverinfo"] @hoverinfo.setter def hoverinfo(self, val): self["hoverinfo"] = val # hoverinfosrc # ------------ @property def hoverinfosrc(self): """ Sets the source reference on plot.ly for hoverinfo . The 'hoverinfosrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hoverinfosrc"] @hoverinfosrc.setter def hoverinfosrc(self, val): self["hoverinfosrc"] = val # hoverlabel # ---------- @property def hoverlabel(self): """ The 'hoverlabel' property is an instance of Hoverlabel that may be specified as: - An instance of plotly.graph_objs.table.Hoverlabel - A dict of string/value properties that will be passed to the Hoverlabel constructor Supported dict properties: align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- plotly.graph_objs.table.Hoverlabel """ return self["hoverlabel"] @hoverlabel.setter def hoverlabel(self, val): self["hoverlabel"] = val # ids # --- @property def ids(self): """ Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. The 'ids' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ids"] @ids.setter def ids(self, val): self["ids"] = val # idssrc # ------ @property def idssrc(self): """ Sets the source reference on plot.ly for ids . The 'idssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["idssrc"] @idssrc.setter def idssrc(self, val): self["idssrc"] = val # meta # ---- @property def meta(self): """ Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. The 'meta' property accepts values of any type Returns ------- Any|numpy.ndarray """ return self["meta"] @meta.setter def meta(self, val): self["meta"] = val # metasrc # ------- @property def metasrc(self): """ Sets the source reference on plot.ly for meta . The 'metasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["metasrc"] @metasrc.setter def metasrc(self, val): self["metasrc"] = val # name # ---- @property def name(self): """ Sets the trace name. The trace name appear as the legend item and on hover. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # stream # ------ @property def stream(self): """ The 'stream' property is an instance of Stream that may be specified as: - An instance of plotly.graph_objs.table.Stream - A dict of string/value properties that will be passed to the Stream constructor Supported dict properties: maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- plotly.graph_objs.table.Stream """ return self["stream"] @stream.setter def stream(self, val): self["stream"] = val # uid # --- @property def uid(self): """ Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. The 'uid' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["uid"] @uid.setter def uid(self, val): self["uid"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # visible # ------- @property def visible(self): """ Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). The 'visible' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'legendonly'] Returns ------- Any """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # type # ---- @property def type(self): return self._props["type"] # property parent name # -------------------- @property def _parent_path_str(self): return "" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ cells plotly.graph_objects.table.Cells instance or dict with compatible properties columnorder Specifies the rendered order of the data columns; for example, a value `2` at position `0` means that column index `0` in the data will be rendered as the third column, as columns have an index base of zero. columnordersrc Sets the source reference on plot.ly for columnorder . columnwidth The width of columns expressed as a ratio. Columns fill the available width in proportion of their specified column widths. columnwidthsrc Sets the source reference on plot.ly for columnwidth . customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . domain plotly.graph_objects.table.Domain instance or dict with compatible properties header plotly.graph_objects.table.Header instance or dict with compatible properties hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.table.Hoverlabel instance or dict with compatible properties ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. stream plotly.graph_objects.table.Stream instance or dict with compatible properties uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). """ def __init__( self, arg=None, cells=None, columnorder=None, columnordersrc=None, columnwidth=None, columnwidthsrc=None, customdata=None, customdatasrc=None, domain=None, header=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, ids=None, idssrc=None, meta=None, metasrc=None, name=None, stream=None, uid=None, uirevision=None, visible=None, **kwargs ): """ Construct a new Table object Table view for detailed data viewing. The data are arranged in a grid of rows and columns. Most styling can be specified for columns, rows or individual cells. Table is using a column- major order, ie. the grid is represented as a vector of column vectors. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.Table cells plotly.graph_objects.table.Cells instance or dict with compatible properties columnorder Specifies the rendered order of the data columns; for example, a value `2` at position `0` means that column index `0` in the data will be rendered as the third column, as columns have an index base of zero. columnordersrc Sets the source reference on plot.ly for columnorder . columnwidth The width of columns expressed as a ratio. Columns fill the available width in proportion of their specified column widths. columnwidthsrc Sets the source reference on plot.ly for columnwidth . customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . domain plotly.graph_objects.table.Domain instance or dict with compatible properties header plotly.graph_objects.table.Header instance or dict with compatible properties hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.table.Hoverlabel instance or dict with compatible properties ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. stream plotly.graph_objects.table.Stream instance or dict with compatible properties uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). Returns ------- Table """ super(Table, self).__init__("table") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.Table constructor must be a dict or an instance of plotly.graph_objs.Table""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators import table as v_table # Initialize validators # --------------------- self._validators["cells"] = v_table.CellsValidator() self._validators["columnorder"] = v_table.ColumnorderValidator() self._validators["columnordersrc"] = v_table.ColumnordersrcValidator() self._validators["columnwidth"] = v_table.ColumnwidthValidator() self._validators["columnwidthsrc"] = v_table.ColumnwidthsrcValidator() self._validators["customdata"] = v_table.CustomdataValidator() self._validators["customdatasrc"] = v_table.CustomdatasrcValidator() self._validators["domain"] = v_table.DomainValidator() self._validators["header"] = v_table.HeaderValidator() self._validators["hoverinfo"] = v_table.HoverinfoValidator() self._validators["hoverinfosrc"] = v_table.HoverinfosrcValidator() self._validators["hoverlabel"] = v_table.HoverlabelValidator() self._validators["ids"] = v_table.IdsValidator() self._validators["idssrc"] = v_table.IdssrcValidator() self._validators["meta"] = v_table.MetaValidator() self._validators["metasrc"] = v_table.MetasrcValidator() self._validators["name"] = v_table.NameValidator() self._validators["stream"] = v_table.StreamValidator() self._validators["uid"] = v_table.UidValidator() self._validators["uirevision"] = v_table.UirevisionValidator() self._validators["visible"] = v_table.VisibleValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("cells", None) self["cells"] = cells if cells is not None else _v _v = arg.pop("columnorder", None) self["columnorder"] = columnorder if columnorder is not None else _v _v = arg.pop("columnordersrc", None) self["columnordersrc"] = columnordersrc if columnordersrc is not None else _v _v = arg.pop("columnwidth", None) self["columnwidth"] = columnwidth if columnwidth is not None else _v _v = arg.pop("columnwidthsrc", None) self["columnwidthsrc"] = columnwidthsrc if columnwidthsrc is not None else _v _v = arg.pop("customdata", None) self["customdata"] = customdata if customdata is not None else _v _v = arg.pop("customdatasrc", None) self["customdatasrc"] = customdatasrc if customdatasrc is not None else _v _v = arg.pop("domain", None) self["domain"] = domain if domain is not None else _v _v = arg.pop("header", None) self["header"] = header if header is not None else _v _v = arg.pop("hoverinfo", None) self["hoverinfo"] = hoverinfo if hoverinfo is not None else _v _v = arg.pop("hoverinfosrc", None) self["hoverinfosrc"] = hoverinfosrc if hoverinfosrc is not None else _v _v = arg.pop("hoverlabel", None) self["hoverlabel"] = hoverlabel if hoverlabel is not None else _v _v = arg.pop("ids", None) self["ids"] = ids if ids is not None else _v _v = arg.pop("idssrc", None) self["idssrc"] = idssrc if idssrc is not None else _v _v = arg.pop("meta", None) self["meta"] = meta if meta is not None else _v _v = arg.pop("metasrc", None) self["metasrc"] = metasrc if metasrc is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("stream", None) self["stream"] = stream if stream is not None else _v _v = arg.pop("uid", None) self["uid"] = uid if uid is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v # Read-only literals # ------------------ from _plotly_utils.basevalidators import LiteralValidator self._props["type"] = "table" self._validators["type"] = LiteralValidator( plotly_name="type", parent_name="table", val="table" ) arg.pop("type", None) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceType as _BaseTraceType import copy as _copy class Surface(_BaseTraceType): # autocolorscale # -------------- @property def autocolorscale(self): """ Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. The 'autocolorscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocolorscale"] @autocolorscale.setter def autocolorscale(self, val): self["autocolorscale"] = val # cauto # ----- @property def cauto(self): """ Determines whether or not the color domain is computed with respect to the input data (here z or surfacecolor) or the bounds set in `cmin` and `cmax` Defaults to `false` when `cmin` and `cmax` are set by the user. The 'cauto' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["cauto"] @cauto.setter def cauto(self, val): self["cauto"] = val # cmax # ---- @property def cmax(self): """ Sets the upper bound of the color domain. Value should have the same units as z or surfacecolor and if set, `cmin` must be set as well. The 'cmax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmax"] @cmax.setter def cmax(self, val): self["cmax"] = val # cmid # ---- @property def cmid(self): """ Sets the mid-point of the color domain by scaling `cmin` and/or `cmax` to be equidistant to this point. Value should have the same units as z or surfacecolor. Has no effect when `cauto` is `false`. The 'cmid' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmid"] @cmid.setter def cmid(self, val): self["cmid"] = val # cmin # ---- @property def cmin(self): """ Sets the lower bound of the color domain. Value should have the same units as z or surfacecolor and if set, `cmax` must be set as well. The 'cmin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmin"] @cmin.setter def cmin(self, val): self["cmin"] = val # coloraxis # --------- @property def coloraxis(self): """ Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. The 'coloraxis' property is an identifier of a particular subplot, of type 'coloraxis', that may be specified as the string 'coloraxis' optionally followed by an integer >= 1 (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) Returns ------- str """ return self["coloraxis"] @coloraxis.setter def coloraxis(self, val): self["coloraxis"] = val # colorbar # -------- @property def colorbar(self): """ The 'colorbar' property is an instance of ColorBar that may be specified as: - An instance of plotly.graph_objs.surface.ColorBar - A dict of string/value properties that will be passed to the ColorBar constructor Supported dict properties: bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.surface.colorba r.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.surface.colorbar.tickformatstopdefaults), sets the default property values to use for elements of surface.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.surface.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use surface.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use surface.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- plotly.graph_objs.surface.ColorBar """ return self["colorbar"] @colorbar.setter def colorbar(self, val): self["colorbar"] = val # colorscale # ---------- @property def colorscale(self): """ Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`cmin` and `cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,Earth,Electric,Vi ridis,Cividis. The 'colorscale' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # connectgaps # ----------- @property def connectgaps(self): """ Determines whether or not gaps (i.e. {nan} or missing values) in the `z` data are filled in. The 'connectgaps' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["connectgaps"] @connectgaps.setter def connectgaps(self, val): self["connectgaps"] = val # contours # -------- @property def contours(self): """ The 'contours' property is an instance of Contours that may be specified as: - An instance of plotly.graph_objs.surface.Contours - A dict of string/value properties that will be passed to the Contours constructor Supported dict properties: x plotly.graph_objects.surface.contours.X instance or dict with compatible properties y plotly.graph_objects.surface.contours.Y instance or dict with compatible properties z plotly.graph_objects.surface.contours.Z instance or dict with compatible properties Returns ------- plotly.graph_objs.surface.Contours """ return self["contours"] @contours.setter def contours(self, val): self["contours"] = val # customdata # ---------- @property def customdata(self): """ Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements The 'customdata' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["customdata"] @customdata.setter def customdata(self, val): self["customdata"] = val # customdatasrc # ------------- @property def customdatasrc(self): """ Sets the source reference on plot.ly for customdata . The 'customdatasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["customdatasrc"] @customdatasrc.setter def customdatasrc(self, val): self["customdatasrc"] = val # hidesurface # ----------- @property def hidesurface(self): """ Determines whether or not a surface is drawn. For example, set `hidesurface` to False `contours.x.show` to True and `contours.y.show` to True to draw a wire frame plot. The 'hidesurface' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["hidesurface"] @hidesurface.setter def hidesurface(self, val): self["hidesurface"] = val # hoverinfo # --------- @property def hoverinfo(self): """ Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. The 'hoverinfo' property is a flaglist and may be specified as a string containing: - Any combination of ['x', 'y', 'z', 'text', 'name'] joined with '+' characters (e.g. 'x+y') OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') - A list or array of the above Returns ------- Any|numpy.ndarray """ return self["hoverinfo"] @hoverinfo.setter def hoverinfo(self, val): self["hoverinfo"] = val # hoverinfosrc # ------------ @property def hoverinfosrc(self): """ Sets the source reference on plot.ly for hoverinfo . The 'hoverinfosrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hoverinfosrc"] @hoverinfosrc.setter def hoverinfosrc(self, val): self["hoverinfosrc"] = val # hoverlabel # ---------- @property def hoverlabel(self): """ The 'hoverlabel' property is an instance of Hoverlabel that may be specified as: - An instance of plotly.graph_objs.surface.Hoverlabel - A dict of string/value properties that will be passed to the Hoverlabel constructor Supported dict properties: align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- plotly.graph_objs.surface.Hoverlabel """ return self["hoverlabel"] @hoverlabel.setter def hoverlabel(self, val): self["hoverlabel"] = val # hovertemplate # ------------- @property def hovertemplate(self): """ Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event- data. Additionally, every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. The 'hovertemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertemplate"] @hovertemplate.setter def hovertemplate(self, val): self["hovertemplate"] = val # hovertemplatesrc # ---------------- @property def hovertemplatesrc(self): """ Sets the source reference on plot.ly for hovertemplate . The 'hovertemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertemplatesrc"] @hovertemplatesrc.setter def hovertemplatesrc(self, val): self["hovertemplatesrc"] = val # hovertext # --------- @property def hovertext(self): """ Same as `text`. The 'hovertext' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertext"] @hovertext.setter def hovertext(self, val): self["hovertext"] = val # hovertextsrc # ------------ @property def hovertextsrc(self): """ Sets the source reference on plot.ly for hovertext . The 'hovertextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertextsrc"] @hovertextsrc.setter def hovertextsrc(self, val): self["hovertextsrc"] = val # ids # --- @property def ids(self): """ Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. The 'ids' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ids"] @ids.setter def ids(self, val): self["ids"] = val # idssrc # ------ @property def idssrc(self): """ Sets the source reference on plot.ly for ids . The 'idssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["idssrc"] @idssrc.setter def idssrc(self, val): self["idssrc"] = val # lighting # -------- @property def lighting(self): """ The 'lighting' property is an instance of Lighting that may be specified as: - An instance of plotly.graph_objs.surface.Lighting - A dict of string/value properties that will be passed to the Lighting constructor Supported dict properties: ambient Ambient light increases overall color visibility but can wash out the image. diffuse Represents the extent that incident rays are reflected in a range of angles. fresnel Represents the reflectance as a dependency of the viewing angle; e.g. paper is reflective when viewing it from the edge of the paper (almost 90 degrees), causing shine. roughness Alters specular reflection; the rougher the surface, the wider and less contrasty the shine. specular Represents the level that incident rays are reflected in a single direction, causing shine. Returns ------- plotly.graph_objs.surface.Lighting """ return self["lighting"] @lighting.setter def lighting(self, val): self["lighting"] = val # lightposition # ------------- @property def lightposition(self): """ The 'lightposition' property is an instance of Lightposition that may be specified as: - An instance of plotly.graph_objs.surface.Lightposition - A dict of string/value properties that will be passed to the Lightposition constructor Supported dict properties: x Numeric vector, representing the X coordinate for each vertex. y Numeric vector, representing the Y coordinate for each vertex. z Numeric vector, representing the Z coordinate for each vertex. Returns ------- plotly.graph_objs.surface.Lightposition """ return self["lightposition"] @lightposition.setter def lightposition(self, val): self["lightposition"] = val # meta # ---- @property def meta(self): """ Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. The 'meta' property accepts values of any type Returns ------- Any|numpy.ndarray """ return self["meta"] @meta.setter def meta(self, val): self["meta"] = val # metasrc # ------- @property def metasrc(self): """ Sets the source reference on plot.ly for meta . The 'metasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["metasrc"] @metasrc.setter def metasrc(self, val): self["metasrc"] = val # name # ---- @property def name(self): """ Sets the trace name. The trace name appear as the legend item and on hover. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the surface. Please note that in the case of using high `opacity` values for example a value greater than or equal to 0.5 on two surfaces (and 0.25 with four surfaces), an overlay of multiple transparent surfaces may not perfectly be sorted in depth by the webgl API. This behavior may be improved in the near future and is subject to change. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # reversescale # ------------ @property def reversescale(self): """ Reverses the color mapping if true. If true, `cmin` will correspond to the last color in the array and `cmax` will correspond to the first color. The 'reversescale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["reversescale"] @reversescale.setter def reversescale(self, val): self["reversescale"] = val # scene # ----- @property def scene(self): """ Sets a reference between this trace's 3D coordinate system and a 3D scene. If "scene" (the default value), the (x,y,z) coordinates refer to `layout.scene`. If "scene2", the (x,y,z) coordinates refer to `layout.scene2`, and so on. The 'scene' property is an identifier of a particular subplot, of type 'scene', that may be specified as the string 'scene' optionally followed by an integer >= 1 (e.g. 'scene', 'scene1', 'scene2', 'scene3', etc.) Returns ------- str """ return self["scene"] @scene.setter def scene(self, val): self["scene"] = val # showscale # --------- @property def showscale(self): """ Determines whether or not a colorbar is displayed for this trace. The 'showscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showscale"] @showscale.setter def showscale(self, val): self["showscale"] = val # stream # ------ @property def stream(self): """ The 'stream' property is an instance of Stream that may be specified as: - An instance of plotly.graph_objs.surface.Stream - A dict of string/value properties that will be passed to the Stream constructor Supported dict properties: maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- plotly.graph_objs.surface.Stream """ return self["stream"] @stream.setter def stream(self, val): self["stream"] = val # surfacecolor # ------------ @property def surfacecolor(self): """ Sets the surface color values, used for setting a color scale independent of `z`. The 'surfacecolor' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["surfacecolor"] @surfacecolor.setter def surfacecolor(self, val): self["surfacecolor"] = val # surfacecolorsrc # --------------- @property def surfacecolorsrc(self): """ Sets the source reference on plot.ly for surfacecolor . The 'surfacecolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["surfacecolorsrc"] @surfacecolorsrc.setter def surfacecolorsrc(self, val): self["surfacecolorsrc"] = val # text # ---- @property def text(self): """ Sets the text elements associated with each z value. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["text"] @text.setter def text(self, val): self["text"] = val # textsrc # ------- @property def textsrc(self): """ Sets the source reference on plot.ly for text . The 'textsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["textsrc"] @textsrc.setter def textsrc(self, val): self["textsrc"] = val # uid # --- @property def uid(self): """ Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. The 'uid' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["uid"] @uid.setter def uid(self, val): self["uid"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # visible # ------- @property def visible(self): """ Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). The 'visible' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'legendonly'] Returns ------- Any """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # x # - @property def x(self): """ Sets the x coordinates. The 'x' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["x"] @x.setter def x(self, val): self["x"] = val # xcalendar # --------- @property def xcalendar(self): """ Sets the calendar system to use with `x` date data. The 'xcalendar' property is an enumeration that may be specified as: - One of the following enumeration values: ['gregorian', 'chinese', 'coptic', 'discworld', 'ethiopian', 'hebrew', 'islamic', 'julian', 'mayan', 'nanakshahi', 'nepali', 'persian', 'jalali', 'taiwan', 'thai', 'ummalqura'] Returns ------- Any """ return self["xcalendar"] @xcalendar.setter def xcalendar(self, val): self["xcalendar"] = val # xsrc # ---- @property def xsrc(self): """ Sets the source reference on plot.ly for x . The 'xsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["xsrc"] @xsrc.setter def xsrc(self, val): self["xsrc"] = val # y # - @property def y(self): """ Sets the y coordinates. The 'y' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["y"] @y.setter def y(self, val): self["y"] = val # ycalendar # --------- @property def ycalendar(self): """ Sets the calendar system to use with `y` date data. The 'ycalendar' property is an enumeration that may be specified as: - One of the following enumeration values: ['gregorian', 'chinese', 'coptic', 'discworld', 'ethiopian', 'hebrew', 'islamic', 'julian', 'mayan', 'nanakshahi', 'nepali', 'persian', 'jalali', 'taiwan', 'thai', 'ummalqura'] Returns ------- Any """ return self["ycalendar"] @ycalendar.setter def ycalendar(self, val): self["ycalendar"] = val # ysrc # ---- @property def ysrc(self): """ Sets the source reference on plot.ly for y . The 'ysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ysrc"] @ysrc.setter def ysrc(self, val): self["ysrc"] = val # z # - @property def z(self): """ Sets the z coordinates. The 'z' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["z"] @z.setter def z(self, val): self["z"] = val # zcalendar # --------- @property def zcalendar(self): """ Sets the calendar system to use with `z` date data. The 'zcalendar' property is an enumeration that may be specified as: - One of the following enumeration values: ['gregorian', 'chinese', 'coptic', 'discworld', 'ethiopian', 'hebrew', 'islamic', 'julian', 'mayan', 'nanakshahi', 'nepali', 'persian', 'jalali', 'taiwan', 'thai', 'ummalqura'] Returns ------- Any """ return self["zcalendar"] @zcalendar.setter def zcalendar(self, val): self["zcalendar"] = val # zsrc # ---- @property def zsrc(self): """ Sets the source reference on plot.ly for z . The 'zsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["zsrc"] @zsrc.setter def zsrc(self, val): self["zsrc"] = val # type # ---- @property def type(self): return self._props["type"] # property parent name # -------------------- @property def _parent_path_str(self): return "" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here z or surfacecolor) or the bounds set in `cmin` and `cmax` Defaults to `false` when `cmin` and `cmax` are set by the user. cmax Sets the upper bound of the color domain. Value should have the same units as z or surfacecolor and if set, `cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `cmin` and/or `cmax` to be equidistant to this point. Value should have the same units as z or surfacecolor. Has no effect when `cauto` is `false`. cmin Sets the lower bound of the color domain. Value should have the same units as z or surfacecolor and if set, `cmax` must be set as well. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.surface.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`cmin` and `cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the `z` data are filled in. contours plotly.graph_objects.surface.Contours instance or dict with compatible properties customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . hidesurface Determines whether or not a surface is drawn. For example, set `hidesurface` to False `contours.x.show` to True and `contours.y.show` to True to draw a wire frame plot. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.surface.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . lighting plotly.graph_objects.surface.Lighting instance or dict with compatible properties lightposition plotly.graph_objects.surface.Lightposition instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the surface. Please note that in the case of using high `opacity` values for example a value greater than or equal to 0.5 on two surfaces (and 0.25 with four surfaces), an overlay of multiple transparent surfaces may not perfectly be sorted in depth by the webgl API. This behavior may be improved in the near future and is subject to change. reversescale Reverses the color mapping if true. If true, `cmin` will correspond to the last color in the array and `cmax` will correspond to the first color. scene Sets a reference between this trace's 3D coordinate system and a 3D scene. If "scene" (the default value), the (x,y,z) coordinates refer to `layout.scene`. If "scene2", the (x,y,z) coordinates refer to `layout.scene2`, and so on. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.surface.Stream instance or dict with compatible properties surfacecolor Sets the surface color values, used for setting a color scale independent of `z`. surfacecolorsrc Sets the source reference on plot.ly for surfacecolor . text Sets the text elements associated with each z value. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the x coordinates. xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . y Sets the y coordinates. ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . z Sets the z coordinates. zcalendar Sets the calendar system to use with `z` date data. zsrc Sets the source reference on plot.ly for z . """ def __init__( self, arg=None, autocolorscale=None, cauto=None, cmax=None, cmid=None, cmin=None, coloraxis=None, colorbar=None, colorscale=None, connectgaps=None, contours=None, customdata=None, customdatasrc=None, hidesurface=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, lighting=None, lightposition=None, meta=None, metasrc=None, name=None, opacity=None, reversescale=None, scene=None, showscale=None, stream=None, surfacecolor=None, surfacecolorsrc=None, text=None, textsrc=None, uid=None, uirevision=None, visible=None, x=None, xcalendar=None, xsrc=None, y=None, ycalendar=None, ysrc=None, z=None, zcalendar=None, zsrc=None, **kwargs ): """ Construct a new Surface object The data the describes the coordinates of the surface is set in `z`. Data in `z` should be a 2D list. Coordinates in `x` and `y` can either be 1D lists or 2D lists (e.g. to graph parametric surfaces). If not provided in `x` and `y`, the x and y coordinates are assumed to be linear starting at 0 with a unit step. The color scale corresponds to the `z` values by default. For custom color scales, use `surfacecolor` which should be a 2D list, where its bounds can be controlled using `cmin` and `cmax`. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.Surface autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here z or surfacecolor) or the bounds set in `cmin` and `cmax` Defaults to `false` when `cmin` and `cmax` are set by the user. cmax Sets the upper bound of the color domain. Value should have the same units as z or surfacecolor and if set, `cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `cmin` and/or `cmax` to be equidistant to this point. Value should have the same units as z or surfacecolor. Has no effect when `cauto` is `false`. cmin Sets the lower bound of the color domain. Value should have the same units as z or surfacecolor and if set, `cmax` must be set as well. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.surface.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`cmin` and `cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the `z` data are filled in. contours plotly.graph_objects.surface.Contours instance or dict with compatible properties customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . hidesurface Determines whether or not a surface is drawn. For example, set `hidesurface` to False `contours.x.show` to True and `contours.y.show` to True to draw a wire frame plot. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.surface.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . lighting plotly.graph_objects.surface.Lighting instance or dict with compatible properties lightposition plotly.graph_objects.surface.Lightposition instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the surface. Please note that in the case of using high `opacity` values for example a value greater than or equal to 0.5 on two surfaces (and 0.25 with four surfaces), an overlay of multiple transparent surfaces may not perfectly be sorted in depth by the webgl API. This behavior may be improved in the near future and is subject to change. reversescale Reverses the color mapping if true. If true, `cmin` will correspond to the last color in the array and `cmax` will correspond to the first color. scene Sets a reference between this trace's 3D coordinate system and a 3D scene. If "scene" (the default value), the (x,y,z) coordinates refer to `layout.scene`. If "scene2", the (x,y,z) coordinates refer to `layout.scene2`, and so on. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.surface.Stream instance or dict with compatible properties surfacecolor Sets the surface color values, used for setting a color scale independent of `z`. surfacecolorsrc Sets the source reference on plot.ly for surfacecolor . text Sets the text elements associated with each z value. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the x coordinates. xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . y Sets the y coordinates. ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . z Sets the z coordinates. zcalendar Sets the calendar system to use with `z` date data. zsrc Sets the source reference on plot.ly for z . Returns ------- Surface """ super(Surface, self).__init__("surface") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.Surface constructor must be a dict or an instance of plotly.graph_objs.Surface""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators import surface as v_surface # Initialize validators # --------------------- self._validators["autocolorscale"] = v_surface.AutocolorscaleValidator() self._validators["cauto"] = v_surface.CautoValidator() self._validators["cmax"] = v_surface.CmaxValidator() self._validators["cmid"] = v_surface.CmidValidator() self._validators["cmin"] = v_surface.CminValidator() self._validators["coloraxis"] = v_surface.ColoraxisValidator() self._validators["colorbar"] = v_surface.ColorBarValidator() self._validators["colorscale"] = v_surface.ColorscaleValidator() self._validators["connectgaps"] = v_surface.ConnectgapsValidator() self._validators["contours"] = v_surface.ContoursValidator() self._validators["customdata"] = v_surface.CustomdataValidator() self._validators["customdatasrc"] = v_surface.CustomdatasrcValidator() self._validators["hidesurface"] = v_surface.HidesurfaceValidator() self._validators["hoverinfo"] = v_surface.HoverinfoValidator() self._validators["hoverinfosrc"] = v_surface.HoverinfosrcValidator() self._validators["hoverlabel"] = v_surface.HoverlabelValidator() self._validators["hovertemplate"] = v_surface.HovertemplateValidator() self._validators["hovertemplatesrc"] = v_surface.HovertemplatesrcValidator() self._validators["hovertext"] = v_surface.HovertextValidator() self._validators["hovertextsrc"] = v_surface.HovertextsrcValidator() self._validators["ids"] = v_surface.IdsValidator() self._validators["idssrc"] = v_surface.IdssrcValidator() self._validators["lighting"] = v_surface.LightingValidator() self._validators["lightposition"] = v_surface.LightpositionValidator() self._validators["meta"] = v_surface.MetaValidator() self._validators["metasrc"] = v_surface.MetasrcValidator() self._validators["name"] = v_surface.NameValidator() self._validators["opacity"] = v_surface.OpacityValidator() self._validators["reversescale"] = v_surface.ReversescaleValidator() self._validators["scene"] = v_surface.SceneValidator() self._validators["showscale"] = v_surface.ShowscaleValidator() self._validators["stream"] = v_surface.StreamValidator() self._validators["surfacecolor"] = v_surface.SurfacecolorValidator() self._validators["surfacecolorsrc"] = v_surface.SurfacecolorsrcValidator() self._validators["text"] = v_surface.TextValidator() self._validators["textsrc"] = v_surface.TextsrcValidator() self._validators["uid"] = v_surface.UidValidator() self._validators["uirevision"] = v_surface.UirevisionValidator() self._validators["visible"] = v_surface.VisibleValidator() self._validators["x"] = v_surface.XValidator() self._validators["xcalendar"] = v_surface.XcalendarValidator() self._validators["xsrc"] = v_surface.XsrcValidator() self._validators["y"] = v_surface.YValidator() self._validators["ycalendar"] = v_surface.YcalendarValidator() self._validators["ysrc"] = v_surface.YsrcValidator() self._validators["z"] = v_surface.ZValidator() self._validators["zcalendar"] = v_surface.ZcalendarValidator() self._validators["zsrc"] = v_surface.ZsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autocolorscale", None) self["autocolorscale"] = autocolorscale if autocolorscale is not None else _v _v = arg.pop("cauto", None) self["cauto"] = cauto if cauto is not None else _v _v = arg.pop("cmax", None) self["cmax"] = cmax if cmax is not None else _v _v = arg.pop("cmid", None) self["cmid"] = cmid if cmid is not None else _v _v = arg.pop("cmin", None) self["cmin"] = cmin if cmin is not None else _v _v = arg.pop("coloraxis", None) self["coloraxis"] = coloraxis if coloraxis is not None else _v _v = arg.pop("colorbar", None) self["colorbar"] = colorbar if colorbar is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("connectgaps", None) self["connectgaps"] = connectgaps if connectgaps is not None else _v _v = arg.pop("contours", None) self["contours"] = contours if contours is not None else _v _v = arg.pop("customdata", None) self["customdata"] = customdata if customdata is not None else _v _v = arg.pop("customdatasrc", None) self["customdatasrc"] = customdatasrc if customdatasrc is not None else _v _v = arg.pop("hidesurface", None) self["hidesurface"] = hidesurface if hidesurface is not None else _v _v = arg.pop("hoverinfo", None) self["hoverinfo"] = hoverinfo if hoverinfo is not None else _v _v = arg.pop("hoverinfosrc", None) self["hoverinfosrc"] = hoverinfosrc if hoverinfosrc is not None else _v _v = arg.pop("hoverlabel", None) self["hoverlabel"] = hoverlabel if hoverlabel is not None else _v _v = arg.pop("hovertemplate", None) self["hovertemplate"] = hovertemplate if hovertemplate is not None else _v _v = arg.pop("hovertemplatesrc", None) self["hovertemplatesrc"] = ( hovertemplatesrc if hovertemplatesrc is not None else _v ) _v = arg.pop("hovertext", None) self["hovertext"] = hovertext if hovertext is not None else _v _v = arg.pop("hovertextsrc", None) self["hovertextsrc"] = hovertextsrc if hovertextsrc is not None else _v _v = arg.pop("ids", None) self["ids"] = ids if ids is not None else _v _v = arg.pop("idssrc", None) self["idssrc"] = idssrc if idssrc is not None else _v _v = arg.pop("lighting", None) self["lighting"] = lighting if lighting is not None else _v _v = arg.pop("lightposition", None) self["lightposition"] = lightposition if lightposition is not None else _v _v = arg.pop("meta", None) self["meta"] = meta if meta is not None else _v _v = arg.pop("metasrc", None) self["metasrc"] = metasrc if metasrc is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("reversescale", None) self["reversescale"] = reversescale if reversescale is not None else _v _v = arg.pop("scene", None) self["scene"] = scene if scene is not None else _v _v = arg.pop("showscale", None) self["showscale"] = showscale if showscale is not None else _v _v = arg.pop("stream", None) self["stream"] = stream if stream is not None else _v _v = arg.pop("surfacecolor", None) self["surfacecolor"] = surfacecolor if surfacecolor is not None else _v _v = arg.pop("surfacecolorsrc", None) self["surfacecolorsrc"] = surfacecolorsrc if surfacecolorsrc is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v _v = arg.pop("textsrc", None) self["textsrc"] = textsrc if textsrc is not None else _v _v = arg.pop("uid", None) self["uid"] = uid if uid is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xcalendar", None) self["xcalendar"] = xcalendar if xcalendar is not None else _v _v = arg.pop("xsrc", None) self["xsrc"] = xsrc if xsrc is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("ycalendar", None) self["ycalendar"] = ycalendar if ycalendar is not None else _v _v = arg.pop("ysrc", None) self["ysrc"] = ysrc if ysrc is not None else _v _v = arg.pop("z", None) self["z"] = z if z is not None else _v _v = arg.pop("zcalendar", None) self["zcalendar"] = zcalendar if zcalendar is not None else _v _v = arg.pop("zsrc", None) self["zsrc"] = zsrc if zsrc is not None else _v # Read-only literals # ------------------ from _plotly_utils.basevalidators import LiteralValidator self._props["type"] = "surface" self._validators["type"] = LiteralValidator( plotly_name="type", parent_name="surface", val="surface" ) arg.pop("type", None) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceType as _BaseTraceType import copy as _copy class Sunburst(_BaseTraceType): # branchvalues # ------------ @property def branchvalues(self): """ Determines how the items in `values` are summed. When set to "total", items in `values` are taken to be value of all its descendants. When set to "remainder", items in `values` corresponding to the root and the branches sectors are taken to be the extra part not part of the sum of the values at their leaves. The 'branchvalues' property is an enumeration that may be specified as: - One of the following enumeration values: ['remainder', 'total'] Returns ------- Any """ return self["branchvalues"] @branchvalues.setter def branchvalues(self, val): self["branchvalues"] = val # count # ----- @property def count(self): """ Determines default for `values` when it is not provided, by inferring a 1 for each of the "leaves" and/or "branches", otherwise 0. The 'count' property is a flaglist and may be specified as a string containing: - Any combination of ['branches', 'leaves'] joined with '+' characters (e.g. 'branches+leaves') Returns ------- Any """ return self["count"] @count.setter def count(self, val): self["count"] = val # customdata # ---------- @property def customdata(self): """ Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements The 'customdata' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["customdata"] @customdata.setter def customdata(self, val): self["customdata"] = val # customdatasrc # ------------- @property def customdatasrc(self): """ Sets the source reference on plot.ly for customdata . The 'customdatasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["customdatasrc"] @customdatasrc.setter def customdatasrc(self, val): self["customdatasrc"] = val # domain # ------ @property def domain(self): """ The 'domain' property is an instance of Domain that may be specified as: - An instance of plotly.graph_objs.sunburst.Domain - A dict of string/value properties that will be passed to the Domain constructor Supported dict properties: column If there is a layout grid, use the domain for this column in the grid for this sunburst trace . row If there is a layout grid, use the domain for this row in the grid for this sunburst trace . x Sets the horizontal domain of this sunburst trace (in plot fraction). y Sets the vertical domain of this sunburst trace (in plot fraction). Returns ------- plotly.graph_objs.sunburst.Domain """ return self["domain"] @domain.setter def domain(self, val): self["domain"] = val # hoverinfo # --------- @property def hoverinfo(self): """ Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. The 'hoverinfo' property is a flaglist and may be specified as a string containing: - Any combination of ['label', 'text', 'value', 'name', 'current path', 'percent root', 'percent entry', 'percent parent'] joined with '+' characters (e.g. 'label+text') OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') - A list or array of the above Returns ------- Any|numpy.ndarray """ return self["hoverinfo"] @hoverinfo.setter def hoverinfo(self, val): self["hoverinfo"] = val # hoverinfosrc # ------------ @property def hoverinfosrc(self): """ Sets the source reference on plot.ly for hoverinfo . The 'hoverinfosrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hoverinfosrc"] @hoverinfosrc.setter def hoverinfosrc(self, val): self["hoverinfosrc"] = val # hoverlabel # ---------- @property def hoverlabel(self): """ The 'hoverlabel' property is an instance of Hoverlabel that may be specified as: - An instance of plotly.graph_objs.sunburst.Hoverlabel - A dict of string/value properties that will be passed to the Hoverlabel constructor Supported dict properties: align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- plotly.graph_objs.sunburst.Hoverlabel """ return self["hoverlabel"] @hoverlabel.setter def hoverlabel(self, val): self["hoverlabel"] = val # hovertemplate # ------------- @property def hovertemplate(self): """ Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event- data. Additionally, every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. variables `currentPath`, `root`, `entry`, `percentRoot`, `percentEntry` and `percentParent`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. The 'hovertemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertemplate"] @hovertemplate.setter def hovertemplate(self, val): self["hovertemplate"] = val # hovertemplatesrc # ---------------- @property def hovertemplatesrc(self): """ Sets the source reference on plot.ly for hovertemplate . The 'hovertemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertemplatesrc"] @hovertemplatesrc.setter def hovertemplatesrc(self, val): self["hovertemplatesrc"] = val # hovertext # --------- @property def hovertext(self): """ Sets hover text elements associated with each sector. If a single string, the same string appears for all data points. If an array of string, the items are mapped in order of this trace's sectors. To be seen, trace `hoverinfo` must contain a "text" flag. The 'hovertext' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertext"] @hovertext.setter def hovertext(self, val): self["hovertext"] = val # hovertextsrc # ------------ @property def hovertextsrc(self): """ Sets the source reference on plot.ly for hovertext . The 'hovertextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertextsrc"] @hovertextsrc.setter def hovertextsrc(self, val): self["hovertextsrc"] = val # ids # --- @property def ids(self): """ Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. The 'ids' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ids"] @ids.setter def ids(self, val): self["ids"] = val # idssrc # ------ @property def idssrc(self): """ Sets the source reference on plot.ly for ids . The 'idssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["idssrc"] @idssrc.setter def idssrc(self, val): self["idssrc"] = val # insidetextfont # -------------- @property def insidetextfont(self): """ Sets the font used for `textinfo` lying inside the sector. The 'insidetextfont' property is an instance of Insidetextfont that may be specified as: - An instance of plotly.graph_objs.sunburst.Insidetextfont - A dict of string/value properties that will be passed to the Insidetextfont constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.sunburst.Insidetextfont """ return self["insidetextfont"] @insidetextfont.setter def insidetextfont(self, val): self["insidetextfont"] = val # labels # ------ @property def labels(self): """ Sets the labels of each of the sectors. The 'labels' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["labels"] @labels.setter def labels(self, val): self["labels"] = val # labelssrc # --------- @property def labelssrc(self): """ Sets the source reference on plot.ly for labels . The 'labelssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["labelssrc"] @labelssrc.setter def labelssrc(self, val): self["labelssrc"] = val # leaf # ---- @property def leaf(self): """ The 'leaf' property is an instance of Leaf that may be specified as: - An instance of plotly.graph_objs.sunburst.Leaf - A dict of string/value properties that will be passed to the Leaf constructor Supported dict properties: opacity Sets the opacity of the leaves. With colorscale it is defaulted to 1; otherwise it is defaulted to 0.7 Returns ------- plotly.graph_objs.sunburst.Leaf """ return self["leaf"] @leaf.setter def leaf(self, val): self["leaf"] = val # level # ----- @property def level(self): """ Sets the level from which this trace hierarchy is rendered. Set `level` to `''` to start from the root node in the hierarchy. Must be an "id" if `ids` is filled in, otherwise plotly attempts to find a matching item in `labels`. The 'level' property accepts values of any type Returns ------- Any """ return self["level"] @level.setter def level(self, val): self["level"] = val # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.sunburst.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if colorsis set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here colors) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if colorsis set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if colorsis set to a numerical array. Value should have the same units as colors and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if colorsis set to a numerical array. Value should have the same units as colors. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if colorsis set to a numerical array. Value should have the same units as colors and if set, `marker.cmax` must be set as well. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.sunburst.marker.ColorBar instance or dict with compatible properties colors Sets the color of each sector of this trace. If not specified, the default trace color set is used to pick the sector colors. colorscale Sets the colorscale. Has an effect only if colorsis set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorssrc Sets the source reference on plot.ly for colors . line plotly.graph_objects.sunburst.marker.Line instance or dict with compatible properties reversescale Reverses the color mapping if true. Has an effect only if colorsis set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if colorsis set to a numerical array. Returns ------- plotly.graph_objs.sunburst.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # maxdepth # -------- @property def maxdepth(self): """ Sets the number of rendered sectors from any given `level`. Set `maxdepth` to "-1" to render all the levels in the hierarchy. The 'maxdepth' property is a integer and may be specified as: - An int (or float that will be cast to an int) Returns ------- int """ return self["maxdepth"] @maxdepth.setter def maxdepth(self, val): self["maxdepth"] = val # meta # ---- @property def meta(self): """ Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. The 'meta' property accepts values of any type Returns ------- Any|numpy.ndarray """ return self["meta"] @meta.setter def meta(self, val): self["meta"] = val # metasrc # ------- @property def metasrc(self): """ Sets the source reference on plot.ly for meta . The 'metasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["metasrc"] @metasrc.setter def metasrc(self, val): self["metasrc"] = val # name # ---- @property def name(self): """ Sets the trace name. The trace name appear as the legend item and on hover. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the trace. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # outsidetextfont # --------------- @property def outsidetextfont(self): """ Sets the font used for `textinfo` lying outside the sector. The 'outsidetextfont' property is an instance of Outsidetextfont that may be specified as: - An instance of plotly.graph_objs.sunburst.Outsidetextfont - A dict of string/value properties that will be passed to the Outsidetextfont constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.sunburst.Outsidetextfont """ return self["outsidetextfont"] @outsidetextfont.setter def outsidetextfont(self, val): self["outsidetextfont"] = val # parents # ------- @property def parents(self): """ Sets the parent sectors for each of the sectors. Empty string items '' are understood to reference the root node in the hierarchy. If `ids` is filled, `parents` items are understood to be "ids" themselves. When `ids` is not set, plotly attempts to find matching items in `labels`, but beware they must be unique. The 'parents' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["parents"] @parents.setter def parents(self, val): self["parents"] = val # parentssrc # ---------- @property def parentssrc(self): """ Sets the source reference on plot.ly for parents . The 'parentssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["parentssrc"] @parentssrc.setter def parentssrc(self, val): self["parentssrc"] = val # stream # ------ @property def stream(self): """ The 'stream' property is an instance of Stream that may be specified as: - An instance of plotly.graph_objs.sunburst.Stream - A dict of string/value properties that will be passed to the Stream constructor Supported dict properties: maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- plotly.graph_objs.sunburst.Stream """ return self["stream"] @stream.setter def stream(self, val): self["stream"] = val # text # ---- @property def text(self): """ Sets text elements associated with each sector. If trace `textinfo` contains a "text" flag, these elements will be seen on the chart. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. The 'text' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["text"] @text.setter def text(self, val): self["text"] = val # textfont # -------- @property def textfont(self): """ Sets the font used for `textinfo`. The 'textfont' property is an instance of Textfont that may be specified as: - An instance of plotly.graph_objs.sunburst.Textfont - A dict of string/value properties that will be passed to the Textfont constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.sunburst.Textfont """ return self["textfont"] @textfont.setter def textfont(self, val): self["textfont"] = val # textinfo # -------- @property def textinfo(self): """ Determines which trace information appear on the graph. The 'textinfo' property is a flaglist and may be specified as a string containing: - Any combination of ['label', 'text', 'value', 'current path', 'percent root', 'percent entry', 'percent parent'] joined with '+' characters (e.g. 'label+text') OR exactly one of ['none'] (e.g. 'none') Returns ------- Any """ return self["textinfo"] @textinfo.setter def textinfo(self, val): self["textinfo"] = val # textsrc # ------- @property def textsrc(self): """ Sets the source reference on plot.ly for text . The 'textsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["textsrc"] @textsrc.setter def textsrc(self, val): self["textsrc"] = val # texttemplate # ------------ @property def texttemplate(self): """ Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `currentPath`, `root`, `entry`, `percentRoot`, `percentEntry`, `percentParent`, `label` and `value`. The 'texttemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["texttemplate"] @texttemplate.setter def texttemplate(self, val): self["texttemplate"] = val # texttemplatesrc # --------------- @property def texttemplatesrc(self): """ Sets the source reference on plot.ly for texttemplate . The 'texttemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["texttemplatesrc"] @texttemplatesrc.setter def texttemplatesrc(self, val): self["texttemplatesrc"] = val # uid # --- @property def uid(self): """ Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. The 'uid' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["uid"] @uid.setter def uid(self, val): self["uid"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # values # ------ @property def values(self): """ Sets the values associated with each of the sectors. Use with `branchvalues` to determine how the values are summed. The 'values' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["values"] @values.setter def values(self, val): self["values"] = val # valuessrc # --------- @property def valuessrc(self): """ Sets the source reference on plot.ly for values . The 'valuessrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["valuessrc"] @valuessrc.setter def valuessrc(self, val): self["valuessrc"] = val # visible # ------- @property def visible(self): """ Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). The 'visible' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'legendonly'] Returns ------- Any """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # type # ---- @property def type(self): return self._props["type"] # property parent name # -------------------- @property def _parent_path_str(self): return "" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ branchvalues Determines how the items in `values` are summed. When set to "total", items in `values` are taken to be value of all its descendants. When set to "remainder", items in `values` corresponding to the root and the branches sectors are taken to be the extra part not part of the sum of the values at their leaves. count Determines default for `values` when it is not provided, by inferring a 1 for each of the "leaves" and/or "branches", otherwise 0. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . domain plotly.graph_objects.sunburst.Domain instance or dict with compatible properties hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.sunburst.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `currentPath`, `root`, `entry`, `percentRoot`, `percentEntry` and `percentParent`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each sector. If a single string, the same string appears for all data points. If an array of string, the items are mapped in order of this trace's sectors. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . insidetextfont Sets the font used for `textinfo` lying inside the sector. labels Sets the labels of each of the sectors. labelssrc Sets the source reference on plot.ly for labels . leaf plotly.graph_objects.sunburst.Leaf instance or dict with compatible properties level Sets the level from which this trace hierarchy is rendered. Set `level` to `''` to start from the root node in the hierarchy. Must be an "id" if `ids` is filled in, otherwise plotly attempts to find a matching item in `labels`. marker plotly.graph_objects.sunburst.Marker instance or dict with compatible properties maxdepth Sets the number of rendered sectors from any given `level`. Set `maxdepth` to "-1" to render all the levels in the hierarchy. meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. outsidetextfont Sets the font used for `textinfo` lying outside the sector. parents Sets the parent sectors for each of the sectors. Empty string items '' are understood to reference the root node in the hierarchy. If `ids` is filled, `parents` items are understood to be "ids" themselves. When `ids` is not set, plotly attempts to find matching items in `labels`, but beware they must be unique. parentssrc Sets the source reference on plot.ly for parents . stream plotly.graph_objects.sunburst.Stream instance or dict with compatible properties text Sets text elements associated with each sector. If trace `textinfo` contains a "text" flag, these elements will be seen on the chart. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the font used for `textinfo`. textinfo Determines which trace information appear on the graph. textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `currentPath`, `root`, `entry`, `percentRoot`, `percentEntry`, `percentParent`, `label` and `value`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. values Sets the values associated with each of the sectors. Use with `branchvalues` to determine how the values are summed. valuessrc Sets the source reference on plot.ly for values . visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). """ def __init__( self, arg=None, branchvalues=None, count=None, customdata=None, customdatasrc=None, domain=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, insidetextfont=None, labels=None, labelssrc=None, leaf=None, level=None, marker=None, maxdepth=None, meta=None, metasrc=None, name=None, opacity=None, outsidetextfont=None, parents=None, parentssrc=None, stream=None, text=None, textfont=None, textinfo=None, textsrc=None, texttemplate=None, texttemplatesrc=None, uid=None, uirevision=None, values=None, valuessrc=None, visible=None, **kwargs ): """ Construct a new Sunburst object Visualize hierarchal data spanning outward radially from root to leaves. The sunburst sectors are determined by the entries in "labels" or "ids" and in "parents". Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.Sunburst branchvalues Determines how the items in `values` are summed. When set to "total", items in `values` are taken to be value of all its descendants. When set to "remainder", items in `values` corresponding to the root and the branches sectors are taken to be the extra part not part of the sum of the values at their leaves. count Determines default for `values` when it is not provided, by inferring a 1 for each of the "leaves" and/or "branches", otherwise 0. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . domain plotly.graph_objects.sunburst.Domain instance or dict with compatible properties hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.sunburst.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `currentPath`, `root`, `entry`, `percentRoot`, `percentEntry` and `percentParent`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each sector. If a single string, the same string appears for all data points. If an array of string, the items are mapped in order of this trace's sectors. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . insidetextfont Sets the font used for `textinfo` lying inside the sector. labels Sets the labels of each of the sectors. labelssrc Sets the source reference on plot.ly for labels . leaf plotly.graph_objects.sunburst.Leaf instance or dict with compatible properties level Sets the level from which this trace hierarchy is rendered. Set `level` to `''` to start from the root node in the hierarchy. Must be an "id" if `ids` is filled in, otherwise plotly attempts to find a matching item in `labels`. marker plotly.graph_objects.sunburst.Marker instance or dict with compatible properties maxdepth Sets the number of rendered sectors from any given `level`. Set `maxdepth` to "-1" to render all the levels in the hierarchy. meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. outsidetextfont Sets the font used for `textinfo` lying outside the sector. parents Sets the parent sectors for each of the sectors. Empty string items '' are understood to reference the root node in the hierarchy. If `ids` is filled, `parents` items are understood to be "ids" themselves. When `ids` is not set, plotly attempts to find matching items in `labels`, but beware they must be unique. parentssrc Sets the source reference on plot.ly for parents . stream plotly.graph_objects.sunburst.Stream instance or dict with compatible properties text Sets text elements associated with each sector. If trace `textinfo` contains a "text" flag, these elements will be seen on the chart. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the font used for `textinfo`. textinfo Determines which trace information appear on the graph. textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `currentPath`, `root`, `entry`, `percentRoot`, `percentEntry`, `percentParent`, `label` and `value`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. values Sets the values associated with each of the sectors. Use with `branchvalues` to determine how the values are summed. valuessrc Sets the source reference on plot.ly for values . visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). Returns ------- Sunburst """ super(Sunburst, self).__init__("sunburst") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.Sunburst constructor must be a dict or an instance of plotly.graph_objs.Sunburst""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators import sunburst as v_sunburst # Initialize validators # --------------------- self._validators["branchvalues"] = v_sunburst.BranchvaluesValidator() self._validators["count"] = v_sunburst.CountValidator() self._validators["customdata"] = v_sunburst.CustomdataValidator() self._validators["customdatasrc"] = v_sunburst.CustomdatasrcValidator() self._validators["domain"] = v_sunburst.DomainValidator() self._validators["hoverinfo"] = v_sunburst.HoverinfoValidator() self._validators["hoverinfosrc"] = v_sunburst.HoverinfosrcValidator() self._validators["hoverlabel"] = v_sunburst.HoverlabelValidator() self._validators["hovertemplate"] = v_sunburst.HovertemplateValidator() self._validators["hovertemplatesrc"] = v_sunburst.HovertemplatesrcValidator() self._validators["hovertext"] = v_sunburst.HovertextValidator() self._validators["hovertextsrc"] = v_sunburst.HovertextsrcValidator() self._validators["ids"] = v_sunburst.IdsValidator() self._validators["idssrc"] = v_sunburst.IdssrcValidator() self._validators["insidetextfont"] = v_sunburst.InsidetextfontValidator() self._validators["labels"] = v_sunburst.LabelsValidator() self._validators["labelssrc"] = v_sunburst.LabelssrcValidator() self._validators["leaf"] = v_sunburst.LeafValidator() self._validators["level"] = v_sunburst.LevelValidator() self._validators["marker"] = v_sunburst.MarkerValidator() self._validators["maxdepth"] = v_sunburst.MaxdepthValidator() self._validators["meta"] = v_sunburst.MetaValidator() self._validators["metasrc"] = v_sunburst.MetasrcValidator() self._validators["name"] = v_sunburst.NameValidator() self._validators["opacity"] = v_sunburst.OpacityValidator() self._validators["outsidetextfont"] = v_sunburst.OutsidetextfontValidator() self._validators["parents"] = v_sunburst.ParentsValidator() self._validators["parentssrc"] = v_sunburst.ParentssrcValidator() self._validators["stream"] = v_sunburst.StreamValidator() self._validators["text"] = v_sunburst.TextValidator() self._validators["textfont"] = v_sunburst.TextfontValidator() self._validators["textinfo"] = v_sunburst.TextinfoValidator() self._validators["textsrc"] = v_sunburst.TextsrcValidator() self._validators["texttemplate"] = v_sunburst.TexttemplateValidator() self._validators["texttemplatesrc"] = v_sunburst.TexttemplatesrcValidator() self._validators["uid"] = v_sunburst.UidValidator() self._validators["uirevision"] = v_sunburst.UirevisionValidator() self._validators["values"] = v_sunburst.ValuesValidator() self._validators["valuessrc"] = v_sunburst.ValuessrcValidator() self._validators["visible"] = v_sunburst.VisibleValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("branchvalues", None) self["branchvalues"] = branchvalues if branchvalues is not None else _v _v = arg.pop("count", None) self["count"] = count if count is not None else _v _v = arg.pop("customdata", None) self["customdata"] = customdata if customdata is not None else _v _v = arg.pop("customdatasrc", None) self["customdatasrc"] = customdatasrc if customdatasrc is not None else _v _v = arg.pop("domain", None) self["domain"] = domain if domain is not None else _v _v = arg.pop("hoverinfo", None) self["hoverinfo"] = hoverinfo if hoverinfo is not None else _v _v = arg.pop("hoverinfosrc", None) self["hoverinfosrc"] = hoverinfosrc if hoverinfosrc is not None else _v _v = arg.pop("hoverlabel", None) self["hoverlabel"] = hoverlabel if hoverlabel is not None else _v _v = arg.pop("hovertemplate", None) self["hovertemplate"] = hovertemplate if hovertemplate is not None else _v _v = arg.pop("hovertemplatesrc", None) self["hovertemplatesrc"] = ( hovertemplatesrc if hovertemplatesrc is not None else _v ) _v = arg.pop("hovertext", None) self["hovertext"] = hovertext if hovertext is not None else _v _v = arg.pop("hovertextsrc", None) self["hovertextsrc"] = hovertextsrc if hovertextsrc is not None else _v _v = arg.pop("ids", None) self["ids"] = ids if ids is not None else _v _v = arg.pop("idssrc", None) self["idssrc"] = idssrc if idssrc is not None else _v _v = arg.pop("insidetextfont", None) self["insidetextfont"] = insidetextfont if insidetextfont is not None else _v _v = arg.pop("labels", None) self["labels"] = labels if labels is not None else _v _v = arg.pop("labelssrc", None) self["labelssrc"] = labelssrc if labelssrc is not None else _v _v = arg.pop("leaf", None) self["leaf"] = leaf if leaf is not None else _v _v = arg.pop("level", None) self["level"] = level if level is not None else _v _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v _v = arg.pop("maxdepth", None) self["maxdepth"] = maxdepth if maxdepth is not None else _v _v = arg.pop("meta", None) self["meta"] = meta if meta is not None else _v _v = arg.pop("metasrc", None) self["metasrc"] = metasrc if metasrc is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("outsidetextfont", None) self["outsidetextfont"] = outsidetextfont if outsidetextfont is not None else _v _v = arg.pop("parents", None) self["parents"] = parents if parents is not None else _v _v = arg.pop("parentssrc", None) self["parentssrc"] = parentssrc if parentssrc is not None else _v _v = arg.pop("stream", None) self["stream"] = stream if stream is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v _v = arg.pop("textfont", None) self["textfont"] = textfont if textfont is not None else _v _v = arg.pop("textinfo", None) self["textinfo"] = textinfo if textinfo is not None else _v _v = arg.pop("textsrc", None) self["textsrc"] = textsrc if textsrc is not None else _v _v = arg.pop("texttemplate", None) self["texttemplate"] = texttemplate if texttemplate is not None else _v _v = arg.pop("texttemplatesrc", None) self["texttemplatesrc"] = texttemplatesrc if texttemplatesrc is not None else _v _v = arg.pop("uid", None) self["uid"] = uid if uid is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("values", None) self["values"] = values if values is not None else _v _v = arg.pop("valuessrc", None) self["valuessrc"] = valuessrc if valuessrc is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v # Read-only literals # ------------------ from _plotly_utils.basevalidators import LiteralValidator self._props["type"] = "sunburst" self._validators["type"] = LiteralValidator( plotly_name="type", parent_name="sunburst", val="sunburst" ) arg.pop("type", None) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceType as _BaseTraceType import copy as _copy class Streamtube(_BaseTraceType): # autocolorscale # -------------- @property def autocolorscale(self): """ Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. The 'autocolorscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocolorscale"] @autocolorscale.setter def autocolorscale(self, val): self["autocolorscale"] = val # cauto # ----- @property def cauto(self): """ Determines whether or not the color domain is computed with respect to the input data (here u/v/w norm) or the bounds set in `cmin` and `cmax` Defaults to `false` when `cmin` and `cmax` are set by the user. The 'cauto' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["cauto"] @cauto.setter def cauto(self, val): self["cauto"] = val # cmax # ---- @property def cmax(self): """ Sets the upper bound of the color domain. Value should have the same units as u/v/w norm and if set, `cmin` must be set as well. The 'cmax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmax"] @cmax.setter def cmax(self, val): self["cmax"] = val # cmid # ---- @property def cmid(self): """ Sets the mid-point of the color domain by scaling `cmin` and/or `cmax` to be equidistant to this point. Value should have the same units as u/v/w norm. Has no effect when `cauto` is `false`. The 'cmid' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmid"] @cmid.setter def cmid(self, val): self["cmid"] = val # cmin # ---- @property def cmin(self): """ Sets the lower bound of the color domain. Value should have the same units as u/v/w norm and if set, `cmax` must be set as well. The 'cmin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmin"] @cmin.setter def cmin(self, val): self["cmin"] = val # coloraxis # --------- @property def coloraxis(self): """ Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. The 'coloraxis' property is an identifier of a particular subplot, of type 'coloraxis', that may be specified as the string 'coloraxis' optionally followed by an integer >= 1 (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) Returns ------- str """ return self["coloraxis"] @coloraxis.setter def coloraxis(self, val): self["coloraxis"] = val # colorbar # -------- @property def colorbar(self): """ The 'colorbar' property is an instance of ColorBar that may be specified as: - An instance of plotly.graph_objs.streamtube.ColorBar - A dict of string/value properties that will be passed to the ColorBar constructor Supported dict properties: bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.streamtube.colo rbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.streamtube.colorbar.tickformatstopdefaults), sets the default property values to use for elements of streamtube.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.streamtube.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use streamtube.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use streamtube.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- plotly.graph_objs.streamtube.ColorBar """ return self["colorbar"] @colorbar.setter def colorbar(self, val): self["colorbar"] = val # colorscale # ---------- @property def colorscale(self): """ Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`cmin` and `cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,Earth,Electric,Vi ridis,Cividis. The 'colorscale' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # customdata # ---------- @property def customdata(self): """ Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements The 'customdata' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["customdata"] @customdata.setter def customdata(self, val): self["customdata"] = val # customdatasrc # ------------- @property def customdatasrc(self): """ Sets the source reference on plot.ly for customdata . The 'customdatasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["customdatasrc"] @customdatasrc.setter def customdatasrc(self, val): self["customdatasrc"] = val # hoverinfo # --------- @property def hoverinfo(self): """ Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. The 'hoverinfo' property is a flaglist and may be specified as a string containing: - Any combination of ['x', 'y', 'z', 'u', 'v', 'w', 'norm', 'divergence', 'text', 'name'] joined with '+' characters (e.g. 'x+y') OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') - A list or array of the above Returns ------- Any|numpy.ndarray """ return self["hoverinfo"] @hoverinfo.setter def hoverinfo(self, val): self["hoverinfo"] = val # hoverinfosrc # ------------ @property def hoverinfosrc(self): """ Sets the source reference on plot.ly for hoverinfo . The 'hoverinfosrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hoverinfosrc"] @hoverinfosrc.setter def hoverinfosrc(self, val): self["hoverinfosrc"] = val # hoverlabel # ---------- @property def hoverlabel(self): """ The 'hoverlabel' property is an instance of Hoverlabel that may be specified as: - An instance of plotly.graph_objs.streamtube.Hoverlabel - A dict of string/value properties that will be passed to the Hoverlabel constructor Supported dict properties: align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- plotly.graph_objs.streamtube.Hoverlabel """ return self["hoverlabel"] @hoverlabel.setter def hoverlabel(self, val): self["hoverlabel"] = val # hovertemplate # ------------- @property def hovertemplate(self): """ Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event- data. Additionally, every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. variables `tubex`, `tubey`, `tubez`, `tubeu`, `tubev`, `tubew`, `norm` and `divergence`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. The 'hovertemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertemplate"] @hovertemplate.setter def hovertemplate(self, val): self["hovertemplate"] = val # hovertemplatesrc # ---------------- @property def hovertemplatesrc(self): """ Sets the source reference on plot.ly for hovertemplate . The 'hovertemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertemplatesrc"] @hovertemplatesrc.setter def hovertemplatesrc(self, val): self["hovertemplatesrc"] = val # hovertext # --------- @property def hovertext(self): """ Same as `text`. The 'hovertext' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["hovertext"] @hovertext.setter def hovertext(self, val): self["hovertext"] = val # ids # --- @property def ids(self): """ Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. The 'ids' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ids"] @ids.setter def ids(self, val): self["ids"] = val # idssrc # ------ @property def idssrc(self): """ Sets the source reference on plot.ly for ids . The 'idssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["idssrc"] @idssrc.setter def idssrc(self, val): self["idssrc"] = val # lighting # -------- @property def lighting(self): """ The 'lighting' property is an instance of Lighting that may be specified as: - An instance of plotly.graph_objs.streamtube.Lighting - A dict of string/value properties that will be passed to the Lighting constructor Supported dict properties: ambient Ambient light increases overall color visibility but can wash out the image. diffuse Represents the extent that incident rays are reflected in a range of angles. facenormalsepsilon Epsilon for face normals calculation avoids math issues arising from degenerate geometry. fresnel Represents the reflectance as a dependency of the viewing angle; e.g. paper is reflective when viewing it from the edge of the paper (almost 90 degrees), causing shine. roughness Alters specular reflection; the rougher the surface, the wider and less contrasty the shine. specular Represents the level that incident rays are reflected in a single direction, causing shine. vertexnormalsepsilon Epsilon for vertex normals calculation avoids math issues arising from degenerate geometry. Returns ------- plotly.graph_objs.streamtube.Lighting """ return self["lighting"] @lighting.setter def lighting(self, val): self["lighting"] = val # lightposition # ------------- @property def lightposition(self): """ The 'lightposition' property is an instance of Lightposition that may be specified as: - An instance of plotly.graph_objs.streamtube.Lightposition - A dict of string/value properties that will be passed to the Lightposition constructor Supported dict properties: x Numeric vector, representing the X coordinate for each vertex. y Numeric vector, representing the Y coordinate for each vertex. z Numeric vector, representing the Z coordinate for each vertex. Returns ------- plotly.graph_objs.streamtube.Lightposition """ return self["lightposition"] @lightposition.setter def lightposition(self, val): self["lightposition"] = val # maxdisplayed # ------------ @property def maxdisplayed(self): """ The maximum number of displayed segments in a streamtube. The 'maxdisplayed' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["maxdisplayed"] @maxdisplayed.setter def maxdisplayed(self, val): self["maxdisplayed"] = val # meta # ---- @property def meta(self): """ Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. The 'meta' property accepts values of any type Returns ------- Any|numpy.ndarray """ return self["meta"] @meta.setter def meta(self, val): self["meta"] = val # metasrc # ------- @property def metasrc(self): """ Sets the source reference on plot.ly for meta . The 'metasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["metasrc"] @metasrc.setter def metasrc(self, val): self["metasrc"] = val # name # ---- @property def name(self): """ Sets the trace name. The trace name appear as the legend item and on hover. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the surface. Please note that in the case of using high `opacity` values for example a value greater than or equal to 0.5 on two surfaces (and 0.25 with four surfaces), an overlay of multiple transparent surfaces may not perfectly be sorted in depth by the webgl API. This behavior may be improved in the near future and is subject to change. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # reversescale # ------------ @property def reversescale(self): """ Reverses the color mapping if true. If true, `cmin` will correspond to the last color in the array and `cmax` will correspond to the first color. The 'reversescale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["reversescale"] @reversescale.setter def reversescale(self, val): self["reversescale"] = val # scene # ----- @property def scene(self): """ Sets a reference between this trace's 3D coordinate system and a 3D scene. If "scene" (the default value), the (x,y,z) coordinates refer to `layout.scene`. If "scene2", the (x,y,z) coordinates refer to `layout.scene2`, and so on. The 'scene' property is an identifier of a particular subplot, of type 'scene', that may be specified as the string 'scene' optionally followed by an integer >= 1 (e.g. 'scene', 'scene1', 'scene2', 'scene3', etc.) Returns ------- str """ return self["scene"] @scene.setter def scene(self, val): self["scene"] = val # showscale # --------- @property def showscale(self): """ Determines whether or not a colorbar is displayed for this trace. The 'showscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showscale"] @showscale.setter def showscale(self, val): self["showscale"] = val # sizeref # ------- @property def sizeref(self): """ The scaling factor for the streamtubes. The default is 1, which avoids two max divergence tubes from touching at adjacent starting positions. The 'sizeref' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["sizeref"] @sizeref.setter def sizeref(self, val): self["sizeref"] = val # starts # ------ @property def starts(self): """ The 'starts' property is an instance of Starts that may be specified as: - An instance of plotly.graph_objs.streamtube.Starts - A dict of string/value properties that will be passed to the Starts constructor Supported dict properties: x Sets the x components of the starting position of the streamtubes xsrc Sets the source reference on plot.ly for x . y Sets the y components of the starting position of the streamtubes ysrc Sets the source reference on plot.ly for y . z Sets the z components of the starting position of the streamtubes zsrc Sets the source reference on plot.ly for z . Returns ------- plotly.graph_objs.streamtube.Starts """ return self["starts"] @starts.setter def starts(self, val): self["starts"] = val # stream # ------ @property def stream(self): """ The 'stream' property is an instance of Stream that may be specified as: - An instance of plotly.graph_objs.streamtube.Stream - A dict of string/value properties that will be passed to the Stream constructor Supported dict properties: maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- plotly.graph_objs.streamtube.Stream """ return self["stream"] @stream.setter def stream(self, val): self["stream"] = val # text # ---- @property def text(self): """ Sets a text element associated with this trace. If trace `hoverinfo` contains a "text" flag, this text element will be seen in all hover labels. Note that streamtube traces do not support array `text` values. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # u # - @property def u(self): """ Sets the x components of the vector field. The 'u' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["u"] @u.setter def u(self, val): self["u"] = val # uid # --- @property def uid(self): """ Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. The 'uid' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["uid"] @uid.setter def uid(self, val): self["uid"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # usrc # ---- @property def usrc(self): """ Sets the source reference on plot.ly for u . The 'usrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["usrc"] @usrc.setter def usrc(self, val): self["usrc"] = val # v # - @property def v(self): """ Sets the y components of the vector field. The 'v' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["v"] @v.setter def v(self, val): self["v"] = val # visible # ------- @property def visible(self): """ Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). The 'visible' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'legendonly'] Returns ------- Any """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # vsrc # ---- @property def vsrc(self): """ Sets the source reference on plot.ly for v . The 'vsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["vsrc"] @vsrc.setter def vsrc(self, val): self["vsrc"] = val # w # - @property def w(self): """ Sets the z components of the vector field. The 'w' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["w"] @w.setter def w(self, val): self["w"] = val # wsrc # ---- @property def wsrc(self): """ Sets the source reference on plot.ly for w . The 'wsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["wsrc"] @wsrc.setter def wsrc(self, val): self["wsrc"] = val # x # - @property def x(self): """ Sets the x coordinates of the vector field. The 'x' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["x"] @x.setter def x(self, val): self["x"] = val # xsrc # ---- @property def xsrc(self): """ Sets the source reference on plot.ly for x . The 'xsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["xsrc"] @xsrc.setter def xsrc(self, val): self["xsrc"] = val # y # - @property def y(self): """ Sets the y coordinates of the vector field. The 'y' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["y"] @y.setter def y(self, val): self["y"] = val # ysrc # ---- @property def ysrc(self): """ Sets the source reference on plot.ly for y . The 'ysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ysrc"] @ysrc.setter def ysrc(self, val): self["ysrc"] = val # z # - @property def z(self): """ Sets the z coordinates of the vector field. The 'z' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["z"] @z.setter def z(self, val): self["z"] = val # zsrc # ---- @property def zsrc(self): """ Sets the source reference on plot.ly for z . The 'zsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["zsrc"] @zsrc.setter def zsrc(self, val): self["zsrc"] = val # type # ---- @property def type(self): return self._props["type"] # property parent name # -------------------- @property def _parent_path_str(self): return "" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here u/v/w norm) or the bounds set in `cmin` and `cmax` Defaults to `false` when `cmin` and `cmax` are set by the user. cmax Sets the upper bound of the color domain. Value should have the same units as u/v/w norm and if set, `cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `cmin` and/or `cmax` to be equidistant to this point. Value should have the same units as u/v/w norm. Has no effect when `cauto` is `false`. cmin Sets the lower bound of the color domain. Value should have the same units as u/v/w norm and if set, `cmax` must be set as well. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.streamtube.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`cmin` and `cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.streamtube.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `tubex`, `tubey`, `tubez`, `tubeu`, `tubev`, `tubew`, `norm` and `divergence`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . lighting plotly.graph_objects.streamtube.Lighting instance or dict with compatible properties lightposition plotly.graph_objects.streamtube.Lightposition instance or dict with compatible properties maxdisplayed The maximum number of displayed segments in a streamtube. meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the surface. Please note that in the case of using high `opacity` values for example a value greater than or equal to 0.5 on two surfaces (and 0.25 with four surfaces), an overlay of multiple transparent surfaces may not perfectly be sorted in depth by the webgl API. This behavior may be improved in the near future and is subject to change. reversescale Reverses the color mapping if true. If true, `cmin` will correspond to the last color in the array and `cmax` will correspond to the first color. scene Sets a reference between this trace's 3D coordinate system and a 3D scene. If "scene" (the default value), the (x,y,z) coordinates refer to `layout.scene`. If "scene2", the (x,y,z) coordinates refer to `layout.scene2`, and so on. showscale Determines whether or not a colorbar is displayed for this trace. sizeref The scaling factor for the streamtubes. The default is 1, which avoids two max divergence tubes from touching at adjacent starting positions. starts plotly.graph_objects.streamtube.Starts instance or dict with compatible properties stream plotly.graph_objects.streamtube.Stream instance or dict with compatible properties text Sets a text element associated with this trace. If trace `hoverinfo` contains a "text" flag, this text element will be seen in all hover labels. Note that streamtube traces do not support array `text` values. u Sets the x components of the vector field. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. usrc Sets the source reference on plot.ly for u . v Sets the y components of the vector field. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). vsrc Sets the source reference on plot.ly for v . w Sets the z components of the vector field. wsrc Sets the source reference on plot.ly for w . x Sets the x coordinates of the vector field. xsrc Sets the source reference on plot.ly for x . y Sets the y coordinates of the vector field. ysrc Sets the source reference on plot.ly for y . z Sets the z coordinates of the vector field. zsrc Sets the source reference on plot.ly for z . """ def __init__( self, arg=None, autocolorscale=None, cauto=None, cmax=None, cmid=None, cmin=None, coloraxis=None, colorbar=None, colorscale=None, customdata=None, customdatasrc=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, ids=None, idssrc=None, lighting=None, lightposition=None, maxdisplayed=None, meta=None, metasrc=None, name=None, opacity=None, reversescale=None, scene=None, showscale=None, sizeref=None, starts=None, stream=None, text=None, u=None, uid=None, uirevision=None, usrc=None, v=None, visible=None, vsrc=None, w=None, wsrc=None, x=None, xsrc=None, y=None, ysrc=None, z=None, zsrc=None, **kwargs ): """ Construct a new Streamtube object Use a streamtube trace to visualize flow in a vector field. Specify a vector field using 6 1D arrays of equal length, 3 position arrays `x`, `y` and `z` and 3 vector component arrays `u`, `v`, and `w`. By default, the tubes' starting positions will be cut from the vector field's x-z plane at its minimum y value. To specify your own starting position, use attributes `starts.x`, `starts.y` and `starts.z`. The color is encoded by the norm of (u, v, w), and the local radius by the divergence of (u, v, w). Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.Streamtube autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here u/v/w norm) or the bounds set in `cmin` and `cmax` Defaults to `false` when `cmin` and `cmax` are set by the user. cmax Sets the upper bound of the color domain. Value should have the same units as u/v/w norm and if set, `cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `cmin` and/or `cmax` to be equidistant to this point. Value should have the same units as u/v/w norm. Has no effect when `cauto` is `false`. cmin Sets the lower bound of the color domain. Value should have the same units as u/v/w norm and if set, `cmax` must be set as well. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.streamtube.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`cmin` and `cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.streamtube.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `tubex`, `tubey`, `tubez`, `tubeu`, `tubev`, `tubew`, `norm` and `divergence`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . lighting plotly.graph_objects.streamtube.Lighting instance or dict with compatible properties lightposition plotly.graph_objects.streamtube.Lightposition instance or dict with compatible properties maxdisplayed The maximum number of displayed segments in a streamtube. meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the surface. Please note that in the case of using high `opacity` values for example a value greater than or equal to 0.5 on two surfaces (and 0.25 with four surfaces), an overlay of multiple transparent surfaces may not perfectly be sorted in depth by the webgl API. This behavior may be improved in the near future and is subject to change. reversescale Reverses the color mapping if true. If true, `cmin` will correspond to the last color in the array and `cmax` will correspond to the first color. scene Sets a reference between this trace's 3D coordinate system and a 3D scene. If "scene" (the default value), the (x,y,z) coordinates refer to `layout.scene`. If "scene2", the (x,y,z) coordinates refer to `layout.scene2`, and so on. showscale Determines whether or not a colorbar is displayed for this trace. sizeref The scaling factor for the streamtubes. The default is 1, which avoids two max divergence tubes from touching at adjacent starting positions. starts plotly.graph_objects.streamtube.Starts instance or dict with compatible properties stream plotly.graph_objects.streamtube.Stream instance or dict with compatible properties text Sets a text element associated with this trace. If trace `hoverinfo` contains a "text" flag, this text element will be seen in all hover labels. Note that streamtube traces do not support array `text` values. u Sets the x components of the vector field. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. usrc Sets the source reference on plot.ly for u . v Sets the y components of the vector field. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). vsrc Sets the source reference on plot.ly for v . w Sets the z components of the vector field. wsrc Sets the source reference on plot.ly for w . x Sets the x coordinates of the vector field. xsrc Sets the source reference on plot.ly for x . y Sets the y coordinates of the vector field. ysrc Sets the source reference on plot.ly for y . z Sets the z coordinates of the vector field. zsrc Sets the source reference on plot.ly for z . Returns ------- Streamtube """ super(Streamtube, self).__init__("streamtube") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.Streamtube constructor must be a dict or an instance of plotly.graph_objs.Streamtube""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators import streamtube as v_streamtube # Initialize validators # --------------------- self._validators["autocolorscale"] = v_streamtube.AutocolorscaleValidator() self._validators["cauto"] = v_streamtube.CautoValidator() self._validators["cmax"] = v_streamtube.CmaxValidator() self._validators["cmid"] = v_streamtube.CmidValidator() self._validators["cmin"] = v_streamtube.CminValidator() self._validators["coloraxis"] = v_streamtube.ColoraxisValidator() self._validators["colorbar"] = v_streamtube.ColorBarValidator() self._validators["colorscale"] = v_streamtube.ColorscaleValidator() self._validators["customdata"] = v_streamtube.CustomdataValidator() self._validators["customdatasrc"] = v_streamtube.CustomdatasrcValidator() self._validators["hoverinfo"] = v_streamtube.HoverinfoValidator() self._validators["hoverinfosrc"] = v_streamtube.HoverinfosrcValidator() self._validators["hoverlabel"] = v_streamtube.HoverlabelValidator() self._validators["hovertemplate"] = v_streamtube.HovertemplateValidator() self._validators["hovertemplatesrc"] = v_streamtube.HovertemplatesrcValidator() self._validators["hovertext"] = v_streamtube.HovertextValidator() self._validators["ids"] = v_streamtube.IdsValidator() self._validators["idssrc"] = v_streamtube.IdssrcValidator() self._validators["lighting"] = v_streamtube.LightingValidator() self._validators["lightposition"] = v_streamtube.LightpositionValidator() self._validators["maxdisplayed"] = v_streamtube.MaxdisplayedValidator() self._validators["meta"] = v_streamtube.MetaValidator() self._validators["metasrc"] = v_streamtube.MetasrcValidator() self._validators["name"] = v_streamtube.NameValidator() self._validators["opacity"] = v_streamtube.OpacityValidator() self._validators["reversescale"] = v_streamtube.ReversescaleValidator() self._validators["scene"] = v_streamtube.SceneValidator() self._validators["showscale"] = v_streamtube.ShowscaleValidator() self._validators["sizeref"] = v_streamtube.SizerefValidator() self._validators["starts"] = v_streamtube.StartsValidator() self._validators["stream"] = v_streamtube.StreamValidator() self._validators["text"] = v_streamtube.TextValidator() self._validators["u"] = v_streamtube.UValidator() self._validators["uid"] = v_streamtube.UidValidator() self._validators["uirevision"] = v_streamtube.UirevisionValidator() self._validators["usrc"] = v_streamtube.UsrcValidator() self._validators["v"] = v_streamtube.VValidator() self._validators["visible"] = v_streamtube.VisibleValidator() self._validators["vsrc"] = v_streamtube.VsrcValidator() self._validators["w"] = v_streamtube.WValidator() self._validators["wsrc"] = v_streamtube.WsrcValidator() self._validators["x"] = v_streamtube.XValidator() self._validators["xsrc"] = v_streamtube.XsrcValidator() self._validators["y"] = v_streamtube.YValidator() self._validators["ysrc"] = v_streamtube.YsrcValidator() self._validators["z"] = v_streamtube.ZValidator() self._validators["zsrc"] = v_streamtube.ZsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autocolorscale", None) self["autocolorscale"] = autocolorscale if autocolorscale is not None else _v _v = arg.pop("cauto", None) self["cauto"] = cauto if cauto is not None else _v _v = arg.pop("cmax", None) self["cmax"] = cmax if cmax is not None else _v _v = arg.pop("cmid", None) self["cmid"] = cmid if cmid is not None else _v _v = arg.pop("cmin", None) self["cmin"] = cmin if cmin is not None else _v _v = arg.pop("coloraxis", None) self["coloraxis"] = coloraxis if coloraxis is not None else _v _v = arg.pop("colorbar", None) self["colorbar"] = colorbar if colorbar is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("customdata", None) self["customdata"] = customdata if customdata is not None else _v _v = arg.pop("customdatasrc", None) self["customdatasrc"] = customdatasrc if customdatasrc is not None else _v _v = arg.pop("hoverinfo", None) self["hoverinfo"] = hoverinfo if hoverinfo is not None else _v _v = arg.pop("hoverinfosrc", None) self["hoverinfosrc"] = hoverinfosrc if hoverinfosrc is not None else _v _v = arg.pop("hoverlabel", None) self["hoverlabel"] = hoverlabel if hoverlabel is not None else _v _v = arg.pop("hovertemplate", None) self["hovertemplate"] = hovertemplate if hovertemplate is not None else _v _v = arg.pop("hovertemplatesrc", None) self["hovertemplatesrc"] = ( hovertemplatesrc if hovertemplatesrc is not None else _v ) _v = arg.pop("hovertext", None) self["hovertext"] = hovertext if hovertext is not None else _v _v = arg.pop("ids", None) self["ids"] = ids if ids is not None else _v _v = arg.pop("idssrc", None) self["idssrc"] = idssrc if idssrc is not None else _v _v = arg.pop("lighting", None) self["lighting"] = lighting if lighting is not None else _v _v = arg.pop("lightposition", None) self["lightposition"] = lightposition if lightposition is not None else _v _v = arg.pop("maxdisplayed", None) self["maxdisplayed"] = maxdisplayed if maxdisplayed is not None else _v _v = arg.pop("meta", None) self["meta"] = meta if meta is not None else _v _v = arg.pop("metasrc", None) self["metasrc"] = metasrc if metasrc is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("reversescale", None) self["reversescale"] = reversescale if reversescale is not None else _v _v = arg.pop("scene", None) self["scene"] = scene if scene is not None else _v _v = arg.pop("showscale", None) self["showscale"] = showscale if showscale is not None else _v _v = arg.pop("sizeref", None) self["sizeref"] = sizeref if sizeref is not None else _v _v = arg.pop("starts", None) self["starts"] = starts if starts is not None else _v _v = arg.pop("stream", None) self["stream"] = stream if stream is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v _v = arg.pop("u", None) self["u"] = u if u is not None else _v _v = arg.pop("uid", None) self["uid"] = uid if uid is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("usrc", None) self["usrc"] = usrc if usrc is not None else _v _v = arg.pop("v", None) self["v"] = v if v is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("vsrc", None) self["vsrc"] = vsrc if vsrc is not None else _v _v = arg.pop("w", None) self["w"] = w if w is not None else _v _v = arg.pop("wsrc", None) self["wsrc"] = wsrc if wsrc is not None else _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xsrc", None) self["xsrc"] = xsrc if xsrc is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("ysrc", None) self["ysrc"] = ysrc if ysrc is not None else _v _v = arg.pop("z", None) self["z"] = z if z is not None else _v _v = arg.pop("zsrc", None) self["zsrc"] = zsrc if zsrc is not None else _v # Read-only literals # ------------------ from _plotly_utils.basevalidators import LiteralValidator self._props["type"] = "streamtube" self._validators["type"] = LiteralValidator( plotly_name="type", parent_name="streamtube", val="streamtube" ) arg.pop("type", None) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceType as _BaseTraceType import copy as _copy class Splom(_BaseTraceType): # customdata # ---------- @property def customdata(self): """ Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements The 'customdata' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["customdata"] @customdata.setter def customdata(self, val): self["customdata"] = val # customdatasrc # ------------- @property def customdatasrc(self): """ Sets the source reference on plot.ly for customdata . The 'customdatasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["customdatasrc"] @customdatasrc.setter def customdatasrc(self, val): self["customdatasrc"] = val # diagonal # -------- @property def diagonal(self): """ The 'diagonal' property is an instance of Diagonal that may be specified as: - An instance of plotly.graph_objs.splom.Diagonal - A dict of string/value properties that will be passed to the Diagonal constructor Supported dict properties: visible Determines whether or not subplots on the diagonal are displayed. Returns ------- plotly.graph_objs.splom.Diagonal """ return self["diagonal"] @diagonal.setter def diagonal(self, val): self["diagonal"] = val # dimensions # ---------- @property def dimensions(self): """ The 'dimensions' property is a tuple of instances of Dimension that may be specified as: - A list or tuple of instances of plotly.graph_objs.splom.Dimension - A list or tuple of dicts of string/value properties that will be passed to the Dimension constructor Supported dict properties: axis plotly.graph_objects.splom.dimension.Axis instance or dict with compatible properties label Sets the label corresponding to this splom dimension. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. values Sets the dimension values to be plotted. valuessrc Sets the source reference on plot.ly for values . visible Determines whether or not this dimension is shown on the graph. Note that even visible false dimension contribute to the default grid generate by this splom trace. Returns ------- tuple[plotly.graph_objs.splom.Dimension] """ return self["dimensions"] @dimensions.setter def dimensions(self, val): self["dimensions"] = val # dimensiondefaults # ----------------- @property def dimensiondefaults(self): """ When used in a template (as layout.template.data.splom.dimensiondefaults), sets the default property values to use for elements of splom.dimensions The 'dimensiondefaults' property is an instance of Dimension that may be specified as: - An instance of plotly.graph_objs.splom.Dimension - A dict of string/value properties that will be passed to the Dimension constructor Supported dict properties: Returns ------- plotly.graph_objs.splom.Dimension """ return self["dimensiondefaults"] @dimensiondefaults.setter def dimensiondefaults(self, val): self["dimensiondefaults"] = val # hoverinfo # --------- @property def hoverinfo(self): """ Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. The 'hoverinfo' property is a flaglist and may be specified as a string containing: - Any combination of ['x', 'y', 'z', 'text', 'name'] joined with '+' characters (e.g. 'x+y') OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') - A list or array of the above Returns ------- Any|numpy.ndarray """ return self["hoverinfo"] @hoverinfo.setter def hoverinfo(self, val): self["hoverinfo"] = val # hoverinfosrc # ------------ @property def hoverinfosrc(self): """ Sets the source reference on plot.ly for hoverinfo . The 'hoverinfosrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hoverinfosrc"] @hoverinfosrc.setter def hoverinfosrc(self, val): self["hoverinfosrc"] = val # hoverlabel # ---------- @property def hoverlabel(self): """ The 'hoverlabel' property is an instance of Hoverlabel that may be specified as: - An instance of plotly.graph_objs.splom.Hoverlabel - A dict of string/value properties that will be passed to the Hoverlabel constructor Supported dict properties: align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- plotly.graph_objs.splom.Hoverlabel """ return self["hoverlabel"] @hoverlabel.setter def hoverlabel(self, val): self["hoverlabel"] = val # hovertemplate # ------------- @property def hovertemplate(self): """ Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event- data. Additionally, every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. The 'hovertemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertemplate"] @hovertemplate.setter def hovertemplate(self, val): self["hovertemplate"] = val # hovertemplatesrc # ---------------- @property def hovertemplatesrc(self): """ Sets the source reference on plot.ly for hovertemplate . The 'hovertemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertemplatesrc"] @hovertemplatesrc.setter def hovertemplatesrc(self, val): self["hovertemplatesrc"] = val # hovertext # --------- @property def hovertext(self): """ Same as `text`. The 'hovertext' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertext"] @hovertext.setter def hovertext(self, val): self["hovertext"] = val # hovertextsrc # ------------ @property def hovertextsrc(self): """ Sets the source reference on plot.ly for hovertext . The 'hovertextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertextsrc"] @hovertextsrc.setter def hovertextsrc(self, val): self["hovertextsrc"] = val # ids # --- @property def ids(self): """ Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. The 'ids' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ids"] @ids.setter def ids(self, val): self["ids"] = val # idssrc # ------ @property def idssrc(self): """ Sets the source reference on plot.ly for ids . The 'idssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["idssrc"] @idssrc.setter def idssrc(self, val): self["idssrc"] = val # legendgroup # ----------- @property def legendgroup(self): """ Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. The 'legendgroup' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["legendgroup"] @legendgroup.setter def legendgroup(self, val): self["legendgroup"] = val # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.splom.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.splom.marker.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . line plotly.graph_objects.splom.marker.Line instance or dict with compatible properties opacity Sets the marker opacity. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. size Sets the marker size (in px). sizemin Has an effect only if `marker.size` is set to a numerical array. Sets the minimum size (in px) of the rendered marker points. sizemode Has an effect only if `marker.size` is set to a numerical array. Sets the rule for which the data in `size` is converted to pixels. sizeref Has an effect only if `marker.size` is set to a numerical array. Sets the scale factor used to determine the rendered size of marker points. Use with `sizemin` and `sizemode`. sizesrc Sets the source reference on plot.ly for size . symbol Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot- open" to a symbol name. symbolsrc Sets the source reference on plot.ly for symbol . Returns ------- plotly.graph_objs.splom.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # meta # ---- @property def meta(self): """ Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. The 'meta' property accepts values of any type Returns ------- Any|numpy.ndarray """ return self["meta"] @meta.setter def meta(self, val): self["meta"] = val # metasrc # ------- @property def metasrc(self): """ Sets the source reference on plot.ly for meta . The 'metasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["metasrc"] @metasrc.setter def metasrc(self, val): self["metasrc"] = val # name # ---- @property def name(self): """ Sets the trace name. The trace name appear as the legend item and on hover. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the trace. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # selected # -------- @property def selected(self): """ The 'selected' property is an instance of Selected that may be specified as: - An instance of plotly.graph_objs.splom.Selected - A dict of string/value properties that will be passed to the Selected constructor Supported dict properties: marker plotly.graph_objects.splom.selected.Marker instance or dict with compatible properties Returns ------- plotly.graph_objs.splom.Selected """ return self["selected"] @selected.setter def selected(self, val): self["selected"] = val # selectedpoints # -------------- @property def selectedpoints(self): """ Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. The 'selectedpoints' property accepts values of any type Returns ------- Any """ return self["selectedpoints"] @selectedpoints.setter def selectedpoints(self, val): self["selectedpoints"] = val # showlegend # ---------- @property def showlegend(self): """ Determines whether or not an item corresponding to this trace is shown in the legend. The 'showlegend' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showlegend"] @showlegend.setter def showlegend(self, val): self["showlegend"] = val # showlowerhalf # ------------- @property def showlowerhalf(self): """ Determines whether or not subplots on the lower half from the diagonal are displayed. The 'showlowerhalf' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showlowerhalf"] @showlowerhalf.setter def showlowerhalf(self, val): self["showlowerhalf"] = val # showupperhalf # ------------- @property def showupperhalf(self): """ Determines whether or not subplots on the upper half from the diagonal are displayed. The 'showupperhalf' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showupperhalf"] @showupperhalf.setter def showupperhalf(self, val): self["showupperhalf"] = val # stream # ------ @property def stream(self): """ The 'stream' property is an instance of Stream that may be specified as: - An instance of plotly.graph_objs.splom.Stream - A dict of string/value properties that will be passed to the Stream constructor Supported dict properties: maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- plotly.graph_objs.splom.Stream """ return self["stream"] @stream.setter def stream(self, val): self["stream"] = val # text # ---- @property def text(self): """ Sets text elements associated with each (x,y) pair to appear on hover. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["text"] @text.setter def text(self, val): self["text"] = val # textsrc # ------- @property def textsrc(self): """ Sets the source reference on plot.ly for text . The 'textsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["textsrc"] @textsrc.setter def textsrc(self, val): self["textsrc"] = val # uid # --- @property def uid(self): """ Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. The 'uid' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["uid"] @uid.setter def uid(self, val): self["uid"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # unselected # ---------- @property def unselected(self): """ The 'unselected' property is an instance of Unselected that may be specified as: - An instance of plotly.graph_objs.splom.Unselected - A dict of string/value properties that will be passed to the Unselected constructor Supported dict properties: marker plotly.graph_objects.splom.unselected.Marker instance or dict with compatible properties Returns ------- plotly.graph_objs.splom.Unselected """ return self["unselected"] @unselected.setter def unselected(self, val): self["unselected"] = val # visible # ------- @property def visible(self): """ Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). The 'visible' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'legendonly'] Returns ------- Any """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # xaxes # ----- @property def xaxes(self): """ Sets the list of x axes corresponding to dimensions of this splom trace. By default, a splom will match the first N xaxes where N is the number of input dimensions. Note that, in case where `diagonal.visible` is false and `showupperhalf` or `showlowerhalf` is false, this splom trace will generate one less x-axis and one less y-axis. The 'xaxes' property is an info array that may be specified as: * a list of elements where: The 'xaxes[i]' property is an identifier of a particular subplot, of type 'x', that may be specified as the string 'x' optionally followed by an integer >= 1 (e.g. 'x', 'x1', 'x2', 'x3', etc.) Returns ------- list """ return self["xaxes"] @xaxes.setter def xaxes(self, val): self["xaxes"] = val # yaxes # ----- @property def yaxes(self): """ Sets the list of y axes corresponding to dimensions of this splom trace. By default, a splom will match the first N yaxes where N is the number of input dimensions. Note that, in case where `diagonal.visible` is false and `showupperhalf` or `showlowerhalf` is false, this splom trace will generate one less x-axis and one less y-axis. The 'yaxes' property is an info array that may be specified as: * a list of elements where: The 'yaxes[i]' property is an identifier of a particular subplot, of type 'y', that may be specified as the string 'y' optionally followed by an integer >= 1 (e.g. 'y', 'y1', 'y2', 'y3', etc.) Returns ------- list """ return self["yaxes"] @yaxes.setter def yaxes(self, val): self["yaxes"] = val # type # ---- @property def type(self): return self._props["type"] # property parent name # -------------------- @property def _parent_path_str(self): return "" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . diagonal plotly.graph_objects.splom.Diagonal instance or dict with compatible properties dimensions A tuple of plotly.graph_objects.splom.Dimension instances or dicts with compatible properties dimensiondefaults When used in a template (as layout.template.data.splom.dimensiondefaults), sets the default property values to use for elements of splom.dimensions hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.splom.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. marker plotly.graph_objects.splom.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. selected plotly.graph_objects.splom.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. showlowerhalf Determines whether or not subplots on the lower half from the diagonal are displayed. showupperhalf Determines whether or not subplots on the upper half from the diagonal are displayed. stream plotly.graph_objects.splom.Stream instance or dict with compatible properties text Sets text elements associated with each (x,y) pair to appear on hover. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.splom.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). xaxes Sets the list of x axes corresponding to dimensions of this splom trace. By default, a splom will match the first N xaxes where N is the number of input dimensions. Note that, in case where `diagonal.visible` is false and `showupperhalf` or `showlowerhalf` is false, this splom trace will generate one less x-axis and one less y-axis. yaxes Sets the list of y axes corresponding to dimensions of this splom trace. By default, a splom will match the first N yaxes where N is the number of input dimensions. Note that, in case where `diagonal.visible` is false and `showupperhalf` or `showlowerhalf` is false, this splom trace will generate one less x-axis and one less y-axis. """ def __init__( self, arg=None, customdata=None, customdatasrc=None, diagonal=None, dimensions=None, dimensiondefaults=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, legendgroup=None, marker=None, meta=None, metasrc=None, name=None, opacity=None, selected=None, selectedpoints=None, showlegend=None, showlowerhalf=None, showupperhalf=None, stream=None, text=None, textsrc=None, uid=None, uirevision=None, unselected=None, visible=None, xaxes=None, yaxes=None, **kwargs ): """ Construct a new Splom object Splom traces generate scatter plot matrix visualizations. Each splom `dimensions` items correspond to a generated axis. Values for each of those dimensions are set in `dimensions[i].values`. Splom traces support all `scattergl` marker style attributes. Specify `layout.grid` attributes and/or layout x-axis and y-axis attributes for more control over the axis positioning and style. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.Splom customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . diagonal plotly.graph_objects.splom.Diagonal instance or dict with compatible properties dimensions A tuple of plotly.graph_objects.splom.Dimension instances or dicts with compatible properties dimensiondefaults When used in a template (as layout.template.data.splom.dimensiondefaults), sets the default property values to use for elements of splom.dimensions hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.splom.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. marker plotly.graph_objects.splom.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. selected plotly.graph_objects.splom.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. showlowerhalf Determines whether or not subplots on the lower half from the diagonal are displayed. showupperhalf Determines whether or not subplots on the upper half from the diagonal are displayed. stream plotly.graph_objects.splom.Stream instance or dict with compatible properties text Sets text elements associated with each (x,y) pair to appear on hover. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.splom.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). xaxes Sets the list of x axes corresponding to dimensions of this splom trace. By default, a splom will match the first N xaxes where N is the number of input dimensions. Note that, in case where `diagonal.visible` is false and `showupperhalf` or `showlowerhalf` is false, this splom trace will generate one less x-axis and one less y-axis. yaxes Sets the list of y axes corresponding to dimensions of this splom trace. By default, a splom will match the first N yaxes where N is the number of input dimensions. Note that, in case where `diagonal.visible` is false and `showupperhalf` or `showlowerhalf` is false, this splom trace will generate one less x-axis and one less y-axis. Returns ------- Splom """ super(Splom, self).__init__("splom") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.Splom constructor must be a dict or an instance of plotly.graph_objs.Splom""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators import splom as v_splom # Initialize validators # --------------------- self._validators["customdata"] = v_splom.CustomdataValidator() self._validators["customdatasrc"] = v_splom.CustomdatasrcValidator() self._validators["diagonal"] = v_splom.DiagonalValidator() self._validators["dimensions"] = v_splom.DimensionsValidator() self._validators["dimensiondefaults"] = v_splom.DimensionValidator() self._validators["hoverinfo"] = v_splom.HoverinfoValidator() self._validators["hoverinfosrc"] = v_splom.HoverinfosrcValidator() self._validators["hoverlabel"] = v_splom.HoverlabelValidator() self._validators["hovertemplate"] = v_splom.HovertemplateValidator() self._validators["hovertemplatesrc"] = v_splom.HovertemplatesrcValidator() self._validators["hovertext"] = v_splom.HovertextValidator() self._validators["hovertextsrc"] = v_splom.HovertextsrcValidator() self._validators["ids"] = v_splom.IdsValidator() self._validators["idssrc"] = v_splom.IdssrcValidator() self._validators["legendgroup"] = v_splom.LegendgroupValidator() self._validators["marker"] = v_splom.MarkerValidator() self._validators["meta"] = v_splom.MetaValidator() self._validators["metasrc"] = v_splom.MetasrcValidator() self._validators["name"] = v_splom.NameValidator() self._validators["opacity"] = v_splom.OpacityValidator() self._validators["selected"] = v_splom.SelectedValidator() self._validators["selectedpoints"] = v_splom.SelectedpointsValidator() self._validators["showlegend"] = v_splom.ShowlegendValidator() self._validators["showlowerhalf"] = v_splom.ShowlowerhalfValidator() self._validators["showupperhalf"] = v_splom.ShowupperhalfValidator() self._validators["stream"] = v_splom.StreamValidator() self._validators["text"] = v_splom.TextValidator() self._validators["textsrc"] = v_splom.TextsrcValidator() self._validators["uid"] = v_splom.UidValidator() self._validators["uirevision"] = v_splom.UirevisionValidator() self._validators["unselected"] = v_splom.UnselectedValidator() self._validators["visible"] = v_splom.VisibleValidator() self._validators["xaxes"] = v_splom.XaxesValidator() self._validators["yaxes"] = v_splom.YaxesValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("customdata", None) self["customdata"] = customdata if customdata is not None else _v _v = arg.pop("customdatasrc", None) self["customdatasrc"] = customdatasrc if customdatasrc is not None else _v _v = arg.pop("diagonal", None) self["diagonal"] = diagonal if diagonal is not None else _v _v = arg.pop("dimensions", None) self["dimensions"] = dimensions if dimensions is not None else _v _v = arg.pop("dimensiondefaults", None) self["dimensiondefaults"] = ( dimensiondefaults if dimensiondefaults is not None else _v ) _v = arg.pop("hoverinfo", None) self["hoverinfo"] = hoverinfo if hoverinfo is not None else _v _v = arg.pop("hoverinfosrc", None) self["hoverinfosrc"] = hoverinfosrc if hoverinfosrc is not None else _v _v = arg.pop("hoverlabel", None) self["hoverlabel"] = hoverlabel if hoverlabel is not None else _v _v = arg.pop("hovertemplate", None) self["hovertemplate"] = hovertemplate if hovertemplate is not None else _v _v = arg.pop("hovertemplatesrc", None) self["hovertemplatesrc"] = ( hovertemplatesrc if hovertemplatesrc is not None else _v ) _v = arg.pop("hovertext", None) self["hovertext"] = hovertext if hovertext is not None else _v _v = arg.pop("hovertextsrc", None) self["hovertextsrc"] = hovertextsrc if hovertextsrc is not None else _v _v = arg.pop("ids", None) self["ids"] = ids if ids is not None else _v _v = arg.pop("idssrc", None) self["idssrc"] = idssrc if idssrc is not None else _v _v = arg.pop("legendgroup", None) self["legendgroup"] = legendgroup if legendgroup is not None else _v _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v _v = arg.pop("meta", None) self["meta"] = meta if meta is not None else _v _v = arg.pop("metasrc", None) self["metasrc"] = metasrc if metasrc is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("selected", None) self["selected"] = selected if selected is not None else _v _v = arg.pop("selectedpoints", None) self["selectedpoints"] = selectedpoints if selectedpoints is not None else _v _v = arg.pop("showlegend", None) self["showlegend"] = showlegend if showlegend is not None else _v _v = arg.pop("showlowerhalf", None) self["showlowerhalf"] = showlowerhalf if showlowerhalf is not None else _v _v = arg.pop("showupperhalf", None) self["showupperhalf"] = showupperhalf if showupperhalf is not None else _v _v = arg.pop("stream", None) self["stream"] = stream if stream is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v _v = arg.pop("textsrc", None) self["textsrc"] = textsrc if textsrc is not None else _v _v = arg.pop("uid", None) self["uid"] = uid if uid is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("unselected", None) self["unselected"] = unselected if unselected is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("xaxes", None) self["xaxes"] = xaxes if xaxes is not None else _v _v = arg.pop("yaxes", None) self["yaxes"] = yaxes if yaxes is not None else _v # Read-only literals # ------------------ from _plotly_utils.basevalidators import LiteralValidator self._props["type"] = "splom" self._validators["type"] = LiteralValidator( plotly_name="type", parent_name="splom", val="splom" ) arg.pop("type", None) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceType as _BaseTraceType import copy as _copy class Scatterternary(_BaseTraceType): # a # - @property def a(self): """ Sets the quantity of component `a` in each data point. If `a`, `b`, and `c` are all provided, they need not be normalized, only the relative values matter. If only two arrays are provided they must be normalized to match `ternary.sum`. The 'a' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["a"] @a.setter def a(self, val): self["a"] = val # asrc # ---- @property def asrc(self): """ Sets the source reference on plot.ly for a . The 'asrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["asrc"] @asrc.setter def asrc(self, val): self["asrc"] = val # b # - @property def b(self): """ Sets the quantity of component `a` in each data point. If `a`, `b`, and `c` are all provided, they need not be normalized, only the relative values matter. If only two arrays are provided they must be normalized to match `ternary.sum`. The 'b' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["b"] @b.setter def b(self, val): self["b"] = val # bsrc # ---- @property def bsrc(self): """ Sets the source reference on plot.ly for b . The 'bsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bsrc"] @bsrc.setter def bsrc(self, val): self["bsrc"] = val # c # - @property def c(self): """ Sets the quantity of component `a` in each data point. If `a`, `b`, and `c` are all provided, they need not be normalized, only the relative values matter. If only two arrays are provided they must be normalized to match `ternary.sum`. The 'c' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["c"] @c.setter def c(self, val): self["c"] = val # cliponaxis # ---------- @property def cliponaxis(self): """ Determines whether or not markers and text nodes are clipped about the subplot axes. To show markers and text nodes above axis lines and tick labels, make sure to set `xaxis.layer` and `yaxis.layer` to *below traces*. The 'cliponaxis' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["cliponaxis"] @cliponaxis.setter def cliponaxis(self, val): self["cliponaxis"] = val # connectgaps # ----------- @property def connectgaps(self): """ Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. The 'connectgaps' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["connectgaps"] @connectgaps.setter def connectgaps(self, val): self["connectgaps"] = val # csrc # ---- @property def csrc(self): """ Sets the source reference on plot.ly for c . The 'csrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["csrc"] @csrc.setter def csrc(self, val): self["csrc"] = val # customdata # ---------- @property def customdata(self): """ Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements The 'customdata' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["customdata"] @customdata.setter def customdata(self, val): self["customdata"] = val # customdatasrc # ------------- @property def customdatasrc(self): """ Sets the source reference on plot.ly for customdata . The 'customdatasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["customdatasrc"] @customdatasrc.setter def customdatasrc(self, val): self["customdatasrc"] = val # fill # ---- @property def fill(self): """ Sets the area to fill with a solid color. Use with `fillcolor` if not "none". scatterternary has a subset of the options available to scatter. "toself" connects the endpoints of the trace (or each segment of the trace if it has gaps) into a closed shape. "tonext" fills the space between two traces if one completely encloses the other (eg consecutive contour lines), and behaves like "toself" if there is no trace before it. "tonext" should not be used if one trace does not enclose the other. The 'fill' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'toself', 'tonext'] Returns ------- Any """ return self["fill"] @fill.setter def fill(self, val): self["fill"] = val # fillcolor # --------- @property def fillcolor(self): """ Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. The 'fillcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["fillcolor"] @fillcolor.setter def fillcolor(self, val): self["fillcolor"] = val # hoverinfo # --------- @property def hoverinfo(self): """ Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. The 'hoverinfo' property is a flaglist and may be specified as a string containing: - Any combination of ['a', 'b', 'c', 'text', 'name'] joined with '+' characters (e.g. 'a+b') OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') - A list or array of the above Returns ------- Any|numpy.ndarray """ return self["hoverinfo"] @hoverinfo.setter def hoverinfo(self, val): self["hoverinfo"] = val # hoverinfosrc # ------------ @property def hoverinfosrc(self): """ Sets the source reference on plot.ly for hoverinfo . The 'hoverinfosrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hoverinfosrc"] @hoverinfosrc.setter def hoverinfosrc(self, val): self["hoverinfosrc"] = val # hoverlabel # ---------- @property def hoverlabel(self): """ The 'hoverlabel' property is an instance of Hoverlabel that may be specified as: - An instance of plotly.graph_objs.scatterternary.Hoverlabel - A dict of string/value properties that will be passed to the Hoverlabel constructor Supported dict properties: align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- plotly.graph_objs.scatterternary.Hoverlabel """ return self["hoverlabel"] @hoverlabel.setter def hoverlabel(self, val): self["hoverlabel"] = val # hoveron # ------- @property def hoveron(self): """ Do the hover effects highlight individual points (markers or line points) or do they highlight filled regions? If the fill is "toself" or "tonext" and there are no markers or text, then the default is "fills", otherwise it is "points". The 'hoveron' property is a flaglist and may be specified as a string containing: - Any combination of ['points', 'fills'] joined with '+' characters (e.g. 'points+fills') Returns ------- Any """ return self["hoveron"] @hoveron.setter def hoveron(self, val): self["hoveron"] = val # hovertemplate # ------------- @property def hovertemplate(self): """ Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event- data. Additionally, every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. The 'hovertemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertemplate"] @hovertemplate.setter def hovertemplate(self, val): self["hovertemplate"] = val # hovertemplatesrc # ---------------- @property def hovertemplatesrc(self): """ Sets the source reference on plot.ly for hovertemplate . The 'hovertemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertemplatesrc"] @hovertemplatesrc.setter def hovertemplatesrc(self, val): self["hovertemplatesrc"] = val # hovertext # --------- @property def hovertext(self): """ Sets hover text elements associated with each (a,b,c) point. If a single string, the same string appears over all the data points. If an array of strings, the items are mapped in order to the the data points in (a,b,c). To be seen, trace `hoverinfo` must contain a "text" flag. The 'hovertext' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertext"] @hovertext.setter def hovertext(self, val): self["hovertext"] = val # hovertextsrc # ------------ @property def hovertextsrc(self): """ Sets the source reference on plot.ly for hovertext . The 'hovertextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertextsrc"] @hovertextsrc.setter def hovertextsrc(self, val): self["hovertextsrc"] = val # ids # --- @property def ids(self): """ Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. The 'ids' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ids"] @ids.setter def ids(self, val): self["ids"] = val # idssrc # ------ @property def idssrc(self): """ Sets the source reference on plot.ly for ids . The 'idssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["idssrc"] @idssrc.setter def idssrc(self, val): self["idssrc"] = val # legendgroup # ----------- @property def legendgroup(self): """ Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. The 'legendgroup' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["legendgroup"] @legendgroup.setter def legendgroup(self, val): self["legendgroup"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.scatterternary.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: color Sets the line color. dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). shape Determines the line shape. With "spline" the lines are drawn using spline interpolation. The other available values correspond to step-wise line shapes. smoothing Has an effect only if `shape` is set to "spline" Sets the amount of smoothing. 0 corresponds to no smoothing (equivalent to a "linear" shape). width Sets the line width (in px). Returns ------- plotly.graph_objs.scatterternary.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.scatterternary.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.scatterternary.marker.Colo rBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . gradient plotly.graph_objects.scatterternary.marker.Grad ient instance or dict with compatible properties line plotly.graph_objects.scatterternary.marker.Line instance or dict with compatible properties maxdisplayed Sets a maximum number of points to be drawn on the graph. 0 corresponds to no limit. opacity Sets the marker opacity. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. size Sets the marker size (in px). sizemin Has an effect only if `marker.size` is set to a numerical array. Sets the minimum size (in px) of the rendered marker points. sizemode Has an effect only if `marker.size` is set to a numerical array. Sets the rule for which the data in `size` is converted to pixels. sizeref Has an effect only if `marker.size` is set to a numerical array. Sets the scale factor used to determine the rendered size of marker points. Use with `sizemin` and `sizemode`. sizesrc Sets the source reference on plot.ly for size . symbol Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot- open" to a symbol name. symbolsrc Sets the source reference on plot.ly for symbol . Returns ------- plotly.graph_objs.scatterternary.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # meta # ---- @property def meta(self): """ Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. The 'meta' property accepts values of any type Returns ------- Any|numpy.ndarray """ return self["meta"] @meta.setter def meta(self, val): self["meta"] = val # metasrc # ------- @property def metasrc(self): """ Sets the source reference on plot.ly for meta . The 'metasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["metasrc"] @metasrc.setter def metasrc(self, val): self["metasrc"] = val # mode # ---- @property def mode(self): """ Determines the drawing mode for this scatter trace. If the provided `mode` includes "text" then the `text` elements appear at the coordinates. Otherwise, the `text` elements appear on hover. If there are less than 20 points and the trace is not stacked then the default is "lines+markers". Otherwise, "lines". The 'mode' property is a flaglist and may be specified as a string containing: - Any combination of ['lines', 'markers', 'text'] joined with '+' characters (e.g. 'lines+markers') OR exactly one of ['none'] (e.g. 'none') Returns ------- Any """ return self["mode"] @mode.setter def mode(self, val): self["mode"] = val # name # ---- @property def name(self): """ Sets the trace name. The trace name appear as the legend item and on hover. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the trace. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # selected # -------- @property def selected(self): """ The 'selected' property is an instance of Selected that may be specified as: - An instance of plotly.graph_objs.scatterternary.Selected - A dict of string/value properties that will be passed to the Selected constructor Supported dict properties: marker plotly.graph_objects.scatterternary.selected.Ma rker instance or dict with compatible properties textfont plotly.graph_objects.scatterternary.selected.Te xtfont instance or dict with compatible properties Returns ------- plotly.graph_objs.scatterternary.Selected """ return self["selected"] @selected.setter def selected(self, val): self["selected"] = val # selectedpoints # -------------- @property def selectedpoints(self): """ Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. The 'selectedpoints' property accepts values of any type Returns ------- Any """ return self["selectedpoints"] @selectedpoints.setter def selectedpoints(self, val): self["selectedpoints"] = val # showlegend # ---------- @property def showlegend(self): """ Determines whether or not an item corresponding to this trace is shown in the legend. The 'showlegend' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showlegend"] @showlegend.setter def showlegend(self, val): self["showlegend"] = val # stream # ------ @property def stream(self): """ The 'stream' property is an instance of Stream that may be specified as: - An instance of plotly.graph_objs.scatterternary.Stream - A dict of string/value properties that will be passed to the Stream constructor Supported dict properties: maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- plotly.graph_objs.scatterternary.Stream """ return self["stream"] @stream.setter def stream(self, val): self["stream"] = val # subplot # ------- @property def subplot(self): """ Sets a reference between this trace's data coordinates and a ternary subplot. If "ternary" (the default value), the data refer to `layout.ternary`. If "ternary2", the data refer to `layout.ternary2`, and so on. The 'subplot' property is an identifier of a particular subplot, of type 'ternary', that may be specified as the string 'ternary' optionally followed by an integer >= 1 (e.g. 'ternary', 'ternary1', 'ternary2', 'ternary3', etc.) Returns ------- str """ return self["subplot"] @subplot.setter def subplot(self, val): self["subplot"] = val # sum # --- @property def sum(self): """ The number each triplet should sum to, if only two of `a`, `b`, and `c` are provided. This overrides `ternary.sum` to normalize this specific trace, but does not affect the values displayed on the axes. 0 (or missing) means to use ternary.sum The 'sum' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["sum"] @sum.setter def sum(self, val): self["sum"] = val # text # ---- @property def text(self): """ Sets text elements associated with each (a,b,c) point. If a single string, the same string appears over all the data points. If an array of strings, the items are mapped in order to the the data points in (a,b,c). If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["text"] @text.setter def text(self, val): self["text"] = val # textfont # -------- @property def textfont(self): """ Sets the text font. The 'textfont' property is an instance of Textfont that may be specified as: - An instance of plotly.graph_objs.scatterternary.Textfont - A dict of string/value properties that will be passed to the Textfont constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.scatterternary.Textfont """ return self["textfont"] @textfont.setter def textfont(self, val): self["textfont"] = val # textposition # ------------ @property def textposition(self): """ Sets the positions of the `text` elements with respects to the (x,y) coordinates. The 'textposition' property is an enumeration that may be specified as: - One of the following enumeration values: ['top left', 'top center', 'top right', 'middle left', 'middle center', 'middle right', 'bottom left', 'bottom center', 'bottom right'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["textposition"] @textposition.setter def textposition(self, val): self["textposition"] = val # textpositionsrc # --------------- @property def textpositionsrc(self): """ Sets the source reference on plot.ly for textposition . The 'textpositionsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["textpositionsrc"] @textpositionsrc.setter def textpositionsrc(self, val): self["textpositionsrc"] = val # textsrc # ------- @property def textsrc(self): """ Sets the source reference on plot.ly for text . The 'textsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["textsrc"] @textsrc.setter def textsrc(self, val): self["textsrc"] = val # texttemplate # ------------ @property def texttemplate(self): """ Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `a`, `b`, `c` and `text`. The 'texttemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["texttemplate"] @texttemplate.setter def texttemplate(self, val): self["texttemplate"] = val # texttemplatesrc # --------------- @property def texttemplatesrc(self): """ Sets the source reference on plot.ly for texttemplate . The 'texttemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["texttemplatesrc"] @texttemplatesrc.setter def texttemplatesrc(self, val): self["texttemplatesrc"] = val # uid # --- @property def uid(self): """ Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. The 'uid' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["uid"] @uid.setter def uid(self, val): self["uid"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # unselected # ---------- @property def unselected(self): """ The 'unselected' property is an instance of Unselected that may be specified as: - An instance of plotly.graph_objs.scatterternary.Unselected - A dict of string/value properties that will be passed to the Unselected constructor Supported dict properties: marker plotly.graph_objects.scatterternary.unselected. Marker instance or dict with compatible properties textfont plotly.graph_objects.scatterternary.unselected. Textfont instance or dict with compatible properties Returns ------- plotly.graph_objs.scatterternary.Unselected """ return self["unselected"] @unselected.setter def unselected(self, val): self["unselected"] = val # visible # ------- @property def visible(self): """ Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). The 'visible' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'legendonly'] Returns ------- Any """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # type # ---- @property def type(self): return self._props["type"] # property parent name # -------------------- @property def _parent_path_str(self): return "" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ a Sets the quantity of component `a` in each data point. If `a`, `b`, and `c` are all provided, they need not be normalized, only the relative values matter. If only two arrays are provided they must be normalized to match `ternary.sum`. asrc Sets the source reference on plot.ly for a . b Sets the quantity of component `a` in each data point. If `a`, `b`, and `c` are all provided, they need not be normalized, only the relative values matter. If only two arrays are provided they must be normalized to match `ternary.sum`. bsrc Sets the source reference on plot.ly for b . c Sets the quantity of component `a` in each data point. If `a`, `b`, and `c` are all provided, they need not be normalized, only the relative values matter. If only two arrays are provided they must be normalized to match `ternary.sum`. cliponaxis Determines whether or not markers and text nodes are clipped about the subplot axes. To show markers and text nodes above axis lines and tick labels, make sure to set `xaxis.layer` and `yaxis.layer` to *below traces*. connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. csrc Sets the source reference on plot.ly for c . customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . fill Sets the area to fill with a solid color. Use with `fillcolor` if not "none". scatterternary has a subset of the options available to scatter. "toself" connects the endpoints of the trace (or each segment of the trace if it has gaps) into a closed shape. "tonext" fills the space between two traces if one completely encloses the other (eg consecutive contour lines), and behaves like "toself" if there is no trace before it. "tonext" should not be used if one trace does not enclose the other. fillcolor Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.scatterternary.Hoverlabel instance or dict with compatible properties hoveron Do the hover effects highlight individual points (markers or line points) or do they highlight filled regions? If the fill is "toself" or "tonext" and there are no markers or text, then the default is "fills", otherwise it is "points". hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (a,b,c) point. If a single string, the same string appears over all the data points. If an array of strings, the items are mapped in order to the the data points in (a,b,c). To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.scatterternary.Line instance or dict with compatible properties marker plotly.graph_objects.scatterternary.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . mode Determines the drawing mode for this scatter trace. If the provided `mode` includes "text" then the `text` elements appear at the coordinates. Otherwise, the `text` elements appear on hover. If there are less than 20 points and the trace is not stacked then the default is "lines+markers". Otherwise, "lines". name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. selected plotly.graph_objects.scatterternary.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.scatterternary.Stream instance or dict with compatible properties subplot Sets a reference between this trace's data coordinates and a ternary subplot. If "ternary" (the default value), the data refer to `layout.ternary`. If "ternary2", the data refer to `layout.ternary2`, and so on. sum The number each triplet should sum to, if only two of `a`, `b`, and `c` are provided. This overrides `ternary.sum` to normalize this specific trace, but does not affect the values displayed on the axes. 0 (or missing) means to use ternary.sum text Sets text elements associated with each (a,b,c) point. If a single string, the same string appears over all the data points. If an array of strings, the items are mapped in order to the the data points in (a,b,c). If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the text font. textposition Sets the positions of the `text` elements with respects to the (x,y) coordinates. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `a`, `b`, `c` and `text`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.scatterternary.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). """ def __init__( self, arg=None, a=None, asrc=None, b=None, bsrc=None, c=None, cliponaxis=None, connectgaps=None, csrc=None, customdata=None, customdatasrc=None, fill=None, fillcolor=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hoveron=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, legendgroup=None, line=None, marker=None, meta=None, metasrc=None, mode=None, name=None, opacity=None, selected=None, selectedpoints=None, showlegend=None, stream=None, subplot=None, sum=None, text=None, textfont=None, textposition=None, textpositionsrc=None, textsrc=None, texttemplate=None, texttemplatesrc=None, uid=None, uirevision=None, unselected=None, visible=None, **kwargs ): """ Construct a new Scatterternary object Provides similar functionality to the "scatter" type but on a ternary phase diagram. The data is provided by at least two arrays out of `a`, `b`, `c` triplets. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.Scatterternary a Sets the quantity of component `a` in each data point. If `a`, `b`, and `c` are all provided, they need not be normalized, only the relative values matter. If only two arrays are provided they must be normalized to match `ternary.sum`. asrc Sets the source reference on plot.ly for a . b Sets the quantity of component `a` in each data point. If `a`, `b`, and `c` are all provided, they need not be normalized, only the relative values matter. If only two arrays are provided they must be normalized to match `ternary.sum`. bsrc Sets the source reference on plot.ly for b . c Sets the quantity of component `a` in each data point. If `a`, `b`, and `c` are all provided, they need not be normalized, only the relative values matter. If only two arrays are provided they must be normalized to match `ternary.sum`. cliponaxis Determines whether or not markers and text nodes are clipped about the subplot axes. To show markers and text nodes above axis lines and tick labels, make sure to set `xaxis.layer` and `yaxis.layer` to *below traces*. connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. csrc Sets the source reference on plot.ly for c . customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . fill Sets the area to fill with a solid color. Use with `fillcolor` if not "none". scatterternary has a subset of the options available to scatter. "toself" connects the endpoints of the trace (or each segment of the trace if it has gaps) into a closed shape. "tonext" fills the space between two traces if one completely encloses the other (eg consecutive contour lines), and behaves like "toself" if there is no trace before it. "tonext" should not be used if one trace does not enclose the other. fillcolor Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.scatterternary.Hoverlabel instance or dict with compatible properties hoveron Do the hover effects highlight individual points (markers or line points) or do they highlight filled regions? If the fill is "toself" or "tonext" and there are no markers or text, then the default is "fills", otherwise it is "points". hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (a,b,c) point. If a single string, the same string appears over all the data points. If an array of strings, the items are mapped in order to the the data points in (a,b,c). To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.scatterternary.Line instance or dict with compatible properties marker plotly.graph_objects.scatterternary.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . mode Determines the drawing mode for this scatter trace. If the provided `mode` includes "text" then the `text` elements appear at the coordinates. Otherwise, the `text` elements appear on hover. If there are less than 20 points and the trace is not stacked then the default is "lines+markers". Otherwise, "lines". name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. selected plotly.graph_objects.scatterternary.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.scatterternary.Stream instance or dict with compatible properties subplot Sets a reference between this trace's data coordinates and a ternary subplot. If "ternary" (the default value), the data refer to `layout.ternary`. If "ternary2", the data refer to `layout.ternary2`, and so on. sum The number each triplet should sum to, if only two of `a`, `b`, and `c` are provided. This overrides `ternary.sum` to normalize this specific trace, but does not affect the values displayed on the axes. 0 (or missing) means to use ternary.sum text Sets text elements associated with each (a,b,c) point. If a single string, the same string appears over all the data points. If an array of strings, the items are mapped in order to the the data points in (a,b,c). If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the text font. textposition Sets the positions of the `text` elements with respects to the (x,y) coordinates. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `a`, `b`, `c` and `text`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.scatterternary.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). Returns ------- Scatterternary """ super(Scatterternary, self).__init__("scatterternary") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.Scatterternary constructor must be a dict or an instance of plotly.graph_objs.Scatterternary""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators import scatterternary as v_scatterternary # Initialize validators # --------------------- self._validators["a"] = v_scatterternary.AValidator() self._validators["asrc"] = v_scatterternary.AsrcValidator() self._validators["b"] = v_scatterternary.BValidator() self._validators["bsrc"] = v_scatterternary.BsrcValidator() self._validators["c"] = v_scatterternary.CValidator() self._validators["cliponaxis"] = v_scatterternary.CliponaxisValidator() self._validators["connectgaps"] = v_scatterternary.ConnectgapsValidator() self._validators["csrc"] = v_scatterternary.CsrcValidator() self._validators["customdata"] = v_scatterternary.CustomdataValidator() self._validators["customdatasrc"] = v_scatterternary.CustomdatasrcValidator() self._validators["fill"] = v_scatterternary.FillValidator() self._validators["fillcolor"] = v_scatterternary.FillcolorValidator() self._validators["hoverinfo"] = v_scatterternary.HoverinfoValidator() self._validators["hoverinfosrc"] = v_scatterternary.HoverinfosrcValidator() self._validators["hoverlabel"] = v_scatterternary.HoverlabelValidator() self._validators["hoveron"] = v_scatterternary.HoveronValidator() self._validators["hovertemplate"] = v_scatterternary.HovertemplateValidator() self._validators[ "hovertemplatesrc" ] = v_scatterternary.HovertemplatesrcValidator() self._validators["hovertext"] = v_scatterternary.HovertextValidator() self._validators["hovertextsrc"] = v_scatterternary.HovertextsrcValidator() self._validators["ids"] = v_scatterternary.IdsValidator() self._validators["idssrc"] = v_scatterternary.IdssrcValidator() self._validators["legendgroup"] = v_scatterternary.LegendgroupValidator() self._validators["line"] = v_scatterternary.LineValidator() self._validators["marker"] = v_scatterternary.MarkerValidator() self._validators["meta"] = v_scatterternary.MetaValidator() self._validators["metasrc"] = v_scatterternary.MetasrcValidator() self._validators["mode"] = v_scatterternary.ModeValidator() self._validators["name"] = v_scatterternary.NameValidator() self._validators["opacity"] = v_scatterternary.OpacityValidator() self._validators["selected"] = v_scatterternary.SelectedValidator() self._validators["selectedpoints"] = v_scatterternary.SelectedpointsValidator() self._validators["showlegend"] = v_scatterternary.ShowlegendValidator() self._validators["stream"] = v_scatterternary.StreamValidator() self._validators["subplot"] = v_scatterternary.SubplotValidator() self._validators["sum"] = v_scatterternary.SumValidator() self._validators["text"] = v_scatterternary.TextValidator() self._validators["textfont"] = v_scatterternary.TextfontValidator() self._validators["textposition"] = v_scatterternary.TextpositionValidator() self._validators[ "textpositionsrc" ] = v_scatterternary.TextpositionsrcValidator() self._validators["textsrc"] = v_scatterternary.TextsrcValidator() self._validators["texttemplate"] = v_scatterternary.TexttemplateValidator() self._validators[ "texttemplatesrc" ] = v_scatterternary.TexttemplatesrcValidator() self._validators["uid"] = v_scatterternary.UidValidator() self._validators["uirevision"] = v_scatterternary.UirevisionValidator() self._validators["unselected"] = v_scatterternary.UnselectedValidator() self._validators["visible"] = v_scatterternary.VisibleValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("a", None) self["a"] = a if a is not None else _v _v = arg.pop("asrc", None) self["asrc"] = asrc if asrc is not None else _v _v = arg.pop("b", None) self["b"] = b if b is not None else _v _v = arg.pop("bsrc", None) self["bsrc"] = bsrc if bsrc is not None else _v _v = arg.pop("c", None) self["c"] = c if c is not None else _v _v = arg.pop("cliponaxis", None) self["cliponaxis"] = cliponaxis if cliponaxis is not None else _v _v = arg.pop("connectgaps", None) self["connectgaps"] = connectgaps if connectgaps is not None else _v _v = arg.pop("csrc", None) self["csrc"] = csrc if csrc is not None else _v _v = arg.pop("customdata", None) self["customdata"] = customdata if customdata is not None else _v _v = arg.pop("customdatasrc", None) self["customdatasrc"] = customdatasrc if customdatasrc is not None else _v _v = arg.pop("fill", None) self["fill"] = fill if fill is not None else _v _v = arg.pop("fillcolor", None) self["fillcolor"] = fillcolor if fillcolor is not None else _v _v = arg.pop("hoverinfo", None) self["hoverinfo"] = hoverinfo if hoverinfo is not None else _v _v = arg.pop("hoverinfosrc", None) self["hoverinfosrc"] = hoverinfosrc if hoverinfosrc is not None else _v _v = arg.pop("hoverlabel", None) self["hoverlabel"] = hoverlabel if hoverlabel is not None else _v _v = arg.pop("hoveron", None) self["hoveron"] = hoveron if hoveron is not None else _v _v = arg.pop("hovertemplate", None) self["hovertemplate"] = hovertemplate if hovertemplate is not None else _v _v = arg.pop("hovertemplatesrc", None) self["hovertemplatesrc"] = ( hovertemplatesrc if hovertemplatesrc is not None else _v ) _v = arg.pop("hovertext", None) self["hovertext"] = hovertext if hovertext is not None else _v _v = arg.pop("hovertextsrc", None) self["hovertextsrc"] = hovertextsrc if hovertextsrc is not None else _v _v = arg.pop("ids", None) self["ids"] = ids if ids is not None else _v _v = arg.pop("idssrc", None) self["idssrc"] = idssrc if idssrc is not None else _v _v = arg.pop("legendgroup", None) self["legendgroup"] = legendgroup if legendgroup is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v _v = arg.pop("meta", None) self["meta"] = meta if meta is not None else _v _v = arg.pop("metasrc", None) self["metasrc"] = metasrc if metasrc is not None else _v _v = arg.pop("mode", None) self["mode"] = mode if mode is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("selected", None) self["selected"] = selected if selected is not None else _v _v = arg.pop("selectedpoints", None) self["selectedpoints"] = selectedpoints if selectedpoints is not None else _v _v = arg.pop("showlegend", None) self["showlegend"] = showlegend if showlegend is not None else _v _v = arg.pop("stream", None) self["stream"] = stream if stream is not None else _v _v = arg.pop("subplot", None) self["subplot"] = subplot if subplot is not None else _v _v = arg.pop("sum", None) self["sum"] = sum if sum is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v _v = arg.pop("textfont", None) self["textfont"] = textfont if textfont is not None else _v _v = arg.pop("textposition", None) self["textposition"] = textposition if textposition is not None else _v _v = arg.pop("textpositionsrc", None) self["textpositionsrc"] = textpositionsrc if textpositionsrc is not None else _v _v = arg.pop("textsrc", None) self["textsrc"] = textsrc if textsrc is not None else _v _v = arg.pop("texttemplate", None) self["texttemplate"] = texttemplate if texttemplate is not None else _v _v = arg.pop("texttemplatesrc", None) self["texttemplatesrc"] = texttemplatesrc if texttemplatesrc is not None else _v _v = arg.pop("uid", None) self["uid"] = uid if uid is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("unselected", None) self["unselected"] = unselected if unselected is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v # Read-only literals # ------------------ from _plotly_utils.basevalidators import LiteralValidator self._props["type"] = "scatterternary" self._validators["type"] = LiteralValidator( plotly_name="type", parent_name="scatterternary", val="scatterternary" ) arg.pop("type", None) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceType as _BaseTraceType import copy as _copy class Scatterpolargl(_BaseTraceType): # connectgaps # ----------- @property def connectgaps(self): """ Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. The 'connectgaps' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["connectgaps"] @connectgaps.setter def connectgaps(self, val): self["connectgaps"] = val # customdata # ---------- @property def customdata(self): """ Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements The 'customdata' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["customdata"] @customdata.setter def customdata(self, val): self["customdata"] = val # customdatasrc # ------------- @property def customdatasrc(self): """ Sets the source reference on plot.ly for customdata . The 'customdatasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["customdatasrc"] @customdatasrc.setter def customdatasrc(self, val): self["customdatasrc"] = val # dr # -- @property def dr(self): """ Sets the r coordinate step. The 'dr' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["dr"] @dr.setter def dr(self, val): self["dr"] = val # dtheta # ------ @property def dtheta(self): """ Sets the theta coordinate step. By default, the `dtheta` step equals the subplot's period divided by the length of the `r` coordinates. The 'dtheta' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["dtheta"] @dtheta.setter def dtheta(self, val): self["dtheta"] = val # fill # ---- @property def fill(self): """ Sets the area to fill with a solid color. Defaults to "none" unless this trace is stacked, then it gets "tonexty" ("tonextx") if `orientation` is "v" ("h") Use with `fillcolor` if not "none". "tozerox" and "tozeroy" fill to x=0 and y=0 respectively. "tonextx" and "tonexty" fill between the endpoints of this trace and the endpoints of the trace before it, connecting those endpoints with straight lines (to make a stacked area graph); if there is no trace before it, they behave like "tozerox" and "tozeroy". "toself" connects the endpoints of the trace (or each segment of the trace if it has gaps) into a closed shape. "tonext" fills the space between two traces if one completely encloses the other (eg consecutive contour lines), and behaves like "toself" if there is no trace before it. "tonext" should not be used if one trace does not enclose the other. Traces in a `stackgroup` will only fill to (or be filled to) other traces in the same group. With multiple `stackgroup`s or some traces stacked and some not, if fill- linked traces are not already consecutive, the later ones will be pushed down in the drawing order. The 'fill' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'tozeroy', 'tozerox', 'tonexty', 'tonextx', 'toself', 'tonext'] Returns ------- Any """ return self["fill"] @fill.setter def fill(self, val): self["fill"] = val # fillcolor # --------- @property def fillcolor(self): """ Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. The 'fillcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["fillcolor"] @fillcolor.setter def fillcolor(self, val): self["fillcolor"] = val # hoverinfo # --------- @property def hoverinfo(self): """ Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. The 'hoverinfo' property is a flaglist and may be specified as a string containing: - Any combination of ['r', 'theta', 'text', 'name'] joined with '+' characters (e.g. 'r+theta') OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') - A list or array of the above Returns ------- Any|numpy.ndarray """ return self["hoverinfo"] @hoverinfo.setter def hoverinfo(self, val): self["hoverinfo"] = val # hoverinfosrc # ------------ @property def hoverinfosrc(self): """ Sets the source reference on plot.ly for hoverinfo . The 'hoverinfosrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hoverinfosrc"] @hoverinfosrc.setter def hoverinfosrc(self, val): self["hoverinfosrc"] = val # hoverlabel # ---------- @property def hoverlabel(self): """ The 'hoverlabel' property is an instance of Hoverlabel that may be specified as: - An instance of plotly.graph_objs.scatterpolargl.Hoverlabel - A dict of string/value properties that will be passed to the Hoverlabel constructor Supported dict properties: align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- plotly.graph_objs.scatterpolargl.Hoverlabel """ return self["hoverlabel"] @hoverlabel.setter def hoverlabel(self, val): self["hoverlabel"] = val # hovertemplate # ------------- @property def hovertemplate(self): """ Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event- data. Additionally, every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. The 'hovertemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertemplate"] @hovertemplate.setter def hovertemplate(self, val): self["hovertemplate"] = val # hovertemplatesrc # ---------------- @property def hovertemplatesrc(self): """ Sets the source reference on plot.ly for hovertemplate . The 'hovertemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertemplatesrc"] @hovertemplatesrc.setter def hovertemplatesrc(self, val): self["hovertemplatesrc"] = val # hovertext # --------- @property def hovertext(self): """ Sets hover text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. The 'hovertext' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertext"] @hovertext.setter def hovertext(self, val): self["hovertext"] = val # hovertextsrc # ------------ @property def hovertextsrc(self): """ Sets the source reference on plot.ly for hovertext . The 'hovertextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertextsrc"] @hovertextsrc.setter def hovertextsrc(self, val): self["hovertextsrc"] = val # ids # --- @property def ids(self): """ Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. The 'ids' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ids"] @ids.setter def ids(self, val): self["ids"] = val # idssrc # ------ @property def idssrc(self): """ Sets the source reference on plot.ly for ids . The 'idssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["idssrc"] @idssrc.setter def idssrc(self, val): self["idssrc"] = val # legendgroup # ----------- @property def legendgroup(self): """ Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. The 'legendgroup' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["legendgroup"] @legendgroup.setter def legendgroup(self, val): self["legendgroup"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.scatterpolargl.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: color Sets the line color. dash Sets the style of the lines. shape Determines the line shape. The values correspond to step-wise line shapes. width Sets the line width (in px). Returns ------- plotly.graph_objs.scatterpolargl.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.scatterpolargl.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.scatterpolargl.marker.Colo rBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . line plotly.graph_objects.scatterpolargl.marker.Line instance or dict with compatible properties opacity Sets the marker opacity. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. size Sets the marker size (in px). sizemin Has an effect only if `marker.size` is set to a numerical array. Sets the minimum size (in px) of the rendered marker points. sizemode Has an effect only if `marker.size` is set to a numerical array. Sets the rule for which the data in `size` is converted to pixels. sizeref Has an effect only if `marker.size` is set to a numerical array. Sets the scale factor used to determine the rendered size of marker points. Use with `sizemin` and `sizemode`. sizesrc Sets the source reference on plot.ly for size . symbol Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot- open" to a symbol name. symbolsrc Sets the source reference on plot.ly for symbol . Returns ------- plotly.graph_objs.scatterpolargl.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # meta # ---- @property def meta(self): """ Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. The 'meta' property accepts values of any type Returns ------- Any|numpy.ndarray """ return self["meta"] @meta.setter def meta(self, val): self["meta"] = val # metasrc # ------- @property def metasrc(self): """ Sets the source reference on plot.ly for meta . The 'metasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["metasrc"] @metasrc.setter def metasrc(self, val): self["metasrc"] = val # mode # ---- @property def mode(self): """ Determines the drawing mode for this scatter trace. If the provided `mode` includes "text" then the `text` elements appear at the coordinates. Otherwise, the `text` elements appear on hover. If there are less than 20 points and the trace is not stacked then the default is "lines+markers". Otherwise, "lines". The 'mode' property is a flaglist and may be specified as a string containing: - Any combination of ['lines', 'markers', 'text'] joined with '+' characters (e.g. 'lines+markers') OR exactly one of ['none'] (e.g. 'none') Returns ------- Any """ return self["mode"] @mode.setter def mode(self, val): self["mode"] = val # name # ---- @property def name(self): """ Sets the trace name. The trace name appear as the legend item and on hover. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the trace. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # r # - @property def r(self): """ Sets the radial coordinates The 'r' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["r"] @r.setter def r(self, val): self["r"] = val # r0 # -- @property def r0(self): """ Alternate to `r`. Builds a linear space of r coordinates. Use with `dr` where `r0` is the starting coordinate and `dr` the step. The 'r0' property accepts values of any type Returns ------- Any """ return self["r0"] @r0.setter def r0(self, val): self["r0"] = val # rsrc # ---- @property def rsrc(self): """ Sets the source reference on plot.ly for r . The 'rsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["rsrc"] @rsrc.setter def rsrc(self, val): self["rsrc"] = val # selected # -------- @property def selected(self): """ The 'selected' property is an instance of Selected that may be specified as: - An instance of plotly.graph_objs.scatterpolargl.Selected - A dict of string/value properties that will be passed to the Selected constructor Supported dict properties: marker plotly.graph_objects.scatterpolargl.selected.Ma rker instance or dict with compatible properties textfont plotly.graph_objects.scatterpolargl.selected.Te xtfont instance or dict with compatible properties Returns ------- plotly.graph_objs.scatterpolargl.Selected """ return self["selected"] @selected.setter def selected(self, val): self["selected"] = val # selectedpoints # -------------- @property def selectedpoints(self): """ Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. The 'selectedpoints' property accepts values of any type Returns ------- Any """ return self["selectedpoints"] @selectedpoints.setter def selectedpoints(self, val): self["selectedpoints"] = val # showlegend # ---------- @property def showlegend(self): """ Determines whether or not an item corresponding to this trace is shown in the legend. The 'showlegend' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showlegend"] @showlegend.setter def showlegend(self, val): self["showlegend"] = val # stream # ------ @property def stream(self): """ The 'stream' property is an instance of Stream that may be specified as: - An instance of plotly.graph_objs.scatterpolargl.Stream - A dict of string/value properties that will be passed to the Stream constructor Supported dict properties: maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- plotly.graph_objs.scatterpolargl.Stream """ return self["stream"] @stream.setter def stream(self, val): self["stream"] = val # subplot # ------- @property def subplot(self): """ Sets a reference between this trace's data coordinates and a polar subplot. If "polar" (the default value), the data refer to `layout.polar`. If "polar2", the data refer to `layout.polar2`, and so on. The 'subplot' property is an identifier of a particular subplot, of type 'polar', that may be specified as the string 'polar' optionally followed by an integer >= 1 (e.g. 'polar', 'polar1', 'polar2', 'polar3', etc.) Returns ------- str """ return self["subplot"] @subplot.setter def subplot(self, val): self["subplot"] = val # text # ---- @property def text(self): """ Sets text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["text"] @text.setter def text(self, val): self["text"] = val # textfont # -------- @property def textfont(self): """ Sets the text font. The 'textfont' property is an instance of Textfont that may be specified as: - An instance of plotly.graph_objs.scatterpolargl.Textfont - A dict of string/value properties that will be passed to the Textfont constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.scatterpolargl.Textfont """ return self["textfont"] @textfont.setter def textfont(self, val): self["textfont"] = val # textposition # ------------ @property def textposition(self): """ Sets the positions of the `text` elements with respects to the (x,y) coordinates. The 'textposition' property is an enumeration that may be specified as: - One of the following enumeration values: ['top left', 'top center', 'top right', 'middle left', 'middle center', 'middle right', 'bottom left', 'bottom center', 'bottom right'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["textposition"] @textposition.setter def textposition(self, val): self["textposition"] = val # textpositionsrc # --------------- @property def textpositionsrc(self): """ Sets the source reference on plot.ly for textposition . The 'textpositionsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["textpositionsrc"] @textpositionsrc.setter def textpositionsrc(self, val): self["textpositionsrc"] = val # textsrc # ------- @property def textsrc(self): """ Sets the source reference on plot.ly for text . The 'textsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["textsrc"] @textsrc.setter def textsrc(self, val): self["textsrc"] = val # texttemplate # ------------ @property def texttemplate(self): """ Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `r`, `theta` and `text`. The 'texttemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["texttemplate"] @texttemplate.setter def texttemplate(self, val): self["texttemplate"] = val # texttemplatesrc # --------------- @property def texttemplatesrc(self): """ Sets the source reference on plot.ly for texttemplate . The 'texttemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["texttemplatesrc"] @texttemplatesrc.setter def texttemplatesrc(self, val): self["texttemplatesrc"] = val # theta # ----- @property def theta(self): """ Sets the angular coordinates The 'theta' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["theta"] @theta.setter def theta(self, val): self["theta"] = val # theta0 # ------ @property def theta0(self): """ Alternate to `theta`. Builds a linear space of theta coordinates. Use with `dtheta` where `theta0` is the starting coordinate and `dtheta` the step. The 'theta0' property accepts values of any type Returns ------- Any """ return self["theta0"] @theta0.setter def theta0(self, val): self["theta0"] = val # thetasrc # -------- @property def thetasrc(self): """ Sets the source reference on plot.ly for theta . The 'thetasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["thetasrc"] @thetasrc.setter def thetasrc(self, val): self["thetasrc"] = val # thetaunit # --------- @property def thetaunit(self): """ Sets the unit of input "theta" values. Has an effect only when on "linear" angular axes. The 'thetaunit' property is an enumeration that may be specified as: - One of the following enumeration values: ['radians', 'degrees', 'gradians'] Returns ------- Any """ return self["thetaunit"] @thetaunit.setter def thetaunit(self, val): self["thetaunit"] = val # uid # --- @property def uid(self): """ Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. The 'uid' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["uid"] @uid.setter def uid(self, val): self["uid"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # unselected # ---------- @property def unselected(self): """ The 'unselected' property is an instance of Unselected that may be specified as: - An instance of plotly.graph_objs.scatterpolargl.Unselected - A dict of string/value properties that will be passed to the Unselected constructor Supported dict properties: marker plotly.graph_objects.scatterpolargl.unselected. Marker instance or dict with compatible properties textfont plotly.graph_objects.scatterpolargl.unselected. Textfont instance or dict with compatible properties Returns ------- plotly.graph_objs.scatterpolargl.Unselected """ return self["unselected"] @unselected.setter def unselected(self, val): self["unselected"] = val # visible # ------- @property def visible(self): """ Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). The 'visible' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'legendonly'] Returns ------- Any """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # type # ---- @property def type(self): return self._props["type"] # property parent name # -------------------- @property def _parent_path_str(self): return "" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dr Sets the r coordinate step. dtheta Sets the theta coordinate step. By default, the `dtheta` step equals the subplot's period divided by the length of the `r` coordinates. fill Sets the area to fill with a solid color. Defaults to "none" unless this trace is stacked, then it gets "tonexty" ("tonextx") if `orientation` is "v" ("h") Use with `fillcolor` if not "none". "tozerox" and "tozeroy" fill to x=0 and y=0 respectively. "tonextx" and "tonexty" fill between the endpoints of this trace and the endpoints of the trace before it, connecting those endpoints with straight lines (to make a stacked area graph); if there is no trace before it, they behave like "tozerox" and "tozeroy". "toself" connects the endpoints of the trace (or each segment of the trace if it has gaps) into a closed shape. "tonext" fills the space between two traces if one completely encloses the other (eg consecutive contour lines), and behaves like "toself" if there is no trace before it. "tonext" should not be used if one trace does not enclose the other. Traces in a `stackgroup` will only fill to (or be filled to) other traces in the same group. With multiple `stackgroup`s or some traces stacked and some not, if fill-linked traces are not already consecutive, the later ones will be pushed down in the drawing order. fillcolor Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.scatterpolargl.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.scatterpolargl.Line instance or dict with compatible properties marker plotly.graph_objects.scatterpolargl.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . mode Determines the drawing mode for this scatter trace. If the provided `mode` includes "text" then the `text` elements appear at the coordinates. Otherwise, the `text` elements appear on hover. If there are less than 20 points and the trace is not stacked then the default is "lines+markers". Otherwise, "lines". name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. r Sets the radial coordinates r0 Alternate to `r`. Builds a linear space of r coordinates. Use with `dr` where `r0` is the starting coordinate and `dr` the step. rsrc Sets the source reference on plot.ly for r . selected plotly.graph_objects.scatterpolargl.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.scatterpolargl.Stream instance or dict with compatible properties subplot Sets a reference between this trace's data coordinates and a polar subplot. If "polar" (the default value), the data refer to `layout.polar`. If "polar2", the data refer to `layout.polar2`, and so on. text Sets text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the text font. textposition Sets the positions of the `text` elements with respects to the (x,y) coordinates. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `r`, `theta` and `text`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . theta Sets the angular coordinates theta0 Alternate to `theta`. Builds a linear space of theta coordinates. Use with `dtheta` where `theta0` is the starting coordinate and `dtheta` the step. thetasrc Sets the source reference on plot.ly for theta . thetaunit Sets the unit of input "theta" values. Has an effect only when on "linear" angular axes. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.scatterpolargl.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). """ def __init__( self, arg=None, connectgaps=None, customdata=None, customdatasrc=None, dr=None, dtheta=None, fill=None, fillcolor=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, legendgroup=None, line=None, marker=None, meta=None, metasrc=None, mode=None, name=None, opacity=None, r=None, r0=None, rsrc=None, selected=None, selectedpoints=None, showlegend=None, stream=None, subplot=None, text=None, textfont=None, textposition=None, textpositionsrc=None, textsrc=None, texttemplate=None, texttemplatesrc=None, theta=None, theta0=None, thetasrc=None, thetaunit=None, uid=None, uirevision=None, unselected=None, visible=None, **kwargs ): """ Construct a new Scatterpolargl object The scatterpolargl trace type encompasses line charts, scatter charts, and bubble charts in polar coordinates using the WebGL plotting engine. The data visualized as scatter point or lines is set in `r` (radial) and `theta` (angular) coordinates Bubble charts are achieved by setting `marker.size` and/or `marker.color` to numerical arrays. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.Scatterpolargl connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dr Sets the r coordinate step. dtheta Sets the theta coordinate step. By default, the `dtheta` step equals the subplot's period divided by the length of the `r` coordinates. fill Sets the area to fill with a solid color. Defaults to "none" unless this trace is stacked, then it gets "tonexty" ("tonextx") if `orientation` is "v" ("h") Use with `fillcolor` if not "none". "tozerox" and "tozeroy" fill to x=0 and y=0 respectively. "tonextx" and "tonexty" fill between the endpoints of this trace and the endpoints of the trace before it, connecting those endpoints with straight lines (to make a stacked area graph); if there is no trace before it, they behave like "tozerox" and "tozeroy". "toself" connects the endpoints of the trace (or each segment of the trace if it has gaps) into a closed shape. "tonext" fills the space between two traces if one completely encloses the other (eg consecutive contour lines), and behaves like "toself" if there is no trace before it. "tonext" should not be used if one trace does not enclose the other. Traces in a `stackgroup` will only fill to (or be filled to) other traces in the same group. With multiple `stackgroup`s or some traces stacked and some not, if fill-linked traces are not already consecutive, the later ones will be pushed down in the drawing order. fillcolor Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.scatterpolargl.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.scatterpolargl.Line instance or dict with compatible properties marker plotly.graph_objects.scatterpolargl.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . mode Determines the drawing mode for this scatter trace. If the provided `mode` includes "text" then the `text` elements appear at the coordinates. Otherwise, the `text` elements appear on hover. If there are less than 20 points and the trace is not stacked then the default is "lines+markers". Otherwise, "lines". name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. r Sets the radial coordinates r0 Alternate to `r`. Builds a linear space of r coordinates. Use with `dr` where `r0` is the starting coordinate and `dr` the step. rsrc Sets the source reference on plot.ly for r . selected plotly.graph_objects.scatterpolargl.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.scatterpolargl.Stream instance or dict with compatible properties subplot Sets a reference between this trace's data coordinates and a polar subplot. If "polar" (the default value), the data refer to `layout.polar`. If "polar2", the data refer to `layout.polar2`, and so on. text Sets text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the text font. textposition Sets the positions of the `text` elements with respects to the (x,y) coordinates. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `r`, `theta` and `text`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . theta Sets the angular coordinates theta0 Alternate to `theta`. Builds a linear space of theta coordinates. Use with `dtheta` where `theta0` is the starting coordinate and `dtheta` the step. thetasrc Sets the source reference on plot.ly for theta . thetaunit Sets the unit of input "theta" values. Has an effect only when on "linear" angular axes. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.scatterpolargl.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). Returns ------- Scatterpolargl """ super(Scatterpolargl, self).__init__("scatterpolargl") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.Scatterpolargl constructor must be a dict or an instance of plotly.graph_objs.Scatterpolargl""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators import scatterpolargl as v_scatterpolargl # Initialize validators # --------------------- self._validators["connectgaps"] = v_scatterpolargl.ConnectgapsValidator() self._validators["customdata"] = v_scatterpolargl.CustomdataValidator() self._validators["customdatasrc"] = v_scatterpolargl.CustomdatasrcValidator() self._validators["dr"] = v_scatterpolargl.DrValidator() self._validators["dtheta"] = v_scatterpolargl.DthetaValidator() self._validators["fill"] = v_scatterpolargl.FillValidator() self._validators["fillcolor"] = v_scatterpolargl.FillcolorValidator() self._validators["hoverinfo"] = v_scatterpolargl.HoverinfoValidator() self._validators["hoverinfosrc"] = v_scatterpolargl.HoverinfosrcValidator() self._validators["hoverlabel"] = v_scatterpolargl.HoverlabelValidator() self._validators["hovertemplate"] = v_scatterpolargl.HovertemplateValidator() self._validators[ "hovertemplatesrc" ] = v_scatterpolargl.HovertemplatesrcValidator() self._validators["hovertext"] = v_scatterpolargl.HovertextValidator() self._validators["hovertextsrc"] = v_scatterpolargl.HovertextsrcValidator() self._validators["ids"] = v_scatterpolargl.IdsValidator() self._validators["idssrc"] = v_scatterpolargl.IdssrcValidator() self._validators["legendgroup"] = v_scatterpolargl.LegendgroupValidator() self._validators["line"] = v_scatterpolargl.LineValidator() self._validators["marker"] = v_scatterpolargl.MarkerValidator() self._validators["meta"] = v_scatterpolargl.MetaValidator() self._validators["metasrc"] = v_scatterpolargl.MetasrcValidator() self._validators["mode"] = v_scatterpolargl.ModeValidator() self._validators["name"] = v_scatterpolargl.NameValidator() self._validators["opacity"] = v_scatterpolargl.OpacityValidator() self._validators["r"] = v_scatterpolargl.RValidator() self._validators["r0"] = v_scatterpolargl.R0Validator() self._validators["rsrc"] = v_scatterpolargl.RsrcValidator() self._validators["selected"] = v_scatterpolargl.SelectedValidator() self._validators["selectedpoints"] = v_scatterpolargl.SelectedpointsValidator() self._validators["showlegend"] = v_scatterpolargl.ShowlegendValidator() self._validators["stream"] = v_scatterpolargl.StreamValidator() self._validators["subplot"] = v_scatterpolargl.SubplotValidator() self._validators["text"] = v_scatterpolargl.TextValidator() self._validators["textfont"] = v_scatterpolargl.TextfontValidator() self._validators["textposition"] = v_scatterpolargl.TextpositionValidator() self._validators[ "textpositionsrc" ] = v_scatterpolargl.TextpositionsrcValidator() self._validators["textsrc"] = v_scatterpolargl.TextsrcValidator() self._validators["texttemplate"] = v_scatterpolargl.TexttemplateValidator() self._validators[ "texttemplatesrc" ] = v_scatterpolargl.TexttemplatesrcValidator() self._validators["theta"] = v_scatterpolargl.ThetaValidator() self._validators["theta0"] = v_scatterpolargl.Theta0Validator() self._validators["thetasrc"] = v_scatterpolargl.ThetasrcValidator() self._validators["thetaunit"] = v_scatterpolargl.ThetaunitValidator() self._validators["uid"] = v_scatterpolargl.UidValidator() self._validators["uirevision"] = v_scatterpolargl.UirevisionValidator() self._validators["unselected"] = v_scatterpolargl.UnselectedValidator() self._validators["visible"] = v_scatterpolargl.VisibleValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("connectgaps", None) self["connectgaps"] = connectgaps if connectgaps is not None else _v _v = arg.pop("customdata", None) self["customdata"] = customdata if customdata is not None else _v _v = arg.pop("customdatasrc", None) self["customdatasrc"] = customdatasrc if customdatasrc is not None else _v _v = arg.pop("dr", None) self["dr"] = dr if dr is not None else _v _v = arg.pop("dtheta", None) self["dtheta"] = dtheta if dtheta is not None else _v _v = arg.pop("fill", None) self["fill"] = fill if fill is not None else _v _v = arg.pop("fillcolor", None) self["fillcolor"] = fillcolor if fillcolor is not None else _v _v = arg.pop("hoverinfo", None) self["hoverinfo"] = hoverinfo if hoverinfo is not None else _v _v = arg.pop("hoverinfosrc", None) self["hoverinfosrc"] = hoverinfosrc if hoverinfosrc is not None else _v _v = arg.pop("hoverlabel", None) self["hoverlabel"] = hoverlabel if hoverlabel is not None else _v _v = arg.pop("hovertemplate", None) self["hovertemplate"] = hovertemplate if hovertemplate is not None else _v _v = arg.pop("hovertemplatesrc", None) self["hovertemplatesrc"] = ( hovertemplatesrc if hovertemplatesrc is not None else _v ) _v = arg.pop("hovertext", None) self["hovertext"] = hovertext if hovertext is not None else _v _v = arg.pop("hovertextsrc", None) self["hovertextsrc"] = hovertextsrc if hovertextsrc is not None else _v _v = arg.pop("ids", None) self["ids"] = ids if ids is not None else _v _v = arg.pop("idssrc", None) self["idssrc"] = idssrc if idssrc is not None else _v _v = arg.pop("legendgroup", None) self["legendgroup"] = legendgroup if legendgroup is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v _v = arg.pop("meta", None) self["meta"] = meta if meta is not None else _v _v = arg.pop("metasrc", None) self["metasrc"] = metasrc if metasrc is not None else _v _v = arg.pop("mode", None) self["mode"] = mode if mode is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("r", None) self["r"] = r if r is not None else _v _v = arg.pop("r0", None) self["r0"] = r0 if r0 is not None else _v _v = arg.pop("rsrc", None) self["rsrc"] = rsrc if rsrc is not None else _v _v = arg.pop("selected", None) self["selected"] = selected if selected is not None else _v _v = arg.pop("selectedpoints", None) self["selectedpoints"] = selectedpoints if selectedpoints is not None else _v _v = arg.pop("showlegend", None) self["showlegend"] = showlegend if showlegend is not None else _v _v = arg.pop("stream", None) self["stream"] = stream if stream is not None else _v _v = arg.pop("subplot", None) self["subplot"] = subplot if subplot is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v _v = arg.pop("textfont", None) self["textfont"] = textfont if textfont is not None else _v _v = arg.pop("textposition", None) self["textposition"] = textposition if textposition is not None else _v _v = arg.pop("textpositionsrc", None) self["textpositionsrc"] = textpositionsrc if textpositionsrc is not None else _v _v = arg.pop("textsrc", None) self["textsrc"] = textsrc if textsrc is not None else _v _v = arg.pop("texttemplate", None) self["texttemplate"] = texttemplate if texttemplate is not None else _v _v = arg.pop("texttemplatesrc", None) self["texttemplatesrc"] = texttemplatesrc if texttemplatesrc is not None else _v _v = arg.pop("theta", None) self["theta"] = theta if theta is not None else _v _v = arg.pop("theta0", None) self["theta0"] = theta0 if theta0 is not None else _v _v = arg.pop("thetasrc", None) self["thetasrc"] = thetasrc if thetasrc is not None else _v _v = arg.pop("thetaunit", None) self["thetaunit"] = thetaunit if thetaunit is not None else _v _v = arg.pop("uid", None) self["uid"] = uid if uid is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("unselected", None) self["unselected"] = unselected if unselected is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v # Read-only literals # ------------------ from _plotly_utils.basevalidators import LiteralValidator self._props["type"] = "scatterpolargl" self._validators["type"] = LiteralValidator( plotly_name="type", parent_name="scatterpolargl", val="scatterpolargl" ) arg.pop("type", None) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceType as _BaseTraceType import copy as _copy class Scatterpolar(_BaseTraceType): # cliponaxis # ---------- @property def cliponaxis(self): """ Determines whether or not markers and text nodes are clipped about the subplot axes. To show markers and text nodes above axis lines and tick labels, make sure to set `xaxis.layer` and `yaxis.layer` to *below traces*. The 'cliponaxis' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["cliponaxis"] @cliponaxis.setter def cliponaxis(self, val): self["cliponaxis"] = val # connectgaps # ----------- @property def connectgaps(self): """ Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. The 'connectgaps' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["connectgaps"] @connectgaps.setter def connectgaps(self, val): self["connectgaps"] = val # customdata # ---------- @property def customdata(self): """ Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements The 'customdata' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["customdata"] @customdata.setter def customdata(self, val): self["customdata"] = val # customdatasrc # ------------- @property def customdatasrc(self): """ Sets the source reference on plot.ly for customdata . The 'customdatasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["customdatasrc"] @customdatasrc.setter def customdatasrc(self, val): self["customdatasrc"] = val # dr # -- @property def dr(self): """ Sets the r coordinate step. The 'dr' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["dr"] @dr.setter def dr(self, val): self["dr"] = val # dtheta # ------ @property def dtheta(self): """ Sets the theta coordinate step. By default, the `dtheta` step equals the subplot's period divided by the length of the `r` coordinates. The 'dtheta' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["dtheta"] @dtheta.setter def dtheta(self, val): self["dtheta"] = val # fill # ---- @property def fill(self): """ Sets the area to fill with a solid color. Use with `fillcolor` if not "none". scatterpolar has a subset of the options available to scatter. "toself" connects the endpoints of the trace (or each segment of the trace if it has gaps) into a closed shape. "tonext" fills the space between two traces if one completely encloses the other (eg consecutive contour lines), and behaves like "toself" if there is no trace before it. "tonext" should not be used if one trace does not enclose the other. The 'fill' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'toself', 'tonext'] Returns ------- Any """ return self["fill"] @fill.setter def fill(self, val): self["fill"] = val # fillcolor # --------- @property def fillcolor(self): """ Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. The 'fillcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["fillcolor"] @fillcolor.setter def fillcolor(self, val): self["fillcolor"] = val # hoverinfo # --------- @property def hoverinfo(self): """ Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. The 'hoverinfo' property is a flaglist and may be specified as a string containing: - Any combination of ['r', 'theta', 'text', 'name'] joined with '+' characters (e.g. 'r+theta') OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') - A list or array of the above Returns ------- Any|numpy.ndarray """ return self["hoverinfo"] @hoverinfo.setter def hoverinfo(self, val): self["hoverinfo"] = val # hoverinfosrc # ------------ @property def hoverinfosrc(self): """ Sets the source reference on plot.ly for hoverinfo . The 'hoverinfosrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hoverinfosrc"] @hoverinfosrc.setter def hoverinfosrc(self, val): self["hoverinfosrc"] = val # hoverlabel # ---------- @property def hoverlabel(self): """ The 'hoverlabel' property is an instance of Hoverlabel that may be specified as: - An instance of plotly.graph_objs.scatterpolar.Hoverlabel - A dict of string/value properties that will be passed to the Hoverlabel constructor Supported dict properties: align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- plotly.graph_objs.scatterpolar.Hoverlabel """ return self["hoverlabel"] @hoverlabel.setter def hoverlabel(self, val): self["hoverlabel"] = val # hoveron # ------- @property def hoveron(self): """ Do the hover effects highlight individual points (markers or line points) or do they highlight filled regions? If the fill is "toself" or "tonext" and there are no markers or text, then the default is "fills", otherwise it is "points". The 'hoveron' property is a flaglist and may be specified as a string containing: - Any combination of ['points', 'fills'] joined with '+' characters (e.g. 'points+fills') Returns ------- Any """ return self["hoveron"] @hoveron.setter def hoveron(self, val): self["hoveron"] = val # hovertemplate # ------------- @property def hovertemplate(self): """ Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event- data. Additionally, every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. The 'hovertemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertemplate"] @hovertemplate.setter def hovertemplate(self, val): self["hovertemplate"] = val # hovertemplatesrc # ---------------- @property def hovertemplatesrc(self): """ Sets the source reference on plot.ly for hovertemplate . The 'hovertemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertemplatesrc"] @hovertemplatesrc.setter def hovertemplatesrc(self, val): self["hovertemplatesrc"] = val # hovertext # --------- @property def hovertext(self): """ Sets hover text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. The 'hovertext' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertext"] @hovertext.setter def hovertext(self, val): self["hovertext"] = val # hovertextsrc # ------------ @property def hovertextsrc(self): """ Sets the source reference on plot.ly for hovertext . The 'hovertextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertextsrc"] @hovertextsrc.setter def hovertextsrc(self, val): self["hovertextsrc"] = val # ids # --- @property def ids(self): """ Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. The 'ids' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ids"] @ids.setter def ids(self, val): self["ids"] = val # idssrc # ------ @property def idssrc(self): """ Sets the source reference on plot.ly for ids . The 'idssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["idssrc"] @idssrc.setter def idssrc(self, val): self["idssrc"] = val # legendgroup # ----------- @property def legendgroup(self): """ Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. The 'legendgroup' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["legendgroup"] @legendgroup.setter def legendgroup(self, val): self["legendgroup"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.scatterpolar.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: color Sets the line color. dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). shape Determines the line shape. With "spline" the lines are drawn using spline interpolation. The other available values correspond to step-wise line shapes. smoothing Has an effect only if `shape` is set to "spline" Sets the amount of smoothing. 0 corresponds to no smoothing (equivalent to a "linear" shape). width Sets the line width (in px). Returns ------- plotly.graph_objs.scatterpolar.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.scatterpolar.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.scatterpolar.marker.ColorB ar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . gradient plotly.graph_objects.scatterpolar.marker.Gradie nt instance or dict with compatible properties line plotly.graph_objects.scatterpolar.marker.Line instance or dict with compatible properties maxdisplayed Sets a maximum number of points to be drawn on the graph. 0 corresponds to no limit. opacity Sets the marker opacity. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. size Sets the marker size (in px). sizemin Has an effect only if `marker.size` is set to a numerical array. Sets the minimum size (in px) of the rendered marker points. sizemode Has an effect only if `marker.size` is set to a numerical array. Sets the rule for which the data in `size` is converted to pixels. sizeref Has an effect only if `marker.size` is set to a numerical array. Sets the scale factor used to determine the rendered size of marker points. Use with `sizemin` and `sizemode`. sizesrc Sets the source reference on plot.ly for size . symbol Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot- open" to a symbol name. symbolsrc Sets the source reference on plot.ly for symbol . Returns ------- plotly.graph_objs.scatterpolar.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # meta # ---- @property def meta(self): """ Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. The 'meta' property accepts values of any type Returns ------- Any|numpy.ndarray """ return self["meta"] @meta.setter def meta(self, val): self["meta"] = val # metasrc # ------- @property def metasrc(self): """ Sets the source reference on plot.ly for meta . The 'metasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["metasrc"] @metasrc.setter def metasrc(self, val): self["metasrc"] = val # mode # ---- @property def mode(self): """ Determines the drawing mode for this scatter trace. If the provided `mode` includes "text" then the `text` elements appear at the coordinates. Otherwise, the `text` elements appear on hover. If there are less than 20 points and the trace is not stacked then the default is "lines+markers". Otherwise, "lines". The 'mode' property is a flaglist and may be specified as a string containing: - Any combination of ['lines', 'markers', 'text'] joined with '+' characters (e.g. 'lines+markers') OR exactly one of ['none'] (e.g. 'none') Returns ------- Any """ return self["mode"] @mode.setter def mode(self, val): self["mode"] = val # name # ---- @property def name(self): """ Sets the trace name. The trace name appear as the legend item and on hover. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the trace. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # r # - @property def r(self): """ Sets the radial coordinates The 'r' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["r"] @r.setter def r(self, val): self["r"] = val # r0 # -- @property def r0(self): """ Alternate to `r`. Builds a linear space of r coordinates. Use with `dr` where `r0` is the starting coordinate and `dr` the step. The 'r0' property accepts values of any type Returns ------- Any """ return self["r0"] @r0.setter def r0(self, val): self["r0"] = val # rsrc # ---- @property def rsrc(self): """ Sets the source reference on plot.ly for r . The 'rsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["rsrc"] @rsrc.setter def rsrc(self, val): self["rsrc"] = val # selected # -------- @property def selected(self): """ The 'selected' property is an instance of Selected that may be specified as: - An instance of plotly.graph_objs.scatterpolar.Selected - A dict of string/value properties that will be passed to the Selected constructor Supported dict properties: marker plotly.graph_objects.scatterpolar.selected.Mark er instance or dict with compatible properties textfont plotly.graph_objects.scatterpolar.selected.Text font instance or dict with compatible properties Returns ------- plotly.graph_objs.scatterpolar.Selected """ return self["selected"] @selected.setter def selected(self, val): self["selected"] = val # selectedpoints # -------------- @property def selectedpoints(self): """ Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. The 'selectedpoints' property accepts values of any type Returns ------- Any """ return self["selectedpoints"] @selectedpoints.setter def selectedpoints(self, val): self["selectedpoints"] = val # showlegend # ---------- @property def showlegend(self): """ Determines whether or not an item corresponding to this trace is shown in the legend. The 'showlegend' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showlegend"] @showlegend.setter def showlegend(self, val): self["showlegend"] = val # stream # ------ @property def stream(self): """ The 'stream' property is an instance of Stream that may be specified as: - An instance of plotly.graph_objs.scatterpolar.Stream - A dict of string/value properties that will be passed to the Stream constructor Supported dict properties: maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- plotly.graph_objs.scatterpolar.Stream """ return self["stream"] @stream.setter def stream(self, val): self["stream"] = val # subplot # ------- @property def subplot(self): """ Sets a reference between this trace's data coordinates and a polar subplot. If "polar" (the default value), the data refer to `layout.polar`. If "polar2", the data refer to `layout.polar2`, and so on. The 'subplot' property is an identifier of a particular subplot, of type 'polar', that may be specified as the string 'polar' optionally followed by an integer >= 1 (e.g. 'polar', 'polar1', 'polar2', 'polar3', etc.) Returns ------- str """ return self["subplot"] @subplot.setter def subplot(self, val): self["subplot"] = val # text # ---- @property def text(self): """ Sets text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["text"] @text.setter def text(self, val): self["text"] = val # textfont # -------- @property def textfont(self): """ Sets the text font. The 'textfont' property is an instance of Textfont that may be specified as: - An instance of plotly.graph_objs.scatterpolar.Textfont - A dict of string/value properties that will be passed to the Textfont constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.scatterpolar.Textfont """ return self["textfont"] @textfont.setter def textfont(self, val): self["textfont"] = val # textposition # ------------ @property def textposition(self): """ Sets the positions of the `text` elements with respects to the (x,y) coordinates. The 'textposition' property is an enumeration that may be specified as: - One of the following enumeration values: ['top left', 'top center', 'top right', 'middle left', 'middle center', 'middle right', 'bottom left', 'bottom center', 'bottom right'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["textposition"] @textposition.setter def textposition(self, val): self["textposition"] = val # textpositionsrc # --------------- @property def textpositionsrc(self): """ Sets the source reference on plot.ly for textposition . The 'textpositionsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["textpositionsrc"] @textpositionsrc.setter def textpositionsrc(self, val): self["textpositionsrc"] = val # textsrc # ------- @property def textsrc(self): """ Sets the source reference on plot.ly for text . The 'textsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["textsrc"] @textsrc.setter def textsrc(self, val): self["textsrc"] = val # texttemplate # ------------ @property def texttemplate(self): """ Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `r`, `theta` and `text`. The 'texttemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["texttemplate"] @texttemplate.setter def texttemplate(self, val): self["texttemplate"] = val # texttemplatesrc # --------------- @property def texttemplatesrc(self): """ Sets the source reference on plot.ly for texttemplate . The 'texttemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["texttemplatesrc"] @texttemplatesrc.setter def texttemplatesrc(self, val): self["texttemplatesrc"] = val # theta # ----- @property def theta(self): """ Sets the angular coordinates The 'theta' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["theta"] @theta.setter def theta(self, val): self["theta"] = val # theta0 # ------ @property def theta0(self): """ Alternate to `theta`. Builds a linear space of theta coordinates. Use with `dtheta` where `theta0` is the starting coordinate and `dtheta` the step. The 'theta0' property accepts values of any type Returns ------- Any """ return self["theta0"] @theta0.setter def theta0(self, val): self["theta0"] = val # thetasrc # -------- @property def thetasrc(self): """ Sets the source reference on plot.ly for theta . The 'thetasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["thetasrc"] @thetasrc.setter def thetasrc(self, val): self["thetasrc"] = val # thetaunit # --------- @property def thetaunit(self): """ Sets the unit of input "theta" values. Has an effect only when on "linear" angular axes. The 'thetaunit' property is an enumeration that may be specified as: - One of the following enumeration values: ['radians', 'degrees', 'gradians'] Returns ------- Any """ return self["thetaunit"] @thetaunit.setter def thetaunit(self, val): self["thetaunit"] = val # uid # --- @property def uid(self): """ Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. The 'uid' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["uid"] @uid.setter def uid(self, val): self["uid"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # unselected # ---------- @property def unselected(self): """ The 'unselected' property is an instance of Unselected that may be specified as: - An instance of plotly.graph_objs.scatterpolar.Unselected - A dict of string/value properties that will be passed to the Unselected constructor Supported dict properties: marker plotly.graph_objects.scatterpolar.unselected.Ma rker instance or dict with compatible properties textfont plotly.graph_objects.scatterpolar.unselected.Te xtfont instance or dict with compatible properties Returns ------- plotly.graph_objs.scatterpolar.Unselected """ return self["unselected"] @unselected.setter def unselected(self, val): self["unselected"] = val # visible # ------- @property def visible(self): """ Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). The 'visible' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'legendonly'] Returns ------- Any """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # type # ---- @property def type(self): return self._props["type"] # property parent name # -------------------- @property def _parent_path_str(self): return "" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ cliponaxis Determines whether or not markers and text nodes are clipped about the subplot axes. To show markers and text nodes above axis lines and tick labels, make sure to set `xaxis.layer` and `yaxis.layer` to *below traces*. connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dr Sets the r coordinate step. dtheta Sets the theta coordinate step. By default, the `dtheta` step equals the subplot's period divided by the length of the `r` coordinates. fill Sets the area to fill with a solid color. Use with `fillcolor` if not "none". scatterpolar has a subset of the options available to scatter. "toself" connects the endpoints of the trace (or each segment of the trace if it has gaps) into a closed shape. "tonext" fills the space between two traces if one completely encloses the other (eg consecutive contour lines), and behaves like "toself" if there is no trace before it. "tonext" should not be used if one trace does not enclose the other. fillcolor Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.scatterpolar.Hoverlabel instance or dict with compatible properties hoveron Do the hover effects highlight individual points (markers or line points) or do they highlight filled regions? If the fill is "toself" or "tonext" and there are no markers or text, then the default is "fills", otherwise it is "points". hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.scatterpolar.Line instance or dict with compatible properties marker plotly.graph_objects.scatterpolar.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . mode Determines the drawing mode for this scatter trace. If the provided `mode` includes "text" then the `text` elements appear at the coordinates. Otherwise, the `text` elements appear on hover. If there are less than 20 points and the trace is not stacked then the default is "lines+markers". Otherwise, "lines". name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. r Sets the radial coordinates r0 Alternate to `r`. Builds a linear space of r coordinates. Use with `dr` where `r0` is the starting coordinate and `dr` the step. rsrc Sets the source reference on plot.ly for r . selected plotly.graph_objects.scatterpolar.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.scatterpolar.Stream instance or dict with compatible properties subplot Sets a reference between this trace's data coordinates and a polar subplot. If "polar" (the default value), the data refer to `layout.polar`. If "polar2", the data refer to `layout.polar2`, and so on. text Sets text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the text font. textposition Sets the positions of the `text` elements with respects to the (x,y) coordinates. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `r`, `theta` and `text`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . theta Sets the angular coordinates theta0 Alternate to `theta`. Builds a linear space of theta coordinates. Use with `dtheta` where `theta0` is the starting coordinate and `dtheta` the step. thetasrc Sets the source reference on plot.ly for theta . thetaunit Sets the unit of input "theta" values. Has an effect only when on "linear" angular axes. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.scatterpolar.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). """ def __init__( self, arg=None, cliponaxis=None, connectgaps=None, customdata=None, customdatasrc=None, dr=None, dtheta=None, fill=None, fillcolor=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hoveron=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, legendgroup=None, line=None, marker=None, meta=None, metasrc=None, mode=None, name=None, opacity=None, r=None, r0=None, rsrc=None, selected=None, selectedpoints=None, showlegend=None, stream=None, subplot=None, text=None, textfont=None, textposition=None, textpositionsrc=None, textsrc=None, texttemplate=None, texttemplatesrc=None, theta=None, theta0=None, thetasrc=None, thetaunit=None, uid=None, uirevision=None, unselected=None, visible=None, **kwargs ): """ Construct a new Scatterpolar object The scatterpolar trace type encompasses line charts, scatter charts, text charts, and bubble charts in polar coordinates. The data visualized as scatter point or lines is set in `r` (radial) and `theta` (angular) coordinates Text (appearing either on the chart or on hover only) is via `text`. Bubble charts are achieved by setting `marker.size` and/or `marker.color` to numerical arrays. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.Scatterpolar cliponaxis Determines whether or not markers and text nodes are clipped about the subplot axes. To show markers and text nodes above axis lines and tick labels, make sure to set `xaxis.layer` and `yaxis.layer` to *below traces*. connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dr Sets the r coordinate step. dtheta Sets the theta coordinate step. By default, the `dtheta` step equals the subplot's period divided by the length of the `r` coordinates. fill Sets the area to fill with a solid color. Use with `fillcolor` if not "none". scatterpolar has a subset of the options available to scatter. "toself" connects the endpoints of the trace (or each segment of the trace if it has gaps) into a closed shape. "tonext" fills the space between two traces if one completely encloses the other (eg consecutive contour lines), and behaves like "toself" if there is no trace before it. "tonext" should not be used if one trace does not enclose the other. fillcolor Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.scatterpolar.Hoverlabel instance or dict with compatible properties hoveron Do the hover effects highlight individual points (markers or line points) or do they highlight filled regions? If the fill is "toself" or "tonext" and there are no markers or text, then the default is "fills", otherwise it is "points". hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.scatterpolar.Line instance or dict with compatible properties marker plotly.graph_objects.scatterpolar.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . mode Determines the drawing mode for this scatter trace. If the provided `mode` includes "text" then the `text` elements appear at the coordinates. Otherwise, the `text` elements appear on hover. If there are less than 20 points and the trace is not stacked then the default is "lines+markers". Otherwise, "lines". name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. r Sets the radial coordinates r0 Alternate to `r`. Builds a linear space of r coordinates. Use with `dr` where `r0` is the starting coordinate and `dr` the step. rsrc Sets the source reference on plot.ly for r . selected plotly.graph_objects.scatterpolar.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.scatterpolar.Stream instance or dict with compatible properties subplot Sets a reference between this trace's data coordinates and a polar subplot. If "polar" (the default value), the data refer to `layout.polar`. If "polar2", the data refer to `layout.polar2`, and so on. text Sets text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the text font. textposition Sets the positions of the `text` elements with respects to the (x,y) coordinates. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `r`, `theta` and `text`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . theta Sets the angular coordinates theta0 Alternate to `theta`. Builds a linear space of theta coordinates. Use with `dtheta` where `theta0` is the starting coordinate and `dtheta` the step. thetasrc Sets the source reference on plot.ly for theta . thetaunit Sets the unit of input "theta" values. Has an effect only when on "linear" angular axes. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.scatterpolar.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). Returns ------- Scatterpolar """ super(Scatterpolar, self).__init__("scatterpolar") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.Scatterpolar constructor must be a dict or an instance of plotly.graph_objs.Scatterpolar""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators import scatterpolar as v_scatterpolar # Initialize validators # --------------------- self._validators["cliponaxis"] = v_scatterpolar.CliponaxisValidator() self._validators["connectgaps"] = v_scatterpolar.ConnectgapsValidator() self._validators["customdata"] = v_scatterpolar.CustomdataValidator() self._validators["customdatasrc"] = v_scatterpolar.CustomdatasrcValidator() self._validators["dr"] = v_scatterpolar.DrValidator() self._validators["dtheta"] = v_scatterpolar.DthetaValidator() self._validators["fill"] = v_scatterpolar.FillValidator() self._validators["fillcolor"] = v_scatterpolar.FillcolorValidator() self._validators["hoverinfo"] = v_scatterpolar.HoverinfoValidator() self._validators["hoverinfosrc"] = v_scatterpolar.HoverinfosrcValidator() self._validators["hoverlabel"] = v_scatterpolar.HoverlabelValidator() self._validators["hoveron"] = v_scatterpolar.HoveronValidator() self._validators["hovertemplate"] = v_scatterpolar.HovertemplateValidator() self._validators[ "hovertemplatesrc" ] = v_scatterpolar.HovertemplatesrcValidator() self._validators["hovertext"] = v_scatterpolar.HovertextValidator() self._validators["hovertextsrc"] = v_scatterpolar.HovertextsrcValidator() self._validators["ids"] = v_scatterpolar.IdsValidator() self._validators["idssrc"] = v_scatterpolar.IdssrcValidator() self._validators["legendgroup"] = v_scatterpolar.LegendgroupValidator() self._validators["line"] = v_scatterpolar.LineValidator() self._validators["marker"] = v_scatterpolar.MarkerValidator() self._validators["meta"] = v_scatterpolar.MetaValidator() self._validators["metasrc"] = v_scatterpolar.MetasrcValidator() self._validators["mode"] = v_scatterpolar.ModeValidator() self._validators["name"] = v_scatterpolar.NameValidator() self._validators["opacity"] = v_scatterpolar.OpacityValidator() self._validators["r"] = v_scatterpolar.RValidator() self._validators["r0"] = v_scatterpolar.R0Validator() self._validators["rsrc"] = v_scatterpolar.RsrcValidator() self._validators["selected"] = v_scatterpolar.SelectedValidator() self._validators["selectedpoints"] = v_scatterpolar.SelectedpointsValidator() self._validators["showlegend"] = v_scatterpolar.ShowlegendValidator() self._validators["stream"] = v_scatterpolar.StreamValidator() self._validators["subplot"] = v_scatterpolar.SubplotValidator() self._validators["text"] = v_scatterpolar.TextValidator() self._validators["textfont"] = v_scatterpolar.TextfontValidator() self._validators["textposition"] = v_scatterpolar.TextpositionValidator() self._validators["textpositionsrc"] = v_scatterpolar.TextpositionsrcValidator() self._validators["textsrc"] = v_scatterpolar.TextsrcValidator() self._validators["texttemplate"] = v_scatterpolar.TexttemplateValidator() self._validators["texttemplatesrc"] = v_scatterpolar.TexttemplatesrcValidator() self._validators["theta"] = v_scatterpolar.ThetaValidator() self._validators["theta0"] = v_scatterpolar.Theta0Validator() self._validators["thetasrc"] = v_scatterpolar.ThetasrcValidator() self._validators["thetaunit"] = v_scatterpolar.ThetaunitValidator() self._validators["uid"] = v_scatterpolar.UidValidator() self._validators["uirevision"] = v_scatterpolar.UirevisionValidator() self._validators["unselected"] = v_scatterpolar.UnselectedValidator() self._validators["visible"] = v_scatterpolar.VisibleValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("cliponaxis", None) self["cliponaxis"] = cliponaxis if cliponaxis is not None else _v _v = arg.pop("connectgaps", None) self["connectgaps"] = connectgaps if connectgaps is not None else _v _v = arg.pop("customdata", None) self["customdata"] = customdata if customdata is not None else _v _v = arg.pop("customdatasrc", None) self["customdatasrc"] = customdatasrc if customdatasrc is not None else _v _v = arg.pop("dr", None) self["dr"] = dr if dr is not None else _v _v = arg.pop("dtheta", None) self["dtheta"] = dtheta if dtheta is not None else _v _v = arg.pop("fill", None) self["fill"] = fill if fill is not None else _v _v = arg.pop("fillcolor", None) self["fillcolor"] = fillcolor if fillcolor is not None else _v _v = arg.pop("hoverinfo", None) self["hoverinfo"] = hoverinfo if hoverinfo is not None else _v _v = arg.pop("hoverinfosrc", None) self["hoverinfosrc"] = hoverinfosrc if hoverinfosrc is not None else _v _v = arg.pop("hoverlabel", None) self["hoverlabel"] = hoverlabel if hoverlabel is not None else _v _v = arg.pop("hoveron", None) self["hoveron"] = hoveron if hoveron is not None else _v _v = arg.pop("hovertemplate", None) self["hovertemplate"] = hovertemplate if hovertemplate is not None else _v _v = arg.pop("hovertemplatesrc", None) self["hovertemplatesrc"] = ( hovertemplatesrc if hovertemplatesrc is not None else _v ) _v = arg.pop("hovertext", None) self["hovertext"] = hovertext if hovertext is not None else _v _v = arg.pop("hovertextsrc", None) self["hovertextsrc"] = hovertextsrc if hovertextsrc is not None else _v _v = arg.pop("ids", None) self["ids"] = ids if ids is not None else _v _v = arg.pop("idssrc", None) self["idssrc"] = idssrc if idssrc is not None else _v _v = arg.pop("legendgroup", None) self["legendgroup"] = legendgroup if legendgroup is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v _v = arg.pop("meta", None) self["meta"] = meta if meta is not None else _v _v = arg.pop("metasrc", None) self["metasrc"] = metasrc if metasrc is not None else _v _v = arg.pop("mode", None) self["mode"] = mode if mode is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("r", None) self["r"] = r if r is not None else _v _v = arg.pop("r0", None) self["r0"] = r0 if r0 is not None else _v _v = arg.pop("rsrc", None) self["rsrc"] = rsrc if rsrc is not None else _v _v = arg.pop("selected", None) self["selected"] = selected if selected is not None else _v _v = arg.pop("selectedpoints", None) self["selectedpoints"] = selectedpoints if selectedpoints is not None else _v _v = arg.pop("showlegend", None) self["showlegend"] = showlegend if showlegend is not None else _v _v = arg.pop("stream", None) self["stream"] = stream if stream is not None else _v _v = arg.pop("subplot", None) self["subplot"] = subplot if subplot is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v _v = arg.pop("textfont", None) self["textfont"] = textfont if textfont is not None else _v _v = arg.pop("textposition", None) self["textposition"] = textposition if textposition is not None else _v _v = arg.pop("textpositionsrc", None) self["textpositionsrc"] = textpositionsrc if textpositionsrc is not None else _v _v = arg.pop("textsrc", None) self["textsrc"] = textsrc if textsrc is not None else _v _v = arg.pop("texttemplate", None) self["texttemplate"] = texttemplate if texttemplate is not None else _v _v = arg.pop("texttemplatesrc", None) self["texttemplatesrc"] = texttemplatesrc if texttemplatesrc is not None else _v _v = arg.pop("theta", None) self["theta"] = theta if theta is not None else _v _v = arg.pop("theta0", None) self["theta0"] = theta0 if theta0 is not None else _v _v = arg.pop("thetasrc", None) self["thetasrc"] = thetasrc if thetasrc is not None else _v _v = arg.pop("thetaunit", None) self["thetaunit"] = thetaunit if thetaunit is not None else _v _v = arg.pop("uid", None) self["uid"] = uid if uid is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("unselected", None) self["unselected"] = unselected if unselected is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v # Read-only literals # ------------------ from _plotly_utils.basevalidators import LiteralValidator self._props["type"] = "scatterpolar" self._validators["type"] = LiteralValidator( plotly_name="type", parent_name="scatterpolar", val="scatterpolar" ) arg.pop("type", None) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceType as _BaseTraceType import copy as _copy class Scattermapbox(_BaseTraceType): # below # ----- @property def below(self): """ Determines if this scattermapbox trace's layers are to be inserted before the layer with the specified ID. By default, scattermapbox layers are inserted above all the base layers. To place the scattermapbox layers above every other layer, set `below` to "''". The 'below' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["below"] @below.setter def below(self, val): self["below"] = val # connectgaps # ----------- @property def connectgaps(self): """ Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. The 'connectgaps' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["connectgaps"] @connectgaps.setter def connectgaps(self, val): self["connectgaps"] = val # customdata # ---------- @property def customdata(self): """ Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements The 'customdata' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["customdata"] @customdata.setter def customdata(self, val): self["customdata"] = val # customdatasrc # ------------- @property def customdatasrc(self): """ Sets the source reference on plot.ly for customdata . The 'customdatasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["customdatasrc"] @customdatasrc.setter def customdatasrc(self, val): self["customdatasrc"] = val # fill # ---- @property def fill(self): """ Sets the area to fill with a solid color. Use with `fillcolor` if not "none". "toself" connects the endpoints of the trace (or each segment of the trace if it has gaps) into a closed shape. The 'fill' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'toself'] Returns ------- Any """ return self["fill"] @fill.setter def fill(self, val): self["fill"] = val # fillcolor # --------- @property def fillcolor(self): """ Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. The 'fillcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["fillcolor"] @fillcolor.setter def fillcolor(self, val): self["fillcolor"] = val # hoverinfo # --------- @property def hoverinfo(self): """ Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. The 'hoverinfo' property is a flaglist and may be specified as a string containing: - Any combination of ['lon', 'lat', 'text', 'name'] joined with '+' characters (e.g. 'lon+lat') OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') - A list or array of the above Returns ------- Any|numpy.ndarray """ return self["hoverinfo"] @hoverinfo.setter def hoverinfo(self, val): self["hoverinfo"] = val # hoverinfosrc # ------------ @property def hoverinfosrc(self): """ Sets the source reference on plot.ly for hoverinfo . The 'hoverinfosrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hoverinfosrc"] @hoverinfosrc.setter def hoverinfosrc(self, val): self["hoverinfosrc"] = val # hoverlabel # ---------- @property def hoverlabel(self): """ The 'hoverlabel' property is an instance of Hoverlabel that may be specified as: - An instance of plotly.graph_objs.scattermapbox.Hoverlabel - A dict of string/value properties that will be passed to the Hoverlabel constructor Supported dict properties: align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- plotly.graph_objs.scattermapbox.Hoverlabel """ return self["hoverlabel"] @hoverlabel.setter def hoverlabel(self, val): self["hoverlabel"] = val # hovertemplate # ------------- @property def hovertemplate(self): """ Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event- data. Additionally, every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. The 'hovertemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertemplate"] @hovertemplate.setter def hovertemplate(self, val): self["hovertemplate"] = val # hovertemplatesrc # ---------------- @property def hovertemplatesrc(self): """ Sets the source reference on plot.ly for hovertemplate . The 'hovertemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertemplatesrc"] @hovertemplatesrc.setter def hovertemplatesrc(self, val): self["hovertemplatesrc"] = val # hovertext # --------- @property def hovertext(self): """ Sets hover text elements associated with each (lon,lat) pair If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (lon,lat) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. The 'hovertext' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertext"] @hovertext.setter def hovertext(self, val): self["hovertext"] = val # hovertextsrc # ------------ @property def hovertextsrc(self): """ Sets the source reference on plot.ly for hovertext . The 'hovertextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertextsrc"] @hovertextsrc.setter def hovertextsrc(self, val): self["hovertextsrc"] = val # ids # --- @property def ids(self): """ Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. The 'ids' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ids"] @ids.setter def ids(self, val): self["ids"] = val # idssrc # ------ @property def idssrc(self): """ Sets the source reference on plot.ly for ids . The 'idssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["idssrc"] @idssrc.setter def idssrc(self, val): self["idssrc"] = val # lat # --- @property def lat(self): """ Sets the latitude coordinates (in degrees North). The 'lat' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["lat"] @lat.setter def lat(self, val): self["lat"] = val # latsrc # ------ @property def latsrc(self): """ Sets the source reference on plot.ly for lat . The 'latsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["latsrc"] @latsrc.setter def latsrc(self, val): self["latsrc"] = val # legendgroup # ----------- @property def legendgroup(self): """ Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. The 'legendgroup' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["legendgroup"] @legendgroup.setter def legendgroup(self, val): self["legendgroup"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.scattermapbox.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: color Sets the line color. width Sets the line width (in px). Returns ------- plotly.graph_objs.scattermapbox.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # lon # --- @property def lon(self): """ Sets the longitude coordinates (in degrees East). The 'lon' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["lon"] @lon.setter def lon(self, val): self["lon"] = val # lonsrc # ------ @property def lonsrc(self): """ Sets the source reference on plot.ly for lon . The 'lonsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["lonsrc"] @lonsrc.setter def lonsrc(self, val): self["lonsrc"] = val # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.scattermapbox.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.scattermapbox.marker.Color Bar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . opacity Sets the marker opacity. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. size Sets the marker size (in px). sizemin Has an effect only if `marker.size` is set to a numerical array. Sets the minimum size (in px) of the rendered marker points. sizemode Has an effect only if `marker.size` is set to a numerical array. Sets the rule for which the data in `size` is converted to pixels. sizeref Has an effect only if `marker.size` is set to a numerical array. Sets the scale factor used to determine the rendered size of marker points. Use with `sizemin` and `sizemode`. sizesrc Sets the source reference on plot.ly for size . symbol Sets the marker symbol. Full list: https://www.mapbox.com/maki-icons/ Note that the array `marker.color` and `marker.size` are only available for "circle" symbols. symbolsrc Sets the source reference on plot.ly for symbol . Returns ------- plotly.graph_objs.scattermapbox.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # meta # ---- @property def meta(self): """ Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. The 'meta' property accepts values of any type Returns ------- Any|numpy.ndarray """ return self["meta"] @meta.setter def meta(self, val): self["meta"] = val # metasrc # ------- @property def metasrc(self): """ Sets the source reference on plot.ly for meta . The 'metasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["metasrc"] @metasrc.setter def metasrc(self, val): self["metasrc"] = val # mode # ---- @property def mode(self): """ Determines the drawing mode for this scatter trace. If the provided `mode` includes "text" then the `text` elements appear at the coordinates. Otherwise, the `text` elements appear on hover. The 'mode' property is a flaglist and may be specified as a string containing: - Any combination of ['lines', 'markers', 'text'] joined with '+' characters (e.g. 'lines+markers') OR exactly one of ['none'] (e.g. 'none') Returns ------- Any """ return self["mode"] @mode.setter def mode(self, val): self["mode"] = val # name # ---- @property def name(self): """ Sets the trace name. The trace name appear as the legend item and on hover. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the trace. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # selected # -------- @property def selected(self): """ The 'selected' property is an instance of Selected that may be specified as: - An instance of plotly.graph_objs.scattermapbox.Selected - A dict of string/value properties that will be passed to the Selected constructor Supported dict properties: marker plotly.graph_objects.scattermapbox.selected.Mar ker instance or dict with compatible properties Returns ------- plotly.graph_objs.scattermapbox.Selected """ return self["selected"] @selected.setter def selected(self, val): self["selected"] = val # selectedpoints # -------------- @property def selectedpoints(self): """ Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. The 'selectedpoints' property accepts values of any type Returns ------- Any """ return self["selectedpoints"] @selectedpoints.setter def selectedpoints(self, val): self["selectedpoints"] = val # showlegend # ---------- @property def showlegend(self): """ Determines whether or not an item corresponding to this trace is shown in the legend. The 'showlegend' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showlegend"] @showlegend.setter def showlegend(self, val): self["showlegend"] = val # stream # ------ @property def stream(self): """ The 'stream' property is an instance of Stream that may be specified as: - An instance of plotly.graph_objs.scattermapbox.Stream - A dict of string/value properties that will be passed to the Stream constructor Supported dict properties: maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- plotly.graph_objs.scattermapbox.Stream """ return self["stream"] @stream.setter def stream(self, val): self["stream"] = val # subplot # ------- @property def subplot(self): """ Sets a reference between this trace's data coordinates and a mapbox subplot. If "mapbox" (the default value), the data refer to `layout.mapbox`. If "mapbox2", the data refer to `layout.mapbox2`, and so on. The 'subplot' property is an identifier of a particular subplot, of type 'mapbox', that may be specified as the string 'mapbox' optionally followed by an integer >= 1 (e.g. 'mapbox', 'mapbox1', 'mapbox2', 'mapbox3', etc.) Returns ------- str """ return self["subplot"] @subplot.setter def subplot(self, val): self["subplot"] = val # text # ---- @property def text(self): """ Sets text elements associated with each (lon,lat) pair If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (lon,lat) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["text"] @text.setter def text(self, val): self["text"] = val # textfont # -------- @property def textfont(self): """ Sets the icon text font (color=mapbox.layer.paint.text-color, size=mapbox.layer.layout.text-size). Has an effect only when `type` is set to "symbol". The 'textfont' property is an instance of Textfont that may be specified as: - An instance of plotly.graph_objs.scattermapbox.Textfont - A dict of string/value properties that will be passed to the Textfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.scattermapbox.Textfont """ return self["textfont"] @textfont.setter def textfont(self, val): self["textfont"] = val # textposition # ------------ @property def textposition(self): """ Sets the positions of the `text` elements with respects to the (x,y) coordinates. The 'textposition' property is an enumeration that may be specified as: - One of the following enumeration values: ['top left', 'top center', 'top right', 'middle left', 'middle center', 'middle right', 'bottom left', 'bottom center', 'bottom right'] Returns ------- Any """ return self["textposition"] @textposition.setter def textposition(self, val): self["textposition"] = val # textsrc # ------- @property def textsrc(self): """ Sets the source reference on plot.ly for text . The 'textsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["textsrc"] @textsrc.setter def textsrc(self, val): self["textsrc"] = val # texttemplate # ------------ @property def texttemplate(self): """ Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `lat`, `lon` and `text`. The 'texttemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["texttemplate"] @texttemplate.setter def texttemplate(self, val): self["texttemplate"] = val # texttemplatesrc # --------------- @property def texttemplatesrc(self): """ Sets the source reference on plot.ly for texttemplate . The 'texttemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["texttemplatesrc"] @texttemplatesrc.setter def texttemplatesrc(self, val): self["texttemplatesrc"] = val # uid # --- @property def uid(self): """ Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. The 'uid' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["uid"] @uid.setter def uid(self, val): self["uid"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # unselected # ---------- @property def unselected(self): """ The 'unselected' property is an instance of Unselected that may be specified as: - An instance of plotly.graph_objs.scattermapbox.Unselected - A dict of string/value properties that will be passed to the Unselected constructor Supported dict properties: marker plotly.graph_objects.scattermapbox.unselected.M arker instance or dict with compatible properties Returns ------- plotly.graph_objs.scattermapbox.Unselected """ return self["unselected"] @unselected.setter def unselected(self, val): self["unselected"] = val # visible # ------- @property def visible(self): """ Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). The 'visible' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'legendonly'] Returns ------- Any """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # type # ---- @property def type(self): return self._props["type"] # property parent name # -------------------- @property def _parent_path_str(self): return "" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ below Determines if this scattermapbox trace's layers are to be inserted before the layer with the specified ID. By default, scattermapbox layers are inserted above all the base layers. To place the scattermapbox layers above every other layer, set `below` to "''". connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . fill Sets the area to fill with a solid color. Use with `fillcolor` if not "none". "toself" connects the endpoints of the trace (or each segment of the trace if it has gaps) into a closed shape. fillcolor Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.scattermapbox.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (lon,lat) pair If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (lon,lat) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . lat Sets the latitude coordinates (in degrees North). latsrc Sets the source reference on plot.ly for lat . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.scattermapbox.Line instance or dict with compatible properties lon Sets the longitude coordinates (in degrees East). lonsrc Sets the source reference on plot.ly for lon . marker plotly.graph_objects.scattermapbox.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . mode Determines the drawing mode for this scatter trace. If the provided `mode` includes "text" then the `text` elements appear at the coordinates. Otherwise, the `text` elements appear on hover. name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. selected plotly.graph_objects.scattermapbox.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.scattermapbox.Stream instance or dict with compatible properties subplot Sets a reference between this trace's data coordinates and a mapbox subplot. If "mapbox" (the default value), the data refer to `layout.mapbox`. If "mapbox2", the data refer to `layout.mapbox2`, and so on. text Sets text elements associated with each (lon,lat) pair If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (lon,lat) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the icon text font (color=mapbox.layer.paint.text- color, size=mapbox.layer.layout.text-size). Has an effect only when `type` is set to "symbol". textposition Sets the positions of the `text` elements with respects to the (x,y) coordinates. textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `lat`, `lon` and `text`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.scattermapbox.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). """ def __init__( self, arg=None, below=None, connectgaps=None, customdata=None, customdatasrc=None, fill=None, fillcolor=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, lat=None, latsrc=None, legendgroup=None, line=None, lon=None, lonsrc=None, marker=None, meta=None, metasrc=None, mode=None, name=None, opacity=None, selected=None, selectedpoints=None, showlegend=None, stream=None, subplot=None, text=None, textfont=None, textposition=None, textsrc=None, texttemplate=None, texttemplatesrc=None, uid=None, uirevision=None, unselected=None, visible=None, **kwargs ): """ Construct a new Scattermapbox object The data visualized as scatter point, lines or marker symbols on a Mapbox GL geographic map is provided by longitude/latitude pairs in `lon` and `lat`. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.Scattermapbox below Determines if this scattermapbox trace's layers are to be inserted before the layer with the specified ID. By default, scattermapbox layers are inserted above all the base layers. To place the scattermapbox layers above every other layer, set `below` to "''". connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . fill Sets the area to fill with a solid color. Use with `fillcolor` if not "none". "toself" connects the endpoints of the trace (or each segment of the trace if it has gaps) into a closed shape. fillcolor Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.scattermapbox.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (lon,lat) pair If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (lon,lat) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . lat Sets the latitude coordinates (in degrees North). latsrc Sets the source reference on plot.ly for lat . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.scattermapbox.Line instance or dict with compatible properties lon Sets the longitude coordinates (in degrees East). lonsrc Sets the source reference on plot.ly for lon . marker plotly.graph_objects.scattermapbox.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . mode Determines the drawing mode for this scatter trace. If the provided `mode` includes "text" then the `text` elements appear at the coordinates. Otherwise, the `text` elements appear on hover. name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. selected plotly.graph_objects.scattermapbox.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.scattermapbox.Stream instance or dict with compatible properties subplot Sets a reference between this trace's data coordinates and a mapbox subplot. If "mapbox" (the default value), the data refer to `layout.mapbox`. If "mapbox2", the data refer to `layout.mapbox2`, and so on. text Sets text elements associated with each (lon,lat) pair If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (lon,lat) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the icon text font (color=mapbox.layer.paint.text- color, size=mapbox.layer.layout.text-size). Has an effect only when `type` is set to "symbol". textposition Sets the positions of the `text` elements with respects to the (x,y) coordinates. textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `lat`, `lon` and `text`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.scattermapbox.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). Returns ------- Scattermapbox """ super(Scattermapbox, self).__init__("scattermapbox") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.Scattermapbox constructor must be a dict or an instance of plotly.graph_objs.Scattermapbox""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators import scattermapbox as v_scattermapbox # Initialize validators # --------------------- self._validators["below"] = v_scattermapbox.BelowValidator() self._validators["connectgaps"] = v_scattermapbox.ConnectgapsValidator() self._validators["customdata"] = v_scattermapbox.CustomdataValidator() self._validators["customdatasrc"] = v_scattermapbox.CustomdatasrcValidator() self._validators["fill"] = v_scattermapbox.FillValidator() self._validators["fillcolor"] = v_scattermapbox.FillcolorValidator() self._validators["hoverinfo"] = v_scattermapbox.HoverinfoValidator() self._validators["hoverinfosrc"] = v_scattermapbox.HoverinfosrcValidator() self._validators["hoverlabel"] = v_scattermapbox.HoverlabelValidator() self._validators["hovertemplate"] = v_scattermapbox.HovertemplateValidator() self._validators[ "hovertemplatesrc" ] = v_scattermapbox.HovertemplatesrcValidator() self._validators["hovertext"] = v_scattermapbox.HovertextValidator() self._validators["hovertextsrc"] = v_scattermapbox.HovertextsrcValidator() self._validators["ids"] = v_scattermapbox.IdsValidator() self._validators["idssrc"] = v_scattermapbox.IdssrcValidator() self._validators["lat"] = v_scattermapbox.LatValidator() self._validators["latsrc"] = v_scattermapbox.LatsrcValidator() self._validators["legendgroup"] = v_scattermapbox.LegendgroupValidator() self._validators["line"] = v_scattermapbox.LineValidator() self._validators["lon"] = v_scattermapbox.LonValidator() self._validators["lonsrc"] = v_scattermapbox.LonsrcValidator() self._validators["marker"] = v_scattermapbox.MarkerValidator() self._validators["meta"] = v_scattermapbox.MetaValidator() self._validators["metasrc"] = v_scattermapbox.MetasrcValidator() self._validators["mode"] = v_scattermapbox.ModeValidator() self._validators["name"] = v_scattermapbox.NameValidator() self._validators["opacity"] = v_scattermapbox.OpacityValidator() self._validators["selected"] = v_scattermapbox.SelectedValidator() self._validators["selectedpoints"] = v_scattermapbox.SelectedpointsValidator() self._validators["showlegend"] = v_scattermapbox.ShowlegendValidator() self._validators["stream"] = v_scattermapbox.StreamValidator() self._validators["subplot"] = v_scattermapbox.SubplotValidator() self._validators["text"] = v_scattermapbox.TextValidator() self._validators["textfont"] = v_scattermapbox.TextfontValidator() self._validators["textposition"] = v_scattermapbox.TextpositionValidator() self._validators["textsrc"] = v_scattermapbox.TextsrcValidator() self._validators["texttemplate"] = v_scattermapbox.TexttemplateValidator() self._validators["texttemplatesrc"] = v_scattermapbox.TexttemplatesrcValidator() self._validators["uid"] = v_scattermapbox.UidValidator() self._validators["uirevision"] = v_scattermapbox.UirevisionValidator() self._validators["unselected"] = v_scattermapbox.UnselectedValidator() self._validators["visible"] = v_scattermapbox.VisibleValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("below", None) self["below"] = below if below is not None else _v _v = arg.pop("connectgaps", None) self["connectgaps"] = connectgaps if connectgaps is not None else _v _v = arg.pop("customdata", None) self["customdata"] = customdata if customdata is not None else _v _v = arg.pop("customdatasrc", None) self["customdatasrc"] = customdatasrc if customdatasrc is not None else _v _v = arg.pop("fill", None) self["fill"] = fill if fill is not None else _v _v = arg.pop("fillcolor", None) self["fillcolor"] = fillcolor if fillcolor is not None else _v _v = arg.pop("hoverinfo", None) self["hoverinfo"] = hoverinfo if hoverinfo is not None else _v _v = arg.pop("hoverinfosrc", None) self["hoverinfosrc"] = hoverinfosrc if hoverinfosrc is not None else _v _v = arg.pop("hoverlabel", None) self["hoverlabel"] = hoverlabel if hoverlabel is not None else _v _v = arg.pop("hovertemplate", None) self["hovertemplate"] = hovertemplate if hovertemplate is not None else _v _v = arg.pop("hovertemplatesrc", None) self["hovertemplatesrc"] = ( hovertemplatesrc if hovertemplatesrc is not None else _v ) _v = arg.pop("hovertext", None) self["hovertext"] = hovertext if hovertext is not None else _v _v = arg.pop("hovertextsrc", None) self["hovertextsrc"] = hovertextsrc if hovertextsrc is not None else _v _v = arg.pop("ids", None) self["ids"] = ids if ids is not None else _v _v = arg.pop("idssrc", None) self["idssrc"] = idssrc if idssrc is not None else _v _v = arg.pop("lat", None) self["lat"] = lat if lat is not None else _v _v = arg.pop("latsrc", None) self["latsrc"] = latsrc if latsrc is not None else _v _v = arg.pop("legendgroup", None) self["legendgroup"] = legendgroup if legendgroup is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v _v = arg.pop("lon", None) self["lon"] = lon if lon is not None else _v _v = arg.pop("lonsrc", None) self["lonsrc"] = lonsrc if lonsrc is not None else _v _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v _v = arg.pop("meta", None) self["meta"] = meta if meta is not None else _v _v = arg.pop("metasrc", None) self["metasrc"] = metasrc if metasrc is not None else _v _v = arg.pop("mode", None) self["mode"] = mode if mode is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("selected", None) self["selected"] = selected if selected is not None else _v _v = arg.pop("selectedpoints", None) self["selectedpoints"] = selectedpoints if selectedpoints is not None else _v _v = arg.pop("showlegend", None) self["showlegend"] = showlegend if showlegend is not None else _v _v = arg.pop("stream", None) self["stream"] = stream if stream is not None else _v _v = arg.pop("subplot", None) self["subplot"] = subplot if subplot is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v _v = arg.pop("textfont", None) self["textfont"] = textfont if textfont is not None else _v _v = arg.pop("textposition", None) self["textposition"] = textposition if textposition is not None else _v _v = arg.pop("textsrc", None) self["textsrc"] = textsrc if textsrc is not None else _v _v = arg.pop("texttemplate", None) self["texttemplate"] = texttemplate if texttemplate is not None else _v _v = arg.pop("texttemplatesrc", None) self["texttemplatesrc"] = texttemplatesrc if texttemplatesrc is not None else _v _v = arg.pop("uid", None) self["uid"] = uid if uid is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("unselected", None) self["unselected"] = unselected if unselected is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v # Read-only literals # ------------------ from _plotly_utils.basevalidators import LiteralValidator self._props["type"] = "scattermapbox" self._validators["type"] = LiteralValidator( plotly_name="type", parent_name="scattermapbox", val="scattermapbox" ) arg.pop("type", None) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceType as _BaseTraceType import copy as _copy class Scattergl(_BaseTraceType): # connectgaps # ----------- @property def connectgaps(self): """ Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. The 'connectgaps' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["connectgaps"] @connectgaps.setter def connectgaps(self, val): self["connectgaps"] = val # customdata # ---------- @property def customdata(self): """ Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements The 'customdata' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["customdata"] @customdata.setter def customdata(self, val): self["customdata"] = val # customdatasrc # ------------- @property def customdatasrc(self): """ Sets the source reference on plot.ly for customdata . The 'customdatasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["customdatasrc"] @customdatasrc.setter def customdatasrc(self, val): self["customdatasrc"] = val # dx # -- @property def dx(self): """ Sets the x coordinate step. See `x0` for more info. The 'dx' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["dx"] @dx.setter def dx(self, val): self["dx"] = val # dy # -- @property def dy(self): """ Sets the y coordinate step. See `y0` for more info. The 'dy' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["dy"] @dy.setter def dy(self, val): self["dy"] = val # error_x # ------- @property def error_x(self): """ The 'error_x' property is an instance of ErrorX that may be specified as: - An instance of plotly.graph_objs.scattergl.ErrorX - A dict of string/value properties that will be passed to the ErrorX constructor Supported dict properties: array Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. arrayminus Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. arrayminussrc Sets the source reference on plot.ly for arrayminus . arraysrc Sets the source reference on plot.ly for array . color Sets the stoke color of the error bars. copy_ystyle symmetric Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. thickness Sets the thickness (in px) of the error bars. traceref tracerefminus type Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. value Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. valueminus Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars visible Determines whether or not this set of error bars is visible. width Sets the width (in px) of the cross-bar at both ends of the error bars. Returns ------- plotly.graph_objs.scattergl.ErrorX """ return self["error_x"] @error_x.setter def error_x(self, val): self["error_x"] = val # error_y # ------- @property def error_y(self): """ The 'error_y' property is an instance of ErrorY that may be specified as: - An instance of plotly.graph_objs.scattergl.ErrorY - A dict of string/value properties that will be passed to the ErrorY constructor Supported dict properties: array Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. arrayminus Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. arrayminussrc Sets the source reference on plot.ly for arrayminus . arraysrc Sets the source reference on plot.ly for array . color Sets the stoke color of the error bars. symmetric Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. thickness Sets the thickness (in px) of the error bars. traceref tracerefminus type Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. value Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. valueminus Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars visible Determines whether or not this set of error bars is visible. width Sets the width (in px) of the cross-bar at both ends of the error bars. Returns ------- plotly.graph_objs.scattergl.ErrorY """ return self["error_y"] @error_y.setter def error_y(self, val): self["error_y"] = val # fill # ---- @property def fill(self): """ Sets the area to fill with a solid color. Defaults to "none" unless this trace is stacked, then it gets "tonexty" ("tonextx") if `orientation` is "v" ("h") Use with `fillcolor` if not "none". "tozerox" and "tozeroy" fill to x=0 and y=0 respectively. "tonextx" and "tonexty" fill between the endpoints of this trace and the endpoints of the trace before it, connecting those endpoints with straight lines (to make a stacked area graph); if there is no trace before it, they behave like "tozerox" and "tozeroy". "toself" connects the endpoints of the trace (or each segment of the trace if it has gaps) into a closed shape. "tonext" fills the space between two traces if one completely encloses the other (eg consecutive contour lines), and behaves like "toself" if there is no trace before it. "tonext" should not be used if one trace does not enclose the other. Traces in a `stackgroup` will only fill to (or be filled to) other traces in the same group. With multiple `stackgroup`s or some traces stacked and some not, if fill- linked traces are not already consecutive, the later ones will be pushed down in the drawing order. The 'fill' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'tozeroy', 'tozerox', 'tonexty', 'tonextx', 'toself', 'tonext'] Returns ------- Any """ return self["fill"] @fill.setter def fill(self, val): self["fill"] = val # fillcolor # --------- @property def fillcolor(self): """ Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. The 'fillcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["fillcolor"] @fillcolor.setter def fillcolor(self, val): self["fillcolor"] = val # hoverinfo # --------- @property def hoverinfo(self): """ Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. The 'hoverinfo' property is a flaglist and may be specified as a string containing: - Any combination of ['x', 'y', 'z', 'text', 'name'] joined with '+' characters (e.g. 'x+y') OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') - A list or array of the above Returns ------- Any|numpy.ndarray """ return self["hoverinfo"] @hoverinfo.setter def hoverinfo(self, val): self["hoverinfo"] = val # hoverinfosrc # ------------ @property def hoverinfosrc(self): """ Sets the source reference on plot.ly for hoverinfo . The 'hoverinfosrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hoverinfosrc"] @hoverinfosrc.setter def hoverinfosrc(self, val): self["hoverinfosrc"] = val # hoverlabel # ---------- @property def hoverlabel(self): """ The 'hoverlabel' property is an instance of Hoverlabel that may be specified as: - An instance of plotly.graph_objs.scattergl.Hoverlabel - A dict of string/value properties that will be passed to the Hoverlabel constructor Supported dict properties: align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- plotly.graph_objs.scattergl.Hoverlabel """ return self["hoverlabel"] @hoverlabel.setter def hoverlabel(self, val): self["hoverlabel"] = val # hovertemplate # ------------- @property def hovertemplate(self): """ Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event- data. Additionally, every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. The 'hovertemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertemplate"] @hovertemplate.setter def hovertemplate(self, val): self["hovertemplate"] = val # hovertemplatesrc # ---------------- @property def hovertemplatesrc(self): """ Sets the source reference on plot.ly for hovertemplate . The 'hovertemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertemplatesrc"] @hovertemplatesrc.setter def hovertemplatesrc(self, val): self["hovertemplatesrc"] = val # hovertext # --------- @property def hovertext(self): """ Sets hover text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. The 'hovertext' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertext"] @hovertext.setter def hovertext(self, val): self["hovertext"] = val # hovertextsrc # ------------ @property def hovertextsrc(self): """ Sets the source reference on plot.ly for hovertext . The 'hovertextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertextsrc"] @hovertextsrc.setter def hovertextsrc(self, val): self["hovertextsrc"] = val # ids # --- @property def ids(self): """ Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. The 'ids' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ids"] @ids.setter def ids(self, val): self["ids"] = val # idssrc # ------ @property def idssrc(self): """ Sets the source reference on plot.ly for ids . The 'idssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["idssrc"] @idssrc.setter def idssrc(self, val): self["idssrc"] = val # legendgroup # ----------- @property def legendgroup(self): """ Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. The 'legendgroup' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["legendgroup"] @legendgroup.setter def legendgroup(self, val): self["legendgroup"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.scattergl.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: color Sets the line color. dash Sets the style of the lines. shape Determines the line shape. The values correspond to step-wise line shapes. width Sets the line width (in px). Returns ------- plotly.graph_objs.scattergl.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.scattergl.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.scattergl.marker.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . line plotly.graph_objects.scattergl.marker.Line instance or dict with compatible properties opacity Sets the marker opacity. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. size Sets the marker size (in px). sizemin Has an effect only if `marker.size` is set to a numerical array. Sets the minimum size (in px) of the rendered marker points. sizemode Has an effect only if `marker.size` is set to a numerical array. Sets the rule for which the data in `size` is converted to pixels. sizeref Has an effect only if `marker.size` is set to a numerical array. Sets the scale factor used to determine the rendered size of marker points. Use with `sizemin` and `sizemode`. sizesrc Sets the source reference on plot.ly for size . symbol Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot- open" to a symbol name. symbolsrc Sets the source reference on plot.ly for symbol . Returns ------- plotly.graph_objs.scattergl.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # meta # ---- @property def meta(self): """ Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. The 'meta' property accepts values of any type Returns ------- Any|numpy.ndarray """ return self["meta"] @meta.setter def meta(self, val): self["meta"] = val # metasrc # ------- @property def metasrc(self): """ Sets the source reference on plot.ly for meta . The 'metasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["metasrc"] @metasrc.setter def metasrc(self, val): self["metasrc"] = val # mode # ---- @property def mode(self): """ Determines the drawing mode for this scatter trace. The 'mode' property is a flaglist and may be specified as a string containing: - Any combination of ['lines', 'markers', 'text'] joined with '+' characters (e.g. 'lines+markers') OR exactly one of ['none'] (e.g. 'none') Returns ------- Any """ return self["mode"] @mode.setter def mode(self, val): self["mode"] = val # name # ---- @property def name(self): """ Sets the trace name. The trace name appear as the legend item and on hover. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the trace. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # selected # -------- @property def selected(self): """ The 'selected' property is an instance of Selected that may be specified as: - An instance of plotly.graph_objs.scattergl.Selected - A dict of string/value properties that will be passed to the Selected constructor Supported dict properties: marker plotly.graph_objects.scattergl.selected.Marker instance or dict with compatible properties textfont plotly.graph_objects.scattergl.selected.Textfon t instance or dict with compatible properties Returns ------- plotly.graph_objs.scattergl.Selected """ return self["selected"] @selected.setter def selected(self, val): self["selected"] = val # selectedpoints # -------------- @property def selectedpoints(self): """ Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. The 'selectedpoints' property accepts values of any type Returns ------- Any """ return self["selectedpoints"] @selectedpoints.setter def selectedpoints(self, val): self["selectedpoints"] = val # showlegend # ---------- @property def showlegend(self): """ Determines whether or not an item corresponding to this trace is shown in the legend. The 'showlegend' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showlegend"] @showlegend.setter def showlegend(self, val): self["showlegend"] = val # stream # ------ @property def stream(self): """ The 'stream' property is an instance of Stream that may be specified as: - An instance of plotly.graph_objs.scattergl.Stream - A dict of string/value properties that will be passed to the Stream constructor Supported dict properties: maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- plotly.graph_objs.scattergl.Stream """ return self["stream"] @stream.setter def stream(self, val): self["stream"] = val # text # ---- @property def text(self): """ Sets text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["text"] @text.setter def text(self, val): self["text"] = val # textfont # -------- @property def textfont(self): """ Sets the text font. The 'textfont' property is an instance of Textfont that may be specified as: - An instance of plotly.graph_objs.scattergl.Textfont - A dict of string/value properties that will be passed to the Textfont constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.scattergl.Textfont """ return self["textfont"] @textfont.setter def textfont(self, val): self["textfont"] = val # textposition # ------------ @property def textposition(self): """ Sets the positions of the `text` elements with respects to the (x,y) coordinates. The 'textposition' property is an enumeration that may be specified as: - One of the following enumeration values: ['top left', 'top center', 'top right', 'middle left', 'middle center', 'middle right', 'bottom left', 'bottom center', 'bottom right'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["textposition"] @textposition.setter def textposition(self, val): self["textposition"] = val # textpositionsrc # --------------- @property def textpositionsrc(self): """ Sets the source reference on plot.ly for textposition . The 'textpositionsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["textpositionsrc"] @textpositionsrc.setter def textpositionsrc(self, val): self["textpositionsrc"] = val # textsrc # ------- @property def textsrc(self): """ Sets the source reference on plot.ly for text . The 'textsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["textsrc"] @textsrc.setter def textsrc(self, val): self["textsrc"] = val # texttemplate # ------------ @property def texttemplate(self): """ Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. The 'texttemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["texttemplate"] @texttemplate.setter def texttemplate(self, val): self["texttemplate"] = val # texttemplatesrc # --------------- @property def texttemplatesrc(self): """ Sets the source reference on plot.ly for texttemplate . The 'texttemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["texttemplatesrc"] @texttemplatesrc.setter def texttemplatesrc(self, val): self["texttemplatesrc"] = val # uid # --- @property def uid(self): """ Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. The 'uid' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["uid"] @uid.setter def uid(self, val): self["uid"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # unselected # ---------- @property def unselected(self): """ The 'unselected' property is an instance of Unselected that may be specified as: - An instance of plotly.graph_objs.scattergl.Unselected - A dict of string/value properties that will be passed to the Unselected constructor Supported dict properties: marker plotly.graph_objects.scattergl.unselected.Marke r instance or dict with compatible properties textfont plotly.graph_objects.scattergl.unselected.Textf ont instance or dict with compatible properties Returns ------- plotly.graph_objs.scattergl.Unselected """ return self["unselected"] @unselected.setter def unselected(self, val): self["unselected"] = val # visible # ------- @property def visible(self): """ Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). The 'visible' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'legendonly'] Returns ------- Any """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # x # - @property def x(self): """ Sets the x coordinates. The 'x' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["x"] @x.setter def x(self, val): self["x"] = val # x0 # -- @property def x0(self): """ Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. The 'x0' property accepts values of any type Returns ------- Any """ return self["x0"] @x0.setter def x0(self, val): self["x0"] = val # xaxis # ----- @property def xaxis(self): """ Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. The 'xaxis' property is an identifier of a particular subplot, of type 'x', that may be specified as the string 'x' optionally followed by an integer >= 1 (e.g. 'x', 'x1', 'x2', 'x3', etc.) Returns ------- str """ return self["xaxis"] @xaxis.setter def xaxis(self, val): self["xaxis"] = val # xcalendar # --------- @property def xcalendar(self): """ Sets the calendar system to use with `x` date data. The 'xcalendar' property is an enumeration that may be specified as: - One of the following enumeration values: ['gregorian', 'chinese', 'coptic', 'discworld', 'ethiopian', 'hebrew', 'islamic', 'julian', 'mayan', 'nanakshahi', 'nepali', 'persian', 'jalali', 'taiwan', 'thai', 'ummalqura'] Returns ------- Any """ return self["xcalendar"] @xcalendar.setter def xcalendar(self, val): self["xcalendar"] = val # xsrc # ---- @property def xsrc(self): """ Sets the source reference on plot.ly for x . The 'xsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["xsrc"] @xsrc.setter def xsrc(self, val): self["xsrc"] = val # y # - @property def y(self): """ Sets the y coordinates. The 'y' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["y"] @y.setter def y(self, val): self["y"] = val # y0 # -- @property def y0(self): """ Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. The 'y0' property accepts values of any type Returns ------- Any """ return self["y0"] @y0.setter def y0(self, val): self["y0"] = val # yaxis # ----- @property def yaxis(self): """ Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. The 'yaxis' property is an identifier of a particular subplot, of type 'y', that may be specified as the string 'y' optionally followed by an integer >= 1 (e.g. 'y', 'y1', 'y2', 'y3', etc.) Returns ------- str """ return self["yaxis"] @yaxis.setter def yaxis(self, val): self["yaxis"] = val # ycalendar # --------- @property def ycalendar(self): """ Sets the calendar system to use with `y` date data. The 'ycalendar' property is an enumeration that may be specified as: - One of the following enumeration values: ['gregorian', 'chinese', 'coptic', 'discworld', 'ethiopian', 'hebrew', 'islamic', 'julian', 'mayan', 'nanakshahi', 'nepali', 'persian', 'jalali', 'taiwan', 'thai', 'ummalqura'] Returns ------- Any """ return self["ycalendar"] @ycalendar.setter def ycalendar(self, val): self["ycalendar"] = val # ysrc # ---- @property def ysrc(self): """ Sets the source reference on plot.ly for y . The 'ysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ysrc"] @ysrc.setter def ysrc(self, val): self["ysrc"] = val # type # ---- @property def type(self): return self._props["type"] # property parent name # -------------------- @property def _parent_path_str(self): return "" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dx Sets the x coordinate step. See `x0` for more info. dy Sets the y coordinate step. See `y0` for more info. error_x plotly.graph_objects.scattergl.ErrorX instance or dict with compatible properties error_y plotly.graph_objects.scattergl.ErrorY instance or dict with compatible properties fill Sets the area to fill with a solid color. Defaults to "none" unless this trace is stacked, then it gets "tonexty" ("tonextx") if `orientation` is "v" ("h") Use with `fillcolor` if not "none". "tozerox" and "tozeroy" fill to x=0 and y=0 respectively. "tonextx" and "tonexty" fill between the endpoints of this trace and the endpoints of the trace before it, connecting those endpoints with straight lines (to make a stacked area graph); if there is no trace before it, they behave like "tozerox" and "tozeroy". "toself" connects the endpoints of the trace (or each segment of the trace if it has gaps) into a closed shape. "tonext" fills the space between two traces if one completely encloses the other (eg consecutive contour lines), and behaves like "toself" if there is no trace before it. "tonext" should not be used if one trace does not enclose the other. Traces in a `stackgroup` will only fill to (or be filled to) other traces in the same group. With multiple `stackgroup`s or some traces stacked and some not, if fill-linked traces are not already consecutive, the later ones will be pushed down in the drawing order. fillcolor Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.scattergl.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.scattergl.Line instance or dict with compatible properties marker plotly.graph_objects.scattergl.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . mode Determines the drawing mode for this scatter trace. name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. selected plotly.graph_objects.scattergl.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.scattergl.Stream instance or dict with compatible properties text Sets text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the text font. textposition Sets the positions of the `text` elements with respects to the (x,y) coordinates. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. texttemplatesrc Sets the source reference on plot.ly for texttemplate . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.scattergl.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the x coordinates. x0 Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . y Sets the y coordinates. y0 Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . """ def __init__( self, arg=None, connectgaps=None, customdata=None, customdatasrc=None, dx=None, dy=None, error_x=None, error_y=None, fill=None, fillcolor=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, legendgroup=None, line=None, marker=None, meta=None, metasrc=None, mode=None, name=None, opacity=None, selected=None, selectedpoints=None, showlegend=None, stream=None, text=None, textfont=None, textposition=None, textpositionsrc=None, textsrc=None, texttemplate=None, texttemplatesrc=None, uid=None, uirevision=None, unselected=None, visible=None, x=None, x0=None, xaxis=None, xcalendar=None, xsrc=None, y=None, y0=None, yaxis=None, ycalendar=None, ysrc=None, **kwargs ): """ Construct a new Scattergl object The data visualized as scatter point or lines is set in `x` and `y` using the WebGL plotting engine. Bubble charts are achieved by setting `marker.size` and/or `marker.color` to a numerical arrays. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.Scattergl connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dx Sets the x coordinate step. See `x0` for more info. dy Sets the y coordinate step. See `y0` for more info. error_x plotly.graph_objects.scattergl.ErrorX instance or dict with compatible properties error_y plotly.graph_objects.scattergl.ErrorY instance or dict with compatible properties fill Sets the area to fill with a solid color. Defaults to "none" unless this trace is stacked, then it gets "tonexty" ("tonextx") if `orientation` is "v" ("h") Use with `fillcolor` if not "none". "tozerox" and "tozeroy" fill to x=0 and y=0 respectively. "tonextx" and "tonexty" fill between the endpoints of this trace and the endpoints of the trace before it, connecting those endpoints with straight lines (to make a stacked area graph); if there is no trace before it, they behave like "tozerox" and "tozeroy". "toself" connects the endpoints of the trace (or each segment of the trace if it has gaps) into a closed shape. "tonext" fills the space between two traces if one completely encloses the other (eg consecutive contour lines), and behaves like "toself" if there is no trace before it. "tonext" should not be used if one trace does not enclose the other. Traces in a `stackgroup` will only fill to (or be filled to) other traces in the same group. With multiple `stackgroup`s or some traces stacked and some not, if fill-linked traces are not already consecutive, the later ones will be pushed down in the drawing order. fillcolor Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.scattergl.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.scattergl.Line instance or dict with compatible properties marker plotly.graph_objects.scattergl.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . mode Determines the drawing mode for this scatter trace. name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. selected plotly.graph_objects.scattergl.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.scattergl.Stream instance or dict with compatible properties text Sets text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the text font. textposition Sets the positions of the `text` elements with respects to the (x,y) coordinates. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. texttemplatesrc Sets the source reference on plot.ly for texttemplate . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.scattergl.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the x coordinates. x0 Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . y Sets the y coordinates. y0 Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . Returns ------- Scattergl """ super(Scattergl, self).__init__("scattergl") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.Scattergl constructor must be a dict or an instance of plotly.graph_objs.Scattergl""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators import scattergl as v_scattergl # Initialize validators # --------------------- self._validators["connectgaps"] = v_scattergl.ConnectgapsValidator() self._validators["customdata"] = v_scattergl.CustomdataValidator() self._validators["customdatasrc"] = v_scattergl.CustomdatasrcValidator() self._validators["dx"] = v_scattergl.DxValidator() self._validators["dy"] = v_scattergl.DyValidator() self._validators["error_x"] = v_scattergl.ErrorXValidator() self._validators["error_y"] = v_scattergl.ErrorYValidator() self._validators["fill"] = v_scattergl.FillValidator() self._validators["fillcolor"] = v_scattergl.FillcolorValidator() self._validators["hoverinfo"] = v_scattergl.HoverinfoValidator() self._validators["hoverinfosrc"] = v_scattergl.HoverinfosrcValidator() self._validators["hoverlabel"] = v_scattergl.HoverlabelValidator() self._validators["hovertemplate"] = v_scattergl.HovertemplateValidator() self._validators["hovertemplatesrc"] = v_scattergl.HovertemplatesrcValidator() self._validators["hovertext"] = v_scattergl.HovertextValidator() self._validators["hovertextsrc"] = v_scattergl.HovertextsrcValidator() self._validators["ids"] = v_scattergl.IdsValidator() self._validators["idssrc"] = v_scattergl.IdssrcValidator() self._validators["legendgroup"] = v_scattergl.LegendgroupValidator() self._validators["line"] = v_scattergl.LineValidator() self._validators["marker"] = v_scattergl.MarkerValidator() self._validators["meta"] = v_scattergl.MetaValidator() self._validators["metasrc"] = v_scattergl.MetasrcValidator() self._validators["mode"] = v_scattergl.ModeValidator() self._validators["name"] = v_scattergl.NameValidator() self._validators["opacity"] = v_scattergl.OpacityValidator() self._validators["selected"] = v_scattergl.SelectedValidator() self._validators["selectedpoints"] = v_scattergl.SelectedpointsValidator() self._validators["showlegend"] = v_scattergl.ShowlegendValidator() self._validators["stream"] = v_scattergl.StreamValidator() self._validators["text"] = v_scattergl.TextValidator() self._validators["textfont"] = v_scattergl.TextfontValidator() self._validators["textposition"] = v_scattergl.TextpositionValidator() self._validators["textpositionsrc"] = v_scattergl.TextpositionsrcValidator() self._validators["textsrc"] = v_scattergl.TextsrcValidator() self._validators["texttemplate"] = v_scattergl.TexttemplateValidator() self._validators["texttemplatesrc"] = v_scattergl.TexttemplatesrcValidator() self._validators["uid"] = v_scattergl.UidValidator() self._validators["uirevision"] = v_scattergl.UirevisionValidator() self._validators["unselected"] = v_scattergl.UnselectedValidator() self._validators["visible"] = v_scattergl.VisibleValidator() self._validators["x"] = v_scattergl.XValidator() self._validators["x0"] = v_scattergl.X0Validator() self._validators["xaxis"] = v_scattergl.XAxisValidator() self._validators["xcalendar"] = v_scattergl.XcalendarValidator() self._validators["xsrc"] = v_scattergl.XsrcValidator() self._validators["y"] = v_scattergl.YValidator() self._validators["y0"] = v_scattergl.Y0Validator() self._validators["yaxis"] = v_scattergl.YAxisValidator() self._validators["ycalendar"] = v_scattergl.YcalendarValidator() self._validators["ysrc"] = v_scattergl.YsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("connectgaps", None) self["connectgaps"] = connectgaps if connectgaps is not None else _v _v = arg.pop("customdata", None) self["customdata"] = customdata if customdata is not None else _v _v = arg.pop("customdatasrc", None) self["customdatasrc"] = customdatasrc if customdatasrc is not None else _v _v = arg.pop("dx", None) self["dx"] = dx if dx is not None else _v _v = arg.pop("dy", None) self["dy"] = dy if dy is not None else _v _v = arg.pop("error_x", None) self["error_x"] = error_x if error_x is not None else _v _v = arg.pop("error_y", None) self["error_y"] = error_y if error_y is not None else _v _v = arg.pop("fill", None) self["fill"] = fill if fill is not None else _v _v = arg.pop("fillcolor", None) self["fillcolor"] = fillcolor if fillcolor is not None else _v _v = arg.pop("hoverinfo", None) self["hoverinfo"] = hoverinfo if hoverinfo is not None else _v _v = arg.pop("hoverinfosrc", None) self["hoverinfosrc"] = hoverinfosrc if hoverinfosrc is not None else _v _v = arg.pop("hoverlabel", None) self["hoverlabel"] = hoverlabel if hoverlabel is not None else _v _v = arg.pop("hovertemplate", None) self["hovertemplate"] = hovertemplate if hovertemplate is not None else _v _v = arg.pop("hovertemplatesrc", None) self["hovertemplatesrc"] = ( hovertemplatesrc if hovertemplatesrc is not None else _v ) _v = arg.pop("hovertext", None) self["hovertext"] = hovertext if hovertext is not None else _v _v = arg.pop("hovertextsrc", None) self["hovertextsrc"] = hovertextsrc if hovertextsrc is not None else _v _v = arg.pop("ids", None) self["ids"] = ids if ids is not None else _v _v = arg.pop("idssrc", None) self["idssrc"] = idssrc if idssrc is not None else _v _v = arg.pop("legendgroup", None) self["legendgroup"] = legendgroup if legendgroup is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v _v = arg.pop("meta", None) self["meta"] = meta if meta is not None else _v _v = arg.pop("metasrc", None) self["metasrc"] = metasrc if metasrc is not None else _v _v = arg.pop("mode", None) self["mode"] = mode if mode is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("selected", None) self["selected"] = selected if selected is not None else _v _v = arg.pop("selectedpoints", None) self["selectedpoints"] = selectedpoints if selectedpoints is not None else _v _v = arg.pop("showlegend", None) self["showlegend"] = showlegend if showlegend is not None else _v _v = arg.pop("stream", None) self["stream"] = stream if stream is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v _v = arg.pop("textfont", None) self["textfont"] = textfont if textfont is not None else _v _v = arg.pop("textposition", None) self["textposition"] = textposition if textposition is not None else _v _v = arg.pop("textpositionsrc", None) self["textpositionsrc"] = textpositionsrc if textpositionsrc is not None else _v _v = arg.pop("textsrc", None) self["textsrc"] = textsrc if textsrc is not None else _v _v = arg.pop("texttemplate", None) self["texttemplate"] = texttemplate if texttemplate is not None else _v _v = arg.pop("texttemplatesrc", None) self["texttemplatesrc"] = texttemplatesrc if texttemplatesrc is not None else _v _v = arg.pop("uid", None) self["uid"] = uid if uid is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("unselected", None) self["unselected"] = unselected if unselected is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("x0", None) self["x0"] = x0 if x0 is not None else _v _v = arg.pop("xaxis", None) self["xaxis"] = xaxis if xaxis is not None else _v _v = arg.pop("xcalendar", None) self["xcalendar"] = xcalendar if xcalendar is not None else _v _v = arg.pop("xsrc", None) self["xsrc"] = xsrc if xsrc is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("y0", None) self["y0"] = y0 if y0 is not None else _v _v = arg.pop("yaxis", None) self["yaxis"] = yaxis if yaxis is not None else _v _v = arg.pop("ycalendar", None) self["ycalendar"] = ycalendar if ycalendar is not None else _v _v = arg.pop("ysrc", None) self["ysrc"] = ysrc if ysrc is not None else _v # Read-only literals # ------------------ from _plotly_utils.basevalidators import LiteralValidator self._props["type"] = "scattergl" self._validators["type"] = LiteralValidator( plotly_name="type", parent_name="scattergl", val="scattergl" ) arg.pop("type", None) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceType as _BaseTraceType import copy as _copy class Scattergeo(_BaseTraceType): # connectgaps # ----------- @property def connectgaps(self): """ Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. The 'connectgaps' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["connectgaps"] @connectgaps.setter def connectgaps(self, val): self["connectgaps"] = val # customdata # ---------- @property def customdata(self): """ Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements The 'customdata' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["customdata"] @customdata.setter def customdata(self, val): self["customdata"] = val # customdatasrc # ------------- @property def customdatasrc(self): """ Sets the source reference on plot.ly for customdata . The 'customdatasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["customdatasrc"] @customdatasrc.setter def customdatasrc(self, val): self["customdatasrc"] = val # fill # ---- @property def fill(self): """ Sets the area to fill with a solid color. Use with `fillcolor` if not "none". "toself" connects the endpoints of the trace (or each segment of the trace if it has gaps) into a closed shape. The 'fill' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'toself'] Returns ------- Any """ return self["fill"] @fill.setter def fill(self, val): self["fill"] = val # fillcolor # --------- @property def fillcolor(self): """ Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. The 'fillcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["fillcolor"] @fillcolor.setter def fillcolor(self, val): self["fillcolor"] = val # geo # --- @property def geo(self): """ Sets a reference between this trace's geospatial coordinates and a geographic map. If "geo" (the default value), the geospatial coordinates refer to `layout.geo`. If "geo2", the geospatial coordinates refer to `layout.geo2`, and so on. The 'geo' property is an identifier of a particular subplot, of type 'geo', that may be specified as the string 'geo' optionally followed by an integer >= 1 (e.g. 'geo', 'geo1', 'geo2', 'geo3', etc.) Returns ------- str """ return self["geo"] @geo.setter def geo(self, val): self["geo"] = val # hoverinfo # --------- @property def hoverinfo(self): """ Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. The 'hoverinfo' property is a flaglist and may be specified as a string containing: - Any combination of ['lon', 'lat', 'location', 'text', 'name'] joined with '+' characters (e.g. 'lon+lat') OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') - A list or array of the above Returns ------- Any|numpy.ndarray """ return self["hoverinfo"] @hoverinfo.setter def hoverinfo(self, val): self["hoverinfo"] = val # hoverinfosrc # ------------ @property def hoverinfosrc(self): """ Sets the source reference on plot.ly for hoverinfo . The 'hoverinfosrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hoverinfosrc"] @hoverinfosrc.setter def hoverinfosrc(self, val): self["hoverinfosrc"] = val # hoverlabel # ---------- @property def hoverlabel(self): """ The 'hoverlabel' property is an instance of Hoverlabel that may be specified as: - An instance of plotly.graph_objs.scattergeo.Hoverlabel - A dict of string/value properties that will be passed to the Hoverlabel constructor Supported dict properties: align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- plotly.graph_objs.scattergeo.Hoverlabel """ return self["hoverlabel"] @hoverlabel.setter def hoverlabel(self, val): self["hoverlabel"] = val # hovertemplate # ------------- @property def hovertemplate(self): """ Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event- data. Additionally, every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. The 'hovertemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertemplate"] @hovertemplate.setter def hovertemplate(self, val): self["hovertemplate"] = val # hovertemplatesrc # ---------------- @property def hovertemplatesrc(self): """ Sets the source reference on plot.ly for hovertemplate . The 'hovertemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertemplatesrc"] @hovertemplatesrc.setter def hovertemplatesrc(self, val): self["hovertemplatesrc"] = val # hovertext # --------- @property def hovertext(self): """ Sets hover text elements associated with each (lon,lat) pair or item in `locations`. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (lon,lat) or `locations` coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. The 'hovertext' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertext"] @hovertext.setter def hovertext(self, val): self["hovertext"] = val # hovertextsrc # ------------ @property def hovertextsrc(self): """ Sets the source reference on plot.ly for hovertext . The 'hovertextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertextsrc"] @hovertextsrc.setter def hovertextsrc(self, val): self["hovertextsrc"] = val # ids # --- @property def ids(self): """ Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. The 'ids' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ids"] @ids.setter def ids(self, val): self["ids"] = val # idssrc # ------ @property def idssrc(self): """ Sets the source reference on plot.ly for ids . The 'idssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["idssrc"] @idssrc.setter def idssrc(self, val): self["idssrc"] = val # lat # --- @property def lat(self): """ Sets the latitude coordinates (in degrees North). The 'lat' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["lat"] @lat.setter def lat(self, val): self["lat"] = val # latsrc # ------ @property def latsrc(self): """ Sets the source reference on plot.ly for lat . The 'latsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["latsrc"] @latsrc.setter def latsrc(self, val): self["latsrc"] = val # legendgroup # ----------- @property def legendgroup(self): """ Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. The 'legendgroup' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["legendgroup"] @legendgroup.setter def legendgroup(self, val): self["legendgroup"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.scattergeo.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: color Sets the line color. dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). width Sets the line width (in px). Returns ------- plotly.graph_objs.scattergeo.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # locationmode # ------------ @property def locationmode(self): """ Determines the set of locations used to match entries in `locations` to regions on the map. The 'locationmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['ISO-3', 'USA-states', 'country names'] Returns ------- Any """ return self["locationmode"] @locationmode.setter def locationmode(self, val): self["locationmode"] = val # locations # --------- @property def locations(self): """ Sets the coordinates via location IDs or names. Coordinates correspond to the centroid of each location given. See `locationmode` for more info. The 'locations' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["locations"] @locations.setter def locations(self, val): self["locations"] = val # locationssrc # ------------ @property def locationssrc(self): """ Sets the source reference on plot.ly for locations . The 'locationssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["locationssrc"] @locationssrc.setter def locationssrc(self, val): self["locationssrc"] = val # lon # --- @property def lon(self): """ Sets the longitude coordinates (in degrees East). The 'lon' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["lon"] @lon.setter def lon(self, val): self["lon"] = val # lonsrc # ------ @property def lonsrc(self): """ Sets the source reference on plot.ly for lon . The 'lonsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["lonsrc"] @lonsrc.setter def lonsrc(self, val): self["lonsrc"] = val # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.scattergeo.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.scattergeo.marker.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . gradient plotly.graph_objects.scattergeo.marker.Gradient instance or dict with compatible properties line plotly.graph_objects.scattergeo.marker.Line instance or dict with compatible properties opacity Sets the marker opacity. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. size Sets the marker size (in px). sizemin Has an effect only if `marker.size` is set to a numerical array. Sets the minimum size (in px) of the rendered marker points. sizemode Has an effect only if `marker.size` is set to a numerical array. Sets the rule for which the data in `size` is converted to pixels. sizeref Has an effect only if `marker.size` is set to a numerical array. Sets the scale factor used to determine the rendered size of marker points. Use with `sizemin` and `sizemode`. sizesrc Sets the source reference on plot.ly for size . symbol Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot- open" to a symbol name. symbolsrc Sets the source reference on plot.ly for symbol . Returns ------- plotly.graph_objs.scattergeo.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # meta # ---- @property def meta(self): """ Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. The 'meta' property accepts values of any type Returns ------- Any|numpy.ndarray """ return self["meta"] @meta.setter def meta(self, val): self["meta"] = val # metasrc # ------- @property def metasrc(self): """ Sets the source reference on plot.ly for meta . The 'metasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["metasrc"] @metasrc.setter def metasrc(self, val): self["metasrc"] = val # mode # ---- @property def mode(self): """ Determines the drawing mode for this scatter trace. If the provided `mode` includes "text" then the `text` elements appear at the coordinates. Otherwise, the `text` elements appear on hover. If there are less than 20 points and the trace is not stacked then the default is "lines+markers". Otherwise, "lines". The 'mode' property is a flaglist and may be specified as a string containing: - Any combination of ['lines', 'markers', 'text'] joined with '+' characters (e.g. 'lines+markers') OR exactly one of ['none'] (e.g. 'none') Returns ------- Any """ return self["mode"] @mode.setter def mode(self, val): self["mode"] = val # name # ---- @property def name(self): """ Sets the trace name. The trace name appear as the legend item and on hover. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the trace. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # selected # -------- @property def selected(self): """ The 'selected' property is an instance of Selected that may be specified as: - An instance of plotly.graph_objs.scattergeo.Selected - A dict of string/value properties that will be passed to the Selected constructor Supported dict properties: marker plotly.graph_objects.scattergeo.selected.Marker instance or dict with compatible properties textfont plotly.graph_objects.scattergeo.selected.Textfo nt instance or dict with compatible properties Returns ------- plotly.graph_objs.scattergeo.Selected """ return self["selected"] @selected.setter def selected(self, val): self["selected"] = val # selectedpoints # -------------- @property def selectedpoints(self): """ Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. The 'selectedpoints' property accepts values of any type Returns ------- Any """ return self["selectedpoints"] @selectedpoints.setter def selectedpoints(self, val): self["selectedpoints"] = val # showlegend # ---------- @property def showlegend(self): """ Determines whether or not an item corresponding to this trace is shown in the legend. The 'showlegend' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showlegend"] @showlegend.setter def showlegend(self, val): self["showlegend"] = val # stream # ------ @property def stream(self): """ The 'stream' property is an instance of Stream that may be specified as: - An instance of plotly.graph_objs.scattergeo.Stream - A dict of string/value properties that will be passed to the Stream constructor Supported dict properties: maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- plotly.graph_objs.scattergeo.Stream """ return self["stream"] @stream.setter def stream(self, val): self["stream"] = val # text # ---- @property def text(self): """ Sets text elements associated with each (lon,lat) pair or item in `locations`. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (lon,lat) or `locations` coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["text"] @text.setter def text(self, val): self["text"] = val # textfont # -------- @property def textfont(self): """ Sets the text font. The 'textfont' property is an instance of Textfont that may be specified as: - An instance of plotly.graph_objs.scattergeo.Textfont - A dict of string/value properties that will be passed to the Textfont constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.scattergeo.Textfont """ return self["textfont"] @textfont.setter def textfont(self, val): self["textfont"] = val # textposition # ------------ @property def textposition(self): """ Sets the positions of the `text` elements with respects to the (x,y) coordinates. The 'textposition' property is an enumeration that may be specified as: - One of the following enumeration values: ['top left', 'top center', 'top right', 'middle left', 'middle center', 'middle right', 'bottom left', 'bottom center', 'bottom right'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["textposition"] @textposition.setter def textposition(self, val): self["textposition"] = val # textpositionsrc # --------------- @property def textpositionsrc(self): """ Sets the source reference on plot.ly for textposition . The 'textpositionsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["textpositionsrc"] @textpositionsrc.setter def textpositionsrc(self, val): self["textpositionsrc"] = val # textsrc # ------- @property def textsrc(self): """ Sets the source reference on plot.ly for text . The 'textsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["textsrc"] @textsrc.setter def textsrc(self, val): self["textsrc"] = val # texttemplate # ------------ @property def texttemplate(self): """ Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `lat`, `lon`, `location` and `text`. The 'texttemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["texttemplate"] @texttemplate.setter def texttemplate(self, val): self["texttemplate"] = val # texttemplatesrc # --------------- @property def texttemplatesrc(self): """ Sets the source reference on plot.ly for texttemplate . The 'texttemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["texttemplatesrc"] @texttemplatesrc.setter def texttemplatesrc(self, val): self["texttemplatesrc"] = val # uid # --- @property def uid(self): """ Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. The 'uid' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["uid"] @uid.setter def uid(self, val): self["uid"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # unselected # ---------- @property def unselected(self): """ The 'unselected' property is an instance of Unselected that may be specified as: - An instance of plotly.graph_objs.scattergeo.Unselected - A dict of string/value properties that will be passed to the Unselected constructor Supported dict properties: marker plotly.graph_objects.scattergeo.unselected.Mark er instance or dict with compatible properties textfont plotly.graph_objects.scattergeo.unselected.Text font instance or dict with compatible properties Returns ------- plotly.graph_objs.scattergeo.Unselected """ return self["unselected"] @unselected.setter def unselected(self, val): self["unselected"] = val # visible # ------- @property def visible(self): """ Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). The 'visible' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'legendonly'] Returns ------- Any """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # type # ---- @property def type(self): return self._props["type"] # property parent name # -------------------- @property def _parent_path_str(self): return "" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . fill Sets the area to fill with a solid color. Use with `fillcolor` if not "none". "toself" connects the endpoints of the trace (or each segment of the trace if it has gaps) into a closed shape. fillcolor Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. geo Sets a reference between this trace's geospatial coordinates and a geographic map. If "geo" (the default value), the geospatial coordinates refer to `layout.geo`. If "geo2", the geospatial coordinates refer to `layout.geo2`, and so on. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.scattergeo.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (lon,lat) pair or item in `locations`. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (lon,lat) or `locations` coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . lat Sets the latitude coordinates (in degrees North). latsrc Sets the source reference on plot.ly for lat . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.scattergeo.Line instance or dict with compatible properties locationmode Determines the set of locations used to match entries in `locations` to regions on the map. locations Sets the coordinates via location IDs or names. Coordinates correspond to the centroid of each location given. See `locationmode` for more info. locationssrc Sets the source reference on plot.ly for locations . lon Sets the longitude coordinates (in degrees East). lonsrc Sets the source reference on plot.ly for lon . marker plotly.graph_objects.scattergeo.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . mode Determines the drawing mode for this scatter trace. If the provided `mode` includes "text" then the `text` elements appear at the coordinates. Otherwise, the `text` elements appear on hover. If there are less than 20 points and the trace is not stacked then the default is "lines+markers". Otherwise, "lines". name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. selected plotly.graph_objects.scattergeo.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.scattergeo.Stream instance or dict with compatible properties text Sets text elements associated with each (lon,lat) pair or item in `locations`. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (lon,lat) or `locations` coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the text font. textposition Sets the positions of the `text` elements with respects to the (x,y) coordinates. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `lat`, `lon`, `location` and `text`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.scattergeo.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). """ def __init__( self, arg=None, connectgaps=None, customdata=None, customdatasrc=None, fill=None, fillcolor=None, geo=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, lat=None, latsrc=None, legendgroup=None, line=None, locationmode=None, locations=None, locationssrc=None, lon=None, lonsrc=None, marker=None, meta=None, metasrc=None, mode=None, name=None, opacity=None, selected=None, selectedpoints=None, showlegend=None, stream=None, text=None, textfont=None, textposition=None, textpositionsrc=None, textsrc=None, texttemplate=None, texttemplatesrc=None, uid=None, uirevision=None, unselected=None, visible=None, **kwargs ): """ Construct a new Scattergeo object The data visualized as scatter point or lines on a geographic map is provided either by longitude/latitude pairs in `lon` and `lat` respectively or by geographic location IDs or names in `locations`. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.Scattergeo connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . fill Sets the area to fill with a solid color. Use with `fillcolor` if not "none". "toself" connects the endpoints of the trace (or each segment of the trace if it has gaps) into a closed shape. fillcolor Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. geo Sets a reference between this trace's geospatial coordinates and a geographic map. If "geo" (the default value), the geospatial coordinates refer to `layout.geo`. If "geo2", the geospatial coordinates refer to `layout.geo2`, and so on. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.scattergeo.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (lon,lat) pair or item in `locations`. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (lon,lat) or `locations` coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . lat Sets the latitude coordinates (in degrees North). latsrc Sets the source reference on plot.ly for lat . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.scattergeo.Line instance or dict with compatible properties locationmode Determines the set of locations used to match entries in `locations` to regions on the map. locations Sets the coordinates via location IDs or names. Coordinates correspond to the centroid of each location given. See `locationmode` for more info. locationssrc Sets the source reference on plot.ly for locations . lon Sets the longitude coordinates (in degrees East). lonsrc Sets the source reference on plot.ly for lon . marker plotly.graph_objects.scattergeo.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . mode Determines the drawing mode for this scatter trace. If the provided `mode` includes "text" then the `text` elements appear at the coordinates. Otherwise, the `text` elements appear on hover. If there are less than 20 points and the trace is not stacked then the default is "lines+markers". Otherwise, "lines". name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. selected plotly.graph_objects.scattergeo.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.scattergeo.Stream instance or dict with compatible properties text Sets text elements associated with each (lon,lat) pair or item in `locations`. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (lon,lat) or `locations` coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the text font. textposition Sets the positions of the `text` elements with respects to the (x,y) coordinates. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `lat`, `lon`, `location` and `text`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.scattergeo.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). Returns ------- Scattergeo """ super(Scattergeo, self).__init__("scattergeo") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.Scattergeo constructor must be a dict or an instance of plotly.graph_objs.Scattergeo""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators import scattergeo as v_scattergeo # Initialize validators # --------------------- self._validators["connectgaps"] = v_scattergeo.ConnectgapsValidator() self._validators["customdata"] = v_scattergeo.CustomdataValidator() self._validators["customdatasrc"] = v_scattergeo.CustomdatasrcValidator() self._validators["fill"] = v_scattergeo.FillValidator() self._validators["fillcolor"] = v_scattergeo.FillcolorValidator() self._validators["geo"] = v_scattergeo.GeoValidator() self._validators["hoverinfo"] = v_scattergeo.HoverinfoValidator() self._validators["hoverinfosrc"] = v_scattergeo.HoverinfosrcValidator() self._validators["hoverlabel"] = v_scattergeo.HoverlabelValidator() self._validators["hovertemplate"] = v_scattergeo.HovertemplateValidator() self._validators["hovertemplatesrc"] = v_scattergeo.HovertemplatesrcValidator() self._validators["hovertext"] = v_scattergeo.HovertextValidator() self._validators["hovertextsrc"] = v_scattergeo.HovertextsrcValidator() self._validators["ids"] = v_scattergeo.IdsValidator() self._validators["idssrc"] = v_scattergeo.IdssrcValidator() self._validators["lat"] = v_scattergeo.LatValidator() self._validators["latsrc"] = v_scattergeo.LatsrcValidator() self._validators["legendgroup"] = v_scattergeo.LegendgroupValidator() self._validators["line"] = v_scattergeo.LineValidator() self._validators["locationmode"] = v_scattergeo.LocationmodeValidator() self._validators["locations"] = v_scattergeo.LocationsValidator() self._validators["locationssrc"] = v_scattergeo.LocationssrcValidator() self._validators["lon"] = v_scattergeo.LonValidator() self._validators["lonsrc"] = v_scattergeo.LonsrcValidator() self._validators["marker"] = v_scattergeo.MarkerValidator() self._validators["meta"] = v_scattergeo.MetaValidator() self._validators["metasrc"] = v_scattergeo.MetasrcValidator() self._validators["mode"] = v_scattergeo.ModeValidator() self._validators["name"] = v_scattergeo.NameValidator() self._validators["opacity"] = v_scattergeo.OpacityValidator() self._validators["selected"] = v_scattergeo.SelectedValidator() self._validators["selectedpoints"] = v_scattergeo.SelectedpointsValidator() self._validators["showlegend"] = v_scattergeo.ShowlegendValidator() self._validators["stream"] = v_scattergeo.StreamValidator() self._validators["text"] = v_scattergeo.TextValidator() self._validators["textfont"] = v_scattergeo.TextfontValidator() self._validators["textposition"] = v_scattergeo.TextpositionValidator() self._validators["textpositionsrc"] = v_scattergeo.TextpositionsrcValidator() self._validators["textsrc"] = v_scattergeo.TextsrcValidator() self._validators["texttemplate"] = v_scattergeo.TexttemplateValidator() self._validators["texttemplatesrc"] = v_scattergeo.TexttemplatesrcValidator() self._validators["uid"] = v_scattergeo.UidValidator() self._validators["uirevision"] = v_scattergeo.UirevisionValidator() self._validators["unselected"] = v_scattergeo.UnselectedValidator() self._validators["visible"] = v_scattergeo.VisibleValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("connectgaps", None) self["connectgaps"] = connectgaps if connectgaps is not None else _v _v = arg.pop("customdata", None) self["customdata"] = customdata if customdata is not None else _v _v = arg.pop("customdatasrc", None) self["customdatasrc"] = customdatasrc if customdatasrc is not None else _v _v = arg.pop("fill", None) self["fill"] = fill if fill is not None else _v _v = arg.pop("fillcolor", None) self["fillcolor"] = fillcolor if fillcolor is not None else _v _v = arg.pop("geo", None) self["geo"] = geo if geo is not None else _v _v = arg.pop("hoverinfo", None) self["hoverinfo"] = hoverinfo if hoverinfo is not None else _v _v = arg.pop("hoverinfosrc", None) self["hoverinfosrc"] = hoverinfosrc if hoverinfosrc is not None else _v _v = arg.pop("hoverlabel", None) self["hoverlabel"] = hoverlabel if hoverlabel is not None else _v _v = arg.pop("hovertemplate", None) self["hovertemplate"] = hovertemplate if hovertemplate is not None else _v _v = arg.pop("hovertemplatesrc", None) self["hovertemplatesrc"] = ( hovertemplatesrc if hovertemplatesrc is not None else _v ) _v = arg.pop("hovertext", None) self["hovertext"] = hovertext if hovertext is not None else _v _v = arg.pop("hovertextsrc", None) self["hovertextsrc"] = hovertextsrc if hovertextsrc is not None else _v _v = arg.pop("ids", None) self["ids"] = ids if ids is not None else _v _v = arg.pop("idssrc", None) self["idssrc"] = idssrc if idssrc is not None else _v _v = arg.pop("lat", None) self["lat"] = lat if lat is not None else _v _v = arg.pop("latsrc", None) self["latsrc"] = latsrc if latsrc is not None else _v _v = arg.pop("legendgroup", None) self["legendgroup"] = legendgroup if legendgroup is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v _v = arg.pop("locationmode", None) self["locationmode"] = locationmode if locationmode is not None else _v _v = arg.pop("locations", None) self["locations"] = locations if locations is not None else _v _v = arg.pop("locationssrc", None) self["locationssrc"] = locationssrc if locationssrc is not None else _v _v = arg.pop("lon", None) self["lon"] = lon if lon is not None else _v _v = arg.pop("lonsrc", None) self["lonsrc"] = lonsrc if lonsrc is not None else _v _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v _v = arg.pop("meta", None) self["meta"] = meta if meta is not None else _v _v = arg.pop("metasrc", None) self["metasrc"] = metasrc if metasrc is not None else _v _v = arg.pop("mode", None) self["mode"] = mode if mode is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("selected", None) self["selected"] = selected if selected is not None else _v _v = arg.pop("selectedpoints", None) self["selectedpoints"] = selectedpoints if selectedpoints is not None else _v _v = arg.pop("showlegend", None) self["showlegend"] = showlegend if showlegend is not None else _v _v = arg.pop("stream", None) self["stream"] = stream if stream is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v _v = arg.pop("textfont", None) self["textfont"] = textfont if textfont is not None else _v _v = arg.pop("textposition", None) self["textposition"] = textposition if textposition is not None else _v _v = arg.pop("textpositionsrc", None) self["textpositionsrc"] = textpositionsrc if textpositionsrc is not None else _v _v = arg.pop("textsrc", None) self["textsrc"] = textsrc if textsrc is not None else _v _v = arg.pop("texttemplate", None) self["texttemplate"] = texttemplate if texttemplate is not None else _v _v = arg.pop("texttemplatesrc", None) self["texttemplatesrc"] = texttemplatesrc if texttemplatesrc is not None else _v _v = arg.pop("uid", None) self["uid"] = uid if uid is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("unselected", None) self["unselected"] = unselected if unselected is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v # Read-only literals # ------------------ from _plotly_utils.basevalidators import LiteralValidator self._props["type"] = "scattergeo" self._validators["type"] = LiteralValidator( plotly_name="type", parent_name="scattergeo", val="scattergeo" ) arg.pop("type", None) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceType as _BaseTraceType import copy as _copy class Scattercarpet(_BaseTraceType): # a # - @property def a(self): """ Sets the a-axis coordinates. The 'a' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["a"] @a.setter def a(self, val): self["a"] = val # asrc # ---- @property def asrc(self): """ Sets the source reference on plot.ly for a . The 'asrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["asrc"] @asrc.setter def asrc(self, val): self["asrc"] = val # b # - @property def b(self): """ Sets the b-axis coordinates. The 'b' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["b"] @b.setter def b(self, val): self["b"] = val # bsrc # ---- @property def bsrc(self): """ Sets the source reference on plot.ly for b . The 'bsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bsrc"] @bsrc.setter def bsrc(self, val): self["bsrc"] = val # carpet # ------ @property def carpet(self): """ An identifier for this carpet, so that `scattercarpet` and `contourcarpet` traces can specify a carpet plot on which they lie The 'carpet' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["carpet"] @carpet.setter def carpet(self, val): self["carpet"] = val # connectgaps # ----------- @property def connectgaps(self): """ Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. The 'connectgaps' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["connectgaps"] @connectgaps.setter def connectgaps(self, val): self["connectgaps"] = val # customdata # ---------- @property def customdata(self): """ Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements The 'customdata' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["customdata"] @customdata.setter def customdata(self, val): self["customdata"] = val # customdatasrc # ------------- @property def customdatasrc(self): """ Sets the source reference on plot.ly for customdata . The 'customdatasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["customdatasrc"] @customdatasrc.setter def customdatasrc(self, val): self["customdatasrc"] = val # fill # ---- @property def fill(self): """ Sets the area to fill with a solid color. Use with `fillcolor` if not "none". scatterternary has a subset of the options available to scatter. "toself" connects the endpoints of the trace (or each segment of the trace if it has gaps) into a closed shape. "tonext" fills the space between two traces if one completely encloses the other (eg consecutive contour lines), and behaves like "toself" if there is no trace before it. "tonext" should not be used if one trace does not enclose the other. The 'fill' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'toself', 'tonext'] Returns ------- Any """ return self["fill"] @fill.setter def fill(self, val): self["fill"] = val # fillcolor # --------- @property def fillcolor(self): """ Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. The 'fillcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["fillcolor"] @fillcolor.setter def fillcolor(self, val): self["fillcolor"] = val # hoverinfo # --------- @property def hoverinfo(self): """ Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. The 'hoverinfo' property is a flaglist and may be specified as a string containing: - Any combination of ['a', 'b', 'text', 'name'] joined with '+' characters (e.g. 'a+b') OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') - A list or array of the above Returns ------- Any|numpy.ndarray """ return self["hoverinfo"] @hoverinfo.setter def hoverinfo(self, val): self["hoverinfo"] = val # hoverinfosrc # ------------ @property def hoverinfosrc(self): """ Sets the source reference on plot.ly for hoverinfo . The 'hoverinfosrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hoverinfosrc"] @hoverinfosrc.setter def hoverinfosrc(self, val): self["hoverinfosrc"] = val # hoverlabel # ---------- @property def hoverlabel(self): """ The 'hoverlabel' property is an instance of Hoverlabel that may be specified as: - An instance of plotly.graph_objs.scattercarpet.Hoverlabel - A dict of string/value properties that will be passed to the Hoverlabel constructor Supported dict properties: align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- plotly.graph_objs.scattercarpet.Hoverlabel """ return self["hoverlabel"] @hoverlabel.setter def hoverlabel(self, val): self["hoverlabel"] = val # hoveron # ------- @property def hoveron(self): """ Do the hover effects highlight individual points (markers or line points) or do they highlight filled regions? If the fill is "toself" or "tonext" and there are no markers or text, then the default is "fills", otherwise it is "points". The 'hoveron' property is a flaglist and may be specified as a string containing: - Any combination of ['points', 'fills'] joined with '+' characters (e.g. 'points+fills') Returns ------- Any """ return self["hoveron"] @hoveron.setter def hoveron(self, val): self["hoveron"] = val # hovertemplate # ------------- @property def hovertemplate(self): """ Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event- data. Additionally, every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. The 'hovertemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertemplate"] @hovertemplate.setter def hovertemplate(self, val): self["hovertemplate"] = val # hovertemplatesrc # ---------------- @property def hovertemplatesrc(self): """ Sets the source reference on plot.ly for hovertemplate . The 'hovertemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertemplatesrc"] @hovertemplatesrc.setter def hovertemplatesrc(self, val): self["hovertemplatesrc"] = val # hovertext # --------- @property def hovertext(self): """ Sets hover text elements associated with each (a,b) point. If a single string, the same string appears over all the data points. If an array of strings, the items are mapped in order to the the data points in (a,b). To be seen, trace `hoverinfo` must contain a "text" flag. The 'hovertext' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertext"] @hovertext.setter def hovertext(self, val): self["hovertext"] = val # hovertextsrc # ------------ @property def hovertextsrc(self): """ Sets the source reference on plot.ly for hovertext . The 'hovertextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertextsrc"] @hovertextsrc.setter def hovertextsrc(self, val): self["hovertextsrc"] = val # ids # --- @property def ids(self): """ Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. The 'ids' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ids"] @ids.setter def ids(self, val): self["ids"] = val # idssrc # ------ @property def idssrc(self): """ Sets the source reference on plot.ly for ids . The 'idssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["idssrc"] @idssrc.setter def idssrc(self, val): self["idssrc"] = val # legendgroup # ----------- @property def legendgroup(self): """ Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. The 'legendgroup' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["legendgroup"] @legendgroup.setter def legendgroup(self, val): self["legendgroup"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.scattercarpet.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: color Sets the line color. dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). shape Determines the line shape. With "spline" the lines are drawn using spline interpolation. The other available values correspond to step-wise line shapes. smoothing Has an effect only if `shape` is set to "spline" Sets the amount of smoothing. 0 corresponds to no smoothing (equivalent to a "linear" shape). width Sets the line width (in px). Returns ------- plotly.graph_objs.scattercarpet.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.scattercarpet.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.scattercarpet.marker.Color Bar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . gradient plotly.graph_objects.scattercarpet.marker.Gradi ent instance or dict with compatible properties line plotly.graph_objects.scattercarpet.marker.Line instance or dict with compatible properties maxdisplayed Sets a maximum number of points to be drawn on the graph. 0 corresponds to no limit. opacity Sets the marker opacity. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. size Sets the marker size (in px). sizemin Has an effect only if `marker.size` is set to a numerical array. Sets the minimum size (in px) of the rendered marker points. sizemode Has an effect only if `marker.size` is set to a numerical array. Sets the rule for which the data in `size` is converted to pixels. sizeref Has an effect only if `marker.size` is set to a numerical array. Sets the scale factor used to determine the rendered size of marker points. Use with `sizemin` and `sizemode`. sizesrc Sets the source reference on plot.ly for size . symbol Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot- open" to a symbol name. symbolsrc Sets the source reference on plot.ly for symbol . Returns ------- plotly.graph_objs.scattercarpet.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # meta # ---- @property def meta(self): """ Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. The 'meta' property accepts values of any type Returns ------- Any|numpy.ndarray """ return self["meta"] @meta.setter def meta(self, val): self["meta"] = val # metasrc # ------- @property def metasrc(self): """ Sets the source reference on plot.ly for meta . The 'metasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["metasrc"] @metasrc.setter def metasrc(self, val): self["metasrc"] = val # mode # ---- @property def mode(self): """ Determines the drawing mode for this scatter trace. If the provided `mode` includes "text" then the `text` elements appear at the coordinates. Otherwise, the `text` elements appear on hover. If there are less than 20 points and the trace is not stacked then the default is "lines+markers". Otherwise, "lines". The 'mode' property is a flaglist and may be specified as a string containing: - Any combination of ['lines', 'markers', 'text'] joined with '+' characters (e.g. 'lines+markers') OR exactly one of ['none'] (e.g. 'none') Returns ------- Any """ return self["mode"] @mode.setter def mode(self, val): self["mode"] = val # name # ---- @property def name(self): """ Sets the trace name. The trace name appear as the legend item and on hover. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the trace. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # selected # -------- @property def selected(self): """ The 'selected' property is an instance of Selected that may be specified as: - An instance of plotly.graph_objs.scattercarpet.Selected - A dict of string/value properties that will be passed to the Selected constructor Supported dict properties: marker plotly.graph_objects.scattercarpet.selected.Mar ker instance or dict with compatible properties textfont plotly.graph_objects.scattercarpet.selected.Tex tfont instance or dict with compatible properties Returns ------- plotly.graph_objs.scattercarpet.Selected """ return self["selected"] @selected.setter def selected(self, val): self["selected"] = val # selectedpoints # -------------- @property def selectedpoints(self): """ Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. The 'selectedpoints' property accepts values of any type Returns ------- Any """ return self["selectedpoints"] @selectedpoints.setter def selectedpoints(self, val): self["selectedpoints"] = val # showlegend # ---------- @property def showlegend(self): """ Determines whether or not an item corresponding to this trace is shown in the legend. The 'showlegend' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showlegend"] @showlegend.setter def showlegend(self, val): self["showlegend"] = val # stream # ------ @property def stream(self): """ The 'stream' property is an instance of Stream that may be specified as: - An instance of plotly.graph_objs.scattercarpet.Stream - A dict of string/value properties that will be passed to the Stream constructor Supported dict properties: maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- plotly.graph_objs.scattercarpet.Stream """ return self["stream"] @stream.setter def stream(self, val): self["stream"] = val # text # ---- @property def text(self): """ Sets text elements associated with each (a,b) point. If a single string, the same string appears over all the data points. If an array of strings, the items are mapped in order to the the data points in (a,b). If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["text"] @text.setter def text(self, val): self["text"] = val # textfont # -------- @property def textfont(self): """ Sets the text font. The 'textfont' property is an instance of Textfont that may be specified as: - An instance of plotly.graph_objs.scattercarpet.Textfont - A dict of string/value properties that will be passed to the Textfont constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.scattercarpet.Textfont """ return self["textfont"] @textfont.setter def textfont(self, val): self["textfont"] = val # textposition # ------------ @property def textposition(self): """ Sets the positions of the `text` elements with respects to the (x,y) coordinates. The 'textposition' property is an enumeration that may be specified as: - One of the following enumeration values: ['top left', 'top center', 'top right', 'middle left', 'middle center', 'middle right', 'bottom left', 'bottom center', 'bottom right'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["textposition"] @textposition.setter def textposition(self, val): self["textposition"] = val # textpositionsrc # --------------- @property def textpositionsrc(self): """ Sets the source reference on plot.ly for textposition . The 'textpositionsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["textpositionsrc"] @textpositionsrc.setter def textpositionsrc(self, val): self["textpositionsrc"] = val # textsrc # ------- @property def textsrc(self): """ Sets the source reference on plot.ly for text . The 'textsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["textsrc"] @textsrc.setter def textsrc(self, val): self["textsrc"] = val # texttemplate # ------------ @property def texttemplate(self): """ Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `a`, `b` and `text`. The 'texttemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["texttemplate"] @texttemplate.setter def texttemplate(self, val): self["texttemplate"] = val # texttemplatesrc # --------------- @property def texttemplatesrc(self): """ Sets the source reference on plot.ly for texttemplate . The 'texttemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["texttemplatesrc"] @texttemplatesrc.setter def texttemplatesrc(self, val): self["texttemplatesrc"] = val # uid # --- @property def uid(self): """ Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. The 'uid' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["uid"] @uid.setter def uid(self, val): self["uid"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # unselected # ---------- @property def unselected(self): """ The 'unselected' property is an instance of Unselected that may be specified as: - An instance of plotly.graph_objs.scattercarpet.Unselected - A dict of string/value properties that will be passed to the Unselected constructor Supported dict properties: marker plotly.graph_objects.scattercarpet.unselected.M arker instance or dict with compatible properties textfont plotly.graph_objects.scattercarpet.unselected.T extfont instance or dict with compatible properties Returns ------- plotly.graph_objs.scattercarpet.Unselected """ return self["unselected"] @unselected.setter def unselected(self, val): self["unselected"] = val # visible # ------- @property def visible(self): """ Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). The 'visible' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'legendonly'] Returns ------- Any """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # xaxis # ----- @property def xaxis(self): """ Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. The 'xaxis' property is an identifier of a particular subplot, of type 'x', that may be specified as the string 'x' optionally followed by an integer >= 1 (e.g. 'x', 'x1', 'x2', 'x3', etc.) Returns ------- str """ return self["xaxis"] @xaxis.setter def xaxis(self, val): self["xaxis"] = val # yaxis # ----- @property def yaxis(self): """ Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. The 'yaxis' property is an identifier of a particular subplot, of type 'y', that may be specified as the string 'y' optionally followed by an integer >= 1 (e.g. 'y', 'y1', 'y2', 'y3', etc.) Returns ------- str """ return self["yaxis"] @yaxis.setter def yaxis(self, val): self["yaxis"] = val # type # ---- @property def type(self): return self._props["type"] # property parent name # -------------------- @property def _parent_path_str(self): return "" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ a Sets the a-axis coordinates. asrc Sets the source reference on plot.ly for a . b Sets the b-axis coordinates. bsrc Sets the source reference on plot.ly for b . carpet An identifier for this carpet, so that `scattercarpet` and `contourcarpet` traces can specify a carpet plot on which they lie connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . fill Sets the area to fill with a solid color. Use with `fillcolor` if not "none". scatterternary has a subset of the options available to scatter. "toself" connects the endpoints of the trace (or each segment of the trace if it has gaps) into a closed shape. "tonext" fills the space between two traces if one completely encloses the other (eg consecutive contour lines), and behaves like "toself" if there is no trace before it. "tonext" should not be used if one trace does not enclose the other. fillcolor Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.scattercarpet.Hoverlabel instance or dict with compatible properties hoveron Do the hover effects highlight individual points (markers or line points) or do they highlight filled regions? If the fill is "toself" or "tonext" and there are no markers or text, then the default is "fills", otherwise it is "points". hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (a,b) point. If a single string, the same string appears over all the data points. If an array of strings, the items are mapped in order to the the data points in (a,b). To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.scattercarpet.Line instance or dict with compatible properties marker plotly.graph_objects.scattercarpet.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . mode Determines the drawing mode for this scatter trace. If the provided `mode` includes "text" then the `text` elements appear at the coordinates. Otherwise, the `text` elements appear on hover. If there are less than 20 points and the trace is not stacked then the default is "lines+markers". Otherwise, "lines". name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. selected plotly.graph_objects.scattercarpet.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.scattercarpet.Stream instance or dict with compatible properties text Sets text elements associated with each (a,b) point. If a single string, the same string appears over all the data points. If an array of strings, the items are mapped in order to the the data points in (a,b). If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the text font. textposition Sets the positions of the `text` elements with respects to the (x,y) coordinates. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `a`, `b` and `text`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.scattercarpet.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. """ def __init__( self, arg=None, a=None, asrc=None, b=None, bsrc=None, carpet=None, connectgaps=None, customdata=None, customdatasrc=None, fill=None, fillcolor=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hoveron=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, legendgroup=None, line=None, marker=None, meta=None, metasrc=None, mode=None, name=None, opacity=None, selected=None, selectedpoints=None, showlegend=None, stream=None, text=None, textfont=None, textposition=None, textpositionsrc=None, textsrc=None, texttemplate=None, texttemplatesrc=None, uid=None, uirevision=None, unselected=None, visible=None, xaxis=None, yaxis=None, **kwargs ): """ Construct a new Scattercarpet object Plots a scatter trace on either the first carpet axis or the carpet axis with a matching `carpet` attribute. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.Scattercarpet a Sets the a-axis coordinates. asrc Sets the source reference on plot.ly for a . b Sets the b-axis coordinates. bsrc Sets the source reference on plot.ly for b . carpet An identifier for this carpet, so that `scattercarpet` and `contourcarpet` traces can specify a carpet plot on which they lie connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . fill Sets the area to fill with a solid color. Use with `fillcolor` if not "none". scatterternary has a subset of the options available to scatter. "toself" connects the endpoints of the trace (or each segment of the trace if it has gaps) into a closed shape. "tonext" fills the space between two traces if one completely encloses the other (eg consecutive contour lines), and behaves like "toself" if there is no trace before it. "tonext" should not be used if one trace does not enclose the other. fillcolor Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.scattercarpet.Hoverlabel instance or dict with compatible properties hoveron Do the hover effects highlight individual points (markers or line points) or do they highlight filled regions? If the fill is "toself" or "tonext" and there are no markers or text, then the default is "fills", otherwise it is "points". hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (a,b) point. If a single string, the same string appears over all the data points. If an array of strings, the items are mapped in order to the the data points in (a,b). To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.scattercarpet.Line instance or dict with compatible properties marker plotly.graph_objects.scattercarpet.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . mode Determines the drawing mode for this scatter trace. If the provided `mode` includes "text" then the `text` elements appear at the coordinates. Otherwise, the `text` elements appear on hover. If there are less than 20 points and the trace is not stacked then the default is "lines+markers". Otherwise, "lines". name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. selected plotly.graph_objects.scattercarpet.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.scattercarpet.Stream instance or dict with compatible properties text Sets text elements associated with each (a,b) point. If a single string, the same string appears over all the data points. If an array of strings, the items are mapped in order to the the data points in (a,b). If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the text font. textposition Sets the positions of the `text` elements with respects to the (x,y) coordinates. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `a`, `b` and `text`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.scattercarpet.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. Returns ------- Scattercarpet """ super(Scattercarpet, self).__init__("scattercarpet") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.Scattercarpet constructor must be a dict or an instance of plotly.graph_objs.Scattercarpet""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators import scattercarpet as v_scattercarpet # Initialize validators # --------------------- self._validators["a"] = v_scattercarpet.AValidator() self._validators["asrc"] = v_scattercarpet.AsrcValidator() self._validators["b"] = v_scattercarpet.BValidator() self._validators["bsrc"] = v_scattercarpet.BsrcValidator() self._validators["carpet"] = v_scattercarpet.CarpetValidator() self._validators["connectgaps"] = v_scattercarpet.ConnectgapsValidator() self._validators["customdata"] = v_scattercarpet.CustomdataValidator() self._validators["customdatasrc"] = v_scattercarpet.CustomdatasrcValidator() self._validators["fill"] = v_scattercarpet.FillValidator() self._validators["fillcolor"] = v_scattercarpet.FillcolorValidator() self._validators["hoverinfo"] = v_scattercarpet.HoverinfoValidator() self._validators["hoverinfosrc"] = v_scattercarpet.HoverinfosrcValidator() self._validators["hoverlabel"] = v_scattercarpet.HoverlabelValidator() self._validators["hoveron"] = v_scattercarpet.HoveronValidator() self._validators["hovertemplate"] = v_scattercarpet.HovertemplateValidator() self._validators[ "hovertemplatesrc" ] = v_scattercarpet.HovertemplatesrcValidator() self._validators["hovertext"] = v_scattercarpet.HovertextValidator() self._validators["hovertextsrc"] = v_scattercarpet.HovertextsrcValidator() self._validators["ids"] = v_scattercarpet.IdsValidator() self._validators["idssrc"] = v_scattercarpet.IdssrcValidator() self._validators["legendgroup"] = v_scattercarpet.LegendgroupValidator() self._validators["line"] = v_scattercarpet.LineValidator() self._validators["marker"] = v_scattercarpet.MarkerValidator() self._validators["meta"] = v_scattercarpet.MetaValidator() self._validators["metasrc"] = v_scattercarpet.MetasrcValidator() self._validators["mode"] = v_scattercarpet.ModeValidator() self._validators["name"] = v_scattercarpet.NameValidator() self._validators["opacity"] = v_scattercarpet.OpacityValidator() self._validators["selected"] = v_scattercarpet.SelectedValidator() self._validators["selectedpoints"] = v_scattercarpet.SelectedpointsValidator() self._validators["showlegend"] = v_scattercarpet.ShowlegendValidator() self._validators["stream"] = v_scattercarpet.StreamValidator() self._validators["text"] = v_scattercarpet.TextValidator() self._validators["textfont"] = v_scattercarpet.TextfontValidator() self._validators["textposition"] = v_scattercarpet.TextpositionValidator() self._validators["textpositionsrc"] = v_scattercarpet.TextpositionsrcValidator() self._validators["textsrc"] = v_scattercarpet.TextsrcValidator() self._validators["texttemplate"] = v_scattercarpet.TexttemplateValidator() self._validators["texttemplatesrc"] = v_scattercarpet.TexttemplatesrcValidator() self._validators["uid"] = v_scattercarpet.UidValidator() self._validators["uirevision"] = v_scattercarpet.UirevisionValidator() self._validators["unselected"] = v_scattercarpet.UnselectedValidator() self._validators["visible"] = v_scattercarpet.VisibleValidator() self._validators["xaxis"] = v_scattercarpet.XAxisValidator() self._validators["yaxis"] = v_scattercarpet.YAxisValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("a", None) self["a"] = a if a is not None else _v _v = arg.pop("asrc", None) self["asrc"] = asrc if asrc is not None else _v _v = arg.pop("b", None) self["b"] = b if b is not None else _v _v = arg.pop("bsrc", None) self["bsrc"] = bsrc if bsrc is not None else _v _v = arg.pop("carpet", None) self["carpet"] = carpet if carpet is not None else _v _v = arg.pop("connectgaps", None) self["connectgaps"] = connectgaps if connectgaps is not None else _v _v = arg.pop("customdata", None) self["customdata"] = customdata if customdata is not None else _v _v = arg.pop("customdatasrc", None) self["customdatasrc"] = customdatasrc if customdatasrc is not None else _v _v = arg.pop("fill", None) self["fill"] = fill if fill is not None else _v _v = arg.pop("fillcolor", None) self["fillcolor"] = fillcolor if fillcolor is not None else _v _v = arg.pop("hoverinfo", None) self["hoverinfo"] = hoverinfo if hoverinfo is not None else _v _v = arg.pop("hoverinfosrc", None) self["hoverinfosrc"] = hoverinfosrc if hoverinfosrc is not None else _v _v = arg.pop("hoverlabel", None) self["hoverlabel"] = hoverlabel if hoverlabel is not None else _v _v = arg.pop("hoveron", None) self["hoveron"] = hoveron if hoveron is not None else _v _v = arg.pop("hovertemplate", None) self["hovertemplate"] = hovertemplate if hovertemplate is not None else _v _v = arg.pop("hovertemplatesrc", None) self["hovertemplatesrc"] = ( hovertemplatesrc if hovertemplatesrc is not None else _v ) _v = arg.pop("hovertext", None) self["hovertext"] = hovertext if hovertext is not None else _v _v = arg.pop("hovertextsrc", None) self["hovertextsrc"] = hovertextsrc if hovertextsrc is not None else _v _v = arg.pop("ids", None) self["ids"] = ids if ids is not None else _v _v = arg.pop("idssrc", None) self["idssrc"] = idssrc if idssrc is not None else _v _v = arg.pop("legendgroup", None) self["legendgroup"] = legendgroup if legendgroup is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v _v = arg.pop("meta", None) self["meta"] = meta if meta is not None else _v _v = arg.pop("metasrc", None) self["metasrc"] = metasrc if metasrc is not None else _v _v = arg.pop("mode", None) self["mode"] = mode if mode is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("selected", None) self["selected"] = selected if selected is not None else _v _v = arg.pop("selectedpoints", None) self["selectedpoints"] = selectedpoints if selectedpoints is not None else _v _v = arg.pop("showlegend", None) self["showlegend"] = showlegend if showlegend is not None else _v _v = arg.pop("stream", None) self["stream"] = stream if stream is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v _v = arg.pop("textfont", None) self["textfont"] = textfont if textfont is not None else _v _v = arg.pop("textposition", None) self["textposition"] = textposition if textposition is not None else _v _v = arg.pop("textpositionsrc", None) self["textpositionsrc"] = textpositionsrc if textpositionsrc is not None else _v _v = arg.pop("textsrc", None) self["textsrc"] = textsrc if textsrc is not None else _v _v = arg.pop("texttemplate", None) self["texttemplate"] = texttemplate if texttemplate is not None else _v _v = arg.pop("texttemplatesrc", None) self["texttemplatesrc"] = texttemplatesrc if texttemplatesrc is not None else _v _v = arg.pop("uid", None) self["uid"] = uid if uid is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("unselected", None) self["unselected"] = unselected if unselected is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("xaxis", None) self["xaxis"] = xaxis if xaxis is not None else _v _v = arg.pop("yaxis", None) self["yaxis"] = yaxis if yaxis is not None else _v # Read-only literals # ------------------ from _plotly_utils.basevalidators import LiteralValidator self._props["type"] = "scattercarpet" self._validators["type"] = LiteralValidator( plotly_name="type", parent_name="scattercarpet", val="scattercarpet" ) arg.pop("type", None) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceType as _BaseTraceType import copy as _copy class Scatter3d(_BaseTraceType): # connectgaps # ----------- @property def connectgaps(self): """ Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. The 'connectgaps' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["connectgaps"] @connectgaps.setter def connectgaps(self, val): self["connectgaps"] = val # customdata # ---------- @property def customdata(self): """ Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements The 'customdata' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["customdata"] @customdata.setter def customdata(self, val): self["customdata"] = val # customdatasrc # ------------- @property def customdatasrc(self): """ Sets the source reference on plot.ly for customdata . The 'customdatasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["customdatasrc"] @customdatasrc.setter def customdatasrc(self, val): self["customdatasrc"] = val # error_x # ------- @property def error_x(self): """ The 'error_x' property is an instance of ErrorX that may be specified as: - An instance of plotly.graph_objs.scatter3d.ErrorX - A dict of string/value properties that will be passed to the ErrorX constructor Supported dict properties: array Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. arrayminus Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. arrayminussrc Sets the source reference on plot.ly for arrayminus . arraysrc Sets the source reference on plot.ly for array . color Sets the stoke color of the error bars. copy_zstyle symmetric Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. thickness Sets the thickness (in px) of the error bars. traceref tracerefminus type Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. value Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. valueminus Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars visible Determines whether or not this set of error bars is visible. width Sets the width (in px) of the cross-bar at both ends of the error bars. Returns ------- plotly.graph_objs.scatter3d.ErrorX """ return self["error_x"] @error_x.setter def error_x(self, val): self["error_x"] = val # error_y # ------- @property def error_y(self): """ The 'error_y' property is an instance of ErrorY that may be specified as: - An instance of plotly.graph_objs.scatter3d.ErrorY - A dict of string/value properties that will be passed to the ErrorY constructor Supported dict properties: array Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. arrayminus Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. arrayminussrc Sets the source reference on plot.ly for arrayminus . arraysrc Sets the source reference on plot.ly for array . color Sets the stoke color of the error bars. copy_zstyle symmetric Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. thickness Sets the thickness (in px) of the error bars. traceref tracerefminus type Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. value Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. valueminus Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars visible Determines whether or not this set of error bars is visible. width Sets the width (in px) of the cross-bar at both ends of the error bars. Returns ------- plotly.graph_objs.scatter3d.ErrorY """ return self["error_y"] @error_y.setter def error_y(self, val): self["error_y"] = val # error_z # ------- @property def error_z(self): """ The 'error_z' property is an instance of ErrorZ that may be specified as: - An instance of plotly.graph_objs.scatter3d.ErrorZ - A dict of string/value properties that will be passed to the ErrorZ constructor Supported dict properties: array Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. arrayminus Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. arrayminussrc Sets the source reference on plot.ly for arrayminus . arraysrc Sets the source reference on plot.ly for array . color Sets the stoke color of the error bars. symmetric Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. thickness Sets the thickness (in px) of the error bars. traceref tracerefminus type Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. value Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. valueminus Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars visible Determines whether or not this set of error bars is visible. width Sets the width (in px) of the cross-bar at both ends of the error bars. Returns ------- plotly.graph_objs.scatter3d.ErrorZ """ return self["error_z"] @error_z.setter def error_z(self, val): self["error_z"] = val # hoverinfo # --------- @property def hoverinfo(self): """ Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. The 'hoverinfo' property is a flaglist and may be specified as a string containing: - Any combination of ['x', 'y', 'z', 'text', 'name'] joined with '+' characters (e.g. 'x+y') OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') - A list or array of the above Returns ------- Any|numpy.ndarray """ return self["hoverinfo"] @hoverinfo.setter def hoverinfo(self, val): self["hoverinfo"] = val # hoverinfosrc # ------------ @property def hoverinfosrc(self): """ Sets the source reference on plot.ly for hoverinfo . The 'hoverinfosrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hoverinfosrc"] @hoverinfosrc.setter def hoverinfosrc(self, val): self["hoverinfosrc"] = val # hoverlabel # ---------- @property def hoverlabel(self): """ The 'hoverlabel' property is an instance of Hoverlabel that may be specified as: - An instance of plotly.graph_objs.scatter3d.Hoverlabel - A dict of string/value properties that will be passed to the Hoverlabel constructor Supported dict properties: align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- plotly.graph_objs.scatter3d.Hoverlabel """ return self["hoverlabel"] @hoverlabel.setter def hoverlabel(self, val): self["hoverlabel"] = val # hovertemplate # ------------- @property def hovertemplate(self): """ Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event- data. Additionally, every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. The 'hovertemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertemplate"] @hovertemplate.setter def hovertemplate(self, val): self["hovertemplate"] = val # hovertemplatesrc # ---------------- @property def hovertemplatesrc(self): """ Sets the source reference on plot.ly for hovertemplate . The 'hovertemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertemplatesrc"] @hovertemplatesrc.setter def hovertemplatesrc(self, val): self["hovertemplatesrc"] = val # hovertext # --------- @property def hovertext(self): """ Sets text elements associated with each (x,y,z) triplet. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y,z) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. The 'hovertext' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertext"] @hovertext.setter def hovertext(self, val): self["hovertext"] = val # hovertextsrc # ------------ @property def hovertextsrc(self): """ Sets the source reference on plot.ly for hovertext . The 'hovertextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertextsrc"] @hovertextsrc.setter def hovertextsrc(self, val): self["hovertextsrc"] = val # ids # --- @property def ids(self): """ Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. The 'ids' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ids"] @ids.setter def ids(self, val): self["ids"] = val # idssrc # ------ @property def idssrc(self): """ Sets the source reference on plot.ly for ids . The 'idssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["idssrc"] @idssrc.setter def idssrc(self, val): self["idssrc"] = val # legendgroup # ----------- @property def legendgroup(self): """ Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. The 'legendgroup' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["legendgroup"] @legendgroup.setter def legendgroup(self, val): self["legendgroup"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.scatter3d.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `line.colorscale`. Has an effect only if in `line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `line.color`) or the bounds set in `line.cmin` and `line.cmax` Has an effect only if in `line.color`is set to a numerical array. Defaults to `false` when `line.cmin` and `line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `line.color`is set to a numerical array. Value should have the same units as in `line.color` and if set, `line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `line.cmin` and/or `line.cmax` to be equidistant to this point. Has an effect only if in `line.color`is set to a numerical array. Value should have the same units as in `line.color`. Has no effect when `line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `line.color`is set to a numerical array. Value should have the same units as in `line.color` and if set, `line.cmax` must be set as well. color Sets thelinecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `line.cmin` and `line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.scatter3d.line.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`line.cmin` and `line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu ,Greens,YlOrRd,Bluered,RdBu,Reds,Blues,Picnic,R ainbow,Portland,Jet,Hot,Blackbody,Earth,Electri c,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . dash Sets the dash style of the lines. reversescale Reverses the color mapping if true. Has an effect only if in `line.color`is set to a numerical array. If true, `line.cmin` will correspond to the last color in the array and `line.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `line.color`is set to a numerical array. width Sets the line width (in px). Returns ------- plotly.graph_objs.scatter3d.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.scatter3d.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.scatter3d.marker.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . line plotly.graph_objects.scatter3d.marker.Line instance or dict with compatible properties opacity Sets the marker opacity. Note that the marker opacity for scatter3d traces must be a scalar value for performance reasons. To set a blending opacity value (i.e. which is not transparent), set "marker.color" to an rgba color and use its alpha channel. reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. size Sets the marker size (in px). sizemin Has an effect only if `marker.size` is set to a numerical array. Sets the minimum size (in px) of the rendered marker points. sizemode Has an effect only if `marker.size` is set to a numerical array. Sets the rule for which the data in `size` is converted to pixels. sizeref Has an effect only if `marker.size` is set to a numerical array. Sets the scale factor used to determine the rendered size of marker points. Use with `sizemin` and `sizemode`. sizesrc Sets the source reference on plot.ly for size . symbol Sets the marker symbol type. symbolsrc Sets the source reference on plot.ly for symbol . Returns ------- plotly.graph_objs.scatter3d.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # meta # ---- @property def meta(self): """ Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. The 'meta' property accepts values of any type Returns ------- Any|numpy.ndarray """ return self["meta"] @meta.setter def meta(self, val): self["meta"] = val # metasrc # ------- @property def metasrc(self): """ Sets the source reference on plot.ly for meta . The 'metasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["metasrc"] @metasrc.setter def metasrc(self, val): self["metasrc"] = val # mode # ---- @property def mode(self): """ Determines the drawing mode for this scatter trace. If the provided `mode` includes "text" then the `text` elements appear at the coordinates. Otherwise, the `text` elements appear on hover. If there are less than 20 points and the trace is not stacked then the default is "lines+markers". Otherwise, "lines". The 'mode' property is a flaglist and may be specified as a string containing: - Any combination of ['lines', 'markers', 'text'] joined with '+' characters (e.g. 'lines+markers') OR exactly one of ['none'] (e.g. 'none') Returns ------- Any """ return self["mode"] @mode.setter def mode(self, val): self["mode"] = val # name # ---- @property def name(self): """ Sets the trace name. The trace name appear as the legend item and on hover. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the trace. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # projection # ---------- @property def projection(self): """ The 'projection' property is an instance of Projection that may be specified as: - An instance of plotly.graph_objs.scatter3d.Projection - A dict of string/value properties that will be passed to the Projection constructor Supported dict properties: x plotly.graph_objects.scatter3d.projection.X instance or dict with compatible properties y plotly.graph_objects.scatter3d.projection.Y instance or dict with compatible properties z plotly.graph_objects.scatter3d.projection.Z instance or dict with compatible properties Returns ------- plotly.graph_objs.scatter3d.Projection """ return self["projection"] @projection.setter def projection(self, val): self["projection"] = val # scene # ----- @property def scene(self): """ Sets a reference between this trace's 3D coordinate system and a 3D scene. If "scene" (the default value), the (x,y,z) coordinates refer to `layout.scene`. If "scene2", the (x,y,z) coordinates refer to `layout.scene2`, and so on. The 'scene' property is an identifier of a particular subplot, of type 'scene', that may be specified as the string 'scene' optionally followed by an integer >= 1 (e.g. 'scene', 'scene1', 'scene2', 'scene3', etc.) Returns ------- str """ return self["scene"] @scene.setter def scene(self, val): self["scene"] = val # showlegend # ---------- @property def showlegend(self): """ Determines whether or not an item corresponding to this trace is shown in the legend. The 'showlegend' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showlegend"] @showlegend.setter def showlegend(self, val): self["showlegend"] = val # stream # ------ @property def stream(self): """ The 'stream' property is an instance of Stream that may be specified as: - An instance of plotly.graph_objs.scatter3d.Stream - A dict of string/value properties that will be passed to the Stream constructor Supported dict properties: maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- plotly.graph_objs.scatter3d.Stream """ return self["stream"] @stream.setter def stream(self, val): self["stream"] = val # surfaceaxis # ----------- @property def surfaceaxis(self): """ If "-1", the scatter points are not fill with a surface If 0, 1, 2, the scatter points are filled with a Delaunay surface about the x, y, z respectively. The 'surfaceaxis' property is an enumeration that may be specified as: - One of the following enumeration values: [-1, 0, 1, 2] Returns ------- Any """ return self["surfaceaxis"] @surfaceaxis.setter def surfaceaxis(self, val): self["surfaceaxis"] = val # surfacecolor # ------------ @property def surfacecolor(self): """ Sets the surface fill color. The 'surfacecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["surfacecolor"] @surfacecolor.setter def surfacecolor(self, val): self["surfacecolor"] = val # text # ---- @property def text(self): """ Sets text elements associated with each (x,y,z) triplet. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y,z) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["text"] @text.setter def text(self, val): self["text"] = val # textfont # -------- @property def textfont(self): """ The 'textfont' property is an instance of Textfont that may be specified as: - An instance of plotly.graph_objs.scatter3d.Textfont - A dict of string/value properties that will be passed to the Textfont constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.scatter3d.Textfont """ return self["textfont"] @textfont.setter def textfont(self, val): self["textfont"] = val # textposition # ------------ @property def textposition(self): """ Sets the positions of the `text` elements with respects to the (x,y) coordinates. The 'textposition' property is an enumeration that may be specified as: - One of the following enumeration values: ['top left', 'top center', 'top right', 'middle left', 'middle center', 'middle right', 'bottom left', 'bottom center', 'bottom right'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["textposition"] @textposition.setter def textposition(self, val): self["textposition"] = val # textpositionsrc # --------------- @property def textpositionsrc(self): """ Sets the source reference on plot.ly for textposition . The 'textpositionsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["textpositionsrc"] @textpositionsrc.setter def textpositionsrc(self, val): self["textpositionsrc"] = val # textsrc # ------- @property def textsrc(self): """ Sets the source reference on plot.ly for text . The 'textsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["textsrc"] @textsrc.setter def textsrc(self, val): self["textsrc"] = val # texttemplate # ------------ @property def texttemplate(self): """ Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. The 'texttemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["texttemplate"] @texttemplate.setter def texttemplate(self, val): self["texttemplate"] = val # texttemplatesrc # --------------- @property def texttemplatesrc(self): """ Sets the source reference on plot.ly for texttemplate . The 'texttemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["texttemplatesrc"] @texttemplatesrc.setter def texttemplatesrc(self, val): self["texttemplatesrc"] = val # uid # --- @property def uid(self): """ Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. The 'uid' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["uid"] @uid.setter def uid(self, val): self["uid"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # visible # ------- @property def visible(self): """ Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). The 'visible' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'legendonly'] Returns ------- Any """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # x # - @property def x(self): """ Sets the x coordinates. The 'x' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["x"] @x.setter def x(self, val): self["x"] = val # xcalendar # --------- @property def xcalendar(self): """ Sets the calendar system to use with `x` date data. The 'xcalendar' property is an enumeration that may be specified as: - One of the following enumeration values: ['gregorian', 'chinese', 'coptic', 'discworld', 'ethiopian', 'hebrew', 'islamic', 'julian', 'mayan', 'nanakshahi', 'nepali', 'persian', 'jalali', 'taiwan', 'thai', 'ummalqura'] Returns ------- Any """ return self["xcalendar"] @xcalendar.setter def xcalendar(self, val): self["xcalendar"] = val # xsrc # ---- @property def xsrc(self): """ Sets the source reference on plot.ly for x . The 'xsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["xsrc"] @xsrc.setter def xsrc(self, val): self["xsrc"] = val # y # - @property def y(self): """ Sets the y coordinates. The 'y' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["y"] @y.setter def y(self, val): self["y"] = val # ycalendar # --------- @property def ycalendar(self): """ Sets the calendar system to use with `y` date data. The 'ycalendar' property is an enumeration that may be specified as: - One of the following enumeration values: ['gregorian', 'chinese', 'coptic', 'discworld', 'ethiopian', 'hebrew', 'islamic', 'julian', 'mayan', 'nanakshahi', 'nepali', 'persian', 'jalali', 'taiwan', 'thai', 'ummalqura'] Returns ------- Any """ return self["ycalendar"] @ycalendar.setter def ycalendar(self, val): self["ycalendar"] = val # ysrc # ---- @property def ysrc(self): """ Sets the source reference on plot.ly for y . The 'ysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ysrc"] @ysrc.setter def ysrc(self, val): self["ysrc"] = val # z # - @property def z(self): """ Sets the z coordinates. The 'z' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["z"] @z.setter def z(self, val): self["z"] = val # zcalendar # --------- @property def zcalendar(self): """ Sets the calendar system to use with `z` date data. The 'zcalendar' property is an enumeration that may be specified as: - One of the following enumeration values: ['gregorian', 'chinese', 'coptic', 'discworld', 'ethiopian', 'hebrew', 'islamic', 'julian', 'mayan', 'nanakshahi', 'nepali', 'persian', 'jalali', 'taiwan', 'thai', 'ummalqura'] Returns ------- Any """ return self["zcalendar"] @zcalendar.setter def zcalendar(self, val): self["zcalendar"] = val # zsrc # ---- @property def zsrc(self): """ Sets the source reference on plot.ly for z . The 'zsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["zsrc"] @zsrc.setter def zsrc(self, val): self["zsrc"] = val # type # ---- @property def type(self): return self._props["type"] # property parent name # -------------------- @property def _parent_path_str(self): return "" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . error_x plotly.graph_objects.scatter3d.ErrorX instance or dict with compatible properties error_y plotly.graph_objects.scatter3d.ErrorY instance or dict with compatible properties error_z plotly.graph_objects.scatter3d.ErrorZ instance or dict with compatible properties hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.scatter3d.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets text elements associated with each (x,y,z) triplet. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y,z) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.scatter3d.Line instance or dict with compatible properties marker plotly.graph_objects.scatter3d.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . mode Determines the drawing mode for this scatter trace. If the provided `mode` includes "text" then the `text` elements appear at the coordinates. Otherwise, the `text` elements appear on hover. If there are less than 20 points and the trace is not stacked then the default is "lines+markers". Otherwise, "lines". name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. projection plotly.graph_objects.scatter3d.Projection instance or dict with compatible properties scene Sets a reference between this trace's 3D coordinate system and a 3D scene. If "scene" (the default value), the (x,y,z) coordinates refer to `layout.scene`. If "scene2", the (x,y,z) coordinates refer to `layout.scene2`, and so on. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.scatter3d.Stream instance or dict with compatible properties surfaceaxis If "-1", the scatter points are not fill with a surface If 0, 1, 2, the scatter points are filled with a Delaunay surface about the x, y, z respectively. surfacecolor Sets the surface fill color. text Sets text elements associated with each (x,y,z) triplet. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y,z) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont plotly.graph_objects.scatter3d.Textfont instance or dict with compatible properties textposition Sets the positions of the `text` elements with respects to the (x,y) coordinates. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. texttemplatesrc Sets the source reference on plot.ly for texttemplate . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the x coordinates. xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . y Sets the y coordinates. ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . z Sets the z coordinates. zcalendar Sets the calendar system to use with `z` date data. zsrc Sets the source reference on plot.ly for z . """ def __init__( self, arg=None, connectgaps=None, customdata=None, customdatasrc=None, error_x=None, error_y=None, error_z=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, legendgroup=None, line=None, marker=None, meta=None, metasrc=None, mode=None, name=None, opacity=None, projection=None, scene=None, showlegend=None, stream=None, surfaceaxis=None, surfacecolor=None, text=None, textfont=None, textposition=None, textpositionsrc=None, textsrc=None, texttemplate=None, texttemplatesrc=None, uid=None, uirevision=None, visible=None, x=None, xcalendar=None, xsrc=None, y=None, ycalendar=None, ysrc=None, z=None, zcalendar=None, zsrc=None, **kwargs ): """ Construct a new Scatter3d object The data visualized as scatter point or lines in 3D dimension is set in `x`, `y`, `z`. Text (appearing either on the chart or on hover only) is via `text`. Bubble charts are achieved by setting `marker.size` and/or `marker.color` Projections are achieved via `projection`. Surface fills are achieved via `surfaceaxis`. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.Scatter3d connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . error_x plotly.graph_objects.scatter3d.ErrorX instance or dict with compatible properties error_y plotly.graph_objects.scatter3d.ErrorY instance or dict with compatible properties error_z plotly.graph_objects.scatter3d.ErrorZ instance or dict with compatible properties hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.scatter3d.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets text elements associated with each (x,y,z) triplet. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y,z) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.scatter3d.Line instance or dict with compatible properties marker plotly.graph_objects.scatter3d.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . mode Determines the drawing mode for this scatter trace. If the provided `mode` includes "text" then the `text` elements appear at the coordinates. Otherwise, the `text` elements appear on hover. If there are less than 20 points and the trace is not stacked then the default is "lines+markers". Otherwise, "lines". name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. projection plotly.graph_objects.scatter3d.Projection instance or dict with compatible properties scene Sets a reference between this trace's 3D coordinate system and a 3D scene. If "scene" (the default value), the (x,y,z) coordinates refer to `layout.scene`. If "scene2", the (x,y,z) coordinates refer to `layout.scene2`, and so on. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.scatter3d.Stream instance or dict with compatible properties surfaceaxis If "-1", the scatter points are not fill with a surface If 0, 1, 2, the scatter points are filled with a Delaunay surface about the x, y, z respectively. surfacecolor Sets the surface fill color. text Sets text elements associated with each (x,y,z) triplet. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y,z) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont plotly.graph_objects.scatter3d.Textfont instance or dict with compatible properties textposition Sets the positions of the `text` elements with respects to the (x,y) coordinates. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. texttemplatesrc Sets the source reference on plot.ly for texttemplate . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the x coordinates. xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . y Sets the y coordinates. ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . z Sets the z coordinates. zcalendar Sets the calendar system to use with `z` date data. zsrc Sets the source reference on plot.ly for z . Returns ------- Scatter3d """ super(Scatter3d, self).__init__("scatter3d") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.Scatter3d constructor must be a dict or an instance of plotly.graph_objs.Scatter3d""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators import scatter3d as v_scatter3d # Initialize validators # --------------------- self._validators["connectgaps"] = v_scatter3d.ConnectgapsValidator() self._validators["customdata"] = v_scatter3d.CustomdataValidator() self._validators["customdatasrc"] = v_scatter3d.CustomdatasrcValidator() self._validators["error_x"] = v_scatter3d.ErrorXValidator() self._validators["error_y"] = v_scatter3d.ErrorYValidator() self._validators["error_z"] = v_scatter3d.ErrorZValidator() self._validators["hoverinfo"] = v_scatter3d.HoverinfoValidator() self._validators["hoverinfosrc"] = v_scatter3d.HoverinfosrcValidator() self._validators["hoverlabel"] = v_scatter3d.HoverlabelValidator() self._validators["hovertemplate"] = v_scatter3d.HovertemplateValidator() self._validators["hovertemplatesrc"] = v_scatter3d.HovertemplatesrcValidator() self._validators["hovertext"] = v_scatter3d.HovertextValidator() self._validators["hovertextsrc"] = v_scatter3d.HovertextsrcValidator() self._validators["ids"] = v_scatter3d.IdsValidator() self._validators["idssrc"] = v_scatter3d.IdssrcValidator() self._validators["legendgroup"] = v_scatter3d.LegendgroupValidator() self._validators["line"] = v_scatter3d.LineValidator() self._validators["marker"] = v_scatter3d.MarkerValidator() self._validators["meta"] = v_scatter3d.MetaValidator() self._validators["metasrc"] = v_scatter3d.MetasrcValidator() self._validators["mode"] = v_scatter3d.ModeValidator() self._validators["name"] = v_scatter3d.NameValidator() self._validators["opacity"] = v_scatter3d.OpacityValidator() self._validators["projection"] = v_scatter3d.ProjectionValidator() self._validators["scene"] = v_scatter3d.SceneValidator() self._validators["showlegend"] = v_scatter3d.ShowlegendValidator() self._validators["stream"] = v_scatter3d.StreamValidator() self._validators["surfaceaxis"] = v_scatter3d.SurfaceaxisValidator() self._validators["surfacecolor"] = v_scatter3d.SurfacecolorValidator() self._validators["text"] = v_scatter3d.TextValidator() self._validators["textfont"] = v_scatter3d.TextfontValidator() self._validators["textposition"] = v_scatter3d.TextpositionValidator() self._validators["textpositionsrc"] = v_scatter3d.TextpositionsrcValidator() self._validators["textsrc"] = v_scatter3d.TextsrcValidator() self._validators["texttemplate"] = v_scatter3d.TexttemplateValidator() self._validators["texttemplatesrc"] = v_scatter3d.TexttemplatesrcValidator() self._validators["uid"] = v_scatter3d.UidValidator() self._validators["uirevision"] = v_scatter3d.UirevisionValidator() self._validators["visible"] = v_scatter3d.VisibleValidator() self._validators["x"] = v_scatter3d.XValidator() self._validators["xcalendar"] = v_scatter3d.XcalendarValidator() self._validators["xsrc"] = v_scatter3d.XsrcValidator() self._validators["y"] = v_scatter3d.YValidator() self._validators["ycalendar"] = v_scatter3d.YcalendarValidator() self._validators["ysrc"] = v_scatter3d.YsrcValidator() self._validators["z"] = v_scatter3d.ZValidator() self._validators["zcalendar"] = v_scatter3d.ZcalendarValidator() self._validators["zsrc"] = v_scatter3d.ZsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("connectgaps", None) self["connectgaps"] = connectgaps if connectgaps is not None else _v _v = arg.pop("customdata", None) self["customdata"] = customdata if customdata is not None else _v _v = arg.pop("customdatasrc", None) self["customdatasrc"] = customdatasrc if customdatasrc is not None else _v _v = arg.pop("error_x", None) self["error_x"] = error_x if error_x is not None else _v _v = arg.pop("error_y", None) self["error_y"] = error_y if error_y is not None else _v _v = arg.pop("error_z", None) self["error_z"] = error_z if error_z is not None else _v _v = arg.pop("hoverinfo", None) self["hoverinfo"] = hoverinfo if hoverinfo is not None else _v _v = arg.pop("hoverinfosrc", None) self["hoverinfosrc"] = hoverinfosrc if hoverinfosrc is not None else _v _v = arg.pop("hoverlabel", None) self["hoverlabel"] = hoverlabel if hoverlabel is not None else _v _v = arg.pop("hovertemplate", None) self["hovertemplate"] = hovertemplate if hovertemplate is not None else _v _v = arg.pop("hovertemplatesrc", None) self["hovertemplatesrc"] = ( hovertemplatesrc if hovertemplatesrc is not None else _v ) _v = arg.pop("hovertext", None) self["hovertext"] = hovertext if hovertext is not None else _v _v = arg.pop("hovertextsrc", None) self["hovertextsrc"] = hovertextsrc if hovertextsrc is not None else _v _v = arg.pop("ids", None) self["ids"] = ids if ids is not None else _v _v = arg.pop("idssrc", None) self["idssrc"] = idssrc if idssrc is not None else _v _v = arg.pop("legendgroup", None) self["legendgroup"] = legendgroup if legendgroup is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v _v = arg.pop("meta", None) self["meta"] = meta if meta is not None else _v _v = arg.pop("metasrc", None) self["metasrc"] = metasrc if metasrc is not None else _v _v = arg.pop("mode", None) self["mode"] = mode if mode is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("projection", None) self["projection"] = projection if projection is not None else _v _v = arg.pop("scene", None) self["scene"] = scene if scene is not None else _v _v = arg.pop("showlegend", None) self["showlegend"] = showlegend if showlegend is not None else _v _v = arg.pop("stream", None) self["stream"] = stream if stream is not None else _v _v = arg.pop("surfaceaxis", None) self["surfaceaxis"] = surfaceaxis if surfaceaxis is not None else _v _v = arg.pop("surfacecolor", None) self["surfacecolor"] = surfacecolor if surfacecolor is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v _v = arg.pop("textfont", None) self["textfont"] = textfont if textfont is not None else _v _v = arg.pop("textposition", None) self["textposition"] = textposition if textposition is not None else _v _v = arg.pop("textpositionsrc", None) self["textpositionsrc"] = textpositionsrc if textpositionsrc is not None else _v _v = arg.pop("textsrc", None) self["textsrc"] = textsrc if textsrc is not None else _v _v = arg.pop("texttemplate", None) self["texttemplate"] = texttemplate if texttemplate is not None else _v _v = arg.pop("texttemplatesrc", None) self["texttemplatesrc"] = texttemplatesrc if texttemplatesrc is not None else _v _v = arg.pop("uid", None) self["uid"] = uid if uid is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xcalendar", None) self["xcalendar"] = xcalendar if xcalendar is not None else _v _v = arg.pop("xsrc", None) self["xsrc"] = xsrc if xsrc is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("ycalendar", None) self["ycalendar"] = ycalendar if ycalendar is not None else _v _v = arg.pop("ysrc", None) self["ysrc"] = ysrc if ysrc is not None else _v _v = arg.pop("z", None) self["z"] = z if z is not None else _v _v = arg.pop("zcalendar", None) self["zcalendar"] = zcalendar if zcalendar is not None else _v _v = arg.pop("zsrc", None) self["zsrc"] = zsrc if zsrc is not None else _v # Read-only literals # ------------------ from _plotly_utils.basevalidators import LiteralValidator self._props["type"] = "scatter3d" self._validators["type"] = LiteralValidator( plotly_name="type", parent_name="scatter3d", val="scatter3d" ) arg.pop("type", None) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceType as _BaseTraceType import copy as _copy class Scatter(_BaseTraceType): # cliponaxis # ---------- @property def cliponaxis(self): """ Determines whether or not markers and text nodes are clipped about the subplot axes. To show markers and text nodes above axis lines and tick labels, make sure to set `xaxis.layer` and `yaxis.layer` to *below traces*. The 'cliponaxis' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["cliponaxis"] @cliponaxis.setter def cliponaxis(self, val): self["cliponaxis"] = val # connectgaps # ----------- @property def connectgaps(self): """ Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. The 'connectgaps' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["connectgaps"] @connectgaps.setter def connectgaps(self, val): self["connectgaps"] = val # customdata # ---------- @property def customdata(self): """ Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements The 'customdata' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["customdata"] @customdata.setter def customdata(self, val): self["customdata"] = val # customdatasrc # ------------- @property def customdatasrc(self): """ Sets the source reference on plot.ly for customdata . The 'customdatasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["customdatasrc"] @customdatasrc.setter def customdatasrc(self, val): self["customdatasrc"] = val # dx # -- @property def dx(self): """ Sets the x coordinate step. See `x0` for more info. The 'dx' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["dx"] @dx.setter def dx(self, val): self["dx"] = val # dy # -- @property def dy(self): """ Sets the y coordinate step. See `y0` for more info. The 'dy' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["dy"] @dy.setter def dy(self, val): self["dy"] = val # error_x # ------- @property def error_x(self): """ The 'error_x' property is an instance of ErrorX that may be specified as: - An instance of plotly.graph_objs.scatter.ErrorX - A dict of string/value properties that will be passed to the ErrorX constructor Supported dict properties: array Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. arrayminus Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. arrayminussrc Sets the source reference on plot.ly for arrayminus . arraysrc Sets the source reference on plot.ly for array . color Sets the stoke color of the error bars. copy_ystyle symmetric Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. thickness Sets the thickness (in px) of the error bars. traceref tracerefminus type Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. value Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. valueminus Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars visible Determines whether or not this set of error bars is visible. width Sets the width (in px) of the cross-bar at both ends of the error bars. Returns ------- plotly.graph_objs.scatter.ErrorX """ return self["error_x"] @error_x.setter def error_x(self, val): self["error_x"] = val # error_y # ------- @property def error_y(self): """ The 'error_y' property is an instance of ErrorY that may be specified as: - An instance of plotly.graph_objs.scatter.ErrorY - A dict of string/value properties that will be passed to the ErrorY constructor Supported dict properties: array Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. arrayminus Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. arrayminussrc Sets the source reference on plot.ly for arrayminus . arraysrc Sets the source reference on plot.ly for array . color Sets the stoke color of the error bars. symmetric Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. thickness Sets the thickness (in px) of the error bars. traceref tracerefminus type Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. value Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. valueminus Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars visible Determines whether or not this set of error bars is visible. width Sets the width (in px) of the cross-bar at both ends of the error bars. Returns ------- plotly.graph_objs.scatter.ErrorY """ return self["error_y"] @error_y.setter def error_y(self, val): self["error_y"] = val # fill # ---- @property def fill(self): """ Sets the area to fill with a solid color. Defaults to "none" unless this trace is stacked, then it gets "tonexty" ("tonextx") if `orientation` is "v" ("h") Use with `fillcolor` if not "none". "tozerox" and "tozeroy" fill to x=0 and y=0 respectively. "tonextx" and "tonexty" fill between the endpoints of this trace and the endpoints of the trace before it, connecting those endpoints with straight lines (to make a stacked area graph); if there is no trace before it, they behave like "tozerox" and "tozeroy". "toself" connects the endpoints of the trace (or each segment of the trace if it has gaps) into a closed shape. "tonext" fills the space between two traces if one completely encloses the other (eg consecutive contour lines), and behaves like "toself" if there is no trace before it. "tonext" should not be used if one trace does not enclose the other. Traces in a `stackgroup` will only fill to (or be filled to) other traces in the same group. With multiple `stackgroup`s or some traces stacked and some not, if fill- linked traces are not already consecutive, the later ones will be pushed down in the drawing order. The 'fill' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'tozeroy', 'tozerox', 'tonexty', 'tonextx', 'toself', 'tonext'] Returns ------- Any """ return self["fill"] @fill.setter def fill(self, val): self["fill"] = val # fillcolor # --------- @property def fillcolor(self): """ Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. The 'fillcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["fillcolor"] @fillcolor.setter def fillcolor(self, val): self["fillcolor"] = val # groupnorm # --------- @property def groupnorm(self): """ Only relevant when `stackgroup` is used, and only the first `groupnorm` found in the `stackgroup` will be used - including if `visible` is "legendonly" but not if it is `false`. Sets the normalization for the sum of this `stackgroup`. With "fraction", the value of each trace at each location is divided by the sum of all trace values at that location. "percent" is the same but multiplied by 100 to show percentages. If there are multiple subplots, or multiple `stackgroup`s on one subplot, each will be normalized within its own set. The 'groupnorm' property is an enumeration that may be specified as: - One of the following enumeration values: ['', 'fraction', 'percent'] Returns ------- Any """ return self["groupnorm"] @groupnorm.setter def groupnorm(self, val): self["groupnorm"] = val # hoverinfo # --------- @property def hoverinfo(self): """ Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. The 'hoverinfo' property is a flaglist and may be specified as a string containing: - Any combination of ['x', 'y', 'z', 'text', 'name'] joined with '+' characters (e.g. 'x+y') OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') - A list or array of the above Returns ------- Any|numpy.ndarray """ return self["hoverinfo"] @hoverinfo.setter def hoverinfo(self, val): self["hoverinfo"] = val # hoverinfosrc # ------------ @property def hoverinfosrc(self): """ Sets the source reference on plot.ly for hoverinfo . The 'hoverinfosrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hoverinfosrc"] @hoverinfosrc.setter def hoverinfosrc(self, val): self["hoverinfosrc"] = val # hoverlabel # ---------- @property def hoverlabel(self): """ The 'hoverlabel' property is an instance of Hoverlabel that may be specified as: - An instance of plotly.graph_objs.scatter.Hoverlabel - A dict of string/value properties that will be passed to the Hoverlabel constructor Supported dict properties: align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- plotly.graph_objs.scatter.Hoverlabel """ return self["hoverlabel"] @hoverlabel.setter def hoverlabel(self, val): self["hoverlabel"] = val # hoveron # ------- @property def hoveron(self): """ Do the hover effects highlight individual points (markers or line points) or do they highlight filled regions? If the fill is "toself" or "tonext" and there are no markers or text, then the default is "fills", otherwise it is "points". The 'hoveron' property is a flaglist and may be specified as a string containing: - Any combination of ['points', 'fills'] joined with '+' characters (e.g. 'points+fills') Returns ------- Any """ return self["hoveron"] @hoveron.setter def hoveron(self, val): self["hoveron"] = val # hovertemplate # ------------- @property def hovertemplate(self): """ Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event- data. Additionally, every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. The 'hovertemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertemplate"] @hovertemplate.setter def hovertemplate(self, val): self["hovertemplate"] = val # hovertemplatesrc # ---------------- @property def hovertemplatesrc(self): """ Sets the source reference on plot.ly for hovertemplate . The 'hovertemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertemplatesrc"] @hovertemplatesrc.setter def hovertemplatesrc(self, val): self["hovertemplatesrc"] = val # hovertext # --------- @property def hovertext(self): """ Sets hover text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. The 'hovertext' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertext"] @hovertext.setter def hovertext(self, val): self["hovertext"] = val # hovertextsrc # ------------ @property def hovertextsrc(self): """ Sets the source reference on plot.ly for hovertext . The 'hovertextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertextsrc"] @hovertextsrc.setter def hovertextsrc(self, val): self["hovertextsrc"] = val # ids # --- @property def ids(self): """ Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. The 'ids' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ids"] @ids.setter def ids(self, val): self["ids"] = val # idssrc # ------ @property def idssrc(self): """ Sets the source reference on plot.ly for ids . The 'idssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["idssrc"] @idssrc.setter def idssrc(self, val): self["idssrc"] = val # legendgroup # ----------- @property def legendgroup(self): """ Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. The 'legendgroup' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["legendgroup"] @legendgroup.setter def legendgroup(self, val): self["legendgroup"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.scatter.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: color Sets the line color. dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). shape Determines the line shape. With "spline" the lines are drawn using spline interpolation. The other available values correspond to step-wise line shapes. simplify Simplifies lines by removing nearly-collinear points. When transitioning lines, it may be desirable to disable this so that the number of points along the resulting SVG path is unaffected. smoothing Has an effect only if `shape` is set to "spline" Sets the amount of smoothing. 0 corresponds to no smoothing (equivalent to a "linear" shape). width Sets the line width (in px). Returns ------- plotly.graph_objs.scatter.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.scatter.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.scatter.marker.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . gradient plotly.graph_objects.scatter.marker.Gradient instance or dict with compatible properties line plotly.graph_objects.scatter.marker.Line instance or dict with compatible properties maxdisplayed Sets a maximum number of points to be drawn on the graph. 0 corresponds to no limit. opacity Sets the marker opacity. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. size Sets the marker size (in px). sizemin Has an effect only if `marker.size` is set to a numerical array. Sets the minimum size (in px) of the rendered marker points. sizemode Has an effect only if `marker.size` is set to a numerical array. Sets the rule for which the data in `size` is converted to pixels. sizeref Has an effect only if `marker.size` is set to a numerical array. Sets the scale factor used to determine the rendered size of marker points. Use with `sizemin` and `sizemode`. sizesrc Sets the source reference on plot.ly for size . symbol Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot- open" to a symbol name. symbolsrc Sets the source reference on plot.ly for symbol . Returns ------- plotly.graph_objs.scatter.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # meta # ---- @property def meta(self): """ Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. The 'meta' property accepts values of any type Returns ------- Any|numpy.ndarray """ return self["meta"] @meta.setter def meta(self, val): self["meta"] = val # metasrc # ------- @property def metasrc(self): """ Sets the source reference on plot.ly for meta . The 'metasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["metasrc"] @metasrc.setter def metasrc(self, val): self["metasrc"] = val # mode # ---- @property def mode(self): """ Determines the drawing mode for this scatter trace. If the provided `mode` includes "text" then the `text` elements appear at the coordinates. Otherwise, the `text` elements appear on hover. If there are less than 20 points and the trace is not stacked then the default is "lines+markers". Otherwise, "lines". The 'mode' property is a flaglist and may be specified as a string containing: - Any combination of ['lines', 'markers', 'text'] joined with '+' characters (e.g. 'lines+markers') OR exactly one of ['none'] (e.g. 'none') Returns ------- Any """ return self["mode"] @mode.setter def mode(self, val): self["mode"] = val # name # ---- @property def name(self): """ Sets the trace name. The trace name appear as the legend item and on hover. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the trace. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # orientation # ----------- @property def orientation(self): """ Only relevant when `stackgroup` is used, and only the first `orientation` found in the `stackgroup` will be used - including if `visible` is "legendonly" but not if it is `false`. Sets the stacking direction. With "v" ("h"), the y (x) values of subsequent traces are added. Also affects the default value of `fill`. The 'orientation' property is an enumeration that may be specified as: - One of the following enumeration values: ['v', 'h'] Returns ------- Any """ return self["orientation"] @orientation.setter def orientation(self, val): self["orientation"] = val # r # - @property def r(self): """ r coordinates in scatter traces are deprecated!Please switch to the "scatterpolar" trace type.Sets the radial coordinatesfor legacy polar chart only. The 'r' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["r"] @r.setter def r(self, val): self["r"] = val # rsrc # ---- @property def rsrc(self): """ Sets the source reference on plot.ly for r . The 'rsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["rsrc"] @rsrc.setter def rsrc(self, val): self["rsrc"] = val # selected # -------- @property def selected(self): """ The 'selected' property is an instance of Selected that may be specified as: - An instance of plotly.graph_objs.scatter.Selected - A dict of string/value properties that will be passed to the Selected constructor Supported dict properties: marker plotly.graph_objects.scatter.selected.Marker instance or dict with compatible properties textfont plotly.graph_objects.scatter.selected.Textfont instance or dict with compatible properties Returns ------- plotly.graph_objs.scatter.Selected """ return self["selected"] @selected.setter def selected(self, val): self["selected"] = val # selectedpoints # -------------- @property def selectedpoints(self): """ Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. The 'selectedpoints' property accepts values of any type Returns ------- Any """ return self["selectedpoints"] @selectedpoints.setter def selectedpoints(self, val): self["selectedpoints"] = val # showlegend # ---------- @property def showlegend(self): """ Determines whether or not an item corresponding to this trace is shown in the legend. The 'showlegend' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showlegend"] @showlegend.setter def showlegend(self, val): self["showlegend"] = val # stackgaps # --------- @property def stackgaps(self): """ Only relevant when `stackgroup` is used, and only the first `stackgaps` found in the `stackgroup` will be used - including if `visible` is "legendonly" but not if it is `false`. Determines how we handle locations at which other traces in this group have data but this one does not. With *infer zero* we insert a zero at these locations. With "interpolate" we linearly interpolate between existing values, and extrapolate a constant beyond the existing values. The 'stackgaps' property is an enumeration that may be specified as: - One of the following enumeration values: ['infer zero', 'interpolate'] Returns ------- Any """ return self["stackgaps"] @stackgaps.setter def stackgaps(self, val): self["stackgaps"] = val # stackgroup # ---------- @property def stackgroup(self): """ Set several scatter traces (on the same subplot) to the same stackgroup in order to add their y values (or their x values if `orientation` is "h"). If blank or omitted this trace will not be stacked. Stacking also turns `fill` on by default, using "tonexty" ("tonextx") if `orientation` is "h" ("v") and sets the default `mode` to "lines" irrespective of point count. You can only stack on a numeric (linear or log) axis. Traces in a `stackgroup` will only fill to (or be filled to) other traces in the same group. With multiple `stackgroup`s or some traces stacked and some not, if fill-linked traces are not already consecutive, the later ones will be pushed down in the drawing order. The 'stackgroup' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["stackgroup"] @stackgroup.setter def stackgroup(self, val): self["stackgroup"] = val # stream # ------ @property def stream(self): """ The 'stream' property is an instance of Stream that may be specified as: - An instance of plotly.graph_objs.scatter.Stream - A dict of string/value properties that will be passed to the Stream constructor Supported dict properties: maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- plotly.graph_objs.scatter.Stream """ return self["stream"] @stream.setter def stream(self, val): self["stream"] = val # t # - @property def t(self): """ t coordinates in scatter traces are deprecated!Please switch to the "scatterpolar" trace type.Sets the angular coordinatesfor legacy polar chart only. The 't' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["t"] @t.setter def t(self, val): self["t"] = val # text # ---- @property def text(self): """ Sets text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["text"] @text.setter def text(self, val): self["text"] = val # textfont # -------- @property def textfont(self): """ Sets the text font. The 'textfont' property is an instance of Textfont that may be specified as: - An instance of plotly.graph_objs.scatter.Textfont - A dict of string/value properties that will be passed to the Textfont constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.scatter.Textfont """ return self["textfont"] @textfont.setter def textfont(self, val): self["textfont"] = val # textposition # ------------ @property def textposition(self): """ Sets the positions of the `text` elements with respects to the (x,y) coordinates. The 'textposition' property is an enumeration that may be specified as: - One of the following enumeration values: ['top left', 'top center', 'top right', 'middle left', 'middle center', 'middle right', 'bottom left', 'bottom center', 'bottom right'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["textposition"] @textposition.setter def textposition(self, val): self["textposition"] = val # textpositionsrc # --------------- @property def textpositionsrc(self): """ Sets the source reference on plot.ly for textposition . The 'textpositionsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["textpositionsrc"] @textpositionsrc.setter def textpositionsrc(self, val): self["textpositionsrc"] = val # textsrc # ------- @property def textsrc(self): """ Sets the source reference on plot.ly for text . The 'textsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["textsrc"] @textsrc.setter def textsrc(self, val): self["textsrc"] = val # texttemplate # ------------ @property def texttemplate(self): """ Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. The 'texttemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["texttemplate"] @texttemplate.setter def texttemplate(self, val): self["texttemplate"] = val # texttemplatesrc # --------------- @property def texttemplatesrc(self): """ Sets the source reference on plot.ly for texttemplate . The 'texttemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["texttemplatesrc"] @texttemplatesrc.setter def texttemplatesrc(self, val): self["texttemplatesrc"] = val # tsrc # ---- @property def tsrc(self): """ Sets the source reference on plot.ly for t . The 'tsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tsrc"] @tsrc.setter def tsrc(self, val): self["tsrc"] = val # uid # --- @property def uid(self): """ Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. The 'uid' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["uid"] @uid.setter def uid(self, val): self["uid"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # unselected # ---------- @property def unselected(self): """ The 'unselected' property is an instance of Unselected that may be specified as: - An instance of plotly.graph_objs.scatter.Unselected - A dict of string/value properties that will be passed to the Unselected constructor Supported dict properties: marker plotly.graph_objects.scatter.unselected.Marker instance or dict with compatible properties textfont plotly.graph_objects.scatter.unselected.Textfon t instance or dict with compatible properties Returns ------- plotly.graph_objs.scatter.Unselected """ return self["unselected"] @unselected.setter def unselected(self, val): self["unselected"] = val # visible # ------- @property def visible(self): """ Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). The 'visible' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'legendonly'] Returns ------- Any """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # x # - @property def x(self): """ Sets the x coordinates. The 'x' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["x"] @x.setter def x(self, val): self["x"] = val # x0 # -- @property def x0(self): """ Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. The 'x0' property accepts values of any type Returns ------- Any """ return self["x0"] @x0.setter def x0(self, val): self["x0"] = val # xaxis # ----- @property def xaxis(self): """ Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. The 'xaxis' property is an identifier of a particular subplot, of type 'x', that may be specified as the string 'x' optionally followed by an integer >= 1 (e.g. 'x', 'x1', 'x2', 'x3', etc.) Returns ------- str """ return self["xaxis"] @xaxis.setter def xaxis(self, val): self["xaxis"] = val # xcalendar # --------- @property def xcalendar(self): """ Sets the calendar system to use with `x` date data. The 'xcalendar' property is an enumeration that may be specified as: - One of the following enumeration values: ['gregorian', 'chinese', 'coptic', 'discworld', 'ethiopian', 'hebrew', 'islamic', 'julian', 'mayan', 'nanakshahi', 'nepali', 'persian', 'jalali', 'taiwan', 'thai', 'ummalqura'] Returns ------- Any """ return self["xcalendar"] @xcalendar.setter def xcalendar(self, val): self["xcalendar"] = val # xsrc # ---- @property def xsrc(self): """ Sets the source reference on plot.ly for x . The 'xsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["xsrc"] @xsrc.setter def xsrc(self, val): self["xsrc"] = val # y # - @property def y(self): """ Sets the y coordinates. The 'y' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["y"] @y.setter def y(self, val): self["y"] = val # y0 # -- @property def y0(self): """ Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. The 'y0' property accepts values of any type Returns ------- Any """ return self["y0"] @y0.setter def y0(self, val): self["y0"] = val # yaxis # ----- @property def yaxis(self): """ Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. The 'yaxis' property is an identifier of a particular subplot, of type 'y', that may be specified as the string 'y' optionally followed by an integer >= 1 (e.g. 'y', 'y1', 'y2', 'y3', etc.) Returns ------- str """ return self["yaxis"] @yaxis.setter def yaxis(self, val): self["yaxis"] = val # ycalendar # --------- @property def ycalendar(self): """ Sets the calendar system to use with `y` date data. The 'ycalendar' property is an enumeration that may be specified as: - One of the following enumeration values: ['gregorian', 'chinese', 'coptic', 'discworld', 'ethiopian', 'hebrew', 'islamic', 'julian', 'mayan', 'nanakshahi', 'nepali', 'persian', 'jalali', 'taiwan', 'thai', 'ummalqura'] Returns ------- Any """ return self["ycalendar"] @ycalendar.setter def ycalendar(self, val): self["ycalendar"] = val # ysrc # ---- @property def ysrc(self): """ Sets the source reference on plot.ly for y . The 'ysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ysrc"] @ysrc.setter def ysrc(self, val): self["ysrc"] = val # type # ---- @property def type(self): return self._props["type"] # property parent name # -------------------- @property def _parent_path_str(self): return "" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ cliponaxis Determines whether or not markers and text nodes are clipped about the subplot axes. To show markers and text nodes above axis lines and tick labels, make sure to set `xaxis.layer` and `yaxis.layer` to *below traces*. connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dx Sets the x coordinate step. See `x0` for more info. dy Sets the y coordinate step. See `y0` for more info. error_x plotly.graph_objects.scatter.ErrorX instance or dict with compatible properties error_y plotly.graph_objects.scatter.ErrorY instance or dict with compatible properties fill Sets the area to fill with a solid color. Defaults to "none" unless this trace is stacked, then it gets "tonexty" ("tonextx") if `orientation` is "v" ("h") Use with `fillcolor` if not "none". "tozerox" and "tozeroy" fill to x=0 and y=0 respectively. "tonextx" and "tonexty" fill between the endpoints of this trace and the endpoints of the trace before it, connecting those endpoints with straight lines (to make a stacked area graph); if there is no trace before it, they behave like "tozerox" and "tozeroy". "toself" connects the endpoints of the trace (or each segment of the trace if it has gaps) into a closed shape. "tonext" fills the space between two traces if one completely encloses the other (eg consecutive contour lines), and behaves like "toself" if there is no trace before it. "tonext" should not be used if one trace does not enclose the other. Traces in a `stackgroup` will only fill to (or be filled to) other traces in the same group. With multiple `stackgroup`s or some traces stacked and some not, if fill-linked traces are not already consecutive, the later ones will be pushed down in the drawing order. fillcolor Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. groupnorm Only relevant when `stackgroup` is used, and only the first `groupnorm` found in the `stackgroup` will be used - including if `visible` is "legendonly" but not if it is `false`. Sets the normalization for the sum of this `stackgroup`. With "fraction", the value of each trace at each location is divided by the sum of all trace values at that location. "percent" is the same but multiplied by 100 to show percentages. If there are multiple subplots, or multiple `stackgroup`s on one subplot, each will be normalized within its own set. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.scatter.Hoverlabel instance or dict with compatible properties hoveron Do the hover effects highlight individual points (markers or line points) or do they highlight filled regions? If the fill is "toself" or "tonext" and there are no markers or text, then the default is "fills", otherwise it is "points". hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.scatter.Line instance or dict with compatible properties marker plotly.graph_objects.scatter.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . mode Determines the drawing mode for this scatter trace. If the provided `mode` includes "text" then the `text` elements appear at the coordinates. Otherwise, the `text` elements appear on hover. If there are less than 20 points and the trace is not stacked then the default is "lines+markers". Otherwise, "lines". name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. orientation Only relevant when `stackgroup` is used, and only the first `orientation` found in the `stackgroup` will be used - including if `visible` is "legendonly" but not if it is `false`. Sets the stacking direction. With "v" ("h"), the y (x) values of subsequent traces are added. Also affects the default value of `fill`. r r coordinates in scatter traces are deprecated!Please switch to the "scatterpolar" trace type.Sets the radial coordinatesfor legacy polar chart only. rsrc Sets the source reference on plot.ly for r . selected plotly.graph_objects.scatter.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stackgaps Only relevant when `stackgroup` is used, and only the first `stackgaps` found in the `stackgroup` will be used - including if `visible` is "legendonly" but not if it is `false`. Determines how we handle locations at which other traces in this group have data but this one does not. With *infer zero* we insert a zero at these locations. With "interpolate" we linearly interpolate between existing values, and extrapolate a constant beyond the existing values. stackgroup Set several scatter traces (on the same subplot) to the same stackgroup in order to add their y values (or their x values if `orientation` is "h"). If blank or omitted this trace will not be stacked. Stacking also turns `fill` on by default, using "tonexty" ("tonextx") if `orientation` is "h" ("v") and sets the default `mode` to "lines" irrespective of point count. You can only stack on a numeric (linear or log) axis. Traces in a `stackgroup` will only fill to (or be filled to) other traces in the same group. With multiple `stackgroup`s or some traces stacked and some not, if fill-linked traces are not already consecutive, the later ones will be pushed down in the drawing order. stream plotly.graph_objects.scatter.Stream instance or dict with compatible properties t t coordinates in scatter traces are deprecated!Please switch to the "scatterpolar" trace type.Sets the angular coordinatesfor legacy polar chart only. text Sets text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the text font. textposition Sets the positions of the `text` elements with respects to the (x,y) coordinates. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. texttemplatesrc Sets the source reference on plot.ly for texttemplate . tsrc Sets the source reference on plot.ly for t . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.scatter.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the x coordinates. x0 Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . y Sets the y coordinates. y0 Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . """ def __init__( self, arg=None, cliponaxis=None, connectgaps=None, customdata=None, customdatasrc=None, dx=None, dy=None, error_x=None, error_y=None, fill=None, fillcolor=None, groupnorm=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hoveron=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, legendgroup=None, line=None, marker=None, meta=None, metasrc=None, mode=None, name=None, opacity=None, orientation=None, r=None, rsrc=None, selected=None, selectedpoints=None, showlegend=None, stackgaps=None, stackgroup=None, stream=None, t=None, text=None, textfont=None, textposition=None, textpositionsrc=None, textsrc=None, texttemplate=None, texttemplatesrc=None, tsrc=None, uid=None, uirevision=None, unselected=None, visible=None, x=None, x0=None, xaxis=None, xcalendar=None, xsrc=None, y=None, y0=None, yaxis=None, ycalendar=None, ysrc=None, **kwargs ): """ Construct a new Scatter object The scatter trace type encompasses line charts, scatter charts, text charts, and bubble charts. The data visualized as scatter point or lines is set in `x` and `y`. Text (appearing either on the chart or on hover only) is via `text`. Bubble charts are achieved by setting `marker.size` and/or `marker.color` to numerical arrays. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.Scatter cliponaxis Determines whether or not markers and text nodes are clipped about the subplot axes. To show markers and text nodes above axis lines and tick labels, make sure to set `xaxis.layer` and `yaxis.layer` to *below traces*. connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dx Sets the x coordinate step. See `x0` for more info. dy Sets the y coordinate step. See `y0` for more info. error_x plotly.graph_objects.scatter.ErrorX instance or dict with compatible properties error_y plotly.graph_objects.scatter.ErrorY instance or dict with compatible properties fill Sets the area to fill with a solid color. Defaults to "none" unless this trace is stacked, then it gets "tonexty" ("tonextx") if `orientation` is "v" ("h") Use with `fillcolor` if not "none". "tozerox" and "tozeroy" fill to x=0 and y=0 respectively. "tonextx" and "tonexty" fill between the endpoints of this trace and the endpoints of the trace before it, connecting those endpoints with straight lines (to make a stacked area graph); if there is no trace before it, they behave like "tozerox" and "tozeroy". "toself" connects the endpoints of the trace (or each segment of the trace if it has gaps) into a closed shape. "tonext" fills the space between two traces if one completely encloses the other (eg consecutive contour lines), and behaves like "toself" if there is no trace before it. "tonext" should not be used if one trace does not enclose the other. Traces in a `stackgroup` will only fill to (or be filled to) other traces in the same group. With multiple `stackgroup`s or some traces stacked and some not, if fill-linked traces are not already consecutive, the later ones will be pushed down in the drawing order. fillcolor Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. groupnorm Only relevant when `stackgroup` is used, and only the first `groupnorm` found in the `stackgroup` will be used - including if `visible` is "legendonly" but not if it is `false`. Sets the normalization for the sum of this `stackgroup`. With "fraction", the value of each trace at each location is divided by the sum of all trace values at that location. "percent" is the same but multiplied by 100 to show percentages. If there are multiple subplots, or multiple `stackgroup`s on one subplot, each will be normalized within its own set. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.scatter.Hoverlabel instance or dict with compatible properties hoveron Do the hover effects highlight individual points (markers or line points) or do they highlight filled regions? If the fill is "toself" or "tonext" and there are no markers or text, then the default is "fills", otherwise it is "points". hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.scatter.Line instance or dict with compatible properties marker plotly.graph_objects.scatter.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . mode Determines the drawing mode for this scatter trace. If the provided `mode` includes "text" then the `text` elements appear at the coordinates. Otherwise, the `text` elements appear on hover. If there are less than 20 points and the trace is not stacked then the default is "lines+markers". Otherwise, "lines". name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. orientation Only relevant when `stackgroup` is used, and only the first `orientation` found in the `stackgroup` will be used - including if `visible` is "legendonly" but not if it is `false`. Sets the stacking direction. With "v" ("h"), the y (x) values of subsequent traces are added. Also affects the default value of `fill`. r r coordinates in scatter traces are deprecated!Please switch to the "scatterpolar" trace type.Sets the radial coordinatesfor legacy polar chart only. rsrc Sets the source reference on plot.ly for r . selected plotly.graph_objects.scatter.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stackgaps Only relevant when `stackgroup` is used, and only the first `stackgaps` found in the `stackgroup` will be used - including if `visible` is "legendonly" but not if it is `false`. Determines how we handle locations at which other traces in this group have data but this one does not. With *infer zero* we insert a zero at these locations. With "interpolate" we linearly interpolate between existing values, and extrapolate a constant beyond the existing values. stackgroup Set several scatter traces (on the same subplot) to the same stackgroup in order to add their y values (or their x values if `orientation` is "h"). If blank or omitted this trace will not be stacked. Stacking also turns `fill` on by default, using "tonexty" ("tonextx") if `orientation` is "h" ("v") and sets the default `mode` to "lines" irrespective of point count. You can only stack on a numeric (linear or log) axis. Traces in a `stackgroup` will only fill to (or be filled to) other traces in the same group. With multiple `stackgroup`s or some traces stacked and some not, if fill-linked traces are not already consecutive, the later ones will be pushed down in the drawing order. stream plotly.graph_objects.scatter.Stream instance or dict with compatible properties t t coordinates in scatter traces are deprecated!Please switch to the "scatterpolar" trace type.Sets the angular coordinatesfor legacy polar chart only. text Sets text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the text font. textposition Sets the positions of the `text` elements with respects to the (x,y) coordinates. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. texttemplatesrc Sets the source reference on plot.ly for texttemplate . tsrc Sets the source reference on plot.ly for t . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.scatter.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the x coordinates. x0 Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . y Sets the y coordinates. y0 Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . Returns ------- Scatter """ super(Scatter, self).__init__("scatter") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.Scatter constructor must be a dict or an instance of plotly.graph_objs.Scatter""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators import scatter as v_scatter # Initialize validators # --------------------- self._validators["cliponaxis"] = v_scatter.CliponaxisValidator() self._validators["connectgaps"] = v_scatter.ConnectgapsValidator() self._validators["customdata"] = v_scatter.CustomdataValidator() self._validators["customdatasrc"] = v_scatter.CustomdatasrcValidator() self._validators["dx"] = v_scatter.DxValidator() self._validators["dy"] = v_scatter.DyValidator() self._validators["error_x"] = v_scatter.ErrorXValidator() self._validators["error_y"] = v_scatter.ErrorYValidator() self._validators["fill"] = v_scatter.FillValidator() self._validators["fillcolor"] = v_scatter.FillcolorValidator() self._validators["groupnorm"] = v_scatter.GroupnormValidator() self._validators["hoverinfo"] = v_scatter.HoverinfoValidator() self._validators["hoverinfosrc"] = v_scatter.HoverinfosrcValidator() self._validators["hoverlabel"] = v_scatter.HoverlabelValidator() self._validators["hoveron"] = v_scatter.HoveronValidator() self._validators["hovertemplate"] = v_scatter.HovertemplateValidator() self._validators["hovertemplatesrc"] = v_scatter.HovertemplatesrcValidator() self._validators["hovertext"] = v_scatter.HovertextValidator() self._validators["hovertextsrc"] = v_scatter.HovertextsrcValidator() self._validators["ids"] = v_scatter.IdsValidator() self._validators["idssrc"] = v_scatter.IdssrcValidator() self._validators["legendgroup"] = v_scatter.LegendgroupValidator() self._validators["line"] = v_scatter.LineValidator() self._validators["marker"] = v_scatter.MarkerValidator() self._validators["meta"] = v_scatter.MetaValidator() self._validators["metasrc"] = v_scatter.MetasrcValidator() self._validators["mode"] = v_scatter.ModeValidator() self._validators["name"] = v_scatter.NameValidator() self._validators["opacity"] = v_scatter.OpacityValidator() self._validators["orientation"] = v_scatter.OrientationValidator() self._validators["r"] = v_scatter.RValidator() self._validators["rsrc"] = v_scatter.RsrcValidator() self._validators["selected"] = v_scatter.SelectedValidator() self._validators["selectedpoints"] = v_scatter.SelectedpointsValidator() self._validators["showlegend"] = v_scatter.ShowlegendValidator() self._validators["stackgaps"] = v_scatter.StackgapsValidator() self._validators["stackgroup"] = v_scatter.StackgroupValidator() self._validators["stream"] = v_scatter.StreamValidator() self._validators["t"] = v_scatter.TValidator() self._validators["text"] = v_scatter.TextValidator() self._validators["textfont"] = v_scatter.TextfontValidator() self._validators["textposition"] = v_scatter.TextpositionValidator() self._validators["textpositionsrc"] = v_scatter.TextpositionsrcValidator() self._validators["textsrc"] = v_scatter.TextsrcValidator() self._validators["texttemplate"] = v_scatter.TexttemplateValidator() self._validators["texttemplatesrc"] = v_scatter.TexttemplatesrcValidator() self._validators["tsrc"] = v_scatter.TsrcValidator() self._validators["uid"] = v_scatter.UidValidator() self._validators["uirevision"] = v_scatter.UirevisionValidator() self._validators["unselected"] = v_scatter.UnselectedValidator() self._validators["visible"] = v_scatter.VisibleValidator() self._validators["x"] = v_scatter.XValidator() self._validators["x0"] = v_scatter.X0Validator() self._validators["xaxis"] = v_scatter.XAxisValidator() self._validators["xcalendar"] = v_scatter.XcalendarValidator() self._validators["xsrc"] = v_scatter.XsrcValidator() self._validators["y"] = v_scatter.YValidator() self._validators["y0"] = v_scatter.Y0Validator() self._validators["yaxis"] = v_scatter.YAxisValidator() self._validators["ycalendar"] = v_scatter.YcalendarValidator() self._validators["ysrc"] = v_scatter.YsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("cliponaxis", None) self["cliponaxis"] = cliponaxis if cliponaxis is not None else _v _v = arg.pop("connectgaps", None) self["connectgaps"] = connectgaps if connectgaps is not None else _v _v = arg.pop("customdata", None) self["customdata"] = customdata if customdata is not None else _v _v = arg.pop("customdatasrc", None) self["customdatasrc"] = customdatasrc if customdatasrc is not None else _v _v = arg.pop("dx", None) self["dx"] = dx if dx is not None else _v _v = arg.pop("dy", None) self["dy"] = dy if dy is not None else _v _v = arg.pop("error_x", None) self["error_x"] = error_x if error_x is not None else _v _v = arg.pop("error_y", None) self["error_y"] = error_y if error_y is not None else _v _v = arg.pop("fill", None) self["fill"] = fill if fill is not None else _v _v = arg.pop("fillcolor", None) self["fillcolor"] = fillcolor if fillcolor is not None else _v _v = arg.pop("groupnorm", None) self["groupnorm"] = groupnorm if groupnorm is not None else _v _v = arg.pop("hoverinfo", None) self["hoverinfo"] = hoverinfo if hoverinfo is not None else _v _v = arg.pop("hoverinfosrc", None) self["hoverinfosrc"] = hoverinfosrc if hoverinfosrc is not None else _v _v = arg.pop("hoverlabel", None) self["hoverlabel"] = hoverlabel if hoverlabel is not None else _v _v = arg.pop("hoveron", None) self["hoveron"] = hoveron if hoveron is not None else _v _v = arg.pop("hovertemplate", None) self["hovertemplate"] = hovertemplate if hovertemplate is not None else _v _v = arg.pop("hovertemplatesrc", None) self["hovertemplatesrc"] = ( hovertemplatesrc if hovertemplatesrc is not None else _v ) _v = arg.pop("hovertext", None) self["hovertext"] = hovertext if hovertext is not None else _v _v = arg.pop("hovertextsrc", None) self["hovertextsrc"] = hovertextsrc if hovertextsrc is not None else _v _v = arg.pop("ids", None) self["ids"] = ids if ids is not None else _v _v = arg.pop("idssrc", None) self["idssrc"] = idssrc if idssrc is not None else _v _v = arg.pop("legendgroup", None) self["legendgroup"] = legendgroup if legendgroup is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v _v = arg.pop("meta", None) self["meta"] = meta if meta is not None else _v _v = arg.pop("metasrc", None) self["metasrc"] = metasrc if metasrc is not None else _v _v = arg.pop("mode", None) self["mode"] = mode if mode is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("orientation", None) self["orientation"] = orientation if orientation is not None else _v _v = arg.pop("r", None) self["r"] = r if r is not None else _v _v = arg.pop("rsrc", None) self["rsrc"] = rsrc if rsrc is not None else _v _v = arg.pop("selected", None) self["selected"] = selected if selected is not None else _v _v = arg.pop("selectedpoints", None) self["selectedpoints"] = selectedpoints if selectedpoints is not None else _v _v = arg.pop("showlegend", None) self["showlegend"] = showlegend if showlegend is not None else _v _v = arg.pop("stackgaps", None) self["stackgaps"] = stackgaps if stackgaps is not None else _v _v = arg.pop("stackgroup", None) self["stackgroup"] = stackgroup if stackgroup is not None else _v _v = arg.pop("stream", None) self["stream"] = stream if stream is not None else _v _v = arg.pop("t", None) self["t"] = t if t is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v _v = arg.pop("textfont", None) self["textfont"] = textfont if textfont is not None else _v _v = arg.pop("textposition", None) self["textposition"] = textposition if textposition is not None else _v _v = arg.pop("textpositionsrc", None) self["textpositionsrc"] = textpositionsrc if textpositionsrc is not None else _v _v = arg.pop("textsrc", None) self["textsrc"] = textsrc if textsrc is not None else _v _v = arg.pop("texttemplate", None) self["texttemplate"] = texttemplate if texttemplate is not None else _v _v = arg.pop("texttemplatesrc", None) self["texttemplatesrc"] = texttemplatesrc if texttemplatesrc is not None else _v _v = arg.pop("tsrc", None) self["tsrc"] = tsrc if tsrc is not None else _v _v = arg.pop("uid", None) self["uid"] = uid if uid is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("unselected", None) self["unselected"] = unselected if unselected is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("x0", None) self["x0"] = x0 if x0 is not None else _v _v = arg.pop("xaxis", None) self["xaxis"] = xaxis if xaxis is not None else _v _v = arg.pop("xcalendar", None) self["xcalendar"] = xcalendar if xcalendar is not None else _v _v = arg.pop("xsrc", None) self["xsrc"] = xsrc if xsrc is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("y0", None) self["y0"] = y0 if y0 is not None else _v _v = arg.pop("yaxis", None) self["yaxis"] = yaxis if yaxis is not None else _v _v = arg.pop("ycalendar", None) self["ycalendar"] = ycalendar if ycalendar is not None else _v _v = arg.pop("ysrc", None) self["ysrc"] = ysrc if ysrc is not None else _v # Read-only literals # ------------------ from _plotly_utils.basevalidators import LiteralValidator self._props["type"] = "scatter" self._validators["type"] = LiteralValidator( plotly_name="type", parent_name="scatter", val="scatter" ) arg.pop("type", None) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceType as _BaseTraceType import copy as _copy class Sankey(_BaseTraceType): # arrangement # ----------- @property def arrangement(self): """ If value is `snap` (the default), the node arrangement is assisted by automatic snapping of elements to preserve space between nodes specified via `nodepad`. If value is `perpendicular`, the nodes can only move along a line perpendicular to the flow. If value is `freeform`, the nodes can freely move on the plane. If value is `fixed`, the nodes are stationary. The 'arrangement' property is an enumeration that may be specified as: - One of the following enumeration values: ['snap', 'perpendicular', 'freeform', 'fixed'] Returns ------- Any """ return self["arrangement"] @arrangement.setter def arrangement(self, val): self["arrangement"] = val # customdata # ---------- @property def customdata(self): """ Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements The 'customdata' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["customdata"] @customdata.setter def customdata(self, val): self["customdata"] = val # customdatasrc # ------------- @property def customdatasrc(self): """ Sets the source reference on plot.ly for customdata . The 'customdatasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["customdatasrc"] @customdatasrc.setter def customdatasrc(self, val): self["customdatasrc"] = val # domain # ------ @property def domain(self): """ The 'domain' property is an instance of Domain that may be specified as: - An instance of plotly.graph_objs.sankey.Domain - A dict of string/value properties that will be passed to the Domain constructor Supported dict properties: column If there is a layout grid, use the domain for this column in the grid for this sankey trace . row If there is a layout grid, use the domain for this row in the grid for this sankey trace . x Sets the horizontal domain of this sankey trace (in plot fraction). y Sets the vertical domain of this sankey trace (in plot fraction). Returns ------- plotly.graph_objs.sankey.Domain """ return self["domain"] @domain.setter def domain(self, val): self["domain"] = val # hoverinfo # --------- @property def hoverinfo(self): """ Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. Note that this attribute is superseded by `node.hoverinfo` and `node.hoverinfo` for nodes and links respectively. The 'hoverinfo' property is a flaglist and may be specified as a string containing: - Any combination of [] joined with '+' characters (e.g. '') OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') Returns ------- Any """ return self["hoverinfo"] @hoverinfo.setter def hoverinfo(self, val): self["hoverinfo"] = val # hoverlabel # ---------- @property def hoverlabel(self): """ The 'hoverlabel' property is an instance of Hoverlabel that may be specified as: - An instance of plotly.graph_objs.sankey.Hoverlabel - A dict of string/value properties that will be passed to the Hoverlabel constructor Supported dict properties: align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- plotly.graph_objs.sankey.Hoverlabel """ return self["hoverlabel"] @hoverlabel.setter def hoverlabel(self, val): self["hoverlabel"] = val # ids # --- @property def ids(self): """ Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. The 'ids' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ids"] @ids.setter def ids(self, val): self["ids"] = val # idssrc # ------ @property def idssrc(self): """ Sets the source reference on plot.ly for ids . The 'idssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["idssrc"] @idssrc.setter def idssrc(self, val): self["idssrc"] = val # link # ---- @property def link(self): """ The links of the Sankey plot. The 'link' property is an instance of Link that may be specified as: - An instance of plotly.graph_objs.sankey.Link - A dict of string/value properties that will be passed to the Link constructor Supported dict properties: color Sets the `link` color. It can be a single value, or an array for specifying color for each `link`. If `link.color` is omitted, then by default, a translucent grey link will be used. colorscales A tuple of plotly.graph_objects.sankey.link.Colorscale instances or dicts with compatible properties colorscaledefaults When used in a template (as layout.template.dat a.sankey.link.colorscaledefaults), sets the default property values to use for elements of sankey.link.colorscales colorsrc Sets the source reference on plot.ly for color . hoverinfo Determines which trace information appear when hovering links. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverlabel plotly.graph_objects.sankey.link.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs- events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `value` and `label`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . label The shown name of the link. labelsrc Sets the source reference on plot.ly for label . line plotly.graph_objects.sankey.link.Line instance or dict with compatible properties source An integer number `[0..nodes.length - 1]` that represents the source node. sourcesrc Sets the source reference on plot.ly for source . target An integer number `[0..nodes.length - 1]` that represents the target node. targetsrc Sets the source reference on plot.ly for target . value A numeric value representing the flow volume value. valuesrc Sets the source reference on plot.ly for value . Returns ------- plotly.graph_objs.sankey.Link """ return self["link"] @link.setter def link(self, val): self["link"] = val # meta # ---- @property def meta(self): """ Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. The 'meta' property accepts values of any type Returns ------- Any|numpy.ndarray """ return self["meta"] @meta.setter def meta(self, val): self["meta"] = val # metasrc # ------- @property def metasrc(self): """ Sets the source reference on plot.ly for meta . The 'metasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["metasrc"] @metasrc.setter def metasrc(self, val): self["metasrc"] = val # name # ---- @property def name(self): """ Sets the trace name. The trace name appear as the legend item and on hover. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # node # ---- @property def node(self): """ The nodes of the Sankey plot. The 'node' property is an instance of Node that may be specified as: - An instance of plotly.graph_objs.sankey.Node - A dict of string/value properties that will be passed to the Node constructor Supported dict properties: color Sets the `node` color. It can be a single value, or an array for specifying color for each `node`. If `node.color` is omitted, then the default `Plotly` color palette will be cycled through to have a variety of colors. These defaults are not fully opaque, to allow some visibility of what is beneath the node. colorsrc Sets the source reference on plot.ly for color . groups Groups of nodes. Each group is defined by an array with the indices of the nodes it contains. Multiple groups can be specified. hoverinfo Determines which trace information appear when hovering nodes. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverlabel plotly.graph_objects.sankey.node.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs- events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `value` and `label`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . label The shown name of the node. labelsrc Sets the source reference on plot.ly for label . line plotly.graph_objects.sankey.node.Line instance or dict with compatible properties pad Sets the padding (in px) between the `nodes`. thickness Sets the thickness (in px) of the `nodes`. x The normalized horizontal position of the node. xsrc Sets the source reference on plot.ly for x . y The normalized vertical position of the node. ysrc Sets the source reference on plot.ly for y . Returns ------- plotly.graph_objs.sankey.Node """ return self["node"] @node.setter def node(self, val): self["node"] = val # orientation # ----------- @property def orientation(self): """ Sets the orientation of the Sankey diagram. The 'orientation' property is an enumeration that may be specified as: - One of the following enumeration values: ['v', 'h'] Returns ------- Any """ return self["orientation"] @orientation.setter def orientation(self, val): self["orientation"] = val # selectedpoints # -------------- @property def selectedpoints(self): """ Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. The 'selectedpoints' property accepts values of any type Returns ------- Any """ return self["selectedpoints"] @selectedpoints.setter def selectedpoints(self, val): self["selectedpoints"] = val # stream # ------ @property def stream(self): """ The 'stream' property is an instance of Stream that may be specified as: - An instance of plotly.graph_objs.sankey.Stream - A dict of string/value properties that will be passed to the Stream constructor Supported dict properties: maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- plotly.graph_objs.sankey.Stream """ return self["stream"] @stream.setter def stream(self, val): self["stream"] = val # textfont # -------- @property def textfont(self): """ Sets the font for node labels The 'textfont' property is an instance of Textfont that may be specified as: - An instance of plotly.graph_objs.sankey.Textfont - A dict of string/value properties that will be passed to the Textfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.sankey.Textfont """ return self["textfont"] @textfont.setter def textfont(self, val): self["textfont"] = val # uid # --- @property def uid(self): """ Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. The 'uid' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["uid"] @uid.setter def uid(self, val): self["uid"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # valueformat # ----------- @property def valueformat(self): """ Sets the value formatting rule using d3 formatting mini- language which is similar to those of Python. See https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format The 'valueformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["valueformat"] @valueformat.setter def valueformat(self, val): self["valueformat"] = val # valuesuffix # ----------- @property def valuesuffix(self): """ Adds a unit to follow the value in the hover tooltip. Add a space if a separation is necessary from the value. The 'valuesuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["valuesuffix"] @valuesuffix.setter def valuesuffix(self, val): self["valuesuffix"] = val # visible # ------- @property def visible(self): """ Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). The 'visible' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'legendonly'] Returns ------- Any """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # type # ---- @property def type(self): return self._props["type"] # property parent name # -------------------- @property def _parent_path_str(self): return "" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ arrangement If value is `snap` (the default), the node arrangement is assisted by automatic snapping of elements to preserve space between nodes specified via `nodepad`. If value is `perpendicular`, the nodes can only move along a line perpendicular to the flow. If value is `freeform`, the nodes can freely move on the plane. If value is `fixed`, the nodes are stationary. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . domain plotly.graph_objects.sankey.Domain instance or dict with compatible properties hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. Note that this attribute is superseded by `node.hoverinfo` and `node.hoverinfo` for nodes and links respectively. hoverlabel plotly.graph_objects.sankey.Hoverlabel instance or dict with compatible properties ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . link The links of the Sankey plot. meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. node The nodes of the Sankey plot. orientation Sets the orientation of the Sankey diagram. selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. stream plotly.graph_objects.sankey.Stream instance or dict with compatible properties textfont Sets the font for node labels uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. valueformat Sets the value formatting rule using d3 formatting mini-language which is similar to those of Python. See https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format valuesuffix Adds a unit to follow the value in the hover tooltip. Add a space if a separation is necessary from the value. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). """ def __init__( self, arg=None, arrangement=None, customdata=None, customdatasrc=None, domain=None, hoverinfo=None, hoverlabel=None, ids=None, idssrc=None, link=None, meta=None, metasrc=None, name=None, node=None, orientation=None, selectedpoints=None, stream=None, textfont=None, uid=None, uirevision=None, valueformat=None, valuesuffix=None, visible=None, **kwargs ): """ Construct a new Sankey object Sankey plots for network flow data analysis. The nodes are specified in `nodes` and the links between sources and targets in `links`. The colors are set in `nodes[i].color` and `links[i].color`, otherwise defaults are used. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.Sankey arrangement If value is `snap` (the default), the node arrangement is assisted by automatic snapping of elements to preserve space between nodes specified via `nodepad`. If value is `perpendicular`, the nodes can only move along a line perpendicular to the flow. If value is `freeform`, the nodes can freely move on the plane. If value is `fixed`, the nodes are stationary. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . domain plotly.graph_objects.sankey.Domain instance or dict with compatible properties hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. Note that this attribute is superseded by `node.hoverinfo` and `node.hoverinfo` for nodes and links respectively. hoverlabel plotly.graph_objects.sankey.Hoverlabel instance or dict with compatible properties ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . link The links of the Sankey plot. meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. node The nodes of the Sankey plot. orientation Sets the orientation of the Sankey diagram. selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. stream plotly.graph_objects.sankey.Stream instance or dict with compatible properties textfont Sets the font for node labels uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. valueformat Sets the value formatting rule using d3 formatting mini-language which is similar to those of Python. See https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format valuesuffix Adds a unit to follow the value in the hover tooltip. Add a space if a separation is necessary from the value. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). Returns ------- Sankey """ super(Sankey, self).__init__("sankey") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.Sankey constructor must be a dict or an instance of plotly.graph_objs.Sankey""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators import sankey as v_sankey # Initialize validators # --------------------- self._validators["arrangement"] = v_sankey.ArrangementValidator() self._validators["customdata"] = v_sankey.CustomdataValidator() self._validators["customdatasrc"] = v_sankey.CustomdatasrcValidator() self._validators["domain"] = v_sankey.DomainValidator() self._validators["hoverinfo"] = v_sankey.HoverinfoValidator() self._validators["hoverlabel"] = v_sankey.HoverlabelValidator() self._validators["ids"] = v_sankey.IdsValidator() self._validators["idssrc"] = v_sankey.IdssrcValidator() self._validators["link"] = v_sankey.LinkValidator() self._validators["meta"] = v_sankey.MetaValidator() self._validators["metasrc"] = v_sankey.MetasrcValidator() self._validators["name"] = v_sankey.NameValidator() self._validators["node"] = v_sankey.NodeValidator() self._validators["orientation"] = v_sankey.OrientationValidator() self._validators["selectedpoints"] = v_sankey.SelectedpointsValidator() self._validators["stream"] = v_sankey.StreamValidator() self._validators["textfont"] = v_sankey.TextfontValidator() self._validators["uid"] = v_sankey.UidValidator() self._validators["uirevision"] = v_sankey.UirevisionValidator() self._validators["valueformat"] = v_sankey.ValueformatValidator() self._validators["valuesuffix"] = v_sankey.ValuesuffixValidator() self._validators["visible"] = v_sankey.VisibleValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("arrangement", None) self["arrangement"] = arrangement if arrangement is not None else _v _v = arg.pop("customdata", None) self["customdata"] = customdata if customdata is not None else _v _v = arg.pop("customdatasrc", None) self["customdatasrc"] = customdatasrc if customdatasrc is not None else _v _v = arg.pop("domain", None) self["domain"] = domain if domain is not None else _v _v = arg.pop("hoverinfo", None) self["hoverinfo"] = hoverinfo if hoverinfo is not None else _v _v = arg.pop("hoverlabel", None) self["hoverlabel"] = hoverlabel if hoverlabel is not None else _v _v = arg.pop("ids", None) self["ids"] = ids if ids is not None else _v _v = arg.pop("idssrc", None) self["idssrc"] = idssrc if idssrc is not None else _v _v = arg.pop("link", None) self["link"] = link if link is not None else _v _v = arg.pop("meta", None) self["meta"] = meta if meta is not None else _v _v = arg.pop("metasrc", None) self["metasrc"] = metasrc if metasrc is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("node", None) self["node"] = node if node is not None else _v _v = arg.pop("orientation", None) self["orientation"] = orientation if orientation is not None else _v _v = arg.pop("selectedpoints", None) self["selectedpoints"] = selectedpoints if selectedpoints is not None else _v _v = arg.pop("stream", None) self["stream"] = stream if stream is not None else _v _v = arg.pop("textfont", None) self["textfont"] = textfont if textfont is not None else _v _v = arg.pop("uid", None) self["uid"] = uid if uid is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("valueformat", None) self["valueformat"] = valueformat if valueformat is not None else _v _v = arg.pop("valuesuffix", None) self["valuesuffix"] = valuesuffix if valuesuffix is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v # Read-only literals # ------------------ from _plotly_utils.basevalidators import LiteralValidator self._props["type"] = "sankey" self._validators["type"] = LiteralValidator( plotly_name="type", parent_name="sankey", val="sankey" ) arg.pop("type", None) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceType as _BaseTraceType import copy as _copy class Pointcloud(_BaseTraceType): # customdata # ---------- @property def customdata(self): """ Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements The 'customdata' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["customdata"] @customdata.setter def customdata(self, val): self["customdata"] = val # customdatasrc # ------------- @property def customdatasrc(self): """ Sets the source reference on plot.ly for customdata . The 'customdatasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["customdatasrc"] @customdatasrc.setter def customdatasrc(self, val): self["customdatasrc"] = val # hoverinfo # --------- @property def hoverinfo(self): """ Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. The 'hoverinfo' property is a flaglist and may be specified as a string containing: - Any combination of ['x', 'y', 'z', 'text', 'name'] joined with '+' characters (e.g. 'x+y') OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') - A list or array of the above Returns ------- Any|numpy.ndarray """ return self["hoverinfo"] @hoverinfo.setter def hoverinfo(self, val): self["hoverinfo"] = val # hoverinfosrc # ------------ @property def hoverinfosrc(self): """ Sets the source reference on plot.ly for hoverinfo . The 'hoverinfosrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hoverinfosrc"] @hoverinfosrc.setter def hoverinfosrc(self, val): self["hoverinfosrc"] = val # hoverlabel # ---------- @property def hoverlabel(self): """ The 'hoverlabel' property is an instance of Hoverlabel that may be specified as: - An instance of plotly.graph_objs.pointcloud.Hoverlabel - A dict of string/value properties that will be passed to the Hoverlabel constructor Supported dict properties: align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- plotly.graph_objs.pointcloud.Hoverlabel """ return self["hoverlabel"] @hoverlabel.setter def hoverlabel(self, val): self["hoverlabel"] = val # ids # --- @property def ids(self): """ Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. The 'ids' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ids"] @ids.setter def ids(self, val): self["ids"] = val # idssrc # ------ @property def idssrc(self): """ Sets the source reference on plot.ly for ids . The 'idssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["idssrc"] @idssrc.setter def idssrc(self, val): self["idssrc"] = val # indices # ------- @property def indices(self): """ A sequential value, 0..n, supply it to avoid creating this array inside plotting. If specified, it must be a typed `Int32Array` array. Its length must be equal to or greater than the number of points. For the best performance and memory use, create one large `indices` typed array that is guaranteed to be at least as long as the largest number of points during use, and reuse it on each `Plotly.restyle()` call. The 'indices' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["indices"] @indices.setter def indices(self, val): self["indices"] = val # indicessrc # ---------- @property def indicessrc(self): """ Sets the source reference on plot.ly for indices . The 'indicessrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["indicessrc"] @indicessrc.setter def indicessrc(self, val): self["indicessrc"] = val # legendgroup # ----------- @property def legendgroup(self): """ Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. The 'legendgroup' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["legendgroup"] @legendgroup.setter def legendgroup(self, val): self["legendgroup"] = val # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.pointcloud.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: blend Determines if colors are blended together for a translucency effect in case `opacity` is specified as a value less then `1`. Setting `blend` to `true` reduces zoom/pan speed if used with large numbers of points. border plotly.graph_objects.pointcloud.marker.Border instance or dict with compatible properties color Sets the marker fill color. It accepts a specific color.If the color is not fully opaque and there are hundreds of thousandsof points, it may cause slower zooming and panning. opacity Sets the marker opacity. The default value is `1` (fully opaque). If the markers are not fully opaque and there are hundreds of thousands of points, it may cause slower zooming and panning. Opacity fades the color even if `blend` is left on `false` even if there is no translucency effect in that case. sizemax Sets the maximum size (in px) of the rendered marker points. Effective when the `pointcloud` shows only few points. sizemin Sets the minimum size (in px) of the rendered marker points, effective when the `pointcloud` shows a million or more points. Returns ------- plotly.graph_objs.pointcloud.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # meta # ---- @property def meta(self): """ Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. The 'meta' property accepts values of any type Returns ------- Any|numpy.ndarray """ return self["meta"] @meta.setter def meta(self, val): self["meta"] = val # metasrc # ------- @property def metasrc(self): """ Sets the source reference on plot.ly for meta . The 'metasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["metasrc"] @metasrc.setter def metasrc(self, val): self["metasrc"] = val # name # ---- @property def name(self): """ Sets the trace name. The trace name appear as the legend item and on hover. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the trace. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # showlegend # ---------- @property def showlegend(self): """ Determines whether or not an item corresponding to this trace is shown in the legend. The 'showlegend' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showlegend"] @showlegend.setter def showlegend(self, val): self["showlegend"] = val # stream # ------ @property def stream(self): """ The 'stream' property is an instance of Stream that may be specified as: - An instance of plotly.graph_objs.pointcloud.Stream - A dict of string/value properties that will be passed to the Stream constructor Supported dict properties: maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- plotly.graph_objs.pointcloud.Stream """ return self["stream"] @stream.setter def stream(self, val): self["stream"] = val # text # ---- @property def text(self): """ Sets text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["text"] @text.setter def text(self, val): self["text"] = val # textsrc # ------- @property def textsrc(self): """ Sets the source reference on plot.ly for text . The 'textsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["textsrc"] @textsrc.setter def textsrc(self, val): self["textsrc"] = val # uid # --- @property def uid(self): """ Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. The 'uid' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["uid"] @uid.setter def uid(self, val): self["uid"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # visible # ------- @property def visible(self): """ Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). The 'visible' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'legendonly'] Returns ------- Any """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # x # - @property def x(self): """ Sets the x coordinates. The 'x' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["x"] @x.setter def x(self, val): self["x"] = val # xaxis # ----- @property def xaxis(self): """ Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. The 'xaxis' property is an identifier of a particular subplot, of type 'x', that may be specified as the string 'x' optionally followed by an integer >= 1 (e.g. 'x', 'x1', 'x2', 'x3', etc.) Returns ------- str """ return self["xaxis"] @xaxis.setter def xaxis(self, val): self["xaxis"] = val # xbounds # ------- @property def xbounds(self): """ Specify `xbounds` in the shape of `[xMin, xMax] to avoid looping through the `xy` typed array. Use it in conjunction with `xy` and `ybounds` for the performance benefits. The 'xbounds' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["xbounds"] @xbounds.setter def xbounds(self, val): self["xbounds"] = val # xboundssrc # ---------- @property def xboundssrc(self): """ Sets the source reference on plot.ly for xbounds . The 'xboundssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["xboundssrc"] @xboundssrc.setter def xboundssrc(self, val): self["xboundssrc"] = val # xsrc # ---- @property def xsrc(self): """ Sets the source reference on plot.ly for x . The 'xsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["xsrc"] @xsrc.setter def xsrc(self, val): self["xsrc"] = val # xy # -- @property def xy(self): """ Faster alternative to specifying `x` and `y` separately. If supplied, it must be a typed `Float32Array` array that represents points such that `xy[i * 2] = x[i]` and `xy[i * 2 + 1] = y[i]` The 'xy' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["xy"] @xy.setter def xy(self, val): self["xy"] = val # xysrc # ----- @property def xysrc(self): """ Sets the source reference on plot.ly for xy . The 'xysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["xysrc"] @xysrc.setter def xysrc(self, val): self["xysrc"] = val # y # - @property def y(self): """ Sets the y coordinates. The 'y' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["y"] @y.setter def y(self, val): self["y"] = val # yaxis # ----- @property def yaxis(self): """ Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. The 'yaxis' property is an identifier of a particular subplot, of type 'y', that may be specified as the string 'y' optionally followed by an integer >= 1 (e.g. 'y', 'y1', 'y2', 'y3', etc.) Returns ------- str """ return self["yaxis"] @yaxis.setter def yaxis(self, val): self["yaxis"] = val # ybounds # ------- @property def ybounds(self): """ Specify `ybounds` in the shape of `[yMin, yMax] to avoid looping through the `xy` typed array. Use it in conjunction with `xy` and `xbounds` for the performance benefits. The 'ybounds' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ybounds"] @ybounds.setter def ybounds(self, val): self["ybounds"] = val # yboundssrc # ---------- @property def yboundssrc(self): """ Sets the source reference on plot.ly for ybounds . The 'yboundssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["yboundssrc"] @yboundssrc.setter def yboundssrc(self, val): self["yboundssrc"] = val # ysrc # ---- @property def ysrc(self): """ Sets the source reference on plot.ly for y . The 'ysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ysrc"] @ysrc.setter def ysrc(self, val): self["ysrc"] = val # type # ---- @property def type(self): return self._props["type"] # property parent name # -------------------- @property def _parent_path_str(self): return "" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.pointcloud.Hoverlabel instance or dict with compatible properties ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . indices A sequential value, 0..n, supply it to avoid creating this array inside plotting. If specified, it must be a typed `Int32Array` array. Its length must be equal to or greater than the number of points. For the best performance and memory use, create one large `indices` typed array that is guaranteed to be at least as long as the largest number of points during use, and reuse it on each `Plotly.restyle()` call. indicessrc Sets the source reference on plot.ly for indices . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. marker plotly.graph_objects.pointcloud.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.pointcloud.Stream instance or dict with compatible properties text Sets text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the x coordinates. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xbounds Specify `xbounds` in the shape of `[xMin, xMax] to avoid looping through the `xy` typed array. Use it in conjunction with `xy` and `ybounds` for the performance benefits. xboundssrc Sets the source reference on plot.ly for xbounds . xsrc Sets the source reference on plot.ly for x . xy Faster alternative to specifying `x` and `y` separately. If supplied, it must be a typed `Float32Array` array that represents points such that `xy[i * 2] = x[i]` and `xy[i * 2 + 1] = y[i]` xysrc Sets the source reference on plot.ly for xy . y Sets the y coordinates. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ybounds Specify `ybounds` in the shape of `[yMin, yMax] to avoid looping through the `xy` typed array. Use it in conjunction with `xy` and `xbounds` for the performance benefits. yboundssrc Sets the source reference on plot.ly for ybounds . ysrc Sets the source reference on plot.ly for y . """ def __init__( self, arg=None, customdata=None, customdatasrc=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, ids=None, idssrc=None, indices=None, indicessrc=None, legendgroup=None, marker=None, meta=None, metasrc=None, name=None, opacity=None, showlegend=None, stream=None, text=None, textsrc=None, uid=None, uirevision=None, visible=None, x=None, xaxis=None, xbounds=None, xboundssrc=None, xsrc=None, xy=None, xysrc=None, y=None, yaxis=None, ybounds=None, yboundssrc=None, ysrc=None, **kwargs ): """ Construct a new Pointcloud object The data visualized as a point cloud set in `x` and `y` using the WebGl plotting engine. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.Pointcloud customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.pointcloud.Hoverlabel instance or dict with compatible properties ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . indices A sequential value, 0..n, supply it to avoid creating this array inside plotting. If specified, it must be a typed `Int32Array` array. Its length must be equal to or greater than the number of points. For the best performance and memory use, create one large `indices` typed array that is guaranteed to be at least as long as the largest number of points during use, and reuse it on each `Plotly.restyle()` call. indicessrc Sets the source reference on plot.ly for indices . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. marker plotly.graph_objects.pointcloud.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.pointcloud.Stream instance or dict with compatible properties text Sets text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the x coordinates. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xbounds Specify `xbounds` in the shape of `[xMin, xMax] to avoid looping through the `xy` typed array. Use it in conjunction with `xy` and `ybounds` for the performance benefits. xboundssrc Sets the source reference on plot.ly for xbounds . xsrc Sets the source reference on plot.ly for x . xy Faster alternative to specifying `x` and `y` separately. If supplied, it must be a typed `Float32Array` array that represents points such that `xy[i * 2] = x[i]` and `xy[i * 2 + 1] = y[i]` xysrc Sets the source reference on plot.ly for xy . y Sets the y coordinates. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ybounds Specify `ybounds` in the shape of `[yMin, yMax] to avoid looping through the `xy` typed array. Use it in conjunction with `xy` and `xbounds` for the performance benefits. yboundssrc Sets the source reference on plot.ly for ybounds . ysrc Sets the source reference on plot.ly for y . Returns ------- Pointcloud """ super(Pointcloud, self).__init__("pointcloud") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.Pointcloud constructor must be a dict or an instance of plotly.graph_objs.Pointcloud""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators import pointcloud as v_pointcloud # Initialize validators # --------------------- self._validators["customdata"] = v_pointcloud.CustomdataValidator() self._validators["customdatasrc"] = v_pointcloud.CustomdatasrcValidator() self._validators["hoverinfo"] = v_pointcloud.HoverinfoValidator() self._validators["hoverinfosrc"] = v_pointcloud.HoverinfosrcValidator() self._validators["hoverlabel"] = v_pointcloud.HoverlabelValidator() self._validators["ids"] = v_pointcloud.IdsValidator() self._validators["idssrc"] = v_pointcloud.IdssrcValidator() self._validators["indices"] = v_pointcloud.IndicesValidator() self._validators["indicessrc"] = v_pointcloud.IndicessrcValidator() self._validators["legendgroup"] = v_pointcloud.LegendgroupValidator() self._validators["marker"] = v_pointcloud.MarkerValidator() self._validators["meta"] = v_pointcloud.MetaValidator() self._validators["metasrc"] = v_pointcloud.MetasrcValidator() self._validators["name"] = v_pointcloud.NameValidator() self._validators["opacity"] = v_pointcloud.OpacityValidator() self._validators["showlegend"] = v_pointcloud.ShowlegendValidator() self._validators["stream"] = v_pointcloud.StreamValidator() self._validators["text"] = v_pointcloud.TextValidator() self._validators["textsrc"] = v_pointcloud.TextsrcValidator() self._validators["uid"] = v_pointcloud.UidValidator() self._validators["uirevision"] = v_pointcloud.UirevisionValidator() self._validators["visible"] = v_pointcloud.VisibleValidator() self._validators["x"] = v_pointcloud.XValidator() self._validators["xaxis"] = v_pointcloud.XAxisValidator() self._validators["xbounds"] = v_pointcloud.XboundsValidator() self._validators["xboundssrc"] = v_pointcloud.XboundssrcValidator() self._validators["xsrc"] = v_pointcloud.XsrcValidator() self._validators["xy"] = v_pointcloud.XyValidator() self._validators["xysrc"] = v_pointcloud.XysrcValidator() self._validators["y"] = v_pointcloud.YValidator() self._validators["yaxis"] = v_pointcloud.YAxisValidator() self._validators["ybounds"] = v_pointcloud.YboundsValidator() self._validators["yboundssrc"] = v_pointcloud.YboundssrcValidator() self._validators["ysrc"] = v_pointcloud.YsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("customdata", None) self["customdata"] = customdata if customdata is not None else _v _v = arg.pop("customdatasrc", None) self["customdatasrc"] = customdatasrc if customdatasrc is not None else _v _v = arg.pop("hoverinfo", None) self["hoverinfo"] = hoverinfo if hoverinfo is not None else _v _v = arg.pop("hoverinfosrc", None) self["hoverinfosrc"] = hoverinfosrc if hoverinfosrc is not None else _v _v = arg.pop("hoverlabel", None) self["hoverlabel"] = hoverlabel if hoverlabel is not None else _v _v = arg.pop("ids", None) self["ids"] = ids if ids is not None else _v _v = arg.pop("idssrc", None) self["idssrc"] = idssrc if idssrc is not None else _v _v = arg.pop("indices", None) self["indices"] = indices if indices is not None else _v _v = arg.pop("indicessrc", None) self["indicessrc"] = indicessrc if indicessrc is not None else _v _v = arg.pop("legendgroup", None) self["legendgroup"] = legendgroup if legendgroup is not None else _v _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v _v = arg.pop("meta", None) self["meta"] = meta if meta is not None else _v _v = arg.pop("metasrc", None) self["metasrc"] = metasrc if metasrc is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("showlegend", None) self["showlegend"] = showlegend if showlegend is not None else _v _v = arg.pop("stream", None) self["stream"] = stream if stream is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v _v = arg.pop("textsrc", None) self["textsrc"] = textsrc if textsrc is not None else _v _v = arg.pop("uid", None) self["uid"] = uid if uid is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xaxis", None) self["xaxis"] = xaxis if xaxis is not None else _v _v = arg.pop("xbounds", None) self["xbounds"] = xbounds if xbounds is not None else _v _v = arg.pop("xboundssrc", None) self["xboundssrc"] = xboundssrc if xboundssrc is not None else _v _v = arg.pop("xsrc", None) self["xsrc"] = xsrc if xsrc is not None else _v _v = arg.pop("xy", None) self["xy"] = xy if xy is not None else _v _v = arg.pop("xysrc", None) self["xysrc"] = xysrc if xysrc is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("yaxis", None) self["yaxis"] = yaxis if yaxis is not None else _v _v = arg.pop("ybounds", None) self["ybounds"] = ybounds if ybounds is not None else _v _v = arg.pop("yboundssrc", None) self["yboundssrc"] = yboundssrc if yboundssrc is not None else _v _v = arg.pop("ysrc", None) self["ysrc"] = ysrc if ysrc is not None else _v # Read-only literals # ------------------ from _plotly_utils.basevalidators import LiteralValidator self._props["type"] = "pointcloud" self._validators["type"] = LiteralValidator( plotly_name="type", parent_name="pointcloud", val="pointcloud" ) arg.pop("type", None) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceType as _BaseTraceType import copy as _copy class Pie(_BaseTraceType): # automargin # ---------- @property def automargin(self): """ Determines whether outside text labels can push the margins. The 'automargin' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["automargin"] @automargin.setter def automargin(self, val): self["automargin"] = val # customdata # ---------- @property def customdata(self): """ Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements The 'customdata' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["customdata"] @customdata.setter def customdata(self, val): self["customdata"] = val # customdatasrc # ------------- @property def customdatasrc(self): """ Sets the source reference on plot.ly for customdata . The 'customdatasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["customdatasrc"] @customdatasrc.setter def customdatasrc(self, val): self["customdatasrc"] = val # direction # --------- @property def direction(self): """ Specifies the direction at which succeeding sectors follow one another. The 'direction' property is an enumeration that may be specified as: - One of the following enumeration values: ['clockwise', 'counterclockwise'] Returns ------- Any """ return self["direction"] @direction.setter def direction(self, val): self["direction"] = val # dlabel # ------ @property def dlabel(self): """ Sets the label step. See `label0` for more info. The 'dlabel' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["dlabel"] @dlabel.setter def dlabel(self, val): self["dlabel"] = val # domain # ------ @property def domain(self): """ The 'domain' property is an instance of Domain that may be specified as: - An instance of plotly.graph_objs.pie.Domain - A dict of string/value properties that will be passed to the Domain constructor Supported dict properties: column If there is a layout grid, use the domain for this column in the grid for this pie trace . row If there is a layout grid, use the domain for this row in the grid for this pie trace . x Sets the horizontal domain of this pie trace (in plot fraction). y Sets the vertical domain of this pie trace (in plot fraction). Returns ------- plotly.graph_objs.pie.Domain """ return self["domain"] @domain.setter def domain(self, val): self["domain"] = val # hole # ---- @property def hole(self): """ Sets the fraction of the radius to cut out of the pie. Use this to make a donut chart. The 'hole' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["hole"] @hole.setter def hole(self, val): self["hole"] = val # hoverinfo # --------- @property def hoverinfo(self): """ Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. The 'hoverinfo' property is a flaglist and may be specified as a string containing: - Any combination of ['label', 'text', 'value', 'percent', 'name'] joined with '+' characters (e.g. 'label+text') OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') - A list or array of the above Returns ------- Any|numpy.ndarray """ return self["hoverinfo"] @hoverinfo.setter def hoverinfo(self, val): self["hoverinfo"] = val # hoverinfosrc # ------------ @property def hoverinfosrc(self): """ Sets the source reference on plot.ly for hoverinfo . The 'hoverinfosrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hoverinfosrc"] @hoverinfosrc.setter def hoverinfosrc(self, val): self["hoverinfosrc"] = val # hoverlabel # ---------- @property def hoverlabel(self): """ The 'hoverlabel' property is an instance of Hoverlabel that may be specified as: - An instance of plotly.graph_objs.pie.Hoverlabel - A dict of string/value properties that will be passed to the Hoverlabel constructor Supported dict properties: align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- plotly.graph_objs.pie.Hoverlabel """ return self["hoverlabel"] @hoverlabel.setter def hoverlabel(self, val): self["hoverlabel"] = val # hovertemplate # ------------- @property def hovertemplate(self): """ Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event- data. Additionally, every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. variables `label`, `color`, `value`, `percent` and `text`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. The 'hovertemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertemplate"] @hovertemplate.setter def hovertemplate(self, val): self["hovertemplate"] = val # hovertemplatesrc # ---------------- @property def hovertemplatesrc(self): """ Sets the source reference on plot.ly for hovertemplate . The 'hovertemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertemplatesrc"] @hovertemplatesrc.setter def hovertemplatesrc(self, val): self["hovertemplatesrc"] = val # hovertext # --------- @property def hovertext(self): """ Sets hover text elements associated with each sector. If a single string, the same string appears for all data points. If an array of string, the items are mapped in order of this trace's sectors. To be seen, trace `hoverinfo` must contain a "text" flag. The 'hovertext' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertext"] @hovertext.setter def hovertext(self, val): self["hovertext"] = val # hovertextsrc # ------------ @property def hovertextsrc(self): """ Sets the source reference on plot.ly for hovertext . The 'hovertextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertextsrc"] @hovertextsrc.setter def hovertextsrc(self, val): self["hovertextsrc"] = val # ids # --- @property def ids(self): """ Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. The 'ids' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ids"] @ids.setter def ids(self, val): self["ids"] = val # idssrc # ------ @property def idssrc(self): """ Sets the source reference on plot.ly for ids . The 'idssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["idssrc"] @idssrc.setter def idssrc(self, val): self["idssrc"] = val # insidetextfont # -------------- @property def insidetextfont(self): """ Sets the font used for `textinfo` lying inside the sector. The 'insidetextfont' property is an instance of Insidetextfont that may be specified as: - An instance of plotly.graph_objs.pie.Insidetextfont - A dict of string/value properties that will be passed to the Insidetextfont constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.pie.Insidetextfont """ return self["insidetextfont"] @insidetextfont.setter def insidetextfont(self, val): self["insidetextfont"] = val # label0 # ------ @property def label0(self): """ Alternate to `labels`. Builds a numeric set of labels. Use with `dlabel` where `label0` is the starting label and `dlabel` the step. The 'label0' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["label0"] @label0.setter def label0(self, val): self["label0"] = val # labels # ------ @property def labels(self): """ Sets the sector labels. If `labels` entries are duplicated, we sum associated `values` or simply count occurrences if `values` is not provided. For other array attributes (including color) we use the first non-empty entry among all occurrences of the label. The 'labels' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["labels"] @labels.setter def labels(self, val): self["labels"] = val # labelssrc # --------- @property def labelssrc(self): """ Sets the source reference on plot.ly for labels . The 'labelssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["labelssrc"] @labelssrc.setter def labelssrc(self, val): self["labelssrc"] = val # legendgroup # ----------- @property def legendgroup(self): """ Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. The 'legendgroup' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["legendgroup"] @legendgroup.setter def legendgroup(self, val): self["legendgroup"] = val # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.pie.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: colors Sets the color of each sector. If not specified, the default trace color set is used to pick the sector colors. colorssrc Sets the source reference on plot.ly for colors . line plotly.graph_objects.pie.marker.Line instance or dict with compatible properties Returns ------- plotly.graph_objs.pie.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # meta # ---- @property def meta(self): """ Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. The 'meta' property accepts values of any type Returns ------- Any|numpy.ndarray """ return self["meta"] @meta.setter def meta(self, val): self["meta"] = val # metasrc # ------- @property def metasrc(self): """ Sets the source reference on plot.ly for meta . The 'metasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["metasrc"] @metasrc.setter def metasrc(self, val): self["metasrc"] = val # name # ---- @property def name(self): """ Sets the trace name. The trace name appear as the legend item and on hover. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the trace. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # outsidetextfont # --------------- @property def outsidetextfont(self): """ Sets the font used for `textinfo` lying outside the sector. The 'outsidetextfont' property is an instance of Outsidetextfont that may be specified as: - An instance of plotly.graph_objs.pie.Outsidetextfont - A dict of string/value properties that will be passed to the Outsidetextfont constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.pie.Outsidetextfont """ return self["outsidetextfont"] @outsidetextfont.setter def outsidetextfont(self, val): self["outsidetextfont"] = val # pull # ---- @property def pull(self): """ Sets the fraction of larger radius to pull the sectors out from the center. This can be a constant to pull all slices apart from each other equally or an array to highlight one or more slices. The 'pull' property is a number and may be specified as: - An int or float in the interval [0, 1] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["pull"] @pull.setter def pull(self, val): self["pull"] = val # pullsrc # ------- @property def pullsrc(self): """ Sets the source reference on plot.ly for pull . The 'pullsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["pullsrc"] @pullsrc.setter def pullsrc(self, val): self["pullsrc"] = val # rotation # -------- @property def rotation(self): """ Instead of the first slice starting at 12 o'clock, rotate to some other angle. The 'rotation' property is a number and may be specified as: - An int or float in the interval [-360, 360] Returns ------- int|float """ return self["rotation"] @rotation.setter def rotation(self, val): self["rotation"] = val # scalegroup # ---------- @property def scalegroup(self): """ If there are multiple pie charts that should be sized according to their totals, link them by providing a non-empty group id here shared by every trace in the same group. The 'scalegroup' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["scalegroup"] @scalegroup.setter def scalegroup(self, val): self["scalegroup"] = val # showlegend # ---------- @property def showlegend(self): """ Determines whether or not an item corresponding to this trace is shown in the legend. The 'showlegend' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showlegend"] @showlegend.setter def showlegend(self, val): self["showlegend"] = val # sort # ---- @property def sort(self): """ Determines whether or not the sectors are reordered from largest to smallest. The 'sort' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["sort"] @sort.setter def sort(self, val): self["sort"] = val # stream # ------ @property def stream(self): """ The 'stream' property is an instance of Stream that may be specified as: - An instance of plotly.graph_objs.pie.Stream - A dict of string/value properties that will be passed to the Stream constructor Supported dict properties: maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- plotly.graph_objs.pie.Stream """ return self["stream"] @stream.setter def stream(self, val): self["stream"] = val # text # ---- @property def text(self): """ Sets text elements associated with each sector. If trace `textinfo` contains a "text" flag, these elements will be seen on the chart. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. The 'text' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["text"] @text.setter def text(self, val): self["text"] = val # textfont # -------- @property def textfont(self): """ Sets the font used for `textinfo`. The 'textfont' property is an instance of Textfont that may be specified as: - An instance of plotly.graph_objs.pie.Textfont - A dict of string/value properties that will be passed to the Textfont constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.pie.Textfont """ return self["textfont"] @textfont.setter def textfont(self, val): self["textfont"] = val # textinfo # -------- @property def textinfo(self): """ Determines which trace information appear on the graph. The 'textinfo' property is a flaglist and may be specified as a string containing: - Any combination of ['label', 'text', 'value', 'percent'] joined with '+' characters (e.g. 'label+text') OR exactly one of ['none'] (e.g. 'none') Returns ------- Any """ return self["textinfo"] @textinfo.setter def textinfo(self, val): self["textinfo"] = val # textposition # ------------ @property def textposition(self): """ Specifies the location of the `textinfo`. The 'textposition' property is an enumeration that may be specified as: - One of the following enumeration values: ['inside', 'outside', 'auto', 'none'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["textposition"] @textposition.setter def textposition(self, val): self["textposition"] = val # textpositionsrc # --------------- @property def textpositionsrc(self): """ Sets the source reference on plot.ly for textposition . The 'textpositionsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["textpositionsrc"] @textpositionsrc.setter def textpositionsrc(self, val): self["textpositionsrc"] = val # textsrc # ------- @property def textsrc(self): """ Sets the source reference on plot.ly for text . The 'textsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["textsrc"] @textsrc.setter def textsrc(self, val): self["textsrc"] = val # texttemplate # ------------ @property def texttemplate(self): """ Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `label`, `color`, `value`, `percent` and `text`. The 'texttemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["texttemplate"] @texttemplate.setter def texttemplate(self, val): self["texttemplate"] = val # texttemplatesrc # --------------- @property def texttemplatesrc(self): """ Sets the source reference on plot.ly for texttemplate . The 'texttemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["texttemplatesrc"] @texttemplatesrc.setter def texttemplatesrc(self, val): self["texttemplatesrc"] = val # title # ----- @property def title(self): """ The 'title' property is an instance of Title that may be specified as: - An instance of plotly.graph_objs.pie.Title - A dict of string/value properties that will be passed to the Title constructor Supported dict properties: font Sets the font used for `title`. Note that the title's font used to be set by the now deprecated `titlefont` attribute. position Specifies the location of the `title`. Note that the title's position used to be set by the now deprecated `titleposition` attribute. text Sets the title of the chart. If it is empty, no title is displayed. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- plotly.graph_objs.pie.Title """ return self["title"] @title.setter def title(self, val): self["title"] = val # titlefont # --------- @property def titlefont(self): """ Deprecated: Please use pie.title.font instead. Sets the font used for `title`. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.pie.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- """ return self["titlefont"] @titlefont.setter def titlefont(self, val): self["titlefont"] = val # titleposition # ------------- @property def titleposition(self): """ Deprecated: Please use pie.title.position instead. Specifies the location of the `title`. Note that the title's position used to be set by the now deprecated `titleposition` attribute. The 'position' property is an enumeration that may be specified as: - One of the following enumeration values: ['top left', 'top center', 'top right', 'middle center', 'bottom left', 'bottom center', 'bottom right'] Returns ------- """ return self["titleposition"] @titleposition.setter def titleposition(self, val): self["titleposition"] = val # uid # --- @property def uid(self): """ Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. The 'uid' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["uid"] @uid.setter def uid(self, val): self["uid"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # values # ------ @property def values(self): """ Sets the values of the sectors. If omitted, we count occurrences of each label. The 'values' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["values"] @values.setter def values(self, val): self["values"] = val # valuessrc # --------- @property def valuessrc(self): """ Sets the source reference on plot.ly for values . The 'valuessrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["valuessrc"] @valuessrc.setter def valuessrc(self, val): self["valuessrc"] = val # visible # ------- @property def visible(self): """ Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). The 'visible' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'legendonly'] Returns ------- Any """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # type # ---- @property def type(self): return self._props["type"] # property parent name # -------------------- @property def _parent_path_str(self): return "" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ automargin Determines whether outside text labels can push the margins. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . direction Specifies the direction at which succeeding sectors follow one another. dlabel Sets the label step. See `label0` for more info. domain plotly.graph_objects.pie.Domain instance or dict with compatible properties hole Sets the fraction of the radius to cut out of the pie. Use this to make a donut chart. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.pie.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `label`, `color`, `value`, `percent` and `text`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each sector. If a single string, the same string appears for all data points. If an array of string, the items are mapped in order of this trace's sectors. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . insidetextfont Sets the font used for `textinfo` lying inside the sector. label0 Alternate to `labels`. Builds a numeric set of labels. Use with `dlabel` where `label0` is the starting label and `dlabel` the step. labels Sets the sector labels. If `labels` entries are duplicated, we sum associated `values` or simply count occurrences if `values` is not provided. For other array attributes (including color) we use the first non-empty entry among all occurrences of the label. labelssrc Sets the source reference on plot.ly for labels . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. marker plotly.graph_objects.pie.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. outsidetextfont Sets the font used for `textinfo` lying outside the sector. pull Sets the fraction of larger radius to pull the sectors out from the center. This can be a constant to pull all slices apart from each other equally or an array to highlight one or more slices. pullsrc Sets the source reference on plot.ly for pull . rotation Instead of the first slice starting at 12 o'clock, rotate to some other angle. scalegroup If there are multiple pie charts that should be sized according to their totals, link them by providing a non-empty group id here shared by every trace in the same group. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. sort Determines whether or not the sectors are reordered from largest to smallest. stream plotly.graph_objects.pie.Stream instance or dict with compatible properties text Sets text elements associated with each sector. If trace `textinfo` contains a "text" flag, these elements will be seen on the chart. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the font used for `textinfo`. textinfo Determines which trace information appear on the graph. textposition Specifies the location of the `textinfo`. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `label`, `color`, `value`, `percent` and `text`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . title plotly.graph_objects.pie.Title instance or dict with compatible properties titlefont Deprecated: Please use pie.title.font instead. Sets the font used for `title`. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleposition Deprecated: Please use pie.title.position instead. Specifies the location of the `title`. Note that the title's position used to be set by the now deprecated `titleposition` attribute. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. values Sets the values of the sectors. If omitted, we count occurrences of each label. valuessrc Sets the source reference on plot.ly for values . visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). """ _mapped_properties = { "titlefont": ("title", "font"), "titleposition": ("title", "position"), } def __init__( self, arg=None, automargin=None, customdata=None, customdatasrc=None, direction=None, dlabel=None, domain=None, hole=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, insidetextfont=None, label0=None, labels=None, labelssrc=None, legendgroup=None, marker=None, meta=None, metasrc=None, name=None, opacity=None, outsidetextfont=None, pull=None, pullsrc=None, rotation=None, scalegroup=None, showlegend=None, sort=None, stream=None, text=None, textfont=None, textinfo=None, textposition=None, textpositionsrc=None, textsrc=None, texttemplate=None, texttemplatesrc=None, title=None, titlefont=None, titleposition=None, uid=None, uirevision=None, values=None, valuessrc=None, visible=None, **kwargs ): """ Construct a new Pie object A data visualized by the sectors of the pie is set in `values`. The sector labels are set in `labels`. The sector colors are set in `marker.colors` Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.Pie automargin Determines whether outside text labels can push the margins. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . direction Specifies the direction at which succeeding sectors follow one another. dlabel Sets the label step. See `label0` for more info. domain plotly.graph_objects.pie.Domain instance or dict with compatible properties hole Sets the fraction of the radius to cut out of the pie. Use this to make a donut chart. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.pie.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `label`, `color`, `value`, `percent` and `text`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each sector. If a single string, the same string appears for all data points. If an array of string, the items are mapped in order of this trace's sectors. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . insidetextfont Sets the font used for `textinfo` lying inside the sector. label0 Alternate to `labels`. Builds a numeric set of labels. Use with `dlabel` where `label0` is the starting label and `dlabel` the step. labels Sets the sector labels. If `labels` entries are duplicated, we sum associated `values` or simply count occurrences if `values` is not provided. For other array attributes (including color) we use the first non-empty entry among all occurrences of the label. labelssrc Sets the source reference on plot.ly for labels . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. marker plotly.graph_objects.pie.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. outsidetextfont Sets the font used for `textinfo` lying outside the sector. pull Sets the fraction of larger radius to pull the sectors out from the center. This can be a constant to pull all slices apart from each other equally or an array to highlight one or more slices. pullsrc Sets the source reference on plot.ly for pull . rotation Instead of the first slice starting at 12 o'clock, rotate to some other angle. scalegroup If there are multiple pie charts that should be sized according to their totals, link them by providing a non-empty group id here shared by every trace in the same group. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. sort Determines whether or not the sectors are reordered from largest to smallest. stream plotly.graph_objects.pie.Stream instance or dict with compatible properties text Sets text elements associated with each sector. If trace `textinfo` contains a "text" flag, these elements will be seen on the chart. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the font used for `textinfo`. textinfo Determines which trace information appear on the graph. textposition Specifies the location of the `textinfo`. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `label`, `color`, `value`, `percent` and `text`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . title plotly.graph_objects.pie.Title instance or dict with compatible properties titlefont Deprecated: Please use pie.title.font instead. Sets the font used for `title`. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleposition Deprecated: Please use pie.title.position instead. Specifies the location of the `title`. Note that the title's position used to be set by the now deprecated `titleposition` attribute. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. values Sets the values of the sectors. If omitted, we count occurrences of each label. valuessrc Sets the source reference on plot.ly for values . visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). Returns ------- Pie """ super(Pie, self).__init__("pie") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.Pie constructor must be a dict or an instance of plotly.graph_objs.Pie""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators import pie as v_pie # Initialize validators # --------------------- self._validators["automargin"] = v_pie.AutomarginValidator() self._validators["customdata"] = v_pie.CustomdataValidator() self._validators["customdatasrc"] = v_pie.CustomdatasrcValidator() self._validators["direction"] = v_pie.DirectionValidator() self._validators["dlabel"] = v_pie.DlabelValidator() self._validators["domain"] = v_pie.DomainValidator() self._validators["hole"] = v_pie.HoleValidator() self._validators["hoverinfo"] = v_pie.HoverinfoValidator() self._validators["hoverinfosrc"] = v_pie.HoverinfosrcValidator() self._validators["hoverlabel"] = v_pie.HoverlabelValidator() self._validators["hovertemplate"] = v_pie.HovertemplateValidator() self._validators["hovertemplatesrc"] = v_pie.HovertemplatesrcValidator() self._validators["hovertext"] = v_pie.HovertextValidator() self._validators["hovertextsrc"] = v_pie.HovertextsrcValidator() self._validators["ids"] = v_pie.IdsValidator() self._validators["idssrc"] = v_pie.IdssrcValidator() self._validators["insidetextfont"] = v_pie.InsidetextfontValidator() self._validators["label0"] = v_pie.Label0Validator() self._validators["labels"] = v_pie.LabelsValidator() self._validators["labelssrc"] = v_pie.LabelssrcValidator() self._validators["legendgroup"] = v_pie.LegendgroupValidator() self._validators["marker"] = v_pie.MarkerValidator() self._validators["meta"] = v_pie.MetaValidator() self._validators["metasrc"] = v_pie.MetasrcValidator() self._validators["name"] = v_pie.NameValidator() self._validators["opacity"] = v_pie.OpacityValidator() self._validators["outsidetextfont"] = v_pie.OutsidetextfontValidator() self._validators["pull"] = v_pie.PullValidator() self._validators["pullsrc"] = v_pie.PullsrcValidator() self._validators["rotation"] = v_pie.RotationValidator() self._validators["scalegroup"] = v_pie.ScalegroupValidator() self._validators["showlegend"] = v_pie.ShowlegendValidator() self._validators["sort"] = v_pie.SortValidator() self._validators["stream"] = v_pie.StreamValidator() self._validators["text"] = v_pie.TextValidator() self._validators["textfont"] = v_pie.TextfontValidator() self._validators["textinfo"] = v_pie.TextinfoValidator() self._validators["textposition"] = v_pie.TextpositionValidator() self._validators["textpositionsrc"] = v_pie.TextpositionsrcValidator() self._validators["textsrc"] = v_pie.TextsrcValidator() self._validators["texttemplate"] = v_pie.TexttemplateValidator() self._validators["texttemplatesrc"] = v_pie.TexttemplatesrcValidator() self._validators["title"] = v_pie.TitleValidator() self._validators["uid"] = v_pie.UidValidator() self._validators["uirevision"] = v_pie.UirevisionValidator() self._validators["values"] = v_pie.ValuesValidator() self._validators["valuessrc"] = v_pie.ValuessrcValidator() self._validators["visible"] = v_pie.VisibleValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("automargin", None) self["automargin"] = automargin if automargin is not None else _v _v = arg.pop("customdata", None) self["customdata"] = customdata if customdata is not None else _v _v = arg.pop("customdatasrc", None) self["customdatasrc"] = customdatasrc if customdatasrc is not None else _v _v = arg.pop("direction", None) self["direction"] = direction if direction is not None else _v _v = arg.pop("dlabel", None) self["dlabel"] = dlabel if dlabel is not None else _v _v = arg.pop("domain", None) self["domain"] = domain if domain is not None else _v _v = arg.pop("hole", None) self["hole"] = hole if hole is not None else _v _v = arg.pop("hoverinfo", None) self["hoverinfo"] = hoverinfo if hoverinfo is not None else _v _v = arg.pop("hoverinfosrc", None) self["hoverinfosrc"] = hoverinfosrc if hoverinfosrc is not None else _v _v = arg.pop("hoverlabel", None) self["hoverlabel"] = hoverlabel if hoverlabel is not None else _v _v = arg.pop("hovertemplate", None) self["hovertemplate"] = hovertemplate if hovertemplate is not None else _v _v = arg.pop("hovertemplatesrc", None) self["hovertemplatesrc"] = ( hovertemplatesrc if hovertemplatesrc is not None else _v ) _v = arg.pop("hovertext", None) self["hovertext"] = hovertext if hovertext is not None else _v _v = arg.pop("hovertextsrc", None) self["hovertextsrc"] = hovertextsrc if hovertextsrc is not None else _v _v = arg.pop("ids", None) self["ids"] = ids if ids is not None else _v _v = arg.pop("idssrc", None) self["idssrc"] = idssrc if idssrc is not None else _v _v = arg.pop("insidetextfont", None) self["insidetextfont"] = insidetextfont if insidetextfont is not None else _v _v = arg.pop("label0", None) self["label0"] = label0 if label0 is not None else _v _v = arg.pop("labels", None) self["labels"] = labels if labels is not None else _v _v = arg.pop("labelssrc", None) self["labelssrc"] = labelssrc if labelssrc is not None else _v _v = arg.pop("legendgroup", None) self["legendgroup"] = legendgroup if legendgroup is not None else _v _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v _v = arg.pop("meta", None) self["meta"] = meta if meta is not None else _v _v = arg.pop("metasrc", None) self["metasrc"] = metasrc if metasrc is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("outsidetextfont", None) self["outsidetextfont"] = outsidetextfont if outsidetextfont is not None else _v _v = arg.pop("pull", None) self["pull"] = pull if pull is not None else _v _v = arg.pop("pullsrc", None) self["pullsrc"] = pullsrc if pullsrc is not None else _v _v = arg.pop("rotation", None) self["rotation"] = rotation if rotation is not None else _v _v = arg.pop("scalegroup", None) self["scalegroup"] = scalegroup if scalegroup is not None else _v _v = arg.pop("showlegend", None) self["showlegend"] = showlegend if showlegend is not None else _v _v = arg.pop("sort", None) self["sort"] = sort if sort is not None else _v _v = arg.pop("stream", None) self["stream"] = stream if stream is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v _v = arg.pop("textfont", None) self["textfont"] = textfont if textfont is not None else _v _v = arg.pop("textinfo", None) self["textinfo"] = textinfo if textinfo is not None else _v _v = arg.pop("textposition", None) self["textposition"] = textposition if textposition is not None else _v _v = arg.pop("textpositionsrc", None) self["textpositionsrc"] = textpositionsrc if textpositionsrc is not None else _v _v = arg.pop("textsrc", None) self["textsrc"] = textsrc if textsrc is not None else _v _v = arg.pop("texttemplate", None) self["texttemplate"] = texttemplate if texttemplate is not None else _v _v = arg.pop("texttemplatesrc", None) self["texttemplatesrc"] = texttemplatesrc if texttemplatesrc is not None else _v _v = arg.pop("title", None) self["title"] = title if title is not None else _v _v = arg.pop("titlefont", None) _v = titlefont if titlefont is not None else _v if _v is not None: self["titlefont"] = _v _v = arg.pop("titleposition", None) _v = titleposition if titleposition is not None else _v if _v is not None: self["titleposition"] = _v _v = arg.pop("uid", None) self["uid"] = uid if uid is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("values", None) self["values"] = values if values is not None else _v _v = arg.pop("valuessrc", None) self["valuessrc"] = valuessrc if valuessrc is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v # Read-only literals # ------------------ from _plotly_utils.basevalidators import LiteralValidator self._props["type"] = "pie" self._validators["type"] = LiteralValidator( plotly_name="type", parent_name="pie", val="pie" ) arg.pop("type", None) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceType as _BaseTraceType import copy as _copy class Parcoords(_BaseTraceType): # customdata # ---------- @property def customdata(self): """ Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements The 'customdata' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["customdata"] @customdata.setter def customdata(self, val): self["customdata"] = val # customdatasrc # ------------- @property def customdatasrc(self): """ Sets the source reference on plot.ly for customdata . The 'customdatasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["customdatasrc"] @customdatasrc.setter def customdatasrc(self, val): self["customdatasrc"] = val # dimensions # ---------- @property def dimensions(self): """ The dimensions (variables) of the parallel coordinates chart. 2..60 dimensions are supported. The 'dimensions' property is a tuple of instances of Dimension that may be specified as: - A list or tuple of instances of plotly.graph_objs.parcoords.Dimension - A list or tuple of dicts of string/value properties that will be passed to the Dimension constructor Supported dict properties: constraintrange The domain range to which the filter on the dimension is constrained. Must be an array of `[fromValue, toValue]` with `fromValue <= toValue`, or if `multiselect` is not disabled, you may give an array of arrays, where each inner array is `[fromValue, toValue]`. label The shown name of the dimension. multiselect Do we allow multiple selection ranges or just a single range? name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. range The domain range that represents the full, shown axis extent. Defaults to the `values` extent. Must be an array of `[fromValue, toValue]` with finite numbers as elements. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" ticktext Sets the text displayed at the ticks position via `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. tickvalssrc Sets the source reference on plot.ly for tickvals . values Dimension values. `values[n]` represents the value of the `n`th point in the dataset, therefore the `values` vector for all dimensions must be the same (longer vectors will be truncated). Each value must be a finite number. valuessrc Sets the source reference on plot.ly for values . visible Shows the dimension when set to `true` (the default). Hides the dimension for `false`. Returns ------- tuple[plotly.graph_objs.parcoords.Dimension] """ return self["dimensions"] @dimensions.setter def dimensions(self, val): self["dimensions"] = val # dimensiondefaults # ----------------- @property def dimensiondefaults(self): """ When used in a template (as layout.template.data.parcoords.dimensiondefaults), sets the default property values to use for elements of parcoords.dimensions The 'dimensiondefaults' property is an instance of Dimension that may be specified as: - An instance of plotly.graph_objs.parcoords.Dimension - A dict of string/value properties that will be passed to the Dimension constructor Supported dict properties: Returns ------- plotly.graph_objs.parcoords.Dimension """ return self["dimensiondefaults"] @dimensiondefaults.setter def dimensiondefaults(self, val): self["dimensiondefaults"] = val # domain # ------ @property def domain(self): """ The 'domain' property is an instance of Domain that may be specified as: - An instance of plotly.graph_objs.parcoords.Domain - A dict of string/value properties that will be passed to the Domain constructor Supported dict properties: column If there is a layout grid, use the domain for this column in the grid for this parcoords trace . row If there is a layout grid, use the domain for this row in the grid for this parcoords trace . x Sets the horizontal domain of this parcoords trace (in plot fraction). y Sets the vertical domain of this parcoords trace (in plot fraction). Returns ------- plotly.graph_objs.parcoords.Domain """ return self["domain"] @domain.setter def domain(self, val): self["domain"] = val # ids # --- @property def ids(self): """ Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. The 'ids' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ids"] @ids.setter def ids(self, val): self["ids"] = val # idssrc # ------ @property def idssrc(self): """ Sets the source reference on plot.ly for ids . The 'idssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["idssrc"] @idssrc.setter def idssrc(self, val): self["idssrc"] = val # labelangle # ---------- @property def labelangle(self): """ Sets the angle of the labels with respect to the horizontal. For example, a `tickangle` of -90 draws the labels vertically. Tilted labels with "labelangle" may be positioned better inside margins when `labelposition` is set to "bottom". The 'labelangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["labelangle"] @labelangle.setter def labelangle(self, val): self["labelangle"] = val # labelfont # --------- @property def labelfont(self): """ Sets the font for the `dimension` labels. The 'labelfont' property is an instance of Labelfont that may be specified as: - An instance of plotly.graph_objs.parcoords.Labelfont - A dict of string/value properties that will be passed to the Labelfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.parcoords.Labelfont """ return self["labelfont"] @labelfont.setter def labelfont(self, val): self["labelfont"] = val # labelside # --------- @property def labelside(self): """ Specifies the location of the `label`. "top" positions labels above, next to the title "bottom" positions labels below the graph Tilted labels with "labelangle" may be positioned better inside margins when `labelposition` is set to "bottom". The 'labelside' property is an enumeration that may be specified as: - One of the following enumeration values: ['top', 'bottom'] Returns ------- Any """ return self["labelside"] @labelside.setter def labelside(self, val): self["labelside"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.parcoords.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `line.colorscale`. Has an effect only if in `line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `line.color`) or the bounds set in `line.cmin` and `line.cmax` Has an effect only if in `line.color`is set to a numerical array. Defaults to `false` when `line.cmin` and `line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `line.color`is set to a numerical array. Value should have the same units as in `line.color` and if set, `line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `line.cmin` and/or `line.cmax` to be equidistant to this point. Has an effect only if in `line.color`is set to a numerical array. Value should have the same units as in `line.color`. Has no effect when `line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `line.color`is set to a numerical array. Value should have the same units as in `line.color` and if set, `line.cmax` must be set as well. color Sets thelinecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `line.cmin` and `line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.parcoords.line.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`line.cmin` and `line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu ,Greens,YlOrRd,Bluered,RdBu,Reds,Blues,Picnic,R ainbow,Portland,Jet,Hot,Blackbody,Earth,Electri c,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `line.color`is set to a numerical array. If true, `line.cmin` will correspond to the last color in the array and `line.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `line.color`is set to a numerical array. Returns ------- plotly.graph_objs.parcoords.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # meta # ---- @property def meta(self): """ Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. The 'meta' property accepts values of any type Returns ------- Any|numpy.ndarray """ return self["meta"] @meta.setter def meta(self, val): self["meta"] = val # metasrc # ------- @property def metasrc(self): """ Sets the source reference on plot.ly for meta . The 'metasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["metasrc"] @metasrc.setter def metasrc(self, val): self["metasrc"] = val # name # ---- @property def name(self): """ Sets the trace name. The trace name appear as the legend item and on hover. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # rangefont # --------- @property def rangefont(self): """ Sets the font for the `dimension` range values. The 'rangefont' property is an instance of Rangefont that may be specified as: - An instance of plotly.graph_objs.parcoords.Rangefont - A dict of string/value properties that will be passed to the Rangefont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.parcoords.Rangefont """ return self["rangefont"] @rangefont.setter def rangefont(self, val): self["rangefont"] = val # stream # ------ @property def stream(self): """ The 'stream' property is an instance of Stream that may be specified as: - An instance of plotly.graph_objs.parcoords.Stream - A dict of string/value properties that will be passed to the Stream constructor Supported dict properties: maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- plotly.graph_objs.parcoords.Stream """ return self["stream"] @stream.setter def stream(self, val): self["stream"] = val # tickfont # -------- @property def tickfont(self): """ Sets the font for the `dimension` tick values. The 'tickfont' property is an instance of Tickfont that may be specified as: - An instance of plotly.graph_objs.parcoords.Tickfont - A dict of string/value properties that will be passed to the Tickfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.parcoords.Tickfont """ return self["tickfont"] @tickfont.setter def tickfont(self, val): self["tickfont"] = val # uid # --- @property def uid(self): """ Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. The 'uid' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["uid"] @uid.setter def uid(self, val): self["uid"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # visible # ------- @property def visible(self): """ Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). The 'visible' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'legendonly'] Returns ------- Any """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # type # ---- @property def type(self): return self._props["type"] # property parent name # -------------------- @property def _parent_path_str(self): return "" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dimensions The dimensions (variables) of the parallel coordinates chart. 2..60 dimensions are supported. dimensiondefaults When used in a template (as layout.template.data.parcoords.dimensiondefaults), sets the default property values to use for elements of parcoords.dimensions domain plotly.graph_objects.parcoords.Domain instance or dict with compatible properties ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . labelangle Sets the angle of the labels with respect to the horizontal. For example, a `tickangle` of -90 draws the labels vertically. Tilted labels with "labelangle" may be positioned better inside margins when `labelposition` is set to "bottom". labelfont Sets the font for the `dimension` labels. labelside Specifies the location of the `label`. "top" positions labels above, next to the title "bottom" positions labels below the graph Tilted labels with "labelangle" may be positioned better inside margins when `labelposition` is set to "bottom". line plotly.graph_objects.parcoords.Line instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. rangefont Sets the font for the `dimension` range values. stream plotly.graph_objects.parcoords.Stream instance or dict with compatible properties tickfont Sets the font for the `dimension` tick values. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). """ def __init__( self, arg=None, customdata=None, customdatasrc=None, dimensions=None, dimensiondefaults=None, domain=None, ids=None, idssrc=None, labelangle=None, labelfont=None, labelside=None, line=None, meta=None, metasrc=None, name=None, rangefont=None, stream=None, tickfont=None, uid=None, uirevision=None, visible=None, **kwargs ): """ Construct a new Parcoords object Parallel coordinates for multidimensional exploratory data analysis. The samples are specified in `dimensions`. The colors are set in `line.color`. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.Parcoords customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dimensions The dimensions (variables) of the parallel coordinates chart. 2..60 dimensions are supported. dimensiondefaults When used in a template (as layout.template.data.parcoords.dimensiondefaults), sets the default property values to use for elements of parcoords.dimensions domain plotly.graph_objects.parcoords.Domain instance or dict with compatible properties ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . labelangle Sets the angle of the labels with respect to the horizontal. For example, a `tickangle` of -90 draws the labels vertically. Tilted labels with "labelangle" may be positioned better inside margins when `labelposition` is set to "bottom". labelfont Sets the font for the `dimension` labels. labelside Specifies the location of the `label`. "top" positions labels above, next to the title "bottom" positions labels below the graph Tilted labels with "labelangle" may be positioned better inside margins when `labelposition` is set to "bottom". line plotly.graph_objects.parcoords.Line instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. rangefont Sets the font for the `dimension` range values. stream plotly.graph_objects.parcoords.Stream instance or dict with compatible properties tickfont Sets the font for the `dimension` tick values. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). Returns ------- Parcoords """ super(Parcoords, self).__init__("parcoords") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.Parcoords constructor must be a dict or an instance of plotly.graph_objs.Parcoords""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators import parcoords as v_parcoords # Initialize validators # --------------------- self._validators["customdata"] = v_parcoords.CustomdataValidator() self._validators["customdatasrc"] = v_parcoords.CustomdatasrcValidator() self._validators["dimensions"] = v_parcoords.DimensionsValidator() self._validators["dimensiondefaults"] = v_parcoords.DimensionValidator() self._validators["domain"] = v_parcoords.DomainValidator() self._validators["ids"] = v_parcoords.IdsValidator() self._validators["idssrc"] = v_parcoords.IdssrcValidator() self._validators["labelangle"] = v_parcoords.LabelangleValidator() self._validators["labelfont"] = v_parcoords.LabelfontValidator() self._validators["labelside"] = v_parcoords.LabelsideValidator() self._validators["line"] = v_parcoords.LineValidator() self._validators["meta"] = v_parcoords.MetaValidator() self._validators["metasrc"] = v_parcoords.MetasrcValidator() self._validators["name"] = v_parcoords.NameValidator() self._validators["rangefont"] = v_parcoords.RangefontValidator() self._validators["stream"] = v_parcoords.StreamValidator() self._validators["tickfont"] = v_parcoords.TickfontValidator() self._validators["uid"] = v_parcoords.UidValidator() self._validators["uirevision"] = v_parcoords.UirevisionValidator() self._validators["visible"] = v_parcoords.VisibleValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("customdata", None) self["customdata"] = customdata if customdata is not None else _v _v = arg.pop("customdatasrc", None) self["customdatasrc"] = customdatasrc if customdatasrc is not None else _v _v = arg.pop("dimensions", None) self["dimensions"] = dimensions if dimensions is not None else _v _v = arg.pop("dimensiondefaults", None) self["dimensiondefaults"] = ( dimensiondefaults if dimensiondefaults is not None else _v ) _v = arg.pop("domain", None) self["domain"] = domain if domain is not None else _v _v = arg.pop("ids", None) self["ids"] = ids if ids is not None else _v _v = arg.pop("idssrc", None) self["idssrc"] = idssrc if idssrc is not None else _v _v = arg.pop("labelangle", None) self["labelangle"] = labelangle if labelangle is not None else _v _v = arg.pop("labelfont", None) self["labelfont"] = labelfont if labelfont is not None else _v _v = arg.pop("labelside", None) self["labelside"] = labelside if labelside is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v _v = arg.pop("meta", None) self["meta"] = meta if meta is not None else _v _v = arg.pop("metasrc", None) self["metasrc"] = metasrc if metasrc is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("rangefont", None) self["rangefont"] = rangefont if rangefont is not None else _v _v = arg.pop("stream", None) self["stream"] = stream if stream is not None else _v _v = arg.pop("tickfont", None) self["tickfont"] = tickfont if tickfont is not None else _v _v = arg.pop("uid", None) self["uid"] = uid if uid is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v # Read-only literals # ------------------ from _plotly_utils.basevalidators import LiteralValidator self._props["type"] = "parcoords" self._validators["type"] = LiteralValidator( plotly_name="type", parent_name="parcoords", val="parcoords" ) arg.pop("type", None) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceType as _BaseTraceType import copy as _copy class Parcats(_BaseTraceType): # arrangement # ----------- @property def arrangement(self): """ Sets the drag interaction mode for categories and dimensions. If `perpendicular`, the categories can only move along a line perpendicular to the paths. If `freeform`, the categories can freely move on the plane. If `fixed`, the categories and dimensions are stationary. The 'arrangement' property is an enumeration that may be specified as: - One of the following enumeration values: ['perpendicular', 'freeform', 'fixed'] Returns ------- Any """ return self["arrangement"] @arrangement.setter def arrangement(self, val): self["arrangement"] = val # bundlecolors # ------------ @property def bundlecolors(self): """ Sort paths so that like colors are bundled together within each category. The 'bundlecolors' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["bundlecolors"] @bundlecolors.setter def bundlecolors(self, val): self["bundlecolors"] = val # counts # ------ @property def counts(self): """ The number of observations represented by each state. Defaults to 1 so that each state represents one observation The 'counts' property is a number and may be specified as: - An int or float in the interval [0, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["counts"] @counts.setter def counts(self, val): self["counts"] = val # countssrc # --------- @property def countssrc(self): """ Sets the source reference on plot.ly for counts . The 'countssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["countssrc"] @countssrc.setter def countssrc(self, val): self["countssrc"] = val # dimensions # ---------- @property def dimensions(self): """ The dimensions (variables) of the parallel categories diagram. The 'dimensions' property is a tuple of instances of Dimension that may be specified as: - A list or tuple of instances of plotly.graph_objs.parcats.Dimension - A list or tuple of dicts of string/value properties that will be passed to the Dimension constructor Supported dict properties: categoryarray Sets the order in which categories in this dimension appear. Only has an effect if `categoryorder` is set to "array". Used with `categoryorder`. categoryarraysrc Sets the source reference on plot.ly for categoryarray . categoryorder Specifies the ordering logic for the categories in the dimension. By default, plotly uses "trace", which specifies the order that is present in the data supplied. Set `categoryorder` to *category ascending* or *category descending* if order should be determined by the alphanumerical order of the category names. Set `categoryorder` to "array" to derive the ordering from the attribute `categoryarray`. If a category is not found in the `categoryarray` array, the sorting behavior for that attribute will be identical to the "trace" mode. The unspecified categories will follow the categories in `categoryarray`. displayindex The display index of dimension, from left to right, zero indexed, defaults to dimension index. label The shown name of the dimension. ticktext Sets alternative tick labels for the categories in this dimension. Only has an effect if `categoryorder` is set to "array". Should be an array the same length as `categoryarray` Used with `categoryorder`. ticktextsrc Sets the source reference on plot.ly for ticktext . values Dimension values. `values[n]` represents the category value of the `n`th point in the dataset, therefore the `values` vector for all dimensions must be the same (longer vectors will be truncated). valuessrc Sets the source reference on plot.ly for values . visible Shows the dimension when set to `true` (the default). Hides the dimension for `false`. Returns ------- tuple[plotly.graph_objs.parcats.Dimension] """ return self["dimensions"] @dimensions.setter def dimensions(self, val): self["dimensions"] = val # dimensiondefaults # ----------------- @property def dimensiondefaults(self): """ When used in a template (as layout.template.data.parcats.dimensiondefaults), sets the default property values to use for elements of parcats.dimensions The 'dimensiondefaults' property is an instance of Dimension that may be specified as: - An instance of plotly.graph_objs.parcats.Dimension - A dict of string/value properties that will be passed to the Dimension constructor Supported dict properties: Returns ------- plotly.graph_objs.parcats.Dimension """ return self["dimensiondefaults"] @dimensiondefaults.setter def dimensiondefaults(self, val): self["dimensiondefaults"] = val # domain # ------ @property def domain(self): """ The 'domain' property is an instance of Domain that may be specified as: - An instance of plotly.graph_objs.parcats.Domain - A dict of string/value properties that will be passed to the Domain constructor Supported dict properties: column If there is a layout grid, use the domain for this column in the grid for this parcats trace . row If there is a layout grid, use the domain for this row in the grid for this parcats trace . x Sets the horizontal domain of this parcats trace (in plot fraction). y Sets the vertical domain of this parcats trace (in plot fraction). Returns ------- plotly.graph_objs.parcats.Domain """ return self["domain"] @domain.setter def domain(self, val): self["domain"] = val # hoverinfo # --------- @property def hoverinfo(self): """ Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. The 'hoverinfo' property is a flaglist and may be specified as a string containing: - Any combination of ['count', 'probability'] joined with '+' characters (e.g. 'count+probability') OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') Returns ------- Any """ return self["hoverinfo"] @hoverinfo.setter def hoverinfo(self, val): self["hoverinfo"] = val # hoveron # ------- @property def hoveron(self): """ Sets the hover interaction mode for the parcats diagram. If `category`, hover interaction take place per category. If `color`, hover interactions take place per color per category. If `dimension`, hover interactions take place across all categories per dimension. The 'hoveron' property is an enumeration that may be specified as: - One of the following enumeration values: ['category', 'color', 'dimension'] Returns ------- Any """ return self["hoveron"] @hoveron.setter def hoveron(self, val): self["hoveron"] = val # hovertemplate # ------------- @property def hovertemplate(self): """ Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event- data. Additionally, every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. variables `count`, `probability`, `category`, `categorycount`, `colorcount` and `bandcolorcount`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. The 'hovertemplate' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["hovertemplate"] @hovertemplate.setter def hovertemplate(self, val): self["hovertemplate"] = val # labelfont # --------- @property def labelfont(self): """ Sets the font for the `dimension` labels. The 'labelfont' property is an instance of Labelfont that may be specified as: - An instance of plotly.graph_objs.parcats.Labelfont - A dict of string/value properties that will be passed to the Labelfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.parcats.Labelfont """ return self["labelfont"] @labelfont.setter def labelfont(self, val): self["labelfont"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.parcats.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `line.colorscale`. Has an effect only if in `line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `line.color`) or the bounds set in `line.cmin` and `line.cmax` Has an effect only if in `line.color`is set to a numerical array. Defaults to `false` when `line.cmin` and `line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `line.color`is set to a numerical array. Value should have the same units as in `line.color` and if set, `line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `line.cmin` and/or `line.cmax` to be equidistant to this point. Has an effect only if in `line.color`is set to a numerical array. Value should have the same units as in `line.color`. Has no effect when `line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `line.color`is set to a numerical array. Value should have the same units as in `line.color` and if set, `line.cmax` must be set as well. color Sets thelinecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `line.cmin` and `line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.parcats.line.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`line.cmin` and `line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu ,Greens,YlOrRd,Bluered,RdBu,Reds,Blues,Picnic,R ainbow,Portland,Jet,Hot,Blackbody,Earth,Electri c,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs- events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `count` and `probability`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. reversescale Reverses the color mapping if true. Has an effect only if in `line.color`is set to a numerical array. If true, `line.cmin` will correspond to the last color in the array and `line.cmax` will correspond to the first color. shape Sets the shape of the paths. If `linear`, paths are composed of straight lines. If `hspline`, paths are composed of horizontal curved splines showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `line.color`is set to a numerical array. Returns ------- plotly.graph_objs.parcats.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # meta # ---- @property def meta(self): """ Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. The 'meta' property accepts values of any type Returns ------- Any|numpy.ndarray """ return self["meta"] @meta.setter def meta(self, val): self["meta"] = val # metasrc # ------- @property def metasrc(self): """ Sets the source reference on plot.ly for meta . The 'metasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["metasrc"] @metasrc.setter def metasrc(self, val): self["metasrc"] = val # name # ---- @property def name(self): """ Sets the trace name. The trace name appear as the legend item and on hover. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # sortpaths # --------- @property def sortpaths(self): """ Sets the path sorting algorithm. If `forward`, sort paths based on dimension categories from left to right. If `backward`, sort paths based on dimensions categories from right to left. The 'sortpaths' property is an enumeration that may be specified as: - One of the following enumeration values: ['forward', 'backward'] Returns ------- Any """ return self["sortpaths"] @sortpaths.setter def sortpaths(self, val): self["sortpaths"] = val # stream # ------ @property def stream(self): """ The 'stream' property is an instance of Stream that may be specified as: - An instance of plotly.graph_objs.parcats.Stream - A dict of string/value properties that will be passed to the Stream constructor Supported dict properties: maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- plotly.graph_objs.parcats.Stream """ return self["stream"] @stream.setter def stream(self, val): self["stream"] = val # tickfont # -------- @property def tickfont(self): """ Sets the font for the `category` labels. The 'tickfont' property is an instance of Tickfont that may be specified as: - An instance of plotly.graph_objs.parcats.Tickfont - A dict of string/value properties that will be passed to the Tickfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.parcats.Tickfont """ return self["tickfont"] @tickfont.setter def tickfont(self, val): self["tickfont"] = val # uid # --- @property def uid(self): """ Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. The 'uid' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["uid"] @uid.setter def uid(self, val): self["uid"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # visible # ------- @property def visible(self): """ Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). The 'visible' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'legendonly'] Returns ------- Any """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # type # ---- @property def type(self): return self._props["type"] # property parent name # -------------------- @property def _parent_path_str(self): return "" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ arrangement Sets the drag interaction mode for categories and dimensions. If `perpendicular`, the categories can only move along a line perpendicular to the paths. If `freeform`, the categories can freely move on the plane. If `fixed`, the categories and dimensions are stationary. bundlecolors Sort paths so that like colors are bundled together within each category. counts The number of observations represented by each state. Defaults to 1 so that each state represents one observation countssrc Sets the source reference on plot.ly for counts . dimensions The dimensions (variables) of the parallel categories diagram. dimensiondefaults When used in a template (as layout.template.data.parcats.dimensiondefaults), sets the default property values to use for elements of parcats.dimensions domain plotly.graph_objects.parcats.Domain instance or dict with compatible properties hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoveron Sets the hover interaction mode for the parcats diagram. If `category`, hover interaction take place per category. If `color`, hover interactions take place per color per category. If `dimension`, hover interactions take place across all categories per dimension. hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `count`, `probability`, `category`, `categorycount`, `colorcount` and `bandcolorcount`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. labelfont Sets the font for the `dimension` labels. line plotly.graph_objects.parcats.Line instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. sortpaths Sets the path sorting algorithm. If `forward`, sort paths based on dimension categories from left to right. If `backward`, sort paths based on dimensions categories from right to left. stream plotly.graph_objects.parcats.Stream instance or dict with compatible properties tickfont Sets the font for the `category` labels. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). """ def __init__( self, arg=None, arrangement=None, bundlecolors=None, counts=None, countssrc=None, dimensions=None, dimensiondefaults=None, domain=None, hoverinfo=None, hoveron=None, hovertemplate=None, labelfont=None, line=None, meta=None, metasrc=None, name=None, sortpaths=None, stream=None, tickfont=None, uid=None, uirevision=None, visible=None, **kwargs ): """ Construct a new Parcats object Parallel categories diagram for multidimensional categorical data. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.Parcats arrangement Sets the drag interaction mode for categories and dimensions. If `perpendicular`, the categories can only move along a line perpendicular to the paths. If `freeform`, the categories can freely move on the plane. If `fixed`, the categories and dimensions are stationary. bundlecolors Sort paths so that like colors are bundled together within each category. counts The number of observations represented by each state. Defaults to 1 so that each state represents one observation countssrc Sets the source reference on plot.ly for counts . dimensions The dimensions (variables) of the parallel categories diagram. dimensiondefaults When used in a template (as layout.template.data.parcats.dimensiondefaults), sets the default property values to use for elements of parcats.dimensions domain plotly.graph_objects.parcats.Domain instance or dict with compatible properties hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoveron Sets the hover interaction mode for the parcats diagram. If `category`, hover interaction take place per category. If `color`, hover interactions take place per color per category. If `dimension`, hover interactions take place across all categories per dimension. hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `count`, `probability`, `category`, `categorycount`, `colorcount` and `bandcolorcount`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. labelfont Sets the font for the `dimension` labels. line plotly.graph_objects.parcats.Line instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. sortpaths Sets the path sorting algorithm. If `forward`, sort paths based on dimension categories from left to right. If `backward`, sort paths based on dimensions categories from right to left. stream plotly.graph_objects.parcats.Stream instance or dict with compatible properties tickfont Sets the font for the `category` labels. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). Returns ------- Parcats """ super(Parcats, self).__init__("parcats") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.Parcats constructor must be a dict or an instance of plotly.graph_objs.Parcats""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators import parcats as v_parcats # Initialize validators # --------------------- self._validators["arrangement"] = v_parcats.ArrangementValidator() self._validators["bundlecolors"] = v_parcats.BundlecolorsValidator() self._validators["counts"] = v_parcats.CountsValidator() self._validators["countssrc"] = v_parcats.CountssrcValidator() self._validators["dimensions"] = v_parcats.DimensionsValidator() self._validators["dimensiondefaults"] = v_parcats.DimensionValidator() self._validators["domain"] = v_parcats.DomainValidator() self._validators["hoverinfo"] = v_parcats.HoverinfoValidator() self._validators["hoveron"] = v_parcats.HoveronValidator() self._validators["hovertemplate"] = v_parcats.HovertemplateValidator() self._validators["labelfont"] = v_parcats.LabelfontValidator() self._validators["line"] = v_parcats.LineValidator() self._validators["meta"] = v_parcats.MetaValidator() self._validators["metasrc"] = v_parcats.MetasrcValidator() self._validators["name"] = v_parcats.NameValidator() self._validators["sortpaths"] = v_parcats.SortpathsValidator() self._validators["stream"] = v_parcats.StreamValidator() self._validators["tickfont"] = v_parcats.TickfontValidator() self._validators["uid"] = v_parcats.UidValidator() self._validators["uirevision"] = v_parcats.UirevisionValidator() self._validators["visible"] = v_parcats.VisibleValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("arrangement", None) self["arrangement"] = arrangement if arrangement is not None else _v _v = arg.pop("bundlecolors", None) self["bundlecolors"] = bundlecolors if bundlecolors is not None else _v _v = arg.pop("counts", None) self["counts"] = counts if counts is not None else _v _v = arg.pop("countssrc", None) self["countssrc"] = countssrc if countssrc is not None else _v _v = arg.pop("dimensions", None) self["dimensions"] = dimensions if dimensions is not None else _v _v = arg.pop("dimensiondefaults", None) self["dimensiondefaults"] = ( dimensiondefaults if dimensiondefaults is not None else _v ) _v = arg.pop("domain", None) self["domain"] = domain if domain is not None else _v _v = arg.pop("hoverinfo", None) self["hoverinfo"] = hoverinfo if hoverinfo is not None else _v _v = arg.pop("hoveron", None) self["hoveron"] = hoveron if hoveron is not None else _v _v = arg.pop("hovertemplate", None) self["hovertemplate"] = hovertemplate if hovertemplate is not None else _v _v = arg.pop("labelfont", None) self["labelfont"] = labelfont if labelfont is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v _v = arg.pop("meta", None) self["meta"] = meta if meta is not None else _v _v = arg.pop("metasrc", None) self["metasrc"] = metasrc if metasrc is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("sortpaths", None) self["sortpaths"] = sortpaths if sortpaths is not None else _v _v = arg.pop("stream", None) self["stream"] = stream if stream is not None else _v _v = arg.pop("tickfont", None) self["tickfont"] = tickfont if tickfont is not None else _v _v = arg.pop("uid", None) self["uid"] = uid if uid is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v # Read-only literals # ------------------ from _plotly_utils.basevalidators import LiteralValidator self._props["type"] = "parcats" self._validators["type"] = LiteralValidator( plotly_name="type", parent_name="parcats", val="parcats" ) arg.pop("type", None) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceType as _BaseTraceType import copy as _copy class Ohlc(_BaseTraceType): # close # ----- @property def close(self): """ Sets the close values. The 'close' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["close"] @close.setter def close(self, val): self["close"] = val # closesrc # -------- @property def closesrc(self): """ Sets the source reference on plot.ly for close . The 'closesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["closesrc"] @closesrc.setter def closesrc(self, val): self["closesrc"] = val # customdata # ---------- @property def customdata(self): """ Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements The 'customdata' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["customdata"] @customdata.setter def customdata(self, val): self["customdata"] = val # customdatasrc # ------------- @property def customdatasrc(self): """ Sets the source reference on plot.ly for customdata . The 'customdatasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["customdatasrc"] @customdatasrc.setter def customdatasrc(self, val): self["customdatasrc"] = val # decreasing # ---------- @property def decreasing(self): """ The 'decreasing' property is an instance of Decreasing that may be specified as: - An instance of plotly.graph_objs.ohlc.Decreasing - A dict of string/value properties that will be passed to the Decreasing constructor Supported dict properties: line plotly.graph_objects.ohlc.decreasing.Line instance or dict with compatible properties Returns ------- plotly.graph_objs.ohlc.Decreasing """ return self["decreasing"] @decreasing.setter def decreasing(self, val): self["decreasing"] = val # high # ---- @property def high(self): """ Sets the high values. The 'high' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["high"] @high.setter def high(self, val): self["high"] = val # highsrc # ------- @property def highsrc(self): """ Sets the source reference on plot.ly for high . The 'highsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["highsrc"] @highsrc.setter def highsrc(self, val): self["highsrc"] = val # hoverinfo # --------- @property def hoverinfo(self): """ Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. The 'hoverinfo' property is a flaglist and may be specified as a string containing: - Any combination of ['x', 'y', 'z', 'text', 'name'] joined with '+' characters (e.g. 'x+y') OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') - A list or array of the above Returns ------- Any|numpy.ndarray """ return self["hoverinfo"] @hoverinfo.setter def hoverinfo(self, val): self["hoverinfo"] = val # hoverinfosrc # ------------ @property def hoverinfosrc(self): """ Sets the source reference on plot.ly for hoverinfo . The 'hoverinfosrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hoverinfosrc"] @hoverinfosrc.setter def hoverinfosrc(self, val): self["hoverinfosrc"] = val # hoverlabel # ---------- @property def hoverlabel(self): """ The 'hoverlabel' property is an instance of Hoverlabel that may be specified as: - An instance of plotly.graph_objs.ohlc.Hoverlabel - A dict of string/value properties that will be passed to the Hoverlabel constructor Supported dict properties: align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . split Show hover information (open, close, high, low) in separate labels. Returns ------- plotly.graph_objs.ohlc.Hoverlabel """ return self["hoverlabel"] @hoverlabel.setter def hoverlabel(self, val): self["hoverlabel"] = val # hovertext # --------- @property def hovertext(self): """ Same as `text`. The 'hovertext' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertext"] @hovertext.setter def hovertext(self, val): self["hovertext"] = val # hovertextsrc # ------------ @property def hovertextsrc(self): """ Sets the source reference on plot.ly for hovertext . The 'hovertextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertextsrc"] @hovertextsrc.setter def hovertextsrc(self, val): self["hovertextsrc"] = val # ids # --- @property def ids(self): """ Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. The 'ids' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ids"] @ids.setter def ids(self, val): self["ids"] = val # idssrc # ------ @property def idssrc(self): """ Sets the source reference on plot.ly for ids . The 'idssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["idssrc"] @idssrc.setter def idssrc(self, val): self["idssrc"] = val # increasing # ---------- @property def increasing(self): """ The 'increasing' property is an instance of Increasing that may be specified as: - An instance of plotly.graph_objs.ohlc.Increasing - A dict of string/value properties that will be passed to the Increasing constructor Supported dict properties: line plotly.graph_objects.ohlc.increasing.Line instance or dict with compatible properties Returns ------- plotly.graph_objs.ohlc.Increasing """ return self["increasing"] @increasing.setter def increasing(self, val): self["increasing"] = val # legendgroup # ----------- @property def legendgroup(self): """ Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. The 'legendgroup' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["legendgroup"] @legendgroup.setter def legendgroup(self, val): self["legendgroup"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.ohlc.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). Note that this style setting can also be set per direction via `increasing.line.dash` and `decreasing.line.dash`. width [object Object] Note that this style setting can also be set per direction via `increasing.line.width` and `decreasing.line.width`. Returns ------- plotly.graph_objs.ohlc.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # low # --- @property def low(self): """ Sets the low values. The 'low' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["low"] @low.setter def low(self, val): self["low"] = val # lowsrc # ------ @property def lowsrc(self): """ Sets the source reference on plot.ly for low . The 'lowsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["lowsrc"] @lowsrc.setter def lowsrc(self, val): self["lowsrc"] = val # meta # ---- @property def meta(self): """ Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. The 'meta' property accepts values of any type Returns ------- Any|numpy.ndarray """ return self["meta"] @meta.setter def meta(self, val): self["meta"] = val # metasrc # ------- @property def metasrc(self): """ Sets the source reference on plot.ly for meta . The 'metasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["metasrc"] @metasrc.setter def metasrc(self, val): self["metasrc"] = val # name # ---- @property def name(self): """ Sets the trace name. The trace name appear as the legend item and on hover. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the trace. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # open # ---- @property def open(self): """ Sets the open values. The 'open' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["open"] @open.setter def open(self, val): self["open"] = val # opensrc # ------- @property def opensrc(self): """ Sets the source reference on plot.ly for open . The 'opensrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["opensrc"] @opensrc.setter def opensrc(self, val): self["opensrc"] = val # selectedpoints # -------------- @property def selectedpoints(self): """ Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. The 'selectedpoints' property accepts values of any type Returns ------- Any """ return self["selectedpoints"] @selectedpoints.setter def selectedpoints(self, val): self["selectedpoints"] = val # showlegend # ---------- @property def showlegend(self): """ Determines whether or not an item corresponding to this trace is shown in the legend. The 'showlegend' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showlegend"] @showlegend.setter def showlegend(self, val): self["showlegend"] = val # stream # ------ @property def stream(self): """ The 'stream' property is an instance of Stream that may be specified as: - An instance of plotly.graph_objs.ohlc.Stream - A dict of string/value properties that will be passed to the Stream constructor Supported dict properties: maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- plotly.graph_objs.ohlc.Stream """ return self["stream"] @stream.setter def stream(self, val): self["stream"] = val # text # ---- @property def text(self): """ Sets hover text elements associated with each sample point. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to this trace's sample points. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["text"] @text.setter def text(self, val): self["text"] = val # textsrc # ------- @property def textsrc(self): """ Sets the source reference on plot.ly for text . The 'textsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["textsrc"] @textsrc.setter def textsrc(self, val): self["textsrc"] = val # tickwidth # --------- @property def tickwidth(self): """ Sets the width of the open/close tick marks relative to the "x" minimal interval. The 'tickwidth' property is a number and may be specified as: - An int or float in the interval [0, 0.5] Returns ------- int|float """ return self["tickwidth"] @tickwidth.setter def tickwidth(self, val): self["tickwidth"] = val # uid # --- @property def uid(self): """ Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. The 'uid' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["uid"] @uid.setter def uid(self, val): self["uid"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # visible # ------- @property def visible(self): """ Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). The 'visible' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'legendonly'] Returns ------- Any """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # x # - @property def x(self): """ Sets the x coordinates. If absent, linear coordinate will be generated. The 'x' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["x"] @x.setter def x(self, val): self["x"] = val # xaxis # ----- @property def xaxis(self): """ Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. The 'xaxis' property is an identifier of a particular subplot, of type 'x', that may be specified as the string 'x' optionally followed by an integer >= 1 (e.g. 'x', 'x1', 'x2', 'x3', etc.) Returns ------- str """ return self["xaxis"] @xaxis.setter def xaxis(self, val): self["xaxis"] = val # xcalendar # --------- @property def xcalendar(self): """ Sets the calendar system to use with `x` date data. The 'xcalendar' property is an enumeration that may be specified as: - One of the following enumeration values: ['gregorian', 'chinese', 'coptic', 'discworld', 'ethiopian', 'hebrew', 'islamic', 'julian', 'mayan', 'nanakshahi', 'nepali', 'persian', 'jalali', 'taiwan', 'thai', 'ummalqura'] Returns ------- Any """ return self["xcalendar"] @xcalendar.setter def xcalendar(self, val): self["xcalendar"] = val # xsrc # ---- @property def xsrc(self): """ Sets the source reference on plot.ly for x . The 'xsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["xsrc"] @xsrc.setter def xsrc(self, val): self["xsrc"] = val # yaxis # ----- @property def yaxis(self): """ Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. The 'yaxis' property is an identifier of a particular subplot, of type 'y', that may be specified as the string 'y' optionally followed by an integer >= 1 (e.g. 'y', 'y1', 'y2', 'y3', etc.) Returns ------- str """ return self["yaxis"] @yaxis.setter def yaxis(self, val): self["yaxis"] = val # type # ---- @property def type(self): return self._props["type"] # property parent name # -------------------- @property def _parent_path_str(self): return "" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ close Sets the close values. closesrc Sets the source reference on plot.ly for close . customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . decreasing plotly.graph_objects.ohlc.Decreasing instance or dict with compatible properties high Sets the high values. highsrc Sets the source reference on plot.ly for high . hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.ohlc.Hoverlabel instance or dict with compatible properties hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . increasing plotly.graph_objects.ohlc.Increasing instance or dict with compatible properties legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.ohlc.Line instance or dict with compatible properties low Sets the low values. lowsrc Sets the source reference on plot.ly for low . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. open Sets the open values. opensrc Sets the source reference on plot.ly for open . selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.ohlc.Stream instance or dict with compatible properties text Sets hover text elements associated with each sample point. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to this trace's sample points. textsrc Sets the source reference on plot.ly for text . tickwidth Sets the width of the open/close tick marks relative to the "x" minimal interval. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the x coordinates. If absent, linear coordinate will be generated. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. """ def __init__( self, arg=None, close=None, closesrc=None, customdata=None, customdatasrc=None, decreasing=None, high=None, highsrc=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, increasing=None, legendgroup=None, line=None, low=None, lowsrc=None, meta=None, metasrc=None, name=None, opacity=None, open=None, opensrc=None, selectedpoints=None, showlegend=None, stream=None, text=None, textsrc=None, tickwidth=None, uid=None, uirevision=None, visible=None, x=None, xaxis=None, xcalendar=None, xsrc=None, yaxis=None, **kwargs ): """ Construct a new Ohlc object The ohlc (short for Open-High-Low-Close) is a style of financial chart describing open, high, low and close for a given `x` coordinate (most likely time). The tip of the lines represent the `low` and `high` values and the horizontal segments represent the `open` and `close` values. Sample points where the close value is higher (lower) then the open value are called increasing (decreasing). By default, increasing items are drawn in green whereas decreasing are drawn in red. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.Ohlc close Sets the close values. closesrc Sets the source reference on plot.ly for close . customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . decreasing plotly.graph_objects.ohlc.Decreasing instance or dict with compatible properties high Sets the high values. highsrc Sets the source reference on plot.ly for high . hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.ohlc.Hoverlabel instance or dict with compatible properties hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . increasing plotly.graph_objects.ohlc.Increasing instance or dict with compatible properties legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.ohlc.Line instance or dict with compatible properties low Sets the low values. lowsrc Sets the source reference on plot.ly for low . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. open Sets the open values. opensrc Sets the source reference on plot.ly for open . selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.ohlc.Stream instance or dict with compatible properties text Sets hover text elements associated with each sample point. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to this trace's sample points. textsrc Sets the source reference on plot.ly for text . tickwidth Sets the width of the open/close tick marks relative to the "x" minimal interval. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the x coordinates. If absent, linear coordinate will be generated. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. Returns ------- Ohlc """ super(Ohlc, self).__init__("ohlc") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.Ohlc constructor must be a dict or an instance of plotly.graph_objs.Ohlc""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators import ohlc as v_ohlc # Initialize validators # --------------------- self._validators["close"] = v_ohlc.CloseValidator() self._validators["closesrc"] = v_ohlc.ClosesrcValidator() self._validators["customdata"] = v_ohlc.CustomdataValidator() self._validators["customdatasrc"] = v_ohlc.CustomdatasrcValidator() self._validators["decreasing"] = v_ohlc.DecreasingValidator() self._validators["high"] = v_ohlc.HighValidator() self._validators["highsrc"] = v_ohlc.HighsrcValidator() self._validators["hoverinfo"] = v_ohlc.HoverinfoValidator() self._validators["hoverinfosrc"] = v_ohlc.HoverinfosrcValidator() self._validators["hoverlabel"] = v_ohlc.HoverlabelValidator() self._validators["hovertext"] = v_ohlc.HovertextValidator() self._validators["hovertextsrc"] = v_ohlc.HovertextsrcValidator() self._validators["ids"] = v_ohlc.IdsValidator() self._validators["idssrc"] = v_ohlc.IdssrcValidator() self._validators["increasing"] = v_ohlc.IncreasingValidator() self._validators["legendgroup"] = v_ohlc.LegendgroupValidator() self._validators["line"] = v_ohlc.LineValidator() self._validators["low"] = v_ohlc.LowValidator() self._validators["lowsrc"] = v_ohlc.LowsrcValidator() self._validators["meta"] = v_ohlc.MetaValidator() self._validators["metasrc"] = v_ohlc.MetasrcValidator() self._validators["name"] = v_ohlc.NameValidator() self._validators["opacity"] = v_ohlc.OpacityValidator() self._validators["open"] = v_ohlc.OpenValidator() self._validators["opensrc"] = v_ohlc.OpensrcValidator() self._validators["selectedpoints"] = v_ohlc.SelectedpointsValidator() self._validators["showlegend"] = v_ohlc.ShowlegendValidator() self._validators["stream"] = v_ohlc.StreamValidator() self._validators["text"] = v_ohlc.TextValidator() self._validators["textsrc"] = v_ohlc.TextsrcValidator() self._validators["tickwidth"] = v_ohlc.TickwidthValidator() self._validators["uid"] = v_ohlc.UidValidator() self._validators["uirevision"] = v_ohlc.UirevisionValidator() self._validators["visible"] = v_ohlc.VisibleValidator() self._validators["x"] = v_ohlc.XValidator() self._validators["xaxis"] = v_ohlc.XAxisValidator() self._validators["xcalendar"] = v_ohlc.XcalendarValidator() self._validators["xsrc"] = v_ohlc.XsrcValidator() self._validators["yaxis"] = v_ohlc.YAxisValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("close", None) self["close"] = close if close is not None else _v _v = arg.pop("closesrc", None) self["closesrc"] = closesrc if closesrc is not None else _v _v = arg.pop("customdata", None) self["customdata"] = customdata if customdata is not None else _v _v = arg.pop("customdatasrc", None) self["customdatasrc"] = customdatasrc if customdatasrc is not None else _v _v = arg.pop("decreasing", None) self["decreasing"] = decreasing if decreasing is not None else _v _v = arg.pop("high", None) self["high"] = high if high is not None else _v _v = arg.pop("highsrc", None) self["highsrc"] = highsrc if highsrc is not None else _v _v = arg.pop("hoverinfo", None) self["hoverinfo"] = hoverinfo if hoverinfo is not None else _v _v = arg.pop("hoverinfosrc", None) self["hoverinfosrc"] = hoverinfosrc if hoverinfosrc is not None else _v _v = arg.pop("hoverlabel", None) self["hoverlabel"] = hoverlabel if hoverlabel is not None else _v _v = arg.pop("hovertext", None) self["hovertext"] = hovertext if hovertext is not None else _v _v = arg.pop("hovertextsrc", None) self["hovertextsrc"] = hovertextsrc if hovertextsrc is not None else _v _v = arg.pop("ids", None) self["ids"] = ids if ids is not None else _v _v = arg.pop("idssrc", None) self["idssrc"] = idssrc if idssrc is not None else _v _v = arg.pop("increasing", None) self["increasing"] = increasing if increasing is not None else _v _v = arg.pop("legendgroup", None) self["legendgroup"] = legendgroup if legendgroup is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v _v = arg.pop("low", None) self["low"] = low if low is not None else _v _v = arg.pop("lowsrc", None) self["lowsrc"] = lowsrc if lowsrc is not None else _v _v = arg.pop("meta", None) self["meta"] = meta if meta is not None else _v _v = arg.pop("metasrc", None) self["metasrc"] = metasrc if metasrc is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("open", None) self["open"] = open if open is not None else _v _v = arg.pop("opensrc", None) self["opensrc"] = opensrc if opensrc is not None else _v _v = arg.pop("selectedpoints", None) self["selectedpoints"] = selectedpoints if selectedpoints is not None else _v _v = arg.pop("showlegend", None) self["showlegend"] = showlegend if showlegend is not None else _v _v = arg.pop("stream", None) self["stream"] = stream if stream is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v _v = arg.pop("textsrc", None) self["textsrc"] = textsrc if textsrc is not None else _v _v = arg.pop("tickwidth", None) self["tickwidth"] = tickwidth if tickwidth is not None else _v _v = arg.pop("uid", None) self["uid"] = uid if uid is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xaxis", None) self["xaxis"] = xaxis if xaxis is not None else _v _v = arg.pop("xcalendar", None) self["xcalendar"] = xcalendar if xcalendar is not None else _v _v = arg.pop("xsrc", None) self["xsrc"] = xsrc if xsrc is not None else _v _v = arg.pop("yaxis", None) self["yaxis"] = yaxis if yaxis is not None else _v # Read-only literals # ------------------ from _plotly_utils.basevalidators import LiteralValidator self._props["type"] = "ohlc" self._validators["type"] = LiteralValidator( plotly_name="type", parent_name="ohlc", val="ohlc" ) arg.pop("type", None) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceType as _BaseTraceType import copy as _copy class Mesh3d(_BaseTraceType): # alphahull # --------- @property def alphahull(self): """ Determines how the mesh surface triangles are derived from the set of vertices (points) represented by the `x`, `y` and `z` arrays, if the `i`, `j`, `k` arrays are not supplied. For general use of `mesh3d` it is preferred that `i`, `j`, `k` are supplied. If "-1", Delaunay triangulation is used, which is mainly suitable if the mesh is a single, more or less layer surface that is perpendicular to `delaunayaxis`. In case the `delaunayaxis` intersects the mesh surface at more than one point it will result triangles that are very long in the dimension of `delaunayaxis`. If ">0", the alpha-shape algorithm is used. In this case, the positive `alphahull` value signals the use of the alpha-shape algorithm, _and_ its value acts as the parameter for the mesh fitting. If 0, the convex-hull algorithm is used. It is suitable for convex bodies or if the intention is to enclose the `x`, `y` and `z` point set into a convex hull. The 'alphahull' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["alphahull"] @alphahull.setter def alphahull(self, val): self["alphahull"] = val # autocolorscale # -------------- @property def autocolorscale(self): """ Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. The 'autocolorscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocolorscale"] @autocolorscale.setter def autocolorscale(self, val): self["autocolorscale"] = val # cauto # ----- @property def cauto(self): """ Determines whether or not the color domain is computed with respect to the input data (here `intensity`) or the bounds set in `cmin` and `cmax` Defaults to `false` when `cmin` and `cmax` are set by the user. The 'cauto' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["cauto"] @cauto.setter def cauto(self, val): self["cauto"] = val # cmax # ---- @property def cmax(self): """ Sets the upper bound of the color domain. Value should have the same units as `intensity` and if set, `cmin` must be set as well. The 'cmax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmax"] @cmax.setter def cmax(self, val): self["cmax"] = val # cmid # ---- @property def cmid(self): """ Sets the mid-point of the color domain by scaling `cmin` and/or `cmax` to be equidistant to this point. Value should have the same units as `intensity`. Has no effect when `cauto` is `false`. The 'cmid' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmid"] @cmid.setter def cmid(self, val): self["cmid"] = val # cmin # ---- @property def cmin(self): """ Sets the lower bound of the color domain. Value should have the same units as `intensity` and if set, `cmax` must be set as well. The 'cmin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmin"] @cmin.setter def cmin(self, val): self["cmin"] = val # color # ----- @property def color(self): """ Sets the color of the whole mesh The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A number that will be interpreted as a color according to mesh3d.colorscale Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # coloraxis # --------- @property def coloraxis(self): """ Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. The 'coloraxis' property is an identifier of a particular subplot, of type 'coloraxis', that may be specified as the string 'coloraxis' optionally followed by an integer >= 1 (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) Returns ------- str """ return self["coloraxis"] @coloraxis.setter def coloraxis(self, val): self["coloraxis"] = val # colorbar # -------- @property def colorbar(self): """ The 'colorbar' property is an instance of ColorBar that may be specified as: - An instance of plotly.graph_objs.mesh3d.ColorBar - A dict of string/value properties that will be passed to the ColorBar constructor Supported dict properties: bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.mesh3d.colorbar .Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.mesh3d.colorbar.tickformatstopdefaults), sets the default property values to use for elements of mesh3d.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.mesh3d.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use mesh3d.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use mesh3d.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- plotly.graph_objs.mesh3d.ColorBar """ return self["colorbar"] @colorbar.setter def colorbar(self, val): self["colorbar"] = val # colorscale # ---------- @property def colorscale(self): """ Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`cmin` and `cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,Earth,Electric,Vi ridis,Cividis. The 'colorscale' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # contour # ------- @property def contour(self): """ The 'contour' property is an instance of Contour that may be specified as: - An instance of plotly.graph_objs.mesh3d.Contour - A dict of string/value properties that will be passed to the Contour constructor Supported dict properties: color Sets the color of the contour lines. show Sets whether or not dynamic contours are shown on hover width Sets the width of the contour lines. Returns ------- plotly.graph_objs.mesh3d.Contour """ return self["contour"] @contour.setter def contour(self, val): self["contour"] = val # customdata # ---------- @property def customdata(self): """ Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements The 'customdata' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["customdata"] @customdata.setter def customdata(self, val): self["customdata"] = val # customdatasrc # ------------- @property def customdatasrc(self): """ Sets the source reference on plot.ly for customdata . The 'customdatasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["customdatasrc"] @customdatasrc.setter def customdatasrc(self, val): self["customdatasrc"] = val # delaunayaxis # ------------ @property def delaunayaxis(self): """ Sets the Delaunay axis, which is the axis that is perpendicular to the surface of the Delaunay triangulation. It has an effect if `i`, `j`, `k` are not provided and `alphahull` is set to indicate Delaunay triangulation. The 'delaunayaxis' property is an enumeration that may be specified as: - One of the following enumeration values: ['x', 'y', 'z'] Returns ------- Any """ return self["delaunayaxis"] @delaunayaxis.setter def delaunayaxis(self, val): self["delaunayaxis"] = val # facecolor # --------- @property def facecolor(self): """ Sets the color of each face Overrides "color" and "vertexcolor". The 'facecolor' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["facecolor"] @facecolor.setter def facecolor(self, val): self["facecolor"] = val # facecolorsrc # ------------ @property def facecolorsrc(self): """ Sets the source reference on plot.ly for facecolor . The 'facecolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["facecolorsrc"] @facecolorsrc.setter def facecolorsrc(self, val): self["facecolorsrc"] = val # flatshading # ----------- @property def flatshading(self): """ Determines whether or not normal smoothing is applied to the meshes, creating meshes with an angular, low-poly look via flat reflections. The 'flatshading' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["flatshading"] @flatshading.setter def flatshading(self, val): self["flatshading"] = val # hoverinfo # --------- @property def hoverinfo(self): """ Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. The 'hoverinfo' property is a flaglist and may be specified as a string containing: - Any combination of ['x', 'y', 'z', 'text', 'name'] joined with '+' characters (e.g. 'x+y') OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') - A list or array of the above Returns ------- Any|numpy.ndarray """ return self["hoverinfo"] @hoverinfo.setter def hoverinfo(self, val): self["hoverinfo"] = val # hoverinfosrc # ------------ @property def hoverinfosrc(self): """ Sets the source reference on plot.ly for hoverinfo . The 'hoverinfosrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hoverinfosrc"] @hoverinfosrc.setter def hoverinfosrc(self, val): self["hoverinfosrc"] = val # hoverlabel # ---------- @property def hoverlabel(self): """ The 'hoverlabel' property is an instance of Hoverlabel that may be specified as: - An instance of plotly.graph_objs.mesh3d.Hoverlabel - A dict of string/value properties that will be passed to the Hoverlabel constructor Supported dict properties: align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- plotly.graph_objs.mesh3d.Hoverlabel """ return self["hoverlabel"] @hoverlabel.setter def hoverlabel(self, val): self["hoverlabel"] = val # hovertemplate # ------------- @property def hovertemplate(self): """ Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event- data. Additionally, every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. The 'hovertemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertemplate"] @hovertemplate.setter def hovertemplate(self, val): self["hovertemplate"] = val # hovertemplatesrc # ---------------- @property def hovertemplatesrc(self): """ Sets the source reference on plot.ly for hovertemplate . The 'hovertemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertemplatesrc"] @hovertemplatesrc.setter def hovertemplatesrc(self, val): self["hovertemplatesrc"] = val # hovertext # --------- @property def hovertext(self): """ Same as `text`. The 'hovertext' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertext"] @hovertext.setter def hovertext(self, val): self["hovertext"] = val # hovertextsrc # ------------ @property def hovertextsrc(self): """ Sets the source reference on plot.ly for hovertext . The 'hovertextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertextsrc"] @hovertextsrc.setter def hovertextsrc(self, val): self["hovertextsrc"] = val # i # - @property def i(self): """ A vector of vertex indices, i.e. integer values between 0 and the length of the vertex vectors, representing the "first" vertex of a triangle. For example, `{i[m], j[m], k[m]}` together represent face m (triangle m) in the mesh, where `i[m] = n` points to the triplet `{x[n], y[n], z[n]}` in the vertex arrays. Therefore, each element in `i` represents a point in space, which is the first vertex of a triangle. The 'i' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["i"] @i.setter def i(self, val): self["i"] = val # ids # --- @property def ids(self): """ Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. The 'ids' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ids"] @ids.setter def ids(self, val): self["ids"] = val # idssrc # ------ @property def idssrc(self): """ Sets the source reference on plot.ly for ids . The 'idssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["idssrc"] @idssrc.setter def idssrc(self, val): self["idssrc"] = val # intensity # --------- @property def intensity(self): """ Sets the vertex intensity values, used for plotting fields on meshes The 'intensity' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["intensity"] @intensity.setter def intensity(self, val): self["intensity"] = val # intensitysrc # ------------ @property def intensitysrc(self): """ Sets the source reference on plot.ly for intensity . The 'intensitysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["intensitysrc"] @intensitysrc.setter def intensitysrc(self, val): self["intensitysrc"] = val # isrc # ---- @property def isrc(self): """ Sets the source reference on plot.ly for i . The 'isrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["isrc"] @isrc.setter def isrc(self, val): self["isrc"] = val # j # - @property def j(self): """ A vector of vertex indices, i.e. integer values between 0 and the length of the vertex vectors, representing the "second" vertex of a triangle. For example, `{i[m], j[m], k[m]}` together represent face m (triangle m) in the mesh, where `j[m] = n` points to the triplet `{x[n], y[n], z[n]}` in the vertex arrays. Therefore, each element in `j` represents a point in space, which is the second vertex of a triangle. The 'j' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["j"] @j.setter def j(self, val): self["j"] = val # jsrc # ---- @property def jsrc(self): """ Sets the source reference on plot.ly for j . The 'jsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["jsrc"] @jsrc.setter def jsrc(self, val): self["jsrc"] = val # k # - @property def k(self): """ A vector of vertex indices, i.e. integer values between 0 and the length of the vertex vectors, representing the "third" vertex of a triangle. For example, `{i[m], j[m], k[m]}` together represent face m (triangle m) in the mesh, where `k[m] = n` points to the triplet `{x[n], y[n], z[n]}` in the vertex arrays. Therefore, each element in `k` represents a point in space, which is the third vertex of a triangle. The 'k' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["k"] @k.setter def k(self, val): self["k"] = val # ksrc # ---- @property def ksrc(self): """ Sets the source reference on plot.ly for k . The 'ksrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ksrc"] @ksrc.setter def ksrc(self, val): self["ksrc"] = val # lighting # -------- @property def lighting(self): """ The 'lighting' property is an instance of Lighting that may be specified as: - An instance of plotly.graph_objs.mesh3d.Lighting - A dict of string/value properties that will be passed to the Lighting constructor Supported dict properties: ambient Ambient light increases overall color visibility but can wash out the image. diffuse Represents the extent that incident rays are reflected in a range of angles. facenormalsepsilon Epsilon for face normals calculation avoids math issues arising from degenerate geometry. fresnel Represents the reflectance as a dependency of the viewing angle; e.g. paper is reflective when viewing it from the edge of the paper (almost 90 degrees), causing shine. roughness Alters specular reflection; the rougher the surface, the wider and less contrasty the shine. specular Represents the level that incident rays are reflected in a single direction, causing shine. vertexnormalsepsilon Epsilon for vertex normals calculation avoids math issues arising from degenerate geometry. Returns ------- plotly.graph_objs.mesh3d.Lighting """ return self["lighting"] @lighting.setter def lighting(self, val): self["lighting"] = val # lightposition # ------------- @property def lightposition(self): """ The 'lightposition' property is an instance of Lightposition that may be specified as: - An instance of plotly.graph_objs.mesh3d.Lightposition - A dict of string/value properties that will be passed to the Lightposition constructor Supported dict properties: x Numeric vector, representing the X coordinate for each vertex. y Numeric vector, representing the Y coordinate for each vertex. z Numeric vector, representing the Z coordinate for each vertex. Returns ------- plotly.graph_objs.mesh3d.Lightposition """ return self["lightposition"] @lightposition.setter def lightposition(self, val): self["lightposition"] = val # meta # ---- @property def meta(self): """ Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. The 'meta' property accepts values of any type Returns ------- Any|numpy.ndarray """ return self["meta"] @meta.setter def meta(self, val): self["meta"] = val # metasrc # ------- @property def metasrc(self): """ Sets the source reference on plot.ly for meta . The 'metasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["metasrc"] @metasrc.setter def metasrc(self, val): self["metasrc"] = val # name # ---- @property def name(self): """ Sets the trace name. The trace name appear as the legend item and on hover. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the surface. Please note that in the case of using high `opacity` values for example a value greater than or equal to 0.5 on two surfaces (and 0.25 with four surfaces), an overlay of multiple transparent surfaces may not perfectly be sorted in depth by the webgl API. This behavior may be improved in the near future and is subject to change. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # reversescale # ------------ @property def reversescale(self): """ Reverses the color mapping if true. If true, `cmin` will correspond to the last color in the array and `cmax` will correspond to the first color. The 'reversescale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["reversescale"] @reversescale.setter def reversescale(self, val): self["reversescale"] = val # scene # ----- @property def scene(self): """ Sets a reference between this trace's 3D coordinate system and a 3D scene. If "scene" (the default value), the (x,y,z) coordinates refer to `layout.scene`. If "scene2", the (x,y,z) coordinates refer to `layout.scene2`, and so on. The 'scene' property is an identifier of a particular subplot, of type 'scene', that may be specified as the string 'scene' optionally followed by an integer >= 1 (e.g. 'scene', 'scene1', 'scene2', 'scene3', etc.) Returns ------- str """ return self["scene"] @scene.setter def scene(self, val): self["scene"] = val # showscale # --------- @property def showscale(self): """ Determines whether or not a colorbar is displayed for this trace. The 'showscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showscale"] @showscale.setter def showscale(self, val): self["showscale"] = val # stream # ------ @property def stream(self): """ The 'stream' property is an instance of Stream that may be specified as: - An instance of plotly.graph_objs.mesh3d.Stream - A dict of string/value properties that will be passed to the Stream constructor Supported dict properties: maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- plotly.graph_objs.mesh3d.Stream """ return self["stream"] @stream.setter def stream(self, val): self["stream"] = val # text # ---- @property def text(self): """ Sets the text elements associated with the vertices. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["text"] @text.setter def text(self, val): self["text"] = val # textsrc # ------- @property def textsrc(self): """ Sets the source reference on plot.ly for text . The 'textsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["textsrc"] @textsrc.setter def textsrc(self, val): self["textsrc"] = val # uid # --- @property def uid(self): """ Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. The 'uid' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["uid"] @uid.setter def uid(self, val): self["uid"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # vertexcolor # ----------- @property def vertexcolor(self): """ Sets the color of each vertex Overrides "color". While Red, green and blue colors are in the range of 0 and 255; in the case of having vertex color data in RGBA format, the alpha color should be normalized to be between 0 and 1. The 'vertexcolor' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["vertexcolor"] @vertexcolor.setter def vertexcolor(self, val): self["vertexcolor"] = val # vertexcolorsrc # -------------- @property def vertexcolorsrc(self): """ Sets the source reference on plot.ly for vertexcolor . The 'vertexcolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["vertexcolorsrc"] @vertexcolorsrc.setter def vertexcolorsrc(self, val): self["vertexcolorsrc"] = val # visible # ------- @property def visible(self): """ Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). The 'visible' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'legendonly'] Returns ------- Any """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # x # - @property def x(self): """ Sets the X coordinates of the vertices. The nth element of vectors `x`, `y` and `z` jointly represent the X, Y and Z coordinates of the nth vertex. The 'x' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["x"] @x.setter def x(self, val): self["x"] = val # xcalendar # --------- @property def xcalendar(self): """ Sets the calendar system to use with `x` date data. The 'xcalendar' property is an enumeration that may be specified as: - One of the following enumeration values: ['gregorian', 'chinese', 'coptic', 'discworld', 'ethiopian', 'hebrew', 'islamic', 'julian', 'mayan', 'nanakshahi', 'nepali', 'persian', 'jalali', 'taiwan', 'thai', 'ummalqura'] Returns ------- Any """ return self["xcalendar"] @xcalendar.setter def xcalendar(self, val): self["xcalendar"] = val # xsrc # ---- @property def xsrc(self): """ Sets the source reference on plot.ly for x . The 'xsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["xsrc"] @xsrc.setter def xsrc(self, val): self["xsrc"] = val # y # - @property def y(self): """ Sets the Y coordinates of the vertices. The nth element of vectors `x`, `y` and `z` jointly represent the X, Y and Z coordinates of the nth vertex. The 'y' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["y"] @y.setter def y(self, val): self["y"] = val # ycalendar # --------- @property def ycalendar(self): """ Sets the calendar system to use with `y` date data. The 'ycalendar' property is an enumeration that may be specified as: - One of the following enumeration values: ['gregorian', 'chinese', 'coptic', 'discworld', 'ethiopian', 'hebrew', 'islamic', 'julian', 'mayan', 'nanakshahi', 'nepali', 'persian', 'jalali', 'taiwan', 'thai', 'ummalqura'] Returns ------- Any """ return self["ycalendar"] @ycalendar.setter def ycalendar(self, val): self["ycalendar"] = val # ysrc # ---- @property def ysrc(self): """ Sets the source reference on plot.ly for y . The 'ysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ysrc"] @ysrc.setter def ysrc(self, val): self["ysrc"] = val # z # - @property def z(self): """ Sets the Z coordinates of the vertices. The nth element of vectors `x`, `y` and `z` jointly represent the X, Y and Z coordinates of the nth vertex. The 'z' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["z"] @z.setter def z(self, val): self["z"] = val # zcalendar # --------- @property def zcalendar(self): """ Sets the calendar system to use with `z` date data. The 'zcalendar' property is an enumeration that may be specified as: - One of the following enumeration values: ['gregorian', 'chinese', 'coptic', 'discworld', 'ethiopian', 'hebrew', 'islamic', 'julian', 'mayan', 'nanakshahi', 'nepali', 'persian', 'jalali', 'taiwan', 'thai', 'ummalqura'] Returns ------- Any """ return self["zcalendar"] @zcalendar.setter def zcalendar(self, val): self["zcalendar"] = val # zsrc # ---- @property def zsrc(self): """ Sets the source reference on plot.ly for z . The 'zsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["zsrc"] @zsrc.setter def zsrc(self, val): self["zsrc"] = val # type # ---- @property def type(self): return self._props["type"] # property parent name # -------------------- @property def _parent_path_str(self): return "" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ alphahull Determines how the mesh surface triangles are derived from the set of vertices (points) represented by the `x`, `y` and `z` arrays, if the `i`, `j`, `k` arrays are not supplied. For general use of `mesh3d` it is preferred that `i`, `j`, `k` are supplied. If "-1", Delaunay triangulation is used, which is mainly suitable if the mesh is a single, more or less layer surface that is perpendicular to `delaunayaxis`. In case the `delaunayaxis` intersects the mesh surface at more than one point it will result triangles that are very long in the dimension of `delaunayaxis`. If ">0", the alpha-shape algorithm is used. In this case, the positive `alphahull` value signals the use of the alpha-shape algorithm, _and_ its value acts as the parameter for the mesh fitting. If 0, the convex-hull algorithm is used. It is suitable for convex bodies or if the intention is to enclose the `x`, `y` and `z` point set into a convex hull. autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here `intensity`) or the bounds set in `cmin` and `cmax` Defaults to `false` when `cmin` and `cmax` are set by the user. cmax Sets the upper bound of the color domain. Value should have the same units as `intensity` and if set, `cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `cmin` and/or `cmax` to be equidistant to this point. Value should have the same units as `intensity`. Has no effect when `cauto` is `false`. cmin Sets the lower bound of the color domain. Value should have the same units as `intensity` and if set, `cmax` must be set as well. color Sets the color of the whole mesh coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.mesh3d.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`cmin` and `cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. contour plotly.graph_objects.mesh3d.Contour instance or dict with compatible properties customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . delaunayaxis Sets the Delaunay axis, which is the axis that is perpendicular to the surface of the Delaunay triangulation. It has an effect if `i`, `j`, `k` are not provided and `alphahull` is set to indicate Delaunay triangulation. facecolor Sets the color of each face Overrides "color" and "vertexcolor". facecolorsrc Sets the source reference on plot.ly for facecolor . flatshading Determines whether or not normal smoothing is applied to the meshes, creating meshes with an angular, low- poly look via flat reflections. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.mesh3d.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . i A vector of vertex indices, i.e. integer values between 0 and the length of the vertex vectors, representing the "first" vertex of a triangle. For example, `{i[m], j[m], k[m]}` together represent face m (triangle m) in the mesh, where `i[m] = n` points to the triplet `{x[n], y[n], z[n]}` in the vertex arrays. Therefore, each element in `i` represents a point in space, which is the first vertex of a triangle. ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . intensity Sets the vertex intensity values, used for plotting fields on meshes intensitysrc Sets the source reference on plot.ly for intensity . isrc Sets the source reference on plot.ly for i . j A vector of vertex indices, i.e. integer values between 0 and the length of the vertex vectors, representing the "second" vertex of a triangle. For example, `{i[m], j[m], k[m]}` together represent face m (triangle m) in the mesh, where `j[m] = n` points to the triplet `{x[n], y[n], z[n]}` in the vertex arrays. Therefore, each element in `j` represents a point in space, which is the second vertex of a triangle. jsrc Sets the source reference on plot.ly for j . k A vector of vertex indices, i.e. integer values between 0 and the length of the vertex vectors, representing the "third" vertex of a triangle. For example, `{i[m], j[m], k[m]}` together represent face m (triangle m) in the mesh, where `k[m] = n` points to the triplet `{x[n], y[n], z[n]}` in the vertex arrays. Therefore, each element in `k` represents a point in space, which is the third vertex of a triangle. ksrc Sets the source reference on plot.ly for k . lighting plotly.graph_objects.mesh3d.Lighting instance or dict with compatible properties lightposition plotly.graph_objects.mesh3d.Lightposition instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the surface. Please note that in the case of using high `opacity` values for example a value greater than or equal to 0.5 on two surfaces (and 0.25 with four surfaces), an overlay of multiple transparent surfaces may not perfectly be sorted in depth by the webgl API. This behavior may be improved in the near future and is subject to change. reversescale Reverses the color mapping if true. If true, `cmin` will correspond to the last color in the array and `cmax` will correspond to the first color. scene Sets a reference between this trace's 3D coordinate system and a 3D scene. If "scene" (the default value), the (x,y,z) coordinates refer to `layout.scene`. If "scene2", the (x,y,z) coordinates refer to `layout.scene2`, and so on. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.mesh3d.Stream instance or dict with compatible properties text Sets the text elements associated with the vertices. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. vertexcolor Sets the color of each vertex Overrides "color". While Red, green and blue colors are in the range of 0 and 255; in the case of having vertex color data in RGBA format, the alpha color should be normalized to be between 0 and 1. vertexcolorsrc Sets the source reference on plot.ly for vertexcolor . visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the X coordinates of the vertices. The nth element of vectors `x`, `y` and `z` jointly represent the X, Y and Z coordinates of the nth vertex. xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . y Sets the Y coordinates of the vertices. The nth element of vectors `x`, `y` and `z` jointly represent the X, Y and Z coordinates of the nth vertex. ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . z Sets the Z coordinates of the vertices. The nth element of vectors `x`, `y` and `z` jointly represent the X, Y and Z coordinates of the nth vertex. zcalendar Sets the calendar system to use with `z` date data. zsrc Sets the source reference on plot.ly for z . """ def __init__( self, arg=None, alphahull=None, autocolorscale=None, cauto=None, cmax=None, cmid=None, cmin=None, color=None, coloraxis=None, colorbar=None, colorscale=None, contour=None, customdata=None, customdatasrc=None, delaunayaxis=None, facecolor=None, facecolorsrc=None, flatshading=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, i=None, ids=None, idssrc=None, intensity=None, intensitysrc=None, isrc=None, j=None, jsrc=None, k=None, ksrc=None, lighting=None, lightposition=None, meta=None, metasrc=None, name=None, opacity=None, reversescale=None, scene=None, showscale=None, stream=None, text=None, textsrc=None, uid=None, uirevision=None, vertexcolor=None, vertexcolorsrc=None, visible=None, x=None, xcalendar=None, xsrc=None, y=None, ycalendar=None, ysrc=None, z=None, zcalendar=None, zsrc=None, **kwargs ): """ Construct a new Mesh3d object Draws sets of triangles with coordinates given by three 1-dimensional arrays in `x`, `y`, `z` and (1) a sets of `i`, `j`, `k` indices (2) Delaunay triangulation or (3) the Alpha- shape algorithm or (4) the Convex-hull algorithm Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.Mesh3d alphahull Determines how the mesh surface triangles are derived from the set of vertices (points) represented by the `x`, `y` and `z` arrays, if the `i`, `j`, `k` arrays are not supplied. For general use of `mesh3d` it is preferred that `i`, `j`, `k` are supplied. If "-1", Delaunay triangulation is used, which is mainly suitable if the mesh is a single, more or less layer surface that is perpendicular to `delaunayaxis`. In case the `delaunayaxis` intersects the mesh surface at more than one point it will result triangles that are very long in the dimension of `delaunayaxis`. If ">0", the alpha-shape algorithm is used. In this case, the positive `alphahull` value signals the use of the alpha-shape algorithm, _and_ its value acts as the parameter for the mesh fitting. If 0, the convex-hull algorithm is used. It is suitable for convex bodies or if the intention is to enclose the `x`, `y` and `z` point set into a convex hull. autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here `intensity`) or the bounds set in `cmin` and `cmax` Defaults to `false` when `cmin` and `cmax` are set by the user. cmax Sets the upper bound of the color domain. Value should have the same units as `intensity` and if set, `cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `cmin` and/or `cmax` to be equidistant to this point. Value should have the same units as `intensity`. Has no effect when `cauto` is `false`. cmin Sets the lower bound of the color domain. Value should have the same units as `intensity` and if set, `cmax` must be set as well. color Sets the color of the whole mesh coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.mesh3d.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`cmin` and `cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. contour plotly.graph_objects.mesh3d.Contour instance or dict with compatible properties customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . delaunayaxis Sets the Delaunay axis, which is the axis that is perpendicular to the surface of the Delaunay triangulation. It has an effect if `i`, `j`, `k` are not provided and `alphahull` is set to indicate Delaunay triangulation. facecolor Sets the color of each face Overrides "color" and "vertexcolor". facecolorsrc Sets the source reference on plot.ly for facecolor . flatshading Determines whether or not normal smoothing is applied to the meshes, creating meshes with an angular, low- poly look via flat reflections. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.mesh3d.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . i A vector of vertex indices, i.e. integer values between 0 and the length of the vertex vectors, representing the "first" vertex of a triangle. For example, `{i[m], j[m], k[m]}` together represent face m (triangle m) in the mesh, where `i[m] = n` points to the triplet `{x[n], y[n], z[n]}` in the vertex arrays. Therefore, each element in `i` represents a point in space, which is the first vertex of a triangle. ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . intensity Sets the vertex intensity values, used for plotting fields on meshes intensitysrc Sets the source reference on plot.ly for intensity . isrc Sets the source reference on plot.ly for i . j A vector of vertex indices, i.e. integer values between 0 and the length of the vertex vectors, representing the "second" vertex of a triangle. For example, `{i[m], j[m], k[m]}` together represent face m (triangle m) in the mesh, where `j[m] = n` points to the triplet `{x[n], y[n], z[n]}` in the vertex arrays. Therefore, each element in `j` represents a point in space, which is the second vertex of a triangle. jsrc Sets the source reference on plot.ly for j . k A vector of vertex indices, i.e. integer values between 0 and the length of the vertex vectors, representing the "third" vertex of a triangle. For example, `{i[m], j[m], k[m]}` together represent face m (triangle m) in the mesh, where `k[m] = n` points to the triplet `{x[n], y[n], z[n]}` in the vertex arrays. Therefore, each element in `k` represents a point in space, which is the third vertex of a triangle. ksrc Sets the source reference on plot.ly for k . lighting plotly.graph_objects.mesh3d.Lighting instance or dict with compatible properties lightposition plotly.graph_objects.mesh3d.Lightposition instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the surface. Please note that in the case of using high `opacity` values for example a value greater than or equal to 0.5 on two surfaces (and 0.25 with four surfaces), an overlay of multiple transparent surfaces may not perfectly be sorted in depth by the webgl API. This behavior may be improved in the near future and is subject to change. reversescale Reverses the color mapping if true. If true, `cmin` will correspond to the last color in the array and `cmax` will correspond to the first color. scene Sets a reference between this trace's 3D coordinate system and a 3D scene. If "scene" (the default value), the (x,y,z) coordinates refer to `layout.scene`. If "scene2", the (x,y,z) coordinates refer to `layout.scene2`, and so on. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.mesh3d.Stream instance or dict with compatible properties text Sets the text elements associated with the vertices. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. vertexcolor Sets the color of each vertex Overrides "color". While Red, green and blue colors are in the range of 0 and 255; in the case of having vertex color data in RGBA format, the alpha color should be normalized to be between 0 and 1. vertexcolorsrc Sets the source reference on plot.ly for vertexcolor . visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the X coordinates of the vertices. The nth element of vectors `x`, `y` and `z` jointly represent the X, Y and Z coordinates of the nth vertex. xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . y Sets the Y coordinates of the vertices. The nth element of vectors `x`, `y` and `z` jointly represent the X, Y and Z coordinates of the nth vertex. ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . z Sets the Z coordinates of the vertices. The nth element of vectors `x`, `y` and `z` jointly represent the X, Y and Z coordinates of the nth vertex. zcalendar Sets the calendar system to use with `z` date data. zsrc Sets the source reference on plot.ly for z . Returns ------- Mesh3d """ super(Mesh3d, self).__init__("mesh3d") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.Mesh3d constructor must be a dict or an instance of plotly.graph_objs.Mesh3d""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators import mesh3d as v_mesh3d # Initialize validators # --------------------- self._validators["alphahull"] = v_mesh3d.AlphahullValidator() self._validators["autocolorscale"] = v_mesh3d.AutocolorscaleValidator() self._validators["cauto"] = v_mesh3d.CautoValidator() self._validators["cmax"] = v_mesh3d.CmaxValidator() self._validators["cmid"] = v_mesh3d.CmidValidator() self._validators["cmin"] = v_mesh3d.CminValidator() self._validators["color"] = v_mesh3d.ColorValidator() self._validators["coloraxis"] = v_mesh3d.ColoraxisValidator() self._validators["colorbar"] = v_mesh3d.ColorBarValidator() self._validators["colorscale"] = v_mesh3d.ColorscaleValidator() self._validators["contour"] = v_mesh3d.ContourValidator() self._validators["customdata"] = v_mesh3d.CustomdataValidator() self._validators["customdatasrc"] = v_mesh3d.CustomdatasrcValidator() self._validators["delaunayaxis"] = v_mesh3d.DelaunayaxisValidator() self._validators["facecolor"] = v_mesh3d.FacecolorValidator() self._validators["facecolorsrc"] = v_mesh3d.FacecolorsrcValidator() self._validators["flatshading"] = v_mesh3d.FlatshadingValidator() self._validators["hoverinfo"] = v_mesh3d.HoverinfoValidator() self._validators["hoverinfosrc"] = v_mesh3d.HoverinfosrcValidator() self._validators["hoverlabel"] = v_mesh3d.HoverlabelValidator() self._validators["hovertemplate"] = v_mesh3d.HovertemplateValidator() self._validators["hovertemplatesrc"] = v_mesh3d.HovertemplatesrcValidator() self._validators["hovertext"] = v_mesh3d.HovertextValidator() self._validators["hovertextsrc"] = v_mesh3d.HovertextsrcValidator() self._validators["i"] = v_mesh3d.IValidator() self._validators["ids"] = v_mesh3d.IdsValidator() self._validators["idssrc"] = v_mesh3d.IdssrcValidator() self._validators["intensity"] = v_mesh3d.IntensityValidator() self._validators["intensitysrc"] = v_mesh3d.IntensitysrcValidator() self._validators["isrc"] = v_mesh3d.IsrcValidator() self._validators["j"] = v_mesh3d.JValidator() self._validators["jsrc"] = v_mesh3d.JsrcValidator() self._validators["k"] = v_mesh3d.KValidator() self._validators["ksrc"] = v_mesh3d.KsrcValidator() self._validators["lighting"] = v_mesh3d.LightingValidator() self._validators["lightposition"] = v_mesh3d.LightpositionValidator() self._validators["meta"] = v_mesh3d.MetaValidator() self._validators["metasrc"] = v_mesh3d.MetasrcValidator() self._validators["name"] = v_mesh3d.NameValidator() self._validators["opacity"] = v_mesh3d.OpacityValidator() self._validators["reversescale"] = v_mesh3d.ReversescaleValidator() self._validators["scene"] = v_mesh3d.SceneValidator() self._validators["showscale"] = v_mesh3d.ShowscaleValidator() self._validators["stream"] = v_mesh3d.StreamValidator() self._validators["text"] = v_mesh3d.TextValidator() self._validators["textsrc"] = v_mesh3d.TextsrcValidator() self._validators["uid"] = v_mesh3d.UidValidator() self._validators["uirevision"] = v_mesh3d.UirevisionValidator() self._validators["vertexcolor"] = v_mesh3d.VertexcolorValidator() self._validators["vertexcolorsrc"] = v_mesh3d.VertexcolorsrcValidator() self._validators["visible"] = v_mesh3d.VisibleValidator() self._validators["x"] = v_mesh3d.XValidator() self._validators["xcalendar"] = v_mesh3d.XcalendarValidator() self._validators["xsrc"] = v_mesh3d.XsrcValidator() self._validators["y"] = v_mesh3d.YValidator() self._validators["ycalendar"] = v_mesh3d.YcalendarValidator() self._validators["ysrc"] = v_mesh3d.YsrcValidator() self._validators["z"] = v_mesh3d.ZValidator() self._validators["zcalendar"] = v_mesh3d.ZcalendarValidator() self._validators["zsrc"] = v_mesh3d.ZsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("alphahull", None) self["alphahull"] = alphahull if alphahull is not None else _v _v = arg.pop("autocolorscale", None) self["autocolorscale"] = autocolorscale if autocolorscale is not None else _v _v = arg.pop("cauto", None) self["cauto"] = cauto if cauto is not None else _v _v = arg.pop("cmax", None) self["cmax"] = cmax if cmax is not None else _v _v = arg.pop("cmid", None) self["cmid"] = cmid if cmid is not None else _v _v = arg.pop("cmin", None) self["cmin"] = cmin if cmin is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("coloraxis", None) self["coloraxis"] = coloraxis if coloraxis is not None else _v _v = arg.pop("colorbar", None) self["colorbar"] = colorbar if colorbar is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("contour", None) self["contour"] = contour if contour is not None else _v _v = arg.pop("customdata", None) self["customdata"] = customdata if customdata is not None else _v _v = arg.pop("customdatasrc", None) self["customdatasrc"] = customdatasrc if customdatasrc is not None else _v _v = arg.pop("delaunayaxis", None) self["delaunayaxis"] = delaunayaxis if delaunayaxis is not None else _v _v = arg.pop("facecolor", None) self["facecolor"] = facecolor if facecolor is not None else _v _v = arg.pop("facecolorsrc", None) self["facecolorsrc"] = facecolorsrc if facecolorsrc is not None else _v _v = arg.pop("flatshading", None) self["flatshading"] = flatshading if flatshading is not None else _v _v = arg.pop("hoverinfo", None) self["hoverinfo"] = hoverinfo if hoverinfo is not None else _v _v = arg.pop("hoverinfosrc", None) self["hoverinfosrc"] = hoverinfosrc if hoverinfosrc is not None else _v _v = arg.pop("hoverlabel", None) self["hoverlabel"] = hoverlabel if hoverlabel is not None else _v _v = arg.pop("hovertemplate", None) self["hovertemplate"] = hovertemplate if hovertemplate is not None else _v _v = arg.pop("hovertemplatesrc", None) self["hovertemplatesrc"] = ( hovertemplatesrc if hovertemplatesrc is not None else _v ) _v = arg.pop("hovertext", None) self["hovertext"] = hovertext if hovertext is not None else _v _v = arg.pop("hovertextsrc", None) self["hovertextsrc"] = hovertextsrc if hovertextsrc is not None else _v _v = arg.pop("i", None) self["i"] = i if i is not None else _v _v = arg.pop("ids", None) self["ids"] = ids if ids is not None else _v _v = arg.pop("idssrc", None) self["idssrc"] = idssrc if idssrc is not None else _v _v = arg.pop("intensity", None) self["intensity"] = intensity if intensity is not None else _v _v = arg.pop("intensitysrc", None) self["intensitysrc"] = intensitysrc if intensitysrc is not None else _v _v = arg.pop("isrc", None) self["isrc"] = isrc if isrc is not None else _v _v = arg.pop("j", None) self["j"] = j if j is not None else _v _v = arg.pop("jsrc", None) self["jsrc"] = jsrc if jsrc is not None else _v _v = arg.pop("k", None) self["k"] = k if k is not None else _v _v = arg.pop("ksrc", None) self["ksrc"] = ksrc if ksrc is not None else _v _v = arg.pop("lighting", None) self["lighting"] = lighting if lighting is not None else _v _v = arg.pop("lightposition", None) self["lightposition"] = lightposition if lightposition is not None else _v _v = arg.pop("meta", None) self["meta"] = meta if meta is not None else _v _v = arg.pop("metasrc", None) self["metasrc"] = metasrc if metasrc is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("reversescale", None) self["reversescale"] = reversescale if reversescale is not None else _v _v = arg.pop("scene", None) self["scene"] = scene if scene is not None else _v _v = arg.pop("showscale", None) self["showscale"] = showscale if showscale is not None else _v _v = arg.pop("stream", None) self["stream"] = stream if stream is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v _v = arg.pop("textsrc", None) self["textsrc"] = textsrc if textsrc is not None else _v _v = arg.pop("uid", None) self["uid"] = uid if uid is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("vertexcolor", None) self["vertexcolor"] = vertexcolor if vertexcolor is not None else _v _v = arg.pop("vertexcolorsrc", None) self["vertexcolorsrc"] = vertexcolorsrc if vertexcolorsrc is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xcalendar", None) self["xcalendar"] = xcalendar if xcalendar is not None else _v _v = arg.pop("xsrc", None) self["xsrc"] = xsrc if xsrc is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("ycalendar", None) self["ycalendar"] = ycalendar if ycalendar is not None else _v _v = arg.pop("ysrc", None) self["ysrc"] = ysrc if ysrc is not None else _v _v = arg.pop("z", None) self["z"] = z if z is not None else _v _v = arg.pop("zcalendar", None) self["zcalendar"] = zcalendar if zcalendar is not None else _v _v = arg.pop("zsrc", None) self["zsrc"] = zsrc if zsrc is not None else _v # Read-only literals # ------------------ from _plotly_utils.basevalidators import LiteralValidator self._props["type"] = "mesh3d" self._validators["type"] = LiteralValidator( plotly_name="type", parent_name="mesh3d", val="mesh3d" ) arg.pop("type", None) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceType as _BaseTraceType import copy as _copy class Isosurface(_BaseTraceType): # autocolorscale # -------------- @property def autocolorscale(self): """ Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. The 'autocolorscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocolorscale"] @autocolorscale.setter def autocolorscale(self, val): self["autocolorscale"] = val # caps # ---- @property def caps(self): """ The 'caps' property is an instance of Caps that may be specified as: - An instance of plotly.graph_objs.isosurface.Caps - A dict of string/value properties that will be passed to the Caps constructor Supported dict properties: x plotly.graph_objects.isosurface.caps.X instance or dict with compatible properties y plotly.graph_objects.isosurface.caps.Y instance or dict with compatible properties z plotly.graph_objects.isosurface.caps.Z instance or dict with compatible properties Returns ------- plotly.graph_objs.isosurface.Caps """ return self["caps"] @caps.setter def caps(self, val): self["caps"] = val # cauto # ----- @property def cauto(self): """ Determines whether or not the color domain is computed with respect to the input data (here `value`) or the bounds set in `cmin` and `cmax` Defaults to `false` when `cmin` and `cmax` are set by the user. The 'cauto' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["cauto"] @cauto.setter def cauto(self, val): self["cauto"] = val # cmax # ---- @property def cmax(self): """ Sets the upper bound of the color domain. Value should have the same units as `value` and if set, `cmin` must be set as well. The 'cmax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmax"] @cmax.setter def cmax(self, val): self["cmax"] = val # cmid # ---- @property def cmid(self): """ Sets the mid-point of the color domain by scaling `cmin` and/or `cmax` to be equidistant to this point. Value should have the same units as `value`. Has no effect when `cauto` is `false`. The 'cmid' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmid"] @cmid.setter def cmid(self, val): self["cmid"] = val # cmin # ---- @property def cmin(self): """ Sets the lower bound of the color domain. Value should have the same units as `value` and if set, `cmax` must be set as well. The 'cmin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmin"] @cmin.setter def cmin(self, val): self["cmin"] = val # coloraxis # --------- @property def coloraxis(self): """ Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. The 'coloraxis' property is an identifier of a particular subplot, of type 'coloraxis', that may be specified as the string 'coloraxis' optionally followed by an integer >= 1 (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) Returns ------- str """ return self["coloraxis"] @coloraxis.setter def coloraxis(self, val): self["coloraxis"] = val # colorbar # -------- @property def colorbar(self): """ The 'colorbar' property is an instance of ColorBar that may be specified as: - An instance of plotly.graph_objs.isosurface.ColorBar - A dict of string/value properties that will be passed to the ColorBar constructor Supported dict properties: bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.isosurface.colo rbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.isosurface.colorbar.tickformatstopdefaults), sets the default property values to use for elements of isosurface.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.isosurface.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use isosurface.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use isosurface.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- plotly.graph_objs.isosurface.ColorBar """ return self["colorbar"] @colorbar.setter def colorbar(self, val): self["colorbar"] = val # colorscale # ---------- @property def colorscale(self): """ Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`cmin` and `cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,Earth,Electric,Vi ridis,Cividis. The 'colorscale' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # contour # ------- @property def contour(self): """ The 'contour' property is an instance of Contour that may be specified as: - An instance of plotly.graph_objs.isosurface.Contour - A dict of string/value properties that will be passed to the Contour constructor Supported dict properties: color Sets the color of the contour lines. show Sets whether or not dynamic contours are shown on hover width Sets the width of the contour lines. Returns ------- plotly.graph_objs.isosurface.Contour """ return self["contour"] @contour.setter def contour(self, val): self["contour"] = val # customdata # ---------- @property def customdata(self): """ Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements The 'customdata' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["customdata"] @customdata.setter def customdata(self, val): self["customdata"] = val # customdatasrc # ------------- @property def customdatasrc(self): """ Sets the source reference on plot.ly for customdata . The 'customdatasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["customdatasrc"] @customdatasrc.setter def customdatasrc(self, val): self["customdatasrc"] = val # flatshading # ----------- @property def flatshading(self): """ Determines whether or not normal smoothing is applied to the meshes, creating meshes with an angular, low-poly look via flat reflections. The 'flatshading' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["flatshading"] @flatshading.setter def flatshading(self, val): self["flatshading"] = val # hoverinfo # --------- @property def hoverinfo(self): """ Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. The 'hoverinfo' property is a flaglist and may be specified as a string containing: - Any combination of ['x', 'y', 'z', 'text', 'name'] joined with '+' characters (e.g. 'x+y') OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') - A list or array of the above Returns ------- Any|numpy.ndarray """ return self["hoverinfo"] @hoverinfo.setter def hoverinfo(self, val): self["hoverinfo"] = val # hoverinfosrc # ------------ @property def hoverinfosrc(self): """ Sets the source reference on plot.ly for hoverinfo . The 'hoverinfosrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hoverinfosrc"] @hoverinfosrc.setter def hoverinfosrc(self, val): self["hoverinfosrc"] = val # hoverlabel # ---------- @property def hoverlabel(self): """ The 'hoverlabel' property is an instance of Hoverlabel that may be specified as: - An instance of plotly.graph_objs.isosurface.Hoverlabel - A dict of string/value properties that will be passed to the Hoverlabel constructor Supported dict properties: align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- plotly.graph_objs.isosurface.Hoverlabel """ return self["hoverlabel"] @hoverlabel.setter def hoverlabel(self, val): self["hoverlabel"] = val # hovertemplate # ------------- @property def hovertemplate(self): """ Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event- data. Additionally, every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. The 'hovertemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertemplate"] @hovertemplate.setter def hovertemplate(self, val): self["hovertemplate"] = val # hovertemplatesrc # ---------------- @property def hovertemplatesrc(self): """ Sets the source reference on plot.ly for hovertemplate . The 'hovertemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertemplatesrc"] @hovertemplatesrc.setter def hovertemplatesrc(self, val): self["hovertemplatesrc"] = val # hovertext # --------- @property def hovertext(self): """ Same as `text`. The 'hovertext' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertext"] @hovertext.setter def hovertext(self, val): self["hovertext"] = val # hovertextsrc # ------------ @property def hovertextsrc(self): """ Sets the source reference on plot.ly for hovertext . The 'hovertextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertextsrc"] @hovertextsrc.setter def hovertextsrc(self, val): self["hovertextsrc"] = val # ids # --- @property def ids(self): """ Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. The 'ids' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ids"] @ids.setter def ids(self, val): self["ids"] = val # idssrc # ------ @property def idssrc(self): """ Sets the source reference on plot.ly for ids . The 'idssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["idssrc"] @idssrc.setter def idssrc(self, val): self["idssrc"] = val # isomax # ------ @property def isomax(self): """ Sets the maximum boundary for iso-surface plot. The 'isomax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["isomax"] @isomax.setter def isomax(self, val): self["isomax"] = val # isomin # ------ @property def isomin(self): """ Sets the minimum boundary for iso-surface plot. The 'isomin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["isomin"] @isomin.setter def isomin(self, val): self["isomin"] = val # lighting # -------- @property def lighting(self): """ The 'lighting' property is an instance of Lighting that may be specified as: - An instance of plotly.graph_objs.isosurface.Lighting - A dict of string/value properties that will be passed to the Lighting constructor Supported dict properties: ambient Ambient light increases overall color visibility but can wash out the image. diffuse Represents the extent that incident rays are reflected in a range of angles. facenormalsepsilon Epsilon for face normals calculation avoids math issues arising from degenerate geometry. fresnel Represents the reflectance as a dependency of the viewing angle; e.g. paper is reflective when viewing it from the edge of the paper (almost 90 degrees), causing shine. roughness Alters specular reflection; the rougher the surface, the wider and less contrasty the shine. specular Represents the level that incident rays are reflected in a single direction, causing shine. vertexnormalsepsilon Epsilon for vertex normals calculation avoids math issues arising from degenerate geometry. Returns ------- plotly.graph_objs.isosurface.Lighting """ return self["lighting"] @lighting.setter def lighting(self, val): self["lighting"] = val # lightposition # ------------- @property def lightposition(self): """ The 'lightposition' property is an instance of Lightposition that may be specified as: - An instance of plotly.graph_objs.isosurface.Lightposition - A dict of string/value properties that will be passed to the Lightposition constructor Supported dict properties: x Numeric vector, representing the X coordinate for each vertex. y Numeric vector, representing the Y coordinate for each vertex. z Numeric vector, representing the Z coordinate for each vertex. Returns ------- plotly.graph_objs.isosurface.Lightposition """ return self["lightposition"] @lightposition.setter def lightposition(self, val): self["lightposition"] = val # meta # ---- @property def meta(self): """ Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. The 'meta' property accepts values of any type Returns ------- Any|numpy.ndarray """ return self["meta"] @meta.setter def meta(self, val): self["meta"] = val # metasrc # ------- @property def metasrc(self): """ Sets the source reference on plot.ly for meta . The 'metasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["metasrc"] @metasrc.setter def metasrc(self, val): self["metasrc"] = val # name # ---- @property def name(self): """ Sets the trace name. The trace name appear as the legend item and on hover. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the surface. Please note that in the case of using high `opacity` values for example a value greater than or equal to 0.5 on two surfaces (and 0.25 with four surfaces), an overlay of multiple transparent surfaces may not perfectly be sorted in depth by the webgl API. This behavior may be improved in the near future and is subject to change. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # reversescale # ------------ @property def reversescale(self): """ Reverses the color mapping if true. If true, `cmin` will correspond to the last color in the array and `cmax` will correspond to the first color. The 'reversescale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["reversescale"] @reversescale.setter def reversescale(self, val): self["reversescale"] = val # scene # ----- @property def scene(self): """ Sets a reference between this trace's 3D coordinate system and a 3D scene. If "scene" (the default value), the (x,y,z) coordinates refer to `layout.scene`. If "scene2", the (x,y,z) coordinates refer to `layout.scene2`, and so on. The 'scene' property is an identifier of a particular subplot, of type 'scene', that may be specified as the string 'scene' optionally followed by an integer >= 1 (e.g. 'scene', 'scene1', 'scene2', 'scene3', etc.) Returns ------- str """ return self["scene"] @scene.setter def scene(self, val): self["scene"] = val # showscale # --------- @property def showscale(self): """ Determines whether or not a colorbar is displayed for this trace. The 'showscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showscale"] @showscale.setter def showscale(self, val): self["showscale"] = val # slices # ------ @property def slices(self): """ The 'slices' property is an instance of Slices that may be specified as: - An instance of plotly.graph_objs.isosurface.Slices - A dict of string/value properties that will be passed to the Slices constructor Supported dict properties: x plotly.graph_objects.isosurface.slices.X instance or dict with compatible properties y plotly.graph_objects.isosurface.slices.Y instance or dict with compatible properties z plotly.graph_objects.isosurface.slices.Z instance or dict with compatible properties Returns ------- plotly.graph_objs.isosurface.Slices """ return self["slices"] @slices.setter def slices(self, val): self["slices"] = val # spaceframe # ---------- @property def spaceframe(self): """ The 'spaceframe' property is an instance of Spaceframe that may be specified as: - An instance of plotly.graph_objs.isosurface.Spaceframe - A dict of string/value properties that will be passed to the Spaceframe constructor Supported dict properties: fill Sets the fill ratio of the `spaceframe` elements. The default fill value is 0.15 meaning that only 15% of the area of every faces of tetras would be shaded. Applying a greater `fill` ratio would allow the creation of stronger elements or could be sued to have entirely closed areas (in case of using 1). show Displays/hides tetrahedron shapes between minimum and maximum iso-values. Often useful when either caps or surfaces are disabled or filled with values less than 1. Returns ------- plotly.graph_objs.isosurface.Spaceframe """ return self["spaceframe"] @spaceframe.setter def spaceframe(self, val): self["spaceframe"] = val # stream # ------ @property def stream(self): """ The 'stream' property is an instance of Stream that may be specified as: - An instance of plotly.graph_objs.isosurface.Stream - A dict of string/value properties that will be passed to the Stream constructor Supported dict properties: maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- plotly.graph_objs.isosurface.Stream """ return self["stream"] @stream.setter def stream(self, val): self["stream"] = val # surface # ------- @property def surface(self): """ The 'surface' property is an instance of Surface that may be specified as: - An instance of plotly.graph_objs.isosurface.Surface - A dict of string/value properties that will be passed to the Surface constructor Supported dict properties: count Sets the number of iso-surfaces between minimum and maximum iso-values. By default this value is 2 meaning that only minimum and maximum surfaces would be drawn. fill Sets the fill ratio of the iso-surface. The default fill value of the surface is 1 meaning that they are entirely shaded. On the other hand Applying a `fill` ratio less than one would allow the creation of openings parallel to the edges. pattern Sets the surface pattern of the iso-surface 3-D sections. The default pattern of the surface is `all` meaning that the rest of surface elements would be shaded. The check options (either 1 or 2) could be used to draw half of the squares on the surface. Using various combinations of capital `A`, `B`, `C`, `D` and `E` may also be used to reduce the number of triangles on the iso-surfaces and creating other patterns of interest. show Hides/displays surfaces between minimum and maximum iso-values. Returns ------- plotly.graph_objs.isosurface.Surface """ return self["surface"] @surface.setter def surface(self, val): self["surface"] = val # text # ---- @property def text(self): """ Sets the text elements associated with the vertices. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["text"] @text.setter def text(self, val): self["text"] = val # textsrc # ------- @property def textsrc(self): """ Sets the source reference on plot.ly for text . The 'textsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["textsrc"] @textsrc.setter def textsrc(self, val): self["textsrc"] = val # uid # --- @property def uid(self): """ Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. The 'uid' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["uid"] @uid.setter def uid(self, val): self["uid"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # value # ----- @property def value(self): """ Sets the 4th dimension (value) of the vertices. The 'value' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["value"] @value.setter def value(self, val): self["value"] = val # valuesrc # -------- @property def valuesrc(self): """ Sets the source reference on plot.ly for value . The 'valuesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["valuesrc"] @valuesrc.setter def valuesrc(self, val): self["valuesrc"] = val # visible # ------- @property def visible(self): """ Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). The 'visible' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'legendonly'] Returns ------- Any """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # x # - @property def x(self): """ Sets the X coordinates of the vertices on X axis. The 'x' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["x"] @x.setter def x(self, val): self["x"] = val # xsrc # ---- @property def xsrc(self): """ Sets the source reference on plot.ly for x . The 'xsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["xsrc"] @xsrc.setter def xsrc(self, val): self["xsrc"] = val # y # - @property def y(self): """ Sets the Y coordinates of the vertices on Y axis. The 'y' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["y"] @y.setter def y(self, val): self["y"] = val # ysrc # ---- @property def ysrc(self): """ Sets the source reference on plot.ly for y . The 'ysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ysrc"] @ysrc.setter def ysrc(self, val): self["ysrc"] = val # z # - @property def z(self): """ Sets the Z coordinates of the vertices on Z axis. The 'z' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["z"] @z.setter def z(self, val): self["z"] = val # zsrc # ---- @property def zsrc(self): """ Sets the source reference on plot.ly for z . The 'zsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["zsrc"] @zsrc.setter def zsrc(self, val): self["zsrc"] = val # type # ---- @property def type(self): return self._props["type"] # property parent name # -------------------- @property def _parent_path_str(self): return "" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. caps plotly.graph_objects.isosurface.Caps instance or dict with compatible properties cauto Determines whether or not the color domain is computed with respect to the input data (here `value`) or the bounds set in `cmin` and `cmax` Defaults to `false` when `cmin` and `cmax` are set by the user. cmax Sets the upper bound of the color domain. Value should have the same units as `value` and if set, `cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `cmin` and/or `cmax` to be equidistant to this point. Value should have the same units as `value`. Has no effect when `cauto` is `false`. cmin Sets the lower bound of the color domain. Value should have the same units as `value` and if set, `cmax` must be set as well. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.isosurface.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`cmin` and `cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. contour plotly.graph_objects.isosurface.Contour instance or dict with compatible properties customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . flatshading Determines whether or not normal smoothing is applied to the meshes, creating meshes with an angular, low- poly look via flat reflections. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.isosurface.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . isomax Sets the maximum boundary for iso-surface plot. isomin Sets the minimum boundary for iso-surface plot. lighting plotly.graph_objects.isosurface.Lighting instance or dict with compatible properties lightposition plotly.graph_objects.isosurface.Lightposition instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the surface. Please note that in the case of using high `opacity` values for example a value greater than or equal to 0.5 on two surfaces (and 0.25 with four surfaces), an overlay of multiple transparent surfaces may not perfectly be sorted in depth by the webgl API. This behavior may be improved in the near future and is subject to change. reversescale Reverses the color mapping if true. If true, `cmin` will correspond to the last color in the array and `cmax` will correspond to the first color. scene Sets a reference between this trace's 3D coordinate system and a 3D scene. If "scene" (the default value), the (x,y,z) coordinates refer to `layout.scene`. If "scene2", the (x,y,z) coordinates refer to `layout.scene2`, and so on. showscale Determines whether or not a colorbar is displayed for this trace. slices plotly.graph_objects.isosurface.Slices instance or dict with compatible properties spaceframe plotly.graph_objects.isosurface.Spaceframe instance or dict with compatible properties stream plotly.graph_objects.isosurface.Stream instance or dict with compatible properties surface plotly.graph_objects.isosurface.Surface instance or dict with compatible properties text Sets the text elements associated with the vertices. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. value Sets the 4th dimension (value) of the vertices. valuesrc Sets the source reference on plot.ly for value . visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the X coordinates of the vertices on X axis. xsrc Sets the source reference on plot.ly for x . y Sets the Y coordinates of the vertices on Y axis. ysrc Sets the source reference on plot.ly for y . z Sets the Z coordinates of the vertices on Z axis. zsrc Sets the source reference on plot.ly for z . """ def __init__( self, arg=None, autocolorscale=None, caps=None, cauto=None, cmax=None, cmid=None, cmin=None, coloraxis=None, colorbar=None, colorscale=None, contour=None, customdata=None, customdatasrc=None, flatshading=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, isomax=None, isomin=None, lighting=None, lightposition=None, meta=None, metasrc=None, name=None, opacity=None, reversescale=None, scene=None, showscale=None, slices=None, spaceframe=None, stream=None, surface=None, text=None, textsrc=None, uid=None, uirevision=None, value=None, valuesrc=None, visible=None, x=None, xsrc=None, y=None, ysrc=None, z=None, zsrc=None, **kwargs ): """ Construct a new Isosurface object Draws isosurfaces between iso-min and iso-max values with coordinates given by four 1-dimensional arrays containing the `value`, `x`, `y` and `z` of every vertex of a uniform or non- uniform 3-D grid. Horizontal or vertical slices, caps as well as spaceframe between iso-min and iso-max values could also be drawn using this trace. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.Isosurface autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. caps plotly.graph_objects.isosurface.Caps instance or dict with compatible properties cauto Determines whether or not the color domain is computed with respect to the input data (here `value`) or the bounds set in `cmin` and `cmax` Defaults to `false` when `cmin` and `cmax` are set by the user. cmax Sets the upper bound of the color domain. Value should have the same units as `value` and if set, `cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `cmin` and/or `cmax` to be equidistant to this point. Value should have the same units as `value`. Has no effect when `cauto` is `false`. cmin Sets the lower bound of the color domain. Value should have the same units as `value` and if set, `cmax` must be set as well. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.isosurface.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`cmin` and `cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. contour plotly.graph_objects.isosurface.Contour instance or dict with compatible properties customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . flatshading Determines whether or not normal smoothing is applied to the meshes, creating meshes with an angular, low- poly look via flat reflections. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.isosurface.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . isomax Sets the maximum boundary for iso-surface plot. isomin Sets the minimum boundary for iso-surface plot. lighting plotly.graph_objects.isosurface.Lighting instance or dict with compatible properties lightposition plotly.graph_objects.isosurface.Lightposition instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the surface. Please note that in the case of using high `opacity` values for example a value greater than or equal to 0.5 on two surfaces (and 0.25 with four surfaces), an overlay of multiple transparent surfaces may not perfectly be sorted in depth by the webgl API. This behavior may be improved in the near future and is subject to change. reversescale Reverses the color mapping if true. If true, `cmin` will correspond to the last color in the array and `cmax` will correspond to the first color. scene Sets a reference between this trace's 3D coordinate system and a 3D scene. If "scene" (the default value), the (x,y,z) coordinates refer to `layout.scene`. If "scene2", the (x,y,z) coordinates refer to `layout.scene2`, and so on. showscale Determines whether or not a colorbar is displayed for this trace. slices plotly.graph_objects.isosurface.Slices instance or dict with compatible properties spaceframe plotly.graph_objects.isosurface.Spaceframe instance or dict with compatible properties stream plotly.graph_objects.isosurface.Stream instance or dict with compatible properties surface plotly.graph_objects.isosurface.Surface instance or dict with compatible properties text Sets the text elements associated with the vertices. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. value Sets the 4th dimension (value) of the vertices. valuesrc Sets the source reference on plot.ly for value . visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the X coordinates of the vertices on X axis. xsrc Sets the source reference on plot.ly for x . y Sets the Y coordinates of the vertices on Y axis. ysrc Sets the source reference on plot.ly for y . z Sets the Z coordinates of the vertices on Z axis. zsrc Sets the source reference on plot.ly for z . Returns ------- Isosurface """ super(Isosurface, self).__init__("isosurface") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.Isosurface constructor must be a dict or an instance of plotly.graph_objs.Isosurface""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators import isosurface as v_isosurface # Initialize validators # --------------------- self._validators["autocolorscale"] = v_isosurface.AutocolorscaleValidator() self._validators["caps"] = v_isosurface.CapsValidator() self._validators["cauto"] = v_isosurface.CautoValidator() self._validators["cmax"] = v_isosurface.CmaxValidator() self._validators["cmid"] = v_isosurface.CmidValidator() self._validators["cmin"] = v_isosurface.CminValidator() self._validators["coloraxis"] = v_isosurface.ColoraxisValidator() self._validators["colorbar"] = v_isosurface.ColorBarValidator() self._validators["colorscale"] = v_isosurface.ColorscaleValidator() self._validators["contour"] = v_isosurface.ContourValidator() self._validators["customdata"] = v_isosurface.CustomdataValidator() self._validators["customdatasrc"] = v_isosurface.CustomdatasrcValidator() self._validators["flatshading"] = v_isosurface.FlatshadingValidator() self._validators["hoverinfo"] = v_isosurface.HoverinfoValidator() self._validators["hoverinfosrc"] = v_isosurface.HoverinfosrcValidator() self._validators["hoverlabel"] = v_isosurface.HoverlabelValidator() self._validators["hovertemplate"] = v_isosurface.HovertemplateValidator() self._validators["hovertemplatesrc"] = v_isosurface.HovertemplatesrcValidator() self._validators["hovertext"] = v_isosurface.HovertextValidator() self._validators["hovertextsrc"] = v_isosurface.HovertextsrcValidator() self._validators["ids"] = v_isosurface.IdsValidator() self._validators["idssrc"] = v_isosurface.IdssrcValidator() self._validators["isomax"] = v_isosurface.IsomaxValidator() self._validators["isomin"] = v_isosurface.IsominValidator() self._validators["lighting"] = v_isosurface.LightingValidator() self._validators["lightposition"] = v_isosurface.LightpositionValidator() self._validators["meta"] = v_isosurface.MetaValidator() self._validators["metasrc"] = v_isosurface.MetasrcValidator() self._validators["name"] = v_isosurface.NameValidator() self._validators["opacity"] = v_isosurface.OpacityValidator() self._validators["reversescale"] = v_isosurface.ReversescaleValidator() self._validators["scene"] = v_isosurface.SceneValidator() self._validators["showscale"] = v_isosurface.ShowscaleValidator() self._validators["slices"] = v_isosurface.SlicesValidator() self._validators["spaceframe"] = v_isosurface.SpaceframeValidator() self._validators["stream"] = v_isosurface.StreamValidator() self._validators["surface"] = v_isosurface.SurfaceValidator() self._validators["text"] = v_isosurface.TextValidator() self._validators["textsrc"] = v_isosurface.TextsrcValidator() self._validators["uid"] = v_isosurface.UidValidator() self._validators["uirevision"] = v_isosurface.UirevisionValidator() self._validators["value"] = v_isosurface.ValueValidator() self._validators["valuesrc"] = v_isosurface.ValuesrcValidator() self._validators["visible"] = v_isosurface.VisibleValidator() self._validators["x"] = v_isosurface.XValidator() self._validators["xsrc"] = v_isosurface.XsrcValidator() self._validators["y"] = v_isosurface.YValidator() self._validators["ysrc"] = v_isosurface.YsrcValidator() self._validators["z"] = v_isosurface.ZValidator() self._validators["zsrc"] = v_isosurface.ZsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autocolorscale", None) self["autocolorscale"] = autocolorscale if autocolorscale is not None else _v _v = arg.pop("caps", None) self["caps"] = caps if caps is not None else _v _v = arg.pop("cauto", None) self["cauto"] = cauto if cauto is not None else _v _v = arg.pop("cmax", None) self["cmax"] = cmax if cmax is not None else _v _v = arg.pop("cmid", None) self["cmid"] = cmid if cmid is not None else _v _v = arg.pop("cmin", None) self["cmin"] = cmin if cmin is not None else _v _v = arg.pop("coloraxis", None) self["coloraxis"] = coloraxis if coloraxis is not None else _v _v = arg.pop("colorbar", None) self["colorbar"] = colorbar if colorbar is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("contour", None) self["contour"] = contour if contour is not None else _v _v = arg.pop("customdata", None) self["customdata"] = customdata if customdata is not None else _v _v = arg.pop("customdatasrc", None) self["customdatasrc"] = customdatasrc if customdatasrc is not None else _v _v = arg.pop("flatshading", None) self["flatshading"] = flatshading if flatshading is not None else _v _v = arg.pop("hoverinfo", None) self["hoverinfo"] = hoverinfo if hoverinfo is not None else _v _v = arg.pop("hoverinfosrc", None) self["hoverinfosrc"] = hoverinfosrc if hoverinfosrc is not None else _v _v = arg.pop("hoverlabel", None) self["hoverlabel"] = hoverlabel if hoverlabel is not None else _v _v = arg.pop("hovertemplate", None) self["hovertemplate"] = hovertemplate if hovertemplate is not None else _v _v = arg.pop("hovertemplatesrc", None) self["hovertemplatesrc"] = ( hovertemplatesrc if hovertemplatesrc is not None else _v ) _v = arg.pop("hovertext", None) self["hovertext"] = hovertext if hovertext is not None else _v _v = arg.pop("hovertextsrc", None) self["hovertextsrc"] = hovertextsrc if hovertextsrc is not None else _v _v = arg.pop("ids", None) self["ids"] = ids if ids is not None else _v _v = arg.pop("idssrc", None) self["idssrc"] = idssrc if idssrc is not None else _v _v = arg.pop("isomax", None) self["isomax"] = isomax if isomax is not None else _v _v = arg.pop("isomin", None) self["isomin"] = isomin if isomin is not None else _v _v = arg.pop("lighting", None) self["lighting"] = lighting if lighting is not None else _v _v = arg.pop("lightposition", None) self["lightposition"] = lightposition if lightposition is not None else _v _v = arg.pop("meta", None) self["meta"] = meta if meta is not None else _v _v = arg.pop("metasrc", None) self["metasrc"] = metasrc if metasrc is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("reversescale", None) self["reversescale"] = reversescale if reversescale is not None else _v _v = arg.pop("scene", None) self["scene"] = scene if scene is not None else _v _v = arg.pop("showscale", None) self["showscale"] = showscale if showscale is not None else _v _v = arg.pop("slices", None) self["slices"] = slices if slices is not None else _v _v = arg.pop("spaceframe", None) self["spaceframe"] = spaceframe if spaceframe is not None else _v _v = arg.pop("stream", None) self["stream"] = stream if stream is not None else _v _v = arg.pop("surface", None) self["surface"] = surface if surface is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v _v = arg.pop("textsrc", None) self["textsrc"] = textsrc if textsrc is not None else _v _v = arg.pop("uid", None) self["uid"] = uid if uid is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("value", None) self["value"] = value if value is not None else _v _v = arg.pop("valuesrc", None) self["valuesrc"] = valuesrc if valuesrc is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xsrc", None) self["xsrc"] = xsrc if xsrc is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("ysrc", None) self["ysrc"] = ysrc if ysrc is not None else _v _v = arg.pop("z", None) self["z"] = z if z is not None else _v _v = arg.pop("zsrc", None) self["zsrc"] = zsrc if zsrc is not None else _v # Read-only literals # ------------------ from _plotly_utils.basevalidators import LiteralValidator self._props["type"] = "isosurface" self._validators["type"] = LiteralValidator( plotly_name="type", parent_name="isosurface", val="isosurface" ) arg.pop("type", None) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceType as _BaseTraceType import copy as _copy class Indicator(_BaseTraceType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the `text` within the box. Note that this attribute has no effect if an angular gauge is displayed: in this case, it is always centered The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'center', 'right'] Returns ------- Any """ return self["align"] @align.setter def align(self, val): self["align"] = val # customdata # ---------- @property def customdata(self): """ Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements The 'customdata' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["customdata"] @customdata.setter def customdata(self, val): self["customdata"] = val # customdatasrc # ------------- @property def customdatasrc(self): """ Sets the source reference on plot.ly for customdata . The 'customdatasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["customdatasrc"] @customdatasrc.setter def customdatasrc(self, val): self["customdatasrc"] = val # delta # ----- @property def delta(self): """ The 'delta' property is an instance of Delta that may be specified as: - An instance of plotly.graph_objs.indicator.Delta - A dict of string/value properties that will be passed to the Delta constructor Supported dict properties: decreasing plotly.graph_objects.indicator.delta.Decreasing instance or dict with compatible properties font Set the font used to display the delta increasing plotly.graph_objects.indicator.delta.Increasing instance or dict with compatible properties position Sets the position of delta with respect to the number. reference Sets the reference value to compute the delta. By default, it is set to the current value. relative Show relative change valueformat Sets the value formatting rule using d3 formatting mini-language which is similar to those of Python. See https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format Returns ------- plotly.graph_objs.indicator.Delta """ return self["delta"] @delta.setter def delta(self, val): self["delta"] = val # domain # ------ @property def domain(self): """ The 'domain' property is an instance of Domain that may be specified as: - An instance of plotly.graph_objs.indicator.Domain - A dict of string/value properties that will be passed to the Domain constructor Supported dict properties: column If there is a layout grid, use the domain for this column in the grid for this indicator trace . row If there is a layout grid, use the domain for this row in the grid for this indicator trace . x Sets the horizontal domain of this indicator trace (in plot fraction). y Sets the vertical domain of this indicator trace (in plot fraction). Returns ------- plotly.graph_objs.indicator.Domain """ return self["domain"] @domain.setter def domain(self, val): self["domain"] = val # gauge # ----- @property def gauge(self): """ The gauge of the Indicator plot. The 'gauge' property is an instance of Gauge that may be specified as: - An instance of plotly.graph_objs.indicator.Gauge - A dict of string/value properties that will be passed to the Gauge constructor Supported dict properties: axis plotly.graph_objects.indicator.gauge.Axis instance or dict with compatible properties bar Set the appearance of the gauge's value bgcolor Sets the gauge background color. bordercolor Sets the color of the border enclosing the gauge. borderwidth Sets the width (in px) of the border enclosing the gauge. shape Set the shape of the gauge steps A tuple of plotly.graph_objects.indicator.gauge.Step instances or dicts with compatible properties stepdefaults When used in a template (as layout.template.dat a.indicator.gauge.stepdefaults), sets the default property values to use for elements of indicator.gauge.steps threshold plotly.graph_objects.indicator.gauge.Threshold instance or dict with compatible properties Returns ------- plotly.graph_objs.indicator.Gauge """ return self["gauge"] @gauge.setter def gauge(self, val): self["gauge"] = val # ids # --- @property def ids(self): """ Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. The 'ids' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ids"] @ids.setter def ids(self, val): self["ids"] = val # idssrc # ------ @property def idssrc(self): """ Sets the source reference on plot.ly for ids . The 'idssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["idssrc"] @idssrc.setter def idssrc(self, val): self["idssrc"] = val # meta # ---- @property def meta(self): """ Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. The 'meta' property accepts values of any type Returns ------- Any|numpy.ndarray """ return self["meta"] @meta.setter def meta(self, val): self["meta"] = val # metasrc # ------- @property def metasrc(self): """ Sets the source reference on plot.ly for meta . The 'metasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["metasrc"] @metasrc.setter def metasrc(self, val): self["metasrc"] = val # mode # ---- @property def mode(self): """ Determines how the value is displayed on the graph. `number` displays the value numerically in text. `delta` displays the difference to a reference value in text. Finally, `gauge` displays the value graphically on an axis. The 'mode' property is a flaglist and may be specified as a string containing: - Any combination of ['number', 'delta', 'gauge'] joined with '+' characters (e.g. 'number+delta') Returns ------- Any """ return self["mode"] @mode.setter def mode(self, val): self["mode"] = val # name # ---- @property def name(self): """ Sets the trace name. The trace name appear as the legend item and on hover. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # number # ------ @property def number(self): """ The 'number' property is an instance of Number that may be specified as: - An instance of plotly.graph_objs.indicator.Number - A dict of string/value properties that will be passed to the Number constructor Supported dict properties: font Set the font used to display main number prefix Sets a prefix appearing before the number. suffix Sets a suffix appearing next to the number. valueformat Sets the value formatting rule using d3 formatting mini-language which is similar to those of Python. See https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format Returns ------- plotly.graph_objs.indicator.Number """ return self["number"] @number.setter def number(self, val): self["number"] = val # stream # ------ @property def stream(self): """ The 'stream' property is an instance of Stream that may be specified as: - An instance of plotly.graph_objs.indicator.Stream - A dict of string/value properties that will be passed to the Stream constructor Supported dict properties: maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- plotly.graph_objs.indicator.Stream """ return self["stream"] @stream.setter def stream(self, val): self["stream"] = val # title # ----- @property def title(self): """ The 'title' property is an instance of Title that may be specified as: - An instance of plotly.graph_objs.indicator.Title - A dict of string/value properties that will be passed to the Title constructor Supported dict properties: align Sets the horizontal alignment of the title. It defaults to `center` except for bullet charts for which it defaults to right. font Set the font used to display the title text Sets the title of this indicator. Returns ------- plotly.graph_objs.indicator.Title """ return self["title"] @title.setter def title(self, val): self["title"] = val # uid # --- @property def uid(self): """ Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. The 'uid' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["uid"] @uid.setter def uid(self, val): self["uid"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # value # ----- @property def value(self): """ Sets the number to be displayed. The 'value' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["value"] @value.setter def value(self, val): self["value"] = val # visible # ------- @property def visible(self): """ Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). The 'visible' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'legendonly'] Returns ------- Any """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # type # ---- @property def type(self): return self._props["type"] # property parent name # -------------------- @property def _parent_path_str(self): return "" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the `text` within the box. Note that this attribute has no effect if an angular gauge is displayed: in this case, it is always centered customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . delta plotly.graph_objects.indicator.Delta instance or dict with compatible properties domain plotly.graph_objects.indicator.Domain instance or dict with compatible properties gauge The gauge of the Indicator plot. ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . mode Determines how the value is displayed on the graph. `number` displays the value numerically in text. `delta` displays the difference to a reference value in text. Finally, `gauge` displays the value graphically on an axis. name Sets the trace name. The trace name appear as the legend item and on hover. number plotly.graph_objects.indicator.Number instance or dict with compatible properties stream plotly.graph_objects.indicator.Stream instance or dict with compatible properties title plotly.graph_objects.indicator.Title instance or dict with compatible properties uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. value Sets the number to be displayed. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). """ def __init__( self, arg=None, align=None, customdata=None, customdatasrc=None, delta=None, domain=None, gauge=None, ids=None, idssrc=None, meta=None, metasrc=None, mode=None, name=None, number=None, stream=None, title=None, uid=None, uirevision=None, value=None, visible=None, **kwargs ): """ Construct a new Indicator object An indicator is used to visualize a single `value` along with some contextual information such as `steps` or a `threshold`, using a combination of three visual elements: a number, a delta, and/or a gauge. Deltas are taken with respect to a `reference`. Gauges can be either angular or bullet (aka linear) gauges. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.Indicator align Sets the horizontal alignment of the `text` within the box. Note that this attribute has no effect if an angular gauge is displayed: in this case, it is always centered customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . delta plotly.graph_objects.indicator.Delta instance or dict with compatible properties domain plotly.graph_objects.indicator.Domain instance or dict with compatible properties gauge The gauge of the Indicator plot. ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . mode Determines how the value is displayed on the graph. `number` displays the value numerically in text. `delta` displays the difference to a reference value in text. Finally, `gauge` displays the value graphically on an axis. name Sets the trace name. The trace name appear as the legend item and on hover. number plotly.graph_objects.indicator.Number instance or dict with compatible properties stream plotly.graph_objects.indicator.Stream instance or dict with compatible properties title plotly.graph_objects.indicator.Title instance or dict with compatible properties uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. value Sets the number to be displayed. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). Returns ------- Indicator """ super(Indicator, self).__init__("indicator") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.Indicator constructor must be a dict or an instance of plotly.graph_objs.Indicator""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators import indicator as v_indicator # Initialize validators # --------------------- self._validators["align"] = v_indicator.AlignValidator() self._validators["customdata"] = v_indicator.CustomdataValidator() self._validators["customdatasrc"] = v_indicator.CustomdatasrcValidator() self._validators["delta"] = v_indicator.DeltaValidator() self._validators["domain"] = v_indicator.DomainValidator() self._validators["gauge"] = v_indicator.GaugeValidator() self._validators["ids"] = v_indicator.IdsValidator() self._validators["idssrc"] = v_indicator.IdssrcValidator() self._validators["meta"] = v_indicator.MetaValidator() self._validators["metasrc"] = v_indicator.MetasrcValidator() self._validators["mode"] = v_indicator.ModeValidator() self._validators["name"] = v_indicator.NameValidator() self._validators["number"] = v_indicator.NumberValidator() self._validators["stream"] = v_indicator.StreamValidator() self._validators["title"] = v_indicator.TitleValidator() self._validators["uid"] = v_indicator.UidValidator() self._validators["uirevision"] = v_indicator.UirevisionValidator() self._validators["value"] = v_indicator.ValueValidator() self._validators["visible"] = v_indicator.VisibleValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("customdata", None) self["customdata"] = customdata if customdata is not None else _v _v = arg.pop("customdatasrc", None) self["customdatasrc"] = customdatasrc if customdatasrc is not None else _v _v = arg.pop("delta", None) self["delta"] = delta if delta is not None else _v _v = arg.pop("domain", None) self["domain"] = domain if domain is not None else _v _v = arg.pop("gauge", None) self["gauge"] = gauge if gauge is not None else _v _v = arg.pop("ids", None) self["ids"] = ids if ids is not None else _v _v = arg.pop("idssrc", None) self["idssrc"] = idssrc if idssrc is not None else _v _v = arg.pop("meta", None) self["meta"] = meta if meta is not None else _v _v = arg.pop("metasrc", None) self["metasrc"] = metasrc if metasrc is not None else _v _v = arg.pop("mode", None) self["mode"] = mode if mode is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("number", None) self["number"] = number if number is not None else _v _v = arg.pop("stream", None) self["stream"] = stream if stream is not None else _v _v = arg.pop("title", None) self["title"] = title if title is not None else _v _v = arg.pop("uid", None) self["uid"] = uid if uid is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("value", None) self["value"] = value if value is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v # Read-only literals # ------------------ from _plotly_utils.basevalidators import LiteralValidator self._props["type"] = "indicator" self._validators["type"] = LiteralValidator( plotly_name="type", parent_name="indicator", val="indicator" ) arg.pop("type", None) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceType as _BaseTraceType import copy as _copy class Image(_BaseTraceType): # colormodel # ---------- @property def colormodel(self): """ Color model used to map the numerical color components described in `z` into colors. The 'colormodel' property is an enumeration that may be specified as: - One of the following enumeration values: ['rgb', 'rgba', 'hsl', 'hsla'] Returns ------- Any """ return self["colormodel"] @colormodel.setter def colormodel(self, val): self["colormodel"] = val # customdata # ---------- @property def customdata(self): """ Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements The 'customdata' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["customdata"] @customdata.setter def customdata(self, val): self["customdata"] = val # customdatasrc # ------------- @property def customdatasrc(self): """ Sets the source reference on plot.ly for customdata . The 'customdatasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["customdatasrc"] @customdatasrc.setter def customdatasrc(self, val): self["customdatasrc"] = val # dx # -- @property def dx(self): """ Set the pixel's horizontal size. The 'dx' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["dx"] @dx.setter def dx(self, val): self["dx"] = val # dy # -- @property def dy(self): """ Set the pixel's vertical size The 'dy' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["dy"] @dy.setter def dy(self, val): self["dy"] = val # hoverinfo # --------- @property def hoverinfo(self): """ Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. The 'hoverinfo' property is a flaglist and may be specified as a string containing: - Any combination of ['x', 'y', 'z', 'color', 'name', 'text'] joined with '+' characters (e.g. 'x+y') OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') - A list or array of the above Returns ------- Any|numpy.ndarray """ return self["hoverinfo"] @hoverinfo.setter def hoverinfo(self, val): self["hoverinfo"] = val # hoverinfosrc # ------------ @property def hoverinfosrc(self): """ Sets the source reference on plot.ly for hoverinfo . The 'hoverinfosrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hoverinfosrc"] @hoverinfosrc.setter def hoverinfosrc(self, val): self["hoverinfosrc"] = val # hoverlabel # ---------- @property def hoverlabel(self): """ The 'hoverlabel' property is an instance of Hoverlabel that may be specified as: - An instance of plotly.graph_objs.image.Hoverlabel - A dict of string/value properties that will be passed to the Hoverlabel constructor Supported dict properties: align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- plotly.graph_objs.image.Hoverlabel """ return self["hoverlabel"] @hoverlabel.setter def hoverlabel(self, val): self["hoverlabel"] = val # hovertemplate # ------------- @property def hovertemplate(self): """ Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event- data. Additionally, every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. variables `z`, `color` and `colormodel`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. The 'hovertemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertemplate"] @hovertemplate.setter def hovertemplate(self, val): self["hovertemplate"] = val # hovertemplatesrc # ---------------- @property def hovertemplatesrc(self): """ Sets the source reference on plot.ly for hovertemplate . The 'hovertemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertemplatesrc"] @hovertemplatesrc.setter def hovertemplatesrc(self, val): self["hovertemplatesrc"] = val # hovertext # --------- @property def hovertext(self): """ Same as `text`. The 'hovertext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["hovertext"] @hovertext.setter def hovertext(self, val): self["hovertext"] = val # hovertextsrc # ------------ @property def hovertextsrc(self): """ Sets the source reference on plot.ly for hovertext . The 'hovertextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertextsrc"] @hovertextsrc.setter def hovertextsrc(self, val): self["hovertextsrc"] = val # ids # --- @property def ids(self): """ Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. The 'ids' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ids"] @ids.setter def ids(self, val): self["ids"] = val # idssrc # ------ @property def idssrc(self): """ Sets the source reference on plot.ly for ids . The 'idssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["idssrc"] @idssrc.setter def idssrc(self, val): self["idssrc"] = val # meta # ---- @property def meta(self): """ Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. The 'meta' property accepts values of any type Returns ------- Any|numpy.ndarray """ return self["meta"] @meta.setter def meta(self, val): self["meta"] = val # metasrc # ------- @property def metasrc(self): """ Sets the source reference on plot.ly for meta . The 'metasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["metasrc"] @metasrc.setter def metasrc(self, val): self["metasrc"] = val # name # ---- @property def name(self): """ Sets the trace name. The trace name appear as the legend item and on hover. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the trace. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # stream # ------ @property def stream(self): """ The 'stream' property is an instance of Stream that may be specified as: - An instance of plotly.graph_objs.image.Stream - A dict of string/value properties that will be passed to the Stream constructor Supported dict properties: maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- plotly.graph_objs.image.Stream """ return self["stream"] @stream.setter def stream(self, val): self["stream"] = val # text # ---- @property def text(self): """ Sets the text elements associated with each z value. The 'text' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["text"] @text.setter def text(self, val): self["text"] = val # textsrc # ------- @property def textsrc(self): """ Sets the source reference on plot.ly for text . The 'textsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["textsrc"] @textsrc.setter def textsrc(self, val): self["textsrc"] = val # uid # --- @property def uid(self): """ Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. The 'uid' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["uid"] @uid.setter def uid(self, val): self["uid"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # visible # ------- @property def visible(self): """ Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). The 'visible' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'legendonly'] Returns ------- Any """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # x0 # -- @property def x0(self): """ Set the image's x position. The 'x0' property accepts values of any type Returns ------- Any """ return self["x0"] @x0.setter def x0(self, val): self["x0"] = val # xaxis # ----- @property def xaxis(self): """ Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. The 'xaxis' property is an identifier of a particular subplot, of type 'x', that may be specified as the string 'x' optionally followed by an integer >= 1 (e.g. 'x', 'x1', 'x2', 'x3', etc.) Returns ------- str """ return self["xaxis"] @xaxis.setter def xaxis(self, val): self["xaxis"] = val # y0 # -- @property def y0(self): """ Set the image's y position. The 'y0' property accepts values of any type Returns ------- Any """ return self["y0"] @y0.setter def y0(self, val): self["y0"] = val # yaxis # ----- @property def yaxis(self): """ Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. The 'yaxis' property is an identifier of a particular subplot, of type 'y', that may be specified as the string 'y' optionally followed by an integer >= 1 (e.g. 'y', 'y1', 'y2', 'y3', etc.) Returns ------- str """ return self["yaxis"] @yaxis.setter def yaxis(self, val): self["yaxis"] = val # z # - @property def z(self): """ A 2-dimensional array in which each element is an array of 3 or 4 numbers representing a color. The 'z' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["z"] @z.setter def z(self, val): self["z"] = val # zmax # ---- @property def zmax(self): """ Array defining the higher bound for each color component. Note that the default value will depend on the colormodel. For the `rgb` colormodel, it is [255, 255, 255]. For the `rgba` colormodel, it is [255, 255, 255, 1]. For the `hsl` colormodel, it is [360, 100, 100]. For the `hsla` colormodel, it is [360, 100, 100, 1]. The 'zmax' property is an info array that may be specified as: * a list or tuple of 4 elements where: (0) The 'zmax[0]' property is a number and may be specified as: - An int or float (1) The 'zmax[1]' property is a number and may be specified as: - An int or float (2) The 'zmax[2]' property is a number and may be specified as: - An int or float (3) The 'zmax[3]' property is a number and may be specified as: - An int or float Returns ------- list """ return self["zmax"] @zmax.setter def zmax(self, val): self["zmax"] = val # zmin # ---- @property def zmin(self): """ Array defining the lower bound for each color component. Note that the default value will depend on the colormodel. For the `rgb` colormodel, it is [0, 0, 0]. For the `rgba` colormodel, it is [0, 0, 0, 0]. For the `hsl` colormodel, it is [0, 0, 0]. For the `hsla` colormodel, it is [0, 0, 0, 0]. The 'zmin' property is an info array that may be specified as: * a list or tuple of 4 elements where: (0) The 'zmin[0]' property is a number and may be specified as: - An int or float (1) The 'zmin[1]' property is a number and may be specified as: - An int or float (2) The 'zmin[2]' property is a number and may be specified as: - An int or float (3) The 'zmin[3]' property is a number and may be specified as: - An int or float Returns ------- list """ return self["zmin"] @zmin.setter def zmin(self, val): self["zmin"] = val # zsrc # ---- @property def zsrc(self): """ Sets the source reference on plot.ly for z . The 'zsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["zsrc"] @zsrc.setter def zsrc(self, val): self["zsrc"] = val # type # ---- @property def type(self): return self._props["type"] # property parent name # -------------------- @property def _parent_path_str(self): return "" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ colormodel Color model used to map the numerical color components described in `z` into colors. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dx Set the pixel's horizontal size. dy Set the pixel's vertical size hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.image.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `z`, `color` and `colormodel`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. stream plotly.graph_objects.image.Stream instance or dict with compatible properties text Sets the text elements associated with each z value. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x0 Set the image's x position. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. y0 Set the image's y position. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. z A 2-dimensional array in which each element is an array of 3 or 4 numbers representing a color. zmax Array defining the higher bound for each color component. Note that the default value will depend on the colormodel. For the `rgb` colormodel, it is [255, 255, 255]. For the `rgba` colormodel, it is [255, 255, 255, 1]. For the `hsl` colormodel, it is [360, 100, 100]. For the `hsla` colormodel, it is [360, 100, 100, 1]. zmin Array defining the lower bound for each color component. Note that the default value will depend on the colormodel. For the `rgb` colormodel, it is [0, 0, 0]. For the `rgba` colormodel, it is [0, 0, 0, 0]. For the `hsl` colormodel, it is [0, 0, 0]. For the `hsla` colormodel, it is [0, 0, 0, 0]. zsrc Sets the source reference on plot.ly for z . """ def __init__( self, arg=None, colormodel=None, customdata=None, customdatasrc=None, dx=None, dy=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, meta=None, metasrc=None, name=None, opacity=None, stream=None, text=None, textsrc=None, uid=None, uirevision=None, visible=None, x0=None, xaxis=None, y0=None, yaxis=None, z=None, zmax=None, zmin=None, zsrc=None, **kwargs ): """ Construct a new Image object Display an image, i.e. data on a 2D regular raster. By default, when an image is displayed in a subplot, its y axis will be reversed (ie. `autorange: 'reversed'`), constrained to the domain (ie. `constrain: 'domain'`) and it will have the same scale as its x axis (ie. `scaleanchor: 'x,`) in order for pixels to be rendered as squares. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.Image colormodel Color model used to map the numerical color components described in `z` into colors. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dx Set the pixel's horizontal size. dy Set the pixel's vertical size hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.image.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `z`, `color` and `colormodel`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. stream plotly.graph_objects.image.Stream instance or dict with compatible properties text Sets the text elements associated with each z value. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x0 Set the image's x position. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. y0 Set the image's y position. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. z A 2-dimensional array in which each element is an array of 3 or 4 numbers representing a color. zmax Array defining the higher bound for each color component. Note that the default value will depend on the colormodel. For the `rgb` colormodel, it is [255, 255, 255]. For the `rgba` colormodel, it is [255, 255, 255, 1]. For the `hsl` colormodel, it is [360, 100, 100]. For the `hsla` colormodel, it is [360, 100, 100, 1]. zmin Array defining the lower bound for each color component. Note that the default value will depend on the colormodel. For the `rgb` colormodel, it is [0, 0, 0]. For the `rgba` colormodel, it is [0, 0, 0, 0]. For the `hsl` colormodel, it is [0, 0, 0]. For the `hsla` colormodel, it is [0, 0, 0, 0]. zsrc Sets the source reference on plot.ly for z . Returns ------- Image """ super(Image, self).__init__("image") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.Image constructor must be a dict or an instance of plotly.graph_objs.Image""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators import image as v_image # Initialize validators # --------------------- self._validators["colormodel"] = v_image.ColormodelValidator() self._validators["customdata"] = v_image.CustomdataValidator() self._validators["customdatasrc"] = v_image.CustomdatasrcValidator() self._validators["dx"] = v_image.DxValidator() self._validators["dy"] = v_image.DyValidator() self._validators["hoverinfo"] = v_image.HoverinfoValidator() self._validators["hoverinfosrc"] = v_image.HoverinfosrcValidator() self._validators["hoverlabel"] = v_image.HoverlabelValidator() self._validators["hovertemplate"] = v_image.HovertemplateValidator() self._validators["hovertemplatesrc"] = v_image.HovertemplatesrcValidator() self._validators["hovertext"] = v_image.HovertextValidator() self._validators["hovertextsrc"] = v_image.HovertextsrcValidator() self._validators["ids"] = v_image.IdsValidator() self._validators["idssrc"] = v_image.IdssrcValidator() self._validators["meta"] = v_image.MetaValidator() self._validators["metasrc"] = v_image.MetasrcValidator() self._validators["name"] = v_image.NameValidator() self._validators["opacity"] = v_image.OpacityValidator() self._validators["stream"] = v_image.StreamValidator() self._validators["text"] = v_image.TextValidator() self._validators["textsrc"] = v_image.TextsrcValidator() self._validators["uid"] = v_image.UidValidator() self._validators["uirevision"] = v_image.UirevisionValidator() self._validators["visible"] = v_image.VisibleValidator() self._validators["x0"] = v_image.X0Validator() self._validators["xaxis"] = v_image.XAxisValidator() self._validators["y0"] = v_image.Y0Validator() self._validators["yaxis"] = v_image.YAxisValidator() self._validators["z"] = v_image.ZValidator() self._validators["zmax"] = v_image.ZmaxValidator() self._validators["zmin"] = v_image.ZminValidator() self._validators["zsrc"] = v_image.ZsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("colormodel", None) self["colormodel"] = colormodel if colormodel is not None else _v _v = arg.pop("customdata", None) self["customdata"] = customdata if customdata is not None else _v _v = arg.pop("customdatasrc", None) self["customdatasrc"] = customdatasrc if customdatasrc is not None else _v _v = arg.pop("dx", None) self["dx"] = dx if dx is not None else _v _v = arg.pop("dy", None) self["dy"] = dy if dy is not None else _v _v = arg.pop("hoverinfo", None) self["hoverinfo"] = hoverinfo if hoverinfo is not None else _v _v = arg.pop("hoverinfosrc", None) self["hoverinfosrc"] = hoverinfosrc if hoverinfosrc is not None else _v _v = arg.pop("hoverlabel", None) self["hoverlabel"] = hoverlabel if hoverlabel is not None else _v _v = arg.pop("hovertemplate", None) self["hovertemplate"] = hovertemplate if hovertemplate is not None else _v _v = arg.pop("hovertemplatesrc", None) self["hovertemplatesrc"] = ( hovertemplatesrc if hovertemplatesrc is not None else _v ) _v = arg.pop("hovertext", None) self["hovertext"] = hovertext if hovertext is not None else _v _v = arg.pop("hovertextsrc", None) self["hovertextsrc"] = hovertextsrc if hovertextsrc is not None else _v _v = arg.pop("ids", None) self["ids"] = ids if ids is not None else _v _v = arg.pop("idssrc", None) self["idssrc"] = idssrc if idssrc is not None else _v _v = arg.pop("meta", None) self["meta"] = meta if meta is not None else _v _v = arg.pop("metasrc", None) self["metasrc"] = metasrc if metasrc is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("stream", None) self["stream"] = stream if stream is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v _v = arg.pop("textsrc", None) self["textsrc"] = textsrc if textsrc is not None else _v _v = arg.pop("uid", None) self["uid"] = uid if uid is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("x0", None) self["x0"] = x0 if x0 is not None else _v _v = arg.pop("xaxis", None) self["xaxis"] = xaxis if xaxis is not None else _v _v = arg.pop("y0", None) self["y0"] = y0 if y0 is not None else _v _v = arg.pop("yaxis", None) self["yaxis"] = yaxis if yaxis is not None else _v _v = arg.pop("z", None) self["z"] = z if z is not None else _v _v = arg.pop("zmax", None) self["zmax"] = zmax if zmax is not None else _v _v = arg.pop("zmin", None) self["zmin"] = zmin if zmin is not None else _v _v = arg.pop("zsrc", None) self["zsrc"] = zsrc if zsrc is not None else _v # Read-only literals # ------------------ from _plotly_utils.basevalidators import LiteralValidator self._props["type"] = "image" self._validators["type"] = LiteralValidator( plotly_name="type", parent_name="image", val="image" ) arg.pop("type", None) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceType as _BaseTraceType import copy as _copy class Histogram2dContour(_BaseTraceType): # autobinx # -------- @property def autobinx(self): """ Obsolete: since v1.42 each bin attribute is auto-determined separately and `autobinx` is not needed. However, we accept `autobinx: true` or `false` and will update `xbins` accordingly before deleting `autobinx` from the trace. The 'autobinx' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autobinx"] @autobinx.setter def autobinx(self, val): self["autobinx"] = val # autobiny # -------- @property def autobiny(self): """ Obsolete: since v1.42 each bin attribute is auto-determined separately and `autobiny` is not needed. However, we accept `autobiny: true` or `false` and will update `ybins` accordingly before deleting `autobiny` from the trace. The 'autobiny' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autobiny"] @autobiny.setter def autobiny(self, val): self["autobiny"] = val # autocolorscale # -------------- @property def autocolorscale(self): """ Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. The 'autocolorscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocolorscale"] @autocolorscale.setter def autocolorscale(self, val): self["autocolorscale"] = val # autocontour # ----------- @property def autocontour(self): """ Determines whether or not the contour level attributes are picked by an algorithm. If True, the number of contour levels can be set in `ncontours`. If False, set the contour level attributes in `contours`. The 'autocontour' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocontour"] @autocontour.setter def autocontour(self, val): self["autocontour"] = val # bingroup # -------- @property def bingroup(self): """ Set the `xbingroup` and `ybingroup` default prefix For example, setting a `bingroup` of 1 on two histogram2d traces will make them their x-bins and y-bins match separately. The 'bingroup' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["bingroup"] @bingroup.setter def bingroup(self, val): self["bingroup"] = val # coloraxis # --------- @property def coloraxis(self): """ Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. The 'coloraxis' property is an identifier of a particular subplot, of type 'coloraxis', that may be specified as the string 'coloraxis' optionally followed by an integer >= 1 (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) Returns ------- str """ return self["coloraxis"] @coloraxis.setter def coloraxis(self, val): self["coloraxis"] = val # colorbar # -------- @property def colorbar(self): """ The 'colorbar' property is an instance of ColorBar that may be specified as: - An instance of plotly.graph_objs.histogram2dcontour.ColorBar - A dict of string/value properties that will be passed to the ColorBar constructor Supported dict properties: bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.histogram2dcont our.colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.histogram2dcontour.colorbar.tickformatstopdef aults), sets the default property values to use for elements of histogram2dcontour.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.histogram2dcontour.colorba r.Title instance or dict with compatible properties titlefont Deprecated: Please use histogram2dcontour.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use histogram2dcontour.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- plotly.graph_objs.histogram2dcontour.ColorBar """ return self["colorbar"] @colorbar.setter def colorbar(self, val): self["colorbar"] = val # colorscale # ---------- @property def colorscale(self): """ Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,Earth,Electric,Vi ridis,Cividis. The 'colorscale' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # contours # -------- @property def contours(self): """ The 'contours' property is an instance of Contours that may be specified as: - An instance of plotly.graph_objs.histogram2dcontour.Contours - A dict of string/value properties that will be passed to the Contours constructor Supported dict properties: coloring Determines the coloring method showing the contour values. If "fill", coloring is done evenly between each contour level If "heatmap", a heatmap gradient coloring is applied between each contour level. If "lines", coloring is done on the contour lines. If "none", no coloring is applied on this trace. end Sets the end contour level value. Must be more than `contours.start` labelfont Sets the font used for labeling the contour levels. The default color comes from the lines, if shown. The default family and size come from `layout.font`. labelformat Sets the contour label formatting rule using d3 formatting mini-language which is very similar to Python, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format operation Sets the constraint operation. "=" keeps regions equal to `value` "<" and "<=" keep regions less than `value` ">" and ">=" keep regions greater than `value` "[]", "()", "[)", and "(]" keep regions inside `value[0]` to `value[1]` "][", ")(", "](", ")[" keep regions outside `value[0]` to value[1]` Open vs. closed intervals make no difference to constraint display, but all versions are allowed for consistency with filter transforms. showlabels Determines whether to label the contour lines with their values. showlines Determines whether or not the contour lines are drawn. Has an effect only if `contours.coloring` is set to "fill". size Sets the step between each contour level. Must be positive. start Sets the starting contour level value. Must be less than `contours.end` type If `levels`, the data is represented as a contour plot with multiple levels displayed. If `constraint`, the data is represented as constraints with the invalid region shaded as specified by the `operation` and `value` parameters. value Sets the value or values of the constraint boundary. When `operation` is set to one of the comparison values (=,<,>=,>,<=) "value" is expected to be a number. When `operation` is set to one of the interval values ([],(),[),(],][,)(,](,)[) "value" is expected to be an array of two numbers where the first is the lower bound and the second is the upper bound. Returns ------- plotly.graph_objs.histogram2dcontour.Contours """ return self["contours"] @contours.setter def contours(self, val): self["contours"] = val # customdata # ---------- @property def customdata(self): """ Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements The 'customdata' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["customdata"] @customdata.setter def customdata(self, val): self["customdata"] = val # customdatasrc # ------------- @property def customdatasrc(self): """ Sets the source reference on plot.ly for customdata . The 'customdatasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["customdatasrc"] @customdatasrc.setter def customdatasrc(self, val): self["customdatasrc"] = val # histfunc # -------- @property def histfunc(self): """ Specifies the binning function used for this histogram trace. If "count", the histogram values are computed by counting the number of values lying inside each bin. If "sum", "avg", "min", "max", the histogram values are computed using the sum, the average, the minimum or the maximum of the values lying inside each bin respectively. The 'histfunc' property is an enumeration that may be specified as: - One of the following enumeration values: ['count', 'sum', 'avg', 'min', 'max'] Returns ------- Any """ return self["histfunc"] @histfunc.setter def histfunc(self, val): self["histfunc"] = val # histnorm # -------- @property def histnorm(self): """ Specifies the type of normalization used for this histogram trace. If "", the span of each bar corresponds to the number of occurrences (i.e. the number of data points lying inside the bins). If "percent" / "probability", the span of each bar corresponds to the percentage / fraction of occurrences with respect to the total number of sample points (here, the sum of all bin HEIGHTS equals 100% / 1). If "density", the span of each bar corresponds to the number of occurrences in a bin divided by the size of the bin interval (here, the sum of all bin AREAS equals the total number of sample points). If *probability density*, the area of each bar corresponds to the probability that an event will fall into the corresponding bin (here, the sum of all bin AREAS equals 1). The 'histnorm' property is an enumeration that may be specified as: - One of the following enumeration values: ['', 'percent', 'probability', 'density', 'probability density'] Returns ------- Any """ return self["histnorm"] @histnorm.setter def histnorm(self, val): self["histnorm"] = val # hoverinfo # --------- @property def hoverinfo(self): """ Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. The 'hoverinfo' property is a flaglist and may be specified as a string containing: - Any combination of ['x', 'y', 'z', 'text', 'name'] joined with '+' characters (e.g. 'x+y') OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') - A list or array of the above Returns ------- Any|numpy.ndarray """ return self["hoverinfo"] @hoverinfo.setter def hoverinfo(self, val): self["hoverinfo"] = val # hoverinfosrc # ------------ @property def hoverinfosrc(self): """ Sets the source reference on plot.ly for hoverinfo . The 'hoverinfosrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hoverinfosrc"] @hoverinfosrc.setter def hoverinfosrc(self, val): self["hoverinfosrc"] = val # hoverlabel # ---------- @property def hoverlabel(self): """ The 'hoverlabel' property is an instance of Hoverlabel that may be specified as: - An instance of plotly.graph_objs.histogram2dcontour.Hoverlabel - A dict of string/value properties that will be passed to the Hoverlabel constructor Supported dict properties: align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- plotly.graph_objs.histogram2dcontour.Hoverlabel """ return self["hoverlabel"] @hoverlabel.setter def hoverlabel(self, val): self["hoverlabel"] = val # hovertemplate # ------------- @property def hovertemplate(self): """ Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event- data. Additionally, every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. variable `z` Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. The 'hovertemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertemplate"] @hovertemplate.setter def hovertemplate(self, val): self["hovertemplate"] = val # hovertemplatesrc # ---------------- @property def hovertemplatesrc(self): """ Sets the source reference on plot.ly for hovertemplate . The 'hovertemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertemplatesrc"] @hovertemplatesrc.setter def hovertemplatesrc(self, val): self["hovertemplatesrc"] = val # ids # --- @property def ids(self): """ Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. The 'ids' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ids"] @ids.setter def ids(self, val): self["ids"] = val # idssrc # ------ @property def idssrc(self): """ Sets the source reference on plot.ly for ids . The 'idssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["idssrc"] @idssrc.setter def idssrc(self, val): self["idssrc"] = val # legendgroup # ----------- @property def legendgroup(self): """ Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. The 'legendgroup' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["legendgroup"] @legendgroup.setter def legendgroup(self, val): self["legendgroup"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.histogram2dcontour.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: color Sets the color of the contour level. Has no effect if `contours.coloring` is set to "lines". dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). smoothing Sets the amount of smoothing for the contour lines, where 0 corresponds to no smoothing. width Sets the contour line width in (in px) Returns ------- plotly.graph_objs.histogram2dcontour.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.histogram2dcontour.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: color Sets the aggregation data. colorsrc Sets the source reference on plot.ly for color . Returns ------- plotly.graph_objs.histogram2dcontour.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # meta # ---- @property def meta(self): """ Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. The 'meta' property accepts values of any type Returns ------- Any|numpy.ndarray """ return self["meta"] @meta.setter def meta(self, val): self["meta"] = val # metasrc # ------- @property def metasrc(self): """ Sets the source reference on plot.ly for meta . The 'metasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["metasrc"] @metasrc.setter def metasrc(self, val): self["metasrc"] = val # name # ---- @property def name(self): """ Sets the trace name. The trace name appear as the legend item and on hover. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # nbinsx # ------ @property def nbinsx(self): """ Specifies the maximum number of desired bins. This value will be used in an algorithm that will decide the optimal bin size such that the histogram best visualizes the distribution of the data. Ignored if `xbins.size` is provided. The 'nbinsx' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nbinsx"] @nbinsx.setter def nbinsx(self, val): self["nbinsx"] = val # nbinsy # ------ @property def nbinsy(self): """ Specifies the maximum number of desired bins. This value will be used in an algorithm that will decide the optimal bin size such that the histogram best visualizes the distribution of the data. Ignored if `ybins.size` is provided. The 'nbinsy' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nbinsy"] @nbinsy.setter def nbinsy(self, val): self["nbinsy"] = val # ncontours # --------- @property def ncontours(self): """ Sets the maximum number of contour levels. The actual number of contours will be chosen automatically to be less than or equal to the value of `ncontours`. Has an effect only if `autocontour` is True or if `contours.size` is missing. The 'ncontours' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [1, 9223372036854775807] Returns ------- int """ return self["ncontours"] @ncontours.setter def ncontours(self, val): self["ncontours"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the trace. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # reversescale # ------------ @property def reversescale(self): """ Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. The 'reversescale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["reversescale"] @reversescale.setter def reversescale(self, val): self["reversescale"] = val # showlegend # ---------- @property def showlegend(self): """ Determines whether or not an item corresponding to this trace is shown in the legend. The 'showlegend' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showlegend"] @showlegend.setter def showlegend(self, val): self["showlegend"] = val # showscale # --------- @property def showscale(self): """ Determines whether or not a colorbar is displayed for this trace. The 'showscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showscale"] @showscale.setter def showscale(self, val): self["showscale"] = val # stream # ------ @property def stream(self): """ The 'stream' property is an instance of Stream that may be specified as: - An instance of plotly.graph_objs.histogram2dcontour.Stream - A dict of string/value properties that will be passed to the Stream constructor Supported dict properties: maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- plotly.graph_objs.histogram2dcontour.Stream """ return self["stream"] @stream.setter def stream(self, val): self["stream"] = val # uid # --- @property def uid(self): """ Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. The 'uid' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["uid"] @uid.setter def uid(self, val): self["uid"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # visible # ------- @property def visible(self): """ Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). The 'visible' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'legendonly'] Returns ------- Any """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # x # - @property def x(self): """ Sets the sample data to be binned on the x axis. The 'x' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["x"] @x.setter def x(self, val): self["x"] = val # xaxis # ----- @property def xaxis(self): """ Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. The 'xaxis' property is an identifier of a particular subplot, of type 'x', that may be specified as the string 'x' optionally followed by an integer >= 1 (e.g. 'x', 'x1', 'x2', 'x3', etc.) Returns ------- str """ return self["xaxis"] @xaxis.setter def xaxis(self, val): self["xaxis"] = val # xbingroup # --------- @property def xbingroup(self): """ Set a group of histogram traces which will have compatible x-bin settings. Using `xbingroup`, histogram2d and histogram2dcontour traces (on axes of the same axis type) can have compatible x-bin settings. Note that the same `xbingroup` value can be used to set (1D) histogram `bingroup` The 'xbingroup' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["xbingroup"] @xbingroup.setter def xbingroup(self, val): self["xbingroup"] = val # xbins # ----- @property def xbins(self): """ The 'xbins' property is an instance of XBins that may be specified as: - An instance of plotly.graph_objs.histogram2dcontour.XBins - A dict of string/value properties that will be passed to the XBins constructor Supported dict properties: end Sets the end value for the x axis bins. The last bin may not end exactly at this value, we increment the bin edge by `size` from `start` until we reach or exceed `end`. Defaults to the maximum data value. Like `start`, for dates use a date string, and for category data `end` is based on the category serial numbers. size Sets the size of each x axis bin. Default behavior: If `nbinsx` is 0 or omitted, we choose a nice round bin size such that the number of bins is about the same as the typical number of samples in each bin. If `nbinsx` is provided, we choose a nice round bin size giving no more than that many bins. For date data, use milliseconds or "M" for months, as in `axis.dtick`. For category data, the number of categories to bin together (always defaults to 1). start Sets the starting value for the x axis bins. Defaults to the minimum data value, shifted down if necessary to make nice round values and to remove ambiguous bin edges. For example, if most of the data is integers we shift the bin edges 0.5 down, so a `size` of 5 would have a default `start` of -0.5, so it is clear that 0-4 are in the first bin, 5-9 in the second, but continuous data gets a start of 0 and bins [0,5), [5,10) etc. Dates behave similarly, and `start` should be a date string. For category data, `start` is based on the category serial numbers, and defaults to -0.5. Returns ------- plotly.graph_objs.histogram2dcontour.XBins """ return self["xbins"] @xbins.setter def xbins(self, val): self["xbins"] = val # xcalendar # --------- @property def xcalendar(self): """ Sets the calendar system to use with `x` date data. The 'xcalendar' property is an enumeration that may be specified as: - One of the following enumeration values: ['gregorian', 'chinese', 'coptic', 'discworld', 'ethiopian', 'hebrew', 'islamic', 'julian', 'mayan', 'nanakshahi', 'nepali', 'persian', 'jalali', 'taiwan', 'thai', 'ummalqura'] Returns ------- Any """ return self["xcalendar"] @xcalendar.setter def xcalendar(self, val): self["xcalendar"] = val # xsrc # ---- @property def xsrc(self): """ Sets the source reference on plot.ly for x . The 'xsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["xsrc"] @xsrc.setter def xsrc(self, val): self["xsrc"] = val # y # - @property def y(self): """ Sets the sample data to be binned on the y axis. The 'y' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["y"] @y.setter def y(self, val): self["y"] = val # yaxis # ----- @property def yaxis(self): """ Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. The 'yaxis' property is an identifier of a particular subplot, of type 'y', that may be specified as the string 'y' optionally followed by an integer >= 1 (e.g. 'y', 'y1', 'y2', 'y3', etc.) Returns ------- str """ return self["yaxis"] @yaxis.setter def yaxis(self, val): self["yaxis"] = val # ybingroup # --------- @property def ybingroup(self): """ Set a group of histogram traces which will have compatible y-bin settings. Using `ybingroup`, histogram2d and histogram2dcontour traces (on axes of the same axis type) can have compatible y-bin settings. Note that the same `ybingroup` value can be used to set (1D) histogram `bingroup` The 'ybingroup' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ybingroup"] @ybingroup.setter def ybingroup(self, val): self["ybingroup"] = val # ybins # ----- @property def ybins(self): """ The 'ybins' property is an instance of YBins that may be specified as: - An instance of plotly.graph_objs.histogram2dcontour.YBins - A dict of string/value properties that will be passed to the YBins constructor Supported dict properties: end Sets the end value for the y axis bins. The last bin may not end exactly at this value, we increment the bin edge by `size` from `start` until we reach or exceed `end`. Defaults to the maximum data value. Like `start`, for dates use a date string, and for category data `end` is based on the category serial numbers. size Sets the size of each y axis bin. Default behavior: If `nbinsy` is 0 or omitted, we choose a nice round bin size such that the number of bins is about the same as the typical number of samples in each bin. If `nbinsy` is provided, we choose a nice round bin size giving no more than that many bins. For date data, use milliseconds or "M" for months, as in `axis.dtick`. For category data, the number of categories to bin together (always defaults to 1). start Sets the starting value for the y axis bins. Defaults to the minimum data value, shifted down if necessary to make nice round values and to remove ambiguous bin edges. For example, if most of the data is integers we shift the bin edges 0.5 down, so a `size` of 5 would have a default `start` of -0.5, so it is clear that 0-4 are in the first bin, 5-9 in the second, but continuous data gets a start of 0 and bins [0,5), [5,10) etc. Dates behave similarly, and `start` should be a date string. For category data, `start` is based on the category serial numbers, and defaults to -0.5. Returns ------- plotly.graph_objs.histogram2dcontour.YBins """ return self["ybins"] @ybins.setter def ybins(self, val): self["ybins"] = val # ycalendar # --------- @property def ycalendar(self): """ Sets the calendar system to use with `y` date data. The 'ycalendar' property is an enumeration that may be specified as: - One of the following enumeration values: ['gregorian', 'chinese', 'coptic', 'discworld', 'ethiopian', 'hebrew', 'islamic', 'julian', 'mayan', 'nanakshahi', 'nepali', 'persian', 'jalali', 'taiwan', 'thai', 'ummalqura'] Returns ------- Any """ return self["ycalendar"] @ycalendar.setter def ycalendar(self, val): self["ycalendar"] = val # ysrc # ---- @property def ysrc(self): """ Sets the source reference on plot.ly for y . The 'ysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ysrc"] @ysrc.setter def ysrc(self, val): self["ysrc"] = val # z # - @property def z(self): """ Sets the aggregation data. The 'z' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["z"] @z.setter def z(self, val): self["z"] = val # zauto # ----- @property def zauto(self): """ Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. The 'zauto' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["zauto"] @zauto.setter def zauto(self, val): self["zauto"] = val # zhoverformat # ------------ @property def zhoverformat(self): """ Sets the hover text formatting rule using d3 formatting mini- languages which are very similar to those in Python. See: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format The 'zhoverformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["zhoverformat"] @zhoverformat.setter def zhoverformat(self, val): self["zhoverformat"] = val # zmax # ---- @property def zmax(self): """ Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. The 'zmax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["zmax"] @zmax.setter def zmax(self, val): self["zmax"] = val # zmid # ---- @property def zmid(self): """ Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. The 'zmid' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["zmid"] @zmid.setter def zmid(self, val): self["zmid"] = val # zmin # ---- @property def zmin(self): """ Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. The 'zmin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["zmin"] @zmin.setter def zmin(self, val): self["zmin"] = val # zsrc # ---- @property def zsrc(self): """ Sets the source reference on plot.ly for z . The 'zsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["zsrc"] @zsrc.setter def zsrc(self, val): self["zsrc"] = val # type # ---- @property def type(self): return self._props["type"] # property parent name # -------------------- @property def _parent_path_str(self): return "" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autobinx Obsolete: since v1.42 each bin attribute is auto- determined separately and `autobinx` is not needed. However, we accept `autobinx: true` or `false` and will update `xbins` accordingly before deleting `autobinx` from the trace. autobiny Obsolete: since v1.42 each bin attribute is auto- determined separately and `autobiny` is not needed. However, we accept `autobiny: true` or `false` and will update `ybins` accordingly before deleting `autobiny` from the trace. autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. autocontour Determines whether or not the contour level attributes are picked by an algorithm. If True, the number of contour levels can be set in `ncontours`. If False, set the contour level attributes in `contours`. bingroup Set the `xbingroup` and `ybingroup` default prefix For example, setting a `bingroup` of 1 on two histogram2d traces will make them their x-bins and y-bins match separately. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.histogram2dcontour.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. contours plotly.graph_objects.histogram2dcontour.Contours instance or dict with compatible properties customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . histfunc Specifies the binning function used for this histogram trace. If "count", the histogram values are computed by counting the number of values lying inside each bin. If "sum", "avg", "min", "max", the histogram values are computed using the sum, the average, the minimum or the maximum of the values lying inside each bin respectively. histnorm Specifies the type of normalization used for this histogram trace. If "", the span of each bar corresponds to the number of occurrences (i.e. the number of data points lying inside the bins). If "percent" / "probability", the span of each bar corresponds to the percentage / fraction of occurrences with respect to the total number of sample points (here, the sum of all bin HEIGHTS equals 100% / 1). If "density", the span of each bar corresponds to the number of occurrences in a bin divided by the size of the bin interval (here, the sum of all bin AREAS equals the total number of sample points). If *probability density*, the area of each bar corresponds to the probability that an event will fall into the corresponding bin (here, the sum of all bin AREAS equals 1). hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.histogram2dcontour.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variable `z` Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.histogram2dcontour.Line instance or dict with compatible properties marker plotly.graph_objects.histogram2dcontour.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. nbinsx Specifies the maximum number of desired bins. This value will be used in an algorithm that will decide the optimal bin size such that the histogram best visualizes the distribution of the data. Ignored if `xbins.size` is provided. nbinsy Specifies the maximum number of desired bins. This value will be used in an algorithm that will decide the optimal bin size such that the histogram best visualizes the distribution of the data. Ignored if `ybins.size` is provided. ncontours Sets the maximum number of contour levels. The actual number of contours will be chosen automatically to be less than or equal to the value of `ncontours`. Has an effect only if `autocontour` is True or if `contours.size` is missing. opacity Sets the opacity of the trace. reversescale Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.histogram2dcontour.Stream instance or dict with compatible properties uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the sample data to be binned on the x axis. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xbingroup Set a group of histogram traces which will have compatible x-bin settings. Using `xbingroup`, histogram2d and histogram2dcontour traces (on axes of the same axis type) can have compatible x-bin settings. Note that the same `xbingroup` value can be used to set (1D) histogram `bingroup` xbins plotly.graph_objects.histogram2dcontour.XBins instance or dict with compatible properties xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . y Sets the sample data to be binned on the y axis. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ybingroup Set a group of histogram traces which will have compatible y-bin settings. Using `ybingroup`, histogram2d and histogram2dcontour traces (on axes of the same axis type) can have compatible y-bin settings. Note that the same `ybingroup` value can be used to set (1D) histogram `bingroup` ybins plotly.graph_objects.histogram2dcontour.YBins instance or dict with compatible properties ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . z Sets the aggregation data. zauto Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. zhoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. See: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format zmax Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. zmid Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. zmin Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. zsrc Sets the source reference on plot.ly for z . """ def __init__( self, arg=None, autobinx=None, autobiny=None, autocolorscale=None, autocontour=None, bingroup=None, coloraxis=None, colorbar=None, colorscale=None, contours=None, customdata=None, customdatasrc=None, histfunc=None, histnorm=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, ids=None, idssrc=None, legendgroup=None, line=None, marker=None, meta=None, metasrc=None, name=None, nbinsx=None, nbinsy=None, ncontours=None, opacity=None, reversescale=None, showlegend=None, showscale=None, stream=None, uid=None, uirevision=None, visible=None, x=None, xaxis=None, xbingroup=None, xbins=None, xcalendar=None, xsrc=None, y=None, yaxis=None, ybingroup=None, ybins=None, ycalendar=None, ysrc=None, z=None, zauto=None, zhoverformat=None, zmax=None, zmid=None, zmin=None, zsrc=None, **kwargs ): """ Construct a new Histogram2dContour object The sample data from which statistics are computed is set in `x` and `y` (where `x` and `y` represent marginal distributions, binning is set in `xbins` and `ybins` in this case) or `z` (where `z` represent the 2D distribution and binning set, binning is set by `x` and `y` in this case). The resulting distribution is visualized as a contour plot. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.Histogram2dContour autobinx Obsolete: since v1.42 each bin attribute is auto- determined separately and `autobinx` is not needed. However, we accept `autobinx: true` or `false` and will update `xbins` accordingly before deleting `autobinx` from the trace. autobiny Obsolete: since v1.42 each bin attribute is auto- determined separately and `autobiny` is not needed. However, we accept `autobiny: true` or `false` and will update `ybins` accordingly before deleting `autobiny` from the trace. autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. autocontour Determines whether or not the contour level attributes are picked by an algorithm. If True, the number of contour levels can be set in `ncontours`. If False, set the contour level attributes in `contours`. bingroup Set the `xbingroup` and `ybingroup` default prefix For example, setting a `bingroup` of 1 on two histogram2d traces will make them their x-bins and y-bins match separately. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.histogram2dcontour.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. contours plotly.graph_objects.histogram2dcontour.Contours instance or dict with compatible properties customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . histfunc Specifies the binning function used for this histogram trace. If "count", the histogram values are computed by counting the number of values lying inside each bin. If "sum", "avg", "min", "max", the histogram values are computed using the sum, the average, the minimum or the maximum of the values lying inside each bin respectively. histnorm Specifies the type of normalization used for this histogram trace. If "", the span of each bar corresponds to the number of occurrences (i.e. the number of data points lying inside the bins). If "percent" / "probability", the span of each bar corresponds to the percentage / fraction of occurrences with respect to the total number of sample points (here, the sum of all bin HEIGHTS equals 100% / 1). If "density", the span of each bar corresponds to the number of occurrences in a bin divided by the size of the bin interval (here, the sum of all bin AREAS equals the total number of sample points). If *probability density*, the area of each bar corresponds to the probability that an event will fall into the corresponding bin (here, the sum of all bin AREAS equals 1). hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.histogram2dcontour.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variable `z` Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.histogram2dcontour.Line instance or dict with compatible properties marker plotly.graph_objects.histogram2dcontour.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. nbinsx Specifies the maximum number of desired bins. This value will be used in an algorithm that will decide the optimal bin size such that the histogram best visualizes the distribution of the data. Ignored if `xbins.size` is provided. nbinsy Specifies the maximum number of desired bins. This value will be used in an algorithm that will decide the optimal bin size such that the histogram best visualizes the distribution of the data. Ignored if `ybins.size` is provided. ncontours Sets the maximum number of contour levels. The actual number of contours will be chosen automatically to be less than or equal to the value of `ncontours`. Has an effect only if `autocontour` is True or if `contours.size` is missing. opacity Sets the opacity of the trace. reversescale Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.histogram2dcontour.Stream instance or dict with compatible properties uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the sample data to be binned on the x axis. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xbingroup Set a group of histogram traces which will have compatible x-bin settings. Using `xbingroup`, histogram2d and histogram2dcontour traces (on axes of the same axis type) can have compatible x-bin settings. Note that the same `xbingroup` value can be used to set (1D) histogram `bingroup` xbins plotly.graph_objects.histogram2dcontour.XBins instance or dict with compatible properties xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . y Sets the sample data to be binned on the y axis. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ybingroup Set a group of histogram traces which will have compatible y-bin settings. Using `ybingroup`, histogram2d and histogram2dcontour traces (on axes of the same axis type) can have compatible y-bin settings. Note that the same `ybingroup` value can be used to set (1D) histogram `bingroup` ybins plotly.graph_objects.histogram2dcontour.YBins instance or dict with compatible properties ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . z Sets the aggregation data. zauto Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. zhoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. See: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format zmax Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. zmid Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. zmin Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. zsrc Sets the source reference on plot.ly for z . Returns ------- Histogram2dContour """ super(Histogram2dContour, self).__init__("histogram2dcontour") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.Histogram2dContour constructor must be a dict or an instance of plotly.graph_objs.Histogram2dContour""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators import histogram2dcontour as v_histogram2dcontour # Initialize validators # --------------------- self._validators["autobinx"] = v_histogram2dcontour.AutobinxValidator() self._validators["autobiny"] = v_histogram2dcontour.AutobinyValidator() self._validators[ "autocolorscale" ] = v_histogram2dcontour.AutocolorscaleValidator() self._validators["autocontour"] = v_histogram2dcontour.AutocontourValidator() self._validators["bingroup"] = v_histogram2dcontour.BingroupValidator() self._validators["coloraxis"] = v_histogram2dcontour.ColoraxisValidator() self._validators["colorbar"] = v_histogram2dcontour.ColorBarValidator() self._validators["colorscale"] = v_histogram2dcontour.ColorscaleValidator() self._validators["contours"] = v_histogram2dcontour.ContoursValidator() self._validators["customdata"] = v_histogram2dcontour.CustomdataValidator() self._validators[ "customdatasrc" ] = v_histogram2dcontour.CustomdatasrcValidator() self._validators["histfunc"] = v_histogram2dcontour.HistfuncValidator() self._validators["histnorm"] = v_histogram2dcontour.HistnormValidator() self._validators["hoverinfo"] = v_histogram2dcontour.HoverinfoValidator() self._validators["hoverinfosrc"] = v_histogram2dcontour.HoverinfosrcValidator() self._validators["hoverlabel"] = v_histogram2dcontour.HoverlabelValidator() self._validators[ "hovertemplate" ] = v_histogram2dcontour.HovertemplateValidator() self._validators[ "hovertemplatesrc" ] = v_histogram2dcontour.HovertemplatesrcValidator() self._validators["ids"] = v_histogram2dcontour.IdsValidator() self._validators["idssrc"] = v_histogram2dcontour.IdssrcValidator() self._validators["legendgroup"] = v_histogram2dcontour.LegendgroupValidator() self._validators["line"] = v_histogram2dcontour.LineValidator() self._validators["marker"] = v_histogram2dcontour.MarkerValidator() self._validators["meta"] = v_histogram2dcontour.MetaValidator() self._validators["metasrc"] = v_histogram2dcontour.MetasrcValidator() self._validators["name"] = v_histogram2dcontour.NameValidator() self._validators["nbinsx"] = v_histogram2dcontour.NbinsxValidator() self._validators["nbinsy"] = v_histogram2dcontour.NbinsyValidator() self._validators["ncontours"] = v_histogram2dcontour.NcontoursValidator() self._validators["opacity"] = v_histogram2dcontour.OpacityValidator() self._validators["reversescale"] = v_histogram2dcontour.ReversescaleValidator() self._validators["showlegend"] = v_histogram2dcontour.ShowlegendValidator() self._validators["showscale"] = v_histogram2dcontour.ShowscaleValidator() self._validators["stream"] = v_histogram2dcontour.StreamValidator() self._validators["uid"] = v_histogram2dcontour.UidValidator() self._validators["uirevision"] = v_histogram2dcontour.UirevisionValidator() self._validators["visible"] = v_histogram2dcontour.VisibleValidator() self._validators["x"] = v_histogram2dcontour.XValidator() self._validators["xaxis"] = v_histogram2dcontour.XAxisValidator() self._validators["xbingroup"] = v_histogram2dcontour.XbingroupValidator() self._validators["xbins"] = v_histogram2dcontour.XBinsValidator() self._validators["xcalendar"] = v_histogram2dcontour.XcalendarValidator() self._validators["xsrc"] = v_histogram2dcontour.XsrcValidator() self._validators["y"] = v_histogram2dcontour.YValidator() self._validators["yaxis"] = v_histogram2dcontour.YAxisValidator() self._validators["ybingroup"] = v_histogram2dcontour.YbingroupValidator() self._validators["ybins"] = v_histogram2dcontour.YBinsValidator() self._validators["ycalendar"] = v_histogram2dcontour.YcalendarValidator() self._validators["ysrc"] = v_histogram2dcontour.YsrcValidator() self._validators["z"] = v_histogram2dcontour.ZValidator() self._validators["zauto"] = v_histogram2dcontour.ZautoValidator() self._validators["zhoverformat"] = v_histogram2dcontour.ZhoverformatValidator() self._validators["zmax"] = v_histogram2dcontour.ZmaxValidator() self._validators["zmid"] = v_histogram2dcontour.ZmidValidator() self._validators["zmin"] = v_histogram2dcontour.ZminValidator() self._validators["zsrc"] = v_histogram2dcontour.ZsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autobinx", None) self["autobinx"] = autobinx if autobinx is not None else _v _v = arg.pop("autobiny", None) self["autobiny"] = autobiny if autobiny is not None else _v _v = arg.pop("autocolorscale", None) self["autocolorscale"] = autocolorscale if autocolorscale is not None else _v _v = arg.pop("autocontour", None) self["autocontour"] = autocontour if autocontour is not None else _v _v = arg.pop("bingroup", None) self["bingroup"] = bingroup if bingroup is not None else _v _v = arg.pop("coloraxis", None) self["coloraxis"] = coloraxis if coloraxis is not None else _v _v = arg.pop("colorbar", None) self["colorbar"] = colorbar if colorbar is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("contours", None) self["contours"] = contours if contours is not None else _v _v = arg.pop("customdata", None) self["customdata"] = customdata if customdata is not None else _v _v = arg.pop("customdatasrc", None) self["customdatasrc"] = customdatasrc if customdatasrc is not None else _v _v = arg.pop("histfunc", None) self["histfunc"] = histfunc if histfunc is not None else _v _v = arg.pop("histnorm", None) self["histnorm"] = histnorm if histnorm is not None else _v _v = arg.pop("hoverinfo", None) self["hoverinfo"] = hoverinfo if hoverinfo is not None else _v _v = arg.pop("hoverinfosrc", None) self["hoverinfosrc"] = hoverinfosrc if hoverinfosrc is not None else _v _v = arg.pop("hoverlabel", None) self["hoverlabel"] = hoverlabel if hoverlabel is not None else _v _v = arg.pop("hovertemplate", None) self["hovertemplate"] = hovertemplate if hovertemplate is not None else _v _v = arg.pop("hovertemplatesrc", None) self["hovertemplatesrc"] = ( hovertemplatesrc if hovertemplatesrc is not None else _v ) _v = arg.pop("ids", None) self["ids"] = ids if ids is not None else _v _v = arg.pop("idssrc", None) self["idssrc"] = idssrc if idssrc is not None else _v _v = arg.pop("legendgroup", None) self["legendgroup"] = legendgroup if legendgroup is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v _v = arg.pop("meta", None) self["meta"] = meta if meta is not None else _v _v = arg.pop("metasrc", None) self["metasrc"] = metasrc if metasrc is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("nbinsx", None) self["nbinsx"] = nbinsx if nbinsx is not None else _v _v = arg.pop("nbinsy", None) self["nbinsy"] = nbinsy if nbinsy is not None else _v _v = arg.pop("ncontours", None) self["ncontours"] = ncontours if ncontours is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("reversescale", None) self["reversescale"] = reversescale if reversescale is not None else _v _v = arg.pop("showlegend", None) self["showlegend"] = showlegend if showlegend is not None else _v _v = arg.pop("showscale", None) self["showscale"] = showscale if showscale is not None else _v _v = arg.pop("stream", None) self["stream"] = stream if stream is not None else _v _v = arg.pop("uid", None) self["uid"] = uid if uid is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xaxis", None) self["xaxis"] = xaxis if xaxis is not None else _v _v = arg.pop("xbingroup", None) self["xbingroup"] = xbingroup if xbingroup is not None else _v _v = arg.pop("xbins", None) self["xbins"] = xbins if xbins is not None else _v _v = arg.pop("xcalendar", None) self["xcalendar"] = xcalendar if xcalendar is not None else _v _v = arg.pop("xsrc", None) self["xsrc"] = xsrc if xsrc is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("yaxis", None) self["yaxis"] = yaxis if yaxis is not None else _v _v = arg.pop("ybingroup", None) self["ybingroup"] = ybingroup if ybingroup is not None else _v _v = arg.pop("ybins", None) self["ybins"] = ybins if ybins is not None else _v _v = arg.pop("ycalendar", None) self["ycalendar"] = ycalendar if ycalendar is not None else _v _v = arg.pop("ysrc", None) self["ysrc"] = ysrc if ysrc is not None else _v _v = arg.pop("z", None) self["z"] = z if z is not None else _v _v = arg.pop("zauto", None) self["zauto"] = zauto if zauto is not None else _v _v = arg.pop("zhoverformat", None) self["zhoverformat"] = zhoverformat if zhoverformat is not None else _v _v = arg.pop("zmax", None) self["zmax"] = zmax if zmax is not None else _v _v = arg.pop("zmid", None) self["zmid"] = zmid if zmid is not None else _v _v = arg.pop("zmin", None) self["zmin"] = zmin if zmin is not None else _v _v = arg.pop("zsrc", None) self["zsrc"] = zsrc if zsrc is not None else _v # Read-only literals # ------------------ from _plotly_utils.basevalidators import LiteralValidator self._props["type"] = "histogram2dcontour" self._validators["type"] = LiteralValidator( plotly_name="type", parent_name="histogram2dcontour", val="histogram2dcontour", ) arg.pop("type", None) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceType as _BaseTraceType import copy as _copy class Histogram2d(_BaseTraceType): # autobinx # -------- @property def autobinx(self): """ Obsolete: since v1.42 each bin attribute is auto-determined separately and `autobinx` is not needed. However, we accept `autobinx: true` or `false` and will update `xbins` accordingly before deleting `autobinx` from the trace. The 'autobinx' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autobinx"] @autobinx.setter def autobinx(self, val): self["autobinx"] = val # autobiny # -------- @property def autobiny(self): """ Obsolete: since v1.42 each bin attribute is auto-determined separately and `autobiny` is not needed. However, we accept `autobiny: true` or `false` and will update `ybins` accordingly before deleting `autobiny` from the trace. The 'autobiny' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autobiny"] @autobiny.setter def autobiny(self, val): self["autobiny"] = val # autocolorscale # -------------- @property def autocolorscale(self): """ Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. The 'autocolorscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocolorscale"] @autocolorscale.setter def autocolorscale(self, val): self["autocolorscale"] = val # bingroup # -------- @property def bingroup(self): """ Set the `xbingroup` and `ybingroup` default prefix For example, setting a `bingroup` of 1 on two histogram2d traces will make them their x-bins and y-bins match separately. The 'bingroup' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["bingroup"] @bingroup.setter def bingroup(self, val): self["bingroup"] = val # coloraxis # --------- @property def coloraxis(self): """ Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. The 'coloraxis' property is an identifier of a particular subplot, of type 'coloraxis', that may be specified as the string 'coloraxis' optionally followed by an integer >= 1 (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) Returns ------- str """ return self["coloraxis"] @coloraxis.setter def coloraxis(self, val): self["coloraxis"] = val # colorbar # -------- @property def colorbar(self): """ The 'colorbar' property is an instance of ColorBar that may be specified as: - An instance of plotly.graph_objs.histogram2d.ColorBar - A dict of string/value properties that will be passed to the ColorBar constructor Supported dict properties: bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.histogram2d.col orbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.histogram2d.colorbar.tickformatstopdefaults), sets the default property values to use for elements of histogram2d.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.histogram2d.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use histogram2d.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use histogram2d.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- plotly.graph_objs.histogram2d.ColorBar """ return self["colorbar"] @colorbar.setter def colorbar(self, val): self["colorbar"] = val # colorscale # ---------- @property def colorscale(self): """ Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,Earth,Electric,Vi ridis,Cividis. The 'colorscale' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # customdata # ---------- @property def customdata(self): """ Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements The 'customdata' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["customdata"] @customdata.setter def customdata(self, val): self["customdata"] = val # customdatasrc # ------------- @property def customdatasrc(self): """ Sets the source reference on plot.ly for customdata . The 'customdatasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["customdatasrc"] @customdatasrc.setter def customdatasrc(self, val): self["customdatasrc"] = val # histfunc # -------- @property def histfunc(self): """ Specifies the binning function used for this histogram trace. If "count", the histogram values are computed by counting the number of values lying inside each bin. If "sum", "avg", "min", "max", the histogram values are computed using the sum, the average, the minimum or the maximum of the values lying inside each bin respectively. The 'histfunc' property is an enumeration that may be specified as: - One of the following enumeration values: ['count', 'sum', 'avg', 'min', 'max'] Returns ------- Any """ return self["histfunc"] @histfunc.setter def histfunc(self, val): self["histfunc"] = val # histnorm # -------- @property def histnorm(self): """ Specifies the type of normalization used for this histogram trace. If "", the span of each bar corresponds to the number of occurrences (i.e. the number of data points lying inside the bins). If "percent" / "probability", the span of each bar corresponds to the percentage / fraction of occurrences with respect to the total number of sample points (here, the sum of all bin HEIGHTS equals 100% / 1). If "density", the span of each bar corresponds to the number of occurrences in a bin divided by the size of the bin interval (here, the sum of all bin AREAS equals the total number of sample points). If *probability density*, the area of each bar corresponds to the probability that an event will fall into the corresponding bin (here, the sum of all bin AREAS equals 1). The 'histnorm' property is an enumeration that may be specified as: - One of the following enumeration values: ['', 'percent', 'probability', 'density', 'probability density'] Returns ------- Any """ return self["histnorm"] @histnorm.setter def histnorm(self, val): self["histnorm"] = val # hoverinfo # --------- @property def hoverinfo(self): """ Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. The 'hoverinfo' property is a flaglist and may be specified as a string containing: - Any combination of ['x', 'y', 'z', 'text', 'name'] joined with '+' characters (e.g. 'x+y') OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') - A list or array of the above Returns ------- Any|numpy.ndarray """ return self["hoverinfo"] @hoverinfo.setter def hoverinfo(self, val): self["hoverinfo"] = val # hoverinfosrc # ------------ @property def hoverinfosrc(self): """ Sets the source reference on plot.ly for hoverinfo . The 'hoverinfosrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hoverinfosrc"] @hoverinfosrc.setter def hoverinfosrc(self, val): self["hoverinfosrc"] = val # hoverlabel # ---------- @property def hoverlabel(self): """ The 'hoverlabel' property is an instance of Hoverlabel that may be specified as: - An instance of plotly.graph_objs.histogram2d.Hoverlabel - A dict of string/value properties that will be passed to the Hoverlabel constructor Supported dict properties: align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- plotly.graph_objs.histogram2d.Hoverlabel """ return self["hoverlabel"] @hoverlabel.setter def hoverlabel(self, val): self["hoverlabel"] = val # hovertemplate # ------------- @property def hovertemplate(self): """ Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event- data. Additionally, every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. variable `z` Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. The 'hovertemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertemplate"] @hovertemplate.setter def hovertemplate(self, val): self["hovertemplate"] = val # hovertemplatesrc # ---------------- @property def hovertemplatesrc(self): """ Sets the source reference on plot.ly for hovertemplate . The 'hovertemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertemplatesrc"] @hovertemplatesrc.setter def hovertemplatesrc(self, val): self["hovertemplatesrc"] = val # ids # --- @property def ids(self): """ Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. The 'ids' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ids"] @ids.setter def ids(self, val): self["ids"] = val # idssrc # ------ @property def idssrc(self): """ Sets the source reference on plot.ly for ids . The 'idssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["idssrc"] @idssrc.setter def idssrc(self, val): self["idssrc"] = val # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.histogram2d.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: color Sets the aggregation data. colorsrc Sets the source reference on plot.ly for color . Returns ------- plotly.graph_objs.histogram2d.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # meta # ---- @property def meta(self): """ Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. The 'meta' property accepts values of any type Returns ------- Any|numpy.ndarray """ return self["meta"] @meta.setter def meta(self, val): self["meta"] = val # metasrc # ------- @property def metasrc(self): """ Sets the source reference on plot.ly for meta . The 'metasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["metasrc"] @metasrc.setter def metasrc(self, val): self["metasrc"] = val # name # ---- @property def name(self): """ Sets the trace name. The trace name appear as the legend item and on hover. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # nbinsx # ------ @property def nbinsx(self): """ Specifies the maximum number of desired bins. This value will be used in an algorithm that will decide the optimal bin size such that the histogram best visualizes the distribution of the data. Ignored if `xbins.size` is provided. The 'nbinsx' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nbinsx"] @nbinsx.setter def nbinsx(self, val): self["nbinsx"] = val # nbinsy # ------ @property def nbinsy(self): """ Specifies the maximum number of desired bins. This value will be used in an algorithm that will decide the optimal bin size such that the histogram best visualizes the distribution of the data. Ignored if `ybins.size` is provided. The 'nbinsy' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nbinsy"] @nbinsy.setter def nbinsy(self, val): self["nbinsy"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the trace. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # reversescale # ------------ @property def reversescale(self): """ Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. The 'reversescale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["reversescale"] @reversescale.setter def reversescale(self, val): self["reversescale"] = val # showscale # --------- @property def showscale(self): """ Determines whether or not a colorbar is displayed for this trace. The 'showscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showscale"] @showscale.setter def showscale(self, val): self["showscale"] = val # stream # ------ @property def stream(self): """ The 'stream' property is an instance of Stream that may be specified as: - An instance of plotly.graph_objs.histogram2d.Stream - A dict of string/value properties that will be passed to the Stream constructor Supported dict properties: maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- plotly.graph_objs.histogram2d.Stream """ return self["stream"] @stream.setter def stream(self, val): self["stream"] = val # uid # --- @property def uid(self): """ Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. The 'uid' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["uid"] @uid.setter def uid(self, val): self["uid"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # visible # ------- @property def visible(self): """ Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). The 'visible' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'legendonly'] Returns ------- Any """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # x # - @property def x(self): """ Sets the sample data to be binned on the x axis. The 'x' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["x"] @x.setter def x(self, val): self["x"] = val # xaxis # ----- @property def xaxis(self): """ Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. The 'xaxis' property is an identifier of a particular subplot, of type 'x', that may be specified as the string 'x' optionally followed by an integer >= 1 (e.g. 'x', 'x1', 'x2', 'x3', etc.) Returns ------- str """ return self["xaxis"] @xaxis.setter def xaxis(self, val): self["xaxis"] = val # xbingroup # --------- @property def xbingroup(self): """ Set a group of histogram traces which will have compatible x-bin settings. Using `xbingroup`, histogram2d and histogram2dcontour traces (on axes of the same axis type) can have compatible x-bin settings. Note that the same `xbingroup` value can be used to set (1D) histogram `bingroup` The 'xbingroup' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["xbingroup"] @xbingroup.setter def xbingroup(self, val): self["xbingroup"] = val # xbins # ----- @property def xbins(self): """ The 'xbins' property is an instance of XBins that may be specified as: - An instance of plotly.graph_objs.histogram2d.XBins - A dict of string/value properties that will be passed to the XBins constructor Supported dict properties: end Sets the end value for the x axis bins. The last bin may not end exactly at this value, we increment the bin edge by `size` from `start` until we reach or exceed `end`. Defaults to the maximum data value. Like `start`, for dates use a date string, and for category data `end` is based on the category serial numbers. size Sets the size of each x axis bin. Default behavior: If `nbinsx` is 0 or omitted, we choose a nice round bin size such that the number of bins is about the same as the typical number of samples in each bin. If `nbinsx` is provided, we choose a nice round bin size giving no more than that many bins. For date data, use milliseconds or "M" for months, as in `axis.dtick`. For category data, the number of categories to bin together (always defaults to 1). start Sets the starting value for the x axis bins. Defaults to the minimum data value, shifted down if necessary to make nice round values and to remove ambiguous bin edges. For example, if most of the data is integers we shift the bin edges 0.5 down, so a `size` of 5 would have a default `start` of -0.5, so it is clear that 0-4 are in the first bin, 5-9 in the second, but continuous data gets a start of 0 and bins [0,5), [5,10) etc. Dates behave similarly, and `start` should be a date string. For category data, `start` is based on the category serial numbers, and defaults to -0.5. Returns ------- plotly.graph_objs.histogram2d.XBins """ return self["xbins"] @xbins.setter def xbins(self, val): self["xbins"] = val # xcalendar # --------- @property def xcalendar(self): """ Sets the calendar system to use with `x` date data. The 'xcalendar' property is an enumeration that may be specified as: - One of the following enumeration values: ['gregorian', 'chinese', 'coptic', 'discworld', 'ethiopian', 'hebrew', 'islamic', 'julian', 'mayan', 'nanakshahi', 'nepali', 'persian', 'jalali', 'taiwan', 'thai', 'ummalqura'] Returns ------- Any """ return self["xcalendar"] @xcalendar.setter def xcalendar(self, val): self["xcalendar"] = val # xgap # ---- @property def xgap(self): """ Sets the horizontal gap (in pixels) between bricks. The 'xgap' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["xgap"] @xgap.setter def xgap(self, val): self["xgap"] = val # xsrc # ---- @property def xsrc(self): """ Sets the source reference on plot.ly for x . The 'xsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["xsrc"] @xsrc.setter def xsrc(self, val): self["xsrc"] = val # y # - @property def y(self): """ Sets the sample data to be binned on the y axis. The 'y' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["y"] @y.setter def y(self, val): self["y"] = val # yaxis # ----- @property def yaxis(self): """ Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. The 'yaxis' property is an identifier of a particular subplot, of type 'y', that may be specified as the string 'y' optionally followed by an integer >= 1 (e.g. 'y', 'y1', 'y2', 'y3', etc.) Returns ------- str """ return self["yaxis"] @yaxis.setter def yaxis(self, val): self["yaxis"] = val # ybingroup # --------- @property def ybingroup(self): """ Set a group of histogram traces which will have compatible y-bin settings. Using `ybingroup`, histogram2d and histogram2dcontour traces (on axes of the same axis type) can have compatible y-bin settings. Note that the same `ybingroup` value can be used to set (1D) histogram `bingroup` The 'ybingroup' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ybingroup"] @ybingroup.setter def ybingroup(self, val): self["ybingroup"] = val # ybins # ----- @property def ybins(self): """ The 'ybins' property is an instance of YBins that may be specified as: - An instance of plotly.graph_objs.histogram2d.YBins - A dict of string/value properties that will be passed to the YBins constructor Supported dict properties: end Sets the end value for the y axis bins. The last bin may not end exactly at this value, we increment the bin edge by `size` from `start` until we reach or exceed `end`. Defaults to the maximum data value. Like `start`, for dates use a date string, and for category data `end` is based on the category serial numbers. size Sets the size of each y axis bin. Default behavior: If `nbinsy` is 0 or omitted, we choose a nice round bin size such that the number of bins is about the same as the typical number of samples in each bin. If `nbinsy` is provided, we choose a nice round bin size giving no more than that many bins. For date data, use milliseconds or "M" for months, as in `axis.dtick`. For category data, the number of categories to bin together (always defaults to 1). start Sets the starting value for the y axis bins. Defaults to the minimum data value, shifted down if necessary to make nice round values and to remove ambiguous bin edges. For example, if most of the data is integers we shift the bin edges 0.5 down, so a `size` of 5 would have a default `start` of -0.5, so it is clear that 0-4 are in the first bin, 5-9 in the second, but continuous data gets a start of 0 and bins [0,5), [5,10) etc. Dates behave similarly, and `start` should be a date string. For category data, `start` is based on the category serial numbers, and defaults to -0.5. Returns ------- plotly.graph_objs.histogram2d.YBins """ return self["ybins"] @ybins.setter def ybins(self, val): self["ybins"] = val # ycalendar # --------- @property def ycalendar(self): """ Sets the calendar system to use with `y` date data. The 'ycalendar' property is an enumeration that may be specified as: - One of the following enumeration values: ['gregorian', 'chinese', 'coptic', 'discworld', 'ethiopian', 'hebrew', 'islamic', 'julian', 'mayan', 'nanakshahi', 'nepali', 'persian', 'jalali', 'taiwan', 'thai', 'ummalqura'] Returns ------- Any """ return self["ycalendar"] @ycalendar.setter def ycalendar(self, val): self["ycalendar"] = val # ygap # ---- @property def ygap(self): """ Sets the vertical gap (in pixels) between bricks. The 'ygap' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ygap"] @ygap.setter def ygap(self, val): self["ygap"] = val # ysrc # ---- @property def ysrc(self): """ Sets the source reference on plot.ly for y . The 'ysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ysrc"] @ysrc.setter def ysrc(self, val): self["ysrc"] = val # z # - @property def z(self): """ Sets the aggregation data. The 'z' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["z"] @z.setter def z(self, val): self["z"] = val # zauto # ----- @property def zauto(self): """ Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. The 'zauto' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["zauto"] @zauto.setter def zauto(self, val): self["zauto"] = val # zhoverformat # ------------ @property def zhoverformat(self): """ Sets the hover text formatting rule using d3 formatting mini- languages which are very similar to those in Python. See: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format The 'zhoverformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["zhoverformat"] @zhoverformat.setter def zhoverformat(self, val): self["zhoverformat"] = val # zmax # ---- @property def zmax(self): """ Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. The 'zmax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["zmax"] @zmax.setter def zmax(self, val): self["zmax"] = val # zmid # ---- @property def zmid(self): """ Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. The 'zmid' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["zmid"] @zmid.setter def zmid(self, val): self["zmid"] = val # zmin # ---- @property def zmin(self): """ Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. The 'zmin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["zmin"] @zmin.setter def zmin(self, val): self["zmin"] = val # zsmooth # ------- @property def zsmooth(self): """ Picks a smoothing algorithm use to smooth `z` data. The 'zsmooth' property is an enumeration that may be specified as: - One of the following enumeration values: ['fast', 'best', False] Returns ------- Any """ return self["zsmooth"] @zsmooth.setter def zsmooth(self, val): self["zsmooth"] = val # zsrc # ---- @property def zsrc(self): """ Sets the source reference on plot.ly for z . The 'zsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["zsrc"] @zsrc.setter def zsrc(self, val): self["zsrc"] = val # type # ---- @property def type(self): return self._props["type"] # property parent name # -------------------- @property def _parent_path_str(self): return "" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autobinx Obsolete: since v1.42 each bin attribute is auto- determined separately and `autobinx` is not needed. However, we accept `autobinx: true` or `false` and will update `xbins` accordingly before deleting `autobinx` from the trace. autobiny Obsolete: since v1.42 each bin attribute is auto- determined separately and `autobiny` is not needed. However, we accept `autobiny: true` or `false` and will update `ybins` accordingly before deleting `autobiny` from the trace. autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. bingroup Set the `xbingroup` and `ybingroup` default prefix For example, setting a `bingroup` of 1 on two histogram2d traces will make them their x-bins and y-bins match separately. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.histogram2d.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . histfunc Specifies the binning function used for this histogram trace. If "count", the histogram values are computed by counting the number of values lying inside each bin. If "sum", "avg", "min", "max", the histogram values are computed using the sum, the average, the minimum or the maximum of the values lying inside each bin respectively. histnorm Specifies the type of normalization used for this histogram trace. If "", the span of each bar corresponds to the number of occurrences (i.e. the number of data points lying inside the bins). If "percent" / "probability", the span of each bar corresponds to the percentage / fraction of occurrences with respect to the total number of sample points (here, the sum of all bin HEIGHTS equals 100% / 1). If "density", the span of each bar corresponds to the number of occurrences in a bin divided by the size of the bin interval (here, the sum of all bin AREAS equals the total number of sample points). If *probability density*, the area of each bar corresponds to the probability that an event will fall into the corresponding bin (here, the sum of all bin AREAS equals 1). hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.histogram2d.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variable `z` Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . marker plotly.graph_objects.histogram2d.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. nbinsx Specifies the maximum number of desired bins. This value will be used in an algorithm that will decide the optimal bin size such that the histogram best visualizes the distribution of the data. Ignored if `xbins.size` is provided. nbinsy Specifies the maximum number of desired bins. This value will be used in an algorithm that will decide the optimal bin size such that the histogram best visualizes the distribution of the data. Ignored if `ybins.size` is provided. opacity Sets the opacity of the trace. reversescale Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.histogram2d.Stream instance or dict with compatible properties uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the sample data to be binned on the x axis. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xbingroup Set a group of histogram traces which will have compatible x-bin settings. Using `xbingroup`, histogram2d and histogram2dcontour traces (on axes of the same axis type) can have compatible x-bin settings. Note that the same `xbingroup` value can be used to set (1D) histogram `bingroup` xbins plotly.graph_objects.histogram2d.XBins instance or dict with compatible properties xcalendar Sets the calendar system to use with `x` date data. xgap Sets the horizontal gap (in pixels) between bricks. xsrc Sets the source reference on plot.ly for x . y Sets the sample data to be binned on the y axis. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ybingroup Set a group of histogram traces which will have compatible y-bin settings. Using `ybingroup`, histogram2d and histogram2dcontour traces (on axes of the same axis type) can have compatible y-bin settings. Note that the same `ybingroup` value can be used to set (1D) histogram `bingroup` ybins plotly.graph_objects.histogram2d.YBins instance or dict with compatible properties ycalendar Sets the calendar system to use with `y` date data. ygap Sets the vertical gap (in pixels) between bricks. ysrc Sets the source reference on plot.ly for y . z Sets the aggregation data. zauto Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. zhoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. See: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format zmax Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. zmid Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. zmin Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. zsmooth Picks a smoothing algorithm use to smooth `z` data. zsrc Sets the source reference on plot.ly for z . """ def __init__( self, arg=None, autobinx=None, autobiny=None, autocolorscale=None, bingroup=None, coloraxis=None, colorbar=None, colorscale=None, customdata=None, customdatasrc=None, histfunc=None, histnorm=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, ids=None, idssrc=None, marker=None, meta=None, metasrc=None, name=None, nbinsx=None, nbinsy=None, opacity=None, reversescale=None, showscale=None, stream=None, uid=None, uirevision=None, visible=None, x=None, xaxis=None, xbingroup=None, xbins=None, xcalendar=None, xgap=None, xsrc=None, y=None, yaxis=None, ybingroup=None, ybins=None, ycalendar=None, ygap=None, ysrc=None, z=None, zauto=None, zhoverformat=None, zmax=None, zmid=None, zmin=None, zsmooth=None, zsrc=None, **kwargs ): """ Construct a new Histogram2d object The sample data from which statistics are computed is set in `x` and `y` (where `x` and `y` represent marginal distributions, binning is set in `xbins` and `ybins` in this case) or `z` (where `z` represent the 2D distribution and binning set, binning is set by `x` and `y` in this case). The resulting distribution is visualized as a heatmap. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.Histogram2d autobinx Obsolete: since v1.42 each bin attribute is auto- determined separately and `autobinx` is not needed. However, we accept `autobinx: true` or `false` and will update `xbins` accordingly before deleting `autobinx` from the trace. autobiny Obsolete: since v1.42 each bin attribute is auto- determined separately and `autobiny` is not needed. However, we accept `autobiny: true` or `false` and will update `ybins` accordingly before deleting `autobiny` from the trace. autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. bingroup Set the `xbingroup` and `ybingroup` default prefix For example, setting a `bingroup` of 1 on two histogram2d traces will make them their x-bins and y-bins match separately. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.histogram2d.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . histfunc Specifies the binning function used for this histogram trace. If "count", the histogram values are computed by counting the number of values lying inside each bin. If "sum", "avg", "min", "max", the histogram values are computed using the sum, the average, the minimum or the maximum of the values lying inside each bin respectively. histnorm Specifies the type of normalization used for this histogram trace. If "", the span of each bar corresponds to the number of occurrences (i.e. the number of data points lying inside the bins). If "percent" / "probability", the span of each bar corresponds to the percentage / fraction of occurrences with respect to the total number of sample points (here, the sum of all bin HEIGHTS equals 100% / 1). If "density", the span of each bar corresponds to the number of occurrences in a bin divided by the size of the bin interval (here, the sum of all bin AREAS equals the total number of sample points). If *probability density*, the area of each bar corresponds to the probability that an event will fall into the corresponding bin (here, the sum of all bin AREAS equals 1). hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.histogram2d.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variable `z` Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . marker plotly.graph_objects.histogram2d.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. nbinsx Specifies the maximum number of desired bins. This value will be used in an algorithm that will decide the optimal bin size such that the histogram best visualizes the distribution of the data. Ignored if `xbins.size` is provided. nbinsy Specifies the maximum number of desired bins. This value will be used in an algorithm that will decide the optimal bin size such that the histogram best visualizes the distribution of the data. Ignored if `ybins.size` is provided. opacity Sets the opacity of the trace. reversescale Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.histogram2d.Stream instance or dict with compatible properties uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the sample data to be binned on the x axis. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xbingroup Set a group of histogram traces which will have compatible x-bin settings. Using `xbingroup`, histogram2d and histogram2dcontour traces (on axes of the same axis type) can have compatible x-bin settings. Note that the same `xbingroup` value can be used to set (1D) histogram `bingroup` xbins plotly.graph_objects.histogram2d.XBins instance or dict with compatible properties xcalendar Sets the calendar system to use with `x` date data. xgap Sets the horizontal gap (in pixels) between bricks. xsrc Sets the source reference on plot.ly for x . y Sets the sample data to be binned on the y axis. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ybingroup Set a group of histogram traces which will have compatible y-bin settings. Using `ybingroup`, histogram2d and histogram2dcontour traces (on axes of the same axis type) can have compatible y-bin settings. Note that the same `ybingroup` value can be used to set (1D) histogram `bingroup` ybins plotly.graph_objects.histogram2d.YBins instance or dict with compatible properties ycalendar Sets the calendar system to use with `y` date data. ygap Sets the vertical gap (in pixels) between bricks. ysrc Sets the source reference on plot.ly for y . z Sets the aggregation data. zauto Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. zhoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. See: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format zmax Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. zmid Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. zmin Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. zsmooth Picks a smoothing algorithm use to smooth `z` data. zsrc Sets the source reference on plot.ly for z . Returns ------- Histogram2d """ super(Histogram2d, self).__init__("histogram2d") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.Histogram2d constructor must be a dict or an instance of plotly.graph_objs.Histogram2d""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators import histogram2d as v_histogram2d # Initialize validators # --------------------- self._validators["autobinx"] = v_histogram2d.AutobinxValidator() self._validators["autobiny"] = v_histogram2d.AutobinyValidator() self._validators["autocolorscale"] = v_histogram2d.AutocolorscaleValidator() self._validators["bingroup"] = v_histogram2d.BingroupValidator() self._validators["coloraxis"] = v_histogram2d.ColoraxisValidator() self._validators["colorbar"] = v_histogram2d.ColorBarValidator() self._validators["colorscale"] = v_histogram2d.ColorscaleValidator() self._validators["customdata"] = v_histogram2d.CustomdataValidator() self._validators["customdatasrc"] = v_histogram2d.CustomdatasrcValidator() self._validators["histfunc"] = v_histogram2d.HistfuncValidator() self._validators["histnorm"] = v_histogram2d.HistnormValidator() self._validators["hoverinfo"] = v_histogram2d.HoverinfoValidator() self._validators["hoverinfosrc"] = v_histogram2d.HoverinfosrcValidator() self._validators["hoverlabel"] = v_histogram2d.HoverlabelValidator() self._validators["hovertemplate"] = v_histogram2d.HovertemplateValidator() self._validators["hovertemplatesrc"] = v_histogram2d.HovertemplatesrcValidator() self._validators["ids"] = v_histogram2d.IdsValidator() self._validators["idssrc"] = v_histogram2d.IdssrcValidator() self._validators["marker"] = v_histogram2d.MarkerValidator() self._validators["meta"] = v_histogram2d.MetaValidator() self._validators["metasrc"] = v_histogram2d.MetasrcValidator() self._validators["name"] = v_histogram2d.NameValidator() self._validators["nbinsx"] = v_histogram2d.NbinsxValidator() self._validators["nbinsy"] = v_histogram2d.NbinsyValidator() self._validators["opacity"] = v_histogram2d.OpacityValidator() self._validators["reversescale"] = v_histogram2d.ReversescaleValidator() self._validators["showscale"] = v_histogram2d.ShowscaleValidator() self._validators["stream"] = v_histogram2d.StreamValidator() self._validators["uid"] = v_histogram2d.UidValidator() self._validators["uirevision"] = v_histogram2d.UirevisionValidator() self._validators["visible"] = v_histogram2d.VisibleValidator() self._validators["x"] = v_histogram2d.XValidator() self._validators["xaxis"] = v_histogram2d.XAxisValidator() self._validators["xbingroup"] = v_histogram2d.XbingroupValidator() self._validators["xbins"] = v_histogram2d.XBinsValidator() self._validators["xcalendar"] = v_histogram2d.XcalendarValidator() self._validators["xgap"] = v_histogram2d.XgapValidator() self._validators["xsrc"] = v_histogram2d.XsrcValidator() self._validators["y"] = v_histogram2d.YValidator() self._validators["yaxis"] = v_histogram2d.YAxisValidator() self._validators["ybingroup"] = v_histogram2d.YbingroupValidator() self._validators["ybins"] = v_histogram2d.YBinsValidator() self._validators["ycalendar"] = v_histogram2d.YcalendarValidator() self._validators["ygap"] = v_histogram2d.YgapValidator() self._validators["ysrc"] = v_histogram2d.YsrcValidator() self._validators["z"] = v_histogram2d.ZValidator() self._validators["zauto"] = v_histogram2d.ZautoValidator() self._validators["zhoverformat"] = v_histogram2d.ZhoverformatValidator() self._validators["zmax"] = v_histogram2d.ZmaxValidator() self._validators["zmid"] = v_histogram2d.ZmidValidator() self._validators["zmin"] = v_histogram2d.ZminValidator() self._validators["zsmooth"] = v_histogram2d.ZsmoothValidator() self._validators["zsrc"] = v_histogram2d.ZsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autobinx", None) self["autobinx"] = autobinx if autobinx is not None else _v _v = arg.pop("autobiny", None) self["autobiny"] = autobiny if autobiny is not None else _v _v = arg.pop("autocolorscale", None) self["autocolorscale"] = autocolorscale if autocolorscale is not None else _v _v = arg.pop("bingroup", None) self["bingroup"] = bingroup if bingroup is not None else _v _v = arg.pop("coloraxis", None) self["coloraxis"] = coloraxis if coloraxis is not None else _v _v = arg.pop("colorbar", None) self["colorbar"] = colorbar if colorbar is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("customdata", None) self["customdata"] = customdata if customdata is not None else _v _v = arg.pop("customdatasrc", None) self["customdatasrc"] = customdatasrc if customdatasrc is not None else _v _v = arg.pop("histfunc", None) self["histfunc"] = histfunc if histfunc is not None else _v _v = arg.pop("histnorm", None) self["histnorm"] = histnorm if histnorm is not None else _v _v = arg.pop("hoverinfo", None) self["hoverinfo"] = hoverinfo if hoverinfo is not None else _v _v = arg.pop("hoverinfosrc", None) self["hoverinfosrc"] = hoverinfosrc if hoverinfosrc is not None else _v _v = arg.pop("hoverlabel", None) self["hoverlabel"] = hoverlabel if hoverlabel is not None else _v _v = arg.pop("hovertemplate", None) self["hovertemplate"] = hovertemplate if hovertemplate is not None else _v _v = arg.pop("hovertemplatesrc", None) self["hovertemplatesrc"] = ( hovertemplatesrc if hovertemplatesrc is not None else _v ) _v = arg.pop("ids", None) self["ids"] = ids if ids is not None else _v _v = arg.pop("idssrc", None) self["idssrc"] = idssrc if idssrc is not None else _v _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v _v = arg.pop("meta", None) self["meta"] = meta if meta is not None else _v _v = arg.pop("metasrc", None) self["metasrc"] = metasrc if metasrc is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("nbinsx", None) self["nbinsx"] = nbinsx if nbinsx is not None else _v _v = arg.pop("nbinsy", None) self["nbinsy"] = nbinsy if nbinsy is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("reversescale", None) self["reversescale"] = reversescale if reversescale is not None else _v _v = arg.pop("showscale", None) self["showscale"] = showscale if showscale is not None else _v _v = arg.pop("stream", None) self["stream"] = stream if stream is not None else _v _v = arg.pop("uid", None) self["uid"] = uid if uid is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xaxis", None) self["xaxis"] = xaxis if xaxis is not None else _v _v = arg.pop("xbingroup", None) self["xbingroup"] = xbingroup if xbingroup is not None else _v _v = arg.pop("xbins", None) self["xbins"] = xbins if xbins is not None else _v _v = arg.pop("xcalendar", None) self["xcalendar"] = xcalendar if xcalendar is not None else _v _v = arg.pop("xgap", None) self["xgap"] = xgap if xgap is not None else _v _v = arg.pop("xsrc", None) self["xsrc"] = xsrc if xsrc is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("yaxis", None) self["yaxis"] = yaxis if yaxis is not None else _v _v = arg.pop("ybingroup", None) self["ybingroup"] = ybingroup if ybingroup is not None else _v _v = arg.pop("ybins", None) self["ybins"] = ybins if ybins is not None else _v _v = arg.pop("ycalendar", None) self["ycalendar"] = ycalendar if ycalendar is not None else _v _v = arg.pop("ygap", None) self["ygap"] = ygap if ygap is not None else _v _v = arg.pop("ysrc", None) self["ysrc"] = ysrc if ysrc is not None else _v _v = arg.pop("z", None) self["z"] = z if z is not None else _v _v = arg.pop("zauto", None) self["zauto"] = zauto if zauto is not None else _v _v = arg.pop("zhoverformat", None) self["zhoverformat"] = zhoverformat if zhoverformat is not None else _v _v = arg.pop("zmax", None) self["zmax"] = zmax if zmax is not None else _v _v = arg.pop("zmid", None) self["zmid"] = zmid if zmid is not None else _v _v = arg.pop("zmin", None) self["zmin"] = zmin if zmin is not None else _v _v = arg.pop("zsmooth", None) self["zsmooth"] = zsmooth if zsmooth is not None else _v _v = arg.pop("zsrc", None) self["zsrc"] = zsrc if zsrc is not None else _v # Read-only literals # ------------------ from _plotly_utils.basevalidators import LiteralValidator self._props["type"] = "histogram2d" self._validators["type"] = LiteralValidator( plotly_name="type", parent_name="histogram2d", val="histogram2d" ) arg.pop("type", None) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceType as _BaseTraceType import copy as _copy class Histogram(_BaseTraceType): # alignmentgroup # -------------- @property def alignmentgroup(self): """ Set several traces linked to the same position axis or matching axes to the same alignmentgroup. This controls whether bars compute their positional range dependently or independently. The 'alignmentgroup' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["alignmentgroup"] @alignmentgroup.setter def alignmentgroup(self, val): self["alignmentgroup"] = val # autobinx # -------- @property def autobinx(self): """ Obsolete: since v1.42 each bin attribute is auto-determined separately and `autobinx` is not needed. However, we accept `autobinx: true` or `false` and will update `xbins` accordingly before deleting `autobinx` from the trace. The 'autobinx' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autobinx"] @autobinx.setter def autobinx(self, val): self["autobinx"] = val # autobiny # -------- @property def autobiny(self): """ Obsolete: since v1.42 each bin attribute is auto-determined separately and `autobiny` is not needed. However, we accept `autobiny: true` or `false` and will update `ybins` accordingly before deleting `autobiny` from the trace. The 'autobiny' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autobiny"] @autobiny.setter def autobiny(self, val): self["autobiny"] = val # bingroup # -------- @property def bingroup(self): """ Set a group of histogram traces which will have compatible bin settings. Note that traces on the same subplot and with the same "orientation" under `barmode` "stack", "relative" and "group" are forced into the same bingroup, Using `bingroup`, traces under `barmode` "overlay" and on different axes (of the same axis type) can have compatible bin settings. Note that histogram and histogram2d* trace can share the same `bingroup` The 'bingroup' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["bingroup"] @bingroup.setter def bingroup(self, val): self["bingroup"] = val # cumulative # ---------- @property def cumulative(self): """ The 'cumulative' property is an instance of Cumulative that may be specified as: - An instance of plotly.graph_objs.histogram.Cumulative - A dict of string/value properties that will be passed to the Cumulative constructor Supported dict properties: currentbin Only applies if cumulative is enabled. Sets whether the current bin is included, excluded, or has half of its value included in the current cumulative value. "include" is the default for compatibility with various other tools, however it introduces a half-bin bias to the results. "exclude" makes the opposite half- bin bias, and "half" removes it. direction Only applies if cumulative is enabled. If "increasing" (default) we sum all prior bins, so the result increases from left to right. If "decreasing" we sum later bins so the result decreases from left to right. enabled If true, display the cumulative distribution by summing the binned values. Use the `direction` and `centralbin` attributes to tune the accumulation method. Note: in this mode, the "density" `histnorm` settings behave the same as their equivalents without "density": "" and "density" both rise to the number of data points, and "probability" and *probability density* both rise to the number of sample points. Returns ------- plotly.graph_objs.histogram.Cumulative """ return self["cumulative"] @cumulative.setter def cumulative(self, val): self["cumulative"] = val # customdata # ---------- @property def customdata(self): """ Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements The 'customdata' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["customdata"] @customdata.setter def customdata(self, val): self["customdata"] = val # customdatasrc # ------------- @property def customdatasrc(self): """ Sets the source reference on plot.ly for customdata . The 'customdatasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["customdatasrc"] @customdatasrc.setter def customdatasrc(self, val): self["customdatasrc"] = val # error_x # ------- @property def error_x(self): """ The 'error_x' property is an instance of ErrorX that may be specified as: - An instance of plotly.graph_objs.histogram.ErrorX - A dict of string/value properties that will be passed to the ErrorX constructor Supported dict properties: array Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. arrayminus Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. arrayminussrc Sets the source reference on plot.ly for arrayminus . arraysrc Sets the source reference on plot.ly for array . color Sets the stoke color of the error bars. copy_ystyle symmetric Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. thickness Sets the thickness (in px) of the error bars. traceref tracerefminus type Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. value Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. valueminus Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars visible Determines whether or not this set of error bars is visible. width Sets the width (in px) of the cross-bar at both ends of the error bars. Returns ------- plotly.graph_objs.histogram.ErrorX """ return self["error_x"] @error_x.setter def error_x(self, val): self["error_x"] = val # error_y # ------- @property def error_y(self): """ The 'error_y' property is an instance of ErrorY that may be specified as: - An instance of plotly.graph_objs.histogram.ErrorY - A dict of string/value properties that will be passed to the ErrorY constructor Supported dict properties: array Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. arrayminus Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. arrayminussrc Sets the source reference on plot.ly for arrayminus . arraysrc Sets the source reference on plot.ly for array . color Sets the stoke color of the error bars. symmetric Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. thickness Sets the thickness (in px) of the error bars. traceref tracerefminus type Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. value Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. valueminus Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars visible Determines whether or not this set of error bars is visible. width Sets the width (in px) of the cross-bar at both ends of the error bars. Returns ------- plotly.graph_objs.histogram.ErrorY """ return self["error_y"] @error_y.setter def error_y(self, val): self["error_y"] = val # histfunc # -------- @property def histfunc(self): """ Specifies the binning function used for this histogram trace. If "count", the histogram values are computed by counting the number of values lying inside each bin. If "sum", "avg", "min", "max", the histogram values are computed using the sum, the average, the minimum or the maximum of the values lying inside each bin respectively. The 'histfunc' property is an enumeration that may be specified as: - One of the following enumeration values: ['count', 'sum', 'avg', 'min', 'max'] Returns ------- Any """ return self["histfunc"] @histfunc.setter def histfunc(self, val): self["histfunc"] = val # histnorm # -------- @property def histnorm(self): """ Specifies the type of normalization used for this histogram trace. If "", the span of each bar corresponds to the number of occurrences (i.e. the number of data points lying inside the bins). If "percent" / "probability", the span of each bar corresponds to the percentage / fraction of occurrences with respect to the total number of sample points (here, the sum of all bin HEIGHTS equals 100% / 1). If "density", the span of each bar corresponds to the number of occurrences in a bin divided by the size of the bin interval (here, the sum of all bin AREAS equals the total number of sample points). If *probability density*, the area of each bar corresponds to the probability that an event will fall into the corresponding bin (here, the sum of all bin AREAS equals 1). The 'histnorm' property is an enumeration that may be specified as: - One of the following enumeration values: ['', 'percent', 'probability', 'density', 'probability density'] Returns ------- Any """ return self["histnorm"] @histnorm.setter def histnorm(self, val): self["histnorm"] = val # hoverinfo # --------- @property def hoverinfo(self): """ Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. The 'hoverinfo' property is a flaglist and may be specified as a string containing: - Any combination of ['x', 'y', 'z', 'text', 'name'] joined with '+' characters (e.g. 'x+y') OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') - A list or array of the above Returns ------- Any|numpy.ndarray """ return self["hoverinfo"] @hoverinfo.setter def hoverinfo(self, val): self["hoverinfo"] = val # hoverinfosrc # ------------ @property def hoverinfosrc(self): """ Sets the source reference on plot.ly for hoverinfo . The 'hoverinfosrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hoverinfosrc"] @hoverinfosrc.setter def hoverinfosrc(self, val): self["hoverinfosrc"] = val # hoverlabel # ---------- @property def hoverlabel(self): """ The 'hoverlabel' property is an instance of Hoverlabel that may be specified as: - An instance of plotly.graph_objs.histogram.Hoverlabel - A dict of string/value properties that will be passed to the Hoverlabel constructor Supported dict properties: align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- plotly.graph_objs.histogram.Hoverlabel """ return self["hoverlabel"] @hoverlabel.setter def hoverlabel(self, val): self["hoverlabel"] = val # hovertemplate # ------------- @property def hovertemplate(self): """ Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event- data. Additionally, every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. variable `binNumber` Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. The 'hovertemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertemplate"] @hovertemplate.setter def hovertemplate(self, val): self["hovertemplate"] = val # hovertemplatesrc # ---------------- @property def hovertemplatesrc(self): """ Sets the source reference on plot.ly for hovertemplate . The 'hovertemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertemplatesrc"] @hovertemplatesrc.setter def hovertemplatesrc(self, val): self["hovertemplatesrc"] = val # hovertext # --------- @property def hovertext(self): """ Same as `text`. The 'hovertext' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertext"] @hovertext.setter def hovertext(self, val): self["hovertext"] = val # hovertextsrc # ------------ @property def hovertextsrc(self): """ Sets the source reference on plot.ly for hovertext . The 'hovertextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertextsrc"] @hovertextsrc.setter def hovertextsrc(self, val): self["hovertextsrc"] = val # ids # --- @property def ids(self): """ Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. The 'ids' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ids"] @ids.setter def ids(self, val): self["ids"] = val # idssrc # ------ @property def idssrc(self): """ Sets the source reference on plot.ly for ids . The 'idssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["idssrc"] @idssrc.setter def idssrc(self, val): self["idssrc"] = val # legendgroup # ----------- @property def legendgroup(self): """ Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. The 'legendgroup' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["legendgroup"] @legendgroup.setter def legendgroup(self, val): self["legendgroup"] = val # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.histogram.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.histogram.marker.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . line plotly.graph_objects.histogram.marker.Line instance or dict with compatible properties opacity Sets the opacity of the bars. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. Returns ------- plotly.graph_objs.histogram.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # meta # ---- @property def meta(self): """ Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. The 'meta' property accepts values of any type Returns ------- Any|numpy.ndarray """ return self["meta"] @meta.setter def meta(self, val): self["meta"] = val # metasrc # ------- @property def metasrc(self): """ Sets the source reference on plot.ly for meta . The 'metasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["metasrc"] @metasrc.setter def metasrc(self, val): self["metasrc"] = val # name # ---- @property def name(self): """ Sets the trace name. The trace name appear as the legend item and on hover. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # nbinsx # ------ @property def nbinsx(self): """ Specifies the maximum number of desired bins. This value will be used in an algorithm that will decide the optimal bin size such that the histogram best visualizes the distribution of the data. Ignored if `xbins.size` is provided. The 'nbinsx' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nbinsx"] @nbinsx.setter def nbinsx(self, val): self["nbinsx"] = val # nbinsy # ------ @property def nbinsy(self): """ Specifies the maximum number of desired bins. This value will be used in an algorithm that will decide the optimal bin size such that the histogram best visualizes the distribution of the data. Ignored if `ybins.size` is provided. The 'nbinsy' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nbinsy"] @nbinsy.setter def nbinsy(self, val): self["nbinsy"] = val # offsetgroup # ----------- @property def offsetgroup(self): """ Set several traces linked to the same position axis or matching axes to the same offsetgroup where bars of the same position coordinate will line up. The 'offsetgroup' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["offsetgroup"] @offsetgroup.setter def offsetgroup(self, val): self["offsetgroup"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the trace. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # orientation # ----------- @property def orientation(self): """ Sets the orientation of the bars. With "v" ("h"), the value of the each bar spans along the vertical (horizontal). The 'orientation' property is an enumeration that may be specified as: - One of the following enumeration values: ['v', 'h'] Returns ------- Any """ return self["orientation"] @orientation.setter def orientation(self, val): self["orientation"] = val # selected # -------- @property def selected(self): """ The 'selected' property is an instance of Selected that may be specified as: - An instance of plotly.graph_objs.histogram.Selected - A dict of string/value properties that will be passed to the Selected constructor Supported dict properties: marker plotly.graph_objects.histogram.selected.Marker instance or dict with compatible properties textfont plotly.graph_objects.histogram.selected.Textfon t instance or dict with compatible properties Returns ------- plotly.graph_objs.histogram.Selected """ return self["selected"] @selected.setter def selected(self, val): self["selected"] = val # selectedpoints # -------------- @property def selectedpoints(self): """ Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. The 'selectedpoints' property accepts values of any type Returns ------- Any """ return self["selectedpoints"] @selectedpoints.setter def selectedpoints(self, val): self["selectedpoints"] = val # showlegend # ---------- @property def showlegend(self): """ Determines whether or not an item corresponding to this trace is shown in the legend. The 'showlegend' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showlegend"] @showlegend.setter def showlegend(self, val): self["showlegend"] = val # stream # ------ @property def stream(self): """ The 'stream' property is an instance of Stream that may be specified as: - An instance of plotly.graph_objs.histogram.Stream - A dict of string/value properties that will be passed to the Stream constructor Supported dict properties: maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- plotly.graph_objs.histogram.Stream """ return self["stream"] @stream.setter def stream(self, val): self["stream"] = val # text # ---- @property def text(self): """ Sets hover text elements associated with each bar. If a single string, the same string appears over all bars. If an array of string, the items are mapped in order to the this trace's coordinates. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["text"] @text.setter def text(self, val): self["text"] = val # textsrc # ------- @property def textsrc(self): """ Sets the source reference on plot.ly for text . The 'textsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["textsrc"] @textsrc.setter def textsrc(self, val): self["textsrc"] = val # uid # --- @property def uid(self): """ Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. The 'uid' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["uid"] @uid.setter def uid(self, val): self["uid"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # unselected # ---------- @property def unselected(self): """ The 'unselected' property is an instance of Unselected that may be specified as: - An instance of plotly.graph_objs.histogram.Unselected - A dict of string/value properties that will be passed to the Unselected constructor Supported dict properties: marker plotly.graph_objects.histogram.unselected.Marke r instance or dict with compatible properties textfont plotly.graph_objects.histogram.unselected.Textf ont instance or dict with compatible properties Returns ------- plotly.graph_objs.histogram.Unselected """ return self["unselected"] @unselected.setter def unselected(self, val): self["unselected"] = val # visible # ------- @property def visible(self): """ Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). The 'visible' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'legendonly'] Returns ------- Any """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # x # - @property def x(self): """ Sets the sample data to be binned on the x axis. The 'x' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["x"] @x.setter def x(self, val): self["x"] = val # xaxis # ----- @property def xaxis(self): """ Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. The 'xaxis' property is an identifier of a particular subplot, of type 'x', that may be specified as the string 'x' optionally followed by an integer >= 1 (e.g. 'x', 'x1', 'x2', 'x3', etc.) Returns ------- str """ return self["xaxis"] @xaxis.setter def xaxis(self, val): self["xaxis"] = val # xbins # ----- @property def xbins(self): """ The 'xbins' property is an instance of XBins that may be specified as: - An instance of plotly.graph_objs.histogram.XBins - A dict of string/value properties that will be passed to the XBins constructor Supported dict properties: end Sets the end value for the x axis bins. The last bin may not end exactly at this value, we increment the bin edge by `size` from `start` until we reach or exceed `end`. Defaults to the maximum data value. Like `start`, for dates use a date string, and for category data `end` is based on the category serial numbers. size Sets the size of each x axis bin. Default behavior: If `nbinsx` is 0 or omitted, we choose a nice round bin size such that the number of bins is about the same as the typical number of samples in each bin. If `nbinsx` is provided, we choose a nice round bin size giving no more than that many bins. For date data, use milliseconds or "M" for months, as in `axis.dtick`. For category data, the number of categories to bin together (always defaults to 1). If multiple non-overlaying histograms share a subplot, the first explicit `size` is used and all others discarded. If no `size` is provided,the sample data from all traces is combined to determine `size` as described above. start Sets the starting value for the x axis bins. Defaults to the minimum data value, shifted down if necessary to make nice round values and to remove ambiguous bin edges. For example, if most of the data is integers we shift the bin edges 0.5 down, so a `size` of 5 would have a default `start` of -0.5, so it is clear that 0-4 are in the first bin, 5-9 in the second, but continuous data gets a start of 0 and bins [0,5), [5,10) etc. Dates behave similarly, and `start` should be a date string. For category data, `start` is based on the category serial numbers, and defaults to -0.5. If multiple non- overlaying histograms share a subplot, the first explicit `start` is used exactly and all others are shifted down (if necessary) to differ from that one by an integer number of bins. Returns ------- plotly.graph_objs.histogram.XBins """ return self["xbins"] @xbins.setter def xbins(self, val): self["xbins"] = val # xcalendar # --------- @property def xcalendar(self): """ Sets the calendar system to use with `x` date data. The 'xcalendar' property is an enumeration that may be specified as: - One of the following enumeration values: ['gregorian', 'chinese', 'coptic', 'discworld', 'ethiopian', 'hebrew', 'islamic', 'julian', 'mayan', 'nanakshahi', 'nepali', 'persian', 'jalali', 'taiwan', 'thai', 'ummalqura'] Returns ------- Any """ return self["xcalendar"] @xcalendar.setter def xcalendar(self, val): self["xcalendar"] = val # xsrc # ---- @property def xsrc(self): """ Sets the source reference on plot.ly for x . The 'xsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["xsrc"] @xsrc.setter def xsrc(self, val): self["xsrc"] = val # y # - @property def y(self): """ Sets the sample data to be binned on the y axis. The 'y' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["y"] @y.setter def y(self, val): self["y"] = val # yaxis # ----- @property def yaxis(self): """ Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. The 'yaxis' property is an identifier of a particular subplot, of type 'y', that may be specified as the string 'y' optionally followed by an integer >= 1 (e.g. 'y', 'y1', 'y2', 'y3', etc.) Returns ------- str """ return self["yaxis"] @yaxis.setter def yaxis(self, val): self["yaxis"] = val # ybins # ----- @property def ybins(self): """ The 'ybins' property is an instance of YBins that may be specified as: - An instance of plotly.graph_objs.histogram.YBins - A dict of string/value properties that will be passed to the YBins constructor Supported dict properties: end Sets the end value for the y axis bins. The last bin may not end exactly at this value, we increment the bin edge by `size` from `start` until we reach or exceed `end`. Defaults to the maximum data value. Like `start`, for dates use a date string, and for category data `end` is based on the category serial numbers. size Sets the size of each y axis bin. Default behavior: If `nbinsy` is 0 or omitted, we choose a nice round bin size such that the number of bins is about the same as the typical number of samples in each bin. If `nbinsy` is provided, we choose a nice round bin size giving no more than that many bins. For date data, use milliseconds or "M" for months, as in `axis.dtick`. For category data, the number of categories to bin together (always defaults to 1). If multiple non-overlaying histograms share a subplot, the first explicit `size` is used and all others discarded. If no `size` is provided,the sample data from all traces is combined to determine `size` as described above. start Sets the starting value for the y axis bins. Defaults to the minimum data value, shifted down if necessary to make nice round values and to remove ambiguous bin edges. For example, if most of the data is integers we shift the bin edges 0.5 down, so a `size` of 5 would have a default `start` of -0.5, so it is clear that 0-4 are in the first bin, 5-9 in the second, but continuous data gets a start of 0 and bins [0,5), [5,10) etc. Dates behave similarly, and `start` should be a date string. For category data, `start` is based on the category serial numbers, and defaults to -0.5. If multiple non- overlaying histograms share a subplot, the first explicit `start` is used exactly and all others are shifted down (if necessary) to differ from that one by an integer number of bins. Returns ------- plotly.graph_objs.histogram.YBins """ return self["ybins"] @ybins.setter def ybins(self, val): self["ybins"] = val # ycalendar # --------- @property def ycalendar(self): """ Sets the calendar system to use with `y` date data. The 'ycalendar' property is an enumeration that may be specified as: - One of the following enumeration values: ['gregorian', 'chinese', 'coptic', 'discworld', 'ethiopian', 'hebrew', 'islamic', 'julian', 'mayan', 'nanakshahi', 'nepali', 'persian', 'jalali', 'taiwan', 'thai', 'ummalqura'] Returns ------- Any """ return self["ycalendar"] @ycalendar.setter def ycalendar(self, val): self["ycalendar"] = val # ysrc # ---- @property def ysrc(self): """ Sets the source reference on plot.ly for y . The 'ysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ysrc"] @ysrc.setter def ysrc(self, val): self["ysrc"] = val # type # ---- @property def type(self): return self._props["type"] # property parent name # -------------------- @property def _parent_path_str(self): return "" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ alignmentgroup Set several traces linked to the same position axis or matching axes to the same alignmentgroup. This controls whether bars compute their positional range dependently or independently. autobinx Obsolete: since v1.42 each bin attribute is auto- determined separately and `autobinx` is not needed. However, we accept `autobinx: true` or `false` and will update `xbins` accordingly before deleting `autobinx` from the trace. autobiny Obsolete: since v1.42 each bin attribute is auto- determined separately and `autobiny` is not needed. However, we accept `autobiny: true` or `false` and will update `ybins` accordingly before deleting `autobiny` from the trace. bingroup Set a group of histogram traces which will have compatible bin settings. Note that traces on the same subplot and with the same "orientation" under `barmode` "stack", "relative" and "group" are forced into the same bingroup, Using `bingroup`, traces under `barmode` "overlay" and on different axes (of the same axis type) can have compatible bin settings. Note that histogram and histogram2d* trace can share the same `bingroup` cumulative plotly.graph_objects.histogram.Cumulative instance or dict with compatible properties customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . error_x plotly.graph_objects.histogram.ErrorX instance or dict with compatible properties error_y plotly.graph_objects.histogram.ErrorY instance or dict with compatible properties histfunc Specifies the binning function used for this histogram trace. If "count", the histogram values are computed by counting the number of values lying inside each bin. If "sum", "avg", "min", "max", the histogram values are computed using the sum, the average, the minimum or the maximum of the values lying inside each bin respectively. histnorm Specifies the type of normalization used for this histogram trace. If "", the span of each bar corresponds to the number of occurrences (i.e. the number of data points lying inside the bins). If "percent" / "probability", the span of each bar corresponds to the percentage / fraction of occurrences with respect to the total number of sample points (here, the sum of all bin HEIGHTS equals 100% / 1). If "density", the span of each bar corresponds to the number of occurrences in a bin divided by the size of the bin interval (here, the sum of all bin AREAS equals the total number of sample points). If *probability density*, the area of each bar corresponds to the probability that an event will fall into the corresponding bin (here, the sum of all bin AREAS equals 1). hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.histogram.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variable `binNumber` Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. marker plotly.graph_objects.histogram.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. nbinsx Specifies the maximum number of desired bins. This value will be used in an algorithm that will decide the optimal bin size such that the histogram best visualizes the distribution of the data. Ignored if `xbins.size` is provided. nbinsy Specifies the maximum number of desired bins. This value will be used in an algorithm that will decide the optimal bin size such that the histogram best visualizes the distribution of the data. Ignored if `ybins.size` is provided. offsetgroup Set several traces linked to the same position axis or matching axes to the same offsetgroup where bars of the same position coordinate will line up. opacity Sets the opacity of the trace. orientation Sets the orientation of the bars. With "v" ("h"), the value of the each bar spans along the vertical (horizontal). selected plotly.graph_objects.histogram.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.histogram.Stream instance or dict with compatible properties text Sets hover text elements associated with each bar. If a single string, the same string appears over all bars. If an array of string, the items are mapped in order to the this trace's coordinates. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.histogram.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the sample data to be binned on the x axis. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xbins plotly.graph_objects.histogram.XBins instance or dict with compatible properties xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . y Sets the sample data to be binned on the y axis. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ybins plotly.graph_objects.histogram.YBins instance or dict with compatible properties ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . """ def __init__( self, arg=None, alignmentgroup=None, autobinx=None, autobiny=None, bingroup=None, cumulative=None, customdata=None, customdatasrc=None, error_x=None, error_y=None, histfunc=None, histnorm=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, legendgroup=None, marker=None, meta=None, metasrc=None, name=None, nbinsx=None, nbinsy=None, offsetgroup=None, opacity=None, orientation=None, selected=None, selectedpoints=None, showlegend=None, stream=None, text=None, textsrc=None, uid=None, uirevision=None, unselected=None, visible=None, x=None, xaxis=None, xbins=None, xcalendar=None, xsrc=None, y=None, yaxis=None, ybins=None, ycalendar=None, ysrc=None, **kwargs ): """ Construct a new Histogram object The sample data from which statistics are computed is set in `x` for vertically spanning histograms and in `y` for horizontally spanning histograms. Binning options are set `xbins` and `ybins` respectively if no aggregation data is provided. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.Histogram alignmentgroup Set several traces linked to the same position axis or matching axes to the same alignmentgroup. This controls whether bars compute their positional range dependently or independently. autobinx Obsolete: since v1.42 each bin attribute is auto- determined separately and `autobinx` is not needed. However, we accept `autobinx: true` or `false` and will update `xbins` accordingly before deleting `autobinx` from the trace. autobiny Obsolete: since v1.42 each bin attribute is auto- determined separately and `autobiny` is not needed. However, we accept `autobiny: true` or `false` and will update `ybins` accordingly before deleting `autobiny` from the trace. bingroup Set a group of histogram traces which will have compatible bin settings. Note that traces on the same subplot and with the same "orientation" under `barmode` "stack", "relative" and "group" are forced into the same bingroup, Using `bingroup`, traces under `barmode` "overlay" and on different axes (of the same axis type) can have compatible bin settings. Note that histogram and histogram2d* trace can share the same `bingroup` cumulative plotly.graph_objects.histogram.Cumulative instance or dict with compatible properties customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . error_x plotly.graph_objects.histogram.ErrorX instance or dict with compatible properties error_y plotly.graph_objects.histogram.ErrorY instance or dict with compatible properties histfunc Specifies the binning function used for this histogram trace. If "count", the histogram values are computed by counting the number of values lying inside each bin. If "sum", "avg", "min", "max", the histogram values are computed using the sum, the average, the minimum or the maximum of the values lying inside each bin respectively. histnorm Specifies the type of normalization used for this histogram trace. If "", the span of each bar corresponds to the number of occurrences (i.e. the number of data points lying inside the bins). If "percent" / "probability", the span of each bar corresponds to the percentage / fraction of occurrences with respect to the total number of sample points (here, the sum of all bin HEIGHTS equals 100% / 1). If "density", the span of each bar corresponds to the number of occurrences in a bin divided by the size of the bin interval (here, the sum of all bin AREAS equals the total number of sample points). If *probability density*, the area of each bar corresponds to the probability that an event will fall into the corresponding bin (here, the sum of all bin AREAS equals 1). hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.histogram.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variable `binNumber` Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. marker plotly.graph_objects.histogram.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. nbinsx Specifies the maximum number of desired bins. This value will be used in an algorithm that will decide the optimal bin size such that the histogram best visualizes the distribution of the data. Ignored if `xbins.size` is provided. nbinsy Specifies the maximum number of desired bins. This value will be used in an algorithm that will decide the optimal bin size such that the histogram best visualizes the distribution of the data. Ignored if `ybins.size` is provided. offsetgroup Set several traces linked to the same position axis or matching axes to the same offsetgroup where bars of the same position coordinate will line up. opacity Sets the opacity of the trace. orientation Sets the orientation of the bars. With "v" ("h"), the value of the each bar spans along the vertical (horizontal). selected plotly.graph_objects.histogram.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.histogram.Stream instance or dict with compatible properties text Sets hover text elements associated with each bar. If a single string, the same string appears over all bars. If an array of string, the items are mapped in order to the this trace's coordinates. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.histogram.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the sample data to be binned on the x axis. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xbins plotly.graph_objects.histogram.XBins instance or dict with compatible properties xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . y Sets the sample data to be binned on the y axis. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ybins plotly.graph_objects.histogram.YBins instance or dict with compatible properties ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . Returns ------- Histogram """ super(Histogram, self).__init__("histogram") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.Histogram constructor must be a dict or an instance of plotly.graph_objs.Histogram""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators import histogram as v_histogram # Initialize validators # --------------------- self._validators["alignmentgroup"] = v_histogram.AlignmentgroupValidator() self._validators["autobinx"] = v_histogram.AutobinxValidator() self._validators["autobiny"] = v_histogram.AutobinyValidator() self._validators["bingroup"] = v_histogram.BingroupValidator() self._validators["cumulative"] = v_histogram.CumulativeValidator() self._validators["customdata"] = v_histogram.CustomdataValidator() self._validators["customdatasrc"] = v_histogram.CustomdatasrcValidator() self._validators["error_x"] = v_histogram.ErrorXValidator() self._validators["error_y"] = v_histogram.ErrorYValidator() self._validators["histfunc"] = v_histogram.HistfuncValidator() self._validators["histnorm"] = v_histogram.HistnormValidator() self._validators["hoverinfo"] = v_histogram.HoverinfoValidator() self._validators["hoverinfosrc"] = v_histogram.HoverinfosrcValidator() self._validators["hoverlabel"] = v_histogram.HoverlabelValidator() self._validators["hovertemplate"] = v_histogram.HovertemplateValidator() self._validators["hovertemplatesrc"] = v_histogram.HovertemplatesrcValidator() self._validators["hovertext"] = v_histogram.HovertextValidator() self._validators["hovertextsrc"] = v_histogram.HovertextsrcValidator() self._validators["ids"] = v_histogram.IdsValidator() self._validators["idssrc"] = v_histogram.IdssrcValidator() self._validators["legendgroup"] = v_histogram.LegendgroupValidator() self._validators["marker"] = v_histogram.MarkerValidator() self._validators["meta"] = v_histogram.MetaValidator() self._validators["metasrc"] = v_histogram.MetasrcValidator() self._validators["name"] = v_histogram.NameValidator() self._validators["nbinsx"] = v_histogram.NbinsxValidator() self._validators["nbinsy"] = v_histogram.NbinsyValidator() self._validators["offsetgroup"] = v_histogram.OffsetgroupValidator() self._validators["opacity"] = v_histogram.OpacityValidator() self._validators["orientation"] = v_histogram.OrientationValidator() self._validators["selected"] = v_histogram.SelectedValidator() self._validators["selectedpoints"] = v_histogram.SelectedpointsValidator() self._validators["showlegend"] = v_histogram.ShowlegendValidator() self._validators["stream"] = v_histogram.StreamValidator() self._validators["text"] = v_histogram.TextValidator() self._validators["textsrc"] = v_histogram.TextsrcValidator() self._validators["uid"] = v_histogram.UidValidator() self._validators["uirevision"] = v_histogram.UirevisionValidator() self._validators["unselected"] = v_histogram.UnselectedValidator() self._validators["visible"] = v_histogram.VisibleValidator() self._validators["x"] = v_histogram.XValidator() self._validators["xaxis"] = v_histogram.XAxisValidator() self._validators["xbins"] = v_histogram.XBinsValidator() self._validators["xcalendar"] = v_histogram.XcalendarValidator() self._validators["xsrc"] = v_histogram.XsrcValidator() self._validators["y"] = v_histogram.YValidator() self._validators["yaxis"] = v_histogram.YAxisValidator() self._validators["ybins"] = v_histogram.YBinsValidator() self._validators["ycalendar"] = v_histogram.YcalendarValidator() self._validators["ysrc"] = v_histogram.YsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("alignmentgroup", None) self["alignmentgroup"] = alignmentgroup if alignmentgroup is not None else _v _v = arg.pop("autobinx", None) self["autobinx"] = autobinx if autobinx is not None else _v _v = arg.pop("autobiny", None) self["autobiny"] = autobiny if autobiny is not None else _v _v = arg.pop("bingroup", None) self["bingroup"] = bingroup if bingroup is not None else _v _v = arg.pop("cumulative", None) self["cumulative"] = cumulative if cumulative is not None else _v _v = arg.pop("customdata", None) self["customdata"] = customdata if customdata is not None else _v _v = arg.pop("customdatasrc", None) self["customdatasrc"] = customdatasrc if customdatasrc is not None else _v _v = arg.pop("error_x", None) self["error_x"] = error_x if error_x is not None else _v _v = arg.pop("error_y", None) self["error_y"] = error_y if error_y is not None else _v _v = arg.pop("histfunc", None) self["histfunc"] = histfunc if histfunc is not None else _v _v = arg.pop("histnorm", None) self["histnorm"] = histnorm if histnorm is not None else _v _v = arg.pop("hoverinfo", None) self["hoverinfo"] = hoverinfo if hoverinfo is not None else _v _v = arg.pop("hoverinfosrc", None) self["hoverinfosrc"] = hoverinfosrc if hoverinfosrc is not None else _v _v = arg.pop("hoverlabel", None) self["hoverlabel"] = hoverlabel if hoverlabel is not None else _v _v = arg.pop("hovertemplate", None) self["hovertemplate"] = hovertemplate if hovertemplate is not None else _v _v = arg.pop("hovertemplatesrc", None) self["hovertemplatesrc"] = ( hovertemplatesrc if hovertemplatesrc is not None else _v ) _v = arg.pop("hovertext", None) self["hovertext"] = hovertext if hovertext is not None else _v _v = arg.pop("hovertextsrc", None) self["hovertextsrc"] = hovertextsrc if hovertextsrc is not None else _v _v = arg.pop("ids", None) self["ids"] = ids if ids is not None else _v _v = arg.pop("idssrc", None) self["idssrc"] = idssrc if idssrc is not None else _v _v = arg.pop("legendgroup", None) self["legendgroup"] = legendgroup if legendgroup is not None else _v _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v _v = arg.pop("meta", None) self["meta"] = meta if meta is not None else _v _v = arg.pop("metasrc", None) self["metasrc"] = metasrc if metasrc is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("nbinsx", None) self["nbinsx"] = nbinsx if nbinsx is not None else _v _v = arg.pop("nbinsy", None) self["nbinsy"] = nbinsy if nbinsy is not None else _v _v = arg.pop("offsetgroup", None) self["offsetgroup"] = offsetgroup if offsetgroup is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("orientation", None) self["orientation"] = orientation if orientation is not None else _v _v = arg.pop("selected", None) self["selected"] = selected if selected is not None else _v _v = arg.pop("selectedpoints", None) self["selectedpoints"] = selectedpoints if selectedpoints is not None else _v _v = arg.pop("showlegend", None) self["showlegend"] = showlegend if showlegend is not None else _v _v = arg.pop("stream", None) self["stream"] = stream if stream is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v _v = arg.pop("textsrc", None) self["textsrc"] = textsrc if textsrc is not None else _v _v = arg.pop("uid", None) self["uid"] = uid if uid is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("unselected", None) self["unselected"] = unselected if unselected is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xaxis", None) self["xaxis"] = xaxis if xaxis is not None else _v _v = arg.pop("xbins", None) self["xbins"] = xbins if xbins is not None else _v _v = arg.pop("xcalendar", None) self["xcalendar"] = xcalendar if xcalendar is not None else _v _v = arg.pop("xsrc", None) self["xsrc"] = xsrc if xsrc is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("yaxis", None) self["yaxis"] = yaxis if yaxis is not None else _v _v = arg.pop("ybins", None) self["ybins"] = ybins if ybins is not None else _v _v = arg.pop("ycalendar", None) self["ycalendar"] = ycalendar if ycalendar is not None else _v _v = arg.pop("ysrc", None) self["ysrc"] = ysrc if ysrc is not None else _v # Read-only literals # ------------------ from _plotly_utils.basevalidators import LiteralValidator self._props["type"] = "histogram" self._validators["type"] = LiteralValidator( plotly_name="type", parent_name="histogram", val="histogram" ) arg.pop("type", None) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceType as _BaseTraceType import copy as _copy class Heatmapgl(_BaseTraceType): # autocolorscale # -------------- @property def autocolorscale(self): """ Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. The 'autocolorscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocolorscale"] @autocolorscale.setter def autocolorscale(self, val): self["autocolorscale"] = val # coloraxis # --------- @property def coloraxis(self): """ Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. The 'coloraxis' property is an identifier of a particular subplot, of type 'coloraxis', that may be specified as the string 'coloraxis' optionally followed by an integer >= 1 (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) Returns ------- str """ return self["coloraxis"] @coloraxis.setter def coloraxis(self, val): self["coloraxis"] = val # colorbar # -------- @property def colorbar(self): """ The 'colorbar' property is an instance of ColorBar that may be specified as: - An instance of plotly.graph_objs.heatmapgl.ColorBar - A dict of string/value properties that will be passed to the ColorBar constructor Supported dict properties: bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.heatmapgl.color bar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.heatmapgl.colorbar.tickformatstopdefaults), sets the default property values to use for elements of heatmapgl.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.heatmapgl.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use heatmapgl.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use heatmapgl.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- plotly.graph_objs.heatmapgl.ColorBar """ return self["colorbar"] @colorbar.setter def colorbar(self, val): self["colorbar"] = val # colorscale # ---------- @property def colorscale(self): """ Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,Earth,Electric,Vi ridis,Cividis. The 'colorscale' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # customdata # ---------- @property def customdata(self): """ Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements The 'customdata' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["customdata"] @customdata.setter def customdata(self, val): self["customdata"] = val # customdatasrc # ------------- @property def customdatasrc(self): """ Sets the source reference on plot.ly for customdata . The 'customdatasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["customdatasrc"] @customdatasrc.setter def customdatasrc(self, val): self["customdatasrc"] = val # dx # -- @property def dx(self): """ Sets the x coordinate step. See `x0` for more info. The 'dx' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["dx"] @dx.setter def dx(self, val): self["dx"] = val # dy # -- @property def dy(self): """ Sets the y coordinate step. See `y0` for more info. The 'dy' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["dy"] @dy.setter def dy(self, val): self["dy"] = val # hoverinfo # --------- @property def hoverinfo(self): """ Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. The 'hoverinfo' property is a flaglist and may be specified as a string containing: - Any combination of ['x', 'y', 'z', 'text', 'name'] joined with '+' characters (e.g. 'x+y') OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') - A list or array of the above Returns ------- Any|numpy.ndarray """ return self["hoverinfo"] @hoverinfo.setter def hoverinfo(self, val): self["hoverinfo"] = val # hoverinfosrc # ------------ @property def hoverinfosrc(self): """ Sets the source reference on plot.ly for hoverinfo . The 'hoverinfosrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hoverinfosrc"] @hoverinfosrc.setter def hoverinfosrc(self, val): self["hoverinfosrc"] = val # hoverlabel # ---------- @property def hoverlabel(self): """ The 'hoverlabel' property is an instance of Hoverlabel that may be specified as: - An instance of plotly.graph_objs.heatmapgl.Hoverlabel - A dict of string/value properties that will be passed to the Hoverlabel constructor Supported dict properties: align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- plotly.graph_objs.heatmapgl.Hoverlabel """ return self["hoverlabel"] @hoverlabel.setter def hoverlabel(self, val): self["hoverlabel"] = val # ids # --- @property def ids(self): """ Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. The 'ids' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ids"] @ids.setter def ids(self, val): self["ids"] = val # idssrc # ------ @property def idssrc(self): """ Sets the source reference on plot.ly for ids . The 'idssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["idssrc"] @idssrc.setter def idssrc(self, val): self["idssrc"] = val # meta # ---- @property def meta(self): """ Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. The 'meta' property accepts values of any type Returns ------- Any|numpy.ndarray """ return self["meta"] @meta.setter def meta(self, val): self["meta"] = val # metasrc # ------- @property def metasrc(self): """ Sets the source reference on plot.ly for meta . The 'metasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["metasrc"] @metasrc.setter def metasrc(self, val): self["metasrc"] = val # name # ---- @property def name(self): """ Sets the trace name. The trace name appear as the legend item and on hover. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the trace. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # reversescale # ------------ @property def reversescale(self): """ Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. The 'reversescale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["reversescale"] @reversescale.setter def reversescale(self, val): self["reversescale"] = val # showscale # --------- @property def showscale(self): """ Determines whether or not a colorbar is displayed for this trace. The 'showscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showscale"] @showscale.setter def showscale(self, val): self["showscale"] = val # stream # ------ @property def stream(self): """ The 'stream' property is an instance of Stream that may be specified as: - An instance of plotly.graph_objs.heatmapgl.Stream - A dict of string/value properties that will be passed to the Stream constructor Supported dict properties: maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- plotly.graph_objs.heatmapgl.Stream """ return self["stream"] @stream.setter def stream(self, val): self["stream"] = val # text # ---- @property def text(self): """ Sets the text elements associated with each z value. The 'text' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["text"] @text.setter def text(self, val): self["text"] = val # textsrc # ------- @property def textsrc(self): """ Sets the source reference on plot.ly for text . The 'textsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["textsrc"] @textsrc.setter def textsrc(self, val): self["textsrc"] = val # transpose # --------- @property def transpose(self): """ Transposes the z data. The 'transpose' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["transpose"] @transpose.setter def transpose(self, val): self["transpose"] = val # uid # --- @property def uid(self): """ Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. The 'uid' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["uid"] @uid.setter def uid(self, val): self["uid"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # visible # ------- @property def visible(self): """ Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). The 'visible' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'legendonly'] Returns ------- Any """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # x # - @property def x(self): """ Sets the x coordinates. The 'x' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["x"] @x.setter def x(self, val): self["x"] = val # x0 # -- @property def x0(self): """ Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. The 'x0' property accepts values of any type Returns ------- Any """ return self["x0"] @x0.setter def x0(self, val): self["x0"] = val # xaxis # ----- @property def xaxis(self): """ Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. The 'xaxis' property is an identifier of a particular subplot, of type 'x', that may be specified as the string 'x' optionally followed by an integer >= 1 (e.g. 'x', 'x1', 'x2', 'x3', etc.) Returns ------- str """ return self["xaxis"] @xaxis.setter def xaxis(self, val): self["xaxis"] = val # xsrc # ---- @property def xsrc(self): """ Sets the source reference on plot.ly for x . The 'xsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["xsrc"] @xsrc.setter def xsrc(self, val): self["xsrc"] = val # xtype # ----- @property def xtype(self): """ If "array", the heatmap's x coordinates are given by "x" (the default behavior when `x` is provided). If "scaled", the heatmap's x coordinates are given by "x0" and "dx" (the default behavior when `x` is not provided). The 'xtype' property is an enumeration that may be specified as: - One of the following enumeration values: ['array', 'scaled'] Returns ------- Any """ return self["xtype"] @xtype.setter def xtype(self, val): self["xtype"] = val # y # - @property def y(self): """ Sets the y coordinates. The 'y' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["y"] @y.setter def y(self, val): self["y"] = val # y0 # -- @property def y0(self): """ Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. The 'y0' property accepts values of any type Returns ------- Any """ return self["y0"] @y0.setter def y0(self, val): self["y0"] = val # yaxis # ----- @property def yaxis(self): """ Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. The 'yaxis' property is an identifier of a particular subplot, of type 'y', that may be specified as the string 'y' optionally followed by an integer >= 1 (e.g. 'y', 'y1', 'y2', 'y3', etc.) Returns ------- str """ return self["yaxis"] @yaxis.setter def yaxis(self, val): self["yaxis"] = val # ysrc # ---- @property def ysrc(self): """ Sets the source reference on plot.ly for y . The 'ysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ysrc"] @ysrc.setter def ysrc(self, val): self["ysrc"] = val # ytype # ----- @property def ytype(self): """ If "array", the heatmap's y coordinates are given by "y" (the default behavior when `y` is provided) If "scaled", the heatmap's y coordinates are given by "y0" and "dy" (the default behavior when `y` is not provided) The 'ytype' property is an enumeration that may be specified as: - One of the following enumeration values: ['array', 'scaled'] Returns ------- Any """ return self["ytype"] @ytype.setter def ytype(self, val): self["ytype"] = val # z # - @property def z(self): """ Sets the z data. The 'z' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["z"] @z.setter def z(self, val): self["z"] = val # zauto # ----- @property def zauto(self): """ Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. The 'zauto' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["zauto"] @zauto.setter def zauto(self, val): self["zauto"] = val # zmax # ---- @property def zmax(self): """ Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. The 'zmax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["zmax"] @zmax.setter def zmax(self, val): self["zmax"] = val # zmid # ---- @property def zmid(self): """ Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. The 'zmid' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["zmid"] @zmid.setter def zmid(self, val): self["zmid"] = val # zmin # ---- @property def zmin(self): """ Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. The 'zmin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["zmin"] @zmin.setter def zmin(self, val): self["zmin"] = val # zsrc # ---- @property def zsrc(self): """ Sets the source reference on plot.ly for z . The 'zsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["zsrc"] @zsrc.setter def zsrc(self, val): self["zsrc"] = val # type # ---- @property def type(self): return self._props["type"] # property parent name # -------------------- @property def _parent_path_str(self): return "" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.heatmapgl.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dx Sets the x coordinate step. See `x0` for more info. dy Sets the y coordinate step. See `y0` for more info. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.heatmapgl.Hoverlabel instance or dict with compatible properties ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. reversescale Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.heatmapgl.Stream instance or dict with compatible properties text Sets the text elements associated with each z value. textsrc Sets the source reference on plot.ly for text . transpose Transposes the z data. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the x coordinates. x0 Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xsrc Sets the source reference on plot.ly for x . xtype If "array", the heatmap's x coordinates are given by "x" (the default behavior when `x` is provided). If "scaled", the heatmap's x coordinates are given by "x0" and "dx" (the default behavior when `x` is not provided). y Sets the y coordinates. y0 Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ysrc Sets the source reference on plot.ly for y . ytype If "array", the heatmap's y coordinates are given by "y" (the default behavior when `y` is provided) If "scaled", the heatmap's y coordinates are given by "y0" and "dy" (the default behavior when `y` is not provided) z Sets the z data. zauto Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. zmax Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. zmid Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. zmin Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. zsrc Sets the source reference on plot.ly for z . """ def __init__( self, arg=None, autocolorscale=None, coloraxis=None, colorbar=None, colorscale=None, customdata=None, customdatasrc=None, dx=None, dy=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, ids=None, idssrc=None, meta=None, metasrc=None, name=None, opacity=None, reversescale=None, showscale=None, stream=None, text=None, textsrc=None, transpose=None, uid=None, uirevision=None, visible=None, x=None, x0=None, xaxis=None, xsrc=None, xtype=None, y=None, y0=None, yaxis=None, ysrc=None, ytype=None, z=None, zauto=None, zmax=None, zmid=None, zmin=None, zsrc=None, **kwargs ): """ Construct a new Heatmapgl object WebGL version of the heatmap trace type. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.Heatmapgl autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.heatmapgl.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dx Sets the x coordinate step. See `x0` for more info. dy Sets the y coordinate step. See `y0` for more info. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.heatmapgl.Hoverlabel instance or dict with compatible properties ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. reversescale Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.heatmapgl.Stream instance or dict with compatible properties text Sets the text elements associated with each z value. textsrc Sets the source reference on plot.ly for text . transpose Transposes the z data. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the x coordinates. x0 Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xsrc Sets the source reference on plot.ly for x . xtype If "array", the heatmap's x coordinates are given by "x" (the default behavior when `x` is provided). If "scaled", the heatmap's x coordinates are given by "x0" and "dx" (the default behavior when `x` is not provided). y Sets the y coordinates. y0 Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ysrc Sets the source reference on plot.ly for y . ytype If "array", the heatmap's y coordinates are given by "y" (the default behavior when `y` is provided) If "scaled", the heatmap's y coordinates are given by "y0" and "dy" (the default behavior when `y` is not provided) z Sets the z data. zauto Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. zmax Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. zmid Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. zmin Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. zsrc Sets the source reference on plot.ly for z . Returns ------- Heatmapgl """ super(Heatmapgl, self).__init__("heatmapgl") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.Heatmapgl constructor must be a dict or an instance of plotly.graph_objs.Heatmapgl""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators import heatmapgl as v_heatmapgl # Initialize validators # --------------------- self._validators["autocolorscale"] = v_heatmapgl.AutocolorscaleValidator() self._validators["coloraxis"] = v_heatmapgl.ColoraxisValidator() self._validators["colorbar"] = v_heatmapgl.ColorBarValidator() self._validators["colorscale"] = v_heatmapgl.ColorscaleValidator() self._validators["customdata"] = v_heatmapgl.CustomdataValidator() self._validators["customdatasrc"] = v_heatmapgl.CustomdatasrcValidator() self._validators["dx"] = v_heatmapgl.DxValidator() self._validators["dy"] = v_heatmapgl.DyValidator() self._validators["hoverinfo"] = v_heatmapgl.HoverinfoValidator() self._validators["hoverinfosrc"] = v_heatmapgl.HoverinfosrcValidator() self._validators["hoverlabel"] = v_heatmapgl.HoverlabelValidator() self._validators["ids"] = v_heatmapgl.IdsValidator() self._validators["idssrc"] = v_heatmapgl.IdssrcValidator() self._validators["meta"] = v_heatmapgl.MetaValidator() self._validators["metasrc"] = v_heatmapgl.MetasrcValidator() self._validators["name"] = v_heatmapgl.NameValidator() self._validators["opacity"] = v_heatmapgl.OpacityValidator() self._validators["reversescale"] = v_heatmapgl.ReversescaleValidator() self._validators["showscale"] = v_heatmapgl.ShowscaleValidator() self._validators["stream"] = v_heatmapgl.StreamValidator() self._validators["text"] = v_heatmapgl.TextValidator() self._validators["textsrc"] = v_heatmapgl.TextsrcValidator() self._validators["transpose"] = v_heatmapgl.TransposeValidator() self._validators["uid"] = v_heatmapgl.UidValidator() self._validators["uirevision"] = v_heatmapgl.UirevisionValidator() self._validators["visible"] = v_heatmapgl.VisibleValidator() self._validators["x"] = v_heatmapgl.XValidator() self._validators["x0"] = v_heatmapgl.X0Validator() self._validators["xaxis"] = v_heatmapgl.XAxisValidator() self._validators["xsrc"] = v_heatmapgl.XsrcValidator() self._validators["xtype"] = v_heatmapgl.XtypeValidator() self._validators["y"] = v_heatmapgl.YValidator() self._validators["y0"] = v_heatmapgl.Y0Validator() self._validators["yaxis"] = v_heatmapgl.YAxisValidator() self._validators["ysrc"] = v_heatmapgl.YsrcValidator() self._validators["ytype"] = v_heatmapgl.YtypeValidator() self._validators["z"] = v_heatmapgl.ZValidator() self._validators["zauto"] = v_heatmapgl.ZautoValidator() self._validators["zmax"] = v_heatmapgl.ZmaxValidator() self._validators["zmid"] = v_heatmapgl.ZmidValidator() self._validators["zmin"] = v_heatmapgl.ZminValidator() self._validators["zsrc"] = v_heatmapgl.ZsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autocolorscale", None) self["autocolorscale"] = autocolorscale if autocolorscale is not None else _v _v = arg.pop("coloraxis", None) self["coloraxis"] = coloraxis if coloraxis is not None else _v _v = arg.pop("colorbar", None) self["colorbar"] = colorbar if colorbar is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("customdata", None) self["customdata"] = customdata if customdata is not None else _v _v = arg.pop("customdatasrc", None) self["customdatasrc"] = customdatasrc if customdatasrc is not None else _v _v = arg.pop("dx", None) self["dx"] = dx if dx is not None else _v _v = arg.pop("dy", None) self["dy"] = dy if dy is not None else _v _v = arg.pop("hoverinfo", None) self["hoverinfo"] = hoverinfo if hoverinfo is not None else _v _v = arg.pop("hoverinfosrc", None) self["hoverinfosrc"] = hoverinfosrc if hoverinfosrc is not None else _v _v = arg.pop("hoverlabel", None) self["hoverlabel"] = hoverlabel if hoverlabel is not None else _v _v = arg.pop("ids", None) self["ids"] = ids if ids is not None else _v _v = arg.pop("idssrc", None) self["idssrc"] = idssrc if idssrc is not None else _v _v = arg.pop("meta", None) self["meta"] = meta if meta is not None else _v _v = arg.pop("metasrc", None) self["metasrc"] = metasrc if metasrc is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("reversescale", None) self["reversescale"] = reversescale if reversescale is not None else _v _v = arg.pop("showscale", None) self["showscale"] = showscale if showscale is not None else _v _v = arg.pop("stream", None) self["stream"] = stream if stream is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v _v = arg.pop("textsrc", None) self["textsrc"] = textsrc if textsrc is not None else _v _v = arg.pop("transpose", None) self["transpose"] = transpose if transpose is not None else _v _v = arg.pop("uid", None) self["uid"] = uid if uid is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("x0", None) self["x0"] = x0 if x0 is not None else _v _v = arg.pop("xaxis", None) self["xaxis"] = xaxis if xaxis is not None else _v _v = arg.pop("xsrc", None) self["xsrc"] = xsrc if xsrc is not None else _v _v = arg.pop("xtype", None) self["xtype"] = xtype if xtype is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("y0", None) self["y0"] = y0 if y0 is not None else _v _v = arg.pop("yaxis", None) self["yaxis"] = yaxis if yaxis is not None else _v _v = arg.pop("ysrc", None) self["ysrc"] = ysrc if ysrc is not None else _v _v = arg.pop("ytype", None) self["ytype"] = ytype if ytype is not None else _v _v = arg.pop("z", None) self["z"] = z if z is not None else _v _v = arg.pop("zauto", None) self["zauto"] = zauto if zauto is not None else _v _v = arg.pop("zmax", None) self["zmax"] = zmax if zmax is not None else _v _v = arg.pop("zmid", None) self["zmid"] = zmid if zmid is not None else _v _v = arg.pop("zmin", None) self["zmin"] = zmin if zmin is not None else _v _v = arg.pop("zsrc", None) self["zsrc"] = zsrc if zsrc is not None else _v # Read-only literals # ------------------ from _plotly_utils.basevalidators import LiteralValidator self._props["type"] = "heatmapgl" self._validators["type"] = LiteralValidator( plotly_name="type", parent_name="heatmapgl", val="heatmapgl" ) arg.pop("type", None) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceType as _BaseTraceType import copy as _copy class Heatmap(_BaseTraceType): # autocolorscale # -------------- @property def autocolorscale(self): """ Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. The 'autocolorscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocolorscale"] @autocolorscale.setter def autocolorscale(self, val): self["autocolorscale"] = val # coloraxis # --------- @property def coloraxis(self): """ Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. The 'coloraxis' property is an identifier of a particular subplot, of type 'coloraxis', that may be specified as the string 'coloraxis' optionally followed by an integer >= 1 (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) Returns ------- str """ return self["coloraxis"] @coloraxis.setter def coloraxis(self, val): self["coloraxis"] = val # colorbar # -------- @property def colorbar(self): """ The 'colorbar' property is an instance of ColorBar that may be specified as: - An instance of plotly.graph_objs.heatmap.ColorBar - A dict of string/value properties that will be passed to the ColorBar constructor Supported dict properties: bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.heatmap.colorba r.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.heatmap.colorbar.tickformatstopdefaults), sets the default property values to use for elements of heatmap.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.heatmap.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use heatmap.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use heatmap.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- plotly.graph_objs.heatmap.ColorBar """ return self["colorbar"] @colorbar.setter def colorbar(self, val): self["colorbar"] = val # colorscale # ---------- @property def colorscale(self): """ Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,Earth,Electric,Vi ridis,Cividis. The 'colorscale' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # connectgaps # ----------- @property def connectgaps(self): """ Determines whether or not gaps (i.e. {nan} or missing values) in the `z` data are filled in. It is defaulted to true if `z` is a one dimensional array and `zsmooth` is not false; otherwise it is defaulted to false. The 'connectgaps' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["connectgaps"] @connectgaps.setter def connectgaps(self, val): self["connectgaps"] = val # customdata # ---------- @property def customdata(self): """ Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements The 'customdata' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["customdata"] @customdata.setter def customdata(self, val): self["customdata"] = val # customdatasrc # ------------- @property def customdatasrc(self): """ Sets the source reference on plot.ly for customdata . The 'customdatasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["customdatasrc"] @customdatasrc.setter def customdatasrc(self, val): self["customdatasrc"] = val # dx # -- @property def dx(self): """ Sets the x coordinate step. See `x0` for more info. The 'dx' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["dx"] @dx.setter def dx(self, val): self["dx"] = val # dy # -- @property def dy(self): """ Sets the y coordinate step. See `y0` for more info. The 'dy' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["dy"] @dy.setter def dy(self, val): self["dy"] = val # hoverinfo # --------- @property def hoverinfo(self): """ Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. The 'hoverinfo' property is a flaglist and may be specified as a string containing: - Any combination of ['x', 'y', 'z', 'text', 'name'] joined with '+' characters (e.g. 'x+y') OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') - A list or array of the above Returns ------- Any|numpy.ndarray """ return self["hoverinfo"] @hoverinfo.setter def hoverinfo(self, val): self["hoverinfo"] = val # hoverinfosrc # ------------ @property def hoverinfosrc(self): """ Sets the source reference on plot.ly for hoverinfo . The 'hoverinfosrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hoverinfosrc"] @hoverinfosrc.setter def hoverinfosrc(self, val): self["hoverinfosrc"] = val # hoverlabel # ---------- @property def hoverlabel(self): """ The 'hoverlabel' property is an instance of Hoverlabel that may be specified as: - An instance of plotly.graph_objs.heatmap.Hoverlabel - A dict of string/value properties that will be passed to the Hoverlabel constructor Supported dict properties: align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- plotly.graph_objs.heatmap.Hoverlabel """ return self["hoverlabel"] @hoverlabel.setter def hoverlabel(self, val): self["hoverlabel"] = val # hoverongaps # ----------- @property def hoverongaps(self): """ Determines whether or not gaps (i.e. {nan} or missing values) in the `z` data have hover labels associated with them. The 'hoverongaps' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["hoverongaps"] @hoverongaps.setter def hoverongaps(self, val): self["hoverongaps"] = val # hovertemplate # ------------- @property def hovertemplate(self): """ Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event- data. Additionally, every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. The 'hovertemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertemplate"] @hovertemplate.setter def hovertemplate(self, val): self["hovertemplate"] = val # hovertemplatesrc # ---------------- @property def hovertemplatesrc(self): """ Sets the source reference on plot.ly for hovertemplate . The 'hovertemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertemplatesrc"] @hovertemplatesrc.setter def hovertemplatesrc(self, val): self["hovertemplatesrc"] = val # hovertext # --------- @property def hovertext(self): """ Same as `text`. The 'hovertext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["hovertext"] @hovertext.setter def hovertext(self, val): self["hovertext"] = val # hovertextsrc # ------------ @property def hovertextsrc(self): """ Sets the source reference on plot.ly for hovertext . The 'hovertextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertextsrc"] @hovertextsrc.setter def hovertextsrc(self, val): self["hovertextsrc"] = val # ids # --- @property def ids(self): """ Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. The 'ids' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ids"] @ids.setter def ids(self, val): self["ids"] = val # idssrc # ------ @property def idssrc(self): """ Sets the source reference on plot.ly for ids . The 'idssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["idssrc"] @idssrc.setter def idssrc(self, val): self["idssrc"] = val # meta # ---- @property def meta(self): """ Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. The 'meta' property accepts values of any type Returns ------- Any|numpy.ndarray """ return self["meta"] @meta.setter def meta(self, val): self["meta"] = val # metasrc # ------- @property def metasrc(self): """ Sets the source reference on plot.ly for meta . The 'metasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["metasrc"] @metasrc.setter def metasrc(self, val): self["metasrc"] = val # name # ---- @property def name(self): """ Sets the trace name. The trace name appear as the legend item and on hover. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the trace. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # reversescale # ------------ @property def reversescale(self): """ Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. The 'reversescale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["reversescale"] @reversescale.setter def reversescale(self, val): self["reversescale"] = val # showscale # --------- @property def showscale(self): """ Determines whether or not a colorbar is displayed for this trace. The 'showscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showscale"] @showscale.setter def showscale(self, val): self["showscale"] = val # stream # ------ @property def stream(self): """ The 'stream' property is an instance of Stream that may be specified as: - An instance of plotly.graph_objs.heatmap.Stream - A dict of string/value properties that will be passed to the Stream constructor Supported dict properties: maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- plotly.graph_objs.heatmap.Stream """ return self["stream"] @stream.setter def stream(self, val): self["stream"] = val # text # ---- @property def text(self): """ Sets the text elements associated with each z value. The 'text' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["text"] @text.setter def text(self, val): self["text"] = val # textsrc # ------- @property def textsrc(self): """ Sets the source reference on plot.ly for text . The 'textsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["textsrc"] @textsrc.setter def textsrc(self, val): self["textsrc"] = val # transpose # --------- @property def transpose(self): """ Transposes the z data. The 'transpose' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["transpose"] @transpose.setter def transpose(self, val): self["transpose"] = val # uid # --- @property def uid(self): """ Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. The 'uid' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["uid"] @uid.setter def uid(self, val): self["uid"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # visible # ------- @property def visible(self): """ Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). The 'visible' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'legendonly'] Returns ------- Any """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # x # - @property def x(self): """ Sets the x coordinates. The 'x' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["x"] @x.setter def x(self, val): self["x"] = val # x0 # -- @property def x0(self): """ Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. The 'x0' property accepts values of any type Returns ------- Any """ return self["x0"] @x0.setter def x0(self, val): self["x0"] = val # xaxis # ----- @property def xaxis(self): """ Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. The 'xaxis' property is an identifier of a particular subplot, of type 'x', that may be specified as the string 'x' optionally followed by an integer >= 1 (e.g. 'x', 'x1', 'x2', 'x3', etc.) Returns ------- str """ return self["xaxis"] @xaxis.setter def xaxis(self, val): self["xaxis"] = val # xcalendar # --------- @property def xcalendar(self): """ Sets the calendar system to use with `x` date data. The 'xcalendar' property is an enumeration that may be specified as: - One of the following enumeration values: ['gregorian', 'chinese', 'coptic', 'discworld', 'ethiopian', 'hebrew', 'islamic', 'julian', 'mayan', 'nanakshahi', 'nepali', 'persian', 'jalali', 'taiwan', 'thai', 'ummalqura'] Returns ------- Any """ return self["xcalendar"] @xcalendar.setter def xcalendar(self, val): self["xcalendar"] = val # xgap # ---- @property def xgap(self): """ Sets the horizontal gap (in pixels) between bricks. The 'xgap' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["xgap"] @xgap.setter def xgap(self, val): self["xgap"] = val # xsrc # ---- @property def xsrc(self): """ Sets the source reference on plot.ly for x . The 'xsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["xsrc"] @xsrc.setter def xsrc(self, val): self["xsrc"] = val # xtype # ----- @property def xtype(self): """ If "array", the heatmap's x coordinates are given by "x" (the default behavior when `x` is provided). If "scaled", the heatmap's x coordinates are given by "x0" and "dx" (the default behavior when `x` is not provided). The 'xtype' property is an enumeration that may be specified as: - One of the following enumeration values: ['array', 'scaled'] Returns ------- Any """ return self["xtype"] @xtype.setter def xtype(self, val): self["xtype"] = val # y # - @property def y(self): """ Sets the y coordinates. The 'y' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["y"] @y.setter def y(self, val): self["y"] = val # y0 # -- @property def y0(self): """ Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. The 'y0' property accepts values of any type Returns ------- Any """ return self["y0"] @y0.setter def y0(self, val): self["y0"] = val # yaxis # ----- @property def yaxis(self): """ Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. The 'yaxis' property is an identifier of a particular subplot, of type 'y', that may be specified as the string 'y' optionally followed by an integer >= 1 (e.g. 'y', 'y1', 'y2', 'y3', etc.) Returns ------- str """ return self["yaxis"] @yaxis.setter def yaxis(self, val): self["yaxis"] = val # ycalendar # --------- @property def ycalendar(self): """ Sets the calendar system to use with `y` date data. The 'ycalendar' property is an enumeration that may be specified as: - One of the following enumeration values: ['gregorian', 'chinese', 'coptic', 'discworld', 'ethiopian', 'hebrew', 'islamic', 'julian', 'mayan', 'nanakshahi', 'nepali', 'persian', 'jalali', 'taiwan', 'thai', 'ummalqura'] Returns ------- Any """ return self["ycalendar"] @ycalendar.setter def ycalendar(self, val): self["ycalendar"] = val # ygap # ---- @property def ygap(self): """ Sets the vertical gap (in pixels) between bricks. The 'ygap' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ygap"] @ygap.setter def ygap(self, val): self["ygap"] = val # ysrc # ---- @property def ysrc(self): """ Sets the source reference on plot.ly for y . The 'ysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ysrc"] @ysrc.setter def ysrc(self, val): self["ysrc"] = val # ytype # ----- @property def ytype(self): """ If "array", the heatmap's y coordinates are given by "y" (the default behavior when `y` is provided) If "scaled", the heatmap's y coordinates are given by "y0" and "dy" (the default behavior when `y` is not provided) The 'ytype' property is an enumeration that may be specified as: - One of the following enumeration values: ['array', 'scaled'] Returns ------- Any """ return self["ytype"] @ytype.setter def ytype(self, val): self["ytype"] = val # z # - @property def z(self): """ Sets the z data. The 'z' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["z"] @z.setter def z(self, val): self["z"] = val # zauto # ----- @property def zauto(self): """ Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. The 'zauto' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["zauto"] @zauto.setter def zauto(self, val): self["zauto"] = val # zhoverformat # ------------ @property def zhoverformat(self): """ Sets the hover text formatting rule using d3 formatting mini- languages which are very similar to those in Python. See: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format The 'zhoverformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["zhoverformat"] @zhoverformat.setter def zhoverformat(self, val): self["zhoverformat"] = val # zmax # ---- @property def zmax(self): """ Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. The 'zmax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["zmax"] @zmax.setter def zmax(self, val): self["zmax"] = val # zmid # ---- @property def zmid(self): """ Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. The 'zmid' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["zmid"] @zmid.setter def zmid(self, val): self["zmid"] = val # zmin # ---- @property def zmin(self): """ Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. The 'zmin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["zmin"] @zmin.setter def zmin(self, val): self["zmin"] = val # zsmooth # ------- @property def zsmooth(self): """ Picks a smoothing algorithm use to smooth `z` data. The 'zsmooth' property is an enumeration that may be specified as: - One of the following enumeration values: ['fast', 'best', False] Returns ------- Any """ return self["zsmooth"] @zsmooth.setter def zsmooth(self, val): self["zsmooth"] = val # zsrc # ---- @property def zsrc(self): """ Sets the source reference on plot.ly for z . The 'zsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["zsrc"] @zsrc.setter def zsrc(self, val): self["zsrc"] = val # type # ---- @property def type(self): return self._props["type"] # property parent name # -------------------- @property def _parent_path_str(self): return "" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.heatmap.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the `z` data are filled in. It is defaulted to true if `z` is a one dimensional array and `zsmooth` is not false; otherwise it is defaulted to false. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dx Sets the x coordinate step. See `x0` for more info. dy Sets the y coordinate step. See `y0` for more info. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.heatmap.Hoverlabel instance or dict with compatible properties hoverongaps Determines whether or not gaps (i.e. {nan} or missing values) in the `z` data have hover labels associated with them. hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. reversescale Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.heatmap.Stream instance or dict with compatible properties text Sets the text elements associated with each z value. textsrc Sets the source reference on plot.ly for text . transpose Transposes the z data. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the x coordinates. x0 Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xcalendar Sets the calendar system to use with `x` date data. xgap Sets the horizontal gap (in pixels) between bricks. xsrc Sets the source reference on plot.ly for x . xtype If "array", the heatmap's x coordinates are given by "x" (the default behavior when `x` is provided). If "scaled", the heatmap's x coordinates are given by "x0" and "dx" (the default behavior when `x` is not provided). y Sets the y coordinates. y0 Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ycalendar Sets the calendar system to use with `y` date data. ygap Sets the vertical gap (in pixels) between bricks. ysrc Sets the source reference on plot.ly for y . ytype If "array", the heatmap's y coordinates are given by "y" (the default behavior when `y` is provided) If "scaled", the heatmap's y coordinates are given by "y0" and "dy" (the default behavior when `y` is not provided) z Sets the z data. zauto Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. zhoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. See: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format zmax Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. zmid Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. zmin Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. zsmooth Picks a smoothing algorithm use to smooth `z` data. zsrc Sets the source reference on plot.ly for z . """ def __init__( self, arg=None, autocolorscale=None, coloraxis=None, colorbar=None, colorscale=None, connectgaps=None, customdata=None, customdatasrc=None, dx=None, dy=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hoverongaps=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, meta=None, metasrc=None, name=None, opacity=None, reversescale=None, showscale=None, stream=None, text=None, textsrc=None, transpose=None, uid=None, uirevision=None, visible=None, x=None, x0=None, xaxis=None, xcalendar=None, xgap=None, xsrc=None, xtype=None, y=None, y0=None, yaxis=None, ycalendar=None, ygap=None, ysrc=None, ytype=None, z=None, zauto=None, zhoverformat=None, zmax=None, zmid=None, zmin=None, zsmooth=None, zsrc=None, **kwargs ): """ Construct a new Heatmap object The data that describes the heatmap value-to-color mapping is set in `z`. Data in `z` can either be a 2D list of values (ragged or not) or a 1D array of values. In the case where `z` is a 2D list, say that `z` has N rows and M columns. Then, by default, the resulting heatmap will have N partitions along the y axis and M partitions along the x axis. In other words, the i-th row/ j-th column cell in `z` is mapped to the i-th partition of the y axis (starting from the bottom of the plot) and the j-th partition of the x-axis (starting from the left of the plot). This behavior can be flipped by using `transpose`. Moreover, `x` (`y`) can be provided with M or M+1 (N or N+1) elements. If M (N), then the coordinates correspond to the center of the heatmap cells and the cells have equal width. If M+1 (N+1), then the coordinates correspond to the edges of the heatmap cells. In the case where `z` is a 1D list, the x and y coordinates must be provided in `x` and `y` respectively to form data triplets. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.Heatmap autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.heatmap.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the `z` data are filled in. It is defaulted to true if `z` is a one dimensional array and `zsmooth` is not false; otherwise it is defaulted to false. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dx Sets the x coordinate step. See `x0` for more info. dy Sets the y coordinate step. See `y0` for more info. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.heatmap.Hoverlabel instance or dict with compatible properties hoverongaps Determines whether or not gaps (i.e. {nan} or missing values) in the `z` data have hover labels associated with them. hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. reversescale Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.heatmap.Stream instance or dict with compatible properties text Sets the text elements associated with each z value. textsrc Sets the source reference on plot.ly for text . transpose Transposes the z data. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the x coordinates. x0 Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xcalendar Sets the calendar system to use with `x` date data. xgap Sets the horizontal gap (in pixels) between bricks. xsrc Sets the source reference on plot.ly for x . xtype If "array", the heatmap's x coordinates are given by "x" (the default behavior when `x` is provided). If "scaled", the heatmap's x coordinates are given by "x0" and "dx" (the default behavior when `x` is not provided). y Sets the y coordinates. y0 Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ycalendar Sets the calendar system to use with `y` date data. ygap Sets the vertical gap (in pixels) between bricks. ysrc Sets the source reference on plot.ly for y . ytype If "array", the heatmap's y coordinates are given by "y" (the default behavior when `y` is provided) If "scaled", the heatmap's y coordinates are given by "y0" and "dy" (the default behavior when `y` is not provided) z Sets the z data. zauto Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. zhoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. See: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format zmax Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. zmid Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. zmin Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. zsmooth Picks a smoothing algorithm use to smooth `z` data. zsrc Sets the source reference on plot.ly for z . Returns ------- Heatmap """ super(Heatmap, self).__init__("heatmap") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.Heatmap constructor must be a dict or an instance of plotly.graph_objs.Heatmap""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators import heatmap as v_heatmap # Initialize validators # --------------------- self._validators["autocolorscale"] = v_heatmap.AutocolorscaleValidator() self._validators["coloraxis"] = v_heatmap.ColoraxisValidator() self._validators["colorbar"] = v_heatmap.ColorBarValidator() self._validators["colorscale"] = v_heatmap.ColorscaleValidator() self._validators["connectgaps"] = v_heatmap.ConnectgapsValidator() self._validators["customdata"] = v_heatmap.CustomdataValidator() self._validators["customdatasrc"] = v_heatmap.CustomdatasrcValidator() self._validators["dx"] = v_heatmap.DxValidator() self._validators["dy"] = v_heatmap.DyValidator() self._validators["hoverinfo"] = v_heatmap.HoverinfoValidator() self._validators["hoverinfosrc"] = v_heatmap.HoverinfosrcValidator() self._validators["hoverlabel"] = v_heatmap.HoverlabelValidator() self._validators["hoverongaps"] = v_heatmap.HoverongapsValidator() self._validators["hovertemplate"] = v_heatmap.HovertemplateValidator() self._validators["hovertemplatesrc"] = v_heatmap.HovertemplatesrcValidator() self._validators["hovertext"] = v_heatmap.HovertextValidator() self._validators["hovertextsrc"] = v_heatmap.HovertextsrcValidator() self._validators["ids"] = v_heatmap.IdsValidator() self._validators["idssrc"] = v_heatmap.IdssrcValidator() self._validators["meta"] = v_heatmap.MetaValidator() self._validators["metasrc"] = v_heatmap.MetasrcValidator() self._validators["name"] = v_heatmap.NameValidator() self._validators["opacity"] = v_heatmap.OpacityValidator() self._validators["reversescale"] = v_heatmap.ReversescaleValidator() self._validators["showscale"] = v_heatmap.ShowscaleValidator() self._validators["stream"] = v_heatmap.StreamValidator() self._validators["text"] = v_heatmap.TextValidator() self._validators["textsrc"] = v_heatmap.TextsrcValidator() self._validators["transpose"] = v_heatmap.TransposeValidator() self._validators["uid"] = v_heatmap.UidValidator() self._validators["uirevision"] = v_heatmap.UirevisionValidator() self._validators["visible"] = v_heatmap.VisibleValidator() self._validators["x"] = v_heatmap.XValidator() self._validators["x0"] = v_heatmap.X0Validator() self._validators["xaxis"] = v_heatmap.XAxisValidator() self._validators["xcalendar"] = v_heatmap.XcalendarValidator() self._validators["xgap"] = v_heatmap.XgapValidator() self._validators["xsrc"] = v_heatmap.XsrcValidator() self._validators["xtype"] = v_heatmap.XtypeValidator() self._validators["y"] = v_heatmap.YValidator() self._validators["y0"] = v_heatmap.Y0Validator() self._validators["yaxis"] = v_heatmap.YAxisValidator() self._validators["ycalendar"] = v_heatmap.YcalendarValidator() self._validators["ygap"] = v_heatmap.YgapValidator() self._validators["ysrc"] = v_heatmap.YsrcValidator() self._validators["ytype"] = v_heatmap.YtypeValidator() self._validators["z"] = v_heatmap.ZValidator() self._validators["zauto"] = v_heatmap.ZautoValidator() self._validators["zhoverformat"] = v_heatmap.ZhoverformatValidator() self._validators["zmax"] = v_heatmap.ZmaxValidator() self._validators["zmid"] = v_heatmap.ZmidValidator() self._validators["zmin"] = v_heatmap.ZminValidator() self._validators["zsmooth"] = v_heatmap.ZsmoothValidator() self._validators["zsrc"] = v_heatmap.ZsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autocolorscale", None) self["autocolorscale"] = autocolorscale if autocolorscale is not None else _v _v = arg.pop("coloraxis", None) self["coloraxis"] = coloraxis if coloraxis is not None else _v _v = arg.pop("colorbar", None) self["colorbar"] = colorbar if colorbar is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("connectgaps", None) self["connectgaps"] = connectgaps if connectgaps is not None else _v _v = arg.pop("customdata", None) self["customdata"] = customdata if customdata is not None else _v _v = arg.pop("customdatasrc", None) self["customdatasrc"] = customdatasrc if customdatasrc is not None else _v _v = arg.pop("dx", None) self["dx"] = dx if dx is not None else _v _v = arg.pop("dy", None) self["dy"] = dy if dy is not None else _v _v = arg.pop("hoverinfo", None) self["hoverinfo"] = hoverinfo if hoverinfo is not None else _v _v = arg.pop("hoverinfosrc", None) self["hoverinfosrc"] = hoverinfosrc if hoverinfosrc is not None else _v _v = arg.pop("hoverlabel", None) self["hoverlabel"] = hoverlabel if hoverlabel is not None else _v _v = arg.pop("hoverongaps", None) self["hoverongaps"] = hoverongaps if hoverongaps is not None else _v _v = arg.pop("hovertemplate", None) self["hovertemplate"] = hovertemplate if hovertemplate is not None else _v _v = arg.pop("hovertemplatesrc", None) self["hovertemplatesrc"] = ( hovertemplatesrc if hovertemplatesrc is not None else _v ) _v = arg.pop("hovertext", None) self["hovertext"] = hovertext if hovertext is not None else _v _v = arg.pop("hovertextsrc", None) self["hovertextsrc"] = hovertextsrc if hovertextsrc is not None else _v _v = arg.pop("ids", None) self["ids"] = ids if ids is not None else _v _v = arg.pop("idssrc", None) self["idssrc"] = idssrc if idssrc is not None else _v _v = arg.pop("meta", None) self["meta"] = meta if meta is not None else _v _v = arg.pop("metasrc", None) self["metasrc"] = metasrc if metasrc is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("reversescale", None) self["reversescale"] = reversescale if reversescale is not None else _v _v = arg.pop("showscale", None) self["showscale"] = showscale if showscale is not None else _v _v = arg.pop("stream", None) self["stream"] = stream if stream is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v _v = arg.pop("textsrc", None) self["textsrc"] = textsrc if textsrc is not None else _v _v = arg.pop("transpose", None) self["transpose"] = transpose if transpose is not None else _v _v = arg.pop("uid", None) self["uid"] = uid if uid is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("x0", None) self["x0"] = x0 if x0 is not None else _v _v = arg.pop("xaxis", None) self["xaxis"] = xaxis if xaxis is not None else _v _v = arg.pop("xcalendar", None) self["xcalendar"] = xcalendar if xcalendar is not None else _v _v = arg.pop("xgap", None) self["xgap"] = xgap if xgap is not None else _v _v = arg.pop("xsrc", None) self["xsrc"] = xsrc if xsrc is not None else _v _v = arg.pop("xtype", None) self["xtype"] = xtype if xtype is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("y0", None) self["y0"] = y0 if y0 is not None else _v _v = arg.pop("yaxis", None) self["yaxis"] = yaxis if yaxis is not None else _v _v = arg.pop("ycalendar", None) self["ycalendar"] = ycalendar if ycalendar is not None else _v _v = arg.pop("ygap", None) self["ygap"] = ygap if ygap is not None else _v _v = arg.pop("ysrc", None) self["ysrc"] = ysrc if ysrc is not None else _v _v = arg.pop("ytype", None) self["ytype"] = ytype if ytype is not None else _v _v = arg.pop("z", None) self["z"] = z if z is not None else _v _v = arg.pop("zauto", None) self["zauto"] = zauto if zauto is not None else _v _v = arg.pop("zhoverformat", None) self["zhoverformat"] = zhoverformat if zhoverformat is not None else _v _v = arg.pop("zmax", None) self["zmax"] = zmax if zmax is not None else _v _v = arg.pop("zmid", None) self["zmid"] = zmid if zmid is not None else _v _v = arg.pop("zmin", None) self["zmin"] = zmin if zmin is not None else _v _v = arg.pop("zsmooth", None) self["zsmooth"] = zsmooth if zsmooth is not None else _v _v = arg.pop("zsrc", None) self["zsrc"] = zsrc if zsrc is not None else _v # Read-only literals # ------------------ from _plotly_utils.basevalidators import LiteralValidator self._props["type"] = "heatmap" self._validators["type"] = LiteralValidator( plotly_name="type", parent_name="heatmap", val="heatmap" ) arg.pop("type", None) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceType as _BaseTraceType import copy as _copy class Funnelarea(_BaseTraceType): # aspectratio # ----------- @property def aspectratio(self): """ Sets the ratio between height and width The 'aspectratio' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["aspectratio"] @aspectratio.setter def aspectratio(self, val): self["aspectratio"] = val # baseratio # --------- @property def baseratio(self): """ Sets the ratio between bottom length and maximum top length. The 'baseratio' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["baseratio"] @baseratio.setter def baseratio(self, val): self["baseratio"] = val # customdata # ---------- @property def customdata(self): """ Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements The 'customdata' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["customdata"] @customdata.setter def customdata(self, val): self["customdata"] = val # customdatasrc # ------------- @property def customdatasrc(self): """ Sets the source reference on plot.ly for customdata . The 'customdatasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["customdatasrc"] @customdatasrc.setter def customdatasrc(self, val): self["customdatasrc"] = val # dlabel # ------ @property def dlabel(self): """ Sets the label step. See `label0` for more info. The 'dlabel' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["dlabel"] @dlabel.setter def dlabel(self, val): self["dlabel"] = val # domain # ------ @property def domain(self): """ The 'domain' property is an instance of Domain that may be specified as: - An instance of plotly.graph_objs.funnelarea.Domain - A dict of string/value properties that will be passed to the Domain constructor Supported dict properties: column If there is a layout grid, use the domain for this column in the grid for this funnelarea trace . row If there is a layout grid, use the domain for this row in the grid for this funnelarea trace . x Sets the horizontal domain of this funnelarea trace (in plot fraction). y Sets the vertical domain of this funnelarea trace (in plot fraction). Returns ------- plotly.graph_objs.funnelarea.Domain """ return self["domain"] @domain.setter def domain(self, val): self["domain"] = val # hoverinfo # --------- @property def hoverinfo(self): """ Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. The 'hoverinfo' property is a flaglist and may be specified as a string containing: - Any combination of ['label', 'text', 'value', 'percent', 'name'] joined with '+' characters (e.g. 'label+text') OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') - A list or array of the above Returns ------- Any|numpy.ndarray """ return self["hoverinfo"] @hoverinfo.setter def hoverinfo(self, val): self["hoverinfo"] = val # hoverinfosrc # ------------ @property def hoverinfosrc(self): """ Sets the source reference on plot.ly for hoverinfo . The 'hoverinfosrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hoverinfosrc"] @hoverinfosrc.setter def hoverinfosrc(self, val): self["hoverinfosrc"] = val # hoverlabel # ---------- @property def hoverlabel(self): """ The 'hoverlabel' property is an instance of Hoverlabel that may be specified as: - An instance of plotly.graph_objs.funnelarea.Hoverlabel - A dict of string/value properties that will be passed to the Hoverlabel constructor Supported dict properties: align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- plotly.graph_objs.funnelarea.Hoverlabel """ return self["hoverlabel"] @hoverlabel.setter def hoverlabel(self, val): self["hoverlabel"] = val # hovertemplate # ------------- @property def hovertemplate(self): """ Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event- data. Additionally, every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. variables `label`, `color`, `value`, `text` and `percent`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. The 'hovertemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertemplate"] @hovertemplate.setter def hovertemplate(self, val): self["hovertemplate"] = val # hovertemplatesrc # ---------------- @property def hovertemplatesrc(self): """ Sets the source reference on plot.ly for hovertemplate . The 'hovertemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertemplatesrc"] @hovertemplatesrc.setter def hovertemplatesrc(self, val): self["hovertemplatesrc"] = val # hovertext # --------- @property def hovertext(self): """ Sets hover text elements associated with each sector. If a single string, the same string appears for all data points. If an array of string, the items are mapped in order of this trace's sectors. To be seen, trace `hoverinfo` must contain a "text" flag. The 'hovertext' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertext"] @hovertext.setter def hovertext(self, val): self["hovertext"] = val # hovertextsrc # ------------ @property def hovertextsrc(self): """ Sets the source reference on plot.ly for hovertext . The 'hovertextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertextsrc"] @hovertextsrc.setter def hovertextsrc(self, val): self["hovertextsrc"] = val # ids # --- @property def ids(self): """ Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. The 'ids' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ids"] @ids.setter def ids(self, val): self["ids"] = val # idssrc # ------ @property def idssrc(self): """ Sets the source reference on plot.ly for ids . The 'idssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["idssrc"] @idssrc.setter def idssrc(self, val): self["idssrc"] = val # insidetextfont # -------------- @property def insidetextfont(self): """ Sets the font used for `textinfo` lying inside the sector. The 'insidetextfont' property is an instance of Insidetextfont that may be specified as: - An instance of plotly.graph_objs.funnelarea.Insidetextfont - A dict of string/value properties that will be passed to the Insidetextfont constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.funnelarea.Insidetextfont """ return self["insidetextfont"] @insidetextfont.setter def insidetextfont(self, val): self["insidetextfont"] = val # label0 # ------ @property def label0(self): """ Alternate to `labels`. Builds a numeric set of labels. Use with `dlabel` where `label0` is the starting label and `dlabel` the step. The 'label0' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["label0"] @label0.setter def label0(self, val): self["label0"] = val # labels # ------ @property def labels(self): """ Sets the sector labels. If `labels` entries are duplicated, we sum associated `values` or simply count occurrences if `values` is not provided. For other array attributes (including color) we use the first non-empty entry among all occurrences of the label. The 'labels' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["labels"] @labels.setter def labels(self, val): self["labels"] = val # labelssrc # --------- @property def labelssrc(self): """ Sets the source reference on plot.ly for labels . The 'labelssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["labelssrc"] @labelssrc.setter def labelssrc(self, val): self["labelssrc"] = val # legendgroup # ----------- @property def legendgroup(self): """ Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. The 'legendgroup' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["legendgroup"] @legendgroup.setter def legendgroup(self, val): self["legendgroup"] = val # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.funnelarea.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: colors Sets the color of each sector. If not specified, the default trace color set is used to pick the sector colors. colorssrc Sets the source reference on plot.ly for colors . line plotly.graph_objects.funnelarea.marker.Line instance or dict with compatible properties Returns ------- plotly.graph_objs.funnelarea.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # meta # ---- @property def meta(self): """ Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. The 'meta' property accepts values of any type Returns ------- Any|numpy.ndarray """ return self["meta"] @meta.setter def meta(self, val): self["meta"] = val # metasrc # ------- @property def metasrc(self): """ Sets the source reference on plot.ly for meta . The 'metasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["metasrc"] @metasrc.setter def metasrc(self, val): self["metasrc"] = val # name # ---- @property def name(self): """ Sets the trace name. The trace name appear as the legend item and on hover. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the trace. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # scalegroup # ---------- @property def scalegroup(self): """ If there are multiple funnelareas that should be sized according to their totals, link them by providing a non-empty group id here shared by every trace in the same group. The 'scalegroup' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["scalegroup"] @scalegroup.setter def scalegroup(self, val): self["scalegroup"] = val # showlegend # ---------- @property def showlegend(self): """ Determines whether or not an item corresponding to this trace is shown in the legend. The 'showlegend' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showlegend"] @showlegend.setter def showlegend(self, val): self["showlegend"] = val # stream # ------ @property def stream(self): """ The 'stream' property is an instance of Stream that may be specified as: - An instance of plotly.graph_objs.funnelarea.Stream - A dict of string/value properties that will be passed to the Stream constructor Supported dict properties: maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- plotly.graph_objs.funnelarea.Stream """ return self["stream"] @stream.setter def stream(self, val): self["stream"] = val # text # ---- @property def text(self): """ Sets text elements associated with each sector. If trace `textinfo` contains a "text" flag, these elements will be seen on the chart. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. The 'text' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["text"] @text.setter def text(self, val): self["text"] = val # textfont # -------- @property def textfont(self): """ Sets the font used for `textinfo`. The 'textfont' property is an instance of Textfont that may be specified as: - An instance of plotly.graph_objs.funnelarea.Textfont - A dict of string/value properties that will be passed to the Textfont constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.funnelarea.Textfont """ return self["textfont"] @textfont.setter def textfont(self, val): self["textfont"] = val # textinfo # -------- @property def textinfo(self): """ Determines which trace information appear on the graph. The 'textinfo' property is a flaglist and may be specified as a string containing: - Any combination of ['label', 'text', 'value', 'percent'] joined with '+' characters (e.g. 'label+text') OR exactly one of ['none'] (e.g. 'none') Returns ------- Any """ return self["textinfo"] @textinfo.setter def textinfo(self, val): self["textinfo"] = val # textposition # ------------ @property def textposition(self): """ Specifies the location of the `textinfo`. The 'textposition' property is an enumeration that may be specified as: - One of the following enumeration values: ['inside', 'none'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["textposition"] @textposition.setter def textposition(self, val): self["textposition"] = val # textpositionsrc # --------------- @property def textpositionsrc(self): """ Sets the source reference on plot.ly for textposition . The 'textpositionsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["textpositionsrc"] @textpositionsrc.setter def textpositionsrc(self, val): self["textpositionsrc"] = val # textsrc # ------- @property def textsrc(self): """ Sets the source reference on plot.ly for text . The 'textsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["textsrc"] @textsrc.setter def textsrc(self, val): self["textsrc"] = val # texttemplate # ------------ @property def texttemplate(self): """ Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `label`, `color`, `value`, `text` and `percent`. The 'texttemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["texttemplate"] @texttemplate.setter def texttemplate(self, val): self["texttemplate"] = val # texttemplatesrc # --------------- @property def texttemplatesrc(self): """ Sets the source reference on plot.ly for texttemplate . The 'texttemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["texttemplatesrc"] @texttemplatesrc.setter def texttemplatesrc(self, val): self["texttemplatesrc"] = val # title # ----- @property def title(self): """ The 'title' property is an instance of Title that may be specified as: - An instance of plotly.graph_objs.funnelarea.Title - A dict of string/value properties that will be passed to the Title constructor Supported dict properties: font Sets the font used for `title`. Note that the title's font used to be set by the now deprecated `titlefont` attribute. position Specifies the location of the `title`. Note that the title's position used to be set by the now deprecated `titleposition` attribute. text Sets the title of the chart. If it is empty, no title is displayed. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- plotly.graph_objs.funnelarea.Title """ return self["title"] @title.setter def title(self, val): self["title"] = val # uid # --- @property def uid(self): """ Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. The 'uid' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["uid"] @uid.setter def uid(self, val): self["uid"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # values # ------ @property def values(self): """ Sets the values of the sectors. If omitted, we count occurrences of each label. The 'values' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["values"] @values.setter def values(self, val): self["values"] = val # valuessrc # --------- @property def valuessrc(self): """ Sets the source reference on plot.ly for values . The 'valuessrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["valuessrc"] @valuessrc.setter def valuessrc(self, val): self["valuessrc"] = val # visible # ------- @property def visible(self): """ Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). The 'visible' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'legendonly'] Returns ------- Any """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # type # ---- @property def type(self): return self._props["type"] # property parent name # -------------------- @property def _parent_path_str(self): return "" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ aspectratio Sets the ratio between height and width baseratio Sets the ratio between bottom length and maximum top length. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dlabel Sets the label step. See `label0` for more info. domain plotly.graph_objects.funnelarea.Domain instance or dict with compatible properties hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.funnelarea.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `label`, `color`, `value`, `text` and `percent`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each sector. If a single string, the same string appears for all data points. If an array of string, the items are mapped in order of this trace's sectors. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . insidetextfont Sets the font used for `textinfo` lying inside the sector. label0 Alternate to `labels`. Builds a numeric set of labels. Use with `dlabel` where `label0` is the starting label and `dlabel` the step. labels Sets the sector labels. If `labels` entries are duplicated, we sum associated `values` or simply count occurrences if `values` is not provided. For other array attributes (including color) we use the first non-empty entry among all occurrences of the label. labelssrc Sets the source reference on plot.ly for labels . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. marker plotly.graph_objects.funnelarea.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. scalegroup If there are multiple funnelareas that should be sized according to their totals, link them by providing a non-empty group id here shared by every trace in the same group. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.funnelarea.Stream instance or dict with compatible properties text Sets text elements associated with each sector. If trace `textinfo` contains a "text" flag, these elements will be seen on the chart. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the font used for `textinfo`. textinfo Determines which trace information appear on the graph. textposition Specifies the location of the `textinfo`. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `label`, `color`, `value`, `text` and `percent`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . title plotly.graph_objects.funnelarea.Title instance or dict with compatible properties uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. values Sets the values of the sectors. If omitted, we count occurrences of each label. valuessrc Sets the source reference on plot.ly for values . visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). """ def __init__( self, arg=None, aspectratio=None, baseratio=None, customdata=None, customdatasrc=None, dlabel=None, domain=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, insidetextfont=None, label0=None, labels=None, labelssrc=None, legendgroup=None, marker=None, meta=None, metasrc=None, name=None, opacity=None, scalegroup=None, showlegend=None, stream=None, text=None, textfont=None, textinfo=None, textposition=None, textpositionsrc=None, textsrc=None, texttemplate=None, texttemplatesrc=None, title=None, uid=None, uirevision=None, values=None, valuessrc=None, visible=None, **kwargs ): """ Construct a new Funnelarea object Visualize stages in a process using area-encoded trapezoids. This trace can be used to show data in a part-to-whole representation similar to a "pie" trace, wherein each item appears in a single stage. See also the "funnel" trace type for a different approach to visualizing funnel data. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.Funnelarea aspectratio Sets the ratio between height and width baseratio Sets the ratio between bottom length and maximum top length. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dlabel Sets the label step. See `label0` for more info. domain plotly.graph_objects.funnelarea.Domain instance or dict with compatible properties hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.funnelarea.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `label`, `color`, `value`, `text` and `percent`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each sector. If a single string, the same string appears for all data points. If an array of string, the items are mapped in order of this trace's sectors. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . insidetextfont Sets the font used for `textinfo` lying inside the sector. label0 Alternate to `labels`. Builds a numeric set of labels. Use with `dlabel` where `label0` is the starting label and `dlabel` the step. labels Sets the sector labels. If `labels` entries are duplicated, we sum associated `values` or simply count occurrences if `values` is not provided. For other array attributes (including color) we use the first non-empty entry among all occurrences of the label. labelssrc Sets the source reference on plot.ly for labels . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. marker plotly.graph_objects.funnelarea.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. scalegroup If there are multiple funnelareas that should be sized according to their totals, link them by providing a non-empty group id here shared by every trace in the same group. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.funnelarea.Stream instance or dict with compatible properties text Sets text elements associated with each sector. If trace `textinfo` contains a "text" flag, these elements will be seen on the chart. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the font used for `textinfo`. textinfo Determines which trace information appear on the graph. textposition Specifies the location of the `textinfo`. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `label`, `color`, `value`, `text` and `percent`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . title plotly.graph_objects.funnelarea.Title instance or dict with compatible properties uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. values Sets the values of the sectors. If omitted, we count occurrences of each label. valuessrc Sets the source reference on plot.ly for values . visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). Returns ------- Funnelarea """ super(Funnelarea, self).__init__("funnelarea") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.Funnelarea constructor must be a dict or an instance of plotly.graph_objs.Funnelarea""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators import funnelarea as v_funnelarea # Initialize validators # --------------------- self._validators["aspectratio"] = v_funnelarea.AspectratioValidator() self._validators["baseratio"] = v_funnelarea.BaseratioValidator() self._validators["customdata"] = v_funnelarea.CustomdataValidator() self._validators["customdatasrc"] = v_funnelarea.CustomdatasrcValidator() self._validators["dlabel"] = v_funnelarea.DlabelValidator() self._validators["domain"] = v_funnelarea.DomainValidator() self._validators["hoverinfo"] = v_funnelarea.HoverinfoValidator() self._validators["hoverinfosrc"] = v_funnelarea.HoverinfosrcValidator() self._validators["hoverlabel"] = v_funnelarea.HoverlabelValidator() self._validators["hovertemplate"] = v_funnelarea.HovertemplateValidator() self._validators["hovertemplatesrc"] = v_funnelarea.HovertemplatesrcValidator() self._validators["hovertext"] = v_funnelarea.HovertextValidator() self._validators["hovertextsrc"] = v_funnelarea.HovertextsrcValidator() self._validators["ids"] = v_funnelarea.IdsValidator() self._validators["idssrc"] = v_funnelarea.IdssrcValidator() self._validators["insidetextfont"] = v_funnelarea.InsidetextfontValidator() self._validators["label0"] = v_funnelarea.Label0Validator() self._validators["labels"] = v_funnelarea.LabelsValidator() self._validators["labelssrc"] = v_funnelarea.LabelssrcValidator() self._validators["legendgroup"] = v_funnelarea.LegendgroupValidator() self._validators["marker"] = v_funnelarea.MarkerValidator() self._validators["meta"] = v_funnelarea.MetaValidator() self._validators["metasrc"] = v_funnelarea.MetasrcValidator() self._validators["name"] = v_funnelarea.NameValidator() self._validators["opacity"] = v_funnelarea.OpacityValidator() self._validators["scalegroup"] = v_funnelarea.ScalegroupValidator() self._validators["showlegend"] = v_funnelarea.ShowlegendValidator() self._validators["stream"] = v_funnelarea.StreamValidator() self._validators["text"] = v_funnelarea.TextValidator() self._validators["textfont"] = v_funnelarea.TextfontValidator() self._validators["textinfo"] = v_funnelarea.TextinfoValidator() self._validators["textposition"] = v_funnelarea.TextpositionValidator() self._validators["textpositionsrc"] = v_funnelarea.TextpositionsrcValidator() self._validators["textsrc"] = v_funnelarea.TextsrcValidator() self._validators["texttemplate"] = v_funnelarea.TexttemplateValidator() self._validators["texttemplatesrc"] = v_funnelarea.TexttemplatesrcValidator() self._validators["title"] = v_funnelarea.TitleValidator() self._validators["uid"] = v_funnelarea.UidValidator() self._validators["uirevision"] = v_funnelarea.UirevisionValidator() self._validators["values"] = v_funnelarea.ValuesValidator() self._validators["valuessrc"] = v_funnelarea.ValuessrcValidator() self._validators["visible"] = v_funnelarea.VisibleValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("aspectratio", None) self["aspectratio"] = aspectratio if aspectratio is not None else _v _v = arg.pop("baseratio", None) self["baseratio"] = baseratio if baseratio is not None else _v _v = arg.pop("customdata", None) self["customdata"] = customdata if customdata is not None else _v _v = arg.pop("customdatasrc", None) self["customdatasrc"] = customdatasrc if customdatasrc is not None else _v _v = arg.pop("dlabel", None) self["dlabel"] = dlabel if dlabel is not None else _v _v = arg.pop("domain", None) self["domain"] = domain if domain is not None else _v _v = arg.pop("hoverinfo", None) self["hoverinfo"] = hoverinfo if hoverinfo is not None else _v _v = arg.pop("hoverinfosrc", None) self["hoverinfosrc"] = hoverinfosrc if hoverinfosrc is not None else _v _v = arg.pop("hoverlabel", None) self["hoverlabel"] = hoverlabel if hoverlabel is not None else _v _v = arg.pop("hovertemplate", None) self["hovertemplate"] = hovertemplate if hovertemplate is not None else _v _v = arg.pop("hovertemplatesrc", None) self["hovertemplatesrc"] = ( hovertemplatesrc if hovertemplatesrc is not None else _v ) _v = arg.pop("hovertext", None) self["hovertext"] = hovertext if hovertext is not None else _v _v = arg.pop("hovertextsrc", None) self["hovertextsrc"] = hovertextsrc if hovertextsrc is not None else _v _v = arg.pop("ids", None) self["ids"] = ids if ids is not None else _v _v = arg.pop("idssrc", None) self["idssrc"] = idssrc if idssrc is not None else _v _v = arg.pop("insidetextfont", None) self["insidetextfont"] = insidetextfont if insidetextfont is not None else _v _v = arg.pop("label0", None) self["label0"] = label0 if label0 is not None else _v _v = arg.pop("labels", None) self["labels"] = labels if labels is not None else _v _v = arg.pop("labelssrc", None) self["labelssrc"] = labelssrc if labelssrc is not None else _v _v = arg.pop("legendgroup", None) self["legendgroup"] = legendgroup if legendgroup is not None else _v _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v _v = arg.pop("meta", None) self["meta"] = meta if meta is not None else _v _v = arg.pop("metasrc", None) self["metasrc"] = metasrc if metasrc is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("scalegroup", None) self["scalegroup"] = scalegroup if scalegroup is not None else _v _v = arg.pop("showlegend", None) self["showlegend"] = showlegend if showlegend is not None else _v _v = arg.pop("stream", None) self["stream"] = stream if stream is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v _v = arg.pop("textfont", None) self["textfont"] = textfont if textfont is not None else _v _v = arg.pop("textinfo", None) self["textinfo"] = textinfo if textinfo is not None else _v _v = arg.pop("textposition", None) self["textposition"] = textposition if textposition is not None else _v _v = arg.pop("textpositionsrc", None) self["textpositionsrc"] = textpositionsrc if textpositionsrc is not None else _v _v = arg.pop("textsrc", None) self["textsrc"] = textsrc if textsrc is not None else _v _v = arg.pop("texttemplate", None) self["texttemplate"] = texttemplate if texttemplate is not None else _v _v = arg.pop("texttemplatesrc", None) self["texttemplatesrc"] = texttemplatesrc if texttemplatesrc is not None else _v _v = arg.pop("title", None) self["title"] = title if title is not None else _v _v = arg.pop("uid", None) self["uid"] = uid if uid is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("values", None) self["values"] = values if values is not None else _v _v = arg.pop("valuessrc", None) self["valuessrc"] = valuessrc if valuessrc is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v # Read-only literals # ------------------ from _plotly_utils.basevalidators import LiteralValidator self._props["type"] = "funnelarea" self._validators["type"] = LiteralValidator( plotly_name="type", parent_name="funnelarea", val="funnelarea" ) arg.pop("type", None) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceType as _BaseTraceType import copy as _copy class Funnel(_BaseTraceType): # alignmentgroup # -------------- @property def alignmentgroup(self): """ Set several traces linked to the same position axis or matching axes to the same alignmentgroup. This controls whether bars compute their positional range dependently or independently. The 'alignmentgroup' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["alignmentgroup"] @alignmentgroup.setter def alignmentgroup(self, val): self["alignmentgroup"] = val # cliponaxis # ---------- @property def cliponaxis(self): """ Determines whether the text nodes are clipped about the subplot axes. To show the text nodes above axis lines and tick labels, make sure to set `xaxis.layer` and `yaxis.layer` to *below traces*. The 'cliponaxis' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["cliponaxis"] @cliponaxis.setter def cliponaxis(self, val): self["cliponaxis"] = val # connector # --------- @property def connector(self): """ The 'connector' property is an instance of Connector that may be specified as: - An instance of plotly.graph_objs.funnel.Connector - A dict of string/value properties that will be passed to the Connector constructor Supported dict properties: fillcolor Sets the fill color. line plotly.graph_objects.funnel.connector.Line instance or dict with compatible properties visible Determines if connector regions and lines are drawn. Returns ------- plotly.graph_objs.funnel.Connector """ return self["connector"] @connector.setter def connector(self, val): self["connector"] = val # constraintext # ------------- @property def constraintext(self): """ Constrain the size of text inside or outside a bar to be no larger than the bar itself. The 'constraintext' property is an enumeration that may be specified as: - One of the following enumeration values: ['inside', 'outside', 'both', 'none'] Returns ------- Any """ return self["constraintext"] @constraintext.setter def constraintext(self, val): self["constraintext"] = val # customdata # ---------- @property def customdata(self): """ Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements The 'customdata' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["customdata"] @customdata.setter def customdata(self, val): self["customdata"] = val # customdatasrc # ------------- @property def customdatasrc(self): """ Sets the source reference on plot.ly for customdata . The 'customdatasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["customdatasrc"] @customdatasrc.setter def customdatasrc(self, val): self["customdatasrc"] = val # dx # -- @property def dx(self): """ Sets the x coordinate step. See `x0` for more info. The 'dx' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["dx"] @dx.setter def dx(self, val): self["dx"] = val # dy # -- @property def dy(self): """ Sets the y coordinate step. See `y0` for more info. The 'dy' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["dy"] @dy.setter def dy(self, val): self["dy"] = val # hoverinfo # --------- @property def hoverinfo(self): """ Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. The 'hoverinfo' property is a flaglist and may be specified as a string containing: - Any combination of ['name', 'x', 'y', 'text', 'percent initial', 'percent previous', 'percent total'] joined with '+' characters (e.g. 'name+x') OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') - A list or array of the above Returns ------- Any|numpy.ndarray """ return self["hoverinfo"] @hoverinfo.setter def hoverinfo(self, val): self["hoverinfo"] = val # hoverinfosrc # ------------ @property def hoverinfosrc(self): """ Sets the source reference on plot.ly for hoverinfo . The 'hoverinfosrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hoverinfosrc"] @hoverinfosrc.setter def hoverinfosrc(self, val): self["hoverinfosrc"] = val # hoverlabel # ---------- @property def hoverlabel(self): """ The 'hoverlabel' property is an instance of Hoverlabel that may be specified as: - An instance of plotly.graph_objs.funnel.Hoverlabel - A dict of string/value properties that will be passed to the Hoverlabel constructor Supported dict properties: align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- plotly.graph_objs.funnel.Hoverlabel """ return self["hoverlabel"] @hoverlabel.setter def hoverlabel(self, val): self["hoverlabel"] = val # hovertemplate # ------------- @property def hovertemplate(self): """ Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event- data. Additionally, every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. variables `percentInitial`, `percentPrevious` and `percentTotal`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. The 'hovertemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertemplate"] @hovertemplate.setter def hovertemplate(self, val): self["hovertemplate"] = val # hovertemplatesrc # ---------------- @property def hovertemplatesrc(self): """ Sets the source reference on plot.ly for hovertemplate . The 'hovertemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertemplatesrc"] @hovertemplatesrc.setter def hovertemplatesrc(self, val): self["hovertemplatesrc"] = val # hovertext # --------- @property def hovertext(self): """ Sets hover text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. The 'hovertext' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertext"] @hovertext.setter def hovertext(self, val): self["hovertext"] = val # hovertextsrc # ------------ @property def hovertextsrc(self): """ Sets the source reference on plot.ly for hovertext . The 'hovertextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertextsrc"] @hovertextsrc.setter def hovertextsrc(self, val): self["hovertextsrc"] = val # ids # --- @property def ids(self): """ Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. The 'ids' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ids"] @ids.setter def ids(self, val): self["ids"] = val # idssrc # ------ @property def idssrc(self): """ Sets the source reference on plot.ly for ids . The 'idssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["idssrc"] @idssrc.setter def idssrc(self, val): self["idssrc"] = val # insidetextanchor # ---------------- @property def insidetextanchor(self): """ Determines if texts are kept at center or start/end points in `textposition` "inside" mode. The 'insidetextanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['end', 'middle', 'start'] Returns ------- Any """ return self["insidetextanchor"] @insidetextanchor.setter def insidetextanchor(self, val): self["insidetextanchor"] = val # insidetextfont # -------------- @property def insidetextfont(self): """ Sets the font used for `text` lying inside the bar. The 'insidetextfont' property is an instance of Insidetextfont that may be specified as: - An instance of plotly.graph_objs.funnel.Insidetextfont - A dict of string/value properties that will be passed to the Insidetextfont constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.funnel.Insidetextfont """ return self["insidetextfont"] @insidetextfont.setter def insidetextfont(self, val): self["insidetextfont"] = val # legendgroup # ----------- @property def legendgroup(self): """ Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. The 'legendgroup' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["legendgroup"] @legendgroup.setter def legendgroup(self, val): self["legendgroup"] = val # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.funnel.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.funnel.marker.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . line plotly.graph_objects.funnel.marker.Line instance or dict with compatible properties opacity Sets the opacity of the bars. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. Returns ------- plotly.graph_objs.funnel.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # meta # ---- @property def meta(self): """ Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. The 'meta' property accepts values of any type Returns ------- Any|numpy.ndarray """ return self["meta"] @meta.setter def meta(self, val): self["meta"] = val # metasrc # ------- @property def metasrc(self): """ Sets the source reference on plot.ly for meta . The 'metasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["metasrc"] @metasrc.setter def metasrc(self, val): self["metasrc"] = val # name # ---- @property def name(self): """ Sets the trace name. The trace name appear as the legend item and on hover. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # offset # ------ @property def offset(self): """ Shifts the position where the bar is drawn (in position axis units). In "group" barmode, traces that set "offset" will be excluded and drawn in "overlay" mode instead. The 'offset' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["offset"] @offset.setter def offset(self, val): self["offset"] = val # offsetgroup # ----------- @property def offsetgroup(self): """ Set several traces linked to the same position axis or matching axes to the same offsetgroup where bars of the same position coordinate will line up. The 'offsetgroup' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["offsetgroup"] @offsetgroup.setter def offsetgroup(self, val): self["offsetgroup"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the trace. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # orientation # ----------- @property def orientation(self): """ Sets the orientation of the funnels. With "v" ("h"), the value of the each bar spans along the vertical (horizontal). By default funnels are tend to be oriented horizontally; unless only "y" array is presented or orientation is set to "v". Also regarding graphs including only 'horizontal' funnels, "autorange" on the "y-axis" are set to "reversed". The 'orientation' property is an enumeration that may be specified as: - One of the following enumeration values: ['v', 'h'] Returns ------- Any """ return self["orientation"] @orientation.setter def orientation(self, val): self["orientation"] = val # outsidetextfont # --------------- @property def outsidetextfont(self): """ Sets the font used for `text` lying outside the bar. The 'outsidetextfont' property is an instance of Outsidetextfont that may be specified as: - An instance of plotly.graph_objs.funnel.Outsidetextfont - A dict of string/value properties that will be passed to the Outsidetextfont constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.funnel.Outsidetextfont """ return self["outsidetextfont"] @outsidetextfont.setter def outsidetextfont(self, val): self["outsidetextfont"] = val # selectedpoints # -------------- @property def selectedpoints(self): """ Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. The 'selectedpoints' property accepts values of any type Returns ------- Any """ return self["selectedpoints"] @selectedpoints.setter def selectedpoints(self, val): self["selectedpoints"] = val # showlegend # ---------- @property def showlegend(self): """ Determines whether or not an item corresponding to this trace is shown in the legend. The 'showlegend' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showlegend"] @showlegend.setter def showlegend(self, val): self["showlegend"] = val # stream # ------ @property def stream(self): """ The 'stream' property is an instance of Stream that may be specified as: - An instance of plotly.graph_objs.funnel.Stream - A dict of string/value properties that will be passed to the Stream constructor Supported dict properties: maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- plotly.graph_objs.funnel.Stream """ return self["stream"] @stream.setter def stream(self, val): self["stream"] = val # text # ---- @property def text(self): """ Sets text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["text"] @text.setter def text(self, val): self["text"] = val # textangle # --------- @property def textangle(self): """ Sets the angle of the tick labels with respect to the bar. For example, a `tickangle` of -90 draws the tick labels vertically. With "auto" the texts may automatically be rotated to fit with the maximum size in bars. The 'textangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["textangle"] @textangle.setter def textangle(self, val): self["textangle"] = val # textfont # -------- @property def textfont(self): """ Sets the font used for `text`. The 'textfont' property is an instance of Textfont that may be specified as: - An instance of plotly.graph_objs.funnel.Textfont - A dict of string/value properties that will be passed to the Textfont constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.funnel.Textfont """ return self["textfont"] @textfont.setter def textfont(self, val): self["textfont"] = val # textinfo # -------- @property def textinfo(self): """ Determines which trace information appear on the graph. In the case of having multiple funnels, percentages & totals are computed separately (per trace). The 'textinfo' property is a flaglist and may be specified as a string containing: - Any combination of ['label', 'text', 'percent initial', 'percent previous', 'percent total', 'value'] joined with '+' characters (e.g. 'label+text') OR exactly one of ['none'] (e.g. 'none') Returns ------- Any """ return self["textinfo"] @textinfo.setter def textinfo(self, val): self["textinfo"] = val # textposition # ------------ @property def textposition(self): """ Specifies the location of the `text`. "inside" positions `text` inside, next to the bar end (rotated and scaled if needed). "outside" positions `text` outside, next to the bar end (scaled if needed), unless there is another bar stacked on this one, then the text gets pushed inside. "auto" tries to position `text` inside the bar, but if the bar is too small and no bar is stacked on this one the text is moved outside. The 'textposition' property is an enumeration that may be specified as: - One of the following enumeration values: ['inside', 'outside', 'auto', 'none'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["textposition"] @textposition.setter def textposition(self, val): self["textposition"] = val # textpositionsrc # --------------- @property def textpositionsrc(self): """ Sets the source reference on plot.ly for textposition . The 'textpositionsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["textpositionsrc"] @textpositionsrc.setter def textpositionsrc(self, val): self["textpositionsrc"] = val # textsrc # ------- @property def textsrc(self): """ Sets the source reference on plot.ly for text . The 'textsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["textsrc"] @textsrc.setter def textsrc(self, val): self["textsrc"] = val # texttemplate # ------------ @property def texttemplate(self): """ Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `percentInitial`, `percentPrevious`, `percentTotal`, `label` and `value`. The 'texttemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["texttemplate"] @texttemplate.setter def texttemplate(self, val): self["texttemplate"] = val # texttemplatesrc # --------------- @property def texttemplatesrc(self): """ Sets the source reference on plot.ly for texttemplate . The 'texttemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["texttemplatesrc"] @texttemplatesrc.setter def texttemplatesrc(self, val): self["texttemplatesrc"] = val # uid # --- @property def uid(self): """ Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. The 'uid' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["uid"] @uid.setter def uid(self, val): self["uid"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # visible # ------- @property def visible(self): """ Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). The 'visible' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'legendonly'] Returns ------- Any """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # width # ----- @property def width(self): """ Sets the bar width (in position axis units). The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # x # - @property def x(self): """ Sets the x coordinates. The 'x' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["x"] @x.setter def x(self, val): self["x"] = val # x0 # -- @property def x0(self): """ Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. The 'x0' property accepts values of any type Returns ------- Any """ return self["x0"] @x0.setter def x0(self, val): self["x0"] = val # xaxis # ----- @property def xaxis(self): """ Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. The 'xaxis' property is an identifier of a particular subplot, of type 'x', that may be specified as the string 'x' optionally followed by an integer >= 1 (e.g. 'x', 'x1', 'x2', 'x3', etc.) Returns ------- str """ return self["xaxis"] @xaxis.setter def xaxis(self, val): self["xaxis"] = val # xsrc # ---- @property def xsrc(self): """ Sets the source reference on plot.ly for x . The 'xsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["xsrc"] @xsrc.setter def xsrc(self, val): self["xsrc"] = val # y # - @property def y(self): """ Sets the y coordinates. The 'y' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["y"] @y.setter def y(self, val): self["y"] = val # y0 # -- @property def y0(self): """ Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. The 'y0' property accepts values of any type Returns ------- Any """ return self["y0"] @y0.setter def y0(self, val): self["y0"] = val # yaxis # ----- @property def yaxis(self): """ Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. The 'yaxis' property is an identifier of a particular subplot, of type 'y', that may be specified as the string 'y' optionally followed by an integer >= 1 (e.g. 'y', 'y1', 'y2', 'y3', etc.) Returns ------- str """ return self["yaxis"] @yaxis.setter def yaxis(self, val): self["yaxis"] = val # ysrc # ---- @property def ysrc(self): """ Sets the source reference on plot.ly for y . The 'ysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ysrc"] @ysrc.setter def ysrc(self, val): self["ysrc"] = val # type # ---- @property def type(self): return self._props["type"] # property parent name # -------------------- @property def _parent_path_str(self): return "" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ alignmentgroup Set several traces linked to the same position axis or matching axes to the same alignmentgroup. This controls whether bars compute their positional range dependently or independently. cliponaxis Determines whether the text nodes are clipped about the subplot axes. To show the text nodes above axis lines and tick labels, make sure to set `xaxis.layer` and `yaxis.layer` to *below traces*. connector plotly.graph_objects.funnel.Connector instance or dict with compatible properties constraintext Constrain the size of text inside or outside a bar to be no larger than the bar itself. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dx Sets the x coordinate step. See `x0` for more info. dy Sets the y coordinate step. See `y0` for more info. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.funnel.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `percentInitial`, `percentPrevious` and `percentTotal`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . insidetextanchor Determines if texts are kept at center or start/end points in `textposition` "inside" mode. insidetextfont Sets the font used for `text` lying inside the bar. legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. marker plotly.graph_objects.funnel.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. offset Shifts the position where the bar is drawn (in position axis units). In "group" barmode, traces that set "offset" will be excluded and drawn in "overlay" mode instead. offsetgroup Set several traces linked to the same position axis or matching axes to the same offsetgroup where bars of the same position coordinate will line up. opacity Sets the opacity of the trace. orientation Sets the orientation of the funnels. With "v" ("h"), the value of the each bar spans along the vertical (horizontal). By default funnels are tend to be oriented horizontally; unless only "y" array is presented or orientation is set to "v". Also regarding graphs including only 'horizontal' funnels, "autorange" on the "y-axis" are set to "reversed". outsidetextfont Sets the font used for `text` lying outside the bar. selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.funnel.Stream instance or dict with compatible properties text Sets text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textangle Sets the angle of the tick labels with respect to the bar. For example, a `tickangle` of -90 draws the tick labels vertically. With "auto" the texts may automatically be rotated to fit with the maximum size in bars. textfont Sets the font used for `text`. textinfo Determines which trace information appear on the graph. In the case of having multiple funnels, percentages & totals are computed separately (per trace). textposition Specifies the location of the `text`. "inside" positions `text` inside, next to the bar end (rotated and scaled if needed). "outside" positions `text` outside, next to the bar end (scaled if needed), unless there is another bar stacked on this one, then the text gets pushed inside. "auto" tries to position `text` inside the bar, but if the bar is too small and no bar is stacked on this one the text is moved outside. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `percentInitial`, `percentPrevious`, `percentTotal`, `label` and `value`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). width Sets the bar width (in position axis units). x Sets the x coordinates. x0 Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xsrc Sets the source reference on plot.ly for x . y Sets the y coordinates. y0 Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ysrc Sets the source reference on plot.ly for y . """ def __init__( self, arg=None, alignmentgroup=None, cliponaxis=None, connector=None, constraintext=None, customdata=None, customdatasrc=None, dx=None, dy=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, insidetextanchor=None, insidetextfont=None, legendgroup=None, marker=None, meta=None, metasrc=None, name=None, offset=None, offsetgroup=None, opacity=None, orientation=None, outsidetextfont=None, selectedpoints=None, showlegend=None, stream=None, text=None, textangle=None, textfont=None, textinfo=None, textposition=None, textpositionsrc=None, textsrc=None, texttemplate=None, texttemplatesrc=None, uid=None, uirevision=None, visible=None, width=None, x=None, x0=None, xaxis=None, xsrc=None, y=None, y0=None, yaxis=None, ysrc=None, **kwargs ): """ Construct a new Funnel object Visualize stages in a process using length-encoded bars. This trace can be used to show data in either a part-to-whole representation wherein each item appears in a single stage, or in a "drop-off" representation wherein each item appears in each stage it traversed. See also the "funnelarea" trace type for a different approach to visualizing funnel data. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.Funnel alignmentgroup Set several traces linked to the same position axis or matching axes to the same alignmentgroup. This controls whether bars compute their positional range dependently or independently. cliponaxis Determines whether the text nodes are clipped about the subplot axes. To show the text nodes above axis lines and tick labels, make sure to set `xaxis.layer` and `yaxis.layer` to *below traces*. connector plotly.graph_objects.funnel.Connector instance or dict with compatible properties constraintext Constrain the size of text inside or outside a bar to be no larger than the bar itself. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dx Sets the x coordinate step. See `x0` for more info. dy Sets the y coordinate step. See `y0` for more info. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.funnel.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `percentInitial`, `percentPrevious` and `percentTotal`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . insidetextanchor Determines if texts are kept at center or start/end points in `textposition` "inside" mode. insidetextfont Sets the font used for `text` lying inside the bar. legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. marker plotly.graph_objects.funnel.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. offset Shifts the position where the bar is drawn (in position axis units). In "group" barmode, traces that set "offset" will be excluded and drawn in "overlay" mode instead. offsetgroup Set several traces linked to the same position axis or matching axes to the same offsetgroup where bars of the same position coordinate will line up. opacity Sets the opacity of the trace. orientation Sets the orientation of the funnels. With "v" ("h"), the value of the each bar spans along the vertical (horizontal). By default funnels are tend to be oriented horizontally; unless only "y" array is presented or orientation is set to "v". Also regarding graphs including only 'horizontal' funnels, "autorange" on the "y-axis" are set to "reversed". outsidetextfont Sets the font used for `text` lying outside the bar. selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.funnel.Stream instance or dict with compatible properties text Sets text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textangle Sets the angle of the tick labels with respect to the bar. For example, a `tickangle` of -90 draws the tick labels vertically. With "auto" the texts may automatically be rotated to fit with the maximum size in bars. textfont Sets the font used for `text`. textinfo Determines which trace information appear on the graph. In the case of having multiple funnels, percentages & totals are computed separately (per trace). textposition Specifies the location of the `text`. "inside" positions `text` inside, next to the bar end (rotated and scaled if needed). "outside" positions `text` outside, next to the bar end (scaled if needed), unless there is another bar stacked on this one, then the text gets pushed inside. "auto" tries to position `text` inside the bar, but if the bar is too small and no bar is stacked on this one the text is moved outside. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `percentInitial`, `percentPrevious`, `percentTotal`, `label` and `value`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). width Sets the bar width (in position axis units). x Sets the x coordinates. x0 Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xsrc Sets the source reference on plot.ly for x . y Sets the y coordinates. y0 Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ysrc Sets the source reference on plot.ly for y . Returns ------- Funnel """ super(Funnel, self).__init__("funnel") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.Funnel constructor must be a dict or an instance of plotly.graph_objs.Funnel""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators import funnel as v_funnel # Initialize validators # --------------------- self._validators["alignmentgroup"] = v_funnel.AlignmentgroupValidator() self._validators["cliponaxis"] = v_funnel.CliponaxisValidator() self._validators["connector"] = v_funnel.ConnectorValidator() self._validators["constraintext"] = v_funnel.ConstraintextValidator() self._validators["customdata"] = v_funnel.CustomdataValidator() self._validators["customdatasrc"] = v_funnel.CustomdatasrcValidator() self._validators["dx"] = v_funnel.DxValidator() self._validators["dy"] = v_funnel.DyValidator() self._validators["hoverinfo"] = v_funnel.HoverinfoValidator() self._validators["hoverinfosrc"] = v_funnel.HoverinfosrcValidator() self._validators["hoverlabel"] = v_funnel.HoverlabelValidator() self._validators["hovertemplate"] = v_funnel.HovertemplateValidator() self._validators["hovertemplatesrc"] = v_funnel.HovertemplatesrcValidator() self._validators["hovertext"] = v_funnel.HovertextValidator() self._validators["hovertextsrc"] = v_funnel.HovertextsrcValidator() self._validators["ids"] = v_funnel.IdsValidator() self._validators["idssrc"] = v_funnel.IdssrcValidator() self._validators["insidetextanchor"] = v_funnel.InsidetextanchorValidator() self._validators["insidetextfont"] = v_funnel.InsidetextfontValidator() self._validators["legendgroup"] = v_funnel.LegendgroupValidator() self._validators["marker"] = v_funnel.MarkerValidator() self._validators["meta"] = v_funnel.MetaValidator() self._validators["metasrc"] = v_funnel.MetasrcValidator() self._validators["name"] = v_funnel.NameValidator() self._validators["offset"] = v_funnel.OffsetValidator() self._validators["offsetgroup"] = v_funnel.OffsetgroupValidator() self._validators["opacity"] = v_funnel.OpacityValidator() self._validators["orientation"] = v_funnel.OrientationValidator() self._validators["outsidetextfont"] = v_funnel.OutsidetextfontValidator() self._validators["selectedpoints"] = v_funnel.SelectedpointsValidator() self._validators["showlegend"] = v_funnel.ShowlegendValidator() self._validators["stream"] = v_funnel.StreamValidator() self._validators["text"] = v_funnel.TextValidator() self._validators["textangle"] = v_funnel.TextangleValidator() self._validators["textfont"] = v_funnel.TextfontValidator() self._validators["textinfo"] = v_funnel.TextinfoValidator() self._validators["textposition"] = v_funnel.TextpositionValidator() self._validators["textpositionsrc"] = v_funnel.TextpositionsrcValidator() self._validators["textsrc"] = v_funnel.TextsrcValidator() self._validators["texttemplate"] = v_funnel.TexttemplateValidator() self._validators["texttemplatesrc"] = v_funnel.TexttemplatesrcValidator() self._validators["uid"] = v_funnel.UidValidator() self._validators["uirevision"] = v_funnel.UirevisionValidator() self._validators["visible"] = v_funnel.VisibleValidator() self._validators["width"] = v_funnel.WidthValidator() self._validators["x"] = v_funnel.XValidator() self._validators["x0"] = v_funnel.X0Validator() self._validators["xaxis"] = v_funnel.XAxisValidator() self._validators["xsrc"] = v_funnel.XsrcValidator() self._validators["y"] = v_funnel.YValidator() self._validators["y0"] = v_funnel.Y0Validator() self._validators["yaxis"] = v_funnel.YAxisValidator() self._validators["ysrc"] = v_funnel.YsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("alignmentgroup", None) self["alignmentgroup"] = alignmentgroup if alignmentgroup is not None else _v _v = arg.pop("cliponaxis", None) self["cliponaxis"] = cliponaxis if cliponaxis is not None else _v _v = arg.pop("connector", None) self["connector"] = connector if connector is not None else _v _v = arg.pop("constraintext", None) self["constraintext"] = constraintext if constraintext is not None else _v _v = arg.pop("customdata", None) self["customdata"] = customdata if customdata is not None else _v _v = arg.pop("customdatasrc", None) self["customdatasrc"] = customdatasrc if customdatasrc is not None else _v _v = arg.pop("dx", None) self["dx"] = dx if dx is not None else _v _v = arg.pop("dy", None) self["dy"] = dy if dy is not None else _v _v = arg.pop("hoverinfo", None) self["hoverinfo"] = hoverinfo if hoverinfo is not None else _v _v = arg.pop("hoverinfosrc", None) self["hoverinfosrc"] = hoverinfosrc if hoverinfosrc is not None else _v _v = arg.pop("hoverlabel", None) self["hoverlabel"] = hoverlabel if hoverlabel is not None else _v _v = arg.pop("hovertemplate", None) self["hovertemplate"] = hovertemplate if hovertemplate is not None else _v _v = arg.pop("hovertemplatesrc", None) self["hovertemplatesrc"] = ( hovertemplatesrc if hovertemplatesrc is not None else _v ) _v = arg.pop("hovertext", None) self["hovertext"] = hovertext if hovertext is not None else _v _v = arg.pop("hovertextsrc", None) self["hovertextsrc"] = hovertextsrc if hovertextsrc is not None else _v _v = arg.pop("ids", None) self["ids"] = ids if ids is not None else _v _v = arg.pop("idssrc", None) self["idssrc"] = idssrc if idssrc is not None else _v _v = arg.pop("insidetextanchor", None) self["insidetextanchor"] = ( insidetextanchor if insidetextanchor is not None else _v ) _v = arg.pop("insidetextfont", None) self["insidetextfont"] = insidetextfont if insidetextfont is not None else _v _v = arg.pop("legendgroup", None) self["legendgroup"] = legendgroup if legendgroup is not None else _v _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v _v = arg.pop("meta", None) self["meta"] = meta if meta is not None else _v _v = arg.pop("metasrc", None) self["metasrc"] = metasrc if metasrc is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("offset", None) self["offset"] = offset if offset is not None else _v _v = arg.pop("offsetgroup", None) self["offsetgroup"] = offsetgroup if offsetgroup is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("orientation", None) self["orientation"] = orientation if orientation is not None else _v _v = arg.pop("outsidetextfont", None) self["outsidetextfont"] = outsidetextfont if outsidetextfont is not None else _v _v = arg.pop("selectedpoints", None) self["selectedpoints"] = selectedpoints if selectedpoints is not None else _v _v = arg.pop("showlegend", None) self["showlegend"] = showlegend if showlegend is not None else _v _v = arg.pop("stream", None) self["stream"] = stream if stream is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v _v = arg.pop("textangle", None) self["textangle"] = textangle if textangle is not None else _v _v = arg.pop("textfont", None) self["textfont"] = textfont if textfont is not None else _v _v = arg.pop("textinfo", None) self["textinfo"] = textinfo if textinfo is not None else _v _v = arg.pop("textposition", None) self["textposition"] = textposition if textposition is not None else _v _v = arg.pop("textpositionsrc", None) self["textpositionsrc"] = textpositionsrc if textpositionsrc is not None else _v _v = arg.pop("textsrc", None) self["textsrc"] = textsrc if textsrc is not None else _v _v = arg.pop("texttemplate", None) self["texttemplate"] = texttemplate if texttemplate is not None else _v _v = arg.pop("texttemplatesrc", None) self["texttemplatesrc"] = texttemplatesrc if texttemplatesrc is not None else _v _v = arg.pop("uid", None) self["uid"] = uid if uid is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("x0", None) self["x0"] = x0 if x0 is not None else _v _v = arg.pop("xaxis", None) self["xaxis"] = xaxis if xaxis is not None else _v _v = arg.pop("xsrc", None) self["xsrc"] = xsrc if xsrc is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("y0", None) self["y0"] = y0 if y0 is not None else _v _v = arg.pop("yaxis", None) self["yaxis"] = yaxis if yaxis is not None else _v _v = arg.pop("ysrc", None) self["ysrc"] = ysrc if ysrc is not None else _v # Read-only literals # ------------------ from _plotly_utils.basevalidators import LiteralValidator self._props["type"] = "funnel" self._validators["type"] = LiteralValidator( plotly_name="type", parent_name="funnel", val="funnel" ) arg.pop("type", None) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceType as _BaseTraceType import copy as _copy class Densitymapbox(_BaseTraceType): # autocolorscale # -------------- @property def autocolorscale(self): """ Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. The 'autocolorscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocolorscale"] @autocolorscale.setter def autocolorscale(self, val): self["autocolorscale"] = val # below # ----- @property def below(self): """ Determines if the densitymapbox trace will be inserted before the layer with the specified ID. By default, densitymapbox traces are placed below the first layer of type symbol If set to '', the layer will be inserted above every existing layer. The 'below' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["below"] @below.setter def below(self, val): self["below"] = val # coloraxis # --------- @property def coloraxis(self): """ Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. The 'coloraxis' property is an identifier of a particular subplot, of type 'coloraxis', that may be specified as the string 'coloraxis' optionally followed by an integer >= 1 (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) Returns ------- str """ return self["coloraxis"] @coloraxis.setter def coloraxis(self, val): self["coloraxis"] = val # colorbar # -------- @property def colorbar(self): """ The 'colorbar' property is an instance of ColorBar that may be specified as: - An instance of plotly.graph_objs.densitymapbox.ColorBar - A dict of string/value properties that will be passed to the ColorBar constructor Supported dict properties: bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.densitymapbox.c olorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.densitymapbox.colorbar.tickformatstopdefaults ), sets the default property values to use for elements of densitymapbox.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.densitymapbox.colorbar.Tit le instance or dict with compatible properties titlefont Deprecated: Please use densitymapbox.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use densitymapbox.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- plotly.graph_objs.densitymapbox.ColorBar """ return self["colorbar"] @colorbar.setter def colorbar(self, val): self["colorbar"] = val # colorscale # ---------- @property def colorscale(self): """ Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,Earth,Electric,Vi ridis,Cividis. The 'colorscale' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # customdata # ---------- @property def customdata(self): """ Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements The 'customdata' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["customdata"] @customdata.setter def customdata(self, val): self["customdata"] = val # customdatasrc # ------------- @property def customdatasrc(self): """ Sets the source reference on plot.ly for customdata . The 'customdatasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["customdatasrc"] @customdatasrc.setter def customdatasrc(self, val): self["customdatasrc"] = val # hoverinfo # --------- @property def hoverinfo(self): """ Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. The 'hoverinfo' property is a flaglist and may be specified as a string containing: - Any combination of ['lon', 'lat', 'z', 'text', 'name'] joined with '+' characters (e.g. 'lon+lat') OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') - A list or array of the above Returns ------- Any|numpy.ndarray """ return self["hoverinfo"] @hoverinfo.setter def hoverinfo(self, val): self["hoverinfo"] = val # hoverinfosrc # ------------ @property def hoverinfosrc(self): """ Sets the source reference on plot.ly for hoverinfo . The 'hoverinfosrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hoverinfosrc"] @hoverinfosrc.setter def hoverinfosrc(self, val): self["hoverinfosrc"] = val # hoverlabel # ---------- @property def hoverlabel(self): """ The 'hoverlabel' property is an instance of Hoverlabel that may be specified as: - An instance of plotly.graph_objs.densitymapbox.Hoverlabel - A dict of string/value properties that will be passed to the Hoverlabel constructor Supported dict properties: align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- plotly.graph_objs.densitymapbox.Hoverlabel """ return self["hoverlabel"] @hoverlabel.setter def hoverlabel(self, val): self["hoverlabel"] = val # hovertemplate # ------------- @property def hovertemplate(self): """ Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event- data. Additionally, every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. The 'hovertemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertemplate"] @hovertemplate.setter def hovertemplate(self, val): self["hovertemplate"] = val # hovertemplatesrc # ---------------- @property def hovertemplatesrc(self): """ Sets the source reference on plot.ly for hovertemplate . The 'hovertemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertemplatesrc"] @hovertemplatesrc.setter def hovertemplatesrc(self, val): self["hovertemplatesrc"] = val # hovertext # --------- @property def hovertext(self): """ Sets hover text elements associated with each (lon,lat) pair If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (lon,lat) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. The 'hovertext' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertext"] @hovertext.setter def hovertext(self, val): self["hovertext"] = val # hovertextsrc # ------------ @property def hovertextsrc(self): """ Sets the source reference on plot.ly for hovertext . The 'hovertextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertextsrc"] @hovertextsrc.setter def hovertextsrc(self, val): self["hovertextsrc"] = val # ids # --- @property def ids(self): """ Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. The 'ids' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ids"] @ids.setter def ids(self, val): self["ids"] = val # idssrc # ------ @property def idssrc(self): """ Sets the source reference on plot.ly for ids . The 'idssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["idssrc"] @idssrc.setter def idssrc(self, val): self["idssrc"] = val # lat # --- @property def lat(self): """ Sets the latitude coordinates (in degrees North). The 'lat' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["lat"] @lat.setter def lat(self, val): self["lat"] = val # latsrc # ------ @property def latsrc(self): """ Sets the source reference on plot.ly for lat . The 'latsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["latsrc"] @latsrc.setter def latsrc(self, val): self["latsrc"] = val # lon # --- @property def lon(self): """ Sets the longitude coordinates (in degrees East). The 'lon' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["lon"] @lon.setter def lon(self, val): self["lon"] = val # lonsrc # ------ @property def lonsrc(self): """ Sets the source reference on plot.ly for lon . The 'lonsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["lonsrc"] @lonsrc.setter def lonsrc(self, val): self["lonsrc"] = val # meta # ---- @property def meta(self): """ Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. The 'meta' property accepts values of any type Returns ------- Any|numpy.ndarray """ return self["meta"] @meta.setter def meta(self, val): self["meta"] = val # metasrc # ------- @property def metasrc(self): """ Sets the source reference on plot.ly for meta . The 'metasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["metasrc"] @metasrc.setter def metasrc(self, val): self["metasrc"] = val # name # ---- @property def name(self): """ Sets the trace name. The trace name appear as the legend item and on hover. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the trace. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # radius # ------ @property def radius(self): """ Sets the radius of influence of one `lon` / `lat` point in pixels. Increasing the value makes the densitymapbox trace smoother, but less detailed. The 'radius' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["radius"] @radius.setter def radius(self, val): self["radius"] = val # radiussrc # --------- @property def radiussrc(self): """ Sets the source reference on plot.ly for radius . The 'radiussrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["radiussrc"] @radiussrc.setter def radiussrc(self, val): self["radiussrc"] = val # reversescale # ------------ @property def reversescale(self): """ Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. The 'reversescale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["reversescale"] @reversescale.setter def reversescale(self, val): self["reversescale"] = val # showscale # --------- @property def showscale(self): """ Determines whether or not a colorbar is displayed for this trace. The 'showscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showscale"] @showscale.setter def showscale(self, val): self["showscale"] = val # stream # ------ @property def stream(self): """ The 'stream' property is an instance of Stream that may be specified as: - An instance of plotly.graph_objs.densitymapbox.Stream - A dict of string/value properties that will be passed to the Stream constructor Supported dict properties: maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- plotly.graph_objs.densitymapbox.Stream """ return self["stream"] @stream.setter def stream(self, val): self["stream"] = val # subplot # ------- @property def subplot(self): """ Sets a reference between this trace's data coordinates and a mapbox subplot. If "mapbox" (the default value), the data refer to `layout.mapbox`. If "mapbox2", the data refer to `layout.mapbox2`, and so on. The 'subplot' property is an identifier of a particular subplot, of type 'mapbox', that may be specified as the string 'mapbox' optionally followed by an integer >= 1 (e.g. 'mapbox', 'mapbox1', 'mapbox2', 'mapbox3', etc.) Returns ------- str """ return self["subplot"] @subplot.setter def subplot(self, val): self["subplot"] = val # text # ---- @property def text(self): """ Sets text elements associated with each (lon,lat) pair If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (lon,lat) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["text"] @text.setter def text(self, val): self["text"] = val # textsrc # ------- @property def textsrc(self): """ Sets the source reference on plot.ly for text . The 'textsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["textsrc"] @textsrc.setter def textsrc(self, val): self["textsrc"] = val # uid # --- @property def uid(self): """ Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. The 'uid' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["uid"] @uid.setter def uid(self, val): self["uid"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # visible # ------- @property def visible(self): """ Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). The 'visible' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'legendonly'] Returns ------- Any """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # z # - @property def z(self): """ Sets the points' weight. For example, a value of 10 would be equivalent to having 10 points of weight 1 in the same spot The 'z' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["z"] @z.setter def z(self, val): self["z"] = val # zauto # ----- @property def zauto(self): """ Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. The 'zauto' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["zauto"] @zauto.setter def zauto(self, val): self["zauto"] = val # zmax # ---- @property def zmax(self): """ Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. The 'zmax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["zmax"] @zmax.setter def zmax(self, val): self["zmax"] = val # zmid # ---- @property def zmid(self): """ Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. The 'zmid' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["zmid"] @zmid.setter def zmid(self, val): self["zmid"] = val # zmin # ---- @property def zmin(self): """ Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. The 'zmin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["zmin"] @zmin.setter def zmin(self, val): self["zmin"] = val # zsrc # ---- @property def zsrc(self): """ Sets the source reference on plot.ly for z . The 'zsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["zsrc"] @zsrc.setter def zsrc(self, val): self["zsrc"] = val # type # ---- @property def type(self): return self._props["type"] # property parent name # -------------------- @property def _parent_path_str(self): return "" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. below Determines if the densitymapbox trace will be inserted before the layer with the specified ID. By default, densitymapbox traces are placed below the first layer of type symbol If set to '', the layer will be inserted above every existing layer. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.densitymapbox.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.densitymapbox.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (lon,lat) pair If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (lon,lat) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . lat Sets the latitude coordinates (in degrees North). latsrc Sets the source reference on plot.ly for lat . lon Sets the longitude coordinates (in degrees East). lonsrc Sets the source reference on plot.ly for lon . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. radius Sets the radius of influence of one `lon` / `lat` point in pixels. Increasing the value makes the densitymapbox trace smoother, but less detailed. radiussrc Sets the source reference on plot.ly for radius . reversescale Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.densitymapbox.Stream instance or dict with compatible properties subplot Sets a reference between this trace's data coordinates and a mapbox subplot. If "mapbox" (the default value), the data refer to `layout.mapbox`. If "mapbox2", the data refer to `layout.mapbox2`, and so on. text Sets text elements associated with each (lon,lat) pair If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (lon,lat) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). z Sets the points' weight. For example, a value of 10 would be equivalent to having 10 points of weight 1 in the same spot zauto Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. zmax Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. zmid Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. zmin Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. zsrc Sets the source reference on plot.ly for z . """ def __init__( self, arg=None, autocolorscale=None, below=None, coloraxis=None, colorbar=None, colorscale=None, customdata=None, customdatasrc=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, lat=None, latsrc=None, lon=None, lonsrc=None, meta=None, metasrc=None, name=None, opacity=None, radius=None, radiussrc=None, reversescale=None, showscale=None, stream=None, subplot=None, text=None, textsrc=None, uid=None, uirevision=None, visible=None, z=None, zauto=None, zmax=None, zmid=None, zmin=None, zsrc=None, **kwargs ): """ Construct a new Densitymapbox object Draws a bivariate kernel density estimation with a Gaussian kernel from `lon` and `lat` coordinates and optional `z` values using a colorscale. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.Densitymapbox autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. below Determines if the densitymapbox trace will be inserted before the layer with the specified ID. By default, densitymapbox traces are placed below the first layer of type symbol If set to '', the layer will be inserted above every existing layer. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.densitymapbox.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.densitymapbox.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (lon,lat) pair If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (lon,lat) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . lat Sets the latitude coordinates (in degrees North). latsrc Sets the source reference on plot.ly for lat . lon Sets the longitude coordinates (in degrees East). lonsrc Sets the source reference on plot.ly for lon . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. radius Sets the radius of influence of one `lon` / `lat` point in pixels. Increasing the value makes the densitymapbox trace smoother, but less detailed. radiussrc Sets the source reference on plot.ly for radius . reversescale Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.densitymapbox.Stream instance or dict with compatible properties subplot Sets a reference between this trace's data coordinates and a mapbox subplot. If "mapbox" (the default value), the data refer to `layout.mapbox`. If "mapbox2", the data refer to `layout.mapbox2`, and so on. text Sets text elements associated with each (lon,lat) pair If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (lon,lat) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). z Sets the points' weight. For example, a value of 10 would be equivalent to having 10 points of weight 1 in the same spot zauto Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. zmax Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. zmid Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. zmin Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. zsrc Sets the source reference on plot.ly for z . Returns ------- Densitymapbox """ super(Densitymapbox, self).__init__("densitymapbox") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.Densitymapbox constructor must be a dict or an instance of plotly.graph_objs.Densitymapbox""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators import densitymapbox as v_densitymapbox # Initialize validators # --------------------- self._validators["autocolorscale"] = v_densitymapbox.AutocolorscaleValidator() self._validators["below"] = v_densitymapbox.BelowValidator() self._validators["coloraxis"] = v_densitymapbox.ColoraxisValidator() self._validators["colorbar"] = v_densitymapbox.ColorBarValidator() self._validators["colorscale"] = v_densitymapbox.ColorscaleValidator() self._validators["customdata"] = v_densitymapbox.CustomdataValidator() self._validators["customdatasrc"] = v_densitymapbox.CustomdatasrcValidator() self._validators["hoverinfo"] = v_densitymapbox.HoverinfoValidator() self._validators["hoverinfosrc"] = v_densitymapbox.HoverinfosrcValidator() self._validators["hoverlabel"] = v_densitymapbox.HoverlabelValidator() self._validators["hovertemplate"] = v_densitymapbox.HovertemplateValidator() self._validators[ "hovertemplatesrc" ] = v_densitymapbox.HovertemplatesrcValidator() self._validators["hovertext"] = v_densitymapbox.HovertextValidator() self._validators["hovertextsrc"] = v_densitymapbox.HovertextsrcValidator() self._validators["ids"] = v_densitymapbox.IdsValidator() self._validators["idssrc"] = v_densitymapbox.IdssrcValidator() self._validators["lat"] = v_densitymapbox.LatValidator() self._validators["latsrc"] = v_densitymapbox.LatsrcValidator() self._validators["lon"] = v_densitymapbox.LonValidator() self._validators["lonsrc"] = v_densitymapbox.LonsrcValidator() self._validators["meta"] = v_densitymapbox.MetaValidator() self._validators["metasrc"] = v_densitymapbox.MetasrcValidator() self._validators["name"] = v_densitymapbox.NameValidator() self._validators["opacity"] = v_densitymapbox.OpacityValidator() self._validators["radius"] = v_densitymapbox.RadiusValidator() self._validators["radiussrc"] = v_densitymapbox.RadiussrcValidator() self._validators["reversescale"] = v_densitymapbox.ReversescaleValidator() self._validators["showscale"] = v_densitymapbox.ShowscaleValidator() self._validators["stream"] = v_densitymapbox.StreamValidator() self._validators["subplot"] = v_densitymapbox.SubplotValidator() self._validators["text"] = v_densitymapbox.TextValidator() self._validators["textsrc"] = v_densitymapbox.TextsrcValidator() self._validators["uid"] = v_densitymapbox.UidValidator() self._validators["uirevision"] = v_densitymapbox.UirevisionValidator() self._validators["visible"] = v_densitymapbox.VisibleValidator() self._validators["z"] = v_densitymapbox.ZValidator() self._validators["zauto"] = v_densitymapbox.ZautoValidator() self._validators["zmax"] = v_densitymapbox.ZmaxValidator() self._validators["zmid"] = v_densitymapbox.ZmidValidator() self._validators["zmin"] = v_densitymapbox.ZminValidator() self._validators["zsrc"] = v_densitymapbox.ZsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autocolorscale", None) self["autocolorscale"] = autocolorscale if autocolorscale is not None else _v _v = arg.pop("below", None) self["below"] = below if below is not None else _v _v = arg.pop("coloraxis", None) self["coloraxis"] = coloraxis if coloraxis is not None else _v _v = arg.pop("colorbar", None) self["colorbar"] = colorbar if colorbar is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("customdata", None) self["customdata"] = customdata if customdata is not None else _v _v = arg.pop("customdatasrc", None) self["customdatasrc"] = customdatasrc if customdatasrc is not None else _v _v = arg.pop("hoverinfo", None) self["hoverinfo"] = hoverinfo if hoverinfo is not None else _v _v = arg.pop("hoverinfosrc", None) self["hoverinfosrc"] = hoverinfosrc if hoverinfosrc is not None else _v _v = arg.pop("hoverlabel", None) self["hoverlabel"] = hoverlabel if hoverlabel is not None else _v _v = arg.pop("hovertemplate", None) self["hovertemplate"] = hovertemplate if hovertemplate is not None else _v _v = arg.pop("hovertemplatesrc", None) self["hovertemplatesrc"] = ( hovertemplatesrc if hovertemplatesrc is not None else _v ) _v = arg.pop("hovertext", None) self["hovertext"] = hovertext if hovertext is not None else _v _v = arg.pop("hovertextsrc", None) self["hovertextsrc"] = hovertextsrc if hovertextsrc is not None else _v _v = arg.pop("ids", None) self["ids"] = ids if ids is not None else _v _v = arg.pop("idssrc", None) self["idssrc"] = idssrc if idssrc is not None else _v _v = arg.pop("lat", None) self["lat"] = lat if lat is not None else _v _v = arg.pop("latsrc", None) self["latsrc"] = latsrc if latsrc is not None else _v _v = arg.pop("lon", None) self["lon"] = lon if lon is not None else _v _v = arg.pop("lonsrc", None) self["lonsrc"] = lonsrc if lonsrc is not None else _v _v = arg.pop("meta", None) self["meta"] = meta if meta is not None else _v _v = arg.pop("metasrc", None) self["metasrc"] = metasrc if metasrc is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("radius", None) self["radius"] = radius if radius is not None else _v _v = arg.pop("radiussrc", None) self["radiussrc"] = radiussrc if radiussrc is not None else _v _v = arg.pop("reversescale", None) self["reversescale"] = reversescale if reversescale is not None else _v _v = arg.pop("showscale", None) self["showscale"] = showscale if showscale is not None else _v _v = arg.pop("stream", None) self["stream"] = stream if stream is not None else _v _v = arg.pop("subplot", None) self["subplot"] = subplot if subplot is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v _v = arg.pop("textsrc", None) self["textsrc"] = textsrc if textsrc is not None else _v _v = arg.pop("uid", None) self["uid"] = uid if uid is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("z", None) self["z"] = z if z is not None else _v _v = arg.pop("zauto", None) self["zauto"] = zauto if zauto is not None else _v _v = arg.pop("zmax", None) self["zmax"] = zmax if zmax is not None else _v _v = arg.pop("zmid", None) self["zmid"] = zmid if zmid is not None else _v _v = arg.pop("zmin", None) self["zmin"] = zmin if zmin is not None else _v _v = arg.pop("zsrc", None) self["zsrc"] = zsrc if zsrc is not None else _v # Read-only literals # ------------------ from _plotly_utils.basevalidators import LiteralValidator self._props["type"] = "densitymapbox" self._validators["type"] = LiteralValidator( plotly_name="type", parent_name="densitymapbox", val="densitymapbox" ) arg.pop("type", None) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceType as _BaseTraceType import copy as _copy class Contourcarpet(_BaseTraceType): # a # - @property def a(self): """ Sets the x coordinates. The 'a' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["a"] @a.setter def a(self, val): self["a"] = val # a0 # -- @property def a0(self): """ Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. The 'a0' property accepts values of any type Returns ------- Any """ return self["a0"] @a0.setter def a0(self, val): self["a0"] = val # asrc # ---- @property def asrc(self): """ Sets the source reference on plot.ly for a . The 'asrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["asrc"] @asrc.setter def asrc(self, val): self["asrc"] = val # atype # ----- @property def atype(self): """ If "array", the heatmap's x coordinates are given by "x" (the default behavior when `x` is provided). If "scaled", the heatmap's x coordinates are given by "x0" and "dx" (the default behavior when `x` is not provided). The 'atype' property is an enumeration that may be specified as: - One of the following enumeration values: ['array', 'scaled'] Returns ------- Any """ return self["atype"] @atype.setter def atype(self, val): self["atype"] = val # autocolorscale # -------------- @property def autocolorscale(self): """ Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. The 'autocolorscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocolorscale"] @autocolorscale.setter def autocolorscale(self, val): self["autocolorscale"] = val # autocontour # ----------- @property def autocontour(self): """ Determines whether or not the contour level attributes are picked by an algorithm. If True, the number of contour levels can be set in `ncontours`. If False, set the contour level attributes in `contours`. The 'autocontour' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocontour"] @autocontour.setter def autocontour(self, val): self["autocontour"] = val # b # - @property def b(self): """ Sets the y coordinates. The 'b' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["b"] @b.setter def b(self, val): self["b"] = val # b0 # -- @property def b0(self): """ Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. The 'b0' property accepts values of any type Returns ------- Any """ return self["b0"] @b0.setter def b0(self, val): self["b0"] = val # bsrc # ---- @property def bsrc(self): """ Sets the source reference on plot.ly for b . The 'bsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bsrc"] @bsrc.setter def bsrc(self, val): self["bsrc"] = val # btype # ----- @property def btype(self): """ If "array", the heatmap's y coordinates are given by "y" (the default behavior when `y` is provided) If "scaled", the heatmap's y coordinates are given by "y0" and "dy" (the default behavior when `y` is not provided) The 'btype' property is an enumeration that may be specified as: - One of the following enumeration values: ['array', 'scaled'] Returns ------- Any """ return self["btype"] @btype.setter def btype(self, val): self["btype"] = val # carpet # ------ @property def carpet(self): """ The `carpet` of the carpet axes on which this contour trace lies The 'carpet' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["carpet"] @carpet.setter def carpet(self, val): self["carpet"] = val # coloraxis # --------- @property def coloraxis(self): """ Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. The 'coloraxis' property is an identifier of a particular subplot, of type 'coloraxis', that may be specified as the string 'coloraxis' optionally followed by an integer >= 1 (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) Returns ------- str """ return self["coloraxis"] @coloraxis.setter def coloraxis(self, val): self["coloraxis"] = val # colorbar # -------- @property def colorbar(self): """ The 'colorbar' property is an instance of ColorBar that may be specified as: - An instance of plotly.graph_objs.contourcarpet.ColorBar - A dict of string/value properties that will be passed to the ColorBar constructor Supported dict properties: bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.contourcarpet.c olorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.contourcarpet.colorbar.tickformatstopdefaults ), sets the default property values to use for elements of contourcarpet.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.contourcarpet.colorbar.Tit le instance or dict with compatible properties titlefont Deprecated: Please use contourcarpet.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use contourcarpet.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- plotly.graph_objs.contourcarpet.ColorBar """ return self["colorbar"] @colorbar.setter def colorbar(self, val): self["colorbar"] = val # colorscale # ---------- @property def colorscale(self): """ Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,Earth,Electric,Vi ridis,Cividis. The 'colorscale' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # contours # -------- @property def contours(self): """ The 'contours' property is an instance of Contours that may be specified as: - An instance of plotly.graph_objs.contourcarpet.Contours - A dict of string/value properties that will be passed to the Contours constructor Supported dict properties: coloring Determines the coloring method showing the contour values. If "fill", coloring is done evenly between each contour level If "lines", coloring is done on the contour lines. If "none", no coloring is applied on this trace. end Sets the end contour level value. Must be more than `contours.start` labelfont Sets the font used for labeling the contour levels. The default color comes from the lines, if shown. The default family and size come from `layout.font`. labelformat Sets the contour label formatting rule using d3 formatting mini-language which is very similar to Python, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format operation Sets the constraint operation. "=" keeps regions equal to `value` "<" and "<=" keep regions less than `value` ">" and ">=" keep regions greater than `value` "[]", "()", "[)", and "(]" keep regions inside `value[0]` to `value[1]` "][", ")(", "](", ")[" keep regions outside `value[0]` to value[1]` Open vs. closed intervals make no difference to constraint display, but all versions are allowed for consistency with filter transforms. showlabels Determines whether to label the contour lines with their values. showlines Determines whether or not the contour lines are drawn. Has an effect only if `contours.coloring` is set to "fill". size Sets the step between each contour level. Must be positive. start Sets the starting contour level value. Must be less than `contours.end` type If `levels`, the data is represented as a contour plot with multiple levels displayed. If `constraint`, the data is represented as constraints with the invalid region shaded as specified by the `operation` and `value` parameters. value Sets the value or values of the constraint boundary. When `operation` is set to one of the comparison values (=,<,>=,>,<=) "value" is expected to be a number. When `operation` is set to one of the interval values ([],(),[),(],][,)(,](,)[) "value" is expected to be an array of two numbers where the first is the lower bound and the second is the upper bound. Returns ------- plotly.graph_objs.contourcarpet.Contours """ return self["contours"] @contours.setter def contours(self, val): self["contours"] = val # customdata # ---------- @property def customdata(self): """ Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements The 'customdata' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["customdata"] @customdata.setter def customdata(self, val): self["customdata"] = val # customdatasrc # ------------- @property def customdatasrc(self): """ Sets the source reference on plot.ly for customdata . The 'customdatasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["customdatasrc"] @customdatasrc.setter def customdatasrc(self, val): self["customdatasrc"] = val # da # -- @property def da(self): """ Sets the x coordinate step. See `x0` for more info. The 'da' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["da"] @da.setter def da(self, val): self["da"] = val # db # -- @property def db(self): """ Sets the y coordinate step. See `y0` for more info. The 'db' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["db"] @db.setter def db(self, val): self["db"] = val # fillcolor # --------- @property def fillcolor(self): """ Sets the fill color if `contours.type` is "constraint". Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. The 'fillcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A number that will be interpreted as a color according to contourcarpet.colorscale Returns ------- str """ return self["fillcolor"] @fillcolor.setter def fillcolor(self, val): self["fillcolor"] = val # hovertext # --------- @property def hovertext(self): """ Same as `text`. The 'hovertext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["hovertext"] @hovertext.setter def hovertext(self, val): self["hovertext"] = val # hovertextsrc # ------------ @property def hovertextsrc(self): """ Sets the source reference on plot.ly for hovertext . The 'hovertextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertextsrc"] @hovertextsrc.setter def hovertextsrc(self, val): self["hovertextsrc"] = val # ids # --- @property def ids(self): """ Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. The 'ids' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ids"] @ids.setter def ids(self, val): self["ids"] = val # idssrc # ------ @property def idssrc(self): """ Sets the source reference on plot.ly for ids . The 'idssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["idssrc"] @idssrc.setter def idssrc(self, val): self["idssrc"] = val # legendgroup # ----------- @property def legendgroup(self): """ Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. The 'legendgroup' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["legendgroup"] @legendgroup.setter def legendgroup(self, val): self["legendgroup"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.contourcarpet.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: color Sets the color of the contour level. Has no effect if `contours.coloring` is set to "lines". dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). smoothing Sets the amount of smoothing for the contour lines, where 0 corresponds to no smoothing. width Sets the contour line width in (in px) Defaults to 0.5 when `contours.type` is "levels". Defaults to 2 when `contour.type` is "constraint". Returns ------- plotly.graph_objs.contourcarpet.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # meta # ---- @property def meta(self): """ Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. The 'meta' property accepts values of any type Returns ------- Any|numpy.ndarray """ return self["meta"] @meta.setter def meta(self, val): self["meta"] = val # metasrc # ------- @property def metasrc(self): """ Sets the source reference on plot.ly for meta . The 'metasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["metasrc"] @metasrc.setter def metasrc(self, val): self["metasrc"] = val # name # ---- @property def name(self): """ Sets the trace name. The trace name appear as the legend item and on hover. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # ncontours # --------- @property def ncontours(self): """ Sets the maximum number of contour levels. The actual number of contours will be chosen automatically to be less than or equal to the value of `ncontours`. Has an effect only if `autocontour` is True or if `contours.size` is missing. The 'ncontours' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [1, 9223372036854775807] Returns ------- int """ return self["ncontours"] @ncontours.setter def ncontours(self, val): self["ncontours"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the trace. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # reversescale # ------------ @property def reversescale(self): """ Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. The 'reversescale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["reversescale"] @reversescale.setter def reversescale(self, val): self["reversescale"] = val # showlegend # ---------- @property def showlegend(self): """ Determines whether or not an item corresponding to this trace is shown in the legend. The 'showlegend' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showlegend"] @showlegend.setter def showlegend(self, val): self["showlegend"] = val # showscale # --------- @property def showscale(self): """ Determines whether or not a colorbar is displayed for this trace. The 'showscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showscale"] @showscale.setter def showscale(self, val): self["showscale"] = val # stream # ------ @property def stream(self): """ The 'stream' property is an instance of Stream that may be specified as: - An instance of plotly.graph_objs.contourcarpet.Stream - A dict of string/value properties that will be passed to the Stream constructor Supported dict properties: maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- plotly.graph_objs.contourcarpet.Stream """ return self["stream"] @stream.setter def stream(self, val): self["stream"] = val # text # ---- @property def text(self): """ Sets the text elements associated with each z value. The 'text' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["text"] @text.setter def text(self, val): self["text"] = val # textsrc # ------- @property def textsrc(self): """ Sets the source reference on plot.ly for text . The 'textsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["textsrc"] @textsrc.setter def textsrc(self, val): self["textsrc"] = val # transpose # --------- @property def transpose(self): """ Transposes the z data. The 'transpose' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["transpose"] @transpose.setter def transpose(self, val): self["transpose"] = val # uid # --- @property def uid(self): """ Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. The 'uid' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["uid"] @uid.setter def uid(self, val): self["uid"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # visible # ------- @property def visible(self): """ Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). The 'visible' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'legendonly'] Returns ------- Any """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # xaxis # ----- @property def xaxis(self): """ Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. The 'xaxis' property is an identifier of a particular subplot, of type 'x', that may be specified as the string 'x' optionally followed by an integer >= 1 (e.g. 'x', 'x1', 'x2', 'x3', etc.) Returns ------- str """ return self["xaxis"] @xaxis.setter def xaxis(self, val): self["xaxis"] = val # yaxis # ----- @property def yaxis(self): """ Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. The 'yaxis' property is an identifier of a particular subplot, of type 'y', that may be specified as the string 'y' optionally followed by an integer >= 1 (e.g. 'y', 'y1', 'y2', 'y3', etc.) Returns ------- str """ return self["yaxis"] @yaxis.setter def yaxis(self, val): self["yaxis"] = val # z # - @property def z(self): """ Sets the z data. The 'z' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["z"] @z.setter def z(self, val): self["z"] = val # zauto # ----- @property def zauto(self): """ Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. The 'zauto' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["zauto"] @zauto.setter def zauto(self, val): self["zauto"] = val # zmax # ---- @property def zmax(self): """ Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. The 'zmax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["zmax"] @zmax.setter def zmax(self, val): self["zmax"] = val # zmid # ---- @property def zmid(self): """ Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. The 'zmid' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["zmid"] @zmid.setter def zmid(self, val): self["zmid"] = val # zmin # ---- @property def zmin(self): """ Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. The 'zmin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["zmin"] @zmin.setter def zmin(self, val): self["zmin"] = val # zsrc # ---- @property def zsrc(self): """ Sets the source reference on plot.ly for z . The 'zsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["zsrc"] @zsrc.setter def zsrc(self, val): self["zsrc"] = val # type # ---- @property def type(self): return self._props["type"] # property parent name # -------------------- @property def _parent_path_str(self): return "" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ a Sets the x coordinates. a0 Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. asrc Sets the source reference on plot.ly for a . atype If "array", the heatmap's x coordinates are given by "x" (the default behavior when `x` is provided). If "scaled", the heatmap's x coordinates are given by "x0" and "dx" (the default behavior when `x` is not provided). autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. autocontour Determines whether or not the contour level attributes are picked by an algorithm. If True, the number of contour levels can be set in `ncontours`. If False, set the contour level attributes in `contours`. b Sets the y coordinates. b0 Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. bsrc Sets the source reference on plot.ly for b . btype If "array", the heatmap's y coordinates are given by "y" (the default behavior when `y` is provided) If "scaled", the heatmap's y coordinates are given by "y0" and "dy" (the default behavior when `y` is not provided) carpet The `carpet` of the carpet axes on which this contour trace lies coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.contourcarpet.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. contours plotly.graph_objects.contourcarpet.Contours instance or dict with compatible properties customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . da Sets the x coordinate step. See `x0` for more info. db Sets the y coordinate step. See `y0` for more info. fillcolor Sets the fill color if `contours.type` is "constraint". Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.contourcarpet.Line instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. ncontours Sets the maximum number of contour levels. The actual number of contours will be chosen automatically to be less than or equal to the value of `ncontours`. Has an effect only if `autocontour` is True or if `contours.size` is missing. opacity Sets the opacity of the trace. reversescale Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.contourcarpet.Stream instance or dict with compatible properties text Sets the text elements associated with each z value. textsrc Sets the source reference on plot.ly for text . transpose Transposes the z data. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. z Sets the z data. zauto Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. zmax Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. zmid Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. zmin Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. zsrc Sets the source reference on plot.ly for z . """ def __init__( self, arg=None, a=None, a0=None, asrc=None, atype=None, autocolorscale=None, autocontour=None, b=None, b0=None, bsrc=None, btype=None, carpet=None, coloraxis=None, colorbar=None, colorscale=None, contours=None, customdata=None, customdatasrc=None, da=None, db=None, fillcolor=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, legendgroup=None, line=None, meta=None, metasrc=None, name=None, ncontours=None, opacity=None, reversescale=None, showlegend=None, showscale=None, stream=None, text=None, textsrc=None, transpose=None, uid=None, uirevision=None, visible=None, xaxis=None, yaxis=None, z=None, zauto=None, zmax=None, zmid=None, zmin=None, zsrc=None, **kwargs ): """ Construct a new Contourcarpet object Plots contours on either the first carpet axis or the carpet axis with a matching `carpet` attribute. Data `z` is interpreted as matching that of the corresponding carpet axis. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.Contourcarpet a Sets the x coordinates. a0 Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. asrc Sets the source reference on plot.ly for a . atype If "array", the heatmap's x coordinates are given by "x" (the default behavior when `x` is provided). If "scaled", the heatmap's x coordinates are given by "x0" and "dx" (the default behavior when `x` is not provided). autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. autocontour Determines whether or not the contour level attributes are picked by an algorithm. If True, the number of contour levels can be set in `ncontours`. If False, set the contour level attributes in `contours`. b Sets the y coordinates. b0 Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. bsrc Sets the source reference on plot.ly for b . btype If "array", the heatmap's y coordinates are given by "y" (the default behavior when `y` is provided) If "scaled", the heatmap's y coordinates are given by "y0" and "dy" (the default behavior when `y` is not provided) carpet The `carpet` of the carpet axes on which this contour trace lies coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.contourcarpet.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. contours plotly.graph_objects.contourcarpet.Contours instance or dict with compatible properties customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . da Sets the x coordinate step. See `x0` for more info. db Sets the y coordinate step. See `y0` for more info. fillcolor Sets the fill color if `contours.type` is "constraint". Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.contourcarpet.Line instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. ncontours Sets the maximum number of contour levels. The actual number of contours will be chosen automatically to be less than or equal to the value of `ncontours`. Has an effect only if `autocontour` is True or if `contours.size` is missing. opacity Sets the opacity of the trace. reversescale Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.contourcarpet.Stream instance or dict with compatible properties text Sets the text elements associated with each z value. textsrc Sets the source reference on plot.ly for text . transpose Transposes the z data. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. z Sets the z data. zauto Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. zmax Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. zmid Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. zmin Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. zsrc Sets the source reference on plot.ly for z . Returns ------- Contourcarpet """ super(Contourcarpet, self).__init__("contourcarpet") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.Contourcarpet constructor must be a dict or an instance of plotly.graph_objs.Contourcarpet""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators import contourcarpet as v_contourcarpet # Initialize validators # --------------------- self._validators["a"] = v_contourcarpet.AValidator() self._validators["a0"] = v_contourcarpet.A0Validator() self._validators["asrc"] = v_contourcarpet.AsrcValidator() self._validators["atype"] = v_contourcarpet.AtypeValidator() self._validators["autocolorscale"] = v_contourcarpet.AutocolorscaleValidator() self._validators["autocontour"] = v_contourcarpet.AutocontourValidator() self._validators["b"] = v_contourcarpet.BValidator() self._validators["b0"] = v_contourcarpet.B0Validator() self._validators["bsrc"] = v_contourcarpet.BsrcValidator() self._validators["btype"] = v_contourcarpet.BtypeValidator() self._validators["carpet"] = v_contourcarpet.CarpetValidator() self._validators["coloraxis"] = v_contourcarpet.ColoraxisValidator() self._validators["colorbar"] = v_contourcarpet.ColorBarValidator() self._validators["colorscale"] = v_contourcarpet.ColorscaleValidator() self._validators["contours"] = v_contourcarpet.ContoursValidator() self._validators["customdata"] = v_contourcarpet.CustomdataValidator() self._validators["customdatasrc"] = v_contourcarpet.CustomdatasrcValidator() self._validators["da"] = v_contourcarpet.DaValidator() self._validators["db"] = v_contourcarpet.DbValidator() self._validators["fillcolor"] = v_contourcarpet.FillcolorValidator() self._validators["hovertext"] = v_contourcarpet.HovertextValidator() self._validators["hovertextsrc"] = v_contourcarpet.HovertextsrcValidator() self._validators["ids"] = v_contourcarpet.IdsValidator() self._validators["idssrc"] = v_contourcarpet.IdssrcValidator() self._validators["legendgroup"] = v_contourcarpet.LegendgroupValidator() self._validators["line"] = v_contourcarpet.LineValidator() self._validators["meta"] = v_contourcarpet.MetaValidator() self._validators["metasrc"] = v_contourcarpet.MetasrcValidator() self._validators["name"] = v_contourcarpet.NameValidator() self._validators["ncontours"] = v_contourcarpet.NcontoursValidator() self._validators["opacity"] = v_contourcarpet.OpacityValidator() self._validators["reversescale"] = v_contourcarpet.ReversescaleValidator() self._validators["showlegend"] = v_contourcarpet.ShowlegendValidator() self._validators["showscale"] = v_contourcarpet.ShowscaleValidator() self._validators["stream"] = v_contourcarpet.StreamValidator() self._validators["text"] = v_contourcarpet.TextValidator() self._validators["textsrc"] = v_contourcarpet.TextsrcValidator() self._validators["transpose"] = v_contourcarpet.TransposeValidator() self._validators["uid"] = v_contourcarpet.UidValidator() self._validators["uirevision"] = v_contourcarpet.UirevisionValidator() self._validators["visible"] = v_contourcarpet.VisibleValidator() self._validators["xaxis"] = v_contourcarpet.XAxisValidator() self._validators["yaxis"] = v_contourcarpet.YAxisValidator() self._validators["z"] = v_contourcarpet.ZValidator() self._validators["zauto"] = v_contourcarpet.ZautoValidator() self._validators["zmax"] = v_contourcarpet.ZmaxValidator() self._validators["zmid"] = v_contourcarpet.ZmidValidator() self._validators["zmin"] = v_contourcarpet.ZminValidator() self._validators["zsrc"] = v_contourcarpet.ZsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("a", None) self["a"] = a if a is not None else _v _v = arg.pop("a0", None) self["a0"] = a0 if a0 is not None else _v _v = arg.pop("asrc", None) self["asrc"] = asrc if asrc is not None else _v _v = arg.pop("atype", None) self["atype"] = atype if atype is not None else _v _v = arg.pop("autocolorscale", None) self["autocolorscale"] = autocolorscale if autocolorscale is not None else _v _v = arg.pop("autocontour", None) self["autocontour"] = autocontour if autocontour is not None else _v _v = arg.pop("b", None) self["b"] = b if b is not None else _v _v = arg.pop("b0", None) self["b0"] = b0 if b0 is not None else _v _v = arg.pop("bsrc", None) self["bsrc"] = bsrc if bsrc is not None else _v _v = arg.pop("btype", None) self["btype"] = btype if btype is not None else _v _v = arg.pop("carpet", None) self["carpet"] = carpet if carpet is not None else _v _v = arg.pop("coloraxis", None) self["coloraxis"] = coloraxis if coloraxis is not None else _v _v = arg.pop("colorbar", None) self["colorbar"] = colorbar if colorbar is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("contours", None) self["contours"] = contours if contours is not None else _v _v = arg.pop("customdata", None) self["customdata"] = customdata if customdata is not None else _v _v = arg.pop("customdatasrc", None) self["customdatasrc"] = customdatasrc if customdatasrc is not None else _v _v = arg.pop("da", None) self["da"] = da if da is not None else _v _v = arg.pop("db", None) self["db"] = db if db is not None else _v _v = arg.pop("fillcolor", None) self["fillcolor"] = fillcolor if fillcolor is not None else _v _v = arg.pop("hovertext", None) self["hovertext"] = hovertext if hovertext is not None else _v _v = arg.pop("hovertextsrc", None) self["hovertextsrc"] = hovertextsrc if hovertextsrc is not None else _v _v = arg.pop("ids", None) self["ids"] = ids if ids is not None else _v _v = arg.pop("idssrc", None) self["idssrc"] = idssrc if idssrc is not None else _v _v = arg.pop("legendgroup", None) self["legendgroup"] = legendgroup if legendgroup is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v _v = arg.pop("meta", None) self["meta"] = meta if meta is not None else _v _v = arg.pop("metasrc", None) self["metasrc"] = metasrc if metasrc is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("ncontours", None) self["ncontours"] = ncontours if ncontours is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("reversescale", None) self["reversescale"] = reversescale if reversescale is not None else _v _v = arg.pop("showlegend", None) self["showlegend"] = showlegend if showlegend is not None else _v _v = arg.pop("showscale", None) self["showscale"] = showscale if showscale is not None else _v _v = arg.pop("stream", None) self["stream"] = stream if stream is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v _v = arg.pop("textsrc", None) self["textsrc"] = textsrc if textsrc is not None else _v _v = arg.pop("transpose", None) self["transpose"] = transpose if transpose is not None else _v _v = arg.pop("uid", None) self["uid"] = uid if uid is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("xaxis", None) self["xaxis"] = xaxis if xaxis is not None else _v _v = arg.pop("yaxis", None) self["yaxis"] = yaxis if yaxis is not None else _v _v = arg.pop("z", None) self["z"] = z if z is not None else _v _v = arg.pop("zauto", None) self["zauto"] = zauto if zauto is not None else _v _v = arg.pop("zmax", None) self["zmax"] = zmax if zmax is not None else _v _v = arg.pop("zmid", None) self["zmid"] = zmid if zmid is not None else _v _v = arg.pop("zmin", None) self["zmin"] = zmin if zmin is not None else _v _v = arg.pop("zsrc", None) self["zsrc"] = zsrc if zsrc is not None else _v # Read-only literals # ------------------ from _plotly_utils.basevalidators import LiteralValidator self._props["type"] = "contourcarpet" self._validators["type"] = LiteralValidator( plotly_name="type", parent_name="contourcarpet", val="contourcarpet" ) arg.pop("type", None) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceType as _BaseTraceType import copy as _copy class Contour(_BaseTraceType): # autocolorscale # -------------- @property def autocolorscale(self): """ Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. The 'autocolorscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocolorscale"] @autocolorscale.setter def autocolorscale(self, val): self["autocolorscale"] = val # autocontour # ----------- @property def autocontour(self): """ Determines whether or not the contour level attributes are picked by an algorithm. If True, the number of contour levels can be set in `ncontours`. If False, set the contour level attributes in `contours`. The 'autocontour' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocontour"] @autocontour.setter def autocontour(self, val): self["autocontour"] = val # coloraxis # --------- @property def coloraxis(self): """ Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. The 'coloraxis' property is an identifier of a particular subplot, of type 'coloraxis', that may be specified as the string 'coloraxis' optionally followed by an integer >= 1 (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) Returns ------- str """ return self["coloraxis"] @coloraxis.setter def coloraxis(self, val): self["coloraxis"] = val # colorbar # -------- @property def colorbar(self): """ The 'colorbar' property is an instance of ColorBar that may be specified as: - An instance of plotly.graph_objs.contour.ColorBar - A dict of string/value properties that will be passed to the ColorBar constructor Supported dict properties: bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.contour.colorba r.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.contour.colorbar.tickformatstopdefaults), sets the default property values to use for elements of contour.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.contour.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use contour.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use contour.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- plotly.graph_objs.contour.ColorBar """ return self["colorbar"] @colorbar.setter def colorbar(self, val): self["colorbar"] = val # colorscale # ---------- @property def colorscale(self): """ Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,Earth,Electric,Vi ridis,Cividis. The 'colorscale' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # connectgaps # ----------- @property def connectgaps(self): """ Determines whether or not gaps (i.e. {nan} or missing values) in the `z` data are filled in. It is defaulted to true if `z` is a one dimensional array otherwise it is defaulted to false. The 'connectgaps' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["connectgaps"] @connectgaps.setter def connectgaps(self, val): self["connectgaps"] = val # contours # -------- @property def contours(self): """ The 'contours' property is an instance of Contours that may be specified as: - An instance of plotly.graph_objs.contour.Contours - A dict of string/value properties that will be passed to the Contours constructor Supported dict properties: coloring Determines the coloring method showing the contour values. If "fill", coloring is done evenly between each contour level If "heatmap", a heatmap gradient coloring is applied between each contour level. If "lines", coloring is done on the contour lines. If "none", no coloring is applied on this trace. end Sets the end contour level value. Must be more than `contours.start` labelfont Sets the font used for labeling the contour levels. The default color comes from the lines, if shown. The default family and size come from `layout.font`. labelformat Sets the contour label formatting rule using d3 formatting mini-language which is very similar to Python, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format operation Sets the constraint operation. "=" keeps regions equal to `value` "<" and "<=" keep regions less than `value` ">" and ">=" keep regions greater than `value` "[]", "()", "[)", and "(]" keep regions inside `value[0]` to `value[1]` "][", ")(", "](", ")[" keep regions outside `value[0]` to value[1]` Open vs. closed intervals make no difference to constraint display, but all versions are allowed for consistency with filter transforms. showlabels Determines whether to label the contour lines with their values. showlines Determines whether or not the contour lines are drawn. Has an effect only if `contours.coloring` is set to "fill". size Sets the step between each contour level. Must be positive. start Sets the starting contour level value. Must be less than `contours.end` type If `levels`, the data is represented as a contour plot with multiple levels displayed. If `constraint`, the data is represented as constraints with the invalid region shaded as specified by the `operation` and `value` parameters. value Sets the value or values of the constraint boundary. When `operation` is set to one of the comparison values (=,<,>=,>,<=) "value" is expected to be a number. When `operation` is set to one of the interval values ([],(),[),(],][,)(,](,)[) "value" is expected to be an array of two numbers where the first is the lower bound and the second is the upper bound. Returns ------- plotly.graph_objs.contour.Contours """ return self["contours"] @contours.setter def contours(self, val): self["contours"] = val # customdata # ---------- @property def customdata(self): """ Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements The 'customdata' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["customdata"] @customdata.setter def customdata(self, val): self["customdata"] = val # customdatasrc # ------------- @property def customdatasrc(self): """ Sets the source reference on plot.ly for customdata . The 'customdatasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["customdatasrc"] @customdatasrc.setter def customdatasrc(self, val): self["customdatasrc"] = val # dx # -- @property def dx(self): """ Sets the x coordinate step. See `x0` for more info. The 'dx' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["dx"] @dx.setter def dx(self, val): self["dx"] = val # dy # -- @property def dy(self): """ Sets the y coordinate step. See `y0` for more info. The 'dy' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["dy"] @dy.setter def dy(self, val): self["dy"] = val # fillcolor # --------- @property def fillcolor(self): """ Sets the fill color if `contours.type` is "constraint". Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. The 'fillcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A number that will be interpreted as a color according to contour.colorscale Returns ------- str """ return self["fillcolor"] @fillcolor.setter def fillcolor(self, val): self["fillcolor"] = val # hoverinfo # --------- @property def hoverinfo(self): """ Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. The 'hoverinfo' property is a flaglist and may be specified as a string containing: - Any combination of ['x', 'y', 'z', 'text', 'name'] joined with '+' characters (e.g. 'x+y') OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') - A list or array of the above Returns ------- Any|numpy.ndarray """ return self["hoverinfo"] @hoverinfo.setter def hoverinfo(self, val): self["hoverinfo"] = val # hoverinfosrc # ------------ @property def hoverinfosrc(self): """ Sets the source reference on plot.ly for hoverinfo . The 'hoverinfosrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hoverinfosrc"] @hoverinfosrc.setter def hoverinfosrc(self, val): self["hoverinfosrc"] = val # hoverlabel # ---------- @property def hoverlabel(self): """ The 'hoverlabel' property is an instance of Hoverlabel that may be specified as: - An instance of plotly.graph_objs.contour.Hoverlabel - A dict of string/value properties that will be passed to the Hoverlabel constructor Supported dict properties: align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- plotly.graph_objs.contour.Hoverlabel """ return self["hoverlabel"] @hoverlabel.setter def hoverlabel(self, val): self["hoverlabel"] = val # hoverongaps # ----------- @property def hoverongaps(self): """ Determines whether or not gaps (i.e. {nan} or missing values) in the `z` data have hover labels associated with them. The 'hoverongaps' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["hoverongaps"] @hoverongaps.setter def hoverongaps(self, val): self["hoverongaps"] = val # hovertemplate # ------------- @property def hovertemplate(self): """ Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event- data. Additionally, every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. The 'hovertemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertemplate"] @hovertemplate.setter def hovertemplate(self, val): self["hovertemplate"] = val # hovertemplatesrc # ---------------- @property def hovertemplatesrc(self): """ Sets the source reference on plot.ly for hovertemplate . The 'hovertemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertemplatesrc"] @hovertemplatesrc.setter def hovertemplatesrc(self, val): self["hovertemplatesrc"] = val # hovertext # --------- @property def hovertext(self): """ Same as `text`. The 'hovertext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["hovertext"] @hovertext.setter def hovertext(self, val): self["hovertext"] = val # hovertextsrc # ------------ @property def hovertextsrc(self): """ Sets the source reference on plot.ly for hovertext . The 'hovertextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertextsrc"] @hovertextsrc.setter def hovertextsrc(self, val): self["hovertextsrc"] = val # ids # --- @property def ids(self): """ Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. The 'ids' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ids"] @ids.setter def ids(self, val): self["ids"] = val # idssrc # ------ @property def idssrc(self): """ Sets the source reference on plot.ly for ids . The 'idssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["idssrc"] @idssrc.setter def idssrc(self, val): self["idssrc"] = val # legendgroup # ----------- @property def legendgroup(self): """ Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. The 'legendgroup' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["legendgroup"] @legendgroup.setter def legendgroup(self, val): self["legendgroup"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.contour.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: color Sets the color of the contour level. Has no effect if `contours.coloring` is set to "lines". dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). smoothing Sets the amount of smoothing for the contour lines, where 0 corresponds to no smoothing. width Sets the contour line width in (in px) Defaults to 0.5 when `contours.type` is "levels". Defaults to 2 when `contour.type` is "constraint". Returns ------- plotly.graph_objs.contour.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # meta # ---- @property def meta(self): """ Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. The 'meta' property accepts values of any type Returns ------- Any|numpy.ndarray """ return self["meta"] @meta.setter def meta(self, val): self["meta"] = val # metasrc # ------- @property def metasrc(self): """ Sets the source reference on plot.ly for meta . The 'metasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["metasrc"] @metasrc.setter def metasrc(self, val): self["metasrc"] = val # name # ---- @property def name(self): """ Sets the trace name. The trace name appear as the legend item and on hover. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # ncontours # --------- @property def ncontours(self): """ Sets the maximum number of contour levels. The actual number of contours will be chosen automatically to be less than or equal to the value of `ncontours`. Has an effect only if `autocontour` is True or if `contours.size` is missing. The 'ncontours' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [1, 9223372036854775807] Returns ------- int """ return self["ncontours"] @ncontours.setter def ncontours(self, val): self["ncontours"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the trace. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # reversescale # ------------ @property def reversescale(self): """ Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. The 'reversescale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["reversescale"] @reversescale.setter def reversescale(self, val): self["reversescale"] = val # showlegend # ---------- @property def showlegend(self): """ Determines whether or not an item corresponding to this trace is shown in the legend. The 'showlegend' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showlegend"] @showlegend.setter def showlegend(self, val): self["showlegend"] = val # showscale # --------- @property def showscale(self): """ Determines whether or not a colorbar is displayed for this trace. The 'showscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showscale"] @showscale.setter def showscale(self, val): self["showscale"] = val # stream # ------ @property def stream(self): """ The 'stream' property is an instance of Stream that may be specified as: - An instance of plotly.graph_objs.contour.Stream - A dict of string/value properties that will be passed to the Stream constructor Supported dict properties: maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- plotly.graph_objs.contour.Stream """ return self["stream"] @stream.setter def stream(self, val): self["stream"] = val # text # ---- @property def text(self): """ Sets the text elements associated with each z value. The 'text' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["text"] @text.setter def text(self, val): self["text"] = val # textsrc # ------- @property def textsrc(self): """ Sets the source reference on plot.ly for text . The 'textsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["textsrc"] @textsrc.setter def textsrc(self, val): self["textsrc"] = val # transpose # --------- @property def transpose(self): """ Transposes the z data. The 'transpose' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["transpose"] @transpose.setter def transpose(self, val): self["transpose"] = val # uid # --- @property def uid(self): """ Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. The 'uid' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["uid"] @uid.setter def uid(self, val): self["uid"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # visible # ------- @property def visible(self): """ Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). The 'visible' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'legendonly'] Returns ------- Any """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # x # - @property def x(self): """ Sets the x coordinates. The 'x' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["x"] @x.setter def x(self, val): self["x"] = val # x0 # -- @property def x0(self): """ Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. The 'x0' property accepts values of any type Returns ------- Any """ return self["x0"] @x0.setter def x0(self, val): self["x0"] = val # xaxis # ----- @property def xaxis(self): """ Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. The 'xaxis' property is an identifier of a particular subplot, of type 'x', that may be specified as the string 'x' optionally followed by an integer >= 1 (e.g. 'x', 'x1', 'x2', 'x3', etc.) Returns ------- str """ return self["xaxis"] @xaxis.setter def xaxis(self, val): self["xaxis"] = val # xcalendar # --------- @property def xcalendar(self): """ Sets the calendar system to use with `x` date data. The 'xcalendar' property is an enumeration that may be specified as: - One of the following enumeration values: ['gregorian', 'chinese', 'coptic', 'discworld', 'ethiopian', 'hebrew', 'islamic', 'julian', 'mayan', 'nanakshahi', 'nepali', 'persian', 'jalali', 'taiwan', 'thai', 'ummalqura'] Returns ------- Any """ return self["xcalendar"] @xcalendar.setter def xcalendar(self, val): self["xcalendar"] = val # xsrc # ---- @property def xsrc(self): """ Sets the source reference on plot.ly for x . The 'xsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["xsrc"] @xsrc.setter def xsrc(self, val): self["xsrc"] = val # xtype # ----- @property def xtype(self): """ If "array", the heatmap's x coordinates are given by "x" (the default behavior when `x` is provided). If "scaled", the heatmap's x coordinates are given by "x0" and "dx" (the default behavior when `x` is not provided). The 'xtype' property is an enumeration that may be specified as: - One of the following enumeration values: ['array', 'scaled'] Returns ------- Any """ return self["xtype"] @xtype.setter def xtype(self, val): self["xtype"] = val # y # - @property def y(self): """ Sets the y coordinates. The 'y' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["y"] @y.setter def y(self, val): self["y"] = val # y0 # -- @property def y0(self): """ Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. The 'y0' property accepts values of any type Returns ------- Any """ return self["y0"] @y0.setter def y0(self, val): self["y0"] = val # yaxis # ----- @property def yaxis(self): """ Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. The 'yaxis' property is an identifier of a particular subplot, of type 'y', that may be specified as the string 'y' optionally followed by an integer >= 1 (e.g. 'y', 'y1', 'y2', 'y3', etc.) Returns ------- str """ return self["yaxis"] @yaxis.setter def yaxis(self, val): self["yaxis"] = val # ycalendar # --------- @property def ycalendar(self): """ Sets the calendar system to use with `y` date data. The 'ycalendar' property is an enumeration that may be specified as: - One of the following enumeration values: ['gregorian', 'chinese', 'coptic', 'discworld', 'ethiopian', 'hebrew', 'islamic', 'julian', 'mayan', 'nanakshahi', 'nepali', 'persian', 'jalali', 'taiwan', 'thai', 'ummalqura'] Returns ------- Any """ return self["ycalendar"] @ycalendar.setter def ycalendar(self, val): self["ycalendar"] = val # ysrc # ---- @property def ysrc(self): """ Sets the source reference on plot.ly for y . The 'ysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ysrc"] @ysrc.setter def ysrc(self, val): self["ysrc"] = val # ytype # ----- @property def ytype(self): """ If "array", the heatmap's y coordinates are given by "y" (the default behavior when `y` is provided) If "scaled", the heatmap's y coordinates are given by "y0" and "dy" (the default behavior when `y` is not provided) The 'ytype' property is an enumeration that may be specified as: - One of the following enumeration values: ['array', 'scaled'] Returns ------- Any """ return self["ytype"] @ytype.setter def ytype(self, val): self["ytype"] = val # z # - @property def z(self): """ Sets the z data. The 'z' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["z"] @z.setter def z(self, val): self["z"] = val # zauto # ----- @property def zauto(self): """ Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. The 'zauto' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["zauto"] @zauto.setter def zauto(self, val): self["zauto"] = val # zhoverformat # ------------ @property def zhoverformat(self): """ Sets the hover text formatting rule using d3 formatting mini- languages which are very similar to those in Python. See: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format The 'zhoverformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["zhoverformat"] @zhoverformat.setter def zhoverformat(self, val): self["zhoverformat"] = val # zmax # ---- @property def zmax(self): """ Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. The 'zmax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["zmax"] @zmax.setter def zmax(self, val): self["zmax"] = val # zmid # ---- @property def zmid(self): """ Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. The 'zmid' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["zmid"] @zmid.setter def zmid(self, val): self["zmid"] = val # zmin # ---- @property def zmin(self): """ Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. The 'zmin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["zmin"] @zmin.setter def zmin(self, val): self["zmin"] = val # zsrc # ---- @property def zsrc(self): """ Sets the source reference on plot.ly for z . The 'zsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["zsrc"] @zsrc.setter def zsrc(self, val): self["zsrc"] = val # type # ---- @property def type(self): return self._props["type"] # property parent name # -------------------- @property def _parent_path_str(self): return "" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. autocontour Determines whether or not the contour level attributes are picked by an algorithm. If True, the number of contour levels can be set in `ncontours`. If False, set the contour level attributes in `contours`. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.contour.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the `z` data are filled in. It is defaulted to true if `z` is a one dimensional array otherwise it is defaulted to false. contours plotly.graph_objects.contour.Contours instance or dict with compatible properties customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dx Sets the x coordinate step. See `x0` for more info. dy Sets the y coordinate step. See `y0` for more info. fillcolor Sets the fill color if `contours.type` is "constraint". Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.contour.Hoverlabel instance or dict with compatible properties hoverongaps Determines whether or not gaps (i.e. {nan} or missing values) in the `z` data have hover labels associated with them. hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.contour.Line instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. ncontours Sets the maximum number of contour levels. The actual number of contours will be chosen automatically to be less than or equal to the value of `ncontours`. Has an effect only if `autocontour` is True or if `contours.size` is missing. opacity Sets the opacity of the trace. reversescale Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.contour.Stream instance or dict with compatible properties text Sets the text elements associated with each z value. textsrc Sets the source reference on plot.ly for text . transpose Transposes the z data. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the x coordinates. x0 Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . xtype If "array", the heatmap's x coordinates are given by "x" (the default behavior when `x` is provided). If "scaled", the heatmap's x coordinates are given by "x0" and "dx" (the default behavior when `x` is not provided). y Sets the y coordinates. y0 Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . ytype If "array", the heatmap's y coordinates are given by "y" (the default behavior when `y` is provided) If "scaled", the heatmap's y coordinates are given by "y0" and "dy" (the default behavior when `y` is not provided) z Sets the z data. zauto Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. zhoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. See: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format zmax Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. zmid Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. zmin Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. zsrc Sets the source reference on plot.ly for z . """ def __init__( self, arg=None, autocolorscale=None, autocontour=None, coloraxis=None, colorbar=None, colorscale=None, connectgaps=None, contours=None, customdata=None, customdatasrc=None, dx=None, dy=None, fillcolor=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hoverongaps=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, legendgroup=None, line=None, meta=None, metasrc=None, name=None, ncontours=None, opacity=None, reversescale=None, showlegend=None, showscale=None, stream=None, text=None, textsrc=None, transpose=None, uid=None, uirevision=None, visible=None, x=None, x0=None, xaxis=None, xcalendar=None, xsrc=None, xtype=None, y=None, y0=None, yaxis=None, ycalendar=None, ysrc=None, ytype=None, z=None, zauto=None, zhoverformat=None, zmax=None, zmid=None, zmin=None, zsrc=None, **kwargs ): """ Construct a new Contour object The data from which contour lines are computed is set in `z`. Data in `z` must be a 2D list of numbers. Say that `z` has N rows and M columns, then by default, these N rows correspond to N y coordinates (set in `y` or auto-generated) and the M columns correspond to M x coordinates (set in `x` or auto- generated). By setting `transpose` to True, the above behavior is flipped. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.Contour autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. autocontour Determines whether or not the contour level attributes are picked by an algorithm. If True, the number of contour levels can be set in `ncontours`. If False, set the contour level attributes in `contours`. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.contour.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the `z` data are filled in. It is defaulted to true if `z` is a one dimensional array otherwise it is defaulted to false. contours plotly.graph_objects.contour.Contours instance or dict with compatible properties customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dx Sets the x coordinate step. See `x0` for more info. dy Sets the y coordinate step. See `y0` for more info. fillcolor Sets the fill color if `contours.type` is "constraint". Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.contour.Hoverlabel instance or dict with compatible properties hoverongaps Determines whether or not gaps (i.e. {nan} or missing values) in the `z` data have hover labels associated with them. hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.contour.Line instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. ncontours Sets the maximum number of contour levels. The actual number of contours will be chosen automatically to be less than or equal to the value of `ncontours`. Has an effect only if `autocontour` is True or if `contours.size` is missing. opacity Sets the opacity of the trace. reversescale Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.contour.Stream instance or dict with compatible properties text Sets the text elements associated with each z value. textsrc Sets the source reference on plot.ly for text . transpose Transposes the z data. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the x coordinates. x0 Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . xtype If "array", the heatmap's x coordinates are given by "x" (the default behavior when `x` is provided). If "scaled", the heatmap's x coordinates are given by "x0" and "dx" (the default behavior when `x` is not provided). y Sets the y coordinates. y0 Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . ytype If "array", the heatmap's y coordinates are given by "y" (the default behavior when `y` is provided) If "scaled", the heatmap's y coordinates are given by "y0" and "dy" (the default behavior when `y` is not provided) z Sets the z data. zauto Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. zhoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. See: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format zmax Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. zmid Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. zmin Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. zsrc Sets the source reference on plot.ly for z . Returns ------- Contour """ super(Contour, self).__init__("contour") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.Contour constructor must be a dict or an instance of plotly.graph_objs.Contour""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators import contour as v_contour # Initialize validators # --------------------- self._validators["autocolorscale"] = v_contour.AutocolorscaleValidator() self._validators["autocontour"] = v_contour.AutocontourValidator() self._validators["coloraxis"] = v_contour.ColoraxisValidator() self._validators["colorbar"] = v_contour.ColorBarValidator() self._validators["colorscale"] = v_contour.ColorscaleValidator() self._validators["connectgaps"] = v_contour.ConnectgapsValidator() self._validators["contours"] = v_contour.ContoursValidator() self._validators["customdata"] = v_contour.CustomdataValidator() self._validators["customdatasrc"] = v_contour.CustomdatasrcValidator() self._validators["dx"] = v_contour.DxValidator() self._validators["dy"] = v_contour.DyValidator() self._validators["fillcolor"] = v_contour.FillcolorValidator() self._validators["hoverinfo"] = v_contour.HoverinfoValidator() self._validators["hoverinfosrc"] = v_contour.HoverinfosrcValidator() self._validators["hoverlabel"] = v_contour.HoverlabelValidator() self._validators["hoverongaps"] = v_contour.HoverongapsValidator() self._validators["hovertemplate"] = v_contour.HovertemplateValidator() self._validators["hovertemplatesrc"] = v_contour.HovertemplatesrcValidator() self._validators["hovertext"] = v_contour.HovertextValidator() self._validators["hovertextsrc"] = v_contour.HovertextsrcValidator() self._validators["ids"] = v_contour.IdsValidator() self._validators["idssrc"] = v_contour.IdssrcValidator() self._validators["legendgroup"] = v_contour.LegendgroupValidator() self._validators["line"] = v_contour.LineValidator() self._validators["meta"] = v_contour.MetaValidator() self._validators["metasrc"] = v_contour.MetasrcValidator() self._validators["name"] = v_contour.NameValidator() self._validators["ncontours"] = v_contour.NcontoursValidator() self._validators["opacity"] = v_contour.OpacityValidator() self._validators["reversescale"] = v_contour.ReversescaleValidator() self._validators["showlegend"] = v_contour.ShowlegendValidator() self._validators["showscale"] = v_contour.ShowscaleValidator() self._validators["stream"] = v_contour.StreamValidator() self._validators["text"] = v_contour.TextValidator() self._validators["textsrc"] = v_contour.TextsrcValidator() self._validators["transpose"] = v_contour.TransposeValidator() self._validators["uid"] = v_contour.UidValidator() self._validators["uirevision"] = v_contour.UirevisionValidator() self._validators["visible"] = v_contour.VisibleValidator() self._validators["x"] = v_contour.XValidator() self._validators["x0"] = v_contour.X0Validator() self._validators["xaxis"] = v_contour.XAxisValidator() self._validators["xcalendar"] = v_contour.XcalendarValidator() self._validators["xsrc"] = v_contour.XsrcValidator() self._validators["xtype"] = v_contour.XtypeValidator() self._validators["y"] = v_contour.YValidator() self._validators["y0"] = v_contour.Y0Validator() self._validators["yaxis"] = v_contour.YAxisValidator() self._validators["ycalendar"] = v_contour.YcalendarValidator() self._validators["ysrc"] = v_contour.YsrcValidator() self._validators["ytype"] = v_contour.YtypeValidator() self._validators["z"] = v_contour.ZValidator() self._validators["zauto"] = v_contour.ZautoValidator() self._validators["zhoverformat"] = v_contour.ZhoverformatValidator() self._validators["zmax"] = v_contour.ZmaxValidator() self._validators["zmid"] = v_contour.ZmidValidator() self._validators["zmin"] = v_contour.ZminValidator() self._validators["zsrc"] = v_contour.ZsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autocolorscale", None) self["autocolorscale"] = autocolorscale if autocolorscale is not None else _v _v = arg.pop("autocontour", None) self["autocontour"] = autocontour if autocontour is not None else _v _v = arg.pop("coloraxis", None) self["coloraxis"] = coloraxis if coloraxis is not None else _v _v = arg.pop("colorbar", None) self["colorbar"] = colorbar if colorbar is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("connectgaps", None) self["connectgaps"] = connectgaps if connectgaps is not None else _v _v = arg.pop("contours", None) self["contours"] = contours if contours is not None else _v _v = arg.pop("customdata", None) self["customdata"] = customdata if customdata is not None else _v _v = arg.pop("customdatasrc", None) self["customdatasrc"] = customdatasrc if customdatasrc is not None else _v _v = arg.pop("dx", None) self["dx"] = dx if dx is not None else _v _v = arg.pop("dy", None) self["dy"] = dy if dy is not None else _v _v = arg.pop("fillcolor", None) self["fillcolor"] = fillcolor if fillcolor is not None else _v _v = arg.pop("hoverinfo", None) self["hoverinfo"] = hoverinfo if hoverinfo is not None else _v _v = arg.pop("hoverinfosrc", None) self["hoverinfosrc"] = hoverinfosrc if hoverinfosrc is not None else _v _v = arg.pop("hoverlabel", None) self["hoverlabel"] = hoverlabel if hoverlabel is not None else _v _v = arg.pop("hoverongaps", None) self["hoverongaps"] = hoverongaps if hoverongaps is not None else _v _v = arg.pop("hovertemplate", None) self["hovertemplate"] = hovertemplate if hovertemplate is not None else _v _v = arg.pop("hovertemplatesrc", None) self["hovertemplatesrc"] = ( hovertemplatesrc if hovertemplatesrc is not None else _v ) _v = arg.pop("hovertext", None) self["hovertext"] = hovertext if hovertext is not None else _v _v = arg.pop("hovertextsrc", None) self["hovertextsrc"] = hovertextsrc if hovertextsrc is not None else _v _v = arg.pop("ids", None) self["ids"] = ids if ids is not None else _v _v = arg.pop("idssrc", None) self["idssrc"] = idssrc if idssrc is not None else _v _v = arg.pop("legendgroup", None) self["legendgroup"] = legendgroup if legendgroup is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v _v = arg.pop("meta", None) self["meta"] = meta if meta is not None else _v _v = arg.pop("metasrc", None) self["metasrc"] = metasrc if metasrc is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("ncontours", None) self["ncontours"] = ncontours if ncontours is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("reversescale", None) self["reversescale"] = reversescale if reversescale is not None else _v _v = arg.pop("showlegend", None) self["showlegend"] = showlegend if showlegend is not None else _v _v = arg.pop("showscale", None) self["showscale"] = showscale if showscale is not None else _v _v = arg.pop("stream", None) self["stream"] = stream if stream is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v _v = arg.pop("textsrc", None) self["textsrc"] = textsrc if textsrc is not None else _v _v = arg.pop("transpose", None) self["transpose"] = transpose if transpose is not None else _v _v = arg.pop("uid", None) self["uid"] = uid if uid is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("x0", None) self["x0"] = x0 if x0 is not None else _v _v = arg.pop("xaxis", None) self["xaxis"] = xaxis if xaxis is not None else _v _v = arg.pop("xcalendar", None) self["xcalendar"] = xcalendar if xcalendar is not None else _v _v = arg.pop("xsrc", None) self["xsrc"] = xsrc if xsrc is not None else _v _v = arg.pop("xtype", None) self["xtype"] = xtype if xtype is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("y0", None) self["y0"] = y0 if y0 is not None else _v _v = arg.pop("yaxis", None) self["yaxis"] = yaxis if yaxis is not None else _v _v = arg.pop("ycalendar", None) self["ycalendar"] = ycalendar if ycalendar is not None else _v _v = arg.pop("ysrc", None) self["ysrc"] = ysrc if ysrc is not None else _v _v = arg.pop("ytype", None) self["ytype"] = ytype if ytype is not None else _v _v = arg.pop("z", None) self["z"] = z if z is not None else _v _v = arg.pop("zauto", None) self["zauto"] = zauto if zauto is not None else _v _v = arg.pop("zhoverformat", None) self["zhoverformat"] = zhoverformat if zhoverformat is not None else _v _v = arg.pop("zmax", None) self["zmax"] = zmax if zmax is not None else _v _v = arg.pop("zmid", None) self["zmid"] = zmid if zmid is not None else _v _v = arg.pop("zmin", None) self["zmin"] = zmin if zmin is not None else _v _v = arg.pop("zsrc", None) self["zsrc"] = zsrc if zsrc is not None else _v # Read-only literals # ------------------ from _plotly_utils.basevalidators import LiteralValidator self._props["type"] = "contour" self._validators["type"] = LiteralValidator( plotly_name="type", parent_name="contour", val="contour" ) arg.pop("type", None) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceType as _BaseTraceType import copy as _copy class Cone(_BaseTraceType): # anchor # ------ @property def anchor(self): """ Sets the cones' anchor with respect to their x/y/z positions. Note that "cm" denote the cone's center of mass which corresponds to 1/4 from the tail to tip. The 'anchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['tip', 'tail', 'cm', 'center'] Returns ------- Any """ return self["anchor"] @anchor.setter def anchor(self, val): self["anchor"] = val # autocolorscale # -------------- @property def autocolorscale(self): """ Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. The 'autocolorscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocolorscale"] @autocolorscale.setter def autocolorscale(self, val): self["autocolorscale"] = val # cauto # ----- @property def cauto(self): """ Determines whether or not the color domain is computed with respect to the input data (here u/v/w norm) or the bounds set in `cmin` and `cmax` Defaults to `false` when `cmin` and `cmax` are set by the user. The 'cauto' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["cauto"] @cauto.setter def cauto(self, val): self["cauto"] = val # cmax # ---- @property def cmax(self): """ Sets the upper bound of the color domain. Value should have the same units as u/v/w norm and if set, `cmin` must be set as well. The 'cmax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmax"] @cmax.setter def cmax(self, val): self["cmax"] = val # cmid # ---- @property def cmid(self): """ Sets the mid-point of the color domain by scaling `cmin` and/or `cmax` to be equidistant to this point. Value should have the same units as u/v/w norm. Has no effect when `cauto` is `false`. The 'cmid' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmid"] @cmid.setter def cmid(self, val): self["cmid"] = val # cmin # ---- @property def cmin(self): """ Sets the lower bound of the color domain. Value should have the same units as u/v/w norm and if set, `cmax` must be set as well. The 'cmin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmin"] @cmin.setter def cmin(self, val): self["cmin"] = val # coloraxis # --------- @property def coloraxis(self): """ Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. The 'coloraxis' property is an identifier of a particular subplot, of type 'coloraxis', that may be specified as the string 'coloraxis' optionally followed by an integer >= 1 (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) Returns ------- str """ return self["coloraxis"] @coloraxis.setter def coloraxis(self, val): self["coloraxis"] = val # colorbar # -------- @property def colorbar(self): """ The 'colorbar' property is an instance of ColorBar that may be specified as: - An instance of plotly.graph_objs.cone.ColorBar - A dict of string/value properties that will be passed to the ColorBar constructor Supported dict properties: bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.cone.colorbar.T ickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.cone.colorbar.tickformatstopdefaults), sets the default property values to use for elements of cone.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.cone.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use cone.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use cone.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- plotly.graph_objs.cone.ColorBar """ return self["colorbar"] @colorbar.setter def colorbar(self, val): self["colorbar"] = val # colorscale # ---------- @property def colorscale(self): """ Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`cmin` and `cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,Earth,Electric,Vi ridis,Cividis. The 'colorscale' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # customdata # ---------- @property def customdata(self): """ Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements The 'customdata' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["customdata"] @customdata.setter def customdata(self, val): self["customdata"] = val # customdatasrc # ------------- @property def customdatasrc(self): """ Sets the source reference on plot.ly for customdata . The 'customdatasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["customdatasrc"] @customdatasrc.setter def customdatasrc(self, val): self["customdatasrc"] = val # hoverinfo # --------- @property def hoverinfo(self): """ Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. The 'hoverinfo' property is a flaglist and may be specified as a string containing: - Any combination of ['x', 'y', 'z', 'u', 'v', 'w', 'norm', 'text', 'name'] joined with '+' characters (e.g. 'x+y') OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') - A list or array of the above Returns ------- Any|numpy.ndarray """ return self["hoverinfo"] @hoverinfo.setter def hoverinfo(self, val): self["hoverinfo"] = val # hoverinfosrc # ------------ @property def hoverinfosrc(self): """ Sets the source reference on plot.ly for hoverinfo . The 'hoverinfosrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hoverinfosrc"] @hoverinfosrc.setter def hoverinfosrc(self, val): self["hoverinfosrc"] = val # hoverlabel # ---------- @property def hoverlabel(self): """ The 'hoverlabel' property is an instance of Hoverlabel that may be specified as: - An instance of plotly.graph_objs.cone.Hoverlabel - A dict of string/value properties that will be passed to the Hoverlabel constructor Supported dict properties: align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- plotly.graph_objs.cone.Hoverlabel """ return self["hoverlabel"] @hoverlabel.setter def hoverlabel(self, val): self["hoverlabel"] = val # hovertemplate # ------------- @property def hovertemplate(self): """ Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event- data. Additionally, every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. variable `norm` Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. The 'hovertemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertemplate"] @hovertemplate.setter def hovertemplate(self, val): self["hovertemplate"] = val # hovertemplatesrc # ---------------- @property def hovertemplatesrc(self): """ Sets the source reference on plot.ly for hovertemplate . The 'hovertemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertemplatesrc"] @hovertemplatesrc.setter def hovertemplatesrc(self, val): self["hovertemplatesrc"] = val # hovertext # --------- @property def hovertext(self): """ Same as `text`. The 'hovertext' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertext"] @hovertext.setter def hovertext(self, val): self["hovertext"] = val # hovertextsrc # ------------ @property def hovertextsrc(self): """ Sets the source reference on plot.ly for hovertext . The 'hovertextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertextsrc"] @hovertextsrc.setter def hovertextsrc(self, val): self["hovertextsrc"] = val # ids # --- @property def ids(self): """ Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. The 'ids' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ids"] @ids.setter def ids(self, val): self["ids"] = val # idssrc # ------ @property def idssrc(self): """ Sets the source reference on plot.ly for ids . The 'idssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["idssrc"] @idssrc.setter def idssrc(self, val): self["idssrc"] = val # lighting # -------- @property def lighting(self): """ The 'lighting' property is an instance of Lighting that may be specified as: - An instance of plotly.graph_objs.cone.Lighting - A dict of string/value properties that will be passed to the Lighting constructor Supported dict properties: ambient Ambient light increases overall color visibility but can wash out the image. diffuse Represents the extent that incident rays are reflected in a range of angles. facenormalsepsilon Epsilon for face normals calculation avoids math issues arising from degenerate geometry. fresnel Represents the reflectance as a dependency of the viewing angle; e.g. paper is reflective when viewing it from the edge of the paper (almost 90 degrees), causing shine. roughness Alters specular reflection; the rougher the surface, the wider and less contrasty the shine. specular Represents the level that incident rays are reflected in a single direction, causing shine. vertexnormalsepsilon Epsilon for vertex normals calculation avoids math issues arising from degenerate geometry. Returns ------- plotly.graph_objs.cone.Lighting """ return self["lighting"] @lighting.setter def lighting(self, val): self["lighting"] = val # lightposition # ------------- @property def lightposition(self): """ The 'lightposition' property is an instance of Lightposition that may be specified as: - An instance of plotly.graph_objs.cone.Lightposition - A dict of string/value properties that will be passed to the Lightposition constructor Supported dict properties: x Numeric vector, representing the X coordinate for each vertex. y Numeric vector, representing the Y coordinate for each vertex. z Numeric vector, representing the Z coordinate for each vertex. Returns ------- plotly.graph_objs.cone.Lightposition """ return self["lightposition"] @lightposition.setter def lightposition(self, val): self["lightposition"] = val # meta # ---- @property def meta(self): """ Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. The 'meta' property accepts values of any type Returns ------- Any|numpy.ndarray """ return self["meta"] @meta.setter def meta(self, val): self["meta"] = val # metasrc # ------- @property def metasrc(self): """ Sets the source reference on plot.ly for meta . The 'metasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["metasrc"] @metasrc.setter def metasrc(self, val): self["metasrc"] = val # name # ---- @property def name(self): """ Sets the trace name. The trace name appear as the legend item and on hover. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the surface. Please note that in the case of using high `opacity` values for example a value greater than or equal to 0.5 on two surfaces (and 0.25 with four surfaces), an overlay of multiple transparent surfaces may not perfectly be sorted in depth by the webgl API. This behavior may be improved in the near future and is subject to change. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # reversescale # ------------ @property def reversescale(self): """ Reverses the color mapping if true. If true, `cmin` will correspond to the last color in the array and `cmax` will correspond to the first color. The 'reversescale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["reversescale"] @reversescale.setter def reversescale(self, val): self["reversescale"] = val # scene # ----- @property def scene(self): """ Sets a reference between this trace's 3D coordinate system and a 3D scene. If "scene" (the default value), the (x,y,z) coordinates refer to `layout.scene`. If "scene2", the (x,y,z) coordinates refer to `layout.scene2`, and so on. The 'scene' property is an identifier of a particular subplot, of type 'scene', that may be specified as the string 'scene' optionally followed by an integer >= 1 (e.g. 'scene', 'scene1', 'scene2', 'scene3', etc.) Returns ------- str """ return self["scene"] @scene.setter def scene(self, val): self["scene"] = val # showscale # --------- @property def showscale(self): """ Determines whether or not a colorbar is displayed for this trace. The 'showscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showscale"] @showscale.setter def showscale(self, val): self["showscale"] = val # sizemode # -------- @property def sizemode(self): """ Determines whether `sizeref` is set as a "scaled" (i.e unitless) scalar (normalized by the max u/v/w norm in the vector field) or as "absolute" value (in the same units as the vector field). The 'sizemode' property is an enumeration that may be specified as: - One of the following enumeration values: ['scaled', 'absolute'] Returns ------- Any """ return self["sizemode"] @sizemode.setter def sizemode(self, val): self["sizemode"] = val # sizeref # ------- @property def sizeref(self): """ Adjusts the cone size scaling. The size of the cones is determined by their u/v/w norm multiplied a factor and `sizeref`. This factor (computed internally) corresponds to the minimum "time" to travel across two successive x/y/z positions at the average velocity of those two successive positions. All cones in a given trace use the same factor. With `sizemode` set to "scaled", `sizeref` is unitless, its default value is 0.5 With `sizemode` set to "absolute", `sizeref` has the same units as the u/v/w vector field, its the default value is half the sample's maximum vector norm. The 'sizeref' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["sizeref"] @sizeref.setter def sizeref(self, val): self["sizeref"] = val # stream # ------ @property def stream(self): """ The 'stream' property is an instance of Stream that may be specified as: - An instance of plotly.graph_objs.cone.Stream - A dict of string/value properties that will be passed to the Stream constructor Supported dict properties: maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- plotly.graph_objs.cone.Stream """ return self["stream"] @stream.setter def stream(self, val): self["stream"] = val # text # ---- @property def text(self): """ Sets the text elements associated with the cones. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["text"] @text.setter def text(self, val): self["text"] = val # textsrc # ------- @property def textsrc(self): """ Sets the source reference on plot.ly for text . The 'textsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["textsrc"] @textsrc.setter def textsrc(self, val): self["textsrc"] = val # u # - @property def u(self): """ Sets the x components of the vector field. The 'u' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["u"] @u.setter def u(self, val): self["u"] = val # uid # --- @property def uid(self): """ Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. The 'uid' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["uid"] @uid.setter def uid(self, val): self["uid"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # usrc # ---- @property def usrc(self): """ Sets the source reference on plot.ly for u . The 'usrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["usrc"] @usrc.setter def usrc(self, val): self["usrc"] = val # v # - @property def v(self): """ Sets the y components of the vector field. The 'v' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["v"] @v.setter def v(self, val): self["v"] = val # visible # ------- @property def visible(self): """ Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). The 'visible' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'legendonly'] Returns ------- Any """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # vsrc # ---- @property def vsrc(self): """ Sets the source reference on plot.ly for v . The 'vsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["vsrc"] @vsrc.setter def vsrc(self, val): self["vsrc"] = val # w # - @property def w(self): """ Sets the z components of the vector field. The 'w' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["w"] @w.setter def w(self, val): self["w"] = val # wsrc # ---- @property def wsrc(self): """ Sets the source reference on plot.ly for w . The 'wsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["wsrc"] @wsrc.setter def wsrc(self, val): self["wsrc"] = val # x # - @property def x(self): """ Sets the x coordinates of the vector field and of the displayed cones. The 'x' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["x"] @x.setter def x(self, val): self["x"] = val # xsrc # ---- @property def xsrc(self): """ Sets the source reference on plot.ly for x . The 'xsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["xsrc"] @xsrc.setter def xsrc(self, val): self["xsrc"] = val # y # - @property def y(self): """ Sets the y coordinates of the vector field and of the displayed cones. The 'y' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["y"] @y.setter def y(self, val): self["y"] = val # ysrc # ---- @property def ysrc(self): """ Sets the source reference on plot.ly for y . The 'ysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ysrc"] @ysrc.setter def ysrc(self, val): self["ysrc"] = val # z # - @property def z(self): """ Sets the z coordinates of the vector field and of the displayed cones. The 'z' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["z"] @z.setter def z(self, val): self["z"] = val # zsrc # ---- @property def zsrc(self): """ Sets the source reference on plot.ly for z . The 'zsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["zsrc"] @zsrc.setter def zsrc(self, val): self["zsrc"] = val # type # ---- @property def type(self): return self._props["type"] # property parent name # -------------------- @property def _parent_path_str(self): return "" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ anchor Sets the cones' anchor with respect to their x/y/z positions. Note that "cm" denote the cone's center of mass which corresponds to 1/4 from the tail to tip. autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here u/v/w norm) or the bounds set in `cmin` and `cmax` Defaults to `false` when `cmin` and `cmax` are set by the user. cmax Sets the upper bound of the color domain. Value should have the same units as u/v/w norm and if set, `cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `cmin` and/or `cmax` to be equidistant to this point. Value should have the same units as u/v/w norm. Has no effect when `cauto` is `false`. cmin Sets the lower bound of the color domain. Value should have the same units as u/v/w norm and if set, `cmax` must be set as well. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.cone.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`cmin` and `cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.cone.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variable `norm` Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . lighting plotly.graph_objects.cone.Lighting instance or dict with compatible properties lightposition plotly.graph_objects.cone.Lightposition instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the surface. Please note that in the case of using high `opacity` values for example a value greater than or equal to 0.5 on two surfaces (and 0.25 with four surfaces), an overlay of multiple transparent surfaces may not perfectly be sorted in depth by the webgl API. This behavior may be improved in the near future and is subject to change. reversescale Reverses the color mapping if true. If true, `cmin` will correspond to the last color in the array and `cmax` will correspond to the first color. scene Sets a reference between this trace's 3D coordinate system and a 3D scene. If "scene" (the default value), the (x,y,z) coordinates refer to `layout.scene`. If "scene2", the (x,y,z) coordinates refer to `layout.scene2`, and so on. showscale Determines whether or not a colorbar is displayed for this trace. sizemode Determines whether `sizeref` is set as a "scaled" (i.e unitless) scalar (normalized by the max u/v/w norm in the vector field) or as "absolute" value (in the same units as the vector field). sizeref Adjusts the cone size scaling. The size of the cones is determined by their u/v/w norm multiplied a factor and `sizeref`. This factor (computed internally) corresponds to the minimum "time" to travel across two successive x/y/z positions at the average velocity of those two successive positions. All cones in a given trace use the same factor. With `sizemode` set to "scaled", `sizeref` is unitless, its default value is 0.5 With `sizemode` set to "absolute", `sizeref` has the same units as the u/v/w vector field, its the default value is half the sample's maximum vector norm. stream plotly.graph_objects.cone.Stream instance or dict with compatible properties text Sets the text elements associated with the cones. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textsrc Sets the source reference on plot.ly for text . u Sets the x components of the vector field. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. usrc Sets the source reference on plot.ly for u . v Sets the y components of the vector field. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). vsrc Sets the source reference on plot.ly for v . w Sets the z components of the vector field. wsrc Sets the source reference on plot.ly for w . x Sets the x coordinates of the vector field and of the displayed cones. xsrc Sets the source reference on plot.ly for x . y Sets the y coordinates of the vector field and of the displayed cones. ysrc Sets the source reference on plot.ly for y . z Sets the z coordinates of the vector field and of the displayed cones. zsrc Sets the source reference on plot.ly for z . """ def __init__( self, arg=None, anchor=None, autocolorscale=None, cauto=None, cmax=None, cmid=None, cmin=None, coloraxis=None, colorbar=None, colorscale=None, customdata=None, customdatasrc=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, lighting=None, lightposition=None, meta=None, metasrc=None, name=None, opacity=None, reversescale=None, scene=None, showscale=None, sizemode=None, sizeref=None, stream=None, text=None, textsrc=None, u=None, uid=None, uirevision=None, usrc=None, v=None, visible=None, vsrc=None, w=None, wsrc=None, x=None, xsrc=None, y=None, ysrc=None, z=None, zsrc=None, **kwargs ): """ Construct a new Cone object Use cone traces to visualize vector fields. Specify a vector field using 6 1D arrays, 3 position arrays `x`, `y` and `z` and 3 vector component arrays `u`, `v`, `w`. The cones are drawn exactly at the positions given by `x`, `y` and `z`. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.Cone anchor Sets the cones' anchor with respect to their x/y/z positions. Note that "cm" denote the cone's center of mass which corresponds to 1/4 from the tail to tip. autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here u/v/w norm) or the bounds set in `cmin` and `cmax` Defaults to `false` when `cmin` and `cmax` are set by the user. cmax Sets the upper bound of the color domain. Value should have the same units as u/v/w norm and if set, `cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `cmin` and/or `cmax` to be equidistant to this point. Value should have the same units as u/v/w norm. Has no effect when `cauto` is `false`. cmin Sets the lower bound of the color domain. Value should have the same units as u/v/w norm and if set, `cmax` must be set as well. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.cone.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`cmin` and `cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.cone.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variable `norm` Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . lighting plotly.graph_objects.cone.Lighting instance or dict with compatible properties lightposition plotly.graph_objects.cone.Lightposition instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the surface. Please note that in the case of using high `opacity` values for example a value greater than or equal to 0.5 on two surfaces (and 0.25 with four surfaces), an overlay of multiple transparent surfaces may not perfectly be sorted in depth by the webgl API. This behavior may be improved in the near future and is subject to change. reversescale Reverses the color mapping if true. If true, `cmin` will correspond to the last color in the array and `cmax` will correspond to the first color. scene Sets a reference between this trace's 3D coordinate system and a 3D scene. If "scene" (the default value), the (x,y,z) coordinates refer to `layout.scene`. If "scene2", the (x,y,z) coordinates refer to `layout.scene2`, and so on. showscale Determines whether or not a colorbar is displayed for this trace. sizemode Determines whether `sizeref` is set as a "scaled" (i.e unitless) scalar (normalized by the max u/v/w norm in the vector field) or as "absolute" value (in the same units as the vector field). sizeref Adjusts the cone size scaling. The size of the cones is determined by their u/v/w norm multiplied a factor and `sizeref`. This factor (computed internally) corresponds to the minimum "time" to travel across two successive x/y/z positions at the average velocity of those two successive positions. All cones in a given trace use the same factor. With `sizemode` set to "scaled", `sizeref` is unitless, its default value is 0.5 With `sizemode` set to "absolute", `sizeref` has the same units as the u/v/w vector field, its the default value is half the sample's maximum vector norm. stream plotly.graph_objects.cone.Stream instance or dict with compatible properties text Sets the text elements associated with the cones. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textsrc Sets the source reference on plot.ly for text . u Sets the x components of the vector field. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. usrc Sets the source reference on plot.ly for u . v Sets the y components of the vector field. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). vsrc Sets the source reference on plot.ly for v . w Sets the z components of the vector field. wsrc Sets the source reference on plot.ly for w . x Sets the x coordinates of the vector field and of the displayed cones. xsrc Sets the source reference on plot.ly for x . y Sets the y coordinates of the vector field and of the displayed cones. ysrc Sets the source reference on plot.ly for y . z Sets the z coordinates of the vector field and of the displayed cones. zsrc Sets the source reference on plot.ly for z . Returns ------- Cone """ super(Cone, self).__init__("cone") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.Cone constructor must be a dict or an instance of plotly.graph_objs.Cone""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators import cone as v_cone # Initialize validators # --------------------- self._validators["anchor"] = v_cone.AnchorValidator() self._validators["autocolorscale"] = v_cone.AutocolorscaleValidator() self._validators["cauto"] = v_cone.CautoValidator() self._validators["cmax"] = v_cone.CmaxValidator() self._validators["cmid"] = v_cone.CmidValidator() self._validators["cmin"] = v_cone.CminValidator() self._validators["coloraxis"] = v_cone.ColoraxisValidator() self._validators["colorbar"] = v_cone.ColorBarValidator() self._validators["colorscale"] = v_cone.ColorscaleValidator() self._validators["customdata"] = v_cone.CustomdataValidator() self._validators["customdatasrc"] = v_cone.CustomdatasrcValidator() self._validators["hoverinfo"] = v_cone.HoverinfoValidator() self._validators["hoverinfosrc"] = v_cone.HoverinfosrcValidator() self._validators["hoverlabel"] = v_cone.HoverlabelValidator() self._validators["hovertemplate"] = v_cone.HovertemplateValidator() self._validators["hovertemplatesrc"] = v_cone.HovertemplatesrcValidator() self._validators["hovertext"] = v_cone.HovertextValidator() self._validators["hovertextsrc"] = v_cone.HovertextsrcValidator() self._validators["ids"] = v_cone.IdsValidator() self._validators["idssrc"] = v_cone.IdssrcValidator() self._validators["lighting"] = v_cone.LightingValidator() self._validators["lightposition"] = v_cone.LightpositionValidator() self._validators["meta"] = v_cone.MetaValidator() self._validators["metasrc"] = v_cone.MetasrcValidator() self._validators["name"] = v_cone.NameValidator() self._validators["opacity"] = v_cone.OpacityValidator() self._validators["reversescale"] = v_cone.ReversescaleValidator() self._validators["scene"] = v_cone.SceneValidator() self._validators["showscale"] = v_cone.ShowscaleValidator() self._validators["sizemode"] = v_cone.SizemodeValidator() self._validators["sizeref"] = v_cone.SizerefValidator() self._validators["stream"] = v_cone.StreamValidator() self._validators["text"] = v_cone.TextValidator() self._validators["textsrc"] = v_cone.TextsrcValidator() self._validators["u"] = v_cone.UValidator() self._validators["uid"] = v_cone.UidValidator() self._validators["uirevision"] = v_cone.UirevisionValidator() self._validators["usrc"] = v_cone.UsrcValidator() self._validators["v"] = v_cone.VValidator() self._validators["visible"] = v_cone.VisibleValidator() self._validators["vsrc"] = v_cone.VsrcValidator() self._validators["w"] = v_cone.WValidator() self._validators["wsrc"] = v_cone.WsrcValidator() self._validators["x"] = v_cone.XValidator() self._validators["xsrc"] = v_cone.XsrcValidator() self._validators["y"] = v_cone.YValidator() self._validators["ysrc"] = v_cone.YsrcValidator() self._validators["z"] = v_cone.ZValidator() self._validators["zsrc"] = v_cone.ZsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("anchor", None) self["anchor"] = anchor if anchor is not None else _v _v = arg.pop("autocolorscale", None) self["autocolorscale"] = autocolorscale if autocolorscale is not None else _v _v = arg.pop("cauto", None) self["cauto"] = cauto if cauto is not None else _v _v = arg.pop("cmax", None) self["cmax"] = cmax if cmax is not None else _v _v = arg.pop("cmid", None) self["cmid"] = cmid if cmid is not None else _v _v = arg.pop("cmin", None) self["cmin"] = cmin if cmin is not None else _v _v = arg.pop("coloraxis", None) self["coloraxis"] = coloraxis if coloraxis is not None else _v _v = arg.pop("colorbar", None) self["colorbar"] = colorbar if colorbar is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("customdata", None) self["customdata"] = customdata if customdata is not None else _v _v = arg.pop("customdatasrc", None) self["customdatasrc"] = customdatasrc if customdatasrc is not None else _v _v = arg.pop("hoverinfo", None) self["hoverinfo"] = hoverinfo if hoverinfo is not None else _v _v = arg.pop("hoverinfosrc", None) self["hoverinfosrc"] = hoverinfosrc if hoverinfosrc is not None else _v _v = arg.pop("hoverlabel", None) self["hoverlabel"] = hoverlabel if hoverlabel is not None else _v _v = arg.pop("hovertemplate", None) self["hovertemplate"] = hovertemplate if hovertemplate is not None else _v _v = arg.pop("hovertemplatesrc", None) self["hovertemplatesrc"] = ( hovertemplatesrc if hovertemplatesrc is not None else _v ) _v = arg.pop("hovertext", None) self["hovertext"] = hovertext if hovertext is not None else _v _v = arg.pop("hovertextsrc", None) self["hovertextsrc"] = hovertextsrc if hovertextsrc is not None else _v _v = arg.pop("ids", None) self["ids"] = ids if ids is not None else _v _v = arg.pop("idssrc", None) self["idssrc"] = idssrc if idssrc is not None else _v _v = arg.pop("lighting", None) self["lighting"] = lighting if lighting is not None else _v _v = arg.pop("lightposition", None) self["lightposition"] = lightposition if lightposition is not None else _v _v = arg.pop("meta", None) self["meta"] = meta if meta is not None else _v _v = arg.pop("metasrc", None) self["metasrc"] = metasrc if metasrc is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("reversescale", None) self["reversescale"] = reversescale if reversescale is not None else _v _v = arg.pop("scene", None) self["scene"] = scene if scene is not None else _v _v = arg.pop("showscale", None) self["showscale"] = showscale if showscale is not None else _v _v = arg.pop("sizemode", None) self["sizemode"] = sizemode if sizemode is not None else _v _v = arg.pop("sizeref", None) self["sizeref"] = sizeref if sizeref is not None else _v _v = arg.pop("stream", None) self["stream"] = stream if stream is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v _v = arg.pop("textsrc", None) self["textsrc"] = textsrc if textsrc is not None else _v _v = arg.pop("u", None) self["u"] = u if u is not None else _v _v = arg.pop("uid", None) self["uid"] = uid if uid is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("usrc", None) self["usrc"] = usrc if usrc is not None else _v _v = arg.pop("v", None) self["v"] = v if v is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("vsrc", None) self["vsrc"] = vsrc if vsrc is not None else _v _v = arg.pop("w", None) self["w"] = w if w is not None else _v _v = arg.pop("wsrc", None) self["wsrc"] = wsrc if wsrc is not None else _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xsrc", None) self["xsrc"] = xsrc if xsrc is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("ysrc", None) self["ysrc"] = ysrc if ysrc is not None else _v _v = arg.pop("z", None) self["z"] = z if z is not None else _v _v = arg.pop("zsrc", None) self["zsrc"] = zsrc if zsrc is not None else _v # Read-only literals # ------------------ from _plotly_utils.basevalidators import LiteralValidator self._props["type"] = "cone" self._validators["type"] = LiteralValidator( plotly_name="type", parent_name="cone", val="cone" ) arg.pop("type", None) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceType as _BaseTraceType import copy as _copy class Choroplethmapbox(_BaseTraceType): # autocolorscale # -------------- @property def autocolorscale(self): """ Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. The 'autocolorscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocolorscale"] @autocolorscale.setter def autocolorscale(self, val): self["autocolorscale"] = val # below # ----- @property def below(self): """ Determines if the choropleth polygons will be inserted before the layer with the specified ID. By default, choroplethmapbox traces are placed above the water layers. If set to '', the layer will be inserted above every existing layer. The 'below' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["below"] @below.setter def below(self, val): self["below"] = val # coloraxis # --------- @property def coloraxis(self): """ Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. The 'coloraxis' property is an identifier of a particular subplot, of type 'coloraxis', that may be specified as the string 'coloraxis' optionally followed by an integer >= 1 (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) Returns ------- str """ return self["coloraxis"] @coloraxis.setter def coloraxis(self, val): self["coloraxis"] = val # colorbar # -------- @property def colorbar(self): """ The 'colorbar' property is an instance of ColorBar that may be specified as: - An instance of plotly.graph_objs.choroplethmapbox.ColorBar - A dict of string/value properties that will be passed to the ColorBar constructor Supported dict properties: bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.choroplethmapbo x.colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.choroplethmapbox.colorbar.tickformatstopdefau lts), sets the default property values to use for elements of choroplethmapbox.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.choroplethmapbox.colorbar. Title instance or dict with compatible properties titlefont Deprecated: Please use choroplethmapbox.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use choroplethmapbox.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- plotly.graph_objs.choroplethmapbox.ColorBar """ return self["colorbar"] @colorbar.setter def colorbar(self, val): self["colorbar"] = val # colorscale # ---------- @property def colorscale(self): """ Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,Earth,Electric,Vi ridis,Cividis. The 'colorscale' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # customdata # ---------- @property def customdata(self): """ Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements The 'customdata' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["customdata"] @customdata.setter def customdata(self, val): self["customdata"] = val # customdatasrc # ------------- @property def customdatasrc(self): """ Sets the source reference on plot.ly for customdata . The 'customdatasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["customdatasrc"] @customdatasrc.setter def customdatasrc(self, val): self["customdatasrc"] = val # geojson # ------- @property def geojson(self): """ Sets the GeoJSON data associated with this trace. Can be set as a valid GeoJSON object or as URL string Note that we only accept GeoJSON of type "FeatureCollection" and "Feature" with geometries of type "Polygon" and "MultiPolygon". The 'geojson' property accepts values of any type Returns ------- Any """ return self["geojson"] @geojson.setter def geojson(self, val): self["geojson"] = val # hoverinfo # --------- @property def hoverinfo(self): """ Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. The 'hoverinfo' property is a flaglist and may be specified as a string containing: - Any combination of ['location', 'z', 'text', 'name'] joined with '+' characters (e.g. 'location+z') OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') - A list or array of the above Returns ------- Any|numpy.ndarray """ return self["hoverinfo"] @hoverinfo.setter def hoverinfo(self, val): self["hoverinfo"] = val # hoverinfosrc # ------------ @property def hoverinfosrc(self): """ Sets the source reference on plot.ly for hoverinfo . The 'hoverinfosrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hoverinfosrc"] @hoverinfosrc.setter def hoverinfosrc(self, val): self["hoverinfosrc"] = val # hoverlabel # ---------- @property def hoverlabel(self): """ The 'hoverlabel' property is an instance of Hoverlabel that may be specified as: - An instance of plotly.graph_objs.choroplethmapbox.Hoverlabel - A dict of string/value properties that will be passed to the Hoverlabel constructor Supported dict properties: align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- plotly.graph_objs.choroplethmapbox.Hoverlabel """ return self["hoverlabel"] @hoverlabel.setter def hoverlabel(self, val): self["hoverlabel"] = val # hovertemplate # ------------- @property def hovertemplate(self): """ Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event- data. Additionally, every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. variable `properties` Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. The 'hovertemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertemplate"] @hovertemplate.setter def hovertemplate(self, val): self["hovertemplate"] = val # hovertemplatesrc # ---------------- @property def hovertemplatesrc(self): """ Sets the source reference on plot.ly for hovertemplate . The 'hovertemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertemplatesrc"] @hovertemplatesrc.setter def hovertemplatesrc(self, val): self["hovertemplatesrc"] = val # hovertext # --------- @property def hovertext(self): """ Same as `text`. The 'hovertext' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertext"] @hovertext.setter def hovertext(self, val): self["hovertext"] = val # hovertextsrc # ------------ @property def hovertextsrc(self): """ Sets the source reference on plot.ly for hovertext . The 'hovertextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertextsrc"] @hovertextsrc.setter def hovertextsrc(self, val): self["hovertextsrc"] = val # ids # --- @property def ids(self): """ Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. The 'ids' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ids"] @ids.setter def ids(self, val): self["ids"] = val # idssrc # ------ @property def idssrc(self): """ Sets the source reference on plot.ly for ids . The 'idssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["idssrc"] @idssrc.setter def idssrc(self, val): self["idssrc"] = val # locations # --------- @property def locations(self): """ Sets which features found in "geojson" to plot using their feature `id` field. The 'locations' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["locations"] @locations.setter def locations(self, val): self["locations"] = val # locationssrc # ------------ @property def locationssrc(self): """ Sets the source reference on plot.ly for locations . The 'locationssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["locationssrc"] @locationssrc.setter def locationssrc(self, val): self["locationssrc"] = val # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.choroplethmapbox.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: line plotly.graph_objects.choroplethmapbox.marker.Li ne instance or dict with compatible properties opacity Sets the opacity of the locations. opacitysrc Sets the source reference on plot.ly for opacity . Returns ------- plotly.graph_objs.choroplethmapbox.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # meta # ---- @property def meta(self): """ Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. The 'meta' property accepts values of any type Returns ------- Any|numpy.ndarray """ return self["meta"] @meta.setter def meta(self, val): self["meta"] = val # metasrc # ------- @property def metasrc(self): """ Sets the source reference on plot.ly for meta . The 'metasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["metasrc"] @metasrc.setter def metasrc(self, val): self["metasrc"] = val # name # ---- @property def name(self): """ Sets the trace name. The trace name appear as the legend item and on hover. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # reversescale # ------------ @property def reversescale(self): """ Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. The 'reversescale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["reversescale"] @reversescale.setter def reversescale(self, val): self["reversescale"] = val # selected # -------- @property def selected(self): """ The 'selected' property is an instance of Selected that may be specified as: - An instance of plotly.graph_objs.choroplethmapbox.Selected - A dict of string/value properties that will be passed to the Selected constructor Supported dict properties: marker plotly.graph_objects.choroplethmapbox.selected. Marker instance or dict with compatible properties Returns ------- plotly.graph_objs.choroplethmapbox.Selected """ return self["selected"] @selected.setter def selected(self, val): self["selected"] = val # selectedpoints # -------------- @property def selectedpoints(self): """ Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. The 'selectedpoints' property accepts values of any type Returns ------- Any """ return self["selectedpoints"] @selectedpoints.setter def selectedpoints(self, val): self["selectedpoints"] = val # showscale # --------- @property def showscale(self): """ Determines whether or not a colorbar is displayed for this trace. The 'showscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showscale"] @showscale.setter def showscale(self, val): self["showscale"] = val # stream # ------ @property def stream(self): """ The 'stream' property is an instance of Stream that may be specified as: - An instance of plotly.graph_objs.choroplethmapbox.Stream - A dict of string/value properties that will be passed to the Stream constructor Supported dict properties: maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- plotly.graph_objs.choroplethmapbox.Stream """ return self["stream"] @stream.setter def stream(self, val): self["stream"] = val # subplot # ------- @property def subplot(self): """ Sets a reference between this trace's data coordinates and a mapbox subplot. If "mapbox" (the default value), the data refer to `layout.mapbox`. If "mapbox2", the data refer to `layout.mapbox2`, and so on. The 'subplot' property is an identifier of a particular subplot, of type 'mapbox', that may be specified as the string 'mapbox' optionally followed by an integer >= 1 (e.g. 'mapbox', 'mapbox1', 'mapbox2', 'mapbox3', etc.) Returns ------- str """ return self["subplot"] @subplot.setter def subplot(self, val): self["subplot"] = val # text # ---- @property def text(self): """ Sets the text elements associated with each location. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["text"] @text.setter def text(self, val): self["text"] = val # textsrc # ------- @property def textsrc(self): """ Sets the source reference on plot.ly for text . The 'textsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["textsrc"] @textsrc.setter def textsrc(self, val): self["textsrc"] = val # uid # --- @property def uid(self): """ Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. The 'uid' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["uid"] @uid.setter def uid(self, val): self["uid"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # unselected # ---------- @property def unselected(self): """ The 'unselected' property is an instance of Unselected that may be specified as: - An instance of plotly.graph_objs.choroplethmapbox.Unselected - A dict of string/value properties that will be passed to the Unselected constructor Supported dict properties: marker plotly.graph_objects.choroplethmapbox.unselecte d.Marker instance or dict with compatible properties Returns ------- plotly.graph_objs.choroplethmapbox.Unselected """ return self["unselected"] @unselected.setter def unselected(self, val): self["unselected"] = val # visible # ------- @property def visible(self): """ Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). The 'visible' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'legendonly'] Returns ------- Any """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # z # - @property def z(self): """ Sets the color values. The 'z' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["z"] @z.setter def z(self, val): self["z"] = val # zauto # ----- @property def zauto(self): """ Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. The 'zauto' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["zauto"] @zauto.setter def zauto(self, val): self["zauto"] = val # zmax # ---- @property def zmax(self): """ Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. The 'zmax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["zmax"] @zmax.setter def zmax(self, val): self["zmax"] = val # zmid # ---- @property def zmid(self): """ Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. The 'zmid' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["zmid"] @zmid.setter def zmid(self, val): self["zmid"] = val # zmin # ---- @property def zmin(self): """ Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. The 'zmin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["zmin"] @zmin.setter def zmin(self, val): self["zmin"] = val # zsrc # ---- @property def zsrc(self): """ Sets the source reference on plot.ly for z . The 'zsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["zsrc"] @zsrc.setter def zsrc(self, val): self["zsrc"] = val # type # ---- @property def type(self): return self._props["type"] # property parent name # -------------------- @property def _parent_path_str(self): return "" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. below Determines if the choropleth polygons will be inserted before the layer with the specified ID. By default, choroplethmapbox traces are placed above the water layers. If set to '', the layer will be inserted above every existing layer. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.choroplethmapbox.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . geojson Sets the GeoJSON data associated with this trace. Can be set as a valid GeoJSON object or as URL string Note that we only accept GeoJSON of type "FeatureCollection" and "Feature" with geometries of type "Polygon" and "MultiPolygon". hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.choroplethmapbox.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variable `properties` Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . locations Sets which features found in "geojson" to plot using their feature `id` field. locationssrc Sets the source reference on plot.ly for locations . marker plotly.graph_objects.choroplethmapbox.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. reversescale Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. selected plotly.graph_objects.choroplethmapbox.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.choroplethmapbox.Stream instance or dict with compatible properties subplot Sets a reference between this trace's data coordinates and a mapbox subplot. If "mapbox" (the default value), the data refer to `layout.mapbox`. If "mapbox2", the data refer to `layout.mapbox2`, and so on. text Sets the text elements associated with each location. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.choroplethmapbox.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). z Sets the color values. zauto Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. zmax Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. zmid Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. zmin Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. zsrc Sets the source reference on plot.ly for z . """ def __init__( self, arg=None, autocolorscale=None, below=None, coloraxis=None, colorbar=None, colorscale=None, customdata=None, customdatasrc=None, geojson=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, locations=None, locationssrc=None, marker=None, meta=None, metasrc=None, name=None, reversescale=None, selected=None, selectedpoints=None, showscale=None, stream=None, subplot=None, text=None, textsrc=None, uid=None, uirevision=None, unselected=None, visible=None, z=None, zauto=None, zmax=None, zmid=None, zmin=None, zsrc=None, **kwargs ): """ Construct a new Choroplethmapbox object GeoJSON features to be filled are set in `geojson` The data that describes the choropleth value-to-color mapping is set in `locations` and `z`. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.Choroplethmapbox autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. below Determines if the choropleth polygons will be inserted before the layer with the specified ID. By default, choroplethmapbox traces are placed above the water layers. If set to '', the layer will be inserted above every existing layer. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.choroplethmapbox.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . geojson Sets the GeoJSON data associated with this trace. Can be set as a valid GeoJSON object or as URL string Note that we only accept GeoJSON of type "FeatureCollection" and "Feature" with geometries of type "Polygon" and "MultiPolygon". hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.choroplethmapbox.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variable `properties` Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . locations Sets which features found in "geojson" to plot using their feature `id` field. locationssrc Sets the source reference on plot.ly for locations . marker plotly.graph_objects.choroplethmapbox.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. reversescale Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. selected plotly.graph_objects.choroplethmapbox.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.choroplethmapbox.Stream instance or dict with compatible properties subplot Sets a reference between this trace's data coordinates and a mapbox subplot. If "mapbox" (the default value), the data refer to `layout.mapbox`. If "mapbox2", the data refer to `layout.mapbox2`, and so on. text Sets the text elements associated with each location. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.choroplethmapbox.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). z Sets the color values. zauto Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. zmax Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. zmid Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. zmin Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. zsrc Sets the source reference on plot.ly for z . Returns ------- Choroplethmapbox """ super(Choroplethmapbox, self).__init__("choroplethmapbox") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.Choroplethmapbox constructor must be a dict or an instance of plotly.graph_objs.Choroplethmapbox""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators import choroplethmapbox as v_choroplethmapbox # Initialize validators # --------------------- self._validators[ "autocolorscale" ] = v_choroplethmapbox.AutocolorscaleValidator() self._validators["below"] = v_choroplethmapbox.BelowValidator() self._validators["coloraxis"] = v_choroplethmapbox.ColoraxisValidator() self._validators["colorbar"] = v_choroplethmapbox.ColorBarValidator() self._validators["colorscale"] = v_choroplethmapbox.ColorscaleValidator() self._validators["customdata"] = v_choroplethmapbox.CustomdataValidator() self._validators["customdatasrc"] = v_choroplethmapbox.CustomdatasrcValidator() self._validators["geojson"] = v_choroplethmapbox.GeojsonValidator() self._validators["hoverinfo"] = v_choroplethmapbox.HoverinfoValidator() self._validators["hoverinfosrc"] = v_choroplethmapbox.HoverinfosrcValidator() self._validators["hoverlabel"] = v_choroplethmapbox.HoverlabelValidator() self._validators["hovertemplate"] = v_choroplethmapbox.HovertemplateValidator() self._validators[ "hovertemplatesrc" ] = v_choroplethmapbox.HovertemplatesrcValidator() self._validators["hovertext"] = v_choroplethmapbox.HovertextValidator() self._validators["hovertextsrc"] = v_choroplethmapbox.HovertextsrcValidator() self._validators["ids"] = v_choroplethmapbox.IdsValidator() self._validators["idssrc"] = v_choroplethmapbox.IdssrcValidator() self._validators["locations"] = v_choroplethmapbox.LocationsValidator() self._validators["locationssrc"] = v_choroplethmapbox.LocationssrcValidator() self._validators["marker"] = v_choroplethmapbox.MarkerValidator() self._validators["meta"] = v_choroplethmapbox.MetaValidator() self._validators["metasrc"] = v_choroplethmapbox.MetasrcValidator() self._validators["name"] = v_choroplethmapbox.NameValidator() self._validators["reversescale"] = v_choroplethmapbox.ReversescaleValidator() self._validators["selected"] = v_choroplethmapbox.SelectedValidator() self._validators[ "selectedpoints" ] = v_choroplethmapbox.SelectedpointsValidator() self._validators["showscale"] = v_choroplethmapbox.ShowscaleValidator() self._validators["stream"] = v_choroplethmapbox.StreamValidator() self._validators["subplot"] = v_choroplethmapbox.SubplotValidator() self._validators["text"] = v_choroplethmapbox.TextValidator() self._validators["textsrc"] = v_choroplethmapbox.TextsrcValidator() self._validators["uid"] = v_choroplethmapbox.UidValidator() self._validators["uirevision"] = v_choroplethmapbox.UirevisionValidator() self._validators["unselected"] = v_choroplethmapbox.UnselectedValidator() self._validators["visible"] = v_choroplethmapbox.VisibleValidator() self._validators["z"] = v_choroplethmapbox.ZValidator() self._validators["zauto"] = v_choroplethmapbox.ZautoValidator() self._validators["zmax"] = v_choroplethmapbox.ZmaxValidator() self._validators["zmid"] = v_choroplethmapbox.ZmidValidator() self._validators["zmin"] = v_choroplethmapbox.ZminValidator() self._validators["zsrc"] = v_choroplethmapbox.ZsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autocolorscale", None) self["autocolorscale"] = autocolorscale if autocolorscale is not None else _v _v = arg.pop("below", None) self["below"] = below if below is not None else _v _v = arg.pop("coloraxis", None) self["coloraxis"] = coloraxis if coloraxis is not None else _v _v = arg.pop("colorbar", None) self["colorbar"] = colorbar if colorbar is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("customdata", None) self["customdata"] = customdata if customdata is not None else _v _v = arg.pop("customdatasrc", None) self["customdatasrc"] = customdatasrc if customdatasrc is not None else _v _v = arg.pop("geojson", None) self["geojson"] = geojson if geojson is not None else _v _v = arg.pop("hoverinfo", None) self["hoverinfo"] = hoverinfo if hoverinfo is not None else _v _v = arg.pop("hoverinfosrc", None) self["hoverinfosrc"] = hoverinfosrc if hoverinfosrc is not None else _v _v = arg.pop("hoverlabel", None) self["hoverlabel"] = hoverlabel if hoverlabel is not None else _v _v = arg.pop("hovertemplate", None) self["hovertemplate"] = hovertemplate if hovertemplate is not None else _v _v = arg.pop("hovertemplatesrc", None) self["hovertemplatesrc"] = ( hovertemplatesrc if hovertemplatesrc is not None else _v ) _v = arg.pop("hovertext", None) self["hovertext"] = hovertext if hovertext is not None else _v _v = arg.pop("hovertextsrc", None) self["hovertextsrc"] = hovertextsrc if hovertextsrc is not None else _v _v = arg.pop("ids", None) self["ids"] = ids if ids is not None else _v _v = arg.pop("idssrc", None) self["idssrc"] = idssrc if idssrc is not None else _v _v = arg.pop("locations", None) self["locations"] = locations if locations is not None else _v _v = arg.pop("locationssrc", None) self["locationssrc"] = locationssrc if locationssrc is not None else _v _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v _v = arg.pop("meta", None) self["meta"] = meta if meta is not None else _v _v = arg.pop("metasrc", None) self["metasrc"] = metasrc if metasrc is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("reversescale", None) self["reversescale"] = reversescale if reversescale is not None else _v _v = arg.pop("selected", None) self["selected"] = selected if selected is not None else _v _v = arg.pop("selectedpoints", None) self["selectedpoints"] = selectedpoints if selectedpoints is not None else _v _v = arg.pop("showscale", None) self["showscale"] = showscale if showscale is not None else _v _v = arg.pop("stream", None) self["stream"] = stream if stream is not None else _v _v = arg.pop("subplot", None) self["subplot"] = subplot if subplot is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v _v = arg.pop("textsrc", None) self["textsrc"] = textsrc if textsrc is not None else _v _v = arg.pop("uid", None) self["uid"] = uid if uid is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("unselected", None) self["unselected"] = unselected if unselected is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("z", None) self["z"] = z if z is not None else _v _v = arg.pop("zauto", None) self["zauto"] = zauto if zauto is not None else _v _v = arg.pop("zmax", None) self["zmax"] = zmax if zmax is not None else _v _v = arg.pop("zmid", None) self["zmid"] = zmid if zmid is not None else _v _v = arg.pop("zmin", None) self["zmin"] = zmin if zmin is not None else _v _v = arg.pop("zsrc", None) self["zsrc"] = zsrc if zsrc is not None else _v # Read-only literals # ------------------ from _plotly_utils.basevalidators import LiteralValidator self._props["type"] = "choroplethmapbox" self._validators["type"] = LiteralValidator( plotly_name="type", parent_name="choroplethmapbox", val="choroplethmapbox" ) arg.pop("type", None) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceType as _BaseTraceType import copy as _copy class Choropleth(_BaseTraceType): # autocolorscale # -------------- @property def autocolorscale(self): """ Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. The 'autocolorscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocolorscale"] @autocolorscale.setter def autocolorscale(self, val): self["autocolorscale"] = val # coloraxis # --------- @property def coloraxis(self): """ Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. The 'coloraxis' property is an identifier of a particular subplot, of type 'coloraxis', that may be specified as the string 'coloraxis' optionally followed by an integer >= 1 (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) Returns ------- str """ return self["coloraxis"] @coloraxis.setter def coloraxis(self, val): self["coloraxis"] = val # colorbar # -------- @property def colorbar(self): """ The 'colorbar' property is an instance of ColorBar that may be specified as: - An instance of plotly.graph_objs.choropleth.ColorBar - A dict of string/value properties that will be passed to the ColorBar constructor Supported dict properties: bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.choropleth.colo rbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.choropleth.colorbar.tickformatstopdefaults), sets the default property values to use for elements of choropleth.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.choropleth.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use choropleth.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use choropleth.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- plotly.graph_objs.choropleth.ColorBar """ return self["colorbar"] @colorbar.setter def colorbar(self, val): self["colorbar"] = val # colorscale # ---------- @property def colorscale(self): """ Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,Earth,Electric,Vi ridis,Cividis. The 'colorscale' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # customdata # ---------- @property def customdata(self): """ Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements The 'customdata' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["customdata"] @customdata.setter def customdata(self, val): self["customdata"] = val # customdatasrc # ------------- @property def customdatasrc(self): """ Sets the source reference on plot.ly for customdata . The 'customdatasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["customdatasrc"] @customdatasrc.setter def customdatasrc(self, val): self["customdatasrc"] = val # geo # --- @property def geo(self): """ Sets a reference between this trace's geospatial coordinates and a geographic map. If "geo" (the default value), the geospatial coordinates refer to `layout.geo`. If "geo2", the geospatial coordinates refer to `layout.geo2`, and so on. The 'geo' property is an identifier of a particular subplot, of type 'geo', that may be specified as the string 'geo' optionally followed by an integer >= 1 (e.g. 'geo', 'geo1', 'geo2', 'geo3', etc.) Returns ------- str """ return self["geo"] @geo.setter def geo(self, val): self["geo"] = val # hoverinfo # --------- @property def hoverinfo(self): """ Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. The 'hoverinfo' property is a flaglist and may be specified as a string containing: - Any combination of ['location', 'z', 'text', 'name'] joined with '+' characters (e.g. 'location+z') OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') - A list or array of the above Returns ------- Any|numpy.ndarray """ return self["hoverinfo"] @hoverinfo.setter def hoverinfo(self, val): self["hoverinfo"] = val # hoverinfosrc # ------------ @property def hoverinfosrc(self): """ Sets the source reference on plot.ly for hoverinfo . The 'hoverinfosrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hoverinfosrc"] @hoverinfosrc.setter def hoverinfosrc(self, val): self["hoverinfosrc"] = val # hoverlabel # ---------- @property def hoverlabel(self): """ The 'hoverlabel' property is an instance of Hoverlabel that may be specified as: - An instance of plotly.graph_objs.choropleth.Hoverlabel - A dict of string/value properties that will be passed to the Hoverlabel constructor Supported dict properties: align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- plotly.graph_objs.choropleth.Hoverlabel """ return self["hoverlabel"] @hoverlabel.setter def hoverlabel(self, val): self["hoverlabel"] = val # hovertemplate # ------------- @property def hovertemplate(self): """ Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event- data. Additionally, every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. The 'hovertemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertemplate"] @hovertemplate.setter def hovertemplate(self, val): self["hovertemplate"] = val # hovertemplatesrc # ---------------- @property def hovertemplatesrc(self): """ Sets the source reference on plot.ly for hovertemplate . The 'hovertemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertemplatesrc"] @hovertemplatesrc.setter def hovertemplatesrc(self, val): self["hovertemplatesrc"] = val # hovertext # --------- @property def hovertext(self): """ Same as `text`. The 'hovertext' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertext"] @hovertext.setter def hovertext(self, val): self["hovertext"] = val # hovertextsrc # ------------ @property def hovertextsrc(self): """ Sets the source reference on plot.ly for hovertext . The 'hovertextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertextsrc"] @hovertextsrc.setter def hovertextsrc(self, val): self["hovertextsrc"] = val # ids # --- @property def ids(self): """ Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. The 'ids' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ids"] @ids.setter def ids(self, val): self["ids"] = val # idssrc # ------ @property def idssrc(self): """ Sets the source reference on plot.ly for ids . The 'idssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["idssrc"] @idssrc.setter def idssrc(self, val): self["idssrc"] = val # locationmode # ------------ @property def locationmode(self): """ Determines the set of locations used to match entries in `locations` to regions on the map. The 'locationmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['ISO-3', 'USA-states', 'country names'] Returns ------- Any """ return self["locationmode"] @locationmode.setter def locationmode(self, val): self["locationmode"] = val # locations # --------- @property def locations(self): """ Sets the coordinates via location IDs or names. See `locationmode` for more info. The 'locations' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["locations"] @locations.setter def locations(self, val): self["locations"] = val # locationssrc # ------------ @property def locationssrc(self): """ Sets the source reference on plot.ly for locations . The 'locationssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["locationssrc"] @locationssrc.setter def locationssrc(self, val): self["locationssrc"] = val # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.choropleth.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: line plotly.graph_objects.choropleth.marker.Line instance or dict with compatible properties opacity Sets the opacity of the locations. opacitysrc Sets the source reference on plot.ly for opacity . Returns ------- plotly.graph_objs.choropleth.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # meta # ---- @property def meta(self): """ Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. The 'meta' property accepts values of any type Returns ------- Any|numpy.ndarray """ return self["meta"] @meta.setter def meta(self, val): self["meta"] = val # metasrc # ------- @property def metasrc(self): """ Sets the source reference on plot.ly for meta . The 'metasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["metasrc"] @metasrc.setter def metasrc(self, val): self["metasrc"] = val # name # ---- @property def name(self): """ Sets the trace name. The trace name appear as the legend item and on hover. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # reversescale # ------------ @property def reversescale(self): """ Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. The 'reversescale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["reversescale"] @reversescale.setter def reversescale(self, val): self["reversescale"] = val # selected # -------- @property def selected(self): """ The 'selected' property is an instance of Selected that may be specified as: - An instance of plotly.graph_objs.choropleth.Selected - A dict of string/value properties that will be passed to the Selected constructor Supported dict properties: marker plotly.graph_objects.choropleth.selected.Marker instance or dict with compatible properties Returns ------- plotly.graph_objs.choropleth.Selected """ return self["selected"] @selected.setter def selected(self, val): self["selected"] = val # selectedpoints # -------------- @property def selectedpoints(self): """ Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. The 'selectedpoints' property accepts values of any type Returns ------- Any """ return self["selectedpoints"] @selectedpoints.setter def selectedpoints(self, val): self["selectedpoints"] = val # showscale # --------- @property def showscale(self): """ Determines whether or not a colorbar is displayed for this trace. The 'showscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showscale"] @showscale.setter def showscale(self, val): self["showscale"] = val # stream # ------ @property def stream(self): """ The 'stream' property is an instance of Stream that may be specified as: - An instance of plotly.graph_objs.choropleth.Stream - A dict of string/value properties that will be passed to the Stream constructor Supported dict properties: maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- plotly.graph_objs.choropleth.Stream """ return self["stream"] @stream.setter def stream(self, val): self["stream"] = val # text # ---- @property def text(self): """ Sets the text elements associated with each location. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["text"] @text.setter def text(self, val): self["text"] = val # textsrc # ------- @property def textsrc(self): """ Sets the source reference on plot.ly for text . The 'textsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["textsrc"] @textsrc.setter def textsrc(self, val): self["textsrc"] = val # uid # --- @property def uid(self): """ Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. The 'uid' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["uid"] @uid.setter def uid(self, val): self["uid"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # unselected # ---------- @property def unselected(self): """ The 'unselected' property is an instance of Unselected that may be specified as: - An instance of plotly.graph_objs.choropleth.Unselected - A dict of string/value properties that will be passed to the Unselected constructor Supported dict properties: marker plotly.graph_objects.choropleth.unselected.Mark er instance or dict with compatible properties Returns ------- plotly.graph_objs.choropleth.Unselected """ return self["unselected"] @unselected.setter def unselected(self, val): self["unselected"] = val # visible # ------- @property def visible(self): """ Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). The 'visible' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'legendonly'] Returns ------- Any """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # z # - @property def z(self): """ Sets the color values. The 'z' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["z"] @z.setter def z(self, val): self["z"] = val # zauto # ----- @property def zauto(self): """ Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. The 'zauto' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["zauto"] @zauto.setter def zauto(self, val): self["zauto"] = val # zmax # ---- @property def zmax(self): """ Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. The 'zmax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["zmax"] @zmax.setter def zmax(self, val): self["zmax"] = val # zmid # ---- @property def zmid(self): """ Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. The 'zmid' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["zmid"] @zmid.setter def zmid(self, val): self["zmid"] = val # zmin # ---- @property def zmin(self): """ Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. The 'zmin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["zmin"] @zmin.setter def zmin(self, val): self["zmin"] = val # zsrc # ---- @property def zsrc(self): """ Sets the source reference on plot.ly for z . The 'zsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["zsrc"] @zsrc.setter def zsrc(self, val): self["zsrc"] = val # type # ---- @property def type(self): return self._props["type"] # property parent name # -------------------- @property def _parent_path_str(self): return "" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.choropleth.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . geo Sets a reference between this trace's geospatial coordinates and a geographic map. If "geo" (the default value), the geospatial coordinates refer to `layout.geo`. If "geo2", the geospatial coordinates refer to `layout.geo2`, and so on. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.choropleth.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . locationmode Determines the set of locations used to match entries in `locations` to regions on the map. locations Sets the coordinates via location IDs or names. See `locationmode` for more info. locationssrc Sets the source reference on plot.ly for locations . marker plotly.graph_objects.choropleth.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. reversescale Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. selected plotly.graph_objects.choropleth.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.choropleth.Stream instance or dict with compatible properties text Sets the text elements associated with each location. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.choropleth.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). z Sets the color values. zauto Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. zmax Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. zmid Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. zmin Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. zsrc Sets the source reference on plot.ly for z . """ def __init__( self, arg=None, autocolorscale=None, coloraxis=None, colorbar=None, colorscale=None, customdata=None, customdatasrc=None, geo=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, locationmode=None, locations=None, locationssrc=None, marker=None, meta=None, metasrc=None, name=None, reversescale=None, selected=None, selectedpoints=None, showscale=None, stream=None, text=None, textsrc=None, uid=None, uirevision=None, unselected=None, visible=None, z=None, zauto=None, zmax=None, zmid=None, zmin=None, zsrc=None, **kwargs ): """ Construct a new Choropleth object The data that describes the choropleth value-to-color mapping is set in `z`. The geographic locations corresponding to each value in `z` are set in `locations`. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.Choropleth autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.choropleth.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . geo Sets a reference between this trace's geospatial coordinates and a geographic map. If "geo" (the default value), the geospatial coordinates refer to `layout.geo`. If "geo2", the geospatial coordinates refer to `layout.geo2`, and so on. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.choropleth.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . locationmode Determines the set of locations used to match entries in `locations` to regions on the map. locations Sets the coordinates via location IDs or names. See `locationmode` for more info. locationssrc Sets the source reference on plot.ly for locations . marker plotly.graph_objects.choropleth.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. reversescale Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. selected plotly.graph_objects.choropleth.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.choropleth.Stream instance or dict with compatible properties text Sets the text elements associated with each location. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.choropleth.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). z Sets the color values. zauto Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. zmax Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. zmid Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. zmin Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. zsrc Sets the source reference on plot.ly for z . Returns ------- Choropleth """ super(Choropleth, self).__init__("choropleth") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.Choropleth constructor must be a dict or an instance of plotly.graph_objs.Choropleth""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators import choropleth as v_choropleth # Initialize validators # --------------------- self._validators["autocolorscale"] = v_choropleth.AutocolorscaleValidator() self._validators["coloraxis"] = v_choropleth.ColoraxisValidator() self._validators["colorbar"] = v_choropleth.ColorBarValidator() self._validators["colorscale"] = v_choropleth.ColorscaleValidator() self._validators["customdata"] = v_choropleth.CustomdataValidator() self._validators["customdatasrc"] = v_choropleth.CustomdatasrcValidator() self._validators["geo"] = v_choropleth.GeoValidator() self._validators["hoverinfo"] = v_choropleth.HoverinfoValidator() self._validators["hoverinfosrc"] = v_choropleth.HoverinfosrcValidator() self._validators["hoverlabel"] = v_choropleth.HoverlabelValidator() self._validators["hovertemplate"] = v_choropleth.HovertemplateValidator() self._validators["hovertemplatesrc"] = v_choropleth.HovertemplatesrcValidator() self._validators["hovertext"] = v_choropleth.HovertextValidator() self._validators["hovertextsrc"] = v_choropleth.HovertextsrcValidator() self._validators["ids"] = v_choropleth.IdsValidator() self._validators["idssrc"] = v_choropleth.IdssrcValidator() self._validators["locationmode"] = v_choropleth.LocationmodeValidator() self._validators["locations"] = v_choropleth.LocationsValidator() self._validators["locationssrc"] = v_choropleth.LocationssrcValidator() self._validators["marker"] = v_choropleth.MarkerValidator() self._validators["meta"] = v_choropleth.MetaValidator() self._validators["metasrc"] = v_choropleth.MetasrcValidator() self._validators["name"] = v_choropleth.NameValidator() self._validators["reversescale"] = v_choropleth.ReversescaleValidator() self._validators["selected"] = v_choropleth.SelectedValidator() self._validators["selectedpoints"] = v_choropleth.SelectedpointsValidator() self._validators["showscale"] = v_choropleth.ShowscaleValidator() self._validators["stream"] = v_choropleth.StreamValidator() self._validators["text"] = v_choropleth.TextValidator() self._validators["textsrc"] = v_choropleth.TextsrcValidator() self._validators["uid"] = v_choropleth.UidValidator() self._validators["uirevision"] = v_choropleth.UirevisionValidator() self._validators["unselected"] = v_choropleth.UnselectedValidator() self._validators["visible"] = v_choropleth.VisibleValidator() self._validators["z"] = v_choropleth.ZValidator() self._validators["zauto"] = v_choropleth.ZautoValidator() self._validators["zmax"] = v_choropleth.ZmaxValidator() self._validators["zmid"] = v_choropleth.ZmidValidator() self._validators["zmin"] = v_choropleth.ZminValidator() self._validators["zsrc"] = v_choropleth.ZsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autocolorscale", None) self["autocolorscale"] = autocolorscale if autocolorscale is not None else _v _v = arg.pop("coloraxis", None) self["coloraxis"] = coloraxis if coloraxis is not None else _v _v = arg.pop("colorbar", None) self["colorbar"] = colorbar if colorbar is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("customdata", None) self["customdata"] = customdata if customdata is not None else _v _v = arg.pop("customdatasrc", None) self["customdatasrc"] = customdatasrc if customdatasrc is not None else _v _v = arg.pop("geo", None) self["geo"] = geo if geo is not None else _v _v = arg.pop("hoverinfo", None) self["hoverinfo"] = hoverinfo if hoverinfo is not None else _v _v = arg.pop("hoverinfosrc", None) self["hoverinfosrc"] = hoverinfosrc if hoverinfosrc is not None else _v _v = arg.pop("hoverlabel", None) self["hoverlabel"] = hoverlabel if hoverlabel is not None else _v _v = arg.pop("hovertemplate", None) self["hovertemplate"] = hovertemplate if hovertemplate is not None else _v _v = arg.pop("hovertemplatesrc", None) self["hovertemplatesrc"] = ( hovertemplatesrc if hovertemplatesrc is not None else _v ) _v = arg.pop("hovertext", None) self["hovertext"] = hovertext if hovertext is not None else _v _v = arg.pop("hovertextsrc", None) self["hovertextsrc"] = hovertextsrc if hovertextsrc is not None else _v _v = arg.pop("ids", None) self["ids"] = ids if ids is not None else _v _v = arg.pop("idssrc", None) self["idssrc"] = idssrc if idssrc is not None else _v _v = arg.pop("locationmode", None) self["locationmode"] = locationmode if locationmode is not None else _v _v = arg.pop("locations", None) self["locations"] = locations if locations is not None else _v _v = arg.pop("locationssrc", None) self["locationssrc"] = locationssrc if locationssrc is not None else _v _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v _v = arg.pop("meta", None) self["meta"] = meta if meta is not None else _v _v = arg.pop("metasrc", None) self["metasrc"] = metasrc if metasrc is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("reversescale", None) self["reversescale"] = reversescale if reversescale is not None else _v _v = arg.pop("selected", None) self["selected"] = selected if selected is not None else _v _v = arg.pop("selectedpoints", None) self["selectedpoints"] = selectedpoints if selectedpoints is not None else _v _v = arg.pop("showscale", None) self["showscale"] = showscale if showscale is not None else _v _v = arg.pop("stream", None) self["stream"] = stream if stream is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v _v = arg.pop("textsrc", None) self["textsrc"] = textsrc if textsrc is not None else _v _v = arg.pop("uid", None) self["uid"] = uid if uid is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("unselected", None) self["unselected"] = unselected if unselected is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("z", None) self["z"] = z if z is not None else _v _v = arg.pop("zauto", None) self["zauto"] = zauto if zauto is not None else _v _v = arg.pop("zmax", None) self["zmax"] = zmax if zmax is not None else _v _v = arg.pop("zmid", None) self["zmid"] = zmid if zmid is not None else _v _v = arg.pop("zmin", None) self["zmin"] = zmin if zmin is not None else _v _v = arg.pop("zsrc", None) self["zsrc"] = zsrc if zsrc is not None else _v # Read-only literals # ------------------ from _plotly_utils.basevalidators import LiteralValidator self._props["type"] = "choropleth" self._validators["type"] = LiteralValidator( plotly_name="type", parent_name="choropleth", val="choropleth" ) arg.pop("type", None) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceType as _BaseTraceType import copy as _copy class Carpet(_BaseTraceType): # a # - @property def a(self): """ An array containing values of the first parameter value The 'a' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["a"] @a.setter def a(self, val): self["a"] = val # a0 # -- @property def a0(self): """ Alternate to `a`. Builds a linear space of a coordinates. Use with `da` where `a0` is the starting coordinate and `da` the step. The 'a0' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["a0"] @a0.setter def a0(self, val): self["a0"] = val # aaxis # ----- @property def aaxis(self): """ The 'aaxis' property is an instance of Aaxis that may be specified as: - An instance of plotly.graph_objs.carpet.Aaxis - A dict of string/value properties that will be passed to the Aaxis constructor Supported dict properties: arraydtick The stride between grid lines along the axis arraytick0 The starting index of grid lines along the axis autorange Determines whether or not the range of this axis is computed in relation to the input data. See `rangemode` for more info. If `range` is provided, then `autorange` is set to False. categoryarray Sets the order in which categories on this axis appear. Only has an effect if `categoryorder` is set to "array". Used with `categoryorder`. categoryarraysrc Sets the source reference on plot.ly for categoryarray . categoryorder Specifies the ordering logic for the case of categorical variables. By default, plotly uses "trace", which specifies the order that is present in the data supplied. Set `categoryorder` to *category ascending* or *category descending* if order should be determined by the alphanumerical order of the category names. Set `categoryorder` to "array" to derive the ordering from the attribute `categoryarray`. If a category is not found in the `categoryarray` array, the sorting behavior for that attribute will be identical to the "trace" mode. The unspecified categories will follow the categories in `categoryarray`. cheatertype color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. dtick The stride between grid lines along the axis endline Determines whether or not a line is drawn at along the final value of this axis. If True, the end line is drawn on top of the grid lines. endlinecolor Sets the line color of the end line. endlinewidth Sets the width (in px) of the end line. exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. fixedrange Determines whether or not this axis is zoom- able. If true, then zoom is disabled. gridcolor Sets the axis line color. gridwidth Sets the width (in px) of the axis line. labelpadding Extra padding between label and the axis labelprefix Sets a axis label prefix. labelsuffix Sets a axis label suffix. linecolor Sets the axis line color. linewidth Sets the width (in px) of the axis line. minorgridcolor Sets the color of the grid lines. minorgridcount Sets the number of minor grid ticks per major grid tick minorgridwidth Sets the width (in px) of the grid lines. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". range Sets the range of this axis. If the axis `type` is "log", then you must take the log of your desired range (e.g. to set the range from 1 to 100, set the range from 0 to 2). If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. rangemode If "normal", the range is computed in relation to the extrema of the input data. If *tozero*`, the range extends to 0, regardless of the input data If "nonnegative", the range is non- negative, regardless of the input data. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showgrid Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. showline Determines whether or not a line bounding this axis is drawn. showticklabels Determines whether axis labels are drawn on the low side, the high side, both, or neither side of the axis. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. smoothing startline Determines whether or not a line is drawn at along the starting value of this axis. If True, the start line is drawn on top of the grid lines. startlinecolor Sets the line color of the start line. startlinewidth Sets the width (in px) of the start line. tick0 The starting index of grid lines along the axis tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickfont Sets the tick font. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.carpet.aaxis.Ti ckformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.carpet.aaxis.tickformatstopdefaults), sets the default property values to use for elements of carpet.aaxis.tickformatstops tickmode tickprefix Sets a tick label prefix. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . title plotly.graph_objects.carpet.aaxis.Title instance or dict with compatible properties titlefont Deprecated: Please use carpet.aaxis.title.font instead. Sets this axis' title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleoffset Deprecated: Please use carpet.aaxis.title.offset instead. An additional amount by which to offset the title from the tick labels, given in pixels. Note that this used to be set by the now deprecated `titleoffset` attribute. type Sets the axis type. By default, plotly attempts to determined the axis type by looking into the data of the traces that referenced the axis in question. Returns ------- plotly.graph_objs.carpet.Aaxis """ return self["aaxis"] @aaxis.setter def aaxis(self, val): self["aaxis"] = val # asrc # ---- @property def asrc(self): """ Sets the source reference on plot.ly for a . The 'asrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["asrc"] @asrc.setter def asrc(self, val): self["asrc"] = val # b # - @property def b(self): """ A two dimensional array of y coordinates at each carpet point. The 'b' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["b"] @b.setter def b(self, val): self["b"] = val # b0 # -- @property def b0(self): """ Alternate to `b`. Builds a linear space of a coordinates. Use with `db` where `b0` is the starting coordinate and `db` the step. The 'b0' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["b0"] @b0.setter def b0(self, val): self["b0"] = val # baxis # ----- @property def baxis(self): """ The 'baxis' property is an instance of Baxis that may be specified as: - An instance of plotly.graph_objs.carpet.Baxis - A dict of string/value properties that will be passed to the Baxis constructor Supported dict properties: arraydtick The stride between grid lines along the axis arraytick0 The starting index of grid lines along the axis autorange Determines whether or not the range of this axis is computed in relation to the input data. See `rangemode` for more info. If `range` is provided, then `autorange` is set to False. categoryarray Sets the order in which categories on this axis appear. Only has an effect if `categoryorder` is set to "array". Used with `categoryorder`. categoryarraysrc Sets the source reference on plot.ly for categoryarray . categoryorder Specifies the ordering logic for the case of categorical variables. By default, plotly uses "trace", which specifies the order that is present in the data supplied. Set `categoryorder` to *category ascending* or *category descending* if order should be determined by the alphanumerical order of the category names. Set `categoryorder` to "array" to derive the ordering from the attribute `categoryarray`. If a category is not found in the `categoryarray` array, the sorting behavior for that attribute will be identical to the "trace" mode. The unspecified categories will follow the categories in `categoryarray`. cheatertype color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. dtick The stride between grid lines along the axis endline Determines whether or not a line is drawn at along the final value of this axis. If True, the end line is drawn on top of the grid lines. endlinecolor Sets the line color of the end line. endlinewidth Sets the width (in px) of the end line. exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. fixedrange Determines whether or not this axis is zoom- able. If true, then zoom is disabled. gridcolor Sets the axis line color. gridwidth Sets the width (in px) of the axis line. labelpadding Extra padding between label and the axis labelprefix Sets a axis label prefix. labelsuffix Sets a axis label suffix. linecolor Sets the axis line color. linewidth Sets the width (in px) of the axis line. minorgridcolor Sets the color of the grid lines. minorgridcount Sets the number of minor grid ticks per major grid tick minorgridwidth Sets the width (in px) of the grid lines. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". range Sets the range of this axis. If the axis `type` is "log", then you must take the log of your desired range (e.g. to set the range from 1 to 100, set the range from 0 to 2). If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. rangemode If "normal", the range is computed in relation to the extrema of the input data. If *tozero*`, the range extends to 0, regardless of the input data If "nonnegative", the range is non- negative, regardless of the input data. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showgrid Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. showline Determines whether or not a line bounding this axis is drawn. showticklabels Determines whether axis labels are drawn on the low side, the high side, both, or neither side of the axis. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. smoothing startline Determines whether or not a line is drawn at along the starting value of this axis. If True, the start line is drawn on top of the grid lines. startlinecolor Sets the line color of the start line. startlinewidth Sets the width (in px) of the start line. tick0 The starting index of grid lines along the axis tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickfont Sets the tick font. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.carpet.baxis.Ti ckformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.carpet.baxis.tickformatstopdefaults), sets the default property values to use for elements of carpet.baxis.tickformatstops tickmode tickprefix Sets a tick label prefix. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . title plotly.graph_objects.carpet.baxis.Title instance or dict with compatible properties titlefont Deprecated: Please use carpet.baxis.title.font instead. Sets this axis' title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleoffset Deprecated: Please use carpet.baxis.title.offset instead. An additional amount by which to offset the title from the tick labels, given in pixels. Note that this used to be set by the now deprecated `titleoffset` attribute. type Sets the axis type. By default, plotly attempts to determined the axis type by looking into the data of the traces that referenced the axis in question. Returns ------- plotly.graph_objs.carpet.Baxis """ return self["baxis"] @baxis.setter def baxis(self, val): self["baxis"] = val # bsrc # ---- @property def bsrc(self): """ Sets the source reference on plot.ly for b . The 'bsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bsrc"] @bsrc.setter def bsrc(self, val): self["bsrc"] = val # carpet # ------ @property def carpet(self): """ An identifier for this carpet, so that `scattercarpet` and `contourcarpet` traces can specify a carpet plot on which they lie The 'carpet' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["carpet"] @carpet.setter def carpet(self, val): self["carpet"] = val # cheaterslope # ------------ @property def cheaterslope(self): """ The shift applied to each successive row of data in creating a cheater plot. Only used if `x` is been ommitted. The 'cheaterslope' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cheaterslope"] @cheaterslope.setter def cheaterslope(self, val): self["cheaterslope"] = val # color # ----- @property def color(self): """ Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # customdata # ---------- @property def customdata(self): """ Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements The 'customdata' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["customdata"] @customdata.setter def customdata(self, val): self["customdata"] = val # customdatasrc # ------------- @property def customdatasrc(self): """ Sets the source reference on plot.ly for customdata . The 'customdatasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["customdatasrc"] @customdatasrc.setter def customdatasrc(self, val): self["customdatasrc"] = val # da # -- @property def da(self): """ Sets the a coordinate step. See `a0` for more info. The 'da' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["da"] @da.setter def da(self, val): self["da"] = val # db # -- @property def db(self): """ Sets the b coordinate step. See `b0` for more info. The 'db' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["db"] @db.setter def db(self, val): self["db"] = val # font # ---- @property def font(self): """ The default font used for axis & tick labels on this carpet The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.carpet.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.carpet.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # ids # --- @property def ids(self): """ Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. The 'ids' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ids"] @ids.setter def ids(self, val): self["ids"] = val # idssrc # ------ @property def idssrc(self): """ Sets the source reference on plot.ly for ids . The 'idssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["idssrc"] @idssrc.setter def idssrc(self, val): self["idssrc"] = val # meta # ---- @property def meta(self): """ Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. The 'meta' property accepts values of any type Returns ------- Any|numpy.ndarray """ return self["meta"] @meta.setter def meta(self, val): self["meta"] = val # metasrc # ------- @property def metasrc(self): """ Sets the source reference on plot.ly for meta . The 'metasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["metasrc"] @metasrc.setter def metasrc(self, val): self["metasrc"] = val # name # ---- @property def name(self): """ Sets the trace name. The trace name appear as the legend item and on hover. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the trace. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # stream # ------ @property def stream(self): """ The 'stream' property is an instance of Stream that may be specified as: - An instance of plotly.graph_objs.carpet.Stream - A dict of string/value properties that will be passed to the Stream constructor Supported dict properties: maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- plotly.graph_objs.carpet.Stream """ return self["stream"] @stream.setter def stream(self, val): self["stream"] = val # uid # --- @property def uid(self): """ Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. The 'uid' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["uid"] @uid.setter def uid(self, val): self["uid"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # visible # ------- @property def visible(self): """ Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). The 'visible' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'legendonly'] Returns ------- Any """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # x # - @property def x(self): """ A two dimensional array of x coordinates at each carpet point. If ommitted, the plot is a cheater plot and the xaxis is hidden by default. The 'x' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["x"] @x.setter def x(self, val): self["x"] = val # xaxis # ----- @property def xaxis(self): """ Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. The 'xaxis' property is an identifier of a particular subplot, of type 'x', that may be specified as the string 'x' optionally followed by an integer >= 1 (e.g. 'x', 'x1', 'x2', 'x3', etc.) Returns ------- str """ return self["xaxis"] @xaxis.setter def xaxis(self, val): self["xaxis"] = val # xsrc # ---- @property def xsrc(self): """ Sets the source reference on plot.ly for x . The 'xsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["xsrc"] @xsrc.setter def xsrc(self, val): self["xsrc"] = val # y # - @property def y(self): """ A two dimensional array of y coordinates at each carpet point. The 'y' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["y"] @y.setter def y(self, val): self["y"] = val # yaxis # ----- @property def yaxis(self): """ Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. The 'yaxis' property is an identifier of a particular subplot, of type 'y', that may be specified as the string 'y' optionally followed by an integer >= 1 (e.g. 'y', 'y1', 'y2', 'y3', etc.) Returns ------- str """ return self["yaxis"] @yaxis.setter def yaxis(self, val): self["yaxis"] = val # ysrc # ---- @property def ysrc(self): """ Sets the source reference on plot.ly for y . The 'ysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ysrc"] @ysrc.setter def ysrc(self, val): self["ysrc"] = val # type # ---- @property def type(self): return self._props["type"] # property parent name # -------------------- @property def _parent_path_str(self): return "" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ a An array containing values of the first parameter value a0 Alternate to `a`. Builds a linear space of a coordinates. Use with `da` where `a0` is the starting coordinate and `da` the step. aaxis plotly.graph_objects.carpet.Aaxis instance or dict with compatible properties asrc Sets the source reference on plot.ly for a . b A two dimensional array of y coordinates at each carpet point. b0 Alternate to `b`. Builds a linear space of a coordinates. Use with `db` where `b0` is the starting coordinate and `db` the step. baxis plotly.graph_objects.carpet.Baxis instance or dict with compatible properties bsrc Sets the source reference on plot.ly for b . carpet An identifier for this carpet, so that `scattercarpet` and `contourcarpet` traces can specify a carpet plot on which they lie cheaterslope The shift applied to each successive row of data in creating a cheater plot. Only used if `x` is been ommitted. color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . da Sets the a coordinate step. See `a0` for more info. db Sets the b coordinate step. See `b0` for more info. font The default font used for axis & tick labels on this carpet ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. stream plotly.graph_objects.carpet.Stream instance or dict with compatible properties uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x A two dimensional array of x coordinates at each carpet point. If ommitted, the plot is a cheater plot and the xaxis is hidden by default. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xsrc Sets the source reference on plot.ly for x . y A two dimensional array of y coordinates at each carpet point. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ysrc Sets the source reference on plot.ly for y . """ def __init__( self, arg=None, a=None, a0=None, aaxis=None, asrc=None, b=None, b0=None, baxis=None, bsrc=None, carpet=None, cheaterslope=None, color=None, customdata=None, customdatasrc=None, da=None, db=None, font=None, ids=None, idssrc=None, meta=None, metasrc=None, name=None, opacity=None, stream=None, uid=None, uirevision=None, visible=None, x=None, xaxis=None, xsrc=None, y=None, yaxis=None, ysrc=None, **kwargs ): """ Construct a new Carpet object The data describing carpet axis layout is set in `y` and (optionally) also `x`. If only `y` is present, `x` the plot is interpreted as a cheater plot and is filled in using the `y` values. `x` and `y` may either be 2D arrays matching with each dimension matching that of `a` and `b`, or they may be 1D arrays with total length equal to that of `a` and `b`. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.Carpet a An array containing values of the first parameter value a0 Alternate to `a`. Builds a linear space of a coordinates. Use with `da` where `a0` is the starting coordinate and `da` the step. aaxis plotly.graph_objects.carpet.Aaxis instance or dict with compatible properties asrc Sets the source reference on plot.ly for a . b A two dimensional array of y coordinates at each carpet point. b0 Alternate to `b`. Builds a linear space of a coordinates. Use with `db` where `b0` is the starting coordinate and `db` the step. baxis plotly.graph_objects.carpet.Baxis instance or dict with compatible properties bsrc Sets the source reference on plot.ly for b . carpet An identifier for this carpet, so that `scattercarpet` and `contourcarpet` traces can specify a carpet plot on which they lie cheaterslope The shift applied to each successive row of data in creating a cheater plot. Only used if `x` is been ommitted. color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . da Sets the a coordinate step. See `a0` for more info. db Sets the b coordinate step. See `b0` for more info. font The default font used for axis & tick labels on this carpet ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. stream plotly.graph_objects.carpet.Stream instance or dict with compatible properties uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x A two dimensional array of x coordinates at each carpet point. If ommitted, the plot is a cheater plot and the xaxis is hidden by default. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xsrc Sets the source reference on plot.ly for x . y A two dimensional array of y coordinates at each carpet point. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ysrc Sets the source reference on plot.ly for y . Returns ------- Carpet """ super(Carpet, self).__init__("carpet") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.Carpet constructor must be a dict or an instance of plotly.graph_objs.Carpet""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators import carpet as v_carpet # Initialize validators # --------------------- self._validators["a"] = v_carpet.AValidator() self._validators["a0"] = v_carpet.A0Validator() self._validators["aaxis"] = v_carpet.AaxisValidator() self._validators["asrc"] = v_carpet.AsrcValidator() self._validators["b"] = v_carpet.BValidator() self._validators["b0"] = v_carpet.B0Validator() self._validators["baxis"] = v_carpet.BaxisValidator() self._validators["bsrc"] = v_carpet.BsrcValidator() self._validators["carpet"] = v_carpet.CarpetValidator() self._validators["cheaterslope"] = v_carpet.CheaterslopeValidator() self._validators["color"] = v_carpet.ColorValidator() self._validators["customdata"] = v_carpet.CustomdataValidator() self._validators["customdatasrc"] = v_carpet.CustomdatasrcValidator() self._validators["da"] = v_carpet.DaValidator() self._validators["db"] = v_carpet.DbValidator() self._validators["font"] = v_carpet.FontValidator() self._validators["ids"] = v_carpet.IdsValidator() self._validators["idssrc"] = v_carpet.IdssrcValidator() self._validators["meta"] = v_carpet.MetaValidator() self._validators["metasrc"] = v_carpet.MetasrcValidator() self._validators["name"] = v_carpet.NameValidator() self._validators["opacity"] = v_carpet.OpacityValidator() self._validators["stream"] = v_carpet.StreamValidator() self._validators["uid"] = v_carpet.UidValidator() self._validators["uirevision"] = v_carpet.UirevisionValidator() self._validators["visible"] = v_carpet.VisibleValidator() self._validators["x"] = v_carpet.XValidator() self._validators["xaxis"] = v_carpet.XAxisValidator() self._validators["xsrc"] = v_carpet.XsrcValidator() self._validators["y"] = v_carpet.YValidator() self._validators["yaxis"] = v_carpet.YAxisValidator() self._validators["ysrc"] = v_carpet.YsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("a", None) self["a"] = a if a is not None else _v _v = arg.pop("a0", None) self["a0"] = a0 if a0 is not None else _v _v = arg.pop("aaxis", None) self["aaxis"] = aaxis if aaxis is not None else _v _v = arg.pop("asrc", None) self["asrc"] = asrc if asrc is not None else _v _v = arg.pop("b", None) self["b"] = b if b is not None else _v _v = arg.pop("b0", None) self["b0"] = b0 if b0 is not None else _v _v = arg.pop("baxis", None) self["baxis"] = baxis if baxis is not None else _v _v = arg.pop("bsrc", None) self["bsrc"] = bsrc if bsrc is not None else _v _v = arg.pop("carpet", None) self["carpet"] = carpet if carpet is not None else _v _v = arg.pop("cheaterslope", None) self["cheaterslope"] = cheaterslope if cheaterslope is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("customdata", None) self["customdata"] = customdata if customdata is not None else _v _v = arg.pop("customdatasrc", None) self["customdatasrc"] = customdatasrc if customdatasrc is not None else _v _v = arg.pop("da", None) self["da"] = da if da is not None else _v _v = arg.pop("db", None) self["db"] = db if db is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("ids", None) self["ids"] = ids if ids is not None else _v _v = arg.pop("idssrc", None) self["idssrc"] = idssrc if idssrc is not None else _v _v = arg.pop("meta", None) self["meta"] = meta if meta is not None else _v _v = arg.pop("metasrc", None) self["metasrc"] = metasrc if metasrc is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("stream", None) self["stream"] = stream if stream is not None else _v _v = arg.pop("uid", None) self["uid"] = uid if uid is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xaxis", None) self["xaxis"] = xaxis if xaxis is not None else _v _v = arg.pop("xsrc", None) self["xsrc"] = xsrc if xsrc is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("yaxis", None) self["yaxis"] = yaxis if yaxis is not None else _v _v = arg.pop("ysrc", None) self["ysrc"] = ysrc if ysrc is not None else _v # Read-only literals # ------------------ from _plotly_utils.basevalidators import LiteralValidator self._props["type"] = "carpet" self._validators["type"] = LiteralValidator( plotly_name="type", parent_name="carpet", val="carpet" ) arg.pop("type", None) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceType as _BaseTraceType import copy as _copy class Candlestick(_BaseTraceType): # close # ----- @property def close(self): """ Sets the close values. The 'close' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["close"] @close.setter def close(self, val): self["close"] = val # closesrc # -------- @property def closesrc(self): """ Sets the source reference on plot.ly for close . The 'closesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["closesrc"] @closesrc.setter def closesrc(self, val): self["closesrc"] = val # customdata # ---------- @property def customdata(self): """ Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements The 'customdata' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["customdata"] @customdata.setter def customdata(self, val): self["customdata"] = val # customdatasrc # ------------- @property def customdatasrc(self): """ Sets the source reference on plot.ly for customdata . The 'customdatasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["customdatasrc"] @customdatasrc.setter def customdatasrc(self, val): self["customdatasrc"] = val # decreasing # ---------- @property def decreasing(self): """ The 'decreasing' property is an instance of Decreasing that may be specified as: - An instance of plotly.graph_objs.candlestick.Decreasing - A dict of string/value properties that will be passed to the Decreasing constructor Supported dict properties: fillcolor Sets the fill color. Defaults to a half- transparent variant of the line color, marker color, or marker line color, whichever is available. line plotly.graph_objects.candlestick.decreasing.Lin e instance or dict with compatible properties Returns ------- plotly.graph_objs.candlestick.Decreasing """ return self["decreasing"] @decreasing.setter def decreasing(self, val): self["decreasing"] = val # high # ---- @property def high(self): """ Sets the high values. The 'high' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["high"] @high.setter def high(self, val): self["high"] = val # highsrc # ------- @property def highsrc(self): """ Sets the source reference on plot.ly for high . The 'highsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["highsrc"] @highsrc.setter def highsrc(self, val): self["highsrc"] = val # hoverinfo # --------- @property def hoverinfo(self): """ Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. The 'hoverinfo' property is a flaglist and may be specified as a string containing: - Any combination of ['x', 'y', 'z', 'text', 'name'] joined with '+' characters (e.g. 'x+y') OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') - A list or array of the above Returns ------- Any|numpy.ndarray """ return self["hoverinfo"] @hoverinfo.setter def hoverinfo(self, val): self["hoverinfo"] = val # hoverinfosrc # ------------ @property def hoverinfosrc(self): """ Sets the source reference on plot.ly for hoverinfo . The 'hoverinfosrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hoverinfosrc"] @hoverinfosrc.setter def hoverinfosrc(self, val): self["hoverinfosrc"] = val # hoverlabel # ---------- @property def hoverlabel(self): """ The 'hoverlabel' property is an instance of Hoverlabel that may be specified as: - An instance of plotly.graph_objs.candlestick.Hoverlabel - A dict of string/value properties that will be passed to the Hoverlabel constructor Supported dict properties: align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . split Show hover information (open, close, high, low) in separate labels. Returns ------- plotly.graph_objs.candlestick.Hoverlabel """ return self["hoverlabel"] @hoverlabel.setter def hoverlabel(self, val): self["hoverlabel"] = val # hovertext # --------- @property def hovertext(self): """ Same as `text`. The 'hovertext' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertext"] @hovertext.setter def hovertext(self, val): self["hovertext"] = val # hovertextsrc # ------------ @property def hovertextsrc(self): """ Sets the source reference on plot.ly for hovertext . The 'hovertextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertextsrc"] @hovertextsrc.setter def hovertextsrc(self, val): self["hovertextsrc"] = val # ids # --- @property def ids(self): """ Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. The 'ids' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ids"] @ids.setter def ids(self, val): self["ids"] = val # idssrc # ------ @property def idssrc(self): """ Sets the source reference on plot.ly for ids . The 'idssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["idssrc"] @idssrc.setter def idssrc(self, val): self["idssrc"] = val # increasing # ---------- @property def increasing(self): """ The 'increasing' property is an instance of Increasing that may be specified as: - An instance of plotly.graph_objs.candlestick.Increasing - A dict of string/value properties that will be passed to the Increasing constructor Supported dict properties: fillcolor Sets the fill color. Defaults to a half- transparent variant of the line color, marker color, or marker line color, whichever is available. line plotly.graph_objects.candlestick.increasing.Lin e instance or dict with compatible properties Returns ------- plotly.graph_objs.candlestick.Increasing """ return self["increasing"] @increasing.setter def increasing(self, val): self["increasing"] = val # legendgroup # ----------- @property def legendgroup(self): """ Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. The 'legendgroup' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["legendgroup"] @legendgroup.setter def legendgroup(self, val): self["legendgroup"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.candlestick.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: width Sets the width (in px) of line bounding the box(es). Note that this style setting can also be set per direction via `increasing.line.width` and `decreasing.line.width`. Returns ------- plotly.graph_objs.candlestick.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # low # --- @property def low(self): """ Sets the low values. The 'low' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["low"] @low.setter def low(self, val): self["low"] = val # lowsrc # ------ @property def lowsrc(self): """ Sets the source reference on plot.ly for low . The 'lowsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["lowsrc"] @lowsrc.setter def lowsrc(self, val): self["lowsrc"] = val # meta # ---- @property def meta(self): """ Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. The 'meta' property accepts values of any type Returns ------- Any|numpy.ndarray """ return self["meta"] @meta.setter def meta(self, val): self["meta"] = val # metasrc # ------- @property def metasrc(self): """ Sets the source reference on plot.ly for meta . The 'metasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["metasrc"] @metasrc.setter def metasrc(self, val): self["metasrc"] = val # name # ---- @property def name(self): """ Sets the trace name. The trace name appear as the legend item and on hover. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the trace. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # open # ---- @property def open(self): """ Sets the open values. The 'open' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["open"] @open.setter def open(self, val): self["open"] = val # opensrc # ------- @property def opensrc(self): """ Sets the source reference on plot.ly for open . The 'opensrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["opensrc"] @opensrc.setter def opensrc(self, val): self["opensrc"] = val # selectedpoints # -------------- @property def selectedpoints(self): """ Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. The 'selectedpoints' property accepts values of any type Returns ------- Any """ return self["selectedpoints"] @selectedpoints.setter def selectedpoints(self, val): self["selectedpoints"] = val # showlegend # ---------- @property def showlegend(self): """ Determines whether or not an item corresponding to this trace is shown in the legend. The 'showlegend' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showlegend"] @showlegend.setter def showlegend(self, val): self["showlegend"] = val # stream # ------ @property def stream(self): """ The 'stream' property is an instance of Stream that may be specified as: - An instance of plotly.graph_objs.candlestick.Stream - A dict of string/value properties that will be passed to the Stream constructor Supported dict properties: maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- plotly.graph_objs.candlestick.Stream """ return self["stream"] @stream.setter def stream(self, val): self["stream"] = val # text # ---- @property def text(self): """ Sets hover text elements associated with each sample point. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to this trace's sample points. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["text"] @text.setter def text(self, val): self["text"] = val # textsrc # ------- @property def textsrc(self): """ Sets the source reference on plot.ly for text . The 'textsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["textsrc"] @textsrc.setter def textsrc(self, val): self["textsrc"] = val # uid # --- @property def uid(self): """ Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. The 'uid' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["uid"] @uid.setter def uid(self, val): self["uid"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # visible # ------- @property def visible(self): """ Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). The 'visible' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'legendonly'] Returns ------- Any """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # whiskerwidth # ------------ @property def whiskerwidth(self): """ Sets the width of the whiskers relative to the box' width. For example, with 1, the whiskers are as wide as the box(es). The 'whiskerwidth' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["whiskerwidth"] @whiskerwidth.setter def whiskerwidth(self, val): self["whiskerwidth"] = val # x # - @property def x(self): """ Sets the x coordinates. If absent, linear coordinate will be generated. The 'x' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["x"] @x.setter def x(self, val): self["x"] = val # xaxis # ----- @property def xaxis(self): """ Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. The 'xaxis' property is an identifier of a particular subplot, of type 'x', that may be specified as the string 'x' optionally followed by an integer >= 1 (e.g. 'x', 'x1', 'x2', 'x3', etc.) Returns ------- str """ return self["xaxis"] @xaxis.setter def xaxis(self, val): self["xaxis"] = val # xcalendar # --------- @property def xcalendar(self): """ Sets the calendar system to use with `x` date data. The 'xcalendar' property is an enumeration that may be specified as: - One of the following enumeration values: ['gregorian', 'chinese', 'coptic', 'discworld', 'ethiopian', 'hebrew', 'islamic', 'julian', 'mayan', 'nanakshahi', 'nepali', 'persian', 'jalali', 'taiwan', 'thai', 'ummalqura'] Returns ------- Any """ return self["xcalendar"] @xcalendar.setter def xcalendar(self, val): self["xcalendar"] = val # xsrc # ---- @property def xsrc(self): """ Sets the source reference on plot.ly for x . The 'xsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["xsrc"] @xsrc.setter def xsrc(self, val): self["xsrc"] = val # yaxis # ----- @property def yaxis(self): """ Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. The 'yaxis' property is an identifier of a particular subplot, of type 'y', that may be specified as the string 'y' optionally followed by an integer >= 1 (e.g. 'y', 'y1', 'y2', 'y3', etc.) Returns ------- str """ return self["yaxis"] @yaxis.setter def yaxis(self, val): self["yaxis"] = val # type # ---- @property def type(self): return self._props["type"] # property parent name # -------------------- @property def _parent_path_str(self): return "" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ close Sets the close values. closesrc Sets the source reference on plot.ly for close . customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . decreasing plotly.graph_objects.candlestick.Decreasing instance or dict with compatible properties high Sets the high values. highsrc Sets the source reference on plot.ly for high . hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.candlestick.Hoverlabel instance or dict with compatible properties hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . increasing plotly.graph_objects.candlestick.Increasing instance or dict with compatible properties legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.candlestick.Line instance or dict with compatible properties low Sets the low values. lowsrc Sets the source reference on plot.ly for low . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. open Sets the open values. opensrc Sets the source reference on plot.ly for open . selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.candlestick.Stream instance or dict with compatible properties text Sets hover text elements associated with each sample point. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to this trace's sample points. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). whiskerwidth Sets the width of the whiskers relative to the box' width. For example, with 1, the whiskers are as wide as the box(es). x Sets the x coordinates. If absent, linear coordinate will be generated. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. """ def __init__( self, arg=None, close=None, closesrc=None, customdata=None, customdatasrc=None, decreasing=None, high=None, highsrc=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, increasing=None, legendgroup=None, line=None, low=None, lowsrc=None, meta=None, metasrc=None, name=None, opacity=None, open=None, opensrc=None, selectedpoints=None, showlegend=None, stream=None, text=None, textsrc=None, uid=None, uirevision=None, visible=None, whiskerwidth=None, x=None, xaxis=None, xcalendar=None, xsrc=None, yaxis=None, **kwargs ): """ Construct a new Candlestick object The candlestick is a style of financial chart describing open, high, low and close for a given `x` coordinate (most likely time). The boxes represent the spread between the `open` and `close` values and the lines represent the spread between the `low` and `high` values Sample points where the close value is higher (lower) then the open value are called increasing (decreasing). By default, increasing candles are drawn in green whereas decreasing are drawn in red. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.Candlestick close Sets the close values. closesrc Sets the source reference on plot.ly for close . customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . decreasing plotly.graph_objects.candlestick.Decreasing instance or dict with compatible properties high Sets the high values. highsrc Sets the source reference on plot.ly for high . hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.candlestick.Hoverlabel instance or dict with compatible properties hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . increasing plotly.graph_objects.candlestick.Increasing instance or dict with compatible properties legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.candlestick.Line instance or dict with compatible properties low Sets the low values. lowsrc Sets the source reference on plot.ly for low . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. open Sets the open values. opensrc Sets the source reference on plot.ly for open . selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.candlestick.Stream instance or dict with compatible properties text Sets hover text elements associated with each sample point. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to this trace's sample points. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). whiskerwidth Sets the width of the whiskers relative to the box' width. For example, with 1, the whiskers are as wide as the box(es). x Sets the x coordinates. If absent, linear coordinate will be generated. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. Returns ------- Candlestick """ super(Candlestick, self).__init__("candlestick") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.Candlestick constructor must be a dict or an instance of plotly.graph_objs.Candlestick""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators import candlestick as v_candlestick # Initialize validators # --------------------- self._validators["close"] = v_candlestick.CloseValidator() self._validators["closesrc"] = v_candlestick.ClosesrcValidator() self._validators["customdata"] = v_candlestick.CustomdataValidator() self._validators["customdatasrc"] = v_candlestick.CustomdatasrcValidator() self._validators["decreasing"] = v_candlestick.DecreasingValidator() self._validators["high"] = v_candlestick.HighValidator() self._validators["highsrc"] = v_candlestick.HighsrcValidator() self._validators["hoverinfo"] = v_candlestick.HoverinfoValidator() self._validators["hoverinfosrc"] = v_candlestick.HoverinfosrcValidator() self._validators["hoverlabel"] = v_candlestick.HoverlabelValidator() self._validators["hovertext"] = v_candlestick.HovertextValidator() self._validators["hovertextsrc"] = v_candlestick.HovertextsrcValidator() self._validators["ids"] = v_candlestick.IdsValidator() self._validators["idssrc"] = v_candlestick.IdssrcValidator() self._validators["increasing"] = v_candlestick.IncreasingValidator() self._validators["legendgroup"] = v_candlestick.LegendgroupValidator() self._validators["line"] = v_candlestick.LineValidator() self._validators["low"] = v_candlestick.LowValidator() self._validators["lowsrc"] = v_candlestick.LowsrcValidator() self._validators["meta"] = v_candlestick.MetaValidator() self._validators["metasrc"] = v_candlestick.MetasrcValidator() self._validators["name"] = v_candlestick.NameValidator() self._validators["opacity"] = v_candlestick.OpacityValidator() self._validators["open"] = v_candlestick.OpenValidator() self._validators["opensrc"] = v_candlestick.OpensrcValidator() self._validators["selectedpoints"] = v_candlestick.SelectedpointsValidator() self._validators["showlegend"] = v_candlestick.ShowlegendValidator() self._validators["stream"] = v_candlestick.StreamValidator() self._validators["text"] = v_candlestick.TextValidator() self._validators["textsrc"] = v_candlestick.TextsrcValidator() self._validators["uid"] = v_candlestick.UidValidator() self._validators["uirevision"] = v_candlestick.UirevisionValidator() self._validators["visible"] = v_candlestick.VisibleValidator() self._validators["whiskerwidth"] = v_candlestick.WhiskerwidthValidator() self._validators["x"] = v_candlestick.XValidator() self._validators["xaxis"] = v_candlestick.XAxisValidator() self._validators["xcalendar"] = v_candlestick.XcalendarValidator() self._validators["xsrc"] = v_candlestick.XsrcValidator() self._validators["yaxis"] = v_candlestick.YAxisValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("close", None) self["close"] = close if close is not None else _v _v = arg.pop("closesrc", None) self["closesrc"] = closesrc if closesrc is not None else _v _v = arg.pop("customdata", None) self["customdata"] = customdata if customdata is not None else _v _v = arg.pop("customdatasrc", None) self["customdatasrc"] = customdatasrc if customdatasrc is not None else _v _v = arg.pop("decreasing", None) self["decreasing"] = decreasing if decreasing is not None else _v _v = arg.pop("high", None) self["high"] = high if high is not None else _v _v = arg.pop("highsrc", None) self["highsrc"] = highsrc if highsrc is not None else _v _v = arg.pop("hoverinfo", None) self["hoverinfo"] = hoverinfo if hoverinfo is not None else _v _v = arg.pop("hoverinfosrc", None) self["hoverinfosrc"] = hoverinfosrc if hoverinfosrc is not None else _v _v = arg.pop("hoverlabel", None) self["hoverlabel"] = hoverlabel if hoverlabel is not None else _v _v = arg.pop("hovertext", None) self["hovertext"] = hovertext if hovertext is not None else _v _v = arg.pop("hovertextsrc", None) self["hovertextsrc"] = hovertextsrc if hovertextsrc is not None else _v _v = arg.pop("ids", None) self["ids"] = ids if ids is not None else _v _v = arg.pop("idssrc", None) self["idssrc"] = idssrc if idssrc is not None else _v _v = arg.pop("increasing", None) self["increasing"] = increasing if increasing is not None else _v _v = arg.pop("legendgroup", None) self["legendgroup"] = legendgroup if legendgroup is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v _v = arg.pop("low", None) self["low"] = low if low is not None else _v _v = arg.pop("lowsrc", None) self["lowsrc"] = lowsrc if lowsrc is not None else _v _v = arg.pop("meta", None) self["meta"] = meta if meta is not None else _v _v = arg.pop("metasrc", None) self["metasrc"] = metasrc if metasrc is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("open", None) self["open"] = open if open is not None else _v _v = arg.pop("opensrc", None) self["opensrc"] = opensrc if opensrc is not None else _v _v = arg.pop("selectedpoints", None) self["selectedpoints"] = selectedpoints if selectedpoints is not None else _v _v = arg.pop("showlegend", None) self["showlegend"] = showlegend if showlegend is not None else _v _v = arg.pop("stream", None) self["stream"] = stream if stream is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v _v = arg.pop("textsrc", None) self["textsrc"] = textsrc if textsrc is not None else _v _v = arg.pop("uid", None) self["uid"] = uid if uid is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("whiskerwidth", None) self["whiskerwidth"] = whiskerwidth if whiskerwidth is not None else _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xaxis", None) self["xaxis"] = xaxis if xaxis is not None else _v _v = arg.pop("xcalendar", None) self["xcalendar"] = xcalendar if xcalendar is not None else _v _v = arg.pop("xsrc", None) self["xsrc"] = xsrc if xsrc is not None else _v _v = arg.pop("yaxis", None) self["yaxis"] = yaxis if yaxis is not None else _v # Read-only literals # ------------------ from _plotly_utils.basevalidators import LiteralValidator self._props["type"] = "candlestick" self._validators["type"] = LiteralValidator( plotly_name="type", parent_name="candlestick", val="candlestick" ) arg.pop("type", None) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceType as _BaseTraceType import copy as _copy class Box(_BaseTraceType): # alignmentgroup # -------------- @property def alignmentgroup(self): """ Set several traces linked to the same position axis or matching axes to the same alignmentgroup. This controls whether bars compute their positional range dependently or independently. The 'alignmentgroup' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["alignmentgroup"] @alignmentgroup.setter def alignmentgroup(self, val): self["alignmentgroup"] = val # boxmean # ------- @property def boxmean(self): """ If True, the mean of the box(es)' underlying distribution is drawn as a dashed line inside the box(es). If "sd" the standard deviation is also drawn. The 'boxmean' property is an enumeration that may be specified as: - One of the following enumeration values: [True, 'sd', False] Returns ------- Any """ return self["boxmean"] @boxmean.setter def boxmean(self, val): self["boxmean"] = val # boxpoints # --------- @property def boxpoints(self): """ If "outliers", only the sample points lying outside the whiskers are shown If "suspectedoutliers", the outlier points are shown and points either less than 4*Q1-3*Q3 or greater than 4*Q3-3*Q1 are highlighted (see `outliercolor`) If "all", all sample points are shown If False, only the box(es) are shown with no sample points The 'boxpoints' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'outliers', 'suspectedoutliers', False] Returns ------- Any """ return self["boxpoints"] @boxpoints.setter def boxpoints(self, val): self["boxpoints"] = val # customdata # ---------- @property def customdata(self): """ Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements The 'customdata' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["customdata"] @customdata.setter def customdata(self, val): self["customdata"] = val # customdatasrc # ------------- @property def customdatasrc(self): """ Sets the source reference on plot.ly for customdata . The 'customdatasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["customdatasrc"] @customdatasrc.setter def customdatasrc(self, val): self["customdatasrc"] = val # fillcolor # --------- @property def fillcolor(self): """ Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. The 'fillcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["fillcolor"] @fillcolor.setter def fillcolor(self, val): self["fillcolor"] = val # hoverinfo # --------- @property def hoverinfo(self): """ Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. The 'hoverinfo' property is a flaglist and may be specified as a string containing: - Any combination of ['x', 'y', 'z', 'text', 'name'] joined with '+' characters (e.g. 'x+y') OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') - A list or array of the above Returns ------- Any|numpy.ndarray """ return self["hoverinfo"] @hoverinfo.setter def hoverinfo(self, val): self["hoverinfo"] = val # hoverinfosrc # ------------ @property def hoverinfosrc(self): """ Sets the source reference on plot.ly for hoverinfo . The 'hoverinfosrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hoverinfosrc"] @hoverinfosrc.setter def hoverinfosrc(self, val): self["hoverinfosrc"] = val # hoverlabel # ---------- @property def hoverlabel(self): """ The 'hoverlabel' property is an instance of Hoverlabel that may be specified as: - An instance of plotly.graph_objs.box.Hoverlabel - A dict of string/value properties that will be passed to the Hoverlabel constructor Supported dict properties: align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- plotly.graph_objs.box.Hoverlabel """ return self["hoverlabel"] @hoverlabel.setter def hoverlabel(self, val): self["hoverlabel"] = val # hoveron # ------- @property def hoveron(self): """ Do the hover effects highlight individual boxes or sample points or both? The 'hoveron' property is a flaglist and may be specified as a string containing: - Any combination of ['boxes', 'points'] joined with '+' characters (e.g. 'boxes+points') Returns ------- Any """ return self["hoveron"] @hoveron.setter def hoveron(self, val): self["hoveron"] = val # hovertemplate # ------------- @property def hovertemplate(self): """ Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event- data. Additionally, every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. The 'hovertemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertemplate"] @hovertemplate.setter def hovertemplate(self, val): self["hovertemplate"] = val # hovertemplatesrc # ---------------- @property def hovertemplatesrc(self): """ Sets the source reference on plot.ly for hovertemplate . The 'hovertemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertemplatesrc"] @hovertemplatesrc.setter def hovertemplatesrc(self, val): self["hovertemplatesrc"] = val # hovertext # --------- @property def hovertext(self): """ Same as `text`. The 'hovertext' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertext"] @hovertext.setter def hovertext(self, val): self["hovertext"] = val # hovertextsrc # ------------ @property def hovertextsrc(self): """ Sets the source reference on plot.ly for hovertext . The 'hovertextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertextsrc"] @hovertextsrc.setter def hovertextsrc(self, val): self["hovertextsrc"] = val # ids # --- @property def ids(self): """ Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. The 'ids' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ids"] @ids.setter def ids(self, val): self["ids"] = val # idssrc # ------ @property def idssrc(self): """ Sets the source reference on plot.ly for ids . The 'idssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["idssrc"] @idssrc.setter def idssrc(self, val): self["idssrc"] = val # jitter # ------ @property def jitter(self): """ Sets the amount of jitter in the sample points drawn. If 0, the sample points align along the distribution axis. If 1, the sample points are drawn in a random jitter of width equal to the width of the box(es). The 'jitter' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["jitter"] @jitter.setter def jitter(self, val): self["jitter"] = val # legendgroup # ----------- @property def legendgroup(self): """ Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. The 'legendgroup' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["legendgroup"] @legendgroup.setter def legendgroup(self, val): self["legendgroup"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.box.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: color Sets the color of line bounding the box(es). width Sets the width (in px) of line bounding the box(es). Returns ------- plotly.graph_objs.box.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.box.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. line plotly.graph_objects.box.marker.Line instance or dict with compatible properties opacity Sets the marker opacity. outliercolor Sets the color of the outlier sample points. size Sets the marker size (in px). symbol Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot- open" to a symbol name. Returns ------- plotly.graph_objs.box.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # meta # ---- @property def meta(self): """ Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. The 'meta' property accepts values of any type Returns ------- Any|numpy.ndarray """ return self["meta"] @meta.setter def meta(self, val): self["meta"] = val # metasrc # ------- @property def metasrc(self): """ Sets the source reference on plot.ly for meta . The 'metasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["metasrc"] @metasrc.setter def metasrc(self, val): self["metasrc"] = val # name # ---- @property def name(self): """ Sets the trace name. The trace name appear as the legend item and on hover. For box traces, the name will also be used for the position coordinate, if `x` and `x0` (`y` and `y0` if horizontal) are missing and the position axis is categorical The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # notched # ------- @property def notched(self): """ Determines whether or not notches should be drawn. The 'notched' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["notched"] @notched.setter def notched(self, val): self["notched"] = val # notchwidth # ---------- @property def notchwidth(self): """ Sets the width of the notches relative to the box' width. For example, with 0, the notches are as wide as the box(es). The 'notchwidth' property is a number and may be specified as: - An int or float in the interval [0, 0.5] Returns ------- int|float """ return self["notchwidth"] @notchwidth.setter def notchwidth(self, val): self["notchwidth"] = val # offsetgroup # ----------- @property def offsetgroup(self): """ Set several traces linked to the same position axis or matching axes to the same offsetgroup where bars of the same position coordinate will line up. The 'offsetgroup' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["offsetgroup"] @offsetgroup.setter def offsetgroup(self, val): self["offsetgroup"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the trace. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # orientation # ----------- @property def orientation(self): """ Sets the orientation of the box(es). If "v" ("h"), the distribution is visualized along the vertical (horizontal). The 'orientation' property is an enumeration that may be specified as: - One of the following enumeration values: ['v', 'h'] Returns ------- Any """ return self["orientation"] @orientation.setter def orientation(self, val): self["orientation"] = val # pointpos # -------- @property def pointpos(self): """ Sets the position of the sample points in relation to the box(es). If 0, the sample points are places over the center of the box(es). Positive (negative) values correspond to positions to the right (left) for vertical boxes and above (below) for horizontal boxes The 'pointpos' property is a number and may be specified as: - An int or float in the interval [-2, 2] Returns ------- int|float """ return self["pointpos"] @pointpos.setter def pointpos(self, val): self["pointpos"] = val # selected # -------- @property def selected(self): """ The 'selected' property is an instance of Selected that may be specified as: - An instance of plotly.graph_objs.box.Selected - A dict of string/value properties that will be passed to the Selected constructor Supported dict properties: marker plotly.graph_objects.box.selected.Marker instance or dict with compatible properties Returns ------- plotly.graph_objs.box.Selected """ return self["selected"] @selected.setter def selected(self, val): self["selected"] = val # selectedpoints # -------------- @property def selectedpoints(self): """ Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. The 'selectedpoints' property accepts values of any type Returns ------- Any """ return self["selectedpoints"] @selectedpoints.setter def selectedpoints(self, val): self["selectedpoints"] = val # showlegend # ---------- @property def showlegend(self): """ Determines whether or not an item corresponding to this trace is shown in the legend. The 'showlegend' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showlegend"] @showlegend.setter def showlegend(self, val): self["showlegend"] = val # stream # ------ @property def stream(self): """ The 'stream' property is an instance of Stream that may be specified as: - An instance of plotly.graph_objs.box.Stream - A dict of string/value properties that will be passed to the Stream constructor Supported dict properties: maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- plotly.graph_objs.box.Stream """ return self["stream"] @stream.setter def stream(self, val): self["stream"] = val # text # ---- @property def text(self): """ Sets the text elements associated with each sample value. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["text"] @text.setter def text(self, val): self["text"] = val # textsrc # ------- @property def textsrc(self): """ Sets the source reference on plot.ly for text . The 'textsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["textsrc"] @textsrc.setter def textsrc(self, val): self["textsrc"] = val # uid # --- @property def uid(self): """ Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. The 'uid' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["uid"] @uid.setter def uid(self, val): self["uid"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # unselected # ---------- @property def unselected(self): """ The 'unselected' property is an instance of Unselected that may be specified as: - An instance of plotly.graph_objs.box.Unselected - A dict of string/value properties that will be passed to the Unselected constructor Supported dict properties: marker plotly.graph_objects.box.unselected.Marker instance or dict with compatible properties Returns ------- plotly.graph_objs.box.Unselected """ return self["unselected"] @unselected.setter def unselected(self, val): self["unselected"] = val # visible # ------- @property def visible(self): """ Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). The 'visible' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'legendonly'] Returns ------- Any """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # whiskerwidth # ------------ @property def whiskerwidth(self): """ Sets the width of the whiskers relative to the box' width. For example, with 1, the whiskers are as wide as the box(es). The 'whiskerwidth' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["whiskerwidth"] @whiskerwidth.setter def whiskerwidth(self, val): self["whiskerwidth"] = val # width # ----- @property def width(self): """ Sets the width of the box in data coordinate If 0 (default value) the width is automatically selected based on the positions of other box traces in the same subplot. The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # x # - @property def x(self): """ Sets the x sample data or coordinates. See overview for more info. The 'x' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["x"] @x.setter def x(self, val): self["x"] = val # x0 # -- @property def x0(self): """ Sets the x coordinate of the box. See overview for more info. The 'x0' property accepts values of any type Returns ------- Any """ return self["x0"] @x0.setter def x0(self, val): self["x0"] = val # xaxis # ----- @property def xaxis(self): """ Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. The 'xaxis' property is an identifier of a particular subplot, of type 'x', that may be specified as the string 'x' optionally followed by an integer >= 1 (e.g. 'x', 'x1', 'x2', 'x3', etc.) Returns ------- str """ return self["xaxis"] @xaxis.setter def xaxis(self, val): self["xaxis"] = val # xcalendar # --------- @property def xcalendar(self): """ Sets the calendar system to use with `x` date data. The 'xcalendar' property is an enumeration that may be specified as: - One of the following enumeration values: ['gregorian', 'chinese', 'coptic', 'discworld', 'ethiopian', 'hebrew', 'islamic', 'julian', 'mayan', 'nanakshahi', 'nepali', 'persian', 'jalali', 'taiwan', 'thai', 'ummalqura'] Returns ------- Any """ return self["xcalendar"] @xcalendar.setter def xcalendar(self, val): self["xcalendar"] = val # xsrc # ---- @property def xsrc(self): """ Sets the source reference on plot.ly for x . The 'xsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["xsrc"] @xsrc.setter def xsrc(self, val): self["xsrc"] = val # y # - @property def y(self): """ Sets the y sample data or coordinates. See overview for more info. The 'y' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["y"] @y.setter def y(self, val): self["y"] = val # y0 # -- @property def y0(self): """ Sets the y coordinate of the box. See overview for more info. The 'y0' property accepts values of any type Returns ------- Any """ return self["y0"] @y0.setter def y0(self, val): self["y0"] = val # yaxis # ----- @property def yaxis(self): """ Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. The 'yaxis' property is an identifier of a particular subplot, of type 'y', that may be specified as the string 'y' optionally followed by an integer >= 1 (e.g. 'y', 'y1', 'y2', 'y3', etc.) Returns ------- str """ return self["yaxis"] @yaxis.setter def yaxis(self, val): self["yaxis"] = val # ycalendar # --------- @property def ycalendar(self): """ Sets the calendar system to use with `y` date data. The 'ycalendar' property is an enumeration that may be specified as: - One of the following enumeration values: ['gregorian', 'chinese', 'coptic', 'discworld', 'ethiopian', 'hebrew', 'islamic', 'julian', 'mayan', 'nanakshahi', 'nepali', 'persian', 'jalali', 'taiwan', 'thai', 'ummalqura'] Returns ------- Any """ return self["ycalendar"] @ycalendar.setter def ycalendar(self, val): self["ycalendar"] = val # ysrc # ---- @property def ysrc(self): """ Sets the source reference on plot.ly for y . The 'ysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ysrc"] @ysrc.setter def ysrc(self, val): self["ysrc"] = val # type # ---- @property def type(self): return self._props["type"] # property parent name # -------------------- @property def _parent_path_str(self): return "" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ alignmentgroup Set several traces linked to the same position axis or matching axes to the same alignmentgroup. This controls whether bars compute their positional range dependently or independently. boxmean If True, the mean of the box(es)' underlying distribution is drawn as a dashed line inside the box(es). If "sd" the standard deviation is also drawn. boxpoints If "outliers", only the sample points lying outside the whiskers are shown If "suspectedoutliers", the outlier points are shown and points either less than 4*Q1-3*Q3 or greater than 4*Q3-3*Q1 are highlighted (see `outliercolor`) If "all", all sample points are shown If False, only the box(es) are shown with no sample points customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . fillcolor Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.box.Hoverlabel instance or dict with compatible properties hoveron Do the hover effects highlight individual boxes or sample points or both? hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . jitter Sets the amount of jitter in the sample points drawn. If 0, the sample points align along the distribution axis. If 1, the sample points are drawn in a random jitter of width equal to the width of the box(es). legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.box.Line instance or dict with compatible properties marker plotly.graph_objects.box.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. For box traces, the name will also be used for the position coordinate, if `x` and `x0` (`y` and `y0` if horizontal) are missing and the position axis is categorical notched Determines whether or not notches should be drawn. notchwidth Sets the width of the notches relative to the box' width. For example, with 0, the notches are as wide as the box(es). offsetgroup Set several traces linked to the same position axis or matching axes to the same offsetgroup where bars of the same position coordinate will line up. opacity Sets the opacity of the trace. orientation Sets the orientation of the box(es). If "v" ("h"), the distribution is visualized along the vertical (horizontal). pointpos Sets the position of the sample points in relation to the box(es). If 0, the sample points are places over the center of the box(es). Positive (negative) values correspond to positions to the right (left) for vertical boxes and above (below) for horizontal boxes selected plotly.graph_objects.box.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.box.Stream instance or dict with compatible properties text Sets the text elements associated with each sample value. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.box.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). whiskerwidth Sets the width of the whiskers relative to the box' width. For example, with 1, the whiskers are as wide as the box(es). width Sets the width of the box in data coordinate If 0 (default value) the width is automatically selected based on the positions of other box traces in the same subplot. x Sets the x sample data or coordinates. See overview for more info. x0 Sets the x coordinate of the box. See overview for more info. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . y Sets the y sample data or coordinates. See overview for more info. y0 Sets the y coordinate of the box. See overview for more info. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . """ def __init__( self, arg=None, alignmentgroup=None, boxmean=None, boxpoints=None, customdata=None, customdatasrc=None, fillcolor=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hoveron=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, jitter=None, legendgroup=None, line=None, marker=None, meta=None, metasrc=None, name=None, notched=None, notchwidth=None, offsetgroup=None, opacity=None, orientation=None, pointpos=None, selected=None, selectedpoints=None, showlegend=None, stream=None, text=None, textsrc=None, uid=None, uirevision=None, unselected=None, visible=None, whiskerwidth=None, width=None, x=None, x0=None, xaxis=None, xcalendar=None, xsrc=None, y=None, y0=None, yaxis=None, ycalendar=None, ysrc=None, **kwargs ): """ Construct a new Box object In vertical (horizontal) box plots, statistics are computed using `y` (`x`) values. By supplying an `x` (`y`) array, one box per distinct x (y) value is drawn If no `x` (`y`) list is provided, a single box is drawn. That box position is then positioned with with `name` or with `x0` (`y0`) if provided. Each box spans from quartile 1 (Q1) to quartile 3 (Q3). The second quartile (Q2) is marked by a line inside the box. By default, the whiskers correspond to the box' edges +/- 1.5 times the interquartile range (IQR: Q3-Q1), see "boxpoints" for other options. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.Box alignmentgroup Set several traces linked to the same position axis or matching axes to the same alignmentgroup. This controls whether bars compute their positional range dependently or independently. boxmean If True, the mean of the box(es)' underlying distribution is drawn as a dashed line inside the box(es). If "sd" the standard deviation is also drawn. boxpoints If "outliers", only the sample points lying outside the whiskers are shown If "suspectedoutliers", the outlier points are shown and points either less than 4*Q1-3*Q3 or greater than 4*Q3-3*Q1 are highlighted (see `outliercolor`) If "all", all sample points are shown If False, only the box(es) are shown with no sample points customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . fillcolor Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.box.Hoverlabel instance or dict with compatible properties hoveron Do the hover effects highlight individual boxes or sample points or both? hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . jitter Sets the amount of jitter in the sample points drawn. If 0, the sample points align along the distribution axis. If 1, the sample points are drawn in a random jitter of width equal to the width of the box(es). legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.box.Line instance or dict with compatible properties marker plotly.graph_objects.box.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. For box traces, the name will also be used for the position coordinate, if `x` and `x0` (`y` and `y0` if horizontal) are missing and the position axis is categorical notched Determines whether or not notches should be drawn. notchwidth Sets the width of the notches relative to the box' width. For example, with 0, the notches are as wide as the box(es). offsetgroup Set several traces linked to the same position axis or matching axes to the same offsetgroup where bars of the same position coordinate will line up. opacity Sets the opacity of the trace. orientation Sets the orientation of the box(es). If "v" ("h"), the distribution is visualized along the vertical (horizontal). pointpos Sets the position of the sample points in relation to the box(es). If 0, the sample points are places over the center of the box(es). Positive (negative) values correspond to positions to the right (left) for vertical boxes and above (below) for horizontal boxes selected plotly.graph_objects.box.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.box.Stream instance or dict with compatible properties text Sets the text elements associated with each sample value. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.box.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). whiskerwidth Sets the width of the whiskers relative to the box' width. For example, with 1, the whiskers are as wide as the box(es). width Sets the width of the box in data coordinate If 0 (default value) the width is automatically selected based on the positions of other box traces in the same subplot. x Sets the x sample data or coordinates. See overview for more info. x0 Sets the x coordinate of the box. See overview for more info. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . y Sets the y sample data or coordinates. See overview for more info. y0 Sets the y coordinate of the box. See overview for more info. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . Returns ------- Box """ super(Box, self).__init__("box") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.Box constructor must be a dict or an instance of plotly.graph_objs.Box""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators import box as v_box # Initialize validators # --------------------- self._validators["alignmentgroup"] = v_box.AlignmentgroupValidator() self._validators["boxmean"] = v_box.BoxmeanValidator() self._validators["boxpoints"] = v_box.BoxpointsValidator() self._validators["customdata"] = v_box.CustomdataValidator() self._validators["customdatasrc"] = v_box.CustomdatasrcValidator() self._validators["fillcolor"] = v_box.FillcolorValidator() self._validators["hoverinfo"] = v_box.HoverinfoValidator() self._validators["hoverinfosrc"] = v_box.HoverinfosrcValidator() self._validators["hoverlabel"] = v_box.HoverlabelValidator() self._validators["hoveron"] = v_box.HoveronValidator() self._validators["hovertemplate"] = v_box.HovertemplateValidator() self._validators["hovertemplatesrc"] = v_box.HovertemplatesrcValidator() self._validators["hovertext"] = v_box.HovertextValidator() self._validators["hovertextsrc"] = v_box.HovertextsrcValidator() self._validators["ids"] = v_box.IdsValidator() self._validators["idssrc"] = v_box.IdssrcValidator() self._validators["jitter"] = v_box.JitterValidator() self._validators["legendgroup"] = v_box.LegendgroupValidator() self._validators["line"] = v_box.LineValidator() self._validators["marker"] = v_box.MarkerValidator() self._validators["meta"] = v_box.MetaValidator() self._validators["metasrc"] = v_box.MetasrcValidator() self._validators["name"] = v_box.NameValidator() self._validators["notched"] = v_box.NotchedValidator() self._validators["notchwidth"] = v_box.NotchwidthValidator() self._validators["offsetgroup"] = v_box.OffsetgroupValidator() self._validators["opacity"] = v_box.OpacityValidator() self._validators["orientation"] = v_box.OrientationValidator() self._validators["pointpos"] = v_box.PointposValidator() self._validators["selected"] = v_box.SelectedValidator() self._validators["selectedpoints"] = v_box.SelectedpointsValidator() self._validators["showlegend"] = v_box.ShowlegendValidator() self._validators["stream"] = v_box.StreamValidator() self._validators["text"] = v_box.TextValidator() self._validators["textsrc"] = v_box.TextsrcValidator() self._validators["uid"] = v_box.UidValidator() self._validators["uirevision"] = v_box.UirevisionValidator() self._validators["unselected"] = v_box.UnselectedValidator() self._validators["visible"] = v_box.VisibleValidator() self._validators["whiskerwidth"] = v_box.WhiskerwidthValidator() self._validators["width"] = v_box.WidthValidator() self._validators["x"] = v_box.XValidator() self._validators["x0"] = v_box.X0Validator() self._validators["xaxis"] = v_box.XAxisValidator() self._validators["xcalendar"] = v_box.XcalendarValidator() self._validators["xsrc"] = v_box.XsrcValidator() self._validators["y"] = v_box.YValidator() self._validators["y0"] = v_box.Y0Validator() self._validators["yaxis"] = v_box.YAxisValidator() self._validators["ycalendar"] = v_box.YcalendarValidator() self._validators["ysrc"] = v_box.YsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("alignmentgroup", None) self["alignmentgroup"] = alignmentgroup if alignmentgroup is not None else _v _v = arg.pop("boxmean", None) self["boxmean"] = boxmean if boxmean is not None else _v _v = arg.pop("boxpoints", None) self["boxpoints"] = boxpoints if boxpoints is not None else _v _v = arg.pop("customdata", None) self["customdata"] = customdata if customdata is not None else _v _v = arg.pop("customdatasrc", None) self["customdatasrc"] = customdatasrc if customdatasrc is not None else _v _v = arg.pop("fillcolor", None) self["fillcolor"] = fillcolor if fillcolor is not None else _v _v = arg.pop("hoverinfo", None) self["hoverinfo"] = hoverinfo if hoverinfo is not None else _v _v = arg.pop("hoverinfosrc", None) self["hoverinfosrc"] = hoverinfosrc if hoverinfosrc is not None else _v _v = arg.pop("hoverlabel", None) self["hoverlabel"] = hoverlabel if hoverlabel is not None else _v _v = arg.pop("hoveron", None) self["hoveron"] = hoveron if hoveron is not None else _v _v = arg.pop("hovertemplate", None) self["hovertemplate"] = hovertemplate if hovertemplate is not None else _v _v = arg.pop("hovertemplatesrc", None) self["hovertemplatesrc"] = ( hovertemplatesrc if hovertemplatesrc is not None else _v ) _v = arg.pop("hovertext", None) self["hovertext"] = hovertext if hovertext is not None else _v _v = arg.pop("hovertextsrc", None) self["hovertextsrc"] = hovertextsrc if hovertextsrc is not None else _v _v = arg.pop("ids", None) self["ids"] = ids if ids is not None else _v _v = arg.pop("idssrc", None) self["idssrc"] = idssrc if idssrc is not None else _v _v = arg.pop("jitter", None) self["jitter"] = jitter if jitter is not None else _v _v = arg.pop("legendgroup", None) self["legendgroup"] = legendgroup if legendgroup is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v _v = arg.pop("meta", None) self["meta"] = meta if meta is not None else _v _v = arg.pop("metasrc", None) self["metasrc"] = metasrc if metasrc is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("notched", None) self["notched"] = notched if notched is not None else _v _v = arg.pop("notchwidth", None) self["notchwidth"] = notchwidth if notchwidth is not None else _v _v = arg.pop("offsetgroup", None) self["offsetgroup"] = offsetgroup if offsetgroup is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("orientation", None) self["orientation"] = orientation if orientation is not None else _v _v = arg.pop("pointpos", None) self["pointpos"] = pointpos if pointpos is not None else _v _v = arg.pop("selected", None) self["selected"] = selected if selected is not None else _v _v = arg.pop("selectedpoints", None) self["selectedpoints"] = selectedpoints if selectedpoints is not None else _v _v = arg.pop("showlegend", None) self["showlegend"] = showlegend if showlegend is not None else _v _v = arg.pop("stream", None) self["stream"] = stream if stream is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v _v = arg.pop("textsrc", None) self["textsrc"] = textsrc if textsrc is not None else _v _v = arg.pop("uid", None) self["uid"] = uid if uid is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("unselected", None) self["unselected"] = unselected if unselected is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("whiskerwidth", None) self["whiskerwidth"] = whiskerwidth if whiskerwidth is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("x0", None) self["x0"] = x0 if x0 is not None else _v _v = arg.pop("xaxis", None) self["xaxis"] = xaxis if xaxis is not None else _v _v = arg.pop("xcalendar", None) self["xcalendar"] = xcalendar if xcalendar is not None else _v _v = arg.pop("xsrc", None) self["xsrc"] = xsrc if xsrc is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("y0", None) self["y0"] = y0 if y0 is not None else _v _v = arg.pop("yaxis", None) self["yaxis"] = yaxis if yaxis is not None else _v _v = arg.pop("ycalendar", None) self["ycalendar"] = ycalendar if ycalendar is not None else _v _v = arg.pop("ysrc", None) self["ysrc"] = ysrc if ysrc is not None else _v # Read-only literals # ------------------ from _plotly_utils.basevalidators import LiteralValidator self._props["type"] = "box" self._validators["type"] = LiteralValidator( plotly_name="type", parent_name="box", val="box" ) arg.pop("type", None) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceType as _BaseTraceType import copy as _copy class Barpolar(_BaseTraceType): # base # ---- @property def base(self): """ Sets where the bar base is drawn (in radial axis units). In "stack" barmode, traces that set "base" will be excluded and drawn in "overlay" mode instead. The 'base' property accepts values of any type Returns ------- Any|numpy.ndarray """ return self["base"] @base.setter def base(self, val): self["base"] = val # basesrc # ------- @property def basesrc(self): """ Sets the source reference on plot.ly for base . The 'basesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["basesrc"] @basesrc.setter def basesrc(self, val): self["basesrc"] = val # customdata # ---------- @property def customdata(self): """ Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements The 'customdata' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["customdata"] @customdata.setter def customdata(self, val): self["customdata"] = val # customdatasrc # ------------- @property def customdatasrc(self): """ Sets the source reference on plot.ly for customdata . The 'customdatasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["customdatasrc"] @customdatasrc.setter def customdatasrc(self, val): self["customdatasrc"] = val # dr # -- @property def dr(self): """ Sets the r coordinate step. The 'dr' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["dr"] @dr.setter def dr(self, val): self["dr"] = val # dtheta # ------ @property def dtheta(self): """ Sets the theta coordinate step. By default, the `dtheta` step equals the subplot's period divided by the length of the `r` coordinates. The 'dtheta' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["dtheta"] @dtheta.setter def dtheta(self, val): self["dtheta"] = val # hoverinfo # --------- @property def hoverinfo(self): """ Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. The 'hoverinfo' property is a flaglist and may be specified as a string containing: - Any combination of ['r', 'theta', 'text', 'name'] joined with '+' characters (e.g. 'r+theta') OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') - A list or array of the above Returns ------- Any|numpy.ndarray """ return self["hoverinfo"] @hoverinfo.setter def hoverinfo(self, val): self["hoverinfo"] = val # hoverinfosrc # ------------ @property def hoverinfosrc(self): """ Sets the source reference on plot.ly for hoverinfo . The 'hoverinfosrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hoverinfosrc"] @hoverinfosrc.setter def hoverinfosrc(self, val): self["hoverinfosrc"] = val # hoverlabel # ---------- @property def hoverlabel(self): """ The 'hoverlabel' property is an instance of Hoverlabel that may be specified as: - An instance of plotly.graph_objs.barpolar.Hoverlabel - A dict of string/value properties that will be passed to the Hoverlabel constructor Supported dict properties: align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- plotly.graph_objs.barpolar.Hoverlabel """ return self["hoverlabel"] @hoverlabel.setter def hoverlabel(self, val): self["hoverlabel"] = val # hovertemplate # ------------- @property def hovertemplate(self): """ Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event- data. Additionally, every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. The 'hovertemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertemplate"] @hovertemplate.setter def hovertemplate(self, val): self["hovertemplate"] = val # hovertemplatesrc # ---------------- @property def hovertemplatesrc(self): """ Sets the source reference on plot.ly for hovertemplate . The 'hovertemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertemplatesrc"] @hovertemplatesrc.setter def hovertemplatesrc(self, val): self["hovertemplatesrc"] = val # hovertext # --------- @property def hovertext(self): """ Same as `text`. The 'hovertext' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertext"] @hovertext.setter def hovertext(self, val): self["hovertext"] = val # hovertextsrc # ------------ @property def hovertextsrc(self): """ Sets the source reference on plot.ly for hovertext . The 'hovertextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertextsrc"] @hovertextsrc.setter def hovertextsrc(self, val): self["hovertextsrc"] = val # ids # --- @property def ids(self): """ Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. The 'ids' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ids"] @ids.setter def ids(self, val): self["ids"] = val # idssrc # ------ @property def idssrc(self): """ Sets the source reference on plot.ly for ids . The 'idssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["idssrc"] @idssrc.setter def idssrc(self, val): self["idssrc"] = val # legendgroup # ----------- @property def legendgroup(self): """ Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. The 'legendgroup' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["legendgroup"] @legendgroup.setter def legendgroup(self, val): self["legendgroup"] = val # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.barpolar.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.barpolar.marker.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . line plotly.graph_objects.barpolar.marker.Line instance or dict with compatible properties opacity Sets the opacity of the bars. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. Returns ------- plotly.graph_objs.barpolar.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # meta # ---- @property def meta(self): """ Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. The 'meta' property accepts values of any type Returns ------- Any|numpy.ndarray """ return self["meta"] @meta.setter def meta(self, val): self["meta"] = val # metasrc # ------- @property def metasrc(self): """ Sets the source reference on plot.ly for meta . The 'metasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["metasrc"] @metasrc.setter def metasrc(self, val): self["metasrc"] = val # name # ---- @property def name(self): """ Sets the trace name. The trace name appear as the legend item and on hover. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # offset # ------ @property def offset(self): """ Shifts the angular position where the bar is drawn (in "thetatunit" units). The 'offset' property is a number and may be specified as: - An int or float - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["offset"] @offset.setter def offset(self, val): self["offset"] = val # offsetsrc # --------- @property def offsetsrc(self): """ Sets the source reference on plot.ly for offset . The 'offsetsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["offsetsrc"] @offsetsrc.setter def offsetsrc(self, val): self["offsetsrc"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the trace. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # r # - @property def r(self): """ Sets the radial coordinates The 'r' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["r"] @r.setter def r(self, val): self["r"] = val # r0 # -- @property def r0(self): """ Alternate to `r`. Builds a linear space of r coordinates. Use with `dr` where `r0` is the starting coordinate and `dr` the step. The 'r0' property accepts values of any type Returns ------- Any """ return self["r0"] @r0.setter def r0(self, val): self["r0"] = val # rsrc # ---- @property def rsrc(self): """ Sets the source reference on plot.ly for r . The 'rsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["rsrc"] @rsrc.setter def rsrc(self, val): self["rsrc"] = val # selected # -------- @property def selected(self): """ The 'selected' property is an instance of Selected that may be specified as: - An instance of plotly.graph_objs.barpolar.Selected - A dict of string/value properties that will be passed to the Selected constructor Supported dict properties: marker plotly.graph_objects.barpolar.selected.Marker instance or dict with compatible properties textfont plotly.graph_objects.barpolar.selected.Textfont instance or dict with compatible properties Returns ------- plotly.graph_objs.barpolar.Selected """ return self["selected"] @selected.setter def selected(self, val): self["selected"] = val # selectedpoints # -------------- @property def selectedpoints(self): """ Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. The 'selectedpoints' property accepts values of any type Returns ------- Any """ return self["selectedpoints"] @selectedpoints.setter def selectedpoints(self, val): self["selectedpoints"] = val # showlegend # ---------- @property def showlegend(self): """ Determines whether or not an item corresponding to this trace is shown in the legend. The 'showlegend' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showlegend"] @showlegend.setter def showlegend(self, val): self["showlegend"] = val # stream # ------ @property def stream(self): """ The 'stream' property is an instance of Stream that may be specified as: - An instance of plotly.graph_objs.barpolar.Stream - A dict of string/value properties that will be passed to the Stream constructor Supported dict properties: maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- plotly.graph_objs.barpolar.Stream """ return self["stream"] @stream.setter def stream(self, val): self["stream"] = val # subplot # ------- @property def subplot(self): """ Sets a reference between this trace's data coordinates and a polar subplot. If "polar" (the default value), the data refer to `layout.polar`. If "polar2", the data refer to `layout.polar2`, and so on. The 'subplot' property is an identifier of a particular subplot, of type 'polar', that may be specified as the string 'polar' optionally followed by an integer >= 1 (e.g. 'polar', 'polar1', 'polar2', 'polar3', etc.) Returns ------- str """ return self["subplot"] @subplot.setter def subplot(self, val): self["subplot"] = val # text # ---- @property def text(self): """ Sets hover text elements associated with each bar. If a single string, the same string appears over all bars. If an array of string, the items are mapped in order to the this trace's coordinates. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["text"] @text.setter def text(self, val): self["text"] = val # textsrc # ------- @property def textsrc(self): """ Sets the source reference on plot.ly for text . The 'textsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["textsrc"] @textsrc.setter def textsrc(self, val): self["textsrc"] = val # theta # ----- @property def theta(self): """ Sets the angular coordinates The 'theta' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["theta"] @theta.setter def theta(self, val): self["theta"] = val # theta0 # ------ @property def theta0(self): """ Alternate to `theta`. Builds a linear space of theta coordinates. Use with `dtheta` where `theta0` is the starting coordinate and `dtheta` the step. The 'theta0' property accepts values of any type Returns ------- Any """ return self["theta0"] @theta0.setter def theta0(self, val): self["theta0"] = val # thetasrc # -------- @property def thetasrc(self): """ Sets the source reference on plot.ly for theta . The 'thetasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["thetasrc"] @thetasrc.setter def thetasrc(self, val): self["thetasrc"] = val # thetaunit # --------- @property def thetaunit(self): """ Sets the unit of input "theta" values. Has an effect only when on "linear" angular axes. The 'thetaunit' property is an enumeration that may be specified as: - One of the following enumeration values: ['radians', 'degrees', 'gradians'] Returns ------- Any """ return self["thetaunit"] @thetaunit.setter def thetaunit(self, val): self["thetaunit"] = val # uid # --- @property def uid(self): """ Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. The 'uid' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["uid"] @uid.setter def uid(self, val): self["uid"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # unselected # ---------- @property def unselected(self): """ The 'unselected' property is an instance of Unselected that may be specified as: - An instance of plotly.graph_objs.barpolar.Unselected - A dict of string/value properties that will be passed to the Unselected constructor Supported dict properties: marker plotly.graph_objects.barpolar.unselected.Marker instance or dict with compatible properties textfont plotly.graph_objects.barpolar.unselected.Textfo nt instance or dict with compatible properties Returns ------- plotly.graph_objs.barpolar.Unselected """ return self["unselected"] @unselected.setter def unselected(self, val): self["unselected"] = val # visible # ------- @property def visible(self): """ Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). The 'visible' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'legendonly'] Returns ------- Any """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # width # ----- @property def width(self): """ Sets the bar angular width (in "thetaunit" units). The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["width"] @width.setter def width(self, val): self["width"] = val # widthsrc # -------- @property def widthsrc(self): """ Sets the source reference on plot.ly for width . The 'widthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["widthsrc"] @widthsrc.setter def widthsrc(self, val): self["widthsrc"] = val # type # ---- @property def type(self): return self._props["type"] # property parent name # -------------------- @property def _parent_path_str(self): return "" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ base Sets where the bar base is drawn (in radial axis units). In "stack" barmode, traces that set "base" will be excluded and drawn in "overlay" mode instead. basesrc Sets the source reference on plot.ly for base . customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dr Sets the r coordinate step. dtheta Sets the theta coordinate step. By default, the `dtheta` step equals the subplot's period divided by the length of the `r` coordinates. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.barpolar.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. marker plotly.graph_objects.barpolar.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. offset Shifts the angular position where the bar is drawn (in "thetatunit" units). offsetsrc Sets the source reference on plot.ly for offset . opacity Sets the opacity of the trace. r Sets the radial coordinates r0 Alternate to `r`. Builds a linear space of r coordinates. Use with `dr` where `r0` is the starting coordinate and `dr` the step. rsrc Sets the source reference on plot.ly for r . selected plotly.graph_objects.barpolar.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.barpolar.Stream instance or dict with compatible properties subplot Sets a reference between this trace's data coordinates and a polar subplot. If "polar" (the default value), the data refer to `layout.polar`. If "polar2", the data refer to `layout.polar2`, and so on. text Sets hover text elements associated with each bar. If a single string, the same string appears over all bars. If an array of string, the items are mapped in order to the this trace's coordinates. textsrc Sets the source reference on plot.ly for text . theta Sets the angular coordinates theta0 Alternate to `theta`. Builds a linear space of theta coordinates. Use with `dtheta` where `theta0` is the starting coordinate and `dtheta` the step. thetasrc Sets the source reference on plot.ly for theta . thetaunit Sets the unit of input "theta" values. Has an effect only when on "linear" angular axes. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.barpolar.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). width Sets the bar angular width (in "thetaunit" units). widthsrc Sets the source reference on plot.ly for width . """ def __init__( self, arg=None, base=None, basesrc=None, customdata=None, customdatasrc=None, dr=None, dtheta=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, legendgroup=None, marker=None, meta=None, metasrc=None, name=None, offset=None, offsetsrc=None, opacity=None, r=None, r0=None, rsrc=None, selected=None, selectedpoints=None, showlegend=None, stream=None, subplot=None, text=None, textsrc=None, theta=None, theta0=None, thetasrc=None, thetaunit=None, uid=None, uirevision=None, unselected=None, visible=None, width=None, widthsrc=None, **kwargs ): """ Construct a new Barpolar object The data visualized by the radial span of the bars is set in `r` Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.Barpolar base Sets where the bar base is drawn (in radial axis units). In "stack" barmode, traces that set "base" will be excluded and drawn in "overlay" mode instead. basesrc Sets the source reference on plot.ly for base . customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dr Sets the r coordinate step. dtheta Sets the theta coordinate step. By default, the `dtheta` step equals the subplot's period divided by the length of the `r` coordinates. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.barpolar.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. marker plotly.graph_objects.barpolar.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. offset Shifts the angular position where the bar is drawn (in "thetatunit" units). offsetsrc Sets the source reference on plot.ly for offset . opacity Sets the opacity of the trace. r Sets the radial coordinates r0 Alternate to `r`. Builds a linear space of r coordinates. Use with `dr` where `r0` is the starting coordinate and `dr` the step. rsrc Sets the source reference on plot.ly for r . selected plotly.graph_objects.barpolar.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.barpolar.Stream instance or dict with compatible properties subplot Sets a reference between this trace's data coordinates and a polar subplot. If "polar" (the default value), the data refer to `layout.polar`. If "polar2", the data refer to `layout.polar2`, and so on. text Sets hover text elements associated with each bar. If a single string, the same string appears over all bars. If an array of string, the items are mapped in order to the this trace's coordinates. textsrc Sets the source reference on plot.ly for text . theta Sets the angular coordinates theta0 Alternate to `theta`. Builds a linear space of theta coordinates. Use with `dtheta` where `theta0` is the starting coordinate and `dtheta` the step. thetasrc Sets the source reference on plot.ly for theta . thetaunit Sets the unit of input "theta" values. Has an effect only when on "linear" angular axes. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.barpolar.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). width Sets the bar angular width (in "thetaunit" units). widthsrc Sets the source reference on plot.ly for width . Returns ------- Barpolar """ super(Barpolar, self).__init__("barpolar") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.Barpolar constructor must be a dict or an instance of plotly.graph_objs.Barpolar""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators import barpolar as v_barpolar # Initialize validators # --------------------- self._validators["base"] = v_barpolar.BaseValidator() self._validators["basesrc"] = v_barpolar.BasesrcValidator() self._validators["customdata"] = v_barpolar.CustomdataValidator() self._validators["customdatasrc"] = v_barpolar.CustomdatasrcValidator() self._validators["dr"] = v_barpolar.DrValidator() self._validators["dtheta"] = v_barpolar.DthetaValidator() self._validators["hoverinfo"] = v_barpolar.HoverinfoValidator() self._validators["hoverinfosrc"] = v_barpolar.HoverinfosrcValidator() self._validators["hoverlabel"] = v_barpolar.HoverlabelValidator() self._validators["hovertemplate"] = v_barpolar.HovertemplateValidator() self._validators["hovertemplatesrc"] = v_barpolar.HovertemplatesrcValidator() self._validators["hovertext"] = v_barpolar.HovertextValidator() self._validators["hovertextsrc"] = v_barpolar.HovertextsrcValidator() self._validators["ids"] = v_barpolar.IdsValidator() self._validators["idssrc"] = v_barpolar.IdssrcValidator() self._validators["legendgroup"] = v_barpolar.LegendgroupValidator() self._validators["marker"] = v_barpolar.MarkerValidator() self._validators["meta"] = v_barpolar.MetaValidator() self._validators["metasrc"] = v_barpolar.MetasrcValidator() self._validators["name"] = v_barpolar.NameValidator() self._validators["offset"] = v_barpolar.OffsetValidator() self._validators["offsetsrc"] = v_barpolar.OffsetsrcValidator() self._validators["opacity"] = v_barpolar.OpacityValidator() self._validators["r"] = v_barpolar.RValidator() self._validators["r0"] = v_barpolar.R0Validator() self._validators["rsrc"] = v_barpolar.RsrcValidator() self._validators["selected"] = v_barpolar.SelectedValidator() self._validators["selectedpoints"] = v_barpolar.SelectedpointsValidator() self._validators["showlegend"] = v_barpolar.ShowlegendValidator() self._validators["stream"] = v_barpolar.StreamValidator() self._validators["subplot"] = v_barpolar.SubplotValidator() self._validators["text"] = v_barpolar.TextValidator() self._validators["textsrc"] = v_barpolar.TextsrcValidator() self._validators["theta"] = v_barpolar.ThetaValidator() self._validators["theta0"] = v_barpolar.Theta0Validator() self._validators["thetasrc"] = v_barpolar.ThetasrcValidator() self._validators["thetaunit"] = v_barpolar.ThetaunitValidator() self._validators["uid"] = v_barpolar.UidValidator() self._validators["uirevision"] = v_barpolar.UirevisionValidator() self._validators["unselected"] = v_barpolar.UnselectedValidator() self._validators["visible"] = v_barpolar.VisibleValidator() self._validators["width"] = v_barpolar.WidthValidator() self._validators["widthsrc"] = v_barpolar.WidthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("base", None) self["base"] = base if base is not None else _v _v = arg.pop("basesrc", None) self["basesrc"] = basesrc if basesrc is not None else _v _v = arg.pop("customdata", None) self["customdata"] = customdata if customdata is not None else _v _v = arg.pop("customdatasrc", None) self["customdatasrc"] = customdatasrc if customdatasrc is not None else _v _v = arg.pop("dr", None) self["dr"] = dr if dr is not None else _v _v = arg.pop("dtheta", None) self["dtheta"] = dtheta if dtheta is not None else _v _v = arg.pop("hoverinfo", None) self["hoverinfo"] = hoverinfo if hoverinfo is not None else _v _v = arg.pop("hoverinfosrc", None) self["hoverinfosrc"] = hoverinfosrc if hoverinfosrc is not None else _v _v = arg.pop("hoverlabel", None) self["hoverlabel"] = hoverlabel if hoverlabel is not None else _v _v = arg.pop("hovertemplate", None) self["hovertemplate"] = hovertemplate if hovertemplate is not None else _v _v = arg.pop("hovertemplatesrc", None) self["hovertemplatesrc"] = ( hovertemplatesrc if hovertemplatesrc is not None else _v ) _v = arg.pop("hovertext", None) self["hovertext"] = hovertext if hovertext is not None else _v _v = arg.pop("hovertextsrc", None) self["hovertextsrc"] = hovertextsrc if hovertextsrc is not None else _v _v = arg.pop("ids", None) self["ids"] = ids if ids is not None else _v _v = arg.pop("idssrc", None) self["idssrc"] = idssrc if idssrc is not None else _v _v = arg.pop("legendgroup", None) self["legendgroup"] = legendgroup if legendgroup is not None else _v _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v _v = arg.pop("meta", None) self["meta"] = meta if meta is not None else _v _v = arg.pop("metasrc", None) self["metasrc"] = metasrc if metasrc is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("offset", None) self["offset"] = offset if offset is not None else _v _v = arg.pop("offsetsrc", None) self["offsetsrc"] = offsetsrc if offsetsrc is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("r", None) self["r"] = r if r is not None else _v _v = arg.pop("r0", None) self["r0"] = r0 if r0 is not None else _v _v = arg.pop("rsrc", None) self["rsrc"] = rsrc if rsrc is not None else _v _v = arg.pop("selected", None) self["selected"] = selected if selected is not None else _v _v = arg.pop("selectedpoints", None) self["selectedpoints"] = selectedpoints if selectedpoints is not None else _v _v = arg.pop("showlegend", None) self["showlegend"] = showlegend if showlegend is not None else _v _v = arg.pop("stream", None) self["stream"] = stream if stream is not None else _v _v = arg.pop("subplot", None) self["subplot"] = subplot if subplot is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v _v = arg.pop("textsrc", None) self["textsrc"] = textsrc if textsrc is not None else _v _v = arg.pop("theta", None) self["theta"] = theta if theta is not None else _v _v = arg.pop("theta0", None) self["theta0"] = theta0 if theta0 is not None else _v _v = arg.pop("thetasrc", None) self["thetasrc"] = thetasrc if thetasrc is not None else _v _v = arg.pop("thetaunit", None) self["thetaunit"] = thetaunit if thetaunit is not None else _v _v = arg.pop("uid", None) self["uid"] = uid if uid is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("unselected", None) self["unselected"] = unselected if unselected is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v _v = arg.pop("widthsrc", None) self["widthsrc"] = widthsrc if widthsrc is not None else _v # Read-only literals # ------------------ from _plotly_utils.basevalidators import LiteralValidator self._props["type"] = "barpolar" self._validators["type"] = LiteralValidator( plotly_name="type", parent_name="barpolar", val="barpolar" ) arg.pop("type", None) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceType as _BaseTraceType import copy as _copy class Bar(_BaseTraceType): # alignmentgroup # -------------- @property def alignmentgroup(self): """ Set several traces linked to the same position axis or matching axes to the same alignmentgroup. This controls whether bars compute their positional range dependently or independently. The 'alignmentgroup' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["alignmentgroup"] @alignmentgroup.setter def alignmentgroup(self, val): self["alignmentgroup"] = val # base # ---- @property def base(self): """ Sets where the bar base is drawn (in position axis units). In "stack" or "relative" barmode, traces that set "base" will be excluded and drawn in "overlay" mode instead. The 'base' property accepts values of any type Returns ------- Any|numpy.ndarray """ return self["base"] @base.setter def base(self, val): self["base"] = val # basesrc # ------- @property def basesrc(self): """ Sets the source reference on plot.ly for base . The 'basesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["basesrc"] @basesrc.setter def basesrc(self, val): self["basesrc"] = val # cliponaxis # ---------- @property def cliponaxis(self): """ Determines whether the text nodes are clipped about the subplot axes. To show the text nodes above axis lines and tick labels, make sure to set `xaxis.layer` and `yaxis.layer` to *below traces*. The 'cliponaxis' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["cliponaxis"] @cliponaxis.setter def cliponaxis(self, val): self["cliponaxis"] = val # constraintext # ------------- @property def constraintext(self): """ Constrain the size of text inside or outside a bar to be no larger than the bar itself. The 'constraintext' property is an enumeration that may be specified as: - One of the following enumeration values: ['inside', 'outside', 'both', 'none'] Returns ------- Any """ return self["constraintext"] @constraintext.setter def constraintext(self, val): self["constraintext"] = val # customdata # ---------- @property def customdata(self): """ Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements The 'customdata' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["customdata"] @customdata.setter def customdata(self, val): self["customdata"] = val # customdatasrc # ------------- @property def customdatasrc(self): """ Sets the source reference on plot.ly for customdata . The 'customdatasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["customdatasrc"] @customdatasrc.setter def customdatasrc(self, val): self["customdatasrc"] = val # dx # -- @property def dx(self): """ Sets the x coordinate step. See `x0` for more info. The 'dx' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["dx"] @dx.setter def dx(self, val): self["dx"] = val # dy # -- @property def dy(self): """ Sets the y coordinate step. See `y0` for more info. The 'dy' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["dy"] @dy.setter def dy(self, val): self["dy"] = val # error_x # ------- @property def error_x(self): """ The 'error_x' property is an instance of ErrorX that may be specified as: - An instance of plotly.graph_objs.bar.ErrorX - A dict of string/value properties that will be passed to the ErrorX constructor Supported dict properties: array Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. arrayminus Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. arrayminussrc Sets the source reference on plot.ly for arrayminus . arraysrc Sets the source reference on plot.ly for array . color Sets the stoke color of the error bars. copy_ystyle symmetric Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. thickness Sets the thickness (in px) of the error bars. traceref tracerefminus type Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. value Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. valueminus Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars visible Determines whether or not this set of error bars is visible. width Sets the width (in px) of the cross-bar at both ends of the error bars. Returns ------- plotly.graph_objs.bar.ErrorX """ return self["error_x"] @error_x.setter def error_x(self, val): self["error_x"] = val # error_y # ------- @property def error_y(self): """ The 'error_y' property is an instance of ErrorY that may be specified as: - An instance of plotly.graph_objs.bar.ErrorY - A dict of string/value properties that will be passed to the ErrorY constructor Supported dict properties: array Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. arrayminus Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. arrayminussrc Sets the source reference on plot.ly for arrayminus . arraysrc Sets the source reference on plot.ly for array . color Sets the stoke color of the error bars. symmetric Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. thickness Sets the thickness (in px) of the error bars. traceref tracerefminus type Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. value Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. valueminus Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars visible Determines whether or not this set of error bars is visible. width Sets the width (in px) of the cross-bar at both ends of the error bars. Returns ------- plotly.graph_objs.bar.ErrorY """ return self["error_y"] @error_y.setter def error_y(self, val): self["error_y"] = val # hoverinfo # --------- @property def hoverinfo(self): """ Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. The 'hoverinfo' property is a flaglist and may be specified as a string containing: - Any combination of ['x', 'y', 'z', 'text', 'name'] joined with '+' characters (e.g. 'x+y') OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') - A list or array of the above Returns ------- Any|numpy.ndarray """ return self["hoverinfo"] @hoverinfo.setter def hoverinfo(self, val): self["hoverinfo"] = val # hoverinfosrc # ------------ @property def hoverinfosrc(self): """ Sets the source reference on plot.ly for hoverinfo . The 'hoverinfosrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hoverinfosrc"] @hoverinfosrc.setter def hoverinfosrc(self, val): self["hoverinfosrc"] = val # hoverlabel # ---------- @property def hoverlabel(self): """ The 'hoverlabel' property is an instance of Hoverlabel that may be specified as: - An instance of plotly.graph_objs.bar.Hoverlabel - A dict of string/value properties that will be passed to the Hoverlabel constructor Supported dict properties: align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- plotly.graph_objs.bar.Hoverlabel """ return self["hoverlabel"] @hoverlabel.setter def hoverlabel(self, val): self["hoverlabel"] = val # hovertemplate # ------------- @property def hovertemplate(self): """ Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event- data. Additionally, every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. variables `value` and `label`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. The 'hovertemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertemplate"] @hovertemplate.setter def hovertemplate(self, val): self["hovertemplate"] = val # hovertemplatesrc # ---------------- @property def hovertemplatesrc(self): """ Sets the source reference on plot.ly for hovertemplate . The 'hovertemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertemplatesrc"] @hovertemplatesrc.setter def hovertemplatesrc(self, val): self["hovertemplatesrc"] = val # hovertext # --------- @property def hovertext(self): """ Sets hover text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. The 'hovertext' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["hovertext"] @hovertext.setter def hovertext(self, val): self["hovertext"] = val # hovertextsrc # ------------ @property def hovertextsrc(self): """ Sets the source reference on plot.ly for hovertext . The 'hovertextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hovertextsrc"] @hovertextsrc.setter def hovertextsrc(self, val): self["hovertextsrc"] = val # ids # --- @property def ids(self): """ Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. The 'ids' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ids"] @ids.setter def ids(self, val): self["ids"] = val # idssrc # ------ @property def idssrc(self): """ Sets the source reference on plot.ly for ids . The 'idssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["idssrc"] @idssrc.setter def idssrc(self, val): self["idssrc"] = val # insidetextanchor # ---------------- @property def insidetextanchor(self): """ Determines if texts are kept at center or start/end points in `textposition` "inside" mode. The 'insidetextanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['end', 'middle', 'start'] Returns ------- Any """ return self["insidetextanchor"] @insidetextanchor.setter def insidetextanchor(self, val): self["insidetextanchor"] = val # insidetextfont # -------------- @property def insidetextfont(self): """ Sets the font used for `text` lying inside the bar. The 'insidetextfont' property is an instance of Insidetextfont that may be specified as: - An instance of plotly.graph_objs.bar.Insidetextfont - A dict of string/value properties that will be passed to the Insidetextfont constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.bar.Insidetextfont """ return self["insidetextfont"] @insidetextfont.setter def insidetextfont(self, val): self["insidetextfont"] = val # legendgroup # ----------- @property def legendgroup(self): """ Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. The 'legendgroup' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["legendgroup"] @legendgroup.setter def legendgroup(self, val): self["legendgroup"] = val # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.bar.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.bar.marker.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . line plotly.graph_objects.bar.marker.Line instance or dict with compatible properties opacity Sets the opacity of the bars. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. Returns ------- plotly.graph_objs.bar.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # meta # ---- @property def meta(self): """ Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. The 'meta' property accepts values of any type Returns ------- Any|numpy.ndarray """ return self["meta"] @meta.setter def meta(self, val): self["meta"] = val # metasrc # ------- @property def metasrc(self): """ Sets the source reference on plot.ly for meta . The 'metasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["metasrc"] @metasrc.setter def metasrc(self, val): self["metasrc"] = val # name # ---- @property def name(self): """ Sets the trace name. The trace name appear as the legend item and on hover. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # offset # ------ @property def offset(self): """ Shifts the position where the bar is drawn (in position axis units). In "group" barmode, traces that set "offset" will be excluded and drawn in "overlay" mode instead. The 'offset' property is a number and may be specified as: - An int or float - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["offset"] @offset.setter def offset(self, val): self["offset"] = val # offsetgroup # ----------- @property def offsetgroup(self): """ Set several traces linked to the same position axis or matching axes to the same offsetgroup where bars of the same position coordinate will line up. The 'offsetgroup' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["offsetgroup"] @offsetgroup.setter def offsetgroup(self, val): self["offsetgroup"] = val # offsetsrc # --------- @property def offsetsrc(self): """ Sets the source reference on plot.ly for offset . The 'offsetsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["offsetsrc"] @offsetsrc.setter def offsetsrc(self, val): self["offsetsrc"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the trace. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # orientation # ----------- @property def orientation(self): """ Sets the orientation of the bars. With "v" ("h"), the value of the each bar spans along the vertical (horizontal). The 'orientation' property is an enumeration that may be specified as: - One of the following enumeration values: ['v', 'h'] Returns ------- Any """ return self["orientation"] @orientation.setter def orientation(self, val): self["orientation"] = val # outsidetextfont # --------------- @property def outsidetextfont(self): """ Sets the font used for `text` lying outside the bar. The 'outsidetextfont' property is an instance of Outsidetextfont that may be specified as: - An instance of plotly.graph_objs.bar.Outsidetextfont - A dict of string/value properties that will be passed to the Outsidetextfont constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.bar.Outsidetextfont """ return self["outsidetextfont"] @outsidetextfont.setter def outsidetextfont(self, val): self["outsidetextfont"] = val # r # - @property def r(self): """ r coordinates in scatter traces are deprecated!Please switch to the "scatterpolar" trace type.Sets the radial coordinatesfor legacy polar chart only. The 'r' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["r"] @r.setter def r(self, val): self["r"] = val # rsrc # ---- @property def rsrc(self): """ Sets the source reference on plot.ly for r . The 'rsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["rsrc"] @rsrc.setter def rsrc(self, val): self["rsrc"] = val # selected # -------- @property def selected(self): """ The 'selected' property is an instance of Selected that may be specified as: - An instance of plotly.graph_objs.bar.Selected - A dict of string/value properties that will be passed to the Selected constructor Supported dict properties: marker plotly.graph_objects.bar.selected.Marker instance or dict with compatible properties textfont plotly.graph_objects.bar.selected.Textfont instance or dict with compatible properties Returns ------- plotly.graph_objs.bar.Selected """ return self["selected"] @selected.setter def selected(self, val): self["selected"] = val # selectedpoints # -------------- @property def selectedpoints(self): """ Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. The 'selectedpoints' property accepts values of any type Returns ------- Any """ return self["selectedpoints"] @selectedpoints.setter def selectedpoints(self, val): self["selectedpoints"] = val # showlegend # ---------- @property def showlegend(self): """ Determines whether or not an item corresponding to this trace is shown in the legend. The 'showlegend' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showlegend"] @showlegend.setter def showlegend(self, val): self["showlegend"] = val # stream # ------ @property def stream(self): """ The 'stream' property is an instance of Stream that may be specified as: - An instance of plotly.graph_objs.bar.Stream - A dict of string/value properties that will be passed to the Stream constructor Supported dict properties: maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- plotly.graph_objs.bar.Stream """ return self["stream"] @stream.setter def stream(self, val): self["stream"] = val # t # - @property def t(self): """ t coordinates in scatter traces are deprecated!Please switch to the "scatterpolar" trace type.Sets the angular coordinatesfor legacy polar chart only. The 't' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["t"] @t.setter def t(self, val): self["t"] = val # text # ---- @property def text(self): """ Sets text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["text"] @text.setter def text(self, val): self["text"] = val # textangle # --------- @property def textangle(self): """ Sets the angle of the tick labels with respect to the bar. For example, a `tickangle` of -90 draws the tick labels vertically. With "auto" the texts may automatically be rotated to fit with the maximum size in bars. The 'textangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["textangle"] @textangle.setter def textangle(self, val): self["textangle"] = val # textfont # -------- @property def textfont(self): """ Sets the font used for `text`. The 'textfont' property is an instance of Textfont that may be specified as: - An instance of plotly.graph_objs.bar.Textfont - A dict of string/value properties that will be passed to the Textfont constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.bar.Textfont """ return self["textfont"] @textfont.setter def textfont(self, val): self["textfont"] = val # textposition # ------------ @property def textposition(self): """ Specifies the location of the `text`. "inside" positions `text` inside, next to the bar end (rotated and scaled if needed). "outside" positions `text` outside, next to the bar end (scaled if needed), unless there is another bar stacked on this one, then the text gets pushed inside. "auto" tries to position `text` inside the bar, but if the bar is too small and no bar is stacked on this one the text is moved outside. The 'textposition' property is an enumeration that may be specified as: - One of the following enumeration values: ['inside', 'outside', 'auto', 'none'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["textposition"] @textposition.setter def textposition(self, val): self["textposition"] = val # textpositionsrc # --------------- @property def textpositionsrc(self): """ Sets the source reference on plot.ly for textposition . The 'textpositionsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["textpositionsrc"] @textpositionsrc.setter def textpositionsrc(self, val): self["textpositionsrc"] = val # textsrc # ------- @property def textsrc(self): """ Sets the source reference on plot.ly for text . The 'textsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["textsrc"] @textsrc.setter def textsrc(self, val): self["textsrc"] = val # texttemplate # ------------ @property def texttemplate(self): """ Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `value` and `label`. The 'texttemplate' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["texttemplate"] @texttemplate.setter def texttemplate(self, val): self["texttemplate"] = val # texttemplatesrc # --------------- @property def texttemplatesrc(self): """ Sets the source reference on plot.ly for texttemplate . The 'texttemplatesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["texttemplatesrc"] @texttemplatesrc.setter def texttemplatesrc(self, val): self["texttemplatesrc"] = val # tsrc # ---- @property def tsrc(self): """ Sets the source reference on plot.ly for t . The 'tsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tsrc"] @tsrc.setter def tsrc(self, val): self["tsrc"] = val # uid # --- @property def uid(self): """ Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. The 'uid' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["uid"] @uid.setter def uid(self, val): self["uid"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # unselected # ---------- @property def unselected(self): """ The 'unselected' property is an instance of Unselected that may be specified as: - An instance of plotly.graph_objs.bar.Unselected - A dict of string/value properties that will be passed to the Unselected constructor Supported dict properties: marker plotly.graph_objects.bar.unselected.Marker instance or dict with compatible properties textfont plotly.graph_objects.bar.unselected.Textfont instance or dict with compatible properties Returns ------- plotly.graph_objs.bar.Unselected """ return self["unselected"] @unselected.setter def unselected(self, val): self["unselected"] = val # visible # ------- @property def visible(self): """ Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). The 'visible' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'legendonly'] Returns ------- Any """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # width # ----- @property def width(self): """ Sets the bar width (in position axis units). The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["width"] @width.setter def width(self, val): self["width"] = val # widthsrc # -------- @property def widthsrc(self): """ Sets the source reference on plot.ly for width . The 'widthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["widthsrc"] @widthsrc.setter def widthsrc(self, val): self["widthsrc"] = val # x # - @property def x(self): """ Sets the x coordinates. The 'x' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["x"] @x.setter def x(self, val): self["x"] = val # x0 # -- @property def x0(self): """ Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. The 'x0' property accepts values of any type Returns ------- Any """ return self["x0"] @x0.setter def x0(self, val): self["x0"] = val # xaxis # ----- @property def xaxis(self): """ Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. The 'xaxis' property is an identifier of a particular subplot, of type 'x', that may be specified as the string 'x' optionally followed by an integer >= 1 (e.g. 'x', 'x1', 'x2', 'x3', etc.) Returns ------- str """ return self["xaxis"] @xaxis.setter def xaxis(self, val): self["xaxis"] = val # xcalendar # --------- @property def xcalendar(self): """ Sets the calendar system to use with `x` date data. The 'xcalendar' property is an enumeration that may be specified as: - One of the following enumeration values: ['gregorian', 'chinese', 'coptic', 'discworld', 'ethiopian', 'hebrew', 'islamic', 'julian', 'mayan', 'nanakshahi', 'nepali', 'persian', 'jalali', 'taiwan', 'thai', 'ummalqura'] Returns ------- Any """ return self["xcalendar"] @xcalendar.setter def xcalendar(self, val): self["xcalendar"] = val # xsrc # ---- @property def xsrc(self): """ Sets the source reference on plot.ly for x . The 'xsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["xsrc"] @xsrc.setter def xsrc(self, val): self["xsrc"] = val # y # - @property def y(self): """ Sets the y coordinates. The 'y' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["y"] @y.setter def y(self, val): self["y"] = val # y0 # -- @property def y0(self): """ Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. The 'y0' property accepts values of any type Returns ------- Any """ return self["y0"] @y0.setter def y0(self, val): self["y0"] = val # yaxis # ----- @property def yaxis(self): """ Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. The 'yaxis' property is an identifier of a particular subplot, of type 'y', that may be specified as the string 'y' optionally followed by an integer >= 1 (e.g. 'y', 'y1', 'y2', 'y3', etc.) Returns ------- str """ return self["yaxis"] @yaxis.setter def yaxis(self, val): self["yaxis"] = val # ycalendar # --------- @property def ycalendar(self): """ Sets the calendar system to use with `y` date data. The 'ycalendar' property is an enumeration that may be specified as: - One of the following enumeration values: ['gregorian', 'chinese', 'coptic', 'discworld', 'ethiopian', 'hebrew', 'islamic', 'julian', 'mayan', 'nanakshahi', 'nepali', 'persian', 'jalali', 'taiwan', 'thai', 'ummalqura'] Returns ------- Any """ return self["ycalendar"] @ycalendar.setter def ycalendar(self, val): self["ycalendar"] = val # ysrc # ---- @property def ysrc(self): """ Sets the source reference on plot.ly for y . The 'ysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ysrc"] @ysrc.setter def ysrc(self, val): self["ysrc"] = val # type # ---- @property def type(self): return self._props["type"] # property parent name # -------------------- @property def _parent_path_str(self): return "" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ alignmentgroup Set several traces linked to the same position axis or matching axes to the same alignmentgroup. This controls whether bars compute their positional range dependently or independently. base Sets where the bar base is drawn (in position axis units). In "stack" or "relative" barmode, traces that set "base" will be excluded and drawn in "overlay" mode instead. basesrc Sets the source reference on plot.ly for base . cliponaxis Determines whether the text nodes are clipped about the subplot axes. To show the text nodes above axis lines and tick labels, make sure to set `xaxis.layer` and `yaxis.layer` to *below traces*. constraintext Constrain the size of text inside or outside a bar to be no larger than the bar itself. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dx Sets the x coordinate step. See `x0` for more info. dy Sets the y coordinate step. See `y0` for more info. error_x plotly.graph_objects.bar.ErrorX instance or dict with compatible properties error_y plotly.graph_objects.bar.ErrorY instance or dict with compatible properties hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.bar.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `value` and `label`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . insidetextanchor Determines if texts are kept at center or start/end points in `textposition` "inside" mode. insidetextfont Sets the font used for `text` lying inside the bar. legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. marker plotly.graph_objects.bar.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. offset Shifts the position where the bar is drawn (in position axis units). In "group" barmode, traces that set "offset" will be excluded and drawn in "overlay" mode instead. offsetgroup Set several traces linked to the same position axis or matching axes to the same offsetgroup where bars of the same position coordinate will line up. offsetsrc Sets the source reference on plot.ly for offset . opacity Sets the opacity of the trace. orientation Sets the orientation of the bars. With "v" ("h"), the value of the each bar spans along the vertical (horizontal). outsidetextfont Sets the font used for `text` lying outside the bar. r r coordinates in scatter traces are deprecated!Please switch to the "scatterpolar" trace type.Sets the radial coordinatesfor legacy polar chart only. rsrc Sets the source reference on plot.ly for r . selected plotly.graph_objects.bar.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.bar.Stream instance or dict with compatible properties t t coordinates in scatter traces are deprecated!Please switch to the "scatterpolar" trace type.Sets the angular coordinatesfor legacy polar chart only. text Sets text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textangle Sets the angle of the tick labels with respect to the bar. For example, a `tickangle` of -90 draws the tick labels vertically. With "auto" the texts may automatically be rotated to fit with the maximum size in bars. textfont Sets the font used for `text`. textposition Specifies the location of the `text`. "inside" positions `text` inside, next to the bar end (rotated and scaled if needed). "outside" positions `text` outside, next to the bar end (scaled if needed), unless there is another bar stacked on this one, then the text gets pushed inside. "auto" tries to position `text` inside the bar, but if the bar is too small and no bar is stacked on this one the text is moved outside. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `value` and `label`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . tsrc Sets the source reference on plot.ly for t . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.bar.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). width Sets the bar width (in position axis units). widthsrc Sets the source reference on plot.ly for width . x Sets the x coordinates. x0 Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . y Sets the y coordinates. y0 Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . """ def __init__( self, arg=None, alignmentgroup=None, base=None, basesrc=None, cliponaxis=None, constraintext=None, customdata=None, customdatasrc=None, dx=None, dy=None, error_x=None, error_y=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, insidetextanchor=None, insidetextfont=None, legendgroup=None, marker=None, meta=None, metasrc=None, name=None, offset=None, offsetgroup=None, offsetsrc=None, opacity=None, orientation=None, outsidetextfont=None, r=None, rsrc=None, selected=None, selectedpoints=None, showlegend=None, stream=None, t=None, text=None, textangle=None, textfont=None, textposition=None, textpositionsrc=None, textsrc=None, texttemplate=None, texttemplatesrc=None, tsrc=None, uid=None, uirevision=None, unselected=None, visible=None, width=None, widthsrc=None, x=None, x0=None, xaxis=None, xcalendar=None, xsrc=None, y=None, y0=None, yaxis=None, ycalendar=None, ysrc=None, **kwargs ): """ Construct a new Bar object The data visualized by the span of the bars is set in `y` if `orientation` is set th "v" (the default) and the labels are set in `x`. By setting `orientation` to "h", the roles are interchanged. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.Bar alignmentgroup Set several traces linked to the same position axis or matching axes to the same alignmentgroup. This controls whether bars compute their positional range dependently or independently. base Sets where the bar base is drawn (in position axis units). In "stack" or "relative" barmode, traces that set "base" will be excluded and drawn in "overlay" mode instead. basesrc Sets the source reference on plot.ly for base . cliponaxis Determines whether the text nodes are clipped about the subplot axes. To show the text nodes above axis lines and tick labels, make sure to set `xaxis.layer` and `yaxis.layer` to *below traces*. constraintext Constrain the size of text inside or outside a bar to be no larger than the bar itself. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dx Sets the x coordinate step. See `x0` for more info. dy Sets the y coordinate step. See `y0` for more info. error_x plotly.graph_objects.bar.ErrorX instance or dict with compatible properties error_y plotly.graph_objects.bar.ErrorY instance or dict with compatible properties hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.bar.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `value` and `label`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . insidetextanchor Determines if texts are kept at center or start/end points in `textposition` "inside" mode. insidetextfont Sets the font used for `text` lying inside the bar. legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. marker plotly.graph_objects.bar.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. offset Shifts the position where the bar is drawn (in position axis units). In "group" barmode, traces that set "offset" will be excluded and drawn in "overlay" mode instead. offsetgroup Set several traces linked to the same position axis or matching axes to the same offsetgroup where bars of the same position coordinate will line up. offsetsrc Sets the source reference on plot.ly for offset . opacity Sets the opacity of the trace. orientation Sets the orientation of the bars. With "v" ("h"), the value of the each bar spans along the vertical (horizontal). outsidetextfont Sets the font used for `text` lying outside the bar. r r coordinates in scatter traces are deprecated!Please switch to the "scatterpolar" trace type.Sets the radial coordinatesfor legacy polar chart only. rsrc Sets the source reference on plot.ly for r . selected plotly.graph_objects.bar.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.bar.Stream instance or dict with compatible properties t t coordinates in scatter traces are deprecated!Please switch to the "scatterpolar" trace type.Sets the angular coordinatesfor legacy polar chart only. text Sets text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textangle Sets the angle of the tick labels with respect to the bar. For example, a `tickangle` of -90 draws the tick labels vertically. With "auto" the texts may automatically be rotated to fit with the maximum size in bars. textfont Sets the font used for `text`. textposition Specifies the location of the `text`. "inside" positions `text` inside, next to the bar end (rotated and scaled if needed). "outside" positions `text` outside, next to the bar end (scaled if needed), unless there is another bar stacked on this one, then the text gets pushed inside. "auto" tries to position `text` inside the bar, but if the bar is too small and no bar is stacked on this one the text is moved outside. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `value` and `label`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . tsrc Sets the source reference on plot.ly for t . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.bar.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). width Sets the bar width (in position axis units). widthsrc Sets the source reference on plot.ly for width . x Sets the x coordinates. x0 Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . y Sets the y coordinates. y0 Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . Returns ------- Bar """ super(Bar, self).__init__("bar") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.Bar constructor must be a dict or an instance of plotly.graph_objs.Bar""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators import bar as v_bar # Initialize validators # --------------------- self._validators["alignmentgroup"] = v_bar.AlignmentgroupValidator() self._validators["base"] = v_bar.BaseValidator() self._validators["basesrc"] = v_bar.BasesrcValidator() self._validators["cliponaxis"] = v_bar.CliponaxisValidator() self._validators["constraintext"] = v_bar.ConstraintextValidator() self._validators["customdata"] = v_bar.CustomdataValidator() self._validators["customdatasrc"] = v_bar.CustomdatasrcValidator() self._validators["dx"] = v_bar.DxValidator() self._validators["dy"] = v_bar.DyValidator() self._validators["error_x"] = v_bar.ErrorXValidator() self._validators["error_y"] = v_bar.ErrorYValidator() self._validators["hoverinfo"] = v_bar.HoverinfoValidator() self._validators["hoverinfosrc"] = v_bar.HoverinfosrcValidator() self._validators["hoverlabel"] = v_bar.HoverlabelValidator() self._validators["hovertemplate"] = v_bar.HovertemplateValidator() self._validators["hovertemplatesrc"] = v_bar.HovertemplatesrcValidator() self._validators["hovertext"] = v_bar.HovertextValidator() self._validators["hovertextsrc"] = v_bar.HovertextsrcValidator() self._validators["ids"] = v_bar.IdsValidator() self._validators["idssrc"] = v_bar.IdssrcValidator() self._validators["insidetextanchor"] = v_bar.InsidetextanchorValidator() self._validators["insidetextfont"] = v_bar.InsidetextfontValidator() self._validators["legendgroup"] = v_bar.LegendgroupValidator() self._validators["marker"] = v_bar.MarkerValidator() self._validators["meta"] = v_bar.MetaValidator() self._validators["metasrc"] = v_bar.MetasrcValidator() self._validators["name"] = v_bar.NameValidator() self._validators["offset"] = v_bar.OffsetValidator() self._validators["offsetgroup"] = v_bar.OffsetgroupValidator() self._validators["offsetsrc"] = v_bar.OffsetsrcValidator() self._validators["opacity"] = v_bar.OpacityValidator() self._validators["orientation"] = v_bar.OrientationValidator() self._validators["outsidetextfont"] = v_bar.OutsidetextfontValidator() self._validators["r"] = v_bar.RValidator() self._validators["rsrc"] = v_bar.RsrcValidator() self._validators["selected"] = v_bar.SelectedValidator() self._validators["selectedpoints"] = v_bar.SelectedpointsValidator() self._validators["showlegend"] = v_bar.ShowlegendValidator() self._validators["stream"] = v_bar.StreamValidator() self._validators["t"] = v_bar.TValidator() self._validators["text"] = v_bar.TextValidator() self._validators["textangle"] = v_bar.TextangleValidator() self._validators["textfont"] = v_bar.TextfontValidator() self._validators["textposition"] = v_bar.TextpositionValidator() self._validators["textpositionsrc"] = v_bar.TextpositionsrcValidator() self._validators["textsrc"] = v_bar.TextsrcValidator() self._validators["texttemplate"] = v_bar.TexttemplateValidator() self._validators["texttemplatesrc"] = v_bar.TexttemplatesrcValidator() self._validators["tsrc"] = v_bar.TsrcValidator() self._validators["uid"] = v_bar.UidValidator() self._validators["uirevision"] = v_bar.UirevisionValidator() self._validators["unselected"] = v_bar.UnselectedValidator() self._validators["visible"] = v_bar.VisibleValidator() self._validators["width"] = v_bar.WidthValidator() self._validators["widthsrc"] = v_bar.WidthsrcValidator() self._validators["x"] = v_bar.XValidator() self._validators["x0"] = v_bar.X0Validator() self._validators["xaxis"] = v_bar.XAxisValidator() self._validators["xcalendar"] = v_bar.XcalendarValidator() self._validators["xsrc"] = v_bar.XsrcValidator() self._validators["y"] = v_bar.YValidator() self._validators["y0"] = v_bar.Y0Validator() self._validators["yaxis"] = v_bar.YAxisValidator() self._validators["ycalendar"] = v_bar.YcalendarValidator() self._validators["ysrc"] = v_bar.YsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("alignmentgroup", None) self["alignmentgroup"] = alignmentgroup if alignmentgroup is not None else _v _v = arg.pop("base", None) self["base"] = base if base is not None else _v _v = arg.pop("basesrc", None) self["basesrc"] = basesrc if basesrc is not None else _v _v = arg.pop("cliponaxis", None) self["cliponaxis"] = cliponaxis if cliponaxis is not None else _v _v = arg.pop("constraintext", None) self["constraintext"] = constraintext if constraintext is not None else _v _v = arg.pop("customdata", None) self["customdata"] = customdata if customdata is not None else _v _v = arg.pop("customdatasrc", None) self["customdatasrc"] = customdatasrc if customdatasrc is not None else _v _v = arg.pop("dx", None) self["dx"] = dx if dx is not None else _v _v = arg.pop("dy", None) self["dy"] = dy if dy is not None else _v _v = arg.pop("error_x", None) self["error_x"] = error_x if error_x is not None else _v _v = arg.pop("error_y", None) self["error_y"] = error_y if error_y is not None else _v _v = arg.pop("hoverinfo", None) self["hoverinfo"] = hoverinfo if hoverinfo is not None else _v _v = arg.pop("hoverinfosrc", None) self["hoverinfosrc"] = hoverinfosrc if hoverinfosrc is not None else _v _v = arg.pop("hoverlabel", None) self["hoverlabel"] = hoverlabel if hoverlabel is not None else _v _v = arg.pop("hovertemplate", None) self["hovertemplate"] = hovertemplate if hovertemplate is not None else _v _v = arg.pop("hovertemplatesrc", None) self["hovertemplatesrc"] = ( hovertemplatesrc if hovertemplatesrc is not None else _v ) _v = arg.pop("hovertext", None) self["hovertext"] = hovertext if hovertext is not None else _v _v = arg.pop("hovertextsrc", None) self["hovertextsrc"] = hovertextsrc if hovertextsrc is not None else _v _v = arg.pop("ids", None) self["ids"] = ids if ids is not None else _v _v = arg.pop("idssrc", None) self["idssrc"] = idssrc if idssrc is not None else _v _v = arg.pop("insidetextanchor", None) self["insidetextanchor"] = ( insidetextanchor if insidetextanchor is not None else _v ) _v = arg.pop("insidetextfont", None) self["insidetextfont"] = insidetextfont if insidetextfont is not None else _v _v = arg.pop("legendgroup", None) self["legendgroup"] = legendgroup if legendgroup is not None else _v _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v _v = arg.pop("meta", None) self["meta"] = meta if meta is not None else _v _v = arg.pop("metasrc", None) self["metasrc"] = metasrc if metasrc is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("offset", None) self["offset"] = offset if offset is not None else _v _v = arg.pop("offsetgroup", None) self["offsetgroup"] = offsetgroup if offsetgroup is not None else _v _v = arg.pop("offsetsrc", None) self["offsetsrc"] = offsetsrc if offsetsrc is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("orientation", None) self["orientation"] = orientation if orientation is not None else _v _v = arg.pop("outsidetextfont", None) self["outsidetextfont"] = outsidetextfont if outsidetextfont is not None else _v _v = arg.pop("r", None) self["r"] = r if r is not None else _v _v = arg.pop("rsrc", None) self["rsrc"] = rsrc if rsrc is not None else _v _v = arg.pop("selected", None) self["selected"] = selected if selected is not None else _v _v = arg.pop("selectedpoints", None) self["selectedpoints"] = selectedpoints if selectedpoints is not None else _v _v = arg.pop("showlegend", None) self["showlegend"] = showlegend if showlegend is not None else _v _v = arg.pop("stream", None) self["stream"] = stream if stream is not None else _v _v = arg.pop("t", None) self["t"] = t if t is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v _v = arg.pop("textangle", None) self["textangle"] = textangle if textangle is not None else _v _v = arg.pop("textfont", None) self["textfont"] = textfont if textfont is not None else _v _v = arg.pop("textposition", None) self["textposition"] = textposition if textposition is not None else _v _v = arg.pop("textpositionsrc", None) self["textpositionsrc"] = textpositionsrc if textpositionsrc is not None else _v _v = arg.pop("textsrc", None) self["textsrc"] = textsrc if textsrc is not None else _v _v = arg.pop("texttemplate", None) self["texttemplate"] = texttemplate if texttemplate is not None else _v _v = arg.pop("texttemplatesrc", None) self["texttemplatesrc"] = texttemplatesrc if texttemplatesrc is not None else _v _v = arg.pop("tsrc", None) self["tsrc"] = tsrc if tsrc is not None else _v _v = arg.pop("uid", None) self["uid"] = uid if uid is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("unselected", None) self["unselected"] = unselected if unselected is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v _v = arg.pop("widthsrc", None) self["widthsrc"] = widthsrc if widthsrc is not None else _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("x0", None) self["x0"] = x0 if x0 is not None else _v _v = arg.pop("xaxis", None) self["xaxis"] = xaxis if xaxis is not None else _v _v = arg.pop("xcalendar", None) self["xcalendar"] = xcalendar if xcalendar is not None else _v _v = arg.pop("xsrc", None) self["xsrc"] = xsrc if xsrc is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("y0", None) self["y0"] = y0 if y0 is not None else _v _v = arg.pop("yaxis", None) self["yaxis"] = yaxis if yaxis is not None else _v _v = arg.pop("ycalendar", None) self["ycalendar"] = ycalendar if ycalendar is not None else _v _v = arg.pop("ysrc", None) self["ysrc"] = ysrc if ysrc is not None else _v # Read-only literals # ------------------ from _plotly_utils.basevalidators import LiteralValidator self._props["type"] = "bar" self._validators["type"] = LiteralValidator( plotly_name="type", parent_name="bar", val="bar" ) arg.pop("type", None) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceType as _BaseTraceType import copy as _copy class Area(_BaseTraceType): # customdata # ---------- @property def customdata(self): """ Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements The 'customdata' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["customdata"] @customdata.setter def customdata(self, val): self["customdata"] = val # customdatasrc # ------------- @property def customdatasrc(self): """ Sets the source reference on plot.ly for customdata . The 'customdatasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["customdatasrc"] @customdatasrc.setter def customdatasrc(self, val): self["customdatasrc"] = val # hoverinfo # --------- @property def hoverinfo(self): """ Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. The 'hoverinfo' property is a flaglist and may be specified as a string containing: - Any combination of ['x', 'y', 'z', 'text', 'name'] joined with '+' characters (e.g. 'x+y') OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') - A list or array of the above Returns ------- Any|numpy.ndarray """ return self["hoverinfo"] @hoverinfo.setter def hoverinfo(self, val): self["hoverinfo"] = val # hoverinfosrc # ------------ @property def hoverinfosrc(self): """ Sets the source reference on plot.ly for hoverinfo . The 'hoverinfosrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hoverinfosrc"] @hoverinfosrc.setter def hoverinfosrc(self, val): self["hoverinfosrc"] = val # hoverlabel # ---------- @property def hoverlabel(self): """ The 'hoverlabel' property is an instance of Hoverlabel that may be specified as: - An instance of plotly.graph_objs.area.Hoverlabel - A dict of string/value properties that will be passed to the Hoverlabel constructor Supported dict properties: align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- plotly.graph_objs.area.Hoverlabel """ return self["hoverlabel"] @hoverlabel.setter def hoverlabel(self, val): self["hoverlabel"] = val # ids # --- @property def ids(self): """ Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. The 'ids' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ids"] @ids.setter def ids(self, val): self["ids"] = val # idssrc # ------ @property def idssrc(self): """ Sets the source reference on plot.ly for ids . The 'idssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["idssrc"] @idssrc.setter def idssrc(self, val): self["idssrc"] = val # legendgroup # ----------- @property def legendgroup(self): """ Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. The 'legendgroup' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["legendgroup"] @legendgroup.setter def legendgroup(self, val): self["legendgroup"] = val # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.area.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: color Area traces are deprecated! Please switch to the "barpolar" trace type. Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. colorsrc Sets the source reference on plot.ly for color . opacity Area traces are deprecated! Please switch to the "barpolar" trace type. Sets the marker opacity. opacitysrc Sets the source reference on plot.ly for opacity . size Area traces are deprecated! Please switch to the "barpolar" trace type. Sets the marker size (in px). sizesrc Sets the source reference on plot.ly for size . symbol Area traces are deprecated! Please switch to the "barpolar" trace type. Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot-open" to a symbol name. symbolsrc Sets the source reference on plot.ly for symbol . Returns ------- plotly.graph_objs.area.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # meta # ---- @property def meta(self): """ Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. The 'meta' property accepts values of any type Returns ------- Any|numpy.ndarray """ return self["meta"] @meta.setter def meta(self, val): self["meta"] = val # metasrc # ------- @property def metasrc(self): """ Sets the source reference on plot.ly for meta . The 'metasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["metasrc"] @metasrc.setter def metasrc(self, val): self["metasrc"] = val # name # ---- @property def name(self): """ Sets the trace name. The trace name appear as the legend item and on hover. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the trace. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # r # - @property def r(self): """ Area traces are deprecated! Please switch to the "barpolar" trace type. Sets the radial coordinates for legacy polar chart only. The 'r' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["r"] @r.setter def r(self, val): self["r"] = val # rsrc # ---- @property def rsrc(self): """ Sets the source reference on plot.ly for r . The 'rsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["rsrc"] @rsrc.setter def rsrc(self, val): self["rsrc"] = val # showlegend # ---------- @property def showlegend(self): """ Determines whether or not an item corresponding to this trace is shown in the legend. The 'showlegend' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showlegend"] @showlegend.setter def showlegend(self, val): self["showlegend"] = val # stream # ------ @property def stream(self): """ The 'stream' property is an instance of Stream that may be specified as: - An instance of plotly.graph_objs.area.Stream - A dict of string/value properties that will be passed to the Stream constructor Supported dict properties: maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- plotly.graph_objs.area.Stream """ return self["stream"] @stream.setter def stream(self, val): self["stream"] = val # t # - @property def t(self): """ Area traces are deprecated! Please switch to the "barpolar" trace type. Sets the angular coordinates for legacy polar chart only. The 't' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["t"] @t.setter def t(self, val): self["t"] = val # tsrc # ---- @property def tsrc(self): """ Sets the source reference on plot.ly for t . The 'tsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tsrc"] @tsrc.setter def tsrc(self, val): self["tsrc"] = val # uid # --- @property def uid(self): """ Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. The 'uid' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["uid"] @uid.setter def uid(self, val): self["uid"] = val # uirevision # ---------- @property def uirevision(self): """ Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # visible # ------- @property def visible(self): """ Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). The 'visible' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'legendonly'] Returns ------- Any """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # type # ---- @property def type(self): return self._props["type"] # property parent name # -------------------- @property def _parent_path_str(self): return "" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.area.Hoverlabel instance or dict with compatible properties ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. marker plotly.graph_objects.area.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. r Area traces are deprecated! Please switch to the "barpolar" trace type. Sets the radial coordinates for legacy polar chart only. rsrc Sets the source reference on plot.ly for r . showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.area.Stream instance or dict with compatible properties t Area traces are deprecated! Please switch to the "barpolar" trace type. Sets the angular coordinates for legacy polar chart only. tsrc Sets the source reference on plot.ly for t . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). """ def __init__( self, arg=None, customdata=None, customdatasrc=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, ids=None, idssrc=None, legendgroup=None, marker=None, meta=None, metasrc=None, name=None, opacity=None, r=None, rsrc=None, showlegend=None, stream=None, t=None, tsrc=None, uid=None, uirevision=None, visible=None, **kwargs ): """ Construct a new Area object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.Area customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.area.Hoverlabel instance or dict with compatible properties ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. marker plotly.graph_objects.area.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. r Area traces are deprecated! Please switch to the "barpolar" trace type. Sets the radial coordinates for legacy polar chart only. rsrc Sets the source reference on plot.ly for r . showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.area.Stream instance or dict with compatible properties t Area traces are deprecated! Please switch to the "barpolar" trace type. Sets the angular coordinates for legacy polar chart only. tsrc Sets the source reference on plot.ly for t . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). Returns ------- Area """ super(Area, self).__init__("area") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.Area constructor must be a dict or an instance of plotly.graph_objs.Area""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators import area as v_area # Initialize validators # --------------------- self._validators["customdata"] = v_area.CustomdataValidator() self._validators["customdatasrc"] = v_area.CustomdatasrcValidator() self._validators["hoverinfo"] = v_area.HoverinfoValidator() self._validators["hoverinfosrc"] = v_area.HoverinfosrcValidator() self._validators["hoverlabel"] = v_area.HoverlabelValidator() self._validators["ids"] = v_area.IdsValidator() self._validators["idssrc"] = v_area.IdssrcValidator() self._validators["legendgroup"] = v_area.LegendgroupValidator() self._validators["marker"] = v_area.MarkerValidator() self._validators["meta"] = v_area.MetaValidator() self._validators["metasrc"] = v_area.MetasrcValidator() self._validators["name"] = v_area.NameValidator() self._validators["opacity"] = v_area.OpacityValidator() self._validators["r"] = v_area.RValidator() self._validators["rsrc"] = v_area.RsrcValidator() self._validators["showlegend"] = v_area.ShowlegendValidator() self._validators["stream"] = v_area.StreamValidator() self._validators["t"] = v_area.TValidator() self._validators["tsrc"] = v_area.TsrcValidator() self._validators["uid"] = v_area.UidValidator() self._validators["uirevision"] = v_area.UirevisionValidator() self._validators["visible"] = v_area.VisibleValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("customdata", None) self["customdata"] = customdata if customdata is not None else _v _v = arg.pop("customdatasrc", None) self["customdatasrc"] = customdatasrc if customdatasrc is not None else _v _v = arg.pop("hoverinfo", None) self["hoverinfo"] = hoverinfo if hoverinfo is not None else _v _v = arg.pop("hoverinfosrc", None) self["hoverinfosrc"] = hoverinfosrc if hoverinfosrc is not None else _v _v = arg.pop("hoverlabel", None) self["hoverlabel"] = hoverlabel if hoverlabel is not None else _v _v = arg.pop("ids", None) self["ids"] = ids if ids is not None else _v _v = arg.pop("idssrc", None) self["idssrc"] = idssrc if idssrc is not None else _v _v = arg.pop("legendgroup", None) self["legendgroup"] = legendgroup if legendgroup is not None else _v _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v _v = arg.pop("meta", None) self["meta"] = meta if meta is not None else _v _v = arg.pop("metasrc", None) self["metasrc"] = metasrc if metasrc is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("r", None) self["r"] = r if r is not None else _v _v = arg.pop("rsrc", None) self["rsrc"] = rsrc if rsrc is not None else _v _v = arg.pop("showlegend", None) self["showlegend"] = showlegend if showlegend is not None else _v _v = arg.pop("stream", None) self["stream"] = stream if stream is not None else _v _v = arg.pop("t", None) self["t"] = t if t is not None else _v _v = arg.pop("tsrc", None) self["tsrc"] = tsrc if tsrc is not None else _v _v = arg.pop("uid", None) self["uid"] = uid if uid is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v # Read-only literals # ------------------ from _plotly_utils.basevalidators import LiteralValidator self._props["type"] = "area" self._validators["type"] = LiteralValidator( plotly_name="type", parent_name="area", val="area" ) arg.pop("type", None) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseLayoutType as _BaseLayoutType import copy as _copy class Layout(_BaseLayoutType): _subplotid_prop_names = [ "coloraxis", "geo", "mapbox", "polar", "scene", "ternary", "xaxis", "yaxis", ] import re _subplotid_prop_re = re.compile("^(" + "|".join(_subplotid_prop_names) + ")(\d+)$") @property def _subplotid_validators(self): """ dict of validator classes for each subplot type Returns ------- dict """ from plotly.validators.layout import ( ColoraxisValidator, GeoValidator, MapboxValidator, PolarValidator, SceneValidator, TernaryValidator, XAxisValidator, YAxisValidator, ) return { "coloraxis": ColoraxisValidator, "geo": GeoValidator, "mapbox": MapboxValidator, "polar": PolarValidator, "scene": SceneValidator, "ternary": TernaryValidator, "xaxis": XAxisValidator, "yaxis": YAxisValidator, } def _subplot_re_match(self, prop): return self._subplotid_prop_re.match(prop) # angularaxis # ----------- @property def angularaxis(self): """ The 'angularaxis' property is an instance of AngularAxis that may be specified as: - An instance of plotly.graph_objs.layout.AngularAxis - A dict of string/value properties that will be passed to the AngularAxis constructor Supported dict properties: domain Polar chart subplots are not supported yet. This key has currently no effect. endpadding Legacy polar charts are deprecated! Please switch to "polar" subplots. range Legacy polar charts are deprecated! Please switch to "polar" subplots. Defines the start and end point of this angular axis. showline Legacy polar charts are deprecated! Please switch to "polar" subplots. Determines whether or not the line bounding this angular axis will be shown on the figure. showticklabels Legacy polar charts are deprecated! Please switch to "polar" subplots. Determines whether or not the angular axis ticks will feature tick labels. tickcolor Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the color of the tick lines on this angular axis. ticklen Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the length of the tick lines on this angular axis. tickorientation Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the orientation (from the paper perspective) of the angular axis tick labels. ticksuffix Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the length of the tick lines on this angular axis. visible Legacy polar charts are deprecated! Please switch to "polar" subplots. Determines whether or not this axis will be visible. Returns ------- plotly.graph_objs.layout.AngularAxis """ return self["angularaxis"] @angularaxis.setter def angularaxis(self, val): self["angularaxis"] = val # annotations # ----------- @property def annotations(self): """ The 'annotations' property is a tuple of instances of Annotation that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.Annotation - A list or tuple of dicts of string/value properties that will be passed to the Annotation constructor Supported dict properties: align Sets the horizontal alignment of the `text` within the box. Has an effect only if `text` spans more two or more lines (i.e. `text` contains one or more
HTML tags) or if an explicit width is set to override the text width. arrowcolor Sets the color of the annotation arrow. arrowhead Sets the end annotation arrow head style. arrowside Sets the annotation arrow head position. arrowsize Sets the size of the end annotation arrow head, relative to `arrowwidth`. A value of 1 (default) gives a head about 3x as wide as the line. arrowwidth Sets the width (in px) of annotation arrow line. ax Sets the x component of the arrow tail about the arrow head. If `axref` is `pixel`, a positive (negative) component corresponds to an arrow pointing from right to left (left to right). If `axref` is an axis, this is an absolute value on that axis, like `x`, NOT a relative value. axref Indicates in what terms the tail of the annotation (ax,ay) is specified. If `pixel`, `ax` is a relative offset in pixels from `x`. If set to an x axis id (e.g. "x" or "x2"), `ax` is specified in the same terms as that axis. This is useful for trendline annotations which should continue to indicate the correct trend when zoomed. ay Sets the y component of the arrow tail about the arrow head. If `ayref` is `pixel`, a positive (negative) component corresponds to an arrow pointing from bottom to top (top to bottom). If `ayref` is an axis, this is an absolute value on that axis, like `y`, NOT a relative value. ayref Indicates in what terms the tail of the annotation (ax,ay) is specified. If `pixel`, `ay` is a relative offset in pixels from `y`. If set to a y axis id (e.g. "y" or "y2"), `ay` is specified in the same terms as that axis. This is useful for trendline annotations which should continue to indicate the correct trend when zoomed. bgcolor Sets the background color of the annotation. bordercolor Sets the color of the border enclosing the annotation `text`. borderpad Sets the padding (in px) between the `text` and the enclosing border. borderwidth Sets the width (in px) of the border enclosing the annotation `text`. captureevents Determines whether the annotation text box captures mouse move and click events, or allows those events to pass through to data points in the plot that may be behind the annotation. By default `captureevents` is False unless `hovertext` is provided. If you use the event `plotly_clickannotation` without `hovertext` you must explicitly enable `captureevents`. clicktoshow Makes this annotation respond to clicks on the plot. If you click a data point that exactly matches the `x` and `y` values of this annotation, and it is hidden (visible: false), it will appear. In "onoff" mode, you must click the same point again to make it disappear, so if you click multiple points, you can show multiple annotations. In "onout" mode, a click anywhere else in the plot (on another data point or not) will hide this annotation. If you need to show/hide this annotation in response to different `x` or `y` values, you can set `xclick` and/or `yclick`. This is useful for example to label the side of a bar. To label markers though, `standoff` is preferred over `xclick` and `yclick`. font Sets the annotation text font. height Sets an explicit height for the text box. null (default) lets the text set the box height. Taller text will be clipped. hoverlabel plotly.graph_objects.layout.annotation.Hoverlab el instance or dict with compatible properties hovertext Sets text to appear when hovering over this annotation. If omitted or blank, no hover label will appear. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. opacity Sets the opacity of the annotation (text + arrow). showarrow Determines whether or not the annotation is drawn with an arrow. If True, `text` is placed near the arrow's tail. If False, `text` lines up with the `x` and `y` provided. standoff Sets a distance, in pixels, to move the end arrowhead away from the position it is pointing at, for example to point at the edge of a marker independent of zoom. Note that this shortens the arrow from the `ax` / `ay` vector, in contrast to `xshift` / `yshift` which moves everything by this amount. startarrowhead Sets the start annotation arrow head style. startarrowsize Sets the size of the start annotation arrow head, relative to `arrowwidth`. A value of 1 (default) gives a head about 3x as wide as the line. startstandoff Sets a distance, in pixels, to move the start arrowhead away from the position it is pointing at, for example to point at the edge of a marker independent of zoom. Note that this shortens the arrow from the `ax` / `ay` vector, in contrast to `xshift` / `yshift` which moves everything by this amount. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. text Sets the text associated with this annotation. Plotly uses a subset of HTML tags to do things like newline (
), bold (), italics (), hyperlinks (). Tags , , are also supported. textangle Sets the angle at which the `text` is drawn with respect to the horizontal. valign Sets the vertical alignment of the `text` within the box. Has an effect only if an explicit height is set to override the text height. visible Determines whether or not this annotation is visible. width Sets an explicit width for the text box. null (default) lets the text set the box width. Wider text will be clipped. There is no automatic wrapping; use
to start a new line. x Sets the annotation's x position. If the axis `type` is "log", then you must take the log of your desired range. If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. xanchor Sets the text box's horizontal position anchor This anchor binds the `x` position to the "left", "center" or "right" of the annotation. For example, if `x` is set to 1, `xref` to "paper" and `xanchor` to "right" then the right-most portion of the annotation lines up with the right-most edge of the plotting area. If "auto", the anchor is equivalent to "center" for data-referenced annotations or if there is an arrow, whereas for paper-referenced with no arrow, the anchor picked corresponds to the closest side. xclick Toggle this annotation when clicking a data point whose `x` value is `xclick` rather than the annotation's `x` value. xref Sets the annotation's x coordinate axis. If set to an x axis id (e.g. "x" or "x2"), the `x` position refers to an x coordinate If set to "paper", the `x` position refers to the distance from the left side of the plotting area in normalized coordinates where 0 (1) corresponds to the left (right) side. xshift Shifts the position of the whole annotation and arrow to the right (positive) or left (negative) by this many pixels. y Sets the annotation's y position. If the axis `type` is "log", then you must take the log of your desired range. If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. yanchor Sets the text box's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the annotation. For example, if `y` is set to 1, `yref` to "paper" and `yanchor` to "top" then the top- most portion of the annotation lines up with the top-most edge of the plotting area. If "auto", the anchor is equivalent to "middle" for data-referenced annotations or if there is an arrow, whereas for paper-referenced with no arrow, the anchor picked corresponds to the closest side. yclick Toggle this annotation when clicking a data point whose `y` value is `yclick` rather than the annotation's `y` value. yref Sets the annotation's y coordinate axis. If set to an y axis id (e.g. "y" or "y2"), the `y` position refers to an y coordinate If set to "paper", the `y` position refers to the distance from the bottom of the plotting area in normalized coordinates where 0 (1) corresponds to the bottom (top). yshift Shifts the position of the whole annotation and arrow up (positive) or down (negative) by this many pixels. Returns ------- tuple[plotly.graph_objs.layout.Annotation] """ return self["annotations"] @annotations.setter def annotations(self, val): self["annotations"] = val # annotationdefaults # ------------------ @property def annotationdefaults(self): """ When used in a template (as layout.template.layout.annotationdefaults), sets the default property values to use for elements of layout.annotations The 'annotationdefaults' property is an instance of Annotation that may be specified as: - An instance of plotly.graph_objs.layout.Annotation - A dict of string/value properties that will be passed to the Annotation constructor Supported dict properties: Returns ------- plotly.graph_objs.layout.Annotation """ return self["annotationdefaults"] @annotationdefaults.setter def annotationdefaults(self, val): self["annotationdefaults"] = val # autosize # -------- @property def autosize(self): """ Determines whether or not a layout width or height that has been left undefined by the user is initialized on each relayout. Note that, regardless of this attribute, an undefined layout width or height is always initialized on the first call to plot. The 'autosize' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autosize"] @autosize.setter def autosize(self, val): self["autosize"] = val # bargap # ------ @property def bargap(self): """ Sets the gap (in plot fraction) between bars of adjacent location coordinates. The 'bargap' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["bargap"] @bargap.setter def bargap(self, val): self["bargap"] = val # bargroupgap # ----------- @property def bargroupgap(self): """ Sets the gap (in plot fraction) between bars of the same location coordinate. The 'bargroupgap' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["bargroupgap"] @bargroupgap.setter def bargroupgap(self, val): self["bargroupgap"] = val # barmode # ------- @property def barmode(self): """ Determines how bars at the same location coordinate are displayed on the graph. With "stack", the bars are stacked on top of one another With "relative", the bars are stacked on top of one another, with negative values below the axis, positive values above With "group", the bars are plotted next to one another centered around the shared location. With "overlay", the bars are plotted over one another, you might need to an "opacity" to see multiple bars. The 'barmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['stack', 'group', 'overlay', 'relative'] Returns ------- Any """ return self["barmode"] @barmode.setter def barmode(self, val): self["barmode"] = val # barnorm # ------- @property def barnorm(self): """ Sets the normalization for bar traces on the graph. With "fraction", the value of each bar is divided by the sum of all values at that location coordinate. "percent" is the same but multiplied by 100 to show percentages. The 'barnorm' property is an enumeration that may be specified as: - One of the following enumeration values: ['', 'fraction', 'percent'] Returns ------- Any """ return self["barnorm"] @barnorm.setter def barnorm(self, val): self["barnorm"] = val # boxgap # ------ @property def boxgap(self): """ Sets the gap (in plot fraction) between boxes of adjacent location coordinates. Has no effect on traces that have "width" set. The 'boxgap' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["boxgap"] @boxgap.setter def boxgap(self, val): self["boxgap"] = val # boxgroupgap # ----------- @property def boxgroupgap(self): """ Sets the gap (in plot fraction) between boxes of the same location coordinate. Has no effect on traces that have "width" set. The 'boxgroupgap' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["boxgroupgap"] @boxgroupgap.setter def boxgroupgap(self, val): self["boxgroupgap"] = val # boxmode # ------- @property def boxmode(self): """ Determines how boxes at the same location coordinate are displayed on the graph. If "group", the boxes are plotted next to one another centered around the shared location. If "overlay", the boxes are plotted over one another, you might need to set "opacity" to see them multiple boxes. Has no effect on traces that have "width" set. The 'boxmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['group', 'overlay'] Returns ------- Any """ return self["boxmode"] @boxmode.setter def boxmode(self, val): self["boxmode"] = val # calendar # -------- @property def calendar(self): """ Sets the default calendar system to use for interpreting and displaying dates throughout the plot. The 'calendar' property is an enumeration that may be specified as: - One of the following enumeration values: ['gregorian', 'chinese', 'coptic', 'discworld', 'ethiopian', 'hebrew', 'islamic', 'julian', 'mayan', 'nanakshahi', 'nepali', 'persian', 'jalali', 'taiwan', 'thai', 'ummalqura'] Returns ------- Any """ return self["calendar"] @calendar.setter def calendar(self, val): self["calendar"] = val # clickmode # --------- @property def clickmode(self): """ Determines the mode of single click interactions. "event" is the default value and emits the `plotly_click` event. In addition this mode emits the `plotly_selected` event in drag modes "lasso" and "select", but with no event data attached (kept for compatibility reasons). The "select" flag enables selecting single data points via click. This mode also supports persistent selections, meaning that pressing Shift while clicking, adds to / subtracts from an existing selection. "select" with `hovermode`: "x" can be confusing, consider explicitly setting `hovermode`: "closest" when using this feature. Selection events are sent accordingly as long as "event" flag is set as well. When the "event" flag is missing, `plotly_click` and `plotly_selected` events are not fired. The 'clickmode' property is a flaglist and may be specified as a string containing: - Any combination of ['event', 'select'] joined with '+' characters (e.g. 'event+select') OR exactly one of ['none'] (e.g. 'none') Returns ------- Any """ return self["clickmode"] @clickmode.setter def clickmode(self, val): self["clickmode"] = val # coloraxis # --------- @property def coloraxis(self): """ The 'coloraxis' property is an instance of Coloraxis that may be specified as: - An instance of plotly.graph_objs.layout.Coloraxis - A dict of string/value properties that will be passed to the Coloraxis constructor Supported dict properties: autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here corresponding trace color array(s)) or the bounds set in `cmin` and `cmax` Defaults to `false` when `cmin` and `cmax` are set by the user. cmax Sets the upper bound of the color domain. Value should have the same units as corresponding trace color array(s) and if set, `cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `cmin` and/or `cmax` to be equidistant to this point. Value should have the same units as corresponding trace color array(s). Has no effect when `cauto` is `false`. cmin Sets the lower bound of the color domain. Value should have the same units as corresponding trace color array(s) and if set, `cmax` must be set as well. colorbar plotly.graph_objects.layout.coloraxis.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`cmin` and `cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Grey s,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Blues, Picnic,Rainbow,Portland,Jet,Hot,Blackbody,Earth ,Electric,Viridis,Cividis. reversescale Reverses the color mapping if true. If true, `cmin` will correspond to the last color in the array and `cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Returns ------- plotly.graph_objs.layout.Coloraxis """ return self["coloraxis"] @coloraxis.setter def coloraxis(self, val): self["coloraxis"] = val # colorscale # ---------- @property def colorscale(self): """ The 'colorscale' property is an instance of Colorscale that may be specified as: - An instance of plotly.graph_objs.layout.Colorscale - A dict of string/value properties that will be passed to the Colorscale constructor Supported dict properties: diverging Sets the default diverging colorscale. Note that `autocolorscale` must be true for this attribute to work. sequential Sets the default sequential colorscale for positive values. Note that `autocolorscale` must be true for this attribute to work. sequentialminus Sets the default sequential colorscale for negative values. Note that `autocolorscale` must be true for this attribute to work. Returns ------- plotly.graph_objs.layout.Colorscale """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # colorway # -------- @property def colorway(self): """ Sets the default trace colors. The 'colorway' property is a colorlist that may be specified as a tuple, list, one-dimensional numpy array, or pandas Series of valid color strings Returns ------- list """ return self["colorway"] @colorway.setter def colorway(self, val): self["colorway"] = val # datarevision # ------------ @property def datarevision(self): """ If provided, a changed value tells `Plotly.react` that one or more data arrays has changed. This way you can modify arrays in-place rather than making a complete new copy for an incremental change. If NOT provided, `Plotly.react` assumes that data arrays are being treated as immutable, thus any data array with a different identity from its predecessor contains new data. The 'datarevision' property accepts values of any type Returns ------- Any """ return self["datarevision"] @datarevision.setter def datarevision(self, val): self["datarevision"] = val # direction # --------- @property def direction(self): """ Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the direction corresponding to positive angles in legacy polar charts. The 'direction' property is an enumeration that may be specified as: - One of the following enumeration values: ['clockwise', 'counterclockwise'] Returns ------- Any """ return self["direction"] @direction.setter def direction(self, val): self["direction"] = val # dragmode # -------- @property def dragmode(self): """ Determines the mode of drag interactions. "select" and "lasso" apply only to scatter traces with markers or text. "orbit" and "turntable" apply only to 3D scenes. The 'dragmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['zoom', 'pan', 'select', 'lasso', 'orbit', 'turntable', False] Returns ------- Any """ return self["dragmode"] @dragmode.setter def dragmode(self, val): self["dragmode"] = val # editrevision # ------------ @property def editrevision(self): """ Controls persistence of user-driven changes in `editable: true` configuration, other than trace names and axis titles. Defaults to `layout.uirevision`. The 'editrevision' property accepts values of any type Returns ------- Any """ return self["editrevision"] @editrevision.setter def editrevision(self, val): self["editrevision"] = val # extendfunnelareacolors # ---------------------- @property def extendfunnelareacolors(self): """ If `true`, the funnelarea slice colors (whether given by `funnelareacolorway` or inherited from `colorway`) will be extended to three times its original length by first repeating every color 20% lighter then each color 20% darker. This is intended to reduce the likelihood of reusing the same color when you have many slices, but you can set `false` to disable. Colors provided in the trace, using `marker.colors`, are never extended. The 'extendfunnelareacolors' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["extendfunnelareacolors"] @extendfunnelareacolors.setter def extendfunnelareacolors(self, val): self["extendfunnelareacolors"] = val # extendpiecolors # --------------- @property def extendpiecolors(self): """ If `true`, the pie slice colors (whether given by `piecolorway` or inherited from `colorway`) will be extended to three times its original length by first repeating every color 20% lighter then each color 20% darker. This is intended to reduce the likelihood of reusing the same color when you have many slices, but you can set `false` to disable. Colors provided in the trace, using `marker.colors`, are never extended. The 'extendpiecolors' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["extendpiecolors"] @extendpiecolors.setter def extendpiecolors(self, val): self["extendpiecolors"] = val # extendsunburstcolors # -------------------- @property def extendsunburstcolors(self): """ If `true`, the sunburst slice colors (whether given by `sunburstcolorway` or inherited from `colorway`) will be extended to three times its original length by first repeating every color 20% lighter then each color 20% darker. This is intended to reduce the likelihood of reusing the same color when you have many slices, but you can set `false` to disable. Colors provided in the trace, using `marker.colors`, are never extended. The 'extendsunburstcolors' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["extendsunburstcolors"] @extendsunburstcolors.setter def extendsunburstcolors(self, val): self["extendsunburstcolors"] = val # extendtreemapcolors # ------------------- @property def extendtreemapcolors(self): """ If `true`, the treemap slice colors (whether given by `treemapcolorway` or inherited from `colorway`) will be extended to three times its original length by first repeating every color 20% lighter then each color 20% darker. This is intended to reduce the likelihood of reusing the same color when you have many slices, but you can set `false` to disable. Colors provided in the trace, using `marker.colors`, are never extended. The 'extendtreemapcolors' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["extendtreemapcolors"] @extendtreemapcolors.setter def extendtreemapcolors(self, val): self["extendtreemapcolors"] = val # font # ---- @property def font(self): """ Sets the global font. Note that fonts used in traces and other layout components inherit from the global font. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.layout.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.layout.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # funnelareacolorway # ------------------ @property def funnelareacolorway(self): """ Sets the default funnelarea slice colors. Defaults to the main `colorway` used for trace colors. If you specify a new list here it can still be extended with lighter and darker colors, see `extendfunnelareacolors`. The 'funnelareacolorway' property is a colorlist that may be specified as a tuple, list, one-dimensional numpy array, or pandas Series of valid color strings Returns ------- list """ return self["funnelareacolorway"] @funnelareacolorway.setter def funnelareacolorway(self, val): self["funnelareacolorway"] = val # funnelgap # --------- @property def funnelgap(self): """ Sets the gap (in plot fraction) between bars of adjacent location coordinates. The 'funnelgap' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["funnelgap"] @funnelgap.setter def funnelgap(self, val): self["funnelgap"] = val # funnelgroupgap # -------------- @property def funnelgroupgap(self): """ Sets the gap (in plot fraction) between bars of the same location coordinate. The 'funnelgroupgap' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["funnelgroupgap"] @funnelgroupgap.setter def funnelgroupgap(self, val): self["funnelgroupgap"] = val # funnelmode # ---------- @property def funnelmode(self): """ Determines how bars at the same location coordinate are displayed on the graph. With "stack", the bars are stacked on top of one another With "group", the bars are plotted next to one another centered around the shared location. With "overlay", the bars are plotted over one another, you might need to an "opacity" to see multiple bars. The 'funnelmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['stack', 'group', 'overlay'] Returns ------- Any """ return self["funnelmode"] @funnelmode.setter def funnelmode(self, val): self["funnelmode"] = val # geo # --- @property def geo(self): """ The 'geo' property is an instance of Geo that may be specified as: - An instance of plotly.graph_objs.layout.Geo - A dict of string/value properties that will be passed to the Geo constructor Supported dict properties: bgcolor Set the background color of the map center plotly.graph_objects.layout.geo.Center instance or dict with compatible properties coastlinecolor Sets the coastline color. coastlinewidth Sets the coastline stroke width (in px). countrycolor Sets line color of the country boundaries. countrywidth Sets line width (in px) of the country boundaries. domain plotly.graph_objects.layout.geo.Domain instance or dict with compatible properties framecolor Sets the color the frame. framewidth Sets the stroke width (in px) of the frame. lakecolor Sets the color of the lakes. landcolor Sets the land mass color. lataxis plotly.graph_objects.layout.geo.Lataxis instance or dict with compatible properties lonaxis plotly.graph_objects.layout.geo.Lonaxis instance or dict with compatible properties oceancolor Sets the ocean color projection plotly.graph_objects.layout.geo.Projection instance or dict with compatible properties resolution Sets the resolution of the base layers. The values have units of km/mm e.g. 110 corresponds to a scale ratio of 1:110,000,000. rivercolor Sets color of the rivers. riverwidth Sets the stroke width (in px) of the rivers. scope Set the scope of the map. showcoastlines Sets whether or not the coastlines are drawn. showcountries Sets whether or not country boundaries are drawn. showframe Sets whether or not a frame is drawn around the map. showlakes Sets whether or not lakes are drawn. showland Sets whether or not land masses are filled in color. showocean Sets whether or not oceans are filled in color. showrivers Sets whether or not rivers are drawn. showsubunits Sets whether or not boundaries of subunits within countries (e.g. states, provinces) are drawn. subunitcolor Sets the color of the subunits boundaries. subunitwidth Sets the stroke width (in px) of the subunits boundaries. uirevision Controls persistence of user-driven changes in the view (projection and center). Defaults to `layout.uirevision`. Returns ------- plotly.graph_objs.layout.Geo """ return self["geo"] @geo.setter def geo(self, val): self["geo"] = val # grid # ---- @property def grid(self): """ The 'grid' property is an instance of Grid that may be specified as: - An instance of plotly.graph_objs.layout.Grid - A dict of string/value properties that will be passed to the Grid constructor Supported dict properties: columns The number of columns in the grid. If you provide a 2D `subplots` array, the length of its longest row is used as the default. If you give an `xaxes` array, its length is used as the default. But it's also possible to have a different length, if you want to leave a row at the end for non-cartesian subplots. domain plotly.graph_objects.layout.grid.Domain instance or dict with compatible properties pattern If no `subplots`, `xaxes`, or `yaxes` are given but we do have `rows` and `columns`, we can generate defaults using consecutive axis IDs, in two ways: "coupled" gives one x axis per column and one y axis per row. "independent" uses a new xy pair for each cell, left-to-right across each row then iterating rows according to `roworder`. roworder Is the first row the top or the bottom? Note that columns are always enumerated from left to right. rows The number of rows in the grid. If you provide a 2D `subplots` array or a `yaxes` array, its length is used as the default. But it's also possible to have a different length, if you want to leave a row at the end for non- cartesian subplots. subplots Used for freeform grids, where some axes may be shared across subplots but others are not. Each entry should be a cartesian subplot id, like "xy" or "x3y2", or "" to leave that cell empty. You may reuse x axes within the same column, and y axes within the same row. Non-cartesian subplots and traces that support `domain` can place themselves in this grid separately using the `gridcell` attribute. xaxes Used with `yaxes` when the x and y axes are shared across columns and rows. Each entry should be an x axis id like "x", "x2", etc., or "" to not put an x axis in that column. Entries other than "" must be unique. Ignored if `subplots` is present. If missing but `yaxes` is present, will generate consecutive IDs. xgap Horizontal space between grid cells, expressed as a fraction of the total width available to one cell. Defaults to 0.1 for coupled-axes grids and 0.2 for independent grids. xside Sets where the x axis labels and titles go. "bottom" means the very bottom of the grid. "bottom plot" is the lowest plot that each x axis is used in. "top" and "top plot" are similar. yaxes Used with `yaxes` when the x and y axes are shared across columns and rows. Each entry should be an y axis id like "y", "y2", etc., or "" to not put a y axis in that row. Entries other than "" must be unique. Ignored if `subplots` is present. If missing but `xaxes` is present, will generate consecutive IDs. ygap Vertical space between grid cells, expressed as a fraction of the total height available to one cell. Defaults to 0.1 for coupled-axes grids and 0.3 for independent grids. yside Sets where the y axis labels and titles go. "left" means the very left edge of the grid. *left plot* is the leftmost plot that each y axis is used in. "right" and *right plot* are similar. Returns ------- plotly.graph_objs.layout.Grid """ return self["grid"] @grid.setter def grid(self, val): self["grid"] = val # height # ------ @property def height(self): """ Sets the plot's height (in px). The 'height' property is a number and may be specified as: - An int or float in the interval [10, inf] Returns ------- int|float """ return self["height"] @height.setter def height(self, val): self["height"] = val # hiddenlabels # ------------ @property def hiddenlabels(self): """ hiddenlabels is the funnelarea & pie chart analog of visible:'legendonly' but it can contain many labels, and can simultaneously hide slices from several pies/funnelarea charts The 'hiddenlabels' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["hiddenlabels"] @hiddenlabels.setter def hiddenlabels(self, val): self["hiddenlabels"] = val # hiddenlabelssrc # --------------- @property def hiddenlabelssrc(self): """ Sets the source reference on plot.ly for hiddenlabels . The 'hiddenlabelssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["hiddenlabelssrc"] @hiddenlabelssrc.setter def hiddenlabelssrc(self, val): self["hiddenlabelssrc"] = val # hidesources # ----------- @property def hidesources(self): """ Determines whether or not a text link citing the data source is placed at the bottom-right cored of the figure. Has only an effect only on graphs that have been generated via forked graphs from the plotly service (at https://plot.ly or on- premise). The 'hidesources' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["hidesources"] @hidesources.setter def hidesources(self, val): self["hidesources"] = val # hoverdistance # ------------- @property def hoverdistance(self): """ Sets the default distance (in pixels) to look for data to add hover labels (-1 means no cutoff, 0 means no looking for data). This is only a real distance for hovering on point-like objects, like scatter points. For area-like objects (bars, scatter fills, etc) hovering is on inside the area and off outside, but these objects will not supersede hover on point- like objects in case of conflict. The 'hoverdistance' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [-1, 9223372036854775807] Returns ------- int """ return self["hoverdistance"] @hoverdistance.setter def hoverdistance(self, val): self["hoverdistance"] = val # hoverlabel # ---------- @property def hoverlabel(self): """ The 'hoverlabel' property is an instance of Hoverlabel that may be specified as: - An instance of plotly.graph_objs.layout.Hoverlabel - A dict of string/value properties that will be passed to the Hoverlabel constructor Supported dict properties: align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines bgcolor Sets the background color of all hover labels on graph bordercolor Sets the border color of all hover labels on graph. font Sets the default hover label font used by all traces on the graph. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. Returns ------- plotly.graph_objs.layout.Hoverlabel """ return self["hoverlabel"] @hoverlabel.setter def hoverlabel(self, val): self["hoverlabel"] = val # hovermode # --------- @property def hovermode(self): """ Determines the mode of hover interactions. If `clickmode` includes the "select" flag, `hovermode` defaults to "closest". If `clickmode` lacks the "select" flag, it defaults to "x" or "y" (depending on the trace's `orientation` value) for plots based on cartesian coordinates. For anything else the default value is "closest". The 'hovermode' property is an enumeration that may be specified as: - One of the following enumeration values: ['x', 'y', 'closest', False] Returns ------- Any """ return self["hovermode"] @hovermode.setter def hovermode(self, val): self["hovermode"] = val # images # ------ @property def images(self): """ The 'images' property is a tuple of instances of Image that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.Image - A list or tuple of dicts of string/value properties that will be passed to the Image constructor Supported dict properties: layer Specifies whether images are drawn below or above traces. When `xref` and `yref` are both set to `paper`, image is drawn below the entire plot area. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. opacity Sets the opacity of the image. sizex Sets the image container size horizontally. The image will be sized based on the `position` value. When `xref` is set to `paper`, units are sized relative to the plot width. sizey Sets the image container size vertically. The image will be sized based on the `position` value. When `yref` is set to `paper`, units are sized relative to the plot height. sizing Specifies which dimension of the image to constrain. source Specifies the URL of the image to be used. The URL must be accessible from the domain where the plot code is run, and can be either relative or absolute. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. visible Determines whether or not this image is visible. x Sets the image's x position. When `xref` is set to `paper`, units are sized relative to the plot height. See `xref` for more info xanchor Sets the anchor for the x position xref Sets the images's x coordinate axis. If set to a x axis id (e.g. "x" or "x2"), the `x` position refers to an x data coordinate If set to "paper", the `x` position refers to the distance from the left of plot in normalized coordinates where 0 (1) corresponds to the left (right). y Sets the image's y position. When `yref` is set to `paper`, units are sized relative to the plot height. See `yref` for more info yanchor Sets the anchor for the y position. yref Sets the images's y coordinate axis. If set to a y axis id (e.g. "y" or "y2"), the `y` position refers to a y data coordinate. If set to "paper", the `y` position refers to the distance from the bottom of the plot in normalized coordinates where 0 (1) corresponds to the bottom (top). Returns ------- tuple[plotly.graph_objs.layout.Image] """ return self["images"] @images.setter def images(self, val): self["images"] = val # imagedefaults # ------------- @property def imagedefaults(self): """ When used in a template (as layout.template.layout.imagedefaults), sets the default property values to use for elements of layout.images The 'imagedefaults' property is an instance of Image that may be specified as: - An instance of plotly.graph_objs.layout.Image - A dict of string/value properties that will be passed to the Image constructor Supported dict properties: Returns ------- plotly.graph_objs.layout.Image """ return self["imagedefaults"] @imagedefaults.setter def imagedefaults(self, val): self["imagedefaults"] = val # legend # ------ @property def legend(self): """ The 'legend' property is an instance of Legend that may be specified as: - An instance of plotly.graph_objs.layout.Legend - A dict of string/value properties that will be passed to the Legend constructor Supported dict properties: bgcolor Sets the legend background color. Defaults to `layout.paper_bgcolor`. bordercolor Sets the color of the border enclosing the legend. borderwidth Sets the width (in px) of the border enclosing the legend. font Sets the font used to text the legend items. itemclick Determines the behavior on legend item click. "toggle" toggles the visibility of the item clicked on the graph. "toggleothers" makes the clicked item the sole visible item on the graph. False disable legend item click interactions. itemdoubleclick Determines the behavior on legend item double- click. "toggle" toggles the visibility of the item clicked on the graph. "toggleothers" makes the clicked item the sole visible item on the graph. False disable legend item double-click interactions. itemsizing Determines if the legend items symbols scale with their corresponding "trace" attributes or remain "constant" independent of the symbol size on the graph. orientation Sets the orientation of the legend. tracegroupgap Sets the amount of vertical space (in px) between legend groups. traceorder Determines the order at which the legend items are displayed. If "normal", the items are displayed top-to-bottom in the same order as the input data. If "reversed", the items are displayed in the opposite order as "normal". If "grouped", the items are displayed in groups (when a trace `legendgroup` is provided). if "grouped+reversed", the items are displayed in the opposite order as "grouped". uirevision Controls persistence of legend-driven changes in trace and pie label visibility. Defaults to `layout.uirevision`. valign Sets the vertical alignment of the symbols with respect to their associated text. x Sets the x position (in normalized coordinates) of the legend. Defaults to 1.02 for vertical legends and defaults to 0 for horizontal legends. xanchor Sets the legend's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the legend. Value "auto" anchors legends to the right for `x` values greater than or equal to 2/3, anchors legends to the left for `x` values less than or equal to 1/3 and anchors legends with respect to their center otherwise. y Sets the y position (in normalized coordinates) of the legend. Defaults to 1 for vertical legends, defaults to "-0.1" for horizontal legends on graphs w/o range sliders and defaults to 1.1 for horizontal legends on graph with one or multiple range sliders. yanchor Sets the legend's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the legend. Value "auto" anchors legends at their bottom for `y` values less than or equal to 1/3, anchors legends to at their top for `y` values greater than or equal to 2/3 and anchors legends with respect to their middle otherwise. Returns ------- plotly.graph_objs.layout.Legend """ return self["legend"] @legend.setter def legend(self, val): self["legend"] = val # mapbox # ------ @property def mapbox(self): """ The 'mapbox' property is an instance of Mapbox that may be specified as: - An instance of plotly.graph_objs.layout.Mapbox - A dict of string/value properties that will be passed to the Mapbox constructor Supported dict properties: accesstoken Sets the mapbox access token to be used for this mapbox map. Alternatively, the mapbox access token can be set in the configuration options under `mapboxAccessToken`. Note that accessToken are only required when `style` (e.g with values : basic, streets, outdoors, light, dark, satellite, satellite-streets ) and/or a layout layer references the Mapbox server. bearing Sets the bearing angle of the map in degrees counter-clockwise from North (mapbox.bearing). center plotly.graph_objects.layout.mapbox.Center instance or dict with compatible properties domain plotly.graph_objects.layout.mapbox.Domain instance or dict with compatible properties layers A tuple of plotly.graph_objects.layout.mapbox.Layer instances or dicts with compatible properties layerdefaults When used in a template (as layout.template.layout.mapbox.layerdefaults), sets the default property values to use for elements of layout.mapbox.layers pitch Sets the pitch angle of the map (in degrees, where 0 means perpendicular to the surface of the map) (mapbox.pitch). style Defines the map layers that are rendered by default below the trace layers defined in `data`, which are themselves by default rendered below the layers defined in `layout.mapbox.layers`. These layers can be defined either explicitly as a Mapbox Style object which can contain multiple layer definitions that load data from any public or private Tile Map Service (TMS or XYZ) or Web Map Service (WMS) or implicitly by using one of the built-in style objects which use WMSes which do not require any access tokens, or by using a default Mapbox style or custom Mapbox style URL, both of which require a Mapbox access token Note that Mapbox access token can be set in the `accesstoken` attribute or in the `mapboxAccessToken` config option. Mapbox Style objects are of the form described in the Mapbox GL JS documentation available at https://docs.mapbox.com/mapbox-gl-js/style-spec The built-in plotly.js styles objects are: open-street-map, white-bg, carto-positron, carto-darkmatter, stamen-terrain, stamen-toner, stamen-watercolor The built-in Mapbox styles are: basic, streets, outdoors, light, dark, satellite, satellite-streets Mapbox style URLs are of the form: mapbox://mapbox.mapbox-- uirevision Controls persistence of user-driven changes in the view: `center`, `zoom`, `bearing`, `pitch`. Defaults to `layout.uirevision`. zoom Sets the zoom level of the map (mapbox.zoom). Returns ------- plotly.graph_objs.layout.Mapbox """ return self["mapbox"] @mapbox.setter def mapbox(self, val): self["mapbox"] = val # margin # ------ @property def margin(self): """ The 'margin' property is an instance of Margin that may be specified as: - An instance of plotly.graph_objs.layout.Margin - A dict of string/value properties that will be passed to the Margin constructor Supported dict properties: autoexpand Turns on/off margin expansion computations. Legends, colorbars, updatemenus, sliders, axis rangeselector and rangeslider are allowed to push the margins by defaults. b Sets the bottom margin (in px). l Sets the left margin (in px). pad Sets the amount of padding (in px) between the plotting area and the axis lines r Sets the right margin (in px). t Sets the top margin (in px). Returns ------- plotly.graph_objs.layout.Margin """ return self["margin"] @margin.setter def margin(self, val): self["margin"] = val # meta # ---- @property def meta(self): """ Assigns extra meta information that can be used in various `text` attributes. Attributes such as the graph, axis and colorbar `title.text`, annotation `text` `trace.name` in legend items, `rangeselector`, `updatemenus` and `sliders` `label` text all support `meta`. One can access `meta` fields using template strings: `%{meta[i]}` where `i` is the index of the `meta` item in question. `meta` can also be an object for example `{key: value}` which can be accessed %{meta[key]}. The 'meta' property accepts values of any type Returns ------- Any|numpy.ndarray """ return self["meta"] @meta.setter def meta(self, val): self["meta"] = val # metasrc # ------- @property def metasrc(self): """ Sets the source reference on plot.ly for meta . The 'metasrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["metasrc"] @metasrc.setter def metasrc(self, val): self["metasrc"] = val # modebar # ------- @property def modebar(self): """ The 'modebar' property is an instance of Modebar that may be specified as: - An instance of plotly.graph_objs.layout.Modebar - A dict of string/value properties that will be passed to the Modebar constructor Supported dict properties: activecolor Sets the color of the active or hovered on icons in the modebar. bgcolor Sets the background color of the modebar. color Sets the color of the icons in the modebar. orientation Sets the orientation of the modebar. uirevision Controls persistence of user-driven changes related to the modebar, including `hovermode`, `dragmode`, and `showspikes` at both the root level and inside subplots. Defaults to `layout.uirevision`. Returns ------- plotly.graph_objs.layout.Modebar """ return self["modebar"] @modebar.setter def modebar(self, val): self["modebar"] = val # orientation # ----------- @property def orientation(self): """ Legacy polar charts are deprecated! Please switch to "polar" subplots. Rotates the entire polar by the given angle in legacy polar charts. The 'orientation' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["orientation"] @orientation.setter def orientation(self, val): self["orientation"] = val # paper_bgcolor # ------------- @property def paper_bgcolor(self): """ Sets the color of paper where the graph is drawn. The 'paper_bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["paper_bgcolor"] @paper_bgcolor.setter def paper_bgcolor(self, val): self["paper_bgcolor"] = val # piecolorway # ----------- @property def piecolorway(self): """ Sets the default pie slice colors. Defaults to the main `colorway` used for trace colors. If you specify a new list here it can still be extended with lighter and darker colors, see `extendpiecolors`. The 'piecolorway' property is a colorlist that may be specified as a tuple, list, one-dimensional numpy array, or pandas Series of valid color strings Returns ------- list """ return self["piecolorway"] @piecolorway.setter def piecolorway(self, val): self["piecolorway"] = val # plot_bgcolor # ------------ @property def plot_bgcolor(self): """ Sets the color of plotting area in-between x and y axes. The 'plot_bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["plot_bgcolor"] @plot_bgcolor.setter def plot_bgcolor(self, val): self["plot_bgcolor"] = val # polar # ----- @property def polar(self): """ The 'polar' property is an instance of Polar that may be specified as: - An instance of plotly.graph_objs.layout.Polar - A dict of string/value properties that will be passed to the Polar constructor Supported dict properties: angularaxis plotly.graph_objects.layout.polar.AngularAxis instance or dict with compatible properties bargap Sets the gap between bars of adjacent location coordinates. Values are unitless, they represent fractions of the minimum difference in bar positions in the data. barmode Determines how bars at the same location coordinate are displayed on the graph. With "stack", the bars are stacked on top of one another With "overlay", the bars are plotted over one another, you might need to an "opacity" to see multiple bars. bgcolor Set the background color of the subplot domain plotly.graph_objects.layout.polar.Domain instance or dict with compatible properties gridshape Determines if the radial axis grid lines and angular axis line are drawn as "circular" sectors or as "linear" (polygon) sectors. Has an effect only when the angular axis has `type` "category". Note that `radialaxis.angle` is snapped to the angle of the closest vertex when `gridshape` is "circular" (so that radial axis scale is the same as the data scale). hole Sets the fraction of the radius to cut out of the polar subplot. radialaxis plotly.graph_objects.layout.polar.RadialAxis instance or dict with compatible properties sector Sets angular span of this polar subplot with two angles (in degrees). Sector are assumed to be spanned in the counterclockwise direction with 0 corresponding to rightmost limit of the polar subplot. uirevision Controls persistence of user-driven changes in axis attributes, if not overridden in the individual axes. Defaults to `layout.uirevision`. Returns ------- plotly.graph_objs.layout.Polar """ return self["polar"] @polar.setter def polar(self, val): self["polar"] = val # radialaxis # ---------- @property def radialaxis(self): """ The 'radialaxis' property is an instance of RadialAxis that may be specified as: - An instance of plotly.graph_objs.layout.RadialAxis - A dict of string/value properties that will be passed to the RadialAxis constructor Supported dict properties: domain Polar chart subplots are not supported yet. This key has currently no effect. endpadding Legacy polar charts are deprecated! Please switch to "polar" subplots. orientation Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the orientation (an angle with respect to the origin) of the radial axis. range Legacy polar charts are deprecated! Please switch to "polar" subplots. Defines the start and end point of this radial axis. showline Legacy polar charts are deprecated! Please switch to "polar" subplots. Determines whether or not the line bounding this radial axis will be shown on the figure. showticklabels Legacy polar charts are deprecated! Please switch to "polar" subplots. Determines whether or not the radial axis ticks will feature tick labels. tickcolor Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the color of the tick lines on this radial axis. ticklen Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the length of the tick lines on this radial axis. tickorientation Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the orientation (from the paper perspective) of the radial axis tick labels. ticksuffix Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the length of the tick lines on this radial axis. visible Legacy polar charts are deprecated! Please switch to "polar" subplots. Determines whether or not this axis will be visible. Returns ------- plotly.graph_objs.layout.RadialAxis """ return self["radialaxis"] @radialaxis.setter def radialaxis(self, val): self["radialaxis"] = val # scene # ----- @property def scene(self): """ The 'scene' property is an instance of Scene that may be specified as: - An instance of plotly.graph_objs.layout.Scene - A dict of string/value properties that will be passed to the Scene constructor Supported dict properties: annotations A tuple of plotly.graph_objects.layout.scene.Annotation instances or dicts with compatible properties annotationdefaults When used in a template (as layout.template.lay out.scene.annotationdefaults), sets the default property values to use for elements of layout.scene.annotations aspectmode If "cube", this scene's axes are drawn as a cube, regardless of the axes' ranges. If "data", this scene's axes are drawn in proportion with the axes' ranges. If "manual", this scene's axes are drawn in proportion with the input of "aspectratio" (the default behavior if "aspectratio" is provided). If "auto", this scene's axes are drawn using the results of "data" except when one axis is more than four times the size of the two others, where in that case the results of "cube" are used. aspectratio Sets this scene's axis aspectratio. bgcolor camera plotly.graph_objects.layout.scene.Camera instance or dict with compatible properties domain plotly.graph_objects.layout.scene.Domain instance or dict with compatible properties dragmode Determines the mode of drag interactions for this scene. hovermode Determines the mode of hover interactions for this scene. uirevision Controls persistence of user-driven changes in camera attributes. Defaults to `layout.uirevision`. xaxis plotly.graph_objects.layout.scene.XAxis instance or dict with compatible properties yaxis plotly.graph_objects.layout.scene.YAxis instance or dict with compatible properties zaxis plotly.graph_objects.layout.scene.ZAxis instance or dict with compatible properties Returns ------- plotly.graph_objs.layout.Scene """ return self["scene"] @scene.setter def scene(self, val): self["scene"] = val # selectdirection # --------------- @property def selectdirection(self): """ When "dragmode" is set to "select", this limits the selection of the drag to horizontal, vertical or diagonal. "h" only allows horizontal selection, "v" only vertical, "d" only diagonal and "any" sets no limit. The 'selectdirection' property is an enumeration that may be specified as: - One of the following enumeration values: ['h', 'v', 'd', 'any'] Returns ------- Any """ return self["selectdirection"] @selectdirection.setter def selectdirection(self, val): self["selectdirection"] = val # selectionrevision # ----------------- @property def selectionrevision(self): """ Controls persistence of user-driven changes in selected points from all traces. The 'selectionrevision' property accepts values of any type Returns ------- Any """ return self["selectionrevision"] @selectionrevision.setter def selectionrevision(self, val): self["selectionrevision"] = val # separators # ---------- @property def separators(self): """ Sets the decimal and thousand separators. For example, *. * puts a '.' before decimals and a space between thousands. In English locales, dflt is ".," but other locales may alter this default. The 'separators' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["separators"] @separators.setter def separators(self, val): self["separators"] = val # shapes # ------ @property def shapes(self): """ The 'shapes' property is a tuple of instances of Shape that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.Shape - A list or tuple of dicts of string/value properties that will be passed to the Shape constructor Supported dict properties: fillcolor Sets the color filling the shape's interior. layer Specifies whether shapes are drawn below or above traces. line plotly.graph_objects.layout.shape.Line instance or dict with compatible properties name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. opacity Sets the opacity of the shape. path For `type` "path" - a valid SVG path with the pixel values replaced by data values in `xsizemode`/`ysizemode` being "scaled" and taken unmodified as pixels relative to `xanchor` and `yanchor` in case of "pixel" size mode. There are a few restrictions / quirks only absolute instructions, not relative. So the allowed segments are: M, L, H, V, Q, C, T, S, and Z arcs (A) are not allowed because radius rx and ry are relative. In the future we could consider supporting relative commands, but we would have to decide on how to handle date and log axes. Note that even as is, Q and C Bezier paths that are smooth on linear axes may not be smooth on log, and vice versa. no chained "polybezier" commands - specify the segment type for each one. On category axes, values are numbers scaled to the serial numbers of categories because using the categories themselves there would be no way to describe fractional positions On data axes: because space and T are both normal components of path strings, we can't use either to separate date from time parts. Therefore we'll use underscore for this purpose: 2015-02-21_13:45:56.789 templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. type Specifies the shape type to be drawn. If "line", a line is drawn from (`x0`,`y0`) to (`x1`,`y1`) with respect to the axes' sizing mode. If "circle", a circle is drawn from ((`x0`+`x1`)/2, (`y0`+`y1`)/2)) with radius (|(`x0`+`x1`)/2 - `x0`|, |(`y0`+`y1`)/2 -`y0`)|) with respect to the axes' sizing mode. If "rect", a rectangle is drawn linking (`x0`,`y0`), (`x1`,`y0`), (`x1`,`y1`), (`x0`,`y1`), (`x0`,`y0`) with respect to the axes' sizing mode. If "path", draw a custom SVG path using `path`. with respect to the axes' sizing mode. visible Determines whether or not this shape is visible. x0 Sets the shape's starting x position. See `type` and `xsizemode` for more info. x1 Sets the shape's end x position. See `type` and `xsizemode` for more info. xanchor Only relevant in conjunction with `xsizemode` set to "pixel". Specifies the anchor point on the x axis to which `x0`, `x1` and x coordinates within `path` are relative to. E.g. useful to attach a pixel sized shape to a certain data value. No effect when `xsizemode` not set to "pixel". xref Sets the shape's x coordinate axis. If set to an x axis id (e.g. "x" or "x2"), the `x` position refers to an x coordinate. If set to "paper", the `x` position refers to the distance from the left side of the plotting area in normalized coordinates where 0 (1) corresponds to the left (right) side. If the axis `type` is "log", then you must take the log of your desired range. If the axis `type` is "date", then you must convert the date to unix time in milliseconds. xsizemode Sets the shapes's sizing mode along the x axis. If set to "scaled", `x0`, `x1` and x coordinates within `path` refer to data values on the x axis or a fraction of the plot area's width (`xref` set to "paper"). If set to "pixel", `xanchor` specifies the x position in terms of data or plot fraction but `x0`, `x1` and x coordinates within `path` are pixels relative to `xanchor`. This way, the shape can have a fixed width while maintaining a position relative to data or plot fraction. y0 Sets the shape's starting y position. See `type` and `ysizemode` for more info. y1 Sets the shape's end y position. See `type` and `ysizemode` for more info. yanchor Only relevant in conjunction with `ysizemode` set to "pixel". Specifies the anchor point on the y axis to which `y0`, `y1` and y coordinates within `path` are relative to. E.g. useful to attach a pixel sized shape to a certain data value. No effect when `ysizemode` not set to "pixel". yref Sets the annotation's y coordinate axis. If set to an y axis id (e.g. "y" or "y2"), the `y` position refers to an y coordinate If set to "paper", the `y` position refers to the distance from the bottom of the plotting area in normalized coordinates where 0 (1) corresponds to the bottom (top). ysizemode Sets the shapes's sizing mode along the y axis. If set to "scaled", `y0`, `y1` and y coordinates within `path` refer to data values on the y axis or a fraction of the plot area's height (`yref` set to "paper"). If set to "pixel", `yanchor` specifies the y position in terms of data or plot fraction but `y0`, `y1` and y coordinates within `path` are pixels relative to `yanchor`. This way, the shape can have a fixed height while maintaining a position relative to data or plot fraction. Returns ------- tuple[plotly.graph_objs.layout.Shape] """ return self["shapes"] @shapes.setter def shapes(self, val): self["shapes"] = val # shapedefaults # ------------- @property def shapedefaults(self): """ When used in a template (as layout.template.layout.shapedefaults), sets the default property values to use for elements of layout.shapes The 'shapedefaults' property is an instance of Shape that may be specified as: - An instance of plotly.graph_objs.layout.Shape - A dict of string/value properties that will be passed to the Shape constructor Supported dict properties: Returns ------- plotly.graph_objs.layout.Shape """ return self["shapedefaults"] @shapedefaults.setter def shapedefaults(self, val): self["shapedefaults"] = val # showlegend # ---------- @property def showlegend(self): """ Determines whether or not a legend is drawn. Default is `true` if there is a trace to show and any of these: a) Two or more traces would by default be shown in the legend. b) One pie trace is shown in the legend. c) One trace is explicitly given with `showlegend: true`. The 'showlegend' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showlegend"] @showlegend.setter def showlegend(self, val): self["showlegend"] = val # sliders # ------- @property def sliders(self): """ The 'sliders' property is a tuple of instances of Slider that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.Slider - A list or tuple of dicts of string/value properties that will be passed to the Slider constructor Supported dict properties: active Determines which button (by index starting from 0) is considered active. activebgcolor Sets the background color of the slider grip while dragging. bgcolor Sets the background color of the slider. bordercolor Sets the color of the border enclosing the slider. borderwidth Sets the width (in px) of the border enclosing the slider. currentvalue plotly.graph_objects.layout.slider.Currentvalue instance or dict with compatible properties font Sets the font of the slider step labels. len Sets the length of the slider This measure excludes the padding of both ends. That is, the slider's length is this length minus the padding on both ends. lenmode Determines whether this slider length is set in units of plot "fraction" or in *pixels. Use `len` to set the value. minorticklen Sets the length in pixels of minor step tick marks name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. pad Set the padding of the slider component along each side. steps A tuple of plotly.graph_objects.layout.slider.Step instances or dicts with compatible properties stepdefaults When used in a template (as layout.template.layout.slider.stepdefaults), sets the default property values to use for elements of layout.slider.steps templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. tickcolor Sets the color of the border enclosing the slider. ticklen Sets the length in pixels of step tick marks tickwidth Sets the tick width (in px). transition plotly.graph_objects.layout.slider.Transition instance or dict with compatible properties visible Determines whether or not the slider is visible. x Sets the x position (in normalized coordinates) of the slider. xanchor Sets the slider's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the range selector. y Sets the y position (in normalized coordinates) of the slider. yanchor Sets the slider's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the range selector. Returns ------- tuple[plotly.graph_objs.layout.Slider] """ return self["sliders"] @sliders.setter def sliders(self, val): self["sliders"] = val # sliderdefaults # -------------- @property def sliderdefaults(self): """ When used in a template (as layout.template.layout.sliderdefaults), sets the default property values to use for elements of layout.sliders The 'sliderdefaults' property is an instance of Slider that may be specified as: - An instance of plotly.graph_objs.layout.Slider - A dict of string/value properties that will be passed to the Slider constructor Supported dict properties: Returns ------- plotly.graph_objs.layout.Slider """ return self["sliderdefaults"] @sliderdefaults.setter def sliderdefaults(self, val): self["sliderdefaults"] = val # spikedistance # ------------- @property def spikedistance(self): """ Sets the default distance (in pixels) to look for data to draw spikelines to (-1 means no cutoff, 0 means no looking for data). As with hoverdistance, distance does not apply to area- like objects. In addition, some objects can be hovered on but will not generate spikelines, such as scatter fills. The 'spikedistance' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [-1, 9223372036854775807] Returns ------- int """ return self["spikedistance"] @spikedistance.setter def spikedistance(self, val): self["spikedistance"] = val # sunburstcolorway # ---------------- @property def sunburstcolorway(self): """ Sets the default sunburst slice colors. Defaults to the main `colorway` used for trace colors. If you specify a new list here it can still be extended with lighter and darker colors, see `extendsunburstcolors`. The 'sunburstcolorway' property is a colorlist that may be specified as a tuple, list, one-dimensional numpy array, or pandas Series of valid color strings Returns ------- list """ return self["sunburstcolorway"] @sunburstcolorway.setter def sunburstcolorway(self, val): self["sunburstcolorway"] = val # template # -------- @property def template(self): """ Default attributes to be applied to the plot. This should be a dict with format: `{'layout': layoutTemplate, 'data': {trace_type: [traceTemplate, ...], ...}}` where `layoutTemplate` is a dict matching the structure of `figure.layout` and `traceTemplate` is a dict matching the structure of the trace with type `trace_type` (e.g. 'scatter'). Alternatively, this may be specified as an instance of plotly.graph_objs.layout.Template. Trace templates are applied cyclically to traces of each type. Container arrays (eg `annotations`) have special handling: An object ending in `defaults` (eg `annotationdefaults`) is applied to each array item. But if an item has a `templateitemname` key we look in the template array for an item with matching `name` and apply that instead. If no matching `name` is found we mark the item invisible. Any named template item not referenced is appended to the end of the array, so this can be used to add a watermark annotation or a logo image, for example. To omit one of these items on the plot, make an item with matching `templateitemname` and `visible: false`. The 'template' property is an instance of Template that may be specified as: - An instance of plotly.graph_objs.layout.Template - A dict of string/value properties that will be passed to the Template constructor Supported dict properties: data plotly.graph_objects.layout.template.Data instance or dict with compatible properties layout plotly.graph_objects.Layout instance or dict with compatible properties - The name of a registered template where current registered templates are stored in the plotly.io.templates configuration object. The names of all registered templates can be retrieved with: >>> import plotly.io as pio >>> list(pio.templates) # doctest: +ELLIPSIS ['ggplot2', 'seaborn', 'simple_white', 'plotly', 'plotly_white', ...] - A string containing multiple registered template names, joined on '+' characters (e.g. 'template1+template2'). In this case the resulting template is computed by merging together the collection of registered templates Returns ------- plotly.graph_objs.layout.Template """ return self["template"] @template.setter def template(self, val): self["template"] = val # ternary # ------- @property def ternary(self): """ The 'ternary' property is an instance of Ternary that may be specified as: - An instance of plotly.graph_objs.layout.Ternary - A dict of string/value properties that will be passed to the Ternary constructor Supported dict properties: aaxis plotly.graph_objects.layout.ternary.Aaxis instance or dict with compatible properties baxis plotly.graph_objects.layout.ternary.Baxis instance or dict with compatible properties bgcolor Set the background color of the subplot caxis plotly.graph_objects.layout.ternary.Caxis instance or dict with compatible properties domain plotly.graph_objects.layout.ternary.Domain instance or dict with compatible properties sum The number each triplet should sum to, and the maximum range of each axis uirevision Controls persistence of user-driven changes in axis `min` and `title`, if not overridden in the individual axes. Defaults to `layout.uirevision`. Returns ------- plotly.graph_objs.layout.Ternary """ return self["ternary"] @ternary.setter def ternary(self, val): self["ternary"] = val # title # ----- @property def title(self): """ The 'title' property is an instance of Title that may be specified as: - An instance of plotly.graph_objs.layout.Title - A dict of string/value properties that will be passed to the Title constructor Supported dict properties: font Sets the title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. pad Sets the padding of the title. Each padding value only applies when the corresponding `xanchor`/`yanchor` value is set accordingly. E.g. for left padding to take effect, `xanchor` must be set to "left". The same rule applies if `xanchor`/`yanchor` is determined automatically. Padding is muted if the respective anchor value is "middle*/*center". text Sets the plot's title. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. x Sets the x position with respect to `xref` in normalized coordinates from 0 (left) to 1 (right). xanchor Sets the title's horizontal alignment with respect to its x position. "left" means that the title starts at x, "right" means that the title ends at x and "center" means that the title's center is at x. "auto" divides `xref` by three and calculates the `xanchor` value automatically based on the value of `x`. xref Sets the container `x` refers to. "container" spans the entire `width` of the plot. "paper" refers to the width of the plotting area only. y Sets the y position with respect to `yref` in normalized coordinates from 0 (bottom) to 1 (top). "auto" places the baseline of the title onto the vertical center of the top margin. yanchor Sets the title's vertical alignment with respect to its y position. "top" means that the title's cap line is at y, "bottom" means that the title's baseline is at y and "middle" means that the title's midline is at y. "auto" divides `yref` by three and calculates the `yanchor` value automatically based on the value of `y`. yref Sets the container `y` refers to. "container" spans the entire `height` of the plot. "paper" refers to the height of the plotting area only. Returns ------- plotly.graph_objs.layout.Title """ return self["title"] @title.setter def title(self, val): self["title"] = val # titlefont # --------- @property def titlefont(self): """ Deprecated: Please use layout.title.font instead. Sets the title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.layout.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- """ return self["titlefont"] @titlefont.setter def titlefont(self, val): self["titlefont"] = val # transition # ---------- @property def transition(self): """ Sets transition options used during Plotly.react updates. The 'transition' property is an instance of Transition that may be specified as: - An instance of plotly.graph_objs.layout.Transition - A dict of string/value properties that will be passed to the Transition constructor Supported dict properties: duration The duration of the transition, in milliseconds. If equal to zero, updates are synchronous. easing The easing function used for the transition ordering Determines whether the figure's layout or traces smoothly transitions during updates that make both traces and layout change. Returns ------- plotly.graph_objs.layout.Transition """ return self["transition"] @transition.setter def transition(self, val): self["transition"] = val # treemapcolorway # --------------- @property def treemapcolorway(self): """ Sets the default treemap slice colors. Defaults to the main `colorway` used for trace colors. If you specify a new list here it can still be extended with lighter and darker colors, see `extendtreemapcolors`. The 'treemapcolorway' property is a colorlist that may be specified as a tuple, list, one-dimensional numpy array, or pandas Series of valid color strings Returns ------- list """ return self["treemapcolorway"] @treemapcolorway.setter def treemapcolorway(self, val): self["treemapcolorway"] = val # uirevision # ---------- @property def uirevision(self): """ Used to allow user interactions with the plot to persist after `Plotly.react` calls that are unaware of these interactions. If `uirevision` is omitted, or if it is given and it changed from the previous `Plotly.react` call, the exact new figure is used. If `uirevision` is truthy and did NOT change, any attribute that has been affected by user interactions and did not receive a different value in the new figure will keep the interaction value. `layout.uirevision` attribute serves as the default for `uirevision` attributes in various sub-containers. For finer control you can set these sub-attributes directly. For example, if your app separately controls the data on the x and y axes you might set `xaxis.uirevision=*time*` and `yaxis.uirevision=*cost*`. Then if only the y data is changed, you can update `yaxis.uirevision=*quantity*` and the y axis range will reset but the x axis range will retain any user- driven zoom. The 'uirevision' property accepts values of any type Returns ------- Any """ return self["uirevision"] @uirevision.setter def uirevision(self, val): self["uirevision"] = val # updatemenus # ----------- @property def updatemenus(self): """ The 'updatemenus' property is a tuple of instances of Updatemenu that may be specified as: - A list or tuple of instances of plotly.graph_objs.layout.Updatemenu - A list or tuple of dicts of string/value properties that will be passed to the Updatemenu constructor Supported dict properties: active Determines which button (by index starting from 0) is considered active. bgcolor Sets the background color of the update menu buttons. bordercolor Sets the color of the border enclosing the update menu. borderwidth Sets the width (in px) of the border enclosing the update menu. buttons A tuple of plotly.graph_objects.layout.updatemenu.Button instances or dicts with compatible properties buttondefaults When used in a template (as layout.template.lay out.updatemenu.buttondefaults), sets the default property values to use for elements of layout.updatemenu.buttons direction Determines the direction in which the buttons are laid out, whether in a dropdown menu or a row/column of buttons. For `left` and `up`, the buttons will still appear in left-to-right or top-to-bottom order respectively. font Sets the font of the update menu button text. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. pad Sets the padding around the buttons or dropdown menu. showactive Highlights active dropdown item or active button if true. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. type Determines whether the buttons are accessible via a dropdown menu or whether the buttons are stacked horizontally or vertically visible Determines whether or not the update menu is visible. x Sets the x position (in normalized coordinates) of the update menu. xanchor Sets the update menu's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the range selector. y Sets the y position (in normalized coordinates) of the update menu. yanchor Sets the update menu's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the range selector. Returns ------- tuple[plotly.graph_objs.layout.Updatemenu] """ return self["updatemenus"] @updatemenus.setter def updatemenus(self, val): self["updatemenus"] = val # updatemenudefaults # ------------------ @property def updatemenudefaults(self): """ When used in a template (as layout.template.layout.updatemenudefaults), sets the default property values to use for elements of layout.updatemenus The 'updatemenudefaults' property is an instance of Updatemenu that may be specified as: - An instance of plotly.graph_objs.layout.Updatemenu - A dict of string/value properties that will be passed to the Updatemenu constructor Supported dict properties: Returns ------- plotly.graph_objs.layout.Updatemenu """ return self["updatemenudefaults"] @updatemenudefaults.setter def updatemenudefaults(self, val): self["updatemenudefaults"] = val # violingap # --------- @property def violingap(self): """ Sets the gap (in plot fraction) between violins of adjacent location coordinates. Has no effect on traces that have "width" set. The 'violingap' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["violingap"] @violingap.setter def violingap(self, val): self["violingap"] = val # violingroupgap # -------------- @property def violingroupgap(self): """ Sets the gap (in plot fraction) between violins of the same location coordinate. Has no effect on traces that have "width" set. The 'violingroupgap' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["violingroupgap"] @violingroupgap.setter def violingroupgap(self, val): self["violingroupgap"] = val # violinmode # ---------- @property def violinmode(self): """ Determines how violins at the same location coordinate are displayed on the graph. If "group", the violins are plotted next to one another centered around the shared location. If "overlay", the violins are plotted over one another, you might need to set "opacity" to see them multiple violins. Has no effect on traces that have "width" set. The 'violinmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['group', 'overlay'] Returns ------- Any """ return self["violinmode"] @violinmode.setter def violinmode(self, val): self["violinmode"] = val # waterfallgap # ------------ @property def waterfallgap(self): """ Sets the gap (in plot fraction) between bars of adjacent location coordinates. The 'waterfallgap' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["waterfallgap"] @waterfallgap.setter def waterfallgap(self, val): self["waterfallgap"] = val # waterfallgroupgap # ----------------- @property def waterfallgroupgap(self): """ Sets the gap (in plot fraction) between bars of the same location coordinate. The 'waterfallgroupgap' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["waterfallgroupgap"] @waterfallgroupgap.setter def waterfallgroupgap(self, val): self["waterfallgroupgap"] = val # waterfallmode # ------------- @property def waterfallmode(self): """ Determines how bars at the same location coordinate are displayed on the graph. With "group", the bars are plotted next to one another centered around the shared location. With "overlay", the bars are plotted over one another, you might need to an "opacity" to see multiple bars. The 'waterfallmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['group', 'overlay'] Returns ------- Any """ return self["waterfallmode"] @waterfallmode.setter def waterfallmode(self, val): self["waterfallmode"] = val # width # ----- @property def width(self): """ Sets the plot's width (in px). The 'width' property is a number and may be specified as: - An int or float in the interval [10, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # xaxis # ----- @property def xaxis(self): """ The 'xaxis' property is an instance of XAxis that may be specified as: - An instance of plotly.graph_objs.layout.XAxis - A dict of string/value properties that will be passed to the XAxis constructor Supported dict properties: anchor If set to an opposite-letter axis id (e.g. `x2`, `y`), this axis is bound to the corresponding opposite-letter axis. If set to "free", this axis' position is determined by `position`. automargin Determines whether long tick labels automatically grow the figure margins. autorange Determines whether or not the range of this axis is computed in relation to the input data. See `rangemode` for more info. If `range` is provided, then `autorange` is set to False. calendar Sets the calendar system to use for `range` and `tick0` if this is a date axis. This does not set the calendar for interpreting data on this axis, that's specified in the trace or via the global `layout.calendar` categoryarray Sets the order in which categories on this axis appear. Only has an effect if `categoryorder` is set to "array". Used with `categoryorder`. categoryarraysrc Sets the source reference on plot.ly for categoryarray . categoryorder Specifies the ordering logic for the case of categorical variables. By default, plotly uses "trace", which specifies the order that is present in the data supplied. Set `categoryorder` to *category ascending* or *category descending* if order should be determined by the alphanumerical order of the category names. Set `categoryorder` to "array" to derive the ordering from the attribute `categoryarray`. If a category is not found in the `categoryarray` array, the sorting behavior for that attribute will be identical to the "trace" mode. The unspecified categories will follow the categories in `categoryarray`. Set `categoryorder` to *total ascending* or *total descending* if order should be determined by the numerical order of the values. Similarly, the order can be determined by the min, max, sum, mean or median of all the values. color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. constrain If this axis needs to be compressed (either due to its own `scaleanchor` and `scaleratio` or those of the other axis), determines how that happens: by increasing the "range" (default), or by decreasing the "domain". constraintoward If this axis needs to be compressed (either due to its own `scaleanchor` and `scaleratio` or those of the other axis), determines which direction we push the originally specified plot area. Options are "left", "center" (default), and "right" for x axes, and "top", "middle" (default), and "bottom" for y axes. dividercolor Sets the color of the dividers Only has an effect on "multicategory" axes. dividerwidth Sets the width (in px) of the dividers Only has an effect on "multicategory" axes. domain Sets the domain of this axis (in plot fraction). dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. fixedrange Determines whether or not this axis is zoom- able. If true, then zoom is disabled. gridcolor Sets the color of the grid lines. gridwidth Sets the width (in px) of the grid lines. hoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" layer Sets the layer on which this axis is displayed. If *above traces*, this axis is displayed above all the subplot's traces If *below traces*, this axis is displayed below all the subplot's traces, but above the grid lines. Useful when used together with scatter-like traces with `cliponaxis` set to False to show markers and/or text nodes above this axis. linecolor Sets the axis line color. linewidth Sets the width (in px) of the axis line. matches If set to another axis id (e.g. `x2`, `y`), the range of this axis will match the range of the corresponding axis in data-coordinates space. Moreover, matching axes share auto-range values, category lists and histogram auto-bins. Note that setting axes simultaneously in both a `scaleanchor` and a `matches` constraint is currently forbidden. Moreover, note that matching axes must have the same `type`. mirror Determines if the axis lines or/and ticks are mirrored to the opposite side of the plotting area. If True, the axis lines are mirrored. If "ticks", the axis lines and ticks are mirrored. If False, mirroring is disable. If "all", axis lines are mirrored on all shared-axes subplots. If "allticks", axis lines and ticks are mirrored on all shared-axes subplots. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". overlaying If set a same-letter axis id, this axis is overlaid on top of the corresponding same- letter axis, with traces and axes visible for both axes. If False, this axis does not overlay any same-letter axes. In this case, for axes with overlapping domains only the highest- numbered axis will be visible. position Sets the position of this axis in the plotting space (in normalized coordinates). Only has an effect if `anchor` is set to "free". range Sets the range of this axis. If the axis `type` is "log", then you must take the log of your desired range (e.g. to set the range from 1 to 100, set the range from 0 to 2). If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. rangemode If "normal", the range is computed in relation to the extrema of the input data. If *tozero*`, the range extends to 0, regardless of the input data If "nonnegative", the range is non- negative, regardless of the input data. Applies only to linear axes. rangeselector plotly.graph_objects.layout.xaxis.Rangeselector instance or dict with compatible properties rangeslider plotly.graph_objects.layout.xaxis.Rangeslider instance or dict with compatible properties scaleanchor If set to another axis id (e.g. `x2`, `y`), the range of this axis changes together with the range of the corresponding axis such that the scale of pixels per unit is in a constant ratio. Both axes are still zoomable, but when you zoom one, the other will zoom the same amount, keeping a fixed midpoint. `constrain` and `constraintoward` determine how we enforce the constraint. You can chain these, ie `yaxis: {scaleanchor: *x*}, xaxis2: {scaleanchor: *y*}` but you can only link axes of the same `type`. The linked axis can have the opposite letter (to constrain the aspect ratio) or the same letter (to match scales across subplots). Loops (`yaxis: {scaleanchor: *x*}, xaxis: {scaleanchor: *y*}` or longer) are redundant and the last constraint encountered will be ignored to avoid possible inconsistent constraints via `scaleratio`. Note that setting axes simultaneously in both a `scaleanchor` and a `matches` constraint is currently forbidden. scaleratio If this axis is linked to another by `scaleanchor`, this determines the pixel to unit scale ratio. For example, if this value is 10, then every unit on this axis spans 10 times the number of pixels as a unit on the linked axis. Use this for example to create an elevation profile where the vertical scale is exaggerated a fixed amount with respect to the horizontal. separatethousands If "true", even 4-digit integers are separated showdividers Determines whether or not a dividers are drawn between the category levels of this axis. Only has an effect on "multicategory" axes. showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showgrid Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. showline Determines whether or not a line bounding this axis is drawn. showspikes Determines whether or not spikes (aka droplines) are drawn for this axis. Note: This only takes affect when hovermode = closest showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. side Determines whether a x (y) axis is positioned at the "bottom" ("left") or "top" ("right") of the plotting area. spikecolor Sets the spike color. If undefined, will use the series color spikedash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). spikemode Determines the drawing mode for the spike line If "toaxis", the line is drawn from the data point to the axis the series is plotted on. If "across", the line is drawn across the entire plot area, and supercedes "toaxis". If "marker", then a marker dot is drawn on the axis the series is plotted on spikesnap Determines whether spikelines are stuck to the cursor or to the closest datapoints. spikethickness Sets the width (in px) of the zero line. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the tick font. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.layout.xaxis.Ti ckformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.lay out.xaxis.tickformatstopdefaults), sets the default property values to use for elements of layout.xaxis.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. tickson Determines where ticks and grid lines are drawn with respect to their corresponding tick labels. Only has an effect for axes of `type` "category" or "multicategory". When set to "boundaries", ticks and grid lines are drawn half a category to the left/bottom of labels. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.layout.xaxis.Title instance or dict with compatible properties titlefont Deprecated: Please use layout.xaxis.title.font instead. Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. type Sets the axis type. By default, plotly attempts to determined the axis type by looking into the data of the traces that referenced the axis in question. uirevision Controls persistence of user-driven changes in axis `range`, `autorange`, and `title` if in `editable: true` configuration. Defaults to `layout.uirevision`. visible A single toggle to hide the axis while preserving interaction like dragging. Default is true when a cheater plot is present on the axis, otherwise false zeroline Determines whether or not a line is drawn at along the 0 value of this axis. If True, the zero line is drawn on top of the grid lines. zerolinecolor Sets the line color of the zero line. zerolinewidth Sets the width (in px) of the zero line. Returns ------- plotly.graph_objs.layout.XAxis """ return self["xaxis"] @xaxis.setter def xaxis(self, val): self["xaxis"] = val # yaxis # ----- @property def yaxis(self): """ The 'yaxis' property is an instance of YAxis that may be specified as: - An instance of plotly.graph_objs.layout.YAxis - A dict of string/value properties that will be passed to the YAxis constructor Supported dict properties: anchor If set to an opposite-letter axis id (e.g. `x2`, `y`), this axis is bound to the corresponding opposite-letter axis. If set to "free", this axis' position is determined by `position`. automargin Determines whether long tick labels automatically grow the figure margins. autorange Determines whether or not the range of this axis is computed in relation to the input data. See `rangemode` for more info. If `range` is provided, then `autorange` is set to False. calendar Sets the calendar system to use for `range` and `tick0` if this is a date axis. This does not set the calendar for interpreting data on this axis, that's specified in the trace or via the global `layout.calendar` categoryarray Sets the order in which categories on this axis appear. Only has an effect if `categoryorder` is set to "array". Used with `categoryorder`. categoryarraysrc Sets the source reference on plot.ly for categoryarray . categoryorder Specifies the ordering logic for the case of categorical variables. By default, plotly uses "trace", which specifies the order that is present in the data supplied. Set `categoryorder` to *category ascending* or *category descending* if order should be determined by the alphanumerical order of the category names. Set `categoryorder` to "array" to derive the ordering from the attribute `categoryarray`. If a category is not found in the `categoryarray` array, the sorting behavior for that attribute will be identical to the "trace" mode. The unspecified categories will follow the categories in `categoryarray`. Set `categoryorder` to *total ascending* or *total descending* if order should be determined by the numerical order of the values. Similarly, the order can be determined by the min, max, sum, mean or median of all the values. color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. constrain If this axis needs to be compressed (either due to its own `scaleanchor` and `scaleratio` or those of the other axis), determines how that happens: by increasing the "range" (default), or by decreasing the "domain". constraintoward If this axis needs to be compressed (either due to its own `scaleanchor` and `scaleratio` or those of the other axis), determines which direction we push the originally specified plot area. Options are "left", "center" (default), and "right" for x axes, and "top", "middle" (default), and "bottom" for y axes. dividercolor Sets the color of the dividers Only has an effect on "multicategory" axes. dividerwidth Sets the width (in px) of the dividers Only has an effect on "multicategory" axes. domain Sets the domain of this axis (in plot fraction). dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. fixedrange Determines whether or not this axis is zoom- able. If true, then zoom is disabled. gridcolor Sets the color of the grid lines. gridwidth Sets the width (in px) of the grid lines. hoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" layer Sets the layer on which this axis is displayed. If *above traces*, this axis is displayed above all the subplot's traces If *below traces*, this axis is displayed below all the subplot's traces, but above the grid lines. Useful when used together with scatter-like traces with `cliponaxis` set to False to show markers and/or text nodes above this axis. linecolor Sets the axis line color. linewidth Sets the width (in px) of the axis line. matches If set to another axis id (e.g. `x2`, `y`), the range of this axis will match the range of the corresponding axis in data-coordinates space. Moreover, matching axes share auto-range values, category lists and histogram auto-bins. Note that setting axes simultaneously in both a `scaleanchor` and a `matches` constraint is currently forbidden. Moreover, note that matching axes must have the same `type`. mirror Determines if the axis lines or/and ticks are mirrored to the opposite side of the plotting area. If True, the axis lines are mirrored. If "ticks", the axis lines and ticks are mirrored. If False, mirroring is disable. If "all", axis lines are mirrored on all shared-axes subplots. If "allticks", axis lines and ticks are mirrored on all shared-axes subplots. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". overlaying If set a same-letter axis id, this axis is overlaid on top of the corresponding same- letter axis, with traces and axes visible for both axes. If False, this axis does not overlay any same-letter axes. In this case, for axes with overlapping domains only the highest- numbered axis will be visible. position Sets the position of this axis in the plotting space (in normalized coordinates). Only has an effect if `anchor` is set to "free". range Sets the range of this axis. If the axis `type` is "log", then you must take the log of your desired range (e.g. to set the range from 1 to 100, set the range from 0 to 2). If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. rangemode If "normal", the range is computed in relation to the extrema of the input data. If *tozero*`, the range extends to 0, regardless of the input data If "nonnegative", the range is non- negative, regardless of the input data. Applies only to linear axes. scaleanchor If set to another axis id (e.g. `x2`, `y`), the range of this axis changes together with the range of the corresponding axis such that the scale of pixels per unit is in a constant ratio. Both axes are still zoomable, but when you zoom one, the other will zoom the same amount, keeping a fixed midpoint. `constrain` and `constraintoward` determine how we enforce the constraint. You can chain these, ie `yaxis: {scaleanchor: *x*}, xaxis2: {scaleanchor: *y*}` but you can only link axes of the same `type`. The linked axis can have the opposite letter (to constrain the aspect ratio) or the same letter (to match scales across subplots). Loops (`yaxis: {scaleanchor: *x*}, xaxis: {scaleanchor: *y*}` or longer) are redundant and the last constraint encountered will be ignored to avoid possible inconsistent constraints via `scaleratio`. Note that setting axes simultaneously in both a `scaleanchor` and a `matches` constraint is currently forbidden. scaleratio If this axis is linked to another by `scaleanchor`, this determines the pixel to unit scale ratio. For example, if this value is 10, then every unit on this axis spans 10 times the number of pixels as a unit on the linked axis. Use this for example to create an elevation profile where the vertical scale is exaggerated a fixed amount with respect to the horizontal. separatethousands If "true", even 4-digit integers are separated showdividers Determines whether or not a dividers are drawn between the category levels of this axis. Only has an effect on "multicategory" axes. showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showgrid Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. showline Determines whether or not a line bounding this axis is drawn. showspikes Determines whether or not spikes (aka droplines) are drawn for this axis. Note: This only takes affect when hovermode = closest showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. side Determines whether a x (y) axis is positioned at the "bottom" ("left") or "top" ("right") of the plotting area. spikecolor Sets the spike color. If undefined, will use the series color spikedash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). spikemode Determines the drawing mode for the spike line If "toaxis", the line is drawn from the data point to the axis the series is plotted on. If "across", the line is drawn across the entire plot area, and supercedes "toaxis". If "marker", then a marker dot is drawn on the axis the series is plotted on spikesnap Determines whether spikelines are stuck to the cursor or to the closest datapoints. spikethickness Sets the width (in px) of the zero line. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the tick font. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.layout.yaxis.Ti ckformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.lay out.yaxis.tickformatstopdefaults), sets the default property values to use for elements of layout.yaxis.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. tickson Determines where ticks and grid lines are drawn with respect to their corresponding tick labels. Only has an effect for axes of `type` "category" or "multicategory". When set to "boundaries", ticks and grid lines are drawn half a category to the left/bottom of labels. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.layout.yaxis.Title instance or dict with compatible properties titlefont Deprecated: Please use layout.yaxis.title.font instead. Sets this axis' title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. type Sets the axis type. By default, plotly attempts to determined the axis type by looking into the data of the traces that referenced the axis in question. uirevision Controls persistence of user-driven changes in axis `range`, `autorange`, and `title` if in `editable: true` configuration. Defaults to `layout.uirevision`. visible A single toggle to hide the axis while preserving interaction like dragging. Default is true when a cheater plot is present on the axis, otherwise false zeroline Determines whether or not a line is drawn at along the 0 value of this axis. If True, the zero line is drawn on top of the grid lines. zerolinecolor Sets the line color of the zero line. zerolinewidth Sets the width (in px) of the zero line. Returns ------- plotly.graph_objs.layout.YAxis """ return self["yaxis"] @yaxis.setter def yaxis(self, val): self["yaxis"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ angularaxis plotly.graph_objects.layout.AngularAxis instance or dict with compatible properties annotations A tuple of plotly.graph_objects.layout.Annotation instances or dicts with compatible properties annotationdefaults When used in a template (as layout.template.layout.annotationdefaults), sets the default property values to use for elements of layout.annotations autosize Determines whether or not a layout width or height that has been left undefined by the user is initialized on each relayout. Note that, regardless of this attribute, an undefined layout width or height is always initialized on the first call to plot. bargap Sets the gap (in plot fraction) between bars of adjacent location coordinates. bargroupgap Sets the gap (in plot fraction) between bars of the same location coordinate. barmode Determines how bars at the same location coordinate are displayed on the graph. With "stack", the bars are stacked on top of one another With "relative", the bars are stacked on top of one another, with negative values below the axis, positive values above With "group", the bars are plotted next to one another centered around the shared location. With "overlay", the bars are plotted over one another, you might need to an "opacity" to see multiple bars. barnorm Sets the normalization for bar traces on the graph. With "fraction", the value of each bar is divided by the sum of all values at that location coordinate. "percent" is the same but multiplied by 100 to show percentages. boxgap Sets the gap (in plot fraction) between boxes of adjacent location coordinates. Has no effect on traces that have "width" set. boxgroupgap Sets the gap (in plot fraction) between boxes of the same location coordinate. Has no effect on traces that have "width" set. boxmode Determines how boxes at the same location coordinate are displayed on the graph. If "group", the boxes are plotted next to one another centered around the shared location. If "overlay", the boxes are plotted over one another, you might need to set "opacity" to see them multiple boxes. Has no effect on traces that have "width" set. calendar Sets the default calendar system to use for interpreting and displaying dates throughout the plot. clickmode Determines the mode of single click interactions. "event" is the default value and emits the `plotly_click` event. In addition this mode emits the `plotly_selected` event in drag modes "lasso" and "select", but with no event data attached (kept for compatibility reasons). The "select" flag enables selecting single data points via click. This mode also supports persistent selections, meaning that pressing Shift while clicking, adds to / subtracts from an existing selection. "select" with `hovermode`: "x" can be confusing, consider explicitly setting `hovermode`: "closest" when using this feature. Selection events are sent accordingly as long as "event" flag is set as well. When the "event" flag is missing, `plotly_click` and `plotly_selected` events are not fired. coloraxis plotly.graph_objects.layout.Coloraxis instance or dict with compatible properties colorscale plotly.graph_objects.layout.Colorscale instance or dict with compatible properties colorway Sets the default trace colors. datarevision If provided, a changed value tells `Plotly.react` that one or more data arrays has changed. This way you can modify arrays in-place rather than making a complete new copy for an incremental change. If NOT provided, `Plotly.react` assumes that data arrays are being treated as immutable, thus any data array with a different identity from its predecessor contains new data. direction Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the direction corresponding to positive angles in legacy polar charts. dragmode Determines the mode of drag interactions. "select" and "lasso" apply only to scatter traces with markers or text. "orbit" and "turntable" apply only to 3D scenes. editrevision Controls persistence of user-driven changes in `editable: true` configuration, other than trace names and axis titles. Defaults to `layout.uirevision`. extendfunnelareacolors If `true`, the funnelarea slice colors (whether given by `funnelareacolorway` or inherited from `colorway`) will be extended to three times its original length by first repeating every color 20% lighter then each color 20% darker. This is intended to reduce the likelihood of reusing the same color when you have many slices, but you can set `false` to disable. Colors provided in the trace, using `marker.colors`, are never extended. extendpiecolors If `true`, the pie slice colors (whether given by `piecolorway` or inherited from `colorway`) will be extended to three times its original length by first repeating every color 20% lighter then each color 20% darker. This is intended to reduce the likelihood of reusing the same color when you have many slices, but you can set `false` to disable. Colors provided in the trace, using `marker.colors`, are never extended. extendsunburstcolors If `true`, the sunburst slice colors (whether given by `sunburstcolorway` or inherited from `colorway`) will be extended to three times its original length by first repeating every color 20% lighter then each color 20% darker. This is intended to reduce the likelihood of reusing the same color when you have many slices, but you can set `false` to disable. Colors provided in the trace, using `marker.colors`, are never extended. extendtreemapcolors If `true`, the treemap slice colors (whether given by `treemapcolorway` or inherited from `colorway`) will be extended to three times its original length by first repeating every color 20% lighter then each color 20% darker. This is intended to reduce the likelihood of reusing the same color when you have many slices, but you can set `false` to disable. Colors provided in the trace, using `marker.colors`, are never extended. font Sets the global font. Note that fonts used in traces and other layout components inherit from the global font. funnelareacolorway Sets the default funnelarea slice colors. Defaults to the main `colorway` used for trace colors. If you specify a new list here it can still be extended with lighter and darker colors, see `extendfunnelareacolors`. funnelgap Sets the gap (in plot fraction) between bars of adjacent location coordinates. funnelgroupgap Sets the gap (in plot fraction) between bars of the same location coordinate. funnelmode Determines how bars at the same location coordinate are displayed on the graph. With "stack", the bars are stacked on top of one another With "group", the bars are plotted next to one another centered around the shared location. With "overlay", the bars are plotted over one another, you might need to an "opacity" to see multiple bars. geo plotly.graph_objects.layout.Geo instance or dict with compatible properties grid plotly.graph_objects.layout.Grid instance or dict with compatible properties height Sets the plot's height (in px). hiddenlabels hiddenlabels is the funnelarea & pie chart analog of visible:'legendonly' but it can contain many labels, and can simultaneously hide slices from several pies/funnelarea charts hiddenlabelssrc Sets the source reference on plot.ly for hiddenlabels . hidesources Determines whether or not a text link citing the data source is placed at the bottom-right cored of the figure. Has only an effect only on graphs that have been generated via forked graphs from the plotly service (at https://plot.ly or on-premise). hoverdistance Sets the default distance (in pixels) to look for data to add hover labels (-1 means no cutoff, 0 means no looking for data). This is only a real distance for hovering on point-like objects, like scatter points. For area-like objects (bars, scatter fills, etc) hovering is on inside the area and off outside, but these objects will not supersede hover on point-like objects in case of conflict. hoverlabel plotly.graph_objects.layout.Hoverlabel instance or dict with compatible properties hovermode Determines the mode of hover interactions. If `clickmode` includes the "select" flag, `hovermode` defaults to "closest". If `clickmode` lacks the "select" flag, it defaults to "x" or "y" (depending on the trace's `orientation` value) for plots based on cartesian coordinates. For anything else the default value is "closest". images A tuple of plotly.graph_objects.layout.Image instances or dicts with compatible properties imagedefaults When used in a template (as layout.template.layout.imagedefaults), sets the default property values to use for elements of layout.images legend plotly.graph_objects.layout.Legend instance or dict with compatible properties mapbox plotly.graph_objects.layout.Mapbox instance or dict with compatible properties margin plotly.graph_objects.layout.Margin instance or dict with compatible properties meta Assigns extra meta information that can be used in various `text` attributes. Attributes such as the graph, axis and colorbar `title.text`, annotation `text` `trace.name` in legend items, `rangeselector`, `updatemenus` and `sliders` `label` text all support `meta`. One can access `meta` fields using template strings: `%{meta[i]}` where `i` is the index of the `meta` item in question. `meta` can also be an object for example `{key: value}` which can be accessed %{meta[key]}. metasrc Sets the source reference on plot.ly for meta . modebar plotly.graph_objects.layout.Modebar instance or dict with compatible properties orientation Legacy polar charts are deprecated! Please switch to "polar" subplots. Rotates the entire polar by the given angle in legacy polar charts. paper_bgcolor Sets the color of paper where the graph is drawn. piecolorway Sets the default pie slice colors. Defaults to the main `colorway` used for trace colors. If you specify a new list here it can still be extended with lighter and darker colors, see `extendpiecolors`. plot_bgcolor Sets the color of plotting area in-between x and y axes. polar plotly.graph_objects.layout.Polar instance or dict with compatible properties radialaxis plotly.graph_objects.layout.RadialAxis instance or dict with compatible properties scene plotly.graph_objects.layout.Scene instance or dict with compatible properties selectdirection When "dragmode" is set to "select", this limits the selection of the drag to horizontal, vertical or diagonal. "h" only allows horizontal selection, "v" only vertical, "d" only diagonal and "any" sets no limit. selectionrevision Controls persistence of user-driven changes in selected points from all traces. separators Sets the decimal and thousand separators. For example, *. * puts a '.' before decimals and a space between thousands. In English locales, dflt is ".," but other locales may alter this default. shapes A tuple of plotly.graph_objects.layout.Shape instances or dicts with compatible properties shapedefaults When used in a template (as layout.template.layout.shapedefaults), sets the default property values to use for elements of layout.shapes showlegend Determines whether or not a legend is drawn. Default is `true` if there is a trace to show and any of these: a) Two or more traces would by default be shown in the legend. b) One pie trace is shown in the legend. c) One trace is explicitly given with `showlegend: true`. sliders A tuple of plotly.graph_objects.layout.Slider instances or dicts with compatible properties sliderdefaults When used in a template (as layout.template.layout.sliderdefaults), sets the default property values to use for elements of layout.sliders spikedistance Sets the default distance (in pixels) to look for data to draw spikelines to (-1 means no cutoff, 0 means no looking for data). As with hoverdistance, distance does not apply to area-like objects. In addition, some objects can be hovered on but will not generate spikelines, such as scatter fills. sunburstcolorway Sets the default sunburst slice colors. Defaults to the main `colorway` used for trace colors. If you specify a new list here it can still be extended with lighter and darker colors, see `extendsunburstcolors`. template Default attributes to be applied to the plot. This should be a dict with format: `{'layout': layoutTemplate, 'data': {trace_type: [traceTemplate, ...], ...}}` where `layoutTemplate` is a dict matching the structure of `figure.layout` and `traceTemplate` is a dict matching the structure of the trace with type `trace_type` (e.g. 'scatter'). Alternatively, this may be specified as an instance of plotly.graph_objs.layout.Template. Trace templates are applied cyclically to traces of each type. Container arrays (eg `annotations`) have special handling: An object ending in `defaults` (eg `annotationdefaults`) is applied to each array item. But if an item has a `templateitemname` key we look in the template array for an item with matching `name` and apply that instead. If no matching `name` is found we mark the item invisible. Any named template item not referenced is appended to the end of the array, so this can be used to add a watermark annotation or a logo image, for example. To omit one of these items on the plot, make an item with matching `templateitemname` and `visible: false`. ternary plotly.graph_objects.layout.Ternary instance or dict with compatible properties title plotly.graph_objects.layout.Title instance or dict with compatible properties titlefont Deprecated: Please use layout.title.font instead. Sets the title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. transition Sets transition options used during Plotly.react updates. treemapcolorway Sets the default treemap slice colors. Defaults to the main `colorway` used for trace colors. If you specify a new list here it can still be extended with lighter and darker colors, see `extendtreemapcolors`. uirevision Used to allow user interactions with the plot to persist after `Plotly.react` calls that are unaware of these interactions. If `uirevision` is omitted, or if it is given and it changed from the previous `Plotly.react` call, the exact new figure is used. If `uirevision` is truthy and did NOT change, any attribute that has been affected by user interactions and did not receive a different value in the new figure will keep the interaction value. `layout.uirevision` attribute serves as the default for `uirevision` attributes in various sub-containers. For finer control you can set these sub-attributes directly. For example, if your app separately controls the data on the x and y axes you might set `xaxis.uirevision=*time*` and `yaxis.uirevision=*cost*`. Then if only the y data is changed, you can update `yaxis.uirevision=*quantity*` and the y axis range will reset but the x axis range will retain any user-driven zoom. updatemenus A tuple of plotly.graph_objects.layout.Updatemenu instances or dicts with compatible properties updatemenudefaults When used in a template (as layout.template.layout.updatemenudefaults), sets the default property values to use for elements of layout.updatemenus violingap Sets the gap (in plot fraction) between violins of adjacent location coordinates. Has no effect on traces that have "width" set. violingroupgap Sets the gap (in plot fraction) between violins of the same location coordinate. Has no effect on traces that have "width" set. violinmode Determines how violins at the same location coordinate are displayed on the graph. If "group", the violins are plotted next to one another centered around the shared location. If "overlay", the violins are plotted over one another, you might need to set "opacity" to see them multiple violins. Has no effect on traces that have "width" set. waterfallgap Sets the gap (in plot fraction) between bars of adjacent location coordinates. waterfallgroupgap Sets the gap (in plot fraction) between bars of the same location coordinate. waterfallmode Determines how bars at the same location coordinate are displayed on the graph. With "group", the bars are plotted next to one another centered around the shared location. With "overlay", the bars are plotted over one another, you might need to an "opacity" to see multiple bars. width Sets the plot's width (in px). xaxis plotly.graph_objects.layout.XAxis instance or dict with compatible properties yaxis plotly.graph_objects.layout.YAxis instance or dict with compatible properties """ _mapped_properties = {"titlefont": ("title", "font")} def __init__( self, arg=None, angularaxis=None, annotations=None, annotationdefaults=None, autosize=None, bargap=None, bargroupgap=None, barmode=None, barnorm=None, boxgap=None, boxgroupgap=None, boxmode=None, calendar=None, clickmode=None, coloraxis=None, colorscale=None, colorway=None, datarevision=None, direction=None, dragmode=None, editrevision=None, extendfunnelareacolors=None, extendpiecolors=None, extendsunburstcolors=None, extendtreemapcolors=None, font=None, funnelareacolorway=None, funnelgap=None, funnelgroupgap=None, funnelmode=None, geo=None, grid=None, height=None, hiddenlabels=None, hiddenlabelssrc=None, hidesources=None, hoverdistance=None, hoverlabel=None, hovermode=None, images=None, imagedefaults=None, legend=None, mapbox=None, margin=None, meta=None, metasrc=None, modebar=None, orientation=None, paper_bgcolor=None, piecolorway=None, plot_bgcolor=None, polar=None, radialaxis=None, scene=None, selectdirection=None, selectionrevision=None, separators=None, shapes=None, shapedefaults=None, showlegend=None, sliders=None, sliderdefaults=None, spikedistance=None, sunburstcolorway=None, template=None, ternary=None, title=None, titlefont=None, transition=None, treemapcolorway=None, uirevision=None, updatemenus=None, updatemenudefaults=None, violingap=None, violingroupgap=None, violinmode=None, waterfallgap=None, waterfallgroupgap=None, waterfallmode=None, width=None, xaxis=None, yaxis=None, **kwargs ): """ Construct a new Layout object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.Layout angularaxis plotly.graph_objects.layout.AngularAxis instance or dict with compatible properties annotations A tuple of plotly.graph_objects.layout.Annotation instances or dicts with compatible properties annotationdefaults When used in a template (as layout.template.layout.annotationdefaults), sets the default property values to use for elements of layout.annotations autosize Determines whether or not a layout width or height that has been left undefined by the user is initialized on each relayout. Note that, regardless of this attribute, an undefined layout width or height is always initialized on the first call to plot. bargap Sets the gap (in plot fraction) between bars of adjacent location coordinates. bargroupgap Sets the gap (in plot fraction) between bars of the same location coordinate. barmode Determines how bars at the same location coordinate are displayed on the graph. With "stack", the bars are stacked on top of one another With "relative", the bars are stacked on top of one another, with negative values below the axis, positive values above With "group", the bars are plotted next to one another centered around the shared location. With "overlay", the bars are plotted over one another, you might need to an "opacity" to see multiple bars. barnorm Sets the normalization for bar traces on the graph. With "fraction", the value of each bar is divided by the sum of all values at that location coordinate. "percent" is the same but multiplied by 100 to show percentages. boxgap Sets the gap (in plot fraction) between boxes of adjacent location coordinates. Has no effect on traces that have "width" set. boxgroupgap Sets the gap (in plot fraction) between boxes of the same location coordinate. Has no effect on traces that have "width" set. boxmode Determines how boxes at the same location coordinate are displayed on the graph. If "group", the boxes are plotted next to one another centered around the shared location. If "overlay", the boxes are plotted over one another, you might need to set "opacity" to see them multiple boxes. Has no effect on traces that have "width" set. calendar Sets the default calendar system to use for interpreting and displaying dates throughout the plot. clickmode Determines the mode of single click interactions. "event" is the default value and emits the `plotly_click` event. In addition this mode emits the `plotly_selected` event in drag modes "lasso" and "select", but with no event data attached (kept for compatibility reasons). The "select" flag enables selecting single data points via click. This mode also supports persistent selections, meaning that pressing Shift while clicking, adds to / subtracts from an existing selection. "select" with `hovermode`: "x" can be confusing, consider explicitly setting `hovermode`: "closest" when using this feature. Selection events are sent accordingly as long as "event" flag is set as well. When the "event" flag is missing, `plotly_click` and `plotly_selected` events are not fired. coloraxis plotly.graph_objects.layout.Coloraxis instance or dict with compatible properties colorscale plotly.graph_objects.layout.Colorscale instance or dict with compatible properties colorway Sets the default trace colors. datarevision If provided, a changed value tells `Plotly.react` that one or more data arrays has changed. This way you can modify arrays in-place rather than making a complete new copy for an incremental change. If NOT provided, `Plotly.react` assumes that data arrays are being treated as immutable, thus any data array with a different identity from its predecessor contains new data. direction Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the direction corresponding to positive angles in legacy polar charts. dragmode Determines the mode of drag interactions. "select" and "lasso" apply only to scatter traces with markers or text. "orbit" and "turntable" apply only to 3D scenes. editrevision Controls persistence of user-driven changes in `editable: true` configuration, other than trace names and axis titles. Defaults to `layout.uirevision`. extendfunnelareacolors If `true`, the funnelarea slice colors (whether given by `funnelareacolorway` or inherited from `colorway`) will be extended to three times its original length by first repeating every color 20% lighter then each color 20% darker. This is intended to reduce the likelihood of reusing the same color when you have many slices, but you can set `false` to disable. Colors provided in the trace, using `marker.colors`, are never extended. extendpiecolors If `true`, the pie slice colors (whether given by `piecolorway` or inherited from `colorway`) will be extended to three times its original length by first repeating every color 20% lighter then each color 20% darker. This is intended to reduce the likelihood of reusing the same color when you have many slices, but you can set `false` to disable. Colors provided in the trace, using `marker.colors`, are never extended. extendsunburstcolors If `true`, the sunburst slice colors (whether given by `sunburstcolorway` or inherited from `colorway`) will be extended to three times its original length by first repeating every color 20% lighter then each color 20% darker. This is intended to reduce the likelihood of reusing the same color when you have many slices, but you can set `false` to disable. Colors provided in the trace, using `marker.colors`, are never extended. extendtreemapcolors If `true`, the treemap slice colors (whether given by `treemapcolorway` or inherited from `colorway`) will be extended to three times its original length by first repeating every color 20% lighter then each color 20% darker. This is intended to reduce the likelihood of reusing the same color when you have many slices, but you can set `false` to disable. Colors provided in the trace, using `marker.colors`, are never extended. font Sets the global font. Note that fonts used in traces and other layout components inherit from the global font. funnelareacolorway Sets the default funnelarea slice colors. Defaults to the main `colorway` used for trace colors. If you specify a new list here it can still be extended with lighter and darker colors, see `extendfunnelareacolors`. funnelgap Sets the gap (in plot fraction) between bars of adjacent location coordinates. funnelgroupgap Sets the gap (in plot fraction) between bars of the same location coordinate. funnelmode Determines how bars at the same location coordinate are displayed on the graph. With "stack", the bars are stacked on top of one another With "group", the bars are plotted next to one another centered around the shared location. With "overlay", the bars are plotted over one another, you might need to an "opacity" to see multiple bars. geo plotly.graph_objects.layout.Geo instance or dict with compatible properties grid plotly.graph_objects.layout.Grid instance or dict with compatible properties height Sets the plot's height (in px). hiddenlabels hiddenlabels is the funnelarea & pie chart analog of visible:'legendonly' but it can contain many labels, and can simultaneously hide slices from several pies/funnelarea charts hiddenlabelssrc Sets the source reference on plot.ly for hiddenlabels . hidesources Determines whether or not a text link citing the data source is placed at the bottom-right cored of the figure. Has only an effect only on graphs that have been generated via forked graphs from the plotly service (at https://plot.ly or on-premise). hoverdistance Sets the default distance (in pixels) to look for data to add hover labels (-1 means no cutoff, 0 means no looking for data). This is only a real distance for hovering on point-like objects, like scatter points. For area-like objects (bars, scatter fills, etc) hovering is on inside the area and off outside, but these objects will not supersede hover on point-like objects in case of conflict. hoverlabel plotly.graph_objects.layout.Hoverlabel instance or dict with compatible properties hovermode Determines the mode of hover interactions. If `clickmode` includes the "select" flag, `hovermode` defaults to "closest". If `clickmode` lacks the "select" flag, it defaults to "x" or "y" (depending on the trace's `orientation` value) for plots based on cartesian coordinates. For anything else the default value is "closest". images A tuple of plotly.graph_objects.layout.Image instances or dicts with compatible properties imagedefaults When used in a template (as layout.template.layout.imagedefaults), sets the default property values to use for elements of layout.images legend plotly.graph_objects.layout.Legend instance or dict with compatible properties mapbox plotly.graph_objects.layout.Mapbox instance or dict with compatible properties margin plotly.graph_objects.layout.Margin instance or dict with compatible properties meta Assigns extra meta information that can be used in various `text` attributes. Attributes such as the graph, axis and colorbar `title.text`, annotation `text` `trace.name` in legend items, `rangeselector`, `updatemenus` and `sliders` `label` text all support `meta`. One can access `meta` fields using template strings: `%{meta[i]}` where `i` is the index of the `meta` item in question. `meta` can also be an object for example `{key: value}` which can be accessed %{meta[key]}. metasrc Sets the source reference on plot.ly for meta . modebar plotly.graph_objects.layout.Modebar instance or dict with compatible properties orientation Legacy polar charts are deprecated! Please switch to "polar" subplots. Rotates the entire polar by the given angle in legacy polar charts. paper_bgcolor Sets the color of paper where the graph is drawn. piecolorway Sets the default pie slice colors. Defaults to the main `colorway` used for trace colors. If you specify a new list here it can still be extended with lighter and darker colors, see `extendpiecolors`. plot_bgcolor Sets the color of plotting area in-between x and y axes. polar plotly.graph_objects.layout.Polar instance or dict with compatible properties radialaxis plotly.graph_objects.layout.RadialAxis instance or dict with compatible properties scene plotly.graph_objects.layout.Scene instance or dict with compatible properties selectdirection When "dragmode" is set to "select", this limits the selection of the drag to horizontal, vertical or diagonal. "h" only allows horizontal selection, "v" only vertical, "d" only diagonal and "any" sets no limit. selectionrevision Controls persistence of user-driven changes in selected points from all traces. separators Sets the decimal and thousand separators. For example, *. * puts a '.' before decimals and a space between thousands. In English locales, dflt is ".," but other locales may alter this default. shapes A tuple of plotly.graph_objects.layout.Shape instances or dicts with compatible properties shapedefaults When used in a template (as layout.template.layout.shapedefaults), sets the default property values to use for elements of layout.shapes showlegend Determines whether or not a legend is drawn. Default is `true` if there is a trace to show and any of these: a) Two or more traces would by default be shown in the legend. b) One pie trace is shown in the legend. c) One trace is explicitly given with `showlegend: true`. sliders A tuple of plotly.graph_objects.layout.Slider instances or dicts with compatible properties sliderdefaults When used in a template (as layout.template.layout.sliderdefaults), sets the default property values to use for elements of layout.sliders spikedistance Sets the default distance (in pixels) to look for data to draw spikelines to (-1 means no cutoff, 0 means no looking for data). As with hoverdistance, distance does not apply to area-like objects. In addition, some objects can be hovered on but will not generate spikelines, such as scatter fills. sunburstcolorway Sets the default sunburst slice colors. Defaults to the main `colorway` used for trace colors. If you specify a new list here it can still be extended with lighter and darker colors, see `extendsunburstcolors`. template Default attributes to be applied to the plot. This should be a dict with format: `{'layout': layoutTemplate, 'data': {trace_type: [traceTemplate, ...], ...}}` where `layoutTemplate` is a dict matching the structure of `figure.layout` and `traceTemplate` is a dict matching the structure of the trace with type `trace_type` (e.g. 'scatter'). Alternatively, this may be specified as an instance of plotly.graph_objs.layout.Template. Trace templates are applied cyclically to traces of each type. Container arrays (eg `annotations`) have special handling: An object ending in `defaults` (eg `annotationdefaults`) is applied to each array item. But if an item has a `templateitemname` key we look in the template array for an item with matching `name` and apply that instead. If no matching `name` is found we mark the item invisible. Any named template item not referenced is appended to the end of the array, so this can be used to add a watermark annotation or a logo image, for example. To omit one of these items on the plot, make an item with matching `templateitemname` and `visible: false`. ternary plotly.graph_objects.layout.Ternary instance or dict with compatible properties title plotly.graph_objects.layout.Title instance or dict with compatible properties titlefont Deprecated: Please use layout.title.font instead. Sets the title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. transition Sets transition options used during Plotly.react updates. treemapcolorway Sets the default treemap slice colors. Defaults to the main `colorway` used for trace colors. If you specify a new list here it can still be extended with lighter and darker colors, see `extendtreemapcolors`. uirevision Used to allow user interactions with the plot to persist after `Plotly.react` calls that are unaware of these interactions. If `uirevision` is omitted, or if it is given and it changed from the previous `Plotly.react` call, the exact new figure is used. If `uirevision` is truthy and did NOT change, any attribute that has been affected by user interactions and did not receive a different value in the new figure will keep the interaction value. `layout.uirevision` attribute serves as the default for `uirevision` attributes in various sub-containers. For finer control you can set these sub-attributes directly. For example, if your app separately controls the data on the x and y axes you might set `xaxis.uirevision=*time*` and `yaxis.uirevision=*cost*`. Then if only the y data is changed, you can update `yaxis.uirevision=*quantity*` and the y axis range will reset but the x axis range will retain any user-driven zoom. updatemenus A tuple of plotly.graph_objects.layout.Updatemenu instances or dicts with compatible properties updatemenudefaults When used in a template (as layout.template.layout.updatemenudefaults), sets the default property values to use for elements of layout.updatemenus violingap Sets the gap (in plot fraction) between violins of adjacent location coordinates. Has no effect on traces that have "width" set. violingroupgap Sets the gap (in plot fraction) between violins of the same location coordinate. Has no effect on traces that have "width" set. violinmode Determines how violins at the same location coordinate are displayed on the graph. If "group", the violins are plotted next to one another centered around the shared location. If "overlay", the violins are plotted over one another, you might need to set "opacity" to see them multiple violins. Has no effect on traces that have "width" set. waterfallgap Sets the gap (in plot fraction) between bars of adjacent location coordinates. waterfallgroupgap Sets the gap (in plot fraction) between bars of the same location coordinate. waterfallmode Determines how bars at the same location coordinate are displayed on the graph. With "group", the bars are plotted next to one another centered around the shared location. With "overlay", the bars are plotted over one another, you might need to an "opacity" to see multiple bars. width Sets the plot's width (in px). xaxis plotly.graph_objects.layout.XAxis instance or dict with compatible properties yaxis plotly.graph_objects.layout.YAxis instance or dict with compatible properties Returns ------- Layout """ super(Layout, self).__init__("layout") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.Layout constructor must be a dict or an instance of plotly.graph_objs.Layout""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators import layout as v_layout # Initialize validators # --------------------- self._validators["angularaxis"] = v_layout.AngularAxisValidator() self._validators["annotations"] = v_layout.AnnotationsValidator() self._validators["annotationdefaults"] = v_layout.AnnotationValidator() self._validators["autosize"] = v_layout.AutosizeValidator() self._validators["bargap"] = v_layout.BargapValidator() self._validators["bargroupgap"] = v_layout.BargroupgapValidator() self._validators["barmode"] = v_layout.BarmodeValidator() self._validators["barnorm"] = v_layout.BarnormValidator() self._validators["boxgap"] = v_layout.BoxgapValidator() self._validators["boxgroupgap"] = v_layout.BoxgroupgapValidator() self._validators["boxmode"] = v_layout.BoxmodeValidator() self._validators["calendar"] = v_layout.CalendarValidator() self._validators["clickmode"] = v_layout.ClickmodeValidator() self._validators["coloraxis"] = v_layout.ColoraxisValidator() self._validators["colorscale"] = v_layout.ColorscaleValidator() self._validators["colorway"] = v_layout.ColorwayValidator() self._validators["datarevision"] = v_layout.DatarevisionValidator() self._validators["direction"] = v_layout.DirectionValidator() self._validators["dragmode"] = v_layout.DragmodeValidator() self._validators["editrevision"] = v_layout.EditrevisionValidator() self._validators[ "extendfunnelareacolors" ] = v_layout.ExtendfunnelareacolorsValidator() self._validators["extendpiecolors"] = v_layout.ExtendpiecolorsValidator() self._validators[ "extendsunburstcolors" ] = v_layout.ExtendsunburstcolorsValidator() self._validators[ "extendtreemapcolors" ] = v_layout.ExtendtreemapcolorsValidator() self._validators["font"] = v_layout.FontValidator() self._validators["funnelareacolorway"] = v_layout.FunnelareacolorwayValidator() self._validators["funnelgap"] = v_layout.FunnelgapValidator() self._validators["funnelgroupgap"] = v_layout.FunnelgroupgapValidator() self._validators["funnelmode"] = v_layout.FunnelmodeValidator() self._validators["geo"] = v_layout.GeoValidator() self._validators["grid"] = v_layout.GridValidator() self._validators["height"] = v_layout.HeightValidator() self._validators["hiddenlabels"] = v_layout.HiddenlabelsValidator() self._validators["hiddenlabelssrc"] = v_layout.HiddenlabelssrcValidator() self._validators["hidesources"] = v_layout.HidesourcesValidator() self._validators["hoverdistance"] = v_layout.HoverdistanceValidator() self._validators["hoverlabel"] = v_layout.HoverlabelValidator() self._validators["hovermode"] = v_layout.HovermodeValidator() self._validators["images"] = v_layout.ImagesValidator() self._validators["imagedefaults"] = v_layout.ImageValidator() self._validators["legend"] = v_layout.LegendValidator() self._validators["mapbox"] = v_layout.MapboxValidator() self._validators["margin"] = v_layout.MarginValidator() self._validators["meta"] = v_layout.MetaValidator() self._validators["metasrc"] = v_layout.MetasrcValidator() self._validators["modebar"] = v_layout.ModebarValidator() self._validators["orientation"] = v_layout.OrientationValidator() self._validators["paper_bgcolor"] = v_layout.PaperBgcolorValidator() self._validators["piecolorway"] = v_layout.PiecolorwayValidator() self._validators["plot_bgcolor"] = v_layout.PlotBgcolorValidator() self._validators["polar"] = v_layout.PolarValidator() self._validators["radialaxis"] = v_layout.RadialAxisValidator() self._validators["scene"] = v_layout.SceneValidator() self._validators["selectdirection"] = v_layout.SelectdirectionValidator() self._validators["selectionrevision"] = v_layout.SelectionrevisionValidator() self._validators["separators"] = v_layout.SeparatorsValidator() self._validators["shapes"] = v_layout.ShapesValidator() self._validators["shapedefaults"] = v_layout.ShapeValidator() self._validators["showlegend"] = v_layout.ShowlegendValidator() self._validators["sliders"] = v_layout.SlidersValidator() self._validators["sliderdefaults"] = v_layout.SliderValidator() self._validators["spikedistance"] = v_layout.SpikedistanceValidator() self._validators["sunburstcolorway"] = v_layout.SunburstcolorwayValidator() self._validators["template"] = v_layout.TemplateValidator() self._validators["ternary"] = v_layout.TernaryValidator() self._validators["title"] = v_layout.TitleValidator() self._validators["transition"] = v_layout.TransitionValidator() self._validators["treemapcolorway"] = v_layout.TreemapcolorwayValidator() self._validators["uirevision"] = v_layout.UirevisionValidator() self._validators["updatemenus"] = v_layout.UpdatemenusValidator() self._validators["updatemenudefaults"] = v_layout.UpdatemenuValidator() self._validators["violingap"] = v_layout.ViolingapValidator() self._validators["violingroupgap"] = v_layout.ViolingroupgapValidator() self._validators["violinmode"] = v_layout.ViolinmodeValidator() self._validators["waterfallgap"] = v_layout.WaterfallgapValidator() self._validators["waterfallgroupgap"] = v_layout.WaterfallgroupgapValidator() self._validators["waterfallmode"] = v_layout.WaterfallmodeValidator() self._validators["width"] = v_layout.WidthValidator() self._validators["xaxis"] = v_layout.XAxisValidator() self._validators["yaxis"] = v_layout.YAxisValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("angularaxis", None) self["angularaxis"] = angularaxis if angularaxis is not None else _v _v = arg.pop("annotations", None) self["annotations"] = annotations if annotations is not None else _v _v = arg.pop("annotationdefaults", None) self["annotationdefaults"] = ( annotationdefaults if annotationdefaults is not None else _v ) _v = arg.pop("autosize", None) self["autosize"] = autosize if autosize is not None else _v _v = arg.pop("bargap", None) self["bargap"] = bargap if bargap is not None else _v _v = arg.pop("bargroupgap", None) self["bargroupgap"] = bargroupgap if bargroupgap is not None else _v _v = arg.pop("barmode", None) self["barmode"] = barmode if barmode is not None else _v _v = arg.pop("barnorm", None) self["barnorm"] = barnorm if barnorm is not None else _v _v = arg.pop("boxgap", None) self["boxgap"] = boxgap if boxgap is not None else _v _v = arg.pop("boxgroupgap", None) self["boxgroupgap"] = boxgroupgap if boxgroupgap is not None else _v _v = arg.pop("boxmode", None) self["boxmode"] = boxmode if boxmode is not None else _v _v = arg.pop("calendar", None) self["calendar"] = calendar if calendar is not None else _v _v = arg.pop("clickmode", None) self["clickmode"] = clickmode if clickmode is not None else _v _v = arg.pop("coloraxis", None) self["coloraxis"] = coloraxis if coloraxis is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("colorway", None) self["colorway"] = colorway if colorway is not None else _v _v = arg.pop("datarevision", None) self["datarevision"] = datarevision if datarevision is not None else _v _v = arg.pop("direction", None) self["direction"] = direction if direction is not None else _v _v = arg.pop("dragmode", None) self["dragmode"] = dragmode if dragmode is not None else _v _v = arg.pop("editrevision", None) self["editrevision"] = editrevision if editrevision is not None else _v _v = arg.pop("extendfunnelareacolors", None) self["extendfunnelareacolors"] = ( extendfunnelareacolors if extendfunnelareacolors is not None else _v ) _v = arg.pop("extendpiecolors", None) self["extendpiecolors"] = extendpiecolors if extendpiecolors is not None else _v _v = arg.pop("extendsunburstcolors", None) self["extendsunburstcolors"] = ( extendsunburstcolors if extendsunburstcolors is not None else _v ) _v = arg.pop("extendtreemapcolors", None) self["extendtreemapcolors"] = ( extendtreemapcolors if extendtreemapcolors is not None else _v ) _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("funnelareacolorway", None) self["funnelareacolorway"] = ( funnelareacolorway if funnelareacolorway is not None else _v ) _v = arg.pop("funnelgap", None) self["funnelgap"] = funnelgap if funnelgap is not None else _v _v = arg.pop("funnelgroupgap", None) self["funnelgroupgap"] = funnelgroupgap if funnelgroupgap is not None else _v _v = arg.pop("funnelmode", None) self["funnelmode"] = funnelmode if funnelmode is not None else _v _v = arg.pop("geo", None) self["geo"] = geo if geo is not None else _v _v = arg.pop("grid", None) self["grid"] = grid if grid is not None else _v _v = arg.pop("height", None) self["height"] = height if height is not None else _v _v = arg.pop("hiddenlabels", None) self["hiddenlabels"] = hiddenlabels if hiddenlabels is not None else _v _v = arg.pop("hiddenlabelssrc", None) self["hiddenlabelssrc"] = hiddenlabelssrc if hiddenlabelssrc is not None else _v _v = arg.pop("hidesources", None) self["hidesources"] = hidesources if hidesources is not None else _v _v = arg.pop("hoverdistance", None) self["hoverdistance"] = hoverdistance if hoverdistance is not None else _v _v = arg.pop("hoverlabel", None) self["hoverlabel"] = hoverlabel if hoverlabel is not None else _v _v = arg.pop("hovermode", None) self["hovermode"] = hovermode if hovermode is not None else _v _v = arg.pop("images", None) self["images"] = images if images is not None else _v _v = arg.pop("imagedefaults", None) self["imagedefaults"] = imagedefaults if imagedefaults is not None else _v _v = arg.pop("legend", None) self["legend"] = legend if legend is not None else _v _v = arg.pop("mapbox", None) self["mapbox"] = mapbox if mapbox is not None else _v _v = arg.pop("margin", None) self["margin"] = margin if margin is not None else _v _v = arg.pop("meta", None) self["meta"] = meta if meta is not None else _v _v = arg.pop("metasrc", None) self["metasrc"] = metasrc if metasrc is not None else _v _v = arg.pop("modebar", None) self["modebar"] = modebar if modebar is not None else _v _v = arg.pop("orientation", None) self["orientation"] = orientation if orientation is not None else _v _v = arg.pop("paper_bgcolor", None) self["paper_bgcolor"] = paper_bgcolor if paper_bgcolor is not None else _v _v = arg.pop("piecolorway", None) self["piecolorway"] = piecolorway if piecolorway is not None else _v _v = arg.pop("plot_bgcolor", None) self["plot_bgcolor"] = plot_bgcolor if plot_bgcolor is not None else _v _v = arg.pop("polar", None) self["polar"] = polar if polar is not None else _v _v = arg.pop("radialaxis", None) self["radialaxis"] = radialaxis if radialaxis is not None else _v _v = arg.pop("scene", None) self["scene"] = scene if scene is not None else _v _v = arg.pop("selectdirection", None) self["selectdirection"] = selectdirection if selectdirection is not None else _v _v = arg.pop("selectionrevision", None) self["selectionrevision"] = ( selectionrevision if selectionrevision is not None else _v ) _v = arg.pop("separators", None) self["separators"] = separators if separators is not None else _v _v = arg.pop("shapes", None) self["shapes"] = shapes if shapes is not None else _v _v = arg.pop("shapedefaults", None) self["shapedefaults"] = shapedefaults if shapedefaults is not None else _v _v = arg.pop("showlegend", None) self["showlegend"] = showlegend if showlegend is not None else _v _v = arg.pop("sliders", None) self["sliders"] = sliders if sliders is not None else _v _v = arg.pop("sliderdefaults", None) self["sliderdefaults"] = sliderdefaults if sliderdefaults is not None else _v _v = arg.pop("spikedistance", None) self["spikedistance"] = spikedistance if spikedistance is not None else _v _v = arg.pop("sunburstcolorway", None) self["sunburstcolorway"] = ( sunburstcolorway if sunburstcolorway is not None else _v ) _v = arg.pop("template", None) _v = template if template is not None else _v if _v is not None: self["template"] = _v _v = arg.pop("ternary", None) self["ternary"] = ternary if ternary is not None else _v _v = arg.pop("title", None) self["title"] = title if title is not None else _v _v = arg.pop("titlefont", None) _v = titlefont if titlefont is not None else _v if _v is not None: self["titlefont"] = _v _v = arg.pop("transition", None) self["transition"] = transition if transition is not None else _v _v = arg.pop("treemapcolorway", None) self["treemapcolorway"] = treemapcolorway if treemapcolorway is not None else _v _v = arg.pop("uirevision", None) self["uirevision"] = uirevision if uirevision is not None else _v _v = arg.pop("updatemenus", None) self["updatemenus"] = updatemenus if updatemenus is not None else _v _v = arg.pop("updatemenudefaults", None) self["updatemenudefaults"] = ( updatemenudefaults if updatemenudefaults is not None else _v ) _v = arg.pop("violingap", None) self["violingap"] = violingap if violingap is not None else _v _v = arg.pop("violingroupgap", None) self["violingroupgap"] = violingroupgap if violingroupgap is not None else _v _v = arg.pop("violinmode", None) self["violinmode"] = violinmode if violinmode is not None else _v _v = arg.pop("waterfallgap", None) self["waterfallgap"] = waterfallgap if waterfallgap is not None else _v _v = arg.pop("waterfallgroupgap", None) self["waterfallgroupgap"] = ( waterfallgroupgap if waterfallgroupgap is not None else _v ) _v = arg.pop("waterfallmode", None) self["waterfallmode"] = waterfallmode if waterfallmode is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v _v = arg.pop("xaxis", None) self["xaxis"] = xaxis if xaxis is not None else _v _v = arg.pop("yaxis", None) self["yaxis"] = yaxis if yaxis is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseFrameHierarchyType as _BaseFrameHierarchyType import copy as _copy class Frame(_BaseFrameHierarchyType): # baseframe # --------- @property def baseframe(self): """ The name of the frame into which this frame's properties are merged before applying. This is used to unify properties and avoid needing to specify the same values for the same properties in multiple frames. The 'baseframe' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["baseframe"] @baseframe.setter def baseframe(self, val): self["baseframe"] = val # data # ---- @property def data(self): """ A list of traces this frame modifies. The format is identical to the normal trace definition. Returns ------- Any """ return self["data"] @data.setter def data(self, val): self["data"] = val # group # ----- @property def group(self): """ An identifier that specifies the group to which the frame belongs, used by animate to select a subset of frames. The 'group' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["group"] @group.setter def group(self, val): self["group"] = val # layout # ------ @property def layout(self): """ Layout properties which this frame modifies. The format is identical to the normal layout definition. Returns ------- Any """ return self["layout"] @layout.setter def layout(self, val): self["layout"] = val # name # ---- @property def name(self): """ A label by which to identify the frame The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # traces # ------ @property def traces(self): """ A list of trace indices that identify the respective traces in the data attribute The 'traces' property accepts values of any type Returns ------- Any """ return self["traces"] @traces.setter def traces(self, val): self["traces"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ baseframe The name of the frame into which this frame's properties are merged before applying. This is used to unify properties and avoid needing to specify the same values for the same properties in multiple frames. data A list of traces this frame modifies. The format is identical to the normal trace definition. group An identifier that specifies the group to which the frame belongs, used by animate to select a subset of frames. layout Layout properties which this frame modifies. The format is identical to the normal layout definition. name A label by which to identify the frame traces A list of trace indices that identify the respective traces in the data attribute """ def __init__( self, arg=None, baseframe=None, data=None, group=None, layout=None, name=None, traces=None, **kwargs ): """ Construct a new Frame object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.Frame baseframe The name of the frame into which this frame's properties are merged before applying. This is used to unify properties and avoid needing to specify the same values for the same properties in multiple frames. data A list of traces this frame modifies. The format is identical to the normal trace definition. group An identifier that specifies the group to which the frame belongs, used by animate to select a subset of frames. layout Layout properties which this frame modifies. The format is identical to the normal layout definition. name A label by which to identify the frame traces A list of trace indices that identify the respective traces in the data attribute Returns ------- Frame """ super(Frame, self).__init__("frames") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.Frame constructor must be a dict or an instance of plotly.graph_objs.Frame""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators import frame as v_frame # Initialize validators # --------------------- self._validators["baseframe"] = v_frame.BaseframeValidator() self._validators["data"] = v_frame.DataValidator() self._validators["group"] = v_frame.GroupValidator() self._validators["layout"] = v_frame.LayoutValidator() self._validators["name"] = v_frame.NameValidator() self._validators["traces"] = v_frame.TracesValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("baseframe", None) self["baseframe"] = baseframe if baseframe is not None else _v _v = arg.pop("data", None) self["data"] = data if data is not None else _v _v = arg.pop("group", None) self["group"] = group if group is not None else _v _v = arg.pop("layout", None) self["layout"] = layout if layout is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("traces", None) self["traces"] = traces if traces is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.graph_objs import waterfall from plotly.graph_objs import volume from plotly.graph_objs import violin from plotly.graph_objs import treemap from plotly.graph_objs import table from plotly.graph_objs import surface from plotly.graph_objs import sunburst from plotly.graph_objs import streamtube from plotly.graph_objs import splom from plotly.graph_objs import scatterternary from plotly.graph_objs import scatterpolargl from plotly.graph_objs import scatterpolar from plotly.graph_objs import scattermapbox from plotly.graph_objs import scattergl from plotly.graph_objs import scattergeo from plotly.graph_objs import scattercarpet from plotly.graph_objs import scatter3d from plotly.graph_objs import scatter from plotly.graph_objs import sankey from plotly.graph_objs import pointcloud from plotly.graph_objs import pie from plotly.graph_objs import parcoords from plotly.graph_objs import parcats from plotly.graph_objs import ohlc from plotly.graph_objs import mesh3d from plotly.graph_objs import isosurface from plotly.graph_objs import indicator from plotly.graph_objs import image from plotly.graph_objs import histogram2dcontour from plotly.graph_objs import histogram2d from plotly.graph_objs import histogram from plotly.graph_objs import heatmapgl from plotly.graph_objs import heatmap from plotly.graph_objs import funnelarea from plotly.graph_objs import funnel from plotly.graph_objs import densitymapbox from plotly.graph_objs import contourcarpet from plotly.graph_objs import contour from plotly.graph_objs import cone from plotly.graph_objs import choroplethmapbox from plotly.graph_objs import choropleth from plotly.graph_objs import carpet from plotly.graph_objs import candlestick from plotly.graph_objs import box from plotly.graph_objs import barpolar from plotly.graph_objs import bar from plotly.graph_objs import area from plotly.graph_objs import layout from ._figure import Figure from ._deprecations import ( Data, Annotations, Frames, AngularAxis, Annotation, ColorBar, Contours, ErrorX, ErrorY, ErrorZ, Font, Legend, Line, Margin, Marker, RadialAxis, Scene, Stream, XAxis, YAxis, ZAxis, XBins, YBins, Trace, Histogram2dcontour, ) __all__ = [ "AngularAxis", "Annotation", "Annotations", "Area", "Bar", "Barpolar", "Box", "Candlestick", "Carpet", "Choropleth", "Choroplethmapbox", "ColorBar", "Cone", "Contour", "Contourcarpet", "Contours", "Data", "Densitymapbox", "ErrorX", "ErrorY", "ErrorZ", "Figure", "Font", "Frame", "Frames", "Funnel", "Funnelarea", "Heatmap", "Heatmapgl", "Histogram", "Histogram2d", "Histogram2dContour", "Histogram2dcontour", "Image", "Indicator", "Isosurface", "Layout", "Legend", "Line", "Margin", "Marker", "Mesh3d", "Ohlc", "Parcats", "Parcoords", "Pie", "Pointcloud", "RadialAxis", "Sankey", "Scatter", "Scatter3d", "Scattercarpet", "Scattergeo", "Scattergl", "Scattermapbox", "Scatterpolar", "Scatterpolargl", "Scatterternary", "Scene", "Splom", "Stream", "Streamtube", "Sunburst", "Surface", "Table", "Trace", "Treemap", "Violin", "Volume", "Waterfall", "XAxis", "XBins", "YAxis", "YBins", "ZAxis", "area", "bar", "barpolar", "box", "candlestick", "carpet", "choropleth", "choroplethmapbox", "cone", "contour", "contourcarpet", "densitymapbox", "funnel", "funnelarea", "heatmap", "heatmapgl", "histogram", "histogram2d", "histogram2dcontour", "image", "indicator", "isosurface", "layout", "mesh3d", "ohlc", "parcats", "parcoords", "pie", "pointcloud", "sankey", "scatter", "scatter3d", "scattercarpet", "scattergeo", "scattergl", "scattermapbox", "scatterpolar", "scatterpolargl", "scatterternary", "splom", "streamtube", "sunburst", "surface", "table", "treemap", "violin", "volume", "waterfall", ] try: import ipywidgets from distutils.version import LooseVersion if LooseVersion(ipywidgets.__version__) >= LooseVersion("7.0.0"): from ._figurewidget import FigureWidget del LooseVersion del ipywidgets __all__.append("FigureWidget") except ImportError: pass plotly-4.4.1+dfsg.orig/plotly/graph_objs/area/0000755000175000017500000000000013573746613020641 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/area/hoverlabel/0000755000175000017500000000000013573746613022764 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/area/hoverlabel/__init__.py0000644000175000017500000002540513573721545025100 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "area.hoverlabel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Font object Sets the font used in hover labels. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.area.hoverlabel.Font color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.area.hoverlabel.Font constructor must be a dict or an instance of plotly.graph_objs.area.hoverlabel.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.area.hoverlabel import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["colorsrc"] = v_font.ColorsrcValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["familysrc"] = v_font.FamilysrcValidator() self._validators["size"] = v_font.SizeValidator() self._validators["sizesrc"] = v_font.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/area/__init__.py0000644000175000017500000011350113573721546022751 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Stream(_BaseTraceHierarchyType): # maxpoints # --------- @property def maxpoints(self): """ Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. The 'maxpoints' property is a number and may be specified as: - An int or float in the interval [0, 10000] Returns ------- int|float """ return self["maxpoints"] @maxpoints.setter def maxpoints(self, val): self["maxpoints"] = val # token # ----- @property def token(self): """ The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. The 'token' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["token"] @token.setter def token(self, val): self["token"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "area" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """ def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): """ Construct a new Stream object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.area.Stream maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- Stream """ super(Stream, self).__init__("stream") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.area.Stream constructor must be a dict or an instance of plotly.graph_objs.area.Stream""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.area import stream as v_stream # Initialize validators # --------------------- self._validators["maxpoints"] = v_stream.MaxpointsValidator() self._validators["token"] = v_stream.TokenValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("maxpoints", None) self["maxpoints"] = maxpoints if maxpoints is not None else _v _v = arg.pop("token", None) self["token"] = token if token is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Area traces are deprecated! Please switch to the "barpolar" trace type. Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # opacity # ------- @property def opacity(self): """ Area traces are deprecated! Please switch to the "barpolar" trace type. Sets the marker opacity. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # opacitysrc # ---------- @property def opacitysrc(self): """ Sets the source reference on plot.ly for opacity . The 'opacitysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["opacitysrc"] @opacitysrc.setter def opacitysrc(self, val): self["opacitysrc"] = val # size # ---- @property def size(self): """ Area traces are deprecated! Please switch to the "barpolar" trace type. Sets the marker size (in px). The 'size' property is a number and may be specified as: - An int or float in the interval [0, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # symbol # ------ @property def symbol(self): """ Area traces are deprecated! Please switch to the "barpolar" trace type. Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot-open" to a symbol name. The 'symbol' property is an enumeration that may be specified as: - One of the following enumeration values: [0, 'circle', 100, 'circle-open', 200, 'circle-dot', 300, 'circle-open-dot', 1, 'square', 101, 'square-open', 201, 'square-dot', 301, 'square-open-dot', 2, 'diamond', 102, 'diamond-open', 202, 'diamond-dot', 302, 'diamond-open-dot', 3, 'cross', 103, 'cross-open', 203, 'cross-dot', 303, 'cross-open-dot', 4, 'x', 104, 'x-open', 204, 'x-dot', 304, 'x-open-dot', 5, 'triangle-up', 105, 'triangle-up-open', 205, 'triangle-up-dot', 305, 'triangle-up-open-dot', 6, 'triangle-down', 106, 'triangle-down-open', 206, 'triangle-down-dot', 306, 'triangle-down-open-dot', 7, 'triangle-left', 107, 'triangle-left-open', 207, 'triangle-left-dot', 307, 'triangle-left-open-dot', 8, 'triangle-right', 108, 'triangle-right-open', 208, 'triangle-right-dot', 308, 'triangle-right-open-dot', 9, 'triangle-ne', 109, 'triangle-ne-open', 209, 'triangle-ne-dot', 309, 'triangle-ne-open-dot', 10, 'triangle-se', 110, 'triangle-se-open', 210, 'triangle-se-dot', 310, 'triangle-se-open-dot', 11, 'triangle-sw', 111, 'triangle-sw-open', 211, 'triangle-sw-dot', 311, 'triangle-sw-open-dot', 12, 'triangle-nw', 112, 'triangle-nw-open', 212, 'triangle-nw-dot', 312, 'triangle-nw-open-dot', 13, 'pentagon', 113, 'pentagon-open', 213, 'pentagon-dot', 313, 'pentagon-open-dot', 14, 'hexagon', 114, 'hexagon-open', 214, 'hexagon-dot', 314, 'hexagon-open-dot', 15, 'hexagon2', 115, 'hexagon2-open', 215, 'hexagon2-dot', 315, 'hexagon2-open-dot', 16, 'octagon', 116, 'octagon-open', 216, 'octagon-dot', 316, 'octagon-open-dot', 17, 'star', 117, 'star-open', 217, 'star-dot', 317, 'star-open-dot', 18, 'hexagram', 118, 'hexagram-open', 218, 'hexagram-dot', 318, 'hexagram-open-dot', 19, 'star-triangle-up', 119, 'star-triangle-up-open', 219, 'star-triangle-up-dot', 319, 'star-triangle-up-open-dot', 20, 'star-triangle-down', 120, 'star-triangle-down-open', 220, 'star-triangle-down-dot', 320, 'star-triangle-down-open-dot', 21, 'star-square', 121, 'star-square-open', 221, 'star-square-dot', 321, 'star-square-open-dot', 22, 'star-diamond', 122, 'star-diamond-open', 222, 'star-diamond-dot', 322, 'star-diamond-open-dot', 23, 'diamond-tall', 123, 'diamond-tall-open', 223, 'diamond-tall-dot', 323, 'diamond-tall-open-dot', 24, 'diamond-wide', 124, 'diamond-wide-open', 224, 'diamond-wide-dot', 324, 'diamond-wide-open-dot', 25, 'hourglass', 125, 'hourglass-open', 26, 'bowtie', 126, 'bowtie-open', 27, 'circle-cross', 127, 'circle-cross-open', 28, 'circle-x', 128, 'circle-x-open', 29, 'square-cross', 129, 'square-cross-open', 30, 'square-x', 130, 'square-x-open', 31, 'diamond-cross', 131, 'diamond-cross-open', 32, 'diamond-x', 132, 'diamond-x-open', 33, 'cross-thin', 133, 'cross-thin-open', 34, 'x-thin', 134, 'x-thin-open', 35, 'asterisk', 135, 'asterisk-open', 36, 'hash', 136, 'hash-open', 236, 'hash-dot', 336, 'hash-open-dot', 37, 'y-up', 137, 'y-up-open', 38, 'y-down', 138, 'y-down-open', 39, 'y-left', 139, 'y-left-open', 40, 'y-right', 140, 'y-right-open', 41, 'line-ew', 141, 'line-ew-open', 42, 'line-ns', 142, 'line-ns-open', 43, 'line-ne', 143, 'line-ne-open', 44, 'line-nw', 144, 'line-nw-open'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["symbol"] @symbol.setter def symbol(self, val): self["symbol"] = val # symbolsrc # --------- @property def symbolsrc(self): """ Sets the source reference on plot.ly for symbol . The 'symbolsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["symbolsrc"] @symbolsrc.setter def symbolsrc(self, val): self["symbolsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "area" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Area traces are deprecated! Please switch to the "barpolar" trace type. Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. colorsrc Sets the source reference on plot.ly for color . opacity Area traces are deprecated! Please switch to the "barpolar" trace type. Sets the marker opacity. opacitysrc Sets the source reference on plot.ly for opacity . size Area traces are deprecated! Please switch to the "barpolar" trace type. Sets the marker size (in px). sizesrc Sets the source reference on plot.ly for size . symbol Area traces are deprecated! Please switch to the "barpolar" trace type. Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot-open" to a symbol name. symbolsrc Sets the source reference on plot.ly for symbol . """ def __init__( self, arg=None, color=None, colorsrc=None, opacity=None, opacitysrc=None, size=None, sizesrc=None, symbol=None, symbolsrc=None, **kwargs ): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.area.Marker color Area traces are deprecated! Please switch to the "barpolar" trace type. Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. colorsrc Sets the source reference on plot.ly for color . opacity Area traces are deprecated! Please switch to the "barpolar" trace type. Sets the marker opacity. opacitysrc Sets the source reference on plot.ly for opacity . size Area traces are deprecated! Please switch to the "barpolar" trace type. Sets the marker size (in px). sizesrc Sets the source reference on plot.ly for size . symbol Area traces are deprecated! Please switch to the "barpolar" trace type. Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot-open" to a symbol name. symbolsrc Sets the source reference on plot.ly for symbol . Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.area.Marker constructor must be a dict or an instance of plotly.graph_objs.area.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.area import marker as v_marker # Initialize validators # --------------------- self._validators["color"] = v_marker.ColorValidator() self._validators["colorsrc"] = v_marker.ColorsrcValidator() self._validators["opacity"] = v_marker.OpacityValidator() self._validators["opacitysrc"] = v_marker.OpacitysrcValidator() self._validators["size"] = v_marker.SizeValidator() self._validators["sizesrc"] = v_marker.SizesrcValidator() self._validators["symbol"] = v_marker.SymbolValidator() self._validators["symbolsrc"] = v_marker.SymbolsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("opacitysrc", None) self["opacitysrc"] = opacitysrc if opacitysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v _v = arg.pop("symbol", None) self["symbol"] = symbol if symbol is not None else _v _v = arg.pop("symbolsrc", None) self["symbolsrc"] = symbolsrc if symbolsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Hoverlabel(_BaseTraceHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'right', 'auto'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["align"] @align.setter def align(self, val): self["align"] = val # alignsrc # -------- @property def alignsrc(self): """ Sets the source reference on plot.ly for align . The 'alignsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["alignsrc"] @alignsrc.setter def alignsrc(self, val): self["alignsrc"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the hover labels for this trace The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bgcolorsrc # ---------- @property def bgcolorsrc(self): """ Sets the source reference on plot.ly for bgcolor . The 'bgcolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bgcolorsrc"] @bgcolorsrc.setter def bgcolorsrc(self, val): self["bgcolorsrc"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the border color of the hover labels for this trace. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # bordercolorsrc # -------------- @property def bordercolorsrc(self): """ Sets the source reference on plot.ly for bordercolor . The 'bordercolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bordercolorsrc"] @bordercolorsrc.setter def bordercolorsrc(self, val): self["bordercolorsrc"] = val # font # ---- @property def font(self): """ Sets the font used in hover labels. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.area.hoverlabel.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.area.hoverlabel.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # namelength # ---------- @property def namelength(self): """ Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. The 'namelength' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [-1, 9223372036854775807] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|numpy.ndarray """ return self["namelength"] @namelength.setter def namelength(self, val): self["namelength"] = val # namelengthsrc # ------------- @property def namelengthsrc(self): """ Sets the source reference on plot.ly for namelength . The 'namelengthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["namelengthsrc"] @namelengthsrc.setter def namelengthsrc(self, val): self["namelengthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "area" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """ def __init__( self, arg=None, align=None, alignsrc=None, bgcolor=None, bgcolorsrc=None, bordercolor=None, bordercolorsrc=None, font=None, namelength=None, namelengthsrc=None, **kwargs ): """ Construct a new Hoverlabel object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.area.Hoverlabel align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- Hoverlabel """ super(Hoverlabel, self).__init__("hoverlabel") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.area.Hoverlabel constructor must be a dict or an instance of plotly.graph_objs.area.Hoverlabel""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.area import hoverlabel as v_hoverlabel # Initialize validators # --------------------- self._validators["align"] = v_hoverlabel.AlignValidator() self._validators["alignsrc"] = v_hoverlabel.AlignsrcValidator() self._validators["bgcolor"] = v_hoverlabel.BgcolorValidator() self._validators["bgcolorsrc"] = v_hoverlabel.BgcolorsrcValidator() self._validators["bordercolor"] = v_hoverlabel.BordercolorValidator() self._validators["bordercolorsrc"] = v_hoverlabel.BordercolorsrcValidator() self._validators["font"] = v_hoverlabel.FontValidator() self._validators["namelength"] = v_hoverlabel.NamelengthValidator() self._validators["namelengthsrc"] = v_hoverlabel.NamelengthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("alignsrc", None) self["alignsrc"] = alignsrc if alignsrc is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bgcolorsrc", None) self["bgcolorsrc"] = bgcolorsrc if bgcolorsrc is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("bordercolorsrc", None) self["bordercolorsrc"] = bordercolorsrc if bordercolorsrc is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("namelength", None) self["namelength"] = namelength if namelength is not None else _v _v = arg.pop("namelengthsrc", None) self["namelengthsrc"] = namelengthsrc if namelengthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Hoverlabel", "Marker", "Stream", "hoverlabel"] from plotly.graph_objs.area import hoverlabel plotly-4.4.1+dfsg.orig/plotly/graph_objs/histogram2dcontour/0000755000175000017500000000000013573746613023566 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/histogram2dcontour/hoverlabel/0000755000175000017500000000000013573746613025711 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/histogram2dcontour/hoverlabel/__init__.py0000644000175000017500000002552713573721546030033 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram2dcontour.hoverlabel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Font object Sets the font used in hover labels. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.histogram2dcontour.hoverlabel.Font color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.histogram2dcontour.hoverlabel.Font constructor must be a dict or an instance of plotly.graph_objs.histogram2dcontour.hoverlabel.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram2dcontour.hoverlabel import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["colorsrc"] = v_font.ColorsrcValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["familysrc"] = v_font.FamilysrcValidator() self._validators["size"] = v_font.SizeValidator() self._validators["sizesrc"] = v_font.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/histogram2dcontour/colorbar/0000755000175000017500000000000013573746613025371 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/histogram2dcontour/colorbar/title/0000755000175000017500000000000013573746613026512 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/histogram2dcontour/colorbar/title/__init__.py0000644000175000017500000002061513573721546030625 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram2dcontour.colorbar.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.histogram2dcontour.col orbar.title.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.histogram2dcontour.colorbar.title.Font constructor must be a dict or an instance of plotly.graph_objs.histogram2dcontour.colorbar.title.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram2dcontour.colorbar.title import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/histogram2dcontour/colorbar/__init__.py0000644000175000017500000006106513573721547027511 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Title(_BaseTraceHierarchyType): # font # ---- @property def font(self): """ Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.histogram2dcontour.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.histogram2dcontour.colorbar.title.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # side # ---- @property def side(self): """ Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- Any """ return self["side"] @side.setter def side(self, val): self["side"] = val # text # ---- @property def text(self): """ Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram2dcontour.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """ def __init__(self, arg=None, font=None, side=None, text=None, **kwargs): """ Construct a new Title object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.histogram2dcontour.colorbar.Title font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- Title """ super(Title, self).__init__("title") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.histogram2dcontour.colorbar.Title constructor must be a dict or an instance of plotly.graph_objs.histogram2dcontour.colorbar.Title""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram2dcontour.colorbar import title as v_title # Initialize validators # --------------------- self._validators["font"] = v_title.FontValidator() self._validators["side"] = v_title.SideValidator() self._validators["text"] = v_title.TextValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("side", None) self["side"] = side if side is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickformatstop(_BaseTraceHierarchyType): # dtickrange # ---------- @property def dtickrange(self): """ range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" The 'dtickrange' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'dtickrange[0]' property accepts values of any type (1) The 'dtickrange[1]' property accepts values of any type Returns ------- list """ return self["dtickrange"] @dtickrange.setter def dtickrange(self, val): self["dtickrange"] = val # enabled # ------- @property def enabled(self): """ Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. The 'enabled' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["enabled"] @enabled.setter def enabled(self, val): self["enabled"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # value # ----- @property def value(self): """ string - dtickformat for described zoom level, the same as "tickformat" The 'value' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram2dcontour.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """ def __init__( self, arg=None, dtickrange=None, enabled=None, name=None, templateitemname=None, value=None, **kwargs ): """ Construct a new Tickformatstop object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.histogram2dcontour.col orbar.Tickformatstop dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- Tickformatstop """ super(Tickformatstop, self).__init__("tickformatstops") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.histogram2dcontour.colorbar.Tickformatstop constructor must be a dict or an instance of plotly.graph_objs.histogram2dcontour.colorbar.Tickformatstop""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram2dcontour.colorbar import ( tickformatstop as v_tickformatstop, ) # Initialize validators # --------------------- self._validators["dtickrange"] = v_tickformatstop.DtickrangeValidator() self._validators["enabled"] = v_tickformatstop.EnabledValidator() self._validators["name"] = v_tickformatstop.NameValidator() self._validators[ "templateitemname" ] = v_tickformatstop.TemplateitemnameValidator() self._validators["value"] = v_tickformatstop.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtickrange", None) self["dtickrange"] = dtickrange if dtickrange is not None else _v _v = arg.pop("enabled", None) self["enabled"] = enabled if enabled is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram2dcontour.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Tickfont object Sets the color bar's tick label font Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.histogram2dcontour.colorbar.Tickfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Tickfont """ super(Tickfont, self).__init__("tickfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.histogram2dcontour.colorbar.Tickfont constructor must be a dict or an instance of plotly.graph_objs.histogram2dcontour.colorbar.Tickfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram2dcontour.colorbar import tickfont as v_tickfont # Initialize validators # --------------------- self._validators["color"] = v_tickfont.ColorValidator() self._validators["family"] = v_tickfont.FamilyValidator() self._validators["size"] = v_tickfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Tickfont", "Tickformatstop", "Tickformatstop", "Title", "title"] from plotly.graph_objs.histogram2dcontour.colorbar import title plotly-4.4.1+dfsg.orig/plotly/graph_objs/histogram2dcontour/contours/0000755000175000017500000000000013573746613025442 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/histogram2dcontour/contours/__init__.py0000644000175000017500000002076713573721546027565 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Labelfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram2dcontour.contours" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Labelfont object Sets the font used for labeling the contour levels. The default color comes from the lines, if shown. The default family and size come from `layout.font`. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.histogram2dcontour.contours.Labelfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Labelfont """ super(Labelfont, self).__init__("labelfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.histogram2dcontour.contours.Labelfont constructor must be a dict or an instance of plotly.graph_objs.histogram2dcontour.contours.Labelfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram2dcontour.contours import ( labelfont as v_labelfont, ) # Initialize validators # --------------------- self._validators["color"] = v_labelfont.ColorValidator() self._validators["family"] = v_labelfont.FamilyValidator() self._validators["size"] = v_labelfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Labelfont"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/histogram2dcontour/__init__.py0000644000175000017500000041460713573721550025704 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class YBins(_BaseTraceHierarchyType): # end # --- @property def end(self): """ Sets the end value for the y axis bins. The last bin may not end exactly at this value, we increment the bin edge by `size` from `start` until we reach or exceed `end`. Defaults to the maximum data value. Like `start`, for dates use a date string, and for category data `end` is based on the category serial numbers. The 'end' property accepts values of any type Returns ------- Any """ return self["end"] @end.setter def end(self, val): self["end"] = val # size # ---- @property def size(self): """ Sets the size of each y axis bin. Default behavior: If `nbinsy` is 0 or omitted, we choose a nice round bin size such that the number of bins is about the same as the typical number of samples in each bin. If `nbinsy` is provided, we choose a nice round bin size giving no more than that many bins. For date data, use milliseconds or "M" for months, as in `axis.dtick`. For category data, the number of categories to bin together (always defaults to 1). The 'size' property accepts values of any type Returns ------- Any """ return self["size"] @size.setter def size(self, val): self["size"] = val # start # ----- @property def start(self): """ Sets the starting value for the y axis bins. Defaults to the minimum data value, shifted down if necessary to make nice round values and to remove ambiguous bin edges. For example, if most of the data is integers we shift the bin edges 0.5 down, so a `size` of 5 would have a default `start` of -0.5, so it is clear that 0-4 are in the first bin, 5-9 in the second, but continuous data gets a start of 0 and bins [0,5), [5,10) etc. Dates behave similarly, and `start` should be a date string. For category data, `start` is based on the category serial numbers, and defaults to -0.5. The 'start' property accepts values of any type Returns ------- Any """ return self["start"] @start.setter def start(self, val): self["start"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram2dcontour" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ end Sets the end value for the y axis bins. The last bin may not end exactly at this value, we increment the bin edge by `size` from `start` until we reach or exceed `end`. Defaults to the maximum data value. Like `start`, for dates use a date string, and for category data `end` is based on the category serial numbers. size Sets the size of each y axis bin. Default behavior: If `nbinsy` is 0 or omitted, we choose a nice round bin size such that the number of bins is about the same as the typical number of samples in each bin. If `nbinsy` is provided, we choose a nice round bin size giving no more than that many bins. For date data, use milliseconds or "M" for months, as in `axis.dtick`. For category data, the number of categories to bin together (always defaults to 1). start Sets the starting value for the y axis bins. Defaults to the minimum data value, shifted down if necessary to make nice round values and to remove ambiguous bin edges. For example, if most of the data is integers we shift the bin edges 0.5 down, so a `size` of 5 would have a default `start` of -0.5, so it is clear that 0-4 are in the first bin, 5-9 in the second, but continuous data gets a start of 0 and bins [0,5), [5,10) etc. Dates behave similarly, and `start` should be a date string. For category data, `start` is based on the category serial numbers, and defaults to -0.5. """ def __init__(self, arg=None, end=None, size=None, start=None, **kwargs): """ Construct a new YBins object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.histogram2dcontour.YBins end Sets the end value for the y axis bins. The last bin may not end exactly at this value, we increment the bin edge by `size` from `start` until we reach or exceed `end`. Defaults to the maximum data value. Like `start`, for dates use a date string, and for category data `end` is based on the category serial numbers. size Sets the size of each y axis bin. Default behavior: If `nbinsy` is 0 or omitted, we choose a nice round bin size such that the number of bins is about the same as the typical number of samples in each bin. If `nbinsy` is provided, we choose a nice round bin size giving no more than that many bins. For date data, use milliseconds or "M" for months, as in `axis.dtick`. For category data, the number of categories to bin together (always defaults to 1). start Sets the starting value for the y axis bins. Defaults to the minimum data value, shifted down if necessary to make nice round values and to remove ambiguous bin edges. For example, if most of the data is integers we shift the bin edges 0.5 down, so a `size` of 5 would have a default `start` of -0.5, so it is clear that 0-4 are in the first bin, 5-9 in the second, but continuous data gets a start of 0 and bins [0,5), [5,10) etc. Dates behave similarly, and `start` should be a date string. For category data, `start` is based on the category serial numbers, and defaults to -0.5. Returns ------- YBins """ super(YBins, self).__init__("ybins") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.histogram2dcontour.YBins constructor must be a dict or an instance of plotly.graph_objs.histogram2dcontour.YBins""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram2dcontour import ybins as v_ybins # Initialize validators # --------------------- self._validators["end"] = v_ybins.EndValidator() self._validators["size"] = v_ybins.SizeValidator() self._validators["start"] = v_ybins.StartValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("end", None) self["end"] = end if end is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("start", None) self["start"] = start if start is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class XBins(_BaseTraceHierarchyType): # end # --- @property def end(self): """ Sets the end value for the x axis bins. The last bin may not end exactly at this value, we increment the bin edge by `size` from `start` until we reach or exceed `end`. Defaults to the maximum data value. Like `start`, for dates use a date string, and for category data `end` is based on the category serial numbers. The 'end' property accepts values of any type Returns ------- Any """ return self["end"] @end.setter def end(self, val): self["end"] = val # size # ---- @property def size(self): """ Sets the size of each x axis bin. Default behavior: If `nbinsx` is 0 or omitted, we choose a nice round bin size such that the number of bins is about the same as the typical number of samples in each bin. If `nbinsx` is provided, we choose a nice round bin size giving no more than that many bins. For date data, use milliseconds or "M" for months, as in `axis.dtick`. For category data, the number of categories to bin together (always defaults to 1). The 'size' property accepts values of any type Returns ------- Any """ return self["size"] @size.setter def size(self, val): self["size"] = val # start # ----- @property def start(self): """ Sets the starting value for the x axis bins. Defaults to the minimum data value, shifted down if necessary to make nice round values and to remove ambiguous bin edges. For example, if most of the data is integers we shift the bin edges 0.5 down, so a `size` of 5 would have a default `start` of -0.5, so it is clear that 0-4 are in the first bin, 5-9 in the second, but continuous data gets a start of 0 and bins [0,5), [5,10) etc. Dates behave similarly, and `start` should be a date string. For category data, `start` is based on the category serial numbers, and defaults to -0.5. The 'start' property accepts values of any type Returns ------- Any """ return self["start"] @start.setter def start(self, val): self["start"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram2dcontour" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ end Sets the end value for the x axis bins. The last bin may not end exactly at this value, we increment the bin edge by `size` from `start` until we reach or exceed `end`. Defaults to the maximum data value. Like `start`, for dates use a date string, and for category data `end` is based on the category serial numbers. size Sets the size of each x axis bin. Default behavior: If `nbinsx` is 0 or omitted, we choose a nice round bin size such that the number of bins is about the same as the typical number of samples in each bin. If `nbinsx` is provided, we choose a nice round bin size giving no more than that many bins. For date data, use milliseconds or "M" for months, as in `axis.dtick`. For category data, the number of categories to bin together (always defaults to 1). start Sets the starting value for the x axis bins. Defaults to the minimum data value, shifted down if necessary to make nice round values and to remove ambiguous bin edges. For example, if most of the data is integers we shift the bin edges 0.5 down, so a `size` of 5 would have a default `start` of -0.5, so it is clear that 0-4 are in the first bin, 5-9 in the second, but continuous data gets a start of 0 and bins [0,5), [5,10) etc. Dates behave similarly, and `start` should be a date string. For category data, `start` is based on the category serial numbers, and defaults to -0.5. """ def __init__(self, arg=None, end=None, size=None, start=None, **kwargs): """ Construct a new XBins object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.histogram2dcontour.XBins end Sets the end value for the x axis bins. The last bin may not end exactly at this value, we increment the bin edge by `size` from `start` until we reach or exceed `end`. Defaults to the maximum data value. Like `start`, for dates use a date string, and for category data `end` is based on the category serial numbers. size Sets the size of each x axis bin. Default behavior: If `nbinsx` is 0 or omitted, we choose a nice round bin size such that the number of bins is about the same as the typical number of samples in each bin. If `nbinsx` is provided, we choose a nice round bin size giving no more than that many bins. For date data, use milliseconds or "M" for months, as in `axis.dtick`. For category data, the number of categories to bin together (always defaults to 1). start Sets the starting value for the x axis bins. Defaults to the minimum data value, shifted down if necessary to make nice round values and to remove ambiguous bin edges. For example, if most of the data is integers we shift the bin edges 0.5 down, so a `size` of 5 would have a default `start` of -0.5, so it is clear that 0-4 are in the first bin, 5-9 in the second, but continuous data gets a start of 0 and bins [0,5), [5,10) etc. Dates behave similarly, and `start` should be a date string. For category data, `start` is based on the category serial numbers, and defaults to -0.5. Returns ------- XBins """ super(XBins, self).__init__("xbins") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.histogram2dcontour.XBins constructor must be a dict or an instance of plotly.graph_objs.histogram2dcontour.XBins""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram2dcontour import xbins as v_xbins # Initialize validators # --------------------- self._validators["end"] = v_xbins.EndValidator() self._validators["size"] = v_xbins.SizeValidator() self._validators["start"] = v_xbins.StartValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("end", None) self["end"] = end if end is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("start", None) self["start"] = start if start is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Stream(_BaseTraceHierarchyType): # maxpoints # --------- @property def maxpoints(self): """ Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. The 'maxpoints' property is a number and may be specified as: - An int or float in the interval [0, 10000] Returns ------- int|float """ return self["maxpoints"] @maxpoints.setter def maxpoints(self, val): self["maxpoints"] = val # token # ----- @property def token(self): """ The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. The 'token' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["token"] @token.setter def token(self, val): self["token"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram2dcontour" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """ def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): """ Construct a new Stream object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.histogram2dcontour.Stream maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- Stream """ super(Stream, self).__init__("stream") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.histogram2dcontour.Stream constructor must be a dict or an instance of plotly.graph_objs.histogram2dcontour.Stream""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram2dcontour import stream as v_stream # Initialize validators # --------------------- self._validators["maxpoints"] = v_stream.MaxpointsValidator() self._validators["token"] = v_stream.TokenValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("maxpoints", None) self["maxpoints"] = maxpoints if maxpoints is not None else _v _v = arg.pop("token", None) self["token"] = token if token is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the aggregation data. The 'color' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram2dcontour" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the aggregation data. colorsrc Sets the source reference on plot.ly for color . """ def __init__(self, arg=None, color=None, colorsrc=None, **kwargs): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.histogram2dcontour.Marker color Sets the aggregation data. colorsrc Sets the source reference on plot.ly for color . Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.histogram2dcontour.Marker constructor must be a dict or an instance of plotly.graph_objs.histogram2dcontour.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram2dcontour import marker as v_marker # Initialize validators # --------------------- self._validators["color"] = v_marker.ColorValidator() self._validators["colorsrc"] = v_marker.ColorsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the color of the contour level. Has no effect if `contours.coloring` is set to "lines". The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # dash # ---- @property def dash(self): """ Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). The 'dash' property is an enumeration that may be specified as: - One of the following dash styles: ['solid', 'dot', 'dash', 'longdash', 'dashdot', 'longdashdot'] - A string containing a dash length list in pixels or percentages (e.g. '5px 10px 2px 2px', '5, 10, 2, 2', '10% 20% 40%', etc.) Returns ------- str """ return self["dash"] @dash.setter def dash(self, val): self["dash"] = val # smoothing # --------- @property def smoothing(self): """ Sets the amount of smoothing for the contour lines, where 0 corresponds to no smoothing. The 'smoothing' property is a number and may be specified as: - An int or float in the interval [0, 1.3] Returns ------- int|float """ return self["smoothing"] @smoothing.setter def smoothing(self, val): self["smoothing"] = val # width # ----- @property def width(self): """ Sets the contour line width in (in px) The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram2dcontour" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the color of the contour level. Has no effect if `contours.coloring` is set to "lines". dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). smoothing Sets the amount of smoothing for the contour lines, where 0 corresponds to no smoothing. width Sets the contour line width in (in px) """ def __init__( self, arg=None, color=None, dash=None, smoothing=None, width=None, **kwargs ): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.histogram2dcontour.Line color Sets the color of the contour level. Has no effect if `contours.coloring` is set to "lines". dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). smoothing Sets the amount of smoothing for the contour lines, where 0 corresponds to no smoothing. width Sets the contour line width in (in px) Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.histogram2dcontour.Line constructor must be a dict or an instance of plotly.graph_objs.histogram2dcontour.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram2dcontour import line as v_line # Initialize validators # --------------------- self._validators["color"] = v_line.ColorValidator() self._validators["dash"] = v_line.DashValidator() self._validators["smoothing"] = v_line.SmoothingValidator() self._validators["width"] = v_line.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("dash", None) self["dash"] = dash if dash is not None else _v _v = arg.pop("smoothing", None) self["smoothing"] = smoothing if smoothing is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Hoverlabel(_BaseTraceHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'right', 'auto'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["align"] @align.setter def align(self, val): self["align"] = val # alignsrc # -------- @property def alignsrc(self): """ Sets the source reference on plot.ly for align . The 'alignsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["alignsrc"] @alignsrc.setter def alignsrc(self, val): self["alignsrc"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the hover labels for this trace The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bgcolorsrc # ---------- @property def bgcolorsrc(self): """ Sets the source reference on plot.ly for bgcolor . The 'bgcolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bgcolorsrc"] @bgcolorsrc.setter def bgcolorsrc(self, val): self["bgcolorsrc"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the border color of the hover labels for this trace. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # bordercolorsrc # -------------- @property def bordercolorsrc(self): """ Sets the source reference on plot.ly for bordercolor . The 'bordercolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bordercolorsrc"] @bordercolorsrc.setter def bordercolorsrc(self, val): self["bordercolorsrc"] = val # font # ---- @property def font(self): """ Sets the font used in hover labels. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.histogram2dcontour.hoverlabel.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.histogram2dcontour.hoverlabel.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # namelength # ---------- @property def namelength(self): """ Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. The 'namelength' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [-1, 9223372036854775807] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|numpy.ndarray """ return self["namelength"] @namelength.setter def namelength(self, val): self["namelength"] = val # namelengthsrc # ------------- @property def namelengthsrc(self): """ Sets the source reference on plot.ly for namelength . The 'namelengthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["namelengthsrc"] @namelengthsrc.setter def namelengthsrc(self, val): self["namelengthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram2dcontour" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """ def __init__( self, arg=None, align=None, alignsrc=None, bgcolor=None, bgcolorsrc=None, bordercolor=None, bordercolorsrc=None, font=None, namelength=None, namelengthsrc=None, **kwargs ): """ Construct a new Hoverlabel object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.histogram2dcontour.Hoverlabel align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- Hoverlabel """ super(Hoverlabel, self).__init__("hoverlabel") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.histogram2dcontour.Hoverlabel constructor must be a dict or an instance of plotly.graph_objs.histogram2dcontour.Hoverlabel""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram2dcontour import hoverlabel as v_hoverlabel # Initialize validators # --------------------- self._validators["align"] = v_hoverlabel.AlignValidator() self._validators["alignsrc"] = v_hoverlabel.AlignsrcValidator() self._validators["bgcolor"] = v_hoverlabel.BgcolorValidator() self._validators["bgcolorsrc"] = v_hoverlabel.BgcolorsrcValidator() self._validators["bordercolor"] = v_hoverlabel.BordercolorValidator() self._validators["bordercolorsrc"] = v_hoverlabel.BordercolorsrcValidator() self._validators["font"] = v_hoverlabel.FontValidator() self._validators["namelength"] = v_hoverlabel.NamelengthValidator() self._validators["namelengthsrc"] = v_hoverlabel.NamelengthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("alignsrc", None) self["alignsrc"] = alignsrc if alignsrc is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bgcolorsrc", None) self["bgcolorsrc"] = bgcolorsrc if bgcolorsrc is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("bordercolorsrc", None) self["bordercolorsrc"] = bordercolorsrc if bordercolorsrc is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("namelength", None) self["namelength"] = namelength if namelength is not None else _v _v = arg.pop("namelengthsrc", None) self["namelengthsrc"] = namelengthsrc if namelengthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Contours(_BaseTraceHierarchyType): # coloring # -------- @property def coloring(self): """ Determines the coloring method showing the contour values. If "fill", coloring is done evenly between each contour level If "heatmap", a heatmap gradient coloring is applied between each contour level. If "lines", coloring is done on the contour lines. If "none", no coloring is applied on this trace. The 'coloring' property is an enumeration that may be specified as: - One of the following enumeration values: ['fill', 'heatmap', 'lines', 'none'] Returns ------- Any """ return self["coloring"] @coloring.setter def coloring(self, val): self["coloring"] = val # end # --- @property def end(self): """ Sets the end contour level value. Must be more than `contours.start` The 'end' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["end"] @end.setter def end(self, val): self["end"] = val # labelfont # --------- @property def labelfont(self): """ Sets the font used for labeling the contour levels. The default color comes from the lines, if shown. The default family and size come from `layout.font`. The 'labelfont' property is an instance of Labelfont that may be specified as: - An instance of plotly.graph_objs.histogram2dcontour.contours.Labelfont - A dict of string/value properties that will be passed to the Labelfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.histogram2dcontour.contours.Labelfont """ return self["labelfont"] @labelfont.setter def labelfont(self, val): self["labelfont"] = val # labelformat # ----------- @property def labelformat(self): """ Sets the contour label formatting rule using d3 formatting mini-language which is very similar to Python, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format The 'labelformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["labelformat"] @labelformat.setter def labelformat(self, val): self["labelformat"] = val # operation # --------- @property def operation(self): """ Sets the constraint operation. "=" keeps regions equal to `value` "<" and "<=" keep regions less than `value` ">" and ">=" keep regions greater than `value` "[]", "()", "[)", and "(]" keep regions inside `value[0]` to `value[1]` "][", ")(", "](", ")[" keep regions outside `value[0]` to value[1]` Open vs. closed intervals make no difference to constraint display, but all versions are allowed for consistency with filter transforms. The 'operation' property is an enumeration that may be specified as: - One of the following enumeration values: ['=', '<', '>=', '>', '<=', '[]', '()', '[)', '(]', '][', ')(', '](', ')['] Returns ------- Any """ return self["operation"] @operation.setter def operation(self, val): self["operation"] = val # showlabels # ---------- @property def showlabels(self): """ Determines whether to label the contour lines with their values. The 'showlabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showlabels"] @showlabels.setter def showlabels(self, val): self["showlabels"] = val # showlines # --------- @property def showlines(self): """ Determines whether or not the contour lines are drawn. Has an effect only if `contours.coloring` is set to "fill". The 'showlines' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showlines"] @showlines.setter def showlines(self, val): self["showlines"] = val # size # ---- @property def size(self): """ Sets the step between each contour level. Must be positive. The 'size' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # start # ----- @property def start(self): """ Sets the starting contour level value. Must be less than `contours.end` The 'start' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["start"] @start.setter def start(self, val): self["start"] = val # type # ---- @property def type(self): """ If `levels`, the data is represented as a contour plot with multiple levels displayed. If `constraint`, the data is represented as constraints with the invalid region shaded as specified by the `operation` and `value` parameters. The 'type' property is an enumeration that may be specified as: - One of the following enumeration values: ['levels', 'constraint'] Returns ------- Any """ return self["type"] @type.setter def type(self, val): self["type"] = val # value # ----- @property def value(self): """ Sets the value or values of the constraint boundary. When `operation` is set to one of the comparison values (=,<,>=,>,<=) "value" is expected to be a number. When `operation` is set to one of the interval values ([],(),[),(],][,)(,](,)[) "value" is expected to be an array of two numbers where the first is the lower bound and the second is the upper bound. The 'value' property accepts values of any type Returns ------- Any """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram2dcontour" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ coloring Determines the coloring method showing the contour values. If "fill", coloring is done evenly between each contour level If "heatmap", a heatmap gradient coloring is applied between each contour level. If "lines", coloring is done on the contour lines. If "none", no coloring is applied on this trace. end Sets the end contour level value. Must be more than `contours.start` labelfont Sets the font used for labeling the contour levels. The default color comes from the lines, if shown. The default family and size come from `layout.font`. labelformat Sets the contour label formatting rule using d3 formatting mini-language which is very similar to Python, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format operation Sets the constraint operation. "=" keeps regions equal to `value` "<" and "<=" keep regions less than `value` ">" and ">=" keep regions greater than `value` "[]", "()", "[)", and "(]" keep regions inside `value[0]` to `value[1]` "][", ")(", "](", ")[" keep regions outside `value[0]` to value[1]` Open vs. closed intervals make no difference to constraint display, but all versions are allowed for consistency with filter transforms. showlabels Determines whether to label the contour lines with their values. showlines Determines whether or not the contour lines are drawn. Has an effect only if `contours.coloring` is set to "fill". size Sets the step between each contour level. Must be positive. start Sets the starting contour level value. Must be less than `contours.end` type If `levels`, the data is represented as a contour plot with multiple levels displayed. If `constraint`, the data is represented as constraints with the invalid region shaded as specified by the `operation` and `value` parameters. value Sets the value or values of the constraint boundary. When `operation` is set to one of the comparison values (=,<,>=,>,<=) "value" is expected to be a number. When `operation` is set to one of the interval values ([],(),[),(],][,)(,](,)[) "value" is expected to be an array of two numbers where the first is the lower bound and the second is the upper bound. """ def __init__( self, arg=None, coloring=None, end=None, labelfont=None, labelformat=None, operation=None, showlabels=None, showlines=None, size=None, start=None, type=None, value=None, **kwargs ): """ Construct a new Contours object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.histogram2dcontour.Contours coloring Determines the coloring method showing the contour values. If "fill", coloring is done evenly between each contour level If "heatmap", a heatmap gradient coloring is applied between each contour level. If "lines", coloring is done on the contour lines. If "none", no coloring is applied on this trace. end Sets the end contour level value. Must be more than `contours.start` labelfont Sets the font used for labeling the contour levels. The default color comes from the lines, if shown. The default family and size come from `layout.font`. labelformat Sets the contour label formatting rule using d3 formatting mini-language which is very similar to Python, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format operation Sets the constraint operation. "=" keeps regions equal to `value` "<" and "<=" keep regions less than `value` ">" and ">=" keep regions greater than `value` "[]", "()", "[)", and "(]" keep regions inside `value[0]` to `value[1]` "][", ")(", "](", ")[" keep regions outside `value[0]` to value[1]` Open vs. closed intervals make no difference to constraint display, but all versions are allowed for consistency with filter transforms. showlabels Determines whether to label the contour lines with their values. showlines Determines whether or not the contour lines are drawn. Has an effect only if `contours.coloring` is set to "fill". size Sets the step between each contour level. Must be positive. start Sets the starting contour level value. Must be less than `contours.end` type If `levels`, the data is represented as a contour plot with multiple levels displayed. If `constraint`, the data is represented as constraints with the invalid region shaded as specified by the `operation` and `value` parameters. value Sets the value or values of the constraint boundary. When `operation` is set to one of the comparison values (=,<,>=,>,<=) "value" is expected to be a number. When `operation` is set to one of the interval values ([],(),[),(],][,)(,](,)[) "value" is expected to be an array of two numbers where the first is the lower bound and the second is the upper bound. Returns ------- Contours """ super(Contours, self).__init__("contours") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.histogram2dcontour.Contours constructor must be a dict or an instance of plotly.graph_objs.histogram2dcontour.Contours""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram2dcontour import contours as v_contours # Initialize validators # --------------------- self._validators["coloring"] = v_contours.ColoringValidator() self._validators["end"] = v_contours.EndValidator() self._validators["labelfont"] = v_contours.LabelfontValidator() self._validators["labelformat"] = v_contours.LabelformatValidator() self._validators["operation"] = v_contours.OperationValidator() self._validators["showlabels"] = v_contours.ShowlabelsValidator() self._validators["showlines"] = v_contours.ShowlinesValidator() self._validators["size"] = v_contours.SizeValidator() self._validators["start"] = v_contours.StartValidator() self._validators["type"] = v_contours.TypeValidator() self._validators["value"] = v_contours.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("coloring", None) self["coloring"] = coloring if coloring is not None else _v _v = arg.pop("end", None) self["end"] = end if end is not None else _v _v = arg.pop("labelfont", None) self["labelfont"] = labelfont if labelfont is not None else _v _v = arg.pop("labelformat", None) self["labelformat"] = labelformat if labelformat is not None else _v _v = arg.pop("operation", None) self["operation"] = operation if operation is not None else _v _v = arg.pop("showlabels", None) self["showlabels"] = showlabels if showlabels is not None else _v _v = arg.pop("showlines", None) self["showlines"] = showlines if showlines is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("start", None) self["start"] = start if start is not None else _v _v = arg.pop("type", None) self["type"] = type if type is not None else _v _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class ColorBar(_BaseTraceHierarchyType): # bgcolor # ------- @property def bgcolor(self): """ Sets the color of padded area. The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the axis line color. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # borderwidth # ----------- @property def borderwidth(self): """ Sets the width (in px) or the border enclosing this color bar. The 'borderwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["borderwidth"] @borderwidth.setter def borderwidth(self, val): self["borderwidth"] = val # dtick # ----- @property def dtick(self): """ Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" The 'dtick' property accepts values of any type Returns ------- Any """ return self["dtick"] @dtick.setter def dtick(self, val): self["dtick"] = val # exponentformat # -------------- @property def exponentformat(self): """ Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. The 'exponentformat' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'e', 'E', 'power', 'SI', 'B'] Returns ------- Any """ return self["exponentformat"] @exponentformat.setter def exponentformat(self, val): self["exponentformat"] = val # len # --- @property def len(self): """ Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. The 'len' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["len"] @len.setter def len(self, val): self["len"] = val # lenmode # ------- @property def lenmode(self): """ Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. The 'lenmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["lenmode"] @lenmode.setter def lenmode(self, val): self["lenmode"] = val # nticks # ------ @property def nticks(self): """ Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". The 'nticks' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nticks"] @nticks.setter def nticks(self, val): self["nticks"] = val # outlinecolor # ------------ @property def outlinecolor(self): """ Sets the axis line color. The 'outlinecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["outlinecolor"] @outlinecolor.setter def outlinecolor(self, val): self["outlinecolor"] = val # outlinewidth # ------------ @property def outlinewidth(self): """ Sets the width (in px) of the axis line. The 'outlinewidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["outlinewidth"] @outlinewidth.setter def outlinewidth(self, val): self["outlinewidth"] = val # separatethousands # ----------------- @property def separatethousands(self): """ If "true", even 4-digit integers are separated The 'separatethousands' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["separatethousands"] @separatethousands.setter def separatethousands(self, val): self["separatethousands"] = val # showexponent # ------------ @property def showexponent(self): """ If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. The 'showexponent' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showexponent"] @showexponent.setter def showexponent(self, val): self["showexponent"] = val # showticklabels # -------------- @property def showticklabels(self): """ Determines whether or not the tick labels are drawn. The 'showticklabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showticklabels"] @showticklabels.setter def showticklabels(self, val): self["showticklabels"] = val # showtickprefix # -------------- @property def showtickprefix(self): """ If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. The 'showtickprefix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showtickprefix"] @showtickprefix.setter def showtickprefix(self, val): self["showtickprefix"] = val # showticksuffix # -------------- @property def showticksuffix(self): """ Same as `showtickprefix` but for tick suffixes. The 'showticksuffix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showticksuffix"] @showticksuffix.setter def showticksuffix(self, val): self["showticksuffix"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # thicknessmode # ------------- @property def thicknessmode(self): """ Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. The 'thicknessmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["thicknessmode"] @thicknessmode.setter def thicknessmode(self, val): self["thicknessmode"] = val # tick0 # ----- @property def tick0(self): """ Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. The 'tick0' property accepts values of any type Returns ------- Any """ return self["tick0"] @tick0.setter def tick0(self, val): self["tick0"] = val # tickangle # --------- @property def tickangle(self): """ Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. The 'tickangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["tickangle"] @tickangle.setter def tickangle(self, val): self["tickangle"] = val # tickcolor # --------- @property def tickcolor(self): """ Sets the tick color. The 'tickcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["tickcolor"] @tickcolor.setter def tickcolor(self, val): self["tickcolor"] = val # tickfont # -------- @property def tickfont(self): """ Sets the color bar's tick label font The 'tickfont' property is an instance of Tickfont that may be specified as: - An instance of plotly.graph_objs.histogram2dcontour.colorbar.Tickfont - A dict of string/value properties that will be passed to the Tickfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.histogram2dcontour.colorbar.Tickfont """ return self["tickfont"] @tickfont.setter def tickfont(self, val): self["tickfont"] = val # tickformat # ---------- @property def tickformat(self): """ Sets the tick label formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'tickformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickformat"] @tickformat.setter def tickformat(self, val): self["tickformat"] = val # tickformatstops # --------------- @property def tickformatstops(self): """ The 'tickformatstops' property is a tuple of instances of Tickformatstop that may be specified as: - A list or tuple of instances of plotly.graph_objs.histogram2dcontour.colorbar.Tickformatstop - A list or tuple of dicts of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- tuple[plotly.graph_objs.histogram2dcontour.colorbar.Tickformatstop] """ return self["tickformatstops"] @tickformatstops.setter def tickformatstops(self, val): self["tickformatstops"] = val # tickformatstopdefaults # ---------------------- @property def tickformatstopdefaults(self): """ When used in a template (as layout.template.data.histogram2dcon tour.colorbar.tickformatstopdefaults), sets the default property values to use for elements of histogram2dcontour.colorbar.tickformatstops The 'tickformatstopdefaults' property is an instance of Tickformatstop that may be specified as: - An instance of plotly.graph_objs.histogram2dcontour.colorbar.Tickformatstop - A dict of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: Returns ------- plotly.graph_objs.histogram2dcontour.colorbar.Tickformatstop """ return self["tickformatstopdefaults"] @tickformatstopdefaults.setter def tickformatstopdefaults(self, val): self["tickformatstopdefaults"] = val # ticklen # ------- @property def ticklen(self): """ Sets the tick length (in px). The 'ticklen' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ticklen"] @ticklen.setter def ticklen(self, val): self["ticklen"] = val # tickmode # -------- @property def tickmode(self): """ Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). The 'tickmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'linear', 'array'] Returns ------- Any """ return self["tickmode"] @tickmode.setter def tickmode(self, val): self["tickmode"] = val # tickprefix # ---------- @property def tickprefix(self): """ Sets a tick label prefix. The 'tickprefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickprefix"] @tickprefix.setter def tickprefix(self, val): self["tickprefix"] = val # ticks # ----- @property def ticks(self): """ Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. The 'ticks' property is an enumeration that may be specified as: - One of the following enumeration values: ['outside', 'inside', ''] Returns ------- Any """ return self["ticks"] @ticks.setter def ticks(self, val): self["ticks"] = val # ticksuffix # ---------- @property def ticksuffix(self): """ Sets a tick label suffix. The 'ticksuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ticksuffix"] @ticksuffix.setter def ticksuffix(self, val): self["ticksuffix"] = val # ticktext # -------- @property def ticktext(self): """ Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. The 'ticktext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ticktext"] @ticktext.setter def ticktext(self, val): self["ticktext"] = val # ticktextsrc # ----------- @property def ticktextsrc(self): """ Sets the source reference on plot.ly for ticktext . The 'ticktextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ticktextsrc"] @ticktextsrc.setter def ticktextsrc(self, val): self["ticktextsrc"] = val # tickvals # -------- @property def tickvals(self): """ Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. The 'tickvals' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["tickvals"] @tickvals.setter def tickvals(self, val): self["tickvals"] = val # tickvalssrc # ----------- @property def tickvalssrc(self): """ Sets the source reference on plot.ly for tickvals . The 'tickvalssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tickvalssrc"] @tickvalssrc.setter def tickvalssrc(self, val): self["tickvalssrc"] = val # tickwidth # --------- @property def tickwidth(self): """ Sets the tick width (in px). The 'tickwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["tickwidth"] @tickwidth.setter def tickwidth(self, val): self["tickwidth"] = val # title # ----- @property def title(self): """ The 'title' property is an instance of Title that may be specified as: - An instance of plotly.graph_objs.histogram2dcontour.colorbar.Title - A dict of string/value properties that will be passed to the Title constructor Supported dict properties: font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- plotly.graph_objs.histogram2dcontour.colorbar.Title """ return self["title"] @title.setter def title(self, val): self["title"] = val # titlefont # --------- @property def titlefont(self): """ Deprecated: Please use histogram2dcontour.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.histogram2dcontour.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- """ return self["titlefont"] @titlefont.setter def titlefont(self, val): self["titlefont"] = val # titleside # --------- @property def titleside(self): """ Deprecated: Please use histogram2dcontour.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- """ return self["titleside"] @titleside.setter def titleside(self, val): self["titleside"] = val # x # - @property def x(self): """ Sets the x position of the color bar (in plot fraction). The 'x' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["x"] @x.setter def x(self, val): self["x"] = val # xanchor # ------- @property def xanchor(self): """ Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. The 'xanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'center', 'right'] Returns ------- Any """ return self["xanchor"] @xanchor.setter def xanchor(self, val): self["xanchor"] = val # xpad # ---- @property def xpad(self): """ Sets the amount of padding (in px) along the x direction. The 'xpad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["xpad"] @xpad.setter def xpad(self, val): self["xpad"] = val # y # - @property def y(self): """ Sets the y position of the color bar (in plot fraction). The 'y' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["y"] @y.setter def y(self, val): self["y"] = val # yanchor # ------- @property def yanchor(self): """ Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. The 'yanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['top', 'middle', 'bottom'] Returns ------- Any """ return self["yanchor"] @yanchor.setter def yanchor(self, val): self["yanchor"] = val # ypad # ---- @property def ypad(self): """ Sets the amount of padding (in px) along the y direction. The 'ypad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ypad"] @ypad.setter def ypad(self, val): self["ypad"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram2dcontour" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.histogram2dcontour.colo rbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.histog ram2dcontour.colorbar.tickformatstopdefaults), sets the default property values to use for elements of histogram2dcontour.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.histogram2dcontour.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use histogram2dcontour.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use histogram2dcontour.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """ _mapped_properties = { "titlefont": ("title", "font"), "titleside": ("title", "side"), } def __init__( self, arg=None, bgcolor=None, bordercolor=None, borderwidth=None, dtick=None, exponentformat=None, len=None, lenmode=None, nticks=None, outlinecolor=None, outlinewidth=None, separatethousands=None, showexponent=None, showticklabels=None, showtickprefix=None, showticksuffix=None, thickness=None, thicknessmode=None, tick0=None, tickangle=None, tickcolor=None, tickfont=None, tickformat=None, tickformatstops=None, tickformatstopdefaults=None, ticklen=None, tickmode=None, tickprefix=None, ticks=None, ticksuffix=None, ticktext=None, ticktextsrc=None, tickvals=None, tickvalssrc=None, tickwidth=None, title=None, titlefont=None, titleside=None, x=None, xanchor=None, xpad=None, y=None, yanchor=None, ypad=None, **kwargs ): """ Construct a new ColorBar object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.histogram2dcontour.ColorBar bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.histogram2dcontour.colo rbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.histog ram2dcontour.colorbar.tickformatstopdefaults), sets the default property values to use for elements of histogram2dcontour.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.histogram2dcontour.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use histogram2dcontour.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use histogram2dcontour.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- ColorBar """ super(ColorBar, self).__init__("colorbar") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.histogram2dcontour.ColorBar constructor must be a dict or an instance of plotly.graph_objs.histogram2dcontour.ColorBar""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram2dcontour import colorbar as v_colorbar # Initialize validators # --------------------- self._validators["bgcolor"] = v_colorbar.BgcolorValidator() self._validators["bordercolor"] = v_colorbar.BordercolorValidator() self._validators["borderwidth"] = v_colorbar.BorderwidthValidator() self._validators["dtick"] = v_colorbar.DtickValidator() self._validators["exponentformat"] = v_colorbar.ExponentformatValidator() self._validators["len"] = v_colorbar.LenValidator() self._validators["lenmode"] = v_colorbar.LenmodeValidator() self._validators["nticks"] = v_colorbar.NticksValidator() self._validators["outlinecolor"] = v_colorbar.OutlinecolorValidator() self._validators["outlinewidth"] = v_colorbar.OutlinewidthValidator() self._validators["separatethousands"] = v_colorbar.SeparatethousandsValidator() self._validators["showexponent"] = v_colorbar.ShowexponentValidator() self._validators["showticklabels"] = v_colorbar.ShowticklabelsValidator() self._validators["showtickprefix"] = v_colorbar.ShowtickprefixValidator() self._validators["showticksuffix"] = v_colorbar.ShowticksuffixValidator() self._validators["thickness"] = v_colorbar.ThicknessValidator() self._validators["thicknessmode"] = v_colorbar.ThicknessmodeValidator() self._validators["tick0"] = v_colorbar.Tick0Validator() self._validators["tickangle"] = v_colorbar.TickangleValidator() self._validators["tickcolor"] = v_colorbar.TickcolorValidator() self._validators["tickfont"] = v_colorbar.TickfontValidator() self._validators["tickformat"] = v_colorbar.TickformatValidator() self._validators["tickformatstops"] = v_colorbar.TickformatstopsValidator() self._validators[ "tickformatstopdefaults" ] = v_colorbar.TickformatstopValidator() self._validators["ticklen"] = v_colorbar.TicklenValidator() self._validators["tickmode"] = v_colorbar.TickmodeValidator() self._validators["tickprefix"] = v_colorbar.TickprefixValidator() self._validators["ticks"] = v_colorbar.TicksValidator() self._validators["ticksuffix"] = v_colorbar.TicksuffixValidator() self._validators["ticktext"] = v_colorbar.TicktextValidator() self._validators["ticktextsrc"] = v_colorbar.TicktextsrcValidator() self._validators["tickvals"] = v_colorbar.TickvalsValidator() self._validators["tickvalssrc"] = v_colorbar.TickvalssrcValidator() self._validators["tickwidth"] = v_colorbar.TickwidthValidator() self._validators["title"] = v_colorbar.TitleValidator() self._validators["x"] = v_colorbar.XValidator() self._validators["xanchor"] = v_colorbar.XanchorValidator() self._validators["xpad"] = v_colorbar.XpadValidator() self._validators["y"] = v_colorbar.YValidator() self._validators["yanchor"] = v_colorbar.YanchorValidator() self._validators["ypad"] = v_colorbar.YpadValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("borderwidth", None) self["borderwidth"] = borderwidth if borderwidth is not None else _v _v = arg.pop("dtick", None) self["dtick"] = dtick if dtick is not None else _v _v = arg.pop("exponentformat", None) self["exponentformat"] = exponentformat if exponentformat is not None else _v _v = arg.pop("len", None) self["len"] = len if len is not None else _v _v = arg.pop("lenmode", None) self["lenmode"] = lenmode if lenmode is not None else _v _v = arg.pop("nticks", None) self["nticks"] = nticks if nticks is not None else _v _v = arg.pop("outlinecolor", None) self["outlinecolor"] = outlinecolor if outlinecolor is not None else _v _v = arg.pop("outlinewidth", None) self["outlinewidth"] = outlinewidth if outlinewidth is not None else _v _v = arg.pop("separatethousands", None) self["separatethousands"] = ( separatethousands if separatethousands is not None else _v ) _v = arg.pop("showexponent", None) self["showexponent"] = showexponent if showexponent is not None else _v _v = arg.pop("showticklabels", None) self["showticklabels"] = showticklabels if showticklabels is not None else _v _v = arg.pop("showtickprefix", None) self["showtickprefix"] = showtickprefix if showtickprefix is not None else _v _v = arg.pop("showticksuffix", None) self["showticksuffix"] = showticksuffix if showticksuffix is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("thicknessmode", None) self["thicknessmode"] = thicknessmode if thicknessmode is not None else _v _v = arg.pop("tick0", None) self["tick0"] = tick0 if tick0 is not None else _v _v = arg.pop("tickangle", None) self["tickangle"] = tickangle if tickangle is not None else _v _v = arg.pop("tickcolor", None) self["tickcolor"] = tickcolor if tickcolor is not None else _v _v = arg.pop("tickfont", None) self["tickfont"] = tickfont if tickfont is not None else _v _v = arg.pop("tickformat", None) self["tickformat"] = tickformat if tickformat is not None else _v _v = arg.pop("tickformatstops", None) self["tickformatstops"] = tickformatstops if tickformatstops is not None else _v _v = arg.pop("tickformatstopdefaults", None) self["tickformatstopdefaults"] = ( tickformatstopdefaults if tickformatstopdefaults is not None else _v ) _v = arg.pop("ticklen", None) self["ticklen"] = ticklen if ticklen is not None else _v _v = arg.pop("tickmode", None) self["tickmode"] = tickmode if tickmode is not None else _v _v = arg.pop("tickprefix", None) self["tickprefix"] = tickprefix if tickprefix is not None else _v _v = arg.pop("ticks", None) self["ticks"] = ticks if ticks is not None else _v _v = arg.pop("ticksuffix", None) self["ticksuffix"] = ticksuffix if ticksuffix is not None else _v _v = arg.pop("ticktext", None) self["ticktext"] = ticktext if ticktext is not None else _v _v = arg.pop("ticktextsrc", None) self["ticktextsrc"] = ticktextsrc if ticktextsrc is not None else _v _v = arg.pop("tickvals", None) self["tickvals"] = tickvals if tickvals is not None else _v _v = arg.pop("tickvalssrc", None) self["tickvalssrc"] = tickvalssrc if tickvalssrc is not None else _v _v = arg.pop("tickwidth", None) self["tickwidth"] = tickwidth if tickwidth is not None else _v _v = arg.pop("title", None) self["title"] = title if title is not None else _v _v = arg.pop("titlefont", None) _v = titlefont if titlefont is not None else _v if _v is not None: self["titlefont"] = _v _v = arg.pop("titleside", None) _v = titleside if titleside is not None else _v if _v is not None: self["titleside"] = _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xanchor", None) self["xanchor"] = xanchor if xanchor is not None else _v _v = arg.pop("xpad", None) self["xpad"] = xpad if xpad is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("yanchor", None) self["yanchor"] = yanchor if yanchor is not None else _v _v = arg.pop("ypad", None) self["ypad"] = ypad if ypad is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = [ "ColorBar", "Contours", "Hoverlabel", "Line", "Marker", "Stream", "XBins", "YBins", "colorbar", "contours", "hoverlabel", ] from plotly.graph_objs.histogram2dcontour import hoverlabel from plotly.graph_objs.histogram2dcontour import contours from plotly.graph_objs.histogram2dcontour import colorbar plotly-4.4.1+dfsg.orig/plotly/graph_objs/_figurewidget.py0000644000175000017500000273622513573721553023144 0ustar noahfxnoahfxfrom plotly.basewidget import BaseFigureWidget from plotly.graph_objs import ( Area, Bar, Barpolar, Box, Candlestick, Carpet, Choropleth, Choroplethmapbox, Cone, Contour, Contourcarpet, Densitymapbox, Funnel, Funnelarea, Heatmap, Heatmapgl, Histogram, Histogram2d, Histogram2dContour, Image, Indicator, Isosurface, Mesh3d, Ohlc, Parcats, Parcoords, Pie, Pointcloud, Sankey, Scatter, Scatter3d, Scattercarpet, Scattergeo, Scattergl, Scattermapbox, Scatterpolar, Scatterpolargl, Scatterternary, Splom, Streamtube, Sunburst, Surface, Table, Treemap, Violin, Volume, Waterfall, layout as _layout, ) class FigureWidget(BaseFigureWidget): def __init__( self, data=None, layout=None, frames=None, skip_invalid=False, **kwargs ): """ Create a new FigureWidget instance Parameters ---------- data The 'data' property is a tuple of trace instances that may be specified as: - A list or tuple of trace instances (e.g. [Scatter(...), Bar(...)]) - A single trace instance (e.g. Scatter(...), Bar(...), etc.) - A list or tuple of dicts of string/value properties where: - The 'type' property specifies the trace type One of: ['area', 'bar', 'barpolar', 'box', 'candlestick', 'carpet', 'choropleth', 'choroplethmapbox', 'cone', 'contour', 'contourcarpet', 'densitymapbox', 'funnel', 'funnelarea', 'heatmap', 'heatmapgl', 'histogram', 'histogram2d', 'histogram2dcontour', 'image', 'indicator', 'isosurface', 'mesh3d', 'ohlc', 'parcats', 'parcoords', 'pie', 'pointcloud', 'sankey', 'scatter', 'scatter3d', 'scattercarpet', 'scattergeo', 'scattergl', 'scattermapbox', 'scatterpolar', 'scatterpolargl', 'scatterternary', 'splom', 'streamtube', 'sunburst', 'surface', 'table', 'treemap', 'violin', 'volume', 'waterfall'] - All remaining properties are passed to the constructor of the specified trace type (e.g. [{'type': 'scatter', ...}, {'type': 'bar, ...}]) layout The 'layout' property is an instance of Layout that may be specified as: - An instance of plotly.graph_objs.Layout - A dict of string/value properties that will be passed to the Layout constructor Supported dict properties: angularaxis plotly.graph_objects.layout.AngularAxis instance or dict with compatible properties annotations A tuple of plotly.graph_objects.layout.Annotation instances or dicts with compatible properties annotationdefaults When used in a template (as layout.template.layout.annotationdefaults), sets the default property values to use for elements of layout.annotations autosize Determines whether or not a layout width or height that has been left undefined by the user is initialized on each relayout. Note that, regardless of this attribute, an undefined layout width or height is always initialized on the first call to plot. bargap Sets the gap (in plot fraction) between bars of adjacent location coordinates. bargroupgap Sets the gap (in plot fraction) between bars of the same location coordinate. barmode Determines how bars at the same location coordinate are displayed on the graph. With "stack", the bars are stacked on top of one another With "relative", the bars are stacked on top of one another, with negative values below the axis, positive values above With "group", the bars are plotted next to one another centered around the shared location. With "overlay", the bars are plotted over one another, you might need to an "opacity" to see multiple bars. barnorm Sets the normalization for bar traces on the graph. With "fraction", the value of each bar is divided by the sum of all values at that location coordinate. "percent" is the same but multiplied by 100 to show percentages. boxgap Sets the gap (in plot fraction) between boxes of adjacent location coordinates. Has no effect on traces that have "width" set. boxgroupgap Sets the gap (in plot fraction) between boxes of the same location coordinate. Has no effect on traces that have "width" set. boxmode Determines how boxes at the same location coordinate are displayed on the graph. If "group", the boxes are plotted next to one another centered around the shared location. If "overlay", the boxes are plotted over one another, you might need to set "opacity" to see them multiple boxes. Has no effect on traces that have "width" set. calendar Sets the default calendar system to use for interpreting and displaying dates throughout the plot. clickmode Determines the mode of single click interactions. "event" is the default value and emits the `plotly_click` event. In addition this mode emits the `plotly_selected` event in drag modes "lasso" and "select", but with no event data attached (kept for compatibility reasons). The "select" flag enables selecting single data points via click. This mode also supports persistent selections, meaning that pressing Shift while clicking, adds to / subtracts from an existing selection. "select" with `hovermode`: "x" can be confusing, consider explicitly setting `hovermode`: "closest" when using this feature. Selection events are sent accordingly as long as "event" flag is set as well. When the "event" flag is missing, `plotly_click` and `plotly_selected` events are not fired. coloraxis plotly.graph_objects.layout.Coloraxis instance or dict with compatible properties colorscale plotly.graph_objects.layout.Colorscale instance or dict with compatible properties colorway Sets the default trace colors. datarevision If provided, a changed value tells `Plotly.react` that one or more data arrays has changed. This way you can modify arrays in- place rather than making a complete new copy for an incremental change. If NOT provided, `Plotly.react` assumes that data arrays are being treated as immutable, thus any data array with a different identity from its predecessor contains new data. direction Legacy polar charts are deprecated! Please switch to "polar" subplots. Sets the direction corresponding to positive angles in legacy polar charts. dragmode Determines the mode of drag interactions. "select" and "lasso" apply only to scatter traces with markers or text. "orbit" and "turntable" apply only to 3D scenes. editrevision Controls persistence of user-driven changes in `editable: true` configuration, other than trace names and axis titles. Defaults to `layout.uirevision`. extendfunnelareacolors If `true`, the funnelarea slice colors (whether given by `funnelareacolorway` or inherited from `colorway`) will be extended to three times its original length by first repeating every color 20% lighter then each color 20% darker. This is intended to reduce the likelihood of reusing the same color when you have many slices, but you can set `false` to disable. Colors provided in the trace, using `marker.colors`, are never extended. extendpiecolors If `true`, the pie slice colors (whether given by `piecolorway` or inherited from `colorway`) will be extended to three times its original length by first repeating every color 20% lighter then each color 20% darker. This is intended to reduce the likelihood of reusing the same color when you have many slices, but you can set `false` to disable. Colors provided in the trace, using `marker.colors`, are never extended. extendsunburstcolors If `true`, the sunburst slice colors (whether given by `sunburstcolorway` or inherited from `colorway`) will be extended to three times its original length by first repeating every color 20% lighter then each color 20% darker. This is intended to reduce the likelihood of reusing the same color when you have many slices, but you can set `false` to disable. Colors provided in the trace, using `marker.colors`, are never extended. extendtreemapcolors If `true`, the treemap slice colors (whether given by `treemapcolorway` or inherited from `colorway`) will be extended to three times its original length by first repeating every color 20% lighter then each color 20% darker. This is intended to reduce the likelihood of reusing the same color when you have many slices, but you can set `false` to disable. Colors provided in the trace, using `marker.colors`, are never extended. font Sets the global font. Note that fonts used in traces and other layout components inherit from the global font. funnelareacolorway Sets the default funnelarea slice colors. Defaults to the main `colorway` used for trace colors. If you specify a new list here it can still be extended with lighter and darker colors, see `extendfunnelareacolors`. funnelgap Sets the gap (in plot fraction) between bars of adjacent location coordinates. funnelgroupgap Sets the gap (in plot fraction) between bars of the same location coordinate. funnelmode Determines how bars at the same location coordinate are displayed on the graph. With "stack", the bars are stacked on top of one another With "group", the bars are plotted next to one another centered around the shared location. With "overlay", the bars are plotted over one another, you might need to an "opacity" to see multiple bars. geo plotly.graph_objects.layout.Geo instance or dict with compatible properties grid plotly.graph_objects.layout.Grid instance or dict with compatible properties height Sets the plot's height (in px). hiddenlabels hiddenlabels is the funnelarea & pie chart analog of visible:'legendonly' but it can contain many labels, and can simultaneously hide slices from several pies/funnelarea charts hiddenlabelssrc Sets the source reference on plot.ly for hiddenlabels . hidesources Determines whether or not a text link citing the data source is placed at the bottom-right cored of the figure. Has only an effect only on graphs that have been generated via forked graphs from the plotly service (at https://plot.ly or on-premise). hoverdistance Sets the default distance (in pixels) to look for data to add hover labels (-1 means no cutoff, 0 means no looking for data). This is only a real distance for hovering on point-like objects, like scatter points. For area-like objects (bars, scatter fills, etc) hovering is on inside the area and off outside, but these objects will not supersede hover on point-like objects in case of conflict. hoverlabel plotly.graph_objects.layout.Hoverlabel instance or dict with compatible properties hovermode Determines the mode of hover interactions. If `clickmode` includes the "select" flag, `hovermode` defaults to "closest". If `clickmode` lacks the "select" flag, it defaults to "x" or "y" (depending on the trace's `orientation` value) for plots based on cartesian coordinates. For anything else the default value is "closest". images A tuple of plotly.graph_objects.layout.Image instances or dicts with compatible properties imagedefaults When used in a template (as layout.template.layout.imagedefaults), sets the default property values to use for elements of layout.images legend plotly.graph_objects.layout.Legend instance or dict with compatible properties mapbox plotly.graph_objects.layout.Mapbox instance or dict with compatible properties margin plotly.graph_objects.layout.Margin instance or dict with compatible properties meta Assigns extra meta information that can be used in various `text` attributes. Attributes such as the graph, axis and colorbar `title.text`, annotation `text` `trace.name` in legend items, `rangeselector`, `updatemenus` and `sliders` `label` text all support `meta`. One can access `meta` fields using template strings: `%{meta[i]}` where `i` is the index of the `meta` item in question. `meta` can also be an object for example `{key: value}` which can be accessed %{meta[key]}. metasrc Sets the source reference on plot.ly for meta . modebar plotly.graph_objects.layout.Modebar instance or dict with compatible properties orientation Legacy polar charts are deprecated! Please switch to "polar" subplots. Rotates the entire polar by the given angle in legacy polar charts. paper_bgcolor Sets the color of paper where the graph is drawn. piecolorway Sets the default pie slice colors. Defaults to the main `colorway` used for trace colors. If you specify a new list here it can still be extended with lighter and darker colors, see `extendpiecolors`. plot_bgcolor Sets the color of plotting area in-between x and y axes. polar plotly.graph_objects.layout.Polar instance or dict with compatible properties radialaxis plotly.graph_objects.layout.RadialAxis instance or dict with compatible properties scene plotly.graph_objects.layout.Scene instance or dict with compatible properties selectdirection When "dragmode" is set to "select", this limits the selection of the drag to horizontal, vertical or diagonal. "h" only allows horizontal selection, "v" only vertical, "d" only diagonal and "any" sets no limit. selectionrevision Controls persistence of user-driven changes in selected points from all traces. separators Sets the decimal and thousand separators. For example, *. * puts a '.' before decimals and a space between thousands. In English locales, dflt is ".," but other locales may alter this default. shapes A tuple of plotly.graph_objects.layout.Shape instances or dicts with compatible properties shapedefaults When used in a template (as layout.template.layout.shapedefaults), sets the default property values to use for elements of layout.shapes showlegend Determines whether or not a legend is drawn. Default is `true` if there is a trace to show and any of these: a) Two or more traces would by default be shown in the legend. b) One pie trace is shown in the legend. c) One trace is explicitly given with `showlegend: true`. sliders A tuple of plotly.graph_objects.layout.Slider instances or dicts with compatible properties sliderdefaults When used in a template (as layout.template.layout.sliderdefaults), sets the default property values to use for elements of layout.sliders spikedistance Sets the default distance (in pixels) to look for data to draw spikelines to (-1 means no cutoff, 0 means no looking for data). As with hoverdistance, distance does not apply to area- like objects. In addition, some objects can be hovered on but will not generate spikelines, such as scatter fills. sunburstcolorway Sets the default sunburst slice colors. Defaults to the main `colorway` used for trace colors. If you specify a new list here it can still be extended with lighter and darker colors, see `extendsunburstcolors`. template Default attributes to be applied to the plot. This should be a dict with format: `{'layout': layoutTemplate, 'data': {trace_type: [traceTemplate, ...], ...}}` where `layoutTemplate` is a dict matching the structure of `figure.layout` and `traceTemplate` is a dict matching the structure of the trace with type `trace_type` (e.g. 'scatter'). Alternatively, this may be specified as an instance of plotly.graph_objs.layout.Template. Trace templates are applied cyclically to traces of each type. Container arrays (eg `annotations`) have special handling: An object ending in `defaults` (eg `annotationdefaults`) is applied to each array item. But if an item has a `templateitemname` key we look in the template array for an item with matching `name` and apply that instead. If no matching `name` is found we mark the item invisible. Any named template item not referenced is appended to the end of the array, so this can be used to add a watermark annotation or a logo image, for example. To omit one of these items on the plot, make an item with matching `templateitemname` and `visible: false`. ternary plotly.graph_objects.layout.Ternary instance or dict with compatible properties title plotly.graph_objects.layout.Title instance or dict with compatible properties titlefont Deprecated: Please use layout.title.font instead. Sets the title font. Note that the title's font used to be customized by the now deprecated `titlefont` attribute. transition Sets transition options used during Plotly.react updates. treemapcolorway Sets the default treemap slice colors. Defaults to the main `colorway` used for trace colors. If you specify a new list here it can still be extended with lighter and darker colors, see `extendtreemapcolors`. uirevision Used to allow user interactions with the plot to persist after `Plotly.react` calls that are unaware of these interactions. If `uirevision` is omitted, or if it is given and it changed from the previous `Plotly.react` call, the exact new figure is used. If `uirevision` is truthy and did NOT change, any attribute that has been affected by user interactions and did not receive a different value in the new figure will keep the interaction value. `layout.uirevision` attribute serves as the default for `uirevision` attributes in various sub-containers. For finer control you can set these sub-attributes directly. For example, if your app separately controls the data on the x and y axes you might set `xaxis.uirevision=*time*` and `yaxis.uirevision=*cost*`. Then if only the y data is changed, you can update `yaxis.uirevision=*quantity*` and the y axis range will reset but the x axis range will retain any user-driven zoom. updatemenus A tuple of plotly.graph_objects.layout.Updatemenu instances or dicts with compatible properties updatemenudefaults When used in a template (as layout.template.layout.updatemenudefaults), sets the default property values to use for elements of layout.updatemenus violingap Sets the gap (in plot fraction) between violins of adjacent location coordinates. Has no effect on traces that have "width" set. violingroupgap Sets the gap (in plot fraction) between violins of the same location coordinate. Has no effect on traces that have "width" set. violinmode Determines how violins at the same location coordinate are displayed on the graph. If "group", the violins are plotted next to one another centered around the shared location. If "overlay", the violins are plotted over one another, you might need to set "opacity" to see them multiple violins. Has no effect on traces that have "width" set. waterfallgap Sets the gap (in plot fraction) between bars of adjacent location coordinates. waterfallgroupgap Sets the gap (in plot fraction) between bars of the same location coordinate. waterfallmode Determines how bars at the same location coordinate are displayed on the graph. With "group", the bars are plotted next to one another centered around the shared location. With "overlay", the bars are plotted over one another, you might need to an "opacity" to see multiple bars. width Sets the plot's width (in px). xaxis plotly.graph_objects.layout.XAxis instance or dict with compatible properties yaxis plotly.graph_objects.layout.YAxis instance or dict with compatible properties frames The 'frames' property is a tuple of instances of Frame that may be specified as: - A list or tuple of instances of plotly.graph_objs.Frame - A list or tuple of dicts of string/value properties that will be passed to the Frame constructor Supported dict properties: baseframe The name of the frame into which this frame's properties are merged before applying. This is used to unify properties and avoid needing to specify the same values for the same properties in multiple frames. data A list of traces this frame modifies. The format is identical to the normal trace definition. group An identifier that specifies the group to which the frame belongs, used by animate to select a subset of frames. layout Layout properties which this frame modifies. The format is identical to the normal layout definition. name A label by which to identify the frame traces A list of trace indices that identify the respective traces in the data attribute skip_invalid: bool If True, invalid properties in the figure specification will be skipped silently. If False (default) invalid properties in the figure specification will result in a ValueError Raises ------ ValueError if a property in the specification of data, layout, or frames is invalid AND skip_invalid is False """ super(FigureWidget, self).__init__(data, layout, frames, skip_invalid, **kwargs) def add_area( self, customdata=None, customdatasrc=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, ids=None, idssrc=None, legendgroup=None, marker=None, meta=None, metasrc=None, name=None, opacity=None, r=None, rsrc=None, showlegend=None, stream=None, t=None, tsrc=None, uid=None, uirevision=None, visible=None, row=None, col=None, **kwargs ): """ Add a new Area trace Parameters ---------- customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.area.Hoverlabel instance or dict with compatible properties ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. marker plotly.graph_objects.area.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. r Area traces are deprecated! Please switch to the "barpolar" trace type. Sets the radial coordinates for legacy polar chart only. rsrc Sets the source reference on plot.ly for r . showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.area.Stream instance or dict with compatible properties t Area traces are deprecated! Please switch to the "barpolar" trace type. Sets the angular coordinates for legacy polar chart only. tsrc Sets the source reference on plot.ly for t . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- FigureWidget """ new_trace = Area( customdata=customdata, customdatasrc=customdatasrc, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, ids=ids, idssrc=idssrc, legendgroup=legendgroup, marker=marker, meta=meta, metasrc=metasrc, name=name, opacity=opacity, r=r, rsrc=rsrc, showlegend=showlegend, stream=stream, t=t, tsrc=tsrc, uid=uid, uirevision=uirevision, visible=visible, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_bar( self, alignmentgroup=None, base=None, basesrc=None, cliponaxis=None, constraintext=None, customdata=None, customdatasrc=None, dx=None, dy=None, error_x=None, error_y=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, insidetextanchor=None, insidetextfont=None, legendgroup=None, marker=None, meta=None, metasrc=None, name=None, offset=None, offsetgroup=None, offsetsrc=None, opacity=None, orientation=None, outsidetextfont=None, r=None, rsrc=None, selected=None, selectedpoints=None, showlegend=None, stream=None, t=None, text=None, textangle=None, textfont=None, textposition=None, textpositionsrc=None, textsrc=None, texttemplate=None, texttemplatesrc=None, tsrc=None, uid=None, uirevision=None, unselected=None, visible=None, width=None, widthsrc=None, x=None, x0=None, xaxis=None, xcalendar=None, xsrc=None, y=None, y0=None, yaxis=None, ycalendar=None, ysrc=None, row=None, col=None, secondary_y=None, **kwargs ): """ Add a new Bar trace The data visualized by the span of the bars is set in `y` if `orientation` is set th "v" (the default) and the labels are set in `x`. By setting `orientation` to "h", the roles are interchanged. Parameters ---------- alignmentgroup Set several traces linked to the same position axis or matching axes to the same alignmentgroup. This controls whether bars compute their positional range dependently or independently. base Sets where the bar base is drawn (in position axis units). In "stack" or "relative" barmode, traces that set "base" will be excluded and drawn in "overlay" mode instead. basesrc Sets the source reference on plot.ly for base . cliponaxis Determines whether the text nodes are clipped about the subplot axes. To show the text nodes above axis lines and tick labels, make sure to set `xaxis.layer` and `yaxis.layer` to *below traces*. constraintext Constrain the size of text inside or outside a bar to be no larger than the bar itself. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dx Sets the x coordinate step. See `x0` for more info. dy Sets the y coordinate step. See `y0` for more info. error_x plotly.graph_objects.bar.ErrorX instance or dict with compatible properties error_y plotly.graph_objects.bar.ErrorY instance or dict with compatible properties hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.bar.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `value` and `label`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . insidetextanchor Determines if texts are kept at center or start/end points in `textposition` "inside" mode. insidetextfont Sets the font used for `text` lying inside the bar. legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. marker plotly.graph_objects.bar.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. offset Shifts the position where the bar is drawn (in position axis units). In "group" barmode, traces that set "offset" will be excluded and drawn in "overlay" mode instead. offsetgroup Set several traces linked to the same position axis or matching axes to the same offsetgroup where bars of the same position coordinate will line up. offsetsrc Sets the source reference on plot.ly for offset . opacity Sets the opacity of the trace. orientation Sets the orientation of the bars. With "v" ("h"), the value of the each bar spans along the vertical (horizontal). outsidetextfont Sets the font used for `text` lying outside the bar. r r coordinates in scatter traces are deprecated!Please switch to the "scatterpolar" trace type.Sets the radial coordinatesfor legacy polar chart only. rsrc Sets the source reference on plot.ly for r . selected plotly.graph_objects.bar.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.bar.Stream instance or dict with compatible properties t t coordinates in scatter traces are deprecated!Please switch to the "scatterpolar" trace type.Sets the angular coordinatesfor legacy polar chart only. text Sets text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textangle Sets the angle of the tick labels with respect to the bar. For example, a `tickangle` of -90 draws the tick labels vertically. With "auto" the texts may automatically be rotated to fit with the maximum size in bars. textfont Sets the font used for `text`. textposition Specifies the location of the `text`. "inside" positions `text` inside, next to the bar end (rotated and scaled if needed). "outside" positions `text` outside, next to the bar end (scaled if needed), unless there is another bar stacked on this one, then the text gets pushed inside. "auto" tries to position `text` inside the bar, but if the bar is too small and no bar is stacked on this one the text is moved outside. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `value` and `label`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . tsrc Sets the source reference on plot.ly for t . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.bar.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). width Sets the bar width (in position axis units). widthsrc Sets the source reference on plot.ly for width . x Sets the x coordinates. x0 Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . y Sets the y coordinates. y0 Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` secondary_y: boolean or None (default None) If True, associate this trace with the secondary y-axis of the subplot at the specified row and col. Only valid if all of the following conditions are satisfied: * The figure was created using `plotly.subplots.make_subplots`. * The row and col arguments are not None * The subplot at the specified row and col has type xy (which is the default) and secondary_y True. These properties are specified in the specs argument to make_subplots. See the make_subplots docstring for more info. Returns ------- FigureWidget """ new_trace = Bar( alignmentgroup=alignmentgroup, base=base, basesrc=basesrc, cliponaxis=cliponaxis, constraintext=constraintext, customdata=customdata, customdatasrc=customdatasrc, dx=dx, dy=dy, error_x=error_x, error_y=error_y, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, insidetextanchor=insidetextanchor, insidetextfont=insidetextfont, legendgroup=legendgroup, marker=marker, meta=meta, metasrc=metasrc, name=name, offset=offset, offsetgroup=offsetgroup, offsetsrc=offsetsrc, opacity=opacity, orientation=orientation, outsidetextfont=outsidetextfont, r=r, rsrc=rsrc, selected=selected, selectedpoints=selectedpoints, showlegend=showlegend, stream=stream, t=t, text=text, textangle=textangle, textfont=textfont, textposition=textposition, textpositionsrc=textpositionsrc, textsrc=textsrc, texttemplate=texttemplate, texttemplatesrc=texttemplatesrc, tsrc=tsrc, uid=uid, uirevision=uirevision, unselected=unselected, visible=visible, width=width, widthsrc=widthsrc, x=x, x0=x0, xaxis=xaxis, xcalendar=xcalendar, xsrc=xsrc, y=y, y0=y0, yaxis=yaxis, ycalendar=ycalendar, ysrc=ysrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) def add_barpolar( self, base=None, basesrc=None, customdata=None, customdatasrc=None, dr=None, dtheta=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, legendgroup=None, marker=None, meta=None, metasrc=None, name=None, offset=None, offsetsrc=None, opacity=None, r=None, r0=None, rsrc=None, selected=None, selectedpoints=None, showlegend=None, stream=None, subplot=None, text=None, textsrc=None, theta=None, theta0=None, thetasrc=None, thetaunit=None, uid=None, uirevision=None, unselected=None, visible=None, width=None, widthsrc=None, row=None, col=None, **kwargs ): """ Add a new Barpolar trace The data visualized by the radial span of the bars is set in `r` Parameters ---------- base Sets where the bar base is drawn (in radial axis units). In "stack" barmode, traces that set "base" will be excluded and drawn in "overlay" mode instead. basesrc Sets the source reference on plot.ly for base . customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dr Sets the r coordinate step. dtheta Sets the theta coordinate step. By default, the `dtheta` step equals the subplot's period divided by the length of the `r` coordinates. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.barpolar.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. marker plotly.graph_objects.barpolar.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. offset Shifts the angular position where the bar is drawn (in "thetatunit" units). offsetsrc Sets the source reference on plot.ly for offset . opacity Sets the opacity of the trace. r Sets the radial coordinates r0 Alternate to `r`. Builds a linear space of r coordinates. Use with `dr` where `r0` is the starting coordinate and `dr` the step. rsrc Sets the source reference on plot.ly for r . selected plotly.graph_objects.barpolar.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.barpolar.Stream instance or dict with compatible properties subplot Sets a reference between this trace's data coordinates and a polar subplot. If "polar" (the default value), the data refer to `layout.polar`. If "polar2", the data refer to `layout.polar2`, and so on. text Sets hover text elements associated with each bar. If a single string, the same string appears over all bars. If an array of string, the items are mapped in order to the this trace's coordinates. textsrc Sets the source reference on plot.ly for text . theta Sets the angular coordinates theta0 Alternate to `theta`. Builds a linear space of theta coordinates. Use with `dtheta` where `theta0` is the starting coordinate and `dtheta` the step. thetasrc Sets the source reference on plot.ly for theta . thetaunit Sets the unit of input "theta" values. Has an effect only when on "linear" angular axes. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.barpolar.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). width Sets the bar angular width (in "thetaunit" units). widthsrc Sets the source reference on plot.ly for width . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- FigureWidget """ new_trace = Barpolar( base=base, basesrc=basesrc, customdata=customdata, customdatasrc=customdatasrc, dr=dr, dtheta=dtheta, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, legendgroup=legendgroup, marker=marker, meta=meta, metasrc=metasrc, name=name, offset=offset, offsetsrc=offsetsrc, opacity=opacity, r=r, r0=r0, rsrc=rsrc, selected=selected, selectedpoints=selectedpoints, showlegend=showlegend, stream=stream, subplot=subplot, text=text, textsrc=textsrc, theta=theta, theta0=theta0, thetasrc=thetasrc, thetaunit=thetaunit, uid=uid, uirevision=uirevision, unselected=unselected, visible=visible, width=width, widthsrc=widthsrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_box( self, alignmentgroup=None, boxmean=None, boxpoints=None, customdata=None, customdatasrc=None, fillcolor=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hoveron=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, jitter=None, legendgroup=None, line=None, marker=None, meta=None, metasrc=None, name=None, notched=None, notchwidth=None, offsetgroup=None, opacity=None, orientation=None, pointpos=None, selected=None, selectedpoints=None, showlegend=None, stream=None, text=None, textsrc=None, uid=None, uirevision=None, unselected=None, visible=None, whiskerwidth=None, width=None, x=None, x0=None, xaxis=None, xcalendar=None, xsrc=None, y=None, y0=None, yaxis=None, ycalendar=None, ysrc=None, row=None, col=None, secondary_y=None, **kwargs ): """ Add a new Box trace In vertical (horizontal) box plots, statistics are computed using `y` (`x`) values. By supplying an `x` (`y`) array, one box per distinct x (y) value is drawn If no `x` (`y`) list is provided, a single box is drawn. That box position is then positioned with with `name` or with `x0` (`y0`) if provided. Each box spans from quartile 1 (Q1) to quartile 3 (Q3). The second quartile (Q2) is marked by a line inside the box. By default, the whiskers correspond to the box' edges +/- 1.5 times the interquartile range (IQR: Q3-Q1), see "boxpoints" for other options. Parameters ---------- alignmentgroup Set several traces linked to the same position axis or matching axes to the same alignmentgroup. This controls whether bars compute their positional range dependently or independently. boxmean If True, the mean of the box(es)' underlying distribution is drawn as a dashed line inside the box(es). If "sd" the standard deviation is also drawn. boxpoints If "outliers", only the sample points lying outside the whiskers are shown If "suspectedoutliers", the outlier points are shown and points either less than 4*Q1-3*Q3 or greater than 4*Q3-3*Q1 are highlighted (see `outliercolor`) If "all", all sample points are shown If False, only the box(es) are shown with no sample points customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . fillcolor Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.box.Hoverlabel instance or dict with compatible properties hoveron Do the hover effects highlight individual boxes or sample points or both? hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . jitter Sets the amount of jitter in the sample points drawn. If 0, the sample points align along the distribution axis. If 1, the sample points are drawn in a random jitter of width equal to the width of the box(es). legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.box.Line instance or dict with compatible properties marker plotly.graph_objects.box.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. For box traces, the name will also be used for the position coordinate, if `x` and `x0` (`y` and `y0` if horizontal) are missing and the position axis is categorical notched Determines whether or not notches should be drawn. notchwidth Sets the width of the notches relative to the box' width. For example, with 0, the notches are as wide as the box(es). offsetgroup Set several traces linked to the same position axis or matching axes to the same offsetgroup where bars of the same position coordinate will line up. opacity Sets the opacity of the trace. orientation Sets the orientation of the box(es). If "v" ("h"), the distribution is visualized along the vertical (horizontal). pointpos Sets the position of the sample points in relation to the box(es). If 0, the sample points are places over the center of the box(es). Positive (negative) values correspond to positions to the right (left) for vertical boxes and above (below) for horizontal boxes selected plotly.graph_objects.box.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.box.Stream instance or dict with compatible properties text Sets the text elements associated with each sample value. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.box.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). whiskerwidth Sets the width of the whiskers relative to the box' width. For example, with 1, the whiskers are as wide as the box(es). width Sets the width of the box in data coordinate If 0 (default value) the width is automatically selected based on the positions of other box traces in the same subplot. x Sets the x sample data or coordinates. See overview for more info. x0 Sets the x coordinate of the box. See overview for more info. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . y Sets the y sample data or coordinates. See overview for more info. y0 Sets the y coordinate of the box. See overview for more info. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` secondary_y: boolean or None (default None) If True, associate this trace with the secondary y-axis of the subplot at the specified row and col. Only valid if all of the following conditions are satisfied: * The figure was created using `plotly.subplots.make_subplots`. * The row and col arguments are not None * The subplot at the specified row and col has type xy (which is the default) and secondary_y True. These properties are specified in the specs argument to make_subplots. See the make_subplots docstring for more info. Returns ------- FigureWidget """ new_trace = Box( alignmentgroup=alignmentgroup, boxmean=boxmean, boxpoints=boxpoints, customdata=customdata, customdatasrc=customdatasrc, fillcolor=fillcolor, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hoveron=hoveron, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, jitter=jitter, legendgroup=legendgroup, line=line, marker=marker, meta=meta, metasrc=metasrc, name=name, notched=notched, notchwidth=notchwidth, offsetgroup=offsetgroup, opacity=opacity, orientation=orientation, pointpos=pointpos, selected=selected, selectedpoints=selectedpoints, showlegend=showlegend, stream=stream, text=text, textsrc=textsrc, uid=uid, uirevision=uirevision, unselected=unselected, visible=visible, whiskerwidth=whiskerwidth, width=width, x=x, x0=x0, xaxis=xaxis, xcalendar=xcalendar, xsrc=xsrc, y=y, y0=y0, yaxis=yaxis, ycalendar=ycalendar, ysrc=ysrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) def add_candlestick( self, close=None, closesrc=None, customdata=None, customdatasrc=None, decreasing=None, high=None, highsrc=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, increasing=None, legendgroup=None, line=None, low=None, lowsrc=None, meta=None, metasrc=None, name=None, opacity=None, open=None, opensrc=None, selectedpoints=None, showlegend=None, stream=None, text=None, textsrc=None, uid=None, uirevision=None, visible=None, whiskerwidth=None, x=None, xaxis=None, xcalendar=None, xsrc=None, yaxis=None, row=None, col=None, secondary_y=None, **kwargs ): """ Add a new Candlestick trace The candlestick is a style of financial chart describing open, high, low and close for a given `x` coordinate (most likely time). The boxes represent the spread between the `open` and `close` values and the lines represent the spread between the `low` and `high` values Sample points where the close value is higher (lower) then the open value are called increasing (decreasing). By default, increasing candles are drawn in green whereas decreasing are drawn in red. Parameters ---------- close Sets the close values. closesrc Sets the source reference on plot.ly for close . customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . decreasing plotly.graph_objects.candlestick.Decreasing instance or dict with compatible properties high Sets the high values. highsrc Sets the source reference on plot.ly for high . hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.candlestick.Hoverlabel instance or dict with compatible properties hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . increasing plotly.graph_objects.candlestick.Increasing instance or dict with compatible properties legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.candlestick.Line instance or dict with compatible properties low Sets the low values. lowsrc Sets the source reference on plot.ly for low . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. open Sets the open values. opensrc Sets the source reference on plot.ly for open . selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.candlestick.Stream instance or dict with compatible properties text Sets hover text elements associated with each sample point. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to this trace's sample points. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). whiskerwidth Sets the width of the whiskers relative to the box' width. For example, with 1, the whiskers are as wide as the box(es). x Sets the x coordinates. If absent, linear coordinate will be generated. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` secondary_y: boolean or None (default None) If True, associate this trace with the secondary y-axis of the subplot at the specified row and col. Only valid if all of the following conditions are satisfied: * The figure was created using `plotly.subplots.make_subplots`. * The row and col arguments are not None * The subplot at the specified row and col has type xy (which is the default) and secondary_y True. These properties are specified in the specs argument to make_subplots. See the make_subplots docstring for more info. Returns ------- FigureWidget """ new_trace = Candlestick( close=close, closesrc=closesrc, customdata=customdata, customdatasrc=customdatasrc, decreasing=decreasing, high=high, highsrc=highsrc, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, increasing=increasing, legendgroup=legendgroup, line=line, low=low, lowsrc=lowsrc, meta=meta, metasrc=metasrc, name=name, opacity=opacity, open=open, opensrc=opensrc, selectedpoints=selectedpoints, showlegend=showlegend, stream=stream, text=text, textsrc=textsrc, uid=uid, uirevision=uirevision, visible=visible, whiskerwidth=whiskerwidth, x=x, xaxis=xaxis, xcalendar=xcalendar, xsrc=xsrc, yaxis=yaxis, **kwargs ) return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) def add_carpet( self, a=None, a0=None, aaxis=None, asrc=None, b=None, b0=None, baxis=None, bsrc=None, carpet=None, cheaterslope=None, color=None, customdata=None, customdatasrc=None, da=None, db=None, font=None, ids=None, idssrc=None, meta=None, metasrc=None, name=None, opacity=None, stream=None, uid=None, uirevision=None, visible=None, x=None, xaxis=None, xsrc=None, y=None, yaxis=None, ysrc=None, row=None, col=None, secondary_y=None, **kwargs ): """ Add a new Carpet trace The data describing carpet axis layout is set in `y` and (optionally) also `x`. If only `y` is present, `x` the plot is interpreted as a cheater plot and is filled in using the `y` values. `x` and `y` may either be 2D arrays matching with each dimension matching that of `a` and `b`, or they may be 1D arrays with total length equal to that of `a` and `b`. Parameters ---------- a An array containing values of the first parameter value a0 Alternate to `a`. Builds a linear space of a coordinates. Use with `da` where `a0` is the starting coordinate and `da` the step. aaxis plotly.graph_objects.carpet.Aaxis instance or dict with compatible properties asrc Sets the source reference on plot.ly for a . b A two dimensional array of y coordinates at each carpet point. b0 Alternate to `b`. Builds a linear space of a coordinates. Use with `db` where `b0` is the starting coordinate and `db` the step. baxis plotly.graph_objects.carpet.Baxis instance or dict with compatible properties bsrc Sets the source reference on plot.ly for b . carpet An identifier for this carpet, so that `scattercarpet` and `contourcarpet` traces can specify a carpet plot on which they lie cheaterslope The shift applied to each successive row of data in creating a cheater plot. Only used if `x` is been ommitted. color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . da Sets the a coordinate step. See `a0` for more info. db Sets the b coordinate step. See `b0` for more info. font The default font used for axis & tick labels on this carpet ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. stream plotly.graph_objects.carpet.Stream instance or dict with compatible properties uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x A two dimensional array of x coordinates at each carpet point. If ommitted, the plot is a cheater plot and the xaxis is hidden by default. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xsrc Sets the source reference on plot.ly for x . y A two dimensional array of y coordinates at each carpet point. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ysrc Sets the source reference on plot.ly for y . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` secondary_y: boolean or None (default None) If True, associate this trace with the secondary y-axis of the subplot at the specified row and col. Only valid if all of the following conditions are satisfied: * The figure was created using `plotly.subplots.make_subplots`. * The row and col arguments are not None * The subplot at the specified row and col has type xy (which is the default) and secondary_y True. These properties are specified in the specs argument to make_subplots. See the make_subplots docstring for more info. Returns ------- FigureWidget """ new_trace = Carpet( a=a, a0=a0, aaxis=aaxis, asrc=asrc, b=b, b0=b0, baxis=baxis, bsrc=bsrc, carpet=carpet, cheaterslope=cheaterslope, color=color, customdata=customdata, customdatasrc=customdatasrc, da=da, db=db, font=font, ids=ids, idssrc=idssrc, meta=meta, metasrc=metasrc, name=name, opacity=opacity, stream=stream, uid=uid, uirevision=uirevision, visible=visible, x=x, xaxis=xaxis, xsrc=xsrc, y=y, yaxis=yaxis, ysrc=ysrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) def add_choropleth( self, autocolorscale=None, coloraxis=None, colorbar=None, colorscale=None, customdata=None, customdatasrc=None, geo=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, locationmode=None, locations=None, locationssrc=None, marker=None, meta=None, metasrc=None, name=None, reversescale=None, selected=None, selectedpoints=None, showscale=None, stream=None, text=None, textsrc=None, uid=None, uirevision=None, unselected=None, visible=None, z=None, zauto=None, zmax=None, zmid=None, zmin=None, zsrc=None, row=None, col=None, **kwargs ): """ Add a new Choropleth trace The data that describes the choropleth value-to-color mapping is set in `z`. The geographic locations corresponding to each value in `z` are set in `locations`. Parameters ---------- autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.choropleth.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . geo Sets a reference between this trace's geospatial coordinates and a geographic map. If "geo" (the default value), the geospatial coordinates refer to `layout.geo`. If "geo2", the geospatial coordinates refer to `layout.geo2`, and so on. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.choropleth.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . locationmode Determines the set of locations used to match entries in `locations` to regions on the map. locations Sets the coordinates via location IDs or names. See `locationmode` for more info. locationssrc Sets the source reference on plot.ly for locations . marker plotly.graph_objects.choropleth.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. reversescale Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. selected plotly.graph_objects.choropleth.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.choropleth.Stream instance or dict with compatible properties text Sets the text elements associated with each location. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.choropleth.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). z Sets the color values. zauto Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. zmax Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. zmid Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. zmin Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. zsrc Sets the source reference on plot.ly for z . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- FigureWidget """ new_trace = Choropleth( autocolorscale=autocolorscale, coloraxis=coloraxis, colorbar=colorbar, colorscale=colorscale, customdata=customdata, customdatasrc=customdatasrc, geo=geo, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, locationmode=locationmode, locations=locations, locationssrc=locationssrc, marker=marker, meta=meta, metasrc=metasrc, name=name, reversescale=reversescale, selected=selected, selectedpoints=selectedpoints, showscale=showscale, stream=stream, text=text, textsrc=textsrc, uid=uid, uirevision=uirevision, unselected=unselected, visible=visible, z=z, zauto=zauto, zmax=zmax, zmid=zmid, zmin=zmin, zsrc=zsrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_choroplethmapbox( self, autocolorscale=None, below=None, coloraxis=None, colorbar=None, colorscale=None, customdata=None, customdatasrc=None, geojson=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, locations=None, locationssrc=None, marker=None, meta=None, metasrc=None, name=None, reversescale=None, selected=None, selectedpoints=None, showscale=None, stream=None, subplot=None, text=None, textsrc=None, uid=None, uirevision=None, unselected=None, visible=None, z=None, zauto=None, zmax=None, zmid=None, zmin=None, zsrc=None, row=None, col=None, **kwargs ): """ Add a new Choroplethmapbox trace GeoJSON features to be filled are set in `geojson` The data that describes the choropleth value-to-color mapping is set in `locations` and `z`. Parameters ---------- autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. below Determines if the choropleth polygons will be inserted before the layer with the specified ID. By default, choroplethmapbox traces are placed above the water layers. If set to '', the layer will be inserted above every existing layer. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.choroplethmapbox.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . geojson Sets the GeoJSON data associated with this trace. Can be set as a valid GeoJSON object or as URL string Note that we only accept GeoJSON of type "FeatureCollection" and "Feature" with geometries of type "Polygon" and "MultiPolygon". hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.choroplethmapbox.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variable `properties` Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . locations Sets which features found in "geojson" to plot using their feature `id` field. locationssrc Sets the source reference on plot.ly for locations . marker plotly.graph_objects.choroplethmapbox.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. reversescale Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. selected plotly.graph_objects.choroplethmapbox.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.choroplethmapbox.Stream instance or dict with compatible properties subplot Sets a reference between this trace's data coordinates and a mapbox subplot. If "mapbox" (the default value), the data refer to `layout.mapbox`. If "mapbox2", the data refer to `layout.mapbox2`, and so on. text Sets the text elements associated with each location. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.choroplethmapbox.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). z Sets the color values. zauto Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. zmax Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. zmid Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. zmin Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. zsrc Sets the source reference on plot.ly for z . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- FigureWidget """ new_trace = Choroplethmapbox( autocolorscale=autocolorscale, below=below, coloraxis=coloraxis, colorbar=colorbar, colorscale=colorscale, customdata=customdata, customdatasrc=customdatasrc, geojson=geojson, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, locations=locations, locationssrc=locationssrc, marker=marker, meta=meta, metasrc=metasrc, name=name, reversescale=reversescale, selected=selected, selectedpoints=selectedpoints, showscale=showscale, stream=stream, subplot=subplot, text=text, textsrc=textsrc, uid=uid, uirevision=uirevision, unselected=unselected, visible=visible, z=z, zauto=zauto, zmax=zmax, zmid=zmid, zmin=zmin, zsrc=zsrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_cone( self, anchor=None, autocolorscale=None, cauto=None, cmax=None, cmid=None, cmin=None, coloraxis=None, colorbar=None, colorscale=None, customdata=None, customdatasrc=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, lighting=None, lightposition=None, meta=None, metasrc=None, name=None, opacity=None, reversescale=None, scene=None, showscale=None, sizemode=None, sizeref=None, stream=None, text=None, textsrc=None, u=None, uid=None, uirevision=None, usrc=None, v=None, visible=None, vsrc=None, w=None, wsrc=None, x=None, xsrc=None, y=None, ysrc=None, z=None, zsrc=None, row=None, col=None, **kwargs ): """ Add a new Cone trace Use cone traces to visualize vector fields. Specify a vector field using 6 1D arrays, 3 position arrays `x`, `y` and `z` and 3 vector component arrays `u`, `v`, `w`. The cones are drawn exactly at the positions given by `x`, `y` and `z`. Parameters ---------- anchor Sets the cones' anchor with respect to their x/y/z positions. Note that "cm" denote the cone's center of mass which corresponds to 1/4 from the tail to tip. autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here u/v/w norm) or the bounds set in `cmin` and `cmax` Defaults to `false` when `cmin` and `cmax` are set by the user. cmax Sets the upper bound of the color domain. Value should have the same units as u/v/w norm and if set, `cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `cmin` and/or `cmax` to be equidistant to this point. Value should have the same units as u/v/w norm. Has no effect when `cauto` is `false`. cmin Sets the lower bound of the color domain. Value should have the same units as u/v/w norm and if set, `cmax` must be set as well. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.cone.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`cmin` and `cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.cone.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variable `norm` Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . lighting plotly.graph_objects.cone.Lighting instance or dict with compatible properties lightposition plotly.graph_objects.cone.Lightposition instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the surface. Please note that in the case of using high `opacity` values for example a value greater than or equal to 0.5 on two surfaces (and 0.25 with four surfaces), an overlay of multiple transparent surfaces may not perfectly be sorted in depth by the webgl API. This behavior may be improved in the near future and is subject to change. reversescale Reverses the color mapping if true. If true, `cmin` will correspond to the last color in the array and `cmax` will correspond to the first color. scene Sets a reference between this trace's 3D coordinate system and a 3D scene. If "scene" (the default value), the (x,y,z) coordinates refer to `layout.scene`. If "scene2", the (x,y,z) coordinates refer to `layout.scene2`, and so on. showscale Determines whether or not a colorbar is displayed for this trace. sizemode Determines whether `sizeref` is set as a "scaled" (i.e unitless) scalar (normalized by the max u/v/w norm in the vector field) or as "absolute" value (in the same units as the vector field). sizeref Adjusts the cone size scaling. The size of the cones is determined by their u/v/w norm multiplied a factor and `sizeref`. This factor (computed internally) corresponds to the minimum "time" to travel across two successive x/y/z positions at the average velocity of those two successive positions. All cones in a given trace use the same factor. With `sizemode` set to "scaled", `sizeref` is unitless, its default value is 0.5 With `sizemode` set to "absolute", `sizeref` has the same units as the u/v/w vector field, its the default value is half the sample's maximum vector norm. stream plotly.graph_objects.cone.Stream instance or dict with compatible properties text Sets the text elements associated with the cones. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textsrc Sets the source reference on plot.ly for text . u Sets the x components of the vector field. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. usrc Sets the source reference on plot.ly for u . v Sets the y components of the vector field. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). vsrc Sets the source reference on plot.ly for v . w Sets the z components of the vector field. wsrc Sets the source reference on plot.ly for w . x Sets the x coordinates of the vector field and of the displayed cones. xsrc Sets the source reference on plot.ly for x . y Sets the y coordinates of the vector field and of the displayed cones. ysrc Sets the source reference on plot.ly for y . z Sets the z coordinates of the vector field and of the displayed cones. zsrc Sets the source reference on plot.ly for z . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- FigureWidget """ new_trace = Cone( anchor=anchor, autocolorscale=autocolorscale, cauto=cauto, cmax=cmax, cmid=cmid, cmin=cmin, coloraxis=coloraxis, colorbar=colorbar, colorscale=colorscale, customdata=customdata, customdatasrc=customdatasrc, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, lighting=lighting, lightposition=lightposition, meta=meta, metasrc=metasrc, name=name, opacity=opacity, reversescale=reversescale, scene=scene, showscale=showscale, sizemode=sizemode, sizeref=sizeref, stream=stream, text=text, textsrc=textsrc, u=u, uid=uid, uirevision=uirevision, usrc=usrc, v=v, visible=visible, vsrc=vsrc, w=w, wsrc=wsrc, x=x, xsrc=xsrc, y=y, ysrc=ysrc, z=z, zsrc=zsrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_contour( self, autocolorscale=None, autocontour=None, coloraxis=None, colorbar=None, colorscale=None, connectgaps=None, contours=None, customdata=None, customdatasrc=None, dx=None, dy=None, fillcolor=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hoverongaps=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, legendgroup=None, line=None, meta=None, metasrc=None, name=None, ncontours=None, opacity=None, reversescale=None, showlegend=None, showscale=None, stream=None, text=None, textsrc=None, transpose=None, uid=None, uirevision=None, visible=None, x=None, x0=None, xaxis=None, xcalendar=None, xsrc=None, xtype=None, y=None, y0=None, yaxis=None, ycalendar=None, ysrc=None, ytype=None, z=None, zauto=None, zhoverformat=None, zmax=None, zmid=None, zmin=None, zsrc=None, row=None, col=None, secondary_y=None, **kwargs ): """ Add a new Contour trace The data from which contour lines are computed is set in `z`. Data in `z` must be a 2D list of numbers. Say that `z` has N rows and M columns, then by default, these N rows correspond to N y coordinates (set in `y` or auto-generated) and the M columns correspond to M x coordinates (set in `x` or auto- generated). By setting `transpose` to True, the above behavior is flipped. Parameters ---------- autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. autocontour Determines whether or not the contour level attributes are picked by an algorithm. If True, the number of contour levels can be set in `ncontours`. If False, set the contour level attributes in `contours`. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.contour.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the `z` data are filled in. It is defaulted to true if `z` is a one dimensional array otherwise it is defaulted to false. contours plotly.graph_objects.contour.Contours instance or dict with compatible properties customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dx Sets the x coordinate step. See `x0` for more info. dy Sets the y coordinate step. See `y0` for more info. fillcolor Sets the fill color if `contours.type` is "constraint". Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.contour.Hoverlabel instance or dict with compatible properties hoverongaps Determines whether or not gaps (i.e. {nan} or missing values) in the `z` data have hover labels associated with them. hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.contour.Line instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. ncontours Sets the maximum number of contour levels. The actual number of contours will be chosen automatically to be less than or equal to the value of `ncontours`. Has an effect only if `autocontour` is True or if `contours.size` is missing. opacity Sets the opacity of the trace. reversescale Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.contour.Stream instance or dict with compatible properties text Sets the text elements associated with each z value. textsrc Sets the source reference on plot.ly for text . transpose Transposes the z data. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the x coordinates. x0 Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . xtype If "array", the heatmap's x coordinates are given by "x" (the default behavior when `x` is provided). If "scaled", the heatmap's x coordinates are given by "x0" and "dx" (the default behavior when `x` is not provided). y Sets the y coordinates. y0 Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . ytype If "array", the heatmap's y coordinates are given by "y" (the default behavior when `y` is provided) If "scaled", the heatmap's y coordinates are given by "y0" and "dy" (the default behavior when `y` is not provided) z Sets the z data. zauto Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. zhoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. See: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format zmax Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. zmid Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. zmin Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. zsrc Sets the source reference on plot.ly for z . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` secondary_y: boolean or None (default None) If True, associate this trace with the secondary y-axis of the subplot at the specified row and col. Only valid if all of the following conditions are satisfied: * The figure was created using `plotly.subplots.make_subplots`. * The row and col arguments are not None * The subplot at the specified row and col has type xy (which is the default) and secondary_y True. These properties are specified in the specs argument to make_subplots. See the make_subplots docstring for more info. Returns ------- FigureWidget """ new_trace = Contour( autocolorscale=autocolorscale, autocontour=autocontour, coloraxis=coloraxis, colorbar=colorbar, colorscale=colorscale, connectgaps=connectgaps, contours=contours, customdata=customdata, customdatasrc=customdatasrc, dx=dx, dy=dy, fillcolor=fillcolor, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hoverongaps=hoverongaps, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, legendgroup=legendgroup, line=line, meta=meta, metasrc=metasrc, name=name, ncontours=ncontours, opacity=opacity, reversescale=reversescale, showlegend=showlegend, showscale=showscale, stream=stream, text=text, textsrc=textsrc, transpose=transpose, uid=uid, uirevision=uirevision, visible=visible, x=x, x0=x0, xaxis=xaxis, xcalendar=xcalendar, xsrc=xsrc, xtype=xtype, y=y, y0=y0, yaxis=yaxis, ycalendar=ycalendar, ysrc=ysrc, ytype=ytype, z=z, zauto=zauto, zhoverformat=zhoverformat, zmax=zmax, zmid=zmid, zmin=zmin, zsrc=zsrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) def add_contourcarpet( self, a=None, a0=None, asrc=None, atype=None, autocolorscale=None, autocontour=None, b=None, b0=None, bsrc=None, btype=None, carpet=None, coloraxis=None, colorbar=None, colorscale=None, contours=None, customdata=None, customdatasrc=None, da=None, db=None, fillcolor=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, legendgroup=None, line=None, meta=None, metasrc=None, name=None, ncontours=None, opacity=None, reversescale=None, showlegend=None, showscale=None, stream=None, text=None, textsrc=None, transpose=None, uid=None, uirevision=None, visible=None, xaxis=None, yaxis=None, z=None, zauto=None, zmax=None, zmid=None, zmin=None, zsrc=None, row=None, col=None, secondary_y=None, **kwargs ): """ Add a new Contourcarpet trace Plots contours on either the first carpet axis or the carpet axis with a matching `carpet` attribute. Data `z` is interpreted as matching that of the corresponding carpet axis. Parameters ---------- a Sets the x coordinates. a0 Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. asrc Sets the source reference on plot.ly for a . atype If "array", the heatmap's x coordinates are given by "x" (the default behavior when `x` is provided). If "scaled", the heatmap's x coordinates are given by "x0" and "dx" (the default behavior when `x` is not provided). autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. autocontour Determines whether or not the contour level attributes are picked by an algorithm. If True, the number of contour levels can be set in `ncontours`. If False, set the contour level attributes in `contours`. b Sets the y coordinates. b0 Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. bsrc Sets the source reference on plot.ly for b . btype If "array", the heatmap's y coordinates are given by "y" (the default behavior when `y` is provided) If "scaled", the heatmap's y coordinates are given by "y0" and "dy" (the default behavior when `y` is not provided) carpet The `carpet` of the carpet axes on which this contour trace lies coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.contourcarpet.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. contours plotly.graph_objects.contourcarpet.Contours instance or dict with compatible properties customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . da Sets the x coordinate step. See `x0` for more info. db Sets the y coordinate step. See `y0` for more info. fillcolor Sets the fill color if `contours.type` is "constraint". Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.contourcarpet.Line instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. ncontours Sets the maximum number of contour levels. The actual number of contours will be chosen automatically to be less than or equal to the value of `ncontours`. Has an effect only if `autocontour` is True or if `contours.size` is missing. opacity Sets the opacity of the trace. reversescale Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.contourcarpet.Stream instance or dict with compatible properties text Sets the text elements associated with each z value. textsrc Sets the source reference on plot.ly for text . transpose Transposes the z data. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. z Sets the z data. zauto Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. zmax Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. zmid Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. zmin Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. zsrc Sets the source reference on plot.ly for z . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` secondary_y: boolean or None (default None) If True, associate this trace with the secondary y-axis of the subplot at the specified row and col. Only valid if all of the following conditions are satisfied: * The figure was created using `plotly.subplots.make_subplots`. * The row and col arguments are not None * The subplot at the specified row and col has type xy (which is the default) and secondary_y True. These properties are specified in the specs argument to make_subplots. See the make_subplots docstring for more info. Returns ------- FigureWidget """ new_trace = Contourcarpet( a=a, a0=a0, asrc=asrc, atype=atype, autocolorscale=autocolorscale, autocontour=autocontour, b=b, b0=b0, bsrc=bsrc, btype=btype, carpet=carpet, coloraxis=coloraxis, colorbar=colorbar, colorscale=colorscale, contours=contours, customdata=customdata, customdatasrc=customdatasrc, da=da, db=db, fillcolor=fillcolor, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, legendgroup=legendgroup, line=line, meta=meta, metasrc=metasrc, name=name, ncontours=ncontours, opacity=opacity, reversescale=reversescale, showlegend=showlegend, showscale=showscale, stream=stream, text=text, textsrc=textsrc, transpose=transpose, uid=uid, uirevision=uirevision, visible=visible, xaxis=xaxis, yaxis=yaxis, z=z, zauto=zauto, zmax=zmax, zmid=zmid, zmin=zmin, zsrc=zsrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) def add_densitymapbox( self, autocolorscale=None, below=None, coloraxis=None, colorbar=None, colorscale=None, customdata=None, customdatasrc=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, lat=None, latsrc=None, lon=None, lonsrc=None, meta=None, metasrc=None, name=None, opacity=None, radius=None, radiussrc=None, reversescale=None, showscale=None, stream=None, subplot=None, text=None, textsrc=None, uid=None, uirevision=None, visible=None, z=None, zauto=None, zmax=None, zmid=None, zmin=None, zsrc=None, row=None, col=None, **kwargs ): """ Add a new Densitymapbox trace Draws a bivariate kernel density estimation with a Gaussian kernel from `lon` and `lat` coordinates and optional `z` values using a colorscale. Parameters ---------- autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. below Determines if the densitymapbox trace will be inserted before the layer with the specified ID. By default, densitymapbox traces are placed below the first layer of type symbol If set to '', the layer will be inserted above every existing layer. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.densitymapbox.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.densitymapbox.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (lon,lat) pair If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (lon,lat) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . lat Sets the latitude coordinates (in degrees North). latsrc Sets the source reference on plot.ly for lat . lon Sets the longitude coordinates (in degrees East). lonsrc Sets the source reference on plot.ly for lon . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. radius Sets the radius of influence of one `lon` / `lat` point in pixels. Increasing the value makes the densitymapbox trace smoother, but less detailed. radiussrc Sets the source reference on plot.ly for radius . reversescale Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.densitymapbox.Stream instance or dict with compatible properties subplot Sets a reference between this trace's data coordinates and a mapbox subplot. If "mapbox" (the default value), the data refer to `layout.mapbox`. If "mapbox2", the data refer to `layout.mapbox2`, and so on. text Sets text elements associated with each (lon,lat) pair If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (lon,lat) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). z Sets the points' weight. For example, a value of 10 would be equivalent to having 10 points of weight 1 in the same spot zauto Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. zmax Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. zmid Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. zmin Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. zsrc Sets the source reference on plot.ly for z . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- FigureWidget """ new_trace = Densitymapbox( autocolorscale=autocolorscale, below=below, coloraxis=coloraxis, colorbar=colorbar, colorscale=colorscale, customdata=customdata, customdatasrc=customdatasrc, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, lat=lat, latsrc=latsrc, lon=lon, lonsrc=lonsrc, meta=meta, metasrc=metasrc, name=name, opacity=opacity, radius=radius, radiussrc=radiussrc, reversescale=reversescale, showscale=showscale, stream=stream, subplot=subplot, text=text, textsrc=textsrc, uid=uid, uirevision=uirevision, visible=visible, z=z, zauto=zauto, zmax=zmax, zmid=zmid, zmin=zmin, zsrc=zsrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_funnel( self, alignmentgroup=None, cliponaxis=None, connector=None, constraintext=None, customdata=None, customdatasrc=None, dx=None, dy=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, insidetextanchor=None, insidetextfont=None, legendgroup=None, marker=None, meta=None, metasrc=None, name=None, offset=None, offsetgroup=None, opacity=None, orientation=None, outsidetextfont=None, selectedpoints=None, showlegend=None, stream=None, text=None, textangle=None, textfont=None, textinfo=None, textposition=None, textpositionsrc=None, textsrc=None, texttemplate=None, texttemplatesrc=None, uid=None, uirevision=None, visible=None, width=None, x=None, x0=None, xaxis=None, xsrc=None, y=None, y0=None, yaxis=None, ysrc=None, row=None, col=None, secondary_y=None, **kwargs ): """ Add a new Funnel trace Visualize stages in a process using length-encoded bars. This trace can be used to show data in either a part-to-whole representation wherein each item appears in a single stage, or in a "drop-off" representation wherein each item appears in each stage it traversed. See also the "funnelarea" trace type for a different approach to visualizing funnel data. Parameters ---------- alignmentgroup Set several traces linked to the same position axis or matching axes to the same alignmentgroup. This controls whether bars compute their positional range dependently or independently. cliponaxis Determines whether the text nodes are clipped about the subplot axes. To show the text nodes above axis lines and tick labels, make sure to set `xaxis.layer` and `yaxis.layer` to *below traces*. connector plotly.graph_objects.funnel.Connector instance or dict with compatible properties constraintext Constrain the size of text inside or outside a bar to be no larger than the bar itself. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dx Sets the x coordinate step. See `x0` for more info. dy Sets the y coordinate step. See `y0` for more info. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.funnel.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `percentInitial`, `percentPrevious` and `percentTotal`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . insidetextanchor Determines if texts are kept at center or start/end points in `textposition` "inside" mode. insidetextfont Sets the font used for `text` lying inside the bar. legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. marker plotly.graph_objects.funnel.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. offset Shifts the position where the bar is drawn (in position axis units). In "group" barmode, traces that set "offset" will be excluded and drawn in "overlay" mode instead. offsetgroup Set several traces linked to the same position axis or matching axes to the same offsetgroup where bars of the same position coordinate will line up. opacity Sets the opacity of the trace. orientation Sets the orientation of the funnels. With "v" ("h"), the value of the each bar spans along the vertical (horizontal). By default funnels are tend to be oriented horizontally; unless only "y" array is presented or orientation is set to "v". Also regarding graphs including only 'horizontal' funnels, "autorange" on the "y-axis" are set to "reversed". outsidetextfont Sets the font used for `text` lying outside the bar. selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.funnel.Stream instance or dict with compatible properties text Sets text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textangle Sets the angle of the tick labels with respect to the bar. For example, a `tickangle` of -90 draws the tick labels vertically. With "auto" the texts may automatically be rotated to fit with the maximum size in bars. textfont Sets the font used for `text`. textinfo Determines which trace information appear on the graph. In the case of having multiple funnels, percentages & totals are computed separately (per trace). textposition Specifies the location of the `text`. "inside" positions `text` inside, next to the bar end (rotated and scaled if needed). "outside" positions `text` outside, next to the bar end (scaled if needed), unless there is another bar stacked on this one, then the text gets pushed inside. "auto" tries to position `text` inside the bar, but if the bar is too small and no bar is stacked on this one the text is moved outside. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `percentInitial`, `percentPrevious`, `percentTotal`, `label` and `value`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). width Sets the bar width (in position axis units). x Sets the x coordinates. x0 Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xsrc Sets the source reference on plot.ly for x . y Sets the y coordinates. y0 Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ysrc Sets the source reference on plot.ly for y . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` secondary_y: boolean or None (default None) If True, associate this trace with the secondary y-axis of the subplot at the specified row and col. Only valid if all of the following conditions are satisfied: * The figure was created using `plotly.subplots.make_subplots`. * The row and col arguments are not None * The subplot at the specified row and col has type xy (which is the default) and secondary_y True. These properties are specified in the specs argument to make_subplots. See the make_subplots docstring for more info. Returns ------- FigureWidget """ new_trace = Funnel( alignmentgroup=alignmentgroup, cliponaxis=cliponaxis, connector=connector, constraintext=constraintext, customdata=customdata, customdatasrc=customdatasrc, dx=dx, dy=dy, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, insidetextanchor=insidetextanchor, insidetextfont=insidetextfont, legendgroup=legendgroup, marker=marker, meta=meta, metasrc=metasrc, name=name, offset=offset, offsetgroup=offsetgroup, opacity=opacity, orientation=orientation, outsidetextfont=outsidetextfont, selectedpoints=selectedpoints, showlegend=showlegend, stream=stream, text=text, textangle=textangle, textfont=textfont, textinfo=textinfo, textposition=textposition, textpositionsrc=textpositionsrc, textsrc=textsrc, texttemplate=texttemplate, texttemplatesrc=texttemplatesrc, uid=uid, uirevision=uirevision, visible=visible, width=width, x=x, x0=x0, xaxis=xaxis, xsrc=xsrc, y=y, y0=y0, yaxis=yaxis, ysrc=ysrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) def add_funnelarea( self, aspectratio=None, baseratio=None, customdata=None, customdatasrc=None, dlabel=None, domain=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, insidetextfont=None, label0=None, labels=None, labelssrc=None, legendgroup=None, marker=None, meta=None, metasrc=None, name=None, opacity=None, scalegroup=None, showlegend=None, stream=None, text=None, textfont=None, textinfo=None, textposition=None, textpositionsrc=None, textsrc=None, texttemplate=None, texttemplatesrc=None, title=None, uid=None, uirevision=None, values=None, valuessrc=None, visible=None, row=None, col=None, **kwargs ): """ Add a new Funnelarea trace Visualize stages in a process using area-encoded trapezoids. This trace can be used to show data in a part-to-whole representation similar to a "pie" trace, wherein each item appears in a single stage. See also the "funnel" trace type for a different approach to visualizing funnel data. Parameters ---------- aspectratio Sets the ratio between height and width baseratio Sets the ratio between bottom length and maximum top length. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dlabel Sets the label step. See `label0` for more info. domain plotly.graph_objects.funnelarea.Domain instance or dict with compatible properties hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.funnelarea.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `label`, `color`, `value`, `text` and `percent`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each sector. If a single string, the same string appears for all data points. If an array of string, the items are mapped in order of this trace's sectors. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . insidetextfont Sets the font used for `textinfo` lying inside the sector. label0 Alternate to `labels`. Builds a numeric set of labels. Use with `dlabel` where `label0` is the starting label and `dlabel` the step. labels Sets the sector labels. If `labels` entries are duplicated, we sum associated `values` or simply count occurrences if `values` is not provided. For other array attributes (including color) we use the first non-empty entry among all occurrences of the label. labelssrc Sets the source reference on plot.ly for labels . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. marker plotly.graph_objects.funnelarea.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. scalegroup If there are multiple funnelareas that should be sized according to their totals, link them by providing a non-empty group id here shared by every trace in the same group. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.funnelarea.Stream instance or dict with compatible properties text Sets text elements associated with each sector. If trace `textinfo` contains a "text" flag, these elements will be seen on the chart. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the font used for `textinfo`. textinfo Determines which trace information appear on the graph. textposition Specifies the location of the `textinfo`. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `label`, `color`, `value`, `text` and `percent`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . title plotly.graph_objects.funnelarea.Title instance or dict with compatible properties uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. values Sets the values of the sectors. If omitted, we count occurrences of each label. valuessrc Sets the source reference on plot.ly for values . visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- FigureWidget """ new_trace = Funnelarea( aspectratio=aspectratio, baseratio=baseratio, customdata=customdata, customdatasrc=customdatasrc, dlabel=dlabel, domain=domain, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, insidetextfont=insidetextfont, label0=label0, labels=labels, labelssrc=labelssrc, legendgroup=legendgroup, marker=marker, meta=meta, metasrc=metasrc, name=name, opacity=opacity, scalegroup=scalegroup, showlegend=showlegend, stream=stream, text=text, textfont=textfont, textinfo=textinfo, textposition=textposition, textpositionsrc=textpositionsrc, textsrc=textsrc, texttemplate=texttemplate, texttemplatesrc=texttemplatesrc, title=title, uid=uid, uirevision=uirevision, values=values, valuessrc=valuessrc, visible=visible, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_heatmap( self, autocolorscale=None, coloraxis=None, colorbar=None, colorscale=None, connectgaps=None, customdata=None, customdatasrc=None, dx=None, dy=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hoverongaps=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, meta=None, metasrc=None, name=None, opacity=None, reversescale=None, showscale=None, stream=None, text=None, textsrc=None, transpose=None, uid=None, uirevision=None, visible=None, x=None, x0=None, xaxis=None, xcalendar=None, xgap=None, xsrc=None, xtype=None, y=None, y0=None, yaxis=None, ycalendar=None, ygap=None, ysrc=None, ytype=None, z=None, zauto=None, zhoverformat=None, zmax=None, zmid=None, zmin=None, zsmooth=None, zsrc=None, row=None, col=None, secondary_y=None, **kwargs ): """ Add a new Heatmap trace The data that describes the heatmap value-to-color mapping is set in `z`. Data in `z` can either be a 2D list of values (ragged or not) or a 1D array of values. In the case where `z` is a 2D list, say that `z` has N rows and M columns. Then, by default, the resulting heatmap will have N partitions along the y axis and M partitions along the x axis. In other words, the i-th row/ j-th column cell in `z` is mapped to the i-th partition of the y axis (starting from the bottom of the plot) and the j-th partition of the x-axis (starting from the left of the plot). This behavior can be flipped by using `transpose`. Moreover, `x` (`y`) can be provided with M or M+1 (N or N+1) elements. If M (N), then the coordinates correspond to the center of the heatmap cells and the cells have equal width. If M+1 (N+1), then the coordinates correspond to the edges of the heatmap cells. In the case where `z` is a 1D list, the x and y coordinates must be provided in `x` and `y` respectively to form data triplets. Parameters ---------- autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.heatmap.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the `z` data are filled in. It is defaulted to true if `z` is a one dimensional array and `zsmooth` is not false; otherwise it is defaulted to false. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dx Sets the x coordinate step. See `x0` for more info. dy Sets the y coordinate step. See `y0` for more info. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.heatmap.Hoverlabel instance or dict with compatible properties hoverongaps Determines whether or not gaps (i.e. {nan} or missing values) in the `z` data have hover labels associated with them. hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. reversescale Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.heatmap.Stream instance or dict with compatible properties text Sets the text elements associated with each z value. textsrc Sets the source reference on plot.ly for text . transpose Transposes the z data. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the x coordinates. x0 Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xcalendar Sets the calendar system to use with `x` date data. xgap Sets the horizontal gap (in pixels) between bricks. xsrc Sets the source reference on plot.ly for x . xtype If "array", the heatmap's x coordinates are given by "x" (the default behavior when `x` is provided). If "scaled", the heatmap's x coordinates are given by "x0" and "dx" (the default behavior when `x` is not provided). y Sets the y coordinates. y0 Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ycalendar Sets the calendar system to use with `y` date data. ygap Sets the vertical gap (in pixels) between bricks. ysrc Sets the source reference on plot.ly for y . ytype If "array", the heatmap's y coordinates are given by "y" (the default behavior when `y` is provided) If "scaled", the heatmap's y coordinates are given by "y0" and "dy" (the default behavior when `y` is not provided) z Sets the z data. zauto Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. zhoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. See: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format zmax Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. zmid Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. zmin Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. zsmooth Picks a smoothing algorithm use to smooth `z` data. zsrc Sets the source reference on plot.ly for z . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` secondary_y: boolean or None (default None) If True, associate this trace with the secondary y-axis of the subplot at the specified row and col. Only valid if all of the following conditions are satisfied: * The figure was created using `plotly.subplots.make_subplots`. * The row and col arguments are not None * The subplot at the specified row and col has type xy (which is the default) and secondary_y True. These properties are specified in the specs argument to make_subplots. See the make_subplots docstring for more info. Returns ------- FigureWidget """ new_trace = Heatmap( autocolorscale=autocolorscale, coloraxis=coloraxis, colorbar=colorbar, colorscale=colorscale, connectgaps=connectgaps, customdata=customdata, customdatasrc=customdatasrc, dx=dx, dy=dy, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hoverongaps=hoverongaps, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, meta=meta, metasrc=metasrc, name=name, opacity=opacity, reversescale=reversescale, showscale=showscale, stream=stream, text=text, textsrc=textsrc, transpose=transpose, uid=uid, uirevision=uirevision, visible=visible, x=x, x0=x0, xaxis=xaxis, xcalendar=xcalendar, xgap=xgap, xsrc=xsrc, xtype=xtype, y=y, y0=y0, yaxis=yaxis, ycalendar=ycalendar, ygap=ygap, ysrc=ysrc, ytype=ytype, z=z, zauto=zauto, zhoverformat=zhoverformat, zmax=zmax, zmid=zmid, zmin=zmin, zsmooth=zsmooth, zsrc=zsrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) def add_heatmapgl( self, autocolorscale=None, coloraxis=None, colorbar=None, colorscale=None, customdata=None, customdatasrc=None, dx=None, dy=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, ids=None, idssrc=None, meta=None, metasrc=None, name=None, opacity=None, reversescale=None, showscale=None, stream=None, text=None, textsrc=None, transpose=None, uid=None, uirevision=None, visible=None, x=None, x0=None, xaxis=None, xsrc=None, xtype=None, y=None, y0=None, yaxis=None, ysrc=None, ytype=None, z=None, zauto=None, zmax=None, zmid=None, zmin=None, zsrc=None, row=None, col=None, secondary_y=None, **kwargs ): """ Add a new Heatmapgl trace WebGL version of the heatmap trace type. Parameters ---------- autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.heatmapgl.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dx Sets the x coordinate step. See `x0` for more info. dy Sets the y coordinate step. See `y0` for more info. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.heatmapgl.Hoverlabel instance or dict with compatible properties ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. reversescale Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.heatmapgl.Stream instance or dict with compatible properties text Sets the text elements associated with each z value. textsrc Sets the source reference on plot.ly for text . transpose Transposes the z data. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the x coordinates. x0 Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xsrc Sets the source reference on plot.ly for x . xtype If "array", the heatmap's x coordinates are given by "x" (the default behavior when `x` is provided). If "scaled", the heatmap's x coordinates are given by "x0" and "dx" (the default behavior when `x` is not provided). y Sets the y coordinates. y0 Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ysrc Sets the source reference on plot.ly for y . ytype If "array", the heatmap's y coordinates are given by "y" (the default behavior when `y` is provided) If "scaled", the heatmap's y coordinates are given by "y0" and "dy" (the default behavior when `y` is not provided) z Sets the z data. zauto Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. zmax Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. zmid Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. zmin Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. zsrc Sets the source reference on plot.ly for z . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` secondary_y: boolean or None (default None) If True, associate this trace with the secondary y-axis of the subplot at the specified row and col. Only valid if all of the following conditions are satisfied: * The figure was created using `plotly.subplots.make_subplots`. * The row and col arguments are not None * The subplot at the specified row and col has type xy (which is the default) and secondary_y True. These properties are specified in the specs argument to make_subplots. See the make_subplots docstring for more info. Returns ------- FigureWidget """ new_trace = Heatmapgl( autocolorscale=autocolorscale, coloraxis=coloraxis, colorbar=colorbar, colorscale=colorscale, customdata=customdata, customdatasrc=customdatasrc, dx=dx, dy=dy, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, ids=ids, idssrc=idssrc, meta=meta, metasrc=metasrc, name=name, opacity=opacity, reversescale=reversescale, showscale=showscale, stream=stream, text=text, textsrc=textsrc, transpose=transpose, uid=uid, uirevision=uirevision, visible=visible, x=x, x0=x0, xaxis=xaxis, xsrc=xsrc, xtype=xtype, y=y, y0=y0, yaxis=yaxis, ysrc=ysrc, ytype=ytype, z=z, zauto=zauto, zmax=zmax, zmid=zmid, zmin=zmin, zsrc=zsrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) def add_histogram( self, alignmentgroup=None, autobinx=None, autobiny=None, bingroup=None, cumulative=None, customdata=None, customdatasrc=None, error_x=None, error_y=None, histfunc=None, histnorm=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, legendgroup=None, marker=None, meta=None, metasrc=None, name=None, nbinsx=None, nbinsy=None, offsetgroup=None, opacity=None, orientation=None, selected=None, selectedpoints=None, showlegend=None, stream=None, text=None, textsrc=None, uid=None, uirevision=None, unselected=None, visible=None, x=None, xaxis=None, xbins=None, xcalendar=None, xsrc=None, y=None, yaxis=None, ybins=None, ycalendar=None, ysrc=None, row=None, col=None, secondary_y=None, **kwargs ): """ Add a new Histogram trace The sample data from which statistics are computed is set in `x` for vertically spanning histograms and in `y` for horizontally spanning histograms. Binning options are set `xbins` and `ybins` respectively if no aggregation data is provided. Parameters ---------- alignmentgroup Set several traces linked to the same position axis or matching axes to the same alignmentgroup. This controls whether bars compute their positional range dependently or independently. autobinx Obsolete: since v1.42 each bin attribute is auto- determined separately and `autobinx` is not needed. However, we accept `autobinx: true` or `false` and will update `xbins` accordingly before deleting `autobinx` from the trace. autobiny Obsolete: since v1.42 each bin attribute is auto- determined separately and `autobiny` is not needed. However, we accept `autobiny: true` or `false` and will update `ybins` accordingly before deleting `autobiny` from the trace. bingroup Set a group of histogram traces which will have compatible bin settings. Note that traces on the same subplot and with the same "orientation" under `barmode` "stack", "relative" and "group" are forced into the same bingroup, Using `bingroup`, traces under `barmode` "overlay" and on different axes (of the same axis type) can have compatible bin settings. Note that histogram and histogram2d* trace can share the same `bingroup` cumulative plotly.graph_objects.histogram.Cumulative instance or dict with compatible properties customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . error_x plotly.graph_objects.histogram.ErrorX instance or dict with compatible properties error_y plotly.graph_objects.histogram.ErrorY instance or dict with compatible properties histfunc Specifies the binning function used for this histogram trace. If "count", the histogram values are computed by counting the number of values lying inside each bin. If "sum", "avg", "min", "max", the histogram values are computed using the sum, the average, the minimum or the maximum of the values lying inside each bin respectively. histnorm Specifies the type of normalization used for this histogram trace. If "", the span of each bar corresponds to the number of occurrences (i.e. the number of data points lying inside the bins). If "percent" / "probability", the span of each bar corresponds to the percentage / fraction of occurrences with respect to the total number of sample points (here, the sum of all bin HEIGHTS equals 100% / 1). If "density", the span of each bar corresponds to the number of occurrences in a bin divided by the size of the bin interval (here, the sum of all bin AREAS equals the total number of sample points). If *probability density*, the area of each bar corresponds to the probability that an event will fall into the corresponding bin (here, the sum of all bin AREAS equals 1). hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.histogram.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variable `binNumber` Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. marker plotly.graph_objects.histogram.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. nbinsx Specifies the maximum number of desired bins. This value will be used in an algorithm that will decide the optimal bin size such that the histogram best visualizes the distribution of the data. Ignored if `xbins.size` is provided. nbinsy Specifies the maximum number of desired bins. This value will be used in an algorithm that will decide the optimal bin size such that the histogram best visualizes the distribution of the data. Ignored if `ybins.size` is provided. offsetgroup Set several traces linked to the same position axis or matching axes to the same offsetgroup where bars of the same position coordinate will line up. opacity Sets the opacity of the trace. orientation Sets the orientation of the bars. With "v" ("h"), the value of the each bar spans along the vertical (horizontal). selected plotly.graph_objects.histogram.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.histogram.Stream instance or dict with compatible properties text Sets hover text elements associated with each bar. If a single string, the same string appears over all bars. If an array of string, the items are mapped in order to the this trace's coordinates. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.histogram.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the sample data to be binned on the x axis. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xbins plotly.graph_objects.histogram.XBins instance or dict with compatible properties xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . y Sets the sample data to be binned on the y axis. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ybins plotly.graph_objects.histogram.YBins instance or dict with compatible properties ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` secondary_y: boolean or None (default None) If True, associate this trace with the secondary y-axis of the subplot at the specified row and col. Only valid if all of the following conditions are satisfied: * The figure was created using `plotly.subplots.make_subplots`. * The row and col arguments are not None * The subplot at the specified row and col has type xy (which is the default) and secondary_y True. These properties are specified in the specs argument to make_subplots. See the make_subplots docstring for more info. Returns ------- FigureWidget """ new_trace = Histogram( alignmentgroup=alignmentgroup, autobinx=autobinx, autobiny=autobiny, bingroup=bingroup, cumulative=cumulative, customdata=customdata, customdatasrc=customdatasrc, error_x=error_x, error_y=error_y, histfunc=histfunc, histnorm=histnorm, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, legendgroup=legendgroup, marker=marker, meta=meta, metasrc=metasrc, name=name, nbinsx=nbinsx, nbinsy=nbinsy, offsetgroup=offsetgroup, opacity=opacity, orientation=orientation, selected=selected, selectedpoints=selectedpoints, showlegend=showlegend, stream=stream, text=text, textsrc=textsrc, uid=uid, uirevision=uirevision, unselected=unselected, visible=visible, x=x, xaxis=xaxis, xbins=xbins, xcalendar=xcalendar, xsrc=xsrc, y=y, yaxis=yaxis, ybins=ybins, ycalendar=ycalendar, ysrc=ysrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) def add_histogram2d( self, autobinx=None, autobiny=None, autocolorscale=None, bingroup=None, coloraxis=None, colorbar=None, colorscale=None, customdata=None, customdatasrc=None, histfunc=None, histnorm=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, ids=None, idssrc=None, marker=None, meta=None, metasrc=None, name=None, nbinsx=None, nbinsy=None, opacity=None, reversescale=None, showscale=None, stream=None, uid=None, uirevision=None, visible=None, x=None, xaxis=None, xbingroup=None, xbins=None, xcalendar=None, xgap=None, xsrc=None, y=None, yaxis=None, ybingroup=None, ybins=None, ycalendar=None, ygap=None, ysrc=None, z=None, zauto=None, zhoverformat=None, zmax=None, zmid=None, zmin=None, zsmooth=None, zsrc=None, row=None, col=None, secondary_y=None, **kwargs ): """ Add a new Histogram2d trace The sample data from which statistics are computed is set in `x` and `y` (where `x` and `y` represent marginal distributions, binning is set in `xbins` and `ybins` in this case) or `z` (where `z` represent the 2D distribution and binning set, binning is set by `x` and `y` in this case). The resulting distribution is visualized as a heatmap. Parameters ---------- autobinx Obsolete: since v1.42 each bin attribute is auto- determined separately and `autobinx` is not needed. However, we accept `autobinx: true` or `false` and will update `xbins` accordingly before deleting `autobinx` from the trace. autobiny Obsolete: since v1.42 each bin attribute is auto- determined separately and `autobiny` is not needed. However, we accept `autobiny: true` or `false` and will update `ybins` accordingly before deleting `autobiny` from the trace. autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. bingroup Set the `xbingroup` and `ybingroup` default prefix For example, setting a `bingroup` of 1 on two histogram2d traces will make them their x-bins and y-bins match separately. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.histogram2d.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . histfunc Specifies the binning function used for this histogram trace. If "count", the histogram values are computed by counting the number of values lying inside each bin. If "sum", "avg", "min", "max", the histogram values are computed using the sum, the average, the minimum or the maximum of the values lying inside each bin respectively. histnorm Specifies the type of normalization used for this histogram trace. If "", the span of each bar corresponds to the number of occurrences (i.e. the number of data points lying inside the bins). If "percent" / "probability", the span of each bar corresponds to the percentage / fraction of occurrences with respect to the total number of sample points (here, the sum of all bin HEIGHTS equals 100% / 1). If "density", the span of each bar corresponds to the number of occurrences in a bin divided by the size of the bin interval (here, the sum of all bin AREAS equals the total number of sample points). If *probability density*, the area of each bar corresponds to the probability that an event will fall into the corresponding bin (here, the sum of all bin AREAS equals 1). hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.histogram2d.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variable `z` Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . marker plotly.graph_objects.histogram2d.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. nbinsx Specifies the maximum number of desired bins. This value will be used in an algorithm that will decide the optimal bin size such that the histogram best visualizes the distribution of the data. Ignored if `xbins.size` is provided. nbinsy Specifies the maximum number of desired bins. This value will be used in an algorithm that will decide the optimal bin size such that the histogram best visualizes the distribution of the data. Ignored if `ybins.size` is provided. opacity Sets the opacity of the trace. reversescale Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.histogram2d.Stream instance or dict with compatible properties uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the sample data to be binned on the x axis. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xbingroup Set a group of histogram traces which will have compatible x-bin settings. Using `xbingroup`, histogram2d and histogram2dcontour traces (on axes of the same axis type) can have compatible x-bin settings. Note that the same `xbingroup` value can be used to set (1D) histogram `bingroup` xbins plotly.graph_objects.histogram2d.XBins instance or dict with compatible properties xcalendar Sets the calendar system to use with `x` date data. xgap Sets the horizontal gap (in pixels) between bricks. xsrc Sets the source reference on plot.ly for x . y Sets the sample data to be binned on the y axis. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ybingroup Set a group of histogram traces which will have compatible y-bin settings. Using `ybingroup`, histogram2d and histogram2dcontour traces (on axes of the same axis type) can have compatible y-bin settings. Note that the same `ybingroup` value can be used to set (1D) histogram `bingroup` ybins plotly.graph_objects.histogram2d.YBins instance or dict with compatible properties ycalendar Sets the calendar system to use with `y` date data. ygap Sets the vertical gap (in pixels) between bricks. ysrc Sets the source reference on plot.ly for y . z Sets the aggregation data. zauto Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. zhoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. See: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format zmax Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. zmid Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. zmin Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. zsmooth Picks a smoothing algorithm use to smooth `z` data. zsrc Sets the source reference on plot.ly for z . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` secondary_y: boolean or None (default None) If True, associate this trace with the secondary y-axis of the subplot at the specified row and col. Only valid if all of the following conditions are satisfied: * The figure was created using `plotly.subplots.make_subplots`. * The row and col arguments are not None * The subplot at the specified row and col has type xy (which is the default) and secondary_y True. These properties are specified in the specs argument to make_subplots. See the make_subplots docstring for more info. Returns ------- FigureWidget """ new_trace = Histogram2d( autobinx=autobinx, autobiny=autobiny, autocolorscale=autocolorscale, bingroup=bingroup, coloraxis=coloraxis, colorbar=colorbar, colorscale=colorscale, customdata=customdata, customdatasrc=customdatasrc, histfunc=histfunc, histnorm=histnorm, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, ids=ids, idssrc=idssrc, marker=marker, meta=meta, metasrc=metasrc, name=name, nbinsx=nbinsx, nbinsy=nbinsy, opacity=opacity, reversescale=reversescale, showscale=showscale, stream=stream, uid=uid, uirevision=uirevision, visible=visible, x=x, xaxis=xaxis, xbingroup=xbingroup, xbins=xbins, xcalendar=xcalendar, xgap=xgap, xsrc=xsrc, y=y, yaxis=yaxis, ybingroup=ybingroup, ybins=ybins, ycalendar=ycalendar, ygap=ygap, ysrc=ysrc, z=z, zauto=zauto, zhoverformat=zhoverformat, zmax=zmax, zmid=zmid, zmin=zmin, zsmooth=zsmooth, zsrc=zsrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) def add_histogram2dcontour( self, autobinx=None, autobiny=None, autocolorscale=None, autocontour=None, bingroup=None, coloraxis=None, colorbar=None, colorscale=None, contours=None, customdata=None, customdatasrc=None, histfunc=None, histnorm=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, ids=None, idssrc=None, legendgroup=None, line=None, marker=None, meta=None, metasrc=None, name=None, nbinsx=None, nbinsy=None, ncontours=None, opacity=None, reversescale=None, showlegend=None, showscale=None, stream=None, uid=None, uirevision=None, visible=None, x=None, xaxis=None, xbingroup=None, xbins=None, xcalendar=None, xsrc=None, y=None, yaxis=None, ybingroup=None, ybins=None, ycalendar=None, ysrc=None, z=None, zauto=None, zhoverformat=None, zmax=None, zmid=None, zmin=None, zsrc=None, row=None, col=None, secondary_y=None, **kwargs ): """ Add a new Histogram2dContour trace The sample data from which statistics are computed is set in `x` and `y` (where `x` and `y` represent marginal distributions, binning is set in `xbins` and `ybins` in this case) or `z` (where `z` represent the 2D distribution and binning set, binning is set by `x` and `y` in this case). The resulting distribution is visualized as a contour plot. Parameters ---------- autobinx Obsolete: since v1.42 each bin attribute is auto- determined separately and `autobinx` is not needed. However, we accept `autobinx: true` or `false` and will update `xbins` accordingly before deleting `autobinx` from the trace. autobiny Obsolete: since v1.42 each bin attribute is auto- determined separately and `autobiny` is not needed. However, we accept `autobiny: true` or `false` and will update `ybins` accordingly before deleting `autobiny` from the trace. autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. autocontour Determines whether or not the contour level attributes are picked by an algorithm. If True, the number of contour levels can be set in `ncontours`. If False, set the contour level attributes in `contours`. bingroup Set the `xbingroup` and `ybingroup` default prefix For example, setting a `bingroup` of 1 on two histogram2d traces will make them their x-bins and y-bins match separately. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.histogram2dcontour.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. contours plotly.graph_objects.histogram2dcontour.Contours instance or dict with compatible properties customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . histfunc Specifies the binning function used for this histogram trace. If "count", the histogram values are computed by counting the number of values lying inside each bin. If "sum", "avg", "min", "max", the histogram values are computed using the sum, the average, the minimum or the maximum of the values lying inside each bin respectively. histnorm Specifies the type of normalization used for this histogram trace. If "", the span of each bar corresponds to the number of occurrences (i.e. the number of data points lying inside the bins). If "percent" / "probability", the span of each bar corresponds to the percentage / fraction of occurrences with respect to the total number of sample points (here, the sum of all bin HEIGHTS equals 100% / 1). If "density", the span of each bar corresponds to the number of occurrences in a bin divided by the size of the bin interval (here, the sum of all bin AREAS equals the total number of sample points). If *probability density*, the area of each bar corresponds to the probability that an event will fall into the corresponding bin (here, the sum of all bin AREAS equals 1). hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.histogram2dcontour.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variable `z` Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.histogram2dcontour.Line instance or dict with compatible properties marker plotly.graph_objects.histogram2dcontour.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. nbinsx Specifies the maximum number of desired bins. This value will be used in an algorithm that will decide the optimal bin size such that the histogram best visualizes the distribution of the data. Ignored if `xbins.size` is provided. nbinsy Specifies the maximum number of desired bins. This value will be used in an algorithm that will decide the optimal bin size such that the histogram best visualizes the distribution of the data. Ignored if `ybins.size` is provided. ncontours Sets the maximum number of contour levels. The actual number of contours will be chosen automatically to be less than or equal to the value of `ncontours`. Has an effect only if `autocontour` is True or if `contours.size` is missing. opacity Sets the opacity of the trace. reversescale Reverses the color mapping if true. If true, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.histogram2dcontour.Stream instance or dict with compatible properties uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the sample data to be binned on the x axis. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xbingroup Set a group of histogram traces which will have compatible x-bin settings. Using `xbingroup`, histogram2d and histogram2dcontour traces (on axes of the same axis type) can have compatible x-bin settings. Note that the same `xbingroup` value can be used to set (1D) histogram `bingroup` xbins plotly.graph_objects.histogram2dcontour.XBins instance or dict with compatible properties xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . y Sets the sample data to be binned on the y axis. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ybingroup Set a group of histogram traces which will have compatible y-bin settings. Using `ybingroup`, histogram2d and histogram2dcontour traces (on axes of the same axis type) can have compatible y-bin settings. Note that the same `ybingroup` value can be used to set (1D) histogram `bingroup` ybins plotly.graph_objects.histogram2dcontour.YBins instance or dict with compatible properties ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . z Sets the aggregation data. zauto Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` are set by the user. zhoverformat Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. See: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format zmax Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well. zmid Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `false`. zmin Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well. zsrc Sets the source reference on plot.ly for z . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` secondary_y: boolean or None (default None) If True, associate this trace with the secondary y-axis of the subplot at the specified row and col. Only valid if all of the following conditions are satisfied: * The figure was created using `plotly.subplots.make_subplots`. * The row and col arguments are not None * The subplot at the specified row and col has type xy (which is the default) and secondary_y True. These properties are specified in the specs argument to make_subplots. See the make_subplots docstring for more info. Returns ------- FigureWidget """ new_trace = Histogram2dContour( autobinx=autobinx, autobiny=autobiny, autocolorscale=autocolorscale, autocontour=autocontour, bingroup=bingroup, coloraxis=coloraxis, colorbar=colorbar, colorscale=colorscale, contours=contours, customdata=customdata, customdatasrc=customdatasrc, histfunc=histfunc, histnorm=histnorm, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, ids=ids, idssrc=idssrc, legendgroup=legendgroup, line=line, marker=marker, meta=meta, metasrc=metasrc, name=name, nbinsx=nbinsx, nbinsy=nbinsy, ncontours=ncontours, opacity=opacity, reversescale=reversescale, showlegend=showlegend, showscale=showscale, stream=stream, uid=uid, uirevision=uirevision, visible=visible, x=x, xaxis=xaxis, xbingroup=xbingroup, xbins=xbins, xcalendar=xcalendar, xsrc=xsrc, y=y, yaxis=yaxis, ybingroup=ybingroup, ybins=ybins, ycalendar=ycalendar, ysrc=ysrc, z=z, zauto=zauto, zhoverformat=zhoverformat, zmax=zmax, zmid=zmid, zmin=zmin, zsrc=zsrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) def add_image( self, colormodel=None, customdata=None, customdatasrc=None, dx=None, dy=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, meta=None, metasrc=None, name=None, opacity=None, stream=None, text=None, textsrc=None, uid=None, uirevision=None, visible=None, x0=None, xaxis=None, y0=None, yaxis=None, z=None, zmax=None, zmin=None, zsrc=None, row=None, col=None, secondary_y=None, **kwargs ): """ Add a new Image trace Display an image, i.e. data on a 2D regular raster. By default, when an image is displayed in a subplot, its y axis will be reversed (ie. `autorange: 'reversed'`), constrained to the domain (ie. `constrain: 'domain'`) and it will have the same scale as its x axis (ie. `scaleanchor: 'x,`) in order for pixels to be rendered as squares. Parameters ---------- colormodel Color model used to map the numerical color components described in `z` into colors. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dx Set the pixel's horizontal size. dy Set the pixel's vertical size hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.image.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `z`, `color` and `colormodel`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. stream plotly.graph_objects.image.Stream instance or dict with compatible properties text Sets the text elements associated with each z value. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x0 Set the image's x position. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. y0 Set the image's y position. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. z A 2-dimensional array in which each element is an array of 3 or 4 numbers representing a color. zmax Array defining the higher bound for each color component. Note that the default value will depend on the colormodel. For the `rgb` colormodel, it is [255, 255, 255]. For the `rgba` colormodel, it is [255, 255, 255, 1]. For the `hsl` colormodel, it is [360, 100, 100]. For the `hsla` colormodel, it is [360, 100, 100, 1]. zmin Array defining the lower bound for each color component. Note that the default value will depend on the colormodel. For the `rgb` colormodel, it is [0, 0, 0]. For the `rgba` colormodel, it is [0, 0, 0, 0]. For the `hsl` colormodel, it is [0, 0, 0]. For the `hsla` colormodel, it is [0, 0, 0, 0]. zsrc Sets the source reference on plot.ly for z . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` secondary_y: boolean or None (default None) If True, associate this trace with the secondary y-axis of the subplot at the specified row and col. Only valid if all of the following conditions are satisfied: * The figure was created using `plotly.subplots.make_subplots`. * The row and col arguments are not None * The subplot at the specified row and col has type xy (which is the default) and secondary_y True. These properties are specified in the specs argument to make_subplots. See the make_subplots docstring for more info. Returns ------- FigureWidget """ new_trace = Image( colormodel=colormodel, customdata=customdata, customdatasrc=customdatasrc, dx=dx, dy=dy, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, meta=meta, metasrc=metasrc, name=name, opacity=opacity, stream=stream, text=text, textsrc=textsrc, uid=uid, uirevision=uirevision, visible=visible, x0=x0, xaxis=xaxis, y0=y0, yaxis=yaxis, z=z, zmax=zmax, zmin=zmin, zsrc=zsrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) def add_indicator( self, align=None, customdata=None, customdatasrc=None, delta=None, domain=None, gauge=None, ids=None, idssrc=None, meta=None, metasrc=None, mode=None, name=None, number=None, stream=None, title=None, uid=None, uirevision=None, value=None, visible=None, row=None, col=None, **kwargs ): """ Add a new Indicator trace An indicator is used to visualize a single `value` along with some contextual information such as `steps` or a `threshold`, using a combination of three visual elements: a number, a delta, and/or a gauge. Deltas are taken with respect to a `reference`. Gauges can be either angular or bullet (aka linear) gauges. Parameters ---------- align Sets the horizontal alignment of the `text` within the box. Note that this attribute has no effect if an angular gauge is displayed: in this case, it is always centered customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . delta plotly.graph_objects.indicator.Delta instance or dict with compatible properties domain plotly.graph_objects.indicator.Domain instance or dict with compatible properties gauge The gauge of the Indicator plot. ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . mode Determines how the value is displayed on the graph. `number` displays the value numerically in text. `delta` displays the difference to a reference value in text. Finally, `gauge` displays the value graphically on an axis. name Sets the trace name. The trace name appear as the legend item and on hover. number plotly.graph_objects.indicator.Number instance or dict with compatible properties stream plotly.graph_objects.indicator.Stream instance or dict with compatible properties title plotly.graph_objects.indicator.Title instance or dict with compatible properties uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. value Sets the number to be displayed. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- FigureWidget """ new_trace = Indicator( align=align, customdata=customdata, customdatasrc=customdatasrc, delta=delta, domain=domain, gauge=gauge, ids=ids, idssrc=idssrc, meta=meta, metasrc=metasrc, mode=mode, name=name, number=number, stream=stream, title=title, uid=uid, uirevision=uirevision, value=value, visible=visible, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_isosurface( self, autocolorscale=None, caps=None, cauto=None, cmax=None, cmid=None, cmin=None, coloraxis=None, colorbar=None, colorscale=None, contour=None, customdata=None, customdatasrc=None, flatshading=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, isomax=None, isomin=None, lighting=None, lightposition=None, meta=None, metasrc=None, name=None, opacity=None, reversescale=None, scene=None, showscale=None, slices=None, spaceframe=None, stream=None, surface=None, text=None, textsrc=None, uid=None, uirevision=None, value=None, valuesrc=None, visible=None, x=None, xsrc=None, y=None, ysrc=None, z=None, zsrc=None, row=None, col=None, **kwargs ): """ Add a new Isosurface trace Draws isosurfaces between iso-min and iso-max values with coordinates given by four 1-dimensional arrays containing the `value`, `x`, `y` and `z` of every vertex of a uniform or non- uniform 3-D grid. Horizontal or vertical slices, caps as well as spaceframe between iso-min and iso-max values could also be drawn using this trace. Parameters ---------- autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. caps plotly.graph_objects.isosurface.Caps instance or dict with compatible properties cauto Determines whether or not the color domain is computed with respect to the input data (here `value`) or the bounds set in `cmin` and `cmax` Defaults to `false` when `cmin` and `cmax` are set by the user. cmax Sets the upper bound of the color domain. Value should have the same units as `value` and if set, `cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `cmin` and/or `cmax` to be equidistant to this point. Value should have the same units as `value`. Has no effect when `cauto` is `false`. cmin Sets the lower bound of the color domain. Value should have the same units as `value` and if set, `cmax` must be set as well. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.isosurface.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`cmin` and `cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. contour plotly.graph_objects.isosurface.Contour instance or dict with compatible properties customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . flatshading Determines whether or not normal smoothing is applied to the meshes, creating meshes with an angular, low- poly look via flat reflections. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.isosurface.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . isomax Sets the maximum boundary for iso-surface plot. isomin Sets the minimum boundary for iso-surface plot. lighting plotly.graph_objects.isosurface.Lighting instance or dict with compatible properties lightposition plotly.graph_objects.isosurface.Lightposition instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the surface. Please note that in the case of using high `opacity` values for example a value greater than or equal to 0.5 on two surfaces (and 0.25 with four surfaces), an overlay of multiple transparent surfaces may not perfectly be sorted in depth by the webgl API. This behavior may be improved in the near future and is subject to change. reversescale Reverses the color mapping if true. If true, `cmin` will correspond to the last color in the array and `cmax` will correspond to the first color. scene Sets a reference between this trace's 3D coordinate system and a 3D scene. If "scene" (the default value), the (x,y,z) coordinates refer to `layout.scene`. If "scene2", the (x,y,z) coordinates refer to `layout.scene2`, and so on. showscale Determines whether or not a colorbar is displayed for this trace. slices plotly.graph_objects.isosurface.Slices instance or dict with compatible properties spaceframe plotly.graph_objects.isosurface.Spaceframe instance or dict with compatible properties stream plotly.graph_objects.isosurface.Stream instance or dict with compatible properties surface plotly.graph_objects.isosurface.Surface instance or dict with compatible properties text Sets the text elements associated with the vertices. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. value Sets the 4th dimension (value) of the vertices. valuesrc Sets the source reference on plot.ly for value . visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the X coordinates of the vertices on X axis. xsrc Sets the source reference on plot.ly for x . y Sets the Y coordinates of the vertices on Y axis. ysrc Sets the source reference on plot.ly for y . z Sets the Z coordinates of the vertices on Z axis. zsrc Sets the source reference on plot.ly for z . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- FigureWidget """ new_trace = Isosurface( autocolorscale=autocolorscale, caps=caps, cauto=cauto, cmax=cmax, cmid=cmid, cmin=cmin, coloraxis=coloraxis, colorbar=colorbar, colorscale=colorscale, contour=contour, customdata=customdata, customdatasrc=customdatasrc, flatshading=flatshading, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, isomax=isomax, isomin=isomin, lighting=lighting, lightposition=lightposition, meta=meta, metasrc=metasrc, name=name, opacity=opacity, reversescale=reversescale, scene=scene, showscale=showscale, slices=slices, spaceframe=spaceframe, stream=stream, surface=surface, text=text, textsrc=textsrc, uid=uid, uirevision=uirevision, value=value, valuesrc=valuesrc, visible=visible, x=x, xsrc=xsrc, y=y, ysrc=ysrc, z=z, zsrc=zsrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_mesh3d( self, alphahull=None, autocolorscale=None, cauto=None, cmax=None, cmid=None, cmin=None, color=None, coloraxis=None, colorbar=None, colorscale=None, contour=None, customdata=None, customdatasrc=None, delaunayaxis=None, facecolor=None, facecolorsrc=None, flatshading=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, i=None, ids=None, idssrc=None, intensity=None, intensitysrc=None, isrc=None, j=None, jsrc=None, k=None, ksrc=None, lighting=None, lightposition=None, meta=None, metasrc=None, name=None, opacity=None, reversescale=None, scene=None, showscale=None, stream=None, text=None, textsrc=None, uid=None, uirevision=None, vertexcolor=None, vertexcolorsrc=None, visible=None, x=None, xcalendar=None, xsrc=None, y=None, ycalendar=None, ysrc=None, z=None, zcalendar=None, zsrc=None, row=None, col=None, **kwargs ): """ Add a new Mesh3d trace Draws sets of triangles with coordinates given by three 1-dimensional arrays in `x`, `y`, `z` and (1) a sets of `i`, `j`, `k` indices (2) Delaunay triangulation or (3) the Alpha- shape algorithm or (4) the Convex-hull algorithm Parameters ---------- alphahull Determines how the mesh surface triangles are derived from the set of vertices (points) represented by the `x`, `y` and `z` arrays, if the `i`, `j`, `k` arrays are not supplied. For general use of `mesh3d` it is preferred that `i`, `j`, `k` are supplied. If "-1", Delaunay triangulation is used, which is mainly suitable if the mesh is a single, more or less layer surface that is perpendicular to `delaunayaxis`. In case the `delaunayaxis` intersects the mesh surface at more than one point it will result triangles that are very long in the dimension of `delaunayaxis`. If ">0", the alpha-shape algorithm is used. In this case, the positive `alphahull` value signals the use of the alpha-shape algorithm, _and_ its value acts as the parameter for the mesh fitting. If 0, the convex-hull algorithm is used. It is suitable for convex bodies or if the intention is to enclose the `x`, `y` and `z` point set into a convex hull. autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here `intensity`) or the bounds set in `cmin` and `cmax` Defaults to `false` when `cmin` and `cmax` are set by the user. cmax Sets the upper bound of the color domain. Value should have the same units as `intensity` and if set, `cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `cmin` and/or `cmax` to be equidistant to this point. Value should have the same units as `intensity`. Has no effect when `cauto` is `false`. cmin Sets the lower bound of the color domain. Value should have the same units as `intensity` and if set, `cmax` must be set as well. color Sets the color of the whole mesh coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.mesh3d.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`cmin` and `cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. contour plotly.graph_objects.mesh3d.Contour instance or dict with compatible properties customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . delaunayaxis Sets the Delaunay axis, which is the axis that is perpendicular to the surface of the Delaunay triangulation. It has an effect if `i`, `j`, `k` are not provided and `alphahull` is set to indicate Delaunay triangulation. facecolor Sets the color of each face Overrides "color" and "vertexcolor". facecolorsrc Sets the source reference on plot.ly for facecolor . flatshading Determines whether or not normal smoothing is applied to the meshes, creating meshes with an angular, low- poly look via flat reflections. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.mesh3d.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . i A vector of vertex indices, i.e. integer values between 0 and the length of the vertex vectors, representing the "first" vertex of a triangle. For example, `{i[m], j[m], k[m]}` together represent face m (triangle m) in the mesh, where `i[m] = n` points to the triplet `{x[n], y[n], z[n]}` in the vertex arrays. Therefore, each element in `i` represents a point in space, which is the first vertex of a triangle. ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . intensity Sets the vertex intensity values, used for plotting fields on meshes intensitysrc Sets the source reference on plot.ly for intensity . isrc Sets the source reference on plot.ly for i . j A vector of vertex indices, i.e. integer values between 0 and the length of the vertex vectors, representing the "second" vertex of a triangle. For example, `{i[m], j[m], k[m]}` together represent face m (triangle m) in the mesh, where `j[m] = n` points to the triplet `{x[n], y[n], z[n]}` in the vertex arrays. Therefore, each element in `j` represents a point in space, which is the second vertex of a triangle. jsrc Sets the source reference on plot.ly for j . k A vector of vertex indices, i.e. integer values between 0 and the length of the vertex vectors, representing the "third" vertex of a triangle. For example, `{i[m], j[m], k[m]}` together represent face m (triangle m) in the mesh, where `k[m] = n` points to the triplet `{x[n], y[n], z[n]}` in the vertex arrays. Therefore, each element in `k` represents a point in space, which is the third vertex of a triangle. ksrc Sets the source reference on plot.ly for k . lighting plotly.graph_objects.mesh3d.Lighting instance or dict with compatible properties lightposition plotly.graph_objects.mesh3d.Lightposition instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the surface. Please note that in the case of using high `opacity` values for example a value greater than or equal to 0.5 on two surfaces (and 0.25 with four surfaces), an overlay of multiple transparent surfaces may not perfectly be sorted in depth by the webgl API. This behavior may be improved in the near future and is subject to change. reversescale Reverses the color mapping if true. If true, `cmin` will correspond to the last color in the array and `cmax` will correspond to the first color. scene Sets a reference between this trace's 3D coordinate system and a 3D scene. If "scene" (the default value), the (x,y,z) coordinates refer to `layout.scene`. If "scene2", the (x,y,z) coordinates refer to `layout.scene2`, and so on. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.mesh3d.Stream instance or dict with compatible properties text Sets the text elements associated with the vertices. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. vertexcolor Sets the color of each vertex Overrides "color". While Red, green and blue colors are in the range of 0 and 255; in the case of having vertex color data in RGBA format, the alpha color should be normalized to be between 0 and 1. vertexcolorsrc Sets the source reference on plot.ly for vertexcolor . visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the X coordinates of the vertices. The nth element of vectors `x`, `y` and `z` jointly represent the X, Y and Z coordinates of the nth vertex. xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . y Sets the Y coordinates of the vertices. The nth element of vectors `x`, `y` and `z` jointly represent the X, Y and Z coordinates of the nth vertex. ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . z Sets the Z coordinates of the vertices. The nth element of vectors `x`, `y` and `z` jointly represent the X, Y and Z coordinates of the nth vertex. zcalendar Sets the calendar system to use with `z` date data. zsrc Sets the source reference on plot.ly for z . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- FigureWidget """ new_trace = Mesh3d( alphahull=alphahull, autocolorscale=autocolorscale, cauto=cauto, cmax=cmax, cmid=cmid, cmin=cmin, color=color, coloraxis=coloraxis, colorbar=colorbar, colorscale=colorscale, contour=contour, customdata=customdata, customdatasrc=customdatasrc, delaunayaxis=delaunayaxis, facecolor=facecolor, facecolorsrc=facecolorsrc, flatshading=flatshading, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, i=i, ids=ids, idssrc=idssrc, intensity=intensity, intensitysrc=intensitysrc, isrc=isrc, j=j, jsrc=jsrc, k=k, ksrc=ksrc, lighting=lighting, lightposition=lightposition, meta=meta, metasrc=metasrc, name=name, opacity=opacity, reversescale=reversescale, scene=scene, showscale=showscale, stream=stream, text=text, textsrc=textsrc, uid=uid, uirevision=uirevision, vertexcolor=vertexcolor, vertexcolorsrc=vertexcolorsrc, visible=visible, x=x, xcalendar=xcalendar, xsrc=xsrc, y=y, ycalendar=ycalendar, ysrc=ysrc, z=z, zcalendar=zcalendar, zsrc=zsrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_ohlc( self, close=None, closesrc=None, customdata=None, customdatasrc=None, decreasing=None, high=None, highsrc=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, increasing=None, legendgroup=None, line=None, low=None, lowsrc=None, meta=None, metasrc=None, name=None, opacity=None, open=None, opensrc=None, selectedpoints=None, showlegend=None, stream=None, text=None, textsrc=None, tickwidth=None, uid=None, uirevision=None, visible=None, x=None, xaxis=None, xcalendar=None, xsrc=None, yaxis=None, row=None, col=None, secondary_y=None, **kwargs ): """ Add a new Ohlc trace The ohlc (short for Open-High-Low-Close) is a style of financial chart describing open, high, low and close for a given `x` coordinate (most likely time). The tip of the lines represent the `low` and `high` values and the horizontal segments represent the `open` and `close` values. Sample points where the close value is higher (lower) then the open value are called increasing (decreasing). By default, increasing items are drawn in green whereas decreasing are drawn in red. Parameters ---------- close Sets the close values. closesrc Sets the source reference on plot.ly for close . customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . decreasing plotly.graph_objects.ohlc.Decreasing instance or dict with compatible properties high Sets the high values. highsrc Sets the source reference on plot.ly for high . hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.ohlc.Hoverlabel instance or dict with compatible properties hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . increasing plotly.graph_objects.ohlc.Increasing instance or dict with compatible properties legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.ohlc.Line instance or dict with compatible properties low Sets the low values. lowsrc Sets the source reference on plot.ly for low . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. open Sets the open values. opensrc Sets the source reference on plot.ly for open . selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.ohlc.Stream instance or dict with compatible properties text Sets hover text elements associated with each sample point. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to this trace's sample points. textsrc Sets the source reference on plot.ly for text . tickwidth Sets the width of the open/close tick marks relative to the "x" minimal interval. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the x coordinates. If absent, linear coordinate will be generated. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` secondary_y: boolean or None (default None) If True, associate this trace with the secondary y-axis of the subplot at the specified row and col. Only valid if all of the following conditions are satisfied: * The figure was created using `plotly.subplots.make_subplots`. * The row and col arguments are not None * The subplot at the specified row and col has type xy (which is the default) and secondary_y True. These properties are specified in the specs argument to make_subplots. See the make_subplots docstring for more info. Returns ------- FigureWidget """ new_trace = Ohlc( close=close, closesrc=closesrc, customdata=customdata, customdatasrc=customdatasrc, decreasing=decreasing, high=high, highsrc=highsrc, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, increasing=increasing, legendgroup=legendgroup, line=line, low=low, lowsrc=lowsrc, meta=meta, metasrc=metasrc, name=name, opacity=opacity, open=open, opensrc=opensrc, selectedpoints=selectedpoints, showlegend=showlegend, stream=stream, text=text, textsrc=textsrc, tickwidth=tickwidth, uid=uid, uirevision=uirevision, visible=visible, x=x, xaxis=xaxis, xcalendar=xcalendar, xsrc=xsrc, yaxis=yaxis, **kwargs ) return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) def add_parcats( self, arrangement=None, bundlecolors=None, counts=None, countssrc=None, dimensions=None, dimensiondefaults=None, domain=None, hoverinfo=None, hoveron=None, hovertemplate=None, labelfont=None, line=None, meta=None, metasrc=None, name=None, sortpaths=None, stream=None, tickfont=None, uid=None, uirevision=None, visible=None, row=None, col=None, **kwargs ): """ Add a new Parcats trace Parallel categories diagram for multidimensional categorical data. Parameters ---------- arrangement Sets the drag interaction mode for categories and dimensions. If `perpendicular`, the categories can only move along a line perpendicular to the paths. If `freeform`, the categories can freely move on the plane. If `fixed`, the categories and dimensions are stationary. bundlecolors Sort paths so that like colors are bundled together within each category. counts The number of observations represented by each state. Defaults to 1 so that each state represents one observation countssrc Sets the source reference on plot.ly for counts . dimensions The dimensions (variables) of the parallel categories diagram. dimensiondefaults When used in a template (as layout.template.data.parcats.dimensiondefaults), sets the default property values to use for elements of parcats.dimensions domain plotly.graph_objects.parcats.Domain instance or dict with compatible properties hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoveron Sets the hover interaction mode for the parcats diagram. If `category`, hover interaction take place per category. If `color`, hover interactions take place per color per category. If `dimension`, hover interactions take place across all categories per dimension. hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `count`, `probability`, `category`, `categorycount`, `colorcount` and `bandcolorcount`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. labelfont Sets the font for the `dimension` labels. line plotly.graph_objects.parcats.Line instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. sortpaths Sets the path sorting algorithm. If `forward`, sort paths based on dimension categories from left to right. If `backward`, sort paths based on dimensions categories from right to left. stream plotly.graph_objects.parcats.Stream instance or dict with compatible properties tickfont Sets the font for the `category` labels. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- FigureWidget """ new_trace = Parcats( arrangement=arrangement, bundlecolors=bundlecolors, counts=counts, countssrc=countssrc, dimensions=dimensions, dimensiondefaults=dimensiondefaults, domain=domain, hoverinfo=hoverinfo, hoveron=hoveron, hovertemplate=hovertemplate, labelfont=labelfont, line=line, meta=meta, metasrc=metasrc, name=name, sortpaths=sortpaths, stream=stream, tickfont=tickfont, uid=uid, uirevision=uirevision, visible=visible, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_parcoords( self, customdata=None, customdatasrc=None, dimensions=None, dimensiondefaults=None, domain=None, ids=None, idssrc=None, labelangle=None, labelfont=None, labelside=None, line=None, meta=None, metasrc=None, name=None, rangefont=None, stream=None, tickfont=None, uid=None, uirevision=None, visible=None, row=None, col=None, **kwargs ): """ Add a new Parcoords trace Parallel coordinates for multidimensional exploratory data analysis. The samples are specified in `dimensions`. The colors are set in `line.color`. Parameters ---------- customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dimensions The dimensions (variables) of the parallel coordinates chart. 2..60 dimensions are supported. dimensiondefaults When used in a template (as layout.template.data.parcoords.dimensiondefaults), sets the default property values to use for elements of parcoords.dimensions domain plotly.graph_objects.parcoords.Domain instance or dict with compatible properties ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . labelangle Sets the angle of the labels with respect to the horizontal. For example, a `tickangle` of -90 draws the labels vertically. Tilted labels with "labelangle" may be positioned better inside margins when `labelposition` is set to "bottom". labelfont Sets the font for the `dimension` labels. labelside Specifies the location of the `label`. "top" positions labels above, next to the title "bottom" positions labels below the graph Tilted labels with "labelangle" may be positioned better inside margins when `labelposition` is set to "bottom". line plotly.graph_objects.parcoords.Line instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. rangefont Sets the font for the `dimension` range values. stream plotly.graph_objects.parcoords.Stream instance or dict with compatible properties tickfont Sets the font for the `dimension` tick values. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- FigureWidget """ new_trace = Parcoords( customdata=customdata, customdatasrc=customdatasrc, dimensions=dimensions, dimensiondefaults=dimensiondefaults, domain=domain, ids=ids, idssrc=idssrc, labelangle=labelangle, labelfont=labelfont, labelside=labelside, line=line, meta=meta, metasrc=metasrc, name=name, rangefont=rangefont, stream=stream, tickfont=tickfont, uid=uid, uirevision=uirevision, visible=visible, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_pie( self, automargin=None, customdata=None, customdatasrc=None, direction=None, dlabel=None, domain=None, hole=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, insidetextfont=None, label0=None, labels=None, labelssrc=None, legendgroup=None, marker=None, meta=None, metasrc=None, name=None, opacity=None, outsidetextfont=None, pull=None, pullsrc=None, rotation=None, scalegroup=None, showlegend=None, sort=None, stream=None, text=None, textfont=None, textinfo=None, textposition=None, textpositionsrc=None, textsrc=None, texttemplate=None, texttemplatesrc=None, title=None, titlefont=None, titleposition=None, uid=None, uirevision=None, values=None, valuessrc=None, visible=None, row=None, col=None, **kwargs ): """ Add a new Pie trace A data visualized by the sectors of the pie is set in `values`. The sector labels are set in `labels`. The sector colors are set in `marker.colors` Parameters ---------- automargin Determines whether outside text labels can push the margins. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . direction Specifies the direction at which succeeding sectors follow one another. dlabel Sets the label step. See `label0` for more info. domain plotly.graph_objects.pie.Domain instance or dict with compatible properties hole Sets the fraction of the radius to cut out of the pie. Use this to make a donut chart. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.pie.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `label`, `color`, `value`, `percent` and `text`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each sector. If a single string, the same string appears for all data points. If an array of string, the items are mapped in order of this trace's sectors. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . insidetextfont Sets the font used for `textinfo` lying inside the sector. label0 Alternate to `labels`. Builds a numeric set of labels. Use with `dlabel` where `label0` is the starting label and `dlabel` the step. labels Sets the sector labels. If `labels` entries are duplicated, we sum associated `values` or simply count occurrences if `values` is not provided. For other array attributes (including color) we use the first non-empty entry among all occurrences of the label. labelssrc Sets the source reference on plot.ly for labels . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. marker plotly.graph_objects.pie.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. outsidetextfont Sets the font used for `textinfo` lying outside the sector. pull Sets the fraction of larger radius to pull the sectors out from the center. This can be a constant to pull all slices apart from each other equally or an array to highlight one or more slices. pullsrc Sets the source reference on plot.ly for pull . rotation Instead of the first slice starting at 12 o'clock, rotate to some other angle. scalegroup If there are multiple pie charts that should be sized according to their totals, link them by providing a non-empty group id here shared by every trace in the same group. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. sort Determines whether or not the sectors are reordered from largest to smallest. stream plotly.graph_objects.pie.Stream instance or dict with compatible properties text Sets text elements associated with each sector. If trace `textinfo` contains a "text" flag, these elements will be seen on the chart. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the font used for `textinfo`. textinfo Determines which trace information appear on the graph. textposition Specifies the location of the `textinfo`. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `label`, `color`, `value`, `percent` and `text`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . title plotly.graph_objects.pie.Title instance or dict with compatible properties titlefont Deprecated: Please use pie.title.font instead. Sets the font used for `title`. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleposition Deprecated: Please use pie.title.position instead. Specifies the location of the `title`. Note that the title's position used to be set by the now deprecated `titleposition` attribute. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. values Sets the values of the sectors. If omitted, we count occurrences of each label. valuessrc Sets the source reference on plot.ly for values . visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- FigureWidget """ new_trace = Pie( automargin=automargin, customdata=customdata, customdatasrc=customdatasrc, direction=direction, dlabel=dlabel, domain=domain, hole=hole, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, insidetextfont=insidetextfont, label0=label0, labels=labels, labelssrc=labelssrc, legendgroup=legendgroup, marker=marker, meta=meta, metasrc=metasrc, name=name, opacity=opacity, outsidetextfont=outsidetextfont, pull=pull, pullsrc=pullsrc, rotation=rotation, scalegroup=scalegroup, showlegend=showlegend, sort=sort, stream=stream, text=text, textfont=textfont, textinfo=textinfo, textposition=textposition, textpositionsrc=textpositionsrc, textsrc=textsrc, texttemplate=texttemplate, texttemplatesrc=texttemplatesrc, title=title, titlefont=titlefont, titleposition=titleposition, uid=uid, uirevision=uirevision, values=values, valuessrc=valuessrc, visible=visible, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_pointcloud( self, customdata=None, customdatasrc=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, ids=None, idssrc=None, indices=None, indicessrc=None, legendgroup=None, marker=None, meta=None, metasrc=None, name=None, opacity=None, showlegend=None, stream=None, text=None, textsrc=None, uid=None, uirevision=None, visible=None, x=None, xaxis=None, xbounds=None, xboundssrc=None, xsrc=None, xy=None, xysrc=None, y=None, yaxis=None, ybounds=None, yboundssrc=None, ysrc=None, row=None, col=None, secondary_y=None, **kwargs ): """ Add a new Pointcloud trace The data visualized as a point cloud set in `x` and `y` using the WebGl plotting engine. Parameters ---------- customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.pointcloud.Hoverlabel instance or dict with compatible properties ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . indices A sequential value, 0..n, supply it to avoid creating this array inside plotting. If specified, it must be a typed `Int32Array` array. Its length must be equal to or greater than the number of points. For the best performance and memory use, create one large `indices` typed array that is guaranteed to be at least as long as the largest number of points during use, and reuse it on each `Plotly.restyle()` call. indicessrc Sets the source reference on plot.ly for indices . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. marker plotly.graph_objects.pointcloud.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.pointcloud.Stream instance or dict with compatible properties text Sets text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the x coordinates. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xbounds Specify `xbounds` in the shape of `[xMin, xMax] to avoid looping through the `xy` typed array. Use it in conjunction with `xy` and `ybounds` for the performance benefits. xboundssrc Sets the source reference on plot.ly for xbounds . xsrc Sets the source reference on plot.ly for x . xy Faster alternative to specifying `x` and `y` separately. If supplied, it must be a typed `Float32Array` array that represents points such that `xy[i * 2] = x[i]` and `xy[i * 2 + 1] = y[i]` xysrc Sets the source reference on plot.ly for xy . y Sets the y coordinates. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ybounds Specify `ybounds` in the shape of `[yMin, yMax] to avoid looping through the `xy` typed array. Use it in conjunction with `xy` and `xbounds` for the performance benefits. yboundssrc Sets the source reference on plot.ly for ybounds . ysrc Sets the source reference on plot.ly for y . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` secondary_y: boolean or None (default None) If True, associate this trace with the secondary y-axis of the subplot at the specified row and col. Only valid if all of the following conditions are satisfied: * The figure was created using `plotly.subplots.make_subplots`. * The row and col arguments are not None * The subplot at the specified row and col has type xy (which is the default) and secondary_y True. These properties are specified in the specs argument to make_subplots. See the make_subplots docstring for more info. Returns ------- FigureWidget """ new_trace = Pointcloud( customdata=customdata, customdatasrc=customdatasrc, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, ids=ids, idssrc=idssrc, indices=indices, indicessrc=indicessrc, legendgroup=legendgroup, marker=marker, meta=meta, metasrc=metasrc, name=name, opacity=opacity, showlegend=showlegend, stream=stream, text=text, textsrc=textsrc, uid=uid, uirevision=uirevision, visible=visible, x=x, xaxis=xaxis, xbounds=xbounds, xboundssrc=xboundssrc, xsrc=xsrc, xy=xy, xysrc=xysrc, y=y, yaxis=yaxis, ybounds=ybounds, yboundssrc=yboundssrc, ysrc=ysrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) def add_sankey( self, arrangement=None, customdata=None, customdatasrc=None, domain=None, hoverinfo=None, hoverlabel=None, ids=None, idssrc=None, link=None, meta=None, metasrc=None, name=None, node=None, orientation=None, selectedpoints=None, stream=None, textfont=None, uid=None, uirevision=None, valueformat=None, valuesuffix=None, visible=None, row=None, col=None, **kwargs ): """ Add a new Sankey trace Sankey plots for network flow data analysis. The nodes are specified in `nodes` and the links between sources and targets in `links`. The colors are set in `nodes[i].color` and `links[i].color`, otherwise defaults are used. Parameters ---------- arrangement If value is `snap` (the default), the node arrangement is assisted by automatic snapping of elements to preserve space between nodes specified via `nodepad`. If value is `perpendicular`, the nodes can only move along a line perpendicular to the flow. If value is `freeform`, the nodes can freely move on the plane. If value is `fixed`, the nodes are stationary. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . domain plotly.graph_objects.sankey.Domain instance or dict with compatible properties hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. Note that this attribute is superseded by `node.hoverinfo` and `node.hoverinfo` for nodes and links respectively. hoverlabel plotly.graph_objects.sankey.Hoverlabel instance or dict with compatible properties ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . link The links of the Sankey plot. meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. node The nodes of the Sankey plot. orientation Sets the orientation of the Sankey diagram. selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. stream plotly.graph_objects.sankey.Stream instance or dict with compatible properties textfont Sets the font for node labels uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. valueformat Sets the value formatting rule using d3 formatting mini-language which is similar to those of Python. See https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format valuesuffix Adds a unit to follow the value in the hover tooltip. Add a space if a separation is necessary from the value. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- FigureWidget """ new_trace = Sankey( arrangement=arrangement, customdata=customdata, customdatasrc=customdatasrc, domain=domain, hoverinfo=hoverinfo, hoverlabel=hoverlabel, ids=ids, idssrc=idssrc, link=link, meta=meta, metasrc=metasrc, name=name, node=node, orientation=orientation, selectedpoints=selectedpoints, stream=stream, textfont=textfont, uid=uid, uirevision=uirevision, valueformat=valueformat, valuesuffix=valuesuffix, visible=visible, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_scatter( self, cliponaxis=None, connectgaps=None, customdata=None, customdatasrc=None, dx=None, dy=None, error_x=None, error_y=None, fill=None, fillcolor=None, groupnorm=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hoveron=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, legendgroup=None, line=None, marker=None, meta=None, metasrc=None, mode=None, name=None, opacity=None, orientation=None, r=None, rsrc=None, selected=None, selectedpoints=None, showlegend=None, stackgaps=None, stackgroup=None, stream=None, t=None, text=None, textfont=None, textposition=None, textpositionsrc=None, textsrc=None, texttemplate=None, texttemplatesrc=None, tsrc=None, uid=None, uirevision=None, unselected=None, visible=None, x=None, x0=None, xaxis=None, xcalendar=None, xsrc=None, y=None, y0=None, yaxis=None, ycalendar=None, ysrc=None, row=None, col=None, secondary_y=None, **kwargs ): """ Add a new Scatter trace The scatter trace type encompasses line charts, scatter charts, text charts, and bubble charts. The data visualized as scatter point or lines is set in `x` and `y`. Text (appearing either on the chart or on hover only) is via `text`. Bubble charts are achieved by setting `marker.size` and/or `marker.color` to numerical arrays. Parameters ---------- cliponaxis Determines whether or not markers and text nodes are clipped about the subplot axes. To show markers and text nodes above axis lines and tick labels, make sure to set `xaxis.layer` and `yaxis.layer` to *below traces*. connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dx Sets the x coordinate step. See `x0` for more info. dy Sets the y coordinate step. See `y0` for more info. error_x plotly.graph_objects.scatter.ErrorX instance or dict with compatible properties error_y plotly.graph_objects.scatter.ErrorY instance or dict with compatible properties fill Sets the area to fill with a solid color. Defaults to "none" unless this trace is stacked, then it gets "tonexty" ("tonextx") if `orientation` is "v" ("h") Use with `fillcolor` if not "none". "tozerox" and "tozeroy" fill to x=0 and y=0 respectively. "tonextx" and "tonexty" fill between the endpoints of this trace and the endpoints of the trace before it, connecting those endpoints with straight lines (to make a stacked area graph); if there is no trace before it, they behave like "tozerox" and "tozeroy". "toself" connects the endpoints of the trace (or each segment of the trace if it has gaps) into a closed shape. "tonext" fills the space between two traces if one completely encloses the other (eg consecutive contour lines), and behaves like "toself" if there is no trace before it. "tonext" should not be used if one trace does not enclose the other. Traces in a `stackgroup` will only fill to (or be filled to) other traces in the same group. With multiple `stackgroup`s or some traces stacked and some not, if fill-linked traces are not already consecutive, the later ones will be pushed down in the drawing order. fillcolor Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. groupnorm Only relevant when `stackgroup` is used, and only the first `groupnorm` found in the `stackgroup` will be used - including if `visible` is "legendonly" but not if it is `false`. Sets the normalization for the sum of this `stackgroup`. With "fraction", the value of each trace at each location is divided by the sum of all trace values at that location. "percent" is the same but multiplied by 100 to show percentages. If there are multiple subplots, or multiple `stackgroup`s on one subplot, each will be normalized within its own set. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.scatter.Hoverlabel instance or dict with compatible properties hoveron Do the hover effects highlight individual points (markers or line points) or do they highlight filled regions? If the fill is "toself" or "tonext" and there are no markers or text, then the default is "fills", otherwise it is "points". hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.scatter.Line instance or dict with compatible properties marker plotly.graph_objects.scatter.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . mode Determines the drawing mode for this scatter trace. If the provided `mode` includes "text" then the `text` elements appear at the coordinates. Otherwise, the `text` elements appear on hover. If there are less than 20 points and the trace is not stacked then the default is "lines+markers". Otherwise, "lines". name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. orientation Only relevant when `stackgroup` is used, and only the first `orientation` found in the `stackgroup` will be used - including if `visible` is "legendonly" but not if it is `false`. Sets the stacking direction. With "v" ("h"), the y (x) values of subsequent traces are added. Also affects the default value of `fill`. r r coordinates in scatter traces are deprecated!Please switch to the "scatterpolar" trace type.Sets the radial coordinatesfor legacy polar chart only. rsrc Sets the source reference on plot.ly for r . selected plotly.graph_objects.scatter.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stackgaps Only relevant when `stackgroup` is used, and only the first `stackgaps` found in the `stackgroup` will be used - including if `visible` is "legendonly" but not if it is `false`. Determines how we handle locations at which other traces in this group have data but this one does not. With *infer zero* we insert a zero at these locations. With "interpolate" we linearly interpolate between existing values, and extrapolate a constant beyond the existing values. stackgroup Set several scatter traces (on the same subplot) to the same stackgroup in order to add their y values (or their x values if `orientation` is "h"). If blank or omitted this trace will not be stacked. Stacking also turns `fill` on by default, using "tonexty" ("tonextx") if `orientation` is "h" ("v") and sets the default `mode` to "lines" irrespective of point count. You can only stack on a numeric (linear or log) axis. Traces in a `stackgroup` will only fill to (or be filled to) other traces in the same group. With multiple `stackgroup`s or some traces stacked and some not, if fill-linked traces are not already consecutive, the later ones will be pushed down in the drawing order. stream plotly.graph_objects.scatter.Stream instance or dict with compatible properties t t coordinates in scatter traces are deprecated!Please switch to the "scatterpolar" trace type.Sets the angular coordinatesfor legacy polar chart only. text Sets text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the text font. textposition Sets the positions of the `text` elements with respects to the (x,y) coordinates. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. texttemplatesrc Sets the source reference on plot.ly for texttemplate . tsrc Sets the source reference on plot.ly for t . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.scatter.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the x coordinates. x0 Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . y Sets the y coordinates. y0 Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` secondary_y: boolean or None (default None) If True, associate this trace with the secondary y-axis of the subplot at the specified row and col. Only valid if all of the following conditions are satisfied: * The figure was created using `plotly.subplots.make_subplots`. * The row and col arguments are not None * The subplot at the specified row and col has type xy (which is the default) and secondary_y True. These properties are specified in the specs argument to make_subplots. See the make_subplots docstring for more info. Returns ------- FigureWidget """ new_trace = Scatter( cliponaxis=cliponaxis, connectgaps=connectgaps, customdata=customdata, customdatasrc=customdatasrc, dx=dx, dy=dy, error_x=error_x, error_y=error_y, fill=fill, fillcolor=fillcolor, groupnorm=groupnorm, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hoveron=hoveron, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, legendgroup=legendgroup, line=line, marker=marker, meta=meta, metasrc=metasrc, mode=mode, name=name, opacity=opacity, orientation=orientation, r=r, rsrc=rsrc, selected=selected, selectedpoints=selectedpoints, showlegend=showlegend, stackgaps=stackgaps, stackgroup=stackgroup, stream=stream, t=t, text=text, textfont=textfont, textposition=textposition, textpositionsrc=textpositionsrc, textsrc=textsrc, texttemplate=texttemplate, texttemplatesrc=texttemplatesrc, tsrc=tsrc, uid=uid, uirevision=uirevision, unselected=unselected, visible=visible, x=x, x0=x0, xaxis=xaxis, xcalendar=xcalendar, xsrc=xsrc, y=y, y0=y0, yaxis=yaxis, ycalendar=ycalendar, ysrc=ysrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) def add_scatter3d( self, connectgaps=None, customdata=None, customdatasrc=None, error_x=None, error_y=None, error_z=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, legendgroup=None, line=None, marker=None, meta=None, metasrc=None, mode=None, name=None, opacity=None, projection=None, scene=None, showlegend=None, stream=None, surfaceaxis=None, surfacecolor=None, text=None, textfont=None, textposition=None, textpositionsrc=None, textsrc=None, texttemplate=None, texttemplatesrc=None, uid=None, uirevision=None, visible=None, x=None, xcalendar=None, xsrc=None, y=None, ycalendar=None, ysrc=None, z=None, zcalendar=None, zsrc=None, row=None, col=None, **kwargs ): """ Add a new Scatter3d trace The data visualized as scatter point or lines in 3D dimension is set in `x`, `y`, `z`. Text (appearing either on the chart or on hover only) is via `text`. Bubble charts are achieved by setting `marker.size` and/or `marker.color` Projections are achieved via `projection`. Surface fills are achieved via `surfaceaxis`. Parameters ---------- connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . error_x plotly.graph_objects.scatter3d.ErrorX instance or dict with compatible properties error_y plotly.graph_objects.scatter3d.ErrorY instance or dict with compatible properties error_z plotly.graph_objects.scatter3d.ErrorZ instance or dict with compatible properties hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.scatter3d.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets text elements associated with each (x,y,z) triplet. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y,z) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.scatter3d.Line instance or dict with compatible properties marker plotly.graph_objects.scatter3d.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . mode Determines the drawing mode for this scatter trace. If the provided `mode` includes "text" then the `text` elements appear at the coordinates. Otherwise, the `text` elements appear on hover. If there are less than 20 points and the trace is not stacked then the default is "lines+markers". Otherwise, "lines". name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. projection plotly.graph_objects.scatter3d.Projection instance or dict with compatible properties scene Sets a reference between this trace's 3D coordinate system and a 3D scene. If "scene" (the default value), the (x,y,z) coordinates refer to `layout.scene`. If "scene2", the (x,y,z) coordinates refer to `layout.scene2`, and so on. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.scatter3d.Stream instance or dict with compatible properties surfaceaxis If "-1", the scatter points are not fill with a surface If 0, 1, 2, the scatter points are filled with a Delaunay surface about the x, y, z respectively. surfacecolor Sets the surface fill color. text Sets text elements associated with each (x,y,z) triplet. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y,z) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont plotly.graph_objects.scatter3d.Textfont instance or dict with compatible properties textposition Sets the positions of the `text` elements with respects to the (x,y) coordinates. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. texttemplatesrc Sets the source reference on plot.ly for texttemplate . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the x coordinates. xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . y Sets the y coordinates. ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . z Sets the z coordinates. zcalendar Sets the calendar system to use with `z` date data. zsrc Sets the source reference on plot.ly for z . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- FigureWidget """ new_trace = Scatter3d( connectgaps=connectgaps, customdata=customdata, customdatasrc=customdatasrc, error_x=error_x, error_y=error_y, error_z=error_z, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, legendgroup=legendgroup, line=line, marker=marker, meta=meta, metasrc=metasrc, mode=mode, name=name, opacity=opacity, projection=projection, scene=scene, showlegend=showlegend, stream=stream, surfaceaxis=surfaceaxis, surfacecolor=surfacecolor, text=text, textfont=textfont, textposition=textposition, textpositionsrc=textpositionsrc, textsrc=textsrc, texttemplate=texttemplate, texttemplatesrc=texttemplatesrc, uid=uid, uirevision=uirevision, visible=visible, x=x, xcalendar=xcalendar, xsrc=xsrc, y=y, ycalendar=ycalendar, ysrc=ysrc, z=z, zcalendar=zcalendar, zsrc=zsrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_scattercarpet( self, a=None, asrc=None, b=None, bsrc=None, carpet=None, connectgaps=None, customdata=None, customdatasrc=None, fill=None, fillcolor=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hoveron=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, legendgroup=None, line=None, marker=None, meta=None, metasrc=None, mode=None, name=None, opacity=None, selected=None, selectedpoints=None, showlegend=None, stream=None, text=None, textfont=None, textposition=None, textpositionsrc=None, textsrc=None, texttemplate=None, texttemplatesrc=None, uid=None, uirevision=None, unselected=None, visible=None, xaxis=None, yaxis=None, row=None, col=None, secondary_y=None, **kwargs ): """ Add a new Scattercarpet trace Plots a scatter trace on either the first carpet axis or the carpet axis with a matching `carpet` attribute. Parameters ---------- a Sets the a-axis coordinates. asrc Sets the source reference on plot.ly for a . b Sets the b-axis coordinates. bsrc Sets the source reference on plot.ly for b . carpet An identifier for this carpet, so that `scattercarpet` and `contourcarpet` traces can specify a carpet plot on which they lie connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . fill Sets the area to fill with a solid color. Use with `fillcolor` if not "none". scatterternary has a subset of the options available to scatter. "toself" connects the endpoints of the trace (or each segment of the trace if it has gaps) into a closed shape. "tonext" fills the space between two traces if one completely encloses the other (eg consecutive contour lines), and behaves like "toself" if there is no trace before it. "tonext" should not be used if one trace does not enclose the other. fillcolor Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.scattercarpet.Hoverlabel instance or dict with compatible properties hoveron Do the hover effects highlight individual points (markers or line points) or do they highlight filled regions? If the fill is "toself" or "tonext" and there are no markers or text, then the default is "fills", otherwise it is "points". hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (a,b) point. If a single string, the same string appears over all the data points. If an array of strings, the items are mapped in order to the the data points in (a,b). To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.scattercarpet.Line instance or dict with compatible properties marker plotly.graph_objects.scattercarpet.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . mode Determines the drawing mode for this scatter trace. If the provided `mode` includes "text" then the `text` elements appear at the coordinates. Otherwise, the `text` elements appear on hover. If there are less than 20 points and the trace is not stacked then the default is "lines+markers". Otherwise, "lines". name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. selected plotly.graph_objects.scattercarpet.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.scattercarpet.Stream instance or dict with compatible properties text Sets text elements associated with each (a,b) point. If a single string, the same string appears over all the data points. If an array of strings, the items are mapped in order to the the data points in (a,b). If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the text font. textposition Sets the positions of the `text` elements with respects to the (x,y) coordinates. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `a`, `b` and `text`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.scattercarpet.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` secondary_y: boolean or None (default None) If True, associate this trace with the secondary y-axis of the subplot at the specified row and col. Only valid if all of the following conditions are satisfied: * The figure was created using `plotly.subplots.make_subplots`. * The row and col arguments are not None * The subplot at the specified row and col has type xy (which is the default) and secondary_y True. These properties are specified in the specs argument to make_subplots. See the make_subplots docstring for more info. Returns ------- FigureWidget """ new_trace = Scattercarpet( a=a, asrc=asrc, b=b, bsrc=bsrc, carpet=carpet, connectgaps=connectgaps, customdata=customdata, customdatasrc=customdatasrc, fill=fill, fillcolor=fillcolor, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hoveron=hoveron, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, legendgroup=legendgroup, line=line, marker=marker, meta=meta, metasrc=metasrc, mode=mode, name=name, opacity=opacity, selected=selected, selectedpoints=selectedpoints, showlegend=showlegend, stream=stream, text=text, textfont=textfont, textposition=textposition, textpositionsrc=textpositionsrc, textsrc=textsrc, texttemplate=texttemplate, texttemplatesrc=texttemplatesrc, uid=uid, uirevision=uirevision, unselected=unselected, visible=visible, xaxis=xaxis, yaxis=yaxis, **kwargs ) return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) def add_scattergeo( self, connectgaps=None, customdata=None, customdatasrc=None, fill=None, fillcolor=None, geo=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, lat=None, latsrc=None, legendgroup=None, line=None, locationmode=None, locations=None, locationssrc=None, lon=None, lonsrc=None, marker=None, meta=None, metasrc=None, mode=None, name=None, opacity=None, selected=None, selectedpoints=None, showlegend=None, stream=None, text=None, textfont=None, textposition=None, textpositionsrc=None, textsrc=None, texttemplate=None, texttemplatesrc=None, uid=None, uirevision=None, unselected=None, visible=None, row=None, col=None, **kwargs ): """ Add a new Scattergeo trace The data visualized as scatter point or lines on a geographic map is provided either by longitude/latitude pairs in `lon` and `lat` respectively or by geographic location IDs or names in `locations`. Parameters ---------- connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . fill Sets the area to fill with a solid color. Use with `fillcolor` if not "none". "toself" connects the endpoints of the trace (or each segment of the trace if it has gaps) into a closed shape. fillcolor Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. geo Sets a reference between this trace's geospatial coordinates and a geographic map. If "geo" (the default value), the geospatial coordinates refer to `layout.geo`. If "geo2", the geospatial coordinates refer to `layout.geo2`, and so on. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.scattergeo.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (lon,lat) pair or item in `locations`. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (lon,lat) or `locations` coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . lat Sets the latitude coordinates (in degrees North). latsrc Sets the source reference on plot.ly for lat . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.scattergeo.Line instance or dict with compatible properties locationmode Determines the set of locations used to match entries in `locations` to regions on the map. locations Sets the coordinates via location IDs or names. Coordinates correspond to the centroid of each location given. See `locationmode` for more info. locationssrc Sets the source reference on plot.ly for locations . lon Sets the longitude coordinates (in degrees East). lonsrc Sets the source reference on plot.ly for lon . marker plotly.graph_objects.scattergeo.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . mode Determines the drawing mode for this scatter trace. If the provided `mode` includes "text" then the `text` elements appear at the coordinates. Otherwise, the `text` elements appear on hover. If there are less than 20 points and the trace is not stacked then the default is "lines+markers". Otherwise, "lines". name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. selected plotly.graph_objects.scattergeo.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.scattergeo.Stream instance or dict with compatible properties text Sets text elements associated with each (lon,lat) pair or item in `locations`. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (lon,lat) or `locations` coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the text font. textposition Sets the positions of the `text` elements with respects to the (x,y) coordinates. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `lat`, `lon`, `location` and `text`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.scattergeo.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- FigureWidget """ new_trace = Scattergeo( connectgaps=connectgaps, customdata=customdata, customdatasrc=customdatasrc, fill=fill, fillcolor=fillcolor, geo=geo, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, lat=lat, latsrc=latsrc, legendgroup=legendgroup, line=line, locationmode=locationmode, locations=locations, locationssrc=locationssrc, lon=lon, lonsrc=lonsrc, marker=marker, meta=meta, metasrc=metasrc, mode=mode, name=name, opacity=opacity, selected=selected, selectedpoints=selectedpoints, showlegend=showlegend, stream=stream, text=text, textfont=textfont, textposition=textposition, textpositionsrc=textpositionsrc, textsrc=textsrc, texttemplate=texttemplate, texttemplatesrc=texttemplatesrc, uid=uid, uirevision=uirevision, unselected=unselected, visible=visible, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_scattergl( self, connectgaps=None, customdata=None, customdatasrc=None, dx=None, dy=None, error_x=None, error_y=None, fill=None, fillcolor=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, legendgroup=None, line=None, marker=None, meta=None, metasrc=None, mode=None, name=None, opacity=None, selected=None, selectedpoints=None, showlegend=None, stream=None, text=None, textfont=None, textposition=None, textpositionsrc=None, textsrc=None, texttemplate=None, texttemplatesrc=None, uid=None, uirevision=None, unselected=None, visible=None, x=None, x0=None, xaxis=None, xcalendar=None, xsrc=None, y=None, y0=None, yaxis=None, ycalendar=None, ysrc=None, row=None, col=None, secondary_y=None, **kwargs ): """ Add a new Scattergl trace The data visualized as scatter point or lines is set in `x` and `y` using the WebGL plotting engine. Bubble charts are achieved by setting `marker.size` and/or `marker.color` to a numerical arrays. Parameters ---------- connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dx Sets the x coordinate step. See `x0` for more info. dy Sets the y coordinate step. See `y0` for more info. error_x plotly.graph_objects.scattergl.ErrorX instance or dict with compatible properties error_y plotly.graph_objects.scattergl.ErrorY instance or dict with compatible properties fill Sets the area to fill with a solid color. Defaults to "none" unless this trace is stacked, then it gets "tonexty" ("tonextx") if `orientation` is "v" ("h") Use with `fillcolor` if not "none". "tozerox" and "tozeroy" fill to x=0 and y=0 respectively. "tonextx" and "tonexty" fill between the endpoints of this trace and the endpoints of the trace before it, connecting those endpoints with straight lines (to make a stacked area graph); if there is no trace before it, they behave like "tozerox" and "tozeroy". "toself" connects the endpoints of the trace (or each segment of the trace if it has gaps) into a closed shape. "tonext" fills the space between two traces if one completely encloses the other (eg consecutive contour lines), and behaves like "toself" if there is no trace before it. "tonext" should not be used if one trace does not enclose the other. Traces in a `stackgroup` will only fill to (or be filled to) other traces in the same group. With multiple `stackgroup`s or some traces stacked and some not, if fill-linked traces are not already consecutive, the later ones will be pushed down in the drawing order. fillcolor Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.scattergl.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.scattergl.Line instance or dict with compatible properties marker plotly.graph_objects.scattergl.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . mode Determines the drawing mode for this scatter trace. name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. selected plotly.graph_objects.scattergl.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.scattergl.Stream instance or dict with compatible properties text Sets text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the text font. textposition Sets the positions of the `text` elements with respects to the (x,y) coordinates. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. texttemplatesrc Sets the source reference on plot.ly for texttemplate . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.scattergl.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the x coordinates. x0 Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . y Sets the y coordinates. y0 Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` secondary_y: boolean or None (default None) If True, associate this trace with the secondary y-axis of the subplot at the specified row and col. Only valid if all of the following conditions are satisfied: * The figure was created using `plotly.subplots.make_subplots`. * The row and col arguments are not None * The subplot at the specified row and col has type xy (which is the default) and secondary_y True. These properties are specified in the specs argument to make_subplots. See the make_subplots docstring for more info. Returns ------- FigureWidget """ new_trace = Scattergl( connectgaps=connectgaps, customdata=customdata, customdatasrc=customdatasrc, dx=dx, dy=dy, error_x=error_x, error_y=error_y, fill=fill, fillcolor=fillcolor, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, legendgroup=legendgroup, line=line, marker=marker, meta=meta, metasrc=metasrc, mode=mode, name=name, opacity=opacity, selected=selected, selectedpoints=selectedpoints, showlegend=showlegend, stream=stream, text=text, textfont=textfont, textposition=textposition, textpositionsrc=textpositionsrc, textsrc=textsrc, texttemplate=texttemplate, texttemplatesrc=texttemplatesrc, uid=uid, uirevision=uirevision, unselected=unselected, visible=visible, x=x, x0=x0, xaxis=xaxis, xcalendar=xcalendar, xsrc=xsrc, y=y, y0=y0, yaxis=yaxis, ycalendar=ycalendar, ysrc=ysrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) def add_scattermapbox( self, below=None, connectgaps=None, customdata=None, customdatasrc=None, fill=None, fillcolor=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, lat=None, latsrc=None, legendgroup=None, line=None, lon=None, lonsrc=None, marker=None, meta=None, metasrc=None, mode=None, name=None, opacity=None, selected=None, selectedpoints=None, showlegend=None, stream=None, subplot=None, text=None, textfont=None, textposition=None, textsrc=None, texttemplate=None, texttemplatesrc=None, uid=None, uirevision=None, unselected=None, visible=None, row=None, col=None, **kwargs ): """ Add a new Scattermapbox trace The data visualized as scatter point, lines or marker symbols on a Mapbox GL geographic map is provided by longitude/latitude pairs in `lon` and `lat`. Parameters ---------- below Determines if this scattermapbox trace's layers are to be inserted before the layer with the specified ID. By default, scattermapbox layers are inserted above all the base layers. To place the scattermapbox layers above every other layer, set `below` to "''". connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . fill Sets the area to fill with a solid color. Use with `fillcolor` if not "none". "toself" connects the endpoints of the trace (or each segment of the trace if it has gaps) into a closed shape. fillcolor Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.scattermapbox.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (lon,lat) pair If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (lon,lat) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . lat Sets the latitude coordinates (in degrees North). latsrc Sets the source reference on plot.ly for lat . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.scattermapbox.Line instance or dict with compatible properties lon Sets the longitude coordinates (in degrees East). lonsrc Sets the source reference on plot.ly for lon . marker plotly.graph_objects.scattermapbox.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . mode Determines the drawing mode for this scatter trace. If the provided `mode` includes "text" then the `text` elements appear at the coordinates. Otherwise, the `text` elements appear on hover. name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. selected plotly.graph_objects.scattermapbox.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.scattermapbox.Stream instance or dict with compatible properties subplot Sets a reference between this trace's data coordinates and a mapbox subplot. If "mapbox" (the default value), the data refer to `layout.mapbox`. If "mapbox2", the data refer to `layout.mapbox2`, and so on. text Sets text elements associated with each (lon,lat) pair If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (lon,lat) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the icon text font (color=mapbox.layer.paint.text- color, size=mapbox.layer.layout.text-size). Has an effect only when `type` is set to "symbol". textposition Sets the positions of the `text` elements with respects to the (x,y) coordinates. textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `lat`, `lon` and `text`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.scattermapbox.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- FigureWidget """ new_trace = Scattermapbox( below=below, connectgaps=connectgaps, customdata=customdata, customdatasrc=customdatasrc, fill=fill, fillcolor=fillcolor, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, lat=lat, latsrc=latsrc, legendgroup=legendgroup, line=line, lon=lon, lonsrc=lonsrc, marker=marker, meta=meta, metasrc=metasrc, mode=mode, name=name, opacity=opacity, selected=selected, selectedpoints=selectedpoints, showlegend=showlegend, stream=stream, subplot=subplot, text=text, textfont=textfont, textposition=textposition, textsrc=textsrc, texttemplate=texttemplate, texttemplatesrc=texttemplatesrc, uid=uid, uirevision=uirevision, unselected=unselected, visible=visible, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_scatterpolar( self, cliponaxis=None, connectgaps=None, customdata=None, customdatasrc=None, dr=None, dtheta=None, fill=None, fillcolor=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hoveron=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, legendgroup=None, line=None, marker=None, meta=None, metasrc=None, mode=None, name=None, opacity=None, r=None, r0=None, rsrc=None, selected=None, selectedpoints=None, showlegend=None, stream=None, subplot=None, text=None, textfont=None, textposition=None, textpositionsrc=None, textsrc=None, texttemplate=None, texttemplatesrc=None, theta=None, theta0=None, thetasrc=None, thetaunit=None, uid=None, uirevision=None, unselected=None, visible=None, row=None, col=None, **kwargs ): """ Add a new Scatterpolar trace The scatterpolar trace type encompasses line charts, scatter charts, text charts, and bubble charts in polar coordinates. The data visualized as scatter point or lines is set in `r` (radial) and `theta` (angular) coordinates Text (appearing either on the chart or on hover only) is via `text`. Bubble charts are achieved by setting `marker.size` and/or `marker.color` to numerical arrays. Parameters ---------- cliponaxis Determines whether or not markers and text nodes are clipped about the subplot axes. To show markers and text nodes above axis lines and tick labels, make sure to set `xaxis.layer` and `yaxis.layer` to *below traces*. connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dr Sets the r coordinate step. dtheta Sets the theta coordinate step. By default, the `dtheta` step equals the subplot's period divided by the length of the `r` coordinates. fill Sets the area to fill with a solid color. Use with `fillcolor` if not "none". scatterpolar has a subset of the options available to scatter. "toself" connects the endpoints of the trace (or each segment of the trace if it has gaps) into a closed shape. "tonext" fills the space between two traces if one completely encloses the other (eg consecutive contour lines), and behaves like "toself" if there is no trace before it. "tonext" should not be used if one trace does not enclose the other. fillcolor Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.scatterpolar.Hoverlabel instance or dict with compatible properties hoveron Do the hover effects highlight individual points (markers or line points) or do they highlight filled regions? If the fill is "toself" or "tonext" and there are no markers or text, then the default is "fills", otherwise it is "points". hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.scatterpolar.Line instance or dict with compatible properties marker plotly.graph_objects.scatterpolar.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . mode Determines the drawing mode for this scatter trace. If the provided `mode` includes "text" then the `text` elements appear at the coordinates. Otherwise, the `text` elements appear on hover. If there are less than 20 points and the trace is not stacked then the default is "lines+markers". Otherwise, "lines". name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. r Sets the radial coordinates r0 Alternate to `r`. Builds a linear space of r coordinates. Use with `dr` where `r0` is the starting coordinate and `dr` the step. rsrc Sets the source reference on plot.ly for r . selected plotly.graph_objects.scatterpolar.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.scatterpolar.Stream instance or dict with compatible properties subplot Sets a reference between this trace's data coordinates and a polar subplot. If "polar" (the default value), the data refer to `layout.polar`. If "polar2", the data refer to `layout.polar2`, and so on. text Sets text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the text font. textposition Sets the positions of the `text` elements with respects to the (x,y) coordinates. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `r`, `theta` and `text`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . theta Sets the angular coordinates theta0 Alternate to `theta`. Builds a linear space of theta coordinates. Use with `dtheta` where `theta0` is the starting coordinate and `dtheta` the step. thetasrc Sets the source reference on plot.ly for theta . thetaunit Sets the unit of input "theta" values. Has an effect only when on "linear" angular axes. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.scatterpolar.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- FigureWidget """ new_trace = Scatterpolar( cliponaxis=cliponaxis, connectgaps=connectgaps, customdata=customdata, customdatasrc=customdatasrc, dr=dr, dtheta=dtheta, fill=fill, fillcolor=fillcolor, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hoveron=hoveron, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, legendgroup=legendgroup, line=line, marker=marker, meta=meta, metasrc=metasrc, mode=mode, name=name, opacity=opacity, r=r, r0=r0, rsrc=rsrc, selected=selected, selectedpoints=selectedpoints, showlegend=showlegend, stream=stream, subplot=subplot, text=text, textfont=textfont, textposition=textposition, textpositionsrc=textpositionsrc, textsrc=textsrc, texttemplate=texttemplate, texttemplatesrc=texttemplatesrc, theta=theta, theta0=theta0, thetasrc=thetasrc, thetaunit=thetaunit, uid=uid, uirevision=uirevision, unselected=unselected, visible=visible, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_scatterpolargl( self, connectgaps=None, customdata=None, customdatasrc=None, dr=None, dtheta=None, fill=None, fillcolor=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, legendgroup=None, line=None, marker=None, meta=None, metasrc=None, mode=None, name=None, opacity=None, r=None, r0=None, rsrc=None, selected=None, selectedpoints=None, showlegend=None, stream=None, subplot=None, text=None, textfont=None, textposition=None, textpositionsrc=None, textsrc=None, texttemplate=None, texttemplatesrc=None, theta=None, theta0=None, thetasrc=None, thetaunit=None, uid=None, uirevision=None, unselected=None, visible=None, row=None, col=None, **kwargs ): """ Add a new Scatterpolargl trace The scatterpolargl trace type encompasses line charts, scatter charts, and bubble charts in polar coordinates using the WebGL plotting engine. The data visualized as scatter point or lines is set in `r` (radial) and `theta` (angular) coordinates Bubble charts are achieved by setting `marker.size` and/or `marker.color` to numerical arrays. Parameters ---------- connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . dr Sets the r coordinate step. dtheta Sets the theta coordinate step. By default, the `dtheta` step equals the subplot's period divided by the length of the `r` coordinates. fill Sets the area to fill with a solid color. Defaults to "none" unless this trace is stacked, then it gets "tonexty" ("tonextx") if `orientation` is "v" ("h") Use with `fillcolor` if not "none". "tozerox" and "tozeroy" fill to x=0 and y=0 respectively. "tonextx" and "tonexty" fill between the endpoints of this trace and the endpoints of the trace before it, connecting those endpoints with straight lines (to make a stacked area graph); if there is no trace before it, they behave like "tozerox" and "tozeroy". "toself" connects the endpoints of the trace (or each segment of the trace if it has gaps) into a closed shape. "tonext" fills the space between two traces if one completely encloses the other (eg consecutive contour lines), and behaves like "toself" if there is no trace before it. "tonext" should not be used if one trace does not enclose the other. Traces in a `stackgroup` will only fill to (or be filled to) other traces in the same group. With multiple `stackgroup`s or some traces stacked and some not, if fill-linked traces are not already consecutive, the later ones will be pushed down in the drawing order. fillcolor Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.scatterpolargl.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.scatterpolargl.Line instance or dict with compatible properties marker plotly.graph_objects.scatterpolargl.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . mode Determines the drawing mode for this scatter trace. If the provided `mode` includes "text" then the `text` elements appear at the coordinates. Otherwise, the `text` elements appear on hover. If there are less than 20 points and the trace is not stacked then the default is "lines+markers". Otherwise, "lines". name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. r Sets the radial coordinates r0 Alternate to `r`. Builds a linear space of r coordinates. Use with `dr` where `r0` is the starting coordinate and `dr` the step. rsrc Sets the source reference on plot.ly for r . selected plotly.graph_objects.scatterpolargl.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.scatterpolargl.Stream instance or dict with compatible properties subplot Sets a reference between this trace's data coordinates and a polar subplot. If "polar" (the default value), the data refer to `layout.polar`. If "polar2", the data refer to `layout.polar2`, and so on. text Sets text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the text font. textposition Sets the positions of the `text` elements with respects to the (x,y) coordinates. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `r`, `theta` and `text`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . theta Sets the angular coordinates theta0 Alternate to `theta`. Builds a linear space of theta coordinates. Use with `dtheta` where `theta0` is the starting coordinate and `dtheta` the step. thetasrc Sets the source reference on plot.ly for theta . thetaunit Sets the unit of input "theta" values. Has an effect only when on "linear" angular axes. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.scatterpolargl.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- FigureWidget """ new_trace = Scatterpolargl( connectgaps=connectgaps, customdata=customdata, customdatasrc=customdatasrc, dr=dr, dtheta=dtheta, fill=fill, fillcolor=fillcolor, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, legendgroup=legendgroup, line=line, marker=marker, meta=meta, metasrc=metasrc, mode=mode, name=name, opacity=opacity, r=r, r0=r0, rsrc=rsrc, selected=selected, selectedpoints=selectedpoints, showlegend=showlegend, stream=stream, subplot=subplot, text=text, textfont=textfont, textposition=textposition, textpositionsrc=textpositionsrc, textsrc=textsrc, texttemplate=texttemplate, texttemplatesrc=texttemplatesrc, theta=theta, theta0=theta0, thetasrc=thetasrc, thetaunit=thetaunit, uid=uid, uirevision=uirevision, unselected=unselected, visible=visible, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_scatterternary( self, a=None, asrc=None, b=None, bsrc=None, c=None, cliponaxis=None, connectgaps=None, csrc=None, customdata=None, customdatasrc=None, fill=None, fillcolor=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hoveron=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, legendgroup=None, line=None, marker=None, meta=None, metasrc=None, mode=None, name=None, opacity=None, selected=None, selectedpoints=None, showlegend=None, stream=None, subplot=None, sum=None, text=None, textfont=None, textposition=None, textpositionsrc=None, textsrc=None, texttemplate=None, texttemplatesrc=None, uid=None, uirevision=None, unselected=None, visible=None, row=None, col=None, **kwargs ): """ Add a new Scatterternary trace Provides similar functionality to the "scatter" type but on a ternary phase diagram. The data is provided by at least two arrays out of `a`, `b`, `c` triplets. Parameters ---------- a Sets the quantity of component `a` in each data point. If `a`, `b`, and `c` are all provided, they need not be normalized, only the relative values matter. If only two arrays are provided they must be normalized to match `ternary.sum`. asrc Sets the source reference on plot.ly for a . b Sets the quantity of component `a` in each data point. If `a`, `b`, and `c` are all provided, they need not be normalized, only the relative values matter. If only two arrays are provided they must be normalized to match `ternary.sum`. bsrc Sets the source reference on plot.ly for b . c Sets the quantity of component `a` in each data point. If `a`, `b`, and `c` are all provided, they need not be normalized, only the relative values matter. If only two arrays are provided they must be normalized to match `ternary.sum`. cliponaxis Determines whether or not markers and text nodes are clipped about the subplot axes. To show markers and text nodes above axis lines and tick labels, make sure to set `xaxis.layer` and `yaxis.layer` to *below traces*. connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the provided data arrays are connected. csrc Sets the source reference on plot.ly for c . customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . fill Sets the area to fill with a solid color. Use with `fillcolor` if not "none". scatterternary has a subset of the options available to scatter. "toself" connects the endpoints of the trace (or each segment of the trace if it has gaps) into a closed shape. "tonext" fills the space between two traces if one completely encloses the other (eg consecutive contour lines), and behaves like "toself" if there is no trace before it. "tonext" should not be used if one trace does not enclose the other. fillcolor Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.scatterternary.Hoverlabel instance or dict with compatible properties hoveron Do the hover effects highlight individual points (markers or line points) or do they highlight filled regions? If the fill is "toself" or "tonext" and there are no markers or text, then the default is "fills", otherwise it is "points". hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (a,b,c) point. If a single string, the same string appears over all the data points. If an array of strings, the items are mapped in order to the the data points in (a,b,c). To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.scatterternary.Line instance or dict with compatible properties marker plotly.graph_objects.scatterternary.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . mode Determines the drawing mode for this scatter trace. If the provided `mode` includes "text" then the `text` elements appear at the coordinates. Otherwise, the `text` elements appear on hover. If there are less than 20 points and the trace is not stacked then the default is "lines+markers". Otherwise, "lines". name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. selected plotly.graph_objects.scatterternary.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.scatterternary.Stream instance or dict with compatible properties subplot Sets a reference between this trace's data coordinates and a ternary subplot. If "ternary" (the default value), the data refer to `layout.ternary`. If "ternary2", the data refer to `layout.ternary2`, and so on. sum The number each triplet should sum to, if only two of `a`, `b`, and `c` are provided. This overrides `ternary.sum` to normalize this specific trace, but does not affect the values displayed on the axes. 0 (or missing) means to use ternary.sum text Sets text elements associated with each (a,b,c) point. If a single string, the same string appears over all the data points. If an array of strings, the items are mapped in order to the the data points in (a,b,c). If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the text font. textposition Sets the positions of the `text` elements with respects to the (x,y) coordinates. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `a`, `b`, `c` and `text`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.scatterternary.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- FigureWidget """ new_trace = Scatterternary( a=a, asrc=asrc, b=b, bsrc=bsrc, c=c, cliponaxis=cliponaxis, connectgaps=connectgaps, csrc=csrc, customdata=customdata, customdatasrc=customdatasrc, fill=fill, fillcolor=fillcolor, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hoveron=hoveron, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, legendgroup=legendgroup, line=line, marker=marker, meta=meta, metasrc=metasrc, mode=mode, name=name, opacity=opacity, selected=selected, selectedpoints=selectedpoints, showlegend=showlegend, stream=stream, subplot=subplot, sum=sum, text=text, textfont=textfont, textposition=textposition, textpositionsrc=textpositionsrc, textsrc=textsrc, texttemplate=texttemplate, texttemplatesrc=texttemplatesrc, uid=uid, uirevision=uirevision, unselected=unselected, visible=visible, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_splom( self, customdata=None, customdatasrc=None, diagonal=None, dimensions=None, dimensiondefaults=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, legendgroup=None, marker=None, meta=None, metasrc=None, name=None, opacity=None, selected=None, selectedpoints=None, showlegend=None, showlowerhalf=None, showupperhalf=None, stream=None, text=None, textsrc=None, uid=None, uirevision=None, unselected=None, visible=None, xaxes=None, yaxes=None, row=None, col=None, **kwargs ): """ Add a new Splom trace Splom traces generate scatter plot matrix visualizations. Each splom `dimensions` items correspond to a generated axis. Values for each of those dimensions are set in `dimensions[i].values`. Splom traces support all `scattergl` marker style attributes. Specify `layout.grid` attributes and/or layout x-axis and y-axis attributes for more control over the axis positioning and style. Parameters ---------- customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . diagonal plotly.graph_objects.splom.Diagonal instance or dict with compatible properties dimensions A tuple of plotly.graph_objects.splom.Dimension instances or dicts with compatible properties dimensiondefaults When used in a template (as layout.template.data.splom.dimensiondefaults), sets the default property values to use for elements of splom.dimensions hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.splom.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. marker plotly.graph_objects.splom.Marker instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. selected plotly.graph_objects.splom.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. showlowerhalf Determines whether or not subplots on the lower half from the diagonal are displayed. showupperhalf Determines whether or not subplots on the upper half from the diagonal are displayed. stream plotly.graph_objects.splom.Stream instance or dict with compatible properties text Sets text elements associated with each (x,y) pair to appear on hover. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.splom.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). xaxes Sets the list of x axes corresponding to dimensions of this splom trace. By default, a splom will match the first N xaxes where N is the number of input dimensions. Note that, in case where `diagonal.visible` is false and `showupperhalf` or `showlowerhalf` is false, this splom trace will generate one less x-axis and one less y-axis. yaxes Sets the list of y axes corresponding to dimensions of this splom trace. By default, a splom will match the first N yaxes where N is the number of input dimensions. Note that, in case where `diagonal.visible` is false and `showupperhalf` or `showlowerhalf` is false, this splom trace will generate one less x-axis and one less y-axis. row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- FigureWidget """ new_trace = Splom( customdata=customdata, customdatasrc=customdatasrc, diagonal=diagonal, dimensions=dimensions, dimensiondefaults=dimensiondefaults, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, legendgroup=legendgroup, marker=marker, meta=meta, metasrc=metasrc, name=name, opacity=opacity, selected=selected, selectedpoints=selectedpoints, showlegend=showlegend, showlowerhalf=showlowerhalf, showupperhalf=showupperhalf, stream=stream, text=text, textsrc=textsrc, uid=uid, uirevision=uirevision, unselected=unselected, visible=visible, xaxes=xaxes, yaxes=yaxes, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_streamtube( self, autocolorscale=None, cauto=None, cmax=None, cmid=None, cmin=None, coloraxis=None, colorbar=None, colorscale=None, customdata=None, customdatasrc=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, ids=None, idssrc=None, lighting=None, lightposition=None, maxdisplayed=None, meta=None, metasrc=None, name=None, opacity=None, reversescale=None, scene=None, showscale=None, sizeref=None, starts=None, stream=None, text=None, u=None, uid=None, uirevision=None, usrc=None, v=None, visible=None, vsrc=None, w=None, wsrc=None, x=None, xsrc=None, y=None, ysrc=None, z=None, zsrc=None, row=None, col=None, **kwargs ): """ Add a new Streamtube trace Use a streamtube trace to visualize flow in a vector field. Specify a vector field using 6 1D arrays of equal length, 3 position arrays `x`, `y` and `z` and 3 vector component arrays `u`, `v`, and `w`. By default, the tubes' starting positions will be cut from the vector field's x-z plane at its minimum y value. To specify your own starting position, use attributes `starts.x`, `starts.y` and `starts.z`. The color is encoded by the norm of (u, v, w), and the local radius by the divergence of (u, v, w). Parameters ---------- autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here u/v/w norm) or the bounds set in `cmin` and `cmax` Defaults to `false` when `cmin` and `cmax` are set by the user. cmax Sets the upper bound of the color domain. Value should have the same units as u/v/w norm and if set, `cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `cmin` and/or `cmax` to be equidistant to this point. Value should have the same units as u/v/w norm. Has no effect when `cauto` is `false`. cmin Sets the lower bound of the color domain. Value should have the same units as u/v/w norm and if set, `cmax` must be set as well. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.streamtube.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`cmin` and `cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.streamtube.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `tubex`, `tubey`, `tubez`, `tubeu`, `tubev`, `tubew`, `norm` and `divergence`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . lighting plotly.graph_objects.streamtube.Lighting instance or dict with compatible properties lightposition plotly.graph_objects.streamtube.Lightposition instance or dict with compatible properties maxdisplayed The maximum number of displayed segments in a streamtube. meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the surface. Please note that in the case of using high `opacity` values for example a value greater than or equal to 0.5 on two surfaces (and 0.25 with four surfaces), an overlay of multiple transparent surfaces may not perfectly be sorted in depth by the webgl API. This behavior may be improved in the near future and is subject to change. reversescale Reverses the color mapping if true. If true, `cmin` will correspond to the last color in the array and `cmax` will correspond to the first color. scene Sets a reference between this trace's 3D coordinate system and a 3D scene. If "scene" (the default value), the (x,y,z) coordinates refer to `layout.scene`. If "scene2", the (x,y,z) coordinates refer to `layout.scene2`, and so on. showscale Determines whether or not a colorbar is displayed for this trace. sizeref The scaling factor for the streamtubes. The default is 1, which avoids two max divergence tubes from touching at adjacent starting positions. starts plotly.graph_objects.streamtube.Starts instance or dict with compatible properties stream plotly.graph_objects.streamtube.Stream instance or dict with compatible properties text Sets a text element associated with this trace. If trace `hoverinfo` contains a "text" flag, this text element will be seen in all hover labels. Note that streamtube traces do not support array `text` values. u Sets the x components of the vector field. uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. usrc Sets the source reference on plot.ly for u . v Sets the y components of the vector field. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). vsrc Sets the source reference on plot.ly for v . w Sets the z components of the vector field. wsrc Sets the source reference on plot.ly for w . x Sets the x coordinates of the vector field. xsrc Sets the source reference on plot.ly for x . y Sets the y coordinates of the vector field. ysrc Sets the source reference on plot.ly for y . z Sets the z coordinates of the vector field. zsrc Sets the source reference on plot.ly for z . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- FigureWidget """ new_trace = Streamtube( autocolorscale=autocolorscale, cauto=cauto, cmax=cmax, cmid=cmid, cmin=cmin, coloraxis=coloraxis, colorbar=colorbar, colorscale=colorscale, customdata=customdata, customdatasrc=customdatasrc, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, ids=ids, idssrc=idssrc, lighting=lighting, lightposition=lightposition, maxdisplayed=maxdisplayed, meta=meta, metasrc=metasrc, name=name, opacity=opacity, reversescale=reversescale, scene=scene, showscale=showscale, sizeref=sizeref, starts=starts, stream=stream, text=text, u=u, uid=uid, uirevision=uirevision, usrc=usrc, v=v, visible=visible, vsrc=vsrc, w=w, wsrc=wsrc, x=x, xsrc=xsrc, y=y, ysrc=ysrc, z=z, zsrc=zsrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_sunburst( self, branchvalues=None, count=None, customdata=None, customdatasrc=None, domain=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, insidetextfont=None, labels=None, labelssrc=None, leaf=None, level=None, marker=None, maxdepth=None, meta=None, metasrc=None, name=None, opacity=None, outsidetextfont=None, parents=None, parentssrc=None, stream=None, text=None, textfont=None, textinfo=None, textsrc=None, texttemplate=None, texttemplatesrc=None, uid=None, uirevision=None, values=None, valuessrc=None, visible=None, row=None, col=None, **kwargs ): """ Add a new Sunburst trace Visualize hierarchal data spanning outward radially from root to leaves. The sunburst sectors are determined by the entries in "labels" or "ids" and in "parents". Parameters ---------- branchvalues Determines how the items in `values` are summed. When set to "total", items in `values` are taken to be value of all its descendants. When set to "remainder", items in `values` corresponding to the root and the branches sectors are taken to be the extra part not part of the sum of the values at their leaves. count Determines default for `values` when it is not provided, by inferring a 1 for each of the "leaves" and/or "branches", otherwise 0. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . domain plotly.graph_objects.sunburst.Domain instance or dict with compatible properties hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.sunburst.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `currentPath`, `root`, `entry`, `percentRoot`, `percentEntry` and `percentParent`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each sector. If a single string, the same string appears for all data points. If an array of string, the items are mapped in order of this trace's sectors. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . insidetextfont Sets the font used for `textinfo` lying inside the sector. labels Sets the labels of each of the sectors. labelssrc Sets the source reference on plot.ly for labels . leaf plotly.graph_objects.sunburst.Leaf instance or dict with compatible properties level Sets the level from which this trace hierarchy is rendered. Set `level` to `''` to start from the root node in the hierarchy. Must be an "id" if `ids` is filled in, otherwise plotly attempts to find a matching item in `labels`. marker plotly.graph_objects.sunburst.Marker instance or dict with compatible properties maxdepth Sets the number of rendered sectors from any given `level`. Set `maxdepth` to "-1" to render all the levels in the hierarchy. meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. outsidetextfont Sets the font used for `textinfo` lying outside the sector. parents Sets the parent sectors for each of the sectors. Empty string items '' are understood to reference the root node in the hierarchy. If `ids` is filled, `parents` items are understood to be "ids" themselves. When `ids` is not set, plotly attempts to find matching items in `labels`, but beware they must be unique. parentssrc Sets the source reference on plot.ly for parents . stream plotly.graph_objects.sunburst.Stream instance or dict with compatible properties text Sets text elements associated with each sector. If trace `textinfo` contains a "text" flag, these elements will be seen on the chart. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the font used for `textinfo`. textinfo Determines which trace information appear on the graph. textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `currentPath`, `root`, `entry`, `percentRoot`, `percentEntry`, `percentParent`, `label` and `value`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. values Sets the values associated with each of the sectors. Use with `branchvalues` to determine how the values are summed. valuessrc Sets the source reference on plot.ly for values . visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- FigureWidget """ new_trace = Sunburst( branchvalues=branchvalues, count=count, customdata=customdata, customdatasrc=customdatasrc, domain=domain, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, insidetextfont=insidetextfont, labels=labels, labelssrc=labelssrc, leaf=leaf, level=level, marker=marker, maxdepth=maxdepth, meta=meta, metasrc=metasrc, name=name, opacity=opacity, outsidetextfont=outsidetextfont, parents=parents, parentssrc=parentssrc, stream=stream, text=text, textfont=textfont, textinfo=textinfo, textsrc=textsrc, texttemplate=texttemplate, texttemplatesrc=texttemplatesrc, uid=uid, uirevision=uirevision, values=values, valuessrc=valuessrc, visible=visible, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_surface( self, autocolorscale=None, cauto=None, cmax=None, cmid=None, cmin=None, coloraxis=None, colorbar=None, colorscale=None, connectgaps=None, contours=None, customdata=None, customdatasrc=None, hidesurface=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, lighting=None, lightposition=None, meta=None, metasrc=None, name=None, opacity=None, reversescale=None, scene=None, showscale=None, stream=None, surfacecolor=None, surfacecolorsrc=None, text=None, textsrc=None, uid=None, uirevision=None, visible=None, x=None, xcalendar=None, xsrc=None, y=None, ycalendar=None, ysrc=None, z=None, zcalendar=None, zsrc=None, row=None, col=None, **kwargs ): """ Add a new Surface trace The data the describes the coordinates of the surface is set in `z`. Data in `z` should be a 2D list. Coordinates in `x` and `y` can either be 1D lists or 2D lists (e.g. to graph parametric surfaces). If not provided in `x` and `y`, the x and y coordinates are assumed to be linear starting at 0 with a unit step. The color scale corresponds to the `z` values by default. For custom color scales, use `surfacecolor` which should be a 2D list, where its bounds can be controlled using `cmin` and `cmax`. Parameters ---------- autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here z or surfacecolor) or the bounds set in `cmin` and `cmax` Defaults to `false` when `cmin` and `cmax` are set by the user. cmax Sets the upper bound of the color domain. Value should have the same units as z or surfacecolor and if set, `cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `cmin` and/or `cmax` to be equidistant to this point. Value should have the same units as z or surfacecolor. Has no effect when `cauto` is `false`. cmin Sets the lower bound of the color domain. Value should have the same units as z or surfacecolor and if set, `cmax` must be set as well. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.surface.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`cmin` and `cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. connectgaps Determines whether or not gaps (i.e. {nan} or missing values) in the `z` data are filled in. contours plotly.graph_objects.surface.Contours instance or dict with compatible properties customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . hidesurface Determines whether or not a surface is drawn. For example, set `hidesurface` to False `contours.x.show` to True and `contours.y.show` to True to draw a wire frame plot. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.surface.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . lighting plotly.graph_objects.surface.Lighting instance or dict with compatible properties lightposition plotly.graph_objects.surface.Lightposition instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the surface. Please note that in the case of using high `opacity` values for example a value greater than or equal to 0.5 on two surfaces (and 0.25 with four surfaces), an overlay of multiple transparent surfaces may not perfectly be sorted in depth by the webgl API. This behavior may be improved in the near future and is subject to change. reversescale Reverses the color mapping if true. If true, `cmin` will correspond to the last color in the array and `cmax` will correspond to the first color. scene Sets a reference between this trace's 3D coordinate system and a 3D scene. If "scene" (the default value), the (x,y,z) coordinates refer to `layout.scene`. If "scene2", the (x,y,z) coordinates refer to `layout.scene2`, and so on. showscale Determines whether or not a colorbar is displayed for this trace. stream plotly.graph_objects.surface.Stream instance or dict with compatible properties surfacecolor Sets the surface color values, used for setting a color scale independent of `z`. surfacecolorsrc Sets the source reference on plot.ly for surfacecolor . text Sets the text elements associated with each z value. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the x coordinates. xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . y Sets the y coordinates. ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . z Sets the z coordinates. zcalendar Sets the calendar system to use with `z` date data. zsrc Sets the source reference on plot.ly for z . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- FigureWidget """ new_trace = Surface( autocolorscale=autocolorscale, cauto=cauto, cmax=cmax, cmid=cmid, cmin=cmin, coloraxis=coloraxis, colorbar=colorbar, colorscale=colorscale, connectgaps=connectgaps, contours=contours, customdata=customdata, customdatasrc=customdatasrc, hidesurface=hidesurface, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, lighting=lighting, lightposition=lightposition, meta=meta, metasrc=metasrc, name=name, opacity=opacity, reversescale=reversescale, scene=scene, showscale=showscale, stream=stream, surfacecolor=surfacecolor, surfacecolorsrc=surfacecolorsrc, text=text, textsrc=textsrc, uid=uid, uirevision=uirevision, visible=visible, x=x, xcalendar=xcalendar, xsrc=xsrc, y=y, ycalendar=ycalendar, ysrc=ysrc, z=z, zcalendar=zcalendar, zsrc=zsrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_table( self, cells=None, columnorder=None, columnordersrc=None, columnwidth=None, columnwidthsrc=None, customdata=None, customdatasrc=None, domain=None, header=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, ids=None, idssrc=None, meta=None, metasrc=None, name=None, stream=None, uid=None, uirevision=None, visible=None, row=None, col=None, **kwargs ): """ Add a new Table trace Table view for detailed data viewing. The data are arranged in a grid of rows and columns. Most styling can be specified for columns, rows or individual cells. Table is using a column- major order, ie. the grid is represented as a vector of column vectors. Parameters ---------- cells plotly.graph_objects.table.Cells instance or dict with compatible properties columnorder Specifies the rendered order of the data columns; for example, a value `2` at position `0` means that column index `0` in the data will be rendered as the third column, as columns have an index base of zero. columnordersrc Sets the source reference on plot.ly for columnorder . columnwidth The width of columns expressed as a ratio. Columns fill the available width in proportion of their specified column widths. columnwidthsrc Sets the source reference on plot.ly for columnwidth . customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . domain plotly.graph_objects.table.Domain instance or dict with compatible properties header plotly.graph_objects.table.Header instance or dict with compatible properties hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.table.Hoverlabel instance or dict with compatible properties ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. stream plotly.graph_objects.table.Stream instance or dict with compatible properties uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- FigureWidget """ new_trace = Table( cells=cells, columnorder=columnorder, columnordersrc=columnordersrc, columnwidth=columnwidth, columnwidthsrc=columnwidthsrc, customdata=customdata, customdatasrc=customdatasrc, domain=domain, header=header, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, ids=ids, idssrc=idssrc, meta=meta, metasrc=metasrc, name=name, stream=stream, uid=uid, uirevision=uirevision, visible=visible, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_treemap( self, branchvalues=None, count=None, customdata=None, customdatasrc=None, domain=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, insidetextfont=None, labels=None, labelssrc=None, level=None, marker=None, maxdepth=None, meta=None, metasrc=None, name=None, opacity=None, outsidetextfont=None, parents=None, parentssrc=None, pathbar=None, stream=None, text=None, textfont=None, textinfo=None, textposition=None, textsrc=None, texttemplate=None, texttemplatesrc=None, tiling=None, uid=None, uirevision=None, values=None, valuessrc=None, visible=None, row=None, col=None, **kwargs ): """ Add a new Treemap trace Visualize hierarchal data from leaves (and/or outer branches) towards root with rectangles. The treemap sectors are determined by the entries in "labels" or "ids" and in "parents". Parameters ---------- branchvalues Determines how the items in `values` are summed. When set to "total", items in `values` are taken to be value of all its descendants. When set to "remainder", items in `values` corresponding to the root and the branches sectors are taken to be the extra part not part of the sum of the values at their leaves. count Determines default for `values` when it is not provided, by inferring a 1 for each of the "leaves" and/or "branches", otherwise 0. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . domain plotly.graph_objects.treemap.Domain instance or dict with compatible properties hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.treemap.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `currentPath`, `root`, `entry`, `percentRoot`, `percentEntry` and `percentParent`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each sector. If a single string, the same string appears for all data points. If an array of string, the items are mapped in order of this trace's sectors. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . insidetextfont Sets the font used for `textinfo` lying inside the sector. labels Sets the labels of each of the sectors. labelssrc Sets the source reference on plot.ly for labels . level Sets the level from which this trace hierarchy is rendered. Set `level` to `''` to start from the root node in the hierarchy. Must be an "id" if `ids` is filled in, otherwise plotly attempts to find a matching item in `labels`. marker plotly.graph_objects.treemap.Marker instance or dict with compatible properties maxdepth Sets the number of rendered sectors from any given `level`. Set `maxdepth` to "-1" to render all the levels in the hierarchy. meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. outsidetextfont Sets the font used for `textinfo` lying outside the sector. parents Sets the parent sectors for each of the sectors. Empty string items '' are understood to reference the root node in the hierarchy. If `ids` is filled, `parents` items are understood to be "ids" themselves. When `ids` is not set, plotly attempts to find matching items in `labels`, but beware they must be unique. parentssrc Sets the source reference on plot.ly for parents . pathbar plotly.graph_objects.treemap.Pathbar instance or dict with compatible properties stream plotly.graph_objects.treemap.Stream instance or dict with compatible properties text Sets text elements associated with each sector. If trace `textinfo` contains a "text" flag, these elements will be seen on the chart. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textfont Sets the font used for `textinfo`. textinfo Determines which trace information appear on the graph. textposition Sets the positions of the `text` elements. textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `currentPath`, `root`, `entry`, `percentRoot`, `percentEntry`, `percentParent`, `label` and `value`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . tiling plotly.graph_objects.treemap.Tiling instance or dict with compatible properties uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. values Sets the values associated with each of the sectors. Use with `branchvalues` to determine how the values are summed. valuessrc Sets the source reference on plot.ly for values . visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- FigureWidget """ new_trace = Treemap( branchvalues=branchvalues, count=count, customdata=customdata, customdatasrc=customdatasrc, domain=domain, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, insidetextfont=insidetextfont, labels=labels, labelssrc=labelssrc, level=level, marker=marker, maxdepth=maxdepth, meta=meta, metasrc=metasrc, name=name, opacity=opacity, outsidetextfont=outsidetextfont, parents=parents, parentssrc=parentssrc, pathbar=pathbar, stream=stream, text=text, textfont=textfont, textinfo=textinfo, textposition=textposition, textsrc=textsrc, texttemplate=texttemplate, texttemplatesrc=texttemplatesrc, tiling=tiling, uid=uid, uirevision=uirevision, values=values, valuessrc=valuessrc, visible=visible, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_violin( self, alignmentgroup=None, bandwidth=None, box=None, customdata=None, customdatasrc=None, fillcolor=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hoveron=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, jitter=None, legendgroup=None, line=None, marker=None, meanline=None, meta=None, metasrc=None, name=None, offsetgroup=None, opacity=None, orientation=None, pointpos=None, points=None, scalegroup=None, scalemode=None, selected=None, selectedpoints=None, showlegend=None, side=None, span=None, spanmode=None, stream=None, text=None, textsrc=None, uid=None, uirevision=None, unselected=None, visible=None, width=None, x=None, x0=None, xaxis=None, xsrc=None, y=None, y0=None, yaxis=None, ysrc=None, row=None, col=None, secondary_y=None, **kwargs ): """ Add a new Violin trace In vertical (horizontal) violin plots, statistics are computed using `y` (`x`) values. By supplying an `x` (`y`) array, one violin per distinct x (y) value is drawn If no `x` (`y`) list is provided, a single violin is drawn. That violin position is then positioned with with `name` or with `x0` (`y0`) if provided. Parameters ---------- alignmentgroup Set several traces linked to the same position axis or matching axes to the same alignmentgroup. This controls whether bars compute their positional range dependently or independently. bandwidth Sets the bandwidth used to compute the kernel density estimate. By default, the bandwidth is determined by Silverman's rule of thumb. box plotly.graph_objects.violin.Box instance or dict with compatible properties customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . fillcolor Sets the fill color. Defaults to a half-transparent variant of the line color, marker color, or marker line color, whichever is available. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.violin.Hoverlabel instance or dict with compatible properties hoveron Do the hover effects highlight individual violins or sample points or the kernel density estimate or any combination of them? hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . jitter Sets the amount of jitter in the sample points drawn. If 0, the sample points align along the distribution axis. If 1, the sample points are drawn in a random jitter of width equal to the width of the violins. legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. line plotly.graph_objects.violin.Line instance or dict with compatible properties marker plotly.graph_objects.violin.Marker instance or dict with compatible properties meanline plotly.graph_objects.violin.Meanline instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. For violin traces, the name will also be used for the position coordinate, if `x` and `x0` (`y` and `y0` if horizontal) are missing and the position axis is categorical. Note that the trace name is also used as a default value for attribute `scalegroup` (please see its description for details). offsetgroup Set several traces linked to the same position axis or matching axes to the same offsetgroup where bars of the same position coordinate will line up. opacity Sets the opacity of the trace. orientation Sets the orientation of the violin(s). If "v" ("h"), the distribution is visualized along the vertical (horizontal). pointpos Sets the position of the sample points in relation to the violins. If 0, the sample points are places over the center of the violins. Positive (negative) values correspond to positions to the right (left) for vertical violins and above (below) for horizontal violins. points If "outliers", only the sample points lying outside the whiskers are shown If "suspectedoutliers", the outlier points are shown and points either less than 4*Q1-3*Q3 or greater than 4*Q3-3*Q1 are highlighted (see `outliercolor`) If "all", all sample points are shown If False, only the violins are shown with no sample points scalegroup If there are multiple violins that should be sized according to to some metric (see `scalemode`), link them by providing a non-empty group id here shared by every trace in the same group. If a violin's `width` is undefined, `scalegroup` will default to the trace's name. In this case, violins with the same names will be linked together scalemode Sets the metric by which the width of each violin is determined."width" means each violin has the same (max) width*count* means the violins are scaled by the number of sample points makingup each violin. selected plotly.graph_objects.violin.Selected instance or dict with compatible properties selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. side Determines on which side of the position value the density function making up one half of a violin is plotted. Useful when comparing two violin traces under "overlay" mode, where one trace has `side` set to "positive" and the other to "negative". span Sets the span in data space for which the density function will be computed. Has an effect only when `spanmode` is set to "manual". spanmode Sets the method by which the span in data space where the density function will be computed. "soft" means the span goes from the sample's minimum value minus two bandwidths to the sample's maximum value plus two bandwidths. "hard" means the span goes from the sample's minimum to its maximum value. For custom span settings, use mode "manual" and fill in the `span` attribute. stream plotly.graph_objects.violin.Stream instance or dict with compatible properties text Sets the text elements associated with each sample value. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. unselected plotly.graph_objects.violin.Unselected instance or dict with compatible properties visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). width Sets the width of the violin in data coordinates. If 0 (default value) the width is automatically selected based on the positions of other violin traces in the same subplot. x Sets the x sample data or coordinates. See overview for more info. x0 Sets the x coordinate of the box. See overview for more info. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xsrc Sets the source reference on plot.ly for x . y Sets the y sample data or coordinates. See overview for more info. y0 Sets the y coordinate of the box. See overview for more info. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ysrc Sets the source reference on plot.ly for y . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` secondary_y: boolean or None (default None) If True, associate this trace with the secondary y-axis of the subplot at the specified row and col. Only valid if all of the following conditions are satisfied: * The figure was created using `plotly.subplots.make_subplots`. * The row and col arguments are not None * The subplot at the specified row and col has type xy (which is the default) and secondary_y True. These properties are specified in the specs argument to make_subplots. See the make_subplots docstring for more info. Returns ------- FigureWidget """ new_trace = Violin( alignmentgroup=alignmentgroup, bandwidth=bandwidth, box=box, customdata=customdata, customdatasrc=customdatasrc, fillcolor=fillcolor, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hoveron=hoveron, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, jitter=jitter, legendgroup=legendgroup, line=line, marker=marker, meanline=meanline, meta=meta, metasrc=metasrc, name=name, offsetgroup=offsetgroup, opacity=opacity, orientation=orientation, pointpos=pointpos, points=points, scalegroup=scalegroup, scalemode=scalemode, selected=selected, selectedpoints=selectedpoints, showlegend=showlegend, side=side, span=span, spanmode=spanmode, stream=stream, text=text, textsrc=textsrc, uid=uid, uirevision=uirevision, unselected=unselected, visible=visible, width=width, x=x, x0=x0, xaxis=xaxis, xsrc=xsrc, y=y, y0=y0, yaxis=yaxis, ysrc=ysrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) def add_volume( self, autocolorscale=None, caps=None, cauto=None, cmax=None, cmid=None, cmin=None, coloraxis=None, colorbar=None, colorscale=None, contour=None, customdata=None, customdatasrc=None, flatshading=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, isomax=None, isomin=None, lighting=None, lightposition=None, meta=None, metasrc=None, name=None, opacity=None, opacityscale=None, reversescale=None, scene=None, showscale=None, slices=None, spaceframe=None, stream=None, surface=None, text=None, textsrc=None, uid=None, uirevision=None, value=None, valuesrc=None, visible=None, x=None, xsrc=None, y=None, ysrc=None, z=None, zsrc=None, row=None, col=None, **kwargs ): """ Add a new Volume trace Draws volume trace between iso-min and iso-max values with coordinates given by four 1-dimensional arrays containing the `value`, `x`, `y` and `z` of every vertex of a uniform or non- uniform 3-D grid. Horizontal or vertical slices, caps as well as spaceframe between iso-min and iso-max values could also be drawn using this trace. Parameters ---------- autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `colorscale`. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. caps plotly.graph_objects.volume.Caps instance or dict with compatible properties cauto Determines whether or not the color domain is computed with respect to the input data (here `value`) or the bounds set in `cmin` and `cmax` Defaults to `false` when `cmin` and `cmax` are set by the user. cmax Sets the upper bound of the color domain. Value should have the same units as `value` and if set, `cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `cmin` and/or `cmax` to be equidistant to this point. Value should have the same units as `value`. Has no effect when `cauto` is `false`. cmin Sets the lower bound of the color domain. Value should have the same units as `value` and if set, `cmax` must be set as well. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.volume.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`cmin` and `cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. contour plotly.graph_objects.volume.Contour instance or dict with compatible properties customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . flatshading Determines whether or not normal smoothing is applied to the meshes, creating meshes with an angular, low- poly look via flat reflections. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.volume.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Same as `text`. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . isomax Sets the maximum boundary for iso-surface plot. isomin Sets the minimum boundary for iso-surface plot. lighting plotly.graph_objects.volume.Lighting instance or dict with compatible properties lightposition plotly.graph_objects.volume.Lightposition instance or dict with compatible properties meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the surface. Please note that in the case of using high `opacity` values for example a value greater than or equal to 0.5 on two surfaces (and 0.25 with four surfaces), an overlay of multiple transparent surfaces may not perfectly be sorted in depth by the webgl API. This behavior may be improved in the near future and is subject to change. opacityscale Sets the opacityscale. The opacityscale must be an array containing arrays mapping a normalized value to an opacity value. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 1], [0.5, 0.2], [1, 1]]` means that higher/lower values would have higher opacity values and those in the middle would be more transparent Alternatively, `opacityscale` may be a palette name string of the following list: 'min', 'max', 'extremes' and 'uniform'. The default is 'uniform'. reversescale Reverses the color mapping if true. If true, `cmin` will correspond to the last color in the array and `cmax` will correspond to the first color. scene Sets a reference between this trace's 3D coordinate system and a 3D scene. If "scene" (the default value), the (x,y,z) coordinates refer to `layout.scene`. If "scene2", the (x,y,z) coordinates refer to `layout.scene2`, and so on. showscale Determines whether or not a colorbar is displayed for this trace. slices plotly.graph_objects.volume.Slices instance or dict with compatible properties spaceframe plotly.graph_objects.volume.Spaceframe instance or dict with compatible properties stream plotly.graph_objects.volume.Stream instance or dict with compatible properties surface plotly.graph_objects.volume.Surface instance or dict with compatible properties text Sets the text elements associated with the vertices. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textsrc Sets the source reference on plot.ly for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. value Sets the 4th dimension (value) of the vertices. valuesrc Sets the source reference on plot.ly for value . visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). x Sets the X coordinates of the vertices on X axis. xsrc Sets the source reference on plot.ly for x . y Sets the Y coordinates of the vertices on Y axis. ysrc Sets the source reference on plot.ly for y . z Sets the Z coordinates of the vertices on Z axis. zsrc Sets the source reference on plot.ly for z . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` Returns ------- FigureWidget """ new_trace = Volume( autocolorscale=autocolorscale, caps=caps, cauto=cauto, cmax=cmax, cmid=cmid, cmin=cmin, coloraxis=coloraxis, colorbar=colorbar, colorscale=colorscale, contour=contour, customdata=customdata, customdatasrc=customdatasrc, flatshading=flatshading, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, isomax=isomax, isomin=isomin, lighting=lighting, lightposition=lightposition, meta=meta, metasrc=metasrc, name=name, opacity=opacity, opacityscale=opacityscale, reversescale=reversescale, scene=scene, showscale=showscale, slices=slices, spaceframe=spaceframe, stream=stream, surface=surface, text=text, textsrc=textsrc, uid=uid, uirevision=uirevision, value=value, valuesrc=valuesrc, visible=visible, x=x, xsrc=xsrc, y=y, ysrc=ysrc, z=z, zsrc=zsrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col) def add_waterfall( self, alignmentgroup=None, base=None, cliponaxis=None, connector=None, constraintext=None, customdata=None, customdatasrc=None, decreasing=None, dx=None, dy=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, increasing=None, insidetextanchor=None, insidetextfont=None, legendgroup=None, measure=None, measuresrc=None, meta=None, metasrc=None, name=None, offset=None, offsetgroup=None, offsetsrc=None, opacity=None, orientation=None, outsidetextfont=None, selectedpoints=None, showlegend=None, stream=None, text=None, textangle=None, textfont=None, textinfo=None, textposition=None, textpositionsrc=None, textsrc=None, texttemplate=None, texttemplatesrc=None, totals=None, uid=None, uirevision=None, visible=None, width=None, widthsrc=None, x=None, x0=None, xaxis=None, xsrc=None, y=None, y0=None, yaxis=None, ysrc=None, row=None, col=None, secondary_y=None, **kwargs ): """ Add a new Waterfall trace Draws waterfall trace which is useful graph to displays the contribution of various elements (either positive or negative) in a bar chart. The data visualized by the span of the bars is set in `y` if `orientation` is set th "v" (the default) and the labels are set in `x`. By setting `orientation` to "h", the roles are interchanged. Parameters ---------- alignmentgroup Set several traces linked to the same position axis or matching axes to the same alignmentgroup. This controls whether bars compute their positional range dependently or independently. base Sets where the bar base is drawn (in position axis units). cliponaxis Determines whether the text nodes are clipped about the subplot axes. To show the text nodes above axis lines and tick labels, make sure to set `xaxis.layer` and `yaxis.layer` to *below traces*. connector plotly.graph_objects.waterfall.Connector instance or dict with compatible properties constraintext Constrain the size of text inside or outside a bar to be no larger than the bar itself. customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on plot.ly for customdata . decreasing plotly.graph_objects.waterfall.Decreasing instance or dict with compatible properties dx Sets the x coordinate step. See `x0` for more info. dy Sets the y coordinate step. See `y0` for more info. hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on plot.ly for hoverinfo . hoverlabel plotly.graph_objects.waterfall.Hoverlabel instance or dict with compatible properties hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `initial`, `delta` and `final`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. hovertemplatesrc Sets the source reference on plot.ly for hovertemplate . hovertext Sets hover text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. To be seen, trace `hoverinfo` must contain a "text" flag. hovertextsrc Sets the source reference on plot.ly for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on plot.ly for ids . increasing plotly.graph_objects.waterfall.Increasing instance or dict with compatible properties insidetextanchor Determines if texts are kept at center or start/end points in `textposition` "inside" mode. insidetextfont Sets the font used for `text` lying inside the bar. legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. measure An array containing types of values. By default the values are considered as 'relative'. However; it is possible to use 'total' to compute the sums. Also 'absolute' could be applied to reset the computed total or to declare an initial value where needed. measuresrc Sets the source reference on plot.ly for measure . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on plot.ly for meta . name Sets the trace name. The trace name appear as the legend item and on hover. offset Shifts the position where the bar is drawn (in position axis units). In "group" barmode, traces that set "offset" will be excluded and drawn in "overlay" mode instead. offsetgroup Set several traces linked to the same position axis or matching axes to the same offsetgroup where bars of the same position coordinate will line up. offsetsrc Sets the source reference on plot.ly for offset . opacity Sets the opacity of the trace. orientation Sets the orientation of the bars. With "v" ("h"), the value of the each bar spans along the vertical (horizontal). outsidetextfont Sets the font used for `text` lying outside the bar. selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream plotly.graph_objects.waterfall.Stream instance or dict with compatible properties text Sets text elements associated with each (x,y) pair. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to the this trace's (x,y) coordinates. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textangle Sets the angle of the tick labels with respect to the bar. For example, a `tickangle` of -90 draws the tick labels vertically. With "auto" the texts may automatically be rotated to fit with the maximum size in bars. textfont Sets the font used for `text`. textinfo Determines which trace information appear on the graph. In the case of having multiple waterfalls, totals are computed separately (per trace). textposition Specifies the location of the `text`. "inside" positions `text` inside, next to the bar end (rotated and scaled if needed). "outside" positions `text` outside, next to the bar end (scaled if needed), unless there is another bar stacked on this one, then the text gets pushed inside. "auto" tries to position `text` inside the bar, but if the bar is too small and no bar is stacked on this one the text is moved outside. textpositionsrc Sets the source reference on plot.ly for textposition . textsrc Sets the source reference on plot.ly for text . texttemplate Template string used for rendering the information text that appear on points. Note that this will override `textinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. Every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `initial`, `delta`, `final` and `label`. texttemplatesrc Sets the source reference on plot.ly for texttemplate . totals plotly.graph_objects.waterfall.Totals instance or dict with compatible properties uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). width Sets the bar width (in position axis units). widthsrc Sets the source reference on plot.ly for width . x Sets the x coordinates. x0 Alternate to `x`. Builds a linear space of x coordinates. Use with `dx` where `x0` is the starting coordinate and `dx` the step. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xsrc Sets the source reference on plot.ly for x . y Sets the y coordinates. y0 Alternate to `y`. Builds a linear space of y coordinates. Use with `dy` where `y0` is the starting coordinate and `dy` the step. yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. ysrc Sets the source reference on plot.ly for y . row : int or None (default) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` col : int or None (default) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.tools.make_subplots` secondary_y: boolean or None (default None) If True, associate this trace with the secondary y-axis of the subplot at the specified row and col. Only valid if all of the following conditions are satisfied: * The figure was created using `plotly.subplots.make_subplots`. * The row and col arguments are not None * The subplot at the specified row and col has type xy (which is the default) and secondary_y True. These properties are specified in the specs argument to make_subplots. See the make_subplots docstring for more info. Returns ------- FigureWidget """ new_trace = Waterfall( alignmentgroup=alignmentgroup, base=base, cliponaxis=cliponaxis, connector=connector, constraintext=constraintext, customdata=customdata, customdatasrc=customdatasrc, decreasing=decreasing, dx=dx, dy=dy, hoverinfo=hoverinfo, hoverinfosrc=hoverinfosrc, hoverlabel=hoverlabel, hovertemplate=hovertemplate, hovertemplatesrc=hovertemplatesrc, hovertext=hovertext, hovertextsrc=hovertextsrc, ids=ids, idssrc=idssrc, increasing=increasing, insidetextanchor=insidetextanchor, insidetextfont=insidetextfont, legendgroup=legendgroup, measure=measure, measuresrc=measuresrc, meta=meta, metasrc=metasrc, name=name, offset=offset, offsetgroup=offsetgroup, offsetsrc=offsetsrc, opacity=opacity, orientation=orientation, outsidetextfont=outsidetextfont, selectedpoints=selectedpoints, showlegend=showlegend, stream=stream, text=text, textangle=textangle, textfont=textfont, textinfo=textinfo, textposition=textposition, textpositionsrc=textpositionsrc, textsrc=textsrc, texttemplate=texttemplate, texttemplatesrc=texttemplatesrc, totals=totals, uid=uid, uirevision=uirevision, visible=visible, width=width, widthsrc=widthsrc, x=x, x0=x0, xaxis=xaxis, xsrc=xsrc, y=y, y0=y0, yaxis=yaxis, ysrc=ysrc, **kwargs ) return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) def select_coloraxes(self, selector=None, row=None, col=None): """ Select coloraxis subplot objects from a particular subplot cell and/or coloraxis subplot objects that satisfy custom selection criteria. Parameters ---------- selector: dict or None (default None) Dict to use as selection criteria. coloraxis objects will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all coloraxis objects are selected. row, col: int or None (default None) Subplot row and column index of coloraxis objects to select. To select coloraxis objects by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all coloraxis objects are selected. Returns ------- generator Generator that iterates through all of the coloraxis objects that satisfy all of the specified selection criteria """ return self._select_layout_subplots_by_prefix("coloraxis", selector, row, col) def for_each_coloraxis(self, fn, selector=None, row=None, col=None): """ Apply a function to all coloraxis objects that satisfy the specified selection criteria Parameters ---------- fn: Function that inputs a single coloraxis object. selector: dict or None (default None) Dict to use as selection criteria. coloraxis objects will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all coloraxis objects are selected. row, col: int or None (default None) Subplot row and column index of coloraxis objects to select. To select coloraxis objects by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all coloraxis objects are selected. Returns ------- self Returns the Figure object that the method was called on """ for obj in self.select_coloraxes(selector=selector, row=row, col=col): fn(obj) return self def update_coloraxes( self, patch=None, selector=None, overwrite=False, row=None, col=None, **kwargs ): """ Perform a property update operation on all coloraxis objects that satisfy the specified selection criteria Parameters ---------- patch: dict Dictionary of property updates to be applied to all coloraxis objects that satisfy the selection criteria. selector: dict or None (default None) Dict to use as selection criteria. coloraxis objects will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all coloraxis objects are selected. overwrite: bool If True, overwrite existing properties. If False, apply updates to existing properties recursively, preserving existing properties that are not specified in the update operation. row, col: int or None (default None) Subplot row and column index of coloraxis objects to select. To select coloraxis objects by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all coloraxis objects are selected. **kwargs Additional property updates to apply to each selected coloraxis object. If a property is specified in both patch and in **kwargs then the one in **kwargs takes precedence. Returns ------- self Returns the Figure object that the method was called on """ for obj in self.select_coloraxes(selector=selector, row=row, col=col): obj.update(patch, overwrite=overwrite, **kwargs) return self def select_geos(self, selector=None, row=None, col=None): """ Select geo subplot objects from a particular subplot cell and/or geo subplot objects that satisfy custom selection criteria. Parameters ---------- selector: dict or None (default None) Dict to use as selection criteria. geo objects will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all geo objects are selected. row, col: int or None (default None) Subplot row and column index of geo objects to select. To select geo objects by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all geo objects are selected. Returns ------- generator Generator that iterates through all of the geo objects that satisfy all of the specified selection criteria """ return self._select_layout_subplots_by_prefix("geo", selector, row, col) def for_each_geo(self, fn, selector=None, row=None, col=None): """ Apply a function to all geo objects that satisfy the specified selection criteria Parameters ---------- fn: Function that inputs a single geo object. selector: dict or None (default None) Dict to use as selection criteria. geo objects will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all geo objects are selected. row, col: int or None (default None) Subplot row and column index of geo objects to select. To select geo objects by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all geo objects are selected. Returns ------- self Returns the Figure object that the method was called on """ for obj in self.select_geos(selector=selector, row=row, col=col): fn(obj) return self def update_geos( self, patch=None, selector=None, overwrite=False, row=None, col=None, **kwargs ): """ Perform a property update operation on all geo objects that satisfy the specified selection criteria Parameters ---------- patch: dict Dictionary of property updates to be applied to all geo objects that satisfy the selection criteria. selector: dict or None (default None) Dict to use as selection criteria. geo objects will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all geo objects are selected. overwrite: bool If True, overwrite existing properties. If False, apply updates to existing properties recursively, preserving existing properties that are not specified in the update operation. row, col: int or None (default None) Subplot row and column index of geo objects to select. To select geo objects by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all geo objects are selected. **kwargs Additional property updates to apply to each selected geo object. If a property is specified in both patch and in **kwargs then the one in **kwargs takes precedence. Returns ------- self Returns the Figure object that the method was called on """ for obj in self.select_geos(selector=selector, row=row, col=col): obj.update(patch, overwrite=overwrite, **kwargs) return self def select_mapboxes(self, selector=None, row=None, col=None): """ Select mapbox subplot objects from a particular subplot cell and/or mapbox subplot objects that satisfy custom selection criteria. Parameters ---------- selector: dict or None (default None) Dict to use as selection criteria. mapbox objects will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all mapbox objects are selected. row, col: int or None (default None) Subplot row and column index of mapbox objects to select. To select mapbox objects by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all mapbox objects are selected. Returns ------- generator Generator that iterates through all of the mapbox objects that satisfy all of the specified selection criteria """ return self._select_layout_subplots_by_prefix("mapbox", selector, row, col) def for_each_mapbox(self, fn, selector=None, row=None, col=None): """ Apply a function to all mapbox objects that satisfy the specified selection criteria Parameters ---------- fn: Function that inputs a single mapbox object. selector: dict or None (default None) Dict to use as selection criteria. mapbox objects will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all mapbox objects are selected. row, col: int or None (default None) Subplot row and column index of mapbox objects to select. To select mapbox objects by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all mapbox objects are selected. Returns ------- self Returns the Figure object that the method was called on """ for obj in self.select_mapboxes(selector=selector, row=row, col=col): fn(obj) return self def update_mapboxes( self, patch=None, selector=None, overwrite=False, row=None, col=None, **kwargs ): """ Perform a property update operation on all mapbox objects that satisfy the specified selection criteria Parameters ---------- patch: dict Dictionary of property updates to be applied to all mapbox objects that satisfy the selection criteria. selector: dict or None (default None) Dict to use as selection criteria. mapbox objects will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all mapbox objects are selected. overwrite: bool If True, overwrite existing properties. If False, apply updates to existing properties recursively, preserving existing properties that are not specified in the update operation. row, col: int or None (default None) Subplot row and column index of mapbox objects to select. To select mapbox objects by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all mapbox objects are selected. **kwargs Additional property updates to apply to each selected mapbox object. If a property is specified in both patch and in **kwargs then the one in **kwargs takes precedence. Returns ------- self Returns the Figure object that the method was called on """ for obj in self.select_mapboxes(selector=selector, row=row, col=col): obj.update(patch, overwrite=overwrite, **kwargs) return self def select_polars(self, selector=None, row=None, col=None): """ Select polar subplot objects from a particular subplot cell and/or polar subplot objects that satisfy custom selection criteria. Parameters ---------- selector: dict or None (default None) Dict to use as selection criteria. polar objects will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all polar objects are selected. row, col: int or None (default None) Subplot row and column index of polar objects to select. To select polar objects by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all polar objects are selected. Returns ------- generator Generator that iterates through all of the polar objects that satisfy all of the specified selection criteria """ return self._select_layout_subplots_by_prefix("polar", selector, row, col) def for_each_polar(self, fn, selector=None, row=None, col=None): """ Apply a function to all polar objects that satisfy the specified selection criteria Parameters ---------- fn: Function that inputs a single polar object. selector: dict or None (default None) Dict to use as selection criteria. polar objects will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all polar objects are selected. row, col: int or None (default None) Subplot row and column index of polar objects to select. To select polar objects by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all polar objects are selected. Returns ------- self Returns the Figure object that the method was called on """ for obj in self.select_polars(selector=selector, row=row, col=col): fn(obj) return self def update_polars( self, patch=None, selector=None, overwrite=False, row=None, col=None, **kwargs ): """ Perform a property update operation on all polar objects that satisfy the specified selection criteria Parameters ---------- patch: dict Dictionary of property updates to be applied to all polar objects that satisfy the selection criteria. selector: dict or None (default None) Dict to use as selection criteria. polar objects will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all polar objects are selected. overwrite: bool If True, overwrite existing properties. If False, apply updates to existing properties recursively, preserving existing properties that are not specified in the update operation. row, col: int or None (default None) Subplot row and column index of polar objects to select. To select polar objects by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all polar objects are selected. **kwargs Additional property updates to apply to each selected polar object. If a property is specified in both patch and in **kwargs then the one in **kwargs takes precedence. Returns ------- self Returns the Figure object that the method was called on """ for obj in self.select_polars(selector=selector, row=row, col=col): obj.update(patch, overwrite=overwrite, **kwargs) return self def select_scenes(self, selector=None, row=None, col=None): """ Select scene subplot objects from a particular subplot cell and/or scene subplot objects that satisfy custom selection criteria. Parameters ---------- selector: dict or None (default None) Dict to use as selection criteria. scene objects will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all scene objects are selected. row, col: int or None (default None) Subplot row and column index of scene objects to select. To select scene objects by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all scene objects are selected. Returns ------- generator Generator that iterates through all of the scene objects that satisfy all of the specified selection criteria """ return self._select_layout_subplots_by_prefix("scene", selector, row, col) def for_each_scene(self, fn, selector=None, row=None, col=None): """ Apply a function to all scene objects that satisfy the specified selection criteria Parameters ---------- fn: Function that inputs a single scene object. selector: dict or None (default None) Dict to use as selection criteria. scene objects will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all scene objects are selected. row, col: int or None (default None) Subplot row and column index of scene objects to select. To select scene objects by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all scene objects are selected. Returns ------- self Returns the Figure object that the method was called on """ for obj in self.select_scenes(selector=selector, row=row, col=col): fn(obj) return self def update_scenes( self, patch=None, selector=None, overwrite=False, row=None, col=None, **kwargs ): """ Perform a property update operation on all scene objects that satisfy the specified selection criteria Parameters ---------- patch: dict Dictionary of property updates to be applied to all scene objects that satisfy the selection criteria. selector: dict or None (default None) Dict to use as selection criteria. scene objects will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all scene objects are selected. overwrite: bool If True, overwrite existing properties. If False, apply updates to existing properties recursively, preserving existing properties that are not specified in the update operation. row, col: int or None (default None) Subplot row and column index of scene objects to select. To select scene objects by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all scene objects are selected. **kwargs Additional property updates to apply to each selected scene object. If a property is specified in both patch and in **kwargs then the one in **kwargs takes precedence. Returns ------- self Returns the Figure object that the method was called on """ for obj in self.select_scenes(selector=selector, row=row, col=col): obj.update(patch, overwrite=overwrite, **kwargs) return self def select_ternaries(self, selector=None, row=None, col=None): """ Select ternary subplot objects from a particular subplot cell and/or ternary subplot objects that satisfy custom selection criteria. Parameters ---------- selector: dict or None (default None) Dict to use as selection criteria. ternary objects will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all ternary objects are selected. row, col: int or None (default None) Subplot row and column index of ternary objects to select. To select ternary objects by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all ternary objects are selected. Returns ------- generator Generator that iterates through all of the ternary objects that satisfy all of the specified selection criteria """ return self._select_layout_subplots_by_prefix("ternary", selector, row, col) def for_each_ternary(self, fn, selector=None, row=None, col=None): """ Apply a function to all ternary objects that satisfy the specified selection criteria Parameters ---------- fn: Function that inputs a single ternary object. selector: dict or None (default None) Dict to use as selection criteria. ternary objects will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all ternary objects are selected. row, col: int or None (default None) Subplot row and column index of ternary objects to select. To select ternary objects by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all ternary objects are selected. Returns ------- self Returns the Figure object that the method was called on """ for obj in self.select_ternaries(selector=selector, row=row, col=col): fn(obj) return self def update_ternaries( self, patch=None, selector=None, overwrite=False, row=None, col=None, **kwargs ): """ Perform a property update operation on all ternary objects that satisfy the specified selection criteria Parameters ---------- patch: dict Dictionary of property updates to be applied to all ternary objects that satisfy the selection criteria. selector: dict or None (default None) Dict to use as selection criteria. ternary objects will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all ternary objects are selected. overwrite: bool If True, overwrite existing properties. If False, apply updates to existing properties recursively, preserving existing properties that are not specified in the update operation. row, col: int or None (default None) Subplot row and column index of ternary objects to select. To select ternary objects by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all ternary objects are selected. **kwargs Additional property updates to apply to each selected ternary object. If a property is specified in both patch and in **kwargs then the one in **kwargs takes precedence. Returns ------- self Returns the Figure object that the method was called on """ for obj in self.select_ternaries(selector=selector, row=row, col=col): obj.update(patch, overwrite=overwrite, **kwargs) return self def select_xaxes(self, selector=None, row=None, col=None): """ Select xaxis subplot objects from a particular subplot cell and/or xaxis subplot objects that satisfy custom selection criteria. Parameters ---------- selector: dict or None (default None) Dict to use as selection criteria. xaxis objects will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all xaxis objects are selected. row, col: int or None (default None) Subplot row and column index of xaxis objects to select. To select xaxis objects by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all xaxis objects are selected. Returns ------- generator Generator that iterates through all of the xaxis objects that satisfy all of the specified selection criteria """ return self._select_layout_subplots_by_prefix("xaxis", selector, row, col) def for_each_xaxis(self, fn, selector=None, row=None, col=None): """ Apply a function to all xaxis objects that satisfy the specified selection criteria Parameters ---------- fn: Function that inputs a single xaxis object. selector: dict or None (default None) Dict to use as selection criteria. xaxis objects will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all xaxis objects are selected. row, col: int or None (default None) Subplot row and column index of xaxis objects to select. To select xaxis objects by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all xaxis objects are selected. Returns ------- self Returns the Figure object that the method was called on """ for obj in self.select_xaxes(selector=selector, row=row, col=col): fn(obj) return self def update_xaxes( self, patch=None, selector=None, overwrite=False, row=None, col=None, **kwargs ): """ Perform a property update operation on all xaxis objects that satisfy the specified selection criteria Parameters ---------- patch: dict Dictionary of property updates to be applied to all xaxis objects that satisfy the selection criteria. selector: dict or None (default None) Dict to use as selection criteria. xaxis objects will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all xaxis objects are selected. overwrite: bool If True, overwrite existing properties. If False, apply updates to existing properties recursively, preserving existing properties that are not specified in the update operation. row, col: int or None (default None) Subplot row and column index of xaxis objects to select. To select xaxis objects by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all xaxis objects are selected. **kwargs Additional property updates to apply to each selected xaxis object. If a property is specified in both patch and in **kwargs then the one in **kwargs takes precedence. Returns ------- self Returns the Figure object that the method was called on """ for obj in self.select_xaxes(selector=selector, row=row, col=col): obj.update(patch, overwrite=overwrite, **kwargs) return self def select_yaxes(self, selector=None, row=None, col=None, secondary_y=None): """ Select yaxis subplot objects from a particular subplot cell and/or yaxis subplot objects that satisfy custom selection criteria. Parameters ---------- selector: dict or None (default None) Dict to use as selection criteria. yaxis objects will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all yaxis objects are selected. row, col: int or None (default None) Subplot row and column index of yaxis objects to select. To select yaxis objects by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all yaxis objects are selected. secondary_y: boolean or None (default None) * If True, only select yaxis objects associated with the secondary y-axis of the subplot. * If False, only select yaxis objects associated with the primary y-axis of the subplot. * If None (the default), do not filter yaxis objects based on a secondary y-axis condition. To select yaxis objects by secondary y-axis, the Figure must have been created using plotly.subplots.make_subplots. See the docstring for the specs argument to make_subplots for more info on creating subplots with secondary y-axes. Returns ------- generator Generator that iterates through all of the yaxis objects that satisfy all of the specified selection criteria """ return self._select_layout_subplots_by_prefix( "yaxis", selector, row, col, secondary_y=secondary_y ) def for_each_yaxis(self, fn, selector=None, row=None, col=None, secondary_y=None): """ Apply a function to all yaxis objects that satisfy the specified selection criteria Parameters ---------- fn: Function that inputs a single yaxis object. selector: dict or None (default None) Dict to use as selection criteria. yaxis objects will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all yaxis objects are selected. row, col: int or None (default None) Subplot row and column index of yaxis objects to select. To select yaxis objects by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all yaxis objects are selected. secondary_y: boolean or None (default None) * If True, only select yaxis objects associated with the secondary y-axis of the subplot. * If False, only select yaxis objects associated with the primary y-axis of the subplot. * If None (the default), do not filter yaxis objects based on a secondary y-axis condition. To select yaxis objects by secondary y-axis, the Figure must have been created using plotly.subplots.make_subplots. See the docstring for the specs argument to make_subplots for more info on creating subplots with secondary y-axes. Returns ------- self Returns the Figure object that the method was called on """ for obj in self.select_yaxes( selector=selector, row=row, col=col, secondary_y=secondary_y ): fn(obj) return self def update_yaxes( self, patch=None, selector=None, overwrite=False, row=None, col=None, secondary_y=None, **kwargs ): """ Perform a property update operation on all yaxis objects that satisfy the specified selection criteria Parameters ---------- patch: dict Dictionary of property updates to be applied to all yaxis objects that satisfy the selection criteria. selector: dict or None (default None) Dict to use as selection criteria. yaxis objects will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all yaxis objects are selected. overwrite: bool If True, overwrite existing properties. If False, apply updates to existing properties recursively, preserving existing properties that are not specified in the update operation. row, col: int or None (default None) Subplot row and column index of yaxis objects to select. To select yaxis objects by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all yaxis objects are selected. secondary_y: boolean or None (default None) * If True, only select yaxis objects associated with the secondary y-axis of the subplot. * If False, only select yaxis objects associated with the primary y-axis of the subplot. * If None (the default), do not filter yaxis objects based on a secondary y-axis condition. To select yaxis objects by secondary y-axis, the Figure must have been created using plotly.subplots.make_subplots. See the docstring for the specs argument to make_subplots for more info on creating subplots with secondary y-axes. **kwargs Additional property updates to apply to each selected yaxis object. If a property is specified in both patch and in **kwargs then the one in **kwargs takes precedence. Returns ------- self Returns the Figure object that the method was called on """ for obj in self.select_yaxes( selector=selector, row=row, col=col, secondary_y=secondary_y ): obj.update(patch, overwrite=overwrite, **kwargs) return self def select_annotations(self, selector=None, row=None, col=None, secondary_y=None): """ Select annotations from a particular subplot cell and/or annotations that satisfy custom selection criteria. Parameters ---------- selector: dict or None (default None) Dict to use as selection criteria. Annotations will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all annotations are selected. row, col: int or None (default None) Subplot row and column index of annotations to select. To select annotations by row and column, the Figure must have been created using plotly.subplots.make_subplots. To select only those annotation that are in paper coordinates, set row and col to the string 'paper'. If None (the default), all annotations are selected. secondary_y: boolean or None (default None) * If True, only select annotations associated with the secondary y-axis of the subplot. * If False, only select annotations associated with the primary y-axis of the subplot. * If None (the default), do not filter annotations based on secondary y-axis. To select annotations by secondary y-axis, the Figure must have been created using plotly.subplots.make_subplots. See the docstring for the specs argument to make_subplots for more info on creating subplots with secondary y-axes. Returns ------- generator Generator that iterates through all of the annotations that satisfy all of the specified selection criteria """ return self._select_annotations_like( "annotations", selector=selector, row=row, col=col, secondary_y=secondary_y ) def for_each_annotation( self, fn, selector=None, row=None, col=None, secondary_y=None ): """ Apply a function to all annotations that satisfy the specified selection criteria Parameters ---------- fn: Function that inputs a single annotation object. selector: dict or None (default None) Dict to use as selection criteria. Traces will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all annotations are selected. row, col: int or None (default None) Subplot row and column index of annotations to select. To select annotations by row and column, the Figure must have been created using plotly.subplots.make_subplots. To select only those annotations that are in paper coordinates, set row and col to the string 'paper'. If None (the default), all annotations are selected. secondary_y: boolean or None (default None) * If True, only select annotations associated with the secondary y-axis of the subplot. * If False, only select annotations associated with the primary y-axis of the subplot. * If None (the default), do not filter annotations based on secondary y-axis. To select annotations by secondary y-axis, the Figure must have been created using plotly.subplots.make_subplots. See the docstring for the specs argument to make_subplots for more info on creating subplots with secondary y-axes. Returns ------- self Returns the Figure object that the method was called on """ for obj in self._select_annotations_like( prop="annotations", selector=selector, row=row, col=col, secondary_y=secondary_y, ): fn(obj) return self def update_annotations( self, patch, selector=None, row=None, col=None, secondary_y=None, **kwargs ): """ Perform a property update operation on all annotations that satisfy the specified selection criteria Parameters ---------- patch: dict or None (default None) Dictionary of property updates to be applied to all annotations that satisfy the selection criteria. selector: dict or None (default None) Dict to use as selection criteria. Traces will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all annotations are selected. row, col: int or None (default None) Subplot row and column index of annotations to select. To select annotations by row and column, the Figure must have been created using plotly.subplots.make_subplots. To select only those annotation that are in paper coordinates, set row and col to the string 'paper'. If None (the default), all annotations are selected. secondary_y: boolean or None (default None) * If True, only select annotations associated with the secondary y-axis of the subplot. * If False, only select annotations associated with the primary y-axis of the subplot. * If None (the default), do not filter annotations based on secondary y-axis. To select annotations by secondary y-axis, the Figure must have been created using plotly.subplots.make_subplots. See the docstring for the specs argument to make_subplots for more info on creating subplots with secondary y-axes. **kwargs Additional property updates to apply to each selected annotation. If a property is specified in both patch and in **kwargs then the one in **kwargs takes precedence. Returns ------- self Returns the Figure object that the method was called on """ for obj in self._select_annotations_like( prop="annotations", selector=selector, row=row, col=col, secondary_y=secondary_y, ): obj.update(patch, **kwargs) return self def add_annotation( self, arg=None, align=None, arrowcolor=None, arrowhead=None, arrowside=None, arrowsize=None, arrowwidth=None, ax=None, axref=None, ay=None, ayref=None, bgcolor=None, bordercolor=None, borderpad=None, borderwidth=None, captureevents=None, clicktoshow=None, font=None, height=None, hoverlabel=None, hovertext=None, name=None, opacity=None, showarrow=None, standoff=None, startarrowhead=None, startarrowsize=None, startstandoff=None, templateitemname=None, text=None, textangle=None, valign=None, visible=None, width=None, x=None, xanchor=None, xclick=None, xref=None, xshift=None, y=None, yanchor=None, yclick=None, yref=None, yshift=None, row=None, col=None, secondary_y=None, **kwargs ): """ Create and add a new annotation to the figure's layout Parameters ---------- arg instance of Annotation or dict with compatible properties align Sets the horizontal alignment of the `text` within the box. Has an effect only if `text` spans more two or more lines (i.e. `text` contains one or more
HTML tags) or if an explicit width is set to override the text width. arrowcolor Sets the color of the annotation arrow. arrowhead Sets the end annotation arrow head style. arrowside Sets the annotation arrow head position. arrowsize Sets the size of the end annotation arrow head, relative to `arrowwidth`. A value of 1 (default) gives a head about 3x as wide as the line. arrowwidth Sets the width (in px) of annotation arrow line. ax Sets the x component of the arrow tail about the arrow head. If `axref` is `pixel`, a positive (negative) component corresponds to an arrow pointing from right to left (left to right). If `axref` is an axis, this is an absolute value on that axis, like `x`, NOT a relative value. axref Indicates in what terms the tail of the annotation (ax,ay) is specified. If `pixel`, `ax` is a relative offset in pixels from `x`. If set to an x axis id (e.g. "x" or "x2"), `ax` is specified in the same terms as that axis. This is useful for trendline annotations which should continue to indicate the correct trend when zoomed. ay Sets the y component of the arrow tail about the arrow head. If `ayref` is `pixel`, a positive (negative) component corresponds to an arrow pointing from bottom to top (top to bottom). If `ayref` is an axis, this is an absolute value on that axis, like `y`, NOT a relative value. ayref Indicates in what terms the tail of the annotation (ax,ay) is specified. If `pixel`, `ay` is a relative offset in pixels from `y`. If set to a y axis id (e.g. "y" or "y2"), `ay` is specified in the same terms as that axis. This is useful for trendline annotations which should continue to indicate the correct trend when zoomed. bgcolor Sets the background color of the annotation. bordercolor Sets the color of the border enclosing the annotation `text`. borderpad Sets the padding (in px) between the `text` and the enclosing border. borderwidth Sets the width (in px) of the border enclosing the annotation `text`. captureevents Determines whether the annotation text box captures mouse move and click events, or allows those events to pass through to data points in the plot that may be behind the annotation. By default `captureevents` is False unless `hovertext` is provided. If you use the event `plotly_clickannotation` without `hovertext` you must explicitly enable `captureevents`. clicktoshow Makes this annotation respond to clicks on the plot. If you click a data point that exactly matches the `x` and `y` values of this annotation, and it is hidden (visible: false), it will appear. In "onoff" mode, you must click the same point again to make it disappear, so if you click multiple points, you can show multiple annotations. In "onout" mode, a click anywhere else in the plot (on another data point or not) will hide this annotation. If you need to show/hide this annotation in response to different `x` or `y` values, you can set `xclick` and/or `yclick`. This is useful for example to label the side of a bar. To label markers though, `standoff` is preferred over `xclick` and `yclick`. font Sets the annotation text font. height Sets an explicit height for the text box. null (default) lets the text set the box height. Taller text will be clipped. hoverlabel plotly.graph_objects.layout.annotation.Hoverlabel instance or dict with compatible properties hovertext Sets text to appear when hovering over this annotation. If omitted or blank, no hover label will appear. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. opacity Sets the opacity of the annotation (text + arrow). showarrow Determines whether or not the annotation is drawn with an arrow. If True, `text` is placed near the arrow's tail. If False, `text` lines up with the `x` and `y` provided. standoff Sets a distance, in pixels, to move the end arrowhead away from the position it is pointing at, for example to point at the edge of a marker independent of zoom. Note that this shortens the arrow from the `ax` / `ay` vector, in contrast to `xshift` / `yshift` which moves everything by this amount. startarrowhead Sets the start annotation arrow head style. startarrowsize Sets the size of the start annotation arrow head, relative to `arrowwidth`. A value of 1 (default) gives a head about 3x as wide as the line. startstandoff Sets a distance, in pixels, to move the start arrowhead away from the position it is pointing at, for example to point at the edge of a marker independent of zoom. Note that this shortens the arrow from the `ax` / `ay` vector, in contrast to `xshift` / `yshift` which moves everything by this amount. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. text Sets the text associated with this annotation. Plotly uses a subset of HTML tags to do things like newline (
), bold (), italics (), hyperlinks (). Tags , , are also supported. textangle Sets the angle at which the `text` is drawn with respect to the horizontal. valign Sets the vertical alignment of the `text` within the box. Has an effect only if an explicit height is set to override the text height. visible Determines whether or not this annotation is visible. width Sets an explicit width for the text box. null (default) lets the text set the box width. Wider text will be clipped. There is no automatic wrapping; use
to start a new line. x Sets the annotation's x position. If the axis `type` is "log", then you must take the log of your desired range. If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. xanchor Sets the text box's horizontal position anchor This anchor binds the `x` position to the "left", "center" or "right" of the annotation. For example, if `x` is set to 1, `xref` to "paper" and `xanchor` to "right" then the right-most portion of the annotation lines up with the right-most edge of the plotting area. If "auto", the anchor is equivalent to "center" for data- referenced annotations or if there is an arrow, whereas for paper-referenced with no arrow, the anchor picked corresponds to the closest side. xclick Toggle this annotation when clicking a data point whose `x` value is `xclick` rather than the annotation's `x` value. xref Sets the annotation's x coordinate axis. If set to an x axis id (e.g. "x" or "x2"), the `x` position refers to an x coordinate If set to "paper", the `x` position refers to the distance from the left side of the plotting area in normalized coordinates where 0 (1) corresponds to the left (right) side. xshift Shifts the position of the whole annotation and arrow to the right (positive) or left (negative) by this many pixels. y Sets the annotation's y position. If the axis `type` is "log", then you must take the log of your desired range. If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. yanchor Sets the text box's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the annotation. For example, if `y` is set to 1, `yref` to "paper" and `yanchor` to "top" then the top-most portion of the annotation lines up with the top-most edge of the plotting area. If "auto", the anchor is equivalent to "middle" for data-referenced annotations or if there is an arrow, whereas for paper- referenced with no arrow, the anchor picked corresponds to the closest side. yclick Toggle this annotation when clicking a data point whose `y` value is `yclick` rather than the annotation's `y` value. yref Sets the annotation's y coordinate axis. If set to an y axis id (e.g. "y" or "y2"), the `y` position refers to an y coordinate If set to "paper", the `y` position refers to the distance from the bottom of the plotting area in normalized coordinates where 0 (1) corresponds to the bottom (top). yshift Shifts the position of the whole annotation and arrow up (positive) or down (negative) by this many pixels. row Subplot row for annotation col Subplot column for annotation secondary_y Whether to add annotation to secondary y-axis Returns ------- FigureWidget """ new_obj = _layout.Annotation( arg, align=align, arrowcolor=arrowcolor, arrowhead=arrowhead, arrowside=arrowside, arrowsize=arrowsize, arrowwidth=arrowwidth, ax=ax, axref=axref, ay=ay, ayref=ayref, bgcolor=bgcolor, bordercolor=bordercolor, borderpad=borderpad, borderwidth=borderwidth, captureevents=captureevents, clicktoshow=clicktoshow, font=font, height=height, hoverlabel=hoverlabel, hovertext=hovertext, name=name, opacity=opacity, showarrow=showarrow, standoff=standoff, startarrowhead=startarrowhead, startarrowsize=startarrowsize, startstandoff=startstandoff, templateitemname=templateitemname, text=text, textangle=textangle, valign=valign, visible=visible, width=width, x=x, xanchor=xanchor, xclick=xclick, xref=xref, xshift=xshift, y=y, yanchor=yanchor, yclick=yclick, yref=yref, yshift=yshift, **kwargs ) return self._add_annotation_like( "annotation", "annotations", new_obj, row=row, col=col, secondary_y=secondary_y, ) def select_layout_images(self, selector=None, row=None, col=None, secondary_y=None): """ Select images from a particular subplot cell and/or images that satisfy custom selection criteria. Parameters ---------- selector: dict or None (default None) Dict to use as selection criteria. Annotations will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all images are selected. row, col: int or None (default None) Subplot row and column index of images to select. To select images by row and column, the Figure must have been created using plotly.subplots.make_subplots. To select only those image that are in paper coordinates, set row and col to the string 'paper'. If None (the default), all images are selected. secondary_y: boolean or None (default None) * If True, only select images associated with the secondary y-axis of the subplot. * If False, only select images associated with the primary y-axis of the subplot. * If None (the default), do not filter images based on secondary y-axis. To select images by secondary y-axis, the Figure must have been created using plotly.subplots.make_subplots. See the docstring for the specs argument to make_subplots for more info on creating subplots with secondary y-axes. Returns ------- generator Generator that iterates through all of the images that satisfy all of the specified selection criteria """ return self._select_annotations_like( "images", selector=selector, row=row, col=col, secondary_y=secondary_y ) def for_each_layout_image( self, fn, selector=None, row=None, col=None, secondary_y=None ): """ Apply a function to all images that satisfy the specified selection criteria Parameters ---------- fn: Function that inputs a single image object. selector: dict or None (default None) Dict to use as selection criteria. Traces will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all images are selected. row, col: int or None (default None) Subplot row and column index of images to select. To select images by row and column, the Figure must have been created using plotly.subplots.make_subplots. To select only those images that are in paper coordinates, set row and col to the string 'paper'. If None (the default), all images are selected. secondary_y: boolean or None (default None) * If True, only select images associated with the secondary y-axis of the subplot. * If False, only select images associated with the primary y-axis of the subplot. * If None (the default), do not filter images based on secondary y-axis. To select images by secondary y-axis, the Figure must have been created using plotly.subplots.make_subplots. See the docstring for the specs argument to make_subplots for more info on creating subplots with secondary y-axes. Returns ------- self Returns the Figure object that the method was called on """ for obj in self._select_annotations_like( prop="images", selector=selector, row=row, col=col, secondary_y=secondary_y, ): fn(obj) return self def update_layout_images( self, patch, selector=None, row=None, col=None, secondary_y=None, **kwargs ): """ Perform a property update operation on all images that satisfy the specified selection criteria Parameters ---------- patch: dict or None (default None) Dictionary of property updates to be applied to all images that satisfy the selection criteria. selector: dict or None (default None) Dict to use as selection criteria. Traces will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all images are selected. row, col: int or None (default None) Subplot row and column index of images to select. To select images by row and column, the Figure must have been created using plotly.subplots.make_subplots. To select only those image that are in paper coordinates, set row and col to the string 'paper'. If None (the default), all images are selected. secondary_y: boolean or None (default None) * If True, only select images associated with the secondary y-axis of the subplot. * If False, only select images associated with the primary y-axis of the subplot. * If None (the default), do not filter images based on secondary y-axis. To select images by secondary y-axis, the Figure must have been created using plotly.subplots.make_subplots. See the docstring for the specs argument to make_subplots for more info on creating subplots with secondary y-axes. **kwargs Additional property updates to apply to each selected image. If a property is specified in both patch and in **kwargs then the one in **kwargs takes precedence. Returns ------- self Returns the Figure object that the method was called on """ for obj in self._select_annotations_like( prop="images", selector=selector, row=row, col=col, secondary_y=secondary_y, ): obj.update(patch, **kwargs) return self def add_layout_image( self, arg=None, layer=None, name=None, opacity=None, sizex=None, sizey=None, sizing=None, source=None, templateitemname=None, visible=None, x=None, xanchor=None, xref=None, y=None, yanchor=None, yref=None, row=None, col=None, secondary_y=None, **kwargs ): """ Create and add a new image to the figure's layout Parameters ---------- arg instance of Image or dict with compatible properties layer Specifies whether images are drawn below or above traces. When `xref` and `yref` are both set to `paper`, image is drawn below the entire plot area. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. opacity Sets the opacity of the image. sizex Sets the image container size horizontally. The image will be sized based on the `position` value. When `xref` is set to `paper`, units are sized relative to the plot width. sizey Sets the image container size vertically. The image will be sized based on the `position` value. When `yref` is set to `paper`, units are sized relative to the plot height. sizing Specifies which dimension of the image to constrain. source Specifies the URL of the image to be used. The URL must be accessible from the domain where the plot code is run, and can be either relative or absolute. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. visible Determines whether or not this image is visible. x Sets the image's x position. When `xref` is set to `paper`, units are sized relative to the plot height. See `xref` for more info xanchor Sets the anchor for the x position xref Sets the images's x coordinate axis. If set to a x axis id (e.g. "x" or "x2"), the `x` position refers to an x data coordinate If set to "paper", the `x` position refers to the distance from the left of plot in normalized coordinates where 0 (1) corresponds to the left (right). y Sets the image's y position. When `yref` is set to `paper`, units are sized relative to the plot height. See `yref` for more info yanchor Sets the anchor for the y position. yref Sets the images's y coordinate axis. If set to a y axis id (e.g. "y" or "y2"), the `y` position refers to a y data coordinate. If set to "paper", the `y` position refers to the distance from the bottom of the plot in normalized coordinates where 0 (1) corresponds to the bottom (top). row Subplot row for image col Subplot column for image secondary_y Whether to add image to secondary y-axis Returns ------- FigureWidget """ new_obj = _layout.Image( arg, layer=layer, name=name, opacity=opacity, sizex=sizex, sizey=sizey, sizing=sizing, source=source, templateitemname=templateitemname, visible=visible, x=x, xanchor=xanchor, xref=xref, y=y, yanchor=yanchor, yref=yref, **kwargs ) return self._add_annotation_like( "image", "images", new_obj, row=row, col=col, secondary_y=secondary_y, ) def select_shapes(self, selector=None, row=None, col=None, secondary_y=None): """ Select shapes from a particular subplot cell and/or shapes that satisfy custom selection criteria. Parameters ---------- selector: dict or None (default None) Dict to use as selection criteria. Annotations will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all shapes are selected. row, col: int or None (default None) Subplot row and column index of shapes to select. To select shapes by row and column, the Figure must have been created using plotly.subplots.make_subplots. To select only those shape that are in paper coordinates, set row and col to the string 'paper'. If None (the default), all shapes are selected. secondary_y: boolean or None (default None) * If True, only select shapes associated with the secondary y-axis of the subplot. * If False, only select shapes associated with the primary y-axis of the subplot. * If None (the default), do not filter shapes based on secondary y-axis. To select shapes by secondary y-axis, the Figure must have been created using plotly.subplots.make_subplots. See the docstring for the specs argument to make_subplots for more info on creating subplots with secondary y-axes. Returns ------- generator Generator that iterates through all of the shapes that satisfy all of the specified selection criteria """ return self._select_annotations_like( "shapes", selector=selector, row=row, col=col, secondary_y=secondary_y ) def for_each_shape(self, fn, selector=None, row=None, col=None, secondary_y=None): """ Apply a function to all shapes that satisfy the specified selection criteria Parameters ---------- fn: Function that inputs a single shape object. selector: dict or None (default None) Dict to use as selection criteria. Traces will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all shapes are selected. row, col: int or None (default None) Subplot row and column index of shapes to select. To select shapes by row and column, the Figure must have been created using plotly.subplots.make_subplots. To select only those shapes that are in paper coordinates, set row and col to the string 'paper'. If None (the default), all shapes are selected. secondary_y: boolean or None (default None) * If True, only select shapes associated with the secondary y-axis of the subplot. * If False, only select shapes associated with the primary y-axis of the subplot. * If None (the default), do not filter shapes based on secondary y-axis. To select shapes by secondary y-axis, the Figure must have been created using plotly.subplots.make_subplots. See the docstring for the specs argument to make_subplots for more info on creating subplots with secondary y-axes. Returns ------- self Returns the Figure object that the method was called on """ for obj in self._select_annotations_like( prop="shapes", selector=selector, row=row, col=col, secondary_y=secondary_y, ): fn(obj) return self def update_shapes( self, patch, selector=None, row=None, col=None, secondary_y=None, **kwargs ): """ Perform a property update operation on all shapes that satisfy the specified selection criteria Parameters ---------- patch: dict or None (default None) Dictionary of property updates to be applied to all shapes that satisfy the selection criteria. selector: dict or None (default None) Dict to use as selection criteria. Traces will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all shapes are selected. row, col: int or None (default None) Subplot row and column index of shapes to select. To select shapes by row and column, the Figure must have been created using plotly.subplots.make_subplots. To select only those shape that are in paper coordinates, set row and col to the string 'paper'. If None (the default), all shapes are selected. secondary_y: boolean or None (default None) * If True, only select shapes associated with the secondary y-axis of the subplot. * If False, only select shapes associated with the primary y-axis of the subplot. * If None (the default), do not filter shapes based on secondary y-axis. To select shapes by secondary y-axis, the Figure must have been created using plotly.subplots.make_subplots. See the docstring for the specs argument to make_subplots for more info on creating subplots with secondary y-axes. **kwargs Additional property updates to apply to each selected shape. If a property is specified in both patch and in **kwargs then the one in **kwargs takes precedence. Returns ------- self Returns the Figure object that the method was called on """ for obj in self._select_annotations_like( prop="shapes", selector=selector, row=row, col=col, secondary_y=secondary_y, ): obj.update(patch, **kwargs) return self def add_shape( self, arg=None, fillcolor=None, layer=None, line=None, name=None, opacity=None, path=None, templateitemname=None, type=None, visible=None, x0=None, x1=None, xanchor=None, xref=None, xsizemode=None, y0=None, y1=None, yanchor=None, yref=None, ysizemode=None, row=None, col=None, secondary_y=None, **kwargs ): """ Create and add a new shape to the figure's layout Parameters ---------- arg instance of Shape or dict with compatible properties fillcolor Sets the color filling the shape's interior. layer Specifies whether shapes are drawn below or above traces. line plotly.graph_objects.layout.shape.Line instance or dict with compatible properties name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. opacity Sets the opacity of the shape. path For `type` "path" - a valid SVG path with the pixel values replaced by data values in `xsizemode`/`ysizemode` being "scaled" and taken unmodified as pixels relative to `xanchor` and `yanchor` in case of "pixel" size mode. There are a few restrictions / quirks only absolute instructions, not relative. So the allowed segments are: M, L, H, V, Q, C, T, S, and Z arcs (A) are not allowed because radius rx and ry are relative. In the future we could consider supporting relative commands, but we would have to decide on how to handle date and log axes. Note that even as is, Q and C Bezier paths that are smooth on linear axes may not be smooth on log, and vice versa. no chained "polybezier" commands - specify the segment type for each one. On category axes, values are numbers scaled to the serial numbers of categories because using the categories themselves there would be no way to describe fractional positions On data axes: because space and T are both normal components of path strings, we can't use either to separate date from time parts. Therefore we'll use underscore for this purpose: 2015-02-21_13:45:56.789 templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. type Specifies the shape type to be drawn. If "line", a line is drawn from (`x0`,`y0`) to (`x1`,`y1`) with respect to the axes' sizing mode. If "circle", a circle is drawn from ((`x0`+`x1`)/2, (`y0`+`y1`)/2)) with radius (|(`x0`+`x1`)/2 - `x0`|, |(`y0`+`y1`)/2 -`y0`)|) with respect to the axes' sizing mode. If "rect", a rectangle is drawn linking (`x0`,`y0`), (`x1`,`y0`), (`x1`,`y1`), (`x0`,`y1`), (`x0`,`y0`) with respect to the axes' sizing mode. If "path", draw a custom SVG path using `path`. with respect to the axes' sizing mode. visible Determines whether or not this shape is visible. x0 Sets the shape's starting x position. See `type` and `xsizemode` for more info. x1 Sets the shape's end x position. See `type` and `xsizemode` for more info. xanchor Only relevant in conjunction with `xsizemode` set to "pixel". Specifies the anchor point on the x axis to which `x0`, `x1` and x coordinates within `path` are relative to. E.g. useful to attach a pixel sized shape to a certain data value. No effect when `xsizemode` not set to "pixel". xref Sets the shape's x coordinate axis. If set to an x axis id (e.g. "x" or "x2"), the `x` position refers to an x coordinate. If set to "paper", the `x` position refers to the distance from the left side of the plotting area in normalized coordinates where 0 (1) corresponds to the left (right) side. If the axis `type` is "log", then you must take the log of your desired range. If the axis `type` is "date", then you must convert the date to unix time in milliseconds. xsizemode Sets the shapes's sizing mode along the x axis. If set to "scaled", `x0`, `x1` and x coordinates within `path` refer to data values on the x axis or a fraction of the plot area's width (`xref` set to "paper"). If set to "pixel", `xanchor` specifies the x position in terms of data or plot fraction but `x0`, `x1` and x coordinates within `path` are pixels relative to `xanchor`. This way, the shape can have a fixed width while maintaining a position relative to data or plot fraction. y0 Sets the shape's starting y position. See `type` and `ysizemode` for more info. y1 Sets the shape's end y position. See `type` and `ysizemode` for more info. yanchor Only relevant in conjunction with `ysizemode` set to "pixel". Specifies the anchor point on the y axis to which `y0`, `y1` and y coordinates within `path` are relative to. E.g. useful to attach a pixel sized shape to a certain data value. No effect when `ysizemode` not set to "pixel". yref Sets the annotation's y coordinate axis. If set to an y axis id (e.g. "y" or "y2"), the `y` position refers to an y coordinate If set to "paper", the `y` position refers to the distance from the bottom of the plotting area in normalized coordinates where 0 (1) corresponds to the bottom (top). ysizemode Sets the shapes's sizing mode along the y axis. If set to "scaled", `y0`, `y1` and y coordinates within `path` refer to data values on the y axis or a fraction of the plot area's height (`yref` set to "paper"). If set to "pixel", `yanchor` specifies the y position in terms of data or plot fraction but `y0`, `y1` and y coordinates within `path` are pixels relative to `yanchor`. This way, the shape can have a fixed height while maintaining a position relative to data or plot fraction. row Subplot row for shape col Subplot column for shape secondary_y Whether to add shape to secondary y-axis Returns ------- FigureWidget """ new_obj = _layout.Shape( arg, fillcolor=fillcolor, layer=layer, line=line, name=name, opacity=opacity, path=path, templateitemname=templateitemname, type=type, visible=visible, x0=x0, x1=x1, xanchor=xanchor, xref=xref, xsizemode=xsizemode, y0=y0, y1=y1, yanchor=yanchor, yref=yref, ysizemode=ysizemode, **kwargs ) return self._add_annotation_like( "shape", "shapes", new_obj, row=row, col=col, secondary_y=secondary_y, ) plotly-4.4.1+dfsg.orig/plotly/graph_objs/pointcloud/0000755000175000017500000000000013573746613022111 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/pointcloud/hoverlabel/0000755000175000017500000000000013573746613024234 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/pointcloud/hoverlabel/__init__.py0000644000175000017500000002545713573721550026353 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "pointcloud.hoverlabel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Font object Sets the font used in hover labels. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.pointcloud.hoverlabel.Font color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.pointcloud.hoverlabel.Font constructor must be a dict or an instance of plotly.graph_objs.pointcloud.hoverlabel.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.pointcloud.hoverlabel import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["colorsrc"] = v_font.ColorsrcValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["familysrc"] = v_font.FamilysrcValidator() self._validators["size"] = v_font.SizeValidator() self._validators["sizesrc"] = v_font.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/pointcloud/marker/0000755000175000017500000000000013573746613023372 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/pointcloud/marker/__init__.py0000644000175000017500000001443613573721550025504 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Border(_BaseTraceHierarchyType): # arearatio # --------- @property def arearatio(self): """ Specifies what fraction of the marker area is covered with the border. The 'arearatio' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["arearatio"] @arearatio.setter def arearatio(self, val): self["arearatio"] = val # color # ----- @property def color(self): """ Sets the stroke color. It accepts a specific color. If the color is not fully opaque and there are hundreds of thousands of points, it may cause slower zooming and panning. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "pointcloud.marker" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ arearatio Specifies what fraction of the marker area is covered with the border. color Sets the stroke color. It accepts a specific color. If the color is not fully opaque and there are hundreds of thousands of points, it may cause slower zooming and panning. """ def __init__(self, arg=None, arearatio=None, color=None, **kwargs): """ Construct a new Border object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.pointcloud.marker.Border arearatio Specifies what fraction of the marker area is covered with the border. color Sets the stroke color. It accepts a specific color. If the color is not fully opaque and there are hundreds of thousands of points, it may cause slower zooming and panning. Returns ------- Border """ super(Border, self).__init__("border") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.pointcloud.marker.Border constructor must be a dict or an instance of plotly.graph_objs.pointcloud.marker.Border""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.pointcloud.marker import border as v_border # Initialize validators # --------------------- self._validators["arearatio"] = v_border.ArearatioValidator() self._validators["color"] = v_border.ColorValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("arearatio", None) self["arearatio"] = arearatio if arearatio is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Border"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/pointcloud/__init__.py0000644000175000017500000010217713573721550024223 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Stream(_BaseTraceHierarchyType): # maxpoints # --------- @property def maxpoints(self): """ Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. The 'maxpoints' property is a number and may be specified as: - An int or float in the interval [0, 10000] Returns ------- int|float """ return self["maxpoints"] @maxpoints.setter def maxpoints(self, val): self["maxpoints"] = val # token # ----- @property def token(self): """ The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. The 'token' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["token"] @token.setter def token(self, val): self["token"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "pointcloud" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """ def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): """ Construct a new Stream object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.pointcloud.Stream maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- Stream """ super(Stream, self).__init__("stream") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.pointcloud.Stream constructor must be a dict or an instance of plotly.graph_objs.pointcloud.Stream""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.pointcloud import stream as v_stream # Initialize validators # --------------------- self._validators["maxpoints"] = v_stream.MaxpointsValidator() self._validators["token"] = v_stream.TokenValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("maxpoints", None) self["maxpoints"] = maxpoints if maxpoints is not None else _v _v = arg.pop("token", None) self["token"] = token if token is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # blend # ----- @property def blend(self): """ Determines if colors are blended together for a translucency effect in case `opacity` is specified as a value less then `1`. Setting `blend` to `true` reduces zoom/pan speed if used with large numbers of points. The 'blend' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["blend"] @blend.setter def blend(self, val): self["blend"] = val # border # ------ @property def border(self): """ The 'border' property is an instance of Border that may be specified as: - An instance of plotly.graph_objs.pointcloud.marker.Border - A dict of string/value properties that will be passed to the Border constructor Supported dict properties: arearatio Specifies what fraction of the marker area is covered with the border. color Sets the stroke color. It accepts a specific color. If the color is not fully opaque and there are hundreds of thousands of points, it may cause slower zooming and panning. Returns ------- plotly.graph_objs.pointcloud.marker.Border """ return self["border"] @border.setter def border(self, val): self["border"] = val # color # ----- @property def color(self): """ Sets the marker fill color. It accepts a specific color.If the color is not fully opaque and there are hundreds of thousandsof points, it may cause slower zooming and panning. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # opacity # ------- @property def opacity(self): """ Sets the marker opacity. The default value is `1` (fully opaque). If the markers are not fully opaque and there are hundreds of thousands of points, it may cause slower zooming and panning. Opacity fades the color even if `blend` is left on `false` even if there is no translucency effect in that case. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # sizemax # ------- @property def sizemax(self): """ Sets the maximum size (in px) of the rendered marker points. Effective when the `pointcloud` shows only few points. The 'sizemax' property is a number and may be specified as: - An int or float in the interval [0.1, inf] Returns ------- int|float """ return self["sizemax"] @sizemax.setter def sizemax(self, val): self["sizemax"] = val # sizemin # ------- @property def sizemin(self): """ Sets the minimum size (in px) of the rendered marker points, effective when the `pointcloud` shows a million or more points. The 'sizemin' property is a number and may be specified as: - An int or float in the interval [0.1, 2] Returns ------- int|float """ return self["sizemin"] @sizemin.setter def sizemin(self, val): self["sizemin"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "pointcloud" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ blend Determines if colors are blended together for a translucency effect in case `opacity` is specified as a value less then `1`. Setting `blend` to `true` reduces zoom/pan speed if used with large numbers of points. border plotly.graph_objects.pointcloud.marker.Border instance or dict with compatible properties color Sets the marker fill color. It accepts a specific color.If the color is not fully opaque and there are hundreds of thousandsof points, it may cause slower zooming and panning. opacity Sets the marker opacity. The default value is `1` (fully opaque). If the markers are not fully opaque and there are hundreds of thousands of points, it may cause slower zooming and panning. Opacity fades the color even if `blend` is left on `false` even if there is no translucency effect in that case. sizemax Sets the maximum size (in px) of the rendered marker points. Effective when the `pointcloud` shows only few points. sizemin Sets the minimum size (in px) of the rendered marker points, effective when the `pointcloud` shows a million or more points. """ def __init__( self, arg=None, blend=None, border=None, color=None, opacity=None, sizemax=None, sizemin=None, **kwargs ): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.pointcloud.Marker blend Determines if colors are blended together for a translucency effect in case `opacity` is specified as a value less then `1`. Setting `blend` to `true` reduces zoom/pan speed if used with large numbers of points. border plotly.graph_objects.pointcloud.marker.Border instance or dict with compatible properties color Sets the marker fill color. It accepts a specific color.If the color is not fully opaque and there are hundreds of thousandsof points, it may cause slower zooming and panning. opacity Sets the marker opacity. The default value is `1` (fully opaque). If the markers are not fully opaque and there are hundreds of thousands of points, it may cause slower zooming and panning. Opacity fades the color even if `blend` is left on `false` even if there is no translucency effect in that case. sizemax Sets the maximum size (in px) of the rendered marker points. Effective when the `pointcloud` shows only few points. sizemin Sets the minimum size (in px) of the rendered marker points, effective when the `pointcloud` shows a million or more points. Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.pointcloud.Marker constructor must be a dict or an instance of plotly.graph_objs.pointcloud.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.pointcloud import marker as v_marker # Initialize validators # --------------------- self._validators["blend"] = v_marker.BlendValidator() self._validators["border"] = v_marker.BorderValidator() self._validators["color"] = v_marker.ColorValidator() self._validators["opacity"] = v_marker.OpacityValidator() self._validators["sizemax"] = v_marker.SizemaxValidator() self._validators["sizemin"] = v_marker.SizeminValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("blend", None) self["blend"] = blend if blend is not None else _v _v = arg.pop("border", None) self["border"] = border if border is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("sizemax", None) self["sizemax"] = sizemax if sizemax is not None else _v _v = arg.pop("sizemin", None) self["sizemin"] = sizemin if sizemin is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Hoverlabel(_BaseTraceHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'right', 'auto'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["align"] @align.setter def align(self, val): self["align"] = val # alignsrc # -------- @property def alignsrc(self): """ Sets the source reference on plot.ly for align . The 'alignsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["alignsrc"] @alignsrc.setter def alignsrc(self, val): self["alignsrc"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the hover labels for this trace The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bgcolorsrc # ---------- @property def bgcolorsrc(self): """ Sets the source reference on plot.ly for bgcolor . The 'bgcolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bgcolorsrc"] @bgcolorsrc.setter def bgcolorsrc(self, val): self["bgcolorsrc"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the border color of the hover labels for this trace. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # bordercolorsrc # -------------- @property def bordercolorsrc(self): """ Sets the source reference on plot.ly for bordercolor . The 'bordercolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bordercolorsrc"] @bordercolorsrc.setter def bordercolorsrc(self, val): self["bordercolorsrc"] = val # font # ---- @property def font(self): """ Sets the font used in hover labels. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.pointcloud.hoverlabel.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.pointcloud.hoverlabel.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # namelength # ---------- @property def namelength(self): """ Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. The 'namelength' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [-1, 9223372036854775807] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|numpy.ndarray """ return self["namelength"] @namelength.setter def namelength(self, val): self["namelength"] = val # namelengthsrc # ------------- @property def namelengthsrc(self): """ Sets the source reference on plot.ly for namelength . The 'namelengthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["namelengthsrc"] @namelengthsrc.setter def namelengthsrc(self, val): self["namelengthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "pointcloud" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """ def __init__( self, arg=None, align=None, alignsrc=None, bgcolor=None, bgcolorsrc=None, bordercolor=None, bordercolorsrc=None, font=None, namelength=None, namelengthsrc=None, **kwargs ): """ Construct a new Hoverlabel object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.pointcloud.Hoverlabel align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- Hoverlabel """ super(Hoverlabel, self).__init__("hoverlabel") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.pointcloud.Hoverlabel constructor must be a dict or an instance of plotly.graph_objs.pointcloud.Hoverlabel""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.pointcloud import hoverlabel as v_hoverlabel # Initialize validators # --------------------- self._validators["align"] = v_hoverlabel.AlignValidator() self._validators["alignsrc"] = v_hoverlabel.AlignsrcValidator() self._validators["bgcolor"] = v_hoverlabel.BgcolorValidator() self._validators["bgcolorsrc"] = v_hoverlabel.BgcolorsrcValidator() self._validators["bordercolor"] = v_hoverlabel.BordercolorValidator() self._validators["bordercolorsrc"] = v_hoverlabel.BordercolorsrcValidator() self._validators["font"] = v_hoverlabel.FontValidator() self._validators["namelength"] = v_hoverlabel.NamelengthValidator() self._validators["namelengthsrc"] = v_hoverlabel.NamelengthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("alignsrc", None) self["alignsrc"] = alignsrc if alignsrc is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bgcolorsrc", None) self["bgcolorsrc"] = bgcolorsrc if bgcolorsrc is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("bordercolorsrc", None) self["bordercolorsrc"] = bordercolorsrc if bordercolorsrc is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("namelength", None) self["namelength"] = namelength if namelength is not None else _v _v = arg.pop("namelengthsrc", None) self["namelengthsrc"] = namelengthsrc if namelengthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Hoverlabel", "Marker", "Stream", "hoverlabel", "marker"] from plotly.graph_objs.pointcloud import marker from plotly.graph_objs.pointcloud import hoverlabel plotly-4.4.1+dfsg.orig/plotly/graph_objs/scattercarpet/0000755000175000017500000000000013573746613022575 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scattercarpet/unselected/0000755000175000017500000000000013573746613024730 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scattercarpet/unselected/__init__.py0000644000175000017500000002772613573721551027051 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Textfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the text font color of unselected points, applied only when a selection exists. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattercarpet.unselected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the text font color of unselected points, applied only when a selection exists. """ def __init__(self, arg=None, color=None, **kwargs): """ Construct a new Textfont object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattercarpet.unselected.Textfont color Sets the text font color of unselected points, applied only when a selection exists. Returns ------- Textfont """ super(Textfont, self).__init__("textfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattercarpet.unselected.Textfont constructor must be a dict or an instance of plotly.graph_objs.scattercarpet.unselected.Textfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattercarpet.unselected import textfont as v_textfont # Initialize validators # --------------------- self._validators["color"] = v_textfont.ColorValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the marker color of unselected points, applied only when a selection exists. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # opacity # ------- @property def opacity(self): """ Sets the marker opacity of unselected points, applied only when a selection exists. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # size # ---- @property def size(self): """ Sets the marker size of unselected points, applied only when a selection exists. The 'size' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattercarpet.unselected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. size Sets the marker size of unselected points, applied only when a selection exists. """ def __init__(self, arg=None, color=None, opacity=None, size=None, **kwargs): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattercarpet.unselected.Marker color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. size Sets the marker size of unselected points, applied only when a selection exists. Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattercarpet.unselected.Marker constructor must be a dict or an instance of plotly.graph_objs.scattercarpet.unselected.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattercarpet.unselected import marker as v_marker # Initialize validators # --------------------- self._validators["color"] = v_marker.ColorValidator() self._validators["opacity"] = v_marker.OpacityValidator() self._validators["size"] = v_marker.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Marker", "Textfont"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/scattercarpet/hoverlabel/0000755000175000017500000000000013573746613024720 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scattercarpet/hoverlabel/__init__.py0000644000175000017500000002547613573721551027041 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattercarpet.hoverlabel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Font object Sets the font used in hover labels. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattercarpet.hoverlabel.Font color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattercarpet.hoverlabel.Font constructor must be a dict or an instance of plotly.graph_objs.scattercarpet.hoverlabel.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattercarpet.hoverlabel import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["colorsrc"] = v_font.ColorsrcValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["familysrc"] = v_font.FamilysrcValidator() self._validators["size"] = v_font.SizeValidator() self._validators["sizesrc"] = v_font.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/scattercarpet/marker/0000755000175000017500000000000013573746613024056 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scattercarpet/marker/colorbar/0000755000175000017500000000000013573746613025661 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scattercarpet/marker/colorbar/title/0000755000175000017500000000000013573746613027002 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scattercarpet/marker/colorbar/title/__init__.py0000644000175000017500000002062713573721551031114 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattercarpet.marker.colorbar.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattercarpet.marker.c olorbar.title.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattercarpet.marker.colorbar.title.Font constructor must be a dict or an instance of plotly.graph_objs.scattercarpet.marker.colorbar.title.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattercarpet.marker.colorbar.title import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/scattercarpet/marker/colorbar/__init__.py0000644000175000017500000006116313573721551027773 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Title(_BaseTraceHierarchyType): # font # ---- @property def font(self): """ Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.scattercarpet.marker.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.scattercarpet.marker.colorbar.title.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # side # ---- @property def side(self): """ Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- Any """ return self["side"] @side.setter def side(self, val): self["side"] = val # text # ---- @property def text(self): """ Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattercarpet.marker.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """ def __init__(self, arg=None, font=None, side=None, text=None, **kwargs): """ Construct a new Title object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattercarpet.marker.colorbar.Title font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- Title """ super(Title, self).__init__("title") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattercarpet.marker.colorbar.Title constructor must be a dict or an instance of plotly.graph_objs.scattercarpet.marker.colorbar.Title""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattercarpet.marker.colorbar import title as v_title # Initialize validators # --------------------- self._validators["font"] = v_title.FontValidator() self._validators["side"] = v_title.SideValidator() self._validators["text"] = v_title.TextValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("side", None) self["side"] = side if side is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickformatstop(_BaseTraceHierarchyType): # dtickrange # ---------- @property def dtickrange(self): """ range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" The 'dtickrange' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'dtickrange[0]' property accepts values of any type (1) The 'dtickrange[1]' property accepts values of any type Returns ------- list """ return self["dtickrange"] @dtickrange.setter def dtickrange(self, val): self["dtickrange"] = val # enabled # ------- @property def enabled(self): """ Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. The 'enabled' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["enabled"] @enabled.setter def enabled(self, val): self["enabled"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # value # ----- @property def value(self): """ string - dtickformat for described zoom level, the same as "tickformat" The 'value' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattercarpet.marker.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """ def __init__( self, arg=None, dtickrange=None, enabled=None, name=None, templateitemname=None, value=None, **kwargs ): """ Construct a new Tickformatstop object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattercarpet.marker.c olorbar.Tickformatstop dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- Tickformatstop """ super(Tickformatstop, self).__init__("tickformatstops") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattercarpet.marker.colorbar.Tickformatstop constructor must be a dict or an instance of plotly.graph_objs.scattercarpet.marker.colorbar.Tickformatstop""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattercarpet.marker.colorbar import ( tickformatstop as v_tickformatstop, ) # Initialize validators # --------------------- self._validators["dtickrange"] = v_tickformatstop.DtickrangeValidator() self._validators["enabled"] = v_tickformatstop.EnabledValidator() self._validators["name"] = v_tickformatstop.NameValidator() self._validators[ "templateitemname" ] = v_tickformatstop.TemplateitemnameValidator() self._validators["value"] = v_tickformatstop.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtickrange", None) self["dtickrange"] = dtickrange if dtickrange is not None else _v _v = arg.pop("enabled", None) self["enabled"] = enabled if enabled is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattercarpet.marker.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Tickfont object Sets the color bar's tick label font Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattercarpet.marker.c olorbar.Tickfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Tickfont """ super(Tickfont, self).__init__("tickfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattercarpet.marker.colorbar.Tickfont constructor must be a dict or an instance of plotly.graph_objs.scattercarpet.marker.colorbar.Tickfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattercarpet.marker.colorbar import ( tickfont as v_tickfont, ) # Initialize validators # --------------------- self._validators["color"] = v_tickfont.ColorValidator() self._validators["family"] = v_tickfont.FamilyValidator() self._validators["size"] = v_tickfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Tickfont", "Tickformatstop", "Tickformatstop", "Title", "title"] from plotly.graph_objs.scattercarpet.marker.colorbar import title plotly-4.4.1+dfsg.orig/plotly/graph_objs/scattercarpet/marker/__init__.py0000644000175000017500000031032113573721552026162 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # autocolorscale # -------------- @property def autocolorscale(self): """ Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. The 'autocolorscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocolorscale"] @autocolorscale.setter def autocolorscale(self, val): self["autocolorscale"] = val # cauto # ----- @property def cauto(self): """ Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. The 'cauto' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["cauto"] @cauto.setter def cauto(self, val): self["cauto"] = val # cmax # ---- @property def cmax(self): """ Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. The 'cmax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmax"] @cmax.setter def cmax(self, val): self["cmax"] = val # cmid # ---- @property def cmid(self): """ Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. The 'cmid' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmid"] @cmid.setter def cmid(self, val): self["cmid"] = val # cmin # ---- @property def cmin(self): """ Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. The 'cmin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmin"] @cmin.setter def cmin(self, val): self["cmin"] = val # color # ----- @property def color(self): """ Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A number that will be interpreted as a color according to scattercarpet.marker.line.colorscale - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # coloraxis # --------- @property def coloraxis(self): """ Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. The 'coloraxis' property is an identifier of a particular subplot, of type 'coloraxis', that may be specified as the string 'coloraxis' optionally followed by an integer >= 1 (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) Returns ------- str """ return self["coloraxis"] @coloraxis.setter def coloraxis(self, val): self["coloraxis"] = val # colorscale # ---------- @property def colorscale(self): """ Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,Earth,Electric,Vi ridis,Cividis. The 'colorscale' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # reversescale # ------------ @property def reversescale(self): """ Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. The 'reversescale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["reversescale"] @reversescale.setter def reversescale(self, val): self["reversescale"] = val # width # ----- @property def width(self): """ Sets the width (in px) of the lines bounding the marker points. The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["width"] @width.setter def width(self, val): self["width"] = val # widthsrc # -------- @property def widthsrc(self): """ Sets the source reference on plot.ly for width . The 'widthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["widthsrc"] @widthsrc.setter def widthsrc(self, val): self["widthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattercarpet.marker" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . """ def __init__( self, arg=None, autocolorscale=None, cauto=None, cmax=None, cmid=None, cmin=None, color=None, coloraxis=None, colorscale=None, colorsrc=None, reversescale=None, width=None, widthsrc=None, **kwargs ): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattercarpet.marker.Line autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattercarpet.marker.Line constructor must be a dict or an instance of plotly.graph_objs.scattercarpet.marker.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattercarpet.marker import line as v_line # Initialize validators # --------------------- self._validators["autocolorscale"] = v_line.AutocolorscaleValidator() self._validators["cauto"] = v_line.CautoValidator() self._validators["cmax"] = v_line.CmaxValidator() self._validators["cmid"] = v_line.CmidValidator() self._validators["cmin"] = v_line.CminValidator() self._validators["color"] = v_line.ColorValidator() self._validators["coloraxis"] = v_line.ColoraxisValidator() self._validators["colorscale"] = v_line.ColorscaleValidator() self._validators["colorsrc"] = v_line.ColorsrcValidator() self._validators["reversescale"] = v_line.ReversescaleValidator() self._validators["width"] = v_line.WidthValidator() self._validators["widthsrc"] = v_line.WidthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autocolorscale", None) self["autocolorscale"] = autocolorscale if autocolorscale is not None else _v _v = arg.pop("cauto", None) self["cauto"] = cauto if cauto is not None else _v _v = arg.pop("cmax", None) self["cmax"] = cmax if cmax is not None else _v _v = arg.pop("cmid", None) self["cmid"] = cmid if cmid is not None else _v _v = arg.pop("cmin", None) self["cmin"] = cmin if cmin is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("coloraxis", None) self["coloraxis"] = coloraxis if coloraxis is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("reversescale", None) self["reversescale"] = reversescale if reversescale is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v _v = arg.pop("widthsrc", None) self["widthsrc"] = widthsrc if widthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Gradient(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the final color of the gradient fill: the center color for radial, the right for horizontal, or the bottom for vertical. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # type # ---- @property def type(self): """ Sets the type of gradient used to fill the markers The 'type' property is an enumeration that may be specified as: - One of the following enumeration values: ['radial', 'horizontal', 'vertical', 'none'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["type"] @type.setter def type(self, val): self["type"] = val # typesrc # ------- @property def typesrc(self): """ Sets the source reference on plot.ly for type . The 'typesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["typesrc"] @typesrc.setter def typesrc(self, val): self["typesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattercarpet.marker" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the final color of the gradient fill: the center color for radial, the right for horizontal, or the bottom for vertical. colorsrc Sets the source reference on plot.ly for color . type Sets the type of gradient used to fill the markers typesrc Sets the source reference on plot.ly for type . """ def __init__( self, arg=None, color=None, colorsrc=None, type=None, typesrc=None, **kwargs ): """ Construct a new Gradient object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattercarpet.marker.Gradient color Sets the final color of the gradient fill: the center color for radial, the right for horizontal, or the bottom for vertical. colorsrc Sets the source reference on plot.ly for color . type Sets the type of gradient used to fill the markers typesrc Sets the source reference on plot.ly for type . Returns ------- Gradient """ super(Gradient, self).__init__("gradient") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattercarpet.marker.Gradient constructor must be a dict or an instance of plotly.graph_objs.scattercarpet.marker.Gradient""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattercarpet.marker import gradient as v_gradient # Initialize validators # --------------------- self._validators["color"] = v_gradient.ColorValidator() self._validators["colorsrc"] = v_gradient.ColorsrcValidator() self._validators["type"] = v_gradient.TypeValidator() self._validators["typesrc"] = v_gradient.TypesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("type", None) self["type"] = type if type is not None else _v _v = arg.pop("typesrc", None) self["typesrc"] = typesrc if typesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class ColorBar(_BaseTraceHierarchyType): # bgcolor # ------- @property def bgcolor(self): """ Sets the color of padded area. The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the axis line color. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # borderwidth # ----------- @property def borderwidth(self): """ Sets the width (in px) or the border enclosing this color bar. The 'borderwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["borderwidth"] @borderwidth.setter def borderwidth(self, val): self["borderwidth"] = val # dtick # ----- @property def dtick(self): """ Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" The 'dtick' property accepts values of any type Returns ------- Any """ return self["dtick"] @dtick.setter def dtick(self, val): self["dtick"] = val # exponentformat # -------------- @property def exponentformat(self): """ Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. The 'exponentformat' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'e', 'E', 'power', 'SI', 'B'] Returns ------- Any """ return self["exponentformat"] @exponentformat.setter def exponentformat(self, val): self["exponentformat"] = val # len # --- @property def len(self): """ Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. The 'len' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["len"] @len.setter def len(self, val): self["len"] = val # lenmode # ------- @property def lenmode(self): """ Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. The 'lenmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["lenmode"] @lenmode.setter def lenmode(self, val): self["lenmode"] = val # nticks # ------ @property def nticks(self): """ Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". The 'nticks' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nticks"] @nticks.setter def nticks(self, val): self["nticks"] = val # outlinecolor # ------------ @property def outlinecolor(self): """ Sets the axis line color. The 'outlinecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["outlinecolor"] @outlinecolor.setter def outlinecolor(self, val): self["outlinecolor"] = val # outlinewidth # ------------ @property def outlinewidth(self): """ Sets the width (in px) of the axis line. The 'outlinewidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["outlinewidth"] @outlinewidth.setter def outlinewidth(self, val): self["outlinewidth"] = val # separatethousands # ----------------- @property def separatethousands(self): """ If "true", even 4-digit integers are separated The 'separatethousands' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["separatethousands"] @separatethousands.setter def separatethousands(self, val): self["separatethousands"] = val # showexponent # ------------ @property def showexponent(self): """ If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. The 'showexponent' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showexponent"] @showexponent.setter def showexponent(self, val): self["showexponent"] = val # showticklabels # -------------- @property def showticklabels(self): """ Determines whether or not the tick labels are drawn. The 'showticklabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showticklabels"] @showticklabels.setter def showticklabels(self, val): self["showticklabels"] = val # showtickprefix # -------------- @property def showtickprefix(self): """ If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. The 'showtickprefix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showtickprefix"] @showtickprefix.setter def showtickprefix(self, val): self["showtickprefix"] = val # showticksuffix # -------------- @property def showticksuffix(self): """ Same as `showtickprefix` but for tick suffixes. The 'showticksuffix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showticksuffix"] @showticksuffix.setter def showticksuffix(self, val): self["showticksuffix"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # thicknessmode # ------------- @property def thicknessmode(self): """ Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. The 'thicknessmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["thicknessmode"] @thicknessmode.setter def thicknessmode(self, val): self["thicknessmode"] = val # tick0 # ----- @property def tick0(self): """ Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. The 'tick0' property accepts values of any type Returns ------- Any """ return self["tick0"] @tick0.setter def tick0(self, val): self["tick0"] = val # tickangle # --------- @property def tickangle(self): """ Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. The 'tickangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["tickangle"] @tickangle.setter def tickangle(self, val): self["tickangle"] = val # tickcolor # --------- @property def tickcolor(self): """ Sets the tick color. The 'tickcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["tickcolor"] @tickcolor.setter def tickcolor(self, val): self["tickcolor"] = val # tickfont # -------- @property def tickfont(self): """ Sets the color bar's tick label font The 'tickfont' property is an instance of Tickfont that may be specified as: - An instance of plotly.graph_objs.scattercarpet.marker.colorbar.Tickfont - A dict of string/value properties that will be passed to the Tickfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.scattercarpet.marker.colorbar.Tickfont """ return self["tickfont"] @tickfont.setter def tickfont(self, val): self["tickfont"] = val # tickformat # ---------- @property def tickformat(self): """ Sets the tick label formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'tickformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickformat"] @tickformat.setter def tickformat(self, val): self["tickformat"] = val # tickformatstops # --------------- @property def tickformatstops(self): """ The 'tickformatstops' property is a tuple of instances of Tickformatstop that may be specified as: - A list or tuple of instances of plotly.graph_objs.scattercarpet.marker.colorbar.Tickformatstop - A list or tuple of dicts of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- tuple[plotly.graph_objs.scattercarpet.marker.colorbar.Tickformatstop] """ return self["tickformatstops"] @tickformatstops.setter def tickformatstops(self, val): self["tickformatstops"] = val # tickformatstopdefaults # ---------------------- @property def tickformatstopdefaults(self): """ When used in a template (as layout.template.data.scattercarpet. marker.colorbar.tickformatstopdefaults), sets the default property values to use for elements of scattercarpet.marker.colorbar.tickformatstops The 'tickformatstopdefaults' property is an instance of Tickformatstop that may be specified as: - An instance of plotly.graph_objs.scattercarpet.marker.colorbar.Tickformatstop - A dict of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: Returns ------- plotly.graph_objs.scattercarpet.marker.colorbar.Tickformatstop """ return self["tickformatstopdefaults"] @tickformatstopdefaults.setter def tickformatstopdefaults(self, val): self["tickformatstopdefaults"] = val # ticklen # ------- @property def ticklen(self): """ Sets the tick length (in px). The 'ticklen' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ticklen"] @ticklen.setter def ticklen(self, val): self["ticklen"] = val # tickmode # -------- @property def tickmode(self): """ Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). The 'tickmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'linear', 'array'] Returns ------- Any """ return self["tickmode"] @tickmode.setter def tickmode(self, val): self["tickmode"] = val # tickprefix # ---------- @property def tickprefix(self): """ Sets a tick label prefix. The 'tickprefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickprefix"] @tickprefix.setter def tickprefix(self, val): self["tickprefix"] = val # ticks # ----- @property def ticks(self): """ Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. The 'ticks' property is an enumeration that may be specified as: - One of the following enumeration values: ['outside', 'inside', ''] Returns ------- Any """ return self["ticks"] @ticks.setter def ticks(self, val): self["ticks"] = val # ticksuffix # ---------- @property def ticksuffix(self): """ Sets a tick label suffix. The 'ticksuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ticksuffix"] @ticksuffix.setter def ticksuffix(self, val): self["ticksuffix"] = val # ticktext # -------- @property def ticktext(self): """ Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. The 'ticktext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ticktext"] @ticktext.setter def ticktext(self, val): self["ticktext"] = val # ticktextsrc # ----------- @property def ticktextsrc(self): """ Sets the source reference on plot.ly for ticktext . The 'ticktextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ticktextsrc"] @ticktextsrc.setter def ticktextsrc(self, val): self["ticktextsrc"] = val # tickvals # -------- @property def tickvals(self): """ Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. The 'tickvals' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["tickvals"] @tickvals.setter def tickvals(self, val): self["tickvals"] = val # tickvalssrc # ----------- @property def tickvalssrc(self): """ Sets the source reference on plot.ly for tickvals . The 'tickvalssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tickvalssrc"] @tickvalssrc.setter def tickvalssrc(self, val): self["tickvalssrc"] = val # tickwidth # --------- @property def tickwidth(self): """ Sets the tick width (in px). The 'tickwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["tickwidth"] @tickwidth.setter def tickwidth(self, val): self["tickwidth"] = val # title # ----- @property def title(self): """ The 'title' property is an instance of Title that may be specified as: - An instance of plotly.graph_objs.scattercarpet.marker.colorbar.Title - A dict of string/value properties that will be passed to the Title constructor Supported dict properties: font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- plotly.graph_objs.scattercarpet.marker.colorbar.Title """ return self["title"] @title.setter def title(self, val): self["title"] = val # titlefont # --------- @property def titlefont(self): """ Deprecated: Please use scattercarpet.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.scattercarpet.marker.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- """ return self["titlefont"] @titlefont.setter def titlefont(self, val): self["titlefont"] = val # titleside # --------- @property def titleside(self): """ Deprecated: Please use scattercarpet.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- """ return self["titleside"] @titleside.setter def titleside(self, val): self["titleside"] = val # x # - @property def x(self): """ Sets the x position of the color bar (in plot fraction). The 'x' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["x"] @x.setter def x(self, val): self["x"] = val # xanchor # ------- @property def xanchor(self): """ Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. The 'xanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'center', 'right'] Returns ------- Any """ return self["xanchor"] @xanchor.setter def xanchor(self, val): self["xanchor"] = val # xpad # ---- @property def xpad(self): """ Sets the amount of padding (in px) along the x direction. The 'xpad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["xpad"] @xpad.setter def xpad(self, val): self["xpad"] = val # y # - @property def y(self): """ Sets the y position of the color bar (in plot fraction). The 'y' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["y"] @y.setter def y(self, val): self["y"] = val # yanchor # ------- @property def yanchor(self): """ Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. The 'yanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['top', 'middle', 'bottom'] Returns ------- Any """ return self["yanchor"] @yanchor.setter def yanchor(self, val): self["yanchor"] = val # ypad # ---- @property def ypad(self): """ Sets the amount of padding (in px) along the y direction. The 'ypad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ypad"] @ypad.setter def ypad(self, val): self["ypad"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattercarpet.marker" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.scattercarpet.marker.co lorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.scatte rcarpet.marker.colorbar.tickformatstopdefaults), sets the default property values to use for elements of scattercarpet.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.scattercarpet.marker.colorbar.Titl e instance or dict with compatible properties titlefont Deprecated: Please use scattercarpet.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use scattercarpet.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """ _mapped_properties = { "titlefont": ("title", "font"), "titleside": ("title", "side"), } def __init__( self, arg=None, bgcolor=None, bordercolor=None, borderwidth=None, dtick=None, exponentformat=None, len=None, lenmode=None, nticks=None, outlinecolor=None, outlinewidth=None, separatethousands=None, showexponent=None, showticklabels=None, showtickprefix=None, showticksuffix=None, thickness=None, thicknessmode=None, tick0=None, tickangle=None, tickcolor=None, tickfont=None, tickformat=None, tickformatstops=None, tickformatstopdefaults=None, ticklen=None, tickmode=None, tickprefix=None, ticks=None, ticksuffix=None, ticktext=None, ticktextsrc=None, tickvals=None, tickvalssrc=None, tickwidth=None, title=None, titlefont=None, titleside=None, x=None, xanchor=None, xpad=None, y=None, yanchor=None, ypad=None, **kwargs ): """ Construct a new ColorBar object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattercarpet.marker.ColorBar bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.scattercarpet.marker.co lorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.scatte rcarpet.marker.colorbar.tickformatstopdefaults), sets the default property values to use for elements of scattercarpet.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.scattercarpet.marker.colorbar.Titl e instance or dict with compatible properties titlefont Deprecated: Please use scattercarpet.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use scattercarpet.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- ColorBar """ super(ColorBar, self).__init__("colorbar") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattercarpet.marker.ColorBar constructor must be a dict or an instance of plotly.graph_objs.scattercarpet.marker.ColorBar""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattercarpet.marker import colorbar as v_colorbar # Initialize validators # --------------------- self._validators["bgcolor"] = v_colorbar.BgcolorValidator() self._validators["bordercolor"] = v_colorbar.BordercolorValidator() self._validators["borderwidth"] = v_colorbar.BorderwidthValidator() self._validators["dtick"] = v_colorbar.DtickValidator() self._validators["exponentformat"] = v_colorbar.ExponentformatValidator() self._validators["len"] = v_colorbar.LenValidator() self._validators["lenmode"] = v_colorbar.LenmodeValidator() self._validators["nticks"] = v_colorbar.NticksValidator() self._validators["outlinecolor"] = v_colorbar.OutlinecolorValidator() self._validators["outlinewidth"] = v_colorbar.OutlinewidthValidator() self._validators["separatethousands"] = v_colorbar.SeparatethousandsValidator() self._validators["showexponent"] = v_colorbar.ShowexponentValidator() self._validators["showticklabels"] = v_colorbar.ShowticklabelsValidator() self._validators["showtickprefix"] = v_colorbar.ShowtickprefixValidator() self._validators["showticksuffix"] = v_colorbar.ShowticksuffixValidator() self._validators["thickness"] = v_colorbar.ThicknessValidator() self._validators["thicknessmode"] = v_colorbar.ThicknessmodeValidator() self._validators["tick0"] = v_colorbar.Tick0Validator() self._validators["tickangle"] = v_colorbar.TickangleValidator() self._validators["tickcolor"] = v_colorbar.TickcolorValidator() self._validators["tickfont"] = v_colorbar.TickfontValidator() self._validators["tickformat"] = v_colorbar.TickformatValidator() self._validators["tickformatstops"] = v_colorbar.TickformatstopsValidator() self._validators[ "tickformatstopdefaults" ] = v_colorbar.TickformatstopValidator() self._validators["ticklen"] = v_colorbar.TicklenValidator() self._validators["tickmode"] = v_colorbar.TickmodeValidator() self._validators["tickprefix"] = v_colorbar.TickprefixValidator() self._validators["ticks"] = v_colorbar.TicksValidator() self._validators["ticksuffix"] = v_colorbar.TicksuffixValidator() self._validators["ticktext"] = v_colorbar.TicktextValidator() self._validators["ticktextsrc"] = v_colorbar.TicktextsrcValidator() self._validators["tickvals"] = v_colorbar.TickvalsValidator() self._validators["tickvalssrc"] = v_colorbar.TickvalssrcValidator() self._validators["tickwidth"] = v_colorbar.TickwidthValidator() self._validators["title"] = v_colorbar.TitleValidator() self._validators["x"] = v_colorbar.XValidator() self._validators["xanchor"] = v_colorbar.XanchorValidator() self._validators["xpad"] = v_colorbar.XpadValidator() self._validators["y"] = v_colorbar.YValidator() self._validators["yanchor"] = v_colorbar.YanchorValidator() self._validators["ypad"] = v_colorbar.YpadValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("borderwidth", None) self["borderwidth"] = borderwidth if borderwidth is not None else _v _v = arg.pop("dtick", None) self["dtick"] = dtick if dtick is not None else _v _v = arg.pop("exponentformat", None) self["exponentformat"] = exponentformat if exponentformat is not None else _v _v = arg.pop("len", None) self["len"] = len if len is not None else _v _v = arg.pop("lenmode", None) self["lenmode"] = lenmode if lenmode is not None else _v _v = arg.pop("nticks", None) self["nticks"] = nticks if nticks is not None else _v _v = arg.pop("outlinecolor", None) self["outlinecolor"] = outlinecolor if outlinecolor is not None else _v _v = arg.pop("outlinewidth", None) self["outlinewidth"] = outlinewidth if outlinewidth is not None else _v _v = arg.pop("separatethousands", None) self["separatethousands"] = ( separatethousands if separatethousands is not None else _v ) _v = arg.pop("showexponent", None) self["showexponent"] = showexponent if showexponent is not None else _v _v = arg.pop("showticklabels", None) self["showticklabels"] = showticklabels if showticklabels is not None else _v _v = arg.pop("showtickprefix", None) self["showtickprefix"] = showtickprefix if showtickprefix is not None else _v _v = arg.pop("showticksuffix", None) self["showticksuffix"] = showticksuffix if showticksuffix is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("thicknessmode", None) self["thicknessmode"] = thicknessmode if thicknessmode is not None else _v _v = arg.pop("tick0", None) self["tick0"] = tick0 if tick0 is not None else _v _v = arg.pop("tickangle", None) self["tickangle"] = tickangle if tickangle is not None else _v _v = arg.pop("tickcolor", None) self["tickcolor"] = tickcolor if tickcolor is not None else _v _v = arg.pop("tickfont", None) self["tickfont"] = tickfont if tickfont is not None else _v _v = arg.pop("tickformat", None) self["tickformat"] = tickformat if tickformat is not None else _v _v = arg.pop("tickformatstops", None) self["tickformatstops"] = tickformatstops if tickformatstops is not None else _v _v = arg.pop("tickformatstopdefaults", None) self["tickformatstopdefaults"] = ( tickformatstopdefaults if tickformatstopdefaults is not None else _v ) _v = arg.pop("ticklen", None) self["ticklen"] = ticklen if ticklen is not None else _v _v = arg.pop("tickmode", None) self["tickmode"] = tickmode if tickmode is not None else _v _v = arg.pop("tickprefix", None) self["tickprefix"] = tickprefix if tickprefix is not None else _v _v = arg.pop("ticks", None) self["ticks"] = ticks if ticks is not None else _v _v = arg.pop("ticksuffix", None) self["ticksuffix"] = ticksuffix if ticksuffix is not None else _v _v = arg.pop("ticktext", None) self["ticktext"] = ticktext if ticktext is not None else _v _v = arg.pop("ticktextsrc", None) self["ticktextsrc"] = ticktextsrc if ticktextsrc is not None else _v _v = arg.pop("tickvals", None) self["tickvals"] = tickvals if tickvals is not None else _v _v = arg.pop("tickvalssrc", None) self["tickvalssrc"] = tickvalssrc if tickvalssrc is not None else _v _v = arg.pop("tickwidth", None) self["tickwidth"] = tickwidth if tickwidth is not None else _v _v = arg.pop("title", None) self["title"] = title if title is not None else _v _v = arg.pop("titlefont", None) _v = titlefont if titlefont is not None else _v if _v is not None: self["titlefont"] = _v _v = arg.pop("titleside", None) _v = titleside if titleside is not None else _v if _v is not None: self["titleside"] = _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xanchor", None) self["xanchor"] = xanchor if xanchor is not None else _v _v = arg.pop("xpad", None) self["xpad"] = xpad if xpad is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("yanchor", None) self["yanchor"] = yanchor if yanchor is not None else _v _v = arg.pop("ypad", None) self["ypad"] = ypad if ypad is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["ColorBar", "Gradient", "Line", "colorbar"] from plotly.graph_objs.scattercarpet.marker import colorbar plotly-4.4.1+dfsg.orig/plotly/graph_objs/scattercarpet/__init__.py0000644000175000017500000032534013573721552024710 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Unselected(_BaseTraceHierarchyType): # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.scattercarpet.unselected.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. size Sets the marker size of unselected points, applied only when a selection exists. Returns ------- plotly.graph_objs.scattercarpet.unselected.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # textfont # -------- @property def textfont(self): """ The 'textfont' property is an instance of Textfont that may be specified as: - An instance of plotly.graph_objs.scattercarpet.unselected.Textfont - A dict of string/value properties that will be passed to the Textfont constructor Supported dict properties: color Sets the text font color of unselected points, applied only when a selection exists. Returns ------- plotly.graph_objs.scattercarpet.unselected.Textfont """ return self["textfont"] @textfont.setter def textfont(self, val): self["textfont"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattercarpet" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ marker plotly.graph_objects.scattercarpet.unselected.Marker instance or dict with compatible properties textfont plotly.graph_objects.scattercarpet.unselected.Textfont instance or dict with compatible properties """ def __init__(self, arg=None, marker=None, textfont=None, **kwargs): """ Construct a new Unselected object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattercarpet.Unselected marker plotly.graph_objects.scattercarpet.unselected.Marker instance or dict with compatible properties textfont plotly.graph_objects.scattercarpet.unselected.Textfont instance or dict with compatible properties Returns ------- Unselected """ super(Unselected, self).__init__("unselected") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattercarpet.Unselected constructor must be a dict or an instance of plotly.graph_objs.scattercarpet.Unselected""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattercarpet import unselected as v_unselected # Initialize validators # --------------------- self._validators["marker"] = v_unselected.MarkerValidator() self._validators["textfont"] = v_unselected.TextfontValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v _v = arg.pop("textfont", None) self["textfont"] = textfont if textfont is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Textfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattercarpet" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Textfont object Sets the text font. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattercarpet.Textfont color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Textfont """ super(Textfont, self).__init__("textfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattercarpet.Textfont constructor must be a dict or an instance of plotly.graph_objs.scattercarpet.Textfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattercarpet import textfont as v_textfont # Initialize validators # --------------------- self._validators["color"] = v_textfont.ColorValidator() self._validators["colorsrc"] = v_textfont.ColorsrcValidator() self._validators["family"] = v_textfont.FamilyValidator() self._validators["familysrc"] = v_textfont.FamilysrcValidator() self._validators["size"] = v_textfont.SizeValidator() self._validators["sizesrc"] = v_textfont.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Stream(_BaseTraceHierarchyType): # maxpoints # --------- @property def maxpoints(self): """ Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. The 'maxpoints' property is a number and may be specified as: - An int or float in the interval [0, 10000] Returns ------- int|float """ return self["maxpoints"] @maxpoints.setter def maxpoints(self, val): self["maxpoints"] = val # token # ----- @property def token(self): """ The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. The 'token' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["token"] @token.setter def token(self, val): self["token"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattercarpet" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """ def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): """ Construct a new Stream object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattercarpet.Stream maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- Stream """ super(Stream, self).__init__("stream") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattercarpet.Stream constructor must be a dict or an instance of plotly.graph_objs.scattercarpet.Stream""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattercarpet import stream as v_stream # Initialize validators # --------------------- self._validators["maxpoints"] = v_stream.MaxpointsValidator() self._validators["token"] = v_stream.TokenValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("maxpoints", None) self["maxpoints"] = maxpoints if maxpoints is not None else _v _v = arg.pop("token", None) self["token"] = token if token is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Selected(_BaseTraceHierarchyType): # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.scattercarpet.selected.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. size Sets the marker size of selected points. Returns ------- plotly.graph_objs.scattercarpet.selected.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # textfont # -------- @property def textfont(self): """ The 'textfont' property is an instance of Textfont that may be specified as: - An instance of plotly.graph_objs.scattercarpet.selected.Textfont - A dict of string/value properties that will be passed to the Textfont constructor Supported dict properties: color Sets the text font color of selected points. Returns ------- plotly.graph_objs.scattercarpet.selected.Textfont """ return self["textfont"] @textfont.setter def textfont(self, val): self["textfont"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattercarpet" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ marker plotly.graph_objects.scattercarpet.selected.Marker instance or dict with compatible properties textfont plotly.graph_objects.scattercarpet.selected.Textfont instance or dict with compatible properties """ def __init__(self, arg=None, marker=None, textfont=None, **kwargs): """ Construct a new Selected object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattercarpet.Selected marker plotly.graph_objects.scattercarpet.selected.Marker instance or dict with compatible properties textfont plotly.graph_objects.scattercarpet.selected.Textfont instance or dict with compatible properties Returns ------- Selected """ super(Selected, self).__init__("selected") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattercarpet.Selected constructor must be a dict or an instance of plotly.graph_objs.scattercarpet.Selected""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattercarpet import selected as v_selected # Initialize validators # --------------------- self._validators["marker"] = v_selected.MarkerValidator() self._validators["textfont"] = v_selected.TextfontValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v _v = arg.pop("textfont", None) self["textfont"] = textfont if textfont is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # autocolorscale # -------------- @property def autocolorscale(self): """ Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. The 'autocolorscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocolorscale"] @autocolorscale.setter def autocolorscale(self, val): self["autocolorscale"] = val # cauto # ----- @property def cauto(self): """ Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. The 'cauto' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["cauto"] @cauto.setter def cauto(self, val): self["cauto"] = val # cmax # ---- @property def cmax(self): """ Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. The 'cmax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmax"] @cmax.setter def cmax(self, val): self["cmax"] = val # cmid # ---- @property def cmid(self): """ Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. The 'cmid' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmid"] @cmid.setter def cmid(self, val): self["cmid"] = val # cmin # ---- @property def cmin(self): """ Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. The 'cmin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmin"] @cmin.setter def cmin(self, val): self["cmin"] = val # color # ----- @property def color(self): """ Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A number that will be interpreted as a color according to scattercarpet.marker.colorscale - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # coloraxis # --------- @property def coloraxis(self): """ Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. The 'coloraxis' property is an identifier of a particular subplot, of type 'coloraxis', that may be specified as the string 'coloraxis' optionally followed by an integer >= 1 (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) Returns ------- str """ return self["coloraxis"] @coloraxis.setter def coloraxis(self, val): self["coloraxis"] = val # colorbar # -------- @property def colorbar(self): """ The 'colorbar' property is an instance of ColorBar that may be specified as: - An instance of plotly.graph_objs.scattercarpet.marker.ColorBar - A dict of string/value properties that will be passed to the ColorBar constructor Supported dict properties: bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.scattercarpet.m arker.colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.scattercarpet.marker.colorbar.tickformatstopd efaults), sets the default property values to use for elements of scattercarpet.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.scattercarpet.marker.color bar.Title instance or dict with compatible properties titlefont Deprecated: Please use scattercarpet.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use scattercarpet.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- plotly.graph_objs.scattercarpet.marker.ColorBar """ return self["colorbar"] @colorbar.setter def colorbar(self, val): self["colorbar"] = val # colorscale # ---------- @property def colorscale(self): """ Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnB u,Greens,YlOrRd,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland ,Jet,Hot,Blackbody,Earth,Electric,Viridis,Cividis. The 'colorscale' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # gradient # -------- @property def gradient(self): """ The 'gradient' property is an instance of Gradient that may be specified as: - An instance of plotly.graph_objs.scattercarpet.marker.Gradient - A dict of string/value properties that will be passed to the Gradient constructor Supported dict properties: color Sets the final color of the gradient fill: the center color for radial, the right for horizontal, or the bottom for vertical. colorsrc Sets the source reference on plot.ly for color . type Sets the type of gradient used to fill the markers typesrc Sets the source reference on plot.ly for type . Returns ------- plotly.graph_objs.scattercarpet.marker.Gradient """ return self["gradient"] @gradient.setter def gradient(self, val): self["gradient"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.scattercarpet.marker.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,R eds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Black body,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . Returns ------- plotly.graph_objs.scattercarpet.marker.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # maxdisplayed # ------------ @property def maxdisplayed(self): """ Sets a maximum number of points to be drawn on the graph. 0 corresponds to no limit. The 'maxdisplayed' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["maxdisplayed"] @maxdisplayed.setter def maxdisplayed(self, val): self["maxdisplayed"] = val # opacity # ------- @property def opacity(self): """ Sets the marker opacity. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # opacitysrc # ---------- @property def opacitysrc(self): """ Sets the source reference on plot.ly for opacity . The 'opacitysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["opacitysrc"] @opacitysrc.setter def opacitysrc(self, val): self["opacitysrc"] = val # reversescale # ------------ @property def reversescale(self): """ Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. The 'reversescale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["reversescale"] @reversescale.setter def reversescale(self, val): self["reversescale"] = val # showscale # --------- @property def showscale(self): """ Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. The 'showscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showscale"] @showscale.setter def showscale(self, val): self["showscale"] = val # size # ---- @property def size(self): """ Sets the marker size (in px). The 'size' property is a number and may be specified as: - An int or float in the interval [0, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizemin # ------- @property def sizemin(self): """ Has an effect only if `marker.size` is set to a numerical array. Sets the minimum size (in px) of the rendered marker points. The 'sizemin' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["sizemin"] @sizemin.setter def sizemin(self, val): self["sizemin"] = val # sizemode # -------- @property def sizemode(self): """ Has an effect only if `marker.size` is set to a numerical array. Sets the rule for which the data in `size` is converted to pixels. The 'sizemode' property is an enumeration that may be specified as: - One of the following enumeration values: ['diameter', 'area'] Returns ------- Any """ return self["sizemode"] @sizemode.setter def sizemode(self, val): self["sizemode"] = val # sizeref # ------- @property def sizeref(self): """ Has an effect only if `marker.size` is set to a numerical array. Sets the scale factor used to determine the rendered size of marker points. Use with `sizemin` and `sizemode`. The 'sizeref' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["sizeref"] @sizeref.setter def sizeref(self, val): self["sizeref"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # symbol # ------ @property def symbol(self): """ Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot-open" to a symbol name. The 'symbol' property is an enumeration that may be specified as: - One of the following enumeration values: [0, 'circle', 100, 'circle-open', 200, 'circle-dot', 300, 'circle-open-dot', 1, 'square', 101, 'square-open', 201, 'square-dot', 301, 'square-open-dot', 2, 'diamond', 102, 'diamond-open', 202, 'diamond-dot', 302, 'diamond-open-dot', 3, 'cross', 103, 'cross-open', 203, 'cross-dot', 303, 'cross-open-dot', 4, 'x', 104, 'x-open', 204, 'x-dot', 304, 'x-open-dot', 5, 'triangle-up', 105, 'triangle-up-open', 205, 'triangle-up-dot', 305, 'triangle-up-open-dot', 6, 'triangle-down', 106, 'triangle-down-open', 206, 'triangle-down-dot', 306, 'triangle-down-open-dot', 7, 'triangle-left', 107, 'triangle-left-open', 207, 'triangle-left-dot', 307, 'triangle-left-open-dot', 8, 'triangle-right', 108, 'triangle-right-open', 208, 'triangle-right-dot', 308, 'triangle-right-open-dot', 9, 'triangle-ne', 109, 'triangle-ne-open', 209, 'triangle-ne-dot', 309, 'triangle-ne-open-dot', 10, 'triangle-se', 110, 'triangle-se-open', 210, 'triangle-se-dot', 310, 'triangle-se-open-dot', 11, 'triangle-sw', 111, 'triangle-sw-open', 211, 'triangle-sw-dot', 311, 'triangle-sw-open-dot', 12, 'triangle-nw', 112, 'triangle-nw-open', 212, 'triangle-nw-dot', 312, 'triangle-nw-open-dot', 13, 'pentagon', 113, 'pentagon-open', 213, 'pentagon-dot', 313, 'pentagon-open-dot', 14, 'hexagon', 114, 'hexagon-open', 214, 'hexagon-dot', 314, 'hexagon-open-dot', 15, 'hexagon2', 115, 'hexagon2-open', 215, 'hexagon2-dot', 315, 'hexagon2-open-dot', 16, 'octagon', 116, 'octagon-open', 216, 'octagon-dot', 316, 'octagon-open-dot', 17, 'star', 117, 'star-open', 217, 'star-dot', 317, 'star-open-dot', 18, 'hexagram', 118, 'hexagram-open', 218, 'hexagram-dot', 318, 'hexagram-open-dot', 19, 'star-triangle-up', 119, 'star-triangle-up-open', 219, 'star-triangle-up-dot', 319, 'star-triangle-up-open-dot', 20, 'star-triangle-down', 120, 'star-triangle-down-open', 220, 'star-triangle-down-dot', 320, 'star-triangle-down-open-dot', 21, 'star-square', 121, 'star-square-open', 221, 'star-square-dot', 321, 'star-square-open-dot', 22, 'star-diamond', 122, 'star-diamond-open', 222, 'star-diamond-dot', 322, 'star-diamond-open-dot', 23, 'diamond-tall', 123, 'diamond-tall-open', 223, 'diamond-tall-dot', 323, 'diamond-tall-open-dot', 24, 'diamond-wide', 124, 'diamond-wide-open', 224, 'diamond-wide-dot', 324, 'diamond-wide-open-dot', 25, 'hourglass', 125, 'hourglass-open', 26, 'bowtie', 126, 'bowtie-open', 27, 'circle-cross', 127, 'circle-cross-open', 28, 'circle-x', 128, 'circle-x-open', 29, 'square-cross', 129, 'square-cross-open', 30, 'square-x', 130, 'square-x-open', 31, 'diamond-cross', 131, 'diamond-cross-open', 32, 'diamond-x', 132, 'diamond-x-open', 33, 'cross-thin', 133, 'cross-thin-open', 34, 'x-thin', 134, 'x-thin-open', 35, 'asterisk', 135, 'asterisk-open', 36, 'hash', 136, 'hash-open', 236, 'hash-dot', 336, 'hash-open-dot', 37, 'y-up', 137, 'y-up-open', 38, 'y-down', 138, 'y-down-open', 39, 'y-left', 139, 'y-left-open', 40, 'y-right', 140, 'y-right-open', 41, 'line-ew', 141, 'line-ew-open', 42, 'line-ns', 142, 'line-ns-open', 43, 'line-ne', 143, 'line-ne-open', 44, 'line-nw', 144, 'line-nw-open'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["symbol"] @symbol.setter def symbol(self, val): self["symbol"] = val # symbolsrc # --------- @property def symbolsrc(self): """ Sets the source reference on plot.ly for symbol . The 'symbolsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["symbolsrc"] @symbolsrc.setter def symbolsrc(self, val): self["symbolsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattercarpet" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.scattercarpet.marker.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu ,Reds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . gradient plotly.graph_objects.scattercarpet.marker.Gradient instance or dict with compatible properties line plotly.graph_objects.scattercarpet.marker.Line instance or dict with compatible properties maxdisplayed Sets a maximum number of points to be drawn on the graph. 0 corresponds to no limit. opacity Sets the marker opacity. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. size Sets the marker size (in px). sizemin Has an effect only if `marker.size` is set to a numerical array. Sets the minimum size (in px) of the rendered marker points. sizemode Has an effect only if `marker.size` is set to a numerical array. Sets the rule for which the data in `size` is converted to pixels. sizeref Has an effect only if `marker.size` is set to a numerical array. Sets the scale factor used to determine the rendered size of marker points. Use with `sizemin` and `sizemode`. sizesrc Sets the source reference on plot.ly for size . symbol Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot- open" to a symbol name. symbolsrc Sets the source reference on plot.ly for symbol . """ def __init__( self, arg=None, autocolorscale=None, cauto=None, cmax=None, cmid=None, cmin=None, color=None, coloraxis=None, colorbar=None, colorscale=None, colorsrc=None, gradient=None, line=None, maxdisplayed=None, opacity=None, opacitysrc=None, reversescale=None, showscale=None, size=None, sizemin=None, sizemode=None, sizeref=None, sizesrc=None, symbol=None, symbolsrc=None, **kwargs ): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattercarpet.Marker autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.scattercarpet.marker.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu ,Reds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . gradient plotly.graph_objects.scattercarpet.marker.Gradient instance or dict with compatible properties line plotly.graph_objects.scattercarpet.marker.Line instance or dict with compatible properties maxdisplayed Sets a maximum number of points to be drawn on the graph. 0 corresponds to no limit. opacity Sets the marker opacity. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. size Sets the marker size (in px). sizemin Has an effect only if `marker.size` is set to a numerical array. Sets the minimum size (in px) of the rendered marker points. sizemode Has an effect only if `marker.size` is set to a numerical array. Sets the rule for which the data in `size` is converted to pixels. sizeref Has an effect only if `marker.size` is set to a numerical array. Sets the scale factor used to determine the rendered size of marker points. Use with `sizemin` and `sizemode`. sizesrc Sets the source reference on plot.ly for size . symbol Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot- open" to a symbol name. symbolsrc Sets the source reference on plot.ly for symbol . Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattercarpet.Marker constructor must be a dict or an instance of plotly.graph_objs.scattercarpet.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattercarpet import marker as v_marker # Initialize validators # --------------------- self._validators["autocolorscale"] = v_marker.AutocolorscaleValidator() self._validators["cauto"] = v_marker.CautoValidator() self._validators["cmax"] = v_marker.CmaxValidator() self._validators["cmid"] = v_marker.CmidValidator() self._validators["cmin"] = v_marker.CminValidator() self._validators["color"] = v_marker.ColorValidator() self._validators["coloraxis"] = v_marker.ColoraxisValidator() self._validators["colorbar"] = v_marker.ColorBarValidator() self._validators["colorscale"] = v_marker.ColorscaleValidator() self._validators["colorsrc"] = v_marker.ColorsrcValidator() self._validators["gradient"] = v_marker.GradientValidator() self._validators["line"] = v_marker.LineValidator() self._validators["maxdisplayed"] = v_marker.MaxdisplayedValidator() self._validators["opacity"] = v_marker.OpacityValidator() self._validators["opacitysrc"] = v_marker.OpacitysrcValidator() self._validators["reversescale"] = v_marker.ReversescaleValidator() self._validators["showscale"] = v_marker.ShowscaleValidator() self._validators["size"] = v_marker.SizeValidator() self._validators["sizemin"] = v_marker.SizeminValidator() self._validators["sizemode"] = v_marker.SizemodeValidator() self._validators["sizeref"] = v_marker.SizerefValidator() self._validators["sizesrc"] = v_marker.SizesrcValidator() self._validators["symbol"] = v_marker.SymbolValidator() self._validators["symbolsrc"] = v_marker.SymbolsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autocolorscale", None) self["autocolorscale"] = autocolorscale if autocolorscale is not None else _v _v = arg.pop("cauto", None) self["cauto"] = cauto if cauto is not None else _v _v = arg.pop("cmax", None) self["cmax"] = cmax if cmax is not None else _v _v = arg.pop("cmid", None) self["cmid"] = cmid if cmid is not None else _v _v = arg.pop("cmin", None) self["cmin"] = cmin if cmin is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("coloraxis", None) self["coloraxis"] = coloraxis if coloraxis is not None else _v _v = arg.pop("colorbar", None) self["colorbar"] = colorbar if colorbar is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("gradient", None) self["gradient"] = gradient if gradient is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v _v = arg.pop("maxdisplayed", None) self["maxdisplayed"] = maxdisplayed if maxdisplayed is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("opacitysrc", None) self["opacitysrc"] = opacitysrc if opacitysrc is not None else _v _v = arg.pop("reversescale", None) self["reversescale"] = reversescale if reversescale is not None else _v _v = arg.pop("showscale", None) self["showscale"] = showscale if showscale is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizemin", None) self["sizemin"] = sizemin if sizemin is not None else _v _v = arg.pop("sizemode", None) self["sizemode"] = sizemode if sizemode is not None else _v _v = arg.pop("sizeref", None) self["sizeref"] = sizeref if sizeref is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v _v = arg.pop("symbol", None) self["symbol"] = symbol if symbol is not None else _v _v = arg.pop("symbolsrc", None) self["symbolsrc"] = symbolsrc if symbolsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the line color. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # dash # ---- @property def dash(self): """ Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). The 'dash' property is an enumeration that may be specified as: - One of the following dash styles: ['solid', 'dot', 'dash', 'longdash', 'dashdot', 'longdashdot'] - A string containing a dash length list in pixels or percentages (e.g. '5px 10px 2px 2px', '5, 10, 2, 2', '10% 20% 40%', etc.) Returns ------- str """ return self["dash"] @dash.setter def dash(self, val): self["dash"] = val # shape # ----- @property def shape(self): """ Determines the line shape. With "spline" the lines are drawn using spline interpolation. The other available values correspond to step-wise line shapes. The 'shape' property is an enumeration that may be specified as: - One of the following enumeration values: ['linear', 'spline'] Returns ------- Any """ return self["shape"] @shape.setter def shape(self, val): self["shape"] = val # smoothing # --------- @property def smoothing(self): """ Has an effect only if `shape` is set to "spline" Sets the amount of smoothing. 0 corresponds to no smoothing (equivalent to a "linear" shape). The 'smoothing' property is a number and may be specified as: - An int or float in the interval [0, 1.3] Returns ------- int|float """ return self["smoothing"] @smoothing.setter def smoothing(self, val): self["smoothing"] = val # width # ----- @property def width(self): """ Sets the line width (in px). The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattercarpet" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the line color. dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). shape Determines the line shape. With "spline" the lines are drawn using spline interpolation. The other available values correspond to step-wise line shapes. smoothing Has an effect only if `shape` is set to "spline" Sets the amount of smoothing. 0 corresponds to no smoothing (equivalent to a "linear" shape). width Sets the line width (in px). """ def __init__( self, arg=None, color=None, dash=None, shape=None, smoothing=None, width=None, **kwargs ): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattercarpet.Line color Sets the line color. dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). shape Determines the line shape. With "spline" the lines are drawn using spline interpolation. The other available values correspond to step-wise line shapes. smoothing Has an effect only if `shape` is set to "spline" Sets the amount of smoothing. 0 corresponds to no smoothing (equivalent to a "linear" shape). width Sets the line width (in px). Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattercarpet.Line constructor must be a dict or an instance of plotly.graph_objs.scattercarpet.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattercarpet import line as v_line # Initialize validators # --------------------- self._validators["color"] = v_line.ColorValidator() self._validators["dash"] = v_line.DashValidator() self._validators["shape"] = v_line.ShapeValidator() self._validators["smoothing"] = v_line.SmoothingValidator() self._validators["width"] = v_line.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("dash", None) self["dash"] = dash if dash is not None else _v _v = arg.pop("shape", None) self["shape"] = shape if shape is not None else _v _v = arg.pop("smoothing", None) self["smoothing"] = smoothing if smoothing is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Hoverlabel(_BaseTraceHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'right', 'auto'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["align"] @align.setter def align(self, val): self["align"] = val # alignsrc # -------- @property def alignsrc(self): """ Sets the source reference on plot.ly for align . The 'alignsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["alignsrc"] @alignsrc.setter def alignsrc(self, val): self["alignsrc"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the hover labels for this trace The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bgcolorsrc # ---------- @property def bgcolorsrc(self): """ Sets the source reference on plot.ly for bgcolor . The 'bgcolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bgcolorsrc"] @bgcolorsrc.setter def bgcolorsrc(self, val): self["bgcolorsrc"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the border color of the hover labels for this trace. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # bordercolorsrc # -------------- @property def bordercolorsrc(self): """ Sets the source reference on plot.ly for bordercolor . The 'bordercolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bordercolorsrc"] @bordercolorsrc.setter def bordercolorsrc(self, val): self["bordercolorsrc"] = val # font # ---- @property def font(self): """ Sets the font used in hover labels. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.scattercarpet.hoverlabel.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.scattercarpet.hoverlabel.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # namelength # ---------- @property def namelength(self): """ Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. The 'namelength' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [-1, 9223372036854775807] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|numpy.ndarray """ return self["namelength"] @namelength.setter def namelength(self, val): self["namelength"] = val # namelengthsrc # ------------- @property def namelengthsrc(self): """ Sets the source reference on plot.ly for namelength . The 'namelengthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["namelengthsrc"] @namelengthsrc.setter def namelengthsrc(self, val): self["namelengthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattercarpet" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """ def __init__( self, arg=None, align=None, alignsrc=None, bgcolor=None, bgcolorsrc=None, bordercolor=None, bordercolorsrc=None, font=None, namelength=None, namelengthsrc=None, **kwargs ): """ Construct a new Hoverlabel object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattercarpet.Hoverlabel align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- Hoverlabel """ super(Hoverlabel, self).__init__("hoverlabel") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattercarpet.Hoverlabel constructor must be a dict or an instance of plotly.graph_objs.scattercarpet.Hoverlabel""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattercarpet import hoverlabel as v_hoverlabel # Initialize validators # --------------------- self._validators["align"] = v_hoverlabel.AlignValidator() self._validators["alignsrc"] = v_hoverlabel.AlignsrcValidator() self._validators["bgcolor"] = v_hoverlabel.BgcolorValidator() self._validators["bgcolorsrc"] = v_hoverlabel.BgcolorsrcValidator() self._validators["bordercolor"] = v_hoverlabel.BordercolorValidator() self._validators["bordercolorsrc"] = v_hoverlabel.BordercolorsrcValidator() self._validators["font"] = v_hoverlabel.FontValidator() self._validators["namelength"] = v_hoverlabel.NamelengthValidator() self._validators["namelengthsrc"] = v_hoverlabel.NamelengthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("alignsrc", None) self["alignsrc"] = alignsrc if alignsrc is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bgcolorsrc", None) self["bgcolorsrc"] = bgcolorsrc if bgcolorsrc is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("bordercolorsrc", None) self["bordercolorsrc"] = bordercolorsrc if bordercolorsrc is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("namelength", None) self["namelength"] = namelength if namelength is not None else _v _v = arg.pop("namelengthsrc", None) self["namelengthsrc"] = namelengthsrc if namelengthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = [ "Hoverlabel", "Line", "Marker", "Selected", "Stream", "Textfont", "Unselected", "hoverlabel", "marker", "selected", "unselected", ] from plotly.graph_objs.scattercarpet import unselected from plotly.graph_objs.scattercarpet import selected from plotly.graph_objs.scattercarpet import marker from plotly.graph_objs.scattercarpet import hoverlabel plotly-4.4.1+dfsg.orig/plotly/graph_objs/scattercarpet/selected/0000755000175000017500000000000013573746613024365 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scattercarpet/selected/__init__.py0000644000175000017500000002654213573721551026501 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Textfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the text font color of selected points. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattercarpet.selected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the text font color of selected points. """ def __init__(self, arg=None, color=None, **kwargs): """ Construct a new Textfont object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattercarpet.selected.Textfont color Sets the text font color of selected points. Returns ------- Textfont """ super(Textfont, self).__init__("textfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattercarpet.selected.Textfont constructor must be a dict or an instance of plotly.graph_objs.scattercarpet.selected.Textfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattercarpet.selected import textfont as v_textfont # Initialize validators # --------------------- self._validators["color"] = v_textfont.ColorValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the marker color of selected points. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # opacity # ------- @property def opacity(self): """ Sets the marker opacity of selected points. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # size # ---- @property def size(self): """ Sets the marker size of selected points. The 'size' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scattercarpet.selected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. size Sets the marker size of selected points. """ def __init__(self, arg=None, color=None, opacity=None, size=None, **kwargs): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scattercarpet.selected.Marker color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. size Sets the marker size of selected points. Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scattercarpet.selected.Marker constructor must be a dict or an instance of plotly.graph_objs.scattercarpet.selected.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scattercarpet.selected import marker as v_marker # Initialize validators # --------------------- self._validators["color"] = v_marker.ColorValidator() self._validators["opacity"] = v_marker.OpacityValidator() self._validators["size"] = v_marker.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Marker", "Textfont"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/parcats/0000755000175000017500000000000013573746613021366 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/parcats/__init__.py0000644000175000017500000024140513573721551023477 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "parcats" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Tickfont object Sets the font for the `category` labels. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.parcats.Tickfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Tickfont """ super(Tickfont, self).__init__("tickfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.parcats.Tickfont constructor must be a dict or an instance of plotly.graph_objs.parcats.Tickfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.parcats import tickfont as v_tickfont # Initialize validators # --------------------- self._validators["color"] = v_tickfont.ColorValidator() self._validators["family"] = v_tickfont.FamilyValidator() self._validators["size"] = v_tickfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Stream(_BaseTraceHierarchyType): # maxpoints # --------- @property def maxpoints(self): """ Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. The 'maxpoints' property is a number and may be specified as: - An int or float in the interval [0, 10000] Returns ------- int|float """ return self["maxpoints"] @maxpoints.setter def maxpoints(self, val): self["maxpoints"] = val # token # ----- @property def token(self): """ The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. The 'token' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["token"] @token.setter def token(self, val): self["token"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "parcats" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """ def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): """ Construct a new Stream object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.parcats.Stream maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- Stream """ super(Stream, self).__init__("stream") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.parcats.Stream constructor must be a dict or an instance of plotly.graph_objs.parcats.Stream""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.parcats import stream as v_stream # Initialize validators # --------------------- self._validators["maxpoints"] = v_stream.MaxpointsValidator() self._validators["token"] = v_stream.TokenValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("maxpoints", None) self["maxpoints"] = maxpoints if maxpoints is not None else _v _v = arg.pop("token", None) self["token"] = token if token is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # autocolorscale # -------------- @property def autocolorscale(self): """ Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `line.colorscale`. Has an effect only if in `line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. The 'autocolorscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocolorscale"] @autocolorscale.setter def autocolorscale(self, val): self["autocolorscale"] = val # cauto # ----- @property def cauto(self): """ Determines whether or not the color domain is computed with respect to the input data (here in `line.color`) or the bounds set in `line.cmin` and `line.cmax` Has an effect only if in `line.color`is set to a numerical array. Defaults to `false` when `line.cmin` and `line.cmax` are set by the user. The 'cauto' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["cauto"] @cauto.setter def cauto(self, val): self["cauto"] = val # cmax # ---- @property def cmax(self): """ Sets the upper bound of the color domain. Has an effect only if in `line.color`is set to a numerical array. Value should have the same units as in `line.color` and if set, `line.cmin` must be set as well. The 'cmax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmax"] @cmax.setter def cmax(self, val): self["cmax"] = val # cmid # ---- @property def cmid(self): """ Sets the mid-point of the color domain by scaling `line.cmin` and/or `line.cmax` to be equidistant to this point. Has an effect only if in `line.color`is set to a numerical array. Value should have the same units as in `line.color`. Has no effect when `line.cauto` is `false`. The 'cmid' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmid"] @cmid.setter def cmid(self, val): self["cmid"] = val # cmin # ---- @property def cmin(self): """ Sets the lower bound of the color domain. Has an effect only if in `line.color`is set to a numerical array. Value should have the same units as in `line.color` and if set, `line.cmax` must be set as well. The 'cmin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmin"] @cmin.setter def cmin(self, val): self["cmin"] = val # color # ----- @property def color(self): """ Sets thelinecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `line.cmin` and `line.cmax` if set. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A number that will be interpreted as a color according to parcats.line.colorscale - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # coloraxis # --------- @property def coloraxis(self): """ Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. The 'coloraxis' property is an identifier of a particular subplot, of type 'coloraxis', that may be specified as the string 'coloraxis' optionally followed by an integer >= 1 (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) Returns ------- str """ return self["coloraxis"] @coloraxis.setter def coloraxis(self, val): self["coloraxis"] = val # colorbar # -------- @property def colorbar(self): """ The 'colorbar' property is an instance of ColorBar that may be specified as: - An instance of plotly.graph_objs.parcats.line.ColorBar - A dict of string/value properties that will be passed to the ColorBar constructor Supported dict properties: bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.parcats.line.co lorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.parcats.line.colorbar.tickformatstopdefaults) , sets the default property values to use for elements of parcats.line.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.parcats.line.colorbar.Titl e instance or dict with compatible properties titlefont Deprecated: Please use parcats.line.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use parcats.line.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- plotly.graph_objs.parcats.line.ColorBar """ return self["colorbar"] @colorbar.setter def colorbar(self, val): self["colorbar"] = val # colorscale # ---------- @property def colorscale(self): """ Sets the colorscale. Has an effect only if in `line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`line.cmin` and `line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Gr eens,YlOrRd,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet ,Hot,Blackbody,Earth,Electric,Viridis,Cividis. The 'colorscale' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # hovertemplate # ------------- @property def hovertemplate(self): """ Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time- format's syntax %{variable|d3-time-format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event- data. Additionally, every attributes that can be specified per- point (the ones that are `arrayOk: true`) are available. variables `count` and `probability`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. The 'hovertemplate' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["hovertemplate"] @hovertemplate.setter def hovertemplate(self, val): self["hovertemplate"] = val # reversescale # ------------ @property def reversescale(self): """ Reverses the color mapping if true. Has an effect only if in `line.color`is set to a numerical array. If true, `line.cmin` will correspond to the last color in the array and `line.cmax` will correspond to the first color. The 'reversescale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["reversescale"] @reversescale.setter def reversescale(self, val): self["reversescale"] = val # shape # ----- @property def shape(self): """ Sets the shape of the paths. If `linear`, paths are composed of straight lines. If `hspline`, paths are composed of horizontal curved splines The 'shape' property is an enumeration that may be specified as: - One of the following enumeration values: ['linear', 'hspline'] Returns ------- Any """ return self["shape"] @shape.setter def shape(self, val): self["shape"] = val # showscale # --------- @property def showscale(self): """ Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `line.color`is set to a numerical array. The 'showscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showscale"] @showscale.setter def showscale(self, val): self["showscale"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "parcats" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `line.colorscale`. Has an effect only if in `line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `line.color`) or the bounds set in `line.cmin` and `line.cmax` Has an effect only if in `line.color`is set to a numerical array. Defaults to `false` when `line.cmin` and `line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `line.color`is set to a numerical array. Value should have the same units as in `line.color` and if set, `line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `line.cmin` and/or `line.cmax` to be equidistant to this point. Has an effect only if in `line.color`is set to a numerical array. Value should have the same units as in `line.color`. Has no effect when `line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `line.color`is set to a numerical array. Value should have the same units as in `line.color` and if set, `line.cmax` must be set as well. color Sets thelinecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `line.cmin` and `line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.parcats.line.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`line.cmin` and `line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu ,Greens,YlOrRd,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,P ortland,Jet,Hot,Blackbody,Earth,Electric,Viridis,Cividi s. colorsrc Sets the source reference on plot.ly for color . hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `count` and `probability`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. reversescale Reverses the color mapping if true. Has an effect only if in `line.color`is set to a numerical array. If true, `line.cmin` will correspond to the last color in the array and `line.cmax` will correspond to the first color. shape Sets the shape of the paths. If `linear`, paths are composed of straight lines. If `hspline`, paths are composed of horizontal curved splines showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `line.color`is set to a numerical array. """ def __init__( self, arg=None, autocolorscale=None, cauto=None, cmax=None, cmid=None, cmin=None, color=None, coloraxis=None, colorbar=None, colorscale=None, colorsrc=None, hovertemplate=None, reversescale=None, shape=None, showscale=None, **kwargs ): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.parcats.Line autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `line.colorscale`. Has an effect only if in `line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `line.color`) or the bounds set in `line.cmin` and `line.cmax` Has an effect only if in `line.color`is set to a numerical array. Defaults to `false` when `line.cmin` and `line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `line.color`is set to a numerical array. Value should have the same units as in `line.color` and if set, `line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `line.cmin` and/or `line.cmax` to be equidistant to this point. Has an effect only if in `line.color`is set to a numerical array. Value should have the same units as in `line.color`. Has no effect when `line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `line.color`is set to a numerical array. Value should have the same units as in `line.color` and if set, `line.cmax` must be set as well. color Sets thelinecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `line.cmin` and `line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.parcats.line.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`line.cmin` and `line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu ,Greens,YlOrRd,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,P ortland,Jet,Hot,Blackbody,Earth,Electric,Viridis,Cividi s. colorsrc Sets the source reference on plot.ly for color . hovertemplate Template string used for rendering the information that appear on hover box. Note that this will override `hoverinfo`. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format's syntax %{variable|d3-time- format}, for example "Day: %{2019-01-01|%A}". https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax. The variables available in `hovertemplate` are the ones emitted as event data described at this link https://plot.ly/javascript/plotlyjs-events/#event-data. Additionally, every attributes that can be specified per-point (the ones that are `arrayOk: true`) are available. variables `count` and `probability`. Anything contained in tag `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. reversescale Reverses the color mapping if true. Has an effect only if in `line.color`is set to a numerical array. If true, `line.cmin` will correspond to the last color in the array and `line.cmax` will correspond to the first color. shape Sets the shape of the paths. If `linear`, paths are composed of straight lines. If `hspline`, paths are composed of horizontal curved splines showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `line.color`is set to a numerical array. Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.parcats.Line constructor must be a dict or an instance of plotly.graph_objs.parcats.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.parcats import line as v_line # Initialize validators # --------------------- self._validators["autocolorscale"] = v_line.AutocolorscaleValidator() self._validators["cauto"] = v_line.CautoValidator() self._validators["cmax"] = v_line.CmaxValidator() self._validators["cmid"] = v_line.CmidValidator() self._validators["cmin"] = v_line.CminValidator() self._validators["color"] = v_line.ColorValidator() self._validators["coloraxis"] = v_line.ColoraxisValidator() self._validators["colorbar"] = v_line.ColorBarValidator() self._validators["colorscale"] = v_line.ColorscaleValidator() self._validators["colorsrc"] = v_line.ColorsrcValidator() self._validators["hovertemplate"] = v_line.HovertemplateValidator() self._validators["reversescale"] = v_line.ReversescaleValidator() self._validators["shape"] = v_line.ShapeValidator() self._validators["showscale"] = v_line.ShowscaleValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autocolorscale", None) self["autocolorscale"] = autocolorscale if autocolorscale is not None else _v _v = arg.pop("cauto", None) self["cauto"] = cauto if cauto is not None else _v _v = arg.pop("cmax", None) self["cmax"] = cmax if cmax is not None else _v _v = arg.pop("cmid", None) self["cmid"] = cmid if cmid is not None else _v _v = arg.pop("cmin", None) self["cmin"] = cmin if cmin is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("coloraxis", None) self["coloraxis"] = coloraxis if coloraxis is not None else _v _v = arg.pop("colorbar", None) self["colorbar"] = colorbar if colorbar is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("hovertemplate", None) self["hovertemplate"] = hovertemplate if hovertemplate is not None else _v _v = arg.pop("reversescale", None) self["reversescale"] = reversescale if reversescale is not None else _v _v = arg.pop("shape", None) self["shape"] = shape if shape is not None else _v _v = arg.pop("showscale", None) self["showscale"] = showscale if showscale is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Labelfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "parcats" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Labelfont object Sets the font for the `dimension` labels. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.parcats.Labelfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Labelfont """ super(Labelfont, self).__init__("labelfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.parcats.Labelfont constructor must be a dict or an instance of plotly.graph_objs.parcats.Labelfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.parcats import labelfont as v_labelfont # Initialize validators # --------------------- self._validators["color"] = v_labelfont.ColorValidator() self._validators["family"] = v_labelfont.FamilyValidator() self._validators["size"] = v_labelfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Domain(_BaseTraceHierarchyType): # column # ------ @property def column(self): """ If there is a layout grid, use the domain for this column in the grid for this parcats trace . The 'column' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["column"] @column.setter def column(self, val): self["column"] = val # row # --- @property def row(self): """ If there is a layout grid, use the domain for this row in the grid for this parcats trace . The 'row' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["row"] @row.setter def row(self, val): self["row"] = val # x # - @property def x(self): """ Sets the horizontal domain of this parcats trace (in plot fraction). The 'x' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'x[0]' property is a number and may be specified as: - An int or float in the interval [0, 1] (1) The 'x[1]' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- list """ return self["x"] @x.setter def x(self, val): self["x"] = val # y # - @property def y(self): """ Sets the vertical domain of this parcats trace (in plot fraction). The 'y' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'y[0]' property is a number and may be specified as: - An int or float in the interval [0, 1] (1) The 'y[1]' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- list """ return self["y"] @y.setter def y(self, val): self["y"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "parcats" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ column If there is a layout grid, use the domain for this column in the grid for this parcats trace . row If there is a layout grid, use the domain for this row in the grid for this parcats trace . x Sets the horizontal domain of this parcats trace (in plot fraction). y Sets the vertical domain of this parcats trace (in plot fraction). """ def __init__(self, arg=None, column=None, row=None, x=None, y=None, **kwargs): """ Construct a new Domain object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.parcats.Domain column If there is a layout grid, use the domain for this column in the grid for this parcats trace . row If there is a layout grid, use the domain for this row in the grid for this parcats trace . x Sets the horizontal domain of this parcats trace (in plot fraction). y Sets the vertical domain of this parcats trace (in plot fraction). Returns ------- Domain """ super(Domain, self).__init__("domain") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.parcats.Domain constructor must be a dict or an instance of plotly.graph_objs.parcats.Domain""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.parcats import domain as v_domain # Initialize validators # --------------------- self._validators["column"] = v_domain.ColumnValidator() self._validators["row"] = v_domain.RowValidator() self._validators["x"] = v_domain.XValidator() self._validators["y"] = v_domain.YValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("column", None) self["column"] = column if column is not None else _v _v = arg.pop("row", None) self["row"] = row if row is not None else _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Dimension(_BaseTraceHierarchyType): # categoryarray # ------------- @property def categoryarray(self): """ Sets the order in which categories in this dimension appear. Only has an effect if `categoryorder` is set to "array". Used with `categoryorder`. The 'categoryarray' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["categoryarray"] @categoryarray.setter def categoryarray(self, val): self["categoryarray"] = val # categoryarraysrc # ---------------- @property def categoryarraysrc(self): """ Sets the source reference on plot.ly for categoryarray . The 'categoryarraysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["categoryarraysrc"] @categoryarraysrc.setter def categoryarraysrc(self, val): self["categoryarraysrc"] = val # categoryorder # ------------- @property def categoryorder(self): """ Specifies the ordering logic for the categories in the dimension. By default, plotly uses "trace", which specifies the order that is present in the data supplied. Set `categoryorder` to *category ascending* or *category descending* if order should be determined by the alphanumerical order of the category names. Set `categoryorder` to "array" to derive the ordering from the attribute `categoryarray`. If a category is not found in the `categoryarray` array, the sorting behavior for that attribute will be identical to the "trace" mode. The unspecified categories will follow the categories in `categoryarray`. The 'categoryorder' property is an enumeration that may be specified as: - One of the following enumeration values: ['trace', 'category ascending', 'category descending', 'array'] Returns ------- Any """ return self["categoryorder"] @categoryorder.setter def categoryorder(self, val): self["categoryorder"] = val # displayindex # ------------ @property def displayindex(self): """ The display index of dimension, from left to right, zero indexed, defaults to dimension index. The 'displayindex' property is a integer and may be specified as: - An int (or float that will be cast to an int) Returns ------- int """ return self["displayindex"] @displayindex.setter def displayindex(self, val): self["displayindex"] = val # label # ----- @property def label(self): """ The shown name of the dimension. The 'label' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["label"] @label.setter def label(self, val): self["label"] = val # ticktext # -------- @property def ticktext(self): """ Sets alternative tick labels for the categories in this dimension. Only has an effect if `categoryorder` is set to "array". Should be an array the same length as `categoryarray` Used with `categoryorder`. The 'ticktext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ticktext"] @ticktext.setter def ticktext(self, val): self["ticktext"] = val # ticktextsrc # ----------- @property def ticktextsrc(self): """ Sets the source reference on plot.ly for ticktext . The 'ticktextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ticktextsrc"] @ticktextsrc.setter def ticktextsrc(self, val): self["ticktextsrc"] = val # values # ------ @property def values(self): """ Dimension values. `values[n]` represents the category value of the `n`th point in the dataset, therefore the `values` vector for all dimensions must be the same (longer vectors will be truncated). The 'values' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["values"] @values.setter def values(self, val): self["values"] = val # valuessrc # --------- @property def valuessrc(self): """ Sets the source reference on plot.ly for values . The 'valuessrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["valuessrc"] @valuessrc.setter def valuessrc(self, val): self["valuessrc"] = val # visible # ------- @property def visible(self): """ Shows the dimension when set to `true` (the default). Hides the dimension for `false`. The 'visible' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "parcats" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ categoryarray Sets the order in which categories in this dimension appear. Only has an effect if `categoryorder` is set to "array". Used with `categoryorder`. categoryarraysrc Sets the source reference on plot.ly for categoryarray . categoryorder Specifies the ordering logic for the categories in the dimension. By default, plotly uses "trace", which specifies the order that is present in the data supplied. Set `categoryorder` to *category ascending* or *category descending* if order should be determined by the alphanumerical order of the category names. Set `categoryorder` to "array" to derive the ordering from the attribute `categoryarray`. If a category is not found in the `categoryarray` array, the sorting behavior for that attribute will be identical to the "trace" mode. The unspecified categories will follow the categories in `categoryarray`. displayindex The display index of dimension, from left to right, zero indexed, defaults to dimension index. label The shown name of the dimension. ticktext Sets alternative tick labels for the categories in this dimension. Only has an effect if `categoryorder` is set to "array". Should be an array the same length as `categoryarray` Used with `categoryorder`. ticktextsrc Sets the source reference on plot.ly for ticktext . values Dimension values. `values[n]` represents the category value of the `n`th point in the dataset, therefore the `values` vector for all dimensions must be the same (longer vectors will be truncated). valuessrc Sets the source reference on plot.ly for values . visible Shows the dimension when set to `true` (the default). Hides the dimension for `false`. """ def __init__( self, arg=None, categoryarray=None, categoryarraysrc=None, categoryorder=None, displayindex=None, label=None, ticktext=None, ticktextsrc=None, values=None, valuessrc=None, visible=None, **kwargs ): """ Construct a new Dimension object The dimensions (variables) of the parallel categories diagram. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.parcats.Dimension categoryarray Sets the order in which categories in this dimension appear. Only has an effect if `categoryorder` is set to "array". Used with `categoryorder`. categoryarraysrc Sets the source reference on plot.ly for categoryarray . categoryorder Specifies the ordering logic for the categories in the dimension. By default, plotly uses "trace", which specifies the order that is present in the data supplied. Set `categoryorder` to *category ascending* or *category descending* if order should be determined by the alphanumerical order of the category names. Set `categoryorder` to "array" to derive the ordering from the attribute `categoryarray`. If a category is not found in the `categoryarray` array, the sorting behavior for that attribute will be identical to the "trace" mode. The unspecified categories will follow the categories in `categoryarray`. displayindex The display index of dimension, from left to right, zero indexed, defaults to dimension index. label The shown name of the dimension. ticktext Sets alternative tick labels for the categories in this dimension. Only has an effect if `categoryorder` is set to "array". Should be an array the same length as `categoryarray` Used with `categoryorder`. ticktextsrc Sets the source reference on plot.ly for ticktext . values Dimension values. `values[n]` represents the category value of the `n`th point in the dataset, therefore the `values` vector for all dimensions must be the same (longer vectors will be truncated). valuessrc Sets the source reference on plot.ly for values . visible Shows the dimension when set to `true` (the default). Hides the dimension for `false`. Returns ------- Dimension """ super(Dimension, self).__init__("dimensions") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.parcats.Dimension constructor must be a dict or an instance of plotly.graph_objs.parcats.Dimension""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.parcats import dimension as v_dimension # Initialize validators # --------------------- self._validators["categoryarray"] = v_dimension.CategoryarrayValidator() self._validators["categoryarraysrc"] = v_dimension.CategoryarraysrcValidator() self._validators["categoryorder"] = v_dimension.CategoryorderValidator() self._validators["displayindex"] = v_dimension.DisplayindexValidator() self._validators["label"] = v_dimension.LabelValidator() self._validators["ticktext"] = v_dimension.TicktextValidator() self._validators["ticktextsrc"] = v_dimension.TicktextsrcValidator() self._validators["values"] = v_dimension.ValuesValidator() self._validators["valuessrc"] = v_dimension.ValuessrcValidator() self._validators["visible"] = v_dimension.VisibleValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("categoryarray", None) self["categoryarray"] = categoryarray if categoryarray is not None else _v _v = arg.pop("categoryarraysrc", None) self["categoryarraysrc"] = ( categoryarraysrc if categoryarraysrc is not None else _v ) _v = arg.pop("categoryorder", None) self["categoryorder"] = categoryorder if categoryorder is not None else _v _v = arg.pop("displayindex", None) self["displayindex"] = displayindex if displayindex is not None else _v _v = arg.pop("label", None) self["label"] = label if label is not None else _v _v = arg.pop("ticktext", None) self["ticktext"] = ticktext if ticktext is not None else _v _v = arg.pop("ticktextsrc", None) self["ticktextsrc"] = ticktextsrc if ticktextsrc is not None else _v _v = arg.pop("values", None) self["values"] = values if values is not None else _v _v = arg.pop("valuessrc", None) self["valuessrc"] = valuessrc if valuessrc is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = [ "Dimension", "Dimension", "Domain", "Labelfont", "Line", "Stream", "Tickfont", "line", ] from plotly.graph_objs.parcats import line plotly-4.4.1+dfsg.orig/plotly/graph_objs/parcats/line/0000755000175000017500000000000013573746613022315 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/parcats/line/colorbar/0000755000175000017500000000000013573746613024120 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/parcats/line/colorbar/title/0000755000175000017500000000000013573746613025241 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/parcats/line/colorbar/title/__init__.py0000644000175000017500000002055613573721550027353 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "parcats.line.colorbar.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.parcats.line.colorbar.title.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.parcats.line.colorbar.title.Font constructor must be a dict or an instance of plotly.graph_objs.parcats.line.colorbar.title.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.parcats.line.colorbar.title import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/parcats/line/colorbar/__init__.py0000644000175000017500000006071013573721550026226 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Title(_BaseTraceHierarchyType): # font # ---- @property def font(self): """ Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.parcats.line.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.parcats.line.colorbar.title.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # side # ---- @property def side(self): """ Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- Any """ return self["side"] @side.setter def side(self, val): self["side"] = val # text # ---- @property def text(self): """ Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "parcats.line.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """ def __init__(self, arg=None, font=None, side=None, text=None, **kwargs): """ Construct a new Title object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.parcats.line.colorbar.Title font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- Title """ super(Title, self).__init__("title") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.parcats.line.colorbar.Title constructor must be a dict or an instance of plotly.graph_objs.parcats.line.colorbar.Title""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.parcats.line.colorbar import title as v_title # Initialize validators # --------------------- self._validators["font"] = v_title.FontValidator() self._validators["side"] = v_title.SideValidator() self._validators["text"] = v_title.TextValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("side", None) self["side"] = side if side is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickformatstop(_BaseTraceHierarchyType): # dtickrange # ---------- @property def dtickrange(self): """ range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" The 'dtickrange' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'dtickrange[0]' property accepts values of any type (1) The 'dtickrange[1]' property accepts values of any type Returns ------- list """ return self["dtickrange"] @dtickrange.setter def dtickrange(self, val): self["dtickrange"] = val # enabled # ------- @property def enabled(self): """ Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. The 'enabled' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["enabled"] @enabled.setter def enabled(self, val): self["enabled"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # value # ----- @property def value(self): """ string - dtickformat for described zoom level, the same as "tickformat" The 'value' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "parcats.line.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """ def __init__( self, arg=None, dtickrange=None, enabled=None, name=None, templateitemname=None, value=None, **kwargs ): """ Construct a new Tickformatstop object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.parcats.line.colorbar.Tickformatstop dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- Tickformatstop """ super(Tickformatstop, self).__init__("tickformatstops") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.parcats.line.colorbar.Tickformatstop constructor must be a dict or an instance of plotly.graph_objs.parcats.line.colorbar.Tickformatstop""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.parcats.line.colorbar import ( tickformatstop as v_tickformatstop, ) # Initialize validators # --------------------- self._validators["dtickrange"] = v_tickformatstop.DtickrangeValidator() self._validators["enabled"] = v_tickformatstop.EnabledValidator() self._validators["name"] = v_tickformatstop.NameValidator() self._validators[ "templateitemname" ] = v_tickformatstop.TemplateitemnameValidator() self._validators["value"] = v_tickformatstop.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtickrange", None) self["dtickrange"] = dtickrange if dtickrange is not None else _v _v = arg.pop("enabled", None) self["enabled"] = enabled if enabled is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "parcats.line.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Tickfont object Sets the color bar's tick label font Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.parcats.line.colorbar.Tickfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Tickfont """ super(Tickfont, self).__init__("tickfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.parcats.line.colorbar.Tickfont constructor must be a dict or an instance of plotly.graph_objs.parcats.line.colorbar.Tickfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.parcats.line.colorbar import tickfont as v_tickfont # Initialize validators # --------------------- self._validators["color"] = v_tickfont.ColorValidator() self._validators["family"] = v_tickfont.FamilyValidator() self._validators["size"] = v_tickfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Tickfont", "Tickformatstop", "Tickformatstop", "Title", "title"] from plotly.graph_objs.parcats.line.colorbar import title plotly-4.4.1+dfsg.orig/plotly/graph_objs/parcats/line/__init__.py0000644000175000017500000020770513573721550024432 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class ColorBar(_BaseTraceHierarchyType): # bgcolor # ------- @property def bgcolor(self): """ Sets the color of padded area. The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the axis line color. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # borderwidth # ----------- @property def borderwidth(self): """ Sets the width (in px) or the border enclosing this color bar. The 'borderwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["borderwidth"] @borderwidth.setter def borderwidth(self, val): self["borderwidth"] = val # dtick # ----- @property def dtick(self): """ Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" The 'dtick' property accepts values of any type Returns ------- Any """ return self["dtick"] @dtick.setter def dtick(self, val): self["dtick"] = val # exponentformat # -------------- @property def exponentformat(self): """ Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. The 'exponentformat' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'e', 'E', 'power', 'SI', 'B'] Returns ------- Any """ return self["exponentformat"] @exponentformat.setter def exponentformat(self, val): self["exponentformat"] = val # len # --- @property def len(self): """ Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. The 'len' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["len"] @len.setter def len(self, val): self["len"] = val # lenmode # ------- @property def lenmode(self): """ Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. The 'lenmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["lenmode"] @lenmode.setter def lenmode(self, val): self["lenmode"] = val # nticks # ------ @property def nticks(self): """ Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". The 'nticks' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nticks"] @nticks.setter def nticks(self, val): self["nticks"] = val # outlinecolor # ------------ @property def outlinecolor(self): """ Sets the axis line color. The 'outlinecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["outlinecolor"] @outlinecolor.setter def outlinecolor(self, val): self["outlinecolor"] = val # outlinewidth # ------------ @property def outlinewidth(self): """ Sets the width (in px) of the axis line. The 'outlinewidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["outlinewidth"] @outlinewidth.setter def outlinewidth(self, val): self["outlinewidth"] = val # separatethousands # ----------------- @property def separatethousands(self): """ If "true", even 4-digit integers are separated The 'separatethousands' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["separatethousands"] @separatethousands.setter def separatethousands(self, val): self["separatethousands"] = val # showexponent # ------------ @property def showexponent(self): """ If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. The 'showexponent' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showexponent"] @showexponent.setter def showexponent(self, val): self["showexponent"] = val # showticklabels # -------------- @property def showticklabels(self): """ Determines whether or not the tick labels are drawn. The 'showticklabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showticklabels"] @showticklabels.setter def showticklabels(self, val): self["showticklabels"] = val # showtickprefix # -------------- @property def showtickprefix(self): """ If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. The 'showtickprefix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showtickprefix"] @showtickprefix.setter def showtickprefix(self, val): self["showtickprefix"] = val # showticksuffix # -------------- @property def showticksuffix(self): """ Same as `showtickprefix` but for tick suffixes. The 'showticksuffix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showticksuffix"] @showticksuffix.setter def showticksuffix(self, val): self["showticksuffix"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # thicknessmode # ------------- @property def thicknessmode(self): """ Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. The 'thicknessmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["thicknessmode"] @thicknessmode.setter def thicknessmode(self, val): self["thicknessmode"] = val # tick0 # ----- @property def tick0(self): """ Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. The 'tick0' property accepts values of any type Returns ------- Any """ return self["tick0"] @tick0.setter def tick0(self, val): self["tick0"] = val # tickangle # --------- @property def tickangle(self): """ Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. The 'tickangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["tickangle"] @tickangle.setter def tickangle(self, val): self["tickangle"] = val # tickcolor # --------- @property def tickcolor(self): """ Sets the tick color. The 'tickcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["tickcolor"] @tickcolor.setter def tickcolor(self, val): self["tickcolor"] = val # tickfont # -------- @property def tickfont(self): """ Sets the color bar's tick label font The 'tickfont' property is an instance of Tickfont that may be specified as: - An instance of plotly.graph_objs.parcats.line.colorbar.Tickfont - A dict of string/value properties that will be passed to the Tickfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.parcats.line.colorbar.Tickfont """ return self["tickfont"] @tickfont.setter def tickfont(self, val): self["tickfont"] = val # tickformat # ---------- @property def tickformat(self): """ Sets the tick label formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'tickformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickformat"] @tickformat.setter def tickformat(self, val): self["tickformat"] = val # tickformatstops # --------------- @property def tickformatstops(self): """ The 'tickformatstops' property is a tuple of instances of Tickformatstop that may be specified as: - A list or tuple of instances of plotly.graph_objs.parcats.line.colorbar.Tickformatstop - A list or tuple of dicts of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- tuple[plotly.graph_objs.parcats.line.colorbar.Tickformatstop] """ return self["tickformatstops"] @tickformatstops.setter def tickformatstops(self, val): self["tickformatstops"] = val # tickformatstopdefaults # ---------------------- @property def tickformatstopdefaults(self): """ When used in a template (as layout.template.data.parcats.line.c olorbar.tickformatstopdefaults), sets the default property values to use for elements of parcats.line.colorbar.tickformatstops The 'tickformatstopdefaults' property is an instance of Tickformatstop that may be specified as: - An instance of plotly.graph_objs.parcats.line.colorbar.Tickformatstop - A dict of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: Returns ------- plotly.graph_objs.parcats.line.colorbar.Tickformatstop """ return self["tickformatstopdefaults"] @tickformatstopdefaults.setter def tickformatstopdefaults(self, val): self["tickformatstopdefaults"] = val # ticklen # ------- @property def ticklen(self): """ Sets the tick length (in px). The 'ticklen' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ticklen"] @ticklen.setter def ticklen(self, val): self["ticklen"] = val # tickmode # -------- @property def tickmode(self): """ Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). The 'tickmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'linear', 'array'] Returns ------- Any """ return self["tickmode"] @tickmode.setter def tickmode(self, val): self["tickmode"] = val # tickprefix # ---------- @property def tickprefix(self): """ Sets a tick label prefix. The 'tickprefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickprefix"] @tickprefix.setter def tickprefix(self, val): self["tickprefix"] = val # ticks # ----- @property def ticks(self): """ Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. The 'ticks' property is an enumeration that may be specified as: - One of the following enumeration values: ['outside', 'inside', ''] Returns ------- Any """ return self["ticks"] @ticks.setter def ticks(self, val): self["ticks"] = val # ticksuffix # ---------- @property def ticksuffix(self): """ Sets a tick label suffix. The 'ticksuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ticksuffix"] @ticksuffix.setter def ticksuffix(self, val): self["ticksuffix"] = val # ticktext # -------- @property def ticktext(self): """ Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. The 'ticktext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ticktext"] @ticktext.setter def ticktext(self, val): self["ticktext"] = val # ticktextsrc # ----------- @property def ticktextsrc(self): """ Sets the source reference on plot.ly for ticktext . The 'ticktextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ticktextsrc"] @ticktextsrc.setter def ticktextsrc(self, val): self["ticktextsrc"] = val # tickvals # -------- @property def tickvals(self): """ Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. The 'tickvals' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["tickvals"] @tickvals.setter def tickvals(self, val): self["tickvals"] = val # tickvalssrc # ----------- @property def tickvalssrc(self): """ Sets the source reference on plot.ly for tickvals . The 'tickvalssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tickvalssrc"] @tickvalssrc.setter def tickvalssrc(self, val): self["tickvalssrc"] = val # tickwidth # --------- @property def tickwidth(self): """ Sets the tick width (in px). The 'tickwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["tickwidth"] @tickwidth.setter def tickwidth(self, val): self["tickwidth"] = val # title # ----- @property def title(self): """ The 'title' property is an instance of Title that may be specified as: - An instance of plotly.graph_objs.parcats.line.colorbar.Title - A dict of string/value properties that will be passed to the Title constructor Supported dict properties: font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- plotly.graph_objs.parcats.line.colorbar.Title """ return self["title"] @title.setter def title(self, val): self["title"] = val # titlefont # --------- @property def titlefont(self): """ Deprecated: Please use parcats.line.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.parcats.line.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- """ return self["titlefont"] @titlefont.setter def titlefont(self, val): self["titlefont"] = val # titleside # --------- @property def titleside(self): """ Deprecated: Please use parcats.line.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- """ return self["titleside"] @titleside.setter def titleside(self, val): self["titleside"] = val # x # - @property def x(self): """ Sets the x position of the color bar (in plot fraction). The 'x' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["x"] @x.setter def x(self, val): self["x"] = val # xanchor # ------- @property def xanchor(self): """ Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. The 'xanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'center', 'right'] Returns ------- Any """ return self["xanchor"] @xanchor.setter def xanchor(self, val): self["xanchor"] = val # xpad # ---- @property def xpad(self): """ Sets the amount of padding (in px) along the x direction. The 'xpad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["xpad"] @xpad.setter def xpad(self, val): self["xpad"] = val # y # - @property def y(self): """ Sets the y position of the color bar (in plot fraction). The 'y' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["y"] @y.setter def y(self, val): self["y"] = val # yanchor # ------- @property def yanchor(self): """ Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. The 'yanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['top', 'middle', 'bottom'] Returns ------- Any """ return self["yanchor"] @yanchor.setter def yanchor(self, val): self["yanchor"] = val # ypad # ---- @property def ypad(self): """ Sets the amount of padding (in px) along the y direction. The 'ypad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ypad"] @ypad.setter def ypad(self, val): self["ypad"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "parcats.line" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.parcats.line.colorbar.T ickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.parcat s.line.colorbar.tickformatstopdefaults), sets the default property values to use for elements of parcats.line.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.parcats.line.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use parcats.line.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use parcats.line.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """ _mapped_properties = { "titlefont": ("title", "font"), "titleside": ("title", "side"), } def __init__( self, arg=None, bgcolor=None, bordercolor=None, borderwidth=None, dtick=None, exponentformat=None, len=None, lenmode=None, nticks=None, outlinecolor=None, outlinewidth=None, separatethousands=None, showexponent=None, showticklabels=None, showtickprefix=None, showticksuffix=None, thickness=None, thicknessmode=None, tick0=None, tickangle=None, tickcolor=None, tickfont=None, tickformat=None, tickformatstops=None, tickformatstopdefaults=None, ticklen=None, tickmode=None, tickprefix=None, ticks=None, ticksuffix=None, ticktext=None, ticktextsrc=None, tickvals=None, tickvalssrc=None, tickwidth=None, title=None, titlefont=None, titleside=None, x=None, xanchor=None, xpad=None, y=None, yanchor=None, ypad=None, **kwargs ): """ Construct a new ColorBar object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.parcats.line.ColorBar bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.parcats.line.colorbar.T ickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.parcat s.line.colorbar.tickformatstopdefaults), sets the default property values to use for elements of parcats.line.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.parcats.line.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use parcats.line.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use parcats.line.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- ColorBar """ super(ColorBar, self).__init__("colorbar") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.parcats.line.ColorBar constructor must be a dict or an instance of plotly.graph_objs.parcats.line.ColorBar""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.parcats.line import colorbar as v_colorbar # Initialize validators # --------------------- self._validators["bgcolor"] = v_colorbar.BgcolorValidator() self._validators["bordercolor"] = v_colorbar.BordercolorValidator() self._validators["borderwidth"] = v_colorbar.BorderwidthValidator() self._validators["dtick"] = v_colorbar.DtickValidator() self._validators["exponentformat"] = v_colorbar.ExponentformatValidator() self._validators["len"] = v_colorbar.LenValidator() self._validators["lenmode"] = v_colorbar.LenmodeValidator() self._validators["nticks"] = v_colorbar.NticksValidator() self._validators["outlinecolor"] = v_colorbar.OutlinecolorValidator() self._validators["outlinewidth"] = v_colorbar.OutlinewidthValidator() self._validators["separatethousands"] = v_colorbar.SeparatethousandsValidator() self._validators["showexponent"] = v_colorbar.ShowexponentValidator() self._validators["showticklabels"] = v_colorbar.ShowticklabelsValidator() self._validators["showtickprefix"] = v_colorbar.ShowtickprefixValidator() self._validators["showticksuffix"] = v_colorbar.ShowticksuffixValidator() self._validators["thickness"] = v_colorbar.ThicknessValidator() self._validators["thicknessmode"] = v_colorbar.ThicknessmodeValidator() self._validators["tick0"] = v_colorbar.Tick0Validator() self._validators["tickangle"] = v_colorbar.TickangleValidator() self._validators["tickcolor"] = v_colorbar.TickcolorValidator() self._validators["tickfont"] = v_colorbar.TickfontValidator() self._validators["tickformat"] = v_colorbar.TickformatValidator() self._validators["tickformatstops"] = v_colorbar.TickformatstopsValidator() self._validators[ "tickformatstopdefaults" ] = v_colorbar.TickformatstopValidator() self._validators["ticklen"] = v_colorbar.TicklenValidator() self._validators["tickmode"] = v_colorbar.TickmodeValidator() self._validators["tickprefix"] = v_colorbar.TickprefixValidator() self._validators["ticks"] = v_colorbar.TicksValidator() self._validators["ticksuffix"] = v_colorbar.TicksuffixValidator() self._validators["ticktext"] = v_colorbar.TicktextValidator() self._validators["ticktextsrc"] = v_colorbar.TicktextsrcValidator() self._validators["tickvals"] = v_colorbar.TickvalsValidator() self._validators["tickvalssrc"] = v_colorbar.TickvalssrcValidator() self._validators["tickwidth"] = v_colorbar.TickwidthValidator() self._validators["title"] = v_colorbar.TitleValidator() self._validators["x"] = v_colorbar.XValidator() self._validators["xanchor"] = v_colorbar.XanchorValidator() self._validators["xpad"] = v_colorbar.XpadValidator() self._validators["y"] = v_colorbar.YValidator() self._validators["yanchor"] = v_colorbar.YanchorValidator() self._validators["ypad"] = v_colorbar.YpadValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("borderwidth", None) self["borderwidth"] = borderwidth if borderwidth is not None else _v _v = arg.pop("dtick", None) self["dtick"] = dtick if dtick is not None else _v _v = arg.pop("exponentformat", None) self["exponentformat"] = exponentformat if exponentformat is not None else _v _v = arg.pop("len", None) self["len"] = len if len is not None else _v _v = arg.pop("lenmode", None) self["lenmode"] = lenmode if lenmode is not None else _v _v = arg.pop("nticks", None) self["nticks"] = nticks if nticks is not None else _v _v = arg.pop("outlinecolor", None) self["outlinecolor"] = outlinecolor if outlinecolor is not None else _v _v = arg.pop("outlinewidth", None) self["outlinewidth"] = outlinewidth if outlinewidth is not None else _v _v = arg.pop("separatethousands", None) self["separatethousands"] = ( separatethousands if separatethousands is not None else _v ) _v = arg.pop("showexponent", None) self["showexponent"] = showexponent if showexponent is not None else _v _v = arg.pop("showticklabels", None) self["showticklabels"] = showticklabels if showticklabels is not None else _v _v = arg.pop("showtickprefix", None) self["showtickprefix"] = showtickprefix if showtickprefix is not None else _v _v = arg.pop("showticksuffix", None) self["showticksuffix"] = showticksuffix if showticksuffix is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("thicknessmode", None) self["thicknessmode"] = thicknessmode if thicknessmode is not None else _v _v = arg.pop("tick0", None) self["tick0"] = tick0 if tick0 is not None else _v _v = arg.pop("tickangle", None) self["tickangle"] = tickangle if tickangle is not None else _v _v = arg.pop("tickcolor", None) self["tickcolor"] = tickcolor if tickcolor is not None else _v _v = arg.pop("tickfont", None) self["tickfont"] = tickfont if tickfont is not None else _v _v = arg.pop("tickformat", None) self["tickformat"] = tickformat if tickformat is not None else _v _v = arg.pop("tickformatstops", None) self["tickformatstops"] = tickformatstops if tickformatstops is not None else _v _v = arg.pop("tickformatstopdefaults", None) self["tickformatstopdefaults"] = ( tickformatstopdefaults if tickformatstopdefaults is not None else _v ) _v = arg.pop("ticklen", None) self["ticklen"] = ticklen if ticklen is not None else _v _v = arg.pop("tickmode", None) self["tickmode"] = tickmode if tickmode is not None else _v _v = arg.pop("tickprefix", None) self["tickprefix"] = tickprefix if tickprefix is not None else _v _v = arg.pop("ticks", None) self["ticks"] = ticks if ticks is not None else _v _v = arg.pop("ticksuffix", None) self["ticksuffix"] = ticksuffix if ticksuffix is not None else _v _v = arg.pop("ticktext", None) self["ticktext"] = ticktext if ticktext is not None else _v _v = arg.pop("ticktextsrc", None) self["ticktextsrc"] = ticktextsrc if ticktextsrc is not None else _v _v = arg.pop("tickvals", None) self["tickvals"] = tickvals if tickvals is not None else _v _v = arg.pop("tickvalssrc", None) self["tickvalssrc"] = tickvalssrc if tickvalssrc is not None else _v _v = arg.pop("tickwidth", None) self["tickwidth"] = tickwidth if tickwidth is not None else _v _v = arg.pop("title", None) self["title"] = title if title is not None else _v _v = arg.pop("titlefont", None) _v = titlefont if titlefont is not None else _v if _v is not None: self["titlefont"] = _v _v = arg.pop("titleside", None) _v = titleside if titleside is not None else _v if _v is not None: self["titleside"] = _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xanchor", None) self["xanchor"] = xanchor if xanchor is not None else _v _v = arg.pop("xpad", None) self["xpad"] = xpad if xpad is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("yanchor", None) self["yanchor"] = yanchor if yanchor is not None else _v _v = arg.pop("ypad", None) self["ypad"] = ypad if ypad is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["ColorBar", "colorbar"] from plotly.graph_objs.parcats.line import colorbar plotly-4.4.1+dfsg.orig/plotly/graph_objs/scatterpolar/0000755000175000017500000000000013573746613022434 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scatterpolar/unselected/0000755000175000017500000000000013573746613024567 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scatterpolar/unselected/__init__.py0000644000175000017500000002771413573721551026705 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Textfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the text font color of unselected points, applied only when a selection exists. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterpolar.unselected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the text font color of unselected points, applied only when a selection exists. """ def __init__(self, arg=None, color=None, **kwargs): """ Construct a new Textfont object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterpolar.unselected.Textfont color Sets the text font color of unselected points, applied only when a selection exists. Returns ------- Textfont """ super(Textfont, self).__init__("textfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterpolar.unselected.Textfont constructor must be a dict or an instance of plotly.graph_objs.scatterpolar.unselected.Textfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterpolar.unselected import textfont as v_textfont # Initialize validators # --------------------- self._validators["color"] = v_textfont.ColorValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the marker color of unselected points, applied only when a selection exists. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # opacity # ------- @property def opacity(self): """ Sets the marker opacity of unselected points, applied only when a selection exists. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # size # ---- @property def size(self): """ Sets the marker size of unselected points, applied only when a selection exists. The 'size' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterpolar.unselected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. size Sets the marker size of unselected points, applied only when a selection exists. """ def __init__(self, arg=None, color=None, opacity=None, size=None, **kwargs): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterpolar.unselected.Marker color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. size Sets the marker size of unselected points, applied only when a selection exists. Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterpolar.unselected.Marker constructor must be a dict or an instance of plotly.graph_objs.scatterpolar.unselected.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterpolar.unselected import marker as v_marker # Initialize validators # --------------------- self._validators["color"] = v_marker.ColorValidator() self._validators["opacity"] = v_marker.OpacityValidator() self._validators["size"] = v_marker.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Marker", "Textfont"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/scatterpolar/hoverlabel/0000755000175000017500000000000013573746613024557 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scatterpolar/hoverlabel/__init__.py0000644000175000017500000002547113573721551026673 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterpolar.hoverlabel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Font object Sets the font used in hover labels. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterpolar.hoverlabel.Font color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterpolar.hoverlabel.Font constructor must be a dict or an instance of plotly.graph_objs.scatterpolar.hoverlabel.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterpolar.hoverlabel import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["colorsrc"] = v_font.ColorsrcValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["familysrc"] = v_font.FamilysrcValidator() self._validators["size"] = v_font.SizeValidator() self._validators["sizesrc"] = v_font.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/scatterpolar/marker/0000755000175000017500000000000013573746613023715 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scatterpolar/marker/colorbar/0000755000175000017500000000000013573746613025520 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scatterpolar/marker/colorbar/title/0000755000175000017500000000000013573746613026641 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scatterpolar/marker/colorbar/title/__init__.py0000644000175000017500000002062213573721551030746 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterpolar.marker.colorbar.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterpolar.marker.co lorbar.title.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterpolar.marker.colorbar.title.Font constructor must be a dict or an instance of plotly.graph_objs.scatterpolar.marker.colorbar.title.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterpolar.marker.colorbar.title import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/scatterpolar/marker/colorbar/__init__.py0000644000175000017500000006114013573721551027625 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Title(_BaseTraceHierarchyType): # font # ---- @property def font(self): """ Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.scatterpolar.marker.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.scatterpolar.marker.colorbar.title.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # side # ---- @property def side(self): """ Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- Any """ return self["side"] @side.setter def side(self, val): self["side"] = val # text # ---- @property def text(self): """ Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterpolar.marker.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """ def __init__(self, arg=None, font=None, side=None, text=None, **kwargs): """ Construct a new Title object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterpolar.marker.colorbar.Title font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- Title """ super(Title, self).__init__("title") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterpolar.marker.colorbar.Title constructor must be a dict or an instance of plotly.graph_objs.scatterpolar.marker.colorbar.Title""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterpolar.marker.colorbar import title as v_title # Initialize validators # --------------------- self._validators["font"] = v_title.FontValidator() self._validators["side"] = v_title.SideValidator() self._validators["text"] = v_title.TextValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("side", None) self["side"] = side if side is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickformatstop(_BaseTraceHierarchyType): # dtickrange # ---------- @property def dtickrange(self): """ range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" The 'dtickrange' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'dtickrange[0]' property accepts values of any type (1) The 'dtickrange[1]' property accepts values of any type Returns ------- list """ return self["dtickrange"] @dtickrange.setter def dtickrange(self, val): self["dtickrange"] = val # enabled # ------- @property def enabled(self): """ Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. The 'enabled' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["enabled"] @enabled.setter def enabled(self, val): self["enabled"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # value # ----- @property def value(self): """ string - dtickformat for described zoom level, the same as "tickformat" The 'value' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterpolar.marker.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """ def __init__( self, arg=None, dtickrange=None, enabled=None, name=None, templateitemname=None, value=None, **kwargs ): """ Construct a new Tickformatstop object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterpolar.marker.co lorbar.Tickformatstop dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- Tickformatstop """ super(Tickformatstop, self).__init__("tickformatstops") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterpolar.marker.colorbar.Tickformatstop constructor must be a dict or an instance of plotly.graph_objs.scatterpolar.marker.colorbar.Tickformatstop""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterpolar.marker.colorbar import ( tickformatstop as v_tickformatstop, ) # Initialize validators # --------------------- self._validators["dtickrange"] = v_tickformatstop.DtickrangeValidator() self._validators["enabled"] = v_tickformatstop.EnabledValidator() self._validators["name"] = v_tickformatstop.NameValidator() self._validators[ "templateitemname" ] = v_tickformatstop.TemplateitemnameValidator() self._validators["value"] = v_tickformatstop.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtickrange", None) self["dtickrange"] = dtickrange if dtickrange is not None else _v _v = arg.pop("enabled", None) self["enabled"] = enabled if enabled is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterpolar.marker.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Tickfont object Sets the color bar's tick label font Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterpolar.marker.colorbar.Tickfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Tickfont """ super(Tickfont, self).__init__("tickfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterpolar.marker.colorbar.Tickfont constructor must be a dict or an instance of plotly.graph_objs.scatterpolar.marker.colorbar.Tickfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterpolar.marker.colorbar import ( tickfont as v_tickfont, ) # Initialize validators # --------------------- self._validators["color"] = v_tickfont.ColorValidator() self._validators["family"] = v_tickfont.FamilyValidator() self._validators["size"] = v_tickfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Tickfont", "Tickformatstop", "Tickformatstop", "Title", "title"] from plotly.graph_objs.scatterpolar.marker.colorbar import title plotly-4.4.1+dfsg.orig/plotly/graph_objs/scatterpolar/marker/__init__.py0000644000175000017500000031024513573721553026027 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # autocolorscale # -------------- @property def autocolorscale(self): """ Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. The 'autocolorscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocolorscale"] @autocolorscale.setter def autocolorscale(self, val): self["autocolorscale"] = val # cauto # ----- @property def cauto(self): """ Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. The 'cauto' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["cauto"] @cauto.setter def cauto(self, val): self["cauto"] = val # cmax # ---- @property def cmax(self): """ Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. The 'cmax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmax"] @cmax.setter def cmax(self, val): self["cmax"] = val # cmid # ---- @property def cmid(self): """ Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. The 'cmid' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmid"] @cmid.setter def cmid(self, val): self["cmid"] = val # cmin # ---- @property def cmin(self): """ Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. The 'cmin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmin"] @cmin.setter def cmin(self, val): self["cmin"] = val # color # ----- @property def color(self): """ Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A number that will be interpreted as a color according to scatterpolar.marker.line.colorscale - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # coloraxis # --------- @property def coloraxis(self): """ Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. The 'coloraxis' property is an identifier of a particular subplot, of type 'coloraxis', that may be specified as the string 'coloraxis' optionally followed by an integer >= 1 (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) Returns ------- str """ return self["coloraxis"] @coloraxis.setter def coloraxis(self, val): self["coloraxis"] = val # colorscale # ---------- @property def colorscale(self): """ Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,Earth,Electric,Vi ridis,Cividis. The 'colorscale' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # reversescale # ------------ @property def reversescale(self): """ Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. The 'reversescale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["reversescale"] @reversescale.setter def reversescale(self, val): self["reversescale"] = val # width # ----- @property def width(self): """ Sets the width (in px) of the lines bounding the marker points. The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["width"] @width.setter def width(self, val): self["width"] = val # widthsrc # -------- @property def widthsrc(self): """ Sets the source reference on plot.ly for width . The 'widthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["widthsrc"] @widthsrc.setter def widthsrc(self, val): self["widthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterpolar.marker" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . """ def __init__( self, arg=None, autocolorscale=None, cauto=None, cmax=None, cmid=None, cmin=None, color=None, coloraxis=None, colorscale=None, colorsrc=None, reversescale=None, width=None, widthsrc=None, **kwargs ): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterpolar.marker.Line autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterpolar.marker.Line constructor must be a dict or an instance of plotly.graph_objs.scatterpolar.marker.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterpolar.marker import line as v_line # Initialize validators # --------------------- self._validators["autocolorscale"] = v_line.AutocolorscaleValidator() self._validators["cauto"] = v_line.CautoValidator() self._validators["cmax"] = v_line.CmaxValidator() self._validators["cmid"] = v_line.CmidValidator() self._validators["cmin"] = v_line.CminValidator() self._validators["color"] = v_line.ColorValidator() self._validators["coloraxis"] = v_line.ColoraxisValidator() self._validators["colorscale"] = v_line.ColorscaleValidator() self._validators["colorsrc"] = v_line.ColorsrcValidator() self._validators["reversescale"] = v_line.ReversescaleValidator() self._validators["width"] = v_line.WidthValidator() self._validators["widthsrc"] = v_line.WidthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autocolorscale", None) self["autocolorscale"] = autocolorscale if autocolorscale is not None else _v _v = arg.pop("cauto", None) self["cauto"] = cauto if cauto is not None else _v _v = arg.pop("cmax", None) self["cmax"] = cmax if cmax is not None else _v _v = arg.pop("cmid", None) self["cmid"] = cmid if cmid is not None else _v _v = arg.pop("cmin", None) self["cmin"] = cmin if cmin is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("coloraxis", None) self["coloraxis"] = coloraxis if coloraxis is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("reversescale", None) self["reversescale"] = reversescale if reversescale is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v _v = arg.pop("widthsrc", None) self["widthsrc"] = widthsrc if widthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Gradient(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the final color of the gradient fill: the center color for radial, the right for horizontal, or the bottom for vertical. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # type # ---- @property def type(self): """ Sets the type of gradient used to fill the markers The 'type' property is an enumeration that may be specified as: - One of the following enumeration values: ['radial', 'horizontal', 'vertical', 'none'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["type"] @type.setter def type(self, val): self["type"] = val # typesrc # ------- @property def typesrc(self): """ Sets the source reference on plot.ly for type . The 'typesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["typesrc"] @typesrc.setter def typesrc(self, val): self["typesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterpolar.marker" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the final color of the gradient fill: the center color for radial, the right for horizontal, or the bottom for vertical. colorsrc Sets the source reference on plot.ly for color . type Sets the type of gradient used to fill the markers typesrc Sets the source reference on plot.ly for type . """ def __init__( self, arg=None, color=None, colorsrc=None, type=None, typesrc=None, **kwargs ): """ Construct a new Gradient object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterpolar.marker.Gradient color Sets the final color of the gradient fill: the center color for radial, the right for horizontal, or the bottom for vertical. colorsrc Sets the source reference on plot.ly for color . type Sets the type of gradient used to fill the markers typesrc Sets the source reference on plot.ly for type . Returns ------- Gradient """ super(Gradient, self).__init__("gradient") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterpolar.marker.Gradient constructor must be a dict or an instance of plotly.graph_objs.scatterpolar.marker.Gradient""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterpolar.marker import gradient as v_gradient # Initialize validators # --------------------- self._validators["color"] = v_gradient.ColorValidator() self._validators["colorsrc"] = v_gradient.ColorsrcValidator() self._validators["type"] = v_gradient.TypeValidator() self._validators["typesrc"] = v_gradient.TypesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("type", None) self["type"] = type if type is not None else _v _v = arg.pop("typesrc", None) self["typesrc"] = typesrc if typesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class ColorBar(_BaseTraceHierarchyType): # bgcolor # ------- @property def bgcolor(self): """ Sets the color of padded area. The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the axis line color. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # borderwidth # ----------- @property def borderwidth(self): """ Sets the width (in px) or the border enclosing this color bar. The 'borderwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["borderwidth"] @borderwidth.setter def borderwidth(self, val): self["borderwidth"] = val # dtick # ----- @property def dtick(self): """ Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" The 'dtick' property accepts values of any type Returns ------- Any """ return self["dtick"] @dtick.setter def dtick(self, val): self["dtick"] = val # exponentformat # -------------- @property def exponentformat(self): """ Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. The 'exponentformat' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'e', 'E', 'power', 'SI', 'B'] Returns ------- Any """ return self["exponentformat"] @exponentformat.setter def exponentformat(self, val): self["exponentformat"] = val # len # --- @property def len(self): """ Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. The 'len' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["len"] @len.setter def len(self, val): self["len"] = val # lenmode # ------- @property def lenmode(self): """ Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. The 'lenmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["lenmode"] @lenmode.setter def lenmode(self, val): self["lenmode"] = val # nticks # ------ @property def nticks(self): """ Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". The 'nticks' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nticks"] @nticks.setter def nticks(self, val): self["nticks"] = val # outlinecolor # ------------ @property def outlinecolor(self): """ Sets the axis line color. The 'outlinecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["outlinecolor"] @outlinecolor.setter def outlinecolor(self, val): self["outlinecolor"] = val # outlinewidth # ------------ @property def outlinewidth(self): """ Sets the width (in px) of the axis line. The 'outlinewidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["outlinewidth"] @outlinewidth.setter def outlinewidth(self, val): self["outlinewidth"] = val # separatethousands # ----------------- @property def separatethousands(self): """ If "true", even 4-digit integers are separated The 'separatethousands' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["separatethousands"] @separatethousands.setter def separatethousands(self, val): self["separatethousands"] = val # showexponent # ------------ @property def showexponent(self): """ If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. The 'showexponent' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showexponent"] @showexponent.setter def showexponent(self, val): self["showexponent"] = val # showticklabels # -------------- @property def showticklabels(self): """ Determines whether or not the tick labels are drawn. The 'showticklabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showticklabels"] @showticklabels.setter def showticklabels(self, val): self["showticklabels"] = val # showtickprefix # -------------- @property def showtickprefix(self): """ If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. The 'showtickprefix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showtickprefix"] @showtickprefix.setter def showtickprefix(self, val): self["showtickprefix"] = val # showticksuffix # -------------- @property def showticksuffix(self): """ Same as `showtickprefix` but for tick suffixes. The 'showticksuffix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showticksuffix"] @showticksuffix.setter def showticksuffix(self, val): self["showticksuffix"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # thicknessmode # ------------- @property def thicknessmode(self): """ Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. The 'thicknessmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["thicknessmode"] @thicknessmode.setter def thicknessmode(self, val): self["thicknessmode"] = val # tick0 # ----- @property def tick0(self): """ Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. The 'tick0' property accepts values of any type Returns ------- Any """ return self["tick0"] @tick0.setter def tick0(self, val): self["tick0"] = val # tickangle # --------- @property def tickangle(self): """ Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. The 'tickangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["tickangle"] @tickangle.setter def tickangle(self, val): self["tickangle"] = val # tickcolor # --------- @property def tickcolor(self): """ Sets the tick color. The 'tickcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["tickcolor"] @tickcolor.setter def tickcolor(self, val): self["tickcolor"] = val # tickfont # -------- @property def tickfont(self): """ Sets the color bar's tick label font The 'tickfont' property is an instance of Tickfont that may be specified as: - An instance of plotly.graph_objs.scatterpolar.marker.colorbar.Tickfont - A dict of string/value properties that will be passed to the Tickfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.scatterpolar.marker.colorbar.Tickfont """ return self["tickfont"] @tickfont.setter def tickfont(self, val): self["tickfont"] = val # tickformat # ---------- @property def tickformat(self): """ Sets the tick label formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'tickformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickformat"] @tickformat.setter def tickformat(self, val): self["tickformat"] = val # tickformatstops # --------------- @property def tickformatstops(self): """ The 'tickformatstops' property is a tuple of instances of Tickformatstop that may be specified as: - A list or tuple of instances of plotly.graph_objs.scatterpolar.marker.colorbar.Tickformatstop - A list or tuple of dicts of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- tuple[plotly.graph_objs.scatterpolar.marker.colorbar.Tickformatstop] """ return self["tickformatstops"] @tickformatstops.setter def tickformatstops(self, val): self["tickformatstops"] = val # tickformatstopdefaults # ---------------------- @property def tickformatstopdefaults(self): """ When used in a template (as layout.template.data.scatterpolar.m arker.colorbar.tickformatstopdefaults), sets the default property values to use for elements of scatterpolar.marker.colorbar.tickformatstops The 'tickformatstopdefaults' property is an instance of Tickformatstop that may be specified as: - An instance of plotly.graph_objs.scatterpolar.marker.colorbar.Tickformatstop - A dict of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: Returns ------- plotly.graph_objs.scatterpolar.marker.colorbar.Tickformatstop """ return self["tickformatstopdefaults"] @tickformatstopdefaults.setter def tickformatstopdefaults(self, val): self["tickformatstopdefaults"] = val # ticklen # ------- @property def ticklen(self): """ Sets the tick length (in px). The 'ticklen' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ticklen"] @ticklen.setter def ticklen(self, val): self["ticklen"] = val # tickmode # -------- @property def tickmode(self): """ Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). The 'tickmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'linear', 'array'] Returns ------- Any """ return self["tickmode"] @tickmode.setter def tickmode(self, val): self["tickmode"] = val # tickprefix # ---------- @property def tickprefix(self): """ Sets a tick label prefix. The 'tickprefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickprefix"] @tickprefix.setter def tickprefix(self, val): self["tickprefix"] = val # ticks # ----- @property def ticks(self): """ Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. The 'ticks' property is an enumeration that may be specified as: - One of the following enumeration values: ['outside', 'inside', ''] Returns ------- Any """ return self["ticks"] @ticks.setter def ticks(self, val): self["ticks"] = val # ticksuffix # ---------- @property def ticksuffix(self): """ Sets a tick label suffix. The 'ticksuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ticksuffix"] @ticksuffix.setter def ticksuffix(self, val): self["ticksuffix"] = val # ticktext # -------- @property def ticktext(self): """ Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. The 'ticktext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ticktext"] @ticktext.setter def ticktext(self, val): self["ticktext"] = val # ticktextsrc # ----------- @property def ticktextsrc(self): """ Sets the source reference on plot.ly for ticktext . The 'ticktextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ticktextsrc"] @ticktextsrc.setter def ticktextsrc(self, val): self["ticktextsrc"] = val # tickvals # -------- @property def tickvals(self): """ Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. The 'tickvals' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["tickvals"] @tickvals.setter def tickvals(self, val): self["tickvals"] = val # tickvalssrc # ----------- @property def tickvalssrc(self): """ Sets the source reference on plot.ly for tickvals . The 'tickvalssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tickvalssrc"] @tickvalssrc.setter def tickvalssrc(self, val): self["tickvalssrc"] = val # tickwidth # --------- @property def tickwidth(self): """ Sets the tick width (in px). The 'tickwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["tickwidth"] @tickwidth.setter def tickwidth(self, val): self["tickwidth"] = val # title # ----- @property def title(self): """ The 'title' property is an instance of Title that may be specified as: - An instance of plotly.graph_objs.scatterpolar.marker.colorbar.Title - A dict of string/value properties that will be passed to the Title constructor Supported dict properties: font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- plotly.graph_objs.scatterpolar.marker.colorbar.Title """ return self["title"] @title.setter def title(self, val): self["title"] = val # titlefont # --------- @property def titlefont(self): """ Deprecated: Please use scatterpolar.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.scatterpolar.marker.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- """ return self["titlefont"] @titlefont.setter def titlefont(self, val): self["titlefont"] = val # titleside # --------- @property def titleside(self): """ Deprecated: Please use scatterpolar.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- """ return self["titleside"] @titleside.setter def titleside(self, val): self["titleside"] = val # x # - @property def x(self): """ Sets the x position of the color bar (in plot fraction). The 'x' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["x"] @x.setter def x(self, val): self["x"] = val # xanchor # ------- @property def xanchor(self): """ Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. The 'xanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'center', 'right'] Returns ------- Any """ return self["xanchor"] @xanchor.setter def xanchor(self, val): self["xanchor"] = val # xpad # ---- @property def xpad(self): """ Sets the amount of padding (in px) along the x direction. The 'xpad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["xpad"] @xpad.setter def xpad(self, val): self["xpad"] = val # y # - @property def y(self): """ Sets the y position of the color bar (in plot fraction). The 'y' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["y"] @y.setter def y(self, val): self["y"] = val # yanchor # ------- @property def yanchor(self): """ Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. The 'yanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['top', 'middle', 'bottom'] Returns ------- Any """ return self["yanchor"] @yanchor.setter def yanchor(self, val): self["yanchor"] = val # ypad # ---- @property def ypad(self): """ Sets the amount of padding (in px) along the y direction. The 'ypad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ypad"] @ypad.setter def ypad(self, val): self["ypad"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterpolar.marker" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.scatterpolar.marker.col orbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.scatte rpolar.marker.colorbar.tickformatstopdefaults), sets the default property values to use for elements of scatterpolar.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.scatterpolar.marker.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use scatterpolar.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use scatterpolar.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """ _mapped_properties = { "titlefont": ("title", "font"), "titleside": ("title", "side"), } def __init__( self, arg=None, bgcolor=None, bordercolor=None, borderwidth=None, dtick=None, exponentformat=None, len=None, lenmode=None, nticks=None, outlinecolor=None, outlinewidth=None, separatethousands=None, showexponent=None, showticklabels=None, showtickprefix=None, showticksuffix=None, thickness=None, thicknessmode=None, tick0=None, tickangle=None, tickcolor=None, tickfont=None, tickformat=None, tickformatstops=None, tickformatstopdefaults=None, ticklen=None, tickmode=None, tickprefix=None, ticks=None, ticksuffix=None, ticktext=None, ticktextsrc=None, tickvals=None, tickvalssrc=None, tickwidth=None, title=None, titlefont=None, titleside=None, x=None, xanchor=None, xpad=None, y=None, yanchor=None, ypad=None, **kwargs ): """ Construct a new ColorBar object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterpolar.marker.ColorBar bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.scatterpolar.marker.col orbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.scatte rpolar.marker.colorbar.tickformatstopdefaults), sets the default property values to use for elements of scatterpolar.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.scatterpolar.marker.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use scatterpolar.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use scatterpolar.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- ColorBar """ super(ColorBar, self).__init__("colorbar") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterpolar.marker.ColorBar constructor must be a dict or an instance of plotly.graph_objs.scatterpolar.marker.ColorBar""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterpolar.marker import colorbar as v_colorbar # Initialize validators # --------------------- self._validators["bgcolor"] = v_colorbar.BgcolorValidator() self._validators["bordercolor"] = v_colorbar.BordercolorValidator() self._validators["borderwidth"] = v_colorbar.BorderwidthValidator() self._validators["dtick"] = v_colorbar.DtickValidator() self._validators["exponentformat"] = v_colorbar.ExponentformatValidator() self._validators["len"] = v_colorbar.LenValidator() self._validators["lenmode"] = v_colorbar.LenmodeValidator() self._validators["nticks"] = v_colorbar.NticksValidator() self._validators["outlinecolor"] = v_colorbar.OutlinecolorValidator() self._validators["outlinewidth"] = v_colorbar.OutlinewidthValidator() self._validators["separatethousands"] = v_colorbar.SeparatethousandsValidator() self._validators["showexponent"] = v_colorbar.ShowexponentValidator() self._validators["showticklabels"] = v_colorbar.ShowticklabelsValidator() self._validators["showtickprefix"] = v_colorbar.ShowtickprefixValidator() self._validators["showticksuffix"] = v_colorbar.ShowticksuffixValidator() self._validators["thickness"] = v_colorbar.ThicknessValidator() self._validators["thicknessmode"] = v_colorbar.ThicknessmodeValidator() self._validators["tick0"] = v_colorbar.Tick0Validator() self._validators["tickangle"] = v_colorbar.TickangleValidator() self._validators["tickcolor"] = v_colorbar.TickcolorValidator() self._validators["tickfont"] = v_colorbar.TickfontValidator() self._validators["tickformat"] = v_colorbar.TickformatValidator() self._validators["tickformatstops"] = v_colorbar.TickformatstopsValidator() self._validators[ "tickformatstopdefaults" ] = v_colorbar.TickformatstopValidator() self._validators["ticklen"] = v_colorbar.TicklenValidator() self._validators["tickmode"] = v_colorbar.TickmodeValidator() self._validators["tickprefix"] = v_colorbar.TickprefixValidator() self._validators["ticks"] = v_colorbar.TicksValidator() self._validators["ticksuffix"] = v_colorbar.TicksuffixValidator() self._validators["ticktext"] = v_colorbar.TicktextValidator() self._validators["ticktextsrc"] = v_colorbar.TicktextsrcValidator() self._validators["tickvals"] = v_colorbar.TickvalsValidator() self._validators["tickvalssrc"] = v_colorbar.TickvalssrcValidator() self._validators["tickwidth"] = v_colorbar.TickwidthValidator() self._validators["title"] = v_colorbar.TitleValidator() self._validators["x"] = v_colorbar.XValidator() self._validators["xanchor"] = v_colorbar.XanchorValidator() self._validators["xpad"] = v_colorbar.XpadValidator() self._validators["y"] = v_colorbar.YValidator() self._validators["yanchor"] = v_colorbar.YanchorValidator() self._validators["ypad"] = v_colorbar.YpadValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("borderwidth", None) self["borderwidth"] = borderwidth if borderwidth is not None else _v _v = arg.pop("dtick", None) self["dtick"] = dtick if dtick is not None else _v _v = arg.pop("exponentformat", None) self["exponentformat"] = exponentformat if exponentformat is not None else _v _v = arg.pop("len", None) self["len"] = len if len is not None else _v _v = arg.pop("lenmode", None) self["lenmode"] = lenmode if lenmode is not None else _v _v = arg.pop("nticks", None) self["nticks"] = nticks if nticks is not None else _v _v = arg.pop("outlinecolor", None) self["outlinecolor"] = outlinecolor if outlinecolor is not None else _v _v = arg.pop("outlinewidth", None) self["outlinewidth"] = outlinewidth if outlinewidth is not None else _v _v = arg.pop("separatethousands", None) self["separatethousands"] = ( separatethousands if separatethousands is not None else _v ) _v = arg.pop("showexponent", None) self["showexponent"] = showexponent if showexponent is not None else _v _v = arg.pop("showticklabels", None) self["showticklabels"] = showticklabels if showticklabels is not None else _v _v = arg.pop("showtickprefix", None) self["showtickprefix"] = showtickprefix if showtickprefix is not None else _v _v = arg.pop("showticksuffix", None) self["showticksuffix"] = showticksuffix if showticksuffix is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("thicknessmode", None) self["thicknessmode"] = thicknessmode if thicknessmode is not None else _v _v = arg.pop("tick0", None) self["tick0"] = tick0 if tick0 is not None else _v _v = arg.pop("tickangle", None) self["tickangle"] = tickangle if tickangle is not None else _v _v = arg.pop("tickcolor", None) self["tickcolor"] = tickcolor if tickcolor is not None else _v _v = arg.pop("tickfont", None) self["tickfont"] = tickfont if tickfont is not None else _v _v = arg.pop("tickformat", None) self["tickformat"] = tickformat if tickformat is not None else _v _v = arg.pop("tickformatstops", None) self["tickformatstops"] = tickformatstops if tickformatstops is not None else _v _v = arg.pop("tickformatstopdefaults", None) self["tickformatstopdefaults"] = ( tickformatstopdefaults if tickformatstopdefaults is not None else _v ) _v = arg.pop("ticklen", None) self["ticklen"] = ticklen if ticklen is not None else _v _v = arg.pop("tickmode", None) self["tickmode"] = tickmode if tickmode is not None else _v _v = arg.pop("tickprefix", None) self["tickprefix"] = tickprefix if tickprefix is not None else _v _v = arg.pop("ticks", None) self["ticks"] = ticks if ticks is not None else _v _v = arg.pop("ticksuffix", None) self["ticksuffix"] = ticksuffix if ticksuffix is not None else _v _v = arg.pop("ticktext", None) self["ticktext"] = ticktext if ticktext is not None else _v _v = arg.pop("ticktextsrc", None) self["ticktextsrc"] = ticktextsrc if ticktextsrc is not None else _v _v = arg.pop("tickvals", None) self["tickvals"] = tickvals if tickvals is not None else _v _v = arg.pop("tickvalssrc", None) self["tickvalssrc"] = tickvalssrc if tickvalssrc is not None else _v _v = arg.pop("tickwidth", None) self["tickwidth"] = tickwidth if tickwidth is not None else _v _v = arg.pop("title", None) self["title"] = title if title is not None else _v _v = arg.pop("titlefont", None) _v = titlefont if titlefont is not None else _v if _v is not None: self["titlefont"] = _v _v = arg.pop("titleside", None) _v = titleside if titleside is not None else _v if _v is not None: self["titleside"] = _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xanchor", None) self["xanchor"] = xanchor if xanchor is not None else _v _v = arg.pop("xpad", None) self["xpad"] = xpad if xpad is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("yanchor", None) self["yanchor"] = yanchor if yanchor is not None else _v _v = arg.pop("ypad", None) self["ypad"] = ypad if ypad is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["ColorBar", "Gradient", "Line", "colorbar"] from plotly.graph_objs.scatterpolar.marker import colorbar plotly-4.4.1+dfsg.orig/plotly/graph_objs/scatterpolar/__init__.py0000644000175000017500000032522413573721552024550 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Unselected(_BaseTraceHierarchyType): # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.scatterpolar.unselected.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. size Sets the marker size of unselected points, applied only when a selection exists. Returns ------- plotly.graph_objs.scatterpolar.unselected.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # textfont # -------- @property def textfont(self): """ The 'textfont' property is an instance of Textfont that may be specified as: - An instance of plotly.graph_objs.scatterpolar.unselected.Textfont - A dict of string/value properties that will be passed to the Textfont constructor Supported dict properties: color Sets the text font color of unselected points, applied only when a selection exists. Returns ------- plotly.graph_objs.scatterpolar.unselected.Textfont """ return self["textfont"] @textfont.setter def textfont(self, val): self["textfont"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterpolar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ marker plotly.graph_objects.scatterpolar.unselected.Marker instance or dict with compatible properties textfont plotly.graph_objects.scatterpolar.unselected.Textfont instance or dict with compatible properties """ def __init__(self, arg=None, marker=None, textfont=None, **kwargs): """ Construct a new Unselected object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterpolar.Unselected marker plotly.graph_objects.scatterpolar.unselected.Marker instance or dict with compatible properties textfont plotly.graph_objects.scatterpolar.unselected.Textfont instance or dict with compatible properties Returns ------- Unselected """ super(Unselected, self).__init__("unselected") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterpolar.Unselected constructor must be a dict or an instance of plotly.graph_objs.scatterpolar.Unselected""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterpolar import unselected as v_unselected # Initialize validators # --------------------- self._validators["marker"] = v_unselected.MarkerValidator() self._validators["textfont"] = v_unselected.TextfontValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v _v = arg.pop("textfont", None) self["textfont"] = textfont if textfont is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Textfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterpolar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Textfont object Sets the text font. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterpolar.Textfont color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Textfont """ super(Textfont, self).__init__("textfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterpolar.Textfont constructor must be a dict or an instance of plotly.graph_objs.scatterpolar.Textfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterpolar import textfont as v_textfont # Initialize validators # --------------------- self._validators["color"] = v_textfont.ColorValidator() self._validators["colorsrc"] = v_textfont.ColorsrcValidator() self._validators["family"] = v_textfont.FamilyValidator() self._validators["familysrc"] = v_textfont.FamilysrcValidator() self._validators["size"] = v_textfont.SizeValidator() self._validators["sizesrc"] = v_textfont.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Stream(_BaseTraceHierarchyType): # maxpoints # --------- @property def maxpoints(self): """ Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. The 'maxpoints' property is a number and may be specified as: - An int or float in the interval [0, 10000] Returns ------- int|float """ return self["maxpoints"] @maxpoints.setter def maxpoints(self, val): self["maxpoints"] = val # token # ----- @property def token(self): """ The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. The 'token' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["token"] @token.setter def token(self, val): self["token"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterpolar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """ def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): """ Construct a new Stream object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterpolar.Stream maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- Stream """ super(Stream, self).__init__("stream") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterpolar.Stream constructor must be a dict or an instance of plotly.graph_objs.scatterpolar.Stream""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterpolar import stream as v_stream # Initialize validators # --------------------- self._validators["maxpoints"] = v_stream.MaxpointsValidator() self._validators["token"] = v_stream.TokenValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("maxpoints", None) self["maxpoints"] = maxpoints if maxpoints is not None else _v _v = arg.pop("token", None) self["token"] = token if token is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Selected(_BaseTraceHierarchyType): # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.scatterpolar.selected.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. size Sets the marker size of selected points. Returns ------- plotly.graph_objs.scatterpolar.selected.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # textfont # -------- @property def textfont(self): """ The 'textfont' property is an instance of Textfont that may be specified as: - An instance of plotly.graph_objs.scatterpolar.selected.Textfont - A dict of string/value properties that will be passed to the Textfont constructor Supported dict properties: color Sets the text font color of selected points. Returns ------- plotly.graph_objs.scatterpolar.selected.Textfont """ return self["textfont"] @textfont.setter def textfont(self, val): self["textfont"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterpolar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ marker plotly.graph_objects.scatterpolar.selected.Marker instance or dict with compatible properties textfont plotly.graph_objects.scatterpolar.selected.Textfont instance or dict with compatible properties """ def __init__(self, arg=None, marker=None, textfont=None, **kwargs): """ Construct a new Selected object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterpolar.Selected marker plotly.graph_objects.scatterpolar.selected.Marker instance or dict with compatible properties textfont plotly.graph_objects.scatterpolar.selected.Textfont instance or dict with compatible properties Returns ------- Selected """ super(Selected, self).__init__("selected") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterpolar.Selected constructor must be a dict or an instance of plotly.graph_objs.scatterpolar.Selected""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterpolar import selected as v_selected # Initialize validators # --------------------- self._validators["marker"] = v_selected.MarkerValidator() self._validators["textfont"] = v_selected.TextfontValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v _v = arg.pop("textfont", None) self["textfont"] = textfont if textfont is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # autocolorscale # -------------- @property def autocolorscale(self): """ Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. The 'autocolorscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocolorscale"] @autocolorscale.setter def autocolorscale(self, val): self["autocolorscale"] = val # cauto # ----- @property def cauto(self): """ Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. The 'cauto' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["cauto"] @cauto.setter def cauto(self, val): self["cauto"] = val # cmax # ---- @property def cmax(self): """ Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. The 'cmax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmax"] @cmax.setter def cmax(self, val): self["cmax"] = val # cmid # ---- @property def cmid(self): """ Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. The 'cmid' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmid"] @cmid.setter def cmid(self, val): self["cmid"] = val # cmin # ---- @property def cmin(self): """ Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. The 'cmin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmin"] @cmin.setter def cmin(self, val): self["cmin"] = val # color # ----- @property def color(self): """ Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A number that will be interpreted as a color according to scatterpolar.marker.colorscale - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # coloraxis # --------- @property def coloraxis(self): """ Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. The 'coloraxis' property is an identifier of a particular subplot, of type 'coloraxis', that may be specified as the string 'coloraxis' optionally followed by an integer >= 1 (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) Returns ------- str """ return self["coloraxis"] @coloraxis.setter def coloraxis(self, val): self["coloraxis"] = val # colorbar # -------- @property def colorbar(self): """ The 'colorbar' property is an instance of ColorBar that may be specified as: - An instance of plotly.graph_objs.scatterpolar.marker.ColorBar - A dict of string/value properties that will be passed to the ColorBar constructor Supported dict properties: bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.scatterpolar.ma rker.colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.scatterpolar.marker.colorbar.tickformatstopde faults), sets the default property values to use for elements of scatterpolar.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.scatterpolar.marker.colorb ar.Title instance or dict with compatible properties titlefont Deprecated: Please use scatterpolar.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use scatterpolar.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- plotly.graph_objs.scatterpolar.marker.ColorBar """ return self["colorbar"] @colorbar.setter def colorbar(self, val): self["colorbar"] = val # colorscale # ---------- @property def colorscale(self): """ Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnB u,Greens,YlOrRd,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland ,Jet,Hot,Blackbody,Earth,Electric,Viridis,Cividis. The 'colorscale' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # gradient # -------- @property def gradient(self): """ The 'gradient' property is an instance of Gradient that may be specified as: - An instance of plotly.graph_objs.scatterpolar.marker.Gradient - A dict of string/value properties that will be passed to the Gradient constructor Supported dict properties: color Sets the final color of the gradient fill: the center color for radial, the right for horizontal, or the bottom for vertical. colorsrc Sets the source reference on plot.ly for color . type Sets the type of gradient used to fill the markers typesrc Sets the source reference on plot.ly for type . Returns ------- plotly.graph_objs.scatterpolar.marker.Gradient """ return self["gradient"] @gradient.setter def gradient(self, val): self["gradient"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.scatterpolar.marker.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,R eds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Black body,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . Returns ------- plotly.graph_objs.scatterpolar.marker.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # maxdisplayed # ------------ @property def maxdisplayed(self): """ Sets a maximum number of points to be drawn on the graph. 0 corresponds to no limit. The 'maxdisplayed' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["maxdisplayed"] @maxdisplayed.setter def maxdisplayed(self, val): self["maxdisplayed"] = val # opacity # ------- @property def opacity(self): """ Sets the marker opacity. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # opacitysrc # ---------- @property def opacitysrc(self): """ Sets the source reference on plot.ly for opacity . The 'opacitysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["opacitysrc"] @opacitysrc.setter def opacitysrc(self, val): self["opacitysrc"] = val # reversescale # ------------ @property def reversescale(self): """ Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. The 'reversescale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["reversescale"] @reversescale.setter def reversescale(self, val): self["reversescale"] = val # showscale # --------- @property def showscale(self): """ Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. The 'showscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showscale"] @showscale.setter def showscale(self, val): self["showscale"] = val # size # ---- @property def size(self): """ Sets the marker size (in px). The 'size' property is a number and may be specified as: - An int or float in the interval [0, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizemin # ------- @property def sizemin(self): """ Has an effect only if `marker.size` is set to a numerical array. Sets the minimum size (in px) of the rendered marker points. The 'sizemin' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["sizemin"] @sizemin.setter def sizemin(self, val): self["sizemin"] = val # sizemode # -------- @property def sizemode(self): """ Has an effect only if `marker.size` is set to a numerical array. Sets the rule for which the data in `size` is converted to pixels. The 'sizemode' property is an enumeration that may be specified as: - One of the following enumeration values: ['diameter', 'area'] Returns ------- Any """ return self["sizemode"] @sizemode.setter def sizemode(self, val): self["sizemode"] = val # sizeref # ------- @property def sizeref(self): """ Has an effect only if `marker.size` is set to a numerical array. Sets the scale factor used to determine the rendered size of marker points. Use with `sizemin` and `sizemode`. The 'sizeref' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["sizeref"] @sizeref.setter def sizeref(self, val): self["sizeref"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # symbol # ------ @property def symbol(self): """ Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot-open" to a symbol name. The 'symbol' property is an enumeration that may be specified as: - One of the following enumeration values: [0, 'circle', 100, 'circle-open', 200, 'circle-dot', 300, 'circle-open-dot', 1, 'square', 101, 'square-open', 201, 'square-dot', 301, 'square-open-dot', 2, 'diamond', 102, 'diamond-open', 202, 'diamond-dot', 302, 'diamond-open-dot', 3, 'cross', 103, 'cross-open', 203, 'cross-dot', 303, 'cross-open-dot', 4, 'x', 104, 'x-open', 204, 'x-dot', 304, 'x-open-dot', 5, 'triangle-up', 105, 'triangle-up-open', 205, 'triangle-up-dot', 305, 'triangle-up-open-dot', 6, 'triangle-down', 106, 'triangle-down-open', 206, 'triangle-down-dot', 306, 'triangle-down-open-dot', 7, 'triangle-left', 107, 'triangle-left-open', 207, 'triangle-left-dot', 307, 'triangle-left-open-dot', 8, 'triangle-right', 108, 'triangle-right-open', 208, 'triangle-right-dot', 308, 'triangle-right-open-dot', 9, 'triangle-ne', 109, 'triangle-ne-open', 209, 'triangle-ne-dot', 309, 'triangle-ne-open-dot', 10, 'triangle-se', 110, 'triangle-se-open', 210, 'triangle-se-dot', 310, 'triangle-se-open-dot', 11, 'triangle-sw', 111, 'triangle-sw-open', 211, 'triangle-sw-dot', 311, 'triangle-sw-open-dot', 12, 'triangle-nw', 112, 'triangle-nw-open', 212, 'triangle-nw-dot', 312, 'triangle-nw-open-dot', 13, 'pentagon', 113, 'pentagon-open', 213, 'pentagon-dot', 313, 'pentagon-open-dot', 14, 'hexagon', 114, 'hexagon-open', 214, 'hexagon-dot', 314, 'hexagon-open-dot', 15, 'hexagon2', 115, 'hexagon2-open', 215, 'hexagon2-dot', 315, 'hexagon2-open-dot', 16, 'octagon', 116, 'octagon-open', 216, 'octagon-dot', 316, 'octagon-open-dot', 17, 'star', 117, 'star-open', 217, 'star-dot', 317, 'star-open-dot', 18, 'hexagram', 118, 'hexagram-open', 218, 'hexagram-dot', 318, 'hexagram-open-dot', 19, 'star-triangle-up', 119, 'star-triangle-up-open', 219, 'star-triangle-up-dot', 319, 'star-triangle-up-open-dot', 20, 'star-triangle-down', 120, 'star-triangle-down-open', 220, 'star-triangle-down-dot', 320, 'star-triangle-down-open-dot', 21, 'star-square', 121, 'star-square-open', 221, 'star-square-dot', 321, 'star-square-open-dot', 22, 'star-diamond', 122, 'star-diamond-open', 222, 'star-diamond-dot', 322, 'star-diamond-open-dot', 23, 'diamond-tall', 123, 'diamond-tall-open', 223, 'diamond-tall-dot', 323, 'diamond-tall-open-dot', 24, 'diamond-wide', 124, 'diamond-wide-open', 224, 'diamond-wide-dot', 324, 'diamond-wide-open-dot', 25, 'hourglass', 125, 'hourglass-open', 26, 'bowtie', 126, 'bowtie-open', 27, 'circle-cross', 127, 'circle-cross-open', 28, 'circle-x', 128, 'circle-x-open', 29, 'square-cross', 129, 'square-cross-open', 30, 'square-x', 130, 'square-x-open', 31, 'diamond-cross', 131, 'diamond-cross-open', 32, 'diamond-x', 132, 'diamond-x-open', 33, 'cross-thin', 133, 'cross-thin-open', 34, 'x-thin', 134, 'x-thin-open', 35, 'asterisk', 135, 'asterisk-open', 36, 'hash', 136, 'hash-open', 236, 'hash-dot', 336, 'hash-open-dot', 37, 'y-up', 137, 'y-up-open', 38, 'y-down', 138, 'y-down-open', 39, 'y-left', 139, 'y-left-open', 40, 'y-right', 140, 'y-right-open', 41, 'line-ew', 141, 'line-ew-open', 42, 'line-ns', 142, 'line-ns-open', 43, 'line-ne', 143, 'line-ne-open', 44, 'line-nw', 144, 'line-nw-open'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["symbol"] @symbol.setter def symbol(self, val): self["symbol"] = val # symbolsrc # --------- @property def symbolsrc(self): """ Sets the source reference on plot.ly for symbol . The 'symbolsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["symbolsrc"] @symbolsrc.setter def symbolsrc(self, val): self["symbolsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterpolar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.scatterpolar.marker.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu ,Reds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . gradient plotly.graph_objects.scatterpolar.marker.Gradient instance or dict with compatible properties line plotly.graph_objects.scatterpolar.marker.Line instance or dict with compatible properties maxdisplayed Sets a maximum number of points to be drawn on the graph. 0 corresponds to no limit. opacity Sets the marker opacity. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. size Sets the marker size (in px). sizemin Has an effect only if `marker.size` is set to a numerical array. Sets the minimum size (in px) of the rendered marker points. sizemode Has an effect only if `marker.size` is set to a numerical array. Sets the rule for which the data in `size` is converted to pixels. sizeref Has an effect only if `marker.size` is set to a numerical array. Sets the scale factor used to determine the rendered size of marker points. Use with `sizemin` and `sizemode`. sizesrc Sets the source reference on plot.ly for size . symbol Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot- open" to a symbol name. symbolsrc Sets the source reference on plot.ly for symbol . """ def __init__( self, arg=None, autocolorscale=None, cauto=None, cmax=None, cmid=None, cmin=None, color=None, coloraxis=None, colorbar=None, colorscale=None, colorsrc=None, gradient=None, line=None, maxdisplayed=None, opacity=None, opacitysrc=None, reversescale=None, showscale=None, size=None, sizemin=None, sizemode=None, sizeref=None, sizesrc=None, symbol=None, symbolsrc=None, **kwargs ): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterpolar.Marker autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.scatterpolar.marker.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu ,Reds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . gradient plotly.graph_objects.scatterpolar.marker.Gradient instance or dict with compatible properties line plotly.graph_objects.scatterpolar.marker.Line instance or dict with compatible properties maxdisplayed Sets a maximum number of points to be drawn on the graph. 0 corresponds to no limit. opacity Sets the marker opacity. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. size Sets the marker size (in px). sizemin Has an effect only if `marker.size` is set to a numerical array. Sets the minimum size (in px) of the rendered marker points. sizemode Has an effect only if `marker.size` is set to a numerical array. Sets the rule for which the data in `size` is converted to pixels. sizeref Has an effect only if `marker.size` is set to a numerical array. Sets the scale factor used to determine the rendered size of marker points. Use with `sizemin` and `sizemode`. sizesrc Sets the source reference on plot.ly for size . symbol Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot- open" to a symbol name. symbolsrc Sets the source reference on plot.ly for symbol . Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterpolar.Marker constructor must be a dict or an instance of plotly.graph_objs.scatterpolar.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterpolar import marker as v_marker # Initialize validators # --------------------- self._validators["autocolorscale"] = v_marker.AutocolorscaleValidator() self._validators["cauto"] = v_marker.CautoValidator() self._validators["cmax"] = v_marker.CmaxValidator() self._validators["cmid"] = v_marker.CmidValidator() self._validators["cmin"] = v_marker.CminValidator() self._validators["color"] = v_marker.ColorValidator() self._validators["coloraxis"] = v_marker.ColoraxisValidator() self._validators["colorbar"] = v_marker.ColorBarValidator() self._validators["colorscale"] = v_marker.ColorscaleValidator() self._validators["colorsrc"] = v_marker.ColorsrcValidator() self._validators["gradient"] = v_marker.GradientValidator() self._validators["line"] = v_marker.LineValidator() self._validators["maxdisplayed"] = v_marker.MaxdisplayedValidator() self._validators["opacity"] = v_marker.OpacityValidator() self._validators["opacitysrc"] = v_marker.OpacitysrcValidator() self._validators["reversescale"] = v_marker.ReversescaleValidator() self._validators["showscale"] = v_marker.ShowscaleValidator() self._validators["size"] = v_marker.SizeValidator() self._validators["sizemin"] = v_marker.SizeminValidator() self._validators["sizemode"] = v_marker.SizemodeValidator() self._validators["sizeref"] = v_marker.SizerefValidator() self._validators["sizesrc"] = v_marker.SizesrcValidator() self._validators["symbol"] = v_marker.SymbolValidator() self._validators["symbolsrc"] = v_marker.SymbolsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autocolorscale", None) self["autocolorscale"] = autocolorscale if autocolorscale is not None else _v _v = arg.pop("cauto", None) self["cauto"] = cauto if cauto is not None else _v _v = arg.pop("cmax", None) self["cmax"] = cmax if cmax is not None else _v _v = arg.pop("cmid", None) self["cmid"] = cmid if cmid is not None else _v _v = arg.pop("cmin", None) self["cmin"] = cmin if cmin is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("coloraxis", None) self["coloraxis"] = coloraxis if coloraxis is not None else _v _v = arg.pop("colorbar", None) self["colorbar"] = colorbar if colorbar is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("gradient", None) self["gradient"] = gradient if gradient is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v _v = arg.pop("maxdisplayed", None) self["maxdisplayed"] = maxdisplayed if maxdisplayed is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("opacitysrc", None) self["opacitysrc"] = opacitysrc if opacitysrc is not None else _v _v = arg.pop("reversescale", None) self["reversescale"] = reversescale if reversescale is not None else _v _v = arg.pop("showscale", None) self["showscale"] = showscale if showscale is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizemin", None) self["sizemin"] = sizemin if sizemin is not None else _v _v = arg.pop("sizemode", None) self["sizemode"] = sizemode if sizemode is not None else _v _v = arg.pop("sizeref", None) self["sizeref"] = sizeref if sizeref is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v _v = arg.pop("symbol", None) self["symbol"] = symbol if symbol is not None else _v _v = arg.pop("symbolsrc", None) self["symbolsrc"] = symbolsrc if symbolsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the line color. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # dash # ---- @property def dash(self): """ Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). The 'dash' property is an enumeration that may be specified as: - One of the following dash styles: ['solid', 'dot', 'dash', 'longdash', 'dashdot', 'longdashdot'] - A string containing a dash length list in pixels or percentages (e.g. '5px 10px 2px 2px', '5, 10, 2, 2', '10% 20% 40%', etc.) Returns ------- str """ return self["dash"] @dash.setter def dash(self, val): self["dash"] = val # shape # ----- @property def shape(self): """ Determines the line shape. With "spline" the lines are drawn using spline interpolation. The other available values correspond to step-wise line shapes. The 'shape' property is an enumeration that may be specified as: - One of the following enumeration values: ['linear', 'spline'] Returns ------- Any """ return self["shape"] @shape.setter def shape(self, val): self["shape"] = val # smoothing # --------- @property def smoothing(self): """ Has an effect only if `shape` is set to "spline" Sets the amount of smoothing. 0 corresponds to no smoothing (equivalent to a "linear" shape). The 'smoothing' property is a number and may be specified as: - An int or float in the interval [0, 1.3] Returns ------- int|float """ return self["smoothing"] @smoothing.setter def smoothing(self, val): self["smoothing"] = val # width # ----- @property def width(self): """ Sets the line width (in px). The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterpolar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the line color. dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). shape Determines the line shape. With "spline" the lines are drawn using spline interpolation. The other available values correspond to step-wise line shapes. smoothing Has an effect only if `shape` is set to "spline" Sets the amount of smoothing. 0 corresponds to no smoothing (equivalent to a "linear" shape). width Sets the line width (in px). """ def __init__( self, arg=None, color=None, dash=None, shape=None, smoothing=None, width=None, **kwargs ): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterpolar.Line color Sets the line color. dash Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px"). shape Determines the line shape. With "spline" the lines are drawn using spline interpolation. The other available values correspond to step-wise line shapes. smoothing Has an effect only if `shape` is set to "spline" Sets the amount of smoothing. 0 corresponds to no smoothing (equivalent to a "linear" shape). width Sets the line width (in px). Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterpolar.Line constructor must be a dict or an instance of plotly.graph_objs.scatterpolar.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterpolar import line as v_line # Initialize validators # --------------------- self._validators["color"] = v_line.ColorValidator() self._validators["dash"] = v_line.DashValidator() self._validators["shape"] = v_line.ShapeValidator() self._validators["smoothing"] = v_line.SmoothingValidator() self._validators["width"] = v_line.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("dash", None) self["dash"] = dash if dash is not None else _v _v = arg.pop("shape", None) self["shape"] = shape if shape is not None else _v _v = arg.pop("smoothing", None) self["smoothing"] = smoothing if smoothing is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Hoverlabel(_BaseTraceHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'right', 'auto'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["align"] @align.setter def align(self, val): self["align"] = val # alignsrc # -------- @property def alignsrc(self): """ Sets the source reference on plot.ly for align . The 'alignsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["alignsrc"] @alignsrc.setter def alignsrc(self, val): self["alignsrc"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the hover labels for this trace The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bgcolorsrc # ---------- @property def bgcolorsrc(self): """ Sets the source reference on plot.ly for bgcolor . The 'bgcolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bgcolorsrc"] @bgcolorsrc.setter def bgcolorsrc(self, val): self["bgcolorsrc"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the border color of the hover labels for this trace. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # bordercolorsrc # -------------- @property def bordercolorsrc(self): """ Sets the source reference on plot.ly for bordercolor . The 'bordercolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bordercolorsrc"] @bordercolorsrc.setter def bordercolorsrc(self, val): self["bordercolorsrc"] = val # font # ---- @property def font(self): """ Sets the font used in hover labels. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.scatterpolar.hoverlabel.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.scatterpolar.hoverlabel.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # namelength # ---------- @property def namelength(self): """ Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. The 'namelength' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [-1, 9223372036854775807] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|numpy.ndarray """ return self["namelength"] @namelength.setter def namelength(self, val): self["namelength"] = val # namelengthsrc # ------------- @property def namelengthsrc(self): """ Sets the source reference on plot.ly for namelength . The 'namelengthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["namelengthsrc"] @namelengthsrc.setter def namelengthsrc(self, val): self["namelengthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterpolar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """ def __init__( self, arg=None, align=None, alignsrc=None, bgcolor=None, bgcolorsrc=None, bordercolor=None, bordercolorsrc=None, font=None, namelength=None, namelengthsrc=None, **kwargs ): """ Construct a new Hoverlabel object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterpolar.Hoverlabel align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- Hoverlabel """ super(Hoverlabel, self).__init__("hoverlabel") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterpolar.Hoverlabel constructor must be a dict or an instance of plotly.graph_objs.scatterpolar.Hoverlabel""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterpolar import hoverlabel as v_hoverlabel # Initialize validators # --------------------- self._validators["align"] = v_hoverlabel.AlignValidator() self._validators["alignsrc"] = v_hoverlabel.AlignsrcValidator() self._validators["bgcolor"] = v_hoverlabel.BgcolorValidator() self._validators["bgcolorsrc"] = v_hoverlabel.BgcolorsrcValidator() self._validators["bordercolor"] = v_hoverlabel.BordercolorValidator() self._validators["bordercolorsrc"] = v_hoverlabel.BordercolorsrcValidator() self._validators["font"] = v_hoverlabel.FontValidator() self._validators["namelength"] = v_hoverlabel.NamelengthValidator() self._validators["namelengthsrc"] = v_hoverlabel.NamelengthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("alignsrc", None) self["alignsrc"] = alignsrc if alignsrc is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bgcolorsrc", None) self["bgcolorsrc"] = bgcolorsrc if bgcolorsrc is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("bordercolorsrc", None) self["bordercolorsrc"] = bordercolorsrc if bordercolorsrc is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("namelength", None) self["namelength"] = namelength if namelength is not None else _v _v = arg.pop("namelengthsrc", None) self["namelengthsrc"] = namelengthsrc if namelengthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = [ "Hoverlabel", "Line", "Marker", "Selected", "Stream", "Textfont", "Unselected", "hoverlabel", "marker", "selected", "unselected", ] from plotly.graph_objs.scatterpolar import unselected from plotly.graph_objs.scatterpolar import selected from plotly.graph_objs.scatterpolar import marker from plotly.graph_objs.scatterpolar import hoverlabel plotly-4.4.1+dfsg.orig/plotly/graph_objs/scatterpolar/selected/0000755000175000017500000000000013573746613024224 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/scatterpolar/selected/__init__.py0000644000175000017500000002653013573721551026335 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Textfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the text font color of selected points. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterpolar.selected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the text font color of selected points. """ def __init__(self, arg=None, color=None, **kwargs): """ Construct a new Textfont object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterpolar.selected.Textfont color Sets the text font color of selected points. Returns ------- Textfont """ super(Textfont, self).__init__("textfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterpolar.selected.Textfont constructor must be a dict or an instance of plotly.graph_objs.scatterpolar.selected.Textfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterpolar.selected import textfont as v_textfont # Initialize validators # --------------------- self._validators["color"] = v_textfont.ColorValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the marker color of selected points. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # opacity # ------- @property def opacity(self): """ Sets the marker opacity of selected points. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # size # ---- @property def size(self): """ Sets the marker size of selected points. The 'size' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "scatterpolar.selected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. size Sets the marker size of selected points. """ def __init__(self, arg=None, color=None, opacity=None, size=None, **kwargs): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.scatterpolar.selected.Marker color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. size Sets the marker size of selected points. Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.scatterpolar.selected.Marker constructor must be a dict or an instance of plotly.graph_objs.scatterpolar.selected.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.scatterpolar.selected import marker as v_marker # Initialize validators # --------------------- self._validators["color"] = v_marker.ColorValidator() self._validators["opacity"] = v_marker.OpacityValidator() self._validators["size"] = v_marker.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Marker", "Textfont"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/histogram/0000755000175000017500000000000013573746613021726 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/histogram/unselected/0000755000175000017500000000000013573746613024061 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/histogram/unselected/__init__.py0000644000175000017500000002613613573721546026200 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Textfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the text font color of unselected points, applied only when a selection exists. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram.unselected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the text font color of unselected points, applied only when a selection exists. """ def __init__(self, arg=None, color=None, **kwargs): """ Construct a new Textfont object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.histogram.unselected.Textfont color Sets the text font color of unselected points, applied only when a selection exists. Returns ------- Textfont """ super(Textfont, self).__init__("textfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.histogram.unselected.Textfont constructor must be a dict or an instance of plotly.graph_objs.histogram.unselected.Textfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram.unselected import textfont as v_textfont # Initialize validators # --------------------- self._validators["color"] = v_textfont.ColorValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the marker color of unselected points, applied only when a selection exists. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # opacity # ------- @property def opacity(self): """ Sets the marker opacity of unselected points, applied only when a selection exists. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram.unselected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. """ def __init__(self, arg=None, color=None, opacity=None, **kwargs): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.histogram.unselected.Marker color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.histogram.unselected.Marker constructor must be a dict or an instance of plotly.graph_objs.histogram.unselected.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram.unselected import marker as v_marker # Initialize validators # --------------------- self._validators["color"] = v_marker.ColorValidator() self._validators["opacity"] = v_marker.OpacityValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Marker", "Textfont"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/histogram/hoverlabel/0000755000175000017500000000000013573746613024051 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/histogram/hoverlabel/__init__.py0000644000175000017500000002545213573721546026170 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram.hoverlabel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Font object Sets the font used in hover labels. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.histogram.hoverlabel.Font color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.histogram.hoverlabel.Font constructor must be a dict or an instance of plotly.graph_objs.histogram.hoverlabel.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram.hoverlabel import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["colorsrc"] = v_font.ColorsrcValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["familysrc"] = v_font.FamilysrcValidator() self._validators["size"] = v_font.SizeValidator() self._validators["sizesrc"] = v_font.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/histogram/marker/0000755000175000017500000000000013573746613023207 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/histogram/marker/colorbar/0000755000175000017500000000000013573746613025012 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/histogram/marker/colorbar/title/0000755000175000017500000000000013573746613026133 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/histogram/marker/colorbar/title/__init__.py0000644000175000017500000002060213573721546030242 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram.marker.colorbar.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.histogram.marker.colorbar.title.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.histogram.marker.colorbar.title.Font constructor must be a dict or an instance of plotly.graph_objs.histogram.marker.colorbar.title.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram.marker.colorbar.title import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/histogram/marker/colorbar/__init__.py0000644000175000017500000006102113573721546027121 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Title(_BaseTraceHierarchyType): # font # ---- @property def font(self): """ Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.histogram.marker.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.histogram.marker.colorbar.title.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # side # ---- @property def side(self): """ Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- Any """ return self["side"] @side.setter def side(self, val): self["side"] = val # text # ---- @property def text(self): """ Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram.marker.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """ def __init__(self, arg=None, font=None, side=None, text=None, **kwargs): """ Construct a new Title object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.histogram.marker.colorbar.Title font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- Title """ super(Title, self).__init__("title") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.histogram.marker.colorbar.Title constructor must be a dict or an instance of plotly.graph_objs.histogram.marker.colorbar.Title""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram.marker.colorbar import title as v_title # Initialize validators # --------------------- self._validators["font"] = v_title.FontValidator() self._validators["side"] = v_title.SideValidator() self._validators["text"] = v_title.TextValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("side", None) self["side"] = side if side is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickformatstop(_BaseTraceHierarchyType): # dtickrange # ---------- @property def dtickrange(self): """ range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" The 'dtickrange' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'dtickrange[0]' property accepts values of any type (1) The 'dtickrange[1]' property accepts values of any type Returns ------- list """ return self["dtickrange"] @dtickrange.setter def dtickrange(self, val): self["dtickrange"] = val # enabled # ------- @property def enabled(self): """ Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. The 'enabled' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["enabled"] @enabled.setter def enabled(self, val): self["enabled"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # value # ----- @property def value(self): """ string - dtickformat for described zoom level, the same as "tickformat" The 'value' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram.marker.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """ def __init__( self, arg=None, dtickrange=None, enabled=None, name=None, templateitemname=None, value=None, **kwargs ): """ Construct a new Tickformatstop object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.histogram.marker.color bar.Tickformatstop dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- Tickformatstop """ super(Tickformatstop, self).__init__("tickformatstops") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.histogram.marker.colorbar.Tickformatstop constructor must be a dict or an instance of plotly.graph_objs.histogram.marker.colorbar.Tickformatstop""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram.marker.colorbar import ( tickformatstop as v_tickformatstop, ) # Initialize validators # --------------------- self._validators["dtickrange"] = v_tickformatstop.DtickrangeValidator() self._validators["enabled"] = v_tickformatstop.EnabledValidator() self._validators["name"] = v_tickformatstop.NameValidator() self._validators[ "templateitemname" ] = v_tickformatstop.TemplateitemnameValidator() self._validators["value"] = v_tickformatstop.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtickrange", None) self["dtickrange"] = dtickrange if dtickrange is not None else _v _v = arg.pop("enabled", None) self["enabled"] = enabled if enabled is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram.marker.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Tickfont object Sets the color bar's tick label font Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.histogram.marker.colorbar.Tickfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Tickfont """ super(Tickfont, self).__init__("tickfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.histogram.marker.colorbar.Tickfont constructor must be a dict or an instance of plotly.graph_objs.histogram.marker.colorbar.Tickfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram.marker.colorbar import tickfont as v_tickfont # Initialize validators # --------------------- self._validators["color"] = v_tickfont.ColorValidator() self._validators["family"] = v_tickfont.FamilyValidator() self._validators["size"] = v_tickfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Tickfont", "Tickformatstop", "Tickformatstop", "Title", "title"] from plotly.graph_objs.histogram.marker.colorbar import title plotly-4.4.1+dfsg.orig/plotly/graph_objs/histogram/marker/__init__.py0000644000175000017500000027054013573721547025327 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # autocolorscale # -------------- @property def autocolorscale(self): """ Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. The 'autocolorscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocolorscale"] @autocolorscale.setter def autocolorscale(self, val): self["autocolorscale"] = val # cauto # ----- @property def cauto(self): """ Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. The 'cauto' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["cauto"] @cauto.setter def cauto(self, val): self["cauto"] = val # cmax # ---- @property def cmax(self): """ Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. The 'cmax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmax"] @cmax.setter def cmax(self, val): self["cmax"] = val # cmid # ---- @property def cmid(self): """ Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. The 'cmid' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmid"] @cmid.setter def cmid(self, val): self["cmid"] = val # cmin # ---- @property def cmin(self): """ Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. The 'cmin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmin"] @cmin.setter def cmin(self, val): self["cmin"] = val # color # ----- @property def color(self): """ Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A number that will be interpreted as a color according to histogram.marker.line.colorscale - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # coloraxis # --------- @property def coloraxis(self): """ Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. The 'coloraxis' property is an identifier of a particular subplot, of type 'coloraxis', that may be specified as the string 'coloraxis' optionally followed by an integer >= 1 (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) Returns ------- str """ return self["coloraxis"] @coloraxis.setter def coloraxis(self, val): self["coloraxis"] = val # colorscale # ---------- @property def colorscale(self): """ Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,Earth,Electric,Vi ridis,Cividis. The 'colorscale' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # reversescale # ------------ @property def reversescale(self): """ Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. The 'reversescale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["reversescale"] @reversescale.setter def reversescale(self, val): self["reversescale"] = val # width # ----- @property def width(self): """ Sets the width (in px) of the lines bounding the marker points. The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["width"] @width.setter def width(self, val): self["width"] = val # widthsrc # -------- @property def widthsrc(self): """ Sets the source reference on plot.ly for width . The 'widthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["widthsrc"] @widthsrc.setter def widthsrc(self, val): self["widthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram.marker" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . """ def __init__( self, arg=None, autocolorscale=None, cauto=None, cmax=None, cmid=None, cmin=None, color=None, coloraxis=None, colorscale=None, colorsrc=None, reversescale=None, width=None, widthsrc=None, **kwargs ): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.histogram.marker.Line autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.histogram.marker.Line constructor must be a dict or an instance of plotly.graph_objs.histogram.marker.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram.marker import line as v_line # Initialize validators # --------------------- self._validators["autocolorscale"] = v_line.AutocolorscaleValidator() self._validators["cauto"] = v_line.CautoValidator() self._validators["cmax"] = v_line.CmaxValidator() self._validators["cmid"] = v_line.CmidValidator() self._validators["cmin"] = v_line.CminValidator() self._validators["color"] = v_line.ColorValidator() self._validators["coloraxis"] = v_line.ColoraxisValidator() self._validators["colorscale"] = v_line.ColorscaleValidator() self._validators["colorsrc"] = v_line.ColorsrcValidator() self._validators["reversescale"] = v_line.ReversescaleValidator() self._validators["width"] = v_line.WidthValidator() self._validators["widthsrc"] = v_line.WidthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autocolorscale", None) self["autocolorscale"] = autocolorscale if autocolorscale is not None else _v _v = arg.pop("cauto", None) self["cauto"] = cauto if cauto is not None else _v _v = arg.pop("cmax", None) self["cmax"] = cmax if cmax is not None else _v _v = arg.pop("cmid", None) self["cmid"] = cmid if cmid is not None else _v _v = arg.pop("cmin", None) self["cmin"] = cmin if cmin is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("coloraxis", None) self["coloraxis"] = coloraxis if coloraxis is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("reversescale", None) self["reversescale"] = reversescale if reversescale is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v _v = arg.pop("widthsrc", None) self["widthsrc"] = widthsrc if widthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class ColorBar(_BaseTraceHierarchyType): # bgcolor # ------- @property def bgcolor(self): """ Sets the color of padded area. The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the axis line color. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # borderwidth # ----------- @property def borderwidth(self): """ Sets the width (in px) or the border enclosing this color bar. The 'borderwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["borderwidth"] @borderwidth.setter def borderwidth(self, val): self["borderwidth"] = val # dtick # ----- @property def dtick(self): """ Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" The 'dtick' property accepts values of any type Returns ------- Any """ return self["dtick"] @dtick.setter def dtick(self, val): self["dtick"] = val # exponentformat # -------------- @property def exponentformat(self): """ Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. The 'exponentformat' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'e', 'E', 'power', 'SI', 'B'] Returns ------- Any """ return self["exponentformat"] @exponentformat.setter def exponentformat(self, val): self["exponentformat"] = val # len # --- @property def len(self): """ Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. The 'len' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["len"] @len.setter def len(self, val): self["len"] = val # lenmode # ------- @property def lenmode(self): """ Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. The 'lenmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["lenmode"] @lenmode.setter def lenmode(self, val): self["lenmode"] = val # nticks # ------ @property def nticks(self): """ Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". The 'nticks' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nticks"] @nticks.setter def nticks(self, val): self["nticks"] = val # outlinecolor # ------------ @property def outlinecolor(self): """ Sets the axis line color. The 'outlinecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["outlinecolor"] @outlinecolor.setter def outlinecolor(self, val): self["outlinecolor"] = val # outlinewidth # ------------ @property def outlinewidth(self): """ Sets the width (in px) of the axis line. The 'outlinewidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["outlinewidth"] @outlinewidth.setter def outlinewidth(self, val): self["outlinewidth"] = val # separatethousands # ----------------- @property def separatethousands(self): """ If "true", even 4-digit integers are separated The 'separatethousands' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["separatethousands"] @separatethousands.setter def separatethousands(self, val): self["separatethousands"] = val # showexponent # ------------ @property def showexponent(self): """ If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. The 'showexponent' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showexponent"] @showexponent.setter def showexponent(self, val): self["showexponent"] = val # showticklabels # -------------- @property def showticklabels(self): """ Determines whether or not the tick labels are drawn. The 'showticklabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showticklabels"] @showticklabels.setter def showticklabels(self, val): self["showticklabels"] = val # showtickprefix # -------------- @property def showtickprefix(self): """ If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. The 'showtickprefix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showtickprefix"] @showtickprefix.setter def showtickprefix(self, val): self["showtickprefix"] = val # showticksuffix # -------------- @property def showticksuffix(self): """ Same as `showtickprefix` but for tick suffixes. The 'showticksuffix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showticksuffix"] @showticksuffix.setter def showticksuffix(self, val): self["showticksuffix"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # thicknessmode # ------------- @property def thicknessmode(self): """ Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. The 'thicknessmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["thicknessmode"] @thicknessmode.setter def thicknessmode(self, val): self["thicknessmode"] = val # tick0 # ----- @property def tick0(self): """ Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. The 'tick0' property accepts values of any type Returns ------- Any """ return self["tick0"] @tick0.setter def tick0(self, val): self["tick0"] = val # tickangle # --------- @property def tickangle(self): """ Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. The 'tickangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["tickangle"] @tickangle.setter def tickangle(self, val): self["tickangle"] = val # tickcolor # --------- @property def tickcolor(self): """ Sets the tick color. The 'tickcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["tickcolor"] @tickcolor.setter def tickcolor(self, val): self["tickcolor"] = val # tickfont # -------- @property def tickfont(self): """ Sets the color bar's tick label font The 'tickfont' property is an instance of Tickfont that may be specified as: - An instance of plotly.graph_objs.histogram.marker.colorbar.Tickfont - A dict of string/value properties that will be passed to the Tickfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.histogram.marker.colorbar.Tickfont """ return self["tickfont"] @tickfont.setter def tickfont(self, val): self["tickfont"] = val # tickformat # ---------- @property def tickformat(self): """ Sets the tick label formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'tickformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickformat"] @tickformat.setter def tickformat(self, val): self["tickformat"] = val # tickformatstops # --------------- @property def tickformatstops(self): """ The 'tickformatstops' property is a tuple of instances of Tickformatstop that may be specified as: - A list or tuple of instances of plotly.graph_objs.histogram.marker.colorbar.Tickformatstop - A list or tuple of dicts of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- tuple[plotly.graph_objs.histogram.marker.colorbar.Tickformatstop] """ return self["tickformatstops"] @tickformatstops.setter def tickformatstops(self, val): self["tickformatstops"] = val # tickformatstopdefaults # ---------------------- @property def tickformatstopdefaults(self): """ When used in a template (as layout.template.data.histogram.mark er.colorbar.tickformatstopdefaults), sets the default property values to use for elements of histogram.marker.colorbar.tickformatstops The 'tickformatstopdefaults' property is an instance of Tickformatstop that may be specified as: - An instance of plotly.graph_objs.histogram.marker.colorbar.Tickformatstop - A dict of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: Returns ------- plotly.graph_objs.histogram.marker.colorbar.Tickformatstop """ return self["tickformatstopdefaults"] @tickformatstopdefaults.setter def tickformatstopdefaults(self, val): self["tickformatstopdefaults"] = val # ticklen # ------- @property def ticklen(self): """ Sets the tick length (in px). The 'ticklen' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ticklen"] @ticklen.setter def ticklen(self, val): self["ticklen"] = val # tickmode # -------- @property def tickmode(self): """ Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). The 'tickmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'linear', 'array'] Returns ------- Any """ return self["tickmode"] @tickmode.setter def tickmode(self, val): self["tickmode"] = val # tickprefix # ---------- @property def tickprefix(self): """ Sets a tick label prefix. The 'tickprefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickprefix"] @tickprefix.setter def tickprefix(self, val): self["tickprefix"] = val # ticks # ----- @property def ticks(self): """ Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. The 'ticks' property is an enumeration that may be specified as: - One of the following enumeration values: ['outside', 'inside', ''] Returns ------- Any """ return self["ticks"] @ticks.setter def ticks(self, val): self["ticks"] = val # ticksuffix # ---------- @property def ticksuffix(self): """ Sets a tick label suffix. The 'ticksuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ticksuffix"] @ticksuffix.setter def ticksuffix(self, val): self["ticksuffix"] = val # ticktext # -------- @property def ticktext(self): """ Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. The 'ticktext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ticktext"] @ticktext.setter def ticktext(self, val): self["ticktext"] = val # ticktextsrc # ----------- @property def ticktextsrc(self): """ Sets the source reference on plot.ly for ticktext . The 'ticktextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ticktextsrc"] @ticktextsrc.setter def ticktextsrc(self, val): self["ticktextsrc"] = val # tickvals # -------- @property def tickvals(self): """ Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. The 'tickvals' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["tickvals"] @tickvals.setter def tickvals(self, val): self["tickvals"] = val # tickvalssrc # ----------- @property def tickvalssrc(self): """ Sets the source reference on plot.ly for tickvals . The 'tickvalssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tickvalssrc"] @tickvalssrc.setter def tickvalssrc(self, val): self["tickvalssrc"] = val # tickwidth # --------- @property def tickwidth(self): """ Sets the tick width (in px). The 'tickwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["tickwidth"] @tickwidth.setter def tickwidth(self, val): self["tickwidth"] = val # title # ----- @property def title(self): """ The 'title' property is an instance of Title that may be specified as: - An instance of plotly.graph_objs.histogram.marker.colorbar.Title - A dict of string/value properties that will be passed to the Title constructor Supported dict properties: font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- plotly.graph_objs.histogram.marker.colorbar.Title """ return self["title"] @title.setter def title(self, val): self["title"] = val # titlefont # --------- @property def titlefont(self): """ Deprecated: Please use histogram.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.histogram.marker.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- """ return self["titlefont"] @titlefont.setter def titlefont(self, val): self["titlefont"] = val # titleside # --------- @property def titleside(self): """ Deprecated: Please use histogram.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- """ return self["titleside"] @titleside.setter def titleside(self, val): self["titleside"] = val # x # - @property def x(self): """ Sets the x position of the color bar (in plot fraction). The 'x' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["x"] @x.setter def x(self, val): self["x"] = val # xanchor # ------- @property def xanchor(self): """ Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. The 'xanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'center', 'right'] Returns ------- Any """ return self["xanchor"] @xanchor.setter def xanchor(self, val): self["xanchor"] = val # xpad # ---- @property def xpad(self): """ Sets the amount of padding (in px) along the x direction. The 'xpad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["xpad"] @xpad.setter def xpad(self, val): self["xpad"] = val # y # - @property def y(self): """ Sets the y position of the color bar (in plot fraction). The 'y' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["y"] @y.setter def y(self, val): self["y"] = val # yanchor # ------- @property def yanchor(self): """ Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. The 'yanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['top', 'middle', 'bottom'] Returns ------- Any """ return self["yanchor"] @yanchor.setter def yanchor(self, val): self["yanchor"] = val # ypad # ---- @property def ypad(self): """ Sets the amount of padding (in px) along the y direction. The 'ypad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ypad"] @ypad.setter def ypad(self, val): self["ypad"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram.marker" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.histogram.marker.colorb ar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.histog ram.marker.colorbar.tickformatstopdefaults), sets the default property values to use for elements of histogram.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.histogram.marker.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use histogram.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use histogram.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """ _mapped_properties = { "titlefont": ("title", "font"), "titleside": ("title", "side"), } def __init__( self, arg=None, bgcolor=None, bordercolor=None, borderwidth=None, dtick=None, exponentformat=None, len=None, lenmode=None, nticks=None, outlinecolor=None, outlinewidth=None, separatethousands=None, showexponent=None, showticklabels=None, showtickprefix=None, showticksuffix=None, thickness=None, thicknessmode=None, tick0=None, tickangle=None, tickcolor=None, tickfont=None, tickformat=None, tickformatstops=None, tickformatstopdefaults=None, ticklen=None, tickmode=None, tickprefix=None, ticks=None, ticksuffix=None, ticktext=None, ticktextsrc=None, tickvals=None, tickvalssrc=None, tickwidth=None, title=None, titlefont=None, titleside=None, x=None, xanchor=None, xpad=None, y=None, yanchor=None, ypad=None, **kwargs ): """ Construct a new ColorBar object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.histogram.marker.ColorBar bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.histogram.marker.colorb ar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.histog ram.marker.colorbar.tickformatstopdefaults), sets the default property values to use for elements of histogram.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.histogram.marker.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use histogram.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use histogram.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- ColorBar """ super(ColorBar, self).__init__("colorbar") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.histogram.marker.ColorBar constructor must be a dict or an instance of plotly.graph_objs.histogram.marker.ColorBar""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram.marker import colorbar as v_colorbar # Initialize validators # --------------------- self._validators["bgcolor"] = v_colorbar.BgcolorValidator() self._validators["bordercolor"] = v_colorbar.BordercolorValidator() self._validators["borderwidth"] = v_colorbar.BorderwidthValidator() self._validators["dtick"] = v_colorbar.DtickValidator() self._validators["exponentformat"] = v_colorbar.ExponentformatValidator() self._validators["len"] = v_colorbar.LenValidator() self._validators["lenmode"] = v_colorbar.LenmodeValidator() self._validators["nticks"] = v_colorbar.NticksValidator() self._validators["outlinecolor"] = v_colorbar.OutlinecolorValidator() self._validators["outlinewidth"] = v_colorbar.OutlinewidthValidator() self._validators["separatethousands"] = v_colorbar.SeparatethousandsValidator() self._validators["showexponent"] = v_colorbar.ShowexponentValidator() self._validators["showticklabels"] = v_colorbar.ShowticklabelsValidator() self._validators["showtickprefix"] = v_colorbar.ShowtickprefixValidator() self._validators["showticksuffix"] = v_colorbar.ShowticksuffixValidator() self._validators["thickness"] = v_colorbar.ThicknessValidator() self._validators["thicknessmode"] = v_colorbar.ThicknessmodeValidator() self._validators["tick0"] = v_colorbar.Tick0Validator() self._validators["tickangle"] = v_colorbar.TickangleValidator() self._validators["tickcolor"] = v_colorbar.TickcolorValidator() self._validators["tickfont"] = v_colorbar.TickfontValidator() self._validators["tickformat"] = v_colorbar.TickformatValidator() self._validators["tickformatstops"] = v_colorbar.TickformatstopsValidator() self._validators[ "tickformatstopdefaults" ] = v_colorbar.TickformatstopValidator() self._validators["ticklen"] = v_colorbar.TicklenValidator() self._validators["tickmode"] = v_colorbar.TickmodeValidator() self._validators["tickprefix"] = v_colorbar.TickprefixValidator() self._validators["ticks"] = v_colorbar.TicksValidator() self._validators["ticksuffix"] = v_colorbar.TicksuffixValidator() self._validators["ticktext"] = v_colorbar.TicktextValidator() self._validators["ticktextsrc"] = v_colorbar.TicktextsrcValidator() self._validators["tickvals"] = v_colorbar.TickvalsValidator() self._validators["tickvalssrc"] = v_colorbar.TickvalssrcValidator() self._validators["tickwidth"] = v_colorbar.TickwidthValidator() self._validators["title"] = v_colorbar.TitleValidator() self._validators["x"] = v_colorbar.XValidator() self._validators["xanchor"] = v_colorbar.XanchorValidator() self._validators["xpad"] = v_colorbar.XpadValidator() self._validators["y"] = v_colorbar.YValidator() self._validators["yanchor"] = v_colorbar.YanchorValidator() self._validators["ypad"] = v_colorbar.YpadValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("borderwidth", None) self["borderwidth"] = borderwidth if borderwidth is not None else _v _v = arg.pop("dtick", None) self["dtick"] = dtick if dtick is not None else _v _v = arg.pop("exponentformat", None) self["exponentformat"] = exponentformat if exponentformat is not None else _v _v = arg.pop("len", None) self["len"] = len if len is not None else _v _v = arg.pop("lenmode", None) self["lenmode"] = lenmode if lenmode is not None else _v _v = arg.pop("nticks", None) self["nticks"] = nticks if nticks is not None else _v _v = arg.pop("outlinecolor", None) self["outlinecolor"] = outlinecolor if outlinecolor is not None else _v _v = arg.pop("outlinewidth", None) self["outlinewidth"] = outlinewidth if outlinewidth is not None else _v _v = arg.pop("separatethousands", None) self["separatethousands"] = ( separatethousands if separatethousands is not None else _v ) _v = arg.pop("showexponent", None) self["showexponent"] = showexponent if showexponent is not None else _v _v = arg.pop("showticklabels", None) self["showticklabels"] = showticklabels if showticklabels is not None else _v _v = arg.pop("showtickprefix", None) self["showtickprefix"] = showtickprefix if showtickprefix is not None else _v _v = arg.pop("showticksuffix", None) self["showticksuffix"] = showticksuffix if showticksuffix is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("thicknessmode", None) self["thicknessmode"] = thicknessmode if thicknessmode is not None else _v _v = arg.pop("tick0", None) self["tick0"] = tick0 if tick0 is not None else _v _v = arg.pop("tickangle", None) self["tickangle"] = tickangle if tickangle is not None else _v _v = arg.pop("tickcolor", None) self["tickcolor"] = tickcolor if tickcolor is not None else _v _v = arg.pop("tickfont", None) self["tickfont"] = tickfont if tickfont is not None else _v _v = arg.pop("tickformat", None) self["tickformat"] = tickformat if tickformat is not None else _v _v = arg.pop("tickformatstops", None) self["tickformatstops"] = tickformatstops if tickformatstops is not None else _v _v = arg.pop("tickformatstopdefaults", None) self["tickformatstopdefaults"] = ( tickformatstopdefaults if tickformatstopdefaults is not None else _v ) _v = arg.pop("ticklen", None) self["ticklen"] = ticklen if ticklen is not None else _v _v = arg.pop("tickmode", None) self["tickmode"] = tickmode if tickmode is not None else _v _v = arg.pop("tickprefix", None) self["tickprefix"] = tickprefix if tickprefix is not None else _v _v = arg.pop("ticks", None) self["ticks"] = ticks if ticks is not None else _v _v = arg.pop("ticksuffix", None) self["ticksuffix"] = ticksuffix if ticksuffix is not None else _v _v = arg.pop("ticktext", None) self["ticktext"] = ticktext if ticktext is not None else _v _v = arg.pop("ticktextsrc", None) self["ticktextsrc"] = ticktextsrc if ticktextsrc is not None else _v _v = arg.pop("tickvals", None) self["tickvals"] = tickvals if tickvals is not None else _v _v = arg.pop("tickvalssrc", None) self["tickvalssrc"] = tickvalssrc if tickvalssrc is not None else _v _v = arg.pop("tickwidth", None) self["tickwidth"] = tickwidth if tickwidth is not None else _v _v = arg.pop("title", None) self["title"] = title if title is not None else _v _v = arg.pop("titlefont", None) _v = titlefont if titlefont is not None else _v if _v is not None: self["titlefont"] = _v _v = arg.pop("titleside", None) _v = titleside if titleside is not None else _v if _v is not None: self["titleside"] = _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xanchor", None) self["xanchor"] = xanchor if xanchor is not None else _v _v = arg.pop("xpad", None) self["xpad"] = xpad if xpad is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("yanchor", None) self["yanchor"] = yanchor if yanchor is not None else _v _v = arg.pop("ypad", None) self["ypad"] = ypad if ypad is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["ColorBar", "Line", "colorbar"] from plotly.graph_objs.histogram.marker import colorbar plotly-4.4.1+dfsg.orig/plotly/graph_objs/histogram/__init__.py0000644000175000017500000041762413573721550024046 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class YBins(_BaseTraceHierarchyType): # end # --- @property def end(self): """ Sets the end value for the y axis bins. The last bin may not end exactly at this value, we increment the bin edge by `size` from `start` until we reach or exceed `end`. Defaults to the maximum data value. Like `start`, for dates use a date string, and for category data `end` is based on the category serial numbers. The 'end' property accepts values of any type Returns ------- Any """ return self["end"] @end.setter def end(self, val): self["end"] = val # size # ---- @property def size(self): """ Sets the size of each y axis bin. Default behavior: If `nbinsy` is 0 or omitted, we choose a nice round bin size such that the number of bins is about the same as the typical number of samples in each bin. If `nbinsy` is provided, we choose a nice round bin size giving no more than that many bins. For date data, use milliseconds or "M" for months, as in `axis.dtick`. For category data, the number of categories to bin together (always defaults to 1). If multiple non-overlaying histograms share a subplot, the first explicit `size` is used and all others discarded. If no `size` is provided,the sample data from all traces is combined to determine `size` as described above. The 'size' property accepts values of any type Returns ------- Any """ return self["size"] @size.setter def size(self, val): self["size"] = val # start # ----- @property def start(self): """ Sets the starting value for the y axis bins. Defaults to the minimum data value, shifted down if necessary to make nice round values and to remove ambiguous bin edges. For example, if most of the data is integers we shift the bin edges 0.5 down, so a `size` of 5 would have a default `start` of -0.5, so it is clear that 0-4 are in the first bin, 5-9 in the second, but continuous data gets a start of 0 and bins [0,5), [5,10) etc. Dates behave similarly, and `start` should be a date string. For category data, `start` is based on the category serial numbers, and defaults to -0.5. If multiple non-overlaying histograms share a subplot, the first explicit `start` is used exactly and all others are shifted down (if necessary) to differ from that one by an integer number of bins. The 'start' property accepts values of any type Returns ------- Any """ return self["start"] @start.setter def start(self, val): self["start"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ end Sets the end value for the y axis bins. The last bin may not end exactly at this value, we increment the bin edge by `size` from `start` until we reach or exceed `end`. Defaults to the maximum data value. Like `start`, for dates use a date string, and for category data `end` is based on the category serial numbers. size Sets the size of each y axis bin. Default behavior: If `nbinsy` is 0 or omitted, we choose a nice round bin size such that the number of bins is about the same as the typical number of samples in each bin. If `nbinsy` is provided, we choose a nice round bin size giving no more than that many bins. For date data, use milliseconds or "M" for months, as in `axis.dtick`. For category data, the number of categories to bin together (always defaults to 1). If multiple non- overlaying histograms share a subplot, the first explicit `size` is used and all others discarded. If no `size` is provided,the sample data from all traces is combined to determine `size` as described above. start Sets the starting value for the y axis bins. Defaults to the minimum data value, shifted down if necessary to make nice round values and to remove ambiguous bin edges. For example, if most of the data is integers we shift the bin edges 0.5 down, so a `size` of 5 would have a default `start` of -0.5, so it is clear that 0-4 are in the first bin, 5-9 in the second, but continuous data gets a start of 0 and bins [0,5), [5,10) etc. Dates behave similarly, and `start` should be a date string. For category data, `start` is based on the category serial numbers, and defaults to -0.5. If multiple non-overlaying histograms share a subplot, the first explicit `start` is used exactly and all others are shifted down (if necessary) to differ from that one by an integer number of bins. """ def __init__(self, arg=None, end=None, size=None, start=None, **kwargs): """ Construct a new YBins object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.histogram.YBins end Sets the end value for the y axis bins. The last bin may not end exactly at this value, we increment the bin edge by `size` from `start` until we reach or exceed `end`. Defaults to the maximum data value. Like `start`, for dates use a date string, and for category data `end` is based on the category serial numbers. size Sets the size of each y axis bin. Default behavior: If `nbinsy` is 0 or omitted, we choose a nice round bin size such that the number of bins is about the same as the typical number of samples in each bin. If `nbinsy` is provided, we choose a nice round bin size giving no more than that many bins. For date data, use milliseconds or "M" for months, as in `axis.dtick`. For category data, the number of categories to bin together (always defaults to 1). If multiple non- overlaying histograms share a subplot, the first explicit `size` is used and all others discarded. If no `size` is provided,the sample data from all traces is combined to determine `size` as described above. start Sets the starting value for the y axis bins. Defaults to the minimum data value, shifted down if necessary to make nice round values and to remove ambiguous bin edges. For example, if most of the data is integers we shift the bin edges 0.5 down, so a `size` of 5 would have a default `start` of -0.5, so it is clear that 0-4 are in the first bin, 5-9 in the second, but continuous data gets a start of 0 and bins [0,5), [5,10) etc. Dates behave similarly, and `start` should be a date string. For category data, `start` is based on the category serial numbers, and defaults to -0.5. If multiple non-overlaying histograms share a subplot, the first explicit `start` is used exactly and all others are shifted down (if necessary) to differ from that one by an integer number of bins. Returns ------- YBins """ super(YBins, self).__init__("ybins") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.histogram.YBins constructor must be a dict or an instance of plotly.graph_objs.histogram.YBins""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram import ybins as v_ybins # Initialize validators # --------------------- self._validators["end"] = v_ybins.EndValidator() self._validators["size"] = v_ybins.SizeValidator() self._validators["start"] = v_ybins.StartValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("end", None) self["end"] = end if end is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("start", None) self["start"] = start if start is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class XBins(_BaseTraceHierarchyType): # end # --- @property def end(self): """ Sets the end value for the x axis bins. The last bin may not end exactly at this value, we increment the bin edge by `size` from `start` until we reach or exceed `end`. Defaults to the maximum data value. Like `start`, for dates use a date string, and for category data `end` is based on the category serial numbers. The 'end' property accepts values of any type Returns ------- Any """ return self["end"] @end.setter def end(self, val): self["end"] = val # size # ---- @property def size(self): """ Sets the size of each x axis bin. Default behavior: If `nbinsx` is 0 or omitted, we choose a nice round bin size such that the number of bins is about the same as the typical number of samples in each bin. If `nbinsx` is provided, we choose a nice round bin size giving no more than that many bins. For date data, use milliseconds or "M" for months, as in `axis.dtick`. For category data, the number of categories to bin together (always defaults to 1). If multiple non-overlaying histograms share a subplot, the first explicit `size` is used and all others discarded. If no `size` is provided,the sample data from all traces is combined to determine `size` as described above. The 'size' property accepts values of any type Returns ------- Any """ return self["size"] @size.setter def size(self, val): self["size"] = val # start # ----- @property def start(self): """ Sets the starting value for the x axis bins. Defaults to the minimum data value, shifted down if necessary to make nice round values and to remove ambiguous bin edges. For example, if most of the data is integers we shift the bin edges 0.5 down, so a `size` of 5 would have a default `start` of -0.5, so it is clear that 0-4 are in the first bin, 5-9 in the second, but continuous data gets a start of 0 and bins [0,5), [5,10) etc. Dates behave similarly, and `start` should be a date string. For category data, `start` is based on the category serial numbers, and defaults to -0.5. If multiple non-overlaying histograms share a subplot, the first explicit `start` is used exactly and all others are shifted down (if necessary) to differ from that one by an integer number of bins. The 'start' property accepts values of any type Returns ------- Any """ return self["start"] @start.setter def start(self, val): self["start"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ end Sets the end value for the x axis bins. The last bin may not end exactly at this value, we increment the bin edge by `size` from `start` until we reach or exceed `end`. Defaults to the maximum data value. Like `start`, for dates use a date string, and for category data `end` is based on the category serial numbers. size Sets the size of each x axis bin. Default behavior: If `nbinsx` is 0 or omitted, we choose a nice round bin size such that the number of bins is about the same as the typical number of samples in each bin. If `nbinsx` is provided, we choose a nice round bin size giving no more than that many bins. For date data, use milliseconds or "M" for months, as in `axis.dtick`. For category data, the number of categories to bin together (always defaults to 1). If multiple non- overlaying histograms share a subplot, the first explicit `size` is used and all others discarded. If no `size` is provided,the sample data from all traces is combined to determine `size` as described above. start Sets the starting value for the x axis bins. Defaults to the minimum data value, shifted down if necessary to make nice round values and to remove ambiguous bin edges. For example, if most of the data is integers we shift the bin edges 0.5 down, so a `size` of 5 would have a default `start` of -0.5, so it is clear that 0-4 are in the first bin, 5-9 in the second, but continuous data gets a start of 0 and bins [0,5), [5,10) etc. Dates behave similarly, and `start` should be a date string. For category data, `start` is based on the category serial numbers, and defaults to -0.5. If multiple non-overlaying histograms share a subplot, the first explicit `start` is used exactly and all others are shifted down (if necessary) to differ from that one by an integer number of bins. """ def __init__(self, arg=None, end=None, size=None, start=None, **kwargs): """ Construct a new XBins object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.histogram.XBins end Sets the end value for the x axis bins. The last bin may not end exactly at this value, we increment the bin edge by `size` from `start` until we reach or exceed `end`. Defaults to the maximum data value. Like `start`, for dates use a date string, and for category data `end` is based on the category serial numbers. size Sets the size of each x axis bin. Default behavior: If `nbinsx` is 0 or omitted, we choose a nice round bin size such that the number of bins is about the same as the typical number of samples in each bin. If `nbinsx` is provided, we choose a nice round bin size giving no more than that many bins. For date data, use milliseconds or "M" for months, as in `axis.dtick`. For category data, the number of categories to bin together (always defaults to 1). If multiple non- overlaying histograms share a subplot, the first explicit `size` is used and all others discarded. If no `size` is provided,the sample data from all traces is combined to determine `size` as described above. start Sets the starting value for the x axis bins. Defaults to the minimum data value, shifted down if necessary to make nice round values and to remove ambiguous bin edges. For example, if most of the data is integers we shift the bin edges 0.5 down, so a `size` of 5 would have a default `start` of -0.5, so it is clear that 0-4 are in the first bin, 5-9 in the second, but continuous data gets a start of 0 and bins [0,5), [5,10) etc. Dates behave similarly, and `start` should be a date string. For category data, `start` is based on the category serial numbers, and defaults to -0.5. If multiple non-overlaying histograms share a subplot, the first explicit `start` is used exactly and all others are shifted down (if necessary) to differ from that one by an integer number of bins. Returns ------- XBins """ super(XBins, self).__init__("xbins") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.histogram.XBins constructor must be a dict or an instance of plotly.graph_objs.histogram.XBins""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram import xbins as v_xbins # Initialize validators # --------------------- self._validators["end"] = v_xbins.EndValidator() self._validators["size"] = v_xbins.SizeValidator() self._validators["start"] = v_xbins.StartValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("end", None) self["end"] = end if end is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("start", None) self["start"] = start if start is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Unselected(_BaseTraceHierarchyType): # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.histogram.unselected.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. Returns ------- plotly.graph_objs.histogram.unselected.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # textfont # -------- @property def textfont(self): """ The 'textfont' property is an instance of Textfont that may be specified as: - An instance of plotly.graph_objs.histogram.unselected.Textfont - A dict of string/value properties that will be passed to the Textfont constructor Supported dict properties: color Sets the text font color of unselected points, applied only when a selection exists. Returns ------- plotly.graph_objs.histogram.unselected.Textfont """ return self["textfont"] @textfont.setter def textfont(self, val): self["textfont"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ marker plotly.graph_objects.histogram.unselected.Marker instance or dict with compatible properties textfont plotly.graph_objects.histogram.unselected.Textfont instance or dict with compatible properties """ def __init__(self, arg=None, marker=None, textfont=None, **kwargs): """ Construct a new Unselected object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.histogram.Unselected marker plotly.graph_objects.histogram.unselected.Marker instance or dict with compatible properties textfont plotly.graph_objects.histogram.unselected.Textfont instance or dict with compatible properties Returns ------- Unselected """ super(Unselected, self).__init__("unselected") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.histogram.Unselected constructor must be a dict or an instance of plotly.graph_objs.histogram.Unselected""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram import unselected as v_unselected # Initialize validators # --------------------- self._validators["marker"] = v_unselected.MarkerValidator() self._validators["textfont"] = v_unselected.TextfontValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v _v = arg.pop("textfont", None) self["textfont"] = textfont if textfont is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Stream(_BaseTraceHierarchyType): # maxpoints # --------- @property def maxpoints(self): """ Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. The 'maxpoints' property is a number and may be specified as: - An int or float in the interval [0, 10000] Returns ------- int|float """ return self["maxpoints"] @maxpoints.setter def maxpoints(self, val): self["maxpoints"] = val # token # ----- @property def token(self): """ The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. The 'token' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["token"] @token.setter def token(self, val): self["token"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """ def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): """ Construct a new Stream object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.histogram.Stream maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- Stream """ super(Stream, self).__init__("stream") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.histogram.Stream constructor must be a dict or an instance of plotly.graph_objs.histogram.Stream""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram import stream as v_stream # Initialize validators # --------------------- self._validators["maxpoints"] = v_stream.MaxpointsValidator() self._validators["token"] = v_stream.TokenValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("maxpoints", None) self["maxpoints"] = maxpoints if maxpoints is not None else _v _v = arg.pop("token", None) self["token"] = token if token is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Selected(_BaseTraceHierarchyType): # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.histogram.selected.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. Returns ------- plotly.graph_objs.histogram.selected.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # textfont # -------- @property def textfont(self): """ The 'textfont' property is an instance of Textfont that may be specified as: - An instance of plotly.graph_objs.histogram.selected.Textfont - A dict of string/value properties that will be passed to the Textfont constructor Supported dict properties: color Sets the text font color of selected points. Returns ------- plotly.graph_objs.histogram.selected.Textfont """ return self["textfont"] @textfont.setter def textfont(self, val): self["textfont"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ marker plotly.graph_objects.histogram.selected.Marker instance or dict with compatible properties textfont plotly.graph_objects.histogram.selected.Textfont instance or dict with compatible properties """ def __init__(self, arg=None, marker=None, textfont=None, **kwargs): """ Construct a new Selected object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.histogram.Selected marker plotly.graph_objects.histogram.selected.Marker instance or dict with compatible properties textfont plotly.graph_objects.histogram.selected.Textfont instance or dict with compatible properties Returns ------- Selected """ super(Selected, self).__init__("selected") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.histogram.Selected constructor must be a dict or an instance of plotly.graph_objs.histogram.Selected""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram import selected as v_selected # Initialize validators # --------------------- self._validators["marker"] = v_selected.MarkerValidator() self._validators["textfont"] = v_selected.TextfontValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v _v = arg.pop("textfont", None) self["textfont"] = textfont if textfont is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # autocolorscale # -------------- @property def autocolorscale(self): """ Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. The 'autocolorscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocolorscale"] @autocolorscale.setter def autocolorscale(self, val): self["autocolorscale"] = val # cauto # ----- @property def cauto(self): """ Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. The 'cauto' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["cauto"] @cauto.setter def cauto(self, val): self["cauto"] = val # cmax # ---- @property def cmax(self): """ Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. The 'cmax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmax"] @cmax.setter def cmax(self, val): self["cmax"] = val # cmid # ---- @property def cmid(self): """ Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. The 'cmid' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmid"] @cmid.setter def cmid(self, val): self["cmid"] = val # cmin # ---- @property def cmin(self): """ Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. The 'cmin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmin"] @cmin.setter def cmin(self, val): self["cmin"] = val # color # ----- @property def color(self): """ Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A number that will be interpreted as a color according to histogram.marker.colorscale - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # coloraxis # --------- @property def coloraxis(self): """ Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. The 'coloraxis' property is an identifier of a particular subplot, of type 'coloraxis', that may be specified as the string 'coloraxis' optionally followed by an integer >= 1 (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) Returns ------- str """ return self["coloraxis"] @coloraxis.setter def coloraxis(self, val): self["coloraxis"] = val # colorbar # -------- @property def colorbar(self): """ The 'colorbar' property is an instance of ColorBar that may be specified as: - An instance of plotly.graph_objs.histogram.marker.ColorBar - A dict of string/value properties that will be passed to the ColorBar constructor Supported dict properties: bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.histogram.marke r.colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.histogram.marker.colorbar.tickformatstopdefau lts), sets the default property values to use for elements of histogram.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.histogram.marker.colorbar. Title instance or dict with compatible properties titlefont Deprecated: Please use histogram.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use histogram.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- plotly.graph_objs.histogram.marker.ColorBar """ return self["colorbar"] @colorbar.setter def colorbar(self, val): self["colorbar"] = val # colorscale # ---------- @property def colorscale(self): """ Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnB u,Greens,YlOrRd,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland ,Jet,Hot,Blackbody,Earth,Electric,Viridis,Cividis. The 'colorscale' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.histogram.marker.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,R eds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Black body,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . Returns ------- plotly.graph_objs.histogram.marker.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the bars. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # opacitysrc # ---------- @property def opacitysrc(self): """ Sets the source reference on plot.ly for opacity . The 'opacitysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["opacitysrc"] @opacitysrc.setter def opacitysrc(self, val): self["opacitysrc"] = val # reversescale # ------------ @property def reversescale(self): """ Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. The 'reversescale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["reversescale"] @reversescale.setter def reversescale(self, val): self["reversescale"] = val # showscale # --------- @property def showscale(self): """ Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. The 'showscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showscale"] @showscale.setter def showscale(self, val): self["showscale"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.histogram.marker.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu ,Reds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . line plotly.graph_objects.histogram.marker.Line instance or dict with compatible properties opacity Sets the opacity of the bars. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. """ def __init__( self, arg=None, autocolorscale=None, cauto=None, cmax=None, cmid=None, cmin=None, color=None, coloraxis=None, colorbar=None, colorscale=None, colorsrc=None, line=None, opacity=None, opacitysrc=None, reversescale=None, showscale=None, **kwargs ): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.histogram.Marker autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.histogram.marker.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu ,Reds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . line plotly.graph_objects.histogram.marker.Line instance or dict with compatible properties opacity Sets the opacity of the bars. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.histogram.Marker constructor must be a dict or an instance of plotly.graph_objs.histogram.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram import marker as v_marker # Initialize validators # --------------------- self._validators["autocolorscale"] = v_marker.AutocolorscaleValidator() self._validators["cauto"] = v_marker.CautoValidator() self._validators["cmax"] = v_marker.CmaxValidator() self._validators["cmid"] = v_marker.CmidValidator() self._validators["cmin"] = v_marker.CminValidator() self._validators["color"] = v_marker.ColorValidator() self._validators["coloraxis"] = v_marker.ColoraxisValidator() self._validators["colorbar"] = v_marker.ColorBarValidator() self._validators["colorscale"] = v_marker.ColorscaleValidator() self._validators["colorsrc"] = v_marker.ColorsrcValidator() self._validators["line"] = v_marker.LineValidator() self._validators["opacity"] = v_marker.OpacityValidator() self._validators["opacitysrc"] = v_marker.OpacitysrcValidator() self._validators["reversescale"] = v_marker.ReversescaleValidator() self._validators["showscale"] = v_marker.ShowscaleValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autocolorscale", None) self["autocolorscale"] = autocolorscale if autocolorscale is not None else _v _v = arg.pop("cauto", None) self["cauto"] = cauto if cauto is not None else _v _v = arg.pop("cmax", None) self["cmax"] = cmax if cmax is not None else _v _v = arg.pop("cmid", None) self["cmid"] = cmid if cmid is not None else _v _v = arg.pop("cmin", None) self["cmin"] = cmin if cmin is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("coloraxis", None) self["coloraxis"] = coloraxis if coloraxis is not None else _v _v = arg.pop("colorbar", None) self["colorbar"] = colorbar if colorbar is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("opacitysrc", None) self["opacitysrc"] = opacitysrc if opacitysrc is not None else _v _v = arg.pop("reversescale", None) self["reversescale"] = reversescale if reversescale is not None else _v _v = arg.pop("showscale", None) self["showscale"] = showscale if showscale is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Hoverlabel(_BaseTraceHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'right', 'auto'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["align"] @align.setter def align(self, val): self["align"] = val # alignsrc # -------- @property def alignsrc(self): """ Sets the source reference on plot.ly for align . The 'alignsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["alignsrc"] @alignsrc.setter def alignsrc(self, val): self["alignsrc"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the hover labels for this trace The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bgcolorsrc # ---------- @property def bgcolorsrc(self): """ Sets the source reference on plot.ly for bgcolor . The 'bgcolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bgcolorsrc"] @bgcolorsrc.setter def bgcolorsrc(self, val): self["bgcolorsrc"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the border color of the hover labels for this trace. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # bordercolorsrc # -------------- @property def bordercolorsrc(self): """ Sets the source reference on plot.ly for bordercolor . The 'bordercolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bordercolorsrc"] @bordercolorsrc.setter def bordercolorsrc(self, val): self["bordercolorsrc"] = val # font # ---- @property def font(self): """ Sets the font used in hover labels. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.histogram.hoverlabel.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.histogram.hoverlabel.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # namelength # ---------- @property def namelength(self): """ Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. The 'namelength' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [-1, 9223372036854775807] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|numpy.ndarray """ return self["namelength"] @namelength.setter def namelength(self, val): self["namelength"] = val # namelengthsrc # ------------- @property def namelengthsrc(self): """ Sets the source reference on plot.ly for namelength . The 'namelengthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["namelengthsrc"] @namelengthsrc.setter def namelengthsrc(self, val): self["namelengthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """ def __init__( self, arg=None, align=None, alignsrc=None, bgcolor=None, bgcolorsrc=None, bordercolor=None, bordercolorsrc=None, font=None, namelength=None, namelengthsrc=None, **kwargs ): """ Construct a new Hoverlabel object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.histogram.Hoverlabel align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- Hoverlabel """ super(Hoverlabel, self).__init__("hoverlabel") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.histogram.Hoverlabel constructor must be a dict or an instance of plotly.graph_objs.histogram.Hoverlabel""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram import hoverlabel as v_hoverlabel # Initialize validators # --------------------- self._validators["align"] = v_hoverlabel.AlignValidator() self._validators["alignsrc"] = v_hoverlabel.AlignsrcValidator() self._validators["bgcolor"] = v_hoverlabel.BgcolorValidator() self._validators["bgcolorsrc"] = v_hoverlabel.BgcolorsrcValidator() self._validators["bordercolor"] = v_hoverlabel.BordercolorValidator() self._validators["bordercolorsrc"] = v_hoverlabel.BordercolorsrcValidator() self._validators["font"] = v_hoverlabel.FontValidator() self._validators["namelength"] = v_hoverlabel.NamelengthValidator() self._validators["namelengthsrc"] = v_hoverlabel.NamelengthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("alignsrc", None) self["alignsrc"] = alignsrc if alignsrc is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bgcolorsrc", None) self["bgcolorsrc"] = bgcolorsrc if bgcolorsrc is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("bordercolorsrc", None) self["bordercolorsrc"] = bordercolorsrc if bordercolorsrc is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("namelength", None) self["namelength"] = namelength if namelength is not None else _v _v = arg.pop("namelengthsrc", None) self["namelengthsrc"] = namelengthsrc if namelengthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class ErrorY(_BaseTraceHierarchyType): # array # ----- @property def array(self): """ Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. The 'array' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["array"] @array.setter def array(self, val): self["array"] = val # arrayminus # ---------- @property def arrayminus(self): """ Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. The 'arrayminus' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["arrayminus"] @arrayminus.setter def arrayminus(self, val): self["arrayminus"] = val # arrayminussrc # ------------- @property def arrayminussrc(self): """ Sets the source reference on plot.ly for arrayminus . The 'arrayminussrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["arrayminussrc"] @arrayminussrc.setter def arrayminussrc(self, val): self["arrayminussrc"] = val # arraysrc # -------- @property def arraysrc(self): """ Sets the source reference on plot.ly for array . The 'arraysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["arraysrc"] @arraysrc.setter def arraysrc(self, val): self["arraysrc"] = val # color # ----- @property def color(self): """ Sets the stoke color of the error bars. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # symmetric # --------- @property def symmetric(self): """ Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. The 'symmetric' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["symmetric"] @symmetric.setter def symmetric(self, val): self["symmetric"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness (in px) of the error bars. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # traceref # -------- @property def traceref(self): """ The 'traceref' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["traceref"] @traceref.setter def traceref(self, val): self["traceref"] = val # tracerefminus # ------------- @property def tracerefminus(self): """ The 'tracerefminus' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["tracerefminus"] @tracerefminus.setter def tracerefminus(self, val): self["tracerefminus"] = val # type # ---- @property def type(self): """ Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. The 'type' property is an enumeration that may be specified as: - One of the following enumeration values: ['percent', 'constant', 'sqrt', 'data'] Returns ------- Any """ return self["type"] @type.setter def type(self, val): self["type"] = val # value # ----- @property def value(self): """ Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. The 'value' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["value"] @value.setter def value(self, val): self["value"] = val # valueminus # ---------- @property def valueminus(self): """ Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars The 'valueminus' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["valueminus"] @valueminus.setter def valueminus(self, val): self["valueminus"] = val # visible # ------- @property def visible(self): """ Determines whether or not this set of error bars is visible. The 'visible' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # width # ----- @property def width(self): """ Sets the width (in px) of the cross-bar at both ends of the error bars. The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ array Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. arrayminus Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. arrayminussrc Sets the source reference on plot.ly for arrayminus . arraysrc Sets the source reference on plot.ly for array . color Sets the stoke color of the error bars. symmetric Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. thickness Sets the thickness (in px) of the error bars. traceref tracerefminus type Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. value Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. valueminus Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars visible Determines whether or not this set of error bars is visible. width Sets the width (in px) of the cross-bar at both ends of the error bars. """ def __init__( self, arg=None, array=None, arrayminus=None, arrayminussrc=None, arraysrc=None, color=None, symmetric=None, thickness=None, traceref=None, tracerefminus=None, type=None, value=None, valueminus=None, visible=None, width=None, **kwargs ): """ Construct a new ErrorY object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.histogram.ErrorY array Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. arrayminus Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. arrayminussrc Sets the source reference on plot.ly for arrayminus . arraysrc Sets the source reference on plot.ly for array . color Sets the stoke color of the error bars. symmetric Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. thickness Sets the thickness (in px) of the error bars. traceref tracerefminus type Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. value Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. valueminus Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars visible Determines whether or not this set of error bars is visible. width Sets the width (in px) of the cross-bar at both ends of the error bars. Returns ------- ErrorY """ super(ErrorY, self).__init__("error_y") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.histogram.ErrorY constructor must be a dict or an instance of plotly.graph_objs.histogram.ErrorY""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram import error_y as v_error_y # Initialize validators # --------------------- self._validators["array"] = v_error_y.ArrayValidator() self._validators["arrayminus"] = v_error_y.ArrayminusValidator() self._validators["arrayminussrc"] = v_error_y.ArrayminussrcValidator() self._validators["arraysrc"] = v_error_y.ArraysrcValidator() self._validators["color"] = v_error_y.ColorValidator() self._validators["symmetric"] = v_error_y.SymmetricValidator() self._validators["thickness"] = v_error_y.ThicknessValidator() self._validators["traceref"] = v_error_y.TracerefValidator() self._validators["tracerefminus"] = v_error_y.TracerefminusValidator() self._validators["type"] = v_error_y.TypeValidator() self._validators["value"] = v_error_y.ValueValidator() self._validators["valueminus"] = v_error_y.ValueminusValidator() self._validators["visible"] = v_error_y.VisibleValidator() self._validators["width"] = v_error_y.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("array", None) self["array"] = array if array is not None else _v _v = arg.pop("arrayminus", None) self["arrayminus"] = arrayminus if arrayminus is not None else _v _v = arg.pop("arrayminussrc", None) self["arrayminussrc"] = arrayminussrc if arrayminussrc is not None else _v _v = arg.pop("arraysrc", None) self["arraysrc"] = arraysrc if arraysrc is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("symmetric", None) self["symmetric"] = symmetric if symmetric is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("traceref", None) self["traceref"] = traceref if traceref is not None else _v _v = arg.pop("tracerefminus", None) self["tracerefminus"] = tracerefminus if tracerefminus is not None else _v _v = arg.pop("type", None) self["type"] = type if type is not None else _v _v = arg.pop("value", None) self["value"] = value if value is not None else _v _v = arg.pop("valueminus", None) self["valueminus"] = valueminus if valueminus is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class ErrorX(_BaseTraceHierarchyType): # array # ----- @property def array(self): """ Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. The 'array' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["array"] @array.setter def array(self, val): self["array"] = val # arrayminus # ---------- @property def arrayminus(self): """ Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. The 'arrayminus' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["arrayminus"] @arrayminus.setter def arrayminus(self, val): self["arrayminus"] = val # arrayminussrc # ------------- @property def arrayminussrc(self): """ Sets the source reference on plot.ly for arrayminus . The 'arrayminussrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["arrayminussrc"] @arrayminussrc.setter def arrayminussrc(self, val): self["arrayminussrc"] = val # arraysrc # -------- @property def arraysrc(self): """ Sets the source reference on plot.ly for array . The 'arraysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["arraysrc"] @arraysrc.setter def arraysrc(self, val): self["arraysrc"] = val # color # ----- @property def color(self): """ Sets the stoke color of the error bars. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # copy_ystyle # ----------- @property def copy_ystyle(self): """ The 'copy_ystyle' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["copy_ystyle"] @copy_ystyle.setter def copy_ystyle(self, val): self["copy_ystyle"] = val # symmetric # --------- @property def symmetric(self): """ Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. The 'symmetric' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["symmetric"] @symmetric.setter def symmetric(self, val): self["symmetric"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness (in px) of the error bars. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # traceref # -------- @property def traceref(self): """ The 'traceref' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["traceref"] @traceref.setter def traceref(self, val): self["traceref"] = val # tracerefminus # ------------- @property def tracerefminus(self): """ The 'tracerefminus' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["tracerefminus"] @tracerefminus.setter def tracerefminus(self, val): self["tracerefminus"] = val # type # ---- @property def type(self): """ Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. The 'type' property is an enumeration that may be specified as: - One of the following enumeration values: ['percent', 'constant', 'sqrt', 'data'] Returns ------- Any """ return self["type"] @type.setter def type(self, val): self["type"] = val # value # ----- @property def value(self): """ Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. The 'value' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["value"] @value.setter def value(self, val): self["value"] = val # valueminus # ---------- @property def valueminus(self): """ Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars The 'valueminus' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["valueminus"] @valueminus.setter def valueminus(self, val): self["valueminus"] = val # visible # ------- @property def visible(self): """ Determines whether or not this set of error bars is visible. The 'visible' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # width # ----- @property def width(self): """ Sets the width (in px) of the cross-bar at both ends of the error bars. The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ array Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. arrayminus Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. arrayminussrc Sets the source reference on plot.ly for arrayminus . arraysrc Sets the source reference on plot.ly for array . color Sets the stoke color of the error bars. copy_ystyle symmetric Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. thickness Sets the thickness (in px) of the error bars. traceref tracerefminus type Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. value Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. valueminus Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars visible Determines whether or not this set of error bars is visible. width Sets the width (in px) of the cross-bar at both ends of the error bars. """ def __init__( self, arg=None, array=None, arrayminus=None, arrayminussrc=None, arraysrc=None, color=None, copy_ystyle=None, symmetric=None, thickness=None, traceref=None, tracerefminus=None, type=None, value=None, valueminus=None, visible=None, width=None, **kwargs ): """ Construct a new ErrorX object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.histogram.ErrorX array Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. arrayminus Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. arrayminussrc Sets the source reference on plot.ly for arrayminus . arraysrc Sets the source reference on plot.ly for array . color Sets the stoke color of the error bars. copy_ystyle symmetric Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. thickness Sets the thickness (in px) of the error bars. traceref tracerefminus type Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. value Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. valueminus Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars visible Determines whether or not this set of error bars is visible. width Sets the width (in px) of the cross-bar at both ends of the error bars. Returns ------- ErrorX """ super(ErrorX, self).__init__("error_x") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.histogram.ErrorX constructor must be a dict or an instance of plotly.graph_objs.histogram.ErrorX""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram import error_x as v_error_x # Initialize validators # --------------------- self._validators["array"] = v_error_x.ArrayValidator() self._validators["arrayminus"] = v_error_x.ArrayminusValidator() self._validators["arrayminussrc"] = v_error_x.ArrayminussrcValidator() self._validators["arraysrc"] = v_error_x.ArraysrcValidator() self._validators["color"] = v_error_x.ColorValidator() self._validators["copy_ystyle"] = v_error_x.CopyYstyleValidator() self._validators["symmetric"] = v_error_x.SymmetricValidator() self._validators["thickness"] = v_error_x.ThicknessValidator() self._validators["traceref"] = v_error_x.TracerefValidator() self._validators["tracerefminus"] = v_error_x.TracerefminusValidator() self._validators["type"] = v_error_x.TypeValidator() self._validators["value"] = v_error_x.ValueValidator() self._validators["valueminus"] = v_error_x.ValueminusValidator() self._validators["visible"] = v_error_x.VisibleValidator() self._validators["width"] = v_error_x.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("array", None) self["array"] = array if array is not None else _v _v = arg.pop("arrayminus", None) self["arrayminus"] = arrayminus if arrayminus is not None else _v _v = arg.pop("arrayminussrc", None) self["arrayminussrc"] = arrayminussrc if arrayminussrc is not None else _v _v = arg.pop("arraysrc", None) self["arraysrc"] = arraysrc if arraysrc is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("copy_ystyle", None) self["copy_ystyle"] = copy_ystyle if copy_ystyle is not None else _v _v = arg.pop("symmetric", None) self["symmetric"] = symmetric if symmetric is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("traceref", None) self["traceref"] = traceref if traceref is not None else _v _v = arg.pop("tracerefminus", None) self["tracerefminus"] = tracerefminus if tracerefminus is not None else _v _v = arg.pop("type", None) self["type"] = type if type is not None else _v _v = arg.pop("value", None) self["value"] = value if value is not None else _v _v = arg.pop("valueminus", None) self["valueminus"] = valueminus if valueminus is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Cumulative(_BaseTraceHierarchyType): # currentbin # ---------- @property def currentbin(self): """ Only applies if cumulative is enabled. Sets whether the current bin is included, excluded, or has half of its value included in the current cumulative value. "include" is the default for compatibility with various other tools, however it introduces a half-bin bias to the results. "exclude" makes the opposite half-bin bias, and "half" removes it. The 'currentbin' property is an enumeration that may be specified as: - One of the following enumeration values: ['include', 'exclude', 'half'] Returns ------- Any """ return self["currentbin"] @currentbin.setter def currentbin(self, val): self["currentbin"] = val # direction # --------- @property def direction(self): """ Only applies if cumulative is enabled. If "increasing" (default) we sum all prior bins, so the result increases from left to right. If "decreasing" we sum later bins so the result decreases from left to right. The 'direction' property is an enumeration that may be specified as: - One of the following enumeration values: ['increasing', 'decreasing'] Returns ------- Any """ return self["direction"] @direction.setter def direction(self, val): self["direction"] = val # enabled # ------- @property def enabled(self): """ If true, display the cumulative distribution by summing the binned values. Use the `direction` and `centralbin` attributes to tune the accumulation method. Note: in this mode, the "density" `histnorm` settings behave the same as their equivalents without "density": "" and "density" both rise to the number of data points, and "probability" and *probability density* both rise to the number of sample points. The 'enabled' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["enabled"] @enabled.setter def enabled(self, val): self["enabled"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ currentbin Only applies if cumulative is enabled. Sets whether the current bin is included, excluded, or has half of its value included in the current cumulative value. "include" is the default for compatibility with various other tools, however it introduces a half-bin bias to the results. "exclude" makes the opposite half-bin bias, and "half" removes it. direction Only applies if cumulative is enabled. If "increasing" (default) we sum all prior bins, so the result increases from left to right. If "decreasing" we sum later bins so the result decreases from left to right. enabled If true, display the cumulative distribution by summing the binned values. Use the `direction` and `centralbin` attributes to tune the accumulation method. Note: in this mode, the "density" `histnorm` settings behave the same as their equivalents without "density": "" and "density" both rise to the number of data points, and "probability" and *probability density* both rise to the number of sample points. """ def __init__( self, arg=None, currentbin=None, direction=None, enabled=None, **kwargs ): """ Construct a new Cumulative object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.histogram.Cumulative currentbin Only applies if cumulative is enabled. Sets whether the current bin is included, excluded, or has half of its value included in the current cumulative value. "include" is the default for compatibility with various other tools, however it introduces a half-bin bias to the results. "exclude" makes the opposite half-bin bias, and "half" removes it. direction Only applies if cumulative is enabled. If "increasing" (default) we sum all prior bins, so the result increases from left to right. If "decreasing" we sum later bins so the result decreases from left to right. enabled If true, display the cumulative distribution by summing the binned values. Use the `direction` and `centralbin` attributes to tune the accumulation method. Note: in this mode, the "density" `histnorm` settings behave the same as their equivalents without "density": "" and "density" both rise to the number of data points, and "probability" and *probability density* both rise to the number of sample points. Returns ------- Cumulative """ super(Cumulative, self).__init__("cumulative") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.histogram.Cumulative constructor must be a dict or an instance of plotly.graph_objs.histogram.Cumulative""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram import cumulative as v_cumulative # Initialize validators # --------------------- self._validators["currentbin"] = v_cumulative.CurrentbinValidator() self._validators["direction"] = v_cumulative.DirectionValidator() self._validators["enabled"] = v_cumulative.EnabledValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("currentbin", None) self["currentbin"] = currentbin if currentbin is not None else _v _v = arg.pop("direction", None) self["direction"] = direction if direction is not None else _v _v = arg.pop("enabled", None) self["enabled"] = enabled if enabled is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = [ "Cumulative", "ErrorX", "ErrorY", "Hoverlabel", "Marker", "Selected", "Stream", "Unselected", "XBins", "YBins", "hoverlabel", "marker", "selected", "unselected", ] from plotly.graph_objs.histogram import unselected from plotly.graph_objs.histogram import selected from plotly.graph_objs.histogram import marker from plotly.graph_objs.histogram import hoverlabel plotly-4.4.1+dfsg.orig/plotly/graph_objs/histogram/selected/0000755000175000017500000000000013573746613023516 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/histogram/selected/__init__.py0000644000175000017500000002520213573721546025626 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Textfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the text font color of selected points. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram.selected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the text font color of selected points. """ def __init__(self, arg=None, color=None, **kwargs): """ Construct a new Textfont object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.histogram.selected.Textfont color Sets the text font color of selected points. Returns ------- Textfont """ super(Textfont, self).__init__("textfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.histogram.selected.Textfont constructor must be a dict or an instance of plotly.graph_objs.histogram.selected.Textfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram.selected import textfont as v_textfont # Initialize validators # --------------------- self._validators["color"] = v_textfont.ColorValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the marker color of selected points. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # opacity # ------- @property def opacity(self): """ Sets the marker opacity of selected points. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram.selected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. """ def __init__(self, arg=None, color=None, opacity=None, **kwargs): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.histogram.selected.Marker color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.histogram.selected.Marker constructor must be a dict or an instance of plotly.graph_objs.histogram.selected.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram.selected import marker as v_marker # Initialize validators # --------------------- self._validators["color"] = v_marker.ColorValidator() self._validators["opacity"] = v_marker.OpacityValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Marker", "Textfont"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/carpet/0000755000175000017500000000000013573746613021207 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/carpet/__init__.py0000644000175000017500000052637013573721547023334 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Stream(_BaseTraceHierarchyType): # maxpoints # --------- @property def maxpoints(self): """ Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. The 'maxpoints' property is a number and may be specified as: - An int or float in the interval [0, 10000] Returns ------- int|float """ return self["maxpoints"] @maxpoints.setter def maxpoints(self, val): self["maxpoints"] = val # token # ----- @property def token(self): """ The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. The 'token' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["token"] @token.setter def token(self, val): self["token"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "carpet" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """ def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): """ Construct a new Stream object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.carpet.Stream maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- Stream """ super(Stream, self).__init__("stream") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.carpet.Stream constructor must be a dict or an instance of plotly.graph_objs.carpet.Stream""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.carpet import stream as v_stream # Initialize validators # --------------------- self._validators["maxpoints"] = v_stream.MaxpointsValidator() self._validators["token"] = v_stream.TokenValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("maxpoints", None) self["maxpoints"] = maxpoints if maxpoints is not None else _v _v = arg.pop("token", None) self["token"] = token if token is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "carpet" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object The default font used for axis & tick labels on this carpet Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.carpet.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.carpet.Font constructor must be a dict or an instance of plotly.graph_objs.carpet.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.carpet import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Baxis(_BaseTraceHierarchyType): # arraydtick # ---------- @property def arraydtick(self): """ The stride between grid lines along the axis The 'arraydtick' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [1, 9223372036854775807] Returns ------- int """ return self["arraydtick"] @arraydtick.setter def arraydtick(self, val): self["arraydtick"] = val # arraytick0 # ---------- @property def arraytick0(self): """ The starting index of grid lines along the axis The 'arraytick0' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["arraytick0"] @arraytick0.setter def arraytick0(self, val): self["arraytick0"] = val # autorange # --------- @property def autorange(self): """ Determines whether or not the range of this axis is computed in relation to the input data. See `rangemode` for more info. If `range` is provided, then `autorange` is set to False. The 'autorange' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'reversed'] Returns ------- Any """ return self["autorange"] @autorange.setter def autorange(self, val): self["autorange"] = val # categoryarray # ------------- @property def categoryarray(self): """ Sets the order in which categories on this axis appear. Only has an effect if `categoryorder` is set to "array". Used with `categoryorder`. The 'categoryarray' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["categoryarray"] @categoryarray.setter def categoryarray(self, val): self["categoryarray"] = val # categoryarraysrc # ---------------- @property def categoryarraysrc(self): """ Sets the source reference on plot.ly for categoryarray . The 'categoryarraysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["categoryarraysrc"] @categoryarraysrc.setter def categoryarraysrc(self, val): self["categoryarraysrc"] = val # categoryorder # ------------- @property def categoryorder(self): """ Specifies the ordering logic for the case of categorical variables. By default, plotly uses "trace", which specifies the order that is present in the data supplied. Set `categoryorder` to *category ascending* or *category descending* if order should be determined by the alphanumerical order of the category names. Set `categoryorder` to "array" to derive the ordering from the attribute `categoryarray`. If a category is not found in the `categoryarray` array, the sorting behavior for that attribute will be identical to the "trace" mode. The unspecified categories will follow the categories in `categoryarray`. The 'categoryorder' property is an enumeration that may be specified as: - One of the following enumeration values: ['trace', 'category ascending', 'category descending', 'array'] Returns ------- Any """ return self["categoryorder"] @categoryorder.setter def categoryorder(self, val): self["categoryorder"] = val # cheatertype # ----------- @property def cheatertype(self): """ The 'cheatertype' property is an enumeration that may be specified as: - One of the following enumeration values: ['index', 'value'] Returns ------- Any """ return self["cheatertype"] @cheatertype.setter def cheatertype(self, val): self["cheatertype"] = val # color # ----- @property def color(self): """ Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # dtick # ----- @property def dtick(self): """ The stride between grid lines along the axis The 'dtick' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["dtick"] @dtick.setter def dtick(self, val): self["dtick"] = val # endline # ------- @property def endline(self): """ Determines whether or not a line is drawn at along the final value of this axis. If True, the end line is drawn on top of the grid lines. The 'endline' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["endline"] @endline.setter def endline(self, val): self["endline"] = val # endlinecolor # ------------ @property def endlinecolor(self): """ Sets the line color of the end line. The 'endlinecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["endlinecolor"] @endlinecolor.setter def endlinecolor(self, val): self["endlinecolor"] = val # endlinewidth # ------------ @property def endlinewidth(self): """ Sets the width (in px) of the end line. The 'endlinewidth' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["endlinewidth"] @endlinewidth.setter def endlinewidth(self, val): self["endlinewidth"] = val # exponentformat # -------------- @property def exponentformat(self): """ Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. The 'exponentformat' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'e', 'E', 'power', 'SI', 'B'] Returns ------- Any """ return self["exponentformat"] @exponentformat.setter def exponentformat(self, val): self["exponentformat"] = val # fixedrange # ---------- @property def fixedrange(self): """ Determines whether or not this axis is zoom-able. If true, then zoom is disabled. The 'fixedrange' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["fixedrange"] @fixedrange.setter def fixedrange(self, val): self["fixedrange"] = val # gridcolor # --------- @property def gridcolor(self): """ Sets the axis line color. The 'gridcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["gridcolor"] @gridcolor.setter def gridcolor(self, val): self["gridcolor"] = val # gridwidth # --------- @property def gridwidth(self): """ Sets the width (in px) of the axis line. The 'gridwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["gridwidth"] @gridwidth.setter def gridwidth(self, val): self["gridwidth"] = val # labelpadding # ------------ @property def labelpadding(self): """ Extra padding between label and the axis The 'labelpadding' property is a integer and may be specified as: - An int (or float that will be cast to an int) Returns ------- int """ return self["labelpadding"] @labelpadding.setter def labelpadding(self, val): self["labelpadding"] = val # labelprefix # ----------- @property def labelprefix(self): """ Sets a axis label prefix. The 'labelprefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["labelprefix"] @labelprefix.setter def labelprefix(self, val): self["labelprefix"] = val # labelsuffix # ----------- @property def labelsuffix(self): """ Sets a axis label suffix. The 'labelsuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["labelsuffix"] @labelsuffix.setter def labelsuffix(self, val): self["labelsuffix"] = val # linecolor # --------- @property def linecolor(self): """ Sets the axis line color. The 'linecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["linecolor"] @linecolor.setter def linecolor(self, val): self["linecolor"] = val # linewidth # --------- @property def linewidth(self): """ Sets the width (in px) of the axis line. The 'linewidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["linewidth"] @linewidth.setter def linewidth(self, val): self["linewidth"] = val # minorgridcolor # -------------- @property def minorgridcolor(self): """ Sets the color of the grid lines. The 'minorgridcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["minorgridcolor"] @minorgridcolor.setter def minorgridcolor(self, val): self["minorgridcolor"] = val # minorgridcount # -------------- @property def minorgridcount(self): """ Sets the number of minor grid ticks per major grid tick The 'minorgridcount' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["minorgridcount"] @minorgridcount.setter def minorgridcount(self, val): self["minorgridcount"] = val # minorgridwidth # -------------- @property def minorgridwidth(self): """ Sets the width (in px) of the grid lines. The 'minorgridwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["minorgridwidth"] @minorgridwidth.setter def minorgridwidth(self, val): self["minorgridwidth"] = val # nticks # ------ @property def nticks(self): """ Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". The 'nticks' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nticks"] @nticks.setter def nticks(self, val): self["nticks"] = val # range # ----- @property def range(self): """ Sets the range of this axis. If the axis `type` is "log", then you must take the log of your desired range (e.g. to set the range from 1 to 100, set the range from 0 to 2). If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. The 'range' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'range[0]' property accepts values of any type (1) The 'range[1]' property accepts values of any type Returns ------- list """ return self["range"] @range.setter def range(self, val): self["range"] = val # rangemode # --------- @property def rangemode(self): """ If "normal", the range is computed in relation to the extrema of the input data. If *tozero*`, the range extends to 0, regardless of the input data If "nonnegative", the range is non-negative, regardless of the input data. The 'rangemode' property is an enumeration that may be specified as: - One of the following enumeration values: ['normal', 'tozero', 'nonnegative'] Returns ------- Any """ return self["rangemode"] @rangemode.setter def rangemode(self, val): self["rangemode"] = val # separatethousands # ----------------- @property def separatethousands(self): """ If "true", even 4-digit integers are separated The 'separatethousands' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["separatethousands"] @separatethousands.setter def separatethousands(self, val): self["separatethousands"] = val # showexponent # ------------ @property def showexponent(self): """ If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. The 'showexponent' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showexponent"] @showexponent.setter def showexponent(self, val): self["showexponent"] = val # showgrid # -------- @property def showgrid(self): """ Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. The 'showgrid' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showgrid"] @showgrid.setter def showgrid(self, val): self["showgrid"] = val # showline # -------- @property def showline(self): """ Determines whether or not a line bounding this axis is drawn. The 'showline' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showline"] @showline.setter def showline(self, val): self["showline"] = val # showticklabels # -------------- @property def showticklabels(self): """ Determines whether axis labels are drawn on the low side, the high side, both, or neither side of the axis. The 'showticklabels' property is an enumeration that may be specified as: - One of the following enumeration values: ['start', 'end', 'both', 'none'] Returns ------- Any """ return self["showticklabels"] @showticklabels.setter def showticklabels(self, val): self["showticklabels"] = val # showtickprefix # -------------- @property def showtickprefix(self): """ If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. The 'showtickprefix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showtickprefix"] @showtickprefix.setter def showtickprefix(self, val): self["showtickprefix"] = val # showticksuffix # -------------- @property def showticksuffix(self): """ Same as `showtickprefix` but for tick suffixes. The 'showticksuffix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showticksuffix"] @showticksuffix.setter def showticksuffix(self, val): self["showticksuffix"] = val # smoothing # --------- @property def smoothing(self): """ The 'smoothing' property is a number and may be specified as: - An int or float in the interval [0, 1.3] Returns ------- int|float """ return self["smoothing"] @smoothing.setter def smoothing(self, val): self["smoothing"] = val # startline # --------- @property def startline(self): """ Determines whether or not a line is drawn at along the starting value of this axis. If True, the start line is drawn on top of the grid lines. The 'startline' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["startline"] @startline.setter def startline(self, val): self["startline"] = val # startlinecolor # -------------- @property def startlinecolor(self): """ Sets the line color of the start line. The 'startlinecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["startlinecolor"] @startlinecolor.setter def startlinecolor(self, val): self["startlinecolor"] = val # startlinewidth # -------------- @property def startlinewidth(self): """ Sets the width (in px) of the start line. The 'startlinewidth' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["startlinewidth"] @startlinewidth.setter def startlinewidth(self, val): self["startlinewidth"] = val # tick0 # ----- @property def tick0(self): """ The starting index of grid lines along the axis The 'tick0' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["tick0"] @tick0.setter def tick0(self, val): self["tick0"] = val # tickangle # --------- @property def tickangle(self): """ Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. The 'tickangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["tickangle"] @tickangle.setter def tickangle(self, val): self["tickangle"] = val # tickfont # -------- @property def tickfont(self): """ Sets the tick font. The 'tickfont' property is an instance of Tickfont that may be specified as: - An instance of plotly.graph_objs.carpet.baxis.Tickfont - A dict of string/value properties that will be passed to the Tickfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.carpet.baxis.Tickfont """ return self["tickfont"] @tickfont.setter def tickfont(self, val): self["tickfont"] = val # tickformat # ---------- @property def tickformat(self): """ Sets the tick label formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'tickformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickformat"] @tickformat.setter def tickformat(self, val): self["tickformat"] = val # tickformatstops # --------------- @property def tickformatstops(self): """ The 'tickformatstops' property is a tuple of instances of Tickformatstop that may be specified as: - A list or tuple of instances of plotly.graph_objs.carpet.baxis.Tickformatstop - A list or tuple of dicts of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- tuple[plotly.graph_objs.carpet.baxis.Tickformatstop] """ return self["tickformatstops"] @tickformatstops.setter def tickformatstops(self, val): self["tickformatstops"] = val # tickformatstopdefaults # ---------------------- @property def tickformatstopdefaults(self): """ When used in a template (as layout.template.data.carpet.baxis.tickformatstopdefaults), sets the default property values to use for elements of carpet.baxis.tickformatstops The 'tickformatstopdefaults' property is an instance of Tickformatstop that may be specified as: - An instance of plotly.graph_objs.carpet.baxis.Tickformatstop - A dict of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: Returns ------- plotly.graph_objs.carpet.baxis.Tickformatstop """ return self["tickformatstopdefaults"] @tickformatstopdefaults.setter def tickformatstopdefaults(self, val): self["tickformatstopdefaults"] = val # tickmode # -------- @property def tickmode(self): """ The 'tickmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['linear', 'array'] Returns ------- Any """ return self["tickmode"] @tickmode.setter def tickmode(self, val): self["tickmode"] = val # tickprefix # ---------- @property def tickprefix(self): """ Sets a tick label prefix. The 'tickprefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickprefix"] @tickprefix.setter def tickprefix(self, val): self["tickprefix"] = val # ticksuffix # ---------- @property def ticksuffix(self): """ Sets a tick label suffix. The 'ticksuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ticksuffix"] @ticksuffix.setter def ticksuffix(self, val): self["ticksuffix"] = val # ticktext # -------- @property def ticktext(self): """ Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. The 'ticktext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ticktext"] @ticktext.setter def ticktext(self, val): self["ticktext"] = val # ticktextsrc # ----------- @property def ticktextsrc(self): """ Sets the source reference on plot.ly for ticktext . The 'ticktextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ticktextsrc"] @ticktextsrc.setter def ticktextsrc(self, val): self["ticktextsrc"] = val # tickvals # -------- @property def tickvals(self): """ Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. The 'tickvals' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["tickvals"] @tickvals.setter def tickvals(self, val): self["tickvals"] = val # tickvalssrc # ----------- @property def tickvalssrc(self): """ Sets the source reference on plot.ly for tickvals . The 'tickvalssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tickvalssrc"] @tickvalssrc.setter def tickvalssrc(self, val): self["tickvalssrc"] = val # title # ----- @property def title(self): """ The 'title' property is an instance of Title that may be specified as: - An instance of plotly.graph_objs.carpet.baxis.Title - A dict of string/value properties that will be passed to the Title constructor Supported dict properties: font Sets this axis' title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. offset An additional amount by which to offset the title from the tick labels, given in pixels. Note that this used to be set by the now deprecated `titleoffset` attribute. text Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- plotly.graph_objs.carpet.baxis.Title """ return self["title"] @title.setter def title(self, val): self["title"] = val # titlefont # --------- @property def titlefont(self): """ Deprecated: Please use carpet.baxis.title.font instead. Sets this axis' title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.carpet.baxis.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- """ return self["titlefont"] @titlefont.setter def titlefont(self, val): self["titlefont"] = val # titleoffset # ----------- @property def titleoffset(self): """ Deprecated: Please use carpet.baxis.title.offset instead. An additional amount by which to offset the title from the tick labels, given in pixels. Note that this used to be set by the now deprecated `titleoffset` attribute. The 'offset' property is a number and may be specified as: - An int or float Returns ------- """ return self["titleoffset"] @titleoffset.setter def titleoffset(self, val): self["titleoffset"] = val # type # ---- @property def type(self): """ Sets the axis type. By default, plotly attempts to determined the axis type by looking into the data of the traces that referenced the axis in question. The 'type' property is an enumeration that may be specified as: - One of the following enumeration values: ['-', 'linear', 'date', 'category'] Returns ------- Any """ return self["type"] @type.setter def type(self, val): self["type"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "carpet" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ arraydtick The stride between grid lines along the axis arraytick0 The starting index of grid lines along the axis autorange Determines whether or not the range of this axis is computed in relation to the input data. See `rangemode` for more info. If `range` is provided, then `autorange` is set to False. categoryarray Sets the order in which categories on this axis appear. Only has an effect if `categoryorder` is set to "array". Used with `categoryorder`. categoryarraysrc Sets the source reference on plot.ly for categoryarray . categoryorder Specifies the ordering logic for the case of categorical variables. By default, plotly uses "trace", which specifies the order that is present in the data supplied. Set `categoryorder` to *category ascending* or *category descending* if order should be determined by the alphanumerical order of the category names. Set `categoryorder` to "array" to derive the ordering from the attribute `categoryarray`. If a category is not found in the `categoryarray` array, the sorting behavior for that attribute will be identical to the "trace" mode. The unspecified categories will follow the categories in `categoryarray`. cheatertype color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. dtick The stride between grid lines along the axis endline Determines whether or not a line is drawn at along the final value of this axis. If True, the end line is drawn on top of the grid lines. endlinecolor Sets the line color of the end line. endlinewidth Sets the width (in px) of the end line. exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. fixedrange Determines whether or not this axis is zoom-able. If true, then zoom is disabled. gridcolor Sets the axis line color. gridwidth Sets the width (in px) of the axis line. labelpadding Extra padding between label and the axis labelprefix Sets a axis label prefix. labelsuffix Sets a axis label suffix. linecolor Sets the axis line color. linewidth Sets the width (in px) of the axis line. minorgridcolor Sets the color of the grid lines. minorgridcount Sets the number of minor grid ticks per major grid tick minorgridwidth Sets the width (in px) of the grid lines. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". range Sets the range of this axis. If the axis `type` is "log", then you must take the log of your desired range (e.g. to set the range from 1 to 100, set the range from 0 to 2). If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. rangemode If "normal", the range is computed in relation to the extrema of the input data. If *tozero*`, the range extends to 0, regardless of the input data If "nonnegative", the range is non-negative, regardless of the input data. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showgrid Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. showline Determines whether or not a line bounding this axis is drawn. showticklabels Determines whether axis labels are drawn on the low side, the high side, both, or neither side of the axis. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. smoothing startline Determines whether or not a line is drawn at along the starting value of this axis. If True, the start line is drawn on top of the grid lines. startlinecolor Sets the line color of the start line. startlinewidth Sets the width (in px) of the start line. tick0 The starting index of grid lines along the axis tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickfont Sets the tick font. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.carpet.baxis.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.carpet .baxis.tickformatstopdefaults), sets the default property values to use for elements of carpet.baxis.tickformatstops tickmode tickprefix Sets a tick label prefix. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . title plotly.graph_objects.carpet.baxis.Title instance or dict with compatible properties titlefont Deprecated: Please use carpet.baxis.title.font instead. Sets this axis' title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleoffset Deprecated: Please use carpet.baxis.title.offset instead. An additional amount by which to offset the title from the tick labels, given in pixels. Note that this used to be set by the now deprecated `titleoffset` attribute. type Sets the axis type. By default, plotly attempts to determined the axis type by looking into the data of the traces that referenced the axis in question. """ _mapped_properties = { "titlefont": ("title", "font"), "titleoffset": ("title", "offset"), } def __init__( self, arg=None, arraydtick=None, arraytick0=None, autorange=None, categoryarray=None, categoryarraysrc=None, categoryorder=None, cheatertype=None, color=None, dtick=None, endline=None, endlinecolor=None, endlinewidth=None, exponentformat=None, fixedrange=None, gridcolor=None, gridwidth=None, labelpadding=None, labelprefix=None, labelsuffix=None, linecolor=None, linewidth=None, minorgridcolor=None, minorgridcount=None, minorgridwidth=None, nticks=None, range=None, rangemode=None, separatethousands=None, showexponent=None, showgrid=None, showline=None, showticklabels=None, showtickprefix=None, showticksuffix=None, smoothing=None, startline=None, startlinecolor=None, startlinewidth=None, tick0=None, tickangle=None, tickfont=None, tickformat=None, tickformatstops=None, tickformatstopdefaults=None, tickmode=None, tickprefix=None, ticksuffix=None, ticktext=None, ticktextsrc=None, tickvals=None, tickvalssrc=None, title=None, titlefont=None, titleoffset=None, type=None, **kwargs ): """ Construct a new Baxis object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.carpet.Baxis arraydtick The stride between grid lines along the axis arraytick0 The starting index of grid lines along the axis autorange Determines whether or not the range of this axis is computed in relation to the input data. See `rangemode` for more info. If `range` is provided, then `autorange` is set to False. categoryarray Sets the order in which categories on this axis appear. Only has an effect if `categoryorder` is set to "array". Used with `categoryorder`. categoryarraysrc Sets the source reference on plot.ly for categoryarray . categoryorder Specifies the ordering logic for the case of categorical variables. By default, plotly uses "trace", which specifies the order that is present in the data supplied. Set `categoryorder` to *category ascending* or *category descending* if order should be determined by the alphanumerical order of the category names. Set `categoryorder` to "array" to derive the ordering from the attribute `categoryarray`. If a category is not found in the `categoryarray` array, the sorting behavior for that attribute will be identical to the "trace" mode. The unspecified categories will follow the categories in `categoryarray`. cheatertype color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. dtick The stride between grid lines along the axis endline Determines whether or not a line is drawn at along the final value of this axis. If True, the end line is drawn on top of the grid lines. endlinecolor Sets the line color of the end line. endlinewidth Sets the width (in px) of the end line. exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. fixedrange Determines whether or not this axis is zoom-able. If true, then zoom is disabled. gridcolor Sets the axis line color. gridwidth Sets the width (in px) of the axis line. labelpadding Extra padding between label and the axis labelprefix Sets a axis label prefix. labelsuffix Sets a axis label suffix. linecolor Sets the axis line color. linewidth Sets the width (in px) of the axis line. minorgridcolor Sets the color of the grid lines. minorgridcount Sets the number of minor grid ticks per major grid tick minorgridwidth Sets the width (in px) of the grid lines. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". range Sets the range of this axis. If the axis `type` is "log", then you must take the log of your desired range (e.g. to set the range from 1 to 100, set the range from 0 to 2). If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. rangemode If "normal", the range is computed in relation to the extrema of the input data. If *tozero*`, the range extends to 0, regardless of the input data If "nonnegative", the range is non-negative, regardless of the input data. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showgrid Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. showline Determines whether or not a line bounding this axis is drawn. showticklabels Determines whether axis labels are drawn on the low side, the high side, both, or neither side of the axis. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. smoothing startline Determines whether or not a line is drawn at along the starting value of this axis. If True, the start line is drawn on top of the grid lines. startlinecolor Sets the line color of the start line. startlinewidth Sets the width (in px) of the start line. tick0 The starting index of grid lines along the axis tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickfont Sets the tick font. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.carpet.baxis.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.carpet .baxis.tickformatstopdefaults), sets the default property values to use for elements of carpet.baxis.tickformatstops tickmode tickprefix Sets a tick label prefix. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . title plotly.graph_objects.carpet.baxis.Title instance or dict with compatible properties titlefont Deprecated: Please use carpet.baxis.title.font instead. Sets this axis' title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleoffset Deprecated: Please use carpet.baxis.title.offset instead. An additional amount by which to offset the title from the tick labels, given in pixels. Note that this used to be set by the now deprecated `titleoffset` attribute. type Sets the axis type. By default, plotly attempts to determined the axis type by looking into the data of the traces that referenced the axis in question. Returns ------- Baxis """ super(Baxis, self).__init__("baxis") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.carpet.Baxis constructor must be a dict or an instance of plotly.graph_objs.carpet.Baxis""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.carpet import baxis as v_baxis # Initialize validators # --------------------- self._validators["arraydtick"] = v_baxis.ArraydtickValidator() self._validators["arraytick0"] = v_baxis.Arraytick0Validator() self._validators["autorange"] = v_baxis.AutorangeValidator() self._validators["categoryarray"] = v_baxis.CategoryarrayValidator() self._validators["categoryarraysrc"] = v_baxis.CategoryarraysrcValidator() self._validators["categoryorder"] = v_baxis.CategoryorderValidator() self._validators["cheatertype"] = v_baxis.CheatertypeValidator() self._validators["color"] = v_baxis.ColorValidator() self._validators["dtick"] = v_baxis.DtickValidator() self._validators["endline"] = v_baxis.EndlineValidator() self._validators["endlinecolor"] = v_baxis.EndlinecolorValidator() self._validators["endlinewidth"] = v_baxis.EndlinewidthValidator() self._validators["exponentformat"] = v_baxis.ExponentformatValidator() self._validators["fixedrange"] = v_baxis.FixedrangeValidator() self._validators["gridcolor"] = v_baxis.GridcolorValidator() self._validators["gridwidth"] = v_baxis.GridwidthValidator() self._validators["labelpadding"] = v_baxis.LabelpaddingValidator() self._validators["labelprefix"] = v_baxis.LabelprefixValidator() self._validators["labelsuffix"] = v_baxis.LabelsuffixValidator() self._validators["linecolor"] = v_baxis.LinecolorValidator() self._validators["linewidth"] = v_baxis.LinewidthValidator() self._validators["minorgridcolor"] = v_baxis.MinorgridcolorValidator() self._validators["minorgridcount"] = v_baxis.MinorgridcountValidator() self._validators["minorgridwidth"] = v_baxis.MinorgridwidthValidator() self._validators["nticks"] = v_baxis.NticksValidator() self._validators["range"] = v_baxis.RangeValidator() self._validators["rangemode"] = v_baxis.RangemodeValidator() self._validators["separatethousands"] = v_baxis.SeparatethousandsValidator() self._validators["showexponent"] = v_baxis.ShowexponentValidator() self._validators["showgrid"] = v_baxis.ShowgridValidator() self._validators["showline"] = v_baxis.ShowlineValidator() self._validators["showticklabels"] = v_baxis.ShowticklabelsValidator() self._validators["showtickprefix"] = v_baxis.ShowtickprefixValidator() self._validators["showticksuffix"] = v_baxis.ShowticksuffixValidator() self._validators["smoothing"] = v_baxis.SmoothingValidator() self._validators["startline"] = v_baxis.StartlineValidator() self._validators["startlinecolor"] = v_baxis.StartlinecolorValidator() self._validators["startlinewidth"] = v_baxis.StartlinewidthValidator() self._validators["tick0"] = v_baxis.Tick0Validator() self._validators["tickangle"] = v_baxis.TickangleValidator() self._validators["tickfont"] = v_baxis.TickfontValidator() self._validators["tickformat"] = v_baxis.TickformatValidator() self._validators["tickformatstops"] = v_baxis.TickformatstopsValidator() self._validators["tickformatstopdefaults"] = v_baxis.TickformatstopValidator() self._validators["tickmode"] = v_baxis.TickmodeValidator() self._validators["tickprefix"] = v_baxis.TickprefixValidator() self._validators["ticksuffix"] = v_baxis.TicksuffixValidator() self._validators["ticktext"] = v_baxis.TicktextValidator() self._validators["ticktextsrc"] = v_baxis.TicktextsrcValidator() self._validators["tickvals"] = v_baxis.TickvalsValidator() self._validators["tickvalssrc"] = v_baxis.TickvalssrcValidator() self._validators["title"] = v_baxis.TitleValidator() self._validators["type"] = v_baxis.TypeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("arraydtick", None) self["arraydtick"] = arraydtick if arraydtick is not None else _v _v = arg.pop("arraytick0", None) self["arraytick0"] = arraytick0 if arraytick0 is not None else _v _v = arg.pop("autorange", None) self["autorange"] = autorange if autorange is not None else _v _v = arg.pop("categoryarray", None) self["categoryarray"] = categoryarray if categoryarray is not None else _v _v = arg.pop("categoryarraysrc", None) self["categoryarraysrc"] = ( categoryarraysrc if categoryarraysrc is not None else _v ) _v = arg.pop("categoryorder", None) self["categoryorder"] = categoryorder if categoryorder is not None else _v _v = arg.pop("cheatertype", None) self["cheatertype"] = cheatertype if cheatertype is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("dtick", None) self["dtick"] = dtick if dtick is not None else _v _v = arg.pop("endline", None) self["endline"] = endline if endline is not None else _v _v = arg.pop("endlinecolor", None) self["endlinecolor"] = endlinecolor if endlinecolor is not None else _v _v = arg.pop("endlinewidth", None) self["endlinewidth"] = endlinewidth if endlinewidth is not None else _v _v = arg.pop("exponentformat", None) self["exponentformat"] = exponentformat if exponentformat is not None else _v _v = arg.pop("fixedrange", None) self["fixedrange"] = fixedrange if fixedrange is not None else _v _v = arg.pop("gridcolor", None) self["gridcolor"] = gridcolor if gridcolor is not None else _v _v = arg.pop("gridwidth", None) self["gridwidth"] = gridwidth if gridwidth is not None else _v _v = arg.pop("labelpadding", None) self["labelpadding"] = labelpadding if labelpadding is not None else _v _v = arg.pop("labelprefix", None) self["labelprefix"] = labelprefix if labelprefix is not None else _v _v = arg.pop("labelsuffix", None) self["labelsuffix"] = labelsuffix if labelsuffix is not None else _v _v = arg.pop("linecolor", None) self["linecolor"] = linecolor if linecolor is not None else _v _v = arg.pop("linewidth", None) self["linewidth"] = linewidth if linewidth is not None else _v _v = arg.pop("minorgridcolor", None) self["minorgridcolor"] = minorgridcolor if minorgridcolor is not None else _v _v = arg.pop("minorgridcount", None) self["minorgridcount"] = minorgridcount if minorgridcount is not None else _v _v = arg.pop("minorgridwidth", None) self["minorgridwidth"] = minorgridwidth if minorgridwidth is not None else _v _v = arg.pop("nticks", None) self["nticks"] = nticks if nticks is not None else _v _v = arg.pop("range", None) self["range"] = range if range is not None else _v _v = arg.pop("rangemode", None) self["rangemode"] = rangemode if rangemode is not None else _v _v = arg.pop("separatethousands", None) self["separatethousands"] = ( separatethousands if separatethousands is not None else _v ) _v = arg.pop("showexponent", None) self["showexponent"] = showexponent if showexponent is not None else _v _v = arg.pop("showgrid", None) self["showgrid"] = showgrid if showgrid is not None else _v _v = arg.pop("showline", None) self["showline"] = showline if showline is not None else _v _v = arg.pop("showticklabels", None) self["showticklabels"] = showticklabels if showticklabels is not None else _v _v = arg.pop("showtickprefix", None) self["showtickprefix"] = showtickprefix if showtickprefix is not None else _v _v = arg.pop("showticksuffix", None) self["showticksuffix"] = showticksuffix if showticksuffix is not None else _v _v = arg.pop("smoothing", None) self["smoothing"] = smoothing if smoothing is not None else _v _v = arg.pop("startline", None) self["startline"] = startline if startline is not None else _v _v = arg.pop("startlinecolor", None) self["startlinecolor"] = startlinecolor if startlinecolor is not None else _v _v = arg.pop("startlinewidth", None) self["startlinewidth"] = startlinewidth if startlinewidth is not None else _v _v = arg.pop("tick0", None) self["tick0"] = tick0 if tick0 is not None else _v _v = arg.pop("tickangle", None) self["tickangle"] = tickangle if tickangle is not None else _v _v = arg.pop("tickfont", None) self["tickfont"] = tickfont if tickfont is not None else _v _v = arg.pop("tickformat", None) self["tickformat"] = tickformat if tickformat is not None else _v _v = arg.pop("tickformatstops", None) self["tickformatstops"] = tickformatstops if tickformatstops is not None else _v _v = arg.pop("tickformatstopdefaults", None) self["tickformatstopdefaults"] = ( tickformatstopdefaults if tickformatstopdefaults is not None else _v ) _v = arg.pop("tickmode", None) self["tickmode"] = tickmode if tickmode is not None else _v _v = arg.pop("tickprefix", None) self["tickprefix"] = tickprefix if tickprefix is not None else _v _v = arg.pop("ticksuffix", None) self["ticksuffix"] = ticksuffix if ticksuffix is not None else _v _v = arg.pop("ticktext", None) self["ticktext"] = ticktext if ticktext is not None else _v _v = arg.pop("ticktextsrc", None) self["ticktextsrc"] = ticktextsrc if ticktextsrc is not None else _v _v = arg.pop("tickvals", None) self["tickvals"] = tickvals if tickvals is not None else _v _v = arg.pop("tickvalssrc", None) self["tickvalssrc"] = tickvalssrc if tickvalssrc is not None else _v _v = arg.pop("title", None) self["title"] = title if title is not None else _v _v = arg.pop("titlefont", None) _v = titlefont if titlefont is not None else _v if _v is not None: self["titlefont"] = _v _v = arg.pop("titleoffset", None) _v = titleoffset if titleoffset is not None else _v if _v is not None: self["titleoffset"] = _v _v = arg.pop("type", None) self["type"] = type if type is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Aaxis(_BaseTraceHierarchyType): # arraydtick # ---------- @property def arraydtick(self): """ The stride between grid lines along the axis The 'arraydtick' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [1, 9223372036854775807] Returns ------- int """ return self["arraydtick"] @arraydtick.setter def arraydtick(self, val): self["arraydtick"] = val # arraytick0 # ---------- @property def arraytick0(self): """ The starting index of grid lines along the axis The 'arraytick0' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["arraytick0"] @arraytick0.setter def arraytick0(self, val): self["arraytick0"] = val # autorange # --------- @property def autorange(self): """ Determines whether or not the range of this axis is computed in relation to the input data. See `rangemode` for more info. If `range` is provided, then `autorange` is set to False. The 'autorange' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'reversed'] Returns ------- Any """ return self["autorange"] @autorange.setter def autorange(self, val): self["autorange"] = val # categoryarray # ------------- @property def categoryarray(self): """ Sets the order in which categories on this axis appear. Only has an effect if `categoryorder` is set to "array". Used with `categoryorder`. The 'categoryarray' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["categoryarray"] @categoryarray.setter def categoryarray(self, val): self["categoryarray"] = val # categoryarraysrc # ---------------- @property def categoryarraysrc(self): """ Sets the source reference on plot.ly for categoryarray . The 'categoryarraysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["categoryarraysrc"] @categoryarraysrc.setter def categoryarraysrc(self, val): self["categoryarraysrc"] = val # categoryorder # ------------- @property def categoryorder(self): """ Specifies the ordering logic for the case of categorical variables. By default, plotly uses "trace", which specifies the order that is present in the data supplied. Set `categoryorder` to *category ascending* or *category descending* if order should be determined by the alphanumerical order of the category names. Set `categoryorder` to "array" to derive the ordering from the attribute `categoryarray`. If a category is not found in the `categoryarray` array, the sorting behavior for that attribute will be identical to the "trace" mode. The unspecified categories will follow the categories in `categoryarray`. The 'categoryorder' property is an enumeration that may be specified as: - One of the following enumeration values: ['trace', 'category ascending', 'category descending', 'array'] Returns ------- Any """ return self["categoryorder"] @categoryorder.setter def categoryorder(self, val): self["categoryorder"] = val # cheatertype # ----------- @property def cheatertype(self): """ The 'cheatertype' property is an enumeration that may be specified as: - One of the following enumeration values: ['index', 'value'] Returns ------- Any """ return self["cheatertype"] @cheatertype.setter def cheatertype(self, val): self["cheatertype"] = val # color # ----- @property def color(self): """ Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # dtick # ----- @property def dtick(self): """ The stride between grid lines along the axis The 'dtick' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["dtick"] @dtick.setter def dtick(self, val): self["dtick"] = val # endline # ------- @property def endline(self): """ Determines whether or not a line is drawn at along the final value of this axis. If True, the end line is drawn on top of the grid lines. The 'endline' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["endline"] @endline.setter def endline(self, val): self["endline"] = val # endlinecolor # ------------ @property def endlinecolor(self): """ Sets the line color of the end line. The 'endlinecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["endlinecolor"] @endlinecolor.setter def endlinecolor(self, val): self["endlinecolor"] = val # endlinewidth # ------------ @property def endlinewidth(self): """ Sets the width (in px) of the end line. The 'endlinewidth' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["endlinewidth"] @endlinewidth.setter def endlinewidth(self, val): self["endlinewidth"] = val # exponentformat # -------------- @property def exponentformat(self): """ Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. The 'exponentformat' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'e', 'E', 'power', 'SI', 'B'] Returns ------- Any """ return self["exponentformat"] @exponentformat.setter def exponentformat(self, val): self["exponentformat"] = val # fixedrange # ---------- @property def fixedrange(self): """ Determines whether or not this axis is zoom-able. If true, then zoom is disabled. The 'fixedrange' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["fixedrange"] @fixedrange.setter def fixedrange(self, val): self["fixedrange"] = val # gridcolor # --------- @property def gridcolor(self): """ Sets the axis line color. The 'gridcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["gridcolor"] @gridcolor.setter def gridcolor(self, val): self["gridcolor"] = val # gridwidth # --------- @property def gridwidth(self): """ Sets the width (in px) of the axis line. The 'gridwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["gridwidth"] @gridwidth.setter def gridwidth(self, val): self["gridwidth"] = val # labelpadding # ------------ @property def labelpadding(self): """ Extra padding between label and the axis The 'labelpadding' property is a integer and may be specified as: - An int (or float that will be cast to an int) Returns ------- int """ return self["labelpadding"] @labelpadding.setter def labelpadding(self, val): self["labelpadding"] = val # labelprefix # ----------- @property def labelprefix(self): """ Sets a axis label prefix. The 'labelprefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["labelprefix"] @labelprefix.setter def labelprefix(self, val): self["labelprefix"] = val # labelsuffix # ----------- @property def labelsuffix(self): """ Sets a axis label suffix. The 'labelsuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["labelsuffix"] @labelsuffix.setter def labelsuffix(self, val): self["labelsuffix"] = val # linecolor # --------- @property def linecolor(self): """ Sets the axis line color. The 'linecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["linecolor"] @linecolor.setter def linecolor(self, val): self["linecolor"] = val # linewidth # --------- @property def linewidth(self): """ Sets the width (in px) of the axis line. The 'linewidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["linewidth"] @linewidth.setter def linewidth(self, val): self["linewidth"] = val # minorgridcolor # -------------- @property def minorgridcolor(self): """ Sets the color of the grid lines. The 'minorgridcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["minorgridcolor"] @minorgridcolor.setter def minorgridcolor(self, val): self["minorgridcolor"] = val # minorgridcount # -------------- @property def minorgridcount(self): """ Sets the number of minor grid ticks per major grid tick The 'minorgridcount' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["minorgridcount"] @minorgridcount.setter def minorgridcount(self, val): self["minorgridcount"] = val # minorgridwidth # -------------- @property def minorgridwidth(self): """ Sets the width (in px) of the grid lines. The 'minorgridwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["minorgridwidth"] @minorgridwidth.setter def minorgridwidth(self, val): self["minorgridwidth"] = val # nticks # ------ @property def nticks(self): """ Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". The 'nticks' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nticks"] @nticks.setter def nticks(self, val): self["nticks"] = val # range # ----- @property def range(self): """ Sets the range of this axis. If the axis `type` is "log", then you must take the log of your desired range (e.g. to set the range from 1 to 100, set the range from 0 to 2). If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. The 'range' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'range[0]' property accepts values of any type (1) The 'range[1]' property accepts values of any type Returns ------- list """ return self["range"] @range.setter def range(self, val): self["range"] = val # rangemode # --------- @property def rangemode(self): """ If "normal", the range is computed in relation to the extrema of the input data. If *tozero*`, the range extends to 0, regardless of the input data If "nonnegative", the range is non-negative, regardless of the input data. The 'rangemode' property is an enumeration that may be specified as: - One of the following enumeration values: ['normal', 'tozero', 'nonnegative'] Returns ------- Any """ return self["rangemode"] @rangemode.setter def rangemode(self, val): self["rangemode"] = val # separatethousands # ----------------- @property def separatethousands(self): """ If "true", even 4-digit integers are separated The 'separatethousands' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["separatethousands"] @separatethousands.setter def separatethousands(self, val): self["separatethousands"] = val # showexponent # ------------ @property def showexponent(self): """ If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. The 'showexponent' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showexponent"] @showexponent.setter def showexponent(self, val): self["showexponent"] = val # showgrid # -------- @property def showgrid(self): """ Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. The 'showgrid' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showgrid"] @showgrid.setter def showgrid(self, val): self["showgrid"] = val # showline # -------- @property def showline(self): """ Determines whether or not a line bounding this axis is drawn. The 'showline' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showline"] @showline.setter def showline(self, val): self["showline"] = val # showticklabels # -------------- @property def showticklabels(self): """ Determines whether axis labels are drawn on the low side, the high side, both, or neither side of the axis. The 'showticklabels' property is an enumeration that may be specified as: - One of the following enumeration values: ['start', 'end', 'both', 'none'] Returns ------- Any """ return self["showticklabels"] @showticklabels.setter def showticklabels(self, val): self["showticklabels"] = val # showtickprefix # -------------- @property def showtickprefix(self): """ If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. The 'showtickprefix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showtickprefix"] @showtickprefix.setter def showtickprefix(self, val): self["showtickprefix"] = val # showticksuffix # -------------- @property def showticksuffix(self): """ Same as `showtickprefix` but for tick suffixes. The 'showticksuffix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showticksuffix"] @showticksuffix.setter def showticksuffix(self, val): self["showticksuffix"] = val # smoothing # --------- @property def smoothing(self): """ The 'smoothing' property is a number and may be specified as: - An int or float in the interval [0, 1.3] Returns ------- int|float """ return self["smoothing"] @smoothing.setter def smoothing(self, val): self["smoothing"] = val # startline # --------- @property def startline(self): """ Determines whether or not a line is drawn at along the starting value of this axis. If True, the start line is drawn on top of the grid lines. The 'startline' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["startline"] @startline.setter def startline(self, val): self["startline"] = val # startlinecolor # -------------- @property def startlinecolor(self): """ Sets the line color of the start line. The 'startlinecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["startlinecolor"] @startlinecolor.setter def startlinecolor(self, val): self["startlinecolor"] = val # startlinewidth # -------------- @property def startlinewidth(self): """ Sets the width (in px) of the start line. The 'startlinewidth' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["startlinewidth"] @startlinewidth.setter def startlinewidth(self, val): self["startlinewidth"] = val # tick0 # ----- @property def tick0(self): """ The starting index of grid lines along the axis The 'tick0' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["tick0"] @tick0.setter def tick0(self, val): self["tick0"] = val # tickangle # --------- @property def tickangle(self): """ Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. The 'tickangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["tickangle"] @tickangle.setter def tickangle(self, val): self["tickangle"] = val # tickfont # -------- @property def tickfont(self): """ Sets the tick font. The 'tickfont' property is an instance of Tickfont that may be specified as: - An instance of plotly.graph_objs.carpet.aaxis.Tickfont - A dict of string/value properties that will be passed to the Tickfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.carpet.aaxis.Tickfont """ return self["tickfont"] @tickfont.setter def tickfont(self, val): self["tickfont"] = val # tickformat # ---------- @property def tickformat(self): """ Sets the tick label formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'tickformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickformat"] @tickformat.setter def tickformat(self, val): self["tickformat"] = val # tickformatstops # --------------- @property def tickformatstops(self): """ The 'tickformatstops' property is a tuple of instances of Tickformatstop that may be specified as: - A list or tuple of instances of plotly.graph_objs.carpet.aaxis.Tickformatstop - A list or tuple of dicts of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- tuple[plotly.graph_objs.carpet.aaxis.Tickformatstop] """ return self["tickformatstops"] @tickformatstops.setter def tickformatstops(self, val): self["tickformatstops"] = val # tickformatstopdefaults # ---------------------- @property def tickformatstopdefaults(self): """ When used in a template (as layout.template.data.carpet.aaxis.tickformatstopdefaults), sets the default property values to use for elements of carpet.aaxis.tickformatstops The 'tickformatstopdefaults' property is an instance of Tickformatstop that may be specified as: - An instance of plotly.graph_objs.carpet.aaxis.Tickformatstop - A dict of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: Returns ------- plotly.graph_objs.carpet.aaxis.Tickformatstop """ return self["tickformatstopdefaults"] @tickformatstopdefaults.setter def tickformatstopdefaults(self, val): self["tickformatstopdefaults"] = val # tickmode # -------- @property def tickmode(self): """ The 'tickmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['linear', 'array'] Returns ------- Any """ return self["tickmode"] @tickmode.setter def tickmode(self, val): self["tickmode"] = val # tickprefix # ---------- @property def tickprefix(self): """ Sets a tick label prefix. The 'tickprefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickprefix"] @tickprefix.setter def tickprefix(self, val): self["tickprefix"] = val # ticksuffix # ---------- @property def ticksuffix(self): """ Sets a tick label suffix. The 'ticksuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ticksuffix"] @ticksuffix.setter def ticksuffix(self, val): self["ticksuffix"] = val # ticktext # -------- @property def ticktext(self): """ Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. The 'ticktext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ticktext"] @ticktext.setter def ticktext(self, val): self["ticktext"] = val # ticktextsrc # ----------- @property def ticktextsrc(self): """ Sets the source reference on plot.ly for ticktext . The 'ticktextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ticktextsrc"] @ticktextsrc.setter def ticktextsrc(self, val): self["ticktextsrc"] = val # tickvals # -------- @property def tickvals(self): """ Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. The 'tickvals' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["tickvals"] @tickvals.setter def tickvals(self, val): self["tickvals"] = val # tickvalssrc # ----------- @property def tickvalssrc(self): """ Sets the source reference on plot.ly for tickvals . The 'tickvalssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tickvalssrc"] @tickvalssrc.setter def tickvalssrc(self, val): self["tickvalssrc"] = val # title # ----- @property def title(self): """ The 'title' property is an instance of Title that may be specified as: - An instance of plotly.graph_objs.carpet.aaxis.Title - A dict of string/value properties that will be passed to the Title constructor Supported dict properties: font Sets this axis' title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. offset An additional amount by which to offset the title from the tick labels, given in pixels. Note that this used to be set by the now deprecated `titleoffset` attribute. text Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- plotly.graph_objs.carpet.aaxis.Title """ return self["title"] @title.setter def title(self, val): self["title"] = val # titlefont # --------- @property def titlefont(self): """ Deprecated: Please use carpet.aaxis.title.font instead. Sets this axis' title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.carpet.aaxis.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- """ return self["titlefont"] @titlefont.setter def titlefont(self, val): self["titlefont"] = val # titleoffset # ----------- @property def titleoffset(self): """ Deprecated: Please use carpet.aaxis.title.offset instead. An additional amount by which to offset the title from the tick labels, given in pixels. Note that this used to be set by the now deprecated `titleoffset` attribute. The 'offset' property is a number and may be specified as: - An int or float Returns ------- """ return self["titleoffset"] @titleoffset.setter def titleoffset(self, val): self["titleoffset"] = val # type # ---- @property def type(self): """ Sets the axis type. By default, plotly attempts to determined the axis type by looking into the data of the traces that referenced the axis in question. The 'type' property is an enumeration that may be specified as: - One of the following enumeration values: ['-', 'linear', 'date', 'category'] Returns ------- Any """ return self["type"] @type.setter def type(self, val): self["type"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "carpet" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ arraydtick The stride between grid lines along the axis arraytick0 The starting index of grid lines along the axis autorange Determines whether or not the range of this axis is computed in relation to the input data. See `rangemode` for more info. If `range` is provided, then `autorange` is set to False. categoryarray Sets the order in which categories on this axis appear. Only has an effect if `categoryorder` is set to "array". Used with `categoryorder`. categoryarraysrc Sets the source reference on plot.ly for categoryarray . categoryorder Specifies the ordering logic for the case of categorical variables. By default, plotly uses "trace", which specifies the order that is present in the data supplied. Set `categoryorder` to *category ascending* or *category descending* if order should be determined by the alphanumerical order of the category names. Set `categoryorder` to "array" to derive the ordering from the attribute `categoryarray`. If a category is not found in the `categoryarray` array, the sorting behavior for that attribute will be identical to the "trace" mode. The unspecified categories will follow the categories in `categoryarray`. cheatertype color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. dtick The stride between grid lines along the axis endline Determines whether or not a line is drawn at along the final value of this axis. If True, the end line is drawn on top of the grid lines. endlinecolor Sets the line color of the end line. endlinewidth Sets the width (in px) of the end line. exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. fixedrange Determines whether or not this axis is zoom-able. If true, then zoom is disabled. gridcolor Sets the axis line color. gridwidth Sets the width (in px) of the axis line. labelpadding Extra padding between label and the axis labelprefix Sets a axis label prefix. labelsuffix Sets a axis label suffix. linecolor Sets the axis line color. linewidth Sets the width (in px) of the axis line. minorgridcolor Sets the color of the grid lines. minorgridcount Sets the number of minor grid ticks per major grid tick minorgridwidth Sets the width (in px) of the grid lines. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". range Sets the range of this axis. If the axis `type` is "log", then you must take the log of your desired range (e.g. to set the range from 1 to 100, set the range from 0 to 2). If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. rangemode If "normal", the range is computed in relation to the extrema of the input data. If *tozero*`, the range extends to 0, regardless of the input data If "nonnegative", the range is non-negative, regardless of the input data. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showgrid Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. showline Determines whether or not a line bounding this axis is drawn. showticklabels Determines whether axis labels are drawn on the low side, the high side, both, or neither side of the axis. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. smoothing startline Determines whether or not a line is drawn at along the starting value of this axis. If True, the start line is drawn on top of the grid lines. startlinecolor Sets the line color of the start line. startlinewidth Sets the width (in px) of the start line. tick0 The starting index of grid lines along the axis tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickfont Sets the tick font. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.carpet.aaxis.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.carpet .aaxis.tickformatstopdefaults), sets the default property values to use for elements of carpet.aaxis.tickformatstops tickmode tickprefix Sets a tick label prefix. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . title plotly.graph_objects.carpet.aaxis.Title instance or dict with compatible properties titlefont Deprecated: Please use carpet.aaxis.title.font instead. Sets this axis' title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleoffset Deprecated: Please use carpet.aaxis.title.offset instead. An additional amount by which to offset the title from the tick labels, given in pixels. Note that this used to be set by the now deprecated `titleoffset` attribute. type Sets the axis type. By default, plotly attempts to determined the axis type by looking into the data of the traces that referenced the axis in question. """ _mapped_properties = { "titlefont": ("title", "font"), "titleoffset": ("title", "offset"), } def __init__( self, arg=None, arraydtick=None, arraytick0=None, autorange=None, categoryarray=None, categoryarraysrc=None, categoryorder=None, cheatertype=None, color=None, dtick=None, endline=None, endlinecolor=None, endlinewidth=None, exponentformat=None, fixedrange=None, gridcolor=None, gridwidth=None, labelpadding=None, labelprefix=None, labelsuffix=None, linecolor=None, linewidth=None, minorgridcolor=None, minorgridcount=None, minorgridwidth=None, nticks=None, range=None, rangemode=None, separatethousands=None, showexponent=None, showgrid=None, showline=None, showticklabels=None, showtickprefix=None, showticksuffix=None, smoothing=None, startline=None, startlinecolor=None, startlinewidth=None, tick0=None, tickangle=None, tickfont=None, tickformat=None, tickformatstops=None, tickformatstopdefaults=None, tickmode=None, tickprefix=None, ticksuffix=None, ticktext=None, ticktextsrc=None, tickvals=None, tickvalssrc=None, title=None, titlefont=None, titleoffset=None, type=None, **kwargs ): """ Construct a new Aaxis object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.carpet.Aaxis arraydtick The stride between grid lines along the axis arraytick0 The starting index of grid lines along the axis autorange Determines whether or not the range of this axis is computed in relation to the input data. See `rangemode` for more info. If `range` is provided, then `autorange` is set to False. categoryarray Sets the order in which categories on this axis appear. Only has an effect if `categoryorder` is set to "array". Used with `categoryorder`. categoryarraysrc Sets the source reference on plot.ly for categoryarray . categoryorder Specifies the ordering logic for the case of categorical variables. By default, plotly uses "trace", which specifies the order that is present in the data supplied. Set `categoryorder` to *category ascending* or *category descending* if order should be determined by the alphanumerical order of the category names. Set `categoryorder` to "array" to derive the ordering from the attribute `categoryarray`. If a category is not found in the `categoryarray` array, the sorting behavior for that attribute will be identical to the "trace" mode. The unspecified categories will follow the categories in `categoryarray`. cheatertype color Sets default for all colors associated with this axis all at once: line, font, tick, and grid colors. Grid color is lightened by blending this with the plot background Individual pieces can override this. dtick The stride between grid lines along the axis endline Determines whether or not a line is drawn at along the final value of this axis. If True, the end line is drawn on top of the grid lines. endlinecolor Sets the line color of the end line. endlinewidth Sets the width (in px) of the end line. exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. fixedrange Determines whether or not this axis is zoom-able. If true, then zoom is disabled. gridcolor Sets the axis line color. gridwidth Sets the width (in px) of the axis line. labelpadding Extra padding between label and the axis labelprefix Sets a axis label prefix. labelsuffix Sets a axis label suffix. linecolor Sets the axis line color. linewidth Sets the width (in px) of the axis line. minorgridcolor Sets the color of the grid lines. minorgridcount Sets the number of minor grid ticks per major grid tick minorgridwidth Sets the width (in px) of the grid lines. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". range Sets the range of this axis. If the axis `type` is "log", then you must take the log of your desired range (e.g. to set the range from 1 to 100, set the range from 0 to 2). If the axis `type` is "date", it should be date strings, like date data, though Date objects and unix milliseconds will be accepted and converted to strings. If the axis `type` is "category", it should be numbers, using the scale where each category is assigned a serial number from zero in the order it appears. rangemode If "normal", the range is computed in relation to the extrema of the input data. If *tozero*`, the range extends to 0, regardless of the input data If "nonnegative", the range is non-negative, regardless of the input data. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showgrid Determines whether or not grid lines are drawn. If True, the grid lines are drawn at every tick mark. showline Determines whether or not a line bounding this axis is drawn. showticklabels Determines whether axis labels are drawn on the low side, the high side, both, or neither side of the axis. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. smoothing startline Determines whether or not a line is drawn at along the starting value of this axis. If True, the start line is drawn on top of the grid lines. startlinecolor Sets the line color of the start line. startlinewidth Sets the width (in px) of the start line. tick0 The starting index of grid lines along the axis tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickfont Sets the tick font. tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.carpet.aaxis.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.carpet .aaxis.tickformatstopdefaults), sets the default property values to use for elements of carpet.aaxis.tickformatstops tickmode tickprefix Sets a tick label prefix. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . title plotly.graph_objects.carpet.aaxis.Title instance or dict with compatible properties titlefont Deprecated: Please use carpet.aaxis.title.font instead. Sets this axis' title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleoffset Deprecated: Please use carpet.aaxis.title.offset instead. An additional amount by which to offset the title from the tick labels, given in pixels. Note that this used to be set by the now deprecated `titleoffset` attribute. type Sets the axis type. By default, plotly attempts to determined the axis type by looking into the data of the traces that referenced the axis in question. Returns ------- Aaxis """ super(Aaxis, self).__init__("aaxis") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.carpet.Aaxis constructor must be a dict or an instance of plotly.graph_objs.carpet.Aaxis""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.carpet import aaxis as v_aaxis # Initialize validators # --------------------- self._validators["arraydtick"] = v_aaxis.ArraydtickValidator() self._validators["arraytick0"] = v_aaxis.Arraytick0Validator() self._validators["autorange"] = v_aaxis.AutorangeValidator() self._validators["categoryarray"] = v_aaxis.CategoryarrayValidator() self._validators["categoryarraysrc"] = v_aaxis.CategoryarraysrcValidator() self._validators["categoryorder"] = v_aaxis.CategoryorderValidator() self._validators["cheatertype"] = v_aaxis.CheatertypeValidator() self._validators["color"] = v_aaxis.ColorValidator() self._validators["dtick"] = v_aaxis.DtickValidator() self._validators["endline"] = v_aaxis.EndlineValidator() self._validators["endlinecolor"] = v_aaxis.EndlinecolorValidator() self._validators["endlinewidth"] = v_aaxis.EndlinewidthValidator() self._validators["exponentformat"] = v_aaxis.ExponentformatValidator() self._validators["fixedrange"] = v_aaxis.FixedrangeValidator() self._validators["gridcolor"] = v_aaxis.GridcolorValidator() self._validators["gridwidth"] = v_aaxis.GridwidthValidator() self._validators["labelpadding"] = v_aaxis.LabelpaddingValidator() self._validators["labelprefix"] = v_aaxis.LabelprefixValidator() self._validators["labelsuffix"] = v_aaxis.LabelsuffixValidator() self._validators["linecolor"] = v_aaxis.LinecolorValidator() self._validators["linewidth"] = v_aaxis.LinewidthValidator() self._validators["minorgridcolor"] = v_aaxis.MinorgridcolorValidator() self._validators["minorgridcount"] = v_aaxis.MinorgridcountValidator() self._validators["minorgridwidth"] = v_aaxis.MinorgridwidthValidator() self._validators["nticks"] = v_aaxis.NticksValidator() self._validators["range"] = v_aaxis.RangeValidator() self._validators["rangemode"] = v_aaxis.RangemodeValidator() self._validators["separatethousands"] = v_aaxis.SeparatethousandsValidator() self._validators["showexponent"] = v_aaxis.ShowexponentValidator() self._validators["showgrid"] = v_aaxis.ShowgridValidator() self._validators["showline"] = v_aaxis.ShowlineValidator() self._validators["showticklabels"] = v_aaxis.ShowticklabelsValidator() self._validators["showtickprefix"] = v_aaxis.ShowtickprefixValidator() self._validators["showticksuffix"] = v_aaxis.ShowticksuffixValidator() self._validators["smoothing"] = v_aaxis.SmoothingValidator() self._validators["startline"] = v_aaxis.StartlineValidator() self._validators["startlinecolor"] = v_aaxis.StartlinecolorValidator() self._validators["startlinewidth"] = v_aaxis.StartlinewidthValidator() self._validators["tick0"] = v_aaxis.Tick0Validator() self._validators["tickangle"] = v_aaxis.TickangleValidator() self._validators["tickfont"] = v_aaxis.TickfontValidator() self._validators["tickformat"] = v_aaxis.TickformatValidator() self._validators["tickformatstops"] = v_aaxis.TickformatstopsValidator() self._validators["tickformatstopdefaults"] = v_aaxis.TickformatstopValidator() self._validators["tickmode"] = v_aaxis.TickmodeValidator() self._validators["tickprefix"] = v_aaxis.TickprefixValidator() self._validators["ticksuffix"] = v_aaxis.TicksuffixValidator() self._validators["ticktext"] = v_aaxis.TicktextValidator() self._validators["ticktextsrc"] = v_aaxis.TicktextsrcValidator() self._validators["tickvals"] = v_aaxis.TickvalsValidator() self._validators["tickvalssrc"] = v_aaxis.TickvalssrcValidator() self._validators["title"] = v_aaxis.TitleValidator() self._validators["type"] = v_aaxis.TypeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("arraydtick", None) self["arraydtick"] = arraydtick if arraydtick is not None else _v _v = arg.pop("arraytick0", None) self["arraytick0"] = arraytick0 if arraytick0 is not None else _v _v = arg.pop("autorange", None) self["autorange"] = autorange if autorange is not None else _v _v = arg.pop("categoryarray", None) self["categoryarray"] = categoryarray if categoryarray is not None else _v _v = arg.pop("categoryarraysrc", None) self["categoryarraysrc"] = ( categoryarraysrc if categoryarraysrc is not None else _v ) _v = arg.pop("categoryorder", None) self["categoryorder"] = categoryorder if categoryorder is not None else _v _v = arg.pop("cheatertype", None) self["cheatertype"] = cheatertype if cheatertype is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("dtick", None) self["dtick"] = dtick if dtick is not None else _v _v = arg.pop("endline", None) self["endline"] = endline if endline is not None else _v _v = arg.pop("endlinecolor", None) self["endlinecolor"] = endlinecolor if endlinecolor is not None else _v _v = arg.pop("endlinewidth", None) self["endlinewidth"] = endlinewidth if endlinewidth is not None else _v _v = arg.pop("exponentformat", None) self["exponentformat"] = exponentformat if exponentformat is not None else _v _v = arg.pop("fixedrange", None) self["fixedrange"] = fixedrange if fixedrange is not None else _v _v = arg.pop("gridcolor", None) self["gridcolor"] = gridcolor if gridcolor is not None else _v _v = arg.pop("gridwidth", None) self["gridwidth"] = gridwidth if gridwidth is not None else _v _v = arg.pop("labelpadding", None) self["labelpadding"] = labelpadding if labelpadding is not None else _v _v = arg.pop("labelprefix", None) self["labelprefix"] = labelprefix if labelprefix is not None else _v _v = arg.pop("labelsuffix", None) self["labelsuffix"] = labelsuffix if labelsuffix is not None else _v _v = arg.pop("linecolor", None) self["linecolor"] = linecolor if linecolor is not None else _v _v = arg.pop("linewidth", None) self["linewidth"] = linewidth if linewidth is not None else _v _v = arg.pop("minorgridcolor", None) self["minorgridcolor"] = minorgridcolor if minorgridcolor is not None else _v _v = arg.pop("minorgridcount", None) self["minorgridcount"] = minorgridcount if minorgridcount is not None else _v _v = arg.pop("minorgridwidth", None) self["minorgridwidth"] = minorgridwidth if minorgridwidth is not None else _v _v = arg.pop("nticks", None) self["nticks"] = nticks if nticks is not None else _v _v = arg.pop("range", None) self["range"] = range if range is not None else _v _v = arg.pop("rangemode", None) self["rangemode"] = rangemode if rangemode is not None else _v _v = arg.pop("separatethousands", None) self["separatethousands"] = ( separatethousands if separatethousands is not None else _v ) _v = arg.pop("showexponent", None) self["showexponent"] = showexponent if showexponent is not None else _v _v = arg.pop("showgrid", None) self["showgrid"] = showgrid if showgrid is not None else _v _v = arg.pop("showline", None) self["showline"] = showline if showline is not None else _v _v = arg.pop("showticklabels", None) self["showticklabels"] = showticklabels if showticklabels is not None else _v _v = arg.pop("showtickprefix", None) self["showtickprefix"] = showtickprefix if showtickprefix is not None else _v _v = arg.pop("showticksuffix", None) self["showticksuffix"] = showticksuffix if showticksuffix is not None else _v _v = arg.pop("smoothing", None) self["smoothing"] = smoothing if smoothing is not None else _v _v = arg.pop("startline", None) self["startline"] = startline if startline is not None else _v _v = arg.pop("startlinecolor", None) self["startlinecolor"] = startlinecolor if startlinecolor is not None else _v _v = arg.pop("startlinewidth", None) self["startlinewidth"] = startlinewidth if startlinewidth is not None else _v _v = arg.pop("tick0", None) self["tick0"] = tick0 if tick0 is not None else _v _v = arg.pop("tickangle", None) self["tickangle"] = tickangle if tickangle is not None else _v _v = arg.pop("tickfont", None) self["tickfont"] = tickfont if tickfont is not None else _v _v = arg.pop("tickformat", None) self["tickformat"] = tickformat if tickformat is not None else _v _v = arg.pop("tickformatstops", None) self["tickformatstops"] = tickformatstops if tickformatstops is not None else _v _v = arg.pop("tickformatstopdefaults", None) self["tickformatstopdefaults"] = ( tickformatstopdefaults if tickformatstopdefaults is not None else _v ) _v = arg.pop("tickmode", None) self["tickmode"] = tickmode if tickmode is not None else _v _v = arg.pop("tickprefix", None) self["tickprefix"] = tickprefix if tickprefix is not None else _v _v = arg.pop("ticksuffix", None) self["ticksuffix"] = ticksuffix if ticksuffix is not None else _v _v = arg.pop("ticktext", None) self["ticktext"] = ticktext if ticktext is not None else _v _v = arg.pop("ticktextsrc", None) self["ticktextsrc"] = ticktextsrc if ticktextsrc is not None else _v _v = arg.pop("tickvals", None) self["tickvals"] = tickvals if tickvals is not None else _v _v = arg.pop("tickvalssrc", None) self["tickvalssrc"] = tickvalssrc if tickvalssrc is not None else _v _v = arg.pop("title", None) self["title"] = title if title is not None else _v _v = arg.pop("titlefont", None) _v = titlefont if titlefont is not None else _v if _v is not None: self["titlefont"] = _v _v = arg.pop("titleoffset", None) _v = titleoffset if titleoffset is not None else _v if _v is not None: self["titleoffset"] = _v _v = arg.pop("type", None) self["type"] = type if type is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Aaxis", "Baxis", "Font", "Stream", "aaxis", "baxis"] from plotly.graph_objs.carpet import baxis from plotly.graph_objs.carpet import aaxis plotly-4.4.1+dfsg.orig/plotly/graph_objs/carpet/aaxis/0000755000175000017500000000000013573746613022314 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/carpet/aaxis/title/0000755000175000017500000000000013573746613023435 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/carpet/aaxis/title/__init__.py0000644000175000017500000002047313573721545025551 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "carpet.aaxis.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets this axis' title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.carpet.aaxis.title.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.carpet.aaxis.title.Font constructor must be a dict or an instance of plotly.graph_objs.carpet.aaxis.title.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.carpet.aaxis.title import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/carpet/aaxis/__init__.py0000644000175000017500000006024013573721546024425 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Title(_BaseTraceHierarchyType): # font # ---- @property def font(self): """ Sets this axis' title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.carpet.aaxis.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.carpet.aaxis.title.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # offset # ------ @property def offset(self): """ An additional amount by which to offset the title from the tick labels, given in pixels. Note that this used to be set by the now deprecated `titleoffset` attribute. The 'offset' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["offset"] @offset.setter def offset(self, val): self["offset"] = val # text # ---- @property def text(self): """ Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "carpet.aaxis" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Sets this axis' title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. offset An additional amount by which to offset the title from the tick labels, given in pixels. Note that this used to be set by the now deprecated `titleoffset` attribute. text Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """ def __init__(self, arg=None, font=None, offset=None, text=None, **kwargs): """ Construct a new Title object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.carpet.aaxis.Title font Sets this axis' title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. offset An additional amount by which to offset the title from the tick labels, given in pixels. Note that this used to be set by the now deprecated `titleoffset` attribute. text Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- Title """ super(Title, self).__init__("title") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.carpet.aaxis.Title constructor must be a dict or an instance of plotly.graph_objs.carpet.aaxis.Title""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.carpet.aaxis import title as v_title # Initialize validators # --------------------- self._validators["font"] = v_title.FontValidator() self._validators["offset"] = v_title.OffsetValidator() self._validators["text"] = v_title.TextValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("offset", None) self["offset"] = offset if offset is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickformatstop(_BaseTraceHierarchyType): # dtickrange # ---------- @property def dtickrange(self): """ range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" The 'dtickrange' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'dtickrange[0]' property accepts values of any type (1) The 'dtickrange[1]' property accepts values of any type Returns ------- list """ return self["dtickrange"] @dtickrange.setter def dtickrange(self, val): self["dtickrange"] = val # enabled # ------- @property def enabled(self): """ Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. The 'enabled' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["enabled"] @enabled.setter def enabled(self, val): self["enabled"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # value # ----- @property def value(self): """ string - dtickformat for described zoom level, the same as "tickformat" The 'value' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "carpet.aaxis" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """ def __init__( self, arg=None, dtickrange=None, enabled=None, name=None, templateitemname=None, value=None, **kwargs ): """ Construct a new Tickformatstop object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.carpet.aaxis.Tickformatstop dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- Tickformatstop """ super(Tickformatstop, self).__init__("tickformatstops") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.carpet.aaxis.Tickformatstop constructor must be a dict or an instance of plotly.graph_objs.carpet.aaxis.Tickformatstop""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.carpet.aaxis import tickformatstop as v_tickformatstop # Initialize validators # --------------------- self._validators["dtickrange"] = v_tickformatstop.DtickrangeValidator() self._validators["enabled"] = v_tickformatstop.EnabledValidator() self._validators["name"] = v_tickformatstop.NameValidator() self._validators[ "templateitemname" ] = v_tickformatstop.TemplateitemnameValidator() self._validators["value"] = v_tickformatstop.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtickrange", None) self["dtickrange"] = dtickrange if dtickrange is not None else _v _v = arg.pop("enabled", None) self["enabled"] = enabled if enabled is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "carpet.aaxis" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Tickfont object Sets the tick font. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.carpet.aaxis.Tickfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Tickfont """ super(Tickfont, self).__init__("tickfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.carpet.aaxis.Tickfont constructor must be a dict or an instance of plotly.graph_objs.carpet.aaxis.Tickfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.carpet.aaxis import tickfont as v_tickfont # Initialize validators # --------------------- self._validators["color"] = v_tickfont.ColorValidator() self._validators["family"] = v_tickfont.FamilyValidator() self._validators["size"] = v_tickfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Tickfont", "Tickformatstop", "Tickformatstop", "Title", "title"] from plotly.graph_objs.carpet.aaxis import title plotly-4.4.1+dfsg.orig/plotly/graph_objs/carpet/baxis/0000755000175000017500000000000013573746613022315 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/carpet/baxis/title/0000755000175000017500000000000013573746613023436 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/carpet/baxis/title/__init__.py0000644000175000017500000002047313573721545025552 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "carpet.baxis.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets this axis' title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.carpet.baxis.title.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.carpet.baxis.title.Font constructor must be a dict or an instance of plotly.graph_objs.carpet.baxis.title.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.carpet.baxis.title import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/carpet/baxis/__init__.py0000644000175000017500000006024013573721546024426 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Title(_BaseTraceHierarchyType): # font # ---- @property def font(self): """ Sets this axis' title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.carpet.baxis.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.carpet.baxis.title.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # offset # ------ @property def offset(self): """ An additional amount by which to offset the title from the tick labels, given in pixels. Note that this used to be set by the now deprecated `titleoffset` attribute. The 'offset' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["offset"] @offset.setter def offset(self, val): self["offset"] = val # text # ---- @property def text(self): """ Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "carpet.baxis" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Sets this axis' title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. offset An additional amount by which to offset the title from the tick labels, given in pixels. Note that this used to be set by the now deprecated `titleoffset` attribute. text Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """ def __init__(self, arg=None, font=None, offset=None, text=None, **kwargs): """ Construct a new Title object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.carpet.baxis.Title font Sets this axis' title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. offset An additional amount by which to offset the title from the tick labels, given in pixels. Note that this used to be set by the now deprecated `titleoffset` attribute. text Sets the title of this axis. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- Title """ super(Title, self).__init__("title") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.carpet.baxis.Title constructor must be a dict or an instance of plotly.graph_objs.carpet.baxis.Title""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.carpet.baxis import title as v_title # Initialize validators # --------------------- self._validators["font"] = v_title.FontValidator() self._validators["offset"] = v_title.OffsetValidator() self._validators["text"] = v_title.TextValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("offset", None) self["offset"] = offset if offset is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickformatstop(_BaseTraceHierarchyType): # dtickrange # ---------- @property def dtickrange(self): """ range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" The 'dtickrange' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'dtickrange[0]' property accepts values of any type (1) The 'dtickrange[1]' property accepts values of any type Returns ------- list """ return self["dtickrange"] @dtickrange.setter def dtickrange(self, val): self["dtickrange"] = val # enabled # ------- @property def enabled(self): """ Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. The 'enabled' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["enabled"] @enabled.setter def enabled(self, val): self["enabled"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # value # ----- @property def value(self): """ string - dtickformat for described zoom level, the same as "tickformat" The 'value' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "carpet.baxis" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """ def __init__( self, arg=None, dtickrange=None, enabled=None, name=None, templateitemname=None, value=None, **kwargs ): """ Construct a new Tickformatstop object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.carpet.baxis.Tickformatstop dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- Tickformatstop """ super(Tickformatstop, self).__init__("tickformatstops") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.carpet.baxis.Tickformatstop constructor must be a dict or an instance of plotly.graph_objs.carpet.baxis.Tickformatstop""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.carpet.baxis import tickformatstop as v_tickformatstop # Initialize validators # --------------------- self._validators["dtickrange"] = v_tickformatstop.DtickrangeValidator() self._validators["enabled"] = v_tickformatstop.EnabledValidator() self._validators["name"] = v_tickformatstop.NameValidator() self._validators[ "templateitemname" ] = v_tickformatstop.TemplateitemnameValidator() self._validators["value"] = v_tickformatstop.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtickrange", None) self["dtickrange"] = dtickrange if dtickrange is not None else _v _v = arg.pop("enabled", None) self["enabled"] = enabled if enabled is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "carpet.baxis" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Tickfont object Sets the tick font. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.carpet.baxis.Tickfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Tickfont """ super(Tickfont, self).__init__("tickfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.carpet.baxis.Tickfont constructor must be a dict or an instance of plotly.graph_objs.carpet.baxis.Tickfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.carpet.baxis import tickfont as v_tickfont # Initialize validators # --------------------- self._validators["color"] = v_tickfont.ColorValidator() self._validators["family"] = v_tickfont.FamilyValidator() self._validators["size"] = v_tickfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Tickfont", "Tickformatstop", "Tickformatstop", "Title", "title"] from plotly.graph_objs.carpet.baxis import title plotly-4.4.1+dfsg.orig/plotly/graph_objs/splom/0000755000175000017500000000000013573746613021063 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/splom/unselected/0000755000175000017500000000000013573746613023216 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/splom/unselected/__init__.py0000644000175000017500000001544513573721552025333 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the marker color of unselected points, applied only when a selection exists. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # opacity # ------- @property def opacity(self): """ Sets the marker opacity of unselected points, applied only when a selection exists. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # size # ---- @property def size(self): """ Sets the marker size of unselected points, applied only when a selection exists. The 'size' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "splom.unselected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. size Sets the marker size of unselected points, applied only when a selection exists. """ def __init__(self, arg=None, color=None, opacity=None, size=None, **kwargs): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.splom.unselected.Marker color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. size Sets the marker size of unselected points, applied only when a selection exists. Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.splom.unselected.Marker constructor must be a dict or an instance of plotly.graph_objs.splom.unselected.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.splom.unselected import marker as v_marker # Initialize validators # --------------------- self._validators["color"] = v_marker.ColorValidator() self._validators["opacity"] = v_marker.OpacityValidator() self._validators["size"] = v_marker.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Marker"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/splom/hoverlabel/0000755000175000017500000000000013573746613023206 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/splom/hoverlabel/__init__.py0000644000175000017500000002541213573721552025316 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "splom.hoverlabel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Font object Sets the font used in hover labels. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.splom.hoverlabel.Font color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.splom.hoverlabel.Font constructor must be a dict or an instance of plotly.graph_objs.splom.hoverlabel.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.splom.hoverlabel import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["colorsrc"] = v_font.ColorsrcValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["familysrc"] = v_font.FamilysrcValidator() self._validators["size"] = v_font.SizeValidator() self._validators["sizesrc"] = v_font.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/splom/marker/0000755000175000017500000000000013573746613022344 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/splom/marker/colorbar/0000755000175000017500000000000013573746613024147 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/splom/marker/colorbar/title/0000755000175000017500000000000013573746613025270 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/splom/marker/colorbar/title/__init__.py0000644000175000017500000002055613573721552027404 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "splom.marker.colorbar.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.splom.marker.colorbar.title.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.splom.marker.colorbar.title.Font constructor must be a dict or an instance of plotly.graph_objs.splom.marker.colorbar.title.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.splom.marker.colorbar.title import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/splom/marker/colorbar/__init__.py0000644000175000017500000006071013573721552026257 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Title(_BaseTraceHierarchyType): # font # ---- @property def font(self): """ Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.splom.marker.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.splom.marker.colorbar.title.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # side # ---- @property def side(self): """ Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- Any """ return self["side"] @side.setter def side(self, val): self["side"] = val # text # ---- @property def text(self): """ Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "splom.marker.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """ def __init__(self, arg=None, font=None, side=None, text=None, **kwargs): """ Construct a new Title object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.splom.marker.colorbar.Title font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- Title """ super(Title, self).__init__("title") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.splom.marker.colorbar.Title constructor must be a dict or an instance of plotly.graph_objs.splom.marker.colorbar.Title""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.splom.marker.colorbar import title as v_title # Initialize validators # --------------------- self._validators["font"] = v_title.FontValidator() self._validators["side"] = v_title.SideValidator() self._validators["text"] = v_title.TextValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("side", None) self["side"] = side if side is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickformatstop(_BaseTraceHierarchyType): # dtickrange # ---------- @property def dtickrange(self): """ range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" The 'dtickrange' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'dtickrange[0]' property accepts values of any type (1) The 'dtickrange[1]' property accepts values of any type Returns ------- list """ return self["dtickrange"] @dtickrange.setter def dtickrange(self, val): self["dtickrange"] = val # enabled # ------- @property def enabled(self): """ Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. The 'enabled' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["enabled"] @enabled.setter def enabled(self, val): self["enabled"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # value # ----- @property def value(self): """ string - dtickformat for described zoom level, the same as "tickformat" The 'value' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "splom.marker.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """ def __init__( self, arg=None, dtickrange=None, enabled=None, name=None, templateitemname=None, value=None, **kwargs ): """ Construct a new Tickformatstop object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.splom.marker.colorbar.Tickformatstop dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- Tickformatstop """ super(Tickformatstop, self).__init__("tickformatstops") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.splom.marker.colorbar.Tickformatstop constructor must be a dict or an instance of plotly.graph_objs.splom.marker.colorbar.Tickformatstop""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.splom.marker.colorbar import ( tickformatstop as v_tickformatstop, ) # Initialize validators # --------------------- self._validators["dtickrange"] = v_tickformatstop.DtickrangeValidator() self._validators["enabled"] = v_tickformatstop.EnabledValidator() self._validators["name"] = v_tickformatstop.NameValidator() self._validators[ "templateitemname" ] = v_tickformatstop.TemplateitemnameValidator() self._validators["value"] = v_tickformatstop.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtickrange", None) self["dtickrange"] = dtickrange if dtickrange is not None else _v _v = arg.pop("enabled", None) self["enabled"] = enabled if enabled is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "splom.marker.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Tickfont object Sets the color bar's tick label font Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.splom.marker.colorbar.Tickfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Tickfont """ super(Tickfont, self).__init__("tickfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.splom.marker.colorbar.Tickfont constructor must be a dict or an instance of plotly.graph_objs.splom.marker.colorbar.Tickfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.splom.marker.colorbar import tickfont as v_tickfont # Initialize validators # --------------------- self._validators["color"] = v_tickfont.ColorValidator() self._validators["family"] = v_tickfont.FamilyValidator() self._validators["size"] = v_tickfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Tickfont", "Tickformatstop", "Tickformatstop", "Title", "title"] from plotly.graph_objs.splom.marker.colorbar import title plotly-4.4.1+dfsg.orig/plotly/graph_objs/splom/marker/__init__.py0000644000175000017500000027025013573721553024457 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # autocolorscale # -------------- @property def autocolorscale(self): """ Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. The 'autocolorscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocolorscale"] @autocolorscale.setter def autocolorscale(self, val): self["autocolorscale"] = val # cauto # ----- @property def cauto(self): """ Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. The 'cauto' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["cauto"] @cauto.setter def cauto(self, val): self["cauto"] = val # cmax # ---- @property def cmax(self): """ Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. The 'cmax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmax"] @cmax.setter def cmax(self, val): self["cmax"] = val # cmid # ---- @property def cmid(self): """ Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. The 'cmid' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmid"] @cmid.setter def cmid(self, val): self["cmid"] = val # cmin # ---- @property def cmin(self): """ Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. The 'cmin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmin"] @cmin.setter def cmin(self, val): self["cmin"] = val # color # ----- @property def color(self): """ Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A number that will be interpreted as a color according to splom.marker.line.colorscale - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # coloraxis # --------- @property def coloraxis(self): """ Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. The 'coloraxis' property is an identifier of a particular subplot, of type 'coloraxis', that may be specified as the string 'coloraxis' optionally followed by an integer >= 1 (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) Returns ------- str """ return self["coloraxis"] @coloraxis.setter def coloraxis(self, val): self["coloraxis"] = val # colorscale # ---------- @property def colorscale(self): """ Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Bl ues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,Earth,Electric,Vi ridis,Cividis. The 'colorscale' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # reversescale # ------------ @property def reversescale(self): """ Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. The 'reversescale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["reversescale"] @reversescale.setter def reversescale(self, val): self["reversescale"] = val # width # ----- @property def width(self): """ Sets the width (in px) of the lines bounding the marker points. The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["width"] @width.setter def width(self, val): self["width"] = val # widthsrc # -------- @property def widthsrc(self): """ Sets the source reference on plot.ly for width . The 'widthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["widthsrc"] @widthsrc.setter def widthsrc(self, val): self["widthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "splom.marker" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . """ def __init__( self, arg=None, autocolorscale=None, cauto=None, cmax=None, cmid=None, cmin=None, color=None, coloraxis=None, colorscale=None, colorsrc=None, reversescale=None, width=None, widthsrc=None, **kwargs ): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.splom.marker.Line autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrR d,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,H ot,Blackbody,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.splom.marker.Line constructor must be a dict or an instance of plotly.graph_objs.splom.marker.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.splom.marker import line as v_line # Initialize validators # --------------------- self._validators["autocolorscale"] = v_line.AutocolorscaleValidator() self._validators["cauto"] = v_line.CautoValidator() self._validators["cmax"] = v_line.CmaxValidator() self._validators["cmid"] = v_line.CmidValidator() self._validators["cmin"] = v_line.CminValidator() self._validators["color"] = v_line.ColorValidator() self._validators["coloraxis"] = v_line.ColoraxisValidator() self._validators["colorscale"] = v_line.ColorscaleValidator() self._validators["colorsrc"] = v_line.ColorsrcValidator() self._validators["reversescale"] = v_line.ReversescaleValidator() self._validators["width"] = v_line.WidthValidator() self._validators["widthsrc"] = v_line.WidthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autocolorscale", None) self["autocolorscale"] = autocolorscale if autocolorscale is not None else _v _v = arg.pop("cauto", None) self["cauto"] = cauto if cauto is not None else _v _v = arg.pop("cmax", None) self["cmax"] = cmax if cmax is not None else _v _v = arg.pop("cmid", None) self["cmid"] = cmid if cmid is not None else _v _v = arg.pop("cmin", None) self["cmin"] = cmin if cmin is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("coloraxis", None) self["coloraxis"] = coloraxis if coloraxis is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("reversescale", None) self["reversescale"] = reversescale if reversescale is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v _v = arg.pop("widthsrc", None) self["widthsrc"] = widthsrc if widthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class ColorBar(_BaseTraceHierarchyType): # bgcolor # ------- @property def bgcolor(self): """ Sets the color of padded area. The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the axis line color. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # borderwidth # ----------- @property def borderwidth(self): """ Sets the width (in px) or the border enclosing this color bar. The 'borderwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["borderwidth"] @borderwidth.setter def borderwidth(self, val): self["borderwidth"] = val # dtick # ----- @property def dtick(self): """ Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" The 'dtick' property accepts values of any type Returns ------- Any """ return self["dtick"] @dtick.setter def dtick(self, val): self["dtick"] = val # exponentformat # -------------- @property def exponentformat(self): """ Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. The 'exponentformat' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'e', 'E', 'power', 'SI', 'B'] Returns ------- Any """ return self["exponentformat"] @exponentformat.setter def exponentformat(self, val): self["exponentformat"] = val # len # --- @property def len(self): """ Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. The 'len' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["len"] @len.setter def len(self, val): self["len"] = val # lenmode # ------- @property def lenmode(self): """ Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. The 'lenmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["lenmode"] @lenmode.setter def lenmode(self, val): self["lenmode"] = val # nticks # ------ @property def nticks(self): """ Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". The 'nticks' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nticks"] @nticks.setter def nticks(self, val): self["nticks"] = val # outlinecolor # ------------ @property def outlinecolor(self): """ Sets the axis line color. The 'outlinecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["outlinecolor"] @outlinecolor.setter def outlinecolor(self, val): self["outlinecolor"] = val # outlinewidth # ------------ @property def outlinewidth(self): """ Sets the width (in px) of the axis line. The 'outlinewidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["outlinewidth"] @outlinewidth.setter def outlinewidth(self, val): self["outlinewidth"] = val # separatethousands # ----------------- @property def separatethousands(self): """ If "true", even 4-digit integers are separated The 'separatethousands' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["separatethousands"] @separatethousands.setter def separatethousands(self, val): self["separatethousands"] = val # showexponent # ------------ @property def showexponent(self): """ If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. The 'showexponent' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showexponent"] @showexponent.setter def showexponent(self, val): self["showexponent"] = val # showticklabels # -------------- @property def showticklabels(self): """ Determines whether or not the tick labels are drawn. The 'showticklabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showticklabels"] @showticklabels.setter def showticklabels(self, val): self["showticklabels"] = val # showtickprefix # -------------- @property def showtickprefix(self): """ If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. The 'showtickprefix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showtickprefix"] @showtickprefix.setter def showtickprefix(self, val): self["showtickprefix"] = val # showticksuffix # -------------- @property def showticksuffix(self): """ Same as `showtickprefix` but for tick suffixes. The 'showticksuffix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showticksuffix"] @showticksuffix.setter def showticksuffix(self, val): self["showticksuffix"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # thicknessmode # ------------- @property def thicknessmode(self): """ Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. The 'thicknessmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["thicknessmode"] @thicknessmode.setter def thicknessmode(self, val): self["thicknessmode"] = val # tick0 # ----- @property def tick0(self): """ Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. The 'tick0' property accepts values of any type Returns ------- Any """ return self["tick0"] @tick0.setter def tick0(self, val): self["tick0"] = val # tickangle # --------- @property def tickangle(self): """ Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. The 'tickangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["tickangle"] @tickangle.setter def tickangle(self, val): self["tickangle"] = val # tickcolor # --------- @property def tickcolor(self): """ Sets the tick color. The 'tickcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["tickcolor"] @tickcolor.setter def tickcolor(self, val): self["tickcolor"] = val # tickfont # -------- @property def tickfont(self): """ Sets the color bar's tick label font The 'tickfont' property is an instance of Tickfont that may be specified as: - An instance of plotly.graph_objs.splom.marker.colorbar.Tickfont - A dict of string/value properties that will be passed to the Tickfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.splom.marker.colorbar.Tickfont """ return self["tickfont"] @tickfont.setter def tickfont(self, val): self["tickfont"] = val # tickformat # ---------- @property def tickformat(self): """ Sets the tick label formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'tickformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickformat"] @tickformat.setter def tickformat(self, val): self["tickformat"] = val # tickformatstops # --------------- @property def tickformatstops(self): """ The 'tickformatstops' property is a tuple of instances of Tickformatstop that may be specified as: - A list or tuple of instances of plotly.graph_objs.splom.marker.colorbar.Tickformatstop - A list or tuple of dicts of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- tuple[plotly.graph_objs.splom.marker.colorbar.Tickformatstop] """ return self["tickformatstops"] @tickformatstops.setter def tickformatstops(self, val): self["tickformatstops"] = val # tickformatstopdefaults # ---------------------- @property def tickformatstopdefaults(self): """ When used in a template (as layout.template.data.splom.marker.c olorbar.tickformatstopdefaults), sets the default property values to use for elements of splom.marker.colorbar.tickformatstops The 'tickformatstopdefaults' property is an instance of Tickformatstop that may be specified as: - An instance of plotly.graph_objs.splom.marker.colorbar.Tickformatstop - A dict of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: Returns ------- plotly.graph_objs.splom.marker.colorbar.Tickformatstop """ return self["tickformatstopdefaults"] @tickformatstopdefaults.setter def tickformatstopdefaults(self, val): self["tickformatstopdefaults"] = val # ticklen # ------- @property def ticklen(self): """ Sets the tick length (in px). The 'ticklen' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ticklen"] @ticklen.setter def ticklen(self, val): self["ticklen"] = val # tickmode # -------- @property def tickmode(self): """ Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). The 'tickmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'linear', 'array'] Returns ------- Any """ return self["tickmode"] @tickmode.setter def tickmode(self, val): self["tickmode"] = val # tickprefix # ---------- @property def tickprefix(self): """ Sets a tick label prefix. The 'tickprefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickprefix"] @tickprefix.setter def tickprefix(self, val): self["tickprefix"] = val # ticks # ----- @property def ticks(self): """ Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. The 'ticks' property is an enumeration that may be specified as: - One of the following enumeration values: ['outside', 'inside', ''] Returns ------- Any """ return self["ticks"] @ticks.setter def ticks(self, val): self["ticks"] = val # ticksuffix # ---------- @property def ticksuffix(self): """ Sets a tick label suffix. The 'ticksuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ticksuffix"] @ticksuffix.setter def ticksuffix(self, val): self["ticksuffix"] = val # ticktext # -------- @property def ticktext(self): """ Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. The 'ticktext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ticktext"] @ticktext.setter def ticktext(self, val): self["ticktext"] = val # ticktextsrc # ----------- @property def ticktextsrc(self): """ Sets the source reference on plot.ly for ticktext . The 'ticktextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ticktextsrc"] @ticktextsrc.setter def ticktextsrc(self, val): self["ticktextsrc"] = val # tickvals # -------- @property def tickvals(self): """ Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. The 'tickvals' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["tickvals"] @tickvals.setter def tickvals(self, val): self["tickvals"] = val # tickvalssrc # ----------- @property def tickvalssrc(self): """ Sets the source reference on plot.ly for tickvals . The 'tickvalssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tickvalssrc"] @tickvalssrc.setter def tickvalssrc(self, val): self["tickvalssrc"] = val # tickwidth # --------- @property def tickwidth(self): """ Sets the tick width (in px). The 'tickwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["tickwidth"] @tickwidth.setter def tickwidth(self, val): self["tickwidth"] = val # title # ----- @property def title(self): """ The 'title' property is an instance of Title that may be specified as: - An instance of plotly.graph_objs.splom.marker.colorbar.Title - A dict of string/value properties that will be passed to the Title constructor Supported dict properties: font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- plotly.graph_objs.splom.marker.colorbar.Title """ return self["title"] @title.setter def title(self, val): self["title"] = val # titlefont # --------- @property def titlefont(self): """ Deprecated: Please use splom.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.splom.marker.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- """ return self["titlefont"] @titlefont.setter def titlefont(self, val): self["titlefont"] = val # titleside # --------- @property def titleside(self): """ Deprecated: Please use splom.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- """ return self["titleside"] @titleside.setter def titleside(self, val): self["titleside"] = val # x # - @property def x(self): """ Sets the x position of the color bar (in plot fraction). The 'x' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["x"] @x.setter def x(self, val): self["x"] = val # xanchor # ------- @property def xanchor(self): """ Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. The 'xanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'center', 'right'] Returns ------- Any """ return self["xanchor"] @xanchor.setter def xanchor(self, val): self["xanchor"] = val # xpad # ---- @property def xpad(self): """ Sets the amount of padding (in px) along the x direction. The 'xpad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["xpad"] @xpad.setter def xpad(self, val): self["xpad"] = val # y # - @property def y(self): """ Sets the y position of the color bar (in plot fraction). The 'y' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["y"] @y.setter def y(self, val): self["y"] = val # yanchor # ------- @property def yanchor(self): """ Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. The 'yanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['top', 'middle', 'bottom'] Returns ------- Any """ return self["yanchor"] @yanchor.setter def yanchor(self, val): self["yanchor"] = val # ypad # ---- @property def ypad(self): """ Sets the amount of padding (in px) along the y direction. The 'ypad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ypad"] @ypad.setter def ypad(self, val): self["ypad"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "splom.marker" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.splom.marker.colorbar.T ickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.splom. marker.colorbar.tickformatstopdefaults), sets the default property values to use for elements of splom.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.splom.marker.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use splom.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use splom.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """ _mapped_properties = { "titlefont": ("title", "font"), "titleside": ("title", "side"), } def __init__( self, arg=None, bgcolor=None, bordercolor=None, borderwidth=None, dtick=None, exponentformat=None, len=None, lenmode=None, nticks=None, outlinecolor=None, outlinewidth=None, separatethousands=None, showexponent=None, showticklabels=None, showtickprefix=None, showticksuffix=None, thickness=None, thicknessmode=None, tick0=None, tickangle=None, tickcolor=None, tickfont=None, tickformat=None, tickformatstops=None, tickformatstopdefaults=None, ticklen=None, tickmode=None, tickprefix=None, ticks=None, ticksuffix=None, ticktext=None, ticktextsrc=None, tickvals=None, tickvalssrc=None, tickwidth=None, title=None, titlefont=None, titleside=None, x=None, xanchor=None, xpad=None, y=None, yanchor=None, ypad=None, **kwargs ): """ Construct a new ColorBar object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.splom.marker.ColorBar bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.splom.marker.colorbar.T ickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.splom. marker.colorbar.tickformatstopdefaults), sets the default property values to use for elements of splom.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.splom.marker.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use splom.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use splom.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- ColorBar """ super(ColorBar, self).__init__("colorbar") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.splom.marker.ColorBar constructor must be a dict or an instance of plotly.graph_objs.splom.marker.ColorBar""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.splom.marker import colorbar as v_colorbar # Initialize validators # --------------------- self._validators["bgcolor"] = v_colorbar.BgcolorValidator() self._validators["bordercolor"] = v_colorbar.BordercolorValidator() self._validators["borderwidth"] = v_colorbar.BorderwidthValidator() self._validators["dtick"] = v_colorbar.DtickValidator() self._validators["exponentformat"] = v_colorbar.ExponentformatValidator() self._validators["len"] = v_colorbar.LenValidator() self._validators["lenmode"] = v_colorbar.LenmodeValidator() self._validators["nticks"] = v_colorbar.NticksValidator() self._validators["outlinecolor"] = v_colorbar.OutlinecolorValidator() self._validators["outlinewidth"] = v_colorbar.OutlinewidthValidator() self._validators["separatethousands"] = v_colorbar.SeparatethousandsValidator() self._validators["showexponent"] = v_colorbar.ShowexponentValidator() self._validators["showticklabels"] = v_colorbar.ShowticklabelsValidator() self._validators["showtickprefix"] = v_colorbar.ShowtickprefixValidator() self._validators["showticksuffix"] = v_colorbar.ShowticksuffixValidator() self._validators["thickness"] = v_colorbar.ThicknessValidator() self._validators["thicknessmode"] = v_colorbar.ThicknessmodeValidator() self._validators["tick0"] = v_colorbar.Tick0Validator() self._validators["tickangle"] = v_colorbar.TickangleValidator() self._validators["tickcolor"] = v_colorbar.TickcolorValidator() self._validators["tickfont"] = v_colorbar.TickfontValidator() self._validators["tickformat"] = v_colorbar.TickformatValidator() self._validators["tickformatstops"] = v_colorbar.TickformatstopsValidator() self._validators[ "tickformatstopdefaults" ] = v_colorbar.TickformatstopValidator() self._validators["ticklen"] = v_colorbar.TicklenValidator() self._validators["tickmode"] = v_colorbar.TickmodeValidator() self._validators["tickprefix"] = v_colorbar.TickprefixValidator() self._validators["ticks"] = v_colorbar.TicksValidator() self._validators["ticksuffix"] = v_colorbar.TicksuffixValidator() self._validators["ticktext"] = v_colorbar.TicktextValidator() self._validators["ticktextsrc"] = v_colorbar.TicktextsrcValidator() self._validators["tickvals"] = v_colorbar.TickvalsValidator() self._validators["tickvalssrc"] = v_colorbar.TickvalssrcValidator() self._validators["tickwidth"] = v_colorbar.TickwidthValidator() self._validators["title"] = v_colorbar.TitleValidator() self._validators["x"] = v_colorbar.XValidator() self._validators["xanchor"] = v_colorbar.XanchorValidator() self._validators["xpad"] = v_colorbar.XpadValidator() self._validators["y"] = v_colorbar.YValidator() self._validators["yanchor"] = v_colorbar.YanchorValidator() self._validators["ypad"] = v_colorbar.YpadValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("borderwidth", None) self["borderwidth"] = borderwidth if borderwidth is not None else _v _v = arg.pop("dtick", None) self["dtick"] = dtick if dtick is not None else _v _v = arg.pop("exponentformat", None) self["exponentformat"] = exponentformat if exponentformat is not None else _v _v = arg.pop("len", None) self["len"] = len if len is not None else _v _v = arg.pop("lenmode", None) self["lenmode"] = lenmode if lenmode is not None else _v _v = arg.pop("nticks", None) self["nticks"] = nticks if nticks is not None else _v _v = arg.pop("outlinecolor", None) self["outlinecolor"] = outlinecolor if outlinecolor is not None else _v _v = arg.pop("outlinewidth", None) self["outlinewidth"] = outlinewidth if outlinewidth is not None else _v _v = arg.pop("separatethousands", None) self["separatethousands"] = ( separatethousands if separatethousands is not None else _v ) _v = arg.pop("showexponent", None) self["showexponent"] = showexponent if showexponent is not None else _v _v = arg.pop("showticklabels", None) self["showticklabels"] = showticklabels if showticklabels is not None else _v _v = arg.pop("showtickprefix", None) self["showtickprefix"] = showtickprefix if showtickprefix is not None else _v _v = arg.pop("showticksuffix", None) self["showticksuffix"] = showticksuffix if showticksuffix is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("thicknessmode", None) self["thicknessmode"] = thicknessmode if thicknessmode is not None else _v _v = arg.pop("tick0", None) self["tick0"] = tick0 if tick0 is not None else _v _v = arg.pop("tickangle", None) self["tickangle"] = tickangle if tickangle is not None else _v _v = arg.pop("tickcolor", None) self["tickcolor"] = tickcolor if tickcolor is not None else _v _v = arg.pop("tickfont", None) self["tickfont"] = tickfont if tickfont is not None else _v _v = arg.pop("tickformat", None) self["tickformat"] = tickformat if tickformat is not None else _v _v = arg.pop("tickformatstops", None) self["tickformatstops"] = tickformatstops if tickformatstops is not None else _v _v = arg.pop("tickformatstopdefaults", None) self["tickformatstopdefaults"] = ( tickformatstopdefaults if tickformatstopdefaults is not None else _v ) _v = arg.pop("ticklen", None) self["ticklen"] = ticklen if ticklen is not None else _v _v = arg.pop("tickmode", None) self["tickmode"] = tickmode if tickmode is not None else _v _v = arg.pop("tickprefix", None) self["tickprefix"] = tickprefix if tickprefix is not None else _v _v = arg.pop("ticks", None) self["ticks"] = ticks if ticks is not None else _v _v = arg.pop("ticksuffix", None) self["ticksuffix"] = ticksuffix if ticksuffix is not None else _v _v = arg.pop("ticktext", None) self["ticktext"] = ticktext if ticktext is not None else _v _v = arg.pop("ticktextsrc", None) self["ticktextsrc"] = ticktextsrc if ticktextsrc is not None else _v _v = arg.pop("tickvals", None) self["tickvals"] = tickvals if tickvals is not None else _v _v = arg.pop("tickvalssrc", None) self["tickvalssrc"] = tickvalssrc if tickvalssrc is not None else _v _v = arg.pop("tickwidth", None) self["tickwidth"] = tickwidth if tickwidth is not None else _v _v = arg.pop("title", None) self["title"] = title if title is not None else _v _v = arg.pop("titlefont", None) _v = titlefont if titlefont is not None else _v if _v is not None: self["titlefont"] = _v _v = arg.pop("titleside", None) _v = titleside if titleside is not None else _v if _v is not None: self["titleside"] = _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xanchor", None) self["xanchor"] = xanchor if xanchor is not None else _v _v = arg.pop("xpad", None) self["xpad"] = xpad if xpad is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("yanchor", None) self["yanchor"] = yanchor if yanchor is not None else _v _v = arg.pop("ypad", None) self["ypad"] = ypad if ypad is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["ColorBar", "Line", "colorbar"] from plotly.graph_objs.splom.marker import colorbar plotly-4.4.1+dfsg.orig/plotly/graph_objs/splom/__init__.py0000644000175000017500000027627213573721553023210 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Unselected(_BaseTraceHierarchyType): # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.splom.unselected.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. size Sets the marker size of unselected points, applied only when a selection exists. Returns ------- plotly.graph_objs.splom.unselected.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "splom" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ marker plotly.graph_objects.splom.unselected.Marker instance or dict with compatible properties """ def __init__(self, arg=None, marker=None, **kwargs): """ Construct a new Unselected object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.splom.Unselected marker plotly.graph_objects.splom.unselected.Marker instance or dict with compatible properties Returns ------- Unselected """ super(Unselected, self).__init__("unselected") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.splom.Unselected constructor must be a dict or an instance of plotly.graph_objs.splom.Unselected""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.splom import unselected as v_unselected # Initialize validators # --------------------- self._validators["marker"] = v_unselected.MarkerValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Stream(_BaseTraceHierarchyType): # maxpoints # --------- @property def maxpoints(self): """ Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. The 'maxpoints' property is a number and may be specified as: - An int or float in the interval [0, 10000] Returns ------- int|float """ return self["maxpoints"] @maxpoints.setter def maxpoints(self, val): self["maxpoints"] = val # token # ----- @property def token(self): """ The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. The 'token' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["token"] @token.setter def token(self, val): self["token"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "splom" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """ def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): """ Construct a new Stream object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.splom.Stream maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- Stream """ super(Stream, self).__init__("stream") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.splom.Stream constructor must be a dict or an instance of plotly.graph_objs.splom.Stream""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.splom import stream as v_stream # Initialize validators # --------------------- self._validators["maxpoints"] = v_stream.MaxpointsValidator() self._validators["token"] = v_stream.TokenValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("maxpoints", None) self["maxpoints"] = maxpoints if maxpoints is not None else _v _v = arg.pop("token", None) self["token"] = token if token is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Selected(_BaseTraceHierarchyType): # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.splom.selected.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. size Sets the marker size of selected points. Returns ------- plotly.graph_objs.splom.selected.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "splom" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ marker plotly.graph_objects.splom.selected.Marker instance or dict with compatible properties """ def __init__(self, arg=None, marker=None, **kwargs): """ Construct a new Selected object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.splom.Selected marker plotly.graph_objects.splom.selected.Marker instance or dict with compatible properties Returns ------- Selected """ super(Selected, self).__init__("selected") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.splom.Selected constructor must be a dict or an instance of plotly.graph_objs.splom.Selected""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.splom import selected as v_selected # Initialize validators # --------------------- self._validators["marker"] = v_selected.MarkerValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # autocolorscale # -------------- @property def autocolorscale(self): """ Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. The 'autocolorscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocolorscale"] @autocolorscale.setter def autocolorscale(self, val): self["autocolorscale"] = val # cauto # ----- @property def cauto(self): """ Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. The 'cauto' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["cauto"] @cauto.setter def cauto(self, val): self["cauto"] = val # cmax # ---- @property def cmax(self): """ Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. The 'cmax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmax"] @cmax.setter def cmax(self, val): self["cmax"] = val # cmid # ---- @property def cmid(self): """ Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. The 'cmid' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmid"] @cmid.setter def cmid(self, val): self["cmid"] = val # cmin # ---- @property def cmin(self): """ Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. The 'cmin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmin"] @cmin.setter def cmin(self, val): self["cmin"] = val # color # ----- @property def color(self): """ Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A number that will be interpreted as a color according to splom.marker.colorscale - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # coloraxis # --------- @property def coloraxis(self): """ Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. The 'coloraxis' property is an identifier of a particular subplot, of type 'coloraxis', that may be specified as the string 'coloraxis' optionally followed by an integer >= 1 (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) Returns ------- str """ return self["coloraxis"] @coloraxis.setter def coloraxis(self, val): self["coloraxis"] = val # colorbar # -------- @property def colorbar(self): """ The 'colorbar' property is an instance of ColorBar that may be specified as: - An instance of plotly.graph_objs.splom.marker.ColorBar - A dict of string/value properties that will be passed to the ColorBar constructor Supported dict properties: bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.splom.marker.co lorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.splom.marker.colorbar.tickformatstopdefaults) , sets the default property values to use for elements of splom.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.splom.marker.colorbar.Titl e instance or dict with compatible properties titlefont Deprecated: Please use splom.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use splom.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- plotly.graph_objs.splom.marker.ColorBar """ return self["colorbar"] @colorbar.setter def colorbar(self, val): self["colorbar"] = val # colorscale # ---------- @property def colorscale(self): """ Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnB u,Greens,YlOrRd,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland ,Jet,Hot,Blackbody,Earth,Electric,Viridis,Cividis. The 'colorscale' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.splom.marker.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,R eds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Black body,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . Returns ------- plotly.graph_objs.splom.marker.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # opacity # ------- @property def opacity(self): """ Sets the marker opacity. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # opacitysrc # ---------- @property def opacitysrc(self): """ Sets the source reference on plot.ly for opacity . The 'opacitysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["opacitysrc"] @opacitysrc.setter def opacitysrc(self, val): self["opacitysrc"] = val # reversescale # ------------ @property def reversescale(self): """ Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. The 'reversescale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["reversescale"] @reversescale.setter def reversescale(self, val): self["reversescale"] = val # showscale # --------- @property def showscale(self): """ Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. The 'showscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showscale"] @showscale.setter def showscale(self, val): self["showscale"] = val # size # ---- @property def size(self): """ Sets the marker size (in px). The 'size' property is a number and may be specified as: - An int or float in the interval [0, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizemin # ------- @property def sizemin(self): """ Has an effect only if `marker.size` is set to a numerical array. Sets the minimum size (in px) of the rendered marker points. The 'sizemin' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["sizemin"] @sizemin.setter def sizemin(self, val): self["sizemin"] = val # sizemode # -------- @property def sizemode(self): """ Has an effect only if `marker.size` is set to a numerical array. Sets the rule for which the data in `size` is converted to pixels. The 'sizemode' property is an enumeration that may be specified as: - One of the following enumeration values: ['diameter', 'area'] Returns ------- Any """ return self["sizemode"] @sizemode.setter def sizemode(self, val): self["sizemode"] = val # sizeref # ------- @property def sizeref(self): """ Has an effect only if `marker.size` is set to a numerical array. Sets the scale factor used to determine the rendered size of marker points. Use with `sizemin` and `sizemode`. The 'sizeref' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["sizeref"] @sizeref.setter def sizeref(self, val): self["sizeref"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # symbol # ------ @property def symbol(self): """ Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot-open" to a symbol name. The 'symbol' property is an enumeration that may be specified as: - One of the following enumeration values: [0, 'circle', 100, 'circle-open', 200, 'circle-dot', 300, 'circle-open-dot', 1, 'square', 101, 'square-open', 201, 'square-dot', 301, 'square-open-dot', 2, 'diamond', 102, 'diamond-open', 202, 'diamond-dot', 302, 'diamond-open-dot', 3, 'cross', 103, 'cross-open', 203, 'cross-dot', 303, 'cross-open-dot', 4, 'x', 104, 'x-open', 204, 'x-dot', 304, 'x-open-dot', 5, 'triangle-up', 105, 'triangle-up-open', 205, 'triangle-up-dot', 305, 'triangle-up-open-dot', 6, 'triangle-down', 106, 'triangle-down-open', 206, 'triangle-down-dot', 306, 'triangle-down-open-dot', 7, 'triangle-left', 107, 'triangle-left-open', 207, 'triangle-left-dot', 307, 'triangle-left-open-dot', 8, 'triangle-right', 108, 'triangle-right-open', 208, 'triangle-right-dot', 308, 'triangle-right-open-dot', 9, 'triangle-ne', 109, 'triangle-ne-open', 209, 'triangle-ne-dot', 309, 'triangle-ne-open-dot', 10, 'triangle-se', 110, 'triangle-se-open', 210, 'triangle-se-dot', 310, 'triangle-se-open-dot', 11, 'triangle-sw', 111, 'triangle-sw-open', 211, 'triangle-sw-dot', 311, 'triangle-sw-open-dot', 12, 'triangle-nw', 112, 'triangle-nw-open', 212, 'triangle-nw-dot', 312, 'triangle-nw-open-dot', 13, 'pentagon', 113, 'pentagon-open', 213, 'pentagon-dot', 313, 'pentagon-open-dot', 14, 'hexagon', 114, 'hexagon-open', 214, 'hexagon-dot', 314, 'hexagon-open-dot', 15, 'hexagon2', 115, 'hexagon2-open', 215, 'hexagon2-dot', 315, 'hexagon2-open-dot', 16, 'octagon', 116, 'octagon-open', 216, 'octagon-dot', 316, 'octagon-open-dot', 17, 'star', 117, 'star-open', 217, 'star-dot', 317, 'star-open-dot', 18, 'hexagram', 118, 'hexagram-open', 218, 'hexagram-dot', 318, 'hexagram-open-dot', 19, 'star-triangle-up', 119, 'star-triangle-up-open', 219, 'star-triangle-up-dot', 319, 'star-triangle-up-open-dot', 20, 'star-triangle-down', 120, 'star-triangle-down-open', 220, 'star-triangle-down-dot', 320, 'star-triangle-down-open-dot', 21, 'star-square', 121, 'star-square-open', 221, 'star-square-dot', 321, 'star-square-open-dot', 22, 'star-diamond', 122, 'star-diamond-open', 222, 'star-diamond-dot', 322, 'star-diamond-open-dot', 23, 'diamond-tall', 123, 'diamond-tall-open', 223, 'diamond-tall-dot', 323, 'diamond-tall-open-dot', 24, 'diamond-wide', 124, 'diamond-wide-open', 224, 'diamond-wide-dot', 324, 'diamond-wide-open-dot', 25, 'hourglass', 125, 'hourglass-open', 26, 'bowtie', 126, 'bowtie-open', 27, 'circle-cross', 127, 'circle-cross-open', 28, 'circle-x', 128, 'circle-x-open', 29, 'square-cross', 129, 'square-cross-open', 30, 'square-x', 130, 'square-x-open', 31, 'diamond-cross', 131, 'diamond-cross-open', 32, 'diamond-x', 132, 'diamond-x-open', 33, 'cross-thin', 133, 'cross-thin-open', 34, 'x-thin', 134, 'x-thin-open', 35, 'asterisk', 135, 'asterisk-open', 36, 'hash', 136, 'hash-open', 236, 'hash-dot', 336, 'hash-open-dot', 37, 'y-up', 137, 'y-up-open', 38, 'y-down', 138, 'y-down-open', 39, 'y-left', 139, 'y-left-open', 40, 'y-right', 140, 'y-right-open', 41, 'line-ew', 141, 'line-ew-open', 42, 'line-ns', 142, 'line-ns-open', 43, 'line-ne', 143, 'line-ne-open', 44, 'line-nw', 144, 'line-nw-open'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["symbol"] @symbol.setter def symbol(self, val): self["symbol"] = val # symbolsrc # --------- @property def symbolsrc(self): """ Sets the source reference on plot.ly for symbol . The 'symbolsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["symbolsrc"] @symbolsrc.setter def symbolsrc(self, val): self["symbolsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "splom" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.splom.marker.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu ,Reds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . line plotly.graph_objects.splom.marker.Line instance or dict with compatible properties opacity Sets the marker opacity. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. size Sets the marker size (in px). sizemin Has an effect only if `marker.size` is set to a numerical array. Sets the minimum size (in px) of the rendered marker points. sizemode Has an effect only if `marker.size` is set to a numerical array. Sets the rule for which the data in `size` is converted to pixels. sizeref Has an effect only if `marker.size` is set to a numerical array. Sets the scale factor used to determine the rendered size of marker points. Use with `sizemin` and `sizemode`. sizesrc Sets the source reference on plot.ly for size . symbol Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot- open" to a symbol name. symbolsrc Sets the source reference on plot.ly for symbol . """ def __init__( self, arg=None, autocolorscale=None, cauto=None, cmax=None, cmid=None, cmin=None, color=None, coloraxis=None, colorbar=None, colorscale=None, colorsrc=None, line=None, opacity=None, opacitysrc=None, reversescale=None, showscale=None, size=None, sizemin=None, sizemode=None, sizeref=None, sizesrc=None, symbol=None, symbolsrc=None, **kwargs ): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.splom.Marker autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.splom.marker.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu ,Reds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . line plotly.graph_objects.splom.marker.Line instance or dict with compatible properties opacity Sets the marker opacity. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. size Sets the marker size (in px). sizemin Has an effect only if `marker.size` is set to a numerical array. Sets the minimum size (in px) of the rendered marker points. sizemode Has an effect only if `marker.size` is set to a numerical array. Sets the rule for which the data in `size` is converted to pixels. sizeref Has an effect only if `marker.size` is set to a numerical array. Sets the scale factor used to determine the rendered size of marker points. Use with `sizemin` and `sizemode`. sizesrc Sets the source reference on plot.ly for size . symbol Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot- open" to a symbol name. symbolsrc Sets the source reference on plot.ly for symbol . Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.splom.Marker constructor must be a dict or an instance of plotly.graph_objs.splom.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.splom import marker as v_marker # Initialize validators # --------------------- self._validators["autocolorscale"] = v_marker.AutocolorscaleValidator() self._validators["cauto"] = v_marker.CautoValidator() self._validators["cmax"] = v_marker.CmaxValidator() self._validators["cmid"] = v_marker.CmidValidator() self._validators["cmin"] = v_marker.CminValidator() self._validators["color"] = v_marker.ColorValidator() self._validators["coloraxis"] = v_marker.ColoraxisValidator() self._validators["colorbar"] = v_marker.ColorBarValidator() self._validators["colorscale"] = v_marker.ColorscaleValidator() self._validators["colorsrc"] = v_marker.ColorsrcValidator() self._validators["line"] = v_marker.LineValidator() self._validators["opacity"] = v_marker.OpacityValidator() self._validators["opacitysrc"] = v_marker.OpacitysrcValidator() self._validators["reversescale"] = v_marker.ReversescaleValidator() self._validators["showscale"] = v_marker.ShowscaleValidator() self._validators["size"] = v_marker.SizeValidator() self._validators["sizemin"] = v_marker.SizeminValidator() self._validators["sizemode"] = v_marker.SizemodeValidator() self._validators["sizeref"] = v_marker.SizerefValidator() self._validators["sizesrc"] = v_marker.SizesrcValidator() self._validators["symbol"] = v_marker.SymbolValidator() self._validators["symbolsrc"] = v_marker.SymbolsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autocolorscale", None) self["autocolorscale"] = autocolorscale if autocolorscale is not None else _v _v = arg.pop("cauto", None) self["cauto"] = cauto if cauto is not None else _v _v = arg.pop("cmax", None) self["cmax"] = cmax if cmax is not None else _v _v = arg.pop("cmid", None) self["cmid"] = cmid if cmid is not None else _v _v = arg.pop("cmin", None) self["cmin"] = cmin if cmin is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("coloraxis", None) self["coloraxis"] = coloraxis if coloraxis is not None else _v _v = arg.pop("colorbar", None) self["colorbar"] = colorbar if colorbar is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("opacitysrc", None) self["opacitysrc"] = opacitysrc if opacitysrc is not None else _v _v = arg.pop("reversescale", None) self["reversescale"] = reversescale if reversescale is not None else _v _v = arg.pop("showscale", None) self["showscale"] = showscale if showscale is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizemin", None) self["sizemin"] = sizemin if sizemin is not None else _v _v = arg.pop("sizemode", None) self["sizemode"] = sizemode if sizemode is not None else _v _v = arg.pop("sizeref", None) self["sizeref"] = sizeref if sizeref is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v _v = arg.pop("symbol", None) self["symbol"] = symbol if symbol is not None else _v _v = arg.pop("symbolsrc", None) self["symbolsrc"] = symbolsrc if symbolsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Hoverlabel(_BaseTraceHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'right', 'auto'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["align"] @align.setter def align(self, val): self["align"] = val # alignsrc # -------- @property def alignsrc(self): """ Sets the source reference on plot.ly for align . The 'alignsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["alignsrc"] @alignsrc.setter def alignsrc(self, val): self["alignsrc"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the hover labels for this trace The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bgcolorsrc # ---------- @property def bgcolorsrc(self): """ Sets the source reference on plot.ly for bgcolor . The 'bgcolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bgcolorsrc"] @bgcolorsrc.setter def bgcolorsrc(self, val): self["bgcolorsrc"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the border color of the hover labels for this trace. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # bordercolorsrc # -------------- @property def bordercolorsrc(self): """ Sets the source reference on plot.ly for bordercolor . The 'bordercolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bordercolorsrc"] @bordercolorsrc.setter def bordercolorsrc(self, val): self["bordercolorsrc"] = val # font # ---- @property def font(self): """ Sets the font used in hover labels. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.splom.hoverlabel.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.splom.hoverlabel.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # namelength # ---------- @property def namelength(self): """ Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. The 'namelength' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [-1, 9223372036854775807] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|numpy.ndarray """ return self["namelength"] @namelength.setter def namelength(self, val): self["namelength"] = val # namelengthsrc # ------------- @property def namelengthsrc(self): """ Sets the source reference on plot.ly for namelength . The 'namelengthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["namelengthsrc"] @namelengthsrc.setter def namelengthsrc(self, val): self["namelengthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "splom" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """ def __init__( self, arg=None, align=None, alignsrc=None, bgcolor=None, bgcolorsrc=None, bordercolor=None, bordercolorsrc=None, font=None, namelength=None, namelengthsrc=None, **kwargs ): """ Construct a new Hoverlabel object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.splom.Hoverlabel align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- Hoverlabel """ super(Hoverlabel, self).__init__("hoverlabel") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.splom.Hoverlabel constructor must be a dict or an instance of plotly.graph_objs.splom.Hoverlabel""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.splom import hoverlabel as v_hoverlabel # Initialize validators # --------------------- self._validators["align"] = v_hoverlabel.AlignValidator() self._validators["alignsrc"] = v_hoverlabel.AlignsrcValidator() self._validators["bgcolor"] = v_hoverlabel.BgcolorValidator() self._validators["bgcolorsrc"] = v_hoverlabel.BgcolorsrcValidator() self._validators["bordercolor"] = v_hoverlabel.BordercolorValidator() self._validators["bordercolorsrc"] = v_hoverlabel.BordercolorsrcValidator() self._validators["font"] = v_hoverlabel.FontValidator() self._validators["namelength"] = v_hoverlabel.NamelengthValidator() self._validators["namelengthsrc"] = v_hoverlabel.NamelengthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("alignsrc", None) self["alignsrc"] = alignsrc if alignsrc is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bgcolorsrc", None) self["bgcolorsrc"] = bgcolorsrc if bgcolorsrc is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("bordercolorsrc", None) self["bordercolorsrc"] = bordercolorsrc if bordercolorsrc is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("namelength", None) self["namelength"] = namelength if namelength is not None else _v _v = arg.pop("namelengthsrc", None) self["namelengthsrc"] = namelengthsrc if namelengthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Dimension(_BaseTraceHierarchyType): # axis # ---- @property def axis(self): """ The 'axis' property is an instance of Axis that may be specified as: - An instance of plotly.graph_objs.splom.dimension.Axis - A dict of string/value properties that will be passed to the Axis constructor Supported dict properties: matches Determines whether or not the x & y axes generated by this dimension match. Equivalent to setting the `matches` axis attribute in the layout with the correct axis id. type Sets the axis type for this dimension's generated x and y axes. Note that the axis `type` values set in layout take precedence over this attribute. Returns ------- plotly.graph_objs.splom.dimension.Axis """ return self["axis"] @axis.setter def axis(self, val): self["axis"] = val # label # ----- @property def label(self): """ Sets the label corresponding to this splom dimension. The 'label' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["label"] @label.setter def label(self, val): self["label"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # values # ------ @property def values(self): """ Sets the dimension values to be plotted. The 'values' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["values"] @values.setter def values(self, val): self["values"] = val # valuessrc # --------- @property def valuessrc(self): """ Sets the source reference on plot.ly for values . The 'valuessrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["valuessrc"] @valuessrc.setter def valuessrc(self, val): self["valuessrc"] = val # visible # ------- @property def visible(self): """ Determines whether or not this dimension is shown on the graph. Note that even visible false dimension contribute to the default grid generate by this splom trace. The 'visible' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "splom" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ axis plotly.graph_objects.splom.dimension.Axis instance or dict with compatible properties label Sets the label corresponding to this splom dimension. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. values Sets the dimension values to be plotted. valuessrc Sets the source reference on plot.ly for values . visible Determines whether or not this dimension is shown on the graph. Note that even visible false dimension contribute to the default grid generate by this splom trace. """ def __init__( self, arg=None, axis=None, label=None, name=None, templateitemname=None, values=None, valuessrc=None, visible=None, **kwargs ): """ Construct a new Dimension object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.splom.Dimension axis plotly.graph_objects.splom.dimension.Axis instance or dict with compatible properties label Sets the label corresponding to this splom dimension. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. values Sets the dimension values to be plotted. valuessrc Sets the source reference on plot.ly for values . visible Determines whether or not this dimension is shown on the graph. Note that even visible false dimension contribute to the default grid generate by this splom trace. Returns ------- Dimension """ super(Dimension, self).__init__("dimensions") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.splom.Dimension constructor must be a dict or an instance of plotly.graph_objs.splom.Dimension""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.splom import dimension as v_dimension # Initialize validators # --------------------- self._validators["axis"] = v_dimension.AxisValidator() self._validators["label"] = v_dimension.LabelValidator() self._validators["name"] = v_dimension.NameValidator() self._validators["templateitemname"] = v_dimension.TemplateitemnameValidator() self._validators["values"] = v_dimension.ValuesValidator() self._validators["valuessrc"] = v_dimension.ValuessrcValidator() self._validators["visible"] = v_dimension.VisibleValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("axis", None) self["axis"] = axis if axis is not None else _v _v = arg.pop("label", None) self["label"] = label if label is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("values", None) self["values"] = values if values is not None else _v _v = arg.pop("valuessrc", None) self["valuessrc"] = valuessrc if valuessrc is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Diagonal(_BaseTraceHierarchyType): # visible # ------- @property def visible(self): """ Determines whether or not subplots on the diagonal are displayed. The 'visible' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "splom" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ visible Determines whether or not subplots on the diagonal are displayed. """ def __init__(self, arg=None, visible=None, **kwargs): """ Construct a new Diagonal object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.splom.Diagonal visible Determines whether or not subplots on the diagonal are displayed. Returns ------- Diagonal """ super(Diagonal, self).__init__("diagonal") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.splom.Diagonal constructor must be a dict or an instance of plotly.graph_objs.splom.Diagonal""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.splom import diagonal as v_diagonal # Initialize validators # --------------------- self._validators["visible"] = v_diagonal.VisibleValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = [ "Diagonal", "Dimension", "Dimension", "Hoverlabel", "Marker", "Selected", "Stream", "Unselected", "dimension", "hoverlabel", "marker", "selected", "unselected", ] from plotly.graph_objs.splom import unselected from plotly.graph_objs.splom import selected from plotly.graph_objs.splom import marker from plotly.graph_objs.splom import hoverlabel from plotly.graph_objs.splom import dimension plotly-4.4.1+dfsg.orig/plotly/graph_objs/splom/dimension/0000755000175000017500000000000013573746613023050 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/splom/dimension/__init__.py0000644000175000017500000001022213573721552025151 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Axis(_BaseTraceHierarchyType): # matches # ------- @property def matches(self): """ Determines whether or not the x & y axes generated by this dimension match. Equivalent to setting the `matches` axis attribute in the layout with the correct axis id. The 'matches' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["matches"] @matches.setter def matches(self, val): self["matches"] = val # type # ---- @property def type(self): """ Sets the axis type for this dimension's generated x and y axes. Note that the axis `type` values set in layout take precedence over this attribute. The 'type' property is an enumeration that may be specified as: - One of the following enumeration values: ['linear', 'log', 'date', 'category'] Returns ------- Any """ return self["type"] @type.setter def type(self, val): self["type"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "splom.dimension" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ matches Determines whether or not the x & y axes generated by this dimension match. Equivalent to setting the `matches` axis attribute in the layout with the correct axis id. type Sets the axis type for this dimension's generated x and y axes. Note that the axis `type` values set in layout take precedence over this attribute. """ def __init__(self, arg=None, matches=None, type=None, **kwargs): """ Construct a new Axis object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.splom.dimension.Axis matches Determines whether or not the x & y axes generated by this dimension match. Equivalent to setting the `matches` axis attribute in the layout with the correct axis id. type Sets the axis type for this dimension's generated x and y axes. Note that the axis `type` values set in layout take precedence over this attribute. Returns ------- Axis """ super(Axis, self).__init__("axis") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.splom.dimension.Axis constructor must be a dict or an instance of plotly.graph_objs.splom.dimension.Axis""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.splom.dimension import axis as v_axis # Initialize validators # --------------------- self._validators["matches"] = v_axis.MatchesValidator() self._validators["type"] = v_axis.TypeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("matches", None) self["matches"] = matches if matches is not None else _v _v = arg.pop("type", None) self["type"] = type if type is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Axis"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/splom/selected/0000755000175000017500000000000013573746613022653 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/splom/selected/__init__.py0000644000175000017500000001450713573721552024766 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the marker color of selected points. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # opacity # ------- @property def opacity(self): """ Sets the marker opacity of selected points. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # size # ---- @property def size(self): """ Sets the marker size of selected points. The 'size' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "splom.selected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. size Sets the marker size of selected points. """ def __init__(self, arg=None, color=None, opacity=None, size=None, **kwargs): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.splom.selected.Marker color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. size Sets the marker size of selected points. Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.splom.selected.Marker constructor must be a dict or an instance of plotly.graph_objs.splom.selected.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.splom.selected import marker as v_marker # Initialize validators # --------------------- self._validators["color"] = v_marker.ColorValidator() self._validators["opacity"] = v_marker.OpacityValidator() self._validators["size"] = v_marker.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Marker"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/table/0000755000175000017500000000000013573746613021020 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/table/hoverlabel/0000755000175000017500000000000013573746613023143 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/table/hoverlabel/__init__.py0000644000175000017500000002541213573721552025253 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "table.hoverlabel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Font object Sets the font used in hover labels. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.table.hoverlabel.Font color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.table.hoverlabel.Font constructor must be a dict or an instance of plotly.graph_objs.table.hoverlabel.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.table.hoverlabel import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["colorsrc"] = v_font.ColorsrcValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["familysrc"] = v_font.FamilysrcValidator() self._validators["size"] = v_font.SizeValidator() self._validators["sizesrc"] = v_font.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/table/__init__.py0000644000175000017500000017146013573721553023136 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Stream(_BaseTraceHierarchyType): # maxpoints # --------- @property def maxpoints(self): """ Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. The 'maxpoints' property is a number and may be specified as: - An int or float in the interval [0, 10000] Returns ------- int|float """ return self["maxpoints"] @maxpoints.setter def maxpoints(self, val): self["maxpoints"] = val # token # ----- @property def token(self): """ The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. The 'token' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["token"] @token.setter def token(self, val): self["token"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "table" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """ def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): """ Construct a new Stream object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.table.Stream maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- Stream """ super(Stream, self).__init__("stream") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.table.Stream constructor must be a dict or an instance of plotly.graph_objs.table.Stream""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.table import stream as v_stream # Initialize validators # --------------------- self._validators["maxpoints"] = v_stream.MaxpointsValidator() self._validators["token"] = v_stream.TokenValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("maxpoints", None) self["maxpoints"] = maxpoints if maxpoints is not None else _v _v = arg.pop("token", None) self["token"] = token if token is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Hoverlabel(_BaseTraceHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'right', 'auto'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["align"] @align.setter def align(self, val): self["align"] = val # alignsrc # -------- @property def alignsrc(self): """ Sets the source reference on plot.ly for align . The 'alignsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["alignsrc"] @alignsrc.setter def alignsrc(self, val): self["alignsrc"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the hover labels for this trace The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bgcolorsrc # ---------- @property def bgcolorsrc(self): """ Sets the source reference on plot.ly for bgcolor . The 'bgcolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bgcolorsrc"] @bgcolorsrc.setter def bgcolorsrc(self, val): self["bgcolorsrc"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the border color of the hover labels for this trace. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # bordercolorsrc # -------------- @property def bordercolorsrc(self): """ Sets the source reference on plot.ly for bordercolor . The 'bordercolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bordercolorsrc"] @bordercolorsrc.setter def bordercolorsrc(self, val): self["bordercolorsrc"] = val # font # ---- @property def font(self): """ Sets the font used in hover labels. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.table.hoverlabel.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.table.hoverlabel.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # namelength # ---------- @property def namelength(self): """ Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. The 'namelength' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [-1, 9223372036854775807] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|numpy.ndarray """ return self["namelength"] @namelength.setter def namelength(self, val): self["namelength"] = val # namelengthsrc # ------------- @property def namelengthsrc(self): """ Sets the source reference on plot.ly for namelength . The 'namelengthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["namelengthsrc"] @namelengthsrc.setter def namelengthsrc(self, val): self["namelengthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "table" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """ def __init__( self, arg=None, align=None, alignsrc=None, bgcolor=None, bgcolorsrc=None, bordercolor=None, bordercolorsrc=None, font=None, namelength=None, namelengthsrc=None, **kwargs ): """ Construct a new Hoverlabel object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.table.Hoverlabel align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- Hoverlabel """ super(Hoverlabel, self).__init__("hoverlabel") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.table.Hoverlabel constructor must be a dict or an instance of plotly.graph_objs.table.Hoverlabel""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.table import hoverlabel as v_hoverlabel # Initialize validators # --------------------- self._validators["align"] = v_hoverlabel.AlignValidator() self._validators["alignsrc"] = v_hoverlabel.AlignsrcValidator() self._validators["bgcolor"] = v_hoverlabel.BgcolorValidator() self._validators["bgcolorsrc"] = v_hoverlabel.BgcolorsrcValidator() self._validators["bordercolor"] = v_hoverlabel.BordercolorValidator() self._validators["bordercolorsrc"] = v_hoverlabel.BordercolorsrcValidator() self._validators["font"] = v_hoverlabel.FontValidator() self._validators["namelength"] = v_hoverlabel.NamelengthValidator() self._validators["namelengthsrc"] = v_hoverlabel.NamelengthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("alignsrc", None) self["alignsrc"] = alignsrc if alignsrc is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bgcolorsrc", None) self["bgcolorsrc"] = bgcolorsrc if bgcolorsrc is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("bordercolorsrc", None) self["bordercolorsrc"] = bordercolorsrc if bordercolorsrc is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("namelength", None) self["namelength"] = namelength if namelength is not None else _v _v = arg.pop("namelengthsrc", None) self["namelengthsrc"] = namelengthsrc if namelengthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Header(_BaseTraceHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the `text` within the box. Has an effect only if `text` spans more two or more lines (i.e. `text` contains one or more
HTML tags) or if an explicit width is set to override the text width. The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'center', 'right'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["align"] @align.setter def align(self, val): self["align"] = val # alignsrc # -------- @property def alignsrc(self): """ Sets the source reference on plot.ly for align . The 'alignsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["alignsrc"] @alignsrc.setter def alignsrc(self, val): self["alignsrc"] = val # fill # ---- @property def fill(self): """ The 'fill' property is an instance of Fill that may be specified as: - An instance of plotly.graph_objs.table.header.Fill - A dict of string/value properties that will be passed to the Fill constructor Supported dict properties: color Sets the cell fill color. It accepts either a specific color or an array of colors or a 2D array of colors. colorsrc Sets the source reference on plot.ly for color . Returns ------- plotly.graph_objs.table.header.Fill """ return self["fill"] @fill.setter def fill(self, val): self["fill"] = val # font # ---- @property def font(self): """ The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.table.header.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.table.header.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # format # ------ @property def format(self): """ Sets the cell value formatting rule using d3 formatting mini- language which is similar to those of Python. See https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format The 'format' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["format"] @format.setter def format(self, val): self["format"] = val # formatsrc # --------- @property def formatsrc(self): """ Sets the source reference on plot.ly for format . The 'formatsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["formatsrc"] @formatsrc.setter def formatsrc(self, val): self["formatsrc"] = val # height # ------ @property def height(self): """ The height of cells. The 'height' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["height"] @height.setter def height(self, val): self["height"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.table.header.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . width widthsrc Sets the source reference on plot.ly for width . Returns ------- plotly.graph_objs.table.header.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # prefix # ------ @property def prefix(self): """ Prefix for cell values. The 'prefix' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["prefix"] @prefix.setter def prefix(self, val): self["prefix"] = val # prefixsrc # --------- @property def prefixsrc(self): """ Sets the source reference on plot.ly for prefix . The 'prefixsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["prefixsrc"] @prefixsrc.setter def prefixsrc(self, val): self["prefixsrc"] = val # suffix # ------ @property def suffix(self): """ Suffix for cell values. The 'suffix' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["suffix"] @suffix.setter def suffix(self, val): self["suffix"] = val # suffixsrc # --------- @property def suffixsrc(self): """ Sets the source reference on plot.ly for suffix . The 'suffixsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["suffixsrc"] @suffixsrc.setter def suffixsrc(self, val): self["suffixsrc"] = val # values # ------ @property def values(self): """ Header cell values. `values[m][n]` represents the value of the `n`th point in column `m`, therefore the `values[m]` vector length for all columns must be the same (longer vectors will be truncated). Each value must be a finite number or a string. The 'values' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["values"] @values.setter def values(self, val): self["values"] = val # valuessrc # --------- @property def valuessrc(self): """ Sets the source reference on plot.ly for values . The 'valuessrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["valuessrc"] @valuessrc.setter def valuessrc(self, val): self["valuessrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "table" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the `text` within the box. Has an effect only if `text` spans more two or more lines (i.e. `text` contains one or more
HTML tags) or if an explicit width is set to override the text width. alignsrc Sets the source reference on plot.ly for align . fill plotly.graph_objects.table.header.Fill instance or dict with compatible properties font plotly.graph_objects.table.header.Font instance or dict with compatible properties format Sets the cell value formatting rule using d3 formatting mini-language which is similar to those of Python. See https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format formatsrc Sets the source reference on plot.ly for format . height The height of cells. line plotly.graph_objects.table.header.Line instance or dict with compatible properties prefix Prefix for cell values. prefixsrc Sets the source reference on plot.ly for prefix . suffix Suffix for cell values. suffixsrc Sets the source reference on plot.ly for suffix . values Header cell values. `values[m][n]` represents the value of the `n`th point in column `m`, therefore the `values[m]` vector length for all columns must be the same (longer vectors will be truncated). Each value must be a finite number or a string. valuessrc Sets the source reference on plot.ly for values . """ def __init__( self, arg=None, align=None, alignsrc=None, fill=None, font=None, format=None, formatsrc=None, height=None, line=None, prefix=None, prefixsrc=None, suffix=None, suffixsrc=None, values=None, valuessrc=None, **kwargs ): """ Construct a new Header object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.table.Header align Sets the horizontal alignment of the `text` within the box. Has an effect only if `text` spans more two or more lines (i.e. `text` contains one or more
HTML tags) or if an explicit width is set to override the text width. alignsrc Sets the source reference on plot.ly for align . fill plotly.graph_objects.table.header.Fill instance or dict with compatible properties font plotly.graph_objects.table.header.Font instance or dict with compatible properties format Sets the cell value formatting rule using d3 formatting mini-language which is similar to those of Python. See https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format formatsrc Sets the source reference on plot.ly for format . height The height of cells. line plotly.graph_objects.table.header.Line instance or dict with compatible properties prefix Prefix for cell values. prefixsrc Sets the source reference on plot.ly for prefix . suffix Suffix for cell values. suffixsrc Sets the source reference on plot.ly for suffix . values Header cell values. `values[m][n]` represents the value of the `n`th point in column `m`, therefore the `values[m]` vector length for all columns must be the same (longer vectors will be truncated). Each value must be a finite number or a string. valuessrc Sets the source reference on plot.ly for values . Returns ------- Header """ super(Header, self).__init__("header") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.table.Header constructor must be a dict or an instance of plotly.graph_objs.table.Header""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.table import header as v_header # Initialize validators # --------------------- self._validators["align"] = v_header.AlignValidator() self._validators["alignsrc"] = v_header.AlignsrcValidator() self._validators["fill"] = v_header.FillValidator() self._validators["font"] = v_header.FontValidator() self._validators["format"] = v_header.FormatValidator() self._validators["formatsrc"] = v_header.FormatsrcValidator() self._validators["height"] = v_header.HeightValidator() self._validators["line"] = v_header.LineValidator() self._validators["prefix"] = v_header.PrefixValidator() self._validators["prefixsrc"] = v_header.PrefixsrcValidator() self._validators["suffix"] = v_header.SuffixValidator() self._validators["suffixsrc"] = v_header.SuffixsrcValidator() self._validators["values"] = v_header.ValuesValidator() self._validators["valuessrc"] = v_header.ValuessrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("alignsrc", None) self["alignsrc"] = alignsrc if alignsrc is not None else _v _v = arg.pop("fill", None) self["fill"] = fill if fill is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("format", None) self["format"] = format if format is not None else _v _v = arg.pop("formatsrc", None) self["formatsrc"] = formatsrc if formatsrc is not None else _v _v = arg.pop("height", None) self["height"] = height if height is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v _v = arg.pop("prefix", None) self["prefix"] = prefix if prefix is not None else _v _v = arg.pop("prefixsrc", None) self["prefixsrc"] = prefixsrc if prefixsrc is not None else _v _v = arg.pop("suffix", None) self["suffix"] = suffix if suffix is not None else _v _v = arg.pop("suffixsrc", None) self["suffixsrc"] = suffixsrc if suffixsrc is not None else _v _v = arg.pop("values", None) self["values"] = values if values is not None else _v _v = arg.pop("valuessrc", None) self["valuessrc"] = valuessrc if valuessrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Domain(_BaseTraceHierarchyType): # column # ------ @property def column(self): """ If there is a layout grid, use the domain for this column in the grid for this table trace . The 'column' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["column"] @column.setter def column(self, val): self["column"] = val # row # --- @property def row(self): """ If there is a layout grid, use the domain for this row in the grid for this table trace . The 'row' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["row"] @row.setter def row(self, val): self["row"] = val # x # - @property def x(self): """ Sets the horizontal domain of this table trace (in plot fraction). The 'x' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'x[0]' property is a number and may be specified as: - An int or float in the interval [0, 1] (1) The 'x[1]' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- list """ return self["x"] @x.setter def x(self, val): self["x"] = val # y # - @property def y(self): """ Sets the vertical domain of this table trace (in plot fraction). The 'y' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'y[0]' property is a number and may be specified as: - An int or float in the interval [0, 1] (1) The 'y[1]' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- list """ return self["y"] @y.setter def y(self, val): self["y"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "table" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ column If there is a layout grid, use the domain for this column in the grid for this table trace . row If there is a layout grid, use the domain for this row in the grid for this table trace . x Sets the horizontal domain of this table trace (in plot fraction). y Sets the vertical domain of this table trace (in plot fraction). """ def __init__(self, arg=None, column=None, row=None, x=None, y=None, **kwargs): """ Construct a new Domain object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.table.Domain column If there is a layout grid, use the domain for this column in the grid for this table trace . row If there is a layout grid, use the domain for this row in the grid for this table trace . x Sets the horizontal domain of this table trace (in plot fraction). y Sets the vertical domain of this table trace (in plot fraction). Returns ------- Domain """ super(Domain, self).__init__("domain") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.table.Domain constructor must be a dict or an instance of plotly.graph_objs.table.Domain""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.table import domain as v_domain # Initialize validators # --------------------- self._validators["column"] = v_domain.ColumnValidator() self._validators["row"] = v_domain.RowValidator() self._validators["x"] = v_domain.XValidator() self._validators["y"] = v_domain.YValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("column", None) self["column"] = column if column is not None else _v _v = arg.pop("row", None) self["row"] = row if row is not None else _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Cells(_BaseTraceHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the `text` within the box. Has an effect only if `text` spans more two or more lines (i.e. `text` contains one or more
HTML tags) or if an explicit width is set to override the text width. The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'center', 'right'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["align"] @align.setter def align(self, val): self["align"] = val # alignsrc # -------- @property def alignsrc(self): """ Sets the source reference on plot.ly for align . The 'alignsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["alignsrc"] @alignsrc.setter def alignsrc(self, val): self["alignsrc"] = val # fill # ---- @property def fill(self): """ The 'fill' property is an instance of Fill that may be specified as: - An instance of plotly.graph_objs.table.cells.Fill - A dict of string/value properties that will be passed to the Fill constructor Supported dict properties: color Sets the cell fill color. It accepts either a specific color or an array of colors or a 2D array of colors. colorsrc Sets the source reference on plot.ly for color . Returns ------- plotly.graph_objs.table.cells.Fill """ return self["fill"] @fill.setter def fill(self, val): self["fill"] = val # font # ---- @property def font(self): """ The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.table.cells.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.table.cells.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # format # ------ @property def format(self): """ Sets the cell value formatting rule using d3 formatting mini- language which is similar to those of Python. See https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format The 'format' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["format"] @format.setter def format(self, val): self["format"] = val # formatsrc # --------- @property def formatsrc(self): """ Sets the source reference on plot.ly for format . The 'formatsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["formatsrc"] @formatsrc.setter def formatsrc(self, val): self["formatsrc"] = val # height # ------ @property def height(self): """ The height of cells. The 'height' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["height"] @height.setter def height(self, val): self["height"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.table.cells.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . width widthsrc Sets the source reference on plot.ly for width . Returns ------- plotly.graph_objs.table.cells.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # prefix # ------ @property def prefix(self): """ Prefix for cell values. The 'prefix' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["prefix"] @prefix.setter def prefix(self, val): self["prefix"] = val # prefixsrc # --------- @property def prefixsrc(self): """ Sets the source reference on plot.ly for prefix . The 'prefixsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["prefixsrc"] @prefixsrc.setter def prefixsrc(self, val): self["prefixsrc"] = val # suffix # ------ @property def suffix(self): """ Suffix for cell values. The 'suffix' property is a string and must be specified as: - A string - A number that will be converted to a string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["suffix"] @suffix.setter def suffix(self, val): self["suffix"] = val # suffixsrc # --------- @property def suffixsrc(self): """ Sets the source reference on plot.ly for suffix . The 'suffixsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["suffixsrc"] @suffixsrc.setter def suffixsrc(self, val): self["suffixsrc"] = val # values # ------ @property def values(self): """ Cell values. `values[m][n]` represents the value of the `n`th point in column `m`, therefore the `values[m]` vector length for all columns must be the same (longer vectors will be truncated). Each value must be a finite number or a string. The 'values' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["values"] @values.setter def values(self, val): self["values"] = val # valuessrc # --------- @property def valuessrc(self): """ Sets the source reference on plot.ly for values . The 'valuessrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["valuessrc"] @valuessrc.setter def valuessrc(self, val): self["valuessrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "table" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the `text` within the box. Has an effect only if `text` spans more two or more lines (i.e. `text` contains one or more
HTML tags) or if an explicit width is set to override the text width. alignsrc Sets the source reference on plot.ly for align . fill plotly.graph_objects.table.cells.Fill instance or dict with compatible properties font plotly.graph_objects.table.cells.Font instance or dict with compatible properties format Sets the cell value formatting rule using d3 formatting mini-language which is similar to those of Python. See https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format formatsrc Sets the source reference on plot.ly for format . height The height of cells. line plotly.graph_objects.table.cells.Line instance or dict with compatible properties prefix Prefix for cell values. prefixsrc Sets the source reference on plot.ly for prefix . suffix Suffix for cell values. suffixsrc Sets the source reference on plot.ly for suffix . values Cell values. `values[m][n]` represents the value of the `n`th point in column `m`, therefore the `values[m]` vector length for all columns must be the same (longer vectors will be truncated). Each value must be a finite number or a string. valuessrc Sets the source reference on plot.ly for values . """ def __init__( self, arg=None, align=None, alignsrc=None, fill=None, font=None, format=None, formatsrc=None, height=None, line=None, prefix=None, prefixsrc=None, suffix=None, suffixsrc=None, values=None, valuessrc=None, **kwargs ): """ Construct a new Cells object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.table.Cells align Sets the horizontal alignment of the `text` within the box. Has an effect only if `text` spans more two or more lines (i.e. `text` contains one or more
HTML tags) or if an explicit width is set to override the text width. alignsrc Sets the source reference on plot.ly for align . fill plotly.graph_objects.table.cells.Fill instance or dict with compatible properties font plotly.graph_objects.table.cells.Font instance or dict with compatible properties format Sets the cell value formatting rule using d3 formatting mini-language which is similar to those of Python. See https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format formatsrc Sets the source reference on plot.ly for format . height The height of cells. line plotly.graph_objects.table.cells.Line instance or dict with compatible properties prefix Prefix for cell values. prefixsrc Sets the source reference on plot.ly for prefix . suffix Suffix for cell values. suffixsrc Sets the source reference on plot.ly for suffix . values Cell values. `values[m][n]` represents the value of the `n`th point in column `m`, therefore the `values[m]` vector length for all columns must be the same (longer vectors will be truncated). Each value must be a finite number or a string. valuessrc Sets the source reference on plot.ly for values . Returns ------- Cells """ super(Cells, self).__init__("cells") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.table.Cells constructor must be a dict or an instance of plotly.graph_objs.table.Cells""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.table import cells as v_cells # Initialize validators # --------------------- self._validators["align"] = v_cells.AlignValidator() self._validators["alignsrc"] = v_cells.AlignsrcValidator() self._validators["fill"] = v_cells.FillValidator() self._validators["font"] = v_cells.FontValidator() self._validators["format"] = v_cells.FormatValidator() self._validators["formatsrc"] = v_cells.FormatsrcValidator() self._validators["height"] = v_cells.HeightValidator() self._validators["line"] = v_cells.LineValidator() self._validators["prefix"] = v_cells.PrefixValidator() self._validators["prefixsrc"] = v_cells.PrefixsrcValidator() self._validators["suffix"] = v_cells.SuffixValidator() self._validators["suffixsrc"] = v_cells.SuffixsrcValidator() self._validators["values"] = v_cells.ValuesValidator() self._validators["valuessrc"] = v_cells.ValuessrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("alignsrc", None) self["alignsrc"] = alignsrc if alignsrc is not None else _v _v = arg.pop("fill", None) self["fill"] = fill if fill is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("format", None) self["format"] = format if format is not None else _v _v = arg.pop("formatsrc", None) self["formatsrc"] = formatsrc if formatsrc is not None else _v _v = arg.pop("height", None) self["height"] = height if height is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v _v = arg.pop("prefix", None) self["prefix"] = prefix if prefix is not None else _v _v = arg.pop("prefixsrc", None) self["prefixsrc"] = prefixsrc if prefixsrc is not None else _v _v = arg.pop("suffix", None) self["suffix"] = suffix if suffix is not None else _v _v = arg.pop("suffixsrc", None) self["suffixsrc"] = suffixsrc if suffixsrc is not None else _v _v = arg.pop("values", None) self["values"] = values if values is not None else _v _v = arg.pop("valuessrc", None) self["valuessrc"] = valuessrc if valuessrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = [ "Cells", "Domain", "Header", "Hoverlabel", "Stream", "cells", "header", "hoverlabel", ] from plotly.graph_objs.table import hoverlabel from plotly.graph_objs.table import header from plotly.graph_objs.table import cells plotly-4.4.1+dfsg.orig/plotly/graph_objs/table/cells/0000755000175000017500000000000013573746613022122 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/table/cells/__init__.py0000644000175000017500000005672413573721552024244 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # width # ----- @property def width(self): """ The 'width' property is a number and may be specified as: - An int or float - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["width"] @width.setter def width(self, val): self["width"] = val # widthsrc # -------- @property def widthsrc(self): """ Sets the source reference on plot.ly for width . The 'widthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["widthsrc"] @widthsrc.setter def widthsrc(self, val): self["widthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "table.cells" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . width widthsrc Sets the source reference on plot.ly for width . """ def __init__( self, arg=None, color=None, colorsrc=None, width=None, widthsrc=None, **kwargs ): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.table.cells.Line color colorsrc Sets the source reference on plot.ly for color . width widthsrc Sets the source reference on plot.ly for width . Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.table.cells.Line constructor must be a dict or an instance of plotly.graph_objs.table.cells.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.table.cells import line as v_line # Initialize validators # --------------------- self._validators["color"] = v_line.ColorValidator() self._validators["colorsrc"] = v_line.ColorsrcValidator() self._validators["width"] = v_line.WidthValidator() self._validators["widthsrc"] = v_line.WidthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v _v = arg.pop("widthsrc", None) self["widthsrc"] = widthsrc if widthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "table.cells" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Font object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.table.cells.Font color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.table.cells.Font constructor must be a dict or an instance of plotly.graph_objs.table.cells.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.table.cells import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["colorsrc"] = v_font.ColorsrcValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["familysrc"] = v_font.FamilysrcValidator() self._validators["size"] = v_font.SizeValidator() self._validators["sizesrc"] = v_font.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Fill(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the cell fill color. It accepts either a specific color or an array of colors or a 2D array of colors. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "table.cells" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the cell fill color. It accepts either a specific color or an array of colors or a 2D array of colors. colorsrc Sets the source reference on plot.ly for color . """ def __init__(self, arg=None, color=None, colorsrc=None, **kwargs): """ Construct a new Fill object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.table.cells.Fill color Sets the cell fill color. It accepts either a specific color or an array of colors or a 2D array of colors. colorsrc Sets the source reference on plot.ly for color . Returns ------- Fill """ super(Fill, self).__init__("fill") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.table.cells.Fill constructor must be a dict or an instance of plotly.graph_objs.table.cells.Fill""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.table.cells import fill as v_fill # Initialize validators # --------------------- self._validators["color"] = v_fill.ColorValidator() self._validators["colorsrc"] = v_fill.ColorsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Fill", "Font", "Line"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/table/header/0000755000175000017500000000000013573746613022250 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/table/header/__init__.py0000644000175000017500000005674313573721552024373 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # width # ----- @property def width(self): """ The 'width' property is a number and may be specified as: - An int or float - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["width"] @width.setter def width(self, val): self["width"] = val # widthsrc # -------- @property def widthsrc(self): """ Sets the source reference on plot.ly for width . The 'widthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["widthsrc"] @widthsrc.setter def widthsrc(self, val): self["widthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "table.header" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . width widthsrc Sets the source reference on plot.ly for width . """ def __init__( self, arg=None, color=None, colorsrc=None, width=None, widthsrc=None, **kwargs ): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.table.header.Line color colorsrc Sets the source reference on plot.ly for color . width widthsrc Sets the source reference on plot.ly for width . Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.table.header.Line constructor must be a dict or an instance of plotly.graph_objs.table.header.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.table.header import line as v_line # Initialize validators # --------------------- self._validators["color"] = v_line.ColorValidator() self._validators["colorsrc"] = v_line.ColorsrcValidator() self._validators["width"] = v_line.WidthValidator() self._validators["widthsrc"] = v_line.WidthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v _v = arg.pop("widthsrc", None) self["widthsrc"] = widthsrc if widthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "table.header" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Font object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.table.header.Font color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.table.header.Font constructor must be a dict or an instance of plotly.graph_objs.table.header.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.table.header import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["colorsrc"] = v_font.ColorsrcValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["familysrc"] = v_font.FamilysrcValidator() self._validators["size"] = v_font.SizeValidator() self._validators["sizesrc"] = v_font.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Fill(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the cell fill color. It accepts either a specific color or an array of colors or a 2D array of colors. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "table.header" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the cell fill color. It accepts either a specific color or an array of colors or a 2D array of colors. colorsrc Sets the source reference on plot.ly for color . """ def __init__(self, arg=None, color=None, colorsrc=None, **kwargs): """ Construct a new Fill object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.table.header.Fill color Sets the cell fill color. It accepts either a specific color or an array of colors or a 2D array of colors. colorsrc Sets the source reference on plot.ly for color . Returns ------- Fill """ super(Fill, self).__init__("fill") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.table.header.Fill constructor must be a dict or an instance of plotly.graph_objs.table.header.Fill""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.table.header import fill as v_fill # Initialize validators # --------------------- self._validators["color"] = v_fill.ColorValidator() self._validators["colorsrc"] = v_fill.ColorsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Fill", "Font", "Line"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/treemap/0000755000175000017500000000000013573746613021366 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/treemap/pathbar/0000755000175000017500000000000013573746613023007 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/treemap/pathbar/__init__.py0000644000175000017500000002552613573721552025125 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Textfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "treemap.pathbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Textfont object Sets the font used inside `pathbar`. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.treemap.pathbar.Textfont color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Textfont """ super(Textfont, self).__init__("textfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.treemap.pathbar.Textfont constructor must be a dict or an instance of plotly.graph_objs.treemap.pathbar.Textfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.treemap.pathbar import textfont as v_textfont # Initialize validators # --------------------- self._validators["color"] = v_textfont.ColorValidator() self._validators["colorsrc"] = v_textfont.ColorsrcValidator() self._validators["family"] = v_textfont.FamilyValidator() self._validators["familysrc"] = v_textfont.FamilysrcValidator() self._validators["size"] = v_textfont.SizeValidator() self._validators["sizesrc"] = v_textfont.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Textfont"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/treemap/hoverlabel/0000755000175000017500000000000013573746613023511 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/treemap/hoverlabel/__init__.py0000644000175000017500000002544013573721552025622 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "treemap.hoverlabel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Font object Sets the font used in hover labels. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.treemap.hoverlabel.Font color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.treemap.hoverlabel.Font constructor must be a dict or an instance of plotly.graph_objs.treemap.hoverlabel.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.treemap.hoverlabel import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["colorsrc"] = v_font.ColorsrcValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["familysrc"] = v_font.FamilysrcValidator() self._validators["size"] = v_font.SizeValidator() self._validators["sizesrc"] = v_font.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/treemap/marker/0000755000175000017500000000000013573746613022647 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/treemap/marker/colorbar/0000755000175000017500000000000013573746613024452 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/treemap/marker/colorbar/title/0000755000175000017500000000000013573746613025573 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/treemap/marker/colorbar/title/__init__.py0000644000175000017500000002057013573721552027703 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "treemap.marker.colorbar.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.treemap.marker.colorbar.title.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.treemap.marker.colorbar.title.Font constructor must be a dict or an instance of plotly.graph_objs.treemap.marker.colorbar.title.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.treemap.marker.colorbar.title import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/treemap/marker/colorbar/__init__.py0000644000175000017500000006075513573721553026574 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Title(_BaseTraceHierarchyType): # font # ---- @property def font(self): """ Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.treemap.marker.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.treemap.marker.colorbar.title.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # side # ---- @property def side(self): """ Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- Any """ return self["side"] @side.setter def side(self, val): self["side"] = val # text # ---- @property def text(self): """ Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "treemap.marker.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """ def __init__(self, arg=None, font=None, side=None, text=None, **kwargs): """ Construct a new Title object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.treemap.marker.colorbar.Title font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- Title """ super(Title, self).__init__("title") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.treemap.marker.colorbar.Title constructor must be a dict or an instance of plotly.graph_objs.treemap.marker.colorbar.Title""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.treemap.marker.colorbar import title as v_title # Initialize validators # --------------------- self._validators["font"] = v_title.FontValidator() self._validators["side"] = v_title.SideValidator() self._validators["text"] = v_title.TextValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("side", None) self["side"] = side if side is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickformatstop(_BaseTraceHierarchyType): # dtickrange # ---------- @property def dtickrange(self): """ range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" The 'dtickrange' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'dtickrange[0]' property accepts values of any type (1) The 'dtickrange[1]' property accepts values of any type Returns ------- list """ return self["dtickrange"] @dtickrange.setter def dtickrange(self, val): self["dtickrange"] = val # enabled # ------- @property def enabled(self): """ Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. The 'enabled' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["enabled"] @enabled.setter def enabled(self, val): self["enabled"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # value # ----- @property def value(self): """ string - dtickformat for described zoom level, the same as "tickformat" The 'value' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "treemap.marker.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """ def __init__( self, arg=None, dtickrange=None, enabled=None, name=None, templateitemname=None, value=None, **kwargs ): """ Construct a new Tickformatstop object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.treemap.marker.colorba r.Tickformatstop dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- Tickformatstop """ super(Tickformatstop, self).__init__("tickformatstops") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.treemap.marker.colorbar.Tickformatstop constructor must be a dict or an instance of plotly.graph_objs.treemap.marker.colorbar.Tickformatstop""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.treemap.marker.colorbar import ( tickformatstop as v_tickformatstop, ) # Initialize validators # --------------------- self._validators["dtickrange"] = v_tickformatstop.DtickrangeValidator() self._validators["enabled"] = v_tickformatstop.EnabledValidator() self._validators["name"] = v_tickformatstop.NameValidator() self._validators[ "templateitemname" ] = v_tickformatstop.TemplateitemnameValidator() self._validators["value"] = v_tickformatstop.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtickrange", None) self["dtickrange"] = dtickrange if dtickrange is not None else _v _v = arg.pop("enabled", None) self["enabled"] = enabled if enabled is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "treemap.marker.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Tickfont object Sets the color bar's tick label font Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.treemap.marker.colorbar.Tickfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Tickfont """ super(Tickfont, self).__init__("tickfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.treemap.marker.colorbar.Tickfont constructor must be a dict or an instance of plotly.graph_objs.treemap.marker.colorbar.Tickfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.treemap.marker.colorbar import tickfont as v_tickfont # Initialize validators # --------------------- self._validators["color"] = v_tickfont.ColorValidator() self._validators["family"] = v_tickfont.FamilyValidator() self._validators["size"] = v_tickfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Tickfont", "Tickformatstop", "Tickformatstop", "Title", "title"] from plotly.graph_objs.treemap.marker.colorbar import title plotly-4.4.1+dfsg.orig/plotly/graph_objs/treemap/marker/__init__.py0000644000175000017500000023754013573721553024767 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Pad(_BaseTraceHierarchyType): # b # - @property def b(self): """ Sets the padding form the bottom (in px). The 'b' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["b"] @b.setter def b(self, val): self["b"] = val # l # - @property def l(self): """ Sets the padding form the left (in px). The 'l' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["l"] @l.setter def l(self, val): self["l"] = val # r # - @property def r(self): """ Sets the padding form the right (in px). The 'r' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["r"] @r.setter def r(self, val): self["r"] = val # t # - @property def t(self): """ Sets the padding form the top (in px). The 't' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["t"] @t.setter def t(self, val): self["t"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "treemap.marker" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ b Sets the padding form the bottom (in px). l Sets the padding form the left (in px). r Sets the padding form the right (in px). t Sets the padding form the top (in px). """ def __init__(self, arg=None, b=None, l=None, r=None, t=None, **kwargs): """ Construct a new Pad object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.treemap.marker.Pad b Sets the padding form the bottom (in px). l Sets the padding form the left (in px). r Sets the padding form the right (in px). t Sets the padding form the top (in px). Returns ------- Pad """ super(Pad, self).__init__("pad") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.treemap.marker.Pad constructor must be a dict or an instance of plotly.graph_objs.treemap.marker.Pad""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.treemap.marker import pad as v_pad # Initialize validators # --------------------- self._validators["b"] = v_pad.BValidator() self._validators["l"] = v_pad.LValidator() self._validators["r"] = v_pad.RValidator() self._validators["t"] = v_pad.TValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("b", None) self["b"] = b if b is not None else _v _v = arg.pop("l", None) self["l"] = l if l is not None else _v _v = arg.pop("r", None) self["r"] = r if r is not None else _v _v = arg.pop("t", None) self["t"] = t if t is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the color of the line enclosing each sector. Defaults to the `paper_bgcolor` value. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # width # ----- @property def width(self): """ Sets the width (in px) of the line enclosing each sector. The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["width"] @width.setter def width(self, val): self["width"] = val # widthsrc # -------- @property def widthsrc(self): """ Sets the source reference on plot.ly for width . The 'widthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["widthsrc"] @widthsrc.setter def widthsrc(self, val): self["widthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "treemap.marker" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the color of the line enclosing each sector. Defaults to the `paper_bgcolor` value. colorsrc Sets the source reference on plot.ly for color . width Sets the width (in px) of the line enclosing each sector. widthsrc Sets the source reference on plot.ly for width . """ def __init__( self, arg=None, color=None, colorsrc=None, width=None, widthsrc=None, **kwargs ): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.treemap.marker.Line color Sets the color of the line enclosing each sector. Defaults to the `paper_bgcolor` value. colorsrc Sets the source reference on plot.ly for color . width Sets the width (in px) of the line enclosing each sector. widthsrc Sets the source reference on plot.ly for width . Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.treemap.marker.Line constructor must be a dict or an instance of plotly.graph_objs.treemap.marker.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.treemap.marker import line as v_line # Initialize validators # --------------------- self._validators["color"] = v_line.ColorValidator() self._validators["colorsrc"] = v_line.ColorsrcValidator() self._validators["width"] = v_line.WidthValidator() self._validators["widthsrc"] = v_line.WidthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v _v = arg.pop("widthsrc", None) self["widthsrc"] = widthsrc if widthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class ColorBar(_BaseTraceHierarchyType): # bgcolor # ------- @property def bgcolor(self): """ Sets the color of padded area. The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the axis line color. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # borderwidth # ----------- @property def borderwidth(self): """ Sets the width (in px) or the border enclosing this color bar. The 'borderwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["borderwidth"] @borderwidth.setter def borderwidth(self, val): self["borderwidth"] = val # dtick # ----- @property def dtick(self): """ Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" The 'dtick' property accepts values of any type Returns ------- Any """ return self["dtick"] @dtick.setter def dtick(self, val): self["dtick"] = val # exponentformat # -------------- @property def exponentformat(self): """ Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. The 'exponentformat' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'e', 'E', 'power', 'SI', 'B'] Returns ------- Any """ return self["exponentformat"] @exponentformat.setter def exponentformat(self, val): self["exponentformat"] = val # len # --- @property def len(self): """ Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. The 'len' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["len"] @len.setter def len(self, val): self["len"] = val # lenmode # ------- @property def lenmode(self): """ Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. The 'lenmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["lenmode"] @lenmode.setter def lenmode(self, val): self["lenmode"] = val # nticks # ------ @property def nticks(self): """ Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". The 'nticks' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nticks"] @nticks.setter def nticks(self, val): self["nticks"] = val # outlinecolor # ------------ @property def outlinecolor(self): """ Sets the axis line color. The 'outlinecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["outlinecolor"] @outlinecolor.setter def outlinecolor(self, val): self["outlinecolor"] = val # outlinewidth # ------------ @property def outlinewidth(self): """ Sets the width (in px) of the axis line. The 'outlinewidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["outlinewidth"] @outlinewidth.setter def outlinewidth(self, val): self["outlinewidth"] = val # separatethousands # ----------------- @property def separatethousands(self): """ If "true", even 4-digit integers are separated The 'separatethousands' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["separatethousands"] @separatethousands.setter def separatethousands(self, val): self["separatethousands"] = val # showexponent # ------------ @property def showexponent(self): """ If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. The 'showexponent' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showexponent"] @showexponent.setter def showexponent(self, val): self["showexponent"] = val # showticklabels # -------------- @property def showticklabels(self): """ Determines whether or not the tick labels are drawn. The 'showticklabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showticklabels"] @showticklabels.setter def showticklabels(self, val): self["showticklabels"] = val # showtickprefix # -------------- @property def showtickprefix(self): """ If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. The 'showtickprefix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showtickprefix"] @showtickprefix.setter def showtickprefix(self, val): self["showtickprefix"] = val # showticksuffix # -------------- @property def showticksuffix(self): """ Same as `showtickprefix` but for tick suffixes. The 'showticksuffix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showticksuffix"] @showticksuffix.setter def showticksuffix(self, val): self["showticksuffix"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # thicknessmode # ------------- @property def thicknessmode(self): """ Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. The 'thicknessmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["thicknessmode"] @thicknessmode.setter def thicknessmode(self, val): self["thicknessmode"] = val # tick0 # ----- @property def tick0(self): """ Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. The 'tick0' property accepts values of any type Returns ------- Any """ return self["tick0"] @tick0.setter def tick0(self, val): self["tick0"] = val # tickangle # --------- @property def tickangle(self): """ Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. The 'tickangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["tickangle"] @tickangle.setter def tickangle(self, val): self["tickangle"] = val # tickcolor # --------- @property def tickcolor(self): """ Sets the tick color. The 'tickcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["tickcolor"] @tickcolor.setter def tickcolor(self, val): self["tickcolor"] = val # tickfont # -------- @property def tickfont(self): """ Sets the color bar's tick label font The 'tickfont' property is an instance of Tickfont that may be specified as: - An instance of plotly.graph_objs.treemap.marker.colorbar.Tickfont - A dict of string/value properties that will be passed to the Tickfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.treemap.marker.colorbar.Tickfont """ return self["tickfont"] @tickfont.setter def tickfont(self, val): self["tickfont"] = val # tickformat # ---------- @property def tickformat(self): """ Sets the tick label formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'tickformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickformat"] @tickformat.setter def tickformat(self, val): self["tickformat"] = val # tickformatstops # --------------- @property def tickformatstops(self): """ The 'tickformatstops' property is a tuple of instances of Tickformatstop that may be specified as: - A list or tuple of instances of plotly.graph_objs.treemap.marker.colorbar.Tickformatstop - A list or tuple of dicts of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- tuple[plotly.graph_objs.treemap.marker.colorbar.Tickformatstop] """ return self["tickformatstops"] @tickformatstops.setter def tickformatstops(self, val): self["tickformatstops"] = val # tickformatstopdefaults # ---------------------- @property def tickformatstopdefaults(self): """ When used in a template (as layout.template.data.treemap.marker .colorbar.tickformatstopdefaults), sets the default property values to use for elements of treemap.marker.colorbar.tickformatstops The 'tickformatstopdefaults' property is an instance of Tickformatstop that may be specified as: - An instance of plotly.graph_objs.treemap.marker.colorbar.Tickformatstop - A dict of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: Returns ------- plotly.graph_objs.treemap.marker.colorbar.Tickformatstop """ return self["tickformatstopdefaults"] @tickformatstopdefaults.setter def tickformatstopdefaults(self, val): self["tickformatstopdefaults"] = val # ticklen # ------- @property def ticklen(self): """ Sets the tick length (in px). The 'ticklen' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ticklen"] @ticklen.setter def ticklen(self, val): self["ticklen"] = val # tickmode # -------- @property def tickmode(self): """ Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). The 'tickmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'linear', 'array'] Returns ------- Any """ return self["tickmode"] @tickmode.setter def tickmode(self, val): self["tickmode"] = val # tickprefix # ---------- @property def tickprefix(self): """ Sets a tick label prefix. The 'tickprefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickprefix"] @tickprefix.setter def tickprefix(self, val): self["tickprefix"] = val # ticks # ----- @property def ticks(self): """ Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. The 'ticks' property is an enumeration that may be specified as: - One of the following enumeration values: ['outside', 'inside', ''] Returns ------- Any """ return self["ticks"] @ticks.setter def ticks(self, val): self["ticks"] = val # ticksuffix # ---------- @property def ticksuffix(self): """ Sets a tick label suffix. The 'ticksuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ticksuffix"] @ticksuffix.setter def ticksuffix(self, val): self["ticksuffix"] = val # ticktext # -------- @property def ticktext(self): """ Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. The 'ticktext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ticktext"] @ticktext.setter def ticktext(self, val): self["ticktext"] = val # ticktextsrc # ----------- @property def ticktextsrc(self): """ Sets the source reference on plot.ly for ticktext . The 'ticktextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ticktextsrc"] @ticktextsrc.setter def ticktextsrc(self, val): self["ticktextsrc"] = val # tickvals # -------- @property def tickvals(self): """ Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. The 'tickvals' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["tickvals"] @tickvals.setter def tickvals(self, val): self["tickvals"] = val # tickvalssrc # ----------- @property def tickvalssrc(self): """ Sets the source reference on plot.ly for tickvals . The 'tickvalssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tickvalssrc"] @tickvalssrc.setter def tickvalssrc(self, val): self["tickvalssrc"] = val # tickwidth # --------- @property def tickwidth(self): """ Sets the tick width (in px). The 'tickwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["tickwidth"] @tickwidth.setter def tickwidth(self, val): self["tickwidth"] = val # title # ----- @property def title(self): """ The 'title' property is an instance of Title that may be specified as: - An instance of plotly.graph_objs.treemap.marker.colorbar.Title - A dict of string/value properties that will be passed to the Title constructor Supported dict properties: font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- plotly.graph_objs.treemap.marker.colorbar.Title """ return self["title"] @title.setter def title(self, val): self["title"] = val # titlefont # --------- @property def titlefont(self): """ Deprecated: Please use treemap.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.treemap.marker.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- """ return self["titlefont"] @titlefont.setter def titlefont(self, val): self["titlefont"] = val # titleside # --------- @property def titleside(self): """ Deprecated: Please use treemap.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- """ return self["titleside"] @titleside.setter def titleside(self, val): self["titleside"] = val # x # - @property def x(self): """ Sets the x position of the color bar (in plot fraction). The 'x' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["x"] @x.setter def x(self, val): self["x"] = val # xanchor # ------- @property def xanchor(self): """ Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. The 'xanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'center', 'right'] Returns ------- Any """ return self["xanchor"] @xanchor.setter def xanchor(self, val): self["xanchor"] = val # xpad # ---- @property def xpad(self): """ Sets the amount of padding (in px) along the x direction. The 'xpad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["xpad"] @xpad.setter def xpad(self, val): self["xpad"] = val # y # - @property def y(self): """ Sets the y position of the color bar (in plot fraction). The 'y' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["y"] @y.setter def y(self, val): self["y"] = val # yanchor # ------- @property def yanchor(self): """ Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. The 'yanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['top', 'middle', 'bottom'] Returns ------- Any """ return self["yanchor"] @yanchor.setter def yanchor(self, val): self["yanchor"] = val # ypad # ---- @property def ypad(self): """ Sets the amount of padding (in px) along the y direction. The 'ypad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ypad"] @ypad.setter def ypad(self, val): self["ypad"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "treemap.marker" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.treemap.marker.colorbar .Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.treema p.marker.colorbar.tickformatstopdefaults), sets the default property values to use for elements of treemap.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.treemap.marker.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use treemap.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use treemap.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """ _mapped_properties = { "titlefont": ("title", "font"), "titleside": ("title", "side"), } def __init__( self, arg=None, bgcolor=None, bordercolor=None, borderwidth=None, dtick=None, exponentformat=None, len=None, lenmode=None, nticks=None, outlinecolor=None, outlinewidth=None, separatethousands=None, showexponent=None, showticklabels=None, showtickprefix=None, showticksuffix=None, thickness=None, thicknessmode=None, tick0=None, tickangle=None, tickcolor=None, tickfont=None, tickformat=None, tickformatstops=None, tickformatstopdefaults=None, ticklen=None, tickmode=None, tickprefix=None, ticks=None, ticksuffix=None, ticktext=None, ticktextsrc=None, tickvals=None, tickvalssrc=None, tickwidth=None, title=None, titlefont=None, titleside=None, x=None, xanchor=None, xpad=None, y=None, yanchor=None, ypad=None, **kwargs ): """ Construct a new ColorBar object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.treemap.marker.ColorBar bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.treemap.marker.colorbar .Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.treema p.marker.colorbar.tickformatstopdefaults), sets the default property values to use for elements of treemap.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.treemap.marker.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use treemap.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use treemap.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- ColorBar """ super(ColorBar, self).__init__("colorbar") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.treemap.marker.ColorBar constructor must be a dict or an instance of plotly.graph_objs.treemap.marker.ColorBar""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.treemap.marker import colorbar as v_colorbar # Initialize validators # --------------------- self._validators["bgcolor"] = v_colorbar.BgcolorValidator() self._validators["bordercolor"] = v_colorbar.BordercolorValidator() self._validators["borderwidth"] = v_colorbar.BorderwidthValidator() self._validators["dtick"] = v_colorbar.DtickValidator() self._validators["exponentformat"] = v_colorbar.ExponentformatValidator() self._validators["len"] = v_colorbar.LenValidator() self._validators["lenmode"] = v_colorbar.LenmodeValidator() self._validators["nticks"] = v_colorbar.NticksValidator() self._validators["outlinecolor"] = v_colorbar.OutlinecolorValidator() self._validators["outlinewidth"] = v_colorbar.OutlinewidthValidator() self._validators["separatethousands"] = v_colorbar.SeparatethousandsValidator() self._validators["showexponent"] = v_colorbar.ShowexponentValidator() self._validators["showticklabels"] = v_colorbar.ShowticklabelsValidator() self._validators["showtickprefix"] = v_colorbar.ShowtickprefixValidator() self._validators["showticksuffix"] = v_colorbar.ShowticksuffixValidator() self._validators["thickness"] = v_colorbar.ThicknessValidator() self._validators["thicknessmode"] = v_colorbar.ThicknessmodeValidator() self._validators["tick0"] = v_colorbar.Tick0Validator() self._validators["tickangle"] = v_colorbar.TickangleValidator() self._validators["tickcolor"] = v_colorbar.TickcolorValidator() self._validators["tickfont"] = v_colorbar.TickfontValidator() self._validators["tickformat"] = v_colorbar.TickformatValidator() self._validators["tickformatstops"] = v_colorbar.TickformatstopsValidator() self._validators[ "tickformatstopdefaults" ] = v_colorbar.TickformatstopValidator() self._validators["ticklen"] = v_colorbar.TicklenValidator() self._validators["tickmode"] = v_colorbar.TickmodeValidator() self._validators["tickprefix"] = v_colorbar.TickprefixValidator() self._validators["ticks"] = v_colorbar.TicksValidator() self._validators["ticksuffix"] = v_colorbar.TicksuffixValidator() self._validators["ticktext"] = v_colorbar.TicktextValidator() self._validators["ticktextsrc"] = v_colorbar.TicktextsrcValidator() self._validators["tickvals"] = v_colorbar.TickvalsValidator() self._validators["tickvalssrc"] = v_colorbar.TickvalssrcValidator() self._validators["tickwidth"] = v_colorbar.TickwidthValidator() self._validators["title"] = v_colorbar.TitleValidator() self._validators["x"] = v_colorbar.XValidator() self._validators["xanchor"] = v_colorbar.XanchorValidator() self._validators["xpad"] = v_colorbar.XpadValidator() self._validators["y"] = v_colorbar.YValidator() self._validators["yanchor"] = v_colorbar.YanchorValidator() self._validators["ypad"] = v_colorbar.YpadValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("borderwidth", None) self["borderwidth"] = borderwidth if borderwidth is not None else _v _v = arg.pop("dtick", None) self["dtick"] = dtick if dtick is not None else _v _v = arg.pop("exponentformat", None) self["exponentformat"] = exponentformat if exponentformat is not None else _v _v = arg.pop("len", None) self["len"] = len if len is not None else _v _v = arg.pop("lenmode", None) self["lenmode"] = lenmode if lenmode is not None else _v _v = arg.pop("nticks", None) self["nticks"] = nticks if nticks is not None else _v _v = arg.pop("outlinecolor", None) self["outlinecolor"] = outlinecolor if outlinecolor is not None else _v _v = arg.pop("outlinewidth", None) self["outlinewidth"] = outlinewidth if outlinewidth is not None else _v _v = arg.pop("separatethousands", None) self["separatethousands"] = ( separatethousands if separatethousands is not None else _v ) _v = arg.pop("showexponent", None) self["showexponent"] = showexponent if showexponent is not None else _v _v = arg.pop("showticklabels", None) self["showticklabels"] = showticklabels if showticklabels is not None else _v _v = arg.pop("showtickprefix", None) self["showtickprefix"] = showtickprefix if showtickprefix is not None else _v _v = arg.pop("showticksuffix", None) self["showticksuffix"] = showticksuffix if showticksuffix is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("thicknessmode", None) self["thicknessmode"] = thicknessmode if thicknessmode is not None else _v _v = arg.pop("tick0", None) self["tick0"] = tick0 if tick0 is not None else _v _v = arg.pop("tickangle", None) self["tickangle"] = tickangle if tickangle is not None else _v _v = arg.pop("tickcolor", None) self["tickcolor"] = tickcolor if tickcolor is not None else _v _v = arg.pop("tickfont", None) self["tickfont"] = tickfont if tickfont is not None else _v _v = arg.pop("tickformat", None) self["tickformat"] = tickformat if tickformat is not None else _v _v = arg.pop("tickformatstops", None) self["tickformatstops"] = tickformatstops if tickformatstops is not None else _v _v = arg.pop("tickformatstopdefaults", None) self["tickformatstopdefaults"] = ( tickformatstopdefaults if tickformatstopdefaults is not None else _v ) _v = arg.pop("ticklen", None) self["ticklen"] = ticklen if ticklen is not None else _v _v = arg.pop("tickmode", None) self["tickmode"] = tickmode if tickmode is not None else _v _v = arg.pop("tickprefix", None) self["tickprefix"] = tickprefix if tickprefix is not None else _v _v = arg.pop("ticks", None) self["ticks"] = ticks if ticks is not None else _v _v = arg.pop("ticksuffix", None) self["ticksuffix"] = ticksuffix if ticksuffix is not None else _v _v = arg.pop("ticktext", None) self["ticktext"] = ticktext if ticktext is not None else _v _v = arg.pop("ticktextsrc", None) self["ticktextsrc"] = ticktextsrc if ticktextsrc is not None else _v _v = arg.pop("tickvals", None) self["tickvals"] = tickvals if tickvals is not None else _v _v = arg.pop("tickvalssrc", None) self["tickvalssrc"] = tickvalssrc if tickvalssrc is not None else _v _v = arg.pop("tickwidth", None) self["tickwidth"] = tickwidth if tickwidth is not None else _v _v = arg.pop("title", None) self["title"] = title if title is not None else _v _v = arg.pop("titlefont", None) _v = titlefont if titlefont is not None else _v if _v is not None: self["titlefont"] = _v _v = arg.pop("titleside", None) _v = titleside if titleside is not None else _v if _v is not None: self["titleside"] = _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xanchor", None) self["xanchor"] = xanchor if xanchor is not None else _v _v = arg.pop("xpad", None) self["xpad"] = xpad if xpad is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("yanchor", None) self["yanchor"] = yanchor if yanchor is not None else _v _v = arg.pop("ypad", None) self["ypad"] = ypad if ypad is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["ColorBar", "Line", "Pad", "colorbar"] from plotly.graph_objs.treemap.marker import colorbar plotly-4.4.1+dfsg.orig/plotly/graph_objs/treemap/__init__.py0000644000175000017500000033755313573721553023513 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tiling(_BaseTraceHierarchyType): # flip # ---- @property def flip(self): """ Determines if the positions obtained from solver are flipped on each axis. The 'flip' property is a flaglist and may be specified as a string containing: - Any combination of ['x', 'y'] joined with '+' characters (e.g. 'x+y') Returns ------- Any """ return self["flip"] @flip.setter def flip(self, val): self["flip"] = val # packing # ------- @property def packing(self): """ Determines d3 treemap solver. For more info please refer to https://github.com/d3/d3-hierarchy#treemap-tiling The 'packing' property is an enumeration that may be specified as: - One of the following enumeration values: ['squarify', 'binary', 'dice', 'slice', 'slice-dice', 'dice-slice'] Returns ------- Any """ return self["packing"] @packing.setter def packing(self, val): self["packing"] = val # pad # --- @property def pad(self): """ Sets the inner padding (in px). The 'pad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["pad"] @pad.setter def pad(self, val): self["pad"] = val # squarifyratio # ------------- @property def squarifyratio(self): """ When using "squarify" `packing` algorithm, according to https:/ /github.com/d3/d3-hierarchy/blob/master/README.md#squarify_rati o this option specifies the desired aspect ratio of the generated rectangles. The ratio must be specified as a number greater than or equal to one. Note that the orientation of the generated rectangles (tall or wide) is not implied by the ratio; for example, a ratio of two will attempt to produce a mixture of rectangles whose width:height ratio is either 2:1 or 1:2. When using "squarify", unlike d3 which uses the Golden Ratio i.e. 1.618034, Plotly applies 1 to increase squares in treemap layouts. The 'squarifyratio' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["squarifyratio"] @squarifyratio.setter def squarifyratio(self, val): self["squarifyratio"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "treemap" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ flip Determines if the positions obtained from solver are flipped on each axis. packing Determines d3 treemap solver. For more info please refer to https://github.com/d3/d3-hierarchy#treemap- tiling pad Sets the inner padding (in px). squarifyratio When using "squarify" `packing` algorithm, according to https://github.com/d3/d3-hierarchy/blob/master/README.m d#squarify_ratio this option specifies the desired aspect ratio of the generated rectangles. The ratio must be specified as a number greater than or equal to one. Note that the orientation of the generated rectangles (tall or wide) is not implied by the ratio; for example, a ratio of two will attempt to produce a mixture of rectangles whose width:height ratio is either 2:1 or 1:2. When using "squarify", unlike d3 which uses the Golden Ratio i.e. 1.618034, Plotly applies 1 to increase squares in treemap layouts. """ def __init__( self, arg=None, flip=None, packing=None, pad=None, squarifyratio=None, **kwargs ): """ Construct a new Tiling object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.treemap.Tiling flip Determines if the positions obtained from solver are flipped on each axis. packing Determines d3 treemap solver. For more info please refer to https://github.com/d3/d3-hierarchy#treemap- tiling pad Sets the inner padding (in px). squarifyratio When using "squarify" `packing` algorithm, according to https://github.com/d3/d3-hierarchy/blob/master/README.m d#squarify_ratio this option specifies the desired aspect ratio of the generated rectangles. The ratio must be specified as a number greater than or equal to one. Note that the orientation of the generated rectangles (tall or wide) is not implied by the ratio; for example, a ratio of two will attempt to produce a mixture of rectangles whose width:height ratio is either 2:1 or 1:2. When using "squarify", unlike d3 which uses the Golden Ratio i.e. 1.618034, Plotly applies 1 to increase squares in treemap layouts. Returns ------- Tiling """ super(Tiling, self).__init__("tiling") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.treemap.Tiling constructor must be a dict or an instance of plotly.graph_objs.treemap.Tiling""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.treemap import tiling as v_tiling # Initialize validators # --------------------- self._validators["flip"] = v_tiling.FlipValidator() self._validators["packing"] = v_tiling.PackingValidator() self._validators["pad"] = v_tiling.PadValidator() self._validators["squarifyratio"] = v_tiling.SquarifyratioValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("flip", None) self["flip"] = flip if flip is not None else _v _v = arg.pop("packing", None) self["packing"] = packing if packing is not None else _v _v = arg.pop("pad", None) self["pad"] = pad if pad is not None else _v _v = arg.pop("squarifyratio", None) self["squarifyratio"] = squarifyratio if squarifyratio is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Textfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "treemap" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Textfont object Sets the font used for `textinfo`. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.treemap.Textfont color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Textfont """ super(Textfont, self).__init__("textfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.treemap.Textfont constructor must be a dict or an instance of plotly.graph_objs.treemap.Textfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.treemap import textfont as v_textfont # Initialize validators # --------------------- self._validators["color"] = v_textfont.ColorValidator() self._validators["colorsrc"] = v_textfont.ColorsrcValidator() self._validators["family"] = v_textfont.FamilyValidator() self._validators["familysrc"] = v_textfont.FamilysrcValidator() self._validators["size"] = v_textfont.SizeValidator() self._validators["sizesrc"] = v_textfont.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Stream(_BaseTraceHierarchyType): # maxpoints # --------- @property def maxpoints(self): """ Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. The 'maxpoints' property is a number and may be specified as: - An int or float in the interval [0, 10000] Returns ------- int|float """ return self["maxpoints"] @maxpoints.setter def maxpoints(self, val): self["maxpoints"] = val # token # ----- @property def token(self): """ The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. The 'token' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["token"] @token.setter def token(self, val): self["token"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "treemap" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """ def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): """ Construct a new Stream object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.treemap.Stream maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- Stream """ super(Stream, self).__init__("stream") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.treemap.Stream constructor must be a dict or an instance of plotly.graph_objs.treemap.Stream""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.treemap import stream as v_stream # Initialize validators # --------------------- self._validators["maxpoints"] = v_stream.MaxpointsValidator() self._validators["token"] = v_stream.TokenValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("maxpoints", None) self["maxpoints"] = maxpoints if maxpoints is not None else _v _v = arg.pop("token", None) self["token"] = token if token is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Pathbar(_BaseTraceHierarchyType): # edgeshape # --------- @property def edgeshape(self): """ Determines which shape is used for edges between `barpath` labels. The 'edgeshape' property is an enumeration that may be specified as: - One of the following enumeration values: ['>', '<', '|', '\\'] - A string that matches one of the following regular expressions: [''] Returns ------- Any """ return self["edgeshape"] @edgeshape.setter def edgeshape(self, val): self["edgeshape"] = val # side # ---- @property def side(self): """ Determines on which side of the the treemap the `pathbar` should be presented. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['top', 'bottom'] Returns ------- Any """ return self["side"] @side.setter def side(self, val): self["side"] = val # textfont # -------- @property def textfont(self): """ Sets the font used inside `pathbar`. The 'textfont' property is an instance of Textfont that may be specified as: - An instance of plotly.graph_objs.treemap.pathbar.Textfont - A dict of string/value properties that will be passed to the Textfont constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.treemap.pathbar.Textfont """ return self["textfont"] @textfont.setter def textfont(self, val): self["textfont"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness of `pathbar` (in px). If not specified the `pathbar.textfont.size` is used with 3 pixles extra padding on each side. The 'thickness' property is a number and may be specified as: - An int or float in the interval [12, inf] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # visible # ------- @property def visible(self): """ Determines if the path bar is drawn i.e. outside the trace `domain` and with one pixel gap. The 'visible' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "treemap" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ edgeshape Determines which shape is used for edges between `barpath` labels. side Determines on which side of the the treemap the `pathbar` should be presented. textfont Sets the font used inside `pathbar`. thickness Sets the thickness of `pathbar` (in px). If not specified the `pathbar.textfont.size` is used with 3 pixles extra padding on each side. visible Determines if the path bar is drawn i.e. outside the trace `domain` and with one pixel gap. """ def __init__( self, arg=None, edgeshape=None, side=None, textfont=None, thickness=None, visible=None, **kwargs ): """ Construct a new Pathbar object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.treemap.Pathbar edgeshape Determines which shape is used for edges between `barpath` labels. side Determines on which side of the the treemap the `pathbar` should be presented. textfont Sets the font used inside `pathbar`. thickness Sets the thickness of `pathbar` (in px). If not specified the `pathbar.textfont.size` is used with 3 pixles extra padding on each side. visible Determines if the path bar is drawn i.e. outside the trace `domain` and with one pixel gap. Returns ------- Pathbar """ super(Pathbar, self).__init__("pathbar") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.treemap.Pathbar constructor must be a dict or an instance of plotly.graph_objs.treemap.Pathbar""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.treemap import pathbar as v_pathbar # Initialize validators # --------------------- self._validators["edgeshape"] = v_pathbar.EdgeshapeValidator() self._validators["side"] = v_pathbar.SideValidator() self._validators["textfont"] = v_pathbar.TextfontValidator() self._validators["thickness"] = v_pathbar.ThicknessValidator() self._validators["visible"] = v_pathbar.VisibleValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("edgeshape", None) self["edgeshape"] = edgeshape if edgeshape is not None else _v _v = arg.pop("side", None) self["side"] = side if side is not None else _v _v = arg.pop("textfont", None) self["textfont"] = textfont if textfont is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Outsidetextfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "treemap" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Outsidetextfont object Sets the font used for `textinfo` lying outside the sector. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.treemap.Outsidetextfont color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Outsidetextfont """ super(Outsidetextfont, self).__init__("outsidetextfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.treemap.Outsidetextfont constructor must be a dict or an instance of plotly.graph_objs.treemap.Outsidetextfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.treemap import outsidetextfont as v_outsidetextfont # Initialize validators # --------------------- self._validators["color"] = v_outsidetextfont.ColorValidator() self._validators["colorsrc"] = v_outsidetextfont.ColorsrcValidator() self._validators["family"] = v_outsidetextfont.FamilyValidator() self._validators["familysrc"] = v_outsidetextfont.FamilysrcValidator() self._validators["size"] = v_outsidetextfont.SizeValidator() self._validators["sizesrc"] = v_outsidetextfont.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # autocolorscale # -------------- @property def autocolorscale(self): """ Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if colorsis set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. The 'autocolorscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocolorscale"] @autocolorscale.setter def autocolorscale(self, val): self["autocolorscale"] = val # cauto # ----- @property def cauto(self): """ Determines whether or not the color domain is computed with respect to the input data (here colors) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if colorsis set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. The 'cauto' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["cauto"] @cauto.setter def cauto(self, val): self["cauto"] = val # cmax # ---- @property def cmax(self): """ Sets the upper bound of the color domain. Has an effect only if colorsis set to a numerical array. Value should have the same units as colors and if set, `marker.cmin` must be set as well. The 'cmax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmax"] @cmax.setter def cmax(self, val): self["cmax"] = val # cmid # ---- @property def cmid(self): """ Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if colorsis set to a numerical array. Value should have the same units as colors. Has no effect when `marker.cauto` is `false`. The 'cmid' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmid"] @cmid.setter def cmid(self, val): self["cmid"] = val # cmin # ---- @property def cmin(self): """ Sets the lower bound of the color domain. Has an effect only if colorsis set to a numerical array. Value should have the same units as colors and if set, `marker.cmax` must be set as well. The 'cmin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmin"] @cmin.setter def cmin(self, val): self["cmin"] = val # coloraxis # --------- @property def coloraxis(self): """ Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. The 'coloraxis' property is an identifier of a particular subplot, of type 'coloraxis', that may be specified as the string 'coloraxis' optionally followed by an integer >= 1 (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) Returns ------- str """ return self["coloraxis"] @coloraxis.setter def coloraxis(self, val): self["coloraxis"] = val # colorbar # -------- @property def colorbar(self): """ The 'colorbar' property is an instance of ColorBar that may be specified as: - An instance of plotly.graph_objs.treemap.marker.ColorBar - A dict of string/value properties that will be passed to the ColorBar constructor Supported dict properties: bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.treemap.marker. colorbar.Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.treemap.marker.colorbar.tickformatstopdefault s), sets the default property values to use for elements of treemap.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.treemap.marker.colorbar.Ti tle instance or dict with compatible properties titlefont Deprecated: Please use treemap.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use treemap.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- plotly.graph_objs.treemap.marker.ColorBar """ return self["colorbar"] @colorbar.setter def colorbar(self, val): self["colorbar"] = val # colors # ------ @property def colors(self): """ Sets the color of each sector of this trace. If not specified, the default trace color set is used to pick the sector colors. The 'colors' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["colors"] @colors.setter def colors(self, val): self["colors"] = val # colorscale # ---------- @property def colorscale(self): """ Sets the colorscale. Has an effect only if colorsis set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,B luered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Blackbod y,Earth,Electric,Viridis,Cividis. The 'colorscale' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # colorssrc # --------- @property def colorssrc(self): """ Sets the source reference on plot.ly for colors . The 'colorssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorssrc"] @colorssrc.setter def colorssrc(self, val): self["colorssrc"] = val # depthfade # --------- @property def depthfade(self): """ Determines if the sector colors are faded towards the background from the leaves up to the headers. This option is unavailable when a `colorscale` is present, defaults to false when `marker.colors` is set, but otherwise defaults to true. When set to "reversed", the fading direction is inverted, that is the top elements within hierarchy are drawn with fully saturated colors while the leaves are faded towards the background color. The 'depthfade' property is an enumeration that may be specified as: - One of the following enumeration values: [True, False, 'reversed'] Returns ------- Any """ return self["depthfade"] @depthfade.setter def depthfade(self, val): self["depthfade"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.treemap.marker.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: color Sets the color of the line enclosing each sector. Defaults to the `paper_bgcolor` value. colorsrc Sets the source reference on plot.ly for color . width Sets the width (in px) of the line enclosing each sector. widthsrc Sets the source reference on plot.ly for width . Returns ------- plotly.graph_objs.treemap.marker.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # pad # --- @property def pad(self): """ The 'pad' property is an instance of Pad that may be specified as: - An instance of plotly.graph_objs.treemap.marker.Pad - A dict of string/value properties that will be passed to the Pad constructor Supported dict properties: b Sets the padding form the bottom (in px). l Sets the padding form the left (in px). r Sets the padding form the right (in px). t Sets the padding form the top (in px). Returns ------- plotly.graph_objs.treemap.marker.Pad """ return self["pad"] @pad.setter def pad(self, val): self["pad"] = val # reversescale # ------------ @property def reversescale(self): """ Reverses the color mapping if true. Has an effect only if colorsis set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. The 'reversescale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["reversescale"] @reversescale.setter def reversescale(self, val): self["reversescale"] = val # showscale # --------- @property def showscale(self): """ Determines whether or not a colorbar is displayed for this trace. Has an effect only if colorsis set to a numerical array. The 'showscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showscale"] @showscale.setter def showscale(self, val): self["showscale"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "treemap" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if colorsis set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here colors) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if colorsis set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if colorsis set to a numerical array. Value should have the same units as colors and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if colorsis set to a numerical array. Value should have the same units as colors. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if colorsis set to a numerical array. Value should have the same units as colors and if set, `marker.cmax` must be set as well. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.treemap.marker.ColorBar instance or dict with compatible properties colors Sets the color of each sector of this trace. If not specified, the default trace color set is used to pick the sector colors. colorscale Sets the colorscale. Has an effect only if colorsis set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu ,Greens,YlOrRd,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,P ortland,Jet,Hot,Blackbody,Earth,Electric,Viridis,Cividi s. colorssrc Sets the source reference on plot.ly for colors . depthfade Determines if the sector colors are faded towards the background from the leaves up to the headers. This option is unavailable when a `colorscale` is present, defaults to false when `marker.colors` is set, but otherwise defaults to true. When set to "reversed", the fading direction is inverted, that is the top elements within hierarchy are drawn with fully saturated colors while the leaves are faded towards the background color. line plotly.graph_objects.treemap.marker.Line instance or dict with compatible properties pad plotly.graph_objects.treemap.marker.Pad instance or dict with compatible properties reversescale Reverses the color mapping if true. Has an effect only if colorsis set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if colorsis set to a numerical array. """ def __init__( self, arg=None, autocolorscale=None, cauto=None, cmax=None, cmid=None, cmin=None, coloraxis=None, colorbar=None, colors=None, colorscale=None, colorssrc=None, depthfade=None, line=None, pad=None, reversescale=None, showscale=None, **kwargs ): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.treemap.Marker autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if colorsis set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here colors) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if colorsis set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if colorsis set to a numerical array. Value should have the same units as colors and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if colorsis set to a numerical array. Value should have the same units as colors. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if colorsis set to a numerical array. Value should have the same units as colors and if set, `marker.cmax` must be set as well. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar plotly.graph_objects.treemap.marker.ColorBar instance or dict with compatible properties colors Sets the color of each sector of this trace. If not specified, the default trace color set is used to pick the sector colors. colorscale Sets the colorscale. Has an effect only if colorsis set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu ,Greens,YlOrRd,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,P ortland,Jet,Hot,Blackbody,Earth,Electric,Viridis,Cividi s. colorssrc Sets the source reference on plot.ly for colors . depthfade Determines if the sector colors are faded towards the background from the leaves up to the headers. This option is unavailable when a `colorscale` is present, defaults to false when `marker.colors` is set, but otherwise defaults to true. When set to "reversed", the fading direction is inverted, that is the top elements within hierarchy are drawn with fully saturated colors while the leaves are faded towards the background color. line plotly.graph_objects.treemap.marker.Line instance or dict with compatible properties pad plotly.graph_objects.treemap.marker.Pad instance or dict with compatible properties reversescale Reverses the color mapping if true. Has an effect only if colorsis set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if colorsis set to a numerical array. Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.treemap.Marker constructor must be a dict or an instance of plotly.graph_objs.treemap.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.treemap import marker as v_marker # Initialize validators # --------------------- self._validators["autocolorscale"] = v_marker.AutocolorscaleValidator() self._validators["cauto"] = v_marker.CautoValidator() self._validators["cmax"] = v_marker.CmaxValidator() self._validators["cmid"] = v_marker.CmidValidator() self._validators["cmin"] = v_marker.CminValidator() self._validators["coloraxis"] = v_marker.ColoraxisValidator() self._validators["colorbar"] = v_marker.ColorBarValidator() self._validators["colors"] = v_marker.ColorsValidator() self._validators["colorscale"] = v_marker.ColorscaleValidator() self._validators["colorssrc"] = v_marker.ColorssrcValidator() self._validators["depthfade"] = v_marker.DepthfadeValidator() self._validators["line"] = v_marker.LineValidator() self._validators["pad"] = v_marker.PadValidator() self._validators["reversescale"] = v_marker.ReversescaleValidator() self._validators["showscale"] = v_marker.ShowscaleValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autocolorscale", None) self["autocolorscale"] = autocolorscale if autocolorscale is not None else _v _v = arg.pop("cauto", None) self["cauto"] = cauto if cauto is not None else _v _v = arg.pop("cmax", None) self["cmax"] = cmax if cmax is not None else _v _v = arg.pop("cmid", None) self["cmid"] = cmid if cmid is not None else _v _v = arg.pop("cmin", None) self["cmin"] = cmin if cmin is not None else _v _v = arg.pop("coloraxis", None) self["coloraxis"] = coloraxis if coloraxis is not None else _v _v = arg.pop("colorbar", None) self["colorbar"] = colorbar if colorbar is not None else _v _v = arg.pop("colors", None) self["colors"] = colors if colors is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("colorssrc", None) self["colorssrc"] = colorssrc if colorssrc is not None else _v _v = arg.pop("depthfade", None) self["depthfade"] = depthfade if depthfade is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v _v = arg.pop("pad", None) self["pad"] = pad if pad is not None else _v _v = arg.pop("reversescale", None) self["reversescale"] = reversescale if reversescale is not None else _v _v = arg.pop("showscale", None) self["showscale"] = showscale if showscale is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Insidetextfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "treemap" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Insidetextfont object Sets the font used for `textinfo` lying inside the sector. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.treemap.Insidetextfont color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Insidetextfont """ super(Insidetextfont, self).__init__("insidetextfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.treemap.Insidetextfont constructor must be a dict or an instance of plotly.graph_objs.treemap.Insidetextfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.treemap import insidetextfont as v_insidetextfont # Initialize validators # --------------------- self._validators["color"] = v_insidetextfont.ColorValidator() self._validators["colorsrc"] = v_insidetextfont.ColorsrcValidator() self._validators["family"] = v_insidetextfont.FamilyValidator() self._validators["familysrc"] = v_insidetextfont.FamilysrcValidator() self._validators["size"] = v_insidetextfont.SizeValidator() self._validators["sizesrc"] = v_insidetextfont.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Hoverlabel(_BaseTraceHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'right', 'auto'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["align"] @align.setter def align(self, val): self["align"] = val # alignsrc # -------- @property def alignsrc(self): """ Sets the source reference on plot.ly for align . The 'alignsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["alignsrc"] @alignsrc.setter def alignsrc(self, val): self["alignsrc"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the hover labels for this trace The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bgcolorsrc # ---------- @property def bgcolorsrc(self): """ Sets the source reference on plot.ly for bgcolor . The 'bgcolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bgcolorsrc"] @bgcolorsrc.setter def bgcolorsrc(self, val): self["bgcolorsrc"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the border color of the hover labels for this trace. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # bordercolorsrc # -------------- @property def bordercolorsrc(self): """ Sets the source reference on plot.ly for bordercolor . The 'bordercolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bordercolorsrc"] @bordercolorsrc.setter def bordercolorsrc(self, val): self["bordercolorsrc"] = val # font # ---- @property def font(self): """ Sets the font used in hover labels. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.treemap.hoverlabel.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.treemap.hoverlabel.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # namelength # ---------- @property def namelength(self): """ Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. The 'namelength' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [-1, 9223372036854775807] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|numpy.ndarray """ return self["namelength"] @namelength.setter def namelength(self, val): self["namelength"] = val # namelengthsrc # ------------- @property def namelengthsrc(self): """ Sets the source reference on plot.ly for namelength . The 'namelengthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["namelengthsrc"] @namelengthsrc.setter def namelengthsrc(self, val): self["namelengthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "treemap" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """ def __init__( self, arg=None, align=None, alignsrc=None, bgcolor=None, bgcolorsrc=None, bordercolor=None, bordercolorsrc=None, font=None, namelength=None, namelengthsrc=None, **kwargs ): """ Construct a new Hoverlabel object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.treemap.Hoverlabel align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- Hoverlabel """ super(Hoverlabel, self).__init__("hoverlabel") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.treemap.Hoverlabel constructor must be a dict or an instance of plotly.graph_objs.treemap.Hoverlabel""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.treemap import hoverlabel as v_hoverlabel # Initialize validators # --------------------- self._validators["align"] = v_hoverlabel.AlignValidator() self._validators["alignsrc"] = v_hoverlabel.AlignsrcValidator() self._validators["bgcolor"] = v_hoverlabel.BgcolorValidator() self._validators["bgcolorsrc"] = v_hoverlabel.BgcolorsrcValidator() self._validators["bordercolor"] = v_hoverlabel.BordercolorValidator() self._validators["bordercolorsrc"] = v_hoverlabel.BordercolorsrcValidator() self._validators["font"] = v_hoverlabel.FontValidator() self._validators["namelength"] = v_hoverlabel.NamelengthValidator() self._validators["namelengthsrc"] = v_hoverlabel.NamelengthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("alignsrc", None) self["alignsrc"] = alignsrc if alignsrc is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bgcolorsrc", None) self["bgcolorsrc"] = bgcolorsrc if bgcolorsrc is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("bordercolorsrc", None) self["bordercolorsrc"] = bordercolorsrc if bordercolorsrc is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("namelength", None) self["namelength"] = namelength if namelength is not None else _v _v = arg.pop("namelengthsrc", None) self["namelengthsrc"] = namelengthsrc if namelengthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Domain(_BaseTraceHierarchyType): # column # ------ @property def column(self): """ If there is a layout grid, use the domain for this column in the grid for this treemap trace . The 'column' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["column"] @column.setter def column(self, val): self["column"] = val # row # --- @property def row(self): """ If there is a layout grid, use the domain for this row in the grid for this treemap trace . The 'row' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["row"] @row.setter def row(self, val): self["row"] = val # x # - @property def x(self): """ Sets the horizontal domain of this treemap trace (in plot fraction). The 'x' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'x[0]' property is a number and may be specified as: - An int or float in the interval [0, 1] (1) The 'x[1]' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- list """ return self["x"] @x.setter def x(self, val): self["x"] = val # y # - @property def y(self): """ Sets the vertical domain of this treemap trace (in plot fraction). The 'y' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'y[0]' property is a number and may be specified as: - An int or float in the interval [0, 1] (1) The 'y[1]' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- list """ return self["y"] @y.setter def y(self, val): self["y"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "treemap" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ column If there is a layout grid, use the domain for this column in the grid for this treemap trace . row If there is a layout grid, use the domain for this row in the grid for this treemap trace . x Sets the horizontal domain of this treemap trace (in plot fraction). y Sets the vertical domain of this treemap trace (in plot fraction). """ def __init__(self, arg=None, column=None, row=None, x=None, y=None, **kwargs): """ Construct a new Domain object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.treemap.Domain column If there is a layout grid, use the domain for this column in the grid for this treemap trace . row If there is a layout grid, use the domain for this row in the grid for this treemap trace . x Sets the horizontal domain of this treemap trace (in plot fraction). y Sets the vertical domain of this treemap trace (in plot fraction). Returns ------- Domain """ super(Domain, self).__init__("domain") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.treemap.Domain constructor must be a dict or an instance of plotly.graph_objs.treemap.Domain""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.treemap import domain as v_domain # Initialize validators # --------------------- self._validators["column"] = v_domain.ColumnValidator() self._validators["row"] = v_domain.RowValidator() self._validators["x"] = v_domain.XValidator() self._validators["y"] = v_domain.YValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("column", None) self["column"] = column if column is not None else _v _v = arg.pop("row", None) self["row"] = row if row is not None else _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = [ "Domain", "Hoverlabel", "Insidetextfont", "Marker", "Outsidetextfont", "Pathbar", "Stream", "Textfont", "Tiling", "hoverlabel", "marker", "pathbar", ] from plotly.graph_objs.treemap import pathbar from plotly.graph_objs.treemap import marker from plotly.graph_objs.treemap import hoverlabel plotly-4.4.1+dfsg.orig/plotly/graph_objs/densitymapbox/0000755000175000017500000000000013573746613022617 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/densitymapbox/hoverlabel/0000755000175000017500000000000013573746613024742 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/densitymapbox/hoverlabel/__init__.py0000644000175000017500000002547613573721546027067 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "densitymapbox.hoverlabel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Font object Sets the font used in hover labels. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.densitymapbox.hoverlabel.Font color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.densitymapbox.hoverlabel.Font constructor must be a dict or an instance of plotly.graph_objs.densitymapbox.hoverlabel.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.densitymapbox.hoverlabel import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["colorsrc"] = v_font.ColorsrcValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["familysrc"] = v_font.FamilysrcValidator() self._validators["size"] = v_font.SizeValidator() self._validators["sizesrc"] = v_font.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/densitymapbox/colorbar/0000755000175000017500000000000013573746613024422 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/densitymapbox/colorbar/title/0000755000175000017500000000000013573746613025543 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/densitymapbox/colorbar/title/__init__.py0000644000175000017500000002056313573721546027660 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "densitymapbox.colorbar.title" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Font object Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.densitymapbox.colorbar.title.Font color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.densitymapbox.colorbar.title.Font constructor must be a dict or an instance of plotly.graph_objs.densitymapbox.colorbar.title.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.densitymapbox.colorbar.title import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["size"] = v_font.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/densitymapbox/colorbar/__init__.py0000644000175000017500000006073213573721546026541 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Title(_BaseTraceHierarchyType): # font # ---- @property def font(self): """ Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.densitymapbox.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.densitymapbox.colorbar.title.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # side # ---- @property def side(self): """ Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- Any """ return self["side"] @side.setter def side(self, val): self["side"] = val # text # ---- @property def text(self): """ Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. The 'text' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["text"] @text.setter def text(self, val): self["text"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "densitymapbox.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. """ def __init__(self, arg=None, font=None, side=None, text=None, **kwargs): """ Construct a new Title object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.densitymapbox.colorbar.Title font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- Title """ super(Title, self).__init__("title") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.densitymapbox.colorbar.Title constructor must be a dict or an instance of plotly.graph_objs.densitymapbox.colorbar.Title""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.densitymapbox.colorbar import title as v_title # Initialize validators # --------------------- self._validators["font"] = v_title.FontValidator() self._validators["side"] = v_title.SideValidator() self._validators["text"] = v_title.TextValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("side", None) self["side"] = side if side is not None else _v _v = arg.pop("text", None) self["text"] = text if text is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickformatstop(_BaseTraceHierarchyType): # dtickrange # ---------- @property def dtickrange(self): """ range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" The 'dtickrange' property is an info array that may be specified as: * a list or tuple of 2 elements where: (0) The 'dtickrange[0]' property accepts values of any type (1) The 'dtickrange[1]' property accepts values of any type Returns ------- list """ return self["dtickrange"] @dtickrange.setter def dtickrange(self, val): self["dtickrange"] = val # enabled # ------- @property def enabled(self): """ Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. The 'enabled' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["enabled"] @enabled.setter def enabled(self, val): self["enabled"] = val # name # ---- @property def name(self): """ When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. The 'name' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["name"] @name.setter def name(self, val): self["name"] = val # templateitemname # ---------------- @property def templateitemname(self): """ Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. The 'templateitemname' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["templateitemname"] @templateitemname.setter def templateitemname(self, val): self["templateitemname"] = val # value # ----- @property def value(self): """ string - dtickformat for described zoom level, the same as "tickformat" The 'value' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["value"] @value.setter def value(self, val): self["value"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "densitymapbox.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" """ def __init__( self, arg=None, dtickrange=None, enabled=None, name=None, templateitemname=None, value=None, **kwargs ): """ Construct a new Tickformatstop object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.densitymapbox.colorbar.Tickformatstop dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- Tickformatstop """ super(Tickformatstop, self).__init__("tickformatstops") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.densitymapbox.colorbar.Tickformatstop constructor must be a dict or an instance of plotly.graph_objs.densitymapbox.colorbar.Tickformatstop""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.densitymapbox.colorbar import ( tickformatstop as v_tickformatstop, ) # Initialize validators # --------------------- self._validators["dtickrange"] = v_tickformatstop.DtickrangeValidator() self._validators["enabled"] = v_tickformatstop.EnabledValidator() self._validators["name"] = v_tickformatstop.NameValidator() self._validators[ "templateitemname" ] = v_tickformatstop.TemplateitemnameValidator() self._validators["value"] = v_tickformatstop.ValueValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("dtickrange", None) self["dtickrange"] = dtickrange if dtickrange is not None else _v _v = arg.pop("enabled", None) self["enabled"] = enabled if enabled is not None else _v _v = arg.pop("name", None) self["name"] = name if name is not None else _v _v = arg.pop("templateitemname", None) self["templateitemname"] = ( templateitemname if templateitemname is not None else _v ) _v = arg.pop("value", None) self["value"] = value if value is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Tickfont(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["family"] @family.setter def family(self, val): self["family"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "densitymapbox.colorbar" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size """ def __init__(self, arg=None, color=None, family=None, size=None, **kwargs): """ Construct a new Tickfont object Sets the color bar's tick label font Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.densitymapbox.colorbar.Tickfont color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- Tickfont """ super(Tickfont, self).__init__("tickfont") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.densitymapbox.colorbar.Tickfont constructor must be a dict or an instance of plotly.graph_objs.densitymapbox.colorbar.Tickfont""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.densitymapbox.colorbar import tickfont as v_tickfont # Initialize validators # --------------------- self._validators["color"] = v_tickfont.ColorValidator() self._validators["family"] = v_tickfont.FamilyValidator() self._validators["size"] = v_tickfont.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Tickfont", "Tickformatstop", "Tickformatstop", "Title", "title"] from plotly.graph_objs.densitymapbox.colorbar import title plotly-4.4.1+dfsg.orig/plotly/graph_objs/densitymapbox/__init__.py0000644000175000017500000026246413573721547024745 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Stream(_BaseTraceHierarchyType): # maxpoints # --------- @property def maxpoints(self): """ Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. The 'maxpoints' property is a number and may be specified as: - An int or float in the interval [0, 10000] Returns ------- int|float """ return self["maxpoints"] @maxpoints.setter def maxpoints(self, val): self["maxpoints"] = val # token # ----- @property def token(self): """ The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. The 'token' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["token"] @token.setter def token(self, val): self["token"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "densitymapbox" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """ def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): """ Construct a new Stream object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.densitymapbox.Stream maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- Stream """ super(Stream, self).__init__("stream") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.densitymapbox.Stream constructor must be a dict or an instance of plotly.graph_objs.densitymapbox.Stream""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.densitymapbox import stream as v_stream # Initialize validators # --------------------- self._validators["maxpoints"] = v_stream.MaxpointsValidator() self._validators["token"] = v_stream.TokenValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("maxpoints", None) self["maxpoints"] = maxpoints if maxpoints is not None else _v _v = arg.pop("token", None) self["token"] = token if token is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Hoverlabel(_BaseTraceHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'right', 'auto'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["align"] @align.setter def align(self, val): self["align"] = val # alignsrc # -------- @property def alignsrc(self): """ Sets the source reference on plot.ly for align . The 'alignsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["alignsrc"] @alignsrc.setter def alignsrc(self, val): self["alignsrc"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the hover labels for this trace The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bgcolorsrc # ---------- @property def bgcolorsrc(self): """ Sets the source reference on plot.ly for bgcolor . The 'bgcolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bgcolorsrc"] @bgcolorsrc.setter def bgcolorsrc(self, val): self["bgcolorsrc"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the border color of the hover labels for this trace. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # bordercolorsrc # -------------- @property def bordercolorsrc(self): """ Sets the source reference on plot.ly for bordercolor . The 'bordercolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bordercolorsrc"] @bordercolorsrc.setter def bordercolorsrc(self, val): self["bordercolorsrc"] = val # font # ---- @property def font(self): """ Sets the font used in hover labels. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.densitymapbox.hoverlabel.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.densitymapbox.hoverlabel.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # namelength # ---------- @property def namelength(self): """ Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. The 'namelength' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [-1, 9223372036854775807] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|numpy.ndarray """ return self["namelength"] @namelength.setter def namelength(self, val): self["namelength"] = val # namelengthsrc # ------------- @property def namelengthsrc(self): """ Sets the source reference on plot.ly for namelength . The 'namelengthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["namelengthsrc"] @namelengthsrc.setter def namelengthsrc(self, val): self["namelengthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "densitymapbox" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """ def __init__( self, arg=None, align=None, alignsrc=None, bgcolor=None, bgcolorsrc=None, bordercolor=None, bordercolorsrc=None, font=None, namelength=None, namelengthsrc=None, **kwargs ): """ Construct a new Hoverlabel object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.densitymapbox.Hoverlabel align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- Hoverlabel """ super(Hoverlabel, self).__init__("hoverlabel") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.densitymapbox.Hoverlabel constructor must be a dict or an instance of plotly.graph_objs.densitymapbox.Hoverlabel""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.densitymapbox import hoverlabel as v_hoverlabel # Initialize validators # --------------------- self._validators["align"] = v_hoverlabel.AlignValidator() self._validators["alignsrc"] = v_hoverlabel.AlignsrcValidator() self._validators["bgcolor"] = v_hoverlabel.BgcolorValidator() self._validators["bgcolorsrc"] = v_hoverlabel.BgcolorsrcValidator() self._validators["bordercolor"] = v_hoverlabel.BordercolorValidator() self._validators["bordercolorsrc"] = v_hoverlabel.BordercolorsrcValidator() self._validators["font"] = v_hoverlabel.FontValidator() self._validators["namelength"] = v_hoverlabel.NamelengthValidator() self._validators["namelengthsrc"] = v_hoverlabel.NamelengthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("alignsrc", None) self["alignsrc"] = alignsrc if alignsrc is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bgcolorsrc", None) self["bgcolorsrc"] = bgcolorsrc if bgcolorsrc is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("bordercolorsrc", None) self["bordercolorsrc"] = bordercolorsrc if bordercolorsrc is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("namelength", None) self["namelength"] = namelength if namelength is not None else _v _v = arg.pop("namelengthsrc", None) self["namelengthsrc"] = namelengthsrc if namelengthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class ColorBar(_BaseTraceHierarchyType): # bgcolor # ------- @property def bgcolor(self): """ Sets the color of padded area. The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the axis line color. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # borderwidth # ----------- @property def borderwidth(self): """ Sets the width (in px) or the border enclosing this color bar. The 'borderwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["borderwidth"] @borderwidth.setter def borderwidth(self, val): self["borderwidth"] = val # dtick # ----- @property def dtick(self): """ Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" The 'dtick' property accepts values of any type Returns ------- Any """ return self["dtick"] @dtick.setter def dtick(self, val): self["dtick"] = val # exponentformat # -------------- @property def exponentformat(self): """ Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. The 'exponentformat' property is an enumeration that may be specified as: - One of the following enumeration values: ['none', 'e', 'E', 'power', 'SI', 'B'] Returns ------- Any """ return self["exponentformat"] @exponentformat.setter def exponentformat(self, val): self["exponentformat"] = val # len # --- @property def len(self): """ Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. The 'len' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["len"] @len.setter def len(self, val): self["len"] = val # lenmode # ------- @property def lenmode(self): """ Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. The 'lenmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["lenmode"] @lenmode.setter def lenmode(self, val): self["lenmode"] = val # nticks # ------ @property def nticks(self): """ Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". The 'nticks' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["nticks"] @nticks.setter def nticks(self, val): self["nticks"] = val # outlinecolor # ------------ @property def outlinecolor(self): """ Sets the axis line color. The 'outlinecolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["outlinecolor"] @outlinecolor.setter def outlinecolor(self, val): self["outlinecolor"] = val # outlinewidth # ------------ @property def outlinewidth(self): """ Sets the width (in px) of the axis line. The 'outlinewidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["outlinewidth"] @outlinewidth.setter def outlinewidth(self, val): self["outlinewidth"] = val # separatethousands # ----------------- @property def separatethousands(self): """ If "true", even 4-digit integers are separated The 'separatethousands' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["separatethousands"] @separatethousands.setter def separatethousands(self, val): self["separatethousands"] = val # showexponent # ------------ @property def showexponent(self): """ If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. The 'showexponent' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showexponent"] @showexponent.setter def showexponent(self, val): self["showexponent"] = val # showticklabels # -------------- @property def showticklabels(self): """ Determines whether or not the tick labels are drawn. The 'showticklabels' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showticklabels"] @showticklabels.setter def showticklabels(self, val): self["showticklabels"] = val # showtickprefix # -------------- @property def showtickprefix(self): """ If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. The 'showtickprefix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showtickprefix"] @showtickprefix.setter def showtickprefix(self, val): self["showtickprefix"] = val # showticksuffix # -------------- @property def showticksuffix(self): """ Same as `showtickprefix` but for tick suffixes. The 'showticksuffix' property is an enumeration that may be specified as: - One of the following enumeration values: ['all', 'first', 'last', 'none'] Returns ------- Any """ return self["showticksuffix"] @showticksuffix.setter def showticksuffix(self, val): self["showticksuffix"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # thicknessmode # ------------- @property def thicknessmode(self): """ Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. The 'thicknessmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['fraction', 'pixels'] Returns ------- Any """ return self["thicknessmode"] @thicknessmode.setter def thicknessmode(self, val): self["thicknessmode"] = val # tick0 # ----- @property def tick0(self): """ Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. The 'tick0' property accepts values of any type Returns ------- Any """ return self["tick0"] @tick0.setter def tick0(self, val): self["tick0"] = val # tickangle # --------- @property def tickangle(self): """ Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. The 'tickangle' property is a angle (in degrees) that may be specified as a number between -180 and 180. Numeric values outside this range are converted to the equivalent value (e.g. 270 is converted to -90). Returns ------- int|float """ return self["tickangle"] @tickangle.setter def tickangle(self, val): self["tickangle"] = val # tickcolor # --------- @property def tickcolor(self): """ Sets the tick color. The 'tickcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["tickcolor"] @tickcolor.setter def tickcolor(self, val): self["tickcolor"] = val # tickfont # -------- @property def tickfont(self): """ Sets the color bar's tick label font The 'tickfont' property is an instance of Tickfont that may be specified as: - An instance of plotly.graph_objs.densitymapbox.colorbar.Tickfont - A dict of string/value properties that will be passed to the Tickfont constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- plotly.graph_objs.densitymapbox.colorbar.Tickfont """ return self["tickfont"] @tickfont.setter def tickfont(self, val): self["tickfont"] = val # tickformat # ---------- @property def tickformat(self): """ Sets the tick label formatting rule using d3 formatting mini- languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" The 'tickformat' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickformat"] @tickformat.setter def tickformat(self, val): self["tickformat"] = val # tickformatstops # --------------- @property def tickformatstops(self): """ The 'tickformatstops' property is a tuple of instances of Tickformatstop that may be specified as: - A list or tuple of instances of plotly.graph_objs.densitymapbox.colorbar.Tickformatstop - A list or tuple of dicts of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: dtickrange range [*min*, *max*], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null" enabled Determines whether or not this stop is used. If `false`, this stop is ignored even within its `dtickrange`. name When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: false` or `enabled: false` to hide it). Has no effect outside of a template. templateitemname Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: false` or `enabled: false` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: true`. value string - dtickformat for described zoom level, the same as "tickformat" Returns ------- tuple[plotly.graph_objs.densitymapbox.colorbar.Tickformatstop] """ return self["tickformatstops"] @tickformatstops.setter def tickformatstops(self, val): self["tickformatstops"] = val # tickformatstopdefaults # ---------------------- @property def tickformatstopdefaults(self): """ When used in a template (as layout.template.data.densitymapbox. colorbar.tickformatstopdefaults), sets the default property values to use for elements of densitymapbox.colorbar.tickformatstops The 'tickformatstopdefaults' property is an instance of Tickformatstop that may be specified as: - An instance of plotly.graph_objs.densitymapbox.colorbar.Tickformatstop - A dict of string/value properties that will be passed to the Tickformatstop constructor Supported dict properties: Returns ------- plotly.graph_objs.densitymapbox.colorbar.Tickformatstop """ return self["tickformatstopdefaults"] @tickformatstopdefaults.setter def tickformatstopdefaults(self, val): self["tickformatstopdefaults"] = val # ticklen # ------- @property def ticklen(self): """ Sets the tick length (in px). The 'ticklen' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ticklen"] @ticklen.setter def ticklen(self, val): self["ticklen"] = val # tickmode # -------- @property def tickmode(self): """ Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). The 'tickmode' property is an enumeration that may be specified as: - One of the following enumeration values: ['auto', 'linear', 'array'] Returns ------- Any """ return self["tickmode"] @tickmode.setter def tickmode(self, val): self["tickmode"] = val # tickprefix # ---------- @property def tickprefix(self): """ Sets a tick label prefix. The 'tickprefix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["tickprefix"] @tickprefix.setter def tickprefix(self, val): self["tickprefix"] = val # ticks # ----- @property def ticks(self): """ Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. The 'ticks' property is an enumeration that may be specified as: - One of the following enumeration values: ['outside', 'inside', ''] Returns ------- Any """ return self["ticks"] @ticks.setter def ticks(self, val): self["ticks"] = val # ticksuffix # ---------- @property def ticksuffix(self): """ Sets a tick label suffix. The 'ticksuffix' property is a string and must be specified as: - A string - A number that will be converted to a string Returns ------- str """ return self["ticksuffix"] @ticksuffix.setter def ticksuffix(self, val): self["ticksuffix"] = val # ticktext # -------- @property def ticktext(self): """ Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. The 'ticktext' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["ticktext"] @ticktext.setter def ticktext(self, val): self["ticktext"] = val # ticktextsrc # ----------- @property def ticktextsrc(self): """ Sets the source reference on plot.ly for ticktext . The 'ticktextsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["ticktextsrc"] @ticktextsrc.setter def ticktextsrc(self, val): self["ticktextsrc"] = val # tickvals # -------- @property def tickvals(self): """ Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. The 'tickvals' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["tickvals"] @tickvals.setter def tickvals(self, val): self["tickvals"] = val # tickvalssrc # ----------- @property def tickvalssrc(self): """ Sets the source reference on plot.ly for tickvals . The 'tickvalssrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["tickvalssrc"] @tickvalssrc.setter def tickvalssrc(self, val): self["tickvalssrc"] = val # tickwidth # --------- @property def tickwidth(self): """ Sets the tick width (in px). The 'tickwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["tickwidth"] @tickwidth.setter def tickwidth(self, val): self["tickwidth"] = val # title # ----- @property def title(self): """ The 'title' property is an instance of Title that may be specified as: - An instance of plotly.graph_objs.densitymapbox.colorbar.Title - A dict of string/value properties that will be passed to the Title constructor Supported dict properties: font Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. side Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. text Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated. Returns ------- plotly.graph_objs.densitymapbox.colorbar.Title """ return self["title"] @title.setter def title(self, val): self["title"] = val # titlefont # --------- @property def titlefont(self): """ Deprecated: Please use densitymapbox.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.densitymapbox.colorbar.title.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". size Returns ------- """ return self["titlefont"] @titlefont.setter def titlefont(self, val): self["titlefont"] = val # titleside # --------- @property def titleside(self): """ Deprecated: Please use densitymapbox.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. The 'side' property is an enumeration that may be specified as: - One of the following enumeration values: ['right', 'top', 'bottom'] Returns ------- """ return self["titleside"] @titleside.setter def titleside(self, val): self["titleside"] = val # x # - @property def x(self): """ Sets the x position of the color bar (in plot fraction). The 'x' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["x"] @x.setter def x(self, val): self["x"] = val # xanchor # ------- @property def xanchor(self): """ Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. The 'xanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'center', 'right'] Returns ------- Any """ return self["xanchor"] @xanchor.setter def xanchor(self, val): self["xanchor"] = val # xpad # ---- @property def xpad(self): """ Sets the amount of padding (in px) along the x direction. The 'xpad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["xpad"] @xpad.setter def xpad(self, val): self["xpad"] = val # y # - @property def y(self): """ Sets the y position of the color bar (in plot fraction). The 'y' property is a number and may be specified as: - An int or float in the interval [-2, 3] Returns ------- int|float """ return self["y"] @y.setter def y(self, val): self["y"] = val # yanchor # ------- @property def yanchor(self): """ Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. The 'yanchor' property is an enumeration that may be specified as: - One of the following enumeration values: ['top', 'middle', 'bottom'] Returns ------- Any """ return self["yanchor"] @yanchor.setter def yanchor(self, val): self["yanchor"] = val # ypad # ---- @property def ypad(self): """ Sets the amount of padding (in px) along the y direction. The 'ypad' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["ypad"] @ypad.setter def ypad(self, val): self["ypad"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "densitymapbox" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.densitymapbox.colorbar. Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.densit ymapbox.colorbar.tickformatstopdefaults), sets the default property values to use for elements of densitymapbox.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.densitymapbox.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use densitymapbox.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use densitymapbox.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """ _mapped_properties = { "titlefont": ("title", "font"), "titleside": ("title", "side"), } def __init__( self, arg=None, bgcolor=None, bordercolor=None, borderwidth=None, dtick=None, exponentformat=None, len=None, lenmode=None, nticks=None, outlinecolor=None, outlinewidth=None, separatethousands=None, showexponent=None, showticklabels=None, showtickprefix=None, showticksuffix=None, thickness=None, thicknessmode=None, tick0=None, tickangle=None, tickcolor=None, tickfont=None, tickformat=None, tickformatstops=None, tickformatstopdefaults=None, ticklen=None, tickmode=None, tickprefix=None, ticks=None, ticksuffix=None, ticktext=None, ticktextsrc=None, tickvals=None, tickvalssrc=None, tickwidth=None, title=None, titlefont=None, titleside=None, x=None, xanchor=None, xpad=None, y=None, yanchor=None, ypad=None, **kwargs ): """ Construct a new ColorBar object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.densitymapbox.ColorBar bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of plotly.graph_objects.densitymapbox.colorbar. Tickformatstop instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.data.densit ymapbox.colorbar.tickformatstopdefaults), sets the default property values to use for elements of densitymapbox.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title plotly.graph_objects.densitymapbox.colorbar.Title instance or dict with compatible properties titlefont Deprecated: Please use densitymapbox.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use densitymapbox.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- ColorBar """ super(ColorBar, self).__init__("colorbar") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.densitymapbox.ColorBar constructor must be a dict or an instance of plotly.graph_objs.densitymapbox.ColorBar""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.densitymapbox import colorbar as v_colorbar # Initialize validators # --------------------- self._validators["bgcolor"] = v_colorbar.BgcolorValidator() self._validators["bordercolor"] = v_colorbar.BordercolorValidator() self._validators["borderwidth"] = v_colorbar.BorderwidthValidator() self._validators["dtick"] = v_colorbar.DtickValidator() self._validators["exponentformat"] = v_colorbar.ExponentformatValidator() self._validators["len"] = v_colorbar.LenValidator() self._validators["lenmode"] = v_colorbar.LenmodeValidator() self._validators["nticks"] = v_colorbar.NticksValidator() self._validators["outlinecolor"] = v_colorbar.OutlinecolorValidator() self._validators["outlinewidth"] = v_colorbar.OutlinewidthValidator() self._validators["separatethousands"] = v_colorbar.SeparatethousandsValidator() self._validators["showexponent"] = v_colorbar.ShowexponentValidator() self._validators["showticklabels"] = v_colorbar.ShowticklabelsValidator() self._validators["showtickprefix"] = v_colorbar.ShowtickprefixValidator() self._validators["showticksuffix"] = v_colorbar.ShowticksuffixValidator() self._validators["thickness"] = v_colorbar.ThicknessValidator() self._validators["thicknessmode"] = v_colorbar.ThicknessmodeValidator() self._validators["tick0"] = v_colorbar.Tick0Validator() self._validators["tickangle"] = v_colorbar.TickangleValidator() self._validators["tickcolor"] = v_colorbar.TickcolorValidator() self._validators["tickfont"] = v_colorbar.TickfontValidator() self._validators["tickformat"] = v_colorbar.TickformatValidator() self._validators["tickformatstops"] = v_colorbar.TickformatstopsValidator() self._validators[ "tickformatstopdefaults" ] = v_colorbar.TickformatstopValidator() self._validators["ticklen"] = v_colorbar.TicklenValidator() self._validators["tickmode"] = v_colorbar.TickmodeValidator() self._validators["tickprefix"] = v_colorbar.TickprefixValidator() self._validators["ticks"] = v_colorbar.TicksValidator() self._validators["ticksuffix"] = v_colorbar.TicksuffixValidator() self._validators["ticktext"] = v_colorbar.TicktextValidator() self._validators["ticktextsrc"] = v_colorbar.TicktextsrcValidator() self._validators["tickvals"] = v_colorbar.TickvalsValidator() self._validators["tickvalssrc"] = v_colorbar.TickvalssrcValidator() self._validators["tickwidth"] = v_colorbar.TickwidthValidator() self._validators["title"] = v_colorbar.TitleValidator() self._validators["x"] = v_colorbar.XValidator() self._validators["xanchor"] = v_colorbar.XanchorValidator() self._validators["xpad"] = v_colorbar.XpadValidator() self._validators["y"] = v_colorbar.YValidator() self._validators["yanchor"] = v_colorbar.YanchorValidator() self._validators["ypad"] = v_colorbar.YpadValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("borderwidth", None) self["borderwidth"] = borderwidth if borderwidth is not None else _v _v = arg.pop("dtick", None) self["dtick"] = dtick if dtick is not None else _v _v = arg.pop("exponentformat", None) self["exponentformat"] = exponentformat if exponentformat is not None else _v _v = arg.pop("len", None) self["len"] = len if len is not None else _v _v = arg.pop("lenmode", None) self["lenmode"] = lenmode if lenmode is not None else _v _v = arg.pop("nticks", None) self["nticks"] = nticks if nticks is not None else _v _v = arg.pop("outlinecolor", None) self["outlinecolor"] = outlinecolor if outlinecolor is not None else _v _v = arg.pop("outlinewidth", None) self["outlinewidth"] = outlinewidth if outlinewidth is not None else _v _v = arg.pop("separatethousands", None) self["separatethousands"] = ( separatethousands if separatethousands is not None else _v ) _v = arg.pop("showexponent", None) self["showexponent"] = showexponent if showexponent is not None else _v _v = arg.pop("showticklabels", None) self["showticklabels"] = showticklabels if showticklabels is not None else _v _v = arg.pop("showtickprefix", None) self["showtickprefix"] = showtickprefix if showtickprefix is not None else _v _v = arg.pop("showticksuffix", None) self["showticksuffix"] = showticksuffix if showticksuffix is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("thicknessmode", None) self["thicknessmode"] = thicknessmode if thicknessmode is not None else _v _v = arg.pop("tick0", None) self["tick0"] = tick0 if tick0 is not None else _v _v = arg.pop("tickangle", None) self["tickangle"] = tickangle if tickangle is not None else _v _v = arg.pop("tickcolor", None) self["tickcolor"] = tickcolor if tickcolor is not None else _v _v = arg.pop("tickfont", None) self["tickfont"] = tickfont if tickfont is not None else _v _v = arg.pop("tickformat", None) self["tickformat"] = tickformat if tickformat is not None else _v _v = arg.pop("tickformatstops", None) self["tickformatstops"] = tickformatstops if tickformatstops is not None else _v _v = arg.pop("tickformatstopdefaults", None) self["tickformatstopdefaults"] = ( tickformatstopdefaults if tickformatstopdefaults is not None else _v ) _v = arg.pop("ticklen", None) self["ticklen"] = ticklen if ticklen is not None else _v _v = arg.pop("tickmode", None) self["tickmode"] = tickmode if tickmode is not None else _v _v = arg.pop("tickprefix", None) self["tickprefix"] = tickprefix if tickprefix is not None else _v _v = arg.pop("ticks", None) self["ticks"] = ticks if ticks is not None else _v _v = arg.pop("ticksuffix", None) self["ticksuffix"] = ticksuffix if ticksuffix is not None else _v _v = arg.pop("ticktext", None) self["ticktext"] = ticktext if ticktext is not None else _v _v = arg.pop("ticktextsrc", None) self["ticktextsrc"] = ticktextsrc if ticktextsrc is not None else _v _v = arg.pop("tickvals", None) self["tickvals"] = tickvals if tickvals is not None else _v _v = arg.pop("tickvalssrc", None) self["tickvalssrc"] = tickvalssrc if tickvalssrc is not None else _v _v = arg.pop("tickwidth", None) self["tickwidth"] = tickwidth if tickwidth is not None else _v _v = arg.pop("title", None) self["title"] = title if title is not None else _v _v = arg.pop("titlefont", None) _v = titlefont if titlefont is not None else _v if _v is not None: self["titlefont"] = _v _v = arg.pop("titleside", None) _v = titleside if titleside is not None else _v if _v is not None: self["titleside"] = _v _v = arg.pop("x", None) self["x"] = x if x is not None else _v _v = arg.pop("xanchor", None) self["xanchor"] = xanchor if xanchor is not None else _v _v = arg.pop("xpad", None) self["xpad"] = xpad if xpad is not None else _v _v = arg.pop("y", None) self["y"] = y if y is not None else _v _v = arg.pop("yanchor", None) self["yanchor"] = yanchor if yanchor is not None else _v _v = arg.pop("ypad", None) self["ypad"] = ypad if ypad is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["ColorBar", "Hoverlabel", "Stream", "colorbar", "hoverlabel"] from plotly.graph_objs.densitymapbox import hoverlabel from plotly.graph_objs.densitymapbox import colorbar plotly-4.4.1+dfsg.orig/plotly/graph_objs/box/0000755000175000017500000000000013573746613020521 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/box/unselected/0000755000175000017500000000000013573746613022654 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/box/unselected/__init__.py0000644000175000017500000001541713573721545024772 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the marker color of unselected points, applied only when a selection exists. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # opacity # ------- @property def opacity(self): """ Sets the marker opacity of unselected points, applied only when a selection exists. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # size # ---- @property def size(self): """ Sets the marker size of unselected points, applied only when a selection exists. The 'size' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "box.unselected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. size Sets the marker size of unselected points, applied only when a selection exists. """ def __init__(self, arg=None, color=None, opacity=None, size=None, **kwargs): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.box.unselected.Marker color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. size Sets the marker size of unselected points, applied only when a selection exists. Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.box.unselected.Marker constructor must be a dict or an instance of plotly.graph_objs.box.unselected.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.box.unselected import marker as v_marker # Initialize validators # --------------------- self._validators["color"] = v_marker.ColorValidator() self._validators["opacity"] = v_marker.OpacityValidator() self._validators["size"] = v_marker.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Marker"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/box/hoverlabel/0000755000175000017500000000000013573746613022644 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/box/hoverlabel/__init__.py0000644000175000017500000002540013573721545024753 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "box.hoverlabel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Font object Sets the font used in hover labels. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.box.hoverlabel.Font color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.box.hoverlabel.Font constructor must be a dict or an instance of plotly.graph_objs.box.hoverlabel.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.box.hoverlabel import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["colorsrc"] = v_font.ColorsrcValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["familysrc"] = v_font.FamilysrcValidator() self._validators["size"] = v_font.SizeValidator() self._validators["sizesrc"] = v_font.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/box/marker/0000755000175000017500000000000013573746613022002 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/box/marker/__init__.py0000644000175000017500000002506513573721545024120 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # outliercolor # ------------ @property def outliercolor(self): """ Sets the border line color of the outlier sample points. Defaults to marker.color The 'outliercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["outliercolor"] @outliercolor.setter def outliercolor(self, val): self["outliercolor"] = val # outlierwidth # ------------ @property def outlierwidth(self): """ Sets the border line width (in px) of the outlier sample points. The 'outlierwidth' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["outlierwidth"] @outlierwidth.setter def outlierwidth(self, val): self["outlierwidth"] = val # width # ----- @property def width(self): """ Sets the width (in px) of the lines bounding the marker points. The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "box.marker" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. outliercolor Sets the border line color of the outlier sample points. Defaults to marker.color outlierwidth Sets the border line width (in px) of the outlier sample points. width Sets the width (in px) of the lines bounding the marker points. """ def __init__( self, arg=None, color=None, outliercolor=None, outlierwidth=None, width=None, **kwargs ): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.box.marker.Line color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. outliercolor Sets the border line color of the outlier sample points. Defaults to marker.color outlierwidth Sets the border line width (in px) of the outlier sample points. width Sets the width (in px) of the lines bounding the marker points. Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.box.marker.Line constructor must be a dict or an instance of plotly.graph_objs.box.marker.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.box.marker import line as v_line # Initialize validators # --------------------- self._validators["color"] = v_line.ColorValidator() self._validators["outliercolor"] = v_line.OutliercolorValidator() self._validators["outlierwidth"] = v_line.OutlierwidthValidator() self._validators["width"] = v_line.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("outliercolor", None) self["outliercolor"] = outliercolor if outliercolor is not None else _v _v = arg.pop("outlierwidth", None) self["outlierwidth"] = outlierwidth if outlierwidth is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Line"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/box/__init__.py0000644000175000017500000014470013573721546022636 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Unselected(_BaseTraceHierarchyType): # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.box.unselected.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. size Sets the marker size of unselected points, applied only when a selection exists. Returns ------- plotly.graph_objs.box.unselected.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "box" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ marker plotly.graph_objects.box.unselected.Marker instance or dict with compatible properties """ def __init__(self, arg=None, marker=None, **kwargs): """ Construct a new Unselected object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.box.Unselected marker plotly.graph_objects.box.unselected.Marker instance or dict with compatible properties Returns ------- Unselected """ super(Unselected, self).__init__("unselected") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.box.Unselected constructor must be a dict or an instance of plotly.graph_objs.box.Unselected""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.box import unselected as v_unselected # Initialize validators # --------------------- self._validators["marker"] = v_unselected.MarkerValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Stream(_BaseTraceHierarchyType): # maxpoints # --------- @property def maxpoints(self): """ Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. The 'maxpoints' property is a number and may be specified as: - An int or float in the interval [0, 10000] Returns ------- int|float """ return self["maxpoints"] @maxpoints.setter def maxpoints(self, val): self["maxpoints"] = val # token # ----- @property def token(self): """ The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. The 'token' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["token"] @token.setter def token(self, val): self["token"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "box" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """ def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): """ Construct a new Stream object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.box.Stream maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- Stream """ super(Stream, self).__init__("stream") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.box.Stream constructor must be a dict or an instance of plotly.graph_objs.box.Stream""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.box import stream as v_stream # Initialize validators # --------------------- self._validators["maxpoints"] = v_stream.MaxpointsValidator() self._validators["token"] = v_stream.TokenValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("maxpoints", None) self["maxpoints"] = maxpoints if maxpoints is not None else _v _v = arg.pop("token", None) self["token"] = token if token is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Selected(_BaseTraceHierarchyType): # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.box.selected.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. size Sets the marker size of selected points. Returns ------- plotly.graph_objs.box.selected.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "box" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ marker plotly.graph_objects.box.selected.Marker instance or dict with compatible properties """ def __init__(self, arg=None, marker=None, **kwargs): """ Construct a new Selected object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.box.Selected marker plotly.graph_objects.box.selected.Marker instance or dict with compatible properties Returns ------- Selected """ super(Selected, self).__init__("selected") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.box.Selected constructor must be a dict or an instance of plotly.graph_objs.box.Selected""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.box import selected as v_selected # Initialize validators # --------------------- self._validators["marker"] = v_selected.MarkerValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of plotly.graph_objs.box.marker.Line - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. outliercolor Sets the border line color of the outlier sample points. Defaults to marker.color outlierwidth Sets the border line width (in px) of the outlier sample points. width Sets the width (in px) of the lines bounding the marker points. Returns ------- plotly.graph_objs.box.marker.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # opacity # ------- @property def opacity(self): """ Sets the marker opacity. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # outliercolor # ------------ @property def outliercolor(self): """ Sets the color of the outlier sample points. The 'outliercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["outliercolor"] @outliercolor.setter def outliercolor(self, val): self["outliercolor"] = val # size # ---- @property def size(self): """ Sets the marker size (in px). The 'size' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # symbol # ------ @property def symbol(self): """ Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot-open" to a symbol name. The 'symbol' property is an enumeration that may be specified as: - One of the following enumeration values: [0, 'circle', 100, 'circle-open', 200, 'circle-dot', 300, 'circle-open-dot', 1, 'square', 101, 'square-open', 201, 'square-dot', 301, 'square-open-dot', 2, 'diamond', 102, 'diamond-open', 202, 'diamond-dot', 302, 'diamond-open-dot', 3, 'cross', 103, 'cross-open', 203, 'cross-dot', 303, 'cross-open-dot', 4, 'x', 104, 'x-open', 204, 'x-dot', 304, 'x-open-dot', 5, 'triangle-up', 105, 'triangle-up-open', 205, 'triangle-up-dot', 305, 'triangle-up-open-dot', 6, 'triangle-down', 106, 'triangle-down-open', 206, 'triangle-down-dot', 306, 'triangle-down-open-dot', 7, 'triangle-left', 107, 'triangle-left-open', 207, 'triangle-left-dot', 307, 'triangle-left-open-dot', 8, 'triangle-right', 108, 'triangle-right-open', 208, 'triangle-right-dot', 308, 'triangle-right-open-dot', 9, 'triangle-ne', 109, 'triangle-ne-open', 209, 'triangle-ne-dot', 309, 'triangle-ne-open-dot', 10, 'triangle-se', 110, 'triangle-se-open', 210, 'triangle-se-dot', 310, 'triangle-se-open-dot', 11, 'triangle-sw', 111, 'triangle-sw-open', 211, 'triangle-sw-dot', 311, 'triangle-sw-open-dot', 12, 'triangle-nw', 112, 'triangle-nw-open', 212, 'triangle-nw-dot', 312, 'triangle-nw-open-dot', 13, 'pentagon', 113, 'pentagon-open', 213, 'pentagon-dot', 313, 'pentagon-open-dot', 14, 'hexagon', 114, 'hexagon-open', 214, 'hexagon-dot', 314, 'hexagon-open-dot', 15, 'hexagon2', 115, 'hexagon2-open', 215, 'hexagon2-dot', 315, 'hexagon2-open-dot', 16, 'octagon', 116, 'octagon-open', 216, 'octagon-dot', 316, 'octagon-open-dot', 17, 'star', 117, 'star-open', 217, 'star-dot', 317, 'star-open-dot', 18, 'hexagram', 118, 'hexagram-open', 218, 'hexagram-dot', 318, 'hexagram-open-dot', 19, 'star-triangle-up', 119, 'star-triangle-up-open', 219, 'star-triangle-up-dot', 319, 'star-triangle-up-open-dot', 20, 'star-triangle-down', 120, 'star-triangle-down-open', 220, 'star-triangle-down-dot', 320, 'star-triangle-down-open-dot', 21, 'star-square', 121, 'star-square-open', 221, 'star-square-dot', 321, 'star-square-open-dot', 22, 'star-diamond', 122, 'star-diamond-open', 222, 'star-diamond-dot', 322, 'star-diamond-open-dot', 23, 'diamond-tall', 123, 'diamond-tall-open', 223, 'diamond-tall-dot', 323, 'diamond-tall-open-dot', 24, 'diamond-wide', 124, 'diamond-wide-open', 224, 'diamond-wide-dot', 324, 'diamond-wide-open-dot', 25, 'hourglass', 125, 'hourglass-open', 26, 'bowtie', 126, 'bowtie-open', 27, 'circle-cross', 127, 'circle-cross-open', 28, 'circle-x', 128, 'circle-x-open', 29, 'square-cross', 129, 'square-cross-open', 30, 'square-x', 130, 'square-x-open', 31, 'diamond-cross', 131, 'diamond-cross-open', 32, 'diamond-x', 132, 'diamond-x-open', 33, 'cross-thin', 133, 'cross-thin-open', 34, 'x-thin', 134, 'x-thin-open', 35, 'asterisk', 135, 'asterisk-open', 36, 'hash', 136, 'hash-open', 236, 'hash-dot', 336, 'hash-open-dot', 37, 'y-up', 137, 'y-up-open', 38, 'y-down', 138, 'y-down-open', 39, 'y-left', 139, 'y-left-open', 40, 'y-right', 140, 'y-right-open', 41, 'line-ew', 141, 'line-ew-open', 42, 'line-ns', 142, 'line-ns-open', 43, 'line-ne', 143, 'line-ne-open', 44, 'line-nw', 144, 'line-nw-open'] Returns ------- Any """ return self["symbol"] @symbol.setter def symbol(self, val): self["symbol"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "box" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. line plotly.graph_objects.box.marker.Line instance or dict with compatible properties opacity Sets the marker opacity. outliercolor Sets the color of the outlier sample points. size Sets the marker size (in px). symbol Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot- open" to a symbol name. """ def __init__( self, arg=None, color=None, line=None, opacity=None, outliercolor=None, size=None, symbol=None, **kwargs ): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.box.Marker color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. line plotly.graph_objects.box.marker.Line instance or dict with compatible properties opacity Sets the marker opacity. outliercolor Sets the color of the outlier sample points. size Sets the marker size (in px). symbol Sets the marker symbol type. Adding 100 is equivalent to appending "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot- open" to a symbol name. Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.box.Marker constructor must be a dict or an instance of plotly.graph_objs.box.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.box import marker as v_marker # Initialize validators # --------------------- self._validators["color"] = v_marker.ColorValidator() self._validators["line"] = v_marker.LineValidator() self._validators["opacity"] = v_marker.OpacityValidator() self._validators["outliercolor"] = v_marker.OutliercolorValidator() self._validators["size"] = v_marker.SizeValidator() self._validators["symbol"] = v_marker.SymbolValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("outliercolor", None) self["outliercolor"] = outliercolor if outliercolor is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("symbol", None) self["symbol"] = symbol if symbol is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Line(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the color of line bounding the box(es). The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # width # ----- @property def width(self): """ Sets the width (in px) of line bounding the box(es). The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "box" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the color of line bounding the box(es). width Sets the width (in px) of line bounding the box(es). """ def __init__(self, arg=None, color=None, width=None, **kwargs): """ Construct a new Line object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.box.Line color Sets the color of line bounding the box(es). width Sets the width (in px) of line bounding the box(es). Returns ------- Line """ super(Line, self).__init__("line") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.box.Line constructor must be a dict or an instance of plotly.graph_objs.box.Line""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.box import line as v_line # Initialize validators # --------------------- self._validators["color"] = v_line.ColorValidator() self._validators["width"] = v_line.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Hoverlabel(_BaseTraceHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'right', 'auto'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["align"] @align.setter def align(self, val): self["align"] = val # alignsrc # -------- @property def alignsrc(self): """ Sets the source reference on plot.ly for align . The 'alignsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["alignsrc"] @alignsrc.setter def alignsrc(self, val): self["alignsrc"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the hover labels for this trace The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bgcolorsrc # ---------- @property def bgcolorsrc(self): """ Sets the source reference on plot.ly for bgcolor . The 'bgcolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bgcolorsrc"] @bgcolorsrc.setter def bgcolorsrc(self, val): self["bgcolorsrc"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the border color of the hover labels for this trace. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # bordercolorsrc # -------------- @property def bordercolorsrc(self): """ Sets the source reference on plot.ly for bordercolor . The 'bordercolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bordercolorsrc"] @bordercolorsrc.setter def bordercolorsrc(self, val): self["bordercolorsrc"] = val # font # ---- @property def font(self): """ Sets the font used in hover labels. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.box.hoverlabel.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.box.hoverlabel.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # namelength # ---------- @property def namelength(self): """ Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. The 'namelength' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [-1, 9223372036854775807] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|numpy.ndarray """ return self["namelength"] @namelength.setter def namelength(self, val): self["namelength"] = val # namelengthsrc # ------------- @property def namelengthsrc(self): """ Sets the source reference on plot.ly for namelength . The 'namelengthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["namelengthsrc"] @namelengthsrc.setter def namelengthsrc(self, val): self["namelengthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "box" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """ def __init__( self, arg=None, align=None, alignsrc=None, bgcolor=None, bgcolorsrc=None, bordercolor=None, bordercolorsrc=None, font=None, namelength=None, namelengthsrc=None, **kwargs ): """ Construct a new Hoverlabel object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.box.Hoverlabel align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- Hoverlabel """ super(Hoverlabel, self).__init__("hoverlabel") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.box.Hoverlabel constructor must be a dict or an instance of plotly.graph_objs.box.Hoverlabel""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.box import hoverlabel as v_hoverlabel # Initialize validators # --------------------- self._validators["align"] = v_hoverlabel.AlignValidator() self._validators["alignsrc"] = v_hoverlabel.AlignsrcValidator() self._validators["bgcolor"] = v_hoverlabel.BgcolorValidator() self._validators["bgcolorsrc"] = v_hoverlabel.BgcolorsrcValidator() self._validators["bordercolor"] = v_hoverlabel.BordercolorValidator() self._validators["bordercolorsrc"] = v_hoverlabel.BordercolorsrcValidator() self._validators["font"] = v_hoverlabel.FontValidator() self._validators["namelength"] = v_hoverlabel.NamelengthValidator() self._validators["namelengthsrc"] = v_hoverlabel.NamelengthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("alignsrc", None) self["alignsrc"] = alignsrc if alignsrc is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bgcolorsrc", None) self["bgcolorsrc"] = bgcolorsrc if bgcolorsrc is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("bordercolorsrc", None) self["bordercolorsrc"] = bordercolorsrc if bordercolorsrc is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("namelength", None) self["namelength"] = namelength if namelength is not None else _v _v = arg.pop("namelengthsrc", None) self["namelengthsrc"] = namelengthsrc if namelengthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = [ "Hoverlabel", "Line", "Marker", "Selected", "Stream", "Unselected", "hoverlabel", "marker", "selected", "unselected", ] from plotly.graph_objs.box import unselected from plotly.graph_objs.box import selected from plotly.graph_objs.box import marker from plotly.graph_objs.box import hoverlabel plotly-4.4.1+dfsg.orig/plotly/graph_objs/box/selected/0000755000175000017500000000000013573746613022311 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/box/selected/__init__.py0000644000175000017500000001447513573721545024432 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ Sets the marker color of selected points. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # opacity # ------- @property def opacity(self): """ Sets the marker opacity of selected points. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] Returns ------- int|float """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # size # ---- @property def size(self): """ Sets the marker size of selected points. The 'size' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["size"] @size.setter def size(self, val): self["size"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "box.selected" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. size Sets the marker size of selected points. """ def __init__(self, arg=None, color=None, opacity=None, size=None, **kwargs): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.box.selected.Marker color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. size Sets the marker size of selected points. Returns ------- Marker """ super(Marker, self).__init__("marker") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.box.selected.Marker constructor must be a dict or an instance of plotly.graph_objs.box.selected.Marker""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.box.selected import marker as v_marker # Initialize validators # --------------------- self._validators["color"] = v_marker.ColorValidator() self._validators["opacity"] = v_marker.OpacityValidator() self._validators["size"] = v_marker.SizeValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Marker"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/image/0000755000175000017500000000000013573746613021013 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/image/hoverlabel/0000755000175000017500000000000013573746613023136 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/graph_objs/image/hoverlabel/__init__.py0000644000175000017500000002541213573721546025251 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Font(_BaseTraceHierarchyType): # color # ----- @property def color(self): """ The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # family # ------ @property def family(self): """ HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on- premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". The 'family' property is a string and must be specified as: - A non-empty string - A tuple, list, or one-dimensional numpy array of the above Returns ------- str|numpy.ndarray """ return self["family"] @family.setter def family(self, val): self["family"] = val # familysrc # --------- @property def familysrc(self): """ Sets the source reference on plot.ly for family . The 'familysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["familysrc"] @familysrc.setter def familysrc(self, val): self["familysrc"] = val # size # ---- @property def size(self): """ The 'size' property is a number and may be specified as: - An int or float in the interval [1, inf] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["size"] @size.setter def size(self, val): self["size"] = val # sizesrc # ------- @property def sizesrc(self): """ Sets the source reference on plot.ly for size . The 'sizesrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["sizesrc"] @sizesrc.setter def sizesrc(self, val): self["sizesrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "image.hoverlabel" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . """ def __init__( self, arg=None, color=None, colorsrc=None, family=None, familysrc=None, size=None, sizesrc=None, **kwargs ): """ Construct a new Font object Sets the font used in hover labels. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.image.hoverlabel.Font color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- Font """ super(Font, self).__init__("font") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.image.hoverlabel.Font constructor must be a dict or an instance of plotly.graph_objs.image.hoverlabel.Font""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.image.hoverlabel import font as v_font # Initialize validators # --------------------- self._validators["color"] = v_font.ColorValidator() self._validators["colorsrc"] = v_font.ColorsrcValidator() self._validators["family"] = v_font.FamilyValidator() self._validators["familysrc"] = v_font.FamilysrcValidator() self._validators["size"] = v_font.SizeValidator() self._validators["sizesrc"] = v_font.SizesrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("family", None) self["family"] = family if family is not None else _v _v = arg.pop("familysrc", None) self["familysrc"] = familysrc if familysrc is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("sizesrc", None) self["sizesrc"] = sizesrc if sizesrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Font"] plotly-4.4.1+dfsg.orig/plotly/graph_objs/image/__init__.py0000644000175000017500000005235013573721546023127 0ustar noahfxnoahfxfrom plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Stream(_BaseTraceHierarchyType): # maxpoints # --------- @property def maxpoints(self): """ Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. The 'maxpoints' property is a number and may be specified as: - An int or float in the interval [0, 10000] Returns ------- int|float """ return self["maxpoints"] @maxpoints.setter def maxpoints(self, val): self["maxpoints"] = val # token # ----- @property def token(self): """ The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. The 'token' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["token"] @token.setter def token(self, val): self["token"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "image" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """ def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): """ Construct a new Stream object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.image.Stream maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- Stream """ super(Stream, self).__init__("stream") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.image.Stream constructor must be a dict or an instance of plotly.graph_objs.image.Stream""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.image import stream as v_stream # Initialize validators # --------------------- self._validators["maxpoints"] = v_stream.MaxpointsValidator() self._validators["token"] = v_stream.TokenValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("maxpoints", None) self["maxpoints"] = maxpoints if maxpoints is not None else _v _v = arg.pop("token", None) self["token"] = token if token is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Hoverlabel(_BaseTraceHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'right', 'auto'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["align"] @align.setter def align(self, val): self["align"] = val # alignsrc # -------- @property def alignsrc(self): """ Sets the source reference on plot.ly for align . The 'alignsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["alignsrc"] @alignsrc.setter def alignsrc(self, val): self["alignsrc"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the hover labels for this trace The 'bgcolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bgcolorsrc # ---------- @property def bgcolorsrc(self): """ Sets the source reference on plot.ly for bgcolor . The 'bgcolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bgcolorsrc"] @bgcolorsrc.setter def bgcolorsrc(self, val): self["bgcolorsrc"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the border color of the hover labels for this trace. The 'bordercolor' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # bordercolorsrc # -------------- @property def bordercolorsrc(self): """ Sets the source reference on plot.ly for bordercolor . The 'bordercolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bordercolorsrc"] @bordercolorsrc.setter def bordercolorsrc(self, val): self["bordercolorsrc"] = val # font # ---- @property def font(self): """ Sets the font used in hover labels. The 'font' property is an instance of Font that may be specified as: - An instance of plotly.graph_objs.image.hoverlabel.Font - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.image.hoverlabel.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # namelength # ---------- @property def namelength(self): """ Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. The 'namelength' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [-1, 9223372036854775807] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|numpy.ndarray """ return self["namelength"] @namelength.setter def namelength(self, val): self["namelength"] = val # namelengthsrc # ------------- @property def namelengthsrc(self): """ Sets the source reference on plot.ly for namelength . The 'namelengthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["namelengthsrc"] @namelengthsrc.setter def namelengthsrc(self, val): self["namelengthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "image" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """ def __init__( self, arg=None, align=None, alignsrc=None, bgcolor=None, bgcolorsrc=None, bordercolor=None, bordercolorsrc=None, font=None, namelength=None, namelengthsrc=None, **kwargs ): """ Construct a new Hoverlabel object Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.image.Hoverlabel align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- Hoverlabel """ super(Hoverlabel, self).__init__("hoverlabel") # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.image.Hoverlabel constructor must be a dict or an instance of plotly.graph_objs.image.Hoverlabel""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.image import hoverlabel as v_hoverlabel # Initialize validators # --------------------- self._validators["align"] = v_hoverlabel.AlignValidator() self._validators["alignsrc"] = v_hoverlabel.AlignsrcValidator() self._validators["bgcolor"] = v_hoverlabel.BgcolorValidator() self._validators["bgcolorsrc"] = v_hoverlabel.BgcolorsrcValidator() self._validators["bordercolor"] = v_hoverlabel.BordercolorValidator() self._validators["bordercolorsrc"] = v_hoverlabel.BordercolorsrcValidator() self._validators["font"] = v_hoverlabel.FontValidator() self._validators["namelength"] = v_hoverlabel.NamelengthValidator() self._validators["namelengthsrc"] = v_hoverlabel.NamelengthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("alignsrc", None) self["alignsrc"] = alignsrc if alignsrc is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bgcolorsrc", None) self["bgcolorsrc"] = bgcolorsrc if bgcolorsrc is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("bordercolorsrc", None) self["bordercolorsrc"] = bordercolorsrc if bordercolorsrc is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("namelength", None) self["namelength"] = namelength if namelength is not None else _v _v = arg.pop("namelengthsrc", None) self["namelengthsrc"] = namelengthsrc if namelengthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = ["Hoverlabel", "Stream", "hoverlabel"] from plotly.graph_objs.image import hoverlabel plotly-4.4.1+dfsg.orig/plotly/version.py0000644000175000017500000000103313525746125017642 0ustar noahfxnoahfxfrom ._version import get_versions __version__ = get_versions()["version"] del get_versions from ._widget_version import __frontend_version__ def stable_semver(): """ Get the stable portion of the semantic version string (the first three numbers), without any of the trailing labels '3.0.0rc11' -> '3.0.0' """ from distutils.version import LooseVersion version_components = LooseVersion(__version__).version stable_ver_str = 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"pie": [{"automargin": true, "type": "pie"}]}}plotly-4.4.1+dfsg.orig/plotly/package_data/templates/gridon.json0000644000175000017500000000026413573717677024364 0ustar noahfxnoahfx{"layout": {"xaxis": {"showgrid": true, "title": {"standoff": 15}}, "yaxis": {"showgrid": true, "title": {"standoff": 15}}}, "data": {"pie": [{"automargin": true, "type": "pie"}]}}plotly-4.4.1+dfsg.orig/plotly/tools.py0000644000175000017500000006106113562266365017330 0ustar noahfxnoahfx# -*- coding: utf-8 -*- """ tools ===== Functions that USERS will possibly want access to. """ from __future__ import absolute_import import json import warnings import six import re import os from plotly import exceptions, optional_imports from plotly.files import PLOTLY_DIR DEFAULT_PLOTLY_COLORS = [ "rgb(31, 119, 180)", "rgb(255, 127, 14)", "rgb(44, 160, 44)", "rgb(214, 39, 40)", "rgb(148, 103, 189)", "rgb(140, 86, 75)", "rgb(227, 119, 194)", "rgb(127, 127, 127)", "rgb(188, 189, 34)", "rgb(23, 190, 207)", ] REQUIRED_GANTT_KEYS = ["Task", "Start", "Finish"] PLOTLY_SCALES = { "Greys": ["rgb(0,0,0)", "rgb(255,255,255)"], "YlGnBu": ["rgb(8,29,88)", "rgb(255,255,217)"], "Greens": ["rgb(0,68,27)", "rgb(247,252,245)"], "YlOrRd": ["rgb(128,0,38)", "rgb(255,255,204)"], "Bluered": ["rgb(0,0,255)", "rgb(255,0,0)"], "RdBu": ["rgb(5,10,172)", "rgb(178,10,28)"], "Reds": ["rgb(220,220,220)", "rgb(178,10,28)"], "Blues": ["rgb(5,10,172)", "rgb(220,220,220)"], "Picnic": ["rgb(0,0,255)", "rgb(255,0,0)"], "Rainbow": ["rgb(150,0,90)", "rgb(255,0,0)"], "Portland": ["rgb(12,51,131)", "rgb(217,30,30)"], "Jet": ["rgb(0,0,131)", "rgb(128,0,0)"], "Hot": ["rgb(0,0,0)", "rgb(255,255,255)"], "Blackbody": ["rgb(0,0,0)", "rgb(160,200,255)"], "Earth": ["rgb(0,0,130)", "rgb(255,255,255)"], "Electric": ["rgb(0,0,0)", "rgb(255,250,220)"], "Viridis": ["rgb(68,1,84)", "rgb(253,231,37)"], } # color constants for violin plot DEFAULT_FILLCOLOR = "#1f77b4" DEFAULT_HISTNORM = "probability density" ALTERNATIVE_HISTNORM = "probability" # Warning format def warning_on_one_line(message, category, filename, lineno, file=None, line=None): return "%s:%s: %s:\n\n%s\n\n" % (filename, lineno, category.__name__, message) warnings.formatwarning = warning_on_one_line ipython_core_display = optional_imports.get_module("IPython.core.display") sage_salvus = optional_imports.get_module("sage_salvus") ### mpl-related tools ### def mpl_to_plotly(fig, resize=False, strip_style=False, verbose=False): """Convert a matplotlib figure to plotly dictionary and send. All available information about matplotlib visualizations are stored within a matplotlib.figure.Figure object. You can create a plot in python using matplotlib, store the figure object, and then pass this object to the fig_to_plotly function. In the background, mplexporter is used to crawl through the mpl figure object for appropriate information. This information is then systematically sent to the PlotlyRenderer which creates the JSON structure used to make plotly visualizations. Finally, these dictionaries are sent to plotly and your browser should open up a new tab for viewing! Optionally, if you're working in IPython, you can set notebook=True and the PlotlyRenderer will call plotly.iplot instead of plotly.plot to have the graph appear directly in the IPython notebook. Note, this function gives the user access to a simple, one-line way to render an mpl figure in plotly. If you need to trouble shoot, you can do this step manually by NOT running this fuction and entereing the following: =========================================================================== from plotly.matplotlylib import mplexporter, PlotlyRenderer # create an mpl figure and store it under a varialble 'fig' renderer = PlotlyRenderer() exporter = mplexporter.Exporter(renderer) exporter.run(fig) =========================================================================== You can then inspect the JSON structures by accessing these: renderer.layout -- a plotly layout dictionary renderer.data -- a list of plotly data dictionaries """ matplotlylib = optional_imports.get_module("plotly.matplotlylib") if matplotlylib: renderer = matplotlylib.PlotlyRenderer() matplotlylib.Exporter(renderer).run(fig) if resize: renderer.resize() if strip_style: renderer.strip_style() if verbose: print(renderer.msg) return renderer.plotly_fig else: warnings.warn( "To use Plotly's matplotlylib functionality, you'll need to have " "matplotlib successfully installed with all of its dependencies. " "You're getting this error because matplotlib or one of its " "dependencies doesn't seem to be installed correctly." ) ### graph_objs related tools ### def get_subplots(rows=1, columns=1, print_grid=False, **kwargs): """Return a dictionary instance with the subplots set in 'layout'. Example 1: # stack two subplots vertically fig = tools.get_subplots(rows=2) fig['data'] += [Scatter(x=[1,2,3], y=[2,1,2], xaxis='x1', yaxis='y1')] fig['data'] += [Scatter(x=[1,2,3], y=[2,1,2], xaxis='x2', yaxis='y2')] Example 2: # print out string showing the subplot grid you've put in the layout fig = tools.get_subplots(rows=3, columns=2, print_grid=True) Keywords arguments with constant defaults: rows (kwarg, int greater than 0, default=1): Number of rows, evenly spaced vertically on the figure. columns (kwarg, int greater than 0, default=1): Number of columns, evenly spaced horizontally on the figure. horizontal_spacing (kwarg, float in [0,1], default=0.1): Space between subplot columns. Applied to all columns. vertical_spacing (kwarg, float in [0,1], default=0.05): Space between subplot rows. Applied to all rows. print_grid (kwarg, True | False, default=False): If True, prints a tab-delimited string representation of your plot grid. Keyword arguments with variable defaults: horizontal_spacing (kwarg, float in [0,1], default=0.2 / columns): Space between subplot columns. vertical_spacing (kwarg, float in [0,1], default=0.3 / rows): Space between subplot rows. """ # TODO: protected until #282 from plotly.graph_objs import graph_objs warnings.warn( "tools.get_subplots is depreciated. " "Please use tools.make_subplots instead." ) # Throw exception for non-integer rows and columns if not isinstance(rows, int) or rows <= 0: raise Exception("Keyword argument 'rows' " "must be an int greater than 0") if not isinstance(columns, int) or columns <= 0: raise Exception("Keyword argument 'columns' " "must be an int greater than 0") # Throw exception if non-valid kwarg is sent VALID_KWARGS = ["horizontal_spacing", "vertical_spacing"] for key in kwargs.keys(): if key not in VALID_KWARGS: raise Exception("Invalid keyword argument: '{0}'".format(key)) # Set 'horizontal_spacing' / 'vertical_spacing' w.r.t. rows / columns try: horizontal_spacing = float(kwargs["horizontal_spacing"]) except KeyError: horizontal_spacing = 0.2 / columns try: vertical_spacing = float(kwargs["vertical_spacing"]) except KeyError: vertical_spacing = 0.3 / rows fig = dict(layout=graph_objs.Layout()) # will return this at the end plot_width = (1 - horizontal_spacing * (columns - 1)) / columns plot_height = (1 - vertical_spacing * (rows - 1)) / rows plot_num = 0 for rrr in range(rows): for ccc in range(columns): xaxis_name = "xaxis{0}".format(plot_num + 1) x_anchor = "y{0}".format(plot_num + 1) x_start = (plot_width + horizontal_spacing) * ccc x_end = x_start + plot_width yaxis_name = "yaxis{0}".format(plot_num + 1) y_anchor = "x{0}".format(plot_num + 1) y_start = (plot_height + vertical_spacing) * rrr y_end = y_start + plot_height xaxis = dict(domain=[x_start, x_end], anchor=x_anchor) fig["layout"][xaxis_name] = xaxis yaxis = dict(domain=[y_start, y_end], anchor=y_anchor) fig["layout"][yaxis_name] = yaxis plot_num += 1 if print_grid: print("This is the format of your plot grid!") grid_string = "" plot = 1 for rrr in range(rows): grid_line = "" for ccc in range(columns): grid_line += "[{0}]\t".format(plot) plot += 1 grid_string = grid_line + "\n" + grid_string print(grid_string) return graph_objs.Figure(fig) # forces us to validate what we just did... def make_subplots( rows=1, cols=1, shared_xaxes=False, shared_yaxes=False, start_cell="top-left", print_grid=None, **kwargs ): """Return an instance of plotly.graph_objs.Figure with the subplots domain set in 'layout'. Example 1: # stack two subplots vertically fig = tools.make_subplots(rows=2) This is the format of your plot grid: [ (1,1) x1,y1 ] [ (2,1) x2,y2 ] fig['data'] += [Scatter(x=[1,2,3], y=[2,1,2])] fig['data'] += [Scatter(x=[1,2,3], y=[2,1,2], xaxis='x2', yaxis='y2')] # or see Figure.append_trace Example 2: # subplots with shared x axes fig = tools.make_subplots(rows=2, shared_xaxes=True) This is the format of your plot grid: [ (1,1) x1,y1 ] [ (2,1) x1,y2 ] fig['data'] += [Scatter(x=[1,2,3], y=[2,1,2])] fig['data'] += [Scatter(x=[1,2,3], y=[2,1,2], yaxis='y2')] Example 3: # irregular subplot layout (more examples below under 'specs') fig = tools.make_subplots(rows=2, cols=2, specs=[[{}, {}], [{'colspan': 2}, None]]) This is the format of your plot grid! [ (1,1) x1,y1 ] [ (1,2) x2,y2 ] [ (2,1) x3,y3 - ] fig['data'] += [Scatter(x=[1,2,3], y=[2,1,2])] fig['data'] += [Scatter(x=[1,2,3], y=[2,1,2], xaxis='x2', yaxis='y2')] fig['data'] += [Scatter(x=[1,2,3], y=[2,1,2], xaxis='x3', yaxis='y3')] Example 4: # insets fig = tools.make_subplots(insets=[{'cell': (1,1), 'l': 0.7, 'b': 0.3}]) This is the format of your plot grid! [ (1,1) x1,y1 ] With insets: [ x2,y2 ] over [ (1,1) x1,y1 ] fig['data'] += [Scatter(x=[1,2,3], y=[2,1,2])] fig['data'] += [Scatter(x=[1,2,3], y=[2,1,2], xaxis='x2', yaxis='y2')] Example 5: # include subplot titles fig = tools.make_subplots(rows=2, subplot_titles=('Plot 1','Plot 2')) This is the format of your plot grid: [ (1,1) x1,y1 ] [ (2,1) x2,y2 ] fig['data'] += [Scatter(x=[1,2,3], y=[2,1,2])] fig['data'] += [Scatter(x=[1,2,3], y=[2,1,2], xaxis='x2', yaxis='y2')] Example 6: # Include subplot title on one plot (but not all) fig = tools.make_subplots(insets=[{'cell': (1,1), 'l': 0.7, 'b': 0.3}], subplot_titles=('','Inset')) This is the format of your plot grid! [ (1,1) x1,y1 ] With insets: [ x2,y2 ] over [ (1,1) x1,y1 ] fig['data'] += [Scatter(x=[1,2,3], y=[2,1,2])] fig['data'] += [Scatter(x=[1,2,3], y=[2,1,2], xaxis='x2', yaxis='y2')] Keywords arguments with constant defaults: rows (kwarg, int greater than 0, default=1): Number of rows in the subplot grid. cols (kwarg, int greater than 0, default=1): Number of columns in the subplot grid. shared_xaxes (kwarg, boolean or list, default=False) Assign shared x axes. If True, subplots in the same grid column have one common shared x-axis at the bottom of the gird. To assign shared x axes per subplot grid cell (see 'specs'), send list (or list of lists, one list per shared x axis) of cell index tuples. shared_yaxes (kwarg, boolean or list, default=False) Assign shared y axes. If True, subplots in the same grid row have one common shared y-axis on the left-hand side of the gird. To assign shared y axes per subplot grid cell (see 'specs'), send list (or list of lists, one list per shared y axis) of cell index tuples. start_cell (kwarg, 'bottom-left' or 'top-left', default='top-left') Choose the starting cell in the subplot grid used to set the domains of the subplots. print_grid (kwarg, boolean, default=True): If True, prints a tab-delimited string representation of your plot grid. Keyword arguments with variable defaults: horizontal_spacing (kwarg, float in [0,1], default=0.2 / cols): Space between subplot columns. Applies to all columns (use 'specs' subplot-dependents spacing) vertical_spacing (kwarg, float in [0,1], default=0.3 / rows): Space between subplot rows. Applies to all rows (use 'specs' subplot-dependents spacing) subplot_titles (kwarg, list of strings, default=empty list): Title of each subplot. "" can be included in the list if no subplot title is desired in that space so that the titles are properly indexed. specs (kwarg, list of lists of dictionaries): Subplot specifications. ex1: specs=[[{}, {}], [{'colspan': 2}, None]] ex2: specs=[[{'rowspan': 2}, {}], [None, {}]] - Indices of the outer list correspond to subplot grid rows starting from the bottom. The number of rows in 'specs' must be equal to 'rows'. - Indices of the inner lists correspond to subplot grid columns starting from the left. The number of columns in 'specs' must be equal to 'cols'. - Each item in the 'specs' list corresponds to one subplot in a subplot grid. (N.B. The subplot grid has exactly 'rows' times 'cols' cells.) - Use None for blank a subplot cell (or to move pass a col/row span). - Note that specs[0][0] has the specs of the 'start_cell' subplot. - Each item in 'specs' is a dictionary. The available keys are: * is_3d (boolean, default=False): flag for 3d scenes * colspan (int, default=1): number of subplot columns for this subplot to span. * rowspan (int, default=1): number of subplot rows for this subplot to span. * l (float, default=0.0): padding left of cell * r (float, default=0.0): padding right of cell * t (float, default=0.0): padding right of cell * b (float, default=0.0): padding bottom of cell - Use 'horizontal_spacing' and 'vertical_spacing' to adjust the spacing in between the subplots. insets (kwarg, list of dictionaries): Inset specifications. - Each item in 'insets' is a dictionary. The available keys are: * cell (tuple, default=(1,1)): (row, col) index of the subplot cell to overlay inset axes onto. * is_3d (boolean, default=False): flag for 3d scenes * l (float, default=0.0): padding left of inset in fraction of cell width * w (float or 'to_end', default='to_end') inset width in fraction of cell width ('to_end': to cell right edge) * b (float, default=0.0): padding bottom of inset in fraction of cell height * h (float or 'to_end', default='to_end') inset height in fraction of cell height ('to_end': to cell top edge) column_width (kwarg, list of numbers) Column_width specifications - Functions similarly to `column_width` of `plotly.graph_objs.Table`. Specify a list that contains numbers where the amount of numbers in the list is equal to `cols`. - The numbers in the list indicate the proportions that each column domains take across the full horizontal domain excluding padding. - For example, if columns_width=[3, 1], horizontal_spacing=0, and cols=2, the domains for each column would be [0. 0.75] and [0.75, 1] row_width (kwargs, list of numbers) Row_width specifications - Functions similarly to `column_width`. Specify a list that contains numbers where the amount of numbers in the list is equal to `rows`. - The numbers in the list indicate the proportions that each row domains take along the full vertical domain excluding padding. - For example, if row_width=[3, 1], vertical_spacing=0, and cols=2, the domains for each row from top to botton would be [0. 0.75] and [0.75, 1] """ import plotly.subplots warnings.warn( "plotly.tools.make_subplots is deprecated, " "please use plotly.subplots.make_subplots instead", DeprecationWarning, stacklevel=1, ) return plotly.subplots.make_subplots( rows=rows, cols=cols, shared_xaxes=shared_xaxes, shared_yaxes=shared_yaxes, start_cell=start_cell, print_grid=print_grid, **kwargs ) warnings.filterwarnings( "default", r"plotly\.tools\.make_subplots is deprecated", DeprecationWarning ) def get_graph_obj(obj, obj_type=None): """Returns a new graph object. OLD FUNCTION: this will *silently* strip out invalid pieces of the object. NEW FUNCTION: no striping of invalid pieces anymore - only raises error on unrecognized graph_objs """ # TODO: Deprecate or move. #283 from plotly.graph_objs import graph_objs try: cls = getattr(graph_objs, obj_type) except (AttributeError, KeyError): raise exceptions.PlotlyError( "'{}' is not a recognized graph_obj.".format(obj_type) ) return cls(obj) def _replace_newline(obj): """Replaces '\n' with '
' for all strings in a collection.""" if isinstance(obj, dict): d = dict() for key, val in list(obj.items()): d[key] = _replace_newline(val) return d elif isinstance(obj, list): l = list() for index, entry in enumerate(obj): l += [_replace_newline(entry)] return l elif isinstance(obj, six.string_types): s = obj.replace("\n", "
") if s != obj: warnings.warn( "Looks like you used a newline character: '\\n'.\n\n" "Plotly uses a subset of HTML escape characters\n" "to do things like newline (
), bold (),\n" "italics (), etc. Your newline characters \n" "have been converted to '
' so they will show \n" "up right on your Plotly figure!" ) return s else: return obj # we return the actual reference... but DON'T mutate. def return_figure_from_figure_or_data(figure_or_data, validate_figure): from plotly.graph_objs import Figure from plotly.basedatatypes import BaseFigure validated = False if isinstance(figure_or_data, dict): figure = figure_or_data elif isinstance(figure_or_data, list): figure = {"data": figure_or_data} elif isinstance(figure_or_data, BaseFigure): figure = figure_or_data.to_dict() validated = True else: raise exceptions.PlotlyError( "The `figure_or_data` positional " "argument must be " "`dict`-like, `list`-like, or an instance of plotly.graph_objs.Figure" ) if validate_figure and not validated: try: figure = Figure(**figure).to_dict() except exceptions.PlotlyError as err: raise exceptions.PlotlyError( "Invalid 'figure_or_data' argument. " "Plotly will not be able to properly " "parse the resulting JSON. If you " "want to send this 'figure_or_data' " "to Plotly anyway (not recommended), " "you can set 'validate=False' as a " "plot option.\nHere's why you're " "seeing this error:\n\n{0}" "".format(err) ) if not figure["data"]: raise exceptions.PlotlyEmptyDataError( "Empty data list found. Make sure that you populated the " "list of data objects you're sending and try again.\n" "Questions? Visit support.plot.ly" ) return figure # Default colours for finance charts _DEFAULT_INCREASING_COLOR = "#3D9970" # http://clrs.cc _DEFAULT_DECREASING_COLOR = "#FF4136" DIAG_CHOICES = ["scatter", "histogram", "box"] VALID_COLORMAP_TYPES = ["cat", "seq"] # Deprecations class FigureFactory(object): @staticmethod def _deprecated(old_method, new_method=None): if new_method is None: # The method name stayed the same. new_method = old_method warnings.warn( "plotly.tools.FigureFactory.{} is deprecated. " "Use plotly.figure_factory.{}".format(old_method, new_method) ) @staticmethod def create_2D_density(*args, **kwargs): FigureFactory._deprecated("create_2D_density", "create_2d_density") from plotly.figure_factory import create_2d_density return create_2d_density(*args, **kwargs) @staticmethod def create_annotated_heatmap(*args, **kwargs): FigureFactory._deprecated("create_annotated_heatmap") from plotly.figure_factory import create_annotated_heatmap return create_annotated_heatmap(*args, **kwargs) @staticmethod def create_candlestick(*args, **kwargs): FigureFactory._deprecated("create_candlestick") from plotly.figure_factory import create_candlestick return create_candlestick(*args, **kwargs) @staticmethod def create_dendrogram(*args, **kwargs): FigureFactory._deprecated("create_dendrogram") from plotly.figure_factory import create_dendrogram return create_dendrogram(*args, **kwargs) @staticmethod def create_distplot(*args, **kwargs): FigureFactory._deprecated("create_distplot") from plotly.figure_factory import create_distplot return create_distplot(*args, **kwargs) @staticmethod def create_facet_grid(*args, **kwargs): FigureFactory._deprecated("create_facet_grid") from plotly.figure_factory import create_facet_grid return create_facet_grid(*args, **kwargs) @staticmethod def create_gantt(*args, **kwargs): FigureFactory._deprecated("create_gantt") from plotly.figure_factory import create_gantt return create_gantt(*args, **kwargs) @staticmethod def create_ohlc(*args, **kwargs): FigureFactory._deprecated("create_ohlc") from plotly.figure_factory import create_ohlc return create_ohlc(*args, **kwargs) @staticmethod def create_quiver(*args, **kwargs): FigureFactory._deprecated("create_quiver") from plotly.figure_factory import create_quiver return create_quiver(*args, **kwargs) @staticmethod def create_scatterplotmatrix(*args, **kwargs): FigureFactory._deprecated("create_scatterplotmatrix") from plotly.figure_factory import create_scatterplotmatrix return create_scatterplotmatrix(*args, **kwargs) @staticmethod def create_streamline(*args, **kwargs): FigureFactory._deprecated("create_streamline") from plotly.figure_factory import create_streamline return create_streamline(*args, **kwargs) @staticmethod def create_table(*args, **kwargs): FigureFactory._deprecated("create_table") from plotly.figure_factory import create_table return create_table(*args, **kwargs) @staticmethod def create_trisurf(*args, **kwargs): FigureFactory._deprecated("create_trisurf") from plotly.figure_factory import create_trisurf return create_trisurf(*args, **kwargs) @staticmethod def create_violin(*args, **kwargs): FigureFactory._deprecated("create_violin") from plotly.figure_factory import create_violin return create_violin(*args, **kwargs) def get_config_plotly_server_url(): """ Function to get the .config file's 'plotly_domain' without importing the chart_studio package. This property is needed to compute the default value of the plotly.js config plotlyServerURL, so it is independent of the chart_studio integration and still needs to live in Returns ------- str """ config_file = os.path.join(PLOTLY_DIR, ".config") default_server_url = "https://plot.ly" if not os.path.exists(config_file): return default_server_url with open(config_file, "rt") as f: try: config_dict = json.load(f) if not isinstance(config_dict, dict): config_dict = {} except: # TODO: issue a warning and bubble it up config_dict = {} return config_dict.get("plotly_domain", default_server_url) plotly-4.4.1+dfsg.orig/plotly/dashboard_objs.py0000644000175000017500000000017613525746125021130 0ustar noahfxnoahfxfrom __future__ import absolute_import from _plotly_future_ import _chart_studio_error _chart_studio_error("dashboard_objs") plotly-4.4.1+dfsg.orig/plotly/subplots.py0000644000175000017500000014046013573717677020055 0ustar noahfxnoahfx# -*- coding: utf-8 -*- from __future__ import absolute_import, unicode_literals # Constants # --------- # Subplot types that are each individually positioned with a domain # # Each of these subplot types has a `domain` property with `x`/`y` # properties. # Note that this set does not contain `xaxis`/`yaxis` because these behave a # little differently. import collections _single_subplot_types = {"scene", "geo", "polar", "ternary", "mapbox"} _subplot_types = set.union(_single_subplot_types, {"xy", "domain"}) # For most subplot types, a trace is associated with a particular subplot # using a trace property with a name that matches the subplot type. For # example, a `scatter3d.scene` property set to `'scene2'` associates a # scatter3d trace with the second `scene` subplot in the figure. # # There are a few subplot types that don't follow this pattern, and instead # the trace property is just named `subplot`. For example setting # the `scatterpolar.subplot` property to `polar3` associates the scatterpolar # trace with the third polar subplot in the figure _subplot_prop_named_subplot = {"polar", "ternary", "mapbox"} # Named tuple to hold an xaxis/yaxis pair that represent a single subplot SubplotXY = collections.namedtuple("SubplotXY", ("xaxis", "yaxis")) SubplotDomain = collections.namedtuple("SubplotDomain", ("x", "y")) SubplotRef = collections.namedtuple( "SubplotRef", ("subplot_type", "layout_keys", "trace_kwargs") ) def _get_initial_max_subplot_ids(): max_subplot_ids = {subplot_type: 0 for subplot_type in _single_subplot_types} max_subplot_ids["xaxis"] = 0 max_subplot_ids["yaxis"] = 0 return max_subplot_ids def make_subplots( rows=1, cols=1, shared_xaxes=False, shared_yaxes=False, start_cell="top-left", print_grid=False, horizontal_spacing=None, vertical_spacing=None, subplot_titles=None, column_widths=None, row_heights=None, specs=None, insets=None, column_titles=None, row_titles=None, x_title=None, y_title=None, **kwargs ): """ Return an instance of plotly.graph_objs.Figure with predefined subplots configured in 'layout'. Parameters ---------- rows: int (default 1) Number of rows in the subplot grid. Must be greater than zero. cols: int (default 1) Number of columns in the subplot grid. Must be greater than zero. shared_xaxes: boolean or str (default False) Assign shared (linked) x-axes for 2D cartesian subplots - True or 'columns': Share axes among subplots in the same column - 'rows': Share axes among subplots in the same row - 'all': Share axes across all subplots in the grid. shared_yaxes: boolean or str (default False) Assign shared (linked) y-axes for 2D cartesian subplots - 'columns': Share axes among subplots in the same column - True or 'rows': Share axes among subplots in the same row - 'all': Share axes across all subplots in the grid. start_cell: 'bottom-left' or 'top-left' (default 'top-left') Choose the starting cell in the subplot grid used to set the domains_grid of the subplots. - 'top-left': Subplots are numbered with (1, 1) in the top left corner - 'bottom-left': Subplots are numbererd with (1, 1) in the bottom left corner print_grid: boolean (default True): If True, prints a string representation of the plot grid. Grid may also be printed using the `Figure.print_grid()` method on the resulting figure. horizontal_spacing: float (default 0.2 / cols) Space between subplot columns in normalized plot coordinates. Must be a float between 0 and 1. Applies to all columns (use 'specs' subplot-dependents spacing) vertical_spacing: float (default 0.3 / rows) Space between subplot rows in normalized plot coordinates. Must be a float between 0 and 1. Applies to all rows (use 'specs' subplot-dependents spacing) subplot_titles: list of str or None (default None) Title of each subplot as a list in row-major ordering. Empty strings ("") can be included in the list if no subplot title is desired in that space so that the titles are properly indexed. specs: list of lists of dict or None (default None) Per subplot specifications of subplot type, row/column spanning, and spacing. ex1: specs=[[{}, {}], [{'colspan': 2}, None]] ex2: specs=[[{'rowspan': 2}, {}], [None, {}]] - Indices of the outer list correspond to subplot grid rows starting from the top, if start_cell='top-left', or bottom, if start_cell='bottom-left'. The number of rows in 'specs' must be equal to 'rows'. - Indices of the inner lists correspond to subplot grid columns starting from the left. The number of columns in 'specs' must be equal to 'cols'. - Each item in the 'specs' list corresponds to one subplot in a subplot grid. (N.B. The subplot grid has exactly 'rows' times 'cols' cells.) - Use None for a blank a subplot cell (or to move past a col/row span). - Note that specs[0][0] has the specs of the 'start_cell' subplot. - Each item in 'specs' is a dictionary. The available keys are: * type (string, default 'xy'): Subplot type. One of - 'xy': 2D Cartesian subplot type for scatter, bar, etc. - 'scene': 3D Cartesian subplot for scatter3d, cone, etc. - 'polar': Polar subplot for scatterpolar, barpolar, etc. - 'ternary': Ternary subplot for scatterternary - 'mapbox': Mapbox subplot for scattermapbox - 'domain': Subplot type for traces that are individually positioned. pie, parcoords, parcats, etc. - trace type: A trace type which will be used to determine the appropriate subplot type for that trace * secondary_y (bool, default False): If True, create a secondary y-axis positioned on the right side of the subplot. Only valid if type='xy'. * colspan (int, default 1): number of subplot columns for this subplot to span. * rowspan (int, default 1): number of subplot rows for this subplot to span. * l (float, default 0.0): padding left of cell * r (float, default 0.0): padding right of cell * t (float, default 0.0): padding right of cell * b (float, default 0.0): padding bottom of cell - Note: Use 'horizontal_spacing' and 'vertical_spacing' to adjust the spacing in between the subplots. insets: list of dict or None (default None): Inset specifications. Insets are subplots that overlay grid subplots - Each item in 'insets' is a dictionary. The available keys are: * cell (tuple, default=(1,1)): (row, col) index of the subplot cell to overlay inset axes onto. * type (string, default 'xy'): Subplot type * l (float, default=0.0): padding left of inset in fraction of cell width * w (float or 'to_end', default='to_end') inset width in fraction of cell width ('to_end': to cell right edge) * b (float, default=0.0): padding bottom of inset in fraction of cell height * h (float or 'to_end', default='to_end') inset height in fraction of cell height ('to_end': to cell top edge) column_widths: list of numbers or None (default None) list of length `cols` of the relative widths of each column of suplots. Values are normalized internally and used to distribute overall width of the figure (excluding padding) among the columns. For backward compatibility, may also be specified using the `column_width` keyword argument. row_heights: list of numbers or None (default None) list of length `rows` of the relative heights of each row of subplots. If start_cell='top-left' then row heights are applied top to bottom. Otherwise, if start_cell='bottom-left' then row heights are applied bottom to top. For backward compatibility, may also be specified using the `row_width` kwarg. If specified as `row_width`, then the width values are applied from bottom to top regardless of the value of start_cell. This matches the legacy behavior of the `row_width` argument. column_titles: list of str or None (default None) list of length `cols` of titles to place above the top subplot in each column. row_titles: list of str or None (default None) list of length `rows` of titles to place on the right side of each row of subplots. If start_cell='top-left' then row titles are applied top to bottom. Otherwise, if start_cell='bottom-left' then row titles are applied bottom to top. x_title: str or None (default None) Title to place below the bottom row of subplots, centered horizontally y_title: str or None (default None) Title to place to the left of the left column of subplots, centered vertically Examples -------- Example 1: >>> # Stack two subplots vertically, and add a scatter trace to each >>> from plotly.subplots import make_subplots >>> import plotly.graph_objects as go >>> fig = make_subplots(rows=2) This is the format of your plot grid: [ (1,1) xaxis1,yaxis1 ] [ (2,1) xaxis2,yaxis2 ] >>> fig.add_scatter(y=[2, 1, 3], row=1, col=1) # doctest: +ELLIPSIS Figure(...) >>> fig.add_scatter(y=[1, 3, 2], row=2, col=1) # doctest: +ELLIPSIS Figure(...) or see Figure.append_trace Example 2: >>> # Stack a scatter plot >>> fig = make_subplots(rows=2, shared_xaxes=True) This is the format of your plot grid: [ (1,1) xaxis1,yaxis1 ] [ (2,1) xaxis2,yaxis2 ] >>> fig.add_scatter(y=[2, 1, 3], row=1, col=1) # doctest: +ELLIPSIS Figure(...) >>> fig.add_scatter(y=[1, 3, 2], row=2, col=1) # doctest: +ELLIPSIS Figure(...) Example 3: >>> # irregular subplot layout (more examples below under 'specs') >>> fig = make_subplots(rows=2, cols=2, ... specs=[[{}, {}], ... [{'colspan': 2}, None]]) This is the format of your plot grid: [ (1,1) xaxis1,yaxis1 ] [ (1,2) xaxis2,yaxis2 ] [ (2,1) xaxis3,yaxis3 - ] >>> fig.add_trace(go.Scatter(x=[1,2,3], y=[2,1,2]), row=1, col=1) # doctest: +ELLIPSIS Figure(...) >>> fig.add_trace(go.Scatter(x=[1,2,3], y=[2,1,2]), row=1, col=2) # doctest: +ELLIPSIS Figure(...) >>> fig.add_trace(go.Scatter(x=[1,2,3], y=[2,1,2]), row=2, col=1) # doctest: +ELLIPSIS Figure(...) Example 4: >>> # insets >>> fig = make_subplots(insets=[{'cell': (1,1), 'l': 0.7, 'b': 0.3}]) This is the format of your plot grid: [ (1,1) xaxis1,yaxis1 ] With insets: [ xaxis2,yaxis2 ] over [ (1,1) xaxis1,yaxis1 ] >>> fig.add_scatter(x=[1,2,3], y=[2,1,1]) # doctest: +ELLIPSIS Figure(...) >>> fig.add_scatter(x=[1,2,3], y=[2,1,2], xaxis='x2', yaxis='y2') # doctest: +ELLIPSIS Figure(...) Example 5: >>> # include subplot titles >>> fig = make_subplots(rows=2, subplot_titles=('Plot 1','Plot 2')) This is the format of your plot grid: [ (1,1) x1,y1 ] [ (2,1) x2,y2 ] >>> fig.add_scatter(x=[1,2,3], y=[2,1,2], row=1, col=1) # doctest: +ELLIPSIS Figure(...) >>> fig.add_bar(x=[1,2,3], y=[2,1,2], row=2, col=1) # doctest: +ELLIPSIS Figure(...) Example 6: Subplot with mixed subplot types >>> fig = make_subplots(rows=2, cols=2, ... specs=[[{'type': 'xy'}, {'type': 'polar'}], ... [{'type': 'scene'}, {'type': 'ternary'}]]) >>> fig.add_traces( ... [go.Scatter(y=[2, 3, 1]), ... go.Scatterpolar(r=[1, 3, 2], theta=[0, 45, 90]), ... go.Scatter3d(x=[1, 2, 1], y=[2, 3, 1], z=[0, 3, 5]), ... go.Scatterternary(a=[0.1, 0.2, 0.1], ... b=[0.2, 0.3, 0.1], ... c=[0.7, 0.5, 0.8])], ... rows=[1, 1, 2, 2], ... cols=[1, 2, 1, 2]) # doctest: +ELLIPSIS Figure(...) """ import plotly.graph_objs as go # Handle backward compatibility # ----------------------------- use_legacy_row_heights_order = "row_width" in kwargs row_heights = kwargs.pop("row_width", row_heights) column_widths = kwargs.pop("column_width", column_widths) if kwargs: raise TypeError( "make_subplots() got unexpected keyword argument(s): {}".format( list(kwargs) ) ) # Validate coerce inputs # ---------------------- # ### rows ### if not isinstance(rows, int) or rows <= 0: raise ValueError( """ The 'rows' argument to make_suplots must be an int greater than 0. Received value of type {typ}: {val}""".format( typ=type(rows), val=repr(rows) ) ) # ### cols ### if not isinstance(cols, int) or cols <= 0: raise ValueError( """ The 'cols' argument to make_suplots must be an int greater than 0. Received value of type {typ}: {val}""".format( typ=type(cols), val=repr(cols) ) ) # ### start_cell ### if start_cell == "bottom-left": col_dir = 1 row_dir = 1 elif start_cell == "top-left": col_dir = 1 row_dir = -1 else: raise ValueError( """ The 'start_cell` argument to make_subplots must be one of \ ['bottom-left', 'top-left'] Received value of type {typ}: {val}""".format( typ=type(start_cell), val=repr(start_cell) ) ) # ### Helper to validate coerce elements of lists of dictionaries ### def _check_keys_and_fill(name, arg, defaults): def _checks(item, defaults): if item is None: return if not isinstance(item, dict): raise ValueError( """ Elements of the '{name}' argument to make_suplots must be dictionaries \ or None. Received value of type {typ}: {val}""".format( name=name, typ=type(item), val=repr(item) ) ) for k in item: if k not in defaults: raise ValueError( """ Invalid key specified in an element of the '{name}' argument to \ make_subplots: {k} Valid keys include: {valid_keys}""".format( k=repr(k), name=name, valid_keys=repr(list(defaults)) ) ) for k, v in defaults.items(): item.setdefault(k, v) for arg_i in arg: if isinstance(arg_i, (list, tuple)): # 2D list for arg_ii in arg_i: _checks(arg_ii, defaults) elif isinstance(arg_i, dict): # 1D list _checks(arg_i, defaults) # ### specs ### if specs is None: specs = [[{} for c in range(cols)] for r in range(rows)] elif not ( isinstance(specs, (list, tuple)) and specs and all(isinstance(row, (list, tuple)) for row in specs) and len(specs) == rows and all(len(row) == cols for row in specs) and all(all(v is None or isinstance(v, dict) for v in row) for row in specs) ): raise ValueError( """ The 'specs' argument to make_subplots must be a 2D list of dictionaries with \ dimensions ({rows} x {cols}). Received value of type {typ}: {val}""".format( rows=rows, cols=cols, typ=type(specs), val=repr(specs) ) ) for row in specs: for spec in row: # For backward compatibility, # convert is_3d flag to type='scene' kwarg if spec and spec.pop("is_3d", None): spec["type"] = "scene" spec_defaults = dict( type="xy", secondary_y=False, colspan=1, rowspan=1, l=0.0, r=0.0, b=0.0, t=0.0 ) _check_keys_and_fill("specs", specs, spec_defaults) # Validate secondary_y has_secondary_y = False for row in specs: for spec in row: if spec is not None: has_secondary_y = has_secondary_y or spec["secondary_y"] if spec and spec["type"] != "xy" and spec["secondary_y"]: raise ValueError( """ The 'secondary_y' spec property is not supported for subplot of type '{s_typ}' 'secondary_y' is only supported for subplots of type 'xy' """.format( s_typ=spec["type"] ) ) # ### insets ### if insets is None or insets is False: insets = [] elif not ( isinstance(insets, (list, tuple)) and all(isinstance(v, dict) for v in insets) ): raise ValueError( """ The 'insets' argument to make_suplots must be a list of dictionaries. Received value of type {typ}: {val}""".format( typ=type(insets), val=repr(insets) ) ) if insets: for inset in insets: if inset and inset.pop("is_3d", None): inset["type"] = "scene" inset_defaults = dict( cell=(1, 1), type="xy", l=0.0, w="to_end", b=0.0, h="to_end" ) _check_keys_and_fill("insets", insets, inset_defaults) # ### shared_xaxes / shared_yaxes valid_shared_vals = [None, True, False, "rows", "columns", "all"] shared_err_msg = """ The {arg} argument to make_subplots must be one of: {valid_vals} Received value of type {typ}: {val}""" if shared_xaxes not in valid_shared_vals: val = shared_xaxes raise ValueError( shared_err_msg.format( arg="shared_xaxes", valid_vals=valid_shared_vals, typ=type(val), val=repr(val), ) ) if shared_yaxes not in valid_shared_vals: val = shared_yaxes raise ValueError( shared_err_msg.format( arg="shared_yaxes", valid_vals=valid_shared_vals, typ=type(val), val=repr(val), ) ) # ### horizontal_spacing ### if horizontal_spacing is None: if has_secondary_y: horizontal_spacing = 0.4 / cols else: horizontal_spacing = 0.2 / cols # ### vertical_spacing ### if vertical_spacing is None: if subplot_titles is not None: vertical_spacing = 0.5 / rows else: vertical_spacing = 0.3 / rows # ### subplot titles ### if subplot_titles is None: subplot_titles = [""] * rows * cols # ### column_widths ### if has_secondary_y: # Add room for secondary y-axis title max_width = 0.94 elif row_titles: # Add a little breathing room between row labels and legend max_width = 0.98 else: max_width = 1.0 if column_widths is None: widths = [(max_width - horizontal_spacing * (cols - 1)) / cols] * cols elif isinstance(column_widths, (list, tuple)) and len(column_widths) == cols: cum_sum = float(sum(column_widths)) widths = [] for w in column_widths: widths.append((max_width - horizontal_spacing * (cols - 1)) * (w / cum_sum)) else: raise ValueError( """ The 'column_widths' argument to make_suplots must be a list of numbers of \ length {cols}. Received value of type {typ}: {val}""".format( cols=cols, typ=type(column_widths), val=repr(column_widths) ) ) # ### row_heights ### if row_heights is None: heights = [(1.0 - vertical_spacing * (rows - 1)) / rows] * rows elif isinstance(row_heights, (list, tuple)) and len(row_heights) == rows: cum_sum = float(sum(row_heights)) heights = [] for h in row_heights: heights.append((1.0 - vertical_spacing * (rows - 1)) * (h / cum_sum)) if row_dir < 0 and not use_legacy_row_heights_order: heights = list(reversed(heights)) else: raise ValueError( """ The 'row_heights' argument to make_suplots must be a list of numbers of \ length {rows}. Received value of type {typ}: {val}""".format( rows=rows, typ=type(row_heights), val=repr(row_heights) ) ) # ### column_titles / row_titles ### if column_titles and not isinstance(column_titles, (list, tuple)): raise ValueError( """ The column_titles argument to make_subplots must be a list or tuple Received value of type {typ}: {val}""".format( typ=type(column_titles), val=repr(column_titles) ) ) if row_titles and not isinstance(row_titles, (list, tuple)): raise ValueError( """ The row_titles argument to make_subplots must be a list or tuple Received value of type {typ}: {val}""".format( typ=type(row_titles), val=repr(row_titles) ) ) # Init layout # ----------- layout = go.Layout() # Build grid reference # -------------------- # Built row/col sequence using 'row_dir' and 'col_dir' col_seq = range(cols)[::col_dir] row_seq = range(rows)[::row_dir] # Build 2D array of tuples of the start x and start y coordinate of each # subplot grid = [ [ ( (sum(widths[:c]) + c * horizontal_spacing), (sum(heights[:r]) + r * vertical_spacing), ) for c in col_seq ] for r in row_seq ] domains_grid = [[None for _ in range(cols)] for _ in range(rows)] # Initialize subplot reference lists for the grid and insets grid_ref = [[None for c in range(cols)] for r in range(rows)] list_of_domains = [] # added for subplot titles max_subplot_ids = _get_initial_max_subplot_ids() # Loop through specs -- (r, c) <-> (row, col) for r, spec_row in enumerate(specs): for c, spec in enumerate(spec_row): if spec is None: # skip over None cells continue # ### Compute x and y domain for subplot ### c_spanned = c + spec["colspan"] - 1 # get spanned c r_spanned = r + spec["rowspan"] - 1 # get spanned r # Throw exception if 'colspan' | 'rowspan' is too large for grid if c_spanned >= cols: raise Exception( "Some 'colspan' value is too large for " "this subplot grid." ) if r_spanned >= rows: raise Exception( "Some 'rowspan' value is too large for " "this subplot grid." ) # Get x domain using grid and colspan x_s = grid[r][c][0] + spec["l"] x_e = grid[r][c_spanned][0] + widths[c_spanned] - spec["r"] x_domain = [x_s, x_e] # Get y domain (dep. on row_dir) using grid & r_spanned if row_dir > 0: y_s = grid[r][c][1] + spec["b"] y_e = grid[r_spanned][c][1] + heights[r_spanned] - spec["t"] else: y_s = grid[r_spanned][c][1] + spec["b"] y_e = grid[r][c][1] + heights[-1 - r] - spec["t"] y_domain = [y_s, y_e] list_of_domains.append(x_domain) list_of_domains.append(y_domain) domains_grid[r][c] = [x_domain, y_domain] # ### construct subplot container ### subplot_type = spec["type"] secondary_y = spec["secondary_y"] subplot_refs = _init_subplot( layout, subplot_type, secondary_y, x_domain, y_domain, max_subplot_ids ) grid_ref[r][c] = subplot_refs _configure_shared_axes(layout, grid_ref, specs, "x", shared_xaxes, row_dir) _configure_shared_axes(layout, grid_ref, specs, "y", shared_yaxes, row_dir) # Build inset reference # --------------------- # Loop through insets insets_ref = [None for inset in range(len(insets))] if insets else None if insets: for i_inset, inset in enumerate(insets): r = inset["cell"][0] - 1 c = inset["cell"][1] - 1 # Throw exception if r | c is out of range if not (0 <= r < rows): raise Exception( "Some 'cell' row value is out of range. " "Note: the starting cell is (1, 1)" ) if not (0 <= c < cols): raise Exception( "Some 'cell' col value is out of range. " "Note: the starting cell is (1, 1)" ) # Get inset x domain using grid x_s = grid[r][c][0] + inset["l"] * widths[c] if inset["w"] == "to_end": x_e = grid[r][c][0] + widths[c] else: x_e = x_s + inset["w"] * widths[c] x_domain = [x_s, x_e] # Get inset y domain using grid y_s = grid[r][c][1] + inset["b"] * heights[-1 - r] if inset["h"] == "to_end": y_e = grid[r][c][1] + heights[-1 - r] else: y_e = y_s + inset["h"] * heights[-1 - r] y_domain = [y_s, y_e] list_of_domains.append(x_domain) list_of_domains.append(y_domain) subplot_type = inset["type"] subplot_refs = _init_subplot( layout, subplot_type, False, x_domain, y_domain, max_subplot_ids ) insets_ref[i_inset] = subplot_refs # Build grid_str # This is the message printed when print_grid=True grid_str = _build_grid_str(specs, grid_ref, insets, insets_ref, row_seq) # Add subplot titles plot_title_annotations = _build_subplot_title_annotations( subplot_titles, list_of_domains ) layout["annotations"] = plot_title_annotations # Add column titles if column_titles: domains_list = [] if row_dir > 0: for c in range(cols): domain_pair = domains_grid[-1][c] if domain_pair: domains_list.extend(domain_pair) else: for c in range(cols): domain_pair = domains_grid[0][c] if domain_pair: domains_list.extend(domain_pair) # Add subplot titles column_title_annotations = _build_subplot_title_annotations( column_titles, domains_list ) layout["annotations"] += tuple(column_title_annotations) if row_titles: domains_list = [] for r in range(rows): domain_pair = domains_grid[r][-1] if domain_pair: domains_list.extend(domain_pair) # Add subplot titles column_title_annotations = _build_subplot_title_annotations( row_titles, domains_list, title_edge="right" ) layout["annotations"] += tuple(column_title_annotations) if x_title: domains_list = [(0, max_width), (0, 1)] # Add subplot titles column_title_annotations = _build_subplot_title_annotations( [x_title], domains_list, title_edge="bottom", offset=30 ) layout["annotations"] += tuple(column_title_annotations) if y_title: domains_list = [(0, 1), (0, 1)] # Add subplot titles column_title_annotations = _build_subplot_title_annotations( [y_title], domains_list, title_edge="left", offset=40 ) layout["annotations"] += tuple(column_title_annotations) # Handle displaying grid information if print_grid: print(grid_str) # Build resulting figure fig = go.Figure(layout=layout) # Attach subpot grid info to the figure fig.__dict__["_grid_ref"] = grid_ref fig.__dict__["_grid_str"] = grid_str return fig def _configure_shared_axes(layout, grid_ref, specs, x_or_y, shared, row_dir): rows = len(grid_ref) cols = len(grid_ref[0]) layout_key_ind = ["x", "y"].index(x_or_y) if row_dir < 0: rows_iter = range(rows - 1, -1, -1) else: rows_iter = range(rows) def update_axis_matches(first_axis_id, subplot_ref, spec, remove_label): if subplot_ref is None: return first_axis_id if x_or_y == "x": span = spec["colspan"] else: span = spec["rowspan"] if subplot_ref.subplot_type == "xy" and span == 1: if first_axis_id is None: first_axis_name = subplot_ref.layout_keys[layout_key_ind] first_axis_id = first_axis_name.replace("axis", "") else: axis_name = subplot_ref.layout_keys[layout_key_ind] axis_to_match = layout[axis_name] axis_to_match.matches = first_axis_id if remove_label: axis_to_match.showticklabels = False return first_axis_id if shared == "columns" or (x_or_y == "x" and shared is True): for c in range(cols): first_axis_id = None ok_to_remove_label = x_or_y == "x" for r in rows_iter: if not grid_ref[r][c]: continue subplot_ref = grid_ref[r][c][0] spec = specs[r][c] first_axis_id = update_axis_matches( first_axis_id, subplot_ref, spec, ok_to_remove_label ) elif shared == "rows" or (x_or_y == "y" and shared is True): for r in rows_iter: first_axis_id = None ok_to_remove_label = x_or_y == "y" for c in range(cols): if not grid_ref[r][c]: continue subplot_ref = grid_ref[r][c][0] spec = specs[r][c] first_axis_id = update_axis_matches( first_axis_id, subplot_ref, spec, ok_to_remove_label ) elif shared == "all": first_axis_id = None for c in range(cols): for ri, r in enumerate(rows_iter): if not grid_ref[r][c]: continue subplot_ref = grid_ref[r][c][0] spec = specs[r][c] if x_or_y == "y": ok_to_remove_label = c > 0 else: ok_to_remove_label = ri > 0 if row_dir > 0 else r < rows - 1 first_axis_id = update_axis_matches( first_axis_id, subplot_ref, spec, ok_to_remove_label ) def _init_subplot_xy(layout, secondary_y, x_domain, y_domain, max_subplot_ids=None): if max_subplot_ids is None: max_subplot_ids = _get_initial_max_subplot_ids() # Get axis label and anchor x_cnt = max_subplot_ids["xaxis"] + 1 y_cnt = max_subplot_ids["yaxis"] + 1 # Compute x/y labels (the values of trace.xaxis/trace.yaxis x_label = "x{cnt}".format(cnt=x_cnt if x_cnt > 1 else "") y_label = "y{cnt}".format(cnt=y_cnt if y_cnt > 1 else "") # Anchor x and y axes to each other x_anchor, y_anchor = y_label, x_label # Build layout.xaxis/layout.yaxis containers xaxis_name = "xaxis{cnt}".format(cnt=x_cnt if x_cnt > 1 else "") yaxis_name = "yaxis{cnt}".format(cnt=y_cnt if y_cnt > 1 else "") x_axis = {"domain": x_domain, "anchor": x_anchor} y_axis = {"domain": y_domain, "anchor": y_anchor} layout[xaxis_name] = x_axis layout[yaxis_name] = y_axis subplot_refs = [ SubplotRef( subplot_type="xy", layout_keys=(xaxis_name, yaxis_name), trace_kwargs={"xaxis": x_label, "yaxis": y_label}, ) ] if secondary_y: y_cnt += 1 secondary_yaxis_name = "yaxis{cnt}".format(cnt=y_cnt if y_cnt > 1 else "") secondary_y_label = "y{cnt}".format(cnt=y_cnt) # Add secondary y-axis to subplot reference subplot_refs.append( SubplotRef( subplot_type="xy", layout_keys=(xaxis_name, secondary_yaxis_name), trace_kwargs={"xaxis": x_label, "yaxis": secondary_y_label}, ) ) # Add secondary y axis to layout secondary_y_axis = {"anchor": y_anchor, "overlaying": y_label, "side": "right"} layout[secondary_yaxis_name] = secondary_y_axis # increment max_subplot_ids max_subplot_ids["xaxis"] = x_cnt max_subplot_ids["yaxis"] = y_cnt return tuple(subplot_refs) def _init_subplot_single( layout, subplot_type, x_domain, y_domain, max_subplot_ids=None ): if max_subplot_ids is None: max_subplot_ids = _get_initial_max_subplot_ids() # Add scene to layout cnt = max_subplot_ids[subplot_type] + 1 label = "{subplot_type}{cnt}".format( subplot_type=subplot_type, cnt=cnt if cnt > 1 else "" ) scene = dict(domain={"x": x_domain, "y": y_domain}) layout[label] = scene trace_key = ( "subplot" if subplot_type in _subplot_prop_named_subplot else subplot_type ) subplot_ref = SubplotRef( subplot_type=subplot_type, layout_keys=(label,), trace_kwargs={trace_key: label} ) # increment max_subplot_id max_subplot_ids[subplot_type] = cnt return (subplot_ref,) def _init_subplot_domain(x_domain, y_domain): # No change to layout since domain traces are labeled individually subplot_ref = SubplotRef( subplot_type="domain", layout_keys=(), trace_kwargs={"domain": {"x": tuple(x_domain), "y": tuple(y_domain)}}, ) return (subplot_ref,) def _subplot_type_for_trace_type(trace_type): from plotly.validators import DataValidator trace_validator = DataValidator() if trace_type in trace_validator.class_strs_map: # subplot_type is a trace name, find the subplot type for trace trace = trace_validator.validate_coerce([{"type": trace_type}])[0] if "domain" in trace: return "domain" elif "xaxis" in trace and "yaxis" in trace: return "xy" elif "geo" in trace: return "geo" elif "scene" in trace: return "scene" elif "subplot" in trace: for t in _subplot_prop_named_subplot: try: trace.subplot = t return t except ValueError: pass return None def _validate_coerce_subplot_type(subplot_type): # Lowercase subplot_type orig_subplot_type = subplot_type subplot_type = subplot_type.lower() # Check if it's a named subplot type if subplot_type in _subplot_types: return subplot_type # Try to determine subplot type for trace subplot_type = _subplot_type_for_trace_type(subplot_type) if subplot_type is None: raise ValueError("Unsupported subplot type: {}".format(repr(orig_subplot_type))) else: return subplot_type def _init_subplot( layout, subplot_type, secondary_y, x_domain, y_domain, max_subplot_ids=None ): # Normalize subplot type subplot_type = _validate_coerce_subplot_type(subplot_type) if max_subplot_ids is None: max_subplot_ids = _get_initial_max_subplot_ids() # Clamp domain elements between [0, 1]. # This is only needed to combat numerical precision errors # See GH1031 x_domain = [max(0.0, x_domain[0]), min(1.0, x_domain[1])] y_domain = [max(0.0, y_domain[0]), min(1.0, y_domain[1])] if subplot_type == "xy": subplot_refs = _init_subplot_xy( layout, secondary_y, x_domain, y_domain, max_subplot_ids ) elif subplot_type in _single_subplot_types: subplot_refs = _init_subplot_single( layout, subplot_type, x_domain, y_domain, max_subplot_ids ) elif subplot_type == "domain": subplot_refs = _init_subplot_domain(x_domain, y_domain) else: raise ValueError("Unsupported subplot type: {}".format(repr(subplot_type))) return subplot_refs def _get_cartesian_label(x_or_y, r, c, cnt): # Default label (given strictly by cnt) label = "{x_or_y}{cnt}".format(x_or_y=x_or_y, cnt=cnt) return label def _build_subplot_title_annotations( subplot_titles, list_of_domains, title_edge="top", offset=0 ): # If shared_axes is False (default) use list_of_domains # This is used for insets and irregular layouts # if not shared_xaxes and not shared_yaxes: x_dom = list_of_domains[::2] y_dom = list_of_domains[1::2] subtitle_pos_x = [] subtitle_pos_y = [] if title_edge == "top": text_angle = 0 xanchor = "center" yanchor = "bottom" for x_domains in x_dom: subtitle_pos_x.append(sum(x_domains) / 2.0) for y_domains in y_dom: subtitle_pos_y.append(y_domains[1]) yshift = offset xshift = 0 elif title_edge == "bottom": text_angle = 0 xanchor = "center" yanchor = "top" for x_domains in x_dom: subtitle_pos_x.append(sum(x_domains) / 2.0) for y_domains in y_dom: subtitle_pos_y.append(y_domains[0]) yshift = -offset xshift = 0 elif title_edge == "right": text_angle = 90 xanchor = "left" yanchor = "middle" for x_domains in x_dom: subtitle_pos_x.append(x_domains[1]) for y_domains in y_dom: subtitle_pos_y.append(sum(y_domains) / 2.0) yshift = 0 xshift = offset elif title_edge == "left": text_angle = -90 xanchor = "right" yanchor = "middle" for x_domains in x_dom: subtitle_pos_x.append(x_domains[0]) for y_domains in y_dom: subtitle_pos_y.append(sum(y_domains) / 2.0) yshift = 0 xshift = -offset else: raise ValueError("Invalid annotation edge '{edge}'".format(edge=title_edge)) plot_titles = [] for index in range(len(subplot_titles)): if not subplot_titles[index] or index >= len(subtitle_pos_y): pass else: annot = { "y": subtitle_pos_y[index], "xref": "paper", "x": subtitle_pos_x[index], "yref": "paper", "text": subplot_titles[index], "showarrow": False, "font": dict(size=16), "xanchor": xanchor, "yanchor": yanchor, } if xshift != 0: annot["xshift"] = xshift if yshift != 0: annot["yshift"] = yshift if text_angle != 0: annot["textangle"] = text_angle plot_titles.append(annot) return plot_titles def _build_grid_str(specs, grid_ref, insets, insets_ref, row_seq): # Compute rows and columns rows = len(specs) cols = len(specs[0]) # Initialize constants sp = " " # space between cell s_str = "[ " # cell start string e_str = " ]" # cell end string s_top = "⎡ " # U+23A1 s_mid = "⎢ " # U+23A2 s_bot = "⎣ " # U+23A3 e_top = " ⎤" # U+23A4 e_mid = " ⎟" # U+239F e_bot = " ⎦" # U+23A6 colspan_str = " -" # colspan string rowspan_str = " :" # rowspan string empty_str = " (empty) " # empty cell string # Init grid_str with intro message grid_str = "This is the format of your plot grid:\n" # Init tmp list of lists of strings (sorta like 'grid_ref' but w/ strings) _tmp = [["" for c in range(cols)] for r in range(rows)] # Define cell string as function of (r, c) and grid_ref def _get_cell_str(r, c, subplot_refs): layout_keys = sorted({k for ref in subplot_refs for k in ref.layout_keys}) ref_str = ",".join(layout_keys) # Replace yaxis2 -> y2 ref_str = ref_str.replace("axis", "") return "({r},{c}) {ref}".format(r=r + 1, c=c + 1, ref=ref_str) # Find max len of _cell_str, add define a padding function cell_len = ( max( [ len(_get_cell_str(r, c, ref)) for r, row_ref in enumerate(grid_ref) for c, ref in enumerate(row_ref) if ref ] ) + len(s_str) + len(e_str) ) def _pad(s, cell_len=cell_len): return " " * (cell_len - len(s)) # Loop through specs, fill in _tmp for r, spec_row in enumerate(specs): for c, spec in enumerate(spec_row): ref = grid_ref[r][c] if ref is None: if _tmp[r][c] == "": _tmp[r][c] = empty_str + _pad(empty_str) continue if spec["rowspan"] > 1: cell_str = s_top + _get_cell_str(r, c, ref) else: cell_str = s_str + _get_cell_str(r, c, ref) if spec["colspan"] > 1: for cc in range(1, spec["colspan"] - 1): _tmp[r][c + cc] = colspan_str + _pad(colspan_str) if spec["rowspan"] > 1: _tmp[r][c + spec["colspan"] - 1] = ( colspan_str + _pad(colspan_str + e_str) ) + e_top else: _tmp[r][c + spec["colspan"] - 1] = ( colspan_str + _pad(colspan_str + e_str) ) + e_str else: padding = " " * (cell_len - len(cell_str) - 2) if spec["rowspan"] > 1: cell_str += padding + e_top else: cell_str += padding + e_str if spec["rowspan"] > 1: for cc in range(spec["colspan"]): for rr in range(1, spec["rowspan"]): row_str = rowspan_str + _pad(rowspan_str) if cc == 0: if rr < spec["rowspan"] - 1: row_str = s_mid + row_str[2:] else: row_str = s_bot + row_str[2:] if cc == spec["colspan"] - 1: if rr < spec["rowspan"] - 1: row_str = row_str[:-2] + e_mid else: row_str = row_str[:-2] + e_bot _tmp[r + rr][c + cc] = row_str _tmp[r][c] = cell_str + _pad(cell_str) # Append grid_str using data from _tmp in the correct order for r in row_seq[::-1]: grid_str += sp.join(_tmp[r]) + "\n" # Append grid_str to include insets info if insets: grid_str += "\nWith insets:\n" for i_inset, inset in enumerate(insets): r = inset["cell"][0] - 1 c = inset["cell"][1] - 1 ref = grid_ref[r][c] subplot_labels_str = ",".join(insets_ref[i_inset][0].layout_keys) # Replace, e.g., yaxis2 -> y2 subplot_labels_str = subplot_labels_str.replace("axis", "") grid_str += ( s_str + subplot_labels_str + e_str + " over " + s_str + _get_cell_str(r, c, ref) + e_str + "\n" ) return grid_str def _set_trace_grid_reference(trace, layout, grid_ref, row, col, secondary_y=False): if row <= 0: raise Exception( "Row value is out of range. " "Note: the starting cell is (1, 1)" ) if col <= 0: raise Exception( "Col value is out of range. " "Note: the starting cell is (1, 1)" ) try: subplot_refs = grid_ref[row - 1][col - 1] except IndexError: raise Exception( "The (row, col) pair sent is out of " "range. Use Figure.print_grid to view the " "subplot grid. " ) if not subplot_refs: raise ValueError( """ No subplot specified at grid position ({row}, {col})""".format( row=row, col=col ) ) if secondary_y: if len(subplot_refs) < 2: raise ValueError( """ Subplot with type '{subplot_type}' at grid position ({row}, {col}) was not created with the secondary_y spec property set to True. See the docstring for the specs argument to plotly.subplots.make_subplots for more information. """ ) trace_kwargs = subplot_refs[1].trace_kwargs else: trace_kwargs = subplot_refs[0].trace_kwargs for k in trace_kwargs: if k not in trace: raise ValueError( """\ Trace type '{typ}' is not compatible with subplot type '{subplot_type}' at grid position ({row}, {col}) See the docstring for the specs argument to plotly.subplots.make_subplots for more information on subplot types""".format( typ=trace.type, subplot_type=subplot_refs[0].subplot_type, row=row, col=col, ) ) # Update trace reference trace.update(trace_kwargs) def _get_grid_subplot(fig, row, col, secondary_y=False): try: grid_ref = fig._grid_ref except AttributeError: raise Exception( "In order to reference traces by row and column, " "you must first use " "plotly.tools.make_subplots " "to create the figure with a subplot grid." ) rows = len(grid_ref) cols = len(grid_ref[0]) # Validate row if not isinstance(row, int) or row < 1 or rows < row: raise ValueError( """ The row argument to get_subplot must be an integer where 1 <= row <= {rows} Received value of type {typ}: {val}""".format( rows=rows, typ=type(row), val=repr(row) ) ) if not isinstance(col, int) or col < 1 or cols < col: raise ValueError( """ The col argument to get_subplot must be an integer where 1 <= row <= {cols} Received value of type {typ}: {val}""".format( cols=cols, typ=type(col), val=repr(col) ) ) subplot_refs = fig._grid_ref[row - 1][col - 1] if not subplot_refs: return None if secondary_y: if len(subplot_refs) > 1: layout_keys = subplot_refs[1].layout_keys else: return None else: layout_keys = subplot_refs[0].layout_keys if len(layout_keys) == 0: return SubplotDomain(**subplot_refs[0].trace_kwargs["domain"]) elif len(layout_keys) == 1: return fig.layout[layout_keys[0]] elif len(layout_keys) == 2: return SubplotXY( xaxis=fig.layout[layout_keys[0]], yaxis=fig.layout[layout_keys[1]] ) else: raise ValueError( """ Unexpected subplot type with layout_keys of {}""".format( layout_keys ) ) def _get_subplot_ref_for_trace(trace): if "domain" in trace: return SubplotRef( subplot_type="domain", layout_keys=(), trace_kwargs={"domain": {"x": trace.domain.x, "y": trace.domain.y}}, ) elif "xaxis" in trace and "yaxis" in trace: xaxis_name = "xaxis" + trace.xaxis[1:] if trace.xaxis else "xaxis" yaxis_name = "yaxis" + trace.yaxis[1:] if trace.yaxis else "yaxis" return SubplotRef( subplot_type="xy", layout_keys=(xaxis_name, yaxis_name), trace_kwargs={"xaxis": trace.xaxis, "yaxis": trace.yaxis}, ) elif "geo" in trace: return SubplotRef( subplot_type="geo", layout_keys=(trace.geo,), trace_kwargs={"geo": trace.geo}, ) elif "scene" in trace: return SubplotRef( subplot_type="scene", layout_keys=(trace.scene,), trace_kwargs={"scene": trace.scene}, ) elif "subplot" in trace: for t in _subplot_prop_named_subplot: try: validator = trace._get_prop_validator("subplot") validator.validate_coerce(t) return SubplotRef( subplot_type=t, layout_keys=(trace.subplot,), trace_kwargs={"subplot": trace.subplot}, ) except ValueError: pass return None plotly-4.4.1+dfsg.orig/plotly/config.py0000644000175000017500000000016613525746125017430 0ustar noahfxnoahfxfrom __future__ import absolute_import from _plotly_future_ import _chart_studio_error _chart_studio_error("config") plotly-4.4.1+dfsg.orig/plotly/callbacks.py0000644000175000017500000001461013525746125020101 0ustar noahfxnoahfxfrom __future__ import absolute_import from plotly.utils import _list_repr_elided class InputDeviceState: def __init__( self, ctrl=None, alt=None, shift=None, meta=None, button=None, buttons=None, **_ ): self._ctrl = ctrl self._alt = alt self._meta = meta self._shift = shift self._button = button self._buttons = buttons def __repr__(self): return """\ InputDeviceState( ctrl={ctrl}, alt={alt}, shift={shift}, meta={meta}, button={button}, buttons={buttons})""".format( ctrl=repr(self.ctrl), alt=repr(self.alt), meta=repr(self.meta), shift=repr(self.shift), button=repr(self.button), buttons=repr(self.buttons), ) @property def alt(self): """ Whether alt key pressed Returns ------- bool """ return self._alt @property def ctrl(self): """ Whether ctrl key pressed Returns ------- bool """ return self._ctrl @property def shift(self): """ Whether shift key pressed Returns ------- bool """ return self._shift @property def meta(self): """ Whether meta key pressed Returns ------- bool """ return self._meta @property def button(self): """ Integer code for the button that was pressed on the mouse to trigger the event - 0: Main button pressed, usually the left button or the un-initialized state - 1: Auxiliary button pressed, usually the wheel button or the middle button (if present) - 2: Secondary button pressed, usually the right button - 3: Fourth button, typically the Browser Back button - 4: Fifth button, typically the Browser Forward button Returns ------- int """ return self._button @property def buttons(self): """ Integer code for which combination of buttons are pressed on the mouse when the event is triggered. - 0: No button or un-initialized - 1: Primary button (usually left) - 2: Secondary button (usually right) - 4: Auxilary button (usually middle or mouse wheel button) - 8: 4th button (typically the "Browser Back" button) - 16: 5th button (typically the "Browser Forward" button) Combinations of buttons are represented as the decimal form of the bitmask of the values above. For example, pressing both the primary (1) and auxilary (4) buttons will result in a code of 5 Returns ------- int """ return self._buttons class Points: def __init__(self, point_inds=[], xs=[], ys=[], trace_name=None, trace_index=None): self._point_inds = point_inds self._xs = xs self._ys = ys self._trace_name = trace_name self._trace_index = trace_index def __repr__(self): return """\ Points(point_inds={point_inds}, xs={xs}, ys={ys}, trace_name={trace_name}, trace_index={trace_index})""".format( point_inds=_list_repr_elided( self.point_inds, indent=len("Points(point_inds=") ), xs=_list_repr_elided(self.xs, indent=len(" xs=")), ys=_list_repr_elided(self.ys, indent=len(" ys=")), trace_name=repr(self.trace_name), trace_index=repr(self.trace_index), ) @property def point_inds(self): """ List of selected indexes into the trace's points Returns ------- list[int] """ return self._point_inds @property def xs(self): """ List of x-coordinates of selected points Returns ------- list[float] """ return self._xs @property def ys(self): """ List of y-coordinates of selected points Returns ------- list[float] """ return self._ys @property def trace_name(self): """ Name of the trace Returns ------- str """ return self._trace_name @property def trace_index(self): """ Index of the trace in the figure Returns ------- int """ return self._trace_index class BoxSelector: def __init__(self, xrange=None, yrange=None, **_): self._type = "box" self._xrange = xrange self._yrange = yrange def __repr__(self): return """\ BoxSelector(xrange={xrange}, yrange={yrange})""".format( xrange=self.xrange, yrange=self.yrange ) @property def type(self): """ The selector's type Returns ------- str """ return self._type @property def xrange(self): """ x-axis range extents of the box selection Returns ------- (float, float) """ return self._xrange @property def yrange(self): """ y-axis range extents of the box selection Returns ------- (float, float) """ return self._yrange class LassoSelector: def __init__(self, xs=None, ys=None, **_): self._type = "lasso" self._xs = xs self._ys = ys def __repr__(self): return """\ LassoSelector(xs={xs}, ys={ys})""".format( xs=_list_repr_elided(self.xs, indent=len("LassoSelector(xs=")), ys=_list_repr_elided(self.ys, indent=len(" ys=")), ) @property def type(self): """ The selector's type Returns ------- str """ return self._type @property def xs(self): """ list of x-axis coordinates of each point in the lasso selection boundary Returns ------- list[float] """ return self._xs @property def ys(self): """ list of y-axis coordinates of each point in the lasso selection boundary Returns ------- list[float] """ return self._ys plotly-4.4.1+dfsg.orig/plotly/plotly/0000755000175000017500000000000013573746614017137 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/plotly/chunked_requests.py0000644000175000017500000000020713525746125023056 0ustar noahfxnoahfxfrom __future__ import absolute_import from _plotly_future_ import _chart_studio_error _chart_studio_error("plotly.chunked_requests") plotly-4.4.1+dfsg.orig/plotly/plotly/__init__.py0000644000175000017500000000016613525746125021245 0ustar noahfxnoahfxfrom __future__ import absolute_import from _plotly_future_ import _chart_studio_error _chart_studio_error("plotly") plotly-4.4.1+dfsg.orig/plotly/__init__.py0000644000175000017500000000165013547055022017712 0ustar noahfxnoahfx""" https://plot.ly/python/ Plotly's Python API allows users to programmatically access Plotly's server resources. This package is organized as follows: Subpackages: - plotly: all functionality that requires access to Plotly's servers - graph_objs: objects for designing figures and visualizing data - matplotlylib: tools to convert matplotlib figures Modules: - tools: some helpful tools that do not require access to Plotly's servers - utils: functions that you probably won't need, but that subpackages use - version: holds the current API version - exceptions: defines our custom exception classes """ from __future__ import absolute_import from plotly import ( graph_objs, tools, utils, offline, colors, io, data, colors, _docstring_gen, ) from plotly.version import __version__ # Set default template here to make sure import process is complete io.templates._default = "plotly" plotly-4.4.1+dfsg.orig/plotly/matplotlylib/0000755000175000017500000000000013573746613020327 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/matplotlylib/mplexporter/0000755000175000017500000000000013573746613022710 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/matplotlylib/mplexporter/_py3k_compat.py0000644000175000017500000000067013525746125025650 0ustar noahfxnoahfx""" Simple fixes for Python 2/3 compatibility """ import sys PY3K = sys.version_info[0] >= 3 if PY3K: import builtins import functools reduce = functools.reduce zip = builtins.zip xrange = builtins.range map = builtins.map else: import __builtin__ import itertools builtins = __builtin__ reduce = __builtin__.reduce zip = itertools.izip xrange = __builtin__.xrange map = itertools.imap plotly-4.4.1+dfsg.orig/plotly/matplotlylib/mplexporter/exporter.py0000644000175000017500000003045213525746125025131 0ustar noahfxnoahfx""" Matplotlib Exporter =================== This submodule contains tools for crawling a matplotlib figure and exporting relevant pieces to a renderer. """ import warnings import io from . import utils import matplotlib from matplotlib import transforms, collections from matplotlib.backends.backend_agg import FigureCanvasAgg class Exporter(object): """Matplotlib Exporter Parameters ---------- renderer : Renderer object The renderer object called by the exporter to create a figure visualization. See mplexporter.Renderer for information on the methods which should be defined within the renderer. close_mpl : bool If True (default), close the matplotlib figure as it is rendered. This is useful for when the exporter is used within the notebook, or with an interactive matplotlib backend. """ def __init__(self, renderer, close_mpl=True): self.close_mpl = close_mpl self.renderer = renderer def run(self, fig): """ Run the exporter on the given figure Parmeters --------- fig : matplotlib.Figure instance The figure to export """ # Calling savefig executes the draw() command, putting elements # in the correct place. if fig.canvas is None: canvas = FigureCanvasAgg(fig) fig.savefig(io.BytesIO(), format='png', dpi=fig.dpi) if self.close_mpl: import matplotlib.pyplot as plt plt.close(fig) self.crawl_fig(fig) @staticmethod def process_transform(transform, ax=None, data=None, return_trans=False, force_trans=None): """Process the transform and convert data to figure or data coordinates Parameters ---------- transform : matplotlib Transform object The transform applied to the data ax : matplotlib Axes object (optional) The axes the data is associated with data : ndarray (optional) The array of data to be transformed. return_trans : bool (optional) If true, return the final transform of the data force_trans : matplotlib.transform instance (optional) If supplied, first force the data to this transform Returns ------- code : string Code is either "data", "axes", "figure", or "display", indicating the type of coordinates output. transform : matplotlib transform the transform used to map input data to output data. Returned only if return_trans is True new_data : ndarray Data transformed to match the given coordinate code. Returned only if data is specified """ if isinstance(transform, transforms.BlendedGenericTransform): warnings.warn("Blended transforms not yet supported. " "Zoom behavior may not work as expected.") if force_trans is not None: if data is not None: data = (transform - force_trans).transform(data) transform = force_trans code = "display" if ax is not None: for (c, trans) in [("data", ax.transData), ("axes", ax.transAxes), ("figure", ax.figure.transFigure), ("display", transforms.IdentityTransform())]: if transform.contains_branch(trans): code, transform = (c, transform - trans) break if data is not None: if return_trans: return code, transform.transform(data), transform else: return code, transform.transform(data) else: if return_trans: return code, transform else: return code def crawl_fig(self, fig): """Crawl the figure and process all axes""" with self.renderer.draw_figure(fig=fig, props=utils.get_figure_properties(fig)): for ax in fig.axes: self.crawl_ax(ax) def crawl_ax(self, ax): """Crawl the axes and process all elements within""" with self.renderer.draw_axes(ax=ax, props=utils.get_axes_properties(ax)): for line in ax.lines: self.draw_line(ax, line) for text in ax.texts: self.draw_text(ax, text) for (text, ttp) in zip([ax.xaxis.label, ax.yaxis.label, ax.title], ["xlabel", "ylabel", "title"]): if(hasattr(text, 'get_text') and text.get_text()): self.draw_text(ax, text, force_trans=ax.transAxes, text_type=ttp) for artist in ax.artists: # TODO: process other artists if isinstance(artist, matplotlib.text.Text): self.draw_text(ax, artist) for patch in ax.patches: self.draw_patch(ax, patch) for collection in ax.collections: self.draw_collection(ax, collection) for image in ax.images: self.draw_image(ax, image) legend = ax.get_legend() if legend is not None: props = utils.get_legend_properties(ax, legend) with self.renderer.draw_legend(legend=legend, props=props): if props['visible']: self.crawl_legend(ax, legend) def crawl_legend(self, ax, legend): """ Recursively look through objects in legend children """ legendElements = list(utils.iter_all_children(legend._legend_box, skipContainers=True)) legendElements.append(legend.legendPatch) for child in legendElements: # force a large zorder so it appears on top child.set_zorder(1E6 + child.get_zorder()) # reorder border box to make sure marks are visible if isinstance(child, matplotlib.patches.FancyBboxPatch): child.set_zorder(child.get_zorder()-1) try: # What kind of object... if isinstance(child, matplotlib.patches.Patch): self.draw_patch(ax, child, force_trans=ax.transAxes) elif isinstance(child, matplotlib.text.Text): if child.get_text() != 'None': self.draw_text(ax, child, force_trans=ax.transAxes) elif isinstance(child, matplotlib.lines.Line2D): self.draw_line(ax, child, force_trans=ax.transAxes) elif isinstance(child, matplotlib.collections.Collection): self.draw_collection(ax, child, force_pathtrans=ax.transAxes) else: warnings.warn("Legend element %s not impemented" % child) except NotImplementedError: warnings.warn("Legend element %s not impemented" % child) def draw_line(self, ax, line, force_trans=None): """Process a matplotlib line and call renderer.draw_line""" coordinates, data = self.process_transform(line.get_transform(), ax, line.get_xydata(), force_trans=force_trans) linestyle = utils.get_line_style(line) if (linestyle['dasharray'] is None and linestyle['drawstyle'] == 'default'): linestyle = None markerstyle = utils.get_marker_style(line) if (markerstyle['marker'] in ['None', 'none', None] or markerstyle['markerpath'][0].size == 0): markerstyle = None label = line.get_label() if markerstyle or linestyle: self.renderer.draw_marked_line(data=data, coordinates=coordinates, linestyle=linestyle, markerstyle=markerstyle, label=label, mplobj=line) def draw_text(self, ax, text, force_trans=None, text_type=None): """Process a matplotlib text object and call renderer.draw_text""" content = text.get_text() if content: transform = text.get_transform() position = text.get_position() coords, position = self.process_transform(transform, ax, position, force_trans=force_trans) style = utils.get_text_style(text) self.renderer.draw_text(text=content, position=position, coordinates=coords, text_type=text_type, style=style, mplobj=text) def draw_patch(self, ax, patch, force_trans=None): """Process a matplotlib patch object and call renderer.draw_path""" vertices, pathcodes = utils.SVG_path(patch.get_path()) transform = patch.get_transform() coordinates, vertices = self.process_transform(transform, ax, vertices, force_trans=force_trans) linestyle = utils.get_path_style(patch, fill=patch.get_fill()) self.renderer.draw_path(data=vertices, coordinates=coordinates, pathcodes=pathcodes, style=linestyle, mplobj=patch) def draw_collection(self, ax, collection, force_pathtrans=None, force_offsettrans=None): """Process a matplotlib collection and call renderer.draw_collection""" (transform, transOffset, offsets, paths) = collection._prepare_points() offset_coords, offsets = self.process_transform( transOffset, ax, offsets, force_trans=force_offsettrans) path_coords = self.process_transform( transform, ax, force_trans=force_pathtrans) processed_paths = [utils.SVG_path(path) for path in paths] processed_paths = [(self.process_transform( transform, ax, path[0], force_trans=force_pathtrans)[1], path[1]) for path in processed_paths] path_transforms = collection.get_transforms() try: # matplotlib 1.3: path_transforms are transform objects. # Convert them to numpy arrays. path_transforms = [t.get_matrix() for t in path_transforms] except AttributeError: # matplotlib 1.4: path transforms are already numpy arrays. pass styles = {'linewidth': collection.get_linewidths(), 'facecolor': collection.get_facecolors(), 'edgecolor': collection.get_edgecolors(), 'alpha': collection._alpha, 'zorder': collection.get_zorder()} offset_dict = {"data": "before", "screen": "after"} offset_order = offset_dict[collection.get_offset_position()] self.renderer.draw_path_collection(paths=processed_paths, path_coordinates=path_coords, path_transforms=path_transforms, offsets=offsets, offset_coordinates=offset_coords, offset_order=offset_order, styles=styles, mplobj=collection) def draw_image(self, ax, image): """Process a matplotlib image object and call renderer.draw_image""" self.renderer.draw_image(imdata=utils.image_to_base64(image), extent=image.get_extent(), coordinates="data", style={"alpha": image.get_alpha(), "zorder": image.get_zorder()}, mplobj=image) plotly-4.4.1+dfsg.orig/plotly/matplotlylib/mplexporter/tools.py0000644000175000017500000000330413525746125024415 0ustar noahfxnoahfx""" Tools for matplotlib plot exporting """ def ipynb_vega_init(): """Initialize the IPython notebook display elements This function borrows heavily from the excellent vincent package: http://github.com/wrobstory/vincent """ try: from IPython.core.display import display, HTML except ImportError: print('IPython Notebook could not be loaded.') require_js = ''' if (window['d3'] === undefined) {{ require.config({{ paths: {{d3: "http://d3js.org/d3.v3.min"}} }}); require(["d3"], function(d3) {{ window.d3 = d3; {0} }}); }}; if (window['topojson'] === undefined) {{ require.config( {{ paths: {{topojson: "http://d3js.org/topojson.v1.min"}} }} ); require(["topojson"], function(topojson) {{ window.topojson = topojson; }}); }}; ''' d3_geo_projection_js_url = "http://d3js.org/d3.geo.projection.v0.min.js" d3_layout_cloud_js_url = ("http://wrobstory.github.io/d3-cloud/" "d3.layout.cloud.js") topojson_js_url = "http://d3js.org/topojson.v1.min.js" vega_js_url = 'http://trifacta.github.com/vega/vega.js' dep_libs = '''$.getScript("%s", function() { $.getScript("%s", function() { $.getScript("%s", function() { $.getScript("%s", function() { $([IPython.events]).trigger("vega_loaded.vincent"); }) }) }) });''' % (d3_geo_projection_js_url, d3_layout_cloud_js_url, topojson_js_url, vega_js_url) load_js = require_js.format(dep_libs) html = '' display(HTML(html)) plotly-4.4.1+dfsg.orig/plotly/matplotlylib/mplexporter/__init__.py0000644000175000017500000000007713525746125025020 0ustar noahfxnoahfxfrom .renderers import Renderer from .exporter import Exporter plotly-4.4.1+dfsg.orig/plotly/matplotlylib/mplexporter/utils.py0000644000175000017500000002720313525746125024421 0ustar noahfxnoahfx""" Utility Routines for Working with Matplotlib Objects ==================================================== """ import itertools import io import base64 import numpy as np import warnings import matplotlib from matplotlib.colors import colorConverter from matplotlib.path import Path from matplotlib.markers import MarkerStyle from matplotlib.transforms import Affine2D from matplotlib import ticker def export_color(color): """Convert matplotlib color code to hex color or RGBA color""" if color is None or colorConverter.to_rgba(color)[3] == 0: return 'none' elif colorConverter.to_rgba(color)[3] == 1: rgb = colorConverter.to_rgb(color) return '#{0:02X}{1:02X}{2:02X}'.format(*(int(255 * c) for c in rgb)) else: c = colorConverter.to_rgba(color) return "rgba(" + ", ".join(str(int(np.round(val * 255))) for val in c[:3])+', '+str(c[3])+")" def _many_to_one(input_dict): """Convert a many-to-one mapping to a one-to-one mapping""" return dict((key, val) for keys, val in input_dict.items() for key in keys) LINESTYLES = _many_to_one({('solid', '-', (None, None)): 'none', ('dashed', '--'): "6,6", ('dotted', ':'): "2,2", ('dashdot', '-.'): "4,4,2,4", ('', ' ', 'None', 'none'): None}) def get_dasharray(obj): """Get an SVG dash array for the given matplotlib linestyle Parameters ---------- obj : matplotlib object The matplotlib line or path object, which must have a get_linestyle() method which returns a valid matplotlib line code Returns ------- dasharray : string The HTML/SVG dasharray code associated with the object. """ if obj.__dict__.get('_dashSeq', None) is not None: return ','.join(map(str, obj._dashSeq)) else: ls = obj.get_linestyle() dasharray = LINESTYLES.get(ls, 'not found') if dasharray == 'not found': warnings.warn("line style '{0}' not understood: " "defaulting to solid line.".format(ls)) dasharray = LINESTYLES['solid'] return dasharray PATH_DICT = {Path.LINETO: 'L', Path.MOVETO: 'M', Path.CURVE3: 'S', Path.CURVE4: 'C', Path.CLOSEPOLY: 'Z'} def SVG_path(path, transform=None, simplify=False): """Construct the vertices and SVG codes for the path Parameters ---------- path : matplotlib.Path object transform : matplotlib transform (optional) if specified, the path will be transformed before computing the output. Returns ------- vertices : array The shape (M, 2) array of vertices of the Path. Note that some Path codes require multiple vertices, so the length of these vertices may be longer than the list of path codes. path_codes : list A length N list of single-character path codes, N <= M. Each code is a single character, in ['L','M','S','C','Z']. See the standard SVG path specification for a description of these. """ if transform is not None: path = path.transformed(transform) vc_tuples = [(vertices if path_code != Path.CLOSEPOLY else [], PATH_DICT[path_code]) for (vertices, path_code) in path.iter_segments(simplify=simplify)] if not vc_tuples: # empty path is a special case return np.zeros((0, 2)), [] else: vertices, codes = zip(*vc_tuples) vertices = np.array(list(itertools.chain(*vertices))).reshape(-1, 2) return vertices, list(codes) def get_path_style(path, fill=True): """Get the style dictionary for matplotlib path objects""" style = {} style['alpha'] = path.get_alpha() if style['alpha'] is None: style['alpha'] = 1 style['edgecolor'] = export_color(path.get_edgecolor()) if fill: style['facecolor'] = export_color(path.get_facecolor()) else: style['facecolor'] = 'none' style['edgewidth'] = path.get_linewidth() style['dasharray'] = get_dasharray(path) style['zorder'] = path.get_zorder() return style def get_line_style(line): """Get the style dictionary for matplotlib line objects""" style = {} style['alpha'] = line.get_alpha() if style['alpha'] is None: style['alpha'] = 1 style['color'] = export_color(line.get_color()) style['linewidth'] = line.get_linewidth() style['dasharray'] = get_dasharray(line) style['zorder'] = line.get_zorder() style['drawstyle'] = line.get_drawstyle() return style def get_marker_style(line): """Get the style dictionary for matplotlib marker objects""" style = {} style['alpha'] = line.get_alpha() if style['alpha'] is None: style['alpha'] = 1 style['facecolor'] = export_color(line.get_markerfacecolor()) style['edgecolor'] = export_color(line.get_markeredgecolor()) style['edgewidth'] = line.get_markeredgewidth() style['marker'] = line.get_marker() markerstyle = MarkerStyle(line.get_marker()) markersize = line.get_markersize() markertransform = (markerstyle.get_transform() + Affine2D().scale(markersize, -markersize)) style['markerpath'] = SVG_path(markerstyle.get_path(), markertransform) style['markersize'] = markersize style['zorder'] = line.get_zorder() return style def get_text_style(text): """Return the text style dict for a text instance""" style = {} style['alpha'] = text.get_alpha() if style['alpha'] is None: style['alpha'] = 1 style['fontsize'] = text.get_size() style['color'] = export_color(text.get_color()) style['halign'] = text.get_horizontalalignment() # left, center, right style['valign'] = text.get_verticalalignment() # baseline, center, top style['malign'] = text._multialignment # text alignment when '\n' in text style['rotation'] = text.get_rotation() style['zorder'] = text.get_zorder() return style def get_axis_properties(axis): """Return the property dictionary for a matplotlib.Axis instance""" props = {} label1On = axis._major_tick_kw.get('label1On', True) if isinstance(axis, matplotlib.axis.XAxis): if label1On: props['position'] = "bottom" else: props['position'] = "top" elif isinstance(axis, matplotlib.axis.YAxis): if label1On: props['position'] = "left" else: props['position'] = "right" else: raise ValueError("{0} should be an Axis instance".format(axis)) # Use tick values if appropriate locator = axis.get_major_locator() props['nticks'] = len(locator()) if isinstance(locator, ticker.FixedLocator): props['tickvalues'] = list(locator()) else: props['tickvalues'] = None # Find tick formats formatter = axis.get_major_formatter() if isinstance(formatter, ticker.NullFormatter): props['tickformat'] = "" elif isinstance(formatter, ticker.FixedFormatter): props['tickformat'] = list(formatter.seq) elif not any(label.get_visible() for label in axis.get_ticklabels()): props['tickformat'] = "" else: props['tickformat'] = None # Get axis scale props['scale'] = axis.get_scale() # Get major tick label size (assumes that's all we really care about!) labels = axis.get_ticklabels() if labels: props['fontsize'] = labels[0].get_fontsize() else: props['fontsize'] = None # Get associated grid props['grid'] = get_grid_style(axis) # get axis visibility props['visible'] = axis.get_visible() return props def get_grid_style(axis): gridlines = axis.get_gridlines() if axis._gridOnMajor and len(gridlines) > 0: color = export_color(gridlines[0].get_color()) alpha = gridlines[0].get_alpha() dasharray = get_dasharray(gridlines[0]) return dict(gridOn=True, color=color, dasharray=dasharray, alpha=alpha) else: return {"gridOn": False} def get_figure_properties(fig): return {'figwidth': fig.get_figwidth(), 'figheight': fig.get_figheight(), 'dpi': fig.dpi} def get_axes_properties(ax): props = {'axesbg': export_color(ax.patch.get_facecolor()), 'axesbgalpha': ax.patch.get_alpha(), 'bounds': ax.get_position().bounds, 'dynamic': ax.get_navigate(), 'axison': ax.axison, 'frame_on': ax.get_frame_on(), 'patch_visible':ax.patch.get_visible(), 'axes': [get_axis_properties(ax.xaxis), get_axis_properties(ax.yaxis)]} for axname in ['x', 'y']: axis = getattr(ax, axname + 'axis') domain = getattr(ax, 'get_{0}lim'.format(axname))() lim = domain if isinstance(axis.converter, matplotlib.dates.DateConverter): scale = 'date' try: import pandas as pd from pandas.tseries.converter import PeriodConverter except ImportError: pd = None if (pd is not None and isinstance(axis.converter, PeriodConverter)): _dates = [pd.Period(ordinal=int(d), freq=axis.freq) for d in domain] domain = [(d.year, d.month - 1, d.day, d.hour, d.minute, d.second, 0) for d in _dates] else: domain = [(d.year, d.month - 1, d.day, d.hour, d.minute, d.second, d.microsecond * 1E-3) for d in matplotlib.dates.num2date(domain)] else: scale = axis.get_scale() if scale not in ['date', 'linear', 'log']: raise ValueError("Unknown axis scale: " "{0}".format(axis.get_scale())) props[axname + 'scale'] = scale props[axname + 'lim'] = lim props[axname + 'domain'] = domain return props def iter_all_children(obj, skipContainers=False): """ Returns an iterator over all childen and nested children using obj's get_children() method if skipContainers is true, only childless objects are returned. """ if hasattr(obj, 'get_children') and len(obj.get_children()) > 0: for child in obj.get_children(): if not skipContainers: yield child # could use `yield from` in python 3... for grandchild in iter_all_children(child, skipContainers): yield grandchild else: yield obj def get_legend_properties(ax, legend): handles, labels = ax.get_legend_handles_labels() visible = legend.get_visible() return {'handles': handles, 'labels': labels, 'visible': visible} def image_to_base64(image): """ Convert a matplotlib image to a base64 png representation Parameters ---------- image : matplotlib image object The image to be converted. Returns ------- image_base64 : string The UTF8-encoded base64 string representation of the png image. """ ax = image.axes binary_buffer = io.BytesIO() # image is saved in axes coordinates: we need to temporarily # set the correct limits to get the correct image lim = ax.axis() ax.axis(image.get_extent()) image.write_png(binary_buffer) ax.axis(lim) binary_buffer.seek(0) return base64.b64encode(binary_buffer.read()).decode('utf-8') plotly-4.4.1+dfsg.orig/plotly/matplotlylib/mplexporter/renderers/0000755000175000017500000000000013573746613024701 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/matplotlylib/mplexporter/renderers/base.py0000644000175000017500000003442513525746125026170 0ustar noahfxnoahfximport warnings import itertools from contextlib import contextmanager from distutils.version import LooseVersion import numpy as np import matplotlib as mpl from matplotlib import transforms from .. import utils from .. import _py3k_compat as py3k class Renderer(object): @staticmethod def ax_zoomable(ax): return bool(ax and ax.get_navigate()) @staticmethod def ax_has_xgrid(ax): return bool(ax and ax.xaxis._gridOnMajor and ax.yaxis.get_gridlines()) @staticmethod def ax_has_ygrid(ax): return bool(ax and ax.yaxis._gridOnMajor and ax.yaxis.get_gridlines()) @property def current_ax_zoomable(self): return self.ax_zoomable(self._current_ax) @property def current_ax_has_xgrid(self): return self.ax_has_xgrid(self._current_ax) @property def current_ax_has_ygrid(self): return self.ax_has_ygrid(self._current_ax) @contextmanager def draw_figure(self, fig, props): if hasattr(self, "_current_fig") and self._current_fig is not None: warnings.warn("figure embedded in figure: something is wrong") self._current_fig = fig self._fig_props = props self.open_figure(fig=fig, props=props) yield self.close_figure(fig=fig) self._current_fig = None self._fig_props = {} @contextmanager def draw_axes(self, ax, props): if hasattr(self, "_current_ax") and self._current_ax is not None: warnings.warn("axes embedded in axes: something is wrong") self._current_ax = ax self._ax_props = props self.open_axes(ax=ax, props=props) yield self.close_axes(ax=ax) self._current_ax = None self._ax_props = {} @contextmanager def draw_legend(self, legend, props): self._current_legend = legend self._legend_props = props self.open_legend(legend=legend, props=props) yield self.close_legend(legend=legend) self._current_legend = None self._legend_props = {} # Following are the functions which should be overloaded in subclasses def open_figure(self, fig, props): """ Begin commands for a particular figure. Parameters ---------- fig : matplotlib.Figure The Figure which will contain the ensuing axes and elements props : dictionary The dictionary of figure properties """ pass def close_figure(self, fig): """ Finish commands for a particular figure. Parameters ---------- fig : matplotlib.Figure The figure which is finished being drawn. """ pass def open_axes(self, ax, props): """ Begin commands for a particular axes. Parameters ---------- ax : matplotlib.Axes The Axes which will contain the ensuing axes and elements props : dictionary The dictionary of axes properties """ pass def close_axes(self, ax): """ Finish commands for a particular axes. Parameters ---------- ax : matplotlib.Axes The Axes which is finished being drawn. """ pass def open_legend(self, legend, props): """ Beging commands for a particular legend. Parameters ---------- legend : matplotlib.legend.Legend The Legend that will contain the ensuing elements props : dictionary The dictionary of legend properties """ pass def close_legend(self, legend): """ Finish commands for a particular legend. Parameters ---------- legend : matplotlib.legend.Legend The Legend which is finished being drawn """ pass def draw_marked_line(self, data, coordinates, linestyle, markerstyle, label, mplobj=None): """Draw a line that also has markers. If this isn't reimplemented by a renderer object, by default, it will make a call to BOTH draw_line and draw_markers when both markerstyle and linestyle are not None in the same Line2D object. """ if linestyle is not None: self.draw_line(data, coordinates, linestyle, label, mplobj) if markerstyle is not None: self.draw_markers(data, coordinates, markerstyle, label, mplobj) def draw_line(self, data, coordinates, style, label, mplobj=None): """ Draw a line. By default, draw the line via the draw_path() command. Some renderers might wish to override this and provide more fine-grained behavior. In matplotlib, lines are generally created via the plt.plot() command, though this command also can create marker collections. Parameters ---------- data : array_like A shape (N, 2) array of datapoints. coordinates : string A string code, which should be either 'data' for data coordinates, or 'figure' for figure (pixel) coordinates. style : dictionary a dictionary specifying the appearance of the line. mplobj : matplotlib object the matplotlib plot element which generated this line """ pathcodes = ['M'] + (data.shape[0] - 1) * ['L'] pathstyle = dict(facecolor='none', **style) pathstyle['edgecolor'] = pathstyle.pop('color') pathstyle['edgewidth'] = pathstyle.pop('linewidth') self.draw_path(data=data, coordinates=coordinates, pathcodes=pathcodes, style=pathstyle, mplobj=mplobj) @staticmethod def _iter_path_collection(paths, path_transforms, offsets, styles): """Build an iterator over the elements of the path collection""" N = max(len(paths), len(offsets)) # Before mpl 1.4.0, path_transform can be a false-y value, not a valid # transformation matrix. if LooseVersion(mpl.__version__) < LooseVersion('1.4.0'): if path_transforms is None: path_transforms = [np.eye(3)] edgecolor = styles['edgecolor'] if np.size(edgecolor) == 0: edgecolor = ['none'] facecolor = styles['facecolor'] if np.size(facecolor) == 0: facecolor = ['none'] elements = [paths, path_transforms, offsets, edgecolor, styles['linewidth'], facecolor] it = itertools return it.islice(py3k.zip(*py3k.map(it.cycle, elements)), N) def draw_path_collection(self, paths, path_coordinates, path_transforms, offsets, offset_coordinates, offset_order, styles, mplobj=None): """ Draw a collection of paths. The paths, offsets, and styles are all iterables, and the number of paths is max(len(paths), len(offsets)). By default, this is implemented via multiple calls to the draw_path() function. For efficiency, Renderers may choose to customize this implementation. Examples of path collections created by matplotlib are scatter plots, histograms, contour plots, and many others. Parameters ---------- paths : list list of tuples, where each tuple has two elements: (data, pathcodes). See draw_path() for a description of these. path_coordinates: string the coordinates code for the paths, which should be either 'data' for data coordinates, or 'figure' for figure (pixel) coordinates. path_transforms: array_like an array of shape (*, 3, 3), giving a series of 2D Affine transforms for the paths. These encode translations, rotations, and scalings in the standard way. offsets: array_like An array of offsets of shape (N, 2) offset_coordinates : string the coordinates code for the offsets, which should be either 'data' for data coordinates, or 'figure' for figure (pixel) coordinates. offset_order : string either "before" or "after". This specifies whether the offset is applied before the path transform, or after. The matplotlib backend equivalent is "before"->"data", "after"->"screen". styles: dictionary A dictionary in which each value is a list of length N, containing the style(s) for the paths. mplobj : matplotlib object the matplotlib plot element which generated this collection """ if offset_order == "before": raise NotImplementedError("offset before transform") for tup in self._iter_path_collection(paths, path_transforms, offsets, styles): (path, path_transform, offset, ec, lw, fc) = tup vertices, pathcodes = path path_transform = transforms.Affine2D(path_transform) vertices = path_transform.transform(vertices) # This is a hack: if path_coordinates == "figure": path_coordinates = "points" style = {"edgecolor": utils.export_color(ec), "facecolor": utils.export_color(fc), "edgewidth": lw, "dasharray": "10,0", "alpha": styles['alpha'], "zorder": styles['zorder']} self.draw_path(data=vertices, coordinates=path_coordinates, pathcodes=pathcodes, style=style, offset=offset, offset_coordinates=offset_coordinates, mplobj=mplobj) def draw_markers(self, data, coordinates, style, label, mplobj=None): """ Draw a set of markers. By default, this is done by repeatedly calling draw_path(), but renderers should generally overload this method to provide a more efficient implementation. In matplotlib, markers are created using the plt.plot() command. Parameters ---------- data : array_like A shape (N, 2) array of datapoints. coordinates : string A string code, which should be either 'data' for data coordinates, or 'figure' for figure (pixel) coordinates. style : dictionary a dictionary specifying the appearance of the markers. mplobj : matplotlib object the matplotlib plot element which generated this marker collection """ vertices, pathcodes = style['markerpath'] pathstyle = dict((key, style[key]) for key in ['alpha', 'edgecolor', 'facecolor', 'zorder', 'edgewidth']) pathstyle['dasharray'] = "10,0" for vertex in data: self.draw_path(data=vertices, coordinates="points", pathcodes=pathcodes, style=pathstyle, offset=vertex, offset_coordinates=coordinates, mplobj=mplobj) def draw_text(self, text, position, coordinates, style, text_type=None, mplobj=None): """ Draw text on the image. Parameters ---------- text : string The text to draw position : tuple The (x, y) position of the text coordinates : string A string code, which should be either 'data' for data coordinates, or 'figure' for figure (pixel) coordinates. style : dictionary a dictionary specifying the appearance of the text. text_type : string or None if specified, a type of text such as "xlabel", "ylabel", "title" mplobj : matplotlib object the matplotlib plot element which generated this text """ raise NotImplementedError() def draw_path(self, data, coordinates, pathcodes, style, offset=None, offset_coordinates="data", mplobj=None): """ Draw a path. In matplotlib, paths are created by filled regions, histograms, contour plots, patches, etc. Parameters ---------- data : array_like A shape (N, 2) array of datapoints. coordinates : string A string code, which should be either 'data' for data coordinates, 'figure' for figure (pixel) coordinates, or "points" for raw point coordinates (useful in conjunction with offsets, below). pathcodes : list A list of single-character SVG pathcodes associated with the data. Path codes are one of ['M', 'm', 'L', 'l', 'Q', 'q', 'T', 't', 'S', 's', 'C', 'c', 'Z', 'z'] See the SVG specification for details. Note that some path codes consume more than one datapoint (while 'Z' consumes none), so in general, the length of the pathcodes list will not be the same as that of the data array. style : dictionary a dictionary specifying the appearance of the line. offset : list (optional) the (x, y) offset of the path. If not given, no offset will be used. offset_coordinates : string (optional) A string code, which should be either 'data' for data coordinates, or 'figure' for figure (pixel) coordinates. mplobj : matplotlib object the matplotlib plot element which generated this path """ raise NotImplementedError() def draw_image(self, imdata, extent, coordinates, style, mplobj=None): """ Draw an image. Parameters ---------- imdata : string base64 encoded png representation of the image extent : list the axes extent of the image: [xmin, xmax, ymin, ymax] coordinates: string A string code, which should be either 'data' for data coordinates, or 'figure' for figure (pixel) coordinates. style : dictionary a dictionary specifying the appearance of the image mplobj : matplotlib object the matplotlib plot object which generated this image """ raise NotImplementedError() plotly-4.4.1+dfsg.orig/plotly/matplotlylib/mplexporter/renderers/vega_renderer.py0000644000175000017500000001224413525746125030061 0ustar noahfxnoahfximport warnings import json import random from .base import Renderer from ..exporter import Exporter class VegaRenderer(Renderer): def open_figure(self, fig, props): self.props = props self.figwidth = int(props['figwidth'] * props['dpi']) self.figheight = int(props['figheight'] * props['dpi']) self.data = [] self.scales = [] self.axes = [] self.marks = [] def open_axes(self, ax, props): if len(self.axes) > 0: warnings.warn("multiple axes not yet supported") self.axes = [dict(type="x", scale="x", ticks=10), dict(type="y", scale="y", ticks=10)] self.scales = [dict(name="x", domain=props['xlim'], type="linear", range="width", ), dict(name="y", domain=props['ylim'], type="linear", range="height", ),] def draw_line(self, data, coordinates, style, label, mplobj=None): if coordinates != 'data': warnings.warn("Only data coordinates supported. Skipping this") dataname = "table{0:03d}".format(len(self.data) + 1) # TODO: respect the other style settings self.data.append({'name': dataname, 'values': [dict(x=d[0], y=d[1]) for d in data]}) self.marks.append({'type': 'line', 'from': {'data': dataname}, 'properties': { "enter": { "interpolate": {"value": "monotone"}, "x": {"scale": "x", "field": "data.x"}, "y": {"scale": "y", "field": "data.y"}, "stroke": {"value": style['color']}, "strokeOpacity": {"value": style['alpha']}, "strokeWidth": {"value": style['linewidth']}, } } }) def draw_markers(self, data, coordinates, style, label, mplobj=None): if coordinates != 'data': warnings.warn("Only data coordinates supported. Skipping this") dataname = "table{0:03d}".format(len(self.data) + 1) # TODO: respect the other style settings self.data.append({'name': dataname, 'values': [dict(x=d[0], y=d[1]) for d in data]}) self.marks.append({'type': 'symbol', 'from': {'data': dataname}, 'properties': { "enter": { "interpolate": {"value": "monotone"}, "x": {"scale": "x", "field": "data.x"}, "y": {"scale": "y", "field": "data.y"}, "fill": {"value": style['facecolor']}, "fillOpacity": {"value": style['alpha']}, "stroke": {"value": style['edgecolor']}, "strokeOpacity": {"value": style['alpha']}, "strokeWidth": {"value": style['edgewidth']}, } } }) def draw_text(self, text, position, coordinates, style, text_type=None, mplobj=None): if text_type == 'xlabel': self.axes[0]['title'] = text elif text_type == 'ylabel': self.axes[1]['title'] = text class VegaHTML(object): def __init__(self, renderer): self.specification = dict(width=renderer.figwidth, height=renderer.figheight, data=renderer.data, scales=renderer.scales, axes=renderer.axes, marks=renderer.marks) def html(self): """Build the HTML representation for IPython.""" id = random.randint(0, 2 ** 16) html = '
' % id html += '\n' return html def _repr_html_(self): return self.html() def fig_to_vega(fig, notebook=False): """Convert a matplotlib figure to vega dictionary if notebook=True, then return an object which will display in a notebook otherwise, return an HTML string. """ renderer = VegaRenderer() Exporter(renderer).run(fig) vega_html = VegaHTML(renderer) if notebook: return vega_html else: return vega_html.html() VEGA_TEMPLATE = """ ( function() { var _do_plot = function() { if ( (typeof vg == 'undefined') && (typeof IPython != 'undefined')) { $([IPython.events]).on("vega_loaded.vincent", _do_plot); return; } vg.parse.spec(%s, function(chart) { chart({el: "#vis%d"}).update(); }); }; _do_plot(); })(); """ plotly-4.4.1+dfsg.orig/plotly/matplotlylib/mplexporter/renderers/__init__.py0000644000175000017500000000065113525746125027007 0ustar noahfxnoahfx""" Matplotlib Renderers ==================== This submodule contains renderer objects which define renderer behavior used within the Exporter class. The base renderer class is :class:`Renderer`, an abstract base class """ from .base import Renderer from .vega_renderer import VegaRenderer, fig_to_vega from .vincent_renderer import VincentRenderer, fig_to_vincent from .fake_renderer import FakeRenderer, FullFakeRenderer plotly-4.4.1+dfsg.orig/plotly/matplotlylib/mplexporter/renderers/fake_renderer.py0000644000175000017500000000500113525746125030036 0ustar noahfxnoahfxfrom .base import Renderer class FakeRenderer(Renderer): """ Fake Renderer This is a fake renderer which simply outputs a text tree representing the elements found in the plot(s). This is used in the unit tests for the package. Below are the methods your renderer must implement. You are free to do anything you wish within the renderer (i.e. build an XML or JSON representation, call an external API, etc.) Here the renderer just builds a simple string representation for testing purposes. """ def __init__(self): self.output = "" def open_figure(self, fig, props): self.output += "opening figure\n" def close_figure(self, fig): self.output += "closing figure\n" def open_axes(self, ax, props): self.output += " opening axes\n" def close_axes(self, ax): self.output += " closing axes\n" def open_legend(self, legend, props): self.output += " opening legend\n" def close_legend(self, legend): self.output += " closing legend\n" def draw_text(self, text, position, coordinates, style, text_type=None, mplobj=None): self.output += " draw text '{0}' {1}\n".format(text, text_type) def draw_path(self, data, coordinates, pathcodes, style, offset=None, offset_coordinates="data", mplobj=None): self.output += " draw path with {0} vertices\n".format(data.shape[0]) def draw_image(self, imdata, extent, coordinates, style, mplobj=None): self.output += " draw image of size {0}\n".format(len(imdata)) class FullFakeRenderer(FakeRenderer): """ Renderer with the full complement of methods. When the following are left undefined, they will be implemented via other methods in the class. They can be defined explicitly for more efficient or specialized use within the renderer implementation. """ def draw_line(self, data, coordinates, style, label, mplobj=None): self.output += " draw line with {0} points\n".format(data.shape[0]) def draw_markers(self, data, coordinates, style, label, mplobj=None): self.output += " draw {0} markers\n".format(data.shape[0]) def draw_path_collection(self, paths, path_coordinates, path_transforms, offsets, offset_coordinates, offset_order, styles, mplobj=None): self.output += (" draw path collection " "with {0} offsets\n".format(offsets.shape[0])) plotly-4.4.1+dfsg.orig/plotly/matplotlylib/mplexporter/renderers/vincent_renderer.py0000644000175000017500000000360213525746125030603 0ustar noahfxnoahfximport warnings from .base import Renderer from ..exporter import Exporter class VincentRenderer(Renderer): def open_figure(self, fig, props): self.chart = None self.figwidth = int(props['figwidth'] * props['dpi']) self.figheight = int(props['figheight'] * props['dpi']) def draw_line(self, data, coordinates, style, label, mplobj=None): import vincent # only import if VincentRenderer is used if coordinates != 'data': warnings.warn("Only data coordinates supported. Skipping this") linedata = {'x': data[:, 0], 'y': data[:, 1]} line = vincent.Line(linedata, iter_idx='x', width=self.figwidth, height=self.figheight) # TODO: respect the other style settings line.scales['color'].range = [style['color']] if self.chart is None: self.chart = line else: warnings.warn("Multiple plot elements not yet supported") def draw_markers(self, data, coordinates, style, label, mplobj=None): import vincent # only import if VincentRenderer is used if coordinates != 'data': warnings.warn("Only data coordinates supported. Skipping this") markerdata = {'x': data[:, 0], 'y': data[:, 1]} markers = vincent.Scatter(markerdata, iter_idx='x', width=self.figwidth, height=self.figheight) # TODO: respect the other style settings markers.scales['color'].range = [style['facecolor']] if self.chart is None: self.chart = markers else: warnings.warn("Multiple plot elements not yet supported") def fig_to_vincent(fig): """Convert a matplotlib figure to a vincent object""" renderer = VincentRenderer() exporter = Exporter(renderer) exporter.run(fig) return renderer.chart plotly-4.4.1+dfsg.orig/plotly/matplotlylib/__init__.py0000644000175000017500000000064013525746125022433 0ustar noahfxnoahfx""" matplotlylib ============ This module converts matplotlib figure objects into JSON structures which can be understood and visualized by Plotly. Most of the functionality should be accessed through the parent directory's 'tools' module or 'plotly' package. """ from __future__ import absolute_import from plotly.matplotlylib.renderer import PlotlyRenderer from plotly.matplotlylib.mplexporter import Exporter plotly-4.4.1+dfsg.orig/plotly/matplotlylib/mpltools.py0000644000175000017500000004761313525746125022560 0ustar noahfxnoahfx""" Tools A module for converting from mpl language to plotly language. """ import math import datetime import warnings import matplotlib.dates def check_bar_match(old_bar, new_bar): """Check if two bars belong in the same collection (bar chart). Positional arguments: old_bar -- a previously sorted bar dictionary. new_bar -- a new bar dictionary that needs to be sorted. """ tests = [] tests += (new_bar["orientation"] == old_bar["orientation"],) tests += (new_bar["facecolor"] == old_bar["facecolor"],) if new_bar["orientation"] == "v": new_width = new_bar["x1"] - new_bar["x0"] old_width = old_bar["x1"] - old_bar["x0"] tests += (new_width - old_width < 0.000001,) tests += (new_bar["y0"] == old_bar["y0"],) elif new_bar["orientation"] == "h": new_height = new_bar["y1"] - new_bar["y0"] old_height = old_bar["y1"] - old_bar["y0"] tests += (new_height - old_height < 0.000001,) tests += (new_bar["x0"] == old_bar["x0"],) if all(tests): return True else: return False def check_corners(inner_obj, outer_obj): inner_corners = inner_obj.get_window_extent().corners() outer_corners = outer_obj.get_window_extent().corners() if inner_corners[0][0] < outer_corners[0][0]: return False elif inner_corners[0][1] < outer_corners[0][1]: return False elif inner_corners[3][0] > outer_corners[3][0]: return False elif inner_corners[3][1] > outer_corners[3][1]: return False else: return True def convert_dash(mpl_dash): """Convert mpl line symbol to plotly line symbol and return symbol.""" if mpl_dash in DASH_MAP: return DASH_MAP[mpl_dash] else: dash_array = mpl_dash.split(",") if len(dash_array) < 2: return "solid" # Catch the exception where the off length is zero, in case # matplotlib 'solid' changes from '10,0' to 'N,0' if math.isclose(float(dash_array[1]), 0.0): return "solid" # If we can't find the dash pattern in the map, convert it # into custom values in px, e.g. '7,5' -> '7px,5px' dashpx = ",".join([x + "px" for x in dash_array]) # TODO: rewrite the convert_dash code # only strings 'solid', 'dashed', etc allowed if dashpx == "7.4px,3.2px": dashpx = "dashed" elif dashpx == "12.8px,3.2px,2.0px,3.2px": dashpx = "dashdot" elif dashpx == "2.0px,3.3px": dashpx = "dotted" return dashpx def convert_path(path): verts = path[0] # may use this later code = tuple(path[1]) if code in PATH_MAP: return PATH_MAP[code] else: return None def convert_symbol(mpl_symbol): """Convert mpl marker symbol to plotly symbol and return symbol.""" if isinstance(mpl_symbol, list): symbol = list() for s in mpl_symbol: symbol += [convert_symbol(s)] return symbol elif mpl_symbol in SYMBOL_MAP: return SYMBOL_MAP[mpl_symbol] else: return "circle" # default def hex_to_rgb(value): """ Change a hex color to an rgb tuple :param (str|unicode) value: The hex string we want to convert. :return: (int, int, int) The red, green, blue int-tuple. Example: '#FFFFFF' --> (255, 255, 255) """ value = value.lstrip("#") lv = len(value) return tuple(int(value[i : i + lv // 3], 16) for i in range(0, lv, lv // 3)) def merge_color_and_opacity(color, opacity): """ Merge hex color with an alpha (opacity) to get an rgba tuple. :param (str|unicode) color: A hex color string. :param (float|int) opacity: A value [0, 1] for the 'a' in 'rgba'. :return: (int, int, int, float) The rgba color and alpha tuple. """ if color is None: # None can be used as a placeholder, just bail. return None rgb_tup = hex_to_rgb(color) if opacity is None: return "rgb {}".format(rgb_tup) rgba_tup = rgb_tup + (opacity,) return "rgba {}".format(rgba_tup) def convert_va(mpl_va): """Convert mpl vertical alignment word to equivalent HTML word. Text alignment specifiers from mpl differ very slightly from those used in HTML. See the VA_MAP for more details. Positional arguments: mpl_va -- vertical mpl text alignment spec. """ if mpl_va in VA_MAP: return VA_MAP[mpl_va] else: return None # let plotly figure it out! def convert_x_domain(mpl_plot_bounds, mpl_max_x_bounds): """Map x dimension of current plot to plotly's domain space. The bbox used to locate an axes object in mpl differs from the method used to locate axes in plotly. The mpl version locates each axes in the figure so that axes in a single-plot figure might have the bounds, [0.125, 0.125, 0.775, 0.775] (x0, y0, width, height), in mpl's figure coordinates. However, the axes all share one space in plotly such that the domain will always be [0, 0, 1, 1] (x0, y0, x1, y1). To convert between the two, the mpl figure bounds need to be mapped to a [0, 1] domain for x and y. The margins set upon opening a new figure will appropriately match the mpl margins. Optionally, setting margins=0 and simply copying the domains from mpl to plotly would place axes appropriately. However, this would throw off axis and title labeling. Positional arguments: mpl_plot_bounds -- the (x0, y0, width, height) params for current ax ** mpl_max_x_bounds -- overall (x0, x1) bounds for all axes ** ** these are all specified in mpl figure coordinates """ mpl_x_dom = [mpl_plot_bounds[0], mpl_plot_bounds[0] + mpl_plot_bounds[2]] plotting_width = mpl_max_x_bounds[1] - mpl_max_x_bounds[0] x0 = (mpl_x_dom[0] - mpl_max_x_bounds[0]) / plotting_width x1 = (mpl_x_dom[1] - mpl_max_x_bounds[0]) / plotting_width return [x0, x1] def convert_y_domain(mpl_plot_bounds, mpl_max_y_bounds): """Map y dimension of current plot to plotly's domain space. The bbox used to locate an axes object in mpl differs from the method used to locate axes in plotly. The mpl version locates each axes in the figure so that axes in a single-plot figure might have the bounds, [0.125, 0.125, 0.775, 0.775] (x0, y0, width, height), in mpl's figure coordinates. However, the axes all share one space in plotly such that the domain will always be [0, 0, 1, 1] (x0, y0, x1, y1). To convert between the two, the mpl figure bounds need to be mapped to a [0, 1] domain for x and y. The margins set upon opening a new figure will appropriately match the mpl margins. Optionally, setting margins=0 and simply copying the domains from mpl to plotly would place axes appropriately. However, this would throw off axis and title labeling. Positional arguments: mpl_plot_bounds -- the (x0, y0, width, height) params for current ax ** mpl_max_y_bounds -- overall (y0, y1) bounds for all axes ** ** these are all specified in mpl figure coordinates """ mpl_y_dom = [mpl_plot_bounds[1], mpl_plot_bounds[1] + mpl_plot_bounds[3]] plotting_height = mpl_max_y_bounds[1] - mpl_max_y_bounds[0] y0 = (mpl_y_dom[0] - mpl_max_y_bounds[0]) / plotting_height y1 = (mpl_y_dom[1] - mpl_max_y_bounds[0]) / plotting_height return [y0, y1] def display_to_paper(x, y, layout): """Convert mpl display coordinates to plotly paper coordinates. Plotly references object positions with an (x, y) coordinate pair in either 'data' or 'paper' coordinates which reference actual data in a plot or the entire plotly axes space where the bottom-left of the bottom-left plot has the location (x, y) = (0, 0) and the top-right of the top-right plot has the location (x, y) = (1, 1). Display coordinates in mpl reference objects with an (x, y) pair in pixel coordinates, where the bottom-left corner is at the location (x, y) = (0, 0) and the top-right corner is at the location (x, y) = (figwidth*dpi, figheight*dpi). Here, figwidth and figheight are in inches and dpi are the dots per inch resolution. """ num_x = x - layout["margin"]["l"] den_x = layout["width"] - (layout["margin"]["l"] + layout["margin"]["r"]) num_y = y - layout["margin"]["b"] den_y = layout["height"] - (layout["margin"]["b"] + layout["margin"]["t"]) return num_x / den_x, num_y / den_y def get_axes_bounds(fig): """Return the entire axes space for figure. An axes object in mpl is specified by its relation to the figure where (0,0) corresponds to the bottom-left part of the figure and (1,1) corresponds to the top-right. Margins exist in matplotlib because axes objects normally don't go to the edges of the figure. In plotly, the axes area (where all subplots go) is always specified with the domain [0,1] for both x and y. This function finds the smallest box, specified by two points, that all of the mpl axes objects fit into. This box is then used to map mpl axes domains to plotly axes domains. """ x_min, x_max, y_min, y_max = [], [], [], [] for axes_obj in fig.get_axes(): bounds = axes_obj.get_position().bounds x_min.append(bounds[0]) x_max.append(bounds[0] + bounds[2]) y_min.append(bounds[1]) y_max.append(bounds[1] + bounds[3]) x_min, y_min, x_max, y_max = min(x_min), min(y_min), max(x_max), max(y_max) return (x_min, x_max), (y_min, y_max) def get_axis_mirror(main_spine, mirror_spine): if main_spine and mirror_spine: return "ticks" elif main_spine and not mirror_spine: return False elif not main_spine and mirror_spine: return False # can't handle this case yet! else: return False # nuttin'! def get_bar_gap(bar_starts, bar_ends, tol=1e-10): if len(bar_starts) == len(bar_ends) and len(bar_starts) > 1: sides1 = bar_starts[1:] sides2 = bar_ends[:-1] gaps = [s2 - s1 for s2, s1 in zip(sides1, sides2)] gap0 = gaps[0] uniform = all([abs(gap0 - gap) < tol for gap in gaps]) if uniform: return gap0 def convert_rgba_array(color_list): clean_color_list = list() for c in color_list: clean_color_list += [ (dict(r=int(c[0] * 255), g=int(c[1] * 255), b=int(c[2] * 255), a=c[3])) ] plotly_colors = list() for rgba in clean_color_list: plotly_colors += ["rgba({r},{g},{b},{a})".format(**rgba)] if len(plotly_colors) == 1: return plotly_colors[0] else: return plotly_colors def convert_path_array(path_array): symbols = list() for path in path_array: symbols += [convert_path(path)] if len(symbols) == 1: return symbols[0] else: return symbols def convert_linewidth_array(width_array): if len(width_array) == 1: return width_array[0] else: return width_array def convert_size_array(size_array): size = [math.sqrt(s) for s in size_array] if len(size) == 1: return size[0] else: return size def get_markerstyle_from_collection(props): markerstyle = dict( alpha=None, facecolor=convert_rgba_array(props["styles"]["facecolor"]), marker=convert_path_array(props["paths"]), edgewidth=convert_linewidth_array(props["styles"]["linewidth"]), # markersize=convert_size_array(props['styles']['size']), # TODO! markersize=convert_size_array(props["mplobj"].get_sizes()), edgecolor=convert_rgba_array(props["styles"]["edgecolor"]), ) return markerstyle def get_rect_xmin(data): """Find minimum x value from four (x,y) vertices.""" return min(data[0][0], data[1][0], data[2][0], data[3][0]) def get_rect_xmax(data): """Find maximum x value from four (x,y) vertices.""" return max(data[0][0], data[1][0], data[2][0], data[3][0]) def get_rect_ymin(data): """Find minimum y value from four (x,y) vertices.""" return min(data[0][1], data[1][1], data[2][1], data[3][1]) def get_rect_ymax(data): """Find maximum y value from four (x,y) vertices.""" return max(data[0][1], data[1][1], data[2][1], data[3][1]) def get_spine_visible(ax, spine_key): """Return some spine parameters for the spine, `spine_key`.""" spine = ax.spines[spine_key] ax_frame_on = ax.get_frame_on() spine_frame_like = spine.is_frame_like() if not spine.get_visible(): return False elif not spine._edgecolor[-1]: # user's may have set edgecolor alpha==0 return False elif not ax_frame_on and spine_frame_like: return False elif ax_frame_on and spine_frame_like: return True elif not ax_frame_on and not spine_frame_like: return True # we've already checked for that it's visible. else: return False # oh man, and i thought we exhausted the options... def is_bar(bar_containers, **props): """A test to decide whether a path is a bar from a vertical bar chart.""" # is this patch in a bar container? for container in bar_containers: if props["mplobj"] in container: return True return False def make_bar(**props): """Make an intermediate bar dictionary. This creates a bar dictionary which aids in the comparison of new bars to old bars from other bar chart (patch) collections. This is not the dictionary that needs to get passed to plotly as a data dictionary. That happens in PlotlyRenderer in that class's draw_bar method. In other words, this dictionary describes a SINGLE bar, whereas, plotly will require a set of bars to be passed in a data dictionary. """ return { "bar": props["mplobj"], "x0": get_rect_xmin(props["data"]), "y0": get_rect_ymin(props["data"]), "x1": get_rect_xmax(props["data"]), "y1": get_rect_ymax(props["data"]), "alpha": props["style"]["alpha"], "edgecolor": props["style"]["edgecolor"], "facecolor": props["style"]["facecolor"], "edgewidth": props["style"]["edgewidth"], "dasharray": props["style"]["dasharray"], "zorder": props["style"]["zorder"], } def prep_ticks(ax, index, ax_type, props): """Prepare axis obj belonging to axes obj. positional arguments: ax - the mpl axes instance index - the index of the axis in `props` ax_type - 'x' or 'y' (for now) props - an mplexporter poperties dictionary """ axis_dict = dict() if ax_type == "x": axis = ax.get_xaxis() elif ax_type == "y": axis = ax.get_yaxis() else: return dict() # whoops! scale = props["axes"][index]["scale"] if scale == "linear": # get tick location information try: tickvalues = props["axes"][index]["tickvalues"] tick0 = tickvalues[0] dticks = [ round(tickvalues[i] - tickvalues[i - 1], 12) for i in range(1, len(tickvalues) - 1) ] if all([dticks[i] == dticks[i - 1] for i in range(1, len(dticks) - 1)]): dtick = tickvalues[1] - tickvalues[0] else: warnings.warn( "'linear' {0}-axis tick spacing not even, " "ignoring mpl tick formatting.".format(ax_type) ) raise TypeError except (IndexError, TypeError): axis_dict["nticks"] = props["axes"][index]["nticks"] else: axis_dict["tick0"] = tick0 axis_dict["dtick"] = dtick axis_dict["tickmode"] = None elif scale == "log": try: axis_dict["tick0"] = props["axes"][index]["tickvalues"][0] axis_dict["dtick"] = ( props["axes"][index]["tickvalues"][1] - props["axes"][index]["tickvalues"][0] ) axis_dict["tickmode"] = None except (IndexError, TypeError): axis_dict = dict(nticks=props["axes"][index]["nticks"]) base = axis.get_transform().base if base == 10: if ax_type == "x": axis_dict["range"] = [ math.log10(props["xlim"][0]), math.log10(props["xlim"][1]), ] elif ax_type == "y": axis_dict["range"] = [ math.log10(props["ylim"][0]), math.log10(props["ylim"][1]), ] else: axis_dict = dict(range=None, type="linear") warnings.warn( "Converted non-base10 {0}-axis log scale to 'linear'" "".format(ax_type) ) else: return dict() # get tick label formatting information formatter = axis.get_major_formatter().__class__.__name__ if ax_type == "x" and "DateFormatter" in formatter: axis_dict["type"] = "date" try: axis_dict["tick0"] = mpl_dates_to_datestrings(axis_dict["tick0"], formatter) except KeyError: pass finally: axis_dict.pop("dtick", None) axis_dict.pop("tickmode", None) axis_dict["range"] = mpl_dates_to_datestrings(props["xlim"], formatter) if formatter == "LogFormatterMathtext": axis_dict["exponentformat"] = "e" return axis_dict def prep_xy_axis(ax, props, x_bounds, y_bounds): xaxis = dict( type=props["axes"][0]["scale"], range=list(props["xlim"]), showgrid=props["axes"][0]["grid"]["gridOn"], domain=convert_x_domain(props["bounds"], x_bounds), side=props["axes"][0]["position"], tickfont=dict(size=props["axes"][0]["fontsize"]), ) xaxis.update(prep_ticks(ax, 0, "x", props)) yaxis = dict( type=props["axes"][1]["scale"], range=list(props["ylim"]), showgrid=props["axes"][1]["grid"]["gridOn"], domain=convert_y_domain(props["bounds"], y_bounds), side=props["axes"][1]["position"], tickfont=dict(size=props["axes"][1]["fontsize"]), ) yaxis.update(prep_ticks(ax, 1, "y", props)) return xaxis, yaxis def mpl_dates_to_datestrings(dates, mpl_formatter): """Convert matplotlib dates to iso-formatted-like time strings. Plotly's accepted format: "YYYY-MM-DD HH:MM:SS" (e.g., 2001-01-01 00:00:00) Info on mpl dates: http://matplotlib.org/api/dates_api.html """ _dates = dates # this is a pandas datetime formatter, times show up in floating point days # since the epoch (1970-01-01T00:00:00+00:00) if mpl_formatter == "TimeSeries_DateFormatter": try: dates = matplotlib.dates.epoch2num([date * 24 * 60 * 60 for date in dates]) dates = matplotlib.dates.num2date(dates) except: return _dates # the rest of mpl dates are in floating point days since # (0001-01-01T00:00:00+00:00) + 1. I.e., (0001-01-01T00:00:00+00:00) == 1.0 # according to mpl --> try num2date(1) else: try: dates = matplotlib.dates.num2date(dates) except: return _dates time_stings = [ " ".join(date.isoformat().split("+")[0].split("T")) for date in dates ] return time_stings # dashed is dash in matplotlib DASH_MAP = { "10,0": "solid", "6,6": "dash", "2,2": "circle", "4,4,2,4": "dashdot", "none": "solid", "7.4,3.2": "dash", } PATH_MAP = { ("M", "C", "C", "C", "C", "C", "C", "C", "C", "Z"): "o", ("M", "L", "L", "L", "L", "L", "L", "L", "L", "L", "Z"): "*", ("M", "L", "L", "L", "L", "L", "L", "L", "Z"): "8", ("M", "L", "L", "L", "L", "L", "Z"): "h", ("M", "L", "L", "L", "L", "Z"): "p", ("M", "L", "M", "L", "M", "L"): "1", ("M", "L", "L", "L", "Z"): "s", ("M", "L", "M", "L"): "+", ("M", "L", "L", "Z"): "^", ("M", "L"): "|", } SYMBOL_MAP = { "o": "circle", "v": "triangle-down", "^": "triangle-up", "<": "triangle-left", ">": "triangle-right", "s": "square", "+": "cross", "x": "x", "*": "star", "D": "diamond", "d": "diamond", } VA_MAP = {"center": "middle", "baseline": "bottom", "top": "top"} plotly-4.4.1+dfsg.orig/plotly/matplotlylib/renderer.py0000644000175000017500000007535413547055022022511 0ustar noahfxnoahfx""" Renderer Module This module defines the PlotlyRenderer class and a single function, fig_to_plotly, which is intended to be the main way that user's will interact with the matplotlylib package. """ from __future__ import absolute_import import six import warnings import plotly.graph_objs as go from plotly.matplotlylib.mplexporter import Renderer from plotly.matplotlylib import mpltools # Warning format def warning_on_one_line(msg, category, filename, lineno, file=None, line=None): return "%s:%s: %s:\n\n%s\n\n" % (filename, lineno, category.__name__, msg) warnings.formatwarning = warning_on_one_line class PlotlyRenderer(Renderer): """A renderer class inheriting from base for rendering mpl plots in plotly. A renderer class to be used with an exporter for rendering matplotlib plots in Plotly. This module defines the PlotlyRenderer class which handles the creation of the JSON structures that get sent to plotly. All class attributes available are defined in __init__(). Basic Usage: # (mpl code) # fig = gcf() renderer = PlotlyRenderer(fig) exporter = Exporter(renderer) exporter.run(fig) # ... et voila """ def __init__(self): """Initialize PlotlyRenderer obj. PlotlyRenderer obj is called on by an Exporter object to draw matplotlib objects like figures, axes, text, etc. All class attributes are listed here in the __init__ method. """ self.plotly_fig = go.Figure() self.mpl_fig = None self.current_mpl_ax = None self.bar_containers = None self.current_bars = [] self.axis_ct = 0 self.x_is_mpl_date = False self.mpl_x_bounds = (0, 1) self.mpl_y_bounds = (0, 1) self.msg = "Initialized PlotlyRenderer\n" def open_figure(self, fig, props): """Creates a new figure by beginning to fill out layout dict. The 'autosize' key is set to false so that the figure will mirror sizes set by mpl. The 'hovermode' key controls what shows up when you mouse around a figure in plotly, it's set to show the 'closest' point. Positional agurments: fig -- a matplotlib.figure.Figure object. props.keys(): [ 'figwidth', 'figheight', 'dpi' ] """ self.msg += "Opening figure\n" self.mpl_fig = fig self.plotly_fig["layout"] = go.Layout( width=int(props["figwidth"] * props["dpi"]), height=int(props["figheight"] * props["dpi"]), autosize=False, hovermode="closest", ) self.mpl_x_bounds, self.mpl_y_bounds = mpltools.get_axes_bounds(fig) margin = go.layout.Margin( l=int(self.mpl_x_bounds[0] * self.plotly_fig["layout"]["width"]), r=int((1 - self.mpl_x_bounds[1]) * self.plotly_fig["layout"]["width"]), t=int((1 - self.mpl_y_bounds[1]) * self.plotly_fig["layout"]["height"]), b=int(self.mpl_y_bounds[0] * self.plotly_fig["layout"]["height"]), pad=0, ) self.plotly_fig["layout"]["margin"] = margin def close_figure(self, fig): """Closes figure by cleaning up data and layout dictionaries. The PlotlyRenderer's job is to create an appropriate set of data and layout dictionaries. When the figure is closed, some cleanup and repair is necessary. This method removes inappropriate dictionary entries, freeing up Plotly to use defaults and best judgements to complete the entries. This method is called by an Exporter object. Positional arguments: fig -- a matplotlib.figure.Figure object. """ self.plotly_fig["layout"]["showlegend"] = False self.msg += "Closing figure\n" def open_axes(self, ax, props): """Setup a new axes object (subplot in plotly). Plotly stores information about subplots in different 'xaxis' and 'yaxis' objects which are numbered. These are just dictionaries included in the layout dictionary. This function takes information from the Exporter, fills in appropriate dictionary entries, and updates the layout dictionary. PlotlyRenderer keeps track of the number of plots by incrementing the axis_ct attribute. Setting the proper plot domain in plotly is a bit tricky. Refer to the documentation for mpltools.convert_x_domain and mpltools.convert_y_domain. Positional arguments: ax -- an mpl axes object. This will become a subplot in plotly. props.keys() -- [ 'axesbg', (background color for axes obj) 'axesbgalpha', (alpha, or opacity for background) 'bounds', ((x0, y0, width, height) for axes) 'dynamic', (zoom/pan-able?) 'axes', (list: [xaxis, yaxis]) 'xscale', (log, linear, or date) 'yscale', 'xlim', (range limits for x) 'ylim', 'xdomain' (xdomain=xlim, unless it's a date) 'ydomain' ] """ self.msg += " Opening axes\n" self.current_mpl_ax = ax self.bar_containers = [ c for c in ax.containers # empty is OK if c.__class__.__name__ == "BarContainer" ] self.current_bars = [] self.axis_ct += 1 # set defaults in axes xaxis = go.layout.XAxis( anchor="y{0}".format(self.axis_ct), zeroline=False, ticks="inside" ) yaxis = go.layout.YAxis( anchor="x{0}".format(self.axis_ct), zeroline=False, ticks="inside" ) # update defaults with things set in mpl mpl_xaxis, mpl_yaxis = mpltools.prep_xy_axis( ax=ax, props=props, x_bounds=self.mpl_x_bounds, y_bounds=self.mpl_y_bounds ) xaxis.update(mpl_xaxis) yaxis.update(mpl_yaxis) bottom_spine = mpltools.get_spine_visible(ax, "bottom") top_spine = mpltools.get_spine_visible(ax, "top") left_spine = mpltools.get_spine_visible(ax, "left") right_spine = mpltools.get_spine_visible(ax, "right") xaxis["mirror"] = mpltools.get_axis_mirror(bottom_spine, top_spine) yaxis["mirror"] = mpltools.get_axis_mirror(left_spine, right_spine) xaxis["showline"] = bottom_spine yaxis["showline"] = top_spine # put axes in our figure self.plotly_fig["layout"]["xaxis{0}".format(self.axis_ct)] = xaxis self.plotly_fig["layout"]["yaxis{0}".format(self.axis_ct)] = yaxis # let all subsequent dates be handled properly if required if "type" in dir(xaxis) and xaxis["type"] == "date": self.x_is_mpl_date = True def close_axes(self, ax): """Close the axes object and clean up. Bars from bar charts are given to PlotlyRenderer one-by-one, thus they need to be taken care of at the close of each axes object. The self.current_bars variable should be empty unless a bar chart has been created. Positional arguments: ax -- an mpl axes object, not required at this time. """ self.draw_bars(self.current_bars) self.msg += " Closing axes\n" self.x_is_mpl_date = False def draw_bars(self, bars): # sort bars according to bar containers mpl_traces = [] for container in self.bar_containers: mpl_traces.append( [ bar_props for bar_props in self.current_bars if bar_props["mplobj"] in container ] ) for trace in mpl_traces: self.draw_bar(trace) def draw_bar(self, coll): """Draw a collection of similar patches as a bar chart. After bars are sorted, an appropriate data dictionary must be created to tell plotly about this data. Just like draw_line or draw_markers, draw_bar translates patch/path information into something plotly understands. Positional arguments: patch_coll -- a collection of patches to be drawn as a bar chart. """ tol = 1e-10 trace = [mpltools.make_bar(**bar_props) for bar_props in coll] widths = [bar_props["x1"] - bar_props["x0"] for bar_props in trace] heights = [bar_props["y1"] - bar_props["y0"] for bar_props in trace] vertical = abs(sum(widths[0] - widths[iii] for iii in range(len(widths)))) < tol horizontal = ( abs(sum(heights[0] - heights[iii] for iii in range(len(heights)))) < tol ) if vertical and horizontal: # Check for monotonic x. Can't both be true! x_zeros = [bar_props["x0"] for bar_props in trace] if all( (x_zeros[iii + 1] > x_zeros[iii] for iii in range(len(x_zeros[:-1]))) ): orientation = "v" else: orientation = "h" elif vertical: orientation = "v" else: orientation = "h" if orientation == "v": self.msg += " Attempting to draw a vertical bar chart\n" old_heights = [bar_props["y1"] for bar_props in trace] for bar in trace: bar["y0"], bar["y1"] = 0, bar["y1"] - bar["y0"] new_heights = [bar_props["y1"] for bar_props in trace] # check if we're stacked or not... for old, new in zip(old_heights, new_heights): if abs(old - new) > tol: self.plotly_fig["layout"]["barmode"] = "stack" self.plotly_fig["layout"]["hovermode"] = "x" x = [bar["x0"] + (bar["x1"] - bar["x0"]) / 2 for bar in trace] y = [bar["y1"] for bar in trace] bar_gap = mpltools.get_bar_gap( [bar["x0"] for bar in trace], [bar["x1"] for bar in trace] ) if self.x_is_mpl_date: x = [bar["x0"] for bar in trace] formatter = ( self.current_mpl_ax.get_xaxis() .get_major_formatter() .__class__.__name__ ) x = mpltools.mpl_dates_to_datestrings(x, formatter) else: self.msg += " Attempting to draw a horizontal bar chart\n" old_rights = [bar_props["x1"] for bar_props in trace] for bar in trace: bar["x0"], bar["x1"] = 0, bar["x1"] - bar["x0"] new_rights = [bar_props["x1"] for bar_props in trace] # check if we're stacked or not... for old, new in zip(old_rights, new_rights): if abs(old - new) > tol: self.plotly_fig["layout"]["barmode"] = "stack" self.plotly_fig["layout"]["hovermode"] = "y" x = [bar["x1"] for bar in trace] y = [bar["y0"] + (bar["y1"] - bar["y0"]) / 2 for bar in trace] bar_gap = mpltools.get_bar_gap( [bar["y0"] for bar in trace], [bar["y1"] for bar in trace] ) bar = go.Bar( orientation=orientation, x=x, y=y, xaxis="x{0}".format(self.axis_ct), yaxis="y{0}".format(self.axis_ct), opacity=trace[0]["alpha"], # TODO: get all alphas if array? marker=go.bar.Marker( color=trace[0]["facecolor"], # TODO: get all line=dict(width=trace[0]["edgewidth"]), ), ) # TODO ditto if len(bar["x"]) > 1: self.msg += " Heck yeah, I drew that bar chart\n" self.plotly_fig.add_trace(bar), if bar_gap is not None: self.plotly_fig["layout"]["bargap"] = bar_gap else: self.msg += " Bar chart not drawn\n" warnings.warn( "found box chart data with length <= 1, " "assuming data redundancy, not plotting." ) def draw_marked_line(self, **props): """Create a data dict for a line obj. This will draw 'lines', 'markers', or 'lines+markers'. props.keys() -- [ 'coordinates', ('data', 'axes', 'figure', or 'display') 'data', (a list of xy pairs) 'mplobj', (the matplotlib.lines.Line2D obj being rendered) 'label', (the name of the Line2D obj being rendered) 'linestyle', (linestyle dict, can be None, see below) 'markerstyle', (markerstyle dict, can be None, see below) ] props['linestyle'].keys() -- [ 'alpha', (opacity of Line2D obj) 'color', (color of the line if it exists, not the marker) 'linewidth', 'dasharray', (code for linestyle, see DASH_MAP in mpltools.py) 'zorder', (viewing precedence when stacked with other objects) ] props['markerstyle'].keys() -- [ 'alpha', (opacity of Line2D obj) 'marker', (the mpl marker symbol, see SYMBOL_MAP in mpltools.py) 'facecolor', (color of the marker face) 'edgecolor', (color of the marker edge) 'edgewidth', (width of marker edge) 'markerpath', (an SVG path for drawing the specified marker) 'zorder', (viewing precedence when stacked with other objects) ] """ self.msg += " Attempting to draw a line " line, marker = {}, {} if props["linestyle"] and props["markerstyle"]: self.msg += "... with both lines+markers\n" mode = "lines+markers" elif props["linestyle"]: self.msg += "... with just lines\n" mode = "lines" elif props["markerstyle"]: self.msg += "... with just markers\n" mode = "markers" if props["linestyle"]: color = mpltools.merge_color_and_opacity( props["linestyle"]["color"], props["linestyle"]["alpha"] ) # print(mpltools.convert_dash(props['linestyle']['dasharray'])) line = go.scatter.Line( color=color, width=props["linestyle"]["linewidth"], dash=mpltools.convert_dash(props["linestyle"]["dasharray"]), ) if props["markerstyle"]: marker = go.scatter.Marker( opacity=props["markerstyle"]["alpha"], color=props["markerstyle"]["facecolor"], symbol=mpltools.convert_symbol(props["markerstyle"]["marker"]), size=props["markerstyle"]["markersize"], line=dict( color=props["markerstyle"]["edgecolor"], width=props["markerstyle"]["edgewidth"], ), ) if props["coordinates"] == "data": marked_line = go.Scatter( mode=mode, name=( str(props["label"]) if isinstance(props["label"], six.string_types) else props["label"] ), x=[xy_pair[0] for xy_pair in props["data"]], y=[xy_pair[1] for xy_pair in props["data"]], xaxis="x{0}".format(self.axis_ct), yaxis="y{0}".format(self.axis_ct), line=line, marker=marker, ) if self.x_is_mpl_date: formatter = ( self.current_mpl_ax.get_xaxis() .get_major_formatter() .__class__.__name__ ) marked_line["x"] = mpltools.mpl_dates_to_datestrings( marked_line["x"], formatter ) self.plotly_fig.add_trace(marked_line), self.msg += " Heck yeah, I drew that line\n" else: self.msg += " Line didn't have 'data' coordinates, " "not drawing\n" warnings.warn( "Bummer! Plotly can currently only draw Line2D " "objects from matplotlib that are in 'data' " "coordinates!" ) def draw_image(self, **props): """Draw image. Not implemented yet! """ self.msg += " Attempting to draw image\n" self.msg += " Not drawing image\n" warnings.warn( "Aw. Snap! You're gonna have to hold off on " "the selfies for now. Plotly can't import " "images from matplotlib yet!" ) def draw_path_collection(self, **props): """Add a path collection to data list as a scatter plot. Current implementation defaults such collections as scatter plots. Matplotlib supports collections that have many of the same parameters in common like color, size, path, etc. However, they needn't all be the same. Plotly does not currently support such functionality and therefore, the style for the first object is taken and used to define the remaining paths in the collection. props.keys() -- [ 'paths', (structure: [vertices, path_code]) 'path_coordinates', ('data', 'axes', 'figure', or 'display') 'path_transforms', (mpl transform, including Affine2D matrix) 'offsets', (offset from axes, helpful if in 'data') 'offset_coordinates', ('data', 'axes', 'figure', or 'display') 'offset_order', 'styles', (style dict, see below) 'mplobj' (the collection obj being drawn) ] props['styles'].keys() -- [ 'linewidth', (one or more linewidths) 'facecolor', (one or more facecolors for path) 'edgecolor', (one or more edgecolors for path) 'alpha', (one or more opacites for path) 'zorder', (precedence when stacked) ] """ self.msg += " Attempting to draw a path collection\n" if props["offset_coordinates"] is "data": markerstyle = mpltools.get_markerstyle_from_collection(props) scatter_props = { "coordinates": "data", "data": props["offsets"], "label": None, "markerstyle": markerstyle, "linestyle": None, } self.msg += " Drawing path collection as markers\n" self.draw_marked_line(**scatter_props) else: self.msg += " Path collection not linked to 'data', " "not drawing\n" warnings.warn( "Dang! That path collection is out of this " "world. I totally don't know what to do with " "it yet! Plotly can only import path " "collections linked to 'data' coordinates" ) def draw_path(self, **props): """Draw path, currently only attempts to draw bar charts. This function attempts to sort a given path into a collection of horizontal or vertical bar charts. Most of the actual code takes place in functions from mpltools.py. props.keys() -- [ 'data', (a list of verticies for the path) 'coordinates', ('data', 'axes', 'figure', or 'display') 'pathcodes', (code for the path, structure: ['M', 'L', 'Z', etc.]) 'style', (style dict, see below) 'mplobj' (the mpl path object) ] props['style'].keys() -- [ 'alpha', (opacity of path obj) 'edgecolor', 'facecolor', 'edgewidth', 'dasharray', (style for path's enclosing line) 'zorder' (precedence of obj when stacked) ] """ self.msg += " Attempting to draw a path\n" is_bar = mpltools.is_bar(self.current_mpl_ax.containers, **props) if is_bar: self.current_bars += [props] else: self.msg += " This path isn't a bar, not drawing\n" warnings.warn( "I found a path object that I don't think is part " "of a bar chart. Ignoring." ) def draw_text(self, **props): """Create an annotation dict for a text obj. Currently, plotly uses either 'page' or 'data' to reference annotation locations. These refer to 'display' and 'data', respectively for the 'coordinates' key used in the Exporter. Appropriate measures are taken to transform text locations to reference one of these two options. props.keys() -- [ 'text', (actual content string, not the text obj) 'position', (an x, y pair, not an mpl Bbox) 'coordinates', ('data', 'axes', 'figure', 'display') 'text_type', ('title', 'xlabel', or 'ylabel') 'style', (style dict, see below) 'mplobj' (actual mpl text object) ] props['style'].keys() -- [ 'alpha', (opacity of text) 'fontsize', (size in points of text) 'color', (hex color) 'halign', (horizontal alignment, 'left', 'center', or 'right') 'valign', (vertical alignment, 'baseline', 'center', or 'top') 'rotation', 'zorder', (precedence of text when stacked with other objs) ] """ self.msg += " Attempting to draw an mpl text object\n" if not mpltools.check_corners(props["mplobj"], self.mpl_fig): warnings.warn( "Looks like the annotation(s) you are trying \n" "to draw lies/lay outside the given figure size.\n\n" "Therefore, the resulting Plotly figure may not be \n" "large enough to view the full text. To adjust \n" "the size of the figure, use the 'width' and \n" "'height' keys in the Layout object. Alternatively,\n" "use the Margin object to adjust the figure's margins." ) align = props["mplobj"]._multialignment if not align: align = props["style"]["halign"] # mpl default if "annotations" not in self.plotly_fig["layout"]: self.plotly_fig["layout"]["annotations"] = [] if props["text_type"] == "xlabel": self.msg += " Text object is an xlabel\n" self.draw_xlabel(**props) elif props["text_type"] == "ylabel": self.msg += " Text object is a ylabel\n" self.draw_ylabel(**props) elif props["text_type"] == "title": self.msg += " Text object is a title\n" self.draw_title(**props) else: # just a regular text annotation... self.msg += " Text object is a normal annotation\n" if props["coordinates"] is not "data": self.msg += ( " Text object isn't linked to 'data' " "coordinates\n" ) x_px, y_px = ( props["mplobj"].get_transform().transform(props["position"]) ) x, y = mpltools.display_to_paper(x_px, y_px, self.plotly_fig["layout"]) xref = "paper" yref = "paper" xanchor = props["style"]["halign"] # no difference here! yanchor = mpltools.convert_va(props["style"]["valign"]) else: self.msg += " Text object is linked to 'data' " "coordinates\n" x, y = props["position"] axis_ct = self.axis_ct xaxis = self.plotly_fig["layout"]["xaxis{0}".format(axis_ct)] yaxis = self.plotly_fig["layout"]["yaxis{0}".format(axis_ct)] if ( xaxis["range"][0] < x < xaxis["range"][1] and yaxis["range"][0] < y < yaxis["range"][1] ): xref = "x{0}".format(self.axis_ct) yref = "y{0}".format(self.axis_ct) else: self.msg += ( " Text object is outside " "plotting area, making 'paper' reference.\n" ) x_px, y_px = ( props["mplobj"].get_transform().transform(props["position"]) ) x, y = mpltools.display_to_paper( x_px, y_px, self.plotly_fig["layout"] ) xref = "paper" yref = "paper" xanchor = props["style"]["halign"] # no difference here! yanchor = mpltools.convert_va(props["style"]["valign"]) annotation = go.layout.Annotation( text=( str(props["text"]) if isinstance(props["text"], six.string_types) else props["text"] ), opacity=props["style"]["alpha"], x=x, y=y, xref=xref, yref=yref, align=align, xanchor=xanchor, yanchor=yanchor, showarrow=False, # change this later? font=go.layout.annotation.Font( color=props["style"]["color"], size=props["style"]["fontsize"] ), ) self.plotly_fig["layout"]["annotations"] += (annotation,) self.msg += " Heck, yeah I drew that annotation\n" def draw_title(self, **props): """Add a title to the current subplot in layout dictionary. If there exists more than a single plot in the figure, titles revert to 'page'-referenced annotations. props.keys() -- [ 'text', (actual content string, not the text obj) 'position', (an x, y pair, not an mpl Bbox) 'coordinates', ('data', 'axes', 'figure', 'display') 'text_type', ('title', 'xlabel', or 'ylabel') 'style', (style dict, see below) 'mplobj' (actual mpl text object) ] props['style'].keys() -- [ 'alpha', (opacity of text) 'fontsize', (size in points of text) 'color', (hex color) 'halign', (horizontal alignment, 'left', 'center', or 'right') 'valign', (vertical alignment, 'baseline', 'center', or 'top') 'rotation', 'zorder', (precedence of text when stacked with other objs) ] """ self.msg += " Attempting to draw a title\n" if len(self.mpl_fig.axes) > 1: self.msg += ( " More than one subplot, adding title as " "annotation\n" ) x_px, y_px = props["mplobj"].get_transform().transform(props["position"]) x, y = mpltools.display_to_paper(x_px, y_px, self.plotly_fig["layout"]) annotation = go.layout.Annotation( text=props["text"], font=go.layout.annotation.Font( color=props["style"]["color"], size=props["style"]["fontsize"] ), xref="paper", yref="paper", x=x, y=y, xanchor="center", yanchor="bottom", showarrow=False, # no arrow for a title! ) self.plotly_fig["layout"]["annotations"] += (annotation,) else: self.msg += ( " Only one subplot found, adding as a " "plotly title\n" ) self.plotly_fig["layout"]["title"] = props["text"] titlefont = dict( size=props["style"]["fontsize"], color=props["style"]["color"] ) self.plotly_fig["layout"]["titlefont"] = titlefont def draw_xlabel(self, **props): """Add an xaxis label to the current subplot in layout dictionary. props.keys() -- [ 'text', (actual content string, not the text obj) 'position', (an x, y pair, not an mpl Bbox) 'coordinates', ('data', 'axes', 'figure', 'display') 'text_type', ('title', 'xlabel', or 'ylabel') 'style', (style dict, see below) 'mplobj' (actual mpl text object) ] props['style'].keys() -- [ 'alpha', (opacity of text) 'fontsize', (size in points of text) 'color', (hex color) 'halign', (horizontal alignment, 'left', 'center', or 'right') 'valign', (vertical alignment, 'baseline', 'center', or 'top') 'rotation', 'zorder', (precedence of text when stacked with other objs) ] """ self.msg += " Adding xlabel\n" axis_key = "xaxis{0}".format(self.axis_ct) self.plotly_fig["layout"][axis_key]["title"] = str(props["text"]) titlefont = dict(size=props["style"]["fontsize"], color=props["style"]["color"]) self.plotly_fig["layout"][axis_key]["titlefont"] = titlefont def draw_ylabel(self, **props): """Add a yaxis label to the current subplot in layout dictionary. props.keys() -- [ 'text', (actual content string, not the text obj) 'position', (an x, y pair, not an mpl Bbox) 'coordinates', ('data', 'axes', 'figure', 'display') 'text_type', ('title', 'xlabel', or 'ylabel') 'style', (style dict, see below) 'mplobj' (actual mpl text object) ] props['style'].keys() -- [ 'alpha', (opacity of text) 'fontsize', (size in points of text) 'color', (hex color) 'halign', (horizontal alignment, 'left', 'center', or 'right') 'valign', (vertical alignment, 'baseline', 'center', or 'top') 'rotation', 'zorder', (precedence of text when stacked with other objs) ] """ self.msg += " Adding ylabel\n" axis_key = "yaxis{0}".format(self.axis_ct) self.plotly_fig["layout"][axis_key]["title"] = props["text"] titlefont = dict(size=props["style"]["fontsize"], color=props["style"]["color"]) self.plotly_fig["layout"][axis_key]["titlefont"] = titlefont def resize(self): """Revert figure layout to allow plotly to resize. By default, PlotlyRenderer tries its hardest to precisely mimic an mpl figure. However, plotly is pretty good with aesthetics. By running PlotlyRenderer.resize(), layout parameters are deleted. This lets plotly choose them instead of mpl. """ self.msg += "Resizing figure, deleting keys from layout\n" for key in ["width", "height", "autosize", "margin"]: try: del self.plotly_fig["layout"][key] except (KeyError, AttributeError): pass def strip_style(self): self.msg += "Stripping mpl style is no longer supported\n" plotly-4.4.1+dfsg.orig/plotly/optional_imports.py0000644000175000017500000000006613525746125021564 0ustar noahfxnoahfxfrom _plotly_utils.optional_imports import get_module plotly-4.4.1+dfsg.orig/plotly/graph_objects.py0000644000175000017500000000402213573721602020764 0ustar noahfxnoahfxfrom __future__ import absolute_import from plotly.graph_objs import * __all__ = [ "AngularAxis", "Annotation", "Annotations", "Area", "Bar", "Barpolar", "Box", "Candlestick", "Carpet", "Choropleth", "Choroplethmapbox", "ColorBar", "Cone", "Contour", "Contourcarpet", "Contours", "Data", "Densitymapbox", "ErrorX", "ErrorY", "ErrorZ", "Figure", "Font", "Frame", "Frames", "Funnel", "Funnelarea", "Heatmap", "Heatmapgl", "Histogram", "Histogram2d", "Histogram2dContour", "Histogram2dcontour", "Image", "Indicator", "Isosurface", "Layout", "Legend", "Line", "Margin", "Marker", "Mesh3d", "Ohlc", "Parcats", "Parcoords", "Pie", "Pointcloud", "RadialAxis", "Sankey", "Scatter", "Scatter3d", "Scattercarpet", "Scattergeo", "Scattergl", "Scattermapbox", "Scatterpolar", "Scatterpolargl", "Scatterternary", "Scene", "Splom", "Stream", "Streamtube", "Sunburst", "Surface", "Table", "Trace", "Treemap", "Violin", "Volume", "Waterfall", "XAxis", "XBins", "YAxis", "YBins", "ZAxis", "area", "bar", "barpolar", "box", "candlestick", "carpet", "choropleth", "choroplethmapbox", "cone", "contour", "contourcarpet", "densitymapbox", "funnel", "funnelarea", "heatmap", "heatmapgl", "histogram", "histogram2d", "histogram2dcontour", "image", "indicator", "isosurface", "layout", "mesh3d", "ohlc", "parcats", "parcoords", "pie", "pointcloud", "sankey", "scatter", "scatter3d", "scattercarpet", "scattergeo", "scattergl", "scattermapbox", "scatterpolar", "scatterpolargl", "scatterternary", "splom", "streamtube", "sunburst", "surface", "table", "treemap", "violin", "volume", "waterfall", ] plotly-4.4.1+dfsg.orig/plotly/basedatatypes.py0000644000175000017500000050403213573717677021032 0ustar noahfxnoahfxfrom __future__ import absolute_import import collections from collections import OrderedDict import re import six from six import string_types import warnings from contextlib import contextmanager from copy import deepcopy, copy from _plotly_utils.utils import _natural_sort_strings from plotly.subplots import ( _set_trace_grid_reference, _get_grid_subplot, _get_subplot_ref_for_trace, ) from .optional_imports import get_module from _plotly_utils.basevalidators import ( CompoundValidator, CompoundArrayValidator, BaseDataValidator, BaseValidator, LiteralValidator, ) from . import animation from .callbacks import Points, InputDeviceState from plotly.utils import ElidedPrettyPrinter from .validators import DataValidator, LayoutValidator, FramesValidator # Create Undefined sentinel value # - Setting a property to None removes any existing value # - Setting a property to Undefined leaves existing value unmodified Undefined = object() class BaseFigure(object): """ Base class for all figure types (both widget and non-widget) """ _bracket_re = re.compile("^(.*)\[(\d+)\]$") _valid_underscore_properties = { "error_x": "error-x", "error_y": "error-y", "error_z": "error-z", "copy_xstyle": "copy-xstyle", "copy_ystyle": "copy-ystyle", "copy_zstyle": "copy-zstyle", "paper_bgcolor": "paper-bgcolor", "plot_bgcolor": "plot-bgcolor", } _set_trace_uid = False # Constructor # ----------- def __init__( self, data=None, layout_plotly=None, frames=None, skip_invalid=False, **kwargs ): """ Construct a BaseFigure object Parameters ---------- data One of: - A list or tuple of trace objects (or dicts that can be coerced into trace objects) - If `data` is a dict that contains a 'data', 'layout', or 'frames' key then these values are used to construct the figure. - If `data` is a `BaseFigure` instance then the `data`, `layout`, and `frames` properties are extracted from the input figure layout_plotly The plotly layout dict. Note: this property is named `layout_plotly` rather than `layout` to deconflict it with the `layout` constructor parameter of the `widgets.DOMWidget` ipywidgets class, as the `BaseFigureWidget` class is a subclass of both BaseFigure and widgets.DOMWidget. If the `data` property is a BaseFigure instance, or a dict that contains a 'layout' key, then this property is ignored. frames A list or tuple of `plotly.graph_objs.Frame` objects (or dicts that can be coerced into Frame objects) If the `data` property is a BaseFigure instance, or a dict that contains a 'frames' key, then this property is ignored. skip_invalid: bool If True, invalid properties in the figure specification will be skipped silently. If False (default) invalid properties in the figure specification will result in a ValueError Raises ------ ValueError if a property in the specification of data, layout, or frames is invalid AND skip_invalid is False """ super(BaseFigure, self).__init__() # Assign layout_plotly to layout # ------------------------------ # See docstring note for explanation layout = layout_plotly # Subplot properties # ------------------ # These properties are used by the tools.make_subplots logic. # We initialize them to None here, before checking if the input data # object is a BaseFigure, or a dict with _grid_str and _grid_ref # properties, in which case we bring over the _grid* properties of # the input self._grid_str = None self._grid_ref = None # Handle case where data is a Figure or Figure-like dict # ------------------------------------------------------ if isinstance(data, BaseFigure): # Bring over subplot fields self._grid_str = data._grid_str self._grid_ref = data._grid_ref # Extract data, layout, and frames data, layout, frames = data.data, data.layout, data.frames elif isinstance(data, dict) and ( "data" in data or "layout" in data or "frames" in data ): # Bring over subplot fields self._grid_str = data.get("_grid_str", None) self._grid_ref = data.get("_grid_ref", None) # Extract data, layout, and frames data, layout, frames = ( data.get("data", None), data.get("layout", None), data.get("frames", None), ) # Handle data (traces) # -------------------- # ### Construct data validator ### # This is the validator that handles importing sequences of trace # objects self._data_validator = DataValidator(set_uid=self._set_trace_uid) # ### Import traces ### data = self._data_validator.validate_coerce(data, skip_invalid=skip_invalid) # ### Save tuple of trace objects ### self._data_objs = data # ### Import clone of trace properties ### # The _data property is a list of dicts containing the properties # explicitly set by the user for each trace. self._data = [deepcopy(trace._props) for trace in data] # ### Create data defaults ### # _data_defaults is a tuple of dicts, one for each trace. When # running in a widget context, these defaults are populated with # all property values chosen by the Plotly.js library that # aren't explicitly specified by the user. # # Note: No property should exist in both the _data and # _data_defaults for the same trace. self._data_defaults = [{} for _ in data] # ### Reparent trace objects ### for trace_ind, trace in enumerate(data): # By setting the trace's parent to be this figure, we tell the # trace object to use the figure's _data and _data_defaults # dicts to get/set it's properties, rather than using the trace # object's internal _orphan_props dict. trace._parent = self # We clear the orphan props since the trace no longer needs then trace._orphan_props.clear() # Set trace index trace._trace_ind = trace_ind # Layout # ------ # ### Construct layout validator ### # This is the validator that handles importing Layout objects self._layout_validator = LayoutValidator() # ### Import Layout ### self._layout_obj = self._layout_validator.validate_coerce( layout, skip_invalid=skip_invalid ) # ### Import clone of layout properties ### self._layout = deepcopy(self._layout_obj._props) # ### Initialize layout defaults dict ### self._layout_defaults = {} # ### Reparent layout object ### self._layout_obj._orphan_props.clear() self._layout_obj._parent = self # Config # ------ # Pass along default config to the front end. For now this just # ensures that the plotly domain url gets passed to the front end. # In the future we can extend this to allow the user to supply # arbitrary config options like in plotly.offline.plot/iplot. But # this will require a fair amount of testing to determine which # options are compatible with FigureWidget. from plotly.offline.offline import _get_jconfig self._config = _get_jconfig(None) # Frames # ------ # ### Construct frames validator ### # This is the validator that handles importing sequences of frame # objects self._frames_validator = FramesValidator() # ### Import frames ### self._frame_objs = self._frames_validator.validate_coerce( frames, skip_invalid=skip_invalid ) # Note: Because frames are not currently supported in the widget # context, we don't need to follow the pattern above and create # _frames and _frame_defaults properties and then reparent the # frames. The figure doesn't need to be notified of # changes to the properties in the frames object hierarchy. # Context manager # --------------- # ### batch mode indicator ### # Flag that indicates whether we're currently inside a batch_*() # context self._in_batch_mode = False # ### Batch trace edits ### # Dict from trace indexes to trace edit dicts. These trace edit dicts # are suitable as `data` elements of Plotly.animate, but not # the Plotly.update (See `_build_update_params_from_batch`) self._batch_trace_edits = OrderedDict() # ### Batch layout edits ### # Dict from layout properties to new layout values. This dict is # directly suitable for use in Plotly.animate and Plotly.update self._batch_layout_edits = OrderedDict() # Animation property validators # ----------------------------- self._animation_duration_validator = animation.DurationValidator() self._animation_easing_validator = animation.EasingValidator() # Template # -------- # ### Check for default template ### self._initialize_layout_template() # Process kwargs # -------------- for k, v in kwargs.items(): if k in self: self[k] = v elif not skip_invalid: raise TypeError("invalid Figure property: {}".format(k)) # Magic Methods # ------------- def __reduce__(self): """ Custom implementation of reduce is used to support deep copying and pickling """ props = self.to_dict() props["_grid_str"] = self._grid_str props["_grid_ref"] = self._grid_ref return (self.__class__, (props,)) def __setitem__(self, prop, value): # Normalize prop # -------------- # Convert into a property tuple orig_prop = prop prop = BaseFigure._str_to_dict_path(prop) # Handle empty case # ----------------- if len(prop) == 0: raise KeyError(orig_prop) # Handle scalar case # ------------------ # e.g. ('foo',) elif len(prop) == 1: # ### Unwrap scalar tuple ### prop = prop[0] if prop == "data": self.data = value elif prop == "layout": self.layout = value elif prop == "frames": self.frames = value else: raise KeyError(prop) # Handle non-scalar case # ---------------------- # e.g. ('foo', 1) else: res = self for p in prop[:-1]: res = res[p] res[prop[-1]] = value def __setattr__(self, prop, value): """ Parameters ---------- prop : str The name of a direct child of this object value New property value Returns ------- None """ if prop.startswith("_") or hasattr(self, prop): # Let known properties and private properties through super(BaseFigure, self).__setattr__(prop, value) else: # Raise error on unknown public properties raise AttributeError(prop) def __getitem__(self, prop): # Normalize prop # -------------- # Convert into a property tuple orig_prop = prop prop = BaseFigure._str_to_dict_path(prop) # Handle scalar case # ------------------ # e.g. ('foo',) if len(prop) == 1: # Unwrap scalar tuple prop = prop[0] if prop == "data": return self._data_validator.present(self._data_objs) elif prop == "layout": return self._layout_validator.present(self._layout_obj) elif prop == "frames": return self._frames_validator.present(self._frame_objs) else: raise KeyError(orig_prop) # Handle non-scalar case # ---------------------- # e.g. ('foo', 1) else: res = self for p in prop: res = res[p] return res def __iter__(self): return iter(("data", "layout", "frames")) def __contains__(self, prop): prop = BaseFigure._str_to_dict_path(prop) if prop[0] not in ("data", "layout", "frames"): return False elif len(prop) == 1: return True else: return prop[1:] in self[prop[0]] def __eq__(self, other): if not isinstance(other, BaseFigure): # Require objects to both be BaseFigure instances return False else: # Compare plotly_json representations # Use _vals_equal instead of `==` to handle cases where # underlying dicts contain numpy arrays return BasePlotlyType._vals_equal( self.to_plotly_json(), other.to_plotly_json() ) def __repr__(self): """ Customize Figure representation when displayed in the terminal/notebook """ props = self.to_plotly_json() # Elide template template_props = props.get("layout", {}).get("template", {}) if template_props: props["layout"]["template"] = "..." repr_str = BasePlotlyType._build_repr_for_class( props=props, class_name=self.__class__.__name__ ) return repr_str def _ipython_display_(self): """ Handle rich display of figures in ipython contexts """ import plotly.io as pio if pio.renderers.render_on_display and pio.renderers.default: pio.show(self) else: print(repr(self)) def update(self, dict1=None, overwrite=False, **kwargs): """ Update the properties of the figure with a dict and/or with keyword arguments. This recursively updates the structure of the figure object with the values in the input dict / keyword arguments. Parameters ---------- dict1 : dict Dictionary of properties to be updated overwrite: bool If True, overwrite existing properties. If False, apply updates to existing properties recursively, preserving existing properties that are not specified in the update operation. kwargs : Keyword/value pair of properties to be updated Examples -------- >>> import plotly.graph_objs as go >>> fig = go.Figure(data=[{'y': [1, 2, 3]}]) >>> fig.update(data=[{'y': [4, 5, 6]}]) # doctest: +ELLIPSIS Figure(...) >>> fig.to_plotly_json() # doctest: +SKIP {'data': [{'type': 'scatter', 'uid': 'e86a7c7a-346a-11e8-8aa8-a0999b0c017b', 'y': array([4, 5, 6], dtype=int32)}], 'layout': {}} >>> fig = go.Figure(layout={'xaxis': ... {'color': 'green', ... 'range': [0, 1]}}) >>> fig.update({'layout': {'xaxis': {'color': 'pink'}}}) # doctest: +ELLIPSIS Figure(...) >>> fig.to_plotly_json() # doctest: +SKIP {'data': [], 'layout': {'xaxis': {'color': 'pink', 'range': [0, 1]}}} Returns ------- BaseFigure Updated figure """ with self.batch_update(): for d in [dict1, kwargs]: if d: for k, v in d.items(): update_target = self[k] if update_target == () or overwrite: if k == "data": # Overwrite all traces as special due to # restrictions on trace assignment self.data = () self.add_traces(v) else: # Accept v self[k] = v elif ( isinstance(update_target, BasePlotlyType) and isinstance(v, (dict, BasePlotlyType)) ) or ( isinstance(update_target, tuple) and isinstance(update_target[0], BasePlotlyType) ): BaseFigure._perform_update(self[k], v) else: self[k] = v return self def pop(self, key, *args): """ Remove the value associated with the specified key and return it Parameters ---------- key: str Property name dflt The default value to return if key was not found in figure Returns ------- value The removed value that was previously associated with key Raises ------ KeyError If key is not in object and no dflt argument specified """ # Handle default if key not in self and args: return args[0] elif key in self: val = self[key] self[key] = None return val else: raise KeyError(key) # Data # ---- @property def data(self): """ The `data` property is a tuple of the figure's trace objects Returns ------- tuple[BaseTraceType] """ return self["data"] @data.setter def data(self, new_data): # Validate new_data # ----------------- err_header = ( "The data property of a figure may only be assigned \n" "a list or tuple that contains a permutation of a " "subset of itself.\n" ) # ### Treat None as empty ### if new_data is None: new_data = () # ### Check valid input type ### if not isinstance(new_data, (list, tuple)): err_msg = err_header + " Received value with type {typ}".format( typ=type(new_data) ) raise ValueError(err_msg) # ### Check valid element types ### for trace in new_data: if not isinstance(trace, BaseTraceType): err_msg = ( err_header + " Received element value of type {typ}".format(typ=type(trace)) ) raise ValueError(err_msg) # ### Check trace objects ### # Require that no new traces are introduced orig_uids = [id(trace) for trace in self.data] new_uids = [id(trace) for trace in new_data] invalid_uids = set(new_uids).difference(set(orig_uids)) if invalid_uids: err_msg = err_header raise ValueError(err_msg) # ### Check for duplicates in assignment ### uid_counter = collections.Counter(new_uids) duplicate_uids = [uid for uid, count in uid_counter.items() if count > 1] if duplicate_uids: err_msg = err_header + " Received duplicated traces" raise ValueError(err_msg) # Remove traces # ------------- remove_uids = set(orig_uids).difference(set(new_uids)) delete_inds = [] # ### Unparent removed traces ### for i, trace in enumerate(self.data): if id(trace) in remove_uids: delete_inds.append(i) # Unparent trace object to be removed old_trace = self.data[i] old_trace._orphan_props.update(deepcopy(old_trace._props)) old_trace._parent = None old_trace._trace_ind = None # ### Compute trace props / defaults after removal ### traces_props_post_removal = [t for t in self._data] traces_prop_defaults_post_removal = [t for t in self._data_defaults] uids_post_removal = [id(trace_data) for trace_data in self.data] for i in reversed(delete_inds): del traces_props_post_removal[i] del traces_prop_defaults_post_removal[i] del uids_post_removal[i] # Modify in-place so we don't trigger serialization del self._data[i] if delete_inds: # Update widget, if any self._send_deleteTraces_msg(delete_inds) # Move traces # ----------- # ### Compute new index for each remaining trace ### new_inds = [] for uid in uids_post_removal: new_inds.append(new_uids.index(uid)) # ### Compute current index for each remaining trace ### current_inds = list(range(len(traces_props_post_removal))) # ### Check whether a move is needed ### if not all([i1 == i2 for i1, i2 in zip(new_inds, current_inds)]): # #### Save off index lists for moveTraces message #### msg_current_inds = current_inds msg_new_inds = new_inds # #### Reorder trace elements #### # We do so in-place so we don't trigger traitlet property # serialization for the FigureWidget case # ##### Remove by curr_inds in reverse order ##### moving_traces_data = [] for ci in reversed(current_inds): # Push moving traces data to front of list moving_traces_data.insert(0, self._data[ci]) del self._data[ci] # #### Sort new_inds and moving_traces_data by new_inds #### new_inds, moving_traces_data = zip( *sorted(zip(new_inds, moving_traces_data)) ) # #### Insert by new_inds in forward order #### for ni, trace_data in zip(new_inds, moving_traces_data): self._data.insert(ni, trace_data) # #### Update widget, if any #### self._send_moveTraces_msg(msg_current_inds, msg_new_inds) # ### Update data defaults ### # There is to front-end syncronization to worry about so this # operations doesn't need to be in-place self._data_defaults = [ _trace for i, _trace in sorted(zip(new_inds, traces_prop_defaults_post_removal)) ] # Update trace objects tuple self._data_objs = list(new_data) # Update trace indexes for trace_ind, trace in enumerate(self._data_objs): trace._trace_ind = trace_ind def select_traces(self, selector=None, row=None, col=None, secondary_y=None): """ Select traces from a particular subplot cell and/or traces that satisfy custom selection criteria. Parameters ---------- selector: dict or None (default None) Dict to use as selection criteria. Traces will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all traces are selected. row, col: int or None (default None) Subplot row and column index of traces to select. To select traces by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all traces are selected. secondary_y: boolean or None (default None) * If True, only select traces associated with the secondary y-axis of the subplot. * If False, only select traces associated with the primary y-axis of the subplot. * If None (the default), do not filter traces based on secondary y-axis. To select traces by secondary y-axis, the Figure must have been created using plotly.subplots.make_subplots. See the docstring for the specs argument to make_subplots for more info on creating subplots with secondary y-axes. Returns ------- generator Generator that iterates through all of the traces that satisfy all of the specified selection criteria """ if not selector: selector = {} if row is not None or col is not None or secondary_y is not None: grid_ref = self._validate_get_grid_ref() filter_by_subplot = True if row is None and col is not None: # All rows for column grid_subplot_ref_tuples = [ref_row[col - 1] for ref_row in grid_ref] elif col is None and row is not None: # All columns for row grid_subplot_ref_tuples = grid_ref[row - 1] elif col is not None and row is not None: # Single grid cell grid_subplot_ref_tuples = [grid_ref[row - 1][col - 1]] else: # row and col are None, secondary_y not None grid_subplot_ref_tuples = [ refs for refs_row in grid_ref for refs in refs_row ] # Collect list of subplot refs, taking secondary_y into account grid_subplot_refs = [] for refs in grid_subplot_ref_tuples: if not refs: continue if secondary_y is not True: grid_subplot_refs.append(refs[0]) if secondary_y is not False and len(refs) > 1: grid_subplot_refs.append(refs[1]) else: filter_by_subplot = False grid_subplot_refs = None return self._perform_select_traces( filter_by_subplot, grid_subplot_refs, selector ) def _perform_select_traces(self, filter_by_subplot, grid_subplot_refs, selector): for trace in self.data: # Filter by subplot if filter_by_subplot: trace_subplot_ref = _get_subplot_ref_for_trace(trace) if trace_subplot_ref not in grid_subplot_refs: continue # Filter by selector if not self._selector_matches(trace, selector): continue yield trace @staticmethod def _selector_matches(obj, selector): if selector is None: return True for k in selector: if k not in obj: return False obj_val = obj[k] selector_val = selector[k] if isinstance(obj_val, BasePlotlyType): obj_val = obj_val.to_plotly_json() if isinstance(selector_val, BasePlotlyType): selector_val = selector_val.to_plotly_json() if obj_val != selector_val: return False return True def for_each_trace(self, fn, selector=None, row=None, col=None, secondary_y=None): """ Apply a function to all traces that satisfy the specified selection criteria Parameters ---------- fn: Function that inputs a single trace object. selector: dict or None (default None) Dict to use as selection criteria. Traces will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all traces are selected. row, col: int or None (default None) Subplot row and column index of traces to select. To select traces by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all traces are selected. secondary_y: boolean or None (default None) * If True, only select traces associated with the secondary y-axis of the subplot. * If False, only select traces associated with the primary y-axis of the subplot. * If None (the default), do not filter traces based on secondary y-axis. To select traces by secondary y-axis, the Figure must have been created using plotly.subplots.make_subplots. See the docstring for the specs argument to make_subplots for more info on creating subplots with secondary y-axes. Returns ------- self Returns the Figure object that the method was called on """ for trace in self.select_traces( selector=selector, row=row, col=col, secondary_y=secondary_y ): fn(trace) return self def update_traces( self, patch=None, selector=None, row=None, col=None, secondary_y=None, overwrite=False, **kwargs ): """ Perform a property update operation on all traces that satisfy the specified selection criteria Parameters ---------- patch: dict or None (default None) Dictionary of property updates to be applied to all traces that satisfy the selection criteria. selector: dict or None (default None) Dict to use as selection criteria. Traces will be selected if they contain properties corresponding to all of the dictionary's keys, with values that exactly match the supplied values. If None (the default), all traces are selected. row, col: int or None (default None) Subplot row and column index of traces to select. To select traces by row and column, the Figure must have been created using plotly.subplots.make_subplots. If None (the default), all traces are selected. secondary_y: boolean or None (default None) * If True, only select traces associated with the secondary y-axis of the subplot. * If False, only select traces associated with the primary y-axis of the subplot. * If None (the default), do not filter traces based on secondary y-axis. To select traces by secondary y-axis, the Figure must have been created using plotly.subplots.make_subplots. See the docstring for the specs argument to make_subplots for more info on creating subplots with secondary y-axes. overwrite: bool If True, overwrite existing properties. If False, apply updates to existing properties recursively, preserving existing properties that are not specified in the update operation. **kwargs Additional property updates to apply to each selected trace. If a property is specified in both patch and in **kwargs then the one in **kwargs takes precedence. Returns ------- self Returns the Figure object that the method was called on """ for trace in self.select_traces( selector=selector, row=row, col=col, secondary_y=secondary_y ): trace.update(patch, overwrite=overwrite, **kwargs) return self def update_layout(self, dict1=None, overwrite=False, **kwargs): """ Update the properties of the figure's layout with a dict and/or with keyword arguments. This recursively updates the structure of the original layout with the values in the input dict / keyword arguments. Parameters ---------- dict1 : dict Dictionary of properties to be updated overwrite: bool If True, overwrite existing properties. If False, apply updates to existing properties recursively, preserving existing properties that are not specified in the update operation. kwargs : Keyword/value pair of properties to be updated Returns ------- BaseFigure The Figure object that the update_layout method was called on """ self.layout.update(dict1, overwrite=overwrite, **kwargs) return self def _select_layout_subplots_by_prefix( self, prefix, selector=None, row=None, col=None, secondary_y=None ): """ Helper called by code generated select_* methods """ if row is not None or col is not None or secondary_y is not None: # Build mapping from container keys ('xaxis2', 'scene4', etc.) # to (row, col, secondary_y) triplets grid_ref = self._validate_get_grid_ref() container_to_row_col = {} for r, subplot_row in enumerate(grid_ref): for c, subplot_refs in enumerate(subplot_row): if not subplot_refs: continue # collect primary keys for i, subplot_ref in enumerate(subplot_refs): for layout_key in subplot_ref.layout_keys: if layout_key.startswith(prefix): is_secondary_y = i == 1 container_to_row_col[layout_key] = ( r + 1, c + 1, is_secondary_y, ) else: container_to_row_col = None # Natural sort keys so that xaxis20 is after xaxis3 layout_keys = _natural_sort_strings(list(self.layout)) for k in layout_keys: if k.startswith(prefix) and self.layout[k] is not None: # Filter by row/col if ( row is not None and container_to_row_col.get(k, (None, None, None))[0] != row ): # row specified and this is not a match continue elif ( col is not None and container_to_row_col.get(k, (None, None, None))[1] != col ): # col specified and this is not a match continue elif ( secondary_y is not None and container_to_row_col.get(k, (None, None, None))[2] != secondary_y ): continue # Filter by selector if not self._selector_matches(self.layout[k], selector): continue yield self.layout[k] def _select_annotations_like( self, prop, selector=None, row=None, col=None, secondary_y=None ): """ Helper to select annotation-like elements from a layout object array. Compatible with layout.annotations, layout.shapes, and layout.images """ xref_to_col = {} yref_to_row = {} yref_to_secondary_y = {} if isinstance(row, int) or isinstance(col, int) or secondary_y is not None: grid_ref = self._validate_get_grid_ref() for r, subplot_row in enumerate(grid_ref): for c, subplot_refs in enumerate(subplot_row): if not subplot_refs: continue for i, subplot_ref in enumerate(subplot_refs): if subplot_ref.subplot_type == "xy": is_secondary_y = i == 1 xaxis, yaxis = subplot_ref.layout_keys xref = xaxis.replace("axis", "") yref = yaxis.replace("axis", "") xref_to_col[xref] = c + 1 yref_to_row[yref] = r + 1 yref_to_secondary_y[yref] = is_secondary_y for obj in self.layout[prop]: # Filter by row if col is not None and xref_to_col.get(obj.xref, None) != col: continue # Filter by col if row is not None and yref_to_row.get(obj.yref, None) != row: continue # Filter by secondary y if ( secondary_y is not None and yref_to_secondary_y.get(obj.yref, None) != secondary_y ): continue # Filter by selector if not self._selector_matches(obj, selector): continue yield obj def _add_annotation_like( self, prop_singular, prop_plural, new_obj, row=None, col=None, secondary_y=None ): # Make sure we have both row and col or neither if row is not None and col is None: raise ValueError( "Received row parameter but not col.\n" "row and col must be specified together" ) elif col is not None and row is None: raise ValueError( "Received col parameter but not row.\n" "row and col must be specified together" ) # Get grid_ref if specific row or column requested if row is not None: grid_ref = self._validate_get_grid_ref() refs = grid_ref[row - 1][col - 1] if not refs: raise ValueError( "No subplot found at position ({r}, {c})".format(r=row, c=col) ) if refs[0].subplot_type != "xy": raise ValueError( """ Cannot add {prop_singular} to subplot at position ({r}, {c}) because subplot is of type {subplot_type}.""".format( prop_singular=prop_singular, r=row, c=col, subplot_type=refs[0].subplot_type, ) ) if len(refs) == 1 and secondary_y: raise ValueError( """ Cannot add {prop_singular} to secondary y-axis of subplot at position ({r}, {c}) because subplot does not have a secondary y-axis""" ) if secondary_y: xaxis, yaxis = refs[1].layout_keys else: xaxis, yaxis = refs[0].layout_keys xref, yref = xaxis.replace("axis", ""), yaxis.replace("axis", "") new_obj.update(xref=xref, yref=yref) self.layout[prop_plural] += (new_obj,) return self # Restyle # ------- def plotly_restyle(self, restyle_data, trace_indexes=None, **kwargs): """ Perform a Plotly restyle operation on the figure's traces Parameters ---------- restyle_data : dict Dict of trace style updates. Keys are strings that specify the properties to be updated. Nested properties are expressed by joining successive keys on '.' characters (e.g. 'marker.color'). Values may be scalars or lists. When values are scalars, that scalar value is applied to all traces specified by the `trace_indexes` parameter. When values are lists, the restyle operation will cycle through the elements of the list as it cycles through the traces specified by the `trace_indexes` parameter. Caution: To use plotly_restyle to update a list property (e.g. the `x` property of the scatter trace), the property value should be a scalar list containing the list to update with. For example, the following command would be used to update the 'x' property of the first trace to the list [1, 2, 3] >>> import plotly.graph_objects as go >>> fig = go.Figure(go.Scatter(x=[2, 4, 6])) >>> fig.plotly_restyle({'x': [[1, 2, 3]]}, 0) trace_indexes : int or list of int Trace index, or list of trace indexes, that the restyle operation applies to. Defaults to all trace indexes. Returns ------- None """ # Normalize trace indexes # ----------------------- trace_indexes = self._normalize_trace_indexes(trace_indexes) # Handle source_view_id # --------------------- # If not None, the source_view_id is the UID of the frontend # Plotly.js view that initially triggered this restyle operation # (e.g. the user clicked on the legend to hide a trace). We pass # this UID along so that the frontend views can determine whether # they need to apply the restyle operation on themselves. source_view_id = kwargs.get("source_view_id", None) # Perform restyle on trace dicts # ------------------------------ restyle_changes = self._perform_plotly_restyle(restyle_data, trace_indexes) if restyle_changes: # The restyle operation resulted in a change to some trace # properties, so we dispatch change callbacks and send the # restyle message to the frontend (if any) msg_kwargs = ( {"source_view_id": source_view_id} if source_view_id is not None else {} ) self._send_restyle_msg( restyle_changes, trace_indexes=trace_indexes, **msg_kwargs ) self._dispatch_trace_change_callbacks(restyle_changes, trace_indexes) def _perform_plotly_restyle(self, restyle_data, trace_indexes): """ Perform a restyle operation on the figure's traces data and return the changes that were applied Parameters ---------- restyle_data : dict[str, any] See docstring for plotly_restyle trace_indexes : list[int] List of trace indexes that restyle operation applies to Returns ------- restyle_changes: dict[str, any] Subset of restyle_data including only the keys / values that resulted in a change to the figure's traces data """ # Initialize restyle changes # -------------------------- # This will be a subset of the restyle_data including only the # keys / values that are changed in the figure's trace data restyle_changes = {} # Process each key # ---------------- for key_path_str, v in restyle_data.items(): # Track whether any of the new values are cause a change in # self._data any_vals_changed = False for i, trace_ind in enumerate(trace_indexes): if trace_ind >= len(self._data): raise ValueError( "Trace index {trace_ind} out of range".format( trace_ind=trace_ind ) ) # Get new value for this particular trace trace_v = v[i % len(v)] if isinstance(v, list) else v if trace_v is not Undefined: # Get trace being updated trace_obj = self.data[trace_ind] # Validate key_path_str if not BaseFigure._is_key_path_compatible(key_path_str, trace_obj): trace_class = trace_obj.__class__.__name__ raise ValueError( """ Invalid property path '{key_path_str}' for trace class {trace_class} """.format( key_path_str=key_path_str, trace_class=trace_class ) ) # Apply set operation for this trace and thist value val_changed = BaseFigure._set_in( self._data[trace_ind], key_path_str, trace_v ) # Update any_vals_changed status any_vals_changed = any_vals_changed or val_changed if any_vals_changed: restyle_changes[key_path_str] = v return restyle_changes def _restyle_child(self, child, key_path_str, val): """ Process restyle operation on a child trace object Note: This method name/signature must match the one in BasePlotlyType. BasePlotlyType objects call their parent's _restyle_child method without knowing whether their parent is a BasePlotlyType or a BaseFigure. Parameters ---------- child : BaseTraceType Child being restyled key_path_str : str A key path string (e.g. 'foo.bar[0]') val Restyle value Returns ------- None """ # Compute trace index # ------------------- trace_index = child._trace_ind # Not in batch mode # ----------------- # Dispatch change callbacks and send restyle message if not self._in_batch_mode: send_val = [val] restyle = {key_path_str: send_val} self._send_restyle_msg(restyle, trace_indexes=trace_index) self._dispatch_trace_change_callbacks(restyle, [trace_index]) # In batch mode # ------------- # Add key_path_str/val to saved batch edits else: if trace_index not in self._batch_trace_edits: self._batch_trace_edits[trace_index] = OrderedDict() self._batch_trace_edits[trace_index][key_path_str] = val def _normalize_trace_indexes(self, trace_indexes): """ Input trace index specification and return list of the specified trace indexes Parameters ---------- trace_indexes : None or int or list[int] Returns ------- list[int] """ if trace_indexes is None: trace_indexes = list(range(len(self.data))) if not isinstance(trace_indexes, (list, tuple)): trace_indexes = [trace_indexes] return list(trace_indexes) @staticmethod def _str_to_dict_path(key_path_str): """ Convert a key path string into a tuple of key path elements Parameters ---------- key_path_str : str Key path string, where nested keys are joined on '.' characters and array indexes are specified using brackets (e.g. 'foo.bar[1]') Returns ------- tuple[str | int] """ if ( isinstance(key_path_str, string_types) and "." not in key_path_str and "[" not in key_path_str and "_" not in key_path_str ): # Fast path for common case that avoids regular expressions return (key_path_str,) elif isinstance(key_path_str, tuple): # Nothing to do return key_path_str else: # Split string on periods. # e.g. 'foo.bar_baz[1]' -> ['foo', 'bar_baz[1]'] key_path = key_path_str.split(".") # Split out bracket indexes. # e.g. ['foo', 'bar_baz[1]'] -> ['foo', 'bar_baz', '1'] key_path2 = [] for key in key_path: match = BaseFigure._bracket_re.match(key) if match: key_path2.extend(match.groups()) else: key_path2.append(key) # Split out underscore # e.g. ['foo', 'bar_baz', '1'] -> ['foo', 'bar', 'baz', '1'] key_path3 = [] underscore_props = BaseFigure._valid_underscore_properties for key in key_path2: if "_" in key[1:]: # For valid properties that contain underscores (error_x) # replace the underscores with hyphens to protect them # from being split up for under_prop, hyphen_prop in underscore_props.items(): key = key.replace(under_prop, hyphen_prop) # Split key on underscores key = key.split("_") # Replace hyphens with underscores to restore properties # that include underscores for i in range(len(key)): key[i] = key[i].replace("-", "_") key_path3.extend(key) else: key_path3.append(key) # Convert elements to ints if possible. # e.g. ['foo', 'bar', '0'] -> ['foo', 'bar', 0] for i in range(len(key_path3)): try: key_path3[i] = int(key_path3[i]) except ValueError as _: pass return tuple(key_path3) @staticmethod def _set_in(d, key_path_str, v): """ Set a value in a nested dict using a key path string (e.g. 'foo.bar[0]') Parameters ---------- d : dict Input dict to set property in key_path_str : str Key path string, where nested keys are joined on '.' characters and array indexes are specified using brackets (e.g. 'foo.bar[1]') v New value Returns ------- bool True if set resulted in modification of dict (i.e. v was not already present at the specified location), False otherwise. """ # Validate inputs # --------------- assert isinstance(d, dict) # Compute key path # ---------------- # Convert the key_path_str into a tuple of key paths # e.g. 'foo.bar[0]' -> ('foo', 'bar', 0) key_path = BaseFigure._str_to_dict_path(key_path_str) # Initialize val_parent # --------------------- # This variable will be assigned to the parent of the next key path # element currently being processed val_parent = d # Initialize parent dict or list of value to be assigned # ----------------------------------------------------- for kp, key_path_el in enumerate(key_path[:-1]): # Extend val_parent list if needed if isinstance(val_parent, list) and isinstance(key_path_el, int): while len(val_parent) <= key_path_el: val_parent.append(None) elif isinstance(val_parent, dict) and key_path_el not in val_parent: if isinstance(key_path[kp + 1], int): val_parent[key_path_el] = [] else: val_parent[key_path_el] = {} val_parent = val_parent[key_path_el] # Assign value to to final parent dict or list # -------------------------------------------- # ### Get reference to final key path element ### last_key = key_path[-1] # ### Track whether assignment alters parent ### val_changed = False # v is Undefined # -------------- # Don't alter val_parent if v is Undefined: pass # v is None # --------- # Check whether we can remove key from parent elif v is None: if isinstance(val_parent, dict): if last_key in val_parent: # Parent is a dict and has last_key as a current key so # we can pop the key, which alters parent val_parent.pop(last_key) val_changed = True elif isinstance(val_parent, list): if isinstance(last_key, int) and 0 <= last_key < len(val_parent): # Parent is a list and last_key is a valid index so we # can set the element value to None val_parent[last_key] = None val_changed = True else: # Unsupported parent type (numpy array for example) raise ValueError( """ Cannot remove element of type {typ} at location {raw_key}""".format( typ=type(val_parent), raw_key=key_path_str ) ) # v is a valid value # ------------------ # Check whether parent should be updated else: if isinstance(val_parent, dict): if last_key not in val_parent or not BasePlotlyType._vals_equal( val_parent[last_key], v ): # Parent is a dict and does not already contain the # value v at key last_key val_parent[last_key] = v val_changed = True elif isinstance(val_parent, list): if isinstance(last_key, int): # Extend list with Nones if needed so that last_key is # in bounds while len(val_parent) <= last_key: val_parent.append(None) if not BasePlotlyType._vals_equal(val_parent[last_key], v): # Parent is a list and does not already contain the # value v at index last_key val_parent[last_key] = v val_changed = True else: # Unsupported parent type (numpy array for example) raise ValueError( """ Cannot set element of type {typ} at location {raw_key}""".format( typ=type(val_parent), raw_key=key_path_str ) ) return val_changed # Add traces # ---------- @staticmethod def _raise_invalid_rows_cols(name, n, invalid): rows_err_msg = """ If specified, the {name} parameter must be a list or tuple of integers of length {n} (The number of traces being added) Received: {invalid} """.format( name=name, n=n, invalid=invalid ) raise ValueError(rows_err_msg) @staticmethod def _validate_rows_cols(name, n, vals): if vals is None: pass elif isinstance(vals, (list, tuple)): if len(vals) != n: BaseFigure._raise_invalid_rows_cols(name=name, n=n, invalid=vals) if [r for r in vals if not isinstance(r, int)]: BaseFigure._raise_invalid_rows_cols(name=name, n=n, invalid=vals) else: BaseFigure._raise_invalid_rows_cols(name=name, n=n, invalid=vals) def add_trace(self, trace, row=None, col=None, secondary_y=None): """ Add a trace to the figure Parameters ---------- trace : BaseTraceType or dict Either: - An instances of a trace classe from the plotly.graph_objs package (e.g plotly.graph_objs.Scatter, plotly.graph_objs.Bar) - or a dicts where: - The 'type' property specifies the trace type (e.g. 'scatter', 'bar', 'area', etc.). If the dict has no 'type' property then 'scatter' is assumed. - All remaining properties are passed to the constructor of the specified trace type. row : int or None (default None) Subplot row index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.subplots.make_subplots` col : int or None (default None) Subplot col index (starting from 1) for the trace to be added. Only valid if figure was created using `plotly.subplots.make_subplots` secondary_y: boolean or None (default None) If True, associate this trace with the secondary y-axis of the subplot at the specified row and col. Only valid if all of the following conditions are satisfied: * The figure was created using `plotly.subplots.make_subplots`. * The row and col arguments are not None * The subplot at the specified row and col has type xy (which is the default) and secondary_y True. These properties are specified in the specs argument to make_subplots. See the make_subplots docstring for more info. * The trace argument is a 2D cartesian trace (scatter, bar, etc.) Returns ------- BaseFigure The Figure that add_trace was called on Examples -------- >>> from plotly import subplots >>> import plotly.graph_objs as go Add two Scatter traces to a figure >>> fig = go.Figure() >>> fig.add_trace(go.Scatter(x=[1,2,3], y=[2,1,2])) # doctest: +ELLIPSIS Figure(...) >>> fig.add_trace(go.Scatter(x=[1,2,3], y=[2,1,2])) # doctest: +ELLIPSIS Figure(...) Add two Scatter traces to vertically stacked subplots >>> fig = subplots.make_subplots(rows=2) >>> fig.add_trace(go.Scatter(x=[1,2,3], y=[2,1,2]), row=1, col=1) # doctest: +ELLIPSIS Figure(...) >>> fig.add_trace(go.Scatter(x=[1,2,3], y=[2,1,2]), row=2, col=1) # doctest: +ELLIPSIS Figure(...) """ # Make sure we have both row and col or neither if row is not None and col is None: raise ValueError( "Received row parameter but not col.\n" "row and col must be specified together" ) elif col is not None and row is None: raise ValueError( "Received col parameter but not row.\n" "row and col must be specified together" ) return self.add_traces( data=[trace], rows=[row] if row is not None else None, cols=[col] if col is not None else None, secondary_ys=[secondary_y] if secondary_y is not None else None, ) def add_traces(self, data, rows=None, cols=None, secondary_ys=None): """ Add traces to the figure Parameters ---------- data : list[BaseTraceType or dict] A list of trace specifications to be added. Trace specifications may be either: - Instances of trace classes from the plotly.graph_objs package (e.g plotly.graph_objs.Scatter, plotly.graph_objs.Bar) - Dicts where: - The 'type' property specifies the trace type (e.g. 'scatter', 'bar', 'area', etc.). If the dict has no 'type' property then 'scatter' is assumed. - All remaining properties are passed to the constructor of the specified trace type. rows : None or list[int] (default None) List of subplot row indexes (starting from 1) for the traces to be added. Only valid if figure was created using `plotly.tools.make_subplots` cols : None or list[int] (default None) List of subplot column indexes (starting from 1) for the traces to be added. Only valid if figure was created using `plotly.tools.make_subplots` secondary_ys: None or list[boolean] (default None) List of secondary_y booleans for traces to be added. See the docstring for `add_trace` for more info. Returns ------- BaseFigure The Figure that add_traces was called on Examples -------- >>> from plotly import subplots >>> import plotly.graph_objs as go Add two Scatter traces to a figure >>> fig = go.Figure() >>> fig.add_traces([go.Scatter(x=[1,2,3], y=[2,1,2]), ... go.Scatter(x=[1,2,3], y=[2,1,2])]) # doctest: +ELLIPSIS Figure(...) Add two Scatter traces to vertically stacked subplots >>> fig = subplots.make_subplots(rows=2) >>> fig.add_traces([go.Scatter(x=[1,2,3], y=[2,1,2]), ... go.Scatter(x=[1,2,3], y=[2,1,2])], ... rows=[1, 2], cols=[1, 1]) # doctest: +ELLIPSIS Figure(...) """ # Validate traces data = self._data_validator.validate_coerce(data) # Set trace indexes for ind, new_trace in enumerate(data): new_trace._trace_ind = ind + len(self.data) # Validate rows / cols n = len(data) BaseFigure._validate_rows_cols("rows", n, rows) BaseFigure._validate_rows_cols("cols", n, cols) # Make sure we have both rows and cols or neither if rows is not None and cols is None: raise ValueError( "Received rows parameter but not cols.\n" "rows and cols must be specified together" ) elif cols is not None and rows is None: raise ValueError( "Received cols parameter but not rows.\n" "rows and cols must be specified together" ) # Process secondary_ys defaults if secondary_ys is not None and rows is None: # Default rows/cols to 1s if secondary_ys specified but not rows # or cols rows = [1] * len(secondary_ys) cols = rows elif secondary_ys is None and rows is not None: # Default secondary_ys to Nones if secondary_ys is not specified # but not rows and cols are specified secondary_ys = [None] * len(rows) # Apply rows / cols if rows is not None: for trace, row, col, secondary_y in zip(data, rows, cols, secondary_ys): self._set_trace_grid_position(trace, row, col, secondary_y) # Make deep copy of trace data (Optimize later if needed) new_traces_data = [deepcopy(trace._props) for trace in data] # Update trace parent for trace in data: trace._parent = self trace._orphan_props.clear() # Update python side # Use extend instead of assignment so we don't trigger serialization self._data.extend(new_traces_data) self._data_defaults = self._data_defaults + [{} for _ in data] self._data_objs = self._data_objs + data # Update messages self._send_addTraces_msg(new_traces_data) return self # Subplots # -------- def print_grid(self): """ Print a visual layout of the figure's axes arrangement. This is only valid for figures that are created with plotly.tools.make_subplots. """ if self._grid_str is None: raise Exception( "Use plotly.tools.make_subplots " "to create a subplot grid." ) print(self._grid_str) def append_trace(self, trace, row, col): """ Add a trace to the figure bound to axes at the specified row, col index. A row, col index grid is generated for figures created with plotly.tools.make_subplots, and can be viewed with the `print_grid` method Parameters ---------- trace The data trace to be bound row: int Subplot row index (see Figure.print_grid) col: int Subplot column index (see Figure.print_grid) Examples -------- >>> from plotly import tools >>> import plotly.graph_objs as go >>> # stack two subplots vertically >>> fig = tools.make_subplots(rows=2) This is the format of your plot grid: [ (1,1) x1,y1 ] [ (2,1) x2,y2 ] >>> fig.append_trace(go.Scatter(x=[1,2,3], y=[2,1,2]), row=1, col=1) >>> fig.append_trace(go.Scatter(x=[1,2,3], y=[2,1,2]), row=2, col=1) """ warnings.warn( """\ The append_trace method is deprecated and will be removed in a future version. Please use the add_trace method with the row and col parameters. """, DeprecationWarning, ) self.add_trace(trace=trace, row=row, col=col) def _set_trace_grid_position(self, trace, row, col, secondary_y=False): grid_ref = self._validate_get_grid_ref() return _set_trace_grid_reference( trace, self.layout, grid_ref, row, col, secondary_y ) def _validate_get_grid_ref(self): try: grid_ref = self._grid_ref if grid_ref is None: raise AttributeError("_grid_ref") except AttributeError: raise Exception( "In order to reference traces by row and column, " "you must first use " "plotly.tools.make_subplots " "to create the figure with a subplot grid." ) return grid_ref def get_subplot(self, row, col, secondary_y=False): """ Return an object representing the subplot at the specified row and column. May only be used on Figures created using plotly.tools.make_subplots Parameters ---------- row: int 1-based index of subplot row col: int 1-based index of subplot column secondary_y: bool If True, select the subplot that consists of the x-axis and the secondary y-axis at the specified row/col. Only valid if the subplot at row/col is an 2D cartesian subplot that was created with a secondary y-axis. See the docstring for the specs argument to make_subplots for more info on creating a subplot with a secondary y-axis. Returns ------- subplot * None: if subplot is empty * plotly.graph_objs.layout.Scene: if subplot type is 'scene' * plotly.graph_objs.layout.Polar: if subplot type is 'polar' * plotly.graph_objs.layout.Ternary: if subplot type is 'ternary' * plotly.graph_objs.layout.Mapbox: if subplot type is 'ternary' * SubplotDomain namedtuple with `x` and `y` fields: if subplot type is 'domain'. - x: length 2 list of the subplot start and stop width - y: length 2 list of the subplot start and stop height * SubplotXY namedtuple with `xaxis` and `yaxis` fields: if subplot type is 'xy'. - xaxis: plotly.graph_objs.layout.XAxis instance for subplot - yaxis: plotly.graph_objs.layout.YAxis instance for subplot """ return _get_grid_subplot(self, row, col, secondary_y) # Child property operations # ------------------------- def _get_child_props(self, child): """ Return the properties dict for a child trace or child layout Note: this method must match the name/signature of one on BasePlotlyType Parameters ---------- child : BaseTraceType | BaseLayoutType Returns ------- dict """ # Try to find index of child as a trace # ------------------------------------- if isinstance(child, BaseTraceType): # ### Child is a trace ### trace_index = child._trace_ind return self._data[trace_index] # Child is the layout # ------------------- elif child is self.layout: return self._layout # Unknown child # ------------- else: raise ValueError("Unrecognized child: %s" % child) def _get_child_prop_defaults(self, child): """ Return the default properties dict for a child trace or child layout Note: this method must match the name/signature of one on BasePlotlyType Parameters ---------- child : BaseTraceType | BaseLayoutType Returns ------- dict """ # Child is a trace # ---------------- if isinstance(child, BaseTraceType): trace_index = child._trace_ind return self._data_defaults[trace_index] # Child is the layout # ------------------- elif child is self.layout: return self._layout_defaults # Unknown child # ------------- else: raise ValueError("Unrecognized child: %s" % child) def _init_child_props(self, child): """ Initialize the properites dict for a child trace or layout Note: this method must match the name/signature of one on BasePlotlyType Parameters ---------- child : BaseTraceType | BaseLayoutType Returns ------- None """ # layout and traces dict are initialize when figure is constructed # and when new traces are added to the figure pass # Layout # ------ def _initialize_layout_template(self): import plotly.io as pio if self._layout_obj.template is None: if pio.templates.default is not None: self._layout_obj.template = pio.templates.default else: self._layout_obj.template = None @property def layout(self): """ The `layout` property of the figure Returns ------- plotly.graph_objs.Layout """ return self["layout"] @layout.setter def layout(self, new_layout): # Validate new layout # ------------------- new_layout = self._layout_validator.validate_coerce(new_layout) new_layout_data = deepcopy(new_layout._props) # Unparent current layout # ----------------------- if self._layout_obj: old_layout_data = deepcopy(self._layout_obj._props) self._layout_obj._orphan_props.update(old_layout_data) self._layout_obj._parent = None # Parent new layout # ----------------- self._layout = new_layout_data new_layout._parent = self new_layout._orphan_props.clear() self._layout_obj = new_layout # Initialize template object # -------------------------- self._initialize_layout_template() # Notify JS side self._send_relayout_msg(new_layout_data) def plotly_relayout(self, relayout_data, **kwargs): """ Perform a Plotly relayout operation on the figure's layout Parameters ---------- relayout_data : dict Dict of layout updates dict keys are strings that specify the properties to be updated. Nested properties are expressed by joining successive keys on '.' characters (e.g. 'xaxis.range') dict values are the values to use to update the layout. Returns ------- None """ # Handle source_view_id # --------------------- # If not None, the source_view_id is the UID of the frontend # Plotly.js view that initially triggered this relayout operation # (e.g. the user clicked on the toolbar to change the drag mode # from zoom to pan). We pass this UID along so that the frontend # views can determine whether they need to apply the relayout # operation on themselves. if "source_view_id" in kwargs: msg_kwargs = {"source_view_id": kwargs["source_view_id"]} else: msg_kwargs = {} # Perform relayout operation on layout dict # ----------------------------------------- relayout_changes = self._perform_plotly_relayout(relayout_data) if relayout_changes: # The relayout operation resulted in a change to some layout # properties, so we dispatch change callbacks and send the # relayout message to the frontend (if any) self._send_relayout_msg(relayout_changes, **msg_kwargs) self._dispatch_layout_change_callbacks(relayout_changes) def _perform_plotly_relayout(self, relayout_data): """ Perform a relayout operation on the figure's layout data and return the changes that were applied Parameters ---------- relayout_data : dict[str, any] See the docstring for plotly_relayout Returns ------- relayout_changes: dict[str, any] Subset of relayout_data including only the keys / values that resulted in a change to the figure's layout data """ # Initialize relayout changes # --------------------------- # This will be a subset of the relayout_data including only the # keys / values that are changed in the figure's layout data relayout_changes = {} # Process each key # ---------------- for key_path_str, v in relayout_data.items(): if not BaseFigure._is_key_path_compatible(key_path_str, self.layout): raise ValueError( """ Invalid property path '{key_path_str}' for layout """.format( key_path_str=key_path_str ) ) # Apply set operation on the layout dict val_changed = BaseFigure._set_in(self._layout, key_path_str, v) if val_changed: relayout_changes[key_path_str] = v return relayout_changes @staticmethod def _is_key_path_compatible(key_path_str, plotly_obj): """ Return whether the specifieid key path string is compatible with the specified plotly object for the purpose of relayout/restyle operation """ # Convert string to tuple of path components # e.g. 'foo[0].bar[1]' -> ('foo', 0, 'bar', 1) key_path_tuple = BaseFigure._str_to_dict_path(key_path_str) # Remove trailing integer component # e.g. ('foo', 0, 'bar', 1) -> ('foo', 0, 'bar') # We do this because it's fine for relayout/restyle to create new # elements in the final array in the path. if isinstance(key_path_tuple[-1], int): key_path_tuple = key_path_tuple[:-1] # Test whether modified key path tuple is in plotly_obj return key_path_tuple in plotly_obj def _relayout_child(self, child, key_path_str, val): """ Process relayout operation on child layout object Parameters ---------- child : BaseLayoutType The figure's layout key_path_str : A key path string (e.g. 'foo.bar[0]') val Relayout value Returns ------- None """ # Validate input # -------------- assert child is self.layout # Not in batch mode # ------------- # Dispatch change callbacks and send relayout message if not self._in_batch_mode: relayout_msg = {key_path_str: val} self._send_relayout_msg(relayout_msg) self._dispatch_layout_change_callbacks(relayout_msg) # In batch mode # ------------- # Add key_path_str/val to saved batch edits else: self._batch_layout_edits[key_path_str] = val # Dispatch change callbacks # ------------------------- @staticmethod def _build_dispatch_plan(key_path_strs): """ Build a dispatch plan for a list of key path strings A dispatch plan is a dict: - *from* path tuples that reference an object that has descendants that are referenced in `key_path_strs`. - *to* sets of tuples that correspond to descendants of the object above. Parameters ---------- key_path_strs : list[str] List of key path strings. For example: ['xaxis.rangeselector.font.color', 'xaxis.rangeselector.bgcolor'] Returns ------- dispatch_plan: dict[tuple[str|int], set[tuple[str|int]]] Examples -------- >>> key_path_strs = ['xaxis.rangeselector.font.color', ... 'xaxis.rangeselector.bgcolor'] >>> BaseFigure._build_dispatch_plan(key_path_strs) # doctest: +SKIP {(): {'xaxis', ('xaxis', 'rangeselector'), ('xaxis', 'rangeselector', 'bgcolor'), ('xaxis', 'rangeselector', 'font'), ('xaxis', 'rangeselector', 'font', 'color')}, ('xaxis',): {('rangeselector',), ('rangeselector', 'bgcolor'), ('rangeselector', 'font'), ('rangeselector', 'font', 'color')}, ('xaxis', 'rangeselector'): {('bgcolor',), ('font',), ('font', 'color')}, ('xaxis', 'rangeselector', 'font'): {('color',)}} """ dispatch_plan = {} for key_path_str in key_path_strs: key_path = BaseFigure._str_to_dict_path(key_path_str) key_path_so_far = () keys_left = key_path # Iterate down the key path for next_key in key_path: if key_path_so_far not in dispatch_plan: dispatch_plan[key_path_so_far] = set() to_add = [keys_left[: i + 1] for i in range(len(keys_left))] dispatch_plan[key_path_so_far].update(to_add) key_path_so_far = key_path_so_far + (next_key,) keys_left = keys_left[1:] return dispatch_plan def _dispatch_layout_change_callbacks(self, relayout_data): """ Dispatch property change callbacks given relayout_data Parameters ---------- relayout_data : dict[str, any] See docstring for plotly_relayout. Returns ------- None """ # Build dispatch plan # ------------------- key_path_strs = list(relayout_data.keys()) dispatch_plan = BaseFigure._build_dispatch_plan(key_path_strs) # Dispatch changes to each layout objects # --------------------------------------- for path_tuple, changed_paths in dispatch_plan.items(): if path_tuple in self.layout: dispatch_obj = self.layout[path_tuple] if isinstance(dispatch_obj, BasePlotlyType): dispatch_obj._dispatch_change_callbacks(changed_paths) def _dispatch_trace_change_callbacks(self, restyle_data, trace_indexes): """ Dispatch property change callbacks given restyle_data Parameters ---------- restyle_data : dict[str, any] See docstring for plotly_restyle. trace_indexes : list[int] List of trace indexes that restyle operation applied to Returns ------- None """ # Build dispatch plan # ------------------- key_path_strs = list(restyle_data.keys()) dispatch_plan = BaseFigure._build_dispatch_plan(key_path_strs) # Dispatch changes to each object in each trace # --------------------------------------------- for path_tuple, changed_paths in dispatch_plan.items(): for trace_ind in trace_indexes: trace = self.data[trace_ind] if path_tuple in trace: dispatch_obj = trace[path_tuple] if isinstance(dispatch_obj, BasePlotlyType): dispatch_obj._dispatch_change_callbacks(changed_paths) # Frames # ------ @property def frames(self): """ The `frames` property is a tuple of the figure's frame objects Returns ------- tuple[plotly.graph_objs.Frame] """ return self["frames"] @frames.setter def frames(self, new_frames): # Note: Frames are not supported by the FigureWidget subclass so we # only validate coerce the frames. We don't emit any events on frame # changes, and we don't reparent the frames. # Validate frames self._frame_objs = self._frames_validator.validate_coerce(new_frames) # Update # ------ def plotly_update( self, restyle_data=None, relayout_data=None, trace_indexes=None, **kwargs ): """ Perform a Plotly update operation on the figure. Note: This operation both mutates and returns the figure Parameters ---------- restyle_data : dict Traces update specification. See the docstring for the `plotly_restyle` method for details relayout_data : dict Layout update specification. See the docstring for the `plotly_relayout` method for details trace_indexes : Trace index, or list of trace indexes, that the update operation applies to. Defaults to all trace indexes. Returns ------- BaseFigure None """ # Handle source_view_id # --------------------- # If not None, the source_view_id is the UID of the frontend # Plotly.js view that initially triggered this update operation # (e.g. the user clicked a button that triggered an update # operation). We pass this UID along so that the frontend views can # determine whether they need to apply the update operation on # themselves. if "source_view_id" in kwargs: msg_kwargs = {"source_view_id": kwargs["source_view_id"]} else: msg_kwargs = {} # Perform update operation # ------------------------ # This updates the _data and _layout dicts, and returns the changes # to the traces (restyle_changes) and layout (relayout_changes) ( restyle_changes, relayout_changes, trace_indexes, ) = self._perform_plotly_update( restyle_data=restyle_data, relayout_data=relayout_data, trace_indexes=trace_indexes, ) # Send update message # ------------------- # Send a plotly_update message to the frontend (if any) if restyle_changes or relayout_changes: self._send_update_msg( restyle_data=restyle_changes, relayout_data=relayout_changes, trace_indexes=trace_indexes, **msg_kwargs ) # Dispatch changes # ---------------- # ### Dispatch restyle changes ### if restyle_changes: self._dispatch_trace_change_callbacks(restyle_changes, trace_indexes) # ### Dispatch relayout changes ### if relayout_changes: self._dispatch_layout_change_callbacks(relayout_changes) def _perform_plotly_update( self, restyle_data=None, relayout_data=None, trace_indexes=None ): # Check for early exist # --------------------- if not restyle_data and not relayout_data: # Nothing to do return None, None, None # Normalize input # --------------- if restyle_data is None: restyle_data = {} if relayout_data is None: relayout_data = {} trace_indexes = self._normalize_trace_indexes(trace_indexes) # Perform relayout # ---------------- relayout_changes = self._perform_plotly_relayout(relayout_data) # Perform restyle # --------------- restyle_changes = self._perform_plotly_restyle(restyle_data, trace_indexes) # Return changes # -------------- return restyle_changes, relayout_changes, trace_indexes # Plotly message stubs # -------------------- # send-message stubs that may be overridden by the widget subclass def _send_addTraces_msg(self, new_traces_data): pass def _send_moveTraces_msg(self, current_inds, new_inds): pass def _send_deleteTraces_msg(self, delete_inds): pass def _send_restyle_msg(self, style, trace_indexes=None, source_view_id=None): pass def _send_relayout_msg(self, layout, source_view_id=None): pass def _send_update_msg( self, restyle_data, relayout_data, trace_indexes=None, source_view_id=None ): pass def _send_animate_msg( self, styles_data, relayout_data, trace_indexes, animation_opts ): pass # Context managers # ---------------- @contextmanager def batch_update(self): """ A context manager that batches up trace and layout assignment operations into a singe plotly_update message that is executed when the context exits. Examples -------- For example, suppose we have a figure widget, `fig`, with a single trace. >>> import plotly.graph_objs as go >>> fig = go.FigureWidget(data=[{'y': [3, 4, 2]}]) If we want to update the xaxis range, the yaxis range, and the marker color, we could do so using a series of three property assignments as follows: >>> fig.layout.xaxis.range = [0, 5] >>> fig.layout.yaxis.range = [0, 10] >>> fig.data[0].marker.color = 'green' This will work, however it will result in three messages being sent to the front end (two relayout messages for the axis range updates followed by one restyle message for the marker color update). This can cause the plot to appear to stutter as the three updates are applied incrementally. We can avoid this problem by performing these three assignments in a `batch_update` context as follows: >>> with fig.batch_update(): ... fig.layout.xaxis.range = [0, 5] ... fig.layout.yaxis.range = [0, 10] ... fig.data[0].marker.color = 'green' Now, these three property updates will be sent to the frontend in a single update message, and they will be applied by the front end simultaneously. """ if self._in_batch_mode is True: yield else: try: self._in_batch_mode = True yield finally: # ### Disable batch mode ### self._in_batch_mode = False # ### Build plotly_update params ### ( restyle_data, relayout_data, trace_indexes, ) = self._build_update_params_from_batch() # ### Call plotly_update ### self.plotly_update( restyle_data=restyle_data, relayout_data=relayout_data, trace_indexes=trace_indexes, ) # ### Clear out saved batch edits ### self._batch_layout_edits.clear() self._batch_trace_edits.clear() def _build_update_params_from_batch(self): """ Convert `_batch_trace_edits` and `_batch_layout_edits` into the `restyle_data`, `relayout_data`, and `trace_indexes` params accepted by the `plotly_update` method. Returns ------- (dict, dict, list[int]) """ # Handle Style / Trace Indexes # ---------------------------- batch_style_commands = self._batch_trace_edits trace_indexes = sorted(set([trace_ind for trace_ind in batch_style_commands])) all_props = sorted( set( [ prop for trace_style in self._batch_trace_edits.values() for prop in trace_style ] ) ) # Initialize restyle_data dict with all values undefined restyle_data = { prop: [Undefined for _ in range(len(trace_indexes))] for prop in all_props } # Fill in values for trace_ind, trace_style in batch_style_commands.items(): for trace_prop, trace_val in trace_style.items(): restyle_trace_index = trace_indexes.index(trace_ind) restyle_data[trace_prop][restyle_trace_index] = trace_val # Handle Layout # ------------- relayout_data = self._batch_layout_edits # Return plotly_update params # --------------------------- return restyle_data, relayout_data, trace_indexes @contextmanager def batch_animate(self, duration=500, easing="cubic-in-out"): """ Context manager to animate trace / layout updates Parameters ---------- duration : number The duration of the transition, in milliseconds. If equal to zero, updates are synchronous. easing : string The easing function used for the transition. One of: - linear - quad - cubic - sin - exp - circle - elastic - back - bounce - linear-in - quad-in - cubic-in - sin-in - exp-in - circle-in - elastic-in - back-in - bounce-in - linear-out - quad-out - cubic-out - sin-out - exp-out - circle-out - elastic-out - back-out - bounce-out - linear-in-out - quad-in-out - cubic-in-out - sin-in-out - exp-in-out - circle-in-out - elastic-in-out - back-in-out - bounce-in-out Examples -------- Suppose we have a figure widget, `fig`, with a single trace. >>> import plotly.graph_objs as go >>> fig = go.FigureWidget(data=[{'y': [3, 4, 2]}]) 1) Animate a change in the xaxis and yaxis ranges using default duration and easing parameters. >>> with fig.batch_animate(): ... fig.layout.xaxis.range = [0, 5] ... fig.layout.yaxis.range = [0, 10] 2) Animate a change in the size and color of the trace's markers over 2 seconds using the elastic-in-out easing method >>> with fig.batch_animate(duration=2000, easing='elastic-in-out'): ... fig.data[0].marker.color = 'green' ... fig.data[0].marker.size = 20 """ # Validate inputs # --------------- duration = self._animation_duration_validator.validate_coerce(duration) easing = self._animation_easing_validator.validate_coerce(easing) if self._in_batch_mode is True: yield else: try: self._in_batch_mode = True yield finally: # Exit batch mode # --------------- self._in_batch_mode = False # Apply batch animate # ------------------- self._perform_batch_animate( { "transition": {"duration": duration, "easing": easing}, "frame": {"duration": duration}, } ) def _perform_batch_animate(self, animation_opts): """ Perform the batch animate operation This method should be called with the batch_animate() context manager exits. Parameters ---------- animation_opts : dict Animation options as accepted by frontend Plotly.animation command Returns ------- None """ # Apply commands to internal dictionaries as an update # ---------------------------------------------------- ( restyle_data, relayout_data, trace_indexes, ) = self._build_update_params_from_batch() ( restyle_changes, relayout_changes, trace_indexes, ) = self._perform_plotly_update(restyle_data, relayout_data, trace_indexes) # Convert style / trace_indexes into animate form # ----------------------------------------------- if self._batch_trace_edits: animate_styles, animate_trace_indexes = zip( *[ (trace_style, trace_index) for trace_index, trace_style in self._batch_trace_edits.items() ] ) else: animate_styles, animate_trace_indexes = {}, [] animate_layout = copy(self._batch_layout_edits) # Send animate message # -------------------- # Sends animate message to the front end (if any) self._send_animate_msg( styles_data=list(animate_styles), relayout_data=animate_layout, trace_indexes=list(animate_trace_indexes), animation_opts=animation_opts, ) # Clear batched commands # ---------------------- self._batch_layout_edits.clear() self._batch_trace_edits.clear() # Dispatch callbacks # ------------------ # ### Dispatch restyle changes ### if restyle_changes: self._dispatch_trace_change_callbacks(restyle_changes, trace_indexes) # ### Dispatch relayout changes ### if relayout_changes: self._dispatch_layout_change_callbacks(relayout_changes) # Exports # ------- def to_dict(self): """ Convert figure to a dictionary Note: the dictionary includes the properties explicitly set by the user, it does not include default values of unspecified properties Returns ------- dict """ # Handle data # ----------- data = deepcopy(self._data) # Handle layout # ------------- layout = deepcopy(self._layout) # Handle frames # ------------- # Frame key is only added if there are any frames res = {"data": data, "layout": layout} frames = deepcopy([frame._props for frame in self._frame_objs]) if frames: res["frames"] = frames return res def to_plotly_json(self): """ Convert figure to a JSON representation as a Python dict Returns ------- dict """ return self.to_dict() @staticmethod def _to_ordered_dict(d, skip_uid=False): """ Static helper for converting dict or list to structure of ordered dictionaries """ if isinstance(d, dict): # d is a dict result = collections.OrderedDict() for key in sorted(d.keys()): if skip_uid and key == "uid": continue else: result[key] = BaseFigure._to_ordered_dict(d[key], skip_uid=skip_uid) elif isinstance(d, list) and d and isinstance(d[0], dict): # d is a list of dicts result = [BaseFigure._to_ordered_dict(el, skip_uid=skip_uid) for el in d] else: result = d return result def to_ordered_dict(self, skip_uid=True): # Initialize resulting OrderedDict # -------------------------------- result = collections.OrderedDict() # Handle data # ----------- result["data"] = BaseFigure._to_ordered_dict(self._data, skip_uid=skip_uid) # Handle layout # ------------- result["layout"] = BaseFigure._to_ordered_dict(self._layout) # Handle frames # ------------- if self._frame_objs: frames_props = [frame._props for frame in self._frame_objs] result["frames"] = BaseFigure._to_ordered_dict(frames_props) return result # plotly.io methods # ----------------- # Note that docstrings are auto-generated in plotly/_docstring_gen.py def show(self, *args, **kwargs): import plotly.io as pio return pio.show(self, *args, **kwargs) def to_json(self, *args, **kwargs): import plotly.io as pio return pio.to_json(self, *args, **kwargs) def write_json(self, *args, **kwargs): import plotly.io as pio return pio.write_json(self, *args, **kwargs) def to_html(self, *args, **kwargs): import plotly.io as pio return pio.to_html(self, *args, **kwargs) def write_html(self, *args, **kwargs): import plotly.io as pio return pio.write_html(self, *args, **kwargs) def to_image(self, *args, **kwargs): import plotly.io as pio return pio.to_image(self, *args, **kwargs) def write_image(self, *args, **kwargs): import plotly.io as pio return pio.write_image(self, *args, **kwargs) # Static helpers # -------------- @staticmethod def _is_dict_list(v): """ Return true of the input object is a list of dicts """ return isinstance(v, list) and len(v) > 0 and isinstance(v[0], dict) @staticmethod def _perform_update(plotly_obj, update_obj, overwrite=False): """ Helper to support the update() methods on :class:`BaseFigure` and :class:`BasePlotlyType` Parameters ---------- plotly_obj : BasePlotlyType|tuple[BasePlotlyType] Object to up updated update_obj : dict|list[dict]|tuple[dict] When ``plotly_obj`` is an instance of :class:`BaseFigure`, ``update_obj`` should be a dict When ``plotly_obj`` is a tuple of instances of :class:`BasePlotlyType`, ``update_obj`` should be a tuple or list of dicts """ if update_obj is None: # Nothing to do return elif isinstance(plotly_obj, BasePlotlyType): # Handle initializing subplot ids # ------------------------------- # This should be valid even if xaxis2 hasn't been initialized: # >>> layout.update(xaxis2={'title': 'xaxis 2'}) if isinstance(plotly_obj, BaseLayoutType): for key in update_obj: if key not in plotly_obj: match = plotly_obj._subplot_re_match(key) if match: # We need to create a subplotid object plotly_obj[key] = {} # Handle invalid properties # ------------------------- invalid_props = [k for k in update_obj if k not in plotly_obj] plotly_obj._raise_on_invalid_property_error(*invalid_props) # Convert update_obj to dict # -------------------------- if isinstance(update_obj, BasePlotlyType): update_obj = update_obj.to_plotly_json() # Process valid properties # ------------------------ for key in update_obj: val = update_obj[key] if overwrite: # Don't recurse and assign property as-is plotly_obj[key] = val continue validator = plotly_obj._get_prop_validator(key) if isinstance(validator, CompoundValidator) and isinstance(val, dict): # Update compound objects recursively # plotly_obj[key].update(val) BaseFigure._perform_update(plotly_obj[key], val) elif isinstance(validator, CompoundArrayValidator): if plotly_obj[key]: # plotly_obj has an existing non-empty array for key # In this case we merge val into the existing elements BaseFigure._perform_update(plotly_obj[key], val) # If update tuple is longer that current tuple, append the # extra elements to the end if isinstance(val, (list, tuple)) and len(val) > len( plotly_obj[key] ): plotly_obj[key] = plotly_obj[key] + tuple( val[len(plotly_obj[key]) :] ) else: # plotly_obj is an empty or uninitialized list for key # In this case we accept val as is plotly_obj[key] = val else: # Assign non-compound value plotly_obj[key] = val elif isinstance(plotly_obj, tuple): if len(update_obj) == 0: # Nothing to do return else: for i, plotly_element in enumerate(plotly_obj): if isinstance(update_obj, dict): if i in update_obj: update_element = update_obj[i] else: continue else: update_element = update_obj[i % len(update_obj)] BaseFigure._perform_update(plotly_element, update_element) else: raise ValueError( "Unexpected plotly object with type {typ}".format(typ=type(plotly_obj)) ) @staticmethod def _index_is(iterable, val): """ Return the index of a value in an iterable using object identity (not object equality as is the case for list.index) """ index_list = [i for i, curr_val in enumerate(iterable) if curr_val is val] if not index_list: raise ValueError("Invalid value") return index_list[0] class BasePlotlyType(object): """ BasePlotlyType is the base class for all objects in the trace, layout, and frame object hierarchies """ # ### Mapped (deprecated) properties ### # dict for deprecated property name (e.g. 'titlefont') to tuple # of relative path to new property (e.g. ('title', 'font') _mapped_properties = {} def __init__(self, plotly_name, **kwargs): """ Construct a new BasePlotlyType Parameters ---------- plotly_name : str The lowercase name of the plotly object kwargs : dict Invalid props/values to raise on """ # ### _skip_invalid ## # If True, then invalid properties should be skipped, if False then # invalid properties will result in an exception self._skip_invalid = False # Validate inputs # --------------- self._process_kwargs(**kwargs) # Store params # ------------ self._plotly_name = plotly_name # Initialize properties # --------------------- # ### _validators ### # A dict from property names to property validators self._validators = {} # ### _compound_props ### # A dict from compound property names to compound objects self._compound_props = {} # ### _compound_array_props ### # A dict from compound array property names to tuples of compound # objects self._compound_array_props = {} # ### _orphan_props ### # A dict of properties for use while object has no parent. When # object has a parent, it requests its properties dict from its # parent and doesn't use this. self._orphan_props = {} # ### _parent ### # The parent of the object. May be another BasePlotlyType or it may # be a BaseFigure (as is the case for the Layout and Trace objects) self._parent = None # ### _change_callbacks ### # A dict from tuples of child property path tuples to lists # of callbacks that should be executed whenever any of these # properties is modified self._change_callbacks = {} def _process_kwargs(self, **kwargs): """ Process any extra kwargs that are not predefined as constructor params """ invalid_kwargs = {} for k, v in kwargs.items(): if k in self: # e.g. underscore kwargs like marker_line_color self[k] = v else: invalid_kwargs[k] = v if invalid_kwargs and not self._skip_invalid: self._raise_on_invalid_property_error(*invalid_kwargs.keys()) @property def plotly_name(self): """ The plotly name of the object Returns ------- str """ return self._plotly_name @property def _parent_path_str(self): """ dot-separated path string to this object's parent. Returns ------- str Examples -------- >>> import plotly.graph_objs as go >>> go.Layout()._parent_path_str '' >>> go.layout.XAxis()._parent_path_str 'layout' >>> go.layout.xaxis.rangeselector.Button()._parent_path_str 'layout.xaxis.rangeselector' """ raise NotImplementedError @property def _prop_descriptions(self): """ Formatted string containing all of this obejcts child properties and their descriptions Returns ------- str """ raise NotImplementedError @property def _props(self): """ Dictionary used to store this object properties. When the object has a parent, this dict is retreived from the parent. When the object does not have a parent, this dict is the object's `_orphan_props` property Note: Property will return None if the object has a parent and the object's properties have not been initialized using the `_init_props` method. Returns ------- dict|None """ if self.parent is None: # Use orphan data return self._orphan_props else: # Get data from parent's dict return self.parent._get_child_props(self) def _get_child_props(self, child): """ Return properties dict for child Parameters ---------- child : BasePlotlyType Returns ------- dict """ if self._props is None: # If this node's properties are uninitialized then so are its # child's return None else: # ### Child a compound property ### if child.plotly_name in self._compound_props: return self._props.get(child.plotly_name, None) # ### Child an element of a compound array property ### elif child.plotly_name in self._compound_array_props: children = self._compound_array_props[child.plotly_name] child_ind = BaseFigure._index_is(children, child) assert child_ind is not None children_props = self._props.get(child.plotly_name, None) return ( children_props[child_ind] if children_props is not None and len(children_props) > child_ind else None ) # ### Invalid child ### else: raise ValueError("Invalid child with name: %s" % child.plotly_name) def _init_props(self): """ Ensure that this object's properties dict has been initialized. When the object has a parent, this ensures that the parent has an initialized properties dict with this object's plotly_name as a key. Returns ------- None """ # Ensure that _data is initialized. if self._props is not None: pass else: self._parent._init_child_props(self) def _init_child_props(self, child): """ Ensure that a properties dict has been initialized for a child object Parameters ---------- child : BasePlotlyType Returns ------- None """ # Init our own properties # ----------------------- self._init_props() # Child a compound property # ------------------------- if child.plotly_name in self._compound_props: if child.plotly_name not in self._props: self._props[child.plotly_name] = {} # Child an element of a compound array property # --------------------------------------------- elif child.plotly_name in self._compound_array_props: children = self._compound_array_props[child.plotly_name] child_ind = BaseFigure._index_is(children, child) assert child_ind is not None if child.plotly_name not in self._props: # Initialize list self._props[child.plotly_name] = [] # Make sure list is long enough for child children_list = self._props[child.plotly_name] while len(children_list) <= child_ind: children_list.append({}) # Invalid child # ------------- else: raise ValueError("Invalid child with name: %s" % child.plotly_name) def _get_child_prop_defaults(self, child): """ Return default properties dict for child Parameters ---------- child : BasePlotlyType Returns ------- dict """ if self._prop_defaults is None: # If this node's default properties are uninitialized then so are # its child's return None else: # ### Child a compound property ### if child.plotly_name in self._compound_props: return self._prop_defaults.get(child.plotly_name, None) # ### Child an element of a compound array property ### elif child.plotly_name in self._compound_array_props: children = self._compound_array_props[child.plotly_name] child_ind = BaseFigure._index_is(children, child) assert child_ind is not None children_props = self._prop_defaults.get(child.plotly_name, None) return ( children_props[child_ind] if children_props is not None and len(children_props) > child_ind else None ) # ### Invalid child ### else: raise ValueError("Invalid child with name: %s" % child.plotly_name) @property def _prop_defaults(self): """ Return default properties dict Returns ------- dict """ if self.parent is None: return None else: return self.parent._get_child_prop_defaults(self) def _get_prop_validator(self, prop): """ Return the validator associated with the specified property Parameters ---------- prop: str A property that exists in this object Returns ------- BaseValidator """ # Handle remapping # ---------------- if prop in self._mapped_properties: prop_path = self._mapped_properties[prop] plotly_obj = self[prop_path[:-1]] prop = prop_path[-1] else: prop_path = BaseFigure._str_to_dict_path(prop) plotly_obj = self[prop_path[:-1]] prop = prop_path[-1] # Return validator # ---------------- return plotly_obj._validators[prop] @property def parent(self): """ Return the object's parent, or None if the object has no parent Returns ------- BasePlotlyType|BaseFigure """ return self._parent @property def figure(self): """ Reference to the top-level Figure or FigureWidget that this object belongs to. None if the object does not belong to a Figure Returns ------- Union[BaseFigure, None] """ top_parent = self while top_parent is not None: if isinstance(top_parent, BaseFigure): break else: top_parent = top_parent.parent return top_parent # Magic Methods # ------------- def __reduce__(self): """ Custom implementation of reduce is used to support deep copying and pickling """ props = self.to_plotly_json() return (self.__class__, (props,)) def __getitem__(self, prop): """ Get item or nested item from object Parameters ---------- prop : str|tuple If prop is the name of a property of this object, then the property is returned. If prop is a nested property path string (e.g. 'foo[1].bar'), then a nested property is returned (e.g. obj['foo'][1]['bar']) If prop is a path tuple (e.g. ('foo', 1, 'bar')), then a nested property is returned (e.g. obj['foo'][1]['bar']). Returns ------- Any """ # Normalize prop # -------------- # Convert into a property tuple prop = BaseFigure._str_to_dict_path(prop) # Handle remapping # ---------------- if prop and prop[0] in self._mapped_properties: prop = self._mapped_properties[prop[0]] + prop[1:] # Handle scalar case # ------------------ # e.g. ('foo',) if len(prop) == 1: # Unwrap scalar tuple prop = prop[0] if prop not in self._validators: raise KeyError(prop) validator = self._validators[prop] if prop in self._compound_props: return validator.present(self._compound_props[prop]) elif prop in self._compound_array_props: return validator.present(self._compound_array_props[prop]) elif self._props is not None and prop in self._props: return validator.present(self._props[prop]) elif self._prop_defaults is not None: return validator.present(self._prop_defaults.get(prop, None)) else: return None # Handle non-scalar case # ---------------------- # e.g. ('foo', 1), () else: res = self for p in prop: res = res[p] return res def __contains__(self, prop): """ Determine whether object contains a property or nested property Parameters ---------- prop : str|tuple If prop is a simple string (e.g. 'foo'), then return true of the object contains an element named 'foo' If prop is a property path string (e.g. 'foo[0].bar'), then return true if the obejct contains the nested elements for each entry in the path string (e.g. 'bar' in obj['foo'][0]) If prop is a property path tuple (e.g. ('foo', 0, 'bar')), then return true if the object contains the nested elements for each entry in the path string (e.g. 'bar' in obj['foo'][0]) Returns ------- bool """ prop = BaseFigure._str_to_dict_path(prop) # Handle remapping if prop and prop[0] in self._mapped_properties: prop = self._mapped_properties[prop[0]] + prop[1:] obj = self for p in prop: if isinstance(p, int): if isinstance(obj, tuple) and 0 <= p < len(obj): obj = obj[p] else: return False else: if obj is not None and p in obj._validators: obj = obj[p] else: return False return True def __setitem__(self, prop, value): """ Parameters ---------- prop : str The name of a direct child of this object Note: Setting nested properties using property path string or property path tuples is not supported. value New property value Returns ------- None """ # Normalize prop # -------------- # Convert into a property tuple orig_prop = prop prop = BaseFigure._str_to_dict_path(prop) # Handle empty case # ----------------- if len(prop) == 0: raise KeyError(orig_prop) # Handle remapping # ---------------- if prop[0] in self._mapped_properties: prop = self._mapped_properties[prop[0]] + prop[1:] # Handle scalar case # ------------------ # e.g. ('foo',) if len(prop) == 1: # ### Unwrap scalar tuple ### prop = prop[0] # ### Validate prop ### if prop not in self._validators: self._raise_on_invalid_property_error(prop) # ### Get validator for this property ### validator = self._validators[prop] # ### Handle compound property ### if isinstance(validator, CompoundValidator): self._set_compound_prop(prop, value) # ### Handle compound array property ### elif isinstance(validator, (CompoundArrayValidator, BaseDataValidator)): self._set_array_prop(prop, value) # ### Handle simple property ### else: self._set_prop(prop, value) # Handle non-scalar case # ---------------------- # e.g. ('foo', 1), () else: res = self for p in prop[:-1]: res = res[p] res[prop[-1]] = value def __setattr__(self, prop, value): """ Parameters ---------- prop : str The name of a direct child of this object value New property value Returns ------- None """ if prop.startswith("_") or hasattr(self, prop) or prop in self._validators: # Let known properties and private properties through super(BasePlotlyType, self).__setattr__(prop, value) else: # Raise error on unknown public properties self._raise_on_invalid_property_error(prop) def __iter__(self): """ Return an iterator over the object's properties """ res = list(self._validators.keys()) for prop in self._mapped_properties: res.append(prop) return iter(res) def __eq__(self, other): """ Test for equality To be considered equal, `other` must have the same type as this object and their `to_plotly_json` representaitons must be identical. Parameters ---------- other The object to compare against Returns ------- bool """ if not isinstance(other, self.__class__): # Require objects to be of the same plotly type return False else: # Compare plotly_json representations # Use _vals_equal instead of `==` to handle cases where # underlying dicts contain numpy arrays return BasePlotlyType._vals_equal( self._props if self._props is not None else {}, other._props if other._props is not None else {}, ) @staticmethod def _build_repr_for_class(props, class_name, parent_path_str=None): """ Helper to build representation string for a class Parameters ---------- class_name : str Name of the class being represented parent_path_str : str of None (default) Name of the class's parent package to display props : dict Properties to unpack into the constructor Returns ------- str The representation string """ if parent_path_str: class_name = parent_path_str + "." + class_name if len(props) == 0: repr_str = class_name + "()" else: pprinter = ElidedPrettyPrinter(threshold=200, width=120) pprint_res = pprinter.pformat(props) # pprint_res is indented by 1 space. Add extra 3 spaces for PEP8 # complaint indent body = " " + pprint_res[1:-1].replace("\n", "\n ") repr_str = class_name + "({\n " + body + "\n})" return repr_str def __repr__(self): """ Customize object representation when displayed in the terminal/notebook """ # Get all properties props = self._props if self._props is not None else {} # Remove literals (These can't be specified in the constructor) props = { p: v for p, v in props.items() if p in self._validators and not isinstance(self._validators[p], LiteralValidator) } # Elide template if "template" in props: props["template"] = "..." # Build repr string repr_str = BasePlotlyType._build_repr_for_class( props=props, class_name=self.__class__.__name__, parent_path_str=self._parent_path_str, ) return repr_str def _raise_on_invalid_property_error(self, *args): """ Raise informative exception when invalid property names are encountered Parameters ---------- args : list[str] List of property names that have already been determined to be invalid Raises ------ ValueError Always """ invalid_props = args if invalid_props: if len(invalid_props) == 1: prop_str = "property" invalid_str = repr(invalid_props[0]) else: prop_str = "properties" invalid_str = repr(invalid_props) module_root = "plotly.graph_objs." if self._parent_path_str: full_obj_name = ( module_root + self._parent_path_str + "." + self.__class__.__name__ ) else: full_obj_name = module_root + self.__class__.__name__ raise ValueError( "Invalid {prop_str} specified for object of type " "{full_obj_name}: {invalid_str}\n\n" " Valid properties:\n" "{prop_descriptions}".format( prop_str=prop_str, full_obj_name=full_obj_name, invalid_str=invalid_str, prop_descriptions=self._prop_descriptions, ) ) def update(self, dict1=None, overwrite=False, **kwargs): """ Update the properties of an object with a dict and/or with keyword arguments. This recursively updates the structure of the original object with the values in the input dict / keyword arguments. Parameters ---------- dict1 : dict Dictionary of properties to be updated overwrite: bool If True, overwrite existing properties. If False, apply updates to existing properties recursively, preserving existing properties that are not specified in the update operation. kwargs : Keyword/value pair of properties to be updated Returns ------- BasePlotlyType Updated plotly object """ if self.figure: with self.figure.batch_update(): BaseFigure._perform_update(self, dict1, overwrite=overwrite) BaseFigure._perform_update(self, kwargs, overwrite=overwrite) else: BaseFigure._perform_update(self, dict1, overwrite=overwrite) BaseFigure._perform_update(self, kwargs, overwrite=overwrite) return self def pop(self, key, *args): """ Remove the value associated with the specified key and return it Parameters ---------- key: str Property name dflt The default value to return if key was not found in object Returns ------- value The removed value that was previously associated with key Raises ------ KeyError If key is not in object and no dflt argument specified """ # Handle default if key not in self and args: return args[0] elif key in self: val = self[key] self[key] = None return val else: raise KeyError(key) @property def _in_batch_mode(self): """ True if the object belongs to a figure that is currently in batch mode Returns ------- bool """ return self.parent and self.parent._in_batch_mode def _set_prop(self, prop, val): """ Set the value of a simple property Parameters ---------- prop : str Name of a simple (non-compound, non-array) property val The new property value Returns ------- Any The coerced assigned value """ # val is Undefined # ---------------- if val is Undefined: # Do nothing return # Import value # ------------ validator = self._validators.get(prop) try: val = validator.validate_coerce(val) except ValueError as err: if self._skip_invalid: return else: raise err # val is None # ----------- if val is None: # Check if we should send null update if self._props and prop in self._props: # Remove property if not in batch mode if not self._in_batch_mode: self._props.pop(prop) # Send property update message self._send_prop_set(prop, val) # val is valid value # ------------------ else: # Make sure properties dict is initialized self._init_props() # Check whether the value is a change if prop not in self._props or not BasePlotlyType._vals_equal( self._props[prop], val ): # Set property value if not in batch mode if not self._in_batch_mode: self._props[prop] = val # Send property update message self._send_prop_set(prop, val) return val def _set_compound_prop(self, prop, val): """ Set the value of a compound property Parameters ---------- prop : str Name of a compound property val The new property value Returns ------- BasePlotlyType The coerced assigned object """ # val is Undefined # ---------------- if val is Undefined: # Do nothing return # Import value # ------------ validator = self._validators.get(prop) val = validator.validate_coerce(val, skip_invalid=self._skip_invalid) # Save deep copies of current and new states # ------------------------------------------ curr_val = self._compound_props.get(prop, None) if curr_val is not None: curr_dict_val = deepcopy(curr_val._props) else: curr_dict_val = None if val is not None: new_dict_val = deepcopy(val._props) else: new_dict_val = None # Update _props dict # ------------------ if not self._in_batch_mode: if not new_dict_val: if self._props and prop in self._props: self._props.pop(prop) else: self._init_props() self._props[prop] = new_dict_val # Send update if there was a change in value # ------------------------------------------ if not BasePlotlyType._vals_equal(curr_dict_val, new_dict_val): self._send_prop_set(prop, new_dict_val) # Reparent # -------- # ### Reparent new value and clear orphan data ### if isinstance(val, BasePlotlyType): val._parent = self val._orphan_props.clear() # ### Unparent old value and update orphan data ### if curr_val is not None: if curr_dict_val is not None: curr_val._orphan_props.update(curr_dict_val) curr_val._parent = None # Update _compound_props # ---------------------- self._compound_props[prop] = val return val def _set_array_prop(self, prop, val): """ Set the value of a compound property Parameters ---------- prop : str Name of a compound property val The new property value Returns ------- tuple[BasePlotlyType] The coerced assigned object """ # val is Undefined # ---------------- if val is Undefined: # Do nothing return # Import value # ------------ validator = self._validators.get(prop) val = validator.validate_coerce(val, skip_invalid=self._skip_invalid) # Save deep copies of current and new states # ------------------------------------------ curr_val = self._compound_array_props.get(prop, None) if curr_val is not None: curr_dict_vals = [deepcopy(cv._props) for cv in curr_val] else: curr_dict_vals = None if val is not None: new_dict_vals = [deepcopy(nv._props) for nv in val] else: new_dict_vals = None # Update _props dict # ------------------ if not self._in_batch_mode: if not new_dict_vals: if self._props and prop in self._props: self._props.pop(prop) else: self._init_props() self._props[prop] = new_dict_vals # Send update if there was a change in value # ------------------------------------------ if not BasePlotlyType._vals_equal(curr_dict_vals, new_dict_vals): self._send_prop_set(prop, new_dict_vals) # Reparent # -------- # ### Reparent new values and clear orphan data ### if val is not None: for v in val: v._orphan_props.clear() v._parent = self # ### Unparent old value and update orphan data ### if curr_val is not None: for cv, cv_dict in zip(curr_val, curr_dict_vals): if cv_dict is not None: cv._orphan_props.update(cv_dict) cv._parent = None # Update _compound_array_props # ---------------------------- self._compound_array_props[prop] = val return val def _send_prop_set(self, prop_path_str, val): """ Notify parent that a property has been set to a new value Parameters ---------- prop_path_str : str Property path string (e.g. 'foo[0].bar') of property that was set, relative to this object val New value for property. Either a simple value, a dict, or a tuple of dicts. This should *not* be a BasePlotlyType object. Returns ------- None """ raise NotImplementedError() def _prop_set_child(self, child, prop_path_str, val): """ Propagate property setting notification from child to parent Parameters ---------- child : BasePlotlyType Child object prop_path_str : str Property path string (e.g. 'foo[0].bar') of property that was set, relative to `child` val New value for property. Either a simple value, a dict, or a tuple of dicts. This should *not* be a BasePlotlyType object. Returns ------- None """ # Child is compound array property # -------------------------------- child_prop_val = getattr(self, child.plotly_name) if isinstance(child_prop_val, (list, tuple)): child_ind = BaseFigure._index_is(child_prop_val, child) obj_path = "{child_name}.{child_ind}.{prop}".format( child_name=child.plotly_name, child_ind=child_ind, prop=prop_path_str ) # Child is compound property # -------------------------- else: obj_path = "{child_name}.{prop}".format( child_name=child.plotly_name, prop=prop_path_str ) # Propagate to parent # ------------------- self._send_prop_set(obj_path, val) def _restyle_child(self, child, prop, val): """ Propagate _restyle_child to parent Note: This method must match the name and signature of the corresponding method on BaseFigure """ self._prop_set_child(child, prop, val) def _relayout_child(self, child, prop, val): """ Propagate _relayout_child to parent Note: This method must match the name and signature of the corresponding method on BaseFigure """ self._prop_set_child(child, prop, val) # Callbacks # --------- def _dispatch_change_callbacks(self, changed_paths): """ Execute the appropriate change callback functions given a set of changed property path tuples Parameters ---------- changed_paths : set[tuple[int|str]] Returns ------- None """ # Loop over registered callbacks # ------------------------------ for prop_path_tuples, callbacks in self._change_callbacks.items(): # ### Compute callback paths that changed ### common_paths = changed_paths.intersection(set(prop_path_tuples)) if common_paths: # #### Invoke callback #### callback_args = [self[cb_path] for cb_path in prop_path_tuples] for callback in callbacks: callback(self, *callback_args) def on_change(self, callback, *args, **kwargs): """ Register callback function to be called when certain properties or subproperties of this object are modified. Callback will be invoked whenever ANY of these properties is modified. Furthermore, the callback will only be invoked once even if multiple properties are modified during the same restyle / relayout / update operation. Parameters ---------- callback : function Function that accepts 1 + len(`args`) parameters. First parameter is this object. Second through last parameters are the property / subpropery values referenced by args. args : list[str|tuple[int|str]] List of property references where each reference may be one of: 1) A property name string (e.g. 'foo') for direct properties 2) A property path string (e.g. 'foo[0].bar') for subproperties 3) A property path tuple (e.g. ('foo', 0, 'bar')) for subproperties append : bool True if callback should be appended to previously registered callback on the same properties, False if callback should replace previously registered callbacks on the same properties. Defaults to False. Examples -------- Register callback that prints out the range extents of the xaxis and yaxis whenever either either of them changes. >>> import plotly.graph_objects as go >>> fig = go.Figure(go.Scatter(x=[1, 2], y=[1, 0])) >>> fig.layout.on_change( ... lambda obj, xrange, yrange: print("%s-%s" % (xrange, yrange)), ... ('xaxis', 'range'), ('yaxis', 'range')) Returns ------- None """ # Warn if object not descendent of a figure # ----------------------------------------- if not self.figure: class_name = self.__class__.__name__ msg = """ {class_name} object is not a descendant of a Figure. on_change callbacks are not supported in this case. """.format( class_name=class_name ) raise ValueError(msg) # Validate args not empty # ----------------------- if len(args) == 0: raise ValueError("At least one change property must be specified") # Validate args # ------------- invalid_args = [arg for arg in args if arg not in self] if invalid_args: raise ValueError("Invalid property specification(s): %s" % invalid_args) # Process append option # --------------------- append = kwargs.get("append", False) # Normalize args to path tuples # ----------------------------- arg_tuples = tuple([BaseFigure._str_to_dict_path(a) for a in args]) # Initialize callbacks list # ------------------------- # Initialize an empty callbacks list if there are no previously # defined callbacks for this collection of args, or if append is False if arg_tuples not in self._change_callbacks or not append: self._change_callbacks[arg_tuples] = [] # Register callback # ----------------- self._change_callbacks[arg_tuples].append(callback) def to_plotly_json(self): """ Return plotly JSON representation of object as a Python dict Returns ------- dict """ return deepcopy(self._props if self._props is not None else {}) @staticmethod def _vals_equal(v1, v2): """ Recursive equality function that handles nested dicts / tuples / lists that contain numpy arrays. v1 First value to compare v2 Second value to compare Returns ------- bool True if v1 and v2 are equal, False otherwise """ np = get_module("numpy") if np is not None and ( isinstance(v1, np.ndarray) or isinstance(v2, np.ndarray) ): return np.array_equal(v1, v2) elif isinstance(v1, (list, tuple)): # Handle recursive equality on lists and tuples return ( isinstance(v2, (list, tuple)) and len(v1) == len(v2) and all(BasePlotlyType._vals_equal(e1, e2) for e1, e2 in zip(v1, v2)) ) elif isinstance(v1, dict): # Handle recursive equality on dicts return ( isinstance(v2, dict) and set(v1.keys()) == set(v2.keys()) and all(BasePlotlyType._vals_equal(v1[k], v2[k]) for k in v1) ) else: return v1 == v2 class BaseLayoutHierarchyType(BasePlotlyType): """ Base class for all types in the layout hierarchy """ @property def _parent_path_str(self): pass def __init__(self, plotly_name, **kwargs): super(BaseLayoutHierarchyType, self).__init__(plotly_name, **kwargs) def _send_prop_set(self, prop_path_str, val): if self.parent: # ### Inform parent of relayout operation ### self.parent._relayout_child(self, prop_path_str, val) class BaseLayoutType(BaseLayoutHierarchyType): """ Base class for the layout type. The Layout class itself is a code-generated subclass. """ # Dynamic properties # ------------------ # Unlike all other plotly types, BaseLayoutType has dynamic properties. # These are used when a layout has multiple instances of subplot types # (xaxis2, yaxis3, geo4, etc.) # # The base version of each suplot type is defined in the schema and code # generated. So the Layout subclass has statically defined properties # for xaxis, yaxis, geo, ternary, and scene. But, we need to dynamically # generated properties/validators as needed for xaxis2, yaxis3, etc. @property def _subplotid_validators(self): """ dict of validator classes for each subplot type Returns ------- dict """ raise NotImplementedError() def _subplot_re_match(self, prop): raise NotImplementedError() def __init__(self, plotly_name, **kwargs): """ Construct a new BaseLayoutType object Parameters ---------- plotly_name : str Name of the object (should always be 'layout') kwargs : dict[str, any] Properties that were not recognized by the Layout subclass. These are subplot identifiers (xaxis2, geo4, etc.) or they are invalid properties. """ # Validate inputs # --------------- assert plotly_name == "layout" # Call superclass constructor # --------------------------- super(BaseLayoutHierarchyType, self).__init__(plotly_name) # Initialize _subplotid_props # --------------------------- # This is a set storing the names of the layout's dynamic subplot # properties self._subplotid_props = set() # Process kwargs # -------------- self._process_kwargs(**kwargs) def _process_kwargs(self, **kwargs): """ Process any extra kwargs that are not predefined as constructor params """ unknown_kwargs = { k: v for k, v in kwargs.items() if not self._subplot_re_match(k) } super(BaseLayoutHierarchyType, self)._process_kwargs(**unknown_kwargs) subplot_kwargs = {k: v for k, v in kwargs.items() if self._subplot_re_match(k)} for prop, value in subplot_kwargs.items(): self._set_subplotid_prop(prop, value) def _set_subplotid_prop(self, prop, value): """ Set a subplot property on the layout Parameters ---------- prop : str A valid subplot property value Subplot value """ # Get regular expression match # ---------------------------- # Note: we already tested that match exists in the constructor match = self._subplot_re_match(prop) subplot_prop = match.group(1) suffix_digit = int(match.group(2)) # Validate suffix digit # --------------------- if suffix_digit == 0: raise TypeError( "Subplot properties may only be suffixed by an " "integer >= 1\n" "Received {k}".format(k=prop) ) # Handle suffix_digit == 1 # ------------------------ # In this case we remove suffix digit (e.g. xaxis1 -> xaxis) if suffix_digit == 1: prop = subplot_prop # Construct and add validator # --------------------------- if prop not in self._validators: validator_class = self._subplotid_validators[subplot_prop] validator = validator_class(plotly_name=prop) self._validators[prop] = validator # Import value # ------------ # Use the standard _set_compound_prop method to # validate/coerce/import subplot value. This must be called AFTER # the validator instance is added to self._validators above. self._set_compound_prop(prop, value) self._subplotid_props.add(prop) def _strip_subplot_suffix_of_1(self, prop): """ Strip the suffix for subplot property names that have a suffix of 1. All other properties are returned unchanged e.g. 'xaxis1' -> 'xaxis' Parameters ---------- prop : str|tuple Returns ------- str|tuple """ # Let parent handle non-scalar cases # ---------------------------------- # e.g. ('xaxis', 'range') or 'xaxis.range' prop_tuple = BaseFigure._str_to_dict_path(prop) if len(prop_tuple) != 1 or not isinstance(prop_tuple[0], string_types): return prop else: # Unwrap to scalar string prop = prop_tuple[0] # Handle subplot suffix digit of 1 # -------------------------------- # Remove digit of 1 from subplot id (e.g.. xaxis1 -> xaxis) match = self._subplot_re_match(prop) if match: subplot_prop = match.group(1) suffix_digit = int(match.group(2)) if subplot_prop and suffix_digit == 1: prop = subplot_prop return prop def _get_prop_validator(self, prop): """ Custom _get_prop_validator that handles subplot properties """ prop = self._strip_subplot_suffix_of_1(prop) return super(BaseLayoutHierarchyType, self)._get_prop_validator(prop) def __getattr__(self, prop): """ Custom __getattr__ that handles dynamic subplot properties """ prop = self._strip_subplot_suffix_of_1(prop) if prop != "_subplotid_props" and prop in self._subplotid_props: validator = self._validators[prop] return validator.present(self._compound_props[prop]) else: return super(BaseLayoutHierarchyType, self).__getattribute__(prop) def __getitem__(self, prop): """ Custom __getitem__ that handles dynamic subplot properties """ prop = self._strip_subplot_suffix_of_1(prop) return super(BaseLayoutHierarchyType, self).__getitem__(prop) def __contains__(self, prop): """ Custom __contains__ that handles dynamic subplot properties """ prop = self._strip_subplot_suffix_of_1(prop) return super(BaseLayoutHierarchyType, self).__contains__(prop) def __setitem__(self, prop, value): """ Custom __setitem__ that handles dynamic subplot properties """ # Convert prop to prop tuple # -------------------------- prop_tuple = BaseFigure._str_to_dict_path(prop) if len(prop_tuple) != 1 or not isinstance(prop_tuple[0], string_types): # Let parent handle non-scalar non-string cases super(BaseLayoutHierarchyType, self).__setitem__(prop, value) return else: # Unwrap prop tuple prop = prop_tuple[0] # Check for subplot assignment # ---------------------------- match = self._subplot_re_match(prop) if match is None: # Set as ordinary property super(BaseLayoutHierarchyType, self).__setitem__(prop, value) else: # Set as subplotid property self._set_subplotid_prop(prop, value) def __setattr__(self, prop, value): """ Custom __setattr__ that handles dynamic subplot properties """ # Check for subplot assignment # ---------------------------- match = self._subplot_re_match(prop) if match is None: # Set as ordinary property super(BaseLayoutHierarchyType, self).__setattr__(prop, value) else: # Set as subplotid property self._set_subplotid_prop(prop, value) def __dir__(self): """ Custom __dir__ that handles dynamic subplot properties """ # Include any active subplot values if six.PY3: return list(super(BaseLayoutHierarchyType, self).__dir__()) + sorted( self._subplotid_props ) else: def get_attrs(obj): import types if not hasattr(obj, "__dict__"): return [] if not isinstance(obj.__dict__, (dict, types.DictProxyType)): raise TypeError("%s.__dict__ is not a dictionary" "" % obj.__name__) return obj.__dict__.keys() def dir2(obj): attrs = set() if not hasattr(obj, "__bases__"): # obj is an instance if not hasattr(obj, "__class__"): # slots return sorted(get_attrs(obj)) klass = obj.__class__ attrs.update(get_attrs(klass)) else: # obj is a class klass = obj for cls in klass.__bases__: attrs.update(get_attrs(cls)) attrs.update(dir2(cls)) attrs.update(get_attrs(obj)) return list(attrs) return dir2(self) + sorted(self._subplotid_props) class BaseTraceHierarchyType(BasePlotlyType): """ Base class for all types in the trace hierarchy """ def __init__(self, plotly_name, **kwargs): super(BaseTraceHierarchyType, self).__init__(plotly_name, **kwargs) def _send_prop_set(self, prop_path_str, val): if self.parent: # ### Inform parent of restyle operation ### self.parent._restyle_child(self, prop_path_str, val) class BaseTraceType(BaseTraceHierarchyType): """ Base class for the all trace types. Specific trace type classes (Scatter, Bar, etc.) are code generated as subclasses of this class. """ def __init__(self, plotly_name, **kwargs): super(BaseTraceHierarchyType, self).__init__(plotly_name, **kwargs) # Initialize callback function lists # ---------------------------------- # ### Callbacks to be called on hover ### self._hover_callbacks = [] # ### Callbacks to be called on unhover ### self._unhover_callbacks = [] # ### Callbacks to be called on click ### self._click_callbacks = [] # ### Callbacks to be called on selection ### self._select_callbacks = [] # ### Callbacks to be called on deselect ### self._deselect_callbacks = [] # ### Trace index in figure ### self._trace_ind = None # uid # --- # All trace types must have a top-level UID @property def uid(self): raise NotImplementedError @uid.setter def uid(self, val): raise NotImplementedError # Hover # ----- def on_hover(self, callback, append=False): """ Register function to be called when the user hovers over one or more points in this trace Note: Callbacks will only be triggered when the trace belongs to a instance of plotly.graph_objs.FigureWidget and it is displayed in an ipywidget context. Callbacks will not be triggered on figures that are displayed using plot/iplot. Parameters ---------- callback Callable function that accepts 3 arguments - this trace - plotly.callbacks.Points object - plotly.callbacks.InputDeviceState object append : bool If False (the default), this callback replaces any previously defined on_hover callbacks for this trace. If True, this callback is appended to the list of any previously defined callbacks. Returns ------- None Examples -------- >>> import plotly.graph_objects as go >>> from plotly.callbacks import Points, InputDeviceState >>> points, state = Points(), InputDeviceState() >>> def hover_fn(trace, points, state): ... inds = points.point_inds ... # Do something >>> trace = go.Scatter(x=[1, 2], y=[3, 0]) >>> trace.on_hover(hover_fn) Note: The creation of the `points` and `state` objects is optional, it's simply a convenience to help the text editor perform completion on the arguments inside `hover_fn` """ if not append: del self._hover_callbacks[:] if callback: self._hover_callbacks.append(callback) def _dispatch_on_hover(self, points, state): """ Dispatch points and device state all all hover callbacks """ for callback in self._hover_callbacks: callback(self, points, state) # Unhover # ------- def on_unhover(self, callback, append=False): """ Register function to be called when the user unhovers away from one or more points in this trace. Note: Callbacks will only be triggered when the trace belongs to a instance of plotly.graph_objs.FigureWidget and it is displayed in an ipywidget context. Callbacks will not be triggered on figures that are displayed using plot/iplot. Parameters ---------- callback Callable function that accepts 3 arguments - this trace - plotly.callbacks.Points object - plotly.callbacks.InputDeviceState object append : bool If False (the default), this callback replaces any previously defined on_unhover callbacks for this trace. If True, this callback is appended to the list of any previously defined callbacks. Returns ------- None Examples -------- >>> import plotly.graph_objects as go >>> from plotly.callbacks import Points, InputDeviceState >>> points, state = Points(), InputDeviceState() >>> def unhover_fn(trace, points, state): ... inds = points.point_inds ... # Do something >>> trace = go.Scatter(x=[1, 2], y=[3, 0]) >>> trace.on_unhover(unhover_fn) Note: The creation of the `points` and `state` objects is optional, it's simply a convenience to help the text editor perform completion on the arguments inside `unhover_fn` """ if not append: del self._unhover_callbacks[:] if callback: self._unhover_callbacks.append(callback) def _dispatch_on_unhover(self, points, state): """ Dispatch points and device state all all hover callbacks """ for callback in self._unhover_callbacks: callback(self, points, state) # Click # ----- def on_click(self, callback, append=False): """ Register function to be called when the user clicks on one or more points in this trace. Note: Callbacks will only be triggered when the trace belongs to a instance of plotly.graph_objs.FigureWidget and it is displayed in an ipywidget context. Callbacks will not be triggered on figures that are displayed using plot/iplot. Parameters ---------- callback Callable function that accepts 3 arguments - this trace - plotly.callbacks.Points object - plotly.callbacks.InputDeviceState object append : bool If False (the default), this callback replaces any previously defined on_click callbacks for this trace. If True, this callback is appended to the list of any previously defined callbacks. Returns ------- None Examples -------- >>> import plotly.graph_objects as go >>> from plotly.callbacks import Points, InputDeviceState >>> points, state = Points(), InputDeviceState() >>> def click_fn(trace, points, state): ... inds = points.point_inds ... # Do something >>> trace = go.Scatter(x=[1, 2], y=[3, 0]) >>> trace.on_click(click_fn) Note: The creation of the `points` and `state` objects is optional, it's simply a convenience to help the text editor perform completion on the arguments inside `click_fn` """ if not append: del self._click_callbacks[:] if callback: self._click_callbacks.append(callback) def _dispatch_on_click(self, points, state): """ Dispatch points and device state all all hover callbacks """ for callback in self._click_callbacks: callback(self, points, state) # Select # ------ def on_selection(self, callback, append=False): """ Register function to be called when the user selects one or more points in this trace. Note: Callbacks will only be triggered when the trace belongs to a instance of plotly.graph_objs.FigureWidget and it is displayed in an ipywidget context. Callbacks will not be triggered on figures that are displayed using plot/iplot. Parameters ---------- callback Callable function that accepts 4 arguments - this trace - plotly.callbacks.Points object - plotly.callbacks.BoxSelector or plotly.callbacks.LassoSelector append : bool If False (the default), this callback replaces any previously defined on_selection callbacks for this trace. If True, this callback is appended to the list of any previously defined callbacks. Returns ------- None Examples -------- >>> import plotly.graph_objects as go >>> from plotly.callbacks import Points >>> points = Points() >>> def selection_fn(trace, points, selector): ... inds = points.point_inds ... # Do something >>> trace = go.Scatter(x=[1, 2], y=[3, 0]) >>> trace.on_selection(selection_fn) Note: The creation of the `points` object is optional, it's simply a convenience to help the text editor perform completion on the `points` arguments inside `selection_fn` """ if not append: del self._select_callbacks[:] if callback: self._select_callbacks.append(callback) def _dispatch_on_selection(self, points, selector): """ Dispatch points and selector info to selection callbacks """ if "selectedpoints" in self: # Update the selectedpoints property, which will notify all views # of the selection change. This is a special case because no # restyle event is emitted by plotly.js on selection events # even though these events update the selectedpoints property. self.selectedpoints = points.point_inds for callback in self._select_callbacks: callback(self, points, selector) # deselect # -------- def on_deselect(self, callback, append=False): """ Register function to be called when the user deselects points in this trace using doubleclick. Note: Callbacks will only be triggered when the trace belongs to a instance of plotly.graph_objs.FigureWidget and it is displayed in an ipywidget context. Callbacks will not be triggered on figures that are displayed using plot/iplot. Parameters ---------- callback Callable function that accepts 3 arguments - this trace - plotly.callbacks.Points object append : bool If False (the default), this callback replaces any previously defined on_deselect callbacks for this trace. If True, this callback is appended to the list of any previously defined callbacks. Returns ------- None Examples -------- >>> import plotly.graph_objects as go >>> from plotly.callbacks import Points >>> points = Points() >>> def deselect_fn(trace, points): ... inds = points.point_inds ... # Do something >>> trace = go.Scatter(x=[1, 2], y=[3, 0]) >>> trace.on_deselect(deselect_fn) Note: The creation of the `points` object is optional, it's simply a convenience to help the text editor perform completion on the `points` arguments inside `selection_fn` """ if not append: del self._deselect_callbacks[:] if callback: self._deselect_callbacks.append(callback) def _dispatch_on_deselect(self, points): """ Dispatch points info to deselection callbacks """ if "selectedpoints" in self: # Update the selectedpoints property, which will notify all views # of the selection change. This is a special case because no # restyle event is emitted by plotly.js on selection events # even though these events update the selectedpoints property. self.selectedpoints = None for callback in self._deselect_callbacks: callback(self, points) class BaseFrameHierarchyType(BasePlotlyType): """ Base class for all types in the trace hierarchy """ def __init__(self, plotly_name, **kwargs): super(BaseFrameHierarchyType, self).__init__(plotly_name, **kwargs) def _send_prop_set(self, prop_path_str, val): # Note: Frames are not supported by FigureWidget, and updates are not # propagated to parents pass def _restyle_child(self, child, key_path_str, val): # Note: Frames are not supported by FigureWidget, and updates are not # propagated to parents pass def on_change(self, callback, *args): raise NotImplementedError("Change callbacks are not supported on Frames") def _get_child_props(self, child): """ Return the properties dict for a child trace or child layout Note: this method must match the name/signature of one on BasePlotlyType Parameters ---------- child : BaseTraceType | BaseLayoutType Returns ------- dict """ # Try to find index of child as a trace # ------------------------------------- try: trace_index = BaseFigure._index_is(self.data, child) except ValueError as _: trace_index = None # Child is a trace # ---------------- if trace_index is not None: if "data" in self._props: return self._props["data"][trace_index] else: return None # Child is the layout # ------------------- elif child is self.layout: return self._props.get("layout", None) # Unknown child # ------------- else: raise ValueError("Unrecognized child: %s" % child) plotly-4.4.1+dfsg.orig/plotly/utils.py0000644000175000017500000001401013573717677017331 0ustar noahfxnoahfxfrom __future__ import absolute_import, division import textwrap from pprint import PrettyPrinter from _plotly_utils.utils import * # Pretty printing def _list_repr_elided(v, threshold=200, edgeitems=3, indent=0, width=80): """ Return a string representation for of a list where list is elided if it has more than n elements Parameters ---------- v : list Input list threshold : Maximum number of elements to display Returns ------- str """ if isinstance(v, list): open_char, close_char = "[", "]" elif isinstance(v, tuple): open_char, close_char = "(", ")" else: raise ValueError("Invalid value of type: %s" % type(v)) if len(v) <= threshold: disp_v = v else: disp_v = list(v[:edgeitems]) + ["..."] + list(v[-edgeitems:]) v_str = open_char + ", ".join([str(e) for e in disp_v]) + close_char v_wrapped = "\n".join( textwrap.wrap( v_str, width=width, initial_indent=" " * (indent + 1), subsequent_indent=" " * (indent + 1), ) ).strip() return v_wrapped class ElidedWrapper(object): """ Helper class that wraps values of certain types and produces a custom __repr__() that may be elided and is suitable for use during pretty printing """ def __init__(self, v, threshold, indent): self.v = v self.indent = indent self.threshold = threshold @staticmethod def is_wrappable(v): numpy = get_module("numpy") if isinstance(v, (list, tuple)) and len(v) > 0 and not isinstance(v[0], dict): return True elif numpy and isinstance(v, numpy.ndarray): return True elif isinstance(v, str): return True else: return False def __repr__(self): numpy = get_module("numpy") if isinstance(self.v, (list, tuple)): # Handle lists/tuples res = _list_repr_elided( self.v, threshold=self.threshold, indent=self.indent ) return res elif numpy and isinstance(self.v, numpy.ndarray): # Handle numpy arrays # Get original print opts orig_opts = numpy.get_printoptions() # Set threshold to self.max_list_elements numpy.set_printoptions( **dict(orig_opts, threshold=self.threshold, edgeitems=3, linewidth=80) ) res = self.v.__repr__() # Add indent to all but the first line res_lines = res.split("\n") res = ("\n" + " " * self.indent).join(res_lines) # Restore print opts numpy.set_printoptions(**orig_opts) return res elif isinstance(self.v, str): # Handle strings if len(self.v) > 80: return "(" + repr(self.v[:30]) + " ... " + repr(self.v[-30:]) + ")" else: return self.v.__repr__() else: return self.v.__repr__() class ElidedPrettyPrinter(PrettyPrinter): """ PrettyPrinter subclass that elides long lists/arrays/strings """ def __init__(self, *args, **kwargs): self.threshold = kwargs.pop("threshold", 200) PrettyPrinter.__init__(self, *args, **kwargs) def _format(self, val, stream, indent, allowance, context, level): if ElidedWrapper.is_wrappable(val): elided_val = ElidedWrapper(val, self.threshold, indent) return self._format(elided_val, stream, indent, allowance, context, level) else: return PrettyPrinter._format( self, val, stream, indent, allowance, context, level ) def node_generator(node, path=()): """ General, node-yielding generator. Yields (node, path) tuples when it finds values that are dict instances. A path is a sequence of hashable values that can be used as either keys to a mapping (dict) or indices to a sequence (list). A path is always wrt to some object. Given an object, a path explains how to get from the top level of that object to a nested value in the object. :param (dict) node: Part of a dict to be traversed. :param (tuple[str]) path: Defines the path of the current node. :return: (Generator) Example: >>> for node, path in node_generator({'a': {'b': 5}}): ... print(node, path) {'a': {'b': 5}} () {'b': 5} ('a',) """ if not isinstance(node, dict): return # in case it's called with a non-dict node at top level yield node, path for key, val in node.items(): if isinstance(val, dict): for item in node_generator(val, path + (key,)): yield item def get_by_path(obj, path): """ Iteratively get on obj for each key in path. :param (list|dict) obj: The top-level object. :param (tuple[str]|tuple[int]) path: Keys to access parts of obj. :return: (*) Example: >>> figure = {'data': [{'x': [5]}]} >>> path = ('data', 0, 'x') >>> get_by_path(figure, path) [5] """ for key in path: obj = obj[key] return obj def decode_unicode(coll): if isinstance(coll, list): for no, entry in enumerate(coll): if isinstance(entry, (dict, list)): coll[no] = decode_unicode(entry) else: if isinstance(entry, str): try: coll[no] = str(entry) except UnicodeEncodeError: pass elif isinstance(coll, dict): keys, vals = list(coll.keys()), list(coll.values()) for key, val in zip(keys, vals): if isinstance(val, (dict, list)): coll[key] = decode_unicode(val) elif isinstance(val, str): try: coll[key] = str(val) except UnicodeEncodeError: pass coll[str(key)] = coll.pop(key) return coll plotly-4.4.1+dfsg.orig/plotly/basewidget.py0000644000175000017500000010303313547055022020267 0ustar noahfxnoahfximport uuid from importlib import import_module import os import numbers try: from urllib import parse except ImportError: from urlparse import urlparse as parse import ipywidgets as widgets from traitlets import List, Unicode, Dict, observe, Integer from .basedatatypes import BaseFigure, BasePlotlyType from .callbacks import BoxSelector, LassoSelector, InputDeviceState, Points from .serializers import custom_serializers from .version import __frontend_version__ @widgets.register class BaseFigureWidget(BaseFigure, widgets.DOMWidget): """ Base class for FigureWidget. The FigureWidget class is code-generated as a subclass """ # Widget Traits # ------------- # Widget traitlets are automatically synchronized with the FigureModel # JavaScript object _view_name = Unicode("FigureView").tag(sync=True) _view_module = Unicode("plotlywidget").tag(sync=True) _view_module_version = Unicode(__frontend_version__).tag(sync=True) _model_name = Unicode("FigureModel").tag(sync=True) _model_module = Unicode("plotlywidget").tag(sync=True) _model_module_version = Unicode(__frontend_version__).tag(sync=True) # ### _data and _layout ### # These properties store the current state of the traces and # layout as JSON-style dicts. These dicts do not store any subclasses of # `BasePlotlyType` # # Note: These are only automatically synced with the frontend on full # assignment, not on mutation. We use this fact to only directly sync # them to the front-end on FigureWidget construction. All other updates # are made using mutation, and they are manually synced to the frontend # using the relayout/restyle/update/etc. messages. _layout = Dict().tag(sync=True, **custom_serializers) _data = List().tag(sync=True, **custom_serializers) _config = Dict().tag(sync=True, **custom_serializers) # ### Python -> JS message properties ### # These properties are used to send messages from Python to the # frontend. Messages are sent by assigning the message contents to the # appropriate _py2js_* property and then immediatly assigning None to the # property. # # See JSDoc comments in the FigureModel class in js/src/Figure.js for # detailed descriptions of the messages. _py2js_addTraces = Dict(allow_none=True).tag(sync=True, **custom_serializers) _py2js_restyle = Dict(allow_none=True).tag(sync=True, **custom_serializers) _py2js_relayout = Dict(allow_none=True).tag(sync=True, **custom_serializers) _py2js_update = Dict(allow_none=True).tag(sync=True, **custom_serializers) _py2js_animate = Dict(allow_none=True).tag(sync=True, **custom_serializers) _py2js_deleteTraces = Dict(allow_none=True).tag(sync=True, **custom_serializers) _py2js_moveTraces = Dict(allow_none=True).tag(sync=True, **custom_serializers) _py2js_removeLayoutProps = Dict(allow_none=True).tag( sync=True, **custom_serializers ) _py2js_removeTraceProps = Dict(allow_none=True).tag(sync=True, **custom_serializers) # ### JS -> Python message properties ### # These properties are used to receive messages from the frontend. # Messages are received by defining methods that observe changes to these # properties. Receive methods are named `_handler_js2py_*` where '*' is # the name of the corresponding message property. Receive methods are # responsible for setting the message property to None after retreiving # the message data. # # See JSDoc comments in the FigureModel class in js/src/Figure.js for # detailed descriptions of the messages. _js2py_traceDeltas = Dict(allow_none=True).tag(sync=True, **custom_serializers) _js2py_layoutDelta = Dict(allow_none=True).tag(sync=True, **custom_serializers) _js2py_restyle = Dict(allow_none=True).tag(sync=True, **custom_serializers) _js2py_relayout = Dict(allow_none=True).tag(sync=True, **custom_serializers) _js2py_update = Dict(allow_none=True).tag(sync=True, **custom_serializers) _js2py_pointsCallback = Dict(allow_none=True).tag(sync=True, **custom_serializers) # ### Message tracking properties ### # The _last_layout_edit_id and _last_trace_edit_id properties are used # to keep track of the edit id of the message that most recently # requested an update to the Figures layout or traces respectively. # # We track this information because we don't want to update the Figure's # default layout/trace properties (_layout_defaults, _data_defaults) # while edits are in process. This can lead to inconsistent property # states. _last_layout_edit_id = Integer(0).tag(sync=True) _last_trace_edit_id = Integer(0).tag(sync=True) _set_trace_uid = True # Constructor # ----------- def __init__( self, data=None, layout=None, frames=None, skip_invalid=False, **kwargs ): # Call superclass constructors # ---------------------------- # Note: We rename layout to layout_plotly because to deconflict it # with the `layout` constructor parameter of the `widgets.DOMWidget` # ipywidgets class super(BaseFigureWidget, self).__init__( data=data, layout_plotly=layout, frames=frames, skip_invalid=skip_invalid, **kwargs ) # Validate Frames # --------------- # Frames are not supported by figure widget if self._frame_objs: BaseFigureWidget._display_frames_error() # Message States # -------------- # ### Layout ### # _last_layout_edit_id is described above self._last_layout_edit_id = 0 # _layout_edit_in_process is set to True if there are layout edit # operations that have been sent to the frontend that haven't # completed yet. self._layout_edit_in_process = False # _waiting_edit_callbacks is a list of callback functions that # should be executed as soon as all pending edit operations are # completed self._waiting_edit_callbacks = [] # ### Trace ### # _last_trace_edit_id: described above self._last_trace_edit_id = 0 # _trace_edit_in_process is set to True if there are trace edit # operations that have been sent to the frontend that haven't # completed yet. self._trace_edit_in_process = False # View count # ---------- # ipywidget property that stores the number of active frontend # views of this widget self._view_count = 0 # Python -> JavaScript Messages # ----------------------------- def _send_relayout_msg(self, layout_data, source_view_id=None): """ Send Plotly.relayout message to the frontend Parameters ---------- layout_data : dict Plotly.relayout layout data source_view_id : str UID of view that triggered this relayout operation (e.g. By the user clicking 'zoom' in the toolbar). None if the operation was not triggered by a frontend view """ # Increment layout edit messages IDs # ---------------------------------- layout_edit_id = self._last_layout_edit_id + 1 self._last_layout_edit_id = layout_edit_id self._layout_edit_in_process = True # Build message # ------------- msg_data = { "relayout_data": layout_data, "layout_edit_id": layout_edit_id, "source_view_id": source_view_id, } # Send message # ------------ self._py2js_relayout = msg_data self._py2js_relayout = None def _send_restyle_msg(self, restyle_data, trace_indexes=None, source_view_id=None): """ Send Plotly.restyle message to the frontend Parameters ---------- restyle_data : dict Plotly.restyle restyle data trace_indexes : list[int] List of trace indexes that the restyle operation applies to source_view_id : str UID of view that triggered this restyle operation (e.g. By the user clicking the legend to hide a trace). None if the operation was not triggered by a frontend view """ # Validate / normalize inputs # --------------------------- trace_indexes = self._normalize_trace_indexes(trace_indexes) # Increment layout/trace edit message IDs # --------------------------------------- layout_edit_id = self._last_layout_edit_id + 1 self._last_layout_edit_id = layout_edit_id self._layout_edit_in_process = True trace_edit_id = self._last_trace_edit_id + 1 self._last_trace_edit_id = trace_edit_id self._trace_edit_in_process = True # Build message # ------------- restyle_msg = { "restyle_data": restyle_data, "restyle_traces": trace_indexes, "trace_edit_id": trace_edit_id, "layout_edit_id": layout_edit_id, "source_view_id": source_view_id, } # Send message # ------------ self._py2js_restyle = restyle_msg self._py2js_restyle = None def _send_addTraces_msg(self, new_traces_data): """ Send Plotly.addTraces message to the frontend Parameters ---------- new_traces_data : list[dict] List of trace data for new traces as accepted by Plotly.addTraces """ # Increment layout/trace edit message IDs # --------------------------------------- layout_edit_id = self._last_layout_edit_id + 1 self._last_layout_edit_id = layout_edit_id self._layout_edit_in_process = True trace_edit_id = self._last_trace_edit_id + 1 self._last_trace_edit_id = trace_edit_id self._trace_edit_in_process = True # Build message # ------------- add_traces_msg = { "trace_data": new_traces_data, "trace_edit_id": trace_edit_id, "layout_edit_id": layout_edit_id, } # Send message # ------------ self._py2js_addTraces = add_traces_msg self._py2js_addTraces = None def _send_moveTraces_msg(self, current_inds, new_inds): """ Send Plotly.moveTraces message to the frontend Parameters ---------- current_inds : list[int] List of current trace indexes new_inds : list[int] List of new trace indexes """ # Build message # ------------- move_msg = {"current_trace_inds": current_inds, "new_trace_inds": new_inds} # Send message # ------------ self._py2js_moveTraces = move_msg self._py2js_moveTraces = None def _send_update_msg( self, restyle_data, relayout_data, trace_indexes=None, source_view_id=None ): """ Send Plotly.update message to the frontend Parameters ---------- restyle_data : dict Plotly.update restyle data relayout_data : dict Plotly.update relayout data trace_indexes : list[int] List of trace indexes that the update operation applies to source_view_id : str UID of view that triggered this update operation (e.g. By the user clicking a button). None if the operation was not triggered by a frontend view """ # Validate / normalize inputs # --------------------------- trace_indexes = self._normalize_trace_indexes(trace_indexes) # Increment layout/trace edit message IDs # --------------------------------------- trace_edit_id = self._last_trace_edit_id + 1 self._last_trace_edit_id = trace_edit_id self._trace_edit_in_process = True layout_edit_id = self._last_layout_edit_id + 1 self._last_layout_edit_id = layout_edit_id self._layout_edit_in_process = True # Build message # ------------- update_msg = { "style_data": restyle_data, "layout_data": relayout_data, "style_traces": trace_indexes, "trace_edit_id": trace_edit_id, "layout_edit_id": layout_edit_id, "source_view_id": source_view_id, } # Send message # ------------ self._py2js_update = update_msg self._py2js_update = None def _send_animate_msg( self, styles_data, relayout_data, trace_indexes, animation_opts ): """ Send Plotly.update message to the frontend Note: there is no source_view_id parameter because animations triggered by the fontend are not currently supported Parameters ---------- styles_data : list[dict] Plotly.animate styles data relayout_data : dict Plotly.animate relayout data trace_indexes : list[int] List of trace indexes that the animate operation applies to """ # Validate / normalize inputs # --------------------------- trace_indexes = self._normalize_trace_indexes(trace_indexes) # Increment layout/trace edit message IDs # --------------------------------------- trace_edit_id = self._last_trace_edit_id + 1 self._last_trace_edit_id = trace_edit_id self._trace_edit_in_process = True layout_edit_id = self._last_layout_edit_id + 1 self._last_layout_edit_id = layout_edit_id self._layout_edit_in_process = True # Build message # ------------- animate_msg = { "style_data": styles_data, "layout_data": relayout_data, "style_traces": trace_indexes, "animation_opts": animation_opts, "trace_edit_id": trace_edit_id, "layout_edit_id": layout_edit_id, "source_view_id": None, } # Send message # ------------ self._py2js_animate = animate_msg self._py2js_animate = None def _send_deleteTraces_msg(self, delete_inds): """ Send Plotly.deleteTraces message to the frontend Parameters ---------- delete_inds : list[int] List of trace indexes of traces to delete """ # Increment layout/trace edit message IDs # --------------------------------------- trace_edit_id = self._last_trace_edit_id + 1 self._last_trace_edit_id = trace_edit_id self._trace_edit_in_process = True layout_edit_id = self._last_layout_edit_id + 1 self._last_layout_edit_id = layout_edit_id self._layout_edit_in_process = True # Build message # ------------- delete_msg = { "delete_inds": delete_inds, "layout_edit_id": layout_edit_id, "trace_edit_id": trace_edit_id, } # Send message # ------------ self._py2js_deleteTraces = delete_msg self._py2js_deleteTraces = None # JavaScript -> Python Messages # ----------------------------- @observe("_js2py_traceDeltas") def _handler_js2py_traceDeltas(self, change): """ Process trace deltas message from the frontend """ # Receive message # --------------- msg_data = change["new"] if not msg_data: self._js2py_traceDeltas = None return trace_deltas = msg_data["trace_deltas"] trace_edit_id = msg_data["trace_edit_id"] # Apply deltas # ------------ # We only apply the deltas if this message corresponds to the most # recent trace edit operation if trace_edit_id == self._last_trace_edit_id: # ### Loop over deltas ### for delta in trace_deltas: # #### Find existing trace for uid ### trace_uid = delta["uid"] trace_uids = [trace.uid for trace in self.data] trace_index = trace_uids.index(trace_uid) uid_trace = self.data[trace_index] # #### Transform defaults to delta #### delta_transform = BaseFigureWidget._transform_data( uid_trace._prop_defaults, delta ) # #### Remove overlapping properties #### # If a property is present in both _props and _prop_defaults # then we remove the copy from _props remove_props = self._remove_overlapping_props( uid_trace._props, uid_trace._prop_defaults ) # #### Notify frontend model of property removal #### if remove_props: remove_trace_props_msg = { "remove_trace": trace_index, "remove_props": remove_props, } self._py2js_removeTraceProps = remove_trace_props_msg self._py2js_removeTraceProps = None # #### Dispatch change callbacks #### self._dispatch_trace_change_callbacks(delta_transform, [trace_index]) # ### Trace edits no longer in process ### self._trace_edit_in_process = False # ### Call any waiting trace edit callbacks ### if not self._layout_edit_in_process: while self._waiting_edit_callbacks: self._waiting_edit_callbacks.pop()() self._js2py_traceDeltas = None @observe("_js2py_layoutDelta") def _handler_js2py_layoutDelta(self, change): """ Process layout delta message from the frontend """ # Receive message # --------------- msg_data = change["new"] if not msg_data: self._js2py_layoutDelta = None return layout_delta = msg_data["layout_delta"] layout_edit_id = msg_data["layout_edit_id"] # Apply delta # ----------- # We only apply the delta if this message corresponds to the most # recent layout edit operation if layout_edit_id == self._last_layout_edit_id: # ### Transform defaults to delta ### delta_transform = BaseFigureWidget._transform_data( self._layout_defaults, layout_delta ) # ### Remove overlapping properties ### # If a property is present in both _layout and _layout_defaults # then we remove the copy from _layout removed_props = self._remove_overlapping_props( self._layout, self._layout_defaults ) # ### Notify frontend model of property removal ### if removed_props: remove_props_msg = {"remove_props": removed_props} self._py2js_removeLayoutProps = remove_props_msg self._py2js_removeLayoutProps = None # ### Create axis objects ### # For example, when a SPLOM trace is created the layout defaults # may include axes that weren't explicitly defined by the user. for proppath in delta_transform: prop = proppath[0] match = self.layout._subplot_re_match(prop) if match and prop not in self.layout: # We need to create a subplotid object self.layout[prop] = {} # ### Dispatch change callbacks ### self._dispatch_layout_change_callbacks(delta_transform) # ### Layout edits no longer in process ### self._layout_edit_in_process = False # ### Call any waiting layout edit callbacks ### if not self._trace_edit_in_process: while self._waiting_edit_callbacks: self._waiting_edit_callbacks.pop()() self._js2py_layoutDelta = None @observe("_js2py_restyle") def _handler_js2py_restyle(self, change): """ Process Plotly.restyle message from the frontend """ # Receive message # --------------- restyle_msg = change["new"] if not restyle_msg: self._js2py_restyle = None return style_data = restyle_msg["style_data"] style_traces = restyle_msg["style_traces"] source_view_id = restyle_msg["source_view_id"] # Perform restyle # --------------- self.plotly_restyle( restyle_data=style_data, trace_indexes=style_traces, source_view_id=source_view_id, ) self._js2py_restyle = None @observe("_js2py_update") def _handler_js2py_update(self, change): """ Process Plotly.update message from the frontend """ # Receive message # --------------- update_msg = change["new"] if not update_msg: self._js2py_update = None return style = update_msg["style_data"] trace_indexes = update_msg["style_traces"] layout = update_msg["layout_data"] source_view_id = update_msg["source_view_id"] # Perform update # -------------- self.plotly_update( restyle_data=style, relayout_data=layout, trace_indexes=trace_indexes, source_view_id=source_view_id, ) self._js2py_update = None @observe("_js2py_relayout") def _handler_js2py_relayout(self, change): """ Process Plotly.relayout message from the frontend """ # Receive message # --------------- relayout_msg = change["new"] if not relayout_msg: self._js2py_relayout = None return relayout_data = relayout_msg["relayout_data"] source_view_id = relayout_msg["source_view_id"] if "lastInputTime" in relayout_data: # Remove 'lastInputTime'. Seems to be an internal plotly # property that is introduced for some plot types, but it is not # actually a property in the schema relayout_data.pop("lastInputTime") # Perform relayout # ---------------- self.plotly_relayout(relayout_data=relayout_data, source_view_id=source_view_id) self._js2py_relayout = None @observe("_js2py_pointsCallback") def _handler_js2py_pointsCallback(self, change): """ Process points callback message from the frontend """ # Receive message # --------------- callback_data = change["new"] if not callback_data: self._js2py_pointsCallback = None return # Get event type # -------------- event_type = callback_data["event_type"] # Build Selector Object # --------------------- if callback_data.get("selector", None): selector_data = callback_data["selector"] selector_type = selector_data["type"] selector_state = selector_data["selector_state"] if selector_type == "box": selector = BoxSelector(**selector_state) elif selector_type == "lasso": selector = LassoSelector(**selector_state) else: raise ValueError("Unsupported selector type: %s" % selector_type) else: selector = None # Build Input Device State Object # ------------------------------- if callback_data.get("device_state", None): device_state_data = callback_data["device_state"] state = InputDeviceState(**device_state_data) else: state = None # Build Trace Points Dictionary # ----------------------------- points_data = callback_data["points"] trace_points = { trace_ind: { "point_inds": [], "xs": [], "ys": [], "trace_name": self._data_objs[trace_ind].name, "trace_index": trace_ind, } for trace_ind in range(len(self._data_objs)) } for x, y, point_ind, trace_ind in zip( points_data["xs"], points_data["ys"], points_data["point_indexes"], points_data["trace_indexes"], ): trace_dict = trace_points[trace_ind] trace_dict["xs"].append(x) trace_dict["ys"].append(y) trace_dict["point_inds"].append(point_ind) # Dispatch callbacks # ------------------ for trace_ind, trace_points_data in trace_points.items(): points = Points(**trace_points_data) trace = self.data[trace_ind] if event_type == "plotly_click": trace._dispatch_on_click(points, state) elif event_type == "plotly_hover": trace._dispatch_on_hover(points, state) elif event_type == "plotly_unhover": trace._dispatch_on_unhover(points, state) elif event_type == "plotly_selected": trace._dispatch_on_selection(points, selector) elif event_type == "plotly_deselect": trace._dispatch_on_deselect(points) self._js2py_pointsCallback = None # Display # ------- def _ipython_display_(self): """ Handle rich display of figures in ipython contexts """ # Override BaseFigure's display to make sure we display the widget version widgets.DOMWidget._ipython_display_(self) # Callbacks # --------- def on_edits_completed(self, fn): """ Register a function to be called after all pending trace and layout edit operations have completed If there are no pending edit operations then function is called immediately Parameters ---------- fn : callable Function of zero arguments to be called when all pending edit operations have completed """ if self._layout_edit_in_process or self._trace_edit_in_process: self._waiting_edit_callbacks.append(fn) else: fn() # Validate No Frames # ------------------ @property def frames(self): # Note: This property getter is identical to that of the superclass, # but it must be included here because we're overriding the setter # below. return self._frame_objs @frames.setter def frames(self, new_frames): if new_frames: BaseFigureWidget._display_frames_error() @staticmethod def _display_frames_error(): """ Display an informative error when user attempts to set frames on a FigureWidget Raises ------ ValueError always """ msg = """ Frames are not supported by the plotly.graph_objs.FigureWidget class. Note: Frames are supported by the plotly.graph_objs.Figure class""" raise ValueError(msg) # Static Helpers # -------------- @staticmethod def _remove_overlapping_props(input_data, delta_data, prop_path=()): """ Remove properties in input_data that are also in delta_data, and do so recursively. Exception: Never remove 'uid' from input_data, this property is used to align traces Parameters ---------- input_data : dict|list delta_data : dict|list Returns ------- list[tuple[str|int]] List of removed property path tuples """ # Initialize removed # ------------------ # This is the list of path tuples to the properties that were # removed from input_data removed = [] # Handle dict # ----------- if isinstance(input_data, dict): assert isinstance(delta_data, dict) for p, delta_val in delta_data.items(): if isinstance(delta_val, dict) or BaseFigure._is_dict_list(delta_val): if p in input_data: # ### Recurse ### input_val = input_data[p] recur_prop_path = prop_path + (p,) recur_removed = BaseFigureWidget._remove_overlapping_props( input_val, delta_val, recur_prop_path ) removed.extend(recur_removed) # Check whether the last property in input_val # has been removed. If so, remove it entirely if not input_val: input_data.pop(p) removed.append(recur_prop_path) elif p in input_data and p != "uid": # ### Remove property ### input_data.pop(p) removed.append(prop_path + (p,)) # Handle list # ----------- elif isinstance(input_data, list): assert isinstance(delta_data, list) for i, delta_val in enumerate(delta_data): if i >= len(input_data): break input_val = input_data[i] if ( input_val is not None and isinstance(delta_val, dict) or BaseFigure._is_dict_list(delta_val) ): # ### Recurse ### recur_prop_path = prop_path + (i,) recur_removed = BaseFigureWidget._remove_overlapping_props( input_val, delta_val, recur_prop_path ) removed.extend(recur_removed) return removed @staticmethod def _transform_data(to_data, from_data, should_remove=True, relayout_path=()): """ Transform to_data into from_data and return relayout-style description of the transformation Parameters ---------- to_data : dict|list from_data : dict|list Returns ------- dict relayout-style description of the transformation """ # Initialize relayout data # ------------------------ relayout_data = {} # Handle dict # ----------- if isinstance(to_data, dict): # ### Validate from_data ### if not isinstance(from_data, dict): raise ValueError( "Mismatched data types: {to_dict} {from_data}".format( to_dict=to_data, from_data=from_data ) ) # ### Add/modify properties ### # Loop over props/vals for from_prop, from_val in from_data.items(): # #### Handle compound vals recursively #### if isinstance(from_val, dict) or BaseFigure._is_dict_list(from_val): # ##### Init property value if needed ##### if from_prop not in to_data: to_data[from_prop] = {} if isinstance(from_val, dict) else [] # ##### Transform property val recursively ##### input_val = to_data[from_prop] relayout_data.update( BaseFigureWidget._transform_data( input_val, from_val, should_remove=should_remove, relayout_path=relayout_path + (from_prop,), ) ) # #### Handle simple vals directly #### else: if from_prop not in to_data or not BasePlotlyType._vals_equal( to_data[from_prop], from_val ): to_data[from_prop] = from_val relayout_path_prop = relayout_path + (from_prop,) relayout_data[relayout_path_prop] = from_val # ### Remove properties ### if should_remove: for remove_prop in set(to_data.keys()).difference( set(from_data.keys()) ): to_data.pop(remove_prop) # Handle list # ----------- elif isinstance(to_data, list): # ### Validate from_data ### if not isinstance(from_data, list): raise ValueError( "Mismatched data types: to_data: {to_data} {from_data}".format( to_data=to_data, from_data=from_data ) ) # ### Add/modify properties ### # Loop over indexes / elements for i, from_val in enumerate(from_data): # #### Initialize element if needed #### if i >= len(to_data): to_data.append(None) input_val = to_data[i] # #### Handle compound element recursively #### if input_val is not None and ( isinstance(from_val, dict) or BaseFigure._is_dict_list(from_val) ): relayout_data.update( BaseFigureWidget._transform_data( input_val, from_val, should_remove=should_remove, relayout_path=relayout_path + (i,), ) ) # #### Handle simple elements directly #### else: if not BasePlotlyType._vals_equal(to_data[i], from_val): to_data[i] = from_val relayout_data[relayout_path + (i,)] = from_val return relayout_data plotly-4.4.1+dfsg.orig/plotly/colors.py0000644000175000017500000000013013525746125017453 0ustar noahfxnoahfxfrom __future__ import absolute_import from _plotly_utils.colors import * # noqa: F401 plotly-4.4.1+dfsg.orig/plotly/data/0000755000175000017500000000000013573746613016524 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/data/__init__.py0000644000175000017500000000434413525746125020635 0ustar noahfxnoahfx""" Built-in datasets for demonstration, educational and test purposes. """ def gapminder(): """ Each row represents a country on a given year. https://www.gapminder.org/data/ Returns: A `pandas.DataFrame` with 1704 rows and the following columns: `['country', 'continent', 'year', 'lifeExp', 'pop', 'gdpPercap', 'iso_alpha', 'iso_num']`. """ return _get_dataset("gapminder") def tips(): """ Each row represents a restaurant bill. https://vincentarelbundock.github.io/Rdatasets/doc/reshape2/tips.html Returns: A `pandas.DataFrame` with 244 rows and the following columns: `['total_bill', 'tip', 'sex', 'smoker', 'day', 'time', 'size']`. """ return _get_dataset("tips") def iris(): """ Each row represents a flower. https://en.wikipedia.org/wiki/Iris_flower_data_set Returns: A `pandas.DataFrame` with 150 rows and the following columns: `['sepal_length', 'sepal_width', 'petal_length', 'petal_width', 'species', 'species_id']`. """ return _get_dataset("iris") def wind(): """ Each row represents a level of wind intensity in a cardinal direction, and its frequency. Returns: A `pandas.DataFrame` with 128 rows and the following columns: `['direction', 'strength', 'frequency']`. """ return _get_dataset("wind") def election(): """ Each row represents voting results for an electoral district in the 2013 Montreal mayoral election. Returns: A `pandas.DataFrame` with 58 rows and the following columns: `['district', 'Coderre', 'Bergeron', 'Joly', 'total', 'winner', 'result']`. """ return _get_dataset("election") def carshare(): """ Each row represents the availability of car-sharing services near the centroid of a zone in Montreal. Returns: A `pandas.DataFrame` with 249 rows and the following columns: `['centroid_lat', 'centroid_lon', 'car_hours', 'peak_hour']`. """ return _get_dataset("carshare") def _get_dataset(d): import pandas import os return pandas.read_csv( os.path.join( os.path.dirname(os.path.dirname(__file__)), "package_data", "datasets", d + ".csv.gz", ) ) plotly-4.4.1+dfsg.orig/plotly/animation.py0000644000175000017500000000312013525746125020133 0ustar noahfxnoahfxfrom _plotly_utils.basevalidators import EnumeratedValidator, NumberValidator class EasingValidator(EnumeratedValidator): def __init__(self, plotly_name="easing", parent_name="batch_animate", **_): super(EasingValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, values=[ "linear", "quad", "cubic", "sin", "exp", "circle", "elastic", "back", "bounce", "linear-in", "quad-in", "cubic-in", "sin-in", "exp-in", "circle-in", "elastic-in", "back-in", "bounce-in", "linear-out", "quad-out", "cubic-out", "sin-out", "exp-out", "circle-out", "elastic-out", "back-out", "bounce-out", "linear-in-out", "quad-in-out", "cubic-in-out", "sin-in-out", "exp-in-out", "circle-in-out", "elastic-in-out", "back-in-out", "bounce-in-out", ], ) class DurationValidator(NumberValidator): def __init__(self, plotly_name="duration"): super(DurationValidator, self).__init__( plotly_name=plotly_name, parent_name="batch_animate", min=0 ) plotly-4.4.1+dfsg.orig/plotly/_docstring_gen.py0000644000175000017500000000166513525746125021154 0ustar noahfxnoahfxfrom __future__ import absolute_import import re as _re import plotly.io as pio from plotly.basedatatypes import BaseFigure import sys # Perform docstrings generation def copy_doc_without_fig(from_fn, to_method): """ Copy docstring from a plotly.io function to a Figure method, removing the fig argument docstring in the process """ docstr = _re.sub(r" {4}fig:(?:.*?\n)*? {4}(\w+)", r" \1", from_fn.__doc__) if sys.version_info[0] < 3: to_method.__func__.__doc__ = docstr else: to_method.__doc__ = docstr copy_doc_without_fig(pio.show, BaseFigure.show) copy_doc_without_fig(pio.to_json, BaseFigure.to_json) copy_doc_without_fig(pio.write_json, BaseFigure.write_json) copy_doc_without_fig(pio.to_html, BaseFigure.to_html) copy_doc_without_fig(pio.write_html, BaseFigure.write_html) copy_doc_without_fig(pio.to_image, BaseFigure.to_image) copy_doc_without_fig(pio.write_image, BaseFigure.write_image) plotly-4.4.1+dfsg.orig/plotly/serializers.py0000644000175000017500000000524313525746125020520 0ustar noahfxnoahfxfrom .basedatatypes import Undefined from .optional_imports import get_module np = get_module("numpy") def _py_to_js(v, widget_manager): """ Python -> Javascript ipywidget serializer This function must repalce all objects that the ipywidget library can't serialize natively (e.g. numpy arrays) with serializable representations Parameters ---------- v Object to be serialized widget_manager ipywidget widget_manager (unused) Returns ------- any Value that the ipywidget library can serialize natively """ # Handle dict recursively # ----------------------- if isinstance(v, dict): return {k: _py_to_js(v, widget_manager) for k, v in v.items()} # Handle list/tuple recursively # ----------------------------- elif isinstance(v, (list, tuple)): return [_py_to_js(v, widget_manager) for v in v] # Handle numpy array # ------------------ elif np is not None and isinstance(v, np.ndarray): # Convert 1D numpy arrays with numeric types to memoryviews with # datatype and shape metadata. if ( v.ndim == 1 and v.dtype.kind in ["u", "i", "f"] and v.dtype != "int64" and v.dtype != "uint64" ): # We have a numpy array the we can directly map to a JavaScript # Typed array return {"buffer": memoryview(v), "dtype": str(v.dtype), "shape": v.shape} else: # Convert all other numpy arrays to lists return v.tolist() # Handle Undefined # ---------------- if v is Undefined: return "_undefined_" # Handle simple value # ------------------- else: return v def _js_to_py(v, widget_manager): """ Javascript -> Python ipywidget deserializer Parameters ---------- v Object to be deserialized widget_manager ipywidget widget_manager (unused) Returns ------- any Deserialized object for use by the Python side of the library """ # Handle dict # ----------- if isinstance(v, dict): return {k: _js_to_py(v, widget_manager) for k, v in v.items()} # Handle list/tuple # ----------------- elif isinstance(v, (list, tuple)): return [_js_to_py(v, widget_manager) for v in v] # Handle Undefined # ---------------- elif isinstance(v, str) and v == "_undefined_": return Undefined # Handle simple value # ------------------- else: return v # Custom serializer dict for use in ipywidget traitlet definitions custom_serializers = {"from_json": _js_to_py, "to_json": _py_to_js} plotly-4.4.1+dfsg.orig/plotly/presentation_objs.py0000644000175000017500000000020113525746125021701 0ustar noahfxnoahfxfrom __future__ import absolute_import from _plotly_future_ import _chart_studio_error _chart_studio_error("presentation_objs") plotly-4.4.1+dfsg.orig/plotly/files.py0000644000175000017500000000011113525746125017253 0ustar noahfxnoahfxfrom __future__ import absolute_import from _plotly_utils.files import * plotly-4.4.1+dfsg.orig/plotly/express/0000755000175000017500000000000013573746613017304 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/express/data.py0000644000175000017500000000010113525746125020552 0ustar noahfxnoahfxfrom __future__ import absolute_import from plotly.data import * plotly-4.4.1+dfsg.orig/plotly/express/_core.py0000644000175000017500000015524713573717702020760 0ustar noahfxnoahfximport plotly.graph_objs as go import plotly.io as pio from collections import namedtuple, OrderedDict from _plotly_utils.basevalidators import ColorscaleValidator from .colors import qualitative, sequential import math import pandas as pd import numpy as np from plotly.subplots import ( make_subplots, _set_trace_grid_reference, _subplot_type_for_trace_type, ) class PxDefaults(object): def __init__(self): self.template = None self.width = None self.height = None self.color_discrete_sequence = None self.color_continuous_scale = None self.symbol_sequence = None self.line_dash_sequence = None self.size_max = 20 defaults = PxDefaults() del PxDefaults MAPBOX_TOKEN = None def set_mapbox_access_token(token): """ Arguments: token: A Mapbox token to be used in `plotly_express.scatter_mapbox` and \ `plotly_express.line_mapbox` figures. See \ https://docs.mapbox.com/help/how-mapbox-works/access-tokens/ for more details """ global MAPBOX_TOKEN MAPBOX_TOKEN = token def get_trendline_results(fig): """ Extracts fit statistics for trendlines (when applied to figures generated with the `trendline` argument set to `"ols"`). Arguments: fig: the output of a `plotly_express` charting call Returns: A `pandas.DataFrame` with a column "px_fit_results" containing the `statsmodels` results objects, along with columns identifying the subset of the data the trendline was fit on. """ return fig._px_trendlines Mapping = namedtuple( "Mapping", [ "show_in_trace_name", "grouper", "val_map", "sequence", "updater", "variable", "facet", ], ) TraceSpec = namedtuple("TraceSpec", ["constructor", "attrs", "trace_patch", "marginal"]) def get_label(args, column): try: return args["labels"][column] except Exception: return column def get_decorated_label(args, column, role): label = get_label(args, column) if "histfunc" in args and ( (role == "x" and "orientation" in args and args["orientation"] == "h") or (role == "y" and "orientation" in args and args["orientation"] == "v") or (role == "z") ): if label: return "%s of %s" % (args["histfunc"] or "count", label) else: return "count" else: return label def make_mapping(args, variable): if variable == "line_group" or variable == "animation_frame": return Mapping( show_in_trace_name=False, grouper=args[variable], val_map={}, sequence=[""], variable=variable, updater=(lambda trace, v: v), facet=None, ) if variable == "facet_row" or variable == "facet_col": letter = "x" if variable == "facet_col" else "y" return Mapping( show_in_trace_name=False, variable=letter, grouper=args[variable], val_map={}, sequence=[i for i in range(1, 1000)], updater=(lambda trace, v: v), facet="row" if variable == "facet_row" else "col", ) (parent, variable) = variable.split(".") vprefix = variable arg_name = variable if variable == "color": vprefix = "color_discrete" if variable == "dash": arg_name = "line_dash" vprefix = "line_dash" return Mapping( show_in_trace_name=True, variable=variable, grouper=args[arg_name], val_map=args[vprefix + "_map"].copy(), sequence=args[vprefix + "_sequence"], updater=lambda trace, v: trace.update({parent: {variable: v}}), facet=None, ) def make_trace_kwargs(args, trace_spec, g, mapping_labels, sizeref): """Populates a dict with arguments to update trace Parameters ---------- args : dict args to be used for the trace trace_spec : NamedTuple which kind of trace to be used (has constructor, marginal etc. attributes) g : pandas DataFrame data mapping_labels : dict to be used for hovertemplate sizeref : float marker sizeref Returns ------- result : dict dict to be used to update trace fit_results : dict fit information to be used for trendlines """ if "line_close" in args and args["line_close"]: g = g.append(g.iloc[0]) result = trace_spec.trace_patch.copy() or {} fit_results = None hover_header = "" custom_data_len = 0 for k in trace_spec.attrs: v = args[k] v_label = get_decorated_label(args, v, k) if k == "dimensions": dims = [ (name, column) for (name, column) in g.iteritems() if ((not v) or (name in v)) and ( trace_spec.constructor != go.Parcoords or args["data_frame"][name].dtype.kind in "bifc" ) and ( trace_spec.constructor != go.Parcats or len(args["data_frame"][name].unique()) <= 20 ) ] result["dimensions"] = [ dict(label=get_label(args, name), values=column.values) for (name, column) in dims ] if trace_spec.constructor == go.Splom: for d in result["dimensions"]: d["axis"] = dict(matches=True) mapping_labels["%{xaxis.title.text}"] = "%{x}" mapping_labels["%{yaxis.title.text}"] = "%{y}" elif ( v is not None or (trace_spec.constructor == go.Histogram and k in ["x", "y"]) or ( trace_spec.constructor in [go.Histogram2d, go.Histogram2dContour] and k == "z" ) ): if k == "size": if "marker" not in result: result["marker"] = dict() result["marker"]["size"] = g[v] result["marker"]["sizemode"] = "area" result["marker"]["sizeref"] = sizeref mapping_labels[v_label] = "%{marker.size}" elif k == "marginal_x": if trace_spec.constructor == go.Histogram: mapping_labels["count"] = "%{y}" elif k == "marginal_y": if trace_spec.constructor == go.Histogram: mapping_labels["count"] = "%{x}" elif k == "trendline": if v in ["ols", "lowess"] and args["x"] and args["y"] and len(g) > 1: import statsmodels.api as sm # sorting is bad but trace_specs with "trendline" have no other attrs g2 = g.sort_values(by=args["x"]) y = g2[args["y"]] x = g2[args["x"]] result["x"] = x if x.dtype.type == np.datetime64: x = x.astype(int) / 10 ** 9 # convert to unix epoch seconds if v == "lowess": trendline = sm.nonparametric.lowess(y, x) result["y"] = trendline[:, 1] hover_header = "LOWESS trendline

" elif v == "ols": fit_results = sm.OLS(y.values, sm.add_constant(x.values)).fit() result["y"] = fit_results.predict() hover_header = "OLS trendline
" hover_header += "%s = %f * %s + %f
" % ( args["y"], fit_results.params[1], args["x"], fit_results.params[0], ) hover_header += ( "R2=%f

" % fit_results.rsquared ) mapping_labels[get_label(args, args["x"])] = "%{x}" mapping_labels[get_label(args, args["y"])] = "%{y} (trend)" elif k.startswith("error"): error_xy = k[:7] arr = "arrayminus" if k.endswith("minus") else "array" if error_xy not in result: result[error_xy] = {} result[error_xy][arr] = g[v] elif k == "custom_data": result["customdata"] = g[v].values custom_data_len = len(v) # number of custom data columns elif k == "hover_name": if trace_spec.constructor not in [ go.Histogram, go.Histogram2d, go.Histogram2dContour, ]: result["hovertext"] = g[v] if hover_header == "": hover_header = "%{hovertext}

" elif k == "hover_data": if trace_spec.constructor not in [ go.Histogram, go.Histogram2d, go.Histogram2dContour, ]: for col in v: try: position = args["custom_data"].index(col) except (ValueError, AttributeError, KeyError): position = custom_data_len custom_data_len += 1 if "customdata" in result: result["customdata"] = np.hstack( (result["customdata"], g[col].values[:, None]) ) else: result["customdata"] = g[col].values[:, None] v_label_col = get_decorated_label(args, col, None) mapping_labels[v_label_col] = "%%{customdata[%d]}" % (position) elif k == "color": if trace_spec.constructor in [go.Choropleth, go.Choroplethmapbox]: result["z"] = g[v] result["coloraxis"] = "coloraxis1" mapping_labels[v_label] = "%{z}" elif trace_spec.constructor in [ go.Sunburst, go.Treemap, go.Pie, go.Funnelarea, ]: if "marker" not in result: result["marker"] = dict() if args.get("color_is_continuous"): result["marker"]["colors"] = g[v] result["marker"]["coloraxis"] = "coloraxis1" mapping_labels[v_label] = "%{color}" else: result["marker"]["colors"] = [] mapping = {} for cat in g[v]: if mapping.get(cat) is None: mapping[cat] = args["color_discrete_sequence"][ len(mapping) % len(args["color_discrete_sequence"]) ] result["marker"]["colors"].append(mapping[cat]) else: colorable = "marker" if trace_spec.constructor in [go.Parcats, go.Parcoords]: colorable = "line" if colorable not in result: result[colorable] = dict() result[colorable]["color"] = g[v] result[colorable]["coloraxis"] = "coloraxis1" mapping_labels[v_label] = "%%{%s.color}" % colorable elif k == "animation_group": result["ids"] = g[v] elif k == "locations": result[k] = g[v] mapping_labels[v_label] = "%{location}" elif k == "values": result[k] = g[v] _label = "value" if v_label == "values" else v_label mapping_labels[_label] = "%{value}" elif k == "parents": result[k] = g[v] _label = "parent" if v_label == "parents" else v_label mapping_labels[_label] = "%{parent}" elif k == "ids": result[k] = g[v] _label = "id" if v_label == "ids" else v_label mapping_labels[_label] = "%{id}" elif k == "names": if trace_spec.constructor in [ go.Sunburst, go.Treemap, go.Pie, go.Funnelarea, ]: result["labels"] = g[v] _label = "label" if v_label == "names" else v_label mapping_labels[_label] = "%{label}" else: result[k] = g[v] else: if v: result[k] = g[v] mapping_labels[v_label] = "%%{%s}" % k if trace_spec.constructor not in [ go.Parcoords, go.Parcats, ]: hover_lines = [k + "=" + v for k, v in mapping_labels.items()] result["hovertemplate"] = hover_header + "
".join(hover_lines) return result, fit_results def configure_axes(args, constructor, fig, orders): configurators = { go.Scatter: configure_cartesian_axes, go.Scattergl: configure_cartesian_axes, go.Bar: configure_cartesian_axes, go.Box: configure_cartesian_axes, go.Violin: configure_cartesian_axes, go.Histogram: configure_cartesian_axes, go.Histogram2dContour: configure_cartesian_axes, go.Histogram2d: configure_cartesian_axes, go.Scatter3d: configure_3d_axes, go.Scatterternary: configure_ternary_axes, go.Scatterpolar: configure_polar_axes, go.Scatterpolargl: configure_polar_axes, go.Barpolar: configure_polar_axes, go.Scattermapbox: configure_mapbox, go.Choroplethmapbox: configure_mapbox, go.Densitymapbox: configure_mapbox, go.Scattergeo: configure_geo, go.Choropleth: configure_geo, } if constructor in configurators: configurators[constructor](args, fig, orders) def set_cartesian_axis_opts(args, axis, letter, orders): log_key = "log_" + letter range_key = "range_" + letter if log_key in args and args[log_key]: axis["type"] = "log" if range_key in args and args[range_key]: axis["range"] = [math.log(r, 10) for r in args[range_key]] elif range_key in args and args[range_key]: axis["range"] = args[range_key] if args[letter] in orders: axis["categoryorder"] = "array" axis["categoryarray"] = ( orders[args[letter]] if isinstance(axis, go.layout.XAxis) else list(reversed(orders[args[letter]])) ) def configure_cartesian_marginal_axes(args, fig, orders): if "histogram" in [args["marginal_x"], args["marginal_y"]]: fig.layout["barmode"] = "overlay" nrows = len(fig._grid_ref) ncols = len(fig._grid_ref[0]) # Set y-axis titles and axis options in the left-most column for yaxis in fig.select_yaxes(col=1): set_cartesian_axis_opts(args, yaxis, "y", orders) # Set x-axis titles and axis options in the bottom-most row for xaxis in fig.select_xaxes(row=1): set_cartesian_axis_opts(args, xaxis, "x", orders) # Configure axis ticks on marginal subplots if args["marginal_x"]: fig.update_yaxes(showticklabels=False, showline=False, ticks="", row=nrows) if args["template"].layout.yaxis.showgrid is None: fig.update_yaxes(showgrid=args["marginal_x"] == "histogram", row=nrows) if args["template"].layout.xaxis.showgrid is None: fig.update_xaxes(showgrid=True, row=nrows) if args["marginal_y"]: fig.update_xaxes(showticklabels=False, showline=False, ticks="", col=ncols) if args["template"].layout.xaxis.showgrid is None: fig.update_xaxes(showgrid=args["marginal_y"] == "histogram", col=ncols) if args["template"].layout.yaxis.showgrid is None: fig.update_yaxes(showgrid=True, col=ncols) # Add axis titles to non-marginal subplots y_title = get_decorated_label(args, args["y"], "y") if args["marginal_x"]: fig.update_yaxes(title_text=y_title, row=1, col=1) else: for row in range(1, nrows + 1): fig.update_yaxes(title_text=y_title, row=row, col=1) x_title = get_decorated_label(args, args["x"], "x") if args["marginal_y"]: fig.update_xaxes(title_text=x_title, row=1, col=1) else: for col in range(1, ncols + 1): fig.update_xaxes(title_text=x_title, row=1, col=col) # Configure axis type across all x-axes if "log_x" in args and args["log_x"]: fig.update_xaxes(type="log") # Configure axis type across all y-axes if "log_y" in args and args["log_y"]: fig.update_yaxes(type="log") # Configure matching and axis type for marginal y-axes matches_y = "y" + str(ncols + 1) if args["marginal_x"]: for row in range(2, nrows + 1, 2): fig.update_yaxes(matches=matches_y, type=None, row=row) if args["marginal_y"]: for col in range(2, ncols + 1, 2): fig.update_xaxes(matches="x2", type=None, col=col) def configure_cartesian_axes(args, fig, orders): if ("marginal_x" in args and args["marginal_x"]) or ( "marginal_y" in args and args["marginal_y"] ): configure_cartesian_marginal_axes(args, fig, orders) return # Set y-axis titles and axis options in the left-most column y_title = get_decorated_label(args, args["y"], "y") for yaxis in fig.select_yaxes(col=1): yaxis.update(title_text=y_title) set_cartesian_axis_opts(args, yaxis, "y", orders) # Set x-axis titles and axis options in the bottom-most row x_title = get_decorated_label(args, args["x"], "x") for xaxis in fig.select_xaxes(row=1): xaxis.update(title_text=x_title) set_cartesian_axis_opts(args, xaxis, "x", orders) # Configure axis type across all x-axes if "log_x" in args and args["log_x"]: fig.update_xaxes(type="log") # Configure axis type across all y-axes if "log_y" in args and args["log_y"]: fig.update_yaxes(type="log") return fig.layout def configure_ternary_axes(args, fig, orders): fig.update_layout( ternary=dict( aaxis=dict(title=get_label(args, args["a"])), baxis=dict(title=get_label(args, args["b"])), caxis=dict(title=get_label(args, args["c"])), ) ) def configure_polar_axes(args, fig, orders): layout = dict( polar=dict( angularaxis=dict(direction=args["direction"], rotation=args["start_angle"]), radialaxis=dict(), ) ) for var, axis in [("r", "radialaxis"), ("theta", "angularaxis")]: if args[var] in orders: layout["polar"][axis]["categoryorder"] = "array" layout["polar"][axis]["categoryarray"] = orders[args[var]] radialaxis = layout["polar"]["radialaxis"] if args["log_r"]: radialaxis["type"] = "log" if args["range_r"]: radialaxis["range"] = [math.log(x, 10) for x in args["range_r"]] else: if args["range_r"]: radialaxis["range"] = args["range_r"] if args["range_theta"]: layout["polar"]["sector"] = args["range_theta"] fig.update(layout=layout) def configure_3d_axes(args, fig, orders): layout = dict( scene=dict( xaxis=dict(title=get_label(args, args["x"])), yaxis=dict(title=get_label(args, args["y"])), zaxis=dict(title=get_label(args, args["z"])), ) ) for letter in ["x", "y", "z"]: axis = layout["scene"][letter + "axis"] if args["log_" + letter]: axis["type"] = "log" if args["range_" + letter]: axis["range"] = [math.log(x, 10) for x in args["range_" + letter]] else: if args["range_" + letter]: axis["range"] = args["range_" + letter] if args[letter] in orders: axis["categoryorder"] = "array" axis["categoryarray"] = orders[args[letter]] fig.update(layout=layout) def configure_mapbox(args, fig, orders): center = args["center"] if not center and "lat" in args and "lon" in args: center = dict( lat=args["data_frame"][args["lat"]].mean(), lon=args["data_frame"][args["lon"]].mean(), ) fig.update_layout( mapbox=dict( accesstoken=MAPBOX_TOKEN, center=center, zoom=args["zoom"], style=args["mapbox_style"], ) ) def configure_geo(args, fig, orders): fig.update_layout( geo=dict( center=args["center"], scope=args["scope"], projection=dict(type=args["projection"]), ) ) def configure_animation_controls(args, constructor, fig): def frame_args(duration): return { "frame": {"duration": duration, "redraw": constructor != go.Scatter}, "mode": "immediate", "fromcurrent": True, "transition": {"duration": duration, "easing": "linear"}, } if "animation_frame" in args and args["animation_frame"] and len(fig.frames) > 1: fig.layout.updatemenus = [ { "buttons": [ { "args": [None, frame_args(500)], "label": "▶", "method": "animate", }, { "args": [[None], frame_args(0)], "label": "◼", "method": "animate", }, ], "direction": "left", "pad": {"r": 10, "t": 70}, "showactive": False, "type": "buttons", "x": 0.1, "xanchor": "right", "y": 0, "yanchor": "top", } ] fig.layout.sliders = [ { "active": 0, "yanchor": "top", "xanchor": "left", "currentvalue": { "prefix": get_label(args, args["animation_frame"]) + "=" }, "pad": {"b": 10, "t": 60}, "len": 0.9, "x": 0.1, "y": 0, "steps": [ { "args": [[f.name], frame_args(0)], "label": f.name, "method": "animate", } for f in fig.frames ], } ] def make_trace_spec(args, constructor, attrs, trace_patch): # Create base trace specification result = [TraceSpec(constructor, attrs, trace_patch, None)] # Add marginal trace specifications for letter in ["x", "y"]: if "marginal_" + letter in args and args["marginal_" + letter]: trace_spec = None axis_map = dict( xaxis="x1" if letter == "x" else "x2", yaxis="y1" if letter == "y" else "y2", ) if args["marginal_" + letter] == "histogram": trace_spec = TraceSpec( constructor=go.Histogram, attrs=[letter, "marginal_" + letter], trace_patch=dict(opacity=0.5, bingroup=letter, **axis_map), marginal=letter, ) elif args["marginal_" + letter] == "violin": trace_spec = TraceSpec( constructor=go.Violin, attrs=[letter, "hover_name", "hover_data"], trace_patch=dict(scalegroup=letter), marginal=letter, ) elif args["marginal_" + letter] == "box": trace_spec = TraceSpec( constructor=go.Box, attrs=[letter, "hover_name", "hover_data"], trace_patch=dict(notched=True), marginal=letter, ) elif args["marginal_" + letter] == "rug": symbols = {"x": "line-ns-open", "y": "line-ew-open"} trace_spec = TraceSpec( constructor=go.Box, attrs=[letter, "hover_name", "hover_data"], trace_patch=dict( fillcolor="rgba(255,255,255,0)", line={"color": "rgba(255,255,255,0)"}, boxpoints="all", jitter=0, hoveron="points", marker={"symbol": symbols[letter]}, ), marginal=letter, ) if "color" in attrs or "color" not in args: if "marker" not in trace_spec.trace_patch: trace_spec.trace_patch["marker"] = dict() first_default_color = args["color_continuous_scale"][0] trace_spec.trace_patch["marker"]["color"] = first_default_color result.append(trace_spec) # Add trendline trace specifications if "trendline" in args and args["trendline"]: trace_spec = TraceSpec( constructor=go.Scatter, attrs=["trendline"], trace_patch=dict(mode="lines"), marginal=None, ) if args["trendline_color_override"]: trace_spec.trace_patch["line"] = dict( color=args["trendline_color_override"] ) result.append(trace_spec) return result def one_group(x): return "" def apply_default_cascade(args): # first we apply px.defaults to unspecified args for param in ( ["color_discrete_sequence", "color_continuous_scale"] + ["symbol_sequence", "line_dash_sequence", "template"] + ["width", "height", "size_max"] ): if param in args and args[param] is None: args[param] = getattr(defaults, param) # load the default template if set, otherwise "plotly" if args["template"] is None: if pio.templates.default is not None: args["template"] = pio.templates.default else: args["template"] = "plotly" try: # retrieve the actual template if we were given a name args["template"] = pio.templates[args["template"]] except Exception: # otherwise try to build a real template args["template"] = go.layout.Template(args["template"]) # if colors not set explicitly or in px.defaults, defer to a template # if the template doesn't have one, we set some final fallback defaults if "color_continuous_scale" in args: if ( args["color_continuous_scale"] is None and args["template"].layout.colorscale.sequential ): args["color_continuous_scale"] = [ x[1] for x in args["template"].layout.colorscale.sequential ] if args["color_continuous_scale"] is None: args["color_continuous_scale"] = sequential.Viridis if "color_discrete_sequence" in args: if args["color_discrete_sequence"] is None and args["template"].layout.colorway: args["color_discrete_sequence"] = args["template"].layout.colorway if args["color_discrete_sequence"] is None: args["color_discrete_sequence"] = qualitative.D3 # if symbol_sequence/line_dash_sequence not set explicitly or in px.defaults, # see if we can defer to template. If not, set reasonable defaults if "symbol_sequence" in args: if args["symbol_sequence"] is None and args["template"].data.scatter: args["symbol_sequence"] = [ scatter.marker.symbol for scatter in args["template"].data.scatter ] if not args["symbol_sequence"] or not any(args["symbol_sequence"]): args["symbol_sequence"] = ["circle", "diamond", "square", "x", "cross"] if "line_dash_sequence" in args: if args["line_dash_sequence"] is None and args["template"].data.scatter: args["line_dash_sequence"] = [ scatter.line.dash for scatter in args["template"].data.scatter ] if not args["line_dash_sequence"] or not any(args["line_dash_sequence"]): args["line_dash_sequence"] = [ "solid", "dot", "dash", "longdash", "dashdot", "longdashdot", ] # If both marginals and faceting are specified, faceting wins if args.get("facet_col", None) is not None and args.get("marginal_y", None): args["marginal_y"] = None if args.get("facet_row", None) is not None and args.get("marginal_x", None): args["marginal_x"] = None def _check_name_not_reserved(field_name, reserved_names): if field_name not in reserved_names: return field_name else: raise NameError( "A name conflict was encountered for argument %s. " "A column with name %s is already used." % (field_name, field_name) ) def _get_reserved_col_names(args, attrables, array_attrables): """ This function builds a list of columns of the data_frame argument used as arguments, either as str/int arguments or given as columns (pandas series type). """ df = args["data_frame"] reserved_names = set() for field in args: if field not in attrables: continue names = args[field] if field in array_attrables else [args[field]] if names is None: continue for arg in names: if arg is None: continue elif isinstance(arg, str): # no need to add ints since kw arg are not ints reserved_names.add(arg) elif isinstance(arg, pd.Series): arg_name = arg.name if arg_name and hasattr(df, arg_name): in_df = arg is df[arg_name] if in_df: reserved_names.add(arg_name) return reserved_names def build_dataframe(args, attrables, array_attrables): """ Constructs a dataframe and modifies `args` in-place. The argument values in `args` can be either strings corresponding to existing columns of a dataframe, or data arrays (lists, numpy arrays, pandas columns, series). Parameters ---------- args : OrderedDict arguments passed to the px function and subsequently modified attrables : list list of keys into `args`, all of whose corresponding values are converted into columns of a dataframe. array_attrables : list argument names corresponding to iterables, such as `hover_data`, ... """ for field in args: if field in array_attrables and args[field] is not None: args[field] = ( dict(args[field]) if isinstance(args[field], dict) else list(args[field]) ) # Cast data_frame argument to DataFrame (it could be a numpy array, dict etc.) df_provided = args["data_frame"] is not None if df_provided and not isinstance(args["data_frame"], pd.DataFrame): args["data_frame"] = pd.DataFrame(args["data_frame"]) df_input = args["data_frame"] # We start from an empty DataFrame df_output = pd.DataFrame() # Initialize set of column names # These are reserved names if df_provided: reserved_names = _get_reserved_col_names(args, attrables, array_attrables) else: reserved_names = set() # Case of functions with a "dimensions" kw: scatter_matrix, parcats, parcoords if "dimensions" in args and args["dimensions"] is None: if not df_provided: raise ValueError( "No data were provided. Please provide data either with the `data_frame` or with the `dimensions` argument." ) else: df_output[df_input.columns] = df_input[df_input.columns] # Loop over possible arguments for field_name in attrables: # Massaging variables argument_list = ( [args.get(field_name)] if field_name not in array_attrables else args.get(field_name) ) # argument not specified, continue if argument_list is None or argument_list is [None]: continue # Argument name: field_name if the argument is not a list # Else we give names like ["hover_data_0, hover_data_1"] etc. field_list = ( [field_name] if field_name not in array_attrables else [field_name + "_" + str(i) for i in range(len(argument_list))] ) # argument_list and field_list ready, iterate over them # Core of the loop starts here for i, (argument, field) in enumerate(zip(argument_list, field_list)): length = len(df_output) if argument is None: continue # Case of multiindex if isinstance(argument, pd.MultiIndex): raise TypeError( "Argument '%s' is a pandas MultiIndex. " "pandas MultiIndex is not supported by plotly express " "at the moment." % field ) # ----------------- argument is a col name ---------------------- if isinstance(argument, str) or isinstance( argument, int ): # just a column name given as str or int if not df_provided: raise ValueError( "String or int arguments are only possible when a " "DataFrame or an array is provided in the `data_frame` " "argument. No DataFrame was provided, but argument " "'%s' is of type str or int." % field ) # Check validity of column name if argument not in df_input.columns: err_msg = ( "Value of '%s' is not the name of a column in 'data_frame'. " "Expected one of %s but received: %s" % (field, str(list(df_input.columns)), argument) ) if argument == "index": err_msg += ( "\n To use the index, pass it in directly as `df.index`." ) raise ValueError(err_msg) if length and len(df_input[argument]) != length: raise ValueError( "All arguments should have the same length. " "The length of column argument `df[%s]` is %d, whereas the " "length of previous arguments %s is %d" % ( field, len(df_input[argument]), str(list(df_output.columns)), length, ) ) col_name = str(argument) df_output[col_name] = df_input[argument].values # ----------------- argument is a column / array / list.... ------- else: is_index = isinstance(argument, pd.RangeIndex) # First pandas # pandas series have a name but it's None if ( hasattr(argument, "name") and argument.name is not None ) or is_index: col_name = argument.name # pandas df if col_name is None and is_index: col_name = "index" if not df_provided: col_name = field else: if is_index: keep_name = df_provided and argument is df_input.index else: keep_name = ( col_name in df_input and argument is df_input[col_name] ) col_name = ( col_name if keep_name else _check_name_not_reserved(field, reserved_names) ) else: # numpy array, list... col_name = _check_name_not_reserved(field, reserved_names) if length and len(argument) != length: raise ValueError( "All arguments should have the same length. " "The length of argument `%s` is %d, whereas the " "length of previous arguments %s is %d" % (field, len(argument), str(list(df_output.columns)), length) ) if hasattr(argument, "values"): df_output[str(col_name)] = argument.values else: df_output[str(col_name)] = np.array(argument) # Finally, update argument with column name now that column exists if field_name not in array_attrables: args[field_name] = str(col_name) else: args[field_name][i] = str(col_name) args["data_frame"] = df_output return args def infer_config(args, constructor, trace_patch): # Declare all supported attributes, across all plot types attrables = ( ["x", "y", "z", "a", "b", "c", "r", "theta", "size", "dimensions"] + ["custom_data", "hover_name", "hover_data", "text"] + ["names", "values", "parents", "ids"] + ["error_x", "error_x_minus"] + ["error_y", "error_y_minus", "error_z", "error_z_minus"] + ["lat", "lon", "locations", "animation_group"] ) array_attrables = ["dimensions", "custom_data", "hover_data"] group_attrables = ["animation_frame", "facet_row", "facet_col", "line_group"] all_attrables = attrables + group_attrables + ["color"] group_attrs = ["symbol", "line_dash"] for group_attr in group_attrs: if group_attr in args: all_attrables += [group_attr] args = build_dataframe(args, all_attrables, array_attrables) attrs = [k for k in attrables if k in args] grouped_attrs = [] # Compute sizeref sizeref = 0 if "size" in args and args["size"]: sizeref = args["data_frame"][args["size"]].max() / args["size_max"] ** 2 # Compute color attributes and grouping attributes if "color" in args: if "color_continuous_scale" in args: if "color_discrete_sequence" not in args: attrs.append("color") else: if ( args["color"] and args["data_frame"][args["color"]].dtype.kind in "bifc" ): attrs.append("color") args["color_is_continuous"] = True elif constructor in [go.Sunburst, go.Treemap]: attrs.append("color") args["color_is_continuous"] = False else: grouped_attrs.append("marker.color") elif "line_group" in args or constructor == go.Histogram2dContour: grouped_attrs.append("line.color") elif constructor in [go.Pie, go.Funnelarea]: attrs.append("color") if args["color"]: if args["hover_data"] is None: args["hover_data"] = [] args["hover_data"].append(args["color"]) else: grouped_attrs.append("marker.color") show_colorbar = bool( "color" in attrs and args["color"] and constructor not in [go.Pie, go.Funnelarea] and ( constructor not in [go.Treemap, go.Sunburst] or args.get("color_is_continuous") ) ) else: show_colorbar = False # Compute line_dash grouping attribute if "line_dash" in args: grouped_attrs.append("line.dash") # Compute symbol grouping attribute if "symbol" in args: grouped_attrs.append("marker.symbol") # Compute final trace patch trace_patch = trace_patch.copy() if constructor in [go.Histogram2d, go.Densitymapbox]: show_colorbar = True trace_patch["coloraxis"] = "coloraxis1" if "opacity" in args: if args["opacity"] is None: if "barmode" in args and args["barmode"] == "overlay": trace_patch["marker"] = dict(opacity=0.5) else: trace_patch["marker"] = dict(opacity=args["opacity"]) if "line_group" in args: trace_patch["mode"] = "lines" + ("+markers+text" if args["text"] else "") elif constructor != go.Splom and ( "symbol" in args or constructor == go.Scattermapbox ): trace_patch["mode"] = "markers" + ("+text" if args["text"] else "") if "line_shape" in args: trace_patch["line"] = dict(shape=args["line_shape"]) # Compute marginal attribute if "marginal" in args: position = "marginal_x" if args["orientation"] == "v" else "marginal_y" other_position = "marginal_x" if args["orientation"] == "h" else "marginal_y" args[position] = args["marginal"] args[other_position] = None if ( args.get("marginal_x", None) is not None or args.get("marginal_y", None) is not None or args.get("facet_row", None) is not None ): args["facet_col_wrap"] = 0 # Compute applicable grouping attributes for k in group_attrables: if k in args: grouped_attrs.append(k) # Create grouped mappings grouped_mappings = [make_mapping(args, a) for a in grouped_attrs] # Create trace specs trace_specs = make_trace_spec(args, constructor, attrs, trace_patch) return args, trace_specs, grouped_mappings, sizeref, show_colorbar def get_orderings(args, grouper, grouped): """ `orders` is the user-supplied ordering (with the remaining data-frame-supplied ordering appended if the column is used for grouping) `group_names` is the set of groups, ordered by the order above """ orders = {} if "category_orders" not in args else args["category_orders"].copy() group_names = [] for group_name in grouped.groups: if len(grouper) == 1: group_name = (group_name,) group_names.append(group_name) for col in grouper: if col != one_group: uniques = args["data_frame"][col].unique() if col not in orders: orders[col] = list(uniques) else: for val in uniques: if val not in orders[col]: orders[col].append(val) for i, col in reversed(list(enumerate(grouper))): if col != one_group: group_names = sorted( group_names, key=lambda g: orders[col].index(g[i]) if g[i] in orders[col] else -1, ) return orders, group_names def make_figure(args, constructor, trace_patch={}, layout_patch={}): apply_default_cascade(args) args, trace_specs, grouped_mappings, sizeref, show_colorbar = infer_config( args, constructor, trace_patch ) grouper = [x.grouper or one_group for x in grouped_mappings] or [one_group] grouped = args["data_frame"].groupby(grouper, sort=False) orders, sorted_group_names = get_orderings(args, grouper, grouped) subplot_type = _subplot_type_for_trace_type(constructor().type) trace_names_by_frame = {} frames = OrderedDict() trendline_rows = [] nrows = ncols = 1 col_labels = [] row_labels = [] for group_name in sorted_group_names: group = grouped.get_group(group_name if len(group_name) > 1 else group_name[0]) mapping_labels = OrderedDict() trace_name_labels = OrderedDict() frame_name = "" for col, val, m in zip(grouper, group_name, grouped_mappings): if col != one_group: key = get_label(args, col) mapping_labels[key] = str(val) if m.show_in_trace_name: trace_name_labels[key] = str(val) if m.variable == "animation_frame": frame_name = val trace_name = ", ".join(k + "=" + v for k, v in trace_name_labels.items()) if frame_name not in trace_names_by_frame: trace_names_by_frame[frame_name] = set() trace_names = trace_names_by_frame[frame_name] for trace_spec in trace_specs: constructor_to_use = trace_spec.constructor if constructor_to_use in [go.Scatter, go.Scatterpolar]: if "render_mode" in args and ( args["render_mode"] == "webgl" or ( args["render_mode"] == "auto" and len(args["data_frame"]) > 1000 and args["animation_frame"] is None ) ): constructor_to_use = ( go.Scattergl if constructor_to_use == go.Scatter else go.Scatterpolargl ) # Create the trace trace = constructor_to_use(name=trace_name) if trace_spec.constructor not in [ go.Parcats, go.Parcoords, go.Choropleth, go.Choroplethmapbox, go.Densitymapbox, go.Histogram2d, go.Sunburst, go.Treemap, ]: trace.update( legendgroup=trace_name, showlegend=(trace_name != "" and trace_name not in trace_names), ) if trace_spec.constructor in [go.Bar, go.Violin, go.Box, go.Histogram]: trace.update(alignmentgroup=True, offsetgroup=trace_name) if trace_spec.constructor not in [go.Parcats, go.Parcoords]: trace.update(hoverlabel=dict(namelength=0)) trace_names.add(trace_name) # Init subplot row/col trace._subplot_row = 1 trace._subplot_col = 1 for i, m in enumerate(grouped_mappings): val = group_name[i] if val not in m.val_map: m.val_map[val] = m.sequence[len(m.val_map) % len(m.sequence)] try: m.updater(trace, m.val_map[val]) except ValueError: if ( trace_spec != trace_specs[0] and trace_spec.constructor in [go.Violin, go.Box, go.Histogram] and m.variable == "symbol" ): pass elif ( trace_spec != trace_specs[0] and trace_spec.constructor in [go.Histogram] and m.variable == "color" ): trace.update(marker=dict(color=m.val_map[val])) else: raise # Find row for trace, handling facet_row and marginal_x if m.facet == "row": row = m.val_map[val] if args["facet_row"] and len(row_labels) < row: row_labels.append( get_label(args, args["facet_row"]) + "=" + str(val) ) else: if ( bool(args.get("marginal_x", False)) and trace_spec.marginal != "x" ): row = 2 else: row = 1 facet_col_wrap = args.get("facet_col_wrap", 0) # Find col for trace, handling facet_col and marginal_y if m.facet == "col": col = m.val_map[val] if args["facet_col"] and len(col_labels) < col: col_labels.append( get_label(args, args["facet_col"]) + "=" + str(val) ) if facet_col_wrap: # assumes no facet_row, no marginals row = 1 + ((col - 1) // facet_col_wrap) col = 1 + ((col - 1) % facet_col_wrap) else: if trace_spec.marginal == "y": col = 2 else: col = 1 nrows = max(nrows, row) if row > 1: trace._subplot_row = row ncols = max(ncols, col) if col > 1: trace._subplot_col = col if ( trace_specs[0].constructor == go.Histogram2dContour and trace_spec.constructor == go.Box and trace.line.color ): trace.update(marker=dict(color=trace.line.color)) patch, fit_results = make_trace_kwargs( args, trace_spec, group, mapping_labels.copy(), sizeref ) trace.update(patch) if fit_results is not None: trendline_rows.append(mapping_labels.copy()) trendline_rows[-1]["px_fit_results"] = fit_results if frame_name not in frames: frames[frame_name] = dict(data=[], name=frame_name) frames[frame_name]["data"].append(trace) frame_list = [f for f in frames.values()] if len(frame_list) > 1: frame_list = sorted( frame_list, key=lambda f: orders[args["animation_frame"]].index(f["name"]) ) layout_patch = layout_patch.copy() if show_colorbar: colorvar = "z" if constructor in [go.Histogram2d, go.Densitymapbox] else "color" range_color = args["range_color"] or [None, None] colorscale_validator = ColorscaleValidator("colorscale", "make_figure") layout_patch["coloraxis1"] = dict( colorscale=colorscale_validator.validate_coerce( args["color_continuous_scale"] ), cmid=args["color_continuous_midpoint"], cmin=range_color[0], cmax=range_color[1], colorbar=dict(title=get_decorated_label(args, args[colorvar], colorvar)), ) for v in ["title", "height", "width"]: if args[v]: layout_patch[v] = args[v] layout_patch["legend"] = {"tracegroupgap": 0} if "title" not in layout_patch and args["template"].layout.margin.t is None: layout_patch["margin"] = {"t": 60} if ( "size" in args and args["size"] and args["template"].layout.legend.itemsizing is None ): layout_patch["legend"]["itemsizing"] = "constant" fig = init_figure( args, subplot_type, frame_list, nrows, ncols, col_labels, row_labels ) # Position traces in subplots for frame in frame_list: for trace in frame["data"]: if isinstance(trace, go.Splom): # Special case that is not compatible with make_subplots continue _set_trace_grid_reference( trace, fig.layout, fig._grid_ref, nrows - trace._subplot_row + 1, trace._subplot_col, ) # Add traces, layout and frames to figure fig.add_traces(frame_list[0]["data"] if len(frame_list) > 0 else []) fig.layout.update(layout_patch) if "template" in args and args["template"] is not None: fig.update_layout(template=args["template"], overwrite=True) fig.frames = frame_list if len(frames) > 1 else [] fig._px_trendlines = pd.DataFrame(trendline_rows) configure_axes(args, constructor, fig, orders) configure_animation_controls(args, constructor, fig) return fig def init_figure(args, subplot_type, frame_list, nrows, ncols, col_labels, row_labels): # Build subplot specs specs = [[{}] * ncols for _ in range(nrows)] for frame in frame_list: for trace in frame["data"]: row0 = trace._subplot_row - 1 col0 = trace._subplot_col - 1 if isinstance(trace, go.Splom): # Splom not compatible with make_subplots, treat as domain specs[row0][col0] = {"type": "domain"} else: specs[row0][col0] = {"type": trace.type} # Default row/column widths uniform column_widths = [1.0] * ncols row_heights = [1.0] * nrows # Build column_widths/row_heights if subplot_type == "xy": if bool(args.get("marginal_x", False)): if args["marginal_x"] == "histogram" or ("color" in args and args["color"]): main_size = 0.74 else: main_size = 0.84 row_heights = [main_size] * (nrows - 1) + [1 - main_size] vertical_spacing = 0.01 elif args.get("facet_col_wrap", 0): vertical_spacing = 0.07 else: vertical_spacing = 0.03 if bool(args.get("marginal_y", False)): if args["marginal_y"] == "histogram" or ("color" in args and args["color"]): main_size = 0.74 else: main_size = 0.84 column_widths = [main_size] * (ncols - 1) + [1 - main_size] horizontal_spacing = 0.005 else: horizontal_spacing = 0.02 else: # Other subplot types: # 'scene', 'geo', 'polar', 'ternary', 'mapbox', 'domain', None # # We can customize subplot spacing per type once we enable faceting # for all plot types vertical_spacing = 0.1 horizontal_spacing = 0.1 facet_col_wrap = args.get("facet_col_wrap", 0) if facet_col_wrap: subplot_labels = [None] * nrows * ncols while len(col_labels) < nrows * ncols: col_labels.append(None) for i in range(nrows): for j in range(ncols): subplot_labels[i * ncols + j] = col_labels[(nrows - 1 - i) * ncols + j] # Create figure with subplots fig = make_subplots( rows=nrows, cols=ncols, specs=specs, shared_xaxes="all", shared_yaxes="all", row_titles=[] if facet_col_wrap else list(reversed(row_labels)), column_titles=[] if facet_col_wrap else col_labels, subplot_titles=subplot_labels if facet_col_wrap else [], horizontal_spacing=horizontal_spacing, vertical_spacing=vertical_spacing, row_heights=row_heights, column_widths=column_widths, start_cell="bottom-left", ) # Remove explicit font size of row/col titles so template can take over for annot in fig.layout.annotations: annot.update(font=None) return fig plotly-4.4.1+dfsg.orig/plotly/express/_chart_types.py0000644000175000017500000007417013573717677022363 0ustar noahfxnoahfxfrom ._core import make_figure from ._doc import make_docstring import plotly.graph_objs as go def scatter( data_frame=None, x=None, y=None, color=None, symbol=None, size=None, hover_name=None, hover_data=None, custom_data=None, text=None, facet_row=None, facet_col=None, facet_col_wrap=0, error_x=None, error_x_minus=None, error_y=None, error_y_minus=None, animation_frame=None, animation_group=None, category_orders={}, labels={}, color_discrete_sequence=None, color_discrete_map={}, color_continuous_scale=None, range_color=None, color_continuous_midpoint=None, symbol_sequence=None, symbol_map={}, opacity=None, size_max=None, marginal_x=None, marginal_y=None, trendline=None, trendline_color_override=None, log_x=False, log_y=False, range_x=None, range_y=None, render_mode="auto", title=None, template=None, width=None, height=None, ): """ In a scatter plot, each row of `data_frame` is represented by a symbol mark in 2D space. """ return make_figure(args=locals(), constructor=go.Scatter) scatter.__doc__ = make_docstring(scatter) def density_contour( data_frame=None, x=None, y=None, z=None, color=None, facet_row=None, facet_col=None, facet_col_wrap=0, hover_name=None, hover_data=None, animation_frame=None, animation_group=None, category_orders={}, labels={}, color_discrete_sequence=None, color_discrete_map={}, marginal_x=None, marginal_y=None, trendline=None, trendline_color_override=None, log_x=False, log_y=False, range_x=None, range_y=None, histfunc=None, histnorm=None, nbinsx=None, nbinsy=None, title=None, template=None, width=None, height=None, ): """ In a density contour plot, rows of `data_frame` are grouped together into contour marks to visualize the 2D distribution of an aggregate function `histfunc` (e.g. the count or sum) of the value `z`. """ return make_figure( args=locals(), constructor=go.Histogram2dContour, trace_patch=dict( contours=dict(coloring="none"), histfunc=histfunc, histnorm=histnorm, nbinsx=nbinsx, nbinsy=nbinsy, xbingroup="x", ybingroup="y", ), ) density_contour.__doc__ = make_docstring(density_contour) def density_heatmap( data_frame=None, x=None, y=None, z=None, facet_row=None, facet_col=None, facet_col_wrap=0, hover_name=None, hover_data=None, animation_frame=None, animation_group=None, category_orders={}, labels={}, color_continuous_scale=None, range_color=None, color_continuous_midpoint=None, marginal_x=None, marginal_y=None, opacity=None, log_x=False, log_y=False, range_x=None, range_y=None, histfunc=None, histnorm=None, nbinsx=None, nbinsy=None, title=None, template=None, width=None, height=None, ): """ In a density heatmap, rows of `data_frame` are grouped together into colored rectangular tiles to visualize the 2D distribution of an aggregate function `histfunc` (e.g. the count or sum) of the value `z`. """ return make_figure( args=locals(), constructor=go.Histogram2d, trace_patch=dict( histfunc=histfunc, histnorm=histnorm, nbinsx=nbinsx, nbinsy=nbinsy, xbingroup="x", ybingroup="y", ), ) density_heatmap.__doc__ = make_docstring(density_heatmap) def line( data_frame=None, x=None, y=None, line_group=None, color=None, line_dash=None, hover_name=None, hover_data=None, custom_data=None, text=None, facet_row=None, facet_col=None, facet_col_wrap=0, error_x=None, error_x_minus=None, error_y=None, error_y_minus=None, animation_frame=None, animation_group=None, category_orders={}, labels={}, color_discrete_sequence=None, color_discrete_map={}, line_dash_sequence=None, line_dash_map={}, log_x=False, log_y=False, range_x=None, range_y=None, line_shape=None, render_mode="auto", title=None, template=None, width=None, height=None, ): """ In a 2D line plot, each row of `data_frame` is represented as vertex of a polyline mark in 2D space. """ return make_figure(args=locals(), constructor=go.Scatter) line.__doc__ = make_docstring(line) def area( data_frame=None, x=None, y=None, line_group=None, color=None, hover_name=None, hover_data=None, custom_data=None, text=None, facet_row=None, facet_col=None, facet_col_wrap=0, animation_frame=None, animation_group=None, category_orders={}, labels={}, color_discrete_sequence=None, color_discrete_map={}, orientation="v", groupnorm=None, log_x=False, log_y=False, range_x=None, range_y=None, line_shape=None, title=None, template=None, width=None, height=None, ): """ In a stacked area plot, each row of `data_frame` is represented as vertex of a polyline mark in 2D space. The area between successive polylines is filled. """ return make_figure( args=locals(), constructor=go.Scatter, trace_patch=dict( stackgroup=1, mode="lines", orientation=orientation, groupnorm=groupnorm ), ) area.__doc__ = make_docstring(area) def bar( data_frame=None, x=None, y=None, color=None, facet_row=None, facet_col=None, facet_col_wrap=0, hover_name=None, hover_data=None, custom_data=None, text=None, error_x=None, error_x_minus=None, error_y=None, error_y_minus=None, animation_frame=None, animation_group=None, category_orders={}, labels={}, color_discrete_sequence=None, color_discrete_map={}, color_continuous_scale=None, range_color=None, color_continuous_midpoint=None, opacity=None, orientation="v", barmode="relative", log_x=False, log_y=False, range_x=None, range_y=None, title=None, template=None, width=None, height=None, ): """ In a bar plot, each row of `data_frame` is represented as a rectangular mark. """ return make_figure( args=locals(), constructor=go.Bar, trace_patch=dict(orientation=orientation, textposition="auto"), layout_patch=dict(barmode=barmode), ) bar.__doc__ = make_docstring(bar) def histogram( data_frame=None, x=None, y=None, color=None, facet_row=None, facet_col=None, facet_col_wrap=0, hover_name=None, hover_data=None, animation_frame=None, animation_group=None, category_orders={}, labels={}, color_discrete_sequence=None, color_discrete_map={}, marginal=None, opacity=None, orientation="v", barmode="relative", barnorm=None, histnorm=None, log_x=False, log_y=False, range_x=None, range_y=None, histfunc=None, cumulative=None, nbins=None, title=None, template=None, width=None, height=None, ): """ In a histogram, rows of `data_frame` are grouped together into a rectangular mark to visualize the 1D distribution of an aggregate function `histfunc` (e.g. the count or sum) of the value `y` (or `x` if `orientation` is `'h'`). """ return make_figure( args=locals(), constructor=go.Histogram, trace_patch=dict( orientation=orientation, histnorm=histnorm, histfunc=histfunc, nbinsx=nbins if orientation == "v" else None, nbinsy=None if orientation == "v" else nbins, cumulative=dict(enabled=cumulative), bingroup="x" if orientation == "v" else "y", ), layout_patch=dict(barmode=barmode, barnorm=barnorm), ) histogram.__doc__ = make_docstring(histogram) def violin( data_frame=None, x=None, y=None, color=None, facet_row=None, facet_col=None, facet_col_wrap=0, hover_name=None, hover_data=None, custom_data=None, animation_frame=None, animation_group=None, category_orders={}, labels={}, color_discrete_sequence=None, color_discrete_map={}, orientation="v", violinmode="group", log_x=False, log_y=False, range_x=None, range_y=None, points=None, box=False, title=None, template=None, width=None, height=None, ): """ In a violin plot, rows of `data_frame` are grouped together into a curved mark to visualize their distribution. """ return make_figure( args=locals(), constructor=go.Violin, trace_patch=dict( orientation=orientation, points=points, box=dict(visible=box), scalegroup=True, x0=" ", y0=" ", ), layout_patch=dict(violinmode=violinmode), ) violin.__doc__ = make_docstring(violin) def box( data_frame=None, x=None, y=None, color=None, facet_row=None, facet_col=None, facet_col_wrap=0, hover_name=None, hover_data=None, custom_data=None, animation_frame=None, animation_group=None, category_orders={}, labels={}, color_discrete_sequence=None, color_discrete_map={}, orientation="v", boxmode="group", log_x=False, log_y=False, range_x=None, range_y=None, points=None, notched=False, title=None, template=None, width=None, height=None, ): """ In a box plot, rows of `data_frame` are grouped together into a box-and-whisker mark to visualize their distribution. Each box spans from quartile 1 (Q1) to quartile 3 (Q3). The second quartile (Q2) is marked by a line inside the box. By default, the whiskers correspond to the box' edges +/- 1.5 times the interquartile range (IQR: Q3-Q1), see "points" for other options. """ return make_figure( args=locals(), constructor=go.Box, trace_patch=dict( orientation=orientation, boxpoints=points, notched=notched, x0=" ", y0=" " ), layout_patch=dict(boxmode=boxmode), ) box.__doc__ = make_docstring(box) def strip( data_frame=None, x=None, y=None, color=None, facet_row=None, facet_col=None, facet_col_wrap=0, hover_name=None, hover_data=None, custom_data=None, animation_frame=None, animation_group=None, category_orders={}, labels={}, color_discrete_sequence=None, color_discrete_map={}, orientation="v", stripmode="group", log_x=False, log_y=False, range_x=None, range_y=None, title=None, template=None, width=None, height=None, ): """ In a strip plot each row of `data_frame` is represented as a jittered mark within categories. """ return make_figure( args=locals(), constructor=go.Box, trace_patch=dict( orientation=orientation, boxpoints="all", pointpos=0, hoveron="points", fillcolor="rgba(255,255,255,0)", line={"color": "rgba(255,255,255,0)"}, x0=" ", y0=" ", ), layout_patch=dict(boxmode=stripmode), ) strip.__doc__ = make_docstring(strip) def scatter_3d( data_frame=None, x=None, y=None, z=None, color=None, symbol=None, size=None, text=None, hover_name=None, hover_data=None, custom_data=None, error_x=None, error_x_minus=None, error_y=None, error_y_minus=None, error_z=None, error_z_minus=None, animation_frame=None, animation_group=None, category_orders={}, labels={}, size_max=None, color_discrete_sequence=None, color_discrete_map={}, color_continuous_scale=None, range_color=None, color_continuous_midpoint=None, symbol_sequence=None, symbol_map={}, opacity=None, log_x=False, log_y=False, log_z=False, range_x=None, range_y=None, range_z=None, title=None, template=None, width=None, height=None, ): """ In a 3D scatter plot, each row of `data_frame` is represented by a symbol mark in 3D space. """ return make_figure(args=locals(), constructor=go.Scatter3d) scatter_3d.__doc__ = make_docstring(scatter_3d) def line_3d( data_frame=None, x=None, y=None, z=None, color=None, line_dash=None, text=None, line_group=None, hover_name=None, hover_data=None, custom_data=None, error_x=None, error_x_minus=None, error_y=None, error_y_minus=None, error_z=None, error_z_minus=None, animation_frame=None, animation_group=None, category_orders={}, labels={}, color_discrete_sequence=None, color_discrete_map={}, line_dash_sequence=None, line_dash_map={}, log_x=False, log_y=False, log_z=False, range_x=None, range_y=None, range_z=None, title=None, template=None, width=None, height=None, ): """ In a 3D line plot, each row of `data_frame` is represented as vertex of a polyline mark in 3D space. """ return make_figure(args=locals(), constructor=go.Scatter3d) line_3d.__doc__ = make_docstring(line_3d) def scatter_ternary( data_frame=None, a=None, b=None, c=None, color=None, symbol=None, size=None, text=None, hover_name=None, hover_data=None, custom_data=None, animation_frame=None, animation_group=None, category_orders={}, labels={}, color_discrete_sequence=None, color_discrete_map={}, color_continuous_scale=None, range_color=None, color_continuous_midpoint=None, symbol_sequence=None, symbol_map={}, opacity=None, size_max=None, title=None, template=None, width=None, height=None, ): """ In a ternary scatter plot, each row of `data_frame` is represented by a symbol mark in ternary coordinates. """ return make_figure(args=locals(), constructor=go.Scatterternary) scatter_ternary.__doc__ = make_docstring(scatter_ternary) def line_ternary( data_frame=None, a=None, b=None, c=None, color=None, line_dash=None, line_group=None, hover_name=None, hover_data=None, custom_data=None, text=None, animation_frame=None, animation_group=None, category_orders={}, labels={}, color_discrete_sequence=None, color_discrete_map={}, line_dash_sequence=None, line_dash_map={}, line_shape=None, title=None, template=None, width=None, height=None, ): """ In a ternary line plot, each row of `data_frame` is represented as vertex of a polyline mark in ternary coordinates. """ return make_figure(args=locals(), constructor=go.Scatterternary) line_ternary.__doc__ = make_docstring(line_ternary) def scatter_polar( data_frame=None, r=None, theta=None, color=None, symbol=None, size=None, hover_name=None, hover_data=None, custom_data=None, text=None, animation_frame=None, animation_group=None, category_orders={}, labels={}, color_discrete_sequence=None, color_discrete_map={}, color_continuous_scale=None, range_color=None, color_continuous_midpoint=None, symbol_sequence=None, symbol_map={}, opacity=None, direction="clockwise", start_angle=90, size_max=None, range_r=None, range_theta=None, log_r=False, render_mode="auto", title=None, template=None, width=None, height=None, ): """ In a polar scatter plot, each row of `data_frame` is represented by a symbol mark in polar coordinates. """ return make_figure(args=locals(), constructor=go.Scatterpolar) scatter_polar.__doc__ = make_docstring(scatter_polar) def line_polar( data_frame=None, r=None, theta=None, color=None, line_dash=None, hover_name=None, hover_data=None, custom_data=None, line_group=None, text=None, animation_frame=None, animation_group=None, category_orders={}, labels={}, color_discrete_sequence=None, color_discrete_map={}, line_dash_sequence=None, line_dash_map={}, direction="clockwise", start_angle=90, line_close=False, line_shape=None, render_mode="auto", range_r=None, range_theta=None, log_r=False, title=None, template=None, width=None, height=None, ): """ In a polar line plot, each row of `data_frame` is represented as vertex of a polyline mark in polar coordinates. """ return make_figure(args=locals(), constructor=go.Scatterpolar) line_polar.__doc__ = make_docstring(line_polar) def bar_polar( data_frame=None, r=None, theta=None, color=None, hover_name=None, hover_data=None, custom_data=None, animation_frame=None, animation_group=None, category_orders={}, labels={}, color_discrete_sequence=None, color_discrete_map={}, barnorm=None, barmode="relative", direction="clockwise", start_angle=90, range_r=None, range_theta=None, log_r=False, title=None, template=None, width=None, height=None, ): """ In a polar bar plot, each row of `data_frame` is represented as a wedge mark in polar coordinates. """ return make_figure( args=locals(), constructor=go.Barpolar, layout_patch=dict(barnorm=barnorm, barmode=barmode), ) bar_polar.__doc__ = make_docstring(bar_polar) def choropleth( data_frame=None, lat=None, lon=None, locations=None, locationmode=None, color=None, hover_name=None, hover_data=None, custom_data=None, animation_frame=None, animation_group=None, category_orders={}, labels={}, color_continuous_scale=None, range_color=None, color_continuous_midpoint=None, projection=None, scope=None, center=None, title=None, template=None, width=None, height=None, ): """ In a choropleth map, each row of `data_frame` is represented by a colored region mark on a map. """ return make_figure( args=locals(), constructor=go.Choropleth, trace_patch=dict(locationmode=locationmode), ) choropleth.__doc__ = make_docstring(choropleth) def scatter_geo( data_frame=None, lat=None, lon=None, locations=None, locationmode=None, color=None, text=None, hover_name=None, hover_data=None, custom_data=None, size=None, animation_frame=None, animation_group=None, category_orders={}, labels={}, color_discrete_sequence=None, color_discrete_map={}, color_continuous_scale=None, range_color=None, color_continuous_midpoint=None, opacity=None, size_max=None, projection=None, scope=None, center=None, title=None, template=None, width=None, height=None, ): """ In a geographic scatter plot, each row of `data_frame` is represented by a symbol mark on a map. """ return make_figure( args=locals(), constructor=go.Scattergeo, trace_patch=dict(locationmode=locationmode), ) scatter_geo.__doc__ = make_docstring(scatter_geo) def line_geo( data_frame=None, lat=None, lon=None, locations=None, locationmode=None, color=None, line_dash=None, text=None, hover_name=None, hover_data=None, custom_data=None, line_group=None, animation_frame=None, animation_group=None, category_orders={}, labels={}, color_discrete_sequence=None, color_discrete_map={}, line_dash_sequence=None, line_dash_map={}, projection=None, scope=None, center=None, title=None, template=None, width=None, height=None, ): """ In a geographic line plot, each row of `data_frame` is represented as vertex of a polyline mark on a map. """ return make_figure( args=locals(), constructor=go.Scattergeo, trace_patch=dict(locationmode=locationmode), ) line_geo.__doc__ = make_docstring(line_geo) def scatter_mapbox( data_frame=None, lat=None, lon=None, color=None, text=None, hover_name=None, hover_data=None, custom_data=None, size=None, animation_frame=None, animation_group=None, category_orders={}, labels={}, color_discrete_sequence=None, color_discrete_map={}, color_continuous_scale=None, range_color=None, color_continuous_midpoint=None, opacity=None, size_max=None, zoom=8, center=None, mapbox_style=None, title=None, template=None, width=None, height=None, ): """ In a Mapbox scatter plot, each row of `data_frame` is represented by a symbol mark on a Mapbox map. """ return make_figure(args=locals(), constructor=go.Scattermapbox) scatter_mapbox.__doc__ = make_docstring(scatter_mapbox) def choropleth_mapbox( data_frame=None, geojson=None, locations=None, color=None, hover_name=None, hover_data=None, custom_data=None, animation_frame=None, animation_group=None, category_orders={}, labels={}, color_continuous_scale=None, range_color=None, color_continuous_midpoint=None, opacity=None, zoom=8, center=None, mapbox_style=None, title=None, template=None, width=None, height=None, ): """ In a Mapbox choropleth map, each row of `data_frame` is represented by a colored region on a Mapbox map. """ return make_figure( args=locals(), constructor=go.Choroplethmapbox, trace_patch=dict( geojson=geojson if not hasattr(geojson, "__geo_interface__") else geojson.__geo_interface__ ), ) choropleth_mapbox.__doc__ = make_docstring(choropleth_mapbox) def density_mapbox( data_frame=None, lat=None, lon=None, z=None, hover_name=None, hover_data=None, custom_data=None, animation_frame=None, animation_group=None, category_orders={}, labels={}, color_continuous_scale=None, range_color=None, color_continuous_midpoint=None, opacity=None, zoom=8, center=None, mapbox_style=None, radius=None, title=None, template=None, width=None, height=None, ): """ In a Mapbox density map, each row of `data_frame` contributes to the intensity of the color of the region around the corresponding point on the map """ return make_figure( args=locals(), constructor=go.Densitymapbox, trace_patch=dict(radius=radius) ) density_mapbox.__doc__ = make_docstring(density_mapbox) def line_mapbox( data_frame=None, lat=None, lon=None, color=None, text=None, hover_name=None, hover_data=None, custom_data=None, line_group=None, animation_frame=None, animation_group=None, category_orders={}, labels={}, color_discrete_sequence=None, color_discrete_map={}, zoom=8, center=None, mapbox_style=None, title=None, template=None, width=None, height=None, ): """ In a Mapbox line plot, each row of `data_frame` is represented as vertex of a polyline mark on a Mapbox map. """ return make_figure(args=locals(), constructor=go.Scattermapbox) line_mapbox.__doc__ = make_docstring(line_mapbox) def scatter_matrix( data_frame=None, dimensions=None, color=None, symbol=None, size=None, hover_name=None, hover_data=None, custom_data=None, category_orders={}, labels={}, color_discrete_sequence=None, color_discrete_map={}, color_continuous_scale=None, range_color=None, color_continuous_midpoint=None, symbol_sequence=None, symbol_map={}, opacity=None, size_max=None, title=None, template=None, width=None, height=None, ): """ In a scatter plot matrix (or SPLOM), each row of `data_frame` is represented by a multiple symbol marks, one in each cell of a grid of 2D scatter plots, which plot each pair of `dimensions` against each other. """ return make_figure( args=locals(), constructor=go.Splom, layout_patch=dict(dragmode="select") ) scatter_matrix.__doc__ = make_docstring(scatter_matrix) def parallel_coordinates( data_frame=None, dimensions=None, color=None, labels={}, color_continuous_scale=None, range_color=None, color_continuous_midpoint=None, title=None, template=None, width=None, height=None, ): """ In a parallel coordinates plot, each row of `data_frame` is represented by a polyline mark which traverses a set of parallel axes, one for each of the `dimensions`. """ return make_figure(args=locals(), constructor=go.Parcoords) parallel_coordinates.__doc__ = make_docstring(parallel_coordinates) def parallel_categories( data_frame=None, dimensions=None, color=None, labels={}, color_continuous_scale=None, range_color=None, color_continuous_midpoint=None, title=None, template=None, width=None, height=None, ): """ In a parallel categories (or parallel sets) plot, each row of `data_frame` is grouped with other rows that share the same values of `dimensions` and then plotted as a polyline mark through a set of parallel axes, one for each of the `dimensions`. """ return make_figure(args=locals(), constructor=go.Parcats) parallel_categories.__doc__ = make_docstring(parallel_categories) def pie( data_frame=None, names=None, values=None, color=None, color_discrete_sequence=None, color_discrete_map={}, hover_name=None, hover_data=None, custom_data=None, labels={}, title=None, template=None, width=None, height=None, opacity=None, hole=None, ): """ In a pie plot, each row of `data_frame` is represented as a sector of a pie. """ if color_discrete_sequence is not None: layout_patch = {"piecolorway": color_discrete_sequence} else: layout_patch = {} return make_figure( args=locals(), constructor=go.Pie, trace_patch=dict(showlegend=(names is not None), hole=hole), layout_patch=layout_patch, ) pie.__doc__ = make_docstring( pie, override_dict=dict( hole=[ "float", "Sets the fraction of the radius to cut out of the pie." "Use this to make a donut chart.", ], ), ) def sunburst( data_frame=None, names=None, values=None, parents=None, ids=None, color=None, color_continuous_scale=None, range_color=None, color_continuous_midpoint=None, color_discrete_sequence=None, color_discrete_map={}, hover_name=None, hover_data=None, custom_data=None, labels={}, title=None, template=None, width=None, height=None, branchvalues=None, maxdepth=None, ): """ A sunburst plot represents hierarchial data as sectors laid out over several levels of concentric rings. """ if color_discrete_sequence is not None: layout_patch = {"sunburstcolorway": color_discrete_sequence} else: layout_patch = {} return make_figure( args=locals(), constructor=go.Sunburst, trace_patch=dict(branchvalues=branchvalues, maxdepth=maxdepth), layout_patch=layout_patch, ) sunburst.__doc__ = make_docstring(sunburst) def treemap( data_frame=None, names=None, values=None, parents=None, ids=None, color=None, color_continuous_scale=None, range_color=None, color_continuous_midpoint=None, color_discrete_sequence=None, color_discrete_map={}, hover_name=None, hover_data=None, custom_data=None, labels={}, title=None, template=None, width=None, height=None, branchvalues=None, maxdepth=None, ): """ A treemap plot represents hierarchial data as nested rectangular sectors. """ if color_discrete_sequence is not None: layout_patch = {"treemapcolorway": color_discrete_sequence} else: layout_patch = {} return make_figure( args=locals(), constructor=go.Treemap, trace_patch=dict(branchvalues=branchvalues, maxdepth=maxdepth), layout_patch=layout_patch, ) treemap.__doc__ = make_docstring(treemap) def funnel( data_frame=None, x=None, y=None, color=None, facet_row=None, facet_col=None, facet_col_wrap=0, hover_name=None, hover_data=None, custom_data=None, text=None, animation_frame=None, animation_group=None, category_orders={}, labels={}, color_discrete_sequence=None, color_discrete_map={}, opacity=None, orientation="h", log_x=False, log_y=False, range_x=None, range_y=None, title=None, template=None, width=None, height=None, ): """ In a funnel plot, each row of `data_frame` is represented as a rectangular sector of a funnel. """ return make_figure( args=locals(), constructor=go.Funnel, trace_patch=dict(opacity=opacity, orientation=orientation), ) funnel.__doc__ = make_docstring(funnel) def funnel_area( data_frame=None, names=None, values=None, color=None, color_discrete_sequence=None, color_discrete_map={}, hover_name=None, hover_data=None, custom_data=None, labels={}, title=None, template=None, width=None, height=None, opacity=None, ): """ In a funnel area plot, each row of `data_frame` is represented as a trapezoidal sector of a funnel. """ if color_discrete_sequence is not None: layout_patch = {"funnelareacolorway": color_discrete_sequence} else: layout_patch = {} return make_figure( args=locals(), constructor=go.Funnelarea, trace_patch=dict(showlegend=(names is not None)), layout_patch=layout_patch, ) funnel_area.__doc__ = make_docstring(funnel_area) plotly-4.4.1+dfsg.orig/plotly/express/__init__.py0000644000175000017500000000347113573717677021432 0ustar noahfxnoahfx""" `plotly_express` is a terse, consistent, high-level wrapper around `plotly` for rapid \ data exploration and figure generation. See the gallery at https://plotly.github.io/plotly_express """ from __future__ import absolute_import from plotly import optional_imports from ._imshow import imshow pd = optional_imports.get_module("pandas") if pd is None: raise ImportError( """\ Plotly express requires pandas to be installed.""" ) from ._chart_types import ( # noqa: F401 scatter, scatter_3d, scatter_polar, scatter_ternary, scatter_mapbox, scatter_geo, line, line_3d, line_polar, line_ternary, line_mapbox, line_geo, area, bar, bar_polar, violin, box, strip, histogram, scatter_matrix, parallel_coordinates, parallel_categories, choropleth, density_contour, density_heatmap, pie, sunburst, treemap, funnel, funnel_area, choropleth_mapbox, density_mapbox, ) from ._core import ( # noqa: F401 set_mapbox_access_token, defaults, get_trendline_results, ) from . import data, colors # noqa: F401 __all__ = [ "scatter", "scatter_3d", "scatter_polar", "scatter_ternary", "scatter_mapbox", "scatter_geo", "scatter_matrix", "density_contour", "density_heatmap", "density_mapbox", "line", "line_3d", "line_polar", "line_ternary", "line_mapbox", "line_geo", "parallel_coordinates", "parallel_categories", "area", "bar", "bar_polar", "violin", "box", "strip", "histogram", "choropleth", "choropleth_mapbox", "pie", "sunburst", "treemap", "funnel", "funnel_area", "imshow", "data", "colors", "set_mapbox_access_token", "get_trendline_results", ] plotly-4.4.1+dfsg.orig/plotly/express/colors.py0000644000175000017500000000010313525746125021144 0ustar noahfxnoahfxfrom __future__ import absolute_import from plotly.colors import * plotly-4.4.1+dfsg.orig/plotly/express/_imshow.py0000644000175000017500000001421113573717677021332 0ustar noahfxnoahfximport plotly.graph_objs as go from _plotly_utils.basevalidators import ColorscaleValidator from ._core import apply_default_cascade import numpy as np _float_types = [] # Adapted from skimage.util.dtype _integer_types = ( np.byte, np.ubyte, # 8 bits np.short, np.ushort, # 16 bits np.intc, np.uintc, # 16 or 32 or 64 bits np.int_, np.uint, # 32 or 64 bits np.longlong, np.ulonglong, ) # 64 bits _integer_ranges = {t: (np.iinfo(t).min, np.iinfo(t).max) for t in _integer_types} def _vectorize_zvalue(z): if z is None: return z elif np.isscalar(z): return [z] * 3 + [1] elif len(z) == 1: return list(z) * 3 + [1] elif len(z) == 3: return list(z) + [1] elif len(z) == 4: return z else: raise ValueError( "zmax can be a scalar, or an iterable of length 1, 3 or 4. " "A value of %s was passed for zmax." % str(z) ) def _infer_zmax_from_type(img): dt = img.dtype.type rtol = 1.05 if dt in _integer_types: return _integer_ranges[dt][1] else: im_max = img[np.isfinite(img)].max() if im_max <= 1 * rtol: return 1 elif im_max <= 255 * rtol: return 255 elif im_max <= 65535 * rtol: return 65535 else: return 2 ** 32 def imshow( img, zmin=None, zmax=None, origin=None, color_continuous_scale=None, color_continuous_midpoint=None, range_color=None, title=None, template=None, width=None, height=None, ): """ Display an image, i.e. data on a 2D regular raster. Parameters ---------- img: array-like image The image data. Supported array shapes are - (M, N): an image with scalar data. The data is visualized using a colormap. - (M, N, 3): an image with RGB values. - (M, N, 4): an image with RGBA values, i.e. including transparency. zmin, zmax : scalar or iterable, optional zmin and zmax define the scalar range that the colormap covers. By default, zmin and zmax correspond to the min and max values of the datatype for integer datatypes (ie [0-255] for uint8 images, [0, 65535] for uint16 images, etc.). For a multichannel image of floats, the max of the image is computed and zmax is the smallest power of 256 (1, 255, 65535) greater than this max value, with a 5% tolerance. For a single-channel image, the max of the image is used. origin : str, 'upper' or 'lower' (default 'upper') position of the [0, 0] pixel of the image array, in the upper left or lower left corner. The convention 'upper' is typically used for matrices and images. color_continuous_scale : str or list of str colormap used to map scalar data to colors (for a 2D image). This parameter is not used for RGB or RGBA images. If a string is provided, it should be the name of a known color scale, and if a list is provided, it should be a list of CSS- compatible colors. color_continuous_midpoint : number If set, computes the bounds of the continuous color scale to have the desired midpoint. range_color : list of two numbers If provided, overrides auto-scaling on the continuous color scale, including overriding `color_continuous_midpoint`. Also overrides zmin and zmax. Used only for single-channel images. title : str The figure title. template : str or dict or plotly.graph_objects.layout.Template instance The figure template name or definition. width : number The figure width in pixels. height: number The figure height in pixels, defaults to 600. Returns ------- fig : graph_objects.Figure containing the displayed image See also -------- plotly.graph_objects.Image : image trace plotly.graph_objects.Heatmap : heatmap trace Notes ----- In order to update and customize the returned figure, use `go.Figure.update_traces` or `go.Figure.update_layout`. """ args = locals() apply_default_cascade(args) img = np.asanyarray(img) # Cast bools to uint8 (also one byte) if img.dtype == np.bool: img = 255 * img.astype(np.uint8) # For 2d data, use Heatmap trace if img.ndim == 2: trace = go.Heatmap(z=img, coloraxis="coloraxis1") autorange = True if origin == "lower" else "reversed" layout = dict( xaxis=dict(scaleanchor="y", constrain="domain"), yaxis=dict(autorange=autorange, constrain="domain"), ) colorscale_validator = ColorscaleValidator("colorscale", "imshow") if zmin is not None and zmax is None: zmax = img.max() if zmax is not None and zmin is None: zmin = img.min() range_color = range_color or [zmin, zmax] layout["coloraxis1"] = dict( colorscale=colorscale_validator.validate_coerce( args["color_continuous_scale"] ), cmid=color_continuous_midpoint, cmin=range_color[0], cmax=range_color[1], ) # For 2D+RGB data, use Image trace elif img.ndim == 3 and img.shape[-1] in [3, 4]: if zmax is None and img.dtype is not np.uint8: zmax = _infer_zmax_from_type(img) zmin, zmax = _vectorize_zvalue(zmin), _vectorize_zvalue(zmax) trace = go.Image(z=img, zmin=zmin, zmax=zmax) layout = {} if origin == "lower": layout["yaxis"] = dict(autorange=True) else: raise ValueError( "px.imshow only accepts 2D single-channel, RGB or RGBA images. " "An image of shape %s was provided" % str(img.shape) ) layout_patch = dict() for v in ["title", "height", "width"]: if args[v]: layout_patch[v] = args[v] if "title" not in layout_patch and args["template"].layout.margin.t is None: layout_patch["margin"] = {"t": 60} fig = go.Figure(data=trace, layout=layout) fig.update_layout(layout_patch) fig.update_layout(template=args["template"], overwrite=True) return fig plotly-4.4.1+dfsg.orig/plotly/express/_doc.py0000644000175000017500000005675013573717677020607 0ustar noahfxnoahfximport inspect from textwrap import TextWrapper # TODO contents of columns # TODO explain categorical # TODO handle color # TODO handle details of box/violin/histogram # TODO handle details of column selection with `dimensions` # TODO document "or `None`, default `None`" in various places # TODO standardize positioning and casing of 'default' colref_type = "str or int or Series or array-like" colref_desc = "Either a name of a column in `data_frame`, or a pandas Series or array_like object." colref_list_type = "list of str or int, or Series or array-like" colref_list_desc = ( "Either names of columns in `data_frame`, or pandas Series, or array_like objects" ) docs = dict( data_frame=[ "DataFrame or array-like or dict", "This argument needs to be passed for column names (and not keyword names) to be used.", "Array-like and dict are tranformed internally to a pandas DataFrame.", "Optional: if missing, a DataFrame gets constructed under the hood using the other arguments.", ], x=[ colref_type, colref_desc, "Values from this column or array_like are used to position marks along the x axis in cartesian coordinates.", "For horizontal histograms, these values are used as inputs to `histfunc`.", ], y=[ colref_type, colref_desc, "Values from this column or array_like are used to position marks along the y axis in cartesian coordinates.", "For vertical histograms, these values are used as inputs to `histfunc`.", ], z=[ colref_type, colref_desc, "Values from this column or array_like are used to position marks along the z axis in cartesian coordinates.", "For `density_heatmap` and `density_contour` these values are used as the inputs to `histfunc`.", ], a=[ colref_type, colref_desc, "Values from this column or array_like are used to position marks along the a axis in ternary coordinates.", ], b=[ colref_type, colref_desc, "Values from this column or array_like are used to position marks along the b axis in ternary coordinates.", ], c=[ colref_type, colref_desc, "Values from this column or array_like are used to position marks along the c axis in ternary coordinates.", ], r=[ colref_type, colref_desc, "Values from this column or array_like are used to position marks along the radial axis in polar coordinates.", ], theta=[ colref_type, colref_desc, "Values from this column or array_like are used to position marks along the angular axis in polar coordinates.", ], values=[ colref_type, colref_desc, "Values from this column or array_like are used to set values associated to sectors.", ], parents=[ colref_type, colref_desc, "Values from this column or array_like are used as parents in sunburst and treemap charts.", ], ids=[ colref_type, colref_desc, "Values from this column or array_like are used to set ids of sectors", ], lat=[ colref_type, colref_desc, "Values from this column or array_like are used to position marks according to latitude on a map.", ], lon=[ colref_type, colref_desc, "Values from this column or array_like are used to position marks according to longitude on a map.", ], locations=[ colref_type, colref_desc, "Values from this column or array_like are to be interpreted according to `locationmode` and mapped to longitude/latitude.", ], dimensions=[ colref_list_type, colref_list_desc, "Values from these columns are used for multidimensional visualization.", ], error_x=[ colref_type, colref_desc, "Values from this column or array_like are used to size x-axis error bars.", "If `error_x_minus` is `None`, error bars will be symmetrical, otherwise `error_x` is used for the positive direction only.", ], error_x_minus=[ colref_type, colref_desc, "Values from this column or array_like are used to size x-axis error bars in the negative direction.", "Ignored if `error_x` is `None`.", ], error_y=[ colref_type, colref_desc, "Values from this column or array_like are used to size y-axis error bars.", "If `error_y_minus` is `None`, error bars will be symmetrical, otherwise `error_y` is used for the positive direction only.", ], error_y_minus=[ colref_type, colref_desc, "Values from this column or array_like are used to size y-axis error bars in the negative direction.", "Ignored if `error_y` is `None`.", ], error_z=[ colref_type, colref_desc, "Values from this column or array_like are used to size z-axis error bars.", "If `error_z_minus` is `None`, error bars will be symmetrical, otherwise `error_z` is used for the positive direction only.", ], error_z_minus=[ colref_type, colref_desc, "Values from this column or array_like are used to size z-axis error bars in the negative direction.", "Ignored if `error_z` is `None`.", ], color=[ colref_type, colref_desc, "Values from this column or array_like are used to assign color to marks.", ], opacity=["float", "Value between 0 and 1. Sets the opacity for markers."], line_dash=[ colref_type, colref_desc, "Values from this column or array_like are used to assign dash-patterns to lines.", ], line_group=[ colref_type, colref_desc, "Values from this column or array_like are used to group rows of `data_frame` into lines.", ], symbol=[ colref_type, colref_desc, "Values from this column or array_like are used to assign symbols to marks.", ], size=[ colref_type, colref_desc, "Values from this column or array_like are used to assign mark sizes.", ], radius=["int (default is 30)", "Sets the radius of influence of each point.",], hover_name=[ colref_type, colref_desc, "Values from this column or array_like appear in bold in the hover tooltip.", ], hover_data=[ colref_list_type, colref_list_desc, "Values from these columns appear as extra data in the hover tooltip.", ], custom_data=[ colref_list_type, colref_list_desc, "Values from these columns are extra data, to be used in widgets or Dash callbacks for example. This data is not user-visible but is included in events emitted by the figure (lasso selection etc.)", ], text=[ colref_type, colref_desc, "Values from this column or array_like appear in the figure as text labels.", ], names=[ colref_type, colref_desc, "Values from this column or array_like are used as labels for sectors.", ], locationmode=[ "str", "One of 'ISO-3', 'USA-states', or 'country names'", "Determines the set of locations used to match entries in `locations` to regions on the map.", ], facet_row=[ colref_type, colref_desc, "Values from this column or array_like are used to assign marks to facetted subplots in the vertical direction.", ], facet_col=[ colref_type, colref_desc, "Values from this column or array_like are used to assign marks to facetted subplots in the horizontal direction.", ], facet_col_wrap=[ "int", "Maximum number of facet columns.", "Wraps the column variable at this width, so that the column facets span multiple rows.", "Ignored if 0, and forced to 0 if `facet_row` or a `marginal` is set.", ], animation_frame=[ colref_type, colref_desc, "Values from this column or array_like are used to assign marks to animation frames.", ], animation_group=[ colref_type, colref_desc, "Values from this column or array_like are used to provide object-constancy across animation frames: rows with matching `animation_group`s will be treated as if they describe the same object in each frame.", ], symbol_sequence=[ "list of str", "Strings should define valid plotly.js symbols.", "When `symbol` is set, values in that column are assigned symbols by cycling through `symbol_sequence` in the order described in `category_orders`, unless the value of `symbol` is a key in `symbol_map`.", ], symbol_map=[ "dict with str keys and str values (default `{}`)", "String values should define plotly.js symbols", "Used to override `symbol_sequence` to assign a specific symbols to marks corresponding with specific values.", "Keys in `symbol_map` should be values in the column denoted by `symbol`.", ], line_dash_map=[ "dict with str keys and str values (default `{}`)", "Strings values define plotly.js dash-patterns.", "Used to override `line_dash_sequences` to assign a specific dash-patterns to lines corresponding with specific values.", "Keys in `line_dash_map` should be values in the column denoted by `line_dash`.", ], line_dash_sequence=[ "list of str", "Strings should define valid plotly.js dash-patterns.", "When `line_dash` is set, values in that column are assigned dash-patterns by cycling through `line_dash_sequence` in the order described in `category_orders`, unless the value of `line_dash` is a key in `line_dash_map`.", ], color_discrete_sequence=[ "list of str", "Strings should define valid CSS-colors.", "When `color` is set and the values in the corresponding column are not numeric, values in that column are assigned colors by cycling through `color_discrete_sequence` in the order described in `category_orders`, unless the value of `color` is a key in `color_discrete_map`.", "Various useful color sequences are available in the `plotly_express.colors` submodules, specifically `plotly_express.colors.qualitative`.", ], color_discrete_map=[ "dict with str keys and str values (default `{}`)", "String values should define valid CSS-colors", "Used to override `color_discrete_sequence` to assign a specific colors to marks corresponding with specific values.", "Keys in `color_discrete_map` should be values in the column denoted by `color`.", ], color_continuous_scale=[ "list of str", "Strings should define valid CSS-colors", "This list is used to build a continuous color scale when the column denoted by `color` contains numeric data.", "Various useful color scales are available in the `plotly_express.colors` submodules, specifically `plotly_express.colors.sequential`, `plotly_express.colors.diverging` and `plotly_express.colors.cyclical`.", ], color_continuous_midpoint=[ "number (default `None`)", "If set, computes the bounds of the continuous color scale to have the desired midpoint.", "Setting this value is recommended when using `plotly_express.colors.diverging` color scales as the inputs to `color_continuous_scale`.", ], size_max=["int (default `20`)", "Set the maximum mark size when using `size`."], log_x=[ "boolean (default `False`)", "If `True`, the x-axis is log-scaled in cartesian coordinates.", ], log_y=[ "boolean (default `False`)", "If `True`, the y-axis is log-scaled in cartesian coordinates.", ], log_z=[ "boolean (default `False`)", "If `True`, the z-axis is log-scaled in cartesian coordinates.", ], log_r=[ "boolean (default `False`)", "If `True`, the radial axis is log-scaled in polar coordinates.", ], range_x=[ "list of two numbers", "If provided, overrides auto-scaling on the x-axis in cartesian coordinates.", ], range_y=[ "list of two numbers", "If provided, overrides auto-scaling on the y-axis in cartesian coordinates.", ], range_z=[ "list of two numbers", "If provided, overrides auto-scaling on the z-axis in cartesian coordinates.", ], range_color=[ "list of two numbers", "If provided, overrides auto-scaling on the continuous color scale.", ], range_r=[ "list of two numbers", "If provided, overrides auto-scaling on the radial axis in polar coordinates.", ], range_theta=[ "list of two numbers", "If provided, overrides auto-scaling on the angular axis in polar coordinates.", ], title=["str", "The figure title."], template=[ "or dict or plotly.graph_objects.layout.Template instance", "The figure template name or definition.", ], width=["int (default `None`)", "The figure width in pixels."], height=["int (default `600`)", "The figure height in pixels."], labels=[ "dict with str keys and str values (default `{}`)", "By default, column names are used in the figure for axis titles, legend entries and hovers.", "This parameter allows this to be overridden.", "The keys of this dict should correspond to column names, and the values should correspond to the desired label to be displayed.", ], category_orders=[ "dict with str keys and list of str values (default `{}`)", "By default, in Python 3.6+, the order of categorical values in axes, legends and facets depends on the order in which these values are first encountered in `data_frame` (and no order is guaranteed by default in Python below 3.6).", "This parameter is used to force a specific ordering of values per column.", "The keys of this dict should correspond to column names, and the values should be lists of strings corresponding to the specific display order desired.", ], marginal=[ "str", "One of `'rug'`, `'box'`, `'violin'`, or `'histogram'`.", "If set, a subplot is drawn alongside the main plot, visualizing the distribution.", ], marginal_x=[ "str", "One of `'rug'`, `'box'`, `'violin'`, or `'histogram'`.", "If set, a horizontal subplot is drawn above the main plot, visualizing the x-distribution.", ], marginal_y=[ "str", "One of `'rug'`, `'box'`, `'violin'`, or `'histogram'`.", "If set, a vertical subplot is drawn to the right of the main plot, visualizing the y-distribution.", ], trendline=[ "str", "One of `'ols'` or `'lowess'`.", "If `'ols'`, an Ordinary Least Squares regression line will be drawn for each discrete-color/symbol group.", "If `'lowess`', a Locally Weighted Scatterplot Smoothing line will be drawn for each discrete-color/symbol group.", ], trendline_color_override=[ "str", "Valid CSS color.", "If provided, and if `trendline` is set, all trendlines will be drawn in this color.", ], render_mode=[ "str", "One of `'auto'`, `'svg'` or `'webgl'`, default `'auto'`", "Controls the browser API used to draw marks.", "`'svg`' is appropriate for figures of less than 1000 data points, and will allow for fully-vectorized output.", "`'webgl'` is likely necessary for acceptable performance above 1000 points but rasterizes part of the output. ", "`'auto'` uses heuristics to choose the mode.", ], direction=[ "str", "One of '`counterclockwise'` or `'clockwise'`. Default is `'clockwise'`", "Sets the direction in which increasing values of the angular axis are drawn.", ], start_angle=[ "int (default `90`)", "Sets start angle for the angular axis, with 0 being due east and 90 being due north.", ], histfunc=[ "str (default `'count'`)", "One of `'count'`, `'sum'`, `'avg'`, `'min'`, or `'max'`." "Function used to aggregate values for summarization (note: can be normalized with `histnorm`).", "The arguments to this function for `histogram` are the values of `y` if `orientation` is `'v'`,", "otherwise the arguements are the values of `x`.", "The arguments to this function for `density_heatmap` and `density_contour` are the values of `z`.", ], histnorm=[ "str (default `None`)", "One of `'percent'`, `'probability'`, `'density'`, or `'probability density'`", "If `None`, the output of `histfunc` is used as is.", "If `'probability'`, the output of `histfunc` for a given bin is divided by the sum of the output of `histfunc` for all bins.", "If `'percent'`, the output of `histfunc` for a given bin is divided by the sum of the output of `histfunc` for all bins and multiplied by 100.", "If `'density'`, the output of `histfunc` for a given bin is divided by the size of the bin.", "If `'probability density'`, the output of `histfunc` for a given bin is normalized such that it corresponds to the probability that a random event whose distribution is described by the output of `histfunc` will fall into that bin.", ], barnorm=[ "str (default `None`)", "One of `'fraction'` or `'percent'`.", "If `'fraction'`, the value of each bar is divided by the sum of all values at that location coordinate.", "`'percent'` is the same but multiplied by 100 to show percentages.", "`None` will stack up all values at each location coordinate.", ], groupnorm=[ "str (default `None`)", "One of `'fraction'` or `'percent'`.", "If `'fraction'`, the value of each point is divided by the sum of all values at that location coordinate.", "`'percent'` is the same but multiplied by 100 to show percentages.", "`None` will stack up all values at each location coordinate.", ], barmode=[ "str (default `'relative'`)", "One of `'group'`, `'overlay'` or `'relative'`", "In `'relative'` mode, bars are stacked above zero for positive values and below zero for negative values.", "In `'overlay'` mode, bars are drawn on top of one another.", "In `'group'` mode, bars are placed beside each other.", ], boxmode=[ "str (default `'group'`)", "One of `'group'` or `'overlay'`", "In `'overlay'` mode, boxes are on drawn top of one another.", "In `'group'` mode, baxes are placed beside each other.", ], violinmode=[ "str (default `'group'`)", "One of `'group'` or `'overlay'`", "In `'overlay'` mode, violins are on drawn top of one another.", "In `'group'` mode, violins are placed beside each other.", ], stripmode=[ "str (default `'group'`)", "One of `'group'` or `'overlay'`", "In `'overlay'` mode, strips are on drawn top of one another.", "In `'group'` mode, strips are placed beside each other.", ], zoom=["int (default `8`)", "Between 0 and 20.", "Sets map zoom level."], orientation=[ "str (default `'v'`)", "One of `'h'` for horizontal or `'v'` for vertical)", ], line_close=[ "boolean (default `False`)", "If `True`, an extra line segment is drawn between the first and last point.", ], line_shape=["str (default `'linear'`)", "One of `'linear'` or `'spline'`."], scope=[ "str (default `'world'`).", "One of `'world'`, `'usa'`, `'europe'`, `'asia'`, `'africa'`, `'north america'`, or `'south america'`)" "Default is `'world'` unless `projection` is set to `'albers usa'`, which forces `'usa'`.", ], projection=[ "str ", "One of `'equirectangular'`, `'mercator'`, `'orthographic'`, `'natural earth'`, `'kavrayskiy7'`, `'miller'`, `'robinson'`, `'eckert4'`, `'azimuthal equal area'`, `'azimuthal equidistant'`, `'conic equal area'`, `'conic conformal'`, `'conic equidistant'`, `'gnomonic'`, `'stereographic'`, `'mollweide'`, `'hammer'`, `'transverse mercator'`, `'albers usa'`, `'winkel tripel'`, `'aitoff'`, or `'sinusoidal'`" "Default depends on `scope`.", ], center=[ "dict", "Dict keys are `'lat'` and `'lon'`", "Sets the center point of the map.", ], mapbox_style=[ "str (default `'basic'`, needs Mapbox API token)", "Identifier of base map style, some of which require a Mapbox API token to be set using `plotly.express.set_mapbox_access_token()`.", "Allowed values which do not require a Mapbox API token are `'open-street-map'`, `'white-bg'`, `'carto-positron'`, `'carto-darkmatter'`, `'stamen-terrain'`, `'stamen-toner'`, `'stamen-watercolor'`.", "Allowed values which do require a Mapbox API token are `'basic'`, `'streets'`, `'outdoors'`, `'light'`, `'dark'`, `'satellite'`, `'satellite-streets'`.", ], points=[ "str or boolean (default `'outliers'`)", "One of `'outliers'`, `'suspectedoutliers'`, `'all'`, or `False`.", "If `'outliers'`, only the sample points lying outside the whiskers are shown.", "If `'suspectedoutliers'`, all outlier points are shown and those less than 4*Q1-3*Q3 or greater than 4*Q3-3*Q1 are highlighted with the marker's `'outliercolor'`.", "If `'outliers'`, only the sample points lying outside the whiskers are shown.", "If `'all'`, all sample points are shown.", "If `False`, no sample points are shown and the whiskers extend to the full range of the sample.", ], box=["boolean (default `False`)", "If `True`, boxes are drawn inside the violins."], notched=["boolean (default `False`)", "If `True`, boxes are drawn with notches."], geojson=[ "GeoJSON-formatted dict", "Must contain a Polygon feature collection, with IDs, which are references from `locations`.", ], cumulative=[ "boolean (default `False`)", "If `True`, histogram values are cumulative.", ], nbins=["int", "Positive integer.", "Sets the number of bins."], nbinsx=["int", "Positive integer.", "Sets the number of bins along the x axis."], nbinsy=["int", "Positive integer.", "Sets the number of bins along the y axis."], branchvalues=[ "str", "'total' or 'remainder'", "Determines how the items in `values` are summed. When" "set to 'total', items in `values` are taken to be value" "of all its descendants. When set to 'remainder', items" "in `values` corresponding to the root and the branches" ":sectors are taken to be the extra part not part of the" "sum of the values at their leaves.", ], maxdepth=[ "int", "Positive integer", "Sets the number of rendered sectors from any given `level`. Set `maxdepth` to -1 to render all the" "levels in the hierarchy.", ], ) def make_docstring(fn, override_dict={}): tw = TextWrapper(width=75, initial_indent=" ", subsequent_indent=" ") result = (fn.__doc__ or "") + "\nParameters\n----------\n" for param in inspect.getargspec(fn)[0]: if override_dict.get(param): param_doc = override_dict[param] else: param_doc = docs[param] param_desc_list = param_doc[1:] param_desc = ( tw.fill(" ".join(param_desc_list or "")) if param in docs else "(documentation missing from map)" ) param_type = param_doc[0] result += "%s: %s\n%s\n" % (param, param_type, param_desc) result += "\nReturns\n-------\n" result += " A `Figure` object." return result plotly-4.4.1+dfsg.orig/plotly/grid_objs.py0000644000175000017500000000017113525746125020121 0ustar noahfxnoahfxfrom __future__ import absolute_import from _plotly_future_ import _chart_studio_error _chart_studio_error("grid_objs") plotly-4.4.1+dfsg.orig/plotly/widgets.py0000644000175000017500000000016713525746125017632 0ustar noahfxnoahfxfrom __future__ import absolute_import from _plotly_future_ import _chart_studio_error _chart_studio_error("widgets") plotly-4.4.1+dfsg.orig/plotly/io/0000755000175000017500000000000013573746613016222 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotly/io/_orca.py0000644000175000017500000014736513573717677017707 0ustar noahfxnoahfxfrom __future__ import absolute_import import atexit import json import os import socket import subprocess import sys import threading import warnings from copy import copy from contextlib import contextmanager import retrying from six import string_types import _plotly_utils.utils import plotly from plotly.files import PLOTLY_DIR, ensure_writable_plotly_dir from plotly.io._utils import validate_coerce_fig_to_dict from plotly.optional_imports import get_module psutil = get_module("psutil") # Valid image format constants # ---------------------------- valid_formats = ("png", "jpeg", "webp", "svg", "pdf", "eps") format_conversions = {fmt: fmt for fmt in valid_formats} format_conversions.update({"jpg": "jpeg"}) # Utility functions # ----------------- def raise_format_value_error(val): raise ValueError( """ Invalid value of type {typ} receive as an image format specification. Received value: {v} An image format must be specified as one of the following string values: {valid_formats}""".format( typ=type(val), v=val, valid_formats=sorted(format_conversions.keys()) ) ) def validate_coerce_format(fmt): """ Validate / coerce a user specified image format, and raise an informative exception if format is invalid. Parameters ---------- fmt A value that may or may not be a valid image format string. Returns ------- str or None A valid image format string as supported by orca. This may not be identical to the input image designation. For example, the resulting string will always be lower case and 'jpg' is converted to 'jpeg'. If the input format value is None, then no exception is raised and None is returned. Raises ------ ValueError if the input `fmt` cannot be interpreted as a valid image format. """ # Let None pass through if fmt is None: return None # Check format type if not isinstance(fmt, string_types) or not fmt: raise_format_value_error(fmt) # Make lower case fmt = fmt.lower() # Remove leading period, if any. # For example '.png' is accepted and converted to 'png' if fmt[0] == ".": fmt = fmt[1:] # Check string value if fmt not in format_conversions: raise_format_value_error(fmt) # Return converted string specification return format_conversions[fmt] def find_open_port(): """ Use the socket module to find an open port. Returns ------- int An open port """ s = socket.socket() s.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1) s.bind(("", 0)) _, port = s.getsockname() s.close() return port def which_py2(cmd, mode=os.F_OK | os.X_OK, path=None): """ Backport (unmodified) of shutil.which command from Python 3.6 Remove this when Python 2 support is dropped Given a command, mode, and a PATH string, return the path which conforms to the given mode on the PATH, or None if there is no such file. `mode` defaults to os.F_OK | os.X_OK. `path` defaults to the result of os.environ.get("PATH"), or can be overridden with a custom search path. """ # Check that a given file can be accessed with the correct mode. # Additionally check that `file` is not a directory, as on Windows # directories pass the os.access check. def _access_check(fn, mode): return os.path.exists(fn) and os.access(fn, mode) and not os.path.isdir(fn) # If we're given a path with a directory part, look it up directly rather # than referring to PATH directories. This includes checking relative to # the current directory, e.g. ./script if os.path.dirname(cmd): if _access_check(cmd, mode): return cmd return None if path is None: path = os.environ.get("PATH", os.defpath) if not path: return None path = path.split(os.pathsep) if sys.platform == "win32": # The current directory takes precedence on Windows. if not os.curdir in path: path.insert(0, os.curdir) # PATHEXT is necessary to check on Windows. pathext = os.environ.get("PATHEXT", "").split(os.pathsep) # See if the given file matches any of the expected path extensions. # This will allow us to short circuit when given "python.exe". # If it does match, only test that one, otherwise we have to try # others. if any(cmd.lower().endswith(ext.lower()) for ext in pathext): files = [cmd] else: files = [cmd + ext for ext in pathext] else: # On other platforms you don't have things like PATHEXT to tell you # what file suffixes are executable, so just pass on cmd as-is. files = [cmd] seen = set() for dir in path: normdir = os.path.normcase(dir) if not normdir in seen: seen.add(normdir) for thefile in files: name = os.path.join(dir, thefile) if _access_check(name, mode): return name return None def which(cmd): """ Return the absolute path of the input executable string, based on the user's current PATH variable. This is a wrapper for shutil.which that is compatible with Python 2. Parameters ---------- cmd: str String containing the name of an executable on the user's path. Returns ------- str or None String containing the absolute path of the executable, or None if the executable was not found. """ if sys.version_info > (3, 0): import shutil return shutil.which(cmd) else: return which_py2(cmd) # Orca configuration class # ------------------------ class OrcaConfig(object): """ Singleton object containing the current user defined configuration properties for orca. These parameters may optionally be saved to the user's ~/.plotly directory using the `save` method, in which case they are automatically restored in future sessions. """ def __init__(self): # Initialize properties dict self._props = {} # Compute absolute path to the 'plotly/package_data/' directory root_dir = os.path.dirname(os.path.abspath(plotly.__file__)) self.package_dir = os.path.join(root_dir, "package_data") # Load pre-existing configuration self.reload(warn=False) # Compute constants plotlyjs = os.path.join(self.package_dir, "plotly.min.js") self._constants = { "plotlyjs": plotlyjs, "config_file": os.path.join(PLOTLY_DIR, ".orca"), } def restore_defaults(self, reset_server=True): """ Reset all orca configuration properties to their default values """ self._props = {} if reset_server: # Server must restart before setting is active reset_status() def update(self, d={}, **kwargs): """ Update one or more properties from a dict or from input keyword arguments. Parameters ---------- d: dict Dictionary from property names to new property values. kwargs Named argument value pairs where the name is a configuration property name and the value is the new property value. Returns ------- None Examples -------- Update configuration properties using a dictionary >>> import plotly.io as pio >>> pio.orca.config.update({'timeout': 30, 'default_format': 'svg'}) Update configuration properties using keyword arguments >>> pio.orca.config.update(timeout=30, default_format='svg'}) """ # Combine d and kwargs if not isinstance(d, dict): raise ValueError( """ The first argument to update must be a dict, \ but received value of type {typ}l Received value: {val}""".format( typ=type(d), val=d ) ) updates = copy(d) updates.update(kwargs) # Validate keys for k in updates: if k not in self._props: raise ValueError("Invalid property name: {k}".format(k=k)) # Apply keys for k, v in updates.items(): setattr(self, k, v) def reload(self, warn=True): """ Reload orca settings from ~/.plotly/.orca, if any. Note: Settings are loaded automatically when plotly is imported. This method is only needed if the setting are changed by some outside process (e.g. a text editor) during an interactive session. Parameters ---------- warn: bool If True, raise informative warnings if settings cannot be restored. If False, do not raise warnings if setting cannot be restored. Returns ------- None """ if os.path.exists(self.config_file): # ### Load file into a string ### try: with open(self.config_file, "r") as f: orca_str = f.read() except: if warn: warnings.warn( """\ Unable to read orca configuration file at {path}""".format( path=self.config_file ) ) return # ### Parse as JSON ### try: orca_props = json.loads(orca_str) except ValueError: if warn: warnings.warn( """\ Orca configuration file at {path} is not valid JSON""".format( path=self.config_file ) ) return # ### Update _props ### for k, v in orca_props.items(): self._props[k] = v elif warn: warnings.warn( """\ Orca configuration file at {path} not found""".format( path=self.config_file ) ) def save(self): """ Attempt to save current settings to disk, so that they are automatically restored for future sessions. This operation requires write access to the path returned by in the `config_file` property. Returns ------- None """ if ensure_writable_plotly_dir(): with open(self.config_file, "w") as f: json.dump(self._props, f, indent=4) else: warnings.warn( """\ Failed to write orca configuration file at '{path}'""".format( path=self.config_file ) ) @property def server_url(self): """ The server URL to use for an external orca server, or None if orca should be managed locally Overrides executable, port, timeout, mathjax, topojson, and mapbox_access_token Returns ------- str or None """ return self._props.get("server_url", None) @server_url.setter def server_url(self, val): if val is None: self._props.pop("server_url", None) return if not isinstance(val, str): raise ValueError( """ The server_url property must be a string, but received value of type {typ}. Received value: {val}""".format( typ=type(val), val=val ) ) if not val.startswith("http://") and not val.startswith("https://"): val = "http://" + val shutdown_server() self.executable = None self.port = None self.timeout = None self.mathjax = None self.topojson = None self.mapbox_access_token = None self._props["server_url"] = val @property def port(self): """ The specific port to use to communicate with the orca server, or None if the port is to be chosen automatically. If an orca server is active, the port in use is stored in the plotly.io.orca.status.port property. Returns ------- int or None """ return self._props.get("port", None) @port.setter def port(self, val): if val is None: self._props.pop("port", None) return if not isinstance(val, int): raise ValueError( """ The port property must be an integer, but received value of type {typ}. Received value: {val}""".format( typ=type(val), val=val ) ) self._props["port"] = val @property def executable(self): """ The name or full path of the orca executable. - If a name (e.g. 'orca'), then it should be the name of an orca executable on the PATH. The directories on the PATH can be displayed by running the following command: >>> import os >>> print(os.environ.get('PATH').replace(os.pathsep, os.linesep)) - If a full path (e.g. '/path/to/orca'), then it should be the full path to an orca executable. In this case the executable does not need to reside on the PATH. If an orca server has been validated, then the full path to the validated orca executable is stored in the plotly.io.orca.status.executable property. Returns ------- str """ executable_list = self._props.get("executable_list", ["orca"]) if executable_list is None: return None else: return " ".join(executable_list) @executable.setter def executable(self, val): if val is None: self._props.pop("executable", None) else: if not isinstance(val, string_types): raise ValueError( """ The executable property must be a string, but received value of type {typ}. Received value: {val}""".format( typ=type(val), val=val ) ) if isinstance(val, string_types): val = [val] self._props["executable_list"] = val # Server and validation must restart before setting is active reset_status() @property def timeout(self): """ The number of seconds of inactivity required before the orca server is shut down. For example, if timeout is set to 20, then the orca server will shutdown once is has not been used for at least 20 seconds. If timeout is set to None, then the server will not be automatically shut down due to inactivity. Regardless of the value of timeout, a running orca server may be manually shut down like this: >>> import plotly.io as pio >>> pio.orca.shutdown_server() Returns ------- int or float or None """ return self._props.get("timeout", None) @timeout.setter def timeout(self, val): if val is None: self._props.pop("timeout", None) else: if not isinstance(val, (int, float)): raise ValueError( """ The timeout property must be a number, but received value of type {typ}. Received value: {val}""".format( typ=type(val), val=val ) ) self._props["timeout"] = val # Server must restart before setting is active shutdown_server() @property def default_width(self): """ The default width to use on image export. This value is only applied if no width value is supplied to the plotly.io to_image or write_image functions. Returns ------- int or None """ return self._props.get("default_width", None) @default_width.setter def default_width(self, val): if val is None: self._props.pop("default_width", None) return if not isinstance(val, int): raise ValueError( """ The default_width property must be an int, but received value of type {typ}. Received value: {val}""".format( typ=type(val), val=val ) ) self._props["default_width"] = val @property def default_height(self): """ The default height to use on image export. This value is only applied if no height value is supplied to the plotly.io to_image or write_image functions. Returns ------- int or None """ return self._props.get("default_height", None) @default_height.setter def default_height(self, val): if val is None: self._props.pop("default_height", None) return if not isinstance(val, int): raise ValueError( """ The default_height property must be an int, but received value of type {typ}. Received value: {val}""".format( typ=type(val), val=val ) ) self._props["default_height"] = val @property def default_format(self): """ The default image format to use on image export. Valid image formats strings are: - 'png' - 'jpg' or 'jpeg' - 'webp' - 'svg' - 'pdf' - 'eps' (Requires the poppler library to be installed) This value is only applied if no format value is supplied to the plotly.io to_image or write_image functions. Returns ------- str or None """ return self._props.get("default_format", "png") @default_format.setter def default_format(self, val): if val is None: self._props.pop("default_format", None) return val = validate_coerce_format(val) self._props["default_format"] = val @property def default_scale(self): """ The default image scaling factor to use on image export. This value is only applied if no scale value is supplied to the plotly.io to_image or write_image functions. Returns ------- int or None """ return self._props.get("default_scale", 1) @default_scale.setter def default_scale(self, val): if val is None: self._props.pop("default_scale", None) return if not isinstance(val, (int, float)): raise ValueError( """ The default_scale property must be a number, but received value of type {typ}. Received value: {val}""".format( typ=type(val), val=val ) ) self._props["default_scale"] = val @property def topojson(self): """ Path to the topojson files needed to render choropleth traces. If None, topojson files from the plot.ly CDN are used. Returns ------- str """ return self._props.get("topojson", None) @topojson.setter def topojson(self, val): if val is None: self._props.pop("topojson", None) else: if not isinstance(val, string_types): raise ValueError( """ The topojson property must be a string, but received value of type {typ}. Received value: {val}""".format( typ=type(val), val=val ) ) self._props["topojson"] = val # Server must restart before setting is active shutdown_server() @property def mathjax(self): """ Path to the MathJax bundle needed to render LaTeX characters Returns ------- str """ return self._props.get( "mathjax", ("https://cdnjs.cloudflare.com" "/ajax/libs/mathjax/2.7.5/MathJax.js"), ) @mathjax.setter def mathjax(self, val): if val is None: self._props.pop("mathjax", None) else: if not isinstance(val, string_types): raise ValueError( """ The mathjax property must be a string, but received value of type {typ}. Received value: {val}""".format( typ=type(val), val=val ) ) self._props["mathjax"] = val # Server must restart before setting is active shutdown_server() @property def mapbox_access_token(self): """ Mapbox access token required to render mapbox traces. Returns ------- str """ return self._props.get("mapbox_access_token", None) @mapbox_access_token.setter def mapbox_access_token(self, val): if val is None: self._props.pop("mapbox_access_token", None) else: if not isinstance(val, string_types): raise ValueError( """ The mapbox_access_token property must be a string, \ but received value of type {typ}. Received value: {val}""".format( typ=type(val), val=val ) ) self._props["mapbox_access_token"] = val # Server must restart before setting is active shutdown_server() @property def use_xvfb(self): dflt = "auto" return self._props.get("use_xvfb", dflt) @use_xvfb.setter def use_xvfb(self, val): valid_vals = [True, False, "auto"] if val is None: self._props.pop("use_xvfb", None) else: if val not in valid_vals: raise ValueError( """ The use_xvfb property must be one of {valid_vals} Received value of type {typ}: {val}""".format( valid_vals=valid_vals, typ=type(val), val=repr(val) ) ) self._props["use_xvfb"] = val # Server and validation must restart before setting is active reset_status() @property def plotlyjs(self): """ The plotly.js bundle being used for image rendering. Returns ------- str """ return self._constants.get("plotlyjs", None) @property def config_file(self): """ Path to orca configuration file Using the `plotly.io.config.save()` method will save the current configuration settings to this file. Settings in this file are restored at the beginning of each sessions. Returns ------- str """ return os.path.join(PLOTLY_DIR, ".orca") def __repr__(self): """ Display a nice representation of the current orca configuration. """ return """\ orca configuration ------------------ server_url: {server_url} executable: {executable} port: {port} timeout: {timeout} default_width: {default_width} default_height: {default_height} default_scale: {default_scale} default_format: {default_format} mathjax: {mathjax} topojson: {topojson} mapbox_access_token: {mapbox_access_token} use_xvfb: {use_xvfb} constants --------- plotlyjs: {plotlyjs} config_file: {config_file} """.format( server_url=self.server_url, port=self.port, executable=self.executable, timeout=self.timeout, default_width=self.default_width, default_height=self.default_height, default_scale=self.default_scale, default_format=self.default_format, mathjax=self.mathjax, topojson=self.topojson, mapbox_access_token=self.mapbox_access_token, plotlyjs=self.plotlyjs, config_file=self.config_file, use_xvfb=self.use_xvfb, ) # Make config a singleton object # ------------------------------ config = OrcaConfig() del OrcaConfig # Orca status class # ------------------------ class OrcaStatus(object): """ Class to store information about the current status of the orca server. """ _props = { "state": "unvalidated", # or 'validated' or 'running' "executable_list": None, "version": None, "pid": None, "port": None, "command": None, } @property def state(self): """ A string representing the state of the orca server process One of: - unvalidated: The orca executable has not yet been searched for or tested to make sure its valid. - validated: The orca executable has been located and tested for validity, but it is not running. - running: The orca server process is currently running. """ return self._props["state"] @property def executable(self): """ If the `state` property is 'validated' or 'running', this property contains the full path to the orca executable. This path can be specified explicitly by setting the `executable` property of the `plotly.io.orca.config` object. This property will be None if the `state` is 'unvalidated'. """ executable_list = self._props["executable_list"] if executable_list is None: return None else: return " ".join(executable_list) @property def version(self): """ If the `state` property is 'validated' or 'running', this property contains the version of the validated orca executable. This property will be None if the `state` is 'unvalidated'. """ return self._props["version"] @property def pid(self): """ The process id of the orca server process, if any. This property will be None if the `state` is not 'running'. """ return self._props["pid"] @property def port(self): """ The port number that the orca server process is listening to, if any. This property will be None if the `state` is not 'running'. This port can be specified explicitly by setting the `port` property of the `plotly.io.orca.config` object. """ return self._props["port"] @property def command(self): """ The command arguments used to launch the running orca server, if any. This property will be None if the `state` is not 'running'. """ return self._props["command"] def __repr__(self): """ Display a nice representation of the current orca server status. """ return """\ orca status ----------- state: {state} executable: {executable} version: {version} port: {port} pid: {pid} command: {command} """.format( executable=self.executable, version=self.version, port=self.port, pid=self.pid, state=self.state, command=self.command, ) # Make status a singleton object # ------------------------------ status = OrcaStatus() del OrcaStatus @contextmanager def orca_env(): """ Context manager to clear and restore environment variables that are problematic for orca to function properly NODE_OPTIONS: When this variable is set, orca >> plotly.io.orca.config.executable = '/path/to/orca' After updating this executable property, try the export operation again. If it is successful then you may want to save this configuration so that it will be applied automatically in future sessions. You can do this as follows: >>> plotly.io.orca.config.save() If you're still having trouble, feel free to ask for help on the forums at https://community.plot.ly/c/api/python """ # Try to find an executable # ------------------------- # Search for executable name or path in config.executable executable = which(config.executable) path = os.environ.get("PATH", os.defpath) formatted_path = path.replace(os.pathsep, "\n ") if executable is None: raise ValueError( """ The orca executable is required to export figures as static images, but it could not be found on the system path. Searched for executable '{executable}' on the following path: {formatted_path} {instructions}""".format( executable=config.executable, formatted_path=formatted_path, instructions=install_location_instructions, ) ) # Check if we should run with Xvfb # -------------------------------- xvfb_args = [ "--auto-servernum", "--server-args", "-screen 0 640x480x24 +extension RANDR +extension GLX", executable, ] if config.use_xvfb == True: # Use xvfb xvfb_run_executable = which("xvfb-run") if not xvfb_run_executable: raise ValueError( """ The plotly.io.orca.config.use_xvfb property is set to True, but the xvfb-run executable could not be found on the system path. Searched for the executable 'xvfb-run' on the following path: {formatted_path}""".format( formatted_path=formatted_path ) ) executable_list = [xvfb_run_executable] + xvfb_args elif ( config.use_xvfb == "auto" and sys.platform.startswith("linux") and not os.environ.get("DISPLAY") and which("xvfb-run") ): # use_xvfb is 'auto', we're on linux without a display server, # and xvfb-run is available. Use it. xvfb_run_executable = which("xvfb-run") executable_list = [xvfb_run_executable] + xvfb_args else: # Do not use xvfb executable_list = [executable] # Run executable with --help and see if it's our orca # --------------------------------------------------- invalid_executable_msg = """ The orca executable is required in order to export figures as static images, but the executable that was found at '{executable}' does not seem to be a valid plotly orca executable. Please refer to the end of this message for details on what went wrong. {instructions}""".format( executable=executable, instructions=install_location_instructions ) # ### Run with Popen so we get access to stdout and stderr with orca_env(): p = subprocess.Popen( executable_list + ["--help"], stdout=subprocess.PIPE, stderr=subprocess.PIPE ) help_result, help_error = p.communicate() if p.returncode != 0: err_msg = ( invalid_executable_msg + """ Here is the error that was returned by the command $ {executable} --help [Return code: {returncode}] {err_msg} """.format( executable=" ".join(executable_list), err_msg=help_error.decode("utf-8"), returncode=p.returncode, ) ) # Check for Linux without X installed. if sys.platform.startswith("linux") and not os.environ.get("DISPLAY"): err_msg += """\ Note: When used on Linux, orca requires an X11 display server, but none was detected. Please install Xvfb and configure plotly.py to run orca using Xvfb as follows: >>> import plotly.io as pio >>> pio.orca.config.use_xvfb = True You can save this configuration for use in future sessions as follows: >>> pio.orca.config.save() See https://www.x.org/releases/X11R7.6/doc/man/man1/Xvfb.1.xhtml for more info on Xvfb """ raise ValueError(err_msg) if not help_result: raise ValueError( invalid_executable_msg + """ The error encountered is that no output was returned by the command $ {executable} --help """.format( executable=" ".join(executable_list) ) ) if "Plotly's image-exporting utilities" not in help_result.decode("utf-8"): raise ValueError( invalid_executable_msg + """ The error encountered is that unexpected output was returned by the command $ {executable} --help {help_result} """.format( executable=" ".join(executable_list), help_result=help_result ) ) # Get orca version # ---------------- # ### Run with Popen so we get access to stdout and stderr with orca_env(): p = subprocess.Popen( executable_list + ["--version"], stdout=subprocess.PIPE, stderr=subprocess.PIPE, ) version_result, version_error = p.communicate() if p.returncode != 0: raise ValueError( invalid_executable_msg + """ An error occurred while trying to get the version of the orca executable. Here is the command that plotly.py ran to request the version $ {executable} --version This command returned the following error: [Return code: {returncode}] {err_msg} """.format( executable=" ".join(executable_list), err_msg=version_error.decode("utf-8"), returncode=p.returncode, ) ) if not version_result: raise ValueError( invalid_executable_msg + """ The error encountered is that no version was reported by the orca executable. Here is the command that plotly.py ran to request the version: $ {executable} --version """.format( executable=" ".join(executable_list) ) ) else: version_result = version_result.decode() status._props["executable_list"] = executable_list status._props["version"] = version_result.strip() status._props["state"] = "validated" def reset_status(): """ Shutdown the running orca server, if any, and reset the orca status to unvalidated. This command is only needed if the desired orca executable is changed during an interactive session. Returns ------- None """ shutdown_server() status._props["executable_list"] = None status._props["version"] = None status._props["state"] = "unvalidated" # Initialze process control variables # ----------------------------------- orca_lock = threading.Lock() orca_state = {"proc": None, "shutdown_timer": None} # Shutdown # -------- # The @atexit.register annotation ensures that the shutdown function is # is run when the Python process is terminated @atexit.register def cleanup(): shutdown_server() def shutdown_server(): """ Shutdown the running orca server process, if any Returns ------- None """ # Use double-check locking to make sure the properties of orca_state # are updated consistently across threads. if orca_state["proc"] is not None: with orca_lock: if orca_state["proc"] is not None: # We use psutil to kill all child processes of the main orca # process. This prevents any zombie processes from being # left over, and it saves us from needing to write # OS-specific process management code here. parent = psutil.Process(orca_state["proc"].pid) for child in parent.children(recursive=True): try: child.terminate() except: # We tried, move on pass try: # Kill parent process orca_state["proc"].terminate() # Wait for the process to shutdown child_status = orca_state["proc"].wait() except: # We tried, move on pass # Update our internal process management state orca_state["proc"] = None if orca_state["shutdown_timer"] is not None: orca_state["shutdown_timer"].cancel() orca_state["shutdown_timer"] = None orca_state["port"] = None # Update orca.status so the user has an accurate view # of the state of the orca server status._props["state"] = "validated" status._props["pid"] = None status._props["port"] = None status._props["command"] = None # Launch or get server def ensure_server(): """ Start an orca server if none is running. If a server is already running, then reset the timeout countdown Returns ------- None """ # Validate psutil if psutil is None: raise ValueError( """\ Image generation requires the psutil package. Install using pip: $ pip install psutil Install using conda: $ conda install psutil """ ) # Validate requests if not get_module("requests"): raise ValueError( """\ Image generation requires the requests package. Install using pip: $ pip install requests Install using conda: $ conda install requests """ ) if not config.server_url: # Validate orca executable only if server_url is not provided if status.state == "unvalidated": validate_executable() # Acquire lock to make sure that we keep the properties of orca_state # consistent across threads with orca_lock: # Cancel the current shutdown timer, if any if orca_state["shutdown_timer"] is not None: orca_state["shutdown_timer"].cancel() # Start a new server process if none is active if orca_state["proc"] is None: # Determine server port if config.port is None: orca_state["port"] = find_open_port() else: orca_state["port"] = config.port # Build orca command list cmd_list = status._props["executable_list"] + [ "serve", "-p", str(orca_state["port"]), "--plotly", config.plotlyjs, "--graph-only", ] if config.topojson: cmd_list.extend(["--topojson", config.topojson]) if config.mathjax: cmd_list.extend(["--mathjax", config.mathjax]) if config.mapbox_access_token: cmd_list.extend( ["--mapbox-access-token", config.mapbox_access_token] ) # Create subprocess that launches the orca server on the # specified port. DEVNULL = open(os.devnull, "wb") with orca_env(): orca_state["proc"] = subprocess.Popen(cmd_list, stdout=DEVNULL) # Update orca.status so the user has an accurate view # of the state of the orca server status._props["state"] = "running" status._props["pid"] = orca_state["proc"].pid status._props["port"] = orca_state["port"] status._props["command"] = cmd_list # Create new shutdown timer if a timeout was specified if config.timeout is not None: t = threading.Timer(config.timeout, shutdown_server) # Make it a daemon thread so that exit won't wait for timer to # complete t.daemon = True t.start() orca_state["shutdown_timer"] = t @retrying.retry(wait_random_min=5, wait_random_max=10, stop_max_delay=60000) def request_image_with_retrying(**kwargs): """ Helper method to perform an image request to a running orca server process with retrying logic. """ from requests import post if config.server_url: server_url = config.server_url else: server_url = "http://{hostname}:{port}".format( hostname="localhost", port=orca_state["port"] ) request_params = {k: v for k, v, in kwargs.items() if v is not None} json_str = json.dumps(request_params, cls=_plotly_utils.utils.PlotlyJSONEncoder) response = post(server_url + "/", data=json_str) if response.status_code == 522: # On "522: client socket timeout", return server and keep trying shutdown_server() ensure_server() raise OSError("522: client socket timeout") return response def to_image(fig, format=None, width=None, height=None, scale=None, validate=True): """ Convert a figure to a static image bytes string Parameters ---------- fig: Figure object or dict representing a figure format: str or None The desired image format. One of - 'png' - 'jpg' or 'jpeg' - 'webp' - 'svg' - 'pdf' - 'eps' (Requires the poppler library to be installed) If not specified, will default to `plotly.io.config.default_format` width: int or None The width of the exported image in layout pixels. If the `scale` property is 1.0, this will also be the width of the exported image in physical pixels. If not specified, will default to `plotly.io.config.default_width` height: int or None The height of the exported image in layout pixels. If the `scale` property is 1.0, this will also be the height of the exported image in physical pixels. If not specified, will default to `plotly.io.config.default_height` scale: int or float or None The scale factor to use when exporting the figure. A scale factor larger than 1.0 will increase the image resolution with respect to the figure's layout pixel dimensions. Whereas as scale factor of less than 1.0 will decrease the image resolution. If not specified, will default to `plotly.io.config.default_scale` validate: bool True if the figure should be validated before being converted to an image, False otherwise. Returns ------- bytes The image data """ # Make sure orca sever is running # ------------------------------- ensure_server() # Handle defaults # --------------- # Apply configuration defaults to unspecified arguments if format is None: format = config.default_format format = validate_coerce_format(format) if scale is None: scale = config.default_scale if width is None: width = config.default_width if height is None: height = config.default_height # Validate figure # --------------- fig_dict = validate_coerce_fig_to_dict(fig, validate) # Request image from server # ------------------------- try: response = request_image_with_retrying( figure=fig_dict, format=format, scale=scale, width=width, height=height ) except OSError as err: # Get current status string status_str = repr(status) if config.server_url: raise ValueError( """ Plotly.py was unable to communicate with the orca server at {server_url} Please check that the server is running and accessible. """.format( server_url=config.server_url ) ) else: # Check if the orca server process exists pid_exists = psutil.pid_exists(status.pid) # Raise error message based on whether the server process existed if pid_exists: raise ValueError( """ For some reason plotly.py was unable to communicate with the local orca server process, even though the server process seems to be running. Please review the process and connection information below: {info} """.format( info=status_str ) ) else: # Reset the status so that if the user tries again, we'll try to # start the server again reset_status() raise ValueError( """ For some reason the orca server process is no longer running. Please review the process and connection information below: {info} plotly.py will attempt to start the local server process again the next time an image export operation is performed. """.format( info=status_str ) ) # Check response # -------------- if response.status_code == 200: # All good return response.content else: # ### Something went wrong ### err_message = """ The image request was rejected by the orca conversion utility with the following error: {status}: {msg} """.format( status=response.status_code, msg=response.content.decode("utf-8") ) # ### Try to be helpful ### # Status codes from /src/component/plotly-graph/constants.js in the # orca code base. # statusMsg: { # 400: 'invalid or malformed request syntax', # 522: client socket timeout # 525: 'plotly.js error', # 526: 'plotly.js version 1.11.0 or up required', # 530: 'image conversion error' # } if response.status_code == 400 and isinstance(fig, dict) and not validate: err_message += """ Try setting the `validate` argument to True to check for errors in the figure specification""" elif response.status_code == 525: any_mapbox = any( [ trace.get("type", None) == "scattermapbox" for trace in fig_dict.get("data", []) ] ) if any_mapbox and config.mapbox_access_token is None: err_message += """ Exporting scattermapbox traces requires a mapbox access token. Create a token in your mapbox account and then set it using: >>> plotly.io.orca.config.mapbox_access_token = 'pk.abc...' If you would like this token to be applied automatically in future sessions, then save your orca configuration as follows: >>> plotly.io.orca.config.save() """ elif response.status_code == 530 and format == "eps": err_message += """ Exporting to EPS format requires the poppler library. You can install poppler on MacOS or Linux with: $ conda install poppler Or, you can install it on MacOS using homebrew with: $ brew install poppler Or, you can install it on Linux using your distribution's package manager to install the 'poppler-utils' package. Unfortunately, we don't yet know of an easy way to install poppler on Windows. """ raise ValueError(err_message) def write_image( fig, file, format=None, scale=None, width=None, height=None, validate=True ): """ Convert a figure to a static image and write it to a file or writeable object Parameters ---------- fig: Figure object or dict representing a figure file: str or writeable A string representing a local file path or a writeable object (e.g. an open file descriptor) format: str or None The desired image format. One of - 'png' - 'jpg' or 'jpeg' - 'webp' - 'svg' - 'pdf' - 'eps' (Requires the poppler library to be installed) If not specified and `file` is a string then this will default to the file extension. If not specified and `file` is not a string then this will default to `plotly.io.config.default_format` width: int or None The width of the exported image in layout pixels. If the `scale` property is 1.0, this will also be the width of the exported image in physical pixels. If not specified, will default to `plotly.io.config.default_width` height: int or None The height of the exported image in layout pixels. If the `scale` property is 1.0, this will also be the height of the exported image in physical pixels. If not specified, will default to `plotly.io.config.default_height` scale: int or float or None The scale factor to use when exporting the figure. A scale factor larger than 1.0 will increase the image resolution with respect to the figure's layout pixel dimensions. Whereas as scale factor of less than 1.0 will decrease the image resolution. If not specified, will default to `plotly.io.config.default_scale` validate: bool True if the figure should be validated before being converted to an image, False otherwise. Returns ------- None """ # Check if file is a string # ------------------------- file_is_str = isinstance(file, string_types) # Infer format if not specified # ----------------------------- if file_is_str and format is None: _, ext = os.path.splitext(file) if ext: format = validate_coerce_format(ext) else: raise ValueError( """ Cannot infer image type from output path '{file}'. Please add a file extension or specify the type using the format parameter. For example: >>> import plotly.io as pio >>> pio.write_image(fig, file_path, format='png') """.format( file=file ) ) # Request image # ------------- # Do this first so we don't create a file if image conversion fails img_data = to_image( fig, format=format, scale=scale, width=width, height=height, validate=validate ) # Open file # --------- if file_is_str: with open(file, "wb") as f: f.write(img_data) else: file.write(img_data) plotly-4.4.1+dfsg.orig/plotly/io/_json.py0000644000175000017500000001255013573717677017717 0ustar noahfxnoahfxfrom __future__ import absolute_import from six import string_types import json from plotly.io._utils import validate_coerce_fig_to_dict, validate_coerce_output_type def to_json(fig, validate=True, pretty=False, remove_uids=True): """ Convert a figure to a JSON string representation Parameters ---------- fig: Figure object or dict representing a figure validate: bool (default True) True if the figure should be validated before being converted to JSON, False otherwise. pretty: bool (default False) True if JSON representation should be pretty-printed, False if representation should be as compact as possible. remove_uids: bool (default True) True if trace UIDs should be omitted from the JSON representation Returns ------- str Representation of figure as a JSON string """ from _plotly_utils.utils import PlotlyJSONEncoder # Validate figure # --------------- fig_dict = validate_coerce_fig_to_dict(fig, validate) # Remove trace uid # ---------------- if remove_uids: for trace in fig_dict.get("data", []): trace.pop("uid", None) # Dump to a JSON string and return # -------------------------------- opts = {"sort_keys": True} if pretty: opts["indent"] = 2 else: # Remove all whitespace opts["separators"] = (",", ":") return json.dumps(fig_dict, cls=PlotlyJSONEncoder, **opts) def write_json(fig, file, validate=True, pretty=False, remove_uids=True): """ Convert a figure to JSON and write it to a file or writeable object Parameters ---------- fig: Figure object or dict representing a figure file: str or writeable A string representing a local file path or a writeable object (e.g. an open file descriptor) pretty: bool (default False) True if JSON representation should be pretty-printed, False if representation should be as compact as possible. remove_uids: bool (default True) True if trace UIDs should be omitted from the JSON representation Returns ------- None """ # Get JSON string # --------------- # Pass through validate argument and let to_json handle validation logic json_str = to_json(fig, validate=validate, pretty=pretty, remove_uids=remove_uids) # Check if file is a string # ------------------------- file_is_str = isinstance(file, string_types) # Open file # --------- if file_is_str: with open(file, "w") as f: f.write(json_str) else: file.write(json_str) def from_json(value, output_type="Figure", skip_invalid=False): """ Construct a figure from a JSON string Parameters ---------- value: str String containing the JSON representation of a figure output_type: type or str (default 'Figure') The output figure type or type name. One of: graph_objs.Figure, 'Figure', graph_objs.FigureWidget, 'FigureWidget' skip_invalid: bool (default False) False if invalid figure properties should result in an exception. True if invalid figure properties should be silently ignored. Raises ------ ValueError if value is not a string, or if skip_invalid=False and value contains invalid figure properties Returns ------- Figure or FigureWidget """ # Validate value # -------------- if not isinstance(value, string_types): raise ValueError( """ from_json requires a string argument but received value of type {typ} Received value: {value}""".format( typ=type(value), value=value ) ) # Decode JSON # ----------- fig_dict = json.loads(value) # Validate coerce output type # --------------------------- cls = validate_coerce_output_type(output_type) # Create and return figure # ------------------------ fig = cls(fig_dict, skip_invalid=skip_invalid) return fig def read_json(file, output_type="Figure", skip_invalid=False): """ Construct a figure from the JSON contents of a local file or readable Python object Parameters ---------- file: str or readable A string containing the path to a local file or a read-able Python object (e.g. an open file descriptor) output_type: type or str (default 'Figure') The output figure type or type name. One of: graph_objs.Figure, 'Figure', graph_objs.FigureWidget, 'FigureWidget' skip_invalid: bool (default False) False if invalid figure properties should result in an exception. True if invalid figure properties should be silently ignored. Returns ------- Figure or FigureWidget """ # Check if file is a string # ------------------------- # If it's a string we assume it's a local file path. If it's not a string # then we assume it's a read-able Python object file_is_str = isinstance(file, string_types) # Read file contents into JSON string # ----------------------------------- if file_is_str: with open(file, "r") as f: json_str = f.read() else: json_str = file.read() # Construct and return figure # --------------------------- return from_json(json_str, skip_invalid=skip_invalid, output_type=output_type) plotly-4.4.1+dfsg.orig/plotly/io/_renderers.py0000644000175000017500000003715613532445406020727 0ustar noahfxnoahfxfrom __future__ import absolute_import, division import textwrap from copy import copy import six import os from distutils.version import LooseVersion from plotly import optional_imports from plotly.io._base_renderers import ( MimetypeRenderer, ExternalRenderer, PlotlyRenderer, NotebookRenderer, KaggleRenderer, AzureRenderer, ColabRenderer, JsonRenderer, PngRenderer, JpegRenderer, SvgRenderer, PdfRenderer, BrowserRenderer, IFrameRenderer, SphinxGalleryRenderer, CoCalcRenderer, DatabricksRenderer, ) from plotly.io._utils import validate_coerce_fig_to_dict ipython = optional_imports.get_module("IPython") ipython_display = optional_imports.get_module("IPython.display") nbformat = optional_imports.get_module("nbformat") # Renderer configuration class # ----------------------------- class RenderersConfig(object): """ Singleton object containing the current renderer configurations """ def __init__(self): self._renderers = {} self._default_name = None self._default_renderers = [] self._render_on_display = False self._to_activate = [] # ### Magic methods ### # Make this act as a dict of renderers def __len__(self): return len(self._renderers) def __contains__(self, item): return item in self._renderers def __iter__(self): return iter(self._renderers) def __getitem__(self, item): renderer = self._renderers[item] return renderer def __setitem__(self, key, value): if not isinstance(value, (MimetypeRenderer, ExternalRenderer)): raise ValueError( """\ Renderer must be a subclass of MimetypeRenderer or ExternalRenderer. Received value with type: {typ}""".format( typ=type(value) ) ) self._renderers[key] = value def __delitem__(self, key): # Remove template del self._renderers[key] # Check if we need to remove it as the default if self._default == key: self._default = None def keys(self): return self._renderers.keys() def items(self): return self._renderers.items() def update(self, d={}, **kwargs): """ Update one or more renderers from a dict or from input keyword arguments. Parameters ---------- d: dict Dictionary from renderer names to new renderer objects. kwargs Named argument value pairs where the name is a renderer name and the value is a new renderer object """ for k, v in dict(d, **kwargs).items(): self[k] = v # ### Properties ### @property def default(self): """ The default renderer, or None if no there is no default If not None, the default renderer is used to render figures when the `plotly.io.show` function is called on a Figure. If `plotly.io.renderers.render_on_display` is True, then the default renderer will also be used to display Figures automatically when displayed in the Jupyter Notebook Multiple renderers may be registered by separating their names with '+' characters. For example, to specify rendering compatible with the classic Jupyter Notebook, JupyterLab, and PDF export: >>> import plotly.io as pio >>> pio.renderers.default = 'notebook+jupyterlab+pdf' The names of available renderers may be retrieved with: >>> import plotly.io as pio >>> list(pio.renderers) Returns ------- str """ return self._default_name @default.setter def default(self, value): # Handle None if not value: # _default_name should always be a string so we can do # pio.renderers.default.split('+') self._default_name = "" self._default_renderers = [] return # Store defaults name and list of renderer(s) renderer_names = self._validate_coerce_renderers(value) self._default_name = value self._default_renderers = [self[name] for name in renderer_names] # Register renderers for activation before their next use self._to_activate = list(self._default_renderers) @property def render_on_display(self): """ If True, the default mimetype renderers will be used to render figures when they are displayed in an IPython context. Returns ------- bool """ return self._render_on_display @render_on_display.setter def render_on_display(self, val): self._render_on_display = bool(val) def _activate_pending_renderers(self, cls=object): """ Activate all renderers that are waiting in the _to_activate list Parameters ---------- cls Only activate renders that are subclasses of this class """ to_activate_with_cls = [ r for r in self._to_activate if cls and isinstance(r, cls) ] while to_activate_with_cls: # Activate renderers from left to right so that right-most # renderers take precedence renderer = to_activate_with_cls.pop(0) renderer.activate() self._to_activate = [ r for r in self._to_activate if not (cls and isinstance(r, cls)) ] def _validate_coerce_renderers(self, renderers_string): """ Input a string and validate that it contains the names of one or more valid renderers separated on '+' characters. If valid, return a list of the renderer names Parameters ---------- renderers_string: str Returns ------- list of str """ # Validate value if not isinstance(renderers_string, six.string_types): raise ValueError("Renderer must be specified as a string") renderer_names = renderers_string.split("+") invalid = [name for name in renderer_names if name not in self] if invalid: raise ValueError( """ Invalid named renderer(s) received: {}""".format( str(invalid) ) ) return renderer_names def __repr__(self): return """\ Renderers configuration ----------------------- Default renderer: {default} Available renderers: {available} """.format( default=repr(self.default), available=self._available_renderers_str() ) def _available_renderers_str(self): """ Return nicely wrapped string representation of all available renderer names """ available = "\n".join( textwrap.wrap( repr(list(self)), width=79 - 8, initial_indent=" " * 8, subsequent_indent=" " * 9, ) ) return available def _build_mime_bundle(self, fig_dict, renderers_string=None, **kwargs): """ Build a mime bundle dict containing a kev/value pair for each MimetypeRenderer specified in either the default renderer string, or in the supplied renderers_string argument. Note that this method skips any renderers that are not subclasses of MimetypeRenderer. Parameters ---------- fig_dict: dict Figure dictionary renderers_string: str or None (default None) Renderer string to process rather than the current default renderer string Returns ------- dict """ if renderers_string: renderer_names = self._validate_coerce_renderers(renderers_string) renderers_list = [self[name] for name in renderer_names] # Activate these non-default renderers for renderer in renderers_list: if isinstance(renderer, MimetypeRenderer): renderer.activate() else: # Activate any pending default renderers self._activate_pending_renderers(cls=MimetypeRenderer) renderers_list = self._default_renderers bundle = {} for renderer in renderers_list: if isinstance(renderer, MimetypeRenderer): renderer = copy(renderer) for k, v in kwargs.items(): if hasattr(renderer, k): setattr(renderer, k, v) bundle.update(renderer.to_mimebundle(fig_dict)) return bundle def _perform_external_rendering(self, fig_dict, renderers_string=None, **kwargs): """ Perform external rendering for each ExternalRenderer specified in either the default renderer string, or in the supplied renderers_string argument. Note that this method skips any renderers that are not subclasses of ExternalRenderer. Parameters ---------- fig_dict: dict Figure dictionary renderers_string: str or None (default None) Renderer string to process rather than the current default renderer string Returns ------- None """ if renderers_string: renderer_names = self._validate_coerce_renderers(renderers_string) renderers_list = [self[name] for name in renderer_names] # Activate these non-default renderers for renderer in renderers_list: if isinstance(renderer, ExternalRenderer): renderer.activate() else: self._activate_pending_renderers(cls=ExternalRenderer) renderers_list = self._default_renderers for renderer in renderers_list: if isinstance(renderer, ExternalRenderer): renderer = copy(renderer) for k, v in kwargs.items(): if hasattr(renderer, k): setattr(renderer, k, v) renderer.render(fig_dict) # Make renderers a singleton object # --------------------------------- renderers = RenderersConfig() del RenderersConfig # Show def show(fig, renderer=None, validate=True, **kwargs): """ Show a figure using either the default renderer(s) or the renderer(s) specified by the renderer argument Parameters ---------- fig: dict of Figure The Figure object or figure dict to display renderer: str or None (default None) A string containing the names of one or more registered renderers (separated by '+' characters) or None. If None, then the default renderers specified in plotly.io.renderers.default are used. validate: bool (default True) True if the figure should be validated before being shown, False otherwise. Returns ------- None """ fig_dict = validate_coerce_fig_to_dict(fig, validate) # Mimetype renderers bundle = renderers._build_mime_bundle(fig_dict, renderers_string=renderer, **kwargs) if bundle: if not ipython_display: raise ValueError( "Mime type rendering requires ipython but it is not installed" ) if not nbformat or LooseVersion(nbformat.__version__) < LooseVersion("4.2.0"): raise ValueError( "Mime type rendering requires nbformat>=4.2.0 but it is not installed" ) ipython_display.display(bundle, raw=True) # external renderers renderers._perform_external_rendering(fig_dict, renderers_string=renderer, **kwargs) # Register renderers # ------------------ # Plotly mime type plotly_renderer = PlotlyRenderer() renderers["plotly_mimetype"] = plotly_renderer renderers["jupyterlab"] = plotly_renderer renderers["nteract"] = plotly_renderer renderers["vscode"] = plotly_renderer # HTML-based config = {} renderers["notebook"] = NotebookRenderer(config=config) renderers["notebook_connected"] = NotebookRenderer(config=config, connected=True) renderers["kaggle"] = KaggleRenderer(config=config) renderers["azure"] = AzureRenderer(config=config) renderers["colab"] = ColabRenderer(config=config) renderers["cocalc"] = CoCalcRenderer() renderers["databricks"] = DatabricksRenderer() # JSON renderers["json"] = JsonRenderer() # Static Image img_kwargs = dict(height=450, width=700) renderers["png"] = PngRenderer(**img_kwargs) jpeg_renderer = JpegRenderer(**img_kwargs) renderers["jpeg"] = jpeg_renderer renderers["jpg"] = jpeg_renderer renderers["svg"] = SvgRenderer(**img_kwargs) renderers["pdf"] = PdfRenderer(**img_kwargs) # External renderers["browser"] = BrowserRenderer(config=config) renderers["firefox"] = BrowserRenderer(config=config, using="firefox") renderers["chrome"] = BrowserRenderer(config=config, using="chrome") renderers["chromium"] = BrowserRenderer(config=config, using="chromium") renderers["iframe"] = IFrameRenderer(config=config, include_plotlyjs=True) renderers["iframe_connected"] = IFrameRenderer(config=config, include_plotlyjs="cdn") renderers["sphinx_gallery"] = SphinxGalleryRenderer() # Set default renderer # -------------------- # Version 4 renderer configuration default_renderer = None # Handle the PLOTLY_RENDERER environment variable env_renderer = os.environ.get("PLOTLY_RENDERER", None) if env_renderer: try: renderers._validate_coerce_renderers(env_renderer) except ValueError: raise ValueError( """ Invalid named renderer(s) specified in the 'PLOTLY_RENDERER' environment variable: {env_renderer}""".format( env_renderer=env_renderer ) ) default_renderer = env_renderer elif ipython and ipython.get_ipython(): # Try to detect environment so that we can enable a useful # default renderer if not default_renderer: try: import google.colab default_renderer = "colab" except ImportError: pass # Check if we're running in a Kaggle notebook if not default_renderer and os.path.exists("/kaggle/input"): default_renderer = "kaggle" # Check if we're running in an Azure Notebook if not default_renderer and "AZURE_NOTEBOOKS_HOST" in os.environ: default_renderer = "azure" # Check if we're running in VSCode if not default_renderer and "VSCODE_PID" in os.environ: default_renderer = "vscode" # Check if we're running in nteract if not default_renderer and "NTERACT_EXE" in os.environ: default_renderer = "nteract" # Check if we're running in CoCalc if not default_renderer and "COCALC_PROJECT_ID" in os.environ: default_renderer = "cocalc" if not default_renderer and "DATABRICKS_RUNTIME_VERSION" in os.environ: default_renderer = "databricks" # Check if we're running in spyder and orca is installed if not default_renderer and "SPYDER_ARGS" in os.environ: try: from plotly.io.orca import validate_executable validate_executable() default_renderer = "svg" except ValueError: # orca not found pass # Fallback to renderer combination that will work automatically # in the classic notebook (offline), jupyterlab, nteract, vscode, and # nbconvert HTML export. if not default_renderer: default_renderer = "plotly_mimetype+notebook" else: # If ipython isn't available, try to display figures in the default # browser import webbrowser try: webbrowser.get() default_renderer = "browser" except webbrowser.Error: # Default browser could not be loaded pass renderers.render_on_display = True renderers.default = default_renderer plotly-4.4.1+dfsg.orig/plotly/io/_templates.py0000644000175000017500000003517413573717677020753 0ustar noahfxnoahfxfrom __future__ import absolute_import import textwrap import pkgutil import copy import os import json from functools import reduce from six import string_types try: from math import gcd except ImportError: # Python 2 from fractions import gcd # Create Lazy sentinal object to indicate that a template should be loaded # on-demand from package_data Lazy = object() # Templates configuration class # ----------------------------- class TemplatesConfig(object): """ Singleton object containing the current figure templates (aka themes) """ def __init__(self): # Initialize properties dict self._templates = {} # Initialize built-in templates default_templates = [ "ggplot2", "seaborn", "simple_white", "plotly", "plotly_white", "plotly_dark", "presentation", "xgridoff", "ygridoff", "gridon", "none", ] for template_name in default_templates: self._templates[template_name] = Lazy self._validator = None self._default = None # ### Magic methods ### # Make this act as a dict of templates def __len__(self): return len(self._templates) def __contains__(self, item): return item in self._templates def __iter__(self): return iter(self._templates) def __getitem__(self, item): if isinstance(item, string_types): template_names = item.split("+") else: template_names = [item] templates = [] for template_name in template_names: template = self._templates[template_name] if template is Lazy: from plotly.graph_objs.layout import Template if template_name == "none": # "none" is a special built-in named template that applied no defaults template = Template(data_scatter=[{}]) self._templates[template_name] = template else: # Load template from package data path = os.path.join( "package_data", "templates", template_name + ".json" ) template_str = pkgutil.get_data("plotly", path).decode("utf-8") template_dict = json.loads(template_str) template = Template(template_dict) self._templates[template_name] = template templates.append(self._templates[template_name]) return self.merge_templates(*templates) def __setitem__(self, key, value): self._templates[key] = self._validate(value) def __delitem__(self, key): # Remove template del self._templates[key] # Check if we need to remove it as the default if self._default == key: self._default = None def _validate(self, value): if not self._validator: from plotly.validators.layout import TemplateValidator self._validator = TemplateValidator() return self._validator.validate_coerce(value) def keys(self): return self._templates.keys() def items(self): return self._templates.items() def update(self, d={}, **kwargs): """ Update one or more templates from a dict or from input keyword arguments. Parameters ---------- d: dict Dictionary from template names to new template values. kwargs Named argument value pairs where the name is a template name and the value is a new template value. """ for k, v in dict(d, **kwargs).items(): self[k] = v # ### Properties ### @property def default(self): """ The name of the default template, or None if no there is no default If not None, the default template is automatically applied to all figures during figure construction if no explicit template is specified. The names of available templates may be retrieved with: >>> import plotly.io as pio >>> list(pio.templates) Returns ------- str """ return self._default @default.setter def default(self, value): # Validate value # Could be a Template object, the key of a registered template, # Or a string containing the names of multiple templates joined on # '+' characters self._validate(value) self._default = value def __repr__(self): return """\ Templates configuration ----------------------- Default template: {default} Available templates: {available} """.format( default=repr(self.default), available=self._available_templates_str() ) def _available_templates_str(self): """ Return nicely wrapped string representation of all available template names """ available = "\n".join( textwrap.wrap( repr(list(self)), width=79 - 8, initial_indent=" " * 8, subsequent_indent=" " * 9, ) ) return available def merge_templates(self, *args): """ Merge a collection of templates into a single combined template. Templates are process from left to right so if multiple templates specify the same propery, the right-most template will take precedence. Parameters ---------- args: list of Template Zero or more template objects (or dicts with compatible properties) Returns ------- template: A combined template object Examples -------- >>> pio.templates.merge_templates( ... go.layout.Template(layout={'font': {'size': 20}}), ... go.layout.Template(data={'scatter': [{'mode': 'markers'}]}), ... go.layout.Template(layout={'font': {'family': 'Courier'}})) layout.Template({ 'data': {'scatter': [{'mode': 'markers', 'type': 'scatter'}]}, 'layout': {'font': {'family': 'Courier', 'size': 20}} }) """ if args: return reduce(self._merge_2_templates, args) else: from plotly.graph_objs.layout import Template return Template() def _merge_2_templates(self, template1, template2): """ Helper function for merge_templates that merges exactly two templates Parameters ---------- template1: Template template2: Template Returns ------- Template: merged template """ # Validate/copy input templates result = self._validate(template1) other = self._validate(template2) # Cycle traces for trace_type in result.data: result_traces = result.data[trace_type] other_traces = other.data[trace_type] if result_traces and other_traces: lcm = ( len(result_traces) * len(other_traces) // gcd(len(result_traces), len(other_traces)) ) # Cycle result traces result.data[trace_type] = result_traces * (lcm // len(result_traces)) # Cycle other traces other.data[trace_type] = other_traces * (lcm // len(other_traces)) # Perform update result.update(other) return result # Make config a singleton object # ------------------------------ templates = TemplatesConfig() del TemplatesConfig # Template utilities # ------------------ def walk_push_to_template(fig_obj, template_obj, skip): """ Move style properties from fig_obj to template_obj. Parameters ---------- fig_obj: plotly.basedatatypes.BasePlotlyType template_obj: plotly.basedatatypes.BasePlotlyType skip: set of str Set of names of properties to skip """ from _plotly_utils.basevalidators import ( CompoundValidator, CompoundArrayValidator, is_array, ) for prop in list(fig_obj._props): if prop == "template" or prop in skip: # Avoid infinite recursion continue fig_val = fig_obj[prop] template_val = template_obj[prop] validator = fig_obj._validators[prop] if isinstance(validator, CompoundValidator): walk_push_to_template(fig_val, template_val, skip) if not fig_val._props: # Check if we can remove prop itself fig_obj[prop] = None elif isinstance(validator, CompoundArrayValidator) and fig_val: template_elements = list(template_val) template_element_names = [el.name for el in template_elements] template_propdefaults = template_obj[prop[:-1] + "defaults"] for fig_el in fig_val: element_name = fig_el.name if element_name: # No properties are skipped inside a named array element skip = set() if fig_el.name in template_element_names: item_index = template_element_names.index(fig_el.name) template_el = template_elements[item_index] walk_push_to_template(fig_el, template_el, skip) else: template_el = fig_el.__class__() walk_push_to_template(fig_el, template_el, skip) template_elements.append(template_el) template_element_names.append(fig_el.name) # Restore element name # since it was pushed to template above fig_el.name = element_name else: walk_push_to_template(fig_el, template_propdefaults, skip) template_obj[prop] = template_elements elif not validator.array_ok or not is_array(fig_val): # Move property value from figure to template template_obj[prop] = fig_val try: fig_obj[prop] = None except ValueError: # Property cannot be set to None, move on. pass def to_templated(fig, skip=("title", "text")): """ Return a copy of a figure where all styling properties have been moved into the figure's template. The template property of the resulting figure may then be used to set the default styling of other figures. Parameters ---------- fig Figure object or dict representing a figure skip A collection of names of properties to skip when moving properties to the template. Defaults to ('title', 'text') so that the text of figure titles, axis titles, and annotations does not become part of the template Examples -------- Imports >>> import plotly.graph_objs as go >>> import plotly.io as pio Construct a figure with large courier text >>> fig = go.Figure(layout={'title': 'Figure Title', ... 'font': {'size': 20, 'family': 'Courier'}, ... 'template':"none"}) >>> fig # doctest: +NORMALIZE_WHITESPACE Figure({ 'data': [], 'layout': {'font': {'family': 'Courier', 'size': 20}, 'template': '...', 'title': {'text': 'Figure Title'}} }) Convert to a figure with a template. Note how the 'font' properties have been moved into the template property. >>> templated_fig = pio.to_templated(fig) >>> templated_fig.layout.template layout.Template({ 'data': {}, 'layout': {'font': {'family': 'Courier', 'size': 20}} }) >>> templated_fig Figure({ 'data': [], 'layout': {'template': '...', 'title': {'text': 'Figure Title'}} }) Next create a new figure with this template >>> fig2 = go.Figure(layout={ ... 'title': 'Figure 2 Title', ... 'template': templated_fig.layout.template}) >>> fig2.layout.template layout.Template({ 'layout': {'font': {'family': 'Courier', 'size': 20}} }) The default font in fig2 will now be size 20 Courier. Next, register as a named template... >>> pio.templates['large_courier'] = templated_fig.layout.template and specify this template by name when constructing a figure. >>> go.Figure(layout={ ... 'title': 'Figure 3 Title', ... 'template': 'large_courier'}) # doctest: +ELLIPSIS Figure(...) Finally, set this as the default template to be applied to all new figures >>> pio.templates.default = 'large_courier' >>> fig = go.Figure(layout={'title': 'Figure 4 Title'}) >>> fig.layout.template layout.Template({ 'layout': {'font': {'family': 'Courier', 'size': 20}} }) Returns ------- go.Figure """ # process fig from plotly.basedatatypes import BaseFigure from plotly.graph_objs import Figure if not isinstance(fig, BaseFigure): fig = Figure(fig) # Process skip if not skip: skip = set() else: skip = set(skip) # Always skip uids skip.add("uid") # Initialize templated figure with deep copy of input figure templated_fig = copy.deepcopy(fig) # Handle layout walk_push_to_template( templated_fig.layout, templated_fig.layout.template.layout, skip=skip ) # Handle traces trace_type_indexes = {} for trace in list(templated_fig.data): template_index = trace_type_indexes.get(trace.type, 0) # Extend template traces if necessary template_traces = list(templated_fig.layout.template.data[trace.type]) while len(template_traces) <= template_index: # Append empty trace template_traces.append(trace.__class__()) # Get corresponding template trace template_trace = template_traces[template_index] # Perform push properties to template walk_push_to_template(trace, template_trace, skip=skip) # Update template traces in templated_fig templated_fig.layout.template.data[trace.type] = template_traces # Update trace_type_indexes trace_type_indexes[trace.type] = template_index + 1 # Remove useless trace arrays for trace_type in templated_fig.layout.template.data: traces = templated_fig.layout.template.data[trace_type] is_empty = [trace.to_plotly_json() == {"type": trace_type} for trace in traces] if all(is_empty): templated_fig.layout.template.data[trace_type] = None return templated_fig plotly-4.4.1+dfsg.orig/plotly/io/_sg_scraper.py0000644000175000017500000000632413525746125021063 0ustar noahfxnoahfx# This module defines an image scraper for sphinx-gallery # https://sphinx-gallery.github.io/ # which can be used by projects using plotly in their documentation. import inspect, os import plotly from glob import glob import shutil plotly.io.renderers.default = "sphinx_gallery" def plotly_sg_scraper(block, block_vars, gallery_conf, **kwargs): """Scrape Plotly figures for galleries of examples using sphinx-gallery. Examples should use ``plotly.io.show()`` to display the figure with the custom sphinx_gallery renderer. Since the sphinx_gallery renderer generates both html and static png files, we simply crawl these files and give them the appropriate path. Parameters ---------- block : tuple A tuple containing the (label, content, line_number) of the block. block_vars : dict Dict of block variables. gallery_conf : dict Contains the configuration of Sphinx-Gallery **kwargs : dict Additional keyword arguments to pass to :meth:`~matplotlib.figure.Figure.savefig`, e.g. ``format='svg'``. The ``format`` kwarg in particular is used to set the file extension of the output file (currently only 'png' and 'svg' are supported). Returns ------- rst : str The ReSTructuredText that will be rendered to HTML containing the images. Notes ----- Add this function to the image scrapers """ examples_dirs = gallery_conf["examples_dirs"] if isinstance(examples_dirs, (list, tuple)): examples_dirs = examples_dirs[0] pngs = sorted(glob(os.path.join(examples_dirs, "*.png"))) htmls = sorted(glob(os.path.join(examples_dirs, "*.html"))) image_path_iterator = block_vars["image_path_iterator"] image_names = list() seen = set() for html, png in zip(htmls, pngs): if png not in seen: seen |= set(png) this_image_path_png = next(image_path_iterator) this_image_path_html = os.path.splitext(this_image_path_png)[0] + ".html" image_names.append(this_image_path_html) shutil.move(png, this_image_path_png) shutil.move(html, this_image_path_html) # Use the `figure_rst` helper function to generate rST for image files return figure_rst(image_names, gallery_conf["src_dir"]) def figure_rst(figure_list, sources_dir): """Generate RST for a list of PNG filenames. Depending on whether we have one or more figures, we use a single rst call to 'image' or a horizontal list. Parameters ---------- figure_list : list List of strings of the figures' absolute paths. sources_dir : str absolute path of Sphinx documentation sources Returns ------- images_rst : str rst code to embed the images in the document """ figure_paths = [ os.path.relpath(figure_path, sources_dir).replace(os.sep, "/").lstrip("/") for figure_path in figure_list ] images_rst = "" figure_name = figure_paths[0] ext = os.path.splitext(figure_name)[1] figure_path = os.path.join("images", os.path.basename(figure_name)) images_rst = SINGLE_HTML % figure_path return images_rst SINGLE_HTML = """ .. raw:: html :file: %s """ plotly-4.4.1+dfsg.orig/plotly/io/_utils.py0000644000175000017500000000221613547055022020060 0ustar noahfxnoahfxfrom __future__ import absolute_import import plotly import plotly.graph_objs as go def validate_coerce_fig_to_dict(fig, validate): from plotly.basedatatypes import BaseFigure if isinstance(fig, BaseFigure): fig_dict = fig.to_dict() elif isinstance(fig, dict): if validate: # This will raise an exception if fig is not a valid plotly figure fig_dict = plotly.graph_objs.Figure(fig).to_plotly_json() else: fig_dict = fig else: raise ValueError( """ The fig parameter must be a dict or Figure. Received value of type {typ}: {v}""".format( typ=type(fig), v=fig ) ) return fig_dict def validate_coerce_output_type(output_type): if output_type == "Figure" or output_type == go.Figure: cls = go.Figure elif output_type == "FigureWidget" or ( hasattr(go, "FigureWidget") and output_type == go.FigureWidget ): cls = go.FigureWidget else: raise ValueError( """ Invalid output type: {output_type} Must be one of: 'Figure', 'FigureWidget'""" ) return cls plotly-4.4.1+dfsg.orig/plotly/io/_html.py0000644000175000017500000004727013525746125017704 0ustar noahfxnoahfximport uuid import json import os import webbrowser import six from plotly.io._utils import validate_coerce_fig_to_dict from plotly.offline.offline import _get_jconfig, get_plotlyjs from plotly import utils # Build script to set global PlotlyConfig object. This must execute before # plotly.js is loaded. _window_plotly_config = """\ """ _mathjax_config = """\ """ def to_html( fig, config=None, auto_play=True, include_plotlyjs=True, include_mathjax=False, post_script=None, full_html=True, animation_opts=None, default_width="100%", default_height="100%", validate=True, ): """ Convert a figure to an HTML string representation. Parameters ---------- fig: Figure object or dict representing a figure config: dict or None (default None) Plotly.js figure config options auto_play: bool (default=True) Whether to automatically start the animation sequence on page load if the figure contains frames. Has no effect if the figure does not contain frames. include_plotlyjs: bool or string (default True) Specifies how the plotly.js library is included/loaded in the output div string. If True, a script tag containing the plotly.js source code (~3MB) is included in the output. HTML files generated with this option are fully self-contained and can be used offline. If 'cdn', a script tag that references the plotly.js CDN is included in the output. HTML files generated with this option are about 3MB smaller than those generated with include_plotlyjs=True, but they require an active internet connection in order to load the plotly.js library. If 'directory', a script tag is included that references an external plotly.min.js bundle that is assumed to reside in the same directory as the HTML file. If 'require', Plotly.js is loaded using require.js. This option assumes that require.js is globally available and that it has been globally configured to know how to find Plotly.js as 'plotly'. This option is not advised when full_html=True as it will result in a non-functional html file. If a string that ends in '.js', a script tag is included that references the specified path. This approach can be used to point the resulting HTML file to an alternative CDN or local bundle. If False, no script tag referencing plotly.js is included. This is useful when the resulting div string will be placed inside an HTML document that already loads plotly.js. This option is not advised when full_html=True as it will result in a non-functional html file. include_mathjax: bool or string (default False) Specifies how the MathJax.js library is included in the output html div string. MathJax is required in order to display labels with LaTeX typesetting. If False, no script tag referencing MathJax.js will be included in the output. If 'cdn', a script tag that references a MathJax CDN location will be included in the output. HTML div strings generated with this option will be able to display LaTeX typesetting as long as internet access is available. If a string that ends in '.js', a script tag is included that references the specified path. This approach can be used to point the resulting HTML div string to an alternative CDN. post_script: str or list or None (default None) JavaScript snippet(s) to be included in the resulting div just after plot creation. The string(s) may include '{plot_id}' placeholders that will then be replaced by the `id` of the div element that the plotly.js figure is associated with. One application for this script is to install custom plotly.js event handlers. full_html: bool (default True) If True, produce a string containing a complete HTML document starting with an tag. If False, produce a string containing a single
element. animation_opts: dict or None (default None) dict of custom animation parameters to be passed to the function Plotly.animate in Plotly.js. See https://github.com/plotly/plotly.js/blob/master/src/plots/animation_attributes.js for available options. Has no effect if the figure does not contain frames, or auto_play is False. default_width, default_height: number or str (default '100%') The default figure width/height to use if the provided figure does not specify its own layout.width/layout.height property. May be specified in pixels as an integer (e.g. 500), or as a css width style string (e.g. '500px', '100%'). validate: bool (default True) True if the figure should be validated before being converted to JSON, False otherwise. Returns ------- str Representation of figure as an HTML div string """ # ## Validate figure ## fig_dict = validate_coerce_fig_to_dict(fig, validate) # ## Generate div id ## plotdivid = str(uuid.uuid4()) # ## Serialize figure ## jdata = json.dumps( fig_dict.get("data", []), cls=utils.PlotlyJSONEncoder, sort_keys=True ) jlayout = json.dumps( fig_dict.get("layout", {}), cls=utils.PlotlyJSONEncoder, sort_keys=True ) if fig_dict.get("frames", None): jframes = json.dumps(fig_dict.get("frames", []), cls=utils.PlotlyJSONEncoder) else: jframes = None # ## Serialize figure config ## config = _get_jconfig(config) # Set responsive config.setdefault("responsive", True) # Get div width/height layout_dict = fig_dict.get("layout", {}) template_dict = fig_dict.get("layout", {}).get("template", {}).get("layout", {}) div_width = layout_dict.get("width", template_dict.get("width", default_width)) div_height = layout_dict.get("height", template_dict.get("height", default_height)) # Add 'px' suffix to numeric widths try: float(div_width) except (ValueError, TypeError): pass else: div_width = str(div_width) + "px" try: float(div_height) except (ValueError, TypeError): pass else: div_height = str(div_height) + "px" # ## Get platform URL ## if config.get("showLink", False) or config.get("showSendToCloud", False): # Figure is going to include a Chart Studio link or send-to-cloud button, # So we need to configure the PLOTLYENV.BASE_URL property base_url_line = """ window.PLOTLYENV.BASE_URL='{plotly_platform_url}';\ """.format( plotly_platform_url=config.get("plotlyServerURL", "https://plot.ly") ) else: # Figure is not going to include a Chart Studio link or send-to-cloud button, # In this case we don't want https://plot.ly to show up anywhere in the HTML # output config.pop("plotlyServerURL", None) config.pop("linkText", None) config.pop("showLink", None) base_url_line = "" # ## Build script body ## # This is the part that actually calls Plotly.js # build post script snippet(s) then_post_script = "" if post_script: if not isinstance(post_script, (list, tuple)): post_script = [post_script] for ps in post_script: then_post_script += """.then(function(){{ {post_script} }})""".format( post_script=ps.replace("{plot_id}", plotdivid) ) then_addframes = "" then_animate = "" if jframes: then_addframes = """.then(function(){{ Plotly.addFrames('{id}', {frames}); }})""".format( id=plotdivid, frames=jframes ) if auto_play: if animation_opts: animation_opts_arg = ", " + json.dumps(animation_opts) else: animation_opts_arg = "" then_animate = """.then(function(){{ Plotly.animate('{id}', null{animation_opts}); }})""".format( id=plotdivid, animation_opts=animation_opts_arg ) # Serialize config dict to JSON jconfig = json.dumps(config) script = """ if (document.getElementById("{id}")) {{ Plotly.newPlot( '{id}', {data}, {layout}, {config} ){then_addframes}{then_animate}{then_post_script} }}""".format( id=plotdivid, data=jdata, layout=jlayout, config=jconfig, then_addframes=then_addframes, then_animate=then_animate, then_post_script=then_post_script, ) # ## Handle loading/initializing plotly.js ## include_plotlyjs_orig = include_plotlyjs if isinstance(include_plotlyjs, six.string_types): include_plotlyjs = include_plotlyjs.lower() # Start/end of requirejs block (if any) require_start = "" require_end = "" # Init and load load_plotlyjs = "" # Init plotlyjs. This block needs to run before plotly.js is loaded in # order for MathJax configuration to work properly if include_plotlyjs == "require": require_start = 'require(["plotly"], function(Plotly) {' require_end = "});" elif include_plotlyjs == "cdn": load_plotlyjs = """\ {win_config} \ """.format( win_config=_window_plotly_config ) elif include_plotlyjs == "directory": load_plotlyjs = """\ {win_config} \ """.format( win_config=_window_plotly_config ) elif isinstance(include_plotlyjs, six.string_types) and include_plotlyjs.endswith( ".js" ): load_plotlyjs = """\ {win_config} \ """.format( win_config=_window_plotly_config, url=include_plotlyjs_orig ) elif include_plotlyjs: load_plotlyjs = """\ {win_config} \ """.format( win_config=_window_plotly_config, plotlyjs=get_plotlyjs() ) # ## Handle loading/initializing MathJax ## include_mathjax_orig = include_mathjax if isinstance(include_mathjax, six.string_types): include_mathjax = include_mathjax.lower() mathjax_template = """\ """ if include_mathjax == "cdn": mathjax_script = ( mathjax_template.format( url=( "https://cdnjs.cloudflare.com" "/ajax/libs/mathjax/2.7.5/MathJax.js" ) ) + _mathjax_config ) elif isinstance(include_mathjax, six.string_types) and include_mathjax.endswith( ".js" ): mathjax_script = ( mathjax_template.format(url=include_mathjax_orig) + _mathjax_config ) elif not include_mathjax: mathjax_script = "" else: raise ValueError( """\ Invalid value of type {typ} received as the include_mathjax argument Received value: {val} include_mathjax may be specified as False, 'cdn', or a string ending with '.js' """.format( typ=type(include_mathjax), val=repr(include_mathjax) ) ) plotly_html_div = """\
{mathjax_script} {load_plotlyjs}
""".format( mathjax_script=mathjax_script, load_plotlyjs=load_plotlyjs, id=plotdivid, width=div_width, height=div_height, base_url_line=base_url_line, require_start=require_start, script=script, require_end=require_end, ) if full_html: return """\ {div} """.format( div=plotly_html_div ) else: return plotly_html_div def write_html( fig, file, config=None, auto_play=True, include_plotlyjs=True, include_mathjax=False, post_script=None, full_html=True, animation_opts=None, validate=True, default_width="100%", default_height="100%", auto_open=False, ): """ Write a figure to an HTML file representation Parameters ---------- fig: Figure object or dict representing a figure file: str or writeable A string representing a local file path or a writeable object (e.g. an open file descriptor) config: dict or None (default None) Plotly.js figure config options auto_play: bool (default=True) Whether to automatically start the animation sequence on page load if the figure contains frames. Has no effect if the figure does not contain frames. include_plotlyjs: bool or string (default True) Specifies how the plotly.js library is included/loaded in the output div string. If True, a script tag containing the plotly.js source code (~3MB) is included in the output. HTML files generated with this option are fully self-contained and can be used offline. If 'cdn', a script tag that references the plotly.js CDN is included in the output. HTML files generated with this option are about 3MB smaller than those generated with include_plotlyjs=True, but they require an active internet connection in order to load the plotly.js library. If 'directory', a script tag is included that references an external plotly.min.js bundle that is assumed to reside in the same directory as the HTML file. If `file` is a string to a local file path and `full_html` is True then If 'directory', a script tag is included that references an external plotly.min.js bundle that is assumed to reside in the same directory as the HTML file. If `file` is a string to a local file path and `full_html` is True, then the plotly.min.js bundle is copied into the directory of the resulting HTML file. If a file named plotly.min.js already exists in the output directory then this file is left unmodified and no copy is performed. HTML files generated with this option can be used offline, but they require a copy of the plotly.min.js bundle in the same directory. This option is useful when many figures will be saved as HTML files in the same directory because the plotly.js source code will be included only once per output directory, rather than once per output file. If 'require', Plotly.js is loaded using require.js. This option assumes that require.js is globally available and that it has been globally configured to know how to find Plotly.js as 'plotly'. This option is not advised when full_html=True as it will result in a non-functional html file. If a string that ends in '.js', a script tag is included that references the specified path. This approach can be used to point the resulting HTML file to an alternative CDN or local bundle. If False, no script tag referencing plotly.js is included. This is useful when the resulting div string will be placed inside an HTML document that already loads plotly.js. This option is not advised when full_html=True as it will result in a non-functional html file. include_mathjax: bool or string (default False) Specifies how the MathJax.js library is included in the output html div string. MathJax is required in order to display labels with LaTeX typesetting. If False, no script tag referencing MathJax.js will be included in the output. If 'cdn', a script tag that references a MathJax CDN location will be included in the output. HTML div strings generated with this option will be able to display LaTeX typesetting as long as internet access is available. If a string that ends in '.js', a script tag is included that references the specified path. This approach can be used to point the resulting HTML div string to an alternative CDN. post_script: str or list or None (default None) JavaScript snippet(s) to be included in the resulting div just after plot creation. The string(s) may include '{plot_id}' placeholders that will then be replaced by the `id` of the div element that the plotly.js figure is associated with. One application for this script is to install custom plotly.js event handlers. full_html: bool (default True) If True, produce a string containing a complete HTML document starting with an tag. If False, produce a string containing a single
element. animation_opts: dict or None (default None) dict of custom animation parameters to be passed to the function Plotly.animate in Plotly.js. See https://github.com/plotly/plotly.js/blob/master/src/plots/animation_attributes.js for available options. Has no effect if the figure does not contain frames, or auto_play is False. default_width, default_height: number or str (default '100%') The default figure width/height to use if the provided figure does not specify its own layout.width/layout.height property. May be specified in pixels as an integer (e.g. 500), or as a css width style string (e.g. '500px', '100%'). validate: bool (default True) True if the figure should be validated before being converted to JSON, False otherwise. auto_open: bool (default True If True, open the saved file in a web browser after saving. This argument only applies if `full_html` is True. Returns ------- str Representation of figure as an HTML div string """ # Build HTML string html_str = to_html( fig, config=config, auto_play=auto_play, include_plotlyjs=include_plotlyjs, include_mathjax=include_mathjax, post_script=post_script, full_html=full_html, animation_opts=animation_opts, default_width=default_width, default_height=default_height, validate=validate, ) # Check if file is a string file_is_str = isinstance(file, six.string_types) # Write HTML string if file_is_str: with open(file, "w") as f: f.write(html_str) else: file.write(html_str) # Check if we should copy plotly.min.js to output directory if file_is_str and full_html and include_plotlyjs == "directory": bundle_path = os.path.join(os.path.dirname(file), "plotly.min.js") if not os.path.exists(bundle_path): with open(bundle_path, "w") as f: f.write(get_plotlyjs()) # Handle auto_open if file_is_str and full_html and auto_open: url = "file://" + os.path.abspath(file) webbrowser.open(url) plotly-4.4.1+dfsg.orig/plotly/io/orca.py0000644000175000017500000000020213525746125017505 0ustar noahfxnoahfxfrom ._orca import ( ensure_server, shutdown_server, validate_executable, reset_status, config, status, ) plotly-4.4.1+dfsg.orig/plotly/io/__init__.py0000644000175000017500000000101013551353542020312 0ustar noahfxnoahfxfrom ._orca import to_image, write_image from . import orca from ._json import to_json, from_json, read_json, write_json from ._templates import templates, to_templated from ._html import to_html, write_html from ._renderers import renderers, show from . import base_renderers __all__ = [ "to_image", "write_image", "to_json", "from_json", "read_json", "write_json", "templates", "to_templated", "to_html", "write_html", "renderers", "show", "base_renderers", ] plotly-4.4.1+dfsg.orig/plotly/io/_base_renderers.py0000644000175000017500000005670013551561056021716 0ustar noahfxnoahfxfrom __future__ import absolute_import import base64 import json import webbrowser import inspect import os from os.path import isdir import six from plotly.io import to_json, to_image, write_image, write_html from plotly import utils, optional_imports from plotly.io._orca import ensure_server from plotly.offline.offline import _get_jconfig, get_plotlyjs from plotly.tools import return_figure_from_figure_or_data ipython_display = optional_imports.get_module("IPython.display") IPython = optional_imports.get_module("IPython") try: from http.server import BaseHTTPRequestHandler, HTTPServer except ImportError: # Python 2.7 from BaseHTTPServer import BaseHTTPRequestHandler, HTTPServer class BaseRenderer(object): """ Base class for all renderers """ def activate(self): pass def __repr__(self): try: init_sig = inspect.signature(self.__init__) init_args = list(init_sig.parameters.keys()) except AttributeError: # Python 2.7 argspec = inspect.getargspec(self.__init__) init_args = [a for a in argspec.args if a != "self"] return "{cls}({attrs})\n{doc}".format( cls=self.__class__.__name__, attrs=", ".join("{}={!r}".format(k, self.__dict__[k]) for k in init_args), doc=self.__doc__, ) def __hash__(self): # Constructor args fully define uniqueness return hash(repr(self)) class MimetypeRenderer(BaseRenderer): """ Base class for all mime type renderers """ def to_mimebundle(self, fig_dict): raise NotImplementedError() class JsonRenderer(MimetypeRenderer): """ Renderer to display figures as JSON hierarchies. This renderer is compatible with JupyterLab and VSCode. mime type: 'application/json' """ def to_mimebundle(self, fig_dict): value = json.loads(to_json(fig_dict, validate=False, remove_uids=False)) return {"application/json": value} # Plotly mimetype class PlotlyRenderer(MimetypeRenderer): """ Renderer to display figures using the plotly mime type. This renderer is compatible with JupyterLab (using the @jupyterlab/plotly-extension), VSCode, and nteract. mime type: 'application/vnd.plotly.v1+json' """ def __init__(self, config=None): self.config = dict(config) if config else {} def to_mimebundle(self, fig_dict): config = _get_jconfig(self.config) if config: fig_dict["config"] = config json_compatible_fig_dict = json.loads( to_json(fig_dict, validate=False, remove_uids=False) ) return {"application/vnd.plotly.v1+json": json_compatible_fig_dict} # Static Image class ImageRenderer(MimetypeRenderer): """ Base class for all static image renderers """ def __init__( self, mime_type, b64_encode=False, format=None, width=None, height=None, scale=None, ): self.mime_type = mime_type self.b64_encode = b64_encode self.format = format self.width = width self.height = height self.scale = scale def activate(self): # Start up orca server to reduce the delay on first render ensure_server() def to_mimebundle(self, fig_dict): image_bytes = to_image( fig_dict, format=self.format, width=self.width, height=self.height, scale=self.scale, validate=False, ) if self.b64_encode: image_str = base64.b64encode(image_bytes).decode("utf8") else: image_str = image_bytes.decode("utf8") return {self.mime_type: image_str} class PngRenderer(ImageRenderer): """ Renderer to display figures as static PNG images. This renderer requires the orca command-line utility and is broadly compatible across IPython environments (classic Jupyter Notebook, JupyterLab, QtConsole, VSCode, PyCharm, etc) and nbconvert targets (HTML, PDF, etc.). mime type: 'image/png' """ def __init__(self, width=None, height=None, scale=None): super(PngRenderer, self).__init__( mime_type="image/png", b64_encode=True, format="png", width=width, height=height, scale=scale, ) class SvgRenderer(ImageRenderer): """ Renderer to display figures as static SVG images. This renderer requires the orca command-line utility and is broadly compatible across IPython environments (classic Jupyter Notebook, JupyterLab, QtConsole, VSCode, PyCharm, etc) and nbconvert targets (HTML, PDF, etc.). mime type: 'image/svg+xml' """ def __init__(self, width=None, height=None, scale=None): super(SvgRenderer, self).__init__( mime_type="image/svg+xml", b64_encode=False, format="svg", width=width, height=height, scale=scale, ) class JpegRenderer(ImageRenderer): """ Renderer to display figures as static JPEG images. This renderer requires the orca command-line utility and is broadly compatible across IPython environments (classic Jupyter Notebook, JupyterLab, QtConsole, VSCode, PyCharm, etc) and nbconvert targets (HTML, PDF, etc.). mime type: 'image/jpeg' """ def __init__(self, width=None, height=None, scale=None): super(JpegRenderer, self).__init__( mime_type="image/jpeg", b64_encode=True, format="jpg", width=width, height=height, scale=scale, ) class PdfRenderer(ImageRenderer): """ Renderer to display figures as static PDF images. This renderer requires the orca command-line utility and is compatible with JupyterLab and the LaTeX-based nbconvert export to PDF. mime type: 'application/pdf' """ def __init__(self, width=None, height=None, scale=None): super(PdfRenderer, self).__init__( mime_type="application/pdf", b64_encode=True, format="pdf", width=width, height=height, scale=scale, ) # HTML # Build script to set global PlotlyConfig object. This must execute before # plotly.js is loaded. _window_plotly_config = """\ window.PlotlyConfig = {MathJaxConfig: 'local'};""" _mathjax_config = """\ if (window.MathJax) {MathJax.Hub.Config({SVG: {font: "STIX-Web"}});}""" class HtmlRenderer(MimetypeRenderer): """ Base class for all HTML mime type renderers mime type: 'text/html' """ def __init__( self, connected=False, full_html=False, requirejs=True, global_init=False, config=None, auto_play=False, post_script=None, animation_opts=None, ): self.config = dict(config) if config else {} self.auto_play = auto_play self.connected = connected self.global_init = global_init self.requirejs = requirejs self.full_html = full_html self.animation_opts = animation_opts self.post_script = post_script def activate(self): if self.global_init: if not ipython_display: raise ValueError( "The {cls} class requires ipython but it is not installed".format( cls=self.__class__.__name__ ) ) if not self.requirejs: raise ValueError("global_init is only supported with requirejs=True") if self.connected: # Connected so we configure requirejs with the plotly CDN script = """\ """.format( win_config=_window_plotly_config, mathjax_config=_mathjax_config ) else: # If not connected then we embed a copy of the plotly.js # library in the notebook script = """\ """.format( script=get_plotlyjs(), win_config=_window_plotly_config, mathjax_config=_mathjax_config, ) ipython_display.display_html(script, raw=True) def to_mimebundle(self, fig_dict): from plotly.io import to_html if self.requirejs: include_plotlyjs = "require" include_mathjax = False elif self.connected: include_plotlyjs = "cdn" include_mathjax = "cdn" else: include_plotlyjs = True include_mathjax = "cdn" # build post script post_script = [ """ var gd = document.getElementById('{plot_id}'); var x = new MutationObserver(function (mutations, observer) {{ var display = window.getComputedStyle(gd).display; if (!display || display === 'none') {{ console.log([gd, 'removed!']); Plotly.purge(gd); observer.disconnect(); }} }}); // Listen for the removal of the full notebook cells var notebookContainer = gd.closest('#notebook-container'); if (notebookContainer) {{ x.observe(notebookContainer, {childList: true}); }} // Listen for the clearing of the current output cell var outputEl = gd.closest('.output'); if (outputEl) {{ x.observe(outputEl, {childList: true}); }} """ ] # Add user defined post script if self.post_script: if not isinstance(self.post_script, (list, tuple)): post_script.append(self.post_script) else: post_script.extend(self.post_script) html = to_html( fig_dict, config=self.config, auto_play=self.auto_play, include_plotlyjs=include_plotlyjs, include_mathjax=include_mathjax, post_script=post_script, full_html=self.full_html, animation_opts=self.animation_opts, default_width="100%", default_height=525, validate=False, ) return {"text/html": html} class NotebookRenderer(HtmlRenderer): """ Renderer to display interactive figures in the classic Jupyter Notebook. This renderer is also useful for notebooks that will be converted to HTML using nbconvert/nbviewer as it will produce standalone HTML files that include interactive figures. This renderer automatically performs global notebook initialization when activated. mime type: 'text/html' """ def __init__( self, connected=False, config=None, auto_play=False, post_script=None, animation_opts=None, ): super(NotebookRenderer, self).__init__( connected=connected, full_html=False, requirejs=True, global_init=True, config=config, auto_play=auto_play, post_script=post_script, animation_opts=animation_opts, ) class KaggleRenderer(HtmlRenderer): """ Renderer to display interactive figures in Kaggle Notebooks. Same as NotebookRenderer but with connected=True so that the plotly.js bundle is loaded from a CDN rather than being embedded in the notebook. This renderer is enabled by default when running in a Kaggle notebook. mime type: 'text/html' """ def __init__( self, config=None, auto_play=False, post_script=None, animation_opts=None ): super(KaggleRenderer, self).__init__( connected=True, full_html=False, requirejs=True, global_init=True, config=config, auto_play=auto_play, post_script=post_script, animation_opts=animation_opts, ) class AzureRenderer(HtmlRenderer): """ Renderer to display interactive figures in Azure Notebooks. Same as NotebookRenderer but with connected=True so that the plotly.js bundle is loaded from a CDN rather than being embedded in the notebook. This renderer is enabled by default when running in an Azure notebook. mime type: 'text/html' """ def __init__( self, config=None, auto_play=False, post_script=None, animation_opts=None ): super(AzureRenderer, self).__init__( connected=True, full_html=False, requirejs=True, global_init=True, config=config, auto_play=auto_play, post_script=post_script, animation_opts=animation_opts, ) class ColabRenderer(HtmlRenderer): """ Renderer to display interactive figures in Google Colab Notebooks. This renderer is enabled by default when running in a Colab notebook. mime type: 'text/html' """ def __init__( self, config=None, auto_play=False, post_script=None, animation_opts=None ): super(ColabRenderer, self).__init__( connected=True, full_html=True, requirejs=False, global_init=False, config=config, auto_play=auto_play, post_script=post_script, animation_opts=animation_opts, ) class IFrameRenderer(MimetypeRenderer): """ Renderer to display interactive figures using an IFrame. HTML representations of Figures are saved to an `iframe_figures/` directory and iframe HTML elements that reference these files are inserted into the notebook. With this approach, neither plotly.js nor the figure data are embedded in the notebook, so this is a good choice for notebooks that contain so many large figures that basic operations (like saving and opening) become very slow. Notebooks using this renderer will display properly when exported to HTML as long as the `iframe_figures/` directory is placed in the same directory as the exported html file. Note that the HTML files in `iframe_figures/` are numbered according to the IPython cell execution count and so they will start being overwritten each time the kernel is restarted. This directory may be deleted whenever the kernel is restarted and it will be automatically recreated. mime type: 'text/html' """ def __init__( self, config=None, auto_play=False, post_script=None, animation_opts=None, include_plotlyjs=True, html_directory="iframe_figures", ): self.config = config self.auto_play = auto_play self.post_script = post_script self.animation_opts = animation_opts self.include_plotlyjs = include_plotlyjs self.html_directory = html_directory def to_mimebundle(self, fig_dict): from plotly.io import write_html # Make iframe size slightly larger than figure size to avoid # having iframe have its own scroll bar. iframe_buffer = 20 layout = fig_dict.get("layout", {}) if layout.get("width", False): iframe_width = str(layout["width"] + iframe_buffer) + "px" else: iframe_width = "100%" if layout.get("height", False): iframe_height = layout["height"] + iframe_buffer else: iframe_height = str(525 + iframe_buffer) + "px" # Build filename using ipython cell number filename = self.build_filename() # Make directory for try: os.makedirs(self.html_directory) except OSError as error: if not isdir(self.html_directory): raise write_html( fig_dict, filename, config=self.config, auto_play=self.auto_play, include_plotlyjs=self.include_plotlyjs, include_mathjax="cdn", auto_open=False, post_script=self.post_script, animation_opts=self.animation_opts, default_width="100%", default_height=525, validate=False, ) # Build IFrame iframe_html = """\ """.format( width=iframe_width, height=iframe_height, src=self.build_url(filename) ) return {"text/html": iframe_html} def build_filename(self): ip = IPython.get_ipython() if IPython else None cell_number = list(ip.history_manager.get_tail(1))[0][1] + 1 if ip else 0 filename = "{dirname}/figure_{cell_number}.html".format( dirname=self.html_directory, cell_number=cell_number ) return filename def build_url(self, filename): return filename class CoCalcRenderer(IFrameRenderer): _render_count = 0 def build_filename(self): filename = "{dirname}/figure_{render_count}.html".format( dirname=self.html_directory, render_count=CoCalcRenderer._render_count ) CoCalcRenderer._render_count += 1 return filename def build_url(self, filename): return "{filename}?fullscreen=kiosk".format(filename=filename) class ExternalRenderer(BaseRenderer): """ Base class for external renderers. ExternalRenderer subclasses do not display figures inline in a notebook environment, but render figures by some external means (e.g. a separate browser tab). Unlike MimetypeRenderer subclasses, ExternalRenderer subclasses are not invoked when a figure is asked to display itself in the notebook. Instead, they are invoked when the plotly.io.show function is called on a figure. """ def render(self, fig): raise NotImplementedError() def open_html_in_browser(html, using=None, new=0, autoraise=True): """ Display html in a web browser without creating a temp file. Instantiates a trivial http server and uses the webbrowser module to open a URL to retrieve html from that server. Parameters ---------- html: str HTML string to display using, new, autoraise: See docstrings in webbrowser.get and webbrowser.open """ if isinstance(html, six.string_types): html = html.encode("utf8") class OneShotRequestHandler(BaseHTTPRequestHandler): def do_GET(self): self.send_response(200) self.send_header("Content-type", "text/html") self.end_headers() bufferSize = 1024 * 1024 for i in range(0, len(html), bufferSize): self.wfile.write(html[i : i + bufferSize]) def log_message(self, format, *args): # Silence stderr logging pass server = HTTPServer(("127.0.0.1", 0), OneShotRequestHandler) webbrowser.get(using).open( "http://127.0.0.1:%s" % server.server_port, new=new, autoraise=autoraise ) server.handle_request() class BrowserRenderer(ExternalRenderer): """ Renderer to display interactive figures in an external web browser. This renderer will open a new browser window or tab when the plotly.io.show function is called on a figure. This renderer has no ipython/jupyter dependencies and is a good choice for use in environments that do not support the inline display of interactive figures. mime type: 'text/html' """ def __init__( self, config=None, auto_play=False, using=None, new=0, autoraise=True, post_script=None, animation_opts=None, ): self.config = config self.auto_play = auto_play self.using = using self.new = new self.autoraise = autoraise self.post_script = post_script self.animation_opts = animation_opts def render(self, fig_dict): from plotly.io import to_html html = to_html( fig_dict, config=self.config, auto_play=self.auto_play, include_plotlyjs=True, include_mathjax="cdn", post_script=self.post_script, full_html=True, animation_opts=self.animation_opts, default_width="100%", default_height="100%", validate=False, ) open_html_in_browser(html, self.using, self.new, self.autoraise) class DatabricksRenderer(ExternalRenderer): def __init__( self, config=None, auto_play=False, post_script=None, animation_opts=None, include_plotlyjs="cdn", ): self.config = config self.auto_play = auto_play self.post_script = post_script self.animation_opts = animation_opts self.include_plotlyjs = include_plotlyjs self._displayHTML = None @property def displayHTML(self): import inspect if self._displayHTML is None: for frame in inspect.getouterframes(inspect.currentframe()): global_names = set(frame.frame.f_globals) # Check for displayHTML plus a few others to reduce chance of a false # hit. if all(v in global_names for v in ["displayHTML", "display", "spark"]): self._displayHTML = frame.frame.f_globals["displayHTML"] break if self._displayHTML is None: raise EnvironmentError( """ Unable to detect the Databricks displayHTML function. The 'databricks' renderer is only supported when called from within the Databricks notebook environment.""" ) return self._displayHTML def render(self, fig_dict): from plotly.io import to_html html = to_html( fig_dict, config=self.config, auto_play=self.auto_play, include_plotlyjs=self.include_plotlyjs, include_mathjax="cdn", post_script=self.post_script, full_html=True, animation_opts=self.animation_opts, default_width="100%", default_height="100%", validate=False, ) # displayHTML is a Databricks notebook built-in function self.displayHTML(html) class SphinxGalleryRenderer(ExternalRenderer): def render(self, fig_dict): stack = inspect.stack() # Name of script from which plot function was called is retrieved try: filename = stack[3].filename # let's hope this is robust... except: # python 2 filename = stack[3][1] filename_root, _ = os.path.splitext(filename) filename_html = filename_root + ".html" filename_png = filename_root + ".png" figure = return_figure_from_figure_or_data(fig_dict, True) _ = write_html(fig_dict, file=filename_html) write_image(figure, filename_png) plotly-4.4.1+dfsg.orig/plotly/io/base_renderers.py0000644000175000017500000000045713525746125021560 0ustar noahfxnoahfxfrom ._base_renderers import ( MimetypeRenderer, PlotlyRenderer, JsonRenderer, ImageRenderer, PngRenderer, SvgRenderer, PdfRenderer, JpegRenderer, HtmlRenderer, ColabRenderer, KaggleRenderer, NotebookRenderer, ExternalRenderer, BrowserRenderer, ) plotly-4.4.1+dfsg.orig/plotlywidget/0000755000175000017500000000000013573746614017020 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotlywidget/static/0000755000175000017500000000000013573746614020307 5ustar noahfxnoahfxplotly-4.4.1+dfsg.orig/plotlywidget/static/extension.js0000644000175000017500000000572313573746602022665 0ustar noahfxnoahfxdefine(function() { return /******/ (function(modules) { // webpackBootstrap /******/ // The module cache /******/ var installedModules = {}; /******/ /******/ // The require function /******/ function __webpack_require__(moduleId) { /******/ /******/ // Check if module is in cache /******/ if(installedModules[moduleId]) { /******/ return installedModules[moduleId].exports; /******/ } /******/ // Create a new module (and put it into the cache) /******/ var module = installedModules[moduleId] = { /******/ i: moduleId, /******/ l: false, /******/ exports: {} /******/ }; /******/ /******/ // Execute the module function /******/ modules[moduleId].call(module.exports, module, module.exports, __webpack_require__); /******/ /******/ // Flag the module as loaded /******/ module.l = true; /******/ /******/ // Return the exports of the module /******/ return module.exports; /******/ } /******/ /******/ /******/ // expose the modules object (__webpack_modules__) /******/ __webpack_require__.m = modules; /******/ /******/ // expose the module cache /******/ __webpack_require__.c = installedModules; /******/ /******/ // define getter function for harmony exports /******/ __webpack_require__.d = function(exports, name, getter) { /******/ if(!__webpack_require__.o(exports, name)) { /******/ Object.defineProperty(exports, name, { /******/ configurable: false, /******/ enumerable: true, /******/ get: getter /******/ }); /******/ } /******/ }; /******/ /******/ // getDefaultExport function for compatibility with non-harmony modules /******/ __webpack_require__.n = function(module) { /******/ var getter = module && module.__esModule ? 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d3_map_zero + key : key; } function d3_map_unescape(key) { return (key += "")[0] === d3_map_zero ? key.slice(1) : key; } function d3_map_has(key) { return d3_map_escape(key) in this._; } function d3_map_remove(key) { return (key = d3_map_escape(key)) in this._ && delete this._[key]; } function d3_map_keys() { var keys = []; for (var key in this._) keys.push(d3_map_unescape(key)); return keys; } function d3_map_size() { var size = 0; for (var key in this._) ++size; return size; } function d3_map_empty() { for (var key in this._) return false; return true; } d3.nest = function() { var nest = {}, keys = [], sortKeys = [], sortValues, rollup; function map(mapType, array, depth) { if (depth >= keys.length) return rollup ? rollup.call(nest, array) : sortValues ? array.sort(sortValues) : array; var i = -1, n = array.length, key = keys[depth++], keyValue, object, setter, valuesByKey = new d3_Map(), values; while (++i < n) { if (values = valuesByKey.get(keyValue = key(object = array[i]))) { values.push(object); } else { valuesByKey.set(keyValue, [ object ]); } } if (mapType) { object = mapType(); setter = function(keyValue, values) { object.set(keyValue, map(mapType, values, depth)); }; } else { object = {}; setter = function(keyValue, values) { object[keyValue] = map(mapType, values, depth); }; } valuesByKey.forEach(setter); return object; } function entries(map, depth) { if (depth >= keys.length) return map; var array = [], sortKey = sortKeys[depth++]; map.forEach(function(key, keyMap) { array.push({ key: key, values: entries(keyMap, depth) }); }); return sortKey ? array.sort(function(a, b) { return sortKey(a.key, b.key); }) : array; } nest.map = function(array, mapType) { return map(mapType, array, 0); }; nest.entries = function(array) { return entries(map(d3.map, array, 0), 0); }; nest.key = function(d) { keys.push(d); return nest; }; nest.sortKeys = function(order) { sortKeys[keys.length - 1] = order; return nest; }; nest.sortValues = function(order) { sortValues = order; return nest; }; nest.rollup = function(f) { rollup = f; return nest; }; return nest; }; d3.set = function(array) { var set = new d3_Set(); if (array) for (var i = 0, n = array.length; i < n; ++i) set.add(array[i]); return set; }; function d3_Set() { this._ = Object.create(null); } d3_class(d3_Set, { has: d3_map_has, add: function(key) { this._[d3_map_escape(key += "")] = true; return key; }, remove: d3_map_remove, values: d3_map_keys, size: d3_map_size, empty: d3_map_empty, forEach: function(f) { for (var key in this._) f.call(this, d3_map_unescape(key)); } }); d3.behavior = {}; function d3_identity(d) { return d; } d3.rebind = function(target, source) { var i = 1, n = arguments.length, method; while (++i < n) target[method = arguments[i]] = d3_rebind(target, source, source[method]); return target; }; function d3_rebind(target, source, method) { return function() { var value = method.apply(source, arguments); return value === source ? target : value; }; } function d3_vendorSymbol(object, name) { if (name in object) return name; name = name.charAt(0).toUpperCase() + name.slice(1); for (var i = 0, n = d3_vendorPrefixes.length; i < n; ++i) { var prefixName = d3_vendorPrefixes[i] + name; if (prefixName in object) return prefixName; } } var d3_vendorPrefixes = [ "webkit", "ms", "moz", "Moz", "o", "O" ]; function d3_noop() {} d3.dispatch = function() { var dispatch = new d3_dispatch(), i = -1, n = arguments.length; while (++i < n) dispatch[arguments[i]] = d3_dispatch_event(dispatch); return dispatch; }; function d3_dispatch() {} d3_dispatch.prototype.on = function(type, listener) { var i = type.indexOf("."), name = ""; if (i >= 0) { name = type.slice(i + 1); type = type.slice(0, i); } if (type) return arguments.length < 2 ? this[type].on(name) : this[type].on(name, listener); if (arguments.length === 2) { if (listener == null) for (type in this) { if (this.hasOwnProperty(type)) this[type].on(name, null); } return this; } }; function d3_dispatch_event(dispatch) { var listeners = [], listenerByName = new d3_Map(); function event() { var z = listeners, i = -1, n = z.length, l; while (++i < n) if (l = z[i].on) l.apply(this, arguments); return dispatch; } event.on = function(name, listener) { var l = listenerByName.get(name), i; if (arguments.length < 2) return l && l.on; if (l) { l.on = null; listeners = listeners.slice(0, i = listeners.indexOf(l)).concat(listeners.slice(i + 1)); listenerByName.remove(name); } if (listener) listeners.push(listenerByName.set(name, { on: listener })); return dispatch; }; return event; } d3.event = null; function d3_eventPreventDefault() { d3.event.preventDefault(); } function d3_eventSource() { var e = d3.event, s; while (s = e.sourceEvent) e = s; return e; } function d3_eventDispatch(target) { var dispatch = new d3_dispatch(), i = 0, n = arguments.length; while (++i < n) dispatch[arguments[i]] = d3_dispatch_event(dispatch); dispatch.of = function(thiz, argumentz) { return function(e1) { try { var e0 = e1.sourceEvent = d3.event; e1.target = target; d3.event = e1; dispatch[e1.type].apply(thiz, argumentz); } finally { d3.event = e0; } }; }; return dispatch; } d3.requote = function(s) { return s.replace(d3_requote_re, "\\$&"); }; var d3_requote_re = /[\\\^\$\*\+\?\|\[\]\(\)\.\{\}]/g; var d3_subclass = {}.__proto__ ? function(object, prototype) { object.__proto__ = prototype; } : function(object, prototype) { for (var property in prototype) object[property] = prototype[property]; }; function d3_selection(groups) { d3_subclass(groups, d3_selectionPrototype); return groups; } var d3_select = function(s, n) { return n.querySelector(s); }, d3_selectAll = function(s, n) { return n.querySelectorAll(s); }, d3_selectMatches = function(n, s) { var d3_selectMatcher = n.matches || n[d3_vendorSymbol(n, "matchesSelector")]; d3_selectMatches = function(n, s) { return d3_selectMatcher.call(n, s); }; return d3_selectMatches(n, s); }; if (typeof Sizzle === "function") { d3_select = function(s, n) { return Sizzle(s, n)[0] || null; }; d3_selectAll = Sizzle; d3_selectMatches = Sizzle.matchesSelector; } d3.selection = function() { return d3.select(d3_document.documentElement); }; var d3_selectionPrototype = d3.selection.prototype = []; d3_selectionPrototype.select = function(selector) { var subgroups = [], subgroup, subnode, group, node; selector = d3_selection_selector(selector); for (var j = -1, m = this.length; ++j < m; ) { subgroups.push(subgroup = []); subgroup.parentNode = (group = this[j]).parentNode; for (var i = -1, n = group.length; ++i < n; ) { if (node = group[i]) { subgroup.push(subnode = selector.call(node, node.__data__, i, j)); if (subnode && "__data__" in node) subnode.__data__ = node.__data__; } else { subgroup.push(null); } } } return d3_selection(subgroups); }; function d3_selection_selector(selector) { return typeof selector === "function" ? selector : function() { return d3_select(selector, this); }; } d3_selectionPrototype.selectAll = function(selector) { var subgroups = [], subgroup, node; selector = d3_selection_selectorAll(selector); for (var j = -1, m = this.length; ++j < m; ) { for (var group = this[j], i = -1, n = group.length; ++i < n; ) { if (node = group[i]) { subgroups.push(subgroup = d3_array(selector.call(node, node.__data__, i, j))); subgroup.parentNode = node; } } } return d3_selection(subgroups); }; function d3_selection_selectorAll(selector) { return typeof selector === "function" ? selector : function() { return d3_selectAll(selector, this); }; } var d3_nsXhtml = "http://www.w3.org/1999/xhtml"; var d3_nsPrefix = { svg: "http://www.w3.org/2000/svg", xhtml: d3_nsXhtml, xlink: "http://www.w3.org/1999/xlink", xml: "http://www.w3.org/XML/1998/namespace", xmlns: "http://www.w3.org/2000/xmlns/" }; d3.ns = { prefix: d3_nsPrefix, qualify: function(name) { var i = name.indexOf(":"), prefix = name; if (i >= 0 && (prefix = name.slice(0, i)) !== "xmlns") name = name.slice(i + 1); return d3_nsPrefix.hasOwnProperty(prefix) ? { space: d3_nsPrefix[prefix], local: name } : name; } }; d3_selectionPrototype.attr = function(name, value) { if (arguments.length < 2) { if (typeof name === "string") { var node = this.node(); name = d3.ns.qualify(name); return name.local ? node.getAttributeNS(name.space, name.local) : node.getAttribute(name); } for (value in name) this.each(d3_selection_attr(value, name[value])); return this; } return this.each(d3_selection_attr(name, value)); }; function d3_selection_attr(name, value) { name = d3.ns.qualify(name); function attrNull() { this.removeAttribute(name); } function attrNullNS() { this.removeAttributeNS(name.space, name.local); } function attrConstant() { this.setAttribute(name, value); } function attrConstantNS() { this.setAttributeNS(name.space, name.local, value); } function attrFunction() { var x = value.apply(this, arguments); if (x == null) this.removeAttribute(name); else this.setAttribute(name, x); } function attrFunctionNS() { var x = value.apply(this, arguments); if (x == null) this.removeAttributeNS(name.space, name.local); else this.setAttributeNS(name.space, name.local, x); } return value == null ? name.local ? attrNullNS : attrNull : typeof value === "function" ? name.local ? attrFunctionNS : attrFunction : name.local ? attrConstantNS : attrConstant; } function d3_collapse(s) { return s.trim().replace(/\s+/g, " "); } d3_selectionPrototype.classed = function(name, value) { if (arguments.length < 2) { if (typeof name === "string") { var node = this.node(), n = (name = d3_selection_classes(name)).length, i = -1; if (value = node.classList) { while (++i < n) if (!value.contains(name[i])) return false; } else { value = node.getAttribute("class"); while (++i < n) if (!d3_selection_classedRe(name[i]).test(value)) return false; } return true; } for (value in name) this.each(d3_selection_classed(value, name[value])); return this; } return this.each(d3_selection_classed(name, value)); }; function d3_selection_classedRe(name) { return new RegExp("(?:^|\\s+)" + d3.requote(name) + "(?:\\s+|$)", "g"); } function d3_selection_classes(name) { return (name + "").trim().split(/^|\s+/); } function d3_selection_classed(name, value) { name = d3_selection_classes(name).map(d3_selection_classedName); var n = name.length; function classedConstant() { var i = -1; while (++i < n) name[i](this, value); } function classedFunction() { var i = -1, x = value.apply(this, arguments); while (++i < n) name[i](this, x); } return typeof value === "function" ? classedFunction : classedConstant; } function d3_selection_classedName(name) { var re = d3_selection_classedRe(name); return function(node, value) { if (c = node.classList) return value ? c.add(name) : c.remove(name); var c = node.getAttribute("class") || ""; if (value) { re.lastIndex = 0; if (!re.test(c)) node.setAttribute("class", d3_collapse(c + " " + name)); } else { node.setAttribute("class", d3_collapse(c.replace(re, " "))); } }; } d3_selectionPrototype.style = function(name, value, priority) { var n = arguments.length; if (n < 3) { if (typeof name !== "string") { if (n < 2) value = ""; for (priority in name) this.each(d3_selection_style(priority, name[priority], value)); return this; } if (n < 2) { var node = this.node(); return d3_window(node).getComputedStyle(node, null).getPropertyValue(name); } priority = ""; } return this.each(d3_selection_style(name, value, priority)); }; function d3_selection_style(name, value, priority) { function styleNull() { this.style.removeProperty(name); } function styleConstant() { this.style.setProperty(name, value, priority); } function styleFunction() { var x = value.apply(this, arguments); if (x == null) this.style.removeProperty(name); else this.style.setProperty(name, x, priority); } return value == null ? styleNull : typeof value === "function" ? styleFunction : styleConstant; } d3_selectionPrototype.property = function(name, value) { if (arguments.length < 2) { if (typeof name === "string") return this.node()[name]; for (value in name) this.each(d3_selection_property(value, name[value])); return this; } return this.each(d3_selection_property(name, value)); }; function d3_selection_property(name, value) { function propertyNull() { delete this[name]; } function propertyConstant() { this[name] = value; } function propertyFunction() { var x = value.apply(this, arguments); if (x == null) delete this[name]; else this[name] = x; } return value == null ? propertyNull : typeof value === "function" ? propertyFunction : propertyConstant; } d3_selectionPrototype.text = function(value) { return arguments.length ? this.each(typeof value === "function" ? function() { var v = value.apply(this, arguments); this.textContent = v == null ? "" : v; } : value == null ? function() { this.textContent = ""; } : function() { this.textContent = value; }) : this.node().textContent; }; d3_selectionPrototype.html = function(value) { return arguments.length ? this.each(typeof value === "function" ? function() { var v = value.apply(this, arguments); this.innerHTML = v == null ? "" : v; } : value == null ? function() { this.innerHTML = ""; } : function() { this.innerHTML = value; }) : this.node().innerHTML; }; d3_selectionPrototype.append = function(name) { name = d3_selection_creator(name); return this.select(function() { return this.appendChild(name.apply(this, arguments)); }); }; function d3_selection_creator(name) { function create() { var document = this.ownerDocument, namespace = this.namespaceURI; return namespace === d3_nsXhtml && document.documentElement.namespaceURI === d3_nsXhtml ? document.createElement(name) : document.createElementNS(namespace, name); } function createNS() { return this.ownerDocument.createElementNS(name.space, name.local); } return typeof name === "function" ? name : (name = d3.ns.qualify(name)).local ? createNS : create; } d3_selectionPrototype.insert = function(name, before) { name = d3_selection_creator(name); before = d3_selection_selector(before); return this.select(function() { return this.insertBefore(name.apply(this, arguments), before.apply(this, arguments) || null); }); }; d3_selectionPrototype.remove = function() { return this.each(d3_selectionRemove); }; function d3_selectionRemove() { var parent = this.parentNode; if (parent) parent.removeChild(this); } d3_selectionPrototype.data = function(value, key) { var i = -1, n = this.length, group, node; if (!arguments.length) { value = new Array(n = (group = this[0]).length); while (++i < n) { if (node = group[i]) { value[i] = node.__data__; } } return value; } function bind(group, groupData) { var i, n = group.length, m = groupData.length, n0 = Math.min(n, m), updateNodes = new Array(m), enterNodes = new Array(m), exitNodes = new Array(n), node, nodeData; if (key) { var nodeByKeyValue = new d3_Map(), keyValues = new Array(n), keyValue; for (i = -1; ++i < n; ) { if (node = group[i]) { if (nodeByKeyValue.has(keyValue = key.call(node, node.__data__, i))) { exitNodes[i] = node; } else { nodeByKeyValue.set(keyValue, node); } keyValues[i] = keyValue; } } for (i = -1; ++i < m; ) { if (!(node = nodeByKeyValue.get(keyValue = key.call(groupData, nodeData = groupData[i], i)))) { enterNodes[i] = d3_selection_dataNode(nodeData); } else if (node !== true) { updateNodes[i] = node; node.__data__ = nodeData; } nodeByKeyValue.set(keyValue, true); } for (i = -1; ++i < n; ) { if (i in keyValues && nodeByKeyValue.get(keyValues[i]) !== true) { exitNodes[i] = group[i]; } } } else { for (i = -1; ++i < n0; ) { node = group[i]; nodeData = groupData[i]; if (node) { node.__data__ = nodeData; updateNodes[i] = node; } else { enterNodes[i] = d3_selection_dataNode(nodeData); } } for (;i < m; ++i) { enterNodes[i] = d3_selection_dataNode(groupData[i]); } for (;i < n; ++i) { exitNodes[i] = group[i]; } } enterNodes.update = updateNodes; enterNodes.parentNode = updateNodes.parentNode = exitNodes.parentNode = group.parentNode; enter.push(enterNodes); update.push(updateNodes); exit.push(exitNodes); } var enter = d3_selection_enter([]), update = d3_selection([]), exit = d3_selection([]); if (typeof value === "function") { while (++i < n) { bind(group = this[i], value.call(group, group.parentNode.__data__, i)); } } else { while (++i < n) { bind(group = this[i], value); } } update.enter = function() { return enter; }; update.exit = function() { return exit; }; return update; }; function d3_selection_dataNode(data) { return { __data__: data }; } d3_selectionPrototype.datum = function(value) { return arguments.length ? this.property("__data__", value) : this.property("__data__"); }; d3_selectionPrototype.filter = function(filter) { var subgroups = [], subgroup, group, node; if (typeof filter !== "function") filter = d3_selection_filter(filter); for (var j = 0, m = this.length; j < m; j++) { subgroups.push(subgroup = []); subgroup.parentNode = (group = this[j]).parentNode; for (var i = 0, n = group.length; i < n; i++) { if ((node = group[i]) && filter.call(node, node.__data__, i, j)) { subgroup.push(node); } } } return d3_selection(subgroups); }; function d3_selection_filter(selector) { return function() { return d3_selectMatches(this, selector); }; } d3_selectionPrototype.order = function() { for (var j = -1, m = this.length; ++j < m; ) { for (var group = this[j], i = group.length - 1, next = group[i], node; --i >= 0; ) { if (node = group[i]) { if (next && next !== node.nextSibling) next.parentNode.insertBefore(node, next); next = node; } } } return this; }; d3_selectionPrototype.sort = function(comparator) { comparator = d3_selection_sortComparator.apply(this, arguments); for (var j = -1, m = this.length; ++j < m; ) this[j].sort(comparator); return this.order(); }; function d3_selection_sortComparator(comparator) { if (!arguments.length) comparator = d3_ascending; return function(a, b) { return a && b ? comparator(a.__data__, b.__data__) : !a - !b; }; } d3_selectionPrototype.each = function(callback) { return d3_selection_each(this, function(node, i, j) { callback.call(node, node.__data__, i, j); }); }; function d3_selection_each(groups, callback) { for (var j = 0, m = groups.length; j < m; j++) { for (var group = groups[j], i = 0, n = group.length, node; i < n; i++) { if (node = group[i]) callback(node, i, j); } } return groups; } d3_selectionPrototype.call = function(callback) { var args = d3_array(arguments); callback.apply(args[0] = this, args); return this; }; d3_selectionPrototype.empty = function() { return !this.node(); }; d3_selectionPrototype.node = function() { for (var j = 0, m = this.length; j < m; j++) { for (var group = this[j], i = 0, n = group.length; i < n; i++) { var node = group[i]; if (node) return node; } } return null; }; d3_selectionPrototype.size = function() { var n = 0; d3_selection_each(this, function() { ++n; }); return n; }; function d3_selection_enter(selection) { d3_subclass(selection, d3_selection_enterPrototype); return selection; } var d3_selection_enterPrototype = []; d3.selection.enter = d3_selection_enter; d3.selection.enter.prototype = d3_selection_enterPrototype; d3_selection_enterPrototype.append = d3_selectionPrototype.append; d3_selection_enterPrototype.empty = d3_selectionPrototype.empty; d3_selection_enterPrototype.node = d3_selectionPrototype.node; d3_selection_enterPrototype.call = d3_selectionPrototype.call; d3_selection_enterPrototype.size = d3_selectionPrototype.size; d3_selection_enterPrototype.select = function(selector) { var subgroups = [], subgroup, subnode, upgroup, group, node; for (var j = -1, m = this.length; ++j < m; ) { upgroup = (group = this[j]).update; subgroups.push(subgroup = []); subgroup.parentNode = group.parentNode; for (var i = -1, n = group.length; ++i < n; ) { if (node = group[i]) { subgroup.push(upgroup[i] = subnode = selector.call(group.parentNode, node.__data__, i, j)); subnode.__data__ = node.__data__; } else { subgroup.push(null); } } } return d3_selection(subgroups); }; d3_selection_enterPrototype.insert = function(name, before) { if (arguments.length < 2) before = d3_selection_enterInsertBefore(this); return d3_selectionPrototype.insert.call(this, name, before); }; function d3_selection_enterInsertBefore(enter) { var i0, j0; return function(d, i, j) { var group = enter[j].update, n = group.length, node; if (j != j0) j0 = j, i0 = 0; if (i >= i0) i0 = i + 1; while (!(node = group[i0]) && ++i0 < n) ; return node; }; } d3.select = function(node) { var group; if (typeof node === "string") { group = [ d3_select(node, d3_document) ]; group.parentNode = d3_document.documentElement; } else { group = [ node ]; group.parentNode = d3_documentElement(node); } return d3_selection([ group ]); }; d3.selectAll = function(nodes) { var group; if (typeof nodes === "string") { group = d3_array(d3_selectAll(nodes, d3_document)); group.parentNode = d3_document.documentElement; } else { group = d3_array(nodes); group.parentNode = null; } return d3_selection([ group ]); }; d3_selectionPrototype.on = function(type, listener, capture) { var n = arguments.length; if (n < 3) { if (typeof type !== "string") { if (n < 2) listener = false; for (capture in type) this.each(d3_selection_on(capture, type[capture], listener)); return this; } if (n < 2) return (n = this.node()["__on" + type]) && n._; capture = false; } return this.each(d3_selection_on(type, listener, capture)); }; function d3_selection_on(type, listener, capture) { var name = "__on" + type, i = type.indexOf("."), wrap = d3_selection_onListener; if (i > 0) type = type.slice(0, i); var filter = d3_selection_onFilters.get(type); if (filter) type = filter, wrap = d3_selection_onFilter; function onRemove() { var l = this[name]; if (l) { this.removeEventListener(type, l, l.$); delete this[name]; } } function onAdd() { var l = wrap(listener, d3_array(arguments)); onRemove.call(this); this.addEventListener(type, this[name] = l, l.$ = capture); l._ = listener; } function removeAll() { var re = new RegExp("^__on([^.]+)" + d3.requote(type) + "$"), match; for (var name in this) { if (match = name.match(re)) { var l = this[name]; this.removeEventListener(match[1], l, l.$); delete this[name]; } } } return i ? listener ? onAdd : onRemove : listener ? d3_noop : removeAll; } var d3_selection_onFilters = d3.map({ mouseenter: "mouseover", mouseleave: "mouseout" }); if (d3_document) { d3_selection_onFilters.forEach(function(k) { if ("on" + k in d3_document) d3_selection_onFilters.remove(k); }); } function d3_selection_onListener(listener, argumentz) { return function(e) { var o = d3.event; d3.event = e; argumentz[0] = this.__data__; try { listener.apply(this, argumentz); } finally { d3.event = o; } }; } function d3_selection_onFilter(listener, argumentz) { var l = d3_selection_onListener(listener, argumentz); return function(e) { var target = this, related = e.relatedTarget; if (!related || related !== target && !(related.compareDocumentPosition(target) & 8)) { l.call(target, e); } }; } var d3_event_dragSelect, d3_event_dragId = 0; function d3_event_dragSuppress(node) { var name = ".dragsuppress-" + ++d3_event_dragId, click = "click" + name, w = d3.select(d3_window(node)).on("touchmove" + name, d3_eventPreventDefault).on("dragstart" + name, d3_eventPreventDefault).on("selectstart" + name, d3_eventPreventDefault); if (d3_event_dragSelect == null) { d3_event_dragSelect = "onselectstart" in node ? false : d3_vendorSymbol(node.style, "userSelect"); } if (d3_event_dragSelect) { var style = d3_documentElement(node).style, select = style[d3_event_dragSelect]; style[d3_event_dragSelect] = "none"; } return function(suppressClick) { w.on(name, null); if (d3_event_dragSelect) style[d3_event_dragSelect] = select; if (suppressClick) { var off = function() { w.on(click, null); }; w.on(click, function() { d3_eventPreventDefault(); off(); }, true); setTimeout(off, 0); } }; } d3.mouse = function(container) { return d3_mousePoint(container, d3_eventSource()); }; var d3_mouse_bug44083 = this.navigator && /WebKit/.test(this.navigator.userAgent) ? -1 : 0; function d3_mousePoint(container, e) { if (e.changedTouches) e = e.changedTouches[0]; var svg = container.ownerSVGElement || container; if (svg.createSVGPoint) { var point = svg.createSVGPoint(); if (d3_mouse_bug44083 < 0) { var window = d3_window(container); if (window.scrollX || window.scrollY) { svg = d3.select("body").append("svg").style({ position: "absolute", top: 0, left: 0, margin: 0, padding: 0, border: "none" }, "important"); var ctm = svg[0][0].getScreenCTM(); d3_mouse_bug44083 = !(ctm.f || ctm.e); svg.remove(); } } if (d3_mouse_bug44083) point.x = e.pageX, point.y = e.pageY; else point.x = e.clientX, point.y = e.clientY; point = point.matrixTransform(container.getScreenCTM().inverse()); return [ point.x, point.y ]; } var rect = container.getBoundingClientRect(); return [ e.clientX - rect.left - container.clientLeft, e.clientY - rect.top - container.clientTop ]; } d3.touch = function(container, touches, identifier) { if (arguments.length < 3) identifier = touches, touches = d3_eventSource().changedTouches; if (touches) for (var i = 0, n = touches.length, touch; i < n; ++i) { if ((touch = touches[i]).identifier === identifier) { return d3_mousePoint(container, touch); } } }; d3.behavior.drag = function() { var event = d3_eventDispatch(drag, "drag", "dragstart", "dragend"), origin = null, mousedown = dragstart(d3_noop, d3.mouse, d3_window, "mousemove", "mouseup"), touchstart = dragstart(d3_behavior_dragTouchId, d3.touch, d3_identity, "touchmove", "touchend"); function drag() { this.on("mousedown.drag", mousedown).on("touchstart.drag", touchstart); } function dragstart(id, position, subject, move, end) { return function() { var that = this, target = d3.event.target.correspondingElement || d3.event.target, parent = that.parentNode, dispatch = event.of(that, arguments), dragged = 0, dragId = id(), dragName = ".drag" + (dragId == null ? "" : "-" + dragId), dragOffset, dragSubject = d3.select(subject(target)).on(move + dragName, moved).on(end + dragName, ended), dragRestore = d3_event_dragSuppress(target), position0 = position(parent, dragId); if (origin) { dragOffset = origin.apply(that, arguments); dragOffset = [ dragOffset.x - position0[0], dragOffset.y - position0[1] ]; } else { dragOffset = [ 0, 0 ]; } dispatch({ type: "dragstart" }); function moved() { var position1 = position(parent, dragId), dx, dy; if (!position1) return; dx = position1[0] - position0[0]; dy = position1[1] - position0[1]; dragged |= dx | dy; position0 = position1; dispatch({ type: "drag", x: position1[0] + dragOffset[0], y: position1[1] + dragOffset[1], dx: dx, dy: dy }); } function ended() { if (!position(parent, dragId)) return; dragSubject.on(move + dragName, null).on(end + dragName, null); dragRestore(dragged); dispatch({ type: "dragend" }); } }; } drag.origin = function(x) { if (!arguments.length) return origin; origin = x; return drag; }; return d3.rebind(drag, event, "on"); }; function d3_behavior_dragTouchId() { return d3.event.changedTouches[0].identifier; } d3.touches = function(container, touches) { if (arguments.length < 2) touches = d3_eventSource().touches; return touches ? d3_array(touches).map(function(touch) { var point = d3_mousePoint(container, touch); point.identifier = touch.identifier; return point; }) : []; }; var ε = 1e-6, ε2 = ε * ε, Ï€ = Math.PI, Ï„ = 2 * Ï€, τε = Ï„ - ε, halfÏ€ = Ï€ / 2, d3_radians = Ï€ / 180, d3_degrees = 180 / Ï€; function d3_sgn(x) { return x > 0 ? 1 : x < 0 ? -1 : 0; } function d3_cross2d(a, b, c) { return (b[0] - a[0]) * (c[1] - a[1]) - (b[1] - a[1]) * (c[0] - a[0]); } function d3_acos(x) { return x > 1 ? 0 : x < -1 ? Ï€ : Math.acos(x); } function d3_asin(x) { return x > 1 ? halfÏ€ : x < -1 ? -halfÏ€ : Math.asin(x); } function d3_sinh(x) { return ((x = Math.exp(x)) - 1 / x) / 2; } function d3_cosh(x) { return ((x = Math.exp(x)) + 1 / x) / 2; } function d3_tanh(x) { return ((x = Math.exp(2 * x)) - 1) / (x + 1); } function d3_haversin(x) { return (x = Math.sin(x / 2)) * x; } var Ï = Math.SQRT2, Ï2 = 2, Ï4 = 4; d3.interpolateZoom = function(p0, p1) { var ux0 = p0[0], uy0 = p0[1], w0 = p0[2], ux1 = p1[0], uy1 = p1[1], w1 = p1[2], dx = ux1 - ux0, dy = uy1 - uy0, d2 = dx * dx + dy * dy, i, S; if (d2 < ε2) { S = Math.log(w1 / w0) / Ï; i = function(t) { return [ ux0 + t * dx, uy0 + t * dy, w0 * Math.exp(Ï * t * S) ]; }; } else { var d1 = Math.sqrt(d2), b0 = (w1 * w1 - w0 * w0 + Ï4 * d2) / (2 * w0 * Ï2 * d1), b1 = (w1 * w1 - w0 * w0 - Ï4 * d2) / (2 * w1 * Ï2 * d1), r0 = Math.log(Math.sqrt(b0 * b0 + 1) - b0), r1 = Math.log(Math.sqrt(b1 * b1 + 1) - b1); S = (r1 - r0) / Ï; i = function(t) { var s = t * S, coshr0 = d3_cosh(r0), u = w0 / (Ï2 * d1) * (coshr0 * d3_tanh(Ï * s + r0) - d3_sinh(r0)); return [ ux0 + u * dx, uy0 + u * dy, w0 * coshr0 / d3_cosh(Ï * s + r0) ]; }; } i.duration = S * 1e3; return i; }; d3.behavior.zoom = function() { var view = { x: 0, y: 0, k: 1 }, translate0, center0, center, size = [ 960, 500 ], scaleExtent = d3_behavior_zoomInfinity, duration = 250, zooming = 0, mousedown = "mousedown.zoom", mousemove = "mousemove.zoom", mouseup = "mouseup.zoom", mousewheelTimer, touchstart = "touchstart.zoom", touchtime, event = d3_eventDispatch(zoom, "zoomstart", "zoom", "zoomend"), x0, x1, y0, y1; if (!d3_behavior_zoomWheel) { d3_behavior_zoomWheel = "onwheel" in d3_document ? (d3_behavior_zoomDelta = function() { return -d3.event.deltaY * (d3.event.deltaMode ? 120 : 1); }, "wheel") : "onmousewheel" in d3_document ? (d3_behavior_zoomDelta = function() { return d3.event.wheelDelta; }, "mousewheel") : (d3_behavior_zoomDelta = function() { return -d3.event.detail; }, "MozMousePixelScroll"); } function zoom(g) { g.on(mousedown, mousedowned).on(d3_behavior_zoomWheel + ".zoom", mousewheeled).on("dblclick.zoom", dblclicked).on(touchstart, touchstarted); } zoom.event = function(g) { g.each(function() { var dispatch = event.of(this, arguments), view1 = view; if (d3_transitionInheritId) { d3.select(this).transition().each("start.zoom", function() { view = this.__chart__ || { x: 0, y: 0, k: 1 }; zoomstarted(dispatch); }).tween("zoom:zoom", function() { var dx = size[0], dy = size[1], cx = center0 ? center0[0] : dx / 2, cy = center0 ? center0[1] : dy / 2, i = d3.interpolateZoom([ (cx - view.x) / view.k, (cy - view.y) / view.k, dx / view.k ], [ (cx - view1.x) / view1.k, (cy - view1.y) / view1.k, dx / view1.k ]); return function(t) { var l = i(t), k = dx / l[2]; this.__chart__ = view = { x: cx - l[0] * k, y: cy - l[1] * k, k: k }; zoomed(dispatch); }; }).each("interrupt.zoom", function() { zoomended(dispatch); }).each("end.zoom", function() { zoomended(dispatch); }); } else { this.__chart__ = view; zoomstarted(dispatch); zoomed(dispatch); zoomended(dispatch); } }); }; zoom.translate = function(_) { if (!arguments.length) return [ view.x, view.y ]; view = { x: +_[0], y: +_[1], k: view.k }; rescale(); return zoom; }; zoom.scale = function(_) { if (!arguments.length) return view.k; view = { x: view.x, y: view.y, k: null }; scaleTo(+_); rescale(); return zoom; }; zoom.scaleExtent = function(_) { if (!arguments.length) return scaleExtent; scaleExtent = _ == null ? d3_behavior_zoomInfinity : [ +_[0], +_[1] ]; return zoom; }; zoom.center = function(_) { if (!arguments.length) return center; center = _ && [ +_[0], +_[1] ]; return zoom; }; zoom.size = function(_) { if (!arguments.length) return size; size = _ && [ +_[0], +_[1] ]; return zoom; }; zoom.duration = function(_) { if (!arguments.length) return duration; duration = +_; return zoom; }; zoom.x = function(z) { if (!arguments.length) return x1; x1 = z; x0 = z.copy(); view = { x: 0, y: 0, k: 1 }; return zoom; }; zoom.y = function(z) { if (!arguments.length) return y1; y1 = z; y0 = z.copy(); view = { x: 0, y: 0, k: 1 }; return zoom; }; function location(p) { return [ (p[0] - view.x) / view.k, (p[1] - view.y) / view.k ]; } function point(l) { return [ l[0] * view.k + view.x, l[1] * view.k + view.y ]; } function scaleTo(s) { view.k = Math.max(scaleExtent[0], Math.min(scaleExtent[1], s)); } function translateTo(p, l) { l = point(l); view.x += p[0] - l[0]; view.y += p[1] - l[1]; } function zoomTo(that, p, l, k) { that.__chart__ = { x: view.x, y: view.y, k: view.k }; scaleTo(Math.pow(2, k)); translateTo(center0 = p, l); that = d3.select(that); if (duration > 0) that = that.transition().duration(duration); that.call(zoom.event); } function rescale() { if (x1) x1.domain(x0.range().map(function(x) { return (x - view.x) / view.k; }).map(x0.invert)); if (y1) y1.domain(y0.range().map(function(y) { return (y - view.y) / view.k; }).map(y0.invert)); } function zoomstarted(dispatch) { if (!zooming++) dispatch({ type: "zoomstart" }); } function zoomed(dispatch) { rescale(); dispatch({ type: "zoom", scale: view.k, translate: [ view.x, view.y ] }); } function zoomended(dispatch) { if (!--zooming) dispatch({ type: "zoomend" }), center0 = null; } function mousedowned() { var that = this, dispatch = event.of(that, arguments), dragged = 0, subject = d3.select(d3_window(that)).on(mousemove, moved).on(mouseup, ended), location0 = location(d3.mouse(that)), dragRestore = d3_event_dragSuppress(that); d3_selection_interrupt.call(that); zoomstarted(dispatch); function moved() { dragged = 1; translateTo(d3.mouse(that), location0); zoomed(dispatch); } function ended() { subject.on(mousemove, null).on(mouseup, null); dragRestore(dragged); zoomended(dispatch); } } function touchstarted() { var that = this, dispatch = event.of(that, arguments), locations0 = {}, distance0 = 0, scale0, zoomName = ".zoom-" + d3.event.changedTouches[0].identifier, touchmove = "touchmove" + zoomName, touchend = "touchend" + zoomName, targets = [], subject = d3.select(that), dragRestore = d3_event_dragSuppress(that); started(); zoomstarted(dispatch); subject.on(mousedown, null).on(touchstart, started); function relocate() { var touches = d3.touches(that); scale0 = view.k; touches.forEach(function(t) { if (t.identifier in locations0) locations0[t.identifier] = location(t); }); return touches; } function started() { var target = d3.event.target; d3.select(target).on(touchmove, moved).on(touchend, ended); targets.push(target); var changed = d3.event.changedTouches; for (var i = 0, n = changed.length; i < n; ++i) { locations0[changed[i].identifier] = null; } var touches = relocate(), now = Date.now(); if (touches.length === 1) { if (now - touchtime < 500) { var p = touches[0]; zoomTo(that, p, locations0[p.identifier], Math.floor(Math.log(view.k) / Math.LN2) + 1); d3_eventPreventDefault(); } touchtime = now; } else if (touches.length > 1) { var p = touches[0], q = touches[1], dx = p[0] - q[0], dy = p[1] - q[1]; distance0 = dx * dx + dy * dy; } } function moved() { var touches = d3.touches(that), p0, l0, p1, l1; d3_selection_interrupt.call(that); for (var i = 0, n = touches.length; i < n; ++i, l1 = null) { p1 = touches[i]; if (l1 = locations0[p1.identifier]) { if (l0) break; p0 = p1, l0 = l1; } } if (l1) { var distance1 = (distance1 = p1[0] - p0[0]) * distance1 + (distance1 = p1[1] - p0[1]) * distance1, scale1 = distance0 && Math.sqrt(distance1 / distance0); p0 = [ (p0[0] + p1[0]) / 2, (p0[1] + p1[1]) / 2 ]; l0 = [ (l0[0] + l1[0]) / 2, (l0[1] + l1[1]) / 2 ]; scaleTo(scale1 * scale0); } touchtime = null; translateTo(p0, l0); zoomed(dispatch); } function ended() { if (d3.event.touches.length) { var changed = d3.event.changedTouches; for (var i = 0, n = changed.length; i < n; ++i) { delete locations0[changed[i].identifier]; } for (var identifier in locations0) { return void relocate(); } } d3.selectAll(targets).on(zoomName, null); subject.on(mousedown, mousedowned).on(touchstart, touchstarted); dragRestore(); zoomended(dispatch); } } function mousewheeled() { var dispatch = event.of(this, arguments); if (mousewheelTimer) clearTimeout(mousewheelTimer); else d3_selection_interrupt.call(this), translate0 = location(center0 = center || d3.mouse(this)), zoomstarted(dispatch); mousewheelTimer = setTimeout(function() { mousewheelTimer = null; zoomended(dispatch); }, 50); d3_eventPreventDefault(); scaleTo(Math.pow(2, d3_behavior_zoomDelta() * .002) * view.k); translateTo(center0, translate0); zoomed(dispatch); } function dblclicked() { var p = d3.mouse(this), k = Math.log(view.k) / Math.LN2; zoomTo(this, p, location(p), d3.event.shiftKey ? Math.ceil(k) - 1 : Math.floor(k) + 1); } return d3.rebind(zoom, event, "on"); }; var d3_behavior_zoomInfinity = [ 0, Infinity ], d3_behavior_zoomDelta, d3_behavior_zoomWheel; d3.color = d3_color; function d3_color() {} d3_color.prototype.toString = function() { return this.rgb() + ""; }; d3.hsl = d3_hsl; function d3_hsl(h, s, l) { return this instanceof d3_hsl ? void (this.h = +h, this.s = +s, this.l = +l) : arguments.length < 2 ? h instanceof d3_hsl ? new d3_hsl(h.h, h.s, h.l) : d3_rgb_parse("" + h, d3_rgb_hsl, d3_hsl) : new d3_hsl(h, s, l); } var d3_hslPrototype = d3_hsl.prototype = new d3_color(); d3_hslPrototype.brighter = function(k) { k = Math.pow(.7, arguments.length ? k : 1); return new d3_hsl(this.h, this.s, this.l / k); }; d3_hslPrototype.darker = function(k) { k = Math.pow(.7, arguments.length ? k : 1); return new d3_hsl(this.h, this.s, k * this.l); }; d3_hslPrototype.rgb = function() { return d3_hsl_rgb(this.h, this.s, this.l); }; function d3_hsl_rgb(h, s, l) { var m1, m2; h = isNaN(h) ? 0 : (h %= 360) < 0 ? h + 360 : h; s = isNaN(s) ? 0 : s < 0 ? 0 : s > 1 ? 1 : s; l = l < 0 ? 0 : l > 1 ? 1 : l; m2 = l <= .5 ? l * (1 + s) : l + s - l * s; m1 = 2 * l - m2; function v(h) { if (h > 360) h -= 360; else if (h < 0) h += 360; if (h < 60) return m1 + (m2 - m1) * h / 60; if (h < 180) return m2; if (h < 240) return m1 + (m2 - m1) * (240 - h) / 60; return m1; } function vv(h) { return Math.round(v(h) * 255); } return new d3_rgb(vv(h + 120), vv(h), vv(h - 120)); } d3.hcl = d3_hcl; function d3_hcl(h, c, l) { return this instanceof d3_hcl ? void (this.h = +h, this.c = +c, this.l = +l) : arguments.length < 2 ? h instanceof d3_hcl ? new d3_hcl(h.h, h.c, h.l) : h instanceof d3_lab ? d3_lab_hcl(h.l, h.a, h.b) : d3_lab_hcl((h = d3_rgb_lab((h = d3.rgb(h)).r, h.g, h.b)).l, h.a, h.b) : new d3_hcl(h, c, l); } var d3_hclPrototype = d3_hcl.prototype = new d3_color(); d3_hclPrototype.brighter = function(k) { return new d3_hcl(this.h, this.c, Math.min(100, this.l + d3_lab_K * (arguments.length ? k : 1))); }; d3_hclPrototype.darker = function(k) { return new d3_hcl(this.h, this.c, Math.max(0, this.l - d3_lab_K * (arguments.length ? k : 1))); }; d3_hclPrototype.rgb = function() { return d3_hcl_lab(this.h, this.c, this.l).rgb(); }; function d3_hcl_lab(h, c, l) { if (isNaN(h)) h = 0; if (isNaN(c)) c = 0; return new d3_lab(l, Math.cos(h *= d3_radians) * c, Math.sin(h) * c); } d3.lab = d3_lab; function d3_lab(l, a, b) { return this instanceof d3_lab ? void (this.l = +l, this.a = +a, this.b = +b) : arguments.length < 2 ? l instanceof d3_lab ? new d3_lab(l.l, l.a, l.b) : l instanceof d3_hcl ? d3_hcl_lab(l.h, l.c, l.l) : d3_rgb_lab((l = d3_rgb(l)).r, l.g, l.b) : new d3_lab(l, a, b); } var d3_lab_K = 18; var d3_lab_X = .95047, d3_lab_Y = 1, d3_lab_Z = 1.08883; var d3_labPrototype = d3_lab.prototype = new d3_color(); d3_labPrototype.brighter = function(k) { return new d3_lab(Math.min(100, this.l + d3_lab_K * (arguments.length ? k : 1)), this.a, this.b); }; d3_labPrototype.darker = function(k) { return new d3_lab(Math.max(0, this.l - d3_lab_K * (arguments.length ? k : 1)), this.a, this.b); }; d3_labPrototype.rgb = function() { return d3_lab_rgb(this.l, this.a, this.b); }; function d3_lab_rgb(l, a, b) { var y = (l + 16) / 116, x = y + a / 500, z = y - b / 200; x = d3_lab_xyz(x) * d3_lab_X; y = d3_lab_xyz(y) * d3_lab_Y; z = d3_lab_xyz(z) * d3_lab_Z; return new d3_rgb(d3_xyz_rgb(3.2404542 * x - 1.5371385 * y - .4985314 * z), d3_xyz_rgb(-.969266 * x + 1.8760108 * y + .041556 * z), d3_xyz_rgb(.0556434 * x - .2040259 * y + 1.0572252 * z)); } function d3_lab_hcl(l, a, b) { return l > 0 ? new d3_hcl(Math.atan2(b, a) * d3_degrees, Math.sqrt(a * a + b * b), l) : new d3_hcl(NaN, NaN, l); } function d3_lab_xyz(x) { return x > .206893034 ? x * x * x : (x - 4 / 29) / 7.787037; } function d3_xyz_lab(x) { return x > .008856 ? Math.pow(x, 1 / 3) : 7.787037 * x + 4 / 29; } function d3_xyz_rgb(r) { return Math.round(255 * (r <= .00304 ? 12.92 * r : 1.055 * Math.pow(r, 1 / 2.4) - .055)); } d3.rgb = d3_rgb; function d3_rgb(r, g, b) { return this instanceof d3_rgb ? void (this.r = ~~r, this.g = ~~g, this.b = ~~b) : arguments.length < 2 ? r instanceof d3_rgb ? new d3_rgb(r.r, r.g, r.b) : d3_rgb_parse("" + r, d3_rgb, d3_hsl_rgb) : new d3_rgb(r, g, b); } function d3_rgbNumber(value) { return new d3_rgb(value >> 16, value >> 8 & 255, value & 255); } function d3_rgbString(value) { return d3_rgbNumber(value) + ""; } var d3_rgbPrototype = d3_rgb.prototype = new d3_color(); d3_rgbPrototype.brighter = function(k) { k = Math.pow(.7, arguments.length ? k : 1); var r = this.r, g = this.g, b = this.b, i = 30; if (!r && !g && !b) return new d3_rgb(i, i, i); if (r && r < i) r = i; if (g && g < i) g = i; if (b && b < i) b = i; return new d3_rgb(Math.min(255, r / k), Math.min(255, g / k), Math.min(255, b / k)); }; d3_rgbPrototype.darker = function(k) { k = Math.pow(.7, arguments.length ? k : 1); return new d3_rgb(k * this.r, k * this.g, k * this.b); }; d3_rgbPrototype.hsl = function() { return d3_rgb_hsl(this.r, this.g, this.b); }; d3_rgbPrototype.toString = function() { return "#" + d3_rgb_hex(this.r) + d3_rgb_hex(this.g) + d3_rgb_hex(this.b); }; function d3_rgb_hex(v) { return v < 16 ? "0" + Math.max(0, v).toString(16) : Math.min(255, v).toString(16); } function d3_rgb_parse(format, rgb, hsl) { var r = 0, g = 0, b = 0, m1, m2, color; m1 = /([a-z]+)\((.*)\)/.exec(format = format.toLowerCase()); if (m1) { m2 = m1[2].split(","); switch (m1[1]) { case "hsl": { return hsl(parseFloat(m2[0]), parseFloat(m2[1]) / 100, parseFloat(m2[2]) / 100); } case "rgb": { return rgb(d3_rgb_parseNumber(m2[0]), d3_rgb_parseNumber(m2[1]), d3_rgb_parseNumber(m2[2])); } } } if (color = d3_rgb_names.get(format)) { return rgb(color.r, color.g, color.b); } if (format != null && format.charAt(0) === "#" && !isNaN(color = parseInt(format.slice(1), 16))) { if (format.length === 4) { r = (color & 3840) >> 4; r = r >> 4 | r; g = color & 240; g = g >> 4 | g; b = color & 15; b = b << 4 | b; } else if (format.length === 7) { r = (color & 16711680) >> 16; g = (color & 65280) >> 8; b = color & 255; } } return rgb(r, g, b); } function d3_rgb_hsl(r, g, b) { var min = Math.min(r /= 255, g /= 255, b /= 255), max = Math.max(r, g, b), d = max - min, h, s, l = (max + min) / 2; if (d) { s = l < .5 ? d / (max + min) : d / (2 - max - min); if (r == max) h = (g - b) / d + (g < b ? 6 : 0); else if (g == max) h = (b - r) / d + 2; else h = (r - g) / d + 4; h *= 60; } else { h = NaN; s = l > 0 && l < 1 ? 0 : h; } return new d3_hsl(h, s, l); } function d3_rgb_lab(r, g, b) { r = d3_rgb_xyz(r); g = d3_rgb_xyz(g); b = d3_rgb_xyz(b); var x = d3_xyz_lab((.4124564 * r + .3575761 * g + .1804375 * b) / d3_lab_X), y = d3_xyz_lab((.2126729 * r + .7151522 * g + .072175 * b) / d3_lab_Y), z = d3_xyz_lab((.0193339 * r + .119192 * g + .9503041 * b) / d3_lab_Z); return d3_lab(116 * y - 16, 500 * (x - y), 200 * (y - z)); } function d3_rgb_xyz(r) { return (r /= 255) <= .04045 ? r / 12.92 : Math.pow((r + .055) / 1.055, 2.4); } function d3_rgb_parseNumber(c) { var f = parseFloat(c); return c.charAt(c.length - 1) === "%" ? Math.round(f * 2.55) : f; } var d3_rgb_names = d3.map({ aliceblue: 15792383, antiquewhite: 16444375, aqua: 65535, aquamarine: 8388564, azure: 15794175, beige: 16119260, bisque: 16770244, black: 0, blanchedalmond: 16772045, blue: 255, blueviolet: 9055202, brown: 10824234, burlywood: 14596231, cadetblue: 6266528, chartreuse: 8388352, chocolate: 13789470, coral: 16744272, cornflowerblue: 6591981, cornsilk: 16775388, crimson: 14423100, cyan: 65535, darkblue: 139, darkcyan: 35723, darkgoldenrod: 12092939, darkgray: 11119017, darkgreen: 25600, darkgrey: 11119017, darkkhaki: 12433259, darkmagenta: 9109643, darkolivegreen: 5597999, darkorange: 16747520, darkorchid: 10040012, darkred: 9109504, darksalmon: 15308410, darkseagreen: 9419919, darkslateblue: 4734347, darkslategray: 3100495, darkslategrey: 3100495, darkturquoise: 52945, darkviolet: 9699539, deeppink: 16716947, deepskyblue: 49151, dimgray: 6908265, dimgrey: 6908265, dodgerblue: 2003199, firebrick: 11674146, floralwhite: 16775920, forestgreen: 2263842, fuchsia: 16711935, gainsboro: 14474460, ghostwhite: 16316671, gold: 16766720, goldenrod: 14329120, gray: 8421504, green: 32768, greenyellow: 11403055, grey: 8421504, honeydew: 15794160, hotpink: 16738740, indianred: 13458524, indigo: 4915330, ivory: 16777200, khaki: 15787660, lavender: 15132410, lavenderblush: 16773365, lawngreen: 8190976, lemonchiffon: 16775885, lightblue: 11393254, lightcoral: 15761536, lightcyan: 14745599, lightgoldenrodyellow: 16448210, lightgray: 13882323, lightgreen: 9498256, lightgrey: 13882323, lightpink: 16758465, lightsalmon: 16752762, lightseagreen: 2142890, lightskyblue: 8900346, lightslategray: 7833753, lightslategrey: 7833753, lightsteelblue: 11584734, lightyellow: 16777184, lime: 65280, limegreen: 3329330, linen: 16445670, magenta: 16711935, maroon: 8388608, mediumaquamarine: 6737322, mediumblue: 205, mediumorchid: 12211667, mediumpurple: 9662683, mediumseagreen: 3978097, mediumslateblue: 8087790, mediumspringgreen: 64154, mediumturquoise: 4772300, mediumvioletred: 13047173, midnightblue: 1644912, mintcream: 16121850, mistyrose: 16770273, moccasin: 16770229, navajowhite: 16768685, navy: 128, oldlace: 16643558, olive: 8421376, olivedrab: 7048739, orange: 16753920, orangered: 16729344, orchid: 14315734, palegoldenrod: 15657130, palegreen: 10025880, paleturquoise: 11529966, palevioletred: 14381203, papayawhip: 16773077, peachpuff: 16767673, peru: 13468991, pink: 16761035, plum: 14524637, powderblue: 11591910, purple: 8388736, rebeccapurple: 6697881, red: 16711680, rosybrown: 12357519, royalblue: 4286945, saddlebrown: 9127187, salmon: 16416882, sandybrown: 16032864, seagreen: 3050327, seashell: 16774638, sienna: 10506797, silver: 12632256, skyblue: 8900331, slateblue: 6970061, slategray: 7372944, slategrey: 7372944, snow: 16775930, springgreen: 65407, steelblue: 4620980, tan: 13808780, teal: 32896, thistle: 14204888, tomato: 16737095, turquoise: 4251856, violet: 15631086, wheat: 16113331, white: 16777215, whitesmoke: 16119285, yellow: 16776960, yellowgreen: 10145074 }); d3_rgb_names.forEach(function(key, value) { d3_rgb_names.set(key, d3_rgbNumber(value)); }); function d3_functor(v) { return typeof v === "function" ? v : function() { return v; }; } d3.functor = d3_functor; d3.xhr = d3_xhrType(d3_identity); function d3_xhrType(response) { return function(url, mimeType, callback) { if (arguments.length === 2 && typeof mimeType === "function") callback = mimeType, mimeType = null; return d3_xhr(url, mimeType, response, callback); }; } function d3_xhr(url, mimeType, response, callback) { var xhr = {}, dispatch = d3.dispatch("beforesend", "progress", "load", "error"), headers = {}, request = new XMLHttpRequest(), responseType = null; if (this.XDomainRequest && !("withCredentials" in request) && /^(http(s)?:)?\/\//.test(url)) request = new XDomainRequest(); "onload" in request ? request.onload = request.onerror = respond : request.onreadystatechange = function() { request.readyState > 3 && respond(); }; function respond() { var status = request.status, result; if (!status && d3_xhrHasResponse(request) || status >= 200 && status < 300 || status === 304) { try { result = response.call(xhr, request); } catch (e) { dispatch.error.call(xhr, e); return; } dispatch.load.call(xhr, result); } else { dispatch.error.call(xhr, request); } } request.onprogress = function(event) { var o = d3.event; d3.event = event; try { dispatch.progress.call(xhr, request); } finally { d3.event = o; } }; xhr.header = function(name, value) { name = (name + "").toLowerCase(); if (arguments.length < 2) return headers[name]; if (value == null) delete headers[name]; else headers[name] = value + ""; return xhr; }; xhr.mimeType = function(value) { if (!arguments.length) return mimeType; mimeType = value == null ? null : value + ""; return xhr; }; xhr.responseType = function(value) { if (!arguments.length) return responseType; responseType = value; return xhr; }; xhr.response = function(value) { response = value; return xhr; }; [ "get", "post" ].forEach(function(method) { xhr[method] = function() { return xhr.send.apply(xhr, [ method ].concat(d3_array(arguments))); }; }); xhr.send = function(method, data, callback) { if (arguments.length === 2 && typeof data === "function") callback = data, data = null; request.open(method, url, true); if (mimeType != null && !("accept" in headers)) headers["accept"] = mimeType + ",*/*"; if (request.setRequestHeader) for (var name in headers) request.setRequestHeader(name, headers[name]); if (mimeType != null && request.overrideMimeType) request.overrideMimeType(mimeType); if (responseType != null) request.responseType = responseType; if (callback != null) xhr.on("error", callback).on("load", function(request) { callback(null, request); }); dispatch.beforesend.call(xhr, request); request.send(data == null ? null : data); return xhr; }; xhr.abort = function() { request.abort(); return xhr; }; d3.rebind(xhr, dispatch, "on"); return callback == null ? xhr : xhr.get(d3_xhr_fixCallback(callback)); } function d3_xhr_fixCallback(callback) { return callback.length === 1 ? function(error, request) { callback(error == null ? request : null); } : callback; } function d3_xhrHasResponse(request) { var type = request.responseType; return type && type !== "text" ? request.response : request.responseText; } d3.dsv = function(delimiter, mimeType) { var reFormat = new RegExp('["' + delimiter + "\n]"), delimiterCode = delimiter.charCodeAt(0); function dsv(url, row, callback) { if (arguments.length < 3) callback = row, row = null; var xhr = d3_xhr(url, mimeType, row == null ? response : typedResponse(row), callback); xhr.row = function(_) { return arguments.length ? xhr.response((row = _) == null ? response : typedResponse(_)) : row; }; return xhr; } function response(request) { return dsv.parse(request.responseText); } function typedResponse(f) { return function(request) { return dsv.parse(request.responseText, f); }; } dsv.parse = function(text, f) { var o; return dsv.parseRows(text, function(row, i) { if (o) return o(row, i - 1); var a = new Function("d", "return {" + row.map(function(name, i) { return JSON.stringify(name) + ": d[" + i + "]"; }).join(",") + "}"); o = f ? function(row, i) { return f(a(row), i); } : a; }); }; dsv.parseRows = function(text, f) { var EOL = {}, EOF = {}, rows = [], N = text.length, I = 0, n = 0, t, eol; function token() { if (I >= N) return EOF; if (eol) return eol = false, EOL; var j = I; if (text.charCodeAt(j) === 34) { var i = j; while (i++ < N) { if (text.charCodeAt(i) === 34) { if (text.charCodeAt(i + 1) !== 34) break; ++i; } } I = i + 2; var c = text.charCodeAt(i + 1); if (c === 13) { eol = true; if (text.charCodeAt(i + 2) === 10) ++I; } else if (c === 10) { eol = true; } return text.slice(j + 1, i).replace(/""/g, '"'); } while (I < N) { var c = text.charCodeAt(I++), k = 1; if (c === 10) eol = true; else if (c === 13) { eol = true; if (text.charCodeAt(I) === 10) ++I, ++k; } else if (c !== delimiterCode) continue; return text.slice(j, I - k); } return text.slice(j); } while ((t = token()) !== EOF) { var a = []; while (t !== EOL && t !== EOF) { a.push(t); t = token(); } if (f && (a = f(a, n++)) == null) continue; rows.push(a); } return rows; }; dsv.format = function(rows) { if (Array.isArray(rows[0])) return dsv.formatRows(rows); var fieldSet = new d3_Set(), fields = []; rows.forEach(function(row) { for (var field in row) { if (!fieldSet.has(field)) { fields.push(fieldSet.add(field)); } } }); return [ fields.map(formatValue).join(delimiter) ].concat(rows.map(function(row) { return fields.map(function(field) { return formatValue(row[field]); }).join(delimiter); })).join("\n"); }; dsv.formatRows = function(rows) { return rows.map(formatRow).join("\n"); }; function formatRow(row) { return row.map(formatValue).join(delimiter); } function formatValue(text) { return reFormat.test(text) ? '"' + text.replace(/\"/g, '""') + '"' : text; } return dsv; }; d3.csv = d3.dsv(",", "text/csv"); d3.tsv = d3.dsv(" ", "text/tab-separated-values"); var d3_timer_queueHead, d3_timer_queueTail, d3_timer_interval, d3_timer_timeout, d3_timer_frame = this[d3_vendorSymbol(this, "requestAnimationFrame")] || function(callback) { setTimeout(callback, 17); }; d3.timer = function() { d3_timer.apply(this, arguments); }; function d3_timer(callback, delay, then) { var n = arguments.length; if (n < 2) delay = 0; if (n < 3) then = Date.now(); var time = then + delay, timer = { c: callback, t: time, n: null }; if (d3_timer_queueTail) d3_timer_queueTail.n = timer; else d3_timer_queueHead = timer; d3_timer_queueTail = timer; if (!d3_timer_interval) { d3_timer_timeout = clearTimeout(d3_timer_timeout); d3_timer_interval = 1; d3_timer_frame(d3_timer_step); } return timer; } function d3_timer_step() { var now = d3_timer_mark(), delay = d3_timer_sweep() - now; if (delay > 24) { if (isFinite(delay)) { clearTimeout(d3_timer_timeout); d3_timer_timeout = setTimeout(d3_timer_step, delay); } d3_timer_interval = 0; } else { d3_timer_interval = 1; d3_timer_frame(d3_timer_step); } } d3.timer.flush = function() { d3_timer_mark(); d3_timer_sweep(); }; function d3_timer_mark() { var now = Date.now(), timer = d3_timer_queueHead; while (timer) { if (now >= timer.t && timer.c(now - timer.t)) timer.c = null; timer = timer.n; } return now; } function d3_timer_sweep() { var t0, t1 = d3_timer_queueHead, time = Infinity; while (t1) { if (t1.c) { if (t1.t < time) time = t1.t; t1 = (t0 = t1).n; } else { t1 = t0 ? t0.n = t1.n : d3_timer_queueHead = t1.n; } } d3_timer_queueTail = t0; return time; } function d3_format_precision(x, p) { return p - (x ? Math.ceil(Math.log(x) / Math.LN10) : 1); } d3.round = function(x, n) { return n ? Math.round(x * (n = Math.pow(10, n))) / n : Math.round(x); }; var d3_formatPrefixes = [ "y", "z", "a", "f", "p", "n", "µ", "m", "", "k", "M", "G", "T", "P", "E", "Z", "Y" ].map(d3_formatPrefix); d3.formatPrefix = function(value, precision) { var i = 0; if (value = +value) { if (value < 0) value *= -1; if (precision) value = d3.round(value, d3_format_precision(value, precision)); i = 1 + Math.floor(1e-12 + Math.log(value) / Math.LN10); i = Math.max(-24, Math.min(24, Math.floor((i - 1) / 3) * 3)); } return d3_formatPrefixes[8 + i / 3]; }; function d3_formatPrefix(d, i) { var k = Math.pow(10, abs(8 - i) * 3); return { scale: i > 8 ? function(d) { return d / k; } : function(d) { return d * k; }, symbol: d }; } function d3_locale_numberFormat(locale) { var locale_decimal = locale.decimal, locale_thousands = locale.thousands, locale_grouping = locale.grouping, locale_currency = locale.currency, formatGroup = locale_grouping && locale_thousands ? function(value, width) { var i = value.length, t = [], j = 0, g = locale_grouping[0], length = 0; while (i > 0 && g > 0) { if (length + g + 1 > width) g = Math.max(1, width - length); t.push(value.substring(i -= g, i + g)); if ((length += g + 1) > width) break; g = locale_grouping[j = (j + 1) % locale_grouping.length]; } return t.reverse().join(locale_thousands); } : d3_identity; return function(specifier) { var match = d3_format_re.exec(specifier), fill = match[1] || " ", align = match[2] || ">", sign = match[3] || "-", symbol = match[4] || "", zfill = match[5], width = +match[6], comma = match[7], precision = match[8], type = match[9], scale = 1, prefix = "", suffix = "", integer = false, exponent = true; if (precision) precision = +precision.substring(1); if (zfill || fill === "0" && align === "=") { zfill = fill = "0"; align = "="; } switch (type) { case "n": comma = true; type = "g"; break; case "%": scale = 100; suffix = "%"; type = "f"; break; case "p": scale = 100; suffix = "%"; type = "r"; break; case "b": case "o": case "x": case "X": if (symbol === "#") prefix = "0" + type.toLowerCase(); case "c": exponent = false; case "d": integer = true; precision = 0; break; case "s": scale = -1; type = "r"; break; } if (symbol === "$") prefix = locale_currency[0], suffix = locale_currency[1]; if (type == "r" && !precision) type = "g"; if (precision != null) { if (type == "g") precision = Math.max(1, Math.min(21, precision)); else if (type == "e" || type == "f") precision = Math.max(0, Math.min(20, precision)); } type = d3_format_types.get(type) || d3_format_typeDefault; var zcomma = zfill && comma; return function(value) { var fullSuffix = suffix; if (integer && value % 1) return ""; var negative = value < 0 || value === 0 && 1 / value < 0 ? (value = -value, "-") : sign === "-" ? "" : sign; if (scale < 0) { var unit = d3.formatPrefix(value, precision); value = unit.scale(value); fullSuffix = unit.symbol + suffix; } else { value *= scale; } value = type(value, precision); var i = value.lastIndexOf("."), before, after; if (i < 0) { var j = exponent ? value.lastIndexOf("e") : -1; if (j < 0) before = value, after = ""; else before = value.substring(0, j), after = value.substring(j); } else { before = value.substring(0, i); after = locale_decimal + value.substring(i + 1); } if (!zfill && comma) before = formatGroup(before, Infinity); var length = prefix.length + before.length + after.length + (zcomma ? 0 : negative.length), padding = length < width ? new Array(length = width - length + 1).join(fill) : ""; if (zcomma) before = formatGroup(padding + before, padding.length ? width - after.length : Infinity); negative += prefix; value = before + after; return (align === "<" ? negative + value + padding : align === ">" ? padding + negative + value : align === "^" ? padding.substring(0, length >>= 1) + negative + value + padding.substring(length) : negative + (zcomma ? value : padding + value)) + fullSuffix; }; }; } var d3_format_re = /(?:([^{])?([<>=^]))?([+\- ])?([$#])?(0)?(\d+)?(,)?(\.-?\d+)?([a-z%])?/i; var d3_format_types = d3.map({ b: function(x) { return x.toString(2); }, c: function(x) { return String.fromCharCode(x); }, o: function(x) { return x.toString(8); }, x: function(x) { return x.toString(16); }, X: function(x) { return x.toString(16).toUpperCase(); }, g: function(x, p) { return x.toPrecision(p); }, e: function(x, p) { return x.toExponential(p); }, f: function(x, p) { return x.toFixed(p); }, r: function(x, p) { return (x = d3.round(x, d3_format_precision(x, p))).toFixed(Math.max(0, Math.min(20, d3_format_precision(x * (1 + 1e-15), p)))); } }); function d3_format_typeDefault(x) { return x + ""; } var d3_time = d3.time = {}, d3_date = Date; function d3_date_utc() { this._ = new Date(arguments.length > 1 ? Date.UTC.apply(this, arguments) : arguments[0]); } d3_date_utc.prototype = { getDate: function() { return this._.getUTCDate(); }, getDay: function() { return this._.getUTCDay(); }, getFullYear: function() { return this._.getUTCFullYear(); }, getHours: function() { return this._.getUTCHours(); }, getMilliseconds: function() { return this._.getUTCMilliseconds(); }, getMinutes: function() { return this._.getUTCMinutes(); }, getMonth: function() { return this._.getUTCMonth(); }, getSeconds: function() { return this._.getUTCSeconds(); }, getTime: function() { return this._.getTime(); }, getTimezoneOffset: function() { return 0; }, valueOf: function() { return this._.valueOf(); }, setDate: function() { d3_time_prototype.setUTCDate.apply(this._, arguments); }, setDay: function() { d3_time_prototype.setUTCDay.apply(this._, arguments); }, setFullYear: function() { d3_time_prototype.setUTCFullYear.apply(this._, arguments); }, setHours: function() { d3_time_prototype.setUTCHours.apply(this._, arguments); }, setMilliseconds: function() { d3_time_prototype.setUTCMilliseconds.apply(this._, arguments); }, setMinutes: function() { d3_time_prototype.setUTCMinutes.apply(this._, arguments); }, setMonth: function() { d3_time_prototype.setUTCMonth.apply(this._, arguments); }, setSeconds: function() { d3_time_prototype.setUTCSeconds.apply(this._, arguments); }, setTime: function() { d3_time_prototype.setTime.apply(this._, arguments); } }; var d3_time_prototype = Date.prototype; function d3_time_interval(local, step, number) { function round(date) { var d0 = local(date), d1 = offset(d0, 1); return date - d0 < d1 - date ? d0 : d1; } function ceil(date) { step(date = local(new d3_date(date - 1)), 1); return date; } function offset(date, k) { step(date = new d3_date(+date), k); return date; } function range(t0, t1, dt) { var time = ceil(t0), times = []; if (dt > 1) { while (time < t1) { if (!(number(time) % dt)) times.push(new Date(+time)); step(time, 1); } } else { while (time < t1) times.push(new Date(+time)), step(time, 1); } return times; } function range_utc(t0, t1, dt) { try { d3_date = d3_date_utc; var utc = new d3_date_utc(); utc._ = t0; return range(utc, t1, dt); } finally { d3_date = Date; } } local.floor = local; local.round = round; local.ceil = ceil; local.offset = offset; local.range = range; var utc = local.utc = d3_time_interval_utc(local); utc.floor = utc; utc.round = d3_time_interval_utc(round); utc.ceil = d3_time_interval_utc(ceil); utc.offset = d3_time_interval_utc(offset); utc.range = range_utc; return local; } function d3_time_interval_utc(method) { return function(date, k) { try { d3_date = d3_date_utc; var utc = new d3_date_utc(); utc._ = date; return method(utc, k)._; } finally { d3_date = Date; } }; } d3_time.year = d3_time_interval(function(date) { date = d3_time.day(date); date.setMonth(0, 1); return date; }, function(date, offset) { date.setFullYear(date.getFullYear() + offset); }, function(date) { return date.getFullYear(); }); d3_time.years = d3_time.year.range; d3_time.years.utc = d3_time.year.utc.range; d3_time.day = d3_time_interval(function(date) { var day = new d3_date(2e3, 0); day.setFullYear(date.getFullYear(), date.getMonth(), date.getDate()); return day; }, function(date, offset) { date.setDate(date.getDate() + offset); }, function(date) { return date.getDate() - 1; }); d3_time.days = d3_time.day.range; d3_time.days.utc = d3_time.day.utc.range; d3_time.dayOfYear = function(date) { var year = d3_time.year(date); return Math.floor((date - year - (date.getTimezoneOffset() - year.getTimezoneOffset()) * 6e4) / 864e5); }; [ "sunday", "monday", "tuesday", "wednesday", "thursday", "friday", "saturday" ].forEach(function(day, i) { i = 7 - i; var interval = d3_time[day] = d3_time_interval(function(date) { (date = d3_time.day(date)).setDate(date.getDate() - (date.getDay() + i) % 7); return date; }, function(date, offset) { date.setDate(date.getDate() + Math.floor(offset) * 7); }, function(date) { var day = d3_time.year(date).getDay(); return Math.floor((d3_time.dayOfYear(date) + (day + i) % 7) / 7) - (day !== i); }); d3_time[day + "s"] = interval.range; d3_time[day + "s"].utc = interval.utc.range; d3_time[day + "OfYear"] = function(date) { var day = d3_time.year(date).getDay(); return Math.floor((d3_time.dayOfYear(date) + (day + i) % 7) / 7); }; }); d3_time.week = d3_time.sunday; d3_time.weeks = d3_time.sunday.range; d3_time.weeks.utc = d3_time.sunday.utc.range; d3_time.weekOfYear = d3_time.sundayOfYear; function d3_locale_timeFormat(locale) { var locale_dateTime = locale.dateTime, locale_date = locale.date, locale_time = locale.time, locale_periods = locale.periods, locale_days = locale.days, locale_shortDays = locale.shortDays, locale_months = locale.months, locale_shortMonths = locale.shortMonths; function d3_time_format(template) { var n = template.length; function format(date) { var string = [], i = -1, j = 0, c, p, f; while (++i < n) { if (template.charCodeAt(i) === 37) { string.push(template.slice(j, i)); if ((p = d3_time_formatPads[c = template.charAt(++i)]) != null) c = template.charAt(++i); if (f = d3_time_formats[c]) c = f(date, p == null ? c === "e" ? " " : "0" : p); string.push(c); j = i + 1; } } string.push(template.slice(j, i)); return string.join(""); } format.parse = function(string) { var d = { y: 1900, m: 0, d: 1, H: 0, M: 0, S: 0, L: 0, Z: null }, i = d3_time_parse(d, template, string, 0); if (i != string.length) return null; if ("p" in d) d.H = d.H % 12 + d.p * 12; var localZ = d.Z != null && d3_date !== d3_date_utc, date = new (localZ ? d3_date_utc : d3_date)(); if ("j" in d) date.setFullYear(d.y, 0, d.j); else if ("W" in d || "U" in d) { if (!("w" in d)) d.w = "W" in d ? 1 : 0; date.setFullYear(d.y, 0, 1); date.setFullYear(d.y, 0, "W" in d ? (d.w + 6) % 7 + d.W * 7 - (date.getDay() + 5) % 7 : d.w + d.U * 7 - (date.getDay() + 6) % 7); } else date.setFullYear(d.y, d.m, d.d); date.setHours(d.H + (d.Z / 100 | 0), d.M + d.Z % 100, d.S, d.L); return localZ ? date._ : date; }; format.toString = function() { return template; }; return format; } function d3_time_parse(date, template, string, j) { var c, p, t, i = 0, n = template.length, m = string.length; while (i < n) { if (j >= m) return -1; c = template.charCodeAt(i++); if (c === 37) { t = template.charAt(i++); p = d3_time_parsers[t in d3_time_formatPads ? template.charAt(i++) : t]; if (!p || (j = p(date, string, j)) < 0) return -1; } else if (c != string.charCodeAt(j++)) { return -1; } } return j; } d3_time_format.utc = function(template) { var local = d3_time_format(template); function format(date) { try { d3_date = d3_date_utc; var utc = new d3_date(); utc._ = date; return local(utc); } finally { d3_date = Date; } } format.parse = function(string) { try { d3_date = d3_date_utc; var date = local.parse(string); return date && date._; } finally { d3_date = Date; } }; format.toString = local.toString; return format; }; d3_time_format.multi = d3_time_format.utc.multi = d3_time_formatMulti; var d3_time_periodLookup = d3.map(), d3_time_dayRe = d3_time_formatRe(locale_days), d3_time_dayLookup = d3_time_formatLookup(locale_days), d3_time_dayAbbrevRe = d3_time_formatRe(locale_shortDays), d3_time_dayAbbrevLookup = d3_time_formatLookup(locale_shortDays), d3_time_monthRe = d3_time_formatRe(locale_months), d3_time_monthLookup = d3_time_formatLookup(locale_months), d3_time_monthAbbrevRe = d3_time_formatRe(locale_shortMonths), d3_time_monthAbbrevLookup = d3_time_formatLookup(locale_shortMonths); locale_periods.forEach(function(p, i) { d3_time_periodLookup.set(p.toLowerCase(), i); }); var d3_time_formats = { a: function(d) { return locale_shortDays[d.getDay()]; }, A: function(d) { return locale_days[d.getDay()]; }, b: function(d) { return locale_shortMonths[d.getMonth()]; }, B: function(d) { return locale_months[d.getMonth()]; }, c: d3_time_format(locale_dateTime), d: function(d, p) { return d3_time_formatPad(d.getDate(), p, 2); }, e: function(d, p) { return d3_time_formatPad(d.getDate(), p, 2); }, H: function(d, p) { return d3_time_formatPad(d.getHours(), p, 2); }, I: function(d, p) { return d3_time_formatPad(d.getHours() % 12 || 12, p, 2); }, j: function(d, p) { return d3_time_formatPad(1 + d3_time.dayOfYear(d), p, 3); }, L: function(d, p) { return d3_time_formatPad(d.getMilliseconds(), p, 3); }, m: function(d, p) { return d3_time_formatPad(d.getMonth() + 1, p, 2); }, M: function(d, p) { return d3_time_formatPad(d.getMinutes(), p, 2); }, p: function(d) { return locale_periods[+(d.getHours() >= 12)]; }, S: function(d, p) { return d3_time_formatPad(d.getSeconds(), p, 2); }, U: function(d, p) { return d3_time_formatPad(d3_time.sundayOfYear(d), p, 2); }, w: function(d) { return d.getDay(); }, W: function(d, p) { return d3_time_formatPad(d3_time.mondayOfYear(d), p, 2); }, x: d3_time_format(locale_date), X: d3_time_format(locale_time), y: function(d, p) { return d3_time_formatPad(d.getFullYear() % 100, p, 2); }, Y: function(d, p) { return d3_time_formatPad(d.getFullYear() % 1e4, p, 4); }, Z: d3_time_zone, "%": function() { return "%"; } }; var d3_time_parsers = { a: d3_time_parseWeekdayAbbrev, A: d3_time_parseWeekday, b: d3_time_parseMonthAbbrev, B: d3_time_parseMonth, c: d3_time_parseLocaleFull, d: d3_time_parseDay, e: d3_time_parseDay, H: d3_time_parseHour24, I: d3_time_parseHour24, j: d3_time_parseDayOfYear, L: d3_time_parseMilliseconds, m: d3_time_parseMonthNumber, M: d3_time_parseMinutes, p: d3_time_parseAmPm, S: d3_time_parseSeconds, U: d3_time_parseWeekNumberSunday, w: d3_time_parseWeekdayNumber, W: d3_time_parseWeekNumberMonday, x: d3_time_parseLocaleDate, X: d3_time_parseLocaleTime, y: d3_time_parseYear, Y: d3_time_parseFullYear, Z: d3_time_parseZone, "%": d3_time_parseLiteralPercent }; function d3_time_parseWeekdayAbbrev(date, string, i) { d3_time_dayAbbrevRe.lastIndex = 0; var n = d3_time_dayAbbrevRe.exec(string.slice(i)); return n ? (date.w = d3_time_dayAbbrevLookup.get(n[0].toLowerCase()), i + n[0].length) : -1; } function d3_time_parseWeekday(date, string, i) { d3_time_dayRe.lastIndex = 0; var n = d3_time_dayRe.exec(string.slice(i)); return n ? (date.w = d3_time_dayLookup.get(n[0].toLowerCase()), i + n[0].length) : -1; } function d3_time_parseMonthAbbrev(date, string, i) { d3_time_monthAbbrevRe.lastIndex = 0; var n = d3_time_monthAbbrevRe.exec(string.slice(i)); return n ? (date.m = d3_time_monthAbbrevLookup.get(n[0].toLowerCase()), i + n[0].length) : -1; } function d3_time_parseMonth(date, string, i) { d3_time_monthRe.lastIndex = 0; var n = d3_time_monthRe.exec(string.slice(i)); return n ? (date.m = d3_time_monthLookup.get(n[0].toLowerCase()), i + n[0].length) : -1; } function d3_time_parseLocaleFull(date, string, i) { return d3_time_parse(date, d3_time_formats.c.toString(), string, i); } function d3_time_parseLocaleDate(date, string, i) { return d3_time_parse(date, d3_time_formats.x.toString(), string, i); } function d3_time_parseLocaleTime(date, string, i) { return d3_time_parse(date, d3_time_formats.X.toString(), string, i); } function d3_time_parseAmPm(date, string, i) { var n = d3_time_periodLookup.get(string.slice(i, i += 2).toLowerCase()); return n == null ? -1 : (date.p = n, i); } return d3_time_format; } var d3_time_formatPads = { "-": "", _: " ", "0": "0" }, d3_time_numberRe = /^\s*\d+/, d3_time_percentRe = /^%/; function d3_time_formatPad(value, fill, width) { var sign = value < 0 ? "-" : "", string = (sign ? -value : value) + "", length = string.length; return sign + (length < width ? new Array(width - length + 1).join(fill) + string : string); } function d3_time_formatRe(names) { return new RegExp("^(?:" + names.map(d3.requote).join("|") + ")", "i"); } function d3_time_formatLookup(names) { var map = new d3_Map(), i = -1, n = names.length; while (++i < n) map.set(names[i].toLowerCase(), i); return map; } function d3_time_parseWeekdayNumber(date, string, i) { d3_time_numberRe.lastIndex = 0; var n = d3_time_numberRe.exec(string.slice(i, i + 1)); return n ? (date.w = +n[0], i + n[0].length) : -1; } function d3_time_parseWeekNumberSunday(date, string, i) { d3_time_numberRe.lastIndex = 0; var n = d3_time_numberRe.exec(string.slice(i)); return n ? (date.U = +n[0], i + n[0].length) : -1; } function d3_time_parseWeekNumberMonday(date, string, i) { d3_time_numberRe.lastIndex = 0; var n = d3_time_numberRe.exec(string.slice(i)); return n ? (date.W = +n[0], i + n[0].length) : -1; } function d3_time_parseFullYear(date, string, i) { d3_time_numberRe.lastIndex = 0; var n = d3_time_numberRe.exec(string.slice(i, i + 4)); return n ? (date.y = +n[0], i + n[0].length) : -1; } function d3_time_parseYear(date, string, i) { d3_time_numberRe.lastIndex = 0; var n = d3_time_numberRe.exec(string.slice(i, i + 2)); return n ? (date.y = d3_time_expandYear(+n[0]), i + n[0].length) : -1; } function d3_time_parseZone(date, string, i) { return /^[+-]\d{4}$/.test(string = string.slice(i, i + 5)) ? (date.Z = -string, i + 5) : -1; } function d3_time_expandYear(d) { return d + (d > 68 ? 1900 : 2e3); } function d3_time_parseMonthNumber(date, string, i) { d3_time_numberRe.lastIndex = 0; var n = d3_time_numberRe.exec(string.slice(i, i + 2)); return n ? (date.m = n[0] - 1, i + n[0].length) : -1; } function d3_time_parseDay(date, string, i) { d3_time_numberRe.lastIndex = 0; var n = d3_time_numberRe.exec(string.slice(i, i + 2)); return n ? (date.d = +n[0], i + n[0].length) : -1; } function d3_time_parseDayOfYear(date, string, i) { d3_time_numberRe.lastIndex = 0; var n = d3_time_numberRe.exec(string.slice(i, i + 3)); return n ? (date.j = +n[0], i + n[0].length) : -1; } function d3_time_parseHour24(date, string, i) { d3_time_numberRe.lastIndex = 0; var n = d3_time_numberRe.exec(string.slice(i, i + 2)); return n ? (date.H = +n[0], i + n[0].length) : -1; } function d3_time_parseMinutes(date, string, i) { d3_time_numberRe.lastIndex = 0; var n = d3_time_numberRe.exec(string.slice(i, i + 2)); return n ? (date.M = +n[0], i + n[0].length) : -1; } function d3_time_parseSeconds(date, string, i) { d3_time_numberRe.lastIndex = 0; var n = d3_time_numberRe.exec(string.slice(i, i + 2)); return n ? (date.S = +n[0], i + n[0].length) : -1; } function d3_time_parseMilliseconds(date, string, i) { d3_time_numberRe.lastIndex = 0; var n = d3_time_numberRe.exec(string.slice(i, i + 3)); return n ? (date.L = +n[0], i + n[0].length) : -1; } function d3_time_zone(d) { var z = d.getTimezoneOffset(), zs = z > 0 ? "-" : "+", zh = abs(z) / 60 | 0, zm = abs(z) % 60; return zs + d3_time_formatPad(zh, "0", 2) + d3_time_formatPad(zm, "0", 2); } function d3_time_parseLiteralPercent(date, string, i) { d3_time_percentRe.lastIndex = 0; var n = d3_time_percentRe.exec(string.slice(i, i + 1)); return n ? i + n[0].length : -1; } function d3_time_formatMulti(formats) { var n = formats.length, i = -1; while (++i < n) formats[i][0] = this(formats[i][0]); return function(date) { var i = 0, f = formats[i]; while (!f[1](date)) f = formats[++i]; return f[0](date); }; } d3.locale = function(locale) { return { numberFormat: d3_locale_numberFormat(locale), timeFormat: d3_locale_timeFormat(locale) }; }; var d3_locale_enUS = d3.locale({ decimal: ".", thousands: ",", grouping: [ 3 ], currency: [ "$", "" ], dateTime: "%a %b %e %X %Y", date: "%m/%d/%Y", time: "%H:%M:%S", periods: [ "AM", "PM" ], days: [ "Sunday", "Monday", "Tuesday", "Wednesday", "Thursday", "Friday", "Saturday" ], shortDays: [ "Sun", "Mon", "Tue", "Wed", "Thu", "Fri", "Sat" ], months: [ "January", "February", "March", "April", "May", "June", "July", "August", "September", "October", "November", "December" ], shortMonths: [ "Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec" ] }); d3.format = d3_locale_enUS.numberFormat; d3.geo = {}; function d3_adder() {} d3_adder.prototype = { s: 0, t: 0, add: function(y) { d3_adderSum(y, this.t, d3_adderTemp); d3_adderSum(d3_adderTemp.s, this.s, this); if (this.s) this.t += d3_adderTemp.t; else this.s = d3_adderTemp.t; }, reset: function() { this.s = this.t = 0; }, valueOf: function() { return this.s; } }; var d3_adderTemp = new d3_adder(); function d3_adderSum(a, b, o) { var x = o.s = a + b, bv = x - a, av = x - bv; o.t = a - av + (b - bv); } d3.geo.stream = function(object, listener) { if (object && d3_geo_streamObjectType.hasOwnProperty(object.type)) { d3_geo_streamObjectType[object.type](object, listener); } else { d3_geo_streamGeometry(object, listener); } }; function d3_geo_streamGeometry(geometry, listener) { if (geometry && d3_geo_streamGeometryType.hasOwnProperty(geometry.type)) { d3_geo_streamGeometryType[geometry.type](geometry, listener); } } var d3_geo_streamObjectType = { Feature: function(feature, listener) { d3_geo_streamGeometry(feature.geometry, listener); }, FeatureCollection: function(object, listener) { var features = object.features, i = -1, n = features.length; while (++i < n) d3_geo_streamGeometry(features[i].geometry, listener); } }; var d3_geo_streamGeometryType = { Sphere: function(object, listener) { listener.sphere(); }, Point: function(object, listener) { object = object.coordinates; listener.point(object[0], object[1], object[2]); }, MultiPoint: function(object, listener) { var coordinates = object.coordinates, i = -1, n = coordinates.length; while (++i < n) object = coordinates[i], listener.point(object[0], object[1], object[2]); }, LineString: function(object, listener) { d3_geo_streamLine(object.coordinates, listener, 0); }, MultiLineString: function(object, listener) { var coordinates = object.coordinates, i = -1, n = coordinates.length; while (++i < n) d3_geo_streamLine(coordinates[i], listener, 0); }, Polygon: function(object, listener) { d3_geo_streamPolygon(object.coordinates, listener); }, MultiPolygon: function(object, listener) { var coordinates = object.coordinates, i = -1, n = coordinates.length; while (++i < n) d3_geo_streamPolygon(coordinates[i], listener); }, GeometryCollection: function(object, listener) { var geometries = object.geometries, i = -1, n = geometries.length; while (++i < n) d3_geo_streamGeometry(geometries[i], listener); } }; function d3_geo_streamLine(coordinates, listener, closed) { var i = -1, n = coordinates.length - closed, coordinate; listener.lineStart(); while (++i < n) coordinate = coordinates[i], listener.point(coordinate[0], coordinate[1], coordinate[2]); listener.lineEnd(); } function d3_geo_streamPolygon(coordinates, listener) { var i = -1, n = coordinates.length; listener.polygonStart(); while (++i < n) d3_geo_streamLine(coordinates[i], listener, 1); listener.polygonEnd(); } d3.geo.area = function(object) { d3_geo_areaSum = 0; d3.geo.stream(object, d3_geo_area); return d3_geo_areaSum; }; var d3_geo_areaSum, d3_geo_areaRingSum = new d3_adder(); var d3_geo_area = { sphere: function() { d3_geo_areaSum += 4 * Ï€; }, point: d3_noop, lineStart: d3_noop, lineEnd: d3_noop, polygonStart: function() { d3_geo_areaRingSum.reset(); d3_geo_area.lineStart = d3_geo_areaRingStart; }, polygonEnd: function() { var area = 2 * d3_geo_areaRingSum; d3_geo_areaSum += area < 0 ? 4 * Ï€ + area : area; d3_geo_area.lineStart = d3_geo_area.lineEnd = d3_geo_area.point = d3_noop; } }; function d3_geo_areaRingStart() { var λ00, φ00, λ0, cosφ0, sinφ0; d3_geo_area.point = function(λ, φ) { d3_geo_area.point = nextPoint; λ0 = (λ00 = λ) * d3_radians, cosφ0 = Math.cos(φ = (φ00 = φ) * d3_radians / 2 + Ï€ / 4), sinφ0 = Math.sin(φ); }; function nextPoint(λ, φ) { λ *= d3_radians; φ = φ * d3_radians / 2 + Ï€ / 4; var dλ = λ - λ0, sdλ = dλ >= 0 ? 1 : -1, adλ = sdλ * dλ, cosφ = Math.cos(φ), sinφ = Math.sin(φ), k = sinφ0 * sinφ, u = cosφ0 * cosφ + k * Math.cos(adλ), v = k * sdλ * Math.sin(adλ); d3_geo_areaRingSum.add(Math.atan2(v, u)); λ0 = λ, cosφ0 = cosφ, sinφ0 = sinφ; } d3_geo_area.lineEnd = function() { nextPoint(λ00, φ00); }; } function d3_geo_cartesian(spherical) { var λ = spherical[0], φ = spherical[1], cosφ = Math.cos(φ); return [ cosφ * Math.cos(λ), cosφ * Math.sin(λ), Math.sin(φ) ]; } function d3_geo_cartesianDot(a, b) { return a[0] * b[0] + a[1] * b[1] + a[2] * b[2]; } function d3_geo_cartesianCross(a, b) { return [ a[1] * b[2] - a[2] * b[1], a[2] * b[0] - a[0] * b[2], a[0] * b[1] - a[1] * b[0] ]; } function d3_geo_cartesianAdd(a, b) { a[0] += b[0]; a[1] += b[1]; a[2] += b[2]; } function d3_geo_cartesianScale(vector, k) { return [ vector[0] * k, vector[1] * k, vector[2] * k ]; } function d3_geo_cartesianNormalize(d) { var l = Math.sqrt(d[0] * d[0] + d[1] * d[1] + d[2] * d[2]); d[0] /= l; d[1] /= l; d[2] /= l; } function d3_geo_spherical(cartesian) { return [ Math.atan2(cartesian[1], cartesian[0]), d3_asin(cartesian[2]) ]; } function d3_geo_sphericalEqual(a, b) { return abs(a[0] - b[0]) < ε && abs(a[1] - b[1]) < ε; } d3.geo.bounds = function() { var λ0, φ0, λ1, φ1, λ_, λ__, φ__, p0, dλSum, ranges, range; var bound = { point: point, lineStart: lineStart, lineEnd: lineEnd, polygonStart: function() { bound.point = ringPoint; bound.lineStart = ringStart; bound.lineEnd = ringEnd; dλSum = 0; d3_geo_area.polygonStart(); }, polygonEnd: function() { d3_geo_area.polygonEnd(); bound.point = point; bound.lineStart = lineStart; bound.lineEnd = lineEnd; if (d3_geo_areaRingSum < 0) λ0 = -(λ1 = 180), φ0 = -(φ1 = 90); else if (dλSum > ε) φ1 = 90; else if (dλSum < -ε) φ0 = -90; range[0] = λ0, range[1] = λ1; } }; function point(λ, φ) { ranges.push(range = [ λ0 = λ, λ1 = λ ]); if (φ < φ0) φ0 = φ; if (φ > φ1) φ1 = φ; } function linePoint(λ, φ) { var p = d3_geo_cartesian([ λ * d3_radians, φ * d3_radians ]); if (p0) { var normal = d3_geo_cartesianCross(p0, p), equatorial = [ normal[1], -normal[0], 0 ], inflection = d3_geo_cartesianCross(equatorial, normal); d3_geo_cartesianNormalize(inflection); inflection = d3_geo_spherical(inflection); var dλ = λ - λ_, s = dλ > 0 ? 1 : -1, λi = inflection[0] * d3_degrees * s, antimeridian = abs(dλ) > 180; if (antimeridian ^ (s * λ_ < λi && λi < s * λ)) { var φi = inflection[1] * d3_degrees; if (φi > φ1) φ1 = φi; } else if (λi = (λi + 360) % 360 - 180, antimeridian ^ (s * λ_ < λi && λi < s * λ)) { var φi = -inflection[1] * d3_degrees; if (φi < φ0) φ0 = φi; } else { if (φ < φ0) φ0 = φ; if (φ > φ1) φ1 = φ; } if (antimeridian) { if (λ < λ_) { if (angle(λ0, λ) > angle(λ0, λ1)) λ1 = λ; } else { if (angle(λ, λ1) > angle(λ0, λ1)) λ0 = λ; } } else { if (λ1 >= λ0) { if (λ < λ0) λ0 = λ; if (λ > λ1) λ1 = λ; } else { if (λ > λ_) { if (angle(λ0, λ) > angle(λ0, λ1)) λ1 = λ; } else { if (angle(λ, λ1) > angle(λ0, λ1)) λ0 = λ; } } } } else { point(λ, φ); } p0 = p, λ_ = λ; } function lineStart() { bound.point = linePoint; } function lineEnd() { range[0] = λ0, range[1] = λ1; bound.point = point; p0 = null; } function ringPoint(λ, φ) { if (p0) { var dλ = λ - λ_; dλSum += abs(dλ) > 180 ? dλ + (dλ > 0 ? 360 : -360) : dλ; } else λ__ = λ, φ__ = φ; d3_geo_area.point(λ, φ); linePoint(λ, φ); } function ringStart() { d3_geo_area.lineStart(); } function ringEnd() { ringPoint(λ__, φ__); d3_geo_area.lineEnd(); if (abs(dλSum) > ε) λ0 = -(λ1 = 180); range[0] = λ0, range[1] = λ1; p0 = null; } function angle(λ0, λ1) { return (λ1 -= λ0) < 0 ? λ1 + 360 : λ1; } function compareRanges(a, b) { return a[0] - b[0]; } function withinRange(x, range) { return range[0] <= range[1] ? range[0] <= x && x <= range[1] : x < range[0] || range[1] < x; } return function(feature) { φ1 = λ1 = -(λ0 = φ0 = Infinity); ranges = []; d3.geo.stream(feature, bound); var n = ranges.length; if (n) { ranges.sort(compareRanges); for (var i = 1, a = ranges[0], b, merged = [ a ]; i < n; ++i) { b = ranges[i]; if (withinRange(b[0], a) || withinRange(b[1], a)) { if (angle(a[0], b[1]) > angle(a[0], a[1])) a[1] = b[1]; if (angle(b[0], a[1]) > angle(a[0], a[1])) a[0] = b[0]; } else { merged.push(a = b); } } var best = -Infinity, dλ; for (var n = merged.length - 1, i = 0, a = merged[n], b; i <= n; a = b, ++i) { b = merged[i]; if ((dλ = angle(a[1], b[0])) > best) best = dλ, λ0 = b[0], λ1 = a[1]; } } ranges = range = null; return λ0 === Infinity || φ0 === Infinity ? [ [ NaN, NaN ], [ NaN, NaN ] ] : [ [ λ0, φ0 ], [ λ1, φ1 ] ]; }; }(); d3.geo.centroid = function(object) { d3_geo_centroidW0 = d3_geo_centroidW1 = d3_geo_centroidX0 = d3_geo_centroidY0 = d3_geo_centroidZ0 = d3_geo_centroidX1 = d3_geo_centroidY1 = d3_geo_centroidZ1 = d3_geo_centroidX2 = d3_geo_centroidY2 = d3_geo_centroidZ2 = 0; d3.geo.stream(object, d3_geo_centroid); var x = d3_geo_centroidX2, y = d3_geo_centroidY2, z = d3_geo_centroidZ2, m = x * x + y * y + z * z; if (m < ε2) { x = d3_geo_centroidX1, y = d3_geo_centroidY1, z = d3_geo_centroidZ1; if (d3_geo_centroidW1 < ε) x = d3_geo_centroidX0, y = d3_geo_centroidY0, z = d3_geo_centroidZ0; m = x * x + y * y + z * z; if (m < ε2) return [ NaN, NaN ]; } return [ Math.atan2(y, x) * d3_degrees, d3_asin(z / Math.sqrt(m)) * d3_degrees ]; }; var d3_geo_centroidW0, d3_geo_centroidW1, d3_geo_centroidX0, d3_geo_centroidY0, d3_geo_centroidZ0, d3_geo_centroidX1, d3_geo_centroidY1, d3_geo_centroidZ1, d3_geo_centroidX2, d3_geo_centroidY2, d3_geo_centroidZ2; var d3_geo_centroid = { sphere: d3_noop, point: d3_geo_centroidPoint, lineStart: d3_geo_centroidLineStart, lineEnd: d3_geo_centroidLineEnd, polygonStart: function() { d3_geo_centroid.lineStart = d3_geo_centroidRingStart; }, polygonEnd: function() { d3_geo_centroid.lineStart = d3_geo_centroidLineStart; } }; function d3_geo_centroidPoint(λ, φ) { λ *= d3_radians; var cosφ = Math.cos(φ *= d3_radians); d3_geo_centroidPointXYZ(cosφ * Math.cos(λ), cosφ * Math.sin(λ), Math.sin(φ)); } function d3_geo_centroidPointXYZ(x, y, z) { ++d3_geo_centroidW0; d3_geo_centroidX0 += (x - d3_geo_centroidX0) / d3_geo_centroidW0; d3_geo_centroidY0 += (y - d3_geo_centroidY0) / d3_geo_centroidW0; d3_geo_centroidZ0 += (z - d3_geo_centroidZ0) / d3_geo_centroidW0; } function d3_geo_centroidLineStart() { var x0, y0, z0; d3_geo_centroid.point = function(λ, φ) { λ *= d3_radians; var cosφ = Math.cos(φ *= d3_radians); x0 = cosφ * Math.cos(λ); y0 = cosφ * Math.sin(λ); z0 = Math.sin(φ); d3_geo_centroid.point = nextPoint; d3_geo_centroidPointXYZ(x0, y0, z0); }; function nextPoint(λ, φ) { λ *= d3_radians; var cosφ = Math.cos(φ *= d3_radians), x = cosφ * Math.cos(λ), y = cosφ * Math.sin(λ), z = Math.sin(φ), w = Math.atan2(Math.sqrt((w = y0 * z - z0 * y) * w + (w = z0 * x - x0 * z) * w + (w = x0 * y - y0 * x) * w), x0 * x + y0 * y + z0 * z); d3_geo_centroidW1 += w; d3_geo_centroidX1 += w * (x0 + (x0 = x)); d3_geo_centroidY1 += w * (y0 + (y0 = y)); d3_geo_centroidZ1 += w * (z0 + (z0 = z)); d3_geo_centroidPointXYZ(x0, y0, z0); } } function d3_geo_centroidLineEnd() { d3_geo_centroid.point = d3_geo_centroidPoint; } function d3_geo_centroidRingStart() { var λ00, φ00, x0, y0, z0; d3_geo_centroid.point = function(λ, φ) { λ00 = λ, φ00 = φ; d3_geo_centroid.point = nextPoint; λ *= d3_radians; var cosφ = Math.cos(φ *= d3_radians); x0 = cosφ * Math.cos(λ); y0 = cosφ * Math.sin(λ); z0 = Math.sin(φ); d3_geo_centroidPointXYZ(x0, y0, z0); }; d3_geo_centroid.lineEnd = function() { nextPoint(λ00, φ00); d3_geo_centroid.lineEnd = d3_geo_centroidLineEnd; d3_geo_centroid.point = d3_geo_centroidPoint; }; function nextPoint(λ, φ) { λ *= d3_radians; var cosφ = Math.cos(φ *= d3_radians), x = cosφ * Math.cos(λ), y = cosφ * Math.sin(λ), z = Math.sin(φ), cx = y0 * z - z0 * y, cy = z0 * x - x0 * z, cz = x0 * y - y0 * x, m = Math.sqrt(cx * cx + cy * cy + cz * cz), u = x0 * x + y0 * y + z0 * z, v = m && -d3_acos(u) / m, w = Math.atan2(m, u); d3_geo_centroidX2 += v * cx; d3_geo_centroidY2 += v * cy; d3_geo_centroidZ2 += v * cz; d3_geo_centroidW1 += w; d3_geo_centroidX1 += w * (x0 + (x0 = x)); d3_geo_centroidY1 += w * (y0 + (y0 = y)); d3_geo_centroidZ1 += w * (z0 + (z0 = z)); d3_geo_centroidPointXYZ(x0, y0, z0); } } function d3_geo_compose(a, b) { function compose(x, y) { return x = a(x, y), b(x[0], x[1]); } if (a.invert && b.invert) compose.invert = function(x, y) { return x = b.invert(x, y), x && a.invert(x[0], x[1]); }; return compose; } function d3_true() { return true; } function d3_geo_clipPolygon(segments, compare, clipStartInside, interpolate, listener) { var subject = [], clip = []; segments.forEach(function(segment) { if ((n = segment.length - 1) <= 0) return; var n, p0 = segment[0], p1 = segment[n]; if (d3_geo_sphericalEqual(p0, p1)) { listener.lineStart(); for (var i = 0; i < n; ++i) listener.point((p0 = segment[i])[0], p0[1]); listener.lineEnd(); return; } var a = new d3_geo_clipPolygonIntersection(p0, segment, null, true), b = new d3_geo_clipPolygonIntersection(p0, null, a, false); a.o = b; subject.push(a); clip.push(b); a = new d3_geo_clipPolygonIntersection(p1, segment, null, false); b = new d3_geo_clipPolygonIntersection(p1, null, a, true); a.o = b; subject.push(a); clip.push(b); }); clip.sort(compare); d3_geo_clipPolygonLinkCircular(subject); d3_geo_clipPolygonLinkCircular(clip); if (!subject.length) return; for (var i = 0, entry = clipStartInside, n = clip.length; i < n; ++i) { clip[i].e = entry = !entry; } var start = subject[0], points, point; while (1) { var current = start, isSubject = true; while (current.v) if ((current = current.n) === start) return; points = current.z; listener.lineStart(); do { current.v = current.o.v = true; if (current.e) { if (isSubject) { for (var i = 0, n = points.length; i < n; ++i) listener.point((point = points[i])[0], point[1]); } else { interpolate(current.x, current.n.x, 1, listener); } current = current.n; } else { if (isSubject) { points = current.p.z; for (var i = points.length - 1; i >= 0; --i) listener.point((point = points[i])[0], point[1]); } else { interpolate(current.x, current.p.x, -1, listener); } current = current.p; } current = current.o; points = current.z; isSubject = !isSubject; } while (!current.v); listener.lineEnd(); } } function d3_geo_clipPolygonLinkCircular(array) { if (!(n = array.length)) return; var n, i = 0, a = array[0], b; while (++i < n) { a.n = b = array[i]; b.p = a; a = b; } a.n = b = array[0]; b.p = a; } function d3_geo_clipPolygonIntersection(point, points, other, entry) { this.x = point; this.z = points; this.o = other; this.e = entry; this.v = false; this.n = this.p = null; } function d3_geo_clip(pointVisible, clipLine, interpolate, clipStart) { return function(rotate, listener) { var line = clipLine(listener), rotatedClipStart = rotate.invert(clipStart[0], clipStart[1]); var clip = { point: point, lineStart: lineStart, lineEnd: lineEnd, polygonStart: function() { clip.point = pointRing; clip.lineStart = ringStart; clip.lineEnd = ringEnd; segments = []; polygon = []; }, polygonEnd: function() { clip.point = point; clip.lineStart = lineStart; clip.lineEnd = lineEnd; segments = d3.merge(segments); var clipStartInside = d3_geo_pointInPolygon(rotatedClipStart, polygon); if (segments.length) { if (!polygonStarted) listener.polygonStart(), polygonStarted = true; d3_geo_clipPolygon(segments, d3_geo_clipSort, clipStartInside, interpolate, listener); } else if (clipStartInside) { if (!polygonStarted) listener.polygonStart(), polygonStarted = true; listener.lineStart(); interpolate(null, null, 1, listener); listener.lineEnd(); } if (polygonStarted) listener.polygonEnd(), polygonStarted = false; segments = polygon = null; }, sphere: function() { listener.polygonStart(); listener.lineStart(); interpolate(null, null, 1, listener); listener.lineEnd(); listener.polygonEnd(); } }; function point(λ, φ) { var point = rotate(λ, φ); if (pointVisible(λ = point[0], φ = point[1])) listener.point(λ, φ); } function pointLine(λ, φ) { var point = rotate(λ, φ); line.point(point[0], point[1]); } function lineStart() { clip.point = pointLine; line.lineStart(); } function lineEnd() { clip.point = point; line.lineEnd(); } var segments; var buffer = d3_geo_clipBufferListener(), ringListener = clipLine(buffer), polygonStarted = false, polygon, ring; function pointRing(λ, φ) { ring.push([ λ, φ ]); var point = rotate(λ, φ); ringListener.point(point[0], point[1]); } function ringStart() { ringListener.lineStart(); ring = []; } function ringEnd() { pointRing(ring[0][0], ring[0][1]); ringListener.lineEnd(); var clean = ringListener.clean(), ringSegments = buffer.buffer(), segment, n = ringSegments.length; ring.pop(); polygon.push(ring); ring = null; if (!n) return; if (clean & 1) { segment = ringSegments[0]; var n = segment.length - 1, i = -1, point; if (n > 0) { if (!polygonStarted) listener.polygonStart(), polygonStarted = true; listener.lineStart(); while (++i < n) listener.point((point = segment[i])[0], point[1]); listener.lineEnd(); } return; } if (n > 1 && clean & 2) ringSegments.push(ringSegments.pop().concat(ringSegments.shift())); segments.push(ringSegments.filter(d3_geo_clipSegmentLength1)); } return clip; }; } function d3_geo_clipSegmentLength1(segment) { return segment.length > 1; } function d3_geo_clipBufferListener() { var lines = [], line; return { lineStart: function() { lines.push(line = []); }, point: function(λ, φ) { line.push([ λ, φ ]); }, lineEnd: d3_noop, buffer: function() { var buffer = lines; lines = []; line = null; return buffer; }, rejoin: function() { if (lines.length > 1) lines.push(lines.pop().concat(lines.shift())); } }; } function d3_geo_clipSort(a, b) { return ((a = a.x)[0] < 0 ? a[1] - halfÏ€ - ε : halfÏ€ - a[1]) - ((b = b.x)[0] < 0 ? b[1] - halfÏ€ - ε : halfÏ€ - b[1]); } var d3_geo_clipAntimeridian = d3_geo_clip(d3_true, d3_geo_clipAntimeridianLine, d3_geo_clipAntimeridianInterpolate, [ -Ï€, -Ï€ / 2 ]); function d3_geo_clipAntimeridianLine(listener) { var λ0 = NaN, φ0 = NaN, sλ0 = NaN, clean; return { lineStart: function() { listener.lineStart(); clean = 1; }, point: function(λ1, φ1) { var sλ1 = λ1 > 0 ? Ï€ : -Ï€, dλ = abs(λ1 - λ0); if (abs(dλ - Ï€) < ε) { listener.point(λ0, φ0 = (φ0 + φ1) / 2 > 0 ? halfÏ€ : -halfÏ€); listener.point(sλ0, φ0); listener.lineEnd(); listener.lineStart(); listener.point(sλ1, φ0); listener.point(λ1, φ0); clean = 0; } else if (sλ0 !== sλ1 && dλ >= Ï€) { if (abs(λ0 - sλ0) < ε) λ0 -= sλ0 * ε; if (abs(λ1 - sλ1) < ε) λ1 -= sλ1 * ε; φ0 = d3_geo_clipAntimeridianIntersect(λ0, φ0, λ1, φ1); listener.point(sλ0, φ0); listener.lineEnd(); listener.lineStart(); listener.point(sλ1, φ0); clean = 0; } listener.point(λ0 = λ1, φ0 = φ1); sλ0 = sλ1; }, lineEnd: function() { listener.lineEnd(); λ0 = φ0 = NaN; }, clean: function() { return 2 - clean; } }; } function d3_geo_clipAntimeridianIntersect(λ0, φ0, λ1, φ1) { var cosφ0, cosφ1, sinλ0_λ1 = Math.sin(λ0 - λ1); return abs(sinλ0_λ1) > ε ? Math.atan((Math.sin(φ0) * (cosφ1 = Math.cos(φ1)) * Math.sin(λ1) - Math.sin(φ1) * (cosφ0 = Math.cos(φ0)) * Math.sin(λ0)) / (cosφ0 * cosφ1 * sinλ0_λ1)) : (φ0 + φ1) / 2; } function d3_geo_clipAntimeridianInterpolate(from, to, direction, listener) { var φ; if (from == null) { φ = direction * halfÏ€; listener.point(-Ï€, φ); listener.point(0, φ); listener.point(Ï€, φ); listener.point(Ï€, 0); listener.point(Ï€, -φ); listener.point(0, -φ); listener.point(-Ï€, -φ); listener.point(-Ï€, 0); listener.point(-Ï€, φ); } else if (abs(from[0] - to[0]) > ε) { var s = from[0] < to[0] ? Ï€ : -Ï€; φ = direction * s / 2; listener.point(-s, φ); listener.point(0, φ); listener.point(s, φ); } else { listener.point(to[0], to[1]); } } function d3_geo_pointInPolygon(point, polygon) { var meridian = point[0], parallel = point[1], meridianNormal = [ Math.sin(meridian), -Math.cos(meridian), 0 ], polarAngle = 0, winding = 0; d3_geo_areaRingSum.reset(); for (var i = 0, n = polygon.length; i < n; ++i) { var ring = polygon[i], m = ring.length; if (!m) continue; var point0 = ring[0], λ0 = point0[0], φ0 = point0[1] / 2 + Ï€ / 4, sinφ0 = Math.sin(φ0), cosφ0 = Math.cos(φ0), j = 1; while (true) { if (j === m) j = 0; point = ring[j]; var λ = point[0], φ = point[1] / 2 + Ï€ / 4, sinφ = Math.sin(φ), cosφ = Math.cos(φ), dλ = λ - λ0, sdλ = dλ >= 0 ? 1 : -1, adλ = sdλ * dλ, antimeridian = adλ > Ï€, k = sinφ0 * sinφ; d3_geo_areaRingSum.add(Math.atan2(k * sdλ * Math.sin(adλ), cosφ0 * cosφ + k * Math.cos(adλ))); polarAngle += antimeridian ? dλ + sdλ * Ï„ : dλ; if (antimeridian ^ λ0 >= meridian ^ λ >= meridian) { var arc = d3_geo_cartesianCross(d3_geo_cartesian(point0), d3_geo_cartesian(point)); d3_geo_cartesianNormalize(arc); var intersection = d3_geo_cartesianCross(meridianNormal, arc); d3_geo_cartesianNormalize(intersection); var φarc = (antimeridian ^ dλ >= 0 ? -1 : 1) * d3_asin(intersection[2]); if (parallel > φarc || parallel === φarc && (arc[0] || arc[1])) { winding += antimeridian ^ dλ >= 0 ? 1 : -1; } } if (!j++) break; λ0 = λ, sinφ0 = sinφ, cosφ0 = cosφ, point0 = point; } } return (polarAngle < -ε || polarAngle < ε && d3_geo_areaRingSum < -ε) ^ winding & 1; } function d3_geo_clipCircle(radius) { var cr = Math.cos(radius), smallRadius = cr > 0, notHemisphere = abs(cr) > ε, interpolate = d3_geo_circleInterpolate(radius, 6 * d3_radians); return d3_geo_clip(visible, clipLine, interpolate, smallRadius ? [ 0, -radius ] : [ -Ï€, radius - Ï€ ]); function visible(λ, φ) { return Math.cos(λ) * Math.cos(φ) > cr; } function clipLine(listener) { var point0, c0, v0, v00, clean; return { lineStart: function() { v00 = v0 = false; clean = 1; }, point: function(λ, φ) { var point1 = [ λ, φ ], point2, v = visible(λ, φ), c = smallRadius ? v ? 0 : code(λ, φ) : v ? code(λ + (λ < 0 ? Ï€ : -Ï€), φ) : 0; if (!point0 && (v00 = v0 = v)) listener.lineStart(); if (v !== v0) { point2 = intersect(point0, point1); if (d3_geo_sphericalEqual(point0, point2) || d3_geo_sphericalEqual(point1, point2)) { point1[0] += ε; point1[1] += ε; v = visible(point1[0], point1[1]); } } if (v !== v0) { clean = 0; if (v) { listener.lineStart(); point2 = intersect(point1, point0); listener.point(point2[0], point2[1]); } else { point2 = intersect(point0, point1); listener.point(point2[0], point2[1]); listener.lineEnd(); } point0 = point2; } else if (notHemisphere && point0 && smallRadius ^ v) { var t; if (!(c & c0) && (t = intersect(point1, point0, true))) { clean = 0; if (smallRadius) { listener.lineStart(); listener.point(t[0][0], t[0][1]); listener.point(t[1][0], t[1][1]); listener.lineEnd(); } else { listener.point(t[1][0], t[1][1]); listener.lineEnd(); listener.lineStart(); listener.point(t[0][0], t[0][1]); } } } if (v && (!point0 || !d3_geo_sphericalEqual(point0, point1))) { listener.point(point1[0], point1[1]); } point0 = point1, v0 = v, c0 = c; }, lineEnd: function() { if (v0) listener.lineEnd(); point0 = null; }, clean: function() { return clean | (v00 && v0) << 1; } }; } function intersect(a, b, two) { var pa = d3_geo_cartesian(a), pb = d3_geo_cartesian(b); var n1 = [ 1, 0, 0 ], n2 = d3_geo_cartesianCross(pa, pb), n2n2 = d3_geo_cartesianDot(n2, n2), n1n2 = n2[0], determinant = n2n2 - n1n2 * n1n2; if (!determinant) return !two && a; var c1 = cr * n2n2 / determinant, c2 = -cr * n1n2 / determinant, n1xn2 = d3_geo_cartesianCross(n1, n2), A = d3_geo_cartesianScale(n1, c1), B = d3_geo_cartesianScale(n2, c2); d3_geo_cartesianAdd(A, B); var u = n1xn2, w = d3_geo_cartesianDot(A, u), uu = d3_geo_cartesianDot(u, u), t2 = w * w - uu * (d3_geo_cartesianDot(A, A) - 1); if (t2 < 0) return; var t = Math.sqrt(t2), q = d3_geo_cartesianScale(u, (-w - t) / uu); d3_geo_cartesianAdd(q, A); q = d3_geo_spherical(q); if (!two) return q; var λ0 = a[0], λ1 = b[0], φ0 = a[1], φ1 = b[1], z; if (λ1 < λ0) z = λ0, λ0 = λ1, λ1 = z; var δλ = λ1 - λ0, polar = abs(δλ - Ï€) < ε, meridian = polar || δλ < ε; if (!polar && φ1 < φ0) z = φ0, φ0 = φ1, φ1 = z; if (meridian ? polar ? φ0 + φ1 > 0 ^ q[1] < (abs(q[0] - λ0) < ε ? φ0 : φ1) : φ0 <= q[1] && q[1] <= φ1 : δλ > Ï€ ^ (λ0 <= q[0] && q[0] <= λ1)) { var q1 = d3_geo_cartesianScale(u, (-w + t) / uu); d3_geo_cartesianAdd(q1, A); return [ q, d3_geo_spherical(q1) ]; } } function code(λ, φ) { var r = smallRadius ? radius : Ï€ - radius, code = 0; if (λ < -r) code |= 1; else if (λ > r) code |= 2; if (φ < -r) code |= 4; else if (φ > r) code |= 8; return code; } } function d3_geom_clipLine(x0, y0, x1, y1) { return function(line) { var a = line.a, b = line.b, ax = a.x, ay = a.y, bx = b.x, by = b.y, t0 = 0, t1 = 1, dx = bx - ax, dy = by - ay, r; r = x0 - ax; if (!dx && r > 0) return; r /= dx; if (dx < 0) { if (r < t0) return; if (r < t1) t1 = r; } else if (dx > 0) { if (r > t1) return; if (r > t0) t0 = r; } r = x1 - ax; if (!dx && r < 0) return; r /= dx; if (dx < 0) { if (r > t1) return; if (r > t0) t0 = r; } else if (dx > 0) { if (r < t0) return; if (r < t1) t1 = r; } r = y0 - ay; if (!dy && r > 0) return; r /= dy; if (dy < 0) { if (r < t0) return; if (r < t1) t1 = r; } else if (dy > 0) { if (r > t1) return; if (r > t0) t0 = r; } r = y1 - ay; if (!dy && r < 0) return; r /= dy; if (dy < 0) { if (r > t1) return; if (r > t0) t0 = r; } else if (dy > 0) { if (r < t0) return; if (r < t1) t1 = r; } if (t0 > 0) line.a = { x: ax + t0 * dx, y: ay + t0 * dy }; if (t1 < 1) line.b = { x: ax + t1 * dx, y: ay + t1 * dy }; return line; }; } var d3_geo_clipExtentMAX = 1e9; d3.geo.clipExtent = function() { var x0, y0, x1, y1, stream, clip, clipExtent = { stream: function(output) { if (stream) stream.valid = false; stream = clip(output); stream.valid = true; return stream; }, extent: function(_) { if (!arguments.length) return [ [ x0, y0 ], [ x1, y1 ] ]; clip = d3_geo_clipExtent(x0 = +_[0][0], y0 = +_[0][1], x1 = +_[1][0], y1 = +_[1][1]); if (stream) stream.valid = false, stream = null; return clipExtent; } }; return clipExtent.extent([ [ 0, 0 ], [ 960, 500 ] ]); }; function d3_geo_clipExtent(x0, y0, x1, y1) { return function(listener) { var listener_ = listener, bufferListener = d3_geo_clipBufferListener(), clipLine = d3_geom_clipLine(x0, y0, x1, y1), segments, polygon, ring; var clip = { point: point, lineStart: lineStart, lineEnd: lineEnd, polygonStart: function() { listener = bufferListener; segments = []; polygon = []; clean = true; }, polygonEnd: function() { listener = listener_; segments = d3.merge(segments); var clipStartInside = insidePolygon([ x0, y1 ]), inside = clean && clipStartInside, visible = segments.length; if (inside || visible) { listener.polygonStart(); if (inside) { listener.lineStart(); interpolate(null, null, 1, listener); listener.lineEnd(); } if (visible) { d3_geo_clipPolygon(segments, compare, clipStartInside, interpolate, listener); } listener.polygonEnd(); } segments = polygon = ring = null; } }; function insidePolygon(p) { var wn = 0, n = polygon.length, y = p[1]; for (var i = 0; i < n; ++i) { for (var j = 1, v = polygon[i], m = v.length, a = v[0], b; j < m; ++j) { b = v[j]; if (a[1] <= y) { if (b[1] > y && d3_cross2d(a, b, p) > 0) ++wn; } else { if (b[1] <= y && d3_cross2d(a, b, p) < 0) --wn; } a = b; } } return wn !== 0; } function interpolate(from, to, direction, listener) { var a = 0, a1 = 0; if (from == null || (a = corner(from, direction)) !== (a1 = corner(to, direction)) || comparePoints(from, to) < 0 ^ direction > 0) { do { listener.point(a === 0 || a === 3 ? x0 : x1, a > 1 ? y1 : y0); } while ((a = (a + direction + 4) % 4) !== a1); } else { listener.point(to[0], to[1]); } } function pointVisible(x, y) { return x0 <= x && x <= x1 && y0 <= y && y <= y1; } function point(x, y) { if (pointVisible(x, y)) listener.point(x, y); } var x__, y__, v__, x_, y_, v_, first, clean; function lineStart() { clip.point = linePoint; if (polygon) polygon.push(ring = []); first = true; v_ = false; x_ = y_ = NaN; } function lineEnd() { if (segments) { linePoint(x__, y__); if (v__ && v_) bufferListener.rejoin(); segments.push(bufferListener.buffer()); } clip.point = point; if (v_) listener.lineEnd(); } function linePoint(x, y) { x = Math.max(-d3_geo_clipExtentMAX, Math.min(d3_geo_clipExtentMAX, x)); y = Math.max(-d3_geo_clipExtentMAX, Math.min(d3_geo_clipExtentMAX, y)); var v = pointVisible(x, y); if (polygon) ring.push([ x, y ]); if (first) { x__ = x, y__ = y, v__ = v; first = false; if (v) { listener.lineStart(); listener.point(x, y); } } else { if (v && v_) listener.point(x, y); else { var l = { a: { x: x_, y: y_ }, b: { x: x, y: y } }; if (clipLine(l)) { if (!v_) { listener.lineStart(); listener.point(l.a.x, l.a.y); } listener.point(l.b.x, l.b.y); if (!v) listener.lineEnd(); clean = false; } else if (v) { listener.lineStart(); listener.point(x, y); clean = false; } } } x_ = x, y_ = y, v_ = v; } return clip; }; function corner(p, direction) { return abs(p[0] - x0) < ε ? direction > 0 ? 0 : 3 : abs(p[0] - x1) < ε ? direction > 0 ? 2 : 1 : abs(p[1] - y0) < ε ? direction > 0 ? 1 : 0 : direction > 0 ? 3 : 2; } function compare(a, b) { return comparePoints(a.x, b.x); } function comparePoints(a, b) { var ca = corner(a, 1), cb = corner(b, 1); return ca !== cb ? ca - cb : ca === 0 ? b[1] - a[1] : ca === 1 ? a[0] - b[0] : ca === 2 ? a[1] - b[1] : b[0] - a[0]; } } function d3_geo_conic(projectAt) { var φ0 = 0, φ1 = Ï€ / 3, m = d3_geo_projectionMutator(projectAt), p = m(φ0, φ1); p.parallels = function(_) { if (!arguments.length) return [ φ0 / Ï€ * 180, φ1 / Ï€ * 180 ]; return m(φ0 = _[0] * Ï€ / 180, φ1 = _[1] * Ï€ / 180); }; return p; } function d3_geo_conicEqualArea(φ0, φ1) { var sinφ0 = Math.sin(φ0), n = (sinφ0 + Math.sin(φ1)) / 2, C = 1 + sinφ0 * (2 * n - sinφ0), Ï0 = Math.sqrt(C) / n; function forward(λ, φ) { var Ï = Math.sqrt(C - 2 * n * Math.sin(φ)) / n; return [ Ï * Math.sin(λ *= n), Ï0 - Ï * Math.cos(λ) ]; } forward.invert = function(x, y) { var Ï0_y = Ï0 - y; return [ Math.atan2(x, Ï0_y) / n, d3_asin((C - (x * x + Ï0_y * Ï0_y) * n * n) / (2 * n)) ]; }; return forward; } (d3.geo.conicEqualArea = function() { return d3_geo_conic(d3_geo_conicEqualArea); }).raw = d3_geo_conicEqualArea; d3.geo.albers = function() { return d3.geo.conicEqualArea().rotate([ 96, 0 ]).center([ -.6, 38.7 ]).parallels([ 29.5, 45.5 ]).scale(1070); }; d3.geo.albersUsa = function() { var lower48 = d3.geo.albers(); var alaska = d3.geo.conicEqualArea().rotate([ 154, 0 ]).center([ -2, 58.5 ]).parallels([ 55, 65 ]); var hawaii = d3.geo.conicEqualArea().rotate([ 157, 0 ]).center([ -3, 19.9 ]).parallels([ 8, 18 ]); var point, pointStream = { point: function(x, y) { point = [ x, y ]; } }, lower48Point, alaskaPoint, hawaiiPoint; function albersUsa(coordinates) { var x = coordinates[0], y = coordinates[1]; point = null; (lower48Point(x, y), point) || (alaskaPoint(x, y), point) || hawaiiPoint(x, y); return point; } albersUsa.invert = function(coordinates) { var k = lower48.scale(), t = lower48.translate(), x = (coordinates[0] - t[0]) / k, y = (coordinates[1] - t[1]) / k; return (y >= .12 && y < .234 && x >= -.425 && x < -.214 ? alaska : y >= .166 && y < .234 && x >= -.214 && x < -.115 ? hawaii : lower48).invert(coordinates); }; albersUsa.stream = function(stream) { var lower48Stream = lower48.stream(stream), alaskaStream = alaska.stream(stream), hawaiiStream = hawaii.stream(stream); return { point: function(x, y) { lower48Stream.point(x, y); alaskaStream.point(x, y); hawaiiStream.point(x, y); }, sphere: function() { lower48Stream.sphere(); alaskaStream.sphere(); hawaiiStream.sphere(); }, lineStart: function() { lower48Stream.lineStart(); alaskaStream.lineStart(); hawaiiStream.lineStart(); }, lineEnd: function() { lower48Stream.lineEnd(); alaskaStream.lineEnd(); hawaiiStream.lineEnd(); }, polygonStart: function() { lower48Stream.polygonStart(); alaskaStream.polygonStart(); hawaiiStream.polygonStart(); }, polygonEnd: function() { lower48Stream.polygonEnd(); alaskaStream.polygonEnd(); hawaiiStream.polygonEnd(); } }; }; albersUsa.precision = function(_) { if (!arguments.length) return lower48.precision(); lower48.precision(_); alaska.precision(_); hawaii.precision(_); return albersUsa; }; albersUsa.scale = function(_) { if (!arguments.length) return lower48.scale(); lower48.scale(_); alaska.scale(_ * .35); hawaii.scale(_); return albersUsa.translate(lower48.translate()); }; albersUsa.translate = function(_) { if (!arguments.length) return lower48.translate(); var k = lower48.scale(), x = +_[0], y = +_[1]; lower48Point = lower48.translate(_).clipExtent([ [ x - .455 * k, y - .238 * k ], [ x + .455 * k, y + .238 * k ] ]).stream(pointStream).point; alaskaPoint = alaska.translate([ x - .307 * k, y + .201 * k ]).clipExtent([ [ x - .425 * k + ε, y + .12 * k + ε ], [ x - .214 * k - ε, y + .234 * k - ε ] ]).stream(pointStream).point; hawaiiPoint = hawaii.translate([ x - .205 * k, y + .212 * k ]).clipExtent([ [ x - .214 * k + ε, y + .166 * k + ε ], [ x - .115 * k - ε, y + .234 * k - ε ] ]).stream(pointStream).point; return albersUsa; }; return albersUsa.scale(1070); }; var d3_geo_pathAreaSum, d3_geo_pathAreaPolygon, d3_geo_pathArea = { point: d3_noop, lineStart: d3_noop, lineEnd: d3_noop, polygonStart: function() { d3_geo_pathAreaPolygon = 0; d3_geo_pathArea.lineStart = d3_geo_pathAreaRingStart; }, polygonEnd: function() { d3_geo_pathArea.lineStart = d3_geo_pathArea.lineEnd = d3_geo_pathArea.point = d3_noop; d3_geo_pathAreaSum += abs(d3_geo_pathAreaPolygon / 2); } }; function d3_geo_pathAreaRingStart() { var x00, y00, x0, y0; d3_geo_pathArea.point = function(x, y) { d3_geo_pathArea.point = nextPoint; x00 = x0 = x, y00 = y0 = y; }; function nextPoint(x, y) { d3_geo_pathAreaPolygon += y0 * x - x0 * y; x0 = x, y0 = y; } d3_geo_pathArea.lineEnd = function() { nextPoint(x00, y00); }; } var d3_geo_pathBoundsX0, d3_geo_pathBoundsY0, d3_geo_pathBoundsX1, d3_geo_pathBoundsY1; var d3_geo_pathBounds = { point: d3_geo_pathBoundsPoint, lineStart: d3_noop, lineEnd: d3_noop, polygonStart: d3_noop, polygonEnd: d3_noop }; function d3_geo_pathBoundsPoint(x, y) { if (x < d3_geo_pathBoundsX0) d3_geo_pathBoundsX0 = x; if (x > d3_geo_pathBoundsX1) d3_geo_pathBoundsX1 = x; if (y < d3_geo_pathBoundsY0) d3_geo_pathBoundsY0 = y; if (y > d3_geo_pathBoundsY1) d3_geo_pathBoundsY1 = y; } function d3_geo_pathBuffer() { var pointCircle = d3_geo_pathBufferCircle(4.5), buffer = []; var stream = { point: point, lineStart: function() { stream.point = pointLineStart; }, lineEnd: lineEnd, polygonStart: function() { stream.lineEnd = lineEndPolygon; }, polygonEnd: function() { stream.lineEnd = lineEnd; stream.point = point; }, pointRadius: function(_) { pointCircle = d3_geo_pathBufferCircle(_); return stream; }, result: function() { if (buffer.length) { var result = buffer.join(""); buffer = []; return result; } } }; function point(x, y) { buffer.push("M", x, ",", y, pointCircle); } function pointLineStart(x, y) { buffer.push("M", x, ",", y); stream.point = pointLine; } function pointLine(x, y) { buffer.push("L", x, ",", y); } function lineEnd() { stream.point = point; } function lineEndPolygon() { buffer.push("Z"); } return stream; } function d3_geo_pathBufferCircle(radius) { return "m0," + radius + "a" + radius + "," + radius + " 0 1,1 0," + -2 * radius + "a" + radius + "," + radius + " 0 1,1 0," + 2 * radius + "z"; } var d3_geo_pathCentroid = { point: d3_geo_pathCentroidPoint, lineStart: d3_geo_pathCentroidLineStart, lineEnd: d3_geo_pathCentroidLineEnd, polygonStart: function() { d3_geo_pathCentroid.lineStart = d3_geo_pathCentroidRingStart; }, polygonEnd: function() { d3_geo_pathCentroid.point = d3_geo_pathCentroidPoint; d3_geo_pathCentroid.lineStart = d3_geo_pathCentroidLineStart; d3_geo_pathCentroid.lineEnd = d3_geo_pathCentroidLineEnd; } }; function d3_geo_pathCentroidPoint(x, y) { d3_geo_centroidX0 += x; d3_geo_centroidY0 += y; ++d3_geo_centroidZ0; } function d3_geo_pathCentroidLineStart() { var x0, y0; d3_geo_pathCentroid.point = function(x, y) { d3_geo_pathCentroid.point = nextPoint; d3_geo_pathCentroidPoint(x0 = x, y0 = y); }; function nextPoint(x, y) { var dx = x - x0, dy = y - y0, z = Math.sqrt(dx * dx + dy * dy); d3_geo_centroidX1 += z * (x0 + x) / 2; d3_geo_centroidY1 += z * (y0 + y) / 2; d3_geo_centroidZ1 += z; d3_geo_pathCentroidPoint(x0 = x, y0 = y); } } function d3_geo_pathCentroidLineEnd() { d3_geo_pathCentroid.point = d3_geo_pathCentroidPoint; } function d3_geo_pathCentroidRingStart() { var x00, y00, x0, y0; d3_geo_pathCentroid.point = function(x, y) { d3_geo_pathCentroid.point = nextPoint; d3_geo_pathCentroidPoint(x00 = x0 = x, y00 = y0 = y); }; function nextPoint(x, y) { var dx = x - x0, dy = y - y0, z = Math.sqrt(dx * dx + dy * dy); d3_geo_centroidX1 += z * (x0 + x) / 2; d3_geo_centroidY1 += z * (y0 + y) / 2; d3_geo_centroidZ1 += z; z = y0 * x - x0 * y; d3_geo_centroidX2 += z * (x0 + x); d3_geo_centroidY2 += z * (y0 + y); d3_geo_centroidZ2 += z * 3; d3_geo_pathCentroidPoint(x0 = x, y0 = y); } d3_geo_pathCentroid.lineEnd = function() { nextPoint(x00, y00); }; } function d3_geo_pathContext(context) { var pointRadius = 4.5; var stream = { point: point, lineStart: function() { stream.point = pointLineStart; }, lineEnd: lineEnd, polygonStart: function() { stream.lineEnd = lineEndPolygon; }, polygonEnd: function() { stream.lineEnd = lineEnd; stream.point = point; }, pointRadius: function(_) { pointRadius = _; return stream; }, result: d3_noop }; function point(x, y) { context.moveTo(x + pointRadius, y); context.arc(x, y, pointRadius, 0, Ï„); } function pointLineStart(x, y) { context.moveTo(x, y); stream.point = pointLine; } function pointLine(x, y) { context.lineTo(x, y); } function lineEnd() { stream.point = point; } function lineEndPolygon() { context.closePath(); } return stream; } function d3_geo_resample(project) { var δ2 = .5, cosMinDistance = Math.cos(30 * d3_radians), maxDepth = 16; function resample(stream) { return (maxDepth ? resampleRecursive : resampleNone)(stream); } function resampleNone(stream) { return d3_geo_transformPoint(stream, function(x, y) { x = project(x, y); stream.point(x[0], x[1]); }); } function resampleRecursive(stream) { var λ00, φ00, x00, y00, a00, b00, c00, λ0, x0, y0, a0, b0, c0; var resample = { point: point, lineStart: lineStart, lineEnd: lineEnd, polygonStart: function() { stream.polygonStart(); resample.lineStart = ringStart; }, polygonEnd: function() { stream.polygonEnd(); resample.lineStart = lineStart; } }; function point(x, y) { x = project(x, y); stream.point(x[0], x[1]); } function lineStart() { x0 = NaN; resample.point = linePoint; stream.lineStart(); } function linePoint(λ, φ) { var c = d3_geo_cartesian([ λ, φ ]), p = project(λ, φ); resampleLineTo(x0, y0, λ0, a0, b0, c0, x0 = p[0], y0 = p[1], λ0 = λ, a0 = c[0], b0 = c[1], c0 = c[2], maxDepth, stream); stream.point(x0, y0); } function lineEnd() { resample.point = point; stream.lineEnd(); } function ringStart() { lineStart(); resample.point = ringPoint; resample.lineEnd = ringEnd; } function ringPoint(λ, φ) { linePoint(λ00 = λ, φ00 = φ), x00 = x0, y00 = y0, a00 = a0, b00 = b0, c00 = c0; resample.point = linePoint; } function ringEnd() { resampleLineTo(x0, y0, λ0, a0, b0, c0, x00, y00, λ00, a00, b00, c00, maxDepth, stream); resample.lineEnd = lineEnd; lineEnd(); } return resample; } function resampleLineTo(x0, y0, λ0, a0, b0, c0, x1, y1, λ1, a1, b1, c1, depth, stream) { var dx = x1 - x0, dy = y1 - y0, d2 = dx * dx + dy * dy; if (d2 > 4 * δ2 && depth--) { var a = a0 + a1, b = b0 + b1, c = c0 + c1, m = Math.sqrt(a * a + b * b + c * c), φ2 = Math.asin(c /= m), λ2 = abs(abs(c) - 1) < ε || abs(λ0 - λ1) < ε ? (λ0 + λ1) / 2 : Math.atan2(b, a), p = project(λ2, φ2), x2 = p[0], y2 = p[1], dx2 = x2 - x0, dy2 = y2 - y0, dz = dy * dx2 - dx * dy2; if (dz * dz / d2 > δ2 || abs((dx * dx2 + dy * dy2) / d2 - .5) > .3 || a0 * a1 + b0 * b1 + c0 * c1 < cosMinDistance) { resampleLineTo(x0, y0, λ0, a0, b0, c0, x2, y2, λ2, a /= m, b /= m, c, depth, stream); stream.point(x2, y2); resampleLineTo(x2, y2, λ2, a, b, c, x1, y1, λ1, a1, b1, c1, depth, stream); } } } resample.precision = function(_) { if (!arguments.length) return Math.sqrt(δ2); maxDepth = (δ2 = _ * _) > 0 && 16; return resample; }; return resample; } d3.geo.path = function() { var pointRadius = 4.5, projection, context, projectStream, contextStream, cacheStream; function path(object) { if (object) { if (typeof pointRadius === "function") contextStream.pointRadius(+pointRadius.apply(this, arguments)); if (!cacheStream || !cacheStream.valid) cacheStream = projectStream(contextStream); d3.geo.stream(object, cacheStream); } return contextStream.result(); } path.area = function(object) { d3_geo_pathAreaSum = 0; d3.geo.stream(object, projectStream(d3_geo_pathArea)); return d3_geo_pathAreaSum; }; path.centroid = function(object) { d3_geo_centroidX0 = d3_geo_centroidY0 = d3_geo_centroidZ0 = d3_geo_centroidX1 = d3_geo_centroidY1 = d3_geo_centroidZ1 = d3_geo_centroidX2 = d3_geo_centroidY2 = d3_geo_centroidZ2 = 0; d3.geo.stream(object, projectStream(d3_geo_pathCentroid)); return d3_geo_centroidZ2 ? [ d3_geo_centroidX2 / d3_geo_centroidZ2, d3_geo_centroidY2 / d3_geo_centroidZ2 ] : d3_geo_centroidZ1 ? [ d3_geo_centroidX1 / d3_geo_centroidZ1, d3_geo_centroidY1 / d3_geo_centroidZ1 ] : d3_geo_centroidZ0 ? [ d3_geo_centroidX0 / d3_geo_centroidZ0, d3_geo_centroidY0 / d3_geo_centroidZ0 ] : [ NaN, NaN ]; }; path.bounds = function(object) { d3_geo_pathBoundsX1 = d3_geo_pathBoundsY1 = -(d3_geo_pathBoundsX0 = d3_geo_pathBoundsY0 = Infinity); d3.geo.stream(object, projectStream(d3_geo_pathBounds)); return [ [ d3_geo_pathBoundsX0, d3_geo_pathBoundsY0 ], [ d3_geo_pathBoundsX1, d3_geo_pathBoundsY1 ] ]; }; path.projection = function(_) { if (!arguments.length) return projection; projectStream = (projection = _) ? _.stream || d3_geo_pathProjectStream(_) : d3_identity; return reset(); }; path.context = function(_) { if (!arguments.length) return context; contextStream = (context = _) == null ? new d3_geo_pathBuffer() : new d3_geo_pathContext(_); if (typeof pointRadius !== "function") contextStream.pointRadius(pointRadius); return reset(); }; path.pointRadius = function(_) { if (!arguments.length) return pointRadius; pointRadius = typeof _ === "function" ? _ : (contextStream.pointRadius(+_), +_); return path; }; function reset() { cacheStream = null; return path; } return path.projection(d3.geo.albersUsa()).context(null); }; function d3_geo_pathProjectStream(project) { var resample = d3_geo_resample(function(x, y) { return project([ x * d3_degrees, y * d3_degrees ]); }); return function(stream) { return d3_geo_projectionRadians(resample(stream)); }; } d3.geo.transform = function(methods) { return { stream: function(stream) { var transform = new d3_geo_transform(stream); for (var k in methods) transform[k] = methods[k]; return transform; } }; }; function d3_geo_transform(stream) { this.stream = stream; } d3_geo_transform.prototype = { point: function(x, y) { this.stream.point(x, y); }, sphere: function() { this.stream.sphere(); }, lineStart: function() { this.stream.lineStart(); }, lineEnd: function() { this.stream.lineEnd(); }, polygonStart: function() { this.stream.polygonStart(); }, polygonEnd: function() { this.stream.polygonEnd(); } }; function d3_geo_transformPoint(stream, point) { return { point: point, sphere: function() { stream.sphere(); }, lineStart: function() { stream.lineStart(); }, lineEnd: function() { stream.lineEnd(); }, polygonStart: function() { stream.polygonStart(); }, polygonEnd: function() { stream.polygonEnd(); } }; } d3.geo.projection = d3_geo_projection; d3.geo.projectionMutator = d3_geo_projectionMutator; function d3_geo_projection(project) { return d3_geo_projectionMutator(function() { return project; })(); } function d3_geo_projectionMutator(projectAt) { var project, rotate, projectRotate, projectResample = d3_geo_resample(function(x, y) { x = project(x, y); return [ x[0] * k + δx, δy - x[1] * k ]; }), k = 150, x = 480, y = 250, λ = 0, φ = 0, δλ = 0, δφ = 0, δγ = 0, δx, δy, preclip = d3_geo_clipAntimeridian, postclip = d3_identity, clipAngle = null, clipExtent = null, stream; function projection(point) { point = projectRotate(point[0] * d3_radians, point[1] * d3_radians); return [ point[0] * k + δx, δy - point[1] * k ]; } function invert(point) { point = projectRotate.invert((point[0] - δx) / k, (δy - point[1]) / k); return point && [ point[0] * d3_degrees, point[1] * d3_degrees ]; } projection.stream = function(output) { if (stream) stream.valid = false; stream = d3_geo_projectionRadians(preclip(rotate, projectResample(postclip(output)))); stream.valid = true; return stream; }; projection.clipAngle = function(_) { if (!arguments.length) return clipAngle; preclip = _ == null ? (clipAngle = _, d3_geo_clipAntimeridian) : d3_geo_clipCircle((clipAngle = +_) * d3_radians); return invalidate(); }; projection.clipExtent = function(_) { if (!arguments.length) return clipExtent; clipExtent = _; postclip = _ ? d3_geo_clipExtent(_[0][0], _[0][1], _[1][0], _[1][1]) : d3_identity; return invalidate(); }; projection.scale = function(_) { if (!arguments.length) return k; k = +_; return reset(); }; projection.translate = function(_) { if (!arguments.length) return [ x, y ]; x = +_[0]; y = +_[1]; return reset(); }; projection.center = function(_) { if (!arguments.length) return [ λ * d3_degrees, φ * d3_degrees ]; λ = _[0] % 360 * d3_radians; φ = _[1] % 360 * d3_radians; return reset(); }; projection.rotate = function(_) { if (!arguments.length) return [ δλ * d3_degrees, δφ * d3_degrees, δγ * d3_degrees ]; δλ = _[0] % 360 * d3_radians; δφ = _[1] % 360 * d3_radians; δγ = _.length > 2 ? _[2] % 360 * d3_radians : 0; return reset(); }; d3.rebind(projection, projectResample, "precision"); function reset() { projectRotate = d3_geo_compose(rotate = d3_geo_rotation(δλ, δφ, δγ), project); var center = project(λ, φ); δx = x - center[0] * k; δy = y + center[1] * k; return invalidate(); } function invalidate() { if (stream) stream.valid = false, stream = null; return projection; } return function() { project = projectAt.apply(this, arguments); projection.invert = project.invert && invert; return reset(); }; } function d3_geo_projectionRadians(stream) { return d3_geo_transformPoint(stream, function(x, y) { stream.point(x * d3_radians, y * d3_radians); }); } function d3_geo_equirectangular(λ, φ) { return [ λ, φ ]; } (d3.geo.equirectangular = function() { return d3_geo_projection(d3_geo_equirectangular); }).raw = d3_geo_equirectangular.invert = d3_geo_equirectangular; d3.geo.rotation = function(rotate) { rotate = d3_geo_rotation(rotate[0] % 360 * d3_radians, rotate[1] * d3_radians, rotate.length > 2 ? rotate[2] * d3_radians : 0); function forward(coordinates) { coordinates = rotate(coordinates[0] * d3_radians, coordinates[1] * d3_radians); return coordinates[0] *= d3_degrees, coordinates[1] *= d3_degrees, coordinates; } forward.invert = function(coordinates) { coordinates = rotate.invert(coordinates[0] * d3_radians, coordinates[1] * d3_radians); return coordinates[0] *= d3_degrees, coordinates[1] *= d3_degrees, coordinates; }; return forward; }; function d3_geo_identityRotation(λ, φ) { return [ λ > Ï€ ? λ - Ï„ : λ < -Ï€ ? λ + Ï„ : λ, φ ]; } d3_geo_identityRotation.invert = d3_geo_equirectangular; function d3_geo_rotation(δλ, δφ, δγ) { return δλ ? δφ || δγ ? d3_geo_compose(d3_geo_rotationλ(δλ), d3_geo_rotationφγ(δφ, δγ)) : d3_geo_rotationλ(δλ) : δφ || δγ ? d3_geo_rotationφγ(δφ, δγ) : d3_geo_identityRotation; } function d3_geo_forwardRotationλ(δλ) { return function(λ, φ) { return λ += δλ, [ λ > Ï€ ? λ - Ï„ : λ < -Ï€ ? λ + Ï„ : λ, φ ]; }; } function d3_geo_rotationλ(δλ) { var rotation = d3_geo_forwardRotationλ(δλ); rotation.invert = d3_geo_forwardRotationλ(-δλ); return rotation; } function d3_geo_rotationφγ(δφ, δγ) { var cosδφ = Math.cos(δφ), sinδφ = Math.sin(δφ), cosδγ = Math.cos(δγ), sinδγ = Math.sin(δγ); function rotation(λ, φ) { var cosφ = Math.cos(φ), x = Math.cos(λ) * cosφ, y = Math.sin(λ) * cosφ, z = Math.sin(φ), k = z * cosδφ + x * sinδφ; return [ Math.atan2(y * cosδγ - k * sinδγ, x * cosδφ - z * sinδφ), d3_asin(k * cosδγ + y * sinδγ) ]; } rotation.invert = function(λ, φ) { var cosφ = Math.cos(φ), x = Math.cos(λ) * cosφ, y = Math.sin(λ) * cosφ, z = Math.sin(φ), k = z * cosδγ - y * sinδγ; return [ Math.atan2(y * cosδγ + z * sinδγ, x * cosδφ + k * sinδφ), d3_asin(k * cosδφ - x * sinδφ) ]; }; return rotation; } d3.geo.circle = function() { var origin = [ 0, 0 ], angle, precision = 6, interpolate; function circle() { var center = typeof origin === "function" ? origin.apply(this, arguments) : origin, rotate = d3_geo_rotation(-center[0] * d3_radians, -center[1] * d3_radians, 0).invert, ring = []; interpolate(null, null, 1, { point: function(x, y) { ring.push(x = rotate(x, y)); x[0] *= d3_degrees, x[1] *= d3_degrees; } }); return { type: "Polygon", coordinates: [ ring ] }; } circle.origin = function(x) { if (!arguments.length) return origin; origin = x; return circle; }; circle.angle = function(x) { if (!arguments.length) return angle; interpolate = d3_geo_circleInterpolate((angle = +x) * d3_radians, precision * d3_radians); return circle; }; circle.precision = function(_) { if (!arguments.length) return precision; interpolate = d3_geo_circleInterpolate(angle * d3_radians, (precision = +_) * d3_radians); return circle; }; return circle.angle(90); }; function d3_geo_circleInterpolate(radius, precision) { var cr = Math.cos(radius), sr = Math.sin(radius); return function(from, to, direction, listener) { var step = direction * precision; if (from != null) { from = d3_geo_circleAngle(cr, from); to = d3_geo_circleAngle(cr, to); if (direction > 0 ? from < to : from > to) from += direction * Ï„; } else { from = radius + direction * Ï„; to = radius - .5 * step; } for (var point, t = from; direction > 0 ? t > to : t < to; t -= step) { listener.point((point = d3_geo_spherical([ cr, -sr * Math.cos(t), -sr * Math.sin(t) ]))[0], point[1]); } }; } function d3_geo_circleAngle(cr, point) { var a = d3_geo_cartesian(point); a[0] -= cr; d3_geo_cartesianNormalize(a); var angle = d3_acos(-a[1]); return ((-a[2] < 0 ? -angle : angle) + 2 * Math.PI - ε) % (2 * Math.PI); } d3.geo.distance = function(a, b) { var Δλ = (b[0] - a[0]) * d3_radians, φ0 = a[1] * d3_radians, φ1 = b[1] * d3_radians, sinΔλ = Math.sin(Δλ), cosΔλ = Math.cos(Δλ), sinφ0 = Math.sin(φ0), cosφ0 = Math.cos(φ0), sinφ1 = Math.sin(φ1), cosφ1 = Math.cos(φ1), t; return Math.atan2(Math.sqrt((t = cosφ1 * sinΔλ) * t + (t = cosφ0 * sinφ1 - sinφ0 * cosφ1 * cosΔλ) * t), sinφ0 * sinφ1 + cosφ0 * cosφ1 * cosΔλ); }; d3.geo.graticule = function() { var x1, x0, X1, X0, y1, y0, Y1, Y0, dx = 10, dy = dx, DX = 90, DY = 360, x, y, X, Y, precision = 2.5; function graticule() { return { type: "MultiLineString", coordinates: lines() }; } function lines() { return d3.range(Math.ceil(X0 / DX) * DX, X1, DX).map(X).concat(d3.range(Math.ceil(Y0 / DY) * DY, Y1, DY).map(Y)).concat(d3.range(Math.ceil(x0 / dx) * dx, x1, dx).filter(function(x) { return abs(x % DX) > ε; }).map(x)).concat(d3.range(Math.ceil(y0 / dy) * dy, y1, dy).filter(function(y) { return abs(y % DY) > ε; }).map(y)); } graticule.lines = function() { return lines().map(function(coordinates) { return { type: "LineString", coordinates: coordinates }; }); }; graticule.outline = function() { return { type: "Polygon", coordinates: [ X(X0).concat(Y(Y1).slice(1), X(X1).reverse().slice(1), Y(Y0).reverse().slice(1)) ] }; }; graticule.extent = function(_) { if (!arguments.length) return graticule.minorExtent(); return graticule.majorExtent(_).minorExtent(_); }; graticule.majorExtent = function(_) { if (!arguments.length) return [ [ X0, Y0 ], [ X1, Y1 ] ]; X0 = +_[0][0], X1 = +_[1][0]; Y0 = +_[0][1], Y1 = +_[1][1]; if (X0 > X1) _ = X0, X0 = X1, X1 = _; if (Y0 > Y1) _ = Y0, Y0 = Y1, Y1 = _; return graticule.precision(precision); }; graticule.minorExtent = function(_) { if (!arguments.length) return [ [ x0, y0 ], [ x1, y1 ] ]; x0 = +_[0][0], x1 = +_[1][0]; y0 = +_[0][1], y1 = +_[1][1]; if (x0 > x1) _ = x0, x0 = x1, x1 = _; if (y0 > y1) _ = y0, y0 = y1, y1 = _; return graticule.precision(precision); }; graticule.step = function(_) { if (!arguments.length) return graticule.minorStep(); return graticule.majorStep(_).minorStep(_); }; graticule.majorStep = function(_) { if (!arguments.length) return [ DX, DY ]; DX = +_[0], DY = +_[1]; return graticule; }; graticule.minorStep = function(_) { if (!arguments.length) return [ dx, dy ]; dx = +_[0], dy = +_[1]; return graticule; }; graticule.precision = function(_) { if (!arguments.length) return precision; precision = +_; x = d3_geo_graticuleX(y0, y1, 90); y = d3_geo_graticuleY(x0, x1, precision); X = d3_geo_graticuleX(Y0, Y1, 90); Y = d3_geo_graticuleY(X0, X1, precision); return graticule; }; return graticule.majorExtent([ [ -180, -90 + ε ], [ 180, 90 - ε ] ]).minorExtent([ [ -180, -80 - ε ], [ 180, 80 + ε ] ]); }; function d3_geo_graticuleX(y0, y1, dy) { var y = d3.range(y0, y1 - ε, dy).concat(y1); return function(x) { return y.map(function(y) { return [ x, y ]; }); }; } function d3_geo_graticuleY(x0, x1, dx) { var x = d3.range(x0, x1 - ε, dx).concat(x1); return function(y) { return x.map(function(x) { return [ x, y ]; }); }; } function d3_source(d) { return d.source; } function d3_target(d) { return d.target; } d3.geo.greatArc = function() { var source = d3_source, source_, target = d3_target, target_; function greatArc() { return { type: "LineString", coordinates: [ source_ || source.apply(this, arguments), target_ || target.apply(this, arguments) ] }; } greatArc.distance = function() { return d3.geo.distance(source_ || source.apply(this, arguments), target_ || target.apply(this, arguments)); }; greatArc.source = function(_) { if (!arguments.length) return source; source = _, source_ = typeof _ === "function" ? null : _; return greatArc; }; greatArc.target = function(_) { if (!arguments.length) return target; target = _, target_ = typeof _ === "function" ? null : _; return greatArc; }; greatArc.precision = function() { return arguments.length ? greatArc : 0; }; return greatArc; }; d3.geo.interpolate = function(source, target) { return d3_geo_interpolate(source[0] * d3_radians, source[1] * d3_radians, target[0] * d3_radians, target[1] * d3_radians); }; function d3_geo_interpolate(x0, y0, x1, y1) { var cy0 = Math.cos(y0), sy0 = Math.sin(y0), cy1 = Math.cos(y1), sy1 = Math.sin(y1), kx0 = cy0 * Math.cos(x0), ky0 = cy0 * Math.sin(x0), kx1 = cy1 * Math.cos(x1), ky1 = cy1 * Math.sin(x1), d = 2 * Math.asin(Math.sqrt(d3_haversin(y1 - y0) + cy0 * cy1 * d3_haversin(x1 - x0))), k = 1 / Math.sin(d); var interpolate = d ? function(t) { var B = Math.sin(t *= d) * k, A = Math.sin(d - t) * k, x = A * kx0 + B * kx1, y = A * ky0 + B * ky1, z = A * sy0 + B * sy1; return [ Math.atan2(y, x) * d3_degrees, Math.atan2(z, Math.sqrt(x * x + y * y)) * d3_degrees ]; } : function() { return [ x0 * d3_degrees, y0 * d3_degrees ]; }; interpolate.distance = d; return interpolate; } d3.geo.length = function(object) { d3_geo_lengthSum = 0; d3.geo.stream(object, d3_geo_length); return d3_geo_lengthSum; }; var d3_geo_lengthSum; var d3_geo_length = { sphere: d3_noop, point: d3_noop, lineStart: d3_geo_lengthLineStart, lineEnd: d3_noop, polygonStart: d3_noop, polygonEnd: d3_noop }; function d3_geo_lengthLineStart() { var λ0, sinφ0, cosφ0; d3_geo_length.point = function(λ, φ) { λ0 = λ * d3_radians, sinφ0 = Math.sin(φ *= d3_radians), cosφ0 = Math.cos(φ); d3_geo_length.point = nextPoint; }; d3_geo_length.lineEnd = function() { d3_geo_length.point = d3_geo_length.lineEnd = d3_noop; }; function nextPoint(λ, φ) { var sinφ = Math.sin(φ *= d3_radians), cosφ = Math.cos(φ), t = abs((λ *= d3_radians) - λ0), cosΔλ = Math.cos(t); d3_geo_lengthSum += Math.atan2(Math.sqrt((t = cosφ * Math.sin(t)) * t + (t = cosφ0 * sinφ - sinφ0 * cosφ * cosΔλ) * t), sinφ0 * sinφ + cosφ0 * cosφ * cosΔλ); λ0 = λ, sinφ0 = sinφ, cosφ0 = cosφ; } } function d3_geo_azimuthal(scale, angle) { function azimuthal(λ, φ) { var cosλ = Math.cos(λ), cosφ = Math.cos(φ), k = scale(cosλ * cosφ); return [ k * cosφ * Math.sin(λ), k * Math.sin(φ) ]; } azimuthal.invert = function(x, y) { var Ï = Math.sqrt(x * x + y * y), c = angle(Ï), sinc = Math.sin(c), cosc = Math.cos(c); return [ Math.atan2(x * sinc, Ï * cosc), Math.asin(Ï && y * sinc / Ï) ]; }; return azimuthal; } var d3_geo_azimuthalEqualArea = d3_geo_azimuthal(function(cosλcosφ) { return Math.sqrt(2 / (1 + cosλcosφ)); }, function(Ï) { return 2 * Math.asin(Ï / 2); }); (d3.geo.azimuthalEqualArea = function() { return d3_geo_projection(d3_geo_azimuthalEqualArea); }).raw = d3_geo_azimuthalEqualArea; var d3_geo_azimuthalEquidistant = d3_geo_azimuthal(function(cosλcosφ) { var c = Math.acos(cosλcosφ); return c && c / Math.sin(c); }, d3_identity); (d3.geo.azimuthalEquidistant = function() { return d3_geo_projection(d3_geo_azimuthalEquidistant); }).raw = d3_geo_azimuthalEquidistant; function d3_geo_conicConformal(φ0, φ1) { var cosφ0 = Math.cos(φ0), t = function(φ) { return Math.tan(Ï€ / 4 + φ / 2); }, n = φ0 === φ1 ? Math.sin(φ0) : Math.log(cosφ0 / Math.cos(φ1)) / Math.log(t(φ1) / t(φ0)), F = cosφ0 * Math.pow(t(φ0), n) / n; if (!n) return d3_geo_mercator; function forward(λ, φ) { if (F > 0) { if (φ < -halfÏ€ + ε) φ = -halfÏ€ + ε; } else { if (φ > halfÏ€ - ε) φ = halfÏ€ - ε; } var Ï = F / Math.pow(t(φ), n); return [ Ï * Math.sin(n * λ), F - Ï * Math.cos(n * λ) ]; } forward.invert = function(x, y) { var Ï0_y = F - y, Ï = d3_sgn(n) * Math.sqrt(x * x + Ï0_y * Ï0_y); return [ Math.atan2(x, Ï0_y) / n, 2 * Math.atan(Math.pow(F / Ï, 1 / n)) - halfÏ€ ]; }; return forward; } (d3.geo.conicConformal = function() { return d3_geo_conic(d3_geo_conicConformal); }).raw = d3_geo_conicConformal; function d3_geo_conicEquidistant(φ0, φ1) { var cosφ0 = Math.cos(φ0), n = φ0 === φ1 ? Math.sin(φ0) : (cosφ0 - Math.cos(φ1)) / (φ1 - φ0), G = cosφ0 / n + φ0; if (abs(n) < ε) return d3_geo_equirectangular; function forward(λ, φ) { var Ï = G - φ; return [ Ï * Math.sin(n * λ), G - Ï * Math.cos(n * λ) ]; } forward.invert = function(x, y) { var Ï0_y = G - y; return [ Math.atan2(x, Ï0_y) / n, G - d3_sgn(n) * Math.sqrt(x * x + Ï0_y * Ï0_y) ]; }; return forward; } (d3.geo.conicEquidistant = function() { return d3_geo_conic(d3_geo_conicEquidistant); }).raw = d3_geo_conicEquidistant; var d3_geo_gnomonic = d3_geo_azimuthal(function(cosλcosφ) { return 1 / cosλcosφ; }, Math.atan); (d3.geo.gnomonic = function() { return d3_geo_projection(d3_geo_gnomonic); }).raw = d3_geo_gnomonic; function d3_geo_mercator(λ, φ) { return [ λ, Math.log(Math.tan(Ï€ / 4 + φ / 2)) ]; } d3_geo_mercator.invert = function(x, y) { return [ x, 2 * Math.atan(Math.exp(y)) - halfÏ€ ]; }; function d3_geo_mercatorProjection(project) { var m = d3_geo_projection(project), scale = m.scale, translate = m.translate, clipExtent = m.clipExtent, clipAuto; m.scale = function() { var v = scale.apply(m, arguments); return v === m ? clipAuto ? m.clipExtent(null) : m : v; }; m.translate = function() { var v = translate.apply(m, arguments); return v === m ? clipAuto ? m.clipExtent(null) : m : v; }; m.clipExtent = function(_) { var v = clipExtent.apply(m, arguments); if (v === m) { if (clipAuto = _ == null) { var k = Ï€ * scale(), t = translate(); clipExtent([ [ t[0] - k, t[1] - k ], [ t[0] + k, t[1] + k ] ]); } } else if (clipAuto) { v = null; } return v; }; return m.clipExtent(null); } (d3.geo.mercator = function() { return d3_geo_mercatorProjection(d3_geo_mercator); }).raw = d3_geo_mercator; var d3_geo_orthographic = d3_geo_azimuthal(function() { return 1; }, Math.asin); (d3.geo.orthographic = function() { return d3_geo_projection(d3_geo_orthographic); }).raw = d3_geo_orthographic; var d3_geo_stereographic = d3_geo_azimuthal(function(cosλcosφ) { return 1 / (1 + cosλcosφ); }, function(Ï) { return 2 * Math.atan(Ï); }); (d3.geo.stereographic = function() { return d3_geo_projection(d3_geo_stereographic); }).raw = d3_geo_stereographic; function d3_geo_transverseMercator(λ, φ) { return [ Math.log(Math.tan(Ï€ / 4 + φ / 2)), -λ ]; } d3_geo_transverseMercator.invert = function(x, y) { return [ -y, 2 * Math.atan(Math.exp(x)) - halfÏ€ ]; }; (d3.geo.transverseMercator = function() { var projection = d3_geo_mercatorProjection(d3_geo_transverseMercator), center = projection.center, rotate = projection.rotate; projection.center = function(_) { return _ ? center([ -_[1], _[0] ]) : (_ = center(), [ _[1], -_[0] ]); }; projection.rotate = function(_) { return _ ? rotate([ _[0], _[1], _.length > 2 ? _[2] + 90 : 90 ]) : (_ = rotate(), [ _[0], _[1], _[2] - 90 ]); }; return rotate([ 0, 0, 90 ]); }).raw = d3_geo_transverseMercator; d3.geom = {}; function d3_geom_pointX(d) { return d[0]; } function d3_geom_pointY(d) { return d[1]; } d3.geom.hull = function(vertices) { var x = d3_geom_pointX, y = d3_geom_pointY; if (arguments.length) return hull(vertices); function hull(data) { if (data.length < 3) return []; var fx = d3_functor(x), fy = d3_functor(y), i, n = data.length, points = [], flippedPoints = []; for (i = 0; i < n; i++) { points.push([ +fx.call(this, data[i], i), +fy.call(this, data[i], i), i ]); } points.sort(d3_geom_hullOrder); for (i = 0; i < n; i++) flippedPoints.push([ points[i][0], -points[i][1] ]); var upper = d3_geom_hullUpper(points), lower = d3_geom_hullUpper(flippedPoints); var skipLeft = lower[0] === upper[0], skipRight = lower[lower.length - 1] === upper[upper.length - 1], polygon = []; for (i = upper.length - 1; i >= 0; --i) polygon.push(data[points[upper[i]][2]]); for (i = +skipLeft; i < lower.length - skipRight; ++i) polygon.push(data[points[lower[i]][2]]); return polygon; } hull.x = function(_) { return arguments.length ? (x = _, hull) : x; }; hull.y = function(_) { return arguments.length ? (y = _, hull) : y; }; return hull; }; function d3_geom_hullUpper(points) { var n = points.length, hull = [ 0, 1 ], hs = 2; for (var i = 2; i < n; i++) { while (hs > 1 && d3_cross2d(points[hull[hs - 2]], points[hull[hs - 1]], points[i]) <= 0) --hs; hull[hs++] = i; } return hull.slice(0, hs); } function d3_geom_hullOrder(a, b) { return a[0] - b[0] || a[1] - b[1]; } d3.geom.polygon = function(coordinates) { d3_subclass(coordinates, d3_geom_polygonPrototype); return coordinates; }; var d3_geom_polygonPrototype = d3.geom.polygon.prototype = []; d3_geom_polygonPrototype.area = function() { var i = -1, n = this.length, a, b = this[n - 1], area = 0; while (++i < n) { a = b; b = this[i]; area += a[1] * b[0] - a[0] * b[1]; } return area * .5; }; d3_geom_polygonPrototype.centroid = function(k) { var i = -1, n = this.length, x = 0, y = 0, a, b = this[n - 1], c; if (!arguments.length) k = -1 / (6 * this.area()); while (++i < n) { a = b; b = this[i]; c = a[0] * b[1] - b[0] * a[1]; x += (a[0] + b[0]) * c; y += (a[1] + b[1]) * c; } return [ x * k, y * k ]; }; d3_geom_polygonPrototype.clip = function(subject) { var input, closed = d3_geom_polygonClosed(subject), i = -1, n = this.length - d3_geom_polygonClosed(this), j, m, a = this[n - 1], b, c, d; while (++i < n) { input = subject.slice(); subject.length = 0; b = this[i]; c = input[(m = input.length - closed) - 1]; j = -1; while (++j < m) { d = input[j]; if (d3_geom_polygonInside(d, a, b)) { if (!d3_geom_polygonInside(c, a, b)) { subject.push(d3_geom_polygonIntersect(c, d, a, b)); } subject.push(d); } else if (d3_geom_polygonInside(c, a, b)) { subject.push(d3_geom_polygonIntersect(c, d, a, b)); } c = d; } if (closed) subject.push(subject[0]); a = b; } return subject; }; function d3_geom_polygonInside(p, a, b) { return (b[0] - a[0]) * (p[1] - a[1]) < (b[1] - a[1]) * (p[0] - a[0]); } function d3_geom_polygonIntersect(c, d, a, b) { var x1 = c[0], x3 = a[0], x21 = d[0] - x1, x43 = b[0] - x3, y1 = c[1], y3 = a[1], y21 = d[1] - y1, y43 = b[1] - y3, ua = (x43 * (y1 - y3) - y43 * (x1 - x3)) / (y43 * x21 - x43 * y21); return [ x1 + ua * x21, y1 + ua * y21 ]; } function d3_geom_polygonClosed(coordinates) { var a = coordinates[0], b = coordinates[coordinates.length - 1]; return !(a[0] - b[0] || a[1] - b[1]); } var d3_geom_voronoiEdges, d3_geom_voronoiCells, d3_geom_voronoiBeaches, d3_geom_voronoiBeachPool = [], d3_geom_voronoiFirstCircle, d3_geom_voronoiCircles, d3_geom_voronoiCirclePool = []; function d3_geom_voronoiBeach() { d3_geom_voronoiRedBlackNode(this); this.edge = this.site = this.circle = null; } function d3_geom_voronoiCreateBeach(site) { var beach = d3_geom_voronoiBeachPool.pop() || new d3_geom_voronoiBeach(); beach.site = site; return beach; } function d3_geom_voronoiDetachBeach(beach) { d3_geom_voronoiDetachCircle(beach); d3_geom_voronoiBeaches.remove(beach); d3_geom_voronoiBeachPool.push(beach); d3_geom_voronoiRedBlackNode(beach); } function d3_geom_voronoiRemoveBeach(beach) { var circle = beach.circle, x = circle.x, y = circle.cy, vertex = { x: x, y: y }, previous = beach.P, next = beach.N, disappearing = [ beach ]; d3_geom_voronoiDetachBeach(beach); var lArc = previous; while (lArc.circle && abs(x - lArc.circle.x) < ε && abs(y - lArc.circle.cy) < ε) { previous = lArc.P; disappearing.unshift(lArc); d3_geom_voronoiDetachBeach(lArc); lArc = previous; } disappearing.unshift(lArc); d3_geom_voronoiDetachCircle(lArc); var rArc = next; while (rArc.circle && abs(x - rArc.circle.x) < ε && abs(y - rArc.circle.cy) < ε) { next = rArc.N; disappearing.push(rArc); d3_geom_voronoiDetachBeach(rArc); rArc = next; } disappearing.push(rArc); d3_geom_voronoiDetachCircle(rArc); var nArcs = disappearing.length, iArc; for (iArc = 1; iArc < nArcs; ++iArc) { rArc = disappearing[iArc]; lArc = disappearing[iArc - 1]; d3_geom_voronoiSetEdgeEnd(rArc.edge, lArc.site, rArc.site, vertex); } lArc = disappearing[0]; rArc = disappearing[nArcs - 1]; rArc.edge = d3_geom_voronoiCreateEdge(lArc.site, rArc.site, null, vertex); d3_geom_voronoiAttachCircle(lArc); d3_geom_voronoiAttachCircle(rArc); } function d3_geom_voronoiAddBeach(site) { var x = site.x, directrix = site.y, lArc, rArc, dxl, dxr, node = d3_geom_voronoiBeaches._; while (node) { dxl = d3_geom_voronoiLeftBreakPoint(node, directrix) - x; if (dxl > ε) node = node.L; else { dxr = x - d3_geom_voronoiRightBreakPoint(node, directrix); if (dxr > ε) { if (!node.R) { lArc = node; break; } node = node.R; } else { if (dxl > -ε) { lArc = node.P; rArc = node; } else if (dxr > -ε) { lArc = node; rArc = node.N; } else { lArc = rArc = node; } break; } } } var newArc = d3_geom_voronoiCreateBeach(site); d3_geom_voronoiBeaches.insert(lArc, newArc); if (!lArc && !rArc) return; if (lArc === rArc) { d3_geom_voronoiDetachCircle(lArc); rArc = d3_geom_voronoiCreateBeach(lArc.site); d3_geom_voronoiBeaches.insert(newArc, rArc); newArc.edge = rArc.edge = d3_geom_voronoiCreateEdge(lArc.site, newArc.site); d3_geom_voronoiAttachCircle(lArc); d3_geom_voronoiAttachCircle(rArc); return; } if (!rArc) { newArc.edge = d3_geom_voronoiCreateEdge(lArc.site, newArc.site); return; } d3_geom_voronoiDetachCircle(lArc); d3_geom_voronoiDetachCircle(rArc); var lSite = lArc.site, ax = lSite.x, ay = lSite.y, bx = site.x - ax, by = site.y - ay, rSite = rArc.site, cx = rSite.x - ax, cy = rSite.y - ay, d = 2 * (bx * cy - by * cx), hb = bx * bx + by * by, hc = cx * cx + cy * cy, vertex = { x: (cy * hb - by * hc) / d + ax, y: (bx * hc - cx * hb) / d + ay }; d3_geom_voronoiSetEdgeEnd(rArc.edge, lSite, rSite, vertex); newArc.edge = d3_geom_voronoiCreateEdge(lSite, site, null, vertex); rArc.edge = d3_geom_voronoiCreateEdge(site, rSite, null, vertex); d3_geom_voronoiAttachCircle(lArc); d3_geom_voronoiAttachCircle(rArc); } function d3_geom_voronoiLeftBreakPoint(arc, directrix) { var site = arc.site, rfocx = site.x, rfocy = site.y, pby2 = rfocy - directrix; if (!pby2) return rfocx; var lArc = arc.P; if (!lArc) return -Infinity; site = lArc.site; var lfocx = site.x, lfocy = site.y, plby2 = lfocy - directrix; if (!plby2) return lfocx; var hl = lfocx - rfocx, aby2 = 1 / pby2 - 1 / plby2, b = hl / plby2; if (aby2) return (-b + Math.sqrt(b * b - 2 * aby2 * (hl * hl / (-2 * plby2) - lfocy + plby2 / 2 + rfocy - pby2 / 2))) / aby2 + rfocx; return (rfocx + lfocx) / 2; } function d3_geom_voronoiRightBreakPoint(arc, directrix) { var rArc = arc.N; if (rArc) return d3_geom_voronoiLeftBreakPoint(rArc, directrix); var site = arc.site; return site.y === directrix ? site.x : Infinity; } function d3_geom_voronoiCell(site) { this.site = site; this.edges = []; } d3_geom_voronoiCell.prototype.prepare = function() { var halfEdges = this.edges, iHalfEdge = halfEdges.length, edge; while (iHalfEdge--) { edge = halfEdges[iHalfEdge].edge; if (!edge.b || !edge.a) halfEdges.splice(iHalfEdge, 1); } halfEdges.sort(d3_geom_voronoiHalfEdgeOrder); return halfEdges.length; }; function d3_geom_voronoiCloseCells(extent) { var x0 = extent[0][0], x1 = extent[1][0], y0 = extent[0][1], y1 = extent[1][1], x2, y2, x3, y3, cells = d3_geom_voronoiCells, iCell = cells.length, cell, iHalfEdge, halfEdges, nHalfEdges, start, end; while (iCell--) { cell = cells[iCell]; if (!cell || !cell.prepare()) continue; halfEdges = cell.edges; nHalfEdges = halfEdges.length; iHalfEdge = 0; while (iHalfEdge < nHalfEdges) { end = halfEdges[iHalfEdge].end(), x3 = end.x, y3 = end.y; start = halfEdges[++iHalfEdge % nHalfEdges].start(), x2 = start.x, y2 = start.y; if (abs(x3 - x2) > ε || abs(y3 - y2) > ε) { halfEdges.splice(iHalfEdge, 0, new d3_geom_voronoiHalfEdge(d3_geom_voronoiCreateBorderEdge(cell.site, end, abs(x3 - x0) < ε && y1 - y3 > ε ? { x: x0, y: abs(x2 - x0) < ε ? y2 : y1 } : abs(y3 - y1) < ε && x1 - x3 > ε ? { x: abs(y2 - y1) < ε ? x2 : x1, y: y1 } : abs(x3 - x1) < ε && y3 - y0 > ε ? { x: x1, y: abs(x2 - x1) < ε ? y2 : y0 } : abs(y3 - y0) < ε && x3 - x0 > ε ? { x: abs(y2 - y0) < ε ? x2 : x0, y: y0 } : null), cell.site, null)); ++nHalfEdges; } } } } function d3_geom_voronoiHalfEdgeOrder(a, b) { return b.angle - a.angle; } function d3_geom_voronoiCircle() { d3_geom_voronoiRedBlackNode(this); this.x = this.y = this.arc = this.site = this.cy = null; } function d3_geom_voronoiAttachCircle(arc) { var lArc = arc.P, rArc = arc.N; if (!lArc || !rArc) return; var lSite = lArc.site, cSite = arc.site, rSite = rArc.site; if (lSite === rSite) return; var bx = cSite.x, by = cSite.y, ax = lSite.x - bx, ay = lSite.y - by, cx = rSite.x - bx, cy = rSite.y - by; var d = 2 * (ax * cy - ay * cx); if (d >= -ε2) return; var ha = ax * ax + ay * ay, hc = cx * cx + cy * cy, x = (cy * ha - ay * hc) / d, y = (ax * hc - cx * ha) / d, cy = y + by; var circle = d3_geom_voronoiCirclePool.pop() || new d3_geom_voronoiCircle(); circle.arc = arc; circle.site = cSite; circle.x = x + bx; circle.y = cy + Math.sqrt(x * x + y * y); circle.cy = cy; arc.circle = circle; var before = null, node = d3_geom_voronoiCircles._; while (node) { if (circle.y < node.y || circle.y === node.y && circle.x <= node.x) { if (node.L) node = node.L; else { before = node.P; break; } } else { if (node.R) node = node.R; else { before = node; break; } } } d3_geom_voronoiCircles.insert(before, circle); if (!before) d3_geom_voronoiFirstCircle = circle; } function d3_geom_voronoiDetachCircle(arc) { var circle = arc.circle; if (circle) { if (!circle.P) d3_geom_voronoiFirstCircle = circle.N; d3_geom_voronoiCircles.remove(circle); d3_geom_voronoiCirclePool.push(circle); d3_geom_voronoiRedBlackNode(circle); arc.circle = null; } } function d3_geom_voronoiClipEdges(extent) { var edges = d3_geom_voronoiEdges, clip = d3_geom_clipLine(extent[0][0], extent[0][1], extent[1][0], extent[1][1]), i = edges.length, e; while (i--) { e = edges[i]; if (!d3_geom_voronoiConnectEdge(e, extent) || !clip(e) || abs(e.a.x - e.b.x) < ε && abs(e.a.y - e.b.y) < ε) { e.a = e.b = null; edges.splice(i, 1); } } } function d3_geom_voronoiConnectEdge(edge, extent) { var vb = edge.b; if (vb) return true; var va = edge.a, x0 = extent[0][0], x1 = extent[1][0], y0 = extent[0][1], y1 = extent[1][1], lSite = edge.l, rSite = edge.r, lx = lSite.x, ly = lSite.y, rx = rSite.x, ry = rSite.y, fx = (lx + rx) / 2, fy = (ly + ry) / 2, fm, fb; if (ry === ly) { if (fx < x0 || fx >= x1) return; if (lx > rx) { if (!va) va = { x: fx, y: y0 }; else if (va.y >= y1) return; vb = { x: fx, y: y1 }; } else { if (!va) va = { x: fx, y: y1 }; else if (va.y < y0) return; vb = { x: fx, y: y0 }; } } else { fm = (lx - rx) / (ry - ly); fb = fy - fm * fx; if (fm < -1 || fm > 1) { if (lx > rx) { if (!va) va = { x: (y0 - fb) / fm, y: y0 }; else if (va.y >= y1) return; vb = { x: (y1 - fb) / fm, y: y1 }; } else { if (!va) va = { x: (y1 - fb) / fm, y: y1 }; else if (va.y < y0) return; vb = { x: (y0 - fb) / fm, y: y0 }; } } else { if (ly < ry) { if (!va) va = { x: x0, y: fm * x0 + fb }; else if (va.x >= x1) return; vb = { x: x1, y: fm * x1 + fb }; } else { if (!va) va = { x: x1, y: fm * x1 + fb }; else if (va.x < x0) return; vb = { x: x0, y: fm * x0 + fb }; } } } edge.a = va; edge.b = vb; return true; } function d3_geom_voronoiEdge(lSite, rSite) { this.l = lSite; this.r = rSite; this.a = this.b = null; } function d3_geom_voronoiCreateEdge(lSite, rSite, va, vb) { var edge = new d3_geom_voronoiEdge(lSite, rSite); d3_geom_voronoiEdges.push(edge); if (va) d3_geom_voronoiSetEdgeEnd(edge, lSite, rSite, va); if (vb) d3_geom_voronoiSetEdgeEnd(edge, rSite, lSite, vb); d3_geom_voronoiCells[lSite.i].edges.push(new d3_geom_voronoiHalfEdge(edge, lSite, rSite)); d3_geom_voronoiCells[rSite.i].edges.push(new d3_geom_voronoiHalfEdge(edge, rSite, lSite)); return edge; } function d3_geom_voronoiCreateBorderEdge(lSite, va, vb) { var edge = new d3_geom_voronoiEdge(lSite, null); edge.a = va; edge.b = vb; d3_geom_voronoiEdges.push(edge); return edge; } function d3_geom_voronoiSetEdgeEnd(edge, lSite, rSite, vertex) { if (!edge.a && !edge.b) { edge.a = vertex; edge.l = lSite; edge.r = rSite; } else if (edge.l === rSite) { edge.b = vertex; } else { edge.a = vertex; } } function d3_geom_voronoiHalfEdge(edge, lSite, rSite) { var va = edge.a, vb = edge.b; this.edge = edge; this.site = lSite; this.angle = rSite ? Math.atan2(rSite.y - lSite.y, rSite.x - lSite.x) : edge.l === lSite ? Math.atan2(vb.x - va.x, va.y - vb.y) : Math.atan2(va.x - vb.x, vb.y - va.y); } d3_geom_voronoiHalfEdge.prototype = { start: function() { return this.edge.l === this.site ? this.edge.a : this.edge.b; }, end: function() { return this.edge.l === this.site ? this.edge.b : this.edge.a; } }; function d3_geom_voronoiRedBlackTree() { this._ = null; } function d3_geom_voronoiRedBlackNode(node) { node.U = node.C = node.L = node.R = node.P = node.N = null; } d3_geom_voronoiRedBlackTree.prototype = { insert: function(after, node) { var parent, grandpa, uncle; if (after) { node.P = after; node.N = after.N; if (after.N) after.N.P = node; after.N = node; if (after.R) { after = after.R; while (after.L) after = after.L; after.L = node; } else { after.R = node; } parent = after; } else if (this._) { after = d3_geom_voronoiRedBlackFirst(this._); node.P = null; node.N = after; after.P = after.L = node; parent = after; } else { node.P = node.N = null; this._ = node; parent = null; } node.L = node.R = null; node.U = parent; node.C = true; after = node; while (parent && parent.C) { grandpa = parent.U; if (parent === grandpa.L) { uncle = grandpa.R; if (uncle && uncle.C) { parent.C = uncle.C = false; grandpa.C = true; after = grandpa; } else { if (after === parent.R) { d3_geom_voronoiRedBlackRotateLeft(this, parent); after = parent; parent = after.U; } parent.C = false; grandpa.C = true; d3_geom_voronoiRedBlackRotateRight(this, grandpa); } } else { uncle = grandpa.L; if (uncle && uncle.C) { parent.C = uncle.C = false; grandpa.C = true; after = grandpa; } else { if (after === parent.L) { d3_geom_voronoiRedBlackRotateRight(this, parent); after = parent; parent = after.U; } parent.C = false; grandpa.C = true; d3_geom_voronoiRedBlackRotateLeft(this, grandpa); } } parent = after.U; } this._.C = false; }, remove: function(node) { if (node.N) node.N.P = node.P; if (node.P) node.P.N = node.N; node.N = node.P = null; var parent = node.U, sibling, left = node.L, right = node.R, next, red; if (!left) next = right; else if (!right) next = left; else next = d3_geom_voronoiRedBlackFirst(right); if (parent) { if (parent.L === node) parent.L = next; else parent.R = next; } else { this._ = next; } if (left && right) { red = next.C; next.C = node.C; next.L = left; left.U = next; if (next !== right) { parent = next.U; next.U = node.U; node = next.R; parent.L = node; next.R = right; right.U = next; } else { next.U = parent; parent = next; node = next.R; } } else { red = node.C; node = next; } if (node) node.U = parent; if (red) return; if (node && node.C) { node.C = false; return; } do { if (node === this._) break; if (node === parent.L) { sibling = parent.R; if (sibling.C) { sibling.C = false; parent.C = true; d3_geom_voronoiRedBlackRotateLeft(this, parent); sibling = parent.R; } if (sibling.L && sibling.L.C || sibling.R && sibling.R.C) { if (!sibling.R || !sibling.R.C) { sibling.L.C = false; sibling.C = true; d3_geom_voronoiRedBlackRotateRight(this, sibling); sibling = parent.R; } sibling.C = parent.C; parent.C = sibling.R.C = false; d3_geom_voronoiRedBlackRotateLeft(this, parent); node = this._; break; } } else { sibling = parent.L; if (sibling.C) { sibling.C = false; parent.C = true; d3_geom_voronoiRedBlackRotateRight(this, parent); sibling = parent.L; } if (sibling.L && sibling.L.C || sibling.R && sibling.R.C) { if (!sibling.L || !sibling.L.C) { sibling.R.C = false; sibling.C = true; d3_geom_voronoiRedBlackRotateLeft(this, sibling); sibling = parent.L; } sibling.C = parent.C; parent.C = sibling.L.C = false; d3_geom_voronoiRedBlackRotateRight(this, parent); node = this._; break; } } sibling.C = true; node = parent; parent = parent.U; } while (!node.C); if (node) node.C = false; } }; function d3_geom_voronoiRedBlackRotateLeft(tree, node) { var p = node, q = node.R, parent = p.U; if (parent) { if (parent.L === p) parent.L = q; else parent.R = q; } else { tree._ = q; } q.U = parent; p.U = q; p.R = q.L; if (p.R) p.R.U = p; q.L = p; } function d3_geom_voronoiRedBlackRotateRight(tree, node) { var p = node, q = node.L, parent = p.U; if (parent) { if (parent.L === p) parent.L = q; else parent.R = q; } else { tree._ = q; } q.U = parent; p.U = q; p.L = q.R; if (p.L) p.L.U = p; q.R = p; } function d3_geom_voronoiRedBlackFirst(node) { while (node.L) node = node.L; return node; } function d3_geom_voronoi(sites, bbox) { var site = sites.sort(d3_geom_voronoiVertexOrder).pop(), x0, y0, circle; d3_geom_voronoiEdges = []; d3_geom_voronoiCells = new Array(sites.length); d3_geom_voronoiBeaches = new d3_geom_voronoiRedBlackTree(); d3_geom_voronoiCircles = new d3_geom_voronoiRedBlackTree(); while (true) { circle = d3_geom_voronoiFirstCircle; if (site && (!circle || site.y < circle.y || site.y === circle.y && site.x < circle.x)) { if (site.x !== x0 || site.y !== y0) { d3_geom_voronoiCells[site.i] = new d3_geom_voronoiCell(site); d3_geom_voronoiAddBeach(site); x0 = site.x, y0 = site.y; } site = sites.pop(); } else if (circle) { d3_geom_voronoiRemoveBeach(circle.arc); } else { break; } } if (bbox) d3_geom_voronoiClipEdges(bbox), d3_geom_voronoiCloseCells(bbox); var diagram = { cells: d3_geom_voronoiCells, edges: d3_geom_voronoiEdges }; d3_geom_voronoiBeaches = d3_geom_voronoiCircles = d3_geom_voronoiEdges = d3_geom_voronoiCells = null; return diagram; } function d3_geom_voronoiVertexOrder(a, b) { return b.y - a.y || b.x - a.x; } d3.geom.voronoi = function(points) { var x = d3_geom_pointX, y = d3_geom_pointY, fx = x, fy = y, clipExtent = d3_geom_voronoiClipExtent; if (points) return voronoi(points); function voronoi(data) { var polygons = new Array(data.length), x0 = clipExtent[0][0], y0 = clipExtent[0][1], x1 = clipExtent[1][0], y1 = clipExtent[1][1]; d3_geom_voronoi(sites(data), clipExtent).cells.forEach(function(cell, i) { var edges = cell.edges, site = cell.site, polygon = polygons[i] = edges.length ? edges.map(function(e) { var s = e.start(); return [ s.x, s.y ]; }) : site.x >= x0 && site.x <= x1 && site.y >= y0 && site.y <= y1 ? [ [ x0, y1 ], [ x1, y1 ], [ x1, y0 ], [ x0, y0 ] ] : []; polygon.point = data[i]; }); return polygons; } function sites(data) { return data.map(function(d, i) { return { x: Math.round(fx(d, i) / ε) * ε, y: Math.round(fy(d, i) / ε) * ε, i: i }; }); } voronoi.links = function(data) { return d3_geom_voronoi(sites(data)).edges.filter(function(edge) { return edge.l && edge.r; }).map(function(edge) { return { source: data[edge.l.i], target: data[edge.r.i] }; }); }; voronoi.triangles = function(data) { var triangles = []; d3_geom_voronoi(sites(data)).cells.forEach(function(cell, i) { var site = cell.site, edges = cell.edges.sort(d3_geom_voronoiHalfEdgeOrder), j = -1, m = edges.length, e0, s0, e1 = edges[m - 1].edge, s1 = e1.l === site ? e1.r : e1.l; while (++j < m) { e0 = e1; s0 = s1; e1 = edges[j].edge; s1 = e1.l === site ? e1.r : e1.l; if (i < s0.i && i < s1.i && d3_geom_voronoiTriangleArea(site, s0, s1) < 0) { triangles.push([ data[i], data[s0.i], data[s1.i] ]); } } }); return triangles; }; voronoi.x = function(_) { return arguments.length ? (fx = d3_functor(x = _), voronoi) : x; }; voronoi.y = function(_) { return arguments.length ? (fy = d3_functor(y = _), voronoi) : y; }; voronoi.clipExtent = function(_) { if (!arguments.length) return clipExtent === d3_geom_voronoiClipExtent ? null : clipExtent; clipExtent = _ == null ? d3_geom_voronoiClipExtent : _; return voronoi; }; voronoi.size = function(_) { if (!arguments.length) return clipExtent === d3_geom_voronoiClipExtent ? null : clipExtent && clipExtent[1]; return voronoi.clipExtent(_ && [ [ 0, 0 ], _ ]); }; return voronoi; }; var d3_geom_voronoiClipExtent = [ [ -1e6, -1e6 ], [ 1e6, 1e6 ] ]; function d3_geom_voronoiTriangleArea(a, b, c) { return (a.x - c.x) * (b.y - a.y) - (a.x - b.x) * (c.y - a.y); } d3.geom.delaunay = function(vertices) { return d3.geom.voronoi().triangles(vertices); }; d3.geom.quadtree = function(points, x1, y1, x2, y2) { var x = d3_geom_pointX, y = d3_geom_pointY, compat; if (compat = arguments.length) { x = d3_geom_quadtreeCompatX; y = d3_geom_quadtreeCompatY; if (compat === 3) { y2 = y1; x2 = x1; y1 = x1 = 0; } return quadtree(points); } function quadtree(data) { var d, fx = d3_functor(x), fy = d3_functor(y), xs, ys, i, n, x1_, y1_, x2_, y2_; if (x1 != null) { x1_ = x1, y1_ = y1, x2_ = x2, y2_ = y2; } else { x2_ = y2_ = -(x1_ = y1_ = Infinity); xs = [], ys = []; n = data.length; if (compat) for (i = 0; i < n; ++i) { d = data[i]; if (d.x < x1_) x1_ = d.x; if (d.y < y1_) y1_ = d.y; if (d.x > x2_) x2_ = d.x; if (d.y > y2_) y2_ = d.y; xs.push(d.x); ys.push(d.y); } else for (i = 0; i < n; ++i) { var x_ = +fx(d = data[i], i), y_ = +fy(d, i); if (x_ < x1_) x1_ = x_; if (y_ < y1_) y1_ = y_; if (x_ > x2_) x2_ = x_; if (y_ > y2_) y2_ = y_; xs.push(x_); ys.push(y_); } } var dx = x2_ - x1_, dy = y2_ - y1_; if (dx > dy) y2_ = y1_ + dx; else x2_ = x1_ + dy; function insert(n, d, x, y, x1, y1, x2, y2) { if (isNaN(x) || isNaN(y)) return; if (n.leaf) { var nx = n.x, ny = n.y; if (nx != null) { if (abs(nx - x) + abs(ny - y) < .01) { insertChild(n, d, x, y, x1, y1, x2, y2); } else { var nPoint = n.point; n.x = n.y = n.point = null; insertChild(n, nPoint, nx, ny, x1, y1, x2, y2); insertChild(n, d, x, y, x1, y1, x2, y2); } } else { n.x = x, n.y = y, n.point = d; } } else { insertChild(n, d, x, y, x1, y1, x2, y2); } } function insertChild(n, d, x, y, x1, y1, x2, y2) { var xm = (x1 + x2) * .5, ym = (y1 + y2) * .5, right = x >= xm, below = y >= ym, i = below << 1 | right; n.leaf = false; n = n.nodes[i] || (n.nodes[i] = d3_geom_quadtreeNode()); if (right) x1 = xm; else x2 = xm; if (below) y1 = ym; else y2 = ym; insert(n, d, x, y, x1, y1, x2, y2); } var root = d3_geom_quadtreeNode(); root.add = function(d) { insert(root, d, +fx(d, ++i), +fy(d, i), x1_, y1_, x2_, y2_); }; root.visit = function(f) { d3_geom_quadtreeVisit(f, root, x1_, y1_, x2_, y2_); }; root.find = function(point) { return d3_geom_quadtreeFind(root, point[0], point[1], x1_, y1_, x2_, y2_); }; i = -1; if (x1 == null) { while (++i < n) { insert(root, data[i], xs[i], ys[i], x1_, y1_, x2_, y2_); } --i; } else data.forEach(root.add); xs = ys = data = d = null; return root; } quadtree.x = function(_) { return arguments.length ? (x = _, quadtree) : x; }; quadtree.y = function(_) { return arguments.length ? (y = _, quadtree) : y; }; quadtree.extent = function(_) { if (!arguments.length) return x1 == null ? null : [ [ x1, y1 ], [ x2, y2 ] ]; if (_ == null) x1 = y1 = x2 = y2 = null; else x1 = +_[0][0], y1 = +_[0][1], x2 = +_[1][0], y2 = +_[1][1]; return quadtree; }; quadtree.size = function(_) { if (!arguments.length) return x1 == null ? null : [ x2 - x1, y2 - y1 ]; if (_ == null) x1 = y1 = x2 = y2 = null; else x1 = y1 = 0, x2 = +_[0], y2 = +_[1]; return quadtree; }; return quadtree; }; function d3_geom_quadtreeCompatX(d) { return d.x; } function d3_geom_quadtreeCompatY(d) { return d.y; } function d3_geom_quadtreeNode() { return { leaf: true, nodes: [], point: null, x: null, y: null }; } function d3_geom_quadtreeVisit(f, node, x1, y1, x2, y2) { if (!f(node, x1, y1, x2, y2)) { var sx = (x1 + x2) * .5, sy = (y1 + y2) * .5, children = node.nodes; if (children[0]) d3_geom_quadtreeVisit(f, children[0], x1, y1, sx, sy); if (children[1]) d3_geom_quadtreeVisit(f, children[1], sx, y1, x2, sy); if (children[2]) d3_geom_quadtreeVisit(f, children[2], x1, sy, sx, y2); if (children[3]) d3_geom_quadtreeVisit(f, children[3], sx, sy, x2, y2); } } function d3_geom_quadtreeFind(root, x, y, x0, y0, x3, y3) { var minDistance2 = Infinity, closestPoint; (function find(node, x1, y1, x2, y2) { if (x1 > x3 || y1 > y3 || x2 < x0 || y2 < y0) return; if (point = node.point) { var point, dx = x - node.x, dy = y - node.y, distance2 = dx * dx + dy * dy; if (distance2 < minDistance2) { var distance = Math.sqrt(minDistance2 = distance2); x0 = x - distance, y0 = y - distance; x3 = x + distance, y3 = y + distance; closestPoint = point; } } var children = node.nodes, xm = (x1 + x2) * .5, ym = (y1 + y2) * .5, right = x >= xm, below = y >= ym; for (var i = below << 1 | right, j = i + 4; i < j; ++i) { if (node = children[i & 3]) switch (i & 3) { case 0: find(node, x1, y1, xm, ym); break; case 1: find(node, xm, y1, x2, ym); break; case 2: find(node, x1, ym, xm, y2); break; case 3: find(node, xm, ym, x2, y2); break; } } })(root, x0, y0, x3, y3); return closestPoint; } d3.interpolateRgb = d3_interpolateRgb; function d3_interpolateRgb(a, b) { a = d3.rgb(a); b = d3.rgb(b); var ar = a.r, ag = a.g, ab = a.b, br = b.r - ar, bg = b.g - ag, bb = b.b - ab; return function(t) { return "#" + d3_rgb_hex(Math.round(ar + br * t)) + d3_rgb_hex(Math.round(ag + bg * t)) + d3_rgb_hex(Math.round(ab + bb * t)); }; } d3.interpolateObject = d3_interpolateObject; function d3_interpolateObject(a, b) { var i = {}, c = {}, k; for (k in a) { if (k in b) { i[k] = d3_interpolate(a[k], b[k]); } else { c[k] = a[k]; } } for (k in b) { if (!(k in a)) { c[k] = b[k]; } } return function(t) { for (k in i) c[k] = i[k](t); return c; }; } d3.interpolateNumber = d3_interpolateNumber; function d3_interpolateNumber(a, b) { a = +a, b = +b; return function(t) { return a * (1 - t) + b * t; }; } d3.interpolateString = d3_interpolateString; function d3_interpolateString(a, b) { var bi = d3_interpolate_numberA.lastIndex = d3_interpolate_numberB.lastIndex = 0, am, bm, bs, i = -1, s = [], q = []; a = a + "", b = b + ""; while ((am = d3_interpolate_numberA.exec(a)) && (bm = d3_interpolate_numberB.exec(b))) { if ((bs = bm.index) > bi) { bs = b.slice(bi, bs); if (s[i]) s[i] += bs; else s[++i] = bs; } if ((am = am[0]) === (bm = bm[0])) { if (s[i]) s[i] += bm; else s[++i] = bm; } else { s[++i] = null; q.push({ i: i, x: d3_interpolateNumber(am, bm) }); } bi = d3_interpolate_numberB.lastIndex; } if (bi < b.length) { bs = b.slice(bi); if (s[i]) s[i] += bs; else s[++i] = bs; } return s.length < 2 ? q[0] ? (b = q[0].x, function(t) { return b(t) + ""; }) : function() { return b; } : (b = q.length, function(t) { for (var i = 0, o; i < b; ++i) s[(o = q[i]).i] = o.x(t); return s.join(""); }); } var d3_interpolate_numberA = /[-+]?(?:\d+\.?\d*|\.?\d+)(?:[eE][-+]?\d+)?/g, d3_interpolate_numberB = new RegExp(d3_interpolate_numberA.source, "g"); d3.interpolate = d3_interpolate; function d3_interpolate(a, b) { var i = d3.interpolators.length, f; while (--i >= 0 && !(f = d3.interpolators[i](a, b))) ; return f; } d3.interpolators = [ function(a, b) { var t = typeof b; return (t === "string" ? d3_rgb_names.has(b.toLowerCase()) || /^(#|rgb\(|hsl\()/i.test(b) ? d3_interpolateRgb : d3_interpolateString : b instanceof d3_color ? d3_interpolateRgb : Array.isArray(b) ? d3_interpolateArray : t === "object" && isNaN(b) ? d3_interpolateObject : d3_interpolateNumber)(a, b); } ]; d3.interpolateArray = d3_interpolateArray; function d3_interpolateArray(a, b) { var x = [], c = [], na = a.length, nb = b.length, n0 = Math.min(a.length, b.length), i; for (i = 0; i < n0; ++i) x.push(d3_interpolate(a[i], b[i])); for (;i < na; ++i) c[i] = a[i]; for (;i < nb; ++i) c[i] = b[i]; return function(t) { for (i = 0; i < n0; ++i) c[i] = x[i](t); return c; }; } var d3_ease_default = function() { return d3_identity; }; var d3_ease = d3.map({ linear: d3_ease_default, poly: d3_ease_poly, quad: function() { return d3_ease_quad; }, cubic: function() { return d3_ease_cubic; }, sin: function() { return d3_ease_sin; }, exp: function() { return d3_ease_exp; }, circle: function() { return d3_ease_circle; }, elastic: d3_ease_elastic, back: d3_ease_back, bounce: function() { return d3_ease_bounce; } }); var d3_ease_mode = d3.map({ "in": d3_identity, out: d3_ease_reverse, "in-out": d3_ease_reflect, "out-in": function(f) { return d3_ease_reflect(d3_ease_reverse(f)); } }); d3.ease = function(name) { var i = name.indexOf("-"), t = i >= 0 ? name.slice(0, i) : name, m = i >= 0 ? name.slice(i + 1) : "in"; t = d3_ease.get(t) || d3_ease_default; m = d3_ease_mode.get(m) || d3_identity; return d3_ease_clamp(m(t.apply(null, d3_arraySlice.call(arguments, 1)))); }; function d3_ease_clamp(f) { return function(t) { return t <= 0 ? 0 : t >= 1 ? 1 : f(t); }; } function d3_ease_reverse(f) { return function(t) { return 1 - f(1 - t); }; } function d3_ease_reflect(f) { return function(t) { return .5 * (t < .5 ? f(2 * t) : 2 - f(2 - 2 * t)); }; } function d3_ease_quad(t) { return t * t; } function d3_ease_cubic(t) { return t * t * t; } function d3_ease_cubicInOut(t) { if (t <= 0) return 0; if (t >= 1) return 1; var t2 = t * t, t3 = t2 * t; return 4 * (t < .5 ? t3 : 3 * (t - t2) + t3 - .75); } function d3_ease_poly(e) { return function(t) { return Math.pow(t, e); }; } function d3_ease_sin(t) { return 1 - Math.cos(t * halfÏ€); } function d3_ease_exp(t) { return Math.pow(2, 10 * (t - 1)); } function d3_ease_circle(t) { return 1 - Math.sqrt(1 - t * t); } function d3_ease_elastic(a, p) { var s; if (arguments.length < 2) p = .45; if (arguments.length) s = p / Ï„ * Math.asin(1 / a); else a = 1, s = p / 4; return function(t) { return 1 + a * Math.pow(2, -10 * t) * Math.sin((t - s) * Ï„ / p); }; } function d3_ease_back(s) { if (!s) s = 1.70158; return function(t) { return t * t * ((s + 1) * t - s); }; } function d3_ease_bounce(t) { return t < 1 / 2.75 ? 7.5625 * t * t : t < 2 / 2.75 ? 7.5625 * (t -= 1.5 / 2.75) * t + .75 : t < 2.5 / 2.75 ? 7.5625 * (t -= 2.25 / 2.75) * t + .9375 : 7.5625 * (t -= 2.625 / 2.75) * t + .984375; } d3.interpolateHcl = d3_interpolateHcl; function d3_interpolateHcl(a, b) { a = d3.hcl(a); b = d3.hcl(b); var ah = a.h, ac = a.c, al = a.l, bh = b.h - ah, bc = b.c - ac, bl = b.l - al; if (isNaN(bc)) bc = 0, ac = isNaN(ac) ? b.c : ac; if (isNaN(bh)) bh = 0, ah = isNaN(ah) ? b.h : ah; else if (bh > 180) bh -= 360; else if (bh < -180) bh += 360; return function(t) { return d3_hcl_lab(ah + bh * t, ac + bc * t, al + bl * t) + ""; }; } d3.interpolateHsl = d3_interpolateHsl; function d3_interpolateHsl(a, b) { a = d3.hsl(a); b = d3.hsl(b); var ah = a.h, as = a.s, al = a.l, bh = b.h - ah, bs = b.s - as, bl = b.l - al; if (isNaN(bs)) bs = 0, as = isNaN(as) ? b.s : as; if (isNaN(bh)) bh = 0, ah = isNaN(ah) ? b.h : ah; else if (bh > 180) bh -= 360; else if (bh < -180) bh += 360; return function(t) { return d3_hsl_rgb(ah + bh * t, as + bs * t, al + bl * t) + ""; }; } d3.interpolateLab = d3_interpolateLab; function d3_interpolateLab(a, b) { a = d3.lab(a); b = d3.lab(b); var al = a.l, aa = a.a, ab = a.b, bl = b.l - al, ba = b.a - aa, bb = b.b - ab; return function(t) { return d3_lab_rgb(al + bl * t, aa + ba * t, ab + bb * t) + ""; }; } d3.interpolateRound = d3_interpolateRound; function d3_interpolateRound(a, b) { b -= a; return function(t) { return Math.round(a + b * t); }; } d3.transform = function(string) { var g = d3_document.createElementNS(d3.ns.prefix.svg, "g"); return (d3.transform = function(string) { if (string != null) { g.setAttribute("transform", string); var t = g.transform.baseVal.consolidate(); } return new d3_transform(t ? t.matrix : d3_transformIdentity); })(string); }; function d3_transform(m) { var r0 = [ m.a, m.b ], r1 = [ m.c, m.d ], kx = d3_transformNormalize(r0), kz = d3_transformDot(r0, r1), ky = d3_transformNormalize(d3_transformCombine(r1, r0, -kz)) || 0; if (r0[0] * r1[1] < r1[0] * r0[1]) { r0[0] *= -1; r0[1] *= -1; kx *= -1; kz *= -1; } this.rotate = (kx ? Math.atan2(r0[1], r0[0]) : Math.atan2(-r1[0], r1[1])) * d3_degrees; this.translate = [ m.e, m.f ]; this.scale = [ kx, ky ]; this.skew = ky ? Math.atan2(kz, ky) * d3_degrees : 0; } d3_transform.prototype.toString = function() { return "translate(" + this.translate + ")rotate(" + this.rotate + ")skewX(" + this.skew + ")scale(" + this.scale + ")"; }; function d3_transformDot(a, b) { return a[0] * b[0] + a[1] * b[1]; } function d3_transformNormalize(a) { var k = Math.sqrt(d3_transformDot(a, a)); if (k) { a[0] /= k; a[1] /= k; } return k; } function d3_transformCombine(a, b, k) { a[0] += k * b[0]; a[1] += k * b[1]; return a; } var d3_transformIdentity = { a: 1, b: 0, c: 0, d: 1, e: 0, f: 0 }; d3.interpolateTransform = d3_interpolateTransform; function d3_interpolateTransformPop(s) { return s.length ? s.pop() + "," : ""; } function d3_interpolateTranslate(ta, tb, s, q) { if (ta[0] !== tb[0] || ta[1] !== tb[1]) { var i = s.push("translate(", null, ",", null, ")"); q.push({ i: i - 4, x: d3_interpolateNumber(ta[0], tb[0]) }, { i: i - 2, x: d3_interpolateNumber(ta[1], tb[1]) }); } else if (tb[0] || tb[1]) { s.push("translate(" + tb + ")"); } } function d3_interpolateRotate(ra, rb, s, q) { if (ra !== rb) { if (ra - rb > 180) rb += 360; else if (rb - ra > 180) ra += 360; q.push({ i: s.push(d3_interpolateTransformPop(s) + "rotate(", null, ")") - 2, x: d3_interpolateNumber(ra, rb) }); } else if (rb) { s.push(d3_interpolateTransformPop(s) + "rotate(" + rb + ")"); } } function d3_interpolateSkew(wa, wb, s, q) { if (wa !== wb) { q.push({ i: s.push(d3_interpolateTransformPop(s) + "skewX(", null, ")") - 2, x: d3_interpolateNumber(wa, wb) }); } else if (wb) { s.push(d3_interpolateTransformPop(s) + "skewX(" + wb + ")"); } } function d3_interpolateScale(ka, kb, s, q) { if (ka[0] !== kb[0] || ka[1] !== kb[1]) { var i = s.push(d3_interpolateTransformPop(s) + "scale(", null, ",", null, ")"); q.push({ i: i - 4, x: d3_interpolateNumber(ka[0], kb[0]) }, { i: i - 2, x: d3_interpolateNumber(ka[1], kb[1]) }); } else if (kb[0] !== 1 || kb[1] !== 1) { s.push(d3_interpolateTransformPop(s) + "scale(" + kb + ")"); } } function d3_interpolateTransform(a, b) { var s = [], q = []; a = d3.transform(a), b = d3.transform(b); d3_interpolateTranslate(a.translate, b.translate, s, q); d3_interpolateRotate(a.rotate, b.rotate, s, q); d3_interpolateSkew(a.skew, b.skew, s, q); d3_interpolateScale(a.scale, b.scale, s, q); a = b = null; return function(t) { var i = -1, n = q.length, o; while (++i < n) s[(o = q[i]).i] = o.x(t); return s.join(""); }; } function d3_uninterpolateNumber(a, b) { b = (b -= a = +a) || 1 / b; return function(x) { return (x - a) / b; }; } function d3_uninterpolateClamp(a, b) { b = (b -= a = +a) || 1 / b; return function(x) { return Math.max(0, Math.min(1, (x - a) / b)); }; } d3.layout = {}; d3.layout.bundle = function() { return function(links) { var paths = [], i = -1, n = links.length; while (++i < n) paths.push(d3_layout_bundlePath(links[i])); return paths; }; }; function d3_layout_bundlePath(link) { var start = link.source, end = link.target, lca = d3_layout_bundleLeastCommonAncestor(start, end), points = [ start ]; while (start !== lca) { start = start.parent; points.push(start); } var k = points.length; while (end !== lca) { points.splice(k, 0, end); end = end.parent; } return points; } function d3_layout_bundleAncestors(node) { var ancestors = [], parent = node.parent; while (parent != null) { ancestors.push(node); node = parent; parent = parent.parent; } ancestors.push(node); return ancestors; } function d3_layout_bundleLeastCommonAncestor(a, b) { if (a === b) return a; var aNodes = d3_layout_bundleAncestors(a), bNodes = d3_layout_bundleAncestors(b), aNode = aNodes.pop(), bNode = bNodes.pop(), sharedNode = null; while (aNode === bNode) { sharedNode = aNode; aNode = aNodes.pop(); bNode = bNodes.pop(); } return sharedNode; } d3.layout.chord = function() { var chord = {}, chords, groups, matrix, n, padding = 0, sortGroups, sortSubgroups, sortChords; function relayout() { var subgroups = {}, groupSums = [], groupIndex = d3.range(n), subgroupIndex = [], k, x, x0, i, j; chords = []; groups = []; k = 0, i = -1; while (++i < n) { x = 0, j = -1; while (++j < n) { x += matrix[i][j]; } groupSums.push(x); subgroupIndex.push(d3.range(n)); k += x; } if (sortGroups) { groupIndex.sort(function(a, b) { return sortGroups(groupSums[a], groupSums[b]); }); } if (sortSubgroups) { subgroupIndex.forEach(function(d, i) { d.sort(function(a, b) { return sortSubgroups(matrix[i][a], matrix[i][b]); }); }); } k = (Ï„ - padding * n) / k; x = 0, i = -1; while (++i < n) { x0 = x, j = -1; while (++j < n) { var di = groupIndex[i], dj = subgroupIndex[di][j], v = matrix[di][dj], a0 = x, a1 = x += v * k; subgroups[di + "-" + dj] = { index: di, subindex: dj, startAngle: a0, endAngle: a1, value: v }; } groups[di] = { index: di, startAngle: x0, endAngle: x, value: groupSums[di] }; x += padding; } i = -1; while (++i < n) { j = i - 1; while (++j < n) { var source = subgroups[i + "-" + j], target = subgroups[j + "-" + i]; if (source.value || target.value) { chords.push(source.value < target.value ? { source: target, target: source } : { source: source, target: target }); } } } if (sortChords) resort(); } function resort() { chords.sort(function(a, b) { return sortChords((a.source.value + a.target.value) / 2, (b.source.value + b.target.value) / 2); }); } chord.matrix = function(x) { if (!arguments.length) return matrix; n = (matrix = x) && matrix.length; chords = groups = null; return chord; }; chord.padding = function(x) { if (!arguments.length) return padding; padding = x; chords = groups = null; return chord; }; chord.sortGroups = function(x) { if (!arguments.length) return sortGroups; sortGroups = x; chords = groups = null; return chord; }; chord.sortSubgroups = function(x) { if (!arguments.length) return sortSubgroups; sortSubgroups = x; chords = null; return chord; }; chord.sortChords = function(x) { if (!arguments.length) return sortChords; sortChords = x; if (chords) resort(); return chord; }; chord.chords = function() { if (!chords) relayout(); return chords; }; chord.groups = function() { if (!groups) relayout(); return groups; }; return chord; }; d3.layout.force = function() { var force = {}, event = d3.dispatch("start", "tick", "end"), timer, size = [ 1, 1 ], drag, alpha, friction = .9, linkDistance = d3_layout_forceLinkDistance, linkStrength = d3_layout_forceLinkStrength, charge = -30, chargeDistance2 = d3_layout_forceChargeDistance2, gravity = .1, theta2 = .64, nodes = [], links = [], distances, strengths, charges; function repulse(node) { return function(quad, x1, _, x2) { if (quad.point !== node) { var dx = quad.cx - node.x, dy = quad.cy - node.y, dw = x2 - x1, dn = dx * dx + dy * dy; if (dw * dw / theta2 < dn) { if (dn < chargeDistance2) { var k = quad.charge / dn; node.px -= dx * k; node.py -= dy * k; } return true; } if (quad.point && dn && dn < chargeDistance2) { var k = quad.pointCharge / dn; node.px -= dx * k; node.py -= dy * k; } } return !quad.charge; }; } force.tick = function() { if ((alpha *= .99) < .005) { timer = null; event.end({ type: "end", alpha: alpha = 0 }); return true; } var n = nodes.length, m = links.length, q, i, o, s, t, l, k, x, y; for (i = 0; i < m; ++i) { o = links[i]; s = o.source; t = o.target; x = t.x - s.x; y = t.y - s.y; if (l = x * x + y * y) { l = alpha * strengths[i] * ((l = Math.sqrt(l)) - distances[i]) / l; x *= l; y *= l; t.x -= x * (k = s.weight + t.weight ? s.weight / (s.weight + t.weight) : .5); t.y -= y * k; s.x += x * (k = 1 - k); s.y += y * k; } } if (k = alpha * gravity) { x = size[0] / 2; y = size[1] / 2; i = -1; if (k) while (++i < n) { o = nodes[i]; o.x += (x - o.x) * k; o.y += (y - o.y) * k; } } if (charge) { d3_layout_forceAccumulate(q = d3.geom.quadtree(nodes), alpha, charges); i = -1; while (++i < n) { if (!(o = nodes[i]).fixed) { q.visit(repulse(o)); } } } i = -1; while (++i < n) { o = nodes[i]; if (o.fixed) { o.x = o.px; o.y = o.py; } else { o.x -= (o.px - (o.px = o.x)) * friction; o.y -= (o.py - (o.py = o.y)) * friction; } } event.tick({ type: "tick", alpha: alpha }); }; force.nodes = function(x) { if (!arguments.length) return nodes; nodes = x; return force; }; force.links = function(x) { if (!arguments.length) return links; links = x; return force; }; force.size = function(x) { if (!arguments.length) return size; size = x; return force; }; force.linkDistance = function(x) { if (!arguments.length) return linkDistance; linkDistance = typeof x === "function" ? x : +x; return force; }; force.distance = force.linkDistance; force.linkStrength = function(x) { if (!arguments.length) return linkStrength; linkStrength = typeof x === "function" ? x : +x; return force; }; force.friction = function(x) { if (!arguments.length) return friction; friction = +x; return force; }; force.charge = function(x) { if (!arguments.length) return charge; charge = typeof x === "function" ? x : +x; return force; }; force.chargeDistance = function(x) { if (!arguments.length) return Math.sqrt(chargeDistance2); chargeDistance2 = x * x; return force; }; force.gravity = function(x) { if (!arguments.length) return gravity; gravity = +x; return force; }; force.theta = function(x) { if (!arguments.length) return Math.sqrt(theta2); theta2 = x * x; return force; }; force.alpha = function(x) { if (!arguments.length) return alpha; x = +x; if (alpha) { if (x > 0) { alpha = x; } else { timer.c = null, timer.t = NaN, timer = null; event.end({ type: "end", alpha: alpha = 0 }); } } else if (x > 0) { event.start({ type: "start", alpha: alpha = x }); timer = d3_timer(force.tick); } return force; }; force.start = function() { var i, n = nodes.length, m = links.length, w = size[0], h = size[1], neighbors, o; for (i = 0; i < n; ++i) { (o = nodes[i]).index = i; o.weight = 0; } for (i = 0; i < m; ++i) { o = links[i]; if (typeof o.source == "number") o.source = nodes[o.source]; if (typeof o.target == "number") o.target = nodes[o.target]; ++o.source.weight; ++o.target.weight; } for (i = 0; i < n; ++i) { o = nodes[i]; if (isNaN(o.x)) o.x = position("x", w); if (isNaN(o.y)) o.y = position("y", h); if (isNaN(o.px)) o.px = o.x; if (isNaN(o.py)) o.py = o.y; } distances = []; if (typeof linkDistance === "function") for (i = 0; i < m; ++i) distances[i] = +linkDistance.call(this, links[i], i); else for (i = 0; i < m; ++i) distances[i] = linkDistance; strengths = []; if (typeof linkStrength === "function") for (i = 0; i < m; ++i) strengths[i] = +linkStrength.call(this, links[i], i); else for (i = 0; i < m; ++i) strengths[i] = linkStrength; charges = []; if (typeof charge === "function") for (i = 0; i < n; ++i) charges[i] = +charge.call(this, nodes[i], i); else for (i = 0; i < n; ++i) charges[i] = charge; function position(dimension, size) { if (!neighbors) { neighbors = new Array(n); for (j = 0; j < n; ++j) { neighbors[j] = []; } for (j = 0; j < m; ++j) { var o = links[j]; neighbors[o.source.index].push(o.target); neighbors[o.target.index].push(o.source); } } var candidates = neighbors[i], j = -1, l = candidates.length, x; while (++j < l) if (!isNaN(x = candidates[j][dimension])) return x; return Math.random() * size; } return force.resume(); }; force.resume = function() { return force.alpha(.1); }; force.stop = function() { return force.alpha(0); }; force.drag = function() { if (!drag) drag = d3.behavior.drag().origin(d3_identity).on("dragstart.force", d3_layout_forceDragstart).on("drag.force", dragmove).on("dragend.force", d3_layout_forceDragend); if (!arguments.length) return drag; this.on("mouseover.force", d3_layout_forceMouseover).on("mouseout.force", d3_layout_forceMouseout).call(drag); }; function dragmove(d) { d.px = d3.event.x, d.py = d3.event.y; force.resume(); } return d3.rebind(force, event, "on"); }; function d3_layout_forceDragstart(d) { d.fixed |= 2; } function d3_layout_forceDragend(d) { d.fixed &= ~6; } function d3_layout_forceMouseover(d) { d.fixed |= 4; d.px = d.x, d.py = d.y; } function d3_layout_forceMouseout(d) { d.fixed &= ~4; } function d3_layout_forceAccumulate(quad, alpha, charges) { var cx = 0, cy = 0; quad.charge = 0; if (!quad.leaf) { var nodes = quad.nodes, n = nodes.length, i = -1, c; while (++i < n) { c = nodes[i]; if (c == null) continue; d3_layout_forceAccumulate(c, alpha, charges); quad.charge += c.charge; cx += c.charge * c.cx; cy += c.charge * c.cy; } } if (quad.point) { if (!quad.leaf) { quad.point.x += Math.random() - .5; quad.point.y += Math.random() - .5; } var k = alpha * charges[quad.point.index]; quad.charge += quad.pointCharge = k; cx += k * quad.point.x; cy += k * quad.point.y; } quad.cx = cx / quad.charge; quad.cy = cy / quad.charge; } var d3_layout_forceLinkDistance = 20, d3_layout_forceLinkStrength = 1, d3_layout_forceChargeDistance2 = Infinity; d3.layout.hierarchy = function() { var sort = d3_layout_hierarchySort, children = d3_layout_hierarchyChildren, value = d3_layout_hierarchyValue; function hierarchy(root) { var stack = [ root ], nodes = [], node; root.depth = 0; while ((node = stack.pop()) != null) { nodes.push(node); if ((childs = children.call(hierarchy, node, node.depth)) && (n = childs.length)) { var n, childs, child; while (--n >= 0) { stack.push(child = childs[n]); child.parent = node; child.depth = node.depth + 1; } if (value) node.value = 0; node.children = childs; } else { if (value) node.value = +value.call(hierarchy, node, node.depth) || 0; delete node.children; } } d3_layout_hierarchyVisitAfter(root, function(node) { var childs, parent; if (sort && (childs = node.children)) childs.sort(sort); if (value && (parent = node.parent)) parent.value += node.value; }); return nodes; } hierarchy.sort = function(x) { if (!arguments.length) return sort; sort = x; return hierarchy; }; hierarchy.children = function(x) { if (!arguments.length) return children; children = x; return hierarchy; }; hierarchy.value = function(x) { if (!arguments.length) return value; value = x; return hierarchy; }; hierarchy.revalue = function(root) { if (value) { d3_layout_hierarchyVisitBefore(root, function(node) { if (node.children) node.value = 0; }); d3_layout_hierarchyVisitAfter(root, function(node) { var parent; if (!node.children) node.value = +value.call(hierarchy, node, node.depth) || 0; if (parent = node.parent) parent.value += node.value; }); } return root; }; return hierarchy; }; function d3_layout_hierarchyRebind(object, hierarchy) { d3.rebind(object, hierarchy, "sort", "children", "value"); object.nodes = object; object.links = d3_layout_hierarchyLinks; return object; } function d3_layout_hierarchyVisitBefore(node, callback) { var nodes = [ node ]; while ((node = nodes.pop()) != null) { callback(node); if ((children = node.children) && (n = children.length)) { var n, children; while (--n >= 0) nodes.push(children[n]); } } } function d3_layout_hierarchyVisitAfter(node, callback) { var nodes = [ node ], nodes2 = []; while ((node = nodes.pop()) != null) { nodes2.push(node); if ((children = node.children) && (n = children.length)) { var i = -1, n, children; while (++i < n) nodes.push(children[i]); } } while ((node = nodes2.pop()) != null) { callback(node); } } function d3_layout_hierarchyChildren(d) { return d.children; } function d3_layout_hierarchyValue(d) { return d.value; } function d3_layout_hierarchySort(a, b) { return b.value - a.value; } function d3_layout_hierarchyLinks(nodes) { return d3.merge(nodes.map(function(parent) { return (parent.children || []).map(function(child) { return { source: parent, target: child }; }); })); } d3.layout.partition = function() { var hierarchy = d3.layout.hierarchy(), size = [ 1, 1 ]; function position(node, x, dx, dy) { var children = node.children; node.x = x; node.y = node.depth * dy; node.dx = dx; node.dy = dy; if (children && (n = children.length)) { var i = -1, n, c, d; dx = node.value ? dx / node.value : 0; while (++i < n) { position(c = children[i], x, d = c.value * dx, dy); x += d; } } } function depth(node) { var children = node.children, d = 0; if (children && (n = children.length)) { var i = -1, n; while (++i < n) d = Math.max(d, depth(children[i])); } return 1 + d; } function partition(d, i) { var nodes = hierarchy.call(this, d, i); position(nodes[0], 0, size[0], size[1] / depth(nodes[0])); return nodes; } partition.size = function(x) { if (!arguments.length) return size; size = x; return partition; }; return d3_layout_hierarchyRebind(partition, hierarchy); }; d3.layout.pie = function() { var value = Number, sort = d3_layout_pieSortByValue, startAngle = 0, endAngle = Ï„, padAngle = 0; function pie(data) { var n = data.length, values = data.map(function(d, i) { return +value.call(pie, d, i); }), a = +(typeof startAngle === "function" ? startAngle.apply(this, arguments) : startAngle), da = (typeof endAngle === "function" ? endAngle.apply(this, arguments) : endAngle) - a, p = Math.min(Math.abs(da) / n, +(typeof padAngle === "function" ? padAngle.apply(this, arguments) : padAngle)), pa = p * (da < 0 ? -1 : 1), sum = d3.sum(values), k = sum ? (da - n * pa) / sum : 0, index = d3.range(n), arcs = [], v; if (sort != null) index.sort(sort === d3_layout_pieSortByValue ? function(i, j) { return values[j] - values[i]; } : function(i, j) { return sort(data[i], data[j]); }); index.forEach(function(i) { arcs[i] = { data: data[i], value: v = values[i], startAngle: a, endAngle: a += v * k + pa, padAngle: p }; }); return arcs; } pie.value = function(_) { if (!arguments.length) return value; value = _; return pie; }; pie.sort = function(_) { if (!arguments.length) return sort; sort = _; return pie; }; pie.startAngle = function(_) { if (!arguments.length) return startAngle; startAngle = _; return pie; }; pie.endAngle = function(_) { if (!arguments.length) return endAngle; endAngle = _; return pie; }; pie.padAngle = function(_) { if (!arguments.length) return padAngle; padAngle = _; return pie; }; return pie; }; var d3_layout_pieSortByValue = {}; d3.layout.stack = function() { var values = d3_identity, order = d3_layout_stackOrderDefault, offset = d3_layout_stackOffsetZero, out = d3_layout_stackOut, x = d3_layout_stackX, y = d3_layout_stackY; function stack(data, index) { if (!(n = data.length)) return data; var series = data.map(function(d, i) { return values.call(stack, d, i); }); var points = series.map(function(d) { return d.map(function(v, i) { return [ x.call(stack, v, i), y.call(stack, v, i) ]; }); }); var orders = order.call(stack, points, index); series = d3.permute(series, orders); points = d3.permute(points, orders); var offsets = offset.call(stack, points, index); var m = series[0].length, n, i, j, o; for (j = 0; j < m; ++j) { out.call(stack, series[0][j], o = offsets[j], points[0][j][1]); for (i = 1; i < n; ++i) { out.call(stack, series[i][j], o += points[i - 1][j][1], points[i][j][1]); } } return data; } stack.values = function(x) { if (!arguments.length) return values; values = x; return stack; }; stack.order = function(x) { if (!arguments.length) return order; order = typeof x === "function" ? x : d3_layout_stackOrders.get(x) || d3_layout_stackOrderDefault; return stack; }; stack.offset = function(x) { if (!arguments.length) return offset; offset = typeof x === "function" ? x : d3_layout_stackOffsets.get(x) || d3_layout_stackOffsetZero; return stack; }; stack.x = function(z) { if (!arguments.length) return x; x = z; return stack; }; stack.y = function(z) { if (!arguments.length) return y; y = z; return stack; }; stack.out = function(z) { if (!arguments.length) return out; out = z; return stack; }; return stack; }; function d3_layout_stackX(d) { return d.x; } function d3_layout_stackY(d) { return d.y; } function d3_layout_stackOut(d, y0, y) { d.y0 = y0; d.y = y; } var d3_layout_stackOrders = d3.map({ "inside-out": function(data) { var n = data.length, i, j, max = data.map(d3_layout_stackMaxIndex), sums = data.map(d3_layout_stackReduceSum), index = d3.range(n).sort(function(a, b) { return max[a] - max[b]; }), top = 0, bottom = 0, tops = [], bottoms = []; for (i = 0; i < n; ++i) { j = index[i]; if (top < bottom) { top += sums[j]; tops.push(j); } else { bottom += sums[j]; bottoms.push(j); } } return bottoms.reverse().concat(tops); }, reverse: function(data) { return d3.range(data.length).reverse(); }, "default": d3_layout_stackOrderDefault }); var d3_layout_stackOffsets = d3.map({ silhouette: function(data) { var n = data.length, m = data[0].length, sums = [], max = 0, i, j, o, y0 = []; for (j = 0; j < m; ++j) { for (i = 0, o = 0; i < n; i++) o += data[i][j][1]; if (o > max) max = o; sums.push(o); } for (j = 0; j < m; ++j) { y0[j] = (max - sums[j]) / 2; } return y0; }, wiggle: function(data) { var n = data.length, x = data[0], m = x.length, i, j, k, s1, s2, s3, dx, o, o0, y0 = []; y0[0] = o = o0 = 0; for (j = 1; j < m; ++j) { for (i = 0, s1 = 0; i < n; ++i) s1 += data[i][j][1]; for (i = 0, s2 = 0, dx = x[j][0] - x[j - 1][0]; i < n; ++i) { for (k = 0, s3 = (data[i][j][1] - data[i][j - 1][1]) / (2 * dx); k < i; ++k) { s3 += (data[k][j][1] - data[k][j - 1][1]) / dx; } s2 += s3 * data[i][j][1]; } y0[j] = o -= s1 ? s2 / s1 * dx : 0; if (o < o0) o0 = o; } for (j = 0; j < m; ++j) y0[j] -= o0; return y0; }, expand: function(data) { var n = data.length, m = data[0].length, k = 1 / n, i, j, o, y0 = []; for (j = 0; j < m; ++j) { for (i = 0, o = 0; i < n; i++) o += data[i][j][1]; if (o) for (i = 0; i < n; i++) data[i][j][1] /= o; else for (i = 0; i < n; i++) data[i][j][1] = k; } for (j = 0; j < m; ++j) y0[j] = 0; return y0; }, zero: d3_layout_stackOffsetZero }); function d3_layout_stackOrderDefault(data) { return d3.range(data.length); } function d3_layout_stackOffsetZero(data) { var j = -1, m = data[0].length, y0 = []; while (++j < m) y0[j] = 0; return y0; } function d3_layout_stackMaxIndex(array) { var i = 1, j = 0, v = array[0][1], k, n = array.length; for (;i < n; ++i) { if ((k = array[i][1]) > v) { j = i; v = k; } } return j; } function d3_layout_stackReduceSum(d) { return d.reduce(d3_layout_stackSum, 0); } function d3_layout_stackSum(p, d) { return p + d[1]; } d3.layout.histogram = function() { var frequency = true, valuer = Number, ranger = d3_layout_histogramRange, binner = d3_layout_histogramBinSturges; function histogram(data, i) { var bins = [], values = data.map(valuer, this), range = ranger.call(this, values, i), thresholds = binner.call(this, range, values, i), bin, i = -1, n = values.length, m = thresholds.length - 1, k = frequency ? 1 : 1 / n, x; while (++i < m) { bin = bins[i] = []; bin.dx = thresholds[i + 1] - (bin.x = thresholds[i]); bin.y = 0; } if (m > 0) { i = -1; while (++i < n) { x = values[i]; if (x >= range[0] && x <= range[1]) { bin = bins[d3.bisect(thresholds, x, 1, m) - 1]; bin.y += k; bin.push(data[i]); } } } return bins; } histogram.value = function(x) { if (!arguments.length) return valuer; valuer = x; return histogram; }; histogram.range = function(x) { if (!arguments.length) return ranger; ranger = d3_functor(x); return histogram; }; histogram.bins = function(x) { if (!arguments.length) return binner; binner = typeof x === "number" ? function(range) { return d3_layout_histogramBinFixed(range, x); } : d3_functor(x); return histogram; }; histogram.frequency = function(x) { if (!arguments.length) return frequency; frequency = !!x; return histogram; }; return histogram; }; function d3_layout_histogramBinSturges(range, values) { return d3_layout_histogramBinFixed(range, Math.ceil(Math.log(values.length) / Math.LN2 + 1)); } function d3_layout_histogramBinFixed(range, n) { var x = -1, b = +range[0], m = (range[1] - b) / n, f = []; while (++x <= n) f[x] = m * x + b; return f; } function d3_layout_histogramRange(values) { return [ d3.min(values), d3.max(values) ]; } d3.layout.pack = function() { var hierarchy = d3.layout.hierarchy().sort(d3_layout_packSort), padding = 0, size = [ 1, 1 ], radius; function pack(d, i) { var nodes = hierarchy.call(this, d, i), root = nodes[0], w = size[0], h = size[1], r = radius == null ? Math.sqrt : typeof radius === "function" ? radius : function() { return radius; }; root.x = root.y = 0; d3_layout_hierarchyVisitAfter(root, function(d) { d.r = +r(d.value); }); d3_layout_hierarchyVisitAfter(root, d3_layout_packSiblings); if (padding) { var dr = padding * (radius ? 1 : Math.max(2 * root.r / w, 2 * root.r / h)) / 2; d3_layout_hierarchyVisitAfter(root, function(d) { d.r += dr; }); d3_layout_hierarchyVisitAfter(root, d3_layout_packSiblings); d3_layout_hierarchyVisitAfter(root, function(d) { d.r -= dr; }); } d3_layout_packTransform(root, w / 2, h / 2, radius ? 1 : 1 / Math.max(2 * root.r / w, 2 * root.r / h)); return nodes; } pack.size = function(_) { if (!arguments.length) return size; size = _; return pack; }; pack.radius = function(_) { if (!arguments.length) return radius; radius = _ == null || typeof _ === "function" ? _ : +_; return pack; }; pack.padding = function(_) { if (!arguments.length) return padding; padding = +_; return pack; }; return d3_layout_hierarchyRebind(pack, hierarchy); }; function d3_layout_packSort(a, b) { return a.value - b.value; } function d3_layout_packInsert(a, b) { var c = a._pack_next; a._pack_next = b; b._pack_prev = a; b._pack_next = c; c._pack_prev = b; } function d3_layout_packSplice(a, b) { a._pack_next = b; b._pack_prev = a; } function d3_layout_packIntersects(a, b) { var dx = b.x - a.x, dy = b.y - a.y, dr = a.r + b.r; return .999 * dr * dr > dx * dx + dy * dy; } function d3_layout_packSiblings(node) { if (!(nodes = node.children) || !(n = nodes.length)) return; var nodes, xMin = Infinity, xMax = -Infinity, yMin = Infinity, yMax = -Infinity, a, b, c, i, j, k, n; function bound(node) { xMin = Math.min(node.x - node.r, xMin); xMax = Math.max(node.x + node.r, xMax); yMin = Math.min(node.y - node.r, yMin); yMax = Math.max(node.y + node.r, yMax); } nodes.forEach(d3_layout_packLink); a = nodes[0]; a.x = -a.r; a.y = 0; bound(a); if (n > 1) { b = nodes[1]; b.x = b.r; b.y = 0; bound(b); if (n > 2) { c = nodes[2]; d3_layout_packPlace(a, b, c); bound(c); d3_layout_packInsert(a, c); a._pack_prev = c; d3_layout_packInsert(c, b); b = a._pack_next; for (i = 3; i < n; i++) { d3_layout_packPlace(a, b, c = nodes[i]); var isect = 0, s1 = 1, s2 = 1; for (j = b._pack_next; j !== b; j = j._pack_next, s1++) { if (d3_layout_packIntersects(j, c)) { isect = 1; break; } } if (isect == 1) { for (k = a._pack_prev; k !== j._pack_prev; k = k._pack_prev, s2++) { if (d3_layout_packIntersects(k, c)) { break; } } } if (isect) { if (s1 < s2 || s1 == s2 && b.r < a.r) d3_layout_packSplice(a, b = j); else d3_layout_packSplice(a = k, b); i--; } else { d3_layout_packInsert(a, c); b = c; bound(c); } } } } var cx = (xMin + xMax) / 2, cy = (yMin + yMax) / 2, cr = 0; for (i = 0; i < n; i++) { c = nodes[i]; c.x -= cx; c.y -= cy; cr = Math.max(cr, c.r + Math.sqrt(c.x * c.x + c.y * c.y)); } node.r = cr; nodes.forEach(d3_layout_packUnlink); } function d3_layout_packLink(node) { node._pack_next = node._pack_prev = node; } function d3_layout_packUnlink(node) { delete node._pack_next; delete node._pack_prev; } function d3_layout_packTransform(node, x, y, k) { var children = node.children; node.x = x += k * node.x; node.y = y += k * node.y; node.r *= k; if (children) { var i = -1, n = children.length; while (++i < n) d3_layout_packTransform(children[i], x, y, k); } } function d3_layout_packPlace(a, b, c) { var db = a.r + c.r, dx = b.x - a.x, dy = b.y - a.y; if (db && (dx || dy)) { var da = b.r + c.r, dc = dx * dx + dy * dy; da *= da; db *= db; var x = .5 + (db - da) / (2 * dc), y = Math.sqrt(Math.max(0, 2 * da * (db + dc) - (db -= dc) * db - da * da)) / (2 * dc); c.x = a.x + x * dx + y * dy; c.y = a.y + x * dy - y * dx; } else { c.x = a.x + db; c.y = a.y; } } d3.layout.tree = function() { var hierarchy = d3.layout.hierarchy().sort(null).value(null), separation = d3_layout_treeSeparation, size = [ 1, 1 ], nodeSize = null; function tree(d, i) { var nodes = hierarchy.call(this, d, i), root0 = nodes[0], root1 = wrapTree(root0); d3_layout_hierarchyVisitAfter(root1, firstWalk), root1.parent.m = -root1.z; d3_layout_hierarchyVisitBefore(root1, secondWalk); if (nodeSize) d3_layout_hierarchyVisitBefore(root0, sizeNode); else { var left = root0, right = root0, bottom = root0; d3_layout_hierarchyVisitBefore(root0, function(node) { if (node.x < left.x) left = node; if (node.x > right.x) right = node; if (node.depth > bottom.depth) bottom = node; }); var tx = separation(left, right) / 2 - left.x, kx = size[0] / (right.x + separation(right, left) / 2 + tx), ky = size[1] / (bottom.depth || 1); d3_layout_hierarchyVisitBefore(root0, function(node) { node.x = (node.x + tx) * kx; node.y = node.depth * ky; }); } return nodes; } function wrapTree(root0) { var root1 = { A: null, children: [ root0 ] }, queue = [ root1 ], node1; while ((node1 = queue.pop()) != null) { for (var children = node1.children, child, i = 0, n = children.length; i < n; ++i) { queue.push((children[i] = child = { _: children[i], parent: node1, children: (child = children[i].children) && child.slice() || [], A: null, a: null, z: 0, m: 0, c: 0, s: 0, t: null, i: i }).a = child); } } return root1.children[0]; } function firstWalk(v) { var children = v.children, siblings = v.parent.children, w = v.i ? siblings[v.i - 1] : null; if (children.length) { d3_layout_treeShift(v); var midpoint = (children[0].z + children[children.length - 1].z) / 2; if (w) { v.z = w.z + separation(v._, w._); v.m = v.z - midpoint; } else { v.z = midpoint; } } else if (w) { v.z = w.z + separation(v._, w._); } v.parent.A = apportion(v, w, v.parent.A || siblings[0]); } function secondWalk(v) { v._.x = v.z + v.parent.m; v.m += v.parent.m; } function apportion(v, w, ancestor) { if (w) { var vip = v, vop = v, vim = w, vom = vip.parent.children[0], sip = vip.m, sop = vop.m, sim = vim.m, som = vom.m, shift; while (vim = d3_layout_treeRight(vim), vip = d3_layout_treeLeft(vip), vim && vip) { vom = d3_layout_treeLeft(vom); vop = d3_layout_treeRight(vop); vop.a = v; shift = vim.z + sim - vip.z - sip + separation(vim._, vip._); if (shift > 0) { d3_layout_treeMove(d3_layout_treeAncestor(vim, v, ancestor), v, shift); sip += shift; sop += shift; } sim += vim.m; sip += vip.m; som += vom.m; sop += vop.m; } if (vim && !d3_layout_treeRight(vop)) { vop.t = vim; vop.m += sim - sop; } if (vip && !d3_layout_treeLeft(vom)) { vom.t = vip; vom.m += sip - som; ancestor = v; } } return ancestor; } function sizeNode(node) { node.x *= size[0]; node.y = node.depth * size[1]; } tree.separation = function(x) { if (!arguments.length) return separation; separation = x; return tree; }; tree.size = function(x) { if (!arguments.length) return nodeSize ? null : size; nodeSize = (size = x) == null ? sizeNode : null; return tree; }; tree.nodeSize = function(x) { if (!arguments.length) return nodeSize ? size : null; nodeSize = (size = x) == null ? null : sizeNode; return tree; }; return d3_layout_hierarchyRebind(tree, hierarchy); }; function d3_layout_treeSeparation(a, b) { return a.parent == b.parent ? 1 : 2; } function d3_layout_treeLeft(v) { var children = v.children; return children.length ? children[0] : v.t; } function d3_layout_treeRight(v) { var children = v.children, n; return (n = children.length) ? children[n - 1] : v.t; } function d3_layout_treeMove(wm, wp, shift) { var change = shift / (wp.i - wm.i); wp.c -= change; wp.s += shift; wm.c += change; wp.z += shift; wp.m += shift; } function d3_layout_treeShift(v) { var shift = 0, change = 0, children = v.children, i = children.length, w; while (--i >= 0) { w = children[i]; w.z += shift; w.m += shift; shift += w.s + (change += w.c); } } function d3_layout_treeAncestor(vim, v, ancestor) { return vim.a.parent === v.parent ? vim.a : ancestor; } d3.layout.cluster = function() { var hierarchy = d3.layout.hierarchy().sort(null).value(null), separation = d3_layout_treeSeparation, size = [ 1, 1 ], nodeSize = false; function cluster(d, i) { var nodes = hierarchy.call(this, d, i), root = nodes[0], previousNode, x = 0; d3_layout_hierarchyVisitAfter(root, function(node) { var children = node.children; if (children && children.length) { node.x = d3_layout_clusterX(children); node.y = d3_layout_clusterY(children); } else { node.x = previousNode ? x += separation(node, previousNode) : 0; node.y = 0; previousNode = node; } }); var left = d3_layout_clusterLeft(root), right = d3_layout_clusterRight(root), x0 = left.x - separation(left, right) / 2, x1 = right.x + separation(right, left) / 2; d3_layout_hierarchyVisitAfter(root, nodeSize ? function(node) { node.x = (node.x - root.x) * size[0]; node.y = (root.y - node.y) * size[1]; } : function(node) { node.x = (node.x - x0) / (x1 - x0) * size[0]; node.y = (1 - (root.y ? node.y / root.y : 1)) * size[1]; }); return nodes; } cluster.separation = function(x) { if (!arguments.length) return separation; separation = x; return cluster; }; cluster.size = function(x) { if (!arguments.length) return nodeSize ? null : size; nodeSize = (size = x) == null; return cluster; }; cluster.nodeSize = function(x) { if (!arguments.length) return nodeSize ? size : null; nodeSize = (size = x) != null; return cluster; }; return d3_layout_hierarchyRebind(cluster, hierarchy); }; function d3_layout_clusterY(children) { return 1 + d3.max(children, function(child) { return child.y; }); } function d3_layout_clusterX(children) { return children.reduce(function(x, child) { return x + child.x; }, 0) / children.length; } function d3_layout_clusterLeft(node) { var children = node.children; return children && children.length ? d3_layout_clusterLeft(children[0]) : node; } function d3_layout_clusterRight(node) { var children = node.children, n; return children && (n = children.length) ? d3_layout_clusterRight(children[n - 1]) : node; } d3.layout.treemap = function() { var hierarchy = d3.layout.hierarchy(), round = Math.round, size = [ 1, 1 ], padding = null, pad = d3_layout_treemapPadNull, sticky = false, stickies, mode = "squarify", ratio = .5 * (1 + Math.sqrt(5)); function scale(children, k) { var i = -1, n = children.length, child, area; while (++i < n) { area = (child = children[i]).value * (k < 0 ? 0 : k); child.area = isNaN(area) || area <= 0 ? 0 : area; } } function squarify(node) { var children = node.children; if (children && children.length) { var rect = pad(node), row = [], remaining = children.slice(), child, best = Infinity, score, u = mode === "slice" ? rect.dx : mode === "dice" ? rect.dy : mode === "slice-dice" ? node.depth & 1 ? rect.dy : rect.dx : Math.min(rect.dx, rect.dy), n; scale(remaining, rect.dx * rect.dy / node.value); row.area = 0; while ((n = remaining.length) > 0) { row.push(child = remaining[n - 1]); row.area += child.area; if (mode !== "squarify" || (score = worst(row, u)) <= best) { remaining.pop(); best = score; } else { row.area -= row.pop().area; position(row, u, rect, false); u = Math.min(rect.dx, rect.dy); row.length = row.area = 0; best = Infinity; } } if (row.length) { position(row, u, rect, true); row.length = row.area = 0; } children.forEach(squarify); } } function stickify(node) { var children = node.children; if (children && children.length) { var rect = pad(node), remaining = children.slice(), child, row = []; scale(remaining, rect.dx * rect.dy / node.value); row.area = 0; while (child = remaining.pop()) { row.push(child); row.area += child.area; if (child.z != null) { position(row, child.z ? rect.dx : rect.dy, rect, !remaining.length); row.length = row.area = 0; } } children.forEach(stickify); } } function worst(row, u) { var s = row.area, r, rmax = 0, rmin = Infinity, i = -1, n = row.length; while (++i < n) { if (!(r = row[i].area)) continue; if (r < rmin) rmin = r; if (r > rmax) rmax = r; } s *= s; u *= u; return s ? Math.max(u * rmax * ratio / s, s / (u * rmin * ratio)) : Infinity; } function position(row, u, rect, flush) { var i = -1, n = row.length, x = rect.x, y = rect.y, v = u ? round(row.area / u) : 0, o; if (u == rect.dx) { if (flush || v > rect.dy) v = rect.dy; while (++i < n) { o = row[i]; o.x = x; o.y = y; o.dy = v; x += o.dx = Math.min(rect.x + rect.dx - x, v ? round(o.area / v) : 0); } o.z = true; o.dx += rect.x + rect.dx - x; rect.y += v; rect.dy -= v; } else { if (flush || v > rect.dx) v = rect.dx; while (++i < n) { o = row[i]; o.x = x; o.y = y; o.dx = v; y += o.dy = Math.min(rect.y + rect.dy - y, v ? round(o.area / v) : 0); } o.z = false; o.dy += rect.y + rect.dy - y; rect.x += v; rect.dx -= v; } } function treemap(d) { var nodes = stickies || hierarchy(d), root = nodes[0]; root.x = root.y = 0; if (root.value) root.dx = size[0], root.dy = size[1]; else root.dx = root.dy = 0; if (stickies) hierarchy.revalue(root); scale([ root ], root.dx * root.dy / root.value); (stickies ? stickify : squarify)(root); if (sticky) stickies = nodes; return nodes; } treemap.size = function(x) { if (!arguments.length) return size; size = x; return treemap; }; treemap.padding = function(x) { if (!arguments.length) return padding; function padFunction(node) { var p = x.call(treemap, node, node.depth); return p == null ? d3_layout_treemapPadNull(node) : d3_layout_treemapPad(node, typeof p === "number" ? [ p, p, p, p ] : p); } function padConstant(node) { return d3_layout_treemapPad(node, x); } var type; pad = (padding = x) == null ? d3_layout_treemapPadNull : (type = typeof x) === "function" ? padFunction : type === "number" ? (x = [ x, x, x, x ], padConstant) : padConstant; return treemap; }; treemap.round = function(x) { if (!arguments.length) return round != Number; round = x ? Math.round : Number; return treemap; }; treemap.sticky = function(x) { if (!arguments.length) return sticky; sticky = x; stickies = null; return treemap; }; treemap.ratio = function(x) { if (!arguments.length) return ratio; ratio = x; return treemap; }; treemap.mode = function(x) { if (!arguments.length) return mode; mode = x + ""; return treemap; }; return d3_layout_hierarchyRebind(treemap, hierarchy); }; function d3_layout_treemapPadNull(node) { return { x: node.x, y: node.y, dx: node.dx, dy: node.dy }; } function d3_layout_treemapPad(node, padding) { var x = node.x + padding[3], y = node.y + padding[0], dx = node.dx - padding[1] - padding[3], dy = node.dy - padding[0] - padding[2]; if (dx < 0) { x += dx / 2; dx = 0; } if (dy < 0) { y += dy / 2; dy = 0; } return { x: x, y: y, dx: dx, dy: dy }; } d3.random = { normal: function(µ, σ) { var n = arguments.length; if (n < 2) σ = 1; if (n < 1) µ = 0; return function() { var x, y, r; do { x = Math.random() * 2 - 1; y = Math.random() * 2 - 1; r = x * x + y * y; } while (!r || r > 1); return µ + σ * x * Math.sqrt(-2 * Math.log(r) / r); }; }, logNormal: function() { var random = d3.random.normal.apply(d3, arguments); return function() { return Math.exp(random()); }; }, bates: function(m) { var random = d3.random.irwinHall(m); return function() { return random() / m; }; }, irwinHall: function(m) { return function() { for (var s = 0, j = 0; j < m; j++) s += Math.random(); return s; }; } }; d3.scale = {}; function d3_scaleExtent(domain) { var start = domain[0], stop = domain[domain.length - 1]; return start < stop ? [ start, stop ] : [ stop, start ]; } function d3_scaleRange(scale) { return scale.rangeExtent ? scale.rangeExtent() : d3_scaleExtent(scale.range()); } function d3_scale_bilinear(domain, range, uninterpolate, interpolate) { var u = uninterpolate(domain[0], domain[1]), i = interpolate(range[0], range[1]); return function(x) { return i(u(x)); }; } function d3_scale_nice(domain, nice) { var i0 = 0, i1 = domain.length - 1, x0 = domain[i0], x1 = domain[i1], dx; if (x1 < x0) { dx = i0, i0 = i1, i1 = dx; dx = x0, x0 = x1, x1 = dx; } domain[i0] = nice.floor(x0); domain[i1] = nice.ceil(x1); return domain; } function d3_scale_niceStep(step) { return step ? { floor: function(x) { return Math.floor(x / step) * step; }, ceil: function(x) { return Math.ceil(x / step) * step; } } : d3_scale_niceIdentity; } var d3_scale_niceIdentity = { floor: d3_identity, ceil: d3_identity }; function d3_scale_polylinear(domain, range, uninterpolate, interpolate) { var u = [], i = [], j = 0, k = Math.min(domain.length, range.length) - 1; if (domain[k] < domain[0]) { domain = domain.slice().reverse(); range = range.slice().reverse(); } while (++j <= k) { u.push(uninterpolate(domain[j - 1], domain[j])); i.push(interpolate(range[j - 1], range[j])); } return function(x) { var j = d3.bisect(domain, x, 1, k) - 1; return i[j](u[j](x)); }; } d3.scale.linear = function() { return d3_scale_linear([ 0, 1 ], [ 0, 1 ], d3_interpolate, false); }; function d3_scale_linear(domain, range, interpolate, clamp) { var output, input; function rescale() { var linear = Math.min(domain.length, range.length) > 2 ? d3_scale_polylinear : d3_scale_bilinear, uninterpolate = clamp ? d3_uninterpolateClamp : d3_uninterpolateNumber; output = linear(domain, range, uninterpolate, interpolate); input = linear(range, domain, uninterpolate, d3_interpolate); return scale; } function scale(x) { return output(x); } scale.invert = function(y) { return input(y); }; scale.domain = function(x) { if (!arguments.length) return domain; domain = x.map(Number); return rescale(); }; scale.range = function(x) { if (!arguments.length) return range; range = x; return rescale(); }; scale.rangeRound = function(x) { return scale.range(x).interpolate(d3_interpolateRound); }; scale.clamp = function(x) { if (!arguments.length) return clamp; clamp = x; return rescale(); }; scale.interpolate = function(x) { if (!arguments.length) return interpolate; interpolate = x; return rescale(); }; scale.ticks = function(m) { return d3_scale_linearTicks(domain, m); }; scale.tickFormat = function(m, format) { return d3_scale_linearTickFormat(domain, m, format); }; scale.nice = function(m) { d3_scale_linearNice(domain, m); return rescale(); }; scale.copy = function() { return d3_scale_linear(domain, range, interpolate, clamp); }; return rescale(); } function d3_scale_linearRebind(scale, linear) { return d3.rebind(scale, linear, "range", "rangeRound", "interpolate", "clamp"); } function d3_scale_linearNice(domain, m) { d3_scale_nice(domain, d3_scale_niceStep(d3_scale_linearTickRange(domain, m)[2])); d3_scale_nice(domain, d3_scale_niceStep(d3_scale_linearTickRange(domain, m)[2])); return domain; } function d3_scale_linearTickRange(domain, m) { if (m == null) m = 10; var extent = d3_scaleExtent(domain), span = extent[1] - extent[0], step = Math.pow(10, Math.floor(Math.log(span / m) / Math.LN10)), err = m / span * step; if (err <= .15) step *= 10; else if (err <= .35) step *= 5; else if (err <= .75) step *= 2; extent[0] = Math.ceil(extent[0] / step) * step; extent[1] = Math.floor(extent[1] / step) * step + step * .5; extent[2] = step; return extent; } function d3_scale_linearTicks(domain, m) { return d3.range.apply(d3, d3_scale_linearTickRange(domain, m)); } function d3_scale_linearTickFormat(domain, m, format) { var range = d3_scale_linearTickRange(domain, m); if (format) { var match = d3_format_re.exec(format); match.shift(); if (match[8] === "s") { var prefix = d3.formatPrefix(Math.max(abs(range[0]), abs(range[1]))); if (!match[7]) match[7] = "." + d3_scale_linearPrecision(prefix.scale(range[2])); match[8] = "f"; format = d3.format(match.join("")); return function(d) { return format(prefix.scale(d)) + prefix.symbol; }; } if (!match[7]) match[7] = "." + d3_scale_linearFormatPrecision(match[8], range); format = match.join(""); } else { format = ",." + d3_scale_linearPrecision(range[2]) + "f"; } return d3.format(format); } var d3_scale_linearFormatSignificant = { s: 1, g: 1, p: 1, r: 1, e: 1 }; function d3_scale_linearPrecision(value) { return -Math.floor(Math.log(value) / Math.LN10 + .01); } function d3_scale_linearFormatPrecision(type, range) { var p = d3_scale_linearPrecision(range[2]); return type in d3_scale_linearFormatSignificant ? Math.abs(p - d3_scale_linearPrecision(Math.max(abs(range[0]), abs(range[1])))) + +(type !== "e") : p - (type === "%") * 2; } d3.scale.log = function() { return d3_scale_log(d3.scale.linear().domain([ 0, 1 ]), 10, true, [ 1, 10 ]); }; function d3_scale_log(linear, base, positive, domain) { function log(x) { return (positive ? Math.log(x < 0 ? 0 : x) : -Math.log(x > 0 ? 0 : -x)) / Math.log(base); } function pow(x) { return positive ? Math.pow(base, x) : -Math.pow(base, -x); } function scale(x) { return linear(log(x)); } scale.invert = function(x) { return pow(linear.invert(x)); }; scale.domain = function(x) { if (!arguments.length) return domain; positive = x[0] >= 0; linear.domain((domain = x.map(Number)).map(log)); return scale; }; scale.base = function(_) { if (!arguments.length) return base; base = +_; linear.domain(domain.map(log)); return scale; }; scale.nice = function() { var niced = d3_scale_nice(domain.map(log), positive ? Math : d3_scale_logNiceNegative); linear.domain(niced); domain = niced.map(pow); return scale; }; scale.ticks = function() { var extent = d3_scaleExtent(domain), ticks = [], u = extent[0], v = extent[1], i = Math.floor(log(u)), j = Math.ceil(log(v)), n = base % 1 ? 2 : base; if (isFinite(j - i)) { if (positive) { for (;i < j; i++) for (var k = 1; k < n; k++) ticks.push(pow(i) * k); ticks.push(pow(i)); } else { ticks.push(pow(i)); for (;i++ < j; ) for (var k = n - 1; k > 0; k--) ticks.push(pow(i) * k); } for (i = 0; ticks[i] < u; i++) {} for (j = ticks.length; ticks[j - 1] > v; j--) {} ticks = ticks.slice(i, j); } return ticks; }; scale.tickFormat = function(n, format) { if (!arguments.length) return d3_scale_logFormat; if (arguments.length < 2) format = d3_scale_logFormat; else if (typeof format !== "function") format = d3.format(format); var k = Math.max(1, base * n / scale.ticks().length); return function(d) { var i = d / pow(Math.round(log(d))); if (i * base < base - .5) i *= base; return i <= k ? format(d) : ""; }; }; scale.copy = function() { return d3_scale_log(linear.copy(), base, positive, domain); }; return d3_scale_linearRebind(scale, linear); } var d3_scale_logFormat = d3.format(".0e"), d3_scale_logNiceNegative = { floor: function(x) { return -Math.ceil(-x); }, ceil: function(x) { return -Math.floor(-x); } }; d3.scale.pow = function() { return d3_scale_pow(d3.scale.linear(), 1, [ 0, 1 ]); }; function d3_scale_pow(linear, exponent, domain) { var powp = d3_scale_powPow(exponent), powb = d3_scale_powPow(1 / exponent); function scale(x) { return linear(powp(x)); } scale.invert = function(x) { return powb(linear.invert(x)); }; scale.domain = function(x) { if (!arguments.length) return domain; linear.domain((domain = x.map(Number)).map(powp)); return scale; }; scale.ticks = function(m) { return d3_scale_linearTicks(domain, m); }; scale.tickFormat = function(m, format) { return d3_scale_linearTickFormat(domain, m, format); }; scale.nice = function(m) { return scale.domain(d3_scale_linearNice(domain, m)); }; scale.exponent = function(x) { if (!arguments.length) return exponent; powp = d3_scale_powPow(exponent = x); powb = d3_scale_powPow(1 / exponent); linear.domain(domain.map(powp)); return scale; }; scale.copy = function() { return d3_scale_pow(linear.copy(), exponent, domain); }; return d3_scale_linearRebind(scale, linear); } function d3_scale_powPow(e) { return function(x) { return x < 0 ? -Math.pow(-x, e) : Math.pow(x, e); }; } d3.scale.sqrt = function() { return d3.scale.pow().exponent(.5); }; d3.scale.ordinal = function() { return d3_scale_ordinal([], { t: "range", a: [ [] ] }); }; function d3_scale_ordinal(domain, ranger) { var index, range, rangeBand; function scale(x) { return range[((index.get(x) || (ranger.t === "range" ? index.set(x, domain.push(x)) : NaN)) - 1) % range.length]; } function steps(start, step) { return d3.range(domain.length).map(function(i) { return start + step * i; }); } scale.domain = function(x) { if (!arguments.length) return domain; domain = []; index = new d3_Map(); var i = -1, n = x.length, xi; while (++i < n) if (!index.has(xi = x[i])) index.set(xi, domain.push(xi)); return scale[ranger.t].apply(scale, ranger.a); }; scale.range = function(x) { if (!arguments.length) return range; range = x; rangeBand = 0; ranger = { t: "range", a: arguments }; return scale; }; scale.rangePoints = function(x, padding) { if (arguments.length < 2) padding = 0; var start = x[0], stop = x[1], step = domain.length < 2 ? (start = (start + stop) / 2, 0) : (stop - start) / (domain.length - 1 + padding); range = steps(start + step * padding / 2, step); rangeBand = 0; ranger = { t: "rangePoints", a: arguments }; return scale; }; scale.rangeRoundPoints = function(x, padding) { if (arguments.length < 2) padding = 0; var start = x[0], stop = x[1], step = domain.length < 2 ? (start = stop = Math.round((start + stop) / 2), 0) : (stop - start) / (domain.length - 1 + padding) | 0; range = steps(start + Math.round(step * padding / 2 + (stop - start - (domain.length - 1 + padding) * step) / 2), step); rangeBand = 0; ranger = { t: "rangeRoundPoints", a: arguments }; return scale; }; scale.rangeBands = function(x, padding, outerPadding) { if (arguments.length < 2) padding = 0; if (arguments.length < 3) outerPadding = padding; var reverse = x[1] < x[0], start = x[reverse - 0], stop = x[1 - reverse], step = (stop - start) / (domain.length - padding + 2 * outerPadding); range = steps(start + step * outerPadding, step); if (reverse) range.reverse(); rangeBand = step * (1 - padding); ranger = { t: "rangeBands", a: arguments }; return scale; }; scale.rangeRoundBands = function(x, padding, outerPadding) { if (arguments.length < 2) padding = 0; if (arguments.length < 3) outerPadding = padding; var reverse = x[1] < x[0], start = x[reverse - 0], stop = x[1 - reverse], step = Math.floor((stop - start) / (domain.length - padding + 2 * outerPadding)); range = steps(start + Math.round((stop - start - (domain.length - padding) * step) / 2), step); if (reverse) range.reverse(); rangeBand = Math.round(step * (1 - padding)); ranger = { t: "rangeRoundBands", a: arguments }; return scale; }; scale.rangeBand = function() { return rangeBand; }; scale.rangeExtent = function() { return d3_scaleExtent(ranger.a[0]); }; scale.copy = function() { return d3_scale_ordinal(domain, ranger); }; return scale.domain(domain); } d3.scale.category10 = function() { return d3.scale.ordinal().range(d3_category10); }; d3.scale.category20 = function() { return d3.scale.ordinal().range(d3_category20); }; d3.scale.category20b = function() { return d3.scale.ordinal().range(d3_category20b); }; d3.scale.category20c = function() { return d3.scale.ordinal().range(d3_category20c); }; var d3_category10 = [ 2062260, 16744206, 2924588, 14034728, 9725885, 9197131, 14907330, 8355711, 12369186, 1556175 ].map(d3_rgbString); var d3_category20 = [ 2062260, 11454440, 16744206, 16759672, 2924588, 10018698, 14034728, 16750742, 9725885, 12955861, 9197131, 12885140, 14907330, 16234194, 8355711, 13092807, 12369186, 14408589, 1556175, 10410725 ].map(d3_rgbString); var d3_category20b = [ 3750777, 5395619, 7040719, 10264286, 6519097, 9216594, 11915115, 13556636, 9202993, 12426809, 15186514, 15190932, 8666169, 11356490, 14049643, 15177372, 8077683, 10834324, 13528509, 14589654 ].map(d3_rgbString); var d3_category20c = [ 3244733, 7057110, 10406625, 13032431, 15095053, 16616764, 16625259, 16634018, 3253076, 7652470, 10607003, 13101504, 7695281, 10394312, 12369372, 14342891, 6513507, 9868950, 12434877, 14277081 ].map(d3_rgbString); d3.scale.quantile = function() { return d3_scale_quantile([], []); }; function d3_scale_quantile(domain, range) { var thresholds; function rescale() { var k = 0, q = range.length; thresholds = []; while (++k < q) thresholds[k - 1] = d3.quantile(domain, k / q); return scale; } function scale(x) { if (!isNaN(x = +x)) return range[d3.bisect(thresholds, x)]; } scale.domain = function(x) { if (!arguments.length) return domain; domain = x.map(d3_number).filter(d3_numeric).sort(d3_ascending); return rescale(); }; scale.range = function(x) { if (!arguments.length) return range; range = x; return rescale(); }; scale.quantiles = function() { return thresholds; }; scale.invertExtent = function(y) { y = range.indexOf(y); return y < 0 ? [ NaN, NaN ] : [ y > 0 ? thresholds[y - 1] : domain[0], y < thresholds.length ? thresholds[y] : domain[domain.length - 1] ]; }; scale.copy = function() { return d3_scale_quantile(domain, range); }; return rescale(); } d3.scale.quantize = function() { return d3_scale_quantize(0, 1, [ 0, 1 ]); }; function d3_scale_quantize(x0, x1, range) { var kx, i; function scale(x) { return range[Math.max(0, Math.min(i, Math.floor(kx * (x - x0))))]; } function rescale() { kx = range.length / (x1 - x0); i = range.length - 1; return scale; } scale.domain = function(x) { if (!arguments.length) return [ x0, x1 ]; x0 = +x[0]; x1 = +x[x.length - 1]; return rescale(); }; scale.range = function(x) { if (!arguments.length) return range; range = x; return rescale(); }; scale.invertExtent = function(y) { y = range.indexOf(y); y = y < 0 ? NaN : y / kx + x0; return [ y, y + 1 / kx ]; }; scale.copy = function() { return d3_scale_quantize(x0, x1, range); }; return rescale(); } d3.scale.threshold = function() { return d3_scale_threshold([ .5 ], [ 0, 1 ]); }; function d3_scale_threshold(domain, range) { function scale(x) { if (x <= x) return range[d3.bisect(domain, x)]; } scale.domain = function(_) { if (!arguments.length) return domain; domain = _; return scale; }; scale.range = function(_) { if (!arguments.length) return range; range = _; return scale; }; scale.invertExtent = function(y) { y = range.indexOf(y); return [ domain[y - 1], domain[y] ]; }; scale.copy = function() { return d3_scale_threshold(domain, range); }; return scale; } d3.scale.identity = function() { return d3_scale_identity([ 0, 1 ]); }; function d3_scale_identity(domain) { function identity(x) { return +x; } identity.invert = identity; identity.domain = identity.range = function(x) { if (!arguments.length) return domain; domain = x.map(identity); return identity; }; identity.ticks = function(m) { return d3_scale_linearTicks(domain, m); }; identity.tickFormat = function(m, format) { return d3_scale_linearTickFormat(domain, m, format); }; identity.copy = function() { return d3_scale_identity(domain); }; return identity; } d3.svg = {}; function d3_zero() { return 0; } d3.svg.arc = function() { var innerRadius = d3_svg_arcInnerRadius, outerRadius = d3_svg_arcOuterRadius, cornerRadius = d3_zero, padRadius = d3_svg_arcAuto, startAngle = d3_svg_arcStartAngle, endAngle = d3_svg_arcEndAngle, padAngle = d3_svg_arcPadAngle; function arc() { var r0 = Math.max(0, +innerRadius.apply(this, arguments)), r1 = Math.max(0, +outerRadius.apply(this, arguments)), a0 = startAngle.apply(this, arguments) - halfÏ€, a1 = endAngle.apply(this, arguments) - halfÏ€, da = Math.abs(a1 - a0), cw = a0 > a1 ? 0 : 1; if (r1 < r0) rc = r1, r1 = r0, r0 = rc; if (da >= τε) return circleSegment(r1, cw) + (r0 ? circleSegment(r0, 1 - cw) : "") + "Z"; var rc, cr, rp, ap, p0 = 0, p1 = 0, x0, y0, x1, y1, x2, y2, x3, y3, path = []; if (ap = (+padAngle.apply(this, arguments) || 0) / 2) { rp = padRadius === d3_svg_arcAuto ? Math.sqrt(r0 * r0 + r1 * r1) : +padRadius.apply(this, arguments); if (!cw) p1 *= -1; if (r1) p1 = d3_asin(rp / r1 * Math.sin(ap)); if (r0) p0 = d3_asin(rp / r0 * Math.sin(ap)); } if (r1) { x0 = r1 * Math.cos(a0 + p1); y0 = r1 * Math.sin(a0 + p1); x1 = r1 * Math.cos(a1 - p1); y1 = r1 * Math.sin(a1 - p1); var l1 = Math.abs(a1 - a0 - 2 * p1) <= Ï€ ? 0 : 1; if (p1 && d3_svg_arcSweep(x0, y0, x1, y1) === cw ^ l1) { var h1 = (a0 + a1) / 2; x0 = r1 * Math.cos(h1); y0 = r1 * Math.sin(h1); x1 = y1 = null; } } else { x0 = y0 = 0; } if (r0) { x2 = r0 * Math.cos(a1 - p0); y2 = r0 * Math.sin(a1 - p0); x3 = r0 * Math.cos(a0 + p0); y3 = r0 * Math.sin(a0 + p0); var l0 = Math.abs(a0 - a1 + 2 * p0) <= Ï€ ? 0 : 1; if (p0 && d3_svg_arcSweep(x2, y2, x3, y3) === 1 - cw ^ l0) { var h0 = (a0 + a1) / 2; x2 = r0 * Math.cos(h0); y2 = r0 * Math.sin(h0); x3 = y3 = null; } } else { x2 = y2 = 0; } if (da > ε && (rc = Math.min(Math.abs(r1 - r0) / 2, +cornerRadius.apply(this, arguments))) > .001) { cr = r0 < r1 ^ cw ? 0 : 1; var rc1 = rc, rc0 = rc; if (da < Ï€) { var oc = x3 == null ? [ x2, y2 ] : x1 == null ? [ x0, y0 ] : d3_geom_polygonIntersect([ x0, y0 ], [ x3, y3 ], [ x1, y1 ], [ x2, y2 ]), ax = x0 - oc[0], ay = y0 - oc[1], bx = x1 - oc[0], by = y1 - oc[1], kc = 1 / Math.sin(Math.acos((ax * bx + ay * by) / (Math.sqrt(ax * ax + ay * ay) * Math.sqrt(bx * bx + by * by))) / 2), lc = Math.sqrt(oc[0] * oc[0] + oc[1] * oc[1]); rc0 = Math.min(rc, (r0 - lc) / (kc - 1)); rc1 = Math.min(rc, (r1 - lc) / (kc + 1)); } if (x1 != null) { var t30 = d3_svg_arcCornerTangents(x3 == null ? [ x2, y2 ] : [ x3, y3 ], [ x0, y0 ], r1, rc1, cw), t12 = d3_svg_arcCornerTangents([ x1, y1 ], [ x2, y2 ], r1, rc1, cw); if (rc === rc1) { path.push("M", t30[0], "A", rc1, ",", rc1, " 0 0,", cr, " ", t30[1], "A", r1, ",", r1, " 0 ", 1 - cw ^ d3_svg_arcSweep(t30[1][0], t30[1][1], t12[1][0], t12[1][1]), ",", cw, " ", t12[1], "A", rc1, ",", rc1, " 0 0,", cr, " ", t12[0]); } else { path.push("M", t30[0], "A", rc1, ",", rc1, " 0 1,", cr, " ", t12[0]); } } else { path.push("M", x0, ",", y0); } if (x3 != null) { var t03 = d3_svg_arcCornerTangents([ x0, y0 ], [ x3, y3 ], r0, -rc0, cw), t21 = d3_svg_arcCornerTangents([ x2, y2 ], x1 == null ? [ x0, y0 ] : [ x1, y1 ], r0, -rc0, cw); if (rc === rc0) { path.push("L", t21[0], "A", rc0, ",", rc0, " 0 0,", cr, " ", t21[1], "A", r0, ",", r0, " 0 ", cw ^ d3_svg_arcSweep(t21[1][0], t21[1][1], t03[1][0], t03[1][1]), ",", 1 - cw, " ", t03[1], "A", rc0, ",", rc0, " 0 0,", cr, " ", t03[0]); } else { path.push("L", t21[0], "A", rc0, ",", rc0, " 0 0,", cr, " ", t03[0]); } } else { path.push("L", x2, ",", y2); } } else { path.push("M", x0, ",", y0); if (x1 != null) path.push("A", r1, ",", r1, " 0 ", l1, ",", cw, " ", x1, ",", y1); path.push("L", x2, ",", y2); if (x3 != null) path.push("A", r0, ",", r0, " 0 ", l0, ",", 1 - cw, " ", x3, ",", y3); } path.push("Z"); return path.join(""); } function circleSegment(r1, cw) { return "M0," + r1 + "A" + r1 + "," + r1 + " 0 1," + cw + " 0," + -r1 + "A" + r1 + "," + r1 + " 0 1," + cw + " 0," + r1; } arc.innerRadius = function(v) { if (!arguments.length) return innerRadius; innerRadius = d3_functor(v); return arc; }; arc.outerRadius = function(v) { if (!arguments.length) return outerRadius; outerRadius = d3_functor(v); return arc; }; arc.cornerRadius = function(v) { if (!arguments.length) return cornerRadius; cornerRadius = d3_functor(v); return arc; }; arc.padRadius = function(v) { if (!arguments.length) return padRadius; padRadius = v == d3_svg_arcAuto ? d3_svg_arcAuto : d3_functor(v); return arc; }; arc.startAngle = function(v) { if (!arguments.length) return startAngle; startAngle = d3_functor(v); return arc; }; arc.endAngle = function(v) { if (!arguments.length) return endAngle; endAngle = d3_functor(v); return arc; }; arc.padAngle = function(v) { if (!arguments.length) return padAngle; padAngle = d3_functor(v); return arc; }; arc.centroid = function() { var r = (+innerRadius.apply(this, arguments) + +outerRadius.apply(this, arguments)) / 2, a = (+startAngle.apply(this, arguments) + +endAngle.apply(this, arguments)) / 2 - halfÏ€; return [ Math.cos(a) * r, Math.sin(a) * r ]; }; return arc; }; var d3_svg_arcAuto = "auto"; function d3_svg_arcInnerRadius(d) { return d.innerRadius; } function d3_svg_arcOuterRadius(d) { return d.outerRadius; } function d3_svg_arcStartAngle(d) { return d.startAngle; } function d3_svg_arcEndAngle(d) { return d.endAngle; } function d3_svg_arcPadAngle(d) { return d && d.padAngle; } function d3_svg_arcSweep(x0, y0, x1, y1) { return (x0 - x1) * y0 - (y0 - y1) * x0 > 0 ? 0 : 1; } function d3_svg_arcCornerTangents(p0, p1, r1, rc, cw) { var x01 = p0[0] - p1[0], y01 = p0[1] - p1[1], lo = (cw ? rc : -rc) / Math.sqrt(x01 * x01 + y01 * y01), ox = lo * y01, oy = -lo * x01, x1 = p0[0] + ox, y1 = p0[1] + oy, x2 = p1[0] + ox, y2 = p1[1] + oy, x3 = (x1 + x2) / 2, y3 = (y1 + y2) / 2, dx = x2 - x1, dy = y2 - y1, d2 = dx * dx + dy * dy, r = r1 - rc, D = x1 * y2 - x2 * y1, d = (dy < 0 ? -1 : 1) * Math.sqrt(Math.max(0, r * r * d2 - D * D)), cx0 = (D * dy - dx * d) / d2, cy0 = (-D * dx - dy * d) / d2, cx1 = (D * dy + dx * d) / d2, cy1 = (-D * dx + dy * d) / d2, dx0 = cx0 - x3, dy0 = cy0 - y3, dx1 = cx1 - x3, dy1 = cy1 - y3; if (dx0 * dx0 + dy0 * dy0 > dx1 * dx1 + dy1 * dy1) cx0 = cx1, cy0 = cy1; return [ [ cx0 - ox, cy0 - oy ], [ cx0 * r1 / r, cy0 * r1 / r ] ]; } function d3_svg_line(projection) { var x = d3_geom_pointX, y = d3_geom_pointY, defined = d3_true, interpolate = d3_svg_lineLinear, interpolateKey = interpolate.key, tension = .7; function line(data) { var segments = [], points = [], i = -1, n = data.length, d, fx = d3_functor(x), fy = d3_functor(y); function segment() { segments.push("M", interpolate(projection(points), tension)); } while (++i < n) { if (defined.call(this, d = data[i], i)) { points.push([ +fx.call(this, d, i), +fy.call(this, d, i) ]); } else if (points.length) { segment(); points = []; } } if (points.length) segment(); return segments.length ? segments.join("") : null; } line.x = function(_) { if (!arguments.length) return x; x = _; return line; }; line.y = function(_) { if (!arguments.length) return y; y = _; return line; }; line.defined = function(_) { if (!arguments.length) return defined; defined = _; return line; }; line.interpolate = function(_) { if (!arguments.length) return interpolateKey; if (typeof _ === "function") interpolateKey = interpolate = _; else interpolateKey = (interpolate = d3_svg_lineInterpolators.get(_) || d3_svg_lineLinear).key; return line; }; line.tension = function(_) { if (!arguments.length) return tension; tension = _; return line; }; return line; } d3.svg.line = function() { return d3_svg_line(d3_identity); }; var d3_svg_lineInterpolators = d3.map({ linear: d3_svg_lineLinear, "linear-closed": d3_svg_lineLinearClosed, step: d3_svg_lineStep, "step-before": d3_svg_lineStepBefore, "step-after": d3_svg_lineStepAfter, basis: d3_svg_lineBasis, "basis-open": d3_svg_lineBasisOpen, "basis-closed": d3_svg_lineBasisClosed, bundle: d3_svg_lineBundle, cardinal: d3_svg_lineCardinal, "cardinal-open": d3_svg_lineCardinalOpen, "cardinal-closed": d3_svg_lineCardinalClosed, monotone: d3_svg_lineMonotone }); d3_svg_lineInterpolators.forEach(function(key, value) { value.key = key; value.closed = /-closed$/.test(key); }); function d3_svg_lineLinear(points) { return points.length > 1 ? points.join("L") : points + "Z"; } function d3_svg_lineLinearClosed(points) { return points.join("L") + "Z"; } function d3_svg_lineStep(points) { var i = 0, n = points.length, p = points[0], path = [ p[0], ",", p[1] ]; while (++i < n) path.push("H", (p[0] + (p = points[i])[0]) / 2, "V", p[1]); if (n > 1) path.push("H", p[0]); return path.join(""); } function d3_svg_lineStepBefore(points) { var i = 0, n = points.length, p = points[0], path = [ p[0], ",", p[1] ]; while (++i < n) path.push("V", (p = points[i])[1], "H", p[0]); return path.join(""); } function d3_svg_lineStepAfter(points) { var i = 0, n = points.length, p = points[0], path = [ p[0], ",", p[1] ]; while (++i < n) path.push("H", (p = points[i])[0], "V", p[1]); return path.join(""); } function d3_svg_lineCardinalOpen(points, tension) { return points.length < 4 ? d3_svg_lineLinear(points) : points[1] + d3_svg_lineHermite(points.slice(1, -1), d3_svg_lineCardinalTangents(points, tension)); } function d3_svg_lineCardinalClosed(points, tension) { return points.length < 3 ? d3_svg_lineLinearClosed(points) : points[0] + d3_svg_lineHermite((points.push(points[0]), points), d3_svg_lineCardinalTangents([ points[points.length - 2] ].concat(points, [ points[1] ]), tension)); } function d3_svg_lineCardinal(points, tension) { return points.length < 3 ? d3_svg_lineLinear(points) : points[0] + d3_svg_lineHermite(points, d3_svg_lineCardinalTangents(points, tension)); } function d3_svg_lineHermite(points, tangents) { if (tangents.length < 1 || points.length != tangents.length && points.length != tangents.length + 2) { return d3_svg_lineLinear(points); } var quad = points.length != tangents.length, path = "", p0 = points[0], p = points[1], t0 = tangents[0], t = t0, pi = 1; if (quad) { path += "Q" + (p[0] - t0[0] * 2 / 3) + "," + (p[1] - t0[1] * 2 / 3) + "," + p[0] + "," + p[1]; p0 = points[1]; pi = 2; } if (tangents.length > 1) { t = tangents[1]; p = points[pi]; pi++; path += "C" + (p0[0] + t0[0]) + "," + (p0[1] + t0[1]) + "," + (p[0] - t[0]) + "," + (p[1] - t[1]) + "," + p[0] + "," + p[1]; for (var i = 2; i < tangents.length; i++, pi++) { p = points[pi]; t = tangents[i]; path += "S" + (p[0] - t[0]) + "," + (p[1] - t[1]) + "," + p[0] + "," + p[1]; } } if (quad) { var lp = points[pi]; path += "Q" + (p[0] + t[0] * 2 / 3) + "," + (p[1] + t[1] * 2 / 3) + "," + lp[0] + "," + lp[1]; } return path; } function d3_svg_lineCardinalTangents(points, tension) { var tangents = [], a = (1 - tension) / 2, p0, p1 = points[0], p2 = points[1], i = 1, n = points.length; while (++i < n) { p0 = p1; p1 = p2; p2 = points[i]; tangents.push([ a * (p2[0] - p0[0]), a * (p2[1] - p0[1]) ]); } return tangents; } function d3_svg_lineBasis(points) { if (points.length < 3) return d3_svg_lineLinear(points); var i = 1, n = points.length, pi = points[0], x0 = pi[0], y0 = pi[1], px = [ x0, x0, x0, (pi = points[1])[0] ], py = [ y0, y0, y0, pi[1] ], path = [ x0, ",", y0, "L", d3_svg_lineDot4(d3_svg_lineBasisBezier3, px), ",", d3_svg_lineDot4(d3_svg_lineBasisBezier3, py) ]; points.push(points[n - 1]); while (++i <= n) { pi = points[i]; px.shift(); px.push(pi[0]); py.shift(); py.push(pi[1]); d3_svg_lineBasisBezier(path, px, py); } points.pop(); path.push("L", pi); return path.join(""); } function d3_svg_lineBasisOpen(points) { if (points.length < 4) return d3_svg_lineLinear(points); var path = [], i = -1, n = points.length, pi, px = [ 0 ], py = [ 0 ]; while (++i < 3) { pi = points[i]; px.push(pi[0]); py.push(pi[1]); } path.push(d3_svg_lineDot4(d3_svg_lineBasisBezier3, px) + "," + d3_svg_lineDot4(d3_svg_lineBasisBezier3, py)); --i; while (++i < n) { pi = points[i]; px.shift(); px.push(pi[0]); py.shift(); py.push(pi[1]); d3_svg_lineBasisBezier(path, px, py); } return path.join(""); } function d3_svg_lineBasisClosed(points) { var path, i = -1, n = points.length, m = n + 4, pi, px = [], py = []; while (++i < 4) { pi = points[i % n]; px.push(pi[0]); py.push(pi[1]); } path = [ d3_svg_lineDot4(d3_svg_lineBasisBezier3, px), ",", d3_svg_lineDot4(d3_svg_lineBasisBezier3, py) ]; --i; while (++i < m) { pi = points[i % n]; px.shift(); px.push(pi[0]); py.shift(); py.push(pi[1]); d3_svg_lineBasisBezier(path, px, py); } return path.join(""); } function d3_svg_lineBundle(points, tension) { var n = points.length - 1; if (n) { var x0 = points[0][0], y0 = points[0][1], dx = points[n][0] - x0, dy = points[n][1] - y0, i = -1, p, t; while (++i <= n) { p = points[i]; t = i / n; p[0] = tension * p[0] + (1 - tension) * (x0 + t * dx); p[1] = tension * p[1] + (1 - tension) * (y0 + t * dy); } } return d3_svg_lineBasis(points); } function d3_svg_lineDot4(a, b) { return a[0] * b[0] + a[1] * b[1] + a[2] * b[2] + a[3] * b[3]; } var d3_svg_lineBasisBezier1 = [ 0, 2 / 3, 1 / 3, 0 ], d3_svg_lineBasisBezier2 = [ 0, 1 / 3, 2 / 3, 0 ], d3_svg_lineBasisBezier3 = [ 0, 1 / 6, 2 / 3, 1 / 6 ]; function d3_svg_lineBasisBezier(path, x, y) { path.push("C", d3_svg_lineDot4(d3_svg_lineBasisBezier1, x), ",", d3_svg_lineDot4(d3_svg_lineBasisBezier1, y), ",", d3_svg_lineDot4(d3_svg_lineBasisBezier2, x), ",", d3_svg_lineDot4(d3_svg_lineBasisBezier2, y), ",", d3_svg_lineDot4(d3_svg_lineBasisBezier3, x), ",", d3_svg_lineDot4(d3_svg_lineBasisBezier3, y)); } function d3_svg_lineSlope(p0, p1) { return (p1[1] - p0[1]) / (p1[0] - p0[0]); } function d3_svg_lineFiniteDifferences(points) { var i = 0, j = points.length - 1, m = [], p0 = points[0], p1 = points[1], d = m[0] = d3_svg_lineSlope(p0, p1); while (++i < j) { m[i] = (d + (d = d3_svg_lineSlope(p0 = p1, p1 = points[i + 1]))) / 2; } m[i] = d; return m; } function d3_svg_lineMonotoneTangents(points) { var tangents = [], d, a, b, s, m = d3_svg_lineFiniteDifferences(points), i = -1, j = points.length - 1; while (++i < j) { d = d3_svg_lineSlope(points[i], points[i + 1]); if (abs(d) < ε) { m[i] = m[i + 1] = 0; } else { a = m[i] / d; b = m[i + 1] / d; s = a * a + b * b; if (s > 9) { s = d * 3 / Math.sqrt(s); m[i] = s * a; m[i + 1] = s * b; } } } i = -1; while (++i <= j) { s = (points[Math.min(j, i + 1)][0] - points[Math.max(0, i - 1)][0]) / (6 * (1 + m[i] * m[i])); tangents.push([ s || 0, m[i] * s || 0 ]); } return tangents; } function d3_svg_lineMonotone(points) { return points.length < 3 ? d3_svg_lineLinear(points) : points[0] + d3_svg_lineHermite(points, d3_svg_lineMonotoneTangents(points)); } d3.svg.line.radial = function() { var line = d3_svg_line(d3_svg_lineRadial); line.radius = line.x, delete line.x; line.angle = line.y, delete line.y; return line; }; function d3_svg_lineRadial(points) { var point, i = -1, n = points.length, r, a; while (++i < n) { point = points[i]; r = point[0]; a = point[1] - halfÏ€; point[0] = r * Math.cos(a); point[1] = r * Math.sin(a); } return points; } function d3_svg_area(projection) { var x0 = d3_geom_pointX, x1 = d3_geom_pointX, y0 = 0, y1 = d3_geom_pointY, defined = d3_true, interpolate = d3_svg_lineLinear, interpolateKey = interpolate.key, interpolateReverse = interpolate, L = "L", tension = .7; function area(data) { var segments = [], points0 = [], points1 = [], i = -1, n = data.length, d, fx0 = d3_functor(x0), fy0 = d3_functor(y0), fx1 = x0 === x1 ? function() { return x; } : d3_functor(x1), fy1 = y0 === y1 ? function() { return y; } : d3_functor(y1), x, y; function segment() { segments.push("M", interpolate(projection(points1), tension), L, interpolateReverse(projection(points0.reverse()), tension), "Z"); } while (++i < n) { if (defined.call(this, d = data[i], i)) { points0.push([ x = +fx0.call(this, d, i), y = +fy0.call(this, d, i) ]); points1.push([ +fx1.call(this, d, i), +fy1.call(this, d, i) ]); } else if (points0.length) { segment(); points0 = []; points1 = []; } } if (points0.length) segment(); return segments.length ? segments.join("") : null; } area.x = function(_) { if (!arguments.length) return x1; x0 = x1 = _; return area; }; area.x0 = function(_) { if (!arguments.length) return x0; x0 = _; return area; }; area.x1 = function(_) { if (!arguments.length) return x1; x1 = _; return area; }; area.y = function(_) { if (!arguments.length) return y1; y0 = y1 = _; return area; }; area.y0 = function(_) { if (!arguments.length) return y0; y0 = _; return area; }; area.y1 = function(_) { if (!arguments.length) return y1; y1 = _; return area; }; area.defined = function(_) { if (!arguments.length) return defined; defined = _; return area; }; area.interpolate = function(_) { if (!arguments.length) return interpolateKey; if (typeof _ === "function") interpolateKey = interpolate = _; else interpolateKey = (interpolate = d3_svg_lineInterpolators.get(_) || d3_svg_lineLinear).key; interpolateReverse = interpolate.reverse || interpolate; L = interpolate.closed ? "M" : "L"; return area; }; area.tension = function(_) { if (!arguments.length) return tension; tension = _; return area; }; return area; } d3_svg_lineStepBefore.reverse = d3_svg_lineStepAfter; d3_svg_lineStepAfter.reverse = d3_svg_lineStepBefore; d3.svg.area = function() { return d3_svg_area(d3_identity); }; d3.svg.area.radial = function() { var area = d3_svg_area(d3_svg_lineRadial); area.radius = area.x, delete area.x; area.innerRadius = area.x0, delete area.x0; area.outerRadius = area.x1, delete area.x1; area.angle = area.y, delete area.y; area.startAngle = area.y0, delete area.y0; area.endAngle = area.y1, delete area.y1; return area; }; d3.svg.chord = function() { var source = d3_source, target = d3_target, radius = d3_svg_chordRadius, startAngle = d3_svg_arcStartAngle, endAngle = d3_svg_arcEndAngle; function chord(d, i) { var s = subgroup(this, source, d, i), t = subgroup(this, target, d, i); return "M" + s.p0 + arc(s.r, s.p1, s.a1 - s.a0) + (equals(s, t) ? curve(s.r, s.p1, s.r, s.p0) : curve(s.r, s.p1, t.r, t.p0) + arc(t.r, t.p1, t.a1 - t.a0) + curve(t.r, t.p1, s.r, s.p0)) + "Z"; } function subgroup(self, f, d, i) { var subgroup = f.call(self, d, i), r = radius.call(self, subgroup, i), a0 = startAngle.call(self, subgroup, i) - halfÏ€, a1 = endAngle.call(self, subgroup, i) - halfÏ€; return { r: r, a0: a0, a1: a1, p0: [ r * Math.cos(a0), r * Math.sin(a0) ], p1: [ r * Math.cos(a1), r * Math.sin(a1) ] }; } function equals(a, b) { return a.a0 == b.a0 && a.a1 == b.a1; } function arc(r, p, a) { return "A" + r + "," + r + " 0 " + +(a > Ï€) + ",1 " + p; } function curve(r0, p0, r1, p1) { return "Q 0,0 " + p1; } chord.radius = function(v) { if (!arguments.length) return radius; radius = d3_functor(v); return chord; }; chord.source = function(v) { if (!arguments.length) return source; source = d3_functor(v); return chord; }; chord.target = function(v) { if (!arguments.length) return target; target = d3_functor(v); return chord; }; chord.startAngle = function(v) { if (!arguments.length) return startAngle; startAngle = d3_functor(v); return chord; }; chord.endAngle = function(v) { if (!arguments.length) return endAngle; endAngle = d3_functor(v); return chord; }; return chord; }; function d3_svg_chordRadius(d) { return d.radius; } d3.svg.diagonal = function() { var source = d3_source, target = d3_target, projection = d3_svg_diagonalProjection; function diagonal(d, i) { var p0 = source.call(this, d, i), p3 = target.call(this, d, i), m = (p0.y + p3.y) / 2, p = [ p0, { x: p0.x, y: m }, { x: p3.x, y: m }, p3 ]; p = p.map(projection); return "M" + p[0] + "C" + p[1] + " " + p[2] + " " + p[3]; } diagonal.source = function(x) { if (!arguments.length) return source; source = d3_functor(x); return diagonal; }; diagonal.target = function(x) { if (!arguments.length) return target; target = d3_functor(x); return diagonal; }; diagonal.projection = function(x) { if (!arguments.length) return projection; projection = x; return diagonal; }; return diagonal; }; function d3_svg_diagonalProjection(d) { return [ d.x, d.y ]; } d3.svg.diagonal.radial = function() { var diagonal = d3.svg.diagonal(), projection = d3_svg_diagonalProjection, projection_ = diagonal.projection; diagonal.projection = function(x) { return arguments.length ? projection_(d3_svg_diagonalRadialProjection(projection = x)) : projection; }; return diagonal; }; function d3_svg_diagonalRadialProjection(projection) { return function() { var d = projection.apply(this, arguments), r = d[0], a = d[1] - halfÏ€; return [ r * Math.cos(a), r * Math.sin(a) ]; }; } d3.svg.symbol = function() { var type = d3_svg_symbolType, size = d3_svg_symbolSize; function symbol(d, i) { return (d3_svg_symbols.get(type.call(this, d, i)) || d3_svg_symbolCircle)(size.call(this, d, i)); } symbol.type = function(x) { if (!arguments.length) return type; type = d3_functor(x); return symbol; }; symbol.size = function(x) { if (!arguments.length) return size; size = d3_functor(x); return symbol; }; return symbol; }; function d3_svg_symbolSize() { return 64; } function d3_svg_symbolType() { return "circle"; } function d3_svg_symbolCircle(size) { var r = Math.sqrt(size / Ï€); return "M0," + r + "A" + r + "," + r + " 0 1,1 0," + -r + "A" + r + "," + r + " 0 1,1 0," + r + "Z"; } var d3_svg_symbols = d3.map({ circle: d3_svg_symbolCircle, cross: function(size) { var r = Math.sqrt(size / 5) / 2; return "M" + -3 * r + "," + -r + "H" + -r + "V" + -3 * r + "H" + r + "V" + -r + "H" + 3 * r + "V" + r + "H" + r + "V" + 3 * r + "H" + -r + "V" + r + "H" + -3 * r + "Z"; }, diamond: function(size) { var ry = Math.sqrt(size / (2 * d3_svg_symbolTan30)), rx = ry * d3_svg_symbolTan30; return "M0," + -ry + "L" + rx + ",0" + " 0," + ry + " " + -rx + ",0" + "Z"; }, square: function(size) { var r = Math.sqrt(size) / 2; return "M" + -r + "," + -r + "L" + r + "," + -r + " " + r + "," + r + " " + -r + "," + r + "Z"; }, "triangle-down": function(size) { var rx = Math.sqrt(size / d3_svg_symbolSqrt3), ry = rx * d3_svg_symbolSqrt3 / 2; return "M0," + ry + "L" + rx + "," + -ry + " " + -rx + "," + -ry + "Z"; }, "triangle-up": function(size) { var rx = Math.sqrt(size / d3_svg_symbolSqrt3), ry = rx * d3_svg_symbolSqrt3 / 2; return "M0," + -ry + "L" + rx + "," + ry + " " + -rx + "," + ry + "Z"; } }); d3.svg.symbolTypes = d3_svg_symbols.keys(); var d3_svg_symbolSqrt3 = Math.sqrt(3), d3_svg_symbolTan30 = Math.tan(30 * d3_radians); d3_selectionPrototype.transition = function(name) { var id = d3_transitionInheritId || ++d3_transitionId, ns = d3_transitionNamespace(name), subgroups = [], subgroup, node, transition = d3_transitionInherit || { time: Date.now(), ease: d3_ease_cubicInOut, delay: 0, duration: 250 }; for (var j = -1, m = this.length; ++j < m; ) { subgroups.push(subgroup = []); for (var group = this[j], i = -1, n = group.length; ++i < n; ) { if (node = group[i]) d3_transitionNode(node, i, ns, id, transition); subgroup.push(node); } } return d3_transition(subgroups, ns, id); }; d3_selectionPrototype.interrupt = function(name) { return this.each(name == null ? d3_selection_interrupt : d3_selection_interruptNS(d3_transitionNamespace(name))); }; var d3_selection_interrupt = d3_selection_interruptNS(d3_transitionNamespace()); function d3_selection_interruptNS(ns) { return function() { var lock, activeId, active; if ((lock = this[ns]) && (active = lock[activeId = lock.active])) { active.timer.c = null; active.timer.t = NaN; if (--lock.count) delete lock[activeId]; else delete this[ns]; lock.active += .5; active.event && active.event.interrupt.call(this, this.__data__, active.index); } }; } function d3_transition(groups, ns, id) { d3_subclass(groups, d3_transitionPrototype); groups.namespace = ns; groups.id = id; return groups; } var d3_transitionPrototype = [], d3_transitionId = 0, d3_transitionInheritId, d3_transitionInherit; d3_transitionPrototype.call = d3_selectionPrototype.call; d3_transitionPrototype.empty = d3_selectionPrototype.empty; d3_transitionPrototype.node = d3_selectionPrototype.node; d3_transitionPrototype.size = d3_selectionPrototype.size; d3.transition = function(selection, name) { return selection && selection.transition ? d3_transitionInheritId ? selection.transition(name) : selection : d3.selection().transition(selection); }; d3.transition.prototype = d3_transitionPrototype; d3_transitionPrototype.select = function(selector) { var id = this.id, ns = this.namespace, subgroups = [], subgroup, subnode, node; selector = d3_selection_selector(selector); for (var j = -1, m = this.length; ++j < m; ) { subgroups.push(subgroup = []); for (var group = this[j], i = -1, n = group.length; ++i < n; ) { if ((node = group[i]) && (subnode = selector.call(node, node.__data__, i, j))) { if ("__data__" in node) subnode.__data__ = node.__data__; d3_transitionNode(subnode, i, ns, id, node[ns][id]); subgroup.push(subnode); } else { subgroup.push(null); } } } return d3_transition(subgroups, ns, id); }; d3_transitionPrototype.selectAll = function(selector) { var id = this.id, ns = this.namespace, subgroups = [], subgroup, subnodes, node, subnode, transition; selector = d3_selection_selectorAll(selector); for (var j = -1, m = this.length; ++j < m; ) { for (var group = this[j], i = -1, n = group.length; ++i < n; ) { if (node = group[i]) { transition = node[ns][id]; subnodes = selector.call(node, node.__data__, i, j); subgroups.push(subgroup = []); for (var k = -1, o = subnodes.length; ++k < o; ) { if (subnode = subnodes[k]) d3_transitionNode(subnode, k, ns, id, transition); subgroup.push(subnode); } } } } return d3_transition(subgroups, ns, id); }; d3_transitionPrototype.filter = function(filter) { var subgroups = [], subgroup, group, node; if (typeof filter !== "function") filter = d3_selection_filter(filter); for (var j = 0, m = this.length; j < m; j++) { subgroups.push(subgroup = []); for (var group = this[j], i = 0, n = group.length; i < n; i++) { if ((node = group[i]) && filter.call(node, node.__data__, i, j)) { subgroup.push(node); } } } return d3_transition(subgroups, this.namespace, this.id); }; d3_transitionPrototype.tween = function(name, tween) { var id = this.id, ns = this.namespace; if (arguments.length < 2) return this.node()[ns][id].tween.get(name); return d3_selection_each(this, tween == null ? function(node) { node[ns][id].tween.remove(name); } : function(node) { node[ns][id].tween.set(name, tween); }); }; function d3_transition_tween(groups, name, value, tween) { var id = groups.id, ns = groups.namespace; return d3_selection_each(groups, typeof value === "function" ? function(node, i, j) { node[ns][id].tween.set(name, tween(value.call(node, node.__data__, i, j))); } : (value = tween(value), function(node) { node[ns][id].tween.set(name, value); })); } d3_transitionPrototype.attr = function(nameNS, value) { if (arguments.length < 2) { for (value in nameNS) this.attr(value, nameNS[value]); return this; } var interpolate = nameNS == "transform" ? d3_interpolateTransform : d3_interpolate, name = d3.ns.qualify(nameNS); function attrNull() { this.removeAttribute(name); } function attrNullNS() { this.removeAttributeNS(name.space, name.local); } function attrTween(b) { return b == null ? attrNull : (b += "", function() { var a = this.getAttribute(name), i; return a !== b && (i = interpolate(a, b), function(t) { this.setAttribute(name, i(t)); }); }); } function attrTweenNS(b) { return b == null ? attrNullNS : (b += "", function() { var a = this.getAttributeNS(name.space, name.local), i; return a !== b && (i = interpolate(a, b), function(t) { this.setAttributeNS(name.space, name.local, i(t)); }); }); } return d3_transition_tween(this, "attr." + nameNS, value, name.local ? attrTweenNS : attrTween); }; d3_transitionPrototype.attrTween = function(nameNS, tween) { var name = d3.ns.qualify(nameNS); function attrTween(d, i) { var f = tween.call(this, d, i, this.getAttribute(name)); return f && function(t) { this.setAttribute(name, f(t)); }; } function attrTweenNS(d, i) { var f = tween.call(this, d, i, this.getAttributeNS(name.space, name.local)); return f && function(t) { this.setAttributeNS(name.space, name.local, f(t)); }; } return this.tween("attr." + nameNS, name.local ? attrTweenNS : attrTween); }; d3_transitionPrototype.style = function(name, value, priority) { var n = arguments.length; if (n < 3) { if (typeof name !== "string") { if (n < 2) value = ""; for (priority in name) this.style(priority, name[priority], value); return this; } priority = ""; } function styleNull() { this.style.removeProperty(name); } function styleString(b) { return b == null ? styleNull : (b += "", function() { var a = d3_window(this).getComputedStyle(this, null).getPropertyValue(name), i; return a !== b && (i = d3_interpolate(a, b), function(t) { this.style.setProperty(name, i(t), priority); }); }); } return d3_transition_tween(this, "style." + name, value, styleString); }; d3_transitionPrototype.styleTween = function(name, tween, priority) { if (arguments.length < 3) priority = ""; function styleTween(d, i) { var f = tween.call(this, d, i, d3_window(this).getComputedStyle(this, null).getPropertyValue(name)); return f && function(t) { this.style.setProperty(name, f(t), priority); }; } return this.tween("style." + name, styleTween); }; d3_transitionPrototype.text = function(value) { return d3_transition_tween(this, "text", value, d3_transition_text); }; function d3_transition_text(b) { if (b == null) b = ""; return function() { this.textContent = b; }; } d3_transitionPrototype.remove = function() { var ns = this.namespace; return this.each("end.transition", function() { var p; if (this[ns].count < 2 && (p = this.parentNode)) p.removeChild(this); }); }; d3_transitionPrototype.ease = function(value) { var id = this.id, ns = this.namespace; if (arguments.length < 1) return this.node()[ns][id].ease; if (typeof value !== "function") value = d3.ease.apply(d3, arguments); return d3_selection_each(this, function(node) { node[ns][id].ease = value; }); }; d3_transitionPrototype.delay = function(value) { var id = this.id, ns = this.namespace; if (arguments.length < 1) return this.node()[ns][id].delay; return d3_selection_each(this, typeof value === "function" ? function(node, i, j) { node[ns][id].delay = +value.call(node, node.__data__, i, j); } : (value = +value, function(node) { node[ns][id].delay = value; })); }; d3_transitionPrototype.duration = function(value) { var id = this.id, ns = this.namespace; if (arguments.length < 1) return this.node()[ns][id].duration; return d3_selection_each(this, typeof value === "function" ? function(node, i, j) { node[ns][id].duration = Math.max(1, value.call(node, node.__data__, i, j)); } : (value = Math.max(1, value), function(node) { node[ns][id].duration = value; })); }; d3_transitionPrototype.each = function(type, listener) { var id = this.id, ns = this.namespace; if (arguments.length < 2) { var inherit = d3_transitionInherit, inheritId = d3_transitionInheritId; try { d3_transitionInheritId = id; d3_selection_each(this, function(node, i, j) { d3_transitionInherit = node[ns][id]; type.call(node, node.__data__, i, j); }); } finally { d3_transitionInherit = inherit; d3_transitionInheritId = inheritId; } } else { d3_selection_each(this, function(node) { var transition = node[ns][id]; (transition.event || (transition.event = d3.dispatch("start", "end", "interrupt"))).on(type, listener); }); } return this; }; d3_transitionPrototype.transition = function() { var id0 = this.id, id1 = ++d3_transitionId, ns = this.namespace, subgroups = [], subgroup, group, node, transition; for (var j = 0, m = this.length; j < m; j++) { subgroups.push(subgroup = []); for (var group = this[j], i = 0, n = group.length; i < n; i++) { if (node = group[i]) { transition = node[ns][id0]; d3_transitionNode(node, i, ns, id1, { time: transition.time, ease: transition.ease, delay: transition.delay + transition.duration, duration: transition.duration }); } subgroup.push(node); } } return d3_transition(subgroups, ns, id1); }; function d3_transitionNamespace(name) { return name == null ? "__transition__" : "__transition_" + name + "__"; } function d3_transitionNode(node, i, ns, id, inherit) { var lock = node[ns] || (node[ns] = { active: 0, count: 0 }), transition = lock[id], time, timer, duration, ease, tweens; function schedule(elapsed) { var delay = transition.delay; timer.t = delay + time; if (delay <= elapsed) return start(elapsed - delay); timer.c = start; } function start(elapsed) { var activeId = lock.active, active = lock[activeId]; if (active) { active.timer.c = null; active.timer.t = NaN; --lock.count; delete lock[activeId]; active.event && active.event.interrupt.call(node, node.__data__, active.index); } for (var cancelId in lock) { if (+cancelId < id) { var cancel = lock[cancelId]; cancel.timer.c = null; cancel.timer.t = NaN; --lock.count; delete lock[cancelId]; } } timer.c = tick; d3_timer(function() { if (timer.c && tick(elapsed || 1)) { timer.c = null; timer.t = NaN; } return 1; }, 0, time); lock.active = id; transition.event && transition.event.start.call(node, node.__data__, i); tweens = []; transition.tween.forEach(function(key, value) { if (value = value.call(node, node.__data__, i)) { tweens.push(value); } }); ease = transition.ease; duration = transition.duration; } function tick(elapsed) { var t = elapsed / duration, e = ease(t), n = tweens.length; while (n > 0) { tweens[--n].call(node, e); } if (t >= 1) { transition.event && transition.event.end.call(node, node.__data__, i); if (--lock.count) delete lock[id]; else delete node[ns]; return 1; } } if (!transition) { time = inherit.time; timer = d3_timer(schedule, 0, time); transition = lock[id] = { tween: new d3_Map(), time: time, timer: timer, delay: inherit.delay, duration: inherit.duration, ease: inherit.ease, index: i }; inherit = null; ++lock.count; } } d3.svg.axis = function() { var scale = d3.scale.linear(), orient = d3_svg_axisDefaultOrient, innerTickSize = 6, outerTickSize = 6, tickPadding = 3, tickArguments_ = [ 10 ], tickValues = null, tickFormat_; function axis(g) { g.each(function() { var g = d3.select(this); var scale0 = this.__chart__ || scale, scale1 = this.__chart__ = scale.copy(); var ticks = tickValues == null ? scale1.ticks ? scale1.ticks.apply(scale1, tickArguments_) : scale1.domain() : tickValues, tickFormat = tickFormat_ == null ? scale1.tickFormat ? scale1.tickFormat.apply(scale1, tickArguments_) : d3_identity : tickFormat_, tick = g.selectAll(".tick").data(ticks, scale1), tickEnter = tick.enter().insert("g", ".domain").attr("class", "tick").style("opacity", ε), tickExit = d3.transition(tick.exit()).style("opacity", ε).remove(), tickUpdate = d3.transition(tick.order()).style("opacity", 1), tickSpacing = Math.max(innerTickSize, 0) + tickPadding, tickTransform; var range = d3_scaleRange(scale1), path = g.selectAll(".domain").data([ 0 ]), pathUpdate = (path.enter().append("path").attr("class", "domain"), d3.transition(path)); tickEnter.append("line"); tickEnter.append("text"); var lineEnter = tickEnter.select("line"), lineUpdate = tickUpdate.select("line"), text = tick.select("text").text(tickFormat), textEnter = tickEnter.select("text"), textUpdate = tickUpdate.select("text"), sign = orient === "top" || orient === "left" ? -1 : 1, x1, x2, y1, y2; if (orient === "bottom" || orient === "top") { tickTransform = d3_svg_axisX, x1 = "x", y1 = "y", x2 = "x2", y2 = "y2"; text.attr("dy", sign < 0 ? "0em" : ".71em").style("text-anchor", "middle"); pathUpdate.attr("d", "M" + range[0] + "," + sign * outerTickSize + "V0H" + range[1] + "V" + sign * outerTickSize); } else { tickTransform = d3_svg_axisY, x1 = "y", y1 = "x", x2 = "y2", y2 = "x2"; text.attr("dy", ".32em").style("text-anchor", sign < 0 ? "end" : "start"); pathUpdate.attr("d", "M" + sign * outerTickSize + "," + range[0] + "H0V" + range[1] + "H" + sign * outerTickSize); } lineEnter.attr(y2, sign * innerTickSize); textEnter.attr(y1, sign * tickSpacing); lineUpdate.attr(x2, 0).attr(y2, sign * innerTickSize); textUpdate.attr(x1, 0).attr(y1, sign * tickSpacing); if (scale1.rangeBand) { var x = scale1, dx = x.rangeBand() / 2; scale0 = scale1 = function(d) { return x(d) + dx; }; } else if (scale0.rangeBand) { scale0 = scale1; } else { tickExit.call(tickTransform, scale1, scale0); } tickEnter.call(tickTransform, scale0, scale1); tickUpdate.call(tickTransform, scale1, scale1); }); } axis.scale = function(x) { if (!arguments.length) return scale; scale = x; return axis; }; axis.orient = function(x) { if (!arguments.length) return orient; orient = x in d3_svg_axisOrients ? x + "" : d3_svg_axisDefaultOrient; return axis; }; axis.ticks = function() { if (!arguments.length) return tickArguments_; tickArguments_ = d3_array(arguments); return axis; }; axis.tickValues = function(x) { if (!arguments.length) return tickValues; tickValues = x; return axis; }; axis.tickFormat = function(x) { if (!arguments.length) return tickFormat_; tickFormat_ = x; return axis; }; axis.tickSize = function(x) { var n = arguments.length; if (!n) return innerTickSize; innerTickSize = +x; outerTickSize = +arguments[n - 1]; return axis; }; axis.innerTickSize = function(x) { if (!arguments.length) return innerTickSize; innerTickSize = +x; return axis; }; axis.outerTickSize = function(x) { if (!arguments.length) return outerTickSize; outerTickSize = +x; return axis; }; axis.tickPadding = function(x) { if (!arguments.length) return tickPadding; tickPadding = +x; return axis; }; axis.tickSubdivide = function() { return arguments.length && axis; }; return axis; }; var d3_svg_axisDefaultOrient = "bottom", d3_svg_axisOrients = { top: 1, right: 1, bottom: 1, left: 1 }; function d3_svg_axisX(selection, x0, x1) { selection.attr("transform", function(d) { var v0 = x0(d); return "translate(" + (isFinite(v0) ? v0 : x1(d)) + ",0)"; }); } function d3_svg_axisY(selection, y0, y1) { selection.attr("transform", function(d) { var v0 = y0(d); return "translate(0," + (isFinite(v0) ? v0 : y1(d)) + ")"; }); } d3.svg.brush = function() { var event = d3_eventDispatch(brush, "brushstart", "brush", "brushend"), x = null, y = null, xExtent = [ 0, 0 ], yExtent = [ 0, 0 ], xExtentDomain, yExtentDomain, xClamp = true, yClamp = true, resizes = d3_svg_brushResizes[0]; function brush(g) { g.each(function() { var g = d3.select(this).style("pointer-events", "all").style("-webkit-tap-highlight-color", "rgba(0,0,0,0)").on("mousedown.brush", brushstart).on("touchstart.brush", brushstart); var background = g.selectAll(".background").data([ 0 ]); background.enter().append("rect").attr("class", "background").style("visibility", "hidden").style("cursor", "crosshair"); g.selectAll(".extent").data([ 0 ]).enter().append("rect").attr("class", "extent").style("cursor", "move"); var resize = g.selectAll(".resize").data(resizes, d3_identity); resize.exit().remove(); resize.enter().append("g").attr("class", function(d) { return "resize " + d; }).style("cursor", function(d) { return d3_svg_brushCursor[d]; }).append("rect").attr("x", function(d) { return /[ew]$/.test(d) ? -3 : null; }).attr("y", function(d) { return /^[ns]/.test(d) ? -3 : null; }).attr("width", 6).attr("height", 6).style("visibility", "hidden"); resize.style("display", brush.empty() ? "none" : null); var gUpdate = d3.transition(g), backgroundUpdate = d3.transition(background), range; if (x) { range = d3_scaleRange(x); backgroundUpdate.attr("x", range[0]).attr("width", range[1] - range[0]); redrawX(gUpdate); } if (y) { range = d3_scaleRange(y); backgroundUpdate.attr("y", range[0]).attr("height", range[1] - range[0]); redrawY(gUpdate); } redraw(gUpdate); }); } brush.event = function(g) { g.each(function() { var event_ = event.of(this, arguments), extent1 = { x: xExtent, y: yExtent, i: xExtentDomain, j: yExtentDomain }, extent0 = this.__chart__ || extent1; this.__chart__ = extent1; if (d3_transitionInheritId) { d3.select(this).transition().each("start.brush", function() { xExtentDomain = extent0.i; yExtentDomain = extent0.j; xExtent = extent0.x; yExtent = extent0.y; event_({ type: "brushstart" }); }).tween("brush:brush", function() { var xi = d3_interpolateArray(xExtent, extent1.x), yi = d3_interpolateArray(yExtent, extent1.y); xExtentDomain = yExtentDomain = null; return function(t) { xExtent = extent1.x = xi(t); yExtent = extent1.y = yi(t); event_({ type: "brush", mode: "resize" }); }; }).each("end.brush", function() { xExtentDomain = extent1.i; yExtentDomain = extent1.j; event_({ type: "brush", mode: "resize" }); event_({ type: "brushend" }); }); } else { event_({ type: "brushstart" }); event_({ type: "brush", mode: "resize" }); event_({ type: "brushend" }); } }); }; function redraw(g) { g.selectAll(".resize").attr("transform", function(d) { return "translate(" + xExtent[+/e$/.test(d)] + "," + yExtent[+/^s/.test(d)] + ")"; }); } function redrawX(g) { g.select(".extent").attr("x", xExtent[0]); g.selectAll(".extent,.n>rect,.s>rect").attr("width", xExtent[1] - xExtent[0]); } function redrawY(g) { g.select(".extent").attr("y", yExtent[0]); g.selectAll(".extent,.e>rect,.w>rect").attr("height", yExtent[1] - yExtent[0]); } function brushstart() { var target = this, eventTarget = d3.select(d3.event.target), event_ = event.of(target, arguments), g = d3.select(target), resizing = eventTarget.datum(), resizingX = !/^(n|s)$/.test(resizing) && x, resizingY = !/^(e|w)$/.test(resizing) && y, dragging = eventTarget.classed("extent"), dragRestore = d3_event_dragSuppress(target), center, origin = d3.mouse(target), offset; var w = d3.select(d3_window(target)).on("keydown.brush", keydown).on("keyup.brush", keyup); if (d3.event.changedTouches) { w.on("touchmove.brush", brushmove).on("touchend.brush", brushend); } else { w.on("mousemove.brush", brushmove).on("mouseup.brush", brushend); } g.interrupt().selectAll("*").interrupt(); if (dragging) { origin[0] = xExtent[0] - origin[0]; origin[1] = yExtent[0] - origin[1]; } else if (resizing) { var ex = +/w$/.test(resizing), ey = +/^n/.test(resizing); offset = [ xExtent[1 - ex] - origin[0], yExtent[1 - ey] - origin[1] ]; origin[0] = xExtent[ex]; origin[1] = yExtent[ey]; } else if (d3.event.altKey) center = origin.slice(); g.style("pointer-events", "none").selectAll(".resize").style("display", null); d3.select("body").style("cursor", eventTarget.style("cursor")); event_({ type: "brushstart" }); brushmove(); function keydown() { if (d3.event.keyCode == 32) { if (!dragging) { center = null; origin[0] -= xExtent[1]; origin[1] -= yExtent[1]; dragging = 2; } d3_eventPreventDefault(); } } function keyup() { if (d3.event.keyCode == 32 && dragging == 2) { origin[0] += xExtent[1]; origin[1] += yExtent[1]; dragging = 0; d3_eventPreventDefault(); } } function brushmove() { var point = d3.mouse(target), moved = false; if (offset) { point[0] += offset[0]; point[1] += offset[1]; } if (!dragging) { if (d3.event.altKey) { if (!center) center = [ (xExtent[0] + xExtent[1]) / 2, (yExtent[0] + yExtent[1]) / 2 ]; origin[0] = xExtent[+(point[0] < center[0])]; origin[1] = yExtent[+(point[1] < center[1])]; } else center = null; } if (resizingX && move1(point, x, 0)) { redrawX(g); moved = true; } if (resizingY && move1(point, y, 1)) { redrawY(g); moved = true; } if (moved) { redraw(g); event_({ type: "brush", mode: dragging ? "move" : "resize" }); } } function move1(point, scale, i) { var range = d3_scaleRange(scale), r0 = range[0], r1 = range[1], position = origin[i], extent = i ? yExtent : xExtent, size = extent[1] - extent[0], min, max; if (dragging) { r0 -= position; r1 -= size + position; } min = (i ? yClamp : xClamp) ? Math.max(r0, Math.min(r1, point[i])) : point[i]; if (dragging) { max = (min += position) + size; } else { if (center) position = Math.max(r0, Math.min(r1, 2 * center[i] - min)); if (position < min) { max = min; min = position; } else { max = position; } } if (extent[0] != min || extent[1] != max) { if (i) yExtentDomain = null; else xExtentDomain = null; extent[0] = min; extent[1] = max; return true; } } function brushend() { brushmove(); g.style("pointer-events", "all").selectAll(".resize").style("display", brush.empty() ? "none" : null); d3.select("body").style("cursor", null); w.on("mousemove.brush", null).on("mouseup.brush", null).on("touchmove.brush", null).on("touchend.brush", null).on("keydown.brush", null).on("keyup.brush", null); dragRestore(); event_({ type: "brushend" }); } } brush.x = function(z) { if (!arguments.length) return x; x = z; resizes = d3_svg_brushResizes[!x << 1 | !y]; return brush; }; brush.y = function(z) { if (!arguments.length) return y; y = z; resizes = d3_svg_brushResizes[!x << 1 | !y]; return brush; }; brush.clamp = function(z) { if (!arguments.length) return x && y ? [ xClamp, yClamp ] : x ? xClamp : y ? yClamp : null; if (x && y) xClamp = !!z[0], yClamp = !!z[1]; else if (x) xClamp = !!z; else if (y) yClamp = !!z; return brush; }; brush.extent = function(z) { var x0, x1, y0, y1, t; if (!arguments.length) { if (x) { if (xExtentDomain) { x0 = xExtentDomain[0], x1 = xExtentDomain[1]; } else { x0 = xExtent[0], x1 = xExtent[1]; if (x.invert) x0 = x.invert(x0), x1 = x.invert(x1); if (x1 < x0) t = x0, x0 = x1, x1 = t; } } if (y) { if (yExtentDomain) { y0 = yExtentDomain[0], y1 = yExtentDomain[1]; } else { y0 = yExtent[0], y1 = yExtent[1]; if (y.invert) y0 = y.invert(y0), y1 = y.invert(y1); if (y1 < y0) t = y0, y0 = y1, y1 = t; } } return x && y ? [ [ x0, y0 ], [ x1, y1 ] ] : x ? [ x0, x1 ] : y && [ y0, y1 ]; } if (x) { x0 = z[0], x1 = z[1]; if (y) x0 = x0[0], x1 = x1[0]; xExtentDomain = [ x0, x1 ]; if (x.invert) x0 = x(x0), x1 = x(x1); if (x1 < x0) t = x0, x0 = x1, x1 = t; if (x0 != xExtent[0] || x1 != xExtent[1]) xExtent = [ x0, x1 ]; } if (y) { y0 = z[0], y1 = z[1]; if (x) y0 = y0[1], y1 = y1[1]; yExtentDomain = [ y0, y1 ]; if (y.invert) y0 = y(y0), y1 = y(y1); if (y1 < y0) t = y0, y0 = y1, y1 = t; if (y0 != yExtent[0] || y1 != yExtent[1]) yExtent = [ y0, y1 ]; } return brush; }; brush.clear = function() { if (!brush.empty()) { xExtent = [ 0, 0 ], yExtent = [ 0, 0 ]; xExtentDomain = yExtentDomain = null; } return brush; }; brush.empty = function() { return !!x && xExtent[0] == xExtent[1] || !!y && yExtent[0] == yExtent[1]; }; return d3.rebind(brush, event, "on"); }; var d3_svg_brushCursor = { n: "ns-resize", e: "ew-resize", s: "ns-resize", w: "ew-resize", nw: "nwse-resize", ne: "nesw-resize", se: "nwse-resize", sw: "nesw-resize" }; var d3_svg_brushResizes = [ [ "n", "e", "s", "w", "nw", "ne", "se", "sw" ], [ "e", "w" ], [ "n", "s" ], [] ]; var d3_time_format = d3_time.format = d3_locale_enUS.timeFormat; var d3_time_formatUtc = d3_time_format.utc; var d3_time_formatIso = d3_time_formatUtc("%Y-%m-%dT%H:%M:%S.%LZ"); d3_time_format.iso = Date.prototype.toISOString && +new Date("2000-01-01T00:00:00.000Z") ? d3_time_formatIsoNative : d3_time_formatIso; function d3_time_formatIsoNative(date) { return date.toISOString(); } d3_time_formatIsoNative.parse = function(string) { var date = new Date(string); return isNaN(date) ? null : date; }; d3_time_formatIsoNative.toString = d3_time_formatIso.toString; d3_time.second = d3_time_interval(function(date) { return new d3_date(Math.floor(date / 1e3) * 1e3); }, function(date, offset) { date.setTime(date.getTime() + Math.floor(offset) * 1e3); }, function(date) { return date.getSeconds(); }); d3_time.seconds = d3_time.second.range; d3_time.seconds.utc = d3_time.second.utc.range; d3_time.minute = d3_time_interval(function(date) { return new d3_date(Math.floor(date / 6e4) * 6e4); }, function(date, offset) { date.setTime(date.getTime() + Math.floor(offset) * 6e4); }, function(date) { return date.getMinutes(); }); d3_time.minutes = d3_time.minute.range; d3_time.minutes.utc = d3_time.minute.utc.range; d3_time.hour = d3_time_interval(function(date) { var timezone = date.getTimezoneOffset() / 60; return new d3_date((Math.floor(date / 36e5 - timezone) + timezone) * 36e5); }, function(date, offset) { date.setTime(date.getTime() + Math.floor(offset) * 36e5); }, function(date) { return date.getHours(); }); d3_time.hours = d3_time.hour.range; d3_time.hours.utc = d3_time.hour.utc.range; d3_time.month = d3_time_interval(function(date) { date = d3_time.day(date); date.setDate(1); return date; }, function(date, offset) { date.setMonth(date.getMonth() + offset); }, function(date) { return date.getMonth(); }); d3_time.months = d3_time.month.range; d3_time.months.utc = d3_time.month.utc.range; function d3_time_scale(linear, methods, format) { function scale(x) { return linear(x); } scale.invert = function(x) { return d3_time_scaleDate(linear.invert(x)); }; scale.domain = function(x) { if (!arguments.length) return linear.domain().map(d3_time_scaleDate); linear.domain(x); return scale; }; function tickMethod(extent, count) { var span = extent[1] - extent[0], target = span / count, i = d3.bisect(d3_time_scaleSteps, target); return i == d3_time_scaleSteps.length ? [ methods.year, d3_scale_linearTickRange(extent.map(function(d) { return d / 31536e6; }), count)[2] ] : !i ? [ d3_time_scaleMilliseconds, d3_scale_linearTickRange(extent, count)[2] ] : methods[target / d3_time_scaleSteps[i - 1] < d3_time_scaleSteps[i] / target ? i - 1 : i]; } scale.nice = function(interval, skip) { var domain = scale.domain(), extent = d3_scaleExtent(domain), method = interval == null ? tickMethod(extent, 10) : typeof interval === "number" && tickMethod(extent, interval); if (method) interval = method[0], skip = method[1]; function skipped(date) { return !isNaN(date) && !interval.range(date, d3_time_scaleDate(+date + 1), skip).length; } return scale.domain(d3_scale_nice(domain, skip > 1 ? { floor: function(date) { while (skipped(date = interval.floor(date))) date = d3_time_scaleDate(date - 1); return date; }, ceil: function(date) { while (skipped(date = interval.ceil(date))) date = d3_time_scaleDate(+date + 1); return date; } } : interval)); }; scale.ticks = function(interval, skip) { var extent = d3_scaleExtent(scale.domain()), method = interval == null ? tickMethod(extent, 10) : typeof interval === "number" ? tickMethod(extent, interval) : !interval.range && [ { range: interval }, skip ]; if (method) interval = method[0], skip = method[1]; return interval.range(extent[0], d3_time_scaleDate(+extent[1] + 1), skip < 1 ? 1 : skip); }; scale.tickFormat = function() { return format; }; scale.copy = function() { return d3_time_scale(linear.copy(), methods, format); }; return d3_scale_linearRebind(scale, linear); } function d3_time_scaleDate(t) { return new Date(t); } var d3_time_scaleSteps = [ 1e3, 5e3, 15e3, 3e4, 6e4, 3e5, 9e5, 18e5, 36e5, 108e5, 216e5, 432e5, 864e5, 1728e5, 6048e5, 2592e6, 7776e6, 31536e6 ]; var d3_time_scaleLocalMethods = [ [ d3_time.second, 1 ], [ d3_time.second, 5 ], [ d3_time.second, 15 ], [ d3_time.second, 30 ], [ d3_time.minute, 1 ], [ d3_time.minute, 5 ], [ d3_time.minute, 15 ], [ d3_time.minute, 30 ], [ d3_time.hour, 1 ], [ d3_time.hour, 3 ], [ d3_time.hour, 6 ], [ d3_time.hour, 12 ], [ d3_time.day, 1 ], [ d3_time.day, 2 ], [ d3_time.week, 1 ], [ d3_time.month, 1 ], [ d3_time.month, 3 ], [ d3_time.year, 1 ] ]; var d3_time_scaleLocalFormat = d3_time_format.multi([ [ ".%L", function(d) { return d.getMilliseconds(); } ], [ ":%S", function(d) { return d.getSeconds(); } ], [ "%I:%M", function(d) { return d.getMinutes(); } ], [ "%I %p", function(d) { return d.getHours(); } ], [ "%a %d", function(d) { return d.getDay() && d.getDate() != 1; } ], [ "%b %d", function(d) { return d.getDate() != 1; } ], [ "%B", function(d) { return d.getMonth(); } ], [ "%Y", d3_true ] ]); var d3_time_scaleMilliseconds = { range: function(start, stop, step) { return d3.range(Math.ceil(start / step) * step, +stop, step).map(d3_time_scaleDate); }, floor: d3_identity, ceil: d3_identity }; d3_time_scaleLocalMethods.year = d3_time.year; d3_time.scale = function() { return d3_time_scale(d3.scale.linear(), d3_time_scaleLocalMethods, d3_time_scaleLocalFormat); }; var d3_time_scaleUtcMethods = d3_time_scaleLocalMethods.map(function(m) { return [ m[0].utc, m[1] ]; }); var d3_time_scaleUtcFormat = d3_time_formatUtc.multi([ [ ".%L", function(d) { return d.getUTCMilliseconds(); } ], [ ":%S", function(d) { return d.getUTCSeconds(); } ], [ "%I:%M", function(d) { return d.getUTCMinutes(); } ], [ "%I %p", function(d) { return d.getUTCHours(); } ], [ "%a %d", function(d) { return d.getUTCDay() && d.getUTCDate() != 1; } ], [ "%b %d", function(d) { return d.getUTCDate() != 1; } ], [ "%B", function(d) { return d.getUTCMonth(); } ], [ "%Y", d3_true ] ]); d3_time_scaleUtcMethods.year = d3_time.year.utc; d3_time.scale.utc = function() { return d3_time_scale(d3.scale.linear(), d3_time_scaleUtcMethods, d3_time_scaleUtcFormat); }; d3.text = d3_xhrType(function(request) { return request.responseText; }); d3.json = function(url, callback) { return d3_xhr(url, "application/json", d3_json, callback); }; function d3_json(request) { return JSON.parse(request.responseText); } d3.html = function(url, callback) { return d3_xhr(url, "text/html", d3_html, callback); }; function d3_html(request) { var range = d3_document.createRange(); range.selectNode(d3_document.body); return range.createContextualFragment(request.responseText); } d3.xml = d3_xhrType(function(request) { return request.responseXML; }); if (true) this.d3 = d3, !(__WEBPACK_AMD_DEFINE_FACTORY__ = (d3), __WEBPACK_AMD_DEFINE_RESULT__ = (typeof __WEBPACK_AMD_DEFINE_FACTORY__ === 'function' ? (__WEBPACK_AMD_DEFINE_FACTORY__.call(exports, __webpack_require__, exports, module)) : __WEBPACK_AMD_DEFINE_FACTORY__), __WEBPACK_AMD_DEFINE_RESULT__ !== undefined && (module.exports = __WEBPACK_AMD_DEFINE_RESULT__)); else if (typeof module === "object" && module.exports) module.exports = d3; else this.d3 = d3; }(); /***/ }), /* 2 */ /***/ (function(module, exports, __webpack_require__) { "use strict"; /** * Copyright 2012-2019, Plotly, Inc. * All rights reserved. * * This source code is licensed under the MIT license found in the * LICENSE file in the root directory of this source tree. */ var isArray = Array.isArray; // IE9 fallbacks var ab = (typeof ArrayBuffer === 'undefined' || !ArrayBuffer.isView) ? {isView: function() { return false; }} : ArrayBuffer; var dv = (typeof DataView === 'undefined') ? function() {} : DataView; function isTypedArray(a) { return ab.isView(a) && !(a instanceof dv); } exports.isTypedArray = isTypedArray; function isArrayOrTypedArray(a) { return isArray(a) || isTypedArray(a); } exports.isArrayOrTypedArray = isArrayOrTypedArray; /* * Test whether an input object is 1D. * * Assumes we already know the object is an array. * * Looks only at the first element, if the dimensionality is * not consistent we won't figure that out here. */ function isArray1D(a) { return !isArrayOrTypedArray(a[0]); } exports.isArray1D = isArray1D; /* * Ensures an array has the right amount of storage space. If it doesn't * exist, it creates an array. If it does exist, it returns it if too * short or truncates it in-place. * * The goal is to just reuse memory to avoid a bit of excessive garbage * collection. */ exports.ensureArray = function(out, n) { // TODO: typed array support here? This is only used in // traces/carpet/compute_control_points if(!isArray(out)) out = []; // If too long, truncate. (If too short, it will grow // automatically so we don't care about that case) out.length = n; return out; }; /* * TypedArray-compatible concatenation of n arrays * if all arrays are the same type it will preserve that type, * otherwise it falls back on Array. * Also tries to avoid copying, in case one array has zero length * But never mutates an existing array */ exports.concat = function() { var args = []; var allArray = true; var totalLen = 0; var _constructor, arg0, i, argi, posi, leni, out, j; for(i = 0; i < arguments.length; i++) { argi = arguments[i]; leni = argi.length; if(leni) { if(arg0) args.push(argi); else { arg0 = argi; posi = leni; } if(isArray(argi)) { _constructor = false; } else { allArray = false; if(!totalLen) { _constructor = argi.constructor; } else if(_constructor !== argi.constructor) { // TODO: in principle we could upgrade here, // ie keep typed array but convert all to Float64Array? _constructor = false; } } totalLen += leni; } } if(!totalLen) return []; if(!args.length) return arg0; if(allArray) return arg0.concat.apply(arg0, args); if(_constructor) { // matching typed arrays out = new _constructor(totalLen); out.set(arg0); for(i = 0; i < args.length; i++) { argi = args[i]; out.set(argi, posi); posi += argi.length; } return out; } // mismatched types or Array + typed out = new Array(totalLen); for(j = 0; j < arg0.length; j++) out[j] = arg0[j]; for(i = 0; i < args.length; i++) { argi = args[i]; for(j = 0; j < argi.length; j++) out[posi + j] = argi[j]; posi += j; } return out; }; exports.maxRowLength = function(z) { return _rowLength(z, Math.max, 0); }; exports.minRowLength = function(z) { return _rowLength(z, Math.min, Infinity); }; function _rowLength(z, fn, len0) { if(isArrayOrTypedArray(z)) { if(isArrayOrTypedArray(z[0])) { var len = len0; for(var i = 0; i < z.length; i++) { len = fn(len, z[i].length); } return len; } else { return z.length; } } return 0; } /***/ }), /* 3 */ /***/ (function(module, exports, __webpack_require__) { "use strict"; /** * Copyright 2012-2019, Plotly, Inc. * All rights reserved. * * This source code is licensed under the MIT license found in the * LICENSE file in the root directory of this source tree. */ /** * sanitized modulus function that always returns in the range [0, d) * rather than (-d, 0] if v is negative */ function mod(v, d) { var out = v % d; return out < 0 ? out + d : out; } /** * sanitized modulus function that always returns in the range [-d/2, d/2] * rather than (-d, 0] if v is negative */ function modHalf(v, d) { return Math.abs(v) > (d / 2) ? v - Math.round(v / d) * d : v; } module.exports = { mod: mod, modHalf: modHalf }; /***/ }), /* 4 */ /***/ (function(module, exports, __webpack_require__) { "use strict"; /** * Copyright 2012-2019, Plotly, Inc. * All rights reserved. * * This source code is licensed under the MIT license found in the * LICENSE file in the root directory of this source tree. */ /* eslint-disable no-console */ var dfltConfig = __webpack_require__(39).dfltConfig; var loggers = module.exports = {}; /** * ------------------------------------------ * debugging tools * ------------------------------------------ */ loggers.log = function() { if(dfltConfig.logging > 1) { var messages = ['LOG:']; for(var i = 0; i < arguments.length; i++) { messages.push(arguments[i]); } apply(console.trace || console.log, messages); } }; loggers.warn = function() { if(dfltConfig.logging > 0) { var messages = ['WARN:']; for(var i = 0; i < arguments.length; i++) { messages.push(arguments[i]); } apply(console.trace || console.log, messages); } }; loggers.error = function() { if(dfltConfig.logging > 0) { var messages = ['ERROR:']; for(var i = 0; i < arguments.length; i++) { messages.push(arguments[i]); } apply(console.error, messages); } }; /* * Robust apply, for IE9 where console.log doesn't support * apply like other functions do */ function apply(f, args) { if(f && f.apply) { try { // `this` should always be console, since here we're always // applying a method of the console object. f.apply(console, args); return; } catch(e) { /* in case apply failed, fall back on the code below */ } } // no apply - just try calling the function on each arg independently for(var i = 0; i < args.length; i++) { try { f(args[i]); } catch(e) { // still fails - last resort simple console.log console.log(args[i]); } } } /***/ }), /* 5 */ /***/ (function(module, exports, __webpack_require__) { "use strict"; /** * Copyright 2012-2019, Plotly, Inc. * All rights reserved. * * This source code is licensed under the MIT license found in the * LICENSE file in the root directory of this source tree. */ // more info: http://stackoverflow.com/questions/18531624/isplainobject-thing module.exports = function isPlainObject(obj) { // We need to be a little less strict in the `imagetest` container because // of how async image requests are handled. // // N.B. isPlainObject(new Constructor()) will return true in `imagetest` if(window && window.process && window.process.versions) { return Object.prototype.toString.call(obj) === '[object Object]'; } return ( Object.prototype.toString.call(obj) === '[object Object]' && Object.getPrototypeOf(obj) === Object.prototype ); }; /***/ }), /* 6 */ /***/ (function(module, exports, __webpack_require__) { "use strict"; /** * Copyright 2012-2019, Plotly, Inc. * All rights reserved. * * This source code is licensed under the MIT license found in the * LICENSE file in the root directory of this source tree. */ var isPlainObject = __webpack_require__(5); var isArray = Array.isArray; function primitivesLoopSplice(source, target) { var i, value; for(i = 0; i < source.length; i++) { value = source[i]; if(value !== null && typeof(value) === 'object') { return false; } if(value !== void(0)) { target[i] = value; } } return true; } exports.extendFlat = function() { return _extend(arguments, false, false, false); }; exports.extendDeep = function() { return _extend(arguments, true, false, false); }; exports.extendDeepAll = function() { return _extend(arguments, true, true, false); }; exports.extendDeepNoArrays = function() { return _extend(arguments, true, false, true); }; /* * Inspired by https://github.com/justmoon/node-extend/blob/master/index.js * All credit to the jQuery authors for perfecting this amazing utility. * * API difference with jQuery version: * - No optional boolean (true -> deep extend) first argument, * use `extendFlat` for first-level only extend and * use `extendDeep` for a deep extend. * * Other differences with jQuery version: * - Uses a modern (and faster) isPlainObject routine. * - Expected to work with object {} and array [] arguments only. * - Does not check for circular structure. * FYI: jQuery only does a check across one level. * Warning: this might result in infinite loops. * */ function _extend(inputs, isDeep, keepAllKeys, noArrayCopies) { var target = inputs[0]; var length = inputs.length; var input, key, src, copy, copyIsArray, clone, allPrimitives; // TODO does this do the right thing for typed arrays? if(length === 2 && isArray(target) && isArray(inputs[1]) && target.length === 0) { allPrimitives = primitivesLoopSplice(inputs[1], target); if(allPrimitives) { return target; } else { target.splice(0, target.length); // reset target and continue to next block } } for(var i = 1; i < length; i++) { input = inputs[i]; for(key in input) { src = target[key]; copy = input[key]; if(noArrayCopies && isArray(copy)) { // Stop early and just transfer the array if array copies are disallowed: target[key] = copy; } else if(isDeep && copy && (isPlainObject(copy) || (copyIsArray = isArray(copy)))) { // recurse if we're merging plain objects or arrays if(copyIsArray) { copyIsArray = false; clone = src && isArray(src) ? src : []; } else { clone = src && isPlainObject(src) ? src : {}; } // never move original objects, clone them target[key] = _extend([clone, copy], isDeep, keepAllKeys, noArrayCopies); } else if(typeof copy !== 'undefined' || keepAllKeys) { // don't bring in undefined values, except for extendDeepAll target[key] = copy; } } } return target; } /***/ }), /* 7 */ /***/ (function(module, exports, __webpack_require__) { "use strict"; /** * Copyright 2012-2019, Plotly, Inc. * All rights reserved. * * This source code is licensed under the MIT license found in the * LICENSE file in the root directory of this source tree. */ module.exports = { /** * Standardize all missing data in calcdata to use undefined * never null or NaN. * That way we can use !==undefined, or !== BADNUM, * to test for real data */ BADNUM: undefined, /* * Limit certain operations to well below floating point max value * to avoid glitches: Make sure that even when you multiply it by the * number of pixels on a giant screen it still works */ FP_SAFE: Number.MAX_VALUE / 10000, /* * conversion of date units to milliseconds * year and month constants are marked "AVG" * to remind us that not all years and months * have the same length */ ONEAVGYEAR: 31557600000, // 365.25 days ONEAVGMONTH: 2629800000, // 1/12 of ONEAVGYEAR ONEDAY: 86400000, ONEHOUR: 3600000, ONEMIN: 60000, ONESEC: 1000, /* * For fast conversion btwn world calendars and epoch ms, the Julian Day Number * of the unix epoch. From calendars.instance().newDate(1970, 1, 1).toJD() */ EPOCHJD: 2440587.5, /* * Are two values nearly equal? Compare to 1PPM */ ALMOST_EQUAL: 1 - 1e-6, /* * If we're asked to clip a non-positive log value, how far off-screen * do we put it? */ LOG_CLIP: 10, /* * not a number, but for displaying numbers: the "minus sign" symbol is * wider than the regular ascii dash "-" */ MINUS_SIGN: '\u2212' }; /***/ }), /* 8 */ /***/ (function(module, exports, __webpack_require__) { "use strict"; /** * Copyright 2012-2019, Plotly, Inc. * All rights reserved. * * This source code is licensed under the MIT license found in the * LICENSE file in the root directory of this source tree. */ var isNumeric = __webpack_require__(0); var isArrayOrTypedArray = __webpack_require__(2).isArrayOrTypedArray; /** * convert a string s (such as 'xaxis.range[0]') * representing a property of nested object into set and get methods * also return the string and object so we don't have to keep track of them * allows [-1] for an array index, to set a property inside all elements * of an array * eg if obj = {arr: [{a: 1}, {a: 2}]} * you can do p = nestedProperty(obj, 'arr[-1].a') * but you cannot set the array itself this way, to do that * just set the whole array. * eg if obj = {arr: [1, 2, 3]} * you can't do nestedProperty(obj, 'arr[-1]').set(5) * but you can do nestedProperty(obj, 'arr').set([5, 5, 5]) */ module.exports = function nestedProperty(container, propStr) { if(isNumeric(propStr)) propStr = String(propStr); else if(typeof propStr !== 'string' || propStr.substr(propStr.length - 4) === '[-1]') { throw 'bad property string'; } var j = 0; var propParts = propStr.split('.'); var indexed; var indices; var i; // check for parts of the nesting hierarchy that are numbers (ie array elements) while(j < propParts.length) { // look for non-bracket chars, then any number of [##] blocks indexed = String(propParts[j]).match(/^([^\[\]]*)((\[\-?[0-9]*\])+)$/); if(indexed) { if(indexed[1]) propParts[j] = indexed[1]; // allow propStr to start with bracketed array indices else if(j === 0) propParts.splice(0, 1); else throw 'bad property string'; indices = indexed[2] .substr(1, indexed[2].length - 2) .split(']['); for(i = 0; i < indices.length; i++) { j++; propParts.splice(j, 0, Number(indices[i])); } } j++; } if(typeof container !== 'object') { return badContainer(container, propStr, propParts); } return { set: npSet(container, propParts, propStr), get: npGet(container, propParts), astr: propStr, parts: propParts, obj: container }; }; function npGet(cont, parts) { return function() { var curCont = cont; var curPart; var allSame; var out; var i; var j; for(i = 0; i < parts.length - 1; i++) { curPart = parts[i]; if(curPart === -1) { allSame = true; out = []; for(j = 0; j < curCont.length; j++) { out[j] = npGet(curCont[j], parts.slice(i + 1))(); if(out[j] !== out[0]) allSame = false; } return allSame ? out[0] : out; } if(typeof curPart === 'number' && !isArrayOrTypedArray(curCont)) { return undefined; } curCont = curCont[curPart]; if(typeof curCont !== 'object' || curCont === null) { return undefined; } } // only hit this if parts.length === 1 if(typeof curCont !== 'object' || curCont === null) return undefined; out = curCont[parts[i]]; if(out === null) return undefined; return out; }; } /* * Can this value be deleted? We can delete `undefined`, and `null` except INSIDE an * *args* array. * * Previously we also deleted some `{}` and `[]`, in order to try and make set/unset * a net noop; but this causes far more complication than it's worth, and still had * lots of exceptions. See https://github.com/plotly/plotly.js/issues/1410 * * *args* arrays get passed directly to API methods and we should respect null if * the user put it there, but otherwise null is deleted as we use it as code * in restyle/relayout/update for "delete this value" whereas undefined means * "ignore this edit" */ var ARGS_PATTERN = /(^|\.)args\[/; function isDeletable(val, propStr) { return (val === undefined) || (val === null && !propStr.match(ARGS_PATTERN)); } function npSet(cont, parts, propStr) { return function(val) { var curCont = cont; var propPart = ''; var containerLevels = [[cont, propPart]]; var toDelete = isDeletable(val, propStr); var curPart; var i; for(i = 0; i < parts.length - 1; i++) { curPart = parts[i]; if(typeof curPart === 'number' && !isArrayOrTypedArray(curCont)) { throw 'array index but container is not an array'; } // handle special -1 array index if(curPart === -1) { toDelete = !setArrayAll(curCont, parts.slice(i + 1), val, propStr); if(toDelete) break; else return; } if(!checkNewContainer(curCont, curPart, parts[i + 1], toDelete)) { break; } curCont = curCont[curPart]; if(typeof curCont !== 'object' || curCont === null) { throw 'container is not an object'; } propPart = joinPropStr(propPart, curPart); containerLevels.push([curCont, propPart]); } if(toDelete) { if(i === parts.length - 1) { delete curCont[parts[i]]; // The one bit of pruning we still do: drop `undefined` from the end of arrays. // In case someone has already unset previous items, continue until we hit a // non-undefined value. if(Array.isArray(curCont) && +parts[i] === curCont.length - 1) { while(curCont.length && curCont[curCont.length - 1] === undefined) { curCont.pop(); } } } } else curCont[parts[i]] = val; }; } function joinPropStr(propStr, newPart) { var toAdd = newPart; if(isNumeric(newPart)) toAdd = '[' + newPart + ']'; else if(propStr) toAdd = '.' + newPart; return propStr + toAdd; } // handle special -1 array index function setArrayAll(containerArray, innerParts, val, propStr) { var arrayVal = isArrayOrTypedArray(val); var allSet = true; var thisVal = val; var thisPropStr = propStr.replace('-1', 0); var deleteThis = arrayVal ? false : isDeletable(val, thisPropStr); var firstPart = innerParts[0]; var i; for(i = 0; i < containerArray.length; i++) { thisPropStr = propStr.replace('-1', i); if(arrayVal) { thisVal = val[i % val.length]; deleteThis = isDeletable(thisVal, thisPropStr); } if(deleteThis) allSet = false; if(!checkNewContainer(containerArray, i, firstPart, deleteThis)) { continue; } npSet(containerArray[i], innerParts, propStr.replace('-1', i))(thisVal); } return allSet; } /** * make new sub-container as needed. * returns false if there's no container and none is needed * because we're only deleting an attribute */ function checkNewContainer(container, part, nextPart, toDelete) { if(container[part] === undefined) { if(toDelete) return false; if(typeof nextPart === 'number') container[part] = []; else container[part] = {}; } return true; } function badContainer(container, propStr, propParts) { return { set: function() { throw 'bad container'; }, get: function() {}, astr: propStr, parts: propParts, obj: container }; } /***/ }), /* 9 */ /***/ (function(module, exports, __webpack_require__) { "use strict"; /** * Copyright 2012-2019, Plotly, Inc. * All rights reserved. * * This source code is licensed under the MIT license found in the * LICENSE file in the root directory of this source tree. */ /* * make a font attribute group * * @param {object} opts * @param {string} * opts.description: where & how this font is used * @param {optional bool} arrayOk: * should each part (family, size, color) be arrayOk? default false. * @param {string} editType: * the editType for all pieces of this font * @param {optional string} colorEditType: * a separate editType just for color * * @return {object} attributes object containing {family, size, color} as specified */ module.exports = function(opts) { var editType = opts.editType; var colorEditType = opts.colorEditType; if(colorEditType === undefined) colorEditType = editType; var attrs = { family: { valType: 'string', noBlank: true, strict: true, editType: editType, }, size: { valType: 'number', min: 1, editType: editType }, color: { valType: 'color', editType: colorEditType }, editType: editType, // blank strings so compress_attributes can remove // TODO - that's uber hacky... better solution? }; if(opts.arrayOk) { attrs.family.arrayOk = true; attrs.size.arrayOk = true; attrs.color.arrayOk = true; } return attrs; }; /***/ }), /* 10 */ /***/ (function(module, exports) { var g; // This works in non-strict mode g = (function() { return this; })(); try { // This works if eval is allowed (see CSP) g = g || Function("return this")() || (1,eval)("this"); } catch(e) { // This works if the window reference is available if(typeof window === "object") g = window; } // g can still be undefined, but nothing to do about it... // We return undefined, instead of nothing here, so it's // easier to handle this case. if(!global) { ...} module.exports = g; /***/ }), /* 11 */ /***/ (function(module, exports, __webpack_require__) { var __WEBPACK_AMD_DEFINE_RESULT__;// TinyColor v1.4.1 // https://github.com/bgrins/TinyColor // Brian Grinstead, MIT License (function(Math) { var trimLeft = /^\s+/, trimRight = /\s+$/, tinyCounter = 0, mathRound = Math.round, mathMin = Math.min, mathMax = Math.max, mathRandom = Math.random; function tinycolor (color, opts) { color = (color) ? color : ''; opts = opts || { }; // If input is already a tinycolor, return itself if (color instanceof tinycolor) { return color; } // If we are called as a function, call using new instead if (!(this instanceof tinycolor)) { return new tinycolor(color, opts); } var rgb = inputToRGB(color); this._originalInput = color, this._r = rgb.r, this._g = rgb.g, this._b = rgb.b, this._a = rgb.a, this._roundA = mathRound(100*this._a) / 100, this._format = opts.format || rgb.format; this._gradientType = opts.gradientType; // Don't let the range of [0,255] come back in [0,1]. // Potentially lose a little bit of precision here, but will fix issues where // .5 gets interpreted as half of the total, instead of half of 1 // If it was supposed to be 128, this was already taken care of by `inputToRgb` if (this._r < 1) { this._r = mathRound(this._r); } if (this._g < 1) { this._g = mathRound(this._g); } if (this._b < 1) { this._b = mathRound(this._b); } this._ok = rgb.ok; this._tc_id = tinyCounter++; } tinycolor.prototype = { isDark: function() { return this.getBrightness() < 128; }, isLight: function() { return !this.isDark(); }, isValid: function() { return this._ok; }, getOriginalInput: function() { return this._originalInput; }, getFormat: function() { return this._format; }, getAlpha: function() { return this._a; }, getBrightness: function() { //http://www.w3.org/TR/AERT#color-contrast var rgb = this.toRgb(); return (rgb.r * 299 + rgb.g * 587 + rgb.b * 114) / 1000; }, getLuminance: function() { //http://www.w3.org/TR/2008/REC-WCAG20-20081211/#relativeluminancedef var rgb = this.toRgb(); var RsRGB, GsRGB, BsRGB, R, G, B; RsRGB = rgb.r/255; GsRGB = rgb.g/255; BsRGB = rgb.b/255; if (RsRGB <= 0.03928) {R = RsRGB / 12.92;} else {R = Math.pow(((RsRGB + 0.055) / 1.055), 2.4);} if (GsRGB <= 0.03928) {G = GsRGB / 12.92;} else {G = Math.pow(((GsRGB + 0.055) / 1.055), 2.4);} if (BsRGB <= 0.03928) {B = BsRGB / 12.92;} else {B = Math.pow(((BsRGB + 0.055) / 1.055), 2.4);} return (0.2126 * R) + (0.7152 * G) + (0.0722 * B); }, setAlpha: function(value) { this._a = boundAlpha(value); this._roundA = mathRound(100*this._a) / 100; return this; }, toHsv: function() { var hsv = rgbToHsv(this._r, this._g, this._b); return { h: hsv.h * 360, s: hsv.s, v: hsv.v, a: this._a }; }, toHsvString: function() { var hsv = rgbToHsv(this._r, this._g, this._b); var h = mathRound(hsv.h * 360), s = mathRound(hsv.s * 100), v = mathRound(hsv.v * 100); return (this._a == 1) ? "hsv(" + h + ", " + s + "%, " + v + "%)" : "hsva(" + h + ", " + s + "%, " + v + "%, "+ this._roundA + ")"; }, toHsl: function() { var hsl = rgbToHsl(this._r, this._g, this._b); return { h: hsl.h * 360, s: hsl.s, l: hsl.l, a: this._a }; }, toHslString: function() { var hsl = rgbToHsl(this._r, this._g, this._b); var h = mathRound(hsl.h * 360), s = mathRound(hsl.s * 100), l = mathRound(hsl.l * 100); return (this._a == 1) ? "hsl(" + h + ", " + s + "%, " + l + "%)" : "hsla(" + h + ", " + s + "%, " + l + "%, "+ this._roundA + ")"; }, toHex: function(allow3Char) { return rgbToHex(this._r, this._g, this._b, allow3Char); }, toHexString: function(allow3Char) { return '#' + this.toHex(allow3Char); }, toHex8: function(allow4Char) { return rgbaToHex(this._r, this._g, this._b, this._a, allow4Char); }, toHex8String: function(allow4Char) { return '#' + this.toHex8(allow4Char); }, toRgb: function() { return { r: mathRound(this._r), g: mathRound(this._g), b: mathRound(this._b), a: this._a }; }, toRgbString: function() { return (this._a == 1) ? "rgb(" + mathRound(this._r) + ", " + mathRound(this._g) + ", " + mathRound(this._b) + ")" : "rgba(" + mathRound(this._r) + ", " + mathRound(this._g) + ", " + mathRound(this._b) + ", " + this._roundA + ")"; }, toPercentageRgb: function() { return { r: mathRound(bound01(this._r, 255) * 100) + "%", g: mathRound(bound01(this._g, 255) * 100) + "%", b: mathRound(bound01(this._b, 255) * 100) + "%", a: this._a }; }, toPercentageRgbString: function() { return (this._a == 1) ? "rgb(" + mathRound(bound01(this._r, 255) * 100) + "%, " + mathRound(bound01(this._g, 255) * 100) + "%, " + mathRound(bound01(this._b, 255) * 100) + "%)" : "rgba(" + mathRound(bound01(this._r, 255) * 100) + "%, " + mathRound(bound01(this._g, 255) * 100) + "%, " + mathRound(bound01(this._b, 255) * 100) + "%, " + this._roundA + ")"; }, toName: function() { if (this._a === 0) { return "transparent"; } if (this._a < 1) { return false; } return hexNames[rgbToHex(this._r, this._g, this._b, true)] || false; }, toFilter: function(secondColor) { var hex8String = '#' + rgbaToArgbHex(this._r, this._g, this._b, this._a); var secondHex8String = hex8String; var gradientType = this._gradientType ? "GradientType = 1, " : ""; if (secondColor) { var s = tinycolor(secondColor); secondHex8String = '#' + rgbaToArgbHex(s._r, s._g, s._b, s._a); } return "progid:DXImageTransform.Microsoft.gradient("+gradientType+"startColorstr="+hex8String+",endColorstr="+secondHex8String+")"; }, toString: function(format) { var formatSet = !!format; format = format || this._format; var formattedString = false; var hasAlpha = this._a < 1 && this._a >= 0; var needsAlphaFormat = !formatSet && hasAlpha && (format === "hex" || format === "hex6" || format === "hex3" || format === "hex4" || format === "hex8" || format === "name"); if (needsAlphaFormat) { // Special case for "transparent", all other non-alpha formats // will return rgba when there is transparency. if (format === "name" && this._a === 0) { return this.toName(); } return this.toRgbString(); } if (format === "rgb") { formattedString = this.toRgbString(); } if (format === "prgb") { formattedString = this.toPercentageRgbString(); } if (format === "hex" || format === "hex6") { formattedString = this.toHexString(); } if (format === "hex3") { formattedString = this.toHexString(true); } if (format === "hex4") { formattedString = this.toHex8String(true); } if (format === "hex8") { formattedString = this.toHex8String(); } if (format === "name") { formattedString = this.toName(); } if (format === "hsl") { formattedString = this.toHslString(); } if (format === "hsv") { formattedString = this.toHsvString(); } return formattedString || this.toHexString(); }, clone: function() { return tinycolor(this.toString()); }, _applyModification: function(fn, args) { var color = fn.apply(null, [this].concat([].slice.call(args))); this._r = color._r; this._g = color._g; this._b = color._b; this.setAlpha(color._a); return this; }, lighten: function() { return this._applyModification(lighten, arguments); }, brighten: function() { return this._applyModification(brighten, arguments); }, darken: function() { return this._applyModification(darken, arguments); }, desaturate: function() { return this._applyModification(desaturate, arguments); }, saturate: function() { return this._applyModification(saturate, arguments); }, greyscale: function() { return this._applyModification(greyscale, arguments); }, spin: function() { return this._applyModification(spin, arguments); }, _applyCombination: function(fn, args) { return fn.apply(null, [this].concat([].slice.call(args))); }, analogous: function() { return this._applyCombination(analogous, arguments); }, complement: function() { return this._applyCombination(complement, arguments); }, monochromatic: function() { return this._applyCombination(monochromatic, arguments); }, splitcomplement: function() { return this._applyCombination(splitcomplement, arguments); }, triad: function() { return this._applyCombination(triad, arguments); }, tetrad: function() { return this._applyCombination(tetrad, arguments); } }; // If input is an object, force 1 into "1.0" to handle ratios properly // String input requires "1.0" as input, so 1 will be treated as 1 tinycolor.fromRatio = function(color, opts) { if (typeof color == "object") { var newColor = {}; for (var i in color) { if (color.hasOwnProperty(i)) { if (i === "a") { newColor[i] = color[i]; } else { newColor[i] = convertToPercentage(color[i]); } } } color = newColor; } return tinycolor(color, opts); }; // Given a string or object, convert that input to RGB // Possible string inputs: // // "red" // "#f00" or "f00" // "#ff0000" or "ff0000" // "#ff000000" or "ff000000" // "rgb 255 0 0" or "rgb (255, 0, 0)" // "rgb 1.0 0 0" or "rgb (1, 0, 0)" // "rgba (255, 0, 0, 1)" or "rgba 255, 0, 0, 1" // "rgba (1.0, 0, 0, 1)" or "rgba 1.0, 0, 0, 1" // "hsl(0, 100%, 50%)" or "hsl 0 100% 50%" // "hsla(0, 100%, 50%, 1)" or "hsla 0 100% 50%, 1" // "hsv(0, 100%, 100%)" or "hsv 0 100% 100%" // function inputToRGB(color) { var rgb = { r: 0, g: 0, b: 0 }; var a = 1; var s = null; var v = null; var l = null; var ok = false; var format = false; if (typeof color == "string") { color = stringInputToObject(color); } if (typeof color == "object") { if (isValidCSSUnit(color.r) && isValidCSSUnit(color.g) && isValidCSSUnit(color.b)) { rgb = rgbToRgb(color.r, color.g, color.b); ok = true; format = String(color.r).substr(-1) === "%" ? "prgb" : "rgb"; } else if (isValidCSSUnit(color.h) && isValidCSSUnit(color.s) && isValidCSSUnit(color.v)) { s = convertToPercentage(color.s); v = convertToPercentage(color.v); rgb = hsvToRgb(color.h, s, v); ok = true; format = "hsv"; } else if (isValidCSSUnit(color.h) && isValidCSSUnit(color.s) && isValidCSSUnit(color.l)) { s = convertToPercentage(color.s); l = convertToPercentage(color.l); rgb = hslToRgb(color.h, s, l); ok = true; format = "hsl"; } if (color.hasOwnProperty("a")) { a = color.a; } } a = boundAlpha(a); return { ok: ok, format: color.format || format, r: mathMin(255, mathMax(rgb.r, 0)), g: mathMin(255, mathMax(rgb.g, 0)), b: mathMin(255, mathMax(rgb.b, 0)), a: a }; } // Conversion Functions // -------------------- // `rgbToHsl`, `rgbToHsv`, `hslToRgb`, `hsvToRgb` modified from: // // `rgbToRgb` // Handle bounds / percentage checking to conform to CSS color spec // // *Assumes:* r, g, b in [0, 255] or [0, 1] // *Returns:* { r, g, b } in [0, 255] function rgbToRgb(r, g, b){ return { r: bound01(r, 255) * 255, g: bound01(g, 255) * 255, b: bound01(b, 255) * 255 }; } // `rgbToHsl` // Converts an RGB color value to HSL. // *Assumes:* r, g, and b are contained in [0, 255] or [0, 1] // *Returns:* { h, s, l } in [0,1] function rgbToHsl(r, g, b) { r = bound01(r, 255); g = bound01(g, 255); b = bound01(b, 255); var max = mathMax(r, g, b), min = mathMin(r, g, b); var h, s, l = (max + min) / 2; if(max == min) { h = s = 0; // achromatic } else { var d = max - min; s = l > 0.5 ? d / (2 - max - min) : d / (max + min); switch(max) { case r: h = (g - b) / d + (g < b ? 6 : 0); break; case g: h = (b - r) / d + 2; break; case b: h = (r - g) / d + 4; break; } h /= 6; } return { h: h, s: s, l: l }; } // `hslToRgb` // Converts an HSL color value to RGB. // *Assumes:* h is contained in [0, 1] or [0, 360] and s and l are contained [0, 1] or [0, 100] // *Returns:* { r, g, b } in the set [0, 255] function hslToRgb(h, s, l) { var r, g, b; h = bound01(h, 360); s = bound01(s, 100); l = bound01(l, 100); function hue2rgb(p, q, t) { if(t < 0) t += 1; if(t > 1) t -= 1; if(t < 1/6) return p + (q - p) * 6 * t; if(t < 1/2) return q; if(t < 2/3) return p + (q - p) * (2/3 - t) * 6; return p; } if(s === 0) { r = g = b = l; // achromatic } else { var q = l < 0.5 ? l * (1 + s) : l + s - l * s; var p = 2 * l - q; r = hue2rgb(p, q, h + 1/3); g = hue2rgb(p, q, h); b = hue2rgb(p, q, h - 1/3); } return { r: r * 255, g: g * 255, b: b * 255 }; } // `rgbToHsv` // Converts an RGB color value to HSV // *Assumes:* r, g, and b are contained in the set [0, 255] or [0, 1] // *Returns:* { h, s, v } in [0,1] function rgbToHsv(r, g, b) { r = bound01(r, 255); g = bound01(g, 255); b = bound01(b, 255); var max = mathMax(r, g, b), min = mathMin(r, g, b); var h, s, v = max; var d = max - min; s = max === 0 ? 0 : d / max; if(max == min) { h = 0; // achromatic } else { switch(max) { case r: h = (g - b) / d + (g < b ? 6 : 0); break; case g: h = (b - r) / d + 2; break; case b: h = (r - g) / d + 4; break; } h /= 6; } return { h: h, s: s, v: v }; } // `hsvToRgb` // Converts an HSV color value to RGB. // *Assumes:* h is contained in [0, 1] or [0, 360] and s and v are contained in [0, 1] or [0, 100] // *Returns:* { r, g, b } in the set [0, 255] function hsvToRgb(h, s, v) { h = bound01(h, 360) * 6; s = bound01(s, 100); v = bound01(v, 100); var i = Math.floor(h), f = h - i, p = v * (1 - s), q = v * (1 - f * s), t = v * (1 - (1 - f) * s), mod = i % 6, r = [v, q, p, p, t, v][mod], g = [t, v, v, q, p, p][mod], b = [p, p, t, v, v, q][mod]; return { r: r * 255, g: g * 255, b: b * 255 }; } // `rgbToHex` // Converts an RGB color to hex // Assumes r, g, and b are contained in the set [0, 255] // Returns a 3 or 6 character hex function rgbToHex(r, g, b, allow3Char) { var hex = [ pad2(mathRound(r).toString(16)), pad2(mathRound(g).toString(16)), pad2(mathRound(b).toString(16)) ]; // Return a 3 character hex if possible if (allow3Char && hex[0].charAt(0) == hex[0].charAt(1) && hex[1].charAt(0) == hex[1].charAt(1) && hex[2].charAt(0) == hex[2].charAt(1)) { return hex[0].charAt(0) + hex[1].charAt(0) + hex[2].charAt(0); } return hex.join(""); } // `rgbaToHex` // Converts an RGBA color plus alpha transparency to hex // Assumes r, g, b are contained in the set [0, 255] and // a in [0, 1]. Returns a 4 or 8 character rgba hex function rgbaToHex(r, g, b, a, allow4Char) { var hex = [ pad2(mathRound(r).toString(16)), pad2(mathRound(g).toString(16)), pad2(mathRound(b).toString(16)), pad2(convertDecimalToHex(a)) ]; // Return a 4 character hex if possible if (allow4Char && hex[0].charAt(0) == hex[0].charAt(1) && hex[1].charAt(0) == hex[1].charAt(1) && hex[2].charAt(0) == hex[2].charAt(1) && hex[3].charAt(0) == hex[3].charAt(1)) { return hex[0].charAt(0) + hex[1].charAt(0) + hex[2].charAt(0) + hex[3].charAt(0); } return hex.join(""); } // `rgbaToArgbHex` // Converts an RGBA color to an ARGB Hex8 string // Rarely used, but required for "toFilter()" function rgbaToArgbHex(r, g, b, a) { var hex = [ pad2(convertDecimalToHex(a)), pad2(mathRound(r).toString(16)), pad2(mathRound(g).toString(16)), pad2(mathRound(b).toString(16)) ]; return hex.join(""); } // `equals` // Can be called with any tinycolor input tinycolor.equals = function (color1, color2) { if (!color1 || !color2) { return false; } return tinycolor(color1).toRgbString() == tinycolor(color2).toRgbString(); }; tinycolor.random = function() { return tinycolor.fromRatio({ r: mathRandom(), g: mathRandom(), b: mathRandom() }); }; // Modification Functions // ---------------------- // Thanks to less.js for some of the basics here // function desaturate(color, amount) { amount = (amount === 0) ? 0 : (amount || 10); var hsl = tinycolor(color).toHsl(); hsl.s -= amount / 100; hsl.s = clamp01(hsl.s); return tinycolor(hsl); } function saturate(color, amount) { amount = (amount === 0) ? 0 : (amount || 10); var hsl = tinycolor(color).toHsl(); hsl.s += amount / 100; hsl.s = clamp01(hsl.s); return tinycolor(hsl); } function greyscale(color) { return tinycolor(color).desaturate(100); } function lighten (color, amount) { amount = (amount === 0) ? 0 : (amount || 10); var hsl = tinycolor(color).toHsl(); hsl.l += amount / 100; hsl.l = clamp01(hsl.l); return tinycolor(hsl); } function brighten(color, amount) { amount = (amount === 0) ? 0 : (amount || 10); var rgb = tinycolor(color).toRgb(); rgb.r = mathMax(0, mathMin(255, rgb.r - mathRound(255 * - (amount / 100)))); rgb.g = mathMax(0, mathMin(255, rgb.g - mathRound(255 * - (amount / 100)))); rgb.b = mathMax(0, mathMin(255, rgb.b - mathRound(255 * - (amount / 100)))); return tinycolor(rgb); } function darken (color, amount) { amount = (amount === 0) ? 0 : (amount || 10); var hsl = tinycolor(color).toHsl(); hsl.l -= amount / 100; hsl.l = clamp01(hsl.l); return tinycolor(hsl); } // Spin takes a positive or negative amount within [-360, 360] indicating the change of hue. // Values outside of this range will be wrapped into this range. function spin(color, amount) { var hsl = tinycolor(color).toHsl(); var hue = (hsl.h + amount) % 360; hsl.h = hue < 0 ? 360 + hue : hue; return tinycolor(hsl); } // Combination Functions // --------------------- // Thanks to jQuery xColor for some of the ideas behind these // function complement(color) { var hsl = tinycolor(color).toHsl(); hsl.h = (hsl.h + 180) % 360; return tinycolor(hsl); } function triad(color) { var hsl = tinycolor(color).toHsl(); var h = hsl.h; return [ tinycolor(color), tinycolor({ h: (h + 120) % 360, s: hsl.s, l: hsl.l }), tinycolor({ h: (h + 240) % 360, s: hsl.s, l: hsl.l }) ]; } function tetrad(color) { var hsl = tinycolor(color).toHsl(); var h = hsl.h; return [ tinycolor(color), tinycolor({ h: (h + 90) % 360, s: hsl.s, l: hsl.l }), tinycolor({ h: (h + 180) % 360, s: hsl.s, l: hsl.l }), tinycolor({ h: (h + 270) % 360, s: hsl.s, l: hsl.l }) ]; } function splitcomplement(color) { var hsl = tinycolor(color).toHsl(); var h = hsl.h; return [ tinycolor(color), tinycolor({ h: (h + 72) % 360, s: hsl.s, l: hsl.l}), tinycolor({ h: (h + 216) % 360, s: hsl.s, l: hsl.l}) ]; } function analogous(color, results, slices) { results = results || 6; slices = slices || 30; var hsl = tinycolor(color).toHsl(); var part = 360 / slices; var ret = [tinycolor(color)]; for (hsl.h = ((hsl.h - (part * results >> 1)) + 720) % 360; --results; ) { hsl.h = (hsl.h + part) % 360; ret.push(tinycolor(hsl)); } return ret; } function monochromatic(color, results) { results = results || 6; var hsv = tinycolor(color).toHsv(); var h = hsv.h, s = hsv.s, v = hsv.v; var ret = []; var modification = 1 / results; while (results--) { ret.push(tinycolor({ h: h, s: s, v: v})); v = (v + modification) % 1; } return ret; } // Utility Functions // --------------------- tinycolor.mix = function(color1, color2, amount) { amount = (amount === 0) ? 0 : (amount || 50); var rgb1 = tinycolor(color1).toRgb(); var rgb2 = tinycolor(color2).toRgb(); var p = amount / 100; var rgba = { r: ((rgb2.r - rgb1.r) * p) + rgb1.r, g: ((rgb2.g - rgb1.g) * p) + rgb1.g, b: ((rgb2.b - rgb1.b) * p) + rgb1.b, a: ((rgb2.a - rgb1.a) * p) + rgb1.a }; return tinycolor(rgba); }; // Readability Functions // --------------------- // false // tinycolor.isReadable("#000", "#111",{level:"AA",size:"large"}) => false tinycolor.isReadable = function(color1, color2, wcag2) { var readability = tinycolor.readability(color1, color2); var wcag2Parms, out; out = false; wcag2Parms = validateWCAG2Parms(wcag2); switch (wcag2Parms.level + wcag2Parms.size) { case "AAsmall": case "AAAlarge": out = readability >= 4.5; break; case "AAlarge": out = readability >= 3; break; case "AAAsmall": out = readability >= 7; break; } return out; }; // `mostReadable` // Given a base color and a list of possible foreground or background // colors for that base, returns the most readable color. // Optionally returns Black or White if the most readable color is unreadable. // *Example* // tinycolor.mostReadable(tinycolor.mostReadable("#123", ["#124", "#125"],{includeFallbackColors:false}).toHexString(); // "#112255" // tinycolor.mostReadable(tinycolor.mostReadable("#123", ["#124", "#125"],{includeFallbackColors:true}).toHexString(); // "#ffffff" // tinycolor.mostReadable("#a8015a", ["#faf3f3"],{includeFallbackColors:true,level:"AAA",size:"large"}).toHexString(); // "#faf3f3" // tinycolor.mostReadable("#a8015a", ["#faf3f3"],{includeFallbackColors:true,level:"AAA",size:"small"}).toHexString(); // "#ffffff" tinycolor.mostReadable = function(baseColor, colorList, args) { var bestColor = null; var bestScore = 0; var readability; var includeFallbackColors, level, size ; args = args || {}; includeFallbackColors = args.includeFallbackColors ; level = args.level; size = args.size; for (var i= 0; i < colorList.length ; i++) { readability = tinycolor.readability(baseColor, colorList[i]); if (readability > bestScore) { bestScore = readability; bestColor = tinycolor(colorList[i]); } } if (tinycolor.isReadable(baseColor, bestColor, {"level":level,"size":size}) || !includeFallbackColors) { return bestColor; } else { args.includeFallbackColors=false; return tinycolor.mostReadable(baseColor,["#fff", "#000"],args); } }; // Big List of Colors // ------------------ // var names = tinycolor.names = { aliceblue: "f0f8ff", antiquewhite: "faebd7", aqua: "0ff", aquamarine: "7fffd4", azure: "f0ffff", beige: "f5f5dc", bisque: "ffe4c4", black: "000", blanchedalmond: "ffebcd", blue: "00f", blueviolet: "8a2be2", brown: "a52a2a", burlywood: "deb887", burntsienna: "ea7e5d", cadetblue: "5f9ea0", chartreuse: "7fff00", chocolate: "d2691e", coral: "ff7f50", cornflowerblue: "6495ed", cornsilk: "fff8dc", crimson: "dc143c", cyan: "0ff", darkblue: "00008b", darkcyan: "008b8b", darkgoldenrod: "b8860b", darkgray: "a9a9a9", darkgreen: "006400", darkgrey: "a9a9a9", darkkhaki: "bdb76b", darkmagenta: "8b008b", darkolivegreen: "556b2f", darkorange: "ff8c00", darkorchid: "9932cc", darkred: "8b0000", darksalmon: "e9967a", darkseagreen: "8fbc8f", darkslateblue: "483d8b", darkslategray: "2f4f4f", darkslategrey: "2f4f4f", darkturquoise: "00ced1", darkviolet: "9400d3", deeppink: "ff1493", deepskyblue: "00bfff", dimgray: "696969", dimgrey: "696969", dodgerblue: "1e90ff", firebrick: "b22222", floralwhite: "fffaf0", forestgreen: "228b22", fuchsia: "f0f", gainsboro: "dcdcdc", ghostwhite: "f8f8ff", gold: "ffd700", goldenrod: "daa520", gray: "808080", green: "008000", greenyellow: "adff2f", grey: "808080", honeydew: "f0fff0", hotpink: "ff69b4", indianred: "cd5c5c", indigo: "4b0082", ivory: "fffff0", khaki: "f0e68c", lavender: "e6e6fa", lavenderblush: "fff0f5", lawngreen: "7cfc00", lemonchiffon: "fffacd", lightblue: "add8e6", lightcoral: "f08080", lightcyan: "e0ffff", lightgoldenrodyellow: "fafad2", lightgray: "d3d3d3", lightgreen: "90ee90", lightgrey: "d3d3d3", lightpink: "ffb6c1", lightsalmon: "ffa07a", lightseagreen: "20b2aa", lightskyblue: "87cefa", lightslategray: "789", lightslategrey: "789", lightsteelblue: "b0c4de", lightyellow: "ffffe0", lime: "0f0", limegreen: "32cd32", linen: "faf0e6", magenta: "f0f", maroon: "800000", mediumaquamarine: "66cdaa", mediumblue: "0000cd", mediumorchid: "ba55d3", mediumpurple: "9370db", mediumseagreen: "3cb371", mediumslateblue: "7b68ee", mediumspringgreen: "00fa9a", mediumturquoise: "48d1cc", mediumvioletred: "c71585", midnightblue: "191970", mintcream: "f5fffa", mistyrose: "ffe4e1", moccasin: "ffe4b5", navajowhite: "ffdead", navy: "000080", oldlace: "fdf5e6", olive: "808000", olivedrab: "6b8e23", orange: "ffa500", orangered: "ff4500", orchid: "da70d6", palegoldenrod: "eee8aa", palegreen: "98fb98", paleturquoise: "afeeee", palevioletred: "db7093", papayawhip: "ffefd5", peachpuff: "ffdab9", peru: "cd853f", pink: "ffc0cb", plum: "dda0dd", powderblue: "b0e0e6", purple: "800080", rebeccapurple: "663399", red: "f00", rosybrown: "bc8f8f", royalblue: "4169e1", saddlebrown: "8b4513", salmon: "fa8072", sandybrown: "f4a460", seagreen: "2e8b57", seashell: "fff5ee", sienna: "a0522d", silver: "c0c0c0", skyblue: "87ceeb", slateblue: "6a5acd", slategray: "708090", slategrey: "708090", snow: "fffafa", springgreen: "00ff7f", steelblue: "4682b4", tan: "d2b48c", teal: "008080", thistle: "d8bfd8", tomato: "ff6347", turquoise: "40e0d0", violet: "ee82ee", wheat: "f5deb3", white: "fff", whitesmoke: "f5f5f5", yellow: "ff0", yellowgreen: "9acd32" }; // Make it easy to access colors via `hexNames[hex]` var hexNames = tinycolor.hexNames = flip(names); // Utilities // --------- // `{ 'name1': 'val1' }` becomes `{ 'val1': 'name1' }` function flip(o) { var flipped = { }; for (var i in o) { if (o.hasOwnProperty(i)) { flipped[o[i]] = i; } } return flipped; } // Return a valid alpha value [0,1] with all invalid values being set to 1 function boundAlpha(a) { a = parseFloat(a); if (isNaN(a) || a < 0 || a > 1) { a = 1; } return a; } // Take input from [0, n] and return it as [0, 1] function bound01(n, max) { if (isOnePointZero(n)) { n = "100%"; } var processPercent = isPercentage(n); n = mathMin(max, mathMax(0, parseFloat(n))); // Automatically convert percentage into number if (processPercent) { n = parseInt(n * max, 10) / 100; } // Handle floating point rounding errors if ((Math.abs(n - max) < 0.000001)) { return 1; } // Convert into [0, 1] range if it isn't already return (n % max) / parseFloat(max); } // Force a number between 0 and 1 function clamp01(val) { return mathMin(1, mathMax(0, val)); } // Parse a base-16 hex value into a base-10 integer function parseIntFromHex(val) { return parseInt(val, 16); } // Need to handle 1.0 as 100%, since once it is a number, there is no difference between it and 1 // function isOnePointZero(n) { return typeof n == "string" && n.indexOf('.') != -1 && parseFloat(n) === 1; } // Check to see if string passed in is a percentage function isPercentage(n) { return typeof n === "string" && n.indexOf('%') != -1; } // Force a hex value to have 2 characters function pad2(c) { return c.length == 1 ? '0' + c : '' + c; } // Replace a decimal with it's percentage value function convertToPercentage(n) { if (n <= 1) { n = (n * 100) + "%"; } return n; } // Converts a decimal to a hex value function convertDecimalToHex(d) { return Math.round(parseFloat(d) * 255).toString(16); } // Converts a hex value to a decimal function convertHexToDecimal(h) { return (parseIntFromHex(h) / 255); } var matchers = (function() { // var CSS_INTEGER = "[-\\+]?\\d+%?"; // var CSS_NUMBER = "[-\\+]?\\d*\\.\\d+%?"; // Allow positive/negative integer/number. Don't capture the either/or, just the entire outcome. var CSS_UNIT = "(?:" + CSS_NUMBER + ")|(?:" + CSS_INTEGER + ")"; // Actual matching. // Parentheses and commas are optional, but not required. // Whitespace can take the place of commas or opening paren var PERMISSIVE_MATCH3 = "[\\s|\\(]+(" + CSS_UNIT + ")[,|\\s]+(" + CSS_UNIT + ")[,|\\s]+(" + CSS_UNIT + ")\\s*\\)?"; var PERMISSIVE_MATCH4 = "[\\s|\\(]+(" + CSS_UNIT + ")[,|\\s]+(" + CSS_UNIT + ")[,|\\s]+(" + CSS_UNIT + ")[,|\\s]+(" + CSS_UNIT + ")\\s*\\)?"; return { CSS_UNIT: new RegExp(CSS_UNIT), rgb: new RegExp("rgb" + PERMISSIVE_MATCH3), rgba: new RegExp("rgba" + PERMISSIVE_MATCH4), hsl: new RegExp("hsl" + PERMISSIVE_MATCH3), hsla: new RegExp("hsla" + PERMISSIVE_MATCH4), hsv: new RegExp("hsv" + PERMISSIVE_MATCH3), hsva: new RegExp("hsva" + PERMISSIVE_MATCH4), hex3: /^#?([0-9a-fA-F]{1})([0-9a-fA-F]{1})([0-9a-fA-F]{1})$/, hex6: /^#?([0-9a-fA-F]{2})([0-9a-fA-F]{2})([0-9a-fA-F]{2})$/, hex4: /^#?([0-9a-fA-F]{1})([0-9a-fA-F]{1})([0-9a-fA-F]{1})([0-9a-fA-F]{1})$/, hex8: /^#?([0-9a-fA-F]{2})([0-9a-fA-F]{2})([0-9a-fA-F]{2})([0-9a-fA-F]{2})$/ }; })(); // `isValidCSSUnit` // Take in a single string / number and check to see if it looks like a CSS unit // (see `matchers` above for definition). function isValidCSSUnit(color) { return !!matchers.CSS_UNIT.exec(color); } // `stringInputToObject` // Permissive string parsing. Take in a number of formats, and output an object // based on detected format. Returns `{ r, g, b }` or `{ h, s, l }` or `{ h, s, v}` function stringInputToObject(color) { color = color.replace(trimLeft,'').replace(trimRight, '').toLowerCase(); var named = false; if (names[color]) { color = names[color]; named = true; } else if (color == 'transparent') { return { r: 0, g: 0, b: 0, a: 0, format: "name" }; } // Try to match string input using regular expressions. // Keep most of the number bounding out of this function - don't worry about [0,1] or [0,100] or [0,360] // Just return an object and let the conversion functions handle that. // This way the result will be the same whether the tinycolor is initialized with string or object. var match; if ((match = matchers.rgb.exec(color))) { return { r: match[1], g: match[2], b: match[3] }; } if ((match = matchers.rgba.exec(color))) { return { r: match[1], g: match[2], b: match[3], a: match[4] }; } if ((match = matchers.hsl.exec(color))) { return { h: match[1], s: match[2], l: match[3] }; } if ((match = matchers.hsla.exec(color))) { return { h: match[1], s: match[2], l: match[3], a: match[4] }; } if ((match = matchers.hsv.exec(color))) { return { h: match[1], s: match[2], v: match[3] }; } if ((match = matchers.hsva.exec(color))) { return { h: match[1], s: match[2], v: match[3], a: match[4] }; } if ((match = matchers.hex8.exec(color))) { return { r: parseIntFromHex(match[1]), g: parseIntFromHex(match[2]), b: parseIntFromHex(match[3]), a: convertHexToDecimal(match[4]), format: named ? "name" : "hex8" }; } if ((match = matchers.hex6.exec(color))) { return { r: parseIntFromHex(match[1]), g: parseIntFromHex(match[2]), b: parseIntFromHex(match[3]), format: named ? "name" : "hex" }; } if ((match = matchers.hex4.exec(color))) { return { r: parseIntFromHex(match[1] + '' + match[1]), g: parseIntFromHex(match[2] + '' + match[2]), b: parseIntFromHex(match[3] + '' + match[3]), a: convertHexToDecimal(match[4] + '' + match[4]), format: named ? "name" : "hex8" }; } if ((match = matchers.hex3.exec(color))) { return { r: parseIntFromHex(match[1] + '' + match[1]), g: parseIntFromHex(match[2] + '' + match[2]), b: parseIntFromHex(match[3] + '' + match[3]), format: named ? "name" : "hex" }; } return false; } function validateWCAG2Parms(parms) { // return valid WCAG2 parms for isReadable. // If input parms are invalid, return {"level":"AA", "size":"small"} var level, size; parms = parms || {"level":"AA", "size":"small"}; level = (parms.level || "AA").toUpperCase(); size = (parms.size || "small").toLowerCase(); if (level !== "AA" && level !== "AAA") { level = "AA"; } if (size !== "small" && size !== "large") { size = "small"; } return {"level":level, "size":size}; } // Node: Export function if (typeof module !== "undefined" && module.exports) { module.exports = tinycolor; } // AMD/requirejs: Define the module else if (true) { !(__WEBPACK_AMD_DEFINE_RESULT__ = (function () {return tinycolor;}).call(exports, __webpack_require__, exports, module), __WEBPACK_AMD_DEFINE_RESULT__ !== undefined && (module.exports = __WEBPACK_AMD_DEFINE_RESULT__)); } // Browser: Expose to window else { window.tinycolor = tinycolor; } })(Math); /***/ }), /* 12 */ /***/ (function(module, exports, __webpack_require__) { "use strict"; /** * Copyright 2012-2019, Plotly, Inc. * All rights reserved. * * This source code is licensed under the MIT license found in the * LICENSE file in the root directory of this source tree. */ var fxAttrs = __webpack_require__(33); module.exports = { type: { valType: 'enumerated', values: [], // listed dynamically dflt: 'scatter', editType: 'calc+clearAxisTypes', _noTemplating: true // we handle this at a higher level }, visible: { valType: 'enumerated', values: [true, false, 'legendonly'], dflt: true, editType: 'calc', }, showlegend: { valType: 'boolean', dflt: true, editType: 'style', }, legendgroup: { valType: 'string', dflt: '', editType: 'style', }, opacity: { valType: 'number', min: 0, max: 1, dflt: 1, editType: 'style', }, name: { valType: 'string', editType: 'style', }, uid: { valType: 'string', editType: 'plot', anim: true, }, ids: { valType: 'data_array', editType: 'calc', anim: true, }, customdata: { valType: 'data_array', editType: 'calc', }, meta: { valType: 'any', arrayOk: true, editType: 'plot', }, // N.B. these cannot be 'data_array' as they do not have the same length as // other data arrays and arrayOk attributes in general // // Maybe add another valType: // https://github.com/plotly/plotly.js/issues/1894 selectedpoints: { valType: 'any', editType: 'calc', }, hoverinfo: { valType: 'flaglist', flags: ['x', 'y', 'z', 'text', 'name'], extras: ['all', 'none', 'skip'], arrayOk: true, dflt: 'all', editType: 'none', }, hoverlabel: fxAttrs.hoverlabel, stream: { token: { valType: 'string', noBlank: true, strict: true, editType: 'calc', }, maxpoints: { valType: 'number', min: 0, max: 10000, dflt: 500, editType: 'calc', }, editType: 'calc' }, transforms: { _isLinkedToArray: 'transform', editType: 'calc', }, uirevision: { valType: 'any', editType: 'none', } }; /***/ }), /* 13 */ /***/ (function(module, exports, __webpack_require__) { "use strict"; /** * Copyright 2012-2019, Plotly, Inc. * All rights reserved. * * This source code is licensed under the MIT license found in the * LICENSE file in the root directory of this source tree. */ /* * make a regex for matching counter ids/names ie xaxis, xaxis2, xaxis10... * * @param {string} head: the head of the pattern, eg 'x' matches 'x', 'x2', 'x10' etc. * 'xy' is a special case for cartesian subplots: it matches 'x2y3' etc * @param {Optional(string)} tail: a fixed piece after the id * eg counterRegex('scene', '.annotations') for scene2.annotations etc. * @param {boolean} openEnded: if true, the string may continue past the match. * @param {boolean} matchBeginning: if false, the string may start before the match. */ exports.counter = function(head, tail, openEnded, matchBeginning) { var fullTail = (tail || '') + (openEnded ? '' : '$'); var startWithPrefix = matchBeginning === false ? '' : '^'; if(head === 'xy') { return new RegExp(startWithPrefix + 'x([2-9]|[1-9][0-9]+)?y([2-9]|[1-9][0-9]+)?' + fullTail); } return new RegExp(startWithPrefix + head + '([2-9]|[1-9][0-9]+)?' + fullTail); }; /***/ }), /* 14 */ /***/ (function(module, exports, __webpack_require__) { "use strict"; /** * Copyright 2012-2019, Plotly, Inc. * All rights reserved. * * This source code is licensed under the MIT license found in the * LICENSE file in the root directory of this source tree. */ var Loggers = __webpack_require__(4); var noop = __webpack_require__(15); var pushUnique = __webpack_require__(16); var isPlainObject = __webpack_require__(5); var addStyleRule = __webpack_require__(17).addStyleRule; var ExtendModule = __webpack_require__(6); var basePlotAttributes = __webpack_require__(12); var baseLayoutAttributes = __webpack_require__(40); var extendFlat = ExtendModule.extendFlat; var extendDeepAll = ExtendModule.extendDeepAll; exports.modules = {}; exports.allCategories = {}; exports.allTypes = []; exports.subplotsRegistry = {}; exports.transformsRegistry = {}; exports.componentsRegistry = {}; exports.layoutArrayContainers = []; exports.layoutArrayRegexes = []; exports.traceLayoutAttributes = {}; exports.localeRegistry = {}; exports.apiMethodRegistry = {}; exports.collectableSubplotTypes = null; /** * Top-level register routine, exported as Plotly.register * * @param {object array or array of objects} _modules : * module object or list of module object to register. * * A valid `moduleType: 'trace'` module has fields: * - name {string} : the trace type * - categories {array} : categories associated with this trace type, * tested with Register.traceIs() * - meta {object} : meta info (mostly for plot-schema) * * A valid `moduleType: 'locale'` module has fields: * - name {string} : the locale name. Should be a 2-digit language string ('en', 'de') * optionally with a country/region code ('en-GB', 'de-CH'). If a country * code is used but the base language locale has not yet been supplied, * we will use this locale for the base as well. * - dictionary {object} : the dictionary mapping input strings to localized strings * generally the keys should be the literal input strings, but * if default translations are provided you can use any string as a key. * - format {object} : a `d3.locale` format specifier for this locale * any omitted keys we'll fall back on en-US. * * A valid `moduleType: 'transform'` module has fields: * - name {string} : transform name * - transform {function} : default-level transform function * - calcTransform {function} : calc-level transform function * - attributes {object} : transform attributes declarations * - supplyDefaults {function} : attributes default-supply function * * A valid `moduleType: 'component'` module has fields: * - name {string} : the component name, used it with Register.getComponentMethod() * to employ component method. * * A valid `moduleType: 'apiMethod'` module has fields: * - name {string} : the api method name. * - fn {function} : the api method called with Register.call(); * */ exports.register = function register(_modules) { exports.collectableSubplotTypes = null; if(!_modules) { throw new Error('No argument passed to Plotly.register.'); } else if(_modules && !Array.isArray(_modules)) { _modules = [_modules]; } for(var i = 0; i < _modules.length; i++) { var newModule = _modules[i]; if(!newModule) { throw new Error('Invalid module was attempted to be registered!'); } switch(newModule.moduleType) { case 'trace': registerTraceModule(newModule); break; case 'transform': registerTransformModule(newModule); break; case 'component': registerComponentModule(newModule); break; case 'locale': registerLocale(newModule); break; case 'apiMethod': var name = newModule.name; exports.apiMethodRegistry[name] = newModule.fn; break; default: throw new Error('Invalid module was attempted to be registered!'); } } }; /** * Get registered module using trace object or trace type * * @param {object||string} trace * trace object with prop 'type' or trace type as a string * @return {object} * module object corresponding to trace type */ exports.getModule = function(trace) { var _module = exports.modules[getTraceType(trace)]; if(!_module) return false; return _module._module; }; /** * Determine if this trace type is in a given category * * @param {object||string} traceType * a trace (object) or trace type (string) * @param {string} category * category in question * @return {boolean} */ exports.traceIs = function(traceType, category) { traceType = getTraceType(traceType); // old plot.ly workspace hack, nothing to see here if(traceType === 'various') return false; var _module = exports.modules[traceType]; if(!_module) { if(traceType && traceType !== 'area') { Loggers.log('Unrecognized trace type ' + traceType + '.'); } _module = exports.modules[basePlotAttributes.type.dflt]; } return !!_module.categories[category]; }; /** * Determine if this trace has a transform of the given type and return * array of matching indices. * * @param {object} data * a trace object (member of data or fullData) * @param {string} type * type of trace to test * @return {array} * array of matching indices. If none found, returns [] */ exports.getTransformIndices = function(data, type) { var indices = []; var transforms = data.transforms || []; for(var i = 0; i < transforms.length; i++) { if(transforms[i].type === type) { indices.push(i); } } return indices; }; /** * Determine if this trace has a transform of the given type * * @param {object} data * a trace object (member of data or fullData) * @param {string} type * type of trace to test * @return {boolean} */ exports.hasTransform = function(data, type) { var transforms = data.transforms || []; for(var i = 0; i < transforms.length; i++) { if(transforms[i].type === type) { return true; } } return false; }; /** * Retrieve component module method. Falls back on noop if either the * module or the method is missing, so the result can always be safely called * * @param {string} name * name of component (as declared in component module) * @param {string} method * name of component module method * @return {function} */ exports.getComponentMethod = function(name, method) { var _module = exports.componentsRegistry[name]; if(!_module) return noop; return _module[method] || noop; }; /** * Call registered api method. * * @param {string} name : api method name * @param {...array} args : arguments passed to api method * @return {any} : returns api method output */ exports.call = function() { var name = arguments[0]; var args = [].slice.call(arguments, 1); return exports.apiMethodRegistry[name].apply(null, args); }; function registerTraceModule(_module) { var thisType = _module.name; var categoriesIn = _module.categories; var meta = _module.meta; if(exports.modules[thisType]) { Loggers.log('Type ' + thisType + ' already registered'); return; } if(!exports.subplotsRegistry[_module.basePlotModule.name]) { registerSubplot(_module.basePlotModule); } var categoryObj = {}; for(var i = 0; i < categoriesIn.length; i++) { categoryObj[categoriesIn[i]] = true; exports.allCategories[categoriesIn[i]] = true; } exports.modules[thisType] = { _module: _module, categories: categoryObj }; if(meta && Object.keys(meta).length) { exports.modules[thisType].meta = meta; } exports.allTypes.push(thisType); for(var componentName in exports.componentsRegistry) { mergeComponentAttrsToTrace(componentName, thisType); } /* * Collect all trace layout attributes in one place for easier lookup later * but don't merge them into the base schema as it would confuse the docs * (at least after https://github.com/plotly/documentation/issues/202 gets done!) */ if(_module.layoutAttributes) { extendFlat(exports.traceLayoutAttributes, _module.layoutAttributes); } var basePlotModule = _module.basePlotModule; var bpmName = basePlotModule.name; // add mapbox-gl CSS here to avoid console warning on instantiation if(bpmName === 'mapbox') { var styleRules = basePlotModule.constants.styleRules; for(var k in styleRules) { addStyleRule('.js-plotly-plot .plotly .mapboxgl-' + k, styleRules[k]); } } // if `plotly-geo-assets.js` is not included, // add `PlotlyGeoAssets` global to stash references to all fetched // topojson / geojson data if((bpmName === 'geo' || bpmName === 'mapbox') && (typeof window !== undefined && window.PlotlyGeoAssets === undefined) ) { window.PlotlyGeoAssets = {topojson: {}}; } } function registerSubplot(_module) { var plotType = _module.name; if(exports.subplotsRegistry[plotType]) { Loggers.log('Plot type ' + plotType + ' already registered.'); return; } // relayout array handling will look for component module methods with this // name and won't find them because this is a subplot module... but that // should be fine, it will just fall back on redrawing the plot. findArrayRegexps(_module); // not sure what's best for the 'cartesian' type at this point exports.subplotsRegistry[plotType] = _module; for(var componentName in exports.componentsRegistry) { mergeComponentAttrsToSubplot(componentName, _module.name); } } function registerComponentModule(_module) { if(typeof _module.name !== 'string') { throw new Error('Component module *name* must be a string.'); } var name = _module.name; exports.componentsRegistry[name] = _module; if(_module.layoutAttributes) { if(_module.layoutAttributes._isLinkedToArray) { pushUnique(exports.layoutArrayContainers, name); } findArrayRegexps(_module); } for(var traceType in exports.modules) { mergeComponentAttrsToTrace(name, traceType); } for(var subplotName in exports.subplotsRegistry) { mergeComponentAttrsToSubplot(name, subplotName); } for(var transformType in exports.transformsRegistry) { mergeComponentAttrsToTransform(name, transformType); } if(_module.schema && _module.schema.layout) { extendDeepAll(baseLayoutAttributes, _module.schema.layout); } } function registerTransformModule(_module) { if(typeof _module.name !== 'string') { throw new Error('Transform module *name* must be a string.'); } var prefix = 'Transform module ' + _module.name; var hasTransform = typeof _module.transform === 'function'; var hasCalcTransform = typeof _module.calcTransform === 'function'; if(!hasTransform && !hasCalcTransform) { throw new Error(prefix + ' is missing a *transform* or *calcTransform* method.'); } if(hasTransform && hasCalcTransform) { Loggers.log([ prefix + ' has both a *transform* and *calcTransform* methods.', 'Please note that all *transform* methods are executed', 'before all *calcTransform* methods.' ].join(' ')); } if(!isPlainObject(_module.attributes)) { Loggers.log(prefix + ' registered without an *attributes* object.'); } if(typeof _module.supplyDefaults !== 'function') { Loggers.log(prefix + ' registered without a *supplyDefaults* method.'); } exports.transformsRegistry[_module.name] = _module; for(var componentName in exports.componentsRegistry) { mergeComponentAttrsToTransform(componentName, _module.name); } } function registerLocale(_module) { var locale = _module.name; var baseLocale = locale.split('-')[0]; var newDict = _module.dictionary; var newFormat = _module.format; var hasDict = newDict && Object.keys(newDict).length; var hasFormat = newFormat && Object.keys(newFormat).length; var locales = exports.localeRegistry; var localeObj = locales[locale]; if(!localeObj) locales[locale] = localeObj = {}; // Should we use this dict for the base locale? // In case we're overwriting a previous dict for this locale, check // whether the base matches the full locale dict now. If we're not // overwriting, locales[locale] is undefined so this just checks if // baseLocale already had a dict or not. // Same logic for dateFormats if(baseLocale !== locale) { var baseLocaleObj = locales[baseLocale]; if(!baseLocaleObj) locales[baseLocale] = baseLocaleObj = {}; if(hasDict && baseLocaleObj.dictionary === localeObj.dictionary) { baseLocaleObj.dictionary = newDict; } if(hasFormat && baseLocaleObj.format === localeObj.format) { baseLocaleObj.format = newFormat; } } if(hasDict) localeObj.dictionary = newDict; if(hasFormat) localeObj.format = newFormat; } function findArrayRegexps(_module) { if(_module.layoutAttributes) { var arrayAttrRegexps = _module.layoutAttributes._arrayAttrRegexps; if(arrayAttrRegexps) { for(var i = 0; i < arrayAttrRegexps.length; i++) { pushUnique(exports.layoutArrayRegexes, arrayAttrRegexps[i]); } } } } function mergeComponentAttrsToTrace(componentName, traceType) { var componentSchema = exports.componentsRegistry[componentName].schema; if(!componentSchema || !componentSchema.traces) return; var traceAttrs = componentSchema.traces[traceType]; if(traceAttrs) { extendDeepAll(exports.modules[traceType]._module.attributes, traceAttrs); } } function mergeComponentAttrsToTransform(componentName, transformType) { var componentSchema = exports.componentsRegistry[componentName].schema; if(!componentSchema || !componentSchema.transforms) return; var transformAttrs = componentSchema.transforms[transformType]; if(transformAttrs) { extendDeepAll(exports.transformsRegistry[transformType].attributes, transformAttrs); } } function mergeComponentAttrsToSubplot(componentName, subplotName) { var componentSchema = exports.componentsRegistry[componentName].schema; if(!componentSchema || !componentSchema.subplots) return; var subplotModule = exports.subplotsRegistry[subplotName]; var subplotAttrs = subplotModule.layoutAttributes; var subplotAttr = subplotModule.attr === 'subplot' ? subplotModule.name : subplotModule.attr; if(Array.isArray(subplotAttr)) subplotAttr = subplotAttr[0]; var componentLayoutAttrs = componentSchema.subplots[subplotAttr]; if(subplotAttrs && componentLayoutAttrs) { extendDeepAll(subplotAttrs, componentLayoutAttrs); } } function getTraceType(traceType) { if(typeof traceType === 'object') traceType = traceType.type; return traceType; } /***/ }), /* 15 */ /***/ (function(module, exports, __webpack_require__) { "use strict"; /** * Copyright 2012-2019, Plotly, Inc. * All rights reserved. * * This source code is licensed under the MIT license found in the * LICENSE file in the root directory of this source tree. */ // Simple helper functions // none of these need any external deps module.exports = function noop() {}; /***/ }), /* 16 */ /***/ (function(module, exports, __webpack_require__) { "use strict"; /** * Copyright 2012-2019, Plotly, Inc. * All rights reserved. * * This source code is licensed under the MIT license found in the * LICENSE file in the root directory of this source tree. */ /** * Push array with unique items * * Ignores falsy items, except 0 so we can use it to construct arrays of indices. * * @param {array} array * array to be filled * @param {any} item * item to be or not to be inserted * @return {array} * ref to array (now possibly containing one more item) * */ module.exports = function pushUnique(array, item) { if(item instanceof RegExp) { var itemStr = item.toString(); for(var i = 0; i < array.length; i++) { if(array[i] instanceof RegExp && array[i].toString() === itemStr) { return array; } } array.push(item); } else if((item || item === 0) && array.indexOf(item) === -1) array.push(item); return array; }; /***/ }), /* 17 */ /***/ (function(module, exports, __webpack_require__) { "use strict"; /** * Copyright 2012-2019, Plotly, Inc. * All rights reserved. * * This source code is licensed under the MIT license found in the * LICENSE file in the root directory of this source tree. */ var d3 = __webpack_require__(1); var loggers = __webpack_require__(4); /** * Allow referencing a graph DOM element either directly * or by its id string * * @param {HTMLDivElement|string} gd: a graph element or its id * * @returns {HTMLDivElement} the DOM element of the graph */ function getGraphDiv(gd) { var gdElement; if(typeof gd === 'string') { gdElement = document.getElementById(gd); if(gdElement === null) { throw new Error('No DOM element with id \'' + gd + '\' exists on the page.'); } return gdElement; } else if(gd === null || gd === undefined) { throw new Error('DOM element provided is null or undefined'); } // otherwise assume that gd is a DOM element return gd; } function isPlotDiv(el) { var el3 = d3.select(el); return el3.node() instanceof HTMLElement && el3.size() && el3.classed('js-plotly-plot'); } function removeElement(el) { var elParent = el && el.parentNode; if(elParent) elParent.removeChild(el); } /** * for dynamically adding style rules * makes one stylesheet that contains all rules added * by all calls to this function */ function addStyleRule(selector, styleString) { addRelatedStyleRule('global', selector, styleString); } /** * for dynamically adding style rules * to a stylesheet uniquely identified by a uid */ function addRelatedStyleRule(uid, selector, styleString) { var id = 'plotly.js-style-' + uid; var style = document.getElementById(id); if(!style) { style = document.createElement('style'); style.setAttribute('id', id); // WebKit hack :( style.appendChild(document.createTextNode('')); document.head.appendChild(style); } var styleSheet = style.sheet; if(styleSheet.insertRule) { styleSheet.insertRule(selector + '{' + styleString + '}', 0); } else if(styleSheet.addRule) { styleSheet.addRule(selector, styleString, 0); } else loggers.warn('addStyleRule failed'); } /** * to remove from the page a stylesheet identified by a given uid */ function deleteRelatedStyleRule(uid) { var id = 'plotly.js-style-' + uid; var style = document.getElementById(id); if(style) removeElement(style); } module.exports = { getGraphDiv: getGraphDiv, isPlotDiv: isPlotDiv, removeElement: removeElement, addStyleRule: addStyleRule, addRelatedStyleRule: addRelatedStyleRule, deleteRelatedStyleRule: deleteRelatedStyleRule }; /***/ }), /* 18 */ /***/ (function(module, exports, __webpack_require__) { "use strict"; /** * Copyright 2012-2019, Plotly, Inc. * All rights reserved. * * This source code is licensed under the MIT license found in the * LICENSE file in the root directory of this source tree. */ // Simple helper functions // none of these need any external deps module.exports = function identity(d) { return d; }; /***/ }), /* 19 */ /***/ (function(module, exports) { module.exports = {"name":"plotlywidget","version":"1.4.0","description":"The plotly JupyterLab extension","author":"The plotly.py team","license":"MIT","main":"src/index.js","repository":{"type":"git","url":"https://github.com/plotly/plotly.py"},"keywords":["jupyter","widgets","ipython","ipywidgets","plotly"],"files":["src/**/*.js","dist/*.js","style/*.*"],"scripts":{"build":"npm run build:src","build:src":"rimraf dist && tsc","clean":"rimraf dist/ && rimraf ../../python/plotly/plotlywidget/static'","prepublish":"webpack","test":"echo \"Error: no test specified\" && exit 1"},"devDependencies":{"webpack":"^3.10.0","rimraf":"^2.6.1","ify-loader":"^1.1.0","typescript":"~3.1.1"},"dependencies":{"plotly.js":"^1.51.2","@jupyter-widgets/base":"^2.0.0","lodash":"^4.17.4"},"jupyterlab":{"extension":"src/jupyterlab-plugin.js"}} /***/ }), /* 20 */ /***/ (function(module, exports, __webpack_require__) { // Export widget models and views, and the npm package version number. module.exports = __webpack_require__(21); module.exports['version'] = __webpack_require__(19).version; /***/ }), /* 21 */ /***/ (function(module, exports, __webpack_require__) { var widgets = __webpack_require__(22); var _ = __webpack_require__(23); window.PlotlyConfig = {MathJaxConfig: 'local'}; var Plotly = __webpack_require__(25); var PlotlyIndex = __webpack_require__(26); var semver_range = "^" + __webpack_require__(19).version; // Model // ===== /** * A FigureModel holds a mirror copy of the state of a FigureWidget on * the Python side. There is a one-to-one relationship between JavaScript * FigureModels and Python FigureWidgets. The JavaScript FigureModel is * initialized as soon as a Python FigureWidget initialized, this happens * even before the widget is first displayed in the Notebook * @type {widgets.DOMWidgetModel} */ var FigureModel = widgets.DOMWidgetModel.extend({ defaults: _.extend(widgets.DOMWidgetModel.prototype.defaults(), { // Model metadata // -------------- _model_name: "FigureModel", _view_name: "FigureView", _model_module: "plotlywidget", _view_module: "plotlywidget", _view_module_version: semver_range, _model_module_version: semver_range, // Data and Layout // --------------- // The _data and _layout properties are synchronized with the // Python side on initialization only. After initialization, these // properties are kept in sync through the use of the _py2js_* // messages _data: [], _layout: {}, _config: {}, // Python -> JS messages // --------------------- // Messages are implemented using trait properties. This is done so // that we can take advantage of ipywidget's binary serialization // protocol. // // Messages are sent by the Python side by assigning the message // contents to the appropriate _py2js_* property, and then immediately // setting it to None. Messages are received by the JavaScript // side by registering property change callbacks in the initialize // methods for FigureModel and FigureView. e.g. (where this is a // FigureModel): // // this.on('change:_py2js_addTraces', this.do_addTraces, this); // // Message handling methods, do_addTraces, are responsible for // performing the appropriate action if the message contents are // not null /** * @typedef {null|Object} Py2JsAddTracesMsg * @property {Array.} trace_data * Array of traces to append to the end of the figure's current traces * @property {Number} trace_edit_id * Edit ID to use when returning trace deltas using * the _js2py_traceDeltas message. * @property {Number} layout_edit_id * Edit ID to use when returning layout deltas using * the _js2py_layoutDelta message. */ _py2js_addTraces: null, /** * @typedef {null|Object} Py2JsDeleteTracesMsg * @property {Array.} delete_inds * Array of indexes of traces to be deleted, in ascending order * @property {Number} trace_edit_id * Edit ID to use when returning trace deltas using * the _js2py_traceDeltas message. * @property {Number} layout_edit_id * Edit ID to use when returning layout deltas using * the _js2py_layoutDelta message. */ _py2js_deleteTraces: null, /** * @typedef {null|Object} Py2JsMoveTracesMsg * @property {Array.} current_trace_inds * Array of the current indexes of traces to be moved * @property {Array.} new_trace_inds * Array of the new indexes that traces should be moved to. */ _py2js_moveTraces: null, /** * @typedef {null|Object} Py2JsRestyleMsg * @property {Object} restyle_data * Restyle data as accepted by Plotly.restyle * @property {null|Array.} restyle_traces * Array of indexes of the traces that the resytle operation applies * to, or null to apply the operation to all traces * @property {Number} trace_edit_id * Edit ID to use when returning trace deltas using * the _js2py_traceDeltas message * @property {Number} layout_edit_id * Edit ID to use when returning layout deltas using * the _js2py_layoutDelta message * @property {null|String} source_view_id * view_id of the FigureView that triggered the original restyle * event (e.g. by clicking the legend), or null if the restyle was * triggered from Python */ _py2js_restyle: null, /** * @typedef {null|Object} Py2JsRelayoutMsg * @property {Object} relayout_data * Relayout data as accepted by Plotly.relayout * @property {Number} layout_edit_id * Edit ID to use when returning layout deltas using * the _js2py_layoutDelta message * @property {null|String} source_view_id * view_id of the FigureView that triggered the original relayout * event (e.g. by clicking the zoom button), or null if the * relayout was triggered from Python */ _py2js_relayout: null, /** * @typedef {null|Object} Py2JsUpdateMsg * @property {Object} style_data * Style data as accepted by Plotly.update * @property {Object} layout_data * Layout data as accepted by Plotly.update * @property {Array.} style_traces * Array of indexes of the traces that the update operation applies * to, or null to apply the operation to all traces * @property {Number} trace_edit_id * Edit ID to use when returning trace deltas using * the _js2py_traceDeltas message * @property {Number} layout_edit_id * Edit ID to use when returning layout deltas using * the _js2py_layoutDelta message * @property {null|String} source_view_id * view_id of the FigureView that triggered the original update * event (e.g. by clicking a button), or null if the update was * triggered from Python */ _py2js_update: null, /** * @typedef {null|Object} Py2JsAnimateMsg * @property {Object} style_data * Style data as accepted by Plotly.animate * @property {Object} layout_data * Layout data as accepted by Plotly.animate * @property {Array.} style_traces * Array of indexes of the traces that the animate operation applies * to, or null to apply the operation to all traces * @property {Object} animation_opts * Animation options as accepted by Plotly.animate * @property {Number} trace_edit_id * Edit ID to use when returning trace deltas using * the _js2py_traceDeltas message * @property {Number} layout_edit_id * Edit ID to use when returning layout deltas using * the _js2py_layoutDelta message * @property {null|String} source_view_id * view_id of the FigureView that triggered the original animate * event (e.g. by clicking a button), or null if the update was * triggered from Python */ _py2js_animate: null, /** * @typedef {null|Object} Py2JsRemoveLayoutPropsMsg * @property {Array.>} remove_props * Array of property paths to remove. Each propery path is an * array of property names or array indexes that locate a property * inside the _layout object */ _py2js_removeLayoutProps: null, /** * @typedef {null|Object} Py2JsRemoveTracePropsMsg * @property {Number} remove_trace * The index of the trace from which to remove properties * @property {Array.>} remove_props * Array of property paths to remove. Each propery path is an * array of property names or array indexes that locate a property * inside the _data[remove_trace] object */ _py2js_removeTraceProps: null, // JS -> Python messages // --------------------- // Messages are sent by the JavaScript side by assigning the // message contents to the appropriate _js2py_* property and then // calling the `touch` method on the view that triggered the // change. e.g. (where this is a FigureView): // // this.model.set('_js2py_restyle', data); // this.touch(); // // The Python side is responsible for setting the property to None // after receiving the message. // // Message trigger logic is described in the corresponding // handle_plotly_* methods of FigureView /** * @typedef {null|Object} Js2PyRestyleMsg * @property {Object} style_data * Style data that was passed to Plotly.restyle * @property {Array.} style_traces * Array of indexes of the traces that the restyle operation * was applied to, or null if applied to all traces * @property {String} source_view_id * view_id of the FigureView that triggered the original restyle * event (e.g. by clicking the legend) */ _js2py_restyle: null, /** * @typedef {null|Object} Js2PyRelayoutMsg * @property {Object} relayout_data * Relayout data that was passed to Plotly.relayout * @property {String} source_view_id * view_id of the FigureView that triggered the original relayout * event (e.g. by clicking the zoom button) */ _js2py_relayout: null, /** * @typedef {null|Object} Js2PyUpdateMsg * @property {Object} style_data * Style data that was passed to Plotly.update * @property {Object} layout_data * Layout data that was passed to Plotly.update * @property {Array.} style_traces * Array of indexes of the traces that the update operation applied * to, or null if applied to all traces * @property {String} source_view_id * view_id of the FigureView that triggered the original relayout * event (e.g. by clicking the zoom button) */ _js2py_update: null, /** * @typedef {null|Object} Js2PyLayoutDeltaMsg * @property {Object} layout_delta * The layout delta object that contains all of the properties of * _fullLayout that are not identical to those in the * FigureModel's _layout property * @property {Number} layout_edit_id * Edit ID of message that triggered the creation of layout delta */ _js2py_layoutDelta: null, /** * @typedef {null|Object} Js2PyTraceDeltasMsg * @property {Array.} trace_deltas * Array of trace delta objects. Each trace delta contains the * trace's uid along with all of the properties of _fullData that * are not identical to those in the FigureModel's _data property * @property {Number} trace_edit_id * Edit ID of message that triggered the creation of trace deltas */ _js2py_traceDeltas: null, /** * Object representing a collection of points for use in click, hover, * and selection events * @typedef {Object} Points * @property {Array.} trace_indexes * Array of the trace index for each point * @property {Array.} point_indexes * Array of the index of each point in its own trace * @property {null|Array.} xs * Array of the x coordinate of each point (for cartesian trace types) * or null (for non-cartesian trace types) * @property {null|Array.} ys * Array of the y coordinate of each point (for cartesian trace types) * or null (for non-cartesian trace types * @property {null|Array.} zs * Array of the z coordinate of each point (for 3D cartesian * trace types) * or null (for non-3D-cartesian trace types) */ /** * Object representing the state of the input devices during a * plotly event * @typedef {Object} InputDeviceState * @property {boolean} alt - true if alt key pressed, * false otherwise * @property {boolean} ctrl - true if ctrl key pressed, * false otherwise * @property {boolean} meta - true if meta key pressed, * false otherwise * @property {boolean} shift - true if shift key pressed, * false otherwise * * @property {boolean} button * Indicates which button was pressed on the mouse to trigger the * event. * 0: Main button pressed, usually the left button or the * un-initialized state * 1: Auxiliary button pressed, usually the wheel button or * the middle button (if present) * 2: Secondary button pressed, usually the right button * 3: Fourth button, typically the Browser Back button * 4: Fifth button, typically the Browser Forward button * * @property {boolean} buttons * Indicates which buttons were pressed on the mouse when the event * is triggered. * 0 : No button or un-initialized * 1 : Primary button (usually left) * 2 : Secondary button (usually right) * 4 : Auxilary button (usually middle or mouse wheel button) * 8 : 4th button (typically the "Browser Back" button) * 16 : 5th button (typically the "Browser Forward" button) * * Combinations of buttons are represented by the sum of the codes * above. e.g. a value of 7 indicates buttons 1 (primary), * 2 (secondary), and 4 (auxilary) were pressed during the event */ /** * @typedef {Object} BoxSelectorState * @property {Array.} xrange * Two element array containing the x-range of the box selection * @property {Array.} yrange * Two element array containing the y-range of the box selection */ /** * @typedef {Object} LassoSelectorState * @property {Array.} xs * Array of the x-coordinates of the lasso selection region * @property {Array.} ys * Array of the y-coordinates of the lasso selection region */ /** * Object representing the state of the selection tool during a * plotly_select event * @typedef {Object} Selector * @property {String} type * Selection type. One of: 'box', or 'lasso' * @property {BoxSelectorState|LassoSelectorState} selector_state */ /** * @typedef {null|Object} Js2PyPointsCallbackMsg * @property {string} event_type * Name of the triggering event. One of 'plotly_click', * 'plotly_hover', 'plotly_unhover', or 'plotly_selected' * @property {null|Points} points * Points object for event * @property {null|InputDeviceState} device_state * InputDeviceState object for event * @property {null|Selector} selector * State of the selection tool for 'plotly_selected' events, null * for other event types */ _js2py_pointsCallback: null, // Message tracking // ---------------- /** * @type {Number} * layout_edit_id of the last layout modification operation * requested by the Python side */ _last_layout_edit_id: 0, /** * @type {Number} * trace_edit_id of the last trace modification operation * requested by the Python side */ _last_trace_edit_id: 0 }), /** * Initialize FigureModel. Called when the Python FigureWidget is first * constructed */ initialize: function() { FigureModel.__super__.initialize.apply(this, arguments); this.on("change:_data", this.do_data, this); this.on("change:_layout", this.do_layout, this); this.on("change:_py2js_addTraces", this.do_addTraces, this); this.on("change:_py2js_deleteTraces", this.do_deleteTraces, this); this.on("change:_py2js_moveTraces", this.do_moveTraces, this); this.on("change:_py2js_restyle", this.do_restyle, this); this.on("change:_py2js_relayout", this.do_relayout, this); this.on("change:_py2js_update", this.do_update, this); this.on("change:_py2js_animate", this.do_animate, this); this.on("change:_py2js_removeLayoutProps", this.do_removeLayoutProps, this); this.on("change:_py2js_removeTraceProps", this.do_removeTraceProps, this); }, /** * Input a trace index specification and return an Array of trace * indexes where: * * - null|undefined -> Array of all traces * - Trace index as Number -> Single element array of input index * - Array of trace indexes -> Input array unchanged * * @param {undefined|null|Number|Array.} trace_indexes * @returns {Array.} * Array of trace indexes * @private */ _normalize_trace_indexes: function (trace_indexes) { if (trace_indexes === null || trace_indexes === undefined) { var numTraces = this.get("_data").length; trace_indexes = _.range(numTraces); } if (!Array.isArray(trace_indexes)) { // Make sure idx is an array trace_indexes = [trace_indexes]; } return trace_indexes }, /** * Log changes to the _data trait * * This should only happed on FigureModel initialization */ do_data: function () { }, /** * Log changes to the _layout trait * * This should only happed on FigureModel initialization */ do_layout: function () { }, /** * Handle addTraces message */ do_addTraces: function () { // add trace to plot /** @type {Py2JsAddTracesMsg} */ var msgData = this.get("_py2js_addTraces"); if (msgData !== null) { var currentTraces = this.get("_data"); var newTraces = msgData.trace_data; _.forEach(newTraces, function (newTrace) { currentTraces.push(newTrace); }) } }, /** * Handle deleteTraces message */ do_deleteTraces: function () { // remove traces from plot /** @type {Py2JsDeleteTracesMsg} */ var msgData = this.get("_py2js_deleteTraces"); if (msgData !== null) { var delete_inds = msgData.delete_inds; var tracesData = this.get("_data"); // Remove del inds in reverse order so indexes remain valid // throughout loop delete_inds.slice().reverse().forEach(function (del_ind) { tracesData.splice(del_ind, 1); }); } }, /** * Handle moveTraces message */ do_moveTraces: function () { /** @type {Py2JsMoveTracesMsg} */ var msgData = this.get("_py2js_moveTraces"); if (msgData !== null) { var tracesData = this.get("_data"); var currentInds = msgData.current_trace_inds; var newInds = msgData.new_trace_inds; performMoveTracesLike(tracesData, currentInds, newInds); } }, /** * Handle restyle message */ do_restyle: function () { /** @type {Py2JsRestyleMsg} */ var msgData = this.get("_py2js_restyle"); if (msgData !== null) { var restyleData = msgData.restyle_data; var restyleTraces = this._normalize_trace_indexes( msgData.restyle_traces); performRestyleLike(this.get("_data"), restyleData, restyleTraces); } }, /** * Handle relayout message */ do_relayout: function () { /** @type {Py2JsRelayoutMsg} */ var msgData = this.get("_py2js_relayout"); if (msgData !== null) { performRelayoutLike(this.get("_layout"), msgData.relayout_data); } }, /** * Handle update message */ do_update: function() { /** @type {Py2JsUpdateMsg} */ var msgData = this.get("_py2js_update"); if (msgData !== null) { var style = msgData.style_data; var layout = msgData.layout_data; var styleTraces = this._normalize_trace_indexes( msgData.style_traces); performRestyleLike(this.get("_data"), style, styleTraces); performRelayoutLike(this.get("_layout"), layout); } }, /** * Handle animate message */ do_animate: function () { /** @type {Py2JsAnimateMsg} */ var msgData = this.get("_py2js_animate"); if (msgData !== null) { var styles = msgData.style_data; var layout = msgData.layout_data; var trace_indexes = this._normalize_trace_indexes( msgData.style_traces); for (var i = 0; i < styles.length; i++) { var style = styles[i]; var trace_index = trace_indexes[i]; var trace = this.get("_data")[trace_index]; performRelayoutLike(trace, style); } performRelayoutLike(this.get("_layout"), layout); } }, /** * Handle removeLayoutProps message */ do_removeLayoutProps: function () { /** @type {Py2JsRemoveLayoutPropsMsg} */ var msgData = this.get("_py2js_removeLayoutProps"); if (msgData !== null) { var keyPaths = msgData.remove_props; var layout = this.get("_layout"); performRemoveProps(layout, keyPaths); } }, /** * Handle removeTraceProps message */ do_removeTraceProps: function () { /** @type {Py2JsRemoveTracePropsMsg} */ var msgData = this.get("_py2js_removeTraceProps"); if (msgData !== null) { var keyPaths = msgData.remove_props; var traceIndex = msgData.remove_trace; var trace = this.get("_data")[traceIndex]; performRemoveProps(trace, keyPaths); } } }, { serializers: _.extend({ _data: { deserialize: py2js_deserializer, serialize: js2py_serializer}, _layout: { deserialize: py2js_deserializer, serialize: js2py_serializer}, _py2js_addTraces: { deserialize: py2js_deserializer, serialize: js2py_serializer}, _py2js_deleteTraces: { deserialize: py2js_deserializer, serialize: js2py_serializer}, _py2js_moveTraces: { deserialize: py2js_deserializer, serialize: js2py_serializer}, _py2js_restyle: { deserialize: py2js_deserializer, serialize: js2py_serializer}, _py2js_relayout: { deserialize: py2js_deserializer, serialize: js2py_serializer}, _py2js_update: { deserialize: py2js_deserializer, serialize: js2py_serializer}, _py2js_animate: { deserialize: py2js_deserializer, serialize: js2py_serializer}, _py2js_removeLayoutProps: { deserialize: py2js_deserializer, serialize: js2py_serializer}, _py2js_removeTraceProps: { deserialize: py2js_deserializer, serialize: js2py_serializer}, _js2py_restyle: { deserialize: py2js_deserializer, serialize: js2py_serializer}, _js2py_relayout: { deserialize: py2js_deserializer, serialize: js2py_serializer}, _js2py_update: { deserialize: py2js_deserializer, serialize: js2py_serializer}, _js2py_layoutDelta: { deserialize: py2js_deserializer, serialize: js2py_serializer}, _js2py_traceDeltas: { deserialize: py2js_deserializer, serialize: js2py_serializer}, _js2py_pointsCallback: { deserialize: py2js_deserializer, serialize: js2py_serializer} }, widgets.DOMWidgetModel.serializers) }); // View // ==== /** * A FigureView manages the visual presentation of a single Plotly.js * figure for a single notebook output cell. Each FigureView has a * reference to FigureModel. Multiple views may share a single model * instance, as is the case when a Python FigureWidget is displayed in * multiple notebook output cells. * * @type {widgets.DOMWidgetView} */ var FigureView = widgets.DOMWidgetView.extend({ /** * The perform_render method is called by processPhosphorMessage * after the widget's DOM element has been attached to the notebook * output cell. This happens after the initialize of the * FigureModel, and it won't happen at all if the Python FigureWidget * is never displayed in a notebook output cell */ perform_render: function() { var that = this; // Wire up message property callbacks // ---------------------------------- // Python -> JS event properties this.model.on("change:_py2js_addTraces", this.do_addTraces, this); this.model.on("change:_py2js_deleteTraces", this.do_deleteTraces, this); this.model.on("change:_py2js_moveTraces", this.do_moveTraces, this); this.model.on("change:_py2js_restyle", this.do_restyle, this); this.model.on("change:_py2js_relayout", this.do_relayout, this); this.model.on("change:_py2js_update", this.do_update, this); this.model.on("change:_py2js_animate", this.do_animate, this); // MathJax configuration // --------------------- if (window.MathJax) { MathJax.Hub.Config({SVG: {font: "STIX-Web"}}); } // Get message ids // --------------------- var layout_edit_id = this.model.get("_last_layout_edit_id"); var trace_edit_id = this.model.get("_last_trace_edit_id"); // Set view UID // ------------ this.viewID = PlotlyIndex.randstr(); // Initialize Plotly.js figure // --------------------------- // We must clone the model's data and layout properties so that // the model is not directly mutated by the Plotly.js library. var initialTraces = _.cloneDeep(this.model.get("_data")); var initialLayout = _.cloneDeep(this.model.get("_layout")); var config = this.model.get("_config"); Plotly.newPlot(that.el, initialTraces, initialLayout, config).then( function () { // ### Send trace deltas ### // We create an array of deltas corresponding to the new // traces. that._sendTraceDeltas(trace_edit_id); // ### Send layout delta ### that._sendLayoutDelta(layout_edit_id); // Wire up plotly event callbacks that.el.on("plotly_restyle", function (update) { that.handle_plotly_restyle(update) }); that.el.on("plotly_relayout", function (update) { that.handle_plotly_relayout(update) }); that.el.on("plotly_update", function (update) { that.handle_plotly_update(update) }); that.el.on("plotly_click", function (update) { that.handle_plotly_click(update) }); that.el.on("plotly_hover", function (update) { that.handle_plotly_hover(update) }); that.el.on("plotly_unhover", function (update) { that.handle_plotly_unhover(update) }); that.el.on("plotly_selected", function (update) { that.handle_plotly_selected(update) }); that.el.on("plotly_deselect", function (update) { that.handle_plotly_deselect(update) }); that.el.on("plotly_doubleclick", function (update) { that.handle_plotly_doubleclick(update) }); // Emit event indicating that the widget has finished // rendering var event = new CustomEvent("plotlywidget-after-render", { "detail": {"element": that.el, 'viewID': that.viewID}}); // Dispatch/Trigger/Fire the event document.dispatchEvent(event); }); }, /** * Respond to phosphorjs events */ processPhosphorMessage: function(msg) { FigureView.__super__.processPhosphorMessage.apply(this, arguments); var that = this; switch (msg.type) { case 'before-attach': // Render an initial empty figure. This establishes with // the page that the element will not be empty, avoiding // some occasions where the dynamic sizing behavior leads // to collapsed figure dimensions. var axisHidden = { showgrid: false, showline: false, tickvals: []}; Plotly.newPlot(that.el, [], { xaxis: axisHidden, yaxis: axisHidden }); window.addEventListener("resize", function(){ that.autosizeFigure(); }); break; case 'after-attach': // Rendering actual figure in the after-attach event allows // Plotly.js to size the figure to fill the available element this.perform_render(); break; case 'resize': this.autosizeFigure(); break } }, autosizeFigure: function() { var that = this; var layout = that.model.get('_layout'); if (_.isNil(layout) || _.isNil(layout.width)) { Plotly.Plots.resize(that.el).then(function(){ var layout_edit_id = that.model.get( "_last_layout_edit_id"); that._sendLayoutDelta(layout_edit_id); }); } }, /** * Purge Plotly.js data structures from the notebook output display * element when the view is destroyed */ destroy: function() { Plotly.purge(this.el); }, /** * Return the figure's _fullData array merged with its data array * * The merge ensures that for any properties that el._fullData and * el.data have in common, we return the version from el.data * * Named colorscales are one example of why this is needed. The el.data * array will hold named colorscale strings (e.g. 'Viridis'), while the * el._fullData array will hold the actual colorscale array. e.g. * * el.data[0].marker.colorscale == 'Viridis' but * el._fullData[0].marker.colorscale = [[..., ...], ...] * * Performing the merge allows our FigureModel to retain the 'Viridis' * string, rather than having it overridded by the colorscale array. * */ getFullData: function () { return _.mergeWith({}, this.el._fullData, this.el.data, fullMergeCustomizer) }, /** * Return the figure's _fullLayout object merged with its layout object * * See getFullData documentation for discussion of why the merge is * necessary */ getFullLayout: function () { return _.mergeWith({}, this.el._fullLayout, this.el.layout, fullMergeCustomizer); }, /** * Build Points data structure from data supplied by the plotly_click, * plotly_hover, or plotly_select events * @param {Object} data * @returns {null|Points} */ buildPointsObject: function (data) { var pointsObject; if (data.hasOwnProperty("points")) { // Most cartesian plots var pointObjects = data["points"]; var numPoints = pointObjects.length; pointsObject = { "trace_indexes": new Array(numPoints), "point_indexes": new Array(numPoints), "xs": new Array(numPoints), "ys": new Array(numPoints)}; for (var p = 0; p < numPoints; p++) { pointsObject["trace_indexes"][p] = pointObjects[p]["curveNumber"]; pointsObject["point_indexes"][p] = pointObjects[p]["pointNumber"]; pointsObject["xs"][p] = pointObjects[p]["x"]; pointsObject["ys"][p] = pointObjects[p]["y"]; } // Add z if present var hasZ = pointObjects[0] !== undefined && pointObjects[0].hasOwnProperty("z"); if (hasZ) { pointsObject["zs"] = new Array(numPoints); for (p = 0; p < numPoints; p++) { pointsObject["zs"][p] = pointObjects[p]["z"]; } } return pointsObject } else { return null } }, /** * Build InputDeviceState data structure from data supplied by the * plotly_click, plotly_hover, or plotly_select events * @param {Object} data * @returns {null|InputDeviceState} */ buildInputDeviceStateObject: function (data) { var event = data["event"]; if (event === undefined) { return null; } else { /** @type {InputDeviceState} */ var inputDeviceState = { // Keyboard modifiers "alt": event["altKey"], "ctrl": event["ctrlKey"], "meta": event["metaKey"], "shift": event["shiftKey"], // Mouse buttons "button": event["button"], "buttons": event["buttons"] }; return inputDeviceState } }, /** * Build Selector data structure from data supplied by the * plotly_select event * @param data * @returns {null|Selector} */ buildSelectorObject: function(data) { var selectorObject; if (data.hasOwnProperty("range")) { // Box selection selectorObject = { type: "box", selector_state: { xrange: data["range"]["x"], yrange: data["range"]["y"] } }; } else if (data.hasOwnProperty("lassoPoints")) { // Lasso selection selectorObject = { type: "lasso", selector_state: { xs: data["lassoPoints"]["x"], ys: data["lassoPoints"]["y"] } }; } else { selectorObject = null; } return selectorObject }, /** * Handle ploty_restyle events emitted by the Plotly.js library * @param data */ handle_plotly_restyle: function (data) { if (data === null || data === undefined) { // No data to report to the Python side return } if (data[0] && data[0].hasOwnProperty("_doNotReportToPy")) { // Restyle originated on the Python side return } // Unpack data var styleData = data[0]; var styleTraces = data[1]; // Construct restyle message to send to the Python side /** @type {Js2PyRestyleMsg} */ var restyleMsg = { style_data: styleData, style_traces: styleTraces, source_view_id: this.viewID }; this.model.set("_js2py_restyle", restyleMsg); this.touch(); }, /** * Handle plotly_relayout events emitted by the Plotly.js library * @param data */ handle_plotly_relayout: function (data) { if (data === null || data === undefined) { // No data to report to the Python side return } if (data.hasOwnProperty("_doNotReportToPy")) { // Relayout originated on the Python side return } /** @type {Js2PyRelayoutMsg} */ var relayoutMsg = { relayout_data: data, source_view_id: this.viewID }; this.model.set("_js2py_relayout", relayoutMsg); this.touch(); }, /** * Handle plotly_update events emitted by the Plotly.js library * @param data */ handle_plotly_update: function (data) { if (data === null || data === undefined) { // No data to report to the Python side return } if (data["data"] && data["data"][0].hasOwnProperty("_doNotReportToPy")) { // Update originated on the Python side return } /** @type {Js2PyUpdateMsg} */ var updateMsg = { style_data: data["data"][0], style_traces: data["data"][1], layout_data: data["layout"], source_view_id: this.viewID }; // Log message this.model.set("_js2py_update", updateMsg); this.touch(); }, /** * Handle plotly_click events emitted by the Plotly.js library * @param data */ handle_plotly_click: function (data) { this._send_points_callback_message(data, "plotly_click"); }, /** * Handle plotly_hover events emitted by the Plotly.js library * @param data */ handle_plotly_hover: function (data) { this._send_points_callback_message(data, "plotly_hover"); }, /** * Handle plotly_unhover events emitted by the Plotly.js library * @param data */ handle_plotly_unhover: function (data) { this._send_points_callback_message(data, "plotly_unhover"); }, /** * Handle plotly_selected events emitted by the Plotly.js library * @param data */ handle_plotly_selected: function (data) { this._send_points_callback_message(data, "plotly_selected"); }, /** * Handle plotly_deselect events emitted by the Plotly.js library * @param data */ handle_plotly_deselect: function (data) { data = { points : [] } this._send_points_callback_message(data, "plotly_deselect"); }, /** * Build and send a points callback message to the Python side * * @param {Object} data * data object as provided by the plotly_click, plotly_hover, * plotly_unhover, or plotly_selected events * @param {String} event_type * Name of the triggering event. One of 'plotly_click', * 'plotly_hover', 'plotly_unhover', or 'plotly_selected' * @private */ _send_points_callback_message: function (data, event_type) { if (data === null || data === undefined) { // No data to report to the Python side return; } /** @type {Js2PyPointsCallbackMsg} */ var pointsMsg = { event_type: event_type, points: this.buildPointsObject(data), device_state: this.buildInputDeviceStateObject(data), selector: this.buildSelectorObject(data) }; if (pointsMsg["points"] !== null && pointsMsg["points"] !== undefined) { this.model.set("_js2py_pointsCallback", pointsMsg); this.touch(); } }, /** * Stub for future handling of plotly_doubleclick * @param data */ handle_plotly_doubleclick: function (data) {}, /** * Handle Plotly.addTraces request */ do_addTraces: function () { /** @type {Py2JsAddTracesMsg} */ var msgData = this.model.get("_py2js_addTraces"); if (msgData !== null) { // Save off original number of traces var prevNumTraces = this.el.data.length; var that = this; Plotly.addTraces(this.el, msgData.trace_data).then(function () { // ### Send trace deltas ### that._sendTraceDeltas(msgData.trace_edit_id); // ### Send layout delta ### var layout_edit_id = msgData.layout_edit_id; that._sendLayoutDelta(layout_edit_id); }); } }, /** * Handle Plotly.deleteTraces request */ do_deleteTraces: function () { /** @type {Py2JsDeleteTracesMsg} */ var msgData = this.model.get("_py2js_deleteTraces"); if (msgData !== null){ var delete_inds = msgData.delete_inds; var that = this; Plotly.deleteTraces(this.el, delete_inds).then(function () { // ### Send trace deltas ### var trace_edit_id = msgData.trace_edit_id; that._sendTraceDeltas(trace_edit_id); // ### Send layout delta ### var layout_edit_id = msgData.layout_edit_id; that._sendLayoutDelta(layout_edit_id); }); } }, /** * Handle Plotly.moveTraces request */ do_moveTraces: function () { /** @type {Py2JsMoveTracesMsg} */ var msgData = this.model.get("_py2js_moveTraces"); if (msgData !== null){ // Unpack message var currentInds = msgData.current_trace_inds; var newInds = msgData.new_trace_inds; // Check if the new trace indexes are actually different than // the current indexes var inds_equal = _.isEqual(currentInds, newInds); if (!inds_equal) { Plotly.moveTraces(this.el, currentInds, newInds) } } }, /** * Handle Plotly.restyle request */ do_restyle: function () { /** @type {Py2JsRestyleMsg} */ var msgData = this.model.get("_py2js_restyle"); if (msgData !== null) { var restyleData = msgData.restyle_data; var traceIndexes = this.model._normalize_trace_indexes( msgData.restyle_traces); restyleData["_doNotReportToPy"] = true; Plotly.restyle(this.el, restyleData, traceIndexes); // ### Send trace deltas ### // We create an array of deltas corresponding to the restyled // traces. this._sendTraceDeltas(msgData.trace_edit_id); // ### Send layout delta ### var layout_edit_id = msgData.layout_edit_id; this._sendLayoutDelta(layout_edit_id); } }, /** * Handle Plotly.relayout request */ do_relayout: function () { /** @type {Py2JsRelayoutMsg} */ var msgData = this.model.get("_py2js_relayout"); if (msgData !== null) { if (msgData.source_view_id !== this.viewID) { var relayoutData = msgData.relayout_data; relayoutData["_doNotReportToPy"] = true; Plotly.relayout(this.el, msgData.relayout_data); } // ### Send layout delta ### var layout_edit_id = msgData.layout_edit_id; this._sendLayoutDelta(layout_edit_id); } }, /** * Handle Plotly.update request */ do_update: function () { /** @type {Py2JsUpdateMsg} */ var msgData = this.model.get("_py2js_update"); if (msgData !== null) { var style = msgData.style_data || {}; var layout = msgData.layout_data || {}; var traceIndexes = this.model._normalize_trace_indexes( msgData.style_traces); style["_doNotReportToPy"] = true; Plotly.update(this.el, style, layout, traceIndexes); // ### Send trace deltas ### // We create an array of deltas corresponding to the updated // traces. this._sendTraceDeltas(msgData.trace_edit_id); // ### Send layout delta ### var layout_edit_id = msgData.layout_edit_id; this._sendLayoutDelta(layout_edit_id); } }, /** * Handle Plotly.animate request */ do_animate: function() { /** @type {Py2JsAnimateMsg} */ var msgData = this.model.get("_py2js_animate"); if (msgData !== null) { // Unpack params // var animationData = msgData[0]; var animationOpts = msgData.animation_opts; var styles = msgData.style_data; var layout = msgData.layout_data; var traceIndexes = this.model._normalize_trace_indexes( msgData.style_traces); var animationData = { data: styles, layout: layout, traces: traceIndexes }; animationData["_doNotReportToPy"] = true; var that = this; Plotly.animate(this.el, animationData, animationOpts).then( function () { // ### Send trace deltas ### // We create an array of deltas corresponding to the // animated traces. that._sendTraceDeltas(msgData.trace_edit_id); // ### Send layout delta ### var layout_edit_id = msgData.layout_edit_id; that._sendLayoutDelta(layout_edit_id); }); } }, /** * Construct layout delta object and send layoutDelta message to the * Python side * * @param layout_edit_id * Edit ID of message that triggered the creation of the layout delta * @private */ _sendLayoutDelta: function(layout_edit_id) { // ### Handle layout delta ### var layout_delta = createDeltaObject( this.getFullLayout(), this.model.get("_layout")); /** @type{Js2PyLayoutDeltaMsg} */ var layoutDeltaMsg = { layout_delta: layout_delta, layout_edit_id: layout_edit_id}; this.model.set("_js2py_layoutDelta", layoutDeltaMsg); this.touch(); }, /** * Construct trace deltas array for the requested trace indexes and * send traceDeltas message to the Python side * Array of indexes of traces for which to compute deltas * @param trace_edit_id * Edit ID of message that triggered the creation of trace deltas * @private */ _sendTraceDeltas: function (trace_edit_id) { var trace_data = this.model.get("_data"); var traceIndexes = _.range(trace_data.length); var trace_deltas = new Array(traceIndexes.length); var fullData = this.getFullData(); for (var i = 0; i < traceIndexes.length; i++) { var traceInd = traceIndexes[i]; trace_deltas[i] = createDeltaObject( fullData[traceInd], trace_data[traceInd]); } /** @type{Js2PyTraceDeltasMsg} */ var traceDeltasMsg = { trace_deltas: trace_deltas, trace_edit_id: trace_edit_id}; this.model.set("_js2py_traceDeltas", traceDeltasMsg); this.touch(); } }); // Serialization /** * Create a mapping from numpy dtype strings to corresponding typed array * constructors */ var numpy_dtype_to_typedarray_type = { int8: Int8Array, int16: Int16Array, int32: Int32Array, uint8: Uint8Array, uint16: Uint16Array, uint32: Uint32Array, float32: Float32Array, float64: Float64Array }; function serializeTypedArray(v) { var numpyType; if (v instanceof Int8Array) { numpyType = 'int8'; } else if (v instanceof Int16Array) { numpyType = 'int16'; } else if (v instanceof Int32Array) { numpyType = 'int32'; } else if (v instanceof Uint8Array) { numpyType = 'uint8'; } else if (v instanceof Uint16Array) { numpyType = 'uint16'; } else if (v instanceof Uint32Array) { numpyType = 'uint32'; } else if (v instanceof Float32Array) { numpyType = 'float32'; } else if (v instanceof Float64Array) { numpyType = 'float64'; } else { // Don't understand it, return as is return v; } var res = { dtype: numpyType, shape: [v.length], value: v.buffer }; return res } /** * ipywidget JavaScript -> Python serializer */ function js2py_serializer(v, widgetManager) { var res; if (_.isTypedArray(v)) { res = serializeTypedArray(v); } else if (Array.isArray(v)) { // Serialize array elements recursively res = new Array(v.length); for (var i = 0; i < v.length; i++) { res[i] = js2py_serializer(v[i]); } } else if (_.isPlainObject(v)) { // Serialize object properties recursively res = {}; for (var p in v) { if (v.hasOwnProperty(p)) { res[p] = js2py_serializer(v[p]); } } } else if (v === undefined) { // Translate undefined into '_undefined_' sentinal string. The // Python _js_to_py deserializer will convert this into an // Undefined object res = "_undefined_"; } else { // Primitive value to transfer directly res = v; } return res } /** * ipywidget Python -> Javascript deserializer */ function py2js_deserializer(v, widgetManager) { var res; if (Array.isArray(v)) { // Deserialize array elements recursively res = new Array(v.length); for (var i = 0; i < v.length; i++) { res[i] = py2js_deserializer(v[i]); } } else if (_.isPlainObject(v)) { if ((_.has(v, 'value') || _.has(v, 'buffer')) && _.has(v, 'dtype') && _.has(v, 'shape')) { // Deserialize special buffer/dtype/shape objects into typed arrays // These objects correspond to numpy arrays on the Python side // // Note plotly.py<=3.1.1 called the buffer object `buffer` // This was renamed `value` in 3.2 to work around a naming conflict // when saving widget state to a notebook. var typedarray_type = numpy_dtype_to_typedarray_type[v.dtype]; var buffer = _.has(v, 'value')? v.value.buffer: v.buffer.buffer; res = new typedarray_type(buffer); } else { // Deserialize object properties recursively res = {}; for (var p in v) { if (v.hasOwnProperty(p)) { res[p] = py2js_deserializer(v[p]); } } } } else if (v === "_undefined_") { // Convert the _undefined_ sentinal into undefined res = undefined; } else { // Accept primitive value directly res = v; } return res } /** * Return whether the input value is a typed array * @param potentialTypedArray * Value to examine * @returns {boolean} */ function isTypedArray(potentialTypedArray) { return ArrayBuffer.isView(potentialTypedArray) && !(potentialTypedArray instanceof DataView); } /** * Customizer for use with lodash's mergeWith function * * The customizer ensures that typed arrays are not converted into standard * arrays during the recursive merge * * See: https://lodash.com/docs/latest#mergeWith */ function fullMergeCustomizer(objValue, srcValue, key) { if (key[0] === '_') { // Don't recurse into private properties return null } else if (isTypedArray(srcValue)) { // Return typed arrays directly, don't recurse inside return srcValue } } /** * Reform a Plotly.relayout like operation on an input object * * @param {Object} parentObj * The object that the relayout operation should be applied to * @param {Object} relayoutData * An relayout object as accepted by Plotly.relayout * * Examples: * var d = {foo {bar [5, 10]}}; * performRelayoutLike(d, {'foo.bar': [0, 1]}); * d -> {foo: {bar: [0, 1]}} * * var d = {foo {bar [5, 10]}}; * performRelayoutLike(d, {'baz': 34}); * d -> {foo: {bar: [5, 10]}, baz: 34} * * var d = {foo: {bar: [5, 10]}; * performRelayoutLike(d, {'foo.baz[1]': 17}); * d -> {foo: {bar: [5, 17]}} * */ function performRelayoutLike(parentObj, relayoutData) { // Perform a relayout style operation on a given parent object for (var rawKey in relayoutData) { if (!relayoutData.hasOwnProperty(rawKey)) { continue } // Extract value for this key var relayoutVal = relayoutData[rawKey]; // Set property value if (relayoutVal === null) { _.unset(parentObj, rawKey); } else { _.set(parentObj, rawKey, relayoutVal); } } } /** * Perform a Plotly.restyle like operation on an input object array * * @param {Array.} parentArray * The object that the restyle operation should be applied to * @param {Object} restyleData * A restyle object as accepted by Plotly.restyle * @param {Array.} restyleTraces * Array of indexes of the traces that the resytle operation applies to * * Examples: * var d = [{foo: {bar: 1}}, {}, {}] * performRestyleLike(d, {'foo.bar': 2}, [0]) * d -> [{foo: {bar: 2}}, {}, {}] * * var d = [{foo: {bar: 1}}, {}, {}] * performRestyleLike(d, {'foo.bar': 2}, [0, 1, 2]) * d -> [{foo: {bar: 2}}, {foo: {bar: 2}}, {foo: {bar: 2}}] * * var d = [{foo: {bar: 1}}, {}, {}] * performRestyleLike(d, {'foo.bar': [2, 3, 4]}, [0, 1, 2]) * d -> [{foo: {bar: 2}}, {foo: {bar: 3}}, {foo: {bar: 4}}] * */ function performRestyleLike(parentArray, restyleData, restyleTraces) { // Loop over the properties of restyleData for (var rawKey in restyleData) { if (!restyleData.hasOwnProperty(rawKey)) { continue } // Extract value for property and normalize into a value list var valArray = restyleData[rawKey]; if (!Array.isArray(valArray)) { valArray = [valArray] } // Loop over the indexes of the traces being restyled for (var i = 0; i < restyleTraces.length; i++) { // Get trace object var traceInd = restyleTraces[i]; var trace = parentArray[traceInd]; // Extract value for this trace var singleVal = valArray[i % valArray.length]; // Set property value if (singleVal === null) { _.unset(trace, rawKey); } else if (singleVal !== undefined){ _.set(trace, rawKey, singleVal); } } } } /** * Perform a Plotly.moveTraces like operation on an input object array * @param parentArray * The object that the moveTraces operation should be applied to * @param currentInds * Array of the current indexes of traces to be moved * @param newInds * Array of the new indexes that traces selected by currentInds should be * moved to. * * Examples: * var d = [{foo: 0}, {foo: 1}, {foo: 2}] * performMoveTracesLike(d, [0, 1], [2, 0]) * d -> [{foo: 1}, {foo: 2}, {foo: 0}] * * var d = [{foo: 0}, {foo: 1}, {foo: 2}] * performMoveTracesLike(d, [0, 2], [1, 2]) * d -> [{foo: 1}, {foo: 0}, {foo: 2}] */ function performMoveTracesLike(parentArray, currentInds, newInds) { // ### Remove by currentInds in reverse order ### var movingTracesData = []; for (var ci = currentInds.length - 1; ci >= 0; ci--) { // Insert moving parentArray at beginning of the list movingTracesData.splice(0, 0, parentArray[currentInds[ci]]); parentArray.splice(currentInds[ci], 1); } // ### Sort newInds and movingTracesData by newInds ### var newIndexSortedArrays = _(newInds).zip(movingTracesData) .sortBy(0) .unzip() .value(); newInds = newIndexSortedArrays[0]; movingTracesData = newIndexSortedArrays[1]; // ### Insert by newInds in forward order ### for (var ni = 0; ni < newInds.length; ni++) { parentArray.splice(newInds[ni], 0, movingTracesData[ni]); } } /** * Remove nested properties from a parent object * @param {Object} parentObj * Parent object from which properties or nested properties should be removed * @param {Array.>} keyPaths * Array of key paths for properties that should be removed. Each key path * is an array of properties names or array indexes that reference a * property to be removed * * Examples: * var d = {foo: [{bar: 0}, {bar: 1}], baz: 32} * performRemoveProps(d, ['baz']) * d -> {foo: [{bar: 0}, {bar: 1}]} * * var d = {foo: [{bar: 0}, {bar: 1}], baz: 32} * performRemoveProps(d, ['foo[1].bar', 'baz']) * d -> {foo: [{bar: 0}, {}]} * */ function performRemoveProps(parentObj, keyPaths) { for(var i=0; i < keyPaths.length; i++) { var keyPath = keyPaths[i]; _.unset(parentObj, keyPath); } } /** * Return object that contains all properties in fullObj that are not * identical to the corresponding properties in removeObj * * Properties of fullObj and removeObj may be objects or arrays of objects * * Returned object is a deep clone of the properties of the input objects * * @param {Object} fullObj * @param {Object} removeObj * * Examples: * var fullD = {foo: [{bar: 0}, {bar: 1}], baz: 32} * var removeD = {baz: 32} * createDeltaObject(fullD, removeD) * -> {foo: [{bar: 0}, {bar: 1}]} * * var fullD = {foo: [{bar: 0}, {bar: 1}], baz: 32} * var removeD = {baz: 45} * createDeltaObject(fullD, removeD) * -> {foo: [{bar: 0}, {bar: 1}], baz: 32} * * var fullD = {foo: [{bar: 0}, {bar: 1}], baz: 32} * var removeD = {foo: [{bar: 0}, {bar: 1}]} * createDeltaObject(fullD, removeD) * -> {baz: 32} * */ function createDeltaObject(fullObj, removeObj) { // Initialize result as object or array var res; if(Array.isArray(fullObj)) { res = new Array(fullObj.length); } else { res = {}; } // Initialize removeObj to empty object if not specified if (removeObj === null || removeObj === undefined) { removeObj = {}; } // Iterate over object properties or array indices for (var p in fullObj) { if (p[0] !== "_" && // Don't consider private properties fullObj.hasOwnProperty(p) && // Exclude parent properties fullObj[p] !== null // Exclude cases where fullObj doesn't // have the property ) { // Compute object equality var props_equal; props_equal = _.isEqual(fullObj[p], removeObj[p]); // Perform recursive comparison if props are not equal if (!props_equal || p === "uid") { // Let uids through // property has non-null value in fullObj that doesn't // match the value in removeObj var fullVal = fullObj[p]; if (removeObj.hasOwnProperty(p) && typeof fullVal === "object") { // Recurse over object properties if(Array.isArray(fullVal)) { if (fullVal.length > 0 && typeof(fullVal[0]) === "object") { // We have an object array res[p] = new Array(fullVal.length); for (var i = 0; i < fullVal.length; i++) { if (!Array.isArray(removeObj[p]) || removeObj[p].length <= i) { res[p][i] = fullVal[i] } else { res[p][i] = createDeltaObject(fullVal[i], removeObj[p][i]); } } } else { // We have a primitive array or typed array res[p] = fullVal; } } else { // object var full_obj = createDeltaObject(fullVal, removeObj[p]); if (Object.keys(full_obj).length > 0) { // new object is not empty res[p] = full_obj; } } } else if (typeof fullVal === "object" && !Array.isArray(fullVal)) { // Return 'clone' of fullVal // We don't use a standard clone method so that we keep // the special case handling of this method res[p] = createDeltaObject(fullVal, {}); } else if (fullVal !== undefined && typeof fullVal !== 'function') { // No recursion necessary, Just keep value from fullObj. // But skip values with function type res[p] = fullVal; } } } } return res } module.exports = { FigureView : FigureView, FigureModel: FigureModel }; /***/ }), /* 22 */ /***/ (function(module, exports) { module.exports = __WEBPACK_EXTERNAL_MODULE_22__; /***/ }), /* 23 */ /***/ (function(module, exports, __webpack_require__) { /* WEBPACK VAR INJECTION */(function(global, module) {var __WEBPACK_AMD_DEFINE_RESULT__;/** * @license * Lodash * Copyright OpenJS Foundation and other contributors * Released under MIT license * Based on Underscore.js 1.8.3 * Copyright Jeremy Ashkenas, DocumentCloud and Investigative Reporters & Editors */ ;(function() { /** Used as a safe reference for `undefined` in pre-ES5 environments. */ var undefined; /** Used as the semantic version number. */ var VERSION = '4.17.13'; /** Used as the size to enable large array optimizations. */ var LARGE_ARRAY_SIZE = 200; /** Error message constants. */ var CORE_ERROR_TEXT = 'Unsupported core-js use. Try https://npms.io/search?q=ponyfill.', FUNC_ERROR_TEXT = 'Expected a function'; /** Used to stand-in for `undefined` hash values. */ var HASH_UNDEFINED = '__lodash_hash_undefined__'; /** Used as the maximum memoize cache size. */ var MAX_MEMOIZE_SIZE = 500; /** Used as the internal argument placeholder. */ var PLACEHOLDER = '__lodash_placeholder__'; /** Used to compose bitmasks for cloning. */ var CLONE_DEEP_FLAG = 1, CLONE_FLAT_FLAG = 2, CLONE_SYMBOLS_FLAG = 4; /** Used to compose bitmasks for value comparisons. */ var COMPARE_PARTIAL_FLAG = 1, COMPARE_UNORDERED_FLAG = 2; /** Used to compose bitmasks for function metadata. */ var WRAP_BIND_FLAG = 1, WRAP_BIND_KEY_FLAG = 2, WRAP_CURRY_BOUND_FLAG = 4, WRAP_CURRY_FLAG = 8, WRAP_CURRY_RIGHT_FLAG = 16, WRAP_PARTIAL_FLAG = 32, WRAP_PARTIAL_RIGHT_FLAG = 64, WRAP_ARY_FLAG = 128, WRAP_REARG_FLAG = 256, WRAP_FLIP_FLAG = 512; /** Used as default options for `_.truncate`. */ var DEFAULT_TRUNC_LENGTH = 30, DEFAULT_TRUNC_OMISSION = '...'; /** Used to detect hot functions by number of calls within a span of milliseconds. */ var HOT_COUNT = 800, HOT_SPAN = 16; /** Used to indicate the type of lazy iteratees. */ var LAZY_FILTER_FLAG = 1, LAZY_MAP_FLAG = 2, LAZY_WHILE_FLAG = 3; /** Used as references for various `Number` constants. */ var INFINITY = 1 / 0, MAX_SAFE_INTEGER = 9007199254740991, MAX_INTEGER = 1.7976931348623157e+308, NAN = 0 / 0; /** Used as references for the maximum length and index of an array. */ var MAX_ARRAY_LENGTH = 4294967295, MAX_ARRAY_INDEX = MAX_ARRAY_LENGTH - 1, HALF_MAX_ARRAY_LENGTH = MAX_ARRAY_LENGTH >>> 1; /** Used to associate wrap methods with their bit flags. */ var wrapFlags = [ ['ary', WRAP_ARY_FLAG], ['bind', WRAP_BIND_FLAG], ['bindKey', WRAP_BIND_KEY_FLAG], ['curry', WRAP_CURRY_FLAG], ['curryRight', WRAP_CURRY_RIGHT_FLAG], ['flip', WRAP_FLIP_FLAG], ['partial', WRAP_PARTIAL_FLAG], ['partialRight', WRAP_PARTIAL_RIGHT_FLAG], ['rearg', WRAP_REARG_FLAG] ]; /** `Object#toString` result references. */ var argsTag = '[object Arguments]', arrayTag = '[object Array]', asyncTag = '[object AsyncFunction]', boolTag = '[object Boolean]', dateTag = '[object Date]', domExcTag = '[object DOMException]', errorTag = '[object Error]', funcTag = '[object Function]', genTag = '[object GeneratorFunction]', mapTag = '[object Map]', numberTag = '[object Number]', nullTag = '[object Null]', objectTag = '[object Object]', promiseTag = '[object Promise]', proxyTag = '[object Proxy]', regexpTag = '[object RegExp]', setTag = '[object Set]', stringTag = '[object String]', symbolTag = '[object Symbol]', undefinedTag = '[object Undefined]', weakMapTag = '[object WeakMap]', weakSetTag = '[object WeakSet]'; var arrayBufferTag = '[object ArrayBuffer]', dataViewTag = '[object DataView]', float32Tag = '[object Float32Array]', float64Tag = '[object Float64Array]', int8Tag = '[object Int8Array]', int16Tag = '[object Int16Array]', int32Tag = '[object Int32Array]', uint8Tag = '[object Uint8Array]', uint8ClampedTag = '[object Uint8ClampedArray]', uint16Tag = '[object Uint16Array]', uint32Tag = '[object Uint32Array]'; /** Used to match empty string literals in compiled template source. */ var reEmptyStringLeading = /\b__p \+= '';/g, reEmptyStringMiddle = /\b(__p \+=) '' \+/g, reEmptyStringTrailing = /(__e\(.*?\)|\b__t\)) \+\n'';/g; /** Used to match HTML entities and HTML characters. */ var reEscapedHtml = /&(?:amp|lt|gt|quot|#39);/g, reUnescapedHtml = /[&<>"']/g, reHasEscapedHtml = RegExp(reEscapedHtml.source), reHasUnescapedHtml = RegExp(reUnescapedHtml.source); /** Used to match template delimiters. */ var reEscape = /<%-([\s\S]+?)%>/g, reEvaluate = /<%([\s\S]+?)%>/g, reInterpolate = /<%=([\s\S]+?)%>/g; /** Used to match property names within property paths. */ var reIsDeepProp = /\.|\[(?:[^[\]]*|(["'])(?:(?!\1)[^\\]|\\.)*?\1)\]/, reIsPlainProp = /^\w*$/, rePropName = /[^.[\]]+|\[(?:(-?\d+(?:\.\d+)?)|(["'])((?:(?!\2)[^\\]|\\.)*?)\2)\]|(?=(?:\.|\[\])(?:\.|\[\]|$))/g; /** * Used to match `RegExp` * [syntax characters](http://ecma-international.org/ecma-262/7.0/#sec-patterns). */ var reRegExpChar = /[\\^$.*+?()[\]{}|]/g, reHasRegExpChar = RegExp(reRegExpChar.source); /** Used to match leading and trailing whitespace. */ var reTrim = /^\s+|\s+$/g, reTrimStart = /^\s+/, reTrimEnd = /\s+$/; /** Used to match wrap detail comments. */ var reWrapComment = /\{(?:\n\/\* \[wrapped with .+\] \*\/)?\n?/, reWrapDetails = /\{\n\/\* \[wrapped with (.+)\] \*/, reSplitDetails = /,? & /; /** Used to match words composed of alphanumeric characters. */ var reAsciiWord = /[^\x00-\x2f\x3a-\x40\x5b-\x60\x7b-\x7f]+/g; /** Used to match backslashes in property paths. */ var reEscapeChar = /\\(\\)?/g; /** * Used to match * [ES template delimiters](http://ecma-international.org/ecma-262/7.0/#sec-template-literal-lexical-components). */ var reEsTemplate = /\$\{([^\\}]*(?:\\.[^\\}]*)*)\}/g; /** Used to match `RegExp` flags from their coerced string values. */ var reFlags = /\w*$/; /** Used to detect bad signed hexadecimal string values. */ var reIsBadHex = /^[-+]0x[0-9a-f]+$/i; /** Used to detect binary string values. */ var reIsBinary = /^0b[01]+$/i; /** Used to detect host constructors (Safari). */ var reIsHostCtor = /^\[object .+?Constructor\]$/; /** Used to detect octal string values. */ var reIsOctal = /^0o[0-7]+$/i; /** Used to detect unsigned integer values. */ var reIsUint = /^(?:0|[1-9]\d*)$/; /** Used to match Latin Unicode letters (excluding mathematical operators). */ var reLatin = /[\xc0-\xd6\xd8-\xf6\xf8-\xff\u0100-\u017f]/g; /** Used to ensure capturing order of template delimiters. */ var reNoMatch = /($^)/; /** Used to match unescaped characters in compiled string literals. */ var reUnescapedString = /['\n\r\u2028\u2029\\]/g; /** Used to compose unicode character classes. */ var rsAstralRange = '\\ud800-\\udfff', rsComboMarksRange = '\\u0300-\\u036f', reComboHalfMarksRange = '\\ufe20-\\ufe2f', rsComboSymbolsRange = '\\u20d0-\\u20ff', rsComboRange = rsComboMarksRange + reComboHalfMarksRange + rsComboSymbolsRange, rsDingbatRange = '\\u2700-\\u27bf', rsLowerRange = 'a-z\\xdf-\\xf6\\xf8-\\xff', rsMathOpRange = '\\xac\\xb1\\xd7\\xf7', rsNonCharRange = '\\x00-\\x2f\\x3a-\\x40\\x5b-\\x60\\x7b-\\xbf', rsPunctuationRange = '\\u2000-\\u206f', rsSpaceRange = ' \\t\\x0b\\f\\xa0\\ufeff\\n\\r\\u2028\\u2029\\u1680\\u180e\\u2000\\u2001\\u2002\\u2003\\u2004\\u2005\\u2006\\u2007\\u2008\\u2009\\u200a\\u202f\\u205f\\u3000', rsUpperRange = 'A-Z\\xc0-\\xd6\\xd8-\\xde', rsVarRange = '\\ufe0e\\ufe0f', rsBreakRange = rsMathOpRange + rsNonCharRange + rsPunctuationRange + rsSpaceRange; /** Used to compose unicode capture groups. */ var rsApos = "['\u2019]", rsAstral = '[' + rsAstralRange + ']', rsBreak = '[' + rsBreakRange + ']', rsCombo = '[' + rsComboRange + ']', rsDigits = '\\d+', rsDingbat = '[' + rsDingbatRange + ']', rsLower = '[' + rsLowerRange + ']', rsMisc = '[^' + rsAstralRange + rsBreakRange + rsDigits + rsDingbatRange + rsLowerRange + rsUpperRange + ']', rsFitz = '\\ud83c[\\udffb-\\udfff]', rsModifier = '(?:' + rsCombo + '|' + rsFitz + ')', rsNonAstral = '[^' + rsAstralRange + ']', rsRegional = '(?:\\ud83c[\\udde6-\\uddff]){2}', rsSurrPair = '[\\ud800-\\udbff][\\udc00-\\udfff]', rsUpper = '[' + rsUpperRange + ']', rsZWJ = '\\u200d'; /** Used to compose unicode regexes. */ var rsMiscLower = '(?:' + rsLower + '|' + rsMisc + ')', rsMiscUpper = '(?:' + rsUpper + '|' + rsMisc + ')', rsOptContrLower = '(?:' + rsApos + '(?:d|ll|m|re|s|t|ve))?', rsOptContrUpper = '(?:' + rsApos + '(?:D|LL|M|RE|S|T|VE))?', reOptMod = rsModifier + '?', rsOptVar = '[' + rsVarRange + ']?', rsOptJoin = '(?:' + rsZWJ + '(?:' + [rsNonAstral, rsRegional, rsSurrPair].join('|') + ')' + rsOptVar + reOptMod + ')*', rsOrdLower = '\\d*(?:1st|2nd|3rd|(?![123])\\dth)(?=\\b|[A-Z_])', rsOrdUpper = '\\d*(?:1ST|2ND|3RD|(?![123])\\dTH)(?=\\b|[a-z_])', rsSeq = rsOptVar + reOptMod + rsOptJoin, rsEmoji = '(?:' + [rsDingbat, rsRegional, rsSurrPair].join('|') + ')' + rsSeq, rsSymbol = '(?:' + [rsNonAstral + rsCombo + '?', rsCombo, rsRegional, rsSurrPair, rsAstral].join('|') + ')'; /** Used to match apostrophes. */ var reApos = RegExp(rsApos, 'g'); /** * Used to match [combining diacritical marks](https://en.wikipedia.org/wiki/Combining_Diacritical_Marks) and * [combining diacritical marks for symbols](https://en.wikipedia.org/wiki/Combining_Diacritical_Marks_for_Symbols). */ var reComboMark = RegExp(rsCombo, 'g'); /** Used to match [string symbols](https://mathiasbynens.be/notes/javascript-unicode). */ var reUnicode = RegExp(rsFitz + '(?=' + rsFitz + ')|' + rsSymbol + rsSeq, 'g'); /** Used to match complex or compound words. */ var reUnicodeWord = RegExp([ rsUpper + '?' + rsLower + '+' + rsOptContrLower + '(?=' + [rsBreak, rsUpper, '$'].join('|') + ')', rsMiscUpper + '+' + rsOptContrUpper + '(?=' + [rsBreak, rsUpper + rsMiscLower, '$'].join('|') + ')', rsUpper + '?' + rsMiscLower + '+' + rsOptContrLower, rsUpper + '+' + rsOptContrUpper, rsOrdUpper, rsOrdLower, rsDigits, rsEmoji ].join('|'), 'g'); /** Used to detect strings with [zero-width joiners or code points from the astral planes](http://eev.ee/blog/2015/09/12/dark-corners-of-unicode/). */ var reHasUnicode = RegExp('[' + rsZWJ + rsAstralRange + rsComboRange + rsVarRange + ']'); /** Used to detect strings that need a more robust regexp to match words. */ var reHasUnicodeWord = /[a-z][A-Z]|[A-Z]{2}[a-z]|[0-9][a-zA-Z]|[a-zA-Z][0-9]|[^a-zA-Z0-9 ]/; /** Used to assign default `context` object properties. */ var contextProps = [ 'Array', 'Buffer', 'DataView', 'Date', 'Error', 'Float32Array', 'Float64Array', 'Function', 'Int8Array', 'Int16Array', 'Int32Array', 'Map', 'Math', 'Object', 'Promise', 'RegExp', 'Set', 'String', 'Symbol', 'TypeError', 'Uint8Array', 'Uint8ClampedArray', 'Uint16Array', 'Uint32Array', 'WeakMap', '_', 'clearTimeout', 'isFinite', 'parseInt', 'setTimeout' ]; /** Used to make template sourceURLs easier to identify. */ var templateCounter = -1; /** Used to identify `toStringTag` values of typed arrays. */ var typedArrayTags = {}; typedArrayTags[float32Tag] = typedArrayTags[float64Tag] = typedArrayTags[int8Tag] = typedArrayTags[int16Tag] = typedArrayTags[int32Tag] = typedArrayTags[uint8Tag] = typedArrayTags[uint8ClampedTag] = typedArrayTags[uint16Tag] = typedArrayTags[uint32Tag] = true; typedArrayTags[argsTag] = typedArrayTags[arrayTag] = typedArrayTags[arrayBufferTag] = typedArrayTags[boolTag] = typedArrayTags[dataViewTag] = typedArrayTags[dateTag] = typedArrayTags[errorTag] = typedArrayTags[funcTag] = typedArrayTags[mapTag] = typedArrayTags[numberTag] = typedArrayTags[objectTag] = typedArrayTags[regexpTag] = typedArrayTags[setTag] = typedArrayTags[stringTag] = typedArrayTags[weakMapTag] = false; /** Used to identify `toStringTag` values supported by `_.clone`. */ var cloneableTags = {}; cloneableTags[argsTag] = cloneableTags[arrayTag] = cloneableTags[arrayBufferTag] = cloneableTags[dataViewTag] = cloneableTags[boolTag] = cloneableTags[dateTag] = cloneableTags[float32Tag] = cloneableTags[float64Tag] = cloneableTags[int8Tag] = cloneableTags[int16Tag] = cloneableTags[int32Tag] = cloneableTags[mapTag] = cloneableTags[numberTag] = cloneableTags[objectTag] = cloneableTags[regexpTag] = cloneableTags[setTag] = cloneableTags[stringTag] = cloneableTags[symbolTag] = cloneableTags[uint8Tag] = cloneableTags[uint8ClampedTag] = cloneableTags[uint16Tag] = cloneableTags[uint32Tag] = true; cloneableTags[errorTag] = cloneableTags[funcTag] = cloneableTags[weakMapTag] = false; /** Used to map Latin Unicode letters to basic Latin letters. */ var deburredLetters = { // Latin-1 Supplement block. '\xc0': 'A', '\xc1': 'A', '\xc2': 'A', '\xc3': 'A', '\xc4': 'A', '\xc5': 'A', '\xe0': 'a', '\xe1': 'a', '\xe2': 'a', '\xe3': 'a', '\xe4': 'a', '\xe5': 'a', '\xc7': 'C', '\xe7': 'c', '\xd0': 'D', '\xf0': 'd', '\xc8': 'E', '\xc9': 'E', '\xca': 'E', '\xcb': 'E', '\xe8': 'e', '\xe9': 'e', '\xea': 'e', '\xeb': 'e', '\xcc': 'I', '\xcd': 'I', '\xce': 'I', '\xcf': 'I', '\xec': 'i', '\xed': 'i', '\xee': 'i', '\xef': 'i', '\xd1': 'N', '\xf1': 'n', '\xd2': 'O', '\xd3': 'O', '\xd4': 'O', '\xd5': 'O', '\xd6': 'O', '\xd8': 'O', '\xf2': 'o', '\xf3': 'o', '\xf4': 'o', '\xf5': 'o', '\xf6': 'o', '\xf8': 'o', '\xd9': 'U', '\xda': 'U', '\xdb': 'U', '\xdc': 'U', '\xf9': 'u', '\xfa': 'u', '\xfb': 'u', '\xfc': 'u', '\xdd': 'Y', '\xfd': 'y', '\xff': 'y', '\xc6': 'Ae', '\xe6': 'ae', '\xde': 'Th', '\xfe': 'th', '\xdf': 'ss', // Latin Extended-A block. '\u0100': 'A', '\u0102': 'A', '\u0104': 'A', '\u0101': 'a', '\u0103': 'a', '\u0105': 'a', '\u0106': 'C', '\u0108': 'C', '\u010a': 'C', '\u010c': 'C', '\u0107': 'c', '\u0109': 'c', '\u010b': 'c', '\u010d': 'c', '\u010e': 'D', '\u0110': 'D', '\u010f': 'd', '\u0111': 'd', '\u0112': 'E', '\u0114': 'E', '\u0116': 'E', '\u0118': 'E', '\u011a': 'E', '\u0113': 'e', '\u0115': 'e', '\u0117': 'e', '\u0119': 'e', '\u011b': 'e', '\u011c': 'G', '\u011e': 'G', '\u0120': 'G', '\u0122': 'G', '\u011d': 'g', '\u011f': 'g', '\u0121': 'g', '\u0123': 'g', '\u0124': 'H', '\u0126': 'H', '\u0125': 'h', '\u0127': 'h', '\u0128': 'I', '\u012a': 'I', '\u012c': 'I', '\u012e': 'I', '\u0130': 'I', '\u0129': 'i', '\u012b': 'i', '\u012d': 'i', '\u012f': 'i', '\u0131': 'i', '\u0134': 'J', '\u0135': 'j', '\u0136': 'K', '\u0137': 'k', '\u0138': 'k', '\u0139': 'L', '\u013b': 'L', '\u013d': 'L', '\u013f': 'L', '\u0141': 'L', '\u013a': 'l', '\u013c': 'l', '\u013e': 'l', '\u0140': 'l', '\u0142': 'l', '\u0143': 'N', '\u0145': 'N', '\u0147': 'N', '\u014a': 'N', '\u0144': 'n', '\u0146': 'n', '\u0148': 'n', '\u014b': 'n', '\u014c': 'O', '\u014e': 'O', '\u0150': 'O', '\u014d': 'o', '\u014f': 'o', '\u0151': 'o', '\u0154': 'R', '\u0156': 'R', '\u0158': 'R', '\u0155': 'r', '\u0157': 'r', '\u0159': 'r', '\u015a': 'S', '\u015c': 'S', '\u015e': 'S', '\u0160': 'S', '\u015b': 's', '\u015d': 's', '\u015f': 's', '\u0161': 's', '\u0162': 'T', '\u0164': 'T', '\u0166': 'T', '\u0163': 't', '\u0165': 't', '\u0167': 't', '\u0168': 'U', '\u016a': 'U', '\u016c': 'U', '\u016e': 'U', '\u0170': 'U', '\u0172': 'U', '\u0169': 'u', '\u016b': 'u', '\u016d': 'u', '\u016f': 'u', '\u0171': 'u', '\u0173': 'u', '\u0174': 'W', '\u0175': 'w', '\u0176': 'Y', '\u0177': 'y', '\u0178': 'Y', '\u0179': 'Z', '\u017b': 'Z', '\u017d': 'Z', '\u017a': 'z', '\u017c': 'z', '\u017e': 'z', '\u0132': 'IJ', '\u0133': 'ij', '\u0152': 'Oe', '\u0153': 'oe', '\u0149': "'n", '\u017f': 's' }; /** Used to map characters to HTML entities. */ var htmlEscapes = { '&': '&', '<': '<', '>': '>', '"': '"', "'": ''' }; /** Used to map HTML entities to characters. */ var htmlUnescapes = { '&': '&', '<': '<', '>': '>', '"': '"', ''': "'" }; /** Used to escape characters for inclusion in compiled string literals. */ var stringEscapes = { '\\': '\\', "'": "'", '\n': 'n', '\r': 'r', '\u2028': 'u2028', '\u2029': 'u2029' }; /** Built-in method references without a dependency on `root`. */ var freeParseFloat = parseFloat, freeParseInt = parseInt; /** Detect free variable `global` from Node.js. */ var freeGlobal = typeof global == 'object' && global && global.Object === Object && global; /** Detect free variable `self`. */ var freeSelf = typeof self == 'object' && self && self.Object === Object && self; /** Used as a reference to the global object. */ var root = freeGlobal || freeSelf || Function('return this')(); /** Detect free variable `exports`. */ var freeExports = typeof exports == 'object' && exports && !exports.nodeType && exports; /** Detect free variable `module`. */ var freeModule = freeExports && typeof module == 'object' && module && !module.nodeType && module; /** Detect the popular CommonJS extension `module.exports`. */ var moduleExports = freeModule && freeModule.exports === freeExports; /** Detect free variable `process` from Node.js. */ var freeProcess = moduleExports && freeGlobal.process; /** Used to access faster Node.js helpers. */ var nodeUtil = (function() { try { // Use `util.types` for Node.js 10+. var types = freeModule && freeModule.require && freeModule.require('util').types; if (types) { return types; } // Legacy `process.binding('util')` for Node.js < 10. return freeProcess && freeProcess.binding && freeProcess.binding('util'); } catch (e) {} }()); /* Node.js helper references. */ var nodeIsArrayBuffer = nodeUtil && nodeUtil.isArrayBuffer, nodeIsDate = nodeUtil && nodeUtil.isDate, nodeIsMap = nodeUtil && nodeUtil.isMap, nodeIsRegExp = nodeUtil && nodeUtil.isRegExp, nodeIsSet = nodeUtil && nodeUtil.isSet, nodeIsTypedArray = nodeUtil && nodeUtil.isTypedArray; /*--------------------------------------------------------------------------*/ /** * A faster alternative to `Function#apply`, this function invokes `func` * with the `this` binding of `thisArg` and the arguments of `args`. * * @private * @param {Function} func The function to invoke. * @param {*} thisArg The `this` binding of `func`. * @param {Array} args The arguments to invoke `func` with. * @returns {*} Returns the result of `func`. */ function apply(func, thisArg, args) { switch (args.length) { case 0: return func.call(thisArg); case 1: return func.call(thisArg, args[0]); case 2: return func.call(thisArg, args[0], args[1]); case 3: return func.call(thisArg, args[0], args[1], args[2]); } return func.apply(thisArg, args); } /** * A specialized version of `baseAggregator` for arrays. * * @private * @param {Array} [array] The array to iterate over. * @param {Function} setter The function to set `accumulator` values. * @param {Function} iteratee The iteratee to transform keys. * @param {Object} accumulator The initial aggregated object. * @returns {Function} Returns `accumulator`. */ function arrayAggregator(array, setter, iteratee, accumulator) { var index = -1, length = array == null ? 0 : array.length; while (++index < length) { var value = array[index]; setter(accumulator, value, iteratee(value), array); } return accumulator; } /** * A specialized version of `_.forEach` for arrays without support for * iteratee shorthands. * * @private * @param {Array} [array] The array to iterate over. * @param {Function} iteratee The function invoked per iteration. * @returns {Array} Returns `array`. */ function arrayEach(array, iteratee) { var index = -1, length = array == null ? 0 : array.length; while (++index < length) { if (iteratee(array[index], index, array) === false) { break; } } return array; } /** * A specialized version of `_.forEachRight` for arrays without support for * iteratee shorthands. * * @private * @param {Array} [array] The array to iterate over. * @param {Function} iteratee The function invoked per iteration. * @returns {Array} Returns `array`. */ function arrayEachRight(array, iteratee) { var length = array == null ? 0 : array.length; while (length--) { if (iteratee(array[length], length, array) === false) { break; } } return array; } /** * A specialized version of `_.every` for arrays without support for * iteratee shorthands. * * @private * @param {Array} [array] The array to iterate over. * @param {Function} predicate The function invoked per iteration. * @returns {boolean} Returns `true` if all elements pass the predicate check, * else `false`. */ function arrayEvery(array, predicate) { var index = -1, length = array == null ? 0 : array.length; while (++index < length) { if (!predicate(array[index], index, array)) { return false; } } return true; } /** * A specialized version of `_.filter` for arrays without support for * iteratee shorthands. * * @private * @param {Array} [array] The array to iterate over. * @param {Function} predicate The function invoked per iteration. * @returns {Array} Returns the new filtered array. */ function arrayFilter(array, predicate) { var index = -1, length = array == null ? 0 : array.length, resIndex = 0, result = []; while (++index < length) { var value = array[index]; if (predicate(value, index, array)) { result[resIndex++] = value; } } return result; } /** * A specialized version of `_.includes` for arrays without support for * specifying an index to search from. * * @private * @param {Array} [array] The array to inspect. * @param {*} target The value to search for. * @returns {boolean} Returns `true` if `target` is found, else `false`. */ function arrayIncludes(array, value) { var length = array == null ? 0 : array.length; return !!length && baseIndexOf(array, value, 0) > -1; } /** * This function is like `arrayIncludes` except that it accepts a comparator. * * @private * @param {Array} [array] The array to inspect. * @param {*} target The value to search for. * @param {Function} comparator The comparator invoked per element. * @returns {boolean} Returns `true` if `target` is found, else `false`. */ function arrayIncludesWith(array, value, comparator) { var index = -1, length = array == null ? 0 : array.length; while (++index < length) { if (comparator(value, array[index])) { return true; } } return false; } /** * A specialized version of `_.map` for arrays without support for iteratee * shorthands. * * @private * @param {Array} [array] The array to iterate over. * @param {Function} iteratee The function invoked per iteration. * @returns {Array} Returns the new mapped array. */ function arrayMap(array, iteratee) { var index = -1, length = array == null ? 0 : array.length, result = Array(length); while (++index < length) { result[index] = iteratee(array[index], index, array); } return result; } /** * Appends the elements of `values` to `array`. * * @private * @param {Array} array The array to modify. * @param {Array} values The values to append. * @returns {Array} Returns `array`. */ function arrayPush(array, values) { var index = -1, length = values.length, offset = array.length; while (++index < length) { array[offset + index] = values[index]; } return array; } /** * A specialized version of `_.reduce` for arrays without support for * iteratee shorthands. * * @private * @param {Array} [array] The array to iterate over. * @param {Function} iteratee The function invoked per iteration. * @param {*} [accumulator] The initial value. * @param {boolean} [initAccum] Specify using the first element of `array` as * the initial value. * @returns {*} Returns the accumulated value. */ function arrayReduce(array, iteratee, accumulator, initAccum) { var index = -1, length = array == null ? 0 : array.length; if (initAccum && length) { accumulator = array[++index]; } while (++index < length) { accumulator = iteratee(accumulator, array[index], index, array); } return accumulator; } /** * A specialized version of `_.reduceRight` for arrays without support for * iteratee shorthands. * * @private * @param {Array} [array] The array to iterate over. * @param {Function} iteratee The function invoked per iteration. * @param {*} [accumulator] The initial value. * @param {boolean} [initAccum] Specify using the last element of `array` as * the initial value. * @returns {*} Returns the accumulated value. */ function arrayReduceRight(array, iteratee, accumulator, initAccum) { var length = array == null ? 0 : array.length; if (initAccum && length) { accumulator = array[--length]; } while (length--) { accumulator = iteratee(accumulator, array[length], length, array); } return accumulator; } /** * A specialized version of `_.some` for arrays without support for iteratee * shorthands. * * @private * @param {Array} [array] The array to iterate over. * @param {Function} predicate The function invoked per iteration. * @returns {boolean} Returns `true` if any element passes the predicate check, * else `false`. */ function arraySome(array, predicate) { var index = -1, length = array == null ? 0 : array.length; while (++index < length) { if (predicate(array[index], index, array)) { return true; } } return false; } /** * Gets the size of an ASCII `string`. * * @private * @param {string} string The string inspect. * @returns {number} Returns the string size. */ var asciiSize = baseProperty('length'); /** * Converts an ASCII `string` to an array. * * @private * @param {string} string The string to convert. * @returns {Array} Returns the converted array. */ function asciiToArray(string) { return string.split(''); } /** * Splits an ASCII `string` into an array of its words. * * @private * @param {string} The string to inspect. * @returns {Array} Returns the words of `string`. */ function asciiWords(string) { return string.match(reAsciiWord) || []; } /** * The base implementation of methods like `_.findKey` and `_.findLastKey`, * without support for iteratee shorthands, which iterates over `collection` * using `eachFunc`. * * @private * @param {Array|Object} collection The collection to inspect. * @param {Function} predicate The function invoked per iteration. * @param {Function} eachFunc The function to iterate over `collection`. * @returns {*} Returns the found element or its key, else `undefined`. */ function baseFindKey(collection, predicate, eachFunc) { var result; eachFunc(collection, function(value, key, collection) { if (predicate(value, key, collection)) { result = key; return false; } }); return result; } /** * The base implementation of `_.findIndex` and `_.findLastIndex` without * support for iteratee shorthands. * * @private * @param {Array} array The array to inspect. * @param {Function} predicate The function invoked per iteration. * @param {number} fromIndex The index to search from. * @param {boolean} [fromRight] Specify iterating from right to left. * @returns {number} Returns the index of the matched value, else `-1`. */ function baseFindIndex(array, predicate, fromIndex, fromRight) { var length = array.length, index = fromIndex + (fromRight ? 1 : -1); while ((fromRight ? index-- : ++index < length)) { if (predicate(array[index], index, array)) { return index; } } return -1; } /** * The base implementation of `_.indexOf` without `fromIndex` bounds checks. * * @private * @param {Array} array The array to inspect. * @param {*} value The value to search for. * @param {number} fromIndex The index to search from. * @returns {number} Returns the index of the matched value, else `-1`. */ function baseIndexOf(array, value, fromIndex) { return value === value ? strictIndexOf(array, value, fromIndex) : baseFindIndex(array, baseIsNaN, fromIndex); } /** * This function is like `baseIndexOf` except that it accepts a comparator. * * @private * @param {Array} array The array to inspect. * @param {*} value The value to search for. * @param {number} fromIndex The index to search from. * @param {Function} comparator The comparator invoked per element. * @returns {number} Returns the index of the matched value, else `-1`. */ function baseIndexOfWith(array, value, fromIndex, comparator) { var index = fromIndex - 1, length = array.length; while (++index < length) { if (comparator(array[index], value)) { return index; } } return -1; } /** * The base implementation of `_.isNaN` without support for number objects. * * @private * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is `NaN`, else `false`. */ function baseIsNaN(value) { return value !== value; } /** * The base implementation of `_.mean` and `_.meanBy` without support for * iteratee shorthands. * * @private * @param {Array} array The array to iterate over. * @param {Function} iteratee The function invoked per iteration. * @returns {number} Returns the mean. */ function baseMean(array, iteratee) { var length = array == null ? 0 : array.length; return length ? (baseSum(array, iteratee) / length) : NAN; } /** * The base implementation of `_.property` without support for deep paths. * * @private * @param {string} key The key of the property to get. * @returns {Function} Returns the new accessor function. */ function baseProperty(key) { return function(object) { return object == null ? undefined : object[key]; }; } /** * The base implementation of `_.propertyOf` without support for deep paths. * * @private * @param {Object} object The object to query. * @returns {Function} Returns the new accessor function. */ function basePropertyOf(object) { return function(key) { return object == null ? undefined : object[key]; }; } /** * The base implementation of `_.reduce` and `_.reduceRight`, without support * for iteratee shorthands, which iterates over `collection` using `eachFunc`. * * @private * @param {Array|Object} collection The collection to iterate over. * @param {Function} iteratee The function invoked per iteration. * @param {*} accumulator The initial value. * @param {boolean} initAccum Specify using the first or last element of * `collection` as the initial value. * @param {Function} eachFunc The function to iterate over `collection`. * @returns {*} Returns the accumulated value. */ function baseReduce(collection, iteratee, accumulator, initAccum, eachFunc) { eachFunc(collection, function(value, index, collection) { accumulator = initAccum ? (initAccum = false, value) : iteratee(accumulator, value, index, collection); }); return accumulator; } /** * The base implementation of `_.sortBy` which uses `comparer` to define the * sort order of `array` and replaces criteria objects with their corresponding * values. * * @private * @param {Array} array The array to sort. * @param {Function} comparer The function to define sort order. * @returns {Array} Returns `array`. */ function baseSortBy(array, comparer) { var length = array.length; array.sort(comparer); while (length--) { array[length] = array[length].value; } return array; } /** * The base implementation of `_.sum` and `_.sumBy` without support for * iteratee shorthands. * * @private * @param {Array} array The array to iterate over. * @param {Function} iteratee The function invoked per iteration. * @returns {number} Returns the sum. */ function baseSum(array, iteratee) { var result, index = -1, length = array.length; while (++index < length) { var current = iteratee(array[index]); if (current !== undefined) { result = result === undefined ? current : (result + current); } } return result; } /** * The base implementation of `_.times` without support for iteratee shorthands * or max array length checks. * * @private * @param {number} n The number of times to invoke `iteratee`. * @param {Function} iteratee The function invoked per iteration. * @returns {Array} Returns the array of results. */ function baseTimes(n, iteratee) { var index = -1, result = Array(n); while (++index < n) { result[index] = iteratee(index); } return result; } /** * The base implementation of `_.toPairs` and `_.toPairsIn` which creates an array * of key-value pairs for `object` corresponding to the property names of `props`. * * @private * @param {Object} object The object to query. * @param {Array} props The property names to get values for. * @returns {Object} Returns the key-value pairs. */ function baseToPairs(object, props) { return arrayMap(props, function(key) { return [key, object[key]]; }); } /** * The base implementation of `_.unary` without support for storing metadata. * * @private * @param {Function} func The function to cap arguments for. * @returns {Function} Returns the new capped function. */ function baseUnary(func) { return function(value) { return func(value); }; } /** * The base implementation of `_.values` and `_.valuesIn` which creates an * array of `object` property values corresponding to the property names * of `props`. * * @private * @param {Object} object The object to query. * @param {Array} props The property names to get values for. * @returns {Object} Returns the array of property values. */ function baseValues(object, props) { return arrayMap(props, function(key) { return object[key]; }); } /** * Checks if a `cache` value for `key` exists. * * @private * @param {Object} cache The cache to query. * @param {string} key The key of the entry to check. * @returns {boolean} Returns `true` if an entry for `key` exists, else `false`. */ function cacheHas(cache, key) { return cache.has(key); } /** * Used by `_.trim` and `_.trimStart` to get the index of the first string symbol * that is not found in the character symbols. * * @private * @param {Array} strSymbols The string symbols to inspect. * @param {Array} chrSymbols The character symbols to find. * @returns {number} Returns the index of the first unmatched string symbol. */ function charsStartIndex(strSymbols, chrSymbols) { var index = -1, length = strSymbols.length; while (++index < length && baseIndexOf(chrSymbols, strSymbols[index], 0) > -1) {} return index; } /** * Used by `_.trim` and `_.trimEnd` to get the index of the last string symbol * that is not found in the character symbols. * * @private * @param {Array} strSymbols The string symbols to inspect. * @param {Array} chrSymbols The character symbols to find. * @returns {number} Returns the index of the last unmatched string symbol. */ function charsEndIndex(strSymbols, chrSymbols) { var index = strSymbols.length; while (index-- && baseIndexOf(chrSymbols, strSymbols[index], 0) > -1) {} return index; } /** * Gets the number of `placeholder` occurrences in `array`. * * @private * @param {Array} array The array to inspect. * @param {*} placeholder The placeholder to search for. * @returns {number} Returns the placeholder count. */ function countHolders(array, placeholder) { var length = array.length, result = 0; while (length--) { if (array[length] === placeholder) { ++result; } } return result; } /** * Used by `_.deburr` to convert Latin-1 Supplement and Latin Extended-A * letters to basic Latin letters. * * @private * @param {string} letter The matched letter to deburr. * @returns {string} Returns the deburred letter. */ var deburrLetter = basePropertyOf(deburredLetters); /** * Used by `_.escape` to convert characters to HTML entities. * * @private * @param {string} chr The matched character to escape. * @returns {string} Returns the escaped character. */ var escapeHtmlChar = basePropertyOf(htmlEscapes); /** * Used by `_.template` to escape characters for inclusion in compiled string literals. * * @private * @param {string} chr The matched character to escape. * @returns {string} Returns the escaped character. */ function escapeStringChar(chr) { return '\\' + stringEscapes[chr]; } /** * Gets the value at `key` of `object`. * * @private * @param {Object} [object] The object to query. * @param {string} key The key of the property to get. * @returns {*} Returns the property value. */ function getValue(object, key) { return object == null ? undefined : object[key]; } /** * Checks if `string` contains Unicode symbols. * * @private * @param {string} string The string to inspect. * @returns {boolean} Returns `true` if a symbol is found, else `false`. */ function hasUnicode(string) { return reHasUnicode.test(string); } /** * Checks if `string` contains a word composed of Unicode symbols. * * @private * @param {string} string The string to inspect. * @returns {boolean} Returns `true` if a word is found, else `false`. */ function hasUnicodeWord(string) { return reHasUnicodeWord.test(string); } /** * Converts `iterator` to an array. * * @private * @param {Object} iterator The iterator to convert. * @returns {Array} Returns the converted array. */ function iteratorToArray(iterator) { var data, result = []; while (!(data = iterator.next()).done) { result.push(data.value); } return result; } /** * Converts `map` to its key-value pairs. * * @private * @param {Object} map The map to convert. * @returns {Array} Returns the key-value pairs. */ function mapToArray(map) { var index = -1, result = Array(map.size); map.forEach(function(value, key) { result[++index] = [key, value]; }); return result; } /** * Creates a unary function that invokes `func` with its argument transformed. * * @private * @param {Function} func The function to wrap. * @param {Function} transform The argument transform. * @returns {Function} Returns the new function. */ function overArg(func, transform) { return function(arg) { return func(transform(arg)); }; } /** * Replaces all `placeholder` elements in `array` with an internal placeholder * and returns an array of their indexes. * * @private * @param {Array} array The array to modify. * @param {*} placeholder The placeholder to replace. * @returns {Array} Returns the new array of placeholder indexes. */ function replaceHolders(array, placeholder) { var index = -1, length = array.length, resIndex = 0, result = []; while (++index < length) { var value = array[index]; if (value === placeholder || value === PLACEHOLDER) { array[index] = PLACEHOLDER; result[resIndex++] = index; } } return result; } /** * Converts `set` to an array of its values. * * @private * @param {Object} set The set to convert. * @returns {Array} Returns the values. */ function setToArray(set) { var index = -1, result = Array(set.size); set.forEach(function(value) { result[++index] = value; }); return result; } /** * Converts `set` to its value-value pairs. * * @private * @param {Object} set The set to convert. * @returns {Array} Returns the value-value pairs. */ function setToPairs(set) { var index = -1, result = Array(set.size); set.forEach(function(value) { result[++index] = [value, value]; }); return result; } /** * A specialized version of `_.indexOf` which performs strict equality * comparisons of values, i.e. `===`. * * @private * @param {Array} array The array to inspect. * @param {*} value The value to search for. * @param {number} fromIndex The index to search from. * @returns {number} Returns the index of the matched value, else `-1`. */ function strictIndexOf(array, value, fromIndex) { var index = fromIndex - 1, length = array.length; while (++index < length) { if (array[index] === value) { return index; } } return -1; } /** * A specialized version of `_.lastIndexOf` which performs strict equality * comparisons of values, i.e. `===`. * * @private * @param {Array} array The array to inspect. * @param {*} value The value to search for. * @param {number} fromIndex The index to search from. * @returns {number} Returns the index of the matched value, else `-1`. */ function strictLastIndexOf(array, value, fromIndex) { var index = fromIndex + 1; while (index--) { if (array[index] === value) { return index; } } return index; } /** * Gets the number of symbols in `string`. * * @private * @param {string} string The string to inspect. * @returns {number} Returns the string size. */ function stringSize(string) { return hasUnicode(string) ? unicodeSize(string) : asciiSize(string); } /** * Converts `string` to an array. * * @private * @param {string} string The string to convert. * @returns {Array} Returns the converted array. */ function stringToArray(string) { return hasUnicode(string) ? unicodeToArray(string) : asciiToArray(string); } /** * Used by `_.unescape` to convert HTML entities to characters. * * @private * @param {string} chr The matched character to unescape. * @returns {string} Returns the unescaped character. */ var unescapeHtmlChar = basePropertyOf(htmlUnescapes); /** * Gets the size of a Unicode `string`. * * @private * @param {string} string The string inspect. * @returns {number} Returns the string size. */ function unicodeSize(string) { var result = reUnicode.lastIndex = 0; while (reUnicode.test(string)) { ++result; } return result; } /** * Converts a Unicode `string` to an array. * * @private * @param {string} string The string to convert. * @returns {Array} Returns the converted array. */ function unicodeToArray(string) { return string.match(reUnicode) || []; } /** * Splits a Unicode `string` into an array of its words. * * @private * @param {string} The string to inspect. * @returns {Array} Returns the words of `string`. */ function unicodeWords(string) { return string.match(reUnicodeWord) || []; } /*--------------------------------------------------------------------------*/ /** * Create a new pristine `lodash` function using the `context` object. * * @static * @memberOf _ * @since 1.1.0 * @category Util * @param {Object} [context=root] The context object. * @returns {Function} Returns a new `lodash` function. * @example * * _.mixin({ 'foo': _.constant('foo') }); * * var lodash = _.runInContext(); * lodash.mixin({ 'bar': lodash.constant('bar') }); * * _.isFunction(_.foo); * // => true * _.isFunction(_.bar); * // => false * * lodash.isFunction(lodash.foo); * // => false * lodash.isFunction(lodash.bar); * // => true * * // Create a suped-up `defer` in Node.js. * var defer = _.runInContext({ 'setTimeout': setImmediate }).defer; */ var runInContext = (function runInContext(context) { context = context == null ? root : _.defaults(root.Object(), context, _.pick(root, contextProps)); /** Built-in constructor references. */ var Array = context.Array, Date = context.Date, Error = context.Error, Function = context.Function, Math = context.Math, Object = context.Object, RegExp = context.RegExp, String = context.String, TypeError = context.TypeError; /** Used for built-in method references. */ var arrayProto = Array.prototype, funcProto = Function.prototype, objectProto = Object.prototype; /** Used to detect overreaching core-js shims. */ var coreJsData = context['__core-js_shared__']; /** Used to resolve the decompiled source of functions. */ var funcToString = funcProto.toString; /** Used to check objects for own properties. */ var hasOwnProperty = objectProto.hasOwnProperty; /** Used to generate unique IDs. */ var idCounter = 0; /** Used to detect methods masquerading as native. */ var maskSrcKey = (function() { var uid = /[^.]+$/.exec(coreJsData && coreJsData.keys && coreJsData.keys.IE_PROTO || ''); return uid ? ('Symbol(src)_1.' + uid) : ''; }()); /** * Used to resolve the * [`toStringTag`](http://ecma-international.org/ecma-262/7.0/#sec-object.prototype.tostring) * of values. */ var nativeObjectToString = objectProto.toString; /** Used to infer the `Object` constructor. */ var objectCtorString = funcToString.call(Object); /** Used to restore the original `_` reference in `_.noConflict`. */ var oldDash = root._; /** Used to detect if a method is native. */ var reIsNative = RegExp('^' + funcToString.call(hasOwnProperty).replace(reRegExpChar, '\\$&') .replace(/hasOwnProperty|(function).*?(?=\\\()| for .+?(?=\\\])/g, '$1.*?') + '$' ); /** Built-in value references. */ var Buffer = moduleExports ? context.Buffer : undefined, Symbol = context.Symbol, Uint8Array = context.Uint8Array, allocUnsafe = Buffer ? Buffer.allocUnsafe : undefined, getPrototype = overArg(Object.getPrototypeOf, Object), objectCreate = Object.create, propertyIsEnumerable = objectProto.propertyIsEnumerable, splice = arrayProto.splice, spreadableSymbol = Symbol ? Symbol.isConcatSpreadable : undefined, symIterator = Symbol ? Symbol.iterator : undefined, symToStringTag = Symbol ? Symbol.toStringTag : undefined; var defineProperty = (function() { try { var func = getNative(Object, 'defineProperty'); func({}, '', {}); return func; } catch (e) {} }()); /** Mocked built-ins. */ var ctxClearTimeout = context.clearTimeout !== root.clearTimeout && context.clearTimeout, ctxNow = Date && Date.now !== root.Date.now && Date.now, ctxSetTimeout = context.setTimeout !== root.setTimeout && context.setTimeout; /* Built-in method references for those with the same name as other `lodash` methods. */ var nativeCeil = Math.ceil, nativeFloor = Math.floor, nativeGetSymbols = Object.getOwnPropertySymbols, nativeIsBuffer = Buffer ? Buffer.isBuffer : undefined, nativeIsFinite = context.isFinite, nativeJoin = arrayProto.join, nativeKeys = overArg(Object.keys, Object), nativeMax = Math.max, nativeMin = Math.min, nativeNow = Date.now, nativeParseInt = context.parseInt, nativeRandom = Math.random, nativeReverse = arrayProto.reverse; /* Built-in method references that are verified to be native. */ var DataView = getNative(context, 'DataView'), Map = getNative(context, 'Map'), Promise = getNative(context, 'Promise'), Set = getNative(context, 'Set'), WeakMap = getNative(context, 'WeakMap'), nativeCreate = getNative(Object, 'create'); /** Used to store function metadata. */ var metaMap = WeakMap && new WeakMap; /** Used to lookup unminified function names. */ var realNames = {}; /** Used to detect maps, sets, and weakmaps. */ var dataViewCtorString = toSource(DataView), mapCtorString = toSource(Map), promiseCtorString = toSource(Promise), setCtorString = toSource(Set), weakMapCtorString = toSource(WeakMap); /** Used to convert symbols to primitives and strings. */ var symbolProto = Symbol ? Symbol.prototype : undefined, symbolValueOf = symbolProto ? symbolProto.valueOf : undefined, symbolToString = symbolProto ? symbolProto.toString : undefined; /*------------------------------------------------------------------------*/ /** * Creates a `lodash` object which wraps `value` to enable implicit method * chain sequences. Methods that operate on and return arrays, collections, * and functions can be chained together. Methods that retrieve a single value * or may return a primitive value will automatically end the chain sequence * and return the unwrapped value. Otherwise, the value must be unwrapped * with `_#value`. * * Explicit chain sequences, which must be unwrapped with `_#value`, may be * enabled using `_.chain`. * * The execution of chained methods is lazy, that is, it's deferred until * `_#value` is implicitly or explicitly called. * * Lazy evaluation allows several methods to support shortcut fusion. * Shortcut fusion is an optimization to merge iteratee calls; this avoids * the creation of intermediate arrays and can greatly reduce the number of * iteratee executions. Sections of a chain sequence qualify for shortcut * fusion if the section is applied to an array and iteratees accept only * one argument. The heuristic for whether a section qualifies for shortcut * fusion is subject to change. * * Chaining is supported in custom builds as long as the `_#value` method is * directly or indirectly included in the build. * * In addition to lodash methods, wrappers have `Array` and `String` methods. * * The wrapper `Array` methods are: * `concat`, `join`, `pop`, `push`, `shift`, `sort`, `splice`, and `unshift` * * The wrapper `String` methods are: * `replace` and `split` * * The wrapper methods that support shortcut fusion are: * `at`, `compact`, `drop`, `dropRight`, `dropWhile`, `filter`, `find`, * `findLast`, `head`, `initial`, `last`, `map`, `reject`, `reverse`, `slice`, * `tail`, `take`, `takeRight`, `takeRightWhile`, `takeWhile`, and `toArray` * * The chainable wrapper methods are: * `after`, `ary`, `assign`, `assignIn`, `assignInWith`, `assignWith`, `at`, * `before`, `bind`, `bindAll`, `bindKey`, `castArray`, `chain`, `chunk`, * `commit`, `compact`, `concat`, `conforms`, `constant`, `countBy`, `create`, * `curry`, `debounce`, `defaults`, `defaultsDeep`, `defer`, `delay`, * `difference`, `differenceBy`, `differenceWith`, `drop`, `dropRight`, * `dropRightWhile`, `dropWhile`, `extend`, `extendWith`, `fill`, `filter`, * `flatMap`, `flatMapDeep`, `flatMapDepth`, `flatten`, `flattenDeep`, * `flattenDepth`, `flip`, `flow`, `flowRight`, `fromPairs`, `functions`, * `functionsIn`, `groupBy`, `initial`, `intersection`, `intersectionBy`, * `intersectionWith`, `invert`, `invertBy`, `invokeMap`, `iteratee`, `keyBy`, * `keys`, `keysIn`, `map`, `mapKeys`, `mapValues`, `matches`, `matchesProperty`, * `memoize`, `merge`, `mergeWith`, `method`, `methodOf`, `mixin`, `negate`, * `nthArg`, `omit`, `omitBy`, `once`, `orderBy`, `over`, `overArgs`, * `overEvery`, `overSome`, `partial`, `partialRight`, `partition`, `pick`, * `pickBy`, `plant`, `property`, `propertyOf`, `pull`, `pullAll`, `pullAllBy`, * `pullAllWith`, `pullAt`, `push`, `range`, `rangeRight`, `rearg`, `reject`, * `remove`, `rest`, `reverse`, `sampleSize`, `set`, `setWith`, `shuffle`, * `slice`, `sort`, `sortBy`, `splice`, `spread`, `tail`, `take`, `takeRight`, * `takeRightWhile`, `takeWhile`, `tap`, `throttle`, `thru`, `toArray`, * `toPairs`, `toPairsIn`, `toPath`, `toPlainObject`, `transform`, `unary`, * `union`, `unionBy`, `unionWith`, `uniq`, `uniqBy`, `uniqWith`, `unset`, * `unshift`, `unzip`, `unzipWith`, `update`, `updateWith`, `values`, * `valuesIn`, `without`, `wrap`, `xor`, `xorBy`, `xorWith`, `zip`, * `zipObject`, `zipObjectDeep`, and `zipWith` * * The wrapper methods that are **not** chainable by default are: * `add`, `attempt`, `camelCase`, `capitalize`, `ceil`, `clamp`, `clone`, * `cloneDeep`, `cloneDeepWith`, `cloneWith`, `conformsTo`, `deburr`, * `defaultTo`, `divide`, `each`, `eachRight`, `endsWith`, `eq`, `escape`, * `escapeRegExp`, `every`, `find`, `findIndex`, `findKey`, `findLast`, * `findLastIndex`, `findLastKey`, `first`, `floor`, `forEach`, `forEachRight`, * `forIn`, `forInRight`, `forOwn`, `forOwnRight`, `get`, `gt`, `gte`, `has`, * `hasIn`, `head`, `identity`, `includes`, `indexOf`, `inRange`, `invoke`, * `isArguments`, `isArray`, `isArrayBuffer`, `isArrayLike`, `isArrayLikeObject`, * `isBoolean`, `isBuffer`, `isDate`, `isElement`, `isEmpty`, `isEqual`, * `isEqualWith`, `isError`, `isFinite`, `isFunction`, `isInteger`, `isLength`, * `isMap`, `isMatch`, `isMatchWith`, `isNaN`, `isNative`, `isNil`, `isNull`, * `isNumber`, `isObject`, `isObjectLike`, `isPlainObject`, `isRegExp`, * `isSafeInteger`, `isSet`, `isString`, `isUndefined`, `isTypedArray`, * `isWeakMap`, `isWeakSet`, `join`, `kebabCase`, `last`, `lastIndexOf`, * `lowerCase`, `lowerFirst`, `lt`, `lte`, `max`, `maxBy`, `mean`, `meanBy`, * `min`, `minBy`, `multiply`, `noConflict`, `noop`, `now`, `nth`, `pad`, * `padEnd`, `padStart`, `parseInt`, `pop`, `random`, `reduce`, `reduceRight`, * `repeat`, `result`, `round`, `runInContext`, `sample`, `shift`, `size`, * `snakeCase`, `some`, `sortedIndex`, `sortedIndexBy`, `sortedLastIndex`, * `sortedLastIndexBy`, `startCase`, `startsWith`, `stubArray`, `stubFalse`, * `stubObject`, `stubString`, `stubTrue`, `subtract`, `sum`, `sumBy`, * `template`, `times`, `toFinite`, `toInteger`, `toJSON`, `toLength`, * `toLower`, `toNumber`, `toSafeInteger`, `toString`, `toUpper`, `trim`, * `trimEnd`, `trimStart`, `truncate`, `unescape`, `uniqueId`, `upperCase`, * `upperFirst`, `value`, and `words` * * @name _ * @constructor * @category Seq * @param {*} value The value to wrap in a `lodash` instance. * @returns {Object} Returns the new `lodash` wrapper instance. * @example * * function square(n) { * return n * n; * } * * var wrapped = _([1, 2, 3]); * * // Returns an unwrapped value. * wrapped.reduce(_.add); * // => 6 * * // Returns a wrapped value. * var squares = wrapped.map(square); * * _.isArray(squares); * // => false * * _.isArray(squares.value()); * // => true */ function lodash(value) { if (isObjectLike(value) && !isArray(value) && !(value instanceof LazyWrapper)) { if (value instanceof LodashWrapper) { return value; } if (hasOwnProperty.call(value, '__wrapped__')) { return wrapperClone(value); } } return new LodashWrapper(value); } /** * The base implementation of `_.create` without support for assigning * properties to the created object. * * @private * @param {Object} proto The object to inherit from. * @returns {Object} Returns the new object. */ var baseCreate = (function() { function object() {} return function(proto) { if (!isObject(proto)) { return {}; } if (objectCreate) { return objectCreate(proto); } object.prototype = proto; var result = new object; object.prototype = undefined; return result; }; }()); /** * The function whose prototype chain sequence wrappers inherit from. * * @private */ function baseLodash() { // No operation performed. } /** * The base constructor for creating `lodash` wrapper objects. * * @private * @param {*} value The value to wrap. * @param {boolean} [chainAll] Enable explicit method chain sequences. */ function LodashWrapper(value, chainAll) { this.__wrapped__ = value; this.__actions__ = []; this.__chain__ = !!chainAll; this.__index__ = 0; this.__values__ = undefined; } /** * By default, the template delimiters used by lodash are like those in * embedded Ruby (ERB) as well as ES2015 template strings. Change the * following template settings to use alternative delimiters. * * @static * @memberOf _ * @type {Object} */ lodash.templateSettings = { /** * Used to detect `data` property values to be HTML-escaped. * * @memberOf _.templateSettings * @type {RegExp} */ 'escape': reEscape, /** * Used to detect code to be evaluated. * * @memberOf _.templateSettings * @type {RegExp} */ 'evaluate': reEvaluate, /** * Used to detect `data` property values to inject. * * @memberOf _.templateSettings * @type {RegExp} */ 'interpolate': reInterpolate, /** * Used to reference the data object in the template text. * * @memberOf _.templateSettings * @type {string} */ 'variable': '', /** * Used to import variables into the compiled template. * * @memberOf _.templateSettings * @type {Object} */ 'imports': { /** * A reference to the `lodash` function. * * @memberOf _.templateSettings.imports * @type {Function} */ '_': lodash } }; // Ensure wrappers are instances of `baseLodash`. lodash.prototype = baseLodash.prototype; lodash.prototype.constructor = lodash; LodashWrapper.prototype = baseCreate(baseLodash.prototype); LodashWrapper.prototype.constructor = LodashWrapper; /*------------------------------------------------------------------------*/ /** * Creates a lazy wrapper object which wraps `value` to enable lazy evaluation. * * @private * @constructor * @param {*} value The value to wrap. */ function LazyWrapper(value) { this.__wrapped__ = value; this.__actions__ = []; this.__dir__ = 1; this.__filtered__ = false; this.__iteratees__ = []; this.__takeCount__ = MAX_ARRAY_LENGTH; this.__views__ = []; } /** * Creates a clone of the lazy wrapper object. * * @private * @name clone * @memberOf LazyWrapper * @returns {Object} Returns the cloned `LazyWrapper` object. */ function lazyClone() { var result = new LazyWrapper(this.__wrapped__); result.__actions__ = copyArray(this.__actions__); result.__dir__ = this.__dir__; result.__filtered__ = this.__filtered__; result.__iteratees__ = copyArray(this.__iteratees__); result.__takeCount__ = this.__takeCount__; result.__views__ = copyArray(this.__views__); return result; } /** * Reverses the direction of lazy iteration. * * @private * @name reverse * @memberOf LazyWrapper * @returns {Object} Returns the new reversed `LazyWrapper` object. */ function lazyReverse() { if (this.__filtered__) { var result = new LazyWrapper(this); result.__dir__ = -1; result.__filtered__ = true; } else { result = this.clone(); result.__dir__ *= -1; } return result; } /** * Extracts the unwrapped value from its lazy wrapper. * * @private * @name value * @memberOf LazyWrapper * @returns {*} Returns the unwrapped value. */ function lazyValue() { var array = this.__wrapped__.value(), dir = this.__dir__, isArr = isArray(array), isRight = dir < 0, arrLength = isArr ? array.length : 0, view = getView(0, arrLength, this.__views__), start = view.start, end = view.end, length = end - start, index = isRight ? end : (start - 1), iteratees = this.__iteratees__, iterLength = iteratees.length, resIndex = 0, takeCount = nativeMin(length, this.__takeCount__); if (!isArr || (!isRight && arrLength == length && takeCount == length)) { return baseWrapperValue(array, this.__actions__); } var result = []; outer: while (length-- && resIndex < takeCount) { index += dir; var iterIndex = -1, value = array[index]; while (++iterIndex < iterLength) { var data = iteratees[iterIndex], iteratee = data.iteratee, type = data.type, computed = iteratee(value); if (type == LAZY_MAP_FLAG) { value = computed; } else if (!computed) { if (type == LAZY_FILTER_FLAG) { continue outer; } else { break outer; } } } result[resIndex++] = value; } return result; } // Ensure `LazyWrapper` is an instance of `baseLodash`. LazyWrapper.prototype = baseCreate(baseLodash.prototype); LazyWrapper.prototype.constructor = LazyWrapper; /*------------------------------------------------------------------------*/ /** * Creates a hash object. * * @private * @constructor * @param {Array} [entries] The key-value pairs to cache. */ function Hash(entries) { var index = -1, length = entries == null ? 0 : entries.length; this.clear(); while (++index < length) { var entry = entries[index]; this.set(entry[0], entry[1]); } } /** * Removes all key-value entries from the hash. * * @private * @name clear * @memberOf Hash */ function hashClear() { this.__data__ = nativeCreate ? nativeCreate(null) : {}; this.size = 0; } /** * Removes `key` and its value from the hash. * * @private * @name delete * @memberOf Hash * @param {Object} hash The hash to modify. * @param {string} key The key of the value to remove. * @returns {boolean} Returns `true` if the entry was removed, else `false`. */ function hashDelete(key) { var result = this.has(key) && delete this.__data__[key]; this.size -= result ? 1 : 0; return result; } /** * Gets the hash value for `key`. * * @private * @name get * @memberOf Hash * @param {string} key The key of the value to get. * @returns {*} Returns the entry value. */ function hashGet(key) { var data = this.__data__; if (nativeCreate) { var result = data[key]; return result === HASH_UNDEFINED ? undefined : result; } return hasOwnProperty.call(data, key) ? data[key] : undefined; } /** * Checks if a hash value for `key` exists. * * @private * @name has * @memberOf Hash * @param {string} key The key of the entry to check. * @returns {boolean} Returns `true` if an entry for `key` exists, else `false`. */ function hashHas(key) { var data = this.__data__; return nativeCreate ? (data[key] !== undefined) : hasOwnProperty.call(data, key); } /** * Sets the hash `key` to `value`. * * @private * @name set * @memberOf Hash * @param {string} key The key of the value to set. * @param {*} value The value to set. * @returns {Object} Returns the hash instance. */ function hashSet(key, value) { var data = this.__data__; this.size += this.has(key) ? 0 : 1; data[key] = (nativeCreate && value === undefined) ? HASH_UNDEFINED : value; return this; } // Add methods to `Hash`. Hash.prototype.clear = hashClear; Hash.prototype['delete'] = hashDelete; Hash.prototype.get = hashGet; Hash.prototype.has = hashHas; Hash.prototype.set = hashSet; /*------------------------------------------------------------------------*/ /** * Creates an list cache object. * * @private * @constructor * @param {Array} [entries] The key-value pairs to cache. */ function ListCache(entries) { var index = -1, length = entries == null ? 0 : entries.length; this.clear(); while (++index < length) { var entry = entries[index]; this.set(entry[0], entry[1]); } } /** * Removes all key-value entries from the list cache. * * @private * @name clear * @memberOf ListCache */ function listCacheClear() { this.__data__ = []; this.size = 0; } /** * Removes `key` and its value from the list cache. * * @private * @name delete * @memberOf ListCache * @param {string} key The key of the value to remove. * @returns {boolean} Returns `true` if the entry was removed, else `false`. */ function listCacheDelete(key) { var data = this.__data__, index = assocIndexOf(data, key); if (index < 0) { return false; } var lastIndex = data.length - 1; if (index == lastIndex) { data.pop(); } else { splice.call(data, index, 1); } --this.size; return true; } /** * Gets the list cache value for `key`. * * @private * @name get * @memberOf ListCache * @param {string} key The key of the value to get. * @returns {*} Returns the entry value. */ function listCacheGet(key) { var data = this.__data__, index = assocIndexOf(data, key); return index < 0 ? undefined : data[index][1]; } /** * Checks if a list cache value for `key` exists. * * @private * @name has * @memberOf ListCache * @param {string} key The key of the entry to check. * @returns {boolean} Returns `true` if an entry for `key` exists, else `false`. */ function listCacheHas(key) { return assocIndexOf(this.__data__, key) > -1; } /** * Sets the list cache `key` to `value`. * * @private * @name set * @memberOf ListCache * @param {string} key The key of the value to set. * @param {*} value The value to set. * @returns {Object} Returns the list cache instance. */ function listCacheSet(key, value) { var data = this.__data__, index = assocIndexOf(data, key); if (index < 0) { ++this.size; data.push([key, value]); } else { data[index][1] = value; } return this; } // Add methods to `ListCache`. ListCache.prototype.clear = listCacheClear; ListCache.prototype['delete'] = listCacheDelete; ListCache.prototype.get = listCacheGet; ListCache.prototype.has = listCacheHas; ListCache.prototype.set = listCacheSet; /*------------------------------------------------------------------------*/ /** * Creates a map cache object to store key-value pairs. * * @private * @constructor * @param {Array} [entries] The key-value pairs to cache. */ function MapCache(entries) { var index = -1, length = entries == null ? 0 : entries.length; this.clear(); while (++index < length) { var entry = entries[index]; this.set(entry[0], entry[1]); } } /** * Removes all key-value entries from the map. * * @private * @name clear * @memberOf MapCache */ function mapCacheClear() { this.size = 0; this.__data__ = { 'hash': new Hash, 'map': new (Map || ListCache), 'string': new Hash }; } /** * Removes `key` and its value from the map. * * @private * @name delete * @memberOf MapCache * @param {string} key The key of the value to remove. * @returns {boolean} Returns `true` if the entry was removed, else `false`. */ function mapCacheDelete(key) { var result = getMapData(this, key)['delete'](key); this.size -= result ? 1 : 0; return result; } /** * Gets the map value for `key`. * * @private * @name get * @memberOf MapCache * @param {string} key The key of the value to get. * @returns {*} Returns the entry value. */ function mapCacheGet(key) { return getMapData(this, key).get(key); } /** * Checks if a map value for `key` exists. * * @private * @name has * @memberOf MapCache * @param {string} key The key of the entry to check. * @returns {boolean} Returns `true` if an entry for `key` exists, else `false`. */ function mapCacheHas(key) { return getMapData(this, key).has(key); } /** * Sets the map `key` to `value`. * * @private * @name set * @memberOf MapCache * @param {string} key The key of the value to set. * @param {*} value The value to set. * @returns {Object} Returns the map cache instance. */ function mapCacheSet(key, value) { var data = getMapData(this, key), size = data.size; data.set(key, value); this.size += data.size == size ? 0 : 1; return this; } // Add methods to `MapCache`. MapCache.prototype.clear = mapCacheClear; MapCache.prototype['delete'] = mapCacheDelete; MapCache.prototype.get = mapCacheGet; MapCache.prototype.has = mapCacheHas; MapCache.prototype.set = mapCacheSet; /*------------------------------------------------------------------------*/ /** * * Creates an array cache object to store unique values. * * @private * @constructor * @param {Array} [values] The values to cache. */ function SetCache(values) { var index = -1, length = values == null ? 0 : values.length; this.__data__ = new MapCache; while (++index < length) { this.add(values[index]); } } /** * Adds `value` to the array cache. * * @private * @name add * @memberOf SetCache * @alias push * @param {*} value The value to cache. * @returns {Object} Returns the cache instance. */ function setCacheAdd(value) { this.__data__.set(value, HASH_UNDEFINED); return this; } /** * Checks if `value` is in the array cache. * * @private * @name has * @memberOf SetCache * @param {*} value The value to search for. * @returns {number} Returns `true` if `value` is found, else `false`. */ function setCacheHas(value) { return this.__data__.has(value); } // Add methods to `SetCache`. SetCache.prototype.add = SetCache.prototype.push = setCacheAdd; SetCache.prototype.has = setCacheHas; /*------------------------------------------------------------------------*/ /** * Creates a stack cache object to store key-value pairs. * * @private * @constructor * @param {Array} [entries] The key-value pairs to cache. */ function Stack(entries) { var data = this.__data__ = new ListCache(entries); this.size = data.size; } /** * Removes all key-value entries from the stack. * * @private * @name clear * @memberOf Stack */ function stackClear() { this.__data__ = new ListCache; this.size = 0; } /** * Removes `key` and its value from the stack. * * @private * @name delete * @memberOf Stack * @param {string} key The key of the value to remove. * @returns {boolean} Returns `true` if the entry was removed, else `false`. */ function stackDelete(key) { var data = this.__data__, result = data['delete'](key); this.size = data.size; return result; } /** * Gets the stack value for `key`. * * @private * @name get * @memberOf Stack * @param {string} key The key of the value to get. * @returns {*} Returns the entry value. */ function stackGet(key) { return this.__data__.get(key); } /** * Checks if a stack value for `key` exists. * * @private * @name has * @memberOf Stack * @param {string} key The key of the entry to check. * @returns {boolean} Returns `true` if an entry for `key` exists, else `false`. */ function stackHas(key) { return this.__data__.has(key); } /** * Sets the stack `key` to `value`. * * @private * @name set * @memberOf Stack * @param {string} key The key of the value to set. * @param {*} value The value to set. * @returns {Object} Returns the stack cache instance. */ function stackSet(key, value) { var data = this.__data__; if (data instanceof ListCache) { var pairs = data.__data__; if (!Map || (pairs.length < LARGE_ARRAY_SIZE - 1)) { pairs.push([key, value]); this.size = ++data.size; return this; } data = this.__data__ = new MapCache(pairs); } data.set(key, value); this.size = data.size; return this; } // Add methods to `Stack`. Stack.prototype.clear = stackClear; Stack.prototype['delete'] = stackDelete; Stack.prototype.get = stackGet; Stack.prototype.has = stackHas; Stack.prototype.set = stackSet; /*------------------------------------------------------------------------*/ /** * Creates an array of the enumerable property names of the array-like `value`. * * @private * @param {*} value The value to query. * @param {boolean} inherited Specify returning inherited property names. * @returns {Array} Returns the array of property names. */ function arrayLikeKeys(value, inherited) { var isArr = isArray(value), isArg = !isArr && isArguments(value), isBuff = !isArr && !isArg && isBuffer(value), isType = !isArr && !isArg && !isBuff && isTypedArray(value), skipIndexes = isArr || isArg || isBuff || isType, result = skipIndexes ? baseTimes(value.length, String) : [], length = result.length; for (var key in value) { if ((inherited || hasOwnProperty.call(value, key)) && !(skipIndexes && ( // Safari 9 has enumerable `arguments.length` in strict mode. key == 'length' || // Node.js 0.10 has enumerable non-index properties on buffers. (isBuff && (key == 'offset' || key == 'parent')) || // PhantomJS 2 has enumerable non-index properties on typed arrays. (isType && (key == 'buffer' || key == 'byteLength' || key == 'byteOffset')) || // Skip index properties. isIndex(key, length) ))) { result.push(key); } } return result; } /** * A specialized version of `_.sample` for arrays. * * @private * @param {Array} array The array to sample. * @returns {*} Returns the random element. */ function arraySample(array) { var length = array.length; return length ? array[baseRandom(0, length - 1)] : undefined; } /** * A specialized version of `_.sampleSize` for arrays. * * @private * @param {Array} array The array to sample. * @param {number} n The number of elements to sample. * @returns {Array} Returns the random elements. */ function arraySampleSize(array, n) { return shuffleSelf(copyArray(array), baseClamp(n, 0, array.length)); } /** * A specialized version of `_.shuffle` for arrays. * * @private * @param {Array} array The array to shuffle. * @returns {Array} Returns the new shuffled array. */ function arrayShuffle(array) { return shuffleSelf(copyArray(array)); } /** * This function is like `assignValue` except that it doesn't assign * `undefined` values. * * @private * @param {Object} object The object to modify. * @param {string} key The key of the property to assign. * @param {*} value The value to assign. */ function assignMergeValue(object, key, value) { if ((value !== undefined && !eq(object[key], value)) || (value === undefined && !(key in object))) { baseAssignValue(object, key, value); } } /** * Assigns `value` to `key` of `object` if the existing value is not equivalent * using [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) * for equality comparisons. * * @private * @param {Object} object The object to modify. * @param {string} key The key of the property to assign. * @param {*} value The value to assign. */ function assignValue(object, key, value) { var objValue = object[key]; if (!(hasOwnProperty.call(object, key) && eq(objValue, value)) || (value === undefined && !(key in object))) { baseAssignValue(object, key, value); } } /** * Gets the index at which the `key` is found in `array` of key-value pairs. * * @private * @param {Array} array The array to inspect. * @param {*} key The key to search for. * @returns {number} Returns the index of the matched value, else `-1`. */ function assocIndexOf(array, key) { var length = array.length; while (length--) { if (eq(array[length][0], key)) { return length; } } return -1; } /** * Aggregates elements of `collection` on `accumulator` with keys transformed * by `iteratee` and values set by `setter`. * * @private * @param {Array|Object} collection The collection to iterate over. * @param {Function} setter The function to set `accumulator` values. * @param {Function} iteratee The iteratee to transform keys. * @param {Object} accumulator The initial aggregated object. * @returns {Function} Returns `accumulator`. */ function baseAggregator(collection, setter, iteratee, accumulator) { baseEach(collection, function(value, key, collection) { setter(accumulator, value, iteratee(value), collection); }); return accumulator; } /** * The base implementation of `_.assign` without support for multiple sources * or `customizer` functions. * * @private * @param {Object} object The destination object. * @param {Object} source The source object. * @returns {Object} Returns `object`. */ function baseAssign(object, source) { return object && copyObject(source, keys(source), object); } /** * The base implementation of `_.assignIn` without support for multiple sources * or `customizer` functions. * * @private * @param {Object} object The destination object. * @param {Object} source The source object. * @returns {Object} Returns `object`. */ function baseAssignIn(object, source) { return object && copyObject(source, keysIn(source), object); } /** * The base implementation of `assignValue` and `assignMergeValue` without * value checks. * * @private * @param {Object} object The object to modify. * @param {string} key The key of the property to assign. * @param {*} value The value to assign. */ function baseAssignValue(object, key, value) { if (key == '__proto__' && defineProperty) { defineProperty(object, key, { 'configurable': true, 'enumerable': true, 'value': value, 'writable': true }); } else { object[key] = value; } } /** * The base implementation of `_.at` without support for individual paths. * * @private * @param {Object} object The object to iterate over. * @param {string[]} paths The property paths to pick. * @returns {Array} Returns the picked elements. */ function baseAt(object, paths) { var index = -1, length = paths.length, result = Array(length), skip = object == null; while (++index < length) { result[index] = skip ? undefined : get(object, paths[index]); } return result; } /** * The base implementation of `_.clamp` which doesn't coerce arguments. * * @private * @param {number} number The number to clamp. * @param {number} [lower] The lower bound. * @param {number} upper The upper bound. * @returns {number} Returns the clamped number. */ function baseClamp(number, lower, upper) { if (number === number) { if (upper !== undefined) { number = number <= upper ? number : upper; } if (lower !== undefined) { number = number >= lower ? number : lower; } } return number; } /** * The base implementation of `_.clone` and `_.cloneDeep` which tracks * traversed objects. * * @private * @param {*} value The value to clone. * @param {boolean} bitmask The bitmask flags. * 1 - Deep clone * 2 - Flatten inherited properties * 4 - Clone symbols * @param {Function} [customizer] The function to customize cloning. * @param {string} [key] The key of `value`. * @param {Object} [object] The parent object of `value`. * @param {Object} [stack] Tracks traversed objects and their clone counterparts. * @returns {*} Returns the cloned value. */ function baseClone(value, bitmask, customizer, key, object, stack) { var result, isDeep = bitmask & CLONE_DEEP_FLAG, isFlat = bitmask & CLONE_FLAT_FLAG, isFull = bitmask & CLONE_SYMBOLS_FLAG; if (customizer) { result = object ? customizer(value, key, object, stack) : customizer(value); } if (result !== undefined) { return result; } if (!isObject(value)) { return value; } var isArr = isArray(value); if (isArr) { result = initCloneArray(value); if (!isDeep) { return copyArray(value, result); } } else { var tag = getTag(value), isFunc = tag == funcTag || tag == genTag; if (isBuffer(value)) { return cloneBuffer(value, isDeep); } if (tag == objectTag || tag == argsTag || (isFunc && !object)) { result = (isFlat || isFunc) ? {} : initCloneObject(value); if (!isDeep) { return isFlat ? copySymbolsIn(value, baseAssignIn(result, value)) : copySymbols(value, baseAssign(result, value)); } } else { if (!cloneableTags[tag]) { return object ? value : {}; } result = initCloneByTag(value, tag, isDeep); } } // Check for circular references and return its corresponding clone. stack || (stack = new Stack); var stacked = stack.get(value); if (stacked) { return stacked; } stack.set(value, result); if (isSet(value)) { value.forEach(function(subValue) { result.add(baseClone(subValue, bitmask, customizer, subValue, value, stack)); }); } else if (isMap(value)) { value.forEach(function(subValue, key) { result.set(key, baseClone(subValue, bitmask, customizer, key, value, stack)); }); } var keysFunc = isFull ? (isFlat ? getAllKeysIn : getAllKeys) : (isFlat ? keysIn : keys); var props = isArr ? undefined : keysFunc(value); arrayEach(props || value, function(subValue, key) { if (props) { key = subValue; subValue = value[key]; } // Recursively populate clone (susceptible to call stack limits). assignValue(result, key, baseClone(subValue, bitmask, customizer, key, value, stack)); }); return result; } /** * The base implementation of `_.conforms` which doesn't clone `source`. * * @private * @param {Object} source The object of property predicates to conform to. * @returns {Function} Returns the new spec function. */ function baseConforms(source) { var props = keys(source); return function(object) { return baseConformsTo(object, source, props); }; } /** * The base implementation of `_.conformsTo` which accepts `props` to check. * * @private * @param {Object} object The object to inspect. * @param {Object} source The object of property predicates to conform to. * @returns {boolean} Returns `true` if `object` conforms, else `false`. */ function baseConformsTo(object, source, props) { var length = props.length; if (object == null) { return !length; } object = Object(object); while (length--) { var key = props[length], predicate = source[key], value = object[key]; if ((value === undefined && !(key in object)) || !predicate(value)) { return false; } } return true; } /** * The base implementation of `_.delay` and `_.defer` which accepts `args` * to provide to `func`. * * @private * @param {Function} func The function to delay. * @param {number} wait The number of milliseconds to delay invocation. * @param {Array} args The arguments to provide to `func`. * @returns {number|Object} Returns the timer id or timeout object. */ function baseDelay(func, wait, args) { if (typeof func != 'function') { throw new TypeError(FUNC_ERROR_TEXT); } return setTimeout(function() { func.apply(undefined, args); }, wait); } /** * The base implementation of methods like `_.difference` without support * for excluding multiple arrays or iteratee shorthands. * * @private * @param {Array} array The array to inspect. * @param {Array} values The values to exclude. * @param {Function} [iteratee] The iteratee invoked per element. * @param {Function} [comparator] The comparator invoked per element. * @returns {Array} Returns the new array of filtered values. */ function baseDifference(array, values, iteratee, comparator) { var index = -1, includes = arrayIncludes, isCommon = true, length = array.length, result = [], valuesLength = values.length; if (!length) { return result; } if (iteratee) { values = arrayMap(values, baseUnary(iteratee)); } if (comparator) { includes = arrayIncludesWith; isCommon = false; } else if (values.length >= LARGE_ARRAY_SIZE) { includes = cacheHas; isCommon = false; values = new SetCache(values); } outer: while (++index < length) { var value = array[index], computed = iteratee == null ? value : iteratee(value); value = (comparator || value !== 0) ? value : 0; if (isCommon && computed === computed) { var valuesIndex = valuesLength; while (valuesIndex--) { if (values[valuesIndex] === computed) { continue outer; } } result.push(value); } else if (!includes(values, computed, comparator)) { result.push(value); } } return result; } /** * The base implementation of `_.forEach` without support for iteratee shorthands. * * @private * @param {Array|Object} collection The collection to iterate over. * @param {Function} iteratee The function invoked per iteration. * @returns {Array|Object} Returns `collection`. */ var baseEach = createBaseEach(baseForOwn); /** * The base implementation of `_.forEachRight` without support for iteratee shorthands. * * @private * @param {Array|Object} collection The collection to iterate over. * @param {Function} iteratee The function invoked per iteration. * @returns {Array|Object} Returns `collection`. */ var baseEachRight = createBaseEach(baseForOwnRight, true); /** * The base implementation of `_.every` without support for iteratee shorthands. * * @private * @param {Array|Object} collection The collection to iterate over. * @param {Function} predicate The function invoked per iteration. * @returns {boolean} Returns `true` if all elements pass the predicate check, * else `false` */ function baseEvery(collection, predicate) { var result = true; baseEach(collection, function(value, index, collection) { result = !!predicate(value, index, collection); return result; }); return result; } /** * The base implementation of methods like `_.max` and `_.min` which accepts a * `comparator` to determine the extremum value. * * @private * @param {Array} array The array to iterate over. * @param {Function} iteratee The iteratee invoked per iteration. * @param {Function} comparator The comparator used to compare values. * @returns {*} Returns the extremum value. */ function baseExtremum(array, iteratee, comparator) { var index = -1, length = array.length; while (++index < length) { var value = array[index], current = iteratee(value); if (current != null && (computed === undefined ? (current === current && !isSymbol(current)) : comparator(current, computed) )) { var computed = current, result = value; } } return result; } /** * The base implementation of `_.fill` without an iteratee call guard. * * @private * @param {Array} array The array to fill. * @param {*} value The value to fill `array` with. * @param {number} [start=0] The start position. * @param {number} [end=array.length] The end position. * @returns {Array} Returns `array`. */ function baseFill(array, value, start, end) { var length = array.length; start = toInteger(start); if (start < 0) { start = -start > length ? 0 : (length + start); } end = (end === undefined || end > length) ? length : toInteger(end); if (end < 0) { end += length; } end = start > end ? 0 : toLength(end); while (start < end) { array[start++] = value; } return array; } /** * The base implementation of `_.filter` without support for iteratee shorthands. * * @private * @param {Array|Object} collection The collection to iterate over. * @param {Function} predicate The function invoked per iteration. * @returns {Array} Returns the new filtered array. */ function baseFilter(collection, predicate) { var result = []; baseEach(collection, function(value, index, collection) { if (predicate(value, index, collection)) { result.push(value); } }); return result; } /** * The base implementation of `_.flatten` with support for restricting flattening. * * @private * @param {Array} array The array to flatten. * @param {number} depth The maximum recursion depth. * @param {boolean} [predicate=isFlattenable] The function invoked per iteration. * @param {boolean} [isStrict] Restrict to values that pass `predicate` checks. * @param {Array} [result=[]] The initial result value. * @returns {Array} Returns the new flattened array. */ function baseFlatten(array, depth, predicate, isStrict, result) { var index = -1, length = array.length; predicate || (predicate = isFlattenable); result || (result = []); while (++index < length) { var value = array[index]; if (depth > 0 && predicate(value)) { if (depth > 1) { // Recursively flatten arrays (susceptible to call stack limits). baseFlatten(value, depth - 1, predicate, isStrict, result); } else { arrayPush(result, value); } } else if (!isStrict) { result[result.length] = value; } } return result; } /** * The base implementation of `baseForOwn` which iterates over `object` * properties returned by `keysFunc` and invokes `iteratee` for each property. * Iteratee functions may exit iteration early by explicitly returning `false`. * * @private * @param {Object} object The object to iterate over. * @param {Function} iteratee The function invoked per iteration. * @param {Function} keysFunc The function to get the keys of `object`. * @returns {Object} Returns `object`. */ var baseFor = createBaseFor(); /** * This function is like `baseFor` except that it iterates over properties * in the opposite order. * * @private * @param {Object} object The object to iterate over. * @param {Function} iteratee The function invoked per iteration. * @param {Function} keysFunc The function to get the keys of `object`. * @returns {Object} Returns `object`. */ var baseForRight = createBaseFor(true); /** * The base implementation of `_.forOwn` without support for iteratee shorthands. * * @private * @param {Object} object The object to iterate over. * @param {Function} iteratee The function invoked per iteration. * @returns {Object} Returns `object`. */ function baseForOwn(object, iteratee) { return object && baseFor(object, iteratee, keys); } /** * The base implementation of `_.forOwnRight` without support for iteratee shorthands. * * @private * @param {Object} object The object to iterate over. * @param {Function} iteratee The function invoked per iteration. * @returns {Object} Returns `object`. */ function baseForOwnRight(object, iteratee) { return object && baseForRight(object, iteratee, keys); } /** * The base implementation of `_.functions` which creates an array of * `object` function property names filtered from `props`. * * @private * @param {Object} object The object to inspect. * @param {Array} props The property names to filter. * @returns {Array} Returns the function names. */ function baseFunctions(object, props) { return arrayFilter(props, function(key) { return isFunction(object[key]); }); } /** * The base implementation of `_.get` without support for default values. * * @private * @param {Object} object The object to query. * @param {Array|string} path The path of the property to get. * @returns {*} Returns the resolved value. */ function baseGet(object, path) { path = castPath(path, object); var index = 0, length = path.length; while (object != null && index < length) { object = object[toKey(path[index++])]; } return (index && index == length) ? object : undefined; } /** * The base implementation of `getAllKeys` and `getAllKeysIn` which uses * `keysFunc` and `symbolsFunc` to get the enumerable property names and * symbols of `object`. * * @private * @param {Object} object The object to query. * @param {Function} keysFunc The function to get the keys of `object`. * @param {Function} symbolsFunc The function to get the symbols of `object`. * @returns {Array} Returns the array of property names and symbols. */ function baseGetAllKeys(object, keysFunc, symbolsFunc) { var result = keysFunc(object); return isArray(object) ? result : arrayPush(result, symbolsFunc(object)); } /** * The base implementation of `getTag` without fallbacks for buggy environments. * * @private * @param {*} value The value to query. * @returns {string} Returns the `toStringTag`. */ function baseGetTag(value) { if (value == null) { return value === undefined ? undefinedTag : nullTag; } return (symToStringTag && symToStringTag in Object(value)) ? getRawTag(value) : objectToString(value); } /** * The base implementation of `_.gt` which doesn't coerce arguments. * * @private * @param {*} value The value to compare. * @param {*} other The other value to compare. * @returns {boolean} Returns `true` if `value` is greater than `other`, * else `false`. */ function baseGt(value, other) { return value > other; } /** * The base implementation of `_.has` without support for deep paths. * * @private * @param {Object} [object] The object to query. * @param {Array|string} key The key to check. * @returns {boolean} Returns `true` if `key` exists, else `false`. */ function baseHas(object, key) { return object != null && hasOwnProperty.call(object, key); } /** * The base implementation of `_.hasIn` without support for deep paths. * * @private * @param {Object} [object] The object to query. * @param {Array|string} key The key to check. * @returns {boolean} Returns `true` if `key` exists, else `false`. */ function baseHasIn(object, key) { return object != null && key in Object(object); } /** * The base implementation of `_.inRange` which doesn't coerce arguments. * * @private * @param {number} number The number to check. * @param {number} start The start of the range. * @param {number} end The end of the range. * @returns {boolean} Returns `true` if `number` is in the range, else `false`. */ function baseInRange(number, start, end) { return number >= nativeMin(start, end) && number < nativeMax(start, end); } /** * The base implementation of methods like `_.intersection`, without support * for iteratee shorthands, that accepts an array of arrays to inspect. * * @private * @param {Array} arrays The arrays to inspect. * @param {Function} [iteratee] The iteratee invoked per element. * @param {Function} [comparator] The comparator invoked per element. * @returns {Array} Returns the new array of shared values. */ function baseIntersection(arrays, iteratee, comparator) { var includes = comparator ? arrayIncludesWith : arrayIncludes, length = arrays[0].length, othLength = arrays.length, othIndex = othLength, caches = Array(othLength), maxLength = Infinity, result = []; while (othIndex--) { var array = arrays[othIndex]; if (othIndex && iteratee) { array = arrayMap(array, baseUnary(iteratee)); } maxLength = nativeMin(array.length, maxLength); caches[othIndex] = !comparator && (iteratee || (length >= 120 && array.length >= 120)) ? new SetCache(othIndex && array) : undefined; } array = arrays[0]; var index = -1, seen = caches[0]; outer: while (++index < length && result.length < maxLength) { var value = array[index], computed = iteratee ? iteratee(value) : value; value = (comparator || value !== 0) ? value : 0; if (!(seen ? cacheHas(seen, computed) : includes(result, computed, comparator) )) { othIndex = othLength; while (--othIndex) { var cache = caches[othIndex]; if (!(cache ? cacheHas(cache, computed) : includes(arrays[othIndex], computed, comparator)) ) { continue outer; } } if (seen) { seen.push(computed); } result.push(value); } } return result; } /** * The base implementation of `_.invert` and `_.invertBy` which inverts * `object` with values transformed by `iteratee` and set by `setter`. * * @private * @param {Object} object The object to iterate over. * @param {Function} setter The function to set `accumulator` values. * @param {Function} iteratee The iteratee to transform values. * @param {Object} accumulator The initial inverted object. * @returns {Function} Returns `accumulator`. */ function baseInverter(object, setter, iteratee, accumulator) { baseForOwn(object, function(value, key, object) { setter(accumulator, iteratee(value), key, object); }); return accumulator; } /** * The base implementation of `_.invoke` without support for individual * method arguments. * * @private * @param {Object} object The object to query. * @param {Array|string} path The path of the method to invoke. * @param {Array} args The arguments to invoke the method with. * @returns {*} Returns the result of the invoked method. */ function baseInvoke(object, path, args) { path = castPath(path, object); object = parent(object, path); var func = object == null ? object : object[toKey(last(path))]; return func == null ? undefined : apply(func, object, args); } /** * The base implementation of `_.isArguments`. * * @private * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is an `arguments` object, */ function baseIsArguments(value) { return isObjectLike(value) && baseGetTag(value) == argsTag; } /** * The base implementation of `_.isArrayBuffer` without Node.js optimizations. * * @private * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is an array buffer, else `false`. */ function baseIsArrayBuffer(value) { return isObjectLike(value) && baseGetTag(value) == arrayBufferTag; } /** * The base implementation of `_.isDate` without Node.js optimizations. * * @private * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a date object, else `false`. */ function baseIsDate(value) { return isObjectLike(value) && baseGetTag(value) == dateTag; } /** * The base implementation of `_.isEqual` which supports partial comparisons * and tracks traversed objects. * * @private * @param {*} value The value to compare. * @param {*} other The other value to compare. * @param {boolean} bitmask The bitmask flags. * 1 - Unordered comparison * 2 - Partial comparison * @param {Function} [customizer] The function to customize comparisons. * @param {Object} [stack] Tracks traversed `value` and `other` objects. * @returns {boolean} Returns `true` if the values are equivalent, else `false`. */ function baseIsEqual(value, other, bitmask, customizer, stack) { if (value === other) { return true; } if (value == null || other == null || (!isObjectLike(value) && !isObjectLike(other))) { return value !== value && other !== other; } return baseIsEqualDeep(value, other, bitmask, customizer, baseIsEqual, stack); } /** * A specialized version of `baseIsEqual` for arrays and objects which performs * deep comparisons and tracks traversed objects enabling objects with circular * references to be compared. * * @private * @param {Object} object The object to compare. * @param {Object} other The other object to compare. * @param {number} bitmask The bitmask flags. See `baseIsEqual` for more details. * @param {Function} customizer The function to customize comparisons. * @param {Function} equalFunc The function to determine equivalents of values. * @param {Object} [stack] Tracks traversed `object` and `other` objects. * @returns {boolean} Returns `true` if the objects are equivalent, else `false`. */ function baseIsEqualDeep(object, other, bitmask, customizer, equalFunc, stack) { var objIsArr = isArray(object), othIsArr = isArray(other), objTag = objIsArr ? arrayTag : getTag(object), othTag = othIsArr ? arrayTag : getTag(other); objTag = objTag == argsTag ? objectTag : objTag; othTag = othTag == argsTag ? objectTag : othTag; var objIsObj = objTag == objectTag, othIsObj = othTag == objectTag, isSameTag = objTag == othTag; if (isSameTag && isBuffer(object)) { if (!isBuffer(other)) { return false; } objIsArr = true; objIsObj = false; } if (isSameTag && !objIsObj) { stack || (stack = new Stack); return (objIsArr || isTypedArray(object)) ? equalArrays(object, other, bitmask, customizer, equalFunc, stack) : equalByTag(object, other, objTag, bitmask, customizer, equalFunc, stack); } if (!(bitmask & COMPARE_PARTIAL_FLAG)) { var objIsWrapped = objIsObj && hasOwnProperty.call(object, '__wrapped__'), othIsWrapped = othIsObj && hasOwnProperty.call(other, '__wrapped__'); if (objIsWrapped || othIsWrapped) { var objUnwrapped = objIsWrapped ? object.value() : object, othUnwrapped = othIsWrapped ? other.value() : other; stack || (stack = new Stack); return equalFunc(objUnwrapped, othUnwrapped, bitmask, customizer, stack); } } if (!isSameTag) { return false; } stack || (stack = new Stack); return equalObjects(object, other, bitmask, customizer, equalFunc, stack); } /** * The base implementation of `_.isMap` without Node.js optimizations. * * @private * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a map, else `false`. */ function baseIsMap(value) { return isObjectLike(value) && getTag(value) == mapTag; } /** * The base implementation of `_.isMatch` without support for iteratee shorthands. * * @private * @param {Object} object The object to inspect. * @param {Object} source The object of property values to match. * @param {Array} matchData The property names, values, and compare flags to match. * @param {Function} [customizer] The function to customize comparisons. * @returns {boolean} Returns `true` if `object` is a match, else `false`. */ function baseIsMatch(object, source, matchData, customizer) { var index = matchData.length, length = index, noCustomizer = !customizer; if (object == null) { return !length; } object = Object(object); while (index--) { var data = matchData[index]; if ((noCustomizer && data[2]) ? data[1] !== object[data[0]] : !(data[0] in object) ) { return false; } } while (++index < length) { data = matchData[index]; var key = data[0], objValue = object[key], srcValue = data[1]; if (noCustomizer && data[2]) { if (objValue === undefined && !(key in object)) { return false; } } else { var stack = new Stack; if (customizer) { var result = customizer(objValue, srcValue, key, object, source, stack); } if (!(result === undefined ? baseIsEqual(srcValue, objValue, COMPARE_PARTIAL_FLAG | COMPARE_UNORDERED_FLAG, customizer, stack) : result )) { return false; } } } return true; } /** * The base implementation of `_.isNative` without bad shim checks. * * @private * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a native function, * else `false`. */ function baseIsNative(value) { if (!isObject(value) || isMasked(value)) { return false; } var pattern = isFunction(value) ? reIsNative : reIsHostCtor; return pattern.test(toSource(value)); } /** * The base implementation of `_.isRegExp` without Node.js optimizations. * * @private * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a regexp, else `false`. */ function baseIsRegExp(value) { return isObjectLike(value) && baseGetTag(value) == regexpTag; } /** * The base implementation of `_.isSet` without Node.js optimizations. * * @private * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a set, else `false`. */ function baseIsSet(value) { return isObjectLike(value) && getTag(value) == setTag; } /** * The base implementation of `_.isTypedArray` without Node.js optimizations. * * @private * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a typed array, else `false`. */ function baseIsTypedArray(value) { return isObjectLike(value) && isLength(value.length) && !!typedArrayTags[baseGetTag(value)]; } /** * The base implementation of `_.iteratee`. * * @private * @param {*} [value=_.identity] The value to convert to an iteratee. * @returns {Function} Returns the iteratee. */ function baseIteratee(value) { // Don't store the `typeof` result in a variable to avoid a JIT bug in Safari 9. // See https://bugs.webkit.org/show_bug.cgi?id=156034 for more details. if (typeof value == 'function') { return value; } if (value == null) { return identity; } if (typeof value == 'object') { return isArray(value) ? baseMatchesProperty(value[0], value[1]) : baseMatches(value); } return property(value); } /** * The base implementation of `_.keys` which doesn't treat sparse arrays as dense. * * @private * @param {Object} object The object to query. * @returns {Array} Returns the array of property names. */ function baseKeys(object) { if (!isPrototype(object)) { return nativeKeys(object); } var result = []; for (var key in Object(object)) { if (hasOwnProperty.call(object, key) && key != 'constructor') { result.push(key); } } return result; } /** * The base implementation of `_.keysIn` which doesn't treat sparse arrays as dense. * * @private * @param {Object} object The object to query. * @returns {Array} Returns the array of property names. */ function baseKeysIn(object) { if (!isObject(object)) { return nativeKeysIn(object); } var isProto = isPrototype(object), result = []; for (var key in object) { if (!(key == 'constructor' && (isProto || !hasOwnProperty.call(object, key)))) { result.push(key); } } return result; } /** * The base implementation of `_.lt` which doesn't coerce arguments. * * @private * @param {*} value The value to compare. * @param {*} other The other value to compare. * @returns {boolean} Returns `true` if `value` is less than `other`, * else `false`. */ function baseLt(value, other) { return value < other; } /** * The base implementation of `_.map` without support for iteratee shorthands. * * @private * @param {Array|Object} collection The collection to iterate over. * @param {Function} iteratee The function invoked per iteration. * @returns {Array} Returns the new mapped array. */ function baseMap(collection, iteratee) { var index = -1, result = isArrayLike(collection) ? Array(collection.length) : []; baseEach(collection, function(value, key, collection) { result[++index] = iteratee(value, key, collection); }); return result; } /** * The base implementation of `_.matches` which doesn't clone `source`. * * @private * @param {Object} source The object of property values to match. * @returns {Function} Returns the new spec function. */ function baseMatches(source) { var matchData = getMatchData(source); if (matchData.length == 1 && matchData[0][2]) { return matchesStrictComparable(matchData[0][0], matchData[0][1]); } return function(object) { return object === source || baseIsMatch(object, source, matchData); }; } /** * The base implementation of `_.matchesProperty` which doesn't clone `srcValue`. * * @private * @param {string} path The path of the property to get. * @param {*} srcValue The value to match. * @returns {Function} Returns the new spec function. */ function baseMatchesProperty(path, srcValue) { if (isKey(path) && isStrictComparable(srcValue)) { return matchesStrictComparable(toKey(path), srcValue); } return function(object) { var objValue = get(object, path); return (objValue === undefined && objValue === srcValue) ? hasIn(object, path) : baseIsEqual(srcValue, objValue, COMPARE_PARTIAL_FLAG | COMPARE_UNORDERED_FLAG); }; } /** * The base implementation of `_.merge` without support for multiple sources. * * @private * @param {Object} object The destination object. * @param {Object} source The source object. * @param {number} srcIndex The index of `source`. * @param {Function} [customizer] The function to customize merged values. * @param {Object} [stack] Tracks traversed source values and their merged * counterparts. */ function baseMerge(object, source, srcIndex, customizer, stack) { if (object === source) { return; } baseFor(source, function(srcValue, key) { stack || (stack = new Stack); if (isObject(srcValue)) { baseMergeDeep(object, source, key, srcIndex, baseMerge, customizer, stack); } else { var newValue = customizer ? customizer(safeGet(object, key), srcValue, (key + ''), object, source, stack) : undefined; if (newValue === undefined) { newValue = srcValue; } assignMergeValue(object, key, newValue); } }, keysIn); } /** * A specialized version of `baseMerge` for arrays and objects which performs * deep merges and tracks traversed objects enabling objects with circular * references to be merged. * * @private * @param {Object} object The destination object. * @param {Object} source The source object. * @param {string} key The key of the value to merge. * @param {number} srcIndex The index of `source`. * @param {Function} mergeFunc The function to merge values. * @param {Function} [customizer] The function to customize assigned values. * @param {Object} [stack] Tracks traversed source values and their merged * counterparts. */ function baseMergeDeep(object, source, key, srcIndex, mergeFunc, customizer, stack) { var objValue = safeGet(object, key), srcValue = safeGet(source, key), stacked = stack.get(srcValue); if (stacked) { assignMergeValue(object, key, stacked); return; } var newValue = customizer ? customizer(objValue, srcValue, (key + ''), object, source, stack) : undefined; var isCommon = newValue === undefined; if (isCommon) { var isArr = isArray(srcValue), isBuff = !isArr && isBuffer(srcValue), isTyped = !isArr && !isBuff && isTypedArray(srcValue); newValue = srcValue; if (isArr || isBuff || isTyped) { if (isArray(objValue)) { newValue = objValue; } else if (isArrayLikeObject(objValue)) { newValue = copyArray(objValue); } else if (isBuff) { isCommon = false; newValue = cloneBuffer(srcValue, true); } else if (isTyped) { isCommon = false; newValue = cloneTypedArray(srcValue, true); } else { newValue = []; } } else if (isPlainObject(srcValue) || isArguments(srcValue)) { newValue = objValue; if (isArguments(objValue)) { newValue = toPlainObject(objValue); } else if (!isObject(objValue) || isFunction(objValue)) { newValue = initCloneObject(srcValue); } } else { isCommon = false; } } if (isCommon) { // Recursively merge objects and arrays (susceptible to call stack limits). stack.set(srcValue, newValue); mergeFunc(newValue, srcValue, srcIndex, customizer, stack); stack['delete'](srcValue); } assignMergeValue(object, key, newValue); } /** * The base implementation of `_.nth` which doesn't coerce arguments. * * @private * @param {Array} array The array to query. * @param {number} n The index of the element to return. * @returns {*} Returns the nth element of `array`. */ function baseNth(array, n) { var length = array.length; if (!length) { return; } n += n < 0 ? length : 0; return isIndex(n, length) ? array[n] : undefined; } /** * The base implementation of `_.orderBy` without param guards. * * @private * @param {Array|Object} collection The collection to iterate over. * @param {Function[]|Object[]|string[]} iteratees The iteratees to sort by. * @param {string[]} orders The sort orders of `iteratees`. * @returns {Array} Returns the new sorted array. */ function baseOrderBy(collection, iteratees, orders) { var index = -1; iteratees = arrayMap(iteratees.length ? iteratees : [identity], baseUnary(getIteratee())); var result = baseMap(collection, function(value, key, collection) { var criteria = arrayMap(iteratees, function(iteratee) { return iteratee(value); }); return { 'criteria': criteria, 'index': ++index, 'value': value }; }); return baseSortBy(result, function(object, other) { return compareMultiple(object, other, orders); }); } /** * The base implementation of `_.pick` without support for individual * property identifiers. * * @private * @param {Object} object The source object. * @param {string[]} paths The property paths to pick. * @returns {Object} Returns the new object. */ function basePick(object, paths) { return basePickBy(object, paths, function(value, path) { return hasIn(object, path); }); } /** * The base implementation of `_.pickBy` without support for iteratee shorthands. * * @private * @param {Object} object The source object. * @param {string[]} paths The property paths to pick. * @param {Function} predicate The function invoked per property. * @returns {Object} Returns the new object. */ function basePickBy(object, paths, predicate) { var index = -1, length = paths.length, result = {}; while (++index < length) { var path = paths[index], value = baseGet(object, path); if (predicate(value, path)) { baseSet(result, castPath(path, object), value); } } return result; } /** * A specialized version of `baseProperty` which supports deep paths. * * @private * @param {Array|string} path The path of the property to get. * @returns {Function} Returns the new accessor function. */ function basePropertyDeep(path) { return function(object) { return baseGet(object, path); }; } /** * The base implementation of `_.pullAllBy` without support for iteratee * shorthands. * * @private * @param {Array} array The array to modify. * @param {Array} values The values to remove. * @param {Function} [iteratee] The iteratee invoked per element. * @param {Function} [comparator] The comparator invoked per element. * @returns {Array} Returns `array`. */ function basePullAll(array, values, iteratee, comparator) { var indexOf = comparator ? baseIndexOfWith : baseIndexOf, index = -1, length = values.length, seen = array; if (array === values) { values = copyArray(values); } if (iteratee) { seen = arrayMap(array, baseUnary(iteratee)); } while (++index < length) { var fromIndex = 0, value = values[index], computed = iteratee ? iteratee(value) : value; while ((fromIndex = indexOf(seen, computed, fromIndex, comparator)) > -1) { if (seen !== array) { splice.call(seen, fromIndex, 1); } splice.call(array, fromIndex, 1); } } return array; } /** * The base implementation of `_.pullAt` without support for individual * indexes or capturing the removed elements. * * @private * @param {Array} array The array to modify. * @param {number[]} indexes The indexes of elements to remove. * @returns {Array} Returns `array`. */ function basePullAt(array, indexes) { var length = array ? indexes.length : 0, lastIndex = length - 1; while (length--) { var index = indexes[length]; if (length == lastIndex || index !== previous) { var previous = index; if (isIndex(index)) { splice.call(array, index, 1); } else { baseUnset(array, index); } } } return array; } /** * The base implementation of `_.random` without support for returning * floating-point numbers. * * @private * @param {number} lower The lower bound. * @param {number} upper The upper bound. * @returns {number} Returns the random number. */ function baseRandom(lower, upper) { return lower + nativeFloor(nativeRandom() * (upper - lower + 1)); } /** * The base implementation of `_.range` and `_.rangeRight` which doesn't * coerce arguments. * * @private * @param {number} start The start of the range. * @param {number} end The end of the range. * @param {number} step The value to increment or decrement by. * @param {boolean} [fromRight] Specify iterating from right to left. * @returns {Array} Returns the range of numbers. */ function baseRange(start, end, step, fromRight) { var index = -1, length = nativeMax(nativeCeil((end - start) / (step || 1)), 0), result = Array(length); while (length--) { result[fromRight ? length : ++index] = start; start += step; } return result; } /** * The base implementation of `_.repeat` which doesn't coerce arguments. * * @private * @param {string} string The string to repeat. * @param {number} n The number of times to repeat the string. * @returns {string} Returns the repeated string. */ function baseRepeat(string, n) { var result = ''; if (!string || n < 1 || n > MAX_SAFE_INTEGER) { return result; } // Leverage the exponentiation by squaring algorithm for a faster repeat. // See https://en.wikipedia.org/wiki/Exponentiation_by_squaring for more details. do { if (n % 2) { result += string; } n = nativeFloor(n / 2); if (n) { string += string; } } while (n); return result; } /** * The base implementation of `_.rest` which doesn't validate or coerce arguments. * * @private * @param {Function} func The function to apply a rest parameter to. * @param {number} [start=func.length-1] The start position of the rest parameter. * @returns {Function} Returns the new function. */ function baseRest(func, start) { return setToString(overRest(func, start, identity), func + ''); } /** * The base implementation of `_.sample`. * * @private * @param {Array|Object} collection The collection to sample. * @returns {*} Returns the random element. */ function baseSample(collection) { return arraySample(values(collection)); } /** * The base implementation of `_.sampleSize` without param guards. * * @private * @param {Array|Object} collection The collection to sample. * @param {number} n The number of elements to sample. * @returns {Array} Returns the random elements. */ function baseSampleSize(collection, n) { var array = values(collection); return shuffleSelf(array, baseClamp(n, 0, array.length)); } /** * The base implementation of `_.set`. * * @private * @param {Object} object The object to modify. * @param {Array|string} path The path of the property to set. * @param {*} value The value to set. * @param {Function} [customizer] The function to customize path creation. * @returns {Object} Returns `object`. */ function baseSet(object, path, value, customizer) { if (!isObject(object)) { return object; } path = castPath(path, object); var index = -1, length = path.length, lastIndex = length - 1, nested = object; while (nested != null && ++index < length) { var key = toKey(path[index]), newValue = value; if (index != lastIndex) { var objValue = nested[key]; newValue = customizer ? customizer(objValue, key, nested) : undefined; if (newValue === undefined) { newValue = isObject(objValue) ? objValue : (isIndex(path[index + 1]) ? [] : {}); } } assignValue(nested, key, newValue); nested = nested[key]; } return object; } /** * The base implementation of `setData` without support for hot loop shorting. * * @private * @param {Function} func The function to associate metadata with. * @param {*} data The metadata. * @returns {Function} Returns `func`. */ var baseSetData = !metaMap ? identity : function(func, data) { metaMap.set(func, data); return func; }; /** * The base implementation of `setToString` without support for hot loop shorting. * * @private * @param {Function} func The function to modify. * @param {Function} string The `toString` result. * @returns {Function} Returns `func`. */ var baseSetToString = !defineProperty ? identity : function(func, string) { return defineProperty(func, 'toString', { 'configurable': true, 'enumerable': false, 'value': constant(string), 'writable': true }); }; /** * The base implementation of `_.shuffle`. * * @private * @param {Array|Object} collection The collection to shuffle. * @returns {Array} Returns the new shuffled array. */ function baseShuffle(collection) { return shuffleSelf(values(collection)); } /** * The base implementation of `_.slice` without an iteratee call guard. * * @private * @param {Array} array The array to slice. * @param {number} [start=0] The start position. * @param {number} [end=array.length] The end position. * @returns {Array} Returns the slice of `array`. */ function baseSlice(array, start, end) { var index = -1, length = array.length; if (start < 0) { start = -start > length ? 0 : (length + start); } end = end > length ? length : end; if (end < 0) { end += length; } length = start > end ? 0 : ((end - start) >>> 0); start >>>= 0; var result = Array(length); while (++index < length) { result[index] = array[index + start]; } return result; } /** * The base implementation of `_.some` without support for iteratee shorthands. * * @private * @param {Array|Object} collection The collection to iterate over. * @param {Function} predicate The function invoked per iteration. * @returns {boolean} Returns `true` if any element passes the predicate check, * else `false`. */ function baseSome(collection, predicate) { var result; baseEach(collection, function(value, index, collection) { result = predicate(value, index, collection); return !result; }); return !!result; } /** * The base implementation of `_.sortedIndex` and `_.sortedLastIndex` which * performs a binary search of `array` to determine the index at which `value` * should be inserted into `array` in order to maintain its sort order. * * @private * @param {Array} array The sorted array to inspect. * @param {*} value The value to evaluate. * @param {boolean} [retHighest] Specify returning the highest qualified index. * @returns {number} Returns the index at which `value` should be inserted * into `array`. */ function baseSortedIndex(array, value, retHighest) { var low = 0, high = array == null ? low : array.length; if (typeof value == 'number' && value === value && high <= HALF_MAX_ARRAY_LENGTH) { while (low < high) { var mid = (low + high) >>> 1, computed = array[mid]; if (computed !== null && !isSymbol(computed) && (retHighest ? (computed <= value) : (computed < value))) { low = mid + 1; } else { high = mid; } } return high; } return baseSortedIndexBy(array, value, identity, retHighest); } /** * The base implementation of `_.sortedIndexBy` and `_.sortedLastIndexBy` * which invokes `iteratee` for `value` and each element of `array` to compute * their sort ranking. The iteratee is invoked with one argument; (value). * * @private * @param {Array} array The sorted array to inspect. * @param {*} value The value to evaluate. * @param {Function} iteratee The iteratee invoked per element. * @param {boolean} [retHighest] Specify returning the highest qualified index. * @returns {number} Returns the index at which `value` should be inserted * into `array`. */ function baseSortedIndexBy(array, value, iteratee, retHighest) { value = iteratee(value); var low = 0, high = array == null ? 0 : array.length, valIsNaN = value !== value, valIsNull = value === null, valIsSymbol = isSymbol(value), valIsUndefined = value === undefined; while (low < high) { var mid = nativeFloor((low + high) / 2), computed = iteratee(array[mid]), othIsDefined = computed !== undefined, othIsNull = computed === null, othIsReflexive = computed === computed, othIsSymbol = isSymbol(computed); if (valIsNaN) { var setLow = retHighest || othIsReflexive; } else if (valIsUndefined) { setLow = othIsReflexive && (retHighest || othIsDefined); } else if (valIsNull) { setLow = othIsReflexive && othIsDefined && (retHighest || !othIsNull); } else if (valIsSymbol) { setLow = othIsReflexive && othIsDefined && !othIsNull && (retHighest || !othIsSymbol); } else if (othIsNull || othIsSymbol) { setLow = false; } else { setLow = retHighest ? (computed <= value) : (computed < value); } if (setLow) { low = mid + 1; } else { high = mid; } } return nativeMin(high, MAX_ARRAY_INDEX); } /** * The base implementation of `_.sortedUniq` and `_.sortedUniqBy` without * support for iteratee shorthands. * * @private * @param {Array} array The array to inspect. * @param {Function} [iteratee] The iteratee invoked per element. * @returns {Array} Returns the new duplicate free array. */ function baseSortedUniq(array, iteratee) { var index = -1, length = array.length, resIndex = 0, result = []; while (++index < length) { var value = array[index], computed = iteratee ? iteratee(value) : value; if (!index || !eq(computed, seen)) { var seen = computed; result[resIndex++] = value === 0 ? 0 : value; } } return result; } /** * The base implementation of `_.toNumber` which doesn't ensure correct * conversions of binary, hexadecimal, or octal string values. * * @private * @param {*} value The value to process. * @returns {number} Returns the number. */ function baseToNumber(value) { if (typeof value == 'number') { return value; } if (isSymbol(value)) { return NAN; } return +value; } /** * The base implementation of `_.toString` which doesn't convert nullish * values to empty strings. * * @private * @param {*} value The value to process. * @returns {string} Returns the string. */ function baseToString(value) { // Exit early for strings to avoid a performance hit in some environments. if (typeof value == 'string') { return value; } if (isArray(value)) { // Recursively convert values (susceptible to call stack limits). return arrayMap(value, baseToString) + ''; } if (isSymbol(value)) { return symbolToString ? symbolToString.call(value) : ''; } var result = (value + ''); return (result == '0' && (1 / value) == -INFINITY) ? '-0' : result; } /** * The base implementation of `_.uniqBy` without support for iteratee shorthands. * * @private * @param {Array} array The array to inspect. * @param {Function} [iteratee] The iteratee invoked per element. * @param {Function} [comparator] The comparator invoked per element. * @returns {Array} Returns the new duplicate free array. */ function baseUniq(array, iteratee, comparator) { var index = -1, includes = arrayIncludes, length = array.length, isCommon = true, result = [], seen = result; if (comparator) { isCommon = false; includes = arrayIncludesWith; } else if (length >= LARGE_ARRAY_SIZE) { var set = iteratee ? null : createSet(array); if (set) { return setToArray(set); } isCommon = false; includes = cacheHas; seen = new SetCache; } else { seen = iteratee ? [] : result; } outer: while (++index < length) { var value = array[index], computed = iteratee ? iteratee(value) : value; value = (comparator || value !== 0) ? value : 0; if (isCommon && computed === computed) { var seenIndex = seen.length; while (seenIndex--) { if (seen[seenIndex] === computed) { continue outer; } } if (iteratee) { seen.push(computed); } result.push(value); } else if (!includes(seen, computed, comparator)) { if (seen !== result) { seen.push(computed); } result.push(value); } } return result; } /** * The base implementation of `_.unset`. * * @private * @param {Object} object The object to modify. * @param {Array|string} path The property path to unset. * @returns {boolean} Returns `true` if the property is deleted, else `false`. */ function baseUnset(object, path) { path = castPath(path, object); object = parent(object, path); return object == null || delete object[toKey(last(path))]; } /** * The base implementation of `_.update`. * * @private * @param {Object} object The object to modify. * @param {Array|string} path The path of the property to update. * @param {Function} updater The function to produce the updated value. * @param {Function} [customizer] The function to customize path creation. * @returns {Object} Returns `object`. */ function baseUpdate(object, path, updater, customizer) { return baseSet(object, path, updater(baseGet(object, path)), customizer); } /** * The base implementation of methods like `_.dropWhile` and `_.takeWhile` * without support for iteratee shorthands. * * @private * @param {Array} array The array to query. * @param {Function} predicate The function invoked per iteration. * @param {boolean} [isDrop] Specify dropping elements instead of taking them. * @param {boolean} [fromRight] Specify iterating from right to left. * @returns {Array} Returns the slice of `array`. */ function baseWhile(array, predicate, isDrop, fromRight) { var length = array.length, index = fromRight ? length : -1; while ((fromRight ? index-- : ++index < length) && predicate(array[index], index, array)) {} return isDrop ? baseSlice(array, (fromRight ? 0 : index), (fromRight ? index + 1 : length)) : baseSlice(array, (fromRight ? index + 1 : 0), (fromRight ? length : index)); } /** * The base implementation of `wrapperValue` which returns the result of * performing a sequence of actions on the unwrapped `value`, where each * successive action is supplied the return value of the previous. * * @private * @param {*} value The unwrapped value. * @param {Array} actions Actions to perform to resolve the unwrapped value. * @returns {*} Returns the resolved value. */ function baseWrapperValue(value, actions) { var result = value; if (result instanceof LazyWrapper) { result = result.value(); } return arrayReduce(actions, function(result, action) { return action.func.apply(action.thisArg, arrayPush([result], action.args)); }, result); } /** * The base implementation of methods like `_.xor`, without support for * iteratee shorthands, that accepts an array of arrays to inspect. * * @private * @param {Array} arrays The arrays to inspect. * @param {Function} [iteratee] The iteratee invoked per element. * @param {Function} [comparator] The comparator invoked per element. * @returns {Array} Returns the new array of values. */ function baseXor(arrays, iteratee, comparator) { var length = arrays.length; if (length < 2) { return length ? baseUniq(arrays[0]) : []; } var index = -1, result = Array(length); while (++index < length) { var array = arrays[index], othIndex = -1; while (++othIndex < length) { if (othIndex != index) { result[index] = baseDifference(result[index] || array, arrays[othIndex], iteratee, comparator); } } } return baseUniq(baseFlatten(result, 1), iteratee, comparator); } /** * This base implementation of `_.zipObject` which assigns values using `assignFunc`. * * @private * @param {Array} props The property identifiers. * @param {Array} values The property values. * @param {Function} assignFunc The function to assign values. * @returns {Object} Returns the new object. */ function baseZipObject(props, values, assignFunc) { var index = -1, length = props.length, valsLength = values.length, result = {}; while (++index < length) { var value = index < valsLength ? values[index] : undefined; assignFunc(result, props[index], value); } return result; } /** * Casts `value` to an empty array if it's not an array like object. * * @private * @param {*} value The value to inspect. * @returns {Array|Object} Returns the cast array-like object. */ function castArrayLikeObject(value) { return isArrayLikeObject(value) ? value : []; } /** * Casts `value` to `identity` if it's not a function. * * @private * @param {*} value The value to inspect. * @returns {Function} Returns cast function. */ function castFunction(value) { return typeof value == 'function' ? value : identity; } /** * Casts `value` to a path array if it's not one. * * @private * @param {*} value The value to inspect. * @param {Object} [object] The object to query keys on. * @returns {Array} Returns the cast property path array. */ function castPath(value, object) { if (isArray(value)) { return value; } return isKey(value, object) ? [value] : stringToPath(toString(value)); } /** * A `baseRest` alias which can be replaced with `identity` by module * replacement plugins. * * @private * @type {Function} * @param {Function} func The function to apply a rest parameter to. * @returns {Function} Returns the new function. */ var castRest = baseRest; /** * Casts `array` to a slice if it's needed. * * @private * @param {Array} array The array to inspect. * @param {number} start The start position. * @param {number} [end=array.length] The end position. * @returns {Array} Returns the cast slice. */ function castSlice(array, start, end) { var length = array.length; end = end === undefined ? length : end; return (!start && end >= length) ? array : baseSlice(array, start, end); } /** * A simple wrapper around the global [`clearTimeout`](https://mdn.io/clearTimeout). * * @private * @param {number|Object} id The timer id or timeout object of the timer to clear. */ var clearTimeout = ctxClearTimeout || function(id) { return root.clearTimeout(id); }; /** * Creates a clone of `buffer`. * * @private * @param {Buffer} buffer The buffer to clone. * @param {boolean} [isDeep] Specify a deep clone. * @returns {Buffer} Returns the cloned buffer. */ function cloneBuffer(buffer, isDeep) { if (isDeep) { return buffer.slice(); } var length = buffer.length, result = allocUnsafe ? allocUnsafe(length) : new buffer.constructor(length); buffer.copy(result); return result; } /** * Creates a clone of `arrayBuffer`. * * @private * @param {ArrayBuffer} arrayBuffer The array buffer to clone. * @returns {ArrayBuffer} Returns the cloned array buffer. */ function cloneArrayBuffer(arrayBuffer) { var result = new arrayBuffer.constructor(arrayBuffer.byteLength); new Uint8Array(result).set(new Uint8Array(arrayBuffer)); return result; } /** * Creates a clone of `dataView`. * * @private * @param {Object} dataView The data view to clone. * @param {boolean} [isDeep] Specify a deep clone. * @returns {Object} Returns the cloned data view. */ function cloneDataView(dataView, isDeep) { var buffer = isDeep ? cloneArrayBuffer(dataView.buffer) : dataView.buffer; return new dataView.constructor(buffer, dataView.byteOffset, dataView.byteLength); } /** * Creates a clone of `regexp`. * * @private * @param {Object} regexp The regexp to clone. * @returns {Object} Returns the cloned regexp. */ function cloneRegExp(regexp) { var result = new regexp.constructor(regexp.source, reFlags.exec(regexp)); result.lastIndex = regexp.lastIndex; return result; } /** * Creates a clone of the `symbol` object. * * @private * @param {Object} symbol The symbol object to clone. * @returns {Object} Returns the cloned symbol object. */ function cloneSymbol(symbol) { return symbolValueOf ? Object(symbolValueOf.call(symbol)) : {}; } /** * Creates a clone of `typedArray`. * * @private * @param {Object} typedArray The typed array to clone. * @param {boolean} [isDeep] Specify a deep clone. * @returns {Object} Returns the cloned typed array. */ function cloneTypedArray(typedArray, isDeep) { var buffer = isDeep ? cloneArrayBuffer(typedArray.buffer) : typedArray.buffer; return new typedArray.constructor(buffer, typedArray.byteOffset, typedArray.length); } /** * Compares values to sort them in ascending order. * * @private * @param {*} value The value to compare. * @param {*} other The other value to compare. * @returns {number} Returns the sort order indicator for `value`. */ function compareAscending(value, other) { if (value !== other) { var valIsDefined = value !== undefined, valIsNull = value === null, valIsReflexive = value === value, valIsSymbol = isSymbol(value); var othIsDefined = other !== undefined, othIsNull = other === null, othIsReflexive = other === other, othIsSymbol = isSymbol(other); if ((!othIsNull && !othIsSymbol && !valIsSymbol && value > other) || (valIsSymbol && othIsDefined && othIsReflexive && !othIsNull && !othIsSymbol) || (valIsNull && othIsDefined && othIsReflexive) || (!valIsDefined && othIsReflexive) || !valIsReflexive) { return 1; } if ((!valIsNull && !valIsSymbol && !othIsSymbol && value < other) || (othIsSymbol && valIsDefined && valIsReflexive && !valIsNull && !valIsSymbol) || (othIsNull && valIsDefined && valIsReflexive) || (!othIsDefined && valIsReflexive) || !othIsReflexive) { return -1; } } return 0; } /** * Used by `_.orderBy` to compare multiple properties of a value to another * and stable sort them. * * If `orders` is unspecified, all values are sorted in ascending order. Otherwise, * specify an order of "desc" for descending or "asc" for ascending sort order * of corresponding values. * * @private * @param {Object} object The object to compare. * @param {Object} other The other object to compare. * @param {boolean[]|string[]} orders The order to sort by for each property. * @returns {number} Returns the sort order indicator for `object`. */ function compareMultiple(object, other, orders) { var index = -1, objCriteria = object.criteria, othCriteria = other.criteria, length = objCriteria.length, ordersLength = orders.length; while (++index < length) { var result = compareAscending(objCriteria[index], othCriteria[index]); if (result) { if (index >= ordersLength) { return result; } var order = orders[index]; return result * (order == 'desc' ? -1 : 1); } } // Fixes an `Array#sort` bug in the JS engine embedded in Adobe applications // that causes it, under certain circumstances, to provide the same value for // `object` and `other`. See https://github.com/jashkenas/underscore/pull/1247 // for more details. // // This also ensures a stable sort in V8 and other engines. // See https://bugs.chromium.org/p/v8/issues/detail?id=90 for more details. return object.index - other.index; } /** * Creates an array that is the composition of partially applied arguments, * placeholders, and provided arguments into a single array of arguments. * * @private * @param {Array} args The provided arguments. * @param {Array} partials The arguments to prepend to those provided. * @param {Array} holders The `partials` placeholder indexes. * @params {boolean} [isCurried] Specify composing for a curried function. * @returns {Array} Returns the new array of composed arguments. */ function composeArgs(args, partials, holders, isCurried) { var argsIndex = -1, argsLength = args.length, holdersLength = holders.length, leftIndex = -1, leftLength = partials.length, rangeLength = nativeMax(argsLength - holdersLength, 0), result = Array(leftLength + rangeLength), isUncurried = !isCurried; while (++leftIndex < leftLength) { result[leftIndex] = partials[leftIndex]; } while (++argsIndex < holdersLength) { if (isUncurried || argsIndex < argsLength) { result[holders[argsIndex]] = args[argsIndex]; } } while (rangeLength--) { result[leftIndex++] = args[argsIndex++]; } return result; } /** * This function is like `composeArgs` except that the arguments composition * is tailored for `_.partialRight`. * * @private * @param {Array} args The provided arguments. * @param {Array} partials The arguments to append to those provided. * @param {Array} holders The `partials` placeholder indexes. * @params {boolean} [isCurried] Specify composing for a curried function. * @returns {Array} Returns the new array of composed arguments. */ function composeArgsRight(args, partials, holders, isCurried) { var argsIndex = -1, argsLength = args.length, holdersIndex = -1, holdersLength = holders.length, rightIndex = -1, rightLength = partials.length, rangeLength = nativeMax(argsLength - holdersLength, 0), result = Array(rangeLength + rightLength), isUncurried = !isCurried; while (++argsIndex < rangeLength) { result[argsIndex] = args[argsIndex]; } var offset = argsIndex; while (++rightIndex < rightLength) { result[offset + rightIndex] = partials[rightIndex]; } while (++holdersIndex < holdersLength) { if (isUncurried || argsIndex < argsLength) { result[offset + holders[holdersIndex]] = args[argsIndex++]; } } return result; } /** * Copies the values of `source` to `array`. * * @private * @param {Array} source The array to copy values from. * @param {Array} [array=[]] The array to copy values to. * @returns {Array} Returns `array`. */ function copyArray(source, array) { var index = -1, length = source.length; array || (array = Array(length)); while (++index < length) { array[index] = source[index]; } return array; } /** * Copies properties of `source` to `object`. * * @private * @param {Object} source The object to copy properties from. * @param {Array} props The property identifiers to copy. * @param {Object} [object={}] The object to copy properties to. * @param {Function} [customizer] The function to customize copied values. * @returns {Object} Returns `object`. */ function copyObject(source, props, object, customizer) { var isNew = !object; object || (object = {}); var index = -1, length = props.length; while (++index < length) { var key = props[index]; var newValue = customizer ? customizer(object[key], source[key], key, object, source) : undefined; if (newValue === undefined) { newValue = source[key]; } if (isNew) { baseAssignValue(object, key, newValue); } else { assignValue(object, key, newValue); } } return object; } /** * Copies own symbols of `source` to `object`. * * @private * @param {Object} source The object to copy symbols from. * @param {Object} [object={}] The object to copy symbols to. * @returns {Object} Returns `object`. */ function copySymbols(source, object) { return copyObject(source, getSymbols(source), object); } /** * Copies own and inherited symbols of `source` to `object`. * * @private * @param {Object} source The object to copy symbols from. * @param {Object} [object={}] The object to copy symbols to. * @returns {Object} Returns `object`. */ function copySymbolsIn(source, object) { return copyObject(source, getSymbolsIn(source), object); } /** * Creates a function like `_.groupBy`. * * @private * @param {Function} setter The function to set accumulator values. * @param {Function} [initializer] The accumulator object initializer. * @returns {Function} Returns the new aggregator function. */ function createAggregator(setter, initializer) { return function(collection, iteratee) { var func = isArray(collection) ? arrayAggregator : baseAggregator, accumulator = initializer ? initializer() : {}; return func(collection, setter, getIteratee(iteratee, 2), accumulator); }; } /** * Creates a function like `_.assign`. * * @private * @param {Function} assigner The function to assign values. * @returns {Function} Returns the new assigner function. */ function createAssigner(assigner) { return baseRest(function(object, sources) { var index = -1, length = sources.length, customizer = length > 1 ? sources[length - 1] : undefined, guard = length > 2 ? sources[2] : undefined; customizer = (assigner.length > 3 && typeof customizer == 'function') ? (length--, customizer) : undefined; if (guard && isIterateeCall(sources[0], sources[1], guard)) { customizer = length < 3 ? undefined : customizer; length = 1; } object = Object(object); while (++index < length) { var source = sources[index]; if (source) { assigner(object, source, index, customizer); } } return object; }); } /** * Creates a `baseEach` or `baseEachRight` function. * * @private * @param {Function} eachFunc The function to iterate over a collection. * @param {boolean} [fromRight] Specify iterating from right to left. * @returns {Function} Returns the new base function. */ function createBaseEach(eachFunc, fromRight) { return function(collection, iteratee) { if (collection == null) { return collection; } if (!isArrayLike(collection)) { return eachFunc(collection, iteratee); } var length = collection.length, index = fromRight ? length : -1, iterable = Object(collection); while ((fromRight ? index-- : ++index < length)) { if (iteratee(iterable[index], index, iterable) === false) { break; } } return collection; }; } /** * Creates a base function for methods like `_.forIn` and `_.forOwn`. * * @private * @param {boolean} [fromRight] Specify iterating from right to left. * @returns {Function} Returns the new base function. */ function createBaseFor(fromRight) { return function(object, iteratee, keysFunc) { var index = -1, iterable = Object(object), props = keysFunc(object), length = props.length; while (length--) { var key = props[fromRight ? length : ++index]; if (iteratee(iterable[key], key, iterable) === false) { break; } } return object; }; } /** * Creates a function that wraps `func` to invoke it with the optional `this` * binding of `thisArg`. * * @private * @param {Function} func The function to wrap. * @param {number} bitmask The bitmask flags. See `createWrap` for more details. * @param {*} [thisArg] The `this` binding of `func`. * @returns {Function} Returns the new wrapped function. */ function createBind(func, bitmask, thisArg) { var isBind = bitmask & WRAP_BIND_FLAG, Ctor = createCtor(func); function wrapper() { var fn = (this && this !== root && this instanceof wrapper) ? Ctor : func; return fn.apply(isBind ? thisArg : this, arguments); } return wrapper; } /** * Creates a function like `_.lowerFirst`. * * @private * @param {string} methodName The name of the `String` case method to use. * @returns {Function} Returns the new case function. */ function createCaseFirst(methodName) { return function(string) { string = toString(string); var strSymbols = hasUnicode(string) ? stringToArray(string) : undefined; var chr = strSymbols ? strSymbols[0] : string.charAt(0); var trailing = strSymbols ? castSlice(strSymbols, 1).join('') : string.slice(1); return chr[methodName]() + trailing; }; } /** * Creates a function like `_.camelCase`. * * @private * @param {Function} callback The function to combine each word. * @returns {Function} Returns the new compounder function. */ function createCompounder(callback) { return function(string) { return arrayReduce(words(deburr(string).replace(reApos, '')), callback, ''); }; } /** * Creates a function that produces an instance of `Ctor` regardless of * whether it was invoked as part of a `new` expression or by `call` or `apply`. * * @private * @param {Function} Ctor The constructor to wrap. * @returns {Function} Returns the new wrapped function. */ function createCtor(Ctor) { return function() { // Use a `switch` statement to work with class constructors. See // http://ecma-international.org/ecma-262/7.0/#sec-ecmascript-function-objects-call-thisargument-argumentslist // for more details. var args = arguments; switch (args.length) { case 0: return new Ctor; case 1: return new Ctor(args[0]); case 2: return new Ctor(args[0], args[1]); case 3: return new Ctor(args[0], args[1], args[2]); case 4: return new Ctor(args[0], args[1], args[2], args[3]); case 5: return new Ctor(args[0], args[1], args[2], args[3], args[4]); case 6: return new Ctor(args[0], args[1], args[2], args[3], args[4], args[5]); case 7: return new Ctor(args[0], args[1], args[2], args[3], args[4], args[5], args[6]); } var thisBinding = baseCreate(Ctor.prototype), result = Ctor.apply(thisBinding, args); // Mimic the constructor's `return` behavior. // See https://es5.github.io/#x13.2.2 for more details. return isObject(result) ? result : thisBinding; }; } /** * Creates a function that wraps `func` to enable currying. * * @private * @param {Function} func The function to wrap. * @param {number} bitmask The bitmask flags. See `createWrap` for more details. * @param {number} arity The arity of `func`. * @returns {Function} Returns the new wrapped function. */ function createCurry(func, bitmask, arity) { var Ctor = createCtor(func); function wrapper() { var length = arguments.length, args = Array(length), index = length, placeholder = getHolder(wrapper); while (index--) { args[index] = arguments[index]; } var holders = (length < 3 && args[0] !== placeholder && args[length - 1] !== placeholder) ? [] : replaceHolders(args, placeholder); length -= holders.length; if (length < arity) { return createRecurry( func, bitmask, createHybrid, wrapper.placeholder, undefined, args, holders, undefined, undefined, arity - length); } var fn = (this && this !== root && this instanceof wrapper) ? Ctor : func; return apply(fn, this, args); } return wrapper; } /** * Creates a `_.find` or `_.findLast` function. * * @private * @param {Function} findIndexFunc The function to find the collection index. * @returns {Function} Returns the new find function. */ function createFind(findIndexFunc) { return function(collection, predicate, fromIndex) { var iterable = Object(collection); if (!isArrayLike(collection)) { var iteratee = getIteratee(predicate, 3); collection = keys(collection); predicate = function(key) { return iteratee(iterable[key], key, iterable); }; } var index = findIndexFunc(collection, predicate, fromIndex); return index > -1 ? iterable[iteratee ? collection[index] : index] : undefined; }; } /** * Creates a `_.flow` or `_.flowRight` function. * * @private * @param {boolean} [fromRight] Specify iterating from right to left. * @returns {Function} Returns the new flow function. */ function createFlow(fromRight) { return flatRest(function(funcs) { var length = funcs.length, index = length, prereq = LodashWrapper.prototype.thru; if (fromRight) { funcs.reverse(); } while (index--) { var func = funcs[index]; if (typeof func != 'function') { throw new TypeError(FUNC_ERROR_TEXT); } if (prereq && !wrapper && getFuncName(func) == 'wrapper') { var wrapper = new LodashWrapper([], true); } } index = wrapper ? index : length; while (++index < length) { func = funcs[index]; var funcName = getFuncName(func), data = funcName == 'wrapper' ? getData(func) : undefined; if (data && isLaziable(data[0]) && data[1] == (WRAP_ARY_FLAG | WRAP_CURRY_FLAG | WRAP_PARTIAL_FLAG | WRAP_REARG_FLAG) && !data[4].length && data[9] == 1 ) { wrapper = wrapper[getFuncName(data[0])].apply(wrapper, data[3]); } else { wrapper = (func.length == 1 && isLaziable(func)) ? wrapper[funcName]() : wrapper.thru(func); } } return function() { var args = arguments, value = args[0]; if (wrapper && args.length == 1 && isArray(value)) { return wrapper.plant(value).value(); } var index = 0, result = length ? funcs[index].apply(this, args) : value; while (++index < length) { result = funcs[index].call(this, result); } return result; }; }); } /** * Creates a function that wraps `func` to invoke it with optional `this` * binding of `thisArg`, partial application, and currying. * * @private * @param {Function|string} func The function or method name to wrap. * @param {number} bitmask The bitmask flags. See `createWrap` for more details. * @param {*} [thisArg] The `this` binding of `func`. * @param {Array} [partials] The arguments to prepend to those provided to * the new function. * @param {Array} [holders] The `partials` placeholder indexes. * @param {Array} [partialsRight] The arguments to append to those provided * to the new function. * @param {Array} [holdersRight] The `partialsRight` placeholder indexes. * @param {Array} [argPos] The argument positions of the new function. * @param {number} [ary] The arity cap of `func`. * @param {number} [arity] The arity of `func`. * @returns {Function} Returns the new wrapped function. */ function createHybrid(func, bitmask, thisArg, partials, holders, partialsRight, holdersRight, argPos, ary, arity) { var isAry = bitmask & WRAP_ARY_FLAG, isBind = bitmask & WRAP_BIND_FLAG, isBindKey = bitmask & WRAP_BIND_KEY_FLAG, isCurried = bitmask & (WRAP_CURRY_FLAG | WRAP_CURRY_RIGHT_FLAG), isFlip = bitmask & WRAP_FLIP_FLAG, Ctor = isBindKey ? undefined : createCtor(func); function wrapper() { var length = arguments.length, args = Array(length), index = length; while (index--) { args[index] = arguments[index]; } if (isCurried) { var placeholder = getHolder(wrapper), holdersCount = countHolders(args, placeholder); } if (partials) { args = composeArgs(args, partials, holders, isCurried); } if (partialsRight) { args = composeArgsRight(args, partialsRight, holdersRight, isCurried); } length -= holdersCount; if (isCurried && length < arity) { var newHolders = replaceHolders(args, placeholder); return createRecurry( func, bitmask, createHybrid, wrapper.placeholder, thisArg, args, newHolders, argPos, ary, arity - length ); } var thisBinding = isBind ? thisArg : this, fn = isBindKey ? thisBinding[func] : func; length = args.length; if (argPos) { args = reorder(args, argPos); } else if (isFlip && length > 1) { args.reverse(); } if (isAry && ary < length) { args.length = ary; } if (this && this !== root && this instanceof wrapper) { fn = Ctor || createCtor(fn); } return fn.apply(thisBinding, args); } return wrapper; } /** * Creates a function like `_.invertBy`. * * @private * @param {Function} setter The function to set accumulator values. * @param {Function} toIteratee The function to resolve iteratees. * @returns {Function} Returns the new inverter function. */ function createInverter(setter, toIteratee) { return function(object, iteratee) { return baseInverter(object, setter, toIteratee(iteratee), {}); }; } /** * Creates a function that performs a mathematical operation on two values. * * @private * @param {Function} operator The function to perform the operation. * @param {number} [defaultValue] The value used for `undefined` arguments. * @returns {Function} Returns the new mathematical operation function. */ function createMathOperation(operator, defaultValue) { return function(value, other) { var result; if (value === undefined && other === undefined) { return defaultValue; } if (value !== undefined) { result = value; } if (other !== undefined) { if (result === undefined) { return other; } if (typeof value == 'string' || typeof other == 'string') { value = baseToString(value); other = baseToString(other); } else { value = baseToNumber(value); other = baseToNumber(other); } result = operator(value, other); } return result; }; } /** * Creates a function like `_.over`. * * @private * @param {Function} arrayFunc The function to iterate over iteratees. * @returns {Function} Returns the new over function. */ function createOver(arrayFunc) { return flatRest(function(iteratees) { iteratees = arrayMap(iteratees, baseUnary(getIteratee())); return baseRest(function(args) { var thisArg = this; return arrayFunc(iteratees, function(iteratee) { return apply(iteratee, thisArg, args); }); }); }); } /** * Creates the padding for `string` based on `length`. The `chars` string * is truncated if the number of characters exceeds `length`. * * @private * @param {number} length The padding length. * @param {string} [chars=' '] The string used as padding. * @returns {string} Returns the padding for `string`. */ function createPadding(length, chars) { chars = chars === undefined ? ' ' : baseToString(chars); var charsLength = chars.length; if (charsLength < 2) { return charsLength ? baseRepeat(chars, length) : chars; } var result = baseRepeat(chars, nativeCeil(length / stringSize(chars))); return hasUnicode(chars) ? castSlice(stringToArray(result), 0, length).join('') : result.slice(0, length); } /** * Creates a function that wraps `func` to invoke it with the `this` binding * of `thisArg` and `partials` prepended to the arguments it receives. * * @private * @param {Function} func The function to wrap. * @param {number} bitmask The bitmask flags. See `createWrap` for more details. * @param {*} thisArg The `this` binding of `func`. * @param {Array} partials The arguments to prepend to those provided to * the new function. * @returns {Function} Returns the new wrapped function. */ function createPartial(func, bitmask, thisArg, partials) { var isBind = bitmask & WRAP_BIND_FLAG, Ctor = createCtor(func); function wrapper() { var argsIndex = -1, argsLength = arguments.length, leftIndex = -1, leftLength = partials.length, args = Array(leftLength + argsLength), fn = (this && this !== root && this instanceof wrapper) ? Ctor : func; while (++leftIndex < leftLength) { args[leftIndex] = partials[leftIndex]; } while (argsLength--) { args[leftIndex++] = arguments[++argsIndex]; } return apply(fn, isBind ? thisArg : this, args); } return wrapper; } /** * Creates a `_.range` or `_.rangeRight` function. * * @private * @param {boolean} [fromRight] Specify iterating from right to left. * @returns {Function} Returns the new range function. */ function createRange(fromRight) { return function(start, end, step) { if (step && typeof step != 'number' && isIterateeCall(start, end, step)) { end = step = undefined; } // Ensure the sign of `-0` is preserved. start = toFinite(start); if (end === undefined) { end = start; start = 0; } else { end = toFinite(end); } step = step === undefined ? (start < end ? 1 : -1) : toFinite(step); return baseRange(start, end, step, fromRight); }; } /** * Creates a function that performs a relational operation on two values. * * @private * @param {Function} operator The function to perform the operation. * @returns {Function} Returns the new relational operation function. */ function createRelationalOperation(operator) { return function(value, other) { if (!(typeof value == 'string' && typeof other == 'string')) { value = toNumber(value); other = toNumber(other); } return operator(value, other); }; } /** * Creates a function that wraps `func` to continue currying. * * @private * @param {Function} func The function to wrap. * @param {number} bitmask The bitmask flags. See `createWrap` for more details. * @param {Function} wrapFunc The function to create the `func` wrapper. * @param {*} placeholder The placeholder value. * @param {*} [thisArg] The `this` binding of `func`. * @param {Array} [partials] The arguments to prepend to those provided to * the new function. * @param {Array} [holders] The `partials` placeholder indexes. * @param {Array} [argPos] The argument positions of the new function. * @param {number} [ary] The arity cap of `func`. * @param {number} [arity] The arity of `func`. * @returns {Function} Returns the new wrapped function. */ function createRecurry(func, bitmask, wrapFunc, placeholder, thisArg, partials, holders, argPos, ary, arity) { var isCurry = bitmask & WRAP_CURRY_FLAG, newHolders = isCurry ? holders : undefined, newHoldersRight = isCurry ? undefined : holders, newPartials = isCurry ? partials : undefined, newPartialsRight = isCurry ? undefined : partials; bitmask |= (isCurry ? WRAP_PARTIAL_FLAG : WRAP_PARTIAL_RIGHT_FLAG); bitmask &= ~(isCurry ? WRAP_PARTIAL_RIGHT_FLAG : WRAP_PARTIAL_FLAG); if (!(bitmask & WRAP_CURRY_BOUND_FLAG)) { bitmask &= ~(WRAP_BIND_FLAG | WRAP_BIND_KEY_FLAG); } var newData = [ func, bitmask, thisArg, newPartials, newHolders, newPartialsRight, newHoldersRight, argPos, ary, arity ]; var result = wrapFunc.apply(undefined, newData); if (isLaziable(func)) { setData(result, newData); } result.placeholder = placeholder; return setWrapToString(result, func, bitmask); } /** * Creates a function like `_.round`. * * @private * @param {string} methodName The name of the `Math` method to use when rounding. * @returns {Function} Returns the new round function. */ function createRound(methodName) { var func = Math[methodName]; return function(number, precision) { number = toNumber(number); precision = precision == null ? 0 : nativeMin(toInteger(precision), 292); if (precision && nativeIsFinite(number)) { // Shift with exponential notation to avoid floating-point issues. // See [MDN](https://mdn.io/round#Examples) for more details. var pair = (toString(number) + 'e').split('e'), value = func(pair[0] + 'e' + (+pair[1] + precision)); pair = (toString(value) + 'e').split('e'); return +(pair[0] + 'e' + (+pair[1] - precision)); } return func(number); }; } /** * Creates a set object of `values`. * * @private * @param {Array} values The values to add to the set. * @returns {Object} Returns the new set. */ var createSet = !(Set && (1 / setToArray(new Set([,-0]))[1]) == INFINITY) ? noop : function(values) { return new Set(values); }; /** * Creates a `_.toPairs` or `_.toPairsIn` function. * * @private * @param {Function} keysFunc The function to get the keys of a given object. * @returns {Function} Returns the new pairs function. */ function createToPairs(keysFunc) { return function(object) { var tag = getTag(object); if (tag == mapTag) { return mapToArray(object); } if (tag == setTag) { return setToPairs(object); } return baseToPairs(object, keysFunc(object)); }; } /** * Creates a function that either curries or invokes `func` with optional * `this` binding and partially applied arguments. * * @private * @param {Function|string} func The function or method name to wrap. * @param {number} bitmask The bitmask flags. * 1 - `_.bind` * 2 - `_.bindKey` * 4 - `_.curry` or `_.curryRight` of a bound function * 8 - `_.curry` * 16 - `_.curryRight` * 32 - `_.partial` * 64 - `_.partialRight` * 128 - `_.rearg` * 256 - `_.ary` * 512 - `_.flip` * @param {*} [thisArg] The `this` binding of `func`. * @param {Array} [partials] The arguments to be partially applied. * @param {Array} [holders] The `partials` placeholder indexes. * @param {Array} [argPos] The argument positions of the new function. * @param {number} [ary] The arity cap of `func`. * @param {number} [arity] The arity of `func`. * @returns {Function} Returns the new wrapped function. */ function createWrap(func, bitmask, thisArg, partials, holders, argPos, ary, arity) { var isBindKey = bitmask & WRAP_BIND_KEY_FLAG; if (!isBindKey && typeof func != 'function') { throw new TypeError(FUNC_ERROR_TEXT); } var length = partials ? partials.length : 0; if (!length) { bitmask &= ~(WRAP_PARTIAL_FLAG | WRAP_PARTIAL_RIGHT_FLAG); partials = holders = undefined; } ary = ary === undefined ? ary : nativeMax(toInteger(ary), 0); arity = arity === undefined ? arity : toInteger(arity); length -= holders ? holders.length : 0; if (bitmask & WRAP_PARTIAL_RIGHT_FLAG) { var partialsRight = partials, holdersRight = holders; partials = holders = undefined; } var data = isBindKey ? undefined : getData(func); var newData = [ func, bitmask, thisArg, partials, holders, partialsRight, holdersRight, argPos, ary, arity ]; if (data) { mergeData(newData, data); } func = newData[0]; bitmask = newData[1]; thisArg = newData[2]; partials = newData[3]; holders = newData[4]; arity = newData[9] = newData[9] === undefined ? (isBindKey ? 0 : func.length) : nativeMax(newData[9] - length, 0); if (!arity && bitmask & (WRAP_CURRY_FLAG | WRAP_CURRY_RIGHT_FLAG)) { bitmask &= ~(WRAP_CURRY_FLAG | WRAP_CURRY_RIGHT_FLAG); } if (!bitmask || bitmask == WRAP_BIND_FLAG) { var result = createBind(func, bitmask, thisArg); } else if (bitmask == WRAP_CURRY_FLAG || bitmask == WRAP_CURRY_RIGHT_FLAG) { result = createCurry(func, bitmask, arity); } else if ((bitmask == WRAP_PARTIAL_FLAG || bitmask == (WRAP_BIND_FLAG | WRAP_PARTIAL_FLAG)) && !holders.length) { result = createPartial(func, bitmask, thisArg, partials); } else { result = createHybrid.apply(undefined, newData); } var setter = data ? baseSetData : setData; return setWrapToString(setter(result, newData), func, bitmask); } /** * Used by `_.defaults` to customize its `_.assignIn` use to assign properties * of source objects to the destination object for all destination properties * that resolve to `undefined`. * * @private * @param {*} objValue The destination value. * @param {*} srcValue The source value. * @param {string} key The key of the property to assign. * @param {Object} object The parent object of `objValue`. * @returns {*} Returns the value to assign. */ function customDefaultsAssignIn(objValue, srcValue, key, object) { if (objValue === undefined || (eq(objValue, objectProto[key]) && !hasOwnProperty.call(object, key))) { return srcValue; } return objValue; } /** * Used by `_.defaultsDeep` to customize its `_.merge` use to merge source * objects into destination objects that are passed thru. * * @private * @param {*} objValue The destination value. * @param {*} srcValue The source value. * @param {string} key The key of the property to merge. * @param {Object} object The parent object of `objValue`. * @param {Object} source The parent object of `srcValue`. * @param {Object} [stack] Tracks traversed source values and their merged * counterparts. * @returns {*} Returns the value to assign. */ function customDefaultsMerge(objValue, srcValue, key, object, source, stack) { if (isObject(objValue) && isObject(srcValue)) { // Recursively merge objects and arrays (susceptible to call stack limits). stack.set(srcValue, objValue); baseMerge(objValue, srcValue, undefined, customDefaultsMerge, stack); stack['delete'](srcValue); } return objValue; } /** * Used by `_.omit` to customize its `_.cloneDeep` use to only clone plain * objects. * * @private * @param {*} value The value to inspect. * @param {string} key The key of the property to inspect. * @returns {*} Returns the uncloned value or `undefined` to defer cloning to `_.cloneDeep`. */ function customOmitClone(value) { return isPlainObject(value) ? undefined : value; } /** * A specialized version of `baseIsEqualDeep` for arrays with support for * partial deep comparisons. * * @private * @param {Array} array The array to compare. * @param {Array} other The other array to compare. * @param {number} bitmask The bitmask flags. See `baseIsEqual` for more details. * @param {Function} customizer The function to customize comparisons. * @param {Function} equalFunc The function to determine equivalents of values. * @param {Object} stack Tracks traversed `array` and `other` objects. * @returns {boolean} Returns `true` if the arrays are equivalent, else `false`. */ function equalArrays(array, other, bitmask, customizer, equalFunc, stack) { var isPartial = bitmask & COMPARE_PARTIAL_FLAG, arrLength = array.length, othLength = other.length; if (arrLength != othLength && !(isPartial && othLength > arrLength)) { return false; } // Assume cyclic values are equal. var stacked = stack.get(array); if (stacked && stack.get(other)) { return stacked == other; } var index = -1, result = true, seen = (bitmask & COMPARE_UNORDERED_FLAG) ? new SetCache : undefined; stack.set(array, other); stack.set(other, array); // Ignore non-index properties. while (++index < arrLength) { var arrValue = array[index], othValue = other[index]; if (customizer) { var compared = isPartial ? customizer(othValue, arrValue, index, other, array, stack) : customizer(arrValue, othValue, index, array, other, stack); } if (compared !== undefined) { if (compared) { continue; } result = false; break; } // Recursively compare arrays (susceptible to call stack limits). if (seen) { if (!arraySome(other, function(othValue, othIndex) { if (!cacheHas(seen, othIndex) && (arrValue === othValue || equalFunc(arrValue, othValue, bitmask, customizer, stack))) { return seen.push(othIndex); } })) { result = false; break; } } else if (!( arrValue === othValue || equalFunc(arrValue, othValue, bitmask, customizer, stack) )) { result = false; break; } } stack['delete'](array); stack['delete'](other); return result; } /** * A specialized version of `baseIsEqualDeep` for comparing objects of * the same `toStringTag`. * * **Note:** This function only supports comparing values with tags of * `Boolean`, `Date`, `Error`, `Number`, `RegExp`, or `String`. * * @private * @param {Object} object The object to compare. * @param {Object} other The other object to compare. * @param {string} tag The `toStringTag` of the objects to compare. * @param {number} bitmask The bitmask flags. See `baseIsEqual` for more details. * @param {Function} customizer The function to customize comparisons. * @param {Function} equalFunc The function to determine equivalents of values. * @param {Object} stack Tracks traversed `object` and `other` objects. * @returns {boolean} Returns `true` if the objects are equivalent, else `false`. */ function equalByTag(object, other, tag, bitmask, customizer, equalFunc, stack) { switch (tag) { case dataViewTag: if ((object.byteLength != other.byteLength) || (object.byteOffset != other.byteOffset)) { return false; } object = object.buffer; other = other.buffer; case arrayBufferTag: if ((object.byteLength != other.byteLength) || !equalFunc(new Uint8Array(object), new Uint8Array(other))) { return false; } return true; case boolTag: case dateTag: case numberTag: // Coerce booleans to `1` or `0` and dates to milliseconds. // Invalid dates are coerced to `NaN`. return eq(+object, +other); case errorTag: return object.name == other.name && object.message == other.message; case regexpTag: case stringTag: // Coerce regexes to strings and treat strings, primitives and objects, // as equal. See http://www.ecma-international.org/ecma-262/7.0/#sec-regexp.prototype.tostring // for more details. return object == (other + ''); case mapTag: var convert = mapToArray; case setTag: var isPartial = bitmask & COMPARE_PARTIAL_FLAG; convert || (convert = setToArray); if (object.size != other.size && !isPartial) { return false; } // Assume cyclic values are equal. var stacked = stack.get(object); if (stacked) { return stacked == other; } bitmask |= COMPARE_UNORDERED_FLAG; // Recursively compare objects (susceptible to call stack limits). stack.set(object, other); var result = equalArrays(convert(object), convert(other), bitmask, customizer, equalFunc, stack); stack['delete'](object); return result; case symbolTag: if (symbolValueOf) { return symbolValueOf.call(object) == symbolValueOf.call(other); } } return false; } /** * A specialized version of `baseIsEqualDeep` for objects with support for * partial deep comparisons. * * @private * @param {Object} object The object to compare. * @param {Object} other The other object to compare. * @param {number} bitmask The bitmask flags. See `baseIsEqual` for more details. * @param {Function} customizer The function to customize comparisons. * @param {Function} equalFunc The function to determine equivalents of values. * @param {Object} stack Tracks traversed `object` and `other` objects. * @returns {boolean} Returns `true` if the objects are equivalent, else `false`. */ function equalObjects(object, other, bitmask, customizer, equalFunc, stack) { var isPartial = bitmask & COMPARE_PARTIAL_FLAG, objProps = getAllKeys(object), objLength = objProps.length, othProps = getAllKeys(other), othLength = othProps.length; if (objLength != othLength && !isPartial) { return false; } var index = objLength; while (index--) { var key = objProps[index]; if (!(isPartial ? key in other : hasOwnProperty.call(other, key))) { return false; } } // Assume cyclic values are equal. var stacked = stack.get(object); if (stacked && stack.get(other)) { return stacked == other; } var result = true; stack.set(object, other); stack.set(other, object); var skipCtor = isPartial; while (++index < objLength) { key = objProps[index]; var objValue = object[key], othValue = other[key]; if (customizer) { var compared = isPartial ? customizer(othValue, objValue, key, other, object, stack) : customizer(objValue, othValue, key, object, other, stack); } // Recursively compare objects (susceptible to call stack limits). if (!(compared === undefined ? (objValue === othValue || equalFunc(objValue, othValue, bitmask, customizer, stack)) : compared )) { result = false; break; } skipCtor || (skipCtor = key == 'constructor'); } if (result && !skipCtor) { var objCtor = object.constructor, othCtor = other.constructor; // Non `Object` object instances with different constructors are not equal. if (objCtor != othCtor && ('constructor' in object && 'constructor' in other) && !(typeof objCtor == 'function' && objCtor instanceof objCtor && typeof othCtor == 'function' && othCtor instanceof othCtor)) { result = false; } } stack['delete'](object); stack['delete'](other); return result; } /** * A specialized version of `baseRest` which flattens the rest array. * * @private * @param {Function} func The function to apply a rest parameter to. * @returns {Function} Returns the new function. */ function flatRest(func) { return setToString(overRest(func, undefined, flatten), func + ''); } /** * Creates an array of own enumerable property names and symbols of `object`. * * @private * @param {Object} object The object to query. * @returns {Array} Returns the array of property names and symbols. */ function getAllKeys(object) { return baseGetAllKeys(object, keys, getSymbols); } /** * Creates an array of own and inherited enumerable property names and * symbols of `object`. * * @private * @param {Object} object The object to query. * @returns {Array} Returns the array of property names and symbols. */ function getAllKeysIn(object) { return baseGetAllKeys(object, keysIn, getSymbolsIn); } /** * Gets metadata for `func`. * * @private * @param {Function} func The function to query. * @returns {*} Returns the metadata for `func`. */ var getData = !metaMap ? noop : function(func) { return metaMap.get(func); }; /** * Gets the name of `func`. * * @private * @param {Function} func The function to query. * @returns {string} Returns the function name. */ function getFuncName(func) { var result = (func.name + ''), array = realNames[result], length = hasOwnProperty.call(realNames, result) ? array.length : 0; while (length--) { var data = array[length], otherFunc = data.func; if (otherFunc == null || otherFunc == func) { return data.name; } } return result; } /** * Gets the argument placeholder value for `func`. * * @private * @param {Function} func The function to inspect. * @returns {*} Returns the placeholder value. */ function getHolder(func) { var object = hasOwnProperty.call(lodash, 'placeholder') ? lodash : func; return object.placeholder; } /** * Gets the appropriate "iteratee" function. If `_.iteratee` is customized, * this function returns the custom method, otherwise it returns `baseIteratee`. * If arguments are provided, the chosen function is invoked with them and * its result is returned. * * @private * @param {*} [value] The value to convert to an iteratee. * @param {number} [arity] The arity of the created iteratee. * @returns {Function} Returns the chosen function or its result. */ function getIteratee() { var result = lodash.iteratee || iteratee; result = result === iteratee ? baseIteratee : result; return arguments.length ? result(arguments[0], arguments[1]) : result; } /** * Gets the data for `map`. * * @private * @param {Object} map The map to query. * @param {string} key The reference key. * @returns {*} Returns the map data. */ function getMapData(map, key) { var data = map.__data__; return isKeyable(key) ? data[typeof key == 'string' ? 'string' : 'hash'] : data.map; } /** * Gets the property names, values, and compare flags of `object`. * * @private * @param {Object} object The object to query. * @returns {Array} Returns the match data of `object`. */ function getMatchData(object) { var result = keys(object), length = result.length; while (length--) { var key = result[length], value = object[key]; result[length] = [key, value, isStrictComparable(value)]; } return result; } /** * Gets the native function at `key` of `object`. * * @private * @param {Object} object The object to query. * @param {string} key The key of the method to get. * @returns {*} Returns the function if it's native, else `undefined`. */ function getNative(object, key) { var value = getValue(object, key); return baseIsNative(value) ? value : undefined; } /** * A specialized version of `baseGetTag` which ignores `Symbol.toStringTag` values. * * @private * @param {*} value The value to query. * @returns {string} Returns the raw `toStringTag`. */ function getRawTag(value) { var isOwn = hasOwnProperty.call(value, symToStringTag), tag = value[symToStringTag]; try { value[symToStringTag] = undefined; var unmasked = true; } catch (e) {} var result = nativeObjectToString.call(value); if (unmasked) { if (isOwn) { value[symToStringTag] = tag; } else { delete value[symToStringTag]; } } return result; } /** * Creates an array of the own enumerable symbols of `object`. * * @private * @param {Object} object The object to query. * @returns {Array} Returns the array of symbols. */ var getSymbols = !nativeGetSymbols ? stubArray : function(object) { if (object == null) { return []; } object = Object(object); return arrayFilter(nativeGetSymbols(object), function(symbol) { return propertyIsEnumerable.call(object, symbol); }); }; /** * Creates an array of the own and inherited enumerable symbols of `object`. * * @private * @param {Object} object The object to query. * @returns {Array} Returns the array of symbols. */ var getSymbolsIn = !nativeGetSymbols ? stubArray : function(object) { var result = []; while (object) { arrayPush(result, getSymbols(object)); object = getPrototype(object); } return result; }; /** * Gets the `toStringTag` of `value`. * * @private * @param {*} value The value to query. * @returns {string} Returns the `toStringTag`. */ var getTag = baseGetTag; // Fallback for data views, maps, sets, and weak maps in IE 11 and promises in Node.js < 6. if ((DataView && getTag(new DataView(new ArrayBuffer(1))) != dataViewTag) || (Map && getTag(new Map) != mapTag) || (Promise && getTag(Promise.resolve()) != promiseTag) || (Set && getTag(new Set) != setTag) || (WeakMap && getTag(new WeakMap) != weakMapTag)) { getTag = function(value) { var result = baseGetTag(value), Ctor = result == objectTag ? value.constructor : undefined, ctorString = Ctor ? toSource(Ctor) : ''; if (ctorString) { switch (ctorString) { case dataViewCtorString: return dataViewTag; case mapCtorString: return mapTag; case promiseCtorString: return promiseTag; case setCtorString: return setTag; case weakMapCtorString: return weakMapTag; } } return result; }; } /** * Gets the view, applying any `transforms` to the `start` and `end` positions. * * @private * @param {number} start The start of the view. * @param {number} end The end of the view. * @param {Array} transforms The transformations to apply to the view. * @returns {Object} Returns an object containing the `start` and `end` * positions of the view. */ function getView(start, end, transforms) { var index = -1, length = transforms.length; while (++index < length) { var data = transforms[index], size = data.size; switch (data.type) { case 'drop': start += size; break; case 'dropRight': end -= size; break; case 'take': end = nativeMin(end, start + size); break; case 'takeRight': start = nativeMax(start, end - size); break; } } return { 'start': start, 'end': end }; } /** * Extracts wrapper details from the `source` body comment. * * @private * @param {string} source The source to inspect. * @returns {Array} Returns the wrapper details. */ function getWrapDetails(source) { var match = source.match(reWrapDetails); return match ? match[1].split(reSplitDetails) : []; } /** * Checks if `path` exists on `object`. * * @private * @param {Object} object The object to query. * @param {Array|string} path The path to check. * @param {Function} hasFunc The function to check properties. * @returns {boolean} Returns `true` if `path` exists, else `false`. */ function hasPath(object, path, hasFunc) { path = castPath(path, object); var index = -1, length = path.length, result = false; while (++index < length) { var key = toKey(path[index]); if (!(result = object != null && hasFunc(object, key))) { break; } object = object[key]; } if (result || ++index != length) { return result; } length = object == null ? 0 : object.length; return !!length && isLength(length) && isIndex(key, length) && (isArray(object) || isArguments(object)); } /** * Initializes an array clone. * * @private * @param {Array} array The array to clone. * @returns {Array} Returns the initialized clone. */ function initCloneArray(array) { var length = array.length, result = new array.constructor(length); // Add properties assigned by `RegExp#exec`. if (length && typeof array[0] == 'string' && hasOwnProperty.call(array, 'index')) { result.index = array.index; result.input = array.input; } return result; } /** * Initializes an object clone. * * @private * @param {Object} object The object to clone. * @returns {Object} Returns the initialized clone. */ function initCloneObject(object) { return (typeof object.constructor == 'function' && !isPrototype(object)) ? baseCreate(getPrototype(object)) : {}; } /** * Initializes an object clone based on its `toStringTag`. * * **Note:** This function only supports cloning values with tags of * `Boolean`, `Date`, `Error`, `Map`, `Number`, `RegExp`, `Set`, or `String`. * * @private * @param {Object} object The object to clone. * @param {string} tag The `toStringTag` of the object to clone. * @param {boolean} [isDeep] Specify a deep clone. * @returns {Object} Returns the initialized clone. */ function initCloneByTag(object, tag, isDeep) { var Ctor = object.constructor; switch (tag) { case arrayBufferTag: return cloneArrayBuffer(object); case boolTag: case dateTag: return new Ctor(+object); case dataViewTag: return cloneDataView(object, isDeep); case float32Tag: case float64Tag: case int8Tag: case int16Tag: case int32Tag: case uint8Tag: case uint8ClampedTag: case uint16Tag: case uint32Tag: return cloneTypedArray(object, isDeep); case mapTag: return new Ctor; case numberTag: case stringTag: return new Ctor(object); case regexpTag: return cloneRegExp(object); case setTag: return new Ctor; case symbolTag: return cloneSymbol(object); } } /** * Inserts wrapper `details` in a comment at the top of the `source` body. * * @private * @param {string} source The source to modify. * @returns {Array} details The details to insert. * @returns {string} Returns the modified source. */ function insertWrapDetails(source, details) { var length = details.length; if (!length) { return source; } var lastIndex = length - 1; details[lastIndex] = (length > 1 ? '& ' : '') + details[lastIndex]; details = details.join(length > 2 ? ', ' : ' '); return source.replace(reWrapComment, '{\n/* [wrapped with ' + details + '] */\n'); } /** * Checks if `value` is a flattenable `arguments` object or array. * * @private * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is flattenable, else `false`. */ function isFlattenable(value) { return isArray(value) || isArguments(value) || !!(spreadableSymbol && value && value[spreadableSymbol]); } /** * Checks if `value` is a valid array-like index. * * @private * @param {*} value The value to check. * @param {number} [length=MAX_SAFE_INTEGER] The upper bounds of a valid index. * @returns {boolean} Returns `true` if `value` is a valid index, else `false`. */ function isIndex(value, length) { var type = typeof value; length = length == null ? MAX_SAFE_INTEGER : length; return !!length && (type == 'number' || (type != 'symbol' && reIsUint.test(value))) && (value > -1 && value % 1 == 0 && value < length); } /** * Checks if the given arguments are from an iteratee call. * * @private * @param {*} value The potential iteratee value argument. * @param {*} index The potential iteratee index or key argument. * @param {*} object The potential iteratee object argument. * @returns {boolean} Returns `true` if the arguments are from an iteratee call, * else `false`. */ function isIterateeCall(value, index, object) { if (!isObject(object)) { return false; } var type = typeof index; if (type == 'number' ? (isArrayLike(object) && isIndex(index, object.length)) : (type == 'string' && index in object) ) { return eq(object[index], value); } return false; } /** * Checks if `value` is a property name and not a property path. * * @private * @param {*} value The value to check. * @param {Object} [object] The object to query keys on. * @returns {boolean} Returns `true` if `value` is a property name, else `false`. */ function isKey(value, object) { if (isArray(value)) { return false; } var type = typeof value; if (type == 'number' || type == 'symbol' || type == 'boolean' || value == null || isSymbol(value)) { return true; } return reIsPlainProp.test(value) || !reIsDeepProp.test(value) || (object != null && value in Object(object)); } /** * Checks if `value` is suitable for use as unique object key. * * @private * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is suitable, else `false`. */ function isKeyable(value) { var type = typeof value; return (type == 'string' || type == 'number' || type == 'symbol' || type == 'boolean') ? (value !== '__proto__') : (value === null); } /** * Checks if `func` has a lazy counterpart. * * @private * @param {Function} func The function to check. * @returns {boolean} Returns `true` if `func` has a lazy counterpart, * else `false`. */ function isLaziable(func) { var funcName = getFuncName(func), other = lodash[funcName]; if (typeof other != 'function' || !(funcName in LazyWrapper.prototype)) { return false; } if (func === other) { return true; } var data = getData(other); return !!data && func === data[0]; } /** * Checks if `func` has its source masked. * * @private * @param {Function} func The function to check. * @returns {boolean} Returns `true` if `func` is masked, else `false`. */ function isMasked(func) { return !!maskSrcKey && (maskSrcKey in func); } /** * Checks if `func` is capable of being masked. * * @private * @param {*} value The value to check. * @returns {boolean} Returns `true` if `func` is maskable, else `false`. */ var isMaskable = coreJsData ? isFunction : stubFalse; /** * Checks if `value` is likely a prototype object. * * @private * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a prototype, else `false`. */ function isPrototype(value) { var Ctor = value && value.constructor, proto = (typeof Ctor == 'function' && Ctor.prototype) || objectProto; return value === proto; } /** * Checks if `value` is suitable for strict equality comparisons, i.e. `===`. * * @private * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` if suitable for strict * equality comparisons, else `false`. */ function isStrictComparable(value) { return value === value && !isObject(value); } /** * A specialized version of `matchesProperty` for source values suitable * for strict equality comparisons, i.e. `===`. * * @private * @param {string} key The key of the property to get. * @param {*} srcValue The value to match. * @returns {Function} Returns the new spec function. */ function matchesStrictComparable(key, srcValue) { return function(object) { if (object == null) { return false; } return object[key] === srcValue && (srcValue !== undefined || (key in Object(object))); }; } /** * A specialized version of `_.memoize` which clears the memoized function's * cache when it exceeds `MAX_MEMOIZE_SIZE`. * * @private * @param {Function} func The function to have its output memoized. * @returns {Function} Returns the new memoized function. */ function memoizeCapped(func) { var result = memoize(func, function(key) { if (cache.size === MAX_MEMOIZE_SIZE) { cache.clear(); } return key; }); var cache = result.cache; return result; } /** * Merges the function metadata of `source` into `data`. * * Merging metadata reduces the number of wrappers used to invoke a function. * This is possible because methods like `_.bind`, `_.curry`, and `_.partial` * may be applied regardless of execution order. Methods like `_.ary` and * `_.rearg` modify function arguments, making the order in which they are * executed important, preventing the merging of metadata. However, we make * an exception for a safe combined case where curried functions have `_.ary` * and or `_.rearg` applied. * * @private * @param {Array} data The destination metadata. * @param {Array} source The source metadata. * @returns {Array} Returns `data`. */ function mergeData(data, source) { var bitmask = data[1], srcBitmask = source[1], newBitmask = bitmask | srcBitmask, isCommon = newBitmask < (WRAP_BIND_FLAG | WRAP_BIND_KEY_FLAG | WRAP_ARY_FLAG); var isCombo = ((srcBitmask == WRAP_ARY_FLAG) && (bitmask == WRAP_CURRY_FLAG)) || ((srcBitmask == WRAP_ARY_FLAG) && (bitmask == WRAP_REARG_FLAG) && (data[7].length <= source[8])) || ((srcBitmask == (WRAP_ARY_FLAG | WRAP_REARG_FLAG)) && (source[7].length <= source[8]) && (bitmask == WRAP_CURRY_FLAG)); // Exit early if metadata can't be merged. if (!(isCommon || isCombo)) { return data; } // Use source `thisArg` if available. if (srcBitmask & WRAP_BIND_FLAG) { data[2] = source[2]; // Set when currying a bound function. newBitmask |= bitmask & WRAP_BIND_FLAG ? 0 : WRAP_CURRY_BOUND_FLAG; } // Compose partial arguments. var value = source[3]; if (value) { var partials = data[3]; data[3] = partials ? composeArgs(partials, value, source[4]) : value; data[4] = partials ? replaceHolders(data[3], PLACEHOLDER) : source[4]; } // Compose partial right arguments. value = source[5]; if (value) { partials = data[5]; data[5] = partials ? composeArgsRight(partials, value, source[6]) : value; data[6] = partials ? replaceHolders(data[5], PLACEHOLDER) : source[6]; } // Use source `argPos` if available. value = source[7]; if (value) { data[7] = value; } // Use source `ary` if it's smaller. if (srcBitmask & WRAP_ARY_FLAG) { data[8] = data[8] == null ? source[8] : nativeMin(data[8], source[8]); } // Use source `arity` if one is not provided. if (data[9] == null) { data[9] = source[9]; } // Use source `func` and merge bitmasks. data[0] = source[0]; data[1] = newBitmask; return data; } /** * This function is like * [`Object.keys`](http://ecma-international.org/ecma-262/7.0/#sec-object.keys) * except that it includes inherited enumerable properties. * * @private * @param {Object} object The object to query. * @returns {Array} Returns the array of property names. */ function nativeKeysIn(object) { var result = []; if (object != null) { for (var key in Object(object)) { result.push(key); } } return result; } /** * Converts `value` to a string using `Object.prototype.toString`. * * @private * @param {*} value The value to convert. * @returns {string} Returns the converted string. */ function objectToString(value) { return nativeObjectToString.call(value); } /** * A specialized version of `baseRest` which transforms the rest array. * * @private * @param {Function} func The function to apply a rest parameter to. * @param {number} [start=func.length-1] The start position of the rest parameter. * @param {Function} transform The rest array transform. * @returns {Function} Returns the new function. */ function overRest(func, start, transform) { start = nativeMax(start === undefined ? (func.length - 1) : start, 0); return function() { var args = arguments, index = -1, length = nativeMax(args.length - start, 0), array = Array(length); while (++index < length) { array[index] = args[start + index]; } index = -1; var otherArgs = Array(start + 1); while (++index < start) { otherArgs[index] = args[index]; } otherArgs[start] = transform(array); return apply(func, this, otherArgs); }; } /** * Gets the parent value at `path` of `object`. * * @private * @param {Object} object The object to query. * @param {Array} path The path to get the parent value of. * @returns {*} Returns the parent value. */ function parent(object, path) { return path.length < 2 ? object : baseGet(object, baseSlice(path, 0, -1)); } /** * Reorder `array` according to the specified indexes where the element at * the first index is assigned as the first element, the element at * the second index is assigned as the second element, and so on. * * @private * @param {Array} array The array to reorder. * @param {Array} indexes The arranged array indexes. * @returns {Array} Returns `array`. */ function reorder(array, indexes) { var arrLength = array.length, length = nativeMin(indexes.length, arrLength), oldArray = copyArray(array); while (length--) { var index = indexes[length]; array[length] = isIndex(index, arrLength) ? oldArray[index] : undefined; } return array; } /** * Gets the value at `key`, unless `key` is "__proto__" or "constructor". * * @private * @param {Object} object The object to query. * @param {string} key The key of the property to get. * @returns {*} Returns the property value. */ function safeGet(object, key) { if (key === 'constructor' && typeof object[key] === 'function') { return; } if (key == '__proto__') { return; } return object[key]; } /** * Sets metadata for `func`. * * **Note:** If this function becomes hot, i.e. is invoked a lot in a short * period of time, it will trip its breaker and transition to an identity * function to avoid garbage collection pauses in V8. See * [V8 issue 2070](https://bugs.chromium.org/p/v8/issues/detail?id=2070) * for more details. * * @private * @param {Function} func The function to associate metadata with. * @param {*} data The metadata. * @returns {Function} Returns `func`. */ var setData = shortOut(baseSetData); /** * A simple wrapper around the global [`setTimeout`](https://mdn.io/setTimeout). * * @private * @param {Function} func The function to delay. * @param {number} wait The number of milliseconds to delay invocation. * @returns {number|Object} Returns the timer id or timeout object. */ var setTimeout = ctxSetTimeout || function(func, wait) { return root.setTimeout(func, wait); }; /** * Sets the `toString` method of `func` to return `string`. * * @private * @param {Function} func The function to modify. * @param {Function} string The `toString` result. * @returns {Function} Returns `func`. */ var setToString = shortOut(baseSetToString); /** * Sets the `toString` method of `wrapper` to mimic the source of `reference` * with wrapper details in a comment at the top of the source body. * * @private * @param {Function} wrapper The function to modify. * @param {Function} reference The reference function. * @param {number} bitmask The bitmask flags. See `createWrap` for more details. * @returns {Function} Returns `wrapper`. */ function setWrapToString(wrapper, reference, bitmask) { var source = (reference + ''); return setToString(wrapper, insertWrapDetails(source, updateWrapDetails(getWrapDetails(source), bitmask))); } /** * Creates a function that'll short out and invoke `identity` instead * of `func` when it's called `HOT_COUNT` or more times in `HOT_SPAN` * milliseconds. * * @private * @param {Function} func The function to restrict. * @returns {Function} Returns the new shortable function. */ function shortOut(func) { var count = 0, lastCalled = 0; return function() { var stamp = nativeNow(), remaining = HOT_SPAN - (stamp - lastCalled); lastCalled = stamp; if (remaining > 0) { if (++count >= HOT_COUNT) { return arguments[0]; } } else { count = 0; } return func.apply(undefined, arguments); }; } /** * A specialized version of `_.shuffle` which mutates and sets the size of `array`. * * @private * @param {Array} array The array to shuffle. * @param {number} [size=array.length] The size of `array`. * @returns {Array} Returns `array`. */ function shuffleSelf(array, size) { var index = -1, length = array.length, lastIndex = length - 1; size = size === undefined ? length : size; while (++index < size) { var rand = baseRandom(index, lastIndex), value = array[rand]; array[rand] = array[index]; array[index] = value; } array.length = size; return array; } /** * Converts `string` to a property path array. * * @private * @param {string} string The string to convert. * @returns {Array} Returns the property path array. */ var stringToPath = memoizeCapped(function(string) { var result = []; if (string.charCodeAt(0) === 46 /* . */) { result.push(''); } string.replace(rePropName, function(match, number, quote, subString) { result.push(quote ? subString.replace(reEscapeChar, '$1') : (number || match)); }); return result; }); /** * Converts `value` to a string key if it's not a string or symbol. * * @private * @param {*} value The value to inspect. * @returns {string|symbol} Returns the key. */ function toKey(value) { if (typeof value == 'string' || isSymbol(value)) { return value; } var result = (value + ''); return (result == '0' && (1 / value) == -INFINITY) ? '-0' : result; } /** * Converts `func` to its source code. * * @private * @param {Function} func The function to convert. * @returns {string} Returns the source code. */ function toSource(func) { if (func != null) { try { return funcToString.call(func); } catch (e) {} try { return (func + ''); } catch (e) {} } return ''; } /** * Updates wrapper `details` based on `bitmask` flags. * * @private * @returns {Array} details The details to modify. * @param {number} bitmask The bitmask flags. See `createWrap` for more details. * @returns {Array} Returns `details`. */ function updateWrapDetails(details, bitmask) { arrayEach(wrapFlags, function(pair) { var value = '_.' + pair[0]; if ((bitmask & pair[1]) && !arrayIncludes(details, value)) { details.push(value); } }); return details.sort(); } /** * Creates a clone of `wrapper`. * * @private * @param {Object} wrapper The wrapper to clone. * @returns {Object} Returns the cloned wrapper. */ function wrapperClone(wrapper) { if (wrapper instanceof LazyWrapper) { return wrapper.clone(); } var result = new LodashWrapper(wrapper.__wrapped__, wrapper.__chain__); result.__actions__ = copyArray(wrapper.__actions__); result.__index__ = wrapper.__index__; result.__values__ = wrapper.__values__; return result; } /*------------------------------------------------------------------------*/ /** * Creates an array of elements split into groups the length of `size`. * If `array` can't be split evenly, the final chunk will be the remaining * elements. * * @static * @memberOf _ * @since 3.0.0 * @category Array * @param {Array} array The array to process. * @param {number} [size=1] The length of each chunk * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. * @returns {Array} Returns the new array of chunks. * @example * * _.chunk(['a', 'b', 'c', 'd'], 2); * // => [['a', 'b'], ['c', 'd']] * * _.chunk(['a', 'b', 'c', 'd'], 3); * // => [['a', 'b', 'c'], ['d']] */ function chunk(array, size, guard) { if ((guard ? isIterateeCall(array, size, guard) : size === undefined)) { size = 1; } else { size = nativeMax(toInteger(size), 0); } var length = array == null ? 0 : array.length; if (!length || size < 1) { return []; } var index = 0, resIndex = 0, result = Array(nativeCeil(length / size)); while (index < length) { result[resIndex++] = baseSlice(array, index, (index += size)); } return result; } /** * Creates an array with all falsey values removed. The values `false`, `null`, * `0`, `""`, `undefined`, and `NaN` are falsey. * * @static * @memberOf _ * @since 0.1.0 * @category Array * @param {Array} array The array to compact. * @returns {Array} Returns the new array of filtered values. * @example * * _.compact([0, 1, false, 2, '', 3]); * // => [1, 2, 3] */ function compact(array) { var index = -1, length = array == null ? 0 : array.length, resIndex = 0, result = []; while (++index < length) { var value = array[index]; if (value) { result[resIndex++] = value; } } return result; } /** * Creates a new array concatenating `array` with any additional arrays * and/or values. * * @static * @memberOf _ * @since 4.0.0 * @category Array * @param {Array} array The array to concatenate. * @param {...*} [values] The values to concatenate. * @returns {Array} Returns the new concatenated array. * @example * * var array = [1]; * var other = _.concat(array, 2, [3], [[4]]); * * console.log(other); * // => [1, 2, 3, [4]] * * console.log(array); * // => [1] */ function concat() { var length = arguments.length; if (!length) { return []; } var args = Array(length - 1), array = arguments[0], index = length; while (index--) { args[index - 1] = arguments[index]; } return arrayPush(isArray(array) ? copyArray(array) : [array], baseFlatten(args, 1)); } /** * Creates an array of `array` values not included in the other given arrays * using [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) * for equality comparisons. The order and references of result values are * determined by the first array. * * **Note:** Unlike `_.pullAll`, this method returns a new array. * * @static * @memberOf _ * @since 0.1.0 * @category Array * @param {Array} array The array to inspect. * @param {...Array} [values] The values to exclude. * @returns {Array} Returns the new array of filtered values. * @see _.without, _.xor * @example * * _.difference([2, 1], [2, 3]); * // => [1] */ var difference = baseRest(function(array, values) { return isArrayLikeObject(array) ? baseDifference(array, baseFlatten(values, 1, isArrayLikeObject, true)) : []; }); /** * This method is like `_.difference` except that it accepts `iteratee` which * is invoked for each element of `array` and `values` to generate the criterion * by which they're compared. The order and references of result values are * determined by the first array. The iteratee is invoked with one argument: * (value). * * **Note:** Unlike `_.pullAllBy`, this method returns a new array. * * @static * @memberOf _ * @since 4.0.0 * @category Array * @param {Array} array The array to inspect. * @param {...Array} [values] The values to exclude. * @param {Function} [iteratee=_.identity] The iteratee invoked per element. * @returns {Array} Returns the new array of filtered values. * @example * * _.differenceBy([2.1, 1.2], [2.3, 3.4], Math.floor); * // => [1.2] * * // The `_.property` iteratee shorthand. * _.differenceBy([{ 'x': 2 }, { 'x': 1 }], [{ 'x': 1 }], 'x'); * // => [{ 'x': 2 }] */ var differenceBy = baseRest(function(array, values) { var iteratee = last(values); if (isArrayLikeObject(iteratee)) { iteratee = undefined; } return isArrayLikeObject(array) ? baseDifference(array, baseFlatten(values, 1, isArrayLikeObject, true), getIteratee(iteratee, 2)) : []; }); /** * This method is like `_.difference` except that it accepts `comparator` * which is invoked to compare elements of `array` to `values`. The order and * references of result values are determined by the first array. The comparator * is invoked with two arguments: (arrVal, othVal). * * **Note:** Unlike `_.pullAllWith`, this method returns a new array. * * @static * @memberOf _ * @since 4.0.0 * @category Array * @param {Array} array The array to inspect. * @param {...Array} [values] The values to exclude. * @param {Function} [comparator] The comparator invoked per element. * @returns {Array} Returns the new array of filtered values. * @example * * var objects = [{ 'x': 1, 'y': 2 }, { 'x': 2, 'y': 1 }]; * * _.differenceWith(objects, [{ 'x': 1, 'y': 2 }], _.isEqual); * // => [{ 'x': 2, 'y': 1 }] */ var differenceWith = baseRest(function(array, values) { var comparator = last(values); if (isArrayLikeObject(comparator)) { comparator = undefined; } return isArrayLikeObject(array) ? baseDifference(array, baseFlatten(values, 1, isArrayLikeObject, true), undefined, comparator) : []; }); /** * Creates a slice of `array` with `n` elements dropped from the beginning. * * @static * @memberOf _ * @since 0.5.0 * @category Array * @param {Array} array The array to query. * @param {number} [n=1] The number of elements to drop. * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. * @returns {Array} Returns the slice of `array`. * @example * * _.drop([1, 2, 3]); * // => [2, 3] * * _.drop([1, 2, 3], 2); * // => [3] * * _.drop([1, 2, 3], 5); * // => [] * * _.drop([1, 2, 3], 0); * // => [1, 2, 3] */ function drop(array, n, guard) { var length = array == null ? 0 : array.length; if (!length) { return []; } n = (guard || n === undefined) ? 1 : toInteger(n); return baseSlice(array, n < 0 ? 0 : n, length); } /** * Creates a slice of `array` with `n` elements dropped from the end. * * @static * @memberOf _ * @since 3.0.0 * @category Array * @param {Array} array The array to query. * @param {number} [n=1] The number of elements to drop. * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. * @returns {Array} Returns the slice of `array`. * @example * * _.dropRight([1, 2, 3]); * // => [1, 2] * * _.dropRight([1, 2, 3], 2); * // => [1] * * _.dropRight([1, 2, 3], 5); * // => [] * * _.dropRight([1, 2, 3], 0); * // => [1, 2, 3] */ function dropRight(array, n, guard) { var length = array == null ? 0 : array.length; if (!length) { return []; } n = (guard || n === undefined) ? 1 : toInteger(n); n = length - n; return baseSlice(array, 0, n < 0 ? 0 : n); } /** * Creates a slice of `array` excluding elements dropped from the end. * Elements are dropped until `predicate` returns falsey. The predicate is * invoked with three arguments: (value, index, array). * * @static * @memberOf _ * @since 3.0.0 * @category Array * @param {Array} array The array to query. * @param {Function} [predicate=_.identity] The function invoked per iteration. * @returns {Array} Returns the slice of `array`. * @example * * var users = [ * { 'user': 'barney', 'active': true }, * { 'user': 'fred', 'active': false }, * { 'user': 'pebbles', 'active': false } * ]; * * _.dropRightWhile(users, function(o) { return !o.active; }); * // => objects for ['barney'] * * // The `_.matches` iteratee shorthand. * _.dropRightWhile(users, { 'user': 'pebbles', 'active': false }); * // => objects for ['barney', 'fred'] * * // The `_.matchesProperty` iteratee shorthand. * _.dropRightWhile(users, ['active', false]); * // => objects for ['barney'] * * // The `_.property` iteratee shorthand. * _.dropRightWhile(users, 'active'); * // => objects for ['barney', 'fred', 'pebbles'] */ function dropRightWhile(array, predicate) { return (array && array.length) ? baseWhile(array, getIteratee(predicate, 3), true, true) : []; } /** * Creates a slice of `array` excluding elements dropped from the beginning. * Elements are dropped until `predicate` returns falsey. The predicate is * invoked with three arguments: (value, index, array). * * @static * @memberOf _ * @since 3.0.0 * @category Array * @param {Array} array The array to query. * @param {Function} [predicate=_.identity] The function invoked per iteration. * @returns {Array} Returns the slice of `array`. * @example * * var users = [ * { 'user': 'barney', 'active': false }, * { 'user': 'fred', 'active': false }, * { 'user': 'pebbles', 'active': true } * ]; * * _.dropWhile(users, function(o) { return !o.active; }); * // => objects for ['pebbles'] * * // The `_.matches` iteratee shorthand. * _.dropWhile(users, { 'user': 'barney', 'active': false }); * // => objects for ['fred', 'pebbles'] * * // The `_.matchesProperty` iteratee shorthand. * _.dropWhile(users, ['active', false]); * // => objects for ['pebbles'] * * // The `_.property` iteratee shorthand. * _.dropWhile(users, 'active'); * // => objects for ['barney', 'fred', 'pebbles'] */ function dropWhile(array, predicate) { return (array && array.length) ? baseWhile(array, getIteratee(predicate, 3), true) : []; } /** * Fills elements of `array` with `value` from `start` up to, but not * including, `end`. * * **Note:** This method mutates `array`. * * @static * @memberOf _ * @since 3.2.0 * @category Array * @param {Array} array The array to fill. * @param {*} value The value to fill `array` with. * @param {number} [start=0] The start position. * @param {number} [end=array.length] The end position. * @returns {Array} Returns `array`. * @example * * var array = [1, 2, 3]; * * _.fill(array, 'a'); * console.log(array); * // => ['a', 'a', 'a'] * * _.fill(Array(3), 2); * // => [2, 2, 2] * * _.fill([4, 6, 8, 10], '*', 1, 3); * // => [4, '*', '*', 10] */ function fill(array, value, start, end) { var length = array == null ? 0 : array.length; if (!length) { return []; } if (start && typeof start != 'number' && isIterateeCall(array, value, start)) { start = 0; end = length; } return baseFill(array, value, start, end); } /** * This method is like `_.find` except that it returns the index of the first * element `predicate` returns truthy for instead of the element itself. * * @static * @memberOf _ * @since 1.1.0 * @category Array * @param {Array} array The array to inspect. * @param {Function} [predicate=_.identity] The function invoked per iteration. * @param {number} [fromIndex=0] The index to search from. * @returns {number} Returns the index of the found element, else `-1`. * @example * * var users = [ * { 'user': 'barney', 'active': false }, * { 'user': 'fred', 'active': false }, * { 'user': 'pebbles', 'active': true } * ]; * * _.findIndex(users, function(o) { return o.user == 'barney'; }); * // => 0 * * // The `_.matches` iteratee shorthand. * _.findIndex(users, { 'user': 'fred', 'active': false }); * // => 1 * * // The `_.matchesProperty` iteratee shorthand. * _.findIndex(users, ['active', false]); * // => 0 * * // The `_.property` iteratee shorthand. * _.findIndex(users, 'active'); * // => 2 */ function findIndex(array, predicate, fromIndex) { var length = array == null ? 0 : array.length; if (!length) { return -1; } var index = fromIndex == null ? 0 : toInteger(fromIndex); if (index < 0) { index = nativeMax(length + index, 0); } return baseFindIndex(array, getIteratee(predicate, 3), index); } /** * This method is like `_.findIndex` except that it iterates over elements * of `collection` from right to left. * * @static * @memberOf _ * @since 2.0.0 * @category Array * @param {Array} array The array to inspect. * @param {Function} [predicate=_.identity] The function invoked per iteration. * @param {number} [fromIndex=array.length-1] The index to search from. * @returns {number} Returns the index of the found element, else `-1`. * @example * * var users = [ * { 'user': 'barney', 'active': true }, * { 'user': 'fred', 'active': false }, * { 'user': 'pebbles', 'active': false } * ]; * * _.findLastIndex(users, function(o) { return o.user == 'pebbles'; }); * // => 2 * * // The `_.matches` iteratee shorthand. * _.findLastIndex(users, { 'user': 'barney', 'active': true }); * // => 0 * * // The `_.matchesProperty` iteratee shorthand. * _.findLastIndex(users, ['active', false]); * // => 2 * * // The `_.property` iteratee shorthand. * _.findLastIndex(users, 'active'); * // => 0 */ function findLastIndex(array, predicate, fromIndex) { var length = array == null ? 0 : array.length; if (!length) { return -1; } var index = length - 1; if (fromIndex !== undefined) { index = toInteger(fromIndex); index = fromIndex < 0 ? nativeMax(length + index, 0) : nativeMin(index, length - 1); } return baseFindIndex(array, getIteratee(predicate, 3), index, true); } /** * Flattens `array` a single level deep. * * @static * @memberOf _ * @since 0.1.0 * @category Array * @param {Array} array The array to flatten. * @returns {Array} Returns the new flattened array. * @example * * _.flatten([1, [2, [3, [4]], 5]]); * // => [1, 2, [3, [4]], 5] */ function flatten(array) { var length = array == null ? 0 : array.length; return length ? baseFlatten(array, 1) : []; } /** * Recursively flattens `array`. * * @static * @memberOf _ * @since 3.0.0 * @category Array * @param {Array} array The array to flatten. * @returns {Array} Returns the new flattened array. * @example * * _.flattenDeep([1, [2, [3, [4]], 5]]); * // => [1, 2, 3, 4, 5] */ function flattenDeep(array) { var length = array == null ? 0 : array.length; return length ? baseFlatten(array, INFINITY) : []; } /** * Recursively flatten `array` up to `depth` times. * * @static * @memberOf _ * @since 4.4.0 * @category Array * @param {Array} array The array to flatten. * @param {number} [depth=1] The maximum recursion depth. * @returns {Array} Returns the new flattened array. * @example * * var array = [1, [2, [3, [4]], 5]]; * * _.flattenDepth(array, 1); * // => [1, 2, [3, [4]], 5] * * _.flattenDepth(array, 2); * // => [1, 2, 3, [4], 5] */ function flattenDepth(array, depth) { var length = array == null ? 0 : array.length; if (!length) { return []; } depth = depth === undefined ? 1 : toInteger(depth); return baseFlatten(array, depth); } /** * The inverse of `_.toPairs`; this method returns an object composed * from key-value `pairs`. * * @static * @memberOf _ * @since 4.0.0 * @category Array * @param {Array} pairs The key-value pairs. * @returns {Object} Returns the new object. * @example * * _.fromPairs([['a', 1], ['b', 2]]); * // => { 'a': 1, 'b': 2 } */ function fromPairs(pairs) { var index = -1, length = pairs == null ? 0 : pairs.length, result = {}; while (++index < length) { var pair = pairs[index]; result[pair[0]] = pair[1]; } return result; } /** * Gets the first element of `array`. * * @static * @memberOf _ * @since 0.1.0 * @alias first * @category Array * @param {Array} array The array to query. * @returns {*} Returns the first element of `array`. * @example * * _.head([1, 2, 3]); * // => 1 * * _.head([]); * // => undefined */ function head(array) { return (array && array.length) ? array[0] : undefined; } /** * Gets the index at which the first occurrence of `value` is found in `array` * using [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) * for equality comparisons. If `fromIndex` is negative, it's used as the * offset from the end of `array`. * * @static * @memberOf _ * @since 0.1.0 * @category Array * @param {Array} array The array to inspect. * @param {*} value The value to search for. * @param {number} [fromIndex=0] The index to search from. * @returns {number} Returns the index of the matched value, else `-1`. * @example * * _.indexOf([1, 2, 1, 2], 2); * // => 1 * * // Search from the `fromIndex`. * _.indexOf([1, 2, 1, 2], 2, 2); * // => 3 */ function indexOf(array, value, fromIndex) { var length = array == null ? 0 : array.length; if (!length) { return -1; } var index = fromIndex == null ? 0 : toInteger(fromIndex); if (index < 0) { index = nativeMax(length + index, 0); } return baseIndexOf(array, value, index); } /** * Gets all but the last element of `array`. * * @static * @memberOf _ * @since 0.1.0 * @category Array * @param {Array} array The array to query. * @returns {Array} Returns the slice of `array`. * @example * * _.initial([1, 2, 3]); * // => [1, 2] */ function initial(array) { var length = array == null ? 0 : array.length; return length ? baseSlice(array, 0, -1) : []; } /** * Creates an array of unique values that are included in all given arrays * using [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) * for equality comparisons. The order and references of result values are * determined by the first array. * * @static * @memberOf _ * @since 0.1.0 * @category Array * @param {...Array} [arrays] The arrays to inspect. * @returns {Array} Returns the new array of intersecting values. * @example * * _.intersection([2, 1], [2, 3]); * // => [2] */ var intersection = baseRest(function(arrays) { var mapped = arrayMap(arrays, castArrayLikeObject); return (mapped.length && mapped[0] === arrays[0]) ? baseIntersection(mapped) : []; }); /** * This method is like `_.intersection` except that it accepts `iteratee` * which is invoked for each element of each `arrays` to generate the criterion * by which they're compared. The order and references of result values are * determined by the first array. The iteratee is invoked with one argument: * (value). * * @static * @memberOf _ * @since 4.0.0 * @category Array * @param {...Array} [arrays] The arrays to inspect. * @param {Function} [iteratee=_.identity] The iteratee invoked per element. * @returns {Array} Returns the new array of intersecting values. * @example * * _.intersectionBy([2.1, 1.2], [2.3, 3.4], Math.floor); * // => [2.1] * * // The `_.property` iteratee shorthand. * _.intersectionBy([{ 'x': 1 }], [{ 'x': 2 }, { 'x': 1 }], 'x'); * // => [{ 'x': 1 }] */ var intersectionBy = baseRest(function(arrays) { var iteratee = last(arrays), mapped = arrayMap(arrays, castArrayLikeObject); if (iteratee === last(mapped)) { iteratee = undefined; } else { mapped.pop(); } return (mapped.length && mapped[0] === arrays[0]) ? baseIntersection(mapped, getIteratee(iteratee, 2)) : []; }); /** * This method is like `_.intersection` except that it accepts `comparator` * which is invoked to compare elements of `arrays`. The order and references * of result values are determined by the first array. The comparator is * invoked with two arguments: (arrVal, othVal). * * @static * @memberOf _ * @since 4.0.0 * @category Array * @param {...Array} [arrays] The arrays to inspect. * @param {Function} [comparator] The comparator invoked per element. * @returns {Array} Returns the new array of intersecting values. * @example * * var objects = [{ 'x': 1, 'y': 2 }, { 'x': 2, 'y': 1 }]; * var others = [{ 'x': 1, 'y': 1 }, { 'x': 1, 'y': 2 }]; * * _.intersectionWith(objects, others, _.isEqual); * // => [{ 'x': 1, 'y': 2 }] */ var intersectionWith = baseRest(function(arrays) { var comparator = last(arrays), mapped = arrayMap(arrays, castArrayLikeObject); comparator = typeof comparator == 'function' ? comparator : undefined; if (comparator) { mapped.pop(); } return (mapped.length && mapped[0] === arrays[0]) ? baseIntersection(mapped, undefined, comparator) : []; }); /** * Converts all elements in `array` into a string separated by `separator`. * * @static * @memberOf _ * @since 4.0.0 * @category Array * @param {Array} array The array to convert. * @param {string} [separator=','] The element separator. * @returns {string} Returns the joined string. * @example * * _.join(['a', 'b', 'c'], '~'); * // => 'a~b~c' */ function join(array, separator) { return array == null ? '' : nativeJoin.call(array, separator); } /** * Gets the last element of `array`. * * @static * @memberOf _ * @since 0.1.0 * @category Array * @param {Array} array The array to query. * @returns {*} Returns the last element of `array`. * @example * * _.last([1, 2, 3]); * // => 3 */ function last(array) { var length = array == null ? 0 : array.length; return length ? array[length - 1] : undefined; } /** * This method is like `_.indexOf` except that it iterates over elements of * `array` from right to left. * * @static * @memberOf _ * @since 0.1.0 * @category Array * @param {Array} array The array to inspect. * @param {*} value The value to search for. * @param {number} [fromIndex=array.length-1] The index to search from. * @returns {number} Returns the index of the matched value, else `-1`. * @example * * _.lastIndexOf([1, 2, 1, 2], 2); * // => 3 * * // Search from the `fromIndex`. * _.lastIndexOf([1, 2, 1, 2], 2, 2); * // => 1 */ function lastIndexOf(array, value, fromIndex) { var length = array == null ? 0 : array.length; if (!length) { return -1; } var index = length; if (fromIndex !== undefined) { index = toInteger(fromIndex); index = index < 0 ? nativeMax(length + index, 0) : nativeMin(index, length - 1); } return value === value ? strictLastIndexOf(array, value, index) : baseFindIndex(array, baseIsNaN, index, true); } /** * Gets the element at index `n` of `array`. If `n` is negative, the nth * element from the end is returned. * * @static * @memberOf _ * @since 4.11.0 * @category Array * @param {Array} array The array to query. * @param {number} [n=0] The index of the element to return. * @returns {*} Returns the nth element of `array`. * @example * * var array = ['a', 'b', 'c', 'd']; * * _.nth(array, 1); * // => 'b' * * _.nth(array, -2); * // => 'c'; */ function nth(array, n) { return (array && array.length) ? baseNth(array, toInteger(n)) : undefined; } /** * Removes all given values from `array` using * [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) * for equality comparisons. * * **Note:** Unlike `_.without`, this method mutates `array`. Use `_.remove` * to remove elements from an array by predicate. * * @static * @memberOf _ * @since 2.0.0 * @category Array * @param {Array} array The array to modify. * @param {...*} [values] The values to remove. * @returns {Array} Returns `array`. * @example * * var array = ['a', 'b', 'c', 'a', 'b', 'c']; * * _.pull(array, 'a', 'c'); * console.log(array); * // => ['b', 'b'] */ var pull = baseRest(pullAll); /** * This method is like `_.pull` except that it accepts an array of values to remove. * * **Note:** Unlike `_.difference`, this method mutates `array`. * * @static * @memberOf _ * @since 4.0.0 * @category Array * @param {Array} array The array to modify. * @param {Array} values The values to remove. * @returns {Array} Returns `array`. * @example * * var array = ['a', 'b', 'c', 'a', 'b', 'c']; * * _.pullAll(array, ['a', 'c']); * console.log(array); * // => ['b', 'b'] */ function pullAll(array, values) { return (array && array.length && values && values.length) ? basePullAll(array, values) : array; } /** * This method is like `_.pullAll` except that it accepts `iteratee` which is * invoked for each element of `array` and `values` to generate the criterion * by which they're compared. The iteratee is invoked with one argument: (value). * * **Note:** Unlike `_.differenceBy`, this method mutates `array`. * * @static * @memberOf _ * @since 4.0.0 * @category Array * @param {Array} array The array to modify. * @param {Array} values The values to remove. * @param {Function} [iteratee=_.identity] The iteratee invoked per element. * @returns {Array} Returns `array`. * @example * * var array = [{ 'x': 1 }, { 'x': 2 }, { 'x': 3 }, { 'x': 1 }]; * * _.pullAllBy(array, [{ 'x': 1 }, { 'x': 3 }], 'x'); * console.log(array); * // => [{ 'x': 2 }] */ function pullAllBy(array, values, iteratee) { return (array && array.length && values && values.length) ? basePullAll(array, values, getIteratee(iteratee, 2)) : array; } /** * This method is like `_.pullAll` except that it accepts `comparator` which * is invoked to compare elements of `array` to `values`. The comparator is * invoked with two arguments: (arrVal, othVal). * * **Note:** Unlike `_.differenceWith`, this method mutates `array`. * * @static * @memberOf _ * @since 4.6.0 * @category Array * @param {Array} array The array to modify. * @param {Array} values The values to remove. * @param {Function} [comparator] The comparator invoked per element. * @returns {Array} Returns `array`. * @example * * var array = [{ 'x': 1, 'y': 2 }, { 'x': 3, 'y': 4 }, { 'x': 5, 'y': 6 }]; * * _.pullAllWith(array, [{ 'x': 3, 'y': 4 }], _.isEqual); * console.log(array); * // => [{ 'x': 1, 'y': 2 }, { 'x': 5, 'y': 6 }] */ function pullAllWith(array, values, comparator) { return (array && array.length && values && values.length) ? basePullAll(array, values, undefined, comparator) : array; } /** * Removes elements from `array` corresponding to `indexes` and returns an * array of removed elements. * * **Note:** Unlike `_.at`, this method mutates `array`. * * @static * @memberOf _ * @since 3.0.0 * @category Array * @param {Array} array The array to modify. * @param {...(number|number[])} [indexes] The indexes of elements to remove. * @returns {Array} Returns the new array of removed elements. * @example * * var array = ['a', 'b', 'c', 'd']; * var pulled = _.pullAt(array, [1, 3]); * * console.log(array); * // => ['a', 'c'] * * console.log(pulled); * // => ['b', 'd'] */ var pullAt = flatRest(function(array, indexes) { var length = array == null ? 0 : array.length, result = baseAt(array, indexes); basePullAt(array, arrayMap(indexes, function(index) { return isIndex(index, length) ? +index : index; }).sort(compareAscending)); return result; }); /** * Removes all elements from `array` that `predicate` returns truthy for * and returns an array of the removed elements. The predicate is invoked * with three arguments: (value, index, array). * * **Note:** Unlike `_.filter`, this method mutates `array`. Use `_.pull` * to pull elements from an array by value. * * @static * @memberOf _ * @since 2.0.0 * @category Array * @param {Array} array The array to modify. * @param {Function} [predicate=_.identity] The function invoked per iteration. * @returns {Array} Returns the new array of removed elements. * @example * * var array = [1, 2, 3, 4]; * var evens = _.remove(array, function(n) { * return n % 2 == 0; * }); * * console.log(array); * // => [1, 3] * * console.log(evens); * // => [2, 4] */ function remove(array, predicate) { var result = []; if (!(array && array.length)) { return result; } var index = -1, indexes = [], length = array.length; predicate = getIteratee(predicate, 3); while (++index < length) { var value = array[index]; if (predicate(value, index, array)) { result.push(value); indexes.push(index); } } basePullAt(array, indexes); return result; } /** * Reverses `array` so that the first element becomes the last, the second * element becomes the second to last, and so on. * * **Note:** This method mutates `array` and is based on * [`Array#reverse`](https://mdn.io/Array/reverse). * * @static * @memberOf _ * @since 4.0.0 * @category Array * @param {Array} array The array to modify. * @returns {Array} Returns `array`. * @example * * var array = [1, 2, 3]; * * _.reverse(array); * // => [3, 2, 1] * * console.log(array); * // => [3, 2, 1] */ function reverse(array) { return array == null ? array : nativeReverse.call(array); } /** * Creates a slice of `array` from `start` up to, but not including, `end`. * * **Note:** This method is used instead of * [`Array#slice`](https://mdn.io/Array/slice) to ensure dense arrays are * returned. * * @static * @memberOf _ * @since 3.0.0 * @category Array * @param {Array} array The array to slice. * @param {number} [start=0] The start position. * @param {number} [end=array.length] The end position. * @returns {Array} Returns the slice of `array`. */ function slice(array, start, end) { var length = array == null ? 0 : array.length; if (!length) { return []; } if (end && typeof end != 'number' && isIterateeCall(array, start, end)) { start = 0; end = length; } else { start = start == null ? 0 : toInteger(start); end = end === undefined ? length : toInteger(end); } return baseSlice(array, start, end); } /** * Uses a binary search to determine the lowest index at which `value` * should be inserted into `array` in order to maintain its sort order. * * @static * @memberOf _ * @since 0.1.0 * @category Array * @param {Array} array The sorted array to inspect. * @param {*} value The value to evaluate. * @returns {number} Returns the index at which `value` should be inserted * into `array`. * @example * * _.sortedIndex([30, 50], 40); * // => 1 */ function sortedIndex(array, value) { return baseSortedIndex(array, value); } /** * This method is like `_.sortedIndex` except that it accepts `iteratee` * which is invoked for `value` and each element of `array` to compute their * sort ranking. The iteratee is invoked with one argument: (value). * * @static * @memberOf _ * @since 4.0.0 * @category Array * @param {Array} array The sorted array to inspect. * @param {*} value The value to evaluate. * @param {Function} [iteratee=_.identity] The iteratee invoked per element. * @returns {number} Returns the index at which `value` should be inserted * into `array`. * @example * * var objects = [{ 'x': 4 }, { 'x': 5 }]; * * _.sortedIndexBy(objects, { 'x': 4 }, function(o) { return o.x; }); * // => 0 * * // The `_.property` iteratee shorthand. * _.sortedIndexBy(objects, { 'x': 4 }, 'x'); * // => 0 */ function sortedIndexBy(array, value, iteratee) { return baseSortedIndexBy(array, value, getIteratee(iteratee, 2)); } /** * This method is like `_.indexOf` except that it performs a binary * search on a sorted `array`. * * @static * @memberOf _ * @since 4.0.0 * @category Array * @param {Array} array The array to inspect. * @param {*} value The value to search for. * @returns {number} Returns the index of the matched value, else `-1`. * @example * * _.sortedIndexOf([4, 5, 5, 5, 6], 5); * // => 1 */ function sortedIndexOf(array, value) { var length = array == null ? 0 : array.length; if (length) { var index = baseSortedIndex(array, value); if (index < length && eq(array[index], value)) { return index; } } return -1; } /** * This method is like `_.sortedIndex` except that it returns the highest * index at which `value` should be inserted into `array` in order to * maintain its sort order. * * @static * @memberOf _ * @since 3.0.0 * @category Array * @param {Array} array The sorted array to inspect. * @param {*} value The value to evaluate. * @returns {number} Returns the index at which `value` should be inserted * into `array`. * @example * * _.sortedLastIndex([4, 5, 5, 5, 6], 5); * // => 4 */ function sortedLastIndex(array, value) { return baseSortedIndex(array, value, true); } /** * This method is like `_.sortedLastIndex` except that it accepts `iteratee` * which is invoked for `value` and each element of `array` to compute their * sort ranking. The iteratee is invoked with one argument: (value). * * @static * @memberOf _ * @since 4.0.0 * @category Array * @param {Array} array The sorted array to inspect. * @param {*} value The value to evaluate. * @param {Function} [iteratee=_.identity] The iteratee invoked per element. * @returns {number} Returns the index at which `value` should be inserted * into `array`. * @example * * var objects = [{ 'x': 4 }, { 'x': 5 }]; * * _.sortedLastIndexBy(objects, { 'x': 4 }, function(o) { return o.x; }); * // => 1 * * // The `_.property` iteratee shorthand. * _.sortedLastIndexBy(objects, { 'x': 4 }, 'x'); * // => 1 */ function sortedLastIndexBy(array, value, iteratee) { return baseSortedIndexBy(array, value, getIteratee(iteratee, 2), true); } /** * This method is like `_.lastIndexOf` except that it performs a binary * search on a sorted `array`. * * @static * @memberOf _ * @since 4.0.0 * @category Array * @param {Array} array The array to inspect. * @param {*} value The value to search for. * @returns {number} Returns the index of the matched value, else `-1`. * @example * * _.sortedLastIndexOf([4, 5, 5, 5, 6], 5); * // => 3 */ function sortedLastIndexOf(array, value) { var length = array == null ? 0 : array.length; if (length) { var index = baseSortedIndex(array, value, true) - 1; if (eq(array[index], value)) { return index; } } return -1; } /** * This method is like `_.uniq` except that it's designed and optimized * for sorted arrays. * * @static * @memberOf _ * @since 4.0.0 * @category Array * @param {Array} array The array to inspect. * @returns {Array} Returns the new duplicate free array. * @example * * _.sortedUniq([1, 1, 2]); * // => [1, 2] */ function sortedUniq(array) { return (array && array.length) ? baseSortedUniq(array) : []; } /** * This method is like `_.uniqBy` except that it's designed and optimized * for sorted arrays. * * @static * @memberOf _ * @since 4.0.0 * @category Array * @param {Array} array The array to inspect. * @param {Function} [iteratee] The iteratee invoked per element. * @returns {Array} Returns the new duplicate free array. * @example * * _.sortedUniqBy([1.1, 1.2, 2.3, 2.4], Math.floor); * // => [1.1, 2.3] */ function sortedUniqBy(array, iteratee) { return (array && array.length) ? baseSortedUniq(array, getIteratee(iteratee, 2)) : []; } /** * Gets all but the first element of `array`. * * @static * @memberOf _ * @since 4.0.0 * @category Array * @param {Array} array The array to query. * @returns {Array} Returns the slice of `array`. * @example * * _.tail([1, 2, 3]); * // => [2, 3] */ function tail(array) { var length = array == null ? 0 : array.length; return length ? baseSlice(array, 1, length) : []; } /** * Creates a slice of `array` with `n` elements taken from the beginning. * * @static * @memberOf _ * @since 0.1.0 * @category Array * @param {Array} array The array to query. * @param {number} [n=1] The number of elements to take. * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. * @returns {Array} Returns the slice of `array`. * @example * * _.take([1, 2, 3]); * // => [1] * * _.take([1, 2, 3], 2); * // => [1, 2] * * _.take([1, 2, 3], 5); * // => [1, 2, 3] * * _.take([1, 2, 3], 0); * // => [] */ function take(array, n, guard) { if (!(array && array.length)) { return []; } n = (guard || n === undefined) ? 1 : toInteger(n); return baseSlice(array, 0, n < 0 ? 0 : n); } /** * Creates a slice of `array` with `n` elements taken from the end. * * @static * @memberOf _ * @since 3.0.0 * @category Array * @param {Array} array The array to query. * @param {number} [n=1] The number of elements to take. * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. * @returns {Array} Returns the slice of `array`. * @example * * _.takeRight([1, 2, 3]); * // => [3] * * _.takeRight([1, 2, 3], 2); * // => [2, 3] * * _.takeRight([1, 2, 3], 5); * // => [1, 2, 3] * * _.takeRight([1, 2, 3], 0); * // => [] */ function takeRight(array, n, guard) { var length = array == null ? 0 : array.length; if (!length) { return []; } n = (guard || n === undefined) ? 1 : toInteger(n); n = length - n; return baseSlice(array, n < 0 ? 0 : n, length); } /** * Creates a slice of `array` with elements taken from the end. Elements are * taken until `predicate` returns falsey. The predicate is invoked with * three arguments: (value, index, array). * * @static * @memberOf _ * @since 3.0.0 * @category Array * @param {Array} array The array to query. * @param {Function} [predicate=_.identity] The function invoked per iteration. * @returns {Array} Returns the slice of `array`. * @example * * var users = [ * { 'user': 'barney', 'active': true }, * { 'user': 'fred', 'active': false }, * { 'user': 'pebbles', 'active': false } * ]; * * _.takeRightWhile(users, function(o) { return !o.active; }); * // => objects for ['fred', 'pebbles'] * * // The `_.matches` iteratee shorthand. * _.takeRightWhile(users, { 'user': 'pebbles', 'active': false }); * // => objects for ['pebbles'] * * // The `_.matchesProperty` iteratee shorthand. * _.takeRightWhile(users, ['active', false]); * // => objects for ['fred', 'pebbles'] * * // The `_.property` iteratee shorthand. * _.takeRightWhile(users, 'active'); * // => [] */ function takeRightWhile(array, predicate) { return (array && array.length) ? baseWhile(array, getIteratee(predicate, 3), false, true) : []; } /** * Creates a slice of `array` with elements taken from the beginning. Elements * are taken until `predicate` returns falsey. The predicate is invoked with * three arguments: (value, index, array). * * @static * @memberOf _ * @since 3.0.0 * @category Array * @param {Array} array The array to query. * @param {Function} [predicate=_.identity] The function invoked per iteration. * @returns {Array} Returns the slice of `array`. * @example * * var users = [ * { 'user': 'barney', 'active': false }, * { 'user': 'fred', 'active': false }, * { 'user': 'pebbles', 'active': true } * ]; * * _.takeWhile(users, function(o) { return !o.active; }); * // => objects for ['barney', 'fred'] * * // The `_.matches` iteratee shorthand. * _.takeWhile(users, { 'user': 'barney', 'active': false }); * // => objects for ['barney'] * * // The `_.matchesProperty` iteratee shorthand. * _.takeWhile(users, ['active', false]); * // => objects for ['barney', 'fred'] * * // The `_.property` iteratee shorthand. * _.takeWhile(users, 'active'); * // => [] */ function takeWhile(array, predicate) { return (array && array.length) ? baseWhile(array, getIteratee(predicate, 3)) : []; } /** * Creates an array of unique values, in order, from all given arrays using * [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) * for equality comparisons. * * @static * @memberOf _ * @since 0.1.0 * @category Array * @param {...Array} [arrays] The arrays to inspect. * @returns {Array} Returns the new array of combined values. * @example * * _.union([2], [1, 2]); * // => [2, 1] */ var union = baseRest(function(arrays) { return baseUniq(baseFlatten(arrays, 1, isArrayLikeObject, true)); }); /** * This method is like `_.union` except that it accepts `iteratee` which is * invoked for each element of each `arrays` to generate the criterion by * which uniqueness is computed. Result values are chosen from the first * array in which the value occurs. The iteratee is invoked with one argument: * (value). * * @static * @memberOf _ * @since 4.0.0 * @category Array * @param {...Array} [arrays] The arrays to inspect. * @param {Function} [iteratee=_.identity] The iteratee invoked per element. * @returns {Array} Returns the new array of combined values. * @example * * _.unionBy([2.1], [1.2, 2.3], Math.floor); * // => [2.1, 1.2] * * // The `_.property` iteratee shorthand. * _.unionBy([{ 'x': 1 }], [{ 'x': 2 }, { 'x': 1 }], 'x'); * // => [{ 'x': 1 }, { 'x': 2 }] */ var unionBy = baseRest(function(arrays) { var iteratee = last(arrays); if (isArrayLikeObject(iteratee)) { iteratee = undefined; } return baseUniq(baseFlatten(arrays, 1, isArrayLikeObject, true), getIteratee(iteratee, 2)); }); /** * This method is like `_.union` except that it accepts `comparator` which * is invoked to compare elements of `arrays`. Result values are chosen from * the first array in which the value occurs. The comparator is invoked * with two arguments: (arrVal, othVal). * * @static * @memberOf _ * @since 4.0.0 * @category Array * @param {...Array} [arrays] The arrays to inspect. * @param {Function} [comparator] The comparator invoked per element. * @returns {Array} Returns the new array of combined values. * @example * * var objects = [{ 'x': 1, 'y': 2 }, { 'x': 2, 'y': 1 }]; * var others = [{ 'x': 1, 'y': 1 }, { 'x': 1, 'y': 2 }]; * * _.unionWith(objects, others, _.isEqual); * // => [{ 'x': 1, 'y': 2 }, { 'x': 2, 'y': 1 }, { 'x': 1, 'y': 1 }] */ var unionWith = baseRest(function(arrays) { var comparator = last(arrays); comparator = typeof comparator == 'function' ? comparator : undefined; return baseUniq(baseFlatten(arrays, 1, isArrayLikeObject, true), undefined, comparator); }); /** * Creates a duplicate-free version of an array, using * [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) * for equality comparisons, in which only the first occurrence of each element * is kept. The order of result values is determined by the order they occur * in the array. * * @static * @memberOf _ * @since 0.1.0 * @category Array * @param {Array} array The array to inspect. * @returns {Array} Returns the new duplicate free array. * @example * * _.uniq([2, 1, 2]); * // => [2, 1] */ function uniq(array) { return (array && array.length) ? baseUniq(array) : []; } /** * This method is like `_.uniq` except that it accepts `iteratee` which is * invoked for each element in `array` to generate the criterion by which * uniqueness is computed. The order of result values is determined by the * order they occur in the array. The iteratee is invoked with one argument: * (value). * * @static * @memberOf _ * @since 4.0.0 * @category Array * @param {Array} array The array to inspect. * @param {Function} [iteratee=_.identity] The iteratee invoked per element. * @returns {Array} Returns the new duplicate free array. * @example * * _.uniqBy([2.1, 1.2, 2.3], Math.floor); * // => [2.1, 1.2] * * // The `_.property` iteratee shorthand. * _.uniqBy([{ 'x': 1 }, { 'x': 2 }, { 'x': 1 }], 'x'); * // => [{ 'x': 1 }, { 'x': 2 }] */ function uniqBy(array, iteratee) { return (array && array.length) ? baseUniq(array, getIteratee(iteratee, 2)) : []; } /** * This method is like `_.uniq` except that it accepts `comparator` which * is invoked to compare elements of `array`. The order of result values is * determined by the order they occur in the array.The comparator is invoked * with two arguments: (arrVal, othVal). * * @static * @memberOf _ * @since 4.0.0 * @category Array * @param {Array} array The array to inspect. * @param {Function} [comparator] The comparator invoked per element. * @returns {Array} Returns the new duplicate free array. * @example * * var objects = [{ 'x': 1, 'y': 2 }, { 'x': 2, 'y': 1 }, { 'x': 1, 'y': 2 }]; * * _.uniqWith(objects, _.isEqual); * // => [{ 'x': 1, 'y': 2 }, { 'x': 2, 'y': 1 }] */ function uniqWith(array, comparator) { comparator = typeof comparator == 'function' ? comparator : undefined; return (array && array.length) ? baseUniq(array, undefined, comparator) : []; } /** * This method is like `_.zip` except that it accepts an array of grouped * elements and creates an array regrouping the elements to their pre-zip * configuration. * * @static * @memberOf _ * @since 1.2.0 * @category Array * @param {Array} array The array of grouped elements to process. * @returns {Array} Returns the new array of regrouped elements. * @example * * var zipped = _.zip(['a', 'b'], [1, 2], [true, false]); * // => [['a', 1, true], ['b', 2, false]] * * _.unzip(zipped); * // => [['a', 'b'], [1, 2], [true, false]] */ function unzip(array) { if (!(array && array.length)) { return []; } var length = 0; array = arrayFilter(array, function(group) { if (isArrayLikeObject(group)) { length = nativeMax(group.length, length); return true; } }); return baseTimes(length, function(index) { return arrayMap(array, baseProperty(index)); }); } /** * This method is like `_.unzip` except that it accepts `iteratee` to specify * how regrouped values should be combined. The iteratee is invoked with the * elements of each group: (...group). * * @static * @memberOf _ * @since 3.8.0 * @category Array * @param {Array} array The array of grouped elements to process. * @param {Function} [iteratee=_.identity] The function to combine * regrouped values. * @returns {Array} Returns the new array of regrouped elements. * @example * * var zipped = _.zip([1, 2], [10, 20], [100, 200]); * // => [[1, 10, 100], [2, 20, 200]] * * _.unzipWith(zipped, _.add); * // => [3, 30, 300] */ function unzipWith(array, iteratee) { if (!(array && array.length)) { return []; } var result = unzip(array); if (iteratee == null) { return result; } return arrayMap(result, function(group) { return apply(iteratee, undefined, group); }); } /** * Creates an array excluding all given values using * [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) * for equality comparisons. * * **Note:** Unlike `_.pull`, this method returns a new array. * * @static * @memberOf _ * @since 0.1.0 * @category Array * @param {Array} array The array to inspect. * @param {...*} [values] The values to exclude. * @returns {Array} Returns the new array of filtered values. * @see _.difference, _.xor * @example * * _.without([2, 1, 2, 3], 1, 2); * // => [3] */ var without = baseRest(function(array, values) { return isArrayLikeObject(array) ? baseDifference(array, values) : []; }); /** * Creates an array of unique values that is the * [symmetric difference](https://en.wikipedia.org/wiki/Symmetric_difference) * of the given arrays. The order of result values is determined by the order * they occur in the arrays. * * @static * @memberOf _ * @since 2.4.0 * @category Array * @param {...Array} [arrays] The arrays to inspect. * @returns {Array} Returns the new array of filtered values. * @see _.difference, _.without * @example * * _.xor([2, 1], [2, 3]); * // => [1, 3] */ var xor = baseRest(function(arrays) { return baseXor(arrayFilter(arrays, isArrayLikeObject)); }); /** * This method is like `_.xor` except that it accepts `iteratee` which is * invoked for each element of each `arrays` to generate the criterion by * which by which they're compared. The order of result values is determined * by the order they occur in the arrays. The iteratee is invoked with one * argument: (value). * * @static * @memberOf _ * @since 4.0.0 * @category Array * @param {...Array} [arrays] The arrays to inspect. * @param {Function} [iteratee=_.identity] The iteratee invoked per element. * @returns {Array} Returns the new array of filtered values. * @example * * _.xorBy([2.1, 1.2], [2.3, 3.4], Math.floor); * // => [1.2, 3.4] * * // The `_.property` iteratee shorthand. * _.xorBy([{ 'x': 1 }], [{ 'x': 2 }, { 'x': 1 }], 'x'); * // => [{ 'x': 2 }] */ var xorBy = baseRest(function(arrays) { var iteratee = last(arrays); if (isArrayLikeObject(iteratee)) { iteratee = undefined; } return baseXor(arrayFilter(arrays, isArrayLikeObject), getIteratee(iteratee, 2)); }); /** * This method is like `_.xor` except that it accepts `comparator` which is * invoked to compare elements of `arrays`. The order of result values is * determined by the order they occur in the arrays. The comparator is invoked * with two arguments: (arrVal, othVal). * * @static * @memberOf _ * @since 4.0.0 * @category Array * @param {...Array} [arrays] The arrays to inspect. * @param {Function} [comparator] The comparator invoked per element. * @returns {Array} Returns the new array of filtered values. * @example * * var objects = [{ 'x': 1, 'y': 2 }, { 'x': 2, 'y': 1 }]; * var others = [{ 'x': 1, 'y': 1 }, { 'x': 1, 'y': 2 }]; * * _.xorWith(objects, others, _.isEqual); * // => [{ 'x': 2, 'y': 1 }, { 'x': 1, 'y': 1 }] */ var xorWith = baseRest(function(arrays) { var comparator = last(arrays); comparator = typeof comparator == 'function' ? comparator : undefined; return baseXor(arrayFilter(arrays, isArrayLikeObject), undefined, comparator); }); /** * Creates an array of grouped elements, the first of which contains the * first elements of the given arrays, the second of which contains the * second elements of the given arrays, and so on. * * @static * @memberOf _ * @since 0.1.0 * @category Array * @param {...Array} [arrays] The arrays to process. * @returns {Array} Returns the new array of grouped elements. * @example * * _.zip(['a', 'b'], [1, 2], [true, false]); * // => [['a', 1, true], ['b', 2, false]] */ var zip = baseRest(unzip); /** * This method is like `_.fromPairs` except that it accepts two arrays, * one of property identifiers and one of corresponding values. * * @static * @memberOf _ * @since 0.4.0 * @category Array * @param {Array} [props=[]] The property identifiers. * @param {Array} [values=[]] The property values. * @returns {Object} Returns the new object. * @example * * _.zipObject(['a', 'b'], [1, 2]); * // => { 'a': 1, 'b': 2 } */ function zipObject(props, values) { return baseZipObject(props || [], values || [], assignValue); } /** * This method is like `_.zipObject` except that it supports property paths. * * @static * @memberOf _ * @since 4.1.0 * @category Array * @param {Array} [props=[]] The property identifiers. * @param {Array} [values=[]] The property values. * @returns {Object} Returns the new object. * @example * * _.zipObjectDeep(['a.b[0].c', 'a.b[1].d'], [1, 2]); * // => { 'a': { 'b': [{ 'c': 1 }, { 'd': 2 }] } } */ function zipObjectDeep(props, values) { return baseZipObject(props || [], values || [], baseSet); } /** * This method is like `_.zip` except that it accepts `iteratee` to specify * how grouped values should be combined. The iteratee is invoked with the * elements of each group: (...group). * * @static * @memberOf _ * @since 3.8.0 * @category Array * @param {...Array} [arrays] The arrays to process. * @param {Function} [iteratee=_.identity] The function to combine * grouped values. * @returns {Array} Returns the new array of grouped elements. * @example * * _.zipWith([1, 2], [10, 20], [100, 200], function(a, b, c) { * return a + b + c; * }); * // => [111, 222] */ var zipWith = baseRest(function(arrays) { var length = arrays.length, iteratee = length > 1 ? arrays[length - 1] : undefined; iteratee = typeof iteratee == 'function' ? (arrays.pop(), iteratee) : undefined; return unzipWith(arrays, iteratee); }); /*------------------------------------------------------------------------*/ /** * Creates a `lodash` wrapper instance that wraps `value` with explicit method * chain sequences enabled. The result of such sequences must be unwrapped * with `_#value`. * * @static * @memberOf _ * @since 1.3.0 * @category Seq * @param {*} value The value to wrap. * @returns {Object} Returns the new `lodash` wrapper instance. * @example * * var users = [ * { 'user': 'barney', 'age': 36 }, * { 'user': 'fred', 'age': 40 }, * { 'user': 'pebbles', 'age': 1 } * ]; * * var youngest = _ * .chain(users) * .sortBy('age') * .map(function(o) { * return o.user + ' is ' + o.age; * }) * .head() * .value(); * // => 'pebbles is 1' */ function chain(value) { var result = lodash(value); result.__chain__ = true; return result; } /** * This method invokes `interceptor` and returns `value`. The interceptor * is invoked with one argument; (value). The purpose of this method is to * "tap into" a method chain sequence in order to modify intermediate results. * * @static * @memberOf _ * @since 0.1.0 * @category Seq * @param {*} value The value to provide to `interceptor`. * @param {Function} interceptor The function to invoke. * @returns {*} Returns `value`. * @example * * _([1, 2, 3]) * .tap(function(array) { * // Mutate input array. * array.pop(); * }) * .reverse() * .value(); * // => [2, 1] */ function tap(value, interceptor) { interceptor(value); return value; } /** * This method is like `_.tap` except that it returns the result of `interceptor`. * The purpose of this method is to "pass thru" values replacing intermediate * results in a method chain sequence. * * @static * @memberOf _ * @since 3.0.0 * @category Seq * @param {*} value The value to provide to `interceptor`. * @param {Function} interceptor The function to invoke. * @returns {*} Returns the result of `interceptor`. * @example * * _(' abc ') * .chain() * .trim() * .thru(function(value) { * return [value]; * }) * .value(); * // => ['abc'] */ function thru(value, interceptor) { return interceptor(value); } /** * This method is the wrapper version of `_.at`. * * @name at * @memberOf _ * @since 1.0.0 * @category Seq * @param {...(string|string[])} [paths] The property paths to pick. * @returns {Object} Returns the new `lodash` wrapper instance. * @example * * var object = { 'a': [{ 'b': { 'c': 3 } }, 4] }; * * _(object).at(['a[0].b.c', 'a[1]']).value(); * // => [3, 4] */ var wrapperAt = flatRest(function(paths) { var length = paths.length, start = length ? paths[0] : 0, value = this.__wrapped__, interceptor = function(object) { return baseAt(object, paths); }; if (length > 1 || this.__actions__.length || !(value instanceof LazyWrapper) || !isIndex(start)) { return this.thru(interceptor); } value = value.slice(start, +start + (length ? 1 : 0)); value.__actions__.push({ 'func': thru, 'args': [interceptor], 'thisArg': undefined }); return new LodashWrapper(value, this.__chain__).thru(function(array) { if (length && !array.length) { array.push(undefined); } return array; }); }); /** * Creates a `lodash` wrapper instance with explicit method chain sequences enabled. * * @name chain * @memberOf _ * @since 0.1.0 * @category Seq * @returns {Object} Returns the new `lodash` wrapper instance. * @example * * var users = [ * { 'user': 'barney', 'age': 36 }, * { 'user': 'fred', 'age': 40 } * ]; * * // A sequence without explicit chaining. * _(users).head(); * // => { 'user': 'barney', 'age': 36 } * * // A sequence with explicit chaining. * _(users) * .chain() * .head() * .pick('user') * .value(); * // => { 'user': 'barney' } */ function wrapperChain() { return chain(this); } /** * Executes the chain sequence and returns the wrapped result. * * @name commit * @memberOf _ * @since 3.2.0 * @category Seq * @returns {Object} Returns the new `lodash` wrapper instance. * @example * * var array = [1, 2]; * var wrapped = _(array).push(3); * * console.log(array); * // => [1, 2] * * wrapped = wrapped.commit(); * console.log(array); * // => [1, 2, 3] * * wrapped.last(); * // => 3 * * console.log(array); * // => [1, 2, 3] */ function wrapperCommit() { return new LodashWrapper(this.value(), this.__chain__); } /** * Gets the next value on a wrapped object following the * [iterator protocol](https://mdn.io/iteration_protocols#iterator). * * @name next * @memberOf _ * @since 4.0.0 * @category Seq * @returns {Object} Returns the next iterator value. * @example * * var wrapped = _([1, 2]); * * wrapped.next(); * // => { 'done': false, 'value': 1 } * * wrapped.next(); * // => { 'done': false, 'value': 2 } * * wrapped.next(); * // => { 'done': true, 'value': undefined } */ function wrapperNext() { if (this.__values__ === undefined) { this.__values__ = toArray(this.value()); } var done = this.__index__ >= this.__values__.length, value = done ? undefined : this.__values__[this.__index__++]; return { 'done': done, 'value': value }; } /** * Enables the wrapper to be iterable. * * @name Symbol.iterator * @memberOf _ * @since 4.0.0 * @category Seq * @returns {Object} Returns the wrapper object. * @example * * var wrapped = _([1, 2]); * * wrapped[Symbol.iterator]() === wrapped; * // => true * * Array.from(wrapped); * // => [1, 2] */ function wrapperToIterator() { return this; } /** * Creates a clone of the chain sequence planting `value` as the wrapped value. * * @name plant * @memberOf _ * @since 3.2.0 * @category Seq * @param {*} value The value to plant. * @returns {Object} Returns the new `lodash` wrapper instance. * @example * * function square(n) { * return n * n; * } * * var wrapped = _([1, 2]).map(square); * var other = wrapped.plant([3, 4]); * * other.value(); * // => [9, 16] * * wrapped.value(); * // => [1, 4] */ function wrapperPlant(value) { var result, parent = this; while (parent instanceof baseLodash) { var clone = wrapperClone(parent); clone.__index__ = 0; clone.__values__ = undefined; if (result) { previous.__wrapped__ = clone; } else { result = clone; } var previous = clone; parent = parent.__wrapped__; } previous.__wrapped__ = value; return result; } /** * This method is the wrapper version of `_.reverse`. * * **Note:** This method mutates the wrapped array. * * @name reverse * @memberOf _ * @since 0.1.0 * @category Seq * @returns {Object} Returns the new `lodash` wrapper instance. * @example * * var array = [1, 2, 3]; * * _(array).reverse().value() * // => [3, 2, 1] * * console.log(array); * // => [3, 2, 1] */ function wrapperReverse() { var value = this.__wrapped__; if (value instanceof LazyWrapper) { var wrapped = value; if (this.__actions__.length) { wrapped = new LazyWrapper(this); } wrapped = wrapped.reverse(); wrapped.__actions__.push({ 'func': thru, 'args': [reverse], 'thisArg': undefined }); return new LodashWrapper(wrapped, this.__chain__); } return this.thru(reverse); } /** * Executes the chain sequence to resolve the unwrapped value. * * @name value * @memberOf _ * @since 0.1.0 * @alias toJSON, valueOf * @category Seq * @returns {*} Returns the resolved unwrapped value. * @example * * _([1, 2, 3]).value(); * // => [1, 2, 3] */ function wrapperValue() { return baseWrapperValue(this.__wrapped__, this.__actions__); } /*------------------------------------------------------------------------*/ /** * Creates an object composed of keys generated from the results of running * each element of `collection` thru `iteratee`. The corresponding value of * each key is the number of times the key was returned by `iteratee`. The * iteratee is invoked with one argument: (value). * * @static * @memberOf _ * @since 0.5.0 * @category Collection * @param {Array|Object} collection The collection to iterate over. * @param {Function} [iteratee=_.identity] The iteratee to transform keys. * @returns {Object} Returns the composed aggregate object. * @example * * _.countBy([6.1, 4.2, 6.3], Math.floor); * // => { '4': 1, '6': 2 } * * // The `_.property` iteratee shorthand. * _.countBy(['one', 'two', 'three'], 'length'); * // => { '3': 2, '5': 1 } */ var countBy = createAggregator(function(result, value, key) { if (hasOwnProperty.call(result, key)) { ++result[key]; } else { baseAssignValue(result, key, 1); } }); /** * Checks if `predicate` returns truthy for **all** elements of `collection`. * Iteration is stopped once `predicate` returns falsey. The predicate is * invoked with three arguments: (value, index|key, collection). * * **Note:** This method returns `true` for * [empty collections](https://en.wikipedia.org/wiki/Empty_set) because * [everything is true](https://en.wikipedia.org/wiki/Vacuous_truth) of * elements of empty collections. * * @static * @memberOf _ * @since 0.1.0 * @category Collection * @param {Array|Object} collection The collection to iterate over. * @param {Function} [predicate=_.identity] The function invoked per iteration. * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. * @returns {boolean} Returns `true` if all elements pass the predicate check, * else `false`. * @example * * _.every([true, 1, null, 'yes'], Boolean); * // => false * * var users = [ * { 'user': 'barney', 'age': 36, 'active': false }, * { 'user': 'fred', 'age': 40, 'active': false } * ]; * * // The `_.matches` iteratee shorthand. * _.every(users, { 'user': 'barney', 'active': false }); * // => false * * // The `_.matchesProperty` iteratee shorthand. * _.every(users, ['active', false]); * // => true * * // The `_.property` iteratee shorthand. * _.every(users, 'active'); * // => false */ function every(collection, predicate, guard) { var func = isArray(collection) ? arrayEvery : baseEvery; if (guard && isIterateeCall(collection, predicate, guard)) { predicate = undefined; } return func(collection, getIteratee(predicate, 3)); } /** * Iterates over elements of `collection`, returning an array of all elements * `predicate` returns truthy for. The predicate is invoked with three * arguments: (value, index|key, collection). * * **Note:** Unlike `_.remove`, this method returns a new array. * * @static * @memberOf _ * @since 0.1.0 * @category Collection * @param {Array|Object} collection The collection to iterate over. * @param {Function} [predicate=_.identity] The function invoked per iteration. * @returns {Array} Returns the new filtered array. * @see _.reject * @example * * var users = [ * { 'user': 'barney', 'age': 36, 'active': true }, * { 'user': 'fred', 'age': 40, 'active': false } * ]; * * _.filter(users, function(o) { return !o.active; }); * // => objects for ['fred'] * * // The `_.matches` iteratee shorthand. * _.filter(users, { 'age': 36, 'active': true }); * // => objects for ['barney'] * * // The `_.matchesProperty` iteratee shorthand. * _.filter(users, ['active', false]); * // => objects for ['fred'] * * // The `_.property` iteratee shorthand. * _.filter(users, 'active'); * // => objects for ['barney'] */ function filter(collection, predicate) { var func = isArray(collection) ? arrayFilter : baseFilter; return func(collection, getIteratee(predicate, 3)); } /** * Iterates over elements of `collection`, returning the first element * `predicate` returns truthy for. The predicate is invoked with three * arguments: (value, index|key, collection). * * @static * @memberOf _ * @since 0.1.0 * @category Collection * @param {Array|Object} collection The collection to inspect. * @param {Function} [predicate=_.identity] The function invoked per iteration. * @param {number} [fromIndex=0] The index to search from. * @returns {*} Returns the matched element, else `undefined`. * @example * * var users = [ * { 'user': 'barney', 'age': 36, 'active': true }, * { 'user': 'fred', 'age': 40, 'active': false }, * { 'user': 'pebbles', 'age': 1, 'active': true } * ]; * * _.find(users, function(o) { return o.age < 40; }); * // => object for 'barney' * * // The `_.matches` iteratee shorthand. * _.find(users, { 'age': 1, 'active': true }); * // => object for 'pebbles' * * // The `_.matchesProperty` iteratee shorthand. * _.find(users, ['active', false]); * // => object for 'fred' * * // The `_.property` iteratee shorthand. * _.find(users, 'active'); * // => object for 'barney' */ var find = createFind(findIndex); /** * This method is like `_.find` except that it iterates over elements of * `collection` from right to left. * * @static * @memberOf _ * @since 2.0.0 * @category Collection * @param {Array|Object} collection The collection to inspect. * @param {Function} [predicate=_.identity] The function invoked per iteration. * @param {number} [fromIndex=collection.length-1] The index to search from. * @returns {*} Returns the matched element, else `undefined`. * @example * * _.findLast([1, 2, 3, 4], function(n) { * return n % 2 == 1; * }); * // => 3 */ var findLast = createFind(findLastIndex); /** * Creates a flattened array of values by running each element in `collection` * thru `iteratee` and flattening the mapped results. The iteratee is invoked * with three arguments: (value, index|key, collection). * * @static * @memberOf _ * @since 4.0.0 * @category Collection * @param {Array|Object} collection The collection to iterate over. * @param {Function} [iteratee=_.identity] The function invoked per iteration. * @returns {Array} Returns the new flattened array. * @example * * function duplicate(n) { * return [n, n]; * } * * _.flatMap([1, 2], duplicate); * // => [1, 1, 2, 2] */ function flatMap(collection, iteratee) { return baseFlatten(map(collection, iteratee), 1); } /** * This method is like `_.flatMap` except that it recursively flattens the * mapped results. * * @static * @memberOf _ * @since 4.7.0 * @category Collection * @param {Array|Object} collection The collection to iterate over. * @param {Function} [iteratee=_.identity] The function invoked per iteration. * @returns {Array} Returns the new flattened array. * @example * * function duplicate(n) { * return [[[n, n]]]; * } * * _.flatMapDeep([1, 2], duplicate); * // => [1, 1, 2, 2] */ function flatMapDeep(collection, iteratee) { return baseFlatten(map(collection, iteratee), INFINITY); } /** * This method is like `_.flatMap` except that it recursively flattens the * mapped results up to `depth` times. * * @static * @memberOf _ * @since 4.7.0 * @category Collection * @param {Array|Object} collection The collection to iterate over. * @param {Function} [iteratee=_.identity] The function invoked per iteration. * @param {number} [depth=1] The maximum recursion depth. * @returns {Array} Returns the new flattened array. * @example * * function duplicate(n) { * return [[[n, n]]]; * } * * _.flatMapDepth([1, 2], duplicate, 2); * // => [[1, 1], [2, 2]] */ function flatMapDepth(collection, iteratee, depth) { depth = depth === undefined ? 1 : toInteger(depth); return baseFlatten(map(collection, iteratee), depth); } /** * Iterates over elements of `collection` and invokes `iteratee` for each element. * The iteratee is invoked with three arguments: (value, index|key, collection). * Iteratee functions may exit iteration early by explicitly returning `false`. * * **Note:** As with other "Collections" methods, objects with a "length" * property are iterated like arrays. To avoid this behavior use `_.forIn` * or `_.forOwn` for object iteration. * * @static * @memberOf _ * @since 0.1.0 * @alias each * @category Collection * @param {Array|Object} collection The collection to iterate over. * @param {Function} [iteratee=_.identity] The function invoked per iteration. * @returns {Array|Object} Returns `collection`. * @see _.forEachRight * @example * * _.forEach([1, 2], function(value) { * console.log(value); * }); * // => Logs `1` then `2`. * * _.forEach({ 'a': 1, 'b': 2 }, function(value, key) { * console.log(key); * }); * // => Logs 'a' then 'b' (iteration order is not guaranteed). */ function forEach(collection, iteratee) { var func = isArray(collection) ? arrayEach : baseEach; return func(collection, getIteratee(iteratee, 3)); } /** * This method is like `_.forEach` except that it iterates over elements of * `collection` from right to left. * * @static * @memberOf _ * @since 2.0.0 * @alias eachRight * @category Collection * @param {Array|Object} collection The collection to iterate over. * @param {Function} [iteratee=_.identity] The function invoked per iteration. * @returns {Array|Object} Returns `collection`. * @see _.forEach * @example * * _.forEachRight([1, 2], function(value) { * console.log(value); * }); * // => Logs `2` then `1`. */ function forEachRight(collection, iteratee) { var func = isArray(collection) ? arrayEachRight : baseEachRight; return func(collection, getIteratee(iteratee, 3)); } /** * Creates an object composed of keys generated from the results of running * each element of `collection` thru `iteratee`. The order of grouped values * is determined by the order they occur in `collection`. The corresponding * value of each key is an array of elements responsible for generating the * key. The iteratee is invoked with one argument: (value). * * @static * @memberOf _ * @since 0.1.0 * @category Collection * @param {Array|Object} collection The collection to iterate over. * @param {Function} [iteratee=_.identity] The iteratee to transform keys. * @returns {Object} Returns the composed aggregate object. * @example * * _.groupBy([6.1, 4.2, 6.3], Math.floor); * // => { '4': [4.2], '6': [6.1, 6.3] } * * // The `_.property` iteratee shorthand. * _.groupBy(['one', 'two', 'three'], 'length'); * // => { '3': ['one', 'two'], '5': ['three'] } */ var groupBy = createAggregator(function(result, value, key) { if (hasOwnProperty.call(result, key)) { result[key].push(value); } else { baseAssignValue(result, key, [value]); } }); /** * Checks if `value` is in `collection`. If `collection` is a string, it's * checked for a substring of `value`, otherwise * [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) * is used for equality comparisons. If `fromIndex` is negative, it's used as * the offset from the end of `collection`. * * @static * @memberOf _ * @since 0.1.0 * @category Collection * @param {Array|Object|string} collection The collection to inspect. * @param {*} value The value to search for. * @param {number} [fromIndex=0] The index to search from. * @param- {Object} [guard] Enables use as an iteratee for methods like `_.reduce`. * @returns {boolean} Returns `true` if `value` is found, else `false`. * @example * * _.includes([1, 2, 3], 1); * // => true * * _.includes([1, 2, 3], 1, 2); * // => false * * _.includes({ 'a': 1, 'b': 2 }, 1); * // => true * * _.includes('abcd', 'bc'); * // => true */ function includes(collection, value, fromIndex, guard) { collection = isArrayLike(collection) ? collection : values(collection); fromIndex = (fromIndex && !guard) ? toInteger(fromIndex) : 0; var length = collection.length; if (fromIndex < 0) { fromIndex = nativeMax(length + fromIndex, 0); } return isString(collection) ? (fromIndex <= length && collection.indexOf(value, fromIndex) > -1) : (!!length && baseIndexOf(collection, value, fromIndex) > -1); } /** * Invokes the method at `path` of each element in `collection`, returning * an array of the results of each invoked method. Any additional arguments * are provided to each invoked method. If `path` is a function, it's invoked * for, and `this` bound to, each element in `collection`. * * @static * @memberOf _ * @since 4.0.0 * @category Collection * @param {Array|Object} collection The collection to iterate over. * @param {Array|Function|string} path The path of the method to invoke or * the function invoked per iteration. * @param {...*} [args] The arguments to invoke each method with. * @returns {Array} Returns the array of results. * @example * * _.invokeMap([[5, 1, 7], [3, 2, 1]], 'sort'); * // => [[1, 5, 7], [1, 2, 3]] * * _.invokeMap([123, 456], String.prototype.split, ''); * // => [['1', '2', '3'], ['4', '5', '6']] */ var invokeMap = baseRest(function(collection, path, args) { var index = -1, isFunc = typeof path == 'function', result = isArrayLike(collection) ? Array(collection.length) : []; baseEach(collection, function(value) { result[++index] = isFunc ? apply(path, value, args) : baseInvoke(value, path, args); }); return result; }); /** * Creates an object composed of keys generated from the results of running * each element of `collection` thru `iteratee`. The corresponding value of * each key is the last element responsible for generating the key. The * iteratee is invoked with one argument: (value). * * @static * @memberOf _ * @since 4.0.0 * @category Collection * @param {Array|Object} collection The collection to iterate over. * @param {Function} [iteratee=_.identity] The iteratee to transform keys. * @returns {Object} Returns the composed aggregate object. * @example * * var array = [ * { 'dir': 'left', 'code': 97 }, * { 'dir': 'right', 'code': 100 } * ]; * * _.keyBy(array, function(o) { * return String.fromCharCode(o.code); * }); * // => { 'a': { 'dir': 'left', 'code': 97 }, 'd': { 'dir': 'right', 'code': 100 } } * * _.keyBy(array, 'dir'); * // => { 'left': { 'dir': 'left', 'code': 97 }, 'right': { 'dir': 'right', 'code': 100 } } */ var keyBy = createAggregator(function(result, value, key) { baseAssignValue(result, key, value); }); /** * Creates an array of values by running each element in `collection` thru * `iteratee`. The iteratee is invoked with three arguments: * (value, index|key, collection). * * Many lodash methods are guarded to work as iteratees for methods like * `_.every`, `_.filter`, `_.map`, `_.mapValues`, `_.reject`, and `_.some`. * * The guarded methods are: * `ary`, `chunk`, `curry`, `curryRight`, `drop`, `dropRight`, `every`, * `fill`, `invert`, `parseInt`, `random`, `range`, `rangeRight`, `repeat`, * `sampleSize`, `slice`, `some`, `sortBy`, `split`, `take`, `takeRight`, * `template`, `trim`, `trimEnd`, `trimStart`, and `words` * * @static * @memberOf _ * @since 0.1.0 * @category Collection * @param {Array|Object} collection The collection to iterate over. * @param {Function} [iteratee=_.identity] The function invoked per iteration. * @returns {Array} Returns the new mapped array. * @example * * function square(n) { * return n * n; * } * * _.map([4, 8], square); * // => [16, 64] * * _.map({ 'a': 4, 'b': 8 }, square); * // => [16, 64] (iteration order is not guaranteed) * * var users = [ * { 'user': 'barney' }, * { 'user': 'fred' } * ]; * * // The `_.property` iteratee shorthand. * _.map(users, 'user'); * // => ['barney', 'fred'] */ function map(collection, iteratee) { var func = isArray(collection) ? arrayMap : baseMap; return func(collection, getIteratee(iteratee, 3)); } /** * This method is like `_.sortBy` except that it allows specifying the sort * orders of the iteratees to sort by. If `orders` is unspecified, all values * are sorted in ascending order. Otherwise, specify an order of "desc" for * descending or "asc" for ascending sort order of corresponding values. * * @static * @memberOf _ * @since 4.0.0 * @category Collection * @param {Array|Object} collection The collection to iterate over. * @param {Array[]|Function[]|Object[]|string[]} [iteratees=[_.identity]] * The iteratees to sort by. * @param {string[]} [orders] The sort orders of `iteratees`. * @param- {Object} [guard] Enables use as an iteratee for methods like `_.reduce`. * @returns {Array} Returns the new sorted array. * @example * * var users = [ * { 'user': 'fred', 'age': 48 }, * { 'user': 'barney', 'age': 34 }, * { 'user': 'fred', 'age': 40 }, * { 'user': 'barney', 'age': 36 } * ]; * * // Sort by `user` in ascending order and by `age` in descending order. * _.orderBy(users, ['user', 'age'], ['asc', 'desc']); * // => objects for [['barney', 36], ['barney', 34], ['fred', 48], ['fred', 40]] */ function orderBy(collection, iteratees, orders, guard) { if (collection == null) { return []; } if (!isArray(iteratees)) { iteratees = iteratees == null ? [] : [iteratees]; } orders = guard ? undefined : orders; if (!isArray(orders)) { orders = orders == null ? [] : [orders]; } return baseOrderBy(collection, iteratees, orders); } /** * Creates an array of elements split into two groups, the first of which * contains elements `predicate` returns truthy for, the second of which * contains elements `predicate` returns falsey for. The predicate is * invoked with one argument: (value). * * @static * @memberOf _ * @since 3.0.0 * @category Collection * @param {Array|Object} collection The collection to iterate over. * @param {Function} [predicate=_.identity] The function invoked per iteration. * @returns {Array} Returns the array of grouped elements. * @example * * var users = [ * { 'user': 'barney', 'age': 36, 'active': false }, * { 'user': 'fred', 'age': 40, 'active': true }, * { 'user': 'pebbles', 'age': 1, 'active': false } * ]; * * _.partition(users, function(o) { return o.active; }); * // => objects for [['fred'], ['barney', 'pebbles']] * * // The `_.matches` iteratee shorthand. * _.partition(users, { 'age': 1, 'active': false }); * // => objects for [['pebbles'], ['barney', 'fred']] * * // The `_.matchesProperty` iteratee shorthand. * _.partition(users, ['active', false]); * // => objects for [['barney', 'pebbles'], ['fred']] * * // The `_.property` iteratee shorthand. * _.partition(users, 'active'); * // => objects for [['fred'], ['barney', 'pebbles']] */ var partition = createAggregator(function(result, value, key) { result[key ? 0 : 1].push(value); }, function() { return [[], []]; }); /** * Reduces `collection` to a value which is the accumulated result of running * each element in `collection` thru `iteratee`, where each successive * invocation is supplied the return value of the previous. If `accumulator` * is not given, the first element of `collection` is used as the initial * value. The iteratee is invoked with four arguments: * (accumulator, value, index|key, collection). * * Many lodash methods are guarded to work as iteratees for methods like * `_.reduce`, `_.reduceRight`, and `_.transform`. * * The guarded methods are: * `assign`, `defaults`, `defaultsDeep`, `includes`, `merge`, `orderBy`, * and `sortBy` * * @static * @memberOf _ * @since 0.1.0 * @category Collection * @param {Array|Object} collection The collection to iterate over. * @param {Function} [iteratee=_.identity] The function invoked per iteration. * @param {*} [accumulator] The initial value. * @returns {*} Returns the accumulated value. * @see _.reduceRight * @example * * _.reduce([1, 2], function(sum, n) { * return sum + n; * }, 0); * // => 3 * * _.reduce({ 'a': 1, 'b': 2, 'c': 1 }, function(result, value, key) { * (result[value] || (result[value] = [])).push(key); * return result; * }, {}); * // => { '1': ['a', 'c'], '2': ['b'] } (iteration order is not guaranteed) */ function reduce(collection, iteratee, accumulator) { var func = isArray(collection) ? arrayReduce : baseReduce, initAccum = arguments.length < 3; return func(collection, getIteratee(iteratee, 4), accumulator, initAccum, baseEach); } /** * This method is like `_.reduce` except that it iterates over elements of * `collection` from right to left. * * @static * @memberOf _ * @since 0.1.0 * @category Collection * @param {Array|Object} collection The collection to iterate over. * @param {Function} [iteratee=_.identity] The function invoked per iteration. * @param {*} [accumulator] The initial value. * @returns {*} Returns the accumulated value. * @see _.reduce * @example * * var array = [[0, 1], [2, 3], [4, 5]]; * * _.reduceRight(array, function(flattened, other) { * return flattened.concat(other); * }, []); * // => [4, 5, 2, 3, 0, 1] */ function reduceRight(collection, iteratee, accumulator) { var func = isArray(collection) ? arrayReduceRight : baseReduce, initAccum = arguments.length < 3; return func(collection, getIteratee(iteratee, 4), accumulator, initAccum, baseEachRight); } /** * The opposite of `_.filter`; this method returns the elements of `collection` * that `predicate` does **not** return truthy for. * * @static * @memberOf _ * @since 0.1.0 * @category Collection * @param {Array|Object} collection The collection to iterate over. * @param {Function} [predicate=_.identity] The function invoked per iteration. * @returns {Array} Returns the new filtered array. * @see _.filter * @example * * var users = [ * { 'user': 'barney', 'age': 36, 'active': false }, * { 'user': 'fred', 'age': 40, 'active': true } * ]; * * _.reject(users, function(o) { return !o.active; }); * // => objects for ['fred'] * * // The `_.matches` iteratee shorthand. * _.reject(users, { 'age': 40, 'active': true }); * // => objects for ['barney'] * * // The `_.matchesProperty` iteratee shorthand. * _.reject(users, ['active', false]); * // => objects for ['fred'] * * // The `_.property` iteratee shorthand. * _.reject(users, 'active'); * // => objects for ['barney'] */ function reject(collection, predicate) { var func = isArray(collection) ? arrayFilter : baseFilter; return func(collection, negate(getIteratee(predicate, 3))); } /** * Gets a random element from `collection`. * * @static * @memberOf _ * @since 2.0.0 * @category Collection * @param {Array|Object} collection The collection to sample. * @returns {*} Returns the random element. * @example * * _.sample([1, 2, 3, 4]); * // => 2 */ function sample(collection) { var func = isArray(collection) ? arraySample : baseSample; return func(collection); } /** * Gets `n` random elements at unique keys from `collection` up to the * size of `collection`. * * @static * @memberOf _ * @since 4.0.0 * @category Collection * @param {Array|Object} collection The collection to sample. * @param {number} [n=1] The number of elements to sample. * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. * @returns {Array} Returns the random elements. * @example * * _.sampleSize([1, 2, 3], 2); * // => [3, 1] * * _.sampleSize([1, 2, 3], 4); * // => [2, 3, 1] */ function sampleSize(collection, n, guard) { if ((guard ? isIterateeCall(collection, n, guard) : n === undefined)) { n = 1; } else { n = toInteger(n); } var func = isArray(collection) ? arraySampleSize : baseSampleSize; return func(collection, n); } /** * Creates an array of shuffled values, using a version of the * [Fisher-Yates shuffle](https://en.wikipedia.org/wiki/Fisher-Yates_shuffle). * * @static * @memberOf _ * @since 0.1.0 * @category Collection * @param {Array|Object} collection The collection to shuffle. * @returns {Array} Returns the new shuffled array. * @example * * _.shuffle([1, 2, 3, 4]); * // => [4, 1, 3, 2] */ function shuffle(collection) { var func = isArray(collection) ? arrayShuffle : baseShuffle; return func(collection); } /** * Gets the size of `collection` by returning its length for array-like * values or the number of own enumerable string keyed properties for objects. * * @static * @memberOf _ * @since 0.1.0 * @category Collection * @param {Array|Object|string} collection The collection to inspect. * @returns {number} Returns the collection size. * @example * * _.size([1, 2, 3]); * // => 3 * * _.size({ 'a': 1, 'b': 2 }); * // => 2 * * _.size('pebbles'); * // => 7 */ function size(collection) { if (collection == null) { return 0; } if (isArrayLike(collection)) { return isString(collection) ? stringSize(collection) : collection.length; } var tag = getTag(collection); if (tag == mapTag || tag == setTag) { return collection.size; } return baseKeys(collection).length; } /** * Checks if `predicate` returns truthy for **any** element of `collection`. * Iteration is stopped once `predicate` returns truthy. The predicate is * invoked with three arguments: (value, index|key, collection). * * @static * @memberOf _ * @since 0.1.0 * @category Collection * @param {Array|Object} collection The collection to iterate over. * @param {Function} [predicate=_.identity] The function invoked per iteration. * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. * @returns {boolean} Returns `true` if any element passes the predicate check, * else `false`. * @example * * _.some([null, 0, 'yes', false], Boolean); * // => true * * var users = [ * { 'user': 'barney', 'active': true }, * { 'user': 'fred', 'active': false } * ]; * * // The `_.matches` iteratee shorthand. * _.some(users, { 'user': 'barney', 'active': false }); * // => false * * // The `_.matchesProperty` iteratee shorthand. * _.some(users, ['active', false]); * // => true * * // The `_.property` iteratee shorthand. * _.some(users, 'active'); * // => true */ function some(collection, predicate, guard) { var func = isArray(collection) ? arraySome : baseSome; if (guard && isIterateeCall(collection, predicate, guard)) { predicate = undefined; } return func(collection, getIteratee(predicate, 3)); } /** * Creates an array of elements, sorted in ascending order by the results of * running each element in a collection thru each iteratee. This method * performs a stable sort, that is, it preserves the original sort order of * equal elements. The iteratees are invoked with one argument: (value). * * @static * @memberOf _ * @since 0.1.0 * @category Collection * @param {Array|Object} collection The collection to iterate over. * @param {...(Function|Function[])} [iteratees=[_.identity]] * The iteratees to sort by. * @returns {Array} Returns the new sorted array. * @example * * var users = [ * { 'user': 'fred', 'age': 48 }, * { 'user': 'barney', 'age': 36 }, * { 'user': 'fred', 'age': 40 }, * { 'user': 'barney', 'age': 34 } * ]; * * _.sortBy(users, [function(o) { return o.user; }]); * // => objects for [['barney', 36], ['barney', 34], ['fred', 48], ['fred', 40]] * * _.sortBy(users, ['user', 'age']); * // => objects for [['barney', 34], ['barney', 36], ['fred', 40], ['fred', 48]] */ var sortBy = baseRest(function(collection, iteratees) { if (collection == null) { return []; } var length = iteratees.length; if (length > 1 && isIterateeCall(collection, iteratees[0], iteratees[1])) { iteratees = []; } else if (length > 2 && isIterateeCall(iteratees[0], iteratees[1], iteratees[2])) { iteratees = [iteratees[0]]; } return baseOrderBy(collection, baseFlatten(iteratees, 1), []); }); /*------------------------------------------------------------------------*/ /** * Gets the timestamp of the number of milliseconds that have elapsed since * the Unix epoch (1 January 1970 00:00:00 UTC). * * @static * @memberOf _ * @since 2.4.0 * @category Date * @returns {number} Returns the timestamp. * @example * * _.defer(function(stamp) { * console.log(_.now() - stamp); * }, _.now()); * // => Logs the number of milliseconds it took for the deferred invocation. */ var now = ctxNow || function() { return root.Date.now(); }; /*------------------------------------------------------------------------*/ /** * The opposite of `_.before`; this method creates a function that invokes * `func` once it's called `n` or more times. * * @static * @memberOf _ * @since 0.1.0 * @category Function * @param {number} n The number of calls before `func` is invoked. * @param {Function} func The function to restrict. * @returns {Function} Returns the new restricted function. * @example * * var saves = ['profile', 'settings']; * * var done = _.after(saves.length, function() { * console.log('done saving!'); * }); * * _.forEach(saves, function(type) { * asyncSave({ 'type': type, 'complete': done }); * }); * // => Logs 'done saving!' after the two async saves have completed. */ function after(n, func) { if (typeof func != 'function') { throw new TypeError(FUNC_ERROR_TEXT); } n = toInteger(n); return function() { if (--n < 1) { return func.apply(this, arguments); } }; } /** * Creates a function that invokes `func`, with up to `n` arguments, * ignoring any additional arguments. * * @static * @memberOf _ * @since 3.0.0 * @category Function * @param {Function} func The function to cap arguments for. * @param {number} [n=func.length] The arity cap. * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. * @returns {Function} Returns the new capped function. * @example * * _.map(['6', '8', '10'], _.ary(parseInt, 1)); * // => [6, 8, 10] */ function ary(func, n, guard) { n = guard ? undefined : n; n = (func && n == null) ? func.length : n; return createWrap(func, WRAP_ARY_FLAG, undefined, undefined, undefined, undefined, n); } /** * Creates a function that invokes `func`, with the `this` binding and arguments * of the created function, while it's called less than `n` times. Subsequent * calls to the created function return the result of the last `func` invocation. * * @static * @memberOf _ * @since 3.0.0 * @category Function * @param {number} n The number of calls at which `func` is no longer invoked. * @param {Function} func The function to restrict. * @returns {Function} Returns the new restricted function. * @example * * jQuery(element).on('click', _.before(5, addContactToList)); * // => Allows adding up to 4 contacts to the list. */ function before(n, func) { var result; if (typeof func != 'function') { throw new TypeError(FUNC_ERROR_TEXT); } n = toInteger(n); return function() { if (--n > 0) { result = func.apply(this, arguments); } if (n <= 1) { func = undefined; } return result; }; } /** * Creates a function that invokes `func` with the `this` binding of `thisArg` * and `partials` prepended to the arguments it receives. * * The `_.bind.placeholder` value, which defaults to `_` in monolithic builds, * may be used as a placeholder for partially applied arguments. * * **Note:** Unlike native `Function#bind`, this method doesn't set the "length" * property of bound functions. * * @static * @memberOf _ * @since 0.1.0 * @category Function * @param {Function} func The function to bind. * @param {*} thisArg The `this` binding of `func`. * @param {...*} [partials] The arguments to be partially applied. * @returns {Function} Returns the new bound function. * @example * * function greet(greeting, punctuation) { * return greeting + ' ' + this.user + punctuation; * } * * var object = { 'user': 'fred' }; * * var bound = _.bind(greet, object, 'hi'); * bound('!'); * // => 'hi fred!' * * // Bound with placeholders. * var bound = _.bind(greet, object, _, '!'); * bound('hi'); * // => 'hi fred!' */ var bind = baseRest(function(func, thisArg, partials) { var bitmask = WRAP_BIND_FLAG; if (partials.length) { var holders = replaceHolders(partials, getHolder(bind)); bitmask |= WRAP_PARTIAL_FLAG; } return createWrap(func, bitmask, thisArg, partials, holders); }); /** * Creates a function that invokes the method at `object[key]` with `partials` * prepended to the arguments it receives. * * This method differs from `_.bind` by allowing bound functions to reference * methods that may be redefined or don't yet exist. See * [Peter Michaux's article](http://peter.michaux.ca/articles/lazy-function-definition-pattern) * for more details. * * The `_.bindKey.placeholder` value, which defaults to `_` in monolithic * builds, may be used as a placeholder for partially applied arguments. * * @static * @memberOf _ * @since 0.10.0 * @category Function * @param {Object} object The object to invoke the method on. * @param {string} key The key of the method. * @param {...*} [partials] The arguments to be partially applied. * @returns {Function} Returns the new bound function. * @example * * var object = { * 'user': 'fred', * 'greet': function(greeting, punctuation) { * return greeting + ' ' + this.user + punctuation; * } * }; * * var bound = _.bindKey(object, 'greet', 'hi'); * bound('!'); * // => 'hi fred!' * * object.greet = function(greeting, punctuation) { * return greeting + 'ya ' + this.user + punctuation; * }; * * bound('!'); * // => 'hiya fred!' * * // Bound with placeholders. * var bound = _.bindKey(object, 'greet', _, '!'); * bound('hi'); * // => 'hiya fred!' */ var bindKey = baseRest(function(object, key, partials) { var bitmask = WRAP_BIND_FLAG | WRAP_BIND_KEY_FLAG; if (partials.length) { var holders = replaceHolders(partials, getHolder(bindKey)); bitmask |= WRAP_PARTIAL_FLAG; } return createWrap(key, bitmask, object, partials, holders); }); /** * Creates a function that accepts arguments of `func` and either invokes * `func` returning its result, if at least `arity` number of arguments have * been provided, or returns a function that accepts the remaining `func` * arguments, and so on. The arity of `func` may be specified if `func.length` * is not sufficient. * * The `_.curry.placeholder` value, which defaults to `_` in monolithic builds, * may be used as a placeholder for provided arguments. * * **Note:** This method doesn't set the "length" property of curried functions. * * @static * @memberOf _ * @since 2.0.0 * @category Function * @param {Function} func The function to curry. * @param {number} [arity=func.length] The arity of `func`. * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. * @returns {Function} Returns the new curried function. * @example * * var abc = function(a, b, c) { * return [a, b, c]; * }; * * var curried = _.curry(abc); * * curried(1)(2)(3); * // => [1, 2, 3] * * curried(1, 2)(3); * // => [1, 2, 3] * * curried(1, 2, 3); * // => [1, 2, 3] * * // Curried with placeholders. * curried(1)(_, 3)(2); * // => [1, 2, 3] */ function curry(func, arity, guard) { arity = guard ? undefined : arity; var result = createWrap(func, WRAP_CURRY_FLAG, undefined, undefined, undefined, undefined, undefined, arity); result.placeholder = curry.placeholder; return result; } /** * This method is like `_.curry` except that arguments are applied to `func` * in the manner of `_.partialRight` instead of `_.partial`. * * The `_.curryRight.placeholder` value, which defaults to `_` in monolithic * builds, may be used as a placeholder for provided arguments. * * **Note:** This method doesn't set the "length" property of curried functions. * * @static * @memberOf _ * @since 3.0.0 * @category Function * @param {Function} func The function to curry. * @param {number} [arity=func.length] The arity of `func`. * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. * @returns {Function} Returns the new curried function. * @example * * var abc = function(a, b, c) { * return [a, b, c]; * }; * * var curried = _.curryRight(abc); * * curried(3)(2)(1); * // => [1, 2, 3] * * curried(2, 3)(1); * // => [1, 2, 3] * * curried(1, 2, 3); * // => [1, 2, 3] * * // Curried with placeholders. * curried(3)(1, _)(2); * // => [1, 2, 3] */ function curryRight(func, arity, guard) { arity = guard ? undefined : arity; var result = createWrap(func, WRAP_CURRY_RIGHT_FLAG, undefined, undefined, undefined, undefined, undefined, arity); result.placeholder = curryRight.placeholder; return result; } /** * Creates a debounced function that delays invoking `func` until after `wait` * milliseconds have elapsed since the last time the debounced function was * invoked. The debounced function comes with a `cancel` method to cancel * delayed `func` invocations and a `flush` method to immediately invoke them. * Provide `options` to indicate whether `func` should be invoked on the * leading and/or trailing edge of the `wait` timeout. The `func` is invoked * with the last arguments provided to the debounced function. Subsequent * calls to the debounced function return the result of the last `func` * invocation. * * **Note:** If `leading` and `trailing` options are `true`, `func` is * invoked on the trailing edge of the timeout only if the debounced function * is invoked more than once during the `wait` timeout. * * If `wait` is `0` and `leading` is `false`, `func` invocation is deferred * until to the next tick, similar to `setTimeout` with a timeout of `0`. * * See [David Corbacho's article](https://css-tricks.com/debouncing-throttling-explained-examples/) * for details over the differences between `_.debounce` and `_.throttle`. * * @static * @memberOf _ * @since 0.1.0 * @category Function * @param {Function} func The function to debounce. * @param {number} [wait=0] The number of milliseconds to delay. * @param {Object} [options={}] The options object. * @param {boolean} [options.leading=false] * Specify invoking on the leading edge of the timeout. * @param {number} [options.maxWait] * The maximum time `func` is allowed to be delayed before it's invoked. * @param {boolean} [options.trailing=true] * Specify invoking on the trailing edge of the timeout. * @returns {Function} Returns the new debounced function. * @example * * // Avoid costly calculations while the window size is in flux. * jQuery(window).on('resize', _.debounce(calculateLayout, 150)); * * // Invoke `sendMail` when clicked, debouncing subsequent calls. * jQuery(element).on('click', _.debounce(sendMail, 300, { * 'leading': true, * 'trailing': false * })); * * // Ensure `batchLog` is invoked once after 1 second of debounced calls. * var debounced = _.debounce(batchLog, 250, { 'maxWait': 1000 }); * var source = new EventSource('/stream'); * jQuery(source).on('message', debounced); * * // Cancel the trailing debounced invocation. * jQuery(window).on('popstate', debounced.cancel); */ function debounce(func, wait, options) { var lastArgs, lastThis, maxWait, result, timerId, lastCallTime, lastInvokeTime = 0, leading = false, maxing = false, trailing = true; if (typeof func != 'function') { throw new TypeError(FUNC_ERROR_TEXT); } wait = toNumber(wait) || 0; if (isObject(options)) { leading = !!options.leading; maxing = 'maxWait' in options; maxWait = maxing ? nativeMax(toNumber(options.maxWait) || 0, wait) : maxWait; trailing = 'trailing' in options ? !!options.trailing : trailing; } function invokeFunc(time) { var args = lastArgs, thisArg = lastThis; lastArgs = lastThis = undefined; lastInvokeTime = time; result = func.apply(thisArg, args); return result; } function leadingEdge(time) { // Reset any `maxWait` timer. lastInvokeTime = time; // Start the timer for the trailing edge. timerId = setTimeout(timerExpired, wait); // Invoke the leading edge. return leading ? invokeFunc(time) : result; } function remainingWait(time) { var timeSinceLastCall = time - lastCallTime, timeSinceLastInvoke = time - lastInvokeTime, timeWaiting = wait - timeSinceLastCall; return maxing ? nativeMin(timeWaiting, maxWait - timeSinceLastInvoke) : timeWaiting; } function shouldInvoke(time) { var timeSinceLastCall = time - lastCallTime, timeSinceLastInvoke = time - lastInvokeTime; // Either this is the first call, activity has stopped and we're at the // trailing edge, the system time has gone backwards and we're treating // it as the trailing edge, or we've hit the `maxWait` limit. return (lastCallTime === undefined || (timeSinceLastCall >= wait) || (timeSinceLastCall < 0) || (maxing && timeSinceLastInvoke >= maxWait)); } function timerExpired() { var time = now(); if (shouldInvoke(time)) { return trailingEdge(time); } // Restart the timer. timerId = setTimeout(timerExpired, remainingWait(time)); } function trailingEdge(time) { timerId = undefined; // Only invoke if we have `lastArgs` which means `func` has been // debounced at least once. if (trailing && lastArgs) { return invokeFunc(time); } lastArgs = lastThis = undefined; return result; } function cancel() { if (timerId !== undefined) { clearTimeout(timerId); } lastInvokeTime = 0; lastArgs = lastCallTime = lastThis = timerId = undefined; } function flush() { return timerId === undefined ? result : trailingEdge(now()); } function debounced() { var time = now(), isInvoking = shouldInvoke(time); lastArgs = arguments; lastThis = this; lastCallTime = time; if (isInvoking) { if (timerId === undefined) { return leadingEdge(lastCallTime); } if (maxing) { // Handle invocations in a tight loop. clearTimeout(timerId); timerId = setTimeout(timerExpired, wait); return invokeFunc(lastCallTime); } } if (timerId === undefined) { timerId = setTimeout(timerExpired, wait); } return result; } debounced.cancel = cancel; debounced.flush = flush; return debounced; } /** * Defers invoking the `func` until the current call stack has cleared. Any * additional arguments are provided to `func` when it's invoked. * * @static * @memberOf _ * @since 0.1.0 * @category Function * @param {Function} func The function to defer. * @param {...*} [args] The arguments to invoke `func` with. * @returns {number} Returns the timer id. * @example * * _.defer(function(text) { * console.log(text); * }, 'deferred'); * // => Logs 'deferred' after one millisecond. */ var defer = baseRest(function(func, args) { return baseDelay(func, 1, args); }); /** * Invokes `func` after `wait` milliseconds. Any additional arguments are * provided to `func` when it's invoked. * * @static * @memberOf _ * @since 0.1.0 * @category Function * @param {Function} func The function to delay. * @param {number} wait The number of milliseconds to delay invocation. * @param {...*} [args] The arguments to invoke `func` with. * @returns {number} Returns the timer id. * @example * * _.delay(function(text) { * console.log(text); * }, 1000, 'later'); * // => Logs 'later' after one second. */ var delay = baseRest(function(func, wait, args) { return baseDelay(func, toNumber(wait) || 0, args); }); /** * Creates a function that invokes `func` with arguments reversed. * * @static * @memberOf _ * @since 4.0.0 * @category Function * @param {Function} func The function to flip arguments for. * @returns {Function} Returns the new flipped function. * @example * * var flipped = _.flip(function() { * return _.toArray(arguments); * }); * * flipped('a', 'b', 'c', 'd'); * // => ['d', 'c', 'b', 'a'] */ function flip(func) { return createWrap(func, WRAP_FLIP_FLAG); } /** * Creates a function that memoizes the result of `func`. If `resolver` is * provided, it determines the cache key for storing the result based on the * arguments provided to the memoized function. By default, the first argument * provided to the memoized function is used as the map cache key. The `func` * is invoked with the `this` binding of the memoized function. * * **Note:** The cache is exposed as the `cache` property on the memoized * function. Its creation may be customized by replacing the `_.memoize.Cache` * constructor with one whose instances implement the * [`Map`](http://ecma-international.org/ecma-262/7.0/#sec-properties-of-the-map-prototype-object) * method interface of `clear`, `delete`, `get`, `has`, and `set`. * * @static * @memberOf _ * @since 0.1.0 * @category Function * @param {Function} func The function to have its output memoized. * @param {Function} [resolver] The function to resolve the cache key. * @returns {Function} Returns the new memoized function. * @example * * var object = { 'a': 1, 'b': 2 }; * var other = { 'c': 3, 'd': 4 }; * * var values = _.memoize(_.values); * values(object); * // => [1, 2] * * values(other); * // => [3, 4] * * object.a = 2; * values(object); * // => [1, 2] * * // Modify the result cache. * values.cache.set(object, ['a', 'b']); * values(object); * // => ['a', 'b'] * * // Replace `_.memoize.Cache`. * _.memoize.Cache = WeakMap; */ function memoize(func, resolver) { if (typeof func != 'function' || (resolver != null && typeof resolver != 'function')) { throw new TypeError(FUNC_ERROR_TEXT); } var memoized = function() { var args = arguments, key = resolver ? resolver.apply(this, args) : args[0], cache = memoized.cache; if (cache.has(key)) { return cache.get(key); } var result = func.apply(this, args); memoized.cache = cache.set(key, result) || cache; return result; }; memoized.cache = new (memoize.Cache || MapCache); return memoized; } // Expose `MapCache`. memoize.Cache = MapCache; /** * Creates a function that negates the result of the predicate `func`. The * `func` predicate is invoked with the `this` binding and arguments of the * created function. * * @static * @memberOf _ * @since 3.0.0 * @category Function * @param {Function} predicate The predicate to negate. * @returns {Function} Returns the new negated function. * @example * * function isEven(n) { * return n % 2 == 0; * } * * _.filter([1, 2, 3, 4, 5, 6], _.negate(isEven)); * // => [1, 3, 5] */ function negate(predicate) { if (typeof predicate != 'function') { throw new TypeError(FUNC_ERROR_TEXT); } return function() { var args = arguments; switch (args.length) { case 0: return !predicate.call(this); case 1: return !predicate.call(this, args[0]); case 2: return !predicate.call(this, args[0], args[1]); case 3: return !predicate.call(this, args[0], args[1], args[2]); } return !predicate.apply(this, args); }; } /** * Creates a function that is restricted to invoking `func` once. Repeat calls * to the function return the value of the first invocation. The `func` is * invoked with the `this` binding and arguments of the created function. * * @static * @memberOf _ * @since 0.1.0 * @category Function * @param {Function} func The function to restrict. * @returns {Function} Returns the new restricted function. * @example * * var initialize = _.once(createApplication); * initialize(); * initialize(); * // => `createApplication` is invoked once */ function once(func) { return before(2, func); } /** * Creates a function that invokes `func` with its arguments transformed. * * @static * @since 4.0.0 * @memberOf _ * @category Function * @param {Function} func The function to wrap. * @param {...(Function|Function[])} [transforms=[_.identity]] * The argument transforms. * @returns {Function} Returns the new function. * @example * * function doubled(n) { * return n * 2; * } * * function square(n) { * return n * n; * } * * var func = _.overArgs(function(x, y) { * return [x, y]; * }, [square, doubled]); * * func(9, 3); * // => [81, 6] * * func(10, 5); * // => [100, 10] */ var overArgs = castRest(function(func, transforms) { transforms = (transforms.length == 1 && isArray(transforms[0])) ? arrayMap(transforms[0], baseUnary(getIteratee())) : arrayMap(baseFlatten(transforms, 1), baseUnary(getIteratee())); var funcsLength = transforms.length; return baseRest(function(args) { var index = -1, length = nativeMin(args.length, funcsLength); while (++index < length) { args[index] = transforms[index].call(this, args[index]); } return apply(func, this, args); }); }); /** * Creates a function that invokes `func` with `partials` prepended to the * arguments it receives. This method is like `_.bind` except it does **not** * alter the `this` binding. * * The `_.partial.placeholder` value, which defaults to `_` in monolithic * builds, may be used as a placeholder for partially applied arguments. * * **Note:** This method doesn't set the "length" property of partially * applied functions. * * @static * @memberOf _ * @since 0.2.0 * @category Function * @param {Function} func The function to partially apply arguments to. * @param {...*} [partials] The arguments to be partially applied. * @returns {Function} Returns the new partially applied function. * @example * * function greet(greeting, name) { * return greeting + ' ' + name; * } * * var sayHelloTo = _.partial(greet, 'hello'); * sayHelloTo('fred'); * // => 'hello fred' * * // Partially applied with placeholders. * var greetFred = _.partial(greet, _, 'fred'); * greetFred('hi'); * // => 'hi fred' */ var partial = baseRest(function(func, partials) { var holders = replaceHolders(partials, getHolder(partial)); return createWrap(func, WRAP_PARTIAL_FLAG, undefined, partials, holders); }); /** * This method is like `_.partial` except that partially applied arguments * are appended to the arguments it receives. * * The `_.partialRight.placeholder` value, which defaults to `_` in monolithic * builds, may be used as a placeholder for partially applied arguments. * * **Note:** This method doesn't set the "length" property of partially * applied functions. * * @static * @memberOf _ * @since 1.0.0 * @category Function * @param {Function} func The function to partially apply arguments to. * @param {...*} [partials] The arguments to be partially applied. * @returns {Function} Returns the new partially applied function. * @example * * function greet(greeting, name) { * return greeting + ' ' + name; * } * * var greetFred = _.partialRight(greet, 'fred'); * greetFred('hi'); * // => 'hi fred' * * // Partially applied with placeholders. * var sayHelloTo = _.partialRight(greet, 'hello', _); * sayHelloTo('fred'); * // => 'hello fred' */ var partialRight = baseRest(function(func, partials) { var holders = replaceHolders(partials, getHolder(partialRight)); return createWrap(func, WRAP_PARTIAL_RIGHT_FLAG, undefined, partials, holders); }); /** * Creates a function that invokes `func` with arguments arranged according * to the specified `indexes` where the argument value at the first index is * provided as the first argument, the argument value at the second index is * provided as the second argument, and so on. * * @static * @memberOf _ * @since 3.0.0 * @category Function * @param {Function} func The function to rearrange arguments for. * @param {...(number|number[])} indexes The arranged argument indexes. * @returns {Function} Returns the new function. * @example * * var rearged = _.rearg(function(a, b, c) { * return [a, b, c]; * }, [2, 0, 1]); * * rearged('b', 'c', 'a') * // => ['a', 'b', 'c'] */ var rearg = flatRest(function(func, indexes) { return createWrap(func, WRAP_REARG_FLAG, undefined, undefined, undefined, indexes); }); /** * Creates a function that invokes `func` with the `this` binding of the * created function and arguments from `start` and beyond provided as * an array. * * **Note:** This method is based on the * [rest parameter](https://mdn.io/rest_parameters). * * @static * @memberOf _ * @since 4.0.0 * @category Function * @param {Function} func The function to apply a rest parameter to. * @param {number} [start=func.length-1] The start position of the rest parameter. * @returns {Function} Returns the new function. * @example * * var say = _.rest(function(what, names) { * return what + ' ' + _.initial(names).join(', ') + * (_.size(names) > 1 ? ', & ' : '') + _.last(names); * }); * * say('hello', 'fred', 'barney', 'pebbles'); * // => 'hello fred, barney, & pebbles' */ function rest(func, start) { if (typeof func != 'function') { throw new TypeError(FUNC_ERROR_TEXT); } start = start === undefined ? start : toInteger(start); return baseRest(func, start); } /** * Creates a function that invokes `func` with the `this` binding of the * create function and an array of arguments much like * [`Function#apply`](http://www.ecma-international.org/ecma-262/7.0/#sec-function.prototype.apply). * * **Note:** This method is based on the * [spread operator](https://mdn.io/spread_operator). * * @static * @memberOf _ * @since 3.2.0 * @category Function * @param {Function} func The function to spread arguments over. * @param {number} [start=0] The start position of the spread. * @returns {Function} Returns the new function. * @example * * var say = _.spread(function(who, what) { * return who + ' says ' + what; * }); * * say(['fred', 'hello']); * // => 'fred says hello' * * var numbers = Promise.all([ * Promise.resolve(40), * Promise.resolve(36) * ]); * * numbers.then(_.spread(function(x, y) { * return x + y; * })); * // => a Promise of 76 */ function spread(func, start) { if (typeof func != 'function') { throw new TypeError(FUNC_ERROR_TEXT); } start = start == null ? 0 : nativeMax(toInteger(start), 0); return baseRest(function(args) { var array = args[start], otherArgs = castSlice(args, 0, start); if (array) { arrayPush(otherArgs, array); } return apply(func, this, otherArgs); }); } /** * Creates a throttled function that only invokes `func` at most once per * every `wait` milliseconds. The throttled function comes with a `cancel` * method to cancel delayed `func` invocations and a `flush` method to * immediately invoke them. Provide `options` to indicate whether `func` * should be invoked on the leading and/or trailing edge of the `wait` * timeout. The `func` is invoked with the last arguments provided to the * throttled function. Subsequent calls to the throttled function return the * result of the last `func` invocation. * * **Note:** If `leading` and `trailing` options are `true`, `func` is * invoked on the trailing edge of the timeout only if the throttled function * is invoked more than once during the `wait` timeout. * * If `wait` is `0` and `leading` is `false`, `func` invocation is deferred * until to the next tick, similar to `setTimeout` with a timeout of `0`. * * See [David Corbacho's article](https://css-tricks.com/debouncing-throttling-explained-examples/) * for details over the differences between `_.throttle` and `_.debounce`. * * @static * @memberOf _ * @since 0.1.0 * @category Function * @param {Function} func The function to throttle. * @param {number} [wait=0] The number of milliseconds to throttle invocations to. * @param {Object} [options={}] The options object. * @param {boolean} [options.leading=true] * Specify invoking on the leading edge of the timeout. * @param {boolean} [options.trailing=true] * Specify invoking on the trailing edge of the timeout. * @returns {Function} Returns the new throttled function. * @example * * // Avoid excessively updating the position while scrolling. * jQuery(window).on('scroll', _.throttle(updatePosition, 100)); * * // Invoke `renewToken` when the click event is fired, but not more than once every 5 minutes. * var throttled = _.throttle(renewToken, 300000, { 'trailing': false }); * jQuery(element).on('click', throttled); * * // Cancel the trailing throttled invocation. * jQuery(window).on('popstate', throttled.cancel); */ function throttle(func, wait, options) { var leading = true, trailing = true; if (typeof func != 'function') { throw new TypeError(FUNC_ERROR_TEXT); } if (isObject(options)) { leading = 'leading' in options ? !!options.leading : leading; trailing = 'trailing' in options ? !!options.trailing : trailing; } return debounce(func, wait, { 'leading': leading, 'maxWait': wait, 'trailing': trailing }); } /** * Creates a function that accepts up to one argument, ignoring any * additional arguments. * * @static * @memberOf _ * @since 4.0.0 * @category Function * @param {Function} func The function to cap arguments for. * @returns {Function} Returns the new capped function. * @example * * _.map(['6', '8', '10'], _.unary(parseInt)); * // => [6, 8, 10] */ function unary(func) { return ary(func, 1); } /** * Creates a function that provides `value` to `wrapper` as its first * argument. Any additional arguments provided to the function are appended * to those provided to the `wrapper`. The wrapper is invoked with the `this` * binding of the created function. * * @static * @memberOf _ * @since 0.1.0 * @category Function * @param {*} value The value to wrap. * @param {Function} [wrapper=identity] The wrapper function. * @returns {Function} Returns the new function. * @example * * var p = _.wrap(_.escape, function(func, text) { * return '

' + func(text) + '

'; * }); * * p('fred, barney, & pebbles'); * // => '

fred, barney, & pebbles

' */ function wrap(value, wrapper) { return partial(castFunction(wrapper), value); } /*------------------------------------------------------------------------*/ /** * Casts `value` as an array if it's not one. * * @static * @memberOf _ * @since 4.4.0 * @category Lang * @param {*} value The value to inspect. * @returns {Array} Returns the cast array. * @example * * _.castArray(1); * // => [1] * * _.castArray({ 'a': 1 }); * // => [{ 'a': 1 }] * * _.castArray('abc'); * // => ['abc'] * * _.castArray(null); * // => [null] * * _.castArray(undefined); * // => [undefined] * * _.castArray(); * // => [] * * var array = [1, 2, 3]; * console.log(_.castArray(array) === array); * // => true */ function castArray() { if (!arguments.length) { return []; } var value = arguments[0]; return isArray(value) ? value : [value]; } /** * Creates a shallow clone of `value`. * * **Note:** This method is loosely based on the * [structured clone algorithm](https://mdn.io/Structured_clone_algorithm) * and supports cloning arrays, array buffers, booleans, date objects, maps, * numbers, `Object` objects, regexes, sets, strings, symbols, and typed * arrays. The own enumerable properties of `arguments` objects are cloned * as plain objects. An empty object is returned for uncloneable values such * as error objects, functions, DOM nodes, and WeakMaps. * * @static * @memberOf _ * @since 0.1.0 * @category Lang * @param {*} value The value to clone. * @returns {*} Returns the cloned value. * @see _.cloneDeep * @example * * var objects = [{ 'a': 1 }, { 'b': 2 }]; * * var shallow = _.clone(objects); * console.log(shallow[0] === objects[0]); * // => true */ function clone(value) { return baseClone(value, CLONE_SYMBOLS_FLAG); } /** * This method is like `_.clone` except that it accepts `customizer` which * is invoked to produce the cloned value. If `customizer` returns `undefined`, * cloning is handled by the method instead. The `customizer` is invoked with * up to four arguments; (value [, index|key, object, stack]). * * @static * @memberOf _ * @since 4.0.0 * @category Lang * @param {*} value The value to clone. * @param {Function} [customizer] The function to customize cloning. * @returns {*} Returns the cloned value. * @see _.cloneDeepWith * @example * * function customizer(value) { * if (_.isElement(value)) { * return value.cloneNode(false); * } * } * * var el = _.cloneWith(document.body, customizer); * * console.log(el === document.body); * // => false * console.log(el.nodeName); * // => 'BODY' * console.log(el.childNodes.length); * // => 0 */ function cloneWith(value, customizer) { customizer = typeof customizer == 'function' ? customizer : undefined; return baseClone(value, CLONE_SYMBOLS_FLAG, customizer); } /** * This method is like `_.clone` except that it recursively clones `value`. * * @static * @memberOf _ * @since 1.0.0 * @category Lang * @param {*} value The value to recursively clone. * @returns {*} Returns the deep cloned value. * @see _.clone * @example * * var objects = [{ 'a': 1 }, { 'b': 2 }]; * * var deep = _.cloneDeep(objects); * console.log(deep[0] === objects[0]); * // => false */ function cloneDeep(value) { return baseClone(value, CLONE_DEEP_FLAG | CLONE_SYMBOLS_FLAG); } /** * This method is like `_.cloneWith` except that it recursively clones `value`. * * @static * @memberOf _ * @since 4.0.0 * @category Lang * @param {*} value The value to recursively clone. * @param {Function} [customizer] The function to customize cloning. * @returns {*} Returns the deep cloned value. * @see _.cloneWith * @example * * function customizer(value) { * if (_.isElement(value)) { * return value.cloneNode(true); * } * } * * var el = _.cloneDeepWith(document.body, customizer); * * console.log(el === document.body); * // => false * console.log(el.nodeName); * // => 'BODY' * console.log(el.childNodes.length); * // => 20 */ function cloneDeepWith(value, customizer) { customizer = typeof customizer == 'function' ? customizer : undefined; return baseClone(value, CLONE_DEEP_FLAG | CLONE_SYMBOLS_FLAG, customizer); } /** * Checks if `object` conforms to `source` by invoking the predicate * properties of `source` with the corresponding property values of `object`. * * **Note:** This method is equivalent to `_.conforms` when `source` is * partially applied. * * @static * @memberOf _ * @since 4.14.0 * @category Lang * @param {Object} object The object to inspect. * @param {Object} source The object of property predicates to conform to. * @returns {boolean} Returns `true` if `object` conforms, else `false`. * @example * * var object = { 'a': 1, 'b': 2 }; * * _.conformsTo(object, { 'b': function(n) { return n > 1; } }); * // => true * * _.conformsTo(object, { 'b': function(n) { return n > 2; } }); * // => false */ function conformsTo(object, source) { return source == null || baseConformsTo(object, source, keys(source)); } /** * Performs a * [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) * comparison between two values to determine if they are equivalent. * * @static * @memberOf _ * @since 4.0.0 * @category Lang * @param {*} value The value to compare. * @param {*} other The other value to compare. * @returns {boolean} Returns `true` if the values are equivalent, else `false`. * @example * * var object = { 'a': 1 }; * var other = { 'a': 1 }; * * _.eq(object, object); * // => true * * _.eq(object, other); * // => false * * _.eq('a', 'a'); * // => true * * _.eq('a', Object('a')); * // => false * * _.eq(NaN, NaN); * // => true */ function eq(value, other) { return value === other || (value !== value && other !== other); } /** * Checks if `value` is greater than `other`. * * @static * @memberOf _ * @since 3.9.0 * @category Lang * @param {*} value The value to compare. * @param {*} other The other value to compare. * @returns {boolean} Returns `true` if `value` is greater than `other`, * else `false`. * @see _.lt * @example * * _.gt(3, 1); * // => true * * _.gt(3, 3); * // => false * * _.gt(1, 3); * // => false */ var gt = createRelationalOperation(baseGt); /** * Checks if `value` is greater than or equal to `other`. * * @static * @memberOf _ * @since 3.9.0 * @category Lang * @param {*} value The value to compare. * @param {*} other The other value to compare. * @returns {boolean} Returns `true` if `value` is greater than or equal to * `other`, else `false`. * @see _.lte * @example * * _.gte(3, 1); * // => true * * _.gte(3, 3); * // => true * * _.gte(1, 3); * // => false */ var gte = createRelationalOperation(function(value, other) { return value >= other; }); /** * Checks if `value` is likely an `arguments` object. * * @static * @memberOf _ * @since 0.1.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is an `arguments` object, * else `false`. * @example * * _.isArguments(function() { return arguments; }()); * // => true * * _.isArguments([1, 2, 3]); * // => false */ var isArguments = baseIsArguments(function() { return arguments; }()) ? baseIsArguments : function(value) { return isObjectLike(value) && hasOwnProperty.call(value, 'callee') && !propertyIsEnumerable.call(value, 'callee'); }; /** * Checks if `value` is classified as an `Array` object. * * @static * @memberOf _ * @since 0.1.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is an array, else `false`. * @example * * _.isArray([1, 2, 3]); * // => true * * _.isArray(document.body.children); * // => false * * _.isArray('abc'); * // => false * * _.isArray(_.noop); * // => false */ var isArray = Array.isArray; /** * Checks if `value` is classified as an `ArrayBuffer` object. * * @static * @memberOf _ * @since 4.3.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is an array buffer, else `false`. * @example * * _.isArrayBuffer(new ArrayBuffer(2)); * // => true * * _.isArrayBuffer(new Array(2)); * // => false */ var isArrayBuffer = nodeIsArrayBuffer ? baseUnary(nodeIsArrayBuffer) : baseIsArrayBuffer; /** * Checks if `value` is array-like. A value is considered array-like if it's * not a function and has a `value.length` that's an integer greater than or * equal to `0` and less than or equal to `Number.MAX_SAFE_INTEGER`. * * @static * @memberOf _ * @since 4.0.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is array-like, else `false`. * @example * * _.isArrayLike([1, 2, 3]); * // => true * * _.isArrayLike(document.body.children); * // => true * * _.isArrayLike('abc'); * // => true * * _.isArrayLike(_.noop); * // => false */ function isArrayLike(value) { return value != null && isLength(value.length) && !isFunction(value); } /** * This method is like `_.isArrayLike` except that it also checks if `value` * is an object. * * @static * @memberOf _ * @since 4.0.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is an array-like object, * else `false`. * @example * * _.isArrayLikeObject([1, 2, 3]); * // => true * * _.isArrayLikeObject(document.body.children); * // => true * * _.isArrayLikeObject('abc'); * // => false * * _.isArrayLikeObject(_.noop); * // => false */ function isArrayLikeObject(value) { return isObjectLike(value) && isArrayLike(value); } /** * Checks if `value` is classified as a boolean primitive or object. * * @static * @memberOf _ * @since 0.1.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a boolean, else `false`. * @example * * _.isBoolean(false); * // => true * * _.isBoolean(null); * // => false */ function isBoolean(value) { return value === true || value === false || (isObjectLike(value) && baseGetTag(value) == boolTag); } /** * Checks if `value` is a buffer. * * @static * @memberOf _ * @since 4.3.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a buffer, else `false`. * @example * * _.isBuffer(new Buffer(2)); * // => true * * _.isBuffer(new Uint8Array(2)); * // => false */ var isBuffer = nativeIsBuffer || stubFalse; /** * Checks if `value` is classified as a `Date` object. * * @static * @memberOf _ * @since 0.1.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a date object, else `false`. * @example * * _.isDate(new Date); * // => true * * _.isDate('Mon April 23 2012'); * // => false */ var isDate = nodeIsDate ? baseUnary(nodeIsDate) : baseIsDate; /** * Checks if `value` is likely a DOM element. * * @static * @memberOf _ * @since 0.1.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a DOM element, else `false`. * @example * * _.isElement(document.body); * // => true * * _.isElement(''); * // => false */ function isElement(value) { return isObjectLike(value) && value.nodeType === 1 && !isPlainObject(value); } /** * Checks if `value` is an empty object, collection, map, or set. * * Objects are considered empty if they have no own enumerable string keyed * properties. * * Array-like values such as `arguments` objects, arrays, buffers, strings, or * jQuery-like collections are considered empty if they have a `length` of `0`. * Similarly, maps and sets are considered empty if they have a `size` of `0`. * * @static * @memberOf _ * @since 0.1.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is empty, else `false`. * @example * * _.isEmpty(null); * // => true * * _.isEmpty(true); * // => true * * _.isEmpty(1); * // => true * * _.isEmpty([1, 2, 3]); * // => false * * _.isEmpty({ 'a': 1 }); * // => false */ function isEmpty(value) { if (value == null) { return true; } if (isArrayLike(value) && (isArray(value) || typeof value == 'string' || typeof value.splice == 'function' || isBuffer(value) || isTypedArray(value) || isArguments(value))) { return !value.length; } var tag = getTag(value); if (tag == mapTag || tag == setTag) { return !value.size; } if (isPrototype(value)) { return !baseKeys(value).length; } for (var key in value) { if (hasOwnProperty.call(value, key)) { return false; } } return true; } /** * Performs a deep comparison between two values to determine if they are * equivalent. * * **Note:** This method supports comparing arrays, array buffers, booleans, * date objects, error objects, maps, numbers, `Object` objects, regexes, * sets, strings, symbols, and typed arrays. `Object` objects are compared * by their own, not inherited, enumerable properties. Functions and DOM * nodes are compared by strict equality, i.e. `===`. * * @static * @memberOf _ * @since 0.1.0 * @category Lang * @param {*} value The value to compare. * @param {*} other The other value to compare. * @returns {boolean} Returns `true` if the values are equivalent, else `false`. * @example * * var object = { 'a': 1 }; * var other = { 'a': 1 }; * * _.isEqual(object, other); * // => true * * object === other; * // => false */ function isEqual(value, other) { return baseIsEqual(value, other); } /** * This method is like `_.isEqual` except that it accepts `customizer` which * is invoked to compare values. If `customizer` returns `undefined`, comparisons * are handled by the method instead. The `customizer` is invoked with up to * six arguments: (objValue, othValue [, index|key, object, other, stack]). * * @static * @memberOf _ * @since 4.0.0 * @category Lang * @param {*} value The value to compare. * @param {*} other The other value to compare. * @param {Function} [customizer] The function to customize comparisons. * @returns {boolean} Returns `true` if the values are equivalent, else `false`. * @example * * function isGreeting(value) { * return /^h(?:i|ello)$/.test(value); * } * * function customizer(objValue, othValue) { * if (isGreeting(objValue) && isGreeting(othValue)) { * return true; * } * } * * var array = ['hello', 'goodbye']; * var other = ['hi', 'goodbye']; * * _.isEqualWith(array, other, customizer); * // => true */ function isEqualWith(value, other, customizer) { customizer = typeof customizer == 'function' ? customizer : undefined; var result = customizer ? customizer(value, other) : undefined; return result === undefined ? baseIsEqual(value, other, undefined, customizer) : !!result; } /** * Checks if `value` is an `Error`, `EvalError`, `RangeError`, `ReferenceError`, * `SyntaxError`, `TypeError`, or `URIError` object. * * @static * @memberOf _ * @since 3.0.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is an error object, else `false`. * @example * * _.isError(new Error); * // => true * * _.isError(Error); * // => false */ function isError(value) { if (!isObjectLike(value)) { return false; } var tag = baseGetTag(value); return tag == errorTag || tag == domExcTag || (typeof value.message == 'string' && typeof value.name == 'string' && !isPlainObject(value)); } /** * Checks if `value` is a finite primitive number. * * **Note:** This method is based on * [`Number.isFinite`](https://mdn.io/Number/isFinite). * * @static * @memberOf _ * @since 0.1.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a finite number, else `false`. * @example * * _.isFinite(3); * // => true * * _.isFinite(Number.MIN_VALUE); * // => true * * _.isFinite(Infinity); * // => false * * _.isFinite('3'); * // => false */ function isFinite(value) { return typeof value == 'number' && nativeIsFinite(value); } /** * Checks if `value` is classified as a `Function` object. * * @static * @memberOf _ * @since 0.1.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a function, else `false`. * @example * * _.isFunction(_); * // => true * * _.isFunction(/abc/); * // => false */ function isFunction(value) { if (!isObject(value)) { return false; } // The use of `Object#toString` avoids issues with the `typeof` operator // in Safari 9 which returns 'object' for typed arrays and other constructors. var tag = baseGetTag(value); return tag == funcTag || tag == genTag || tag == asyncTag || tag == proxyTag; } /** * Checks if `value` is an integer. * * **Note:** This method is based on * [`Number.isInteger`](https://mdn.io/Number/isInteger). * * @static * @memberOf _ * @since 4.0.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is an integer, else `false`. * @example * * _.isInteger(3); * // => true * * _.isInteger(Number.MIN_VALUE); * // => false * * _.isInteger(Infinity); * // => false * * _.isInteger('3'); * // => false */ function isInteger(value) { return typeof value == 'number' && value == toInteger(value); } /** * Checks if `value` is a valid array-like length. * * **Note:** This method is loosely based on * [`ToLength`](http://ecma-international.org/ecma-262/7.0/#sec-tolength). * * @static * @memberOf _ * @since 4.0.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a valid length, else `false`. * @example * * _.isLength(3); * // => true * * _.isLength(Number.MIN_VALUE); * // => false * * _.isLength(Infinity); * // => false * * _.isLength('3'); * // => false */ function isLength(value) { return typeof value == 'number' && value > -1 && value % 1 == 0 && value <= MAX_SAFE_INTEGER; } /** * Checks if `value` is the * [language type](http://www.ecma-international.org/ecma-262/7.0/#sec-ecmascript-language-types) * of `Object`. (e.g. arrays, functions, objects, regexes, `new Number(0)`, and `new String('')`) * * @static * @memberOf _ * @since 0.1.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is an object, else `false`. * @example * * _.isObject({}); * // => true * * _.isObject([1, 2, 3]); * // => true * * _.isObject(_.noop); * // => true * * _.isObject(null); * // => false */ function isObject(value) { var type = typeof value; return value != null && (type == 'object' || type == 'function'); } /** * Checks if `value` is object-like. A value is object-like if it's not `null` * and has a `typeof` result of "object". * * @static * @memberOf _ * @since 4.0.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is object-like, else `false`. * @example * * _.isObjectLike({}); * // => true * * _.isObjectLike([1, 2, 3]); * // => true * * _.isObjectLike(_.noop); * // => false * * _.isObjectLike(null); * // => false */ function isObjectLike(value) { return value != null && typeof value == 'object'; } /** * Checks if `value` is classified as a `Map` object. * * @static * @memberOf _ * @since 4.3.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a map, else `false`. * @example * * _.isMap(new Map); * // => true * * _.isMap(new WeakMap); * // => false */ var isMap = nodeIsMap ? baseUnary(nodeIsMap) : baseIsMap; /** * Performs a partial deep comparison between `object` and `source` to * determine if `object` contains equivalent property values. * * **Note:** This method is equivalent to `_.matches` when `source` is * partially applied. * * Partial comparisons will match empty array and empty object `source` * values against any array or object value, respectively. See `_.isEqual` * for a list of supported value comparisons. * * @static * @memberOf _ * @since 3.0.0 * @category Lang * @param {Object} object The object to inspect. * @param {Object} source The object of property values to match. * @returns {boolean} Returns `true` if `object` is a match, else `false`. * @example * * var object = { 'a': 1, 'b': 2 }; * * _.isMatch(object, { 'b': 2 }); * // => true * * _.isMatch(object, { 'b': 1 }); * // => false */ function isMatch(object, source) { return object === source || baseIsMatch(object, source, getMatchData(source)); } /** * This method is like `_.isMatch` except that it accepts `customizer` which * is invoked to compare values. If `customizer` returns `undefined`, comparisons * are handled by the method instead. The `customizer` is invoked with five * arguments: (objValue, srcValue, index|key, object, source). * * @static * @memberOf _ * @since 4.0.0 * @category Lang * @param {Object} object The object to inspect. * @param {Object} source The object of property values to match. * @param {Function} [customizer] The function to customize comparisons. * @returns {boolean} Returns `true` if `object` is a match, else `false`. * @example * * function isGreeting(value) { * return /^h(?:i|ello)$/.test(value); * } * * function customizer(objValue, srcValue) { * if (isGreeting(objValue) && isGreeting(srcValue)) { * return true; * } * } * * var object = { 'greeting': 'hello' }; * var source = { 'greeting': 'hi' }; * * _.isMatchWith(object, source, customizer); * // => true */ function isMatchWith(object, source, customizer) { customizer = typeof customizer == 'function' ? customizer : undefined; return baseIsMatch(object, source, getMatchData(source), customizer); } /** * Checks if `value` is `NaN`. * * **Note:** This method is based on * [`Number.isNaN`](https://mdn.io/Number/isNaN) and is not the same as * global [`isNaN`](https://mdn.io/isNaN) which returns `true` for * `undefined` and other non-number values. * * @static * @memberOf _ * @since 0.1.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is `NaN`, else `false`. * @example * * _.isNaN(NaN); * // => true * * _.isNaN(new Number(NaN)); * // => true * * isNaN(undefined); * // => true * * _.isNaN(undefined); * // => false */ function isNaN(value) { // An `NaN` primitive is the only value that is not equal to itself. // Perform the `toStringTag` check first to avoid errors with some // ActiveX objects in IE. return isNumber(value) && value != +value; } /** * Checks if `value` is a pristine native function. * * **Note:** This method can't reliably detect native functions in the presence * of the core-js package because core-js circumvents this kind of detection. * Despite multiple requests, the core-js maintainer has made it clear: any * attempt to fix the detection will be obstructed. As a result, we're left * with little choice but to throw an error. Unfortunately, this also affects * packages, like [babel-polyfill](https://www.npmjs.com/package/babel-polyfill), * which rely on core-js. * * @static * @memberOf _ * @since 3.0.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a native function, * else `false`. * @example * * _.isNative(Array.prototype.push); * // => true * * _.isNative(_); * // => false */ function isNative(value) { if (isMaskable(value)) { throw new Error(CORE_ERROR_TEXT); } return baseIsNative(value); } /** * Checks if `value` is `null`. * * @static * @memberOf _ * @since 0.1.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is `null`, else `false`. * @example * * _.isNull(null); * // => true * * _.isNull(void 0); * // => false */ function isNull(value) { return value === null; } /** * Checks if `value` is `null` or `undefined`. * * @static * @memberOf _ * @since 4.0.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is nullish, else `false`. * @example * * _.isNil(null); * // => true * * _.isNil(void 0); * // => true * * _.isNil(NaN); * // => false */ function isNil(value) { return value == null; } /** * Checks if `value` is classified as a `Number` primitive or object. * * **Note:** To exclude `Infinity`, `-Infinity`, and `NaN`, which are * classified as numbers, use the `_.isFinite` method. * * @static * @memberOf _ * @since 0.1.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a number, else `false`. * @example * * _.isNumber(3); * // => true * * _.isNumber(Number.MIN_VALUE); * // => true * * _.isNumber(Infinity); * // => true * * _.isNumber('3'); * // => false */ function isNumber(value) { return typeof value == 'number' || (isObjectLike(value) && baseGetTag(value) == numberTag); } /** * Checks if `value` is a plain object, that is, an object created by the * `Object` constructor or one with a `[[Prototype]]` of `null`. * * @static * @memberOf _ * @since 0.8.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a plain object, else `false`. * @example * * function Foo() { * this.a = 1; * } * * _.isPlainObject(new Foo); * // => false * * _.isPlainObject([1, 2, 3]); * // => false * * _.isPlainObject({ 'x': 0, 'y': 0 }); * // => true * * _.isPlainObject(Object.create(null)); * // => true */ function isPlainObject(value) { if (!isObjectLike(value) || baseGetTag(value) != objectTag) { return false; } var proto = getPrototype(value); if (proto === null) { return true; } var Ctor = hasOwnProperty.call(proto, 'constructor') && proto.constructor; return typeof Ctor == 'function' && Ctor instanceof Ctor && funcToString.call(Ctor) == objectCtorString; } /** * Checks if `value` is classified as a `RegExp` object. * * @static * @memberOf _ * @since 0.1.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a regexp, else `false`. * @example * * _.isRegExp(/abc/); * // => true * * _.isRegExp('/abc/'); * // => false */ var isRegExp = nodeIsRegExp ? baseUnary(nodeIsRegExp) : baseIsRegExp; /** * Checks if `value` is a safe integer. An integer is safe if it's an IEEE-754 * double precision number which isn't the result of a rounded unsafe integer. * * **Note:** This method is based on * [`Number.isSafeInteger`](https://mdn.io/Number/isSafeInteger). * * @static * @memberOf _ * @since 4.0.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a safe integer, else `false`. * @example * * _.isSafeInteger(3); * // => true * * _.isSafeInteger(Number.MIN_VALUE); * // => false * * _.isSafeInteger(Infinity); * // => false * * _.isSafeInteger('3'); * // => false */ function isSafeInteger(value) { return isInteger(value) && value >= -MAX_SAFE_INTEGER && value <= MAX_SAFE_INTEGER; } /** * Checks if `value` is classified as a `Set` object. * * @static * @memberOf _ * @since 4.3.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a set, else `false`. * @example * * _.isSet(new Set); * // => true * * _.isSet(new WeakSet); * // => false */ var isSet = nodeIsSet ? baseUnary(nodeIsSet) : baseIsSet; /** * Checks if `value` is classified as a `String` primitive or object. * * @static * @since 0.1.0 * @memberOf _ * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a string, else `false`. * @example * * _.isString('abc'); * // => true * * _.isString(1); * // => false */ function isString(value) { return typeof value == 'string' || (!isArray(value) && isObjectLike(value) && baseGetTag(value) == stringTag); } /** * Checks if `value` is classified as a `Symbol` primitive or object. * * @static * @memberOf _ * @since 4.0.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a symbol, else `false`. * @example * * _.isSymbol(Symbol.iterator); * // => true * * _.isSymbol('abc'); * // => false */ function isSymbol(value) { return typeof value == 'symbol' || (isObjectLike(value) && baseGetTag(value) == symbolTag); } /** * Checks if `value` is classified as a typed array. * * @static * @memberOf _ * @since 3.0.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a typed array, else `false`. * @example * * _.isTypedArray(new Uint8Array); * // => true * * _.isTypedArray([]); * // => false */ var isTypedArray = nodeIsTypedArray ? baseUnary(nodeIsTypedArray) : baseIsTypedArray; /** * Checks if `value` is `undefined`. * * @static * @since 0.1.0 * @memberOf _ * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is `undefined`, else `false`. * @example * * _.isUndefined(void 0); * // => true * * _.isUndefined(null); * // => false */ function isUndefined(value) { return value === undefined; } /** * Checks if `value` is classified as a `WeakMap` object. * * @static * @memberOf _ * @since 4.3.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a weak map, else `false`. * @example * * _.isWeakMap(new WeakMap); * // => true * * _.isWeakMap(new Map); * // => false */ function isWeakMap(value) { return isObjectLike(value) && getTag(value) == weakMapTag; } /** * Checks if `value` is classified as a `WeakSet` object. * * @static * @memberOf _ * @since 4.3.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a weak set, else `false`. * @example * * _.isWeakSet(new WeakSet); * // => true * * _.isWeakSet(new Set); * // => false */ function isWeakSet(value) { return isObjectLike(value) && baseGetTag(value) == weakSetTag; } /** * Checks if `value` is less than `other`. * * @static * @memberOf _ * @since 3.9.0 * @category Lang * @param {*} value The value to compare. * @param {*} other The other value to compare. * @returns {boolean} Returns `true` if `value` is less than `other`, * else `false`. * @see _.gt * @example * * _.lt(1, 3); * // => true * * _.lt(3, 3); * // => false * * _.lt(3, 1); * // => false */ var lt = createRelationalOperation(baseLt); /** * Checks if `value` is less than or equal to `other`. * * @static * @memberOf _ * @since 3.9.0 * @category Lang * @param {*} value The value to compare. * @param {*} other The other value to compare. * @returns {boolean} Returns `true` if `value` is less than or equal to * `other`, else `false`. * @see _.gte * @example * * _.lte(1, 3); * // => true * * _.lte(3, 3); * // => true * * _.lte(3, 1); * // => false */ var lte = createRelationalOperation(function(value, other) { return value <= other; }); /** * Converts `value` to an array. * * @static * @since 0.1.0 * @memberOf _ * @category Lang * @param {*} value The value to convert. * @returns {Array} Returns the converted array. * @example * * _.toArray({ 'a': 1, 'b': 2 }); * // => [1, 2] * * _.toArray('abc'); * // => ['a', 'b', 'c'] * * _.toArray(1); * // => [] * * _.toArray(null); * // => [] */ function toArray(value) { if (!value) { return []; } if (isArrayLike(value)) { return isString(value) ? stringToArray(value) : copyArray(value); } if (symIterator && value[symIterator]) { return iteratorToArray(value[symIterator]()); } var tag = getTag(value), func = tag == mapTag ? mapToArray : (tag == setTag ? setToArray : values); return func(value); } /** * Converts `value` to a finite number. * * @static * @memberOf _ * @since 4.12.0 * @category Lang * @param {*} value The value to convert. * @returns {number} Returns the converted number. * @example * * _.toFinite(3.2); * // => 3.2 * * _.toFinite(Number.MIN_VALUE); * // => 5e-324 * * _.toFinite(Infinity); * // => 1.7976931348623157e+308 * * _.toFinite('3.2'); * // => 3.2 */ function toFinite(value) { if (!value) { return value === 0 ? value : 0; } value = toNumber(value); if (value === INFINITY || value === -INFINITY) { var sign = (value < 0 ? -1 : 1); return sign * MAX_INTEGER; } return value === value ? value : 0; } /** * Converts `value` to an integer. * * **Note:** This method is loosely based on * [`ToInteger`](http://www.ecma-international.org/ecma-262/7.0/#sec-tointeger). * * @static * @memberOf _ * @since 4.0.0 * @category Lang * @param {*} value The value to convert. * @returns {number} Returns the converted integer. * @example * * _.toInteger(3.2); * // => 3 * * _.toInteger(Number.MIN_VALUE); * // => 0 * * _.toInteger(Infinity); * // => 1.7976931348623157e+308 * * _.toInteger('3.2'); * // => 3 */ function toInteger(value) { var result = toFinite(value), remainder = result % 1; return result === result ? (remainder ? result - remainder : result) : 0; } /** * Converts `value` to an integer suitable for use as the length of an * array-like object. * * **Note:** This method is based on * [`ToLength`](http://ecma-international.org/ecma-262/7.0/#sec-tolength). * * @static * @memberOf _ * @since 4.0.0 * @category Lang * @param {*} value The value to convert. * @returns {number} Returns the converted integer. * @example * * _.toLength(3.2); * // => 3 * * _.toLength(Number.MIN_VALUE); * // => 0 * * _.toLength(Infinity); * // => 4294967295 * * _.toLength('3.2'); * // => 3 */ function toLength(value) { return value ? baseClamp(toInteger(value), 0, MAX_ARRAY_LENGTH) : 0; } /** * Converts `value` to a number. * * @static * @memberOf _ * @since 4.0.0 * @category Lang * @param {*} value The value to process. * @returns {number} Returns the number. * @example * * _.toNumber(3.2); * // => 3.2 * * _.toNumber(Number.MIN_VALUE); * // => 5e-324 * * _.toNumber(Infinity); * // => Infinity * * _.toNumber('3.2'); * // => 3.2 */ function toNumber(value) { if (typeof value == 'number') { return value; } if (isSymbol(value)) { return NAN; } if (isObject(value)) { var other = typeof value.valueOf == 'function' ? value.valueOf() : value; value = isObject(other) ? (other + '') : other; } if (typeof value != 'string') { return value === 0 ? value : +value; } value = value.replace(reTrim, ''); var isBinary = reIsBinary.test(value); return (isBinary || reIsOctal.test(value)) ? freeParseInt(value.slice(2), isBinary ? 2 : 8) : (reIsBadHex.test(value) ? NAN : +value); } /** * Converts `value` to a plain object flattening inherited enumerable string * keyed properties of `value` to own properties of the plain object. * * @static * @memberOf _ * @since 3.0.0 * @category Lang * @param {*} value The value to convert. * @returns {Object} Returns the converted plain object. * @example * * function Foo() { * this.b = 2; * } * * Foo.prototype.c = 3; * * _.assign({ 'a': 1 }, new Foo); * // => { 'a': 1, 'b': 2 } * * _.assign({ 'a': 1 }, _.toPlainObject(new Foo)); * // => { 'a': 1, 'b': 2, 'c': 3 } */ function toPlainObject(value) { return copyObject(value, keysIn(value)); } /** * Converts `value` to a safe integer. A safe integer can be compared and * represented correctly. * * @static * @memberOf _ * @since 4.0.0 * @category Lang * @param {*} value The value to convert. * @returns {number} Returns the converted integer. * @example * * _.toSafeInteger(3.2); * // => 3 * * _.toSafeInteger(Number.MIN_VALUE); * // => 0 * * _.toSafeInteger(Infinity); * // => 9007199254740991 * * _.toSafeInteger('3.2'); * // => 3 */ function toSafeInteger(value) { return value ? baseClamp(toInteger(value), -MAX_SAFE_INTEGER, MAX_SAFE_INTEGER) : (value === 0 ? value : 0); } /** * Converts `value` to a string. An empty string is returned for `null` * and `undefined` values. The sign of `-0` is preserved. * * @static * @memberOf _ * @since 4.0.0 * @category Lang * @param {*} value The value to convert. * @returns {string} Returns the converted string. * @example * * _.toString(null); * // => '' * * _.toString(-0); * // => '-0' * * _.toString([1, 2, 3]); * // => '1,2,3' */ function toString(value) { return value == null ? '' : baseToString(value); } /*------------------------------------------------------------------------*/ /** * Assigns own enumerable string keyed properties of source objects to the * destination object. Source objects are applied from left to right. * Subsequent sources overwrite property assignments of previous sources. * * **Note:** This method mutates `object` and is loosely based on * [`Object.assign`](https://mdn.io/Object/assign). * * @static * @memberOf _ * @since 0.10.0 * @category Object * @param {Object} object The destination object. * @param {...Object} [sources] The source objects. * @returns {Object} Returns `object`. * @see _.assignIn * @example * * function Foo() { * this.a = 1; * } * * function Bar() { * this.c = 3; * } * * Foo.prototype.b = 2; * Bar.prototype.d = 4; * * _.assign({ 'a': 0 }, new Foo, new Bar); * // => { 'a': 1, 'c': 3 } */ var assign = createAssigner(function(object, source) { if (isPrototype(source) || isArrayLike(source)) { copyObject(source, keys(source), object); return; } for (var key in source) { if (hasOwnProperty.call(source, key)) { assignValue(object, key, source[key]); } } }); /** * This method is like `_.assign` except that it iterates over own and * inherited source properties. * * **Note:** This method mutates `object`. * * @static * @memberOf _ * @since 4.0.0 * @alias extend * @category Object * @param {Object} object The destination object. * @param {...Object} [sources] The source objects. * @returns {Object} Returns `object`. * @see _.assign * @example * * function Foo() { * this.a = 1; * } * * function Bar() { * this.c = 3; * } * * Foo.prototype.b = 2; * Bar.prototype.d = 4; * * _.assignIn({ 'a': 0 }, new Foo, new Bar); * // => { 'a': 1, 'b': 2, 'c': 3, 'd': 4 } */ var assignIn = createAssigner(function(object, source) { copyObject(source, keysIn(source), object); }); /** * This method is like `_.assignIn` except that it accepts `customizer` * which is invoked to produce the assigned values. If `customizer` returns * `undefined`, assignment is handled by the method instead. The `customizer` * is invoked with five arguments: (objValue, srcValue, key, object, source). * * **Note:** This method mutates `object`. * * @static * @memberOf _ * @since 4.0.0 * @alias extendWith * @category Object * @param {Object} object The destination object. * @param {...Object} sources The source objects. * @param {Function} [customizer] The function to customize assigned values. * @returns {Object} Returns `object`. * @see _.assignWith * @example * * function customizer(objValue, srcValue) { * return _.isUndefined(objValue) ? srcValue : objValue; * } * * var defaults = _.partialRight(_.assignInWith, customizer); * * defaults({ 'a': 1 }, { 'b': 2 }, { 'a': 3 }); * // => { 'a': 1, 'b': 2 } */ var assignInWith = createAssigner(function(object, source, srcIndex, customizer) { copyObject(source, keysIn(source), object, customizer); }); /** * This method is like `_.assign` except that it accepts `customizer` * which is invoked to produce the assigned values. If `customizer` returns * `undefined`, assignment is handled by the method instead. The `customizer` * is invoked with five arguments: (objValue, srcValue, key, object, source). * * **Note:** This method mutates `object`. * * @static * @memberOf _ * @since 4.0.0 * @category Object * @param {Object} object The destination object. * @param {...Object} sources The source objects. * @param {Function} [customizer] The function to customize assigned values. * @returns {Object} Returns `object`. * @see _.assignInWith * @example * * function customizer(objValue, srcValue) { * return _.isUndefined(objValue) ? srcValue : objValue; * } * * var defaults = _.partialRight(_.assignWith, customizer); * * defaults({ 'a': 1 }, { 'b': 2 }, { 'a': 3 }); * // => { 'a': 1, 'b': 2 } */ var assignWith = createAssigner(function(object, source, srcIndex, customizer) { copyObject(source, keys(source), object, customizer); }); /** * Creates an array of values corresponding to `paths` of `object`. * * @static * @memberOf _ * @since 1.0.0 * @category Object * @param {Object} object The object to iterate over. * @param {...(string|string[])} [paths] The property paths to pick. * @returns {Array} Returns the picked values. * @example * * var object = { 'a': [{ 'b': { 'c': 3 } }, 4] }; * * _.at(object, ['a[0].b.c', 'a[1]']); * // => [3, 4] */ var at = flatRest(baseAt); /** * Creates an object that inherits from the `prototype` object. If a * `properties` object is given, its own enumerable string keyed properties * are assigned to the created object. * * @static * @memberOf _ * @since 2.3.0 * @category Object * @param {Object} prototype The object to inherit from. * @param {Object} [properties] The properties to assign to the object. * @returns {Object} Returns the new object. * @example * * function Shape() { * this.x = 0; * this.y = 0; * } * * function Circle() { * Shape.call(this); * } * * Circle.prototype = _.create(Shape.prototype, { * 'constructor': Circle * }); * * var circle = new Circle; * circle instanceof Circle; * // => true * * circle instanceof Shape; * // => true */ function create(prototype, properties) { var result = baseCreate(prototype); return properties == null ? result : baseAssign(result, properties); } /** * Assigns own and inherited enumerable string keyed properties of source * objects to the destination object for all destination properties that * resolve to `undefined`. Source objects are applied from left to right. * Once a property is set, additional values of the same property are ignored. * * **Note:** This method mutates `object`. * * @static * @since 0.1.0 * @memberOf _ * @category Object * @param {Object} object The destination object. * @param {...Object} [sources] The source objects. * @returns {Object} Returns `object`. * @see _.defaultsDeep * @example * * _.defaults({ 'a': 1 }, { 'b': 2 }, { 'a': 3 }); * // => { 'a': 1, 'b': 2 } */ var defaults = baseRest(function(object, sources) { object = Object(object); var index = -1; var length = sources.length; var guard = length > 2 ? sources[2] : undefined; if (guard && isIterateeCall(sources[0], sources[1], guard)) { length = 1; } while (++index < length) { var source = sources[index]; var props = keysIn(source); var propsIndex = -1; var propsLength = props.length; while (++propsIndex < propsLength) { var key = props[propsIndex]; var value = object[key]; if (value === undefined || (eq(value, objectProto[key]) && !hasOwnProperty.call(object, key))) { object[key] = source[key]; } } } return object; }); /** * This method is like `_.defaults` except that it recursively assigns * default properties. * * **Note:** This method mutates `object`. * * @static * @memberOf _ * @since 3.10.0 * @category Object * @param {Object} object The destination object. * @param {...Object} [sources] The source objects. * @returns {Object} Returns `object`. * @see _.defaults * @example * * _.defaultsDeep({ 'a': { 'b': 2 } }, { 'a': { 'b': 1, 'c': 3 } }); * // => { 'a': { 'b': 2, 'c': 3 } } */ var defaultsDeep = baseRest(function(args) { args.push(undefined, customDefaultsMerge); return apply(mergeWith, undefined, args); }); /** * This method is like `_.find` except that it returns the key of the first * element `predicate` returns truthy for instead of the element itself. * * @static * @memberOf _ * @since 1.1.0 * @category Object * @param {Object} object The object to inspect. * @param {Function} [predicate=_.identity] The function invoked per iteration. * @returns {string|undefined} Returns the key of the matched element, * else `undefined`. * @example * * var users = { * 'barney': { 'age': 36, 'active': true }, * 'fred': { 'age': 40, 'active': false }, * 'pebbles': { 'age': 1, 'active': true } * }; * * _.findKey(users, function(o) { return o.age < 40; }); * // => 'barney' (iteration order is not guaranteed) * * // The `_.matches` iteratee shorthand. * _.findKey(users, { 'age': 1, 'active': true }); * // => 'pebbles' * * // The `_.matchesProperty` iteratee shorthand. * _.findKey(users, ['active', false]); * // => 'fred' * * // The `_.property` iteratee shorthand. * _.findKey(users, 'active'); * // => 'barney' */ function findKey(object, predicate) { return baseFindKey(object, getIteratee(predicate, 3), baseForOwn); } /** * This method is like `_.findKey` except that it iterates over elements of * a collection in the opposite order. * * @static * @memberOf _ * @since 2.0.0 * @category Object * @param {Object} object The object to inspect. * @param {Function} [predicate=_.identity] The function invoked per iteration. * @returns {string|undefined} Returns the key of the matched element, * else `undefined`. * @example * * var users = { * 'barney': { 'age': 36, 'active': true }, * 'fred': { 'age': 40, 'active': false }, * 'pebbles': { 'age': 1, 'active': true } * }; * * _.findLastKey(users, function(o) { return o.age < 40; }); * // => returns 'pebbles' assuming `_.findKey` returns 'barney' * * // The `_.matches` iteratee shorthand. * _.findLastKey(users, { 'age': 36, 'active': true }); * // => 'barney' * * // The `_.matchesProperty` iteratee shorthand. * _.findLastKey(users, ['active', false]); * // => 'fred' * * // The `_.property` iteratee shorthand. * _.findLastKey(users, 'active'); * // => 'pebbles' */ function findLastKey(object, predicate) { return baseFindKey(object, getIteratee(predicate, 3), baseForOwnRight); } /** * Iterates over own and inherited enumerable string keyed properties of an * object and invokes `iteratee` for each property. The iteratee is invoked * with three arguments: (value, key, object). Iteratee functions may exit * iteration early by explicitly returning `false`. * * @static * @memberOf _ * @since 0.3.0 * @category Object * @param {Object} object The object to iterate over. * @param {Function} [iteratee=_.identity] The function invoked per iteration. * @returns {Object} Returns `object`. * @see _.forInRight * @example * * function Foo() { * this.a = 1; * this.b = 2; * } * * Foo.prototype.c = 3; * * _.forIn(new Foo, function(value, key) { * console.log(key); * }); * // => Logs 'a', 'b', then 'c' (iteration order is not guaranteed). */ function forIn(object, iteratee) { return object == null ? object : baseFor(object, getIteratee(iteratee, 3), keysIn); } /** * This method is like `_.forIn` except that it iterates over properties of * `object` in the opposite order. * * @static * @memberOf _ * @since 2.0.0 * @category Object * @param {Object} object The object to iterate over. * @param {Function} [iteratee=_.identity] The function invoked per iteration. * @returns {Object} Returns `object`. * @see _.forIn * @example * * function Foo() { * this.a = 1; * this.b = 2; * } * * Foo.prototype.c = 3; * * _.forInRight(new Foo, function(value, key) { * console.log(key); * }); * // => Logs 'c', 'b', then 'a' assuming `_.forIn` logs 'a', 'b', then 'c'. */ function forInRight(object, iteratee) { return object == null ? object : baseForRight(object, getIteratee(iteratee, 3), keysIn); } /** * Iterates over own enumerable string keyed properties of an object and * invokes `iteratee` for each property. The iteratee is invoked with three * arguments: (value, key, object). Iteratee functions may exit iteration * early by explicitly returning `false`. * * @static * @memberOf _ * @since 0.3.0 * @category Object * @param {Object} object The object to iterate over. * @param {Function} [iteratee=_.identity] The function invoked per iteration. * @returns {Object} Returns `object`. * @see _.forOwnRight * @example * * function Foo() { * this.a = 1; * this.b = 2; * } * * Foo.prototype.c = 3; * * _.forOwn(new Foo, function(value, key) { * console.log(key); * }); * // => Logs 'a' then 'b' (iteration order is not guaranteed). */ function forOwn(object, iteratee) { return object && baseForOwn(object, getIteratee(iteratee, 3)); } /** * This method is like `_.forOwn` except that it iterates over properties of * `object` in the opposite order. * * @static * @memberOf _ * @since 2.0.0 * @category Object * @param {Object} object The object to iterate over. * @param {Function} [iteratee=_.identity] The function invoked per iteration. * @returns {Object} Returns `object`. * @see _.forOwn * @example * * function Foo() { * this.a = 1; * this.b = 2; * } * * Foo.prototype.c = 3; * * _.forOwnRight(new Foo, function(value, key) { * console.log(key); * }); * // => Logs 'b' then 'a' assuming `_.forOwn` logs 'a' then 'b'. */ function forOwnRight(object, iteratee) { return object && baseForOwnRight(object, getIteratee(iteratee, 3)); } /** * Creates an array of function property names from own enumerable properties * of `object`. * * @static * @since 0.1.0 * @memberOf _ * @category Object * @param {Object} object The object to inspect. * @returns {Array} Returns the function names. * @see _.functionsIn * @example * * function Foo() { * this.a = _.constant('a'); * this.b = _.constant('b'); * } * * Foo.prototype.c = _.constant('c'); * * _.functions(new Foo); * // => ['a', 'b'] */ function functions(object) { return object == null ? [] : baseFunctions(object, keys(object)); } /** * Creates an array of function property names from own and inherited * enumerable properties of `object`. * * @static * @memberOf _ * @since 4.0.0 * @category Object * @param {Object} object The object to inspect. * @returns {Array} Returns the function names. * @see _.functions * @example * * function Foo() { * this.a = _.constant('a'); * this.b = _.constant('b'); * } * * Foo.prototype.c = _.constant('c'); * * _.functionsIn(new Foo); * // => ['a', 'b', 'c'] */ function functionsIn(object) { return object == null ? [] : baseFunctions(object, keysIn(object)); } /** * Gets the value at `path` of `object`. If the resolved value is * `undefined`, the `defaultValue` is returned in its place. * * @static * @memberOf _ * @since 3.7.0 * @category Object * @param {Object} object The object to query. * @param {Array|string} path The path of the property to get. * @param {*} [defaultValue] The value returned for `undefined` resolved values. * @returns {*} Returns the resolved value. * @example * * var object = { 'a': [{ 'b': { 'c': 3 } }] }; * * _.get(object, 'a[0].b.c'); * // => 3 * * _.get(object, ['a', '0', 'b', 'c']); * // => 3 * * _.get(object, 'a.b.c', 'default'); * // => 'default' */ function get(object, path, defaultValue) { var result = object == null ? undefined : baseGet(object, path); return result === undefined ? defaultValue : result; } /** * Checks if `path` is a direct property of `object`. * * @static * @since 0.1.0 * @memberOf _ * @category Object * @param {Object} object The object to query. * @param {Array|string} path The path to check. * @returns {boolean} Returns `true` if `path` exists, else `false`. * @example * * var object = { 'a': { 'b': 2 } }; * var other = _.create({ 'a': _.create({ 'b': 2 }) }); * * _.has(object, 'a'); * // => true * * _.has(object, 'a.b'); * // => true * * _.has(object, ['a', 'b']); * // => true * * _.has(other, 'a'); * // => false */ function has(object, path) { return object != null && hasPath(object, path, baseHas); } /** * Checks if `path` is a direct or inherited property of `object`. * * @static * @memberOf _ * @since 4.0.0 * @category Object * @param {Object} object The object to query. * @param {Array|string} path The path to check. * @returns {boolean} Returns `true` if `path` exists, else `false`. * @example * * var object = _.create({ 'a': _.create({ 'b': 2 }) }); * * _.hasIn(object, 'a'); * // => true * * _.hasIn(object, 'a.b'); * // => true * * _.hasIn(object, ['a', 'b']); * // => true * * _.hasIn(object, 'b'); * // => false */ function hasIn(object, path) { return object != null && hasPath(object, path, baseHasIn); } /** * Creates an object composed of the inverted keys and values of `object`. * If `object` contains duplicate values, subsequent values overwrite * property assignments of previous values. * * @static * @memberOf _ * @since 0.7.0 * @category Object * @param {Object} object The object to invert. * @returns {Object} Returns the new inverted object. * @example * * var object = { 'a': 1, 'b': 2, 'c': 1 }; * * _.invert(object); * // => { '1': 'c', '2': 'b' } */ var invert = createInverter(function(result, value, key) { if (value != null && typeof value.toString != 'function') { value = nativeObjectToString.call(value); } result[value] = key; }, constant(identity)); /** * This method is like `_.invert` except that the inverted object is generated * from the results of running each element of `object` thru `iteratee`. The * corresponding inverted value of each inverted key is an array of keys * responsible for generating the inverted value. The iteratee is invoked * with one argument: (value). * * @static * @memberOf _ * @since 4.1.0 * @category Object * @param {Object} object The object to invert. * @param {Function} [iteratee=_.identity] The iteratee invoked per element. * @returns {Object} Returns the new inverted object. * @example * * var object = { 'a': 1, 'b': 2, 'c': 1 }; * * _.invertBy(object); * // => { '1': ['a', 'c'], '2': ['b'] } * * _.invertBy(object, function(value) { * return 'group' + value; * }); * // => { 'group1': ['a', 'c'], 'group2': ['b'] } */ var invertBy = createInverter(function(result, value, key) { if (value != null && typeof value.toString != 'function') { value = nativeObjectToString.call(value); } if (hasOwnProperty.call(result, value)) { result[value].push(key); } else { result[value] = [key]; } }, getIteratee); /** * Invokes the method at `path` of `object`. * * @static * @memberOf _ * @since 4.0.0 * @category Object * @param {Object} object The object to query. * @param {Array|string} path The path of the method to invoke. * @param {...*} [args] The arguments to invoke the method with. * @returns {*} Returns the result of the invoked method. * @example * * var object = { 'a': [{ 'b': { 'c': [1, 2, 3, 4] } }] }; * * _.invoke(object, 'a[0].b.c.slice', 1, 3); * // => [2, 3] */ var invoke = baseRest(baseInvoke); /** * Creates an array of the own enumerable property names of `object`. * * **Note:** Non-object values are coerced to objects. See the * [ES spec](http://ecma-international.org/ecma-262/7.0/#sec-object.keys) * for more details. * * @static * @since 0.1.0 * @memberOf _ * @category Object * @param {Object} object The object to query. * @returns {Array} Returns the array of property names. * @example * * function Foo() { * this.a = 1; * this.b = 2; * } * * Foo.prototype.c = 3; * * _.keys(new Foo); * // => ['a', 'b'] (iteration order is not guaranteed) * * _.keys('hi'); * // => ['0', '1'] */ function keys(object) { return isArrayLike(object) ? arrayLikeKeys(object) : baseKeys(object); } /** * Creates an array of the own and inherited enumerable property names of `object`. * * **Note:** Non-object values are coerced to objects. * * @static * @memberOf _ * @since 3.0.0 * @category Object * @param {Object} object The object to query. * @returns {Array} Returns the array of property names. * @example * * function Foo() { * this.a = 1; * this.b = 2; * } * * Foo.prototype.c = 3; * * _.keysIn(new Foo); * // => ['a', 'b', 'c'] (iteration order is not guaranteed) */ function keysIn(object) { return isArrayLike(object) ? arrayLikeKeys(object, true) : baseKeysIn(object); } /** * The opposite of `_.mapValues`; this method creates an object with the * same values as `object` and keys generated by running each own enumerable * string keyed property of `object` thru `iteratee`. The iteratee is invoked * with three arguments: (value, key, object). * * @static * @memberOf _ * @since 3.8.0 * @category Object * @param {Object} object The object to iterate over. * @param {Function} [iteratee=_.identity] The function invoked per iteration. * @returns {Object} Returns the new mapped object. * @see _.mapValues * @example * * _.mapKeys({ 'a': 1, 'b': 2 }, function(value, key) { * return key + value; * }); * // => { 'a1': 1, 'b2': 2 } */ function mapKeys(object, iteratee) { var result = {}; iteratee = getIteratee(iteratee, 3); baseForOwn(object, function(value, key, object) { baseAssignValue(result, iteratee(value, key, object), value); }); return result; } /** * Creates an object with the same keys as `object` and values generated * by running each own enumerable string keyed property of `object` thru * `iteratee`. The iteratee is invoked with three arguments: * (value, key, object). * * @static * @memberOf _ * @since 2.4.0 * @category Object * @param {Object} object The object to iterate over. * @param {Function} [iteratee=_.identity] The function invoked per iteration. * @returns {Object} Returns the new mapped object. * @see _.mapKeys * @example * * var users = { * 'fred': { 'user': 'fred', 'age': 40 }, * 'pebbles': { 'user': 'pebbles', 'age': 1 } * }; * * _.mapValues(users, function(o) { return o.age; }); * // => { 'fred': 40, 'pebbles': 1 } (iteration order is not guaranteed) * * // The `_.property` iteratee shorthand. * _.mapValues(users, 'age'); * // => { 'fred': 40, 'pebbles': 1 } (iteration order is not guaranteed) */ function mapValues(object, iteratee) { var result = {}; iteratee = getIteratee(iteratee, 3); baseForOwn(object, function(value, key, object) { baseAssignValue(result, key, iteratee(value, key, object)); }); return result; } /** * This method is like `_.assign` except that it recursively merges own and * inherited enumerable string keyed properties of source objects into the * destination object. Source properties that resolve to `undefined` are * skipped if a destination value exists. Array and plain object properties * are merged recursively. Other objects and value types are overridden by * assignment. Source objects are applied from left to right. Subsequent * sources overwrite property assignments of previous sources. * * **Note:** This method mutates `object`. * * @static * @memberOf _ * @since 0.5.0 * @category Object * @param {Object} object The destination object. * @param {...Object} [sources] The source objects. * @returns {Object} Returns `object`. * @example * * var object = { * 'a': [{ 'b': 2 }, { 'd': 4 }] * }; * * var other = { * 'a': [{ 'c': 3 }, { 'e': 5 }] * }; * * _.merge(object, other); * // => { 'a': [{ 'b': 2, 'c': 3 }, { 'd': 4, 'e': 5 }] } */ var merge = createAssigner(function(object, source, srcIndex) { baseMerge(object, source, srcIndex); }); /** * This method is like `_.merge` except that it accepts `customizer` which * is invoked to produce the merged values of the destination and source * properties. If `customizer` returns `undefined`, merging is handled by the * method instead. The `customizer` is invoked with six arguments: * (objValue, srcValue, key, object, source, stack). * * **Note:** This method mutates `object`. * * @static * @memberOf _ * @since 4.0.0 * @category Object * @param {Object} object The destination object. * @param {...Object} sources The source objects. * @param {Function} customizer The function to customize assigned values. * @returns {Object} Returns `object`. * @example * * function customizer(objValue, srcValue) { * if (_.isArray(objValue)) { * return objValue.concat(srcValue); * } * } * * var object = { 'a': [1], 'b': [2] }; * var other = { 'a': [3], 'b': [4] }; * * _.mergeWith(object, other, customizer); * // => { 'a': [1, 3], 'b': [2, 4] } */ var mergeWith = createAssigner(function(object, source, srcIndex, customizer) { baseMerge(object, source, srcIndex, customizer); }); /** * The opposite of `_.pick`; this method creates an object composed of the * own and inherited enumerable property paths of `object` that are not omitted. * * **Note:** This method is considerably slower than `_.pick`. * * @static * @since 0.1.0 * @memberOf _ * @category Object * @param {Object} object The source object. * @param {...(string|string[])} [paths] The property paths to omit. * @returns {Object} Returns the new object. * @example * * var object = { 'a': 1, 'b': '2', 'c': 3 }; * * _.omit(object, ['a', 'c']); * // => { 'b': '2' } */ var omit = flatRest(function(object, paths) { var result = {}; if (object == null) { return result; } var isDeep = false; paths = arrayMap(paths, function(path) { path = castPath(path, object); isDeep || (isDeep = path.length > 1); return path; }); copyObject(object, getAllKeysIn(object), result); if (isDeep) { result = baseClone(result, CLONE_DEEP_FLAG | CLONE_FLAT_FLAG | CLONE_SYMBOLS_FLAG, customOmitClone); } var length = paths.length; while (length--) { baseUnset(result, paths[length]); } return result; }); /** * The opposite of `_.pickBy`; this method creates an object composed of * the own and inherited enumerable string keyed properties of `object` that * `predicate` doesn't return truthy for. The predicate is invoked with two * arguments: (value, key). * * @static * @memberOf _ * @since 4.0.0 * @category Object * @param {Object} object The source object. * @param {Function} [predicate=_.identity] The function invoked per property. * @returns {Object} Returns the new object. * @example * * var object = { 'a': 1, 'b': '2', 'c': 3 }; * * _.omitBy(object, _.isNumber); * // => { 'b': '2' } */ function omitBy(object, predicate) { return pickBy(object, negate(getIteratee(predicate))); } /** * Creates an object composed of the picked `object` properties. * * @static * @since 0.1.0 * @memberOf _ * @category Object * @param {Object} object The source object. * @param {...(string|string[])} [paths] The property paths to pick. * @returns {Object} Returns the new object. * @example * * var object = { 'a': 1, 'b': '2', 'c': 3 }; * * _.pick(object, ['a', 'c']); * // => { 'a': 1, 'c': 3 } */ var pick = flatRest(function(object, paths) { return object == null ? {} : basePick(object, paths); }); /** * Creates an object composed of the `object` properties `predicate` returns * truthy for. The predicate is invoked with two arguments: (value, key). * * @static * @memberOf _ * @since 4.0.0 * @category Object * @param {Object} object The source object. * @param {Function} [predicate=_.identity] The function invoked per property. * @returns {Object} Returns the new object. * @example * * var object = { 'a': 1, 'b': '2', 'c': 3 }; * * _.pickBy(object, _.isNumber); * // => { 'a': 1, 'c': 3 } */ function pickBy(object, predicate) { if (object == null) { return {}; } var props = arrayMap(getAllKeysIn(object), function(prop) { return [prop]; }); predicate = getIteratee(predicate); return basePickBy(object, props, function(value, path) { return predicate(value, path[0]); }); } /** * This method is like `_.get` except that if the resolved value is a * function it's invoked with the `this` binding of its parent object and * its result is returned. * * @static * @since 0.1.0 * @memberOf _ * @category Object * @param {Object} object The object to query. * @param {Array|string} path The path of the property to resolve. * @param {*} [defaultValue] The value returned for `undefined` resolved values. * @returns {*} Returns the resolved value. * @example * * var object = { 'a': [{ 'b': { 'c1': 3, 'c2': _.constant(4) } }] }; * * _.result(object, 'a[0].b.c1'); * // => 3 * * _.result(object, 'a[0].b.c2'); * // => 4 * * _.result(object, 'a[0].b.c3', 'default'); * // => 'default' * * _.result(object, 'a[0].b.c3', _.constant('default')); * // => 'default' */ function result(object, path, defaultValue) { path = castPath(path, object); var index = -1, length = path.length; // Ensure the loop is entered when path is empty. if (!length) { length = 1; object = undefined; } while (++index < length) { var value = object == null ? undefined : object[toKey(path[index])]; if (value === undefined) { index = length; value = defaultValue; } object = isFunction(value) ? value.call(object) : value; } return object; } /** * Sets the value at `path` of `object`. If a portion of `path` doesn't exist, * it's created. Arrays are created for missing index properties while objects * are created for all other missing properties. Use `_.setWith` to customize * `path` creation. * * **Note:** This method mutates `object`. * * @static * @memberOf _ * @since 3.7.0 * @category Object * @param {Object} object The object to modify. * @param {Array|string} path The path of the property to set. * @param {*} value The value to set. * @returns {Object} Returns `object`. * @example * * var object = { 'a': [{ 'b': { 'c': 3 } }] }; * * _.set(object, 'a[0].b.c', 4); * console.log(object.a[0].b.c); * // => 4 * * _.set(object, ['x', '0', 'y', 'z'], 5); * console.log(object.x[0].y.z); * // => 5 */ function set(object, path, value) { return object == null ? object : baseSet(object, path, value); } /** * This method is like `_.set` except that it accepts `customizer` which is * invoked to produce the objects of `path`. If `customizer` returns `undefined` * path creation is handled by the method instead. The `customizer` is invoked * with three arguments: (nsValue, key, nsObject). * * **Note:** This method mutates `object`. * * @static * @memberOf _ * @since 4.0.0 * @category Object * @param {Object} object The object to modify. * @param {Array|string} path The path of the property to set. * @param {*} value The value to set. * @param {Function} [customizer] The function to customize assigned values. * @returns {Object} Returns `object`. * @example * * var object = {}; * * _.setWith(object, '[0][1]', 'a', Object); * // => { '0': { '1': 'a' } } */ function setWith(object, path, value, customizer) { customizer = typeof customizer == 'function' ? customizer : undefined; return object == null ? object : baseSet(object, path, value, customizer); } /** * Creates an array of own enumerable string keyed-value pairs for `object` * which can be consumed by `_.fromPairs`. If `object` is a map or set, its * entries are returned. * * @static * @memberOf _ * @since 4.0.0 * @alias entries * @category Object * @param {Object} object The object to query. * @returns {Array} Returns the key-value pairs. * @example * * function Foo() { * this.a = 1; * this.b = 2; * } * * Foo.prototype.c = 3; * * _.toPairs(new Foo); * // => [['a', 1], ['b', 2]] (iteration order is not guaranteed) */ var toPairs = createToPairs(keys); /** * Creates an array of own and inherited enumerable string keyed-value pairs * for `object` which can be consumed by `_.fromPairs`. If `object` is a map * or set, its entries are returned. * * @static * @memberOf _ * @since 4.0.0 * @alias entriesIn * @category Object * @param {Object} object The object to query. * @returns {Array} Returns the key-value pairs. * @example * * function Foo() { * this.a = 1; * this.b = 2; * } * * Foo.prototype.c = 3; * * _.toPairsIn(new Foo); * // => [['a', 1], ['b', 2], ['c', 3]] (iteration order is not guaranteed) */ var toPairsIn = createToPairs(keysIn); /** * An alternative to `_.reduce`; this method transforms `object` to a new * `accumulator` object which is the result of running each of its own * enumerable string keyed properties thru `iteratee`, with each invocation * potentially mutating the `accumulator` object. If `accumulator` is not * provided, a new object with the same `[[Prototype]]` will be used. The * iteratee is invoked with four arguments: (accumulator, value, key, object). * Iteratee functions may exit iteration early by explicitly returning `false`. * * @static * @memberOf _ * @since 1.3.0 * @category Object * @param {Object} object The object to iterate over. * @param {Function} [iteratee=_.identity] The function invoked per iteration. * @param {*} [accumulator] The custom accumulator value. * @returns {*} Returns the accumulated value. * @example * * _.transform([2, 3, 4], function(result, n) { * result.push(n *= n); * return n % 2 == 0; * }, []); * // => [4, 9] * * _.transform({ 'a': 1, 'b': 2, 'c': 1 }, function(result, value, key) { * (result[value] || (result[value] = [])).push(key); * }, {}); * // => { '1': ['a', 'c'], '2': ['b'] } */ function transform(object, iteratee, accumulator) { var isArr = isArray(object), isArrLike = isArr || isBuffer(object) || isTypedArray(object); iteratee = getIteratee(iteratee, 4); if (accumulator == null) { var Ctor = object && object.constructor; if (isArrLike) { accumulator = isArr ? new Ctor : []; } else if (isObject(object)) { accumulator = isFunction(Ctor) ? baseCreate(getPrototype(object)) : {}; } else { accumulator = {}; } } (isArrLike ? arrayEach : baseForOwn)(object, function(value, index, object) { return iteratee(accumulator, value, index, object); }); return accumulator; } /** * Removes the property at `path` of `object`. * * **Note:** This method mutates `object`. * * @static * @memberOf _ * @since 4.0.0 * @category Object * @param {Object} object The object to modify. * @param {Array|string} path The path of the property to unset. * @returns {boolean} Returns `true` if the property is deleted, else `false`. * @example * * var object = { 'a': [{ 'b': { 'c': 7 } }] }; * _.unset(object, 'a[0].b.c'); * // => true * * console.log(object); * // => { 'a': [{ 'b': {} }] }; * * _.unset(object, ['a', '0', 'b', 'c']); * // => true * * console.log(object); * // => { 'a': [{ 'b': {} }] }; */ function unset(object, path) { return object == null ? true : baseUnset(object, path); } /** * This method is like `_.set` except that accepts `updater` to produce the * value to set. Use `_.updateWith` to customize `path` creation. The `updater` * is invoked with one argument: (value). * * **Note:** This method mutates `object`. * * @static * @memberOf _ * @since 4.6.0 * @category Object * @param {Object} object The object to modify. * @param {Array|string} path The path of the property to set. * @param {Function} updater The function to produce the updated value. * @returns {Object} Returns `object`. * @example * * var object = { 'a': [{ 'b': { 'c': 3 } }] }; * * _.update(object, 'a[0].b.c', function(n) { return n * n; }); * console.log(object.a[0].b.c); * // => 9 * * _.update(object, 'x[0].y.z', function(n) { return n ? n + 1 : 0; }); * console.log(object.x[0].y.z); * // => 0 */ function update(object, path, updater) { return object == null ? object : baseUpdate(object, path, castFunction(updater)); } /** * This method is like `_.update` except that it accepts `customizer` which is * invoked to produce the objects of `path`. If `customizer` returns `undefined` * path creation is handled by the method instead. The `customizer` is invoked * with three arguments: (nsValue, key, nsObject). * * **Note:** This method mutates `object`. * * @static * @memberOf _ * @since 4.6.0 * @category Object * @param {Object} object The object to modify. * @param {Array|string} path The path of the property to set. * @param {Function} updater The function to produce the updated value. * @param {Function} [customizer] The function to customize assigned values. * @returns {Object} Returns `object`. * @example * * var object = {}; * * _.updateWith(object, '[0][1]', _.constant('a'), Object); * // => { '0': { '1': 'a' } } */ function updateWith(object, path, updater, customizer) { customizer = typeof customizer == 'function' ? customizer : undefined; return object == null ? object : baseUpdate(object, path, castFunction(updater), customizer); } /** * Creates an array of the own enumerable string keyed property values of `object`. * * **Note:** Non-object values are coerced to objects. * * @static * @since 0.1.0 * @memberOf _ * @category Object * @param {Object} object The object to query. * @returns {Array} Returns the array of property values. * @example * * function Foo() { * this.a = 1; * this.b = 2; * } * * Foo.prototype.c = 3; * * _.values(new Foo); * // => [1, 2] (iteration order is not guaranteed) * * _.values('hi'); * // => ['h', 'i'] */ function values(object) { return object == null ? [] : baseValues(object, keys(object)); } /** * Creates an array of the own and inherited enumerable string keyed property * values of `object`. * * **Note:** Non-object values are coerced to objects. * * @static * @memberOf _ * @since 3.0.0 * @category Object * @param {Object} object The object to query. * @returns {Array} Returns the array of property values. * @example * * function Foo() { * this.a = 1; * this.b = 2; * } * * Foo.prototype.c = 3; * * _.valuesIn(new Foo); * // => [1, 2, 3] (iteration order is not guaranteed) */ function valuesIn(object) { return object == null ? [] : baseValues(object, keysIn(object)); } /*------------------------------------------------------------------------*/ /** * Clamps `number` within the inclusive `lower` and `upper` bounds. * * @static * @memberOf _ * @since 4.0.0 * @category Number * @param {number} number The number to clamp. * @param {number} [lower] The lower bound. * @param {number} upper The upper bound. * @returns {number} Returns the clamped number. * @example * * _.clamp(-10, -5, 5); * // => -5 * * _.clamp(10, -5, 5); * // => 5 */ function clamp(number, lower, upper) { if (upper === undefined) { upper = lower; lower = undefined; } if (upper !== undefined) { upper = toNumber(upper); upper = upper === upper ? upper : 0; } if (lower !== undefined) { lower = toNumber(lower); lower = lower === lower ? lower : 0; } return baseClamp(toNumber(number), lower, upper); } /** * Checks if `n` is between `start` and up to, but not including, `end`. If * `end` is not specified, it's set to `start` with `start` then set to `0`. * If `start` is greater than `end` the params are swapped to support * negative ranges. * * @static * @memberOf _ * @since 3.3.0 * @category Number * @param {number} number The number to check. * @param {number} [start=0] The start of the range. * @param {number} end The end of the range. * @returns {boolean} Returns `true` if `number` is in the range, else `false`. * @see _.range, _.rangeRight * @example * * _.inRange(3, 2, 4); * // => true * * _.inRange(4, 8); * // => true * * _.inRange(4, 2); * // => false * * _.inRange(2, 2); * // => false * * _.inRange(1.2, 2); * // => true * * _.inRange(5.2, 4); * // => false * * _.inRange(-3, -2, -6); * // => true */ function inRange(number, start, end) { start = toFinite(start); if (end === undefined) { end = start; start = 0; } else { end = toFinite(end); } number = toNumber(number); return baseInRange(number, start, end); } /** * Produces a random number between the inclusive `lower` and `upper` bounds. * If only one argument is provided a number between `0` and the given number * is returned. If `floating` is `true`, or either `lower` or `upper` are * floats, a floating-point number is returned instead of an integer. * * **Note:** JavaScript follows the IEEE-754 standard for resolving * floating-point values which can produce unexpected results. * * @static * @memberOf _ * @since 0.7.0 * @category Number * @param {number} [lower=0] The lower bound. * @param {number} [upper=1] The upper bound. * @param {boolean} [floating] Specify returning a floating-point number. * @returns {number} Returns the random number. * @example * * _.random(0, 5); * // => an integer between 0 and 5 * * _.random(5); * // => also an integer between 0 and 5 * * _.random(5, true); * // => a floating-point number between 0 and 5 * * _.random(1.2, 5.2); * // => a floating-point number between 1.2 and 5.2 */ function random(lower, upper, floating) { if (floating && typeof floating != 'boolean' && isIterateeCall(lower, upper, floating)) { upper = floating = undefined; } if (floating === undefined) { if (typeof upper == 'boolean') { floating = upper; upper = undefined; } else if (typeof lower == 'boolean') { floating = lower; lower = undefined; } } if (lower === undefined && upper === undefined) { lower = 0; upper = 1; } else { lower = toFinite(lower); if (upper === undefined) { upper = lower; lower = 0; } else { upper = toFinite(upper); } } if (lower > upper) { var temp = lower; lower = upper; upper = temp; } if (floating || lower % 1 || upper % 1) { var rand = nativeRandom(); return nativeMin(lower + (rand * (upper - lower + freeParseFloat('1e-' + ((rand + '').length - 1)))), upper); } return baseRandom(lower, upper); } /*------------------------------------------------------------------------*/ /** * Converts `string` to [camel case](https://en.wikipedia.org/wiki/CamelCase). * * @static * @memberOf _ * @since 3.0.0 * @category String * @param {string} [string=''] The string to convert. * @returns {string} Returns the camel cased string. * @example * * _.camelCase('Foo Bar'); * // => 'fooBar' * * _.camelCase('--foo-bar--'); * // => 'fooBar' * * _.camelCase('__FOO_BAR__'); * // => 'fooBar' */ var camelCase = createCompounder(function(result, word, index) { word = word.toLowerCase(); return result + (index ? capitalize(word) : word); }); /** * Converts the first character of `string` to upper case and the remaining * to lower case. * * @static * @memberOf _ * @since 3.0.0 * @category String * @param {string} [string=''] The string to capitalize. * @returns {string} Returns the capitalized string. * @example * * _.capitalize('FRED'); * // => 'Fred' */ function capitalize(string) { return upperFirst(toString(string).toLowerCase()); } /** * Deburrs `string` by converting * [Latin-1 Supplement](https://en.wikipedia.org/wiki/Latin-1_Supplement_(Unicode_block)#Character_table) * and [Latin Extended-A](https://en.wikipedia.org/wiki/Latin_Extended-A) * letters to basic Latin letters and removing * [combining diacritical marks](https://en.wikipedia.org/wiki/Combining_Diacritical_Marks). * * @static * @memberOf _ * @since 3.0.0 * @category String * @param {string} [string=''] The string to deburr. * @returns {string} Returns the deburred string. * @example * * _.deburr('déjà vu'); * // => 'deja vu' */ function deburr(string) { string = toString(string); return string && string.replace(reLatin, deburrLetter).replace(reComboMark, ''); } /** * Checks if `string` ends with the given target string. * * @static * @memberOf _ * @since 3.0.0 * @category String * @param {string} [string=''] The string to inspect. * @param {string} [target] The string to search for. * @param {number} [position=string.length] The position to search up to. * @returns {boolean} Returns `true` if `string` ends with `target`, * else `false`. * @example * * _.endsWith('abc', 'c'); * // => true * * _.endsWith('abc', 'b'); * // => false * * _.endsWith('abc', 'b', 2); * // => true */ function endsWith(string, target, position) { string = toString(string); target = baseToString(target); var length = string.length; position = position === undefined ? length : baseClamp(toInteger(position), 0, length); var end = position; position -= target.length; return position >= 0 && string.slice(position, end) == target; } /** * Converts the characters "&", "<", ">", '"', and "'" in `string` to their * corresponding HTML entities. * * **Note:** No other characters are escaped. To escape additional * characters use a third-party library like [_he_](https://mths.be/he). * * Though the ">" character is escaped for symmetry, characters like * ">" and "/" don't need escaping in HTML and have no special meaning * unless they're part of a tag or unquoted attribute value. See * [Mathias Bynens's article](https://mathiasbynens.be/notes/ambiguous-ampersands) * (under "semi-related fun fact") for more details. * * When working with HTML you should always * [quote attribute values](http://wonko.com/post/html-escaping) to reduce * XSS vectors. * * @static * @since 0.1.0 * @memberOf _ * @category String * @param {string} [string=''] The string to escape. * @returns {string} Returns the escaped string. * @example * * _.escape('fred, barney, & pebbles'); * // => 'fred, barney, & pebbles' */ function escape(string) { string = toString(string); return (string && reHasUnescapedHtml.test(string)) ? string.replace(reUnescapedHtml, escapeHtmlChar) : string; } /** * Escapes the `RegExp` special characters "^", "$", "\", ".", "*", "+", * "?", "(", ")", "[", "]", "{", "}", and "|" in `string`. * * @static * @memberOf _ * @since 3.0.0 * @category String * @param {string} [string=''] The string to escape. * @returns {string} Returns the escaped string. * @example * * _.escapeRegExp('[lodash](https://lodash.com/)'); * // => '\[lodash\]\(https://lodash\.com/\)' */ function escapeRegExp(string) { string = toString(string); return (string && reHasRegExpChar.test(string)) ? string.replace(reRegExpChar, '\\$&') : string; } /** * Converts `string` to * [kebab case](https://en.wikipedia.org/wiki/Letter_case#Special_case_styles). * * @static * @memberOf _ * @since 3.0.0 * @category String * @param {string} [string=''] The string to convert. * @returns {string} Returns the kebab cased string. * @example * * _.kebabCase('Foo Bar'); * // => 'foo-bar' * * _.kebabCase('fooBar'); * // => 'foo-bar' * * _.kebabCase('__FOO_BAR__'); * // => 'foo-bar' */ var kebabCase = createCompounder(function(result, word, index) { return result + (index ? '-' : '') + word.toLowerCase(); }); /** * Converts `string`, as space separated words, to lower case. * * @static * @memberOf _ * @since 4.0.0 * @category String * @param {string} [string=''] The string to convert. * @returns {string} Returns the lower cased string. * @example * * _.lowerCase('--Foo-Bar--'); * // => 'foo bar' * * _.lowerCase('fooBar'); * // => 'foo bar' * * _.lowerCase('__FOO_BAR__'); * // => 'foo bar' */ var lowerCase = createCompounder(function(result, word, index) { return result + (index ? ' ' : '') + word.toLowerCase(); }); /** * Converts the first character of `string` to lower case. * * @static * @memberOf _ * @since 4.0.0 * @category String * @param {string} [string=''] The string to convert. * @returns {string} Returns the converted string. * @example * * _.lowerFirst('Fred'); * // => 'fred' * * _.lowerFirst('FRED'); * // => 'fRED' */ var lowerFirst = createCaseFirst('toLowerCase'); /** * Pads `string` on the left and right sides if it's shorter than `length`. * Padding characters are truncated if they can't be evenly divided by `length`. * * @static * @memberOf _ * @since 3.0.0 * @category String * @param {string} [string=''] The string to pad. * @param {number} [length=0] The padding length. * @param {string} [chars=' '] The string used as padding. * @returns {string} Returns the padded string. * @example * * _.pad('abc', 8); * // => ' abc ' * * _.pad('abc', 8, '_-'); * // => '_-abc_-_' * * _.pad('abc', 3); * // => 'abc' */ function pad(string, length, chars) { string = toString(string); length = toInteger(length); var strLength = length ? stringSize(string) : 0; if (!length || strLength >= length) { return string; } var mid = (length - strLength) / 2; return ( createPadding(nativeFloor(mid), chars) + string + createPadding(nativeCeil(mid), chars) ); } /** * Pads `string` on the right side if it's shorter than `length`. Padding * characters are truncated if they exceed `length`. * * @static * @memberOf _ * @since 4.0.0 * @category String * @param {string} [string=''] The string to pad. * @param {number} [length=0] The padding length. * @param {string} [chars=' '] The string used as padding. * @returns {string} Returns the padded string. * @example * * _.padEnd('abc', 6); * // => 'abc ' * * _.padEnd('abc', 6, '_-'); * // => 'abc_-_' * * _.padEnd('abc', 3); * // => 'abc' */ function padEnd(string, length, chars) { string = toString(string); length = toInteger(length); var strLength = length ? stringSize(string) : 0; return (length && strLength < length) ? (string + createPadding(length - strLength, chars)) : string; } /** * Pads `string` on the left side if it's shorter than `length`. Padding * characters are truncated if they exceed `length`. * * @static * @memberOf _ * @since 4.0.0 * @category String * @param {string} [string=''] The string to pad. * @param {number} [length=0] The padding length. * @param {string} [chars=' '] The string used as padding. * @returns {string} Returns the padded string. * @example * * _.padStart('abc', 6); * // => ' abc' * * _.padStart('abc', 6, '_-'); * // => '_-_abc' * * _.padStart('abc', 3); * // => 'abc' */ function padStart(string, length, chars) { string = toString(string); length = toInteger(length); var strLength = length ? stringSize(string) : 0; return (length && strLength < length) ? (createPadding(length - strLength, chars) + string) : string; } /** * Converts `string` to an integer of the specified radix. If `radix` is * `undefined` or `0`, a `radix` of `10` is used unless `value` is a * hexadecimal, in which case a `radix` of `16` is used. * * **Note:** This method aligns with the * [ES5 implementation](https://es5.github.io/#x15.1.2.2) of `parseInt`. * * @static * @memberOf _ * @since 1.1.0 * @category String * @param {string} string The string to convert. * @param {number} [radix=10] The radix to interpret `value` by. * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. * @returns {number} Returns the converted integer. * @example * * _.parseInt('08'); * // => 8 * * _.map(['6', '08', '10'], _.parseInt); * // => [6, 8, 10] */ function parseInt(string, radix, guard) { if (guard || radix == null) { radix = 0; } else if (radix) { radix = +radix; } return nativeParseInt(toString(string).replace(reTrimStart, ''), radix || 0); } /** * Repeats the given string `n` times. * * @static * @memberOf _ * @since 3.0.0 * @category String * @param {string} [string=''] The string to repeat. * @param {number} [n=1] The number of times to repeat the string. * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. * @returns {string} Returns the repeated string. * @example * * _.repeat('*', 3); * // => '***' * * _.repeat('abc', 2); * // => 'abcabc' * * _.repeat('abc', 0); * // => '' */ function repeat(string, n, guard) { if ((guard ? isIterateeCall(string, n, guard) : n === undefined)) { n = 1; } else { n = toInteger(n); } return baseRepeat(toString(string), n); } /** * Replaces matches for `pattern` in `string` with `replacement`. * * **Note:** This method is based on * [`String#replace`](https://mdn.io/String/replace). * * @static * @memberOf _ * @since 4.0.0 * @category String * @param {string} [string=''] The string to modify. * @param {RegExp|string} pattern The pattern to replace. * @param {Function|string} replacement The match replacement. * @returns {string} Returns the modified string. * @example * * _.replace('Hi Fred', 'Fred', 'Barney'); * // => 'Hi Barney' */ function replace() { var args = arguments, string = toString(args[0]); return args.length < 3 ? string : string.replace(args[1], args[2]); } /** * Converts `string` to * [snake case](https://en.wikipedia.org/wiki/Snake_case). * * @static * @memberOf _ * @since 3.0.0 * @category String * @param {string} [string=''] The string to convert. * @returns {string} Returns the snake cased string. * @example * * _.snakeCase('Foo Bar'); * // => 'foo_bar' * * _.snakeCase('fooBar'); * // => 'foo_bar' * * _.snakeCase('--FOO-BAR--'); * // => 'foo_bar' */ var snakeCase = createCompounder(function(result, word, index) { return result + (index ? '_' : '') + word.toLowerCase(); }); /** * Splits `string` by `separator`. * * **Note:** This method is based on * [`String#split`](https://mdn.io/String/split). * * @static * @memberOf _ * @since 4.0.0 * @category String * @param {string} [string=''] The string to split. * @param {RegExp|string} separator The separator pattern to split by. * @param {number} [limit] The length to truncate results to. * @returns {Array} Returns the string segments. * @example * * _.split('a-b-c', '-', 2); * // => ['a', 'b'] */ function split(string, separator, limit) { if (limit && typeof limit != 'number' && isIterateeCall(string, separator, limit)) { separator = limit = undefined; } limit = limit === undefined ? MAX_ARRAY_LENGTH : limit >>> 0; if (!limit) { return []; } string = toString(string); if (string && ( typeof separator == 'string' || (separator != null && !isRegExp(separator)) )) { separator = baseToString(separator); if (!separator && hasUnicode(string)) { return castSlice(stringToArray(string), 0, limit); } } return string.split(separator, limit); } /** * Converts `string` to * [start case](https://en.wikipedia.org/wiki/Letter_case#Stylistic_or_specialised_usage). * * @static * @memberOf _ * @since 3.1.0 * @category String * @param {string} [string=''] The string to convert. * @returns {string} Returns the start cased string. * @example * * _.startCase('--foo-bar--'); * // => 'Foo Bar' * * _.startCase('fooBar'); * // => 'Foo Bar' * * _.startCase('__FOO_BAR__'); * // => 'FOO BAR' */ var startCase = createCompounder(function(result, word, index) { return result + (index ? ' ' : '') + upperFirst(word); }); /** * Checks if `string` starts with the given target string. * * @static * @memberOf _ * @since 3.0.0 * @category String * @param {string} [string=''] The string to inspect. * @param {string} [target] The string to search for. * @param {number} [position=0] The position to search from. * @returns {boolean} Returns `true` if `string` starts with `target`, * else `false`. * @example * * _.startsWith('abc', 'a'); * // => true * * _.startsWith('abc', 'b'); * // => false * * _.startsWith('abc', 'b', 1); * // => true */ function startsWith(string, target, position) { string = toString(string); position = position == null ? 0 : baseClamp(toInteger(position), 0, string.length); target = baseToString(target); return string.slice(position, position + target.length) == target; } /** * Creates a compiled template function that can interpolate data properties * in "interpolate" delimiters, HTML-escape interpolated data properties in * "escape" delimiters, and execute JavaScript in "evaluate" delimiters. Data * properties may be accessed as free variables in the template. If a setting * object is given, it takes precedence over `_.templateSettings` values. * * **Note:** In the development build `_.template` utilizes * [sourceURLs](http://www.html5rocks.com/en/tutorials/developertools/sourcemaps/#toc-sourceurl) * for easier debugging. * * For more information on precompiling templates see * [lodash's custom builds documentation](https://lodash.com/custom-builds). * * For more information on Chrome extension sandboxes see * [Chrome's extensions documentation](https://developer.chrome.com/extensions/sandboxingEval). * * @static * @since 0.1.0 * @memberOf _ * @category String * @param {string} [string=''] The template string. * @param {Object} [options={}] The options object. * @param {RegExp} [options.escape=_.templateSettings.escape] * The HTML "escape" delimiter. * @param {RegExp} [options.evaluate=_.templateSettings.evaluate] * The "evaluate" delimiter. * @param {Object} [options.imports=_.templateSettings.imports] * An object to import into the template as free variables. * @param {RegExp} [options.interpolate=_.templateSettings.interpolate] * The "interpolate" delimiter. * @param {string} [options.sourceURL='lodash.templateSources[n]'] * The sourceURL of the compiled template. * @param {string} [options.variable='obj'] * The data object variable name. * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. * @returns {Function} Returns the compiled template function. * @example * * // Use the "interpolate" delimiter to create a compiled template. * var compiled = _.template('hello <%= user %>!'); * compiled({ 'user': 'fred' }); * // => 'hello fred!' * * // Use the HTML "escape" delimiter to escape data property values. * var compiled = _.template('<%- value %>'); * compiled({ 'value': '